Latent functional diversity may accelerate microbial community responses to temperature fluctuations

Abstract

How complex microbial communities respond to climatic fluctuations remains an open question. Due to their relatively short generation times and high functional diversity, microbial populations harbor great potential to respond as a community through a combination of strain-level phenotypic plasticity, adaptation, and species sorting. However, the relative importance of these mechanisms remains unclear. We conducted a laboratory experiment to investigate the degree to which bacterial communities can respond to changes in environmental temperature through a combination of phenotypic plasticity and species sorting alone. We grew replicate soil communities from a single location at six temperatures between 4°C and 50°C. We found that phylogenetically and functionally distinct communities emerge at each of these temperatures, with K-strategist taxa favored under cooler conditions and r-strategist taxa under warmer conditions. We show that this dynamic emergence of distinct communities across a wide range of temperatures (in essence, community-level adaptation) is driven by the resuscitation of latent functional diversity: the parent community harbors multiple strains pre-adapted to different temperatures that are able to 'switch on' at their preferred temperature without immigration or adaptation. Our findings suggest that microbial community function in nature is likely to respond rapidly to climatic temperature fluctuations through shifts in species composition by resuscitation of latent functional diversity.

Keywords: bacteria; diversity; ecology; temperature; thermal response.

Figure 1.. The species sorting experiment.

(A) Different bacterial taxa (colored circles) sampled from the soil community. (B) Samples maintained at 4, 10, 21, 30, 40, and 50°C (only three temperatures shown for illustration), allowing species sorting for 4 weeks. (C) Soil washes from each core plated out onto agar and grown at both the sorting temperature and 22°C (standard temperature) to allow further species sorting and facilitate isolation (next step). (D) The six most abundant (morphologically different) colonies from each plate were picked, streaked, and isolated, and their physiological and life history traits measured. The curves represent each strain’s unique unimodal response of growth rate to temperature.

Figure 2.. Species sorting of soil bacteria driven by temperature change.

(A) Thermal optima of growth rate closely match sorting temperature for the isolates from those temperatures (black line: quadratic linear regression, p<0.0001, R² = 0.94, $n$ = 28). Note that the prediction bounds at three lowest temperatures do not include the 1:1 (dashed) line. (B) No significant association between incubation temperature and thermal optima for standard temperature isolates (simple linear regression, p = 0.488, R² = 0.02, $n$ = 26). These results show that species sorting can act upon latent diversity to select for isolates adapted to different temperature conditions (A), but that isolates maladapted to the sorting conditions can re-emerge (be resuscitated) under the appropriate conditions (B).

Figure 3.. Evolution of Topt.

(A) Ancestral trait reconstruction of ${\displaystyle T_{\text{opt}}}$ visualized on a tree, from lower temperatures in cyan, to higher temperatures in red, with time given in billions of years (BY). All of the higher temperature (40–50°C) isolates belong to the phylum Firmicutes. (B) Projection of the phylogenetic tree into the ${\displaystyle T_{\text{opt}}}$ trait space (y-axis), over relative time (x-axis) since divergence from the root. The clades representative of each phylum are colored on the projection (Actinobacteria, red; Firmicutes, blue; Proteobacteria, yellow).

Figure 4.. Partitioning of growth strategies between phyla.

(A) Principal components analysis (PCA) on life history traits, colored by phylum. Relative to each other, Firmicutes (blue) tend to be $r$ specialists, Proteobacteria (orange) tend to be $K$ specialists. (B) ATP content of cultures is associated with the respiration rate. Firmicutes show a sublinear scaling relationship of ATP with respiration rate (scaling exponent = 0.60 ± 0.07), while Proteobacteria display an approximately linear scaling relationship (scaling exponent = 0.99 ± 0.06). The same color scheme is shared by both sub-plots.

Figure 5.. Comparison of Firmicutes and Proteobacteria in meta-analysis datasets.

(A) Dataset used by DeLong et al., 2010 shows significantly higher active (n = 39) and passive (n = 108) metabolic rates for Proteobacteria than Firmicutes. Significance determined by Wilcoxon rank-sum tests – ns, p≥0.05; *p<0.05; **p<0.01; ***p<0.001. (B) The growth rate data used by DeLong et al., 2010 shows no significant difference between the phyla (n = 31). (C) The growth rate data from Smith et al., 2019 does show significantly increased growth rates for Firmicutes over Proteobacteria however (n = 135). (D) Distribution of Firmicutes and Proteobacteria $T_{\text{opt}}$ from Smith et al., 2019. Proteobacteria account for a large proportion of the low-temperature strains, while Firmicutes dominate the high temperatures. Dotted line marks 40.5°C, a cut-off between mesophiles and thermophiles (Smith et al., 2019).