Untangling Species-Level Composition of Complex Bacterial Communities through a Novel Metagenomic Approach

Abstract

16S small-subunit (SSU) rRNA gene-based bacterial profiling is the gold standard for cost-effective taxonomic reconstruction of complex bacterial populations down to the genus level. However, it has been proven ineffective in clinical and research settings requiring higher taxonomic resolution. We therefore developed a bacterial profiling method based on the internal transcribed spacer (ITS) region employing optimized primers and a comprehensive ITS database for accurate cataloguing of bacterial communities at (sub)species resolution. Performance of the microbial ITS profiling pipeline was tested through analysis of host-associated, food, and environmental matrices, while its efficacy in clinical settings was assessed through analysis of mucosal biopsy specimens of colorectal cancer, leading to the identification of putative novel biomarkers. The data collected indicate that the proposed pipeline represents a major step forward in cost-effective identification and screening of microbial biomarkers at (sub)species level, with relevant impact in research, industrial, and clinical settings. IMPORTANCE We developed a novel method for accurate cataloguing of bacterial communities at (sub)species level involving amplification of the internal transcribed spacer (ITS) region through optimized primers, followed by next-generation sequencing and taxonomic classification of amplicons by means of a comprehensive database of bacterial ITS sequences. Host-associated, food, and environmental matrices were employed to test the performance of the microbial ITS profiling pipeline. Moreover, mucosal biopsy samples from colorectal cancer patients were analyzed to demonstrate the scientific relevance of this profiling approach in a clinical setting through identification of putative novel biomarkers. The results indicate that the ITS-based profiling pipeline proposed here represents a key metagenomic tool with major relevance for research, industrial, and clinical settings.

Beating Naive Bayes at Taxonomic Classification of 16S rRNA Gene Sequences

“…4. Longer read lengths and/or marker-gene targets (Johnson et al, 2019;Milani et al, 2020) 5. Improvements are not limited to accuracy, and could include more efficient classifiers with less runtime, memory, or other resource requirements (Bokulich et al, 2020).…”

HiTaC: a hierarchical taxonomic classifier for fungal ITS sequences compatible with QIIME2

“…In our view, it is challenging to rely on ITS markers alone to classify fungi at the species level, given the current limitations in ITS databases such as low quality sequencing and misidentifications (Badotti et al ., 2017). Nevertheless, ITS has been successfully employed to accurately catalogue bacterial communities at (sub)species resolution (Milani et al ., 2020). Moreover, from an ecological perspective, it is interesting to use amplicon sequencing in addition to shotgun due to the fact that it can more accurately reflect the composition of microbiomes, as well as taxonomic abundance and richness, especially at higher ranks (Tessler et al ., 2017).…”

Towards standardized and reproducible research in skin microbiomes

“…Here, a section covering a few hundred nucleotides of the highly conserved 16S ribosomal RNA gene is amplified and sequenced with HTS (Klindworth et al ., 2013 ). Recently, amplicon sequencing of the nuclear ribosomal internal transcribed spacer (ITS) region has also been used to obtain (sub)species resolution of bacterial communities (Milani et al ., 2020 ). ITS‐based profiling might thus serve as a viable alternative for 16S rRNA‐based profiling of bacterial communities in the future.…”