Biology subjects

Krishna, S.

Publications and source records attributed to Krishna, S..

8 recordsLinked to original sources

bioRxiv2018

Multifunctional CRISPR/Cas9 with engineered immunosilenced human T cell epitopes

The application of Cas9 for genetic and epigenetic therapies in humans raises concerns over immunogenicity of this foreign protein. We report pre-existing human CD8+ T cell immunity to Streptococcus pyogenes Cas9 in the majority of healthy individuals screened. In a proof-of-principle study, we demonstrate that Cas9 protein can be modified to eliminate immunodominant epitopes through targeted mutation while preserving its function and specificity.

immunology↗

bioRxiv2017

A Suv39H1-low chromatin state drives migratory cell populations in cervical cancer

The emergence of migratory cell populations within tumours represents a critical early stage during cancer metastasis. We have previously reported one such population, marked by CD66, in cervical cancers. It is unclear what broad mechanisms regulate such migratory populations. Here, we describe the role of a Suv39H1-low heterochromatin state as a driver of cervical cancer migratory populations. Cervical cancer cells sorted based on migratory ability in vitro show low Suv39H1, and Suv39H1 knockdown enhances cell migration. Histopathology shows the emergence of migratory Suv39H1low populations in advanced carcinoma progression. Meta-analysis of data from The Cancer Genome Atlas (TCGA) reveals that Suv39H1-low tumours show migration and CD66 expression signatures, and correlate with lower patient survival. Lastly, genome-wide profiling of migrated populations using RNA-Seq and H3K9me3 ChIP-Seq reveals Suv39H1-linked transcriptome alterations and a broad loss of H3K9me3, suggesting an increase in chromatin plasticity in migrated populations. The understanding of such chromatin based regulation in migratory populations may prove valuable in efforts to develop anti-metastatic strategies.

cancer biology↗

bioRxiv2017

A minimal "push-pull" bistability model explains oscillations between quiescent and proliferative cell states.

A minimal model for oscillating between quiescent and growth/proliferation states, dependent on the availability of a central metabolic resource, is presented. From the yeast metabolic cycles (YMCs), metabolic oscillations in oxygen consumption are represented as transitions between quiescent and growth states. We consider metabolic resource availability, growth rates, and switching rates (between states) to model a relaxation oscillator explaining transitions between these states. This frustrated bistability model reveals a required communication between the metabolic resource that determines oscillations, and the quiescent and growth state cells. Cells in each state reflect memory, or hysteresis of their current state, and \"push-pull\" cells from the other state. Finally, a parsimonious argument is made for a specific central metabolite as the controller of switching between quiescence and growth states. We discuss how an oscillator built around the availability of such a metabolic resource is sufficient to generally regulate oscillations between growth and quiescence, through committed transitions.

systems biology↗

bioRxiv2017

Complete assembly of a dengue virus type 3 genome from a recent genotype III clade by metagenomic sequencing of serum

BackgroundMosquito-borne flaviviruses causing diseases such as dengue and Japanese encephalitis are devastating, particularly in the tropics. Although, multiple flaviviruses are known to co-circulate in India, when a patient presents with febrile illness, testing is usually limited to specific pathogens. Unbiased metagenomic sequencing of febrile cases can reveal the presence of multiple pathogens and provide complete genome information. Sequence information, a cornerstone for tracing virus evolution, is relevant for the design of vaccines and therapeutics. In order to assess the usefulness of unbiased metagenomic sequencing for the identification of viruses associated with febrile illness, we sequenced serum from four individuals and plasma from one individual, all hospitalized at a tertiary care centre in South India with severe or prolonged febrile illnesses, together with one healthy control in 2014.\n\nResultsWe identified and assembled a complete dengue virus type 3 (DENV3) sequence from the serum of a case classified as severe dengue. We also found a small number of Japanese encephalitis virus (JEV) sequences in the serum of two adults with febrile illness, including the one who had dengue. Phylogenetic analysis of the dengue sequence indicates that it belongs to a predominantly Asian, DENV3, genotype III clade. It had an estimated divergence time of 13.86 years (95% Highest Posterior Densities 12.94 - 14.83 years) with the closest Indian strain. Amino acid substitutions were present throughout the sequenced genome, including 11 substitutions in the antigenic envelope protein compared to the strain used for the development of the first commercial dengue vaccine. Of these one substitution (E361D) was unique and six were in critical antigenic sites.\n\nConclusionsWe demonstrate that both genome assembly and detection of a low number of viral sequences are possible by unbiased sequencing of clinical material. Complete dengue virus sequence analysis places the sequenced genome in a recent, predominantly Asian clade within genotype III of DENV3. The detection of JEV, an agent not routinely tested in febrile illness in India, warrants further analysis and highlights the need to study co-circulating flaviviruses in parallel.

microbiology↗

bioRxiv2017

Evidence of sinks and sources in the PLC activated PIP2 cycle

In many eukaryotic signalling cascades, receptor mediated phospholipase C (PLC) activity triggers phosphatidylinositol 4,5 bisphosphate (PIP2) hydrolysis leading to information transfer in cells. Coupled with PLC activation is a sequence of reactions spread across multiple compartments by which PIP2 is resynthesized, a process essential to maintain PIP2 levels and support sustained PLC signalling. The biochemical strategies to co-ordinate these reactions and support PIP2 levels have remained poorly understood. In particular, the question of whether the PIP2 cycle is a closed cycle with no net addition or loss of metabolites has not been addressed. Using mathematical modelling approaches, we find that a closed PIP2 cycle cannot explain experimentally observed changes in the metabolic intermediates when changing enzyme activities in the PIP2 cycle. Thus, we propose that the PIP2 cycle likely includes at least one metabolic source and one sink whose net activity results in the experimentally observed regulation of this key signalling pathway.

biophysics↗

bioRxiv2017

Dynamic expression of tRNA-derived small RNAs define cellular states

Transfer RNA (tRNA)-derived small RNAs (tsRNAs) have recently emerged as important regulators of protein translation and shown to have diverse biological functions. However, the underlying cellular and molecular mechanisms of tsRNA function in the context of dynamic cell-state transitions remain unclear. Here we report the identification of a set of tsRNAs upregulated in differentiating mouse embryonic stem cells (mESCs). Mechanistic analyses revealed primary functions of tsRNAs in regulating polysome assembly and translation. Notably, interactome studies with differentially-enriched tsRNAs revealed a switch in associations with effector RNPs and target mRNAs in different cell-states. We also demonstrate that a specific pool of tsRNAs can interact with Igf2bp1, an RNA-binding protein, to influence the expression of the pluripotency-promoting factor-c-Myc, thereby providing evidence for tsRNAs in modulating stem cell-states in mESCs. Finally, tsRNA expression analyses in distinct, heterologous cell and tissue models of stem/transformed versus differentiated/normal states reveal that tsRNA-mediated regulation of protein translation may represent a global biological phenomenon associated with cell-state transitions.\n\nOne Sentence SummaryIdentification and functional characterization of tRNA-derived small RNAs (tsRNAs) in cell state switches.

molecular biology↗

bioRxiv2017

Daam2 Driven Degradation Of VHL Promotes Gliomagenesis

Von Hippel-Landau (VHL) protein is a potent tumor suppressor regulating numerous pathways that drive cancer, but mutations in VHL are restricted to limited subsets of malignancies. Here we identified a novel mechanism for VHL suppression in tumors that do not have inactivating mutations. Using developmental processes to uncover new pathways contributing to tumorigenesis, we found that Daam2 promotes glioma formation. Protein expression screening identified an inverse correlation between Daam2 and VHL expression across a host of cancers, including glioma. These in silico insights guided corroborating functional studies, which revealed that Daam2 promotes tumorigenesis by suppressing VHL expression. Furthermore, biochemical analyses demonstrate that Daam2 associates with VHL and facilitates its ubiquitination and degradation. Together, these studies are the first to define an upstream mechanism regulating VHL suppression in cancer and describe the role of Daam2 in tumorigenesis.\n\nStatement of SignificanceWe found that the glial developmental factor Daam2 promotes glioma tumorigenesis by suppressing VHL expression. Our studies show, for the first time, a regulatory mechanism that operates upstream of VHL in cancer and provides an explanation for how VHL expression is extinguished in tumors that do not have inactivating mutations.

cancer biology↗

bioRxiv2017

Detection Of Cooperatively Bound Transcription Factor Pairs Using ChIP-seq Peak Intensities And Expectation Maximization

Transcription factors (TFs) often work cooperatively, where the binding of one TF to DNA enhances the binding affinity of a second TF to a nearby location. Such cooperative binding is important for activating gene expression from promoters and enhancers in both prokaryotic and eukaryotic cells. Existing methods to detect cooperative binding of a TF pair rely on analyzing the sequence that is bound. We propose a method that uses, instead, only ChIP-seq peak intensities and an expectation maximization (CPI-EM) algorithm. We validate our method using ChIP-seq data from cells where one of a pair of TFs under consideration has been genetically knocked out. Our algorithm relies on our observation that cooperative TF-TF binding is correlated with weak binding of one of the TFs, which we demonstrate in a variety of cell types, including E. coli, S. cerevisiae and M. musculus cells. We show that this method performs significantly better than a predictor based only on the ChIP-seq peak distance of the TFs under consideration. This suggests that peak intensities contain information that can help detect the cooperative binding of a TF pair. CPI-EM also outperforms an existing sequence-based algorithm in detecting cooperative binding. The CPI-EM algorithm is available at https://github.com/vishakad/cpi-em.

genomics↗