The next-generation high-throughput sequencing techniques have introduced a new way to assess the gut’s microbial diversity on the basis of 16S rRNA gene-based microbiota analysis. However, the precise appraisal of the biodiversity of Bifidobacterium species within the gut remains a challenging task because of the limited resolving power of the 16S rRNA gene in different species. The groEL gene, a protein-coding gene, evolves quickly and thus is useful for differentiating bifidobacteria. Here, we designed a Bifidobacterium-specific primer pair which targets a hypervariable sequence region within the groEL gene that is suitable for precise taxonomic identification and detection of all recognized species of the genus Bifidobacterium so far. The results showed that the novel designed primer set can specifically differentiate Bifidobacterium species from non-bifidobacteria, and as low as 10⁴ cells of Bifidobacterium species can be detected using the novel designed primer set on the basis of Illumina Miseq high-throughput sequencing. We also developed a novel protocol to assess the diversity of Bifidobacterium species in both human and rat feces through high-throughput sequencing technologies using groEL gene as a discriminative marker.

Dyslipidemia is a well-established risk factor for cardiovascular disease. Serum lipids were affected by several gene polymorphisms, folate, homocysteine and other metabolite levels. We aim to investigate the effects of homocysteine metabolism enzyme polymorphisms (MTHTR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) and their interactions with folate, homocysteine on serum lipid levels in Chinese patients with hypertension. Participants were 480 hypertensive adults that enrolled in September to December 2005 from six different Chinese hospitals (Harbin, Shanghai, Shenyang, Beijing, Xi’an, and Nanjing). Known MTHFR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G genotypes were determined by PCR-RFLP methods. Serum folate was measured by chemiluminescent immunoassay, homocysteine was measured by high-performance liquid chromatography, serum lipids parameters were determined by an automatic biochemistry analyzer, low-density lipoprotein was calculated by Friedewald’s equation. Unitary linear regression model was used to assess the associations of gene polymorphisms, folate and homocysteine on serum lipid profiles. Unconditional logistic regression model was applied to test the interactions of folate, homocysteine and gene polymorphisms on dyslipidemia. No correlations between gene polymorphisms and homocysteine on serum lipid profiles. Compared with normal folate patients, patients with low folate showed higher odds of hypertriglyceridemia (OR = 2.02, 95 % CI: 1.25-3.25, P = 0.004) and low levels of high-density lipoprotein cholesterol (OR = 1.88, 95 % CI: 1.07-3.28, P = 0.027). Each of four gene polymorphisms (MTHTR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) combined with low folate showed higher odds of hypertriglyceridemia (P for trend: 0.049, 0.004, 0.007 and 0.005, respectively). MTHFR C677T and A1298C with low folate showed higher odds of low levels of high-density lipoprotein cholesterol (P for trend: 0.008 and 0.031). Low folate status and homocysteine metabolism gene polymorphisms (MTHTR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) may have a synergistic effect increased the incidence of dyslipidemia in Chinese hypertensive population.

Lactobacillus is a fairly diverse genus of bacteria with more than 260 species and subspecies. Many profiling methods have been developed to carry out phylogenetic analysis of this complex and diverse genus, but limitations remain since there is still a lack of comprehensive and accurate analytical method to profile this genus at species level. To overcome these limitations, a Lactobacillus-specific primer set was developed targeting a hypervariable region in the groEL gene—a single-copy gene that has undergone rapid mutation and evolution. The results showed that this methodology could accurately perform taxonomic identification of Lactobacillus down to the species level. Its detection limit was as low as 10⁴ colony-forming units (cfu)/mL for Lactobacillus species. The assessment of detection specificity using the Lactobacillus groEL profiling method found that Lactobacillus, Pediococcus, Weissella, and Leuconostoc genus could be distinguished, but non-Lactobacillus Genus Complex could not be detected. The groEL gene sequencing and Miseq high-throughput approach were adopted to estimate the richness and diversity of Lactobacillus species in different ecosystems. The method was tested using kurut (fermented yak milk) samples and fecal samples of human, rat, and mouse. The results indicated that Lactobacillus mucosae was the predominant gut Lactobacillus species among Chinese, and L. johnsonii accounted for the majority of lactobacilli in rat and mouse gut. Meanwhile, L. delbrueckii subsp. bulgaricus had the highest relative abundance of Lactobacillus in kurut. Thus, this groEL gene profiling method is expected to promote the application of Lactobacillus for industrial production and therapeutic purpose.

Antibiotic treatment can lead to a loss of diversity of gut microbiota and may adversely affect gut microbiota composition and host health. Previous studies have indicated that the recovery of gut microbes from antibiotic-induced disruption may be guided by specific microbial species. We expect to predict recovery or non-recovery using these crucial species or other indices after antibiotic treatment only when the gut microbiota changes. This study focused on this prediction problem using a novel ensemble learning framework to identify a set of common and reasonably predictive recovery-associated bacterial species (p-RABs), enabling us to predict the host microbiome recovery status under broad-spectrum antibiotic treatment. Our findings also propose other predictive indicators, suggesting that higher taxonomic and functional diversity may correlate with an increased likelihood of successful recovery. Furthermore, to explore the validity of p-RABs, we performed a metabolic support analysis and identified Akkermansia muciniphila and Bacteroides uniformis as potential key supporting species for reconstruction interventions. Experimental results from a C57BL/6J male mouse model demonstrated the effectiveness of p-RABs in facilitating intestinal microbial reconstitution. Thus, we proved the reliability of the new p-RABs and validated a practical intervention scheme for gut microbiota reconstruction under antibiotic disturbance.

The development of antibiotics was a turning point in the history of medicine; however, their misuse and overuse have contributed to the current global epidemic of antibiotic resistance. According to epidemiological studies, early antibiotic exposure increases the risk of immunological and metabolic disorders. This study investigated the effects of exposure to different doses of sulfamethazine (SMZ) on offspring mice and compared the effects of exposure to SMZ on offspring mice in prenatal and early postnatal periods and continuous periods. Furthermore, the effects of SMZ exposure on the gut microbiota of offspring mice were analyzed using metagenome. According to the results, continuous exposure to high-dose SMZ caused weight gain in mice. IL-6, IL-17A, and IL-10 levels in the female offspring significantly increased after high-dose SMZ exposure. In addition, there was a significant gender difference in the impact of SMZ exposure on the gut microbiota of offspring: Continuous high-dose SMZ exposure significantly decreased the relative abundance of Ligilactobacillus murinus, Limosilactobacillus reuteri, Lactobacillus johnsonii, and Bifidobacterium pseudolongum (p < 0.05) in female offspring mice; however, these significant changes were not observed in male offspring mice.