Degradation of Plastic Beads Containing Low Density Polyethylene (LDPE) by Sequential Photolysis, Hydrolysis and Bacterial Isolates.

Plastic is an important part of today's human daily lifestyle, and it is classified as a "global pollutant" due to its durability. The natural degradation of plastic is extremely slow and will take a hundred years or more. The ultimate destinations of plastics as well as their effects on the ecosystem vary with the type of plastic and the rate of their degradation. In this study, an attempt was made to explain the degradation of low-density polyethylene (LDPE) plastic beads with the help of selected bacterial isolates in both laboratory and field conditions. 16 S rRNA gene sequencing further identified the bacterial isolates as Micrococcus luteus and Bacillus pumilus, obtained from the municipal waste disposal site near Anand, Gujarat, India. The beads were subjected to photolysis and hydrolysis for a predetermined amount of time in addition to biodegradation. After 60 days of treatment with Pseudomonas aeruginosa, Micrococcus luteus, and Bacillus pumilus in both laboratory and field conditions, a significant percentage decrease in the weight of LDPE beads was observed. Pseudomonas aeruginosa was taken as a positive control. Further, the rate of degradation was found to be accelerated in the presence of 10% starch.

An Approach to Track and Analyze the Trend of Antimicrobial Resistance Using Python: A Pilot Study for Anand, Gujarat, India-May 2022-August 2023.

The present work deals with the analysis and monitoring of bacterial resistance in using Python for the state of Gujarat, India, where occurrences of drug-resistant bacteria are prevalent. This will provide an insight into the portfolio of drug-resistant bacteria reported, which can be used to track resistance behavior and to suggest a treatment regime for the particular bacteria. The present analysis has been done using Python on Jupyter Notebook as the integrated development environment and its data analysis libraries such as Pandas, Seaborn, and Matplotlib. The data have been loaded from excel file using Pandas and cleaned to transform features into required format. Seaborn and Matplotlib have been used to create data visualizations and represent the data inexplicable manner using graphs, plots, and tables. This program can be used to study disaster epidemiology, tracking, analyzing, and surveillance of antimicrobial resistance with a proper system integration approach.

Mutations in V84I & A184V of blaTEM cluster plays a pivotal role in the dynamics of Ω-loop leading to genesis of IR-TEM.

The Enterobacteriaceae family exhibits resistance to antibiotics by producing ß-Lactamase. Mutations in ß-Lactamase, have led to the generation of inhibitor resistant variants known as IR-TEM. In the present study, IR-TEM ß-Lactamase of Enterobacter hormaechei and Enterobacter asburiae was compared. To investigate the mechanism behind the conferred mutation, we studied its interaction with Clavulanic acid, (ß-Lactamase inhibitor) with different lineages of TEM and IR-TEM. We found that Clavulanic acid quickly left the binding pockets of both variants using molecular dynamics (MD) simulations. Interestingly, mutations at the V84I and A184V positions were found to drastically influence the protein dynamics. Mutating the residues at V84I and A184V positions by computational mutagenesis in Enterobacter hormaechei, it was observed that the residues on the Ω-loop as well as a few downstream residues were primarily involved in generating resistance towards inhibitors by conferring increased flexibility to the loop. This further strongly supports the notion that inhibitor resistance in ß-Lactamase is conferred through allosteric regulation, wherein mutations in positions 84 and 184 may play an important role in regulating the movement of the Ω-loop. These two positions determine the lineage pattern between two clusters in TEM-1 and TEM-116. To date, no reports have been made regarding the importance of these mutations and their dynamics in Ω-loop.Communicated by Ramaswamy H. Sarma.

In Silico Evaluation of Human Cathelicidin LL-37 as a Novel Therapeutic Inhibitor of Panton-Valentine Leukocidin Toxin of Methicillin-Resistant Staphylococcus aureus.

Incidence of drug resistance in clinical isolates of methicillin-resistant Staphylococcus aureus (MRSA) is attributed to its diverse repertoire of virulence factors. Of these virulence determinants, Panton-Valentine Leukocidin (PVL) has been experimentally validated as a prospective drug target due to its conspicuous and comprehensive role in nosocomial infections. This study encompassed an in silico approach to elucidate the antimicrobial potentiality of human cathelicidin LL-37 against PVL toxin of MRSA. Molecular docking studies of LL-37 and its segments with the PVL toxin subunits LukS and LukF were carried out using PatchDock server and the results were refined using FireDock server. The paramount ligand-receptor combination was selected and analyzed based on diverse parametric attributes and compared with the commercial inhibitors of PVL viz. Andrimid, Beclobrate, Beta-sitosterol, Diathymosulfone, and Probucol to determine the most potent inhibitor among them. Our results elucidated that the interaction of LL-37 with the LukS subunit of PVL toxin (minimum global energy of -61.82 kcal/mol) depicted 34 molecular interactions, while the commercial PVL inhibitors depicted fewer and insubstantial interactions. SWISS-ADME (Absorption, Distribution, Metabolism, and Excretion) and ToxinPred analysis of LL-37 further corroborated its null potency of toxicity in systemic milieu. The results obtained may credit this study as basis for the development of LL-37 as a potential inhibitor against virulent MRSA toxins, thereby exalting the treatment regimes for nosocomial infections in health care facilities worldwide.

Computational drug re-purposing targeting the spike glycoprotein of SARS-CoV-2 as an effective strategy to neutralize COVID-19.

COVID-19 has intensified into a global pandemic with over a million deaths worldwide. Experimental research analyses have been implemented and executed with the sole rationale to counteract SARS-CoV-2, which has initiated potent therapeutic strategy development in coherence with computational biology validation focusing on the characterized viral drug targets signified by proteomic and genomic data. Spike glycoprotein is one of such potential drug target that promotes viral attachment to the host cellular membrane by binding to its receptor ACE-2 via its Receptor-Binding Domain (RBD). Multiple Sequence alignment and relative phylogenetic analysis revealed significant sequential disparities of SARS-CoV-2 as compared to previously encountered SARS-CoV and MERS-CoV strains. We implemented a drug re-purposing approach wherein the inhibitory efficacy of a cluster of thirty known drug candidates comprising of antivirals, antibiotics and phytochemicals (selection contingent on their present developmental status in underway clinical trials) was elucidated by subjecting them to molecular docking analyses against the spike protein RBD model (developed using homology modelling and validated using SAVES server 5.0) and the composite trimeric structures of spike glycoprotein of SARS-CoV-2. Our results indicated that Camostat, Favipiravir, Tenofovir, Raltegravir and Stavudine showed significant interactions with spike RBD of SARS-CoV-2. Proficient bioavailability coupled with no predicted in silico toxicity rendered them as prospective alternatives for designing and development of novel combinatorial therapy formulations for improving existing treatment regimes to combat COVID-19.

Interaction of antimicrobial peptide with mycolyl transferase in Mycobacterium tuberculosis.

It is estimated that about 40% of the Indian population are infected with tuberculosis (TB) and that ∼3,000,000 people die as a result of TB annually. TB is caused by Mycobacterium tuberculosis. In 2011, the World Health Organization declared India as having the highest TB burden worldwide. An important criteria for pathogenicity is the presence of mycolic acid linked to the protective outer membrane of bacteria. Mycolyl transferase catalyzes the transfer of mycolic acid and promotes cell wall synthesis. This is also considered as a novel target for drug-mediated intervention strategies. Here, we have attempted to understand the interaction between the antimicrobial peptide (AMP), dermcidin, and mycolyl transferase in M. tuberculosis using a computational approach. The present study was undertaken in order to elucidate the capability of AMPs to treat this bacteria, which is less sensitive to available antibiotics, and to design a novel method for new therapies.