Optimization of biomethane production from sweet sorghum bagasse using artificial neural networks combined with particle swarm algorithm.

In the face of international movement away from fossil fuels caused pollution menace, many research labs are rushing towards next big breakthrough via effective biorefinery development employing non-edible agro-residues as feedstock. This work aims to evaluate and optimize the methane potential of underutilized full strength sweet sorghum bagasse (SSB) via anaerobic digestion (AD). Biochemical methane potential assays are set up for SSB AD under mesophilic and thermophilic conditions at four substrate-o-inoculum ratios (SIR) 3, 5, 7, and 9 with pH 6.5, 7.5, and 8.5 and with 80, 90, and 100 rpm mixing speed over 50 days. SIR 5 produced the highest cumulative biomethane yield of 4.25 L methane g-1 VS with a shorter lag time of 7.5 days and technical digestion time of 24 days. The influence of physio-chemical parameters on AD process dynamics is supported with 16s rRNA metagenomic sequencing. Based on complete experimental data sets, two artificial neural network (ANN) models are developed to identify the relevant significance of process parameters and to predict bagasse methane potential. Further, the developed ANN model is integrated with particle swarm optimization algorithm to create ideal AD process operating conditions which maximize the target variable, biomethane. The trained and cross-validated ANN-PSO model showed good-fit-accuracy with R2 > 0.995 and demonstrated satisfactory performance in the biomethane yield prediction from AD of non-edible agri-residues.

Effects of biotic and abiotic factors on biofilm growth dynamics and their heterogeneous response to antibiotic challenge.

Over the last couple of decades, with the crisis of new antimicrobial arsenal, multidrug-resistant clinical pathogens have been observed extensively. In clinical and medical settings, these persistent pathogens predominantly grow as complex heterogeneous structures enmeshed in a self-produced exopolysaccharide matrix, termed as biofilms. Since biofilms can rapidly form by adapting new environmental surroundings and have potential effect on human health, it is critical to study them promptly and consistently. Biofilm infections are challenging in the contamination of medical devices and implantations, food processing and pharmaceutical industrial settings, and in dental area caries, periodontitis and so on. The persistence of infections associated with biofilms has been mainly attributed to the increased antibiotic resistance offered by the cells growing in biofilms. In fact, it is well known that this recalcitrance of bacterial biofilms is multifactorial, and there are several resistance mechanisms that may act in parallel in order to provide an enhanced level of resistance to the biofilm. In combination, distinct resistance mechanisms significantly decrease our ability to control and eradicate biofilm-associated infections with current antimicrobial arsenal. In addition, various factors are known to influence the process of biofilm formation, growth dynamics, and their heterogeneous response towards antibiotic therapy. The current review discusses the contribution of cellular and physiochemical factors on the growth dynamics of biofilm, especially their role in antibiotic resistance mechanisms of bacterial population living in surface attached growth mode. A systematic investigation on the effects and treatment of biofilms may pave the way for novel therapeutic strategies to prevent and treat biofilms in healthcare and industrial settings.

Review on biological wastewater treatment and resources recovery: attached and suspended growth systems.

The treatment of wastewater for reuse is a potential solution to meet ever increasing urban, industrial, agricultural, and environmental demands across the world, where clean water availability is scarce. There are several traditional wastewater treatment processes that offer varying degrees of effectiveness in addition to presenting environmental, economic, and social disadvantages. Development of promising and inexpensive technologies to provide the reusable water in needful amounts using wastewaters as a cheap source of key nutrients and organic matter is required. Wastewater treatment by biological methods is becoming more important in the light of recovering value-added plant nutrients, heavy metals, biosolids, and bioenergy resources. Different types of solid contaminants in effluents can be removed simultaneously by pure cultures or mixed microbial consortia. Based on the structural organization of microbial biomass, biological treatment systems are classified into two types: dispersed growth system and attached growth system. Biological treatment methods associated with fixed-film growth have been recognized as highly effective and more energy efficient than suspended growth systems. This review discusses the recent breakthroughs in advanced biological wastewater treatment using both the systems, and also focuses on key energetic resources recovery driven by biological technologies.

Influence of Nutrient Availability and Quorum Sensing on the Formation of Metabolically Inactive Microcolonies Within Structurally Heterogeneous Bacterial Biofilms: An Individual-Based 3D Cellular Automata Model.

The resistance of bacterial biofilms to antibiotic treatment has been attributed to the emergence of structurally heterogeneous microenvironments containing metabolically inactive cell populations. In this study, we use a three-dimensional individual-based cellular automata model to investigate the influence of nutrient availability and quorum sensing on microbial heterogeneity in growing biofilms. Mature biofilms exhibited at least three structurally distinct strata: a high-volume, homogeneous region sandwiched between two compact sections of high heterogeneity. Cell death occurred preferentially in layers in close proximity to the substratum, resulting in increased heterogeneity in this section of the biofilm; the thickness and heterogeneity of this lowermost layer increased with time, ultimately leading to sloughing. The model predicted the formation of metabolically dormant cellular microniches embedded within faster-growing cell clusters. Biofilms utilizing quorum sensing were more heterogeneous compared to their non-quorum sensing counterparts, and resisted sloughing, featuring a cell-devoid layer of EPS atop the substratum upon which the remainder of the biofilm developed. Overall, our study provides a computational framework to analyze metabolic diversity and heterogeneity of biofilm-associated microorganisms and may pave the way toward gaining further insights into the biophysical mechanisms of antibiotic resistance.