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Analysis of the global distribution characteristics of arthropod vectorborne microbial risk factors using public datasets
PENG XianHui, HAN Na, ZHANG TingTing, QIANG YuJun, LI XiuWen, ZHANG Wen
2025, 68(11):
1598-1607.
doi:10.16380/j.kcxb.2025.11.013
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【Aim】This study aims to investigate the potential microbial risk factors, including pathogenic bacteria and related antibiotic resistance genes (ARGs), viruses, parasites and fungi carried by arthropod vectors based on public databases, and assess their potential threat to public health, so as to provide a scientific basis for the formulation of disease prevention and control strategies. 【Methods】 A total of 698 gut metagenomic samples, derived from 29 arthropod species across 15 countries worldwide, were retrieved from the National Center for Biotechnology Information (NCBI) database of America. Bacterial community structure was profiled using Metaphlan with the mpa_v30_CHOCOPhlAn_201901 reference database. Pathogenic bacteria were identified by aligning reads against the information of marker genes of disease-related microorganisms (DRMs) in public database using Bowtie2, applying the filtering criteria of >50% coverage and a minimum of 3 marker genes per species. ARGs were screened by aligning reads against the ResFinder database using Bowtie2 (coverage >90%), followed by abundance quantification. A co-occurrence network was then constructed using Gephi (v0.10.1). Viral identification was performed by aligning reads against the DRMVirus 2.0 database using Bowtie2, with a coverage of >90%. Fungi and parasites were identified by aligning sequencing reads against a custom-built NCBI mitochondrial genome database (from which host and plant sequences were excluded) using Bowtie2, requiring >50% coverage. All statistical analyses and data visualizations were conducted using R packages, including but not limited to ggplot2, MicrobiotaProcess and Psych. 【Results】 The study revealed the presence of diverse potential pathogenic microorganisms and resistance factors in the arthropod vector samples. Regarding eukaryotes, no parasite sequence was detected in any samples. However, fungi were identified in 26 samples (accounting for 3.72%), including five species that were listed as Category Ⅲ pathogenic fungal species in China’s List of Pathogenic Microorganisms Transmissible to Humans: Candida parapsilosis, Candida subhashii, Cladophialophora bantiana, Fusarium spp. and Lichtheimia hongkongensis, accounting for 0.43%, 0.14%, 0.29%, 0.29% and 0.14%, respectively. At the bacterial level, 134 samples (19.20%) contained sequences identified as pathogenic or opportunistic bacteria, covering 69 bacterial genera. Species with higher detection rates included Enterobacter cancerogenus (7.88%), Klebsiella oxytoca (6.16%) and Escherichia albertii (5.30%). Furthermore, ARGs were widespread and diverse, with 3 109 types identified in total. Tetracycline resistance genes exhibited the highest detection rate (53.58%), and ARG profiles varied significantly between different regions. For instance, the detection rate for tetracycline resistance genes in Switzerland samples reached 94.44%, whereas in Chinese samples, the detection rates for tetracycline and aminoglycoside ARGs were 61.34% and 60.50%, respectively. Co-occurrence network analysis indicated strong associations between certain bacterial genera and ARGs. For instance, the genus Raoultella was identified as a potential host for multiple ARGs (such as fosA and blaPLA-6A ), and fosA may be transmitted via mobile genetic elements (MGEs). In the viral screening, a total of 20 viruses were detected. Of these, Apis mellifera filamentous virus (AmFV) had the highest detection rate (13.90%) and was prevalent in bee colonies from China and Switzerland, with the detection rates of 19.12% and 11.11%, respectively. 【Conclusion】 The results of this study underscore the critical potential role of arthropod vectors in the global dissemination of pathogens and ARGs, highlighting the importance of continuous surveillance and effective control measures for public health risk management.