Biofertilizer and biocontrol properties of Stenotrophomonas maltophilia BCM emphasize its potential application for sustainable agriculture.

Introduction: Microbial biofertilizers or biocontrol agents are potential sustainable approaches to overcome the limitations of conventional agricultural practice. However, the limited catalog of microbial candidates for diversified crops creates hurdles in successfully implementing sustainable agriculture for increasing global/local populations. The present study aimed to explore the wheat rhizosphere microbiota for microbial strains with a biofertilizer and biocontrol potential. Methods: Using a microbial culturing-based approach, 12 unique microbial isolates were identified and screened for biofertilizer/biocontrol potential using genomics and physiological experimentations. Results and discussion: Molecular, physiological, and phylogenetic characterization identified Stenotrophomonas maltophilia BCM as a potential microbial candidate for sustainable agriculture. Stenotrophomonas maltophilia BCM was identified as a coccus-shaped gram-negative microbe having optimal growth at 37°C in a partially alkaline environment (pH 8.0) with a proliferation time of ~67 minutes. The stress response physiology of Stenotrophomonas maltophilia BCM indicates its successful survival in dynamic environmental conditions. It significantly increased (P <0.05) the wheat seed germination percentage in the presence of phytopathogens and saline conditions. Genomic characterization decoded the presence of genes involved in plant growth promotion, nutrient assimilation, and antimicrobial activity. Experimental evidence also correlates with genomic insights to explain the potential of Stenotrophomonas maltophilia BCM as a potential biofertilizer and biocontrol agent. With these properties, Stenotrophomonas maltophilia BCM could sustainably promote wheat production to ensure food security for the increasing population, especially in native wheat-consuming areas.

Peribacillus frigoritolerans T7-IITJ, a potential biofertilizer, induces plant growth-promoting genes of Arabidopsis thaliana.

AIMS: This study aimed to isolate plant growth and drought tolerance-promoting bacteria from the nutrient-poor rhizosphere soil of Thar desert plants and unravel their molecular mechanisms of plant growth promotion. METHODS AND RESULTS: Among our rhizobacterial isolates, Enterobacter cloacae C1P-IITJ, Kalamiella piersonii J4-IITJ, and Peribacillus frigoritolerans T7-IITJ, significantly enhanced root and shoot growth (4-5-fold) in Arabidopsis thaliana under PEG-induced drought stress. Whole genome sequencing and biochemical analyses of the non-pathogenic bacterium T7-IITJ revealed its plant growth-promoting traits, viz., solubilization of phosphate (40-73 µg/ml), iron (24 ± 0.58 mm halo on chrome azurol S media), and nitrate (1.58 ± 0.01 µg/ml nitrite), along with production of exopolysaccharides (125 ± 20 µg/ml) and auxin-like compounds (42.6 ± 0.05 µg/ml). Transcriptome analysis of A. thaliana inoculated with T7-IITJ and exposure to drought revealed the induction of 445 plant genes (log2fold-change > 1, FDR < 0.05) for photosynthesis, auxin and jasmonate signalling, nutrient uptake, redox homeostasis, and secondary metabolite biosynthesis pathways related to beneficial bacteria-plant interaction, but repression of 503 genes (log2fold-change < -1) including many stress-responsive genes. T7-IITJ enhanced proline 2.5-fold, chlorophyll 2.5-2.8-fold, iron 2-fold, phosphate 1.6-fold, and nitrogen 4-fold, and reduced reactive oxygen species 2-4.7-fold in plant tissues under drought. T7-IITJ also improved the germination and seedling growth of Tephrosia purpurea, Triticum aestivum, and Setaria italica under drought and inhibited the growth of two plant pathogenic fungi, Fusarium oxysporum, and Rhizoctonia solani. CONCLUSIONS: P. frigoritolerans T7-IITJ is a potent biofertilizer that regulates plant genes to promote growth and drought tolerance.

Design, synthesis and exploration of novel triazinoindoles as potent quorum-sensing inhibitors and radical quenchers.

Background: Antimicrobial resistance has become a critical health concern, and quorum-sensing exacerbates the resistance by facilitating cell-to-cell communication within the microbial community, leading to severe pathogenic outbreaks. Methods & results: Novel 1-(2-((5H-[1,2,4]-triazino[5,6-b]indol-3-yl)thio)acetyl)indoline-2,3-diones were synthesized. The title compounds exhibit outstanding anti-quorum-sensing efficacy, and compound 7g demonstrated the maximum proficiency (IC50 = 0.0504 µg/ml). The hybrids displayed potent antioxidant action, and compound 7c showed the highest antioxidant ability (IC50 = 40.71 µg/ml). Molecular docking of the isatin hybrids against DNA gyrase and quorum-sensing receptor CviR validated the observed in vitro findings. The befitting pharmacokinetic profile of the synthesized drug candidates was ascertained through absorption, distribution, metabolism, excretion and toxicity screening. Conclusion: The remarkable biocompetence of the synthesized triazinoindoles may help to combat drug-resistant infections.

Integrating artificial neural networks and response surface methodology for predictive modeling and mechanistic insights into the detoxification of hazardous MB and CV dyes using Saccharum officinarum L. biomass.

The presence of dye pollutants in industrial wastewater poses significant environmental and health risks, necessitating effective treatment methods. The optimal adsorption treatment of methylene blue (MB) and crystal violet (CV) dye-simulated wastewater utilising Saccharum officinarum L presents a key challenge in the selection of appropriate modelling approaches. While RSM and ANN models are frequently used, there is a noticeable knowledge gap when it comes to evaluating their relative strengths and weaknesses in this context. The study compared the predictive abilities of response surface methodology (RSM) and artificial neural network (ANN) for the adsorption treatment of MB and CV dye-simulated wastewater using Saccharum officinarum L. The process experimental variables were modelled and predicted using a three-layer artificial neural network trained using the Levenberg-Marquard backpropagation algorithm and 30 central composite designs (CCD). The adsorption study used a specific mechanism, which led to noteworthy maximum removals of 98.3% and 98.2% for dyes (MB and CV), respectively. The RSM model achieved an impressive R2 of 0.9417, while the ANN model achieved 0.9236 in MB. Adsorption is commonly used to remove colour from many different materials. Saccharum officinarum L., a byproduct of sugarcane processing, has shown potential as an efficient and ecological adsorbent in this environment. The purpose of this study is to evaluate sugarcane bagasse's potential as an adsorbent for the removal of dyes MB and CV from industrial wastewater, providing a long-term strategy for reducing dye pollution. Due to its beneficial economic and environmental characteristics, the Saccharum officinarum L. adsorbent has prompted research into sustainable resources with low pollutant indices.

Introducing machine learning model to response surface methodology for biosorption of methylene blue dye using Triticum aestivum biomass.

A major environmental problem on a global scale is the contamination of water by dyes, particularly from industrial effluents. Consequently, wastewater treatment from various industrial wastes is crucial to restoring environmental quality. Dye is an important class of organic pollutants that are considered harmful to both people and aquatic habitats. The textile industry has become more interested in agricultural-based adsorbents, particularly in adsorption. The biosorption of Methylene blue (MB) dye from aqueous solutions by the wheat straw (T. aestivum) biomass was evaluated in this study. The biosorption process parameters were optimized using the response surface methodology (RSM) approach with a face-centred central composite design (FCCCD). Using a 10 mg/L concentration MB dye, 1.5 mg of biomass, an initial pH of 6, and a contact time of 60 min at 25 °C, the maximum MB dye removal percentages (96%) were obtained. Artificial neural network (ANN) modelling techniques are also employed to stimulate and validate the process, and their efficacy and ability to predict the reaction (removal efficiency) were assessed. The existence of functional groups, which are important binding sites involved in the process of MB biosorption, was demonstrated using Fourier Transform Infrared Spectroscopy (FTIR) spectra. Moreover, a scan electron microscope (SEM) revealed that fresh, shiny particles had been absorbed on the surface of the T. aestivum following the biosorption procedure. The bio-removal of MB from wastewater effluents has been demonstrated to be possible using T. aestivum biomass as a biosorbent. It is also a promising biosorbent that is economical, environmentally friendly, biodegradable, and cost-effective.

Treatment of biologically treated distillery spent wash employing electrocoagulation and reverse-osmosis treatment train.

In the present study, electro-coagulation (EC) with stainless steel (SS) electrodes has been used as a pretreatment process before the reverse osmosis (RO) for the biologically treated distillery spent wash. The optimized operating parameters (pH, time, current, and electrode distance) for the EC process were obtained from the previous study. EC treated wastewater was further used as a feed for the RO system. RO membrane system operating parameters (pH, temperature, and trans-membrane pressure) were optimized by employing response surface methodology. Optimized conditions for the RO process were found to be: pH (pHo): 6.12; temperature (T): 20°C and trans-membrane pressure (TMP): 45.7 bar. The combined (EC-RO) process showed 98%, 99.2%, and 98.5% of COD, color, and TDS removal, respectively, with permeate flux of 40.5 L/m2/h (EC-RO). Experimental results indicated that EC followed by RO could be used as an additional step for biologically treated spent wash treatment to improve the treated effluent quality and membrane life. Results also revealed that the techno-economic performance of combined (EC-RO) treatment in terms of total annual water production is more efficient and economical than RO alone.

Two-stage electrochemical treatment of bio-digested distillery spent wash using stainless steel and aluminum electrodes.

The objective of this study was to determine the effectiveness of two-stage electro-coagulation (EC) process using multi-parameter optimization for treating bio-digested distillery spent wash by stainless steel (SS) and aluminum (Al) electrodes. Operating parameters have been optimized and treatment efficiency of SS and Al electrodes have been compared by central composite design of response surface analysis in terms of COD, color and total organic carbon (TOC) removal. Individual and interactive effects of four independent parameters namely initial pH (pHo: 2-10 and 4-10 for SS and Al electrodes, respectively), current density (j: 30.86-154.32 A m(-2)), inter-electrode distance (g: 0.5-2.5 cm) and electrolysis time (t: 30-150 min) on the COD, color and TOC removal efficiency were evaluated for both the electrodes. SS electrode was found to be more effective for the removal of COD, color and TOC with removal efficiencies of 70%, 93% and 72%, respectively, as compared to Al electrode, which showed respective removal efficiencies of 59%, 80% and 55%. A two-stage EC process was also conducted to study the predominance of different types of electrodes, and to increase the efficiency of EC process. Results shows that SS followed by Al electrode (with total COD, color and TOC removal efficiency of 81%, 94% and 78%, respectively) was found to be more effective than Al followed by SS electrode combination (with total COD, color and TOC removal efficiency of 78%, 89% and 76%, respectively). Present study shows that EC process can be used as an additional step to bio-methanation process so as to meet effluent discharge standards in distilleries.

Membrane autopsy based bio-fouling investigation of distillery spent wash RO treatment plant.

In this paper, a thorough investigation has been done to evaluate the effects of different pollutants on membrane performance by autopsy. Autopsy was performed on fresh and fouled reverse osmosis (RO) membrane elements from a distillery spent wash treatment plant by different analyses, such as field emission scanning electron microscopy, atomic force microscopy, Fourier transform infrared spectroscopy and X-ray diffraction, to identify the cause of poor performance of an RO plant. Results obtained from the analysis of membranes indicate that a mixture of colloids and organic matters (polysaccharides and amines) along with the presence of multivalent ions (Ca, Mg, Fe and SO4) causes membrane fouling, which in turn affects membrane performance. Possible measures to improve treated effluent quality and mitigate fouling have been suggested for this particular case study.