Biology subjects

Kumar, N.

Publications and source records attributed to Kumar, N..

At least 127 records · Page 7Linked to original sources

bioRxiv2022

Differential scanning fluorimetry as a measure of functionality of refolded anti-malarial antibody fragments

Transmission blocking monoclonal antibodies, 4B7 and 1245, targeting Pfs25, have been demonstrated to block the developmental stages of the malarial parasite inside the mosquitoes. In this work, anti-Plasmodium antibody fragments of 4B7 and 1245, designated as diabodies, were expressed in bacteria and refolded using a standardized method, with a yield of 0.1 and 0.4 mg per litre of culture, respectively. Dimeric species was detected for 4B7-Db, but not for 1245-Db, using glutaraldehyde cross-linking experiment. The quality of the purified refolded fraction was assessed with differential scanning fluorimetry (DSF). Refolded 4B7-Db, with a melting temperature of 59{degrees}C, recognized Pfs25 expressed on the surface of ookinete and zygote stages of Plasmodium in an immunofluorescence-based assay, whereas, 1245-Db, exhibiting a skewed melt profile, showed weak recognition. Further, refolded 4B7-Db recognized the linear epitope, on purified Pfs25 protein, both in the denatured and native state. Differential scanning fluorimetry can be potentially employed as a qualitative measure of functionality, to evaluate refolded proteins, with applicability for antibody engineering in passive immunization.

biochemistry↗

bioRxiv2022

Harmonin homology domains of human RTEL1 interact with replication protein A and DNA

The regulator of telomere elongation helicase 1 (RTEL1) is an Fe-S cluster containing helicase that plays important roles in telomere DNA maintenance, DNA repair, and genome stability. It is a modular protein comprising a helicase domain, two tandem harmonin homology domains 1 & 2 (HHD1 and HHD2), and a Zn2+ binding RING domain. In this study, we have unravelled a novel interaction between RTEL1 and replication protein A (RPA) and shown their co-localization upon DNA damage in the cells. Using NMR spectroscopy, we show that 32C domain of RPA and DNA competitively bind with HHD2 of RTEL1. To understand the structural basis of HHD2 - 32C and HHD2 - DNA interactions, we have determined a 1.6 [A] resolution crystal structure of HHD2. NMR chemical shift perturbations-based mapping revealed the 32C and DNA binding surface on HHD2 of RTEL1. Together, these results establish an interplay among RTEL1, RPA, and DNA that provide mechanistic insights into the RTEL1 recruitment at DNA during the processes of replication, repair, and recombination.

biophysics↗

bioRxiv2022

Identification of a TNF-TNFR-like system in malaria vectors (Anopheles stephensi) likely to influence Plasmodium resistance

Identification of Plasmodium-resistance genes in malaria vectors remains an elusive goal despite the recent availability of high-quality genomes of several mosquito vectors. An. stephensi, with its three distinctly-identifiable forms at the egg stage, correlating with varying vector competence, offers an ideal species to discover functional mosquito genes implicated in Plasmodium resistance. Recently, the genomes of several strains of An. stephensi of the type-form, known to display high vectorial capacity, have been reported. Here, we report a chromosomal-level assembly of an intermediate-form of An. stephensi strain (IndInt), shown to have reduced vectorial capacity relative to a strain of type-form (IndCh). The contig level assembly with a L50 of 4 was scaffolded into chromosomes by using the genome of IndCh as the reference. The final assembly shows a heterozygous paracentric inversion, 3Li, involving 8 Mbp, which is syntenic to the extensively-studied 2La inversion implicated in Plasmodium resistance in An. gambiae involving 21 Mbp. Deep annotation of genes within the 3Li region in IndInt assembly using the state-of-the-art protein-fold prediction and other annotation tools reveals the presence of a TNF-like gene, which is the homolog of the eiger gene in Drosophila. Subsequent chromosome-wide searches revealed homologs of wengen (wgn) and grindelwald (grnd) genes in IndInt, which are known to be the receptors for eiger in Drosophila. We have identified all the genes in IndInt required for eiger-mediated signaling by analogy to TNF-TNFR system, suggesting the presence of a functionally active eiger signaling pathway present in IndInt. Comparative genomics of high-quality genome assemblies of the three type-forms with that of IndInt, reveals structurally disruptive mutations in eiger gene in all three strains of the type-form, alluding to compromised innate immunity in the type-form as the cause of high vectorial capacity in these strains. This is the first report of the presence of an intact evolutionarily-conserved TNF-TNFR signaling system in malaria vectors, with a potential role in Plasmodium resistance.

genomics↗

bioRxiv2022

Characterization and Preclinical Treatment of Rotational Force-Induced Brain Injury

Millions of traumatic brain injuries (TBIs) occur annually. TBIs commonly result from falls, traffic accidents, and sports-related injuries, all of which involve rotational acceleration/deceleration of the brain. During these injuries, the brain endures a multitude of primary insults including compression of brain tissue, damaged vasculature, and diffuse axonal injury. All of these deleterious effects can contribute to secondary brain ischemia, cellular death, and neuroinflammation that progress for weeks to months after injury and impede neurological recovery. While the linear effects of head trauma have been extensively modeled, less is known about how rotational injuries mediate neuronal damage following injury. Here, we developed a new model of rotational head trauma in rodents and extensively characterized the pathological, behavioral, and electrophysiological effects of rotational TBI (rTBI). We identify aberrant cyclin dependent kinase 5 (Cdk5) activity as a principal mediator of rTBI and show pharmacological inhibition of Cdk5 reduces the cognitive and pathological consequences of injury. Finally, we utilize Cdk5-enriched phosphoproteomics to uncover potential downstream mediators of rTBI. These studies contribute meaningfully to our understanding of the mechanisms of rTBI and how they may be effectively treated.

neuroscience↗

bioRxiv2022

Identification of Antigenic Regions Responsible for inducing Type 1 diabetes mellitus

There are a number of antigens that induce autoimmune response against {beta}-cells, leading to Type 1 diabetes mellitus (T1DM). Recently several antigen-specific immunotherapies have been developed to treat T1DM. Thus identification of T1DM associated peptides with antigenic regions or epitopes is important for peptide based-therapeutics (e.g., immunotherapeutic). In this study, for the first time an attempt has been made to develop a method for predicting, designing and scanning of T1DM associated peptides with high precision. We analyzed 815 T1DM associated peptides and observed that these peptides are not associated with a specific class of HLA alleles. Thus, HLA binder prediction methods are not suitable for predicting T1DM associated peptides. Firstly, we developed a similarity/alignment based method using BLAST and achieved a high probability of correct hits with poor coverage. Secondly, we developed an alignment free method using machine learning techniques and got maximum AUROC 0.89 using dipeptide composition. Finally, we developed a hybrid method that combines the strength of both alignment free and alignment based methods and achieve maximum AUROC 0.95 with MCC 0.81 on independent dataset. We developed a webserver "DMPPred" and standalone server, for predicting, designing and scanning of T1DM associated peptides (https://webs.iiitd.edu.in/raghava/dmppred/). Key PointsO_LIPrediction of peptides responsible for inducing immune system against {beta}-cells C_LIO_LICompilation and analysis of Type 1 diabetes associated HLA binders C_LIO_LIBLAST based similarity search against Type 1diabetes associated peptides C_LIO_LIAlignment free method using machine learning techniques and composition C_LIO_LIA hybrid method using alignment free and alignment based approach C_LI Authors BiographyO_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_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_LIShubham Choudhury is currently working as Ph.D. in Computational biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India C_LIO_LIRitu Tomer 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_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↗

bioRxiv2022

A comprehensive proteomic and bioinformatics analysis of human spinal cord injury plasma identifies proteins associated with the complement cascade and liver function as potential prognostic indicators of neurological outcome

1.1.1. IntroductionSpinal Cord Injury (SCI) is a major cause of disability, with complications post-injury often leading to life-long health issues with need of extensive treatment. Neurological outcome post-SCI can be variable and difficult to predict, particularly in incomplete injured patients. The identification of specific SCI biomarkers in blood, may be able to improve prognostics in the field. This study has utilised proteomic and bioinformatics methodologies to investigate differentially expressed proteins in plasma samples across human SCI cohorts with the aim of identifying prognostic biomarkers and biological pathway alterations that relate to neurological outcome. 1.2. Methods and MaterialsBlood samples were taken, following informed consent, from ASIA impairment scale (AIS) grade C "Improvers" (those who experienced an AIS grade improvement) and "Non-Improvers" (No AIS change), and AIS grade A and D at <2 weeks ("Acute") and approx. 3 months ("Sub-acute") post-injury. The total protein concentration from each sample was extracted, with pooled samples being labelled and non-pooled samples treated with ProteoMiner beads. Samples were then analysed using two 4-plex isobaric tag for relative and absolute quantification (iTRAQ) analyses and a label-free experiment for comparison, before quantifying with mass spectrometry. Data are available via ProteomeXchange with identifiers PXD035025 and PXD035072 for the iTRAQ and label-free experiments respectively. Proteomic datasets were analysed using OpenMS (version 2.6.0). R (version 4.1.4) and in particular, the R packages MSstats (version 4.0.1) and pathview (version 1.32.0) were used for downstream analysis. Proteins of interest identified from this analysis were further validated by enzyme-linked immunosorbent assay (ELISA). 1.3. ResultsThe data demonstrated proteomic differences between the cohorts, with the results from the iTRAQ approach supporting those of the label-free analysis. A total of 79 and 87 differentially abundant proteins across AIS and longitudinal groups were identified from the iTRAQ and label-free analyses, respectively. Alpha-2-macroglobulin (A2M), retinol binding protein 4 (RBP4), serum amyloid A1 (SAA1), Peroxiredoxin 2, Apolipoprotein A1 (ApoA1) and several immunoglobulins were identified as bio-logically relevant and differentially abundant, with potential as individual prognostic biomarkers of neurological outcome. Bioinformatics analyses revealed that the majority of differentially abundant proteins were components of the complement cascade and most interacted directly with the liver. 1.4. ConclusionsMany of the proteins of interest identified using proteomics were detected only in a single group and therefore have potential as a binary (present or absent) biomarkers, RBP4 and PRX-2 in particular. Additional investigations into the chronology of these proteins, and their levels in other tissues (cerebrospinal fluid in particular) are needed to better understand the underlying pathophysiology, including any potentially modifiable targets. Pathway analysis highlighted the complement cascade as being significant across groups of differential functional recovery.

bioinformatics↗

bioRxiv2022

Selection for greater dispersal in early life leads to increased rate of age-dependent decline in locomotor activity and shorter lifespan

Locomotor activity is one of the major traits that is affected by age. Greater locomotor activity is also known to evolve in the course of dispersal evolution. However, the impact of dispersal evolution on the functional senescence of locomotor activity is largely unknown. We addressed this knowledge gap using large outbred populations of Drosophila melanogaster selected for increased dispersal. We tracked locomotor activity of these flies at regular intervals until a late age. Longevity of these flies was also recorded. We found that locomotor activity declines with age in general. However interestingly, activity level of dispersal selected populations never drops below the ancestry-matched-controls, despite the rate of age-dependent decline in activity of the dispersal selected populations being greater than their respective controls. Dispersal selected population was also found to have shorter lifespan as compared to its control, a potential cost of elevated level of activity throughout their life. These results are crucial in the context of invasion biology as contemporary climate change, habitat degradation, and destruction provide congenial conditions for dispersal evolution. Such controlled and tractable studies investigating the ageing pattern of important functional traits are important in the field of biogerontology as well.

evolutionary biology↗

bioRxiv2022

Novel Antibody Interfaces Revealed Through Structural Mining

Antibodies are fundamental effectors of humoral immunity, and have become a highly successful class of therapeutics. There is increasing evidence that antibodies utilize transient homotypic interactions to enhance function, and elucidation of such interactions can provide insights into their biology and new opportunities for their optimization as drugs. Yet the transitory nature of weak interactions makes them difficult to investigate. Capitalizing on their rich structural data and high conservation, we have characterized all the ways that antibody Fab regions interact crystallographically. This approach led to the discovery of previously unrealized interfaces between antibodies. While diverse interactions exist, {beta}-sheet dimers and variable-constant elbow dimers are recurrent motifs. Disulfide engineering enabled interactions to be trapped and investigated structurally and functionally, providing experimental validation of the interfaces and illustrating their potential for optimization. This work provides first insight into previously undiscovered oligomeric interactions between antibodies, and enables new opportunities for their biotherapeutic optimization.

biochemistry↗

bioRxiv2022

Single-Molecule Analysis of DNA-binding proteins from Nuclear Extracts (SMADNE)

Single-molecule characterization of protein-DNA dynamics provides unprecedented mechanistic details about numerous nuclear processes. Here, we describe a new method that rapidly generates single-molecule information for fluorescently tagged proteins isolated from nuclear extracts of human cells. This approach determines binding lifetimes (koff), events per second ([~]kon), positional dependence (specificity), and characterizes 1D diffusion along DNA. We demonstrated the wide applicability of this approach on three forms of DNA damage using seven native DNA repair proteins and two structural variants, including: poly(ADP-ribose) polymerase (PARP1), heterodimeric ultraviolet-damaged DNA-binding protein (UV-DDB), xeroderma pigmentosum complementation group C protein (XPC), and 8-oxoguanine glycosylase 1 (OGG1). By measuring multiple fluorescent colors simultaneously, we additionally characterized the assembly and disassembly kinetics of multi-protein complexes on DNA. Thus, Single-Molecule Analysis of DNA-binding proteins from Nuclear Extracts (SMADNE) provides new insights about damage recognition and represents a universal technique that can be used to rapidly characterize numerous protein-DNA interactions.

molecular biology↗

bioRxiv2022

Concurrent separation of phase-locked and non-phase-locked activity

Brain dynamics recorded via electroencephalography (EEG) is conceptualized as a sum of two components, "phase-locked" and "non-phase-locked" to the stimulus. Both activities are understood to be stemming from different neuronal mechanisms and hence accurately characterizing them is of immense importance in neuroscientific studies. Here, we discuss the drawbacks of currently used methods to separate the phase-locked and non-phase-locked activity and propose a new method that decomposes the two components simultaneously. First, we demonstrate that single-trial separation of phase-locked and non-phase-locked power is an ill-posed problem. Second, using simulations where ground truth validation is possible, we elucidate the drawbacks of the widely used averaging method and efficacy of the proposed concurrent phaser method (CPM). Using two experimental datasets, audio oddball EEG data and auditory steady-state responses (ASSR) we show how the empirical signal-to-noise estimates warrant the usage of CPM to separate phase-locked and non-phase-locked activity.

neuroscience↗

bioRxiv2022

The NIN-LIKE PROTEIN 7 (NLP7) transcription factor modulates auxin pathways to regulate root cap development

The root cap surrounds the root tip and promotes root growth by protecting the root apical meristem, influencing root branching, and sensing environmental signals like nitrate. The root cap maintains a constant size through the coordination of cell production in the root meristem with cell release at the tip of the root, a process that requires an auxin minima in the last layer of the root cap. To perform its functions, the root cap must maintain a constant size and synchronize external cues with development, but mechanisms underlying such coordination are not well understood. Mutations in the NIN LIKE PROTEIN 7 (NLP7) transcription factor, a master regulator of nitrate signaling, lead to defects in root cap cell release and cell production. Nitrate impacts root development through crosstalk with auxin. Therefore, we hypothesized that NLP7 regulates root cap cell release and cell production by modulating auxin pathways. Here we show that mutations in NLP7 abolish the auxin minima required for root cap cell release and alter root cap expression levels of the auxin carriers PIN-LIKES 3 (PILS3) and PIN-FORMED 7 (PIN7). We find that NLP7 is required for proper root cap cell production and differentiation and for expression of transcription factors that regulate these processes. Nitrate deficiency impacts auxin pathways in the last layer of the root cap, and this is mediated in part by NLP7. Together, our data suggest that NLP7 integrates nitrate signaling with auxin pathways to optimize root cap development in response to external nitrate cues. One sentence summaryThe nitrate master regulator NLP7 controls root cap development through auxin pathways.

plant biology↗

bioRxiv2022

Using machine learning to understand microgeographic determinants of the Zika vector, Aedes aegypti

There are limited data on why the 2016 Zika outbreak in Miami-Dade County, Florida was confined to certain neighborhoods. In this research, Aedes aegypti, the primary vector of Zika virus, are studied to examine neighborhood-level differences in their population dynamics and underlying processes. Weekly mosquito data were acquired from the Miami-Dade County Mosquito Control Division from 2016 to 2020 from 172 traps deployed around Miami-Dade County. Using Random Forest, a machine learning method, predictive models of spatiotemporal dynamics of Ae. aegypti in response to meteorological conditions and neighborhood-specific socio-demographic and physical characteristics, such as land-use and land-cover type and income level, were created. The study area was divided into two groups: areas affected by local transmission of Zika during the 2016 outbreak and unaffected areas. Aedes aegypti populations in areas affected by Zika were more strongly influenced by 14- and 21-day lagged weather conditions. In the unaffected areas, mosquito populations were more strongly influenced by land-use and day-of-collection weather conditions. There are neighborhood-scale differences in Ae. aegypti population dynamics. These differences in turn influence vector-borne disease diffusion in a region. These results have implications for vector control experts to lead neighborhood-specific vector control strategies and for epidemiologists to guide vector-borne disease risk preparations, especially for containing the spread of vector-borne disease in response to ongoing climate change.

ecology↗

bioRxiv2022

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum using Multiscale Phenotypes

Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.

plant biology↗

bioRxiv2022

A novel consensus-based computational pipeline for rapid screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including omicron variant

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike proteins receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with three-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero-dimeric and -trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concern (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variants RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118) -- that may likely neutralize the recently emerged omicron variant -- facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants.

bioinformatics↗

bioRxiv2022

In vitro demonstration of broad host range mobile genetic elements transferring antibiotic resistance from the human microbiome

Mobile genetic elements (MGEs) carrying antibiotic resistance genes (ARGs) disseminate ARGs when they mobilise into new bacterial hosts. To investigate the scale of such horizontal gene transfer (HGT) events between human gut commensals and enteropathogens for the first time, we compared 1354 cultured commensal strains (540 species) to 45,403 enteropathogen strains (12 species) and found 64,188 MGE-mediated ARG transfer events between the two groups using established methods. Among the 5931 MGEs involved, we found 15 broad host range elements predicted to have crossed different bacterial phyla while also occurring in animal and environmental microbiomes. We experimentally demonstrated that predicted broad host range MGEs can mobilise from commensals Dorea longicatena and Hungatella hathewayi to enteropathogens Klebsiella oxytoca, crossing phyla simultaneously. Our work establishes the MGE-mediated ARG dissemination network between human gut commensals and enteropathogens and highlights novel broad host range MGEs as targets for future ARG dissemination management.

genomics↗

bioRxiv2022

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: implications for future surveillance programmes

Understanding the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unsolved challenge for the scientific communities across the world. A key to dissect the susceptibility profiles of animal species to SARS-CoV-2 is to understand how virus enters into the cells. The interaction of SARS-CoV-2 ligands (RBD on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the spike protein of SARS-CoV-2 can bind to many vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Additionally, the present study facilitated the identification of genetic determinants that may differentiate susceptible from the resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified susceptibility of bat species to SARS-CoV-2. The findings from current study highlight the importance of intensive surveillance programs aimed at identifying susceptible hosts, particularly those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

bioinformatics↗

bioRxiv2022

TEX13B is important for germ cell development and male fertility

The recent epidemiological studies suggest that nearly one out of every 7 reproductive age couples face problem to conceive a child after trying for at least one year. Impaired fertility of the male partner is causative in approximately 50% of the infertile couples. However, the etiologies of large proportion of male infertility are still unclear. Our unpublished exome sequencing data identified several novel genes including TEX13B, which motivated us to further explore the role of TEX13B in male infertility in large infertile case control cohort. Hence in this study, we have examined the role of TEX13B in male infertility by whole gene sequencing 628 infertile and 427 control men and have demonstrated the functional role of Tex13b in spermatogonia GC1spg (GC1) cells. We identified 2 variants on TEX13B which are tightly associated with male infertility. TEX13B gene exclusively expressed in germ cells, but its molecular functions in germ cells are still unknown. Hence, we demonstrated the functional importance of Tex13b in GC1 cell line by genomic manipulation via CRISPR-Cas9 and mass spectrometry-based whole cell proteomics. The gene knock out in GC1 cell line clearly shows that Tex13b play an important role in germ cell growth and morphology. We demonstrate that Tex13b knockout or conditional overexpression in GC1 cells reprograms the metabolic status from an oxidative phosphorylation to glycolysis state and vice versa. In conclusion, our study clearly showed the importance of Tex13b in germ cells development and Its association with male infertility.

genetics↗

bioRxiv2021

A vitamin D-RelB/NF-κB pathway limits Chandipura virus multiplication by rewiring the homeostatic state of autoregulatory type 1 interferon-IRF7 signaling

Besides its functions in the skeletomuscular system, vitamin D also promotes protective immunity against viral pathogens. Viral sensing by mammalian cells triggers nuclear activation of RelA/NF-{kappa}B and IRF3 factors, which collaborate in mediating the early induction of antiviral type 1 interferons (T1-IFNs). Autocrine T1-IFN signaling further accumulates otherwise negligibly expressed IRF7 in virus-infected cells that then sustains T1-IFN production in a positive feedback. Surprisingly, prior cell-culture studies revealed that vitamin D actually suppresses signal-induced RelA activation. Indeed, it remains unclear how vitamin D limits viral multiplication in a cell-autonomous manner. Here, we examined the role of vitamin D in controlling cellular infections by the Chandipura virus (CHPV), a cytoplasmic RNA virus implicated in human epidemics. We found that vitamin D conditioning produced an altered cell state less permissive for CHPV multiplication because of the heightened expression of T1-IFNs. It is thought that viruses also induce a distinct RelB/NF-{kappa}B activity, which counteracts RelA-driven T1-IFN expressions in infected cells. Our analyses instead characterized a basal nuclear RelB activity, which was downregulated upon vitamin D-mediated suppression of RelB synthesis. Interestingly, this vitamin D-RelB pathway provoked IRF7-mediated positive autoregulation augmenting constitutive T1-IFN expressions even in the absence of viral infections. Accordingly, RelB deficiency rendered redundant, while IRF7 depletion abrogated antiviral vitamin D actions. In sum, our study suggests that the homeostatic state of the signaling circuitry comprising of the NF-{kappa}B and T1-IFN pathways connects micronutrients to antiviral immunity at the cellular level. Significance statementVitamin D limits viral infections, but the underlying mechanism remains unclear. Linking micronutrients to antiviral immunity, Ratra et al. characterize an immune signaling circuitry engaged by vitamin D that generates a cellular state less permissive to infections by Chandipura virus, a pathogen of public health importance.

immunology↗