Validation of a spike-in control to determine the normalized abundance of microbiota in human milk

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Abstract
Understanding how human milk composition, particularly the milk microbiota, shapes infant gut microbial colonization and health is a rapidly evolving area of investigation. Normalized absolute abundance data is increasingly used in gut microbiome research to accurately reflect community dynamics and avoid compositional artifacts associated with relative abundance data. With relative abundance data, a change in one microbial taxa can significantly affect the apparent abundance of others, resulting in erroneous interpretation of findings. Here, we validated a method for quantifying normalized abundances from human milk 16S rRNA gene sequencing data using a spike-in control, a more efficient and cost-effective alternative to separately performing quantitative polymerase chain reaction. We compared both methods on 30 milk samples from 27 mothers and found no significant differences in community profiles in terms of diversity metrics and total microbial loads. These findings advance normalization strategies to more accurately reflect biological changes in the human milk microbiota.