Inhibition of biofilm formation, quorum sensing and other virulence factors in Pseudomonas aeruginosa by polyphenols of Gynura procumbens leaves
Quorum sensing (QS) regulates bacterial biofilm formation that can lead to chronic and persistent infections. In addition, treatments become difficult since bacteria reside in a biofilm are more antibiotic resistant. In this study, we aimed to investigate the anti-biofilm potency of Gynura procumbens leaves along with the underlying mechanism and characterization of target compound(s). Briefly, the ethanolic leaf extract showed significant antibiofilm activity (P≤0.05) against P. aeruginosa strain MZ2F and MZ4A. Besides, the minimum biofilm eradication concentration was recorded at 250 and 500 μg/ml while total activity was found at 288 and 144 ml/g for strain MZ2F and MZ4A, respectively. Furthermore, the extract was able to reduce the swarming motility (P≤0.005), pigment production, and activity of LasA as well as Rhl system (P≤0.05) significantly in both strains without affecting their growth implying an anti-QS strategy. Initially, the anti-QS compounds were tentatively characterized as flavonoids and phenols. Then, we applied computational methods to identify the target compounds. Thus, two (2) polyphenols (i.e., quercetin and myricetin) out of 33 reported compounds were identified as the potent anti-QS agents. Quercetin and myricetin provided -10.09 and 9.77 kcal/mol of binding affinity, respectively as compared to -8.97 kcal/mol of the control. Besides, the binding free energy (ΔG) of quercetin and myricetin (-71.56 to -74.88 kcal/mol) was lower than the rest. Moreover, dynamics simulation indicates strong and stable interactions of the ligand-bound LasR complexes. Finally, ADMET analysis revealed their suitability as drug candidates. These results altogether support the antibiofilm activity of G. procumbens leaves in which the identified polyphenols could play a vital role in developing QS-based therapeutics. Nevertheless, experimental validation of the in silico part is warranted to confirm our findings.
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Mycoremediation of Reactive Red Dye by Highly Potential Fungal Strain Isolated from Textile Effluents
Besides the detrimental impacts on the aquatic ecosystem, fabric colorants often have a hazardous effect on human health. These problems are more serious in Bangladesh, one of the largest exporters of apparel. Biodegradation of fabric colorants by microorganisms is a prospective and sustainable approach over the conventional physio-chemical methods and fungi mediated mycoremediation is also a significant decontamination approach of these dyes. This study aimed to isolate potential fungal strains from textile effluent that are capable of degrading reactive red (RR) dye, a widely used dye in local thread dyeing industries. Dye degradation assay was performed in potato dextrose broth supplemented with 50 mg/l RR dye by inoculating different fungal strains. A photo-electric-colorimeter was used to analyze the decolorizing potentiality of fungal strains after aerobic incubation under static conditions. For molecular characterization and identification, the PCR product has been performed for partial sequencing. Primarily, six fungal strains were isolated and one strain (TEF-3) exhibited 97.41% degradation of RR dye at a concentration of 50 mg/l after 96 h of incubation. Thus, this fungus has the prospectiveness to be utilized in the textile wastewater treatment plant.
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Pathophysiological Impact of COVID-19 on Different Comorbidities and Vice-Versa
[Currently Under-review]
Despite the fact that the prevalent health conditions may increase the COVID-19 severity, the disease-modifying biomolecules and their pathogenic mechanisms remain unclear. In this study, we aimed to understand the influences of COVID-19 on different comorbidities by employing global RNA-Seq data and expression microarrays. Using the shared dysregulated genes, we identified key biomarkers and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6, and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction (MI), and hypertension (HT), respectively. Notably, COVID-19 shared three upregulated genes (i.e., MX2, IRF7, and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e., PPARGC1A and METTL7A) was found in COVID-19 and LC. In addition, majority of their shared pathways were related to inflammatory responses. Furthermore, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. These molecular determinants and checkpoints might be useful to understand the diseases and as effective drug targets.
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Antibiograms of Multidrug-resistant Acinetobacter
baumannii Isolated from Specimens at Kushtia Medical
College Hospital
[Bachelor's Micro-thesis]
Acinetobacter baumannii is an opportunistic, hospital dwelling pathogen which is responsible for hospital-acquired infections like Ventilator-associated pneumonia (VAP), several respiratory and urinary tract infections, meningitis, wound sepsis and numerous skin/soft tissue infections (SSTIs). The emergence of this notorious bacteria is profoundly observed by recent outbreaks throughout the world. The dominance of this pathogen thrives over the healthcare units, because of its ability to resist every existing first-line antibiotics, reminding the fear of the preantibiotic era to the world. The aim of this study was to isolate and identify A. baumannii from clinical samples and to determine their antimicrobial resistance pattern to commonly prescribed drugs to find out multidrug-resistant A. baumannii (MDRAB). Four different samples were collected from Kushtia Medical College Hospital. A. baumannii was isolated and identified based on their growth, physiological, and biochemical characteristics. Their antibiograms were studied through standard disk diffusion method, and antibiotic susceptibility patterns were interpreted. Ceftriaxone, ciprofloxacin, erythromycin, imipenem and colistin were used to evaluate the sensitivity of the isolates. Out of four specimens, the pathogen was recovered from hospital drain water, hospital dust and urine sample. Though the isolates showed similar growth and physiological characteristics along with similar biochemical profiles, they differ considerably in their sensitivity against several antibiotics. The least resistance showing antibiotic was colistin (22%) and then imipenem (33%). Aside from isolate DW04, HD19, HD20, HD24, all isolates found multidrug-resistant (resistant to ≥ 3 antibiotics group). The recovery of MDRAB, including imipenem-resistant A. baumannii from different clinical specimens, and their antibiotic resistance pattern hint emergence of a formidable pathogen of nosocomial origin. The findings of the study seek up-gradation of current patient maintenance practices in healthcare units of our country to limit the prevalence of antibiotic-resistant A. baumannii.
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Exploring Lassa Virus Proteome to Design a Multi‑epitope Vaccine Through Immunoinformatics and Immune Simulation Analyses
Lassa virus (LASV) is responsible for a type of acute viral haemorrhagic fever referred to as Lassa fever. Lack of adequate treatment and preventive measures against LASV resulted in a high mortality rate in its endemic regions. In this study, a multi-epitope vaccine was designed using immunoinformatics as a prophylactic agent against the virus. Following a rigorous assessment, the vaccine was built using T-cell (NCTL = 8 and NHTL = 6) and B-cell (NLBL = 4) epitopes from each LASV-derived protein in addition with suitable linkers and adjuvant. The physicochemistry, immunogenic potency and safeness of the designed vaccine (~ 68 kDa) were assessed. In addition, chosen CTL and HTL epitopes of our vaccine showed 97.37% worldwide population coverage. Besides, disulphide engineering also improved the stability of the chimeric vaccine. Molecular docking of our vaccine protein with toll-like receptor 2 (TLR2) showed binding efficiency followed by dynamics simulation for stable interaction. Furthermore, higher levels of cell-mediated immunity and rapid antigen clearance were suggested by immune simulation and repeated-exposure simulation, respectively. Finally, the optimized codons were used in in silico cloning to ensure higher expression within E. coli K12 bacterium. With further assessment both in vitro and in Vivo, we believe that our proposed peptide-vaccine would be potential immunogen against Lassa fever.
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Energy-optimized pharmacophore coupled virtual screening in the discovery of quorum sensing inhibitors of LasR protein of Pseudomonas aeruginosa
Pseudomonas aeruginosa is an emerging opportunistic pathogen responsible for cystic fibrosis and nosocomial infections. In addition, empirical treatments are become inefficient due to their multipleantibiotic resistance and extensive colonizing ability. Quorum sensing (QS) plays a vital role in the regulation of virulence factors in P. aeruginosa. Therefore, attenuation of virulence by QS inhibition could be an alternative and effective approach to control the infections. In this study, we sought to discover new QS inhibitors (QSIs) against LasR receptor in P. aeruginosa using chemoinformatics. Initially, a structure-based high-throughput virtual screening was performed using the LasR active site that identified 61404 relevant molecules. The e-pharmacophore (ADAHH) screening of these molecules rendered 72 QSI candidates. In standard-precision docking, only 7 compounds were found as potential QSIs based on their higher binding affinity to LasR receptor (7.53 to 10.32 kcal/mol compared to 7.43 kcal/mol of native ligand). The ADMET properties of these compounds were suitable to be QSIs. Later, extra-precision docking and binding energy calculation suggested ZINC19765885 and ZINC72387263 as the most promising QSIs. The dynamic simulation of the docked complexes showed stable binding affinity and molecular interactions. The current study suggested that these two compounds could be used in P. aeruginosa QS inhibition to combat bacterial infections.
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Computational formulation and immune dynamics of a multi-peptide vaccine candidate against Crimean-Congo hemorrhagic fever virus
The objective of this research is to build an efficient multi epitope-based vaccine as an immune modulator for Crimean-Congo Hemorrhagic Fever Virus using a computer-based vaccine design strategy. Acute outbreaks have recently increased in several countries. Mortality rates increase up to 80% due to the lack of prospective medication and an efficient vaccine. We have used several immunoinformatic tools and servers to predict potent B-cell and T-cell epitopes from the highest antigenic glycoprotein. The effectiveness of our vaccine in terms of stability, solubility, coverage of the population, molecular docking, dynamic and immune simulation, codon adaptation and in silico cloning was also been explored. After a comprehensive evaluation, the final vaccine was built using 6 CTL, 3 HTL and 7 LBL epitopes along with specific adjuvant and linkers. It contains a total of 468 amino acid residues. To enhance the reaction of our immune system, we used the Mycobacterium tuberculosis lipoprotein LprG (Rv1411c) as an adjuvant. By using the I-TASSER server we visualized the 3D structure. We also predicted the binding affinity of the vaccine-TLR2 receptor complex through molecular docking studies. In addition, higher levels of cell-mediated immunity and rapid clearance of antigen were identified by the immune simulation and repetitive exposure simulation. Finally, in silicon cloning, the optimized codons were used to ensure higher expression in E.coli K12 bacterium. Collectively, this study proposes a superior multiepitope based peptide vaccine against CCHFV which should be taken under consideration of both in vivo and in vitro analysis.
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Proteome-wide screening for designing a multiepitope vaccine against emerging pathogen Elizabethkingia anophelis using immunoinformatic approaches
Elizabethkingia anophelis is an emerging human pathogen causing neonatal meningitis, catheter-associated infections and nosocomial outbreaks with high mortality rates. Besides, they are resistant to most antibiotics used in empirical therapy. In this study, therefore, we used immunoinformatic approaches to design a prophylactic peptide vaccine against E. anophelis as an alternative preventive measure. Initially, cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were predicted from the highest antigenic protein. The CTL and HTL epitopes together had a population coverage of 99.97% around the world. Eventually, six CTL, seven HTL, and two LBL epitopes were selected and used to construct a multi-epitope vaccine. The vaccine protein was found to be highly immunogenic, non-allergenic, and non-toxic. Codon adaptation and in silico cloning were performed to ensure better expression within E. coli K12 host system. The stability of the vaccine structure was also improved by disulphide bridging. In addition, molecular docking and dynamics simulation revealed strong and stable binding affinity between the vaccine and toll-like receptor 4 (TLR4) molecule. The immune simulation showed higher levels of T-cell and B-cell activities which was in coherence with actual immune response. Repeated exposure simulation resulted in higher clonal selection and faster antigen clearance. Nevertheless, experimental validation is required to ensure the immunogenic potency and safety of this vaccine to control E. anophelis infection in the future.
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A comprehensive screening of the whole proteome of hantavirus and designing a multi-epitope subunit vaccine for cross-protection against hantavirus: Structural vaccinology and immunoinformatics study
Hantaviruses are a newly zoonotic emerging group of rodent-borne viruses that have a significant impact on global public health by increasing amplitude and magnitude of outbreaks. As no permanent cure yet, it is now growing and challenging interest to develop a vaccine against Hantavirus. This study endeavored to design a robust subunit vaccine using a novel immunoinformatics approach. After meticulous evaluation, top ones from predicted CTL, HTL, and B-cell epitopes were considered as potential vaccine candidates. Among generated four vaccine models with different adjuvant, the model with TLR-4 agonist adjuvant was selected for its high antigenicity, non-allergenicity, and structural quality. The conformational B-cell epitope prediction assured its humoral response inducing ability. Thereafter, the molecular docking and dynamics simulation confirmed a good binding affinity with immune receptor TLR-4 and stability of the vaccine-receptor complex. In immune simulation, significantly high levels of IgM and IgG1 immunoglobulins, TC and TH-cell populations, and various cytokines (i.e. IFN-γ, IL-2 etc.) are coherence with actual immune response and also showed faster antigen clearance for repeated exposures. Finally, disulfide engineering enhanced vaccine stability and in silico cloning confirmed the better expression in E. coli K12. Nonetheless, experimental validation can proof the proposed vaccine’s safety and ability to control Hantavirus infection.
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Combined Bioinformatics Approach to Annotate the Structural and Functional Association of the Hypothetical Proteins of S. maltophilia K279a and Predict Potential T and B Cell Targets for Vaccination
[Currently Under-review]
Stenotrophomonas maltophilia is a multidrug-resistant bacterium with no precise clinical
treatment. This bacterium can be of vital cause for death and different organ failures in immunocompromised, immune-competent, and long-time hospitalized patients. Extensive quorum sensing capability has become a challenge to develop new drugs against this pathogen. Moreover, the organism possesses about 789 proteins which function, structure, and pathogenesis remain obscured. In this piece of work, we tried to enlighten the aforementioned sectors using highly reliable bioinformatics tools validated by the scientific community. At first, the whole proteome sequence of the organism was retrieved and stored. Then we separated the hypothetical proteins and searched for the conserved domain with high confidence level and multi-server validation, which resulted in 24 such proteins. Furthermore, all of their physical and chemical characterizations were performed, such as theoretical isoelectric point, molecular weight, GRAVY value, and many more. Besides, the subcellular localization, protein-protein interactions, functional motifs, 3D structures, antigenicity, and virulence factors were also evaluated. As an extension of this work, 'RTFAMSSER' and 'PAAPQPSAS' were predicted as potential T and B cell epitopes, respectively. We hope our findings will help in better understating of the pathogenesis and smoothen the way to the cure.
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Major Nutritional Constituents and Genetic Diversity Analysis of Different Strains of Oyster Mushrooms
Oyster mushroom is the second runner up of commercially produced mushrooms in the world due to its delicious taste, higher nutritional properties and medicinal importance. The objectives of this study were to determine the nutritional value and to assess the genetic variation of five different strains of oyster mushrooms, namely Pleurotus cystidiosus (strain pcys2); Pleurotus djamor (strain pop1); Pleurotus ostreatus (strain ws); Pleurotus ostreatus (strain po3) and Pleurotus geesteranus (strain pg4). Therefore, carbohydrate, protein, fat, fiber, ash and moisture contents were determined through standard method where DNA extraction and purification of different strains were done through universal and rapid salt extraction method with some modifications and genetic variation was measured through Random Amplified Polymorphic DNA
(RAPD) analysis. The highest moisture, protein, fiber, lipid, ash and carbohydrate content were observed in P. djamor (87.33%), P. ostreatus (24.13%), P. ostreatus (25.46%), P. cystidiosus (5.16%), P. ostreatus (11.46%) and P. djamor (45.33%) respectively. In the case of genetic diversity studies, the maximum and minimum polymorphism were assessed 93.75% and 78.94% where the primer OPA-03 and OPG-04 were used respectively. The segregation of five strains of oyster mushrooms were grouped through unweighted pair group method of arithmetic means average (UPGMA), where the strains were grouped into two main clusters and the generated linkage distance was 48. The strains P. djamor (pop1) and P. ostreatus (po3) were aligned in cluster two (C2) due to their genetic similarity but showed dissimilarities with other strains. Though the strains P. cystidiosus (pcys2), P. ostreatus (ws) and P. geesteranus (pg4) were aligned in the same cluster (C1), the strain P. ostreatus (ws) was aligned in a different sub-cluster due to its few dissimilarities with the other two strains. The variation of nutritional values and genetic diversities among the mushroom strains indicates nutritional and genetic variabilities. These findings would help mushroom breeders for designing and selecting the strains of Oyster mushrooms to achieve the specific goal of nutritionally enriched mushroom production.
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