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| Prediction of local convergent shifts in evolutionary rates with phyloConverge characterizes the phenotypic associations and modularity of regulatory elements |
Saputra E Mao W, Clark N, Chikina M |
bioRxiv |
Physiological and morphological adaptations to extreme environments arise from the molecular evolution of protein-coding regions and regulatory elements (REs) that regulate gene expression. Comparative genomics methods can characterize genetic elements that underlie the organism-level adaptations but convergence analyses of REs are often limited by their evolutionary properties. A RE can be modularly composed of multiple transcription factor binding sites (TFBS) that may each experience different evolutionary pressures. The modular composition and rapid turnover of TFBS also enables a compensatory mechanism among nearby TFBS that allows for weaker sequence conservation/divergence than intuitively expected. Here, we introduce phyloConverge, a comparative genomics method that can perform fast, fine-grained local convergence analysis of genetic elements. phyloConverge calibrates for local shifts in evolutionary rates using a combination of maximum likelihood-based estimation of nucleotide substitution rates and phylogenetic permutation tests. Using the classical convergence case of mammalian adaptation to subterranean environments, we validate that phyloConverge identifies rate-accelerated conserved non-coding elements (CNEs) that are strongly correlated with ocular tissues, with improved specificity compared to competing methods. We use phyloConverge to perform TFBS-scale and nucleotide-scale scoring to dissect each CNE into subregions with uneven convergence signals and demonstrate its utility for understanding the modularity and pleiotropy of REs. Subterranean-accelerated regions are also enriched for molecular pathways and TFBS motifs associated with neuronal phenotypes, suggesting that subterranean eye degeneration may coincide with a remodeling of the nervous system. phyloConverge offers a rapid and accurate approach for understanding the evolution and modularity of regulatory elements underlying phenotypic adaptation.
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| Gene expression and DNA methylation consistently predict cancer mutation states. |
Crawford J Christensen BC, Chikina M, Greene CS |
bioRxiv |
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| Complementary evolution of coding and noncoding sequence underlies mammalian hairlessness. |
Kowalczyk A Chikina M, Clark N |
bioRxiv |
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| A cautionary tale on proper use of branch-site models to detect convergent positive selection. |
Kowalczyk A Chikina M, Clark N |
bioRxiv |
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| Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
Gomes MGM Ferreira MU, Corder RM, King JG, Souto-Maior C, Penha-Gonçalves C, Gonçalves G, Chikina M, Pegden W, Aguas R. |
Journal of Theoretical Biology |
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| Evolutionary rate covariation identifies SLC30A9 (ZnT9) as a mitochondrial zinc transporter. |
Kowalczyk A, Gbadamosi O, Kolor K, Sosa J, Andrzejczuk L, Gibson G, St Croix C, Chikina M, Aizenman E, Clark N, Kiselyov K |
The Biochemical journal |
Recent advances in genome sequencing have led to the identification of new ion and metabolite transporters many of which have not been characterized. Due to the variety of subcellular localizations, cargo and transport mechanisms, such characterization is a daunting task, and predictive approaches focused on the functional context of transporters are very much needed. Here we present a case for identifying a transporter localization using evolutionary rate covariation (ERC), a computational approach based on pairwise correlations of amino acid sequence evolutionary rates across the mammalian phylogeny. As a case study, we find that poorly characterized transporter SLC30A9 (ZnT9) coevolves with several components of the mitochondrial oxidative phosphorylation chain, suggesting mitochondrial localization. We confirmed this computational finding experimentally using recombinant human SLC30A9. SLC30A9 loss caused zinc mishandling in the mitochondria, suggesting that under normal conditions it acts as a zinc exporter. We therefore propose that ERC can be used to predict the functional context of novel transporters and other poorly characterized proteins.
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| Phylogenetic Permulations: A Statistically Rigorous Approach to Measure Confidence in Associations in a Phylogenetic Context. |
Saputra E, Kowalczyk A, Cusick L, Clark N, Chikina M |
Molecular biology and evolution |
Many evolutionary comparative methods seek to identify associations between phenotypic traits or between traits and genotypes often with the goal of inferring potential functional relationships between them. Comparative genomics methods aimed at this goal measure the association between evolutionary changes at the genetic level with traits evolving convergently across phylogenetic lineages. However, these methods have complex statistical behaviors that are influenced by nontrivial and oftentimes unknown confounding factors. Consequently, using standard statistical analyses in interpreting the outputs of these methods leads to potentially inaccurate conclusions. Here, we introduce phylogenetic permulations, a novel statistical strategy that combines phylogenetic simulations and permutations to calculate accurate, unbiased P values from phylogenetic methods. Permulations construct the null expectation for P values from a given phylogenetic method by empirically generating null phenotypes. Subsequently, empirical P values that capture the true statistical confidence given the correlation structure in the data are directly calculated based on the empirical null expectation. We examine the performance of permulation methods by analyzing both binary and continuous phenotypes, including marine, subterranean, and long-lived large-bodied mammal phenotypes. Our results reveal that permulations improve the statistical power of phylogenetic analyses and correctly calibrate statements of confidence in rejecting complex null distributions while maintaining or improving the enrichment of known functions related to the phenotype. We also find that permulations refine pathway enrichment analyses by correcting for nonindependence in gene ranks. Our results demonstrate that permulations are a powerful tool for improving statistical confidence in the conclusions of phylogenetic analysis when the parametric null is unknown.
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| Antibody Responses to SARS-CoV-2 Following an Outbreak Among Marine Recruits With Asymptomatic or Mild Infection. |
Ramos I, Goforth C, Soares-Schanoski A, Weir DL, Samuels EC, Phogat S, Meyer M, Huang K, Pietzsch CA, Ge Y, Pike BL, Regeimbal J, Simons MP, Termini MS, Vangeti S, Marjanovic N, Lizewski S, Lizewski R, George MC, Nair VD, Smith GR, Mao W, Chikina M, Broder CC, Laing ED, Bukreyev A, Sealfon SC, Letizia AG |
Frontiers in immunology |
We investigated serological responses following a SARS-CoV-2 outbreak in spring 2020 on a US Marine recruit training base. 147 participants that were isolated during an outbreak of respiratory illness were enrolled in this study with visits approximately 6 and 10 weeks post-outbreak (PO). This cohort is comprised of young healthy adults, ages 18-26, with a high rate of asymptomatic infection or mild symptoms, and therefore differs from previously reported longitudinal studies on humoral responses to SARS-CoV-2, which often focus on more diverse age populations and worse clinical presentation. 80.9% (119/147) of the participants presented with circulating IgG antibodies against SARS-CoV-2 spike (S) receptor-binding domain (RBD) at 6 weeks PO, of whom 97.3% (111/114) remained positive, with significantly decreased levels, at 10 weeks PO. Neutralizing activity was detected in all sera from SARS-CoV-2 IgG positive participants tested (n=38) at 6 and 10 weeks PO, without significant loss between time points. IgG and IgA antibodies against SARS-CoV-2 RBD, S1, S2, and the nucleocapsid (N) protein, as well neutralization activity, were generally comparable between those participants that had asymptomatic infection or mild disease. A multiplex assay including S proteins from SARS-CoV-2 and related zoonotic and human endemic betacoronaviruses revealed a positive correlation for polyclonal cross- reactivity to S after SARS-CoV-2 infection. Overall, young adults that experienced asymptomatic or mild SARS-CoV-2 infection developed comparable humoral responses, with no decrease in neutralizing activity at least up to 10 weeks after infection.
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| DataRemix: a universal data transformation for optimal inference from gene expression datasets. |
Mao W, Rahimikollu J, Hausler R, Chikina M |
Bioinformatics |
MOTIVATION: RNA-seq technology provides unprecedented power in the assessment of the transcription abundance and can be used to perform a variety of downstream tasks such as inference of gene-correlation network and eQTL discovery. However raw gene expression values have to be normalized for nuisance biological variation and technical covariates, and different normalization strategies can lead to dramatically different results in the downstream study. RESULTS: We describe a generalization of singular value decomposition-based reconstruction for which the common techniques of whitening, rank-k approximation and removing the top k principal components are special cases. Our simple three-parameter transformation, DataRemix, can be tuned to reweigh the contribution of hidden factors and reveal otherwise hidden biological signals. In particular, we demonstrate that the method can effectively prioritize biological signals over noise without leveraging external dataset- specific knowledge, and can outperform normalization methods that make explicit use of known technical factors. We also show that DataRemix can be efficiently optimized via Thompson sampling approach, which makes it feasible for computationally expensive objectives such as eQTL analysis. Finally, we apply our method to the Religious Orders Study and Memory and Aging Project dataset, and we report what to our knowledge is the first replicable trans-eQTL effect in human brain. AVAILABILITYAND IMPLEMENTATION: DataRemix is an R package which is freely available at GitHub (https://github.com/wgmao/DataRemix). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| Modeling strict age-targeted mitigation strategies for COVID-19. |
Chikina M, Pegden W |
PloS one |
We use a simple SIR-like epidemic model integrating known age-contact patterns for the United States to model the effect of age-targeted mitigation strategies for a COVID-19-like epidemic. We find that among strategies which end with population immunity, strict age-targeted mitigation strategies have the potential to greatly reduce mortalities and ICU utilization for natural parameter choices.
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| Causal network perturbations for instance-specific analysis of single cell and disease samples. |
Buschur KL, Chikina M, Benos PV |
Bioinformatics |
MOTIVATION: Complex diseases involve perturbation in multiple pathways and a major challenge in clinical genomics is characterizing pathway perturbations in individual samples. This can lead to patient-specific identification of the underlying mechanism of disease thereby improving diagnosis and personalizing treatment. Existing methods rely on external databases to quantify pathway activity scores. This ignores the data dependencies and that pathways are incomplete or condition-specific. RESULTS: ssNPA is a new approach for subtyping samples based on deregulation of their gene networks. ssNPA learns a causal graph directly from control data. Sample-specific network neighborhood deregulation is quantified via the error incurred in predicting the expression of each gene from its Markov blanket. We evaluate the performance of ssNPA on liver development single-cell RNA-seq data where the correct cell timing is recovered; and two TCGA datasets, where ssNPA patient clusters have significant survival differences. In all analyses ssNPA consistently outperforms alternative methods, highlighting the advantage of network- based approaches. AVAILABILITY AND IMPLEMENTATION: http://www.benoslab.pitt.edu/Software/ssnpa/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| Germinal center B cells selectively oxidize fatty acids for energy while conducting minimal glycolysis. |
Weisel FJ, Mullett SJ, Elsner RA, Menk AV, Trivedi N, Luo W, Wikenheiser D, Hawse WF, Chikina M, Smita S, Conter LJ, Joachim SM, Wendell SG, Jurczak MJ, Winkler TH, Delgoffe GM, Shlomchik MJ |
Nature immunology |
Germinal center B cells (GCBCs) are critical for generating long-lived humoral immunity. How GCBCs meet the energetic challenge of rapid proliferation is poorly understood. Dividing lymphocytes typically rely on aerobic glycolysis over oxidative phosphorylation for energy. Here we report that GCBCs are exceptional among proliferating B and T cells as they actively oxidize fatty acids (FAs) and conduct minimal glycolysis. In vitro, GCBCs had a very low glycolytic extracellular acidification rate but consumed oxygen in response to FAs. [(13)C6]-glucose feeding revealed that GCBCs generate significantly less phosphorylated glucose and little lactate. Further, GCBCs did not metabolize glucose into tricarboxylic acid (TCA) cycle intermediates. Conversely, [(13)C16]-palmitic acid labeling demonstrated that GCBCs generate most of their acetyl-CoA and acetylcarnitine from FAs. FA oxidation was functionally important, as drug-mediated and genetic dampening of FA oxidation resulted in a selective reduction of GCBCs. Hence, GCBCs appear to uncouple rapid proliferation from aerobic glycolysis.
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| Pan-mammalian analysis of molecular constraints underlying extended lifespan. |
Kowalczyk A, Partha R, Clark NL, Chikina M |
eLife |
Although lifespan in mammals varies over 100-fold the precise evolutionary mechanisms underlying variation in longevity remain unknown. Species-specific genetic changes have been observed in long-lived species including the naked mole-rat, bats, and the bowhead whale, but these adaptations do not generalize to other mammals. We present a novel method to identify associations between rates of protein evolution and continuous phenotypes across the entire mammalian phylogeny. Unlike previous analyses that focused on individual species, we treat absolute and relative longevity as quantitative traits and demonstrate that these lifespan traits affect the evolutionary constraint on hundreds of genes. Specifically, we find that genes related to cell cycle, DNA repair, cell death, the IGF1 pathway, and immunity are under increased evolutionary constraint in large and long-lived mammals. For mammals exceptionally long-lived for their body size, we find increased constraint in inflammation, DNA repair, and NFKB-related pathways. Strikingly, these pathways have considerable overlap with those that have been previously reported to have potentially adaptive changes in single-species studies, and thus would be expected to show decreased constraint in our analysis. This unexpected finding of increased constraint in many longevity- associated pathways underscores the power of our quantitative approach to detect patterns that generalize across the mammalian phylogeny.
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| Liver Is a Generative Site for the B Cell Response to Ehrlichia muris. |
Trivedi N, Weisel F, Smita S, Joachim S, Kader M, Radhakrishnan A, Clouser C, Rosenfeld AM, Chikina M, Vigneault F, Hershberg U, Ismail N, Shlomchik MJ |
Immunity |
The B cell response to Ehrlichia muris is dominated by plasmablasts (PBs) with few-if any-germinal centers (GCs), yet it generates protective immunoglobulin M (IgM) memory B cells (MBCs) that express the transcription factor T-bet and harbor V-region mutations. Because Ehrlichia prominently infects the liver, we investigated the nature of liver B cell response and that of the spleen. B cells within infected livers proliferated and underwent somatic hypermutation (SHM). Vh-region sequencing revealed trafficking of clones between the spleen and liver and often subsequent local clonal expansion and intraparenchymal localization of T-bet(+) MBCs. T-bet(+) MBCs expressed MBC subset markers CD80 and PD-L2. Many T-bet(+) MBCs lacked CD11b or CD11c expression but had marginal zone (MZ) B cell phenotypes and colonized the splenic MZ, revealing T-bet(+) MBC plasticity. Hence, liver and spleen are generative sites of B cell responses, and they include V-region mutation and result in liver MBC localization.
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| RERconverge: an R package for associating evolutionary rates with convergent traits. |
Kowalczyk A, Meyer WK, Partha R, Mao W, Clark NL, Chikina M |
Bioinformatics |
MOTIVATION: When different lineages of organisms independently adapt to similar environments selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits. RESULTS: Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results. AVAILABILITY AND IMPLEMENTATION: RERconverge source code, documentation and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila and yeast are available at https://bit.ly/2J2QBnj. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| Robust Method for Detecting Convergent Shifts in Evolutionary Rates. |
Partha R, Kowalczyk A, Clark NL, Chikina M |
Molecular biology and evolution |
Identifying genomic elements underlying phenotypic adaptations is an important problem in evolutionary biology. Comparative analyses learning from convergent evolution of traits are gaining momentum in accurately detecting such elements. We previously developed a method for predicting phenotypic associations of genetic elements by contrasting patterns of sequence evolution in species showing a phenotype with those that do not. Using this method we successfully demonstrated convergent evolutionary rate shifts in genetic elements associated with two phenotypic adaptations, namely the independent subterranean and marine transitions of terrestrial mammalian lineages. Our original method calculates gene- specific rates of evolution on branches of phylogenetic trees using linear regression. These rates represent the extent of sequence divergence on a branch after removing the expected divergence on the branch due to background factors. The rates calculated using this regression analysis exhibit an important statistical limitation, namely heteroscedasticity. We observe that the rates on branches that are longer on average show higher variance, and describe how this problem adversely affects the confidence with which we can make inferences about rate shifts. Using a combination of data transformation and weighted regression, we have developed an updated method that corrects this heteroscedasticity in the rates. We additionally illustrate the improved performance offered by the updated method at robust detection of convergent rate shifts in phylogenetic trees of protein-coding genes across mammals, as well as using simulated tree data sets. Overall, we present an important extension to our evolutionary-rates-based method that performs more robustly and consistently at detecting convergent shifts in evolutionary rates.
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| Pathway-level information extractor (PLIER) for gene expression data. |
Mao W, Zaslavsky E, Hartmann BM, Sealfon SC, Chikina M |
Nature methods |
A major challenge in gene expression analysis is to accurately infer relevant biological insights such as variation in cell-type proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER) ( https://github.com/wgmao/PLIER and http://gobie.csb.pitt.edu/PLIER ), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.
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| Evolutionary rate covariation analysis of E-cadherin identifies Raskol as a regulator of cell adhesion and actin dynamics in Drosophila. |
Raza Q, Choi JY, Li Y, O'Dowd RM, Watkins SC, Chikina M, Hong Y, Clark NL, Kwiatkowski AV |
PLoS genetics |
The adherens junction couples the actin cytoskeletons of neighboring cells to provide the foundation for multicellular organization. The core of the adherens junction is the cadherin-catenin complex that arose early in the evolution of multicellularity to link actin to intercellular adhesions. Over time evolutionary pressures have shaped the signaling and mechanical functions of the adherens junction to meet specific developmental and physiological demands. Evolutionary rate covariation (ERC) identifies proteins with correlated fluctuations in evolutionary rate that can reflect shared selective pressures and functions. Here we use ERC to identify proteins with evolutionary histories similar to the Drosophila E-cadherin (DE-cad) ortholog. Core adherens junction components alpha-catenin and p120-catenin displayed positive ERC correlations with DE-cad, indicating that they evolved under similar selective pressures during evolution between Drosophila species. Further analysis of the DE-cad ERC profile revealed a collection of proteins not previously associated with DE-cad function or cadherin-mediated adhesion. We then analyzed the function of a subset of ERC-identified candidates by RNAi during border cell (BC) migration and identified novel genes that function to regulate DE-cad. Among these, we found that the gene CG42684, which encodes a putative GTPase activating protein (GAP), regulates BC migration and adhesion. We named CG42684 raskol ("to split" in Russian) and show that it regulates DE-cad levels and actin protrusions in BCs. We propose that Raskol functions with DE-cad to restrict Ras/Rho signaling and help guide BC migration. Our results demonstrate that a coordinated selective pressure has shaped the adherens junction and this can be leveraged to identify novel components of the complexes and signaling pathways that regulate cadherin-mediated adhesion.
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| Kidney-infiltrating T cells in murine lupus nephritis are metabolically and functionally exhausted. |
Tilstra JS, Avery L, Menk AV, Gordon RA, Smita S, Kane LP, Chikina M, Delgoffe GM, Shlomchik MJ |
The Journal of clinical investigation |
While T cells are important for the pathogenesis of systemic lupus erythematosus (SLE) and lupus nephritis little is known about how T cells function after infiltrating the kidney. The current paradigm suggests that kidney-infiltrating T cells (KITs) are activated effector cells contributing to tissue damage and ultimately organ failure. Herein, we demonstrate that the majority of CD4+ and CD8+ KITs in 3 murine lupus models are not effector cells, as hypothesized, but rather express multiple inhibitory receptors and are highly dysfunctional, with reduced cytokine production and proliferative capacity. In other systems, this hypofunctional profile is linked directly to metabolic and specifically mitochondrial dysfunction, which we also observed in KITs. The T cell phenotype was driven by the expression of an "exhausted" transcriptional signature. Our data thus reveal that the tissue parenchyma has the capability of suppressing T cell responses and limiting damage to self. These findings suggest avenues for the treatment of autoimmunity based on selectively exploiting the exhausted phenotype of tissue-infiltrating T cells.
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| Ancient convergent losses of Paraoxonase 1 yield potential risks for modern marine mammals. |
Meyer WK, Jamison J, Richter R, Woods SE, Partha R, Kowalczyk A, Kronk C, Chikina M, Bonde RK, Crocker DE, Gaspard J, Lanyon JM, Marsillach J, Furlong CE, Clark NL |
Science (New York N.Y.) |
Mammals diversified by colonizing drastically different environments with each transition yielding numerous molecular changes, including losses of protein function. Though not initially deleterious, these losses could subsequently carry deleterious pleiotropic consequences. We have used phylogenetic methods to identify convergent functional losses across independent marine mammal lineages. In one extreme case, Paraoxonase 1 (PON1) accrued lesions in all marine lineages, while remaining intact in all terrestrial mammals. These lesions coincide with PON1 enzymatic activity loss in marine species' blood plasma. This convergent loss is likely explained by parallel shifts in marine ancestors' lipid metabolism and/or bloodstream oxidative environment affecting PON1's role in fatty acid oxidation. PON1 loss also eliminates marine mammals' main defense against neurotoxicity from specific man-made organophosphorus compounds, implying potential risks in modern environments.
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| Subterranean mammals show convergent regression in ocular genes and enhancers along with adaptation to tunneling. |
Partha R, Chauhan BK, Ferreira Z, Robinson JD, Lathrop K, Nischal KK, Chikina M, Clark NL |
eLife |
The underground environment imposes unique demands on life that have led subterranean species to evolve specialized traits many of which evolved convergently. We studied convergence in evolutionary rate in subterranean mammals in order to associate phenotypic evolution with specific genetic regions. We identified a strong excess of vision- and skin-related genes that changed at accelerated rates in the subterranean environment due to relaxed constraint and adaptive evolution. We also demonstrate that ocular-specific transcriptional enhancers were convergently accelerated, whereas enhancers active outside the eye were not. Furthermore, several uncharacterized genes and regulatory sequences demonstrated convergence and thus constitute novel candidate sequences for congenital ocular disorders. The strong evidence of convergence in these species indicates that evolution in this environment is recurrent and predictable and can be used to gain insights into phenotype-genotype relationships.
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| Differential requirements for myeloid leukemia IFN-gamma conditioning determine graft-versus-leukemia resistance and sensitivity. |
Matte-Martone C, Liu J, Zhou M, Chikina M, Green DR, Harty JT, Shlomchik WD |
The Journal of clinical investigation |
The graft-versus-leukemia (GVL) effect in allogeneic hematopoietic stem cell transplantation (alloSCT) is potent against chronic phase chronic myelogenous leukemia (CP-CML) but blast crisis CML (BC-CML) and acute myeloid leukemias (AML) are GVL resistant. To understand GVL resistance, we studied GVL against mouse models of CP-CML, BC-CML, and AML generated by the transduction of mouse BM with fusion cDNAs derived from human leukemias. Prior work has shown that CD4+ T cell-mediated GVL against CP- CML and BC-CML required intact leukemia MHCII; however, stem cells from both leukemias were MHCII negative. Here, we show that CP-CML, BC-CML, and AML stem cells upregulate MHCII in alloSCT recipients. Using gene- deficient leukemias, we determined that BC-CML and AML MHC upregulation required IFN-gamma stimulation, whereas CP-CML MHC upregulation was independent of both the IFN-gamma receptor (IFN-gammaR) and the IFN- alpha/beta receptor IFNAR1. Importantly, IFN-gammaR-deficient BC-CML and AML were completely resistant to CD4- and CD8-mediated GVL, whereas IFN- gammaR/IFNAR1 double-deficient CP-CML was fully GVL sensitive. Mouse AML and BC-CML stem cells were MHCI+ without IFN-gamma stimulation, suggesting that IFN-gamma sensitizes these leukemias to T cell killing by mechanisms other than MHC upregulation. Our studies identify the requirement of IFN-gamma stimulation as a mechanism for BC-CML and AML GVL resistance, whereas independence from IFN-gamma renders CP-CML more GVL sensitive, even with a lower-level alloimmune response.
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| Interferon-gamma Drives Treg Fragility to Promote Anti-tumor Immunity. |
Overacre-Delgoffe AE, Chikina M, Dadey RE, Yano H, Brunazzi EA, Shayan G, Horne W, Moskovitz JM, Kolls JK, Sander C, Shuai Y, Normolle DP, Kirkwood JM, Ferris RL, Delgoffe GM, Bruno TC, Workman CJ, Vignali DAA |
Cell |
Regulatory T cells (Tregs) are a barrier to anti-tumor immunity. Neuropilin-1 (Nrp1) is required to maintain intratumoral Treg stability and function but is dispensable for peripheral immune tolerance. Treg- restricted Nrp1 deletion results in profound tumor resistance due to Treg functional fragility. Thus identifying the basis for Nrp1 dependency and the key drivers of Treg fragility could help to improve immunotherapy for human cancer. We show that a high percentage of intratumoral NRP1(+) Tregs correlates with poor prognosis in melanoma and head and neck squamous cell carcinoma. Using a mouse model of melanoma where Nrp1-deficient (Nrp1(-/-)) and wild-type (Nrp1(+/+)) Tregs can be assessed in a competitive environment, we find that a high proportion of intratumoral Nrp1(-/-) Tregs produce interferon-gamma (IFNgamma), which drives the fragility of surrounding wild-type Tregs, boosts anti-tumor immunity, and facilitates tumor clearance. We also show that IFNgamma- induced Treg fragility is required for response to anti-PD1, suggesting that cancer therapies promoting Treg fragility may be efficacious.
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| LAG3 limits regulatory T cell proliferation and function in autoimmune diabetes. |
Zhang Q, Chikina M, Szymczak-Workman AL, Horne W, Kolls JK, Vignali KM, Normolle D, Bettini M, Workman CJ, Vignali DAA |
Science immunology |
Inhibitory receptors (IRs) are pivotal in controlling T cell homeostasis because of their intrinsic regulation of conventional effector T (Tconv) cell proliferation viability, and function. However, the role of IRs on regulatory T cells (Tregs) remains obscure because they could be required for suppressive activity and/or limit Treg function. We evaluated the role of lymphocyte activation gene 3 (LAG3; CD223) on Tregs by generating mice in which LAG3 is absent on the cell surface of Tregs in a murine model of type 1 diabetes. Unexpectedly, mice that lacked LAG3 expression on Tregs exhibited reduced autoimmune diabetes, consistent with enhanced Treg proliferation and function. Whereas the transcriptional landscape of peripheral wild-type (WT) and Lag3-deficient Tregs was largely comparable, substantial differences between intra-islet Tregs were evident and involved a subset of genes and pathways that promote Treg maintenance and function. Consistent with these observations, Lag3-deficient Tregs outcompeted WT Tregs in the islets but not in the periphery in cotransfer experiments because of enhanced interleukin-2-signal transducer and activator of transcription 5 signaling and increased Eos expression. Our study suggests that LAG3 intrinsically limits Treg proliferation and function at inflammatory sites, promotes autoimmunity in a chronic autoimmune-prone environment, and may contribute to Treg insufficiency in autoimmune disease.
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| Assessing significance in a Markov chain without mixing. |
Chikina M, Frieze A, Pegden W |
Proceedings of the National Academy of Sciences |
We present a statistical test to detect that a presented state of a reversible Markov chain was not chosen from a stationary distribution. In particular given a value function for the states of the Markov chain, we would like to show rigorously that the presented state is an outlier with respect to the values, by establishing a [Formula: see text] value under the null hypothesis that it was chosen from a stationary distribution of the chain. A simple heuristic used in practice is to sample ranks of states from long random trajectories on the Markov chain and compare these with the rank of the presented state; if the presented state is a [Formula: see text] outlier compared with the sampled ranks (its rank is in the bottom [Formula: see text] of sampled ranks), then this observation should correspond to a [Formula: see text] value of [Formula: see text] This significance is not rigorous, however, without good bounds on the mixing time of the Markov chain. Our test is the following: Given the presented state in the Markov chain, take a random walk from the presented state for any number of steps. We prove that observing that the presented state is an [Formula: see text]-outlier on the walk is significant at [Formula: see text] under the null hypothesis that the state was chosen from a stationary distribution. We assume nothing about the Markov chain beyond reversibility and show that significance at [Formula: see text] is best possible in general. We illustrate the use of our test with a potential application to the rigorous detection of gerrymandering in Congressional districting.
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| Wnt signaling regulates hepatobiliary repair following cholestatic liver injury in mice. |
Okabe H, Yang J, Sylakowski K, Yovchev M, Miyagawa Y, Nagarajan S, Chikina M, Thompson M, Oertel M, Baba H, Monga SP, Nejak-Bowen KN |
Hepatology (Baltimore Md.) |
Hepatic repair is directed chiefly by the proliferation of resident mature epithelial cells. Furthermore if predominant injury is to cholangiocytes, the hepatocytes can transdifferentiate to cholangiocytes to assist in the repair and vice versa, as shown by various fate-tracing studies. However, the molecular bases of reprogramming remain elusive. Using two models of biliary injury where repair occurs through cholangiocyte proliferation and hepatocyte transdifferentiation to cholangiocytes, we identify an important role of Wnt signaling. First we identify up-regulation of specific Wnt proteins in the cholangiocytes. Next, using conditional knockouts of Wntless and Wnt coreceptors low- density lipoprotein-related protein 5/6, transgenic mice expressing stable beta-catenin, and in vitro studies, we show a role of Wnt signaling through beta-catenin in hepatocyte to biliary transdifferentiation. Last, we show that specific Wnts regulate cholangiocyte proliferation, but in a beta-catenin-independent manner. CONCLUSION: Wnt signaling regulates hepatobiliary repair after cholestatic injury in both beta-catenin-dependent and -independent manners. (Hepatology 2016;64:1652-1666).
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| Modeling a human hepatocellular carcinoma subset in mice through coexpression of met and point-mutant beta-catenin. |
Tao J, Xu E, Zhao Y, Singh S, Li X, Couchy G, Chen X, Zucman-Rossi J, Chikina M, Monga SP |
Hepatology (Baltimore Md.) |
Hepatocellular cancer (HCC) remains a significant therapeutic challenge due to its poorly understood molecular basis. In the current study we investigated two independent cohorts of 249 and 194 HCC cases for any combinatorial molecular aberrations. Specifically we assessed for simultaneous HMET expression or hMet activation and catenin beta1 gene (CTNNB1) mutations to address any concomitant Met and Wnt signaling. To investigate cooperation in tumorigenesis, we coexpressed hMet and beta- catenin point mutants (S33Y or S45Y) in hepatocytes using sleeping beauty transposon/transposase and hydrodynamic tail vein injection and characterized tumors for growth, signaling, gene signatures, and similarity to human HCC. Missense mutations in exon 3 of CTNNB1 were identified in subsets of HCC patients. Irrespective of amino acid affected, all exon 3 mutations induced similar changes in gene expression. Concomitant HMET overexpression or hMet activation and CTNNB1 mutations were evident in 9%-12.5% of HCCs. Coexpression of hMet and mutant-beta-catenin led to notable HCC in mice. Tumors showed active Wnt and hMet signaling with evidence of glutamine synthetase and cyclin D1 positivity and mitogen-activated protein kinase/extracellular signal- regulated kinase, AKT/Ras/mammalian target of rapamycin activation. Introduction of dominant-negative T-cell factor 4 prevented tumorigenesis. The gene expression of mouse tumors in hMet-mutant beta- catenin showed high correlation, with subsets of human HCC displaying concomitant hMet activation signature and CTNNB1 mutations. CONCLUSION: We have identified cooperation of hMet and beta-catenin activation in a subset of HCC patients and modeled this human disease in mice with a significant transcriptomic intersection; this model will provide novel insight into the biology of this tumor and allow us to evaluate novel therapies as a step toward precision medicine. (Hepatology 2016;64:1587-1605).
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| Characterization of Gonadotrope Secretoproteome Identifies Neurosecretory Protein VGF-derived Peptide Suppression of Follicle-stimulating Hormone Gene Expression. |
Choi SG, Wang Q, Jia J, Chikina M, Pincas H, Dolios G, Sasaki K, Wang R, Minamino N, Salton SR, Sealfon SC |
The Journal of biological chemistry |
Reproductive function is controlled by the pulsatile release of hypothalamic gonadotropin-releasing hormone (GnRH) which regulates the expression of the gonadotropins luteinizing hormone and FSH in pituitary gonadotropes. Paradoxically, Fshb gene expression is maximally induced at lower frequency GnRH pulses, which provide a very low average concentration of GnRH stimulation. We studied the role of secreted factors in modulating gonadotropin gene expression. Inhibition of secretion specifically disrupted gonadotropin subunit gene regulation but left early gene induction intact. We characterized the gonadotrope secretoproteome and global mRNA expression at baseline and after Galphas knockdown, which has been found to increase Fshb gene expression (1). We identified 1077 secreted proteins or peptides, 19 of which showed mRNA regulation by GnRH or/and Galphas knockdown. Among several novel secreted factors implicated in Fshb gene regulation, we focused on the neurosecretory protein VGF. Vgf mRNA, whose gene has been implicated in fertility (2), exhibited high induction by GnRH and depended on Galphas In contrast with Fshb induction, Vgf induction occurred preferentially at high GnRH pulse frequency. We hypothesized that a VGF-derived peptide might regulate Fshb gene induction. siRNA knockdown or extracellular immunoneutralization of VGF augmented Fshb mRNA induction by GnRH. GnRH stimulated the secretion of the VGF-derived peptide NERP1. NERP1 caused a concentration-dependent decrease in Fshb gene induction. These findings implicate a VGF-derived peptide in selective regulation of the Fshb gene. Our results support the concept that signaling specificity from the cell membrane GnRH receptor to the nuclear Fshb gene involves integration of intracellular signaling and exosignaling regulatory motifs.
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| Hundreds of Genes Experienced Convergent Shifts in Selective Pressure in Marine Mammals. |
Chikina M, Robinson JD, Clark NL |
Molecular biology and evolution |
Mammal species have made the transition to the marine environment several times and their lineages represent one of the classical examples of convergent evolution in morphological and physiological traits. Nevertheless, the genetic mechanisms of their phenotypic transition are poorly understood, and investigations into convergence at the molecular level have been inconclusive. While past studies have searched for convergent changes at specific amino acid sites, we propose an alternative strategy to identify those genes that experienced convergent changes in their selective pressures, visible as changes in evolutionary rate specifically in the marine lineages. We present evidence of widespread convergence at the gene level by identifying parallel shifts in evolutionary rate during three independent episodes of mammalian adaptation to the marine environment. Hundreds of genes accelerated their evolutionary rates in all three marine mammal lineages during their transition to aquatic life. These marine-accelerated genes are highly enriched for pathways that control recognized functional adaptations in marine mammals, including muscle physiology, lipid-metabolism, sensory systems, and skin and connective tissue. The accelerations resulted from both adaptive evolution as seen in skin and lung genes, and loss of function as in gustatory and olfactory genes. In regard to sensory systems, this finding provides further evidence that reduced senses of taste and smell are ubiquitous in marine mammals. Our analysis demonstrates the feasibility of identifying genes underlying convergent organism-level characteristics on a genome-wide scale and without prior knowledge of adaptations, and provides a powerful approach for investigating the physiological functions of mammalian genes.
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| A Temporal Switch in the Germinal Center Determines Differential Output of Memory B and Plasma Cells. |
Weisel FJ, Zuccarino-Catania GV, Chikina M, Shlomchik MJ |
Immunity |
There is little insight into or agreement about the signals that control differentiation of memory B cells (MBCs) and long-lived plasma cells (LLPCs). By performing BrdU pulse-labeling studies we found that MBC formation preceded the formation of LLPCs in an adoptive transfer immunization system, which allowed for a synchronized Ag-specific response with homogeneous Ag-receptor, yet at natural precursor frequencies. We confirmed these observations in wild-type (WT) mice and extended them with germinal center (GC) disruption experiments and variable region gene sequencing. We thus show that the GC response undergoes a temporal switch in its output as it matures, revealing that the reaction engenders both MBC subsets with different immune effector function and, ultimately, LLPCs at largely separate points in time. These data demonstrate the kinetics of the formation of the cells that provide stable humoral immunity and therefore have implications for autoimmunity, for vaccine development, and for understanding long-term pathogen resistance.
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| A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes. |
Aghaeepour N, Chattopadhyay P, Chikina M, Dhaene T, Van Gassen S, Kursa M, Lambrecht BN, Malek M, McLachlan GJ, Qian Y, Qiu P, Saeys Y, Stanton R, Tong D, Vens C, Walkowiak S, Wang K, Finak G, Gottardo R, Mosmann T, Nolan GP, Scheuermann RH, Brinkman RR |
Cytometry. Part A : the journal of the International Society for |
The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of computational methods for identifying cell populations in multidimensional flow cytometry data. Here we report the results of FlowCAP-IV where algorithms from seven different research groups predicted the time to progression to AIDS among a cohort of 384 HIV+ subjects using antigen-stimulated peripheral blood mononuclear cell (PBMC) samples analyzed with a 14-color staining panel. Two approaches (FlowReMi.1 and flowDensity-flowType-RchyOptimyx) provided statistically significant predictive value in the blinded test set. Manual validation of submitted results indicated that unbiased analysis of single cell phenotypes could reveal unexpected cell types that correlated with outcomes of interest in high dimensional flow cytometry datasets.
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| Human Dendritic Cell Response Signatures Distinguish 1918 Pandemic, and Seasonal H1N1 Influenza Viruses. |
Hartmann BM, Thakar J, Albrecht RA, Avey S, Zaslavsky E, Marjanovic N, Chikina M, Fribourg M, Hayot F, Schmolke M, Meng H, Wetmur J, Garcia-Sastre A, Kleinstein SH, Sealfon SC |
Journal of virology |
UNLABELLED: Influenza viruses continue to present global threats to human health. Antigenic drift and shift genetic reassortment, and cross- species transmission generate new strains with differences in epidemiology and clinical severity. We compared the temporal transcriptional responses of human dendritic cells (DC) to infection with two pandemic (A/Brevig Mission/1/1918, A/California/4/2009) and two seasonal (A/New Caledonia/20/1999, A/Texas/36/1991) H1N1 influenza viruses. Strain-specific response differences included stronger activation of NF-kappaB following infection with A/New Caledonia/20/1999 and a unique cluster of genes expressed following infection with A/Brevig Mission/1/1918. A common antiviral program showing strain-specific timing was identified in the early DC response and found to correspond with reported transcript changes in blood during symptomatic human influenza virus infection. Comparison of the global responses to the seasonal and pandemic strains showed that a dramatic divergence occurred after 4 h, with only the seasonal strains inducing widespread mRNA loss. IMPORTANCE: Continuously evolving influenza viruses present a global threat to human health; however, these host responses display strain-dependent differences that are incompletely understood. Thus, we conducted a detailed comparative study assessing the immune responses of human DC to infection with two pandemic and two seasonal H1N1 influenza strains. We identified in the immune response to viral infection both common and strain-specific features. Among the stain-specific elements were a time shift of the interferon-stimulated gene response, selective induction of NF-kappaB signaling by one of the seasonal strains, and massive RNA degradation as early as 4 h postinfection by the seasonal, but not the pandemic, viruses. These findings illuminate new aspects of the distinct differences in the immune responses to pandemic and seasonal influenza viruses.
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| CellCODE: a robust latent variable approach to differential expression analysis for heterogeneous cell populations. |
Chikina M, Zaslavsky E, Sealfon SC |
Bioinformatics |
MOTIVATION: Identifying alterations in gene expression associated with different clinical states is important for the study of human biology. However clinical samples used in gene expression studies are often derived from heterogeneous mixtures with variable cell-type composition, complicating statistical analysis. Considerable effort has been devoted to modeling sample heterogeneity, and presently, there are many methods that can estimate cell proportions or pure cell-type expression from mixture data. However, there is no method that comprehensively addresses mixture analysis in the context of differential expression without relying on additional proportion information, which can be inaccurate and is frequently unavailable. RESULTS: In this study, we consider a clinically relevant situation where neither accurate proportion estimates nor pure cell expression is of direct interest, but where we are rather interested in detecting and interpreting relevant differential expression in mixture samples. We develop a method, Cell-type COmputational Differential Estimation (CellCODE), that addresses the specific statistical question directly, without requiring a physical model for mixture components. Our approach is based on latent variable analysis and is computationally transparent; it requires no additional experimental data, yet outperforms existing methods that use independent proportion measurements. CellCODE has few parameters that are robust and easy to interpret. The method can be used to track changes in proportion, improve power to detect differential expression and assign the differentially expressed genes to the correct cell type.
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| Low-variance RNAs identify Parkinson's disease molecular signature in blood. |
Chikina MD, Gerald CP, Li X, Ge Y, Pincas H, Nair VD, Wong AK, Krishnan A, Troyanskaya OG, Raymond D, Saunders-Pullman R, Bressman SB, Yue Z, Sealfon SC |
Movement disorders : official journal of the Movement Disorder Society |
The diagnosis of Parkinson's disease (PD) is usually not established until advanced neurodegeneration leads to clinically detectable symptoms. Previous blood PD transcriptome studies show low concordance possibly resulting from the use of microarray technology, which has high measurement variation. The Leucine-rich repeat kinase 2 (LRRK2) G2019S mutation predisposes to PD. Using preclinical and clinical studies, we sought to develop a novel statistically motivated transcriptomic-based approach to identify a molecular signature in the blood of Ashkenazi Jewish PD patients, including LRRK2 mutation carriers. Using a digital gene expression platform to quantify 175 messenger RNA (mRNA) markers with low coefficients of variation (CV), we first compared whole-blood transcript levels in mouse models (1) overexpressing wild-type (WT) LRRK2, (2) overexpressing G2019S LRRK2, (3) lacking LRRK2 (knockout), and (4) and in WT controls. We then studied an Ashkenazi Jewish cohort of 34 symptomatic PD patients (both WT LRRK2 and G2019S LRRK2) and 32 asymptomatic controls. The expression profiles distinguished the four mouse groups with different genetic background. In patients, we detected significant differences in blood transcript levels both between individuals differing in LRRK2 genotype and between PD patients and controls. Discriminatory PD markers included genes associated with innate and adaptive immunity and inflammatory disease. Notably, gene expression patterns in levodopa-treated PD patients were significantly closer to those of healthy controls in a dose-dependent manner. We identify whole- blood mRNA signatures correlating with LRRK2 genotype and with PD disease state. This approach may provide insight into pathogenesis and a route to early disease detection.
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| Hybrid Bayesian-rank integration approach improves the predictive power of genomic dataset aggregation. |
Badgeley MA, Sealfon SC, Chikina MD |
Bioinformatics |
MOTIVATION: Modern molecular technologies allow the collection of large amounts of high-throughput data on the functional attributes of genes. Often multiple technologies and study designs are used to address the same biological question such as which genes are overexpressed in a specific disease state. Consequently there is considerable interest in methods that can integrate across datasets to present a unified set of predictions. RESULTS: An important aspect of data integration is being able to account for the fact that datasets may differ in how accurately they capture the biological signal of interest. While many methods to address this problem exist, they always rely either on dataset internal statistics, which reflect data structure and not necessarily biological relevance, or external gold standards, which may not always be available. We present a new rank aggregation method for data integration that requires neither external standards nor internal statistics but relies on Bayesian reasoning to assess dataset relevance. We demonstrate that our method outperforms established techniques and significantly improves the predictive power of rank-based aggregations. We show that our method, which does not require an external gold standard, provides reliable estimates of dataset relevance and allows the same set of data to be integrated differently depending on the specific signal of interest. AVAILABILITY: The method is implemented in R and is freely available at http://www.pitt.edu/~mchikina/BIRRA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| Homer1 alternative splicing is regulated by gonadotropin-releasing hormone and modulates gonadotropin gene expression. |
Wang Q, Chikina MD, Pincas H, Sealfon SC |
Molecular and cellular biology |
Hypothalamic gonadotropin-releasing hormone (GnRH) plays a critical role in reproductive physiology by regulating follicle-stimulating hormone (FSH) and luteinizing hormone (LH) gene expression in the pituitary. Analysis of gonadotrope deep-sequencing data identified a global regulation of pre-mRNA splicing by GnRH. Homer1 a gene encoding a postsynaptic density scaffolding protein, was selected for further study. Homer1 expresses a short splice form, Homer1a, and more-abundant long transcripts Homer1b/c. GnRH induced a modest increase in Homer1b/c expression and a dramatic increase in the Homer1a splice form. G protein knockdown studies suggested that the Homer1 induction, but not the regulated splicing, was Galphaq/11 dependent. Phosphorylation of the splicing regulator SRp20 was found to be induced by GnRH. SRp20 depletion attenuated the GnRH-induced increase in the Homer1a-to-Homer1b/c ratio and modulated the effects of GnRH on FSHbeta and LHbeta expression. Homer1 gene knockdown resulted in increased GnRH-induced FSHbeta and LHbeta transcript levels. Furthermore, splice-form-specific reduction of Homer1b/c increased both FSHbeta and LHbeta mRNA induction, whereas reduction of Homer1a had the opposite effect on FSHbeta induction. These results indicate that the regulation of Homer1 splicing by GnRH contributes to gonadotropin gene control.
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| Increasing consistency of disease biomarker prediction across datasets. |
Chikina MD, Sealfon SC |
PloS one |
Microarray studies with human subjects often have limited sample sizes which hampers the ability to detect reliable biomarkers associated with disease and motivates the need to aggregate data across studies. However human gene expression measurements may be influenced by many non-random factors such as genetics, sample preparations, and tissue heterogeneity. These factors can contribute to a lack of agreement among related studies, limiting the utility of their aggregation. We show that it is feasible to carry out an automatic correction of individual datasets to reduce the effect of such 'latent variables' (without prior knowledge of the variables) in such a way that datasets addressing the same condition show better agreement once each is corrected. We build our approach on the method of surrogate variable analysis but we demonstrate that the original algorithm is unsuitable for the analysis of human tissue samples that are mixtures of different cell types. We propose a modification to SVA that is crucial to obtaining the improvement in agreement that we observe. We develop our method on a compendium of multiple sclerosis data and verify it on an independent compendium of Parkinson's disease datasets. In both cases, we show that our method is able to improve agreement across varying study designs, platforms, and tissues. This approach has the potential for wide applicability to any field where lack of inter-study agreement has been a concern.
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| beta-catenin regulates GnRH-induced FSHbeta gene expression. |
Wang Q, Chikina M, Zaslavsky E, Pincas H, Sealfon SC |
Molecular endocrinology (Baltimore Md.) |
The regulation of gonadotropin synthesis by GnRH plays an essential role in the neuroendocrine control of reproduction. The known signaling mechanisms involved in gonadotropin synthesis have been expanding. For example involvement of beta-catenin in LHbeta induction by GnRH has been discovered. We examined the role of beta-catenin in FSHbeta gene expression in LbetaT2 gonadotrope cells. GnRH caused a sustained increase in nuclear beta-catenin levels, which was significantly reduced by c-Jun N-terminal kinase (JNK) inhibition. Small interfering RNA-mediated knockdown of beta-catenin mRNA demonstrated that induction of FSHbeta mRNA by GnRH depended on beta-catenin and that regulation of FSHbeta by beta-catenin occurred independently of the JNK-c-jun pathway. beta- Catenin depletion had no impact on FSHbeta mRNA stability. In LbetaT2 cells transfected with FSHbeta promoter luciferase fusion constructs, GnRH responsiveness was conferred by the proximal promoter (-944/-1) and was markedly decreased by beta-catenin knockdown. However, none of the T-cell factor/lymphoid enhancer factor binding sites in that region were required for promoter activation by GnRH. Chromatin immunoprecipitation further corroborated the absence of direct interaction between beta- catenin and the 1.8-kb FSHbeta promoter. To elucidate the mechanism for the beta-catenin effect, we analyzed approximately 1 billion reads of next-generation RNA sequencing beta-catenin knockdown assays and selected the nuclear cofactor breast cancer metastasis-suppressor 1-like (Brms1L) as one candidate for further study. Subsequent experiments confirmed that Brms1L mRNA expression was decreased by beta-catenin knockdown as well as by JNK inhibition. Furthermore, knockdown of Brms1L significantly attenuated GnRH-induced FSHbeta expression. Thus, our findings indicate that the expression of Brms1L depends on beta-catenin activity and contributes to FSHbeta induction by GnRH.
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| Involvement of histone demethylase LSD1 in short-time-scale gene expression changes during cell cycle progression in embryonic stem cells. |
Nair VD, Ge Y, Balasubramaniyan N, Kim J, Okawa Y, Chikina M, Troyanskaya O, Sealfon SC |
Molecular and cellular biology |
The histone demethylase LSD1 a component of the CoREST (corepressor for element 1-silencing transcription factor) corepressor complex, plays an important role in the downregulation of gene expression during development. However, the activities of LSD1 in mediating short-time- scale gene expression changes have not been well understood. To reveal the mechanisms underlying these two distinct functions of LSD1, we performed genome-wide mapping and cellular localization studies of LSD1 and its dimethylated histone 3 lysine 4 (substrate H3K4me2) in mouse embryonic stem cells (ES cells). Our results showed an extensive overlap between the LSD1 and H3K4me2 genomic regions and a correlation between the genomic levels of LSD1/H3K4me2 and gene expression, including many highly expressed ES cell genes. LSD1 is recruited to the chromatin of cells in the G(1)/S/G(2) phases and is displaced from the chromatin of M-phase cells, suggesting that LSD1 or H3K4me2 alternatively occupies LSD1 genomic regions during cell cycle progression. LSD1 knockdown by RNA interference or its displacement from the chromatin by antineoplastic agents caused an increase in the levels of a subset of LSD1 target genes. Taken together, these results suggest that cell cycle-dependent association and dissociation of LSD1 with chromatin mediates short-time- scale gene expression changes during embryonic stem cell cycle progression.
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| An effective statistical evaluation of ChIPseq dataset similarity. |
Chikina MD, Troyanskaya OG |
Bioinformatics |
MOTIVATION: ChIPseq is rapidly becoming a common technique for investigating protein-DNA interactions. However results from individual experiments provide a limited understanding of chromatin structure, as various chromatin factors cooperate in complex ways to orchestrate transcription. In order to quantify chromtain interactions, it is thus necessary to devise a robust similarity metric applicable to ChIPseq data. Unfortunately, moving past simple overlap calculations to give statistically rigorous comparisons of ChIPseq datasets often involves arbitrary choices of distance metrics, with significance being estimated by computationally intensive permutation tests whose statistical power may be sensitive to non-biological experimental and post-processing variation. RESULTS: We show that it is in fact possible to compare ChIPseq datasets through the efficient computation of exact P-values for proximity. Our method is insensitive to non-biological variation in datasets such as peak width, and can rigorously model peak location biases by evaluating similarity conditioned on a restricted set of genomic regions (such as mappable genome or promoter regions). Applying our method to the well-studied dataset of Chen et al. (2008), we elucidate novel interactions which conform well with our biological understanding. By comparing ChIPseq data in an asymmetric way, we are able to observe clear interaction differences between cofactors such as p300 and factors that bind DNA directly. AVAILABILITY: Source code is available for download at http://sonorus.princeton.edu/IntervalStats/IntervalStats.tar.gz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| Misfolded proteins inhibit proliferation and promote stress-induced death in SV40-transformed mammalian cells. |
Arslan MA, Chikina M, Csermely P, Soti C |
FASEB journal : official publication of the Federation of American |
Protein misfolding is implicated in neurodegenerative diseases and occurs in aging. However the contribution of the misfolded ensembles to toxicity remains largely unknown. Here we introduce 2 primate cell models of destabilized proteins devoid of specific cellular functions and interactors, as bona fide misfolded proteins, allowing us to isolate the gain-of-function of non-native structures. Both GFP-degron and a mutant chloramphenicol-acetyltransferase fused to GFP (GFP-Delta9CAT) form perinuclear aggregates, are degraded by the proteasome, and colocalize with and induce the chaperone Hsp70 (HSPA1A/B) in COS-7 cells. We find that misfolded proteins neither significantly compromise chaperone- mediated folding capacity nor induce cell death. However, they do induce growth arrest in cells that are unable to degrade them and promote stress-induced death upon proteasome inhibition by MG-132 and heat shock. Finally, we show that overexpression of all heat-shock factor-1 (HSF1) and Hsp70 proteins, as well as wild-type and deacetylase-deficient (H363Y) SIRT1, rescue survival upon stress, implying a noncatalytic action of SIRT1 in response to protein misfolding. Our study establishes a novel model and extends our knowledge on the mechanism of the function- independent proteotoxicity of misfolded proteins in dividing cells.
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| Accurate quantification of functional analogy among close homologs. |
Chikina MD, Troyanskaya OG |
PLoS computational biology |
Correctly evaluating functional similarities among homologous proteins is necessary for accurate transfer of experimental knowledge from one organism to another and is of particular importance for the development of animal models of human disease. While the fact that sequence similarity implies functional similarity is a fundamental paradigm of molecular biology, sequence comparison does not directly assess the extent to which two proteins participate in the same biological processes, and has limited utility for analyzing families with several parologous members. Nevertheless, we show that it is possible to provide a cross-organism functional similarity measure in an unbiased way through the exclusive use of high-throughput gene-expression data. Our methodology is based on probabilistic cross-species mapping of functionally analogous proteins based on Bayesian integrative analysis of gene expression compendia. We demonstrate that even among closely related genes, our method is able to predict functionally analogous homolog pairs better than relying on sequence comparison alone. We also demonstrate that the landscape of functional similarity is often complex and that definitive "functional orthologs" do not always exist. Even in these cases, our method and the online interface we provide are designed to allow detailed exploration of sources of inferred functional similarity that can be evaluated by the user.
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| Global prediction of tissue-specific gene expression and context- dependent gene networks in Caenorhabditis elegans. |
Chikina MD, Huttenhower C, Murphy CT, Troyanskaya OG |
PLoS computational biology |
Tissue-specific gene expression plays a fundamental role in metazoan biology and is an important aspect of many complex diseases. Nevertheless an organism-wide map of tissue-specific expression remains elusive due to difficulty in obtaining these data experimentally. Here, we leveraged existing whole-animal Caenorhabditis elegans microarray data representing diverse conditions and developmental stages to generate accurate predictions of tissue-specific gene expression and experimentally validated these predictions. These patterns of tissue- specific expression are more accurate than existing high-throughput experimental studies for nearly all tissues; they also complement existing experiments by addressing tissue-specific expression present at particular developmental stages and in small tissues. We used these predictions to address several experimentally challenging questions, including the identification of tissue-specific transcriptional motifs and the discovery of potential miRNA regulation specific to particular tissues. We also investigate the role of tissue context in gene function through tissue-specific functional interaction networks. To our knowledge, this is the first study producing high-accuracy predictions of tissue-specific expression and interactions for a metazoan organism based on whole-animal data.
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| The Sleipnir library for computational functional genomics. |
Huttenhower C, Schroeder M, Chikina MD, Troyanskaya OG |
Bioinformatics |
MOTIVATION: Biological data generation has accelerated to the point where hundreds or thousands of whole-genome datasets of various types are available for many model organisms. This wealth of data can lead to valuable biological insights when analyzed in an integrated manner but the computational challenge of managing such large data collections is substantial. In order to mine these data efficiently, it is necessary to develop methods that use storage, memory and processing resources carefully. RESULTS: The Sleipnir C++ library implements a variety of machine learning and data manipulation algorithms with a focus on heterogeneous data integration and efficiency for very large biological data collections. Sleipnir allows microarray processing, functional ontology mining, clustering, Bayesian learning and inference and support vector machine tasks to be performed for heterogeneous data on scales not previously practical. In addition to the library, which can easily be integrated into new computational systems, prebuilt tools are provided to perform a variety of common tasks. Many tools are multithreaded for parallelization in desktop or high-throughput computing environments, and most tasks can be performed in minutes for hundreds of datasets using a standard personal computer. AVAILABILITY: Source code (C++) and documentation are available at http://function.princeton.edu/sleipnir and compiled binaries are available from the authors on request.
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