High-quality DNA extraction is a crucial step in metagenomic studies.Bias by different isolation kits impairs the comparison across datasets.A trending topic is,however,the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases.We thus collected bile,stool,saliva,plaque,sputum,and conjunctival swab samples and performed DNA extraction with three commercial kits.For each combination of the specimen type and DNA extraction kit,20-gigabase(Gb)metagenomic data were generated using short-read sequencing.While profiles of the specimen types showed close proximity to each other,we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits.No kit outperformed all selected kits on every specimen.We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit.Depending on the specimen,our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution,but DNA-based identification is superior to identification by mass spectrometry.Finally,long-read nanopore sequencing confirmed the results(correlation coefficient＞0.98).Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients.

Chronic obstructive pulmonary disease (COPD) significantly increases the risk of developing cancer. Biomarker studies frequently follow a case-control set-up in which patients diagnosed with a disease are compared to controls. Longitudinal cohort studies such as the COPD-centered German COPD and SYstemic consequences-COmorbidities NETwork (COSYCONET) study provide the patient and biomaterial base for discovering predictive molecular markers. We asked whether microRNA (miRNA) profiles in blood collected from COPD patients prior to a tumor diagnosis could support an early diagnosis of tumor development independent of the tumor type. From 2741 participants of COSYCONET diagnosed with COPD, we selected 534 individuals including 33 patients who developed cancer during the follow-up period of 54 months and 501 patients who did not develop cancer, but had similar age, gender and smoking history. Genome-wide miRNA profiles were generated and evaluated using machine learning techniques. For patients developing cancer we identified nine miRNAs with significantly decreased abundance (two-tailed unpaired t-test adjusted for multiple testing P < 0.05), including members of the miR-320 family. The identified miRNAs regulate different cancer-related pathways including the MAPK pathway (P = 2.3 × 10). We also observed the impact of confounding factors on the generated miRNA profiles, underlining the value of our matched analysis. For selected miRNAs, qRT-PCR analysis was applied to validate the results. In conclusion, we identified several miRNAs in blood of COPD patients, which could serve as candidates for biomarkers to help identify COPD patients at risk of developing cancer.
Aged ; Biomarkers, Tumor ; genetics ; Cohort Studies ; Female ; Gene Expression Profiling ; Genome, Human ; Humans ; Male ; MicroRNAs ; genetics ; Neoplasms ; diagnosis ; etiology ; genetics ; Prognosis ; Pulmonary Disease, Chronic Obstructive ; complications