Dataset Information

Identification of Streptococcus suis putative zoonotic virulence factors: A systematic review and genomic meta-analysis.

ABSTRACT: Streptococcus suis is an emerging zoonotic pathogen. Over 100 putative virulence factors have been described, but it is unclear to what extent these virulence factors could contribute to zoonotic potential of S. suis. We identified all S. suis virulence factors studied in experimental models of human origin in a systematic review and assessed their contribution to zoonotic potential in a subsequent genomic meta-analysis. PubMed and Scopus were searched for English-language articles that studied S. suis virulence published until 31 March 2021. Articles that analyzed a virulence factor by knockout mutation, purified protein, and/or recombinant protein in a model of human origin, were included. Data on virulence factor, strain characteristics, used human models and experimental outcomes were extracted. All publicly available S. suis genomes with available metadata on host, disease status and country of origin, were included in a genomic meta-analysis. We calculated the ratio of the prevalence of each virulence factor in human and pig isolates. We included 130 articles and 1703 S. suis genomes in the analysis. We identified 53 putative virulence factors that were encoded by genes which are part of the S. suis core genome and 26 factors that were at least twice as prevalent in human isolates as in pig isolates. Hhly3 and NisK/R were particularly enriched in human isolates, after stratification by genetic lineage and country of isolation. This systematic review and genomic meta-analysis have identified virulence factors that are likely to contribute to the zoonotic potential of S. suis.

SUBMITTER: Roodsant TJ

PROVIDER: S-EPMC8632099 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Streptococcus suis (S. suis) is a gram-positive bacterial pathogen in pigs which can cause serious infections in human including meningitis, and septicaemia resulting in serious complications. There were discrepancies between different data and little is known concerning associated risk factors of S. suis. A systematic review and meta-analysis was conducted to investigate on S. suis infection risk factors in human. We searched eight relevant databases using the MeSH terms "Streptococcus suis" OR "Streptococcus suis AND infection" limited in human with no time nor language restriction. Out of 4,999 articles identified, 32 and 3 studies were included for systematic review and meta-analysis respectively with a total of 1,454 Streptococcus suis cases reported. S. suis patients were generally adult males and the elderly. The mean age ranged between 37 to 63 years. Meningitis was the most common clinical manifestation, and deafness was the most common sequelae found among survivors followed by vestibular dysfunction. Infective endocarditis was also noted as among the most common clinical presentations associated with high mortality rate in a few studies. Meta-analyses categorized by type of control groups (community control, and non-S. suis sepsis) were done among 850 participants in 3 studies. The combined odd ratios for studies using community control groups and non-S. Suis sepsis as controls respectively were 4.63 (95% CI 2.94-7.29) and 78.00 (95% CI 10.38-585.87) for raw pork consumption, 4.01 (95% CI 2.61-6.15) and 3.03 (95% CI 1.61-5.68) for exposure to pigs or pork, 11.47, (95% CI 5.68-23.14) and 3.07 (95% CI 1.81-5.18) for pig-related occupation and 3.56 (95% CI 2.18-5.80) and 5.84 (95% CI 2.76-12.36) for male sex. The results were found to be significantly associated with S. suis infection and there was non-significant heterogeneity. History of skin injury and underlying diseases were noted only a small percentage in most studies. Setting up an effective screening protocol and public health interventions would be effective to enhance understanding about the disease.

Project description:BackgroundAntimicrobial resistance (AMR) is among the gravest threats to human health and food security worldwide. The use of antimicrobials in livestock production can lead to emergence of AMR, which can have direct effects on humans through spread of zoonotic disease. Pigs pose a particular risk as they are a source of zoonotic diseases and receive more antimicrobials than most other livestock. Here we use a large-scale genomic approach to characterise AMR in Streptococcus suis, a commensal found in most pigs, but which can also cause serious disease in both pigs and humans.ResultsWe obtained replicated measures of Minimum Inhibitory Concentration (MIC) for 16 antibiotics, across a panel of 678 isolates, from the major pig-producing regions of the world. For several drugs, there was no natural separation into 'resistant' and 'susceptible', highlighting the need to treat MIC as a quantitative trait. We found differences in MICs between countries, consistent with their patterns of antimicrobial usage. AMR levels were high even for drugs not used to treat S. suis, with many multidrug-resistant isolates. Similar levels of resistance were found in pigs and humans from regions associated with zoonotic transmission. We next used whole genome sequences for each isolate to identify 43 candidate resistance determinants, 22 of which were novel in S. suis. The presence of these determinants explained most of the variation in MIC. But there were also interesting complications, including epistatic interactions, where known resistance alleles had no effect in some genetic backgrounds. Beta-lactam resistance involved many core genome variants of small effect, appearing in a characteristic order.ConclusionsWe present a large dataset allowing the analysis of the multiple contributing factors to AMR in S. suis. The high levels of AMR in S. suis that we observe are reflected by antibiotic usage patterns but our results confirm the potential for genomic data to aid in the fight against AMR.

Dataset Information

Identification of Streptococcus suis putative zoonotic virulence factors: A systematic review and genomic meta-analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets