Biology subjects

Ghatak, A.

Publications and source records attributed to Ghatak, A..

11 recordsLinked to original sources

bioRxiv2026

Mechanical Signaling Regulates DNA Methylation to Maintain Muscle Stem Cell Quiescence

Skeletal muscle stem cells (MuSCs) reside within a mechanically dynamic niche where they integrate biophysical and biochemical cues to maintain quiescence. Here, we show that substrate stiffness and RhoA-dependent signaling regulate MuSC fate. MuSCs cultured on soft matrices or depleted of RhoA exhibit altered morphology, diminished actomyosin organization, and undergo premature activation. Loss of RhoA reshapes the DNA methylation landscape, leading to widespread changes in gene expression and alternative splicing. Dnmt3a was among the genes transcriptionally downregulated following loss of RhoA signaling. Mechanistically, RhoA maintains Dnmt3a expression by promoting SP1 occupancy at its promoter. Importantly, loss of Dnmt3a in quiescent MuSCs is sufficient to drive activation, identifying Dnmt3a as a key epigenetic effector downstream of mechanical signaling. Together, these findings define a mechanotransduction-epigenetic axis in which RhoA maintains stem cell quiescence by preserving DNA methylation programs through Dnmt3A.

cell biology↗

bioRxiv2025

Energy trade-offs under fluctuating light govern bioenergetics and growth in Chlamydomonas reinhardtii

Rapidly changing light intensity is a natural challenge that photosynthetic organisms can tolerate. Regulatory mechanisms of light harvesting and alternative electron pathways are critical in dissipating and distributing energy under fluctuating light intensities (FL), but less is known about downstream metabolic regulations. Here, we compared the cellular responses of Chlamydomonas reinhardtii grown under FL to cells acclimated to constant high (HL) or low light (LL), either under high (2 %) or low (0.04 %) CO2. Under low CO2, the physiology of FL cells resembled HL cells and proteomics revealed an induction of the ATP consuming carbon-concentrating mechanism, and photorespiration particularly under FL. High CO2 promoted growth under FL, albeit by a lesser extent than under HL and led to higher ATP contents than under low CO2. To fuel ATP production under low CO2, cells upregulated mitochondrial respiration under FL, while enhanced cyclic electron flow and redox shuttling between intracellular compartments was most evident under FL and LL. Chloroplastic carbon metabolism rapidly responded to light changes, independent of CO2 availability, whereas metabolites associated with mitochondrial bioenergetics responded slower, and remained abundant under high CO2. The accumulation of enzymes involved in starch synthesis and breakdown under FL, together with the transient accumulation of hexoses and hexose phosphates, indicated that cells relied on sugars as a transient carbon pool to meet changing metabolic demands under FL. We conclude that the interplay between light intensity and CO2 availability drives critical energy trade-offs, balancing photoprotection, repair, and carbon allocation, that regulate growth under FL.

plant biology↗

bioRxiv2025

Regulation of early-stage tomato fruit growth by the splicing factor RS2Z36

Fruit growth is mediated by cell division and expansion. In tomato, the model for fleshy fruit development, both processes are tightly linked to changes in gene expression, including transcriptional regulation and RNA processing. While several transcription factors are implicated in fruit developmental programs, the role of splicing regulators remains largely unexplored. Expression profiling of splicing-related genes revealed expression patterns. The serine/arginine-rich splicing factor RS2Z36 is expressed in ovaries and during early fruit development. Loss-of-function mutations in RS2Z36 result in ovaries with altered patterning and in smaller, ellipsoid fruits. rs2z36 mutants display elongated pericarp cells along the longitudinal axis of pre-anthesis ovaries, indicating that RS2Z36-dependent expansion patterns are established before anthesis. RNA-seq uncovered widespread alternative splicing of genes across diverse biological processes, while proteome analysis revealed altered protein abundance and peptides derived from novel splice variants. In addition, rs2z36-1 pericarps show increased deposition of LM6-recognized arabinan and AGP epitopes. Together, these findings identify RS2Z36 as a regulator of ovary and fruit development and highlight a previously underappreciated role for splicing control in shaping early fruit morphology.

developmental biology↗

bioRxiv2024

A fast-track, high-throughput screening platform for biological nitrification inhibitors discovery based on soil relevant ammonia oxidizing strains

Nitrogen cycling is critical for ecosystem functioning, with nitrification playing a central role. Excessive nitrification, triggered by heavy nitrogen fertilisation, contributes to reduced nitrogen use efficiency, nitrate leaching, and nitrous oxide emissions. While synthetic nitrification inhibitors (SNIs) help reduce these impacts, their erratic performance and environmental risks have shifted focus to biological nitrification inhibitors (BNIs) as sustainable alternatives. In vitro bioassays with ammonia-oxidising microorganisms (AOM) are valuable for BNI discovery and research, but often have low throughput and rely on a limited number of mostly non-soil-relevant or genetically modified ammonia-oxidizing bacteria (AOB) strains, lacking validation with established BNIs. We present a refined fast-track, high-throughput assay for BNI screening, utilizing soil-relevant, ecophysiologically and phylogenetically diverse AOB (Nitrosospira multiformis, Nitrosomonas ureae, Nitrosomonas communis) and ammonia-oxidizing archaea (AOA) strains (Nitrososphaera viennensis, "Ca. Nitrosocosmicus franklandianus"), achieving consistent cellular activity and density. The assay was validated with established SNIs and BNIs, showing differences in inhibition efficacy and strain sensitivity, consistent with literature. As a proof of concept, root exudates from diverse wheat genotypes were screened, demonstrating distinct inhibition profiles. The proposed system advances previously available screening systems and, when integrated with realistic soil tests, will facilitate the discovery of novel BNIs and BNI-producing plant genotypes.

microbiology↗

bioRxiv2024

Integration of multi-omics and deep phenotyping provides novel insights into multiple abiotic stress responses in potato

Potato is highly water and space efficient but susceptible to abiotic stresses such as heat, drought, or flooding, which are severely exacerbated by climate change. Understanding of crop acclimation to abiotic stress, however, remains limited. Here, we present a comprehensive molecular and physiological high-throughput profiling of potato (Solanum tuberosum, cv. Desiree) under heat, drought and waterlogging applied as single stresses or in combinations designed to mimic realistic future scenarios. Stress-responses were monitored via daily phenotyping and multi-omics analyses of leaf samples comprising transcriptomics, proteomics, metabolomics and hormonomics at several timepoints during and after stress treatments. Additionally, critical metabolites of tuber samples were analysed at the end of the stress period. Integrative analysis of multi-omics data was performed using a bioinformatic pipeline, which was established here, based on machine learning and knowledge networks. Overall, waterlogging had the most immediate and dramatic effects on potato plants, interestingly activating ABA-responses similar to drought stress. In addition, we observed distinct stress signatures at multiple molecular levels in response to heat or drought and to a combination of both. In response to all treatments, we found a downregulation of photosynthesis at different molecular levels, an accumulation of minor amino acids and diverse stress induced hormones. Our integrative multi-omics analysis provides global insights into plant stress responses, facilitating improved breeding strategies towards climate-adapted potato varieties. One Sentence SummaryIntegrated multi-omics analysis of high-throughput phenotyping in potato reveals distinct molecular signatures of acclimation to single and combined abiotic stresses related to climate change.

plant biology↗

bioRxiv2023

Reducing the vicissitudes of heterologous prochiral substrate catalysis by alcohol dehydrogenases through machine learning algorithms

Alcohol dehydrogenases (ADHs) encompass three distinctive superfamilies: medium-chain dehydrogenase (MDRs), short-chain dehydrogenase (SDRs), and iron-containing alcohol dehydrogenases. MDRs and SDRs have pivotal roles in converting pro-pharmaceutical ketones into chiral alcohols, serving as active pharmaceutical intermediate catalysts in industries. Nevertheless, the pursuit of aligning enzymes to a one enzyme-one substrate paradigm is intricate and resource-intensive. This study undertook the catalysis of 284 antibacterial ketone intermediates, yielding distinct patterns for both MDRs and SDRs. We endeavored to leverage machine learning to discriminate between compounds subjected to the influence of these superfamilies. To this end, we curated a dataset comprising 33 features, encompassing 4 descriptors for each compound. Subsequently, an ensemble of machine learning techniques, including Partial Least Squares (PLS) regression, k-Nearest Neighbors (kNN) regression, and Support Vector Machine (SVM) regression, was harnessed. Furthermore, the assimilation of Principal Component Analysis (PCA) augmented precision and accuracy, refining compound classification and intensifying differentiation and demarcation within diverse compound classes. As such, this classification strategy emerged as a potent approach for discerning substrates amenable to diverse alcohol dehydrogenases, thereby mitigating the reliance on high-throughput screening in identifying the optimal enzyme for specific substrate preferences.

biochemistry↗

bioRxiv2022

Identification and structural modeling of the chlamydial RNA polymerase omega subunit

Gene transcription in bacteria is carried out by the multisubunit RNA polymerase (RNAP), which is composed of a catalytic core enzyme and a promoter-recognizing {sigma} factor. RNAP core enzyme comprises two subunits, one {beta} subunit, one {beta} s subunit, and one {omega} (omega) subunit. Across multiple bacterial taxa, the RNAP {omega} subunit plays critical roles in the assembly of RNAP core enzyme and in other cellular functions, including regulation of bacterial growth, stress response, and biofilm formation. However, for several intracellular bacterium, including the obligate intracellular bacterium Chlamydia, no RNAP {omega} subunit previously has been identified. Here, we report the identification of Chlamydia trachomatis hypothetical protein CTL0286 as the chlamydial RNAP {omega} ortholog, based on sequence, synteny, and AlphaFold and AlphaFold-Multimer three-dimensional-structure predictions. We conclude that CTL0286 functions as the previously missing chlamydial {omega} ortholog. Extensions of our analysis indicate that all obligate intracellular bacteria have {omega} orthologs. IMPORTANCEChlamydiae are common mammalian pathogens. Chlamydiae have a unique developmental cycle characterized with an infectious but nondividing elementary body (EB), which can temporarily survive outside host cells, and a noninfectious reticulate body (RB), which replicates only intracellularly. Chlamydial development inside host cells can be arrested during persistence in response to adverse environmental conditions. Transcription plays a central role in the progression of the chlamydial developmental cycle as well as entry into and recovery from persistence. The identification of the elusive {omega} subunit of chlamydial RNAP makes possible future study of its regulatory roles in gene expression during chlamydial growth, development, and stress responses. This discovery also paves the way to prepare and study the intact chlamydial RNAP and its interactions with inhibitors in vitro.

molecular biology↗

bioRxiv2021

ZeBox: A novel non-intrusivecontinuous-use technology to trap and killairborne microbes

Preventing nosocomial infection is a major unmet need of our times. Existing air decontamination technologies suffer from demerits such as toxicity of exposure, species specificity, noxious gas emission, environment-dependent performance and high power consumption. Here, we present a novel technology called "ZeBox" that transcends the conventional limitations and achieves high microbicidal efficiency. In ZeBox, a non-ionizing electric field extracts naturally charged microbes from flowing air and deposits them on engineered microbicidal surfaces. The surfaces three dimensional topography traps the microbes long enough for them to be inactivated. The electric field and chemical surfaces synergistically achieve rapid inactivation of a broad spectrum of microbes. ZeBox achieved near complete kill of airborne microbes in challenge tests (5-9 log reduction) and >90% efficiency in a fully functional stem cell research facility in the presence of humans. Thus, ZeBox fulfills the dire need for a real-time, continuous, safe, trap-and-kill air decontamination technology.

microbiology↗

bioRxiv2021

Steps to (s)-stereoisomers: Rationalization of a standard Short-chain dehydrogenase for the reduction of multiple pharmaceutical ketone intermediates

Short-chain dehydrogenases/reductases (SDRs) are a convenient class of enzymes used to synthesize enantiopure alcohols. Several studies describe native or engineered SDRs for converting substrates of interest using cost and time-intensive high-throughput approaches. The classification of SDRs is based on chain length and cofactor binding site. Of these, the shorter Classical and the longer Extended enzymes participate in ketoreduction. However, comparative analysis of various modelled SDRs reveals a length independent conserved N-terminal Rossmann fold and a variable C-terminus region for both types. The general hypothesis is that the latter domain influences the enzymes flexibility that may affect the observed promiscuity of the enzyme. We have used a machine learning algorithm on this flexible domain to build a rationale to screen promiscuous candidates. We have built a data set consisting of physicochemical properties derived from the amino-acid composition of enzymes to select closely associated promiscuous mesophilic enzymes. The resulting in vitro studies on pro-pharmaceutical substrates illustrate a direct correlation between the C-terminal lid-loop structure, enzyme melting temperature and the turnover number. We present a walkthrough for exploring promiscuous SDRs for catalyzing enantiopure alcohols of industrial importance.

biochemistry↗

bioRxiv2019

Maximization of non-nitrogenous metabolite production in E. coli using population systems biology

The E. coli metabolome is an interconnected set of enzymes that has measurable kinetic parameters ascribed for the production of most of its metabolites. Flux Balance Analysis (FBA) or Ordinary Differential Equation (ODE) models are used to increase product yield using defined media. However, they either give a range (FBA) or exact amount (ODE) of metabolite yield which isnt true as the transcriptome diversity of individual cells isnt considered. We formulate the metabolic-behaviour of individual cells by using a POpulation SYstems-Biology ALgorithm (POSYBAL) which predicts multiple-gene knockouts for increasing industrially relevant metabolites. We validate this prediction for producing isobutanol (Heterogenous metabolite) and shikimate (Homogenous metabolite) where, the product-yield was increased by 40 times (~2000 ppm) and 42 times (~3000 ppm) respectively. Also, we introduce a nitrogen-swap in standard media to its low-nitrogen counterpart during post-growth phase to redistribute flux towards non-nitrogenous pathways for increasing overall product-yield. Further, our model shows growth-phase diversity in bacterial population even under normal glucose-uptake, portraying a real-world scenario of diverse and robust environment thus, making it evolutionarily favourable to threats such as anti-bacterial attack.

bioengineering↗

bioRxiv2018

Genomic footprints of repeated evolution of CAM photosynthesis in tillandsioid bromeliads

The adaptive radiation of Bromeliaceae (pineapple family) is one of the most diverse among Neotropical flowering plants. Diversification in this group was facilitated by several key innovations including the transition from C3 to CAM photosynthesis. We used a phylogenomic approach complemented by differential gene expression (RNA-seq) and targeted metabolite profiling to address the patterns and mechanisms of C3/CAM evolution in the extremely species-rich bromeliad genus Tillandsia and related taxa. Evolutionary analyses at a range of different levels (selection on protein-coding genes, gene duplication and loss, regulatory evolution) revealed three common themes driving the evolution of CAM: response to heat and drought, alterations to basic carbohydrate metabolism, and regulation of organic acid storage. At the level of genes and their products, CAM/C3 shifts were accompanied by gene expansion of a circadian regulator, re-programming of ABA-related gene expression, and adaptive sequence evolution of an enolase, effectively linking carbohydrate metabolism to ABA-mediated stress response. These changes include several pleiotropic regulators, which facilitated the evolution of correlated adaptive traits during a textbook adaptive radiation.

genomics↗