Biology subjects

Nair, A.

Publications and source records attributed to Nair, A..

9 recordsLinked to original sources

bioRxiv2018

The first draft genomes of the ant Formica exsecta, and its Wolbachia endosymbiont reveal extensive gene transfer from endosymbiont to host.

The wood ant Formica exsecta (Formicidae; Hymenoptera), is a common ant species throughout the Palearctic region. The species is a well established model for studies of ecological characteristics and evolutionary conflict. In this study, we sequenced and assembled draft genomes for Formica exsecta and its endosymbiont Wolbachia. The draft F. exsecta genome is 277.7 Mb long; we identify 13,767 protein coding genes for which we provide gene ontology, and protein domain annotations. This is also the first report of a Wolbachia genome from ants, and provides insights into the phylogenetic position of this endosymbiont. We also identified multiple horizontal gene transfer events (HGTs) from Wolbachia to F. exsecta. Some of these HGTs have also occurred in parallel in multiple other insect genomes, highlighting the extent of HGTs in eukaryotes. We expect that the F. exsecta genome will be valuable resource in further exploration of the molecular basis of the evolution of social organization.

genomics↗

bioRxiv2018

Quantitative modelling explains distinct STAT1 and STAT3 activation dynamics in response to both IFNγ and IL-10 stimuli and predicts emergence of reciprocal signalling at the level of single cells

IFN{gamma} and IL10 pathways elicit functionally opposing cell fates, however, these two stimuli activate common transcription factors like STAT1 and STAT3 (S/1/3). How the two stimuli regulate the dynamics of S/1/3 activation remains less understood. Here, we experimentally measured the signaling dynamics of S/1/3 in response to IFN{gamma} and IL10 and found that STAT3, in particular, exhibits a bell-shaped response to both stimuli with maximal activation in an intermediate dose. We built a mathematical model, which quantitatively captured the S/1/3 dynamics and by model analysis, we identified the primary regulators controlling the bell-shaped STAT3 responses in both pathways. As the STATs are activated in response to both stimuli, in a scenario when cells are subjected to co-stimulation of IFN{gamma} and IL10, an interpathway competition to activate the common substrate is plausible. Additionally, a strong transcriptional induction of SOCS1 (a negative regulator of IFN{gamma} pathway) was observed upon IL10 stimulation, suggesting that IL10 pathway can potentially inhibit the IFN{gamma} pathway via SOCS1 induction. To quantitatively understand the S/1/3 responses to co-stimulation we next simulated the same which predicted STAT3 activation and SOCS1 induction dynamics would robustly remain IL10 driven. Subsequent experiments validated the model predictions. Further, the model analysis identified the primary regulators controlling the robustness of IL10-STAT3 axis in co-stimulation. Together, our data-driven model quantitatively captured the dynamics of the STATs in response to both pro (IFN{gamma}) and anti (IL10)-inflammatory stimuli and identifies distinct regulatory elements controlling STAT3 signaling in individual and co-stimulation conditions.

systems biology↗

bioRxiv2018

Molecular Complexes for Effective Inhibition of Tau Aggregation

Tau is an axonal protein known to form abnormal aggregates and is the biomarker of Alzheimers disease. Metal-based therapeutics for inhibition of Tau aggregation is limited and rarely reported in the contemporary science. Here, the first example is reported of a rationally designed molecular cobalt(II)-complexes for effective inhibition of Tau and disaggregation of preformed Tau fibrils. The mechanistic studies revealed that the prevention of Tau aggregation by CBMCs is concentration-dependent and Tau seldom exhibits conformational changes. Interestingly, CBMCs play a dual role by causing disassembly of preformed aggregates as well as complete Tau inhibition. We believe that this unprecedented finding by the newly developed molecular complexes has a potential to lead to developing innovative metal-based therapeutics for Alzheimers disease.

neuroscience↗

bioRxiv2018

Host dietary specialization and neutral assembly shape gut bacterial communities of wild dragonflies

Host-associated gut microbial communities can have large impacts on host ecology and evolution, and are typically shaped by host taxonomy and diet. Different host species often harbor distinct microbial communities, potentially because (1) host dietary specialization determines microbial colonization, (2) host-specific selection acts on diet-acquired microbiota, and (3) a combination of both processes. While the first possibility involves passive community structuring, the other two may arise from a functional association and should produce stable microbial communities. However, these alternatives have rarely been tested in wild host populations. We used 16S rRNA amplicon sequencing to characterize the gut bacterial communities of six dragonfly species collected across multiple seasons and locations. We found that variation in bacterial community composition was predominantly explained by sampling season and location, and secondarily by host species. To distinguish the role of host dietary specialization and host-imposed selection, we used insect-specific primers to identify prey in the gut contents of three focal dragonfly species. We found that these dragonflies - considered to be generalist predators - consumed distinct prey, with seasonal diet variation. Together, the patterns of host dietary specialization and spatial and temporal variation suggest a strong role of passive processes in shaping the gut bacterial community. Indeed, the abundance and distribution of ~76% of the bacterial community members were consistent with neutral community assembly. Our results contradict the pervasive expectation that host-imposed selection shapes gut microbial communities, and highlight the importance of joint analyses of variation in host diet and gut microbial communities of natural host populations.

evolutionary biology↗

bioRxiv2018

Dynein catch bond as a mediator of codependent bidirectional cellular transport

Intracellular bidirectional transport of cargo on Microtubule filaments is achieved by the collective action of oppositely directed dynein and kinesin motors. Experiments have found that in certain cases, inhibiting the activity of one type of motor results in an overall decline in the motility of the cellular cargo in both directions. This counter-intuitive observation, referred to as paradox of codependence is inconsistent with the existing paradigm of a mechanistic tug-of-war between oppositely directed motors. Unlike kinesin, dynein motors exhibit catchbonding, wherein the unbinding rates of these motors decrease with increasing force on them. Incorporating this catchbonding behavior of dynein in a theoretical model, we show that the functional divergence of the two motors species manifests itself as an internal regulatory mechanism and provides a plausible resolution of the paradox of codependence.

biophysics↗

bioRxiv2017

Transcriptomes of major renal collecting-duct cell types in mouse identified by single-cell RNA-Seq

Prior RNA sequencing (RNA-Seq) studies have identified complete transcriptomes for most renal epithelial cell types. The exceptions are the cell types that make up the renal collecting duct, namely intercalated cells (ICs) and principal cells (PCs), which account for only a small fraction of the kidney mass, but play critical physiological roles in the regulation of blood pressure, extracellular fluid volume and extracellular fluid composition. To enrich these cell types, we used fluorescence-activated cell sorting (FACS) that employed well established lectin cell surface markers for PCs and type B ICs, as well as a newly identified cell surface marker for type A ICs, viz. c-Kit. Single-cell RNA-Seq using the 1C- and PC-enriched populations as input enabled identification of complete transcriptomes of A-ICs, B-ICs and PCs. The data were used to create a freely-accessible online gene-expression database for collecting duct cells. This database allowed identification of genes that are selectively expressed in each cell type including cell-surface receptors, transcription factors, transporters and secreted proteins. The analysis also identified a small fraction of hybrid cells expressing both aquapor{inverted exclamation}n-2 and either anion exchanger 1 or pendrin transcripts. In many cases, mRNAs for receptors and their ligands were identified in different cells (e.g. Notch2 chiefly in PCs vs Jag1 chiefly in ICs) suggesting signaling crosstalk among the three cell types. The identified patterns of gene expression among the three types of collecting duct cells provide a foundation for understanding physiological regulation and pathophysiology in the renal collecting duct.\n\nSIGNIFICANCE STATEMENTA long-term goal in mammalian biology is to identify the genes expressed in every cell type of the body. In kidney, the expressed genes (\"transcriptome\") of all epithelial cell types have already been identified with the exception of the cells that make up the renal collecting duct, responsible for regulation of blood pressure and body fluid composition. Here, a technique called \"single-cell RNA-Seq\" was used in mouse to identify transcriptomes for the major collecting-duct cell types: type A intercalated cells, type B intercalated cells and principal cells. The information was used to create a publicly-accessible online resource. The data allowed identification of genes that are selectively expressed in each cell type, informative for cell-level understanding of physiology and pathophysiology.

physiology↗

bioRxiv2017

CRISPRi is not strand-specific and redefines the transcriptional landscape

CRISPRi, an adapted CRISPR-Cas9 system, is proposed to act as a strand-specific roadblock to repress transcription in eukaryotic cells using guide RNAs (sgRNAs) to target catalytically inactive Cas9 (dCas9) and offers an alternative to genetic interventions for studying pervasive antisense transcription. Here we successfully use click chemistry to construct DNA templates for sgRNA expression and show, rather than acting simply as a roadblock, binding of sgRNA/dCas9 creates an environment that is permissive for transcription initiation and termination, thus generating novel sense and antisense transcripts. At HMS2 in Saccharomyces cerevisiae, sgRNA/dCas9 targeting to the non-template strand results in antisense transcription termination, premature termination of a proportion of sense transcripts and initiation of a novel antisense transcript downstream of the sgRNA/dCas9 binding site. This redefinition of the transcriptional landscape by CRISPRi demonstrates that it is not strand-specific and highlights the controls and locus understanding required to properly interpret results from CRISPRi interventions.

genetics↗

bioRxiv2017

Post-inference Methods Of Prior Knowledge Incorporation In Gene Regulatory Network Inference

The regulatory interactions in a cell control cellular response to environmental and genetic perturbations. Gene regulatory network (GRN) inference from high-throughput gene expression data helps to identify unknown regulatory interactions in a cell. One of the main challenges in the GRN inference is to identify complex biological interactions from the limited information contained in the gene expression data. Using prior biological knowledge, in addition to the gene expression data, is a common method to overcome this challenge. However, only a few GRN inference methods can inherently incorporate the prior knowledge and these methods are also not among the best-ranked in benchmarking studies.\n\nWe propose to incorporate the prior knowledge after the GRN inference so that any inference method can be used. Two algorithms have been developed and tested on the well studied Escherichia coli, yeast, and realistic in silico networks. Their accuracy is higher than the best-ranking method in the latest community-wide benchmarking study. Further, one of the algorithms identifies and removes wrong interactions predicted by the inference methods. With half of the available prior knowledge of interactions, around 970 additional correct edges were obtained and 1300 wrong interactions were removed. Moreover, the limitation that only a few GRN inference methods can incorporate the prior knowledge is overcome. Therefore, a post-inference method of incorporating the prior knowledge improves accuracy, removes wrong edges, and overcomes the limitation of GRN inference methods.

systems biology↗

bioRxiv2017

RegCyanoDB: a database of cyanobacterial regulatory interactions

BackgroundCyanobacteria are photoautotrophic organisms with environmental, evolutionary, and industrial importance. Knowledge of its regulatory interactions are important to predict, optimise, and engineer their characteristics. However, at present, very few of their regulatory interactions are known. The regulatory interactions are known only for a few model organisms such as Escherichia coli due to technical and economical constraints, which are unlikely to change soon. Thus, mapping of regulatory interactions from well-studied organisms to less-studied organisms by using computational techniques is widely used. Reverse Best Hit (RBH), with appropriate algorithm parameters, is a simple and efficient method for detecting functional homologs.\n\nDescriptionWe predict the regulatory interactions in 30 strains of cyanobacteria using the known regulatory interactions from the best-studied organism, E. coli. RBH method with appropriate parameters is used to identify the functional homologs. An interaction is mapped to a cyanobacterial strain if functional homologs exist for a known transcription factor and its target gene. The confidence of the detected homologs and interactions are also provided. Since RBH is a conservative method, homolog-grouping is performed to recover lost putative interactions. A database of the predicted interactions from all the 30 strains of cyanobacteria is constructed.\n\nConclusionRegcyanoDB contains 20,280 interactions with confidence levels for 30 cyanobacterial strains. The predicted regulatory interactions exhibit a scale free network topology as observed in model organisms. The interacting genes in E. coli and cyanobacteria are mostly found to have the same gene annotation. This database can be used for posing novel hypotheses and validation studies in wet-lab and computational domains.\n\nThe database is available at http://www.che.iitb.ac.in/grn/RegCyanoDB/

bioinformatics↗