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The Role of Exosomes in Metabolic Regulation

Author: Larry H. Bernstein, MD, FCAP

 

On 9/25/2017, Aviva Lev-Ari, PhD, RN commissioned Dr. Larry H. Bernstein to write a short article on the following topic reported on 9/22/2017 in sciencemission.com

 

We are publishing, below the new article created by Larry H. Bernstein, MD, FCAP.

 

Background

During the period between 9/2015  and 6/2017 the Team at Leaders in Pharmaceutical Business Intelligence (LPBI)  has launched an R&D effort lead by Aviva Lev-Ari, PhD, RN in conjunction with SBH Sciences, Inc. headed by Dr. Raphael Nir.

This effort, also known as, “DrugDiscovery @LPBI Group”  has yielded several publications on EXOSOMES on this Open Access Online Scientific Journal. Among them are included the following:

 

QIAGEN – International Leader in NGS and RNA Sequencing, 10/08/2017

Reporter: Aviva Lev-Ari, PhD, RN

 

cell-free DNA (cfDNA) tests could become the ultimate “Molecular Stethoscope” that opens up a whole new way of practicing Medicine, 09/08/2017

Reporter: Aviva Lev-Ari, PhD, RN

 

Detecting Multiple Types of Cancer With a Single Blood Test (Human Exomes Galore), 07/02/2017

Reporter and Curator: Irina Robu, PhD

 

Exosomes: Natural Carriers for siRNA Delivery, 04/24/2017

Reporter: Aviva Lev-Ari, PhD, RN

 

One blood sample can be tested for a comprehensive array of cancer cell biomarkers: R&D at WPI, 01/05/2017

Curator: Marzan Khan, B.Sc

 

SBI’s Exosome Research Technologies, 12/29/2016

Reporter: Aviva Lev-Ari, PhD, RN

 

A novel 5-gene pancreatic adenocarcinoma classifier: Meta-analysis of transcriptome data – Clinical Genomics Research @BIDMC, 12/28/2016

Curator: Tilda Barliya, PhD

 

Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood – R&D @Worcester Polytechnic Institute, Micro and Nanotechnology Lab, 12/28/2016

Reporters: Tilda Barliya, PhD and Aviva Lev-Ari, PhD, RN

 

Exosomes – History and Promise, 04/28/2016

Reporter: Aviva Lev-Ari, PhD, RN

 

Exosomes, 11/17/2015

Curator: Larry H. Bernstein, MD, FCAP

 

Liquid Biopsy Assay May Predict Drug Resistance, 11/16/2015

Curator: Larry H. Bernstein, MD, FCAP

 

Glypican-1 identifies cancer exosomes, 10/31/2015

Curator: Larry H. Bernstein, MD, FCAP

 

Circulating Biomarkers World Congress, March 23-24, 2015, Boston: Exosomes, Microvesicles, Circulating DNA, Circulating RNA, Circulating Tumor Cells, Sample Preparation, 03/24/2015

Reporter: Aviva Lev-Ari, PhD, RN

 

Cambridge Healthtech Institute’s Second Annual Exosomes and Microvesicles as Biomarkers and Diagnostics Conference, March 16-17, 2015 in Cambridge, MA, 03/17, 2015

Reporter: Aviva Lev-Ari, PhD, RN

 

The newly created think-piece on the relationship between regulatory functions of Exosomes and Metabolic processes is developed conceptually, below.

 

The Role of Exosomes in Metabolic Regulation

Author: Larry H. Bernstein, MD, FCAP

We have had more than a half century of research into the genetic code and transcription leading to abundant work on RNA and proteomics. However, more recent work in the last two decades has identified RNA interference in siRNA. These molecules may be found in the circulation, but it has been a challenge to find their use in therapeutics. Exosomes were first discovered in the 1980s, but only recently there has been a huge amount of research into their origin, structure and function. Exosomes are 30–120 nm endocytic membrane-bound extracellular vesicles (EVs)(1-23) , and more specifically multiple vesicle bodies (MVBs) by a budding process from invagination of the outer cell membrane that carry microRNA (miRNA), and have structures composed of protein and lipids (1,23-27 ). EVs are the membrane vesicles secreted by eukaryotic cells for intracellular communication by transferring the proteins, lipids, and RNA under various physiologic conditions as well as during the disease stage. EVs also act as a signalosomes in many biological processes. Inward budding of the plasma membrane forms small vesicles that fuse. Intraluminal vesicles (ILVs) are formed by invagination of the limiting endosomal membrane during the maturation process of early endosome.

EVs are the MVBs secreted that serve in intracellular communication by transferring a cargo consisting of proteins, lipids, and RNA under various physiologic conditions (4, 23). Exosome-mediated miRNA transfer between cells is considered to be necessary for intercellular signaling and exosome-associated miRNAs in biofluids (23). Exosomes carry various molecular constituents of their cell of origin, including proteins, lipids, mRNAs, and microRNAs (miRNAs) (. They are released from many cell types, such as dendritic cells (DCs), lymphocytes, platelets, mast cells, epithelial cells, endothelial cells, and neurons, and can be found in most bodily fluids including blood, urine, saliva, amniotic fluid, breast milk, hydrothoracic fluid, and ascitic fluid, as well as in culture medium of most cell types.Exosomes have also been shown to be involved in noncoding RNA surveillance machinery in generating antibody diversity (24). There are also a vast number of long non-coding RNAs (lncRNAs) and enhancer RNAs (eRNAs) that accumulate R-loop structures upon RNA exosome ablation, thereby, resolving deleterious DNA/RNA hybrids arising from active enhancers and distal divergent eRNA-expressing elements (lncRNA-CSR) engaged in long-range DNA interactions (25). RNA exosomes are large multimeric 3′-5′ exo- and endonucleases representing the central RNA 3′-end processing factor and are implicated in processing, quality control, and turnover of both coding and noncoding RNAs. They are large macromolecular cages that channel RNA to the ribonuclease sites (29). A major interest has been developed to characterize of exosomal cargo, which includes numerous non-randomly packed proteins and nucleic acids (1). Moreover, exosomes play an active role in tumorigenesis, metastasis, and response to therapy through the transfer of oncogenes and onco-miRNAs between cancer cells and the tumor stroma. Blood cells and the vascular endothelium is also exosomal shedding, which has significance for cardiovascular,   neurologicological disorders, stroke, and antiphospholipid syndrome (1). Dysregulation of microRNAs and the affected pathways is seen in numerous pathologies their expression can reflect molecular processes of tumor onset and progression qualifying microRNAs as potential diagnostic and prognostic biomarkers (30).

Exosomes are secreted by many cells like B lymphocytes and dendritic cells of hematopoietic and non-hematopoietic origin viz. platelets, Schwann cells, neurons, mast cells, cytotoxic T cells, oligodendrocytes, intestinal epithelial cells were also found to be releasing exosomes (4). They are engaged in complex functions like persuading immune response as the exosomes secreted by antigen presenting cells activate T cells (4). They all have a common set of proteins e.g. Rab family of GTPases, Alix and ESCRT (required for transport) protein and they maintain their cytoskeleton dynamics and participate in membrane fusion. However, they are involved in retrovirus disease pathology as a result of recruitment of the host`s endosomal compartments in order to generate viral vesicles, and they can either spread or limit an infection based on the type of pathogen and its target cells (5).

Upon further consideration, it is understandable how this growing biological work on exosomes has enormous significance for laboratory diagnostics (1, 3, 5, 6, 11, 14, 15, 17-20, 23,30-41) . They are released from many cell types, such as dendritic cells (DCs), lymphocytes, platelets, mast cells, epithelial cells, endothelial cells, and neurons, and can be found in most bodily fluids including blood, urine, saliva, amniotic fluid, breast milk, thoracic and abdominal effusions, and ascitic fluid (1). The involvement of exosomes in disease is broad, and includes: cancer, autoimmune and infectious disease, hematologic disorders, neurodegenerative diseases, and cardiovascular disease. Proteins frequently identified in exosomes include membrane transporters and fusion proteins (e.g., GTPases, annexins, and flotillin), heat shock proteins (e.g., HSC70), tetraspanins (e.g., CD9, CD63, and CD81), MVB biogenesis proteins (e.g., alix and TSG101), and lipid-related proteins and phospholipases. The exosomal lipid composition has been thoroughly analyzed in exosomes secreted from several cell types including DCs and mast cells, reticulocytes, and B-lymphocytes (1). Dysregulation of microRNAs of pathways observed in numerous pathologies (5, 10, 12, 21, 27, 35, 37) including cancers (30), particularly, colon, pancreas, breast, liver, brain, lung (2, 6, 17-20, 30, 33-36, 38, 39). Following these considerations, it is important that we characterize the content of exosomal cargo to gain clues to their biogenesis, targeting, and cellular effects which may lead to identification of biomarkers for disease diagnosis, prognosis and response to treatment (42).

We might continue in pursuit of a particular noteworthy exosome, the NLRP3 inflammasome, which is activated by a variety of external or host-derived stimuli, thereby, initiating an inflammatory response through caspase-1 activation, resulting in inflammatory cytokine IL-1b maturation and secretion (43).
Inflammasomes are multi-protein signaling complexes that activate the inflammatory caspases and the maturation of interleukin-1b. The NLRP3 inflammasome is linked with human autoinflammatory and autoimmune diseases (44). This makes the NLRP3 inflammasome a promising target for anti-inflammatory therapies. The NLRP3 inflammasome is activated in response to a variety of signals that indicate tissue damage, metabolic stress, and infection (45). Upon activation, the NLRP3 inflammasome serves as a platform for activation of the cysteine protease caspase-1, which leads to the processing and secretion of the proinflammatory cytokines interleukin-1β (IL-1β) and IL-18. Heritable and acquired inflammatory diseases are both characterized by dysregulation of NLRP3 inflammasome activation (45).
Receptors of innate immunity recognize conserved moieties associated with either cellular damage [danger-associated molecular patterns (DAMPs)] or invading organisms [pathogen-associated molecular patterns (PAMPs)](45). Either chronic stimulation or overwhelming tissue damage is injurious and responsible for the pathology seen in a number of autoinflammatory and autoimmune disorders, such as arthritis and diabetes. The nucleotide-binding domain leucine-rich repeat (LRR)-containing receptors (NLRs) are PRRs are found intracellularly and they share a unique domain architecture. It consists of a central nucleotide binding and oligomerization domain called the NACHT domain that is located between an N-terminal effector domain and a C-terminal LRR domain (45). The NLR family members NLRP1, NLRP3, and NLRC4 are capable of forming multiprotein complexes called inflammasomes when activated.

The (NLRP3) inflammasome is important in chronic airway diseases such as asthma and chronic obstructive pulmonary disease because the activation results, in pro-IL-1β processing and the secretion of the proinflammatory cytokine IL-1β (46). It has been proposed that Activation of the NLRP3 inflammasome by invading pathogens may prove cell type-specific in exacerbations of airway inflammation in asthma (46). First, NLRP3 interacts with the adaptor protein ASC by sensing microbial pathogens and self-danger signals. Then pro-caspase-1 is recruited and the large protein complex called the NLRP3 inflammasome is formed. This is followed by autocleavage and activation of caspase-1, after which pro-IL-1β and pro-IL-18 are converted into their mature forms. Ion fluxes disrupt membrane integrity, and also mitochondrial damage both play key roles in NLRP3 inflammasome activation (47). Depletion of mitochondria as well as inhibitors that block mitochondrial respiration and ROS production prevented NLRP3 inflammasome activation. Futhermore, genetic ablation of VDAC channels (namely VDAC1 and VDAC3) that are located on the mitochondrial outer membrane and that are responsible for exchanging ions and metabolites with the cytoplasm, leads to diminished mitochondrial (mt) ROS production and inhibition of NLRP3 inflammasome activation (47). Inflammasome activation not only occurs in immune cells, primarily macrophages and dendritic cells, but also in kidney cells, specifically the renal tubular epithelium. The NLRP3 inflammasome is probably involved in the pathogenesis of acute kidney injury, chronic kidney disease, diabetic nephropathy and crystal-related nephropathy (48). The inflammasome also plays a role in autoimmune kidney disease. IL-1 blockade and two recently identified specific NLRP3 inflammasome blockers, MCC950 and β-hydroxybutyrate, may prove to have value in the treatment of inflammasome-mediated conditions.

Autophagosomes derived from tumor cells are referred to as defective ribosomal products in blebs (DRibbles). DRibbles mediate tumor regression by stimulating potent T-cell responses and, thus, have been used as therapeutic cancer vaccines in multiple preclinical cancer models (49). It has been found that DRibbles could induce a rapid differentiation of monocytes and DC precursor (pre-DC) cells into functional APCs (49). Consequently, DRibbles could potentially induce strong innate immune responses via multiple pattern recognition receptors. This explains why DRibbles might be excellent antigen carriers to induce adaptive immune responses to both tumor cells and viruses. This suggests that isolated autophagosomes (DRibbles) from antigen donor cells activate inflammasomes by providing the necessary signals required for IL-1β production.

The Hsp90 system is characterized by a cohort of co-chaperones that bind to Hsp90 and affect its function (50). The co-chaperones enable Hsp90 to chaperone structurally and functionally diverse client proteins. Sahasrabudhe et al. (50) show that the nature of the client protein dictates the contribution of a co-chaperone to its maturation. The study reveals the general importance of the cochaperone Sgt1 (50). In addition to Hsp90, we have to consider Hsp60. Adult cardiac myocytes release heat shock protein (HSP)60 in exosomes. Extracellular HSP60, when not in exosomes, causes cardiac myocyte apoptosis via the activation of Toll-like receptor 4. the protein content of cardiac exosomes differed significantly from other types of exosomes in the literature and contained cytosolic, sarcomeric, and mitochondrial proteins (21).

A new Protein Organic Solvent Precipitation (PROSPR) method efficiently isolates the EV repertoire from human biological samples. Proteomic profiling of PROSPR-enriched CNS EVs indicated that > 75 % of the proteins identified matched previously reported exosomal and microvesicle cargoes. In addition lipidomic characterization of enriched CNS vesicles identified previously reported EV-specific lipid families and novel lipid isoforms not previously detected in human EVs. The characterization of these structures from central nervous system (CNS) tissues is relevant to current neuroscience, especially to advance the understanding of neurodegeneration in amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD) and Alzheimer’s disease (AD)(15). In addition, study of EVs in brain will enable characterization of the degenerative posttranslational modifications (DPMs) occurring in those proteins.
Neurodegenerative disease is characterized by dysregulation because of NLRP3 inflammasome activation. Alzheimer’s disease (AD) and Parkinson’s disease (PD), both neurodegenerative diseases are associated with the NLRP3 inflammasome. PD is characterized by accumulation of Lewy bodies (LB) formed by a-synuclein (aSyn) aggregation. A recent study revealed that aSyn induces synthesis of pro-IL-1b by an interaction with TLR2 and activates NLRP3 inflammasome resulting in caspase-1 activation and IL-1b maturation in human primary monocytes (43). In addition mitophagy downregulates NLRP3 inflammasome activation by eliminating damaged mitochondria, blocking NLRP3 inflammasome activating signals. It is notable that in this aberrant activation mitophagy downregulates NLRP3 inflammasome activation by eliminating damaged mitochondria, blocking NLRP3 inflammasome activating signals (43).

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RNAi – On Transcription and Metabolic Control

Writer and Curator: Larry H Bernstein, MD, FCAP

 

RNAi

This is the third contribution to a series on transcription and metabolic control. It reveals the enormous complexity in this emerging research.

 

mRNA, small RNAs, long RNAs, RNAi and DicAR

Aberrant mRNA translation in cancer pathogenesis
Pier Paolo Pandolfi
Oncogene (2004) 23, 3134–3137
http://dx.doi.org:/10.1038/sj.onc.1207618

As the molecular processes that control mRNA translation and ribosome biogenesis in the eukaryotic cell are extremely complex and multilayered, their deregulation can in principle occur at multiple levels, leading to both disease and cancer pathogenesis. For a long time, it was speculated that disruption of these processes may participate in tumorigenesis, but this notion was, until recently, solely supported by correlative studies. Strong genetic support is now being accrued, while new molecular links between tumor-suppressive and oncogenic pathways and the control of protein synthetic machinery are being unraveled. The importance of aberrant protein synthesis in tumorigenesis is further underscored by the discovery that compounds such as Rapamycin, known to modulate signaling pathways regulatory of this process, are effective anticancer drugs. A number of fundamental questions remain to be addressed and a number of novel ones emerge as this exciting field evolves.

 

mRNA Translation and Energy Metabolism in Cancer
I. Topisirovic and N. Sonenberg
Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI
http://dx.doi.org:/10.1101/sqb.2011.76.010785

A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995).In mammalian cells it consumes >20% of cellular ATP, not considering the energy that is required for the biosynthesis of the components of the translational machinery (e.g., ribosome biogenesis; Buttgereit and Brand 1995). Control of mRNA translation plays a pivotal role in the regulation of gene expression (Sonenberg and Hinnebusch 2009). In fact, a recent study demonstrated that mammalian proteome is mostly governed at the mRNA translation level (Schwanhausser et al. 2011). Malfunction of mRNA translation critically contributes to human disease, including diabetes, heart disease, blood disorders, and, most notably, cancer (Fig. 1; Crozier et al. 2006; Narla and Ebert 2010; Silvera et al. 2010; Spriggs et al. 2010). The first account of changes in the translational apparatus in cancer dates back to 1896, showing enlarged and irregularly shaped nucleoli that are the site of ribosome biogenesis (Pianese 1896). Rapidly proliferating cancer cells have more ribosomes than normal cells.

Figure 1. Dysregulated mRNA translation plays a pivotal role in cancer. Malignant cells are characterized by enlarged nucleoli and a larger number of ribosomes than their normal counterparts. Mutations and/or altered expression of ribosomal proteins (e.g., RPS19, RPS 24), rRNA-modifying enzymes (e.g., dyskerin), translation initiation factors (e.g., eIF4E), or the initiator tRNA (tRNAiMet) result in malignant transformation. Signaling pathways whose dysfunction is frequent in cancer (e.g., MAPK, PI3K/AKT) affect mRNA translation. Perturbations in the translatome result in aberrant cellular growth, proliferation, and survival characteristic of tumorigenesis.

 

In stark contrast to normal cells, in cancer cells ribosomal biogenesis is uncoupled from cell proliferation (Stanners et al. 1979). Accordingly, cancer cells exhibit abnormally high rates of protein synthesis (Silvera et al. 2010). That ribosomal dysfunction plays a central role in cancer is further corroborated by the findings that genetic alterations, which encompass the components of the ribosome machinery (i.e., “ribosomopathies”), are characterized by elevated cancer risk (Narla and Ebert 2010).

mRNA translation is the most energy-consuming process in the cell and strongly correlates with cellular metabolic activity. Translation and energy metabolism play important roles in homeostatic cell growth and proliferation, and when dysregulated lead to cancer. eIF4E is a key regulator of translation, which promotes oncogenesis by selectively enhancing translation of a subset of tumor-promoting mRNAs (e.g., cyclins and c-myc). PI3K/AKT and mitogen-activated protein kinase (MAPK) pathways, which are strongly implicated in cancer etiology, exert a number of their biological effects by modulating translation. The PI3K/AKT pathway regulates eIF4E function by inactivating the inhibitory 4E-BPs via mTORC1, whereas MAPKs activate MAP kinase signal-integrating kinases 1 and 2, which phosphorylate eIF4E. In addition, AMP-activated protein kinase, which is a central sensor of the cellular energy balance, impairs translation by inhibiting mTORC1. Thus, eIF4E plays a major role in mediating the effects of PI3K/AKT, MAPK, and cellular energetics on mRNA translation.Figure 2. eIF4E is regulated by multiple mechanisms. The expression of eIF4E is regulated by several transcription factors (e.g., c-myc, hnRNPK, p53) and adenine-uracil-rich element binding proteins (i.e., HuR and AUF1). eIF4E is suppressed by 4E-BPs, which are regulated by mTORC1. MAP kinase signal integrating kinases 1 and 2 (MNKs) phosphorylate eIF4E.

 

Figure 3. Ras/MAPK and PI3K/AKT/mTORC1 regulate the activity of eIF4E. Various stimuli activate phosphoinositide-3-kinase (PI3K) through the receptor tyrosine kinases (RTKs). Upon activation, PI3K converts phosphatidylinositol 4,5-bisphosphate (PIP2) into phosphatidylinositol-3,4,5-triphosphate (PIP3). This reaction is reversed by PTEN. Phosphoinositide-dependent protein kinase 1 (PDK1) and AKT bind to PIP3 via their pleckstrin homology domains, which allows for the phosphorylation and activation of AKT by PDK1. In addition, the mammalian target of rapamycin complex 2 (mTORC2) modulates the activity of AKT by phosphorylating its hydrophobic motif. AKT phosphorylates tuberous sclerosis complex 2 (TSC2) at multiple sites, which results in its inhibition and consequent activation of Ras homolog enriched in brain (Rheb), which is a small GTPase that activates mTORC1. mTORC1 phosphorylates 4E-BPs leading to their dissociation from eIF4E. In addition to the PI3K/AKT pathway, the activity of mTORC1 is regulated by the serine/threonine kinase 11/LKB1/AMP-kinase (LKB1/AMPK) pathway, regulated in development and DNA damage response 1 (REDD1) and Rag GTPases in response to the changes in cellular energy balance, oxygen and amino acid availability, respectively. Ras and the MAPK pathways are activated by various stimuli through receptor tyrosine kinases (RTKs). In addition the MAPK pathway isactivatedthrough theGprotein–coupled receptors(GPCRs) and byproteinkinaseC (PKC;notshown).TheMAPK pathways encompass an initial GTPase-regulated kinase (MAPKKK), which activates an effector kinase (MAPK) via an intermediate kinase (MAPKK). In response to stimuli such as growth factors, hormones, and phorbol-esters, Ras GTPase stimulates Raf kinase (MAPKKK), which activates extracellular signal-regulated kinases 1 and 2 (ERK 1 and 2) via extracellular signal-regulated kinase activator kinases MEK1 and 2 (MAPKK). Cellular stresses, including osmotic shock, inflammatory cytokines, and UV light, activate p38 MAPKs via multiple mechanisms including Rac kinase (MAPKKK) and MKK3 and 6 (MAPKK). p38 MAPK and ERK activate the MAPK signal–integrating kinases 1 and 2 (MNK1/2), which phosphorylate eIF4E. Additional abbreviations are provided in the text.

 

Cancer Exosomes Perform Cell-Independent MicroRNA Biogenesis and Promote Tumorigenesis
Cancer Cell Nov, 2014; 26: 707–721.
http://dx.doi.org/10.1016/j.ccell.2014.09.005

Breast cancer cells secrete exosomes with specific capacity for cell-independent miRNA biogenesis, while normal cellderivedexosomes lack thisability. Exosomes derivedfrom cancer cellsand serum frompatients withbreast cancer contain the RISC loading complex proteins, Dicer, TRBP, and AGO2, which process pre-miRNAs into mature miRNAs. Cancer exosomes alter the transcriptome of target cells in a Dicer-dependent manner, which stimulate nontumorigenic epithelial cells to form tumors.This study identifies a mechanism whereby cancer cells impart an oncogenic field effect by manipulating the surrounding cells via exosomes. Presence of Dicer in exosomes may serve as biomarker for detection of cancer.


Dicers at RISC. The Mechanism of RNAi

Marcel Tijsterman and Ronald H.A. Plasterk
Cell, Apr 2014; 117:1–4

Figure 1. Model for RNA Silencing in Drosophila In an ordered biochemical pathway, miRNAs (left panel) and siRNAs (right panel) are processed from double-stranded precursor molecules by Dcr-1and Dcr-2, respectively, and stay attached to Dicer-containing complexes, which assemble into RISC. The degree of complementarity between the RNA silencing molecule (in red) and its cognate target determines the fate of the mRNA: blocked translation or immediate destruction.

Argonaute2 Cleaves the Anti-Guide Strand of siRNA during RISC Activation
Cell 2005; 123:621-629
http://www.cell.com/cgi/content/full/123/4/621/DC1/
Dicing and slicing- The core machinery of the RNA interference pathway
Scott C Hammond
FEBS Letters 579 (2005) 5822–5829
http://dx.doi.org:/10.1016/j.febslet.2005.08.079

Fig. 1. Domain organization of RNaseIII gene family. Three classes of RNaseIII genes are shown. The PAZ domain in Dm-Dicer-2 contains mutations in several residues required for RNA binding and may not be functional.

Fig. 2. Model for Dicer catalysis. The PAZ domain binds the 2 nt 30 overhang of a dsRNA terminus. The RNaseIII domains form a pseudo-dimer. Each domain hydrolyzes one strand of the substrate. The binding site of the dsRBD is not defined. The function of the helicase domain is not known.

Fig. 3. Biogenesis pathway of microRNAs. MicroRNA genes are transcribed by RNA polymerase II. The primary transcript is referred to as ‘‘primicroRNA’’. Drosha processing occurs in the nucleus. The resulting precursor, ‘‘pre-microRNA’’, is exported to the cytoplasm for Dicer processing. In a coordinated manner, the mature microRNA is transferred to RISC and unwound by a helicase. mRNA targets that duplex in the Slicer scissile site are cleaved and degraded, if the microRNA is loaded into an Ago2 RISC. Mismatched targets are translationally suppressed. All Ago family members are believed to function in translational suppression.

Fig. 4. Model for Slicer catalysis. The siRNA guide strand is bound at the 50 end by the PIWI domain and at the 30 end by the PAZ domain. The 50 phosphate is coordinated by conserved basic residues. mRNA targets are initially bound by the seed region of the siRNA and pairing is extended to the 30 end. The RNaseH fold hydrolyzes the target in a cation dependent manner. Slicer cleavage is measured from the 50 end of the siRNA. Product is released by an unknown mechanism and the enzyme recycles.

 

 

RNA interference (RNAi) is a biological process in which RNA molecules inhibit gene expression, typically by causing the destruction of specific mRNA molecules. Historically, it was known by other names, including co-suppression, post transcriptional gene silencing (PTGS), and quelling. Only after these apparently unrelated processes were fully understood did it become clear that they all described the RNAi phenomenon. Andrew Fire and Craig C. Mello shared the 2006 Nobel Prize in Physiology or Medicine for their work on RNA interference in the nematode worm Caenorhabditis elegans, which they published in 1998.

 

Two types of small ribonucleic acid (RNA) molecules – microRNA (miRNA) and small interfering RNA (siRNA) – are central to RNA interference. RNAs are the direct products of genes, and these small RNAs can bind to other specific messenger RNA (mRNA) molecules and either increase or decrease their activity, for example by preventing an mRNA from producing a protein. RNA interference has an important role in defending cells against parasitic nucleotide sequences – viruses and transposons. It also influences development.

 

The RNAi pathway is found in many eukaryotes, including animals, and is initiated by the enzyme Dicer, which cleaves long double-stranded RNA (dsRNA) molecules into short double stranded fragments of ~20 nucleotide siRNAs. Each siRNA is unwound into two single-stranded RNAs (ssRNAs), the passenger strand and the guide strand. The passenger strand is degraded and the guide strand is incorporated into the RNA-induced silencing complex (RISC). The most well-studied outcome is post-transcriptional gene silencing, which occurs when the guide strand pairs with a complementary sequence in a messenger RNA molecule and induces cleavage by Argonaute, the catalytic component of the RISC complex. In some organisms, this process spreads systemically, despite the initially limited molar concentrations of siRNA.
http://en.wikipedia.org/wiki/RNA_interference

 

http://upload.wikimedia.org/wikipedia/commons/thumb/e/e4/ShRNA_Lentivirus.svg/481px-ShRNA_Lentivirus.svg.png

 

http://www.frontiersin.org/files/Articles/66078/fnmol-06-00040-HTML/image_m/fnmol-06-00040-g001.jpg
http://dx.doi.org:/10.3389/fnmol.2013.00040

The enzyme dicer trims double stranded RNA, to form small interfering RNA or microRNA. These processed RNAs are incorporated into the RNA-induced silencing.
MiRNA biogenesis and function. (A) The canonical miRNA biogenesis pathway is Drosha- and Dicer-dependent. It begins with RNA Pol II-mediated transcription..

 

Dicer Promotes Transcription Termination

Dicer Promotes Transcription Termination

Dicer Promotes Transcription Termination at Sites of Replication Stress to Maintain Genome Stability
Cell Oct 2014; 159(3): 572–583
http://dx.doi.org/10.1016/j.cell.2014.09.031

http://www.cell.com/cms/attachment/2019646604/2039684570/fx1.jpg

 

18-13 miRNA- protein complex ap-chap-18-pp-42-728

18-13 miRNA- protein complex ap-chap-18-pp-42-728

18-13 miRNA- protein complex (a) Primary miRNA transcript Translation blocked Hydrogen bond (b) Generation and function of miRNAs Hairpin miRNA miRNA Dicer …

http://image.slidesharecdn.com/ap-chap-18-pp-1229097198123780-1/95/ap-chap-18-pp-42-728.jpg?cb=1229090143

 

 

Identification and characterization of small RNAs involved in RNA silencing
FEBS Letters 579 (2005) 5830–5840
http://dx.doi.org:/10.1016/j.febslet.2005.08.009

Fig. 1. Small RNA cloning procedure. Outline of the small RNA cloning procedure. RNA is dephosphorylated (step 1) for joining the 30 adapter by T4 RNA ligase 1 in the presence of ATP (step 2). The use of a chemically adenylated adapter and truncated form of T4 RNA ligase 2 (Rnl2) allows eliminating the dephosphorylation step (step 4). If the RNA was dephosphorylated, it is re-phosphorylated (step 3) prior to 50 adapter ligation with T4 RNA ligase 1 and ATP (step 5). After 50 adapter ligation, a standard reverse transcription is performed (step 6). Alternatively, after 30 adapter ligation, the RNA is used directly for reverse transcription simultaneously with 50 adaptor joining (step 7). In this case, the property of reverse transcriptase to add non-templated cytidine residues at the 50 end of synthesized DNA is used to facilitate template switch of the reverse transcriptase to the 30 guanosine residues of the 50 adapter (SMART technology, Invitrogen). Abbreviations: P and OH indicate phosphate and hydroxyl ends of the RNA; App indicates 50 chemically adenylated adapter; L, 30 blocking group; CIP, calf alkaline phosphatase and PNK, polynucleotide kinase.

 

Transcriptional regulatory functions of nuclear long noncoding RNAs
Trends in Genetics, Aug 2014; 30(8):348-356
http://dx.doi.org/10.1016/j.tig.2014.06.001

Cis-acting lncRNAEnhancer-associated lncRNAIntergenic lncRNA

lncRNA

Promoter-associated lncRNA

Proximity transfer

Trans-acting lncRNA

 

Functional interactions among microRNAs and long noncoding RNAs
Sem Cell Dev Biol 2014; 34:9-14
http://dx.doi.org/10.1016/j.semcdb.2014.05.015
Genome-wide application of RNAi to the discovery of potential drug targets
FEBS Letters 579 (2005) 5988–599
http://dx.doi.org://10.1016/j.febslet.2005.08.015

Fig. 1. Schematic representation of gene silencing by an shRNA-expression vector. The shRNA is processed by Dicer. The processed siRNA enters the RNA-induced silencing complex (RISC), where it targets mRNA for degradation.

Fig. 2. Schematic representation of a transcription system for production of siRNA

Fig. 3. (A) Schematic representation of the proposed siRNA-expression system. Three or four C to U or A to G mutations are introduced into the sense strand. (B) Schematic representation of the discovery of a novel gene using an siRNA library.

 

Imperfect centered miRNA binding sites are common and can mediate repression of target mRNAs
Martin et al. Genome Biology 2014, 15:R51 http://genomebiology.com/2014/15/3/R51

 

 

 

 

Table 1 Number of inferred targets for each miRNA tested

miRNA Probes Transcripts Genes
miR-10a 2,206 5,963 1,887
miR-10a-iso 1,648 1,468 4,211
miR-10b 1,588 3,940 1,365
miR-10b-iso 963 2,235 889
miR-17-5p 1,223 2,862 1,137
miR-17-5p-iso 1,656 3,731 1,461
miR-182 2,261 6,423 2,008
miR-182-iso 1,569 4,316 1,444
miR-23b 2,248 5,383 1,990
miR-27a 2,334 5,310 2,069

Probes: number of probes significantly enriched in pull-downs compared to controls (5% FDR). Transcripts: number of transcripts to which those probes map exactly. Genes: number of genes from which those transcripts originate

Figure 2 Biotin pull-downs identify bone fide miRNA targets. (A) Volcano plot showing the significance of the difference in expression between the miR-17-5p pull-down and the mock-transfected control, for all transcripts expressed in HEK293T cells. Both targets predicted by TargetScan or validated previously via luciferase assay were significantly enriched in the pull-down compared to the controls. (B) Results from luciferase assays on previously untested targets predicted using TargetScan and uncovered using the biotin pull-down. The plot indicates mean luciferase activity from either the empty plasmid or from pMIR containing a miRNA binding site in the 3′ UTR, relative to a negative control. Asterisks indicate a significant reduction in luciferase activity (one-sided t-test; P<0.05) and error bars the standard error of the mean over three replicates. (C-E) Targets identified through PAR-CLIP or through miRNA over-expression studies show greater enrichment in the pull-down. Cumulative distribution of log fold-change in the pull-down for transcripts identified as targets by the indicated miRNA over-expression study or not. Red, canonical transcripts found to be miR-17-5p targets in the indicated study (Table S5 in Additional file 1); black, all other canonical transcripts; p, one-sided P-value from Kolmogorov-Smirnov test for a difference in distributions. (F) To confirm that our results were dependent on RISC association, cells were transfected with either single or double-stranded synthetic miRNAs, then subjected to AGO2 immunoprecipitation. The biotin pull-down was performed in the AGO2-enriched and AGO2-depleted fractions. (G-H) Quantitative RT-PCR revealed that, with double-stranded (ds) miRNA (G), four out of five known targets were enriched relative to input mRNA (*P≤0.05, **P<0.01, ***P<0.001) in the AGO2-enriched but not in the AGO2-depleted fractions, but this enrichment was not seen for the cells transfected with a single-stranded (ss) miRNA (H). The numbers on the x-axis correspond to those in Figure 2F. Error bars represent the standard error of mean (sem).

Figure 5 IsomiRs and canonical miRNAs target many of the same transcripts.

Hammerhead ribozymes in therapeutic target discovery and validation
Drug Disc Today 2009; 14(15/16): 776-783
http://dx.doi.org/10.1016/j.drudis.2009.05.003

Figure 1. Features of hammerhead ribozymes. A generic diagram of a hammerhead ribozyme bound to its target substrate: NUH is the cleavage triplet on target sequence, stems I and III are sites of the specific interactions between ribozyme and target, stem II is the structural element connecting separate parts of the catalytic core. Arrows represent the cleavage site, numbering system according to Hertel et al. [60].

hammerhead ribozyme

hammerhead ribozyme

https://www-ssrl.slac.stanford.edu/research/highlights_archive/ribozyme_fig1.jpg

 

Figure 1  Schematic (A) and ribbon (B) diagrams depicting the crystal structure of the full-length hammerhead ribozyme. The sequence and secondary structure

 

TABLE 1 Typical examples of successful applications of hammerhead ribozymes. Most of the data are derived from [10] and [11], the others are expressly specified.

  • Growth factors, receptors, transduction elements
  • Oncogenes, protoncogenes, fusion genes
  • Apoptosis, survival factors, drug resistance
  • Transcription factors
  • Extracellular matrix, matrix modulating factors
  • Circulating factors
  • Viral genome, viral genes

Figure 2.Target–ribozyme interactions. (a) As cheme of ribozyme binding to full substrate. The calculated energy of this binding ensures the formation of a stable complex. At the denaturating temperature, Tm, will allow this complex to survive to biological conditions. Conversely, after cleavage, binding energies calculated on single, (b) and (c), ribozyme arms are very low and no longer stable. These properties will ensure both the efficient release of cleavage fragments and the prevention of binding to unrelated targets. RNAs complementary to one binding arm only will not be bound or cleaved by the hammerhead catalytic sequence.

Figure 3. ‘Chemical omics’ approach. According to this target discovery strategy: (1) a first round of ‘omic’ study (proteomic, genomic, metabolomic, …) will enable the discovery of a set of (2) putative markers. A series of hammerhead ribozymes will then be prepared in order to target each marker. (4) A second ‘omic’ study round will be performed on (3) knocked down samples obtained after ribozymes administration. (5) A new series of markers will then be produced. An expanding analytical process of this type may be further repeated. Finally, a robust bioinformatic algorithm will make it possible to connect the different markers and draw new hypothetical links and pathways.

 

miRNA

ADAR Enzyme and miRNA Story
Sara Tomaselli, Barbara Bonamassa, Anna Alisi, et al.
Int. J. Mol. Sci. 2013, 14, 22796-22816;
http://dx.doi.org:/10.3390/ijms141122796

Adenosine deaminase acting on RNA (ADAR) enzymes convert adenosine (A) to inosine (I) in double-stranded (ds) RNAs. Since Inosine is read as Guanosine, the biological consequence of ADAR enzyme activity is an A/G conversion within RNA molecules. A-to-I editing events can occur on both coding and non-coding RNAs, including microRNAs (miRNAs), which are small regulatory RNAs of ~20–23 nucleotides that regulate several cell processes by annealing to target mRNAs and inhibiting their translation. Both miRNA precursors and mature miRNAs undergo A-to-I RNA editing, affecting the miRNA maturation process and activity. ADARs can also edit 3′ UTR of mRNAs, further increasing the interplay between mRNA targets and miRNAs. In this review, we provide a general overview of the ADAR enzymes and their mechanisms of action as well as miRNA processing and function. We then review the more recent findings about the impact of ADAR-mediated activity on the miRNA pathway in terms of biogenesis, target recognition, and gene expression regulation.

Figure 1. Structure of ADAR family proteins: ADAR1, ADAR2, and ADAR3. The ADAR enzymes contain a C-terminal conserved catalytic deaminase domain (DM), two or three dsRBDs in the N-terminal portion. ADAR1 full-length protein also contains a N-terminal Zα domain with a nuclear export signal (NES) and a Zβ domain, while ADAR3 has a  R-domain. A nuclear localization signal is also indicated.

 

Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites
Doron Betel, Anjali Koppal, Phaedra Agius, Chris Sander, Christina Leslie
Genome Biology 2010, 11:R90 http://genomebiology.com/2010/11/8/R90

microRNAs are a class of small regulatory RNAs that are involved in post-transcriptional gene silencing. These small (approximately 22 nucleotide) single-strand RNAs guide a gene silencing complex to an mRNA by complementary base pairing, mostly at the 3′ untranslated region (3′ UTR). The association of the RNAinduced silencing complex (RISC) to the conjugate mRNA results in silencing the gene either by translational repression or by degradation of the mRNA. Reliable microRNA target prediction is an important and still unsolved computational challenge, hampered both by insufficient knowledge of microRNA biology as well as the limited number of experimentally validated targets.

mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
Human RISC – MicroRNA Biogenesis and Posttranscriptional Gene Silencing
Cell 2005; 123:631-640
http://dx.doi.org:/10.1016/j.cell.2005.10.022
Development of microRNA therapeutics
Eva van Rooij & Sakari Kauppinen
EMBO Mol Med (2014) 6: 851–864
http://dx.doi.org:/10.15252/emmm.20110089

MicroRNAs (miRNAs) play key regulatory roles in diverse biological processes and are frequently dysregulated in human diseases. Thus, miRNAs have emerged as a class of promising targets for therapeutic intervention. Here, we describe the current strategies for therapeutic modulation of miRNAs and provide an update on the development of miRNA-based therapeutics for the treatment of cancer, cardiovascular disease and hepatitis C virus (HCV) infection.

Figure 1. miRNA biogenesis and modulation of miRNA activity by miRNA mimics and antimiR oligonucleotides. MiRNA genes are transcribed by RNA polymerase II from intergenic, intronic or polycistronic loci to long primary miRNA transcripts (pri-miRNAs) and processed in the nucleus by the Drosha–DGCR8 complex to approximately 70 nt pre-miRNA hairpin structures. The most common alternative miRNA biogenesis pathway involves short intronic hairpins, termed mirtrons, that are spliced and debranched to form pre-miRNA hairpins. Pre-miRNAs are exported into the cytoplasm and then cleaved by the Dicer–TRBP complex to imperfect miRNA: miRNA* duplexes about 22 nucleotides in length. In the cytoplasm, miRNA duplexes are incorporated into Argonaute-containing miRNA induced silencing complex (miRISC), followed by unwinding of the duplex and retention of the mature miRNA strand in miRISC, while the complementary strand is released and degraded. The mature miRNA functions as a guide molecule for miRISC by directing it to partially complementary sites in the target mRNAs, resulting in translational repression and/or mRNA degradation. Currently, two strategies are employed to modulate miRNA activity: restoring the function of a miRNA using double-stranded miRNA mimics, and inhibition of miRNA function using single-stranded anti-miR oligonucleotides.

Figure 2. Design of chemically modified miRNA modulators. (A) Structures of chemical modifications used in miRNA modulators. A number of different sugar modifications are used to increase the duplex melting temperature (Tm) of anti-miR oligonucleotides. The20-O-methyl(20-O-Me), 20-O-methoxyethyl(20-MOE )and 20-fluoro(20-F) nucleotides are modified at the 20 position of the sugar moiety, whereas locked nucleic acid (LNA) is a bicyclic RNA analogue in which the ribose is locked in a C30-endo conformation by introduction of a 20-O,40-C methylene bridge. To increase nuclease resistance and enhance the pharmacokinetic properties, most anti-miR oligonucleotides harbor phosphorothioate (PS) backbone linkages, in which sulfur replaces one of the non-bridging oxygen atoms in the phosphate group. In morpholino oligomers, a six-membered morpholine ring replaces the sugar moiety. Morpholinos are uncharged and exhibit a slight increase in binding affinity to their cognate miRNAs. PNA oligomers are uncharged oligonucleotide analogues, in which the sugar–phosphate backbone has been replaced by a peptide-like backbone consisting of N-(2-aminoethyl)-glycine units. (B) An example of a synthetic double-stranded miRNA mimic described in this review. One way to therapeutically mimic a miRNA is by using synthetic RNA duplexes that harbor chemical modifications for improved stability and cellular uptake. In such constructs, the antisense (guide) strand is identical to the miRNA of interest, while the sense (passenger) strand is modified and can be linked to a molecule, such as cholesterol, for enhanced cellular uptake. The sense strand contains chemical modifications to prevent mi-RISC loading. Several mismatches can be introduced to prevent this strand from functioning as an anti-miR, while it is further left unmodified to ensure rapid degradation.The20-F modification helps to protect the antisense strand against exonucleases, hence making the guide strand more stable, while it does not interfere with mi-RISC loading. (C) Design of chemically modified anti-miR oligonucleotides described in this review. Antagomirs are30 cholesterol-conjugated,20-O-Me oligonucleotides fully complementary to the mature miRNA sequence with several PS moieties to increase their in vivo stability. The use of unconjugated 20-F/MOE-, 20-MOE- or LNA-modified anti-miR oligonucleotides harboring a complete PS backbone represents another approach for inhibition of miRNA function in vivo. The high duplex melting temperature of LNA-modified oligonucleotides allows efficient miRNA inhibition using truncated, high-affinity 15–16-nucleotide LNA/DNA anti-miR oligonucleotides targeting the 50 region of the mature miRNA. Furthermore, the high binding affinity of fully LNA-modified 8-mer PS oligonucleotides, designated as tiny LNAs, facilitates simultaneous inhibition of entire miRNA seed families by targeting the shared seed sequence.

Human MicroRNA Targets
Bino John, Anton J. Enright, Alexei Aravin, Thomas Tuschl,.., Debora S. Mark
PLoS Biol 2004; 2(11): e363  http://www.plosbiology.org

More than ten years after the discovery of the first miRNA gene, lin-4 (Chalfie et al. 1981; Lee et al. 1993), we know that miRNA genes constitute about 1%–2% of the known genes in eukaryotes. Investigation of miRNA expression combined with genetic and molecular studies in Caenorhabditis elegans, Drosophila melanogaster, and Arabidopsis thaliana have identified the biological functions of several miRNAs (recent review, Bartel 2004). In C. elegans, lin-4 and let-7 were first discovered as key regulators of developmental timing in early larval developmental transitions (Ambros 2000; Abrahante et al. 2003; Lin et al. 2003; Vella et al. 2004). More recently lsy-6 was shown to determine the left–right asymmetry of chemoreceptor expression (Johnston and Hobert 2003). In D. melanogaster, miR-14 has a role in apoptosis and fat metabolism (Xu et al. 2003) and the bantam miRNA targets the gene hid involved in apoptosis and growth control (Brennecke et al. 2003).

MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 39 untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

Figure 1. Target Prediction Pipeline for miRNA Targets in Vertebrates The mammalian (human, mouse, and rat) and fish (zebra and fugu) 39 UTRs were first scanned for miRNA target sites using position specific rules of sequence complementarity. Next, aligned UTRs of orthologous genes were used to check for conservation of miRNA– target relationships (‘‘target conservation’’) between mammalian genomes and, separately, between fish genomes. The main results (bottom) are the conserved mammalian and conserved fish targets, for each miRNA,as well as a smaller set of super-conserved vertebrate targets.   http://dx.doi.org:/10.1371/journal.pbio.0020363.g00
Figure 2. Distribution of Transcripts with Cooperativity of Target Sites and Estimated Number of False Positives Each bar reflects the number of human transcripts with a given number of target sites on their UTR. Estimated rate of false positives(e.g., 39%for2 targets) is given by the number of target sites predicted using shuffled miRNAs processed in a way identical to real miRNAs, including the use of interspecies conservation filter. http://dx.doi.org:/10.1371/journal.pbio.0020363.g002

Conserved Seed Pairing, Often improved an-Flanked by Adenosines, Indicates Thousands of Human Genes are MicroRNA Targets
Cell, Jan 2005; 120: 15–20
http://dx.doi.org:/10.1016/j.cell.2004.12.035

Integrated analysis of microRNA and mRNA expression. adding biological significance to microRNA target predictions.
Maarten van Iterson, Sander Bervoets, Emile J. de Meijer, et al.
Nucleic Acids Research, 2013; 41(15), e146
http://dx.doi.org:/10.1093/nar/gkt525

Current microRNA target predictions are based on sequence information and empirically derived rules but do not make use of the expression of microRNAs and their targets. This study aimed to improve microRNA target predictions in a given biological context, using in silico predictions, microRNA and mRNA expression. We used target prediction tools to produce lists of predicted targets and used a gene set test designed to detect consistent effects of microRNAs on the joint expression of multiple targets. In a single test, association between microRNA expression and target gene set expression as well as the contribution of the individual target genes on the association are determined. The strongest negatively associated mRNAs as measured by the test were prioritized. We applied our integration method to a well-defined muscle differentiation model. Validation of our predictions in C2C12 cells confirmed predicted targets of known as well as novel muscle-related microRNAs. We further studied associations between microRNA–mRNA pairs in human prostate cancer, finding some pairs that have been recently experimentally validated by others. Using the same study, we showed the advantages of the global test over Pearson correlation and lasso. We conclude that our integrated approach successfully identifies regulated microRNAs and their targets.

Long non-coding RNA and microRNAs might act in regulating the expression of BARD1 mRNAs
Int J Biol & Cell Biol 2014; 54:356-367
http://dx.doi.org/10.1016/j.biocel.2014.06.018

 

Passenger-Strand Cleavage Facilitates Assembly of siRNA into Ago2-Containing RNAi Enzyme Complexes
Cell 2006; 123:607-620
http://dx.doi.org:/10.1016/j.cell.2006.08.044

 

RNAi- RISC Gets Loaded
Cell 2005; 123:543-553
http://dx.doi.org:/10.1016/j.cell.2005.11.006
RNAi- The Nuts and Bolts of the RISC Machine
Cell 2005; 122:17-20
http://dx.doi.org:/10.1016/j.cell.2005.06.023
Structural domains in RNAi
FEBS Letters 579 (2005) 5841–5849
http://dx.doi.org:/10.1016/j.febslet.2005.07.072

Fig. 1. A ‘‘Domain-centric’’ view of RNAi. (A) The conserved pathways of RNA silencing. The domain structure of each protein in (hypothetical) interaction with its RNA is shown. For clarity, the second column lists domains in order N- to C-terminal. Figures are not to scale. In brief, Drosha, an RNase III enzyme, and its obligate binding partner, Pasha recognize pri-mRNA loops, and cut these into 70 nt hairpin pre-miRNAs. Dicer utilizes a PAZ domain to sense the 30 2-nt overhang created, and further processes these, and dsRNAs into miRNAs and siRNAs. Argonaute binds the 50 end of guide RNAs via its PIWI domain, and the 30 end via a PAZ domain, yielding RISCs that effect RNA silencing through several mechanisms. A Viral protein, VP19 can suppress RNA silencing by sequestering siRNAs. (B) A summary of known siRNA structural biology. Listed by domain are solved structures, their protein/organism of origin, and ligands, where applicable. Also shown are PDB codes.

Fig. 2. Novel modes of RNA recognition. (A) A typical dsRBD: Xenopus binding protein A (1DI2). A RNA helix is modeled pink, and the protein is rendered in transparent electrostatic contours (blue is basic, red acidic). Note the interaction of helices along the major groove, and the position of helix 1. A second dsRBD protein is visible, in the lower right. (B) A dsRBD, Saccharomyces Rnt1P (1T4L), recognizes hairpin loops. A novel third helix (top) pushes helix one into the loop of a hairpin RNA. (C) 30-OH recognition by PAZ. Human Eif2c1 (1SI3) bound to RNA (pink) is shown. PAZ is green, with transparent electrostatic surface plot. The OB-fold (nucleotide binding fold) and the insertion domain are labeled. Note the glove-and-thumb like cleft they form, that the 30-OH is inserted into. A basic groove (blue) the RNA binds along outside the cleft is visible. (D) A close-up view of PAZ, as in C (surface not-transparent, slightly rotated). See white arrows for orientation, and location of 30-OH binding site. RNA is shown red in sticks. The terminal –OH is barely visible, buried in a cleft. It and the carbon it bonds have been colored yellow for clarity. (E) The PIWI domain (2BGG). Note the insertion of the 50P red (labeled) into the binding site. Its complimentary strand (pink) is not annealed to it, and the 30 overhang and first complimentary bases sit on the protein surface. (F) An enlarged view of (E), with protein in slate and RNA modeled as red sticks. The coordinated magnesium is a grey sphere, which is coordinated by the terminal carboxylate of the protein, protein side chains, and RNA phosphate oxygens. The 50 base stacks against a conserved Tyr. Several other sidechain contacts are shown.

Fig. 3. Argonaute/RISC. (A) P. furiosus Argonaute (PDB 1Z26). A color-guided key to the domains is presented. PAZ sits over the PIWI/N/MID bowl and active site. The liganding atoms for the catalytic metal are depicted as yellow balls for clarity. The tungstate binding site (50P surrogate) is shown as tan spheres. (B) A guide strand channel. Looking down from the PAZ domain towards the active site, Z-sections are clipped off. Colors of domains are as in the key in (A). Wrapping down along a basic cleft from the PAZ 30OH binding site (approximate position labeled), a RNA binding groove passes the active site (yellow), and runs down to the 50P binding site (tan balls). A second cleft running perpendicular to this one at its entry may accommodate target strand RNA. For more detail, and models of siRNA placed into the grooves, see [27,29].

Fig. 4. VP19 sequestration of siRNA. (A) CIRV VP19 (1RPU, RNA removed). Two monomers (blue and cyan) form an 8 strand, concave b-sheet with bracketing helices at the ends. (B) Tombus viral VP19 bound to siRNA (1 monomer shown). RNA strands are modeled as sticks, with one strand pink and one red. The bracketing helix places two tryptophans in position to stack over the terminal RNA bases. On the b-sheet surface, and Arg and a Lys interact with the phosphate backbone, and at the center of the RNA binding surface, a number of Ser and Thr mediate an extensive hydrogen bond network. Both the Trp brackets and RNA binding by an extended b-sheet are unique.

 

Small RNA asymmetry in RNAi- Function in RISC assembly and gene regulation
FEBS Letters 579 (2005) 5850–5857
http://dx.doi.org:/10.1016/j.febslet.2005.08.071

 

The role of the oncofetal IGF2 mRNA-binding protein 3 (IGF2BP3) in cancer
Seminars in Cancer Biol 2014; 29:3-12
http://dx.doi.org/10.1016/j.semcancer.2014.07.006

Table 1 – Target mRNAs of IGF2BP3.

Target cis-Element Regulation
CD44 3’ -utr Control of mRNA stability
IGF2 5’ -utr Translational control
H19 ncRNA Unknown
ACTB 3’ -utr Unknown
MYC CRD Unknown
CD164 Unknown Control of mRNA stability
MMP9 Unknown Control of mRNA stability
ABCG2 Unknown Unknown
PDPN 3’ -utr Control of mRNA stability
HMGA2 3’ -utr Protection from miR directed degradation
CCND1 3’ -utr translational control
CCND3 3’ -utr translational control
CCNG1 3’ -utr translationalcontrol

 

Targeting glucose uptake with siRNA-based nanomedicine for cancer therapy
Biomaterials 2015; 51:1-11
http://dx.doi.org/10.1016/j.biomaterials.2015.01.068
The therapeutic potential of RNA interference
FEBS Letters 579 (2005) 5996–6007
http://dx.doi.og:/10.1016/j.febslet.2005.08.004

Table 1 Companies developing RNAi therapeutics that includes cancer

Company name Primary areas of interest
Atugen AG Metabolic disease; cancer ocular disease; skin disease
Benitec Australia Limited Hepatitis C virus; HIV/AIDS; cancer; diabetes/obesity
Calando Pharmaceuticals Nanoparticle technology
Genta Incorporated Cancer
Intradigm Corporation Cancer; SARS; arthritis
Sirna Therapeutics, Inc. AMD; Hepatitis C virus; asthma; diabetes; cancer; Huntington s disease; hearing loss

 

The Noncoding RNA Revolution—Trashing Old Rules to Forge New Ones
Cell 2014; 157:77-94
http://dx.doi.org/10.1016/j.cell.2014.03.008

Figure 1. Noncoding RNAs Function in Diverse Contexts Noncoding RNAs function in all domains of life, regulating gene expression from transcription to splicing to translation and contributing to genome organization and stability. Self-splicing RNAs, ribosomes, and riboswitches function in both eukaryotes and bacteria. Archaea (not shown) also utilize ncRNA systems including ribosomes, riboswitches, snoRNPs, and CRISPR. Orange strands, ncRNA performing the action indicated; red strands, the RNA acted upon by the ncRNA. Blue strands, DNA. Triangle, small-molecule metabolite bound by a riboswitch. Ovals indicate protein components of an RNP, such as the spliceosome (white oval), ribosome (two purple subunits), or other RNPs (yellow ovals). Because of the importance of RNA structure in these ncRNAs, some structures are shown but they are not meant to be realistic.

 

miRNAs and cancer targeting

Table 1 of targets

miRNA Cancer type reference
NA GI cancer Current status of miRNA-targeting therapeutics and preclinical studies against gastroenterological carcinoma
NA Renal cell Differential expression profiling of microRNAs and their potential involvement in renal cell carcinoma pathogenesis
NA urothelial
cancer
A microRNA expression ratio defining the invasive phenotype in bladder tumors
miR-31 breast A Pleiotropically Acting MicroRNA, miR-31, inhibits breast cancer growth
miR-512-3p NSCLC Inhibition of RAC1-GEF DOCK3 by miR-512-3p contributes to suppression of metastasis in non-small cell lung cancer
miR-495 gastric Methylation-associated silencing of miR-495 inhibit the migration and invasion of human gastric cancer cells
microRNA-218 prostate microRNA-218 inhibits prostate cancer cell growth and promotes apoptosis by repressing TPD52 expression
MicroRNA-373 cervical cancer MicroRNA-373 functions as an oncogene and targets YOD1 gene in cervical cancer
miR-25 NSCLC miR-25 modulates NSCLC cell radio-sensitivity – inhibiting BTG2 expression
miR-92a cervical cancer miR-92a. upregulated in cervical cancer & promotes cell proliferation and invasion by targeting FBXW7
MiR-153 NSCLC MiR-153 inhibits migration and invasion of human non-small-cell lung cancer by targeting ADAM19
miR-203 melanoma miR-203 inhibits melanoma invasive and proliferative abilities by targeting the polycomb group gene BMI1
miR-204-5p Papillary thyroid miR-204-5p suppresses cell proliferation by inhibiting IGFBP5 in papillary thyroid carcinoma
miR-342-3p Hepato-cellular miR-342-3p affects hepatocellular carcinoma cell proliferation via regulating NF-κB pathway
miR-1271 NSCLC miR-1271 promotes non-small-cell lung cancer cell proliferation and invasion via targeting HOXA5
miR-203 pancreas Pancreatic cancer derived exosomes regulate the expression of TLR4 in dendritic cells via miR-203
miR-203 metastatic SCC Rewiring of an Epithelial Differentiation Factor, miR-203, to Inhibit Human SCC Metastasis
miR-204 RCC TRPM3 and miR-204 Establish a Regulatory Circuit that Controls Oncogenic Autophagy in Clear Cell Renal Cell Carcinoma
NA urologic MicroRNAs and cancer. Current and future perspectives in urologic oncology
NA RCC MicroRNAs and their target gene networks in renal cell carcinoma
NA osteoSA MicroRNAs in osteosarcoma
NA urologic MicroRNA in Prostate, Bladder, and Kidney Cancer
NA urologic Micro-RNA profiling in kidney and bladder cancers

 

Current status of miRNA-targeting therapeutics and preclinical studies against gastroenterological carcinoma
Shibata et al. Molecular and Cellular Therapies 2013, 1:5 http://www.molcelltherapies.com/content/1/1/5

Differential expression profiling of microRNAs and their potential involvement in renal cell carcinoma pathogenesis
Clinical Biochemistry 43 (2010) 150–158
http://dx.doi.org:/10.1016/j.clinbiochem.2009.07.020

A microRNA expression ratio defining the invasive phenotype in bladder tumors
Urologic Oncology: Seminars and Original Investigations 28 (2010) 39–48
http://dx.doi.org:/10.1016/j.urolonc.2008.06.006

A Pleiotropically Acting MicroRNA, miR-31, inhibits breast cancer growth
Cell 137, 1032–1046, June 12, 2009
http://dx.doi.org:/10.1016/j.cell.2009.03.047

Inhibition of RAC1-GEF DOCK3 by miR-512-3p contributes to suppression of metastasis in non-small cell lung cancer
Intl JBiochem & Cell Biol 2015; 61:103-114
http://dx.doi.org/10.1016/j.biocel.2015.02.005

Methylation-associated silencing of miR-495 inhibit the migration and invasion of human gastric cancer cells by directly targeting PRL-3
Biochem Biochem Res Commun 2014; 456:344-350
http://dx.doi.org/10.1016/j.bbrc.2014.11.083

microRNA-218 inhibits prostate cancer cell growth and promotes apoptosis by repressing TPD52 expression
Biochem Biophys Res Commun 2015; 456:804-809
http://dx.doi.org/10.1016/j.bbrc.2014.12.026

MicroRNA-373 functions as an oncogene and targets YOD1 gene in cervical cancer
BBRC 2015; xx:1-6
http://dx.doi.org/10.1016/j.bbrc.2015.02.138

miR-25 modulates NSCLC cell radio-sensitivity – inhibiting BTG2 expression
BBRC 2015; 457:235-241
http://dx.doi.org/10.1016/j.bbrc.2014.12.094

miR-92a. upregulated in cervical cancer & promotes cell proliferation and invasion by targeting FBXW7
BBRC 2015; 458:63-69
http://dx.doi.org/10.1016/j.bbrc.2015.01.066

MiR-153 inhibits migration and invasion of human non-small-cell lung cancer by targeting ADAM19
BBRC 2015; 456:381-385
http://dx.doi.org/10.1016/j.bbrc.2014.11.093

miR-203 inhibits melanoma invasive and proliferative abilities by targeting the polycomb group gene BMI1
BBMC 2015; 456: 361-366
http://dx.doi.org/10.1016/j.bbrc.2014.11.087

miR-204-5p suppresses cell proliferation by inhibiting IGFBP5 in papillary thyroid carcinoma
BBRC 2015; 457:621-627
http://dx.doi.org/10.1016/j.bbrc.2015.01.037

miR-342-3p affects hepatocellular carcinoma cell proliferation via regulating NF-κB pathway
BBRC 2015; 457:370-377
http://dx.doi.org/10.1016/j.bbrc.2014.12.119

miR-1271 promotes non-small-cell lung cancer cell proliferation and invasion via targeting HOXA5
BBRC 2015; 458:714-719
http://dx.doi.org/10.1016/j.bbrc.2015.02.033

Pancreatic cancer derived exosomes regulate the expression of TLR4 in dendritic cells via miR-203
Cell Immunol 2014; 292:65-69
http://dx.doi.org/10.1016/j.cellimm.2014.09.004

Rewiring of an Epithelial Differentiation Factor, miR-203, to Inhibit Human Squamous Cell Carcinoma Metastasis
Cell Reports 2014; 9:104-117
http://dx.doi.org/10.1016/j.celrep.2014.08.062

TRPM3 and miR-204 Establish a Regulatory Circuit that Controls Oncogenic Autophagy in Clear Cell Renal Cell Carcinoma
Cancer Cell Nov 10, 2014; 26: 738–753
http://dx.doi.org/10.1016/j.ccell.2014.09.015

MicroRNA in Prostate, Bladder, and Kidney Cancer
Eur Urol 2011; 59:671-681
http://dx.doi.org/10.1016/j.eururo.2011.01.044

Micro-RNA profiling in kidney and bladder cancers
Urologic Oncology: Seminars and Original Investigations 2007; 25:387–392
http://dx.doi.org:/10.1016/j.urolonc.2007.01.019

MicroRNAs and cancer. Current and future perspectives in urologic oncology
Urologic Oncology: Seminars and Original Investigations 2010; 28:4–13
http://dx.doi.org:/10.1016/j.urolonc.2008.10.021

MicroRNAs and their target gene networks in renal cell carcinoma
BBRC 2011; 405:153-156
http://dx.doi.org/10.1016/j.bbrc.2011.01.019

MicroRNAs in osteosarcoma
Clin Chim Acta 2015; 444:9-17
http://dx.doi.org/10.1016/j.cca.2015.01.025

 

Table 2. miRNA cancer therapeutics

 

 

  • miRNA and mRNA cancer signatures determined by analysis of expression levels in large cohorts of patients
    | PNAS | Nov 19, 2013; 110(47): 19160–19165
    http://www.pnas.org/cgi/doi/10.1073/pnas.1316991110The study of mRNA and microRNA (miRNA) expression profiles of cells and tissue has become a major tool for therapeutic development. The results of such experiments are expected to change the methods used in the diagnosis and prognosis of disease. We introduce surprisal analysis, an information-theoretic approach grounded in thermodynamics, to compactly transform the information acquired from microarray studies into applicable knowledge about the cancer phenotypic state. The analysis of mRNA and miRNA expression data from ovarian serous carcinoma, prostate adenocarcinoma, breast invasive carcinoma, and lung adenocarcinoma cancer patients and organ specific control patients identifies cancer-specific signatures. We experimentally examine these signatures and their respective networks as possible therapeutic targets for cancer in single cell experiments.

 

 

RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently,RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA  editing may be a potential target for therapeutic natural products

 

Aberrant microRNA (miRNA) expression is implicated in tumorigenesis. The underlying mechanisms are unclear because the regulations of each miRNA on potentially hundreds of mRNAs are sample specific.

 

We describe a novel approach to infer Probabilistic Mi RNA–mRNA  Interaction Signature (‘ProMISe’) from a single pair of miRNA–mRNA expression profile. Our model considers mRNA and miRNA competition as a probabilistic function of the expressed seeds (matches). To demonstrate ProMISe, we extensively exploited The Cancer Genome Atlas data. As a target predictor, ProMISe identifies more confidence/validated targets than other methods. Importantly, ProMISe confers higher cancer diagnostic power than using expression profiles alone.

Gene set enrichment analysis on averaged ProMISe uniquely revealed respective target enrichments of oncomirs miR-21 and 145 in glioblastoma and ovarian cancers. Moreover, comparing matched breast (BRCA) and thyroid (THCA) tumor/normal samples uncovered thousands of tumor-related interactions. For example, ProMISe– BRCA network involves miR-155/183/21, which exhibits higher ProMISe coupled with coherently higher miRNA expression and lower target expression; oncomirs miR-221/222 in the ProMISe–THCA network engage with many downregulated target genes. Together, our probabilistic approach of integrating expression and sequence scores establishes a functional link between the aberrant miRNA and mRNA expression, which was previously under-appreciated due to the methodological differences.

 

 

 

 

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What is the meaning of so many RNAs?

Writer and Curator: Larry H. Bernstein, MD, FCAP

 

The following is a third in the 2nd series that is focused on the topic of the impact of genomics and transcriptomics in the evolution of 21st century of medicine, We have already visited the transcription process, by which an RNA sequence is read.  This is essential for protein synthesis through the ordering of the amino acids in the primary structure. However, there are microRNAs and noncoding RNAs, and there are transcription factors.  The transcription factors bind to chromatin, and the RNAs also have some role in regulating the transcription process. We shall examine this further.

  • RNA and the transcription the genetic code

Larry H. Bernstein, MD, FCAP, Writer and Curator https://pharmaceuticalintelligence.com/2014/08/02/rna-and-the-transcription-of-the-genetic-code/

  • The role and importance of transcription factors?

Larry H. Bernstein, MD, FCAP, Writer and Curator https://pharmaceuticalintelligence.com/2014/8/05/What-is-the-meaning-of-so-many-RNAs

  • What is the meaning of so many RNAs?

Larry H. Bernstein, MD, FCAP, Writer and Curator https://pharmaceuticalintelligence.com/2014/8/05/What-is-the-meaning-of-so-many-RNAs

  • Pathology Emergence in the 21st Century

Larry Bernstein, MD, FCAP, Author and Curator https://pharmaceuticalintelligence.com/2014/08/03/pathology-emergence-in-the-21st-century/

  • The Arnold Relman Challenge: US HealthCare Costs vs US HealthCare Outcomes

Larry H. Bernstein, MD, FCAP, Reviewer and Curator; and Aviva Lev-Ari, PhD, RN, Curator https://pharmaceuticalintelligence.com/2014/08/05/the-relman-challenge/

Exploring the Roles of Enhancer RNAs Scientists have recently discovered that enhancers are often transcribed into RNAs. But they’re still not sure what, if anything, these eRNAs do.

By Ashley P. Taylor | May 7, 2014

http://www.the-scientist.com/?articles.view/articleNo/39906/title/Exploring-the-Roles-of-Enhancer-RNAs/

Four mechanisms by which eRNAs can function

Four mechanisms by which eRNAs can function

Four mechanisms by which eRNAs can function Wikimedia, PClermont There’s a lot that scientists don’t yet know about enhancers, genetic elements first described almost 35 years ago that, unlike promoters,

  • can upregulate genes from some distance.

That distance, while generally under 100 kilobases, can vary greatly. Usually,

  • enhancers regulate the genes closest to them,

but not always; the enhancer for the developmental gene Sonic hedgehog is a megabase away from its promoter in the human genome. What scientists do know is that enhancers seem to play key roles in human biology. One recently published atlas of enhancer expression in the human genome suggested that

  • enhancers, which are expressed differently across cell types,

could help explain how one genome encodes so many different kinds of cells. The same paper reported that

  • single-nucleotide changes associated with human diseases are
  • over-represented in enhancers and promoters relative to exons.

In a 2010 Nature paper, researchers in the lab of neurobiologist Michael Greenberg at Harvard Medical School reported that enhancers can produce RNA. Working with cultured mouse neurons, the scientists found that

  • enhancers activated by neuron depolarization were transcribed all over the genome
  • and that levels of enhancer RNAs (eRNAs)
  • correlated with the production of messenger RNA (mRNA)
  • from genes near the enhancers.

Researchers had observed enhancer RNAs before, but this was the first evidence of widespread enhancer transcription. In the years since, several other groups have reported finding eRNAs in various biological systems. While eRNAs promise to help researchers understand how enhancers work, they also raise many questions of their own. ERNAs are fairly short, ranging in length from 500 basepairs to 5 kilobases. Most of the time, although not always,

  • enhancer RNAs are transcribed from both DNA strands, producing what are called bidirectional transcripts.

As the Greenberg lab originally found,

  • eRNA production correlates with the production of mRNA from the genes that enhancers regulate.

“Perhaps the best mark of an active enhancer is the induction of an enhancer RNA,” said M. Geoffrey Rosenfeld from the University of California, San Diego, whose group studies genome-wide regulation of gene expression and has been probing eRNA function. Of course, correlation does not equal causation, he warned. “The next question is whether the enhancer RNA is just a mark of an active enhancer or if it could have function, per se.” What might those functions be? Scientists have crafted a few hypotheses, although most agree that the mechanisms by which eRNAs function remain a mystery. One thought is that eRNAs represent transcriptional noise. That’s a view held by Albin Sandelin at the Bioinformatics Centre of Copenhagen University, who led the aforementioned enhancer atlas project. “Something that most people believe is that the enhancer, when it’s active, it loops in to the promoter, and then the concentration of RNA polymerase II will be a lot higher,” Sandelin told The Scientist. He referred to the idea that

  • enhancers upregulate genes by physically interacting with target promoters;
  • as enhancers and the promoters they regulate are usually on the same chromosome,
  • this interaction creates a loop of DNA between the two genetic elements.

“I think that most of the eRNAs are due to this: you have piece of open DNA, which is the enhancer, near a promoter with high concentrations of RNA polymerase II, and

  • then you will get transcription of the enhancer.”

This idea is supported by the fact that, because they are so short, eRNAs tend to degrade rather quickly. “There are a few cases where [enhancer RNAs] are proven to be functional; I just personally don’t think that the majority work that way,” Sandelin said. “[But] it seems to me that this [supposed function] is a byproduct of proximity to some sites that have a lot of polymerase II.” Another hypothesis suggests that

  • the act of transcription trumps the importance of the transcripts themselves.

Experiments in macrophages, led by the University of California, San Diego’s Chris Glass, support this idea. “I don’t think that transcription at enhancers is noise,” said Vittorio Sartorelli, a researcher at the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) who has studied eRNAs in the context of myogenesis. “Whether eRNAs are absolutely required in every situation or the act of transcription at enhancers is the major determinant, I think that it’s still open for debate,” he said. Several studies have presented evidence to suggest that eRNAs do play a key role. As described in a 2013 Nature paper, the Rosenfeld lab found that estrogen bound to its receptor in breast cancer cells increases expression of particular genes by binding to enhancers and inducing the transcription of eRNAs. Eliminating the eRNAs using both RNA interference (RNAi) and antisense oligonucleotides—

  • which bind to the RNA and lead to its degradation by an RNase—
  • reduced the ability of enhancers to upregulate gene expression.

Depletion of eRNAs in this system also

  • reduced looping between enhancers and promoters.

“Using two different strategies, there [was] evidence that

  • the presence of the interrogated eRNA is important for activation of the target gene
  • and for the interaction between the enhancer and the cognate regulated promoter,” said Rosenfeld.

Taking the reverse approach, the researchers also tested whether eRNAs could upregulate transcription independent of the enhancer itself. Rosenfeld and his colleagues experimentally

  • tethered eRNAs to a promoter driving expression of a luciferase reporter gene in a plasmid construct. When this construct was
  • transfected into cultured breast cancer cells,
    • luciferase expression was upregulated about 2.5-fold.

“These data indicate that

  • the interrogated eRNA plays a functional role, at least in this system,
  • in activation of the coding target gene,”

said Rosenfeld. “But it does not distinguish between the alternative possibilities that this is because of a specific sequence in the eRNA that might interact with a regulatory factor or that some other function of the eRNA …” Scientists, such as Reuven Agami from the Netherlands Cancer Institute, the NIAMS’s Sartorelli, and San Diego’s Glass, have reported similar results in other systems. Greenberg said that some eRNAs could have functions unrelated to the promoters activated by their associated enhancers while others could play direct roles in gene expression. “I think that we need to keep an open mind as to what the functions are; there are likely to be multiple functions.” Tags: transcriptional       regulationtranscriptionRNAipromotersmRNAEnhancers and DNA   SiRNA-Mediated Down-Regulation of Livin Expression in Breast Cancer Cells Hussein Sabit, Mohamed M.M. Ibrahim and Nabil S. Awad 1College of Biotechnology, Misr University for Science and Technology, Egypt 2Scientific Research Deanship, Taif University, KSA Academic Journal of Cancer Research 6 (2): 69-73, 2013  http://dx.doi.org:/10.5829/idosi.ajcr.2013.6.2.76211   Livin, also called melanoma inhibitor of apoptosis protein (IAP) or kidney IAP, is an anti-apoptotic protein belonging to the IAP family which consists of eight members. The genes of this family render cancer cells insensitive to apoptotic stimulation. The aim of the present study was to investigate and assess the role of siRNA

  • in the regulation of livin gene expression in two breast cancer cell lines (4Ti and MCF-7).

Lipofection was carried out to introduce the livin-specific small interference RNA (siRNA) segment (19 mer) into the cancerous cells and the livin expression was determined using RT-PCR. Trypan blue assay was conducted to assess the integrity of the cell membranes after being transfected. 3-(4, 5-dimethylthiazol-2-yl)-2-5-diphenyltetrazolium bromide (MTT) assay was also implemented to assess the cell viability through the mitochondrial reductase enzymes activity. The obtained results concluded that

  • transfecting the cancerous cells with livin-specific siRNA have
  • led to the down regulation of livin expression.

RNA interference (RNAi) targeting the anti-apoptotic genes such as livin is a promising approach and may help as a future therapeutic tool for breast cancer. Key words: SiRNA Livin Down-regulation Breast cancer     Endogenous RNA interference is driven by copy number Cristina Cruz, Jonathan Houseley* Epigenetics Programme, The Babraham Institute, Cambridge, United Kingdom Cell biology | Genomics and evolutionary biology cruz and Houseley. eLife 2014;3:e01581  http://dx.doi.org:/10.7554/elife.01581   A plethora of non-protein coding RNAs are produced throughout eukaryotic genomes, many of which are transcribed antisense to protein-coding genes and could potentially instigate

  • RNA interference (RNAi) responses.

Here we have used a synthetic RNAi system to show that

  • gene copy number is a key factor controlling RNAi for transcripts from endogenous loci,

since transcripts from multi-copy loci form double stranded RNA more efficiently than transcripts from equivalently expressed single-copy loci.

  • Selectivity towards transcripts from high-copy DNA

is therefore an emergent property of a minimal RNAi system. The ability of RNAi to

  • selectively degrade transcripts from high-copy loci
  • would allow suppression of newly emerging transposable elements,

but such a surveillance system requires transcription. We show that

  • low-level genome-wide pervasive transcription
  • is sufficient to instigate RNAi, and propose that
  • pervasive transcription is part of a defense mechanism capable of directing a
  • sequence-independent RNAi response against
  • transposable elements amplifying within the genome.

http://dx.doi.org:/10.7554/eLife.01581.001     Over the past decade, our understanding of the complexity of the eukaryotic transcriptome has been revolutionized. Genome-wide sequencing studies in many organisms have revealed that protein-coding mRNAs are augmented by a multitude of non-protein coding RNAs (ncRNAs), many produced from regions of the genome traditionally considered to be transcriptionally silent (Brummelkamp et al., 2002; Bertone et al., 2004; Cheng et al., 2005; David et al., 2006; Birney et al., 2007). Functional data for the vast majority of ncRNAs are currently lacking, with only a few examples characterized in any detail; however, the diversity of mechanisms by which these act suggests that ncRNAs have a rich and varied biology that is largely still to be sampled. Long ncRNAs which overlap protein-coding genes have the potential to modulate the expression of their cognate coding RNA. Early characterized examples in yeast were thought to work by directly disrupting transcription factor or polymerase binding to the promoter of the coding RNA (Martens et al., 2004; Hongay et al., 2006); however, more recent data implicate specific chromatin structure changes in repression (Gelfand et al., 2011; Hainer et al., 2011), and many other cases of ncRNAs that alter chromatin modifications have been described (Camblong et al., 2007; Berretta et al., 2008; Houseley et al., 2008; Pinskaya et al., 2009; van Werven et al., 2012). Chromatin modifications are not necessarily repressive, and ncRNAs that enhance expression of their overlapping coding gene have also been described (Uhler et al., 2007; Hirota et al., 2008).

Frequency of annotated antisense non-protein coding RNAs

Frequency of annotated antisense non-protein coding RNAs

Figure 1. Frequency of annotated antisense non-protein coding RNAs (ncRNAs) and effects on mRNA abundance. (A) Schematic of an example sense mRNA-antisense (ncRNA) system. (B) Number of annotated open reading frames (ORFs) with antisense transcripts. Positions of CUTs, SUTs, and XUTs were collated with expressed ORFs (Xu et al., 2009; van Dijk et al., 2011), SUTs were later re-classified as XUTs were removed. Overlaps between ORFs expressed in glucose media (total 5171, Xu et al., 2009) and other RNAs were calculated and summed for increasing minimum overlaps of 50–500 bp. ORF–ORF overlaps and ORF–ncRNA overlaps were analyzed separately as ORF–ORF overlaps are consistently smaller. Detailed figures are given in Table 1. (C) Abundance of short interfering RNAs (siRNAs) in RNA interference (RNAi)+ strain produced from expressed ORFs with and without an annotated overlapping antisense ncRNA, based on read counts from published high-throughput sequencing data (Drinnenberg et al., 2011). Minimum antisense overlap with ORF was set at 250 bp; only ORFs with >100 reads in the wild-type poly(A)+ library were assessed to remove noise. Stated p value calculated by Student’s t test. (D) Abundance of mRNA in RNAi+ cells relative to wild-type; data source and categories as in C, differences were not significant. http://dx.doi.org:/10.7554/eLife.01581.003

Multi-copy loci are preferentially targeted by RNA interference (RNAi).

Multi-copy loci are preferentially targeted by RNA interference (RNAi).

Figure 4. Multi-copy loci are preferentially targeted by RNA interference (RNAi). (A) Short interfering RNA (siRNA) (Drinnenberg et al., 2011) and total RNA (Silva et al., 2002) abundance for loci with copy number <2 (left, single-copy) or ≥2 (right, multi-copy). (B) Quantification of data from A binned into categories of increasing total RNA level, with p values for pairwise comparisons of siRNA abundance in single-copy and multi-copy datasets using the Wilcoxon Rank Sum test. (C) Copy number distribution of the 1% of loci with the highest siRNA:total RNA ratio compared with other loci; difference is significant by Wilcoxon Rank Sum test, p<2.2 × 10−16, loci scoring below noise threshold (0–2 category in B) were removed. n values for tests in B and C are given in Table 2. (D) Comparison of copy number with siRNA:total RNA ratio across chromosome I. Cruz and Houseley. eLife 2014;3:e01581. http://dx.doi.org:/10.7554/elife.01581   eLife digest Genes contain the codes that are needed to make the proteins used by cells. This code is transcribed to make a messenger RNA molecule that is then translated to make a protein. However, other types of RNA called

  • non-coding RNA molecules can disrupt this process
  • by binding to messenger RNA molecules,
  • with matching sequences, before translation begins.

RNA interference involves enzymes called Dicer and Argonaute. Many cells contain large numbers of non-coding RNA molecules—

  • so called because they are not translated to produce proteins—
  • and many of these are capable of starting the process of RNA interference.

However, most do not, and the reasons for this are not understood. Now, work by Cruz and Houseley has provided new insight into this phenomenon by showing that

  • it is related to the number of copies of the gene encoding such RNAs in the genome.

Yeast cells normally do not have the genes for RNA interference, but Cruz and Houseley used

  • genetically engineered yeast cells containing Dicer and Argonaute.

Although most of the messenger RNA molecules in these cells showed no change,

  • the expression of some genes with high ‘copy numbers’ was reduced.

Further experiments that involved adding more and more copies of other genes showed that

  • RNA interference could selectively target messenger RNA molecules produced from genes with an increased copy number—
  • particularly if the copies of the genes were clustered in one location in the genome.

RNA interference is also used to defend against DNA sequences that invade and multiply within a genome, such as viruses and other ‘genetic parasites’. As such, the effect observed by Cruz and Houseley could explain why entire genomes are often continuously copied to RNA at low levels. This activity would allow the monitoring of the genome for the invasion of any genetic parasites that had multiplied to high numbers. Following on from this work, the next challenge will be to understand how gene copy number and location are balanced to achieve a selective RNA interference system.   RNA in unexpected places: long non-coding RNA functions in diverse cellular contexts Sarah Geisler1,2 and Jeff Coller1 1Center for RNA Molecular Biology, Case Western Reserve, Cleveland , OH 2Present address: Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, 4058 Basel, Switzerland. NATURE REVIEWS | MOLECULAR CELL BIOLOGY

  1. nature.com/reviews/molcellbio http://dx.doi.org:/10.1038/nrm3679

Abstract | The increased application of transcriptome-wide profiling approaches has led to an explosion in the number of documented long non-coding RNAs (lncRNAs). While these new and enigmatic players in the complex transcriptional milieu are encoded by a significant proportion of the genome, their functions are mostly unknown. Early discoveries support a paradigm in which   lncRNAs regulate transcription via chromatin modulation, but

  • new functions are steadily emerging.

Given the biochemical versatility of RNA, lncRNAs may be used for various tasks, including

  • post-transcriptional regulation,
  • organization of protein complexes,
  • cell-cell signalling and
  • allosteric regulation of proteins.

Nature Reviews – Molecular Cell Biology | 9 Oct 2013; http://dx.doi.org:/10.1038/nrm3679   In this Review, we focus on the functional attrib­utes of RNA and highlight the unconventional, and perhaps underappreciated, biological contributions of lncRNAs, including the diverse mechanisms through which lncRNAs participate in transcriptional regu­lation. We touch briefly on the roles of lncRNAs in regulating chromatin states, as this has been explored in several recent reviews (see REFS 8,9,13–15). In addi­tion, we highlight roles beyond transcription whereby lncRNAs function in various cellular contexts, includ­ing

  1. post-transcriptional regulation,
  2. post-translational regulation of protein activity,
  3. organization of protein complexes,
  4. cell–cell signalling, as well as
  5. recombination

Transcription activator-like effectors (TALEs). Naturally found in some bacteria, TALEs are proteins that bind DNA through repeat domains, and their code for sequence specificity has been elucidated allowing sequence specific TALEs to be engineered.

  • PUF proteins

A family of sequence-specific RNA-binding proteins, which bind 3ʹ untranslated regions within mRNAs to repress target mRNA translation.

  • Pseudogenes

Dysfunctional relatives of normal genes thought to arise from duplication or retrotransposition.

  • Chromatin-modifying complexes

Protein complexes that catalyse the covalent chemical modification of chromatin

  • Adaptive immune system

A system of specialized cells that create immunological memory via specific antibodies after an initial response to a pathogen.   A biochemically versatile polymer   Figure 1 | RNA is a biochemically versatile polymer. a | RNA is particularly well suited for sequence-specific nucleic acid targeting through base pairing interactions over a short region (for example, eight nucleotides). By contrast, proteins require repeat motifs comprising 35–39 amino acids (105–117 base pairs of genomic sequence) to recognize a single RNA base with specificity. Therefore, to recognize eight nucleotides, 280–312 amino acids (840–936 base pairs of genomic sequence) would be required. Compared to the eight base pairs required for an RNA, protein-based nucleic acid recognition requires substantially more genomic sequence17. b | RNA can fold into complex three-dimensional structures that can specifically bind various ligands, including small molecules and peptides18. c | RNA is suitable for transient expression, because a fully functional RNA can be generated immediately following transcription and processing but can also be rapidly degraded. Together, this allows RNA effectors to be produced in quick pulses. Proteins, however, require additional steps, including mRNA export and translation, to produce a functional peptide. Likewise, both the mRNA and the protein need to be degraded to turn off expression. d | RNA is malleable and, therefore, more tolerant of mutations. Although some mutations in protein-coding genes are silent, many are deleterious such as nonsense mutations that generate truncated polypeptides. RNA, however, can tolerate mutations even within the regions responsible for target recognition. e | RNA-dependent events can be heritable. For instance, processed pseudogenes were once RNA transcripts that have been genomically integrated. In addition, telomerase uses an RNA template to add telomeric repeats to the ends of chromosomes. ORF, open reading frame; Pol II, RNA polymerase II.   lncRNAs as regulators of transcription   Figure 2 | lncRNAs regulate transcription through several mechanisms. ac | Long non-coding RNAs (lncRNAs) can modulate chromatin through transcription-independent (part a) and transcription-dependent mechanisms (parts b and c). lncRNAs can bind one or more chromatin-modifying complexes and target their activities to specific DNA loci (part a). Depending on the nature of the enzymes bound, lncRNA-mediated chromatin modifications can activate or repress gene expression22,23,26,27,120. Chromatin-modifying complexes bound to the RNA polymerase II (Pol II) carboxy-terminal domain (CTD) can modify chromatin during transcription of lncRNAs33–35 (part b). Transcription of lncRNAs can also result in chromatin remodelling that can either favour or inhibit the binding of regulatory factors (part c). Depending on the nature of the factors that bind during remodelling, gene expression is activated or repressed 37–40. dg | lncRNAs can modulate both the general transcription machinery (parts d and e) as well as specific regulatory factors (parts f and g). lncRNAs can bind Pol II directly to inhibit transcription47 (part d). Formation of lncRNA–DNA triplex structures can also inhibit the assembly of the pre-initiation complex48 (part e). lncRNAs can fold into structures that mimic DNA-binding sites (left) or that generally inhibit or enhance the activity of specific transcription factors (right)50–53 (part f). lncRNAs can also regulate gene expression by binding specific transport factors to inhibit the nuclear localization of specific transcription factors54 (part g). Regulators of mRNA processing Modulators of post-transcriptional control   Figure 3 | lncRNAs influence mRNA processing and post-transcriptional regulation. a,b | Long non-coding RNAs (lncRNAs) can modulate mRNA processing. Splicing patterns can be influenced by lncRNAs that associate with the pre-mRNA (part a). For example, splicing of the first intron of neuroblastoma MYC mRNA is prevented by a natural antisense transcript61. Antisense lncRNAs that associate with an mRNA could direct mRNA editing, perhaps through association of the duplex with ADAR (adenosine deaminase acting on RNA) enzymes that catalyse adenosine to inosine conversion in double-stranded RNA63,66 (part b). cf | lncRNAs modulate post-transcriptional regulatory events. lncRNAs containing SINEB2 repeat elements can upregulate translation through association with the 5ʹ region of an mRNA68 (part c). lncRNAs containing Alu repeat elements associate with the Alu elements in the 3ʹ untranslated region (UTR) of an mRNA, and this double-stranded structure can direct Staufen-mediated decay through a pathway that is molecularly similar to nonsense-mediated decay70 (part d). lncRNAs can mask miRNA-binding sites on a target mRNA to block miRNA-induced silencing through the RNA-induced silencing complex (RISC)72 (part e). Linear or circular lncRNAs can function as miRNA decoys to sequester miRNAs from their target mRNAs74,75 (part f).                   Regulators of protein activity                 Scaffolds for higher-order complexes                 Signaling molecules   Figure 4 | lncRNAs are involved in various cellular contexts. Long non-coding RNAs (lncRNAs) modulate protein activity by post-translational mechanisms (parts ac). a | Small nucleolar lncRNAs (sno-lncRNAs) generated from the 15q11‑q13 locus bind and modulate the activity of the FOX2 alternative splicing factor, and this can inhibit FOX2‑mediated splicing80. b | The highly structured rncs‑1 lncRNA binds Dicer to inhibit the processing of small RNAs81. c | The gadd7 lncRNA binds and modulates the ability of TDP43 (TAR DNA-binding protein 43) to target and process specific mRNAs84. d | lncRNAs can act as scaffolds to organize several complexes24. e | As the cargo of exosomes that mediate transfer of material between cells, exosomal shuttle RNAs (exRNAs) may act as signalling molecules during cell–cell communication; exosomal cargo includes mRNAs, microRNAs (miRNAs) and lncRNAs102. f | lncRNAs expressed from the switch region of genes encoding antibodies form R‑loops to direct class switch recombination via activation-induced deaminase (AID) recruitment111                   Vehicles for increasing genetic diversity                 Conclusions and perspectives                 lncRNAs have now been demonstrated to regulate all aspects of gene expression, including transcription (FIG. 2), processing and post-transcriptional control path­ways (FIG. 3). Likewise, lncRNAs have also been shown to regulate protein function and organize multiprotein com­plex assembly. Now with hints that lncRNAs might par­ticipate in cell–cell communication and recombination, the possible reach of lncRNA functions seems endless (FIG. 4).   Targeting Noncoding RNAs in Disease: Challenges and Opportunities Science/AAAS technology webinar   4 Sept 2013  

  • Noncoding RNAs serve a wide range of functions in cellular and developmental processes and are therefore likely involved in the development and pathophysiology of many diseases.

Thanks to the effective inhibition of micro RNAs in vivo, scientists have already made groundbreaking discoveries about the contribution of short regulating RNAs in human diseases in areas such as cancer, heart disease, and diabetes. Dr. David Corey from the Department of Pharmacology at the University of Texas Southwestern Medical Campus in Dallas, Texas; Dr. Stefanie Dimmeler from the Institute of Cardiovascular Regeneration at Goethe‐University in Frankfurt, Germany; Dr. Jan‐Wilhelm Kornfeld from the Department of Mouse Genetics and Metabolism, University of Cologne in Germany.   Dr. Corey’s group is interested in antigene oligonucleotides, antisense oligonucleotides, nucleic acids, RNAi, and telomerase.   I have two goals for my presentation today.

  • give a brief introduction to the concept of using nucleic acids as dugs.
  • show the boundaries of using nucleic acids to affect gene expression

 

  • a search for new methods to develop drugs includes nucleic acids that can bind to RNA and affect gene expression. The advantages of this approach are that one can identify an active oligomer, a lead compound very quickly in weeks rather than years.
  • the medicinal chemistry and pharmacology of all of these nucleic acids is similar
  • by affecting gene expression, one has the ability to treat almost any disease

the two main strategies for using nucleic acid to affect gene expression are

  • use single cell stranded oligonucleotides to bind directly to an RNA target and block their action.
  • use double stranded RNA. Double stranded RNA then goes through the RNA silencing process. That machinery
  • helps it to find a messenger RNA target and efficiently inhibit gene expression.

What kind of cellular RNAs can be targeted by nucleic acids?

  • they could be the RNA domains of ribonucleoproteins and the classic example of that is telomerase.
  • One could also target messenger RNA.
  • You could block translation or you could affect splicing so for example upregulate an isoform that might be useful in treating a disease.
  • Today, we focus mainly on targetingnoncodingRNAs and one of thosenoncodingRNAs ismicroRNAs and by
    • blocking the microRNA you can affect its action.

I’m going to discuss targeting long noncoding RNAs, which can be used to either up or down regulate gene transcription. Earlier this year Kynamro, an antisense oligonucleotide that targets Ap‐B1 messenger RNA, was approved by the food and drug administration. This is a systemically administered oligonucleotide that’s been shown to reduce LDL cholesterol. So it’s the strongest proof to date that synthetic oligonucleotides can be made on the scale that’s large enough to be used as drugs and be administered to patients and get through the FDA approval process.

  • Now I’d like to show you just how the boundaries of regulation can be pushed by using noncoding RNAs to regulate transcription of an operon within the icosanoid signaling pathway. Messenger RNAs are often overlapped by long RNAs at both their 3’ and the 5’ termini as well as within the gene providing a new realm of potential targets for addressing gene expression.

 

  • examples of the important ones include XIST and HOTAIR
  • These are genes that are known to regulate x chromosome inactivation or transcriptional multigene regulation programs. one might think that with RNA that RNAi factors that are so successful in regulating messenger RNA might be involved. But today they haven’t really been strongly implicated in mammalian cells.

 

  •  we know that microRNAs are in the nucleus.
  • we also know that RNAi factors like argonaute 2 are in the nucleus.
  • we also know that noncoding RNAs are in the nucleus.

The hypothesis that we’ve built up over that time is that these RNAi factors can interact with small RNAs

  • to form what are essentially ribonucleoprotein complexes that can act to control either gene transcription or gene splicing.
  • The RNA domain protects the RNA and promotes binding to the target. The RNA domain directs specificity to a particular RNA target inside the cell, for example a long noncoding RNA.

in about 2010 working with my colleague Bethany Janowski, we decided to go very deeply into an important physiology pathway — the eicosanoid production pathway and cyclooxygenase‐2 and PLA2G4a

  • we began by asking whether or not there was noncoding expression at the COX‐2 promoter
  • we characterized this expression by RNA sequencing by quantitative PCI and 5’ RACE and
  • we discovered that there were transcripts overlapping the COX-promoter in both the antisense and the sense direction –
  • we now have the noncoding RNA raw material that might allow recognition to control gene expression of COX‐2 messenger RNA.

 

  • there were a substantial number of microRNAs with complementarity to the COX‐2 promoter.
  • small RNA sequencing to identify microRNAs in the nucleus and
  • microRNAs that were both in the nucleus and complementary to the

COX‐2 promoter became candidates for regulating COX‐2.

  • The most promising of these microRNAs was microRNA‐
  • It had strong complementarity to two adjacent sequences within the COX‐2

promoter. So that resembles how micro‐RNAs recognize typically 3’ untranslated regions.

  • it became our prime candidate for investigating for potential regulation of COX‐2 expression through regulating its transcription by binding a noncoding RNA.
  •  we used a microRNA inhibitor
  • When we add these inhibitors into cells COX‐2 expression goes down.
  • consistent with a microRNA binding to the noncoding RNA and activating COX‐2 expression

This is as far as this reviewer wishes to prodeed in the presentation(s)   Explore microRNA as therapeutic targets Efficient [in vivo] silencing using LNA™-enhanced inhibitors exiqon.com/in-vivo-mirna-inhibitors   Nature Reprint Collection MicroRNAs from bench to clinic   Progress in the microRNA fi eld over the last 12 years has been nothing but remarkable. MicroRNAs were only discovered in humans in 2001, but since then they have revolutionized cell biology and completely changed the way we view the regulation of gene expression. They are now known to be involved, at some level, in all cellular and developmental pathways and all major types of disease, including all cancers, as well as metabolic, cardiovascular, neuronal and immune-related disorders. Exiqon’s LNA™- based microRNA research tools have been instrumental in many of the groundbreaking discoveries in the field. In this collection, we are thrilled to present some of the recent advances in moving microRNAs from basic research into the clinic both as biomarkers and therapeutic targets. Since the discovery of circulating or extracellular microRNAs, their potential as minimally invasive diagnostic and prognostic markers for disease has been actively investigated. Here we feature two articles where qPCR profiling of microRNAs in biofluids have been shown to have diagnostic potential. Another promising area with clinical prospects is microRNA in situ hybridization (ISH) in FFPE samples. We have included an article detailing the prognostic potential of microRNA ISH in this collection. Due to their extensive involvement in human disease, microRNAs are naturally interesting targets for therapeutic intervention. One of the most advanced areas in this respect is the potential of microRNAs as therapeutic targets in cardiovascular disease and we have included a review of this area. In addition, two very recent and groundbreaking studies that have shown the exciting potential for microRNA inhibition in diabetes and epilepsy are also included.   Identification of serum microRNA profiles in colon cancer E Hofsli*,1,2,7, W Sjursen3,4,7, W S Prestvik5, J Johansen2, M Rye2, G Tranø6, et al. 1Department of Oncology, St Olavs Hospital, Trondheim University Hospital, 2Faculty of Medicine, Department of Cancer and Molecular Medicine, Norwegian University of Science and Technology,  3Department of Laboratory Medicine Children’s and Women’s Health, Norwegian University of Science and Technology, 4Department of Pathology and Medical Genetics, St Olavs Hospital, Trondheim University Hospital, 5 Faculty of Technology, Sør-Trøndelag University College, and 6Department of Gastrointestinal Surgery, St Olavs Hospital, Trondheim University Hospital, Olav Kyrresgt 17, Trondheim 7006, Norway British Journal of Cancer (2013) 108, 1712–1719 |  http://dx.doi.org/10.1038/bjc.2013.121 Background: microRNAs (miRNAs) exist in blood in an apparently stable form. We have explored whether serum miRNAs can be used as non-invasive early biomarkers of colon cancer. Methods: Serum samples from 30 patients with colon cancer stage IV and 10 healthy controls were examined for the expression of 375 cancer-relevant miRNAs. Based on the miRNA profile in this study, 34 selected miRNAs were measured in serum from 40 patients with stage I–II colon cancer and from 10 additional controls. Results: Twenty miRNAs were differentially expressed in serum from stage IV patients compared with controls (Po0.01). Unsupervised clustering revealed four subgroups; one corresponding mostly to the control group and the three others to the patient groups. Of the 34 miRNAs measured in the follow-up study of stage I–II patients, 21 showed concordant expression between stage IV and stage I–II patient. Based on the profiles of these 21 miRNAs, a supervised linear regression analysis (Partial Least Squares Regression) was performed. Using this model we correctly assigned stage I–II colon cancer patients based on miRNA profiles of stage IV patients. Conclusion: Serum miRNA expression profiling may be utilised in early detection of colon cancer. MicroRNAs from bench to clinic   Figure 2. Differentially expressed miRNAs in stage IV (red bars) vs stage I–II (blue bars) colon cancer. The expression of 34 miRNAs was compared, and 26 miRNAs were detected. In all, 21 of 26 detected miRNAs showed the same expression profile in early-stage I–II vs metastatic stage IV colon cancer.     Figure 3. Prediction analysis of early-stage colon cancer patients. Controls are shown in red and cancer samples in blue. 9 out of 10 healthy controls were correctly predicted as true negatives and 35 out of 40 patients with cancer as true positives.     MicroRNA profiling of diagnostic needle aspirates from patients with pancreatic cancer S Ali1, H Saleh2,3, S Sethi2, FH Sarkar1,2 and PA Philip*,1 1Department of Oncology; 2Department of Pathology; 3Karmanos Cancer Institute, Detroit Medical Center, Wayne State University School of Medicine, Detroit, MI   BACKGROUND: A major challenge to the development of biomarkers for pancreatic cancer (PC) is the small amount of tissue obtained at the time of diagnosis. Single-gene analyses may not reliably predict biology of PC because of its complex molecular makeup.MicroRNA (miRNA) profiling may provide a more informative molecular interrogation of tumours. The primary objective of this study was to determine the feasibility of performing miRNA arrays and quantitative real-time PCR (qRT– PCR) from archival formalin fixed paraffin-embedded (FFPE) cell blocks obtained from fine-needle aspirates (FNAs) that is the commonest diagnostic procedure for suspected PC. METHODS: MicroRNA expression profiling was performed on FFPE from FNA of suspicious pancreatic masses. Subjects included those who had a pathological diagnosis of pancreatic adenocarcinoma and others with a non-malignant pancreatic histology. Exiqon assay was used to quantify miRNA levels and qRT–PCR was used to validate abnormal expression of selected miRNAs. RESULTS: A total of 29 and 15 subjects had pancreatic adenocarcinoma and no evidence of cancer, respectively. The RNA yields per patient varied from 25 to 100 ng. Profiling demonstrated deregulation of over 228 miRNAs in pancreatic adenocarcinoma of which the top 7 were further validated by qRT–PCR. The expression of let-7c, let-7 f, and miR-200c were significantly reduced in most patients whereas the expression of miR-486-5p and miR-451 were significantly elevated in all pancreas cancer patients. MicroRNAs let-7d and miR-423-5p was either downregulated or upregulated with a significant inter-individual variation in their expression. CONCLUSION: This study demonstrated the feasibility of using archival FFPE cell blocks from FNAs to establish RNA-based molecular signatures unique to pancreatic adenocarcinoma with potential applications in clinical trials for risk stratification, patient selection, and target validation. British Journal of Cancer (2012) 107, 1354–1360.  http://dx.doi,org:/10.1038/bjc.2012.383 Comparative expression of seven miRNAs tested in FNA samples   Figure 1 Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs analysed by miRNA profiling in PC and their targeted genes.

miRNAs analysed by miRNA profiling in PC and their targeted genes

miRNAs analysed by miRNA profiling in PC and their targeted genes

Figure 2 Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs involved in PC and their target genes (A). The solid lines connecting genes represent a direct relation and dotted lines indirect relation. We also observed 15 bio functional network groups that included cancer, genetic disorder, and gastrointestinal disease (B).

Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs involved in PC and their target genes

Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs involved in PC and their target genes

Figure 6 Box plot representing the expression of 7 miRNAs as assessed by qRT–PCR in 29 FNA cell blocks from PC patients analysed individually compared with FNA cell blocks obtained from 15 normal controls by using qRT–PCR. The graph is presented in log2 values and 1.0 represents average of normal subjects (n¼15). [not shown]   The prognostic importance of miR-21 in stage II colon cancer:a population-based study S Kjaer-Frifeldt*,1,2, TF Hansen1, BS Nielsen3, S Joergensen3, J Lindebjerg4, …on behalf of Danish Colorectal Cancer Group 1Department of Oncology, Danish Colorectal Cancer Group South, Vejle Hospital; 2University of Southern Denmark, Odense, Denmark; 3Diagnostic Product Development, Exiqon A/S, Vedbæk 2950, Denmark; 4Department of Clinical Pathology, Vejle Hospital, Vejle, Denmark British Journal of Cancer (2012) 107, 1169–1174   BACKGROUND: Despite several years of research and attempts to develop prognostic models a considerable fraction of stage II colon cancer patients will experience relapse within few years from their operation. The aim of the present study was to investigate the prognostic importance of miRNA-21 (miR-21), quantified by in situ hybridisation, in a unique, large population-based cohort. PATIENTS AND METHODS: The study included 764 patients diagnosed with stage II colon cancer in Denmark in the year 2003. One section from a representative paraffin-embedded tumour tissue specimen from each patient was processed for analysis of miR-21 and quantitatively assessed by image analysis. RESULTS: The miR-21 signal was predominantly observed in fibroblast-like cells located in the stromal compartment of the tumours. We found that patients expressing high levels of miR-21 had significantly inferior recurrence-free cancer-specific survival (RF-CSS): HR¼1.26; 95% CI: 1.15–1.60; Po0.001. In Cox regression analysis, a high level of miR-21 retained its prognostic importance and was found to be significantly related to poor RF-CSS: HR¼1.41; 95% CI: 1.19–1.67; Po0.001. CONCLUSION: The present study showed that increasing miR-21 expression levels were significantly correlated to decreasing RF-CSS. Further investigations of the clinical importance of miR-21 in the selection of high-risk stage II colon cancer patients are merited. British Journal of Cancer (2012) 107, 1169–1174. http://dx.doi.org:/10.1038/bjc.2012.365

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RNA and the Transcription the Genetic Code

Curator: Larry H. Bernstein, MD, FCAP

 

 

This portion of the series is a followup on the series on the replication of the genetic code (DNA).  It may be considered alone, or as a tenth article.  Just as DNA has become far more than it was envisioned 60 years ago, the RNA, which was opened to further investigation by Roger Kornberg, Nobel Laureate, and son of the Nobel Laureate, Arthur Kornberg, who studied DNA polymerase, and with his Nobel Associate, attracted the finest minds in biochemistry and built the best academic department of Biochemistry at Stanford University.  RNA is associated with RNA polymerase as DNA is associated with DNA polymerase.  We have already highlighted the several critical reactions involved in the step-by-step replication of DNA.  The classic model has dictated DNA-RNA-protein.  We shall here look at the amazing view that RNA is heterogeneous, and is involved in living processes in health and disease.

 

 

Transcription (Wikipedia)

Transcription is the first step of gene expression, in which a particular segment of DNA is copied into RNA

Both RNA and DNA are nucleic acids, which use base pairs of nucleotides as a complementary language

  • that can be converted back and forth from DNA to RNA by the action of the correct enzymes.

During transcription, a DNA sequence is read by an RNA polymerase,

As opposed to DNA replication, transcription results in

  1. an RNA complement that includes the nucleotide uracil (U) in all instances
  • where thymine (T) would have occurred in a DNA complement.

Also unlike DNA replication where DNA is synthesized, transcription does not involve an RNA primer to initiate RNA synthesis.

Eukaryotic transcription is the elaborate process that eukaryotic cells use to copy genetic information stored in DNA into units of RNA replica. Gene transcription occurs in both eukaryotic and prokaryotic cells.
A eukaryotic cell has a nucleus that separates the processes of transcription and translation. Eukaryotic transcription occurs

The complexity of the eukaryotic genome necessitates a great variety and complexity of gene expression control.

Transcription can be reduced to the following steps, each moving like a wave along the DNA.

  1. One or more sigma factors initiate transcription of a gene by enabling binding of RNA polymerase to promoter DNA.
  2. RNA polymerase moves a transcription bubble, like the slider of a zipper, which splits the double helix DNA molecule into two strands of unpaired DNA nucleotides, by breaking the hydrogen bonds between complementary DNA nucleotides.
  3. RNA polymerase adds matching RNA nucleotides that are paired with complementary DNA nucleotides of one DNA strand.
  4. RNA sugar-phosphate backbone forms with assistance from RNA polymerase to form an RNA strand.
  5. Hydrogen bonds of the untwisted RNA + DNA helix break, freeing the newly synthesized RNA strand.
  6. If the cell has a nucleus, the RNA may be further processed (with the addition of a 3’UTR poly-A tail and a 5’UTR cap) and exits to the cytoplasm through the nuclear pore complex.

The stretch of DNA transcribed into an RNA molecule is called a transcription unit and encodes at least one gene. If the gene transcribed encodes a protein, the result of transcription is messenger RNA (mRNA), which will then be used to create that protein via the process of translation. Alternatively, the transcribed gene may encode for either non-coding RNA genes (such as microRNA, lincRNA, etc.) or ribosomal RNA (rRNA) or transfer RNA (tRNA), other components of the protein-assembly process, or other ribozymes.[1]

Making RNA replication of gene in eukaryotic cells

Transcription is the process of copying genetic information stored in a DNA strand into a transportable complementary strand of RNA.[1] Eukaryotic transcription takes place in the nucleus of the cell and proceeds in three sequential stages: initiation, elongation, and termination.[1] The transcriptional machinery that catalyzes this complex reaction has at its core three multi-subunit RNA polymerases.[1]

Protein coding genes are transcribed into messenger RNAs (mRNAs) that carry the information from DNA to the site of protein synthesis.[1] Although mRNAs possess great diversity, they are not the most abundant RNA species made in the cell. The so-called non-coding RNAs account for the large majority of the transcriptional output of a cell.[2] These non-coding RNAs perform a variety of important cellular functions.[2]

RNA Polymerase

Eukaryotes have three nuclear RNA polymerases, each with distinct roles and properties

Name Location Product
RNA Polymerase I (Pol I, Pol A) nucleolus larger ribosomal RNA (rRNA) (28S, 18S, 5.8S)
RNA Polymerase II (Pol II, Pol B) nucleus messenger RNA (mRNA), most small nuclear RNAs (snRNAs), small interfering RNA (siRNAs) and micro RNA (miRNA).
RNA Polymerase III (Pol III, Pol C) nucleus (and possibly the nucleolus-nucleoplasm interface) transfer RNA (tRNA), other small RNAs (including the small 5S ribosomal RNA (5s rRNA), snRNA U6, signal recognition particle RNA (SRP RNA) and other stable short RNAs

RNA polymerase I (Pol I)

  • catalyzes the transcription of all rRNA genes except 5S.[3][4]

These rRNA genes are organized into a single transcriptional unit and are transcribed into a continuous transcript. This precursor is then processed into

  • three rRNAs: 18S, 5.8S, and 28S.

The transcription of rRNA genes

  1. takes place in a specialized structure of the nucleus called the nucleolus,[5] where
  2. the transcribed rRNAs are combined with proteins to form ribosomes.[6]

RNA polymerase II (Pol II)

  • is responsible for the transcription of all mRNAs, some snRNAs, siRNAs, and all miRNAs.[3][4]

Many Pol II transcripts exist transiently as single strand precursor RNAs (pre-RNAs) that

  • are further processed to generate mature RNAs.[1]
  1.  precursor mRNAs (pre-mRNAs)are extensively processed
  2. before exiting into the cytoplasm through the nuclear pore for protein translation.

RNA polymerase III (Pol III) transcribes small non-coding RNAs, including tRNAs, 5S rRNA, U6 snRNA, SRP RNA, and other stable short RNAs such as ribonuclease P RNA.[7]

Structure of eukaryotic RNA polymerase II (light blue) in complex with α-amanitin (red), a strong poison found in death cap mushrooms that targets this vital enzyme

RNA Polymerases I, II, and III contain 14, 12, and 17 subunits, respectively.[8] All three eukaryotic polymerases have five core subunits that exhibit

  • homology with the β, β’, αI, αII, and ω subunits of E. coli RNA polymerase.

An identical ω-like subunit (RBP6) is used by all three eukaryotic polymerases,

  • while the same α-like subunits are used by Pol I and III.

The three eukaryotic polymerases share four other common subunits among themselves. The remaining subunits are unique to each RNA polymerase.

The additional subunits found in Pol I and Pol III relative to Pol II, are

  • homologous to Pol II transcription factors.[8]

Crystal structures of RNA polymerases I[9] and II [10] provide an opportunity to understand the interactions among the subunits and the molecular mechanism of eukaryotic transcription in atomic detail.

The carboxyl terminal domain (CTD) of RPB1, the largest subunit of RNA polymerase II,

  • plays an important role in bringing together the machinery necessary for the synthesis and processing of Pol II transcripts.[11]

Long and structurally disordered, the CTD

  • contains multiple repeats of heptapeptide sequence YSPTSPS
  1. that are subject to phosphorylation and
  2. other posttranslational modifications during the transcription cycle.

These modifications and their regulation constitute

  • the operational code for the CTD to control
  1. transcription initiation,
  2. elongation and
  3. termination and
  • to couple transcription and RNA processing.[11]

A DNA transcription unit encoding for a protein contains

  • not only the sequence that will eventually be directly translated into the protein (the coding sequence)
  • but also regulatory sequences that direct and regulate the synthesis of that protein.

The regulatory sequence before (i.e., upstream from) the coding sequence is called

the sequence following (downstream from) the coding sequence is called

Initiation

The initiation of gene transcription in eukaryotes occurs in specific steps.[1]

First, an RNA polymerase along with general transcription factors binds to the promoter region of the gene

The subsequent transition of the complex from the closed state to the open state results in

  • the melting or separation of the two DNA strands and
  • the positioning of the template strand to the active site of the RNA polymerase.

Without the need of a primer

  1. RNA polymerase can initiate the synthesis of a new RNA chain using the template DNA strand
  2. to guide ribonucleotide selection and polymerization chemistry.[1]

However, many of the initiated syntheses are aborted

  • before the transcripts reach a significant length (~10 nucleotides).

During these abortive cycles, the polymerase keeps making and releasing short transcripts

  • until it is able to produce a transcript that surpasses ten nucleotides in length.

Once this threshold is attained, RNA polymerase escapes the promoter and

  • transcription proceeds to the elongation phase.[1]

Eukaryotic promoters and general transcription factors

Pol II-transcribed genes contain a region

  • in the immediate vicinity of the transcription start site (TSS) that binds and positions the preinitiation complex.

This region is called the core promoter because of its essential role in transcription initiation.[12][13] Different classes

  • of sequence elements are found in the promoters. For example,
  • the TATA box is the highly conserved DNA recognition sequence for the TATA box binding protein,
  • TBP, whose binding initiates transcription complex assembly at many genes.

Eukaryotic genes

  • contain regulatory sequences beyond the core promoter.

These cis-acting control elements

  • bind transcriptional activators or repressors to increase or decrease transcription from the core promoter.

Well-characterized regulatory elements include

These regulatory sequences

  • can be spread over a large genomic distance, sometimes located
  • hundreds of kilobases from the core promoters.[1]

General transcription factors are

  • a group of proteins involved in transcription initiation and regulation.[1]

These factors typically have DNA-binding domains that bind

  1. specific sequence elements of the core promoter and
  2. help recruit RNA polymerase to the transcriptional start site.

General transcription factors for RNA polymerase II include TFIID, TFIIA, TFIIB, TFIIF, TFIIE, and TFIIH.[1][14][15]

Transcription has some proofreading mechanisms

  • but they are fewer and less effective than the controls for copying DNA; therefore, transcription has a lower copying fidelity than DNA replication.[2]

As in DNA replication, DNA is read from 3′ end → 5′ end during transcription. Meanwhile,

  • the complementary RNA is created from the 5′ end → 3′ end direction.

This means its 5′ end is created first in base pairing. Although DNA is arranged as two antiparallel strands in a double helix, only

one of the two DNA strands, called the template strand, is used for transcription.

This is because RNA is only single-stranded, as opposed to double-stranded DNA. The other DNA strand (the non-template strand) is called the coding strand,

  • because its sequence is the same as the newly created RNA transcript (except for the substitution of uracil for thymine).

The use of only the 3′ end → 5′ end strand eliminates the need for the Okazaki fragments seen in DNA replication.[1]

In virology, the term may also be used when referring to mRNA synthesis from a RNA molecule (i.e. RNA replication). For instance,

  • the genome of an negative-sense single-stranded RNA (ssRNA -) virus
  1. may serve as a template to transcribe a positive-sense single-stranded RNA (ssRNA +) molecule,
  • since the positive-sense strand contains the information needed
  • to translate the viral proteins for viral replication afterwards.

This process is catalysed by a viral RNA replicase.

Transcription is divided into pre-initiation, initiation, promoter clearance, elongation and termination.

Pre-initiation

In eukaryotes, RNA polymerase, and therefore the initiation of transcription, requires

  • the presence of a core promoter sequence in the DNA.

Promoters are regions of DNA that promote transcription and, in eukaryotes, are found at -30, -75, and -90 base pairs

  • upstream from the transcription start site (abbreviated to TSS).

Core promoters are sequences within the promoter that are essential for transcription initiation. RNA polymerase is able to

The most characterized type of core promoter in eukaryotes is

  • a short DNA sequence known as a TATA box, found 25-30 base pairs upstream from the TSS.

The TATA box, as a core promoter, is the binding site for

  1. a transcription factor known as TATA-binding protein (TBP), which
  2. is itself a subunit of another transcription factor, called Transcription Factor II D (TFIID).

After TFIID binds to the TATA box via the TBP,

  • five more transcription factors and RNA polymerase combine around the TATA box
  • in a series of stages to form a preinitiation complex.

One transcription factor, Transcription factor II H, has two components

  • with helicase activity and so
  • is involved in the separating of opposing strands of double-stranded DNA
  • to form the initial transcription bubble.

However, only a low, or basal, rate of transcription is driven by the preinitiation complex alone. Other proteins known as

  1. activators and repressors,
  2. along with any associated coactivators or corepressors,
  3. are responsible for modulating transcription rate.

Thus, preinitiation complex contains:

  1. Core Promoter Sequence
  2. Transcription Factors
  3. RNA Polymerase
  4. Activators and Repressors.

The transcription preinitiation in archaea is, in essence, homologous to that of eukaryotes, but is much less complex.[3]

The archaeal preinitiation complex assembles at a TATA-box binding site; however,

  • in archaea, this complex is composed of only RNA polymerase II, TBP, and TFB (the archaeal homologue of eukaryotic transcription factor II B (TFIIB)).[4][5]

Initiation

Simple diagram of transcription initiation. RNAP = RNA polymerase

In bacteria, transcription begins with the binding of RNA polymerase to the promoter in DNA. RNA polymerase is a core enzyme consisting of five subunits: 2 α subunits, 1 β subunit, 1 β’ subunit, and 1 ω subunit. At the start of initiation,

  • the core enzyme is associated with a sigma factor that
  • aids in finding the appropriate -35 and -10 base pairs downstream of promoter sequences.[6]

When the sigma factor and RNA polymerase combine, they form a holoenzyme.

Transcription initiation is more complex in eukaryotes. Eukaryotic RNA polymerase

  • does not directly recognize the core promoter sequences. Instead,
  • a collection of proteins called transcription factors mediate
  • the binding of RNA polymerase and the initiation of transcription.

Only after certain transcription factors are attached to the promoter does the RNA polymerase bind to it. The completed assembly of

  • transcription factors and RNA polymerase bind to the promoter,
  • forming a transcription initiation complex.

Transcription in the archaea domain is similar to transcription in eukaryotes.[7]

Promoter clearance

After the first bond is synthesized, the RNA polymerase must clear the promoter. During this time

  • there is a tendency to release the RNA transcript and produce truncated transcripts. This is called
  • abortive initiation and is common for both eukaryotes and prokaryotes.[8]

In prokaryotes, abortive initiation continues to occur

  • until an RNA product of a threshold length of approximately 10 nucleotides is synthesized,
  • at which point promoter escape occurs and a transcription elongation complex is formed.

The σ factor is released according to a stochastic model.[9] Mechanistically, promoter escape occurs through a scrunching mechanism, where

  • the energy built up by DNA scrunching provides the energy needed to break interactions between RNA polymerase holoenzyme and the promoter.[10]

In eukaryotes, after several rounds of 10nt abortive initiation,

  • promoter clearance coincides with the TFIIH’s phosphorylation of serine 5 on the carboxy terminal domain of RNAP II,
  • leading to the recruitment of capping enzyme (CE).[11][12]

The exact mechanism of how CE induces promoter clearance in eukaryotes is not yet known.

Elongation

Simple diagram of transcription elongation

One strand of the DNA, the template strand (or noncoding strand), is used as a template for RNA synthesis. As transcription proceeds,

  • RNA polymerase traverses the template strand and uses base pairing complementarity with the DNA template to create an RNA copy.

Although RNA polymerase traverses the template strand from 3′ → 5′, the coding (non-template) strand and newly formed RNA can also be used as reference points,

  • so transcription can be described as occurring 5′ → 3′.

This produces an RNA molecule from 5′ → 3′, an exact copy of the coding strand (except that thymines are replaced with uracils, and the nucleotides are composed of a ribose (5-carbon) sugar where DNA has deoxyribose (one fewer oxygen atom) in its sugar-phosphate backbone).

mRNA transcription can involve multiple RNA polymerases on a single DNA template and multiple rounds of transcription (amplification of particular mRNA),

  • so many mRNA molecules can be rapidly produced from a single copy of a gene.

Elongation also involves a proofreading mechanism

  • that can replace incorrectly incorporated bases.

In eukaryotes,

  • short pauses during transcription allow appropriate RNA editing factors to bind.

These pauses may be intrinsic to the RNA polymerase or due to chromatin structure.

Termination

Main article: Terminator (genetics)

Bacteria use two different strategies for transcription termination –

  1. Rho-independent termination and
  2. Rho-dependent termination.

In Rho-independent transcription termination, also called intrinsic termination,

RNA transcription stops when the newly synthesized RNA molecule forms

  1. a G-C-rich hairpin loop followed by a run of Us. When the hairpin forms,
  2. the mechanical stress breaks the weak rU-dA bonds,
  3. now filling the DNA-RNA hybrid. This pulls the poly-U transcript out of the active site of the RNA polymerase,
  4. in effect, terminating transcription.

In the “Rho-dependent” type of termination, a protein factor called “Rho

  • destabilizes the interaction between the template and the mRNA, thus
  • releasing the newly synthesized mRNA from the elongation complex.[13]

Transcription termination in eukaryotes is less understood but involves cleavage of the new transcript followed by template-independent addition of As at its new 3′ end, in a process called polyadenylation.[14]

Inhibitors

Transcription inhibitors can be used as antibiotics against, for example, pathogenic bacteria (antibacterials) and fungi (antifungals). An example of such an antibacterial is

8-Hydroxyquinoline is an antifungal transcription inhibitor.[15] The effects of histone methylation may also work to inhibit the action of transcription.

Transcription factories

Active transcription units are clustered in the nucleus, in discrete sites called transcription factories or euchromatin. Such sites can be visualized by allowing engaged polymerases to extend their transcripts in tagged precursors (Br-UTP or Br-U) and immuno-labeling the tagged nascent RNA. Transcription factories can also be localized using fluorescence in situ hybridization or marked by antibodies directed against polymerases. There are ~10,000 factories in the nucleoplasm of a HeLa cell, among which are ~8,000 polymerase II factories and ~2,000 polymerase III factories. Each polymerase II factory contains ~8 polymerases. As most active transcription units are associated with only one polymerase, each factory usually contains ~8 different transcription units. These units might be associated through promoters and/or enhancers, with loops forming a ‘cloud’ around the factor.[16]

History

A molecule that allows the genetic material to be realized as a protein was first hypothesized by François Jacob and Jacques Monod. Severo Ochoa won a Nobel Prize in Physiology or Medicine in 1959 for developing a process for synthesizing RNA in vitro with polynucleotide phosphorylase, which was useful for cracking the genetic code. RNA synthesis by RNA polymerase was established in vitro by several laboratories by 1965; however, the RNA synthesized by these enzymes had properties that suggested the existence of an additional factor needed to terminate transcription correctly.

In 1972, Walter Fiers became the first person to actually prove the existence of the terminating enzyme.

Roger D. Kornberg won the 2006 Nobel Prize in Chemistry “for his studies of the molecular basis of eukaryotic transcription”.

Reverse transcription

Some viruses (such as HIV, the cause of AIDS), have the ability to transcribe RNA into DNA. HIV has an RNA genome that is reverse transcribed into DNA. The resulting DNA can be merged with the DNA genome of the host cell. The main enzyme responsible for synthesis of DNA from an RNA template is called reverse transcriptase.

Some eukaryotic cells contain an enzyme with reverse transcription activity called telomerase. Telomerase is a reverse transcriptase that lengthens the ends of linear chromosomes. Telomerase carries an RNA template from which it synthesizes a repeating sequence of DNA, or “junk” DNA. This repeated sequence of DNA is called a telomere and can be thought of as a “cap” for a chromosome. It is important because every time a linear chromosome is duplicated, it is shortened. With this “junk” DNA or “cap” at the ends of chromosomes, the shortening eliminates some of the non-essential, repeated sequence rather than the protein-encoding DNA sequence, that is farther away from the chromosome end.

Telomerase is often activated in cancer cells to enable cancer cells to duplicate their genomes indefinitely without losing important protein-coding DNA sequence. Activation of telomerase could be part of the process that allows cancer cells to become immortal. The immortalizing factor of cancer via telomere lengthening due to telomerase has been proven to occur in 90% of all carcinogenic tumors in vivo with the remaining 10% using an alternative telomere maintenance route called ALT or Alternative Lengthening of Telomeres.[20]

RNA-Seq Dissects the Transcriptome

Transcript Targeting  Kathy Liszewski
GEN    Jul 1, 2014 (Vol. 34, No. 13)

With the rapid rise of next-generation sequencing (NGS), one of its technologies, RNA sequencing (RNA-Seq), has taken center stage for analyzing whole transcriptomes.

Although RNA-Seq is still the new kid on the block,

  • this technology has the potential to revolutionize transcriptomics,
  • revealing the architecture of gene expression in unprecedented detail.

RNA-Seq applications are proliferating and include

  • the elucidation of disease processes,
  • targeted drug development, and
  • personalized medicine.

To orient researchers who are unfamiliar with the differences between  RNA-Seq platforms, Kelli Bramlett, R&D scientist, Life Technologies, poses two key questions:

1. Are you interested in pure discovery, in a nonguided fashion, of every RNA species present in your test samples?

2. Are you mainly focused on measuring expression levels of well-annotated coding RNA transcripts?

You might have a set of genes crucial to

 

  • identifying a disease state, or
  • profiling the stage of a specific type of cancer, or
  • monitoring development in your experimental system,

You then would want to employ a system that

  • “allows you to quickly and efficiently focus on just your genes of interest and screen through many different samples in a short amount of time.”

RNA-Seq allows for true discovery but

  • “requires sequencing depth and
  • requires significant additional time for analysis
  • If a focused panel targeting specific RNAs will better meet your needs, this can be accomplished on systems with
  • much faster turnaround time and less sequencing depth.”( according to Dr. Bramlett)

Enhancing Sensitivity

RNA-Seq has advanced our ability to characterize transcriptomes at high resolution, and the laboratory and data analysis techniques used for this NGS application continue to mature, notes John Tan, Ph.D., senior scientist, Roche NimbleGen. “High sequencing costs combined with the omnipresence of pervasive, abundant transcripts decrease our power to study rare transcripts, decrease throughput, and limit the routine use of this technology.”

For example, notes Dr. Tan, a small number of

  • highly expressed housekeeping genes can be responsible for a large fraction of total sequence reads in an experiment, thus
  • increasing the amount of sequencing required to characterize less abundant transcripts of interest.

To improve the cost-effectiveness, throughput, and sensitivity of RNA-Seq, Dr. Tan and colleagues are developing methods to perform targeted RNA-Seq.
“Targeted enrichment of transcripts of interest

  • circumvents the need to perform separate rRNA depletion or polyA enrichment steps on input RNA,” explains Dr. Tan.

“By targeting their sequencing, researchers can avoid wasting resources on

  • housekeeping transcripts and focus instead on genes or genomic regions of interest.”

Targeted RNA-Seq can allow deeper sequence coverage, increased sensitivity for low-abundance transcripts, less total sequencing per sample, and more samples processed per sequencing instrument run. “Significantly, we observe that the enrichment step also preserves quantitative information very well,” adds Dr. Tan. “These advances will facilitate a more routine use of RNA-Seq technology.”

  • Sample Integrity Issues

“Formalin-fixed, paraffin-embedded (FFPE) patient tissue archives and the clinical data associated with them may provide only limited amounts of sample that may also be degraded,” comments Gary Schroth, Ph.D., distinguished scientist, Illumina. Dr. Schroth says that most labs currently gauge RNA integrity via the RIN (RNA integrity number). but the RIN number from FFPE samples is not a sensitive measure of RNA quality or a good predictor for library preparation. A better predictor is RNA fragment size. We developed the DV200 metric, the percentage of RNA fragments greater than 200 nucleotides, a size needed for accurate construction of libraries.”

Illumina offers its TruSeq® RNA Access Library Preparation Kit especially for FFPE samples. This kit, when used with the DV200 metric, provides cleaner and more accurate library preparation. This new approach allows researchers to start with five-to tenfold less material when making libraries from FFPE samples.

  • Strand Specificity

Most NGS requires initial construction of libraries that may not provide the specificity desired even when prepared from mRNA. “Traditional RNA-Seq library preparation loses the strandedness of transcripts—information that is critical in understanding cellular transcription,” says Jungsoo Park, senior marketing and sales manager, Lexogen.

According to Park, Lexogen tackled this problem

  • by developing a method to generate libraries with greater than 99.9% strand specificity with a simplified process that takes 4.5 hours to complete.

Lexogen’s SENSE mRNA-Seq library kit initially isolates mRNA via

  • the poly A tail and utilizes random hybridization of the transcripts that
  • are bound to the magnetic beads without transcript fragmentation.

“This is a revolutionary method, which keeps high strandedness of the transcripts,” asserts Park.

One of the novel aspects of this approach is the use of starter/stopper heterodimers containing platform-specific linkers that hybridize to the mRNA.
“The starters serve as primers for reverse transcription, which then

  • terminates once the stopper from the next heterodimer is reached,

“At this point, the newly synthesized cDNA and the stopper are ligated while still bound to the RNA template.” According to Park,

  • there is no need for a time-consuming fragmentation step, and library size is determined simply by the protocol itself.

For researchers only intending to see the expression levels, sequencing of the entire mRNA transcript will require subsequent bioinformatics processes such as RPKM, a measure of relative molar RNA concentration.

  RNA-Seq Libraries

NuGEN Technologies offers its Ovation Human Blood RNA-Seq Library System as an end-to-end solution for strand-specific RNA-Seq library construction. NuGEN’s Insert Dependent Adaptor Cleavage (InDA-C) technology can provide targeted depletion of unwanted high-abundance transcripts.
  • Cells possess many thousands of transcripts.
  • uninformative transcript species that can compromise data quality and the cost-effectiveness of sequencing
  • NuGEN Technologies has developed a method for targeted depletion of unwanted transcripts following construction of RNA-Seq libraries. (Insert Dependent Adaptor Cleavage (InDA-C),

employs customized primers that target specific transcripts, such as ribosomal and globin RNAs, to exclude from final RNA-Seq libraries. (hemoglobin RNA derived from blood accounts for at least 60% of transcripts)  “By depleting these two transcript classes, InDA-C quadruples informative reads. and it avoids off-target mRNA cross-hybridization events that can potentially introduce bias. The species and transcript specificity of the workflow relies on the design of InDA-C primers, which can be constructed

  • to target virtually any class of unwanted transcripts for targeted depletion,”  according to Dr. Kain.

NuGEN has developed Single Primer Enrichment Technology, which can be used to prepare targeted NGS libraries from both gDNA or cDNA,

  •  used to identify gene fusion products and alternative splicing patterns from enriched cDNA libraries.

platforms automate the RNA sequencing sample preparation process [Beckman Coulter]

Preparation of libraries for RNA-Seq entails an intensive workflow.  according to Alisa Jackson, senior marketing manager, Genomic Solutions, Beckman Coulter, automation provides four key advantages:

  • Creation of high-quality mRNA libraries. Initial steps in this process include depleting samples of ribosomal RNA. Although it has the greatest abundance, rRNA gives the least amount of information.
  • “We’ve automated this process on our Biomek instruments using popular sample preparation kits from Illumina and New England Biolabs,” notes Jackson. “Accurate pipetting and thorough mixing are critical for this process. The Biomek liquid handler’s 96-channel pipetting head is used in combination with an on-deck orbital shaker to vigorously mix samples. Results show this ‘mix and shake’ approach works well.”
  • Limited exposure to RNAses from human contact. Every scientist’s nemesis when working with RNA is the universal presence of RNA-degrading RNAses. To help overcome this problem, says Jackson, “Biomek consumables such as pipette tips are DNase and RNase-free.”
  • Reduced exposure to toxic chemicals. “An instrument dispenses all reagents involved in the various steps of process.”
  • Enhanced reproducibility. “This is still a very expensive process,” asserts Jackson. “Obtaining accurate results the first time prevents costly repetitions. For this reason, we provide Biomek methods for many NGS library preparation kits. By fully testing these methods with real-life samples, we ensure reliable and repeatable creation of sequence-ready RNA libraries, whether stranded or nonstranded, mRNA or total RNA.”
  • What’s Next?

RNA-seq data analysis

RNA-seq data analysis for target identification. [Boehringer Ingelheim]

  •  “With RNA-Seq, we are closing in on personalized medicine,” suggests Qichao Zhu, Ph.D., principal scientist, Boehringer Ingelheim. “This technology allows more exact identification of patient subgroups. Instead of ‘one drug fits all,’ we can now begin to more appropriately define which drugs will work in which patients. Diseases such as cancer and cystic fibrosis as well as neurodegenerative illnesses have many patient subcategories. Future pharmaceutical drug discovery will be better able to develop targeted therapeutics with the help of RNA-Seq.
  • ”There are still many challenges in the field, however. “A critical aspect is accuracy. Given the large scale set of RNA-Seq, even 99.99% accuracy is not good enough for diagnostics,” insists Dr. Zhu. “Further, as we move forward, we will need to improve many aspects of the technology including
  • disease tissue sample isolation,
  • library construction methodologies, as well as
  • analysis of massive datasets.

“In the future, a patient will go into the doctor’s office and have a whole transcriptome profile test performed.“When PCR technology was discovered, no one knew just how powerful it would become or how many applications it would generate. Now, it is used everywhere. NGS technology and RNA-Seq have a similar potential. ”

 

Gene Paces microRNAs to Set Developmental Rhythms

Kevin Mayer   Jul 18, 2014   GEN News Highlights

http:/www.genengnews.com/gen-news-highlights/gene-paces-micrornas-to-set-developmental-rhythms/81250124/

Using C. elegans as a model researchers identified LIN-42, a gene that is found in animals across the evolutionary tree, as a potent regulator of numerous developmental processes. [C. Hammell, Cold Spring Harbor Laboratory]

  • Although the how of a gene’s function is important, the when, too, is crucial. The ebb and flow ofgene expression can influence a cell’s fate during development, the maturation of entire organisms, and even the evolution of species—helping to explain how species with very similar gene content can differ so dramatically.

Nature’s developmental clockwork

  • depends on the activation or repression of a specific and unique complement of genes. And these genes, in turn,
  • are regulated by microRNA molecules. And, finally,
  • the microRNAs are also subject to regulation.
  •  one must then study the regulators of the regulators of the regulators.

Little is known of the ultimate regulators—the elements that determine the activities of microRNAs. These elements, however, are presumably as subtle as they are powerful—

  1. subtle because microRNAs defined temporal gene expression and cell lineage patterns in a dosage-dependent manner;
  2. powerful because a single microRNA gene can control hundreds of other genes at once.
  3. as always, timing is everything: If a microRNA turns off genes too early or too late, the organism that depends on them will likely suffer severe developmental defects.

To undertake a search for genes that control developmental timing through microRNAs, a team of researchers at Cold Spring Harbor Laboratory relied on a tried-and-true model of animal development, Caenorhabditis elegans. These worms have a fixed number of cells, and each cell division is precisely timed.  “It enables us to understand

  • exactly how a mutation affects development,
  • whether maturation is precocious or delayed,
  • by directly observing defects in the timing of gene expression.” (said team leader Christopher Hammell, Ph.D.)

The researchers described their work in an article entitled, “LIN-42, the Caenorhabditis elegans PERIOD  homolog, Negatively Regulates MicroRNA Transcription,” which appeared July 17 in PLoS Genetics.

the goal to unveil factors that regulate the expression of microRNAs that control developmental timing –

  • they  identified LIN-42, the C. elegans homolog of the human and Drosophila period gene implicated in circadian gene regulation, as a negative regulator of microRNA expression

“By analyzing the transcriptional expression patterns of representative microRNAs, we found that the transcription of many microRNAs is normally highly dynamic and coupled aspects of post-embryonic growth and behavior.”

“LIN-42 shares a significant amount of similarity to the genes that control circadian rhythms in organisms such as mice and humans,” explained Roberto Perales, Ph.D., one of the lead authors of the study. “These are genes that control the timing of cellular processes on a daily basis for you and me. In the worm, these same genes and mechanisms control development, growth, and behavior. This system will provide us with leverage to understand how all of these things are coordinated.”

  1.  LIN-42 controls the repression of numerous genes in addition to microRNAs.
  2.  levels of the protein encoded by LIN-42 tend to
  • oscillate over the course of development and form a part of a developmental clock.

“LIN-42 provides the organism with a kind of cadence or temporal memory, so that

  1. it can remember that it has completed one developmental step before it moves on to the next,” emphasized Dr. Hammell. “This way, LIN-42 coordinates optimal levels of the genes required throughout development.”

 

Intracellular RNA-Seq

This literature review highlights a study led by George Church describing FISSEQ, or fluorescent in situ RNA sequencing.

Anton Simeonov, Ph.D.   Jul 25, 2014

http://www.genengnews.com/insight-and-intelligence/intracellular-rna-seq/77900207/

 

 FISSEQ appears to be sensitive to genes associated with cell type and function, and this in turn could be used for cell typing. [© Alila Medicinal Media – Fotolia.com]

  • Methods such as fluorescence in situ hybridization (FISH) allow gene expression to be observed at the tissue and cellular level; however, only a limited number of genes can be monitored in this manner, making transcriptome-wide studies impractical. George Church’s group* is presenting the further development of their original approach called
  • fluorescent in situ sequencing (FISSEQ) to incorporate a spatially structured sequencing library and an imaging method capable of resolving the amplicons (see Figure 1).

In fixed cells, RNA was reverse transcribed with tagged random hexamers to produce cDNA amplicons.

  1. Aminoallyl deoxyuridine 5-triphosphate (dUTP) was incorporated during reverse transcription and
  2. after the cDNA fragments were circularized before rolling circle amplification (RCA),
  3. an amine-reactive linker was used to cross-link the RCA amplicons containing aminoallyl dUTP.

The team generated RNA sequencing libraries in different cell types, tissue sections, and whole-mount embryos for three-dimensional (3D) visualization that spanned multiple resolution scales (see Figure 1).

Click Image To Enlarge +
Figure 1
  • Figure 1. Construction of 3D RNA-seq libraries in situ. After RT using random hexamers with an adapter sequence in fixed cells, the cDNA is amplified and cross-linked in situ. (A) A fluorescent probe is hybridized to the adapter sequence and imaged by confocal microscopy in human iPS cells (hiPSCs; scale bar: 10 μm) and fibroblasts (scale bar: 25 μm). (B) FISSEQ can localize the total RNA transcriptome in mouse embryo and adult brain sections (scale bar: 1 mm) and whole-mount Drosophila embryos (scale bar: 5 μm), although we have not sequenced these samples. (C) 3D rendering of gene-specific or adapter-specific probes hybridized to cDNA amplicons. 3D, three-dimensional; RT, reverse transcription; FISSEQ, fluorescent in situ sequencing; FISH, fluorescence in situ hybridization.
  • In a proof-of-concept experiment (see Figure 2) the authors sequenced primary fibroblasts in situ after simulating a response to injury, which yielded 156,762 reads, mapped to 8,102 annotated genes. When the 100 highest ranked genes were clustered, cells kept in fetal bovine serum medium were enriched for fibroblast-associated gene hits, while the rapidly dividing cells in epidermal growth factor medium were less fibroblast-like, reaffirming that the FISSEQ platform output reflects the change in transcription status as a function of the cellular environment and stress factors.

 

  • Figure 2. Overcoming resolution limitations and enhancing the signal-to-noise ratio. Ligation of fluorescent oligonucleotides occurs when the sequencing primer ends are perfectly complementary to the template. Extending sequencing primers by one or more bases, one can randomly sample amplicons at 1/4th, 1/16th, and 1/256th of the original density in fibroblasts (scale bar: 5 μm). N, nucleus; C, cytoplasm.
  • The authors further noted that FISSEQ appears to be sensitive to genes associated with cell type and function, and this in turn could be used for cell typing. It was also speculated that FISSEQ might allow for a combined transcriptome profiling and mutation detection in situ.
  • *Abstract from Science 2014, Vol. 343:1360–1363

Understanding the spatial organization of gene expression with single-nucleotide resolution requires

  • localizing the sequences of expressed RNA transcripts within a cell in situ.

Here, we describe fluorescent in situ RNA sequencing (FISSEQ), in which stably cross-linked complementary DNA (cDNA) amplicons are sequenced within a biological sample.

  1. Using 30-base reads from 8102 genes in situ, we examined RNA expression and localization in human primary fibroblasts with a simulated wound-healing assay.
  2. FISSEQ is compatible with tissue sections and whole-mount embryos and
  3. reduces the limitations of optical resolution and noisy signals on single-molecule detection.

Our platform enables massively parallel detection of genetic elements, including

  • gene transcripts and molecular barcodes, and can be used
  • to investigate cellular phenotype, gene regulation, and environment in situ.

Anton Simeonov, Ph.D., works at the NIH.

ASSAY & Drug Development Technologies, is published by Mary Ann Liebert, Inc.
GEN presents here one article that was analyzed in the “Literature Search and Review” column, a paper published in Science titled “Highly multiplexed subcellular RNA sequencing in situ.” Authors of the paper are Lee JH, Daugharthy ER, Scheiman J, Kalhor R, Yang JL, Ferrante TC, Terry R, … and Church GM.

 

Completely ablate microRNA genes on the genomic level

  • miR-KOs are transcription activator-like effector (TALE) nucleases that
  • precisely edit specific miRNAs in mammalian cells.
  • SBI designed miR-TALE-nucleases to cleave within the miRNA seed region.

In the absence of HR donor vectors, the cellular machinery repairs such breaks via

  • non-homologous end joining (NHEJ).

This is an error-prone system that typically generates small deletions or insertions (indels) at or near the site of cleavage. Since the seed region (defined as bases 2-8 of the microRNA) directs miRNA binding to its target DNA, indels within the seed region completely abolish miRNA function.

 

Design of miR-KO TALE Nucleases

The miR-KOs are designed to disrupt the miRNA seed region. Pairing miR-KOs with an HR donor

  • replaces the entire miRNA hairpin structure with an insulated selectable marker cassette.

Sample data for miR-KO 21 Knockout

Selection for HR events by puromycin or by FACS-based sorting for RFP can enrich for properly knocked-out alleles. The enriched cell populations are then

  • genotyped to determine whether the knockout is at a single allele or bi-allelic (as in the case of hsa-miR-21).

Genotyping for HR events is performed via junction PCR of genomic DNA-insert junctions at 5′ and/or 3′ ends of an HR site. PCR primer pairs are designed with one of the primer sequences corresponding to the targeted genomic DNA region and the other corresponding to the HR vector.

Primer design strategy for HR-directed genotyping

Genomic DNA PCR was used to to detect HR integration in one or both alleles of hsa-miR-21. Individual cellular clones that display one HR event typically display mutated seed regions in the other allele. miR-KOs, when combined with HR donor vectors have been shown to be highly efficient in generating double miRNA knockouts. For example, a miR-KO strategy against human miR-21 in HEK293T cells resulted in 30 puromycin-resistant lines out of 96 single cell-derived clones. Subsequent PCR-based genotyping of 23 successful PCR amplifications revealed that ~96% (22/23) were mono-allelic (i.e. one allele with HR and other with NHEJ or WT) and ~4% (1/23) were bi-allelic (e.g. both alleles undergone HR) for HR-induced miR-21 deletion. Furthermore, sequencing of PCR products spanning the targeted seed region of miR-21 revealed that 91% (10/11) were NHEJ-modified.

Taken together, these results show a 87% bi-allelic modification rate (20 out of 23 clones)

  • when the miR-KOs are combined with an HR donor vector.

Validation and phenotypic analysis of miR-KO of hsa-miR-21

To confirm complete loss of miRNA-21 expression, we quantified miR-21 expression in three independent miR-21 double knockouts by qPCR.

  1. Clone #1 and #7 carry one deletion of the miR-21 hairpin structure (via HR) and
  2. one indel within the seed region (via NHEJ);
  3. clone #5 carries bi-allelic deletions of the hairpin structure (bi-allelic HR).

We found complete abolishment of miR-21 expression in all three cell lines.

Growth phenotype uncovered in miR-21 KO cell lines

MicroRNA-21 has been characterized as a cell-promoting OncomiR. The abalation of the genomic hsa-miR-21 in human cells resulted in reduced proliferation in all three miR-21 knockout lines tested. Growth curves were plotted for the parental HEK293 cells as well as the three independent knockout lines.

Increase the ease and efficiency of obtaining KOs with matched HR vectors

While the use of miR-KOs alone can successfully abolish miRNA function,

  • screening for bi-allelic indels can be laborious.

Due to the small changes seen with indels, many clonal lines have to be established through limited dilution or single-cell sorting techniques, and

  • subsequently genomic DNA is PCR-amplified,
  • cloned into vectors and
  • subjected to genotyping by Sanger sequencing.

Since many cells will only have either zero or one alleles modified, tremendous work is often required to obtain bi-allelic indels.

To facilitate the screening process,

  • one may combine miRNA-specific TALE-nucleases with HR donor vectors, which enables positive selection and convenient screening of targeted cells.

Because NHEJ occurs more frequently than HR donor integration,

  • the majority of cells that undergo HR integration on one allele carry an indel in the miRNA seed region of the second allele.

This strategy has been shown to be highly efficient in generating bi-allelic miRNA knockouts. A positive selection strategy reveals puromycin-resistant and RFP-positive single-cell derived colonies, majority of which are double knockouts (i.e. HR event on one allele and indel in seed region of second allele).

Shown above is an overview of miR-KO strategies with miR-KOs alone and in combination with an HR donor vector. The HR donor vector enables positive selection, which allows for simple and efficient generation of cells harboring double knockouts.
Gene Described as Critical to Stem Cell Development

GEN News Highlights  Jul 18, 2014
http://www.genengnews.com/gen-news-highlights/gene-described-as-critical-to-stem-cell-development/81250121/

  • Scientists at Michigan State University say they have found that a gene known as ASF1A could be critical to the development of stem cells. ASF1A is at least one of the genes responsible for the mechanism of cellular reprogramming, a phenomenon that can turn one cell type into another, which is key to the making of stem cells, according to the researchers.

In a paper (“Histone chaperone ASF1A is required for maintenance of pluripotency and cellular reprogramming”) published in Science, the MSU team describes

  • how they analyzed more than 5,000 genes from a human oocyte before determining that
  • the ASF1A, along with another gene known as OCT4 and a helper soluble molecule, were the ones responsible for the reprogramming.

In 2006, an MSU team identified the thousands of genes that reside in the oocyte. In 2007, a team of Japanese researchers found that

  • by introducing four other genes into cells, induced pluripotent stem cells (iPSCs) could be created without the use of a human egg.

The researchers say that the genes ASF1A and OCT4 work in tandem with a ligand,

  • a hormone-like substance that also is produced in the oocyte called GDF9, to facilitate the reprogramming process.
  • overexpression of just ASF1A and OCT4 in hADFs exposed to the oocyte-specific paracrine growth factor GDF9 can reprogram hADFs into pluripotent cells

The report underscores the importance of studying the unfertilized MII [metaphase II human] as a means

  • to understand the molecular pathways governing somatic cell reprogramming.

“We believe that ASF1A and GDF9 are two players among many others that remain to be discovered, which are part of the cellular-reprogramming process,” noted Dr. Cibelli. “We hope that in the near future, with what we have learned here, we will be able to test new hypotheses that will reveal more secrets the oocyte is hiding from us. In turn, we will be able to develop new and safer cell therapy strategies.”

  • Although the how of a gene’s function is important, the when, too, is crucial. The ebb and flow of gene expression can influence a cell’s fate during development, the maturation of entire organisms, and even the evolution of species—helping to explain how species with very similar gene content can differ so dramatically.

 

Identification and Insilico Analysis of Retinoblastoma Serum microRNA Profile and Gene Targets Towards Prediction of Novel Serum Biomarkers

M Beta, A Venkatesan, M Vasudevan, U Vetrivel, et al. Identification and Insilico Analysis of Retinoblastoma Serum microRNA Profile and Gene Targets Towards Prediction of Novel Serum Biomarkers.

Bioinformatics and Biology Insights 2013:7 21–34.   http://dx.doi.org:/10.4137/BBI.S10501

This study was undertaken

  • to identify the differentially expressed miRNAs in the serum of children with RB in comparison with the normal age matched serum,
  • to analyze its concurrence with the existing RB tumor miRNA profile,
  • to identify its novel gene targets specific to RB, and
  • to study the expression of a few of the identified oncogenic miRNAs in the advanced stage primary RB patient’s serum sample.

MiRNA profiling performed on 14 pooled serum from chil­dren with advanced RB and 14 normal age matched serum samples

  • 21 miRNAs found to be upregulated (fold change > 2.0, P < 0.05) and
  • 24 downregulated (fold change > 2.0, P < 0.05).

Intersection of 59 significantly deregulated miRNAs identified from RB tumor profiles with that of miRNAs detected in serum profile revealed that

  • 33 miRNAs had followed a similar deregulation pattern in RB serum.

Later we validated a few of the miRNAs (miRNA 17-92) identified by microarray in the RB patient serum samples (n = 20) by using qRT-PCR.

Expression of the oncogenic miRNAs, miR-17, miR-18a, and miR-20a by qRT-PCR was significant in the serum samples

  • exploring the potential of serum miRNAs identification as noninvasive diagnosis.

Moreover, from miRNA gene target prediction, key regulatory genes of

  • cell proliferation,
  • apoptosis, and
  • positive and negative regulatory networks

involved in RB progression were identified in the gene expression profile of RB tumors.
Therefore, these identified miRNAs and their corresponding target genes could give insights on

  • potential biomarkers and key events involved in the RB pathway.

 

Prediction of Breast Cancer Metastasis by Gene Expression Profiles: A Comparison of Metagenes and Single Genes

(M Burton, M Thomassen, Q Tan, and TA Kruse.) Cancer Informatics 2012:11 193–217

http://dx.doi.org:/10.4137/CIN.S10375

The popularity of a large number of microarray applications has in cancer research led to the development of predictive or prognostic gene expression profiles. However, the diversity of microarray platforms has made the full validation of such profiles and their related gene lists across studies difficult and, at the level of classification accuracies, rarely validated in multiple independent datasets. Frequently, while the individual genes between such lists may not match, genes with same function are included across such gene lists. Development of such lists does not take into account the fact that

  • genes can be grouped together as metagenes (MGs) based on common characteristics such as pathways, regulation, or genomic location.

In this study we compared the performance of either metagene- or single gene-based feature sets and classifiers using random forest and two support vector machines for classifier building. The performance

  • within the same dataset,
  • feature set validation perfor­mance, and
  • validation performance of entire classifiers in strictly independent datasets

were assessed by

  • 10 times repeated 10-fold cross validation,
  • leave-one-out cross validation, and
  • one-fold validation, respectively.

To test the significance of the performance difference between MG- and SG-features/classifiers, we used a repeated down-sampled binomial test approach.

MG- and SG-feature sets are transferable and perform well for training and testing prediction of metastasis outcome

  • in strictly independent data sets, both
  • between different and
  • within similar microarray platforms, while
  • classifiers had a poorer performance when validated in strictly independent datasets.

The study showed that MG- and SG-feature sets perform equally well in classifying indepen­dent data. Furthermore, SG-classifiers significantly outperformed MG-classifier

  • when validation is conducted between datasets using similar platforms, while
  • no significant performance difference was found when validation was performed between different platforms.

Prediction of metastasis outcome in lymph node–negative patients by MG- and SG-classifiers showed that SG-classifiers performed significantly better than MG-classifiers when validated in independent data based on the same microarray platform as used for developing the classifier. However, the MG- and SG-classifiers had similar performance when conducting classifier validation in independent data based on a different microarray platform. The latter was also true when only validating sets of MG- and SG-features in independent datasets, both between and within similar and different platforms.

 

Molecular basis of transcription pausing

Jeffrey W. Roberts

Science 13 June 2014;  344(6189), pp. 1226-1227   http://dx.doi.org:/10.1126/science.1255712

+Author Affiliations

  1. Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA.
  2. E-mail: jwr7@cornell.edu

During RNA synthesis, RNA polymerase moves erratically along DNA,

  1. frequently resting as it produces an RNA copy of the DNA sequence.

Such pausing helps coordinate the appearance of a transcript with its utilization by cellular processes; to this end,

  • the movement of RNA polymerase is modulated by mechanisms that determine its rate. For example,
  1. pausing is critical to regulatory activities of the enzyme such as the termination of transcription. It is also essential
  2. during early modifications of eukaryotic RNA polymerase II that activate the enzyme for elongation.

Two reports analyzing transcription pausing on a global scale in Escherichia coli, by Larson et al. (1) and by Vvedenskaya et al. (2) on page 1285 of this issue, suggest new functions of pausing and reveal important aspects of its molecular basis.

The studies of Larson et al. and Vvedenskaya et al. follow decades of analysis of bacterial transcription that has illuminated

  • the molecular basis of polymerase pausing events that serve critical regulatory functions.

A transcription pause specified by the DNA sequence

  • synchronizes the translation of RNA into protein with
  • the transcription of leader regions of operons (groups of genes transcribed together) for amino acid biosynthesis;
  • this coordination controls amino acid synthesis in response to amino acid availability (3).

A protein-induced pause occurs when the E. coli initiation factor σ70 restrains RNA polymerase

  • by binding a second occurrence of the “−10” promoter element.

This paused polymerase provides a structure for

  1. engaging a transcription antiterminator (the bacteriophage λ Q protein) (4) that,
  2. inhibits transcription pauses, including those essential for transcription termination.

Knowledge about the interactions between nucleic acids and RNA polymerase that induce pausing

  • comes partly from studies on the E. coli histidine biosynthesis operon.

RNA polymerase pauses at the leader region of this cluster of genes (the “his pause”),

  • allowing an essential RNA hairpin structure to form just upstream of the RNA-DNA hybrid
  • where RNA synthesis is templated in the polymerase’s catalytic cleft.

Importantly, however, other sequence elements are required to induce and stabilize the his pause—particularly

  • the nucleotide at the newly formed, growing end of the RNA (pausing is favored by pyrimidines rather than purines) (5), and
  • at the incoming nucleotide position [pausing is favored particularly by guanine (G)] (6), as well as surrounding elements.

Biochemical and structural analyses have identified an endpoint of the pausing process called the “elemental pause” in which

  • the catalytic structure in the active site is distorted, preventing further nucleotide addition (7).

The elemental paused state also involves distinct conformational changes in the polymerase

  1. that may favor transcription termination and
  2. allow the his and related pauses to be stabilized by RNA hairpins (8).

ILLUSTRATION: V. ALTOUNIAN/SCIENCE

Single-molecule analysis of transcribing RNA polymerase, at nearly single-nucleotide resolution, identified many specific pause sites in the E. coli genome (9). Pausing occurs on essentially any DNA, and very frequently—every 100 nucleotides or so. These “ubiquitous” pauses are only partly efficient (i.e., not always recognized as the enzyme transits), and mostly have not been associated with specific functions. However, their existence is consistent with biochemical experiments showing that the progress of RNA polymerase is generally erratic. A consensus sequence for ubiquitous pauses was identified, with two important elements:

  • a preference for pyrimidine [mostly cytosine (C)] at the newly formed RNA end,
  • followed by G to be incorporated next—just as found for the his pause; and
  • a preference for G at position −10 of the RNA (10 nucleotides before the 3′ end), which is
  • at the upstream boundary of the RNA-DNA templating hybrid.

Remarkably, the tendency of a G in this position to induce pausing was recognized earlier, when DNA could be sequenced only through its transcript (10); it was thought that inhibited unwinding of the RNA-DNA hybrid underlies the pause.

 

Polyymerase, paused.

During transcription, RNA exists in two states as RNA polymerase progresses:

  1. pretranslocated, just after the addition of the last nucleotide [here, cytosine (C)]; and
  2. posttranslocated, after all nucleic acids have shifted in register by one nucleotide relative to the enzyme,
  • exposing the active site for binding of the next substrate molecule [here, guanine (G)].

The pretranslocated state is dominant in the pause. The critical G-C base (RNA-DNA) pair at position −10 in pretranslocated state and

  • the nontemplate DNA strand G bound in the polymerase in the posttranslocated state are marked with an asterisk.

ILLUSTRATION: V. ALTOUNIAN/SCIENCE

This ubiquitous pausing consensus sequence now has been refined and mapped exhaustively in the E. coligenome by Larson et al. and Vvedenskaya et al. (see the figure). In an analysis called native elongating transcript sequencing (NET-Seq) (11), transcripts associated with the whole cellular population of RNA polymerase are isolated from abruptly frozen cells and their growing ends are sequenced, giving a snapshot at nucleotide resolution of global transcription activity; DNA sites that are highly populated by RNA polymerase represent pauses. Larson et al. identified ∼20,000 transcription pause sites in the E. coli genome, including those expected from previous analysis of known sites like the his pause. Their analysis raises interesting questions about the role of such abundant pausing sequences.

Primarily, Larson et al. note that pauses frequently occur

  • exactly at the site of translation initiation, suggesting an important role in gene expression.

This coincidence of events is understandable when you examine the sequences. The consensus sequence in RNA for RNA polymerase pausing is G−10Y−1G+1 [G at position −10 and at the site after the pause; Y denotes either C or uracil (U) at the RNA end] according to Larson et al. and Vvedenskaya et al. The Shine-Dalgarno consensus sequence in RNA that the small-subunit ribosome recognizes is AGGAGG [adenine (A)] providing the G at the −10 position;

  • the downstream initiation codon for RNA translation is AUG, providing (for E. coli) the U at the pause end at position −1, with a following G at position +1.

A slightly modified pausing consensus sequence in the bacterium Bacillus subtilis accommodates the difference in spacing between the Shine-Dalgarno sequence and the initiation codon. What might be the role of a pause exactly at the translation initiation site? Because the ribosome binding site is physically concealed by RNA at the pause,

  • pausing may enable some process that prepares the RNA for translation once RNA polymerase transits the pause site.

Larson et al. suggest that the pause allows upstream RNA secondary structure to resolve in order to present the initiation region properly to the ribosome.

A particularly informative application of NET-Seq that provides new mechanistic information about pausing is based on the discovery of a specific binding site in RNA polymerase [the core recognition element (CRE)] for G in the non-template DNA strand (the strand not transcribed), at position +1 in the “posttranslocated” structure (12).

  • It could be that specific binding of a nucleotide to the enzyme in this position enhances pausing by slowing translocation;

surprisingly, however, Vvedenskaya et al. find the opposite. Cells altered to destroy the G binding site have up to twice as many sites of pausing as in wild-type cells, with

  • a greater preference for G as the incoming nucleotide.

However, this result is understandable in terms of the translocation cycle of RNA polymerase and the ubiquitous pausing sequence that has G at position +1. Binding of G at position +1 to CRE only occurs in the posttranslocated state, which would thus be favored over the pretranslocated state. Hence,

  • if G binding inhibits pausing, then the rate-limiting paused structure must be in the pretranslocated state (a conclusion also made by Larson et al. from biochemical experiments).

This is an important insight into the sequence of protein–nucleic acid interactions that occur in pausing. Vvedenskaya et al. suggest that the actual role of the G binding site is to promote translocation and thus inhibit pausing, to smooth out adventitious pauses in genomic DNA.

The studies by Larson et al. and Vvedenskaya et al. provide a refined and detailed analysis of DNA sequence–induced transcription pausing. As a core process in gene expression, this understanding is relevant not only for the basic biology of transcription, but also has applications in synthetic biology and the design of genetic circuits.

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The editors suggest the following Related Resources on Science sites

In Science Magazine

REPORT Interactions between RNA polymerase and the “core recognition element” counteract pausing

Irina O. Vvedenskaya,  Hanif Vahedian-Movahed, Jeremy G. Bird, Jared G. Knoblauch, Seth R. Goldman,

Yu Zhang, Richard H. Ebright, and Bryce E. Nickels

Science 13 June 2014: 1285-1289.

 

“miR”roring Lupus Control

Angela Colmone

Sci.Signal., 29 July 2014;; 7(336),, p. ec202   http://dx.doi.org:/10.1126/scisignal.2005732

Decreased expression of the B cell signaling inhibitor PTEN may contribute to lupus pathology. Wu et al. found that microRNA (miR)–mediated regulation of PTEN is altered in patients with the autoimmune disease systemic lupus erythematosus (SLE). Patients with SLE have hyperactivated B cells, which results in the production of autoantibodies. The authors found that decreased expression of PTEN in B cells from SLE patients contributes to this B cell hyperactivation. What’s more, they found that PTEN expression in these cells was regulated by miRs and that blocking miR-7 could restore PTEN expression and function to that of healthy controls. These data support exploring miR-7 and PTEN as therapeutic targets for SLE.

X-n. Wu, Y-x. Ye, J-w. Niu, Y. Li, X. Li, X. You, H. Chen, L-d. Zhao, X-f. Zeng, F-c. Zhang, F-l. Tang, W. He, X-t. Cao, X. Zhang, P. E. Lipsky, Defective PTEN regulation contributes to B cell hyperresponsiveness in systemic lupus erythematosus. Sci. Transl. Med. 6, 246ra99 (2014). [Full Text]

Citation:

  1. Colmone, “miR”roring Lupus Control. Sci. Signal.7, ec202 (2014).

 

Long Noncoding RNA Regulating Apoptosis Discovered

Source: © Dmitry Sunagatov – Fotolia.com

  • Scientists from the University of São Paulo (USP) have identified an RNA molecule known as INXS that, although containing no instructions for the production of a protein, modulates the action of an important gene that impactsapoptosis.

According to Sergio Verjovski-Almeida, Ph.D., professor at the USP Chemistry Institute, INXS expression is generally diminished in cancer cells, and methods that are capable of stimulating the production of this noncoding RNA can be used to treat tumors. In experiments on mice, the USP scientists were able to effect a 10-fold reduction in the volume of subcutaneous malignant tumors by administering local injections of a plasmid containing INXS.

The team’s findings (“Long noncoding RNA INXS is a critical mediator of BCL-XS induced apoptosis”) were published in Nucleic Acids Research.

The group headed by Dr. Verjovski-Almeida at USP has been investigating the regulatory role of so-called intronic nonprotein-coding genes—those found in the same region of the genome as a coding gene but on the opposite DNA strand. INXS, for example, is an RNA expressed on the opposite strand of a gene coding for  the BCL-X protein.

“We were studying several protein-coding genes involved in cell death in search of evidence that one of them was regulated by intronic noncoding RNA. That was when we found the gene for BCL-X, which is located on chromosome 20,” he explained.

BCL-X is present in cells in two different forms: one that inhibits apoptosis (BCL-XL) and one that induces the process of cell death (BCL-XS). The two isoforms act on the mitochondria but in opposite ways. The BCL-XS isoform is considered a tumor suppressor because it activates caspases, which are required for the activation of other genes that cause cell death.

“In a healthy cell, there is a balance between the two BCL-X isoforms. Normally, there is already a smaller number of the pro-apoptotic form (BCL-XS). However, in comparing tumor cells to nontumor cells, we observed that tumor cells contain even fewer of the pro-apoptotic form, as well as reduced levels of INXS. We suspect that one thing affects the other,” continued Dr. Verjovski-Almeida.

To confirm the hypothesis, the group silenced INXS expression in a normal cell lineage and the result, as expected, was an increase in the BCL-XL (anti-apoptotic) isoform. “The rate between the two—which was 0.25—decreased to 0.15; in other words, the pro-apoptotic form that previously represented one fourth of the total began to represent only one sixth,” noted Dr. Verjovski-Almeida.

The opposite occurred when the researchers artificially increased the amount of INXS using plasmid expression in a kidney cancer cell line, with the noncoding RNA being reduced. “The pro-apoptotic form increased, and the anti-apoptotic form decreased,” he added.

“In a mouse xenograft model, intra-tumor injections of an INXS-expressing plasmid caused a marked reduction in tumor weight, and an increase in BCL-XS isoform, as determined in the excised tumors,” wrote the investigators. “We revealed an endogenous lncRNA that induces apoptosis, suggesting that INXS is a possible target to be explored in cancer therapies.

 

Scientists map one of the most important proteins in life—and cancer

Mon, 07/21/2014

Scientists have revealed the structure of one of the most important and complicated proteins in cell division—a fundamental process in life and the development of cancer—in research published in Nature.

Images of the gigantic protein in unprecedented detail will transform scientists’ understanding of exactly how cells copy their chromosomes and divide, and could reveal binding sites for future cancer drugs.

A team from The Institute of Cancer Research, London, and the Medical Research Council Laboratory of Molecular Biology in Cambridge produced the first detailed images of the anaphase-promoting complex (APC/C).

The APC/C performs a wide range of vital tasks associated with mitosis,

  1. the process during which a cell copies its chromosomes and
  2. pulls them apart into two separate cells.
  3. Mitosis is used in cell division by all animals and plants.

Discovering its structure could ultimately lead to new treatments for cancer, which

  • hijacks the normal process of cell division to make thousands of copies of harmful cancer cells.

In the study, which was funded by Cancer Research UK,

the researchers reconstituted human APC/C and used a combination of electron microscopy and imaging software to visualize it at a resolution of less than a billionth of a meter.

The resolution was so fine that it allowed the researchers to see the secondary structure—

  • the set of basic building blocks which combine to form every protein.

Alpha-helix rods and folded beta-sheet constructions were clearly visible within the 20 subunits of the APC/C, defining the overall architecture of the complex.

Previous studies led by the same research team had shown

  • a globular structure for APC/C in much lower resolution, but
  • the secondary structure had not previously been mapped.

The new study could identify binding sites for potential cancer drugs.

Each of the APC/C’s subunits bond and mesh with other units at different points in the cell cycle,

  1. allowing it to control a range of mitotic processes including the initiation of DNA replication,
  2. the segregation of chromosomes along protein ‘rails’ called spindles, and
  3. the ultimate splitting of one cell into two, called cytokinesis.

Disrupting each of these processes could

  • selectively kill cancer cells or prevent them from dividing.

Dr David Barford, who led the study as Professor of Molecular Biology at The Institute of Cancer Research, London, before taking up a new position at the Medical Research Council Laboratory of Molecular Biology in Cambridge, said:

“It’s very rewarding to finally tie down the detailed structure of this important protein, which is both

  • one of the most important and most complicated found in all of nature.

We hope our discovery will open up whole new avenues of research that increase our understanding of the process of mitosis, and ultimately lead to the discovery of new cancer drugs.”

Professor Paul Workman, Interim Chief Executive of The Institute of Cancer Research, London, said: “The fantastic insights into molecular structure

  • provided by this study are a vivid illustration of the critical role played by fundamental cell biology in cancer research.

“The new study is a major step forward in our understanding of cell division. When this process goes awry

  • it is a critical difference that separates cancer cells from their healthy counterparts.

Understanding exactly how cancer cells divide inappropriately is crucial to

  • the discovery of innovative cancer treatments to improve outcomes for cancer patients.”

Dr Kat Arney, Science Information Manager at Cancer Research UK, said “Figuring out how the fundamental molecular ‘nuts and bolts’ of cells work is vital

  • if we’re to make progress understanding what goes wrong in cancer cells and how to tackle them more effectively.

Revealing the intricate details of biological shapes is a hugely important step towards identifying targets for future cancer drugs.”

Source: The Institute of Cancer Research, London

 

A cell death avenue evolved from a life-saving path

  1. Harm H. Kampinga

+Author Affiliations

  1. Department of Cell Biology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
  2. E-mail: h.kampinga@umcg.nl

Related Resources

In Science Magazine

Science 20 June 2014: 1389-1392.Published online 22 May 2014

In Science Signaling

Sci. Signal. 24 June 2014: ec175.

Yeast metacaspases are the ancestral enzymes of caspases that execute cellular suicide (“programmed cell death”) in multicellular organisms. Studies on metacaspase 1 (Mca1)

  • have suggested that single-cell eukaryotes can also commit programmed cell death (12). However,

on page 1389 of this issue, Malmgren Hill et al. (3) show that

  • Mca1 has positive rather than negative effects on the life span of the budding yeast Saccharomyces cerevisiae,
  • especially when protein homeostasis is impaired.

Mca1 helps to degrade misfolded proteins that accumulate during aging or that are generated by acute stress, and

  • thereby ensures the continuous and healthy generation of daughter cells
  • that are free of insoluble aggregates that otherwise would limit life span.

View larger version:

 

ILLUSTRATION: V. ALTOUNIAN/SCIENCE

Loss of Mca1 activity has been associated with a reduced appearance of programmed cell death markers (14),

  • implying that its overexpression should decrease the replicative life span of yeast (the number of daughter cells a mother cell can produce throughout its life). Cells lacking Mca1
  • have increased amounts of protein aggregates and oxidized proteins (45).

Malmgren Hill et al. not only show that this is related to decreased survival,

  • but also provide mechanistic insights into the mode of action of Mca1.

Its pro-life action depends on the chaperone heat shock protein 104 (Hsp104), a protein that

  1. can disentangle protein aggregates and
  2. is crucial for the asymmetric segregation of protein aggregates in dividing cells.

Mca1 deficiency does not affect life span of wild-type strains, but

  1. further decreases life span in strains already compromised in protein quality control. In particular,
  2. replicative aging is accelerated in strains lacking the Hsp70 co-chaperone Ydj1.

Mca1 does not improve protein folding but supports

  • degradation of terminally misfolded proteins.

Malmgren Hill et al. show that Mca1 requires proteasomes (protein structures that break down proteins) for all its effects.

The study by Malmgren Hill et al. challenges the idea that

  1. caspases are activated as an altruistic suicide mechanism in single-cell eukaryotes
  2. as a means to provide nutrients for younger and fitter cells in the population (2). Rather,
  3. the data suggest that from an evolutionary perspective, caspase activation is an integrated part of a protective response
  4. to help cells survive toxic stress caused by the accumulation of misfolded proteins.

When, however, activated incorrectly (e.g., in the absence of proteotoxic stress) or too strongly (e.g., in the case of excessive damage to the cell),

  1. the caspase activity may become nonselective and thus
  2. lead to the typical Mca1-dependent hallmarks of programmed cell death (124). Also,
  3. caspase activation in metazoa may function primarily in cell-autonomous protection and cellular remodeling or
  4. pruning. Its role in programmed cell death may also simply reflect overactivation upon severe cellular damage or
  5. hijacking of the caspases in the absence of stress to serve in non–cell-autonomous regulated tissue homeostasis.

View larger version:

Defense against protein damage.

Stress-damaged proteins that form aggregates in cells can be reactivated with the Hsp104-Ssa-Ydj1 chaperone machinery. Mca1 may act

  • in parallel by binding to misfolded proteins during early stages of aggregation for proteasomal degradation (this is independent of Mca1’s enzymatic activity). Alternatively,
  • Mca1 may associate with misfolded proteins formed at late stages of aggregation (together with Hsp104 and Ssa), helping to disentangle
  • the aggregates by its protease cleavage activity before shunting them to the proteasome for degradation.

ILLUSTRATION: V. ALTOUNIAN/SCIENCE

The results of Malmgren Hill et al. also highlight the importance of protein quality control for cellular aging. A collapse of protein homeostasis

  • has been implicated mostly in chronological aging of differentiated cells and, for example,
  • as a cause of neurodegenerative diseases (6).

The authors show that it also plays a prominent role in replicative aging.

  • This supports early findings in yeast (7) and may also be relevant to metazoa,
  • in which stem cells have extremely efficient protein degradation mechanisms (8) and
  • also use asymmetric segregation of protein damage for rejuvenation (9).

The data of Malmgren Hill et al. also suggest the existence of an additional layer of control of protein homeostasis. Beyond the

  • activation and induction of chaperones that assist in protein sorting, refolding, and protein degradation via proteasomes and
  • autophagosomes (membrane structures that deliver proteins to lysosomes for enzymatic destruction) (10),
  • Malmgren Hill et al. show that activation of caspases also belongs to the cell’s repertoire of defense mechanisms against protein damage.
  • Mca1 might act in parallel to the Ssa-Ydj1 machinery. Although
  • Ssa-Ydj1 collaborates with Hsp104 to refold proteins after their aggregation (11),
  • Mca1 primarily supports protein degradation, as its actions require not only Hsp104 but also proteasomal activity (3).

Precisely how Mca1 exerts its effect is yet unclear. It can associate with aggregates independent of other chaperones (35) and

  • independent of its catalytic activity (5), suggesting that
  • it binds directly to misfolded proteins [likely through its amino-terminal “pro-domain”
  • that is rich in glutamine and asparagine repeats].

This interaction may exert chaperone-like activity by keeping unfolded proteins

  • in a proteasome-competent form, which explains why part of Mca1’s protective actions in wild-type strains is independent of its protease activity.

However, the caspase activity of Mca1 is required for protein homeostasis and control of life span in Ydj1-deficient strains. It could be that

  • for more terminally misfolded proteins that accumulate in the absence of Ydj1,
  • protease cleavage may help to dismantle such aggregates in concert with Ssa and Hsp104 (see the figure).

This would also explain why the strongest phenotypes of Mca1 are seen under conditions in which Ydj1 is absent. More biochemical data with purified proteins will be needed to test these ideas.

The study of Malmgren Hill et al. suggests that altruism may not exist among cells. However, life and death seem to be close neighbors, and the things that are life saving may also become lethal. It will therefore be a challenge

  • to make use of these insights into caspase function in order to treat diseases by selectively tipping the balance toward life (e.g., in neurodegenerative diseases) or death (e.g., in cancer).

References

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, Proc. Natl. Acad. Sci. U.S.A. 102, 17326 (2005).

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 the following Related Report

Life-span extension by a metacaspase in the yeast Saccharomyces cerevisiae

Sandra Malmgren Hill, Xinxin Hao, Beidong Liu, and Thomas Nyström

Science 20 June 2014: 1389-1392.

 

Synthetic biology: the many facets of T7 RNA polymerase

David L Shis, Matthew R Bennett
Molecular Systems Biology(2014)10:745   30.07.2014
http://dx.doi.org:/10.15252/msb.20145492

 

Added 8-2-2014

Split T7 RNA polymerase provides new avenues for creating synthetic gene circuits that are decoupled from host regulatory processes—but how many times can this enzyme be split, yet retain function? New research by Voigt and colleagues (SegallShapiro et al, 2014) indicates that it may be more than you think.

See also: TH Segall‐Shapiro et al (July 2014)

Synthetic gene circuits have become an invaluable tool for studying the design principles of native gene networks and facilitating new biotechnologies (Wayet al2014). Synthetic biologists often strive to build circuits within a framework that enables their consistent and robust operation across a range of hosts and conditions. Currently, however, each circuit must be fastidiously tuned and retuned in order to properly function within a particular host, leading to costly design cycles and esoteric conclusions. As a result, researchers have invested a great deal in developing strategies that

  • decouple synthetic gene circuits from host metabolism and regulation.

In their recent work, Segall‐Shapiro et al (2014) address this problem by

  • expanding the capabilities of orthogonal transcriptional systems in Escherichia coli using fragmented mutants of bacteriophage‐T7 RNA polymerase (T7 RNAP).

T7 RNAP has had a long relationship with biotechnology and

  • is renowned for its compactness and transcriptional activity.

This single subunit polymerase strongly

  • drives transcription from a miniscule 17‐bp promoter
  • that is orthogonally regulated inE. coli.

In this context, orthogonal means that

  • T7 RNAP will not transcribe genes driven by native E. coli promoters, and
  • native polymerases in E. coli will not recognize T7 RNAP’s special promoter—that is
  • the two transcriptional systems leave each other alone.

Interestingly, T7 RNAP drives transcription so strongly that,

  • if left unregulated, it can quickly exhaust cellular resources and lead to cell death.

Because of this, T7 RNAP

  • has been leveraged in many situations calling for protein over‐expression (Studier & Moffatt, 1986).

Additionally, studies examining the binding of T7 RNAP to its promoter have identified

  • a specificity loop within the enzyme that makes direct contact with the promoter
  • between base pairs −11 and −8.

This has led to a number of efforts that have generated T7 RNAP mutants

  • with modified specificities to promoters orthogonal to the original (Chelliserrykattil et al2001).

Given the growing interest in the development of synthetic gene circuits, researchers have taken a renewed interest in T7 RNAP. The orthogonality,

  • transcriptional activity and promoter malleability of T7 RNAP make the enzyme uniquely suited for use in synthetic gene circuits. Importantly,
  • any modifications made to the enzyme increase the possible functionality of circuits. For instance, we recently utilized
  • a split version of T7 RNAP in conjunction with promoter specificity mutants to create a library of transcriptional AND gates (Shis & Bennett, 2013).

The split version of T7 RNAP was originally discovered during purification and shown to be active in vitro (Ikeda & Richardson, 1987). While the catalytic core and DNA‐binding domain

  • are both located on the C‐terminal fragment of split T7 RNAP,
  • the N‐terminal fragment is needed for transcript elongation.

Therefore, if the two halves of split T7 RNAP are placed behind two different inducible promoters,

  1. both inputs must be active in order to form a functional enzyme and
  2. activate a downstream gene.

When the split mutant is combined with promoter specificity mutants,

  • a library of transcriptional AND gates is created.

Segall‐Shapiro et al take the idea of splitting T7 RNAP for novel regulatory architectures one step further. Instead of settling for the one split site already discovered,

  • the authors first streamlined a transposon mutagenesis strategy (Segall‐Shapiro et al2011) to identify four novel cut sites within T7 RNAP.

By expressing T7 RNAP split at two different sites,

  • they create a tripartite T7 RNAP—a polymerase
  • that requires all three subunits for activity.

The authors suggestively designate the fragments of the tripartite enzyme as ‘core’, ‘alpha’, and ‘sigma’ (Fig 1) and they go on to show that

  • tripartite T7 RNAP can not only be used to create 3‐input AND gates, but
  • it also works as a ‘resource allocator’.

In other words, the transcriptional activity of the split polymerase can be regulated

  • by limiting the availability of core and/or alpha fragment, or
  • by expressing additional sigma fragments.

The authors demonstrate strategies to account for common pitfalls in synthetic gene networks

  • such as host toxicity and plasmid copy number variability.

 

Figure 1. Segall‐Shapiro et al extend previous efforts to engineer split T7 RNAP by fragmenting the enzyme at two novel locations to create a tripartite transcription complex.

Co‐expressing different sigma fragments with the alpha and core fragments enables a network of multi‐input transcriptional AND gates.

The tripartite T7 RNAP presented by Segall‐Shapiro et al

  • expands the utility of T7 RNAP in orthogonal gene circuits.

Until now, while T7 RNAP has been attractive for use in synthetic gene circuits,

  • the inability to regulate its activity has often prevented its use.

Splitting the protein into fragments and regulating the transcription complex by fragment availability

  • brings the regulation of T7 RNAP closer to the regulation of multi‐subunit prokaryotic RNA polymerases.

Sigma fragments direct the activity of the transcription complex much like σ‐factors, and the alpha fragment helps activate transcription

  • in the same way as α‐fragments of prokaryotic polymerases.

For additional regulation, the authors note that the tripartite T7 RNAP can be further split at the previously discovered split site to create a four‐fragment enzyme.

More nuanced regulation using split T7 RNAP may be possible

  • with the addition of heterodimerization domains
  • that can drive the specific association of fragments.

This strategy has been successfully applied to engineer specificity and signal diversity

  • in two‐component signaling pathways (Whitaker et al2012).

The activity of T7 RNAP might also be directed to various promoters

  • by using multiple sigma fragments simultaneously,
  • just as σ‐factors do in E. coli.

Finally, synthetic gene circuits driven primarily by T7 RNAP create the possibility of easily transplantable gene circuits. A synthetic gene circuit driven entirely by fragmented T7 RNAP

  • would depend more on fragment availability than unknown interactions with host metabolism.

This would enable rapid prototyping of synthetic gene circuits in laboratory‐friendly strains or cell‐free systems (Shin & Noireaux, 2012) before transplantation into the desired host.

References

  1. Chelliserrykattil J, Cai G, Ellington AD (2001) A combined in vitro/in vivo selection for polymerases with novel promoter specificities. BMC Biotechnol 1: 13

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  1. Ikeda RA, Richardson CC (1987) Interactions of a proteolytically nicked RNApolymerase of bacteriophageT7 with its promoter. J Biol Chem 262: 3800–3808

Abstract/FREE Full Text

  1. SegallShapiro TH, Meyer AJ, Ellington AD, Sontag ED, Voigt CA (2014) A “resource allocator” for transcription based on a highly fragmented T7 RNA polymerase.Mol Syst Biol 10: 742

Abstract/FREE Full Text

  1. SegallShapiro TH, Nguyen PQ, Dos Santos ED, Subedi S, Judd J, Suh J, Silberg JJ(2011) Mesophilic and hyperthermophilic adenylate kinases differ in their tolerance to random fragmentation. J Mol Biol 406: 135–148

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  1. Shin J, Noireaux V (2012) An  coli cellfree expression toolbox: application to synthetic gene circuits and artificial cells. Acs Synth Biol 1: 29–41

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  1. Shis DL, Bennett MR (2013) Library of synthetic transcriptional AND gates built with split T7 RNA polymerase mutants. Proc Natl Acad Sci USA 110: 5028–5033

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  1. Studier FW, Moffatt BA (1986) Use of bacteriophageT7 RNApolymerase to direct selective highlevel expression of cloned genes. J Mol Biol 189: 113–130

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  1. Way JC, Collins JJ, Keasling JD, Silver PA (2014) Integrating biological redesign: where synthetic biology came from and where it needs to go. Cell 157: 151–161
  2. Whitaker WR, Davis SA, Arkin AP, Dueber JE (2012) Engineering robust control of twocomponent system phosphotransfer using modular scaffolds. Proc Natl Acad Sci USA 109: 18090–18095

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© 2014 The Authors. Published under the terms of the CC BY 4.0 license

 

 

MicroRNA References

Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure. Dickinson BA, Semus HM, Montgomery RL, Stack C, Latimer PA, et al. Eur J Heart Fail. 2013 Jun; 15(6):650-9.  http://dx.doi.org:/10.1093/eurjhf/hft018

Circulating microRNAs – Biomarkers or mediators of cardiovascular disease?  S Fichtlscherer, AM Zeiher, S Dimmeler. Arteriosclerosis, Thrombosis, and Vascular Biology. 2011; 31:2383-2390.
http://dx.doi.org:/10.1161/​ATVBAHA.111.226696

Circulating microRNAs as diagnostic biomarkers for cardiovascular diseases. AJ Tijsen, YM Pinto, and EE Creemers. Am J Physiol Heart Circ Physiol 303: H1085–H1095, 2012.  http://dx.doi.org:/10.1152/ajpheart.00191.2012.

MicroRNAs in Patients on Chronic Hemodialysis (MINOS Study). Emilian C, Goretti E, Prospert F, Pouthier D, Duhoux P, et al. Clin J Am Soc Nephrol  (CJASN)2012;  7: 619-623. http://dx.doi.org:/10.2215/CJN.10471011

Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure.  BA Dickinson, HM Semus, RL Montgomery, C Stack, PA Latimer, et al. Eur J Heart Fail 2013 Jun 6;15(6):650-9. http://www.pubfacts.com/detail/23388090/Plasma-microRNAs-serve-as-biomarkers-of-therapeutic-efficacy-and-disease-progression-in-hypertension

Circulating MicroRNAs: Novel Biomarkers and Extracellular Communicators in Cardiovascular Disease?  Esther E. Creemers, Anke J. Tijsen, Yigal M. Pinto.  Circulation Research. 2012; 110: 483-495    http://dx.doi.org:/10.1161/​CIRCRESAHA.111.247452

Novel techniques and targets in cardiovascular microRNA research.  Dangwal S, Bang C, Thum T. Cardiovasc Res. 2012 Mar 15; 93(4):545-54.  http://dx.doi.org:/10.1093/cvr/cvr297

Microparticles: major transport vehicles for distinct microRNAs in circulation. Diehl P, Fricke A, Sander L, Stamm J, Bassler N, Htun N, et al.  Cardiovasc Res. 2012 Mar 15; 93(4):633-44. http://dx.doi.org:/10.1093/cvr/cvs007.

Profiling of circulating microRNAs: from single biomarkers to re-wired networks. A  ZampetakiP Willeit, I Drozdov, S Kiechl and M Mayr. Cardiovasc Res 2012; 93 (4): 555-562.  http://dx.doi.org:/10.1093/cvr/cvr266

Small but smart–microRNAs in the centre of inflammatory processes during cardiovascular diseases, the metabolic syndrome, and ageing. Schroen B, Heymans S.
Cardiovasc Res. 2012; 93(4):605-613http://dx.doi.org:/10.1093/cvr/cvr268

Therapeutic Inhibition of miR-208a Improves Cardiac Function and Survival During Heart Failure. RL Montgomery, TG Hullinger, HM Semus, BA Dickinson, AG Seto, et al.
http://dx.doi.org:/10.1161/​CIRCULATIONAHA.111.030932

Circulating microRNAs to identify human heart failure.  Seto AG, van Rooij E.
Eur J Heart Fail. 2012;14(2):118-119http://dx.doi.org:/10.1093/eurjhf/hfr179.

Use of Circulating MicroRNAs to Diagnose Acute Myocardial Infarction. Y Devaux,
M Vausort, E Goretti, PV Nazarov, F Azuaje. Clin Chem. 2012; 58:559-567. http://dx.doi.org:/10.1373/clinchem.2011.173823

Next Steps in Cardiovascular Disease Genomic Research–Sequencing, Epigenetics, and Transcriptomics  RB Schnabel, A Baccarelli, H Lin, PT Ellinor, and EJ Benjamin.
Clin Chem . 2012 Jan; 58(1): 113–126.  http://dx.doi.org:/10.1373/clinchem.2011.170423

MicroRNA-133 Modulates the {beta}1-Adrenergic Receptor Transduction Cascade.  A Castaldi, T Zaglia, V Di Mauro, P Carullo, G Viggiani, et al.  Circ. Res.. 2014; 115:273-283.
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Development of microRNA therapeutics is coming of age.  E van Rooij, S Kauppinen.  EMBO Mol Med.. 2014; 6:851-864.  http://dx.doi.org:/10.15252/emmm.201100899

Pitx2-microRNA pathway that delimits sinoatrial node development and inhibits predisposition to atrial fibrillation.   J Wang, Y Bai, N Li, W Ye, M Zhang,et al. PNAS 2014; 111: 9181-9186.

MicroRNA-126 modulates endothelial SDF-1 expression and mobilization of Sca-1+/Lin- progenitor cells in ischaemia  Cardiovasc Res. 2011; 92:449-455,

The use of genomics for treatment is another matter, and has several factors, e.g., age, residual function after AMI, comorbidities

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Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalinnovation.com/2012-12-09/larryhbern/Silencing Cancers with Synthetic siRNAs

The challenge of cancer drug development has been marker by less than a century of development of major insights into the know of biochemical pathways and the changes in those pathways in a dramatic shift in enrgy utilization and organ development, and the changes in those pathways with the development of malignant neoplasia.  The first notable change is the Warburg Effect (attributed to the 1860 obsevation by Pasteur that yeast cells use glycolysis under anaerobic conditions).  Warburg also referred to earlier work by Meyerhoff, in a ratio of CO2 release to O2 consumption, a Meyerhoff ratio.  Much more was elucidated after the discovery of the pyridine nucleotides, which gave understanding of glycolysis and lactate production with a key two enzyme separation at the forward LDH reaction and the back reentry to the TCA cycle.  But the TCA cycle could be used for oxidative energy utilization in the mitochondria by oxidative phosphorylation elucidated by Peter Mitchell, or it can alternatively be used for syntheses, like proteins and lipid membrane structures.

A brilliant student in Leloir’s laboratory in Brazil undertook a study of isoenzyme structure in 1971, at a time that I was working under Nathan O. Kaplan on the mechanism of inhibition of mitochondrial malate dehydrogenase. In his descripton, taking into account the effect of substrates upon protein stability (FEBS) could be, in a prebiotic system, the form required in order to select protein and RNA in parallel or in tandem in a way that generates the genetic code (3 bases for one amino acid). Later, other proteins like reverse transcriptase, could transcribe it into the more stable DNA. Leloir had just finished ( a few years before 1971 but, not published by these days yet) a somehow similar reasoning about metabolic regions rich in A or in C or .. G or T.  He later spent time in London to study the early events in the transition of growing cells linked to ion fluxes, which he was attracted to by the idea that life is so strongly associated with the K (potassium) and Na (sodium) asymmetry.   Moreover, he notes that while DNA is the same no matter the cell is dead or alive,  and therefore,  it is a huge mistake to call DNA the molecule of life. In all life forms, you will find K reach inside and Na rich outside its membrane. On his return to Brazil, he accepted a request to collaborate with the Surgery department in energetic metabolism of tissues submitted to ischemia and reperfusion. This led me back to Pasteur and Warburg effects and like in Leloir´s time, he worked with a dimorphic yeast/mold that was considered a morphogenetic presentation of the Pasteur Effect.  His findings were as follows. In absence of glucose, a condition that prevents the yeast like cell morphology, which led to the study of an enzyme “half reaction”. The reaction that on the half, “seen in our experimental conditions did not followed classical thermodynamics” (According to Collowick & Kaplan (of your personal knowledge) vol. I See Utter and Kurahashi in it). This somehow contributed to a way of seeing biochemistry with modesty. The second and more strongly related to the Pasteur Effect was the use an entirely designed and produced in our Medical School Coulometer spirometer that measures oxygen consumption in a condition of constant oxygen supply. At variance with Warburg apparatus and Clark´s electrode, this oxymeters uses decrease in partial oxygen pressure and decrease electrical signal of oxygen polarography to measure it (Leite, J.V.P. Research in Physiol. Kao, Koissumi, Vassali eds Aulo Gaggi Bologna, 673-80-1971). “With this, I was able to measure the same mycelium in low and high “cell density” inside the same culture media. The result shows, high density one stops mitochondrial function while low density continues to consume oxygen (the internal increase or decrease in glycogen levels shows which one does or does not do it). Translation for today: The same genome in the same chemical environment behave differently mostly likely by its interaction differences. This previous experience fits well with what  I have to read by that time of my work with surgeons.  Submitted to total ischemia tissues mitochondrial function is stopped when they already have enough oxyhemoglobin (1) Epstein, Balaban and Ross Am J Physiol.243, F356-63 (1982) 2) Bashford , C. L, Biological membranes a practical approach Oxford Was. P 219-239 (1987).”

Of course, the world of medical and pharmaceutical engagement with this problem, though changed in focus, has benefitted hugely from “The Human Genome Project”, and the events since the millenium, because of technology advances in instrumental analysis, and in bioinformatics and computational biology.  This has lead to recent advances in regenerative biology with stem cell “models”, to advances in resorbable matrices, and so on.  We proceed to an interesting work that applies synthetic work with nucleic acid signaling to pharmacotherapy of cancer.

Synthetic RNAs Designed to Fight Cancer

Fri, 12/06/2013 Biosci Technology
Xiaowei Wang and his colleagues have designed synthetic molecules that combine the advantages of two experimental RNA therapies against cancer. (Source: WUSTL/Robert J. Boston)In search of better cancer treatments, researchers at Washington University School of Medicine in St. Louis have designed synthetic molecules that combine the advantages of two experimental RNA therapies.  The study appears in the December issue of the journal RNA.
 RNAs play an important role in how genes are turned on and off in the body. Both siRNAs and microRNAs are snippets of RNA known to modulate a gene’s signal or shut it down entirely. Separately, siRNA and microRNA treatment strategies are in early clinical trials against cancer, but few groups have attempted to marry the two.   “These are preliminary findings, but we have shown that the concept is worth pursuing,” said Xiaowei Wang, assistant professor of radiation oncology at the School of Medicine and a member of the Siteman Cancer Center. “We are trying to merge two largely separate fields of RNA research and harness the advantages of both.”
 “We designed an artificial RNA that is a combination of siRNA and microRNA, The showed that the artificial RNA combines the functions of the two separate molecules, simultaneously inhibiting both cell migration and proliferation. They designed and assembled small interfering” RNAs, or siRNAs,  made to shut down– or interfere with– a single specific gene that drives cancer.  The siRNA molecules work extremely well at silencing a gene target because the siRNA sequence is made to perfectly complement the target sequence, thereby
  • silencing a gene’s expression.
Though siRNAs are great at turning off the gene target, they also have potentially dangerous side effects:
  • siRNAs inadvertently can shut down other genes that need to be expressed to carry out tasks that keep the body healthy.
 According to Wang and his colleagues, siRNAs interfere with off-target genes that closely complement their “seed region,” a short but important
  • section of the siRNA sequence that governs binding to a gene target.
 “We can never predict all of the toxic side effects that we might see with a particular siRNA,” said Wang. “In the past, we tried to block the seed region in an attempt to reduce the side effects. Until now,
  • we never tried to replace the seed region completely.”
 Wang and his colleagues asked whether
  • they could replace the siRNA’s seed region with the seed region from microRNA.
Unlike siRNA, microRNA is a natural part of the body’s gene expression. And it can also shut down genes. As such, the microRNA seed region (with its natural targets) might reduce
  • the toxic side effects caused by the artificial siRNA seed region. Plus,
  • the microRNA seed region would add a new tool to shut down other genes that also may be driving cancer.
 Wang’s group started with a bioinformatics approach, using a computer algorithm to design
  • siRNA sequences against a common driver of cancer,
  • a gene called AKT1 that encourages uncontrolled cell division.
They used the program to select siRNAs against AKT1 that also had a seed region highly similar to the seed region of a microRNA known to inhibit a cell’s ability to move, thus
  • potentially reducing the cancer’s ability to spread.
In theory, replacing the siRNA seed region with the microRNA seed region also would combine their functions
  • reducing cell division and
  • movement with a single RNA molecule.
 Of more than 1,000 siRNAs that can target AKT1,
  • they found only three that each had a seed region remarkably similar to the seed region of the microRNA that reduces cell movement.
 They then took the microRNA seed region and
  • used it to replace the seed region in the three siRNAs that target AKT1.
The close similarity between the two seed regions is required because
  • changing the original siRNA sequence too much would make it less effective at shutting down AKT1.
 They dubbed the resulting combination RNA molecule “artificial interfering” RNA, or aiRNA. Once they arrived at these three sequences using computer models,
  1. they assembled the aiRNAs and
  2. tested them in cancer cells.
 One of the three artificial RNAs that they built in the lab
  • combined the advantages of the original siRNA and the microRNA seed region that was transplanted into it.
This aiRNA greatly reduced both
  1. cell division (like the siRNA) and
  2. movement (like the microRNA).
And to further show proof-of-concept, they also did the reverse, designing an aiRNA that
  1. both resists chemotherapy and
  2. promotes movement of the cancer cells.
 “Obviously, we would not increase cell survival and movement for cancer therapy, but we wanted to show how flexible this technology can be, potentially expanding it to treat diseases other than cancer,” Wang said.
Source: WUSTL

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Nanotechnology and HIV/AIDS Treatment

Author: Tilda Barliya, PhD

 

AIDS was first reported in 1981 followed by the identification of HIV as the cause of the disease in 1983 and is now a global pandemic that has become the leading infectious killer of adults worldwide. By 2006, more than 65 million people had been infected with the HIV virus worldwide and 25 million had died of AIDS (Merson MH. The HIV-AIDS pandemic at 25 – the global response. (1, 2). This has caused tremendous social and economic damage worldwide, with developing countries, particularly Sub-Saharan Africa, heavily affected.

A cure for HIV/AIDS has been elusive in almost 30 years of research. Early treatments focused on antiretroviral drugs that were effective only to a certain degree. The first drug, zidovudine, was approved by the US FDA in 1987, leading to the approval of a total of 25 drugs to date, many of which are also available in fixed-dose combinations and generic formulations for use in resource-limited settings (to date, only zidovudine and didanosine are available as true generics in the USA).

However, it was the advent of a class of drugs known as protease inhibitors and the introduction of triple-drug therapy in the mid-1990s that revolutionized HIV/AIDS treatment (3,4). This launched the era of highly active antiretroviral therapy (HAART), where a combination of three or more different classes of drugs are administered simultaneously.

Challenges of HIV/AIDS treatment

  • HIV resides in latent cellular and anatomical reservoirs where current drugs are unable to completely eradicate the virus.
  • Macrophages are major cellular reservoirs, which also contribute to the generation of elusive mutant viral genotypes by serving as the host for viral genetic recombination.
  • Anatomical latent reservoirs include secondary lymphoid tissue, testes, liver, kidney, lungs, the gut and the brain.
  • The major challenge facing current drug regimens is that they do not fully eramacrdicate the virus from these reservoirs; requiring patients take medications for life. Under current treatment, pills are taken daily, resulting in problems of patient adherence. The drugs also have side effects and in some people the virus develops resistance against certain drugs.

Current treatment in HIV/AIDS

The use of the HAART regimen, particularly in the developed world, has resulted in tremendous success in improving the expectancy and quality of lives for patients. However, some HAART regimens have serious side effects and, in all cases, HAART has to be taken for a lifetime, with daily dosing of one or more pills. Due to the need to take the medication daily for a lifetime, patients fail to adhere to the treatment schedule, leading to ineffective drug levels in the body and rebound of viral replication.Some patients also develop resistance to certain combinations of drugs, resulting in failure of the treatment. The absence of complete cure under current treatment underscores the great need for continued efforts in seeking innovative approaches for treatment of HIV/AIDS.

Drug resistance is mainly caused by the high genetic diversity of HIV-1 and the continuous mutation it undergoes. This problem is being addressed with individualized therapy, whereby resistance testing is performed to select a combination of drugs that is most effective for each patient (5). In addition, side effects due to toxicities of the drugs are also a concern. There are reports that patients taking HAART experience increased rates of heart disease, diabetes, liver disease, cancer and accelerated aging. Most experts agree that these effects could be due to the HIV infection itself or co-infection with another virus, such as co-infection with hepatitis C virus resulting in liver disease. However, the toxicities resulting from the drugs used in HAART could also contribute to these effects.

Under current treatment, complete eradication of the virus from the body has not been possible. The major cause for this is that the virus resides in ‘latent reservoirs’ within memory CD4+ T cells and cells of the macrophage–monocyte lineage. A major study recently found that, in addition to acting as latent reservoirs, macrophages significantly contribute to the generation of elusive mutant viral genotypes by serving as the host for viral genetic recombination (6).  The cells that harbor latent HIV are typically concentrated in specific anatomic sites, such as secondary lymphoid tissue, testes, liver, kidney, lungs, gut and the CNS. The eradication of the virus from such reservoirs is critical to the effective long-term treatment of HIV/AIDS patients.

Therefore, there is a great need to explore new approaches for developing nontoxic, lower-dosage treatment modalities that provide more sustained dosing coverage and effectively eradicate the virus from the reservoirs, avoiding the need for lifetime treatments.

Nanotechnology for HIV/AIDS treatment

The use of nanotechnology platforms for delivery of drugs is revolutionizing medicine in many areas of disease treatment.

Nanotechnology-based platforms for systemic delivery of antiretroviral drugs could have similar advantages.

  • Controlled-release delivery systems can enhance their half-lives, keeping them in circulation at therapeutic concentrations for longer periods of time. This could have major implications in improving adherence to the drugs.
  • Nanoscale delivery systems also enhance and modulate the distribution of hydrophobic and hydrophilic drugs into and within different tissues due to their small size. This particular feature of nanoscale delivery systems appears to hold the most promise for their use in clinical treatment and prevention of HIV. Specifically, targeted delivery of antiretroviral drugs to CD4+ T cells and macrophages as well as delivery to the brain and other organ systems could ensure that drugs reach latent reservoirs
  • Moreover, by controlling the release profiles of the delivery systems, drugs could be released over a longer time and at higher effective doses to the specific targets. Figure 1. Various nanoscale drug delivery systems.

Optional treatments:

  •    Antiretroviral drugs
  •    Gene Therapy
  •    Immune Therapy
  •    Prevention

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The use of nanotechnology systems for delivery of antiretroviral drugs has been extensively reviewed by Nowacek et al. and Amiji et al. (7,8).

In a recent study based on polymeric systems, nanosuspensions (200 nm) of the drug rilpivirine (TMC278) stabilized by polyethylene. A series of experiments by Dou et al. showed that nanosuspension of the drug indinavir can be stabilized by a surfactant system comprised of Lipoid E80 for effective delivery to various tissues. The indinavir nanosuspensions were loaded into macrophages and their uptake was investigated. Macrophages loaded with indinavir nanosuspensions were then injected intravenously into mice, resulting in a high distribution in the lungs, liver and spleen. More significantly, the intravenous administration of a single dose of the nanoparticle-loaded macrophages in a rodent mouse model of HIV brain infection resulted in significant antiviral activity in the brain and produced measureable drug levels in the blood up to 14 days post-treatment.polypropylene glycol (poloxamer 338) and PEGylated tocopheryl succinate ester (TPGS 1000) were studied in dogs and mice. A single-dose administration of the drug in nanosuspensions resulted in sustained release over 3 months in dogs and 3 weeks in mice, compared with a half-life of 38 h for free drug. These results serve as a proof-of-concept that nanoscale drug delivery may potentially lower dosing frequency and improve adherence.

Active targeting strategies have also been employed for antiretroviral drug delivery. Macrophages, which are the major HIV reservoir cells, have various receptors on their surface such as formyl peptide, mannose, galactose and Fc receptors, which could be utilized for receptor-mediated internalization. The drug stavudine was encapsulated using various liposomes (120–200 nm) conjugated with mannose and galactose, resulting in increased cellular uptake compared with free drug or plain liposomes, and generating significant level of the drug in liver, spleen and lungs. Stavudine is a water-soluble drug with a very short serum half-life (1 h). Hence, the increased cellular uptake and sustained release in the tissues afforded by targeted liposomes is a major improvement compared with free drug. The drug zidovudine, with half-life of 1 h and low solubility, was also encapsulated in a mannose-targeted liposome made from stearylamine, showing increased localization in lymph node and spleen. An important factor to consider here is that although most of the nucleoside drugs such as stavudine and zidovudine have short serum half-lives, the clinically relevant half-life is that of the intracellular triphosphate form of the drug. For example, despite zidovudine’s 1 h half-life in plasma, it is dosed twice daily based on intracellular pharmacokinetic and clinical efficacy data. Therefore, future nanotechnology-based delivery systems will have to focus in showing significant increase of the half-lives of the encapsulated drugs to achieve a less frequent dosing such as once weekly, once-monthly or even less.

Gene Therapy for HIV/AIDS

In addition to improving existing antiretroviral therapy, there are ongoing efforts to discover alternative approaches for treatment of HIV/AIDS. One promising alternative approach is gene therapy, in which a gene is inserted into a cell to interfere with viral infection or replication. Other nucleic acid-based compounds, such as DNA, siRNA, RNA decoys, ribozymes and aptamers or protein-based agents such as fusion inhibitors and zinc-finger nucleases can also be used to interfere with viral replication.

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RNAi is also considered to have therapeutic potential for HIV/AIDS. Gene silencing is induced by double stranded siRNA, which targets for destruction

he mRNA of the gene of interest. For HIV/AIDS, RNAi can either target the various stages of the viral replication cycle or various cellular targets involved in viral infection such as CD4, CCR5, and/or CXCR4, the major cell surface co-receptors responsible for viral entry. HIV replicates by reverse transcription to form DNA and uses the DNA to produce copies of its mRNA for protein synthesis; siRNA therapy could be used to knock down this viral mRNA. As with other gene therapy techniques, delivery of siRNA to specific cells and tissues has been the major challenge in realizing the potential of RNAi.

New nanotechnology platforms are tackling this problem by providing nonviral alternatives for effective and safe delivery. The first nontargeted delivery of siRNA in humans via self-assembling, cyclodextrin polymer-based nanoparticles for cancer treatment have recently entered Phase I clinical trials.

Although at an early stage, nonviral delivery of siRNA for treatment of HIV infection is also gaining ground. A fusion protein, with a peptide transduction domain and a double stranded RNA-binding domain, was used to encapsulate and deliver siRNA to T cells in vivo. CD4- and CD8-specific siRNA delivery caused RNAi responses with no adverse effects such as cyto-toxicity or immune stimulation. Similarly, a protamine-antibody fusion protein-based siRNA delivery demonstrated that siRNA knockdown of the gag gene can inhibit HIV replication in primary T cells

Single-walled nanotubes were shown to deliver CXCR4 and CD4 specific siRNA to human T cells and peripheral blood mononuclear cells. Up to 90% knockdown of CXCR4 receptors and up to 60% knockdown of CD4 expression on T cells was observed while the knockdown of CXCR4 receptors on peripheral blood mononuclear cells was as high as 60%. In a separate study, amino-terminated carbosilane dendrimers (with interior carbon-silicon bonds) were used for delivery of siRNA to HIV-infected lymphocytes.

These pioneering studies demonstrate that nonviral siRNA delivery is possible for HIV/AIDS treatment. However, more work needs to be done in optimizing the delivery systems and utilizing designs for efficient targeting and intracellular delivery. The recent developments in polymer- and liposome-based siRNA delivery systems could be optimized for targeting cells that are infected with HIV, such as T cells and macrophages. Moreover, since HIV mutates and has multiple strains with different genetic sequences, combination siRNA therapy targeting multiple genes should be pursued. For these applications, nanotechnology platforms with capability for co-delivery and targeting need to be developed specifically for HIV-susceptible cells. A macrophage and T-cell-targeted and nanotechnology-based combination gene therapy may be a promising platform for efficient HIV/AIDS treatment.

Immunotherapy for HIV/AIDS

The various treatment approaches described above focus on treating HIV/AIDS by directly targeting HIV at the level of the host cell or the virus itself. An alternative approach is immunotherapy aimed at modulating the immune response against HIV. CD8+ cytotoxic T-cell responses to acute HIV infection appear to be relatively normal, while neutralizing antibody production by B cells is delayed or even absent.

Immunotherapy is a treatment approach involving the use of immunomodulatory agents to modulate the immune response against a disease. Similar to vaccines, it is based on immunization of individuals with various immunologic formulations; however, the purpose is to treat HIV-infected patients as opposed to protect healthy individuals (preventive vaccines will be discussed in an upcoming section). The various immunotherapy approaches for HIV/AIDS could be based on delivering cytokines (such as IL-2, IL-7 and IL-15) or antigens. The development of cellular immunity, and to a large degree humoral immunity, requires antigen-presenting cells (APCs) to process and present antigens to CD4+and CD8+ T cells. Dendritic cells (DCs) are the quintessential professional APCs responsible for initiating and orchestrating the development of cellular and humoral (antibody) immunity.

Various polymeric systems have been explored for in vivo targeting of DCs and delivery of small molecules, proteins or DNAs showing potential for immunotherapy. Poly(ethylene glycol) (PEG) stabilized poly(propylene sulfide) polymer nanoparticles accumulated in DCs in lymph nodes. Following nanoparticle injection, DCs containing nanoparticles accumulated in lymph nodes, peaking at 4 days with 40–50% of DCs and other APCs having internalized nanoparticles.

In another study, nanoparticles of the copolymer poly(D,L-lacticide-co-glycolide) (PLGA) showed efficient delivery of antigens to murine bone marrow-derived DCs in vitro, suggesting their potential use in immunotherapy. More recently, a very interesting work showed that HIV p24 protein adsorbed on the surface of surfactant-free anionic poly(D,L-lactide) (PLA) nanoparticles were efficiently taken-up by mouse DCs, inducing DC maturation. he p24-nanoparticles induced enhanced cellular and mucosal immune responses in mice. Although this targeting is seen in ex vivo-generated DCs and not in vivo DCs, the efficient delivery of the antigen to DCs through the nanoparticles is an important demonstration that may eventually be applied to in vivo DC targeting.

Clinical Trial

he most clinically advanced application of nanotechnology for immunotherapy of HIV/AIDS is the DermaVir patch that has reached Phase II clinical trials (9). DermaVir is a targeted nanoparticle system based on polyethyleimine mannose (PEIm), glucose and HIV antigen coding DNA plasmid formulated into nanoparticles (~100 nm) and administered under a patch after a skin preparation. The nanoparticles are delivered to epidermal Langerhans cells that trap the nanoparticles and mature to become highly immunogenic on their way to the lymph nodes. Mature DCs containing the nanoparticles present antigens to T cells inducing cellular immunity. Preclinical studies and Phase I clinical trials showed safety and tolerability of the DermaVir patch, which led the progression to Phase II trials. This is the first nanotechnology-based immunotherapy for HIV/AIDS that has reached the clinic and encourages further work in this area.

Table 1

Summary of nanotechnology-based treatment approaches for HIV/AIDS.

Type of therapy Therapeutic agent (drug or gene) Nanotechnology delivery platform Development stage Refs.
Antiretroviral therapy Rilpivirine (TMC278) Poloxamer 338/TPGS 1000 Preclinical [35]
Indinavir Liposome-laden macrophages Preclinical [3638]
Stavudine Mannose- and galactose-targeted liposome Preclinical [3941]
Zidovudine Mannose-targeted liposome Preclinical [42]
Efavirenz Mannose-targeted dendrimer Preclinical [43,45]
Lamivudine Mannose-targeted dendrimer Preclinical [46]
Nanomaterials Fullerene derivatives Preclinical [4955]
Dendrimers Preclinical [56,57]
Silver nanoparticles Preclinical [58,59]
SDC-1721/gold nanoparticles Gold nanoparticles Preclinical [60]
Gene therapy siRNA Peptide fusion proteins, protamine–antibody fusion proteins, dendrimers, single walled carbon nanotubes, peptide–antibody conjugates Preclinical [7781]
Immunotherapy P24 protein Poly (D,L-lactide) nanoparticles/dendritic cells Preclinical [98]
Plasmid DNA Mannose-targeted polyethyleimine polymers Phase II clinical trials [99]

Note:  to open the references in the table 1, please go to ref 1 in this post to see full ref info.

Nanotechnology for HIV/AIDS prevention

The search for a safe and effective HIV/AIDS vaccine has been challenging in the almost three decades since the discovery of the disease. Recently, high-profile clinical trial failures have prompted great debate over the vaccine research, with some suggesting the need for a major focus on fundamental research, with fewer efforts on clinical trials.

The major challenges in the development of a preventive HIV/AIDS vaccine have been the extensive viral strain and sequence diversity, viral evasion of humoral and cellular immune responses, coupled with the lack of methods to elicit broadly reactive neutralizing antibodies and cytotoxic T cells. The challenge associated with delivery of any exogenous antigen (such as nanoparticles) to APCs, is that exogenous antigens require specialized ‘cross-presentation’ in order to be presented by MHC class I and activate CD8+cytotoxic T cells.

his requirement for cytosolic delivery of antigens and cross-presentation represents yet another hurdle for HIV intracellular antigen vaccine, but potentially an advantage of nanodelivery. Humoral responses (neutralizing antibodies produced by B cells) are generated to intact antigen presented on the surface for the virus, or nanoparticles, but these humoral responses typically require ‘help’ from CD4+ T cells, but rather both. Nanoparticles have potential as adjuvants and delivery systems for vaccines. Table 2 present the different approaches.

Table 2

Summary of nanotechnology developments for prevention of HIV/AIDS.

Type of preventive agent Antigen/adjuvant or drug Nanotechnology platform Development stage Refs.
Protein or peptide vaccine gp41, gp120, gp160, p24, Env, Gag, Tat Liposomes, nanoemulsion, MF59, PLA nanoparticles, poly(γ-glutamic acid) nanoparticles Preclinical [108111]
[119120]
[122125]
[128130]
DNA vaccine env, rev, gag, tat, CpG ODN Liposomes, nanoemulsion, PLA nanoparticles Preclinical [115,121]
Inactivated viral particle Inactivated HIV viral particle Polystyrene nanospheres Preclinical [126127]
Microbicides L-lysine dendrimer L-lysine dendrimer Phase I/II [136138]
PLGA nanoparticles
PSC-RANTES PLGA Preclinical [139]
siRNA Nanoparticles, lipids, cholesterol conjugation Preclinical [141144]

ODN: Oligonucleotides; PLA: Poly(D,L-lactide); PLGA: Poly(D,L-lacticide-co-glycolide).

Note:  to open the references in the table 2, please go to ref 1 in this post to see full ref info.

 

Summary

Nanotechnology can impact the treatment and prevention of HIV/AIDS with various innovative approaches. Treatment options may be improved using nanotechnology platforms for delivery of antiretroviral drugs. Controlled and sustained release of the drugs could improve patient adherence to drug regimens, increasing treatment effectiveness.

While there is exciting potential for nanomedicine in the treatment of HIV/AIDS, challenges remain to be overcome before the potential is realized. These include toxicity of nanomaterials, stability of nanoparticles in physiological conditions and their scalability for large-scale production. These are challenges general to all areas of nanomedicine and various works are underway to tackle them.

Another important consideration in investigating nanotechnology-based systems for HIV/AIDS is the economic aspect, as the hardest hit and most vulnerable populations reside in underdeveloped and economically poor countries. In the case of antiretroviral therapy, nanotherapeutics may increase the overall cost of treatment, reducing the overall value. However, if the nanotherapeutics could improve patient adherence by reducing dosing frequency as expected, and furthermore, if they can eradicate viral reservoirs leading to a sterile immunity, these advantages may effectively offset the added cost.

 

Ref:

1. Mamo T, Moseman EA., Kolishetti N., Salvadoe-Morales C., Shi J., Kuritzkes DR., Langer R., von-Adrian U and Farokhzad OF.   Emerging nanotechnology approaches for HIV/AIDS treatment and prevention. Nanomedicine (Lond) 2010; 5(2): 269-295.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2861897/

2. Merson MH. The HIV-AIDS pandemic at 25 – the global response. N Engl J Med.2006;354(23):2414–2417

3. Walensky RP, Paltiel AD, Losina E, et al. The survival benefits of AIDS treatment in the United States. J Infect Dis. 2006;194(1):11–19

4. Richman DD, Margolis DM, Delaney M, Greene WC, Hazuda D, Pomerantz RJ. The challenge of finding a cure for HIV infection. Science. 2009;323(5919):1304–1307)

5.Sax PE, Cohen CJ, Kuritzkes DR. HIV Essentials. Physicians’ Press; Royal Oak, MI, USA: 2007.

6. Lamers SL, Salemi M, Galligan DC, et al. Extensive HIV-1 intra-host recombination is common in tissues with abnormal histopathology. PLoS One. 2009;4(3):E5065.

7. Vyas TK, Shah L, Amiji MM. Nanoparticulate drug carriers for delivery of HIV/AIDS therapy to viral reservoir sites. Expert Opin Drug Deliv. 2006;3(5):613–628.

8. Amiji MM, Vyas TK, Shah LK. Role of nanotechnology in HIV/AIDS treatment: Potential to overcome the viral reservoir challenge. Discov Med. 2006;6(34):157–162

9. Lori F, Calarota SA, Lisziewicz J. Nanochemistry-based immunotherapy for HIV-1. Curr Med Chem. 2007;14(18):1911–1919

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

Genome-scale studies of cancer samples have begun to provide a global depiction of genetic alterations in human cancers, but the complexity and volume of data that emerge from these efforts have made dissecting the underlying biology of cancer difficult, and little is known about the functions of most of the candidates that emerge. For example, in studies of 489 primary high-grade serous ovarian cancer genomes, 1825 genes were identified as targeted by recurrent amplification events. Systematic approaches to study the function of genes in cancer cell lines, such as genome-scale pooled short hairpin RNA (shRNA) screens, offer a means to assess the consequences of the genetic alterations found in such genome characterization efforts. The comprehensive characterization of a large number of cancer genomes will eventually lead to a compendium of genetic alterations in specific cancers. Unfortunately, the number and complexity of identified alterations complicate endeavors to identify biologically relevant mutations critical for tumor maintenance because many of these targets are not amenable to manipulation by small molecules or antibodies. RNA interference provides a direct way to study putative cancer targets; however, specific delivery of therapeutics to the tumor parenchyma remains an intractable problem.

Recently an shRNA-based approach was used to find genes that are both overexpressed in human primary tumors and essential for the proliferation of ovarian cancer cells. This approach identified 54 overexpressed and essential genes in ovarian cancer and 16 genes in non–small cell lung cancer that required further validation in vivo. Furthermore, many of these candidates represent targets that are not amenable to antibody-based therapeutics or traditional small molecule approaches. Thus, if one envisions a discovery pipeline that begins with cancer genomes and ends with novel therapeutics, there is a bottleneck at the point of in vivo validation of novel targets. Achieving silencing in the epithelial cells in the tumor parenchyma is especially critical to study the genetic alterations of interest. RNA interference (RNAi) is a potentially attractive means to silence the expression of candidate genes in vivo, particularly for undruggable gene products. However, systemic delivery of small interfering RNA (siRNA) to tumors has been challenging, owing to rapid clearance, susceptibility to serum nucleases, and endosomal entrapment of small RNAs, in addition to their inherent inadequate tumor penetration. Tumor penetration is also a problem for the delivery of siRNA and shRNA, among other cargos, and is characterized by limited transport into the extravascular tumor tissue beyond the perivascular region. This low penetration is thought to arise from the combination of dysfunctional blood vessels that are poorly perfused and a high interstitial pressure, especially in solid tumors, in part due to dysfunctional lymphatics. The leakiness of tumor vessels partially counteracts the poor penetration [the so-called enhanced permeability and retention (EPR) effect], but the size dependence and variability of this property can limit its usefulness. Desmoplastic stromal barriers can further impede transport of therapeutics through tumors. A new class of tumor-penetrating peptides has been described recently, which home to several types of tumors and leverage a consensus R/KXXR/K C-terminal peptide motif [the C-end rule (CendR)] to stimulate transvascular transport and rapidly deliver therapeutic cargo deep into the tumor parenchyma. These peptides are tumorspecific, unlike canonical cell-penetrating peptides (CPPs) that do not display cell- or tissue-type specificity, and are able to improve the delivery of small molecules, antibodies, and nanoparticles. Despite their promise, this class of peptides has not been successfully co-opted for siRNA delivery, in part owing to the additional challenges of delivering oligonucleotides across cell membranes, out of endosomes, and into the cytosol to achieve gene silencing. Here, an siRNA delivery vehicle has been designed that was tumorpenetrating and modular, so it could be easily assembled in a single step to accommodate different payloads to various genes of interest. It can be envisaged that such a technology would enable a platform wherein novel targets can be identified by structural and functional genomics and subsequently rapidly credentialed both in vitro and in vivo. Followup studies could then identify the mechanism of action underlying the observations and establish (and ultimately prioritize) novel oncogenes as therapeutic targets. To achieve this goal, a systematic effort was combined to identify genes that are both essential and genetically altered in human cancer cell lines and tumors with the development and deployment of a novel tumor-specific and tissue-penetrating siRNA delivery platform.

Current genome characterization efforts will eventually provide insight into the genetic alterations that occur in most cancers and may define new therapeutic targets. However, most epithelial cancers harbor hundreds of genetic alterations as a consequence of genomic instability. For example, whereas recurrent somatic alterations occur in a small number of genes in high-grade ovarian cancers, ovarian cancer genomes are characterized by multiple regions of copy number gain and loss involving at least 1825 genes. This genomic chaos complicates efforts to identify biologically relevant mutations critical for tumor maintenance.

To isolate which recurrent genetic alterations are involved in cancer initiation, tumor maintenance, and/or metastasis, functional assays can be performed after systematic manipulation of the candidate oncogenes. Results from Project Achilles was combined, a large scale screening effort to identify genes essential for proliferation and survival in human cancer cell lines with genome characterization of high-grade ovarian cancers. Using this approach, an oncogene candidate  was identified, ID4, which was amplified in 32% of high-grade serous ovarian cancers. ID4 is overexpressed in a large fraction of high-grade serous ovarian cancers, and ovarian cancer cell lines that overexpress ID4 are highly dependent on ID4 for survival and tumorigenicity. Expression of ID4 at levels corresponding to those observed in patient-derived samples induced transformation of immortalized ovarian and FT epithelial cells.

In summary, a targeted TPN was developed capable of precisely delivering siRNA into the tumor parenchyma, and have combined this technology with large-scale methods to credential ID4 as an oncogene target in ovarian cancer. Because large-scale efforts to characterize all cancer genomes accelerate, this capability illustrates a path to identify genes that are altered in tumors, validate those that are critical to cancer initiation and maintenance, and rapidly evaluate in vivo the subset of such genes amenable to RNAi therapies and clinical translation. These observations not only credential ID4 as an oncogene in 32% of high-grade ovarian cancers but also provide a framework for the identification, validation, and understanding of potential therapeutic cancer targets.

Source References:

http://www.ncbi.nlm.nih.gov/pubmed/22896676

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