In silico approach for the identification of tRNA-derived small non-coding RNAs in SARS-CoV infection.

tsRNAs (tRNA-derived small non-coding RNAs), including tRNA halves (tiRNAs) and tRNA fragments (tRFs), have been implicated in some viral infections, such as respiratory viral infections. However, their involvement in SARS-CoV infection is completely unknown. A comprehensive analysis was performed to determine tsRNA populations in a mouse model of SARS-CoV-infected samples containing the wild-type and attenuated viruses. Data from the Gene Expression Omnibus (GEO) dataset at NCBI (accession ID GSE90624 ) was used for this study. A count matrix was generated for the tRNAs. Differentially expressed tRNAs, followed by tsRNAs derived from each significant tRNAs at different conditions and time points between the two groups WT(SARS-CoV-MA15-WT) vs Mock and ΔE (SARS-CoV-MA15-ΔE) vs Mock were identified. Notably, significantly differentially expressed tRNAs at 2dpi but not at 4dpi. The tsRNAs originating from differentially expressed tRNAs across all the samples belonging to each condition (WT, ΔE, and Mock) were identified. Intriguingly, tRFs (tRNA-derived RNA fragments) exhibited higher levels compared to tiRNAs (tRNA-derived stress-induced RNAs) across all samples associated with WT SARS-CoV strain compared to ΔE and mock-infected samples. This discrepancy suggests a non-random formation of tsRNAs, hinting at a possible involvement of tsRNAs in SARS-CoV viral infection.

PsychArray-Based Genome Wide Association Study of Suicidal Deaths in India.

Background: Suicide is a preventable but escalating global health crisis. Genome-wide association studies (GWAS) studies to date have been limited, and some are underpowered. In this study, we aimed to perform the PsychArray-based GWAS study to identify single nucleotide variations associated with suicide in the Indian population. Methods: We recruited unrelated subjects who died by suicide as cases (N = 313) and the non-suicidal deaths as controls (N = 294). The 607 samples were genotyped, including cases and controls using the Illumina Infinium PsychArray-24 BeadChip v1.3 Results: In our study, four single nucleotide polymorphisms (SNPs) crossed the threshold of significance level <1 × 10−5. One of them is intronic at Chromosome2:rs1901851 and three are intergenic at Chromosome12:rs3847911, Chromosome8:rs2941489, Chromosome8:rs1464092. At a significance level of 5 × 10−5, we found a few more SNPs, with the majority of them being intergenic variants. The associated genes were associated with various important functions ranging from cell signaling, GTP binding, GPCR binding, and transcription factor binding. Conclusions: The SNPs identified in our study were not reported earlier. To our best knowledge, this study is one of the first GWAS for suicide in the Indian population. The results indicate few novel SNPs that may be associated with suicide and require further investigation. Their clinical significance is to be studied in the future.

A two-step process for in silico screening to assess the performance of qRTPCR kits against variant strains of SARS-CoV-2.

BACKGROUND: Since inception of the COVID-19 pandemic, early detection and isolation of positive cases is one of the key strategies to restrict disease transmission. Real time reverse transcription polymerase chain reaction (qRTPCR) has been the mainstay of diagnosis. Most of the qRTPCR kits were designed against the target genes of original strain of SARS-CoV-2. However, with the emergence of variant strains of SARS-CoV-2, sensitivity of the qRTPCR assays has reportedly reduced. In view of this, it is critical to continuously monitor the performance of the qRTPCR kits in the backdrop of variant strains of SARS-CoV-2. Real world monitoring of assay performance is challenging. Therefore, we developed a two-step in-silico screening process for evaluating the performance of various qRTPCR kits used in India. RESULTS: We analysed 73 qRT-PCR kits marketed in India, against the two SARS-CoV-2 VoCs. Sequences of both Delta (B.1.617.2) and Omicron (B.1.1.529) VoCs submitted to GISAID within a specific timeframe were downloaded, clustered to identify unique sequences and aligned with primer and probe sequences. Results were analysed following a two-step screening process. Out of 73 kits analysed, seven were unsatisfactory for detection of both Delta and Omicron VoCs, 10 were unsatisfactory for Delta VoC whereas 2 were unsatisfactory for only Omicron VoC. CONCLUSION: Overall, we have developed a useful screening process for evaluating the performance of qRTPCR assays against Delta and Omicron VoCs of SARS-CoV-2 which can be used for detecting SARS-CoV-2 VoCs that may emerge in future and can also be redeployed for other evolving pathogens of public health importance.

Development of the first DNA database and identification portal for identification of Unidentified bodies in India - UMID.

Identifying missing persons and unidentified dead bodies is a well-documented global problem in recent years. To curb this issue, countries such as the USA, UK, and Australia already have well-established DNA databases. Considering the alarming number of unidentified/unclaimed dead bodies reported in India every year, it is evident that the current practices are not sufficient to establish their identities. Forensic medicine professionals are ethically, morally, and dutybound to collect information about missing and unidentified persons and work with the government agencies to determine their identity. Concerning the social and public interest, we have developed the first-ever identification portal and DNA database of unidentified dead bodies autopsied at the Department of Forensic Medicine and Toxicology, AIIMS, New Delhi, India. After the investigation officer's informed consent, biological samples from unidentified dead bodies and a detailed phenotypic description, anthropological data and other visual characteristics of the deceased are recorded at the time of autopsy. This information is uploaded on our database which is available for public access, and the genotypic information generated through STR analysis is only available for internal usage.Claimants (biological relatives) may browse through the URL (https://umid-aiims.icmr.org.in/), and if they wish to claim an unidentified dead body, they may approach as per the given guidelines. The DNA profiles generated include a total of 16 STRs (15 autosomal tetranucleotide microsatellite STRs and 1 Sex Chromosome Specific STR). The claimant's STR profile is run through the questioned database to look for a potential match. If positive, the investigating officer of that particular case is informed for further necessary action. Until December 2020, our database consisted the information of 255 individuals and two unidentified cadavers were identified. This project's success can also lead to a pioneering National DNA database of unidentified and missing persons in India.

Biochemical findings in sudden unexpected death in epilepsy: Hospital based case-control study.

PURPOSE: A review study on the biochemistry of epilepsy showed that in epileptic patients, serum glucose and cholesterol concentrations are low, sodium is unaffected, potassium increases, glucose is high and mild hypocalcemia. We have conducted a biochemical study on sudden unexpected death in epilepsy (SUDEP) cases in an attempt to establish the characteristic biochemical values to diagnose these deaths. METHODS: This was a hospital based case-control study done at All India Institute of Medical Sciences, New Delhi for one year. Twenty SUDEP cases and 20 age- and sex-matched controls were included in the study. Femoral blood, cerebrospinal fluid, vitreous humor, and pericardial fluid were biochemically analyzed for sodium, potassium, calcium, glucose, N-acetyl- cysteine activated creatine kinase (CK-NAC) and isoenzyme CK-MB. RESULT: Serum sodium, CK-MB and CK-NAC level was found significantly increased and potassium level was found decreased in SUDEP cases in comparison to non-epileptic deaths. Likewise, in CSF, sodium and CK-NAC was found increased and potassium level was found decreased in SUDEP cases. In vitreous humor, sodium and CK-MB level was found increased and potassium level was found decreased in SUDEP cases in comparison to non-epileptic deaths. In pericardial fluid, sodium, CK-NAC and CK-MB level was found increased and potassium level was found decreased in SUDEP cases in comparison to non-epileptic deaths. CONCLUSION: It concludes that high sodium level and low potassium level could be associated with SUDEP. However, this is a small size study, a larger study is needed to verify the findings. Furthermore, it is difficult to conclude whether these findings are exclusive to SUDEP.

Solution-Processed Organic Field-Effect Transistors with High Performance and Stability on Paper Substrates.

High-performance operationally stable organic field-effect transistors were successfully fabricated on a PowerCoat HD 230 paper substrate with a TIPS-pentacene:polystyrene blend as the active layer and poly(4-vinylphenol)/HfO2 as the hybrid gate dielectric. The fabricated devices exhibited excellent p-channel characteristics with a maximum and av field effect mobility of 0.44 and 0.22(±0.11) cm2 V-1 s-1, respectively, av threshold voltage of 0.021(±0.63) V, and current on-off ratio of ∼105 while operating at -10 V. These devices exhibited remarkable stability under effects of gate bias stress and large number of repeated transfer scans with negligible performance spread. In addition, these devices displayed very stable electrical characteristics after long exposure periods to humidity and an excellent shelf life of more than 6 months in ambient environment. Thermal stress at high temperatures however deteriorates the device characteristics because of the generation and propagation of cracks in the active semiconductor crystals. Furthermore, novel paper-based phototransistors have been demonstrated with these devices.

GCAC: galaxy workflow system for predictive model building for virtual screening.

BACKGROUND: Traditional drug discovery approaches are time-consuming, tedious and expensive. Identifying a potential drug-like molecule using high throughput screening (HTS) with high confidence is always a challenging task in drug discovery and cheminformatics. A small percentage of molecules that pass the clinical trial phases receives FDA approval. This whole process takes 10-12 years and millions of dollar of investment. The inconsistency in HTS is also a challenge for reproducible results. Reproducible research in computational research is highly desirable as a measure to evaluate scientific claims and published findings. This paper describes the development and availability of a knowledge based predictive model building system using the R Statistical Computing Environment and its ensured reproducibility using Galaxy workflow system. RESULTS: We describe a web-enabled data mining analysis pipeline which employs reproducible research approaches to confront the issue of availability of tools in high throughput virtual screening. The pipeline, named as "Galaxy for Compound Activity Classification (GCAC)" includes descriptor calculation, feature selection, model building, and screening to extract potent candidates, by leveraging the combined capabilities of R statistical packages and literate programming tools contained within a workflow system environment with automated configuration. CONCLUSION: GCAC can serve as a standard for screening drug candidates using predictive model building under galaxy environment, allowing for easy installation and reproducibility. A demo site of the tool is available at http://ccbb.jnu.ac.in/gcac.

Solvent sensitivity of protein aggregation in Cu, Zn superoxide dismutase: a molecular dynamics simulation study.

Misfolding and aggregation of Cu, Zn Superoxide Dismutase (SOD1) is often found in amyotrophic lateral sclerosis (ALS) patients. The central apo SOD1 barrel was involved in protein maturation and pathological aggregation in ALS. In this work, we employed atomistic molecular dynamics (MD) simulations to study the conformational dynamics of SOD1barrel monomer in different concentrations of trifluoroethanol (TFE). We find concentration dependence unusual structural and dynamical features, characterized by the local unfolding of SOD1barrel. This partially unfolded structure is characterized by the exposure of hydrophobic core, is highly dynamic in nature, and is the precursor of aggregation seen in SOD1barrel. Our computational studies supports the hypothesis of the formation of aggregation 'building blocks' by means of local unfolding of apo monomer as the mechanism of SOD1 fibrillar aggregation. The non-monotonic TFE concentration dependence of protein conformational changes was explored through simulation studies. Our results suggest that altered protein conformation and dynamics within its structure may underlie the aggregation of SOD1 in ALS.

Directional Solvent Vapor Annealing for Crystal Alignment in Solution-Processed Organic Semiconductors.

A unified approach of directional solvent vapor annealing for crystal alignment in solution-processed organic semiconductors is proposed. Highly crystalline molecular self-assembly of the drop-cast technique is further enhanced by postprocessing scheme of the solvent vapor annealing with additional benefit of alignment of the crystalline domains. In this technique, a mixture of carrier gas and solvent vapors are made to flow in a certain direction and in the close proximity of the surface of the substrates carrying the solution. Flow of the carrier gas imparts directionality to the semiconducting crystalline ribbons, whereas the influx of the solvent vapors improves the crystalline order in the semiconducting film. The flow rate of the carrier gas and the position of the substrate in the interaction chamber are the primary regulating factors, which have the ability to provide a semiconducting layer with a well-aligned and interconnected assembly of long ribbons. These favorable film properties further materialize in the form of electrical performance of the corresponding field-effect transistors. The versatility of this technique makes it a viable alternative for the solution processing of organic semiconductors.

QSAR based predictive modeling for anti-malarial molecules.

Malaria is a predominant infectious disease, with a global footprint, but especially severe in developing countries in the African subcontinent. In recent years, drug-resistant malaria has become an alarming factor, and hence the requirement of new and improved drugs is more crucial than ever before. One of the promising locations for antimalarial drug target is the apicoplast, as this organelle does not occur in humans. The apicoplast is associated with many unique and essential pathways in many Apicomplexan pathogens, including Plasmodium. The use of machine learning methods is now commonly available through open source programs. In the present work, we describe a standard protocol to develop molecular descriptor based predictive models (QSAR models), which can be further utilized for the screening of large chemical libraries. This protocol is used to build models using training data sourced from apicoplast specific bioassays. Multiple model building methods are used including Generalized Linear Models (GLM), Random Forest (RF), C5.0 implementation of a decision tree, Support Vector Machines (SVM), K-Nearest Neighbour and Naive Bayes. Methods to evaluate the accuracy of the model building method are included in the protocol. For the given dataset, the C5.0, SVM and RF perform better than other methods, with comparable accuracy over the test data.

Low prevalence of CCR5-Δ32, CCR2-64I and SDF1-3'A alleles in the Baiga and Gond tribes of Central India.

Human immunodeficiency virus-1 (HIV-1) which causes acquired immune deficiency syndrome (AIDS), by infecting CD4(+) immune cells and hence weakening the host defense mechanism till death, is one of the major factor responsible for human demises worldwide. Both innate (monocytes and macrophages) and adaptive (T cells) immune cells expresses chemokines receptors (2 and 5) and stromal cell derived factor-1 (SDF-1) which play crucial role in HIV-1 virus entry and progression. Allele variants of genes CCR5 (CCR5-Δ32), CCR2 (CCR2-64I) and SDF1 (SDFA-3'A; the ligand of CXCR4) are known to slow down the HIV-1 progression in infected individual. In the present study, the frequency of CCR5-Δ32, CCR2-64I and SDF1-3'A alleles in primitive tribe (Baiga) and a non-primitive tribe (Gond) of central India were investigated. A total 200 seronegative samples for HIV from healthy individuals of tribes were analyzed and observed allele frequencies of CCR5-Δ32, CCR2-64I and SDF1-3'A were (0, 0.035, 0.080) and (0, 0.110, 0.100) in Baiga and Gond respectively. Minor allele frequency of these alleles of Gond and Baiga tribes were compared with different populations of the world for relative hazard (RH), which indicate the risk of progression after infection of HIV1. The RH values were calculated based on genotypic frequency, showed the high RH value (RH1-AIDS1993-0.98, RH2-AIDS1987-0.98 and death/RH3-0.97) in Baiga tribe, indicates the low level of resistance against HIV-1 progression after infection.

The role of TLR9 polymorphism in susceptibility to pulmonary tuberculosis.

Mycobacterium tuberculosis (MTB) is the causative agent of pulmonary tuberculosis (PTB), a major health problem that leads to 1.5 million deaths annually. Host genetic factors play a significant role in disease resistance/susceptibility by altering immunity against MTB. Toll-like receptor (TLR) sensors such as TLR2, TLR4, TLR8, and TLR9 are known to play a pivotal role in PTB via modulating sensor expression and/or effector responses. Single-nucleotide polymorphism (SNP) rs187084 (T-1486C) of the TLR9 promoter is associated with various autoimmune disorders and cancers. A recent bioinformatic analysis predicted that the T-1486C SNP is involved in PTB, although its potential role is unclear. To investigate the role of T-1486C in PTB, we stimulated PBMCs with the H37Rv whole cell lysate. We found that the presence of the "C" allele increases the transcriptional activity of the TLR9, which in turn induces high levels of Interferon gamma-induced protein 10 (IP-10), a biomarker for PTB. However, the expression of protective cytokines such as IFNγ and TNFα was observed significantly less with "C" allele in comparison to "T" allele. We further selected three different tribe populations showing differential susceptibility to PTB and performed genotypic analyses for the TLR9 promoter. We found a significantly lower minor allele frequency (MAF) of T-1486C in the Baiga tribe, wherein fewer PTB cases were reported, than that in the Gond and Korku tribes. Collectively, these data suggest that the minor "C" allele at rs187084 locus may be associated with susceptibility to PTB, which may explain the relatively lower PTB rates observed in Baiga tribe members.