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Shah, S.

Publications and source records attributed to Shah, S..

15 recordsLinked to original sources

Mycobacterium tuberculosis inhibits autocrine type I interferon signaling to increase intracellular survival.

The type I interferons (IFN- and -{beta}) are important for host defense against viral infections. In contrast, their role in defense against non-viral pathogens is more ambiguous. Here we report that IFN-{beta}-signaling in macrophages has protective capacity against Mycobacterium tuberculosis (Mtb) via the increased production of nitric oxide. Furthermore, Mtb is able to inhibit IFN-/{beta}-receptor-mediated cell signaling and the transcription of 309 IFN-{beta} stimulated genes which includes genes associated with innate host cell defense. The molecular mechanism of inhibition by Mtb involves reduced phosphorylation of the IFNAR-associated protein kinases JAK1 and TYK2 leading to reduced phosphorylation of the downstream targets STAT1 and STAT2. Overall, our study supports the novel concept that Mtb evolved to inhibit autocrine type I IFN signaling in order to evade host defense mechanisms.

microbiology

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Essential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.

genomics

Dynamics and spatial genomics of the nascent transcriptome in single mESCs by intron seqFISH

Recent single cell experiments have revealed significant heterogeneities at the levels of transcription, DNA methylation and chromosome organization in individual cells. However, existing method of profiling mRNAs effectively averages transcriptional dynamics over many hours due to hours-long life time of most mRNAs. To capture the instantaneous activity of the transcriptome that reflects the rapid regulatory changes in cells, we imaged up to 10,421 nascent transcription active sites (TAS) in single mouse embryonic stem cells using seqFISH followed by multiple rounds of single molecule FISH and immunofluorescence. We observed that nascent transcription active sites appear to be distributed on the surface of individual chromosome territories and are dispersed throughout the nucleus. In addition, there are significant variability in the number of active transcription sites in single cells, representing globally more active to quiescent states. These states interconverted on the time scale of 2 hours as determined by a single cell pulse-chase experiment. Thus, transcriptome level seqFISH experiments provide an unprecedented spatial and dynamic view of chromosome organization and global nascent transcription activity in single cells.

systems biology

Decomposing spatially dependent and cell type specific contributions to cellular heterogeneity

Both the intrinsic regulatory network and spatial environment are contributors of cellular identity and result in cell state variations. However, their individual contributions remain poorly understood. Here we present a systematic approach to integrate both sequencing-and imaging-based single-cell transcriptomic profiles, thereby combining whole-transcriptomic and spatial information from these assays. We applied this approach to dissect the cell-type and spatial domain associated heterogeneity within the mouse visual cortex region. Our analysis identified distinct spatially associated signatures within glutamatergic and astrocyte cell compartments, indicating strong interactions between cells and their spatial environment. Using these signatures as a guide to analyze single cell RNAseq data, we identified previously unknown, but spatially associated subpopulations. As such, our integrated approach provides a powerful tool for dissecting the roles of intrinsic regulatory networks and spatial environment in the maintenance of cellular states.

bioinformatics

Integrated single-nucleotide and structural variation signatures of DNA-repair deficient human cancers

Mutation signatures in cancer genomes reflect endogenous and exogenous mutational processes, offering insights into tumour etiology, features for prognostic and biologic stratification and vulnerabilities to be exploited therapeutically. We present a novel machine learning formalism for improved signature inference, based on multi-modal correlated topic models (MMCTM) which can at once infer signatures from both single nucleotide and structural variation counts derived from cancer genome sequencing data. We exemplify the utility of our approach on two hormone driven, DNA repair deficient cancers: breast and ovary (n=755 cases total). Our results illuminate a new age-associated structural variation signature in breast cancer, and an independently identified substructure within homologous recombination deficient (HRD) tumours in breast and ovarian cancer. Together, our study emphasizes the importance of integrating multiple mutation modes for signature discovery and patient stratification, with biological and clinical implications for DNA repair deficient cancers.

cancer biology

Structural and functional influences of urban and rural childhoods on the medial prefrontal cortex

Global increases in urbanization have brought dramatic economic, environmental and social changes. However, less is understood about how these may influence disease-related brain mechanisms underlying epidemiological observations that urban birth and childhoods may increase the risk for neuropsychiatric disorders, including increased social stress and depression. In a genetically homogeneous Han Chinese adult population with divergent urban and rural birth and childhoods, we examined the structural and functional MRI neural correlates of childhood urbanicity, focusing on behavioral traits responding to social status threats, and polygenic risk for depression. Subjects with divergent rural and urban childhoods were similar in adult socioeconomic status and were genetically homogeneous. Urban childhoods, however, were associated with higher trait anxiety-depression. On structural MRI, urban childhoods were associated with relatively reduced medial prefrontal gray matter volumes. Functional medial prefrontal engagement under social status threat during working memory correlated with trait anxiety-depression in subjects with urban childhoods, to a significantly greater extent than in their rural counterparts, implicating an exaggerated physiological response to the threat context. Stress-associated medial prefrontal engagement also interacted with polygenic risk for depression, significantly predicting a differential response in individuals with urban but not rural childhoods. Developmental urbanicity thus differentially influenced medial prefrontal structure and function, at least in part through mechanisms associated with the neural processing of social status threat, trait anxiety, and genetic risk for depression, which may be factors in the association of urbanicity with adult psychopathology.\n\nSignificance StatementUrban living has been associated with social inequalities and stress. However, less is understood about the neural underpinnings by which these stressors affect disease risk, and in particular, genetic risk for depression. Leveraging urbanization in China, we studied adults with diverse urban and rural upbringings, who were genetically homogeneous and with similar current socioeconomic status, to isolate the effects of childhood urbanicity. At medial prefrontal cortex, a region critical for processing emotional stressors and social status, genetic risk for depression resulted in more deleterious function under stress in individuals with urban, but not rural childhoods. This implicates medial prefrontal cortexs critical role in brain development, integrating genetic mechanisms of stress and depression with the childhood environment.

neuroscience

Genome-wide discovery of somatic coding and regulatory variants in Diffuse Large B-cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer originating from mature B-cells. Many known driver mutations are over-represented in one of its two molecular subgroups, knowledge of which has aided in the development of therapeutics that target these features. The heterogeneity of DLBCL determined through prior genomic analysis suggests an incomplete understanding of its molecular aetiology, with a limited diversity of genetic events having thus far been attributed to the activated B-cell (ABC) subgroup. Through an integrative genomic analysis we uncovered genes and non-coding loci that are commonly mutated in DLBCL including putative regulatory sequences. We implicate recurrent mutations in the 3UTR of NFKBIZ as a novel mechanism of oncogene deregulation and found small amplifications associated with over-expression of FC-{gamma} receptor genes. These results inform on mechanisms of NF-{kappa}B pathway activation in ABC DLBCL and may reveal a high-risk population of patients that might not benefit from standard therapeutics.

genomics

MuClone: Somatic mutation detection and classification through probabilistic integration of clonal population structure

Accurate detection and classification of somatic single nucleotide variants (SNVs) is important in defining the clonal composition of human cancers. Existing tools are prone to miss low prevalence mutations and methods for classification of mutations into clonal groups across the whole genome are underdeveloped. Increasing interest in deciphering clonal population dynamics over multiple samples in time or anatomic space from the same patient is resulting in whole genome sequence (WGS) data from phylogenetically related samples. With the access to this data, we posited that injecting clonal structure information into the inference of mutations from multiple samples would improve mutation detection.\n\nWe developed MuClone: a novel statistical framework for simultaneous detection and classification of mutations across multiple tumour samples of a patient from whole genome or exome sequencing data. The key advance lies in incorporating prior knowledge about the cellular prevalences of clones to improve the performance of detecting mutations, particularly low prevalence mutations. We evaluated MuClone through synthetic and real data from spatially sampled ovarian cancers. Results support the hypothesis that clonal information improves sensitivity in detecting somatic mutations without compromising specificity. In addition, MuClone classifies mutations across whole genomes of multiple samples into biologically meaningful groups, providing additional phylogenetic insights and enhancing the study of WGS-derived clonal dynamics.

bioinformatics

EIF4A3 associated splicing and nonsense mediated decay defined by a systems analysis with novel small molecule inhibitors

Chemical biology approaches to the global functions of splicing reactions are gaining momentum, with an increasing repertoire of small molecule probes becoming available. Here we map the association of eIF4A3 with transcript expression, NMD and alternative splicing using a set of selective novel small molecule allosteric helicase inhibitors whose synthesis and chemical properties we have recently described. We show through analysis of dose monotonic transcriptional responses to increasing inhibition that both full length and NMD prone transcripts link eIF4A3 to normal functioning of cell division including chromosome segregation and cell cycle checkpoints, pointing to a conserved role of splicing and transcript quality processing in cell cycle functions. Cell cycle analysis and microscopy of inhibitor treated cells demonstrates chromosome mis-segregation and spindle defects, associated with a G2/M arrest, validating this observation. Through analysis of conserved alternative splicing patterns exhibiting monotonic responses, we find that eIF4A3 dependent alternative splicing involves exons that are longer and introns that are shorter than transcripts not modulated by eIF4A3. Moreover we observe conservation of over/under representation of RBP binding motif density over introns and exons implicated eIF4A3 modulated skipped exon and retained introns. The distribution of motif densities over 5 and branch intron sites and 5 exons is consistent with function of the exon-junction complex. Taken together we have defined a fraction of the transcrip-tome dependent on eIF4A3 functions and revealed a link between eIF4A3 and cell cycle regulation. The systems approach described here suggests additional avenues for therapeutic exploitation of eIF4A3 functions in cancer and related diseases.

genomics

Project Dhaka: Variational Autoencoder for Unmasking Tumor Heterogeneity from Single Cell Genomic Data

Intra-tumor heterogeneity is one of the key confounding factors in deciphering tumor evolution. Malignant cells will have variations in their gene expression, copy numbers, and mutation even when coming from a single tumor. Single cell sequencing of tumor cells is of paramount importance for unmasking the underlying the tumor heterogeneity. However extracting features from the single cell genomic data coherent with the underlying biology is computationally challenging, given the extremely noisy and sparse nature of the data. Here we are proposing Dhaka a variational autoencoder based single cell analysis tool to transform genomic data to a latent encoded feature space that is more efficient in differentiating between the hidden tumor subpopulations. This technique is generalized across different types of genomic data such as copy number variation from DNA sequencing and gene expression data from RNA sequencing. We have tested the method on two gene expression datasets having 4K to 6K tumor cells and two copy number variation datasets having 250 to 260 tumor cells. Analysis of the encoded feature space revealed sub-populations of cells bearing distinct genomic signatures and the evolutionary relationship between them, which other existing feature transformation methods like t-SNE and PCA fail to do.

genomics

Preparation of H-Ras GTPase conjugated to lipid nanodiscs for NMR spectroscopy

Ras GTPase is a peripheral membrane protein central to cellular signaling of growth and proliferation. Membrane attachment is critical for a range of Ras activities, therefore, ability to make faithful in-vitro samples of a mem-brane-bound Ras for detailed biophysical studies is a highly desirable goal. In this manuscript, we are describing preparation of a large-scale sample of isotopically labeled H-Ras conjugated to lipid nanodiscs. We demonstrate that the Ras-nanodisc sample is fairly stable to allow for a range of Nuclear Magnetic Resonance (NMR) and other biophysical measurements. The need to achieve a homogeneous protein-nanodisc ratio is also emphasized.

biophysics

Identification of 55,000 Replicated DNA Methylation QTL

DNA methylation plays an important role in the regulation of transcription. Genetic control of DNA methylation is a potential candidate for explaining the many identified SNP associations with disease that are not found in coding regions. We replicated 52,916 cis and 2,025 trans DNA methylation quantitative trait loci (mQTL) using methylation measured on Illumina HumanMethylation450 arrays in the Brisbane Systems Genetics Study (n=614 from 177 families) and the Lothian Birth Cohorts of 1921 and 1936 (combined n = 1366). The trans mQTL SNPs were found to be over-represented in 1Mbp subtelomeric regions, and on chromosomes 16 and 19. There was a significant increase in trans mQTL DNA methylation sites in upstream and 5 UTR regions. No association was observed between either the SNPs or DNA methylation sites of trans mQTL and telomere length. The genetic heritability of a number of complex traits and diseases was partitioned into components due to mQTL and the remainder of the genome. Significant enrichment was observed for height (p = 2.1x10-10), ulcerative colitis (p = 2x10-5), Crohns disease (p = 6x10-8) and coronary artery disease (p = 5.5x10-6) when compared to a random sample of SNPs with matched minor allele frequency, although this enrichment is explained by the genomic location of the mQTL SNPs.

genomics

Spatial distribution of extensively drug-resistant tuberculosis (XDR-TB) patients in KwaZulu-Natal, South Africa

BackgroundKwaZulu-Natal province, South Africa, has among the highest burden of XDR-TB worldwide with the majority of cases occurring due to transmission. Poor access to health facilities can be a barrier to timely diagnosis and treatment of TB, which can contribute to ongoing transmission. We sought to determine the geographic distribution of XDR-TB patients and proximity to health facilities in KwaZulu-Natal.\n\nMethodsWe recruited adults and children with XDR-TB diagnosed in KwaZulu-Natal. We calculated distance and time from participants home to the closest hospital or clinic, as well as to the actual facility that diagnosed XDR-TB, using tools within ArcGIS Network analyst. Speed of travel was assigned to road classes based on Department of Transport regulations. Results were compared to guidelines for the provision of social facilities in South Africa: 5km to a clinic and 30km to a hospital.\n\nResultsDuring 2011-2014, 1027 new XDR-TB cases were diagnosed throughout all 11 districts of KwaZulu-Natal, of whom 404 (39%) were enrolled and had geospatial data collected. Participants would have had to travel a mean distance of 2.9 km (CI 95%: 1.8-4.1) to the nearest clinic and 17.6 km (CI 95%: 11.4-23.8) to the nearest hospital. Actual distances that participants travelled to the health facility that diagnosed XDR-TB ranged from <10 km (n=143, 36%) to >50 km (n=109, 27%). The majority (77%) of participants travelled farther than the recommended distance to a clinic (5 km) and 39% travelled farther than the recommended distance to a hospital (30 km). Nearly half (46%) of participants were diagnosed at a health facility in eThekwini district, of whom, 36% resided outside the Durban metropolitan area.\n\nConclusionsXDR-TB cases are widely distributed throughout KwaZulu-Natal province with a denser focus in eThekwini district. Patients travelled long distances to the health facility where they were diagnosed with XDR-TB, suggesting a potential role for migration or transportation in the XDR-TB epidemic.

epidemiology

Multiplexed dynamic imaging of genomic loci in single cells by combined CRISPR imaging and DNA sequential FISH

Visualization of chromosome dynamics allows the investigation of spatiotemporal chromatin organization and its role in gene regulation and other cellular processes. However, current approaches to label multiple genomic loci in live cells have a fundamental limitation in the number of loci that can be labelled and uniquely identified. Here we describe an approach we call \"track first and identify later\" for multiplexed visualization of chromosome dynamics by combining two techniques: CRISPR labeling and DNA sequential fluorescence in situ hybridization (DNA seqFISH). Our approach first labels and tracks chromosomal loci in live cells with the CRISPR system, then barcodes those loci by DNA seqFISH in fixed cells and resolves their identities. We demonstrate our approach by tracking telomere dynamics, identifying 12 unique subtelomeric regions with variable detection efficiencies, and tracking back the telomere dynamics of respective chromosomes in mouse embryonic stem cells.

systems biology

Enhancing Knowledge Discovery from Cancer Genomics Data with Galaxy

We present a collection of Galaxy tools representing many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We implemented methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability on cloud-based infrastructure and commodity hardware. Some tools represents extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate several of these to perform some standard data integration and visualization tasks are demonstrated on a cohort of 96 diffuse large B-cell lymphomas, enabling the discovery of multiple candidate lymphoma-related genes that have not been reported previously.

genomics