[
Abrahamsson, T. R., Jakobsson, H. E., Andersson, A. F., Björkstén, B., Engstrand, L., Jenmalm, M. C. (2014). Low gut microbiota diversity in early infancy precedes asthma at school age. Clin. Exper. Allergy, 44 (6), 842–850. https://doi.org/10.1111/cea.1225310.1111/cea.1225324330256
]Search in Google Scholar
[
Arumugam, M., Raes, J., Pelletier, E., le Paslier, D., Yamada, T., Mende, D. R., Fernandes, G. R., Tap, J., Bruls, T., Batto, J.-M., et al. (2011). Enterotypes of the human gut microbiome. Nature, 473 (7346), 174–180. https://doi.org/10.1038/nature0994410.1038/nature09944372864721508958
]Search in Google Scholar
[
Azad, M. B., Konya, T., Maughan, H., Guttman, D. S., Field, C. J., Chari, R. S., Sears, M. R., Becker, A. B., Scott, J. A., Kozyrskyj, A. L. (2013). Gut microbiota of healthy Canadian infants: Profiles by mode of delivery and infant diet at 4 months. Canad. Med. Assoc. J., 185 (5), 385–394. https://doi.org/10.1503/cmaj.12118910.1503/cmaj.121189360225423401405
]Search in Google Scholar
[
Boxberger, M., Cenizo, V., Cassir, N., la Scola, B. (2021). Challenges in exploring and manipulating the human skin microbiome. Microbiome, 9 (1), 125. https://doi.org/10.1186/s40168-021-01062-510.1186/s40168-021-01062-5816613634053468
]Search in Google Scholar
[
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., Holmes, S. P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Meth., 13 (7), 581–583. https://doi.org/10.1038/nmeth.386910.1038/nmeth.3869492737727214047
]Search in Google Scholar
[
Daneberga, Z., Nakazawa-Miklasevica, M., Berga-Svitina, E., Murmane, D., Isarova, D., Cupane, L., Masinska, M., Nartisa, I., Lazdane, A., Miklasevics, E. (2021). Urinary organic acids spectra in children with altered gut microbiota composition and autistic spectrum disorder. Nordic J. Psychiatry, 76 (7), 523-529.
]Search in Google Scholar
[
Fouhy, F., Ross, R. P., Fitzgerald, G. F., Stanton, C., Cotter, P. D. (2012). Composition of the early intestinal microbiota. Gut Microbes, 3 (3), 203–220. https://doi.org/10.4161/gmic.2016910.4161/gmic.20169342721322572829
]Search in Google Scholar
[
Hill, C. J., Lynch, D. B., Murphy, K., Ulaszewska, M., Jeffery, I. B., O’Shea, C. A., Watkins, C., Dempsey, E., Mattivi, F., Tuohy, K., et al. (2017). Evolution of gut microbiota composition from birth to 24 weeks in the INFANTMET Cohort. Microbiome, 5 (1), 4. https://doi.org/10.1186/s40168-016-0213-y10.1186/s40168-016-0213-y524027428095889
]Search in Google Scholar
[
Homann, C.-M., Rossel, C. A. J., Dizzell, S., Bervoets, L., Simioni, J., Li, J., Gunn, E., Surette, M. G., de Souza, R. J., Mommers, M., Hutton, E. K., et al. (2021). Infants’ first solid foods: Impact on gut microbiota development in two intercontinental cohorts. Nutrients, 13 (8), 2639. https://doi.org/10.3390/nu1308263910.3390/nu13082639840033734444798
]Search in Google Scholar
[
Janda, J. M., Abbott, S. L. (2007). 16S rRNA gene sequencing for bacterial identification in the diagnostic laboratory: Pluses, perils, and pitfalls. J. Clin. Microbiol., 45 (9), 2761–2764. https://doi.org/10.1128/JCM.01228-0710.1128/JCM.01228-07204524217626177
]Search in Google Scholar
[
Katoh, K., Standley, D. M. (2013). MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol. Biol. Evol., 30 (4), 772–780. https://doi.org/10.1093/molbev/mst01010.1093/molbev/mst010360331823329690
]Search in Google Scholar
[
Kevin Blighe, A. L. (2021). PCAtools: Everything Principal Component Analysis. https://Github.Com/Kevinblighe/PCAtools (12.09.2022).
]Search in Google Scholar
[
Kroiča, J., Reinis, A., Kakar, M., Delorme, M., Broks, R., Asare, L., Berezovska, M., Jansins, V., Zviedre, A., Enģelis, A., Saxena, A., Pētersons, A. (2020). Culture based evaluation of microbiota in children with acute appendicitis. Proc. Latvian Acad. Sci., Section B, 74 (2), 100–105. https://doi.org/10.2478/prolas-2020-001610.2478/prolas-2020-0016
]Search in Google Scholar
[
Love, M. I., Huber, W., Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol., 15 (12), 550. https://doi.org/10.1186/s13059-014-0550-810.1186/s13059-014-0550-8430204925516281
]Search in Google Scholar
[
McMurdie, P. J., Holmes, S. (2013). phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE, 8 (4), e61217. https://doi.org/10.1371/journal.pone.006121710.1371/journal.pone.0061217363253023630581
]Search in Google Scholar
[
Morais, J., Marques, C., Teixeira, D., Durão, C., Faria, A., Brito, S., Cardoso, M., Macedo, I., Pereira, E., Tomé, T., Calhau, C. (2020). Extremely preterm neonates have more Lactobacillus in meconium than very preterm neonates: The in utero microbial colonization hypothesis. Gut Microbes, 12 (1). https://doi.org/10.1080/19490976.2020.178580410.1080/19490976.2020.1785804752439432658601
]Search in Google Scholar
[
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., et al. (2011). Scikit-learn: Machine learning in python. J. Machine Learning Res., 12, 2825–2830.
]Search in Google Scholar
[
Penders, J., Vink, C., Driessen, C., London, N., Thijs, C., Stobberingh, E. E. (2005). Quantification of Bifidobacterium spp., Escherichia coli and Clostridium difficile in faecal samples of breast-fed and formula-fed infants by real-time PCR. FEMS Microbiol. Lett., 243 (1), 141–147. https://doi.org/10.1016/j.femsle.2004.11.05210.1016/j.femsle.2004.11.05215668012
]Search in Google Scholar
[
Price, M. N., Dehal, P. S., Arkin, A. P. (2010). FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments. PLoS ONE, 5 (3), e9490. https://doi.org/10.1371/journal.pone.000949010.1371/journal.pone.0009490283573620224823
]Search in Google Scholar
[
R Core Team (2020). A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.eea.europa.eu/data-and-maps/indicators/oxygen-consuming-substances-in-rivers/r-development-core-team-2006 (accessed 14.09.2022).
]Search in Google Scholar
[
Ratsika, A., Codagnone, M. C., O’Mahony, S., Stanton, C., Cryan, J. F. (2021). Priming for life: Early life nutrition and the Microbiota-Gut-Brain Axis. Nutrients, 13 (2), 423. https://doi.org/10.3390/nu1302042310.3390/nu13020423791205833525617
]Search in Google Scholar
[
Rinninella, E., Raoul, P., Cintoni, M., Franceschi, F., Miggiano, G., Gasbarrini, A., Mele, M. (2019). What is the healthy gut microbiota composition? A changing ecosystem across age, environment, diet, and diseases. Microorganisms, 7 (1), 14. https://doi.org/10.3390/microorganisms701001410.3390/microorganisms7010014635193830634578
]Search in Google Scholar
[
Rizzatti, G., Lopetuso, L. R., Gibiino, G., Binda, C., Gasbarrini, A. (2017). Proteobacteria: A common factor in human diseases. BioMed Res. Int., 2017, 1–7. https://doi.org/10.1155/2017/935150710.1155/2017/9351507568835829230419
]Search in Google Scholar
[
Roger, L. C., Costabile, A., Holland, D. T., Hoyles, L., McCartney, A. L. (2010). Examination of faecal bifidobacterium populations in breast- and formula-fed infants during the first 18 months of life. Microbiology, 156 (11), 3329–3341. https://doi.org/10.1099/mic.0.043224-010.1099/mic.0.043224-020864478
]Search in Google Scholar
[
Saturio, S., Nogacka, A. M., Alvarado-Jasso, G. M., Salazar, N., de los Reyes-Gavilán, C. G., Gueimonde, M., Arboleya, S. (2021). Role of bifidobacteria on infant health. Microorganisms, 9 (12), 2415. https://doi.org/10.3390/microorganisms912241510.3390/microorganisms9122415870844934946017
]Search in Google Scholar
[
Vester-Andersen, M. K., Mirsepasi-Lauridsen, H. C., Prosberg, M. V., Mortensen, C. O., Träger, C., Skovsen, K., Thorkilgaard, T., Nøjgaard, C., Vind, I., Krogfelt, K. A., Sørensen, N., Bendtsen, F., Petersen, A. M. (2019). Increased abundance of proteobacteria in aggressive Crohn’s disease seven years after diagnosis. Sci. Rep., 9 (1), 13473. https://doi.org/10.1038/s41598-019-49833-3.10.1038/s41598-019-49833-3674895331530835
]Search in Google Scholar
