Assessment of bacterial and viral gut communities in healthy and tumoral colorectal tissue using RNA and DNA deep sequencing.

BACKGROUND: Colorectal cancer (CRC) is known to present a distinct microbiome profile compared to healthy mucosa. Non-targeted deep-sequencing strategies enable nowadays full microbiome characterization up to species level. AIM: We aimed to analyze both bacterial and viral communities in CRC using these strategies. MATERIALS & METHODS: We analyzed bacterial and viral communities using both DNA and RNA deep-sequencing (Novaseq) in colorectal tissue specimens from 10 CRC patients and 10 matched control patients. Following taxonomy classification using Kraken 2, different metrics for alpha and beta diversities as well as relative and differential abundance were calculated to compare tumoral and healthy samples. RESULTS: No viral differences were identified between tissue types, but bacterial species Polynucleobacter necessarius had a highly increased presence for DNA in tumors (p = 0.001). RNA analyses showed that bacterial species Arabia massiliensis had a highly decreased transcription in tumors (p = 0.002) while Fusobacterium nucleatum transcription was highly increased in tumors (p = 0.002). DISCUSSION: Sequencing of both DNA and RNA enables a wider perspective of micriobiome profiles. Lack of RNA transcription (Polynucleobacter necessarius) casts doubt on possible role of a microorganism in CRC. The association of F. nucleatum mainly with transcription, may provide further insights on its role in CRC. CONCLUSION: Joint assessment of the metagenome (DNA) and the metatranscriptome (RNA) at the species level provided a huge coverage for both bacteria and virus and identifies differential specific bacterial species as tumor associated.

Using HPV-meta for human papillomavirus RNA quality detection.

In the era of cervical cancer elimination, accurate and validated pipelines to detect human papillomavirus are essential to elucidate and understand HPV association with human cancers. We aimed to provide an open-source pipeline, "HPV-meta", to detect HPV transcripts in RNA sequencing data, including several steps to warn operators for possible viral contamination. The "HPV-meta" pipeline automatically performs several steps, starting with quality trimming, human genome filtering, HPV detection (blastx), cut-off settlement (10 reads and 690 bp coverage to make an HPV call) and finishing with fasta sequence generation for HPV positive samples. Fasta sequences can then be aligned to assess sequence diversity among HPV positive samples. All RNA sequencing files (n = 10,908) present in the cancer genome atlas (TCGA) were analyzed. "HPV-meta" identified 25 different HPV types being present in 488/10,904 specimens. Validation of results showed 99.98% agreement (10,902/10,904). Multiple alignment from fasta files warned about high sequence identity between several HPV 18 and 38 positive samples, whose contamination had previously been reported. The "HPV-meta" pipeline is a robust and validated pipeline that detects HPV in RNA sequencing data. Obtaining the fasta files enables contamination investigation, a non very rare occurrence in next generation sequencing.