Comparative assessment of soil microbial community in crude oil contaminated sites.

Petroleum refineries generate oily sludge that contains hazardous polycyclic aromatic hydrocarbons (PAH), and hence, its proper disposal is of foremost concern. Analysis of the physicochemical properties and functions of indigenous microbes of the contaminated sites are essential in deciding the strategy for bioremediation. This study analyses both parameters at two geographically distant sites, with different crude oil sources, and compares the metabolic capability of soil bacteria with reference to different contamination sources and the age of the contaminated site. The results indicate that organic carbon and total nitrogen derived from petroleum hydrocarbon negatively affect microbial diversity. Contamination levels vary widely on site, with levels of PAHs ranging from 5.04 to 1.66 × 103 µg kg-1 and 6.20 to 5.64 × 103 µg kg-1 in Assam and Gujarat sites respectively, covering a higher proportion of low molecular weight (LMW) PAHs (fluorene, phenanthrene, pyrene, and anthracene). Functional diversity values were observed to be positively correlated (p < 0.05) with acenaphthylene, fluorene, anthracene, and phenanthrene. Microbial diversity was the highest in fresh oily sludge which decreased upon storage, indicating that immediate bioremediation, soon after its generation, would be beneficial. Improvement in the bio-accessibility of hydrocarbon compounds by the treatment of biosurfactant produced by a (soil isolate/isolate) was demonstrated., with respect to substrate utilization.

Optimization of microbial fuel cell process using a novel consortium for aromatic hydrocarbon bioremediation and bioelectricity generation.

Microbial Fuel Cell (MFC) is an innovative bio-electrochemical approach which converts biochemical energy inherent in wastewater into electrical energy, thus contributing to circular economy. Five electrogenic bacteria, Kocuria rosea (GTPAS76), two strains of Bacillus circulans (GTPO28 and GTPAS54), and two strains of Corynebacterium vitaeruminis (GTPO38 and GTPO42) were isolated from a common effluent treatment plant (CETP) and were used individually as well as in consortium form to run double chambered "H" type microbial fuel cell. Individually they could produce voltage in the range of 0.4-0.7 V in the MFC systems. Consortium developed using GTPO28, GTPO38, GTPAS54 and GTPAS76 were capable of producing voltage output of 0.8 V with 81.81 % and 64 % COD and BOD reduction, respectively. The EPS production capacity and electricity generation by the isolated bacteria correlated significantly (r = 0.72). Various parameters like, effect of preformed biofilm, length of salt bridge and its reuse, aeration, substrate concentration and external resistance were studied in detail. The study emphasizes on improving the commercialization aspect of MFC with repeated use of salt bridge and improving wastewater treatment potential after optimization of MFC system. Polarization curve and power density trends were studied in optimized MFC. A maximum power density and current density achieved were 18.15 mW/m2 and 370.37 mA/m2, respectively using 5 mM sodium benzoate. This study reports the use of sodium benzoate as a substrate along with reusing of the salt bridge in MFC study with promising results for BOD and COD reduction, proving it to be futuristic technology for bio-based circular ecosystem development.

Comparative RNA-Seq profiling of a resistant and susceptible peanut (Arachis hypogaea) genotypes in response to leaf rust infection caused by Puccinia arachidis.

The goal of this study was to identify differentially expressed genes (DEGs) responsible for peanut plant (Arachis hypogaea) defence against Puccinia arachidis (causative agent of rust disease). Genes were identified using a high-throughput RNA-sequencing strategy. In total, 86,380,930 reads were generated from RNA-Seq data of two peanut genotypes, JL-24 (susceptible), and GPBD-4 (resistant). Gene Ontology (GO) and KEGG analysis of DEGs revealed essential genes and their pathways responsible for defence response to P. arachidis. DEGs uniquely upregulated in resistant genotype included pathogenesis-related (PR) proteins, MLO such as protein, ethylene-responsive factor, thaumatin, and F-box, whereas, other genes down-regulated in susceptible genotype were Caffeate O-methyltransferase, beta-glucosidase, and transcription factors (WRKY, bZIP, MYB). Moreover, various genes, such as Chitinase, Cytochrome P450, Glutathione S-transferase, and R genes such as NBS-LRR were highly up-regulated in the resistant genotype, indicating their involvement in the plant defence mechanism. RNA-Seq analysis data were validated by RT-qPCR using 15 primer sets derived from DEGs producing high correlation value (R 2 = 0.82). A total of 4511 EST-SSRs were identified from the unigenes, which can be useful in evaluating genetic diversity among genotypes, QTL mapping, and plant variety improvement through marker-assisted breeding. These findings will help to understand the molecular defence mechanisms of the peanut plant in response to P. arachidis infection.

Structure prediction and molecular docking studies of aromatic hydrocarbon sensing proteins TbuT, HbpR and PhnR to detect priority pollutants.

On-line detection of aromatic hydrocarbon pollutants in aqueous environments can be achieved by biosensing strains having fusion of gene responsible for pollutant sensing protein with a reporter gene. Regulatory proteins TbuT, HbpR and PhnR are such proteins for recognizing one-, two-and three-ring aromatic hydrocarbon pollutants respectively, for which the structure is not known till date. Aim of the present study was to predict the structure of proteins and to determine their in-silico interaction with array of pollutants. Structure prediction of proteins was performed using I-TASSER and Phyre2 and refined with ModRefiner and 3DRefine. Total 14 models were obtained for each protein and the best model had more than 95% coverage in Ramachandran plot region. After successful structure prediction, molecular interaction of proteins with respective aromatic hydrocarbon pollutants categorized by United States Environmental Protection Agency was studied using AutoDockVina where the binding energy was found to fall in range of -4.6 to -8.4 kcal/mol. The types of protein-pollutant interaction were analyzed by LigPlus and Discovery Studio 2017 R2 Client which were found to be similar for standard and pollutant compounds. This study enables us to predict the range of pollutants possible to be detected using these regulatory protein-based biosensors.

Development of fluorescent protein-based biosensing strains: A new tool for the detection of aromatic hydrocarbon pollutants in the environment.

The major sources for release of hydrocarbons into the environment include the effluents generated from chemical processing industries and ports. The introduction of such hazardous compounds into natural water bodies creates considerable disturbances in aquatic life and causes a threat to humans. Thus, it is essential to detect and quantify pollutants at various stages of the wastewater generation and treatment before they reach natural aquatic environments and contaminate them. This study reports the development of "biosensing strains" by cloning hydrocarbon recognizing promoter-operator and a reporter gene in bacterial strains for sensing the presence of pollutants at their lowest possible concentration. So far, various biosensing strains have been constructed with a fused promoter-operator region of the hydrocarbon degrading operons, but most of them use luxAB as a reporter gene. A novel approach in the present study aimed at constructing strains harboring two different fluorescent protein (FP)-based reporter genes for the quantification of multiple pollutants at a time. Two vectors were designed with a fusion of tbuT-gfp and phnR-cfp for the quantification of mono- and poly-aromatic hydrocarbons, respectively. The designed vectors were transformed into E. coli DH5α, and these strains were designated as E. coli DH5α 2296-gfp (containing pPROBE-Tbut-RBS-gfp-npt) and E. coli DH5α 2301-cfp (containing pPROBE-phn-RBS-cfp-npt). Both the developed recombinant strains were capable of successfully detecting mono- and poly-aromatic hydrocarbons in the range of 1-100 µM. The sensing capacity of recombinant strains was successfully validated with actual wastewater samples against available physico-chemical analytical techniques. The development of such recombinant microbial strains indicates the future for online contaminant detection, treatment quality monitoring and protection of aquatic flora and fauna.

Modification of extraction method for community DNA isolation from salt affected compact wasteland soil samples.

To overcome the issue of interferences by salt and compactness in release of bacterial cell required for lysis, method described by Yeates et al. (1998), was optimized for isolation of genomic material (Deoxyribo Nucleic Acid, DNA) from soil microbial community by addition of Al(NH4)SO4. Very low total viable count was observed in the samples tested and hence use of higher amount of soil is required primarily for DNA isolation from wasteland soils. The method proves itself efficient where commercially available bead beating and enzymatic lysis methods could not give isolation of any amount of community genomic DNA due to compact nature and salt concentrations present in soil. •The protocol was found efficient for soil samples with high clay content for microbial community DNA extraction.•Variation in lysis incubation and amount of soil may help with soil samples containing low microbial population.•Addition of Al(NH4)SO4 is crucial step in humic acid removal from extracted DNA samples for soil samples containing high salinity and clay particles.