{"doi":"10.3389/fbinf.2025.1484113","title":"Using short-read 16S rRNA sequencing of multiple variable regions to generate high-quality results to a species level","abstract":"Introduction: Short-read amplicon sequencing studies have typically focused on 1-2 variable regions of the 16S rRNA gene. Species-level resolution is limited in these studies, as each variable region enables the characterisation of a different subsection of the microbiome. Although long-read sequencing techniques can take advantage of all 9 variable regions by sequencing the entire 16S rRNA gene, short-read sequencing has remained a commonly used approach in 16S rRNA research. This work assessed the feasibility of accurate species-level resolution and reproducibility using a relatively new sequencing kit and bioinformatics pipeline developed for short-read sequencing of multiple variable regions of the 16S rRNA gene. In addition, we evaluated the potential impact of different sample collection methods on our outcomes. Methods: Using xGen™ 16S Amplicon Panel v2 kits, sequencing of all 9 variable regions of the 16S rRNA gene was carried out on an Illumina MiSeq platform. Mock cells and mock DNA for 8 bacterial species were included as extraction and sequencing controls respectively. Within-run and between-run replicate samples, and pairs of stool and rectal swabs collected at 0-5 weeks from the same infants, were incorporated. Observed relative abundances of each species were compared to theoretical abundances provided by ZymoBIOMICS. Paired Wilcoxon rank sum tests and distance-based intraclass correlation coefficients were used to statistically compare alpha and beta diversity measures, respectively, for pairs of replicates and stool/rectal swab sample pairs. Results: Using multiple variable regions of the 16S ribosomal Ribonucleic Acid (rRNA) gene, we found that we could accurately identify taxa to a species level and obtain highly reproducible results at a species level. Yet, the microbial profiles of stool and rectal swab sample pairs differed substantially despite being collected concurrently from the same infants. Conclusion: This protocol provides an effective means for studying infant gut microbial samples at a species level. However, sample collection approaches need to be accounted for in any downstream analysis.","journal":"Frontiers in Bioinformatics","year":2025,"id":540651,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9416,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1344474,"name":"Fadheela Patel","orcid":null,"position":1,"is_corresponding":false},{"id":403920,"name":"Francesca Little","orcid":"0000-0002-5917-9928","position":2,"is_corresponding":false},{"id":63232,"name":"André van der Kouwe","orcid":"0000-0002-2754-6594","position":3,"is_corresponding":false},{"id":1077435,"name":"Mamadou Kaba","orcid":null,"position":4,"is_corresponding":false},{"id":507051,"name":"M. Holmes","orcid":"0000-0001-5873-2405","position":5,"is_corresponding":false},{"id":507050,"name":"Amy S. Graham","orcid":"0000-0002-5956-8341","position":0,"is_corresponding":true}],"reference_count":82,"raw_metadata":null,"created_at":"2026-07-19T02:52:38.861025Z","pmid":"40166373","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}