1. Ecology

Latent functional diversity may accelerate microbial community responses to temperature fluctuations

  1. Thomas P Smith  Is a corresponding author
  2. Shorok Mombrikotb
  3. Emma Ransome
  4. Dimitrios - Georgios Kontopoulos
  5. Samraat Pawar
  6. Thomas Bell
  1. The Georgina Mace Centre for the Living Planet, Imperial College London, United Kingdom
  2. LOEWE Centre for Translational Biodiversity Genomics, Germany
  3. Senckenberg Research Institute, Germany
https://doi.org/10.7554/eLife.80867
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Cite this article
  1. Thomas P Smith
  2. Shorok Mombrikotb
  3. Emma Ransome
  4. Dimitrios - Georgios Kontopoulos
  5. Samraat Pawar
  6. Thomas Bell
(2022)
Latent functional diversity may accelerate microbial community responses to temperature fluctuations
eLife 11:e80867.
https://doi.org/10.7554/eLife.80867
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5 figures, 2 tables and 1 additional file

Figures

Figure 1
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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
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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
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Evolution of Topt.

(A) Ancestral trait reconstruction of Topt 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 Topt 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
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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
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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 Topt 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).

Tables

Table 1
Details of time tree calibration nodes.

We constrained the time calibration of our RAxML tree based on estimated divergence times from TimeTree (Kumar et al., 2017).

Taxa ATaxa BMin divergence time (MYA)Max divergence time (MYA)
BacteriaArchaea4290-
PseudomonasBacillus31003254
PseudomonasLabrys10533135
PseudomonasCollimonas10533135
CollimonasVariovorax1271-
ArthrobacterStreptomyces14201870
ArthrobacterBacillus31003254
BacillusBrevibacillus17342398
Table 2
List of revivable strains and GenBank accession numbers.

Strain codes follow XX_YY_ZZ naming convention, where XX is the incubation temperature, YY is the isolation temperature, and ZZ is a numeric designator for the specific isolate. RT = room temperature (22°C, termed ‘standard temperature’). All 16S sequences are archived on NCBI’s GenBank with the accession numbers indicated.

StrainAccession no.PhylumClassOrderFamilyGenus
04_04_02ON804144ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
04_04_04ON804145ProteobacteriaBetaproteobacteriaBurkholderialesOxalobacteraceaeCollimonas
04_04_05ON804146FirmicutesBacilliBacillalesBacillaceaeBacillus
04_04_06ON804147ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
04_RT_01ON804148FirmicutesBacilliBacillalesBacillaceaeBacillus
04_RT_02ON804149ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
04_RT_03ON804150FirmicutesBacilliBacillalesBacillaceaeBacillus
04_RT_05ON804151ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
10_10_06ON804152ActinobacteriaActinobacteriaMicrococcalesMicrococcaceaeArthrobacter
10_RT_01ON804153ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
10_RT_02ON804154ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
10_RT_03ON804155FirmicutesBacilliBacillalesBacillaceaeBacillus
21_21_01ON804156FirmicutesBacilliBacillalesBacillaceaeBacillus
21_21_02ON804157ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
21_21_04ON804158ProteobacteriaBetaproteobacteriaBurkholderialesOxalobacteraceaeCollimonas
21_21_05ON804159FirmicutesBacilliBacillalesBacillaceaeBacillus
21_21_06ON804160ProteobacteriaGammaproteobacteriaPseudomonadalesPseudomonadaceaePseudomonas
21_RT_01ON804161ProteobacteriaBetaproteobacteriaBurkholderialesOxalobacteraceaeCollimonas
21_RT_02ON804162FirmicutesBacilliBacillalesBacillaceaeBacillus
21_RT_03ON804163FirmicutesBacilliBacillalesPaenibacillaceaePaenibacillus
21_RT_04ON804164ProteobacteriaGammaproteobacteriaXanthomonadalesRhodanobacteraceaeDyella
21_RT_05ON804165ActinobacteriaActinobacteriaCorynebacterialesNocardiaceaeNocardia
21_RT_06ON804166FirmicutesBacilliBacillalesBacillaceaeBacillus
30_30_01ON804167ActinobacteriaActinobacteriaStreptomycetalesStreptomycetaceaeStreptomyces
30_30_02ON804168FirmicutesBacilliBacillalesBacillaceaeBacillus
30_30_03ON804169ActinobacteriaActinobacteriaStreptomycetalesStreptomycetaceaeStreptomyces
30_30_04ON804170FirmicutesBacilliBacillalesBacillaceaeBacillus
30_30_05ON804171FirmicutesBacilliBacillalesBacillaceaeBacillus
30_30_06ON804172ActinobacteriaActinobacteriaStreptomycetalesStreptomycetaceaeStreptomyces
30_30_07ON804173ActinobacteriaActinobacteriaStreptomycetalesStreptomycetaceaeStreptomyces
30_30_08ON804174ProteobacteriaAlphaproteobacteriaRhizobialesXanthobacteraceaeLabrys
30_RT_01ON804175ProteobacteriaBetaproteobacteriaBurkholderialesComamonadaceaeVariovorax
30_RT_02ON804176ProteobacteriaBetaproteobacteriaBurkholderialesComamonadaceaeVariovorax
30_RT_03ON804177FirmicutesBacilliBacillalesBacillaceaeBacillus
30_RT_04ON804178ProteobacteriaGammaproteobacteriaXanthomonadalesRhodanobacteraceaeDyella
30_RT_05ON804179ProteobacteriaBetaproteobacteriaBurkholderialesComamonadaceaeVariovorax
30_RT_06ON804180FirmicutesBacilliBacillalesBacillaceaeBacillus
40_40_01ON804181FirmicutesBacilliBacillalesBacillaceaeBacillus
40_40_02ON804182FirmicutesBacilliBacillalesPaenibacillaceaeCohnella
40_40_03ON804183FirmicutesBacilliBacillalesBacillaceaeBacillus
40_40_04ON804184FirmicutesBacilliBacillalesPlanococcaceaeRummeliibacillus
40_40_05ON804185FirmicutesBacilliBacillalesPaenibacillaceaeCohnella
40_40_06ON804186FirmicutesBacilliBacillalesPlanococcaceaeViridibacillus
40_RT_01ON804187FirmicutesBacilliBacillalesBacillaceaeBacillus
40_RT_02ON804188FirmicutesBacilliBacillalesBacillaceaeBacillus
40_RT_03ON804189FirmicutesBacilliBacillalesPlanococcaceaeViridibacillus
40_RT_04ON804190FirmicutesBacilliBacillalesPlanococcaceaeViridibacillus
40_RT_05ON804191FirmicutesBacilliBacillalesBacillaceaeBacillus
40_RT_06ON804192FirmicutesBacilliBacillalesBacillaceaeBacillus
50_50_01ON804193FirmicutesBacilliBacillalesPlanococcaceaeRummeliibacillus
50_50_02ON804194FirmicutesBacilliBacillalesBacillaceaeAnoxybacillus
50_50_03ON804195FirmicutesBacilliBacillalesPaenibacillaceaeBrevibacillus
50_50_04ON804196FirmicutesBacilliBacillalesPaenibacillaceaeBrevibacillus
50_50_05ON804197FirmicutesBacilliBacillalesBacillaceaeBacillus
50_50_06ON804198FirmicutesBacilliBacillalesBacillaceaeAnoxybacillus
50_RT_01ON804199FirmicutesBacilliBacillalesBacillaceaeBacillus
50_RT_02ON804200FirmicutesBacilliBacillalesBacillaceaeBacillus
50_RT_03ON804201FirmicutesBacilliBacillalesBacillaceaeBacillus
50_RT_04ON804202FirmicutesBacilliBacillalesBacillaceaeBacillus
50_RT_06ON804203FirmicutesBacilliBacillalesBacillaceaeBacillus

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  1. Thomas P Smith
  2. Shorok Mombrikotb
  3. Emma Ransome
  4. Dimitrios - Georgios Kontopoulos
  5. Samraat Pawar
  6. Thomas Bell
(2022)
Latent functional diversity may accelerate microbial community responses to temperature fluctuations
eLife 11:e80867.
https://doi.org/10.7554/eLife.80867