Microbial rRNA Synthesis and Growth Compared through Quantitative Stable Isotope Probing with H218O

Advances and perspectives of using stable isotope probing (SIP)-based technologies in contaminant biodegradation

Stable isotope probing (SIP) is a powerful tool to study microbial community structure and function in both nature and engineered environments. Coupling with advanced genomics and other techniques, SIP studies have generated substantial information to allow researchers to draw a clearer picture of what is occurring in complex microbial ecosystems. This review provides an overview of the advances of SIP-based technologies over time, summarizes the status of SIP applications to contaminant biodegradation, provides critical perspectives on ecological interactions within the community, and important factors (controllable and non-controllable) to be considered in SIP experimental designs and data interpretation. Current trend and perspectives of adapting SIP techniques for environmental applications are also discussed.

Melanization slows the rapid movement of fungal necromass carbon and nitrogen into both bacterial and fungal decomposer communities and soils

Microbial necromass contributes significantly to both soil carbon (C) persistence and ecosystem nitrogen (N) availability, but quantitative estimates of C and N movement from necromass into soils and decomposer communities are lacking. Additionally, while melanin is known to slow fungal necromass decomposition, how it influences microbial C and N acquisition as well as elemental release into soils remains unclear. Here, we tracked decomposition of isotopically labeled low and high melanin fungal necromass and measured 13C and 15N accumulation in surrounding soils and microbial communities over 77 d in a temperate forest in Minnesota, USA. Mass loss was significantly higher from low melanin necromass, corresponding with greater 13C and 15N soil inputs. A taxonomically and functionally diverse array of bacteria and fungi was enriched in 13C and/or 15N at all sampling points, with enrichment being consistently higher on low melanin necromass and earlier in decomposition. Similar patterns of preferential C and N enrichment of many bacterial and fungal genera early in decomposition suggest that both microbial groups co-contribute to the rapid assimilation of resource-rich soil organic matter inputs. While overall richness of taxa enriched in C was higher than in N for both bacteria and fungi, there was a significant positive relationship between C and N in co-enriched taxa. Collectively, our results demonstrate that melanization acts as a key ecological trait mediating not only fungal necromass decomposition rate but also necromass C and N release and that both elements are rapidly co-utilized by diverse bacterial and fungal decomposers in natural settings. IMPORTANCE Recent studies indicate that microbial dead cells, particularly those of fungi, play an important role in long-term carbon persistence in soils. Despite this growing recognition, how the resources within dead fungal cells (also known as fungal necromass) move into decomposer communities and soils are poorly quantified, particularly in studies based in natural environments. In this study, we found that the contribution of fungal necromass to soil carbon and nitrogen availability was slowed by the amount of melanin present in fungal cell walls. Further, despite the overall rapid acquisition of carbon and nitrogen from necromass by a diverse range of both bacteria and fungi, melanization also slowed microbial uptake of both elements. Collectively, our results indicate that melanization acts as a key ecological trait mediating not only fungal necromass decomposition rate, but also necromass carbon and nitrogen release into soil as well as microbial resource acquisition.

Diversity and assembly of active bacteria and their potential function along soil aggregates in a paddy field

Numerous studies have found that soil microbiomes differ at the aggregate level indicating they provide spatially heterogeneous habitats for microbial communities to develop. However, an understanding of the assembly processes and the functional profile of microbes at the aggregate level remain largely rudimentary, particularly for those active members in soil aggregates. In this study, we investigated the diversity, co-occurrence network, assembly process and predictive functional profile of active bacteria in aggregates of different sizes using H₂¹⁸O-based DNA stable isotope probing (SIP) and 16S rRNA gene sequencing. Most of the bacterial reads were active with 91 % of total reads incorporating labelled water during the incubation. The active microbial community belonged mostly of Proteobacteria and Actinobacteria, with a relative abundance of 55.32 % and 28.12 %, respectively. Assembly processes of the active bacteria were more stochastic than total bacteria, while the assembly processes of total bacteria were more influenced by deterministic processes. Furthermore, many functional profiles such as environmental information processing increased in active bacteria (19.39 %) compared to total bacteria (11.22 %). After incubation, the diversity and relative abundance of active bacteria of certain phyla increased, such as Proteobacteria (50.70 % to 59.95 %), Gemmatimonadetes (2.63 % to 4.11 %), and Bacteroidetes (1.50 % to 2.84 %). In small macroaggregates (SMA: 0.25-2 mm), the active bacterial community and its assembly processes differed from that of other soil aggregates (MA: microaggregates, <0.25 mm; LMA: large macroaggregates, 2-4 mm). For functional profiles, the relative abundance of important functions, such as amino acid metabolism, signal transduction and cell motility, increased with incubation days and/or in SMA compared to other aggregates. This study provides robust evidence that the community of active bacteria and its assembly processes in soil aggregates differed from total bacteria, and suggests the importance of dominant active bacteria (such as Proteobacteria) for the predicted functional profiles in the soil ecosystem.

Quantitative Stable-Isotope Probing (qSIP) with Metagenomics Links Microbial Physiology and Activity to Soil Moisture in Mediterranean-Climate Grassland Ecosystems

The growth and physiology of soil microorganisms, which play vital roles in biogeochemical cycling, are shaped by both current and historical soil environmental conditions. Here, we developed and applied a genome-resolved metagenomic implementation of quantitative stable isotope probing (qSIP) with an H₂¹⁸O labeling experiment to identify actively growing soil microorganisms and their genomic capacities. 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 the active subset of soil community members and identify their characteristic ecophysiological traits. Higher year-round precipitation levels correlated with higher activity and growth rates of flagellar motile microorganisms. In addition to heavily isotopically labeled bacteria, 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 capacity to decompose the diverse complex carbohydrates common in soil organic matter 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. IMPORTANCE Soil moisture is a critical factor that strongly shapes the lifestyle of soil organisms by changing access to nutrients, controlling oxygen diffusion, and regulating the potential for mobility. We identified active microorganisms in three grassland soils with similar mineral contexts, yet different historic rainfall inputs, by adding water labeled with a stable isotope and tracking that isotope in DNA of growing microbes. By examining the genomes of active and inactive microorganisms, we identified functions that are enriched in growing organisms, and showed that different functions were selected for in different soils. Wetter soil had higher activity of motile organisms, but activity of pathways for degradation of soil organic carbon compounds, including simple carbon substrates, were comparable for all three soils. We identified many labeled, and thus active bacteriophages (viruses that infect bacteria), implying that the cells they killed contributed to soil organic matter. The activity of these bacteriophages was significantly correlated with activity of their hosts.

Soil minerals affect taxon-specific bacterial growth

Secondary minerals (clays and metal oxides) are important components of the soil matrix. Clay minerals affect soil carbon persistence and cycling, and they also select for distinct microbial communities. Here we show that soil mineral assemblages-particularly short-range order minerals-affect both bacterial community composition and taxon-specific growth. Three soils with different parent material and presence of short-range order minerals were collected from ecosystems with similar vegetation and climate. These three soils were provided with ¹⁸O-labeled water and incubated with or without artificial root exudates or pine needle litter. Quantitative stable isotope probing was used to determine taxon-specific growth. We found that the growth of bacteria varied among soils of different mineral assemblages but found the trend of growth suppression in the presence of short-range order minerals. Relative growth of bacteria declined with increasing concentration of short-range order minerals between 25-36% of taxa present in all soils. Carbon addition in the form of plant litter or root exudates weakly affected relative growth of taxa (p = 0.09) compared to the soil type (p < 0.01). However, both exudate and litter carbon stimulated growth for at least 34% of families in the soils with the most and least short-range order minerals. In the intermediate short-range order soil, fresh carbon reduced growth for more bacterial families than were stimulated. These results highlight how bacterial-mineral-substrate interactions are critical to soil organic carbon processing, and how growth variation in bacterial taxa in these interactions may contribute to soil carbon persistence and loss.

Response of Total (DNA) and Metabolically Active (RNA) Microbial Communities in Miscanthus × Giganteus Cultivated Soil to Different Nitrogen Fertilization Rates

Miscanthus × giganteus is a promising high-yielding perennial plant to meet growing bioenergy demands; however, the degree to which the soil microbiome affects its nitrogen cycling and subsequently, biomass yield remains unclear. In this study, we hypothesize that contributions of metabolically active soil microbial membership may be underestimated with DNA-based approaches. We assessed the response of the soil microbiome to nitrogen availability in terms of both DNA and RNA soil microbial communities from the Long-term Assessment of Miscanthus Productivity and Sustainability (LAMPS) field trial. DNA and RNA were extracted from 271 samples, and 16S small subunit (SSU) rRNA amplicon sequencing was performed to characterize microbial community structure. Significant differences were observed in the resulting soil microbiomes and were best explained by the sequencing library of origin, either DNA or RNA. Similar numbers of membership were detected in DNA and RNA microbial communities, with more than 90% of membership shared. However, the profile of dominant membership within DNA and RNA differed, with varying proportions of Actinobacteria and Proteobacteria and Firmicutes and Proteobacteria. Only RNA microbial communities showed seasonal responses to nitrogen fertilization, and these differences were associated with nitrogen-cycling bacteria. The relative abundance of bacteria associated with nitrogen cycling was 7-fold higher in RNA than in DNA, and genes associated with denitrifying bacteria were significantly enriched in RNA, suggesting that these bacteria may be underestimated with DNA-only approaches. Our findings indicate that RNA-based SSU characterization can be a significant and complementing resource for understanding the role of soil microbiomes in bioenergy crop production. IMPORTANCEMiscanthus × giganteus is a promising candidate for bioeconomy cropping systems; however, it remains unclear how the soil microbiome supplies nitrogen to this low-input crop. DNA-based techniques are used to provide community characterization, but may miss important metabolically active taxa. By analyzing both DNA- and actively transcribed RNA-based microbial communities, we found that nitrogen cycling taxa in the soil microbiome may be underestimated using only DNA-based approaches. Accurately understanding the role of microbes and how they cycle nutrients is important for the development of sustainable bioenergy crops, and RNA-based approaches are recommended as a complement to DNA approaches to better understand the microbial, plant, and management interactions.

Decreased growth of wild soil microbes after 15 years of transplant-induced warming in a montane meadow

The carbon stored in soil exceeds that of plant biomass and atmospheric carbon and its stability can impact global climate. Growth of decomposer microorganisms mediates both the accrual and loss of soil carbon. Growth is sensitive to temperature and given the vast biological diversity of soil microorganisms, the response of decomposer growth rates to warming may be strongly idiosyncratic, varying among taxa, making ecosystem predictions difficult. Here, we show that 15 years of warming by transplanting plant-soil mesocosms down in elevation, strongly reduced the growth rates of soil microorganisms, measured in the field using undisturbed soil. The magnitude of the response to warming varied among microbial taxa. However, the direction of the response-reduced growth-was universal and warming explained twofold more variation than did the sum of taxonomic identity and its interaction with warming. For this ecosystem, most of the growth responses to warming could be explained without taxon-specific information, suggesting that in some cases microbial responses measured in aggregate may be adequate for climate modeling. Long-term experimental warming also reduced soil carbon content, likely a consequence of a warming-induced increase in decomposition, as warming-induced changes in plant productivity were negligible. The loss of soil carbon and decreased microbial biomass with warming may explain the reduced growth of the microbial community, more than the direct effects of temperature on growth. These findings show that direct and indirect effects of long-term warming can reduce growth rates of soil microbes, which may have important feedbacks to global warming.

Toward a function-first framework to make soil microbial ecology predictive

Soil microbial communities perform vital ecosystem functions, such as the decomposition of organic matter to provide plant nutrition. However, despite the functional importance of soil microorganisms, attribution of ecosystem function to particular constituents of the microbial community has been impeded by a lack of information linking microbial function to community composition and structure. Here, we propose a function-first framework to predict how microbial communities influence ecosystem functions. We first view the microbial community associated with a specific function as a whole and describe the dependence of microbial functions on environmental factors (e.g., the intrinsic temperature dependence of bacterial growth rates). This step defines the aggregate functional response curve of the community. Second, the contribution of the whole community to ecosystem function can be predicted, by combining the functional response curve with current environmental conditions. Functional response curves can then be linked with taxonomic data in order to identify sets of "biomarker" taxa that signal how microbial communities regulate ecosystem functions. Ultimately, such indicator taxa may be used as a diagnostic tool, enabling predictions of ecosystem function from community composition. In this paper, we provide three examples to illustrate the proposed framework, whereby the dependence of bacterial growth on environmental factors, including temperature, pH, and salinity, is defined as the functional response curve used to interlink soil bacterial community structure and function. Applying this framework will make it possible to predict ecosystem functions directly from microbial community composition.

Stabilising role of seed banks and the maintenance of bacterial diversity

Coexisting species often exhibit negative frequency dependence due to mechanisms that promote population growth and persistence when rare. These stabilising mechanisms can maintain diversity through interspecific niche differences, but also through life-history strategies like dormancy that buffer populations in fluctuating environments. However, there are few tests demonstrating how seed banks contribute to long-term community dynamics and the maintenance of diversity. Using a multi-year, high-frequency time series of bacterial community data from a north temperate lake, we documented patterns consistent with stabilising coexistence. Bacterial taxa exhibited differential responses to seasonal environmental conditions, while seed bank dynamics helped maintain diversity over less-favourable winter periods. Strong negative frequency dependence in rare, but metabolically active, taxa suggested a role for biotic interactions in promoting coexistence. Together, our results provide field-based evidence that niche differences and seed banks contribute to recurring community dynamics and the long-term maintenance of diversity in nature.

Community structure - Ecosystem function relationships in the Congo Basin methane cycle depend on the physiological scale of function

Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here, we argue that this stems from at least three issues: (a) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge; (b) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge; and (c) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. We test these assertions using methane (CH₄ )-cycling processes in soil samples collected along a wetland-to-upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and statistically control for environmental covariates to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high-affinity CH₄ oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine-scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.

Bioorthogonal non-canonical amino acid tagging reveals translationally active subpopulations of the cystic fibrosis lung microbiota

Culture-independent studies of cystic fibrosis lung microbiota have provided few mechanistic insights into the polymicrobial basis of disease. Deciphering the specific contributions of individual taxa to CF pathogenesis requires comprehensive understanding of their ecophysiology at the site of infection. We hypothesize that only a subset of CF microbiota are translationally active and that these activities vary between subjects. Here, we apply bioorthogonal non-canonical amino acid tagging (BONCAT) to visualize and quantify bacterial translational activity in expectorated sputum. We report that the percentage of BONCAT-labeled (i.e. active) bacterial cells varies substantially between subjects (6-56%). We use fluorescence-activated cell sorting (FACS) and genomic sequencing to assign taxonomy to BONCAT-labeled cells. While many abundant taxa are indeed active, most bacterial species detected by conventional molecular profiling show a mixed population of both BONCAT-labeled and unlabeled cells, suggesting heterogeneous growth rates in sputum. Differentiating translationally active subpopulations adds to our evolving understanding of CF lung disease and may help guide antibiotic therapies targeting bacteria most likely to be susceptible.

Glucose triggers strong taxon-specific responses in microbial growth and activity: insights from DNA and RNA qSIP

Growth of soil microorganisms is often described as carbon limited, and adding labile carbon to soil often results in a transient and large increase in respiration. In contrast, soil microbial biomass changes little, suggesting that growth and respiration are decoupled in response to a carbon pulse. Alternatively, measuring bulk responses of the entire community (total respiration and biomass) could mask ecologically important variation among taxa in response to the added carbon. Here, we assessed taxon-specific variation in cellular growth (measured as DNA synthesis) and metabolic activity (measured as rRNA synthesis) following glucose addition to soil using quantitative stable isotope probing with H₂ ¹⁸ O. We found that glucose addition altered rates of DNA and rRNA synthesis, but the effects were strongly taxon specific: glucose stimulated growth and rRNA transcription for some taxa, and suppressed these for others. These contrasting taxon-specific responses could explain the small and transient changes in total soil microbial biomass. Responses to glucose were not well predicted by a priori assignments of taxa into copiotrophic or oligotrophic categories. Across all taxa, rates of DNA and rRNA synthesis changed in parallel, indicating that growth and activity were coupled, and the degree of coupling was unaffected by glucose addition. This pattern argues against the idea that labile carbon addition causes a large reduction in metabolic growth efficiency; rather, the large pulse of respiration observed with labile substrate addition is more likely to be the result of rapid turnover of microbial biomass, possibly due to trophic interactions. Our results support a strong connection between rRNA synthesis and bacterial growth, and indicate that taxon-specific responses among soil bacteria can buffer responses at the scale of the whole community.

Use of RNA and DNA to Identify Mechanisms of Bacterial Community Homogenization

Biotic homogenization, i.e., the increase in community similarity through time or space, is a commonly observed response following conversion of native ecosystems to agriculture, but our understanding of the ecological mechanisms underlying this process is limited for bacterial communities. Identifying mechanisms of bacterial community homogenization following rapid environmental change may be complicated by the fact only a minority of taxa is active at any time. Here we used RNA- and DNA-based metabarcoding to distinguish putatively active taxa in the bacterial community from inactive taxa. We asked how soil bacterial communities respond to land use change following a rapid transition from rainforest to agriculture in the Congo Basin using a chronosequence that spans from roughly 1 week following slash-and-burn to an active plantation roughly 1.5 years post-conversion. Our results indicate that the magnitude of community homogenization is larger in the RNA-inferred community than the DNA-inferred perspective. We show that as the soil environment changes, the RNA-inferred community structure tracks environmental variation and loses spatial structure. The DNA-inferred community does not respond to environmental variability to the same degree, and is instead homogenized by a subset of taxa that is shared between forest and conversion sites. Our results suggest that complementing DNA-based surveys with RNA can provide insights into the way bacterial communities respond to environmental change.

Predictive genomic traits for bacterial growth in culture versus actual growth in soil

Relationships between microbial genes and performance are often evaluated in the laboratory in pure cultures, with little validation in nature. Here, we show that genomic traits related to laboratory measurements of maximum growth potential failed to predict the growth rates of bacteria in unamended soil, but successfully predicted growth responses to resource pulses: growth increased with 16S rRNA gene copy number and declined with genome size after substrate addition to soils, responses that were repeated in four different ecosystems. Genome size best predicted growth rate in response to addition of glucose alone; adding ammonium with glucose weakened the relationship, and the relationship was absent in nutrient-replete pure cultures, consistent with the idea that reduced genome size is a mechanism of nutrient conservation. Our findings demonstrate that genomic traits of soil bacteria can map to their ecological performance in nature, but the mapping is poor under native soil conditions, where genomic traits related to stress tolerance may prove more predictive. These results remind that phenotype depends on environmental context, underscoring the importance of verifying proposed schemes of trait-based strategies through direct measurement of performance in nature, an important and currently missing foundation for translating microbial processes from genes to ecosystems.

Predictive genomic traits for bacterial growth in culture versus actual growth in soil

Relationships between microbial genes and performance are often evaluated in the laboratory in pure cultures, with little validation in nature. Here, we show that genomic traits related to laboratory measurements of maximum growth potential failed to predict the growth rates of bacteria in unamended soil, but successfully predicted growth responses to resource pulses: growth increased with 16S rRNA gene copy number and declined with genome size after substrate addition to soils, responses that were repeated in four different ecosystems. Genome size best predicted growth rate in response to addition of glucose alone; adding ammonium with glucose weakened the relationship, and the relationship was absent in nutrient-replete pure cultures, consistent with the idea that reduced genome size is a mechanism of nutrient conservation. Our findings demonstrate that genomic traits of soil bacteria can map to their ecological performance in nature, but the mapping is poor under native soil conditions, where genomic traits related to stress tolerance may prove more predictive. These results remind that phenotype depends on environmental context, underscoring the importance of verifying proposed schemes of trait-based strategies through direct measurement of performance in nature, an important and currently missing foundation for translating microbial processes from genes to ecosystems.

16S rRNA/rRNA Gene Ratios and Cell Activity Staining Reveal Consistent Patterns of Microbial Activity in Plant-Associated Soil

Although the majority of microorganisms in natural ecosystems are dormant, relatively little is known about the dynamics of the active and dormant microbial pools through both space and time. The limited knowledge of microbial activity-dormancy dynamics is in part due to uncertainty in the methods currently used to quantify active taxa. Here, we directly compared two of the most common methods (16S ratios and active cell staining) for estimating microbial activity in plant-associated soil and found that they were largely in agreement in the overarching patterns. Our results suggest that 16S ratios and active cell staining provide complementary information for measuring and interpreting microbial activity-dormancy dynamics in soils. They also support the idea that 16S rRNA/rRNA gene ratios have comparative value and offer a high-throughput, sequencing-based option for understanding relative changes in microbiome activity, as long as this method is coupled with quantification of community size.

At any given time, only a subset of microbial community members are active in their environment. The others are in a state of dormancy, with strongly reduced metabolic rates. It is of interest to distinguish active and inactive microbial cells and taxa to understand their functional contributions to ecosystem processes and to understand shifts in microbial activity in response to change. Of the methods used to assess microbial activity-dormancy dynamics, 16S rRNA/rRNA gene amplicons (16S ratios) and active cell staining with 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) are two of the most common, yet each method has limitations. Given that in situ activity-dormancy dynamics are proxied only by laboratory methods, further study is needed to assess the level of agreement and potential complementarity of these methods. We conducted two experiments investigating microbial activity in plant-associated soils. First, we treated corn field soil with phytohormones to simulate plant soil stress signaling, and second, we used rhizosphere soil from common bean plants exposed to drought or nutrient enrichment. Overall, the 16S ratio and CTC methods exhibited similar patterns of relative activity across treatments when treatment effects were large, and the instances in which they differed could be attributed to changes in community size (e.g., cell death or growth). Therefore, regardless of the method used to assess activity, we recommend quantifying community size to inform ecological interpretation. Our results suggest that the 16S ratio and CTC methods report comparable patterns of activity that can be applied to observe ecological dynamics over time, space, or experimental treatment.

IMPORTANCE Although the majority of microorganisms in natural ecosystems are dormant, relatively little is known about the dynamics of the active and dormant microbial pools through both space and time. The limited knowledge of microbial activity-dormancy dynamics is in part due to uncertainty in the methods currently used to quantify active taxa. Here, we directly compared two of the most common methods (16S ratios and active cell staining) for estimating microbial activity in plant-associated soil and found that they were largely in agreement in the overarching patterns. Our results suggest that 16S ratios and active cell staining provide complementary information for measuring and interpreting microbial activity-dormancy dynamics in soils. They also support the idea that 16S rRNA/rRNA gene ratios have comparative value and offer a high-throughput, sequencing-based option for understanding relative changes in microbiome activity, as long as this method is coupled with quantification of community size.

What is new and relevant for sequencing-based microbiome research? A mini-review

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Sample storage and nucleic acid isolation influence microbiota compositions.

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Error-corrected amplicon sequence variants (ASVs) improve 16S rRNA analysis.

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Contamination and host cells confound and complicate microbiota analysis.

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Quantitative and active microbiota analyses can complement existing methods.

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Open data and protocol sharing increases transparency and reproducibility.

Microbiome research has transformed the scientific landscape, as reflected by the exponential increase in microbiome-related publications from many different disciplines. Host-associated microbial communities play a role for almost all aspects of human, animal and plant biology and health. Consequently, there are tremendous expectations for the development of new clinical, agricultural and biotechnological applications of microbiome research. However, the field continues to be largely shaped by descriptive studies, the mechanistic understanding of microbiome functions for their hosts remains fragmentary, and direct applications of microbiome research are lacking. The aim of this review is therefore to provide a general introduction to the technical opportunities and challenges of microbiome research, as well as to make experimental and bioinformatic recommendations, i.e. (i) to avoid, reduce and assess the confounding effects of sample storage, nucleic acid isolation and microbial contamination; (ii) to minimize non-microbial contributions in host-associated microbiome samples; (iii) to sharpen the focus on physiologically relevant microbiome features by distinguishing signals from metabolically active and inactive or dead microbes and by adopting quantitative methods; and (iv) to enforce open data and protocol policies in order increase the transparency, reproducibility and credibility of the field.

Quantifying population-specific growth in benthic bacterial communities under low oxygen using H218O

The benthos in estuarine environments often experiences periods of regularly occurring hypoxic and anoxic conditions, dramatically impacting biogeochemical cycles. How oxygen depletion affects the growth of specific uncultivated microbial populations within these diverse benthic communities, however, remains poorly understood. Here, we applied H₂¹⁸O quantitative stable isotope probing (qSIP) in order to quantify the growth of diverse, uncultured bacterial populations in response to low oxygen concentrations in estuarine sediments. Over the course of 7- and 28-day incubations with redox conditions spanning from hypoxia to euxinia (sulfidic), ¹⁸O labeling of bacterial populations exhibited different patterns consistent with micro-aerophilic, anaerobic, facultative anaerobic, and aerotolerant anaerobic growth. ¹⁸O-labeled populations displaying anaerobic growth had a significantly non-random phylogenetic distribution, exhibited by numerous clades currently lacking cultured representatives within the Planctomycetes, Actinobacteria, Latescibacteria, Verrucomicrobia, and Acidobacteria. Genes encoding the beta-subunit of the dissimilatory sulfate reductase (dsrB) became ¹⁸O labeled only during euxinic conditions. Sequencing of these ¹⁸O-labeled dsrB genes showed that Acidobacteria were the dominant group of growing sulfate-reducing bacteria, highlighting their importance for sulfur cycling in estuarine sediments. Our findings provide the first experimental constraints on the redox conditions underlying increased growth in several groups of "microbial dark matter", validating hypotheses put forth by earlier metagenomic studies.

Metabarcoding reveals that rhizospheric microbiota of Quercus pyrenaica is composed by a relatively small number of bacterial taxa highly abundant

Melojo oak (Quercus pyrenaica Willd.) is a key tree species of Mediterranean forests; however, these forests show an advanced stage of deterioration in the Iberian Peninsula. Plant-associated microorganisms play an essential role improving their host’s fitness, hence, a better understanding of oak rhizospheric microbiome, especially of those active members, could be the first step towards microbiome-based approaches for oak-forest improvement. Here we reported, for the first time, the diversity of total (DNA-based) and potentially active (RNA-based) bacterial communities of different melojo-oak forest formations through pyrosequencing of 16S rRNA gene amplicons. We found that potentially active bacterial communities were as rich and diverse as total bacterial communities, but different in terms of relative abundance patterns in some of the studied areas. Both core microbiomes were dominated by a relatively small percentage of OTUs, most of which showed positive correlation between both libraries. However, the uncoupling between abundance (rDNA) and potential activity (rRNA) for some taxa suggests that the most abundant taxa are not always the most active, and that low-abundance OTUs may have a strong influence on oak’s rhizospheric ecology. Thus, measurement of rRNA:rDNA ratio could be helpful in identifying major players for the development of bacterial bioinoculants.