Statistical evaluation of metaproteomics and 16s rRNA amplicon sequencing techniques for the study of the gut microbiota establishment of infants with cystic fibrosis

Abstract

The newborn screening for cystic fibrosis (CF) can identify affected but still asymptomatic infants. The selection of omic technique for gut microbiota study is therefore crucial due to both the small amount of feces available and the low microorganism load. Our aim was to compare the agreement between 16S rRNA amplicon sequencing and metaproteomics by a robust statistical analysis including McNemar (taxa presence) test and Bland–Altman (taxa abundance) data plotting for studying the sequential establishment of the gut microbiota during the first year of life in 8 infants with CF (28 fecal samples). The taxonomic assignation was similar by the two techniques, whereas certain discrepancies were observed in the abundance detection, mostly the underrepresentation of Bifidobacterium and the overestimation of certain Firmicutes and Proteobacteria by amplicon sequencing. During the first months of life, the CF gut microbiota is characterized by poor alpha diversity, a significant enrichment of Ruminococcus gnavus, the expression of certain virulent bacterial traits, and the detection of human inflammation-related proteins. Our study provides an extended comparative analysis with robust statistical support that could optimize the use of both approaches for gut microbiota research. Metaproteomics provides information on composition and functionality, as well as data on host-microbiome interactions. Its strength is the identification and quantification of Actinobacteria and certain classes of Firmicutes. Both techniques detected an aberrant microbiota in infants with CF during their first year of life, dominated by the enrichment of R. gnavus within a human inflammatory environment.