Implications of Mobile Genetic Elements for Salmonella enterica Single-Nucleotide Polymorphism Subtyping and Source Tracking Investigations

Comprehensive blueprint of Salmonella genomic plasticity identifies hotspots for pathogenicity genes

Understanding the dynamic evolution of Salmonella is vital for effective bacterial infection management. This study explores the role of the flexible genome, organised in regions of genomic plasticity (RGP), in shaping the pathogenicity of Salmonella lineages. Through comprehensive genomic analysis of 12,244 Salmonella spp. genomes covering 2 species, 6 subspecies, and 46 serovars, we uncover distinct integration patterns of pathogenicity-related gene clusters into RGP, challenging traditional views of gene distribution. These RGP exhibit distinct preferences for specific genomic spots, and the presence or absence of such spots across Salmonella lineages profoundly shapes strain pathogenicity. RGP preferences are guided by conserved flanking genes surrounding integration spots, implicating their involvement in regulatory networks and functional synergies with integrated gene clusters. Additionally, we emphasise the multifaceted contributions of plasmids and prophages to the pathogenicity of diverse Salmonella lineages. Overall, this study provides a comprehensive blueprint of the pathogenicity potential of Salmonella. This unique insight identifies genomic spots in nonpathogenic lineages that hold the potential for harbouring pathogenicity genes, providing a foundation for predicting future adaptations and developing targeted strategies against emerging human pathogenic strains.

From farm to fork: Spread of a multidrug resistant Salmonella Infantis clone encoding blaCTX-M-1 on pESI-like plasmids in Central Italy

Salmonella enterica subsp. enterica serovar Infantis (S. Infantis) is one of the "top five Salmonella serovars" of clinical significance in the European Union (EU). Antimicrobial resistant and extended spectrum β-lactamase (ESBL) AmpC-producing S. Infantis have been described in food production systems and human clinical samples in Italy. Recently, an increase of MDR S. Infantis carrying blaCTX-M genes involved in 3rd generation cephalosporin resistance was noticed in the EU, including Italy, mainly due to the spread of S. Infantis harboring a pESI-like plasmid. The aim of this study was to investigate the occurrence of the S. Infantis pESI-like plasmid among antibiotic resistant S. Infantis strains isolated at different points of the food chain, and to provide a phylogenetic analysis to gain further insight on their transmission pathways from 'farm to fork'. MDR S. Infantis strains (n. 35) isolated from 2016 to 2021 at different stages of the food chain (animals, food, food-related environments, and humans) were investigated with in depth molecular characterization using real-time PCR, S1 nuclease pulsed-field gel electrophoresis (S1-PFGE) and whole genome sequencing (WGS). Our study reported the occurrence of S. Infantis strains harboring pESI-like plasmids, carrying blaCTX-M-1 genes, in Central Italy, at different sampling points along the food chain. Results confirmed the presence of a plasmid with a molecular size around 224-310 kb, thus consistent with the pESI-like, in 97 % of the 35 samples investigated. Two variants of S. Infantis pESI-like IncFIB(K)_1_Kpn3 were detected, one associated with the European clone carrying blaCTX-M-1 (21 isolates) and the other associated with U.S. isolates carrying blaCTX-M-65 (2 isolates, pESI-like U.S. variant). The majority was resistant to 3rd generation cephalosporins but none of the strains tested positive for the carbapenemase encoding genes. A total of 118 virulence genes were identified in isolates harboring the pESI-like plasmid. cgMLST and SNP-based analysis revealed the presence of one main cluster, composed by strains isolated from the environment, animals, food and humans. The results of this investigation underline the importance of phylogenetic studies to monitor and understand pathogen and AMR spread in a One Health approach.

Local and Environmental Reservoirs of Salmonella enterica After Hurricane Florence Flooding

In many regions of the world, including the United States, human and animal fecal genetic markers have been found in flood waters. In this study, we use high-resolution whole genomic sequencing to examine the origin and distribution of Salmonella enterica after the 2018 Hurricane Florence flooding. We specifically asked whether S. enterica isolated from water samples collected near swine farms in North Carolina shortly after Hurricane Florence had evidence of swine origin. To investigate this, we isolated and fully sequenced 18 independent S. enterica strains from 10 locations (five flooded and five unflooded). We found that all strains have extremely similar chromosomes with only five single nucleotide polymorphisms (SNPs) and possessed two plasmids assigned bioinformatically to the incompatibility groups IncFIB and IncFII. The chromosomal core genome and the IncFIB plasmid are most closely related to environmental Salmonella strains isolated previously from the southeastern US. In contrast, the IncFII plasmid was found in environmental S. enterica strains whose genomes were more divergent, suggesting the IncFII plasmid is more promiscuous than the IncFIB type. We identified 65 antibiotic resistance genes (ARGs) in each of our 18 S. enterica isolates. All ARGs were located on the Salmonella chromosome, similar to other previously characterized environmental isolates. All isolates with different SNPs were resistant to a panel of commonly used antibiotics. These results highlight the importance of environmental sources of antibiotic-resistant S. enterica after extreme flood events.

Prevalence of IncFIB Plasmids Found among Salmonella enterica Serovar Schwarzengrund Isolates from Animal Sources in Taiwan Using Whole-Genome Sequencing

Salmonella enterica serovar Schwarzengrund is one of the most frequently isolated Salmonella serotypes responsible for human and poultry infections in Taiwan, and it has raised public health concerns. To better facilitate the understanding of transmission patterns and the dynamics of epidemics, sharing molecular data on pathogen profiles is urgently needed. The objectives of the current study were to determine and establish baseline data of S. enterica serovar Schwarzengrund isolates from 23 epidemiologically unrelated sources from year 2000 to 2018 and examine their phenotypic and genotypic characteristics. Genomic DNA of the Salmonella isolates was extracted and subjected to whole-genome sequencing using an Illumina platform. Results showed that all selected isolates exhibited multidrug resistance, and six of those were resistant to ciprofloxacin phenotypically. Genotypically, these isolates carried genes resistant to aminoglycoside (100%), phenicol (91.3%), β-lactams (69.5%), folate pathway antagonist (100%), tetracycline (82.6%), and fluoroquinolone (4.3%). Moreover, these isolates harbor integrons with five different gene cassettes identified for the first time, which are associated with resistance to trimethoprim, streptomycin, tetracycline, sulfonamide, chloramphenicol, and gentamicin. Furthermore, prevalence of IncFIB plasmid was found among studied isolates, which may increase its ability to colonize the chicken cecum and cause extra-intestinal disease. Salmonella pathogenicity islands SPI-1 to SPI-5, SPI-13, and SPI-14, as well as C63PI locus, were also detected in all isolates. This study demonstrated that a considerable high antimicrobial resistance with high virulence levels of Salmonella were found from animal sources. Sharing data on these pathogen profiles can not only help increase the reproducibility and accessibility of genomic analysis but can also support surveillance and epidemiological investigations for salmonellosis in the region.

Whole Genome Sequencing Applied to Pathogen Source Tracking in Food Industry: Key Considerations for Robust Bioinformatics Data Analysis and Reliable Results Interpretation

Whole genome sequencing (WGS) has arisen as a powerful tool to perform pathogen source tracking in the food industry thanks to several developments in recent years. However, the cost associated to this technology and the degree of expertise required to accurately process and understand the data has limited its adoption at a wider scale. Additionally, the time needed to obtain actionable information is often seen as an impairment for the application and use of the information generated via WGS. Ongoing work towards standardization of wet lab including sequencing protocols, following guidelines from the regulatory authorities and international standardization efforts make the technology more and more accessible. However, data analysis and results interpretation guidelines are still subject to initiatives coming from distinct groups and institutions. There are multiple bioinformatics software and pipelines developed to handle such information. Nevertheless, little consensus exists on a standard way to process the data and interpret the results. Here, we want to present the constraints we face in an industrial setting and the steps we consider necessary to obtain high quality data, reproducible results and a robust interpretation of the obtained information. All of this, in a time frame allowing for data-driven actions supporting factories and their needs.

Microevolution and Gain or Loss of Mobile Genetic Elements of Outbreak-Related Listeria monocytogenes in Food Processing Environments Identified by Whole Genome Sequencing Analysis

Whole genome sequencing (WGS) analyses have been instrumental in traceback investigations of Listeria monocytogenes (Lm). To demonstrate how long-read sequencing analysis can capture and describe relationships among isolates from clinical, food, and environmental sources, we analyzed 366 long-read- and shotgun-sequenced isolates from 16 Lm outbreak strains associated with cantaloupe, leafy green, stone fruit, caramel apple, mung bean sprout, multiple cheese products, multiple ice cream products, and their production environments. The analyses demonstrated that outbreak strains could be distributed in different areas and zones of food production environments through persistent or repeated contamination. Multi-strain and multi-clone contamination were common. Further, WGS could differentiate among isolates collected at different time points or from different production lines in the same facility, revealing microevolution events in processing environments. Our comparison between complete and shotgun genomes showed that isolates of the same outbreak strain diversified mostly by gain/loss of plasmids and chromosome-borne prophages that constitute 2 to 5% of the chromosome. In contrast, other genes missing in the shotgun genomes were randomly scattered, constituting ~0.5% of the chromosome. Among different outbreak strains of the same CC, most gene-scale differences were due to gain/loss of mobile genetic elements, such as plasmids, chromosome-borne prophages, a Tn916 like transposon, and Listeria Genomic Island 2. The nucleotide variations in the same prophage and the same plasmid shared among isolates of the same outbreak strain were limited, which enabled different WGS tools to unambiguously cluster isolates of the same outbreak strain. In some outbreak strains, correlation between prophage gain/loss and single nucleotide polymorphism (SNP) accumulations in the genome backbone were observed.