Neufeld JD, Wagner M, Murrell JC. Who eats what, where and when? Isotope-labelling experiments are coming of age. ISME J. 2007;1:103–10.
Google Scholar
Boschker HTS, Nold SC, Wellsbury P, Bos D, de Graaf W, Pel R, et al. Direct linking of microbial populations to specific biogeochemical processes by 13C-labelling of biomarkers. Nature. 1998;392:801–5
Jehmlich N, Schmidt F, von Bergen M, Richnow H-H, Vogt C. Protein-based stable isotope probing (Protein-SIP) reveals active species within anoxic mixed cultures. ISME J. 2008;2:1122–33.
Google Scholar
Radajewski S, Ineson P, Parekh NR, Colin Murrell J. Stable-isotope probing as a tool in microbial ecology. Nature. 2000;403:646–9.
Google Scholar
Manefield M, Whiteley AS, Griffiths RI, Bailey MJ. RNA stable isotope probing, a novel means of linking microbial community function to phylogeny. Appl Environ Microbiol. 2002;68:5367–73.
Google Scholar
Berry D, Mader E, Lee TK, Woebken D, Wang Y, Zhu D, et al. Tracking heavy water (D2O) incorporation for identifying and sorting active microbial cells. Proc Natl Acad Sci USA. 2015;112:E194–203.
Google Scholar
Jehmlich N, Vogt C, Lünsmann V, Richnow HH, von Bergen M. Protein-SIP in environmental studies. Curr Opin Biotechnol. 2016;41:26–33.
Google Scholar
Haichar, FEZ, Achouak W, Christen R, Heulin T, et al. Identification of cellulolytic bacteria in soil by stable isotope probing. Environ Microbiol. 2007;9:625–34
Rangel-Castro JI, Ignacio Rangel-Castro J, Killham K, Ostle N, Nicol GW, Anderson IC, et al. Stable isotope probing analysis of the influence of liming on root exudate utilization by soil microorganisms. Environ Microbiol. 2005;7:828–38.
Google Scholar
Wang Y, Song Y, Tao Y, Muhamadali H, Goodacre R, Zhou N-Y, et al. Reverse and multiple stable isotope probing to study bacterial metabolism and interactions at the single cell level. Anal Chem. 2016;88:9443–50.
Google Scholar
Sharma K, Palatinszky M, Nikolov G, Berry D, Shank EA. Transparent soil microcosms for live-cell imaging and non-destructive stable isotope probing of soil microorganisms. Elife. 2020;9:e56275.
Google Scholar
Lee KS, Landry Z, Pereira FC, Wagner M, Berry D, Huang WE, et al. Raman microspectroscopy for microbiology. Nat. Rev. Methods Primers. 2021;1:80.
Google Scholar
Hatzenpichler R, Krukenberg V, Spietz RL, Jay ZJ. Next-generation physiology approaches to study microbiome function at single cell level. Nat Rev Microbiol. 2020;18:241–56.
Google Scholar
Wagner M. Single-cell ecophysiology of microbes as revealed by raman microspectroscopy or secondary ion mass spectrometry imaging. Ann Rev Microbiol. 2009;63:411–29
Lennon JT, Jones SE. Microbial seed banks: the ecological and evolutionary implications of dormancy. Nat Rev Microbiol. 2011;9:119–30.
Google Scholar
Lewis K. Persister cells, dormancy and infectious disease. Nat Rev Microbiol. 2006;5:48–56.
Google Scholar
Nielsen KM, Johnsen PJ, Bensasson D, Daffonchio D. Release and persistence of extracellular DNA in the environment. Environ Biosafety Res. 2007;6:37–53.
Google Scholar
Blazewicz SJ, Barnard RL, Daly RA, Firestone MK. Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. ISME J. 2013;7:2061–8.
Google Scholar
Nocker A, Sossa-Fernandez P, Burr MD, Camper AK. Use of propidium monoazide for live/dead distinction in microbial ecology. Appl Environ Microbiol. 2007;73:5111–7.
Google Scholar
Tawakoli PN, Al-Ahmad A, Hoth-Hannig W, Hannig M, Hannig C. Comparison of different live/dead stainings for detection and quantification of adherent microorganisms in the initial oral biofilm. Clin Oral Investig. 2013;17:841–50.
Google Scholar
Netuschil L, Auschill TM, Sculean A, Arweiler NB. Confusion over live/dead stainings for the detection of vital microorganisms in oral biofilms-which stain is suitable? BMC Oral Health. 2014;14:2.
Google Scholar
Hatzenpichler R, Connon SA, Goudeau D, Malmstrom RR, Woyke T, Orphan VJ. Visualizing in situ translational activity for identifying and sorting slow-growing archaeal−bacterial consortia. Proc Natl Acad Sci USA. 2016;113:E4069–78.
Google Scholar
Kuru E, Hughes HV, Brown PJ, Hall E, Tekkam S, Cava F, et al. In Situ probing of newly synthesized peptidoglycan in live bacteria with fluorescent D-amino acids. Angew Chem Int Ed Engl. 2012;51:12519–23.
Google Scholar
Kopf SH, McGlynn SE, Green-Saxena A, Guan Y, Newman DK, Orphan VJ. Heavy water and15N labelling with NanoSIMS analysis reveals growth rate-dependent metabolic heterogeneity in chemostats. Environ Microbiol. 2015;17:2542–56
Kopf SH, Sessions AL, Cowley ES, Reyes C, Van Sambeek L, Hu Y, et al. Trace incorporation of heavy water reveals slow and heterogeneous pathogen growth rates in cystic fibrosis sputum. Proc Natl Acad Sci USA. 2016;113:E110–6.
Google Scholar
Neubauer C, Kasi AS, Grahl N, Sessions AL, Kopf SH, Kato R, et al. Refining the Application of Microbial Lipids as Tracers of Staphylococcus aureus Growth Rates in Cystic Fibrosis Sputum. J Bacteriol. 2018;200:e00365–18.
Google Scholar
Haider S, Wagner M, Schmid MC, Sixt BS, Christian JG, Häcker G, et al. Raman microspectroscopy reveals long-term extracellular activity of Chlamydiae. Mol Microbiol. 2010;77:687–700.
Google Scholar
Kloehn J, Boughton BA, Saunders EC, O’Callaghan S, Binger KJ, McConville MJ. Identification of Metabolically Quiescent Leishmania mexicana Parasites in Peripheral and Cured Dermal Granulomas Using Stable Isotope Tracing Imaging Mass Spectrometry. mBio. 2021;12:e00129–21.
Google Scholar
Kong L, Setlow P, Li Y-Q. Direct analysis of water content and movement in single dormant bacterial spores using confocal Raman microspectroscopy and Raman imaging. Anal Chem. 2013;85:7094–101.
Google Scholar
Knudsen SM, Cermak N, Delgado FF, Setlow B, Setlow P, Manalis SR. Water and small-molecule permeation of dormant Bacillus subtilis spores. J Bacteriol. 2016;198:168–77.
Google Scholar
Chen D, Huang S-S, Li Y-Q. Real-time detection of kinetic germination and heterogeneity of single Bacillus spores by laser tweezers Raman spectroscopy. Anal Chem. 2006;78:6936–41.
Google Scholar
Devictor V, Clavel J, Julliard R, Lavergne S, Mouillot D, Thuiller W, et al. Defining and measuring ecological specialization. J Appl Ecol. 2010;47:15–25.
Google Scholar
Pereira FC, Berry D. Microbial nutrient niches in the gut. Environ Microbiol. 2017;19:1366–78.
Google Scholar
Shakya M, Lo C-C, Chain PSG. Advances and challenges in metatranscriptomic analysis. Front Genet. 2019;10:904.
Google Scholar
Berry D, Loy A. Stable-Isotope probing of human and animal microbiome function. Trends Microbiol. 2018;26:999–1007.
Google Scholar
Terrado R, Pasulka AL, Lie AA-Y, Orphan VJ, Heidelberg KB, Caron DA. Autotrophic and heterotrophic acquisition of carbon and nitrogen by a mixotrophic chrysophyte established through stable isotope analysis. ISME J. 2017;11:2022–34.
Google Scholar
Dekas AE, Parada AE, Mayali X, Fuhrman JA, Wollard J, Weber PK, et al. Characterizing Chemoautotrophy and Heterotrophy in Marine Archaea and Bacteria With Single-Cell Multi-isotope NanoSIP. Front Microbiol. 2019;10:2682.
Google Scholar
Wegener G, Bausch M, Holler T, Thang NM, Mollar XP, Kellermann MY, et al. Assessing sub-seafloor microbial activity by combined stable isotope probing with deuterated water and 13C-bicarbonate. Environ Microbiol. 2019;14:1517–27
Jing X, Gou H, Gong Y, Su X, Xu L, Ji Y, et al. Raman-activated cell sorting and metagenomic sequencing revealing carbon-fixing bacteria in the ocean. Environ Microbiol. 2018;20:2241–55.
Google Scholar
Xu J, Zhu D, Ibrahim AD, Allen CCR, Gibson CM, Fowler PW, et al. Raman deuterium isotope probing reveals microbial metabolism at the single-cell level. Anal Chem. 2017;89:13305–12.
Google Scholar
Zhang M, Hong W, Abutaleb NS, Li J, Dong P-T, Zong C, et al. Rapid determination of antimicrobial susceptibility by stimulated Raman scattering imaging of D2O metabolic incorporation in a single bacterium. Adv Chem Microsc Life Sci Transl Med. 2021.
Lima C, Muhamadali H, Xu Y, Kansiz M, Goodacre R. Imaging Isotopically Labeled Bacteria at the Single-Cell Level Using High-Resolution Optical Infrared Photothermal Spectroscopy. Anal Chem. 2021;93:3082–8.
Google Scholar
Ackermann M. A functional perspective on phenotypic heterogeneity in microorganisms. Nat Rev Microbiol. 2015;13:497–508.
Google Scholar
Balaban NQ, Merrin J, Chait R, Kowalik L, Leibler S. Bacterial persistence as a phenotypic switch. Science. 2004;305:1622–5.
Google Scholar
Maamar H, Raj A, Dubnau D. Noise in gene expression determines cell fate in Bacillus subtilis. Science. 2007;317:526–9.
Google Scholar
Emonet T, Cluzel P. Relationship between cellular response and behavioral variability in bacterial chemotaxis. Proc Natl Acad Sci USA. 2008;105:3304–9.
Google Scholar
Ozbudak EM, Thattai M, Lim HN, Shraiman BI, Van Oudenaarden A. Multistability in the lactose utilization network of Escherichia coli. Nature. 2004;427:737–40.
Google Scholar
Kiviet DJ, Nghe P, Walker N, Boulineau S, Sunderlikova V, Tans SJ. Stochasticity of metabolism and growth at the single-cell level. Nature. 2014;514:376–9.
Google Scholar
Kotte O, Volkmer B, Radzikowski JL, Heinemann M. Phenotypic bistability in Escherichia coli’s central carbon metabolism. Mol Syst Biol. 2014;10:736.
Google Scholar
New AM, Cerulus B, Govers SK, Perez-Samper G, Zhu B, Boogmans S, et al. Different levels of catabolite repression optimize growth in stable and variable environments. PLoS Biol. 2014;12:e1001764.
Google Scholar
Solopova A, van Gestel J, Weissing FJ, Bachmann H, Teusink B, Kok J, et al. Bet-hedging during bacterial diauxic shift. Proc Natl Acad Sci USA. 2014;111:7427–32.
Google Scholar
Schreiber F, Littmann S, Lavik G, Escrig S, Meibom A, Kuypers MMM, et al. Phenotypic heterogeneity driven by nutrient limitation promotes growth in fluctuating environments. Nat Microbiol. 2016;1:16055.
Google Scholar
Nikolic N, Schreiber F, Dal Co A, Kiviet DJ, Bergmiller T, Littmann S, et al. Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genet. 2017;13:e1007122.
Google Scholar
Takhaveev V, Heinemann M. Metabolic heterogeneity in clonal microbial populations. Curr Opin Microbiol. 2018;45:30–8.
Google Scholar
Altschuler SJ, Wu LF. Cellular heterogeneity: do differences make a difference? Cell. 2010;141:559–63.
Google Scholar
Beaumont HJE, Gallie J, Kost C, Ferguson GC, Rainey PB. Experimental evolution of bet hedging. Nature. 2009;462:90–3.
Google Scholar
Calabrese F, Voloshynovska I, Musat F, Thullner M, Schlömann M, Richnow HH, et al. Quantitation and comparison of phenotypic heterogeneity among single cells of monoclonal microbial populations. Front Microbiol. 2019;10:2814.
Google Scholar
Zimmermann M, Escrig S, Hübschmann T, Kirf MK, Brand A, Inglis RF, et al. Phenotypic heterogeneity in metabolic traits among single cells of a rare bacterial species in its natural environment quantified with a combination of flow cell sorting and NanoSIMS. Front Microbiol. 2015;6:243.
Google Scholar
Zimmermann M, Escrig S, Lavik G, Kuypers MMM, Meibom A, Ackermann M, et al. Substrate and electron donor limitation induce phenotypic heterogeneity in different metabolic activities in a green sulphur bacterium. Environ Microbiol Rep. 2018;10:179–83.
Google Scholar
Sheik AR, Muller EE, Audinot J-N, Lebrun LA, Grysan P, Guignard C, et al. In situ phenotypic heterogeneity among single cells of the filamentous bacterium Candidatus Microthrix parvicella. ISME J. 2016;10:1274–9.
Google Scholar
Seyedsayamdost MR, Case RJ, Kolter R, Clardy J. The Jekyll-and-Hyde chemistry of Phaeobacter gallaeciensis. Nat Chem. 2011;3:331–5.
Google Scholar
Ferrier-Pagès C, Leal MC. Stable isotopes as tracers of trophic interactions in marine mutualistic symbioses. Ecol Evol. 2019;9:723–40.
Google Scholar
Pasulka AL, Thamatrakoln K, Kopf SH, Guan Y, Poulos B, Moradian A, et al. Interrogating marine virus-host interactions and elemental transfer with BONCAT and nanoSIMS-based methods. Environ Microbiol. 2018;20:671–92.
Google Scholar
Kopp C, Domart-Coulon I, Escrig S, Humbel BM, Hignette M, Meibom A. Subcellular investigation of photosynthesis-driven carbon assimilation in the symbiotic reef coral Pocillopora damicornis. mBio. 2015;6:e02299–14.
Google Scholar
Rädecker N, Pogoreutz C, Gegner HM, Cárdenas A, Roth F, Bougoure J, et al. Heat stress destabilizes symbiotic nutrient cycling in corals. Proc Natl Acad Sci U S A. 2021;118:e2022653118.
Google Scholar
Krueger T, Bodin J, Horwitz N, Loussert-Fonta C, Sakr A, Escrig S, et al. Temperature and feeding induce tissue level changes in autotrophic and heterotrophic nutrient allocation in the coral symbiosis – a NanoSIMS study. Sci Rep. 2018;8:12710.
Google Scholar
Gibbin E, Gavish A, Krueger T, Kramarsky-Winter E, Shapiro O, Guiet R, et al. Vibrio coralliilyticus infection triggers a behavioural response and perturbs nutritional exchange and tissue integrity in a symbiotic coral. ISME J. 2019;13:989–1003.
Google Scholar
Rix L, Ribes M, Coma R, Jahn MT, de Goeij JM, van Oevelen D, et al. Heterotrophy in the earliest gut: a single-cell view of heterotrophic carbon and nitrogen assimilation in sponge-microbe symbioses. ISME J. 2020;14:2554–67.
Google Scholar
Thomas T, Moitinho-Silva L, Lurgi M, Björk JR, Easson C, Astudillo-García C, et al. Diversity, structure and convergent evolution of the global sponge microbiome. Nat Commun. 2016;7:11870.
Google Scholar
Mills MM, Turk-Kubo KA, van Dijken GL, Henke BA, Harding K, Wilson ST, et al. Unusual marine cyanobacteria/haptophyte symbiosis relies on N2 fixation even in N-rich environments. ISME J. 2020;14:2395–406.
Google Scholar
Turk-Kubo KA, Mills MM, Arrigo KR, van Dijken G, Henke BA, Stewart B, et al. UCYN-A/haptophyte symbioses dominate N2 fixation in the Southern California Current System. ISME Commun. 2021;1:1–13.
Google Scholar
Moore CM, Mills MM, Arrigo KR, Berman-Frank I, Bopp L, Boyd PW, et al. Processes and patterns of oceanic nutrient limitation. Nat Geosci. 2013;6:701–10.
Google Scholar
Scheller S, Yu H, Chadwick GL, McGlynn SE, Orphan VJ. Artificial electron acceptors decouple archaeal methane oxidation from sulfate reduction. Science. 2016;351:703–7.
Google Scholar
Pereira FC, Wasmund K, Cobankovic I, Jehmlich N, Herbold CW, Lee KS, et al. Rational design of a microbial consortium of mucosal sugar utilizers reduces Clostridiodes difficile colonization. Nat Commun. 2020;11:5104.
Google Scholar
Mooshammer M, Kitzinger K, Schintlmeister A, Ahmerkamp S, Nielsen JL, Nielsen PH, et al. Flow-through stable isotope probing (Flow-SIP) minimizes cross-feeding in complex microbial communities. ISME J. 2021;15:348–53.
Google Scholar
Drescher K, Nadell CD, Stone HA, Wingreen NS, Bassler BL. Solutions to the public goods dilemma in bacterial biofilms. Curr Biol. 2014;24:50–5.
Google Scholar
Słomka J, Alcolombri U, Secchi E, Stocker R, Fernandez VI. Encounter rates between bacteria and small sinking particles. New J Phys. 2020;22:043016.
Google Scholar
Alcolombri U, Peaudecerf FJ, Fernandez VI, Behrendt L, Lee KS, Stocker R. Sinking enhances the degradation of organic particles by marine bacteria. Nat Geosci. 2021;14:775–80.
Google Scholar
University of Massachusetts Amherst Massachusetts Lynn Margulis, Margulis L, Fester R. Symbiosis as a source of evolutionary innovation: speciation and morphogenesis. MIT Press; 1991. 454 p.
Legin AA, Schintlmeister A, Sommerfeld NS, Eckhard M, Theiner S, Reipert S, et al. Nano-scale imaging of dual stable isotope labeled oxaliplatin in human colon cancer cells reveals the nucleolus as a putative node for therapeutic effect. Nanoscale Adv. 2021;3:249–62.
Google Scholar
Schaible GA, et al. Correlative SIP-FISH-Raman-SEM-NanoSIMS links identity, morphology, biochemistry, and physiology of environmental microbes. ISME COMMUN. 2022;2:52.
Google Scholar
Yu G-H, Chi Z-L, Kappler A, Sun F-S, Liu C-Q, Teng HH, et al. Fungal nanophase particles catalyze iron transformation for oxidative stress removal and iron acquisition. Curr Biol. 2020;30:2943–50.e4.
Google Scholar
Subirana MA, Riemschneider S, Hause G, Dobritzsch D, Schaumlöffel D, Herzberg M. High spatial resolution imaging of subcellular macro and trace element distribution during phagocytosis. Metallomics. 2022;14:mfac011.
Google Scholar
Bonnin EA, Fornasiero EF, Lange F, Turck CW, Rizzoli SO. NanoSIMS observations of mouse retinal cells reveal strict metabolic controls on nitrogen turnover. BMC Mol Cell Biol. 2021;22:5.
Google Scholar
Jo MC, Liu W, Gu L, Dang W, Qin L. High-throughput analysis of yeast replicative aging using a microfluidic system. Proc Natl Acad Sci U S A. 2015;112:9364–9.
Google Scholar
Anggraini D, Ota N, Shen Y, Tang T, Tanaka Y, Hosokawa Y, et al. Recent advances in microfluidic devices for single-cell cultivation: methods and applications. Lab Chip. 2022;22:1438–68.
Google Scholar
Eriksen R, Daria V, Gluckstad J. Fully dynamic multiple-beam optical tweezers. Opt Express. 2002;10:597–602.
Google Scholar
Dai X, Fu W, Chi H, Mesias VSD, Zhu H, Leung CW, et al. Optical tweezers-controlled hotspot for sensitive and reproducible surface-enhanced Raman spectroscopy characterization of native protein structures. Nat Commun. 2021;12:1292.
Google Scholar
Collins DJ, Morahan B, Garcia-Bustos J, Doerig C, Plebanski M, Neild A. Two-dimensional single-cell patterning with one cell per well driven by surface acoustic waves. Nat Commun. 2015;6:8686.
Google Scholar
Hu F, Shi L, Min W. Biological imaging of chemical bonds by stimulated Raman scattering microscopy. Nat Methods. 2019;16:830–42.
Google Scholar
Ge X, Pereira FC, Mitteregger M, Berry D, Zhang M, Hausmann B, et al. SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level. Proc Natl Acad Sci U S A. 2022;119:e2203519119.
Google Scholar
Vandergrift GW, Kew W, Lukowski JK, Bhattacharjee A, Liyu AV, Shank EA, et al. Imaging and direct sampling capabilities of nanospray desorption electrospray ionization with absorption-mode 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry. Anal Chem. 2022;94:3629–36.
Google Scholar
Harrison JP, Berry D. Vibrational spectroscopy for imaging single microbial cells in complex biological samples. Front Microbiol. 2017;8:675.
Google Scholar
Mayali X. NanoSIMS: microscale quantification of biogeochemical activity with large-scale impacts. Ann Rev Mar Sci. 2020;12:449–67.
Google Scholar
Alexandrov T. Spatial metabolomics and imaging mass spectrometry in the age of artificial intelligence. Annu Rev Biomed Data Sci. 2020;3:61–87.
Google Scholar
Boschker HTS, Middelburg JJ. Stable isotopes and biomarkers in microbial ecology. FEMS Microbiol Ecol. 2002;40:85–95.
Google Scholar
Mayali X, Weber PK, Nuccio E, Lietard J, Somoza M, Blazewicz SJ, et al. Chip-SIP: Stable Isotope Probing analyzed with rRNA-targeted microarrays and nanoSIMS. Methods Mol Biol. 2019;2046:71–87.
Google Scholar
Chokkathukalam A, Kim D-H, Barrett MP, Breitling R, Creek DJ. Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks. Bioanalysis. 2014;6:511–24.
Google Scholar
Hiller K, Metallo CM, Kelleher JK, Stephanopoulos G. Nontargeted elucidation of metabolic pathways using stable-isotope tracers and mass spectrometry. Anal Chem. 2010;82:6621–8.
Google Scholar
Rusconi R, Garren M, Stocker R. Microfluidics expanding the frontiers of microbial ecology. Annu Rev Biophys. 2014;43:65–91.
Google Scholar
Lee KS, Pereira FC, Palatinszky M, Behrendt L, Alcolombri U, Berry D, et al. Optofluidic Raman-activated cell sorting for targeted genome retrieval or cultivation of microbial cells with specific functions. Nat Protoc. 2021;16:634–76.
Google Scholar
Wagner M, Haider S. New trends in fluorescence in situ hybridization for identification and functional analyses of microbes. Curr Opin Biotechnol. 2012;23:96–102.
Google Scholar
Source: Ecology - nature.com
