We report the genome sequence of a novel species of nontuberculous mycobacterium (NTM) belonging to the Mycobacterium terrae complex (MTC). The strain SVM_VP21 was isolated from the mouthwash sample of a healthy human adult residing in Delhi, India. The strain exhibited smooth, cream-coloured colonies on Lowenstein Jensen (LJ) medium after 2 weeks of incubation and could not be identified by Hain’s Genotype Mycobacterium CM/AS line probe assay. Whole genome sequencing (WGS) of SVM_VP21 was performed using Illumina NovaSeq 6000 platform for final identification. The whole genome sequence was assembled using Shovill. Gene annotation was performed by Rapid Annotation using Subsystem Technology (RAST) and Prokaryotic Genome Annotation Pipeline (PGAP). The genome of 4,882,418 bp exhibited 67.3

Overexpression of efflux pumps has been associated with drug resistance in Mycobacterium tuberculosis. However, their specific role in delamanid resistance remains unclear. This study aimed to identify efflux pump genes influenced by delamanid exposure through transcriptomic analysis. Cultures of M. tuberculosis H37Rv were exposed to delamanid at a sub-inhibitory concentration of ½ MIC for 24 h and transcriptomic sequencing was performed on exposed and unexposed cultures. Differentially expressed genes (DEGs) were annotated using the UniProt database. Transcriptomic analysis revealed that 23 efflux pump genes were significantly upregulated under delamanid stress, with 17/23 (73.9%) belonging to the ABC family, 4/23 (17.39%) to the RND family and 2/23 (8.69%) to the MFS superfamily. Quantitative real-time PCR (qRT-PCR) was conducted to validate the transcriptomic results for efflux pump genes following exposure of M. tuberculosis H37Rv to delamanid at ½ and ¼ MIC. qRT-PCR confirmed that 20/23 (86.95%) genes were significantly upregulated at ½ MIC, with 14/20 (70%) of these belonging to the ABC family. In contrast, only 3/23 (13%) efflux pump genes demonstrated upregulation at ¼ MIC. This study identified a set of efflux pump genes significantly upregulated in response to sub-inhibitory concentrations of delamanid and suggested that ½ MIC is a more suitable concentration than ¼ MIC for evaluating the expression of efflux pump genes in response to delamanid in M. tuberculosis.

The increase in drug-resistant tuberculosis (DR-TB) is a significant barrier to achieving the targets set by the WHO’s End TB Strategy. The introduction of various first- and second-line medications has improved the treatment of TB which was once deemed deadly. However, the growing public health threat of DR-TB necessitates the development of novel drugs and dosing regimens for effective treatment. Linezolid, an oxazolidinone, has recently been approved for the treatment of mycobacterial infections and its inclusion in the National TB programmes has expanded. Despite its clinical efficacy, resistance to linezolid has been reported in TB patients. Emerging evidence of increasing population-level resistance to linezolid is concerning, particularly due to the drug’s vital role in the treatment of DR-TB and its importance in injection-free regimens. The current review summarizes the available data on linezolid resistance and describes its antimicrobial properties.

Inhibition of Reactive Oxygen Species (ROS) is one of the strategies that Mycobacterium tuberculosis (Mtb) employs as its defence mechanism. In this study, the role of PPE15 (Rv1039c), a late-stage protein, has been investigated in modulating the cellular ROS. We discovered PPE15 to be a secretory protein that downregulates ROS generation in THP1 macrophages. Our in-silico analysis revealed the presence of a eukaryote-like SH3 (SH3e) domain in PPE15. The predicted SH3e-domain of PPE15 was found to interact with cytosolic components of NADPH Oxidase (NOX), p67phox and p47phox through molecular docking. In-vitro experiments using THP1 macrophages showed a diminished NADP/NADPH ratio, indicating reduced NOX activity. We also observed increased levels of p67phox and p47phox in the cytoplasmic fraction of PPE15 treated macrophages as compared to the plasma membrane fraction. To understand the role of the SH3e-domain in ROS modulation, this domain was deleted from the full-length PPE15 (PPE15-/-SH3). We observed an increase in cellular ROS and NADP/NADPH ratio in response to PPE15-/-SH3 protein. The interaction of PPE15-/-SH3 with p67phox or p47phox was also reduced in the cytoplasm, indicating migration of NOX subunits to the plasma membrane. Additionally, M. smegmatis expressing PPE15 was observed to be resistant to oxidative stress with significant intracellular survival in THP1 macrophages as compared to M. smegmatis expressing PPE15-/-SH3. These observations suggest that the SH3e-domain of PPE15 interferes with ROS generation by sequestering NOX components that inhibit NOX assembly at the cell membrane. Therefore, PPE15 acts like a molecular mimic of SH3-domain carrying eukaryotic proteins that can be employed by Mtb at late stages of infection for its survival. These findings give us new insights about the pathogen evading strategy of Mtb which may help in improving the therapeutics for TB treatment.

New or mild heart failure (HF) is mainly caused by left ventricular dysfunction. We hypothesised that gene expression differ between the left (LV) and right ventricle (RV) and secondly by type of LV dysfunction. We compared gene expression through myocardial biopsies from LV and RV of patients undergoing elective coronary bypass surgery (CABG). Patients were categorised based on LV ejection fraction (EF), diastolic function and NT-proBNP into pEF (preserved; LVEF ≥ 45%), rEF (reduced; LVEF < 45%) or normal LV function. Principal component analysis of gene expression displayed two clusters corresponding to LV and RV. Up-regulated genes in LV included natriuretic peptides NPPA and NPPB, transcription factors/coactivators STAT4 and VGLL2, ion channel related HCN2 and LRRC38 associated with cardiac muscle contraction, cytoskeleton, and cellular component movement. Patients with pEF phenotype versus normal differed in gene expression predominantly in LV, supporting that diastolic dysfunction and structural changes reflect early LV disease in pEF. DKK2 was overexpressed in LV of HFpEF phenotype, potentially leading to lower expression levels of β-catenin, α-SMA (smooth muscle actin), and enhanced apoptosis, and could be a possible factor in the development of HFpEF. CXCL14 was down-regulated in both pEF and rEF, and may play a role to promote development of HF.

T cells are an important component of adaptive immunity and T-cell-derived lymphomas are very complex due to many functional sub-types and functional elasticity of T-cells. As with other tumors, tissues specific factors are crucial in the development of T-cell lymphomas. In addition to neoplastic cells, T- cell lymphomas consist of a tumor micro-environment composed of normal cells and stroma. Numerous studies established the qualitative and quantitative differences between the tumor microenvironment and normal cell surroundings. Interaction between the various component of the tumor microenvironment is crucial since tumor cells can change the microenvironment and vice versa. In normal T-cell development, T-cells must respond to various stimulants deferentially and during these courses of adaptation. T-cells undergo various metabolic alterations. From the stage of quiescence to attention of fully active form T-cells undergoes various stage in terms of metabolic activity. Predominantly quiescent T-cells have ATP-generating metabolism while during the proliferative stage, their metabolism tilted towards the growth-promoting pathways. In addition to this, a functionally different subset of T-cells requires to activate the different metabolic pathways, and consequently, this regulation of the metabolic pathway control activation and function of T-cells. So, it is obvious that dynamic, and well-regulated metabolic pathways are important for the normal functioning of T-cells and their interaction with the microenvironment. There are various cell signaling mechanisms of metabolism are involved in this regulation and more and more studies have suggested the involvement of additional signaling in the development of the overall metabolic phenotype of T cells. These important signaling mediators include cytokines and hormones. The impact and role of these mediators especially the cytokines on the interplay between T-cell metabolism and the interaction of T-cells with their micro-environments in the context of T-cells lymphomas are discussed in this review article.

Mammalian cell entry (mce) operons play a vital role in cell invasion and survival of M. tuberculosis. Of the mce genes, the function of Rv0590A is still unknown. The present study was performed to investigate the function and immunogenic properties of the protein Rv0590A. Human leukemia monocytic cell line (THP-1) derived macrophages were infected with M. tuberculosis H37Rv at 3, 6, and 24 h of infection. The maximum colony forming units (CFU) were observed at 6 h (p < 0.005), followed by 3 h after infection. M. tuberculosis H37Rv and clinical isolates representative of Delhi/CAS, EAI, Beijing, Haarlem and Euro-American-superlineage were included in the study for expression analysis of mce1A, mce2A, mce3A, mce4A, and Rv0590A genes. Maximum upregulation of all mce genes was observed at 3 h of infection. All the five clinical isolates and H37Rv upregulated Rv0590A at various time points. Macrophage infection with M. tuberculosis H37Rv-overexpressing Rv0590A gene showed higher intracellular CFU as compared to that of wild-type H37Rv. Further, purified Rv0590A protein stimulated the production of TNFα, IFNγ, and IL-10 in macrophages. Thus, Rv0590A was found to be involved in cell invasion and showed good immunological response.

Background: Understanding the protein's subcellular localization and secretory nature can greatly improve the target identification for diagnostic assays and drug discovery, although their identification in laboratory experiments is a time-consuming and labor-intensive process. In order to identify proteins that could be targeted for therapeutic intervention or the development of diagnostic assays, we used a variety of computational tools to predict the subcellular localization or secretory nature of mycobacterial proline-glutamate/proline-proline-glutamate (PE/PPE) proteins. Methods: PSORTb version 3.0.3, TBpred, and Gpos-mPLoc analyses were performed on 30 selected PE/PPE protein sequences, while, SignalP 6.0, SignalP 5.0, Phobius, PSORTb version 3.0.3 and TBpred were used for signal sequence predictions. Results: Gpos-mPLoc and TBpred had the highest concordance for extracellular prediction, while PSORTb and TBpred had the highest concordance for prediction of membrane localization. The tools for predicting the secretory nature of proteins had little agreement. Conclusion: Multiple computational tools must be considered to provide an indication of the subcellular localization of PE/PPE proteins. Laboratory experiments should be used to confirm the findings of the tools.

Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a global public health problem.The real-time reverse transcription-polymerase chain reaction (RT-PCR) is the gold standard test for the detection of SARS-CoV-2.However, the assay requires hours to get the final results.Therefore, antigen-based rapid assays are being used extensively to reduce the time.We have evaluated the performance of the antigen-based rapid test for the detection of SARS-CoV-2 virus in comparison with RT-PCR.Materials and methods: Nasopharyngeal and throat swabs were collected from 366 suspected patients of COVID-19 visiting our institute and subjected to qualitative RT-PCR and antigen-based rapid assays to detect the presence of SARS-CoV-2 virus.The sensitivity and specificity of the antigen-based assay were calculated in comparison with RT-PCR.Results: Compared with RT-PCR, sensitivity and specificity of the antigen-based rapid assay were observed to be 70.5% and 98.6%, respectively, in comparison with RT-PCR.However, the sensitivity of antigen-based rapid assay varied significantly with decreasing viral load.The sensitivity of the rapid antigen assay was equivalent to RT-PCR (23/23, 100%) at a higher viral load (Ct value 15-20).In contrast, the antigen assay could only detect 3/21 (14.28%) samples with Ct value >30. Conclusion:The antigen-based assay could assist in the rapid screening of a large population.However, the rapid antigen assay might not detect early stages of infection represented by low viral load.Therefore, the antigen-based assay could not replace RT-PCR testing.The study reiterates that all antigen-based negative tests should be confirmed by RT-PCR.

Nonalcoholic fatty liver disease (NAFLD) is the most rapidly growing contributor to chronic liver disease worldwide with high disease burden and suffers from limitations in diagnosis. Inspired by recent advances in machine learning digital diagnostics, we explored the efficacy of training a neural network to classify high risk NAFLD vs. non-NAFLD patients in the UK Biobank dataset based on proton density fat fraction (PDFF). We compared the performance of several ResNet-derived architectures in the context of whole abdomen MRI, segmented liver and abdomen excluding liver (sans-liver). Non-local ResNet trained on whole abdomen MRI images yielded the highest precision (0.88 for NAFLD) and F1 (0.89 for NAFLD). Furthermore, our work on a second, larger cohort explored multi-task learning and the relationship among PDFF, visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT). Interestingly, multi-task learning experiments found a decline in performance for PDFF when combined with VAT and ASAT. We address this deterioration using Multi-gate Mixture-of-Experts (MMoE) approaches. Our work opens the possibility for using a non-invasive deep learning-based diagnostic for NAFLD, and directly enables clinical and genomic research using a larger cohort of potential NAFLD patients in the UK Biobank study.

In an attempt to uncover genotypic indicators for isoniazid (INH) resistance in M. tuberculosis, in addition to the canonical mutations in genes associated with INH resistance, including katG, inhA and fabG promoter; we analyzed, two INH monoresistant isolates, ASTS24/13 (INHR1) and SHR1/14 (INHR2). Targeted Sanger sequencing detected a canonical mutation at katG315 only in INHR2. Infection of THP-1 cells and exposure to antituberculosis drugs led to two-fold increase in the minimum inhibitory concentration of INH in INHR2. Whole genome sequences revealed that INHR1 and INHR2 belonged to Delhi Central Asian Strain and East African Indian lineages, respectively. The sequences were compared with INH susceptible isolates with the same lineage as the INH monoresistant strains. INHR1 had a novel unique mutation STOP420Trp in the efflux pump gene Rv0849, while INHR2 had a novel mutation Arg579Ser in efflux pump gene mmpL5. Comparison of lipid associated genes showed novel mutations in INHR1 in fadE16, fadD3 and fbpD; while INHR2 had mutations in fadE1, Rv0145, Rv1425, fadD9 and mmaA3. Both isolates also demonstrated novel mutations in cell wall associated genes. Our study highlights the importance of searching for alternate mechanisms of INH resistance that may contribute to the development of more comprehensive diagnostic tools.

Environmental and genetic factors cause defects in pancreatic islets driving type 2 diabetes (T2D) together with the progression of multi-tissue insulin resistance. Mass spectrometry proteomics on samples from five key metabolic tissues of a cross-sectional cohort of 43 multi-organ donors provides deep coverage of their proteomes. Enrichment analysis of Gene Ontology terms provides a tissue-specific map of altered biological processes across healthy, prediabetes (PD), and T2D subjects. We find widespread alterations in several relevant biological pathways, including increase in hemostasis in pancreatic islets of PD, increase in the complement cascade in liver and pancreatic islets of PD, and elevation in cholesterol biosynthesis in liver of T2D. Our findings point to inflammatory, immune, and vascular alterations in pancreatic islets in PD that are hypotheses to be tested for potential contributions to hormonal perturbations such as impaired insulin and increased glucagon production. This multi-tissue proteomic map suggests tissue-specific metabolic dysregulations in T2D.

Precise and timely detection of tuberculosis (TB) is crucial to reduce transmission. This study aims to assess the accuracy of Xpert MTB/RIF Ultra on stool samples and systematically review the performance of Xpert MTB/RIF Ultra with different sample types by meta-analysis. Stool samples of smear-negative pulmonary TB (PTB), cervical lymph node TB, and abdominal TB patients were tested on the Xpert MTB/RIF Ultra system. Meta-analysis was performed on a set of 44 studies. Data were grouped by sample type, and the pooled sensitivity and specificity of Xpert MTB/RIF Ultra were calculated. The sensitivity of Xpert MTB/RIF Ultra with stool samples was 100% for smear-negative PTB, 27.27% for cervical lymph node TB, and 50% for abdominal TB patients, with 100% specificity for all included TB groups. The summary estimate for all PTB samples showed 84.2% sensitivity and 94.5% specificity, and EPTB samples showed 88.6% sensitivity and 96.4% specificity. Among all sample types included in our meta-analysis, urine showed the best performance for EPTB diagnosis. This pilot study supports the use of stool as an alternative non-invasive sample on Xpert MTB/RIF Ultra for rapid testing, suitable for both PTB and EPTB diagnosis.

Background: Rapidly growing mycobacteria (RGM) are increasingly being recognized as potential pathogens. RGM, particularly Mycobacterium abscessus, Mycobacterium fortuitum, and Mycobacterium chelonae, have been observed in both pulmonary and extrapulmonary infections including cutaneous, soft-tissue, and wound infections. However, there are limited reports of these potential pathogens from skin and soft-tissue infections. Moreover, the drug susceptibility profile of RGM is largely unknown in several regions of the world. Methods: We analyzed reports on RGM isolated from skin and soft-tissue infections globally for details of RGM species and drug susceptibility profile. We also analyzed the drug susceptibility profile of four RGM isolates, obtained from skin and soft-tissue infections in our laboratory, by broth microdilution method. Results: In the reports reviewed, the most common RGM isolated from skin and soft-tissue infections were M. abscessus (184/475, 38.7%), M. fortuitum (150/475, 31.5%), M. chelonae (72/475, 15%), and M. chelonae–M. abscessus complex (46/475, 9.6%). However, drug susceptibility was tested only in 26/39 (66.6%) reports. In our own laboratory, we obtained three isolates of M. abscessus and one isolate of M. fortuitum from one case of breast abscess and three cases of postsurgical wound infections. Maximum susceptibility of M. abscessus was observed to clarithromycin, amikacin, and linezolid. The M. fortuitum isolate was susceptible to clarithromycin, amikacin, clofazimine, and linezolid. Conclusion: Paucity of information available on RGM isolated from skin and soft-tissue infections highlights the need to be aware of the pathogenic potential and the drug susceptibility profile of these organisms.

There is an avalanche of biomedical data generation and a parallel expansion in computational capabilities to analyze and make sense of these data. Starting with genome sequencing and widely employed deep sequencing technologies, these trends have now taken hold in all omics disciplines and increasingly call for multi-omics integration as well as data interpretation by artificial intelligence technologies. Here, we focus on mass spectrometry (MS)-based proteomics and describe how machine learning and, in particular, deep learning now predicts experimental peptide measurements from amino acid sequences alone. This will dramatically improve the quality and reliability of analytical workflows because experimental results should agree with predictions in a multi-dimensional data landscape. Machine learning has also become central to biomarker discovery from proteomics data, which now starts to outperform existing best-in-class assays. Finally, we discuss model transparency and explainability and data privacy that are required to deploy MS-based biomarkers in clinical settings.

Long-chain polyunsaturated fatty acids (LC-PUFAs) influence human health in several areas, including cardiovascular disease, diabetes, fatty liver disease, and cancer. ELOVL2 encodes one of the key enzymes in the in vivo synthesis of LC-PUFAs from their precursors. Variants near ELOVL2 have repeatedly been associated with levels of LC-PUFA-derived metabolites in genome-wide association studies (GWAS), but the mechanisms behind these observations remain poorly defined. In this study, we found that rs953413, located in the first intron of ELOVL2, lies within a functional FOXA and HNF4α cooperative binding site. The G allele of rs953413 increases binding of FOXA1/FOXA2 and HNF4α to an evolutionarily conserved enhancer element, conferring allele-specific upregulation of the rs953413-associated gene ELOVL2. The expression of ELOVL2 was significantly downregulated by both FOXA1 and HNF4α knockdown and CRISPR/Cas9-mediated direct mutation to the enhancer element. Our results suggest that rs953413 regulates LC-PUFAs metabolism by altering ELOVL2 expression through FOXA1/FOXA2 and HNF4α cooperation.