ObjectivesWe aimed to evaluate the relationships between climate variability, animal reservoirs and scrub typhus incidence in Southern China.MethodsWe obtained data on scrub typhus cases in Guangzhou every month from 2006 to 2014 from the Chinese communicable disease network. Time-series Poisson regression models and distributed lag nonlinear models (DLNM) were used to evaluate the relationship between risk factors and scrub typhus.ResultsWavelet analysis found the incidence of scrub typhus cycled with a period of approximately 8–12 months and long-term trends with a period of approximately 24–36 months. The DLNM model shows that relative humidity, rainfall, DTR, MEI and rodent density were associated with the incidence of scrub typhus.ConclusionsOur findings suggest that the incidence scrub typhus has two main temporal cycles. Determining the reason for this trend and how it can be used for disease control and prevention requires additional research. The transmission of scrub typhus is highly dependent on climate factors and rodent density, both of which should be considered in prevention and control strategies for scrub typhus.

Scrub typhus is a zoonotic disease caused by Orientia tsutsugamushi (O. tsutsugamushi). Orientia tsutsugamushi has various genotypes and more new strains with difference in sequences increasingly appeared. Whether the accurateness of one special nested PCR method which amplifies segment instead of entire open reading frame (ORF) sequence meets the current work of identifying new strains and classifying genotypes remains to be confirmed. And the origins and evolution of this organism have not been thoroughly elucidated. Accordingly, in this study, segments and the entire ORF of the 56-kDa type-specific antigen (TSA56) gene of O. tsutsugamushi were collected, including 209 clinically isolated strains in Guangzhou, China from 2012 to 2016 and 139 reference strains worldwide. By performing phylogenetic analysis, we proved that the accurateness of the particular PCR method which almost met detection need. This regrouping result showed that segments perfectly represented and identified strains of Karp, Boryong, Gilliam, TA763, Kawasaki and part of Kato genotype, and this accuracy is not restricted by region and time. Sequence diversification of Shimokoshi and some Kato strains made their genotyping need to consider entire ORF sequences, but their weak recognition might not be due to recombination. The frequent genetic recombination and high point mutations contributed to genetic diversification of the TSA56 gene. Major overlapping regions of most recombination events occurred between strains of the same genotype, especially Karp and Kato genotype. And cross-genotype overlapping events occurred between Karp and Boryong/Gilliam/TA763/Kato, Kato and Kawasaki/Gilliam/TA686, Boryong and TA686, and Gilliam and Kawasaki. But Segment has quite low recombination frequency and stable mutation trend from 1943 to 2016. So segment is a relatively conserved part of the TSA56 ORF as for its stable trend of genetic diversity, and it may anchor and represent the entire TSA56 ORF gene. And genetic diversity is rejected as one potential reason for the increased incidence of scrub typhus. But an occasional recombination event created an unrecognized genotype which might be due to the breakage of VD II and AD II. Additionally, strains in Guangzhou were homologous and Karp genotype was detected as a dominant.

This study aimed to determine the prevalence of extended-spectrum beta-lactamases (ESBLs) in Enterobacteriaceae and to characterize the genetic composition of ESBL determinants among Enterobacteriaceae isolates from healthy people in Guangzhou, China. A total of 200 rectal swab samples were collected from healthy asymptomatic individuals and tested for ESBL production using ChromID ESBL agar. Phenotypic ESBL producers were screened for blaCTX-M, blaTEM, and blaSHV genes using PCR and DNA sequencing. The prevalence of ESBL-producing Enterobacteriaceae among rectal swab samples was 69.5%. All ESBL-producing isolates harbored blaCTX-M genes (n=138) except for one isolate that harbored blaSHV-2a. Eleven CTX-M ESBL genes were detected. The most predominant CTX-M-type genes were blaCTX-M-14 (n=82), followed by blaCTX-M-55 (n=19), blaCTX-M-65 (n=10), and blaCTX-M-27 (n=9). Isolates carrying blaCTX-M-38,-3,-15,-14b,-98,-121 and -123 were also identified. Molecular homology analysis of the selected isolates was performed by phylogenetic grouping and multilocus sequence typing and indicated that the predominant clone belonged to A-CC10. This study showed a high rate of CTX-M-type ESBL genes among Enterobacteriaceae isolates from healthy individuals in China.

Introduction. The oral cavity is one of the largest reservoirs of microorganisms and many pathogenic bacteria have been shown to be associated with the aetiology of oral cancers. Gap Statement. Owing to the complexity of oral microbial communities and their unclear relationship with oral cancer, identification of specific bacteria which contribute to oral cancer is a key imperative. Aim. To compare and investigate the variations in the composition of the bacterial microbiome and its functions between patients with oral tumorous lesions and healthy subjects. Methodology. Twenty-seven samples from individuals with oral tumours (five oral benign tumours and 22 oral squamous cell carcinomas) and 15 samples from healthy subjects were collected. Genomic DNA was extracted and the V3–V5 region of the 16S rRNA gene was sequenced. Subsequently, bioinformatic assessment was conducted using QIIME2, PICRUSt and linear discriminant analysis effect size analyses (LEfSe). Results. The oral microbiota was composed mainly of the phyla Proteobacteria (31.76 %, 35.00 %), Bacteroidetes (30.13 %, 25.13 %) and Firmicutes (23.92 %, 17.07 %) in tumorous and healthy individuals, respectively. Neisseria , Prevotella , Fusobacterium , Streptococcus , Capnocytophaga , Veillonella , Haemophilus , Prevotella , Porphyromonas and Leptotrichia were the most abundant genera. Alpha diversity in the tumour group was significantly greater than that in the healthy group (P<0.05). Differential analysis of microbes between groups demonstrated a significantly higher number of Neisseria , Veillonella , Streptococcus , Leptotrichia , Lautropia , Sphingopyxis , Sphingobium , Tannerella , Actinomyces and Rothia in healthy controls compared with the tumour group. However, the genera Treponema , Micrococcus , Pseudomonas , Janthinobacterium , Parvimos, Loktanella , Staphylococcus , Acinetobacter , Catonella , Aggregatibacter and Propionibacterium were significantly higher in the tumour group. Pathways related to cancers, cell motility, environmental adaptation, metabolism and signal transduction were enhanced in the tumour group, while functions associated with immune system diseases, replication, repair and translation were significantly enhanced in the healthy group. Conclusion. Variations in the oral microbiota and its functions showed a correlation with oral tumours. The tumour group showed an increased abundance of some multi-drug-resistant and periodontitis-related pathogens. The significantly altered microbiotas may serve as potential biomarkers or inform combination therapy for oral tumours.