Distinct compositions and functions of circulating microbial DNA in the peripheral blood compared to fecal microbial DNA in healthy individuals

ABSTRACT The crucial function of circulating microbial DNA (cmDNA) in peripheral blood is gaining recognition because of its importance in normal physiology and immunity in healthy individuals. Evidence suggests that cmDNA in peripheral blood is derived from highly abundant, translocating gut microbes. However, the associations with and differences between cmDNA in peripheral blood and the gut microbiome remain unclear. We collected blood, urine, and fecal samples from volunteers to compare their microbial information via 16S rDNA sequencing. The results revealed that, compared with gut microbial DNA, cmDNA in peripheral blood was associated with reduced diversity and a distinct microbiota composition. The cmDNA in the blood reflects the biochemical processes of microorganisms, including synthesis, energy conversion, degradation, and adaptability, surpassing that of fecal samples. Interestingly, cmDNA in blood showed a limited presence of DNA from anaerobes and gram-positive bacteria, which contrast with the trend observed in fecal samples. Furthermore, analysis of cmDNA revealed traits associated with mobile elements and potential pathologies, among others, which were minimal in stool samples. Notably, cmDNA analysis indicated similarities between the microbial functions and phenotypes in blood and urine samples, although greater diversity was observed in urine samples. Source Tracker analysis suggests that gut microbes might not be the main source of blood cmDNA, or a selective mechanism allows only certain microbial DNA into the bloodstream. In conclusion, our study highlights the composition and potential functions associated with cmDNA in peripheral blood, emphasizing its selective presence; however, further research is required to elucidate the mechanisms involved. IMPORTANCE Our research provides novel insights into the unique characteristics and potential functional implications of circulating microbial DNA (cmDNA) in peripheral blood. Unlike other studies that analyzed sequencing data from fecal or blood microbiota in different study cohorts, our comparative analysis of cmDNA from blood, urine, and fecal samples from the same group of volunteers revealed a distinct blood-specific cmDNA composition. We discovered a decreased diversity of microbial DNA in blood samples compared to fecal samples as well as an increased presence of biochemical processes microbial DNA in blood. Notably, we add to the existing knowledge by documenting a reduced abundance of anaerobes and gram-positive bacteria in blood compared to fecal samples according to the analysis of cmDNA and gut microbial DNA, respectively. This observation suggested that a potential selective barrier or screening mechanism might filter microbial DNA molecules, indicating potential selectivity in the translocation process which contrasts with the traditional view that cmDNA primarily originates from random translocation from the gut and other regions. By highlighting these differences, our findings prompt a reconsideration of the origin and role of cmDNA in blood circulation and suggest that selective processes involving more complex biological mechanisms may be involved.

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Dear Editor,
We truly appreciate your feedback on our article.We have taken your comments into serious consideration and made the necessary changes to the text as advised.Your guidance has been instrumental in refining our manuscript, and we are grateful for your meticulous attention to detail and dedication to upholding the highest standards of academic publishing.Thank you for your invaluable input, and we look forward to hearing from you soon.
We have highlighted all the changes in the marked-up file.Moreover, to prevent potential grammatical or other errors resulting from significant revisions, the amended manuscript has already undergone a subsequent review by AJE (American Journal Experts) for enhancement, ensuring the document's quality.The following is a pointby-point response to your comments.
Comment 1: Page 2. Lines 54-56.Importance: Please delete last sentence as it is redundant: "These contributions underscore the significance of our study in expanding the current state of knowledge on cmDNA and its implications for human health." Response 1: We have made the requested change to the manuscript per your feedback.
Thank you for your input.
Comment 2: Page 6. Lines 147-16 and throughout the manuscript.Add summary stats (test name and FDR-adj.P value) to statements of significance and nonsignificance.For example, lines 147: "The α-diversity analysis revealed significantly lower (Kruskal-Wallis test, FDR-adj.P values≤0.05)Chao1 and Shannon indices (Figure 1B, 1C) and a significantly higher (Kruskal-Wallis test, FDRadj.P-values≤ 0.05) Good's coverage index (Figure 1D) in the blood samples than in the urine and fecal samples.
Response 2: Based on this comment, we have added statistical information to the appropriate places in the article, including results 1 and 2. (Page 6, Line 144-149. Comment 3: Page 6. Lines 159-161.Need to document ANOSIM analysis in Methods.Also, by stating R-values and P-values as well as sample size (N) in the text in paratheses (as mentioned above in point 2) you can eliminate Table 2. Also please expand any abbreviations at their first usage in the manuscript (i.e., Analysis of Similarity (ANOSIM)) as well as provide a citation for that analysis tool or database.
Response 3: We appreciate your valuable feedback.Regarding your comment on the need for additional information on the ANOSIM analysis in the Methods section, we have ensured that the relevant details are now included.To enhance clarity, we have also included the R values, P values, and sample sizes (N) in parentheses within the text in the Results section, thus eliminating the need for Table 2. Furthermore, we have expanded upon the abbreviations at their first usage in the manuscript, specifically in the "Data analysis" section of the Methods section.(Page 6, Line 157-159.Page 16,Line 450,[452][453][454][459][460][461][462][463][464][465][466][467][468][469][470] Comment 4: Lines 176-181.I agree with Comment #6 made by Reviewer 2 that you need provide a statistical test for ASV comparisons in Figures 2C and 2D.FDR adj.P-values needed to be reported.I would also suggest including these values in a Supplemental Data file in MSExcel format along with taxon names, mean values, standard deviations. Response 4: Thank you for your feedback.We agree that a statistical test for ASV comparisons in Figures 2C and 2D is necessary, and we have provided FDR adj.P values in the revised manuscript.Additionally, we will include these values in a Supplemental Data file in Microsoft Excel.We appreciate your suggestions and will make the necessary changes to improve the quality of our work.(Page 7, Line 179-183.) Comment 5: For Figure 5A-I, also mentioned by the reviewer, you have provided the whole group Pvalue but not the pairwise FDR-adj.values between each sample type, Blood, Feces and Urine.These could be added as horizontal lines above the tested pairs with "*" notations for significance level and "ns" for non-significance.I would also suggest sharing the data used to generate this figure in another Supplementary data file.Further comments about Figure 5 and the phenotype analysis follow below.
In general, it is good practice to include supplementary files with the data used togenerate any figures so that others can replicated your analyses.
Response 5: Thank you for your insightful feedback.During our earlier data processing stage, we generated the raw statistical data utilized in creating these figures.In accordance with your suggestion, we have compiled the underlying data for all nine figures in a supplementary file for easier accessibility and comprehensive presentation of our findings.We believe this approach will enhance the clarity and reproducibility of our research.We appreciate your guidance and will continue to strive for excellence in our work.(Figure 5. Page 9, Line 232-233.)Comment 6: Line 209.Expand "KO" abbreviation and add citation to PICRUSt2.Response 6: Based on your feedback, we have added references to the PICRUSt2 analysis in Line 464 and revised the KO database to the MetaCyc database.(Page 8, Line 211.Page 17, Line 468.) Comment 7: Line 208-221. Figure 4B.I suggest caution in emphasizing the linkage to human pathways and diseases which is likely a spurious effect of using the KEGG database.KEGG generalizes enzyme functions across eukaryotes and prokaryotes.KEGG updates are also restricted to paid subscribers.PRICRUSt2 now uses MetaCyc as its default database, which is prokaryote specific, open source and regularly updated.It might be worthwhile redoing your analyses with MetaCyc.Response 7: Thank you for your detailed feedback on Figure 4B.Your comments regarding the KEGG database are very pertinent, and we recognize the potential issues associated with using KEGG.Based on your suggestions, we have completed the reanalysis using MetaCyc as the default database to ensure the accuracy and relevance of the results.Furthermore, we have modified the descriptive content related to Figure 4B, including the Abstract, Results and Discussion sections.(Page 1, Line 21-23.Page 2, Line 44.Page 8, Line 212-222.Page 11, Line 290-300.)