Biology subjects

Chatterjee, P.

Publications and source records attributed to Chatterjee, P..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Optimizing PDIA1 Inhibition as a Strategy to Inhibit NLRP3 Inflammasome Activation and Activity

The NLRP3 inflammasome is a protein complex that promotes pro-inflammatory signaling as part of the innate immune response. Hyperactivation of the NLRP3 inflammasome has been implicated in many inflammatory and neurodegenerative diseases, leading to significant effort in developing strategies to limit its activation to intervene in these disorders. We previously showed that pharmacologic inhibition of the endoplasmic reticulum (ER)-localized protein disulfide isomerase PDIA1 suppresses NLRP3 activation and activity, identifying PDIA1 as a potential therapeutic target to mitigate hyperactive NLRP3 activity. Herein, we screen PDIA1 inhibitors to identify highly-potent compounds, including P1 and PACMA31, that pharmacologically target PDIA1 and block NLRP3 inflammasome assembly and activity. While sustained treatment with these PDIA1 inhibitors reduces THP1 viability, we show that acute treatment with these compounds is sufficient to both fully modify PDIA1 and inhibit NLRP3 inflammasome activity independent of any overt cellular toxicity. These results establish a treatment paradigm that can be exploited to develop highly-selective PDIA1 inhibitors to mitigate hyperactive NLRP3 inflammasome activity implicated in etiologically-diverse diseases.

biochemistry↗

bioRxiv2025

Macrophage ferroptosis inhibits Aspergillus conidial killing in lung transplantation

Immune suppression heightens the risk for fungal infections, but the mechanisms that result in clinical disease are poorly understood. Here we demonstrate that macrophage ferroptosis, an iron-dependent form of regulated cell death, inhibits Aspergillus fumigatus (Af) killing. In a mouse tracheal transplant model of Af infection, we observed an increase in macrophage lipid peroxidation, a decreased expression of negative ferroptosis regulators Gpx4 and Slc7a11, and an increase in positive regulators Ptgs2 and Nox2, relative to syntransplants. Depletion of macrophages in transplant recipients decreased Af invasion. In vitro, iron overload reduced macrophage viability and decreased their capability to kill Af spores, through a decrease in lysosomal acidification and lysosomal loss. Treatment with ferrostatin-1, a ferroptosis inhibitor, and deferasirox (an iron chelator) restored Af killing. Ferroptotic alveolar macrophages isolated from lung transplant patients also showed a decreased ability to kill Af spores and the patients bronchoalveolar lavage was characterized by higher iron levels and markers of ferroptotic stress compared to non-lung transplants. These characteristics were strongly correlated with a clinical history of fungal infections, independent of immune suppressive medications. Our findings indicate that macrophage ferroptosis augments the risk of invasive aspergillosis, representing a novel mechanism for host immune dysfunction. Graphical AbstractSchematic of proposed mechanism underlying ferroptosis induced immune dysregulation and increased Af invasion in lung transplantation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/643092v1_ufig1.gif" ALT="Figure 1"> View larger version (104K): org.highwire.dtl.DTLVardef@1112102org.highwire.dtl.DTLVardef@18e2ec1org.highwire.dtl.DTLVardef@19f9c5forg.highwire.dtl.DTLVardef@1d325e8_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

EVOFLOW-RNA: GENERATING AND REPRESENTINGNON-CODING RNA WITH A LANGUAGE MODEL

RNA plays a critical role across numerous biological functions. Recent advances in language modeling show promise with representing RNA, but the possibility of large-scale RNA design and optimization has not been fully explored. We propose EvoFlow-RNA, a bidirectional non-coding RNA language model leveraging a masked discrete diffusion model (MDM) formulation for both generative modeling and representation learning. EvoFlow-RNA bridges the gap between RNA sequence representation and design. It outperforms leading RNA models on three BEACON tasks critical to understanding RNA function, spanning from structure prediction to gene editing. For unconditional generation, it synthesizes diverse RNA sequences with native-like structural and binding properties. Additionally, EvoFlow-RNA can globally redesign aptamer sequences around preserved binding recognition sites with enhanced functionality. Our results demonstrate the effectiveness of EvoFlow-RNA in RNA modeling, highlighting the capability and potential of masked discrete diffusion for both recapitulating and enhancing existing RNAs.

synthetic biology↗

bioRxiv2025

Generative latent diffusion language modeling yields anti-infective synthetic peptides

Generative artificial intelligence (AI) offers a powerful avenue for peptide design, yet this process remains challenging due to the vast sequence space, complex structure-activity relationships, and the need to balance antimicrobial potency with low toxicity. Traditional approaches often rely on trial-and-error screening and fail to efficiently navigate the immense diversity of potential sequences. Here, we introduce AMP-Diffusion, a novel latent diffusion model fine-tuned on antimicrobial peptide (AMP) sequences using embeddings from protein language models. By systematically exploring sequence space, AMP-Diffusion enables the rapid discovery of promising antibiotic candidates. We generated 50,000 candidate sequences, which were subsequently filtered and ranked using our APEX predictor model. From these, 46 top candidates were synthesized and experimentally validated. The resulting AMP-Diffusion peptides demonstrated broad-spectrum antibacterial activity, targeting clinically relevant pathogens--including multidrug-resistant strains--while exhibiting low cytotoxicity in human cell assays. Mechanistic studies revealed bacterial killing via membrane permeabilization and depolarization, and the peptides showed favorable physicochemical profiles. In preclinical mouse models of infection, lead peptides effectively reduced bacterial burdens, displaying efficacy comparable to polymyxin B and levofloxacin, with no detectable adverse effects. This study highlights the potential of AMP-Diffusion as a robust generative platform for designing novel antibiotics and bioactive peptides, offering a promising strategy to address the escalating challenge of antimicrobial resistance.

microbiology↗

bioRxiv2025

Quorum sensing mediates morphology and motility transitions in the model archaeon Haloferax volcanii

Quorum sensing (QS) is a mechanism of intercellular communication that enables microbes to alter gene expression and adapt to the environment. This cell-cell signaling is necessary for intra- and interspecies behaviors such as virulence and biofilm formation. While QS has been extensively studied in bacteria, little is known about cell-cell communication in archaea. Here we established an archaeal model system to study QS. We showed that for Haloferax volcanii, the transition from motile rods to non-motile disks is dependent on a possibly novel, secreted small molecule present in cell-free conditioned medium (CM). Moreover, we determined that this putative QS molecule fails to induce the morphology transition in mutants lacking the regulatory factors, DdfA and CirA. Using quantitative proteomics of wild-type cells, we detected significant differential abundances of 236 proteins in the presence of CM. Conversely, in the {Delta}ddfA mutant, addition of CM resulted in only 110 proteins of significant differential abundances. These results confirm that DdfA is involved in CM-dependent regulation. CirA, along with other proteins involved in morphology and swimming motility transitions, is among the proteins regulated by DdfA. These discoveries significantly advance our understanding of microbial communication within archaeal species.

microbiology↗

bioRxiv2024

Programmable protein degraders enable selective knockdown of pathogenic β-catenin subpopulations in vitro and in vivo

Aberrant activation of Wnt signaling results in unregulated accumulation of cytosolic {beta}-catenin, which subsequently enters the nucleus and promotes transcription of genes that contribute to cellular proliferation and malignancy. Here, we sought to eliminate pathogenic {beta}-catenin from the cytosol using designer ubiquibodies (uAbs), chimeric proteins composed of an E3 ubiquitin ligase and a target-binding domain that redirect intracellular proteins to the proteasome for degradation. To accelerate uAb development, we leveraged a protein language model (pLM)-driven algorithm called SaLT&PepPr to computationally design "guide" peptides with affinity for {beta}-catenin, which were subsequently fused to the catalytic domain of a human E3 called C-terminus of Hsp70-interacting protein (CHIP). Expression of the resulting peptide-guided uAbs in colorectal cancer cells led to the identification of several designs that significantly reduced the abnormally stable pool of free {beta}-catenin in the cytosol and nucleus while preserving the normal membrane-associated subpopulation. This selective knockdown of pathogenic {beta}-catenin suppressed Wnt/{beta}-catenin signaling and impaired tumor cell survival and proliferation. Furthermore, one of the best degraders selectively decreased cytosolic but not membrane-associated {beta}-catenin levels in livers of BALB/c mice following delivery as a lipid nanoparticle (LNP)-encapsulated mRNA. Collectively, these findings reveal the unique ability of uAbs to selectively eradicate abnormal proteins in vitro and in vivo and open the door to peptide-programmable biologic modulators of other disease-causing proteins.

bioengineering↗

bioRxiv2024

SUV39H1 mediated regulation of KLF4 and KDM4A coordinate smooth muscle cell phenotypic plasticity

BackgroundReversible DNA methylation contributes to the phenotypic plasticity of vascular smooth muscle cells (VSMCs). This plasticity contributes to vascular growth remodeling, but also underlies cardiovascular pathologies, including intimal hyperplasia. We investigated the role of SUV39H1, a histone methyltransferase that generates the H3K9me3 repressive epigenetic mark, in VSMC plasticity MethodsWe applied knockdown, qPCR, western blotting, chromatin immunoprecipitation (ChIP) assays, and RNA-Seq in human coronary artery SMCs (hCASMCs), and murine carotid ligation to determine the role of SUV39H1 in VSMC plasticity. ResultsExpression of SUV39H1 and the H3K9me3 mark it generates increase, whereas the cognate H3K9me3 demethylase KDM4A decreases, over time during the progression of murine intimal hyperplasia following carotid artery ligation, with marked elevation of SUV39H1 and H3K9me in the neointima. SUV39H1 knockdown induced contractile genes and contractility while decreasing migration and proliferation in hCASMCs. Transcriptomic analysis confirmed that SUV39H1 promotes SMC dedifferentiation. SUV39H1 knockdown revealed that SUV39H1 promotes KLF4 upregulation by increasing KLF4 mRNA stability. PDGF-BB induced SUV39H1 expression and SUV39H1-dependent H3K9me3 modification of contractile gene promoters in hCASMC. SUV39H1 knockdown reduced the repressive H3K9me3 and 5mC marks but increased the activating H3K27Ac mark at these promoters. SUV39H1 knockdown also increased expression of KDM4A and its binding to contractile promoters, suggesting an opposing regulatory relationship between the writer and eraser of H3K9me3. ConclusionsWe identify SUV39H1 as an epigenetic regulator that promotes VSMC dedifferentiation by stabilizing KLF4 expression and by altering chromatin state. We report SUV39H1-dependent dynamic regulation of the repressive H3K9me3 mark at contractile gene promoters, and opposing regulation of the enzymes that write (SUV39H1) and erase (KDM4A) these marks during VSMC phenotypic switching. These studies suggest that coordinate regulation of both histone and DNA methylation contribute to VSMC phenotypic plasticity. HighlightsO_LIThe histone methyl transferase SUV39H1 is differentially regulated in VSMC phenotypic switching in culture and in vascular remodeling. SUV39H1 and the H3K9me3 mark it generates increase, whereas the cognate H3K9me3 eraser KDM4A decreases, during the progression of murine intimal hyperplasia. C_LIO_LISUV39H1 promotes PDGF-induced VSMC de-differentiation, stabilizing KLF4 mRNA. SUV39H1 opposes VSMC contractility and promotes proliferation and migration. C_LIO_LIPDGF-BB induces SUV39H1-dependent H3K9me3 marks at VSMC contractile gene promoters, and SUV39H1 loss of function alters multiple marks that govern chromatin accessibility at these promoters, with opposing effects on the repressive H3K9me3 and 5mC and activating H3K27Ac marks. C_LIO_LISUV39H1 generates H3K9me3 marks that are associated with silenced heterochromatin. We note dynamic regulation of this mark at VSMC contractile gene promoters, and opposing regulation of the enzymes that write (SUV39H1) and erase (KDM4A) these marks during VSMC phenotypic switching. C_LI

cell biology↗

bioRxiv2024

Intestinal Epithelial PTPN2 Limits Pathobiont Colonization by Immune-Directed Antimicrobial Responses

Background and AimsLoss of activity of the inflammatory bowel disease (IBD) susceptibility gene, protein tyrosine phosphatase non-receptor type 2 (PTPN2), is associated with altered microbiome composition in both human subjects and mice. Further, expansion of the bacterial pathobiont, adherent- invasive E. coli (AIEC), is strongly linked to IBD pathogenesis. The mechanism by which intestinal epithelial cells (IEC) maintain equilibrium between commensal microbiota and immune cells to restrict invading pathobionts is poorly understood. Here, we investigated the role of IEC-specific PTPN2 in regulating AIEC colonization. MethodsTamoxifen-inducible, intestinal epithelial cell-specific Ptpn2 knockout mice (Ptpn2{Delta}IEC) and control Ptpn2fl/fl mice were infected with either non-invasive E. coli K12, or fluorescent-tagged mAIEC (mAIECred) for four consecutive days or administered PBS. Subsequently, bacterial colonization in mouse tissues was quantified. mRNA and protein expression were assayed in intestinal epithelial cells (IECs) or whole tissue lysates by PCR and Western blot. Tissue cytokine expression was determined by ELISA. Intestinal barrier function was determined by in vivo administration of 4 kDa FITC-dextran (FD4) or 70kDa Rhodamine-B dextran (RD70) fluorescent probes. Confocal microscopy was used to determine the localization of tight-junction proteins. ResultsPtpn2{Delta}IEC mice exhibited increased mAIECred - but not K12 - bacterial load in the distal colon compared to infected Ptpn2fl/fl mice. The higher susceptibility to mAIECred infection was associated with altered levels of antimicrobial peptide (AMPs). Ileal RNA expression of the alpha-defensin AMPs, Defa5 and Defa6, as well as MMP7, was significantly lower in Ptpn2{Delta}IEC vs. Ptpn2fl/fl mice, after mAIECred but not K12 infection. Further, we observed increased tight junction-regulated permeability determined by elevated in vivo FD4 but not RD70 permeability in Ptpn2{Delta}IEC-K12 mice compared to their respective controls. This effect was further exacerbated in Ptpn2{Delta}IEC mAIEC-infected mice. Further, Ptpn2{Delta}IEC mice displayed lower IL-22, IL-6, IL-17A cytokine expression post mAIEC infection compared to Ptpn2fl/fl controls. Recombinant IL-22 reversed the FD4 permeability defect and reduced bacterial burden in Ptpn2{Delta}IEC mice post mAIEC challenge. ConclusionOur findings highlight that intestinal epithelial PTPN2 is crucial for mucosal immunity and gut homeostasis by promoting anti-bacterial defense mechanisms involving coordinated epithelial-immune responses to restrict pathobiont colonization.

immunology↗

bioRxiv2024

moPPIt: De Novo Generation of Motif-Specific Binders with Protein Language Models

Targeting specific functional motifs, whether conserved viral epitopes, intrinsically disordered regions (IDRs), or fusion breakpoints, is essential for modulating protein function and protein-protein interactions (PPIs). Current design methods, however, depend on stable tertiary structures, limiting their utility for disordered or dynamic targets. Here, we present a motif-specific PPI targeting algorithm (moPPIt), a framework for the de novo generation of motif-specific peptide binders derived solely from target sequence data. The core of this approach is BindEvaluator, a transformer architecture that interpolates protein language model embeddings to predict peptide-protein binding site interactions with high accuracy (AUC = 0.97). We integrate this predictor into a novel Multi-Objective-Guided Discrete Flow Matching (MOG-DFM) framework, which steers generative trajectories toward peptides that simultaneously maximize binding affinity and motif specificity. After comprehensive in silico validation of binding and motif-specific targeting, we validate moPPIt in vitro by generating binders that strictly discriminate between the FN3 and IgG domains of NCAM1, confirming domain-level specificity, and further demonstrate precise targeting of IDRs by generating binders to the N-terminal disordered domain of {beta}-catenin. In functional, disease-relevant assays, moPPIt-designed peptides specifically targeting the GM-CSF receptor [a] subunit effectively block human macrophage polarization. Finally, we demonstrate utility in cell engineering, where binders directed against a defined motif on a synthetic cell surface ligand (AGR2t) drive specific chimeric antigen receptor regulatory T cell (CAR Treg) activation and suppressive function, including in the context of human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes. Altogether, moPPIt serves as a theoretically-justified, sequence-based paradigm for controllably targeting the complete proteome with immediate therapeutic applications.

synthetic biology↗

bioRxiv2024

MetaLATTE: Metal Binding Prediction via Multi-Task Learning on Protein Language Model Latents

The bioremediation of environments contaminated with heavy metals is an important challenge in environmental biotechnology, which may benefit from the identification of proteins that bind and neutralize these metals. Here, we introduce a novel predictive algorithm that conducts Metal binding prediction via LAnguage model laTenT Embeddings using a multi-task learning approach to accurately classify the metal-binding properties of input protein sequences. Our MetaLATTE model utilizes the state-of-the-art ESM-2 protein language model (pLM) embeddings and a position-sensitive attention mechanism to predict the likelihood of binding to specific metals, such as zinc, lead, and mercury. Importantly, our approach addresses the challenges posed by proteins from understudied organisms, which are often absent in traditional metal-binding databases, without the requirement of an input structure. By providing a probability distribution over potential binding metals, our classifier elucidates specific interactions of proteins with diverse metal ions. We envision that MetaLATTE will serve as a powerful tool for rapidly screening and identifying new metal-binding proteins, from metagenomic discovery or de novo design efforts, which can later be employed in targeted bioremediation campaigns.

bioinformatics↗

bioRxiv2024

FusOn-pLM: A Fusion Oncoprotein-Specific Language Model via Focused Probabilistic Masking

Fusion oncoproteins, a class of chimeric proteins arising from chromosomal translocations, drive and sustain various cancers, particularly those impacting children. Unfortunately, due to their intrinsically disordered nature, large size, and lack of well-defined, druggable pockets, they have been historically challenging to target therapeutically: neither small molecule-based methods nor structure-based approaches for binder design are strong options for this class of molecules. Recently, protein language models (pLMs) have demonstrated success at representing protein sequences with information-rich embeddings, enabling downstream design applications from sequence alone. However, no current pLM has been trained on fusion oncoprotein sequences and thus may not produce optimal representations for these proteins. In this work, we introduce FusOn-pLM, a novel pLM that fine-tunes the state-of-the-art ESM-2 model on fusion oncoprotein sequences. We specifically introduce a novel masked language modeling (MLM) strategy, employing a binding-site probability predictor to focus masking on key amino acid residues, thereby generating more optimal fusion oncoprotein-aware embeddings. Our model improves performance on both fusion oncoprotein-specific benchmarks and disorder prediction tasks in comparison to baseline ESM-2 representations, as well as manually-constructed biophysical embeddings, motivating downstream usage of FusOn-pLM embeddings for therapeutic design tasks targeting these fusions. We have made our model publicly available to the community at https://huggingface.co/ChatterjeeLab/FusOn-pLM.

bioinformatics↗

bioRxiv2024

Standardized Nomenclature and Reporting for PacBio HiFi Sequencing and Analysis of rAAV Gene Therapy Vectors

Despite recombinant adeno-associated viruses (rAAVs) being the leading platform for gene therapy, there is a lack of standardized computational analysis methods and reporting to assess the contents of each capsid through long-read sequencing. PacBios highly accurate long-read HiFi sequencing enables comprehensive characterization of AAV genomes but requires bioinformatics expertise for analyzing, interpreting and comparing the results. To address this need and improve the understanding of functional viral payloads, our working group established standardized nomenclature and reporting for long-read sequencing data of rAAV vectors. The working group recommendations cover critical quality attributes (CQAs) related to vector purity (full-length vs. fragmented genomes) and identification of contaminants (host DNA, plasmid DNA). Our data analyses of de novo manufacturing runs by the recommended protocol revealed specificity of full and partially filled capsids and high-resolution characterization of partial/truncated vector species. Finally, we provide an open-source software implementing this standardized AAV analysis and reporting to promote transparency, facilitate data comparability, and improve rAAV vector design and quality control.

bioinformatics↗

bioRxiv2024

AMP-Diffusion: Integrating Latent Diffusion with Protein Language Models for Antimicrobial Peptide Generation

Denoising Diffusion Probabilistic Models (DDPMs) have emerged as a potent class of generative models, demonstrating exemplary performance across diverse AI domains such as computer vision and natural language processing. In the realm of protein design, while there have been advances in structure-based, graph-based, and discrete sequence-based diffusion, the exploration of continuous latent space diffusion within protein language models (pLMs) remains nascent. In this work, we introduce AMP-Diffusion, a latent space diffusion model tailored for antimicrobial peptide (AMP) design, harnessing the capabilities of the state-of-the-art pLM, ESM-2, to de novo generate functional AMPs for downstream experimental application. Our evaluations reveal that peptides generated by AMP-Diffusion align closely in both pseudo-perplexity and amino acid diversity when benchmarked against experimentally-validated AMPs, and further exhibit relevant physicochemical properties similar to these naturally-occurring sequences. Overall, these findings underscore the biological plausibility of our generated sequences and pave the way for their empirical validation. In total, our framework motivates future exploration of pLM-based diffusion models for peptide and protein design.

bioinformatics↗

bioRxiv2024

Involvement of ArlI, ArlJ, and CirA in Archaeal Type-IV Pilin-Mediated Motility Regulation

Many prokaryotes use swimming motility to move toward favorable conditions and escape adverse surroundings. Regulatory mechanisms governing bacterial flagella-driven motility are well-established, however, little is yet known about the regulation underlying swimming motility propelled by the archaeal cell surface structure, the archaella. Previous research showed that deletion of the adhesion pilins (PilA1-6), subunits of the type IV pili cell surface structure, renders the model archaeon Haloferax volcanii non-motile. In this study, we used EMS mutagenesis and a motility assay to identify motile suppressors of the {Delta}pilA[1-6] strain. Of the eight suppressors identified, six contain missense mutations in archaella biosynthesis genes, arlI and arlJ. Overexpression of these arlI and arlJ mutant constructs in the respective multi-deletion strains {Delta}pilA[1-6]{Delta}arlI and {Delta}pilA[1-6]{Delta}arlJ confirmed their role in suppressing the {Delta}pilA[1-6] motility defect. Additionally, three suppressors harbor co-occurring disruptive missense and nonsense mutations in cirA, a gene encoding a proposed regulatory protein. A deletion of cirA resulted in hypermotility, while cirA overexpression in wild-type cells led to decreased motility. Moreover, qRT-PCR analysis revealed that in wild-type cells, higher expression levels of arlI, arlJ, and the archaellin gene arlA1 were observed in motile early-log phase rod-shaped cells compared to non-motile mid-log phase disk-shaped cells. Conversely, {Delta}cirA cells, which form rods during both early and mid-log phases, exhibited similar expression levels of arl genes in both growth phases. Our findings contribute to a deeper understanding of the mechanisms governing archaeal motility, highlighting the involvement of ArlI, ArlJ, and CirA in pilin- mediated motility regulation. ImportanceArchaea are close relatives of eukaryotes and play crucial ecological roles. Certain behaviors, such as swimming motility, are thought to be important for archaeal environmental adaptation. Archaella, the archaeal motility appendages, are evolutionarily distinct from bacterial flagella, and the regulatory mechanisms driving archaeal motility are largely unknown. Previous research has linked the loss of type IV pili subunits to archaeal motility suppression. This study reveals three Haloferax volcanii proteins involved in pilin-mediated motility regulation, offering a deeper understanding of motility regulation in this understudied domain while also paving the way for uncovering novel mechanisms that govern archaeal motility. Understanding archaeal cellular processes will help elucidate the ecological roles of archaea as well as the evolution of these processes across domains.

microbiology↗

bioRxiv2024

PTM-Mamba: A PTM-Aware Protein Language Model with Bidirectional Gated Mamba Blocks

AO_SCPLOWBSTRACTC_SCPLOWProteins serve as the workhorses of living organisms, orchestrating a wide array of vital functions. Post-translational modifications (PTMs) of their amino acids greatly influence the structural and functional diversity of different protein types and uphold proteostasis, allowing cells to swiftly respond to environmental changes and intricately regulate complex biological processes. To this point, efforts to model the complex features of proteins have involved the training of large and expressive protein language models (pLMs) such as ESM-2 and ProtT5, which accurately encode structural, functional, and physicochemical properties of input protein sequences. However, the over 200 million sequences that these pLMs were trained on merely scratch the surface of proteomic diversity, as they neither input nor account for the effects of PTMs. In this work, we fill this major gap in protein sequence modeling by introducing PTM tokens into the pLM training regime. We then leverage recent advancements in structured state space models (SSMs), specifically Mamba, which utilizes efficient hardware-aware primitives to overcome the quadratic time complexities of Transformers. After adding a comprehensive set of PTM tokens to the model vocabulary, we train bidirectional Mamba blocks whose outputs are fused with state-of-the-art ESM-2 embeddings via a novel gating mechanism. We demonstrate that our resultant PTM-aware pLM, PTM-Mamba, improves upon ESM-2s performance on various PTM-specific tasks. PTM-Mamba is the first and only pLM that can uniquely input and represent both wild-type and PTM sequences, motivating downstream modeling and design applications specific to post-translationally modified proteins. To facilitate PTM-aware protein language modeling applications, we have made our model available at: https://huggingface.co/ChatterjeeLab/PTM-Mamba.

bioinformatics↗

bioRxiv2024

Rapid proteome-wide prediction of lipid-interacting proteins through ligand-guided structural genomics

Lipids are essential metabolites that play critical roles in multiple cellular pathways. Like many primary metabolites, mutations that disrupt lipid synthesis can be lethal. Proteins involved in lipid synthesis, trafficking, and modification, are targets for therapeutic intervention in infectious disease and metabolic disorders. The ability to rapidly detect these proteins can accelerate their evaluation as targets for deranged lipid pathologies. However, it remains challenging to identify lipid binding motifs in proteins because the rules that govern protein engagement with specific lipids are poorly understood. As such, new bioinformatic tools that reveal conserved features in lipid binding proteins are necessary. Here, we present Structure-based Lipid-interacting Pocket Predictor (SLiPP), an algorithm that leverages machine learning to detect protein cavities capable of binding to lipids in protein structures. SLiPP uses a Random Forest classifier and operates at scale to predict lipid binding pockets with an accuracy of 96.8% and an F1 score of 86.9% when testing against a set of 8,380 pockets embedded within proteins. Our analyses revealed that the algorithm relies on hydrophobicity-related features to distinguish lipid binding pockets from those that bind to other ligands. SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. Additionally, SLiPP identified many new putative lipid binders in well studied proteomes. Because of its ability to identify novel lipid binding proteins, SLiPP can spur the discovery of new and "targetable" lipid-sensitive pathways.

bioinformatics↗

bioRxiv2023

Mitochondrial genes affect the immune response against bacterial infection (Duck Pasteurellosis) through a cascade of mechanisms mediated by nuclear immune genes- a cross talk with nuclear and mitochondrial gene

Mitochondria possess 37 genes of its own, helpful for carrying out various functions including oxidative phosphorylation. But the mitochondria is neither independent in terms of its structure, nor its function, it depend upon nuclear gene for its functionality and replication. Our lab has earlier reported the role of mitochondrial genome in controlling health and reproduction in animal model. Reports also indicate that mitochondria have role in immune response against bacterial infection. In our current study, we depict the role of two polypeptide coding mitochondrial gene as cytochrome B and cytochrome C in providing host immunity against bacterial disease (Duck Pasteurellosis). We further observe that the mechanism was governed by cascade of mechanisms mediated through nuclear genes NRLP3, IL18 and Sting. In the first phase of the study, we have characterized Cytochrome B and Cytochrome C genes from Bengal duck and quantified through the assesment of the expression profiling with respect to healthy and Pasteurella infected ducks following a natural challenge with Pasteurella multocida. In the next phase of our study, we have characterized the above nuclear genes in Bengal duck and attempted to correlate the expression with mitochondrial genes. We attempted to explore the mechanism of pathway how mitochondrial DNA triggers the nuclear immune response leading to destruction of bacterial pathogen. Molecular docking revealed how IL18 directly binds with the pathogen. This is the first report in animal model.

genomics↗

bioRxiv2023

Role of IL-6 and IL10 immune response genes against nematode Haemonchus contortus in ovis aries- a novel report

Haemonchus contortus is one of the most deadly parasites affecting sheep industry causing heavy economic loss. In our earlier study, we have reported RIGI, an earlier established antiviral molecule and CD14 (an earlier established antibacterial molecule) to have potential role in antiparasitic immunity for the first time. In this current study, we aim to clone and sequence the IL-6 and IL10 genes in sheep (Ovis aries) and utilized bioinformatics methods to analyze and compare the functional and structural domains of peptides produced from IL6 and IL10. Furthermore, the study explored these domains in three-dimensional structures. The findings of this study provide molecular characterization of IL-6 and IL10 in sheep, which is essential for advancing our understanding of functional immune responses in this animal. We report IL6 and IL10 to have potential antiparasitic role against H. contortus for first time. The production of these molecules opens up possibilities for its potential use as recombinant proteins to manipulate the immune response. Evaluating its value in vaccine research and gaining a broader understanding of its role in immune responses becomes feasible with the availability of IL-6 and IL10. Moreover, the differential mRNA expression levels of IL-6, IL10 between healthy and diseased sheep indicate its crucial role in maintaining homeostasis and mounting immune responses. IL10 acts as receptor for H. contortus. The identification of this immune-responsive gene also offers new avenues for investigating long-term resistance to H. contortus infection in sheep.

genomics↗