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Copyright © 2008 by The National Academy of Sciences of the USA Environmental Sciences A single-cell view on the ecophysiology of anaerobic phototrophic bacteria aMax Planck Institute for Marine Microbiology, Celsiusstrasse 1, 28359 Bremen, Germany; bMax Planck Institute for Chemistry, Johann-Joachim-Becher Weg 27, 55128 Mainz, Germany; cCantonal Institute of Microbiology and Alpine Biology Center Foundation Piora, Via Mirasole 22A, CH-6500 Bellinzona, Switzerland; and dCameca, Quai des Gresillons 29, 92622 Gennevilliers Cedex, France 1To whom correspondence should be addressed. E-mail: nmusat/at/mpi-bremen.de Communicated by John M. Hayes, Woods Hole Oceanographic Institution, Woods Hole, MA, September 22, 2008. Author contributions: N.M. and M.M.M.K. designed research; N.M., H.H., and B.W. performed research; B.W., P.H., S.P., F. Hillion, F. Horreard, R.A., and B.B.J. contributed new reagents/analytic tools; N.M., F. Horreard, and M.M.M.K. analyzed data; and N.M. and M.M.M.K. wrote the paper. Received April 21, 2008. Freely available online through the PNAS open access option. This article has been cited by other articles in PMC.Abstract Quantitative information on the ecophysiology of individual microorganisms is generally limited because it is difficult to assign specific metabolic activities to identified single cells. Here, we develop and apply a method, Halogen In Situ Hybridization-Secondary Ion Mass Spectroscopy (HISH-SIMS), and show that it allows simultaneous phylogenetic identification and quantitation of metabolic activities of single microbial cells in the environment. Using HISH-SIMS, individual cells of the anaerobic, phototropic bacteria Chromatium okenii, Lamprocystis purpurea, and Chlorobium clathratiforme inhabiting the oligotrophic, meromictic Lake Cadagno were analyzed with respect to H13CO3− and 15NH4+ assimilation. Metabolic rates were found to vary greatly between individual cells of the same species, showing that microbial populations in the environment are heterogeneous, being comprised of physiologically distinct individuals. Furthermore, C. okenii, the least abundant species representing ≈0.3% of the total cell number, contributed more than 40% of the total uptake of ammonium and 70% of the total uptake of carbon in the system, thereby emphasizing that numerically inconspicuous microbes can play a significant role in the nitrogen and carbon cycles in the environment. By introducing this quantification method for the ecophysiological roles of individual cells, our study opens a variety of possibilities of research in environmental microbiology, especially by increasing the ability to examine the ecophysiological roles of individual cells, including those of less abundant and less active microbes, and by the capacity to track not only nitrogen and carbon but also phosphorus, sulfur, and other biological element flows within microbial communities. Keywords: anaerobic phototrophs, nanoSIMS Molecular biological approaches have in recent years provided a wealth of high-resolution information regarding the genetics, ecology, and evolution of microbial populations (1–5). At the cellular level, however, quantitative information on the ecophysiology of individual microorganisms in the environment is generally scarce (see refs. 6 and 7). A major goal, therefore, is to assign specific metabolic activities to the identities of individual cells. A particularly promising approach to this objective is Secondary Ion Mass Spectrometry (SIMS), which was applied for the first time in environmental microbiology to follow inorganic carbon and nitrogen assimilation by bacterial and fungal cells and to show that aggregates of archaea and sulfate-reducing bacteria founds in sediments where anaerobic oxidation of methane predominated were indeed consuming methane (6, 8). Single-cell resolution with sufficient mass-resolving power was, however, only recently achieved through the development of nano-scale secondary-ion mass spectrometry (nanoSIMS). Other methods currently used either do not provide single-cell resolution or, like microautoradiography, require that microorganisms be fed radioactively labeled substrates. The uptake of radioisotopes then directly links individual microbial cells to their activity in the environment (ref. 7 and references therein). However, this approach is limited to elements that have a radioisotope with a suitable half-life (>1 d; for example 14C and 3H) and excludes the study of other elements such as nitrogen. NanoSIMS, on the other hand, can be used to measure the distribution of any stable isotope as well as any radioisotope with a suitable half-life, and thus, the uptake of radioactive or stable-isotope labeled substrates can be monitored (9). Using nanoSIMS, carbon and nitrogen uptake by nitrogen-fixing cyanobacteria (10) and in situ nitrogen fixation by individual bacterial symbionts of shipworms (11) have been quantified. When combined with in situ hybridization using halogen- or stable-isotope-labeled gene probes, nanoSIMS can additionally be used for the identification of individual microbes (12, 13). Here we developed and applied a method that allowed us to examine the ecophysiology of single cells in the environment using nanoSIMS. It uses horseradish-peroxidase-labeled oligonucleotide probes and fluorine-containing tyramides for the identification of microorganisms in combination with stable-isotope-labeling experiments for analyzing the metabolic function of single microbial cells. Using this method, we have quantified metabolic activities of single cells of purple and green sulfur bacteria inhabiting the oligotrophic, meromictic Lake Cadagno, a stratified alpine lake located in the Piora Valley in the Southern Alps of Switzerland. Springs supply salty water to its depths (14), and, as a result, Lake Cadagno is permanently stratified. The upper, oxic waters are well-mixed and contain low concentrations of phosphate and nitrate (14, 15). The anoxic, lower layer is stagnant and enriched in phosphate and ammonium. At the chemocline between these 2 layers, sharp gradients appear in depth profiles of these nutrients and in those of oxygen, sulfate, sulfide, and light (14, 16). The physicochemical conditions favor development at the chemocline of a community consisting mainly of purple and green photosynthetic sulfur bacteria. The seasonal variations of this assemblage have been studied intensively in the past 10 years (15–17) and make this lake an attractive test system for investigating the activities of single cells. These anaerobic phototrophs, which use light energy to oxidize sulfide and other reduced sulfur compounds, are commonly found in seasonally or permanently stratified lakes, anoxic ponds or sediments. Numerically abundant, in many of these environments they are responsible for the oxidation of the entire sulfide flux and thus play a critical role in the sulfur cycle (18–20). However, the distribution of processes and materials among individual cells in such environments remains unknown. Here we quantified and compared ammonium and inorganic carbon uptake of 3 species of anaerobic phototrophs, Chlorobium clathratiforme, Chromatium okenii, and Lamprocystis purpurea, and quantitatively determined their contribution to the total ammonium and inorganic carbon assimilation in the system. Moreover, metabolic activities of individual cells belonging to the same species were analyzed and compared. We conclude that halogen in situ hybridization coupled to secondary ion mass spectrometry (HISH-SIMS) will provide hitherto unavailable information about microbial populations. Results and Discussion Physicochemical Parameters of Lake Cadagno and Relative Abundance of Anaerobic Phototrophs. Measurements of physicochemical parameters confirmed earlier reports (16, 21, 22), showing steep vertical gradients of nutrients and oxygen within the pycnocline and a shift in redox potential between 10- and 11-m depth, indicating anoxic, reducing conditions in the hypolimnion (Fig. 1
Single-Cell Analysis. We analyzed single cells of C. clathratiforme, the most abundant microorganism at all depths investigated, L. purpurea, one of the most abundant, small-celled, purple sulfur bacteria, and C. okenii, the only large-celled purple sulfur bacterium present. For this purpose, water samples from 11.5-m depth were incubated for 12 h at in situ light and temperature conditions after addition of 15N-labeled ammonium and 13C-labeled bicarbonate. After incubation, the samples were handled as described for Escherichia coli and Azoarcus sp. cells (SI Text) and hybridized with HRP-labeled oligonucleotide probes targeting specific regions of the 16S rRNA of the 3 species. After the deposition of fluorine-containing tyramides, filters were immediately analyzed using nanoSIMS. For each individual cell, we recorded simultaneously secondary-ion images of naturally abundant 12C (measured as 12C−) and 14N (measured as 12C14N−) atoms and, similarly, of 13C, 15N, and 19F (Figs. 3
All analyzed cells were substantially enriched in 15N and 13C relative to the nonamended cells (Figs. 3
A notable exception was one particular C. okenii cell that had epibiontic microorganisms attached to the surface and that was characterized by significantly lower ammonium uptake than other C. okenii cells (Figs. 5 By averaging and comparing the uptake rates of individual cells of each species, we determined that the least abundant C. okenii assimilated approximately 60 times more ammonium and 70 times more inorganic carbon than L. purpurea and approximately 700 times more ammonium and 1,000 times more inorganic carbon than C. clathratiforme in the chemocline of Lake Cadagno (Fig. 6 Based on 15N/14N and 13C/12C ratios of individual cells and on the labeling percentages of the substrates used (i.e., H13CO3− and 15NH4+), we calculated the doubling times for C. okenii, L. purpurea, and C. clathratiforme cells. We assumed that all carbon and ammonium assimilated stimulated growth of new cells. This supposition can lead to an underestimation of the carbon-based doubling times for species that deposit C-rich storage compounds (20). For all 3 species, particularly C. clathratiforme, C-based doubling times varied widely (Fig. 7
We determined the total uptake of ammonium and inorganic carbon for each species by multiplying the average uptake rates by the absolute cell abundance. Summed, these accounted for ≈57% of total ammonium uptake and ≈85% of total inorganic carbon uptake in the system as measured by bulk incubations and analyses (Figs. 6 At present, we can only speculate why an organism with an average doubling time 7 times shorter than C. clathratiforme is present in such low abundance. The relative abundance of these species might have been influenced by an enhanced predation pressure in the system. C. okenii could have been subjected to a higher predation pressure by anaerobic protozoa and predatory prokaryotes (23, 32). Growing in net-like structures or large aggregates, C. clathratiforme and L. purpurea are less susceptible to protozoan grazers than are the single cells of C. okenii (33, 34). On the other hand, growth as single, motile cells provides an advantage to C. okenii, which can move freely through the water column and find the best zones of nutrient availability and light intensity for its metabolic requirements. One of the most intriguing findings in our study was the large range of uptake rates of ammonium and inorganic carbon for single cells of the same species (Fig. 6 An alternative explanation for the high metabolic variability of individual cells within the same species could be nongenetic heterogeneity caused by differences in gene expression among individual bacteria (39). Cells of different age or with different life histories would be in different physiological states. They might have experienced different ammonium or sulfide concentrations, have suffered from traces of oxygen, or adapted to different light intensities. Although this hypothesis could be tested by monitoring specific mRNA in single cells of a 16S rRNA-defined population (40), a proof of genomic heterogeneity would still require population-genetic studies of isolates or metagenomic studies. In conclusion, by applying HISH-SIMS to green and purple sulfur bacteria from a natural environment, we found a remarkable variability in metabolic rates of individual cells of the same species. Consequently, a microbial population can now be studied as a heterogeneous group of physiologically distinct individuals. Moreover, the major contribution of less abundant but highly active microorganisms to ammonium and carbon uptake underlines the great importance of rare keystone species to the nitrogen and carbon cycles in the environment. The HISH-SIMS method opens new lines of research in environmental microbiology, especially by enabling studies of the ecophysiology of individual, phylogenetically identified cells and by the capacity to track not only the flows of nitrogen and carbon but also those of phosphorus, sulfur, and other biologically active elements within microbial communities. Materials and Methods Measurements of Physicochemical Parameters. Culture Preparation and Fixation. Sample Collection and Preparation. Water samples were collected from the center of Lake Cadagno (46° 33′ N, 8° 43′ E) in June 2007. The depth at the center (the deepest point) was 21 m. Water samples were collected at depths of 10.5, 11.5, and 12.5 m, fixed for FISH in 1% PFA for 1 h at room temperature, filtered on polycarbonate filters, and kept at −20 °C until processing. Parallel water samples from 11.5-m depth were collected and incubated with 15N-labeled ammonium (21.6 atom percent 15N) and 13C-labeled bicarbonate (19.3 atom percent 13C) in 250-mL bottles at in situ light and temperature conditions for 4, 8, and 12 h (SI Text). Subsamples were taken for bulk measurements of nitrogen and carbon and for nanoSIMS analysis of single cells (see SI Text). Whole Cell Hybridization. Catalyzed reporter deposition (CARD)-FISH and cell counts were done using standard protocols (SI Text). The oligonucleotide probes used in this study are shown in Table S3. For nanoSIMS analysis, fixed cells were permeabilized in a lysozyme solution [10 mg mL−1 in 0.05 M EDTA (pH 8.0) and 0.1 M Tris·HCl, pH (7.5); Fluka] for 1 h at 37 °C. After permeabilization, filters were washed twice with 2 mL of ultrapure water (MQ; Millipore), treated with HCl (0.01 M) for 10 min, washed twice in MQ water, and dehydrated with 96% ethanol for 1 min. Before hybridization, filters were prehybridized for 1 h at 46 °C in hybridization buffer containing 0.9 M NaCl, 40 mM Tris-HCl (pH 7.5), 10% dextran sulfate, 0.01% SDS (SDS), 10% Blocking Reagent (Boehringer), 1× Denhard's reagent, 0.26 mg mL−1 sheared salmon sperm DNA (Ambion), 0.2 mg mL−1 yeast RNA (Ambion), and the corresponding formamide concentration (Table S3). The hybridization was performed using the protocol previously described (41) with the following modifications: After prehybridization, the HRP-labeled probe working solution (50 ng μL−1; Biomers) was added (1:150 vol/vol) to the hybridization buffer and well mixed. Hybridizations were carried out for 6 h at 46 °C. After hybridization, filters were incubated in 50 mL of prewarmed washing buffer containing NaCl (215 mM for Chlc190, 46 mM for Apur453, and 70 mM for Cmok453 hybridized filters), 5 mM EDTA (pH 8.0), 20 mM Tris-HCl (pH 7.5), and 0.01% SDS for 15 min at 48 °C. After washing, filters were transferred in 1× PBS (pH 7.6) for 30 min to equilibrate the probe-delivered HRP. Subsequently, the filters were incubated for 20 min at 46 °C in darkness for tyramide signal amplification. The reactant mixture contained amplification buffer and fluorine-containing tyramides (1,000:1 vol/vol) and 0.015% H2O2. The filters were then washed once for 15 min in 1× PBS in darkness, twice with MQ water, and once for 1 min in 96% ethanol. Synthesis of tyramides and preparation of the substrate mixture containing amplification buffer and H2O2 were done as described (SI Text and ref. 42). Nitrogen and Carbon Bulk Measurements. Abundances of 15N and 13C were measured using standard methods (SI Text). NanoSIMS Analysis of Single Cells—Image Acquisition and Data Processing. The hybridized filters were analyzed between January 2007 and October 2007 using a NanoSIMS 50 and a NanoSIMS 50L manufactured by Cameca. For each individual cell, we recorded simultaneously secondary ion images of 12C−, 13C−, 12C14N−, 12C15N−, and 19F− using 5 electron multipliers (Figs. 3 Biovolume Calculation and Biomass Conversion. The sizes of C. okenii, L. purpurea, and C. clathtratiforme cells were directly measured from the epifluorescence microscope images taken after fluorescence in situ hybridization and DAPI staining. Biovolume calculation and biomass conversion are described in SI Text. Calculation of the Ammonium and Inorganic Carbon Assimilation Rates. Amounts of ammonium and inorganic carbon assimilated by individual cells were calculated from the 15N/14N and the 13C/12C ratios of the individual regions of interest (Table S2), the mean biovolume for the corresponding species, and the amounts of label added in the incubation experiments. The total assimilation for each species was calculated by multiplying the average assimilation rates of individual cells by the number of cells of the corresponding species (as determined by FISH). Calculation of the Doubling Times. Doubling times of the 3 species were calculated using the 15N/14N and 13C/12C ratios, the biovolume and the conversion factor into biomass to calculate first the 15N and 13C excess (as atomic percent) into individual cells. Using these values and the percentage of label added in the incubation experiments as well as the time of incubation, we calculated the doubling time for individual C. okenii, C. clathratiforme, and L. purpurea cells. SI. Further information, including Figs. S2 and S3, is available in SI Text. Acknowledgments. We thank G. Lavik, F. Musat, B. Fuchs, and C. Moraru for useful discussions and D. Franzke and G. Klockgether for technical support. This study was supported by the Max-Planck-Gesellschaft. 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Nat Rev Genet. 2002 Jun; 3(6):462-73.
[Nat Rev Genet. 2002]Annu Rev Microbiol. 2003; 57():369-94.
[Annu Rev Microbiol. 2003]Nature. 2004 Jul 29; 430(6999):551-4.
[Nature. 2004]Curr Opin Microbiol. 2002 Oct; 5(5):520-4.
[Curr Opin Microbiol. 2002]Environ Microbiol. 2004 Sep; 6(9):875-8.
[Environ Microbiol. 2004]Appl Environ Microbiol. 1999 Mar; 65(3):1325-30.
[Appl Environ Microbiol. 1999]Appl Environ Microbiol. 1999 Mar; 65(3):1325-30.
[Appl Environ Microbiol. 1999]Appl Environ Microbiol. 2005 Jul; 71(7):3544-50.
[Appl Environ Microbiol. 2005]Appl Environ Microbiol. 2005 Jul; 71(7):3544-50.
[Appl Environ Microbiol. 2005]Proc Natl Acad Sci U S A. 1986 Apr; 83():2138-42.
[Proc Natl Acad Sci U S A. 1986]Arch Mikrobiol. 1970; 73(1):1-18.
[Arch Mikrobiol. 1970]Appl Environ Microbiol. 1989 Jan; 55(1):78-85.
[Appl Environ Microbiol. 1989]Proc Natl Acad Sci U S A. 1986 Apr; 83():2138-42.
[Proc Natl Acad Sci U S A. 1986]FEMS Microbiol Ecol. 2001 Apr; 35(2):113-121.
[FEMS Microbiol Ecol. 2001]Nature. 1998 Jun 4; 393(6684):464-7.
[Nature. 1998]Appl Environ Microbiol. 2004 Aug; 70(8):4831-9.
[Appl Environ Microbiol. 2004]Annu Rev Microbiol. 2003; 57():369-94.
[Annu Rev Microbiol. 2003]Curr Opin Microbiol. 2002 Oct; 5(5):520-4.
[Curr Opin Microbiol. 2002]Science. 2005 Feb 25; 307(5713):1311-3.
[Science. 2005]Mol Microbiol. 1998 Mar; 27(6):1099-105.
[Mol Microbiol. 1998]Appl Environ Microbiol. 2005 Jul; 71(7):3544-50.
[Appl Environ Microbiol. 2005]Appl Environ Microbiol. 2002 Jun; 68(6):3094-101.
[Appl Environ Microbiol. 2002]