Transcriptome profiling provides insights into regulatory factors involved in Trichoderma viride-Azotobacter chroococcum biofilm formation

Deciphering the photoactive species-directed antibacterial mechanism of bismuth oxychloride with modulated nanoscale thickness

As an environmentally benign disinfection strategy, photocatalytic bacterial inactivation using nanoparticles involves photogenerated reactive species that cause cellular oxidative stress. Rationalising the structural performance of photocatalysts for the practical uses such as wastewater treatment has attracted significant attention; however, the contribution of reactive species to their photocatalytic antibacterial activities at the molecular and transcriptomic levels remains unclear. In this study, nontoxic bismuth oxychloride (BiOCl) photocatalysts with different nanoscale thicknesses, including nanosheets (Ns, ∼5.4 nm), nanoplates (Np, ∼1.8 nm), and ultra-nanosheets (Uns, ∼1.1 nm), were synthesised under hydrothermal conditions. Among the three samples, BiOCl Uns exhibited the most effective photocatalytic degradation efficiency with the calculated apparent rate constant of 0.0294 min^-1, ∼4 times faster than that of Ns, whereas BiOCl Ns possessed the most pronounced bactericidal effect (5.4 log inactivation). Such findings indicate the distinct role of the photoactive species responsible for photocatalytic bacterial inactivation. Moreover, transcriptome analysis of Escherichia coli after photocatalytic treatment revealed that the underlying photocatalytic antibacterial mechanism at the genetic expression level involves cellular component biosynthesis, energy metabolism, and material transportation. Notably, the differences between BiOCl Ns and BiOCl Uns were significantly enriched in purine metabolism. Therefore, the cost-effective preparation of BiOCl nanosheets with nanoscale thickness-modulated photocatalytic antibacterial activity has remarkable potential for sustainable environmental and biomedical applications.

Biological Control of Plant Pathogens: A Global Perspective

The increase in the world population has generated an important need for both quality and quantity agricultural products, which has led to a significant surge in the use of chemical pesticides to fight crop diseases. Consumers, however, have become very concerned in recent years over the side effects of chemical fungicides on human health and the environment. As a result, research into alternative solutions to protect crops has been imposed and attracted wide attention from researchers worldwide. Among these alternatives, biological controls through beneficial microorganisms have gained considerable importance, whilst several biological control agents (BCAs) have been screened, among them Bacillus, Pantoea, Streptomyces, Trichoderma, Clonostachys, Pseudomonas, Burkholderia, and certain yeasts. At present, biopesticide products have been developed and marketed either to fight leaf diseases, root diseases, or fruit storage diseases. However, no positive correlation has been observed between the number of screened BCAs and available marketed products. Therefore, this review emphasizes the development of biofungicides products from screening to marketing and the problems that hinder their development. Finally, particular attention was given to the gaps observed in this sector and factors that hamper its development, particularly in terms of efficacy and legislation procedures.

Formation of Multispecies Biofilms and Their Resistance to Disinfectants in Food Processing Environments: A Review

ABSTRACT

In food processing environments, various microorganisms can adhere and aggregate on the surface of equipment, resulting in the formation of multispecies biofilms. Complex interactions among microorganisms may affect the formation of multispecies biofilms and resistance to disinfectants, which are food safety and quality concerns. This article reviews the various interactions among microorganisms in multispecies biofilms, including competitive, cooperative, and neutral interactions. Then, the preliminary mechanisms underlying the formation of multispecies biofilms are discussed in relation to factors, such as quorum-sensing signal molecules, extracellular polymeric substances, and biofilm-regulated genes. Finally, the resistance mechanisms of common contaminating microorganisms to disinfectants in food processing environments are also summarized. This review is expected to facilitate a better understanding of interspecies interactions and provide some implications for the control of multispecies biofilms in food processing.

HIGHLIGHTS

Inhibitory Mechanism of Trichoderma virens ZT05 on Rhizoctonia solani

Trichoderma is a filamentous fungus that is widely distributed in nature. As a biological control agent of agricultural pests, Trichoderma species have been widely studied in recent years. This study aimed to understand the inhibitory mechanism of Trichoderma virens ZT05 on Rhizoctonia solani through the side-by-side culture of T. virens ZT05 and R. solani. To this end, we investigated the effect of volatile and nonvolatile metabolites of T. virens ZT05 on the mycelium growth and enzyme activity of R. solani and analyzed transcriptome data collected from side-by-side culture. T. virens ZT05 has a significant antagonistic effect against R. solani. The mycelium of T. virens ZT05 spirally wraps around and penetrates the mycelium of R. solani and inhibits the growth of R. solani. The volatile and nonvolatile metabolites of T. virens ZT05 have significant inhibitory effects on the growth of R. solani. The nonvolatile metabolites of T. virens ZT05 significantly affect the mycelium proteins of R. solani, including catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), selenium-dependent glutathione peroxidase (GSH-Px), soluble proteins, and malondialdehyde (MDA). Twenty genes associated with hyperparasitism, including extracellular proteases, oligopeptide transporters, G-protein coupled receptors (GPCRs), chitinases, glucanases, and proteases were found to be upregulated during the antagonistic process between T. virens ZT05 and R. solani. Thirty genes related to antibiosis function, including tetracycline resistance proteins, reductases, the heat shock response, the oxidative stress response, ATP-binding cassette (ABC) efflux transporters, and multidrug resistance transporters, were found to be upregulated during the side-by-side culture of T. virens ZT05 and R. solani. T. virens ZT05 has a significant inhibitory effect on R. solani, and its mechanism of action is associated with hyperparasitism and antibiosis.

Application of artificial neural networks to describe the combined effect of pH, time, NaCl and ethanol concentrations on the biofilm formation of Staphylococcus aureus

Biofilms are organized communities, adherent to the surface and resistant to adverse environmental and antimicrobial agents. So, its control is very important. Staphylococcus aureus is an opportunistic pathogen with the biofilm-forming ability that causes numerous problems in the medicine and food industry. Therefore, this study aimed to investigate the effect of pH, ethanol and NaCl concentrations after 24 and 48 h incubation times at 37 °C, also modeling the results with artificial neural network (ANN). For this purpose, after both incubation times, the effect of each parameter was studied, separately and also in combination at the levels in which the highest biofilm was formed. All results were modeled using multiple ANN and compared in terms of R-value and MSE. The highest biofilm formation ability was in neutral pH. Adding the ethanol and NaCl stimulated biofilm formation, but the inhibitory effect was observed at high concentrations of ethanol and NaCl and very acidic or highly alkaline pH levels. The more incubation time also led to an increase in biofilm formation. Eventually, the Feed-Forward, Back-Propagation Neural Network model with the Levenberg-Marquardt training algorithm and 4-12-1 topology was chosen (R-value = 0.995 and validation MSE = 0.011467). This ANN had high modeling ability because there was a high correlation between experimental data and modeling data. Therefore, it was concluded that pH, ethanol, NaCl, and time are effective parameters in the biofilm formation and there is a nonlinear relationship between these factors that the ANN is capable of modeling them.