Surveillance of SARS-CoV-2 RNA in wastewater matrix: a review.

SARS-CoV-2 is the agent responsible for the global pandemic sickness, COVID-19. It is an enveloped virus that belongs to the family Coronaviridae. Recent studies have revealed the fecal shedding of the virus and have been found to enter wastewater and aquatic systems. Prolonged viral presence in fecal samples is a common observation in the reported literature. Survival of the virus in the recipient environment could be a crucial factor that influences its fecal-oral transmission. The detection of a novel coronavirus in wastewater opportunity has potential for environmental surveillance at the community or population level. Such a surveillance system can enable the early detection of disease outbreaks in zones with pre-symptomatic/asymptomatic patients and act as a complementary tool for continuous monitoring of quarantine zones. In contrast to developed regions, resource constraints in underdeveloped communities coupled with different sanitation settings may pose a challenge to wastewater sampling and surveillance. To begin, this review summarizes the literature on the presence of SARS-CoV-2 in feces. The approaches for viral extraction, concentration, and detection in wastewater matrices are then highlighted. Finally, investigations on wastewater-based epidemiology for SARS-CoV-2 surveillance are reviewed.

In silico modelling and molecular dynamics simulation studies on L-Asparaginase isolated from bacterial endophyte of Ocimum tenuiflorum.

Bioactive compounds from endophytes have been used to treat various diseases. In the present study, L-Asparaginase producing endophytes were isolated from Ocimum tenuiflorum (Tulasi) from NIT Warangal, Telangana, India to treat Acute Lymphoblastic Leukemia (ALL) in which L-Asparagine (L-Asn) deamination plays a vital role in ALL treatment. 20 (bacteria and fungi) out of 35 endophytes have been screened for L-Asparaginase production using rapid plate assay technique, in which four strains produced high amounts of L-Asparaginase. 16 s Ribosomal RNA sequencing studies were performed, Bacillus stratosphericus organism was identified, and purified L-Asparaginase sequence has been tailored using MALDI/TOF (Applied Biosystems). The homology model was developed by using MODELLER 9.15v as the endophyte lacks crystal structure of L-Asparaginase enzyme and validated by dint of quality index tools. Docking studies were performed using iGemdock 2.1v. In comparison, free energy binding efficiency of receptor towards L-Asparagine (L-Asn) is good with lesser energy -71.6 kcal/mol in comparison to L-Glutamine (L-Gln) having -67.7 kcal/mol. In order to find the stability of the docked complexes in dynamics environment, molecular dynamics and simulation studies were performed using GROMACS V4.6.5. The trajectory analysis for 10 ns shows the better RMSD, RMSF, Rg and average number of hydrogen bonds for complex 1 (L-Asparaginase + L-Asn docked complex). Hence, complex 1 was found to be more stable than Complex 2 (L-Asparaginase + L-Gln docked complex).

Multi level statistical optimization of l-asparaginase from Bacillus subtilis VUVD001.

Physical and chemical factors influencing the anti-leukemic l-asparaginase enzyme production by Bacillus subtilis VUVD001 were optimized using multi-stage optimization on the basis of preliminary experimental outcomes obtained by conventional one-factor-at-a-time approach using shake flasks. Process variables namely carbon, nitrogen sources, pH and temperature were taken into consideration during response surface methodology (RSM) optimization. The finest enzyme activity of 0.51 IUml-1 obtained by OFAT method was enhanced by 3.2 folds using RSM optimization. Artificial neural network (ANN) modelling and genetic algorithm (GA) based optimizations were further carried out to improve the enzyme drug yield. Results were also validated by conducting experiments at optimum conditions determined by RSM and GA optimization methods. The novel bacterium yielded in 2.88 IUml-1 of enzyme activity at optimum process variables determined by GA optimization, i.e., 0.5% glucose, 8.0% beef extract, 8.3 pH and 49.9 °C temperature. The study explored the optimized culture conditions for better yielding of anti-leukemic enzyme drug from a new bacterial source namely Bacillus subtilis VUVD001.

Optimization of L-asparaginase production from novel Enterobacter sp., by submerged fermentation using response surface methodology.

The culture conditions and nutritional rations influencing the production of extra cellular antileukemic enzyme by novel Enterobacter aerogenes KCTC2190/MTCC111 were optimized in shake-flask culture. Process variables like pH, temperature, incubation time, carbon and nitrogen sources, inducer concentration, and inoculum size were taken into account. In the present study, finest enzyme activity achieved by traditional one variable at a time method was 7.6 IU/mL which was a 2.6-fold increase compared to the initial value. Further, the L-asparaginase production was optimized using response surface methodology, and validated experimental result at optimized process variables gave 18.35 IU/mL of L-asparaginase activity, which is 2.4-times higher than the traditional optimization approach. The study explored the E. aerogenes MTCC111 as a potent and potential bacterial source for high yield of antileukemic drug.

Molecular dynamic simulations of Escherichia coli L-asparaginase to illuminate its role in deamination of asparagine and glutamine residues.

Acute lymphocytic leukemia (ALL) is an outrageous disease worldwide. L-Asparagine (L-Asn) and L-Glutamine (L-Gln) deamination play a crucial role in ALL treatment. Role of Elspar® (L-asparaginase from Escherichia coli) in regulation of L-Asn and L-Gln has been confirmed by the other researchers through experimental studies. Therapeutic research against ALL remained elusive with the lack of information on molecular interactions of Elspar® with amino acid substrates. In the present study, using different docking tools binding cavities, key residues in binding and ligand binding mechanisms were identified. For the apo state enzyme and ligand bound state complexes, MD simulations were performed. Trajectory analysis for 30 ns run confirmed the kinship of L-Asn with L-asparaginase enzyme in the dynamic system with less stability in comparison to L-Gln docked complex. Overall findings strongly supported the bi-functional nature of the enzyme drug. A good number of conformational changes were observed with 1NNS structure due to ligand binding. Results of present study give much more information on structural and functional aspects of E. coli L-asparaginase upon the interaction with its ligands which may be useful in designing effective therapeutics for ALL.