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

Predicting antimicrobial resistance in E. coli with discriminative position fused deep learning classifier

Escherichia coli (E. coli) has become a particular concern due to the increasing incidence of antimicrobial resistance (AMR) observed worldwide. Using machine learning (ML) to predict E. coli AMR is a more efficient method than traditional laboratory testing. However, further improvement in the predictive performance of existing models remains challenging. In this study, we collected 1937 high-quality whole genome sequencing (WGS) data from public databases with an antimicrobial resistance phenotype and modified the existing workflow by adding an attention mechanism to enable the modified workflow to focus more on core single nucleotide polymorphisms (SNPs) that may significantly lead to the development of AMR in E. coli. While comparing the model performance before and after adding the attention mechanism, we also performed a cross-comparison among the published models using random forest (RF), support vector machine (SVM), logistic regression (LR), and convolutional neural network (CNN). Our study demonstrates that the discriminative positional colors of Chaos Game Representation (CGR) images can selectively influence and highlight genome regions without prior knowledge, enhancing prediction accuracy. Furthermore, we developed an online tool (https://github.com/tjiaa/E.coli-ML/tree/main) for assisting clinicians in the rapid prediction of the AMR phenotype of E. coli and accelerating clinical decision-making.

Trends in antimicrobial susceptibility pattern of Salmonella species isolated from bacteremia patients at a tertiary care center in Northern India

The study was done to assess the antimicrobial susceptibility pattern among Salmonella enterica serovars causing bacteremia in Northern India. In this observational study, blood samples positive for Salmonella enterica serovars from January 2021 to April 2023 were studied. Species identification was done using MALDI-ToF MS. Serotyping was done using slide agglutination method. Antimicrobial susceptibility was interpreted as per the CLSI guidelines. During the study period, 32 Salmonella enterica serovars were isolated. Salmonella enterica serovar Typhi was the predominant serovar, followed by Salmonella enterica serovar Paratyphi A. All isolates were susceptible to ceftriaxone, chloramphenicol, co-trimoxazole and cefotaxime. Pefloxacin showed 100% resistance. Resistance to nalidixic acid was found in 81.2% isolates. Of the isolates resistant to nalidixic acid, 19(73.08%) isolates were resistant to ciprofloxacin also. This changing susceptibility pattern necessitates continuous surveillance of antibiogram of Salmonella isolates to rationalize the treatment protocols for invasive salmonellosis and prevent emergence of resistant strains.

Epidemiology and antimicrobial resistance of Salmonella serovars Typhimurium and 4,[5],12:i- recovered from hospitalized patients in China

Global emergence of multidrug-resistant (MDR) Salmonella enterica serovar Typhimurium is a continuing challenge for modern healthcare. However, the knowledge, regarding the epidemiology of salmonellosis caused by the monophasic variant S. 4,[5],12:i:- in hospitalized patients, is limited in China. To bridge this gap, we carried out a retrospective study to determine the antimicrobial resistance, trends, and risk factors of S. Typhimurium and S. 4,[5],12:i:- (n = 329) recovered from patients in Zhejiang province between 2011 and 2019. The results showed that 90.57% (298/329) of the isolates were MDR; among them, 48.94% (161/329) and 12.46% (41/329) were phenotypically resistant to cephalosporins and fluoroquinolones, respectively, which are the drugs of choice used to treat salmonellosis in clinics. Additionally, we observed a higher incidence of infections among the young population (<5 years old). Notably, the higher prevalence of ST34 (sequence type 34) isolates, especially after 2014, with MDR (57.05%, 170/298) phenotype, and incidence of ST34 isolates co-harbouring mcr-1 (mobile colistin resistance gene) and blaCTX-M-14 (β-lactamase gene) suggest an association between STs and drug resistance. Together, the increasing prevalence of MDR ST34 calls for enhanced monitoring strategies to mitigate the spread and dissemination of MDR clones of S. Typhimurium and S. 4,[5],12:i-. Our study provides improved knowledge about non-typhoid Salmonella (NTS) infections, which could help in the effective recommendation of antimicrobials in hospitalized patients.

Microbiological hazards in infant and toddler food in China: A comprehensive study between 2004 and 2022

Infant and toddler food (ITF), including powdered infant and follow-up formula (PIFF) and complementary food (CF), provides the majority of early-life nutrients for young children. As infants and toddlers are more vulnerable to foodborne diseases, the safety concern of ITF is the ultimate priority. However, nationwide surveillance for the presence of hazards, specifically microbiological hazards, in the Chinese ITF is partially known, posing a significant knowledge gap for risk ranking. Most importantly, the related regional surveys were largely published in Chinese, making the data unavailable for global sharing. To bridge these gaps, we screened 5,306 publications and conducted a comprehensive meta-analysis for microbiological hazards using 129 qualified studies. The four most reported microbiological hazards in ITF were Bacillus cereus (13.4 %), Cronobacter (4.8 %), Staphylococcus aureus (1.3 %), and Salmonella (1.1 %). B. cereus is a risk factor in ITF, specifically in PIFF, cereals, and ready-to-eat food. The prevalence of B. cereus was high in Northern and Southern China, while the prevalence of Cronobacter was high in Central China. Cronobacter is a microbiological hazard, specifically in PIFF, with a prevalence of 3.0 %. Interestingly, the prevalence dynamics of Cronobacter and B. cereus in ITF were rising and stable, respectively, whereas the prevalence of S. aureus and Salmonella decreased over time. Together, our analysis will promote the global sharing of these critical findings and may guide future policy making.

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.

Typhoid Fever and Non-typhoidal Salmonella Outbreaks: A Portrait of Regional Socioeconomic Inequalities in Brazil

Typhoid fever occurs in an endemic form in Brazil and is a serious public health problem in some regions. In this scenario, further research is urgently needed to identify the associations between socioeconomic factors and typhoid fever, contributing to guiding policy decisions in the country. We aimed to investigate the influence of socioeconomic disparities on the prevalence of typhoid fever and non-typhoidal Salmonella (NTS) in Brazil. A search for data from 2010 to 2019 was carried out with the national health and human development agencies. As milk and derivatives are the fourth food incriminated in food outbreaks in Brazil, analyses for detecting Salmonella spp. in commercial dairy products allowed us to assess whether the outbreaks associated with these foods are due to inadequacies in sanitary control in dairy establishments or whether they are mainly home-based outbreaks. Predictive models validated by the bootstrapping method demonstrate an association of NTS prevalence reduction with improvements in the Sanitation Service Index (Rv ≥  -8 0.686; p ≤ 0.01) and Municipal Human Development Index - MHDI - (Rv =  -0.789; p ≤ 0.02). In the North, typhoid fever prevalence had seasonal variability with the rainfall, while sanitation services (Rv ≥-0.684; p ≤ 0.04) and MHDI (Rv ≥-0.949; p ≤ 0.003) directly influenced Northeast and South Brazil. Thus, the unequal distribution of investments in the sanitation sector contributed to disparities in typhoid fever prevalence among Brazilian regions. The absence of Salmonella spp. in commercial samples ratified the collected data that the outbreaks of Salmonella spp. in the Brazilian population occur mainly at residences. These findings show that implementing public health education and increasing investments in sanitation in regions with poor service can control outbreaks of Salmonella spp. in Brazilian endemic areas.