Optimization of DNA extraction from prostate tissue for metagenomic sequencing
Hirva, Petteri (2025-05-27)
Optimization of DNA extraction from prostate tissue for metagenomic sequencing
(27.05.2025)
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2025061065755
https://urn.fi/URN:NBN:fi-fe2025061065755
Tiivistelmä
The gut microbiome composition of prostate cancer patients has been observed to differ from that of healthy patients. A limited number of studies have shown that the prostate may harbor a unique microbiome, which could contribute to the development of prostate cancer. However, a reliable method for determining tissue microbiota is still lacking. Next generation sequencing of the 16S rRNA gene and the whole DNA in Shotgun Metagenomic Sequencing are most often used for microbiome composition analysis, but both methods have known experimental and computational challenges. In this study, we compared whether removing host background (host depletion) affected the microbial profiles of prostate tissue samples analyzed with 16S sequencing and Shotgun metagenomics.
Prostate tissue samples were obtained from Turku University Hospital. Tissue samples were homogenized and divided in two subsample sets, of which one was treated with MolYsis™ Basic5 kit and the other went straight to microbial DNA extraction, which was performed to both sets. The extraction was done using Chemagic ™ DNA Stool 200 mg Kit H96 with Magnetic Separation Module I extraction robot. The analysis also included negative controls (OMNIgene fluid, DNA/RNA Shield fluid), extraction controls (Chemagic Lysis Buffer 1) and ZymoBIOMICS Gut microbiome standards. The microbial composition was determined by using 16S rRNA gene amplicon sequencing targeting the V3–V4 hypervariable regions as well as Shotgun Metagenomics. Both pooled libraries were sequenced with the Illumina platform.
The number of reads of the samples received from 16S rRNA gene amplicon sequencing was on average 21×105 while the average for Shotgun Metagenomics was 44×106. Majority of the reads were either host reads or unclassified by the database. All the species shared by negative controls and samples that might be attributable to contamination were excluded, which left a small number of bacteria species. Moreover, the microbial profiles were different between host depletion samples and untreated samples which refers that the host depletion changed the microbial profile of a prostate tissue sample. In the future, the V1–V2 region of the 16S rRNA gene could be tested instead of V3–V4 region for tissue microbiome analysis to check if it has better specificity compared to V3–V4. Shotgun metagenomics on the other hand would need more sequencing depth.
Prostate tissue samples were obtained from Turku University Hospital. Tissue samples were homogenized and divided in two subsample sets, of which one was treated with MolYsis™ Basic5 kit and the other went straight to microbial DNA extraction, which was performed to both sets. The extraction was done using Chemagic ™ DNA Stool 200 mg Kit H96 with Magnetic Separation Module I extraction robot. The analysis also included negative controls (OMNIgene fluid, DNA/RNA Shield fluid), extraction controls (Chemagic Lysis Buffer 1) and ZymoBIOMICS Gut microbiome standards. The microbial composition was determined by using 16S rRNA gene amplicon sequencing targeting the V3–V4 hypervariable regions as well as Shotgun Metagenomics. Both pooled libraries were sequenced with the Illumina platform.
The number of reads of the samples received from 16S rRNA gene amplicon sequencing was on average 21×105 while the average for Shotgun Metagenomics was 44×106. Majority of the reads were either host reads or unclassified by the database. All the species shared by negative controls and samples that might be attributable to contamination were excluded, which left a small number of bacteria species. Moreover, the microbial profiles were different between host depletion samples and untreated samples which refers that the host depletion changed the microbial profile of a prostate tissue sample. In the future, the V1–V2 region of the 16S rRNA gene could be tested instead of V3–V4 region for tissue microbiome analysis to check if it has better specificity compared to V3–V4. Shotgun metagenomics on the other hand would need more sequencing depth.