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Posts Tagged ‘Messenger RNA’

Transcript Dynamics of Proinflammatory Genes

Posted in Biological Networks, Gene Regulation and Evolution, Cell Biology, Signaling & Cell Circuits, Computational Biology/Systems and Bioinformatics, Genome Biology, International Global Work in Pharmaceutical, Pharmaceutical Industry Competitive Intelligence, tagged , , , , , on March 4, 2013| 3 Comments »

Transcript Dynamics of Proinflammatory Genes

Author: Larry H Bernstein, MD, FCAP

Transcript Dynamics of Proinflammatory Genes Revealed by Sequence Analysis of Subcellular RNA Fractions

DM Bhatt, A Pandya-Jones, Ann-Jay Tong, I Barozzi, MM Lissner, et al.
Cell 2012;150: 279–290

In addition to documenting the subcellular locations of coding and noncoding transcripts, the results provide a high-resolution view of the relationship between
  • defined promoter and chromatin properties and
    • the temporal regulation of diverse classes of coexpressed genes.
The data also reveal a striking accumulation of full-length yet incompletely spliced transcripts in the chromatin fraction, suggesting that
  • splicing often occurs after transcription has been completed,
  • with transcripts retained on the chromatin until fully spliced.
Summary
Macrophages respond to inflammatory stimuli by modulating the expression of hundreds of genes in
  • a defined temporal cascade,
  • with diverse transcriptional and posttranscriptional mechanisms contributing to the regulatory network.
We examined proinflammatory gene regulation in activated macrophages by
  • performing RNA-seq with fractionated chromatin-associated, nucleoplasmic, and cytoplasmic transcripts.
This methodological approach allowed us
  • to separate the synthesis of nascent transcripts from transcript processing and
  • the accumulation of mature mRNAs.
In addition to documenting the subcellular locations of coding and noncoding transcripts,
the results provide a high-resolution view of the relationship between
  • defined promoter and chromatin properties and
  • the temporal regulation of diverse classes of coexpressed genes.
The data also reveal a striking accumulation of full-length yet incompletely spliced transcripts in the chromatin fraction, suggesting that
  • splicing often occurs after transcription has been completed, with transcripts retained on the chromatin until fully spliced.

Two independent experiments were performed with lipid A-stimulated bone marrow-derived macrophages. The two experiments made use of different macrophages prepared from different mice, several months apart.(A) Pearson pair-wise correlation values (R) derived from an analysis of greater than 500 lipid A-induced genes (>5-fold induced) are shown. Each time point from the first experiment, A, was compared to every other time point from the same experiment and from the second experiment, B.(B) Hierarchical clustering of the R-values from panel A was performed. This analysis reveals that, when only induced genes are considered, each time point from each experiment correlates more closely with the corresponding time point from the other experiment than with any of the other time points from either experiment.(C)

This analysis reveals that, when the transcript levels of expressed genes are compared,
  • each time point from a given experiment correlates with the same time point from the independent experiment.
The results reveal close correlations between all time-points from both experiments, presumably because genes that are consistently unexpressed (i.e., not counted in B) are contributing to the high degree of correlation. Nevertheless, the time points of each independent experiment still have the highest degree of correlation with each other.
Hierarchical clustering of the R values from panel D was performed. As with other clusterings, each sample clusters with its cognate time point in the independent experiment
Highlights
► Coding and noncoding transcripts exhibit characteristic subcellular distributions
► The most potently induced genes favor promoters with low CpG content
► Full-length, incompletely spliced transcripts accumulate on the chromatin
► Delayed transcript release may reflect a requirement for the completion of splicing
Eukaryotic transcription overview

Eukaryotic transcription overview (Photo credit: Allen Gathman)

English: Nucleosome structure.

English: Nucleosome structure. (Photo credit: Wikipedia)

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When Clinical Application of miRNAs?

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Computational Biology/Systems and Bioinformatics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Pharmaceutical Industry Competitive Intelligence, Pharmacogenomics, Scientist: Career considerations, Technology Transfer: Biotech and Pharmaceutical, tagged , , , , , , , on March 4, 2013| 1 Comment »

When Clinical Application of miRNAs?

Author: Larry H Bernstein, MD, FCAP

Clinical Application of miRNAs Remains a Ways Off
When its time comes, prognostic tests will be first.
Patricia Fitzpatrick Dimond, Ph.D             GEN Insight & Intelligence

It’s still early to tell how well microRNAs (miRNAs) will prove clinically useful.  Preclinical research findings indicate their central role in controlling cellular pathways.
This novel class of nucleotides, about 20–25 nucleotides in length, affects gene expression by interacting with messenger RNAs. But unlike Small Interfering RNA,  siRNAs, miRNAs are encoded in the human genome and function as natural regulators of global gene expression.
Each of the more than 1,500 encoded miRNAs appears to regulate the expression of tens to hundreds of different genes, on-off switches, regulating multiple cellular functions including
  • growth and
  • proliferation.
miRNAs regulate the translation of genes through
  • sequence-specific binding to mRNA.

Depending on the degree of sequence complimentarity, they can inhibit

  • the translation and/or degradation of their target mRNAs.

Because of their role in controlling “suites” of genes and, ultimately, pathway function, these molecules have attracted considerable scientific and investor interest in the control of diseases ranging from cardiovascular diseases to cancer.

miRNAs target numerous biomolecules that play a role in carcinogenesis,
  • functioning as both tumor promoters or suppressors.
Aberrant expression of miRNAs
  • correlates with the development and progression of tumors;

inhibition of their expression can

  1. modulate the cancer phenotype,
  2. suggesting their potential as anticancer drug targets.

Further supporting their potential use as drug targets, miRNA expression profiling in a variety of tissue, cell, and disease types has revealed

  • a “miRNA signature” specific to those cell types or disease states.
Research

Carlo Croce, M.D., director of Human Cancer Genetics at the Ohio State University Comprehensive Cancer Center, and colleagues reported that

  • they identified a 9-miRNA signature that differentiated invasive (IDC) from in situ carcinoma (DCIS).

In studying the global changes of the miRNA repertoire along the transitions defining breast cancer progression, the scientists found that

  1. let-7d, miR-210, and miR-221 were downregulated in the in situ and
  2. upregulated in the invasive transition, thus
  3. featuring an expression reversal along the cancer progression path.
  4. in addition,  miRNAs for overall survival and time to metastasis.
Dr. Croce posed that targeted prognostic tests using miRNA will be available within the next two years.
  • the problem he suggests is validating the signature in a large enough cohort of patients.
They used deep sequencing, an extremely sensitive approach to the determination of miRNAs because you count the molecules. Studies have used microarrays and RT-PCR, and his group used general microarrays and validated RT-PCR.  Their method avoided the possibility of artifacts (by counting).  Sequencing permits counts of molecules to provide good data.

John F. McDonald, Ph.D., CSO Ovarian Cancer Institute, and colleagues at the Georgia Institute of Technology

  1. separately transfected two miRNAs (miR-7 and miR-128) into the ovarian cancer cell line (HEY) and
  2. then monitored global changes in gene expression levels.
  • 20% of the changes in expression patterns of hundreds to thousands of genes
  • could be attributed to direct miRNA–mRNA interactions, but
  • the majority of the changes were indirect,
involving the downstream consequences of miRNA-mediated changes in regulatory gene expression.
The pathways most significantly affected by miR-7 transfection, are involved with
  1. cell adhesion and
  2. developmental networks previously associated with epithelial-mesenchymal transitions and
  3. processes linked with metastasis.

http://www.genengnews.com/insight-and-intelligenceand153/clinical-application-of-mirnas-remains-a-ways-off/77899650/

ATVB in Focus
MicroRNAs 
From Basic Mechanisms to Clinical Application in Cardiovascular Medicine
Christian Weber, Ludwig-Maximilians-Univ and German Centre for Cardiovasc Res, Munich, Germany
Arterioscler Thromb Vasc Biol. 2013;33:168-169.  http://dx.doi.org/10.1161/ATVBAHA.112.300920
MicroRNAs (miRs) are small noncoding RNAs (≈23 nucleotides) that regulate gene expression at a posttranscriptional level by degradation or translational inhibition of target mRNAs. Initially discovered as regulators of development in plants, worms, and fruitflies,
miRs are emerging as
  • pivotal modulators of cardiovascular biology and disease in mice and men.
Besides a cell-specific transcription factor profile,
  • cell-specific miR-regulated gene expression is integral to cell fate and activation decisions.
Thus, the cell types involved in
  • atherosclerosis,
  • vascular disease, and
    • its myocardial sequelae may be
  • differentially regulated by distinct miRs, thereby
    • controlling highly complex processes
      • smooth muscle cell phenotype and
      • inflammatory responses of endothelial cells or macrophages.
The generation of mature miR strands requires several steps of processing of the primary miR gene transcript, including
  • cleavage of the terminal loop of miR-precursors by the RNase III enzyme,Dicer, to produce miR duplexes.
Although either strand of the miR duplex can be stably associated with an Argonaute (Ago) family protein,
  • preferential loading of a specific strand (ie, the guide strand) onto the miR-induced silencing complex (RISC) is common.
The strand that is not loaded into the RISC (ie, the passenger strand or miR*) is typically degraded.3 Strand selection may be tissue-specific, and an accumulation observed for both strands implies that
  • each strand can separately enter the silencing complex.4
Because of the often imperfect complementary binding of the miR seed sequence to the mRNA recognition element,
  • an individual miR can affect the expression of hundreds of target mRNAs.
http://atvb.ahajournals.org/content/33/2/168.extract

Life’s Tiniest Architects Pinpointed by Yale Researchers
If a genome is the blueprint for life, then the chief architects are
  • tiny slices of genetic material that orchestrate how we are assembled and function.
The study pinpoints the molecular regulators of epigenetics — the process by which unchanging genes along our DNA are switched on and off at precisely right time and place.
“Our genome is like a landscape with lakes, mountains, and rivers, but it is not yet a community or a city full of buildings,” said Haifan Lin, director of the Yale Stem Cell Center and senior author of the study. “What this system does is decide where and when to send out the masons, carpenters, and electricians to build a city or a community.”
In the past 20 years, scientists have discovered that some proteins, called epigenetic factors, traverse the static genome and turn the genes on or off. The staggering number of potential combinations of active and inactive genes explains why a relatively small number of genes can carry out such a wide range of functions.
What guides these epigenetic factors to their target? The answer:

  • specialized RNAs called piRNAs.
In the latest study, the Yale team discovered that
  • piRNAs guide epigenetic factors to numerous sites throughout the genome of the fruit fly Drosophila, where
    • these switches  work to turn genes on or off.
The dramatic change in gene expression patterns found illustrated
  • piRNAs key role in coordinating biological activity.
“This is the first major mechanism discovered that controls where epigenetic factors —the gene switches — are to be placed in the genome,” Lin said.
Several types of cancers appeared to be
  • triggered when the wrong kinds of piRNAs guide epigenetic factors to activate the wrong genes.
Blocking the action of these piRNAs should become a new opportunity to treat cancers, Lin said.
Xiao A. Huang and Hang Yin of Yale are co-lead authors of the paper.
The research was funded by a National Institutes of Health Pioneer Award to Haifan Lin and a grant from Connecticut Stem Cell Research Fund to
Lin and former Yale professor and co-author Michael Snyder, now of Stanford University.
English: A diagram showing at which stages in ...

English: A diagram showing at which stages in the DNA-mRNA-protein pathway expression can be controlled. (Photo credit: Wikipedia)

Virus-Encoded microRNAs

Virus-Encoded microRNAs (Photo credit: AJC1)

English: A Tet-ON doxycycline inducible transg...

English: A Tet-ON doxycycline inducible transgene expression system. (Photo credit: Wikipedia)

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Mechanism involved in Breast Cancer Cell Growth: Function in Early Detection & Treatment

Posted in Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Chemical Genetics, Genome Biology, Genomic Testing: Methodology for Diagnosis, Technology Transfer: Biotech and Pharmaceutical, tagged , , , , , on January 17, 2013| 9 Comments »

Reporter: Aviva Lev-Ari, PhD, RN

Press Release 16 January, 2013

Dr. Rotem Karni and PhD student Vered Ben Hur at the Institute for Medical Research Israel-Canada of the Hebrew University,

Dr. Rotem Karni and PhD student Vered Ben Hur at the Institute for Medical Research Israel-Canada of the Hebrew University,

Screen Shot 2021-07-19 at 7.20.33 PM

Word Cloud By Danielle Smolyar

Mechanism involved in breast cancer cell growth provides opening for early detection, treatment


Researchers at the Hebrew University Institute of Medical Research Israel-Canada have discovered a new mechanism by which breast cancer cells switch on their aggressive cancerous behavior. The discovery provides a valuable marker for the early diagnosis and follow-up treatment of malignant growths.

In normal cell reproduction, a process of RNA splicing takes place. RNA (ribonucleic acid) is a family of large biological molecules that performs multiple, vital roles in the coding, decoding, regulation and expression of genes. Cellular organisms use messenger RNA, called mRNA, to convey genetic information that directs synthesis of specific proteins.

RNA splicing is similar to the process of editing a movie. In this process, the information needed for the production of a mature protein is encoded in segments called exons (which like important movie scenes are needed in a specific sequence in order to understand the movie). In the splicing process, the non-coding segments of the RNA (unimportant scenes, called introns) are spliced from the pre-mRNA and the exons are joined together.

Alternative splicing is when a specific ”scene” (or exon) is either inserted or deleted from the movie (mRNA), thus changing its meaning. Over 90 percent of the genes in our genome undergo alternative splicing of one or more of their exons, and the resulting changes in the proteins encoded by these different mRNAs are required for normal function. In cancer, the normal
process of alternative splicing is altered, and ”bad” protein forms are generated that aid cancer cell proliferation and survival.

In a study published in the online edition of Cell Reports, conducted by Ph.D. student Vered Ben Hur in the lab of Dr. Rotem Karni at the Institute for Medical Research Israel-Canada of the Hebrew University, the researchers found that breast cancer cells change the alternative splicing of an important enzyme, called S6K1, which is a protein involved in the transmission of information into the cell.

The researchers found that when this happens, breast cancer cells start to produce shorter versions of this enzyme and that these shorter versions transmit signals ordering the cells to grow, proliferate, survive and invade other tissues. On the other hand, the researchers found that the long form of this protein acts as a tumor suppressor that protects normal cells from becoming cancerous.

There are several medical implications emanating from the research, say the researchers. One of them is the use of the newly discovered short forms of S6K1 as a diagnostic marker for the detection of breast cancer. Several new anticancer drugs, which have entered the clinic recently, can inhibit the cancerous activity of the short forms of S6K1. Thus, the detection of these new forms can predict the efficacy of these drugs to treat cancer patients.

These implications were recently submitted as a patent application by Yissum, the technology transfer company of the Hebrew University. Another future application will be to ”reverse” the alternative splicing of S6K1 in cancer cells back to the normal situation as a novel anti-cancer therapy. The research group of Dr. Karni is actively engaged in this effort.

SOURCE:

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BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, Chemical Genetics, Molecular Genetics & Pharmaceutical, tagged , , , , , , , on December 4, 2012| 4 Comments »

BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

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

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Word Cloud By Danielle Smolyar

Interest in BRCA1 stems from its role as a tumour suppressor in breast and ovarian cancer. Intensive research in BRCA1 has revealed little about its specific role in cancer; rather, this protein has been implicated in a multitude of important cellular processes.

The diverse biochemical activities of BRCA1 combine to protect the genome from damage.

New data reveal that BRCA1

BRCA1 functions in several processes, but it is unclear how these relate to the BRCA1 requirement in all cell types. Similar to the p53 tumour suppressor, BRCA1 activates genes encoding the DNA-repair response. Unlike p53, BRCA1 also has a direct role in the repair process.

According to the earlier suggested model, BRCA1–BARD1 functions in genome surveillance by scanning active genes in association with the holo-pol, and when the elongating transcription complex encounters DNA lesions, BRCA1 initiates a repair response. It is interesting to note that a BRCA1-binding cofactor, COBRA1, which regulates BRCA1 function in a chromatin decompression assay, has been found to be a required subunit of a complex that regulates transcription elongation.

When damage is encountered on the DNA template, the lesion could be corrected by transcription-coupled repair (step 1), a known BRCA1 function. Alternatively, some types of damage might require that the polymerase be removed to effect repair. Since the polymerase synthesizing mRNA on a DNA template is quite stably bound, it has been hypothesized that BRCA1 would then ubiquitinate the polymerase signaling its degradation (step 2).

Although current evidence does not implicate BRCA1 in this process, the polymerase is ubiquitinated and degraded following DNA damage. The residual BRCA1 complex might remain bound to the DNA lesion.

BRCA1 has been found to bind DNA cruciforms and three-way junctions, such as might occur at damage sites (step 3). This bound BRCA1 would then recruit repair factors, such as the RAD50-containing complex, which would then mend the lesion (steps 4 and 5).

One might infer from the recruitment of the H2AX kinase to sites in which BRCA1 is bound to DNA that this surveillance of the template by transcription results in BRCA1-dependent degradation of the transcription apparatus and recruitment of the H2AX kinase to nucleate the assembly of a repair focus.

Although there is no yeast homolog for BRCA1, perhaps a analogous pathway is conserved in this organism, mediated by a transcription elongation factor that is genetically linked in this pathway to holo-pol components.

The key cellular functions assigned to BRCA1 are numerous. BRCA1 can interact with many cellular proteins and pathways, but how these many interactions address the key questions of required ubiquitous function and tumour suppressing breast and ovarian cell function are unclear. These diverse activities of BRCA1 may be linked in a single pathway, or BRCA1 might function in multiple nuclear processes.

Source References:

http://www.ncbi.nlm.nih.gov/pubmed?term=The%20multiple%20nuclear%20functions%20of%20BRCA1%3A%20transcription%2C%20ubiquitination%20and%20DNA%20repair

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Leptin and Puberty

Posted in Population Health Management, Genetics & Pharmaceutical, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, Reproductive Biology & Bio Instrumentation, tagged , , , , , , , on November 5, 2012| 5 Comments »

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

It is well established that food restriction delays pubertal onset, whereas refeeding abolishes this delay. In addition, murine and human genetic models of leptin deficiency fail to enter puberty, and treatment with leptin can establish a pulsatile secretory pattern of gonadotropins that is characteristic of early puberty. The female transgenic skinny mouse, which is an in vivo model of chronic hyperleptinemia in the absence of adipose tissue, enters puberty precociously. Data regarding the effects of leptin administration on pubertal onset are controversial. It has been shown that intracerebroventricular leptin administration prevents the delay in vaginal opening induced by chronic food restriction in the rat. By contrast, it has been found that artificially raised leptin levels are not sufficient to abolish the delay of pubertal onset caused by food deprivation. Thus, the question arises whether leptin might be a ‘permissive factor’ (tonic mediator), whose concentration above a certain threshold is required for pubertal onset, or a ‘trigger’ (phasic mediator) that determines the pubertal spurt through a rise in serum concentration at an appropriate time of development.

The temporal correlation between increases in leptin concentration and the initiation of LH pulsatility over the peripubertal period has been studied in several species. In men it has been shown that leptin levels rise by 50% before the onset of puberty, and decrease to baseline after the initiation of puberty. Other cross-sectional studies showed that age has a significant effect on serum leptin concentrations through prepuberty into early puberty. It has been reported repeatedly that there are no significant changes in leptin levels over the peripubertal period in male rhesus macaques; however, more recent studies performed in castrated male monkeys showed that nocturnal levels of leptin increase just before the nocturnal prepubertal increase in pulsatile LH release.

A possible explanation for such contrasting reports in monkeys could be the sampling of nocturnal rather than diurnal blood. Indeed, in primates, prepubertal changes in nocturnal LH release occur approximately five months before diurnal variations. Another reason might be the use of different models: agonadal monkeys were treated with intermittent exogenous GnRH to sensitize the pituitary to endogenous GnRH, thus magnifying the LH release independently from gonadal influences. In the same study, the leptin rise was accompanied by a sustained increase in nocturnal GH and IGF-I concentrations before the onset of puberty, which is defined as the increase in nocturnal pulsatile LH secretion. It is not clear whether one of the two metabolic signals has a predominant role or whether both act in concert. Indeed, it has been reported that the maximum increase in GH and leptin occurs simultaneously, about 10–30 days before the onset of puberty. However, these conclusions were based on results from a study that used castrated animals, which in the strictest sense do not undergo puberty. Thus, it remains to be clarified whether the same mechanisms that result in the onset of the pubertal rise in LH secretion in castrated animals are also responsible for the reactivation of the HPG axis in intact animals.

The sexual dimorphism in leptin concentrations becomes evident after puberty. In males, leptin levels rise throughout childhood, reach a peak in the early stages of puberty and then decline, whereas they increase steadily during pubertal development in females. Consequently, leptin levels are three to four times higher in females than in males. The reason for this postpubertal sexual dimorphism in leptin levels is not clear. After puberty, serum testosterone and testicular volume are inversely related to leptin levels in males, whereas in females, when adjusted for adiposity indexes, estradiol is directly correlated with leptin levels. These observations indicate that androgens and estradiol might account, at least in part, for the gender differences in circulating leptin levels. This is also supported by in vitro studies which show that androgens and estrogens inhibit and stimulate leptin expression and release from human adipocytes in culture, respectively.

Thus, puberty represents a turning point in the sexual dimorphic relationships between the HPG axis and leptin by determining the steroid milieu that leads to a different regulation of leptin secretion in the sexes.

Source References:

http://www.sciencedirect.com/science/article/pii/S1043276000003520#

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Commentary on Dr. Baker’s post “Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes”

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Molecular Genetics & Pharmaceutical, tagged , , , , , , , , , , , , , , , , , , , , on October 3, 2012| 6 Comments »

 

Author and Curator: Ritu Saxena, Ph.D.

A recent post by Dr. Margaret Baker entitled “Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes” talks about how the ENCODE project is revealing new insights into the functions of non-coding region of the human genome previously labeled as “junk DNA”. MicroRNA or miRNA, which as stated by Dr. Baker, “are among the non-gene encoding sequences in the genome and have been shown to play a major post-transcriptional role in expression of multiple genes.”

The post has touched upon several aspects of miRNA including origin, function, and mechanism of action. This commentary is an extension of Dr. Baker’s post, expanding upon the mechanism of action of miRNAs along with their role in potential disease therapy.

microRNA: Revisiting the past

MicroRNA were not discovered long back, infact, it was in 1998 when the presence of the non-coding RNAs that could be involved in switching ‘on’ and ‘off’ of certain genes. In the last decade, 2006 Nobel Prize for medicine or physiology was awarded to scientists Andrew Fire and Craig Mello for their discovery of this new role of RNA molecules.

A breakthrough research was published in the September 2010 issue of Nature journal, stating that mammalian microRNAs predominantly act by decreasing the levels of target mRNA. Mammalian microRNAs predominantly act to decrease target mRNA levels. miRNAs were initially thought to repress protein output without changes in the corresponding mRNA levels. Guo et al challenged the previous notion of ‘translational repression’ and concluded on the basis of their experimental results that ‘mRNA-destabilization’ scenario for the major part is responsible for the repression in protein expression via miRNAs. Authors utilized the method of ‘ribosome profiling’ to measure the overall effects of miRNA on protein production and then compared these to simultaneously measured effects on mRNA levels. Ribosome profiling prepares maps that exact positions of ribosomes on transcripts after nucleases chew upon the exposed part of transcripts that are not covered by ribosomes. MiR-1 and miR-155 were introduced into the HeLa-cell line. Both of these miRNAs are not  normally expressed in HeLa cells. Another miRNA used was mir-223 which is expressed in significant amounts in neutrophils. The reason for choosing the set of these miRNAs was that they had already been shown to repress protein levels via proteomics research. It was deciphered that miRNA-mediated repression was similar regardless of target expression level and further stated that “for both ectopic and endogenous miRNA regulatory interactions, lowered mRNA levels account for lowered mRNA levels accounted for most for most (>/=84%) of the decreased protein production.” These results show that changes in mRNA levels closely reflect the impact of miRNAs on gene expression and indicate that destabilization of target mRNAs is the predominant reason for reduced protein output.

Authors concluded that the discovery “will apply broadly to the vast majority of miRNA targeting interactions. If indeed general, this conclusion will be welcome news to biologists wanting to measure the ultimate impact of miRNAs on their direct regulatory targets.”

Since then and even before the paper was published, several other miRNAs and their roles have been discovered. Information on miRNAs has been consolidated in a database that can be accessed online at http://www.mirbase.org/

microRNA: From bench to bedside

Scientific community had speculated the role of non-coding RNAs in disease treatment right after their discovery. One such study demonstrating the utilization of microRNA for Cancer treatment was published in the September 2010 issue of the journal Nature Medicine. miR-380-5p represses p53 to control cellular survival and is associated with poor outcome inMYCN-amplified neuroblastoma

The p53 gene is known as a tumor suppressor gene and its inactivation has been associated in some cancers such as neuroblastoma. The study reported that microRNA-380 (miR-380) was able to repress the expression of p53 gene in cancer patients causing uninhibited cell survival and proliferation. The research group was able to decrease the tumor size in vivo in a mouse model of the neuroblastoma by delivering miR-380 antagonist. The researchers also observed that the inhibition of endogenous miR-380 in embryonic stem or neuroblastoma cells resulted in induction of p53, and extensive apoptotic cell death.

Thus, the success of miR antagonist for decreasing tumor size speaks of the effectiveness of miR as a potential therapeutic target for cancer treatment.

In conclusion, as stated by Dr. Baker in her post, “the miRNA data for tissues and specific cell types involved in disease pathology form a new approach to either detecting or possibly correcting gene (coding or non-coding) dysregulation. miRNA mimics and anti-miRNA agents are being developed as new therapeutic modalities.”

Reference:

Pharmaceutical Intelligence post, Author, Dr. Margaret Baker: Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes

http://pharmaceuticalintelligence.com/2012/09/24/junk-dna-codes-for-valuable-mirnas/

 

Research articles: Mammalian microRNAs predominantly act to decrease target mRNA levels

miR-380-5p represses p53 to control cellular survival and is associated with poor outcome inMYCN-amplified neuroblastoma

Expert reviews- miRNA and Cancer treatment

 

News briefs: http://ygoy.com/2010/10/02/new-treatment-for-junk-dna-induced-cancers-discovered/

http://www.evolutionnews.org/2010/10/micrornas–once_dismissed_as_j038861.html

 

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Calcium Dependent NOS Induction by Sex Hormones: Estrogen

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, Chemical Genetics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Medical and Population Genetics, Molecular Genetics & Pharmaceutical, Nitric Oxide in Health and Disease, Personalized and Precision Medicine & Genomic Research, Pharmaceutical R&D Investment, Population Health Management, Genetics & Pharmaceutical, Reproductive Biology & Bio Instrumentation, Technology Transfer: Biotech and Pharmaceutical, tagged , , , , , , , , , on October 3, 2012| 5 Comments »

Calcium Dependent NOS Induction by Sex Hormones: Estrogen

Reporter and Curator:  Sudipta Saha, Ph.D.

Nitric oxide (NO) synthases (NOSs) constitute a family of isozymes that catalyze the oxidation of L-arginine to NO and citrulline. First identified in the vascular endothelium, NO synthesis has subsequently been shown to play important roles in:

  • the regulation of vascular and gastrointestinal tone,
  • in cell-mediated cytotoxicity against bacteria and tumors, and
  • in a variety of central and peripheral nervous system activities.

NOSs can be divided into three functional classes based on their sensitivity to calcium.

  • The cytokine- or bacterial product-inducible isoenzyme iNOS binds calmodulin tightly at resting intracellular calcium concentrations.
  • The constitutive forms, isozymes eNOS (originally described in endothelial cells) and
  • nNOS (originally described in neuronal tissue), bind calmodulin in a reversible and calcium-dependent fashion.

The mechanisms by which their synthesis is controlled are unknown. The cDNA species encoding the rat, mouse, and human nNOS, the human and bovine eNOS, and iNOS from several species and cell types have been cloned and sequenced. The three human isozymes characterized to date are distinct, with their deduced protein sequences showing only 50-60%o amino acid identity. nNOS, which in rats and humans localizes to neurons in the central and peripheral nervous system and colocalizes with NADPHdiaphorase activity, has also been shown to be widely distributed in several non-neuronal tissues including human skeletal muscle.

It had been thought that both nNOS and eNOS were purely constitutive enzymes, although studies suggest eNOS may be induced by shear stress. Studies demonstrate that these NOSs can be induced in several tissues during pregnancy and in nonpregnant female and male animals by estradiol and that in skeletal muscle it is accompanied by an increase in NOS-specific mRNA.

Evidences emerging from various laboratories showed that there is an increase in the release of NO from the vasculature during pregnancy. Furthermore, treatment of pregnant animals at the end of gestation with tamoxifen reduced NOS activity in the cerebellum, an organ where tamoxifen acts as a pure estrogen-receptor antagonist. Thus, the increase in calcium-dependent NOS activity during pregnancy is mediated by estrogen. This conclusion is supported by the fact that treatment of nonpregnant females and male animals with estradiol also increased calcium-dependent NOS activity in all tissues studied.

Interestingly, testosterone treatment also increased cerebellar NOS activity without affecting other tissues. However, testosterone may increase brain NOS by directly binding estrogen receptors as has been reported. Furthermore, the cerebellum was the only tissue in the male to respond to a 5-day course of estradiol, suggesting that it may have a larger number and/or a greater availability of estrogen receptors than other tissues. In addition, the brain is rich in aromatase, which converts testosterone into estradiol. This, together with the observation that progesterone does not induce NOS, indicates that the induction of both nNOS and eNOS is specific for estrogen and not a characteristic of all sex steroids. These experiments do not exclude the possibility that the addition of progesterone might modify the estradiol effect.

The increases in NOS activity are the result of augmented enzyme synthesis (enzyme induction) since they are accompanied by increases in the specific mRNAs for both eNOS and nNOS. It is not, however, possible to tell whether the increases in mRNA are caused by an upregulation of mRNA synthesis (transcriptional induction) or decreased mRNA breakdown.

Although calcium-dependent NOS activity was increased by estradiol in tissues obtained from both female and male guinea pigs, a longer duration of treatment was necessary in the male. The most likely explanation for this observation is that the number or availability of estrogen receptors is initially too low in most tissues of the male and requires a period of estrogen priming. Although other factors may play a role, the duration of exposure may well explain the observation that the effect of pregnancy on NOS-specific mRNA is greater than estradiol alone.

The observation that estradiol induces calcium-dependent NOSs has several important implications:

  • An increase in release of NO from the endothelium would decrease vascular tone and contractility, events that are characteristic in pregnancy.
  • Heterogeneity among tissue endothelium regarding the effects of estrogen on basal NO release could explain the selective redistribution of maternal cardiac output to organs important for a successful pregnancy.
  • Consistent with this possibility is the observation that the effect of pregnancy on endothelium-derived NO is greatest in the uterine artery, followed by the mesenteric artery and then renal arteries.
  • An alternative hypothesis to explain the adaptation of smooth muscle to pregnancy is that it is caused by prostacyclin. Prostacyclin is increased during pregnancy and contributes to the observed reduced contractility of the ovine uterine artery to angiotensin II.

However, estradiol does not increase the synthesis of prostacyclin by the endothelium, nor does inhibition of prostacyclin synthesis prevent the effects of pregnancy on smooth muscle. In addition, both the incidence of esophageal reflux and the gastrointestinal transit time are increased during pregnancy. Although this phenomenon has previously been attributed to a direct effect of progesterone, NO is a powerful dilator of the gastrointestinal smooth muscle. If the increase in NOS activity observed in the esophagus applies to the bowel, enhanced NO might be the mechanism underlying both increased esophageal reflux and transit time.

The biological signifcance of an estradiol-dependent increase in the NOS in the central nervous system is of great interest and deserves further investigation. Furthermore, an estradiol-mediated increase in NOS in the vasculature could be the mechanism whereby premenopausal women are protected from coronary artery disease since increased NOS may slow the development of atherosclerosis and reduce the contractile response to acute thrombosis. Finally, the induction of calcium-dependent NOS enzymes by estradiol suggests that the present classification of this family of enzymes into constitutive and inducible types needs to be revised, since eNOS and nNOS enzymes at least are both constitutive and inducible.

Source References:

http://www.ncbi.nlm.nih.gov/pubmed?term=Calcium%20dependent%20NOS%20induction%20by%20sex%20hormones

Other research published on Nitric Oxide on this Scientific Web Site include the following:

Nitric Oxide in bone metabolism July 16, 2012

Author: Aviral Vatsa PhD, MBBS

http://pharmaceuticalintelligence.com/2012/07/16/nitric-oxide-in-bone-metabolism/?goback=%2Egde_4346921_member_134751669

 

Nitric Oxide production in Systemic sclerosis July 25, 2012

Curator: Aviral Vatsa, PhD, MBBS

http://pharmaceuticalintelligence.com/2012/07/25/nitric-oxide-production-in-systemic-sclerosis/?goback=%2Egde_4346921_member_138370383

Nitric Oxide Signalling Pathways August 22, 2012 by

Curator/ Author: Aviral Vatsa, PhD, MBBS

http://pharmaceuticalintelligence.com/2012/08/22/nitric-oxide-signalling-pathways/?goback=%2Egde_4346921_member_151245569

Nitric Oxide: a short historic perspective August 5, 2012

Author/Curator: Aviral Vatsa PhD, MBBS

http://pharmaceuticalintelligence.com/2012/08/05/nitric-oxide-a-short-historic-perspective-7/

 

Nitric Oxide: Chemistry and function August 10, 2012

Curator/Author: Aviral Vatsa PhD, MBBS

http://pharmaceuticalintelligence.com/2012/08/10/nitric-oxide-chemistry-and-function/?goback=%2Egde_4346921_member_145137865

Nitric Oxide and Platelet Aggregation August 16, 2012 by

Author: Dr. Venkat S. Karra, Ph.D.

http://pharmaceuticalintelligence.com/2012/08/16/no-and-platelet-aggregation/?goback=%2Egde_4346921_member_147475405

 

The rationale and use of inhaled NO in Pulmonary Artery Hypertension and Right Sided Heart Failure August 20, 2012

Author: Larry Bernstein, MD

http://pharmaceuticalintelligence.com/2012/08/20/the-rationale-and-use-of-inhaled-no-in-pulmonary-artery-hypertension-and-right-sided-heart-failure/

Nitric Oxide: The Nobel Prize in Physiology or Medicine 1998 Robert F. Furchgott, Louis J. Ignarro, Ferid Murad August 16, 2012

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/08/16/nitric-oxide-the-nobel-prize-in-physiology-or-medicine-1998-robert-f-furchgott-louis-j-ignarro-ferid-murad/

 

Coronary Artery Disease – Medical Devices Solutions: From First-In-Man Stent Implantation, via Medical Ethical Dilemmas to Drug Eluting Stents August 13, 2012

Author: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/08/13/coronary-artery-disease-medical-devices-solutions-from-first-in-man-stent-implantation-via-medical-ethical-dilemmas-to-drug-eluting-stents/

Cardiovascular Disease (CVD) and the Role of agent alternatives in endothelial Nitric Oxide Synthase (eNOS) Activation and Nitric Oxide Production July 19, 2012

Curator and Research Study Originator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/07/19/cardiovascular-disease-cvd-and-the-role-of-agent-alternatives-in-endothelial-nitric-oxide-synthase-enos-activation-and-nitric-oxide-production/

Macrovascular Disease – Therapeutic Potential of cEPCs: Reduction Methods for CV Risk

An Investigation of the Potential of circulating Endothelial Progenitor Cells (cEPCs) as a Therapeutic Target for Pharmacological Therapy Design for Cardiovascular Risk Reduction: A New Multimarker Biomarker Discovery

Curator: Aviva Lev-Ari, PhD, RN, July 12, 2012

http://pharmaceuticalintelligence.com/2012/07/02/macrovascular-disease-therapeutic-potential-of-cepcs-reduction-methods-for-cv-risk/

 

Bone remodelling in a nutshell June 22, 2012

Author: Aviral Vatsa, Ph.D., MBBS

http://pharmaceuticalintelligence.com/2012/06/22/bone-remodelling-in-a-nutshell/

Targeted delivery of therapeutics to bone and connective tissues: current status and challenges – Part 1

AuthorL Aviral Vatsa, PhD, September 23, 2012

http://pharmaceuticalintelligence.com/2012/09/23/targeted-delivery-of-therapeutics-to-bone-and-connective-tissues-current-status-and-challenges-part-i/

Calcium dependent NOS induction by sex hormones: Estrogen

Curator: S. Saha, PhD, October 3, 2012

http://pharmaceuticalintelligence.com/2012/10/03/calcium-dependent-nos-induction-by-sex-hormones/

 

Nitric Oxide and Platelet Aggregation

Author V. Karra, PhD, August 16, 2012

http://pharmaceuticalintelligence.com/2012/08/16/no-and-platelet-aggregation/

Bystolic’s generic Nebivolol – positive effect on circulating Endothelial Progenitor Cells endogenous augmentation

Curator: Aviva Lev-Ari, PhD, July 16, 2012

http://pharmaceuticalintelligence.com/?s=Nebivolol

 

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Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes

Posted in Biomarkers & Medical Diagnostics, Bone Disease and Musculoskeletal Disease, Cardiovascular Pharmacogenomics, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, Chemical Genetics, Computational Biology/Systems and Bioinformatics, Genome Biology, Genomic Testing: Methodology for Diagnosis, Glycobiology: Biopharmaceutical Production, Pharmacodynamics and Pharmacokinetics, Liver & Digestive Diseases Research, Medical and Population Genetics, Molecular Genetics & Pharmaceutical, Nutrigenomics, Nutrition, Personalized and Precision Medicine & Genomic Research, Systemic Inflammatory Response Related Disorders, Technology Transfer: Biotech and Pharmaceutical, Uncategorized, tagged , , , , , , , , , , on September 24, 2012| 11 Comments »

Author: Margaret Baker, PhD, Registered Patent Agent

The Encyclopedia of DNA Elements (ENCODE) Project was launched in September of 2003. In 2007 the ENCODE project was expanded to study the entire human genome, Genome-wide association studies or GWAS, and published a Nature paper entitled “An integrated encyclopedia of DNA elements in the human genome,” this month also all data are available at http://genome.ucsc.edu/ENCODE/.  Novel functional roles have been discovered for both transcribed and non-transcribed portions of DNA.  See several articles and commentary in Science 7 September 2012: Vol. 337 no. 6099 including Maurano et al. pp. 1190-1195  DOI: 10.1126/science.1222794b

For the first time, the 3-dimensional connections that cross the genome have been mapped as long-range looping interactions between functional elements and the genes controlled. These regions of the genome, formerly referred to as “junk DNA”, have the potential to be involved in disease initiation, pathophysiology, and complications. Further, epigenetic factors may be seen to play a more direct role in the expression or silencing of protein coding genes as DNase I hot spots, nucleosomal anchor points, and DNA methylation sites are added to the map.

Non-coding transcribed DNA includes a large percentage of sequences coding for RNA. In fact, RNA encoding genes number nearly equal to the protein encoding genes- 18,400 v 20,687 – and previously unknown non-coding RNA (ncRNA) have also been characterized.

Some of the known elements that were cataloged include:

  • cis elements – promoters, transcription factor binding sites;
  • gene contiguous non-coding stretches such as introns, polyA, and UTR, splice variants;
  • pseudogenes (11,224);
  • long range gene associated elements – enhancers, insulators, suppressors, and predicted promoter flanking regions;
  • ribosomal RNA genes; and
  • sequences for 7,052 small RNAs of which 85% are small nuclear(sn)RNA, small nucleolar(sno)RNA), transfer(t)RNA, and micro(mi)RNA.

What has been found is that distinct non-coding regions, including ncRNA, can be associated with distinct disease traits. miRNA are among the non-gene encoding sequences in the genome which have already been shown to play a major post-transcriptional role in expression of multiple genes..

Most miRNA genes are intergenic or oriented antisense to neighboring genes and therefore assumed to be controlled by independent promoter units. However, in some cases a microRNA gene is transcribed together with its target gene implying coupled regulation of miRNA and protein-coding gene. About one third of miRNA genes reside in polycistronic clusters. miRNA genes can occupy the introns of protein, non-protein coding genes, or nonprotein-coding transcripts. The promoters have been shown to have some similarities in their motifs to promoters of other genes transcribed by RNA polymerase II such as protein coding genes. The ENCODE project also noted that miRNA promoters were in chromatin regions of high promiscuity. There may be up to 1000 miRNA genes in the human genome. In addition, human miRNAs show RNA editing of sequences to yield products different from those encoded by their DNA.  miRNA are implicated in cellular roles as diverse as developmental timing in worms, cell death and fat metabolism in flies, haematopoiesis in mammals, and leaf development and floral patterning in plants

The final miRNA gene product is a ∼22 nt functional RNA molecule. The mature miRNA (designated miR-#) is processed from a characteristic stem–loop sequence (called a pre-mir), which in turn may be excised from a longer primary transcript (or pri-mir). It is processed by the same enzyme (DICER) that processes short hairpin RNA, forming interfering RNA, which provides and additional level of control.

MiRNA controls gene expression by binding to complementary regions of messenger transcripts in the 3’ untranslated region to repress their translation or regulate degradation. What makes the mechanism more powerful (or complicated) is the imperfect but specific binding motif associates with a large number of mRNAs in the 3’ untranslated region having the complimentary motif.  Conversely then, each mRNA can potentially associate with a number miRNA. Mature processed cytosolic miRNA can act in a manner akin to small interfering(si)RNA, and form the RNA-induced silencing complex (RISC) to block translation. Computational methods have been used to identify potential gene targets based on complimentarity between the miRNA and mRNA sequences.

Gerstein et al. explored the “Architecture of the human regulatory network derived from ENCODE data” Nature 489:91-100 (06 Sep 2012) focusing on the regulation of transcription factors (TF) and association between TF and miRNAs, miRNA and miRNA, protein-protein interactions, and protein phosphorylation. Not surprisingly, not all TF are the upstream factor in each network.

These new and remarkably detailed examinations of the different elements within and transcribed from the human genome perhaps do more to aid our knowledge of why we have stumbled in attempts to eradicate diseases, initially by focusing on a single gene or constellation of coding regions. The miRNA wikipedia is also being re-written on a daily basis and new disease associations made*.  As an example of a pathological state that may be linked to miRNA controlled elements, in vitro as well as in small population studies have examined miRNA species in diabetogenic conditions and patients with diabetes (Type I and Type II).

Diabetes and miRNA

In adult β-cell islets, miR-375 is low when glucose is freely available and low miR-375 induces insulin secretion. Interestingly, miR-375 is found only in brain and β-cells which share a secretion pathway.

Diabetic Complications

Organ specific miRNA have been identified in liver, skeletal muscle, kidney, vascular, and adipose tissue which are responsive to transient or sustained hyperglycemia.

miR-17-5p and miR-132 were reported to show significant differences between obese and non obese omental fat and were also abnormal in the blood of obese subjects.  Altered expression of miR-17-5p and miR-132 were found to correlate significantly with BMI, fasting blood glucose and glycosylated hemoglobin. (Kloting et al. PLoS ONE 4(3), e4699 (2009).

Clinical practice related to miRNA in diabetes may be possible as one group has identified eight miRNAs (miR-144, miR-146a, miR-150, miR-182, miR-192, miR-29a, miR-30d and miR-320) as potential ‘signature miRNAs’ that could distinguish prediabetic patients from those with overt T2D (Karolina DS, Armugam A, Tavintharan S et al. MicroRNA 144 impairs insulin signaling by inhibiting the expression of insulin receptor substrate 1 in Type 2 diabetes mellitus. PLoS ONE 6(8), e22839 (2011).

Due to the autoimmune component of T1D, the constellation of miRNA would be expected to be different: upregulation of miR-510 and underexpression of miR-191 and miR-342 were observed in the Tregs (regulatory T-cells) of T1D patients (Hezova R, Slaby O, Faltejskova P et al. microRNA-342, microRNA-191 and microRNA-510 are differentially expressed in T regulatory cells of Type 1 diabetic patients. Cell. Immunol. 260(2),70–74 (2010).

Taken together with the “physical” mapping of miRNA genes in the context of the 3-dimensional genome provided by the ENCODE studies and new understanding of potential concerted regulatory mechanisms, the miRNA data for tissues and specific cell types involved in disease pathology form a new approach to either detecting or possibly correcting gene (coding or non-coding) dysregulation.  miRNA mimics and anti-miRNA agents are being developed as new therapeutic modalities.

References

Bartel, DP et al. MicroRNAs: Genomics, Biogenesis, Mechanism, and Function” Cell 2004, 116:281-297.

Fernandez-Valverde, SL et al. MicroRNAs in beta-cell Biology, insulin resistance, diabetes and its complications. Diabetes July 2011 60 (7):1825-31.

Kantharidis, et al.  Diabetes Complications: The MicroRNA Perspective http://diabetes.diabetesjournals.org/content/60/7/1832.short

MEDSCAPE Review article: “miRNAs and Diabetes Mellitus: miRNAs in Diabetic Complicatons”  http://www.medscape.org/viewarticle/763729_6

*Based on initial studies in the worm C. elegans showing the temporal appearance of 21- and 22-nt RNAs during development, a family of highly conserved micro RNA sequences (miRNA) existing in invertebrates and vertebrates, were cataloged by Tuschl et al. at the Max-Planck-Institute and others (see Eddy, SR  Non-coding RNA genes and the modern RNA world Nature Reviews Genetics, 2:920-929, 2001). The sequence-specific post-transcriptional regulatory mechanisms mediated by these miRNAs have been associated with certain disease states such as cancer miR-21) and more specifically, lung cancer (miR-124) or breast cancer (miR-7, miR-21) and new species and function continue to be found (see http://www.mirbase.org/ ).

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Speeding Up Genome Analysis: MIT Algorithms for Direct Computation on Compressed Genomic Datasets

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Chemical Genetics, Computational Biology/Systems and Bioinformatics, FDA Regulatory Affairs, Genome Biology, Genomic Testing: Methodology for Diagnosis, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Proteomics, Scientist: Career considerations, Statistical Methods for Research Evaluation, Technology Transfer: Biotech and Pharmaceutical, tagged , , , , , , on September 18, 2012| 2 Comments »

Reporter: Aviva Lev-Ari, PhD, RN

A New Approach Uses Compression to Speed Up Genome Analysis

Public-Domain Computing Resources

Structural Bioinformatics

The BetaWrap program detects the right-handed parallel beta-helix super-secondary structural motif in primary amino acid sequences by using beta-strand interactions learned from non-beta-helix structures.
Wrap-and-pack detects beta-trefoils in protein sequences by using both pairwise beta-strand interactions and 3-D energetic packing information
The BetaWrapPro program predicts right-handed beta-helices and beta-trefoils by using both sequence profiles and pairwise beta-strand interactions, and returns coordinates for the structure.
The MSARi program indentifies conserved RNA secondary structure in non-coding RNA genes and mRNAs by searching multiple sequence alignments of a large set of candidate catalogs for correlated arrangements of reverse-complementary regions
The Paircoil2 program predicts coiled-coil domains in protein sequences by using pairwise residue correlations obtained from a coiled-coil database. The original Paircoil program is still available for use.
The MultiCoil program predicts the location of coiled-coil regions in amino acid sequences and classifies the predictions as dimeric or trimeric. An updated version, Multicoil2, will soon be available.
The LearnCoil Histidase Kinase program uses an iterative learning algorithm to detect possible coiled-coil domains in histidase kinase receptors.
The LearnCoil-VMF program uses an iterative learning algorithm to detect coiled-coil-like regions in viral membrane-fusion proteins.
The Trilogy program discovers novel sequence-structure patterns in proteins by exhaustively searching through three-residue motifs using both sequence and structure information.
The ChainTweak program efficiently samples from the neighborhood of a given base configuration by iteratively modifying a conformation using a dihedral angle representation.
The TreePack program uses a tree-decomposition based algorithm to solve the side-chain packing problem more efficiently. This algorithm is more efficient than SCWRL 3.0 while maintaining the same level of accuracy.
PartiFold: Ensemble prediction of transmembrane protein structures. Using statistical mechanics principles, partiFold computes residue contact probabilities and sample super-secondary structures from sequence only.
tFolder: Prediction of beta sheet folding pathways. Predict a coarse grained representation of the folding pathway of beta sheet proteins in a couple of minutes.
RNAmutants: Algorithms for exploring the RNA mutational landscape.Predict the effect of mutations on structures and reciprocally the influence of structures on mutations. A tool for molecular evolution studies and RNA design.
AmyloidMutants is a statistical mechanics approach for de novo prediction and analysis of wild-type and mutant amyloid structures. Based on the premise of protein mutational landscapes, AmyloidMutants energetically quantifies the effects of sequence mutation on fibril conformation and stability.

Genomics

GLASS aligns large orthologous genomic regions using an iterative global alignment system. Rosetta identifies genes based on conservation of exonic features in sequences aligned by GLASS.
RNAiCut – Automated Detection of Significant Genes from Functional Genomic Screens.
MinoTar – Predict microRNA Targets in Coding Sequence.

Systems Biology

The Struct2Net program predicts protein-protein interactions (PPI) by integrating structure-based information with other functional annotations, e.g. GO, co-expression and co-localization etc. The structure-based protein interaction prediction is conducted using a protein threading server RAPTOR plus logistic regression.
IsoRank is an algorithm for global alignment of multiple protein-protein interaction (PPI) networks. The intuition is that a protein in one PPI network is a good match for a protein in another network if the former’s neighbors are good matches for the latter’s neighbors.

Other

t-sample is an online algorithm for time-series experiments that allows an experimenter to determine which biological samples should be hybridized to arrays to recover expression profiles within a given error bound.

http://people.csail.mit.edu/bab/computing_new.html#systems

Compressive genomics

http://www.nature.com/nbt/journal/v30/n7/abs/nbt.2241.html

Nature Biotechnology 30, 627–630 (2012) doi:10.1038/nbt.2241

Published online 10 July 2012
Algorithms that compute directly on compressed genomic data allow analyses to keep pace with data generation.

Figures at a glance

Introduction

In the past two decades, genomic sequencing capabilities have increased exponentially1, 2, 3, outstripping advances in computing power4, 5, 6, 7, 8. Extracting new insights from the data sets currently being generated will require not only faster computers, but also smarter algorithms. However, most genomes currently sequenced are highly similar to ones already collected9; thus, the amount of new sequence information is growing much more slowly.
Here we show that this redundancy can be exploited by compressing sequence data in such a way as to allow direct computation on the compressed data using methods we term ‘compressive’ algorithms. This approach reduces the task of computing on many similar genomes to only slightly more than that of operating on just one. Moreover, its relative advantage over existing algorithms will grow with the accumulation of genomic data. We demonstrate this approach by implementing compressive versions of both the Basic Local Alignment Search Tool (BLAST)10 and the BLAST-Like Alignment Tool (BLAT)11, and we emphasize how compressive genomics will enable biologists to keep pace with current data.

Conclusions

Compressive algorithms for genomics have the great advantage of becoming proportionately faster with the size of the available data. Although the compression schemes for BLAST and BLAT that we presented yield an increase in computational speed and, more importantly, in scaling, they are only a first step. Many enhancements of our proof-of-concept implementations are possible; for example, hierarchical compression structures, which respect the phylogeny underlying a set of sequences, may yield additional long-term performance gains. Moreover, analyses of such compressive structures will lead to insights as well. As sequencing technologies continue to improve, the compressive genomic paradigm will become critical to fully realizing the potential of large-scale genomics.Software is available at http://cast.csail.mit.edu/.
References
  1. Lander, E.S. et al. Nature 409, 860–921 (2001).
  2. Venter, J.C. et al. Science 291, 1304–1351 (2001).
  3. Kircher, M. & Kelso, J. Bioessays 32, 524–536 (2010).
  4. Kahn, S.D. Science 331, 728–729 (2011).
  5. Gross, M. Curr. Biol. 21, R204–R206 (2011).
  6. Huttenhower, C. & Hofmann, O. PLoS Comput. Biol. 6, e1000779 (2010).
  7. Schatz, M., Langmead, B. & Salzberg, S. Nat. Biotechnol. 28, 691–693 (2010).
  8. 1000 Genomes Project data available on Amazon Cloud. NIH press release, 29 March 2012.
  9. Stratton, M. Nat. Biotechnol. 26, 65–66 (2008).
  10. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. & Lipman, D.J. J. Mol. Biol. 215, 403–410 (1990).
  11. Kent, W.J. Genome Res. 12, 656–664 (2002).
  12. Grumbach, S. & Tahi, F. J. Inf. Process. Manag. 30, 875–886 (1994).
  13. Chen, X., Li, M., Ma, B. & Tromp, J. Bioinformatics 18, 1696–1698 (2002).
  14. Christley, S., Lu, Y., Li, C. & Xie, X. Bioinformatics 25, 274–275 (2009).
  15. Brandon, M.C., Wallace, D.C. & Baldi, P. Bioinformatics 25, 1731–1738 (2009).
  16. Mäkinen, V., Navarro, G., Sirén, J. & Välimäki, N. in Research in Computational Molecular Biology, vol. 5541 of Lecture Notes in Computer Science (Batzoglou, S., ed.) 121–137 (Springer Berlin/Heidelberg, 2009).
  17. Kozanitis, C., Saunders, C., Kruglyak, S., Bafna, V. & Varghese, G. in Research in Computational Molecular Biology, vol. 6044 of Lecture Notes in Computer Science (Berger, B., ed.) 310–324 (Springer Berlin/Heidelberg, 2010).
  18. Hsi-Yang Fritz, M., Leinonen, R., Cochrane, G. & Birney, E. Genome Res. 21, 734–740 (2011).
  19. Mäkinen, V., Navarro, G., Sirén, J. & Välimäki, N. J. Comput. Biol. 17, 281–308 (2010).
  20. Deorowicz, S. & Grabowski, S. Bioinformatics 27, 2979–2986 (2011).
  21. Li, H., Ruan, J. & Durbin, R. Genome Res. 18, 1851–1858 (2008).
  22. Li, H. & Durbin, R. Bioinformatics 25, 1754–1760 (2009).
  23. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. Genome Biol. 10, R25 (2009).
  24. Carter, D.M. Saccharomyces genome resequencing project. Wellcome Trust Sanger Institute http://www.sanger.ac.uk/Teams/Team118/sgrp/ (2005).
  25. Tweedie, S. et al. Nucleic Acids Res. 37, D555–D559 (2009).

Primary authors

  1. P.-R.L. and M.B. contributed equally to this work.
    • Po-Ru Loh &
    • Michael Baym

Affiliations

  1. Po-Ru Loh, Michael Baym and Bonnie Berger are in the Department of Mathematics and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
  2. Michael Baym is also in the Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.

Competing financial interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to:

September 2012

Compressing a dataset with specialized algorithms is typically done in the context of data storage, where compression tools can shrink data to save space on a hard drive. But a group of researchers at MIT has developed tools that compute directly on compressed genomic datasets by exploiting the fact that most sequenced genomes are very similar to previously sequenced genomes.

 Speed Up Genome Analysis

by exploiting the fact that most sequenced genomes are very similar to previously sequenced genomes.

Led by MIT professor Bonnie Berger, the group has recently released tools called CaBlast and CaBlat, compressive versions of the widely used Blast and Blat alignment tools, respectively.

In a Nature Biotechnology paper published in July, Berger and her colleagues describe how the algorithms deliver alignment and analysis results up to four times faster than Blast and Blat when searching for a particular sequence in 36 yeast genomes.

“What we demonstrate is that the more highly similar genomes there are in a database, the greater the relative speed of CaBlast and CaBlat compared to the original non-compressive versions,” Berger says. “As we increase the number of genomes, the amount of work required for compressive algorithms scales only linearly in the amount of non-redundant data. The idea is that we’ve already done most of the work on the first genome.”

These two algorithms are still in the beta phase, and the MIT team has several refinements planned for future release to optimize performance. To that end, Berger has made the code for both algorithms available with the hope that developers will help them build “industrial-strength” software that can be used by the research community.

“To achieve optimal performance in real-use cases, we expect the code will need to be tuned for the engineering trade-offs specific to the application at hand,” she says. “The algorithm used to find and compress similar sequences in the database may need to be tweaked to take this issue into account, and the coarse- and fine-search steps should be aware of these constraints as well.”

While computing resources are becoming increasingly powerful, Berger contends that better algorithms and the use of compression technology will play a crucial role in helping researchers to keep up with the production of next-generation sequencing data.

Matthew Dublin is a senior writer at Genome Technology.

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Protein Folding may lead to better FLU Vaccine

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Health Economics and Outcomes Research, Infectious Disease & New Antibiotic Targets, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Proteomics, tagged , , , , , , , , , , on July 25, 2012| 2 Comments »

Reporter: Aviva Lev-Ari, PhD, RN
July 25, 2012
Insights into protein folding may lead to better flu vaccine
folding proteins

S.B. Qian
This image shows shows mRNA (purple) with ribosomes (beige) bearing nascent protein chains (pink) in different stages of folding.

A new method for looking at how proteins fold inside mammal cells could one day lead to better flu vaccines, among other practical applications, say Cornell researchers.

The method, described online in the Proceedings of the National Academy of Sciences July 16, allows researchers to take snapshots of the cell’s protein-making machinery — called ribosomes — in various stages of protein production. The scientists then pieced together the snapshots to reconstruct how proteins fold during their synthesis.

Proteins are made up of long chains of amino acids called polypeptides, and folding gives each protein its characteristic structure, which determines its function. Though researchers have used synthetic and purified proteins to study protein folding, this study looks at proteins from their inception, providing a truer picture for how partially synthesized polypeptides can fold in cells.

Proteins fold so quickly — in microseconds — that it has been a longtime mystery just how polypeptide chains fold to create the protein’s structure.

“The speed is very fast, so it’s very hard to capture certain steps, but our approach can look at protein folding at the same time as it is being synthesized by the ribosomes,” said Shu-Bing Qian, assistant professor of nutritional sciences and the corresponding author on the paper. Yan Han, a postdoctoral associate in Qian’s lab, is the paper’s first author.

In a nutshell, messenger RNA (mRNA) carries the coding information for proteins from the DNA to ribosomes, which translate those codes into chains of amino acids that make up proteins. Previously, other researchers had developed a technique to localize the exact position of the ribosomes on the mRNA. Qian and colleagues further advanced this technique to selectively enrich only a certain portion of the protein-making machinery, basically taking snapshots of different stages of the protein synthesis process.

“Like a magnifier, we enrich a small pool from the bigger ocean and then paint a picture from early to late stages of the process,” Qian said.

In the paper, the researchers also describe applying this technique to better understanding a protein called hemagglutinin (HA), located on the surface of the influenza A virus; HA’s structure (folding) allows it to infect the cell.

Flu vaccines are based on antibodies that recognize such proteins as HA. But viruses have high mutation rates to escape antibody detection. Often, flu vaccines lose their effectiveness because surface proteins on the virus mutate. HA, for example, has the highest mutation rate of the flu virus’ surface proteins.

The researchers proved that their technique can identify how the folding process changes when HA mutates.

“If people know the folding picture of how a mutation changes, it will be helpful for designing a better vaccine,” Qian said.

“Folding is a very fundamental issue in biology,” Qian added. “It’s been a long-term mystery how the cell achieves this folding successfully, with such speed and with such a great success rate.”

Co-authors include researchers at the National Institute of Allergy and Infectious Diseases.

The research was funded by the National Institute of Allergy and Infectious Diseases Division of Intramural Research, National Institutes of Health Grant, Ellison Medical Foundation Grant and U.S. Department of Defense Exploration-Hypothesis Development Award.

 http://www.news.cornell.edu/stories/July12/ProteinFoldingQian.html

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