Cell-Free Microbial DNA Analysis: Effects of Blood Plasma and Serum Quantity, Biobanking Protocols, and Isolation Kits

Recent studies highlight the presence of bacterial sequences in the human blood, suggesting potential clinical significance for circulating microbial signatures. These sequences could presumably serve in the diagnosis, prediction, or monitoring of various health conditions. Ensuring the similarity of samples before bacterial analysis is crucial, especially when combining samples from different biobanks prepared under varying conditions (such as different DNA extraction kits, centrifugation conditions, blood collection tubes, etc.). In this study, we aimed to analyze the impact of different sample collection and nucleic acid extraction criteria (blood collection tube, centrifugation, input volume, and DNA extraction kit) on circulating bacterial composition. Blood samples from four healthy individuals were collected into three different sample collection tubes: K2EDTA plasma tube, sodium citrate plasma tube, and gel tube for blood serum. Tubes were centrifugated at standard and double centrifugation conditions. DNA extraction was performed using 100, 200, and 500 μL plasma/serum input volumes. DNA extraction was performed using three different isolation kits: Norgen plasma/serum cell-free circulating DNA purification micro kit, Applied Biosystems MagMAX cell-free DNA isolation kit, and Qiagen QIAamp MinElute cell-free circulating DNA mini kit. All samples were subjected to 16S rRNA V1-V2 library preparation and sequencing. In total, 216 DNA and 18 water control samples were included in the study. According to PERMANOVA, PCoA, Mann-Whitney, and FDR tests the effect of the DNA extraction kit on the microbiota composition was the greatest, whereas the type of blood collection tube, centrifugation type, and sample input volume for the extraction had minor effects. Samples extracted with the Norgen DNA extraction kit were enriched with Gram-negative bacteria, whereas samples extracted with the Qiagen and MagMAX kits were enriched with Gram-positive bacteria. Bacterial profiles of samples prepared with the Qiagen and MagMAX DNA extraction kits were more similar, whereas samples prepared with the Norgen DNA extraction kit were significantly different from other groups.

Detailed Characterization of the Lung-Gut Microbiome Axis Reveals the Link between PD-L1 and the Microbiome in Non-Small-Cell Lung Cancer Patients

Next-generation sequencing technologies have started a new era of respiratory tract research in recent years. Alterations in the respiratory microbiome between healthy and malignant conditions have been revealed. However, the composition of the microbiome varies among studies, even in similar medical conditions. Also, there is a lack of complete knowledge about lung-gut microbiome interactions in lung cancer patients. The aim of this study was to explore the lung-gut axis in non-small-cell lung cancer (NSCLC) patients and the associations between lung-gut axis microbiota and clinical parameters (CRP, NLR, LPS, CD8, and PD-L1). Lung tissue and fecal samples were used for bacterial 16S rRNA sequencing. The results revealed, for the first time, that the bacterial richness in lung tumor tissue gradually decreased with an increase in the level of PD-L1 expression (p < 0.05). An analysis of β-diversity indicated a significant positive correlation between the genera Romboutsia and Alistipes in both the lung tumor biopsies and stool samples from NSCLC patients (p < 0.05). Survival analysis showed that NSCLC patients with higher bacterial richness in their stool samples had prolonged overall survival (HR: 2.06, 95% CI: 1.025-4.17, p = 0.0426).

The colibactin-producing Escherichia coli alters the tumor microenvironment to immunosuppressive lipid overload facilitating colorectal cancer progression and chemoresistance

Intratumoral bacteria flexibly contribute to cellular and molecular tumor heterogeneity for supporting cancer recurrence through poorly understood mechanisms. Using spatial metabolomic profiling technologies and 16SrRNA sequencing, we herein report that right-sided colorectal tumors are predominantly populated with Colibactin-producing Escherichia coli (CoPEC) that are locally establishing a high-glycerophospholipid microenvironment with lowered immunogenicity. It coincided with a reduced infiltration of CD8+ T lymphocytes that produce the cytotoxic cytokines IFN-γ where invading bacteria have been geolocated. Mechanistically, the accumulation of lipid droplets in infected cancer cells relied on the production of colibactin as a measure to limit genotoxic stress to some extent. Such heightened phosphatidylcholine remodeling by the enzyme of the Land's cycle supplied CoPEC-infected cancer cells with sufficient energy for sustaining cell survival in response to chemotherapies. This accords with the lowered overall survival of colorectal patients at stage III-IV who were colonized by CoPEC when compared to patients at stage I-II. Accordingly, the sensitivity of CoPEC-infected cancer cells to chemotherapies was restored upon treatment with an acyl-CoA synthetase inhibitor. By contrast, such metabolic dysregulation leading to chemoresistance was not observed in human colon cancer cells that were infected with the mutant strain that did not produce colibactin (11G5∆ClbQ). This work revealed that CoPEC locally supports an energy trade-off lipid overload within tumors for lowering tumor immunogenicity. This may pave the way for improving chemoresistance and subsequently outcome of CRC patients who are colonized by CoPEC.

Microbial composition of tumorous and adjacent gastric tissue is associated with prognosis of gastric cancer

Helicobacter pylori (H. pylori) infection has been considered as the main causal factor in gastric carcinogenesis, but other bacterial species may also play an important role in pathophysiology of gastric cancer. The aim of the study was to explore the link between gastric cancer prognosis and the mucosal microbial community in tumorous and adjacent gastric tissue. The bacterial profile was analysed using 16S sequencing (V1-V2 region). Microbial differences were mostly characterized by lower relative abundances of H. pylori in tumorous gastric tissues. Bacterial community and outcome data analysis revealed the genus Fusobacterium and Prevotella significantly associated with worse overall survival in gastric cancer patients. In particular, Fusobacterium was associated with significant increase in hazard ratio in both univariable and multivariable analysis and independently validated using TCMA data. Phylogenetic biodiversity of Fusobacterium species in the stomach revealed F. periodonticum as the most prevalent in healthy subjects, while F. nucleatum was most abundant in patients with gastric cancer. Bacterial community network analysis in gastric cancer suggests substantial complexity and a strong interplay between F. nucleatum and Prevotella. In summary, mucosal microbial community in the stomach was associated with worse overall survival in gastric cancer patients. Strongest negative impact on prognosis was linked to the abundance of F. nucleatum in tumorous specimens, suggesting its translational relevance in management of gastric cancer patients.

Comparison of genomic and transcriptional microbiome analysis in gastric cancer patients and healthy individuals

BACKGROUND

Helicobacter pylori and the stomach microbiome play a crucial role in gastric carcinogenesis, and detailed characterization of the microbiome is necessary for a better understanding of the pathophysiology of the disease. There are two common modalities for microbiome analysis: DNA (16S rRNA gene) and RNA (16S rRNA transcript) sequencing. The implications from the use of one or another sequencing approach on the characterization and comparability of the mucosal microbiome in gastric cancer (GC) are poorly studied.

AIM

To characterize the microbiota of GC using 16S rRNA gene and its transcript and determine difference in the bacterial composition.

METHODS

In this study, 316 DNA and RNA samples extracted from 105 individual stomach biopsies were included. The study cohort consisted of 29 healthy control individuals and 76 patients with GC. Gastric tissue biopsy samples were collected from damaged mucosa and healthy mucosa at least 5 cm from the tumor tissue. From the controls, healthy stomach mucosa biopsies were collected. From all biopsies RNA and DNA were extracted. RNA was reverse transcribed into cDNA. V1-V2 region of bacterial 16S rRNA gene from all samples were amplified and sequenced on an Illumina MiSeq platform. Bray-Curtis algorithm was used to construct sample-similarity matrices abundances of taxonomic ranks in each sample type. For significant differences between groups permutational multivariate analysis of variance and Mann-Whitney test followed by false-discovery rate test were used.

RESULTS

Microbial analysis revealed that only a portion of phylotypes (18%-30%) overlapped between microbial profiles obtained from DNA and RNA samples. Detailed analysis revealed differences between GC and controls depending on the chosen modality, identifying 17 genera at the DNA level and 27 genera at the RNA level. Ten of those bacteria were found to be different from the control group at both levels. The key taxa showed congruent results in various tests used; however, differences in 7 bacteria taxa were found uniquely only at the DNA level, and 17 uniquely only at the RNA level. Furthermore, RNA sequencing was more sensitive for detecting differences in bacterial richness, as well as differences in the relative abundance of Reyranella and Sediminibacterium according to the type of GC. In each study group (control, tumor, and tumor adjacent) were found differences between DNA and RNA bacterial profiles.

CONCLUSION

Comprehensive microbial study provides evidence for the effect of choice of sequencing modality on the microbiota profile, as well as on the identified differences between case and control.