20.500.12556/DiRROS-28972 Bioinformatic challenges in metagenomic next generation sequencing data analysis while unravelling a case of uncommon campylobacteriosis Objective: This study aimed to employ advanced bioinformatics and modern sequencing approaches to solve a diagnostic problem of persistent Campylobacter spp. molecular detection yet negative culture results from four consecutive stool samples of a previously healthy patient with newly diagnosed selective IgA deficiency and prolonged diarrhoea. Methods: Metagenomic next-generation sequencing (mNGS) based on short-paired end reads with basic bioinformatic read classification analysis was used at first. Due to ambiguous results, advanced bioinformatics involving contigs construction and classification, reference genome mappings and reads filtering with BBSplit, additionally coupled with metagenomic long-reads sequencing and Full-length 16S rRNA metabarcoding were employed to further elucidate the results. Virulence factors were analysed using the Prokka Genome Annotation tool. Modified classical bacteriology methods were finally used for further clarification. Results: Short-pair end reads analysis identified several Campylobacter species in all four samples. After advanced bioinformatic approaches were applied, candidatus C. infans was suspected as the putative pathogen. This result was further supported by metagenomic long-reads sequencing and Full-length 16S rRNA metabarcoding. Nevertheless, after modifying the culture conditions based on mNGS results, a mixed culture of candidatus C. infans and C.ureolyticus was obtained. Sequencing of the mixed culture resulted in an 87.48% and 73.47% genome coverage of candidatus C. infans and C. ureolyticus, respectively. In the candidatus C. infans genome more virulence factors hits were found than in the C. ureolyticus genome thus supporting the first as the most probable cause of symptoms. Conclusion: This study shows the pivotal role and strengths of mNGS in unravelling an unusual case of diarrhoea and demonstrates how mNGS can guide established microbiological methods to improve on current limitations. However, it also emphasises the need for careful interpretation of sequencing data, particularly for closely related bacterial species from clinical samples that are known to support complex microbial communities. 16S rRNA metabarcoding bioinformatics campylobacter metagenomics NGS metačrtno kodiranje 16S rRNA bioinformatika kampilobakter metagenomika true false true Angleški jezik Slovenski jezik Neznano 2026-04-15 12:36:05 2026-04-15 12:36:06 2026-04-16 04:06:21 0000-00-00 00:00:00 2025 0 0 Nasl. z nasl. zaslona; Opis vira z dne 27. 5. 2025; str. 1-7 iss. [article no.] 104841 Vol. 166 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 659.2:004 1532-0480 10.1016/j.jbi.2025.104841 237243395 RAZ_Kogoj_Rok_2025.pdf RAZ_Kogoj_Rok_2025.pdf 1 A1CB566DD0D223B35F18952D7943895B e4267cb741c06bfa27191f4a2f2a2d1be879f7a54f476717b487fc590b41a5e8 3d9f3e33-38b7-11f1-9cc3-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=43235 https://www.sciencedirect.com/science/article/pii/S153204642500070X?via%3Dihub 1 ea15a309-38b6-11f1-9cc3-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=43234 Univerzitetni klinični center Ljubljana 0 0 0