Quantitative stable isotope probing with H218O reveals that most bacterial taxa in soil synthesize new ribosomal RNA

Soil fungi remain active and invest in storage compounds during drought independent of future climate conditions

Microbial growth is central to soil carbon cycling. However, how microbial communities grow under climate change is still largely unexplored. Here we use a unique field experiment simulating future climate conditions (increased atmospheric CO2 and temperature) and drought concomitantly and investigate impacts on soil microbial activity. We trace 2H or 18O applied via water-vapor exchange into membrane (and storage) fatty acids or DNA, respectively, to assess community- and group-level adjustments in soil microbial physiology (replication, storage product synthesis, and carbon use efficiency). We show that, while bacterial growth decreases by half during drought, fungal growth remains stable, demonstrating a remarkable resistance against soil moisture changes. In addition, fungal investment into storage triglycerides increases more than five-fold under drought. Community-level carbon use efficiency (the balance between anabolism and catabolism) is unaffected by drought but decreases in future climate conditions, favoring catabolism. Our results highlight that accounting for different microbial growth strategies can foster our understanding of soil microbial contributions to carbon cycling and feedback on the climate system.

Seasonal effects of long-term warming on ecosystem function and bacterial diversity

Across biomes, soil biodiversity promotes ecosystem functions. However, whether this relationship will be maintained within ecosystems under climate change is uncertain. Here, using two long-term soil warming experiments, we investigated how warming affects the relationship between ecosystem functions and bacterial diversity across seasons, soil horizons, and warming duration. Soils were sampled from these warming experiments located at the Harvard Forest Long-Term Ecological Research (LTER) site, where soils had been heated +5°C above ambient for 13 or 28 years at the time of sampling. We assessed seven measurements representative of different ecosystem functions and nutrient pools. We also surveyed bacterial community diversity. We found that ecosystem function was significantly affected by season, with autumn samples having a higher intercept than summer samples in our model, suggesting a higher overall baseline of ecosystem function in the fall. The effect of warming on bacterial diversity was similarly affected by season, where warming in the summer was associated with decreased bacterial evenness in the organic horizon. Despite the decreased bacterial evenness in the warmed plots, we found that the relationship between ecosystem function and bacterial diversity was unaffected by warming or warming duration. Our findings highlight that season is a consistent driver of ecosystem function as well as a modulator of climate change effects on bacterial community evenness.

Resource partitioning and amino acid assimilation in a terrestrial geothermal spring

High-temperature geothermal springs host simplified microbial communities; however, the activities of individual microorganisms and their roles in the carbon cycle in nature are not well understood. Here, quantitative stable isotope probing (qSIP) was used to track the assimilation of 13C-acetate and 13C-aspartate into DNA in 74 °C sediments in Gongxiaoshe Hot Spring, Tengchong, China. This revealed a community-wide preference for aspartate and a tight coupling between aspartate incorporation into DNA and the proliferation of aspartate utilizers during labeling. Both 13C incorporation into DNA and changes in the abundance of taxa during incubations indicated strong resource partitioning and a significant phylogenetic signal for aspartate incorporation. Of the active amplicon sequence variants (ASVs) identified by qSIP, most could be matched with genomes from Gongxiaoshe Hot Spring or nearby springs with an average nucleotide similarity of 99.4%. Genomes corresponding to aspartate primary utilizers were smaller, near-universally encoded polar amino acid ABC transporters, and had codon preferences indicative of faster growth rates. The most active ASVs assimilating both substrates were not abundant, suggesting an important role for the rare biosphere in the community response to organic carbon addition. The broad incorporation of aspartate into DNA over acetate by the hot spring community may reflect dynamic cycling of cell lysis products in situ or substrates delivered during monsoon rains and may reflect N limitation.

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.

Thrive or survive: prokaryotic life in hypersaline soils

BACKGROUND

Soil services are central to life on the planet, with microorganisms as their main drivers. Thus, the evaluation of soil quality requires an understanding of the principles and factors governing microbial dynamics within it. High salt content is a constraint for life affecting more than 900 million hectares of land, a number predicted to rise at an alarming rate due to changing climate. Nevertheless, little is known about how microbial life unfolds in these habitats. In this study, DNA stable-isotope probing (DNA-SIP) with ¹⁸O-water was used to determine for the first time the taxa able to grow in hypersaline soil samples (EC_e = 97.02 dS/m). We further evaluated the role of light on prokaryotes growth in this habitat.

RESULTS

We detected growth of both archaea and bacteria, with taxon-specific growth patterns providing insights into the drivers of success in saline soils. Phylotypes related to extreme halophiles, including haloarchaea and Salinibacter, which share an energetically efficient mechanism for salt adaptation (salt-in strategy), dominated the active community. Bacteria related to moderately halophilic and halotolerant taxa, such as Staphylococcus, Aliifodinibius, Bradymonadales or Chitinophagales also grew during the incubations, but they incorporated less heavy isotope. Light did not stimulate prokaryotic photosynthesis but instead restricted the growth of most bacteria and reduced the diversity of archaea that grew.

CONCLUSIONS

The results of this study suggest that life in saline soils is energetically expensive and that soil heterogeneity and traits such as exopolysaccharide production or predation may support growth in hypersaline soils. The contribution of phototrophy to supporting the heterotrophic community in saline soils remains unclear. This study paves the way toward a more comprehensive understanding of the functioning of these environments, which is fundamental to their management. Furthermore, it illustrates the potential of further research in saline soils to deepen our understanding of the effect of salinity on microbial communities.

Linking transcriptional dynamics of CH4-cycling grassland soil microbiomes to seasonal gas fluxes

Soil CH₄ fluxes are driven by CH₄-producing and -consuming microorganisms that determine whether soils are sources or sinks of this potent greenhouse gas. To date, a comprehensive understanding of underlying microbiome dynamics has rarely been obtained in situ. Using quantitative metatranscriptomics, we aimed to link CH₄-cycling microbiomes to net surface CH₄ fluxes throughout a year in two grassland soils. CH₄ fluxes were highly dynamic: both soils were net CH₄ sources in autumn and winter and sinks in spring and summer, respectively. Correspondingly, methanogen mRNA abundances per gram soil correlated well with CH₄ fluxes. Methanotroph to methanogen mRNA ratios were higher in spring and summer, when the soils acted as net CH₄ sinks. CH₄ uptake was associated with an increased proportion of USCα and γ pmoA and pmoA2 transcripts. We assume that methanogen transcript abundance may be useful to approximate changes in net surface CH₄ emissions from grassland soils. High methanotroph to methanogen ratios would indicate CH₄ sink properties. Our study links for the first time the seasonal transcriptional dynamics of CH₄-cycling soil microbiomes to gas fluxes in situ. It suggests mRNA transcript abundances as promising indicators of dynamic ecosystem-level processes.

A framework for integrating microbial dispersal modes into soil ecosystem ecology

Dispersal is a fundamental community assembly process that maintains soil microbial biodiversity across spatial and temporal scales, yet the impact of dispersal on ecosystem function is largely unpredictable. Dispersal is unique in that it contributes to both ecological and evolutionary processes and is shaped by both deterministic and stochastic forces. The ecosystem-level ramifications of dispersal outcomes are further compounded by microbial dormancy dynamics and environmental selection. Here we review the knowledge gaps and challenges that remain in defining how dispersal, environmental filtering, and microbial dormancy interact to influence the relationship between microbial community structure and function in soils. We propose the classification of microbial dispersal into three categories, through vegetative or active cells, through dormant cells, and through acellular dispersal, each with unique spatiotemporal dynamics and microbial trait associations. This conceptual framework should improve the integration of dispersal in defining soil microbial community structure-function relationships.

Active virus-host interactions at sub-freezing temperatures in Arctic peat soil

BACKGROUND

Winter carbon loss in northern ecosystems is estimated to be greater than the average growing season carbon uptake and is primarily driven by microbial decomposers. Viruses modulate microbial carbon cycling via induced mortality and metabolic controls, but it is unknown whether viruses are active under winter conditions (anoxic and sub-freezing temperatures).

RESULTS

We used stable isotope probing (SIP) targeted metagenomics to reveal the genomic potential of active soil microbial populations under simulated winter conditions, with an emphasis on viruses and virus-host dynamics. Arctic peat soils from the Bonanza Creek Long-Term Ecological Research site in Alaska were incubated under sub-freezing anoxic conditions with H218O or natural abundance water for 184 and 370 days. We sequenced 23 SIP-metagenomes and measured carbon dioxide (CO2) efflux throughout the experiment. We identified 46 bacterial populations (spanning 9 phyla) and 243 viral populations that actively took up 18O in soil and respired CO2 throughout the incubation. Active bacterial populations represented only a small portion of the detected microbial community and were capable of fermentation and organic matter degradation. In contrast, active viral populations represented a large portion of the detected viral community and one third were linked to active bacterial populations. We identified 86 auxiliary metabolic genes and other environmentally relevant genes. The majority of these genes were carried by active viral populations and had diverse functions such as carbon utilization and scavenging that could provide their host with a fitness advantage for utilizing much-needed carbon sources or acquiring essential nutrients.

CONCLUSIONS

Overall, there was a stark difference in the identity and function of the active bacterial and viral community compared to the unlabeled community that would have been overlooked with a non-targeted standard metagenomic analysis. Our results illustrate that substantial active virus-host interactions occur in sub-freezing anoxic conditions and highlight viruses as a major community-structuring agent that likely modulates carbon loss in peat soils during winter, which may be pivotal for understanding the future fate of arctic soils' vast carbon stocks. Video abstract.

Metatranscriptomic analysis reveals active microbes and genes responded to short-term Cr(VI) stress

Heavy metals have been severely polluting the environment. However, the response mechanism of microbial communities to short-term heavy metals stress remains unclear. In this study, metagenomics (MG) and metatranscriptomics (MT) was performed to observe the microbial response to short-term Cr(VI) stress. MG data showed that 99.1% of species were similar in the control and Cr(VI) treated groups. However, MT data demonstrated that 83% of the microbes were active in which 58.7% increased, while the relative abundance of 41.3% decreased after short-term Cr(VI) incubation. The MT results also revealed 9% of microbes were dormant in samples. Genes associated with oxidative stress, Cr(VI) transport, resistance, and reduction, as well as genes with unknown functions were 2-10 times upregulated after Cr(VI) treatment. To further confirm the function of unknown genes, two genes (314 and 494) were selected to detect the Cr(VI) resistance and reduction ability. The results showed that these genes significantly increased the Cr(VI) remediation ability of Escherichia coli. MT results also revealed an increase in the expression of some rare genera (at least two times) after Cr(VI) treatment, indicating these rare species played a crucial role in microbial response to short-term Cr(VI) stress. In summary, MT is an efficient way to understand the role of active and dormant microbes in specific environmental conditions.

Use of NanoSIMS to Identify the Lower Limits of Metabolic Activity and Growth by Serratia liquefaciens Exposed to Sub-Zero Temperatures

Serratia liquefaciens is a cold-adapted facultative anaerobic astrobiology model organism with the ability to grow at a Martian atmospheric pressure of 7 hPa. Currently there is a lack of data on its limits of growth and metabolic activity at sub-zero temperatures found in potential habitable regions on Mars. Growth curves and nano-scale secondary ion mass spectrometry (NanoSIMS) were used to characterize the growth and metabolic threshold for S. liquefaciens ATCC 27,592 grown at and below 0 °C. Cells were incubated in Spizizen medium containing three stable isotopes substituting their unlabeled counterparts; i.e., ¹³C-glucose, (¹⁵NH₄)₂SO₄, and H₂¹⁸O; at 0, −1.5, −3, −5, −10, or −15 °C. The isotopic ratios of ¹³C/¹²C, ¹⁵N/¹⁴N, and ¹⁸O/¹⁶O and their corresponding fractions were determined for 240 cells. NanoSIMS results revealed that with decreasing temperature the cellular amounts of labeled ions decreased indicating slower metabolic rates for isotope uptake and incorporation. Metabolism was significantly reduced at −1.5 and −3 °C, almost halted at −5 °C, and shut-down completely at or below −10 °C. While growth was observed at 0 °C after 5 days, samples incubated at −1.5 and −3 °C exhibited significantly slower growth rates until growth was detected at 70 days. In contrast, cell densities decreased by at least half an order of magnitude over 70 days in cultures incubated at ≤ −5 °C. Results suggest that S. liquefaciens, if transported to Mars, might be able to metabolize and grow in shallow sub-surface niches at temperatures above −5 °C and might survive—but not grow—at temperatures below −5 °C.

Biological nitrification inhibition in the rhizosphere: determining interactions and impact on microbially mediated processes and potential applications

Nitrification is the microbial conversion of reduced forms of nitrogen (N) to nitrate (NO3-), and in fertilized soils it can lead to substantial N losses via NO3- leaching or nitrous oxide (N2O) production. To limit such problems, synthetic nitrification inhibitors have been applied but their performance differs between soils. In recent years, there has been an increasing interest in the occurrence of biological nitrification inhibition (BNI), a natural phenomenon according to which certain plants can inhibit nitrification through the release of active compounds in root exudates. Here, we synthesize the current state of research but also unravel knowledge gaps in the field. The nitrification process is discussed considering recent discoveries in genomics, biochemistry and ecology of nitrifiers. Secondly, we focus on the 'where' and 'how' of BNI. The N transformations and their interconnections as they occur in, and are affected by, the rhizosphere, are also discussed. The NH4+ and NO3- retention pathways alternative to BNI are reviewed as well. We also provide hypotheses on how plant compounds with putative BNI ability can reach their targets inside the cell and inhibit ammonia oxidation. Finally, we discuss a set of techniques that can be successfully applied to solve unresearched questions in BNI studies.

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets-from soil and seawater microbiomes-to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon's abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.IMPORTANCE One of the biggest challenges in microbial ecology is correlating the identity of microorganisms with the roles they fulfill in natural environmental systems. Studies of microbes in pure culture reveal much about their genomic content and potential functions but may not reflect an organism's activity within its natural community. Culture-independent studies supply a community-wide view of composition and function in the context of community interactions but often fail to link the two. Quantitative stable isotope probing (qSIP) is a method that can link the identity and functional activity of specific microbes within a naturally occurring community. Here, we explore how the resolution of density gradient fractionation affects the error and precision of qSIP results, how they may be improved via additional experimental replication, and discuss cost-benefit balanced scenarios for SIP experimental design.

Microbial Taxon-Specific Isotope Incorporation with DNA Quantitative Stable Isotope Probing

Quantitative stable isotope probing (qSIP) measures rates of taxon-specific element assimilation in intact microbial communities, utilizing substrates labeled with a heavy isotope.The laboratory protocol for qSIP is nearly identical to that for conventional stable isotope probing, with two key additions: (1) in qSIP, qPCR measurements are conducted on each density fraction recovered after isopycnic separation, and (2) in qSIP, multiple density fractions are sequenced spanning the entire range of densities over which nucleic acids were recovered. qSIP goes beyond identifying taxa assimilating a substrate, as it also allows for measuring that assimilation for each taxon within a given microbial community. Here, we describe an analysis process necessary to determine atom fraction excess of a heavy stable isotope added to an environmental sample for a given taxon's DNA.

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.

Next-generation physiology approaches to study microbiome function at single cell level

The function of cells in their native habitat often cannot be reliably predicted from genomic data or from physiology studies of isolates. Traditional experimental approaches to study the function of taxonomically and metabolically diverse microbiomes are limited by their destructive nature, low spatial resolution or low throughput. Recently developed technologies can offer new insights into cellular function in natural and human-made systems and how microorganisms interact with and shape the environments that they inhabit. In this Review, we provide an overview of these next-generation physiology approaches and discuss how the non-destructive analysis of cellular phenotypes, in combination with the separation of the target cells for downstream analyses, provide powerful new, complementary ways to study microbiome function. We anticipate that the widespread application of next-generation physiology approaches will transform the field of microbial ecology and dramatically improve our understanding of how microorganisms function in their native environment.

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.

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.