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Abstract Methanogens are a diverse group of Archaea that obligately couple energy conservation to the production of methane. Some methanogens encode alternate pathways for energy conservation, like anaerobic respiration, but the biochemical details of this process are unknown. We show that a multiheme c-type cytochrome called MmcA from Methanosarcina acetivorans is important for intracellular electron transport during methanogenesis and can also reduce extracellular electron acceptors like soluble Fe3+ and anthraquinone-2,6-disulfonate. Consistent with these observations, MmcA displays reversible redox features ranging from −100 to −450 mV versus SHE. Additionally, mutants lacking mmcA have significantly slower Fe3+ reduction rates. The mmcA locus is prevalent in members of the Order Methanosarcinales and is a part of a distinct clade of multiheme cytochromes that are closely related to octaheme tetrathionate reductases. Taken together, MmcA might act as an electron conduit that can potentially support a variety of energy conservation strategies that extend beyond methanogenesis.

Objective: To develop machine learning (ML) models, using pre and intraoperative surgical parameters, for predicting trabeculectomy outcomes in the eyes of patients with juvenile-onset primary open-angle glaucoma (JOAG) undergoing primary surgery. Subjects: The study included 207 JOAG patients from a single center who met the following criteria: diagnosed between 10 and 40 years of age, with an IOP of >22 mmHg in the eyes on two or more occasions, open angle on gonioscopy in both eyes, with glaucomatous optic neuropathy, and requiring a trabeculectomy for IOP control. Only the patients with a minimum 5-year follow-up after surgery were included in the study. Methods: A successful surgical outcome was defined as IOP ≤18 mmHg (criterion A) or 50% reduction in IOP from baseline (criterion B) 5 years after trabeculectomy. Feature selection techniques were used to select the most important contributory parameters, and tenfold cross-validation was used to evaluate model performance. The ML models were evaluated, compared, and prioritized based on their accuracy, sensitivity, specificity, Matthew correlation coefficient (MCC) index, and mean area under the receiver operating characteristic curve (AUROC). The prioritized models were further optimized by tuning the hyperparameters, and feature contributions were evaluated. In addition, an unbiased relationship analysis among the parameters was performed for clinical utility. Results: Age at diagnosis, preoperative baseline IOP, duration of preoperative medical treatment, Tenon’s thickness, scleral fistulation technique, and intraoperative mitomycin C (MMC) use, were identified as the main contributing parameters for developing efficient models. The three models developed for a consensus-based outcome to predict trabeculectomy success showed an accuracy of >86%, sensitivity of >90%, and specificity of >74%, using tenfold cross-validation. The use of intraoperative MMC and a punch for scleral fistulation compared to the traditional excision with scissors were significantly associated with long-term success of trabeculectomy. Conclusion: Optimizing surgical parameters by using these ML models might reduce surgical failures associated with trabeculectomy and provide more realistic expectations regarding surgical outcomes in young patients.

Background: Prostate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients’ well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer. Methods: The study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs. Results: Six molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024). Conclusions: Our study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

Purpose: To predict the presence of angle dysgenesis on anterior-segment optical coherence tomography (ADoA) by using deep learning (DL) and to correlate ADoA with mutations in known glaucoma genes. Participants: In total, 800 high-definition anterior-segment optical coherence tomography (AS-OCT) images were included, of which 340 images were used to build the machine learning (ML) model. Images used to build the ML model included 170 scans of primary congenital glaucoma (16 patients), juvenile-onset open-angle glaucoma (62 patients), and adult-onset primary open-angle glaucoma eyes (37 patients); the rest were controls (n = 85). The genetic validation dataset consisted of another 393 images of patients with known mutations that were compared with 320 images of healthy controls. Methods: ADoA was defined as the absence of Schlemm's canal, the presence of hyperreflectivity over the region of the trabecular meshwork, or a hyperreflective membrane. DL was used to classify a given AS-OCT image as either having angle dysgenesis or not. ADoA was then specifically looked for on AS-OCT images of patients with mutations in the known genes for glaucoma. Results: The final prediction, which was a consensus-based outcome from the three optimized DL models, had an accuracy of >95%, a specificity of >97%, and a sensitivity of >96% in detecting ADoA in the internal test dataset. Among the patients with known gene mutations, (MYOC, CYP1B1, FOXC1, and LTBP2) ADoA was observed among all the patients in the majority of the images, compared to only 5% of the healthy controls. Conclusion: ADoA can be objectively identified using models built with DL.

The tau-tubulin kinase 1 (TTBK1) protein is a casein kinase 1 superfamily member located at chromosome 6p21.1. It is expressed explicitly in the brain, particularly in the cytoplasm of cortical and hippocampal neurons. TTBK1 has been implicated in the phosphorylation and aggregation of tau in Alzheimer’s disease (AD). Considering its significance in AD, TTBK1 has emerged as a promising target for AD treatment. In the present study, we identified novel TTBK1 inhibitors using various computational techniques. We performed a virtual screening-based docking study followed by E-pharmacophore modeling, cavity-based pharmacophore, and ligand design techniques and found ZINC000095101333, LD7, LD55, and LD75 to be potential novel TTBK1 lead inhibitors. The docking results were complemented by Molecular Mechanics/Generalized Born Surface Area (MMGBSA) calculations. The molecular dynamics (MD) simulation studies at a 500 ns scale were carried out to monitor the behavior of the protein toward the identified ligands. Pharmacological and ADME/T studies were carried out to check the drug-likeness of the compounds. In summary, we identified a new series of compounds that could effectively bind the TTBK1 receptor. The newly designed compounds are promising candidates for developing therapeutics targeting TTBK1 for AD.

Abstract Hemoglobin degradation is crucial for the growth and survival of Plasmodium falciparum in human erythrocytes. Although the process of Hb degradation has been studied in detail, the mechanisms of Hb uptake remain ambiguous to date. Here, we characterized Heme Detoxification Protein (PfHDP); a protein localized in the parasitophorus vacuole, parasite food vacuole, and infected erythrocyte cytosol for its role in Hb uptake. Immunoprecipitation of PfHDP‐GFP fusion protein from a transgenic line using GFP trap beads showed the association of PfHDP with Hb as well as with the members of PTEX translocon complex. Association of PfHDP with Hb or Pfexp‐2, a component of translocon complex was confirmed by protein–protein interaction and immunolocalization tools. Based on these associations, we studied the role of PfHDP in Hb uptake using the PfHDP‐HA‐GlmS transgenic parasites line. PfHDP knockdown significantly reduced the Hb uptake in these transgenic parasites in comparison to the wild‐type parasites. Morphological analysis of PfHDP‐HA‐GlmS transgenic parasites in the presence of GlcN showed food vacuole abnormalities and parasite stress, thereby causing a growth defect in the development of these parasites. Transient knockdown of a member of translocon complex, PfHSP101 in HSP101‐DDDHA parasites also showed a decreased uptake of Hb inside the parasite. Together, these results advocate an interaction between PfHDP and the translocon complex at the parasitophorus vacuole membrane and also suggest a role for PfHDP in the uptake of Hb and parasite development. The study thus reveals new insights into the function of PfHDP, making it an extremely important target for developing new antimalarials.

This study aimed to valorize microcrystalline cellulose (MCC) using protonated zeolite catalysts such as (H-ZSM-5) and Cr/H-ZSM-5 (5%) in ionic liquid. The catalytic effect in synergy with 1-butyl-3-methylimidazolium Chloride ([BMIM] Cl) ionic liquid was studied in detail. The total reducing sugar (TRS) was determined using the 3, 5-dinitrisalcylic acid (DNS) array method. The catalysts were characterized using techniques such as Fourier transform infrared (FT-IR), X-ray diffraction analysis (XRD), temperature-programmed desorption of ammonia (NH3-TPD), and BET-surface area analyzer. H-ZSM-5 effectively depolymerized cellulose with a maximum yield of 70% total reducing sugar (34% glucose, 8% fructose, and 4.5% 5-HMF). Cr/H-ZSM-5 catalyst dehydrated fructose to 5-HMF with a yield of 53%. The use of ionic liquid significantly reduced the activation energy of formation and decomposition. The activation energy determined in cellulose hydrolysis was 85.83 KJ mol−1 for a reaction time of 180 min while the decomposition energy was found to be 42.5 kJ mol−1.

Tumor heterogeneity and the unclear metastasis mechanisms are the leading cause for the unavailability of effective targeted therapy for Triple-negative breast cancer (TNBC), a breast cancer (BrCa) subtype characterized by high mortality and high frequency of distant metastasis cases. The identification of prognostic biomarker can improve prognosis and personalized treatment regimes. Herein, we collected gene expression datasets representing TNBC and Non-TNBC BrCa. From the complete dataset, a subset reflecting solely known cancer driver genes was also constructed. Recursive Feature Elimination (RFE) was employed to identify top 20, 25, 30, 35, 40, 45, and 50 gene signatures that differentiate TNBC from the other BrCa subtypes. Five machine learning algorithms were employed on these selected features and on the basis of model performance evaluation, it was found that for the complete and driver dataset, XGBoost performs the best for a subset of 25 and 20 genes, respectively. Out of these 45 genes from the two datasets, 34 genes were found to be differentially regulated. The Kaplan-Meier (KM) analysis for Distant Metastasis Free Survival (DMFS) of these 34 differentially regulated genes revealed four genes, out of which two are novel that could be potential prognostic genes (POU2AF1 and S100B). Finally, interactome and pathway enrichment analyses were carried out to investigate the functional role of the identified potential prognostic genes in TNBC. These genes are associated with MAPK, PI3-AkT, Wnt, TGF-β, and other signal transduction pathways, pivotal in metastasis cascade. These gene signatures can provide novel molecular-level insights into metastasis.

Structural Variants (SVs) and Copy Number Variations (CNVs) at the genomic level are responsible for forming chimeric genes at the transcriptome level, posing significant implications in cancers. In this study, we performed an integrated analysis of the SVs, CNVs and fusion genes in breast cancer sequencing datasets to predict driver fusion genes using paired RNA and WGS (Whole Genome Sequencing) datasets. The combined effect of genomic fusions, chromosomal rearrangements and CNV can help analyze the highly perturbed cancer genome and how they work together, leading to cancer progression. Our analysis yielded chimeric fusion genes supported by multiple events, such as trans-splicing at the transcriptome level, formed due to CNV variation and SVs at the genomic level. We discovered novel gene fusions, such as RARA-PKIA in the SK-BR3 cell line and PLA2R1-RBMS1 in the HCC1395BL cell line. The analysis pipeline of the study can be utilized to explore the other less investigated cancer genomes, which may also help develop diagnostics and better cancer therapeutics, especially for personalized treatments.

Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE) are the two highly prevalent debilitating and sometimes life-threatening systemic inflammatory autoimmune diseases. The etiology and pathogenesis of RA and SLE are interconnected in several ways, with limited knowledge about the underlying molecular mechanisms. With the motivation to better understand shared biological mechanisms and determine novel therapeutic targets, we explored common molecular disease signatures by performing a meta-analysis of publicly available microarray gene expression datasets of RA and SLE. We performed an integrated, multi-cohort analysis of 1088 transcriptomic profiles from 14 independent studies to identify common gene signatures. We identified sixty-two genes common among RA and SLE, out of which fifty-nine genes (21 upregulated and 38 downregulated) had similar expression profiles in the diseases. However, antagonistic expression profiles were observed for ACVR2A, FAM135A, and MAPRE1 genes. Thirty genes common between RA and SLE were proposed as robust gene signatures, with persistent expression in all the studies and cell types. These gene signatures were found to be involved in innate as well as adaptive immune responses, bone development and growth. In conclusion, our analysis of multicohort and multiple microarray datasets would provide the basis for understanding the common mechanisms of pathogenesis and exploring these gene signatures for their diagnostic and therapeutic potential.

The microbiological profile, associated risk factors and demographic characteristics of patients with IE has changed in the recent times. In the present study, the antibiotic susceptibility profile of 66 isolates (40 from IDU and 26 from non IDU) recovered over a period of three years from the patients with definitive diagnosis of IE along with their absolute minimum inhibitory concentrations (MIC-μg/ml) was determined as per CLSI, 2017 guidelines. Staphylococcus aureus was found to be the predominant pathogen associated with IE out of which 90.2% isolates were MRSA, although none of the isolates were found resistant to vancomycin, teicoplanin, daptomycin and linezolid. Pseudomonas aeruginosa isolates were 100% susceptible to carbapenams, however variable resistance was observed against other antimicrobials. All Enterococci were found to be 100% susceptible to linezolid and daptomycin, whereas vancomycin resistant enterococci phenotype was observed in 25% of the Enterococcal isolates. A noticeable difference in the antimicrobial susceptibility profile and their MICs were observed in the present study, as compared to published literature across the globe and within the country. However, no statistically significant difference (λ 2 test, p > 0.01)in the AST pattern of isolates from IDU vs. Non IDU was observed. After reviewing the local antibiogram it seems that we need to have our own regional guidelines, which may partially replace the currently prevailing AHA/ESC guidelines.

Post‐translational modifications, especially reversible phosphorylation, are among the most common mechanisms that regulate protein function and biological processes in Plasmodium species. Of the Plasmodium phosphatases, phosphatase of regenerating liver (PfPRL) is secreted and is an essential phosphatase. Here, we expressed PfPRL in a heterologous expression system, and then purified and characterized its phosphatase activity. We found that Novartis_003209, a previously identified inhibitor, inhibited the PfPRL phosphatase activity of recombinant PfPRL and blocked in vitro parasite growth in a dose‐dependent manner. Further, in silico docking analysis of Novartis_003209 with all four P. falciparum tyrosine phosphatases (PTP) demonstrated that Novartis_003209 is a Plasmodium PTP inhibitor. Overall, our results identify a scaffold as a potential starting point to design a PTP‐specific inhibitor.

The ongoing prevailing COVID-19 pandemic caused by SARS-CoV-2 is becoming one of the major global health concerns worldwide. The SARS-CoV-2 genome encodes spike (S) glycoprotein that plays a very crucial role in viral entry into the host cell via binding of its receptor binding domain (RBD) to the host angiotensin converting enzyme 2 (ACE2) receptor. The continuously evolving SARS-CoV-2 genome results in more severe and transmissible variants characterized by the emergence of novel mutations called ‘variants of concern’ (VOC). The currently designated alpha, beta, gamma, delta and omicron VOC are the focus of this study due to their high transmissibility, increased virulence, and concerns for decreased effectiveness of the available vaccines. In VOC, the spike (S) gene and other non-structural protein mutations may affect the efficacies of the approved COVID-19 vaccines. To understand the diversity of SARS-CoV-2, several studies have been performed on a limited number of sequences. However, only a few studies have focused on codon usage bias (CUBs) pattern analysis of all the VOC strains. Therefore, to evaluate the evolutionary divergence of all VOC S-genes, we performed CUBs analysis on 300,354 sequences to understand the evolutionary relationship with its adaptation in different hosts, i.e., humans, bats, and pangolins. Base composition and RSCU analysis revealed the presence of 20 preferred AU-ended and 10 under-preferred GC-ended codons. In addition, CpG was found to be depleted, which may be attributable to the adaptive response by viruses to escape from the host defense process. Moreover, the ENC values revealed a higher bias in codon usage in the VOC S-gene. Further, the neutrality plot analysis demonstrated that S-genes analyzed in this study are under 83.93% influence of natural selection, suggesting its pivotal role in shaping the CUBs. The CUBs pattern of S-genes was found to be very similar among all the VOC strains. Interestingly, we observed that VOC strains followed a trend of antagonistic codon usage with respect to the human host. The identified CUBs divergence would help to understand the virus evolution and its host adaptation, thus help design novel vaccine strategies against the emerging VOC strains. To the best of our knowledge, this is the first report for identifying the evolution of CUBs pattern in all the currently identified VOC.

ABSTRACT Despite a remarkable improvement in health care and continued drug discovery efforts, malaria control efforts are continuously challenged by the emergence of drug-resistant parasite strains. Given a long and risky development path of new drugs, repurposing existing drugs for the treatment of malaria is an attractive and shorter path. Tamoxifen, a selective estrogen receptor modulator (SERM) for the treatment and prevention of estrogen receptor-positive breast cancer, possesses antibacterial, antifungal, and antiparasitic activities. Hence, we assessed tamoxifen, raloxifene, and bazedoxifene, which represent the first-, second-, and third-generation SERMs, respectively, for antimalarial activity. Raloxifene and bazedoxifene inhibited the erythrocytic development of Plasmodium falciparum with submicromolar 50% inhibitory concentration (IC50) values. Among the three, bazedoxifene was the most potent and also decreased P. berghei infection in female mice but not in male mice. However, bazedoxifene similarly inhibited P. falciparum growth in erythrocytes of male and female origin, which highlights the importance of sex-specific host physiology in drug efficacy. Bazedoxifene was most potent on early ring-stage parasites, and about 35% of the treated parasites did not contain hemozoin in the food vacuole. Bazedoxifene-treated parasites had almost 34% less hemozoin content than the control parasites. However, both control and bazedoxifene-treated parasites had similar hemoglobin levels, suggesting that bazedoxifene inhibits hemozoin formation and that toxicity due to accumulation of free heme could be a mechanism of its antimalarial activity. Because bazedoxifene is in clinical use and bazedoxifene-chloroquine combination shows an additive antiparasitic effect, bazedoxifene could be an adjunctive partner of currently used antimalarial regimens. IMPORTANCE The emergence and spread of drug-resistant strains of the human malaria parasite Plasmodium falciparum has necessitated new drugs. Selective estrogen receptor modulators are in clinical use for the prevention and treatment of breast cancer and postmenopausal osteoporosis. We demonstrate that bazedoxifene, a third-generation selective estrogen receptor modulator, has potent inhibitory activity against both susceptible and drug-resistant strains of Plasmodium falciparum. It also blocked the development of Plasmodium berghei in mice. The inhibitory effect was strongest on the ring stage and resulted in the inhibition of hemozoin formation, which could be the major mechanism of bazedoxifene action. Hemozoin is a nontoxic polymer of heme, which is a by-product of hemoglobin degradation by the malaria parasite during its development within the erythrocyte. Because bazedoxifene is already in clinical use for the treatment of postmenopausal osteoporosis, our findings support repurposing of bazedoxifene as an antimalarial.

Background: Pseudoexfoliation syndrome is an age-related systemic microfibrillopathy, caused by progressive accumulation and gradual deposition of extracellular grey and white material over various tissues. It is associated with many intraocular abnormalities like poor pupillary dilatation, zonular dehiscence, glaucoma etc. Hence it is important to do detailed slit lamp examination with dilated pupil to detect the pseudoexfoliative deposits in eye, especially in elderly to prevent unforeseen complications. Aims and Objective: To study pattern of distribution of pseudoexfoliative material in eyes with pseudoexfoliation syndrome and to study the dilatation profile of pupil in such eyes. Materials and Methods: This observational study was conducted on patients with pseudoexfoliation syndrome who attended OPD in the Upgraded Department of Ophthalmology, Government Medical College, Jammu from 1st April 2018 for a period of 6 months. The clearance was taken from ethical committee for the study in reference. Informed consent was taken from all the patients enrolled in the study. Results: Pupillary margin was found to be the most common site for deposition of pex material i.e. 51 (75%) patients followed by anterior surface of lens in 32(47.05%) patients. Patients had simultaneous deposition of pex material over various parts of the eye. 64 (94.12%) patients had pex material deposited on pupil or lens. Only 1(1.47%) patient had pex deposits over cornea. 56 (82.35%) patients attained good to moderate dilatation of pupil with 0.8% tropicamide e/d. 12(17.65%) patients had pupillary dilatation of ≤4mm hence poor dilatation. Conclusion: Pseudoexfoliation presents challenges that must be adequately addressed with detailed slit lamp examination. Cases may go undetected due to failure to dilate the pupil or to examine with slit lamp after dilatation. Adequate pre-operative assessment should especially be done before cataract surgery with the aim to identify problems like the possibility of fragile zonules and inadequate mydriasis which could increase intraoperative complications arising from undue manipulations.

Background: Peribulbar anaesthesia has almost totally replaced general anaesthesia and retrobulbar block for ocular procedures especially in adults. Peribulbar block involves injections above and below the orbit, with local anesthetic deposited within the orbit but does not enter the muscle cone. Relatively safe but it is still associated with complications which are detailed in this study. Aims and Objective: To study the complications of classic double injection technique of peribulbar anaesthesia given in supine position before cataract surgery and to find the percentage of patients achieving complete block with 7ml of anaesthetic solution given by peribulbar route. Materials and Methods: This prospective observational study was conducted on 500 patients who were admitted for undergoing cataract extraction surgery in the Department of Ophthalmology in GMC Jammu for a period of 8 months from December 2018 to July 2019. Results: It was observed that 103 patients out of 500 (20.6%) developed one or more of complications. Chemosis was the most common complication which occurred in 87 (17.4%) patients followed by subcunjunctival haemorrhage observed in 19 (3.8%) patients. Lid ecchymosis occurred in 16 (2.4%) patients. Retrobulbar haemorrhage occurred in 11 (2.2%) patients. 2 (0.4%) patients developed severe lid edema. In 2 (0.4%) patients wrong eye was given block. 1 (0.2%) patient developed CRAO. Complete akinesia was obtained in 415 (83%) patients with 7ml of block. Rest required supplementary injections. 14 (2.8%) patients did not attain full akinesia after 12ml of block. Conclusion: Peribulbar block is a relatively safe procedure for obtaining ocular analgesia and akinesia, but is still associated with complications ranging from minor lid edema and chemosis to grave events like RBH to CRAO.

ABSTRACT Diagnosis of latent tuberculosis infection (LTBI) using biomarkers in order to identify the risk of progressing to active TB and therefore predicting a preventive therapy has been the main bottleneck in eradication of tuberculosis. We compared two assays for the diagnosis of LTBI: transcript signatures and interferon gamma release assay (IGRA), among household contacts (HHCs) in a high tuberculosis-burden population. HHCs of active TB cases were recruited for our study; these were confirmed to be clinically negative for active TB disease. Eighty HHCs were screened by IGRA using QuantiFERON-TB Gold Plus (QFT-Plus) to identify LTBI and uninfected cohorts; further, quantitative levels of transcript for selected six genes (TNFRSF10C, ASUN, NEMF, FCGR1B, GBP1, and GBP5) were determined. Machine learning (ML) was used to construct models of different gene combinations, with a view to identify hidden but significant underlying patterns of their transcript levels. Forty-three HHCs were found to be IGRA positive (LTBI) and thirty-seven were IGRA negative (uninfected). FCGR1B, GBP1, and GBP5 transcripts differentiated LTBI from uninfected among HHCs using Livak method. ML and ROC (Receiver Operator Characteristic) analysis validated this transcript signature to have a specificity of 72.7%. In this study, we compared a quantitative transcript signature with IGRA to assess the diagnostic ability of the two, for detection of LTBI cases among HHCs of a high-TB burden population; we concluded that a three gene (FCGR1B, GBP1, and GBP5) transcript signature can be used as a biomarker for rapid screening. IMPORTANCE The study compares potential of transcript signature and IGRA to diagnose LTBI. It is first of its kind study to screen household contacts (HHCs) in high TB burden area of India. A transcript signature (FCGR1B, GBP1, & GBP5) is identified as potential biomarker for LTBI. These results can lead to development of point-of-care (POC) like device for LTBI screening in a high TB burdened area.

Plasmodium falciparum is one of the plasmodium species responsible for the majority of life-threatening malaria cases. The current antimalarial therapies are becoming less effective due to growing drug resistance, leading to the urgent requirement for alternative and more effective antimalarial drugs or vaccines. To facilitate the novel drug discovery or vaccine development efforts, recent advances in sequencing technologies provide valuable information about the whole genome of the parasite, yet a lot more needs to be deciphered due to its incomplete proteome annotation. Surprisingly, out of the 5,389 proteins currently annotated in the Plasmodium falciparum 3D7 strain, 1,626 proteins (∼30% data) are annotated as hypothetical proteins. In parasite genomic studies, the challenge to annotate hypothetical proteins is often ignored, which may obscure the crucial information related to the pathogenicity of the parasite. In this study, we attempt to characterize hypothetical proteins of the parasite to identify novel drug targets using a computational pipeline. The study reveals that out of the overall pool of the hypothetical proteins, 266 proteins have conserved functional signatures. Furthermore, the pathway analysis of these proteins revealed that 23 proteins have an essential role in various biochemical, signalling and metabolic pathways. Additionally, all the proteins (266) were subjected to computational structure analysis. We could successfully model 11 proteins. We validated and checked the structural stability of the models by performing molecular dynamics simulation. Interestingly, eight proteins show stable conformations, and seven proteins are specific for Plasmodium falciparum, based on homology analysis. Lastly, mapping the seven shortlisted hypothetical proteins on the Plasmodium falciparum protein-protein interaction network revealed 3,299 nodes and 2,750,692 edges. Our study revealed interesting functional details of seven hypothetical proteins of the parasite, which help learn more about the less-studied molecules and their interactions, providing valuable clues to unravel the role of these proteins via future experimental validation.

c-Type cytochromes (cyt c) are proteins that undergo post-translational modification to covalently bind heme, which allows them to facilitate redox reactions in electron transport chains across all domains of life. Genomic evidence suggests that cyt c are involved in electron transfer processes among the Archaea, especially in members that produce or consume the potent greenhouse gas methane. However, neither the maturation machinery for cyt c in Archaea nor their role in methane metabolism has ever been functionally characterized. Here, we have used CRISPR-Cas9 genome editing tools to map a distinct pathway for cyt c biogenesis in the model methanogenic archaeon Methanosarcina acetivorans, and have also identified substrate-specific functional roles for cyt c during methanogenesis. Although the cyt c maturation machinery from M. acetivorans is universally conserved in the Archaea, our evolutionary analyses indicate that different clades of Archaea acquired this machinery through multiple independent horizontal gene transfer events from different groups of Bacteria. Overall, we demonstrate the convergent evolution of a novel Archaea-specific cyt c maturation machinery and its physiological role during methanogenesis, a process which contributes substantially to global methane emissions.

Drug repositioning continues to be the most effective, practicable possibility to treat COVID-19 patients. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters target cells by binding to the ACE2 receptor via its spike (S) glycoprotein. We used molecular docking-based virtual screening approaches to categorize potential antagonists, halting ACE2-spike interactions by utilizing 450 FDA-approved chemical compounds. Three drug candidates (i.e., anidulafungin, lopinavir, and indinavir) were selected, which show high binding affinity toward the ACE2 receptor. The conformational stability of selected docked complexes was analyzed through molecular dynamics (MD) simulations. The MD simulation trajectories were assessed and monitored for ACE2 deviation, residue fluctuation, the radius of gyration, solvent accessible surface area, and free energy landscapes. The inhibitory activities of the selected compounds were eventually tested in-vitro using Vero and HEK-ACE2 cells. Interestingly, besides inhibiting SARS-CoV-2 S glycoprotein induced syncytia formation, anidulafungin and lopinavir also blocked S-pseudotyped particle entry into target cells. Altogether, anidulafungin and lopinavir are ranked the most effective among all the tested drugs against ACE2 receptor-S glycoprotein interaction. Based on these findings, we propose that anidulafungin is a novel potential drug targeting ACE2, which warrants further investigation for COVID-19 treatment.

Introduction: Infective endocarditis (IE) is the most dreaded complication of intravenous drug abuse (IVDA). IVDA is present in significant proportions in India. Since there is scarcity of Indian data on IVDA associated IE, we report a study comparing IVDA to non IVDA associated IE. We compare differences in clinical profile, microbiology, echocardiography and clinical outcome from a tertiary care hospital. Methods: A total of 133 patients admitted from 1st January 2017 to 31st December 2019 who met the Modified Duke ‘‘definitive’’ criteria for IE were included. Detailed Information was collected regarding demography, clinical data and laboratory investigations. All patients underwent transthoracic echocardiography and trans-esophageal echocardiogram wherever necessary. Results: Among a total of 133 patients, 54 patients (40.6%) were iv drug abusers. Patients in IVDA-group were younger, mostly males, more likely to have concomitant HCV and HIV infections compared to non IVDA-group. Chronic comorbidities such as DM and CKD were more common in non IVDA-group. Rate of positive blood culture was higher in IVDA-group compared to non IVDA-group (74.1%v/s 32.9%,p

We developed the DriverFuse package to integrate orthogonal data types such as Structural Variants (SV) and Copy Number Variations (CNV) to characterize fusion genes in cancer datasets. A fusion gene is reported as a driver or passenger fusion gene, based on mapping SV and CNV profiles. DriverFuse generates a fusion plot of fusion genes with their mapping SV, CNV profile, domain architecture and classification of its role in cancer. The analysis facilitates discrimination of driver fusions from passenger fusions. To demonstrate the utility of DriverFuse, we analyzed two datasets, one each for CCLE (Cancer Cell Line Encyclopedia) for lung cancer and HCC1395BL for breast cancer. The analysis validates the driver fusion genes that are already reported for the datasets. Thus, DriverFuse is a valuable tool for studying the driver fusion genes in cancers, enabling the identification of recurrent complex rearrangements that provide intuitive insights into disease driver events.

Many studies have shown that the lysosomal cathepsins, especially cathepsins B/L (CTSB/L) are required for SARS-CoV-2 entry into host cells. Lysosomal proteases, cathepsins are indispensable for normal health and are involved in several brain disorders occurring at different development age periods. On the other hand, it has been well known that COVID-19 infection is largely associated with several neurological disorders. Taken together these findings and given the high levels of expression of CTSB/L in the brain, we here proposed a reasonable hypothesis about the involvement of CTSB/L in the neurological manifestations linked to COVID-19. Pharmacological inhibitions of the CTSB/L could be a potential therapeutic target to block the virus entry as well as to mitigate the brain disorders. To this end, we utilized the network-based drug repurposing analyses to identify the possible drugs that can target CTSB/L. This study identifies the molecules like cyclosporine, phenytoin, and paclitaxel as potential drugs with binding ability to the CTSB/L. Further, we have performed molecular docking and all-atom molecular dynamics (MD) simulations to investigate the stability of CTSL-drug complexes. The results showed strong and stable binding of drugs with CTSL.

Background: While our battle with the COVID-19 pandemic continues, a multitude of Omics data have been generated from patient samples in various studies. Translation of these data into clinical interventions against COVID-19 remains to be accomplished. Exploring host response to COVID-19 in the upper respiratory tract can unveil prognostic markers and therapeutic targets. Methods: We conducted a meta-analysis of published transcriptome and proteome profiles of respiratory samples of COVID-19 patients to shortlist high confidence upregulated host factors. Subsequently, mRNA overexpression of selected genes was validated in nasal swabs from a cohort of COVID-19 positive/negative, symptomatic/asymptomatic individuals. Guided by this analysis, we sought to check for potential drug targets. An FDA-approved drug, Auranofin, was tested against SARS-CoV-2 replication in cell culture and Syrian hamster challenge model. Findings: The meta-analysis and validation in the COVID-19 cohort revealed S100 family genes (S100A6, S100A8, S100A9, and S100P) as prognostic markers of severe COVID-19. Furthermore, Thioredoxin (TXN) was found to be consistently upregulated. Auranofin, which targets Thioredoxin reductase, was found to mitigate SARS-CoV-2 replication in vitro. Furthermore, oral administration of Auranofin in Syrian hamsters in therapeutic as well as prophylactic regimen reduced viral replication, IL-6 production, and inflammation in the lungs. Interpretation: Elevated mRNA level of S100s in the nasal swabs indicate severe COVID-19 disease, and FDA-approved drug Auranofin mitigated SARS-CoV-2 replication in preclinical hamster model. Funding: This study was supported by the DBT-IISc partnership program (DBT (IED/4/2020-MED/DBT)), the Infosys Young Investigator award (YI/2019/1106), DBT-BIRAC grant (BT/CS0007/CS/02/20) and the DBT-Wellcome Trust India Alliance Intermediate Fellowship (IA/I/18/1/503613) to ST lab.

Malaria is one of the major global health concerns still prevailing in this 21st century. Even the effect of artemisinin combination therapies (ACT) have declined and causing more mortality across the globe. Therefore, it is important to understand the basic biology of malaria parasite in order to find novel drug targets. Helicases play important role in nucleic acid metabolism and are components of cellular machinery in various organisms. In this manuscript we have performed the biochemical characterization of homologue of DDX17 from Plasmodium falciparum (PfDDX17). Our results show that PfDDX17 is an active RNA helicase and uses mostly ATP for its function. The qRT-PCR experiment results suggest that PfDDX17 is highly expressed in the trophozoite stage and it is localised mainly in the cytoplasm and in infected RBC (iRBC) membrane mostly in the trophozoite stage. The dsRNA knockdown study suggests that PfDDX17 is important for cell cycle progression. These studies report the biochemical functions of PfDDX17 helicase and further augment the fundamental knowledge about helicase families of P. falciparum.

Abstract Background Protein secretion is an essential process in all eukaryotes including organisms belonging to the phylum Apicomplexa, which includes many intracellular parasites. The apicomplexan parasites possess a specialized collection of secretory organelles that release a number of proteins to facilitate the invasion of host cells and some of these proteins also participate in immune evasion. Like in other eukaryotes, these parasites possess a series of membrane-bound compartments, namely the endoplasmic reticulum (ER), the intermediate compartments (IC) or vesicular tubular clusters (VTS) and Golgi complex through which proteins pass in a sequential and vectorial fashion. Two sets of proteins; COPI and COPII are important for directing the sequential transfer of material between the ER and Golgi complex. Results Here, using in silico approaches, we identify the components of COPI and COPII complexes in the genome of apicomplexan organisms. The results showed that the COPI and COPII protein complexes are conserved in most apicomplexan genomes with few exceptions. Diversity among the components of COPI and COPII complexes in apicomplexan is either due to the absence of a subunit or due to the difference in the number of protein domains. For example, the COPI epsilon subunit and COPII sec13 subunit is absent in Babesia bovis, Theileria parva, and Theileria annulata genomes. Phylogenetic and domain analyses for all the proteins of COPI and COPII complexes was performed to predict their evolutionary relationship and functional significance. Conclusions The study thus provides insights into the apicomplexan COPI and COPII coating machinery, which is crucial for parasites secretory network needed for the invasion of host cells.

With the availability of COVID-19-related clinical data, healthcare researchers can now explore the potential of computational technologies such as artificial intelligence (AI) and machine learning (ML) to discover biomarkers for accurate detection, early diagnosis, and prognosis for the management of COVID-19. However, the identification of biomarkers associated with survival and deaths remains a major challenge for early prognosis. In the present study, we have evaluated and developed AI-based prediction algorithms for predicting a COVID-19 patient’s survival or death based on a publicly available dataset consisting of clinical parameters and protein profile data of hospital-admitted COVID-19 patients. The best classification model based on clinical parameters achieved a maximum accuracy of 89.47% for predicting survival or death of COVID-19 patients, with a sensitivity and specificity of 85.71 and 92.45%, respectively. The classification model based on normalized protein expression values of 45 proteins achieved a maximum accuracy of 89.01% for predicting the survival or death, with a sensitivity and specificity of 92.68 and 86%, respectively. Interestingly, we identified 9 clinical and 45 protein-based putative biomarkers associated with the survival/death of COVID-19 patients. Based on our findings, few clinical features and proteins correlate significantly with the literature and reaffirm their role in the COVID-19 disease progression at the molecular level. The machine learning–based models developed in the present study have the potential to predict the survival chances of COVID-19 positive patients in the early stages of the disease or at the time of hospitalization. However, this has to be verified on a larger cohort of patients before it can be put to actual clinical practice. We have also developed a webserver CovidPrognosis, where clinical information can be uploaded to predict the survival chances of a COVID-19 patient. The webserver is available at http://14.139.62.220/covidprognosis/.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92–2.59,

Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive form of pancreatic cancer that typically manifests itself at an advanced stage and does not respond to most treatment modalities. The survival rate of a PDAC patient is less than 5%, with a median survival of just a couple of months. A better understanding of the molecular pathology of PDAC is needed to guide research for the development of better clinical treatment modalities for PDAC patients. Gene expression studies performed to date have identified different subtypes of PDAC with prognostic and clinical relevance. Subtypes identified to date are highly heterogeneous since pancreatic cancer is heterogeneous cancer. Tumor microenvironment and stroma constitute a major chunk of PDAC and contribute to the heterogeneity. Better subtyping methods are need of the hour for better prognosis and classification of PDAC for future personalized treatment. In this work, we have performed an integrated analysis of DNA methylation and gene expression datasets to provide better mechanistic and molecular insights into Pancreatic cancers, especially PDAC. The use of varied and diverse datasets has provided valuable insights into different cancer types and can play an integral role in revealing the complex nature of underlying biological mechanisms. We performed subtyping of TCGA-PAAD gene expression and methylation datasets into different subtypes using state-of-the-art normalization methods and unsupervised clustering methods that reveal latent hidden factors, leading to additional insights for subtyping. Differential expression and differential methylation were performed for each of the subtypes obtained from clustering. Our analysis gave a consensus of five cluster solution with relevant pathways like MAPK, MET. The five subtypes corresponded to the tumor and stromal subtypes. This analysis helps in distinguishing and identifying different subtypes based on enriched putative genes. These results help propose novel experimentally-verifiable PDAC subtyping and demonstrate that using varied data sets and integrated methods can contribute to disease prognostication and precision medicine in PDAC treatment.

The dataset contains images of 10 out of 32 notified Indian basmati seeds varieties (by the Government of India). Indian basmati paddy varieties included in the dataset are 1121, 1509, 1637, 1718, 1728, BAS-370, CSR 30, Type-3/Dehraduni Basmati, PB-1 and PB-6. Moreover, several images of other seeds and related entities available in the household have also been included in the dataset. Thus, the dataset contains 11 classes such that ten classes contain images from ten different basmati paddy varieties. In contrast, the 11th class- named “Unknown” contains images from a mixture of two morphologically similar paddy varieties (1121 and 1509), different pulses, other grains and related food entities. The Unknown class is useful in discriminating the paddy seeds from other types of seeds and related food entities. All the images were captured (in standard conditions) manually using an apparatus developed in-house and a tablet with a five-megapixel camera (5MP). The camera was used to capture 3210 RGB coloured images in JPG format. The data pre-processing was performed to generate the ready-to-use images for training and testing machine learning-based models. AI-based paddy seed variety classification models have been developed using the dataset. The dataset can be used to generate different types of AI-based models for adulteration detection, automated classification models (along with independent devices) at the time of rice threshing, and to increase the classification potential (Supplementing images representing additional basmati varieties).

Understanding the host regulatory mechanisms opposing virus infection and virulence can provide actionable insights to identify novel therapeutics against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have used a network biology approach to elucidate the crucial factors involved in host responses involving host–microRNA (miRNA) interactions with host and virus genes using recently published experimentally verified protein–protein interaction data. We were able to identify 311 host genes to be potentially targetable by 2,197 human miRNAs. These miRNAs are known to be involved in various biological processes, such as T-cell differentiation and activation, virus replication, and immune system. Among these, the anti-viral activity of 38 miRNAs to target 148 host genes is experimentally validated. Six anti-viral miRNAs, namely, hsa-miR-1-3p, hsa-miR-17-5p, hsa-miR-199a-3p, hsa-miR-429, hsa-miR-15a-5p, and hsa-miR-20a-5p, are previously reported to be anti-viral in respiratory diseases and were found to be downregulated. The interaction network of the 2,197 human miRNAs and interacting transcription factors (TFs) enabled the identification of 51 miRNAs to interact with 77 TFs inducing activation or repression and affecting gene expression of linked genes. Further, from the gene regulatory network analysis, the top five hub genes HMOX1, DNMT1, PLAT, GDF1, and ITGB1 are found to be involved in interferon (IFN)-α2b induction, epigenetic modification, and modulation of anti-viral activity. The comparative miRNAs target identification analysis in other respiratory viruses revealed the presence of 98 unique host miRNAs targeting SARS-CoV-2 genome. Our findings identify prioritized key regulatory interactions that include miRNAs and TFs that provide opportunities for the identification of novel drug targets and development of anti-viral drugs.

The identification of host-miRNAs targeting mutated virus genes is crucial to understand the miRNA mediated host-defense mechanism in virus infections. To understand the mechanism in COVID-19 infections, we collected genome sequences of SARS-CoV-2 with its metadata from the GISAID database (submitted till April 2020) and identified mutational changes in the sequences. The dataset consists of genes with mutation event count and entropy scores. We predicted host-miRNAs targeting the genes in the genomes and compared it with that in related viral species. We have identified 2284 miRNAs targeting MERS genomes, 2074 miRNAs targeting SARS genomes, and 1599 miRNAs targeting SARS-CoV-2 genomes, identified using the miRNA target prediction software miRanda. The host miRNAs targeting SARS-CoV-2 genes were further validated to be anti-viral miRNAs and their role in respiratory diseases through a literature survey, which helped in the identification of 42 conserved antiviral miRNAs. The data could be used to validate the anti-viral role of the predicted miRNAs and design miRNA-based therapeutics against SARS-CoV-2.

We have performed an integrative analysis of SARS-CoV-2 genome sequences from different countries. Apart from mutational analysis, we have predicted host antiviral miRNAs targeting virus genes, PTMs in the virus proteins and antiviral peptides. A comparison of the analyses with other coronavirus genomes has been performed, wherever possible. Our analysis confirms unique features in the SARS-CoV-2 genomes absent in other evolutionarily related coronavirus family genomes, which presumably confer unique infection, transmission and virulence capabilities to the virus. For understanding the crucial factors involved in host-virus interactions, we have performed Bioinformatics aided analysis integrated with experimental data related to other corona viruses. We have identified 42 conserved miRNAs that can potentially target SARS-CoV-2 genomes. Interestingly, out of these, 3 are previously reported to exhibit antiviral activity against other respiratory viruses. Gene expression analysis of known host antiviral factors reveals significant over-expression of IFITM3 and down regulation of cathepsins during SARS-CoV-2 infection, suggesting its active role in pathogenesis and delayed immune response. We also predicted antiviral peptides which can be used in designing peptide based drugs against SARS-CoV-2. Our analysis explores the functional impact of the virus mutations on its proteins and interaction of its genes with host antiviral mechanisms.

Summary: Condensin is a multi-subunit protein complex regulating chromosome condensation and segregation during cell division. In Plasmodium spp., the causative agent of malaria, cell division is atypical and the role of condensin is unclear. Here we examine the role of SMC2 and SMC4, the core subunits of condensin, during endomitosis in schizogony and endoreduplication in male gametogenesis. During early schizogony, SMC2/SMC4 localize to a distinct focus, identified as the centromeres by NDC80 fluorescence and chromatin immunoprecipitation sequencing (ChIP-seq) analyses, but do not form condensin I or II complexes. In mature schizonts and during male gametogenesis, there is a diffuse SMC2/SMC4 distribution on chromosomes and in the nucleus, and both condensin I and condensin II complexes form at these stages. Knockdown of smc2 and smc4 gene expression reveals essential roles in parasite proliferation and transmission. The condensin core subunits (SMC2/SMC4) form different complexes and may have distinct functions at various stages of the parasite life cycle. : Pandey et al. use live cell imaging, proteomics, and genetic approaches to show that Plasmodium condensin core subunits (SMC2/SMC4) have differential cellular location and condensin complex formation during parasite development and have essential roles in parasite proliferation and transmission. Keywords: condensin, SMC4, atypical mitosis, Plasmodium, mosquito, transmision, chromosome, protein complex, kleisin, oocyst

The purity of seeds is the most important factor in agriculture that determines crop yield, price, and quality. Rice is a major staple food consumed in different forms globally. The identification of high yielding and good quality paddy seeds is a challenging job and mainly dependent on expensive molecular techniques. The practical and day-to-day usage of the molecular-laboratory based techniques are very costly and time-consuming, and involves several logistical issues too. Moreover, such techniques are not easily accessible to paddy farmers. Thus, there is an unmet need to develop alternative, easily accessible and rapid methods for correct identification of paddy seed varieties, especially of commercial importance. We have developed iRSVPred, deep learning based on seed images, for the identification and differentiation of ten major varieties of basmati rice namely, Pusa basmati 1121 (1121), Pusa basmati 1509 (1509), Pusa basmati 1637 (1637), salt-tolerant basmati rice variety CSR 30 (CSR-30), Dehradoon basmati Type-3 (DHBT-3), Pusa Basmati-1 (PB-1), Pusa Basmati-6 (PB-6), Basmati -370 (BAS-370), Pusa Basmati 1718 (1718) and Pusa Basmati 1728 (1728). The method has an overall accuracy of 100% and 97% on the training set (total 61,632 images) and internal validation set (total 15,408 images), respectively. Furthermore, accuracies of greater than or equal to 80% have been achieved for all the ten varieties on the external validation dataset (642 images) used in the study. The iRSVPred web-server is freely available at http://14.139.62.220/rice/.

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has led to global health and healthcare crisis, apart from the tremendous socioeconomic effects. One of the significant challenges in this crisis is to identify and monitor the COVID-19 patients quickly and efficiently to facilitate timely decisions for their treatment, monitoring, and management. Research efforts are on to develop less time-consuming methods to replace or to supplement RT-PCR-based methods. The present study is aimed at creating efficient deep learning models, trained with chest X-ray images, for rapid screening of COVID-19 patients. We used publicly available PA chest X-ray images of adult COVID-19 patients for the development of Artificial Intelligence (AI)-based classification models for COVID-19 and other major infectious diseases. To increase the dataset size and develop generalized models, we performed 25 different types of augmentations on the original images. Furthermore, we utilized the transfer learning approach for the training and testing of the classification models. The combination of two best-performing models (each trained on 286 images, rotated through 120° or 140° angle) displayed the highest prediction accuracy for normal, COVID-19, non-COVID-19, pneumonia, and tuberculosis images. AI-based classification models trained through the transfer learning approach can efficiently classify the chest X-ray images representing studied diseases. Our method is more efficient than previously published methods. It is one step ahead towards the implementation of AI-based methods for classification problems in biomedical imaging related to COVID-19.

ABSTRACT Photoferrotrophy is a form of anoxygenic photosynthesis whereby bacteria utilize soluble or insoluble forms of ferrous iron as an electron donor to fix carbon dioxide using light energy. They can also use poised electrodes as their electron donor via phototrophic extracellular electron uptake (phototrophic EEU). The electron uptake mechanisms underlying these processes are not well understood. Using Rhodopseudomonas palustris TIE-1 as a model, we show that a single periplasmic decaheme cytochrome c, PioA, and an outer membrane porin, PioB, form a complex allowing extracellular electron uptake across the outer membrane from both soluble iron and poised electrodes. We observe that PioA undergoes postsecretory proteolysis of its N terminus to produce a shorter heme-attached PioA (holo-PioAC, where PioAC represents the C terminus of PioA), which can exist both freely in the periplasm and in a complex with PioB. The extended N-terminal peptide controls heme attachment, and its processing is required to produce wild-type levels of holo-PioAC and holo-PioACB complex. It is also conserved in PioA homologs from other phototrophs. The presence of PioAB in these organisms correlate with their ability to perform photoferrotrophy and phototrophic EEU. IMPORTANCE Some anoxygenic phototrophs use soluble iron, insoluble iron minerals (such as rust), or their proxies (poised electrodes) as electron donors for photosynthesis. However, the underlying electron uptake mechanisms are not well established. Here, we show that these phototrophs use a protein complex made of an outer membrane porin and a periplasmic decaheme cytochrome (electron transfer protein) to harvest electrons from both soluble iron and poised electrodes. This complex has two unique characteristics: (i) it lacks an extracellular cytochrome c, and (ii) the periplasmic decaheme cytochrome c undergoes proteolytic cleavage to produce a functional electron transfer protein. These characteristics are conserved in phototrophs harboring homologous proteins.

Background: The burden of HF in India is high, with an estimated prevalence of about 5 million patients, an annual incidence of one million, an in hospital mortality as high as 30.8%, with postdischarge 6 month major adverse event and mortality rates at 39.5% and 26.3%. Acute decompensated HF is caused by a variety of precipitating factors and many are preventable. Methods: This 1 year study was a prospective study conducted on the patients admitted under a tertiary care unit in north India. Patients included in the study had chronic stable left ventricular systolic dysfunction and developed acute decompensated HF. Results: This study included 150 Patients with ADHF . Moderate to severe anemia was found to be the factor in 63.8% of the patients. New onset myocardial ischemia was the next most common factor leading to acute decompensated HF, Dietary indiscretion was seen in 45.3% of the patients. Noncompliance to drugs was also very common. The study revealed that higher rates of admissions with acute decompensated HF were seen in winters (October to December and January to March). Conclusion: Anemia and noncompliance with drugs were most common precipitating factors leading acute decompensated HF in North Indian population.Every patient needs a more intensive regular follow up and adequate diet pattern for prevention of acute decompensated HF. Systematic patient education and treatment can reduce the burden, risk of ADHF, and re hospitalization.

Background: OHCA (out of hospital cardiac arrest) is a leading cause of death in developed countries, outcome of which depends upon various factors. Not much data is available in India, on outcome of OHCA. Thus, this study was conducted to assess various clinical and biochemical parameters in predicting outcome of survivors of out of hospital cardiac arrest. Methods: This prospective study was done in HDHI Unit of DMCH, Ludhiana over a period of 12 months (January, 2016 to December 2016). Patients of OHCA who were revived following CPR were enrolled for the study and outcome in terms of GCPS and NYHA was seen after one month. Results: A total of 542 patients of OHCA presented to the emergency, of which 49 (9.04%) patients were admitted after ROSC following CPR. Of these 49 patients, 18 (36.73%) survived to hospital discharge and 31 (63.26%) expired or took discharge in a critical condition and presumed to be expired. Mean age of patients was 58.06 ± 15.1 years and males constituted 67.35%. Mean time from arrest to hospital was 7.44 ± 6.9 minutes (survivors) compared to 13.23 ± 8.1 minutes (non survivors) (P value = 0.009). Mean duration of stay was more among discharged (P = 0.006). Patients presenting with VF/VT (P = 0.003) as first monitored rhythm compared to asystole (P = 0.004) had better outcome. On multivariate analysis VF, duration of hospital stay, raised urea and creatinine, time from arrest to first help and hospital were predictors of good outcome. Conclusion: Shorter time interval from arrest to reaching the hospital and shockable rhythm were associated with better outcome in patients of OHCA. Duration of CPR (cardiopulmonary resuscitation), age, gender, comorbidities, witnessed arrest and resuscitation attempt by bystander (bystander CPR) did not show any relation in predicting outcome in out of hospital cardiac arrest survivors. Raised urea and creatinine (correctable biochemical parameters) played a significant role in survival was cardiac arrest on way to hospital.

Reduced sensitivity of the human malaria parasite, Plasmodium falciparum, to Artemisinin and its derivatives (ARTs) threatens the global efforts towards eliminating malaria. ARTs have been shown to cause ubiquitous cellular and genetic insults, which results in the activation of the unfolded protein response (UPR) pathways. The UPR restores protein homeostasis, which otherwise would be toxic to cellular survival. Here, we interrogated the role of DNA-damage inducible protein 1 (PfDdi1), a unique proteasome-interacting retropepsin in mediating the actions of the ARTs. We demonstrate that PfDdi1 is an active A2 family protease that hydrolyzes ubiquitinated proteasome substrates. Treatment of P. falciparum parasites with ARTs leads to the accumulation of ubiquitinated proteins in the parasites and blocks the destruction of ubiquitinated proteins by inhibiting the PfDdi1 protease activity. Besides, whereas the PfDdi1 is predominantly localized in the cytoplasm, exposure of the parasites to ARTs leads to DNA fragmentation and increased recruitment of the PfDdi1 into the nucleus. Furthermore, we show that Ddi1 knock-out Saccharomycescerevisiae cells are more susceptible to ARTs and the PfDdI1 protein robustly restores the corresponding functions in the knock-out cells. Together, these results show that ARTs act in multiple ways; by inducing DNA and protein damage and might be impairing the damage recovery by inhibiting the activity of PfDdi1, an essential ubiquitin-proteasome retropepsin.

Paulowina elongata is a fast-growing tree species is grown in different climates and types of soils. Environmental adaptability as well as high-yielding biomass make the P. elongata species an ideal candidate for biofuel production. High soil salinity is known to inhibit plant growth dramatically or leads to plant death. The purpose of this study was to characterize the salt-induced changes in the transcriptome of P. elongata. Transcriptome differences in response to salt stress were determined by RNA sequencing (RNA-seq) using next generation sequencing and bioinformatics analysis. A total of 645 genes were found to have significant altered expression in response to salt stress. Expression levels of a selective subset of these genes were chosen and confirmed using quantitative real-time PCR. To the best of our knowledge, this is the first report of salt-induced transcriptome analysis in P. elongata. The current study indicates that differential expression of a select group of genes of P. elongata and their possible roles in pathways and mechanisms related to salt tolerance. Functional characterization of these genes will assist in future investigations of salt tolerance in P. elongata, which could be used to enhance biofuel production. Abbreviations: ABA: abscisic acid; SOS: salt overly sensitive; ROS: reactive oxygen species; PCR: polymerase chain reaction; qPCR: quantitative real-time polymerase chain reaction

Background: Human papilloma viruses (HPVs) are small DNA viruses that have been identified in periodontal pocket as well as gingival sulcus. High risk HPVs are also associated with a subset of head and neck carcinomas. It is thought that the periodontium could be a reservoir for HPV. Aims: 1. Detection of Human Papilloma virus (HPV) in periodontal pocket as well as gingival of patients having localized chronic periodontitis and gingival sulcus of periodontally healthy subjects. 2. Quantitative estimation of E6 and E7 mRNA in subjects showing presence of HPV3. To assess whether periodontal pocket is a reservoir for HPV. Settings and Design: This case-control study included 30 subjects with localized chronic Periodontitis (cases) and 30 periodontally healthy subjects (controls). Two samples were taken from cases, one from periodontal pocket and one from gingival sulcus and one sample was taken from controls. Methods and Materials: Samples were collected in the form of pocket scrapings and gingival sulcus scrapings from cases and controls respectively. These samples were sent in storage media for identification and estimation of E6/E7 mRNA of HPV using in situ hybridization and flow cytometry. Statistical analysis: Statistical analysis was done by using, mean, percentage and Chi Square test. A statistical package SPSS version 13.0 was used to analyze the data. P value < 0.05 was considered as statistically significant. Results: pocket samples as well as sulcus samples for both cases and controls were found to contain HPV E6/E7 mRNAInterpretation and Conclusion: Presence of HPV E6/E7 mRNA in periodontium supports the hypothesis that periodontal tissues serve as a reservoir for latent HPV and there may be a synergy between oral cancer, periodontitis and HPV. However prospective studies are required to further explore this link.

The serine protease, DegP exhibits proteolytic and chaperone activities, essential for cellular protein quality control and normal cell development in eukaryotes. The P. falciparum DegP is essential for the parasite survival and required to combat the oscillating thermal stress conditions during the infection, protein quality checks and protein homeostasis in the extra-cytoplasmic compartments, thereby establishing it as a potential target for drug development against malaria. Previous studies have shown that diisopropyl fluorophosphate (DFP) and the peptide SPMFKGV inhibit E. coli DegP protease activity. To identify novel potential inhibitors specific to PfDegP allosteric and the catalytic binding sites, we performed a high throughput in silico screening using Malaria Box, Pathogen Box, Maybridge library, ChEMBL library and the library of FDA approved compounds. The screening helped identify five best binders that showed high affinity to PfDegP allosteric (T0873, T2823, T2801, RJC02337, CD00811) and the catalytic binding site (T0078L, T1524, T2328, BTB11534 and 552691). Further, molecular dynamics simulation analysis revealed RJC02337, BTB11534 as the best hits forming a stable complex. WaterMap and electrostatic complementarity were used to evaluate the novel bio-isosteric chemotypes of RJC02337, that led to the identification of 231 chemotypes that exhibited better binding affinity. Further analysis of the top 5 chemotypes, based on better binding affinity, revealed that the addition of electron donors like nitrogen and sulphur to the side chains of butanoate group are more favoured than the backbone of butanoate group. In a nutshell, the present study helps identify novel, potent and Plasmodium specific inhibitors, using high throughput in silico screening and bio-isosteric replacement, which may be experimentally validated.

Introduction: Aluminum phosphide (AlP) poisoning has a high mortality rate despite intensive care management, primarily because it causes severe myocardial depression and severe acute respiratory distress syndrome. The purpose of this study was to evaluate the impact of the novel use of extracorporeal membrane oxygenation (ECMO), a modified “heart-lung” machine, in a specific subset of AlP poisoning patients who had profound myocardial dysfunction along with either severe metabolic acidosis and/or refractory cardiogenic shock. Methods: Between January 2011 and September 2014, 83 patients with AlP poisoning were enrolled in this study; 45 patients were classified as high risk. The outcome of the patients who received ECMO (n = 15) was compared with that of patients who received conventional treatment (n = 30). Results: In the high-risk group (n = 45), the mortality rate was significantly (p

Aim: Human papilloma viruses (HPVs) are small DNA viruses that have been identified in periodontal pocket as well as gingival sulcus. High risk HPVs are also associated with a subset of head and neck carcinomas. HPV detection in periodontium has previously involved DNA detection. This study attempts to: (a) Detect the presence or absence of high risk HPV in marginal periodontiun by identifying E6/E7 messenger RNA (mRNA) in cells from samples obtained by periodontal pocket scraping. (b) Detect the percentage of HPV E6/E7 mRNA in cells of pocket scrapings, which is responsible for producing oncoproteins E6 and E7. Materials and Methods: Pocket scrapings from the periodontal pockets of eight subjects with generalized chronic periodontitis were taken the detection of presence or absence of E6, E7 mRNA was performed using in situ hybridization and flow cytometry. Results: HPV E6/E7 mRNA was detected in four of the eight samples. Conclusion: Presence of high risk human papillomaviruses in periodontal pockets patients of diagnosed with chronic periodontitis, not suffering from head and neck squamous cell carcinoma in the present day could link periodontitis to HPV related squamous cell carcinoma. Prevalence studies are needed detecting the presence of HPV in marginal periodontium as well as prospective studies of HPV positive periodontitis patients are required to explore this possible link.

Protein methylation is an important Post-Translational Modification (PTMs) of proteins. Arginine methylation carries out and regulates several important biological functions, including gene regulation and signal transduction. Experimental identification of arginine methylation site is a daunting task as it is costly as well as time and labour intensive. Hence reliable prediction tools play an important task in rapid screening and identification of possible methylation sites in proteomes. Our preliminary assessment using the available prediction methods on collected data yielded unimpressive results. This motivated us to perform a comprehensive data analysis and appraisal of features relevant in the context of biological significance, that led to the development of a prediction tool PRmePRed with better performance. The PRmePRed perform reasonably well with an accuracy of 84.10%, 82.38% sensitivity, 83.77% specificity, and Matthew's correlation coefficient of 66.20% in 10-fold cross-validation. PRmePRed is freely available at http://bioinfo.icgeb.res.in/PRmePRed/.

Influenza still remains one of the most challenging diseases, posing a significant threat to public health. Host lipid rafts play a critical role in influenza A virus (IAV) assembly and budding, however, their role in polyvalent IAV host binding and endocytosis had remained elusive until now. In the present study, we observed co-localization of IAV with a lipid raft marker ganglioside, GM1, on the host surface. Further, we isolated the lipid raft micro-domains from IAV infected cells and detected IAV protein in the raft fraction. Finally, raft disruption using Methyl-β-Cyclodextrin revealed significant reduction in IAV host binding, suggesting utilization of host rafts for polyvalent binding on the host cell surface. In addition to this, cyclodextrin mediated inhibition of raft-dependent endocytosis showed significantly reduced IAV internalization. Interestingly, exposure of cells to cyclodextrin two hours post-IAV binding showed no such reduction in IAV entry, indicating use of raft-dependent endocytosis for host entry. In summary, this study demonstrates that host lipid rafts are selected by IAV as a host attachment factors for multivalent binding, and IAV utilizes these micro-domains to exploit raft-dependent endocytosis for host internalization, a virus entry route previously unknown for IAV.