Scholarly article on topic 'Tracking activity and function of microorganisms by stable isotope probing of membrane lipids'

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Abstract of research paper on Biological sciences, author of scientific article — Gunter Wegener, Matthias Y Kellermann, Marcus Elvert

Microorganisms in soils and sediments are highly abundant and phylogenetically diverse, but their specific metabolic activity and function in the environment is often not well constrained. To address this critical aspect in environmental biogeochemistry, different methods involving stable isotope probing (SIP) and detection of the isotope label in a variety of molecular compounds have been developed. Here we review recent progress in lipid-SIP, a technique that combines the assimilation of specific 13C-labeled metabolic substrates such as inorganic carbon, methane, glucose and amino acids into diagnostic membrane lipid compounds. Using the structural characteristics of certain lipid types in combination with genetic molecular techniques, the SIP approach reveals the activity and function of distinct microbial groups in the environment. More recently, deuterium labeling in the form of deuterated water (D2O) extended the lipid-SIP portfolio. Since lipid biosynthetic pathways involve hydrogen (H+) uptake from water, lipid production can be inferred from the detection of D-assimilation into these compounds. Furthermore, by combining D2O and 13C-inorganic carbon (IC) labeling in a dual-SIP approach, rates of auto- and heterotrophic carbon fixation can be estimated. We discuss the design, analytical prerequisites, data processing and interpretation of single and dual-SIP experiments and highlight a case study on anaerobic methanotrophic communities inhabiting hydrothermally heated marine sediments.

Academic research paper on topic "Tracking activity and function of microorganisms by stable isotope probing of membrane lipids"

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Current Opinion in

Biotechnology

Tracking activity and function of microorganisms by stable isotope probing of membrane lipids

Gunter Wegener1,2, Matthias Y Kellermann3 and Marcus Elvert2

CrossMark

Microorganisms in soils and sediments are highly abundant and phylogenetically diverse, but their specific metabolic activity and function in the environment is often not well constrained. To address this critical aspect in environmental biogeochemistry, different methods involving stable isotope probing (SIP) and detection of the isotope label in a variety of molecular compounds have been developed. Here we review recent progress in lipid-SIP, a technique that combines the assimilation of specific 13C-labeled metabolic substrates such as inorganic carbon, methane, glucose and amino acids into diagnostic membrane lipid compounds. Using the structural characteristics of certain lipid types in combination with genetic molecular techniques, the SIP approach reveals the activity and function of distinct microbial groups in the environment. More recently, deuterium labeling in the form of deuterated water (D2O) extended the lipid-SIP portfolio. Since lipid biosynthetic pathways involve hydrogen (H+) uptake from water, lipid production can be inferred from the detection of D-assimilation into these compounds. Furthermore, by combining D2O and 13C-inorganic carbon (IC) labeling in a dual-SIP approach, rates of auto- and heterotrophic carbon fixation can be estimated. We discuss the design, analytical prerequisites, data processing and interpretation of single and dual-SIP experiments and highlight a case study on anaerobic methanotrophic communities inhabiting hydrothermally heated marine sediments. Addresses

1 Max Planck Institute for Marine Microbiology, Celsiusstraße 1, 28359 Bremen, Germany

2 MARUM Center for Marine Environmental Sciences, Leobener Straße, 28359 Bremen, Germany

3 Department of Earth Science and Marine Science Institute, University of California, Santa Barbara, CA 93106, USA

Corresponding author: Wegener, Gunter (gwegener@mpi-bremen.de)

Introduction

Microorganisms are key players in sediments and soils, mineralizing organic carbon and performing redox reactions.

Based on taxonomic marker genes such as 16S rRNA an enormous phylogenetic complexity of these organisms has been revealed. To quantify the abundance of specific groups of microorganisms in the environment different approaches based on direct counting via fluorescence in situ hybridization (FISH [1]), real-time polymerase chain reactions (qPCR; [2]), or intact polar lipids (IPLs) [3] are used. Furthermore, metagenomic and metatranscriptomic approaches successfully identify metabolic potentials of single microorganism or microbial groups [4]. However, all these approaches cannot measure or estimate the activity and anabolic substrate turnover of specific microbial groups in a natural sample, and therefore stable isotope probing (SIP) has been designed. Here, specific bio-accessible compounds with artificially labeled isotopic compositions are added to samples, with metabolically active organisms incorporating these compounds. The fraction enriched in the heavy isotope (e.g., D = 2H, 13C or 15N) is recovered in whole cells or in formed cell compounds (e.g., nucleic acids, proteins or lipids), which then allows the identification of active community members. In terms of lipid-SIP this approach is highly quantitative, as deviations from natural isotopic compositions are measured using precise isotope ratio mass spectrometry (IRMS). Lipids, however, do not possess the taxonomic specificity of nucleic acids, thus lipid-SIP often requires supplementary nucleic acid based information to fully complement the underlying community compositions.

The natural carbon isotope composition of lipids — expressed as 813C values relative to the internationally calibrated Vienna Peedee Belemnite (VPDB) standard — reveals first insights into the origin and pathways of biomass production. Heterotrophic organisms are usually limited by substrate availability, therefore their biomass largely reflects the isotopic composition of the substrate, with S13C values in the range of -15 to -27% vs VPDB [5,6]. On the contrary, autotrophic carbon fixation is accompanied by much stronger isotope effects, particularly for microorganisms from anoxic environments. For example, microbial lipids of archaea performing the anaerobic oxidation of methane (AOM) show S13C values of -100% and below [7,8,9]. Due to the high relative mass difference between the two stable isotopes of hydrogen (H and D), the microbial lipids are even stronger depleted in deuterium, reaching values down to -380% relative to the Vienna Standard Mean Ocean Water (VSMOW) standard [10].

SIP on polar/phospholipid derived fatty acids (PLFAs) has been first applied by Boschker and co-workers (1998)

Current Opinion in Biotechnology 2016, 41:43-52

This review comes from a themed issue on Analytical biotechnology

Edited by Hans Richnow and Tilmann Lueders

http://dx.doi.org/10.10167j.copbio.2016.04.022

0958-1669/© 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).

to track carbon flow from methane and acetate into biomass of sedimentary marine microorganisms [11] and since then has been applied in several soil, peat and sedimentary environments, aquifers and water bodies. Over the past 15 years, lipid-SIP employing various carbon substrates (single-SIP) was extended to a variety of microbial lipid types, including the analysis of isoprenoid-based molecules, hopanoids and steroids characteristic for archaea [12,13,14*], bacteria [15,16,17], and eukaryotes [16,18], respectively. But only most recently a combined approach using both, inorganic carbon (IC) and deuterated water (D2O) called dual-SIP was introduced, allowing the simultaneous analysis of hetero- and autotrophic carbon fixation without altering the substrate availability of the present microbial community [19**,20*].

General considerations for lipid-based SIP

In general, microorganisms are strongly adapted to specific environmental conditions. To trace the activity of certain microorganisms in a natural sample, the physico-chemical parameters of the experiment such as temperature, salinity, nutrients, pH and oxygenation should be controlled and closely mimic environmental conditions. In addition, the label uptake through potential food chains and trophic levels should be tracked by performing a time series, thus allowing insights into the interaction of multiple microbial groups across domains of life (e.g. [21,22**]). However, especially for energy-rich substrate combinations, the incubation time of the respective SIP experiment should be adjusted to prevent drastic shifts in community structures (i.e., limit cross-feeding). Thus, information about concentrations of organic substrates is mandatory in order to draw realistic conclusions about the importance and dominance of the microbial target group. Furthermore, we strongly recommend to pair lipid-SIP with detailed knowledge of the turnover of a given compound (i.e., measuring the S13C of produced IC for heterotrophic substrates) as well as the investigation of microbial community structures (i.e., 16S rRNA approaches). The knowledge on the predicted lipid biosynthesis pathways as well as metagenomic information will help to better understand the fate of the substrates in microorganisms and its turnover in the environment. Finally, lipid-SIP experiments should be scaled in a way that the membrane lipid concentrations are sufficient to measure its isotope ratios. For reasonable peak sizes (i.e., equivalent to 10 ng per lipid for S13C and ^100 ng per lipid for SD measurements) and relatively low label content (S13C < 500%; SD < 5000%) technical precisions of 1% for carbon and of 10% for deuterium can be reached. However, abiotic label incorporation and natural variation between samples has to be taken into account. Hence, killed controls should be performed, measurements should be triplicated and only results with statistical significance should be considered.

From lipid extractions to isotope values

Lipid extraction often base on protocols by Bligh and Dyer [23] with modifications described by Sturt etal. [24], which are optimized for a high extraction efficiency of IPLs. To verify lipid yields, extractions involve internal standards that resemble structural analogues of components of interest. Isotope analysis via gas chromatography (GC)-IRMS requires cleavage of polar headgroups and carbon side chains, including derivatization reactions. Mild saponification followed by esterification or directly via acidic transesterification yields fatty acid methyl esters (FAMEs; [25,26]) from bacterial and eukaryotic membranes. Analysis of ether bound isoprenoid side chains from archaeal or ether bound alkyl side chains from bacterial lipids demands harsher cleavage by hydrogen iodide or boron tribromide treatments [27,28]. The latter reactions are followed by reduction of the intermediates by either lithium aluminium hydride, lithium triethylborohydride or H2/PtO2, yielding the corresponding isoprenoid branched or straight-chain hydrocarbons [27,29]. Cleavage reaction products are accessible for carbon and hydrogen isotope ratio measurements by GC-IRMS coupled to a combustion interface as described by Hayes and colleagues for carbon [30] and Burgoyne and Hayes for hydrogen [31]. Ratios are referenced against compounds of known isotopic composition and cross-checked with pulses of reference gas (i.e., CO2 or H2) that has been standardized before with internationally certified reference compounds [32]. In order to yield true isotopic compositions of the fatty acids (S13Cfa [Eq. (1)]; SDfa; [Eq. (2)]) according to

d Cfa = [(C + 1)xd CFAME d CMeOH]/C

¿Dfa = [(Hn + 3)xdDFAME-d13DMeOH]/Hn (2)

isotopic composition of FAMEs (S13CFAME; SDFAME) need to be corrected for the introduction ofa methyl group (S13CMeOH; SDMeOH) thereby taking the number of carbon (Cn) and hydrogen (Hn) atoms into account (cf. [6]).

Quantitative aspects of single and dual-SIP

During the lipid-SIP approach, isotope ratios are compared with the compound isotopic compositions of the original sample of the experiment (i.e., time point right before label addition — T0). After the SIP experiment, positive deviations relative to the T0 sample indicate label uptake into specific membrane lipids. However, rather than using the development of the S13C or SD values that derive from the mixture of originally present and experimentally labeled lipids, a translation into lipid production rates is recommended. Many single SIP studies converted the amount of 13C-label incorporation into nanogram of label assimilation per PLFA per gram of sample, which results in specific chemotaxonomic fingerprints of microbial activity. Such calculations have been presented before (e.g. [33,34,35]). The calculation oflipid production based on the deuterium

assimilation (prodLü) during dual-SIP experiments, however, is defined by Eq. (3):

Fd -Fd

prodLD

LDT„

fd _FD

F Med F LDTn

cconcLDXaH/D

with the fractions of deuterium in the lipid (F£d; derived from the abundances of D and H; FDd = Dld/(Hld + Dld)) after an incubation interval (Tn) compared to the untreated sample (T0), the deuterium fraction in the medium (FMed) and the concentration of the lipid (concLD). All values are normalized to weight (i.e., per gram) and a time interval (i.e., per day, month or year). Moreover, a fractionation factor aH/D has to be considered because deuterium is heavily discriminated during lipid biosynthesis. A aH/D value is determined by comparing fractions of deuterium of lipid and medium (i.e., seawater or pore water: aH/D = FMed/FDDj, ). For instance, a aH/D = 1.32 is retrieved for lipids with SD values of -250% produced in water medium with a SD value of 0% [19**,36]. For the assimilation ofIC (assimjc; in autotrophic microorganisms equaling the lipid production) the respective fractions of 13C are used (Eq. (4)):

F c _F c

FLDt„ FLDT 0

assimic = F13C F13C 0 xconcLD

FDIC FLDTn

with the fractions of 13C in the lipid (fLD") after an incubation interval (Tn) compared to the untreated sample (T0) and the 13C fraction in the DIC pool (FDIC). As isotope fractionation in carbon is comparably low (^20%), a correction employing a fractionation factor is usually not necessary, but could be determined as described above.

To assess the relative importance of auto- and heterotro-phy during the dual lipid-SIP approach, the ratio Ra/p is defined as (Eq. (5)):

assim¡C

a/p prodLD

All anaerobic microorganisms assimilate substantial amounts of IC, which stays in the range of 5-30% of produced lipid carbon, resulting in Ra/p values between 0.05 and 0.3 for their membrane lipids [19**]. Autotrophic microorganisms fix all their carbon from IC, hence assimIC and prodLD are similar, which leads to Ra/p values of ~1. Intermediate lipid Ra/p values suggest production of either multiple microorganisms (mix of autotrophic and heterotrophic organisms) or by a single mixotrophic mi-crobial group.

Recent single SIP studies

Since its early description in the late 1990s, lipid-SIP has been intensively applied to determine the turnover of methane, to track inorganic carbon fixation and to study degradation and assimilation of pollutants such as toluene

in various environments [11,37,38]. Fatty acid labeling patterns derived from the calculation of 13C-incorporation in these studies have been correlated with those from cultures, thus identifying the abundance of microbial players in the environment. For a detailed overview of many of these approaches published before 2006 we refer to the review by Evershed et al. [35].

SIP using C1 - compounds

In the following years, lipid-SIP has been used preliminary in freshwater habitats such as rice paddies, peats and soils, and largely methane has been utilized as 13C-labeled carbon source (e.g., [17,22**,39] (Table 1)). With the increasing knowledge on lipid patterns of specific microorganisms, lipid 13C-incorporation and production estimates could be better addressed relative to the active community members. For example, Shrestha and coworkers (2008) and Qiu and colleagues (2008) combined PLFA- and functional gene analysis or ribosomal nucleic acid (RNA)-SIP to identify and quantify the active methanotrophic community members within the rice rhizosphere [40*,41 *]. Using a similar approach Chen and colleagues (2008) investigated methanotrophic bacteria in peatlands [42**], showing that different habitats (i.e., Calluna or Sphagnum/Eriophorum-covered moorland) are characterized by specific groups of Methylocella andMethylocystis methanotrophs. Employing an isotope switching (SIS) approach in a multi pulse-chase way, Maxfield and colleagues first added 13C-methane to a landfill cover soil, and replaced it in the middle of the experiment by 12C-methane [22**]. Their experiment resulted in a sequential assimilation of 13C first by metha-notrophic bacteria followed by secondary (Gram-negative and Gram-positive bacteria) and tertiary consumers (eukar-yotes). SIS thus provides a valuable tool where total carbon dynamics (i.e., substrate incorporation, turnover and lipid decay) in complex environmental and biological matrices are accessible.

Multiple applications of IC 13C-labeling were performed to track autotrophic community members. For example, in a IC 13C pulse-chase in situ incubation, Miyatake and coworkers traced the carbon flow from microphyto-benthos (i.e., diatoms) into bacteria such as Gammapro-teobacteria, Bacteroidetes, and Deltaproteobacteria in intertidal marine sediments [43]. Employing the same approach, Boschker and colleagues [44**] related enhanced dark carbon fixation to sulfide-oxidizing Gamma-proteobacteria that may act as important players in the coastal carbon cycle. In contrast, 13C-IC assimilation via anapleurotic reactions of Acidobacteriaceae, next to che-molithoautotrophic utilization by methanogens, was suggested to be most important in a wetland mofette soil characterized by high emanations of CO2 [45].

SIP using multiple and complex substrates

A variety of experiments focusing on bacteria and using a combination of 13C-IC and other 13C-labeled organic

Table 1

Representative studies employing SIP with various substrates and targeting membrane lipids

Labeled substrate Studied environment Targeted Employed Conclusions Ref.

membrane phylogenetic

lipid methods

CH4 Rice rhizosphere PLFAs RNA-SIP Rice rhizosphere is dominated by Type I [41-]

methanotrophs

Rice rhizosphere PLFAs pmoA-genes Methanotrophic populations exhibit a [40-]

pronounced spatial and temporal

variations

Acidic peatlands PLFAs pmoA-based Diversity of methanotrophs in peatlands [42"]

microarray are greater than previously assumed

Peat moss PLFAs, Type II methanotrophs are dominant in [17]

hopanoids peat moss

Submerged PLFAs Moss-associated methanotrophic [39]

brown moss bacteria reduce methane emissions in

tundra

Landfill cover PLFAs Sequential methane carbon assimilation [22"]

soils by methanotrophs, Gram-negative and -

positive bacteria and eukaryotes

IC* Desert soils Bacterial and Elevated CO2 concentrations lead to shifts [46]

fungal PLFAs from bacterial to fungal carbon fixation

Wetland mofette PLFAs, DNA-SIP CO2 promotes anaerobic and acidophilic [45]

isoprenoids microorganisms and alters carbon

turnover in soils

Potato plant and PLFAs RNA-SIP Rapid organic carbon transfer from roots [47]

rhizosphere TRFLP, qPCR into saprotrophic and mycorrhizal fungi

Intertidal sediments PLFAs 16S rRNA Seq Chemolithoautotrophic bacteria are [44"]

important biomass producers in

sediments

Intertidal sediments PLFAs Mag-SIP Activity of diatoms and bacteria in [48]

intertidal sediments is tightly coupled

IC, CH4 Seep sediments PLFAs, Metabolic coupling of ANME and partner [49]

isoprenoids bacteria, dominance of autotrophy

Enrichment culture PLFAs Genome analysis Dominance of autotrophic carbon dioxide [50-]

fixation during growth of denitrifying

methanotrophic bacteria

IC, CH4, methanol, AOM-dominated Isoprenoids Co-occurrence of methanotrophy and [51]

acetate microbial mat methanogenesis in AOM systems

Deep-sea sediments Polar lipid Archaeal lipid production rates imply [14-]

subgroups accumulation of 2G-GDGT in marine

sediments

IC, CH4, acetate, Yellowstone streamer PLFAs Streamer biofilms thrive predominantly on [52]

glucose, leucine, biofilm exogenous organic material

Spirulina

IC, acetate, glucose Iceland shelf sediments GDGTs Low metabolic activity in sedimentary [53]

Thaumarchaeota

IC, glucose, amino Coastal hypoxic basin PLFAs 16S rRNA gene Seq. Chemoorganotrophic cable bacteria form [54"]

acids, pyruvate consortia with autotrophic bacteria

IC, propionate Anammox bacteria, PLFAs, Ladderane lipids are formed by a yet [55]

culture ether lipids unknown pathway of biosynthesis

Acetate Grassland soils Soil microbial biomass response depend [56]

on the concentration of supplied energy

sources

Glucose Ectomycorrhizal fungi, PLFAs Position-specific 13C-glucose labeling [57"]

culture provides a framework for analyzing carbon

flow and lipid biosynthesis in fungi

Soil PLFAs Incorporation of individual glucose 13C- [58"]

positions into PLFAs showed intensive

recycling via gluconeogenesis

Deep-sea sediments Isoprenoids Arch. 16S rRNA Exclusive 13C-labeling of glycerol [59"]

glycerol units Seq. qPCR backbone indicated recycling of

membrane lipids by archaea

Table 1 (Continued )

Labeled substrate Studied environment Targeted membrane lipid Employed phylogenetic methods Conclusions Ref.

Amino acids Soil PLFAs Position-specific 13C-labeling allows insight into carbon utilization by various microbial groups [60]

Toluene Contaminated aquifer PLFAs 16S rRNA TRFLP Desulfocapsa related bacteria are main toluene-degraders in contaminated aquifers [61]

Benzene Benzene-degrading biofilm PLFAs Amino acid SIP Transfer of pollutant carbon into multiple trophic levels including midge larvae [21]

Beggiatoa Mangrove sediments PLFAs 18S rRNA Seq. Chemolithoautotrophic bacteria play a minor role for mangrove grazers [62]

* IC: Includes experiments using either bicarbonate or CO2. Abbreviations: pmoA = gene that encodes for the alpha subunit of the particulate methane monooxygenase; TRFLP = Terminal restriction fragment length polymorphism; Mag-SIP = magnetic-bead-captured rRNA-SIP.

carbon compounds such as methane, acetate and glucose has been performed in the last years. Vasquez-Cardenas and colleagues [54**], for example, studied carbon fixation in sediments dominated by cable bacteria performing longdistance electron transport. The authors identified cable bacteria to be propionate assimilating heterotrophs, which support increased autotrophic carbon fixation by side communities. Schubotz and coworkers (2015) studied the carbon fixation in streamer biofilms and found a rather mixotrophic nature of most microorganisms in this community [52]. To minimize the effect of additional substrate availability, which is a crucial aspect during SIP studies using organic substrates, Dungait and colleagues [56] used trace amounts of 13C-labeled glucose to disentangle active microbes in soils. Together with lipid patterns they were able to show that a large portion of glucose was metabolized by Actinobacteria and other Gram-positive bacteria.

Lipid-SIP on archaeal lipids was introduced by Wuchter and colleagues (2003) demonstrating that marine Cre-narchaeota are autotrophs. In the following years, many lipid-SIP experiments have been designed to trace the activity of archaea, specifically of those performing AOM. For example, Blumenberg and coworkers [63] and Jagersma etal. [13] traced the assimilation of 13C-methane into AOM communities, recovering it in anaerobic metha-notrophic archaea (ANME) and their sulfate-reducing partner bacteria. Evidence that a large fraction of lipid carbon in ANME and their partner bacteria derives from IC was provided in follow-up experiments by Wegener and colleagues [49] using either 13C-labeled methane or IC. Extension of this approach to additional 13C-sub-strates such as methanol and acetate by Bertram etal. [51] gave rise to the question whether certain ANME may contain the metabolic capabilities to concomitantly function as methanogens.

Focusing on the activity of archaea in sediments, several lipid-SIP studies were performed including different substrates and amendments. For example, Takano and coworkers [59**] carried out benthic in situ-labeling

experiments in order to address the question whether sedimentary archaea are actively growing on organic substrates such as glucose. Whereas archaeal core lipid-derived hydrocarbons were not found to incorporate any of the 13C-labeled glucose, the glycerol moieties of the ether lipids were strongly labeled. The authors concluded that the glycerol unit is synthesized de novo, while the isoprenoid unit is recycled from relic archaeal membranes. Subsequently, approaches by Lin et al. [14*] and Lengger et al. [53] used a wider suite of 13C-labeled substrates (i.e., IC, acetate, glucose) and found a minor or lacking uptake into archaeal lipids, respectively. Based on low 13C -incorporation and extremely slow turnover rates of archaeal lipids both studies concluded that benthic archaea are rather inactive and that sedimentary archaeal membrane components have either a long residence time or an allochthonous origin.

A recent development in the field of SIP employed 13C-labeling at specific positions of sugars and amino acids [57**,58**,60], representing carbohydrates and proteins as two of the most abundant carbon pools within microorganisms and the environment. By applying the same molecule but carrying 13C-label at a different C-position provides detailed information about carbon utilization and metabolic pathways such as gluconeogenesis as well as lipid biosynthesis in single microorganisms. Information about lipid biosynthetic pathways, however, could likewise be obtained by following the strength of label uptake into various fatty acids molecules and moieties such as performed by Rattray et al. (2009) targeting ladderane lipid biosynthesis of anaerobic ammonium oxidizing (ana-mmox) bacteria [55]. These authors combined classical PLFA analysis with high-field 13C nuclear magnetic resonance spectroscopy on isolated fatty acids and found that ring moieties of ladderane lipids are produced via a different route than straight-chain fatty acids.

The dual-SIP approach

In the past, autotrophic carbon fixation and heterotro-phic activity has been independently investigated by

Figure 1

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1,500-

ÈÎ 1,000-

1,500-

èî 1,000-

50,000

30,000

èî -

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>. 6,000

Ol "O 4,000

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13C-CH4 assimilation

ô 13C values

®T„

■ IÎ

Dual-SIP

13C-IC assimilation

ô 13C values

' T24 (13CH4)

x T24 (no-CH4) T

Dual-SIP

D2O assimilation

ôD values

* T24 (13CH4)

X T24 (no-CH T

Dual-SIP

Lipid production and IC assimilation

assimIC Ra/p= prodL[)

■if iHùo

6" 6" 6" ^ ^ 1-1-1-

00 00O

<ö O 03O OOO

'<5 6" 6" a 6" Ü

= 0.6 0. ci b.d.

,_. ,_. ,_. ,_.

0 1— CM CO

n CL CL n

m m m m

Current Opinion in Biotechnology

T24 (13CH4)

Shift of lipid carbon and hydrogen isotopic composition in a single (a), in dual-SIP experiment (b, c) and lipid production/assimilation rates (d) between (T0) and after 24 days of incubation with labeled substrates (T24). (a) 813C values in a single SIP experiment with 13CH4 (■) and (b) 813C and (c) SD values in a dual-SIP experiment with (*) and without (x) methane. Green symbols mark isotope values above 0% with different scales; grey background line: Sections of exemplary gas chromatograms. (d) Calculated rates of IC assimilation into lipids (assimIC) and production of lipids (prodLD) and their respective ratios (Ra/p) for only the 'plus methane'-experiment; bold = production by autotrophs, italic: production by hetero- or mixotrophs. Bacterial fatty acid nomenclature: xCn:pvq; where 'x' defines a methyl branch at the terminal 'i = iso' or subterminal ' ai = anteiso' position, ' n' refers to the carbon chain length, and 'p'v'q' to number of double bounds and position from the hydrophobic ' w' end, respectively. Archaeal isoprenoid nomenclature: Phy = phytane derived from the glycerol diether lipid archaeol, and BP = biphytane derived from glycerol dibiphytanyl glycerol tetraethers (GDGTs), with index (n) indicating the number of cyclopentane rings (exception BP(3) with two cyclopentane and one cyclohexane ring).

13C-uptake from IC and assimilation of various 13C-labeled organic carbon sources, respectively. However, the addition of 13C-labeled organic substrates supplies an extra energy source that likely stimulates a certain group of specialized heterotrophs. Hence, lipid-SIP experiments with single heterotrophic substrates are suitable to identify active microorganisms, but often fail to reproduce natural activity of the entire microbial

population. SIP with IC, on the other hand, will also detect anapleurotic carbon fixation, i.e., to refuel critical intermediates in the metabolic machinery, by hetero-trophic microorganisms. Depending on biochemical pathways and substrates, heterotrophic organisms have shown to assimilate IC between 1 and 30% [19**,64] and up to 50% in type II methanotrophic bacteria [65].

To overcome the limitations of single SIP, dual-SIP with D2O combined with 13C-IC was developed [19**]. D2O labeling allows quantitative tracking of lipid production under in situ conditions without providing an additional energy source as suspected for carbon substrates. This approach facilitates the determination of total lipid production rates because the reduced proton carrier nicotin-amide adenine dinucleotide phosphate (NADPH) introduces protons during all reduction steps of lipid synthesis. In both, bacteria and archaea, first the precursor acetyl-CoA is formed. In the bacterial fatty acid synthesis pathway the acetyl CoA is reduced with NADPH to butyryl-subunits, which by combination are elongated up to palmitate [66]. Archaeal isoprenoid lipid formation, on the contrary, uses the acetyl-CoA reduction with NADPH in the mevalonate pathway [67]. Abiotic exchange between lipids and water hydrogen is meanwhile inherently slow, as shown by the preservation of the lipid hydrogen isotope signal on geological time scales [68]. Moreover, it has to be considered that the addition of high amounts of D2O (60-90%) slows down metabolic activity or is even toxic to microorganisms [69]. Microorganisms with low energy yields such as acetotrophic and hydro-genotrophic methanogens seem to be even more sensitive to D2O. Here, only D2O concentrations of <10% and <23%, respectively, did not affect methane production rates (Wegener, unpublished data).

The concurrent tracking of 13C-IC assimilation and lipid production rates via D2O can provide an estimate of the ratio between auto- and heterotrophic carbon fixation. The applicability of this approach has been demonstrated for the first time by Wegener and coworkers [19**] using cultures of Desulfosarcina variabilis. The dual-SIP approach was applied to study the metabolic activity of microorganisms in marine sediments and identified het-erotrophic microorganisms being responsible for the high lipid production rates close to the sediment surface. The steeply declining lipid biomass production rates and the increase of autotrophic carbon fixation in deeper horizons suggested a microbial community that was less dependent on organic carbon sources. However, the strongest contribution of autotrophic carbon fixation so far was observed within the sulfate-methane transition zone, thus confirming the autotrophic nature of AOM communities. The specific lifestyle of AOM communities was later explored in much detail by Kellermann et al. applying the dual-SIP approach in hydrothermally-heated sediments from the Guaymas Basin [20*] (see case study below). Moreover, based on these experiments and ar-chaeal lipid hydrogen isotope analysis of purified IPL fractions, Kellermann and coworkers most recently suggested that the tetraether biosynthetic pathway involves i) the production of intact phospho-archaeols, ii) condensation of two phospho-archaeol molecules to phospho-GDGTs and iii) progressive substitution ofphospho- with glyco-headgroups in GDGTs [70*].

Case Study: Tracing metabolic activity, function and carbon sources in anaerobic methanotrophic communities by single and dual-SIP approaches.

The case study we present in Figure 1 used incubations with (i) 13C-labeled methane (16%), (ii) 13C-IC (10%), D2O (3%) and non-labeled methane, and (iii) labeling as applied in (ii) but without methane. The samples were incubated in a time series for up to 24 days at 37 °C (for details see [20*]). Microbial lipids were extracted and analyzed as described above. The single-SIP approach shows 13C-methane carbon uptake for both, archaeal and bacterial lipids (Figure 1a). However, both lipid groups show even higher methane-dependent 13C-IC uptake (Figure 1b), which strongly decreases in the absence of methane (displayed with red crosses in Figure 1b and c). These results provide strong evidence for the central role of methane as energy source but also for its minor importance as direct carbon source for the AOM communities. To fully assess the role of IC fixation the same lipids were analyzed for deuterium uptake (Figure 1c). To quantitatively compare de novo lipid production from 13C-IC and D2O uptake from water, isotope values are converted into IC assimilation rates (assimIC) and lipid production rates (prodLD) as described above. In the presence of methane, Ra/p values of for specific bacterial fatty acids (i.e., iC16:1v6, iCi8:iV6, C18:1v7) and archaeal isoprenoid hydrocarbons (i.e., phytane), confirmed their production by microorganisms functioning as autotrophs (Figure 1d). Bacterial lipids with Ra/p values lower than 0.6 are likely not only produced by AOM partner bacteria but also by co-occurring heterotrophic background communities.

Conclusions and future perspectives

In the past two decades, SIP of microbial lipids has been established as an essential, quantitative and culture-independent approach to study the activity as well as the carbon substrate turnover of microorganisms in various environments. The previously forecasted expansion of lipid-SIP applications [35] including the widening of the traceable lipid portfolio has been met. Approaches such as SIS, dual and position-specific SIP opens the field towards an extended understanding of microbial activity, metabolic function, lipid biosynthesis and carbon flow in any system holding active microbial communities. The limited phylogenetic resolution of lipid-SIP has been encountered by additional taxonomic nucleic acid based approaches to identify the active microbial community members. In addition, the sensitivity and specificity of lipid-SIP can be further increased by focusing on IPL classes derived from solely live and metabolically active microorganisms which are purified by preparative, multidimensional liquid chromatography [70*]. By excluding non-labeled, extracellular bulk lipids, the detection limit of isotope analysis is potentially lowered, which in turn allows SIP applications to microbial communities with lower activities that so far were inaccessible to current

lipid-SIP approaches. Lipid-SIP has not been recognized by applied sciences, but its application would allow quantitative insights into microbial activity during in situ microcosm experiments involving natural and stimulated biodegradation of organic pollutants (e.g., Fischer et al., this issue [71]). We also hypothesize that future D2O labeling approaches may combine 13C-labeling of organic carbon sources other than methane or IC. In these experiments, the lipid deuterium signal could be used to identify the influence of the organic carbon compound on the overall lipid production relative to a control sample without organic substrate addition. Finally, to fully understand the fate of organic carbon substrates, 13C-labeled metabolic intermediates should be monitored by coupled liquid chromatography - IRMS techniques, thus accessing the full complexity during lipid biosynthesis and of carbon transfer between various microbial groups.

Acknowledgements

The study was supported by the Deutsche Forschungsgemeinschaft (through the Research Center/Excellence Cluster MARUM - Center for Marine Environmental Sciences; M.E. and G.W.), the Gottfried Wilhelm Leibniz Price awarded to Antje Boetius (G.W.) and the National Science Foundation (Grant No. QCE-1046144; M.Y.K.).

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