Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

Microbial community responses to environmental change are largely associated with ecological processes; however, the potential for microbes to rapidly evolve and adapt remains relatively unexplored in natural environments. To assess how ecological and evolutionary processes simultaneously alter the genetic diversity of a microbiome, we conducted two concurrent experiments in the leaf litter layer of soil over 18 mo across a climate gradient in Southern California. In the first experiment, we reciprocally transplanted microbial communities from five sites to test whether ecological shifts in ecotypes of the abundant bacterium, Curtobacterium, corresponded to past adaptive differentiation. In the transplanted communities, ecotypes converged toward that of the native communities growing on a common litter substrate. Moreover, these shifts were correlated with community-weighted mean trait values of the Curtobacterium ecotypes, indicating that some of the trait variation among ecotypes could be explained by local adaptation to climate conditions. In the second experiment, we transplanted an isogenic Curtobacterium strain and tracked genomic mutations associated with the sites across the same climate gradient. Using a combination of genomic and metagenomic approaches, we identified a variety of nonrandom, parallel mutations associated with transplantation, including mutations in genes related to nutrient acquisition, stress response, and exopolysaccharide production. Together, the field experiments demonstrate how both demographic shifts of previously adapted ecotypes and contemporary evolution can alter the diversity of a soil microbiome on the same timescale.

Microbial communities respond quickly to environmental change (1, 2). These responses are typically associated with ecological processes; however, the potential for microbes to evolve and adapt to changes in the environment on ecological timescales remains largely unexplored in natural ecosystems. While evolutionary processes are typically considered over longer timescales, the short generation times, large populations, and high mutation rates indicative of microorganisms may allow for rapid adaptation. Laboratory studies have repeatedly demonstrated rapid evolution of bacterial populations (3) with consequences for organismal physiology (4), yet it remains unclear how these in vitro studies extend to in situ communities (5).Both ecological and evolutionary processes likely contribute simultaneously (6, 7) to the response of a microbiome to changing environmental conditions (8). However, separating these processes for bacteria can be difficult as they occur along a continuum of temporal and genetic scales. In terms of ecological processes, microbiome composition can respond demographically, as selective forces promote the growth and survival of differentially adapted taxa within the bacterial community. Certainly, many studies have observed such shifts in taxonomic composition of 16S ribosomal RNA (rRNA)–defined taxa in response to simulated global changes (9), and these responses are considered an ecological process (e.g., species sorting). Few examples, however, link these responses to trait differences among bacterial taxa (10–13), precluding direct insights into whether these ecological shifts are due to adaptive differentiation among taxa as a result of past evolutionary divergence. Concurrently, the same selective forces can also shift the abundance of conspecific strains and alter the allele frequencies of preexisting genetic variation, which at this genetic scale is defined as an evolutionary process (14). Finally, evolution through de novo mutation can provide a new source of genetic variation that may allow for further adaptation to environmental change.In this study, we aimed to capture this continuum of ecological and evolutionary processes that together produce the response of a microbiome’s diversity to environmental change (Fig. 1A). Studying evolution in microbial communities in situ, however, is challenging. For one, variation in highly conserved marker genes used in many microbiome studies (e.g., 16S rRNA) represents distant evolutionary divergences, and thus these regions are too conserved to detect locally adapted lineages (11, 12, 15), let alone recent evolutionary change within communities (16). To overcome this limitation, studies have leveraged shotgun metagenomic data (17, 18) and genome sequences of co-occurring, closely related strains (19, 20) to characterize evolutionary processes (e.g., recombination and gene flow) structuring the genetic diversity of bacterial lineages. However, these studies are also limited by an inherent challenge in microbiome research: delineating population boundaries, the fundamental unit of evolution. While progress has been made in defining microbial species (21–23), the high genetic heterogeneity within diverse microbial communities, such as soils, convolute the boundaries of the fine-scale patterns of genetic diversity within microbial taxonomic units (12). For instance, metagenome-assembled genomes are often composed of a composite of strains forming a large population of mosaic genomes (24) that may not fully capture the diversity of the local population (25). As such, it remains difficult to study evolutionary rates within microbial communities (however, see refs. 26, 27), and the extent and time scale at which evolutionary processes contribute to both standing and new genetic variation relative to ecological processes.Open in a separate windowFig. 1.Microbial community transplant experiment. (A) Changes in microbial community composition can be due to a continuum of ecological and evolutionary processes. For instance, shifts in standing genetic variation can be attributed to both ecological and evolutionary processes depending on the level of biological resolution, while de novo mutations can be a result from evolutionary adaptation. (B) A schematic of the two parallel transplant experiments at the community and strain level. Inoculated litterbags were transplanted to all sites along an elevation gradient that covaried in temperature and precipitation. Site codes: D=Desert; Sc=Scrubland; G=Grassland; P=Pine-Oak; S=Subalpine.Here, we asked the following question: can we characterize the ecological and evolutionary processes that are contributing concurrently to the response of a soil bacterial community to a changing environment? To answer this question, we utilized a field-based experimental approach to quantify the influence of both ecological and evolutionary processes on one focal soil bacterium in its natural environment, the genus Curtobacterium (28). Specifically, we transplanted the bacterium across an elevation gradient on a common resource (leaf litter) substrate (29) to assess its response to new climates in two parallel experiments over the same 18 mo time period (Fig. 1B). In both experiments, we used microbial cages [nylon mesh bags that allow for nutrient transport (30)] to manipulate microbial composition while restricting microbial migration to eliminate the introduction of new alleles and/or variants from dispersal (31). A reciprocal transplant design allowed for direct testing of microbial adaptation to abiotic conditions (i.e., moisture and temperature) in a natural setting.In the first experiment, we conducted a reciprocal transplant of the entire microbial community (32) and tracked the ecological response of Curtobacterium ecotypes (33). A bacterial ecotype is defined as highly clustered genotypic and phenotypic strains occupying the same ecological niche, somewhat equivalent to a eukaryotic species (34). To test the hypothesis that Curtobacterium ecotypes are locally adapted to their climate conditions, we assessed the convergence of ecotype composition in the transplanted communities to that of control communities (those that remained in their native environment; Fig. 1B). We further hypothesized that the demographic shifts were due to differential adaptation to local climates as a result of trait variation among the ecotypes. Thus, we expected that the climate gradient would select for a strong trait–environment relationship (assessed by community-weighted mean (CWM) trait values) as typically observed in plant communities (35, 36).In parallel, we conducted an in situ evolution experiment by transplanting an isogenic Curtobacterium strain across the same gradient to investigate the potential for rapid evolution on the same timescales. We hypothesized that a variety of genomic mutations would be associated with adaptation to local climate conditions. Therefore, we expected fewer genetic changes when the strain was transplanted to its original environment, the midelevation Grassland site, while the extreme sites of the gradient would impose stronger selective pressures resulting in greater genetic changes. We further expected to observe parallel mutations among replicates within a site, which would be indicative of adaptive events (37). Variation in such mutations across sites would suggest selection differences across the climate gradient. Together, the two experiments capture the simultaneous effects of both ecological and evolutionary processes on the response of a soil bacterium to new climates in the field.     

A C-Peptide-Based Model of Pancreatic Insulin Secretion in Extremely Preterm Neonates in Intensive Care

Background:

Model-based glycemic control relies on sufficiency of underlying models to describe underlying patient physiology. In particular, very preterm infant glucose-insulin metabolism can differ significantly from adults, and is relatively unstudied. In this study, C-peptide concentrations are used to develop insulin-secretion models for the purposes of glycemic control in neonatal intensive care.

Methods:

Plasma C-peptide, insulin, and blood glucose concentrations (BGC) were retrospectively analyzed from a cohort of 41 hyperglycemic very preterm (median age 27.2 [26.2-28.7] weeks) and very low birth-weight infants (median birth weight 839 [735-1000] g). A 2-compartment model of C-peptide kinetics was used to estimate insulin secretion. Insulin secretion was examined with respect to nutritional intake, exogenous and plasma insulin concentration, and BGC.

Results:

Insulin secretion was found to be highly variable between patients and over time, and could not be modeled with respect to age, weight, or protein or dextrose intake. In 13 of 54 samples exogenous insulin was being administered, and insulin secretion was lower. However, low data numbers make this result inconclusive. Insulin secretion was found to increase with BG, with a stronger association in female infants than males (R² = .51 vs R² = .13, and R² = .26 for the combined cohort).

Conclusions:

A sex-based insulin secretion model was created and incorporated into a model-based glycemic control framework. Nutritional intake did not predict insulin secretion, indicating that insulin secretion is a complex function of a number of metabolic factors.     

When Genetic Load Does Not Correlate with Phenotypic Spectrum: Lessons from the GnRH Receptor (GNRHR)

Context: A broad spectrum of GnRH-deficient phenotypes has been identified in individuals with both mono- and biallelic GNRHR mutations. Objective: The objective of the study was to determine the correlation between the severity of the reproductive phenotype(s) and the number and functional severity of rare sequence variants in GNRHR. Subjects: Eight hundred sixty-three probands with different forms of GnRH deficiency, 46 family members and 422 controls were screened for GNRHR mutations. The 70 subjects (32 patients and 38 family members) harboring mutations were divided into four groups (G1-G4) based on the functional severity of the mutations (complete or partial loss of function) and the number of affected alleles (monoallelic or biallelic) with mutations, and these classes were mapped on their clinical phenotypes. Results: The prevalence of heterozygous rare sequence variants in GNRHR was significantly higher in probands vs. controls (P < 0.01). Among the G1-G3 groups (homozygous subjects with successively decreasing severity and number of mutations), the hypogonadotropic phenotype related to their genetic load. In contrast, subjects in G4, with only monoallelic mutations, demonstrated a greater diversity of clinical phenotypes. Conclusions: In patients with GnRH deficiency and biallelic mutations in GNRHR, genetic burden defined by severity and dose is associated with clinical phenotype. In contrast, for patients with monoallelic GNRHR mutations this correlation does not hold. Taken together, these data indicate that as-yet-unidentified genetic and/or environmental factors may combine with singly mutated GNRHR alleles to produce reproductive phenotypes.     

GABAergic processes in the mesencephalic tegmentum modulate the occurrence of active (rapid eye movement) sleep in guinea pigs

The ventrolateral subdivision of the periaqueductal gray (vlPAG) and the adjacent dorsal mesencephalic reticular formation (dMRF) are involved in the modulation of active (rapid eye movement) sleep (AS). In order to determine the effects on AS of the suppression of neuronal activity in these regions, muscimol, a GABA receptor A (GABA(A)) receptor agonist, and bicuculline, a GABA(A) receptor antagonist, were microinjected bilaterally in guinea pigs and the states of sleep and wakefulness were examined. The main effect of muscimol was an increase in AS; this increase occurred in conjunction with a reduction in the time spent in wakefulness. The powerful effect of muscimol was striking especially when considering the small amount of naturally-occurring AS that is present in this species. Additional observable effects that were induced by muscimol were: 1) long lasting episodes of hypotonia/atonia during wakefulness and quiet sleep that included a lack of extensor tone in the hind limbs, and 2) frequently occurring cortical spindles, similar to those observed during naturally-occurring quiet sleep (sleep spindles), that were present during wakefulness. Conversely, bilateral microinjections of bicuculline induced a prolonged state of wakefulness and blocked the effect of subsequent injections of muscimol. These data suggest that endogenous GABA acts on GABA(A) receptors within the vlPAG and dMRF to promote AS in the guinea pig.