Non-invasive early detection on esophageal squamous cell carcinoma and precancerous lesions by microbial biomarkers combining epidemiological factors in China.

BACKGROUND: Microbiota may be associated with esophageal squamous cell carcinoma (ESCC) development. However, it is not known the predictive value of microbial biomarkers combining epidemiological factors for the early detection of ESCC and precancerous lesions. METHODS: A total of 449 specimens (esophageal swabs and saliva) were collected from 349 participants with different esophageal statuses in China to explore and validate ESCC-associated microbial biomarkers from genes level to species level by 16S rRNA sequencing, metagenomic sequencing and real-time quantitative polymerase chain reaction. RESULTS: A bacterial biomarker panel including Actinomyces graevenitzii (A.g_1, A.g_2, A.g_3, A.g_4), Fusobacteria nucleatum (F.n_1, F.n_2, F.n_3), Haemophilus haemolyticus (H.h_1), Porphyromonas gingivalis (P.g_1, P.g_2, P.g_3) and Streptococcus australis (S.a_1) was explored by metagenomic sequencing to early detect the participants in Need group (low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia and ESCC) vs participants without these lesions as the Noneed group. Significant quantitative differences existed for each microbial target in which the detection efficiency rate was higher in saliva than esophageal swab. In saliva, the area under the curve (AUC) based on the microbial biomarkers (A.g_4 ∩ P.g_3 ∩ H.h_1 ∩ S.a_1 ∩ F.n_2) was 0.722 (95% CI 0.621-0.823) in the exploration cohort. Combining epidemiological factors (age, smoking, drinking, intake of high-temperature food and toothache), the AUC improved to 0.869 (95% CI 0.802-0.937) in the exploration cohort, which was validated with AUC of 0.757 (95% CI 0.663-0.852) in the validation cohort. CONCLUSIONS: It is feasible to combine microbial biomarkers in saliva and epidemiological factors to early detect ESCC and precancerous lesions in China.

Characterization of the Genitourinary Microbiome of 1,165 Middle-Aged and Elderly Healthy Individuals.

Accumulated evidence shows that complex microbial communities resides in the healthy human urinary tract and can change in urological disorders. However, there lacks a comprehensive profiling of the genitourinary microbiota in healthy cohort. Here, we performed 16S rRNA gene sequencing of midstream urine specimens from 1,172 middle-aged and elderly healthy individuals. The core microbiota included 6 dominant genera (mean relative abundance >5%), including Prevotella, Streptococcus, Lactobacillus, Gardnerella, Escherichia-Shigella, and Veillonella, and 131 low-abundance genera (0.01-5%), displaying a distinct microbiome profiles to that of host-matched gut microbiota. The composition and diversity of genitourinary microbiome (GM) were distinct between genders and may fluctuate with ages. Several urotypes were identified by the stratification of microbiome profiles, which were mainly dominated by the six most predominant genera. The prevalence of urotypes was disparate between genders, and the male sample additionally harbored other urotypes dominated by Acinetobacter, Corynebacterium, Staphylococcus, or Sphingomonas. Peptoniphilus, Ezakiella, and Porphyromonas were co-occurred and co-abundant, and they may play crucial roles as keystone genera and be associated with increased microbial diversity. Our results delineated the microbial structure and diversity landscape of the GM in healthy middle-aged and elderly adults and provided insights into the influence of gender and age to it.