Biology subjects

Mukherjee, S.

Publications and source records attributed to Mukherjee, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Insights into the mechanism of succinimide formation in an archaeal glutaminase.

Succinimide (SNN), an intermediate formed during asparaginyl deamidation or aspartyl dehydration in proteins, is generally hydrolysis-prone, leading to isomerization to L/D /{beta}-aspartyl residue, with the latter being considered deleterious to protein structure and function. An unusually stable SNN-mediated conformational rigidity through restriction of the backbone dihedral angle, {psi}, enhances the thermostability of glutamine amidotransferase (GATase) from Methanocaldococcus jannaschii (Mj). Although several structural features involved in maintaining a stable SNN and imparting SNN-mediated thermostability have been identified in MjGATase, the residues in the protein that catalyse the rapid and complete conversion of Asn109 to SNN remain unknown. Here, we investigated several site-directed mutants of MjGATase for their ability to retain Asn109 side chain in the unmodified form. Mass spectrometric analysis of 10 single mutants enabled the identification of residues that impacted the proportion of SNN and Asn population in the protein sample. This led to the generation of two double mutants that retained intact Asn109 side chain as observed in the mass spectra and crystal structures. These mutants with intact Asn residue at position 109, displayed lower thermal stability than the protein with the SNN modification. Further understanding of the deprotonation mechanism was addressed using QM/MM MD metadynamics simulations. HighlightsO_LIStable succinimide (SNN) arising from deamidation of Asn109 residue imparts hyperthermostability to MjGATase. C_LIO_LIExamination of the structure of MjGATase suggests neighbouring residues playing possible roles in deamidation and cyclization. C_LIO_LIExamination by LC-MS of single site-directed mutants of residues contacting SNN revealed varied levels of intact Asn109 enabling generation of double mutants with complete absence of deamidation. C_LIO_LIPresence of intact Asn109 confirmed by X-ray crystallography highlights the role of Y158, D110, and K151 in mediating SNN formation. C_LIO_LIQM/MM MD metadynamics simulations support experimental findings. C_LI

biochemistry↗

bioRxiv2025

A switch from histone methyltransferase-EZH2 to demethylase KDM6A activity marks reinitiation of proliferation of drug treated colorectal cancer cells

Colorectal cancer (CRC) is one of the deadliest cancers, ranking third in cancer incidence worldwide. These tumor cells often adopt unique strategies under drug stress to attain a reversible drug-tolerant state and evade cell death. However, the molecular adaptations associated with this transitory emergence of the drug-tolerant state remain elusive. Herein, epigenetic alterations often dictate such reversible dynamic changes, and this study aims to characterize the role of specific epigenetic modifiers governing CRC cell survival under drug pressure and their subsequent relapse. We observed that under drug stress there is a drastic increase in the histone-repressive mark-H3K27me3, linked to an enhanced expression of EZH2 driving transcriptional inhibition of cell proliferation-associated genes and a proliferative arrest. Interestingly, drug-induced oxidative stress increased the expression of the P65 protein, which was found to interact and regulate EZH2 expression. Quenching of ROS, drug vacation, or P65 inactivation compromised EZH2 activity concurrent with a re-initiation of cell proliferation. Interestingly, this reversal to proliferative state was associated with an elevated activity of the histone lysine demethylase-KDM6A. The promoter elements of the proliferative genes were now occupied by KDM6A instead of EZH2. Accordingly, a genetic knockdown or pharmacological inhibition of KDM6A in vitro not only resulted in increased cell death but also prevented emergence of the re-proliferative CRC cells. Furthermore, KDM6A inhibition in combination with chemotherapy drug, resulted in an increased tumor regression in vivo. Our study thus highlights the importance of KDM6A as a therapeutic target in preventing CRC growth and relapse which can have future therapeutic implications.

cancer biology↗

bioRxiv2025

Non-Optimal Codon Usage Shapes Cell Cycle Regulators: Codon Optimization Studies on CDK1 and NUF2

The expression and functions of genes are largely dependent on genome integrity and stability. Codon usage plays a significant role in maintaining stability and functions of genes. Perturbation in codon sequence can lead to functional and structural dysfunction of a gene. In our study, we performed the codon usage analyses of cell cycle-dependent genes. Various codon usage parameters analyzed using nucleotide compositions like RSCU, ENC, and GC analyses showed that cell cycle dependent genes follow non-optimal codon usage. Genes preferred AT-rich ending over GC-rich ending, thereby suggesting preference for non-optimal codons. Neutrality and parity plot showed that the codon preference is a result of mutation selection pressure. To study the codon usage implications, we optimized the codons of cell cycle dependent genes (CDK1 and NUF2) to study their effects on cell cycle and apoptosis in vitro. We observed that codon optimization alters the cell cycle length in cell cycle-dependent genes impacting cell fate and survival. Our studies revealed that codon usage preferences directly affect the stability of both mRNA and proteins. Specifically, genes and proteins with non-optimal codons exhibited reduced stability compared to their optimized counterparts, suggesting critical implications for cell cycle regulation and apoptosis.

molecular biology↗

bioRxiv2025

LncRNA YIYA enhances pancreatic cancer proliferation under high-glucose conditions through RAS and PKM2 mediated metabolic reprogramming that reinforces the Warburg phenotype

Diabetes and the resulting hyperglycemia are metabolic complications frequently linked to pancreatic cancer (PC). In this study, we observe that the long non-coding RNA (lncRNA)-YIYA, which resides in a genomic region (1q32), frequently altered in various cancers, is overexpressed under conditions of chronic or intermittent high glucose (HG; 25 mM) compared to normal glucose (NG; 5.5 mM) in pancreatic ductal adenocarcinoma (PDAC) cells. It plays a pivotal role in regulating cellular metabolism-linked proliferation of PDAC cells, both under 2D and 3D conditions. Analysis of clinical datasets suggested that patients with elevated YIYA expression generally experience reduced survival in pancreatic cancer. Mechanistically, YIYA was found to regulate cellular energy metabolism and promote a Warburg phenotype, thereby facilitating the rapid proliferative status of PDAC cells. YIYA-mediated effects were found to be dependent on KRAS. Interestingly, the RIP assay revealed that YIYA interacts not only with KRAS but also with an important enzyme catalyzing the final step of the biochemical process, glycolysis, pyruvate kinase M2 (PKM2). YIYA was found to be predominantly localised in the cytoplasm, protecting the stability of the KRAS protein under a hyperglycaemic state. Importantly, YIYA knockdown enhanced autophagy-mediated degradation of KRAS. Our study is the first to identify YIYA as a glucose-responsive lncRNA in PDAC cells, and to reveal a novel YIYA-mediated connection between oncogenic KRAS signalling and metabolic reprogramming. Targeting YIYA represents a promising therapeutic strategy by disrupting the KRAS-PKM2-Warburg axis, thereby sensitizing PDAC cells. Graphical abstracts figure: Proposed model illustrating the effect of hyperglycemia on lncRNA YIYA-mediated regulation of KRAS signaling and metabolic reprogramming in pancreatic cancerUnder hyperglycemic conditions, elevated glucose uptake through GLUT (Glucose Transporter) enhances glycolytic flux, leading to increased levels of PEP (Phosphoenolpyruvate) and activation of PKM2 (Pyruvate Kinase M2), which results in increased pyruvate flux toward the LDH (Lactate Dehydrogenase) pathway and subsequent increased lactate production, promoting the Warburg effect. Downregulation of MPC (Mitochondrial Pyruvate Carrier) also supports reduced shuttling of pyruvate towards the TCA (Tricarboxylic Acid) cycle. On the other hand, constitutively activated master regulator KRAS activates the downstream proliferative signalling via AKT and other DTs (Downstream targets), which upregulates various genes, including lncRNA YIYA aka LINC00538. YIYA exists in a functional complex with KRAS and PKM2, further reinforcing glycolytic and proliferative signalling. Additionally, YIYA suppresses autophagy-mediated degradation of KRAS. Together, these events contribute to hyperglycemia-driven epigenetic changes, metabolic reprogramming, and tumor progression in pancreatic cancer cells. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/685546v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@13d271org.highwire.dtl.DTLVardef@15d01fcorg.highwire.dtl.DTLVardef@12d7225org.highwire.dtl.DTLVardef@a11c5e_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Leveraging death of drug-sensitive cancer cells to promote immune-mediated bystander killing of subclones of drug-resistant tumor cells

The response of lung cancer patients to drugs targeting the G12C mutant form of KRAS is limited by the development of resistance through multiple mechanisms. In order to achieve lasting benefit with these therapies, effective strategies for tackling the evolution of drug resistance are required. We have developed a preclinical model system to mimic the development of resistance to KRAS G12Ci inhibitors (G12Ci) such as adagrasib and RMC-4998. Treatment of tumours containing a minor subpopulation of resistant cancer cells with G12Ci leads to their rapid outgrowth to replace the drug-sensitive cells within a few weeks. However, when combined with therapies that, at least in part, target the immune response, such as SHP2 inhibitors or PD-1 blockade, drug-resistant cells can be eliminated, even by drug combinations that do not impact their growth in the absence of drug-sensitive cells. This bystander killing of drug-resistant cells when drug-sensitive cells are targeted is dependent on an intact adaptive immune system. Mechanistically, these combination therapies lead to profound remodelling of the tumour immune microenvironment, with influx of T cells recognising a tumour associated antigen shared between drug-resistant and drug-sensitive cancer cells. Promotion of immune-mediated bystander killing of drug-resistant cells may provide a paradigm for tackling the problem of drug resistance in cancer more broadly.

cancer biology↗

bioRxiv2025

AI-based supervised treatment response prediction from tumor transcriptomics: A large-scale pan-cancer study

Precision oncology aims to guide treatment decisions using biomarkers. While DNA-based panels are increasingly applied, RNA transcriptomics remain underused due to limited datasets and the absence of robust models. We assembled the largest transcriptomic resource for drug response prediction to date, spanning 91 cohorts, 5,675 patients, nine cancer types, and six frontline therapies: anti-PD-1/PD-L1 immune-checkpoint inhibitors, trastuzumab, bevacizumab, BRAF inhibitors, paclitaxel, and FAC/FEC (Fluorouracil-Adriamycin-Cyclophosphamide/Fluorouracil-Epirubicin-Cyclophosphamide) chemotherapy. We developed EXPRESSO (EXpression-Profile-RESponSe-Optimizer), a supervised machine-learning framework that predicts treatment response from pre-treatment transcriptomes by integrating drug targets and context-specific biomarkers. EXPRESSO achieves mean ROC-AUCs of 0.62-0.73 and median odds ratios of 2.4-4.6 across therapies, outperforming 20 published transcriptomic signatures and other machine learning methods. Prospective validation on 22 independent cohorts confirms that performance generalizes beyond cross-validation. The EXPRESSO signature additionally stratifies progression-free survival in immune checkpoint blockade-treated cohorts, demonstrating prognostic value beyond binary response prediction. Robustness analysis reveals that predictive performance plateaued for some therapies with increasing training cohorts but continued to improve for others. These findings suggest inherent limits of supervised brute-force learning for certain treatments, but additional data and deeper mechanistic modeling may further enhance transcriptomics-based predictors. SIGNIFICANCEEXPRESSO forms the next step in studying the feasibility of harnessing bulk transcriptomic data to inform therapeutic decision-making, advancing the role of transcriptomics from exploratory biomarker discovery to actionable predictive modeling.

cancer biology↗

bioRxiv2025

velotest: Statistical assessment of RNA velocity embeddings reveals quality differences for reliable trajectory visualizations

Contemporary single-cell RNA-sequencing studies typically use RNA velocity analyses to investigate cellular dynamics. Commonly, RNA velocities are assessed with two-dimensional projections. Although it is well established that nonlinear embeddings of gene expression data cannot comprehensively preserve the structure of the original high-dimensional data across scales, there is no tool that systematically assesses and quantifies the faithfulness of velocity embeddings. This situation potentially leads to misleading velocity visualizations and putative cell state transitions. To this end, we introduce velotest, a cell-level statistical test that quantifies the faithfulness of a velocity embedding with respect to its high-dimensional counterpart. Applying velotest across multiple datasets and embedding methods, we find strong differences in the embedding qualities between embedding methods, datasets, and regions in individual datasets. velotest thus provides an essential validation step and enables researchers to select a suitable visualization of high-dimensional velocities, ensuring that hypotheses drawn from velocity projections are grounded in accurately represented dynamics.

bioinformatics↗

bioRxiv2025

From human joints to bioreactor setups: quantifying mechanical stimuli in cartilage physiology and regeneration

ObjectiveBioreactors are widely used to apply mechanical stimuli to osteochondral (OC) explants and cartilage tissue-engineered (TE) constructs, yet their ability to replicate native joint mechanics is not well quantified. This study benchmarks common bioreactor loading protocols against a finite element (FE) model of the human knee during gait, enabling direct comparison to physiologically relevant mechanical parameters. MethodsA validated FE model of the human knee joint simulating the stance phase of gait was used to characterize physiological mechanical conditions, including maximum principal stress, maximum shear strain, pore pressure, and fluid velocity. These outputs were compared with those generated by representative bioreactor setups: dynamic unconfined compression (10-30%) and combined compression (10%) with ball rotation ({+/-}25{degrees}), which were applied to both OC plugs and TE constructs, and hydrostatic pressure (0.5-50 MPa), which was applied only to TE constructs. FE simulations evaluated spatial and magnitude-based agreement with native cartilage mechanics. ResultsIn OC plugs, 10% unconfined compression generated maximum principal stresses ([~]7.5 MPa) and pore pressures ([~] 4 MPa) closely matching native tissue ([~] 4.5 MPa and [~]5 MPa, respectively). In TE constructs, even at 30% unconfined strain, maximum principal stresses and pore pressures remained around 100 times lower than physiological values, while fluid velocities were 10 times higher. Hydrostatic loading of TE constructs at 5 MPa matched native pore pressures ([~]5 MPa) but induced negligible strains. ConclusionsThis study provides a quantitative framework for evaluating how well bioreactor loading regimens replicate physiological joint mechanics. The findings offer actionable guidance to experimentalists for selecting bioreactor conditions based on specific mechanical targets. This can lead to more effective design of in vitro cartilage studies and support translational strategies in cartilage repair and tissue engineering.

bioengineering↗

bioRxiv2025

Adipose Tissue Overexpression of Nicotinamide Phosphoribosyltransferase Prevents Metabolic Dysfunction in Obese Mice

Nicotinamide adenine dinucleotide (NAD+) is a vital coenzyme and a central factor in energy metabolism. Nicotinamide phosphoribosyltransferase (NAMPT) maintains the cellular NAD+ pool by synthesizing the NAD+ precursor, nicotinamide mononucleotide (NMN), and diminished adipocyte NAMPT activity has been implicated in aging- and obesity-related metabolic dysfunction. Herein, we examined the effects of overexpressing or knocking out NAMPT in adipocytes on metabolic dysfunction and interorgan communication in mice. We generated new adipocyte-specific NAMPT overexpressing(ANOV) mice model. Male ANOV mice are protected from diet-induced metabolic dysfunction including adipose tissue inflammation, glucose intolerance, and insulin resistance. In contrast female ANOV mice were less protected from metabolic dysfunction, possibly due to higher endogenous expression of NAMPT in WT female mice. Livers of ANOV mice showed improved insulin signaling, increased NAD content, and reduced steatosis, suggesting that NAMPT regulates interorgan communication between adipocytes and hepatocytes. Extracellular vesicles (EV) isolated from ANOV mice enhanced insulin signaling in HepG2 cells and improved glucose tolerance in WT obese mice. In contrast, EV from ANKO mice suppressed HepG2 insulin signaling and inhibition of EV release improved glucose tolerance in ANKO female mice. Collectively, these data highlight a novel mechanism by which adipocyte NAD+ metabolism regulates systemic metabolic dysfunction via EVs.

physiology↗

bioRxiv2025

Distribution of big tau isoforms in the human central and peripheral nervous system

ObjectiveTau is widely studied in the field of neurodegenerative disease research, yet most work has focused on canonical brain tau isoforms. A longer isoform, "big tau," produced by inclusion of exon 4a, is expressed in the peripheral nervous system (PNS) and select central nervous system (CNS) regions. We sought to characterize big tau molecular composition, anatomical distribution, and relevance to neurodegenerative disease. MethodsMass spectrometry was used to sequence big tau and map its distribution across the human nervous system. Postmortem samples included brain tissue from Alzheimers disease (AD), amyotrophic lateral sclerosis (ALS), and controls; spinal cord from ALS and controls; and peripheral nerves. Big and canonical ("small") tau isoforms were also quantified in cerebrospinal fluid (CSF) from young controls and participants stratified by amyloid status and cognitive impairment. ResultsHuman big tau results from insertion of either 355 or 251 amino acids encoded by exon 4a-long and exon 4a-short, respectively. Alternative splicing of exons 2, 3, and 10 generates multiple big tau isoforms. Total tau levels were [~]1000-fold higher in brain than in the PNS; however, the relative abundance of big tau increased from the CNS to the PNS, comprising 50 % of the total tau in the periphery and exhibiting considerable regional heterogeneity in the brain ([~] 1 % of total tau). In CSF, big tau levels were unchanged by amyloid abnormalities or cognitive impairment, whereas canonical tau increased with AD-related pathology. InterpretationBig tau represents a distinct tau population enriched in the PNS and largely uncoupled from disease-associated changes in brain-derived tau, suggesting that distinguishing big tau from canonical tau may improve interpretation of tau biomarkers and help differentiate CNS neurodegeneration from peripheral nerve pathology.

neuroscience↗

bioRxiv2025

Proteome integral solubility alteration assay for monitoring antibody-antigen cell interactions

The Proteome Integral Solubility Alteration (PISA) assay is commonly used to identify and characterize interactions between small molecules and the cellular proteome. In this study, a modified PISA approach identified tumor necrosis factor alpha (TNF) as the antigen of the monoclonal antibody infliximab in activated monocytes - uniquely among [~]8,000 cellular proteins. These results highlight the potential of PISA-based analysis not only for monitoring antibody-antigen interactions in therapeutic development, but also for identifying new antigens and characterizing the initial effector functions of antibodies within complex proteome environments. TeaserModified PISA pinpointed TNF- as Infliximabs antigen among 8000 proteins, highlighting broad potential for therapeutic antigen studies.

molecular biology↗

bioRxiv2025

A conserved Hsp70 phosphorylation regulates cell cycle progression after DNA damage

Hsp70s are essential molecular chaperones that are increasingly recognized to be regulated by post-translational modifications. Here, we show that phosphorylation of a conserved threonine (T495), previously shown to be exploited by a Legionella pneumophila kinase to inhibit Hsp70, occurs endogenously in human cells in response to DNA damage, particularly when base excision repair is overburdened. This modification is cell cycle dependent, and in yeast, phosphomimetic or phosphonull Hsp70 variants disrupt G1/S progression under normal and DNA-damaging conditions. Biochemically, the phosphomimetic T495E mutation locks Hsp70 in an open-like conformation without blocking substrate engagement. Together, our results reveal a conserved mechanism by which dynamic Hsp70 phosphorylation regulates the G1/S transition, and delays cell cycle progression during DNA damage, highlighting how pathogen-derived insights can uncover fundamental cell biology principles.

cell biology↗

bioRxiv2025

SynGlue: AI-Driven Designer for Clinically Actionable Multi-Target Therapeutics

The rational design of protein degraders, such as proteolysis-targeting chimeras (PROTACs), requires the simultaneous optimization of multiple molecular properties, a complex challenge that limits efficient discovery. Here, we introduce SynGlue, a generative artificial intelligence (AI) framework that addresses this challenge through two core modules: data-driven, leveraging large-scale protein-ligand intelligence, and structure-guided, for physics-aware molecular design. SynGlue harness MagnetDB, a curated database of 6.37 million experimental protein-ligand interactions, and couples it with deep learning models that quantitatively predict degradation potency (DC50), maximal degradation (Dmax), and guide ternary-complex-compatible linker design. Benchmarked against 6,935 compounds, SynGlue demonstrates superior performance in relevant pharmacology prediction. To validate SynGlue, we engineered degraders for BRD4 and GSPT1. Our data-driven design for BRD4 yielded compounds with novel warhead scaffolds (<50% warhead similarity with known PROTACs), which proved to be potent degraders in vitro (DC50 = 0.19 nM) and efficacious in vivo in mouse models. Independently, our structure-guided de novo design for GSPT1 produced ultrapotent degraders (DC50 {approx} 0.0011 M) that are also effective both in vitro and in vivo, uncovering a new oncogenic dependency. By unifying data-driven and physics-aware design, SynGlue establishes a generalizable AI framework for the rapid development of clinically relevant protein degraders, with principled extension to other multi-target modalities.

bioinformatics↗

bioRxiv2025

Cisplatin-induced oxidative stress regulates YAP to modulate epigenome promoting survival of osteosarcoma cells

The widely used chemotherapeutic drug cisplatin (CDDP) is an integral part of the pre-operative chemotherapy protocol for high-grade osteosarcoma (OS). However, despite an aggressive treatment regimen, drug refractoriness is a major hindrance to successful therapy. We previously identified key transcriptomic alterations essential for the survival of OS cells following CDDP exposure. In the present study, we further demonstrate that CDDP treatment resulted in a ROS-dependent enrichment of the repressive histone mark H3K27me3 at the upstream promoter regions of growth-promoting genes such as CCNA2, and on the promoter of the negative regulator of Yes-Associated Protein (YAP)-LATS1, thereby contributing to their transcriptional repression. This was associated with a growth arrest, and quenching of ROS with N-acetyl cysteine (NAC) reversed it. Importantly, repression of LATS1 led to an increased nuclear localization of YAP, while pharmacological or genetic ablation of YAP reduced CDDP-mediated induction of repressive marks. YAP was further found to co-localize and co-immunoprecipitate with the Polycomb Repressive Complex 2 (PRC2) catalytic member-the histone methyl transferase-EZH2, indicating its putative role in mediating transcriptional repression. In lieu of the above, inhibition of YAP or reversal of the repressive chromatin state using a histone deacetylase (HDAC) inhibitor sensitized OS cells to a low-dose CDDP treatment as well. Overall, the present study demonstrates an interplay between oxidative stress, epigenetics, and YAP in modulating OS cell fate post CDDP exposure.

cancer biology↗

bioRxiv2025

Optimized ChIP-exo for mammalian cells and patterned sequencing flow cells

By combining chromatin immunoprecipitation (ChIP) with an exonuclease digestion of protein-bound DNA fragments, ChIP-exo characterizes genome-wide protein-DNA interactions at near base-pair resolution. However, the widespread adoption of ChIP-exo has been hindered by several technical challenges, including lengthy protocols, the need for multiple custom reactions, and incompatibilities with recent Illumina sequencing platforms. To address these barriers, we systematically optimized and adapted the ChIP-exo library construction protocol for the unique requirements of mammalian cells and current sequencing technologies. We introduce a Mammalian-Optimized ChIP-exo (MO-ChIP-exo) protocol that builds upon previous ChIP-exo protocols with systematic optimization of crosslinking, harvesting, and library construction. We validate MO-ChIP-exo by comparing it to previously published ChIP-exo protocols and demonstrate its adaptability to both suspension (K562) and adherent (HepG2, mESC) cell lines. This improved protocol provides a more robust and efficient method for generating high-quality ChIP-exo libraries from mammalian cells. SUMMARYChIP-exo is a genome-wide protein-DNA binding assay with unrivalled resolution, but its widespread adoption has been hindered by technical challenges, particularly when applied to mammalian cells or when used with recent sequencing platforms. We introduce a Mammalian-Optimized ChIP-exo (MO-ChIP-exo) protocol with key modifications that overcome previous technical hurdles. We demonstrate that our optimized protocol produces high-quality data comparable to previously published protocols and is adaptable for use with both suspension (K562) and adherent (HepG2, mESC) cell lines.

genomics↗

bioRxiv2025

Covalent Drug binding in Live Cells Monitored by Mid-IR Quantum Cascade Laser Spectroscopy: Photoactive Yellow Protein as a Model System

The detection of drug-target interactions in live cells enables analysis of therapeutic compounds in a native cellular environment. Recent advances in spectroscopy and molecular biology have facilitated the development of genetically encoded vibrational probes like nitriles that can sensitively report on molecular interactions. Nitriles are powerful tools for measuring electrostatic environments within condensed media like proteins, but such measurements in live cells have been hindered by low signal-to-noise ratios. In this study, we design a spectrometer based on a double-beam quantum cascade laser (QCL)-based transmission infrared (IR) source with balanced detection that can significantly enhance sensitivity to nitrile vibrational probes embedded in proteins within cells compared to a conventional FTIR spectrometer. Using this approach, we detect small-molecule binding in E. coli, with particular focus on the interaction between para-coumaric acid (pCA) and nitrile-incorporated photoactive yellow protein (PYP). This system effectively serves as a model for investigating covalent drug binding in a cellular environment. Notably, we observe large spectral shifts of up to 15 cm-1 for nitriles embedded in PYP between the unbound and drug-bound states directly within bacteria, in agreement with observations for purified proteins. Such large spectral shifts are ascribed to the changes in the hydrogen-bonding environment around the local environment of nitriles, accurately modeled through high-level molecular dynamics simulations using the AMOEBA force field. Our findings underscore the QCL spectrometers ability to enhance sensitivity for monitoring drug-protein interactions, offering new opportunities for advanced methodologies in drug development and biochemical research. Authors are required to submit a graphic entry for the Table of Contents (TOC) that, in conjunction with the manuscript title, should give the reader a representative idea of one of the following: A key structure, reaction, equation, concept, or theorem, etc., that is discussed in the manuscript. Consult the journals Instructions for Authors for TOC graphic specifications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/670201v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@13bd30forg.highwire.dtl.DTLVardef@9db2bcorg.highwire.dtl.DTLVardef@141590forg.highwire.dtl.DTLVardef@13dfcf2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

CRISPR/Cas9-mediated identification of human macrophage SphK1 as druggable target for development of anti-leishmanial chemotherapeutics

Sphingosine-1-phosphate (S1P) is a bioactive lipid that regulates apoptosis, autophagy, inflammation, and intracellular pathogen survival. While S1P signaling has been implicated in Leishmania donovani infection, the specific roles of its biosynthetic enzymes Sphingosine kinases SphK1 and SphK2 in host macrophage remains poorly defined. Here, we delineate the role of SphK1 in modulating host-pathogen interactions using CRISPR/Cas9-mediated knockout and pharmacological inhibition in THP-1 macrophages. We generated and validated CRISPR constructs targeting SphK1 (promoter, SBS, exon 6) and SphK2 (exon 3). SphK1 Knockout was confirmed at transcript and protein levels, accompanied by a marked reduction in SphK1 enzymatic activity and S1P levels. Functionally, SphK1 knockout macrophages exhibited decreased intracellular L. donovani burden, elevated TNF-, and reduced IL-10, and increased autophagic and apoptotic markers, suggesting a pro-inflammatory, cell-death-prone state. Pharmacological inhibition using the selective SphK1 inhibitor, PF-543 recapitulated these findings, showing reduced phosphorylated SphK1, enhanced p38MAPK activation, and augmented autophagy and apoptosis. Conversely, the SphK2 inhibitor ABC294640 had minimal effect, reinforcing the predominant role of SphK1. Together, our study identifies SphK1 as a critical host factor that facilitates L. donovani survival by modulating lysosomal stress, immune evasion, and cell fate pathways. Targeting SphK1-S1P signalling may offer a novel therapeutic approach for visceral leishmaniasis.

molecular biology↗

bioRxiv2025

What's next for Indian Ornithology? 101 key research questions

India has a rich history of ornithology, and bird research in this field has expanded considerably in recent decades, spurred by a growing number of birdwatchers and ornithologists. Despite this progress, critical gaps remain. This paper highlights key areas where further research is needed and identifies pressing questions that will shape Indian ornithology in the coming years. Drawing from diverse inputs, we present a curated list of 101 research questions spanning across the various disciplines in ornithology - Natural History, Physiology and Disease Ecology, Behaviour, Population and Community Ecology, Habitat Ecology, Macroecology and Biogeography, Population Genetics and Evolution, Applied/Economic Ornithology and Conservation. The list was compiled through a multi-stage process, starting with a public open call for questions, followed by review and curation by a smaller panel of subject specialists. Each question was independently scored by a panel of experts based on three criteria: generality, novelty, and relevance. To account for variation in scoring styles, scores were normalised using Z-scores. The top 101 research questions were then selected based on these standardised scores. Each question is accompanied by an annotation that describes the significance of the question, and highlights opportunities to address it. While our list of research questions highlights significant research priorities, it is not intended to be exhaustive. Rather, it reflects the perspectives of those involved in its curation, who deemed these questions particularly relevant and impactful towards advancing Indian ornithology. We expect these questions to spark new project ideas among students, researchers, and citizen scientists, while guiding funders, managers, and policymakers toward priority research areas.

ecology↗