Mechanisms Driving Microbial Community Composition in Anaerobic Co-Digestion of Waste-Activated Sewage Sludge

Prevalence, Antimicrobial Resistance and Toxin-Encoding Genes of Clostridioides difficile from Environmental Sources Contaminated by Feces

Clostridioides difficile (C. difficile) is the most common pathogen causing antibiotic-associated intestinal diseases in humans and some animal species, but it can also be present in various environments outside hospitals. Thus, the objective of this study was to investigate the presence and the characteristics of toxin-encoding genes and antimicrobial resistance of C. difficile isolates from different environmental sources. C. difficile was found in 32 out of 81 samples (39.50%) after selective enrichment of spore-forming bacteria and in 45 samples (55.56%) using a TaqMan-based qPCR assay. A total of 169 C. difficile isolates were recovered from those 32 C. difficile-positive environmental samples. The majority of environmental C. difficile isolates were toxigenic, with many (88.75%) positive for tcdA and tcdB. Seventy-four isolates (43.78%) were positive for binary toxins, cdtA and cdtB, and 19 isolates were non-toxigenic. All the environmental C. difficile isolates were susceptible to vancomycin and metronidazole, and most isolates were resistant to ciprofloxacin (66.86%) and clindamycin (46.15%), followed by moxifloxacin (13.02%) and tetracycline (4.73%). Seventy-five isolates (44.38%) showed resistance to at least two of the tested antimicrobials. C. difficile strains are commonly present in various environmental sources contaminated by feces and could be a potential source of community-associated C. difficile infections.

Microbiome Analysis via OTU and ASV-Based Pipelines-A Comparative Interpretation of Ecological Data in WWTP Systems

Linking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service.