Quantitative Detection of Bifidobacterium longum Strains in Feces Using Strain-Specific Primers

Abstract

We adopted a bioinformatics-based technique to identify strain-specific markers, which were then used to quantify the abundances of three distinct B. longum sup. longum strains in fecal samples of humans and mice. A pangenome analysis of 205 B. longum sup. longum genomes revealed the accumulation of considerable strain-specific genes within this species; specifically, 28.7% of the total identified genes were strain-specific. We identified 32, 14, and 49 genes specific to B. longum sup. longum RG4-1, B. longum sup. longum M1-20-R01-3, and B. longum sup. longum FGSZY6M4, respectively. After performing an in silico validation of these strain-specific markers using a nucleotide BLAST against both the B. longum sup. longum genome database and an NR/NT database, RG4-1_01874 (1331 bp), M1-20-R01-3_00324 (1745 bp), and FGSZY6M4_01477 (1691 bp) were chosen as target genes for strain-specific quantification. The specificities of the qPCR primers were validated against 47 non-target microorganisms and fecal baseline microbiota to ensure that they produced no PCR amplification products. The performance of the qPCR primer-based analysis was further assessed using fecal samples. After oral administration, the target B. longum strains appeared to efficiently colonize both the human and mouse guts, with average population levels of >108 CFU/g feces. The bioinformatics pipeline proposed here can be applied to the quantification of various bacterial species.