Biology subjects

Srivastava, A. K.

Publications and source records attributed to Srivastava, A. K..

At least 19 recordsLinked to original sources

bioRxiv2026

Deep Brain Stimulation Microelectrodes as a Source of Human Subcortical RNA: Validation of a Low-Input Transcriptomic Protocol

BackgroundUnderstanding the molecular basis of Parkinsons disease (PD) phenotypic heterogeneity maybe improved by in vivo access to deep brain tissue. Deep brain stimulation (DBS) surgery offers a unique opportunity: microelectrodes traversing the subthalamic nucleus (STN) carry adherent brain tissue upon withdrawal, providing a source of RNA from subcortical regions in living patients without additional invasive procedures. AimTo develop and validate a low-input RNA extraction and transcriptomic profiling protocol using DBS microelectrodes in post-mortem human brain, to confirm that recovered RNA is of brain rather than blood origin, and to characterise its sub-regional and cellular identity. MethodologyDBS microelectrodes were inserted without image guidance or guide tube into three unfixed post-mortem human brains targeting the STN trajectory. In clinical practice, a guide tube shields the electrode from cortical tissue; its absence here means tissue from the full insertion trajectory may contribute to recovered RNA. Thirty-eight microelectrodes were evaluated across single and pooled strategies. RNA was extracted using a modified RNeasy Micro low-input protocol; libraries prepared using NEBNext Single Cell/Low Input RNA Library Kit and sequenced on Illumina NovaSeq 6000 (paired-end, 2x150 bp). Tissue identity was validated against GTEx v10 (54 tissues) and Allen Human Brain Atlas (ABA, 19 subcortical regions including STN) using Pearson correlation with permutation testing (1,000 permutations) and BH-FDR correction. Transcriptional overlap between subcortical and cortical reference regions was quantified and subcortical-enriched gene filtering performed. ResultsTwenty-five RNA isolates were obtained from 38 microelectrodes; 54.5% of Bioanalyzer-assessed samples achieved RIN [≥]5 (median 7.1; range: 5.9-7.8). Fifteen libraries passed sequencing QC (mean depth 43.0 {+/-} 14.1 million read pairs; mean Q30 83.2 {+/-} 5.6 %). PCA of rlog transformed expression data resolved samples by donor identity. All samples confirmed brain tissue origin by GTEx {tau}-index tissue specificity correlation (n=996 brain and blood specific markers). Brain correlations were highest for frontal cortex (mean r= 0.683 {+/-} 0.072), anterior cingulate cortex (mean r= 0.658 {+/-} 0.069), amygdala (mean r= 0.615 {+/-} 0.068), and basal ganglia including caudate (mean r= 0.553 {+/-} 0.059), putamen (mean r= 0.546 {+/-} 0.059), and nucleus accumbens (mean r= 0.544 {+/-} 0.057); all BH-FDR < 0.05. Cerebellum showed the lowest brain correlations (cerebellar hemisphere: mean r = 0.327 {+/-} 0.039; cerebellum: mean r = 0.314 {+/-} 0.037). Whole blood correlation was strongly negative (mean r= -0.250 {+/-} 0.079), confirming non-haematological origin. ABA genome-wide analysis confirmed positive STN correlation (r=0.54-0.62; permutation p<0.001). MuSiC cell-type deconvolution against the Allen Brain Atlas HMBA-BG snRNA-seq reference identified oligodendrocytes (33.5 {+/-} 17.2%), frontal cortical neurons (9.1 {+/-} 7.0%), STR D1 MSNs (6.0 {+/-} 4.9%), and dopaminergic neurons (1.1{+/-} 2.7%) as the principal cell types, independently corroborating bulk transcriptomic findings at single-cell resolution. ConclusionThis study validates a low-input RNA extraction protocol for DBS microelectrodes, confirming brain-specific transcriptomic profiles consistent with STN-adjacent subcortical sampling. The 96% transcriptional overlap between cortical and subcortical regions, combined with absence of a guide tube in this post-mortem model, limits sub-regional specificity; clinical application with a guide tube would enrich the subcortical signal. These findings provide the methodological framework for in vivo molecular profiling of the human basal ganglia during DBS surgery in PD patients.

genetics↗

bioRxiv2026

Safe Redosable Low-Immunogenic In Vivo CAR-T Therapy for B Cell Malignancies and Solid Tumors

In vivo CAR-T cell therapy eliminates manufacturing complexities associated with ex vivo autologous approaches, but safety concerns have limited adoption. We developed viroVbot, a next-generation in vivo CAR-T platform, by combining computational immunogenicity prediction (CIMMEXTM) with envelope engineering. Screening 22,562 glycoprotein sequences, we identified 641 vesiculovirus homologs, from which we selected Piry virus glycoprotein (PIRYV) as the optimal candidate. PIRYV exhibited lower MHC-epitope density, reduced human seroprevalence, with decreased T cell activation compared to VSV-G. To enhance targeting specificity, we engineered receptor-binding-deficient PIRYV (ePIRYVRBD) displaying CD3/CD7 nanobodies for T cell-selective transduction. To maximize safety, we engineered CAR-TRAP producer cells to eliminate unwanted B cell transduction and incorporated machine learning-optimized T cell-specific promoters that restrict CAR activation exclusively to lymphocytes. Additional modifications suppressed hepatocyte expression and prevented phagocytic uptake. In humanized xenograft models, viroVbot3 generated potent BCMA/CD19 specific CAR-T responses against multiple myeloma and Claudin18.2-targeting gastric cancer, demonstrating sequential redosing with alternative envelopes. Critically, viroVbot3 exhibited minimal off-target organ biodistribution with CAR expression restricted to T lymphocytes. These findings establish viroVbot as a low-immunogenic platform for scalable in vivo CAR-T manufacturing with capability for sequential redosing across hematologic and solid tumors.

bioengineering↗

bioRxiv2026

Pathogen and host biomarkers to aid early diagnosis and prognosis of tuberculous meningitis

BackgroundTuberculous meningitis (TBM) is the most sinister form of extrapulmonary tuberculosis (EPTB), associated with high mortality due to delayed diagnosis and limited sensitivity of conventional and molecular tests. Current study evaluated the diagnostic utility of Lipoarabinomannan antigen (LAM) detection in CSF and urine and explored host inflammatory biomarkers for diagnosis and prognosis of TBM. MethodsThis prospective observational study enrolled 80 patients with presumptive TBM at a tertiary care centre. CSF samples were subjected to AFB microscopy, liquid culture(MGIT-960), GeneXpert MTB/RIF (GX), and LAM lateral flow assay. Urine LAM was performed at baseline. Serum and CSF levels of IL-1{beta}, IL-6, TNF-, IFN-{gamma}, IL-17A, and IP-10 were measured at baseline and after 1 month treatment. ResultsAmong 80 participants, 23 (28.7%) had definite TBM and 46 (57.5%) had probable TBM. CSF LAM sensitivity and specificity against microbiological reference standards was 43.5% and 80.7%, while urine LAM sensitivity (60.9%) and specificity 82.5% was higher. Against composite reference standards, both CSF and urine LAM showed reduced sensitivity but achieved 100% specificity. Serum IL-1{beta} showed the best diagnostic performance (AUC 0.943; sensitivity 88.9%, specificity 90.9%). Elevated serum and CSF IP-10 levels were associated with poor outcomes, whereas declining IL-6 and TNF- levels correlated with treatment response. ConclusionLAM detection in CSF and urine may serve as a highly specific, rapid rule-in test for TBM. Host inflammatory biomarkers, especially IL-1{beta} and IP-10, show additional diagnostic and prognostic value. Combining LAM testing with cytokine biomarkers may improve early diagnosis and efficient clinical management of TBM.

microbiology↗

bioRxiv2026

Reprogramming BCMA-Targeted CAR-T Cells through γ-Secretase Modulation Blocks Antigen Shedding and Extends CAR-T Longevity

B-cell maturation antigen (BCMA) shedding by {gamma}-secretase generates soluble BCMA (sBCMA), which diminishes membrane antigen density, and limits the durability of BCMA-directed immunotherapies in multiple myeloma (MM). Here, using AI-driven diffusion modeling, we identify peptide inhibitors that selectively block {gamma}-secretase-mediated BCMA cleavage, stabilizing membrane-bound BCMA (mBCMA) without compromising cellular viability. The lead peptide, P5, suppresses sBCMA and restores mBCMA in vitro and in xenograft models. To create sustained, cell-intrinsic inhibition, we engineered Shedding Deterrent Locked-in (SHEDLOCK) CAR-T cells that locally secrete {gamma}-secretase-modulatory peptides. SHEDLOCK-1 CAR-T cells secreting P5 exhibits enhanced cytotoxicity and persistence relative to conventional CAR-T cells. Building on this, SHEDLOCK-2 CAR-T cells were generated, which secrete a modified, naturally derived peptide (nxP) that directly engages the {gamma}-secretase catalytic site, concurrently preventing BCMA shedding, and surprisingly enhancing CAR-T cell longevity by preserving telomere integrity and metabolic fitness. In MM xenograft and patient-derived models, SHEDLOCK-2 CAR-T cells demonstrate durable antitumor activity with a favorable safety profile. Together, these findings establish SHEDLOCK as a next-generation CAR-T platform and provide a strong preclinical foundation for Phase I clinical evaluation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/700575v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@3cd38aorg.highwire.dtl.DTLVardef@164167borg.highwire.dtl.DTLVardef@1ffed21org.highwire.dtl.DTLVardef@1294d06_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Donor Sex and Platelet Storage Influence the Therapeutic Effects of Platelet-Derived Extracellular Vesicles on Endothelial Barrier Function

Platelet-derived extracellular vesicles (PEVs) play an active role in vascular protection and repair and are being explored as a viable alternative to platelet therapy. Because platelet function and stability are shaped by donor sex and storage conditions, these same factors are likely to influence the PEVs they release. Understanding these influences is key to developing PEVs into a safe and dependable therapeutic option. In this study, we investigated how donor sex and platelet storage affect the therapeutic properties of PEVs. To address this, PEVs were isolated from platelets of healthy male and female donors. Platelets were either processed immediately after blood collection to represent a resting state or stored overnight at room temperature on a rocker to mimic platelet storage conditions. PEVs isolated from these preparations displayed similar size, morphology, and cellular uptake across groups, but their biological effects diverged. Female PEVs, particularly from resting platelets, provided the strongest protection against thrombin-induced endothelial barrier disruption, stabilized junctional proteins, and reduced oxidative stress. Male PEVs showed weaker barrier protection compared to female-derived PEVs but more pronounced modulation of certain inflammatory mediators. In addition, PEVs derived from resting platelets (RP-PEVs) consistently showed stronger protective effects than those from stored platelets (SP-PEVs), regardless of donor sex. These results highlight that donor sex and platelet storage influence PEVs function and underscore the need to account for both when developing PEV-based therapies. Key PointThe endothelial-protective effects of platelet-derived extracellular vesicles are modulated by platelet storage conditions and donor sex.

molecular biology↗

bioRxiv2025

AI-Guided Design and AKT3 Degradation Synergize to Enhance Bispecific and Trispecific CAR-T Cell Persistence and Overcome Antigen Escape

The structural design of chimeric antigen receptors (CARs) is critical for achieving robust and durable anti-tumor responses, particularly when targeting multiple antigens to prevent tumor antigen escape. However, increasing CAR complexity can introduce structural vulnerabilities, leading to antigen-independent T cell activation, activation-induced cell death, and reduced CAR-T cell persistence. To overcome these challenges, we designed 10,824 CAR molecules across diverse formats and screened 1,452 constructs in-vitro to develop an artificial intelligence model, termed CAR-Mediated Self-Destruction (CARMSeD), which predicts CAR designs susceptible to self-activation and dysfunction. Guided by CARMSeD and structural CAR-CAR interaction modeling, we identified optimized CAR architectures incorporating ICOS and 4-1BB co-stimulatory domains. Humanized bispecific CARs targeting CD20/CD19 and CD22/CD19 demonstrated superior anti-tumor efficacy and persistence both in-vitro and in various xenograft mice models. To further extend CAR-T cell persistence, we engineered bispecific CARs integrated with an AKT3-targeted PROTAC strategy. Targeted degradation of AKT3 enhanced anti-tumor potency, promoted memory T cell formation, and enabled sustained responses even under tumor rechallenge and CD19 antigen-loss conditions. Mechanistically, these effects were mediated by metabolic reprogramming involving FOXO4; notably, FOXO4-deficient CAR-T cells exhibited impaired long-term persistence. Leveraging these mechanistic insights, we developed a trispecific CAR-T cell platform incorporating a bispecific T cell engager (BiTE) targeting CD22/CD3, combined with AKT3 PROTACs. These trispecific CAR-T cells achieved potent tumor eradication, even against malignancies lacking both CD19 and CD20 expression. Collectively, this study presents a comprehensive strategy combining structure-based design, AI-guided screening, and targeted protein degradation to engineer next-generation bi and trispecific CAR-T cells with enhanced persistence, broad antigen coverage, and superior therapeutic durability.

cancer biology↗

bioRxiv2025

Disruption of the mRNA m6A writer complex triggers autoimmunity in Arabidopsis

Distinguishing self from non-self is crucial to direct immune responses against pathogens. Unmodified RNAs stimulate human innate immunity, but RNA modifications suppress this response. mRNA m6A modification is essential for Arabidopsis thaliana viability. However, the molecular basis of the impact of mRNA m6A depletion is poorly understood. Here, we show that disruption of the Arabidopsis mRNA m6A writer complex triggers autoimmunity. Most gene expression changes in m6A writer complex vir-1 mutants grown at 17{degrees}C are explained by defence gene activation and are suppressed at 27{degrees}C, consistent with the frequent temperature sensitivity of Arabidopsis immunity. Accordingly, we found enhanced pathogen resistance and increased premature cell death in vir-1 mutants at 17{degrees}C but not 27{degrees}C. Global temperature-sensitive mRNA poly(A) tail length changes accompany these phenotypes. Our results demonstrate that autoimmunity is a major phenotype of mRNA m6A writer complex mutants, with important implications for interpreting the role of this modification. Furthermore, we open the broader question of whether unmodified RNA triggers immune signalling in plants.

plant biology↗

bioRxiv2023

Length-dependent RNA foci formation and RAN translation are associated with SCA12 disorder

Spinocerebellar ataxia type-12 (SCA-12) is a neurodegenerative disease caused by tandem CAG repeat expansion in the 5-UTR/non-coding region of PPP2R2B. Molecular pathology of SCA12 has not been studied in the context of CAG repeats and no appropriate models exist. We found in human SCA12-iPSC derived neuronal lineage that expanded CAG in PPP2R2B transcript forms nuclear RNA foci and were found to sequester variety of proteins. Further, the ectopic expression of transcript containing varying length of CAG repeats exhibits non-canonical Repeat Associated Non-AUG (RAN) translation in multiple frames in HEK293T cells, which was further validated in patient-derived neural stem cells using specific antibodies. mRNA sequencing of the SCA12 and control neurons have shown a network of crucial transcription factors affecting neural fate, in addition to alteration of various signaling pathways involved in neurodevelopment. Altogether, this study identifies the molecular signatures of spinocerebellar ataxia type-12 disorder using patient-derived neuronal cell lines.

neuroscience↗

bioRxiv2023

Computational and experimental hunt for expansion prone tandem CNG repeats in human genomes

IntroductionSpinocerebellar ataxias (SCA) are a group of clinically and genetically heterogeneous neurodegenerative disorders. Tandem repeat expansion is the pathogenic mutation in most of SCA cases. The pathophysiology of SCAs is still not completely defined due to the lack of genetic mutation in around 50% of cases worldwide. These uncharacterized cases must be genetically diagnosed for a better understanding and future treatment purposes. In this study, we tried a combination of computational and experimental approaches to find out novel CNG repeat loci that may be associated with SCAs. MethodologyWe investigate the human reference genome (hg-37) to find out all the possible CNG repeats present in more than 3 continuous uninterrupted units and annotated their functional locations. For experiment purposes, we targeted 52 loci from exonic and UTR regions and screened them in our 100 control samples through fragment analysis to know their polymorphic status. All the highly polymorphic loci were further investigated in 100 patient samples to know any large repeat expansion. ResultsThere are 15069 CNG repeat loci present in the human genome. After the examination of 52 loci in the control samples, 19 loci showed a highly polymorphic repeat pattern and were screened in patients. The 1000 genome different population data also suggested the polymorphic status in the available 15 loci data. From the GTEx database, 18 loci proposed the expression in the brain, suggesting any variation in these genes may cause neurological disorders. ConclusionWe tried a different kind of approach to find out tandem repeat expansion mutation in a cost-effective manner. Although we were unable to identify any disease-causing mutation in our patient cohort recently, various studies from different populations of the world have vouched for the genetic changes in these genes like GLS, RAI1, GIPC1, and CNKSR2 resulted in neurological disorders. Moreover, publications on the same identified repeats in GIPC1 for OPMD and GLS for ataxia with developmental delay, confirm the hypothesis to evaluate these repeat loci in different populations and other neurological disorders to identify novel targets.

genetics↗

bioRxiv2022

Calibration of crop phenology models: Going beyond recommendations

A major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments is important. Mechanistic crop models are a major tool for such predictions, but calibration of crop phenology models is difficult and there is no consensus on the best approach. Here we propose an original, detailed approach, a protocol, for calibration of such models. The protocol covers all the steps in the calibration work-flow, namely choice of default parameter values, choice of objective function, choice of parameters to estimate from the data, calculation of optimal parameter values and diagnostics. The major innovation is in the choice of which parameters to estimate from the data, which combines expert knowledge and data-based model selection. First, almost additive parameters are identified and estimated. This should make bias (average difference between observed and simulated values) nearly zero. These are "obligatory" parameters, that will definitely be estimated. Then candidate parameters are identified, which are parameters likely to explain the remaining discrepancies between simulated and observed values. A candidate is only added to the list of parameters to estimate if it leads to a reduction in BIC (Bayesian Information Criterion), which is a model selection criterion. A second original aspect of the protocol is the specification of documentation for each stage of the protocol. The protocol was applied by 19 modeling teams to three data sets for wheat phenology. All teams first calibrated their model using their "usual" calibration approach, so it was possible to compare usual and protocol calibration. Evaluation of prediction error was based on data from sites and years not represented in the training data. Compared to usual calibration, calibration following the new protocol reduced the variability between modeling teams by 22% and significantly reduced prediction error.

plant biology↗

bioRxiv2020

Multi-model evaluation of phenology prediction for wheat in Australia

Predicting wheat phenology is important for cultivar selection, for effective crop management and provides a baseline for evaluating the effects of global change. Evaluating how well crop phenology can be predicted is therefore of major interest. Twenty-eight wheat modeling groups participated in this evaluation. Our target population was wheat fields in the major wheat growing regions of Australia under current climatic conditions and with current local management practices. The environments used for calibration and for evaluation were both sampled from this same target population. The calibration and evaluation environments had neither sites nor years in common, so this is a rigorous evaluation of the ability of modeling groups to predict phenology for new sites and weather conditions. Mean absolute error (MAE) for the evaluation environments, averaged over predictions of three phenological stages and over modeling groups, was 9 days, with a range from 6 to 20 days. Predictions using the multi-modeling group mean and median had prediction errors nearly as small as the best modeling group. About two thirds of the modeling groups performed better than a simple but relevant benchmark, which predicts phenology by assuming a constant temperature sum for each development stage. The added complexity of crop models beyond just the effect of temperature was thus justified in most cases. There was substantial variability between modeling groups using the same model structure, which implies that model improvement could be achieved not only by improving model structure, but also by improving parameter values, and in particular by improving calibration techniques.

plant biology↗

bioRxiv2020

Haplotype-based heritability estimations reveal gestational duration as a maternal trait and fetal size measurements at birth as fetal traits in human pregnancy

AbstractGenotype-based approaches for the estimation of SNP-based narrow-sense heritability [Formula] have limited utility in pregnancy-related outcomes due to confounding by the shared alleles between mother and child. Here, we propose a haplotype-based approach to estimate the genetic variance attributable to three haplotypes - maternal transmitted [Formula], maternal non-transmitted [Formula] and paternal transmitted [Formula] in mother-child pairs. We show through extensive simulations that our haplotype-based approach outperforms the conventional and contemporary approaches for resolving the contribution of maternal and fetal effects, particularly when m1 and p1 have different effects in the offspring. We apply this approach to estimate the explicit and relative maternal-fetal genetic contribution to the phenotypic variance of gestational duration and gestational duration adjusted fetal size measurements at birth in 10,375 mother-child pairs. The results reveal that variance of gestational duration is mainly attributable to m1 and m2 ([Formula]= 17.3%, S. E. = 5.2%; [Formula] = 12.2%, S. E. = 5.2%; [Formula] = 0.0%, S. E. = 5.0%). In contrast, variance of fetal size measurements at birth are mainly attributable to m1 and p1 ([Formula] = 18.6 - 36.4%, [Formula] = 0.0 - 5.2% and [Formula] = 4.4 - 13.6%). Our results suggest that gestational duration and fetal size measurements are primarily genetically determined by the maternal and fetal genomes, respectively. In addition, a greater contribution of m1 as compared to m2 and p1 [Formula] to birth length and head circumference suggests a substantial influence of correlated maternal-fetal genetic effects on these traits. Our newly developed approach provides a direct and robust alternative for resolving explicit maternal and fetal genetic contributions to the phenotypic variance of pregnancy-related outcomes.

genetics↗

bioRxiv2020

A virus that has gone viral: Amino acid mutation in S protein of Indian isolate of Coronavirus COVID-19 might impact receptor binding and thus infectivity

Since 2002, beta coronaviruses (CoV) have caused three zoonotic outbreaks, SARS-CoV in 2002, MERS-CoV in 2012, and the recent outbreak of SARS-CoV-2 late in 2019 (also named as COVID-19 or novel coronavirus 2019 or nCoV2019. Spike(S) protein, one of the structural proteins of this virus plays key role in receptor (ACE2) binding and thus virus entry. Thus, this protein has attracted scientists for detailed study and therapeutic targeting. As the 2019 novel coronavirus takes its course throughout the world, more and more sequence analyses are been done and genome sequences getting deposited in various databases. From India two clinical isolates have been sequenced and the full genome deposited in GenBank. We have performed sequence analyses of the spike protein of the Indian isolates and compared with that of the Wuhan, China (where the outbreak was first reported). While all the sequences of Wuhan isolates are identical, we found point mutations in the Indian isolates. Out of the two isolates one was found to harbour a mutation in its Receptor binding domain (RBD) at position 407. At this site arginine (a positively charged amino acid) was replaced by isoleucine (a hydrophobic amino acid that is also a C-beta branched amino acid). This mutation has been seen to change the secondary structure of the protein at that region and this can potentially alter receptor ding of the virus. Although this finding needs further validation and more sequencing, the information might be useful in rational drug designing and vaccine engineering.

microbiology↗

bioRxiv2020

Detection of HER2 expression and its structural alterations in gastric cancer tissues infected with cagA+ H. pylori

BackgroundHelicobacter pylori (HP) cagA is the causing agent for development of gastric cancer (GC). H. pylori also involves to trigger the EGFR (epidermal growth factor receptor) expression in gastric cancer cells. However, the prognostic relation of cagA with HER2 status in GC was not well understood. ObjectiveThe main aim of this study was to investigate the link of HER2 expression with CagA+ H. pylori in GC tissues. Materials and MethodsThe study was performed on 85 GC tissues of GC patients. The specific primers of 16S rDNA and cagA for PCR amplification were used. For investigation of HER2 status in GC tissues, immunohistochemistry and PCR amplification were performed. In silico study was performed for the investigation of interactive potential of HER2 with CagA protein. ResultsPCR amplified the 54 (63.52 %) of 85 GC tissues for HP that showed 34 (62.96 %) cagA+ HP. Immunohistochemistry of tissues revealed 57 (67.05 %) diffuse and 28 (32.94 %) intestinal type cancer. Of 85 cases, 21 GC tissues scored (2 + or 3 +) for positive HER2 expression and score (0 or 1 +) of 64 (75.29 %) showed negative. Of 21 HER2 + GC tissue, 15 biopsies had cagA+ HP and 2 were negative. PCR amplified single amplicon in 17 (20 %) CagA+ tissues and 3 (5.55 %) in CagA - HP. The molecular interactions of CagA was also showed its efficiency for HER2 expression. ConclusionThe study concluded that CagA+ HP may induce HER2 overexpression in GC tissues.

cancer biology↗

bioRxiv2020

Virtaul screening of MAP-Tau protein inhibitors from Semecarpus anacardium Linn. leaf extract for cancer prevention

Semecarpus anacardium is a well known Indian medicinal plant with various medicinal properties like hypoglycemic, antioxidant, anticancer, anti-inflammatory, anti-geriatric, antimicrobial and hair growth promoter, etc. The molecular mechanism of metabolites from fruiting bodies of S. anacardium against cancer has been described but anticancerous properties in its leaves are still unknown. The leaves were extracted in petroleum ether, ethyl acetate and methanol and assayed for anticancer activity using MTT assay. The active extract was evaluated for mode of cell death induction using EtBr-AO double staining and analyzed for phytochemical constituents using GC-MS, followed by molecular docking studies for exploration of possibility for anticancer agents and Drugability. In this study, ethyl acetate extract of leaf was found potent cytotoxic in MCF-7 cells and also induced apoptosis. It has also found the SLE is safe for normal cells. The molecular docking studies were done to explore the probable mechanism of action of the extract which showed 9 compounds are targeting the microtubule-associated protein tau (MAPT). MAPT promotes assembling and prevents disassembling to arrest the cell cycle. The overexpression of MAPT induces chemoresistance to cancerous cells against conventional drugs like paclitaxel. We have identified 17 compounds from ethyl acetate extract of S. anacardium leaves and drawn its chemical structure by using chembiodraw software to transform into pdb format. Further, the compounds have been subjected for molecular docking study to investigate its interactive efficiency with MAPT protein. The compound 13 had higher interactive potential to MAPT with binding energy -31.75 kcal/mol and lowest binding energy (-15.44 kcal/mol) was observed in compound 6. The present study suggested that the compounds from leaves of S. anacardium could be alternative approach of conventional drug for cancer treatment with cost effective and less side effect.

bioinformatics↗

bioRxiv2019

How well do crop models predict phenology, with emphasis on the effect of calibration?

Predicting phenology is essential for adapting varieties to different environmental conditions and for crop management. Therefore, it is important to evaluate how well different crop modeling groups can predict phenology. Multiple evaluation studies have been previously published, but it is still difficult to generalize the findings from such studies since they often test some specific aspect of extrapolation to new conditions, or do not test on data that is truly independent of the data used for calibration. In this study, we analyzed the prediction of wheat phenology in Northern France under observed weather and current management, which is a problem of practical importance for wheat management. The results of 27 modeling groups are evaluated, where modeling group encompasses model structure, i.e. the model equations, the calibration method and the values of those parameters not affected by calibration. The data for calibration and evaluation are sampled from the same target population, thus extrapolation is limited. The calibration and evaluation data have neither year nor site in common, to guarantee rigorous evaluation of prediction for new weather and sites. The best modeling groups, and also the mean and median of the simulations, have a mean absolute error (MAE) of about 3 days, which is comparable to the measurement error. Almost all models do better than using average number of days or average sum of degree days to predict phenology. On the other hand, there are important differences between modeling groups, due to model structural differences and to differences between groups using the same model structure, which emphasizes that model structure alone does not completely determine prediction accuracy. In addition to providing information for our specific environments and varieties, these results are a useful contribution to a knowledge base of how well modeling groups can predict phenology, when provided with calibration data from the target population.

plant biology↗

bioRxiv2019

Targeted mutagenesis of the SUMO protease, Overly Tolerant to Salt1 in rice through CRISPR/Cas9-mediated genome editing reveals a major role of this SUMO protease in salt tolerance.

SUMO proteases are encoded by a large gene family in rice and are a potential source of specificity within the SUMO system that is responding to different environmental cues. We previously demonstrated a critical role of OsOTS class of SUMO proteases in salt and drought stress in rice by silencing several family members collectively via RNAi methods. However, to date it has not been possible to assign a role to specific family members due to limitations of RNAi mediated off target silencing across several members of the gene family. The clustered regularly interspaced short palindromic repeats (CRISPR)-associated endonuclease 9 (CRISPR/Cas9) system has emerged as a promising technology for specific gene editing in crop plants. Here, we demonstrate targeted mutagenesis of OsOTS1 in rice using the CRISPR/Cas9 gene editing system in the rice cultivar Kitaake. Guide RNA mediated mutations in OsOTS1 was highly efficient with almost 95% of T0 transgenics showing the desired effect with no off-target mutations. The OsOTS1 mutations observed in T0 generation were heritable in subsequent generations. OsOTS1 CRISPR lines show enhanced sensitivity to salt with reduced root and shoot biomass indicating that OsOTS1 has a major role in salt stress tolerance in rice. This unexpected finding indicates that precise and effective genome editing can be used to characterise specificity within the SUMO system in rice.

plant biology↗

bioRxiv2018

Lipid Lowering Oxopropanylindole Hydrazone Derivatives with Antioxidant and Antihyperglycemic Activity

A series of substituted oxopropanylindole hydrazone derivatives was synthesized and evaluated for anti-oxidant and anti-dyslipidemic activity. Among these 12 compounds the three compounds 6c, 7b and 7d showed good anti-oxidant activity and the compound 6c attenuataed LDL oxidation by 32%. The compounds 6c and 7d also showed good anti-dyslipidemic activity by reducing serum levels of total cholesterol (TC), phospholipids (PL) and triglycerides (TG). These two compounds were further evaluated for anti-adipogenic and anti-hyperglycemic activity, where 6c was found most active compound with 44% reduction in lipid accumulation and 20.5% and 24.3% reduction in blood glucose at 5h and 24h respectively, as compared to standard drug metformin.

biochemistry↗