Disentangling direct from indirect relationships in association networks.

Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect interactions are pervasive in all types of networks. However, quantitatively disentangling direct and indirect relationships in networks remains a formidable task. Here, we present a framework, called iDIRECT (Inference of Direct and Indirect Relationships with Effective Copula-based Transitivity), for quantitatively inferring direct dependencies in association networks. Using copula-based transitivity, iDIRECT eliminates/ameliorates several challenging mathematical problems, including ill-conditioning, self-looping, and interaction strength overflow. With simulation data as benchmark examples, iDIRECT showed high prediction accuracies. Application of iDIRECT to reconstruct gene regulatory networks in Escherichia coli also revealed considerably higher prediction power than the best-performing approaches in the DREAM5 (Dialogue on Reverse Engineering Assessment and Methods project, #5) Network Inference Challenge. In addition, applying iDIRECT to highly diverse grassland soil microbial communities in response to climate warming showed that the iDIRECT-processed networks were significantly different from the original networks, with considerably fewer nodes, links, and connectivity, but higher relative modularity. Further analysis revealed that the iDIRECT-processed network was more complex under warming than the control and more robust to both random and target species removal (P < 0.001). As a general approach, iDIRECT has great advantages for network inference, and it should be widely applicable to infer direct relationships in association networks across diverse disciplines in science and engineering.

Stimulation of soil respiration by elevated CO2 is enhanced under nitrogen limitation in a decade-long grassland study.

Whether and how CO2 and nitrogen (N) availability interact to influence carbon (C) cycling processes such as soil respiration remains a question of considerable uncertainty in projecting future C-climate feedbacks, which are strongly influenced by multiple global change drivers, including elevated atmospheric CO2 concentrations (eCO2) and increased N deposition. However, because decades of research on the responses of ecosystems to eCO2 and N enrichment have been done largely independently, their interactive effects on soil respiratory CO2 efflux remain unresolved. Here, we show that in a multifactor free-air CO2 enrichment experiment, BioCON (Biodiversity, CO2, and N deposition) in Minnesota, the positive response of soil respiration to eCO2 gradually strengthened at ambient (low) N supply but not enriched (high) N supply for the 12-y experimental period from 1998 to 2009. In contrast to earlier years, eCO2 stimulated soil respiration twice as much at low than at high N supply from 2006 to 2009. In parallel, microbial C degradation genes were significantly boosted by eCO2 at low but not high N supply. Incorporating those functional genes into a coupled C-N ecosystem model reduced model parameter uncertainty and improved the projections of the effects of different CO2 and N levels on soil respiration. If our observed results generalize to other ecosystems, they imply widely positive effects of eCO2 on soil respiration even in infertile systems.

Electrostimulation triggers an increase in cross-niche microbial associations toward enhancing organic nitrogen wastewater treatment.

As an efficient wastewater pretreatment biotechnology, electrostimulated hydrolysis acidification (eHA) has been used to accelerate the removal of refractory pollutants, which is closely related to the effects of electrostimulation on microbial interspecies associations. However, the ecological processes underpinning such linkages remain unresolved, especially for the microbial communities derived from different niches, such as the electrode surface and plankton. Herein, the principles of cross-niche microbial associations and community assembly were investigated using molecular ecological network and phylogenetic bin-based null model analysis (iCAMP) based on 16S rRNA gene sequences. The electrostimulated planktonic sludge and electrode biofilm displayed significantly (P < 0.05) 1.67 and 1.53 times higher organic nitrogen pollutant (azo dye Alizarin Yellow R) degradation efficiency than non-electrostimulation group, and the corresponding microbial community composition and structure were significantly (P < 0.05) changed. Electroactive bacteria and functional degraders were enriched in the electrode biofilm and planktonic sludge, respectively. Notably, electrostimulation strengthened the synergistic microbial associations (1.8 times more links) between sludge and biofilm members. Additionally, both electrostimulation and cross-niche microbial associations induced greater importance of deterministic assembly. Overall, this study highlights the specificity of cross-electrode surface microbial associations and ecological processes with electrostimulation and advances our understanding of the manipulation of sludge microbiomes in engineered wastewater treatment systems.

Towards revealing the global diversity and community assembly of soil eukaryotes.

Soil fungi, protists, and animals (i.e., the eukaryome) play a critical role in key ecosystem functions in terrestrial ecosystems. Yet, we lack a holistic understanding of the processes shaping the global distribution of the eukaryome. We conducted a molecular analysis of 193 composite soil samples spanning the world's major biomes. Our analysis showed that the importance of selection processes was higher in the community assemblage of smaller-bodied and wider niche breadth organisms. Soil pH and mean annual precipitation were the primary determinants of the community structure of eukaryotic microbes and animals, respectively. We further found contrasting latitudinal diversity patterns and strengths for soil eukaryotic microbes and animals. Our results point to a potential link between body size and niche breadth of soil eukaryotes and the relative effect of ecological processes and environmental factors in driving their biogeographic patterns.

Ecophysiological and genomic analyses of a representative isolate of highly abundant Bacillus cereus strains in contaminated subsurface sediments.

Bacillus cereus strain CPT56D-587-MTF (CPTF) was isolated from the highly contaminated Oak Ridge Reservation (ORR) subsurface. This site is contaminated with high levels of nitric acid and multiple heavy metals. Amplicon sequencing of the 16S rRNA genes (V4 region) in sediment from this area revealed an amplicon sequence variant (ASV) with 100% identity to the CPTF 16S rRNA sequence. Notably, this CPTF-matching ASV had the highest relative abundance in this community survey, with a median relative abundance of 3.77% and comprised 20%-40% of reads in some samples. Pangenomic analysis revealed that strain CPTF has expanded genomic content compared to other B. cereus species-largely due to plasmid acquisition and expansion of transposable elements. This suggests that these features are important for rapid adaptation to native environmental stressors. We connected genotype to phenotype in the context of the unique geochemistry of the site. These analyses revealed that certain genes (e.g. nitrate reductase, heavy metal efflux pumps) that allow this strain to successfully occupy the geochemically heterogenous microniches of its native site are characteristic of the B. cereus species while others such as acid tolerance are mobile genetic element associated and are generally unique to strain CPTF.

A general framework for quantitatively assessing ecological stochasticity.

Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. Here we propose a general mathematical framework to quantify ecological stochasticity under different situations in which deterministic factors drive the communities more similar or dissimilar than null expectation. An index, normalized stochasticity ratio (NST), was developed with 50% as the boundary point between more deterministic (<50%) and more stochastic (>50%) assembly. NST was tested with simulated communities by considering abiotic filtering, competition, environmental noise, and spatial scales. All tested approaches showed limited performance at large spatial scales or under very high environmental noise. However, in all of the other simulated scenarios, NST showed high accuracy (0.90 to 1.00) and precision (0.91 to 0.99), with averages of 0.37 higher accuracy (0.1 to 0.7) and 0.33 higher precision (0.0 to 1.8) than previous approaches. NST was also applied to estimate stochasticity in the succession of a groundwater microbial community in response to organic carbon (vegetable oil) injection. Our results showed that community assembly was shifted from more deterministic (NST = 21%) to more stochastic (NST = 70%) right after organic carbon input. As the vegetable oil was consumed, the community gradually returned to be more deterministic (NST = 27%). In addition, our results demonstrated that null model algorithms and community similarity metrics had strong effects on quantifying ecological stochasticity.

High historical variability weakens the effects of current climate differentiation on microbial community dissimilarity and assembly.

Understanding the influences of global climate change on soil microbial communities is essential in evaluating the terrestrial biosphere's feedback to this alarming anthropogenic disturbance. However, little is known about how intra-site historical climate variability can mediate the influences of current climate differences on community dissimilarity and assembly. To fill this gap, we examined and disentangled the interactive effects of historical climate variability and current climate differences on the soil bacterial community dissimilarity and stochasticity of community assembly among 143 sites from 28 forests across eastern China. We hypothesize that the relative importance of stochasticity and community dissimilarity are related to historical climate variability and that an increasing sum of intra-site historical variability enhances stochasticity while reduces dissimilarity between two communities. To test our hypothesis, we statistically controlled for covariates between sites including differences in soil chemistry, plant diversity, spatial distance, and seasonal climate variations at annual timescales. We observed that an increase in inter-site current climate differences led to a reduced impact of stochasticity in community assembly and a pronounced divergence between communities. In stark contrast, when communities were subjected to a high level of intra-site historical climate fluctuation, the observed impact incurred from current climate differences was substantially weakened. Moreover, the influence of increased historical variability was consistent along the gradient of current temperature differences between sites. However, effects induced by historical fluctuation in precipitation were disproportional and only evident when small inter-site differences were observed. Consequently, if the prior climate variability is ignored, especially regarding environmental factors like temperature, we assert that the influence current climate differentiation has on regulating community dissimilarity and assembly stochasticity will be underestimated. Together, our findings highlight the importance and need of explicitly controlling the mean and the historical variability of climate factors for the next "generation" of climate change experiments to come.

Biogeography and Assembly of Microbial Communities in Wastewater Treatment Plants in China.

Scientific understanding of microbial biogeography and assembly is lacking for activated sludge microbial communities, even though the diversity of microbial communities in wastewater treatment plants (WWTPs) is thought to have a direct influence on system performance. Here, utilizing large-scale 16S rRNA gene data generated from 211 activated sludge samples collected from 15 cities across China, we show activated sludge microbes, whose growth and metabolism can be regulated followed with the metabolic theory of ecology with an apparent Ea value (apparent activation energy) of 0.08 eV. WWTPs at a lower latitude tend to harbor a more diverse array of microorganisms. In agreement with the general understanding, the activated sludge microbial assembly was mainly driven by deterministic processes and the mean annual temperature was identified as the most important factor affecting the microbial community structure. The treatment process types with similar microbial growth types and functions had a distinct impact on the activated sludge microbial community structure only when WWTPs were located near each other and received similar influent. Overall, these findings provide us with a deeper understanding of activated sludge microbial communities from an ecological perspective. Moreover, these findings suggest that, for a given set of performance characteristics (e.g., combined nitrification, denitrification, and phosphorus removal), it may be difficult to employ common engineering levers to control additional aspects of community structure due to the influence of natural environmental factors.

Deterministic Assembly and Diversity Gradient Altered the Biofilm Community Performances of Bioreactors.

Community assembly process (determinism vs stochasticity) determines the composition and diversity of a microbial community, and then shapes its functions. Understanding this complex process and its relationship to the community functions becomes a very important task for the applications of microbial biotechnology. In this study, we applied microbial electrolysis cells (MECs) with moderate species numbers and easily tractable functions as a model ecosystem, and constructed a series of biofilm communities with gradient biodiversity to examine the roles of community assembly in determining microbial community structure and functions. After stable biofilms formed, the best MEC reactor performances (e.g., gas productivity, total energy efficiency) were achieved in the group in which biofilms had the second highest α-diversity, and biofilms with even lower diversity showed declining performance. Null model analyses indicated that both deterministic and stochastic assembly played roles in the formation of biofilm communities. When deterministic assembly dominates this formation, the higher diversity of the biofilm community would generally show better reactor performance. However, when the stochasticity dominates the assembly process, the bioreactor performance would decline. This study provides novel evidence that the assembly mechanism could be one of the key processes to shift the functions, and proposes an important guidance for selecting the most efficient microorganisms for environmental biotechnologies.

Deterministic and stochastic processes driving the shift in the prokaryotic community composition in wastewater treatment plants of a coastal Chinese city.

Wastewater treatment plants (WWTPs) rely mainly on the microbial assemblages to contribute significantly for the removal of organic pollutants and nutrients. However, limited information is available on the ecological driving forces underlying the turnover of prokaryotic communities across wastewater treatment processes (i.e., from influents (IFs) and effluents (EFs)) within WWTPs. Here, we used a combination of the 16S rRNA gene amplicon sequencing and a quantitative ecological null model analysis to explore the ecological processes governing the turnover of the prokaryotic communities and the dominant taxonomic taxa across wastewater treatment processes of five full-scale WWTPs in China. Our results indicated that a significant variation in the composition of prokaryotic communities and the dominant taxa between IFs and EFs. The analysis of the environmental sources of indicator OTUs showed that a relatively lower abundance of the sludge/sewage and human guts associated OTUs in EFs than in IFs. Ecological null models revealed that among the ecological processes, deterministic processes were dominant in controlling the turnover of the overall communities from IFs to EFs, whereas the relative importance of deterministic processes varied among the dominant taxa (i.e., Bacteroidetes > Proteobacteria > Gammaproteobacteria > Firmicutes > Betaproteobacteria). However, the assembly of IF and EF communities was influenced mainly by the deterministic and stochastic processes, respectively. In addition, our results indicated that EF communities have a higher phylogenetic diversity than those of the IF communities, but the abundance of prokaryotic 16S rRNA genes was lower in EFs than in IFs. Overall, our study provides a novel insight of the assembly mechanisms underlying the turnover of prokaryotic communities during wastewater treatment processes.

Microbial community assembly differs across minerals in a rhizosphere microcosm.

Mineral-associated microbes drive many critical soil processes, including mineral weathering, soil aggregation and cycling of mineral-sorbed organic matter. To investigate the interactions between soil minerals and microbes in the rhizosphere, we incubated three types of minerals (ferrihydrite, kaolinite and quartz) and a native soil mineral fraction near roots of a common Californian annual grass, Avena barbata, growing in its resident soil. We followed microbial colonization of these minerals for up to 2.5 months - the plant's lifespan. Bacteria and fungi that colonized mineral surfaces during this experiment differed across mineral types and differed from those in the background soil, implying that microbial colonization was the result of processes in addition to passive movement with water to mineral surfaces. Null model analysis revealed that dispersal limitation was a dominant factor structuring mineral-associated microbial communities for all mineral types. Once bacteria arrived at a mineral surface, capacity for rapid growth appeared important, as ribosomal copy number was significantly correlated with relative enrichment on minerals. Glomeromycota (a phylum associated with arbuscular mycorrhizal fungi) appeared to preferentially associate with ferrihydrite surfaces. The mechanisms enabling the colonization of soil minerals may be foundational in shaping the overall soil microbiome composition and development of persistent organic matter in soils.

Spatial scaling of forest soil microbial communities across a temperature gradient.

Temperature is an important correlate of global patterns of biodiversity, yet the mechanisms driving these relationships are not well understood. Taxa-area relationships (TARs) have been intensively examined, but the effects of temperature on TARs, particularly for microbial communities, are largely undocumented. Here we present a continental-scale description of temperature-dependent nested TARs of microbial communities (bacteria and archaea) from soils of six forest sites spanning a temperature gradient from subalpine Colorado to tropical Panama. Our results revealed that spatial scaling rates (z-values) of microbial communities varied with both taxonomic resolutions and phylogenetic groups. Additionally, microbial TAR z-values increased with temperature (r = 0.739, P < 0.05), but were not correlated with other environmental variables tested (P > 0.05), indicating that microbial spatial scaling rate is temperature-dependent. Understanding how temperature affects the spatial scaling of microbial biodiversity is of fundamental importance for preservation of soil biodiversity and management of ecosystems.

Flavobacterium phocarum sp. nov., isolated from soils of a seal habitat in Antarctica.

A Gram-stain-negative, yellow-pigmented, non-flagellated, gliding, rod-shaped, oxidase-negative and catalase-positive bacterium, designated SE14T, was isolated from soil on King George Island, South Shetland Islands, Antarctica. Strain SE14T grew at 4-25 °C (optimum, 20 °C), at pH 6.0-9.0 (optimum, pH 7.0-7.5) and with 0-3.0 % NaCl (optimum, 1.0-1.5 %), and could not produce flexirubin-type pigments. 16S rRNA gene sequence analysis showed the the isolate belonged to the genus Flavobacterium. Strain SE14T had the highest 16S rRNA gene sequence similarity to Flavobacterium antarcticum, F. tegetincola and F. degerlachei with 95.8, 95.5 and 95.2 %, respectively. The strain SE14T consisted of a clade with Flavobacteriumnoncentrifugens (16S rRNA gene sequence similarity 94.9 %) and F. qiangtangense (16S rRNA gene sequence similarity 94.2 %) and simultaneously formed a distinct phyletic lineage in the neighbour-joining phylogenetic tree. Polar lipids of the strain included phosphatidylethanolamine and four unidentified aminolipids. Strain SE14T contained anteiso-C15 : 0, iso-C15 : 0 and a mixture of iso-C15 : 0 2-OH and/or C16 : 1ω7c as the main fatty acids, and the only respiratory quinone was menaquinone-6. The genomic DNA G+C content was 42.3 mol%. The polyphasic taxonomic study revealed that strain SE14T belongs to a novel species within the genus Flavobacterium , and the name Flavobacterium phocarum sp. nov. is proposed. The type strain is SE14T (=CCTCC AB 2017225T=KCTC 52612T).

Biodegradation of Polyethylene and Plastic Mixtures in Mealworms (Larvae of Tenebrio molitor) and Effects on the Gut Microbiome.

Recent studies have demonstrated the ability for polystyrene (PS) degradation within the gut of mealworms ( Tenebrio molitor). To determine whether plastics may be broadly susceptible to biodegradation within mealworms, we evaluated the fate of polyethylene (PE) and mixtures (PE + PS). We find that PE biodegrades at comparable rates to PS. Mass balances indicate conversion of up 49.0 ± 1.4% of the ingested PE into a putative gas fraction (CO2). The molecular weights ( Mn) of egested polymer residues decreased by 40.1 ± 8.5% in PE-fed mealworms and by 12.8 ± 3.1% in PS-fed mealworms. NMR and FTIR analyses revealed chemical modifications consistent with degradation and partial oxidation of the polymer. Mixtures likewise degraded. Our results are consistent with a nonspecific degradation mechanism. Analysis of the gut microbiome by next-generation sequencing revealed two OTUs ( Citrobacter sp. and Kosakonia sp.) strongly associated with both PE and PS as well as OTUs unique to each plastic. Our results suggest that adaptability of the mealworm gut microbiome enables degradation of chemically dissimilar plastics.

Nearly a decade-long repeatable seasonal diversity patterns of bacterioplankton communities in the eutrophic Lake Donghu (Wuhan, China).

Uncovering which environmental factors govern community diversity patterns and how ecological processes drive community turnover are key questions related to understand the community assembly. However, the ecological mechanisms regulating long-term variations of bacterioplankton communities in lake ecosystems remain poorly understood. Here we present nearly a decade-long study of bacterioplankton communities from the eutrophic Lake Donghu (Wuhan, China) using 16S rRNA gene amplicon sequencing with MiSeq platform. We found strong repeatable seasonal diversity patterns in terms of both common (detected in more than 50% samples) and dominant (relative abundance >1%) bacterial taxa turnover. Moreover, community composition tracked the seasonal temperature gradient, indicating that temperature is a key environmental factor controlling observed diversity patterns. Total phosphorus also contributed significantly to the seasonal shifts in bacterioplankton composition. However, any spatial pattern of bacterioplankton communities across the main lake areas within season was overwhelmed by their temporal variabilities. Phylogenetic analysis further indicated that 75%-82% of community turnover was governed by homogeneous selection due to consistent environmental conditions within seasons, suggesting that the microbial communities in Lake Donghu are mainly controlled by niche-based processes. Therefore, dominant niches available within seasons might be occupied by similar combinations of bacterial taxa with modest dispersal rates throughout different lake areas.

Biogeochemistry drives diversity in the prokaryotes, fungi, and invertebrates of a Panama forest.

Humans are both fertilizing the world and depleting its soils, decreasing the diversity of aquatic ecosystems and terrestrial plants in the process. We know less about how nutrients shape the abundance and diversity of the prokaryotes, fungi, and invertebrates of Earth's soils. Here we explore this question in the soils of a Panama forest subject to a 13-yr fertilization with factorial combinations of nitrogen (N), phosphorus (P), and potassium (K) and a separate micronutrient cocktail. We contrast three hypotheses linking biogeochemistry to abundance and diversity. Consistent with the Stress Hypothesis, adding N suppressed the abundance of invertebrates and the richness of all three groups of organisms by ca. 1 SD or more below controls. Nitrogen addition plots were 0.8 pH units more acidic with 18% more exchangeable aluminum, which is toxic to both prokaryotes and eukaryotes. These stress effects were frequently reversed, however, when N was added with P (for prokaryotes and invertebrates) and with added K (for fungi). Consistent with the Abundance Hypothesis, adding P generally increased prokaryote and invertebrate diversity, and adding K enhanced invertebrate diversity. Also consistent with the Abundance Hypothesis, increases in invertebrate abundance generated increases in richness. We found little evidence for the Competition Hypothesis: that single nutrients suppressed diversity by favoring a subset of high nutrient specialists, and that nutrient combinations suppressed diversity even more. Instead, combinations of nutrients, and especially the cation/micronutrient treatment, yielded the largest increases in richness in the two eukaryote groups. In sum, changes in soil biogeochemistry revealed a diversity of responses among the three dominant soil groups, positive synergies among nutrients, and-in contrast with terrestrial plants-the frequent enhancement of soil biodiversity.

Warming effects on grassland soil microbial communities are amplified in cool months.

Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (P < 0.05) the taxonomic and functional compositions of microbial communities. During the cool months (January to February and October to December), warming induced a soil microbiome with a higher genomic potential for carbon decomposition, community-level ribosomal RNA operon (rrn) copy numbers, and microbial metabolic quotients, suggesting that warming stimulated fast-growing microorganisms that enhanced carbon decomposition. Modeling analyses further showed that warming reduced the temperature sensitivity of microbial carbon use efficiency (CUE) by 28.7% when monthly average temperature was low, resulting in lower microbial CUE and higher heterotrophic respiration (Rh) potentials. Structural equation modeling showed that warming modulated both Rh and RS directly by altering soil temperature and indirectly by influencing microbial community traits, soil moisture, nitrate content, soil pH, and gross primary productivity. The modulation of Rh by warming was more pronounced in cooler months compared to warmer ones. Together, our findings reveal distinct warming-induced effects on microbial functional traits in cool months, challenging the norm of soil sampling only in the peak growing season, and advancing our mechanistic understanding of the seasonal pattern of RS and Rh sensitivity to warming.

Reproducible responses of geochemical and microbial successional patterns in the subsurface to carbon source amendment.

Carbon amendments designed to remediate environmental contamination lead to substantial perturbations when injected into the subsurface. For the remediation of uranium contamination, carbon amendments promote reducing conditions to allow microorganisms to reduce uranium to an insoluble, less mobile state. However, the reproducibility of these amendments and underlying microbial community assembly mechanisms have rarely been investigated in the field. In this study, two injections of emulsified vegetable oil were performed in 2009 and 2017 to immobilize uranium in the groundwater at Oak Ridge, TN, USA. Our objectives were to determine whether and how the injections resulted in similar abiotic and biotic responses and their underlying community assembly mechanisms. Both injections caused similar geochemical and microbial succession. Uranium, nitrate, and sulfate concentrations in the groundwater dropped following the injection, and specific microbial taxa responded at roughly the same time points in both injections, including Geobacter, Desulfovibrio, and members of the phylum Comamonadaceae, all of which are well established in uranium, nitrate, and sulfate reduction. Both injections induced a transition from relatively stochastic to more deterministic assembly of microbial taxonomic and phylogenetic community structures based on 16S rRNA gene analysis. We conclude that geochemical and microbial successions after biostimulation are reproducible, likely owing to the selection of similar phylogenetic groups in response to EVO injection.

Novel order-level lineage of ammonia-oxidizing archaea widespread in marine and terrestrial environments.

Ammonia-oxidizing archaea (AOA) are among the most ubiquitous and abundant archaea on Earth, widely distributed in marine, terrestrial, and geothermal ecosystems. However, the genomic diversity, biogeography, and evolutionary process of AOA populations in subsurface environments are vastly understudied compared to those in marine and soil systems. Here, we report a novel AOA order Candidatus (Ca.) Nitrosomirales which forms a sister lineage to the thermophilic Ca. Nitrosocaldales. Metagenomic and 16S rRNA gene-read mapping demonstrates the abundant presence of Nitrosomirales AOA in various groundwater environments and their widespread distribution across a range of geothermal, terrestrial, and marine habitats. Terrestrial Nitrosomirales AOA show the genetic capacity of using formate as a source of reductant and using nitrate as an alternative electron acceptor. Nitrosomirales AOA appear to have acquired key metabolic genes and operons from other mesophilic populations via horizontal gene transfer, including genes encoding urease, nitrite reductase, and V-type ATPase. The additional metabolic versatility conferred by acquired functions may have facilitated their radiation into a variety of subsurface, marine, and soil environments. We also provide evidence that each of the four AOA orders spans both marine and terrestrial habitats, which suggests a more complex evolutionary history for major AOA lineages than previously proposed. Together, these findings establish a robust phylogenomic framework of AOA and provide new insights into the ecology and adaptation of this globally abundant functional guild.

Experimental warming accelerates positive soil priming in a temperate grassland ecosystem.

Unravelling biosphere feedback mechanisms is crucial for predicting the impacts of global warming. Soil priming, an effect of fresh plant-derived carbon (C) on native soil organic carbon (SOC) decomposition, is a key feedback mechanism that could release large amounts of soil C into the atmosphere. However, the impacts of climate warming on soil priming remain elusive. Here, we show that experimental warming accelerates soil priming by 12.7% in a temperate grassland. Warming alters bacterial communities, with 38% of unique active phylotypes detected under warming. The functional genes essential for soil C decomposition are also stimulated, which could be linked to priming effects. We incorporate lab-derived information into an ecosystem model showing that model parameter uncertainty can be reduced by 32-37%. Model simulations from 2010 to 2016 indicate an increase in soil C decomposition under warming, with a 9.1% rise in priming-induced CO2 emissions. If our findings can be generalized to other ecosystems over an extended period of time, soil priming could play an important role in terrestrial C cycle feedbacks and climate change.