Biology subjects

Singh, A.

Publications and source records attributed to Singh, A..

At least 631 records · Page 35Linked to original sources

bioRxiv2020

Subcellular localization of the J-protein Sis1 regulates the heat shock response

Cells exposed to heat shock induce a conserved gene expression program - the heat shock response (HSR) - encoding chaperones like Hsp70 and other protein homeostasis (proteostasis) factors. Heat shock also triggers proteostasis factors to form subcellular quality control bodies, but the relationship between these spatial structures and the HSR is unclear. Here we show that localization of the J-protein Sis1 - a co-chaperone for Hsp70 - controls HSR activation in yeast. Under nonstress conditions, Sis1 is concentrated in the nucleoplasm where it promotes Hsp70 binding to the transcription factor Hsf1, repressing the HSR. Upon heat shock, Sis1 forms an interconnected network with other proteostasis factors that spans the nucleolus and the surface of the cortical ER. We propose that localization of Sis1 to this network directs Hsp70 activity away from Hsf1 in the nucleoplasm, leaving Hsf1 free to induce the HSR. In this manner, Sis1 couples HSR activation to the spatial organization of the proteostasis network. One sentence summaryLocalization of the J-protein Sis1 to a subcellular network of proteostasis factors activates the heat shock response.

cell biology↗

bioRxiv2020

Noise propagation in gene expression in the presence of decoys

Genetically-identical cells can show remarkable intercellular variability in the level of a given protein which is commonly known as the gene expression noise. Besides intrinsic fluctuations that arise from the inherent stochasticity of the biochemical processes, a significant source of expression noise is extrinsic. Such extrinsic noise in gene expression arises from cell-to-cell differences in expression machinery, transcription factors, cell size, and cell cycle stage. Here, we consider the synthesis of a transcription factor (TF) whose production is impacted by a dynamic extrinsic disturbance, and systematically investigate the regulation of expression noise by decoy sites that can sequester the protein. Our analysis shows that increasing decoy numbers reduce noise in the level of the free (unbound) TF with noise levels approaching the Poisson limit for large number of decoys. Interestingly, the suppression of expression noise compared to no-decoy levels is maximized at intermediate disturbance timescales. Finally, we quantify the noise propagation from the TF to a downstream target protein and find counterintuitive behaviors. More specifically, for nonlinear dose responses of target-protein activation, the noise in the target protein can increase with the inclusion of decoys, and this phenomenon is explained by smaller but more prolonged fluctuations in the TF level. In summary, our results illustrates the nontrivial effects of high-affinity decoys in shaping the stochastic dynamics of gene expression to alter cell fate and phenotype at the single-cell level.

systems biology↗

bioRxiv2020

Hybrid systems modeling of ecological population dynamics

Discrete-time models are the traditional approach for capturing population dynamics of insects living in the temperate regions of the world. These models are characterized by an update function that connects the population densities from one year to the next. We revisit classical discrete-time models used for modeling interactions between two insect species (a host and a parasitoid), and provide novel result on the stability of the population dynamics. In particular, for a class of models we show that the fixed point is stable, if and only if, the host equilibrium density is an increasing function of the hosts reproduction rate. We also introduce a hybrid approach for obtaining the update functions by solving ordinary differential equations that mechanistically capture the ecological interactions between the host and the parasitoid. This hybrid approach is used to study the suppression of host density by a parasitoid. Our analysis shows that when the parasitoid attacks the host at a constant rate, then the host density cannot by suppressed beyond a certain point without making the population dynamics unstable. In contrast, when the parasitoids attack rate increases with increasing host density, then the host population density can be suppressed to arbitrarily low levels. These results have important implications for biological control where a natural enemy, such as a parasitoid wasp, is introduced to eliminate a pest that is the host species for the parasitoid.

ecology↗

bioRxiv2020

COP9 signalosome is an essential and druggable parasite target that regulates protein degradation

Understanding how the protozoan protein degradation pathway is regulated could uncover new parasite biology for drug discovery. We found the COP9 signalosome (CSN) conserved in multiple pathogens such as Leishmania, Trypanosoma, Toxoplasma, and used the severe diarrhea-causing Entamoeba histolytica to study its function in medically significant protozoa. We show that CSN is an essential upstream regulator of parasite protein degradation. Genetic disruption of E. histolytica CSN by two distinct approaches inhibited cell proliferation and viability. Both CSN5 knockdown and dominant negative mutation trapped cullin in a neddylated state, disrupting UPS activity and protein degradation. In addition, zinc ditiocarb (ZnDTC), a main metabolite of the inexpensive FDA-approved alcohol-abuse drug disulfiram, was active against parasites acting in a COP9-dependent manner. ZnDTC, given as disulfiram-zinc, had oral efficacy in clearing parasites in vivo. Our findings provide insights into the regulation of parasite protein degradation, and supports the significant therapeutic potential of COP9 inhibition. Summary sentenceParasite-encoded COP9 signalosome is an essential upstream regulator of ubiquitin-proteasome mediated protein degradation, and shows significant potential as a therapeutic target.

microbiology↗

bioRxiv2020

Validating a semi-quantitative method for assessment of degree of methylene blue staining in sentinel lymph nodes

Purpose To develop a digital algorithm and validate a semi-quantitative scoring method for surface methylene blue (MB) staining in whole lymph nodes (LN).Methods Lymph nodes from canine models undergoing sentinel lymph node (SLN) mapping were prospectively assessed ex vivo and photographed. Two blinded observers evaluated all images and assigned a semi-quantitative score based on surface staining (0 – no blue stain, 1 – 1-50% stained, 2 – 51-100% stained). A standard reference for degree of blue staining was based on signal-to-background ratios using computer-based imaging software with an output measurement of percentage of staining of the LN. Agreement between observers was assessed using the Kappa coefficient.Results 124 lymph nodes were included and demonstrated strong agreement (K = 0.8007, p < 0.0001) between results of semi-quantitative scoring and image analysis. Also, strong interobserver and intraobserver agreement was observed for the scoring system (K = 0.8051, p < 0.0001 and K = 0.9493, p < 0.0001, respectively).Discussion Agreement between the observer-based scoring system and imaging software illustrates a validated method in assessing MB staining, without the need for analysis software. The use of a semi-quantitative scoring system shows promise for a simple, objective assessment of MB staining in surgery and for future study. Lymph nodes can have variable surface colour, which can make assessment of blue staining challenging for novice observers in certain cases. This study describes a digital algorithm for quantitative analysis of blue staining in LN thereby providing a novel and objective reporting mechanism in scientific research involving SLN mapping.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pathology↗

bioRxiv2020

Noise propagation in metabolic pathways: the role of growth-mediated feedback

Metabolic networks are known to deal with the chemical reactions responsible to fuel cellular activities with energy and carbon source and, as a matter of fact, to set the growth rate of the cell. To this end, feedback and regulatory networks play a crucial role to handle adaptation to external perturbations and internal noise. In this work, a cellular resource is assumed to be activated at the end of a metabolic pathway, by means of a cascade of transformations. Such a cascade is triggered by the catalytic action of an enzyme that promotes the first transformation. The final product is responsible for the cellular growth rate modulation. This mechanism acts in feedback at the enzymatic level, since the enzyme (as well as all species) is subject to dilution, with the dilution rate set by growth. Enzymatic production is modeled by the occurrence of noisy bursts: a Stochastic Hybrid System is exploited to model the network and to investigate how such noise propagates on growth fluctuations. A major biological finding is that, differently from other models of metabolic pathways disregarding growth-mediated feedback, fluctuations in enzyme levels do not produce only local effects, but propagate up to the final product (hence to the growth rate). Furthermore, the delay provided by the cascade length helps in reducing the impact of enzymatic noise on to growth fluctuations. Analytical results are supported by Monte Carlo simulations.

systems biology↗

bioRxiv2020

Fluorophore-labelled RNA aptamers to common protein tags as super-resolution imaging reagents.

Developing labelling methods that densely and specifically label targeted cellular structures is critically important for centroid localization-based super-resolution microscopy. Being easy and inexpensive to produce in the laboratory and of relatively small size, RNA aptamers have potential as a substitute for conventional antibody labelling. By using aptamers selected against common protein tags - GFP (green fluorescent protein) in this case - we demonstrate labelling methods using dSTORM-compatible fluorophores for STORM and hybridizable imager strands for DNA-PAINT super-resolution optical imaging of any cellular proteins fused to the aptamer binding target. We show that we can label both extracellular and intracellular proteins for super-resolution imaging, and that the method in particular, offers some interesting advantages for live cell super-resolution imaging of plasma membrane proteins. KEY POINTSO_LIA simple to use RNA aptamer method for super-resolution STORM and PAINT imaging in cells expressing common protein tags. C_LIO_LIThe method has a number of unique advantages for live cell imaging at the nanometer scale. C_LIO_LIProvides a means to quantify the number of proteins being trafficked on the plasma membrane. C_LI

biophysics↗

bioRxiv2020

Coevolution of retroviruses with SERINCs following whole-genome duplication divergence

The SERINC gene family comprises of five paralogs in humans of which SERINC3 and SERINC5 inhibit HIV-1 infectivity and are counteracted by Nef. The origin of this anti-retroviral activity, its prevalence among the remaining paralogs, and its ability to target retroviruses remain largely unknown. Here we show that despite their early divergence, the anti-retroviral activity is functionally conserved among four human SERINC paralogs with SERINC2 being an exception. The lack of activity in human SERINC2 is associated with its post-whole genome duplication (WGD) divergence, as evidenced by the ability of pre-WGD orthologs from yeast, fly, and a post-WGD-proximate SERINC2 from coelacanth to inhibit nef-defective HIV-1. Intriguingly, potent retroviral factors from HIV-1 and MLV are not able to relieve the SERINC2-mediated particle infectivity inhibition, indicating that such activity was directed towards other retroviruses that are found in coelacanth (like foamy viruses). However, foamy-derived vectors are intrinsically resistant to the action of SERINC2, and we show that a foamy virus envelope confers this resistance. Despite the presence of weak arms-race signatures, the functional reciprocal adaptation among SERINC2 and SERINC5 and, in response, the emergence of antagonizing ability in foamy virus appears to have resulted from a long-term conflict with the host.

microbiology↗

bioRxiv2020

Organoid Polymer Functionality and Mode of Klebsiella Pneumoniae Membrane Antigen Presentation Regulates Ex Vivo Germinal Center Epigenetics in Young and Aged B Cells

Antibiotic-resistant bacteria are a major global health threat that continues to rise due to a lack of effective vaccines. Of concern are Klebsiella pneumoniae that fail to induce in vivo germinal center B cell responses, which facilitate antibody production to fight infection. Immunotherapies using antibodies targeting antibiotic-resistant bacteria are emerging as promising alternatives, however, cannot be efficiently derived ex vivo, necessitating the need for immune technologies to develop therapeutics. Here, four-arm PEG-organoids were developed to elucidate the effects of polymer end-point chemistry, integrin ligands, and mode of K. pneumoniae antigen presentation on germinal center-like B cell epigenetics, to better define the cell-microenvironment factors regulating ex vivo germinal center dynamics. Notably, PEG vinyl sulfone or acrylate failed to sustain primary immune cells, but functionalization with maleimide (PEG-4MAL) led to B cell expansion and germinal center-like induction. RNA sequencing analysis of lymph node stromal and germinal center B cells showed niche associated heterogeneity of integrin-related genes. Incorporation of niche-mimicking bioadhesive peptides revealed that collagen 1 mimicking peptides promoted germinal center-like dynamics and epigenetics. PEG-4MAL organoids elucidated the impact of K. pneumoniae membrane embedded protein antigen versus soluble antigen presentation on germinal center-like activation and preserved the response across young and aged mice.

immunology↗

bioRxiv2020

Optimum Threshold Minimizes Noise in Timing of Intracellular Events

How the noisy expression of regulatory proteins affects timing of intracellular events is an intriguing fundamental problem that influences diverse cellular processes. Here we use the bacteriophage {lambda} to study event timing in individual cells where cell lysis is the result of expression and accumulation of a single protein (holin) in the Escherchia coli cell membrane up to a critical threshold level. Site-directed mutagenesis of the holin gene was used to generate phage variants that vary in their timing of lysis from 30 to 190 min. Observation of the lysis times of single cells reveals an intriguing finding - the noise in lysis timing first decreases with increasing lysis time to reach a minimum, and then sharply increases at longer longer lysis times. A mathematical model with stochastic expression of holin together with dilution from cell growth was sufficient to explain the non-monotonic noise profile, and identify holin accumulation thresholds that generate precision in lysis timing.

biophysics↗

bioRxiv2020

RASSF effectors couple diverse RAS subfamily GTPases to the Hippo pathway

Activated RAS GTPases signal by directly binding effector proteins. Effectors have a folded RAS association (RA) domain that binds exclusively to GTP-loaded RAS, but the specificity of most RA domains for >150 RAS superfamily GTPases is unknown. Ten RAS-association domain family (RASSF) proteins comprise the largest group of effectors, proposed to couple RAS to the pro-apoptotic Hippo pathway. We show that RASSF1-6 complex with Hippo kinase, while RASSF7-10 are a separate family related to p53-regulatory ASPP effectors. Only RASSF5 directly binds activated HRAS and KRAS. Structural modelling reveals that expansion of RASSFs in vertebrates included amino acid substitutions that alter their GTPase binding specificity. We demonstrate that the tumour suppressor RASSF1A complexes with the GTPases GEM, REM1, REM2 and the enigmatic RASL12. Interplay between RASSFs and RAS GTPases can drastically restrict YAP1 nuclear localization. Thus, these simple scaffolds can link activation of diverse RAS proteins to Hippo or p53 regulation.

biochemistry↗

bioRxiv2020

Salinomycin inhibits epigenetic modulator EZH2 to enhance Death Receptors in Colon Cancer Stem Cells

Drug resistance is one of the trademark features of Cancer Stem Cells (CSCs). We and others have recently shown that paucity of functional death receptors (DR4/5) on the cell surface of tumor cells is one of the major reasons for drug resistance, but their involvement in the context of in CSCs is poorly understood. By harnessing CSC specific cytotoxic function of salinomycin, we discovered a critical role of epigenetic modulator EZH2 in regulating the expression of DRs in colon CSCs. Our unbiased proteome profiler array approach followed by ChIP analysis of salinomycin treated cells indicated that the expression of DRs, especially DR4 is epigenetically repressed in colon CSCs. Concurrently, EZH2 knockdown demonstrated increased expression of DR4/DR5, significant reduction of CSC phenotype such as spheroid formation in-vitro and tumorigenic potential in-vivo in colon cancer. TCGA data analysis of human colon cancer clinical samples shows strong inverse correlation between EZH2 and DR4. Taken together, this study provides an insight about epigenetic regulation of DR4 in colon CSCs and advocates that drug resistant colon cancer can be therapeutically targeted by combining TRAIL and small molecule EZH2 inhibitors.

cancer biology↗

bioRxiv2020

Stoichiometric Analysis of Protein Complexes by Cell Fusion and Single Molecule Imaging

The composition, stoichiometry and interactions of supramolecular protein complexes are a critical determinant of biological function. Several techniques have been developed to study molecular interactions and quantify subunit stoichiometry at the single molecule level; however, these typically require artificially low expression levels to achieve the low fluorophore concentration required for single molecule imaging, or use of detergent isolation of complexes that may perturb native subunit interactions. Here we present an alternative approach where protein complexes are assembled at physiological concentrations and subsequently diluted in situ for single-molecule level observations while preserving them in a near-native cellular environment. We show that coupling this in situ dilution strategy with single molecule techniques such as in vivo Fluorescence Correlation Spectroscopy (FCS), bleach step counting for quantifying protein complex stoichiometry, and two-color single molecule colocalization, improves the quality of data obtained using these single molecule fluorescence methods. Single Protein Recovery After Dilution (SPReAD) is a simple and versatile means of extending the concentration range of single molecule measurements into the cellular regime while minimizing potential artifacts and perturbations of protein complex stoichiometry. SIGNIFICANCE STATEMENTQuantifying the composition and stoichiometry of protein complexes in live cells is critical to understanding mechanisms involved in their function. Here we detail a method in which protein complexes are assembled intracellularly at physiological concentrations, but then diluted to levels suitable for single-molecule fluorescence observations while still within a cellular environment. The technique permits the use of common single molecule analysis techniques such as stepwise photobleaching quantification and fluorescence correlation spectroscopy to determine stoichiometry and functional interactions while avoiding artifacts that may occur from the use of detergent isolation methods or from the artificially low expression levels sometimes used to attain single molecule observation levels.

biophysics↗

bioRxiv2020

Host-induced silencing of the Colletotrichum gloeosporioides conidial morphology 1 gene (CgCOM1) confers resistance against Anthracnose disease in chilli and tomato

Anthracnose disease is caused by the ascomycetes fungal species Colletotrichum, which is responsible for heavy yield losses in chilli and tomato worldwide. Conventionally, harmful pesticides are used to contain anthracnose disease with limited success. In this study, we assessed the potential of Host-Induced Gene Silencing (HIGS) approach to target the Colletotrichum gloeosporioides COM1 (CgCOM1) developmental gene involved in the fungal conidial and appressorium formation, to restrict fungal infection in chilli and tomato fruits. For this study, we have developed stable transgenic lines of chilli and tomato expressing CgCOM1-RNAi construct employing Agrobacterium-mediated transformation. Transgenic plants were characterized by molecular and gene expression analyses. Production of specific CgCOM1 siRNA in transgenic chilli and tomato RNAi lines was confirmed by stem-loop RT-PCR. Fungal challenge assays on leaves and fruits showed that the transgenic lines were resistant to anthracnose disease-causing C. gloeosporioides in comparison to wild type and empty-vector control plants. RT-qPCR analyses in transgenic lines revealed barely any CgCOM1 transcripts in the C. gloeosporioides infected tissues, indicating near complete silencing of CgCOM1 gene expression in the pathogen. Microscopic examination of the Cg-challenged leaves of chilli-CgCOM1i lines revealed highly suppressed conidial germination, germ tube development, appressoria formation and mycelial growth of C. gloeosporioides, resulting in reduced infection of plant tissues. These results demonstrated highly efficient use of HIGS in silencing the expression of essential fungal developmental genes to inhibit the growth of pathogenic fungi, thus providing a highly precise approach to arrest the spread of disease.

plant biology↗

bioRxiv2019

Replication timing maintains the global epigenetic state in human cells.

DNA is replicated in a defined temporal order termed the replication timing (RT) program. RT is spatially segregated in the nucleus with early/late replication corresponding to Hi-C A/B chromatin compartments, respectively. Early replication is also associated with active histone modifications and transcriptional permissiveness. However, the mechanistic interplay between RT, chromatin state, and genome compartmentalization is largely unknown. Here we report that RT is central to epigenome maintenance and compartmentalization in both human embryonic stem cells (hESCs) and cancer cell line HCT116. Knockout (KO) of the conserved RT control factor RIF1, rather than causing discrete RT switches as previously suspected, lead to dramatically increased cell to cell heterogeneity of RT genome wide, despite RIF1s enrichment in late replicating chromatin. RIF1 KO hESCs have a nearly random RT program, unlike all prior RIF1 KO cells, including HCT116, which show localized alterations. Regions that retain RT, which are prevalent in HCT116 but rare in hESCs, consist of large H3K9me3 domains revealing two independent mechanisms of RT regulation that are used to different extents in different cell types. RIF1 KO results in a striking genome wide downregulation of H3K27ac peaks and enrichment of H3K9me3 at large domains that remain late replicating, while H3K27me3 and H3K4me3 are re-distributed genome wide in a cell type specific manner. These histone modification changes coincided with global reorganization of genome compartments, transcription changes and a genome wide strengthening of TAD structures. Inducible degradation of RIF1 revealed that disruption of RT is upstream of genome compartmentalization changes. Our findings demonstrate that disruption of RT leads to widespread epigenetic mis-regulation, supporting previously speculative models in which the timing of chromatin assembly at the replication fork plays a key role in maintaining the global epigenetic state, which in turn drives genome architecture.

molecular biology↗

bioRxiv2019

Enhancement of gene expression noise due to nonspecific transcription factor binding

The genome contains several high-affinity non-functional binding sites for transcription factors (TFs) creating a hidden and unexplored layer of gene regulation. We investigate the role of such "decoy sites" in controlling noise (random fluctuations) in the level of a TF that is synthesized in stochastic bursts. Prior studies have assumed that decoy-bound TFs are protected from degradation, and in this case decoys function to buffer noise. Relaxing this assumption to consider arbitrary degradation rates for both bound/unbound TF states, we find rich noise behaviors. For low-affinity decoys, noise in the level of unbound TF always monotonically decreases to the Poisson limit with increasing decoy numbers. In contrast, for high affinity decoys, noise levels first increase with increasing decoy numbers, before decreasing back to the Poisson limit. Interestingly, while protection of bound TFs from degradation slows the time-scale of fluctuations in the unbound TF levels, decay of bounds TFs leads to faster fluctuations and smaller noise propagation to downstream target proteins. In summary, our analysis reveals stochastic dynamics emerging from nonspecific binding of TFs, and highlight the dual role of decoys as attenuators or amplifiers of gene expression noise depending on their binding affinity and stability of the bound TF.

systems biology↗

bioRxiv2019

Towards a Digital Diatom: image processing and deep learning analysis of Bacillaria paradoxa dynamic morphology

Recent years have witnessed a convergence of data and methods that allow us to approximate the shape, size, and functional attributes of biological organisms. This is not only limited to traditional model species: given the ability to culture and visualize a specific organism, we can capture both its structural and functional attributes. We present a quantitative model for the colonial diatom Bacillaria paradoxa, an organism that presents a number of unique attributes in terms of form and function. To acquire a digital model of B. paradoxa, we extract a series of quantitative parameters from microscopy videos from both primary and secondary sources. These data are then analyzed using a variety of techniques, including two rival deep learning approaches. We provide an overview of neural networks for non-specialists as well as present a series of analysis on Bacillaria phenotype data. The application of deep learning networks allows for two analytical purposes. Application of the DeepLabv3 pre-trained model extracts phenotypic parameters describing the shape of cells constituting Bacillaria colonies. Application of a semantic model trained on nematode embryogenesis data (OpenDevoCell) provides a means to analyze masked images of potential intracellular features. We also advance the analysis of Bacillaria colony movement dynamics by using templating techniques and biomechanical analysis to better understand the movement of individual cells relative to an entire colony. The broader implications of these results are presented, with an eye towards future applications to both hypothesis-driven studies and theoretical advancements in understanding the dynamic morphology of Bacillaria.

systems biology↗

bioRxiv2019

Intelli-NGS: Intelligent NGS, a deep neural network-based artificial intelligence to delineate good and bad variant calls from IonTorrent sequencer data

BackgroundIonTorrent is a second-generation sequencing platform with smaller capital costs than Illumina but is also prone to higher machine error than later. Given its lower costs, the platform is generally preferred in developing countries where next-generation sequencing is still a very exclusive technique. There are many software tools available for other platforms but IonTorrent. This makes the already tricky analysis part more error-prone. MotivationWe have been using the IonTorrent platform in our hospital setting for aiding diagnosis or treatment for the past couple of years. Given to our experience, analysis part of IonTorrent data takes the longest time and still, we used to get stuck with certain variants which seemed fine on looking at their metrics but were found to be negative in Sanger sequencing verification. This made us determined to develop a tool that could aid us in reducing false positive and negative rates while still retaining good recall. The artificial intelligence-based technique was our final choice after developing pipelines with less success. MethodologyThe artificial intelligence was developed from scratch in Python 3 using TensorFlow fully connected dense layers. The model takes VCF files as input and solves each variant based on the thirty-five parameters given by the IonTorrent platform, including the flow-space information which is missed by variant callers other than the default torrent variant caller. ResultsThe final trained model was able to achieve an accuracy of 93.08% and a ROC-AUC of 0.95 with GIAB validation data. The additional program that was written to run the model annotates each variant using online databases such as dbSNP, ClinVar and others. A probability score for each outcome for each variant is also provided to aid in decision making. AvailabilityThe model and running code are available for free only for non-commercial users at https://www.github.com/aditya-88/intelli-ngs.

bioinformatics↗