Whole genome sequence of denitrifying bacterium Stutzerimonas stutzeri strain NGHE31, collected from an eutrophic wetland in Sunamganj, Bangladesh, following the 2017 flash floods.

Here, we report the whole genome sequence of Stutzerimonas stutzeri strain NGHE31, isolated from Dekhar Haor, following the 2017 flash flood that resulted in mass die-offs of local wildlife. The predicted genome size is 4,434,670 bp, with 63.97% GC content, 4,035 coding sequences, 3 rRNAs, and 50 tRNAs.

Convergence of resistance and evolutionary responses in Escherichia coli and Salmonella enterica co-inhabiting chicken farms in China.

Sharing of genetic elements among different pathogens and commensals inhabiting same hosts and environments has significant implications for antimicrobial resistance (AMR), especially in settings with high antimicrobial exposure. We analysed 661 Escherichia coli and Salmonella enterica isolates collected within and across hosts and environments, in 10 Chinese chicken farms over 2.5 years using data-mining methods. Most isolates within same hosts possessed the same clinically relevant AMR-carrying mobile genetic elements (plasmids: 70.6%, transposons: 78%), which also showed recent common evolution. Supervised machine learning classifiers revealed known and novel AMR-associated mutations and genes underlying resistance to 28 antimicrobials, primarily associated with resistance in E. coli and susceptibility in S. enterica. Many were essential and affected same metabolic processes in both species, albeit with varying degrees of phylogenetic penetration. Multi-modal strategies are crucial to investigate the interplay of mobilome, resistance and metabolism in cohabiting bacteria, especially in ecological settings where community-driven resistance selection occurs.

Impact of antibiotic-coated sutures on surgical site infections: a second-order meta-analysis.

BACKGROUND: Surgical site infections (SSIs) pose a global challenge, impacting patients and healthcare expenditures. This second-order meta-analysis endeavors to assess the efficacy of antibiotic sutures in averting SSIs by amalgamating data from various meta-studies. MATERIALS AND METHODS: This research adhered to the PRISMA 2020 guidelines. The quality and comprehensiveness of the encompassed meta-analyses were assessed through the QUOROM checklist and AMSTAR techniques. The primary study overlap was evaluated via measures such as pairwise intersection heat maps, corrected covered area, and the citation matrix of evidence. The statistical power at the study-level was determined utilizing the meta-meta package. Data synthesis employed random and fixed effects models at a 95% CI. A meta-regression analysis was conducted to explore potential correlations between the CDC classification of SSIs, trial types, and the observed effect sizes in the studies. RESULTS: This investigation revealed a significant reduction in SSI rates due to antimicrobial-coated sutures, evidenced by a relative risk (RR) of 0.68 (95% CI: 0.59-0.76), with a prediction interval of 0.38-1.19. The analysis encompassed 18 studies with 22 meta-analyses, demonstrating a median QUOROM score of 13.6 out of 18 and an AMSTAR score of 9.1 out of 11. The presence of moderate heterogeneity was noted ( Q =106.611, I2 =54.038%), with nonrandomized controlled trials exhibiting an RR of 0.56 (95% CI: 0.39-0.80), and RCTs displaying an RR of 0.71 (95% CI: 0.63-0.81). Subgroup analysis unveiled variable RR reductions for specific surgical procedures. CONCLUSION: Antimicrobial-coated sutures offer a promising approach to mitigating SSIs risk. However, their efficacy is optimally realized when employed in conjunction with other robust practices.

Gut microbiota shifts favorably with delivery of handwashing with soap and water treatment intervention in a prospective cohort (CHoBI7 trial).

BACKGROUND: Cholera can result in the expulsion of important microbiota from the gut and result in death if left untreated. The disease transmits mainly via drinking water carrying Vibrio cholerae; and household contacts (HHC) of cholera patients are at elevated risk during the first week of infection. The gut microbiota profiles of HHC-children of cholera patients at Dhaka city slums were investigated before (day 0) and after (day 8) delivery of chlorinated water as part of the major study 'CHoBI7 trial (cholera-hospital-based intervention for 7 days)'. RESULT: Results of sequencing and analysis of bacterial community DNA revealed the predominance of two bacterial phyla: Bacteroidetes and Firmicutes at day 0 with a relative abundance of 62 ± 6 (mean ± SEM%) and 32 ± 7, respectively. The pattern reversed at day 8 with a decreased relative abundance of Bacteroidetes (39 ± 12; p = 0.034) and an increased abundance of Firmicutes (49 ± 12; p = 0.057). Of 65 bacterial families confirmed at day 0, six belonging to Proteobacteria including Vibrionaceae disappeared at day 8. Interestingly, the relative abundance of four Firmicutes families-Lachnospiraceae, Bifidobacteriaceae, Clostridiaceae, and Ruminococcaceae was increased in all five study children at day 8. CONCLUSION: The observed exclusion of pathogenic Proteobacteria and enhancement of beneficial Firmicutes in the gut of children delivered with chlorinated water as part of WASH intervention reflect a great promise of the CHoBI7 program in preventing cholera and improving child health.

Deep Learning Framework for Liver Segmentation from T1-Weighted MRI Images.

The human liver exhibits variable characteristics and anatomical information, which is often ambiguous in radiological images. Machine learning can be of great assistance in automatically segmenting the liver in radiological images, which can be further processed for computer-aided diagnosis. Magnetic resonance imaging (MRI) is preferred by clinicians for liver pathology diagnosis over volumetric abdominal computerized tomography (CT) scans, due to their superior representation of soft tissues. The convenience of Hounsfield unit (HoU) based preprocessing in CT scans is not available in MRI, making automatic segmentation challenging for MR images. This study investigates multiple state-of-the-art segmentation networks for liver segmentation from volumetric MRI images. Here, T1-weighted (in-phase) scans are investigated using expert-labeled liver masks from a public dataset of 20 patients (647 MR slices) from the Combined Healthy Abdominal Organ Segmentation grant challenge (CHAOS). The reason for using T1-weighted images is that it demonstrates brighter fat content, thus providing enhanced images for the segmentation task. Twenty-four different state-of-the-art segmentation networks with varying depths of dense, residual, and inception encoder and decoder backbones were investigated for the task. A novel cascaded network is proposed to segment axial liver slices. The proposed framework outperforms existing approaches reported in the literature for the liver segmentation task (on the same test set) with a dice similarity coefficient (DSC) score and intersect over union (IoU) of 95.15% and 92.10%, respectively.

Some common deleterious mutations are shared in SARS-CoV-2 genomes from deceased COVID-19 patients across continents.

The identification of deleterious mutations in different variants of SARS-CoV-2 and their roles in the morbidity of COVID-19 patients has yet to be thoroughly investigated. To unravel the spectrum of mutations and their effects within SARS-CoV-2 genomes, we analyzed 5,724 complete genomes from deceased COVID-19 patients sourced from the GISAID database. This analysis was conducted using the Nextstrain platform, applying a generalized time-reversible model for evolutionary phylogeny. These genomes were compared to the reference strain (hCoV-19/Wuhan/WIV04/2019) using MAFFT v7.470. Our findings revealed that SARS-CoV-2 genomes from deceased individuals belonged to 21 Nextstrain clades, with clade 20I (Alpha variant) being the most predominant, followed by clade 20H (Beta variant) and clade 20J (Gamma variant). The majority of SARS-CoV-2 genomes from deceased patients (33.4%) were sequenced in North America, while the lowest percentage (0.98%) came from Africa. The 'G' clade was dominant in the SARS-CoV-2 genomes of Asian, African, and North American regions, while the 'GRY' clade prevailed in Europe. In our analysis, we identified 35,799 nucleotide (NT) mutations throughout the genome, with the highest frequency (11,402 occurrences) found in the spike protein. Notably, we observed 4150 point-specific amino acid (AA) mutations in SARS-CoV-2 genomes, with D614G (20%) and N501Y (14%) identified as the top two deleterious mutations in the spike protein on a global scale. Furthermore, we detected five common deleterious AA mutations, including G18V, W45S, I33T, P30L, and Q418H, which play a key role in defining each clade of SARS-CoV-2. Our novel findings hold potential value for genomic surveillance, enabling the monitoring of the evolving pattern of SARS-CoV-2 infection, its emerging variants, and their impact on the development of effective vaccination and control strategies.

BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data.

Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge from the datasets collected from 930 COVID-19 patients hospitalized in Italy during the first wave of COVID-19 (March-June 2020). The dataset consists of twenty-five biomarkers from electronic health record and Chest X-ray (CXR) images. It is found that the system can diagnose low- or high-risk patients with an accuracy, sensitivity, and F1-score of 89.03%, 90.44%, and 89.03%, respectively. The system exhibits 6% higher accuracy than the systems that employ either CXR images or biomarker data. In addition, the system can calculate the mortality risk of high-risk patients using multivariate logistic regression-based nomogram scoring technique. Interested physicians can use the presented system to predict the early mortality risks of COVID-19 patients using the web-link: Covid-severity-grading-AI. In this case, a physician needs to input the following information: CXR image file, Lactate Dehydrogenase (LDH), Oxygen Saturation (O2%), White Blood Cells Count, C-reactive protein, and Age. This way, this study contributes to the management of COVID-19 patients by predicting early mortality risk. Supplementary Information: The online version contains supplementary material available at 10.1007/s00521-023-08606-w.

Genomic landscape of prominent XDR Acinetobacter clonal complexes from Dhaka, Bangladesh.

BACKGROUND: Acinetobacter calcoaceticus-A. baumannii (ACB) complex pathogens are known for their prevalence in nosocomial infections and extensive antimicrobial resistance (AMR) capabilities. While genomic studies worldwide have elucidated the genetic context of antibiotic resistance in major international clones (ICs) of clinical Acinetobacter spp., not much information is available from Bangladesh. In this study, we analysed the AMR profiles of 63 ACB complex strains collected from Dhaka, Bangladesh. Following this, we generated draft genomes of 15 of these strains to understand the prevalence and genomic environments of AMR, virulence and mobilization associated genes in different Acinetobacter clones. RESULTS: Around 84% (n = 53) of the strains were extensively drug resistant (XDR) with two showing pan-drug resistance. Draft genomes generated for 15 strains confirmed 14 to be A. baumannii while one was A. nosocomialis. Most A. baumannii genomes fell under three clonal complexes (CCs): the globally dominant CC1 and CC2, and CC10; one strain had a novel sequence type (ST). AMR phenotype-genotype agreement was observed and the genomes contained various beta-lactamase genes including blaOXA-23 (n = 12), blaOXA-66 (n = 6), and blaNDM-1 (n = 3). All genomes displayed roughly similar virulomes, however some virulence genes such as the Acinetobactin bauA and the type IV pilus gene pilA displayed high genetic variability. CC2 strains carried highest levels of plasmidic gene content and possessed conjugative elements carrying AMR genes, virulence factors and insertion sequences. CONCLUSION: This study presents the first comparative genomic analysis of XDR clinical Acinetobacter spp. from Bangladesh. It highlights the prevalence of different classes of beta-lactamases, mobilome-derived heterogeneity in genetic architecture and virulence gene variability in prominent Acinetobacter clonal complexes in the country. The findings of this study would be valuable in understanding the genomic epidemiology of A. baumannii clones and their association with closely related pathogenic species like A. nosocomialis in Bangladesh.

Draft-genome analysis provides insights into the virulence properties and genome plasticity of Vibrio fluvialis organisms isolated from shrimp farms and Turag river in Bangladesh.

Vibrio fluvialis is an opportunistic waterborne and seafood-borne enteric pathogen capable of causing severe diarrhea leading to death. This pathogen is endemic to Bangladesh, a country which is a major producer of cultured shrimp and wild-caught prawns. In this study, we carried out whole-genome sequencing of three V. fluvialis organisms isolated from shrimp farm and river sediment showing strong pathogenic characteristics in vivo and in vitro and compared their genomes against other V. fluvialis and related pathogenic species to glean insights into their potential as pathogens. Numerous virulence-associated genes including hemolysins, cytolysins, three separate Type IV pili, Types II and VI secretion systems, biofilm, and the V. cholerae pathogenesis regulating gene, toxR, were identified. Moreover, we found strain S-10 to have the propensity to acquire antibiotic resistance genes through horizontal gene transfer. These findings indicate that shrimp farms and rivers could be potential sources of V. fluvialis organisms which are an infection threat of public health concern.

Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities.

Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.

Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh.

We conducted a cluster-randomized trial to measure the effect of community-level mask distribution and promotion on symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in rural Bangladesh from November 2020 to April 2021 (N = 600 villages, N = 342,183 adults). We cross-randomized mask type (cloth versus surgical) and promotion strategies at the village and household level. Proper mask-wearing increased from 13.3% in the control group to 42.3% in the intervention arm (adjusted percentage point difference = 0.29; 95% confidence interval = [0.26, 0.31]). The intervention reduced symptomatic seroprevalence (adjusted prevalence ratio = 0.91 [0.82, 1.00]), especially among adults ≥60 years old in villages where surgical masks were distributed (adjusted prevalence ratio = 0.65 [0.45, 0.85]). Mask distribution with promotion was a scalable and effective method to reduce symptomatic SARS-CoV-2 infections.

High prevalence of multiple antibiotic resistance in clinical E. coli isolates from Bangladesh and prediction of molecular resistance determinants using WGS of an XDR isolate.

Multi-drug-resistance (MDR) is a severe public health concern worldwide, and its containment is more challenging in developing countries due to poor antimicrobial resistance (AMR) surveillance and irrational use of antibiotics. The current study investigated 100 clinical E. coli isolates and revealed that 98% of them were MDR. PCR analysis using 25 selected isolates showed the predominance of metallo-ß-lactamase gene blaNDM (80%) and ESBL genes blaOXA (48%) and blaCTX-M-15 (32%). The AmpC gene was detected in 68% of the isolates, while 32% was tetC positive. Notably, 34% of the isolates were resistant to carbapenem. Whole genome sequence (WGS) analysis of an extensively drug-resistant (XDR) isolate (L16) revealed the presence of the notorious sequence type 131 responsible for multi-drug-resistant infections, multiple antibiotic resistance genes (ARGs), virulence genes, and mobile genetic elements that pose risks to environmental transmission. Our results indicate that MDR is alarmingly increasing in Bangladesh that critically limits the treatment option against infections and contributes to further aggravation to the prevailing situation of MDR worldwide. The findings of this study will be valuable in designing sustainable strategies to contain MDR in the region.

Prevalence of SARS-CoV-2 in Communities Through Wastewater Surveillance-a Potential Approach for Estimation of Disease Burden.

The episodic outbreak of COVID-19 due to SARS-CoV-2 is severely affecting the economy, and the global count of infected patients is increasing. The actual number of patients had been underestimated due to limited facilities for testing as well as asymptomatic nature of the expression of COVID-19 on individual basis. Tragically, for emerging economies with high population density, the situation has been more complex due to insufficient testing facilities for diagnosis of the disease. However, the recent reports about persistent shedding of viral RNA of SARS-CoV-2 in the human feces have created a possibility to track the prevalence and trends of the disease in communities, known as wastewater-based epidemiology (WBE). In this article, we highlight the current limitations and future prospects for WBE to manage pandemics.

Leaf powder supplementation of Senna alexandrina ameliorates oxidative stress, inflammation, and hepatic steatosis in high-fat diet-fed obese rats.

Obesity is an enduring medical issue that has raised concerns around the world. Natural plant extracts have shown therapeutic potential in preventing oxidative stress and inflammation related to obesity complications. In this study, Senna alexandrina Mill. leaves were utilized to treat high-fat diet-related metabolic disorders and non-alcoholic fatty liver diseases. Plasma biochemical assays were conducted to determine the lipid profiles and oxidative stress parameters, and the gene expression of antioxidant enzymes and inflammatory mediators was measured. Histological stained livers of high-fat diet-fed rats were observed. S. alexandrina leaf powder supplementation prevented the increase in cholesterol and triglyceride levels in high-fat diet-fed rats. Moreover, S. alexandrina leaves also reduced lipid peroxidation and nitric oxide production in these rats. Prevention of oxidative stress by S. alexandrina leaf supplementation in high-fat diet-fed rats is regulated by enhancing the antioxidant enzyme activity, followed by the restoration of corresponding gene expressions, such as NRF-2, HO-1, SOD, and CAT. Histological staining provides further evidence that S. alexandrina leaf supplementation prevents inflammatory cell infiltration, lipid droplet deposition, and fibrosis in the liver of high-fat diet-fed rats. Furthermore, this investigation revealed that S. alexandrina leaf supplementation controlled non-alcoholic fatty liver disease by modulating the expression of fat metabolizing enzymes in high-fat diet-fed rats. Therefore, S. alexandrina leaf supplementation inhibits fatty liver inflammation and fibrosis, suggesting its usefulness in treating non-alcoholic steatohepatitis. Thus, this natural leaf extract has potential in treatment of obesity related liver dysfunction.

Whole genome mapping and identification of single nucleotide polymorphisms of four Bangladeshi individuals and their functional significance.

OBJECTIVE: The major objective of the study was to sequence the whole genome of four Bangladeshi individuals and identify variants that are known to be associated with functional changes or disease states. We also carried out an ontology analysis to identify the functions and pathways most likely to be affected by these variants. RESULTS: We identified around 900,000 common variants and close to 5 million unique ones in all four of the individuals. This included over 11,500 variants that caused nonsynonymous changes in proteins. Heart function associated pathways were heavily implicated by the ontology analysis; corroborating previous studies that claimed the Bangladeshi population as highly susceptible to heart disorders. Two variants were found that have been previously identified as pathogenic factors in familial hypercholesteremia and structural disorders of the heart. Other pathogenic variants we found were associated with pseudoxanthoma elasticum, cancer progression, polyagglutinable erythrocyte syndrome, preeclampsia, and others.

First detection of SARS-CoV-2 genetic material in the vicinity of COVID-19 isolation Centre in Bangladesh: Variation along the sewer network.

We made the first and successful attempt to detect SARS-CoV-2 genetic material in the vicinity wastewaters of an isolation centre i.e. Shaheed Bhulu Stadium, situated at Noakhali, Southeastern Bangladesh. Owing to the fact that isolation centre, in general, always contained a constant number of 200 COVID-19 patients, the prime objective of the study was to check if several drains carrying RNA of coronavirus are actually getting diluted or accumulated along with the sewage network. Our finding suggested that while the temporal variation of the genetic load decreased in small drains over the span of 50 days, the main sewer exhibited accumulation of SARS-CoV-2 RNA. Other interesting finding displays that probably distance of sampling location in meters is not likely to have a significant impact on the detected gene concentration, although the quantity of the RNA extracted in the downstream of the drain was higher. These findings are of immense value from the perspective of wastewater surveillance of COVID-19, as they largely imply that we do not need to monitor every wastewater system, and probably major drains monitoring may illustrate the city health. Perhaps, we are reporting the accumulation of SARS-CoV-2 genetic material along with the sewer network i.e. from primary to tertiary drains. The study sought further data collection in this line to simulate conditions prevailed in most of the developing countries and to shed further light on decay/accumulation processes of the genetic load of the SARS-COV-2.

Coding-Complete Genome Sequences of Three SARS-CoV-2 Strains from Bangladesh.

We report the sequencing of three severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Bangladesh. We have identified a unique mutation (NSP2_V480I) in one of the sequenced genomes (isolate hCoV-19/Bangladesh/BCSIR-NILMRC-006/2020) compared to the sequences available in the Global Initiative on Sharing All Influenza Data (GISAID) database. The data from this analysis will contribute to advancing our understanding of the epidemiology of SARS-CoV-2 in Bangladesh as well as worldwide at the molecular level and will identify potential new targets for interventions.

Genotype-phenotype correlation of ß-lactamase-producing uropathogenic Escherichia coli (UPEC) strains from Bangladesh.

Escherichia coli is a pathogen commonly encountered in clinical laboratories, and is capable of causing a variety of diseases, both within the intestinal tract (intestinal pathogenic strains) and outside (extraintestinal pathogenic E. coli, or ExPEC). It is associated with urinary tract infections (UTIs), one of the most common infectious diseases in the world. This report represents the first comparative analysis of the draft genome sequences of 11 uropathogenic E. coli (UPEC) strains isolated from two tertiary hospitals located in Dhaka and Sylhet, Bangladesh, and is focused on comparing their genomic characteristics to each other and to other available UPEC strains. Multilocus sequence typing (MLST) confirmed the strains belong to ST59, ST131, ST219, ST361, ST410, ST448 and ST4204, with one of the isolates classified as a previously undocumented ST. De novo identification of the antibiotic resistance genes blaNDM-5, blaNDM-7, blaCTX-M-15 and blaOXA-1 was determined, and phenotypic-genotypic analysis of virulence revealed significant heterogeneity within UPEC phylogroups.

Draft Genome Sequence of Bacillus cereus TN10, a Chromium-Resistant and -Reducing Strain Isolated from Tannery Effluent.

Here, we present the draft genome sequence of Bacillus cereus strain TN10, which exhibited chromium resistance and chromium-reducing ability. The whole-genome sequence analysis of strain TN10 will help us to understand its genetic factors involved in the bioremediation of Cr6.