Neutralizing antibody responses to SARS-CoV-2 Omicron variants: Post six months following two-dose & three-dose vaccination of ChAdOx1 nCoV-19 or BBV152.

BACKGROUND OBJECTIVES: The Omicron sub-lineages are known to have higher infectivity, immune escape and lower virulence. During December 2022 - January 2023 and March - April 2023, India witnessed increased SARS-CoV-2 infections, mostly due to newer Omicron sub-lineages. With this unprecedented rise in cases, we assessed the neutralization potential of individuals vaccinated with ChAdOx1 nCoV (Covishield) and BBV152 (Covaxin) against emerging Omicron sub-lineages. METHODS: Neutralizing antibody responses were measured in the sera collected from individuals six months post-two doses (n=88) of Covishield (n=44) or Covaxin (n=44) and post-three doses (n=102) of Covishield (n=46) or Covaxin (n=56) booster dose against prototype B.1 strain, lineages of Omicron; XBB.1, BQ.1, BA.5.2 and BF.7. RESULTS: The sera of individuals collected six months after the two-dose and the three-dose demonstrated neutralizing activity against all variants. The neutralizing antibody (NAbs) level was highest against the prototype B.1 strain, followed by BA5.2 (5-6 fold lower), BF.7 (11-12 fold lower), BQ.1 (12 fold lower) and XBB.1 (18-22 fold lower). INTERPRETATION CONCLUSIONS: Persistence of NAb responses was comparable in individuals with two- and three-dose groups post six months of vaccination. Among the Omicron sub-variants, XBB.1 showed marked neutralization escape, thus pointing towards an eventual immune escape, which may cause more infections. Further, the correlation of study data with complete clinical profile of the participants along with observations for cell-mediated immunity may provide a clear picture for the sustained protection due to three-dose vaccination as well as hybrid immunity against the newer variants.

PgxSAVy: A tool for comprehensive evaluation of variant peptide quality in proteogenomics - catching the (un)usual suspects.

Variant peptides resulting from single nucleotide polymorphisms (SNPs) can lead to aberrant protein functions and have translational potential for disease diagnosis and personalized therapy. Variant peptides detected by proteogenomics are fraught with high number of false positives, but there is no uniform and comprehensive approach to assess variant quality across analysis pipelines. Despite class-specific FDR along with ad-hoc filters, the problem is far from solved. These protocols are typically manual and tedious, and thus not uniform across labs. We demonstrate that variant peptide rescoring, integrated with intensity, variant event information and search result features, allows better discrimination of correct variant peptides. Implemented into PgxSAVy - a tool for quality control of variant peptides, this method can tackle the high rate of false positives. PgxSAVy provides a rigorous framework for quality control and annotations of variant peptides on the basis of (i) variant quality, (ii) isobaric masses, and (iii) disease annotation. PgxSAVy demonstrated high accuracy by identifying true variants with 98.43% accuracy on simulated data. Large-scale proteogenomic reanalysis of ∼2.8 million spectra (PXD004010 and PXD001468) resulted in 12,705 variant peptide spectrum matches (PSMs), of which PgxSAVy evaluated 3028 (23.8%), 1409 (11.1%) and 8268 (65.1%) as confident, semi-confident and doubtful respectively. PgxSAVy also annotates the variants based on their pathogenicity and provides support for assisted manual validation. The analysis of proteins carrying variants can provide fine granularity in discovering important pathways. PgxSAVy will advance personalized medicine by providing a comprehensive framework for quality control and prioritization of proteogenomics variants. PgxSAVy is freely available at https://pgxsavy.igib.res.in/ as a webserver and https://github.com/anuragraj/PgxSAVy as a stand-alone tool.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response.

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Reclamation of chromium-contaminated soil by native Cr(VI)-reducing and PHA-accumulating Bacillus aryabhattai CTSI-07.

Reclamation of chromium-contaminated soil by bacteria is a big confront concerning to soil health restoration, food safety, and environmental protection. Herein, the chromium-resistant Bacillus aryabhattai CTSI-07 (MG757377) showed resistance to 1000 and 300 ppm of Cr(VI) in nutrient rich Luria Bertani (LB) and nutrient-deficient sucrose low phosphate (SLP) medium, respectively. It reduced 96.7% of Cr(VI) from contaminated soil in the presence of 100 ppm of Mg within 96 h under optimized conditions. Furthermore, Cr(VI) reduction by the bacteria was validated by Fourier transform infrared spectroscopic (FTIR) and X-ray diffraction (XRD) analysis. Besides Cr(VI) reduction, the bacterial strain also showed plant growth promoting traits like N2 fixation and indole acetic acid (IAA) production. On the other hand, transmission electron microscopy (TEM) imaging confirmed polyhydroxyalkanoates' (PHAs) granule accumulation and 0.5 g/l of PHAs was extracted from bacterial cell using SLP medium. Infra-red (IR) spectra and proton nuclear magnetic resonance (1H NMR) chemical shift patterns established the PHAs as polyhydroxybutyrate (PHB). Melting (Tm) and thermal degradation (Td) temperature of the PHB were 169 °C and 275 °C, respectively, as evident from thermogravimetry differential thermal analysis (TG-DTA). Atomic force microscopic (AFM) imaging depicted that the PHB film surface was rough and regular. Furthermore, the multi-metal-resistant, plant growth-promoting, and PHB-producing bacteria could reduce 99.82% of Cr(VI) from contaminated soil within 120 days in pot culture. Thus, it can be used for long-term reclamation of chromium-contaminated soil to restore soil health, provide food safety, and environmental protection.

Detection, characterization and possible biofragmentation of synthetic microfibers released from domestic laundering wastewater as an emerging source of marine pollution.

Synthetic microfibers are universally recognized as an emerging pollutant in all ecosystems. The present investigation focuses on the evaluation and quantification of synthetic microfiber released from domestic laundering wastewater from different regions of Bhubaneswar city of Odisha state of India. The estimated number of microfibers collected from 500 ml of sample varied from 200 to 500 in numbers with an average amount of biomass in the range of 0.4-4 g. The surface morphology of the samples was assessed by Scanning Electron Microscopic analysis which revealed that the fibers were having a length of approximately 10-30 mm and diameter of 10-20 µm. Carbonyl (CO) stretching band at 1711 cm-1 and Aldehyde (CH) Weak bond at 2917.38 cm-1 absorption were recorded from Fourier transform infrared spectroscopic analysis. As microfibers released from synthetic apparels are major source of environmental microplastic pollution their precise detection could help in controlling this problem.

Transcriptomic Profiling of Human Limbus-Derived Stromal/Mesenchymal Stem Cells-Novel Mechanistic Insights into the Pathways Involved in Corneal Wound Healing.

Limbus-derived stromal/mesenchymal stem cells (LMSCs) are vital for corneal homeostasis and wound healing. However, despite multiple pre-clinical and clinical studies reporting the potency of LMSCs in avoiding inflammation and scarring during corneal wound healing, the molecular basis for the ability of LMSCs remains unknown. This study aimed to uncover the factors and pathways involved in LMSC-mediated corneal wound healing by employing RNA-Sequencing (RNA-Seq) in human LMSCs for the first time. We characterized the cultured LMSCs at the stages of initiation (LMSC-P0) and pure population (LMSC-P3) and subjected them to RNA-Seq to identify the differentially expressed genes (DEGs) in comparison to native limbus and cornea, and scleral tissues. Of the 28,000 genes detected, 7800 DEGs were subjected to pathway-specific enrichment Gene Ontology (GO) analysis. These DEGs were involved in Wnt, TGF-ß signaling pathways, and 16 other biological processes, including apoptosis, cell motility, tissue remodeling, and stem cell maintenance, etc. Two hundred fifty-four genes were related to wound healing pathways. COL5A1 (11.81 ± 0.48) and TIMP1 (20.44 ± 0.94) genes were exclusively up-regulated in LMSC-P3. Our findings provide new insights involved in LMSC-mediated corneal wound healing.

A Review on Heavy Metal Ion Adsorption on Synthetic Microfiber Surface in Aquatic Environments.

Synthetic microfibers (SMFs), tiny particles which gets fragmented from large fragments of large synthetic fibers having less than 10 µm in diameter, have gathered ubiquitously in each and every corner of the earth. After their release into the aquatic environment, they remain there without natural degradation. Furthermore, it can be anticipated that floating units are transported along the food chain leading to bioaccumulation. It has been estimated that approximately 10-20 Mt of large fabric products as garbage enter into aquatic system per annum. Recently, these synthetic fragments have been investigated as transporters of heavy metal ions (HMs) showing different types of interactions. Yet, the underlying mechanism of these types of interaction is not known, especially the factors stimulating this process and how badly they affect biotic communities. Through this article, a detailed survey was carried out on the sources of microfibers and HMs into the aquatic environment, adsorption of different types of HMs on the SMF surface, mechanics favors these HM-MF interactions, particularly highlighting the significant roles of interaction on microbial biofilm formation. Their collaborative effects which possess harmful effects on aquatic as well as terrestrial organisms was also discussed. Lastly, the future investigations should focus on rigorous research in this field. This article to the best of our knowledge briefly describes the current research developments and emphasizes the vital function of the microorganisms on MFs-HMs interactions with the encouragement for rigorous research in this field to reveal accurate mechanisms and decrease the hazards related with MF presence.

Feasibility of establishing a multi-center research database using the electronic health record: The PURSUIT network.

BACKGROUND: Although multi-center research is needed in pediatric urology, collaboration is impeded by differences in physician documentation and research resources. Electronic health record (EHR) tools offer a promising avenue to overcome these barriers. OBJECTIVE: To assess the accuracy, completeness, and utilization of structured data elements across multiple practices. STUDY DESIGN: A standardized template was developed and implemented at five academic pediatric urology practices to document clinic visits for patients with congenital hydronephrosis and/or vesicoureteral reflux. Data from standardized elements in the template and from pre-existing EHR fields were extracted into a secure database. A 20% random sample of infants with data from structured elements from 1/1/2020 and 4/30/2021 were identified and compared to manual chart review at sites with >100 charts; all other sites reviewed at least 20 charts. Manual chart review was standardized across sites and included: clinic and operative notes, orders linked to the clinic encounter, radiology results, and active medications. Accuracy of data extraction was evaluated by computing the kappa statistic and percentage agreement. For sites that had adopted the templates prior to 6/1/2019 (early adopters), a list of eligible patients with an initial clinic visit from 1/1/2020-7/27/2020 was generated using standardized reporting techniques and confirmed by manual chart review. Physician utilization of the template was then calculated by comparing patients with data obtained from the note template to the generated list of eligible patients. RESULTS: 230 patient records met study criteria. Agreement between manual chart review and data extracted from the EHR was high (>85%). Race, ethnicity and insurance data were misclassified in about 10-15% of cases; this was due to site-specific differences in how these fields were coded. Renal ultrasound was misclassified 12% of the time; this was primarily due to outside images documented in radiology results but not included in the clinical note. All other data elements had >90% agreement (Figure). Template utilization for early adopters was >75% (75.5-87.5%). DISCUSSION: This is the first study in urology to demonstrate that use of structured data elements can support multi-center research. Limitations include: inclusion of only academic sites with the Epic EHR and lack of data on utilization and sustainability at sites without a prior history of structured template use. CONCLUSIONS: Multi-center research collaboration using EHR-based data collection tools is feasible with generally high accuracy compared to manual chart review. Additionally, sites with a long history of template adoption have high levels of provider utilization.

A High Throughput Lipidomics Method Using Scheduled Multiple Reaction Monitoring.

Lipid compositions of cells, tissues, and bio-fluids are complex, with varying concentrations and structural diversity making their identification challenging. Newer methods for comprehensive analysis of lipids are thus necessary. Herein, we propose a targeted-mass spectrometry based lipidomics screening method using a combination of variable retention time window and relative dwell time weightage. Using this method, we identified more than 1000 lipid species within 24-min. The limit of detection varied from the femtomolar to the nanomolar range. About 883 lipid species were detected with a coefficient of variance <30%. We used this method to identify plasma lipids altered due to vitamin B12 deficiency and found a total of 18 lipid species to be altered. Some of the lipid species with ω-6 fatty acid chains were found to be significantly increased while ω-3 decreased in vitamin B12 deficient samples. This method enables rapid screening of a large number of lipid species in a single experiment and would substantially advance our understanding of the role of lipids in biological processes.

False discovery rate: the Achilles' heel of proteogenomics.

Proteogenomics refers to the integrated analysis of the genome and proteome that leverages mass-spectrometry (MS)-based proteomics data to improve genome annotations, understand gene expression control through proteoforms and find sequence variants to develop novel insights for disease classification and therapeutic strategies. However, proteogenomic studies often suffer from reduced sensitivity and specificity due to inflated database size. To control the error rates, proteogenomics depends on the target-decoy search strategy, the de-facto method for false discovery rate (FDR) estimation in proteomics. The proteogenomic databases constructed from three- or six-frame nucleotide database translation not only increase the search space and compute-time but also violate the equivalence of target and decoy databases. These searches result in poorer separation between target and decoy scores, leading to stringent FDR thresholds. Understanding these factors and applying modified strategies such as two-pass database search or peptide-class-specific FDR can result in a better interpretation of MS data without introducing additional statistical biases. Based on these considerations, a user can interpret the proteogenomics results appropriately and control false positives and negatives in a more informed manner. In this review, first, we briefly discuss the proteogenomic workflows and limitations in database construction, followed by various considerations that can influence potential novel discoveries in a proteogenomic study. We conclude with suggestions to counter these challenges for better proteogenomic data interpretation.

High failure rate of ChAdOx1-nCoV19 immunization against asymptomatic infection in healthcare workers during a Delta variant surge.

Immunization is expected to confer protection against infection and severe disease for vaccines while reducing risks to unimmunized populations by inhibiting transmission. Here, based on serial serological studies of an observational cohort of healthcare workers, we show that during a Severe Acute Respiratory Syndrome -Coronavirus 2 Delta-variant outbreak in Delhi, 25.3% (95% Confidence Interval 16.9-35.2) of previously uninfected, ChAdOx1-nCoV19 double vaccinated, healthcare workers were infected within less than two months, based on serology. Induction of anti-spike response was similar between groups with breakthrough infection (541 U/ml, Inter Quartile Range 374) and without (342 U/ml, Inter Quartile Range 497), as was the induction of neutralization activity to wildtype. This was not vaccine failure since vaccine effectiveness estimate based on infection rates in an unvaccinated cohort were about 70% and most infections were asymptomatic. We find that while ChAdOx1-nCoV19 vaccination remains effective in preventing severe infections, it is unlikely to be completely able to block transmission and provide herd immunity.

Whole Exome Sequencing in Healthy Individuals of Extreme Constitution Types Reveals Differential Disease Risk: A Novel Approach towards Predictive Medicine.

Precision medicine aims to move from traditional reactive medicine to a system where risk groups can be identified before the disease occurs. However, phenotypic heterogeneity amongst the diseased and healthy poses a major challenge for identification markers for risk stratification and early actionable interventions. In Ayurveda, individuals are phenotypically stratified into seven constitution types based on multisystem phenotypes termed "Prakriti". It enables the prediction of health and disease trajectories and the selection of health interventions. We hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous Prakriti types might enable the identification of functional variations associated with the constitution types. Exomes of 144 healthy Prakriti stratified individuals and controls from two genetically homogeneous cohorts (north and western India) revealed differential risk for diseases/traits like metabolic disorders, liver diseases, and body and hematological measurements amongst healthy individuals. These SNPs differ significantly from the Indo-European background control as well. Amongst these we highlight novel SNPs rs304447 (IFIT5) and rs941590 (SERPINA10) that could explain differential trajectories for immune response, bleeding or thrombosis. Our method demonstrates the requirement of a relatively smaller sample size for a well powered study. This study highlights the potential of integrating a unique phenotyping approach for the identification of predictive markers and the at-risk population amongst the healthy.

Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays.

SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficient training data prevented effective deep learning (DL) solutions for the diagnosis of COVID-19 based on X-Ray data. Here, addressing the lacunae in existing literature and algorithms with the paucity of initial training data; we describe CovBaseAI, an explainable tool using an ensemble of three DL models and an expert decision system (EDS) for COVID-Pneumonia diagnosis, trained entirely on pre-COVID-19 datasets. The performance and explainability of CovBaseAI was primarily validated on two independent datasets. Firstly, 1401 randomly selected CxR from an Indian quarantine center to assess effectiveness in excluding radiological COVID-Pneumonia requiring higher care. Second, curated dataset; 434 RT-PCR positive cases and 471 non-COVID/Normal historical scans, to assess performance in advanced medical settings. CovBaseAI had an accuracy of 87% with a negative predictive value of 98% in the quarantine-center data. However, sensitivity was 0.66-0.90 taking RT-PCR/radiologist opinion as ground truth. This work provides new insights on the usage of EDS with DL methods and the ability of algorithms to confidently predict COVID-Pneumonia while reinforcing the established learning; that benchmarking based on RT-PCR may not serve as reliable ground truth in radiological diagnosis. Such tools can pave the path for multi-modal high throughput detection of COVID-Pneumonia in screening and referral.

Genetic epidemiology of autoinflammatory disease variants in Indian population from 1029 whole genomes.

BACKGROUND: Autoinflammatory disorders are the group of inherited inflammatory disorders caused due to the genetic defect in the genes that regulates innate immune systems. These have been clinically characterized based on the duration and occurrence of unprovoked fever, skin rash, and patient's ancestry. There are several autoinflammatory disorders that are found to be prevalent in a specific population and whose disease genetic epidemiology within the population has been well understood. However, India has a limited number of genetic studies reported for autoinflammatory disorders till date. The whole genome sequencing and analysis of 1029 Indian individuals performed under the IndiGen project persuaded us to perform the genetic epidemiology of the autoinflammatory disorders in India. RESULTS: We have systematically annotated the genetic variants of 56 genes implicated in autoinflammatory disorder. These genetic variants were reclassified into five categories (i.e., pathogenic, likely pathogenic, benign, likely benign, and variant of uncertain significance (VUS)) according to the American College of Medical Genetics and Association of Molecular pathology (ACMG-AMP) guidelines. Our analysis revealed 20 pathogenic and likely pathogenic variants with significant differences in the allele frequency compared with the global population. We also found six causal founder variants in the IndiGen dataset belonging to different ancestry. We have performed haplotype prediction analysis for founder mutations haplotype that reveals the admixture of the South Asian population with other populations. The cumulative carrier frequency of the autoinflammatory disorder in India was found to be 3.5% which is much higher than reported. CONCLUSION: With such frequency in the Indian population, there is a great need for awareness among clinicians as well as the general public regarding the autoinflammatory disorder. To the best of our knowledge, this is the first and most comprehensive population scale genetic epidemiological study being reported from India.

Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India.

Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of >50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi.

Sputum Protein Biomarkers in Airway Diseases: A Pilot Study.

Background: Chronic mucous hypersecretion (CMH or chronic bronchitis) per se or when associated with chronic inflammatory airway diseases such as asthma or chronic obstructive pulmonary disease (COPD) has several adverse clinical consequences. The sputum fluid phase has several candidate proteins including mucins which have the potential of being therapeutic targets, but has not yet been explored in-depth. This study aimed at exploring the profile of sputum proteins in various airway diseases. Methods: Sputum from thirty-one patients with various airway diseases was collected and the fluid phase analyzed by LC-MS/MS and subsequently by sequential window acquisition of all theoretical fragments ion spectra (SWATH) (n = 15) for protein quantitation. Hierarchical clustering and functional grouping were performed. Results: A total of 185 proteins were quantitated by SWATH of which 21 proteins were identified which could distinguish between the clinical phenotypes by hierarchical clustering. Functional protein clustering revealed 4 groups: those that are inflammation related, oxidative stress related, mucin related and a cytoskeletal and calcium related group. The levels of eight proteins (Azurocidin1, Neutrophil defensin 3, Lactotransferrin, Calmodulin 3, Coronin1A, Mucin 5B, Mucin 5AC and BPI fold containing family B1) were significantly altered (relative to mean) in exacerbator prone subjects compared to nonexacerbators. Another simple but useful metric which emerged from this study was total protein concentration in sputum which was significantly higher in frequent exacerbators. Conclusion: Sputum proteins can detect the various airway disease clinical phenotypes. Total protein concentration and eight other proteins are biomarkers for frequent exacerbators. The clinical and therapeutic implications of the functional groups of proteins need further evaluation.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Comparative Genomic Analysis of Mycobacteriaceae Reveals Horizontal Gene Transfer-Mediated Evolution of the CRISPR-Cas System in the Mycobacterium tuberculosis Complex.

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) genes are conserved genetic elements in many prokaryotes, including Mycobacterium tuberculosis, the causative agent of tuberculosis. Although knowledge of CRISPR locus variability has been utilized in M. tuberculosis strain genotyping, its evolutionary path in Mycobacteriaceae is not well understood. In this study, we have performed a comparative analysis of 141 mycobacterial genomes and identified the exclusive presence of the CRISPR-Cas type III-A system in M. tuberculosis complex (MTBC). Our global phylogenetic analysis of CRISPR repeats and Cas10 proteins offers evidence of horizontal gene transfer (HGT) of the CRISPR-Cas module in the last common ancestor of MTBC and Mycobacterium canettii from a Streptococcus-like environmental bacterium. Additionally, our results show that the variation of CRISPR-Cas organization in M. tuberculosis lineages, especially in the Beijing sublineage of lineage 2, is due to the transposition of insertion sequence IS6110 The direct repeat (DR) region of the CRISPR-Cas locus acts as a hot spot for IS6110 insertion. We show in M. tuberculosis H37Rv that the repeat at the 5' end of CRISPR1 of the forward strand is an atypical repeat made up partly of IS-terminal inverted repeat and partly CRISPR DR. By tracing an undetectable spacer sequence in the DR region, the two CRISPR loci could theoretically be joined to reconstruct the ancestral single CRISPR-Cas locus organization, as seen in M. canettii This study retracing the evolutionary events of HGT and IS6110-driven genomic deletions helps us to better understand the strain-specific variations in M. tuberculosis lineages.IMPORTANCE Comparative genomic analysis of prokaryotes has led to a better understanding of the biology of several pathogenic microorganisms. One such clinically important pathogen is M. tuberculosis, the leading cause of bacterial infection worldwide. Recent evidence on the functionality of the CRISPR-Cas system in M. tuberculosis has brought back focus on these conserved genetic elements, present in many prokaryotes. Our study advances understanding of mycobacterial CRISPR-Cas origin and its diversity among the different species. We provide phylogenetic evidence of acquisition of CRISPR-Cas type III-A in the last common ancestor shared between MTBC and M. canettii, by HGT-mediated events. The most likely source of HGT was an environmental Firmicutes bacterium. Genomic mapping of the CRISPR loci showed the IS6110 transposition-driven variations in M. tuberculosis strains. Thus, this study offers insights into events related to the evolution of CRISPR-Cas in M. tuberculosis lineages.

IndiGenomes: a comprehensive resource of genetic variants from over 1000 Indian genomes.

With the advent of next-generation sequencing, large-scale initiatives for mining whole genomes and exomes have been employed to better understand global or population-level genetic architecture. India encompasses more than 17% of the world population with extensive genetic diversity, but is under-represented in the global sequencing datasets. This gave us the impetus to perform and analyze the whole genome sequencing of 1029 healthy Indian individuals under the pilot phase of the 'IndiGen' program. We generated a compendium of 55,898,122 single allelic genetic variants from geographically distinct Indian genomes and calculated the allele frequency, allele count, allele number, along with the number of heterozygous or homozygous individuals. In the present study, these variants were systematically annotated using publicly available population databases and can be accessed through a browsable online database named as 'IndiGenomes' http://clingen.igib.res.in/indigen/. The IndiGenomes database will help clinicians and researchers in exploring the genetic component underlying medical conditions. Till date, this is the most comprehensive genetic variant resource for the Indian population and is made freely available for academic utility. The resource has also been accessed extensively by the worldwide community since it's launch.