Community-level signatures of ecological succession in natural bacterial communities

Abstract

A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units. We profiled (16S rRNA sequencing) > 700 semi-aquatic bacterial communities while measuring their functional capacity when grown in laboratory conditions. This approach allowed us to investigate the relationship between composition and function excluding confounding environmental factors. Simulated data allowed us to reject the hypothesis that stochastic processes were responsible for community assembly, suggesting that niche effects prevailed. Consistent with this idea we identified six distinct community classes that contained samples collected from distant locations. Structural equation models showed there was a functional signature associated with each community class. We obtained a more mechanistic understanding of the classes using metagenomic predictions (PiCRUST). This approach allowed us to show that the classes contained distinct genetic repertoires reflecting community-level ecological strategies. The ecological strategies resemble the classical distinction between r-and K-strategists, suggesting that bacterial community assembly may be explained by simple ecological mechanisms.

Relationships between community composition, productivity and invasion resistance in semi-natural bacterial microcosms

“…Similarly, in a study system more similar to our own, it has been shown that the ability bacterial species to colonise a new phyllosphere environment depends on the local density (and by implication, identity) of other neighbouring bacteria colonising the environment at the same time – likely because more intense competition for resources reduces the average growth success of the population ( Remus-Emsermann et al, 2012 ). Such species interactions/succession-type dynamics are likely to be at least partly driving productivity-mediated effects of composition in our system also – especially as our previous work has shown our ‘functional groups’ correspond to distinct metabolic profiles inferred from predicted metagenomes ( Pascual-García and Bell, 2020a ).…”

Metabolically cohesive microbial consortia and ecosystem functioning

“…Bar-plots were generated rarefying samples to 1000 reads and represented with the R package phyloseq [75,76]. For figure 1, the classes, β-diversity distance matrix and GPS locations of the samples were retrieved from [9], and we performed a principal coordinate analysis (PCoA) of the samples with the R function dudi.pco, from package ade4 [77]. Results are represented projecting the samples into the first two PCoA coordinates and computing the centroids of the clusters defined by both the sampling sites and the community classes.…”

“…Bell [9] showed that there was significant spatial autocorrelation, which may be explained by stochastic processes and dispersal limitation (figure 1b). Nonetheless, the six classes contained communities that were often distant in space (more than 100 km), suggesting community similarity was at least partly driven by local environmental conditions.…”

“…Overall, the data suggest that local environmental conditions occurring in different locations, rather than neutral evolution with dispersal limitation, shape these communities. More details in [9].…”

Latent functional diversity may accelerate microbial community responses to temperature fluctuations

“…The K -selected taxa may therefore be thought of as general constituents of soil, associated with standard low turnover of carbon, whilst the r -selected taxa may been seen as more opportunistic from their involvement in early succession. Indeed, signatures of community-level differences in r -versus K -selection have been observed in microbial communities at different successional stages [68]. Fluctuating temperatures may therefore drive repeated assembly dynamics via sorting on latent microbial diversity, leading to functional community changes through time.…”