Biology subjects

Panda, S.

Publications and source records attributed to Panda, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

PAMD-Ch17, a Polymeric Analog of Plerixafor, Induces Mitochondrial Dysfunction in T-ALL Cells Independent of CXCR4

PAMD-Ch17 is a polymer composed of the CXCR4 inhibitor AMD3100/Plerixafor with a cholesterol modification. In previous work, we showed that PAMD-Ch17, but not AMD3100, induces cell death and differentiation in mouse Acute Myeloid Leukemia cells. To investigate the mechanism of PAMD-Ch17s novel anti-leukemic effects, we tested PAMD-Ch17 against a panel of human leukemia cell lines and found that PAMD-Ch17 is effective against a variety of acute leukemias, with T-ALL cell lines being highly sensitive. Surprisingly, CXCR4 knock out T-ALL cells were equally sensitive to PAMD-Ch17. Using a fluorescently tagged PAMD-Ch17, we found that the drug colocalized to the mitochondria. We also found that PAMD-Ch17 induced changes in expression of genes related to mitochondrial function, increased levels of mitochondrial superoxide, and decreased mitochondrial membrane potential. Using seahorse assays, we found that PAMD-Ch17 decreased baseline oxygen consumption, ATP production, and proton leakage. PAMD-Ch17 also decreased baseline extracellular acidification rate, indicating a decrease in overall metabolism. In mouse primary T-ALL but not healthy bone marrow cells, PAMD-Ch17 induced both mitochondrial superoxide and cell death. Using human bone marrow organoids, we found that PAMD-Ch17 induced mitochondrial superoxide and cell death in human primary T-ALL cells, but not in healthy stromal and hematopoietic cells. Collectively, our results indicate that PAMD-Ch17 has anti-leukemic effects against T-ALL cells but not healthy cells, likely mediated through a CXCR4 independent, mitochondrial based mechanism. These findings support further development of PAMDs as potential therapeutics for patients with T-ALL. KEY POINTSO_LIPAMD-Ch17, a polymeric drug based on AMD3100/Plerixafor, has novel anti-leukemic activities against T-ALL that are independent of CXCR4 inhibition. C_LIO_LIPAMD-Ch17 induces increased mitochondrial superoxide and cell death in primary ALL cells, but not healthy bone marrow cells. C_LI

cancer biology↗

bioRxiv2025

The Splicing Factor PTBP1 interacts with RUNX1 and is Required for Leukemia Cell Survival

Runt-related Transcription Factor 1 (RUNX1) is essential for definitive hematopoiesis and is among the most frequently mutated genes in leukemia. Previous work from our lab demonstrated that Histone Deacetylase 1 (HDAC1), a known RUNX1 partner, is unexpectedly required for active transcription suggesting a non-histone role for HDAC1 regulating components of the RUNX1 complex. Here, we use proteomics, genomics, and long-read transcriptomics to identify novel RUNX1 interacting partners and decipher their role in gene regulation and RNA splicing in leukemia cells. We demonstrate that Polypyrimidine Tract Binding Protein 1 (PTBP1) interacts with RUNX1 in an HDAC1 dependent manner. Chromatin profiling revealed extensive genome-wide overlap in sites occupied by RUNX1 and PTBP1, with significant enrichment at promoters of actively transcribed genes. Loss of PTBP1 in AML cells led to widespread alterations in RNA splicing and decreased expression of genes whose promoters are bound by both factors, including metabolic genes. In agreement with these findings, we found that loss of PTBP1 reduced glycolysis and glucose uptake and ultimately caused cell death. Based on our data, we propose that the interaction between RUNX1 and PTBP1 facilitates expression of metabolic proteins essential for leukemia cell growth and survival. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/654547v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@74e3b9org.highwire.dtl.DTLVardef@12a090org.highwire.dtl.DTLVardef@eb5a48org.highwire.dtl.DTLVardef@17465dc_HPS_FORMAT_FIGEXP M_FIG C_FIG KEY POINTSO_LIPTBP1 binds RUNX1 in a HDAC1-dependent manner and co-localizes to the promoters of target genes in leukemia cells. C_LIO_LILoss of PTBP1 decreases expression of key metabolic genes, resulting in decreased cell growth and glycolysis, increased sensitivity to chemotherapy, and cell death. C_LI

cancer biology↗

bioRxiv2024

Implications of diabetes mellitus on pathophysiology of Tuberculosis: Role of AGE-RAGE Axis and Glycated Proteins

Chronic hyperglycemia in diabetes mellitus promotes the formation of advanced glycation end products (AGEs) via non-enzymatic glycation of plasma proteins. AGEs and their receptor RAGE are central to diabetic complications, as they activate inflammatory pathways and oxidative stress. We studied the AGE-RAGE axis in uncontrolled diabetic individuals having pulmonary TB (PTB+DM), uncontrolled diabetic individuals with no infection (DM), and pulmonary TB patients (PTB). Levels of AGEs and RAGE were measured across these groups and compared to controls. The results showed significantly higher AGEs and RAGE levels in the diabetic milieu, reflecting chronic hyperglycemia. These AGEs were shown to be associated with impaired macrophage function, evidenced by reduced phagocytic capacity. Increased AGEs correlated with disease severity in tuberculosis patients co-affected by diabetes, indicating compromised immune responses. RAGE expression also showed a higher trend in TB patients, although not statistically significant, potentially influencing infection outcomes. Glycated calmodulin was also elevated in diabetic and TB-diabetes comorbid patients and negatively correlated with nitric oxide (NO) levels, suggesting that calmodulin glycation hinders NO production in diabetic conditions. Molecular dynamic studies revealed that glycosylation disrupts calmodulins interaction with inducible nitric oxide synthase (iNOS), potentially explaining the decreased NO levels in TB-diabetes comorbid patients. These findings underscore the detrimental impact of AGEs and RAGE in diabetic immune dysregulation, highlighting the need for therapeutic strategies to mitigate their effects on macrophage function and restore immune responses. HighlightsO_LIWe conducted this study to examine how hyperglycemia-driven AGEs and RAGE contribute to immune dysfunction and disease severity in diabetic and TB-diabetes patients. C_LIO_LIHigh AGEs and RAGE impairs macrophage function, decreasing phagocytic capacity and worsening disease severity in TB-diabetes comorbidity. C_LIO_LIGlycosylation disrupts calmodulins interaction with iNOS, contributing to lower NO levels and weakened immune responses in TB-diabetes comorbidity. C_LIO_LIThe AGE-RAGE axis should be studied further for these comorbid conditions to assess and improve macrophage function and restore immune responses. C_LI

immunology↗

bioRxiv2024

Predicting Immunogenic CD4+ T Cell Epitopes in Bacteria Using Antigen and Peptide Features

BackgroundT cell epitope prediction methods have been broadly utilized to facilitate epitope discovery in infectious agents and help design reagents, diagnostics, and vaccines. Current prediction methods are mainly focused on peptide presentation by MHC molecules, which is a necessary but not sufficient requirement for an epitope. For complex pathogens such as bacteria, it would be desirable to make such predictions more specific to limit the number of candidates that have to be experimentally tested. ObjectiveTo develop a machine learning-based prediction model that integrates both peptide-level and antigen-level features to improve the specificity of CD4+ T cell epitope predictions for bacteria. MethodsWe used a dataset of 20,216 peptides from Mycobacterium tuberculosis (Mtb), tested for T cell recognition in Mtb-infected participants, that led to the discovery of n = 144 peptide epitopes. For each peptide, we calculated six peptide-level features (e.g. MHC class II binding predictions and conservation scores) and six antigen-level features (e.g. including RNA expression levels and subcellular localization scores). Three machine learning algorithms--Random Forest, Gradient Boosting, and XGBoost--were trained using stratified, 5-fold cross-validation and combined into an ensemble model. Experimental validation was performed on Streptococcus pneumoniae peptides, using ex vivo IFN{gamma} assays to confirm the predictive performance. ResultsThe ensemble model achieved an ROC-AUC of 0.91 in predicting immunogenic peptides in the Mycobacterium tuberculosis (Mtb) dataset. Gene expression and conservation were identified as the most impactful features, followed by MHC class II binding predictions. When validated on an independent Bordetella pertussis dataset, the model demonstrated accurate predictive capability, especially for peptides with broad recognition in the participant cohort (ROC-AUC up to 0.82). Prospectively applying the model to Streptococcus pneumoniae, we synthesized peptides predicted by our ensemble model to be immunogenic or non-immunogenic. Ex vivo testing with PBMCs from healthy participants showed that peptides predicted to be immunogenic elicited significantly higher IFN{gamma} responses than non-immunogenic peptides, validating the model. ConclusionsOur machine learning approach, integrating both peptide and antigen features, effectively predicts immunogenic CD4+ T cell epitopes across different bacterial pathogens. This method enhances epitope selection efficiency, aiding vaccine development and immunological research by reducing the need for extensive experimental screening.

immunology↗

bioRxiv2024

G-quadruplexes in the RSV genome: potential anti-viral targets.

The Rous sarcoma virus (RSV) is an onco-retrovirus that infects avian species such as the chicken (Gallus gallus). RSV is the first oncovirus to be described and the oncogenic activity of this virus is related to the expression of a tyrosine kinase that induces carcinogenic transformation. Interestingly, we have noted that the RSV genome contains various potential G4 forming sequences. Among these, two sequences located in the GAG and POL genes, respectively, show high G4 forming potential. Additionally, the SRC oncogene also harbours a putative G4 forming sequence. In this study, we have characterised the G4 formation and topology in these three loci in the RSV-DNA. We have found that these sequences form dynamic G4 structures in physiological conditions and such dynamicity may be associated with their cellular functions. Further, we have also established that these G4s are recognized by G4 interacting small-molecule ligands and the G4-stabilizing protein nucleolin. Binding of these ligands induces structural shifts in the G4 leading to change in structure and stability. Thus, the RSV-DNA G4s may be further studied as targets to control its infection and oncogenic effects.

biophysics↗

bioRxiv2024

Loss of the Inv(16) Oncogene CBFB::MYH11 Eliminates Leukemia from the Blood and Spleen, but not the Bone Marrow

Inversion of chromosome 16 [inv(16)] generates the fusion gene CBFB::MYH11 (CM) and is one of the most common chromosomal rearrangements in Acute Myeloid Leukemia (AML). Expression of CM is required for leukemia initiation. Patients with inv(16) at diagnosis invariably have the rearrangement at relapse, leading to the assumption that CM is also required after leukemic transformation. However, a role for CM in leukemia maintenance has yet to be shown experimentally. To address this, we used an inducible CM knockdown (KD) mouse model and found that decreased CM eliminated leukemia cells from the peripheral blood and spleen, but not the bone marrow, despite all populations exhibiting significantly decreased CM mRNA and protein. The surviving CM KD cells in the bone marrow showed decreased apoptosis and proliferation, and increased expression of autophagy related genes. Surprisingly, with prolonged KD of CM, [~]40% of mice re-established disease despite maintaining decreased CM. Our work indicates that CM is required for leukemia survival in the spleen and peripheral blood, but in the bone marrow CM KD leukemia cells can survive and re-establish disease independent of the fusion protein. These findings imply that targeting CM alone has potential to reduce leukemic burden but not cure the disease.

cancer biology↗

bioRxiv2024

RCoxNet: deep learning framework for enhanced cancer survival prediction integrating random walk with restart with mutation and clinical data

Cancer poses a significant global health challenge, characterized by a complex disease progression and disrupted growth regulation. A thorough understanding of cellular and molecular biological mechanisms is essential for developing novel treatments and improving the accuracy of patient survival predictions. While prior studies have leveraged gene expression and clinical data to forecast survival outcomes through current machine learning and deep learning approaches, gene mutation data--despite being a widely recognized metric--has rarely been incorporated due to its limited information, inadequate representation of gene relationships, and data sparsity, which negatively affects the robustness, effectiveness, and interpretability of current survival analysis approaches. To overcome the challenges of mutation data sparsity, we propose RCoxNet, a novel deep learning neural network framework that integrates the Random Walk with Restart (RWR) algorithm with a deep learning Cox Proportional Hazards model. By applying this framework to mutation data from cBioportal, our model achieved an average concordance index of 0.62 {+/-} 0.05 across four cancer types, outperforming existing deep neural network models. Additionally, we identified clinical features critical for differentiating between predicted high- and low-risk patients, with the relevance of these features being partially supported by previous studies.

bioinformatics↗

bioRxiv2024

Selective promotion of oligonucleotides in the course of evolution

Evolution shapes the structure and content of genomes, yet the contribution of local sequence composition to variant selection remains poorly understood. While traditional models emphasize protein function or cross-species conservation, we propose that intra-genomic patterns of oligonucleotide (k-mer) frequencies also reflect selective forces. To explore this, we developed kGain score, a metric that quantifies the frequency shift of a k-mer upon single-nucleotide substitution, using the surrounding genomic context as a baseline. We hypothesize that variants arising in high-kGain contexts are more likely to persist due to evolutionary favorability. We validated this hypothesis across multiple systems. In E. coli and S. cerevisiae long-term evolution experiments, we found that fixed, essential, and parallel mutations consistently show elevated kGain scores. This trend held in SARS-CoV-2 variants of concern and in an in-house antibiotic adaptation experiment, where a high-kGain fusA Y515N mutation conferred resistance and maintained fitness when overexpressed, demonstrating a causal link between kGain and adaptive potential. To enable cross-species generalization, we trained a transformer-based neural network regressor on LTEE-derived mutations to predict kGain from sequence alone. The model achieved high correlation in held-out in-domain data (Pearson r = 0.81) and accurately predicted kGain trends in out-of-domain data (Pearson r = 0.82), demonstrating that k-mer-based sequence constraints learned from one genome can be effectively transferred to others. Together, our results establish kGain as a biologically meaningful, scalable metric for probing within-genome sequence selection, offering a complementary lens to existing conservation-based frameworks for understanding evolutionary fitness and variant persistence.

evolutionary biology↗

bioRxiv2024

Purifying selection and intraspecies recombination may drive the speciation in Crassostrea: evidence from complete mitochondria sequence of Crassostrea hongkongensis and comparative genomic analysis

Repeat dynamics and recombination play a crucial role during the evolution of the mitochondrial genome in plants and animals. However, this phenomenon has got less attention within Crassostrea, a complex marine species found worldwide having high commercial value as well as efficient carbon neutralizer. During this study, we characterized the whole mitochondrial genomes of C. hongkongensis retrieved from transcriptome data (GenBank acc. no. MZ073671). The current mitochondrial genome (18,616 bp) was composed of a non-coding control region (D-loop region), 2 ribosomal RNA (rRNA genes), 12 protein-coding genes (PCGs), and 23 transfer RNA (tRNA). Furthermore, comparative genomics analysis revealed that the present isolate is closely related to the Chinese isolate (NC_011518) with 99.82% similarity. Microsatellite analysis within the mitochondrial genome revealed its bias towards mononucleotide repeat A/T, di-nucleotide AG followed by AT and AC, trinucleotide AAT followed by AAG, ATC, and ATG. The recombination analysis deciphered the lack of interspecific recombination, but the presence of intraspecific recombination within ND1, ND2, and ND4L of Crassostrea species. Selection pressure analysis revealed the presence of purifying selection within maximum genes which drive the evolution of the species.

evolutionary biology↗

bioRxiv2024

Remodeling Ca2+ dynamics by targeting a promising E-box containing G-quadruplex at ORAI1 promoter in triple-negative breast cancer.

ORAI1 is an intrinsic component of store-operated calcium entry (SOCE) that strictly regulates Ca2+ influx in most non-excitable cells. ORAI1 has been extensively studied to have been overexpressed in various cancer phenotypes, and its signal transduction has been associated with oncotherapy resistance. There is extensive proteomic interaction of ORAI1 with other channels and effectors, resulting in various altered phenotypes. However, the transcription regulation of this gene is not well understood. We have found a putative G-quadruplex (G4) motif, ORAI1-Pu, in the upstream promoter region of the gene, having regulatory functions. High-resolution 3-D NMR structure elucidation suggests that ORAI1-Pu is a stable parallel-stranded G4, having an unusual 8-nt loop imparting dynamics without affecting the structural stability. The protruded loop further houses an E-box motif that provides a docking site for transcription factors like Zeb1. The G4 structure was also endogenously observed using Chromatin Immunoprecipitation (ChIP) with anti-G4 antibody (BG4) in the MDA-MB-231 cell line overexpressing ORAI1. Ligand-mediated stabilization suggested that the stabilized G4 represses transcription in cancer cell line MDA-MB-231. Downregulation of transcription further cascaded down to a decrease in Ca2+ entry by the SOCE pathway, as observed by Fura-2 confocal Ca2+ imaging.

biochemistry↗

bioRxiv2024

In Silico designed cell-penetrating anti-cancer peptide specifically inhibits VEGF-A expression

Vascular Endothelial Growth Factor-A (VEGF-A), a pluripotent cytokine and angiogenic growth factor mediates the switch to an angiogenic phenotype in cancer cells. The interaction of VEGF-A protein with the VEGF receptors (VEGFR-1and VEGFR-2) starts downstream effect that promotes angiogenesis by mediating migration and increasing the permeability of endothelial cells. A cis-regulatory elements consisting of a polypurine/polypyrimidine (pPu/pPy) tract in the proximal 36-bp region (-85 to -50), can participate in the formation of a stable higher order G-quadruplex structure (G4) which is essential for VEGF promoter activity. During cancer progression the VEGF-A G4 succumbs to cellular pressure and fails to maintain the stable structure. This shifts the balance to form duplex structure thereby increasing the rate of transcription. Earlier research has tried to develop small-molecule ligands to target and stabilize G4, however they either lack specificity or non-toxicity. Peptide on the other hand are very less studied. Here we used bioinformatics in-silico tool to develop peptides which can successfully bind and stabilize the VEGF-A G4 while reducing its gene expression. This further alters the expression fate of the VEGF-A signalling cascade and prevents angiogenesis in cancer cells. We used high resolution Nuclear magnetic resonance and molecular dynamics simulation to map the chemistry of the interaction while the qPCR and western blot allowed us to check the expression pattern of the molecules of VEGF-A signalling cascade. In this investigation, we navigate the complex interplay between peptides and quadruplex structures, unravelling valuable insights that can enhance the crafting of pharmacophores directed at the dynamic quadruplex structure. The outcomes of our study are promising, paving the way for progress in the realms of research, characterization, and optimization of peptides binding to G-quadruplexes, with potential implications for therapeutic applications.

biophysics↗

bioRxiv2024

ALTering cancer by triggering telomere replication stress through the stabilization of promoter G-quadruplex in SMARCAL1

Most of the human cancers are dependent on telomerase to extend the telomeres. But [~]10% of all cancers use a telomerase-independent, homologous recombination mediated pathway called alternative lengthening of telomeres (ALT). Due to poor prognosis, the ALT status is not being considered yet in the diagnosis of cancer. No such specific treatment is available till date for ALT cancers. ALT positive cancers are dependent on replication stress to deploy DNA repair pathways to the telomeres to execute homology recombination mediated telomere extension. SMARCAL1 (SWI/SNF related, matrix-associated, actin-dependent regulator of chromatin, subfamily A-like 1) is associated with the ALT telomeres to resolve replication stress thus providing telomere stability. Thus, the dependency on replication stress regulatory factors like SMARCAL1 made it a suitable therapeutic target for the treatment of ALT positive cancers. In this study, we found a significant downregulation of SMARCAL1 expression by stabilizing the G-quadruplex (G4) motif found in the promoter of SMARCAL1 by potent G4 stabilizers, like TMPyP4 and BRACO-19. SMARCAL1 downregulation led towards the increased localization of PML (promyelocytic leukaemia) bodies in ALT telomeres and triggered the formation of APBs (ALT-associated promyelocytic leukaemia bodies) in ALT positive cell lines, thus increasing telomere replication stress and DNA damage at genomic level. Induction of replication stress and hyper recombinogenic phenotype in ALT cells mediated by G4 stabilizing molecules already highlighted their possible application as a new therapeutic window to target ALT-positive tumors. In accordance with this, our study will also provide a valuable insight towards the development of G4 based ALT-therapeutics targeting SMARCAL1.

biochemistry↗

bioRxiv2024

Staphylococcus aureus counters organic acid anion-mediated inhibition of peptidoglycan cross-linking through robust alanine racemase activity

Weak organic acids are commonly found in host niches colonized by bacteria, and they can inhibit bacterial growth as the environment becomes acidic. This inhibition is often attributed to the toxicity resulting from the accumulation of high concentrations of organic anions in the cytosol, which disrupts cellular homeostasis. However, the precise cellular targets that organic anions poison and the mechanisms used to counter organic anion intoxication in bacteria have not been elucidated. Here, we utilize acetic acid, a weak organic acid abundantly found in the gut to investigate its impact on the growth of Staphylococcus aureus. We demonstrate that acetate anions bind to and inhibit D-alanyl-D-alanine ligase (Ddl) activity in S. aureus. Ddl inhibition reduces intracellular D-alanyl-D-alanine (D-Ala-D-Ala) levels, compromising staphylococcal peptidoglycan cross-linking and cell wall integrity. To overcome the effects of acetate-mediated Ddl inhibition, S. aureus maintains a substantial intracellular D-Ala pool through alanine racemase (Alr1) activity and additionally limits the flux of D-Ala to D-glutamate by controlling D-alanine aminotransferase (Dat) activity. Surprisingly, the modus operandi of acetate intoxication in S. aureus is common to multiple biologically relevant weak organic acids indicating that Ddl is a conserved target of small organic anions. These findings suggest that S. aureus may have evolved to maintain high intracellular D-Ala concentrations, partly to counter organic anion intoxication. SignificanceUnder mildly acidic conditions, weak organic acids like acetic acid accumulate to high concentrations within the cytosol as organic anions. However, the physiological consequence of organic anion accumulation is poorly defined. Here we investigate how the acetate anion impacts S. aureus. We show that acetate anions directly bind Ddl and inhibit its activity. The resulting decrease in intracellular D-Ala-D-Ala pools impacts peptidoglycan integrity. Since acetate is a weak inhibitor of Ddl, mechanisms that maintain a high intracellular D-Ala pools are sufficient to counter the effect of acetate-mediated Ddl inhibition in S. aureus.

microbiology↗

bioRxiv2023

Genome-wide and chromosomal microsatellite marker landscape analysis within the genus Crassostrea

Microsatellite is a classical codominant marker frequently used to study genetics and evolution of living entities as well as molecular breeding in commercially important species. Although it has a tremendous application in oyster aquaculture, the lack of knowledge about its type, distribution pattern, and comparative analysis is limited. Thus, in this study, we conducted a genome-wide as well as chromosomal microsatellite landscape analysis within the genus Crassostrea. The genome-wide microsatellites number varied from 169432-212368, with relative abundance (RA) and relative density (RD) ranging from 310.18-336.5 loci/Mb and 7553.4-8793.42 bp/Mb, respectively. About 14.99-16.75% of total microsatellites were considered compound microsatellites having cRA and cRD, 21.78-25.5 loci/Mb, and 1332.81-1694.54 bp/Mb, respectively. The mononucleotide microsatellites were predominant followed by di and tetranucleotide. The RA and RD of the SSRs revealed no correlation with genome size but a significant correlation with GC content. However, the number of SSRs showed a significant relationship with the genome size but no relation with GC content. In contrast, the incidence of cSSR was positively associated with genome size and GC content. Finally, 29 cSSR loci were developed and validated in C. hongkonensis using one wild population followed by its cross-species amplification. The allele number (Ne), observed heterozygosity (Ho), expected heterozygosity (He), inbreeding co-efficient (Fis), the polymorphic information content (PIC), ranged from 2-10, 0.092-0.897, 0.0001-1, 0.088-0.828, respectively. The present study elucidated microsatellite evolution within the Crassostrea genome and the loci developed can be utilized for brood stock analysis, parentage assignment, and construction of linkage map of the respective species.

genomics↗

bioRxiv2023

First complete genome characterization of an Indian pigeon pox virus directly from a clinical sample

Avian pox disease is a highly contagious infection caused by pox virus and has serious consequences on avian species with regards to economic and conservation aspects. This viral genus named as Avipox virus (APV) that infects nearly 300 bird species and lack of enough complete genome information creates hindrance to infer this virus biology. Thus in this study, we have revealed the first complete genome of an Indian pigeon pox virus that belongs to the genus APV followed by comparative genomics analysis. The entire genome of present isolate (PPV/Pur-Od-4b/01/Ind) having 280058 bp nucleotide sequences with the GC content 29.51%. The unique feature of this complete genome revealed the presence of 270 open reading frames (ORFs) circumscribed by inverted terminal repeats (ITRs) of 4,689 bp at each end and lack of recombination events. The concatenated amino acid phylogenetic tree deciphered the present isolate closely related with Feral Pigeon pox virus derived from Africa. The molecular markers, such as microsatellites were ubiquitously distributed throughout the genome and more prevalent within the functional genes.

evolutionary biology↗

bioRxiv2023

FiPhA: An Open-Source Platform for Fiber Photometry Analysis

SignificanceFiber photometry is a widely used technique in modern behavioral neuroscience, employing genetically encoded fluorescent sensors to monitor neural activity and neurotransmitter release in awake-behaving animals, However, analyzing photometry data can be both laborious and time-consuming. AimWe propose the FiPhA (Fiber Photometry Analysis) app, which is a general-purpose fiber photometry analysis application. The goal is to develop a pipeline suitable for a wide range of photometry approaches, including spectrally resolved, camera-based, and lock-in demodulation. ApproachFiPhA was developed using the R Shiny framework and offers interactive visualization, quality control, and batch processing functionalities in a user-friendly interface. ResultsThis application simplifies and streamlines the analysis process, thereby reducing labor and time requirements. It offers interactive visualizations, event-triggered average processing, powerful tools for filtering behavioral events and quality control features. ConclusionsFiPhA is a valuable tool for behavioral neuroscientists working with discrete, event-based fiber photometry data. It addresses the challenges associated with analyzing and investigating such data, offering a robust and user-friendly solution without the complexity of having to hand-design custom analysis pipelines. This application thus helps standardize an approach to fiber photometry analysis.

neuroscience↗

bioRxiv2023

Identification of differentially recognized T cell epitopes in the spectrum of Mtb infection

Tuberculosis caused by Mycobacterium tuberculosis is one of the leading causes of death from a single infectious agent. Identifying dominant epitopes and comparing their reactivity in different tuberculosis (TB) infection states can help design diagnostics and vaccines. We performed a proteome-wide screen of 20,610 Mtb derived peptides in 21 Active TB (ATB) patients 3-4 months post-diagnosis of pulmonary TB (mid-treatment) using an IFN{gamma} and IL-17 Fluorospot assay. Responses were mediated exclusively by IFN{gamma} and identified a total of 137 unique epitopes, with each patient recognizing, on average, 8 individual epitopes and 22 epitopes (16%) recognized by 2 or more participants. Responses were predominantly directed against antigens part of the cell wall and cell processes category. Testing 517 peptides spanning TB vaccine candidates and ESAT- 6 and CFP10 antigens also revealed differential recognition between ATB participants mid-treatment and healthy IGRA+ participants of several vaccine antigens. An ATB-specific peptide pool consisting of epitopes exclusively recognized by participants mid-treatment, allowed distinguishing participants with active pulmonary TB from healthy interferon-gamma release assay (IGRA)+/- participants from diverse geographical locations. Analysis of longitudinal samples indicated decreased reactivity during treatment for pulmonary TB. Together, these results show that a proteome-wide screen of T cell reactivity identifies epitopes and antigens that are differentially recognized depending on the Mtb infection stage. These have potential use in developing diagnostics and vaccine candidates and measuring correlates of protection.

immunology↗

bioRxiv2023

Inferring B-cell derived T-cell receptor induced multi epitope-based vaccine candidate against enterovirus 71 (EV 71): A reverse vaccinology approach.

In addition to Coxsackie virus (CV), another pathogen that causes Hand-foot and mouth disease (HFMD), Enterovirus 71 (EV 71) is currently regarded as an increasing neurotropic virus in Asia and can cause severe complications in paediatric patients with blister like sores or rashes on the hand, feet and mouth. Not withstanding the significant burden of the disease, few treatments are currently available, and there is no authorised vaccine available for the disease prevention. Several vaccinations based on attenuated and inactivated vaccines have previously been identified, however they become worthless over time owing to changes in the viral genome. As a result, the goal of the study is to create an immunoinformatics and reverse vaccinology pipeline for predicting a multi epitope vaccine. A novel vaccine construct using B-cell derived T-cell epitopes from the virulent polyprotein and found the induction of possible immune response, in order to boost the immune system, aBeta-defensin 1 preproprotein adjuvant with EAAAK linker was added at the N-terminal end of the vaccine sequence. The immunogenicity of the designed, refined, and verified prospective 3D- structure of multi-epitope vaccine was found to be quite high with non-allergen, and antigenic property. The vaccine candidates bound to the TLR-3 in a molecular docking analysis and the efficacy of the potential vaccine to generate a strong immune response was assessed by means of an in silico immunological simulation. Computational analysis has shown that the proposed multi epitope vaccine possibility safe for use in humans and elicit an immune response, making it a promising tool against HFMD viral genome.

immunology↗