Nimble vs. torpid responders to hydration pulse duration among soil microbes

Environmental parameters vary in time, and variability is inherent in soils, where microbial activity follows precipitation pulses. The expanded pulse-reserve paradigm (EPRP) contends that

arid soil microorganisms have adaptively diversified in response to pulse regimes differing in frequency and duration. To test this, we incubate Chihuahuan Desert soil microbiomes under

separate treatments in which 60 h of hydration was reached with pulses of different pulse duration (PD), punctuated by intervening periods of desiccation. Using 16S rRNA gene amplicon data,

we measure treatment effects on microbiome net growth, growth efficiency, diversity, and species composition, tracking the fate of 370 phylotypes (23% of those detected). Consistent with

predictions, microbial diversity is a direct, saturating function of PD. Increasingly larger shifts in community composition are detected with decreasing PD, as specialist phylotypes become

more prominent. One in five phylotypes whose fate was tracked responds consistently to PD, some preferring short pulses (nimble responders; NIRs) and some longer pulses (torpid responders;

TORs). For pulses shorter than a day, microbiome growth efficiency is an inverse function of PD, as predicted. We conclude that PD in pulsed soil environments constitutes a major driver of

microbial community assembly and function, largely consistent with the EPRP predictions.

Organisms must acclimate to environmental parameters that typically fluctuate, rather than being constant1,2,3. The consequences of environmental fluctuations may be rather mild, requiring

only small physiological responses to cope. For example, episodes of elevated temperature may be dealt with satisfactorily through the deployment of heat-shock proteins to ensure the correct

folding of proteins under the new conditions4. But fluctuations can also exert severe impacts on physiology, requiring a switch between fundamentally different physiological states

characterized by different biochemical and regulatory blueprints. The purple sulfur bacterium Thiocapsa roseopersicina, for example, must toggle quickly and recurrently between aerobic

chemolithotrophy and anaerobic photolithotrophy to match the diel chemical shifts in coastal sulfidic sediments5, requiring extensive biochemical reorganization. Perhaps the most extreme

form of fluctuation crosses environmental thresholds so harsh as to impinge on an organism’s overall metabolic activity: full desiccation or extreme cold come to mind. In ecology, when

environmental changes are recurrent, intense, and involve a parameter necessary for biological activity, one speaks of “activity pulses”, and of “pulsed ecosystems”, of which polar6 or arid

environments7 are quintessential examples. In pulses involving desiccation, the physiological burden to adaptation is compounded by direct cellular damage to the cell membrane8, nucleic

acids and proteins9. While a wealth of examples exists showing evolutionary adaptations leading to the development of specialist “extremophiles”10,11,12, adaptations that provide fitness to

organisms specifically under pulsed conditions are much less obvious. It is even unclear if organisms exist that are evolutionarily specialized to a pulsed existence or to specific types of

pulse regimes. Consistent with this notion, however, experiments with microbial communities in biocrusts have demonstrated that a decrease in precipitation pulse size, but maintaining

constant total rainfall, results in major relative increases for some cyanobacteria over others13, and, similarly, addition of small precipitation pulses gives a field advantage to

cyanobacteria over mosses14. In any event, nowhere are such pulses better defined and more patent than in surface soils from dryland ecosystems, where fluctuations between water saturation

and complete desiccation faithfully follow pulsed rainfall events15. There, microbes must toggle between physiological states geared to support (typically short) pulses of activity when

hydrated, and (typically long) periods of quiescence when dry16,17. This extremely pulsed regime makes arid top-soil microbiomes prime targets of inquiry in this arena.

Theoretical considerations suggest that organisms in pulsed environments are indeed adapted to pulse variability, not just to the end-member situations within a pulse (i.e., high and low

salinity, inactive and desiccated vs active and hydrated, oxic vs. anoxic). In other words, their adaptations are suited to surviving the changes themselves because to transition between

appropriate physiological blueprints in a pulse is costly18,19,20 and it takes time. Time is particularly important under regimes where growth-enabling time is at a premium. The

long-standing pulse-reserve paradigm (PRP) of arid ecosystem function calls for the central role of organismal reserves gathered during times of plenty to power such transitions

effectively21,22. Pulse duration (PD) will determine whether enough reserves can be acquired to eventually start a new growth phase. Short pulses may end up costing more resources than can

be acquired, leading to organismal demise. According to theory23, adaptations to a pulsed existence will fall along a continuum between two end-member strategies. At one end “Nimble

Responders (NIRs)” transition swiftly in and out of growth mode by constantly allocating a proportion of resources to reserves, maintaining a constitutive physiological readiness for

inter-pulse conditions, and ensuring that metabolic systems are inherently hardy and protected. This comes at the cost of depressing their growth potential during the activity pulse; they

become inherently slow growers. At the opposite end, “Torpid Responders (TORs)”, must also allocate resources to reserves to fuel transitions, but they only do so as an activity pulse nears

its end. Consequently, TORs fulfill their growth potential during much of the pulse, unconstrained by allocation to reserves, and they grow swiftly during most of it. But their lag times for

transition to dormancy and back into growth are long, as reserves are synthesized ad hoc at the end of a pulse. TORs also have comparatively long minimal pulse duration for viability. NIRs

can be understood as conservative investors, focused on certainty of returns that are moderate but frequent, while TORs act like risky investors whose strategy relies on high returns that

occur rarely. Specific organisms will fall within a continuum between the extremes exemplified in the NIR and TOR acronyms.

The NIR-TOR continuum theory, while consistent with available phenomenology and some anecdotal evidence, has yet to be tested directly. We sought to conduct an experimental, quantitative

test of some of its predictions. Specifically, we asked if one could indeed find evidence for physiological diversification of soil bacteria along the NIR-TOR continuum, and if this would

translate into a community’s overall growth capacity. To do this, we used (heterotrophic) dryland soil microbiomes from the aphotic zone of biological soil crusts and subjected them to

defined pulsed hydration incubation regimes with a diverse carbon source. We then determined the changes that ensued in basic microbial diversity and growth parameters, as well as the fates

of the populations of hundreds of phylotypes as a function of pulse duration to show that, indeed, pulse duration strongly influences structural and functional properties of microbial

communities on soil.

As a main experimental material, dry biocrust soil was collected in the Jornada Long Term Experimental Range near Las Cruces, New Mexico (32°34'06.9“N, 106°45'29.4“W). The biocrust were of

the light-crust type and dominated by the cyanobacterium Microcoleus vaginatus24. The 2-mm thin phototrophic layer of the biocrust was peeled off the surface by hand, and the soil below was

collected down to a depth of 2 cm. The removal of phototrophs was done for the sake of experimental simplicity since biocrust phototrophs have doubling times in the order of 1–15 days 25,

which would have imposed a far longer experiment, and also to avoid cascading effects since heterotrophs would be dependent on phototrophic exudates. The soil was sifted through a 4.75 mm

sieve to remove or break up larger particles, transported and stored in a closed bucket at room temperature until experiments were started, then homogenized by shaking and mixing by hand.

Plates for incubations were constructed as shown in Fig. 1, provided with sterile paper filters at the bottom and filled with 40 g of homogenized soil to a soil depth of 3–4 mm. All tubing,

manifolds, and plates were either autoclaved or sterilized in ethanol and dried under UV in an engaged laminar flow hood. The incubation plates were assembled using one Petri plate lid and

one bottom, the lid rim glued to the bottom side as shown in Fig. 1A. The bottom section had 30 interspaced holes to allow the exit of the soil solution when under vacuum and the lid had a

side hook-up for a vacuum line.

A Soil incubation chambers constructed from Petri dishes. B Connection of chambers to vacuum and medium sources for desiccation and wetting. C Pulse regime treatment schedule, with wetting

(blue) and dry (yellow) periods. Blue periods always add to 60 h, dry times are invariably 12 h.

Five treatments were designed to isolate pulse duration as the independent variable. They included variations of the number and duration of pulses so that all had a total active (hydrated)

time of 60 h. Treatments experienced 12 h long dry periods between pulses. The treatments were: never wet (control), 12 five-hour long wet pulses (5 h), six ten-hour long wet pulses (10 h),

four 15-h long wet pulses (15 h), three 20-h wet pulse (20 h), and one 60-h wet pulse (60 h). A graphic schedule of treatments is in Fig. 1. Desiccation to 5% water content in this set-up

was enhanced by vacuum and was attained within 4.3 h after the end of the wet period as measured by a conductivity-based water content miniprobe (UP Umweltanalytische Produkte GmbH,

Ibbenbüren, Germany) in situ (Fig. S1). Plates were kept in an engaged laminar flow hood through the incubation to prevent external contamination. To prepare an appropriate medium for

wetting the soil, the cyanobacterium Microcoleus vaginatus strain PCC9802 was grown in 50% strength BG-11 medium for two weeks at room temperature in flasks with vented-caps under a 12 h

photoperiod26. The spent medium was then filter-sterilized by passage through a 0.2 µm pore diameter filter and used as a close-to-natural source of diverse C compounds27 for the communityt.

At the end of each prescribed wet period, the soil solution was actively suctioned under mild vacuum (−0.22 bar) for one hour, then kept dry for 11 h. Soil moisture dropped below 5% water

content, within 4.3 h, which is not an unusually fast desiccation speed compared to those experienced in crusts during summer conditions, remaining at levels too low for microbial

activity28,29 until the next wetting (Fig. S1). These regimes resulted in significant and sustained soil respiration at each wetting, but the soils never got anoxic, even at depth (Fig. S1),

as measured directly in situ using a O2-measuring microoptode with a 50 µm tip diameter, connected to a Fire-Sting O2 oxygen meter, both from Pyroscience Gmbh (Germany). After the final

drying cycle, dishes were stored wrapped in parafilm and covered in tin foil at 4 °C. Once all treatments were completed samples were promptly processed.

Three 0.25 g samples of soil were taken from each plate to extract community DNA with Qiagen DNeasy PowerSoil Pro Kit (Qiagen Inc. Germantown, MD, USA) used according to the manufacturer’s

instructions. DNA concentrations in the extracts were determined initially via Qubit (Qubit 3 Fluorometer Invitrogen by ThermoFisher Scientific, Waltham, Massachusetts, USA). Guided by these

data, extracts were diluted for qPCR to quantify the content of 16S rRNA gene copies and amplified using universal primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 518R

(5′-ATTACCGCGGCTGCTGG-3′)30. The PCR reaction was performed in triplicate alongside negative controls of molecular grade water using SYBR Green FastMix ROX Quantabio (Beverly, Massachusetts,

USA) under the following conditions: an initial denaturation phase (2 min at 98 °C), followed by 40 cycles of denaturation at 95 °C for 10 s and annealing at 55 °C for 30 s, followed by the

melting curve acquisition (increasing temperature from 55 to 95 °C at 0.5 °C s-1 speed)31. This qPCR produced a standard curve with an R2 of 0.998. The standard curve was then used to

calculate the number of copies of the 16S rRNA gene per mg of soil.

Additionally, 20 µL of the same extract as used for qPCR for each sample was used for 16S rRNA gene sequencing with MiSeq sequencing (Illumina NGS) with the 515F/806R primers which target

the V4 region of the 16S rRNA gene32.

15 mL of the spent Microcoleus medium were initially added per wetting event to all treatments to achieve soil saturation. This corresponds to a rain event of 2.3 mm (15 mL over a surface 64

 cm2 surface), which is within the low end of rain event size at the site of origin (Fig. S2). To maintain soil hydration throughout the full duration of the wetting pulse, an additional 3 

mL was added every five hours thereafter to bring the soil to saturation. The soil was wet to saturation as dryland soils are commonly saturated and experience runoff following rainfall.

Total DOC added per pulse was computed from total wetting volume and the DOC concentrations of the spent medium (39 mg L-1), and was set to match natural steady state levels of biocrust in

the soil solution33,34,35, the totals added varying between 0.9 and 3.0 mg per plate, so as to balance consumption in longer incubations. Net DOC accumulation in the soil after incubation

was determined by subtraction of the DOC content of untreated control soils (0.93 mg per plate or 0.02 mg/g) from the end-point DOC content in each plate. The additions thus maintained the

DOC concentrations well within the very low DOC (oligotrophic realm) natural for these soils. Dissolved organic carbon extraction from soils was performed on 20 g (50%) of each plate,

following ref. 36. All DOC determinations were processed by Arizona State University Metals Environmental and Terrestrial Analytical Laboratory for total carbon and dissolved organic carbon

(DOC) quantification by an elemental analyzer.

16S rRNA gene sequences obtained were demultiplexed and quality controlled using the DADA2 plugin of Qiime2 2022.8 refs. 37,38. Raw sequences were then trimmed for quality control, which

created a feature table of unique sequences (amplicon sequence variants, ASV) along with their frequency of occurrence. Singletons were disregarded from this table. The sample with the least

reads had 11939, and that with the most had 28484 (Fig. S3). To ensure equal sampling effort, all samples were trimmed randomly to include a sampling depth of 11939. Alpha rarefaction

analysis showed that this was sufficient to reach saturation of diversity assessment in all samples (Fig. S3). ASV were initially automatically classified using Greengenes 13.8 ref. 39. and

any Archaeal reads discarded, but more detailed taxonomic assignments were carried out through BLAST for any ASV of interest, given the low resolution and high level of errors in this

database40. BLAST assignments were conducted using the 16S gene sequence and the strain with the highest percent identity was selected with all of the sequences which underwent BLAST having

100% similarity with a sequence in the NCBI database. Disagreements between the Qiime2, Greengenes 13.8 assignment and BLAST were handled by selecting the taxonomic classification from BLAST

as Greengenes has been demonstrated to have a high error rate41. When a specific strain could not be selected as multiple different sequences shared 100% similarity it is noted using a “/”.

Qiime2 2022.8 was used for all diversity metrics including Shannon’s Diversity, Chao1, Weighted UniFrac, Unweighted UniFrac, Jaccard’s index, and Bray-Curtis index. Beta-diversity was

assessed using principal coordinates analysis (PCoA) in Qiime2. From Qiime2, coordinates were extracted and plotted in R so that 95% confidence ellipses could be calculated with the R vegan

package42. Differential abundance analyses were also done in R using Hellinger to normalize the feature table created above. ASVs which were differentially abundant between the 5-h and 60-h

pulse regimes were determined using the DeSeq2 method43 in the R BiocManager package.

Linear regressions of log base 2 abundance as a function of treatment duration (excluding controls) were conducted in R on data from any ASVs detected in at least six different samples. This

culled ASVs to 370 out of an original 1639 detected. The slopes of such regressions are a proxy for the NIR vs. TOR character of an ASV, where NIRs would show consistently increasing

abundance with shorter pulse and vice-versa. To do this properly absolute counts are needed, but absolute counts are lost on sequencing because of the intervening PCR reaction. To restore an

absolute measure of abundance, we multiplied each ASV’s relative abundance by the total number of 16S rRNA gene copy counts per unit weight of soil determined by qPCR on aliquots of the

same extract that was sequenced.44. Because this is an indirect measure, we refer to it as Restored Absolute Abundance (REA). A log2 transformation of REA values was then conducted to yield

units that reflect apparent number of doublings. To assess the statistical significance of regressions, we adjusted p values using the Benjamini-Hochberg correction to account for the

multiplicity of statistical analyses conducted.

All statistical analyses were performed in R statistical software version 4.1.2 (2021-11-01) refs. 42,45,46,47,48. Levene’s Test was used to test for equal variance and Shapiro-Wilk Test for

normality. After verifying that assumptions were met, the data was analyzed by Analysis of Variance (ANOVA). Tukey’s honest significant difference was used as a post-hoc test for pairwise

comparisons. The experimental design was based on the detection of trends in measured or derives parameters (reponse variables) as a function of increased severity of treatments, and as such

it contains an inherent measure of reproducibility with an n of 5 against controls.

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

We gauged microbial community diversity in the soil under different pulse regimes using both Chao1 and Shannon diversity indices applied to the 16S rRNA gene data (compositional) at the

maximal phylogenetic resolution possible (ASVs level; Fig. 2; detailed counts can be found in Supplementary Data 1). Data binned by treatment had equal variances for both indices, and data

for both indices were normally distributed according to, respectively, Levene’s and Shapiro-Wilk tests. Therefore, ANOVA was an appropriate statistical test. It showed significant

differences with treatment for both Chao1 Richness (df = 12, F = 4.2, p = 0.019) and Shannon Diversity (df = 12, F = 25.0, p = 6 × 10−6). We found a depression of community diversity with

decreasing pulse duration, the 5 h treatment being only half as rich as the control in the case of Chao1 and with a similar decline when considering Shannon Diversity. These declining trends

in diversity and richness with shorter pulse duration were not only significant but fit a logarithmic (saturating) function of PD best (R2 = 0.35 with p = 0.02 for Chao1 and R2 = 0.75 with

p = 3 × 10−5 for Shannon; Fig. S4), apparent Chao richness and Shannon diversity loses thus intensifying in the short pulse range.

Estimators of Richness (Chao1 Richness) and Diversity (Shannon Diversity) showed congruent trends of increase with increasing pulse duration. Data shown as box-and-whisker plots with n = 3,

where x are means, lines are medians and bars are two standard deviations. Different letters above boxes indicate significant differences (p