Escherichia coli bacteria are the most common causes of diarrhea and septicemia in calves. Moreover, calves form a major reservoir for transmission of pathogenic E. coli to humans. Systematic reviews and meta-analyses of publications on E. coli as calf pathogens and the role of calves as reservoir have not been done so far. We reviewed studies between 1951 and 2013 reporting the presence of virulence associated factors (VAFs) in calf E. coli and extracted the following information: year(s) and country of sampling, animal number, health status, isolate number, VAF prevalence, serotypes, diagnostic methods, and biological assays. The prevalence of VAFs or E. coli pathotypes was compared between healthy and diarrheic animals and was analyzed for time courses. Together, 106 papers with 25,982 E. coli isolates from 27 countries tested for VAFs were included. F5, F17, and F41 fimbriae and heat-stable enterotoxin (ST) – VAFs of enterotoxigenic E. coli (ETEC) were significantly associated with calf diarrhea. On the contrary, ETEC VAF F4 fimbriae and heat-labile enterotoxin as well as enteropathogenic (EPEC), Shiga toxin-producing (STEC), and enterohemorrhagic E. coli (EHEC) were not associated with diarrhea. The prevalence increased overtime for ST-positive isolates, but decreased for F5- and STEC-positive isolates. Our study provides useful information about the history of scientific investigations performed in this domain so far, and helps to define etiological agents of calf disease, and to evaluate calves as reservoir hosts for human pathogenic E. coli.

Bacterial biofilm formation is a widespread phenomenon and a complex process requiring a set of genes facilitating the initial adhesion, maturation, and production of the extracellular polymeric matrix and subsequent dispersal of bacteria. Most studies on biofilm formation have investigated nonpathogenic K-12 strains. Due to the extensive focus on laboratory strains in most studies, there is poor information regarding biofilm formation by pathogenic isolates. In this study, we genotypically and phenotypically characterized 187 human clinical isolates representing various pathotypes (e.g., uropathogenic, enteropathogenic, and enteroaggregative ). We investigated the presence of biofilm-associated genes ("genotype") and phenotypically analyzed the isolates for motility and curli and cellulose production ("phenotype"). We developed a new screening method to examine the biofilm formation ability. In summary, we found a high prevalence of biofilm-associated genes. However, we could not detect a biofilm-associated gene or specific phenotype correlating with the biofilm formation ability. In contrast, we did identify an association of increased biofilm formation with a specific pathotype. Enteroaggregative (EAEC) was found to exhibit the highest capacity for biofilm formation. Using our image-based technology for the screening of biofilm formation, we demonstrated the characteristic biofilm formation pattern of EAEC, consisting of thick bacterial aggregates. In summary, our results highlight the fact that biofilm-promoting factors shown to be critical for biofilm formation in nonpathogenic strains do not reflect their impact in clinical isolates and that the ability of biofilm formation is a defined characteristic of EAEC. Bacterial biofilms are ubiquitous and consist of sessile bacterial cells surrounded by a self-produced extracellular polymeric matrix. They cause chronic and device-related infections due to their high resistance to antibiotics and the host immune system. In nonpathogenic , cell surface components playing a pivotal role in biofilm formation are well known. In contrast, there is poor information for their role in biofilm formation of pathogenic isolates. Our study provides insights into the correlation of biofilm-associated genes or specific phenotypes with the biofilm formation ability of commensal and pathogenic Additionally, we describe a newly developed method enabling qualitative biofilm analysis by automated image analysis, which is beneficial for high-throughput screenings. Our results help to establish a better understanding of biofilm formation.

Amyloids are proteins associated with several clinical disorders, including Alzheimer’s, and Creutzfeldt-Jakob’s. Despite their diversity, all amyloid proteins can undergo aggregation initiated by short segments called hot spots. To find the patterns defining the hot spots, we trained predictors of amyloidogenicity, using n-grams and random forest classifiers. Since the amyloidogenicity may not depend on the exact sequence of amino acids but on their more general properties, we tested 524,284 reduced amino acid alphabets of different lengths (three to six letters) to find the alphabet providing the best performance in cross-validation. The predictor based on this alphabet, called AmyloGram, was benchmarked against the most popular tools for the detection of amyloid peptides using an external data set and obtained the highest values of performance measures (AUC: 0.90, MCC: 0.63). Our results showed sequential patterns in the amyloids which are strongly correlated with hydrophobicity, a tendency to form β-sheets, and lower flexibility of amino acid residues. Among the most informative n-grams of AmyloGram we identified 15 that were previously confirmed experimentally. AmyloGram is available as the web-server: http://smorfland.uni.wroc.pl/shiny/AmyloGram/ and as the R package AmyloGram. R scripts and data used to produce the results of this manuscript are available at http://github.com/michbur/AmyloGramAnalysis.

Antimicrobial peptides (AMPs) are molecules widespread in all branches of the tree of life that participate in host defense and/or microbial competition. Due to their positive charge, hydrophobicity and amphipathicity, they preferentially disrupt negatively charged bacterial membranes. AMPs are considered an important alternative to traditional antibiotics, especially at the time when multidrug-resistant bacteria being on the rise. Therefore, to reduce the costs of experimental research, robust computational tools for AMP prediction and identification of the best AMP candidates are essential. AmpGram is our novel tool for AMP prediction; it outperforms top-ranking AMP classifiers, including AMPScanner, CAMPR3R and iAMPpred. It is the first AMP prediction tool created for longer AMPs and for high-throughput proteomic screening. AmpGram prediction reliability was confirmed on the example of lactoferrin and thrombin. The former is a well known antimicrobial protein and the latter a cryptic one. Both proteins produce (after protease treatment) functional AMPs that have been experimentally validated at molecular level. The lactoferrin and thrombin AMPs were located in the antimicrobial regions clearly detected by AmpGram. Moreover, AmpGram also provides a list of shot 10 amino acid fragments in the antimicrobial regions, along with their probability predictions; these can be used for further studies and the rational design of new AMPs. AmpGram is available as a web-server, and an easy-to-use R package for proteomic analysis at CRAN repository.

Background: Inappropriate use of antimicrobial agents in animal production has led to the development of antimicrobial resistance (AMR) in foodborne pathogens. Transmission of AMR foodborne pathogens from reservoirs, particularly chickens to the human population do occur. Recently, we reported that occupational exposure was a risk factor for multidrug-resistant (MDR) Escherichia coli (E. coli) among poultry-workers. Here we determined the prevalence and genetic relatedness among MDR E. coli isolated from poultry-workers, chickens, and poultry environments in Abuja, Nigeria. This study was conducted to address the gaps identi ed by the Nigerian AMR situation analysis. Methods: We conducted a cross-sectional study among poultry-workers, chickens, and poultry farm/live bird market (LBM) environments. The isolates were tested phenotypically for their antimicrobial susceptibility pro les, genotypically characterized using whole-genome sequencing (WGS) and in silico multilocus sequence types (MLST). We conducted a phylogenetic single nucleotide polymorphism (SNPs) analysis to determine relatedness and clonality among the isolates. Results: A total of 115 (26.8%) out of 429 samples were positive for E. coli. Of these, 110 isolates were viable for phenotypic and genotypic characterization. The selection comprised 47 (42.7%) isolates from poultry-workers, 36 (32.7%) from chickens, and 27 (24.5%) from poultry-farm or LBM environments. Overall, 101 (91.8%) isolates were determined MDR conferring resistance to at least three drug classes. High frequency of resistance were observed for tetracycline (n = 102; 92.7%), trimethoprim/sulfamethoxazole (n = 93; 84.5%), streptomycin (n = 87; 79.1%) and ampicillin (n = 88; 80%). Two plasmid-mediated colistin genes-mcr-1.1 harboured on IncX4 plasmids were detected in environmental isolates. The most prevalent sequence types (ST) were ST-155 (n = 8), ST-48 (n = 8) and ST-10 (n = 6). Two isolates of human and environmental sources with a SNPs difference of 6161 originating from the same farm shared a novel ST. The isolates had similar AMR genes and plasmid replicons. Conclusion: MDR E.coli isolates were prevalent amongst poultry-workers, poultry, and the poultry farm/LBM environment. The emergence of MDR E. coli with novel ST in two isolates may be plasmidmediated. Competent authorities should enforce AMR regulations to ensure prudent use of antimicrobials to limit the risk of transmission along the food chain.