Pathogen detection in clinical samples based on 16S metagenomic sequencing technology in microbiology laboratories is an important strategy for clinical diagnosis, public health surveillance, and investigations of outbreaks. However, the implementation of the technology is limited by its accuracy and the time required for bioinformatics analysis. Therefore, a simple, standardized, and rapid analysis pipeline from the receipt of clinical samples to the generation of a test report is needed to increase the use of metagenomic analyses in clinical settings. We developed a comprehensive bioinformatics analysis pipeline for the identification of pathogens in clinical samples based on 16S metagenomic sequencing data, named 16SPIP. This pipeline offers two analysis modes (fast and sensitive mode) for the rapid conversion of clinical 16S metagenomic data to test reports for pathogen detection. The pipeline includes tools for data conversion, quality control, merging of paired-end reads, alignment, and pathogen identification. We validated the feasibility and accuracy of the pipeline using a combination of culture and whole-genome shotgun (WGS) metagenomic analyses. 16SPIP may be effective for the analysis of 16S metagenomic sequencing data for real-time, rapid, and unbiased pathogen detection in clinical samples.

Background: Early classification of prokaryotes was based solely on phenotypic similarities, but modern prokaryote characterization has been strongly influenced by advances in genetic methods. With the fast development of the sequencing technology, the ever increasing number of genomic sequences per species offers the possibility for developing distance determinations based on whole-genome information. The average nucleotide identity (ANI), calculated from pair-wise comparisons of all sequences shared between two given strains, has been proposed as the new metrics for bacterial species definition and classification. Results: In this study, we developed the web version of ANItools ( http://ani.mypathogen.cn/ ), which helps users directly get ANI values from online sources. A database covering ANI values of any two strains in a genus was also included (2773 strains, 1487 species and 668 genera). Importantly, ANItools web can automatically run genome comparison between the input genomic sequence and data sequences (Genus and Species levels), and generate a graphical report for ANI calculation results. Conclusion: ANItools web is useful for defining the relationship between bacterial strains, further contributing to the classification and identification of bacterial species using genome data. Database URL:http://ani.mypathogen.cn/

Escherichia coli (E. coli ) is a common microorganism that is widely present in the environment and closely related to human health. The extent of E. coli presence in the human gut has been a subject of ongoing debate. Through whole-genome shotgun metagenomic sequencing, our study revealed that E. coli exists in the human body at a low abundance (average abundance 1.21%), with occasional short-term bursts leading to temporary increases in abundance, with the highest recorded at 50.91%. Further investigations into the factors contributing to these short-term blooms of E. coli showed significant variations in strain types and genomes within fecal samples collected from the same individuals at different time points. Evolutionary tree analysis indicated that samples from different individuals crossed, suggesting a change in the dominant E. coli strains within the human gut. Therefore, it can be inferred that E. coli in the human body are more likely to be transient bacteria rather than permanent residents in the gut. The rapid rate of turnover among months (87.5% within a month) and short-term blooms of E. coli in the human body can establish "latent infections" of nonpathogenic strains in healthy individuals while also posing a potential risk of introducing pathogenic strains, thereby impacting human health. In summary, our study revealed the variation in E. coli abundance and strains within the human gut, influenced by geographic area and temporal factors. These findings contribute to a better understanding of the relationship between E. coli , the gut microbiota, and human health. IMPORTANCE: Escherichia coli (E. coli ) is a microorganism closely linked to human health, and its presence in the human gut has been a topic of debate. Our study, using whole-genome shotgun metagenomic sequencing, revealed that E. coli exists at a low abundance in the human body, with occasional short-term bursts leading to temporary increases. Strain and genome variations were observed within fecal samples from the same individuals at different time points, suggesting transient rather than permanent residence of E. coli in the gut. The rapid turnover rate and short-term blooms of E. coli can establish latent infections while also posing a risk of introducing pathogenic strains. These findings enhance our understanding of the relationship between E. coli , the gut microbiota, and human health.

China accounts for approximately 1/5th of the world’s total population. Differences in environment, ethnicity, and living habits could impart unique features to the structure of the gut microbiota of Chinese individuals.

Advances in high-throughput sequencing have led to unprecedented growth in the amount of available genome sequencing data, especially for bacterial genomes, which has been accompanied by a challenge for the storage and management of such huge datasets. To facilitate bacterial research and related studies, we have developed the Mypathogen database (MPD), which provides access to users for searching, downloading, storing and sharing bacterial genomics data. The MPD represents the first pathogenic database for microbial genomes and metagenomes, and currently covers pathogenic microbial genomes (6604 genera, 11 071 species, 41 906 strains) and metagenomic data from host, air, water and other sources (28 816 samples). The MPD also functions as a management system for statistical and storage data that can be used by different organizations, thereby facilitating data sharing among different organizations and research groups. A user-friendly local client tool is provided to maintain the steady transmission of big sequencing data. The MPD is a useful tool for analysis and management in genomic research, especially for clinical Centers for Disease Control and epidemiological studies, and is expected to contribute to advancing knowledge on pathogenic bacteria genomes and metagenomes. Database URL: http://data.mypathogen.org