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Financial support and sponsorship
This publication has emanated from research conducted with financial support from Science Foundation
Ireland (SFI) under Grant No. 12/RC/2273_P2 and 19/SP/6989. This publication has emanated from
research conducted with financial support of International Flavors and Fragances (IFF). Shuo Wang
(No.202006790046) is grateful for the financial support from the China Scholarship Council (CSC).
Conflicts of interest
R. Paul Ross and Catherine Stanton served as Guest Editors for the Special Issue “Exploring the Infant
Microbiome: From Birth to Early Growth and Development.” In addition, R. Paul Ross is a Senior Editor,
Catherine Stanton is an Executive Editor, and Bo Yang is an Editorial Board member of Microbiome
Research Reports. All three individuals were not involved in any part of the editorial process for this
manuscript, including reviewer selection, manuscript handling, or decision making. The other authors
declared that there are no conflicts of interest.
discovery rate. Brief Bioinform. 2019;20:210-21. DOI
Ethical approval and consent to participate
Ethical approval was obtained from the Cork Teaching Hospitals Clinical Research Ethics Committee
(ethical approval reference: ECM 4 (q) 07/03/18). Written informed consent was obtained from all
participating mothers for both their own and their infants’ involvement in the study.
Availability of data and materials
The data that support the findings of this study are available from the corresponding author upon
reasonable request.
Consent for publication
Not applicable
Copyright
© The Author(s) 2025.
REFERENCES
1. Roche KE, Mukherjee S. The accuracy of absolute differential abundance analysis from relative count data. PLoS Comput Biol.
2022;18:e1010284. DOI PubMed PMC
2. Knight R, Vrbanac A, Taylor BC, et al. Best practices for analysing microbiomes. Nat Rev Microbiol. 2018;16:410-22. DOI
3. Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ. Microbiome datasets are compositional: and this is not optional. Front
Microbiol. 2017;8:2224. DOI PubMed PMC
4. Weiss S, Xu ZZ, Peddada S, et al. Normalization and microbial differential abundance strategies depend upon data characteristics.
Microbiome. 2017;5:27. DOI PubMed PMC
5. Hawinkel S, Mattiello F, Bijnens L, Thas O. A broken promise: microbiome differential abundance methods do not control the false
6. Vandeputte D, Kathagen G, D'hoe K, et al. Quantitative microbiome profiling links gut community variation to microbial load. Nature.
2017;551:507-11. DOI
7. Jian C, Luukkonen P, Yki-Järvinen H, Salonen A, Korpela K. Quantitative PCR provides a simple and accessible method for
quantitative microbiota profiling. PLoS One. 2020;15:e0227285. DOI PubMed PMC
8. Lou J, Yang L, Wang H, Wu L, Xu J. Assessing soil bacterial community and dynamics by integrated high-throughput absolute
abundance quantification. PeerJ. 2018;6:e4514. DOI PubMed PMC
9. Kleyer H, Tecon R, Or D. Resolving species level changes in a representative soil bacterial community using microfluidic quantitative
PCR. Front Microbiol. 2017;8:2017. DOI PubMed PMC
10. Nishijima S, Stankevic E, Aasmets O, et al. Fecal microbial load is a major determinant of gut microbiome variation and a confounder
for disease associations. Cell. 2024;188:222-36. DOI
11. Contijoch EJ, Britton GJ, Yang C, et al. Gut microbiota density influences host physiology and is shaped by host and microbial factors.
Elife. 2019:8. DOI
12. Korpela K, Blakstad EW, Moltu SJ, et al. Intestinal microbiota development and gestational age in preterm neonates. Sci Rep.

