Work

Absolute abundance unveils Basidiobolus as a cross-domain bridge indirectly bolstering gut microbiome homeostasis

Year: 2025

Type: article

Abstract: The host microbiome is integral to metabolism, immune function, and pathogen resistance. Yet, reliance on relative abundance in microbiome studies introduces compositional biases that obscure ecological interpretation, while the absence of robust tools for absolute abundance quantification has limited biological discovery. Here, we apply absolute abundance profiling to uncover host-specific microbial patterns across herpetofauna orders that are masked in relative abundance data. Relative- and absolute abundance-derived bacterial and fungal microbiomes exhibit divergent profiles shaped by compositional bias and multifactorial effects. Absolute abundance identified key genera, Lactococcus, Parabacteroides, and Cetobacterium in salamanders, and Basidiobolus and Mortierella in lizards, turtles, snakes, and tortoises, that consistently emerged as core taxa, revealing host-associated patterns previously obscured by compositional constraints. In closely related Desmognathus species, where environmental and phylogenetic variation was minimized, absolute abundance enabled finer resolution of microbiome dynamics and significantly reduced false discovery rates. Absolute abundance-based network analyses further revealed distinct keystone taxa between the relative and absolute abundance datasets. Despite low redundancy, Basidiobolus exhibited high network betweenness, efficiency, and degree, suggesting its role as a key connector between microbial modules and a contributor to overall network robustness. This predicted structural role aligns with Burt's structural hole theory, which suggests that nodes linking otherwise disconnected modules occupy influential network positions. These findings underscore the value of absolute abundance in resolving microbial dynamics and supporting meaningful interpretation of host-microbiome associations. This advance is made possible by DspikeIn, a flexible wet-lab and computational framework that enhances ecological resolution and cross-study comparability.

Source: The ISME Journal

DOI: 10.1093/ismejo/wraf150