Microbes and microbial strategies in carcinogenic polycyclic aromatic hydrocarbons remediation: a systematic review.

Degradation, detoxification, or removal of the omnipresent polycyclic aromatic hydrocarbons (PAHs) from the ecosphere as well as their prevention from entering into food chain has never appeared simple. In this context, cost-effective, eco-friendly, and sustainable solutions like microbe-mediated strategies have been adopted worldwide. With this connection, measures have been taken by multifarious modes of microbial remedial strategies, i.e., enzymatic degradation, biofilm and biosurfactant production, application of biochar-immobilized microbes, lactic acid bacteria, rhizospheric-phyllospheric-endophytic microorganisms, genetically engineered microorganisms, and bioelectrochemical techniques like microbial fuel cell. In this review, a nine-way directional approach which is based on the microbial resources reported over the last couple of decades has been described. Fungi were found to be the most dominant taxa among the CPAH-degrading microbial community constituting 52.2%, while bacteria, algae, and yeasts occupied 37.4%, 9.1%, and 1.3%, respectively. In addition to these, category-wise CPAH degrading efficiencies of each microbial taxon, consortium-based applications, CPAH degradation-related molecular tools, and factors affecting CPAH degradation are the other important aspects of this review in light of their appropriate selection and application in the PAH-contaminated environment for better human-health management in order to achieve a sustainable ecosystem.

Comparison of recovery times by using bispectral index monitoring versus end-tidal agent concentration monitoring in patients undergoing inhalational general anaesthesia.

Background and Aims: End-tidal anaesthetic gas concentration (ETAG) and bispectral index (BIS) are both used to monitor depth of anaesthesia. Maintaining an accurate depth of anaesthesia helps in early post-operative recovery. This study compared the recovery times from sevoflurane-nitrous oxide anaesthesia using ETAG monitoring with BIS monitoring. Methods: Four hundred and two patients undergoing elective surgeries under sevoflurane- nitrous oxide anaesthesia were enroled in this double blinded parallel group prospective randomised trial and allocated into two groups. The depth of anaesthesia was monitored using BIS in BIS group (n = 202) and end-tidal sevoflurane concentration (EtSevo) in ETAG group (n = 200). The time to extubation and recovery were compared between the groups. Parametric, non-parametric and categorical variables were compared using Student's 't' test, Wilcoxon's rank sum test and Chi-square test, respectively. Results: Time to extubation (min) [BIS group - 10, 5; ETAG group - 10, 5 (median, inter-quartile range, IQR), P = 0.32] and time to recovery (min) [BIS group - 14, 6; ETAG group - 13.5, 7 (median, IQR), P = 0.34] did not differ significantly between the two groups. The EtSevo concentration (vol%) was significantly higher in the BIS group at 5 min [BIS group - 1.2, 0.4; ETAG group - 1.0, 0.4 (median, IQR), P < 0.001], 30 min [BIS group - 1.1, 0.4; ETAG group - 1.0, 0.3 (median, IQR), P = 0.002] and 120 min [BIS group - 1.11 ± 0.28; ETAG group - 0.96 ± 0.27 (mean ± standard deviation), P = 0.014] after induction of anaesthesia. Conclusions: BIS and ETAG monitoring are associated with comparable recovery profiles. ETAG monitoring is associated with significantly less sevoflurane consumption.

Enzyme producing insect gut microbes: an unexplored biotechnological aspect.

To explore the unmapped biotechnologically important microbial platforms for human welfare, the insect gut system is such a promising arena. Insects, the inhabitant of all ecological niches, harbor a healthy diversified microbial population in their versatile gut environment. This deep-rooted symbiotic relationship between insects and gut microbes is the result of several indispensable microbial performances that include: enzyme production, detoxification of plant defense compounds and insecticides, maintenance of life cycle, host fertility, bioremediation, pest biocontrol, production of antimicrobial compounds, and in addition provide vitamins, amino acids, and lactic acids to their hosts. Insects have developed such symbiotic interactions with different microorganisms for nutritional benefits like the digestion of dietary compounds by the production of several key hydrolytic enzymes viz: amylase, cellulase, lignocellulase, protease, lipase, xylanase, pectinase, chitinase, laccase, etc. The nutritional enrichment offered by these microbes to insects may be the key factor in the evolutionary attainment of this group. Around one million insect species are grouped under 31 orders, however, only ten of such groups' have been studied in relation to enzyme-producing gut microbes. Moreover, insect gut symbionts are a potential source of biotechnologically active biomolecules as these microbes go through a course of selection pressures in their host gut environment. As symbiosis has pronounced potential regarding the production of novel compounds, especially enzymes with multidimensional industrial capabilities, so there are ample scopes to explore this treasure box for human welfare. Biological significance as well as industrially compatible capabilities can categorize these insect gut symbionts as an unexplored biotechnological aspect.

Data driven covid-19 spread prediction based on mobility and mask mandate information.

COVID-19 is one of the largest spreading pandemic diseases faced in the documented history of mankind. Human to human interaction is the most prolific method of transmission of this virus. Nations all across the globe started to issue stay at home orders and mandating to wear masks or a form of face-covering in public to minimize the transmission by reducing contact between majority of the populace. The epidemiological models used in the literature have considerable drawbacks in the assumption of homogeneous mixing among the populace. Moreover, the effect of mitigation strategies such as mask mandate and stay at home orders cannot be efficiently accounted for in these models. In this work, we propose a novel data driven approach using LSTM (Long Short Term Memory) neural network model to form a functional mapping of daily new confirmed cases with mobility data which has been quantified from cell phone traffic information and mask mandate information. With this approach no pre-defined equations are used to predict the spread, no homogeneous mixing assumption is made, and the effect of mitigation strategies can be accounted for. The model learns the spread of the virus based on factual data from verified resources. A study of the number of cases for the state of New York (NY) and state of Florida (FL) in the USA are performed using the model. The model correctly predicts that with higher mobility the cases would increase and vice-versa. It further predicts the rate of new cases would see a decline if a mask mandate is administered. Both these predictions are in agreement with the opinions of leading medical and immunological experts. The model also predicts that with the mask mandate option even a higher mobility would reduce the daily cases than lower mobility without masks. We additionally generate results and provide RMSE (Root Mean Square Error) comparison with ARIMA based model of other published work for Italy, Turkey, Australia, Brazil, Canada, Egypt, Japan, and the UK. Our model reports lower RMSE than the ARIMA based work for all eight countries which were tested. The proposed model would provide administrations with a quantifiable basis of how mobility, mask mandates are related to new confirmed cases; so far no epidemiological models provide that information. It gives fast and relatively accurate prediction of the number of cases and would enable the administrations to make informed decisions and make plans for mitigation strategies and changes in hospital resources.

Enhanced biogas production from Lantana camara via bioaugmentation of cellulolytic bacteria.

A study was designed to isolate cellulolytic bacteria from termite-gut and soil, optimizing their cellulase production to enhance biogas generation, using Lantana camara as a substrate. Out of 57 bacteria screened, two isolates DSB1 and DSB12, showed significant cellulolytic activity. 16S rRNA based methods identified these isolates as Microbacterium sp. and Arthrobacter sp. respectively. Maximum cellulase activity of 1.26 ± 0.044 U/ml and 1.31 ± 0.052 U/ml for DSB1 and DSB12 was observed at pH 7 and 7.2 under 35°C and 37°C, respectively. The L. camara biomass substrate with cow dung as an inoculum, bioaugmented with DSB1 and DSB12 separately, was tested for biogas production, producing 950 l/kg and 980 l/kg VS biogas with 57% and 60% methane, respectively. DSB1 and DSB12 revealed as potent cellulase producers that can be harnessed in the anaerobic digester for biomass conversion practices for enhanced biogas production.

Structural-genetic insight and optimization of protease production from a novel strain of Aeromonas veronii CMF, a gut isolate of Chrysomya megacephala.

Structural-genetic characterization of protease producing genes and enzymes from microbial sources are seldom appreciated despite having its substantial utilization in protein engineering or genetic manipulation for biotechnological applications. Aeromonas veronii CMF, a mesophilic bacterium isolated from the gut of Chrysomya megacephala, was found to exhibited significant level of protease activity. For the revelation of genetic potential in relation to protease production, whole genome of this organism was sequenced and analysed while structure-function of different protease enzyme was predicated using various in silico analysis. The 4.5 mb CMF genome was found to encompass various types of protease and mostly they are neutral in nature. Enzyme production was highest in an optimum pH and temperature of 6.0 (32.09 ± 1.015 U/ml) and 35ºC (41.65 ± 1.152 U/ml), respectively. Other culture parameters for optimum production of protease were determined to be inoculum size (1%), incubation period (72 h), shaking condition (125 rpm), carbon and nitrogen source [2% lactose (92.21 ± 3.16 U/ml) and 0.5% urea (163.62 ± 4.31 U/ml), respectively] and effect of surfactants [0.02 mg/ml Tween 80 (174.72 ± 4.48 U/ml)]. Furthermore, A. veronii CMF exhibited significant enzyme production like serine protease (15.22 ± 0.563 U/ml), aspartate protease (33.16 ± 0.762 U/ml) and collagenase (17.26 ± 0.626 U/ml). Genomic information and results of physio-biochemical assays indicate its cost-effective potential use in different enzyme-industry.

Unraveling the heavy metal resistance and biocontrol potential of Pseudomonas sp. K32 strain facilitating rice seedling growth under Cd stress.

Heavy metal and metalloid toxicity in agricultural land needs special attention for crop production essential to feed increasing population globally. Plant growth-promoting rhizobacteria (PGPR) are native biological agents that have tremendous potential to augment crop production in contaminated fields. This study involves selection and identification (through 16S rRNA gene sequence and FAME analysis) of a potent Pseudomonas sp. (strain K32) isolated from a metal-contaminated rice rhizosphere, aimed to its application for sustainable agriculture. Apart from multi-heavy metal(loid) resistance (Cd2+, Pb2+ and As3+ upto 4000, 3800, 3700 µg/ml respectively) along with remarkable Cd bioaccumulation potential (∼90%), this strain showed IAA production, nitrogen-fixation and phosphate solubilization under Cd stress. This bioaccumulation efficiency coupled with PGP traits resulted in the significant enhancement of rice seedling growth under Cd stress. This positive impact of K32 strain was clearly manifested in morphological and biochemical improvements under Cd stress including successful root colonization with rice roots. Cd uptake was also reduced significantly in seedlings in presence of K32 strain. Together with all mentioned properties, K32 showed bio-control potential against plant pathogenic fungi viz. Aspergillus flavus, Aspergillus parasiticus, Paecilomyces sp., Cladosporium herbarum, Rhizopus stolonifer and Alternaria alternata which establish K32 strain a key player in effective bioremediation of agricultural fields. Biocontrol potential was found to be the result of enzymatic activities viz. chitinase, ß-1,3-glucanase and protease which were estimated as 8.17 ± 0.44, 4.38 ± 0.35 and 7.72 ± 0.28 U/mg protein respectively.

Computational-based structural, functional and phylogenetic analysis of Enterobacter phytases.

Myo-inositol hexakisphosphate phosphohydrolases (i.e., phytases) are known to be a very important enzyme responsible for solubilization of insoluble phosphates. In the present study, Enterobacter phytases have characterized by different phylogenetic, structural and functional parameters using some standard bio-computational tools. Results showed that majority of the Enterobacter phytases are acidic in nature as most of the isoelectric points were under 7.0. The aliphatic indices predicted for the selected proteins were below 40 indicating their thermostable nature. The average molecular weight of the proteins was 48 kDa. The lower values of GRAVY of the said proteins implied that they have better interactions with water. Secondary structure prediction revealed that alpha-helical content was highest among the other forms such as sheets, coils, etc. Moreover, the predicted 3D structure of Enterobacter phytases divulged that the proteins consisted of four monomeric polypeptide chains i.e., it was a tetrameric protein. The predicted tertiary model of E. aerogenes (A0A0M3HCJ2) was deposited in Protein Model Database (Acc. No.: PM0080561) for further utilization after a thorough quality check from QMEAN and SAVES server. Functional analysis supported their classification as histidine acid phosphatases. Besides, multiple sequence alignment revealed that "DG-DP-LG" was the most highly conserved residues within the Enterobacter phytases. Thus, the present study will be useful in selecting suitable phytase-producing microbe exclusively for using in the animal food industry as a food additive.

Identification and product optimization of amylolytic Rhodococcus opacus GAA 31.1 isolated from gut of Gryllotalpa africana.

An attempt has been made to isolate potent amylase producing gut bacteria from Gryllotalpa africana. Out of 82 isolates, GAA 31.1 was selected as potent producer, having enzyme activity 9.6 ± 0.861 U/ml. The isolate GAA 31.1 was identified as Rhodococcus opacus following morphological, biochemical, physiological characterization and phylogenetic analysis through 16S rRNA gene sequencing. Fatty acid methyl ester profile of the isolate was also studied. The optimized physical cultural conditions for amylase production were found as incubation period 48 h, inoculum volume 2%, initial pH of the fermentation medium 7.0, temperature 38 °C and aeration at 150 rpm. Optimum nutrient conditions were determined as: supplementation of maltose 1.4% and sodium nitrate 1.4%. Surfactants SDS, EDTA, Tween 80 and Triton X-100 showed positive effect on enzyme production. Riboflavin (50 µg/ml) among the tested vitamins stimulated the production maximally. The isolate was also able to produce amylase using agro-industrial waste. This actinobacterium may be a potent candidate for amylase as it is capable of enhanced production (326.72 ± 6.081 U/ml) by utilizing agro-residues.