Raman-Activated, Interactive Sorting of Isotope-Labeled Bacteria.

Due to its high spatial resolution, Raman microspectroscopy allows for the analysis of single microbial cells. Since Raman spectroscopy analyzes the whole cell content, this method is phenotypic and can therefore be used to evaluate cellular changes. In particular, labeling with stable isotopes (SIPs) enables the versatile use and observation of different metabolic states in microbes. Nevertheless, static measurements can only analyze the present situation and do not allow for further downstream evaluations. Therefore, a combination of Raman analysis and cell sorting is necessary to provide the possibility for further research on selected bacteria in a sample. Here, a new microfluidic approach for Raman-activated continuous-flow sorting of bacteria using an optical setup for image-based particle sorting with synchronous acquisition and analysis of Raman spectra for making the sorting decision is demonstrated, showing that active cells can be successfully sorted by means of this microfluidic chip.

Phenotypic Differentiation of Autotrophic and Heterotrophic Bacterial Cells Using Raman-D2O Labeling.

Carbon cycling is one of the major biogeochemical processes driven by bacteria. Autotrophic bacteria convert carbon dioxide (CO2) into organic compounds that are used by heterotrophs. Mixotrophic bacteria can employ both autotrophy and heterotrophy for growth. The characterization of the lifestyle of individual cells is essential to understand the microbial activity and thus reveal the implication of bacteria in the carbon flux. In this study, we used groundwater bacteria to investigate the potential of Raman-D2O labeling in combination with chemometrics to identify the carbon assimilation strategies of bacteria. Classification models were built using principal component analysis (PCA) followed by linear discriminant analysis (LDA). Autotrophs assimilated a significantly higher amount (mean C-D ratio between 16.63 and 21.69%) of deuterium than heterotrophs. The C-D signal only provides information about the activity since it appears in the Raman-silent region, where no interference with the taxonomic information is expected. The classification between autotrophs and heterotrophs achieved an overall accuracy of 96.3%. In the validation step with an independent dataset containing species not included in the model, the PCA-LDA model achieved 100% accuracy. This demonstrated that the C-D signal contributed to the identification of autotrophic and heterotrophic bacterial cells. This work reports a robust, rapid, and nondestructive approach for the identification of single cells based on their carbon acquisition strategies. The present study foresees the potential of Raman-D2O labeling as a promising method for automated discrimination of in situ functional activities of bacteria in environmental systems.

Monitoring Deuterium Uptake in Single Bacterial Cells via Two-Dimensional Raman Correlation Spectroscopy.

Raman-stable isotope labeling using heavy water (Raman-D2O) is attracting great interest as a fast technique with various applications ranging from the identification of pathogens in medical samples to the determination of microbial activity in the environment. Despite its widespread applications, little is known about the fundamental processes of hydrogen-deuterium (H/D) exchange, which are crucial for understanding molecular interactions in microorganisms. By combining two-dimensional (2D) correlation spectroscopy and Raman deuterium labeling, we have investigated H/D exchange in bacterial cells under time dependence. Most C-H stretching signals decreased in intensity over time, prior to the formation of the C-D stretching vibration signals. The intensity of the C-D signal gradually increased over time, and the shape of the C-D signal was more uniform after longer incubation times. Deuterium uptake showed high variability between the bacterial genera and mainly led to an observable labeling of methylene and methyl groups. Thus, the C-D signal encompassed a combination of symmetric and antisymmetric CD2 and CD3 stretching vibrations, depending on the bacterial genera. The present study allowed for the determination of the sequential order of deuterium incorporation into the functional groups of proteins, lipids, and nucleic acids and hence understanding the process of biomolecule synthesis and the growth strategies of different bacterial taxa. We present the combination of Raman-D2O labeling and 2D correlation spectroscopy as a promising approach to gain a fundamental understanding of molecular interactions in biological systems.

Influence of Carbon Sources on Quantification of Deuterium Incorporation in Heterotrophic Bacteria: A Raman-Stable Isotope Labeling Approach.

A rapid and reliable method for the differentiation between active and inactive bacteria at single cell level is urgently needed in many fields including clinical diagnosis and environmental microbiology, to understand the contribution of metabolically active bacteria in fundamental processes triggering environmental and public health risks. Here, using heavy water (D2O) with Raman-stable isotope labeling (Raman-D2O), we evaluated the reliability of the quantification of deuterium uptake, a well-known indicator for the general metabolic activity of bacteria. For this purpose, we based our study on the quantification of deuterium assimilation from heavy water into single bacterial cells to check the influence of carbon source and bacterial identity on the deuterium uptake. We show that compared to complex carbon substrates, the deuterium assimilation is higher in the presence of simpler substrates such as sugars but differs significantly among bacterial isolates. Despite this variability, the developed classification models could differentiate deuterium labeled and nonlabeled single cells with high sensitivity and specificity. Highlighting the variability between single bacterial cells, the study emphasizes the challenges in establishing a threshold in terms of deuterium uptake to distinguish deuterium labeled and nonlabeled cells. Overall, we show that the Raman-D2O approach, when coupled with chemometrics, constitutes a powerful approach for monitoring single bacterial cells.

Communal metabolism by Methylococcaceae and Methylophilaceae is driving rapid aerobic methane oxidation in sediments of a shallow seep near Elba, Italy.

The release of abiotic methane from marine seeps into the atmosphere is a major source of this potent greenhouse gas. Methanotrophic microorganisms in methane seeps use methane as carbon and energy source, thus significantly mitigating global methane emissions. Here, we investigated microbial methane oxidation at the sediment-water interface of a shallow marine methane seep. Metagenomics and metaproteomics, combined with 13 C-methane stable isotope probing, demonstrated that various members of the gammaproteobacterial family Methylococcaceae were the key players for methane oxidation, catalysing the first reaction step to methanol. We observed a transfer of carbon to methanol-oxidizing methylotrophs of the betaproteobacterial family Methylophilaceae, suggesting an interaction between methanotrophic and methylotrophic microorganisms that allowed for rapid methane oxidation. From our microcosms, we estimated methane oxidation rates of up to 871 nmol of methane per gram sediment per day. This implies that more than 50% of methane at the seep is removed by microbial oxidation at the sediment-water interface, based on previously reported in situ methane fluxes. The organic carbon produced was further assimilated by different heterotrophic microbes, demonstrating that the methane-oxidizing community supported a complex trophic network. Our results provide valuable eco-physiological insights into this specialized microbial community performing an ecosystem function of global relevance.

Tracking active groundwater microbes with D2 O labelling to understand their ecosystem function.

Microbial activity is key in understanding the contribution of microbial communities to ecosystem functions. Metabolic labelling with heavy water (D2 O) leads to the formation of carbon-deuterium bonds in active microorganisms. We illustrated how D2 O labelling allows monitoring of metabolic activity combined with a functional characterization of active populations in complex microbial communities. First, we demonstrated by single cell Raman microspectroscopy that all measured bacterial cells from groundwater isolates growing in complex medium with D2 O were labelled. Next, we conducted a labelling approach with the total groundwater microbiome in D2 O amended microcosms. Deuterium was incorporated in most measured cells, indicating metabolic activity in the oligotrophic groundwater. Moreover, we spiked the groundwater microbiome with organic model compounds. We discovered that heterotrophs assimilating veratric acid, a lignin derivative, showed higher labelling than heterotrophs assimilating methylamine, a degradation product of biomass. This difference can be explained by dilution of the deuterium through hydrogen from the organic compounds. Metaproteomics identified Sphingomonadaceae and Microbacteriaceae as key players in veratric acid degradation, and the metabolic pathways employed. Methylamine, in contrast, stimulated various proteobacterial genera. We propose this combined approach of Raman microspectroscopy and metaproteomics for elucidating the complex metabolic response of microbial populations to different stimuli.

Methylamine as a nitrogen source for microorganisms from a coastal marine environment.

Nitrogen is a key limiting resource for biomass production in the marine environment. Methylated amines, released from the degradation of osmolytes, could provide a nitrogen source for marine microbes. Thus far, studies in aquatic habitats on the utilization of methylamine, the simplest methylated amine, have mainly focussed on the fate of the carbon from this compound. Various groups of methylotrophs, microorganisms that can grow on one-carbon compounds, use methylamine as a carbon source. Non-methylotrophic microorganisms may also utilize methylamine as a nitrogen source, but little is known about their diversity, especially in the marine environment. In this proof-of-concept study, stable isotope probing (SIP) was used to identify microorganisms from a coastal environment that assimilate nitrogen from methylamine. SIP experiments using 15 N methylamine combined with metagenomics and metaproteomics facilitated identification of active methylamine-utilizing Alpha- and Gammaproteobacteria. The draft genomes of two methylamine utilizers were obtained and their metabolism with respect to methylamine was examined. Both bacteria identified in these SIP experiments used the γ-glutamyl-methylamide pathway, found in both methylotrophs and non-methylotrophs, to metabolize methylamine. The utilization of 15 N methylamine also led to the release of 15 N ammonium that was used as nitrogen source by other microorganisms not directly using methylamine.

MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics.

We propose a joint experimental and theoretical approach to the automated reconstruction of elemental fluxes in microbial communities. While stable isotope probing of proteins (protein-SIP) has been successfully applied to study interactions and elemental carbon and nitrogen fluxes, the volume and complexity of mass spectrometric data in protein-SIP experiments pose new challenges for data analysis. Together with a flexible experimental setup, the novel bioinformatics tool MetaProSIP offers an automated high-throughput solution for a wide range of (13)C or (15)N protein-SIP experiments with special emphasis on the analysis of metaproteomic experiments where differential labeling of organisms can occur. The information calculated in MetaProSIP includes the determination of multiple relative isotopic abundances, the labeling ratio between old and new synthesized proteins, and the shape of the isotopic distribution. These parameters define the metabolic capacities and dynamics within the investigated microbial culture. MetaProSIP features a high degree of reproducibility, reliability, and quality control reporting. The ability to embed into the OpenMS framework allows for flexible construction of custom-tailored workflows. Software and documentation are available under an open-source license at www.openms.de/MetaProSIP.

XoxF encoding an alternative methanol dehydrogenase is widespread in coastal marine environments.

The xoxF gene, encoding a pyrroloquinoline quinone-dependent methanol dehydrogenase, is found in all known proteobacterial methylotrophs. In several newly discovered methylotrophs, XoxF is the active methanol dehydrogenase, catalysing the oxidation of methanol to formaldehyde. Apart from that, its potential role in methylotrophy and carbon cycling is unknown. So far, the diversity of xoxF in the environment has received little attention. We designed PCR primer sets targeting clades of the xoxF gene, and used 454 pyrosequencing of PCR amplicons obtained from the DNA of four coastal marine environments for a unique assessment of the diversity of xoxF in these habitats. Phylogenetic analysis of the data obtained revealed a high diversity of xoxF genes from two of the investigated clades, and substantial differences in sequence composition between environments. Sequences were classified as being related to a wide range of both methylotrophs and non-methylotrophs from Alphaproteobacteria, Betaproteobacteria and Gammaproteobacteria. The most prominent sequences detected were related to the family Rhodobacteraceae, the genus Methylotenera and the OM43 clade of Methylophilales, and are thus related to organisms that employ XoxF for methanol oxidation. Furthermore, our analyses revealed a high degree of so far undescribed sequences, suggesting a high number of unknown bacterial species in these habitats.

Combining metagenomics with metaproteomics and stable isotope probing reveals metabolic pathways used by a naturally occurring marine methylotroph.

A variety of culture-independent techniques have been developed that can be used in conjunction with culture-dependent physiological and metabolic studies of key microbial organisms in order to better understand how the activity of natural populations influences and regulates all major biogeochemical cycles. In this study, we combined deoxyribonucleic acid-stable isotope probing (DNA-SIP) with metagenomics and metaproteomics to characterize an uncultivated marine methylotroph that actively incorporated carbon from (13) C-labeled methanol into biomass. By metagenomic sequencing of the heavy DNA, we retrieved virtually the whole genome of this bacterium and determined its metabolic potential. Through protein-stable isotope probing, the RuMP cycle was established as the main carbon assimilation pathway, and the classical methanol dehydrogenase-encoding gene mxaF, as well as three out of four identified xoxF homologues were found to be expressed. This proof-of-concept study is the first in which the culture-independent techniques of DNA-SIP and protein-SIP have been used to characterize the metabolism of a naturally occurring Methylophaga-like bacterium in the marine environment (i.e. Methylophaga thiooxydans L4) and thus provides a powerful approach to access the genome and proteome of uncultivated microbes involved in key processes in the environment.

Sulfur-34S stable isotope labeling of amino acids for quantification (SULAQ34) of proteomic changes in Pseudomonas fluorescens during naphthalene degradation.

The relative quantification of proteins is one of the major techniques used to elucidate physiological reactions. Because it allows one to avoid artifacts due to chemical labeling, the metabolic introduction of heavy isotopes into proteins and peptides is the preferred method for relative quantification. For eukaryotic cells, stable isotope labeling by amino acids in cell culture (SILAC) has become the gold standard and can be readily applied in a vast number of scenarios. In the microbial realm, with its highly versatile metabolic capabilities, SILAC is often not feasible, and the use of other (13)C or (15)N labeled substrates might not be practical. Here, the incorporation of heavy sulfur isotopes is shown to be a useful alternative. We introduce (34)S stable isotope labeling of amino acids for quantification and the corresponding tools required for spectra extraction and disintegration of the isotopic overlaps caused by the small mass shift. As proof of principle, we investigated the proteomic changes related to naphthalene degradation in P. fluorescens ATCC 17483 and uncovered a specific oxidative-stress-like response.

Iron coatings on carbonate rocks shape the attached bacterial aquifer community.

Most studies of groundwater ecosystems target planktonic microbes, which are easily obtained via water samples. In contrast, little is known about the diversity and function of microbes adhering to rock surfaces, particularly to consolidated rocks. To investigate microbial attachment to rock surfaces, we incubated rock chips from fractured aquifers in limestone-mudstone alternations in bioreactors fed with groundwater from two wells representing oxic and anoxic conditions. Half of the chips were coated with iron oxides, representing common secondary mineralization in fractured rock. Our time-series analysis showed bacteria colonizing the chips within two days, reaching cell numbers up to 4.16 × 105 cells/mm2 after 44 days. Scanning electron microscopy analyses revealed extensive colonization but no multi-layered biofilms, with chips from oxic bioreactors more densely colonized than from anoxic ones. Estimated attached-to-planktonic cell ratios yielded values of up to 106: 1 and 103: 1, for oxic and anoxic aquifers, respectively. We identified distinct attached and planktonic communities with an overlap between 17 % and 42 %. Oxic bioreactors were dominated by proteobacterial genera Aquabacterium and Rhodoferax, while Rheinheimera and Simplicispira were the key players of anoxic bioreactors. Motility, attachment, and biofilm formation traits were predicted in major genera based on groundwater metagenome-assembled genomes and reference genomes. Early rock colonizers appeared to be facultative autotrophs, capable of fixing CO2 to synthesize biomass and a biofilm matrix. Late colonizers were predicted to possess biofilm degrading enzymes such as beta-glucosidase, beta-galactosidase, amylases. Fe-coated chips of both bioreactors featured more potential iron reducers and oxidizers than bare rock chips. As secondary minerals can also serve as energy source, they might favor primary production and thus contribute to subsurface ecosystem services like carbon fixation. Since most subsurface microbes seem to be attached, their contribution to ecosystem services should be considered in future studies.

Enrichment of different taxa of the enigmatic candidate phyla radiation bacteria using a novel picolitre droplet technique.

The candidate phyla radiation (CPR) represents a distinct monophyletic clade and constitutes a major portion of the tree of life. Extensive efforts have focused on deciphering the functional diversity of its members, primarily using sequencing-based techniques. However, cultivation success remains scarce, presenting a significant challenge, particularly in CPR-dominated groundwater microbiomes characterized by low biomass. Here, we employ an advanced high-throughput droplet microfluidics technique to enrich CPR taxa from groundwater. Utilizing a low-volume filtration approach, we successfully harvested a microbiome resembling the original groundwater microbial community. We assessed CPR enrichment in droplet and aqueous bulk cultivation for 30 days using a novel CPR-specific primer to rapidly track the CPR fraction through the cultivation attempts. The combination of soil extract and microbial-derived necromass provided the most supportive conditions for CPR enrichment. Employing these supplemented conditions, droplet cultivation proved superior to bulk cultivation, resulting in up to a 13-fold CPR enrichment compared to a 1- to 2-fold increase in bulk cultivation. Amplicon sequencing revealed 10 significantly enriched CPR orders. The highest enrichment in CPRs was observed for some unknown members of the Parcubacteria order, Cand. Jorgensenbacteria, and unclassified UBA9983. Furthermore, we identified co-enriched putative host taxa, which may guide more targeted CPR isolation approaches in subsequent investigations.

Protein-based stable isotope probing (protein-SIP) in functional metaproteomics.

The community phenotype as the sum of molecular functions of organisms living in consortia strongly depends on interactions within these communities. Therefore, the analyses of the most significant molecules in terms of the phenotype, the proteins, have to be performed on samples without disrupting the meta-species environment. Due to the increasing genomic information, proteins provide insights into a potential molecular function and the phylogenetic structure of the community. Unfortunately, the lists of identified proteins are often based first on the technical capacity of the used methods or instruments, and second on the interpretation of them by the assignment of molecular functions to proteins in databases. Especially in non-model organisms the functions of many proteins are often not known and an increasing number of studies indicate a significant amount of uncertainty. To decrease the dependency on assumptions and to enable functional insights by metaproteome approaches, the metabolic labeling from an isotopically labeled substrate can be used. Since the metabolites deriving from the substrate are very rarely species-specific, the incorporation of the stable isotope into proteins can be used as a surrogate marker for metabolic activity. The degree of incorporation can be determined accurately on the peptide level by mass spectrometry; additionally, the peptide sequence provides information on the metabolic active species. Thereby, protein-stable isotope probing (protein-SIP) adds functional information to metaproteome approaches. The classical metaproteome approaches will be reviewed with an emphasis on their attempts towards functional interpretation. The gain from functional insights into metaproteomics by using metabolic labeling of stable isotopes of carbon, nitrogen, and sulfur is reviewed with a focus on the techniques of measurement, calculation of incorporation and data processing.

Limitations in detection of 15N incorporation by mass spectrometry in protein-based stable isotope probing (protein-SIP).

The method of protein-based stable isotope probing (protein-SIP) has previously been shown to allow the modeling of carbon fluxes in microbial communities, thus tackling one of the key questions in microbial ecology. The method allows the analysis of stable isotope distribution in peptides, revealing metabolic activities of the species present in an ecosystem. Besides carbon, an application of protein-SIP with nitrogen is of interest for resolving the nitrogen fluxes in microbial communities. Thus, the sensitivity and reliability of a protein-SIP approach employing (15)N was analyzed. For this, cultivations of Pseudomonas fluorescens ATCC 17483 with different ratios of (14)N/(15)N were performed, from 10 % down to 0.1 % (15)N. After incubation leading to complete labeling of biomass, proteins were extracted and separated by one-dimensional gel electrophoresis, followed by tryptic digest and UPLC Orbitrap MS/MS analysis. (15)N relative isotope abundance (RIA) was calculated based on isotopic patterns from identified peptides in mass spectra. Proteomics data have been deposited to ProteomeXchange with identifier PXD000127. The distribution of (15)N RIA values among peptides was analyzed in samples with different (15)N amount, and potential causes for variations within individual samples of either technical or biological origin were investigated. Using a number of 50 peptides, significant differences (p ≤ 0.05) in (15)N incorporation were found between samples of different (15)N RIA down to 0.1 %. The study demonstrates that protein-SIP using (15)N is sufficiently sensitive for quantitative investigation of microbial activity in nitrogen cycling processes.

Metabolic versatility enables sulfur-oxidizers to dominate primary production in groundwater.

High rates of CO2 fixation and the genetic potential of various groundwater microbes for autotrophic activity have shown that primary production is an important source of organic C in groundwater ecosystems. However, the contribution of specific chemolithoautotrophic groups such as S-oxidizing bacteria (SOB) to groundwater primary production and their adaptation strategies remain largely unknown. Here, we stimulated anoxic groundwater microcosms with reduced S and sampled the microbial community after 1, 3 and 6 weeks. Genome-resolved metaproteomics was combined with 50at-% 13CO2 stable isotope probing to follow the C flux through the microbial food web and infer traits expressed by active SOB in the groundwater microcosms. Already after 7 days, 90% of the total microbial biomass C in the microcosms was replaced by CO2-derived C, increasing to 97% at the end of incubation. Stable Isotope Cluster Analysis revealed active autotrophs, characterized by a uniform 13C-incorporation of 45% in their peptides, to dominate the microbial community throughout incubation. Mixo- and heterotrophs, characterized by 10 to 40% 13C-incorporation, utilized the primarily produced organic C. Interestingly, obligate autotrophs affiliated with Sulfuricella and Sulfuritalea contained traits enabling the storage of elemental S in globules to maintain primary production under energy limitation. Others related to Sulfurimonas seemed to rapidly utilize substrates for fast proliferation, and most autotrophs further maximized their energy yield via efficient denitrification and the potential for H2 oxidation. Mixotrophic SOB, belonging to Curvibacter or Polaromonas, enhanced metabolic flexibility by using organic compounds to satisfy their C requirements. Time series data spanning eight years further revealed that key taxa of our microcosms composed up to 15% of the microbial groundwater community, demonstrating their in-situ importance. This showed that SOB, by using different metabolic strategies, are able to account for high rates of primary production in groundwater, especially at sites limited to geogenic nutrient sources. The widespread presence of SOB with traits such as S storage, H2 oxidation, and organic C utilization in many aquatic habitats further suggested that metabolic versatility governs S-fueled primary production in the environment.

Differential contribution of nitrifying prokaryotes to groundwater nitrification.

The ecophysiology of complete ammonia-oxidizing bacteria (CMX) of the genus Nitrospira and their widespread occurrence in groundwater suggests that CMX bacteria have a competitive advantage over ammonia-oxidizing bacteria (AOB) and archaea (AOA) in these environments. However, the specific contribution of their activity to nitrification processes has remained unclear. We aimed to disentangle the contribution of CMX, AOA and AOB to nitrification and to identify the environmental drivers of their niche differentiation at different levels of ammonium and oxygen in oligotrophic carbonate rock aquifers. CMX ammonia monooxygenase sub-unit A (amoA) genes accounted on average for 16 to 75% of the total groundwater amoA genes detected. Nitrification rates were positively correlated to CMX clade A associated phylotypes and AOB affiliated with Nitrosomonas ureae. Short-term incubations amended with the nitrification inhibitors allylthiourea and chlorate suggested that AOB contributed a large fraction to overall ammonia oxidation, while metaproteomics analysis confirmed an active role of CMX in both ammonia and nitrite oxidation. Ecophysiological niche differentiation of CMX clades A and B, AOB and AOA was linked to their requirements for ammonium, oxygen tolerance, and metabolic versatility. Our results demonstrate that despite numerical predominance of CMX, the first step of nitrification in oligotrophic groundwater appears to be primarily governed by AOB. Higher growth yields at lower ammonia turnover rates and energy derived from nitrite oxidation most likely enable CMX to maintain consistently high populations.

DNA-, RNA-, and Protein-Based Stable-Isotope Probing for High-Throughput Biomarker Analysis of Active Microorganisms.

Stable-isotope probing (SIP) enables researchers to target active populations within complex microbial communities, which is achieved by providing growth substrates enriched in heavy isotopes, usually in the form of 13C, 18O, or 15N. After growth on the substrate and subsequent extraction of microbial biomarkers, typically nucleic acids or proteins, the SIP technique is used for the recovery and analysis of isotope-labelled biomarkers from active microbial populations. In the years following the initial development of DNA- and RNA-based SIP, it was common practice to characterize labelled populations by targeted gene analysis. Such approaches usually involved fingerprint-based analyses or sequencing clone libraries containing 16S rRNA genes or functional marker gene amplicons. Although molecular fingerprinting remains a valuable approach for rapid confirmation of isotope labelling, recent advances in sequencing technology mean that it is possible to obtain affordable and comprehensive amplicon profiles, or even metagenomes and metatranscriptomes from SIP experiments. Not only can the abundance of microbial groups be inferred from metagenomes, but researchers can bin, assemble, and explore individual genomes to build hypotheses about the metabolic capabilities of labelled microorganisms. Analysis of labelled mRNA is a more recent advance that can provide independent metatranscriptome-based analysis of active microorganisms. The power of metatranscriptomics is that mRNA abundance often correlates closely with the corresponding activity of encoded enzymes, thus providing insight into microbial metabolism at the time of sampling. Together, these advances have improved the sensitivity of SIP methods and allowed using labelled substrates at environmentally relevant concentrations. Particularly as methods improve and costs continue to drop, we expect that the integration of SIP with multiple omics-based methods will become prevalent components of microbial ecology studies, leading to further breakthroughs in our understanding of novel microbial populations and elucidation of the metabolic function of complex microbial communities. In this chapter, we provide protocols for obtaining labelled DNA, RNA, and proteins that can be used for downstream omics-based analyses.

Bacterial Necromass Is Rapidly Metabolized by Heterotrophic Bacteria and Supports Multiple Trophic Levels of the Groundwater Microbiome.

Pristine groundwater is a highly stable environment with microbes adapted to dark, oligotrophic conditions. Input events like heavy rainfalls can introduce the excess particulate organic matter, including surface-derived microorganisms, thereby disturbing the groundwater microbiome. Some surface-derived bacteria will not survive this translocation, leading to an input of necromass to the groundwater. Here, we investigated the effects of necromass addition to the microbial community in fractured bedrock groundwater, using groundwater mesocosms as model systems. We followed the uptake of 13C-labeled necromass by the bacterial and eukaryotic groundwater community quantitatively and over time using a complementary protein-stable and DNA-stable isotope probing approach. Necromass was rapidly depleted in the mesocosms within 4 days, accompanied by a strong decrease in Shannon diversity and a 10-fold increase in bacterial 16S rRNA gene copy numbers. Species of Flavobacterium, Massilia, Rheinheimera, Rhodoferax, and Undibacterium dominated the microbial community within 2 days and were identified as key players in necromass degradation, based on a 13C incorporation of >90% in their peptides. Their proteomes comprised various proteins for uptake and transport functions and amino acid metabolization. After 4 and 8 days, the autotrophic and mixotrophic taxa Nitrosomonas, Limnohabitans, Paucibacter, and Acidovorax increased in abundance with a 13C incorporation between 0.5% and 23%. Likewise, eukaryotes assimilated necromass-derived carbon either directly or indirectly. Our data point toward a fast and exclusive uptake of labeled necromass by a few specialists followed by a concerted action of groundwater microorganisms, including autotrophs presumably fueled by released, reduced nitrogen and sulfur compounds generated during necromass degradation. IMPORTANCE Subsurface microbiomes provide essential ecosystem services, like the generation of drinking water. These ecosystems are devoid of light-driven primary production, and microbial life is adapted to the resulting oligotrophic conditions. Modern groundwater is most vulnerable to anthropogenic and climatic impacts. Heavy rainfalls, which will increase with climate change, can result in high surface inputs into shallow aquifers by percolation or lateral flow. These inputs include terrestrial organic matter and surface-derived microbes that are not all capable to flourish in aquatic subsurface habitats. Here, we investigated the response of groundwater mesocosms to the addition of bacterial necromass, simulating event-driven surface input. We found that the groundwater microbiome responds with a rapid bloom of only a few primary degraders, followed by the activation of typical groundwater autotrophs and mixotrophs, as well as eukaryotes. Our results suggest that this multiphase strategy is essential to maintain the balance of the groundwater microbiome to provide ecosystem services.

Microbial community functioning during plant litter decomposition.

Microbial life in soil is fueled by dissolved organic matter (DOM) that leaches from the litter layer. It is well known that decomposer communities adapt to the available litter source, but it remains unclear if they functionally compete or synergistically address different litter types. Therefore, we decomposed beech, oak, pine and grass litter from two geologically distinct sites in a lab-scale decomposition experiment. We performed a correlative network analysis on the results of direct infusion HR-MS DOM analysis and cross-validated functional predictions from 16S rRNA gene amplicon sequencing and with DOM and metaproteomic analyses. Here we show that many functions are redundantly distributed within decomposer communities and that their relative expression is rapidly optimized to address litter-specific properties. However, community changes are likely forced by antagonistic mechanisms as we identified several natural antibiotics in DOM. As a consequence, the decomposer community is specializing towards the litter source and the state of decomposition (community divergence) but showing similar litter metabolomes (metabolome convergence). Our multi-omics-based results highlight that DOM not only fuels microbial life, but it additionally holds meta-metabolomic information on the functioning of ecosystems.