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Kumar, N.

Publications and source records attributed to Kumar, N..

At least 91 records · Page 5Linked to original sources

Molecular heterogeneity of quiescent melanocyte stem cells revealed by single-cell RNA-sequencing.

Melanocyte stem cells (McSCs) of the hair follicle are a rare cell population within the skin and are notably underrepresented in whole-skin, single-cell RNA sequencing (scRNA-seq) datasets. Using a cell enrichment strategy to isolate KIT+/CD45-cells from the telogen skin of adult female C57BL/6J mice, we evaluated the transcriptional landscape of quiescent McSCs (qMcSCs) at high resolution. Through this evaluation, we confirmed existing molecular signatures for qMcCS subpopulations (e.g., Kit+, Cd34+/-, Plp1+, Cd274+/-, Thy1+, Cdh3+/-) and identified novel qMcSC subpopulations, including two that differentially regulate their immune privilege status. Within qMcSC subpopulations, we also predicted melanocyte differentiation potential, neural crest potential, and quiescence depth. Taken together, the results demonstrate that the qMcSC population is heterogenous and future studies focused on investigating changes in qMcSCs should consider changes in subpopulation composition. SignificanceSingle cell transcriptomics has revolutionized our ability to interrogate the dynamic nature of tissues. Here we provide a high-resolution map of the melanocyte stem cell population during quiescence. This map provides one of few examples highlighting broad heterogeneity in stem cells during the quiescent cell state. The map also unifies previous observations using other cell, molecular and functional analyses to define the unique features of the quiescent melanocyte stem cell population. This data provides a valuable resource to individuals interested in further evaluating aspects of cellular quiescence in stem cells broadly or melanocyte stem cells specifically.

cell biology↗

Unraveling molecular basis for reduced neuraminidase inhibitors susceptibility in highly pathogenic avian influenza A (H5N1) viruses isolated from chickens in India

The increasing resistance cases in influenza viruses to different classes of antiviral drugs, necessitates the in-depth analysis of molecular interactions governing reduced susceptibility to these drugs. This study explores the molecular basis of neuraminidase inhibitors resistance in avian H5N1 influenza viruses identified in our previous research. Using comprehensive modeling and docking tools, we investigated two isolates--A/chicken/India/85459/2008 (N294S) and A/chicken/WestBengal/142121/2008 (E119A + I117V). The N294S mutation conferred oseltamivir resistance while retaining zanamivir susceptibility, whereas the E119A + I117V mutations led to zanamivir resistance while reducing oseltamivir susceptibility. Molecular interactions analysis unveiled varied fitness levels, hydrogen bonding, and affinity transitions associated with N294S and E119A + I117V mutations. This study provides crucial insights into molecular interactions responsible for reduced susceptibility to neuraminidase inhibitors, which is essential for optimizing antiviral strategies and pandemic preparedness.

microbiology↗

Non-canonical NF-κB signaling in dendritic cells promotes intestinal inflammation by restraining the tolerogenic β-catenin-Raldh2 axis

Dendritic cell (DC) dysfunctions exacerbate intestinal pathologies. However, the mechanisms compromising DC-mediated immune controls remain unclear. We found that intestinal DCs from mice subjected to experimental colitis possessed heightened non-canonical NF-{kappa}B signaling, which activates the RelB:p52 heterodimer. Genetic inactivation of this pathway in DCs alleviated inflammation in colitogenic mice. Unexpectedly, RelB:p52 deficiency diminished the transcription of Axin1, a critical component of the {beta}-catenin destruction complex. This reinforced {beta}-catenin-driven expression of Raldh2, which imparts tolerogenic DC attributes by promoting retinoic acid (RA) synthesis. Indeed, DC-specific non-canonical NF-{kappa}B impairment improved the colonic frequency of Tregs and IgA+ B cells, which fostered luminal IgA and eubiosis. Introducing {beta}-catenin haploinsufficiency in non-canonical NF-{kappa}B-deficient DCs moderated Raldh2 activity, reinstating colitogenic sensitivity in mice. Finally, IBD patients displayed a deleterious non-canonical NF-{kappa}B signature in intestinal DCs. In sum, we establish a DC network that integrates non-canonical NF-{kappa}B signaling to subvert RA metabolic pathway in fueling intestinal inflammation. Significance (100)Distorted dendritic cell (DC) functions have been implicated in aberrant intestinal inflammation; however, the underlying mechanism remains obscure. We discovered that the non-canonical NF-{kappa}B pathway exacerbates inflammation in the colitogenic gut by downmodulating {beta}-catenin-driven synthesis of Raldh2 in DCs. Raldh2 represents a key enzyme involved in the production of tolerogenic retinoic acid in intestinal DCs. Beyond regulating immune genes, therefore, non-canonical NF-{kappa}B signaling appears to instruct retinoic acid-mediated control of gut health. While we illustrate a DC network integrating immune signaling and micronutrient metabolic pathways in the intestine, our finding may have broad relevance for nutritional interventions in inflammatory ailments. eToCDeka and Kumar et al. illustrate a DC-circuitry that exacerbates intestinal inflammation in IBD patients and colitogenic mice. Non-canonical NF-{kappa}B signaling restrains {beta}-catenin in DCs to downmodulate Raldh2, which promotes tolerogenic RA synthesis, leading to diminished Treg and IgA+ cell frequencies in the gut. HighlightsO_LIAberrant intestinal inflammation is associated with and exacerbated by non-canonical NF-{kappa}B signaling in DCs. C_LIO_LINon-canonical signaling restrains the tolerogenic {beta}-catenin-Raldh2 axis in DCs by upregulating Axin1. C_LIO_LIDC-specific RelB:p52 impairment promotes {beta}-catenin-dependent Treg accumulation in the gut. C_LIO_LIA DC defect of non-canonical signaling causes {beta}-catenin-dependent increase in luminal sIgA, fostering the gut microbiome. C_LI One sentenceThe non-canonical NF-{kappa}B pathway fuels intestinal inflammation by waning the tolerogenic {beta}-catenin-Raldh2-retinoic acid axis in DCs.

immunology↗

A novel highly divergent enteric calicivirus in a bovine calf, India

In 2015, a novel highly divergent bovine calicivirus was detected in an Indian calf with enteritis. Phylogenetic analysis linked it to the Nebovirus with only 38.5% sequence identities, emphasizing the need for separate taxonomic classification. Furthermore, PCR screening detected these unique caliciviruses widely in Indias northern states.

microbiology↗

NK and NKT cells in the pathogenesis of Hidradenitis suppurativa: Novel therapeutic strategy through targeting of CD2

Hidradenitis suppurativa (HS) is a chronic debilitating inflammatory skin disease with poorly understood pathogenesis. Single-cell RNAseq analysis of HS lesional and healthy individual skins revealed that NKT and NK cell populations were greatly expanded in HS, and they expressed elevated CD2, an activation receptor. Immunohistochemistry analyses confirmed significantly expanded numbers of CD2+ cells distributed throughout HS lesional tissue, and many co-expressed the NK marker, CD56. While CD4+ T cells were expanded in HS, CD8 T cells were rare. CD20+ B cells in HS were localized within tertiary follicle like structures. Immunofluorescence microscopy showed that NK cells (CD2+CD56dim) expressing perforin, granzymes A and B were enriched within the hyperplastic follicular epidermis and tunnels of HS and juxtaposed with apoptotic cells. In contrast, NKT cells (CD2+CD3+CD56bright) primarily expressed granzyme A and were associated with -SMA expressing fibroblasts within the fibrotic regions of the hypodermis. Keratinocytes and fibroblasts expressed high levels of CD58 (CD2 ligand) and they interacted with CD2 expressing NKT and NK cells. The NKT/NK maturation and activating cytokines, IL-12, IL-15 and IL-18, were significantly elevated in HS. Inhibition of cognate CD2-CD58 interaction with blocking anti-CD2 mAb in HS skin organotypic cultures resulted in a profound reduction of the inflammatory gene signature and secretion of inflammatory cytokines and chemokines in the culture supernate. In summary, we show that a cellular network of heterogenous NKT and NK cell populations drives inflammation, tunnel formation and fibrosis in the pathogenesis of HS. Furthermore, CD2 blockade is a viable immunotherapeutic approach for the management of HS.

immunology↗

p38-MAPK is prerequisite for the synthesis of SARS-CoV-2 protein

The inhibition of p38 mitogen-activated protein kinase (p38-MAPK) by small molecule chemical inhibitors was previously shown to impair severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) replication, however, mechanisms underlying antiviral activity remains unexplored. In this study, reduced growth of SARS-CoV-2 in p38- knockout Vero cells, together with enhanced viral yield in cells transfected with construct expressing p38, suggested that p38-MAPK is essential for the propagation of SARS-CoV-2. The SARS-CoV-2 was also shown to induce phosphorylation (activation) of p38, at time when transcription/translational activities are considered to be at the peak levels. Further, we demonstrated that p38 supports viral RNA/protein synthesis without affecting viral attachment, entry, and budding in the target cells. In addition, we demonstrated that long-term culture of SARS-CoV-2 in the presence of p38 inhibitor SB203580 does not easily select resistant viral mutants. In conclusion, we provide mechanistic insights on the regulation of SARS-CoV-2 replication by p38 MAPK.

microbiology↗

MolPhase: An Advanced Phase Separation Predictor and an Investigation of Phytobacterial Effector in Plant

We introduce MolPhase (http://molphase.sbs.ntu.edu.sg/), an advanced protein phase separation (PS) prediction algorithm that improves accuracy and reliability by utilizing diverse physicochemical features and extensive experimental datasets. MolPhase applies a user-friendly interface to compare distinct biophysical features side-by-side along protein sequences. By additional comparison with structural predictions, MolPhase enables efficient predictions of new phase-separating proteins and guides hypothesis generation and experimental design. Key contributing factors underlying MolPhase include pi-pi interaction, disorder, and prion-like domain. As an example, MolPhase finds that phytobacterial type III effectors (T3Es) are highly prone to homotypic PS, which was experimentally validated in vitro biochemically and in vivo in plants, mimicking their injection and accumulation in the host during microbial infection. In addition, the phase-separation of T3Es were evolved both in vivo and in vitro, suggesting their determinative scaffolding function, though there is a difference in material properties, implying a difference in homotypic and heterotypic macromolecular condensation. Robust integration of MolPhases effective prediction and experimental validation exhibit the potential to evaluate and explore how biomolecule PS functions in biological systems.

biophysics↗

A Light sheet fluorescence microscopy and machine learning-based approach to investigate drug and biomarker distribution in whole organs and tumors.

Tissue clearing and Light sheet fluorescence microscopy (LSFM) provide spatial information at a subcellular resolution in intact organs and tumors which is a significant advance over tools that limit imaging to a few representative tissue sections. The spatial distribution of drugs, targets, and biomarkers can help inform relationships between exposure at the site of action, efficacy, and safety during drug discovery. We demonstrate the use of LSFM to investigate distribution of an oncolytic virus (OV) and vasculature in xenograft tumors, as well as brain A{beta} pathology in an Alzheimers disease (AD) mouse model. Machine learning-based image analysis tools developed to segment vasculature in tumors showed that random forest and deep learning methods provided superior segmentation accuracy vs intensity-based thresholding. Sub-cellular resolution enabled detection of punctate and diffuse intracellular OV distribution profiles. LSFM investigation in the brain in a TgCRND8 AD mouse model at 6.5 months of age enabled evaluation of A{beta} plaque density in different brain regions. The utility of LSFM data to support quantitative systems pharmacology (QSP) and physiology-based pharmacokinetics (PBPK) modeling to inform drug development are also discussed. In summary, we showcase how LSFM can expand our understanding of macromolecular drug and biomarker distribution to advance drug discovery and development.

cancer biology↗

Diet-induced plasticity of life-history traits and gene expression in outbred Drosophila melanogaster population

Food is fundamental for the survival of organisms, governing growth, maintenance, and reproduction through the provision of essential macronutrients. However, access to food with optimum macronutrient composition, which will maximize the evolutionary fitness of an organism, is not always guaranteed. This leads to dietary mismatches with potential impacts on organismal performance. To understand the consequences of such dietary mismatches, we examined the effects of isocaloric diets varying in macronutrient composition on eight key organismal traits spanning across the lifespan of a large outbred Drosophila melanogaster population (n [~] 2500). Our findings reveal that carbohydrate-reduced isocaloric diets correlates to accelerated pre-adult development and boosts reproductive output without impacting pre-adult viability and body size. Conversely, an elevated dietary carbohydrate content correlated to reduced lifespan in flies, evidenced by accelerated functional senescence including compromised locomotor activity and deteriorating gut integrity. Furthermore, transcriptomic analysis indicated a substantial difference in gene regulatory landscapes between flies subject to high carbohydrate vs high protein diet, with elevated protein levels indicating transcriptomes primed for reduced synthesis of fatty acids. Taken together, our study helps advance our understanding of the effect of macronutrient composition on life history traits and their interrelations, offering critical insights into potential adaptive strategies that organisms might adopt against the continual dietary imbalances prevalent in the rapidly evolving environment.

evolutionary biology↗

Molecular Property Diagnostic Suite for COVID-19 (MPDSCOVID-19): An open access disease specific drug discovery portal

Computational drug discovery is intrinsically interdisciplinary and has to deal with the multifarious factors which are often dependent on the type of disease. Molecular Property Diagnostic Suite (MPDS) is a Galaxy based web portal which was conceived and developed as a disease specific web portal, originally developed for tuberculosis (MPDSTB). As specific computational tools are often required for a given disease, developing a disease specific web portal is highly desirable. This paper emphasises on the development of the customised web portal for COVID-19 infection and is referred to as MPDSCOVID-19. Expectedly, the MPDS suites of programs have modules which are essentially independent of a given disease, whereas some modules are specific to a particular disease. In the MPDSCOVID-19 portal, there are modules which are specific to COVID-19, and these are clubbed in SARS-COV-2 disease library. Further, the new additions and/or significant improvements were made to the disease independent modules, besides the addition of tools from galaxy toolshed. This manuscript provides a latest update on the disease independent modules of MPDS after almost 6 years, as well as provide the contemporary information and tool-shed necessary to engage in the drug discovery research of COVID-19. The disease independent modules include file format converter and descriptor calculation under the data processing module; QSAR, pharmacophore, scaffold analysis, active site analysis, docking, screening, drug repurposing tool, virtual screening, visualisation, sequence alignment, phylogenetic analysis under the data analysis module; and various machine learning packages, algorithms and in-house developed machine learning antiviral prediction model are available. The MPDS suite of programs are expected to bring a paradigm shift in computational drug discovery, especially in the academic community, guided through a transparent and open innovation approach. The MPDSCOVID-19 can be accessed at http://mpds.neist.res.in:8085.

bioinformatics↗

Unravelling Genomic Origin of Lumpy Skin Disease Virus in Recent Outbreaks

Lumpy skin disease virus (LSDV) belongs to the genus Capripox virus and family Poxviridae. LSDV was endemic in most of Africa, Middle east and Turkey, but since 2015, several outbreaks have been reported in Asian countries. In this study we used Whole Genome Sequence (WGS) approach to investigate the origin of the outbreak and understand the genomic landscape of the virus. Our study showed that the LSDV strain of 2022 outbreak exhibited many genetic variations, compared to the Reference Neethling strain sequence and the previous field strains from India. A total of 1819 variations were found in 22 genome sequences, which includes 399 extragenic mutations, 153 insertion frameshift mutations, 234 deletion frameshift mutations, 271 Single nucleotide polymorphisms (SNPs) and 762 silent SNPs. 38 genes have more than 2 variations per gene and these genes belong to viral-core protein, viral binding proteins, replication and RNA polymerase proteins. We highlight the importance of several SNPs in various genes which may play an essential role in pathogenesis of LSDV. Phylogenetic analysis performed on all whole genome sequences of LSDV showed two types of variants in India. One group of the variant with fewer mutations was found to lie closer to the LSDV 2019 strain from Ranchi while the other group clustered with previous Russian outbreaks from 2015. Our study highlights the importance of genomic characterization of viral outbreaks to not only monitor the frequency of mutations but also address its role in pathogenesis of LSDV as the outbreak continues.

microbiology↗

KLP-7/Kinesin-13 orchestrates axon-dendrite checkpoints for polarized trafficking in neurons

Neurons are compartmentalized cells with spatiotemporal distinction of anatomy and molecular repertoire. Microtubule organization in the neuron is crucial for its polarized structure and composition. Microtubule dynamics are differentially optimized in the axons and dendrites by the interplay between the microtubule-stabilizing and destabilizing factors. It is unclear how the destabilizing factors are important for developing and maintaining neuronal polarity. We investigated the function of KLP-7, a microtubule depolymerizing motor from the Kinesin-13 family, in the compartmentalization of axons and dendrites using the PVD neurons in Caenorhabditis elegans. In the absence of KLP-7, axonal proteins such as RAB-3 and SAD-1 were mislocalized to dendrites, suggesting a disruption in axon-dendrite compartmentalization. Notably, this phenomenon was independent of other depolymerizing factors like EFA-6, highlighting the specific role of KLP-7 in this process. We observed a reduced rate of microtubule polymerization and an altered polarity of microtubules in the PVD major dendrite due to the loss of klp-7. Additionally, the deletion of klp-7 led to the formation of ectopic neurites from the cell body and the ectopic localization of UNC-44/Ankyrin-G, a protein associated with the axon initial segment (AIS), to the dendrites. Additionally, live imaging of GFP::KLP-7 revealed that KLP-7 is more dynamic in the dendrites as compared to the axon. These observations indicate that the precise dynamics of KLP-7 in neurites are crucial for maintaining distinct microtubule polymerization in the axons and dendrites, thereby influencing neuronal polarity. Our findings shed light on the pivotal role of KLP-7/Kinesin-13 in the establishment of axon-dendrite checkpoints, which in turn impact the polarized trafficking of cellular components within neurons.

cell biology↗

Reverse engineering morphogenesis through Bayesian optimization of physics-based models

Morphogenetic programs direct the cell signaling and nonlinear mechanical interactions between multiple cell types and tissue layers to define organ shape and size. A key challenge for systems and synthetic biology is determining optimal combinations of intra- and inter-cellular interactions to predict an organs shape, size, and function. Physics-based mechanistic models that define the subcellular force distribution facilitate this, but it is extremely challenging to calibrate parameters in these models from data. To solve this inverse problem, we created a Bayesian optimization framework to determine the optimal cellular force distribution such that the predicted organ shapes match the desired organ shapes observed within the experimental imaging data. This integrative framework employs Gaussian Process Regression (GPR), a non-parametric kernel-based probabilistic machine learning modeling paradigm, to learn the mapping functions relating to the morphogenetic programs that generate and maintain the final organ shape. We calibrated and tested the method on cross-sections of Drosophila wing imaginal discs, a highly informative model organ system, to study mechanisms that regulate epithelial processes that range from development to cancer. As a specific test case, the parameter estimation framework successfully infers the underlying changes in core parameters needed to match simulation data with time series imaging data of wing discs perturbed with collagenase. Unexpectedly, the framework also identifies multiple distinct parameter sets that generate shapes similar to wild-type organ shapes. This platform enables an efficient, global sensitivity analysis to support the necessity of both actomyosin contractility and basal ECM stiffness to generate and maintain the curved shape of the wing imaginal disc. The optimization framework, combined with fixed tissue imaging, identified that Piezo, a mechanosensitive ion channel, impacts fold formation by regulating the apical-basal balance of actomyosin contractility and elasticity of ECM. This framework is extensible toward reverse-engineering the morphogenesis of any organ system and can be utilized in real-time control of complex multicellular systems.

systems biology↗

Piezo regulates epithelial topology and promotes precision in organ size control

Mechanosensitive Piezo channels regulate cell division through calcium-mediated activation of ERK signaling or activate Rho signaling to mediate cell extrusion and cell death. However, systems-level functions of Piezo in regulating organogenesis remain poorly understood. Here, we demonstrate that Piezo controls epithelial cell topology to ensure precise organ growth through the integration of live imaging experiments with pharmacological and genetic perturbations and computational modeling. Notably, knockout or knockdown of Piezo led to bilateral asymmetry in wing phenotypes. While pharmacological activation of Piezo stimulated an increase in the frequency of spikes in cytosolic Ca2+, we discovered that Piezo overexpression counterintuitively reduces Ca2+ signaling dynamics. Knockdown of Piezo inhibited proliferation and decreased apoptosis, resulting in an overall increase in epithelial overcrowding. In contrast, either genetic overexpression or pharmacological activation of Piezo increased cell proliferation and cell removal through basal extrusion. Surprisingly, Piezo overexpression increased the hexagonality of cellular topology. To test whether Piezo regulates cell topology, we formulated computational simulations to investigate how expression levels of Piezo protein regulate cell proliferation and apoptosis through modulation of the cut-off tension required for Piezo channel activation. Quantitative analysis validated computational simulation predictions of how perturbations to Piezo impacted epithelial topology. Overall, our findings demonstrate that Piezo promotes robustness in regulating epithelial topology and is necessary for precise organ size control.

developmental biology↗

Data-Driven Modeling and Analysis of Fatty Acid Desaturase in Plants

Fatty acids and their derivatives continue to garner attention as sustainable alternatives to petrochemically derived materials. Towards this goal, we examine the plant membrane-bound fatty acid desaturases (FADs) and develop an overview of their 3D structure and phylogenic relationships. Through this effort we developed two plant fatty acid desaturase homology models that we analyzed with substrate docking and molecular dynamics simulations to better understand the diiron binding pocket that is characteristic of these proteins. The comparison between the Omega6 and Delta12 homology models specifically in regards to the binding affinity as a function of carbon chain length indicates that there is a dip in binding affinity near the 18:2 carbon chain length but the rest maintain a rather consistent binding affinity throughout. Furthermore, MD analysis highlights the importance of regions within the cytosolic cap domain on the binding pocket. PACS: 0000, 1111 2000 MSC: 0000, 1111 Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/553759v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1674c18org.highwire.dtl.DTLVardef@b4e775org.highwire.dtl.DTLVardef@c7ec21org.highwire.dtl.DTLVardef@15fa66c_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDeveloped pipeline to predict function from protein sequence C_LIO_LIModeled two fatty acid desaturases and predicted their structure and functions C_LIO_LILeveraged docking simulations and molecular dynamics to confirm protein function C_LI

molecular biology↗

Changes in an Enzyme Ensemble During Catalysis Observed by High Resolution XFEL Crystallography

Enzymes populate ensembles of structures with intrinsically different catalytic proficiencies that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL) to observe catalysis in a designed mutant (G150T) isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations and formation of the thioimidate catalytic intermediate selects for catalytically competent substates. A prior proposal for active site cysteine charge-coupled conformational changes in ICH is validated by determining structures of the enzyme over a range of pH values. A combination of large molecular dynamics simulations of the enzyme in crystallo and time-resolved electron density maps shows that ionization of the general acid Asp17 during catalysis causes additional conformational changes that propagate across the dimer interface, connecting the two active sites. These ionization-linked changes in the ICH conformational ensemble permit water to enter the active site in a location that is poised for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

biochemistry↗

HLA-DR4Pred2: an improved method for predicting HLA-DRB1*04:01 binders

HLA-DRB1*04:01 is associated with many disease that include sclerosis, arthritis, diabetes and Covid19. Thus, it is important to scan binders of HLA-DRB1*04:01 in an antigen to develop immunotherapy, vaccine and protection against these diseases. One of the major limitations of existing methods for predicting with HLA-DRB1*04:01 binders is that these methods trained on small datasets. This study present a method HLA-DR4Pred2 developed on a large dataset contain 12676 binders and equal number of non-binders. It is an improved version of HLA-DR4Pred, which was trained on a small dataset contain only 576 binders and equal number of binders. All models in this study were trained, optimized and tested on 80% of data called training datasets using five-fold cross-validation; final models were evaluated on 20% of data called validation/independent dataset. A wide range of machine learning techniques have been employed to develop prediction models and achieved maximum AUC of 0.90 and 0.87 on validation dataset using composition and binary profile features respectively. The performance of our composition based model increased from 0.90 to 0.93 when combined with BLAST search. In addition, we also developed our models on alternate or realistic dataset that contain 12676 binders and 86300 non-binders and achieved maximum AUC 0.99. Our method perform better than existing methods when we compare the performance of our best model with performance of existing methods on validation dataset. Finally, we developed standalone and online version of HLA-DR4Pred2 for predicting, designing and virtual scanning of HLA- DRB1*04:01(https://webs.iiitd.edu.in/raghava/hladr4pred2/; https://github.com/raghavagps/hladr4pred2). Key PointsO_LIHLADR4Pred2.0 is an update of HLADR4Pred C_LIO_LIPredict the binding or non-binding peptides for MHC-Class II allele HLA- DRB1*04:01 C_LIO_LIUsed alignment free and alignment based hybrid approach C_LIO_LIMotifs which are highly specific to HLA-DRB1*04:01 binders C_LIO_LIBenchmark the performance of the other existing methods with HLADR4Pred2.0 C_LI Authors BiographyO_LISumeet Patiyal is currently working as Ph.D. in Computational biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India C_LIO_LIAnjali Dhall is currently working as Ph.D. in Computational Biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India. C_LIO_LINishant Kumar is currently working as Ph.D. in Computational biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India C_LIO_LIGajendra P. S. Raghava is currently working as Professor and Head of Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India. C_LI

bioinformatics↗

Ecological Impacts of Poultry Waste on Urban Raptors: Conflicts, Diseases, and Climate Change Implications amidst Pandemic Threats

O_LIThe dramatic increase in poultry production and consumption (PPC) over the past decades has raised questions about its impacts on biodiversity, particularly in the Global South. This study focuses on the ecological and environmental impacts of PPC waste metabolism at Asias largest livestock wet market, located next to the continents largest landfill of Ghazipur in Delhi, which I have been monitoring since 2012. C_LIO_LIDaily processing of >100,000 poultry-fowls at Ghazipur results in an annual production of [~]27,375 metric tonnes of poultry-waste, attracting massive flocks of Black-eared kites, migratory facultative scavengers that winter in South Asia. Approximately >33,600 kites foraged in the area every day and disposed 8.83% of the total PPC slaughter-remains produced during October-April. However, with their return migration to Central Asia, kite flocks over Ghazipur reduced by 90%, leading to a proportional decrease in scavenging services. Absence of kites from the larger, migratory race during May-September did not elicit any compensatory response from the small Indian kite, whose numbers over landfill remained unchanged. This raises vital questions about microclimate impacts by green house gases (GHG) released from massive amounts of routine detritus. Bearing in mind the prevalence of ritual feeding of meat chunks to kites in Delhi, my research indicates how life-history traits (migratory vs. resident) enable exploitation of specific anthropogenic resources, creating distinct kite-niche(s). Other opportunistic scavengers, e.g., dogs, rats, cattle-egrets, several passerines, and livestock (fishes and pigs) also benefited from PPC waste. C_LIO_LIPublic health and ethical concerns, including Avian-influenza outbreaks in 2018-21 and pandemic-lockdowns from 2020-22 - that affected informal meat processing - reduced the flocking of kites at Ghazipur by altering spatial dispersion of PPC remains. C_LIO_LIWaste-biomass driven cross-species associations can exacerbate zoonotic threats by putting humans and animals in close contact. The ecological impacts of waste-based biomass, as well as the aerospace conflicts caused by avian scavengers that cause birdstrikes must factor in the integrated management of city waste. The quantity, type, dispersion, and accessibility of food-waste for opportunistic urban fauna in tropical cities along avian migratory pathways are crucial for public health, and for conservation of (facultative) migratory avian-scavengers like Eurasian Griffons and Steppe Eagles that are facing extinction threats. C_LI Lay SummaryO_LIThe global trend of increasing consumption of broiler chickens, driven by rising incomes in tropical cities, has significant ecological implications for both native and migratory birds, as well as other commensal species. C_LIO_LIThe resulting large amounts of debris produced by poultry production and consumption have created a "chicken reconfigured biosphere" in cities along migratory paths. C_LIO_LITo better understand the local and global impacts of poultry production and consumption chains, I conducted a long-term study at Asias largest livestock wet market in Ghazipur, Delhi. C_LIO_LIThe findings reveal that informal handling of poultry waste and cultural practices have had significant impacts on animals that scavenge on the slaughter remains, particularly during the bird flu and COVID-19 pandemics. C_LIO_LIThe study recommends ways to minimise conflicts and health risks and reduce the potential impacts of rotting garbage on the climate by accommodating animals that have adapted to shared urban environments. C_LI

ecology↗