Biology subjects

Sinha, S.

Publications and source records attributed to Sinha, S..

At least 217 records · Page 12Linked to original sources

bioRxiv2019

Knowledge-guided analysis of ‘omics’ data using the KnowEnG cloud platform

We present KnowEnG, a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis and expression signature analysis. The system offers knowledge-guided data-mining and machine learning algorithms, where user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge-bases and encoded in a massive Knowledge Network. KnowEnG adheres to FAIR principles: its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution of compute-intensive and data-intensive algorithms, and are interoperable with other computing platforms. They are made available through multiple access modes including a web-portal, and include specialized visualization modules. We present use cases and re-analysis of published cancer data sets using KnowEnG tools and demonstrate its potential value in democratization of advanced tools for the modern genomics era.

cancer biology↗

bioRxiv2019

Cell cycle regulators control mesoderm specification in human pluripotent stem cells

Mesoderm is one of the three germ layers produced during gastrulation from which muscle, bones, kidneys and the cardiovascular system originate. Understanding the mechanisms controlling mesoderm specification could be essential for a diversity of applications, including the development of regenerative medicine therapies against diseases affecting these tissues. Here, we use human pluripotent stem cells (hPSCs) to investigate the role of cell cycle in mesoderm formation. For that, proteins controlling G1 and G2/M cell cycle phases were inhibited during differentiation of hPSCs into lateral plate, cardiac and presomitic mesoderm using small molecules or by conditional knock down. These loss of function experiments revealed that CDKs and pRb phosphorylation are necessary for efficient mesoderm formation in a context-dependent manner. Further investigations showed that inhibition of the G2/M regulator CDK1 decreases BMP signaling activity specifically during lateral plate mesoderm formation while reducing FGF/ERK1/2 activity in all mesoderm subtypes. Taken together, our findings reveal that cell cycle regulators direct mesoderm formation by controlling the activity of key developmental pathways.

developmental biology↗

bioRxiv2019

A competence-regulated toxin-antitoxin system in Haemophilus influenzae

Natural competence allows bacteria to respond to environmental and nutritional cues by taking up free DNA from their surroundings, thus gaining both nutrients and genetic information. In the Gram-negative bacterium Haemophilus influenzae, the genes needed for DNA uptake are induced by the CRP and Sxy transcription factors in response to lack of preferred carbon sources and nucleotide precursors. Here we show that one of these genes, HI0659, encodes the antitoxin of a competence-regulated toxin-antitoxin operon ( toxTA), likely acquired by horizontal gene transfer from a Streptococcus species. Deletion of the putative toxin (HI0660) restores uptake to the antitoxin mutant. The full toxTA operon was present in only 17 of the 181 strains we examined; complete deletion was seen in 22 strains and deletions removing parts of the toxin gene in 142 others. In addition to the expected Sxy-and CRP-dependent-competence promoter, HI0659/660 transcript analysis using RNA-seq identified an internal antitoxin-repressed promoter whose transcription starts within toxT and will yield nonfunctional protein. We propose that the most likely effect of unopposed toxin expression is non-specific cleavage of mRNAs and arrest or death of competent cells in the culture. Although the high frequency of toxT and toxTA deletions suggests that this competence-regulated toxin-antitoxin system may be mildly deleterious, it could also facilitate downregulation of protein synthesis and recycling of nucleotides under starvation conditions. Although our analyses were focused on the effects of toxTA, the RNA-seq dataset will be a useful resource for further investigations into competence regulation.\n\nABBREVIATED SUMMARYThe competence regulon of Haemophilus influenzae includes an unprecedented toxin/antitoxin gene pair. When not opposed by antitoxin, the toxin completely prevents DNA uptake but causes only very minor decreases in cell growth and competence gene expression. The TA gene pair was acquired by horizontal gene transfer, and the toxin gene has undergone repeated deletions in other strains.

microbiology↗

bioRxiv2019

Gene Sets Analysis using Network Patterns

High throughput assays allow researchers to identify sets of genes related to experimental conditions or phenotypes of interest. These gene sets are frequently subjected to functional interpretation using databases of gene annotations. Recent approaches have extended this approach to also consider networks of gene-gene relationships and interactions when attempting to characterize properties of a gene set. We present here a supervised learning algorithm for gene set analysis, called GeneSet MAPR, that for the first time explicitly considers the patterns of direct as well as indirect relationships present in the network to quantify gene-gene similarities and then report shared properties of the gene set. Our extensive evaluations show that GeneSet MAPR performs better than other network-based methods for the task of identifying genes related to a given gene set, enabling more reliable functional characterizations of the gene set. When applied to the set of response-associated genes from a triple negative breast cancer study, GeneSet MAPR uncovers gene families such as claudins, kallikreins, and collagen type alpha chains related to patients response to treatment, and which are not uncovered with traditional analysis.

systems biology↗

bioRxiv2019

4q-D4Z4 chromatin architecture regulates the transcription of muscle atrophic genes in FSHD

Despite increasing insights in genome structure organization, the role of DNA repetitive elements, accounting for more than two thirds of the human genome, remains elusive. Facioscapulohumeral Dystrophy (FSHD) is associated with deletion of D4Z4 repeat array below 11 units at 4q35.2. It is known that the deletion alters chromatin structure in cis, leading to genes upregulation. Here we show a genome-wide role of 4q-D4Z4 array in modulating gene expression via 3D nuclear contacts. We have developed an integrated strategy of 4q-D4Z4 specific 4C-seq and chromatin segmentation analyses, showing that 4q-D4Z4 3D interactome and chromatin states of interacting genes are impaired in FSHD1 condition; in particular, genes which have lost the 4q-D4Z4 interaction and with a more active chromatin state are enriched for muscle atrophy transcriptional signature. Expression level of these genes is restored by the interaction with an ectopic 4q-D4Z4 array, suggesting that the repeat directly modulates the transcription of contacted targets.\n\nOf note, the upregulation of atrophic genes is a common feature of several FSHD1 and FSHD2 patients, indicating that we have identified a core set of deregulated genes involved in FSHD pathophysiology.

genomics↗

bioRxiv2019

Molecular evolution guided functional analyses reveals Nucleobindin-1 as a canonical E-box binding protein promoting Epithelial-to-Mesenchymal transition (EMT)

Calcium binding proteins (CBPs) function in response to changes in intracellular calcium (Ca2+) levels by modulating intracellular signaling pathways. Calcium sensors, including Nucleobindins (Nucb1/2) undergo Ca2+-binding induced conformational changes and bind to target proteins. Nucleobindins possess additional uncharacterized domains including partly characterized EF-hands. We study the molecular evolution of Nucleobindins in eukaryotes emphasizing on the N-terminal DNA binding domain (DBD) that emerged as a result of domain insertion event in Nucb1/2 domain-scaffold in an ancestor to the opisthokonts. Our results from in silico analyses and functional assays revealed that DBD of Nucb1 binds to canonical E-box sequences and triggers cell epithelial-mesenchymal transition (EMT). Thus, post gene duplication, Nucb1 has emerged as unconventional Ca2+-binding transcriptional regulators that can induce EMT.\n\nHighlightsO_LINucleobindins emerged from prokaryotic EF-hand containing protein.\nC_LIO_LIThe DNA-binding domain was gained in these in opisthokonts.\nC_LIO_LIGene duplication in ancestor of euteleostomes, lead to emergence of Nucb1/2.\nC_LIO_LINucb1 emerged as a canonical E-box binding protein promoting EMT\nC_LI

cell biology↗

bioRxiv2019

Identification of RBPMS as a smooth muscle master splicing regulator via proximity of its gene with super-enhancers

Alternative splicing (AS) programs are primarily controlled by regulatory RNA binding proteins (RBPs). It has been proposed that a small number of master splicing regulators might control cell-specific splicing networks and that these RBPs could be identified by proximity of their genes to transcriptional super-enhancers. Using this approach we identified RBPMS as a critical splicing regulator in differentiated vascular smooth muscle cells (SMCs). RBPMS is highly down-regulated during phenotypic switching of SMCs from a contractile to a motile and proliferative phenotype and is responsible for 20% of the AS changes during this transition. RBPMS directly regulates AS of numerous components of the actin cytoskeleton and focal adhesion machineries whose activity is critical for SMC function in both phenotypes. RBPMS also regulates splicing of other splicing, post-transcriptional and transcription regulators including the key SMC transcription factor Myocardin, thereby matching many of the criteria of a master regulator of AS in SMCs.

molecular biology↗

bioRxiv2019

A 3D-printed hand-powered centrifuge for molecular biology

The centrifuge is an essential tool for many aspects of research and medical diagnostics. However, conventional centrifuges are often inaccessible outside of conventional laboratory settings, such as remote field sites, require a constant external power source, and can be prohibitively costly in resource-limited settings and STEM-focused programs. Here we present the 3D-Fuge, a 3D-printed hand-powered centrifuge, as a novel alternative to standard benchtop centrifuges. Based on the design principles of a paper-based centrifuge, this 3D-printed instrument increases the volume capacity to 2 mL and can reach hand-powered centrifugation speeds up to 6,000 rpm. The 3D-Fuge devices presented here are capable of centrifugation of a wide variety of different solutions such as spinning down samples for biomarker applications and performing nucleotide extractions as part of a portable molecular lab setup. We introduce the design and proof-of-principle trials that demonstrate the utility of low-cost 3D printed centrifuges for use in remote and educational settings.

bioengineering↗

bioRxiv2018

ElectroPen: An ultralow-cost piezoelectric electroporator

Electroporation is a basic yet powerful method for delivering small molecules (RNA, DNA, drugs) across cell membranes by application of an electrical field. Due to its vital role, electroporation has wide applicability from genetically engineering cells, to drug- and DNA-based vaccine delivery. Despite its broad applications in biological research, the high cost of electroporators is an obstacle for many budget-conscious laboratories. To address this need, we describe a simple, inexpensive, and hand-held electroporator inspired by a common household piezoelectric gas lighter. The proposed \"ElectroPen\" device costs about 20 cents, is portable (13 g), is fabricated on-demand using 3D-printing, and delivers repeatable exponentially decaying pulses of about 2000 V in 5 ms. We provide a proof-of-concept demonstration by genetically transforming plasmids into E. coli strains and show comparable transformation efficiency and cell growth with commercial devices, but at a fraction of the cost. Our results are validated by an independent team across the globe, providing a real-world example of democratizing science through frugal tools. Thus, the simplicity, accessibility, and affordability of our device holds potential for making modern synthetic biology accessible in high-school, community, and field-ecology laboratories.

bioengineering↗

bioRxiv2018

Genome-wide non-coding variant interpretation improves discovery of transcriptional regulators of drug response

Identification of functional non-coding variants (polymorphisms) and their mechanistic interpretation is a major challenge of modern genomics, especially for precision medicine. Transcription factor (TF) binding profiles and epigenomic landscapes in reference samples can help us functionally annotate the genome, but do not provide ready answers regarding the effects of non-coding variants. A promising computational approach is to build models that predict TF-DNA binding from sequence, and use such models to score a variants impact on TF binding strength. Here, we asked if this mechanistic approach to variant interpretation can be combined with information on genotype-phenotype associations to discover important transcription factors regulating phenotypic variation among individuals. We developed a statistical approach that integrates phenotype, genotype, gene expression, TF ChIP-seq and Hi-C chromatin interaction data to answer this question. Using drug sensitivity measured in lymphoblastoid cell lines as the phenotype of interest, we tested if the non-coding variants statistically linked to the phenotype are enriched for strong predicted impact on DNA-binding strength of a TF, and used this test to identify TFs regulating individual differences in the phenotype. Our method relies on a new method for predicting variant impact on TF-DNA binding, that uses a combination of biophysical modelling and machine learning. We report statistical and literature-based support for many of the TFs discovered here as regulators of drug response variation. We show that the use of mechanistically driven variant impact predictors can identify TF-drug associations that would otherwise be missed. We examined in depth the evidence underlying one reported association - that of the transcription factor ELF1 with the drug doxorubicin - and identified several genes that may mediate this regulatory relationship.

bioinformatics↗

bioRxiv2018

Heptad repeat regions of coiled-coil domains of Mfn1 are crucial for Mfn1 mediated mitochondrial fusion

Mitofusin mediate fusion of outer mitochondrial membranes (OMM). Recent studies have explained the role of GTPase domain for Mfn1 dimerization and outer mitochondrial membrane (OMM) fusion. Coiled-coiled domains [namely, coiled-coil/Middle domains (CC1MD) and coiled-coil-2 GTPase effector domain (CC2/GED)] form helical bundles that mediate open-to-close conformations of Mfn1 upon GTP binding and have been previously reported to be important for OMM tethering and OMM fusion. To further decipher the significance of helical structure of MD, we functionally characterized the heptad repeat regions of MD. Consistent with previous studies, we show that MD consists of two heptad repeats (HR1, namely HR1a and HR1b) and both of these are crucial for Mfn1 mediated OMM fusion.\n\nHIGHLIGHTSO_LICoiled-coil1 (also known as Middle domain, MD) contains two heptad repeat regions.\nC_LIO_LIHeptad repeats of MD (namely HR1a and HR1b) are crucial for fusogenic property of Mfn1\nC_LIO_LIMutations disrupting of helical structure of HR1b lead to loss of fusogenic activity of Mfn1\nC_LI

cell biology↗

bioRxiv2018

A systematic genome-wide mapping of the oncogenic risks associated with CRISPR-Cas9 editing

Recent studies have reported that CRISPR-Cas9 gene editing induces a p53-dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations11,12. It is unclear whether these CRISPR-induced changes are applicable to different cell types, and whether CRISPR gene editing may select for other oncogenic mutations. Addressing these questions, we analyzed genome-wide CRISPR and RNAi screens to systematically chart the mutation selection potential of CRISPR knockouts across the whole exome. Our analysis suggests that CRISPR gene editing can select for mutants of KRAS and VHL, at a level comparable to that reported for p53. These predictions were further validated in a genome-wide manner by analyzing independent CRISPR screens and patients tumor data. Finally, we performed a new set of pooled and arrayed CRISPR screens to evaluate the competition between CRISPR-edited isogenic p53 WT and mutant cell lines, which further validated our predictions. In summary, our study systematically charts and points to the potential selection of specific cancer driver mutations during CRISPR-Cas9 gene editing.

cancer biology↗

bioRxiv2018

Regularization Improves the Robustness of Learned Sequence-to-Expression Models

Understanding of the gene regulatory activity of enhancers is a major problem in regulatory biology. The nascent field of sequence-to-expression modelling seeks to create quantitative models of gene expression based on regulatory DNA (cis) and cellular environmental (trans) contexts. All quantitative models are defined partially by numerical parameters, and it is common to fit these parameters to data provided by existing experimental results. However, the relative paucity of experimental data appropriate for this task, and lacunae in our knowledge of all components of the systems, results in problems often being under-specified, which in turn may lead to a situation where wildly different model parameterizations perform similarly well on training data. It may also lead to models being fit to the idiosyncrasies of the training data, without representing the more general process (overfitting).\n\nIn other contexts where parameter-fitting is performed, it is common to apply regularization to reduce overfitting. We systematically evaluated the efficacy of three types of regularization in improving the generalizability of trained sequence-to-expression models. The evaluation was performed in two types of cross-validation experiments: one training on D. melanogaster data and predicting on orthologous enhancers from related species, and the other cross-validating between four D. melanogaster neurogenic ectoderm enhancers, which are thought to be under control of the same transcription factors. We show that training with a combination of noise-injection, L1, and L2 regularization can drastically reduce overfitting and improve the generalizability of learned sequence-to-expression models. These results suggest that it may be possible to mitigate the tendency of sequence-to-expression models to overfit available data, thus improving predictive power and potentially resulting in models that provide better insight into underlying biological processes.

systems biology↗

bioRxiv2018

Inference of phenotype-relevant transcriptional regulatory networks elucidates cancer type-specific regulatory mechanisms in a pan-cancer study

Reconstruction of transcriptional regulatory networks (TRNs) is a powerful approach to unravel the gene expression programs involved in healthy and disease states of a cell. However, these networks are usually reconstructed independent of the phenotypic properties of the samples and therefore cannot identify regulatory mechanisms that are related to a phenotypic outcome of interest. In this study, we developed a new method called InPheRNo to identify phenotype-relevant transcriptional regulatory networks. This method is based on a probabilistic graphical model whose conditional probability distributions model the simultaneous effects of multiple transcription factors (TFs) on their target genes as well as the statistical relationship between target gene expression and phenotype. Extensive comparison of InPheRNo with related approaches using primary tumor samples of 18 cancer types from The Cancer Genome Atlas revealed that InPheRNo can accurately reconstruct cancer type-relevant TRNs and identify cancer driver TFs. In addition, survival analysis revealed that the activity level of TFs with many target genes could distinguish patients with good prognosis from those with poor prognosis.

bioinformatics↗

bioRxiv2018

A competence-regulated toxin-antitoxin system in Haemophilus influenzae

Natural competence allows bacteria to respond to environmental and nutritional cues by taking up free DNA from their surroundings, thus gaining nutrients and genetic information. In the Gram-negative bacterium Haemophilus influenae, the DNA uptake machinery is induced by the CRP and Sxy transcription factors in response to lack of preferred carbon sources and nucleotide precursors. Here we show that HI0659--which is absolutely required for DNA uptake-- encodes the antitoxin of a competence-regulated toxin-antitoxin operon ( toxTA), likely acquired by horizontal gene transfer from a Streptococcus species. Deletion of the toxin restores uptake to the antitoxin mutant. In addition to the expected Sxy-and CRP-dependent-competence promoter, transcript analysis using RNA-seq identified an internal antitoxin-repressed promoter whose transcription starts within toxT and will yield nonfunctional protein. We present evidence that the most likely effect of unopposed toxin expression is non-specific cleavage of mRNAs and arrest or death of competent cells in the culture, and we show that the toxin gene has been inactivated by deletion in many H. influenzae strains. We suggest that this competence-regulated toxin-antitoxin system may facilitate downregulation of protein synthesis and recycling of nucleotides under starvation conditions, or alternatively be a simple genetic parasite.

microbiology↗

bioRxiv2018

Evolutionary changes in DNA accessibility and sequence predict divergence of transcription factor binding and enhancer activity

Transcription factor (TF) binding is determined by sequence as well as chromatin accessibility. While the role of accessibility in shaping TF-binding landscapes is well recorded, its role in evolutionary divergence of TF binding, which in turn can alter cis-regulatory activities, is not well understood. In this work, we studied the evolution of genome-wide binding landscapes of five major transcription factors (TFs) in the core network of mesoderm specification, between D. melanogaster and D. virilis, and examined its relationship to accessibility and sequence-level changes. We generated chromatin accessibility data from three important stages of embryogenesis in both D. melanogaster and D. virilis, and recorded conservation and divergence patterns. We then used multi-variable models to correlate accessibility and sequence changes to TF binding divergence. We found that accessibility changes can in some cases, e.g., for the master regulator Twist and for earlier developmental stages, more accurately predict binding change than is possible using TF binding motif changes between orthologous enhancers. Accessibility changes also explain a significant portion of the co-divergence of TF pairs. We noted that accessibility and motif changes offer complementary views of the evolution of TF binding, and developed a combined model that captures the evolutionary data much more accurately than either view alone. Finally, we trained machine learning models to predict enhancer activity from TF binding, and used these functional models to argue that motif and accessibility-based predictors of TF binding change can substitute for experimentally measured binding change, for the purpose of predicting evolutionary changes in enhancer activity.

evolutionary biology↗

bioRxiv2018

An information theoretic treatment of sequence-to-expression modeling

Studying a genes regulatory mechanisms is a tedious process that involves identification of candidate regulators by transcription factor (TF) knockout or over-expression experiments, delineation of enhancers by reporter assays, and demonstration of direct TF influence by site mutagenesis, among other approaches. Such experiments are often chosen based on the biologists intuition, from several testable hypotheses. We pursue the goal of making this process systematic by using ideas from information theory to reason about experiments in gene regulation, in the hope of ultimately enabling rigorous experiment design strategies. For this, we make use of a state-of-the-art mathematical model of gene expression, which provides a way to formalize our current knowledge of cis- as well as trans-regulatory mechanisms of a gene. Ambiguities in such knowledge can be expressed as uncertainties in the model, which we capture formally by building an ensemble of plausible models that fit the existing data and defining a probability distribution over the ensemble. We then characterize the impact of a new experiment on our understanding of the genes regulation based on how the ensemble of plausible models and its probability distribution changes when challenged with results from that experiment. This allows us to assess the value of the experiment retroactively as the reduction in entropy of the distribution (information gain) resulting from the experiments results. We fully formalize this novel approach to reasoning about gene regulation experiments and use it to evaluate a variety of perturbation experiments on two developmental genes of D. melanogaster. We also provide objective and biologist-friendly descriptions of the information gained from each such experiment. The rigorously defined information theoretic approaches presented here can be used in the future to formulate systematic strategies for experiment design pertaining to studies of gene regulatory mechanisms.\n\nAuthor summaryIn-depth studies of gene regulatory mechanisms employ a variety of experimental approaches such as identifying a genes enhancer(s) and testing its variants through reporter assays, followed by transcription factor mis-expression or knockouts, site mutagenesis, etc. The biologist is often faced with the challenging problem of selecting the ideal next experiment to perform so that its results provide novel mechanistic insights, and has to rely on their intuition about what is currently known on the topic and which experiments may add to that knowledge. We seek to make this intuition-based process more systematic, by borrowing ideas from the mature statistical field of experiment design. Towards this goal, we use the language of mathematical models to formally describe what is known about a genes regulatory mechanisms, and how an experiments results enhance that knowledge. We use information theoretic ideas to assign a value to an experiment as well as explain objectively what is learned from that experiment. We demonstrate use of this novel approach on two extensively studied developmental genes in fruitfly. We expect our work to lead to systematic strategies for selecting the most informative experiments in a study of gene regulation.

systems biology↗

bioRxiv2018

Finding reliable phenotypes and detecting artefacts among in vivo and in vitro assays to characterize the refractory transcriptional activator Sxy (TfoX) in Escherichia coli

The Sxy (TfoX) protein is required for expression of a distinct subset of the genes regulated by the cAMP receptor protein (CRP) in the model organisms Escherichia coli, Haemophilus influenzae, and Vibrio cholerae. Genetic studies have established that CRP and Sxy co-activate transcription at gene promoters containing DNA binding sites called CRP-S sites. In contrast, CRP acts without Sxy at gene promoters containing canonical CRP-N sites, suggesting that Sxy makes physical contacts with CRP and/or DNA to assist in transcriptional activation at CRP-S promoters. Despite growing interest in Sxys activity as a transcription factor, Sxy remains poorly characterized due to a lack of reliable phenotypes in E. coli. Experiments are further hampered by growth inhibition and formation of inclusion bodies when Sxy is overexpressed. In this study we applied diverse phenotypic and molecular assays to test for postulated Sxy functions and interactions. Mutations in conserved regions of Sxy and truncations in the Sxy C-terminus abolish transcriptional activation of a CRP-S promoter, and a 37 amino acid truncation of the C-terminus relieves the growth inhibition normally caused by Sxy overexpression. Sxy was unable to augment weakened CRP interactions to restore carbon metabolism phenotypes. Bandshift analysis and chromatin pull-down assays of Sxy-CRP-DNA interactions yielded intriguing evidence of CRP-Sxy and Sxy-DNA physical interactions. However, despite the careful application of standard protein purification protocols and quality control steps for nickel affinity column purification, protein mass spectrometry revealed the enrichment of additional DNA-binding proteins in nickel column eluates, presenting a probable source of artefactual protein-protein and protein-DNA interaction results. These findings highlight the importance of extensive controls and phenotypic assays for the study of poorly characterized and recalcitrant proteins like Sxy.

microbiology↗