Biology subjects

Singh, A.

Publications and source records attributed to Singh, A..

31 records · Page 2Linked to original sources

bioRxiv2018

Lentiviral co-packaging mitigates the effects of intermolecular recombination and multiple integrations in pooled genetic screens

Lentiviral vectors are widely used for functional genomic screens, enabling efficient and stable transduction of target cells with libraries of genetic elements. Unfortunately, designs that rely on integrating multiple variable sequences, such as combinatorial perturbations or perturbations linked to barcodes, may be compromised by unintended consequences of lentiviral packaging. Intermolecular recombination between library elements and integration of multiple perturbations (even at limiting virus dilution) can negatively impact the sensitivity of pooled screens. Here, we describe a simple approach to prevent recombination between lentiviral vectors containing multiple linked variable elements, such as the recently reported CRISP-seq, Perturb-seq, and Mosaic-seq designs. We show that modifying the packaging protocol by diluting the perturbation library with a carrier plasmid increases the fraction of correct, single integrations from <60% to >90%, at the cost of reducing titer by 100-fold.

genomics↗

bioRxiv2018

TuBA: Tunable Biclustering Algorithm Reveals Clinically Relevant Tumor Transcriptional Profiles in Breast Cancer

BackgroundTraditional clustering approaches for gene expression data are not well adapted to address the complexity and heterogeneity of tumors, where small sets of genes may be aberrantly co-expressed in specific subsets of tumors. Biclustering algorithms that perform local clustering on subsets of genes and conditions help address this problem. We propose a graph-based Tunable Biclustering Algorithm (TuBA) based on a novel pairwise proximity measure, examining the relationship of samples at the extremes of genes expression profiles to identify similarly altered signatures. ResultsTuBAs predictions are consistent in 3,940 Breast Invasive Carcinoma (BRCA) samples from three independent sources, employing different technologies for measuring gene expression (RNASeq and Microarray). Over 60% of biclusters identified independently in each dataset had significant agreement in their gene sets, as well as similar clinical implications. About 50% of biclusters were enriched in the ER-/HER2- (or basal-like) subtype, while more than 50% were associated with transcriptionally active copy number changes. Biclusters representing gene co-expression patterns in stromal tissue were also identified in tumor specimens. ConclusionTuBA offers a simple biclustering method that can identify biologically relevant gene co-expression signatures not captured by traditional unsupervised clustering approaches. It complements biclustering approaches that are designed to identify constant or coherent submatrices in gene expression datasets, and outperforms them in identifying a multitude of altered transcriptional profiles that are associated with observed genomic heterogeneity of diseased states in breast cancer, both within and across tumor subtypes, a promising step in understanding disease heterogeneity, and a necessary first step in individualized therapy.

systems biology↗

bioRxiv2018

Synaptic transmission may provide an evolutionary benefit to HIV through modulation of latency

Transmission of HIV is known to occur by two mechanisms in vivo: the free virus pathway, where viral particles bud off an infected cell before attaching to an uninfected cell, and the cell-cell pathway, where infected cells form virological synapses through close contact with an uninfected cell. It has also been shown that HIV replication includes a positive feedback loop controlled by the viral protein Tat, which may act as a stochastic switch in determining whether an infected cell enters latency. In this paper, we introduce a simple mathematical model of HIV replication containing both the free virus and cell-cell pathways. Using this model, we demonstrate that the high multiplicity of infection in cell-cell transmission results in a suppression of latent infection, and that this modulation of latency through balancing the two transmission mechanisms can provide an evolutionary benefit to the virus. This benefit increases with decreasing overall viral fitness, which may provide a within-host evolutionary pressure toward more cell-cell transmission in late-stage HIV infection.

microbiology↗

bioRxiv2017

Interrelationship of photoperiod and feed utilization on growth and reproductive performance in the Red eyed orange molly (Poecilia sphenops)

Light is a major environmental factors that synchronize all life-stages of fish, from body growth to sexual maturation. The objective of this research is to enhance the growth and reproductive performance in the test fish, red eyed orange molly (Poecilia sphenops) exposed to standardized manipulated photoperiod. In present study, growth and gonadal development of the test fish with an average initial weight (0.52g) and an average total length (3.2cm) exposed to two photoperiods (18L:6D and 10L:14D) at constant light intensity (1500 lx) for a period of 60 days was investigated. The fish were fed with formulated feed twice a day as per 10% of body weight. During a long day photoperiod (18L:6D) significant increase in growth parameters such as, weight gain (2.2 {+/-} 0.04), feed conversion ratio (8.9 {+/-} 0.004) and specific growth rate (1.2 {+/-} 0% day-1) was observed. Mean gonadosomatic index (GSI) in female (30.4{+/-} 0.11) and male fish (2.0 {+/-} 0.17) was also significantly higher in long-day photoperiod followed by short day photoperiod (10L:14D). The results confirm that manipulated long-day photoperiod induced somatic growth and enhanced gonadal development in P. sphenops without causing any stress.\n\nSummaryThis work is novel to research field since photoperiodic effect on Poecilia sphenops, a live-bearer fish under artificial environmental conditions resulted in enhanced growth and reproductive performance with fry production.

zoology↗

bioRxiv2017

Joint regulation of growth and division timing drives size homeostasis in proliferating animal cells

How organisms maintain cell size homeostasis is a long-standing problem that remains unresolved, especially in multicellular organisms. Recent experiments in diverse animal cell types demonstrate that within a cell population the extent of growth and cellular proliferation (i.e., fitness) is low for small and large cells, but high at intermediate sizes. Here we use mathematical models to explore size-control strategies that drive such a non-monotonic fitness profile resulting in an optimal cell size. Our analysis reveals that if cell size grows exponentially or linearly over time, then fitness always varies monotonically with size irrespective of how timing of division is regulated. Furthermore, if the cell divides upon attaining a critical size (as in the Sizer or size-checkpoint model), then fitness always increases with size irrespective of how growth rate is regulated. These results show that while several size control models can maintain cell size homeostasis, they fail to predict the optimal cell size, and hence unable to explain why cells prefer a certain size. Interestingly, fitness maximization at an optimal size requires two key ingredients: 1) The growth rate decreases with increasing size for large enough cells; and 2) The cell size at the time of division is a function of the newborn size. The latter condition is consistent with the Adder paradigm for division control (division is triggered upon adding a fixed size from birth), or a Sizer-Adder combination. Consistent with theory, Jurkat T cell growth rates, as measured via oxygen consumption or mitochondrial activity, increase with size for small cells, but decrease with size for large cells. In summary, regulation of both growth and cell division timing is critical for size control in animal cells, and this joint-regulation leads to an optimal size where cellular fitness is maximized. Address inquires to A. Singh, E-mail: absingh@udel.edu.

systems biology↗

bioRxiv2017

Redox-Dependent Condensation Of Mycobacterial Genome By WhiB4

Oxidative stress response in bacteria is generally mediated through coordination between the regulators of oxidant-remediation systems (e.g. OxyR, SoxR) and nucleoid condensation (e.g. Dps, Fis). However, these genetic factors are either absent or rendered nonfunctional in the human pathogen Mycobacterium tuberculosis (Mtb). Therefore, how Mtb organizes genome architecture and regulates gene expression to counterbalance oxidative imbalance during infection is not known. Here, we report that an intracellular redox-sensor, WhiB4, dynamically links genome condensation and oxidative stress response in Mtb. Disruption of WhiB4 affects the expression of genes involved in maintaining redox homeostasis, central carbon metabolism (CCM), respiration, cell wall biogenesis, DNA repair and protein quality control under oxidative stress. Notably, disulfide-linked oligomerization of WhiB4 in response to oxidative stress activates the proteins ability to condense DNA in vitro and in vivo. Further, overexpression of WhiB4 led to hypercondensation of nucleoids, redox imbalance and increased susceptibility to oxidative stress, whereas WhiB4 disruption reversed this effect. In accordance with the findings in vitro, ChIP-Seq data demonstrated non-specific binding of WhiB4 to GC-rich regions of the Mtb genome. Lastly, data indicate that WhiB4 deletion affected the expression of only a fraction of genes preferentially bound by the protein, suggesting its indirect effect on gene expression. We propose that WhiB4 is a novel redox-dependent nucleoid condensing protein that structurally couples Mtbs response to oxidative stress with genome organization and transcription.\n\nSignificance StatementMycobacterium tuberculosis (Mtb) needs to adapt in response to oxidative stress encountered inside human phagocytes. In other bacteria, condensation state of nucleoids modulates gene expression to coordinate oxidative stress response. However, this relation remains elusive in Mtb. We performed molecular dissection of a mechanism controlled by an intracellular redox sensor, WhiB4, in organizing both chromosomal structure and selective expression of adaptive traits to counter oxidative stress in Mtb. Using high-resolution sequencing, transcriptomics, imaging, and redox biosensor, we describe how WhiB4 modulates nucleoid condensation, global gene expression, and redox-homeostasis. WhiB4 over-expression hypercondensed nucleoids and perturbed redox homeostasis whereas WhiB4 disruption had an opposite effect. Our study discovered an empirical role for WhiB4 in integrating redox signals with nucleoid condensation in Mtb.

microbiology↗

bioRxiv2017

High Cooperativity In Negative Feedback Can Amplify Noisy Gene Expression

Burst-like synthesis of protein is a significant source of cell-to-cell variability in protein levels. Negative feedback is a common example of a regulatory mechanism by which such stochasticity can be controlled. Here we consider a specific kind of negative feedback, which makes bursts smaller in the excess of protein. Increasing the strength of the feedback may lead to dramatically different outcomes depending on a key parameter, the noise load, which is defined as the squared coefficient of variation the protein exhibits in the absence of feedback. Combining stochastic simulation with asymptotic analysis, we identify a critical value of noise load: for noise loads smaller than critical, the coefficient of variation remains bounded with increasing feedback strength; contrastingly, if the noise load is larger than critical, the coefficient of variation diverges to infinity in the limit of ever greater feedback strengths. Interestingly, high-cooperativity feedbacks have lower critical noise loads, implying that low-cooperativity feedbacks in burst size can be preferable for noisy proteins. Finally, we discuss our findings in the context of previous results on the impact of negative feedback in burst size and burst frequency on gene-expression noise.

systems biology↗

bioRxiv2017

Modeling noise mechanisms in neuronal synaptic transmission

In the nervous system, communication occurs via synaptic transmission where signaling molecules (neurotransmitters) are released by the presynaptic neuron, and they influence electrical activity of another neuron (postsynaptic neuron). The inherent probabilistic release of neurotransmitters is a significant source of noise that critically impacts the timing of spikes (action potential) in the postsynaptic neuron. We develop a stochastic model that incorporates noise mechanisms in synaptic transmission, such as, random docking of neurotransmitter-filled vesicle to a finite number of docking sites, with each site having a probability of vesicle release upon arrival of an action potential. This random, burst-like release of neurotransmitters serves as an input to an integrate-and-fire model, where spikes in the postsynaptic neuron are triggered when its membrane potential reaches a critical threshold for the first time. We derive novel analytical results for the probability distribution function of spike timing, and systematically investigate how underlying model parameters and noise processes regulate variability in the inter-spike times. Interestingly, in some parameter regimes, independent arrivals of action potentials in the presynaptic neuron generate strong dependencies in the spike timing of the postsynaptic neuron. Finally, we argue that probabilistic release of neurotransmitters is not only a source of disturbance, but plays a beneficial role in synaptic information processing.

neuroscience↗

bioRxiv2017

mixOmics: an R package for ‘omics feature selection and multiple data integration

The advent of high throughput technologies has led to a wealth of publicly available omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a molecular signature) to explain or predict biological conditions, but mainly for a single type of omics. In addition, commonly used methods are univariate and consider each biological feature independently.\n\nWe introduce mixOmics, an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a system biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latest mixOmics integrative frameworks for the multivariate analyses of omics data available from the package.

bioinformatics↗

bioRxiv2017

Efficacy of the β-lactam\β-lactamase inhibitor combination is linked to WhiB4 mediated changes in redox physiology of Mycobacterium tuberculosis

AimsInhibition of {beta}-lactamase by clavulanate (Clav) sensitizes multi-and extensively drug-resistant Mycobacterium tuberculosis (Mtb) strains towards {beta}-lactams such as amoxicillin (Amox). However, the underlying mechanism of how Mtb responds to Amox-Clav combination (Augmentin; AG) is not characterized.\n\nResultsWe integrated global expression profiling with the protein-protein interaction landscape and generated a genome-scale network of Mtb in response to AG. In addition to specific targets (e.g., peptidoglycan biosynthesis and {beta}-lactamase), the response to AG was also centered on redox-balance, central carbon metabolism (CCM), and respiration in Mtb. We discovered that AG modulates superoxide levels, NADH/NAD+ balance and mycothiol redox potential (EMSH) of Mtb. Higher intra-mycobacterial EMSH potentiates mycobactericidal efficacy of AG, whereas lower EMSH induces tolerance. Further, Mtb responds to AG via a redox-sensitive transcription factor, WhiB4. Mtb{Delta}whiB4 displayed higher expression of genes involved in {beta}-lactam resistance along with those mediating respiration, CCM and redox balance. Moreimportantly, WhiB4 binds to the promoter regions and represses transcription of genes involved in {beta}-lactamase expression in a redox-dependent manner. Lastly, while Mtb{Delta}whiB4 maintained internal EMSH, exhibited greater {beta}-lactamase activity and displayed AG-tolerance, overexpression of WhiB4 induced oxidative shift in EMSH and repressed {beta}-lactamase activity to aggravate AG-mediated killing of drug-sensitive and -resistant strains of Mtb.\n\nInnovation and ConclusionsThis work demonstrate that efficacy of {beta}-lactam\\{beta}-lactamase inhibitor combination can be attenuated by elevating mycobacterial antioxidant capabilities and potentiated by impairing redox buffering capacity of Mtb. The functional linkage between {beta}-lactams, redox balance, and WhiB4 can be exploited to potentiate AG action against drug-resistant Mtb.

microbiology↗

bioRxiv2017

Noise suppression in cell-size control

Diverse cell types employ mechanisms to maintain size homeostasis and minimize aberrant fluctuations in cell size. It is well known that exponential cellular growth can drive unbounded intercellular variations in cell size, if the timing of cell division is size independent. Hence coupling of division timing to size is an essential feature of size control. We formulate a stochastic model, where exponential cellular growth is coupled with random cell division events, and the rate at which division events occur increases as a power function of cell size. Interestingly, in spite of nonlinearities in the stochastic dynamical model, statistical moments of the newborn cell size can be determined in closed form, providing fundamental limits to suppression of size fluctuations. In particular, formulas reveal that the magnitude of fluctuations in the newborn size is determined by the inverse of the size exponent in the division rate, and this relationship is independent of other model parameters, such as the growth rate. We further expand these results to consider randomness in the partitioning of mother cell size among daughters at the time of division. The sensitivity of newborn size fluctuations to partitioning noise is found to monotonically decrease, and approach a non-zero value, with increasing size exponent in the division rate. Finally, we discuss how our analytical results provide limits on noise control in commonly used models for cell size regulation.

systems biology↗

bioRxiv2017

Frequency-dependent response of Chromobacterium violaceum to sonic stimulation, and altered gene expression associated with enhanced violacein production at 300 Hz

Chromobacterium violaceum was subjected to sonic (100-2000 Hz) stimulation, and the effect on its cell yield and quorum sensing regulated pigment (violacein) production was investigated. Sound corresponding to the 300 Hz was found to promote (by 1.52 fold) violacein production the most, with only marginal impact on cell yield. Whole transcriptome analysis revealed that a total of 342 genes (i.e. 4.63% of whole genome) were significantly up-regulated in the sonic stimulated culture. Enhanced violacein production in the sound stimulated culture seems to have stemmed from enhanced expression of the genes involved in glucose metabolism through pentose phosphate pathway, resulting in increased availability of erythrose-4-phosphate, to be used for synthesis of tryptophan, the precursor for violacein synthesis. Multiple ribosomal subunit genes, enzyme coding genes, and those associated with secretion/transport were up-regulated owing to sonic stimulation. This study is a good demonstration of the ability of sound waves to alter bacterial metabolism.

microbiology↗

bioRxiv2016

RNAtor: an Android-based application for biologists to plan RNA sequencing experiments.

RNA sequencing (RNA-seq) is a powerful technology for identification of novel transcripts (coding, non-coding and splice variants), understanding of transcript structures and estimation of gene and/or allelic expression. There are specific challenges that biologists face in determining the number of replicates to use, total number of sequencing reads to generate for detecting marginally differentially expressed transcripts and the number of lanes in a sequencing flow cell to use for the production of right amount of information. Although past studies attempted answering some of these questions, there is a lack of accessible and biologist-friendly mobile applications to answer these questions. Keeping this in mind, we have developed RNAtor, a mobile application for Android platforms, to aid biologists in correctly designing their RNA-seq experiments. The recommendations from RNAtor are based on simulations and real data.\n\nAvailability and ImplementationThe Android version of RNAtor is available on Google Play Store and the code from GitHub (https://github.com/binaypanda/RNAtor).

bioinformatics↗