Page 133 - Read Online

Page 18 of 19 Wang et al. Microbiome Res Rep. 2025;4:23 https://dx.doi.org/10.20517/mrr.2024.94

2018;8:2453. DOI PubMed PMC
13. Roussel C, Galia W, Leriche F, et al. Comparison of conventional plating, PMA-qPCR, and flow cytometry for the determination of
viable enterotoxigenic Escherichia coli along a gastrointestinal in vitro model. Appl Microbiol Biotechnol. 2018;102:9793-802. DOI
14. Ou F, McGoverin C, Swift S, Vanholsbeeck F. Absolute bacterial cell enumeration using flow cytometry. J Appl Microbiol.
2017;123:464-77. DOI PubMed
15. Brankatschk R, Bodenhausen N, Zeyer J, Bürgmann H. Simple absolute quantification method correcting for quantitative PCR
efficiency variations for microbial community samples. Appl Environ Microbiol. 2012;78:4481-9. DOI PubMed PMC
16. Stämmler F, Gläsner J, Hiergeist A, et al. Adjusting microbiome profiles for differences in microbial load by spike-in bacteria.
Microbiome. 2016;4:28. DOI PubMed PMC
17. Rao C, Coyte KZ, Bainter W, Geha RS, Martin CR, Rakoff-Nahoum S. Multi-kingdom ecological drivers of microbiota assembly in
preterm infants. Nature. 2021;591:633-8. DOI PubMed PMC
18. Tourlousse DM, Yoshiike S, Ohashi A, Matsukura S, Noda N, Sekiguchi Y. Synthetic spike-in standards for high-throughput 16S
rRNA gene amplicon sequencing. Nucleic Acids Res. 2017;45:e23. DOI PubMed PMC
19. Zaramela LS, Tjuanta M, Moyne O, Neal M, Zengler K. synDNA-a Synthetic DNA Spike-in method for absolute quantification of
shotgun metagenomic sequencing. mSystems. 2022;7:e0044722. DOI PubMed PMC
20. Camacho-Sanchez M. A new spike-in-based method for quantitative metabarcoding of soil fungi and bacteria. Int Microbiol.
2024;27:719-30. DOI
21. Warda AK, Dempsey EM, Forssten SD, et al. Cross-sectional observational study protocol: missing microbes in infants born by
caesarean section (MiMIC): antenatal antibiotics and mode of delivery. BMJ Open. 2022;12:e064398. DOI PubMed PMC
22. Lopez-Siles M, Khan TM, Duncan SH, Harmsen HJ, Garcia-Gil LJ, Flint HJ. Cultured representatives of two major phylogroups of
human colonic faecalibacterium prausnitzii can utilize pectin, uronic acids, and host-derived substrates for growth. Appl Environ
Microbiol. 2012;78:420-8. DOI PubMed PMC
23. Uniacke-Lowe S, Collins FWJ, Hill C, Ross RP. Bioactivity screening and genomic analysis reveals deep-sea fish microbiome isolates
as sources of novel antimicrobials. Mar Drugs. 2023;21:444. DOI PubMed PMC
24. Vynne NG, Månsson M, Nielsen KF, Gram L. Bioactivity, chemical profiling, and 16S rRNA-based phylogeny of Pseudoalteromonas
strains collected on a global research cruise. Mar Biotechnol (NY). 2011;13:1062-73. DOI PubMed
25. Yoon JH, Weiss N, Kang KH, Oh TK, Park YH. Planococcus maritimus sp. nov., isolated from sea water of a tidal flat in Korea. Int J
Syst Evol Microbiol. 2003;53:2013-7. DOI PubMed
26. Stoddard SF, Smith BJ, Hein R, Roller BR, Schmidt TM. rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and
archaea and a new foundation for future development. Nucleic Acids Res. 2015;43:D593-8. DOI PubMed PMC
27. human breast milk. Benef Microbes. 2022;13:319-30. DOI
Yu Z, Morrison M. Improved extraction of PCR-quality community DNA from digesta and fecal samples. Biotechniques.
2004;36:808-12. DOI PubMed
28. Clifford RJ, Milillo M, Prestwood J, et al. Detection of bacterial 16S rRNA and identification of four clinically important bacteria by
real-time PCR. PLoS One. 2012;7:e48558. DOI PubMed PMC
29. Delroisse JM, Boulvin AL, Parmentier I, Dauphin RD, Vandenbol M, Portetelle D. Quantification of bifidobacterium spp. and
lactobacillus spp. in rat fecal samples by real-time PCR. Microbiol Res. 2008;163:663-70. DOI PubMed
30. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina
amplicon data. Nat Methods. 2016;13:581-3. DOI PubMed PMC
31. Quast C, Pruesse E, Yilmaz P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based
tools. Nucleic Acids Res. 2013;41:D590-6. DOI PubMed PMC
32. Ding M, Chen H, Yu R, et al. Shared and non-shared sIgA-coated and -uncoated bacteria in intestine of mother-infant pairs. Int J Mol
Sci. 2022;23:9873. DOI PubMed PMC
33. Yap BW, Sim CH. Comparisons of various types of normality tests. J Stat Comput Simul. 2011;81:2141-55. DOI
34. Corder GW, Foreman DI. Nonparametric statistics: A step-by-step approach. 2nd ed. Hoboken, NJ: John, Wiley and Sons; 2014.
35. Ding M, Zheng Y, Liu F, et al. Lactation time influences the composition of Bifidobacterium and Lactobacillus at species level in

36. Bishara AJ, Hittner JB. Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman,
transformation, and resampling approaches. Psychol Methods. 2012;17:399-417. DOI PubMed
37. Healy DB, Wang S, Patangia D, Grimaud G, Ross RP, Stanton C, Dempsey EM. Late-onset sepsis treatment in very preterm infants
alters longitudinal microbiome trajectory with lower abundance of Bifidobacterium despite probiotic supplementation. Gut Microbes.
2025. DOI
TM
38. Thermo Fisher Scientific. LIVE/DEAD® BacLigh Bacterial Viability and Counting Kit (L34856): Product Information Sheet. 2004.
Available from: https://assets.thermofisher.com/TFS-Assets/LSG/manuals/mp34856.pdf.
39. Brando B, Barnett D, Janossy G, et al; European Working Group on Clinical Cell Analysis (EWGCCA). Cytofluorometric methods for
assessing absolute numbers of cell subsets in blood. Cytometry. 2000;42:327-46. DOI
40. Wulff S, Martin K, Vandergaw A, et al. Guide to flow cytometry. Glostrup: Dako Cytomation; 2006.
41. Kennedy NA, Walker AW, Berry SH, et al; UK IBD Genetics Consortium. The impact of different DNA extraction kits and
laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing. PLoS One. 2014;9:e88982.
DOI PubMed PMC