iPromoter-FSEn: Identification of bacterial σ70 promoter sequences using feature subspace based ensemble classifier.

Sigma promoter sequences in bacterial genomes are important due to their role in transcription initiation. Sigma 70 is one of the most important and crucial sigma factors. In this paper, we address the problem of identification of σ70 promoter sequences in bacterial genome. We propose iPromoter-FSEn, a novel predictor for identification of σ70 promoter sequences. Our proposed method is based on a feature subspace based ensemble classifier. A large set of of features extracted from the sequence of nucleotides are divided into subsets and each subset is given to individual single classifiers to learn. Based on the decisions of the ensemble an aggregate decision is made by the ensemble voting classifier. We tested our method on a standard benchmark dataset extracted from experimentally validated results. Experimental results shows that iPromoter-FSEn significantly improves over the state-of-the art σ70 promoter sequence predictors. The accuracy and area under receiver operating characteristic curve of iPromoter-FSEn are 86.32% and 0.9319 respectively. We have also made our method readily available for use as an web application from: http://ipromoterfsen.pythonanywhere.com/server.

iPro70-FMWin: identifying Sigma70 promoters using multiple windowing and minimal features.

In bacterial DNA, there are specific sequences of nucleotides called promoters that can bind to the RNA polymerase. Sigma70 ([Formula: see text]) is one of the most important promoter sequences due to its presence in most of the DNA regulatory functions. In this paper, we identify the most effective and optimal sequence-based features for prediction of [Formula: see text] promoter sequences in a bacterial genome. We used both short-range and long-range DNA sequences in our proposed method. A very small number of effective features are selected from a large number of the extracted features using multi-window of different sizes within the DNA sequences. We call our prediction method iPro70-FMWin and made it freely accessible online via a web application established at http://ipro70.pythonanywhere.com/server for the sake of convenience of the researchers. We have tested our method using a standard benchmark dataset. In the experiments, iPro70-FMWin has achieved an area under the curve of the receiver operating characteristic and accuracy of 0.959 and 90.57%, respectively, which significantly outperforms the state-of-the-art predictors.

Characterization of a new isolate of pepper chlorotic spot virus from Yunnan province, China.

A new isolate, 14YV733, of pepper chlorotic spot virus (PCSV) from chili peppers in Yunnan province of China was identified. The typical tospoviral particles of 80-120 nm in diameter were observed by electron microscopy. The virus caused systemic symptoms in several solanaceous plants and the Brassica rapa L. Chinensis group with mechanical inoculation. The sap from infected leaves reacted positively to a rabbit antibody to the N protein of watermelon silver mottle virus (WSMoV) in immunoblotting. The S, M, and L RNAs of PCSV-14YV733 are 3310 nts, 4711 nts, and 8913 nts long, respectively. This is the first report of complete sequences of PCSV in mainland China. Phylogenetic analysis of all tospoviral proteins indicated that PCSV-14YV733 is closely related to members of the WSMoV serogroup.

Bovine and Caprine Brucellosis in Bangladesh: Bayesian evaluation of four serological tests, true prevalence, and associated risk factors in household animals.

A cross-sectional study was carried out to estimate the true prevalence of Brucella spp. and identify allied risk factors/indicators associated with brucellosis in the Dinajpur and Mymensingh districts of Bangladesh. A total 320 stratified random blood samples were collected and tested in parallel for Brucella antibodies using Rose Bengal (RBT), slow agglutination (SAT), and indirect and competitive ELISA. In addition, a structured questionnaire was administered to each household herd owner to gather information regarding potential risk factors. Both univariate and multivariate logistic regression analyses were used to identify potential risk factors or indicators at animal level. A Bayesian approach was used to estimate the true prevalence of brucellosis along with the test performances (Se and Sp). The estimated animal level true prevalence in cattle was 9.70 % (95 % CPI 5.0-16 %) and in goat 6.3 % (95 % CPI 2.8-11.0 %). The highest sensitivity was achieved by SAT ranges from 69.6 to 78.9 %, and iELISA was found to be more specific (97.4 to 98.8 %) in comparison with other tests. On the other hand, a significant level of (P < 0.05) Brucella seropositivity was found in cattle that breed naturally compared with those that undergo artificial insemination. In goats, exotic breeds were significantly associated (P < 0.05) with Brucella seroprevalence compared with indigenous breeds. Goats with a previous records of abortion and/or retained placenta were also found to have significant levels (P < 0.05). Cows with previous abortion records showed higher odds (18 times) of being seropositive. None of the evaluated tests can be recommended to apply alone for the diagnosis of bovine and caprine brucellosis.

Identification of medicinal plant-based phytochemicals as a potential inhibitor for SARS-CoV-2 main protease (Mpro) using molecular docking and deep learning methods.

Highly transmissive and rapidly evolving Coronavirus disease-2019 (COVID-19), a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), triggered a global pandemic, which is one of the most researched viruses in the academia. Effective drugs to treat people with COVID-19 have yet to be developed to reduce mortality and transmission. Studies on the SARS-CoV-2 virus identified that its main protease (Mpro) might be a potential therapeutic target for drug development, as this enzyme plays a key role in viral replication. In search of potential inhibitors of Mpro, we developed a phytochemical library consisting of 2431 phytochemicals from 104 Korean medicinal plants that exhibited medicinal and antioxidant properties. The library was screened by molecular docking, followed by revalidation by re-screening with a deep learning method. Recurrent Neural Networks (RNN) computing system was used to develop an inhibitory predictive model using SARS coronavirus Mpro dataset. It was deployed to screen the top 12 compounds based on their docked binding affinity that ranged from -8.0 to -8.9 kcal/mol. The top two lead compounds, Catechin gallate and Quercetin 3-O-malonylglucoside, were selected depending on inhibitory potency against Mpro. Interactions with the target protein active sites, including His41, Met49, Cys145, Met165, and Thr190 were also examined. Molecular dynamics simulation was performed to analyze root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (RG), solvent accessible surface area (SASA), and number of hydrogen bonds. Results confirmed the inflexible nature of the docked complexes. Absorption, distribution, metabolism, excretion, and toxicity (ADMET), as well as bioactivity prediction confirmed the pharmaceutical activities of the lead compound. Findings of this research might help scientists to optimize compatible drugs for the treatment of COVID-19 patients.

Identification, molecular characterization and phylogenetic analysis of a novel nucleorhabdovirus infecting Paris polyphylla var. yunnanensis.

A novel betanucleorhabdovirus infecting Paris polyphylla var. yunnanensis, tentatively named Paris yunnanensis rhabdovirus 1 (PyRV1), was recently identified in Yunnan Province, China. The infected plants showed vein clearing and leaf crinkle at early stage of infection, followed by leaf yellowing and necrosis. Enveloped bacilliform particles were observed using electron microscopy. The virus was mechanically transmissible to Nicotiana bethamiana and N. glutinosa. The complete genome of PyRV1 consists of 13,509 nucleotides, the organization of which was typical of rhabdoviruses, containing six open reading frames encoding proteins N-P-P3-M-G-L on the anti-sense strand, separated by conserved intergenic regions and flanked by complementary 3'-leader and 5'-trailer sequences. The genome of PyRV1 shared highest nucleotide sequence identity (55.1%) with Sonchus yellow net virus (SYNV), and the N, P, P3, M, G, and L proteins showed 56.9%, 37.2%, 38.4%, 41.8%, 56.7%, and 49.4% amino acid sequence identities with respective proteins of SYNV, suggesting RyRV1 belongs to a new species of the genus Betanucleorhabdovirus.

Microbial Contamination and Antibiotic Resistance in Marketed Food in Bangladesh: Current Situation and Possible Improvements.

Antimicrobial resistance (AMR) is a public health problem worldwide. Bangladesh, like its neighboring countries, faces many public health challenges, including access to safe food, inadequate food surveillance, as well as increasing AMR. This study investigated bacterial contamination and the AMR profile of pathogens in marketed food in Bangladesh and explored barriers to reducing AMR in the country. We collected 366 tomatoes, 359 chicken and 249 fish samples from 732 vendors in traditional markets in urban, peri-urban and rural areas in Bangladesh, as well as from 121 modern retails in Dhaka capital to analyse Vibrio cholerae and Escherichia coli in fish, Salmonella in chicken, and Salmonella and E. coli in tomatoes. Antibiotic susceptibility against 11 antibiotics was tested using a disc diffusion test and interpreted by an automated zone inhibition reader. In addition, a qualitative study using key informant interviews was conducted to explore antimicrobial use and AMR reduction potential in Bangladesh. We found E. coli in 14.21% of tomatoes and 26.91% of fish samples, while 7.38% of tomatoes and 17.27% of chicken were positive for Salmonella, and 44.98% of fish were positive for Vibrio cholerae. In total 231/319 (72.4%) of all pathogens isolated were multidrug-resistant (MDR) (resistant to three or more antibiotic groups). Qualitative interviews revealed an inadequate surveillance system for antibiotic use and AMR in Bangladesh, especially in the agriculture sector. To be able to fully understand the human health risks from bacterial hazards in the food and the AMR situation in Bangladesh, a nationwide study with a one health approach should be conducted, within all sectors, including AMR testing as well as assessment of the antimicrobial use and its drivers.

Standard feeding strategies with natural insemination improved fertility in repeat breeding dairy cows.

OBJECTIVE: The experiment was designed to establish suitable management strategies through the different feeding and breeding approaches on fertility improvement in the experimental repeat breeding (RB) cows. MATERIALS AND METHODS: 80 RB cows were selected for this experiment. Before grouping, all cows were deworming and then divided into four equal groups, namely Group-TF1 [traditional feeding practice and natural insemination (NI)], Group-TF2 [traditional feeding practice and Artificial insemination (AI)], Group-SF1 [standard (STD) feeding practice and NI], and Group-SF2 (STD feeding practice and AI). These allocated RB cows were fed by traditional and STD feeding methods for 90 days and then inseminated by AI and NI breeding systems. The dominant follicle (DF) diameter, hemato-biochemical elements, and estrogen (E2) hormone were estimated during the insemination of cows. Estimation of the pregnancy rate was carried out at days 45-90 post-insemination in the cows. RESULTS: The pregnancy rate was significantly (p < 0.05) higher in STD feeding practice with NI when compared to traditional feeding practice irrespective of breeding systems, and it was also significantly (p < 0.05) higher in NI than in AI breeding system, irrespective of feeding strategies. The results also showed that the diameter of DF, serum E2, total erythrocyte count, hemoglobin, packed cell volume, total cholesterol, total protein, glucose, calcium, phosphorus, ferric iron, copper, zinc, and magnesium at the time of insemination were significantly (p < 0.01) elevated in the experimental RB cows with STD feeding practice. The diameter of DF and serum E2 were significant (p < 0.01) and positively correlated with all hemato-biochemical elements in the cows at the time of insemination. CONCLUSION: The results suggest that NI with STD feeding practice may increase fertility in RB cows by improving general health status. Finally, it could support the veterinarians and researchers to define the management strategies using feeding and breeding strategies to prevent repeat breeding syndrome in dairy cows.

How air quality and COVID-19 transmission change under different lockdown scenarios? A case from Dhaka city, Bangladesh.

The transmission of novel coronavirus (COVID-19) can be reduced by implementing a lockdown policy, which has also been proven as an effective control measure for air pollution in the urban cities. In this study, we applied ground- and satellite-based data of five criteria air pollutants (PM2.5, NO2, SO2, O3, and CO) and meteorological factors from March 8 to May 15, 2020 (before, partial-, and full-lockdown). The generalized additive models (GAMs), wavelet coherence, and random forest (RF) model were employed to explore the relationship between air quality indicators and COVID-19 transmission in Dhaka city. Results show that overall, 26, 20.4, 17.5, 9.7 and 8.8% declined in PM 2.5, NO2, SO2, O3, and CO concentrations, respectively, in Dhaka City during the partial and full lockdown compared to the period before the lockdown. The implementation of lockdown policy for containing COVID-19 transmission played a crucial role in reducing air pollution. The findings of wavelet coherence and partial wavelet coherence demonstrate no standalone coherence, but interestingly, multiple wavelet coherence indicated a strong short-term coherence among air pollutants and meteorological factors with the COVID-19 outbreak. Outcomes of GAMs indicated that an increase of 1-unit in long-term exposure to O3 and CO (lag1) was associated with a 2.9% (95% CI: -0.3%, -5.6%), and 53.9% (95% CI: 0.2%, -107.9%) decreased risk of COVID-19 infection rate during the full-lockdown period. Whereas, COVID-19 infection and MT (mean temperature) are modulated by a peak during full-lockdown, which is mostly attributed to contact transmission in Dhaka city. RF model revealed among the parameters being studied, MT, RH (relative humidity), and O3 were the dominant factors that could be associated with COVID-19 cases during the study period. The outcomes reported here could elucidate the effectiveness of lockdown scenarios for COVID-19 containment and air pollution control in Dhaka city.

Are precipitation concentration and intensity changing in Bangladesh overtimes? Analysis of the possible causes of changes in precipitation systems.

A comprehensive understanding of the changing behaviors of precipitation concentration and intensity plays a pivotal role in water resource management. Hence, we investigated the spatiotemporal changing behaviors of frequency and intensity of 13 precipitation indices and their probable causes of changes in precipitation systems. This study used daily precipitation datasets from 23 sites in Bangladesh and six atmospheric circulation indices during 1975-2017. The results showed that the precipitation concentration index (LCI) varies between 0.57 and 0.63, and the highest value was found in the southeastern region. The precipitation days frequency indices such as AD, LPD, MPD, HPD, and WPD have significantly increased in Bangladesh while precipitation intensity indices such as AII, LPI, MPI, HPI, and WPI have significantly declined; all types of indices have clear rapid changes. The results of detrended fluctuation analysis (DFA) exhibit long-term correlations among all precipitation indices, suggesting that these indices will sustain their present trend line in the upcoming period. The Sunspot (SS) and East Asian Summer Monsoon Index (EASMI) had a negative influence on ACI and South Asian Summer Monsoon index (SASMI) had a strong positive influence on precipitation days frequency indices. The significance analysis using the random forest (RF) algorithm showed that SS is the largest contributing factor affecting the precipitation systems in Bangladesh. ECMWF ERA5 reanalysis datasets revealed that elevating summer geopotential height, higher anticyclonic anomaly, increasing low and decreasing high cloud covers and lower solar radiation with adequate moisture divergence fluxes contributed to variations in precipitation extremes in Bangladesh.

Non-Caloric Artificial Sweeteners Modulate the Expression of Key Metabolic Genes in the Omnipresent Gut Microbe Escherichia coli.

The human gut is inhabited by several hundred different bacterial species. These bacteria are closely associated with our health and well-being. The composition of these diverse commensals is influenced by our dietary intakes. Non-caloric artificial sweeteners (NAS) have gained global popularity, particularly among diabetic patients, due to their perceived health benefits, such as reduction of body weight and maintenance of blood glucose level compared to caloric sugars. Recent studies have reported that these artificial sweeteners can alter the composition of gut microbiota and, thus, affect our normal physiological state. Here, we investigated the effect of aspartame and acesulfame potassium (ace-K), two popular NAS, in a commercial formulation on the growth and metabolic pathways of omnipresent gut commensal Escherichia coliby analyzing the relative expression levels of the key genes, which control over twenty important metabolic pathways. Treatment with NAS preparation (aspartame and ace-K) modulates the growth of E. colias well as inducing the expression of important metabolic genes associated with glucose (pfkA, sucA, aceE, pfkB, lpdA), nucleotide (tmk, adk, tdk, thyA), and fatty acid (fabI) metabolisms, among others. Several of the affected geneswere previously reported to be important for the colonization of the microbes in the gut. These findings may shed light on the mechanism of alteration of gut microbes and their metabolism by NAS.