Biology subjects

Srinivasan, S.

Publications and source records attributed to Srinivasan, S..

138 records · Page 8Linked to original sources

bioRxiv2019

Complementing 16S rRNA gene amplicon sequencing with estimates of total bacterial load to infer absolute species concentrations in the vaginal microbiome

Whereas 16S rRNA gene amplicon sequencing quantifies relative abundances of bacterial taxa, variation in total bacterial load between samples restricts its ability to reflect absolute concentration of individual species. Quantitative PCR (qPCR) can quantify individual species, but it is not practical to develop a suite of qPCR assays for every bacterium present in a diverse sample. We analyzed 1320 samples from 20 women with a history of frequent bacterial vaginosis, who self-collected vaginal swabs daily over 60 days. We inferred bacterial concentrations by taking the product of species relative abundance (assessed by 16S rRNA gene amplicon sequencing) and total bacterial load (measured by broad-range 16S rRNA gene qPCR). Log10-converted inferred concentrations correlated with targeted qPCR (r = 0. 935, p<2.2e-16) for seven key bacterial species. The mean inferred concentration error varied across bacteria, with rarer bacterial vaginosis-associated bacteria associated with larger errors. 92% of errors >0.5 log10 occurred when relative abundance was <10%. Many errors occurred during early bacterial expansion or late contraction. When relative abundance of a species is >10%, inferred concentrations are reliable proxies for targeted qPCR. However, targeted qPCR is required to capture bacteria at low relative abundance, particularly with BV-associated bacteria during the early onset of bacterial vaginosis.

microbiology↗

bioRxiv2019

Cyanobacteria is uniquely enriched in the roots of grain amaranths

Plants and microbes have coexisted for millions of years and some have evolved mechanisms to achieve symbiosis driving positive selection. The bartering of chemicals produced by soil microbes and plants favour enrichment of certain types of bacteria near the roots that offers selective advantage to the plant under a given environment. Grain amaranths display certain important agronomic characteristics like C4 dicot, high protein and high lysine grains, resistance to biotic and abiotic stress, which can be translated to other crops. Considering an unusual collection of desirable traits shown by grain amaranths, it is worth pondering if symbiosis with bacteria has played any role in these traits. The objective of this study is to identify bacterial root microflora unique to grain amaranths. Here, by comparing rhizospheric and endophytic composition of 16S rRNA from various sections of roots from selected species under major plant orders including the three varieties of grain amaranths, we report that Cyanobacteria are uniquely enriched by grain amaranths. The diversity in OTUs among the Cyanobacteria also significantly increased among samples from amaranth species compared to negative control. This finding is also validated using root transcriptome of Amaranthus hypochondriacus, where we observe relative increase in Cyanobacterial population between day 15 to day 30 compared to other abundant phylum during this period.

plant biology↗

bioRxiv2019

A Hybrid Deep Clustering Approach for Robust Cell Type Profiling Using Single-cell RNA-seq Data

Single-cell RNA sequencing (scRNA-seq) is a recent technology that enables fine-grained discovery of cellular subtypes and specific cell states. It routinely uses machine learning methods, such as feature learning, clustering, and classification, to assist in uncovering novel information from scRNA-seq data. However, current methods are not well suited to deal with the substantial amounts of noise that is created by the experiments or the variation that occurs due to differences in the cells of the same type. Here, we develop a new hybrid approach, Deep Unsupervised Single-cell Clustering (DUSC), that integrates feature generation based on a deep learning architecture with a model-based clustering algorithm, to find a compact and informative representation of the single-cell transcriptomic data generating robust clusters. We also include a technique to estimate an efficient number of latent features in the deep learning model. Our method outperforms both classical and state-of-the-art feature learning and clustering methods, approaching the accuracy of supervised learning. The method is freely available to the community and will hopefully facilitate our understanding of the cellular atlas of living organisms as well as provide the means to improve patient diagnostics and treatment.

bioinformatics↗

bioRxiv2018

A conserved principle of glial organization in the paleocortex and neocortex

The organizational principles of glia remain largely unknown despite their vital role in nervous system function. Previous work has shown that the number of glia per unit volume of neocortex is constant across mammalian species. We hypothesize that the conservation of glia volume density within brain regions might be a governing principle of organization across species. To test this hypothesis, we used stereology, light microscopy, and data available in the literature to examine five brain regions: the cerebral cortex and four brain regions that differ from the cerebral cortex and each other - the anterior piriform cortex, the posterior piriform cortex, the entorhinal cortex, and the cerebellum. We discovered two orderly relationships: First, glia volume density within a brain region was constant across species, including humans, although it significantly differed between regions, suggesting that glia density might constitute a region-specific marker. Second, the ratio of glia to neuron increased with brain volume according to a [1/4] power law in the primate frontal cortex and the neocortex, the mammalian paleocortex, and the cerebellum. These relationships show that the development of glia and neurons are coupled, and suggest that what a neural circuit computes depends as much on its glial components as on its neurons. Main PointsO_LIThe volume density of glia (i.e., number of glia per unit volume) within a brain region is con-served across mammalian species including humans. C_LIO_LIThe ratio of glia to neuron increases with bigger brains. C_LIO_LIThe volume density of glia is significantly different across functionally and architecturally dif-ferent brain regions and could function as a region-specific marker. C_LIO_LIGlia obey scaling constraints that are different from scaling constraints for neurons. C_LI

neuroscience↗

bioRxiv2018

Scaling principles of distributed circuits

Distributed circuits like the olfactory cortex, hippocampus, and cerebellum contain sub-circuits whose inputs distribute their axons over the entire circuit creating a puzzle of how information is encoded. One method for approaching the puzzle is to view them as scalable systems. In scalable systems the quantitative relationship between circuit components is conserved across brain sizes, and by mapping circuit size to functional abilities - e.g. visual acuity in the visual circuit - scientists have explained information encoding. This approach has not been applied to anti-map circuits as their scalability is unknown. To address this gap in knowledge, we obtained quantitative descriptions of the olfactory bulb and piriform cortex in six mammals using stereology techniques and light microscopy. We found that the olfactory circuit is scalable as it satisfies three requirements of scalable systems. First, quantitative relationships between circuit components are conserved: the number piriform neurons n scales with bulb glomeruli g as n ~ g3/2. Second, the olfactory circuit has an invariant property: the average number of synapses between a bulb glomerulus and piriform neuron is one. Third, the olfactory circuit is symmorphic, i.e. olfactory ability improves with circuit size. Other distributed circuits with similar properties might also be scalable.

neuroscience↗

bioRxiv2018

Dynamics of spreading microbial swarms and films

Bacterial swarming and biofilm formation are collective multicellular phenomena through which diverse microbial species colonize and spread over water-permeable tissue. During both modes of surface translocation, fluid uptake and transport play a key role in shaping the overall morphology and spreading dynamics. Here, using Bacillus subtilis as our model experimental system, we develop a generalized two-phase thin-film model that couples hydrodynamics, mechanics, osmotic flux and nutrient transport to describe the expansion of both highly motile bacterial swarms, and sessile bacterial biofilms. We show that swarm expansion corresponds to steady-state solutions in a nutrient-rich, capillarity dominated regime. In contrast, biofilm colony growth is described by transient solutions associated with a nutrient-limited, extracellular polymer stress driven limit. We apply our unified framework to explain a range of recent experimental observations associated with the shape, form and dynamics of Escherichia coli and Bacillus subtilis swarms and biofilms. Our results demonstrate how hydrodynamics and transport serve as key physical constraints in regulating biological organization and function in microbial communities.

biophysics↗

bioRxiv2018

Hierarchical organization of the human cell from a cancer coessentiality network

Genetic interactions mediate the emergence of phenotype from genotype. Systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Systematic surveys of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains, and similarly implies shared biological function. We constructed a network of genes with correlated fitness profiles across 400 CRISPR knockout screens in cancer cell lines into a \"coessentiality network,\" with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of human gene function. Modules in the network are connected in a layered web that gives insight into the hierarchical organization of the cell.

systems biology↗

bioRxiv2018

A non-canonical role for dynamin-1 in regulating early stages of clathrin-mediated endocytosis in non-neuronal cells

Dynamin GTPases are best studied for their role in the terminal membrane fission process of clathrin-mediated endocytosis (CME); but, they have also been proposed to regulate earlier stages of CME. Although highly enriched in neurons, dynamin-1 (Dyn1) is, in fact, widely expressed along with dynamin-2 (Dyn2), but inactivated in non-neuronal cells via phosphorylation by GSK3{beta} kinase. Here, we study the differential, isoform-specific functions of Dyn1 and Dyn2 as regulators of CME. Endogenously expressed Dyn1 and Dyn2 were fluorescently-tagged either separately or together in two cell lines with contrasting Dyn1 expression levels. By quantitative live cell dual and triple-channel total internal reflection fluorescence microscopy we find that Dyn2 is more efficiently recruited to clathrin-coated pits (CCPs) than Dyn1, and that Dyn2, but not Dyn1 exhibits a burst of assembly prior to CCV formation. Activation of Dyn1 by acute inhibition of GSK3{beta} results in more rapid endocytosis of transferrin receptors, increased rates of CCP initiation and decreased CCP lifetimes, but did not significantly affect the extent of Dyn1 recruitment to CCPs. Thus, activated Dyn1 can regulate early stages of CME even when present at low, substoichiometric levels relative to Dyn2, and apparently without assembly into supramolecular collar-like structures. Under physiological conditions Dyn1 is activated downstream of EGF-receptor signaling to alter CCP dynamics. We identify sorting nexin 9 (SNX9) as a preferred binding partner to activated Dyn1 that is partially required for Dyn1-dependent effects on early stages of CCP maturation. Together, we decouple regulatory and scission functions of dynamins and report a scission-independent, isoformspecific regulatory role for Dyn1 in clathrin-mediated endocytosis.

cell biology↗

bioRxiv2017

Oxygen-sensing neurons reciprocally regulate peripheral lipid metabolism via neuropeptide signaling in Caenorhabditis elegans

The mechanisms by which the sensory environment instructs metabolic homeostasis remains poorly understood. In this report, we show that oxygen, a potent environmental signal, is an important regulator of whole body lipid metabolism. C. elegans oxygen-sensing neurons reciprocally regulate peripheral lipid metabolism under normoxia in the following way: under high oxygen and food absence, URX sensory neurons are activated, and stimulate fat loss in the intestine, the major metabolic organ for C. elegans. Under lower oxygen conditions or when food is present, the BAG sensory neurons respond by repressing the resting properties of the URX neurons. A genetic screen to identify modulators of this effect led to the identification of a BAG-neuron-specific neuropeptide called FLP-17, whose cognate receptor EGL-6 functions in URX neurons. Thus, BAG sensory neurons counterbalance the metabolic effect of tonically active URX neurons via neuropeptide communication. The combined regulatory actions of these neurons serve to precisely tune the rate and extent of fat loss, to the availability of food and oxygen.

neuroscience↗

bioRxiv2017

Accuracy, Reproducibility And Bias Of Next Generation Sequencing For Quantitative Small RNA Profiling: A Multiple Protocol Study Across Multiple Laboratories

Small RNA-seq is increasingly being used for profiling of small RNAs. Quantitative characteristics of long RNA-seq have been extensively described, but small RNA-seq involves fundamentally different methods for library preparation, with distinct protocols and technical variations that have not been fully and systematically studied. We report here the results of a study using common references (synthetic RNA pools of defined composition, as well as plasma-derived RNA) to evaluate the accuracy, reproducibility and bias of small RNA-seq library preparation for five distinct protocols and across nine different laboratories. We observed protocol-specific and sequence-specific bias, which was ameliorated using adapters for ligation with randomized end-nucleotides, and computational correction factors. Despite this technical bias, relative quantification using small RNA-seq was remarkably accurate and reproducible, even across multiple laboratories using different methods. These results provide strong evidence for the feasibility of reproducible cross-laboratory small RNA-seq studies, even those involving analysis of data generated using different protocols.

genomics↗

bioRxiv2017

Matrix Production In Bacillus subtilis Biofilms Is Localized To A Propagating Front

Bacterial biofilms are surface attached microbial communities encased in self-produced extracellular polymeric substances (EPS). Development of a mature biofilm must require coordinating cell differentiation and multicellular activity at scales much larger than the single microbial unit. Here we demonstrate that during development of Bacillus subtilis biofilms, EPS matrix production is localized to a front propagating at the periphery. We show that within the front, cells switch off matrix production and transition to sporulation after a set time delay of[~] 100 min. Correlation analyses of fluctuations in fluorescence reporter activity reveals that the front emerges from a pair of gene expression waves of matrix production and sporulation. The expression waves travel across cells that are immobilized in the biofilm matrix, in contrast to active cell migration or horizontal colony spreading. A single length scale and time scale couples the spatiotemporal propagation of both fronts throughout development, with the front displacement obeying a t1/2 scaling law. As a result, gene expression patterns within the advancing fronts collapse to self-similar expression profiles. Our results indicate that development of bacterial biofilms may be governed by universal wave-like dynamics localized to a self-similar front.

biophysics↗

bioRxiv2017

A quantitative description of the mouse piriform cortex

In this report, we provide a quantitative description for 2 aspects of the mouse piriform cortex. First, we give volumetric estimates of regions within the anterior and posterior piriform cortex. Second, we estimate the neuronal densities in each of these regions. From these two estimates, we calculate that the mouse piriform contains around half a million neurons equally distributed over the anterior and posterior piriform cortex. Quantitative descriptions such as these are important because they make it possible to construct realistic models and provide a constraint that theories of the olfactory circuit must fulfil. We show how quantitative descriptions can be useful for modelling by using our data to refine and improve earlier models of piriform cortex activity.

neuroscience↗