Building a genome-based understanding of bacterial pH preferences

Abstract

The environmental preferences of many microbes remain undetermined. This is the case for bacterial pH preferences, which can be difficult to predict a priori despite the importance of pH as a factor structuring bacterial communities in many systems. We compiled data on bacterial distributions from five datasets spanning pH gradients in soil and freshwater systems (1470 samples in total), quantified the pH preferences of bacterial taxa across these datasets, and compiled genomic data from representative bacterial taxa. While taxonomic and phylogenetic information were generally poor predictors of bacterial pH preferences, we identified genes consistently associated with pH preference across environments. We then developed and validated a machine learning model to estimate bacterial pH preferences from genomic information alone, a model which could aid in the selection of microbial inoculants, improve species distribution models, or help design effective cultivation strategies. More generally, we demonstrate the value of combining biogeographic and genomic data to infer and predict the environmental preferences of diverse bacterial taxa.

The native distribution of a common legume shrub is limited by the range of its nitrogen‐fixing mutualist

“…It is now established that soil pH is one of the main drivers of soil microbial community composition and, in particular, has a strong influence on the abundance of N 2 ‐fixing bacteria (Lemaire et al ., 2015; Fierer, 2017; de Castro et al ., 2018; Ramoneda et al ., 2023; Sepp et al ., 2023). Alkaline soils limit the growth and survival of some species of Bradyrhizobia and may limit their geographical range (Tang et al ., 1991; Graham, 1992; Rathi et al ., 2018; Bouhnik et al ., 2022).…”

“…For example, insufficient availabilities of soil micronutrients such as iron or molybdenum limit the process of bacterial N 2 fixation (O'Hara, 2001; Brear et al ., 2013). Additionally, highly acidic or alkaline soils limit the growth of some rhizobial species, as well as the development of root nodules, the structures in which legume plants host the bacteria (Rupela & Saxena, 1987; Graham, 1992; Shen et al ., 2013; Ramoneda et al ., 2023). Environmental limitations resulting in the complete absence of a compatible rhizobial partner from an otherwise permissive environment have been reported in several cases, primarily in the context of their effect on productivity in agricultural systems (Graham, 2003; Lugtenberg, 2015).…”

Functional regimes define the response of the soil microbiome to environmental change

“…Identifying which of these processes are the key drivers of the community-level metabolic response remains a challenge. Surveys of communities in the wild [16][17][18] reveal patterns relating community composition, environmental variation, and metabolic processes [19][20][21][22][23][24][25][26][27][28]. However, the origins of these patterns are difficult to dissect [14], and establishing causal relationships from observational data alone is challenging given many confounding factors.…”

“…It remains difficult to determine which of these processes is important for determining how environmental changes alter collective metabolic rates. Surveys of communities in the wild [16][17][18] reveal patterns relating community composition, environmental variation, and metabolic processes [19][20][21][22][23][24][25][26][27][28]. The existence of reproducible patterns in natural systems suggests underlying principles linking environmental change, community composition, and metabolism.…”

Predicting microbial growth conditions from amino acid composition

“…An alternative strategy is to correlate operational taxonomic units (OTUs) to physicochemical variables like pH and oxygen across habitats 10 . It is unclear if gene-based models can be more accurate 1,[11][12][13][14][15][16] . First, the genes underlying these physicochemical adaptations in diverse organisms remain unknown.…”