Evaluation of Faecalibacterium 16S rDNA genetic markers for accurate identification of swine faecal waste by quantitative PCR

Coexistence of antibiotic resistance genes, fecal bacteria, and potential pathogens in anthropogenically impacted water

Microbial indicators are often used to monitor microbial safety of aquatic environments. However, information regarding the correlation between microbial indicators and ecotoxicological factors such as potential pathogens and antibiotic resistance genes (ARGs) in anthropogenically impacted waters remains highly limited. Here, we investigated the bacterial community composition, potential pathogens, ARGs diversity, ARG hosts, and horizontal gene transfer (HGT) potential in urban river and wastewater samples from Chaohu Lake Basin using 16S rRNA and metagenomic sequencing. The composition of the microbial community and potential pathogens differed significantly in wastewater and river water samples, and the total relative abundance of fecal indicator bacteria was positively correlated with the total relative abundance of potential pathogens (p < 0.001 and Pearson's r = 0.758). Network analysis indicated that partial ARG subtypes such as dfrE, sul2, and PmrE were significantly correlated with indicator bacteria (p < 0.05 and Pearson's r > 0.6). Notably, Klebsiella was the indicator bacteria significantly correlated with 4 potential pathogens and 14 ARG subtypes. ARGs coexisting with mobile gene elements were mainly found in Thauera, Pseudomonas, Escherichia, and Acinetobacter. Next-generation sequencing (NGS) can be used to conduct preliminary surveys of environmental samples to access potential health risks, thereby facilitating water resources management.

Homogeneous selection drives antibiotic resistome in two adjacent sub-watersheds, China

Rivers are a significant reservoir of antibiotic resistance genes (ARGs), yet the biogeographic pattern of riverine ARGs and its underlying driving forces remain poorly understood. Here, we used metagenomic approach to investigate the spatio-temporal variation of ARGs in two adjacent sub-watersheds viz. North River (NR) and West River (WR), China. The results demonstrated that Bacitracin (22.8 % of the total ARGs), multidrug (20.7 %), sulfonamide (15.2 %) and tetracycline (10.9 %) were the dominant ARG types. SourceTracker analysis indicated that sewage treatment plants as the main source of ARGs, while animal feces mainly contributed in spreading the ARGs in the upstream of NR. Random forest and network analyses confirmed that NR was under the influence of fecal pollution. PCoA analysis demonstrated that the composition of ARGs changed along with the anthropogenic gradients, while the Raup-Crick null model showed that homogenizing selection mediated by class 1 integron intI1 resulted in stable ARG communities at whole watershed scale. Structural equation models revealed that microbial community, grassland and several non-antibiotic micropollutants may also play certain roles in influencing the distribution of ARGs. Overall, the observed deterministic formation of ARGs in riverine systems calls effective management strategies to mitigate the risks of antibiotic resistance on public health.

Application of a Faecalibacterium 16S rDNA genetic marker for species identification of dog fecal waste

A dog-associated 16S rDNA genetic marker (ED-1) was designed to detect dog fecal contamination in water through a comparative bioinformatics analysis of Faecalibacterium sequences. For the dog fecal samples, ED-1 had 100% specificity, a high positive rate (89% in dog feces and 92.3% in dog fecal-contaminated water samples), and a low detection limit (10⁷ copies/100 mL) in dog-contaminated water samples. Detection of water samples from seven provinces or cities of China showed that ED-1 was stable enough to be applied in practice. Furthermore, the abundance and diversity of dog gut microbiota from two private house pets (PHP) and Third Military Medical University (TMMU) dogs were estimated by using operational taxonomic units, and the significant differences of dog feces were found, as the PHP dogs have a more diverse diet and closer contact with human than dogs in TMMU. However, ED-1 could detect the feces from the two regions, indicating that ED-1 has good reliability.

Variations in Oral Microbiota Composition Are Associated With a Risk of Throat Cancer

In this study, a next-generation sequencing strategy on 16S ribosomal RNA (16S rRNA) gene was employed to analyze 70 oral samples from 32 patients with throat cancer, nine patients with vocal cord polyp, and 29 healthy individuals (normal controls). Using this strategy, we demonstrated, for the first time, that the salivary microbiota of cancer patients were significantly different from those of patients with a polyp and healthy individuals. We observed that the beta diversity of the cancer group was divergent from both the normal and polyp groups, while alpha-diversity indices such as the Chao1 estimator (P = 8.1e-05), Simpson (P = 0.0045), and Shannon (P = 0.0071) were significantly reduced in cancer patients compared with patients containing a polyp and normal healthy individuals. Linear discriminant analysis (LDA) and Kruskal–Wallis test analyses and real-time quantitative polymerase chain reaction (qPCR) verification test revealed that the genera Aggregatibacter, Pseudomonas, Bacteroides, and Ruminiclostridium were significantly enriched in the throat cancer group compared with the vocal cord polyp and normal control groups (score value >2). Finally, diagnostic models based on putatively important constituent bacteria were constructed with 87.5% accuracy [area under the curve (AUC) = 0.875, 95% confidence interval (CI): 0.695–1]. In summary, in this study we characterized, for the first time, the oral microbiota of throat cancer patients without smoking history. We speculate that these results will help in the pathogenic mechanism and early diagnosis of throat cancer.