BolA promotes the generation of multicellular behavior in S. Typhimurium by regulating the c-di-GMP pathway genes yeaJ and yhjH.

The generation of multicellular behavior enhances the stress adaptability, antibiotic resistance, and pathogenic potential of Salmonella enterica serovar Typhimurium (S. Typhimurium), which is challenging for its prevention and control. Therefore, determination of the mechanism of multicellular behavior development is urgently required. Accordingly, this study investigated BolA, a transcription factor that promotes bacterial survival under different stresses. We found that BolA promoted the generation of multicellular behavior. Furthermore, transcriptome analysis revealed that BolA affected the expression of numerous genes, including biofilm formation and motility-related genes. In terms of biofilm formation, compared with the wild-type strain, bolA overexpression (269BolA+) increased the extracellular matrix content (extracellular polysaccharide, extracellular protein, and extracellular DNA (eDNA) by upregulating gene expression, ultimately increasing the biofilm formation ability by 2.56 times. For motility, bolA overexpression inhibited the expression of flagella synthesis genes, resulting in a 91.15 % decrease in motility compared with the wild-type (6 h). Further mechanistic analysis demonstrated that BolA affected the expression of the C-di-GMP pathway genes yeaJ and yhjH, which influenced the generation of multicellular behavior. In terms of biofilms, the extracellular polysaccharide content of 269BolA + ∆Yeaj (bolA overexpression and yeaJ deletion) was reduced by 89.91 % compared with 269BolA+, resulting in a 71.1 % reduction in biofilm forming ability. The motility of the 269∆BolA∆Yhjh (bolA/yhjH double deletion) strain was significantly decreased compared with that of 269∆BolA. Finally, the LacZ gene reporting showed that BolA promoted and inhibited the expression of yeaJ and yhjH, respectively. In conclusion, BolA mainly improves the content of extracellular polysaccharide by promoting the expression of yeaJ, thus enhancing the formation of biofilms. BolA also restricts flagellar synthesis by inhibiting yhjH expression, therefore reducing motility, ultimately promoting multicellular behavior arises. These findings lay a theoretical foundation for the prevention and control of S. Typhimurium.

THE SCALABLE BIRTH-DEATH MCMC ALGORITHM FOR MIXED GRAPHICAL MODEL LEARNING WITH APPLICATION TO GENOMIC DATA INTEGRATION.

Recent advances in biological research have seen the emergence of high-throughput technologies with numerous applications that allow the study of biological mechanisms at an unprecedented depth and scale. A large amount of genomic data is now distributed through consortia like The Cancer Genome Atlas (TCGA), where specific types of biological information on specific type of tissue or cell are available. In cancer research, the challenge is now to perform integrative analyses of high-dimensional multi-omic data with the goal to better understand genomic processes that correlate with cancer outcomes, e.g. elucidate gene networks that discriminate a specific cancer subgroups (cancer sub-typing) or discovering gene networks that overlap across different cancer types (pan-cancer studies). In this paper, we propose a novel mixed graphical model approach to analyze multi-omic data of different types (continuous, discrete and count) and perform model selection by extending the Birth-Death MCMC (BDMCMC) algorithm initially proposed by Stephens (2000) and later developed by Mohammadi and Wit (2015). We compare the performance of our method to the LASSO method and the standard BDMCMC method using simulations and find that our method is superior in terms of both computational efficiency and the accuracy of the model selection results. Finally, an application to the TCGA breast cancer data shows that integrating genomic information at different levels (mutation and expression data) leads to better subtyping of breast cancers.

BolA affects the biofilm formation ability, outer membrane permeability and virulence, thus is required for the adaptability of Salmonella enterica serotype Typhimurium to the harsh survival environment.

Salmonella enterica serotype Typhimurium, an important foodborne pathogen with high adaptability to the host's internal and external survival environment, seriously threatens public health. Therefore, to understand the mechanism underlying the high adaptability, this study investigated the transcription factor BolA by constructing BolA deletion strain 269△BolA, complemented strain 269BolAR and overexpression strain 269BolA+ based on WT269. BolA significantly inhibited motility; at 6 h, the BolA overexpression strain (269BolA+) showed 91.2% and 90.7% lower motility than the wild type (WT269) and BolA deletion strain (269△BolA), respectively, by downregulating motility-related flagellar genes. BolA promoted biofilm formation; 269BolA+ showed 3.6-fold and 5.2-fold higher biofilm formation ability than WT269 and 269ΔBolA, respectively, by upregulation biofilm formation-related genes. BolA overexpression downregulated the outer membrane gene OmpF and upregulated OmpC, thereby regulating cell permeability, and reducing the antibacterial effect of vancomycin, which can destruct the outer membrane. BolA improved adaptability; 269△BolA showed higher susceptibility to eight antibiotics and 2.5- and 4-fold lower acid and oxidative stress tolerance, respectively, than WT269. In Caco-2 and HeLa cells, 269△BolA showed 2.8- and 3-fold lower cell adhesion ability, respectively, and 4- and 2-fold lower cell invasion ability, respectively, than WT269, through downregulation of the virulence genes. Thus, BolA expression promotes biofilm formation and balances the membrane permeability, thereby improving the resistance of the strains, and enhances its host cell invasion ability by upregulating bacterial virulence factors. Results of this study suggest that the BolA gene may serve as a potential target of therapeutic or preventative strategies to control Salmonella Typhimurium infections.