Intestinal microbes play an important role in human health. The development of various clinical diseases, such as obesity, diabetes and cardiovascular disease, is closely related to the imbalance of intestinal microflora. With the development of high?throughput sequencing technology, there has been a breakthrough in the understanding of intestinal microorganism. The interaction between intestinal epithelial cells and intestinal microbes has become one of the hotspots and difficulties of current research. Because of the constraints of ethical review and experimental cost, people are more interested in the development of interaction models between the intestinal microflora and the host cells. In this paper, interaction models between intestinal microflora and host cells, and its working principle and application prospect are reviewed, hoping to provide new techniques and new ideas for studying functions of intestinal microbes.

Intestinal microbes play an important role in human health. The development of various clinical diseases, such as obesity, diabetes and cardiovascular disease, is closely related to the imbalance of intestinal microflora. With the development of high?throughput sequencing technology, there has been a breakthrough in the understanding of intestinal microorganism. The interaction between intestinal epithelial cells and intestinal microbes has become one of the hotspots and difficulties of current research. Because of the constraints of ethical review and experimental cost, people are more interested in the development of interaction models between the intestinal microflora and the host cells. In this paper, interaction models between intestinal microflora and host cells, and its working principle and application prospect are reviewed, hoping to provide new techniques and new ideas for studying functions of intestinal microbes.

Objective:To investigate the cognitive status of fatigue among patients with coronary heart disease (CHD) in the community and analyze its influencing factors.Methods:From May to July 2020, a total of 250 patients with CHD in the community were selected as the research objects by multi-stage sampling method. The general information questionnaire and Fatigue Cognition Questionnaire for Patients with CHD were used for investigation. Multiple linear regression analysis was used to analyze the influencing factors. A total of 250 questionnaires were distributed and 245 were effectively recovered.Results:The total score of fatigue cognition of 245 patients with CHD in the community was 6 (4, 7) . Univariate analysis showed that there were statistically significant differences in the total scores of fatigue cognition among community CHD patients with different education level, duration of disease, grading of cardiac function, whether pay attention to fatigue knowledge, number of combined chronic diseases and treatment methods ( P<0.05) . Multiple linear regression analysis showed that education level, duration of disease, whether pay attention to fatigue knowledge, number of combined chronic diseases and treatment methods were the main influencing factors on fatigue cognition of CHD patients in the community ( P<0.05) . Conclusions:The cognition of patients with CHD in the community on fatigue needs to be improved, and community medical workers should take corresponding measures to increase the attention and active response of patients with CHD to fatigue.

Intestinal microbes play an important role in human health. The development of various clinical diseases, such as obesity, diabetes and cardiovascular disease, is closely related to the imbalance of intestinal microflora. With the development of high-throughput sequencing technology, there has been a breakthrough in the understanding of intestinal microorganism. The interaction between intestinal epithelial cells and intestinal microbes has become one of the hotspots and difficulties of current research. Because of the constraints of ethical review and experimental cost, people are more interested in the development of interaction models between the intestinal microflora and the host cells. In this paper, interaction models between intestinal microflora and host cells, and its working principle and application prospect are reviewed, hoping to provide new techniques and new ideas for studying functions of intestinal microbes.

The research on the relationship between gut microbiota and human health continues to be a hot topic in the field of life science. Culture independent 16S rRNA gene high-throughput sequencing is the current main research method. However, with the reduction of sequencing cost and the maturity of data analysis methods, shotgun metagenome sequencing is gradually becoming an important method for the study of gut microbiome due to its advantages of obtaining more information. With the support from the human microbiome project, 30 805 metagenome samples were sequenced in the United States. By searching NCBI PubMed and SRA databases, it was found that 72 studies collecting about 10 000 Chinese intestinal samples were used for metagenome sequencing. To date, only 56 studies were published, including 16 related to metabolic diseases, 16 related to infectious and immune diseases, and 12 related to cardiovascular and cerebrovascular diseases. The samples were mainly collected in Beijing, Guangzhou, Shanghai and other cosmopolitan cities, where great differences exist in sequencing platforms and methods. The outcome of most studies are based on correlation analysis, which has little practical value in guiding the diagnosis and treatment of clinical diseases. Standardizing sampling methods, sequencing platform and data analysis process, and carrying out multi center parallel research will contribute to data integration and comparative analysis. Moreover, insights into the functional verification and molecular mechanism by using the combination of transcriptomics, proteomics and culturomics will enable the gut microbiota research to better serve the clinical diagnosis and treatment.
China ; Gastrointestinal Microbiome/genetics* ; Humans ; Metagenome ; Microbiota ; RNA, Ribosomal, 16S/genetics* ; United States

Antimicrobial resistance is on the rise while the number of antibiotics being brought to market continues to drop. Drug-resistant genes and drug-resistant bacteria infection have seriously threatened human health. Therefore, antimicrobial resistance presents an ongoing challenge that requires multifaceted approaches including: biomedical innovation; improved surveillance of antibiotic consumption and antimicrobial resistance generated rates; prevention of health-care-associated infections and transmission of multidrug-resistant bacteria and environmental dissemination; rapid microbiological diagnosis; and curtailed clinical and veterinary misuse. Fortunately, combating antimicrobial resistance has been highly valued and supported by the government, scientists and entrepreneurs of various countries. With the continuous introduction of new technologies, new products, and new management measures, the problem of antimicrobial resistance must be controlled and alleviated.

Genome sequences of 4 644 representative strains from human gut microbiota were analyzed to mine gene clusters for biosynthesis of novel secondary metabolites, as well as genes encoding antibiotic resistance and virulence factors. AntiSMASH analysis showed that more than 60% of the representative strains encoded at least one secondary metabolite gene cluster, and 8 potential novel secondary metabolite gene clusters were identified from 8 unculturable bacteria. The secondary metabolite gene clusters in human intestine are mainly composed of nonribosomal peptide synthetase (NRPS), bacteriocin, arylpolyene, terpene, betalactone and NRPS like gene clusters distributed in Clostridia, Bacilli, Gammaproteobacteria, Bacteroidia, Actinobacteria and Negativicutes. PathoFact analysis showed that genes encoding antibiotic resistance and virulence factors are widely distributed in representative strains, but the frequency encoded by potential pathogens is significantly higher than that of non-potential pathogens. The frequency of genes encoding secretory toxins such as outer membrane protein, PapC N-terminal domain, PapC C-terminal domain, peptidase M16 inactive domain, and non-secretory toxins such as nitroreductase family, AcrB/AcrD/AcrF family, PLD-like domain, Cupin domain, putative hemolysin, S24-like peptidase, phosphotransferase enzyme family, endonuclease/ exonuclease/ phosphatase family, glyoxalase/ bleomycin resistance was high in potential pathogens. This study may facilitate mining new microbial natural products from the intestinal microbiome, understanding the colonization and infection mechanism of intestinal microorganisms, and providing targeted prevention and treatment of intestinal microbial related diseases.
Humans ; Virulence ; Multigene Family ; Bacteria ; Drug Resistance, Microbial ; Virulence Factors ; Peptide Hydrolases