Genomic Investigation Reveals a Community Typhoid Outbreak Caused by Contaminated Drinking Water in China, 2016

Time series data on typhoid fever incidence during outbreaks from 2000 to 2022

This article presents a comprehensive dataset compiling reported cases of typhoid fever from culture-confirmed outbreaks across various geographical locations from 2000 through 2022, categorized into daily, weekly, and monthly time series. The dataset was curated by identifying peer-reviewed epidemiological studies available in PubMed, OVID-Medline, and OVID-Embase. Time-series incidence data were extracted from plots using WebPlotDigitizer, followed by verification of a subset of the dataset. The primary aim of this dataset is to serve as a foundational tool for researchers and policymakers, enabling the development of robust, model-based strategies for the control of typhoid fever outbreaks. The article describes the method by which the dataset has been compiled and how the quality of the data has been verified. Furthermore, it discusses the dataset's potential applications in optimizing vaccination campaigns, improving public health planning, and tailoring interventions to specific epidemiologic contexts. This article contributes significantly to the field of infectious disease modeling, offering a valuable resource for enhancing typhoid fever control measures globally.

Case report: Thoracic vertebral abscess caused by Salmonella via diagnosed next-generation sequencing

The genus Salmonella consists of Gram-negative bacteria with various serotypes. It commonly causes bacterial infections that affect the intestines. Infection can occur in humans and animals through the ingestion of contaminated food or water, or through contact with infected animals or environments. Complications commonly include intestinal hemorrhage and perforation, though vertebral osteomyelitis is rarely observed. Therefore, in patients with spinal cord abscesses, The genus Salmonella is typically not considered a likely pathogen, especially in the absence of typical symptoms. In this case, the limited information provided by traditional cultivation methods, particularly under the influence of antibiotics. However, next-generation sequencing (NGS) unexpectedly detected Salmonella, which assisted in formulating the final treatment plan. This underscores the role and clinical value of NGS in pathogen identification.

Salmonellosis outbreak archive in China: data collection and assembly

Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that self-limiting diarrhoea of sporadic cases is usually underreported, the Salmonella outbreak (SO) study offers a unique opportunity for source tracing, spatiotemporal correlation, and outbreak prediction. To summarize the pattern of SO and estimate observational epidemiological indicators, 1,134 qualitative reports screened from 1949 to 2023 were included in the systematic review dataset, which contained a 506-study meta-analysis dataset. In addition to the dataset comprising over 50 columns with a total of 46,494 entries eligible for inclusion in systematic reviews or input into prediction models, we also provide initial literature collection datasets and datasets containing socio-economic and climate information for relevant regions. This study has a broad impact on advancing knowledge regarding epidemic trends and prevention priorities in diverse salmonellosis outbreaks and guiding rational policy-making or predictive modeling to mitigate the infringement upon the right to life imposed by significant epidemics.

Climate change affects the spread of typhoid pathogens

Typhoid fever is caused by Salmonella enterica serotype Typhi (Salmonella Typhi). Syndromes in patients vary from asymptomatic carriers to severe or death outcomes, which are frequently reported in African and Southeast Asian countries. It is one of the most common waterborne transmission agents, whose transmission is likely impacted by climate change. Here, we claimed the evidence and consequences of climate-related foodborne and waterborne diseases have increased and provided possible mitigations against Typhoidal Salmonella dissemination.

An integrated nationwide genomics study reveals transmission modes of typhoid fever in China

IMPORTANCE

Typhoid fever is a life-threatening disease caused by Salmonella enterica serovar Typhi, resulting in a significant disease burden across developing countries. Historically, China was very much close to the global epicenter of typhoid, but the role of typhoid transmission within China and among epicenter remains overlooked in previous investigations. By using newly produced genomics on a national scale, we clarify the complex local and global transmission history of such a notorious disease agent in China spanning the most recent five decades, which largely undermines the global public health network.

A nontyphoidal Salmonella serovar domestication accompanying enhanced niche adaptation

Invasive nontyphoidal Salmonella (iNTS) causes extraintestinal infections with ~15% case fatality in many countries. However, the mechanism by which iNTS emerged in China remains unaddressed. We conducted clinical investigations of iNTS infection with recurrent treatment failure, caused by underreported Salmonella enterica serovar Livingstone (SL). Genomic epidemiology demonstrated five clades in the SL population and suggested that the international animal feed trade was a likely vehicle for their introduction into China, as evidenced by multiple independent transmission incidents. Importantly, isolates from Clade-5-I-a/b, predominant in China, showed an invasive nature in mice, chicken and zebrafish infection models. The antimicrobial susceptibility testing revealed most isolates (> 96%) in China are multidrug-resistant (MDR). Overall, we offer exploiting genomics in uncovering international transmission led by the animal feed trade and highlight an emerging hypervirulent clade with increased resistance to frontline antibiotics.

Comprehensive Assessment of Subtyping Methods for Improved Surveillance of Foodborne Salmonella

High-resolution and efficient typing for the bacterial pathogen is essential for tracking the sources, detecting or diagnosing variants, and conducting a risk assessment. However, a systematic in-field investigation of Salmonella along the food chain has not been documented. This study assessed 12 typing methods, such as antimicrobial-resistance (AMR) gene profile typing, Core Genome Multilocus Sequence Typing (cgMLST), and CRISPR multi-virulence locus sequence typing (CRISPR-MVLST), to evaluate their effectiveness for use in routine monitoring of foodborne Salmonella transmission along the poultry production chain. During 2015-16, a total of 1,064 samples were collected from poultry production chain, starting from breeding farms and slaughterhouses to the markets of Zhejiang province in China. A total of 61 consecutive unique Salmonella isolates recovered from these samples were selected for genome sequencing and further comparative typing analysis. Traditional typing methods, including serotyping, AMR phenotype-based typing, as well as modern genotyping approaches, were evaluated and compared by their discrimination index (DI). The results showed that the serotyping method identified nine serovars. The gold standard cgMLST method indicated only 18 different types (DI = 0.8541), while the CRISPR-MVLST method detected 30 types (DI = 0.9628), with a higher DI than all examined medium-resolution WGS-based genotyping methods. We demonstrate that the CRISPR-MVLST might be used as a tool with high discriminatory power, comparable ease of use, ability of tracking the source of Salmonella strains along the food chain and indication of genetic features especially virulence genes. The available methods with different purposes and laboratory expertise were also illustrated to assist in rational implementation. IMPORTANCE In public health field, high-resolution and efficient typing of the bacterial pathogen is essential, considering source-tracking and risk assessment are fundamental issues. Currently, there are no recommendations for applying molecular characterization methods for Salmonella along the food chain, and a systematic in-field investigation comparing subtyping methods in the context of routine surveillance was partially addressed. Using 1,064 samples along a poultry production chain with a considerable level of Salmonella contamination, we collected representative isolates for genome sequencing and comparative analysis by using 12 typing techniques, particularly with whole-genome sequence (WGS) based methods and a recently invented CRISPR multi-virulence locus sequence typing (CRISPR-MVLST) method. CRISPR-MVLST is identified as a tool with higher discriminatory power compared with medium-resolution WGS-based typing methods, comparable ease of use and proven ability of tracking Salmonella isolates. Besides, we also offer recommendations for rational choice of subtyping methods to assist in better implementation schemes.

Antimicrobial resistance and genomic investigation of non-typhoidal Salmonella isolated from outpatients in Shaoxing city, China

Human non-typhoidal salmonellosis is among the leading cause of morbidity and mortality worldwide, resulting in huge economic losses and threatening the public health systems. To date, epidemiological characteristics of non-typhoidal Salmonella (NTS) implicated in human salmonellosis in China are still obscure. Herein, we investigate the antimicrobial resistance and genomic features of NTS isolated from outpatients in Shaoxing city in 2020. Eighty-seven Salmonella isolates were recovered and tested against 28 different antimicrobial agents, representing 12 categories. The results showed high resistance to cefazolin (86.21%), streptomycin (81.61%), ampicillin (77.01%), ampicillin-sulbactam (74.71%), doxycycline (72.41%), tetracycline (71.26%), and levofloxacin (70.11%). Moreover, 83.91% of isolates were resistant to ≥3 categories, which were considered multi-drug resistant (MDR). Whole-genome sequencing (WGS) combined with bioinformatic analysis was used to predict serovars, MLST types, plasmid replicons, antimicrobial resistance genes, and virulence genes, in addition to the construction of phylogenomic to determine the epidemiological relatedness between isolates. Fifteen serovars and 16 STs were identified, with the dominance of S. I 4, [5], 12:i:- ST34 (25.29%), S. Enteritidis ST11 (22.99%), and S. Typhimurium ST19. Additionally, 50 resistance genes representing ten categories were detected with a high prevalence of aac(6')-Iaa (100%), bla _TEM-1B (65.52%), and tet(A) (52.87%), encoding resistance to aminoglycosides, β-lactams, and tetracyclines, respectively; in addition to chromosomic mutations affecting gyrA gene. Moreover, we showed the detection of 18 different plasmids with the dominance of IncFIB(S) and IncFII(S) (39.08%). Interestingly, all isolates harbor the typical virulence genes implicated in the virulence mechanisms of Salmonella, while one isolate of S. Jangwani contains the cdtB gene encoding typhoid toxin production. Furthermore, the phylogenomic analysis showed that all isolates of the same serovar are very close to each other and clustered together in the same clade. Together, we showed a high incidence of MDR among the studied isolates which is alarming for public health services and is a major threat to the currently available treatments to deal with human salmonellosis; hence, efforts should be gathered to further introduce WGS in routinely monitoring of AMR Salmonella in the medical field in order to enhance the effectiveness of surveillance systems and to limit the spread of MDR clones.

Paving the way for precise diagnostics of antimicrobial resistant bacteria

The antimicrobial resistance (AMR) crisis from bacterial pathogens is frequently emerging and rapidly disseminated during the sustained antimicrobial exposure in human-dominated communities, posing a compelling threat as one of the biggest challenges in humans. The frequent incidences of some common but untreatable infections unfold the public health catastrophe that antimicrobial-resistant pathogens have outpaced the available countermeasures, now explicitly amplified during the COVID-19 pandemic. Nowadays, biotechnology and machine learning advancements help create more fundamental knowledge of distinct spatiotemporal dynamics in AMR bacterial adaptation and evolutionary processes. Integrated with reliable diagnostic tools and powerful analytic approaches, a collaborative and systematic surveillance platform with high accuracy and predictability should be established and implemented, which is not just for an effective controlling strategy on AMR but also for protecting the longevity of valuable antimicrobials currently and in the future.

Prevalence and Genomic Investigation of Multidrug-Resistant Salmonella Isolates from Companion Animals in Hangzhou, China

Salmonella is a group of bacteria that constitutes the leading cause of diarrheal diseases, posing a great disease burden worldwide. There are numerous pathways for zoonotic Salmonella transmission to humans; however, the role of companion animals in spreading these bacteria is largely underestimated in China. We aimed to investigate the prevalence of Salmonella in pet dogs and cats in Hangzhou, China, and characterize the antimicrobial resistance profile and genetic features of these pet-derived pathogens. In total, 137 fecal samples of pets were collected from an animal hospital in Hangzhou in 2018. The prevalence of Salmonella was 5.8% (8/137) in pets, with 9.3% (5/54) of cats and 3.6% (3/83) of dogs being Salmonella positive. By whole-genome sequencing (WGS), in silico serotyping, and multilocus sequence typing (MLST), 26 pet-derived Salmonella isolates were identified as Salmonella Dublin (ST10, n = 22) and Salmonella Typhimurium (ST19, n = 4). All of the isolates were identified as being multidrug-resistant (MDR), by conducting antimicrobial susceptibility testing under both aerobic and anaerobic conditions. The antibiotics of the most prevalent resistance were streptomycin (100%), cotrimoxazole (100%), tetracycline (96.20%), and ceftriaxone (92.30%). Versatile antimicrobial-resistant genes were identified, including floR (phenicol-resistant gene), blaCTX-M-15, and blaCTX-M-55 (extended-spectrum beta-lactamase genes). A total of 11 incompatible (Inc) plasmids were identified, with IncA/C2, IncFII(S), and IncX1 being the most predominant among Salmonella Dublin, and IncFIB(S), IncFII(S), IncI1, and IncQ1 being the most prevailing among Salmonella Typhimurium. Our study applied WGS to characterize pet-derived Salmonella in China, showing the presence of MDR Salmonella in pet dogs and cats with a high diversity of ARGs and plasmids. These data indicate a necessity for the regular surveillance of pet-derived pathogens to mitigate zoonotic diseases.