Pangenome analysis reveals genetic isolation in Campylobacter hyointestinalis subspecies adapted to different mammalian hosts.

Campylobacter hyointestinalis is an emerging pathogen currently divided in two subspecies: C. hyointestinalis subsp. lawsonii which is predominantly recovered from pigs, and C. hyointestinalis subsp. hyointestinalis which can be found in a much wider range of mammalian hosts. Despite C. hyointestinalis being reported as an emerging pathogen, its evolutionary and host-associated diversification patterns are still vastly unexplored. For this reason, we generated whole-genome sequences of 13 C. hyointestinalis subsp. hyointestinalis strains and performed a comprehensive comparative analysis including publicly available C. hyointestinalis subsp. hyointestinalis and C. hyointestinalis subsp. lawsonii genomes, to gain insight into the genomic variation of these differentially-adapted subspecies. Both subspecies are distinct phylogenetic lineages which present an apparent barrier to homologous recombination, suggesting genetic isolation. This is further supported by accessory gene patterns that recapitulate the core genome phylogeny. Additionally, C. hyointestinalis subsp. hyointestinalis presents a bigger and more diverse accessory genome, which probably reflects its capacity to colonize different mammalian hosts unlike C. hyointestinalis subsp. lawsonii that is presumably host-restricted. This greater plasticity in the accessory genome of C. hyointestinalis subsp. hyointestinalis correlates to a higher incidence of genome-wide recombination events, that may be the underlying mechanism driving its diversification. Concordantly, both subspecies present distinct patterns of gene families involved in genome plasticity and DNA repair like CRISPR-associated proteins and restriction-modification systems. Together, our results provide an overview of the genetic mechanisms shaping the genomes of C. hyointestinalis subspecies, contributing to understand the biology of Campylobacter species that are increasingly recognized as emerging pathogens.

Integrated genomic epidemiology and phenotypic profiling of Clostridium difficile across intra-hospital and community populations in Colombia.

Clostridium difficile, the causal agent of antibiotic-associated diarrhea, has a complex epidemiology poorly studied in Latin America. We performed a robust genomic and phenotypic profiling of 53 C. difficile clinical isolates established from diarrheal samples from either intrahospital (IH) or community (CO) populations in central Colombia. In vitro tests were conducted to evaluate the cytopathic effect, the minimum inhibitory concentration of ten antimicrobial agents, the sporulation efficiency and the colony forming ability. Eleven different sequence types (STs) were found, the majority present individually in each sample, however in three samples two different STs were isolated. Interestingly, CO patients were infected with STs associated with hypervirulent strains (ST-1 in Clade-2). Three coexistence events (two STs simultaneously detected in the same sample) were observed always involving ST-8 from Clade-1. A total of 2,502 genes were present in 99% of the isolates with 95% of identity or more, it represents a core genome of 28.6% of the 8,735 total genes identified in the set of genomes. A high cytopathic effect was observed for the isolates positive for the two main toxins but negative for binary toxin (TcdA+/TcdB+/CDT- toxin production type), found only in Clade-1. Molecular markers conferring resistance to fluoroquinolones (cdeA and gyrA) and to sulfonamides (folP) were the most frequent in the analyzed genomes. In addition, 15 other markers were found mostly in Clade-2 isolates. These results highlight the regional differences that C. difficile isolates display, being in this case the CO isolates the ones having a greater number of accessory genes and virulence-associated factors.

Comparative genomics identifies potential virulence factors in Clostridium tertium and C. paraputrificum.

Some well-known Clostridiales species such as Clostridium difficile and C. perfringens are agents of high impact diseases worldwide. Nevertheless, other foreseen Clostridiales species have recently emerged such as Clostridium tertium and C. paraputrificum. Three fecal isolates were identified as Clostridium tertium (Gcol.A2 and Gcol.A43) and C. paraputrificum (Gcol.A11) during public health screening for C. difficile infections in Colombia. C. paraputrificum genomes were highly diverse and contained large numbers of accessory genes. Genetic diversity and accessory gene percentage were lower among the C. tertium genomes than in the C. paraputrificum genomes. C. difficile tcdA and tcdB toxins encoding homologous sequences and other potential virulence factors were also identified. EndoA interferase, a toxic component of the type II toxin-antitoxin system, was found among the C. tertium genomes. toxA was the only toxin encoding gene detected in Gcol.A43, the Colombian isolate with an experimentally-determined high cytotoxic effect. Gcol.A2 and Gcol.A43 had higher sporulation efficiencies than Gcol.A11 (84.5%, 83.8% and 57.0%, respectively), as supported by the greater number of proteins associated with sporulation pathways in the C. tertium genomes compared with the C. paraputrificum genomes (33.3 and 28.4 on average, respectively). This work allowed complete genome description of two clostridiales species revealing high levels of intra-taxa diversity, accessory genomes containing virulence-factors encoding genes (especially in C. paraputrificum), with proteins involved in sporulation processes more highly represented in C. tertium. These finding suggest the need to advance in the study of those species with potential importance at public health level.

Distinct Campylobacter fetus lineages adapted as livestock pathogens and human pathobionts in the intestinal microbiota.

Campylobacter fetus is a venereal pathogen of cattle and sheep, and an opportunistic human pathogen. It is often assumed that C. fetus infection occurs in humans as a zoonosis through food chain transmission. Here we show that mammalian C. fetus consists of distinct evolutionary lineages, primarily associated with either human or bovine hosts. We use whole-genome phylogenetics on 182 strains from 17 countries to provide evidence that C. fetus may have originated in humans around 10,500 years ago and may have "jumped" into cattle during the livestock domestication period. We detect C. fetus genomes in 8% of healthy human fecal metagenomes, where the human-associated lineages are the dominant type (78%). Thus, our work suggests that C. fetus is an unappreciated human intestinal pathobiont likely spread by human to human transmission. This genome-based evolutionary framework will facilitate C. fetus epidemiology research and the development of improved molecular diagnostics and prevention schemes for this neglected pathogen.

Growth Characteristics Modeling of Mixed Culture of Bifidobacterium bifidum and Lactobacillus acidophilus using Response Surface Methodology and Artificial Neural Network

Different culture conditions viz. additional carbon and nitrogen content, inoculum size and age, temperature and pH of the mixed culture of Bifidobacterium bifidum and Lactobacillus acidophilus were optimized using response surface methodology (RSM) and artificial neural network (ANN). Kinetic growth models were fitted for the cultivations using a Fractional Factorial (FF) design experiments for different variables. This novel concept of combining the optimization and modeling presented different optimal conditions for the mixture of B. bifidum and L. acidophilus growth from their one variable at-a-time (OVAT) optimization study. Through these statistical tools, the product yield (cell mass) of the mixture of B. bifidum and L. acidophilus was increased. Regression coefficients (R2) of both the statistical tools predicted that ANN was better than RSM and the regression equation was solved with the help of genetic algorithms (GA). The normalized percentage mean squared error obtained from the ANN and RSM models were 0.08 and 0.3%, respectively. The optimum conditions for the maximum biomass yield were at temperature 38°C, pH 6.5, inoculum volume 1.60 mL, inoculum age 30 h, carbon content 42.31% (w/v), and nitrogen content 14.20% (w/v). The results demonstrated a higher prediction accuracy of ANN compared to RSM.

Growth characteristics modeling of Lactobacillus acidophilus using RSM and ANN

The culture conditions viz. additional carbon and nitrogen content, inoculum size, age, temperature and pH of Lactobacillus acidophilus were optimized using response surface methodology (RSM) and artificial neural network (ANN). Kinetic growth models were fitted to cultivations from a Box-Behnken Design (BBD) design experiments for different variables. This concept of combining the optimization and modeling presented different optimal conditions for L. acidophilus growth from their original optimization study. Through these statistical tools, the product yield (cell mass) of L. acidophilus was increased. Regression coefficients (R²) of both the statistical tools predicted that ANN was better than RSM and the regression equation was solved with the help of genetic algorithms (GA). The normalized percentage mean squared error obtained from the ANN and RSM models were 0.06 and 0.2%, respectively. The results demonstrated a higher prediction accuracy of ANN compared to RSM.