Biology subjects

Chandrasekaran, S.

Publications and source records attributed to Chandrasekaran, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Manufacturing DNA in E. coli yields higher fidelity DNA than in vitro enzymatic synthesis

The rise of biotechnologies such as gene therapy have brought DNA vectors to the forefront of pharmaceutical development. The quality of the genetic starting material plays a pivotal role in determining the quality of the final product. In this study we examined the fidelity of DNA replication using enzymatic methods (in vitro) compared to plasmid DNA produced in vivo in E. coli. Next-generation sequencing approaches predominantly rely on in vitro polymerases, which have inherent limitations in sensitivity. To address this challenge, we introduce a novel assay based on loss-of-function (LOF) mutations in the conditionally toxic sacB gene. Our findings show that DNA production in E. coli results in significantly fewer LOF mutations (approximately 80-to 3000-fold less) compared to various enzymatic DNA synthesis methods. This includes the most accurate PCR polymerase (Q5) and a commonly employed rolling circle amplification (RCA) DNA polymerase (Phi29). These results suggest that using low-fidelity starting material DNA synthesized in vitro by PCR or RCA may introduce a substantial number of impurities, potentially affecting the quality and yield of final pharmaceutical products. In summary, our study underscores that DNA synthesized in vitro has a significantly higher mutation rate than DNA produced traditionally in E. coli. Therefore, utilizing in vitro enzymatically-produced DNA in biotechnology and biomanufacturing may entail considerable fidelity-related risks, while DNA starting material derived from E. coli substantially mitigates this risk, enhancing overall quality in the production processes.

synthetic biology↗

bioRxiv2023

Mapping host-microbe transcriptional interactions by dual perturb-seq

Intracellular pathogens and other endosymbionts reprogram host cell transcription to suppress immune responses and recalibrate biosynthetic pathways. This reprogramming is critical in determining the outcome of infection or colonisation. Here, we combine pooled CRISPR knockout screening with dual host-microbe single-cell RNA-sequencing to identify the molecular mediators of these transcriptional interactions, a method we term dual perturb-seq. Applying dual perturb-seq to the intracellular pathogen Toxoplasma gondii, we are able to identify previously uncharacterised effector proteins and directly infer their function from the transcriptomic data. We show that TgGRA59 contributes to the export of other effector proteins from the parasite into the host cell and identify a novel effector, TgSOS1, that is necessary for sustained host STAT6 signalling and thereby contributes to parasite immune evasion and persistence. Together, this work demonstrates a novel tool that can be broadly adapted to interrogate host-microbe transcriptional interactions and reveal mechanisms of infection and immune evasion.

molecular biology↗

bioRxiv2023

Signal Transduction and Kinase Control in Nanodisc Reconstituted E. coli Aerotaxis Receptor

WITHDRAWAL STATEMENTThe authors have withdrawn this manuscript because its being revised. The authors wish to withdraw this manuscript for two reasons. Firstly, the relevance and validity of some of the mass spectrometry data in the manuscript are being questioned by the authors. Secondly, some of the authors had not adequately reviewed the manuscript before it was uploaded to bioRxiv. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

biophysics↗

bioRxiv2023

Data-Driven Screening to Infer Metabolic Modulators of the Cancer Epigenome

Metabolites such as acetyl-CoA and citrate play an important moonlighting role by influencing the levels of histone post-translational modifications (PTMs) and regulating gene expression. This cross talk between metabolism and epigenome impacts numerous biological processes including development and tumorigenesis. However, the extent of moonlighting activities of cellular metabolites in modulating the epigenome is unknown. We developed a data-driven screen to discover moonlighting metabolites by constructing a histone PTM-metabolite interaction network using global chromatin profiles, metabolomics, and epigenetic drug sensitivity data from over 600 cell lines. Our ensemble statistical learning approach uncovered metabolites that are predictive of histone PTM levels and epigenetic drug sensitivity. We experimentally validated synergistic and antagonistic interactions between histone deacetylase and demethylase inhibitors with epigenetic metabolites kynurenic acid, pantothenate, and 1-methylnicotinamide. We apply our approach to track metaboloepigenetic interactions during the epithelial-mesenchymal transition. Overall, our data-driven approach unveils a broader range of metaboloepigenetic interactions than anticipated from previous studies, with implications for reversing aberrant epigenetic alterations and enhancing epigenetic therapies through diet.

systems biology↗

bioRxiv2022

Phosphorylation, disorder, and phase separation govern the behavior of Frequency in the fungal circadian clock

Circadian clocks are composed of molecular oscillators that pace rhythms of gene expression to the diurnal cycle. Therein, transcriptional-translational negative feedback loops (TTFLs) generate oscillating levels of transcriptional repressor proteins that regulate their own gene expression. In the filamentous fungus Neurospora crassa, the proteins Frequency (FRQ), the FRQ-interacting RNA helicase (FRH) and Casein-Kinase I (CK1) form the FFC complex that represses expression of genes activated by the White-Collar complex (WCC). A key question concerns how FRQ orchestrates molecular interactions at the core of the clock despite containing little predicted tertiary structure. We present the reconstitution and biophysical characterization of FRQ and the FFC in unphosphorylated and highly phosphorylated states. Site-specific spin labeling and pulse- dipolar ESR spectroscopy provides domain-specific structural details on the full-length, 989- residue intrinsically disordered FRQ and the FFC. FRQ contains a compact core that associates and organizes FRH and CK1 to coordinate their roles in WCC repression. FRQ phosphorylation increases conformational flexibility and alters oligomeric state but the changes in structure and dynamics are non-uniform. Full-length FRQ undergoes liquid-liquid phase separation (LLPS) to sequester FRH and CK1 and influence CK1 enzymatic activity. Although FRQ phosphorylation favors LLPS, LLPS feeds back to reduce FRQ phosphorylation by CK1 at higher temperatures. Live imaging of Neurospora hyphae reveals FRQ foci characteristic of condensates near the nuclear periphery. Analogous clock repressor proteins in higher organisms share little position-specific sequence identity with FRQ; yet, they contain amino-acid compositions that promote LLPS. Hence, condensate formation may be a conserved feature of eukaryotic circadian clocks.

biochemistry↗

bioRxiv2022

ROP16-mediated activation of STAT6 facilitates encystment of type III Toxoplasma gondii in neurons

Toxoplasma gondii establishes a long-lived latent infection in the central nervous system (CNS) of its hosts. Reactivation in immunocompromised individuals can lead to life threatening disease. Latent infection is driven by the ability of the parasite to convert from the acute-stage tachyzoite to the latent-stage bradyzoite which resides in long-lived intracellular cysts. While much work has focused on the parasitic factors that drive cyst development, the host factors that influence encystment are not well defined. Here we show that a polymorphic secreted parasite kinase (ROP16), that phosphorylates host cell proteins, mediates efficient encystment of T. gondii in stress-induced models of encystment and primary neuronal cell cultures (PNCs) in a strain-specific manner. Using short-hairpin RNA (shRNA) knockdowns in human foreskin fibroblasts (HFFs) and PNCs from transgenic mice, we determined that ROP16s cyst enhancing abilities are mediated by phosphorylation of the host cell transcription factor STAT6. To test the role of STAT6 in vivo, we infected STAT6KO mice, finding that, compared to infected wild-type mice, infected STAT6KO mice have a decrease in cyst burden, but not overall parasite burden or dissemination to the CNS. Finally, we found a similar ROP16-dependent encystment defect in human pluripotent stem cell-derived neurons. Together, these findings identify a host cell factor (STAT6) that T. gondii manipulates in a strain-specific manner to generate a favorable encystment environment.

microbiology↗

bioRxiv2022

HIV integration in the human brain is linked to microglial activation and 3D genome remodeling

Exploration of genome organization and function in the HIV infected brain is critical to aid in the development of treatments for HIV-associated neurocognitive disorder (HAND) and HIV cure strategies. Here, we generated a resource comprised of single nuclei transcriptomics, complemented by cell-type-specific Hi-C chromosomal conformation ( 3D genome) and viral integration site sequencing (IS-seq) in frontal brain tissues from individuals with HIV encephalitis (HIVE), HIV-infected people without encephalitis (HIV+), and HIV uninfected (HIV-) controls. We observed profound 3D genomic reorganization of open/repressive (A/B) compartment structures encompassing 6.4% of the HIVE microglial genome that was associated with transcriptomic reprogramming, including down-regulation of homeostasis and synapse-related functions and robust activation of interferon signaling and cell migratory pathways. HIV RNA was detected in 0.003% of all nuclei in HIVE brain, predominantly in the most activated microglia where it ranked as the second most highly expressed transcript. Microglia from HIV+ brains showed, to a lesser extent, similar transcriptional alterations. IS-seq recovered 1,221 insertion events in glial nuclei that were enriched for chromosomal domains newly mobilized into a permissive chromatin environment in HIVE microglia. Brain and peripheral myeloid cell integration revealed a preference overall for transcription-permissive chromatin, but robust differences in the frequency of recurrent insertions, intergenic integration, and enrichment for pre-integration complex-associated factors at integration sites. Our resource highlights critical differences in the genomic patterns of HIV infection in brain versus blood and points to a dynamic interrelationship between inflammation-associated 3D genome remodeling and successful integration in brain.

neuroscience↗

bioRxiv2022

Constraint-based modeling identifies metabolic vulnerabilities during the epithelial to mesenchymal transition

Epithelial-to-mesenchymal transition (EMT) is a developmentally conserved cellular process critical for tumor metastasis. EMT enables malignant epithelial cells to acquire mesenchymal-like migratory and invasive phenotype. During EMT cancer cells undergo extensive metabolic reprogramming that correlates with the suppression of proliferation, and stimulation of the energy-intensive migratory behavior. However, the causal relationship between metabolic changes and coordinated physiological phenotypes that occur during EMT is still unclear. We used bulk time-course transcriptomics and proteomics, and single-cell transcriptomics from five independent EMT studies in A549 lung adenocarcinoma cells to simulate metabolic network activity using constraint-based modeling. Model predictions were validated using literature mining, experimental studies and CRISPR-Cas9 essentiality screens. We uncovered temporal metabolic dependencies in glycolysis and glutamine metabolism reactions, and experimentally validated isoform-specific dependency on Enolase3 for cell survival during EMT. Together, our approach uncovered temporally regulated cell-state-specific metabolic dependencies in cells undergoing EMT.

cancer biology↗

bioRxiv2021

IFN-γ stimulated murine and human neurons mount anti-parasitic defenses against the intracellular parasite Toxoplasma gondii

Dogma holds that Toxoplasma gondii persists in neurons because neurons cannot clear intracellular parasites, even with IFN-{gamma} stimulation. As several recent studies questioned this idea, we used primary murine neuronal cultures from wild-type and transgenic mice in combination with IFN-{gamma} stimulation and parental and transgenic parasites to reassess IFN-{gamma} dependent neuronal clearance of intracellular parasites. We found that neurons respond to IFN-{gamma} and that a subset of neurons clear intracellular parasites via immunity regulated GTPases. Whole neuron reconstructions from mice infected with parasites that trigger neuron GFP expression only after full invasion revealed that [~]40% of these T. gondii-invaded neurons no longer harbor parasites. Finally, IFN-{gamma} stimulated human stem cell derived neurons showed a [~] 50% decrease in parasite infection rate when compared to unstimulated cultures. This work highlights the capability of human and murine neurons to mount cytokine-dependent anti-T. gondii defense mechanisms in vitro and in vivo.

neuroscience↗

bioRxiv2021

Large-scale discovery of recombinases for integrating DNA into the human genome

Recent microbial genome sequencing efforts have revealed a vast reservoir of mobile genetic elements containing integrases that could be useful genome engineering tools. Large serine recombinases (LSRs), such as Bxb1 and PhiC31, are bacteriophage-encoded integrases that can facilitate the insertion of phage DNA into bacterial genomes. However, only a few LSRs have been previously characterized and they have limited efficiency in human cells. Here, we developed a systematic computational discovery workflow that identifies thousands of new LSRs and their cognate DNA attachment sites by. We validate this approach via experimental characterization of LSRs in human cells, leading to three classes of LSRs distinguished from one another by their efficiency and specificity. We identify landing pad LSRs that efficiently integrate into synthetically installed attachment sites orthogonal to the human genome, human genome-targeting LSRs with computationally predictable pseudosites, and multi-targeting LSRs that can unidirectionally integrate cargos at with similar efficiency and superior specificity to commonly used transposases. LSRs from each category were functionally characterized in human cells, overall achieving up to 7-fold higher plasmid recombination than Bxb1 and genome insertion efficiencies of 40-70% with cargo sizes over 7 kb. Overall, we establish a paradigm for large-scale discovery of microbial recombinases and reconstruction of their target sites directly from microbial sequencing data. This strategy provides a rich resource of over 60 experimentally characterized LSRs that can function in human cells and thousands of additional candidates for large-payload genome editing without exposed DNA double-stranded breaks.

bioengineering↗

bioRxiv2021

Dynamic metabolic network modeling of a mammalian cell cycle using time-course multi-omics data

Cell cycle is a fundamental process for cell growth and proliferation, and its dysregulation leads to many diseases. How metabolic networks are regulated and rewired during the cell cycle is unknown. Here we apply a dynamic genome-scale metabolic modeling framework (DFA) to simulate a cell cycle of cytokine-activated murine pro-B cells. Phase-specific reaction activity predicted by DFA using time-course metabolomics were validated using matched time-course proteomics and phospho-proteomics data. Our model correctly predicted changes in methionine metabolism at the G1/S transition and the activation of lysine metabolism, nucleotides synthesis, fatty acid elongation and heme biosynthesis at the critical G0/G1 transition into cell growth and proliferation. Metabolic fluxes predicted from proteomics and phosphoproteomics constrained metabolic models were highly consistent with DFA fluxes and revealed that most reaction fluxes are regulated indirectly. Our model can help predict the impact of changes in nutrients, enzymes, or regulators on this critical cellular process.

systems biology↗

bioRxiv2021

Mechanistic insight into light-dependent recognition of Timeless by Drosophila cryptochrome

Cryptochrome (CRY) entrains the fly circadian clock by binding to Timeless (TIM) in light and triggering its degradation. Undocking of a helical C-terminal tail (CTT) in response to photoreduction of the CRY flavin cofactor gates TIM binding. A generally-applicable Select Western-blot-Free Tagged-protein Interaction (SWFTI) assay enables quantification of CRY binding to TIM in dark and light. The assay is utilized to study CRY variants with residue substitutions in the flavin pocket and correlate their TIM affinities with CTT undocking, as measured by pulse-dipolar ESR spectroscopy and evaluated by molecular dynamics simulations. CRY variants with the CTT removed or undocked bind TIM constitutively, whereas those incapable of photoreduction bind TIM weakly. In response to flavin redox state, two conserved histidine residues contribute to a robust on/off switch by mediating CTT interactions with the flavin pocket and TIM. Our approach provides an expeditious means to quantify protein-protein interactions and photoreceptor targeting.

biochemistry↗

bioRxiv2021

NEURON-SPECIFIC CHROMOSOMAL MEGADOMAIN ORGANIZATION IS ADAPTIVE TO RECENT RETROTRANSPOSON EXPANSIONS

Here, we mapped cell-type specific chromatin domain organization in adult mouse cerebral cortex and report strong enrichment of Endogenous Retrovirus 2 (ERV2) repeat sequences in the neuron-specific heterochromatic B2NeuN+ megabase-scaling subcompartment. Comparative chromosomal conformation mapping in Mus spretus and Mus musculus revealed neuron-specific reconfigurations tracking recent ERV2 retrotransposon expansions in the murine germline, with significantly higher B2 megadomain contact frequencies at sites with ongoing ERV2 insertions in Mus musculus. Ablation of the retrotransposon silencer Kmt1e/Setdb1 triggered B2 megadomain disintegration and rewiring with open chromatin domains enriched for cellular stress response genes, along with severe neuroinflammation and proviral assembly of ERV2/Intracisternal-A-Particles (IAPs) infiltrating dendrites and spines. We conclude that neuronal megadomain architectures include evolutionarily adaptive heterochromatic organization which, upon perturbation, unleashes ERV proviruses with strong tropism within mature neurons.

neuroscience↗

bioRxiv2021

Decoupling the ATP-binding Domain in the CheA Kinase by Increasing Linker Flexibility Dramatically Alters Kinase Activity

Bacterial chemoreceptors regulate the cytosolic multi-domain histidine kinase CheA through largely unknown mechanisms. Residue substitutions in the peptide linkers that connect the P4 kinase domain to the P3 dimerization and P5 regulatory domain affect CheA basal activity and activation. To understand the role that these linkers play in CheA activity, the P3-to-P4 linker (L3) and P4-to-P5 linker (L4) were extended and altered in variants of Thermotoga maritima (Tm) CheA. Flexible extensions of the L3 and L4 linkers in CheA-LVI (linker variant 1) allowed for a well-folded kinase domain that retained wild-type (WT){-}like binding affinities for nucleotide and normal interactions with the receptor-coupling protein CheW. However, CheA-LV1 autophosphorylation activity registered -50-fold lower compared to WT. Neither a WT nor LV1 dimer containing a single P4 domain could autophosphorylate the P1 substrate domain. Autophosphorylation activity was rescued in variants with extended L3 and L4 linkers that favor helical structure and heptad spacing. Autophosphorylation depended on linker spacing and flexibility and not on sequence. Pulse-dipolar electron-spin resonance (ESR) measurements with spin-labeled ATP analogs indicated that CheA autophosphorylation activity inversely correlated with the proximity of the P4 domains within the dimers of the variants. Despite their separation in primary sequence and space, the L3 and L4 linkers also influence the mobility of the P1 substrate domains. In all, interactions of the P4 domains, as modulated by the L3 and L4 linkers, affect domain dynamics and autophosphorylation of CheA, thereby providing potential mechanisms for receptors to regulate the kinase.

biophysics↗

bioRxiv2021

Longitudinal monitoring of individual infection progression in Drosophila melanogaster

The innate immune system is critical for host survival of infection. Infection models in organisms like Drosophila melanogaster are key for understanding evolution and dynamics of innate immunity. However, current toolsets for fly infection studies are limited in their throughput and their ability to generate longitudinal measurements of infection progression in single animals. Here we report a novel bioluminescent imaging strategy enabling non-invasive characterization of pathogen load over time. We demonstrate that photon flux from autobioluminescent reporter bacteria can be used to monitor relative pathogen loads in individual animals. Escherichia coli expressing the ilux operon were imaged in whole, living flies at relevant concentrations for immune study. Because animal sacrifice was not necessary to estimate pathogen load, stochastic responses to infection were characterized in individuals over time for the first time. The high temporal resolution of bioluminescence imaging also enabled visualization of the fine dynamics of microbial clearance on the hours time-scale. Overall, this non-invasive imaging strategy provides a simple and scalable platform to observe changes in pathogen load in vivo over time.

immunology↗

bioRxiv2021

An interpretable flux-based machine learning model of drug interactions across metabolic space and time

AO_SCPLOWBSTRACTC_SCPLOWDrug combinations are a promising strategy to counter antibiotic resistance. However, current experimental and computational approaches do not account for the entire complexity involved in combination therapy design, such as the effect of pathogen metabolic heterogeneity, changes in the growth environment, drug treatment order and time interval. To address these limitations, we present a comprehensive approach that uses genome-scale metabolic modeling and machine learning to guide combination therapy design. Our mechanistic approach (a) accommodates diverse data types, (b) accounts for time- and order-specific interactions, and (c) accurately predicts drug interactions in various growth conditions and their robustness to pathogen metabolic heterogeneity. Our approach achieved high accuracy (AUC = 0.83 for synergy, AUC = 0.98 for antagonism) in predicting drug interactions for E. coli cultured in 57 metabolic conditions based on experimental validation. The entropy in bacterial metabolic response was predictive of combination therapy outcomes across time scales and growth conditions. Simulation of metabolic heterogeneity using population FBA identified two sub-populations of E. coli cells defined by the levels of three proteins (eno, fadB and fabD) in glycolysis and lipid metabolism that influence cell tolerance to a broad range of antibiotic combinations. Analysis of the vast landscape of condition-specific drug interactions revealed a set of 24 robustly synergistic drug combinations with potential for clinical use. SO_SCPLOWIGNIFICANCEC_SCPLOWWorldwide, 700,000 people die each year from drug-resistant infections. Drug combinations have great potential to reduce the spread of drug-resistant bacteria. However, their potency is impacted by both the pathogen growth environment and the heterogeneity in pathogen metabolism. The metabolic heterogeneity in a pathogen population allows them to survive antibiotic treatment. Here we present a flexible machine-learning framework that utilizes diverse data types to effectively search through the large design space of both sequential and simultaneous combination therapies across hundreds of simulated growth conditions and pathogen metabolic states. Our approach can serve as a useful guide for the selection of robustly synergistic drug combinations.

systems biology↗

bioRxiv2021

TaxiBGC: a Taxonomy-guided Approach for the Identification of Experimentally Verified Microbial Biosynthetic Gene Clusters in Shotgun Metagenomic Data

Biosynthetic gene clusters (BGCs) in microbial genomes encode for bioactive secondary metabolites (SMs), which can play important roles in microbe-microbe and host-microbe interactions. Given the biological significance of SMs and the current profound interest in the metabolic functions of microbiomes, the unbiased identification of BGCs from high-throughput metagenomic data could offer novel insights into the complex chemical ecology of microbial communities. Currently available tools for predicting BGCs from shotgun metagenomes have several limitations, including the need for computationally demanding read-assembly; predicting a narrow breadth of BGC classes; and not providing the SM product. To overcome these limitations, we developed TaxiBGC (Taxonomy-guided Identification of Biosynthetic Gene Clusters), a command-line tool for predicting experimentally characterized BGCs (and inferring their known SMs) in metagenomes by first pinpointing the microbial species likely to harbor them. We benchmarked TaxiBGC on various simulated metagenomes, showing that our taxonomy-guided approach could predict BGCs with much-improved performance (mean F1 score: 0.56, mean PPV score: 0.80) compared to directly identifying BGCs by mapping sequencing reads onto the BGC genes (mean F1 score: 0.49, mean PPV score: 0.41). Next, by applying TaxiBGC on 2,650 metagenomes from the Human Microbiome Project and various case-control gut microbiome studies, we were able to associate BGCs (and their SMs) with different human body sites and with multiple gastrointestinal diseases, including Crohns disease and liver cirrhosis. In all, TaxiBGC provides an in silico platform to predict experimentally characterized BGCs and their SM production potential in metagenomic data while demonstrating important advantages over existing techniques. IMPORTANCECurrently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally-oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source. Through rigorous benchmarking techniques on simulated metagenomes, we show that TaxiBGC provides a significant advantage over existing methods. When demonstrating TaxiBGC on thousands of human microbiome samples, we associate BGCs encoding for bacteriocins with different human body sites and diseases, thereby elucidating a possible novel role of this antibiotic class in maintaining the stability of microbial ecosystems throughout the human body. Furthermore, we report for the first time gut microbial BGC associations shared amongst multiple pathologies. Ultimately, we expect our tool to facilitate future investigations into the chemical ecology of microbial communities across diverse niches and pathologies.

bioinformatics↗

bioRxiv2021

Acetyl-CoA metabolism drives epigenome change and contributes to carcinogenesis risk in fatty liver disease

The rate of nonalcoholic fatty liver disease (NAFLD)-associated hepatocellular carcinoma (HCC) is increasing worldwide, but the steps in precancerous hepatocytes which lead to HCC driver mutations are not well understood. Here we provide evidence that metabolically-driven histone hyperacetylation in steatotic hepatocytes can increase DNA damage to initiate carcinogenesis. Genome-wide histone acetylation is increased in steatotic livers of rodents fed high fructose or high fat diet. In vitro, steatosis relaxes chromatin and increases DNA damage marker {gamma}H2AX, which is reversed by inhibiting acetyl-CoA production. Steatosis-associated acetylation and {gamma}H2AX are enriched at gene clusters in telomere-proximal regions which contain HCC tumor suppressors in hepatocytes and human fatty livers. Regions of metabolically-driven epigenetic change also have increased levels of DNA mutation in non-cancerous tissue from NAFLD patients. Finally, genome-scale network modelling indicates that redox balance is a key contributor to this mechanism. Thus abnormal histone hyperacetylation is a potential initiating event in HCC carcinogenesis.

cancer biology↗