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Archive for the ‘Gene Regulation and Evolution’ Category

Pathophysiology in Hypertension: Opposing Roles of Human Adaptive Immunity

Reporter: Aviva Lev-Ari, PhD, RN

T regulatory lymphocytes counteract hypertensive effects by suppressing innate and adaptive immune responses and T effector lymphocytes promote differentiation towards pro-inflammatory T helper cells

 

Dual opposing roles of adaptive immunity in hypertension

 

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DOI: http://dx.doi.org/10.1093/eurheartj/ehu119 1238-1244 First published online: 30 March 2014

Abstract

Hypertension involves remodelling and inflammation of the arterial wall. Interactions between vascular and inflammatory cells play a critical role in disease initiation and progression. T effector and regulatory lymphocytes, members of the adaptive immune system, play contrasting roles in hypertension. Signals from the central nervous system and the innate immune system antigen-presenting cells activate T effector lymphocytes and promote their differentiation towards pro-inflammatory T helper (Th) 1 and Th17 phenotypes. Th1 and Th17 effector cells, via production of pro-inflammatory mediators, participate in the low-grade inflammation that leads to blood pressure elevation and end-organ damage. T regulatory lymphocytes, on the other hand, counteract hypertensive effects by suppressing innate and adaptive immune responses. The present review summarizes and discusses the adaptive immune mechanisms that participate in the pathophysiology in hypertension.

  • Blood pressure
  • Adaptive immunity
  • Inflammation
  • T effector lymphocytes
  • T regulatory lymphocytes
  • Cytokines

Conclusion

Experimental and clinical evidence discussed in this review strongly suggests that adaptive immunity, represented by T effector and regulatory lymphocyte subsets, plays a dual role in hypertension (Figure 2). Increased sympathetic outflow as a consequence of stimulation of the CNS by hypertensive stimuli may result in mild blood pressure elevation, causing tissue injury and formation of neoantigens2 and/or damage-associated molecular patterns (DAMPs).80 Activation of innate APCs by DAMPs, or by pathogen-associated molecular patterns (PAMPs) generated in response to low-grade infection,80,81 and direct stimulation by CNS, may be the cause of activation of CD4+, and perhaps CD8+, T effector lymphocytes, and differentiation of CD4+ T cells towards pro-inflammatory Th1/Th17 phenotypes.41 Th1/Th17 effector lymphocytes contribute to the progression of hypertension by producing pro-inflammatory mediators, including ROS, IFN-γ, TNF-α, and IL-17, to promote low-grade inflammation.24,41,42,51,52 T regulatory lymphocytes, on the other hand, counteract hypertensive abnormalities by suppressing innate and adaptive immune responses, perhaps by secreting IL-10.6571 As such, circulating levels of Tregs or their immune-suppressive activity may be affected in hypertension.

 SOURCE

http://eurheartj.oxfordjournals.org/content/35/19/1238

Idris-Khodja et al. (2014) Dual opposing roles of adaptive immunity in hypertension. European Heart Journal (doi: 10.1093/eurheartj/ehu119)

 

Adaptive Immunity

Figure 1

Differentiation of naïve T lymphocytes into various subsets in a normal immune response. Antigen-presenting cells (dendritic cells and monocyte/macrophages) present antigens on major histocompatibility complex (MHC)-II to naïve T cells (Th0) in secondary lymphoid tissues, leading to T-cell clonal expansion and differentiation into effector T cells, such as T helper (Th)1, Th2, and Th17 or T regulatory (Treg) cells according to combined stimulation by different cytokines. Th effector lymphocytes and Tregs migrate into tissues such as the vasculature, particularly at the level of the adventitia and perivascular fat. The effector lymphocytes (Th1 and Th17) cells activate other immune cells and participate in inflammation by producing pro-inflammatory cytokines such as interferon-γ, interleukin (IL)-6, and IL-17. T regulatory lymphocytes suppress innate and adaptive responses via production of anti-inflammatory cytokines IL-10 and transforming growth factor-β. CD, cluster of differentiation; DC, dendritic cell; MΦ, macrophage; NK cell, natural killer cell; Tc, cytotoxic T cell; TCR, T-cell receptor.

IMAGE SOURCE

http://eurheartj.oxfordjournals.org/content/35/19/1238

 

Hypertention

 

IMAGE SOURCE

http://eurheartj.oxfordjournals.org/content/35/19/1238

Figure 2

Proposed role of T effector and regulatory lymphocytes in hypertension. Slight elevation in blood pressure (BP) in response to hypertensive stimuli (angiotensin II, aldosterone, endothelin-1, salt and genetic susceptibility) occurs due to increased central signalling, perhaps causing mild tissue injury and formation of damage-associated molecular patterns (DAMPs) and neoantigens. This may lead to activation of innate antigen-presenting cells (APCs) and, subsequently, activation and polarization of naïve CD4+ T effector lymphocytes (Th0) towards pro-inflammatory T helper (Th)1/Th17 phenotypes. Th1/Th17 may contribute to vascular and kidney damage via production of reactive oxygen species (ROS), interferon (IFN)-γ and interleukin (IL)-17 and lead to maintenance of hypertension and progression of end-organ damage. T regulatory lymphocytes counteract hypertension and associated injury by producing IL-10 or by other mechanisms, and suppression of innate and adaptive immune responses. CD, cluster of differentiation; CNS, central nervous system; MHC-II, major histocompatibility complex-II; PAMPs, pathogen-associated molecular patterns; TCR, T-cell receptor.

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A New Computational Method illuminates the Heterogeneity and Evolutionary Histories of cells within a Tumor, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

A New Computational Method illuminates the Heterogeneity and Evolutionary Histories of cells within a Tumor

Reporter: Aviva Lev-Ari, PhD, RN

 

Start Quote

Numerous computational approaches aimed at inferring tumor phylogenies from single or multi-region bulk sequencing data have recently been proposed. Most of these methods utilize the variant allele fraction or cancer cell fraction for somatic single-nucleotide variants restricted to diploid regions to infer a two-state perfect phylogeny, assuming an infinite-site model such that each site can mutate only once and persists. In practice, convergent evolution could result in the acquisition of the same mutation more than once, thereby violating this assumption. Similarly, mutations could be lost due to loss of heterozygosity. Indeed, both single-nucleotide variants and copy number alterations arise during tumor evolution, and both the variant allele fraction and cancer cell fraction depend on the copy number state whose inference reciprocally relies on the relative ordering of these alterations such that joint analysis can help resolve their ancestral relationship (Figure 1). To tackle this outstanding problem, El-Kebir et al. (2016) formulated the multi-state perfect phylogeny mixture deconvolution problem to infer clonal genotypes, clonal fractions, and phylogenies by simultaneously modeling single-nucleotide variants and copy number alterations from multi-region sequencing of individual tumors. Based on this framework, they present SPRUCE (Somatic Phylogeny Reconstruction Using Combinatorial Enumeration), an algorithm designed for this task. This new approach uses the concept of a ‘‘character’’ to represent the status of a variant in the genome.

Commonly, binary characters have been used to represent single-nucleotide variants— that is, the variant is present or absent. In contrast, El-Kebir et al. use multi-state characters to represent copy number alterations, which may be present in zero, one, two, or more copies in the genome.

SPRUCE outperforms existing methods on simulated data, yielding higher recall rates under a variety of scenarios. Moreover, it is more robust to noise in variant allele frequency estimates, which is a significant feature of tumor genome sequencing data. Importantly, El-Kebir and colleagues demonstrate that there is often an ensemble of phylogenetic trees consistent with the underlying data. This uncertainty calls for caution in deriving definitive conclusions about the evolutionary process from a single solution.”

End Quote

 

From Original Paper

Inferring Tumor Phylogenies from Multi-region Sequencing

Zheng Hu1,2 and Christina Curtis1,2,*

1Departments of Medicine and Genetics

2Stanford Cancer Institute

Stanford University School of Medicine, Stanford, CA 94305, USA

*Correspondence: cncurtis@stanford.edu

http://dx.doi.org/10.1016/j.cels.2016.07.007

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Crowdsourcing Genetic Data Yields Discovery of DNA loci associated with Major Depressive Disorder (MDD) in European Descendants, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Crowdsourcing Genetic Data Yields Discovery of DNA loci associated with Major Depressive Disorder (MDD) in European Descendants

 

Reporter: Kelly Perlman, Life Sciences Student and Research Assistant, McGill University

 

UPDATED on 11/24/2019

Can AI help diagnose depression? It’s a long shot

At the moment, machine intelligence is just as subjective as human intelligence

Alejandra Canales

https://www.salon.com/2019/11/23/can-ai-help-diagnose-depression-its-a-long-shot_partner/amp?__twitter_impression=true

Researchers from Pfizer Global Research and Development, 23andMe, and the Massachusetts General Hospital have published a study in Nature Genetics, pinpointing 15 genetic loci associated with the risk of developing major depressive disorder (MDD) in individuals of European ancestry. Evidence from previous research suggests that MDD is heritable, but the details of the specific gene correlates are unclear. The identification of loci where single nucleotide polymorphisms (SNPs) related to MDD exist could provide better insight into the neurobiology of depression, and therefore better treatment options.

23andMe, a private biotechnology company situated in California, offers a DNA sequencing service in which consumers send in a saliva swab for testing, and later receive a report listing the findings of the analysis related to ancestry, physical and behavioral traits, along with risk of inheriting certain diseases. The participants of this study had agreed to provide the results of their genetic testing for scientific research.

The results of 75,607 participants with self-reported diagnoses of depression were compared to the results of 231,747 participants reporting having never experienced depression. This data was combined with the results of previously published MDD genome-wide association studies (GWAS). To test the whether these results could be replicated, another set of results from 23andMe was analyzed, in which there were 45,773 MDD subjects, and 106,354 controls.

After the joint analysis, 17 SNPs were identified at 15 different loci. Tissue and gene enrichment assays showed that the genes that were over-expressed in the CNS were related to functions including neurodevelopment, histone methylation, neurogenesis and synaptic modification.

The team then created a weighted genetic risk score (GRS) in which they compared the 17 SNPs with factors including medication use, comorbid diseases and behavioral phenotypes, all of which were correlated with the GRS. Of note, the GRS was very highly correlated with age of onset of MDD.

The crowdsourcing of genetic data proves to be an efficient and powerful tool for large-scale MDD studies. Pooling large subject databases together is essential in order to account for the heterogeneous nature of the disease. Despite not being able to precisely assess each subject’s disease phenotype, scientists can make more rapid headway by collaborating with biotechnology companies in the quest to better understand the biological mechanisms of depression. Ron Perlis, M.D., M.Sc., of the Massachusetts General Hospital and co-author of this paper explained that “finding genes associated with depression should help make clear that this is a brain disease, which we hope will decrease the stigma still associated with these kinds of illnesses”.

 

Details on specific significant genes:

http://www.genecards.org/cgi-bin/carddisp.pl?gene=OLFM4

http://www.genecards.org/cgi-bin/carddisp.pl?gene=TMEM161B

http://www.genecards.org/cgi-bin/carddisp.pl?gene=MEF2C

http://www.genecards.org/cgi-bin/carddisp.pl?gene=MEIS2

http://www.genecards.org/cgi-bin/carddisp.pl?gene=TMCO5A

http://www.genecards.org/cgi-bin/carddisp.pl?gene=NEGR1

 

SOURCES

Hyde, C. L., Nagle, M. W., Tian, C., Chen, X., Paciga, S. A., Wendland, J. R., . . . Winslow, A. R. (2016). Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nature Genetics Nat Genet. doi:10.1038/ng.3623

Major Depressive Disorder Loci Discovered in Large GWAS Enabled by 23andMe Participants’ Data. (2016, August 01). Retrieved August 09, 2016, from https://www.genomeweb.com/microarrays-multiplexing/major-depressive-disorder-loci-discovered-large-gwas-enabled-23andme

 

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Deep Learning for In-silico Drug Discovery and Drug Repurposing: Artificial Intelligence to search for molecules boosting response rates in Cancer Immunotherapy: Insilico Medicine @John Hopkins University, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Deep Learning for In-silico Drug Discovery and Drug Repurposing: Artificial Intelligence to search for molecules boosting response rates in Cancer Immunotherapy: Insilico Medicine @John Hopkins University

Reporter: Aviva Lev-Ari, PhD, RN

Insilico Medicine –>>> transcriptome-based pathway perturbation analysis

Insilico Medicine, Inc. is a bioinformatics company located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore with R&D resources in Belgium, Russia, and Poland hiring talent through hackathons and competitions. It utilizes advances in genomics, big data analysis and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. The company pursues internal drug discovery programs in cancer, Parkinson’s, Alzheimer’s, sarcopenia and geroprotector discovery. Through its Pharmaceutical Artificial Intelligence division the company provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies.

WATCH VIDEO

Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8.

Insilico Medicine develops a new approach to concomitant cancer immunotherapy

Artificial intelligence to search for molecules boosting response rates in cancer immunotherapy

INSILICO MEDICINE, INC.

IMAGE
IMAGE: THIS IS THE INSILICO MEDICINE LOGO.view more

CREDIT: INSILICO MEDICINE

Summary:

  • Some of the most promising drugs for cancer therapy called checkpoint inhibitors often result in complete remissions, however, a majority of patients fail cancer immunotherapy with antibodies targeting immune checkpoints, such as CTLA-4 or programmed death-1 (PD-1).
  • Insilico Medicine developed a set of pathway-based signatures of response to popular checkpoint inhibitors
  • Using these markers and a deep learned drug scoring engine Insilico Medicine identified 12 leads that may help increase response to cancer immunotherapy and is seeking industry partnerships to test these leads

Thursday, July 14, 2016, Baltimore, MD — Recent advances in cancer immunotherapy demonstrated complete remission in multiple tumor types including melanoma and lung cancers. Almost every major pharmaceutical company operating in oncology space started multiple programs in immuno-oncology with thousands of clinical trials underway. Immuno-oncology is now a very broad field ranging from treatment of a patient with an engineered antibody to genome editing of patient’s immune cells. Genetic mutations accruing from the inherent genomic instability of tumor cells present neo-antigens that are recognized by the immune system. Cross-presentation of tumor antigens at the immune synapse between antigen-presenting dendritic cells and T lymphocytes can potentially activate an adaptive antitumor immune response, however, tumors continuously evolve to counteract and ultimately defeat such immune surveillance by co-opting and amplifying mechanisms of immune tolerance to evade elimination by the immune system. This prerequisite for tumor progression is enabled by the ability of cancers to produce negative regulators of immune response.

Cancer immunotherapy is currently focused on targeting immune inhibitory checkpoints that control T cell activation, such as CTLA-4 and PD-1. Monoclonal antibodies that block these immune checkpoints (commonly referred to as immune checkpoint inhibitors) can unleash antitumor immunity and produce durable clinical responses in a subset of patients with advanced cancers, such as melanoma and non-small-cell lung cancer. However, these immunotherapeutics are currently constrained by their inability to induce clinical responses in the vast majority of patients and the frequent occurrence of immune-related adverse events. A key limitation of checkpoint inhibitors is that they narrowly focus on modulating the immune synapse but do not address other key molecular determinants that may also be responsible for immune dysfunction.

Immunoresistance often ensues as a result of the concomitant activation of multiple, often overlapping signaling pathways. Therefore, inhibition of multiple, cross-talking pathways involved in survival control with combination therapy is usually more effective in decreasing the likelihood that cancer cells will develop therapeutic resistance than with single agent therapy. While research efforts are now focused on identifying new inhibitory mechanisms that could be targeted to achieve responses in patients with refractory cancers and provide durable and adaptable cancer control, there are outstanding challenges in determining what combination of immunotherapies and conventional therapies will prove beneficial against each tumor type.

“Immunotherapy is the most promising area in oncology resulting in cures, but we need to identify effective combinations of both established methods and new drugs developed specifically to boost response rates. At Insilico Medicine we developed a new method for screening, scoring and personalizing small molecules that may boost response rates to PD-1, PD-L1, CTLA4 and other checkpoint inhibitors. We can identify effective combinations of both established methods and new drugs developed specifically to boost response rates to immunotherapy”, said Artem Artemov, director of computational drug repurposing at Insilico Medicine.

Insilico Medicine, Inc. is one of the leaders in transcriptome-based pathway perturbation analysis. It is also a pioneer in applying cutting edge artificial intelligence techniques to biological and medical data analysis, particularly focused on in silico screening for new compounds against cancer and known drugs which can be repurposed against different cancers. One of the major programs currently ongoing at Insilico Medicine is evaluation of the transcriptional responses to multiple checkpoint inhibitors and analyzing the pathway-level differences in patients who respond and fail to respond to clinically approved checkpoint inhibitors. This novel computational approach is aimed at identifying new drug candidates which can be used in combination with immunotherapy to unleash durable antitumor effect against several types of cancers.

Recently, scientists at Insilico Medicine performed a large in silico screening of compounds that can be administered in combination with anti-PD1 immunotherapy to increase response rates. The researchers collected transcriptomic data from tumors of patients who either responded or failed to respond to standard immunotherapy, using both publically available and internally generated data. Next, they used differential pathway activation analysis and deep learning based approaches to identify transcriptomic signatures predicting the success of immunotherapy in a particular tumor type.

Finally, they analyzed drug-induced transcriptomic effects to screen for the drugs that can robustly drive transcriptomes of tumor cells from non-responsive state to the state responsive to immunotherapy. In other words, researchers developed approach that can predict whether drug of interest would induce a transcriptional signature that characterizes those patients that respond to cancer immunotherapy in non-respondents. This method allows personalizing these drugs to individual patients and specific checkpoint inhibitors. Among the top-scoring drugs, they found several compounds known to increase response rates in combination with cancer immunotherapy. One of the top-scoring compounds included a naturally-occurring substance marketed as a natural product.

The current list of top-scoring leads that may increase response rates to checkpoint inhibitors included 12 small molecules identified using signaling pathway perturbation analysis and annotated using a deeply learned drug scoring system. Insilico Medicine is currently open for partnerships which will allow further testing and validation of the discovered compounds ex vivo on cell cultures established from tumors which respond and failed to respond to immunotherapy, as well as in mice with patient-derived tumor xenografts. This approach may greatly reduce the costs of preclinical trials and significantly shorten the timeframe from a drug prediction to validation and marketing. The compounds, after preclinical and clinical validation, may improve cancer care and dramatically increase the lifespan of cancer patients.

A panel of leads for concomitant immunotherapy is part of a large number of leads developed using DeepPharma™, artificially-intelligent drug discovery engine, which includes a large number of molecules predicted to be effective antineoplastic agents, metabolic regulators, CVD and CNS lead, senolytics and ED drugs. Recently Insilico Medicine published several seminal papers demonstrating proof of concept of utilizing deep learning techniques to predict pharmacological properties of small molecules using transcriptional response data utilizing deep neural networks for biomarker development. “Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data,” a paper published in Molecular Pharmaceuticals received the American Chemical Society Editors’ Choice Award. Another recent collaboration with Biotime, Inc resulted in a launch of Embryonic.AI, deep learned predictor of differentiation state of the sample.

###

 

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

SOURCE

http://www.eurekalert.org/pub_releases/2016-07/imi-imd071416.php?utm_content=buffer36d53&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer

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First challenge to make use of the new NCI Cloud Pilots – Somatic Mutation Challenge – RNA: Best algorithms for detecting all of the abnormal RNA molecules in a cancer cell, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

First challenge to make use of the new NCI Cloud Pilots – Somatic Mutation Challenge – RNA: Best algorithms for detecting all of the abnormal RNA molecules in a cancer cell

Reporter: Aviva Lev-Ari, PhD, RN

 

Genomic rearrangements in cancer cells produce fusion transcripts, which may give rise to chimeric protein products not present in normal cells. In addition, cancer cells can express alternate forms of encoded messages that give rise to protein variants different from normal tissue. These chimeras and protein variants can serve as robust diagnostic markers or drug targets. Moreover, ongoing research efforts are beginning to unveil the potential clinical relevance of these variant RNA products. Increasing the “alterome” of tumors by fully characterizing their RNA landscapes will expand our understanding of cancer mechanisms, provide new biomarkers and reveal possible new RNA-based therapeutics, thus improving personalized patient treatment.

“Predicting RNA species in a cancer cell is a particularly challenging task,” says Josh Stuart, Professor at the UC Santa Cruz Genomics Institute and one of the challenge leaders. “RNA expression reflects much of the deranged complexity of the underlying cancer cell DNA and then adds another level of derangement on top of that.”

The goal of the SMC-RNA Challenge is to identify the best methods for detecting rearrangements in RNA sequencing (RNA-seq) data. Sub-challenges are focused on detecting and quantifying mRNA fusions and isoforms. Methods will be evaluated with both in silico and spiked-in data.

Two key questions that will be addressed are:

1) What is the best way to estimate the abundances of a set of known RNA isoforms? and

2) What is the best way to predict the presence of novel gene fusions?

Both of these questions will involve in silico generated and wet lab spiked-in RNA sequencing data.

SOURCE

http://scienmag.com/international-team-launches-community-competition-to-find-how-cancer-changes-a-cells-rna/

Challenge Overview

We are launching the ICGC-TCGA DREAM Somatic Mutation Calling RNA Challenge (SMC-RNA), a community-based collaborative competition of researchers from across the world. We will rigorously assess the accuracy of methods to perform two key tasks in cancer RNA-Seq data analysis: the quantification of known isoforms and detecting novel fusion transcripts. We will generate RNA-Seq data for a synthetic-based challenge. Since synthetic data may not capture the complexity of real human tumours, we will also introduce a phase in which teams make predictions on real human-tumours. Challenge organizers will perform retrospective experimental validation on predictions to create a gold-standard. Validation will employ a combination of long-read sequencing and target-capture approaches. The SMC-RNA Challenge will analyze a couple of dozen samples created to have known alterations representing different tumor types, allowing confidence that the winning methods will be generalizable across the broad range of human cancers.

SOURCE

https://www.synapse.org/#!Synapse:syn2813589/wiki/401437

Important Dates

Registration open

Register

The ICGC-TCGA DREAM Somatic Mutation Calling – RNA Challenge (SMC-RNA) is an international effort to improve standard methods for identifying cancer-associated rearrangements in RNA sequencing (RNA-seq) data. Leaders of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cancer genomics projects are joining with Sage Bionetworks and IBM-DREAM to initiate this innovative open crowd-sourced Challenge [1-3].

Why is RNA biology important in cancer?

While only a small fraction of the genome encodes proteins, the majority is either transcribed or has putative regulatory functions, with the consequence that cellular functions are extensively regulated at the RNA level. The regulation of RNA, and its dramatic dysregulation in cancer cells, occurs in multiple ways. RNA abundances may be altered, and these have served as the basis for clinically-important prognostic biomarkers. Genomic rearrangements in cancer cells produce fusion transcripts which may give rise to chimeric protein products not present in normal cells. These can serve as robust diagnostic markers (e.g. TMPRSS2-ERG in prostate cancer) or drug targets (e.g. BCR-ABL in CML). Ongoing research efforts are beginning to unveil the potential clinical relevance of aberrant processing of RNA in cancer, such as defects in alternative-splicing. To fully document the molecular differences in transcription between tumor cells and their normal counterparts an assortment of computational methods are needed. Increasing the “alterome” of tumors by fully characterizing their RNA landscapes will expand our understanding of cancer mechanisms, provide new biomarkers and reveal possible new RNA-based therapeutics, improving personalized patient treatment.

What is RNA Sequencing?

RNA-seq is using next-generation sequencing techniques to sequence RNA. It allows the the transcriptome to be sequenced at high coverage, provides raw read counts that can be used to assess expression levels, and from it elucidate other biologically relevant information. RNA is reverse transcribed into cDNA and then sequenced at high depth by high-throughput technologies, such as Illumina HiSeq, Roche 454, and PacBio [4]. After sequencing, reads can be aligned de novo, to a reference genome, or to a reference transcriptome. Using RNA-seq has some advantages over microarrays, including no prior knowledge of the transcriptome needed and an unbiased expression analysis [5]. In comparison, microarrays, the current gold standard for RNA analysis require probe design and have been found to contain more bias in low-intensity genes [6]. Some key challenges in RNA-seq include biases occurring in RNA fragmentation, cDNA fragmentation, and library preparation, in addition to, potential PCR artifacts that skew expression levels, and possible alignment to multiple locations in a reference genome [5]. Due to these and other influences, methods for detecting and quantifying transcriptional isoforms, as well as fusion genes remains a challenging set of problems and competing methods for interpreting RNA-Seq results continues to be poor.

Fusion Prediction

Scientific Rationale: Gene fusions occur when two genes at the DNA level are joined and may be due to an oncogenic event. A fusion may also occur at the RNA level where a ligation between two transcripts occurs. Gene fusions have an important role in the initial steps of tumorigenesis. Specifically, gene fusions have been found to be the driver mutations in neoplasia and have been linked to various tumour subtypes. An increasing number of gene fusions are being recognized as important diagnostic and prognostic parameters in malignant haematological disorders and childhood sarcomas. Gene fusions occur in all malignancies and account for 20% of human cancer morbidity [7].

Isoform Prediction

Scientific Rationale: Isoforms are alternative expressions of a gene formed from splicing during post-transcriptional processing. Dysregulation of alternative splicing occurs in every category of Hanahan’s and Weinberg’s hallmarks of cancer. Modifications in splicing may occur due to mutations of cis-acting splicing elements, trans-acting regulators, and microRNAs. Moreover, cancer cell lines, regardless of their tissue of origin, can be effectively discriminated from non-cancer cell lines at isoform level, but not at gene level. Existence of an isoform signature, rather than a gene signature, could be used to distinguish cancer cells from normal cells [8].

Challenges

The goal of this Challenge is to use a crowd-based competition to identify the optimal methods for detecting (and quantifying) mRNA fusions and isoforms from RNA-seq data.

Sub-Challenge 1: Quantify Known Isoforms
Can algorithms estimate the levels of a set of provided isoforms?
1a: In silico simulated data challenge
1b: Spike-in data challenge on real data from long-reads and hybrid capture.

Sub-Challenge 2: Detect Gene Fusions
Can algorithms predict the presence of gene fusions?
2a: In silico simulated gene fusions.
2b: Spike-in long-read data.

Reward

  • All participants will be invited as consortium co-authors on Challenge marker papers
  • Winners will receive travel awards & speaking invitations at the next DREAM conference or Sage Congress
  • New methods will be considered for co-publication with the Challenge marker papers by our publishing partner
  • Other rewards will be announced as they are determined.

Challenge Organizers / Scientific Advisory Board

  • Kyle Ellrott, Oregon Health Sciences University
  • Josh Stuart, University of California, Santa Cruz
  • Paul C. Boutros, Ontario Institute for Cancer Research
  • Paul Spellman, Oregon Health Sciences University
  • Christopher Maher, Washington University
  • Stephen Friend, Sage Bionetworks
  • Thea Norman, Sage Bionetworks
  • Gustavo Stolovitzky, IBM, DREAM

 

SOURCE

https://www.synapse.org/#!Synapse:syn2813589/wiki/401435

REFERENCES

  1. International Cancer Genome Consortium et al. International network of cancer genome projects. Nature 464, 993–998 (2010).http://icgc.org/
  2. The Cancer Genome Atlas (TCGA). http://cancergenome.nih.gov/
  3. Dialogue for Reverse Engineering Assessments and Methods (DREAM). http://www.the-dream-project.org/
  4. Wang, Z., Gerstein, M., & Snyder, M. (2009). RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics, 10(1), 57-63.
  5. Han, Y., Gao, S., Muegge, K., Zhang, W., & Zhou, B. (2015). Advanced Applications of RNA Sequencing and Challenges.Bioinformatics and biology insights, 9(Suppl 1), 29.
  6. Robinson, D., Wang, J., & Storey, J. (2015). A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays. Nucleic Acids Research. 43(20)
  7. Mertens, F., Johansson, B., Fioretos, T., & Mitelman, F. (2015). The emerging complexity of gene fusions in cancer. Nature Reviews Cancer, 15(6), 371-381.
  8. Liu S, Cheng C. Alternative RNA splicing and cancer. Wiley interdisciplinary reviews RNA. 2013,4(5),547-566.

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Somatic Mutation Theory – Why it’s Wrong for Most Cancers, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Somatic Mutation Theory – Why it’s Wrong for Most Cancers

Reporter: Aviva Lev-Ari, PhD, RN

 

 

Somatic Mutation Theory – Why it’s Wrong for Most Cancers.

Cell Physiol Biochem 2016;38:1663-1680. http://www.karger.com/Article/FullText/443106

Björn L.D.M. Brücher and Ijaz S. Jamall

Brucher [a to d] and Jamall [a,b,e]

a Theodor-Billroth-Academy®, Munich, Germany – Sacramento, California, USA;

b INCORE, International Consortium of Research Excellence of the Theodor-Billroth-Academy®, Munich, Germany – Sacramento, California, USA;

c Bon Secours Cancer Institute, Richmond, VA, USA;

d Dep. of Surgery, Carl- Thiem-Klinikum, Cottbus, Germany;

e Risk-Based Decisions Inc., Sacramento, CA, USA

 

Key Words

Carcinogenesis • Somatic mutation theory • Microenvironment • Cell communication • Signaling • Inflammation • Chronic inflammation • Fibrosis • Cell transition • Precancerous niche

Abstract

Hysteron proteron reverses both temporal and logical order and this syllogism occurs in carcinogenesis and the somatic mutation theory (SMT): the first (somatic mutation) occurs only after the second (onset of cancer) and, therefore, observed somatic mutations in most cancers appear well after the early cues of carcinogenesis are in place. It is no accident that mutations are increasingly being questioned as the causal event in the origin of the vast majority of cancers as clinical data show little support for this theory when compared against the metrics of patient outcomes. Ever since the discovery of the double helical structure of DNA, virtually all chronic diseases came to be viewed as causally linked to one degree or another to mutations, even though we now know that genes are not simply blueprints, but rather an assemblage of alphabets that can, under non-genetic influences, be used to assemble a business letter or a work of Shakespearean literature. A minority of all cancers is indeed caused by mutations but the SMT has been applied to all cancers, and even to chemical carcinogenesis, in the absence of hard evidence of causality. Herein, we review the 100 year story of SMT and aspects that show why genes are not just blueprints, how radiation and mutation are associated in a more nuanced view, the proposed risk of cancer and bad luck, and the in vitro and in vivo evidence for a new cancer paradigm. This paradigm is scientifically applicable for the majority of non-heritable cancers and consists of a six-step sequence for the origin of cancer. This new cancer paradigm proclaims that somatic mutations are epiphenomena or later events occurring after carcinogenesis is already underway. This serves not just as a plausible alternative to SMT and explains the origin of the majority of cancers, but also provides opportunities for early interventions and prevention of the onset of cancer as a disease.

  

Conclusions

The incorrect interpretation of data can sometimes appear to be the more parsimonious explanation especially when it has acquired the mantle of a paradigm, as in the case of the SMT. Summa Cancerologica is not hypothetical or ontological. Its syllogism of carcinogenesis needs the consideration of all reasonable perspectives such as whether somatic mutations are later events or epiphenomena occurring at the end of the sequence of events in carcinogenesis. This mutatio praemissarum leads to a reflection of reasoned judgments of correct findings in cancer (mutations within tumors) together with clinical observations (relevance of such mutations to cancer therapy). An overemphasis of the SMT as the sole reason of the origin of carcinogenesis elevated it to the status of a dogma which downplays significant findings of mutations and genetics in different fields of nature, biology and science. However, there is hope that hereditary cancers can be treated in the near future as new technologies make it possible to manipulate proteins packaging DNA to turn on specific gene promoters and enhancers [164]. If this were applicable to the mass of non-hereditary cancers this approach would still be only symptomatic as the genesis of non-hereditary cancers is not caused by somatic mutations though somatic mutations occur within tumors. Focusing on the tumor cell without its origin including the microenvironment won’t be enough [165]. The reasoning on the origin of carcinogenesis, including different step-wise sequences, may help unmask mechanisms of the transition of a normal into a cancer cell (cancer genesis) as well as its different primary pathogenic stimulus, which can serve to prevent or retard cancers instead of concentrating on symptomatic strategies or for a cure for all cancers. It is scientifically valid based on in vitro and in vivo genetic findings that carcinogenesis consists of a six-step multi sequence process [17, 18]. This serves not just as a plausible alternative to the SMT to explain the origin of the majority of cancers, but could also suggest early interventions and thereby prevent the onset of cancer as a disease.

FULL ARTICLE

2016-CELL-PHYSIOL-BIOCHEM-Somatic-Mutation-Theory

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Immune System Stimulants: Articles of Note @pharmaceuticalintelligence.com

Curators: Larry H. Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

 

  • New Approaches to Immunotherapy

 

New Class of Immune System Stimulants: Cyclic Di-Nucleotides (CDN): Shrink Tumors and bolster Vaccines, re-arm the Immune System’s Natural Killer Cells, which attack Cancer Cells and Virus-infected Cells

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Basic Research in Immune Oncology and Molecular Genomics: Methods to Stimulate Immunity by Alteration of Tumor Antigens – Reporting on R&D @MGH

New insights in cancer, cancer immunogenesis and circulating cancer cells

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Issues Need to be Resolved With Immuno-Modulatory Therapies: NK cells, mAbs, and adoptive T cells

 

  •  Current Methods of Immuno-Therapy

 

 

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LIVE 10:25 am – 12:00 pm 4/26/2016 Fireside Chat: Robert Bradway, CEO, Amgen & Immunotherapy I: Checkpoint Activation and Cancer Vaccines @2016 World Medical Innovation Forum: CANCER, April 25-27, 2016, Westin Hotel, Boston

Natural Killer Cell Response: Treatment of Cancer

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Perspectives on Anti-metastatic Effects in Cancer Research 2015

 

  • Evolving Approaches including Combination Oncotherapy

 

LIVE – 8:00 am – 12:00 pm 4/25/2016 – First Look: The Next Wave of Cancer Breakthroughs @2016 World Medical Innovation Forum: CANCER, April 25-27, 2016, Westin Hotel, Boston 2016 World Medical Innovation Forum: CANCER, April 25-27, 2016, Partners HealthCare, Boston, at the Westin Hotel, Boston

Brain Cancer Vaccine in Development and other considerations

Rapid regression of HER2 breast cancer

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Novel biomarkers for targeting cancer immunotherapy

Humanized Mice May Revolutionize Cancer Drug Discovery

Immunomodulatory Therapeutic Antibodies for Cancer, August 13-15, 2013 – Boston, MA – Final Agenda

Melanoma: Molecule in Immune System Could Help Treat Dangerous Skin Cancer

NIH Study Demonstrates that a New Cancer Immunotherapy Method could be Effective against a wide range of Cancers

Aptamers and Scaffolds

 

  • Microbiological Factors in Cancer Growth

 

Microbe meets cancer

Gut microbiome and anti-tumor response

Malaria Protein Anti-cancer Activity

Retroviruses and Immunity

Oncolytic Viruses in Cancer Therapy @ CHI’s PreClinical Congress, June 14, 2016 Westin Boston Waterfront, Boston

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BET Proteins Connect Diabetes and Cancer

Signaling of Immune Response in Colon Cancer

Myc and Cancer Resistance

Renal (Kidney) Cancer: Connections in Metabolism at Krebs cycle and Histone Modulation

Pancreatic Cancer and Crossing Roads of Metabolism

Autophagy-Modulating Proteins and Small Molecules Candidate Targets for Cancer Therapy: Commentary of Bioinformatics Approaches

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Embryonic Stem Cell differentiation

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Plant Homeo Domain Finger Protein 8 Regulates Mesodermal and Cardiac Differentiation of Embryonic Stem Cells Through Mediating the Histone Demethylation of pmaip1

Yan Tang1, Ya-Zhen Hong1, Hua-Jun Bai1, Qiang Wu1, Charlie Degui Chen2, Jing-Yu Lang1, Kenneth R. Boheler3 and Huang-Tian Yang1,4,*

STEM CELLS: 18 APR 2016     http://dx.doi.org:/10.1002/stem.2333

Histone demethylases have emerged as key regulators of biological processes. The H3K9me2 demethylase plant homeo domain finger protein 8(PHF8), for example, is involved in neuronal differentiation, but its potential function in the differentiation of embryonic stem cells (ESCs) to cardiomyocytes is poorly understood. Here, we explored the role of PHF8 during mesodermal and cardiac lineage commitment of mouse ESCs (mESCs). Using a phf8 knockout (ph8-/Y) model, we found that deletion ofphf8 in ESCs did not affect self-renewal, proliferation or early ectodermal/endodermal differentiation, but it did promote the mesodermal lineage commitment with the enhanced cardiomyocyte differentiation. The effects were accompanied by a reduction in apoptosis through a caspase 3-independent pathway during early ESC differentiation, without significant differences between differentiating wide-type (ph8+/Y) and ph8-/Y ESCs in cell cycle progression or proliferation. Functionally, PHF8 promoted the loss of a repressive mark H3K9me2 from the transcription start site of a proapoptotic gene pmaip1 and activated its transcription. Furthermore, knockdown ofpmaip1 mimicked the phenotype of ph8-/Y by showing the decreased apoptosis during early differentiation of ESCs and promoted mesodermal and cardiac commitment, while overexpression of pmaip1 or phf8 rescued the phenotype of ph8-/Y ESCs by increasing the apoptosis and weakening the mesodermal and cardiac differentiation. These results reveal that the histone demethylase PHF8 regulates mesodermal lineage and cell fate decisions in differentiating mESCs through epigenetic control of the gene critical to programmed cell death pathways. Stem Cells2016

 

Significance Statement

Embryonic stem cells (ESCs) have the unique ability to differentiate into derivatives of all three germ layers both in vitro and in vivo. Thus, ESCs provide a unique model for the study of early embryonic development. We report here previously unrecognized effects of histone demethylase plant homeo domain finger protein 8 (PHF8) on mesodermal and early cardiac differentiation. This effect is resulted from the regulation of PHF8 on apoptosis through activating the transcription of pro-apoptotic gene pmaip1. These findings extend the knowledge in understanding of the epigenetic modification in apoptosis during ESC differentiation and of the link between apoptosis and cell lineage decision as well as cardiogenesis.

 

Embryonic stem cells (ESCs) have the unique ability to differentiate into derivatives of all three germ layers both in vitro and in vivo. Due to this plasticity, mechanisms controlling cell autonomous and regulatory events critical to in vivo mammalian development have benefitted from the in vitro study of differentiating ESCs [1, 2]. Early embryogenesis and cavity formation as well as early ESC differentiation, for example, are accompanied by a reduction in proliferation and increased apoptosis [3-5]. Withdrawal of leukemia inhibitory factor (LIF) from mouse embryonic stem cells (mESCs) cultivated in vitro causes approximately 20%-30% of the cells to die by spontaneous (constitutive) apoptosis [4, 5]. This occurs secondary to the induction of cleaved caspase 3 [3] and apoptosis-inducing factor (AIF)-complex proteins [6]. Blockade of spontaneous apoptosis in vitro by a p38 mitogen-activated protein kinase (MAPK) inhibitor alters the differentiation markers and increases the abundance of both antiapoptotic proteins (Bcl-2, Bcl-XL) and Ca2+-binding proteins [4, 7]. In addition, Ca2+ released from type 3 inositol 1, 4, 5-trisphosphate receptors (IP3R3) negatively regulates this apoptotic response, which in turn modulates the mesodermal lineage commitment of early differentiating mESCs [5]. These findings explain, in part, how apoptosis contributes to specific lineage commitment during early development. However, in contrast to the relatively advanced knowledge of signaling pathways [8], little is known about the contribution of epigenetic regulators, especially, histone lysine demethylases (KDMs), in the regulation of apoptosis during ESC differentiation and how the affected programmed cell death by KDMs contributes to the lineage commitment.

Epigenetic regulators and dynamic histone modifications by KDMs are emerging as important players in ESC fate decisions [9]. Histone modifications coordinate transient changes in gene transcription and help maintaining differential patterns of gene expression during differentiation [10-13]. The molecular and biological functions of many KDMs, however, remain enigmatic during ESC differentiation. PHF8, an X-linked gene encoding an evolutionarily conserved histone demethylase harboring an N-terminal plant homeo domain (PHD) and an active jumonji-C domain (JmjC), is able to catalyze demethylation from histones [14, 15]. It is actively recruited to and enriched in the promoters of transcriptionally active genes [14], and it functions to maintain the active state of rRNA through the removal of the repressive H3K9me2 methylation mark at the active rRNA promoters. Mutation of PHF8 is associated with X-linked mental retardation with cleft lip/cleft palate in human [16-18]. Knockdown of phf8 in mouse embryonic carcinoma P19 cells impairs neuronal differentiation [19] and leads to brain defects in zebrafish by directly regulating the expression of the homeo domain transcription factor MSX1/MSXB [20]. However, the precise function of PHF8 in the regulation of lineage differentiation derived from other germ layers remains to be identified.

Here, we report previously unrecognized effects of the PHF8 histone demethylase on germ layer commitment and differentiation of mESCs. The results are based on an assessment of early steps of differentiation to mesodermal lineages and cardiomyocytes using phf8 knockout (phf8-/Y) and wild-type (phf8+/Y) mESCs. The data show that PHF8 regulates gene transcription of a proapoptotic gene pmaip1 (also named Noxa) [21]. Activation or repression of pmaip1 controlled by PHF8 ultimately determines mESC lineage commitment through the regulation of caspase 3-independent apoptosis during mesodermal and cardiac differentiation. Our data reveal that PHF8-mediated the demethylation of histone proteins coordinates ESC lineage commitment through the regulation of apoptosis in early differentiating ESCs.

 

Deletion of phf8 Promotes Mesodermal and Cardiac Lineage Commitment

The PHF8 protein was detectable in undifferentiated ESCs, but its abundance significantly increased within one day of LIF withdrawal. Then it gradually decreased to a level at day 5 lower than that observed in the undifferentiated ESCs (Fig. 1A).    http://onlinelibrary.wiley.com/store/10.1002/stem.2333/asset/image_t/stem2333-fig-0001-t.gif

 

Figure 1. Plant homeo domain finger protein 8 (PHF8) regulates the mesodermal and early cardiac differentiation of mouse embryonic stem cells (mESCs). (A): Western blot analysis of PHF8 expression in undifferentiated and differentiating ESCs. n = 3. (B): quantitative RT-PCR (qRT-PCR) analysis of pluripotency markers nanog, rex1, sox2, and oct4. n = 8. (C): qRT-PCR analysis of gene expression of pluripotency marker oct4; early mesodermal markers brachyury (T), gsc, eomes, and mesp1; cardiovascular progenitor markers flk-1 and nrp1; and the cardiac transcription factors hand1, tbx5, and mef2c during ESC differentiation. n = 5. (D): qRT-PCR analysis of the early ectodermal markersnestin and fgf5 during ESC differentiation. n = 3. (E): qRT-PCR analysis of early endodermal markers afp, foxa2, sox17, and gata4 during ESC differentiation. n = 3. Data are presented as mean ± SEM *, p < .05; **, p < .01; ***, p < .001 compared with the corresponding phf8+/Y value.

To determine the significance of phf8 gene expression on ESC fate decision, we knocked out the X-chromosome-encoded phf8 gene in one allele of male SCR012 ESCs by deletion of exons 7 and 8 through Cre-mediated recombination (Supporting Information Fig. S1A). Gene inactivation was confirmed by the lack of Phf8 mRNA and PHF8 protein expression in these targeted ESCs (Supporting Information Fig. S1B). Transcripts for pluripotency marker genes nanog, rex1 (zfp42), sox2, and oct4 (pou5f1) were not significantly different between phf8+/Y and phf8-/Y ESCs (Fig. 1B). No significant difference was observed in cell morphology (Supporting Information Fig. S1C) of undifferentiated phf8+/Y and phf8-/Y ESCs or in alkaline phosphatase activity (Supporting Information Fig. S1D). Immunofluorescence staining confirmed that the expression of pluripotency marker SOX2 and SSEA-1 did not differ between the phf8+/Y and phf8-/Y ESCs (Supporting Information Fig. S1E). These results indicate that phf8 may be dispensable for normal growth and maintenance of mESCs.

We then analyzed the role of PHF8 in the mesodermal and cardiac lineage commitment. By microarray analysis of differentiating phf8+/Y and phf8-/Y cells from days 0, 1, to 3.5, we found a significant decrease in transcripts for pluripotency markers, accompanied by a significant increase in transcripts for ectoderm, mesoderm and endoderm, while in phf8-/Y cells some transcripts for mesodermal and cardiac lineage commitment were significantly enhanced compared with those in phf8+/Y cells (Supporting Information Fig. S2A). These differentiation-dependent changes in transcript abundance were confirmed by qRT-PCR for early mesodermal markers brachyury (T) [28], goosecoid (gsc),eomes[29], and mesp1[30], cardiovascular progenitor marker flk-1[31, 32] and neuropilin 1 (nrp1) [33]. Early cardiac transcription factors, including myocyte enhancer factor 2C (mef2c) [34], hand1[35], and tbx5[36, 37] were also up-regulated in phf8-/Y cells at differentiation day 5, while no difference in the expression levels of pluripotent markersoct4 (Fig. 1C), rex1, and nanog (Supporting Information Fig. S2B) were detected between phf8+/Y and phf8-/Y cells at the time points examined.

Because mESCs can differentiate into all three germ layers, we also examined whether phf8 affected ectodermal and endodermal differentiation. qRT-PCR analysis did not show any significantly difference in the expression of early ectodermal markers nestin and fgf5 between the phf8+/Y and phf8-/Y cells (Fig. 1D). Moreover, in the induced early ectodermal differentiation system [23], the expression of ectodermal markers nestin, fgf5, and pax6 were comparable between the phf8+/Y and phf8-/Y cells (Supporting Information Fig. S3A). Besides, the expression of endodermal markers afp, foxa2, sox17, and gata4 were not significantly different between the phf8+/Y and phf8-/Y cells (Fig.1E). Consistently, the expression of endodermal markers foxa2, sox17, and gata4 were comparable during induced endodermal differentiation [24] between the phf8+/Y andphf8-/Y cells (Supporting Information Fig. S3B). Thus, phf8 appears not to affect early ectodermal and endodermal differentiation.

The increased mesodermal and cardiac marker expressions were associated with a significant increase in the total number of cardiac progenitors and cardiomyocytes in differentiating phf8-/Y cells. By flow cytometry analysis, marked increases in the population of FLK-1 positive (FLK-1+) cells were detected in phf8-/Y cells at differentiation day 3 and day 4 (Fig. 2A). Consistently, the percentage of contracting EBs was higher in phf8-/Y cells than in phf8+/Y cells (Fig. 2B). The transcripts for progenitor marker nrp1, early cardiac transcription factor tbx5, and cardiac specific genes tnnt2, myh6, myl2, and gja1 were higher in phf8-/Y EBs than those in phf8+/Y ones (Fig. 2C). The areas of immunostained EBs positive for the cardiac cytoskeletal and myofilamental proteins α-actinin and TNNT2 were also greater in phf8-/Y than in phf8+/Y EBs (Fig. 2D). Flow cytometry analysis of MYH6+ (Fig. 2E) and TNNT2+ (Fig. 2F) cells at differentiation day 9 further confirmed the increase of cardiomyocytes in phf8-/Y cells. Taken together, these data indicate that the phf8 deletion facilitates the differentiation of mesodermal and cardiac linage commitment.

Figure 2. phf8 deletion promotes cardiac differentiation of mouse embryonic stem cells (mESCs). (A): Left, representative flow cytometry plots showing FLK-1 expression at differentiation day 3 (n = 6), day 4 and day 5 (n = 3 each). Right, the quantification of flow cytometry data. (B): Differentiation profile of cardiomyocytes during embryoid bodies (EB) outgrowth. n = 6. (C): qRT-PCR analysis of ESCs for the expression of cardiac markers at differentiation day 14. n = 3. (D): Immunofluorescence analysis of TNNT2 and α-actinin in day 14 EBs. Scale bars = 400 μm. (E) Flow cytometry analysis of MYH6 positive cells and (F) TNNT2 positive cells in day 9 EBs. n = 3 each. Data are presented as mean ± SEM *, p < .05; **, p < .01; ***, p < .001 compared with the corresponding phf8+/Y value.   http://onlinelibrary.wiley.com/store/10.1002/stem.2333/asset/image_t/stem2333-fig-0002-t.gif

PHF8 Inactivation Increases Cell Viability but not Proliferation of the Differentiating ESCs

Differentiation of both phf8+/Y and phf8-/Y ESCs via EB formation produced normal round shaped EBs but, by day 3, phf8-/Y EBs were larger than those generated from phf8+/YESCs, and the size differences were visibly obvious at differentiation days 5 and 7 (Fig. 3A). Although no significant differences in cell viability could be demonstrated between undifferentiated phf8+/Y and phf8-/Y ESCs (Fig. 3B), the viability of phf8-/Y cells was significantly greater than that in phf8+/Y cells at differentiation days 3 to 7 (Fig. 3C). However, no significant change in BrdU staining was detected by flow cytometry between phf8+/Y and phf8-/Y ESCs at differentiation days 0, 3, or 5 (Fig. 3D). Moreover, no significant difference in the cell cycle distribution between the differentiating Phf8+/Y and Phf8-/Y ESCs was detected, although the percentage of cells in S phase gradually decreased while those in G1 phase increased upon differentiation (Fig. 3E). Knockout of phf8 thus increases cell numbers in the early differentiating ESCs through the improvement of cell viability without changes in cell proliferation or cell cycle progression.

Figure 3. phf8 deletion increases cell viability in differentiating mouse embryonic stem cells (mESCs) without affecting cell proliferation. (A): Left, phase-contrast images of embryoid bodies (EB) morphology during EB formation from ESCs. Scale bar = 200 μm. Right, the diameter of EB formed from ESCs. (B): Cell viability of undifferentiated and (C): differentiating ESCs analyzed by MTT assay for seven consecutive days. n = 3. (D): Flow cytometry analysis of BrdU positive proportion of undifferentiated (n = 4) and differentiating ESCs at day 3 and day 5.n = 5 each. (E): Flow cytometry analysis of cell cycle distribution by propidium iodide (PI) staining at differentiation day 3 (n = 6) and day 5 (n = 3). Data are presented as mean ± SEM *, p < .05; ***, p < .001 compared with the corresponding phf8+/Y value.   http://onlinelibrary.wiley.com/store/10.1002/stem.2333/asset/image_t/stem2333-fig-0003-t.gif

PHF8 Regulates Apoptosis During the Early Stage of Cardiac Lineage Commitment

We then examined whether cell death might account for the differences in the cell viability observed between the differentiating phf8+/Y and phf8-/Y ESCs. In undifferentiated ESCs, no significant difference was demonstrated with Annexin V (an early apoptosis marker) staining, TUNEL assay, total DNA fragmentation or caspase 3 protein cleavage between phf8+/Y and phf8-/Y cells (Fig. 4A–4C, 4E). In contrast, Annexin V staining (Fig. 4A) and TUNEL assay (Fig. 4B) showed significant decreases in the number of apoptotic cells in phf8-/Y ESCs at differentiation days 3 and 5 compared with those in phf8+/Y cells. Genomic DNA fragmentation with a pattern typical for apoptosis was detected in phf8+/Y cells at differentiation days 3 and 5, but it was reduced in phf8-/Y cells at the same time points (Fig. 4C). Moreover, approximately 35% of Annexin V+ cells were present in FLK-1+/phf8+/Y cells at differentiation day 4, whereas only 9% of the cells were Annexin V+ in FLK-1+/phf8-/Y cells (Fig. 4D). The ratio of TUNEL+ to either NESTIN+ (ectoderm) or SOX17+ (endoderm) cells did not differ between the phf8+/Y and phf8-/Y cells (Supporting Information Fig. S3C, S3D). In addition, phf8+/Y ESCs at differentiation days 3 and 5 increased the caspase 3 cleavage (Fig. 4E, upper and lower left panels) and the ratio of cleaved caspase 3 to total caspase 3 protein (Fig. 4E, lower right panel). Unexpectedly, the ratio of cleaved caspase 3 to total caspase 3 in phf8-/Y ESCs did not significantly differ from that observed in phf8+/Y ones. Consistently, a significant enhancement of the downstream target PARP1 cleavage [38, 39] was observed at differentiation days 3 and 5, but it was comparable between the phf8+/Y andphf8-/Y cells (Fig. 4F). These data suggest that the cell death associated with phf8 function does not operate through the conventional caspase 3-mediated apoptosis.

Figure 4. Plant homeo domain finger protein 8 (PHF8) regulates apoptosis during the early mouse embryonic stem cells (mESC) differentiation. (A): Left, representative flow cytometry plots showing Annexin V (x-axis), and PI (y-axis) staining in ECSs at differentiation day 0 (n = 4), day 3 (n = 3) and day 5 (n = 7). Right, the quantification of flow cytometry data. (B): Flow cytometry detection of apoptotic responses of TUNEL positive cells at differentiation day 0 (n = 3), day 3 (n = 4), and day 5 (n = 4). (C): DNA laddering analysis at differentiation days 0, 3, and 5. n = 6 each. (D): Cells double stained with FLK-1 and Annexin V were analyzed by flow cytometry at differentiation day 4. n = 3. (E): Western blot analysis of caspase 3 during the mESC differentiation. β-actin was used as a loading control. n = 4. (F): Western blot analysis of PARP1 expression during the differentiation. β-actin was used as a loading control. n = 4. Data are presented as mean ± SEM *, p < .05; ***, p < .001 compared with the corresponding phf8+/Yvalue; #, p < .05; ##, p < .01 compared with the corresponding d0 value.  http://onlinelibrary.wiley.com/store/10.1002/stem.2333/asset/image_t/stem2333-fig-0004-t.gif

pmaip1 is a Direct Target Gene of PHF8 in the Early Differentiating ESCs

To understand how PHF8 might regulate apoptosis during early ESC differentiation, we compared the profiles of apoptosis-related gene transcripts in undifferentiated and early differentiating phf8+/Y and phf8-/Y ESCs using gene expression microarrays. Among the apoptosis-related genes, the transcript to pmaip1, a proapoptotic Bcl-2 family member crucial in fine-turning the cell death decision [21, 40-42], was markedly increased during early differentiation of phf8+/Y cells but it was reduced in phf8-/Y cells at differentiation days 1 and 3.5 (Fig. 5A). These expression patterns were confirmed by qRT-PCR during cardiac differentiation (Fig. 5B), and the results were consistent with the apoptotic pattern observed during the early ESC differentiation (Fig. 4A–4C). In addition, qRT-PCR analysis showed that the expression of pmaip1 did not show any significant difference between the phf8+/Y and phf8-/Y cells during the induced ectodermal (Supporting Information Fig. S3E) or endodermal (Supporting Information Fig. S3F) differentiation.

Figure 5. pmaip1 is a direct target gene of plant homeo domain finger protein 8 (PHF8) in mouse embryonic stem cells (mESCs). (A): Microarray gene expression heat map depicting the expression of apoptosis-related genes at differentiation days 0, 1 and 3.5 in phf8+/Y and phf8-/Y ESCs. The expression values in log2 scale were calculated and presented on the heat map with red representing highly abundant transcripts and green representing poorly abundant transcripts. n = 3. (B): qRT-PCR analysis of pmaip1 during the ESC differentiation. (C): ChIP assay of PHF8 around the TSS of pmaip1 in phf8+/Y andphf8-/Y ESCs at differentiation days 0 and 3. n = 4 each. (D): Western blot analysis of H3K9me2 and H3 in phf8+/Y and phf8-/Y ESCs during the differentiation. H3 was used as a loading control. n = 9. (E): H3K9me2 staining inphf8+/Y and phf8-/Y embryoid bodies (EBs) at differentiation day 1. Scale bars = 25 μm. (F): ChIP assay of H3K9me2 around the TSS of pmaip1 in phf8+/Y andphf8-/Y ESCs at differentiation day 3. n = 4. Data are presented as mean ± SEM. *, p < .05; **, p < .01; ***, p < .001 compared with the corresponding phf8+/Y value or d0.  http://onlinelibrary.wiley.com/store/10.1002/stem.2333/asset/image_t/stem2333-fig-0005-t.gif

A direct link between the PHF8 and pmaip1 was then confirmed by ChIP analysis. We detected the endogenous binding of PHF8 at the transcription start site (TSS, from −45 bp to 104 bp) of pmaip1 in phf8+/Y ESCs and determined that binding was enhanced at differentiation day 3. The binding of PHF8 was not detectable above the IgG control levels in phf8-/Y cells (Fig. 5C). Global methylation (H3K9me2 normalized to H3) was unchanged at differentiation days 3 and 5, but it was significantly enhanced at differentiation day 1 in phf8-/Y cells (Fig. 5D). The augmentation of H3K9me2 methylation in phf8-/Y ESCs was then confirmed by immunostaining at differentiation day 1 (Fig.5E). An increase in the repressive mark of H3K9me2 was also observed at the TSS of pmaip1 in the early differentiating phf8-/Y ESCs (Fig. 5F), indicating that the PHF8 demethylase activity is actively involved in the regulation of pmaip1 gene.

Transient Knockdown of pmaip1 Decreases Apoptosis and Promotes Mesodermal and Cardiac Differentiation

To clarify the role of pmaip1 in mESC differentiation, we transfected specific siRNAs against pmaip1 (si-Pmaip1) into phf8+/Y ESCs followed by EB formation. The negative control siRNA (si-NC) did not alter pmaip1 transcript levels compared with untreated (NT) cells, while si-Pmaip1 significantly inhibited pmaip1 transcripts by 74%-76% at differentiation days 0 and 1 (Fig. 6A-a). si-Pmaip1 cells had fewer TUNEL+ cells compared with the NT and si-NC cells at differentiation day 3 in both phf8+/Y and phf8-/Y cells (Fig. 6A-b). We then examined whether the pmaip1 knockdown influences mesodermal and early cardiac differentiation. As shown in Figure 6B, the apoptosis of FLK-1+ cells was significantly decreased in si-Pmaip1 mESCs (Fig. 6B). The expression of T and gsc as well as nrp1 and flk-1 were increased in si-Pmaip1 cells compared with those in NT and si-NC cells at differentiation day 3. In addition, the expression of cardiac transcript factors mef2c and tbx5 was up-regulated at differentiation day 5, and myh6 andtnnt2 were up-regulated at differentiation day 9 (Fig. 6C). We also transfected si-Pmaip1 into phf8-/Y ESCs. The expression of pmaip1 was downregulated at differentiation day 0 and day 1 in phf8-/Y ESCs with si-Pmaip1 (Supporting Information as Fig. S4A-a), accompanied by a decrease in TUNEL+ cells compared with NT and si-NC (Fig. 6A-b), while Annexin V remained unchanged (Supporting Information Fig. S4A-b). The expression of nrp1 and flk1 did not significantly change in phf8-/Y ESCs with si-Pmaip1 at differentiation day 3, while mef2c was upregulated at differentiation day 5, and myh6 was upregulated at differentiation day 9 (Supporting Information as Fig. S4B). These results suggest that downregulation of pmaip1 in phf8-/Y ESCs may not lead to as robust of a phenotype as it did in phf8+/Y ESCs. This difference is likely due to the level ofpmaip1 during early differentiation of phf8-/Y ESCs was already decreased to a low level similar to that observed in the undifferentiated cells (Fig. 5B). Taken together, these data demonstrate that the decreased apoptosis via down-regulation of pmaip1 contributes, at least partially, to the phf8-/Y-facilitated mesodermal and cardiomyocyte commitment.

Figure 6. Plant homeo domain finger protein 8 (PHF8) regulates the mesodermal and cardiac differentiation through pmaip1. (A-a): qRT-PCR analysis of thepmaip1 expression in phf8+/Y ESCs after being transiently transfected with si-NC or si-Pmaip1. n = 4. (A-b): Apoptosis cells were quantified by flow cytometry analysis of TUNEL assay at differentiation day 3 in phf8+/Y and phf8-/Y ESCs after transient transfection with si-NC or si-Pmaip1. n = 3. (B): Cells double stained with FLK-1 and Annexin V were analyzed by flow cytometry at differentiation day 4. n = 4. (C): qRT-PCR analysis of the expression of T, gsc, flk-1, nrp1, tbx5, mef2c, myh6, and tnnt2 in phf8+/Y ESCs after transient transfection with si-NC or si-Pmaip1. n = 5. (D): Flow cytometry detection of TUNEL positive cells at differentiation day 3, Annexin V positive cells and double stained FLK-1 and Annexin V at differentiation day 4 in phf8-/Y, phf8-NC-/+, phf8-pmaip1-/+, and phf8-hPHF8-/+ mouse embryonic stem cells (mESCs). n = 4. (E): qRT-PCR analysis of the expression of T, gsc, flk-1, nrp1, tbx5, mef2c, myh6, and tnnt2 in phf8-/Y, phf8-NC-/+, phf8-pmaip1-/+, and phf8-hPHF8-/+ mESCs. n = 3. Data are presented as mean ± SEM. *, p < .05; **, p < .01; ***, p < .001 compared with the corresponding phf8+/Y or phf8-/Y value.
http://onlinelibrary.wiley.com/store/10.1002/stem.2333/asset/image_t/stem2333-fig-0006-t.gif

Overexpression of pmaip1 or hPHF8 in phf8-/Y ESCs Increases Apoptosis and Weakens Mesodermal and Cardiac Differentiation

To further determine whether PHF8 contributes to mesoderm and cardiac cell commitment through the regulation of apoptosis via targeting pmaip1, we rescued the expression of pmaip1 and phf8 in phf8-/Y ESCs by generating pmaip1-ovexpressing phf8-/Y mESCs (phf8-pmaip1-/+ mESCs) and hPHF8-overexpressing phf8-/Y mESCs (phf8-hPHF8-/+ mESCs). The qRT-PCR analysis confirmed that the expression of hPHF8 or pmaip1 was significantly upregulated in the respective overexpressing cell lines (Supporting Information Fig. S4C). The expression of pmaip1 in undifferentiated phf8-/Y mESCs was not affected by hPHF8 overexpression. However, Pmaip1 transcripts increased by differentiation day 3 in overexpressing cells (Supporting Information Fig. S4D), indicating that PHF8 does regulate the expression of pmaip1 during differentiation. Both TUNEL and Annexin V analysis revealed significant increases of apoptosis in phf8-pmaip1-/+ and phf8-hPHF8-/+ mESCs compared with the phf8-/Y andphf8-NC-/+ mESCs at differentiation day 3 or day 4, accompanied by a higher apoptosis ratio in FLK-1+ cells (Fig. 6D). Moreover, the expression of T and gsc as well as nrp1and flk-1 were significantly decreased in phf8-pmaip1-/+ and phf8-hPHF8-/+ mESCs at differentiation day 3, followed by a down-regulation of mef2c and tbx5 at differentiation day 5, and myh6 and tnnt2 at differentiation day 9 (Fig. 6E). In addition, TUNEL analysis showed no changes in the apoptotic responses either through knockout or overexpression of phf8 compared with the corresponding wild-type cells or phf8+/Y cells during induced ectodermal differentiation (Supporting information Fig. S4E). These data are consistent with a regulatory role of phf8 on mesodermal and cardiac differentiation through targeting of pmaip1

Discussion

This is the first study to unravel a regulatory role of histone demethylase in the differentiation of ESCs through the control of apoptosis and subsequent effects on cell lineage commitment. The role of PHF8 in the regulation of ESC differentiation to the mesodermal lineage and cardiac differentiation is supported by selective changes in RNA markers for mesodermal lineages, and an increase in cardiomyocyte progenitors and cardiomyocytes (Figs. 1C, 2C). Moreover, deletion of phf8 specifically inhibits apoptosis of Flk-1+ mesodermal cells with a concomitant reduction in Annexin V+ staining (Fig. 4D) and cardiac differentiation (Fig. 2B–E), while the ratio of TUNEL+ to either NESTIN+(ectodermal cells) or SOX17+ (endodermal cells) cells does not differ between the phf8+/Y and phf8-/Y lines (Supporting Information Fig. S3C, S3D). Consistently, the proportion of early apoptotic cells (Annexin V+) in pmaip1-knockdown (Fig. 6B) is also decreased, while pmaip1-overexpression or hPHF8-overexpression in phf8-/Y cells increase the proportion of TUNEL+ and Annexin V+ cells simultaneously with a reduction in mesodermal and cardiac differentiation (Fig. 6D, 6E). These findings indicate that the PHF8 functions, at least partially, through regulation of apoptosis.

It is well known that the regulation of apoptosis is of critical importance for proper ESC differentiation and embryo development [8, 43]. ESC differentiation is regulated by apoptosis induced by MAPK activation [7] and IP3R3-regulated Ca2+ release [5]. Previously only histone 3 lysine 4 methyltransferase MLL2 had been shown to activate the antiapoptotic gene bcl2 to inhibit apoptosis during ESC differentiation [44]. The data presented, here, extends and reveals the importance of epigenetic controls in the activation of proapoptotic gene associated with ESC differentiation.

Mesodermal and cardiac differentiation have been shown to be regulated by the histone demethylase ubiquitously transcribed tetratricopeptide repeat, X chromosome (UTX)[13, 45] and jumonji domain–containing protein 3 (JMJD3) [12] through transcriptional activation of mesodermal and cardiac genes. These findings together with those presented in this paper support the critical role of histone demethylases in lineage commitment through regulatory mechanisms that control the expression of core lineage specific transcription factors and apoptotic genes. The decrease in apoptosis through deletion of phf8 can be attributed to the maintenance of repressive H3K9me2 mark on the TSS of pmaip1 after phf8 deletion, resulting in a ∼70% downregulation of pmaip1 at differentiation day 3 in the phf8-/Y cells (Fig. 5B). The pro-apoptotic gene pmaip1 is, therefore, epigenetically regulated by the histone demethylase, which subsequently affects the mesodermal and cardiac differentiation.

PMAIP1 is a Bcl2 homology domain 3 (BH3)-only protein that acts as an important mediator of apoptosis [46]. Its expression is regulated transcriptionally by various transcription factors and, when present, it acts to promote cell death in a variety of ways [21] including caspase 3 dependent [47] and independent apoptosis [48] and autophagy [40]. Here, we find that PHF8 and its regulation on the pmaip1 promote DNA fragmentation and cell death most likely through a caspase 3-independent pathway. This conclusion is based on the observation that neither the ratio of cleaved caspase 3 to total caspase 3 [49, 50] nor PARP1, a downstream target of caspase 3, is significantly affected. While this may be explained as the inhibitor of apoptosis proteins can counteract the function of caspase 3 [51, 52], the exact mechanisms we observed here need to be further explored.

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Finch character displacement

Larry H. Bernstein, MD, FCAP

LPBI

 

Genetic Study of Darwin’s Finches Catches Evolution in Action

http://www.genengnews.com/gen-news-highlights/genetic-study-of-darwin-s-finches-catches-evolution-in-action/81252647/

http://www.genengnews.com/Media/images/GENHighlight/Apr22_2016_PeterRGrant_MediumGroundFinch2037196235.jpg

The medium ground finch (Geospiza fortis), shown here, diverged in beak size from the large ground finch (Geospiza magnirostris) on Daphne Major Island, Galápagos following a severe drought. Genomic screening of the genomes of medium ground finches revealed that a particular gene, HMGA2, played a large role in the rapid evolution of a smaller overall beak size in the medium ground finch. [Peter R. Grant]

An evolutionary phenomenon first described by Charles Darwin has the support of new and unusually strong supporting evidence. The phenomenon, called character displacement, may occur when species compete for the same food source. The species may evolve different body shapes, such as different beak sizes in the case of finches, diverging from each other until they relieve competitive stress.

Darwin developed the idea of character displacement after observing the finches of the Galápagos Islands. He proposed that changes in the size and form of the beak have enabled different species to utilize different food resources, such as insects, seeds, and nectar from cactus flowers, as well as blood from seabirds.

In a study of character displacement among Darwin’s finches, researchers from Uppsala University and Princeton University have now identified a gene that explains variation in beak size within and among species. The gene contributed to a rapid shift in beak size of the medium ground finch following a severe drought.

The details of the study appeared April 22 in the journal Science, in an article entitled, “A Beak Size Locus in Darwin’s Finches Facilitated Character Displacement during a Drought.” The article describes how the researchers alighted on a gene called HMGA2 after screening the genomes of medium ground finches that survived or died during a drought that occurred between 2004 and 2005. The researchers found that the HMGA2 gene comes in two forms: one is common in finches with small beaks, whereas the other is common in finches with large beaks. The proportion of the two forms in the birds’ genome changed as a result of the better survival of birds with small beaks.

“We used genomic analysis to investigate the genetic basis of a documented character displacement event in Darwin’s finches on Daphne Major in the Galápagos Islands,” wrote the authors. “We discovered a genomic region containing the HMGA2 gene that varies systematically among Darwin’s finch species with different beak sizes. Two haplotypes that diverged early in the radiation were involved in the character displacement event.”

In a previous study from the same team, the ALX1 gene was revealed to control beak shape (pointed or blunt). The HMGA gene that figures in the current study was previously associated with variation in body size in dogs and horses, and it is one of the genes that show the most consistent association with variation in stature in humans, a trait that is affected by hundreds of genes. HMGA2 has also a role in cancer biology as it affects the epithelial–mesenchymal transition (EMT) that is important for metastasis and cancer progression.

“Our data show that beak morphology is affected by many genes, as is the case for most biological traits,” said Sangeet Lamichhaney, the current study’s first author and a doctoral student in the laboratory of Leif Andersson, one of the study’s senior authors and a genomics professor at Uppsala. “However, we are convinced that we now have identified the two loci with the largest individual effects that have shaped the evolution of beak morphology among the Darwin’s finches.”

Andersson collaborated with Princeton researchers Peter Grant, the Class of 1877 Professor of Zoology, Emeritus, and B. Rosemary Grant, a senior research biologist, emeritus, in ecology and evolutionary biology.

“It was an exceptionally strong natural-selection event,” noted Peter Grant, who pointed out that that because Daphne Major is in an entirely natural state, the occurrence was completely unaffected by humans. “Now we have demonstrated that HMGA2 played a critical role in this evolutionary shift and that the natural selection acting on this gene during the drought is one of the highest yet recorded in nature.”

“This research tells us that a complex trait such as beak size can evolve significantly in a short time when the environment is stressful,” Rosemary Grant added. “We know that bacteria can evolve very quickly in the lab, but it is quite unusual to find a strong evolutionary change in a short time in a vertebrate animal.”

 

Linked loci and Galapagos finch size

Observations of parallel evolution in the finches of the Galapagos, including body and beak size, contributed to Darwin’s theories. Lamichhaney et al. carried out whole-genome sequencing of 60 Darwin’s finches. These included small, medium, and large ground finches as well as small, medium, and large tree finches. A genomic region containing the HMGA2 gene correlated strongly with beak size across different species. This locus appears to have played a role in beak diversification throughout the radiation of Darwin’s finches.

Science, this issue p. 470

Ecological character displacement is a process of morphological divergence that reduces competition for limited resources. We used genomic analysis to investigate the genetic basis of a documented character displacement event in Darwin’s finches on Daphne Major in the Galápagos Islands: The medium ground finch diverged from its competitor, the large ground finch, during a severe drought. We discovered a genomic region containing the HMGA2 gene that varies systematically among Darwin’s finch species with different beak sizes. Two haplotypes that diverged early in the radiation were involved in the character displacement event: Genotypes associated with large beak size were at a strong selective disadvantage in medium ground finches (selection coefficient s = 0.59). Thus, a major locus has apparently facilitated a rapid ecological diversification in the adaptive radiation of Darwin’s finches.

 

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New Insights into mtDNA, mitochondrial proteins, aging, and metabolic control

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Newly discovered proteins may protect against age-related illnesses  

The proteins could play a key role in the aging process and the onset of diseases linked to older age

BY Beth Newcomb   APRIL 13, 2016

http://news.usc.edu/98412/newly-discovered-proteins-may-protect-against-agings-illnesses/

http://news.usc.edu/files/2016/04/20160208_PinchasCohen_web-824×549.jpg

Pinchas Cohen led a team that identified tiny proteins that appear to play a role in controlling how the body ages. (Photo/Beth Newcomb)

A group of six newly discovered proteins may help to divulge secrets of how we age, potentially unlocking insights into diabetes, Alzheimer’s, cancer and other aging-related diseases.

The tiny proteins appear to play several big roles in our bodies’ cells, from decreasing the amount of damaging free radicals and controlling the rate at which cells die to boosting metabolism and helping tissues throughout the body respond better to insulin. The naturally occurring amounts of each protein decrease with age, leading researchers to believe that they play an important role in the aging process and the onset of diseases linked to older age.

The research team led by Pinchas Cohen, dean of the USC Davis School of Gerontology, identified the tiny proteins for the first time and observed their surprising origin from organelles in the cell called mitochondria and their game-changing roles in metabolism and cell survival. This latest finding builds upon prior research by Cohen and his team that uncovered two significant proteins, humanin and MOTS-c, hormones that appear to have significant roles in metabolism and diseases of aging.

Unlike most other proteins, humanin and MOTS-c are encoded in mitochondria, the structure within cells that produces energy from food, instead of in the cell’s nucleus where most genes are contained.

Key functions

Mitochondria have their own small collection of genes, which were once thought to play only minor roles within cells but now appear to have important functions throughout the body. Cohen’s team used computer analysis to see if the part of the mitochondrial genome that provides the code for humanin was coding for other proteins as well. The analysis uncovered the genes for six new proteins, which were dubbed small humanin-like peptides, or SHLPs, 1 through 6 (the name of this hardworking group of proteins is appropriately pronounced “schlep”).

After identifying the six SHLPs and successfully developing antibodies to test for several of them, the team examined both mouse tissues and human cells to determine their abundance in different organs as well as their functions. The proteins were distributed quite differently among organs, which suggests that the proteins have varying functions based on where they are in the body.

Of particular interest is SHLP 2, Cohen said. The protein appears to have profound insulin-sensitizing, anti-diabetic effects as well as potent neuro-protective activity that may emerge as a strategy to combat Alzheimer’s disease. He added that SHLP 6 is also intriguing, with a unique ability to promote cancer cell death and thus potentially target malignant diseases.

“Together with the previously identified mitochondrial peptides, the newly recognized SHLP family expands the understanding of the mitochondria as an intracellular signaling organelle that communicates with the rest of the body to regulate metabolism and cell fate,” Cohen said. “The findings are an important advance that will be ripe for rapid translation into drug development for diseases of aging.”

The study first appeared online in the journal Aging on April 10. Cohen’s research team included collaborators from the Albert Einstein College of Medicine; the findings have been licensed to the biotechnology company CohBar for possible drug development.

The research was supported by a Glenn Foundation Award and National Institutes of Health grants to Cohen (1P01AG034906, 1R01AG 034430, 1R01GM 090311, 1R01ES 020812) and an Ellison/AFAR postdoctoral fellowship to Kelvin Yen. Study authors Laura Cobb, Changhan Lee, Nir Barzilai and Pinchas Cohen are consultants and stockholders of CohBar Inc.

Feature: The man who wants to beat back aging

By Stephen S. Hall Sep. 16, 201

Nir Barzilai hopes to persuade FDA to bless the proposed anti-aging trial, which is unconventional in its goals and design.
http://www.sciencemag.org/news/2015/09/feature-man-who-wants-beat-back-aging

On a blazingly hot morning this past June, a half-dozen scientists convened in a hotel conference room in suburban Maryland for the dress rehearsal of what they saw as a landmark event in the history of aging research. In a few hours, the group would meet with officials at the U.S. Food and Drug Administration (FDA), a few kilometers away, to pitch an unprecedented clinical trial—nothing less than the first test of a drug to specifically target the process of human aging.

“We think this is a groundbreaking, perhaps paradigm-shifting trial,” said Steven Austad, chairman of biology at the University of Alabama, Birmingham, and scientific director of the American Federation for Aging Research (AFAR). After Austad’s brief introductory remarks, a scientist named Nir Barzilai tuned up his PowerPoint and launched into a practice run of the main presentation.

Barzilai is a former Israeli army medical officer and head of a well-known study of centenarians based at the Albert Einstein College of Medicine in the Bronx, New York. To anyone who has seen the ebullient scientist in his natural laboratory habitat, often in a short-sleeved shirt and always cracking jokes, he looked uncharacteristically kempt in a blue blazer and dress khakis. But his practice run kept hitting a historical speed bump. He had barely begun to explain the rationale for the trial when he mentioned, in passing, “lots of unproven, untested treatments under the category of anti-aging.” His colleagues pounced.

“Nir,” interrupted S. Jay Olshansky, a biodemographer of aging from the University of Illinois, Chicago. The phrase “anti-aging … has an association that is negative.”

“I wouldn’t dignify them by calling them ‘treatments,’” added Michael Pollak, director of cancer prevention at McGill University in Montreal, Canada. “They’re products.”

Barzilai, a 59-year-old with a boyish mop of gray hair, wore a contrite grin. “We know the FDA is concerned about this,” he conceded, and deleted the offensive phrase.

Then he proceeded to lay out the details of an ambitious clinical trial. The group—academics all—wanted to conduct a double-blind study of roughly 3000 elderly people; half would get a placebo and half would get an old (indeed, ancient) drug for type 2 diabetes called metformin, which has been shown to modify aging in some animal studies. Because there is still no accepted biomarker for aging, the drug’s success would be judged by an unusual standard—whether it could delay the development of several diseases whose incidence increases dramatically with age: cardiovascular disease, cancer, and cognitive decline, along with mortality. When it comes to these diseases, Barzilai is fond of saying, “aging is a bigger risk factor than all of the other factors combined.”

But the phrase “anti-aging” kept creeping into the rehearsal, and critics kept jumping in. “Okay,” Barzilai said with a laugh when it came up again. “Third time, the death penalty.”

The group’s paranoia about the term “anti-aging” captured both the audacity of the proposed trial and the cultural challenge of venturing into medical territory historically associated with charlatans and quacks. The metformin initiative, which Barzilai is generally credited with spearheading, is unusual by almost any standard of drug development. The people pushing for the trial are all academics, none from industry (although Barzilai is co-founder of a biotech company, CohBar Inc., that is working to develop drugs targeting age-related diseases). The trial would be sponsored by the nonprofit AFAR, not a pharmaceutical company. No one stood to make money if the drug worked, the scientists all claimed; indeed, metformin is not only generic, costing just a few cents a dose, but belongs to a class of drugs that has been part of the human apothecary for 500 years. Patient safety was unlikely to be an issue; millions of diabetics have taken metformin since the 1960s, and its generally mild side effects are well-known.

Finally, the metformin group insisted they didn’t need a cent of federal money to proceed (although they do intend to ask for some). Nor did they need formal approval from FDA to proceed. But they very much wanted the agency’s blessing. By recognizing the merit of such a trial, Barzilai believes,  FDA would make aging itself a legitimate target for drug development.

By the time the scientists were done, the rehearsal—which was being filmed for a television documentary—had the feel of a pep rally. They spoke with unguarded optimism. “What we’re talking about here,” Olshansky said, “is a fundamental sea change in how we look at aging and disease.” To Austad, it is “the key, potentially, to saving the health care system.”

As the group piled into a van for the drive to FDA headquarters, there was more talk about setting precedents and opening doors. So it was a little disconcerting when Austad led the delegation up to the main entrance of FDA—and couldn’t get the door open.   ……

Mitochondrial Peptides Found in a Preclinical Study Seen to Control Cell Metabolism

APRIL 13, 2016 BY MAGDALENA KEGEL  IN NEWS.
http://mitochondrialdiseasenews.com/2016/04/13/newly-discovered-mitochondrial-factors-might-give-insights-into-aging/

 

CohBar, a developer of mitochondria-based therapeutics, announced that preclinical research by its academic collaborators has found small humanin-like peptides (SHLPs) that can control metabolism and cell survival. The findings have implications for age-related diseases such as Alzheimer’s and cancer.

The study, “Naturally Occurring Mitochondrial-derived Peptides are Age-dependent Regulators of Apoptosis, Insulin Sensitivity, and Inflammatory Markers,” was the result of a joint effort between researchers at the University of Southern California (USC) and theInstitute for Aging Research at the Albert Einstein College of Medicine of Yeshiva University. The study was published in the journal Aging.

Researchers discovered the SHLPs by examining the genome of mitochondria with the help of a bioinformatics approach, which identified six peptides. The team then verified the presence of the factors and explored their function in laboratory animals.

CohBar, who have the exclusive license to develop SHLPs into therapeutics, works closely with its academic partners to explore the peptides in preclinical models.

While it was previously believed that mitochondria only have 37 genes, research has revealed that the mitochondrial genome is far more versatile, potentially harboring a multitude of new genes, which can encode peptides acting as cellular signaling factors. The peptides, it has turned out, have shown neuroprotective and anti-inflammatory effects, and act to protect cells in disease-modifying ways in preclinical models of aging.

CohBar’s goal is to bring these peptides to the market as therapies for age-related diseases, such as obesity, type 2 diabetes, cancer, atherosclerosis and neurodegenerative disorders.

“Together with the previously described mitochondrial-derived peptides humanin and MOTS-c, the SHLP family expands our understanding of the role that these peptides play in intracellular signaling throughout the body to regulate both metabolism and cell survival,” Pinchas Cohen, dean of the USC Leonard Davis School of Gerontology, founder and director of CohBar, and the study’s senior author, said in a press release. “These findings further illustrate the enormous potential that mitochondria-based therapeutics could have on treating age-associated diseases like Alzheimer’s and cancer.”

“The pre-clinical evidence continues to confirm that these peptides represent a new class of naturally occurring metabolic regulators,” added Simon Allen, CohBar’s CEO. “They form the foundation of our pipeline of first-in-class treatments for age-related diseases, and we are committed to rapidly advancing them through pre-clinical and clinical activities as we move forward.”

Naturally occurring mitochondrial-derived peptides are age-dependent regulators of apoptosis, insulin sensitivity, and inflammatory markers

Laura J. Cobb1,5, Changhan Lee2, Jialin Xiao2, Kelvin Yen2, Richard G. Wong2, Hiromi K. Nakamura1, ….., Derek M. Huffman4, Junxiang Wan2, Radhika Muzumdar3, Nir Barzilai4 , and Pinchas Cohen2
http://www.impactaging.com/papers/v8/n4/full/100943.html

Mitochondria are key players in aging and in the pathogenesis of age-related diseases. Recent mitochondrial transcriptome analyses revealed the existence of multiple small mRNAs transcribed from mitochondrial DNA (mtDNA). Humanin (HN), a peptide encoded in the mtDNA 16S ribosomal RNA region, is a neuroprotective factor. An in silico search revealed six additional peptides in the same region of mtDNA as humanin; we named these peptides small humanin-like peptides (SHLPs). We identified the functional roles for these peptides and the potential mechanisms of action. The SHLPs differed in their ability to regulate cell viability in vitro. We focused on SHLP2 and SHLP3 because they shared similar protective effects with HN. Specifically, they significantly reduced apoptosis and the generation of reactive oxygen species, and improved mitochondrial metabolism in vitro. SHLP2 and SHLP3 also enhanced 3T3-L1 pre-adipocyte differentiation. Systemic hyperinsulinemic-euglycemic clamp studies showed that intracerebrally infused SHLP2 increased glucose uptake and suppressed hepatic glucose production, suggesting that it functions as an insulin sensitizer both peripherally and centrally. Similar to HN, the levels of circulating SHLP2 were found to decrease with age. These results suggest that mitochondria play critical roles in metabolism and survival through the synthesis of mitochondrial peptides, and provide new insights into mitochondrial biology with relevance to aging and human biology.

Human mitochondrial DNA (mtDNA) is a double-stranded, circular molecule of 16,569 bp and contains 37 genes encoding 13 proteins, 22 tRNAs, and 2 rRNAs. Recent mitochondrial transcriptome analyses revealed the existence of small RNAs derived from mtDNA [1]. In 2001, Nishimoto and colleagues identified humanin (HN), a 24-amino-acid peptide encoded from the 16S ribosomal RNA (rRNA) region of mtDNA. HN is a potent neuroprotective factor capable of antagonizing Alzheimer’s disease (AD)-related cellular insults [2]. HN is a component of a novel retrograde signaling pathway from the mitochondria to the nucleus, which is distinct from mitochondrial signaling pathways, such as the SIRT4-AMPK pathway [3]. HN-dependent cellular protection is mediated in part by interacting with and antagonizing pro-apoptotic Bax-related peptides [4] and IGFBP-3 (IGF binding protein 3) [5].

Because of their involvement in energy production and free radical generation, mitochondria likely play a major role in aging and age-related diseases [68]. In fact, improvement of mitochondrial function has been shown to ameliorate age-related memory loss in aged mice [9]. Recent studies have shown that HN levels decrease with age, suggesting that HN could play a role in aging and age-related diseases, such as Alzheimer’s disease (AD), atherosclerosis, and diabetes. Along with lower HN levels in the hypothalamus, skeletal muscle, and cortex of older rodents, the circulating levels of HN were found to decline with age in both humans and mice [10]. Notably, circulating HN levels were found to be (i) significantly higher in long-lived Ames dwarf mice but lower in short-lived growth hormone (GH) transgenic mice, (ii) significantly higher in a GH-deficient cohort of patients with Laron syndrome, and (iii) reduced in mice and humans treated with GH or IGF-1 (insulin-like growth factor 1) [11]. Age-dependent declines in the circulating HN levels may be due to higher levels of reactive oxygen species (ROS) that contribute to atherosclerosis development. Using mouse models of atherosclerosis, it was found that HN-treated mice had a reduced disease burden and significant health improvements [12,13]. In addition, HN improved insulin sensitivity, suggesting clinical potential for mitochondrial peptides in diseases of aging [10]. The discovery of HN represents a unique addition to the spectrum of roles that mitochondria play in the cell [14,15]. A second mitochondrial-derived peptide (MDP), MOTS-c (mitochondrial open reading frame of the 12S rRNA-c), has also been shown to have metabolic effects on muscle and may also play a role in aging [16].

We further investigated mtDNA for the presence of other MDPs. Recent technological advances have led to the identification of small open reading frames (sORFs) in the nuclear genomes ofDrosophila[17,18] and mammals [19,20]. Therefore, we attempted to identify novel sORFs using the following approaches: 1) in silico identification of potential sORFs; 2) determination of mRNA expression levels; 3) development of specific antibodies against these novel peptides to allow for peptide detection in cells, organs, and plasma; 4) elucidating the actions of these peptides by performing cell-based assays for mitochondrial function, signaling, viability, and differentiation; and 5) delivering these peptides in vivo to determine their systemic metabolic effects. Focusing on the 16S rRNA region of the mtDNA where the humanin gene is located, we identified six sORFs and named them small humanin-like peptides (SHLPs) 1-6. While surveying the biological effects of SHLPs, we found that SHLP2 and SHLP3 were cytoprotective; therefore, we investigated their effects on apoptosis and metabolism in greater detail. Further, we showed that circulating SHLP2 levels declined with age, similar to HN, suggesting that SHLP2 is involved in aging and age-related disease progression.

SHLP2 and SHLP3 regulate the expression of metabolic and inflammatory markers

Epidemiological studies have demonstrated that increased levels of mediators of inflammation and acute-phase reactants, such as fibrinogen, C-reactive protein (CRP), and IL-6, correlate with the incidence of type 2 diabetes mellitus (T2DM) [3436]. In humans, anti-inflammatory drugs, such as aspirin and sodium salicylate, reduce fasting plasma glucose levels and ameliorate the symptoms of T2DM. In addition, anti-diabetic drugs, such as fibrates [37] and thiazolidinediones [38], have been found to lower some markers of inflammation. SHLP2 increased the levels of leptin, which is known to improve insulin sensitivity, but had no effect on the levels of the pro-inflammatory cytokines IL-6 and MCP-1. SHLP3 significantly increased the leptin levels, but also elevated IL-6 and MCP-1 levels, which could explain the lack of an in vivo insulin-sensitizing effect of SHLP3. The mechanism by which SHLPs regulate the expression of metabolic and inflammatory markers remains unclear and needs to be further investigated. Furthermore, SHLPs have different effects on inflammatory marker expression, suggesting differential regulation and function of individual SHLPs.

SHLP2 in aging

Mitochondria have been implicated in increased lifespan in several life-extending treatments [39,40]; however, it is not known whether the relationship is correlative or causative [40]. Additionally, it is well known that hormone levels change with aging. For example, levels of aldosterone, calcitonin, growth hormone, and IGF-I decrease with age. Circulating HN levels decline with age in humans and rodents, specifically in the hypothalamus and skeletal muscle of older rats. These changes parallel increases in the incidence of age-associated diseases such as AD and T2DM. The decline in circulating SHLP2 levels with age (Fig. 6), the anti-oxidative stress function of SHLP2 (Fig. 3C), and its neuroprotective effect (Fig. 6B) indicate that SHLP2 has a role in the regulation of aging and age-related diseases.

Conclusion

By analyzing the mitochondrial transcriptome, we found that sORFs from mitochondrial DNA encode functional peptides. We identified many mRNA transcripts within 13 protein-coding mitochondrial genes [1]. Such previously underappreciated sORFs have also been described in the nuclear genome [41]. The MDPs we describe here may represent retrograde communication signals from the mitochondria to the nucleus and may explain important aspects of mitochondrial biology that are implicated in health and longevity.

Larry, John Walker is working on mt proteins dynamics. His rotor – stator mechanism in ATPase synthase, a ‘complex’ that biologist accepted as energy generator is likely wrong. I was suppose to have met him in Germany few years ago. Energy in biological systems has nothing to do with heat. Heat is an outcome of a reaction, meaning that IR spectra accordingly to wave theory is a source of information memorized in water interference with carbon open systems within protein and glyo-proteins complexes as well as genome space-time outcomes. Physically speaking from a pure perspective of science ATP is highly unstable form of phosphate ‘chains’. It cannot hold energy, it is actually in contrary, it is like a resonator, trapping negativity, thus functioning as space propeller by expanding carbon skeleton of protein ‘machines’ Now, we don’t know what is ‘aging’ in a pure physical sense, except that we observe structural changes in what we call complexes. We we know is that proteins are not stationary structures, but highly dynamic forms of matter, seemingly occupying discrete and relative spaces. A piece of mt ATP ase could be discovered in the nucleus as transcription factor. Our notion of operational space in terms of electro dynamics from a motor – stator perspective is now translated toward defining semi conducting and supracoductive strings. The reality of which is so much more fascinating and beautiful as time progresses overally. There are spaces where time does not change, and there are spaces where time walks, and there are spaces, where time flies, and there are spaces where time runs. Amazing, indeed! The story of aging gets a lot deeper that science could even imagine, probably to roots of immortal energy- spaces. We know that matter is transient, that is nearly all living matter, replenishes of about 3 to 7 weeks.

Take a glass full of some kind of liquid, you know the mass of the glass and the mass of the liquid (say wine, beer, water, or milk) You also know to an approximate reality the composition of both. Now lift the glass full of liquid and let it break on a surface of your choice. Depending on the surface pieces of the glass would travel differential from a center projected by the vertical axis of your hand. What technology does today is recollecting those pieces and modelling them to fit in a form again that would resemble a holding device, a glass. The liquid we don’t know exactly how it spilled due the nature of its absorbancy of both surface physics and physical ‘state’ properties. Thus we can say how much approximate energy we have held thinking of m/z as time flight objectives. Each technology can read 1D and approximate the 2D, absolutely lacking computational methodology for 3D dynamic reality. Many scientists confuse space and volume. Volume is a one dimensional characteristic! So is crystalography! BY taking quantum chemical method computing principles following imaginative rules we could approach 2D, however , that is not enough to define 3D. Time we use as a reference frame of clocks we have invented in order to keep track of a sense to observable ‘change’ . But remember, time is absolute and parallel in continuity while energy is discrete , coming in quantum packages, realization of accumulated information. Information is highly redundant we see, so annotating information is an objective to modern days simulations that could predict outcomes of possible parallel realities we call worlds. One could ‘jump’ from one reality to another through guidance of light and water, but what remains unsolved is why people make mistakes, constantly by accusing in name of greed and power , or disobedience of commandments of the Lord!

On Thu, Apr 21, 2016 at 3:41 AM, Leaders in Pharmaceutical Business Intelligence (LPBI) Group wrote:

> larryhbern posted: “New Insights into mtDNA, mitochondrial proteins, > aging, and metabolic control Larry H. Bernstein, MD, FCAP, Curator LPBI > Newly discovered proteins may protect against age-related illnesses The > proteins could play a key role in the ” >

 

Metabolic features of the cell danger response
– Mitochondria in Health and Disease

Mitochondrion  Volume 16, May 2014, Pages 7–17     doi:10.1016/j.mito.2013.08.006

 

Highlights

  •  The Cell Danger Response (CDR) is defined in terms of an ancient metabolic response to threat.
  •  The CDR encompasses inflammation, innate immunity, oxidative stress, and the ER stress response.
  •  The CDR is maintained by extracellular nucleotide (purinergic) signaling.
  •  Abnormal persistence of the CDR lies at the heart of many chronic diseases.
  •  Antipurinergic therapy (APT) has proven effective in many chronic disorders in animal models

The cell danger response (CDR) is the evolutionarily conserved metabolic response that protects cells and hosts from harm. It is triggered by encounters with chemical, physical, or biological threats that exceed the cellular capacity for homeostasis. The resulting metabolic mismatch between available resources and functional capacity produces a cascade of changes in cellular electron flow, oxygen consumption, redox, membrane fluidity, lipid dynamics, bioenergetics, carbon and sulfur resource allocation, protein folding and aggregation, vitamin availability, metal homeostasis, indole, pterin, 1-carbon and polyamine metabolism, and polymer formation. The first wave of danger signals consists of the release of metabolic intermediates like ATP and ADP, Krebs cycle intermediates, oxygen, and reactive oxygen species (ROS), and is sustained by purinergic signaling. After the danger has been eliminated or neutralized, a choreographed sequence of anti-inflammatory and regenerative pathways is activated to reverse the CDR and to heal. When the CDR persists abnormally, whole body metabolism and the gut microbiome are disturbed, the collective performance of multiple organ systems is impaired, behavior is changed, and chronic disease results. Metabolic memory of past stress encounters is stored in the form of altered mitochondrial and cellular macromolecule content, resulting in an increase in functional reserve capacity through a process known as mitocellular hormesis. The systemic form of the CDR, and its magnified form, the purinergic life-threat response (PLTR), are under direct control by ancient pathways in the brain that are ultimately coordinated by centers in the brainstem. Chemosensory integration of whole body metabolism occurs in the brainstem and is a prerequisite for normal brain, motor, vestibular, sensory, social, and speech development. An understanding of the CDR permits us to reframe old concepts of pathogenesis for a broad array of chronic, developmental, autoimmune, and degenerative disorders. These disorders include autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), asthma, atopy, gluten and many other food and chemical sensitivity syndromes, emphysema, Tourette’s syndrome, bipolar disorder, schizophrenia, post-traumatic stress disorder (PTSD), chronic traumatic encephalopathy (CTE), traumatic brain injury (TBI), epilepsy, suicidal ideation, organ transplant biology, diabetes, kidney, liver, and heart disease, cancer, Alzheimer and Parkinson disease, and autoimmune disorders like lupus, rheumatoid arthritis, multiple sclerosis, and primary sclerosing cholangitis.

The double face of mitochondrial dysfunction

Dmitry Knorre, Anna Zyrina, and Fedor Severin

pp 420-420

Full text | PDF

 

 

Flawed Mitochondrial DNA Could Undermine Stem Cell Therapies

http://www.genengnews.com/gen-news-highlights/flawed-mitochondrial-dna-could-undermine-stem-cell-therapies/81252622/

http://www.genengnews.com/Media/images/GENHighlight/thumb_Apr18_2016_OHSU_ConfocalMicroscopyImage7543773219.jpg

This is a confocal microscopy image of human fibroblasts derived from embryonic stem cells. The nuclei appear in blue, while smaller and more numerous mitochondria appear in red. [Shoukhrat Mitalipov]

Mutations in our mitochondrial DNA tend to be inconspicuous, but they can become more prevalent as we age. They can even vary in frequency from cell to cell. Naturally, some cells will be relatively compromised because they happen to have a higher percentage of mutated mitochondrial DNA. Such cells make a poor basis for stem cell lines. They should be excluded. But how?

To answer this question, a team of scientists scrutinized skin fibroblasts, blood cells, and induced pluripotent stem cells (iPSCs) for mitochondrial genome integrity. When the scientists tested the samples for mitochondrial DNA mutations, the levels of mutations appeared low. But when the scientists sequenced the iPS cell lines, they found higher numbers of mitochondrial DNA mutations, particularly in cells from patients over 60.

The scientists were led by Shoukhrat Mitalipov, Ph.D., director of the Center for Embryonic Cell and Gene Therapy at Oregon Health & Science University, and Taosheng Huang, M.D., a medical geneticist and director of the Mitochondrial Medicine Program at Cincinnati Children’s Hospital. The Mitalipov/Huang-led team also found higher percentages of mitochondria containing mutations within a cell. The higher the load of mutated mitochondrial DNA in a cell, the more compromised the cell’s function.

Since each iPSC line is created from a different cell, each line may contain different types of mitochondrial DNA mutations and mutation loads. To choose the least damaged line, the authors recommend screening multiple lines per patient. “It’s a good idea to check the iPS clones for mitochondrial DNA mutations and make sure you pick a good cell line,” said Dr. Huang.

This recommendation appeared April 14 in the journal Cell Stem Cell, in an article entitled, “Age-Related Accumulation of Somatic Mitochondrial DNA Mutations in Adult-Derived Human iPSCs.” This article holds that mitochondrial genome integrity is a vital readout in assessing the proficiency of patient-derived regenerative products destined for clinical applications.

“We found that pooled skin and blood mtDNA contained low heteroplasmic point mutations, but a panel of ten individual iPSC lines from each tissue or clonally expanded fibroblasts carried an elevated load of heteroplasmic or homoplasmic mutations, suggesting that somatic mutations randomly arise within individual cells but are not detectable in whole tissues,” wrote the article’s authors. “The frequency of mtDNA defects in iPSCs increased with age, and many mutations were nonsynonymous or resided in RNA coding genes and thus can lead to respiratory defects.”

Potential therapies using stem cells hold tremendous promise for treating human disease. However, defects in the mitochondria could undermine the iPS cells’ ability to repair damaged tissue or organs.

“If you want to use iPS cells in a human, you must check for mutations in the mitochondrial genome,” declared Dr. Huang. “Every single cell can be different. Two cells next to each other could have different mutations or different percentages of mutations.”

Prior to the creation of a therapeutic iPS cell line, a collection of cells is taken from the patient. These cells will be tested for mutations. If the tester uses Sanger sequencing, older technology that is not as sensitive as newer next-generation sequencing, any mutation that occurs in less than 20% of the sample will go undetected. But mitochondrial DNA mutations might occur in less than 20% of mitochondria in the pooled cells. As a result, mutation rates have not been well understood. “These mitochondrial mutations are actually hidden,” explained Dr. Mitalipov.

The mitochondrial genome is relatively small, containing just 37 genes, so screening should be feasible using next generation sequencing, Dr. Mitalipov added. “It should be relatively cheap and do-able.”

Dr. Mitalipov also commented on a more general point, the implications of the current study on illuminating the mechanisms of age-related disease: “Pathogenic mutations in our mitochondrial DNA have long been thought to be a driving force in aging and age-onset diseases, though clear evidence was missing. This foundational knowledge of how cells are damaged in the natural process of aging may help to illuminate the role of mutated mitochondria in degenerative disease.”

New Mitalipov paper on stem cell mitochondria: challenge for IPS cell field?

http://www.ipscell.com/tag/age-related-accumulation-of-somatic-mitochondrial-dna-mutations-in-adult-derived-human-ipscs/

A new paper from Shoukhrat Mitalipov’s lab on stem cell mitochondria points to a pattern whereby induced pluripotent stem (IPS) cells tend to have more problems if they are from older patients.

What does this paper mean for the stem cell field and could it impact more specifically the clinical applications of IPS cells?

http://i0.wp.com/www.ipscell.com/wp-content/uploads/2016/04/Mitalipov-mitochondrial-mutations.jpg?resize=300%2C295

Graphical Abstract, Kang, et al. 2016

The new paper Kang, et al is entitled “Age-Related Accumulation of Somatic Mitochondrial DNA Mutations in Adult-Derived Human iPSCs”.

This paper reminds us of the very important realities that mitochondria are key players in stem cell function and that mitochondria have their own genomes that impact that function. A lot of us don’t think about mitochondria and their genome as often as we should.

The paper came to three major scientific conclusions (this from the Highlights section of the paper and also see the graphical abstract for a visual sense of the results overall):

  • Human iPSC clones derived from elderly adults show accumulation of mtDNA mutations
  • Fewer mtDNA mutations are present in ESCs and iPSCs derived from younger adults
  • Accumulated mtDNA mutations can impact metabolic function in iPSCs

Importantly the team looked at IPS cells derived from both blood and skin cells and found that the former were less likely to have mitochondrial mutations.

This study suggests that those teams producing or working with human IPS cells (hIPSCs) should be screening the different lines for mitochondrial mutations. This excellent piece from Sara Reardon on the Mitalipov paper quotes IPS cell expert Jeanne Loring on this very point:

“It’s one of those things most of us don’t think about,” says Jeanne Loring, a stem-cell biologist at the Scripps Research Institute in La Jolla, California. Her lab is working towards using iPS cells to treat Parkinson’s disease, and Loring now plans to go back and examine the mitochondria in her cell lines. She suspects that it will be fairly easy for researchers to screen cells for use in therapies.”

Mitalipov goes further and suggests that his team’s new findings could support the use of human embryonic stem cells (hESC) derived by somatic cell nuclear transfer (SCNT) which would be expected to have mitochondria with fewer mutations. However, as Loring points out in the Reardon article, SCNT is really difficult to successfully perform and only a few labs in the world can do it at present. In that context, working with hIPSC and adding on the additional layer of mitochondrial DNA mutation screening could be more practical.

New York stem cell researcher Dieter Egli, however, is quoted that hIPSC have other differences with hESC as well such as epigenetic differences and he’s quoted in the Reardon piece, “It’s going to be very hard to find a cell line that’s perfect.”

One might reasonably ask both Egli and oneself, “What is a perfect cell line”?

In the end the best approach for use of human pluripotent stem cells of any kind is going to involve a balance between practicality of production and the potentially positive or negative traits of those cells as determined by rigorous validation screening.

With this new paper we’ve just learned more about another layer of screening that is needed. An interesting question is whether adult stem cells such as mesenchymal stromal/stem cells (MSC) also should be screened for mitochondrial mutations. They are often produced from patients who are getting up there in years. I hope that someone will publish on that too.

As to pluripotent cells, I expect that sometimes the best lines, meaning those most perfect for a given clinical application, will be hIPSC (autologous or allogeneic in some instances) and in other cases they may be hESC made from leftover IVF embryos. If SCNT-derived hESC can be more widely produced in an affordable manner and they pass validation as well then those (sometimes called NT-hESC) may also come into play clinically. So far that hasn’t happened for the SCNT cells, but it may over time.   …..

 Age-Related Accumulation of Somatic Mitochondrial DNA Mutations in Adult-Derived Human iPSCs

Eunju Kang, Xinjian Wang, Rebecca Tippner-Hedges, …, Don P. Wolf, Taosheng Huang, Shoukhrat Mitalipov
http://www.cell.com/cell-stem-cell/pdfExtended/S1934-5909(16)00067-9

In Brief Mitalipov, Huang, and colleagues show that human iPSCs derived from older adults carry more mitochondrial DNA mutations than those derived from younger individuals. Defects in metabolic function caused by mtDNA mutations suggest careful screening of hiPSC clones for mutational load before clinical application.

Highlights

  1. Human iPSC clones derived from elderly adults show accumulation of mtDNA mutations
  2. Fewer mtDNA mutations are present in ESCs and iPSCs derived from younger adults
  3. Accumulated mtDNA mutations can impact metabolic function in iPSCs

Kang et al., 2016, Cell Stem Cell 18, 1–12 May 5, 2016 ª2016 Elsevier Inc. http://dx.doi.org/10.1016/j.stem.2016.02.005

The genetic integrity of iPSCs is an important consideration for therapeutic application. In this study, we examine the accumulation of somatic mitochondrial genome (mtDNA) mutations in skin fibroblasts, blood, and iPSCs derived from young and elderly subjects (24–72 years). We found that pooled skin and blood mtDNA contained low heteroplasmic point mutations, but a panel of ten individual iPSC lines from each tissue or clonally expanded fibroblasts carried an elevated load of heteroplasmic or homoplasmic mutations, suggesting that somatic mutations randomly arise within individual cells but are not detectable in whole tissues. The frequency of mtDNA defects in iPSCs increased with age, and many mutations were non-synonymous or resided in RNA coding genes and thus can lead to respiratory defects. Our results highlight a need to monitor mtDNA mutations in iPSCs, especially those generated from older patients, and to examine the metabolic status of iPSCs destined for clinical applications.

Induced pluripotent stem cells (iPSCs) offer an unlimited source for autologous cell replacement therapies to treat age-associated degenerative diseases. Aging is generally characterized by increased DNA damage and genomic instability (Garinis et al., 2008; Lombard et al., 2005); thus, iPSCs derived from elderly subjects may harbor point mutations and larger genomic rearrangements. Indeed, iPSCs display increased chromosome aberrations (Mayshar et al., 2010), subchromosomal copy number variations (CNVs) (Abyzov et al., 2012; Laurent et al., 2011), and exome mutations (Johannesson et al., 2014), compared to natural embryonic stem cell (ESC) counterparts (Ma et al., 2014). The rate of mtDNA mutations is believed to be at least 10- to 20-fold higher than that observed in the nuclear genome (Wallace, 1994), and often both mutated and wild-type mtDNA (heteroplasmy) can coexist in the same cell (Rossignol et al., 2003). Large deletions are most frequently observed mtDNA abnormalities in aged post-mitotic tissues such as brain, heart, and muscle (Bender et al., 2006; Bua et al., 2006; Corral-Debrinski et al., 1992; Cortopassi et al., 1992; Mohamed et al., 2006) and have been implicated in aging and diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and diabetes (Larsson, 2010; Lin and Beal, 2006; Petersen et al., 2003; Wallace, 2005). In addition, mtDNA point mutations were reported in some tumors and replicating tissues (Chatterjee et al., 2006; Ju et al., 2014; Michikawa et al., 1999; Taylor et al., 2003). However, the extent of mtDNA defects in proliferating peripheral tissues commonly used for iPSC induction, such as skin and blood, is thought to be low and limited to common non-coding variants (Schon et al., 2012; Yao et al., 2015). Accumulation of mtDNA variants in these tissues with age was insignificant (Greaves et al., 2010; Hashizume et al., 2015). Several point mutations were identified in iPSCs generated from the newborn foreskin fibroblasts, although most of these variants were non-coding, common for the general population, and did not affect their metabolic activity (Prigione et al., 2011). Somatic mtDNA mutations may be under-reported secondary to the level of sample interrogation. …..

Figure 2. mtDNA Mutations in Skin Fibroblasts, Blood, and the iPSCs of a 72-YearOld B Subject (A) Sixteen mutations at low heteroplasmy levels were detected in the DNA of PF, while a panel of ten FiPSC lines carried nine mutations, including four that were homoplasmic. Gray rectangles define the mutations shared between PF and FiPSCs. (B) Venn diagram showing only one mutation in FiPSCs shared with PF. (C) All ten FiPSC lines carried between one and five high-heteroplasmy (>15%) mutations. (D) Mutation distribution in whole blood and BiPSCs was similar to that in PF and FiPSCs. Six mutations at low-heteroplasmy levels were observed in blood, while BiPSC lines displayed 21 mutations, including four over the 80% heteroplasmy level. (E) Venn diagram showing four mutations in BiPSCs shared with whole blood and the 17 novel variants. (F) Distribution of mutations in individual BiPSC lines. See also Figures S2 and S3; Table S1; Table S3, sheet 2; and Table S4, sheet 1   ….

Figure 4. Transmission and Distribution of Somatic mtDNA Mutations to iPSCs (A) A total of 112 mtDNA mutations were discovered in parental cells (PF, CF, and blood) from 11 subjects. Of these, 39 variants (35%) were found in corresponding 130 iPSC lines. Among non-transmitted, transmitted, and novel mutations in iPSCs, comparable percentages of variants (68%, 69%, and 79%, respectively) were coding mutations in protein, rRNA, or tRNA genes. This suggests that most pathogenic mutations do not affect iPSC induction. However, certain coding mutations including in ND3, ND4L, and 14 tRNA genes were not detected in iPSCs, suggesting possible pathogenicity. n, the number of mtDNA mutations. Blue font genes were detected in parental cells. (B–D) A total of 80 high heteroplasmic (>15%) variants were detected in the present study in 130 FiPSC or BiPSC lines from 11 subjects. (B) The majority of these variants (76%) were non-synonymous or frame-shift mutations in protein-coding genes or affected rRNA and tRNA genes. (C) More than half of the mutations (56%) were never reported in a database containing whole mtDNA sequences from 26,850 healthy subjects representing the general human population (http://www.mitomap.org/MITOMAP). (D) Most mutations (90%) were never reported in a database containing sequences from healthy subjects with corresponding mtDNA haplotypes. freq., frequent. See also Figure S5 and Tables S3 and S4. ….

sjwilliamspa

Mutations will accumulate over age in mitochondrial DNA, however the current study has the difficulty that the authors could not use patient-age-matched controls, in essence they could only compare induced pluripotent stem cells derived from different patients. This could confound the results but the result with higher frequency of mutation in mtDNA in cells reprogrammed from younger patients is interesting but might limit the ability of autologous regenerative therapy in older patients. However reprogramming, although the method not mentioned here although I am assuming by transfection with lentivirus is a rough procedure, involving multiple dedifferentiation steps. Therefore it is very understandable that cells obtained from elderly patients would respond less favorably to such a rough reprogramming regimen, especially if it produced a higher degree of ROS, which has been shown to alter mtDNA. This is why I feel it is more advantageous to obtain a stem cell population from fat cells and forgo the Oct4, htert, reprogramming with lentiviral vectors.

 

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