Temporal dynamics and species-level complexity of Prevotella spp. in the human gut microbiota: implications for enterotypes and health.

The concept of "enterotypes" in microbiome research has attracted substantial interest, particularly focusing on the abundance of Prevotella spp. in the human gut. In this study, the intricate dynamics of Prevotella spp. in the human gut microbiota was investigated, based on the metagenomic method. First, 239 fecal samples from individuals across four regions of China revealed a bimodal distribution, highlighting the abundance and variability in Prevotella spp. within the Chinese population. Second, the longitudinal cohort study included 184 fecal samples from 52 time points collected from seven individuals who demonstrated either the outbreaks or disappearances of Prevotella spp., emphasizing the transient nature of Prevotella abundance levels and suggesting shifts in Prevotella "enterotypes." Furthermore, a turnover of the dominant Prevotella spp. was observed, indicating the potential presence of diverse subtypes of Prevotella enterotype. Notably, the genomic analysis demonstrated the persistence of specific Prevotella strains within individuals over extended periods, highlighting the enduring presence of Prevotella in the human gut. In conclusion, by integrating the temporal and geographical scales in our research, we gained deeper insights into the dynamics of Prevotella, emphasizing the importance of considering the dynamics at the time and species level in gut microbiota studies and their implications on human health.

Rapid turnover and short-term blooms of Escherichia coli in the human gut.

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.

Genetic characteristics of Blastocystis sp. ST3 at the genome level in the Chinese population.

The gut microbiota comprises the collective genomes of microbial symbionts and is composed of bacteria, fungi, viruses, and protists within the gastrointestinal tract of a host. Although the literature associated with gut microbiota is increasing, studies on eukaryotes in the human gut are just beginning to surface. Blastocystis is one of the most common intestinal parasites of humans and animals and is estimated to colonise more than 1 billion people on a global scale. However, the understanding of the genetic characteristics of Blastocystis subtype (ST) at the genome level and its relationship with other members of the gut microbiota is still limited. In this study, by surveying the prevalence and genome characteristics of Blastocystis sp. ST3 in a Chinese population (prevalence % = 6.09%), the association of Blastocystis sp. ST3 with region and time and the structure of the resident gut bacterial population was clarified. We identified novel sequences (50 mitochondrial and 41 genome sequences) and determined their genetic diversity amongst strains within Blastocystis sp. ST3 (4.14 SNPs/kb). Furthermore, we found that colonisation of Blastocystis was strongly associated with increased bacterial richness and higher abundance of several anaerobes. Finally, we performed time series sampling on two Blastocystis-positive individuals and confirmed that Blastocystis could exist continually in the human gut microbiota and persist for a long time, even for 4 years.

Time-scale analysis of the long-term variability of human gut microbiota characteristics in Chinese individuals.

Studying the dynamics and stability of the human gut microbiota over time is important for exploring their relationship with human health and developing treatment strategies for putative microbiome-related ailments. Here, we collected stool samples from seven healthy Chinese subjects at 1-month intervals between 2016 and 2020. Sequencing and bioinformatics analyses revealed that the bacteria in the collected fecal samples fluctuated over time, and the extent of these changes increased over time. Further, the average shared proportion value obtained using Sourcetracker2 was 63.5% for samples collected from the same individual in the preceding month, and over a 3-year period, this value decreased to 40.7%. Furthermore, the proportion of different bacteria in the gut microbiota of the different subjects fluctuated to varying degrees. Therefore, our results suggested that it is important to consider the effect of time on gut microbiota composition when it is used to evaluate health. Our study opens up a new field of microbiota research, considering not just the instantaneous microbiota, but also the change of the gut microbiota over time.

The Spatial Features and Temporal Changes in the Gut Microbiota of a Healthy Chinese Population.

In this study, we aimed to understand the characteristics of the gut microbial composition in a healthy Chinese population and to evaluate if they differed across different regions. In addition, we aimed to understand the changes in the gut microbial composition over time. We collected 239 fecal samples from healthy Chinese adults living in four regions and performed a 1-year time cohort study in a small population in Beijing. The Chinese gut microbiota share 34 core bacterial genera and 39 core bacterial species, which exist in all collected samples. Several disease-related microorganisms (DRMs), virulence factors, and antibiotic resistance genes were found in one or more healthy Chinese samples. Differences in gut microbiota were observed in samples from different regions, locations, individuals, and time points. Compared to other factors, time was associated with a lower degree of change in the gut microbiota. Our findings revealed spatial and temporal changes in the gut microbiota of healthy Chinese individuals. Compared to fecal microbiomes of 152 samples in the publicly released the Human Microbiome Project (HMP) project from the United States, samples in this study have higher variability in the fecal microbiome, with higher richness, Shannon diversity indices, and Pielou evenness indexes, at both the genus and species levels. The microbiota data obtained in this study will provide a detailed basis for further understanding the composition of the gut microbiota in the healthy Chinese population. IMPORTANCE 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. In 2016, we started to investigate healthy Chinese people and their gut microbiomes. Phase I results for 16S rRNA amplicons have been released. However, owing to the limitations of 16S rRNA amplicon sequencing, the gut microbiome of a healthy Chinese population could not be examined thoroughly at the species level, and the detailed changes in the gut microbiota over time need to be investigated. To address these knowledge gaps, we started a phase II study and investigated the basis for variations in the gut microbiome composition in a healthy Chinese population at the species level using shotgun metagenomics technology. In the phase II study, we also conducted a time scale analysis of fecal samples from healthy Chinese subjects, as a pioneered study, which quantitatively clarified the changes in the gut microbiota at both the spatial and temporal levels and elucidated the distribution pattern of DRMs in healthy Chinese individuals.

MDACP: A Pathogen Genome and Metagenome Analysis Cloud Platform.

Pathogenic microorganism analysis based on next-generation sequencing technology is an important tool for clinical diagnosis, public health surveillance, and outbreak investigation. However, scientific researchers without the relevant background lack the time, training, or infrastructure to use large data sets or install and use command line tools. Therefore, the bioinformatic team at the Chinese Center for Disease Control and Prevention developed the Microbial Data Analysis Cloud Platform (MDACP) as a safe, professional, and efficient pathogen genetic data analysis platform for rapid microbial data mining, such as for candidate pathogen detection, genome typing, and traceability. MDACP is a web service system based on the Docker platform and can be used for data analysis on various operating systems. The platform focuses on pathogen analysis and continuously develops new analysis processes according to the analysis needs of the users. This platform has a friendly user interface and is easy to operate, allowing users to submit data through data pages or graphical clients, flexibly control parameters according to data conditions, and analyze data in parallel with multiple tasks. Researchers can quickly carry out bioinformatic analyses without coding work, promote follow-up research and information mining of projects, and improve the utilization of big data in the field of disease control. MDACP enables research personnel to conduct data analysis and management and assists clinicians and disease control personnel with mining information, such as pathogen identification, classification, and traceability.

[A new quantitative 16S rRNA amplicon sequencing method].

In recent years, 16S rRNA amplicon sequencing technology has been widely used to study human gut microbiota and to detect unknown pathogens in clinical samples. However, its resolution to bacterial population can only reach the relative abundance of genus level, and different factors affect the final bacterial profile, such as sample concentrations, PCR cycle numbers and amplification primers. In order to solve these problems, we developed a quantitative 16S rRNA amplicon sequencing method by combining random tag and internal marker method. The new methods improved the accuracy of human gut microbiota, reduced the impact of experimental operation on the results, and improved the comparability between sequencing and other molecular biological methods.

Gut microbiota community characteristics and disease-related microorganism pattern in a population of healthy Chinese people.

China's population accounts for about 1/5th of the world's total population. Owing to differences in environment, race, living habits, and other factors, the structure of the intestinal flora of Chinese individuals is expected to have unique features; however, this has not been thoroughly examined. Here, we collected faecal samples from healthy adults living in three cities of China and investigated their gut microbiome using metagenomics and bioinformatics technology. We found that 11 core bacterial genera were present in all of the Chinese faecal samples; moreover, several patient characteristics (age, region, body mass index, physical exercise, smoking habits, and alcoholic drink, and yogurt consumption) were found to have different effects on the gut microbiome of healthy Chinese people. We also examined the distribution patterns of disease-related microorganisms (DRMs), revealing which DRMs can potentially be used as markers for assessment of health risk. We also developed a program called "Guthealthy" for evaluating the health status associated with the microbiome and DRM pattern in the faecal samples. The microbiota data obtained in this study will provide a basis for a healthy gut microbiome composition in the Chinese population.

MPD: a pathogen genome and metagenome database.

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.

16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 16SPIP may be effective for the analysis of 16S metagenomic sequencing data for real-time, rapid, and unbiased pathogen detection in clinical samples.

Genomic study of the Type IVC secretion system in Clostridium difficile: understanding C. difficile evolution via horizontal gene transfer.

Clostridium difficile, the etiological agent of Clostridium difficile infection (CDI), is a gram-positive, spore-forming bacillus that is responsible for ∼20% of antibiotic-related cases of diarrhea and nearly all cases of pseudomembranous colitis. Previous data have shown that a substantial proportion (11%) of the C. difficile genome consists of mobile genetic elements, including seven conjugative transposons. However, the mechanism underlying the formation of a mosaic genome in C. difficile is unknown. The type-IV secretion system (T4SS) is the only secretion system known to transfer DNA segments among bacteria. We searched genome databases to identify a candidate T4SS in C. difficile that could transfer DNA among different C. difficile strains. All T4SS gene clusters in C. difficile are located within genomic islands (GIs), which have variable lengths and structures and are all conjugative transposons. During the horizontal-transfer process of T4SS GIs within the C. difficile population, the excision sites were altered, resulting in different short-tandem repeat sequences among the T4SS GIs, as well as different chromosomal insertion sites and additional regions in the GIs.

T4SP Database 2.0: An Improved Database for Type IV Secretion Systems in Bacterial Genomes with New Online Analysis Tools.

Type IV secretion system (T4SS) can mediate the passage of macromolecules across cellular membranes and is essential for virulent and genetic material exchange among bacterial species. The Type IV Secretion Project 2.0 (T4SP 2.0) database is an improved and extended version of the platform released in 2013 aimed at assisting with the detection of Type IV secretion systems (T4SS) in bacterial genomes. This advanced version provides users with web server tools for detecting the existence and variations of T4SS genes online. The new interface for the genome browser provides a user-friendly access to the most complete and accurate resource of T4SS gene information (e.g., gene number, name, type, position, sequence, related articles, and quick links to other webs). Currently, this online database includes T4SS information of 5239 bacterial strains. Conclusions. T4SS is one of the most versatile secretion systems necessary for the virulence and survival of bacteria and the secretion of protein and/or DNA substrates from a donor to a recipient cell. This database on virB/D genes of the T4SS system will help scientists worldwide to improve their knowledge on secretion systems and also identify potential pathogenic mechanisms of various microbial species.

Genotyping of Klebsiella Pneumonia Strains Isolated from Eldly Inpatients by Multiple-locus Variable-number Tandem-repeat Analysis.

Objective To investigate the genotype of klebsiella pneumonia strains isolated from eldly inpatients by multiple-locus variable-number tandem-repeat analysis. Methods Totally 184 klebsiella pneumonia strains,isolated from eldly inpatients,were collected,and their genome DNA were extracted. The polymorphism of 7 variable-number tandem-repeat locus in the DNA samples was analyzed by multiple primers polymerase chain reaction and capillary electrophoresis. The clustering analysis of genotyping was carried out with the BioNumerics 5.1 software. Results A total of 139 genotypes were identified in 184 klebsiella pneumonia clinical strains,showing obvious genetic polymorphisms. With clustering analysis of genotypes,all the strains were categorized into three gene clusters (genogroups 1,2,and 3). The genogroup 1 was the biggest cluster,containing 93.06% of the isolated strains. Conclusion There was a predominant cluster in the klebsiella pneumonia strains isolated from eldly inpatients in our center,and the major source of klebsiella pneumonia infection remained the nosocomial infection.

Nosocomial transmission of Clostridium difficile ribotype 027 in a Chinese hospital, 2012-2014, traced by whole genome sequencing.

BACKGROUND: The rapid spread of Clostridium difficile NAP1/BI/027 (C. difficile 027) has become one of the leading threats of healthcare-associated infections worldwide. However, C. difficile 027 infections have been rarely reported in Asia, particularly in China. RESULTS: In this study, we identified a rare C. difficile bloodstream infection (BSI) from three isolates of a patient during repeated hospital admission. This finding triggered a retrospective epidemiological study to scan all cases and strains emerged from this ward during the past three years. Using medical personnel interviews, medical record reviews and the genomic epidemiology, two outbreaks in 2012 and 2013-2014 were identified. Through using whole genome sequencing, we succeeded to trace the origin of the BSI strain. Surprisingly, we found the genome sequences were similar to C. difficile 027 strain R20291, indicating the occurrence of a rare C. difficile 027 strain in China. Integrated epidemiological investigation and whole genome sequencing of all strains, we constructed a nosocomial transmission map of these two C. difficile 027 outbreaks and traced the origin of the infection. CONCLUSIONS: By genome sequencing, spatio-temporal analysis and field epidemiology investigation, we can estimate their complex transform network and reveal the possible modes of transmission in this ward. Based on their genetic diversity, we can assume that the toilets, bathroom, and janitor's equipment room may be contaminated area, which may be suggested to improve infection control measures in the following health care.

ANItools web: a web tool for fast genome comparison within multiple bacterial strains.

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/.