Benjamin J. Koch

Background: Infections caused by antibiotic-resistant bacteria are increasingly frequent, burdening healthcare systems worldwide. As pathogens acquire resistance to all known antibiotics – i.e., become pan-resistant – treatment of the associated infections will become exceedingly difficult. We hypothesized that the emergence of pan-resistant bacterial pathogens will result in a sharp increase in human mortality. Methods: We tested this hypothesis by modeling the impact of a single hypothetical pan-resistant Escherichia coli strain on sepsis deaths in the United States. We used long-term data on sepsis incidence, mortality rates, strain dynamics, and treatment outcomes to parameterize a set of models encompassing a range of plausible future scenarios. All models accounted for historical and projected temporal changes in population size and age distribution. Results: The models suggest that sepsis deaths could increase 18- to 46-fold within 5 years of the emergence of a single pan-resistant E. coli strain. This large and rapid change contrasts sharply with the current expectation of gradual change under continuing multidrug-resistance. Conclusions: Failure to prevent the emergence of pan-resistance would have dire consequences for public health.

Measuring the growth rate of a microorganism is a simple yet profound way to quantify its effect on the world. The absolute growth rate of a microbial population reflects rates of resource assimilation, biomass production and element transformation—some of the many ways in which organisms affect Earth’s ecosystems and climate. Microbial fitness in the environment depends on the ability to reproduce quickly when conditions are favourable and adopt a survival physiology when conditions worsen, which cells coordinate by adjusting their relative growth rate. At the population level, relative growth rate is a sensitive metric of fitness, linking survival and reproduction to the ecology and evolution of populations. Techniques combining omics and stable isotope probing enable sensitive measurements of the growth rates of microbial assemblages and individual taxa in soil. Microbial ecologists can explore how the growth rates of taxa with known traits and evolutionary histories respond to changes in resource availability, environmental conditions and interactions with other organisms. We anticipate that quantitative and scalable data on the growth rates of soil microorganisms, coupled with measurements of biogeochemical fluxes, will allow scientists to test and refine ecological theory and advance process-based models of carbon flux, nutrient uptake and ecosystem productivity. Measurements of in situ microbial growth rates provide insights into the ecology of populations and can be used to quantitatively link microbial diversity to soil biogeochemistry.

Climate change increases the frequency and intensity of drought events, affecting soil functions including carbon sequestration and nutrient cycling, which are driven by growing microorganisms. Yet we know little about microbial responses to drought due to methodological limitations. Here, we estimate microbial growth rates in montane grassland soils exposed to ambient conditions, drought, and potential future climate conditions (i.e., soils exposed to 6 years of elevated temperatures and elevated CO₂ levels). For this purpose, we combined ¹⁸O-water vapor equilibration with quantitative stable isotope probing (termed ‘vapor-qSIP’) to measure taxon-specific microbial growth in dry soils. In our experiments, drought caused >90% of bacterial and archaeal taxa to stop dividing and reduced the growth rates of persisting ones. Under drought, growing taxa accounted for only 4% of the total community as compared to 35% in the controls. Drought-tolerant communities were dominated by specialized members of the Actinobacteriota, particularly the genus Streptomyces. Six years of pre-exposure to future climate conditions (3 °C warming and + 300 ppm atmospheric CO₂) alleviated drought effects on microbial growth, through more drought-tolerant taxa across major phyla, accounting for 9% of the total community. Our results provide insights into the response of active microbes to drought today and in a future climate, and highlight the importance of studying drought in combination with future climate conditions to capture interactive effects and improve predictions of future soil-climate feedbacks.

Predicting ecosystem function is critical to assess and mitigate the impacts of climate change. Quantitative predictions of microbially mediated ecosystem processes are typically uninformed by microbial biodiversity. Yet new tools allow the measurement of taxon-specific traits within natural microbial communities. There is mounting evidence of a phylogenetic signal in these traits, which may support prediction and microbiome management frameworks. We investigated phylogeny-based trait prediction using bacterial growth rates from soil communities in Arctic, boreal, temperate, and tropical ecosystems. Here we show that phylogeny predicts growth rates of soil bacteria, explaining an average of 31%, and up to 58%, of the variation within ecosystems. Despite limited overlap in community composition across these ecosystems, shared nodes in the phylogeny enabled ancestral trait reconstruction and cross-ecosystem predictions. Phylogenetic relationships could explain up to 38% (averaging 14%) of the variation in growth rates across the highly disparate ecosystems studied. Our results suggest that shared evolutionary history contributes to similarity in the relative growth rates of related bacteria in the wild, allowing phylogeny-based predictions to explain a substantial amount of the variation in taxon-specific functional traits, within and across ecosystems.

Candidate bacterial phylum Omnitrophota has not been isolated and is poorly understood. We analysed 72 newly sequenced and 349 existing Omnitrophota genomes representing 6 classes and 276 species, along with Earth Microbiome Project data to evaluate habitat, metabolic traits and lifestyles. We applied fluorescence-activated cell sorting and differential size filtration, and showed that most Omnitrophota are ultra-small (~0.2 μm) cells that are found in water, sediments and soils. Omnitrophota genomes in 6 classes are reduced, but maintain major biosynthetic and energy conservation pathways, including acetogenesis (with or without the Wood-Ljungdahl pathway) and diverse respirations. At least 64% of Omnitrophota genomes encode gene clusters typical of bacterial symbionts, suggesting host-associated lifestyles. We repurposed quantitative stable-isotope probing data from soils dominated by andesite, basalt or granite weathering and identified 3 families with high isotope uptake consistent with obligate bacterial predators. We propose that most Omnitrophota inhabit various ecosystems as predators or parasites.

Study of life history strategies may help predict the performance of microorganisms in nature by organizing the complexity of microbial communities into groups of organisms with similar strategies. Here, we tested the extent that one common application of life history theory, the copiotroph-oligotroph framework, could predict the relative population growth rate of bacterial taxa in soils from four different ecosystems. We measured the change of in situ relative growth rate to added glucose and ammonium using both ¹⁸O–H₂O and ¹³C quantitative stable isotope probing to test whether bacterial taxa sorted into copiotrophic and oligotrophic groups. We saw considerable overlap in nutrient responses across most bacteria regardless of phyla, with many taxa growing slowly and few taxa that grew quickly. To define plausible life history boundaries based on in situ relative growth rates, we applied Gaussian mixture models to organisms’ joint ¹⁸O–¹³C signatures and found that across experimental replicates, few taxa could consistently be assigned as copiotrophs, despite their potential for fast growth. When life history classifications were assigned based on average relative growth rate at varying taxonomic levels, finer resolutions (e.g., genus level) were significantly more effective in capturing changes in nutrient response than broad taxonomic resolution (e.g., phylum level). Our results demonstrate the difficulty in generalizing bacterial life history strategies to broad lineages, and even to single organisms across a range of soils and experimental conditions. We conclude that there is a continued need for the direct measurement of microbial communities in soil to advance ecologically realistic frameworks.

The growth and physiology of soil microorganisms, which play vital roles in biogeochemical cycling, are likely dependent on current and prior soil moisture levels. Here, we developed and applied a genome-resolved metagenomic implementation of quantitative stable isotope probing (qSIP) to an H ₂ ¹⁸ O labeling experiment to determine which microbial community members, and with what capacities, are growing under in situ conditions. qSIP enabled measurement of taxon-specific growth because isotopic incorporation into microbial DNA requires production of new genome copies. We studied three Mediterranean grassland soils across a rainfall gradient to evaluate the hypothesis that historic precipitation levels are an important factor controlling trait selection. We used qSIP-informed genome-resolved metagenomics to resolve an active subset of soil community members and identify the ecophysiological traits that characterize them. Higher year-round precipitation levels correlated with higher activity and growth rates of flagellar motile microorganisms. In addition to bacteria that were heavily isotopically labeled, we identified abundant isotope-labeled phages suggesting phage-induced cell lysis likely contributed to necromass production at all three sites. Further, there was a positive correlation between phage activity and the activity of putative phage hosts. Contrary to our expectations, the capabilities to decompose the diverse complex carbohydrates common in soil necromass or oxidize methanol and carbon monoxide were broadly distributed across active and inactive bacteria in all three soils, implying that these traits are not highly selected for by historical precipitation.

Candidate bacterial phylum Omnitrophota has never been grown in axenic culture and is poorly understood. Here, we combined analysis of 421 Omnitrophota genomes representing six classes and 276 species and show that they are prevalent in water, sediments, and soils globally. Fluorescence-activated cell sorting and differential size filtration showed ultra-small (~0.2 μm) cells to be common across the phylum. Reduced genomes in all six classes maintained major biosynthetic and energy conservation pathways, particularly the acetogenic Wood-Ljungdahl pathway or diverse aerobic and anaerobic respirations. However, most genomes also encoded multiple systems typical of bacterial predators and intracellular parasites, suggesting possible predatory or parasitic lifestyles. In support of this, quantitative stable-isotope probing revealed three families with high isotope uptake rates comparable to obligate bacterial predators in diverse soils. Based on their ubiquity, small cell size, high metabolic activity, and genomic repertoire, many Omnitrophota are likely to be ecologically important in a wide range of ecosystems, possibly as predators or parasites.

Soil microorganisms shape global element cycles in life and death. Living soil microorganisms are a major engine of terrestrial biogeochemistry, driving the turnover of soil organic matter — Earth’s largest terrestrial carbon pool and the primary source of plant nutrients. Their metabolic functions are influenced by ecological interactions with other soil microbial populations, soil fauna and plants, and the surrounding soil environment. Remnants of dead microbial cells serve as fuel for these biogeochemical engines because their chemical constituents persist as soil organic matter. This non-living microbial biomass accretes over time in soil, forming one of the largest pools of organic matter on the planet. In this Review, we discuss how the biogeochemical cycling of organic matter depends on both living and dead soil microorganisms, their functional traits, and their interactions with the soil matrix and other organisms. With recent omics advances, many of the traits that frame microbial population dynamics and their ecophysiological adaptations can be deciphered directly from assembled genomes or patterns of gene or protein expression. Thus, it is now possible to leverage a trait-based understanding of microbial life and death within improved biogeochemical models and to better predict ecosystem functioning under new climate regimes.

The nonconsumptive effects of predators on prey include behavioral, physiological, and life-history changes that reduce the risk of predation but have associated energetic or fitness costs to prey individuals and populations. Biologists have documented such changes for a wide array of predator–prey interactions in a variety of ecosystems; however, the energetic cost of nonconsumptive effects to prey populations has rarely been measured directly. Using a reach-scale manipulation of a naturally-fishless stream, we added chemical cues produced by live Brook Trout (Salvelinus fontinalis Mitchill, 1814) to simulate the presence of trout predation risk, and we quantified the impact of nonconsumptive effects on the secondary production of mayfly prey in the stream. The addition of trout chemical cues reduced the secondary production of larval Baetis mayflies in the treatment reach by 17% compared to an upstream, unmanipulated reference reach. This reduction was driven by smaller body size and earlier emergence of mayflies from the reach with added predator cues. The nonconsumptive effects of a predator can consequently reduce the flux of energy through a dominant stream invertebrate by altering individual life-history and development patterns. Furthermore, quantifying the population-level impact of nonconsumptive effects enables understanding the extent to which these widespread predator effects shape food-web dynamics and ecosystem processes.