Abstract
Technological advances over the past 30 years have led to the improvement of existing and the development of new analytical techniques, which have very high sensitivity and/or spatial-temporal resolution. Moreover, many of them can be implemented on commercially available devices. All this has created the conditions for obtaining fundamentally new quantitative information about the physical and chemical properties of single cells of various origins, including such tiny ones as yeasts and bacteria, the size of which can be about 0.5 μm. A basic toolbox of methods that is used in microbiology for research at the level of single cells includes flow and laser scanning cytometry, optical microscopy coupled with computer image analysis, scanning probe microscopy, vibrational spectroscopy, nanoscale secondary ion mass spectrometry, and some of their variations. The studies using quantitative analytical methods of single cells of microorganisms have opened up prospects for solving such problems as genotypic and phenotypic heterogeneity of microbial populations, the nature of unculturable and persistent forms, the development of biofilms, the interaction of microbial pathogens and host cells, the relationship of structure and function in the metabolism, and others.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abucayon E, Ke N, Cornut R, Patelunas A et al (2014) Investigating catalase activity through hydrogen peroxide decomposition by bacteria biofilms in real time using scanning electrochemical microscopy. Anal Chem 86(1):498–505. https://doi.org/10.1021/ac402475m
Akamatsu M, Lin Y, Bewersdorf J, Pollard TD (2017) Analysis of interphase node proteins in fission yeast by quantitative and superresolution fluorescence microscopy. Mol Biol Cell 28(23):3203–3214. https://doi.org/10.1091/mbc.E16-07-0522
Altinoglu I, Merrifield CJ, Yamaichi Y (2019) Single molecule super-resolution imaging of bacterial cell pole proteins with high-throughput quantitative analysis pipeline. Sci Rep 9:6680. https://doi.org/10.1038/s41598-019-43051-7
Ambriz-Aviña V, Contreras-Garduño JA, Pedraza-Reyes M (2014) Applications of flow cytometry to characterize bacterial physiological responses. Biomed Res Int 2014:461941. https://doi.org/10.1155/2014/461941
Angeloni L, Passeri D, Reggente M et al (2016) Microbial cells force spectroscopy by atomic force microscopy: a review. Nanosci Nanometrol 2(1):30–40. https://doi.org/10.11648/j.nsnm.20160201.13
Arasada R, Sayyad WA, Berro J, Pollard TD (2018) High-speed superresolution imaging of the proteins in fission yeast clathrin-mediated endocytic actin patches. Mol Biol Cell 29(3):295–303. https://doi.org/10.1091/mbc.E17-06-0415
Avery SV (2006) Microbial cell individuality and the underlying sources of heterogeneity. Nat Rev Microbiol 4(8):577–587
Ball DA, Mehta GD, Salomon-Kent R, Mazza D, Morisaki T, Mueller F, McNally JG, Karpova TS (2016) Single molecule tracking of Ace1p in Saccharomyces cerevisiae defines a characteristic residence time for non-specific interactions of transcription factors with chromatin. Nucleic Acids Res 44(21):e160
Balomenos AD, Tsakanikas P, Aspridou Z et al (2017) Image analysis driven single-cell analytics for systems microbiology. BMC Syst Biol 11(1):43. https://doi.org/10.1186/s12918-017-0399-z
Barteneva NS, Fasler-Kan E, Vorobjev IA (2012) Imaging flow cytometry: coping with heterogeneity in biological systems. J Histochem Cytochem 60(10):723–733
Baudart J, Olaizola A, Coallier J et al (2005) Assessment of a new technique combining a viability test, whole-cell hybridization and laser-scanning cytometry for the direct counting of viable Enterobacteriaceae cells in drinking water. FEMS Microbiol Lett 243(2):405–409
Behrens S, Kappler A, Obst M (2012) Linking environmental processes to the in situ functioning of microorganisms by high-resolution secondary ion mass spectrometry (NanoSIMS) and scanning transmission X-ray microscopy (STXM). Environ Microbiol 14(11):2851–2869. https://doi.org/10.1111/j.1462-2920.2012.02724.x
Bestul AJ, Yu Z, Unruh JR, Jaspersen SL (2017) Molecular model of fission yeast centrosome assembly determined by superresolution imaging. J Cell Biol 216(8):2409–2424. https://doi.org/10.1083/jcb.201701041
Bhushan B, Marti O (2011) Scanning probe microscopy – principle of operation, instrumentation and probes. In: Bhushan B (ed) Nanotribology and nanomechanics. Springer, Berlin/Heidelberg, pp 37–110. https://doi.org/10.1007/978-3-642-15283-2_2
Bjerling P, Olsson I, Meng X (2012) Quantitative live cell fluorescence-microscopy analysis of fission yeast. J Vis Exp 59:e3454. https://doi.org/10.3791/3454
Brehm-Stecher BF, Johnson EA (2004) Single-cell microbiology: tools, technologies, and applications. Microbiol Mol Biol Rev 68(3):538–559
Burns S, Avena JS, Unruh JR, Yu Z, Smith SE, Slaughter BD, Winey M, Jaspersen SL (2015) Structured illumination with particle averaging reveals novel roles for yeast centrosome components during duplication.eLife 4:e08586. https://doi.org/10.7554/eLife.08586
Calvert ME, Lannigan JA, Pemberton LF (2008) Optimization of yeast cell cycle analysis and morphological characterization by multispectral imaging flow cytometry. Cytometry A 73(9):825–833. https://doi.org/10.1002/cyto.a.20609
Chen S-C, Zhao T, Gordon GJ et al (2007) Automated image analysis of protein localization in budding yeast. Bioinformatics 23:i66–i71. https://doi.org/10.1093/bioinformatics/btm206
Chen CH, Cho SH, Chiang HI et al (2011) Specific sorting of single bacterial cells with microfabricated fluorescence-activated cell sorting and tyramide signal amplification fluorescence in situ hybridization. Anal Chem 83(19):7269–7275. https://doi.org/10.1021/ac2013465
Chen J, McSwiggen D, Ünal E (2018) Single molecule fluorescence in situ hybridization (smFISH) analysis in budding yeast vegetative growth and meiosis. J Vis Exp 135:e57774. https://doi.org/10.3791/57774.
Choi H, Rangarajan N, Weisshaar JC (2016) Lights, camera, action! Antimicrobial peptide mechanisms imaged in space and time. Trends Microbiol 24(2):111–122. https://doi.org/10.1016/j.tim.2015.11.004
Chong YT, Cox MJ, Andrews B (2012) Proteome-wide screens in Saccharomyces cerevisiae using the yeast GFP collection. Adv Exp Med Biol 736:169–178. https://doi.org/10.1007/978-1-4419-7210-1_8
Chozinski TJ, Gagnon LA, Vaughan JC (2014) Twinkle, twinkle little star: photoswitchable fluorophores for super-resolution imaging. FEBS Lett 588(19):3603–3612. https://doi.org/10.1016/j.febslet.2014.06.043
Coltharp C, Xiao J (2012) Superresolution microscopy for microbiology. Cell Microbiol 14(12):1808–1818
Connella JL, Kimb J, Shearb JB et al (2014) Real-time monitoring of quorum sensing in 3D-printed bacterial aggregates using scanning electrochemical microscopy. Proc Natl Acad Sci U S A 111(551):18255–18260. https://doi.org/10.1073/pnas.1421211111
Cortesi M, Bandiera L, Pasini A et al (2017) Reliable measurement of E. coli single cell fluorescence distribution using a standard microscope set-up. J Biol Eng 11:8. https://doi.org/10.1186/s13036-017-0050-y
Dashkova V, Malashenkov D, Poulton N et al (2017) Imaging flow cytometry for phytoplankton analysis. Methods 112:188–200. https://doi.org/10.1016/j.ymeth.2016.05.007
Dawson KS, Scheller S, Dillon JG et al (2016) Stable isotope phenotyping via cluster analysis of NanoSIMS data as a method for characterizing distinct microbial ecophysiologies and sulfur-cycling in the environment. Front Microbiol 7:774. https://doi.org/10.3389/fmicb.2016.00774
Dazzo FB, Niccum BC (2015) Use of CMEIAS image analysis software to accurately compute attributes of cell size, morphology, spatial aggregation and color segmentation that signify in situ ecophysiological adaptations in microbial biofilm communities. Computation 3:72–98
Dazzo FB, Sexton R, Jain A et al (2017) Influence of substratum hydrophobicity on the geomicrobiology of river biofilm architecture and ecology analyzed by CMEIAS bioimage informatics. Geosciences 7(56):1–36. https://doi.org/10.3390/geosciences7030056
Dekel E, Rivkin A, Heidenreich M et al (2017) Identification and classification of the malaria parasite blood developmental stages, using imaging flow cytometry. Methods 112:157–166. https://doi.org/10.1016/j.ymeth.2016.06.021
Domke KF, Pettinger B (2010) Studying surface chemistry beyond the diffraction limit: 10 years of TERS. ChemPhysChem 11(7):1365–1373. https://doi.org/10.1002/cphc.200900975
Dorobantu LS, Goss GG, Burrell RE (2012) Atomic force microscopy: a nanoscopic view of microbial cell surfaces. Micron 43(12):1312–1322. https://doi.org/10.1016/j.micron.2012.05.005
Drechsler-Hake D, Alamir H, Hahn J et al (2016) Mononuclear phagocytes contribute to intestinal invasion and dissemination of Yersinia enterocolitica. Int J Med Microbiol 306(6):357–366. https://doi.org/10.1016/j.ijmm.2016.04.002
Dufrêne YF (2014) Atomic force microscopy in microbiology: new structural and functional insights into the microbial cell surface. MBio 5(4):e01363–e01314. https://doi.org/10.1128/mBio.01363-14
Emerson JB, Adams RI, Román CMB et al (2017) Schrödinger’s microbes: tools for distinguishing the living from the dead in microbial ecosystems. Microbiome 5(10):86. https://doi.org/10.1186/s40168-017-0285-3
Endesfelder U (2019) From single bacterial cell imaging towards in vivo single-molecule biochemistry studies. Essays Biochem 63(2):187–196. https://doi.org/10.1042/EBC20190002
Femino AM, Fay FS, Fogarty K, Singer RH (1998) Visualization of single RNA transcripts in situ. Science 280(5363):585–590
Ferraro J, Nakamoto K, Brown CW (2003) Introductory Raman spectroscopy, 2nd edn. Elsevier, San Diego
Flynn JD, Haas BL, Biteen JS (2016) Plasmon-enhanced fluorescence from single proteins in living bacteria. J Phys Chem C 120(37):20512–20517. https://doi.org/10.1021/acs.jpcc.5b08049
Gahlmann A, Moerner WE (2014) Exploring bacterial cell biology with single-molecule tracking and super-resolution imaging. Nat Rev Microbiol 12(1):9–22. https://doi.org/10.1038/nrmicro3154
Gangan MS, Athale CA (2017) Threshold effect of growth rate on population variability of Escherichia coli cell lengths. R Soc Open Sci 4(2):160417. https://doi.org/10.1098/rsos.160417
Gao L, Smith RT (2015) Optical hyperspectral imaging in microscopy and spectroscopy - a review of data acquisition. J Biophotonics 8(6):441–456. https://doi.org/10.1002/jbio.201400051
Gao D, Huang X, Tao Y (2016) A critical review of NanoSIMS in analysis of microbial metabolic activities at single-cell level. Crit Rev Biotechnol 36(5):884–890. https://doi.org/10.3109/07388551.2015.1057550
Gebre A, Okada H, Kim C et al (2015) Profiling of the effects of antifungal agents on yeast cells based on morphometric analysis. FEMS Yeast Res 15(5):fov040. https://doi.org/10.1093/femsyr/fov040
Große C, Bergner N, Dellith J et al (2015) Label-free imaging and spectroscopic analysis of intracellular bacterial infections. Anal Chem 87(4):2137–2142. https://doi.org/10.1021/ac503316s
Haas BL, Matson JS, DiRita VJ, Biteen JS (2014) Imaging live cells at the nanometer-scale with single-molecule microscopy: obstacles and achievements in experiment optimization for microbiology. Molecules 19(8):12116–12149. https://doi.org/10.3390/molecules190812116
Hagen N, Kudenov MW (2003) Review of snapshot spectral imaging technologies. Opt Eng 52(9):090901
Han J, Kamber M, Pei J (2011) Data mining: concepts and techniques, 3rd edn. Elsevier, Amsterdam
Haridas V, Ranjbar S, Vorobjev IA et al (2017) Imaging flow cytometry analysis of intracellular pathogens. Methods 112:91–104. https://doi.org/10.1016/j.ymeth.2016.09.007
Harrison JP, Berry D (2017) Vibrational spectroscopy for imaging single microbial cells in complex biological samples. Front Microbiol 8:675. https://doi.org/10.3389/fmicb.2017.00675
Harz M, Rösch P, Popp J (2009) Vibrational spectroscopy – a powerful tool for the rapid identification of microbial cells at the single-cell level. Cytometry A 75(20):104–113. https://doi.org/10.1002/cyto.a.20682
Hennig H, Rees P, Blasi T et al (2017) An open-source solution for advanced imaging flow cytometry data analysis using machine learning. Methods 112:201–210. https://doi.org/10.1016/j.ymeth.2016.08.018
Herman-Bausier P, Formosa-Dague C, Feuillie C et al (2017) Forces guiding staphylococcal adhesion. J Struct Biol 197(1):65–69. https://doi.org/10.1016/j.jsb.2015.12.009
Herzenberg LA, Parks D, Sahaf B et al (2002) The history and future of the fluorescence activated cell sorter and flow cytometry: a view from Stanford. Clin Chem 48(10):1819–1827
Ho SH, Tirrell DA (2019) Enzymatic labeling of bacterial proteins for super-resolution imaging in live cells. ACS Central Sci 5(12):1911–1919. https://doi.org/10.1021/acscentsci.9b00617
Huang F, Hartwich TM, Rivera-Molina FE, Lin Y, Duim WC, Long JJ, Uchil PD, Myers JR, Baird MA, Mothes W, Davidson MW, Toomre D, Bewersdorf J (2013) Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms. Nat Methods 10(7):653–658. https://doi.org/10.1038/nmeth.2488
Huang Q, Wu H, Cai P et al (2015) Atomic force microscopy measurements of bacterial adhesion and biofilm formation onto clay-sized particles. Sci Rep 5:16857. https://doi.org/10.1038/srep16857
Ishii S, Tago K, Senoo K (2010) Single-cell analysis and isolation for microbiology and biotechnology: methods and applications. Appl Microbiol Biotechnol 86(5):1281–1292. https://doi.org/10.1007/s00253-010-2524-4
James SA, Hilal N, Wright CJ (2017) Atomic force microscopy studies of bioprocess engineering surfaces – imaging, interactions and mechanical properties mediating bacterial adhesion. Biotechnol J 12:7. https://doi.org/10.1002/biot.201600698
Kamentsky LA, Kamentsky LD (1991) Microscope-based multiparameter laser scanning cytometer yielding data comparable to flow cytometry data. Cytometry 12(5):381–387
Kan A (2017) Machine learning applications in cell image analysis. Immunol Cell Biol 95(6):525–530. https://doi.org/10.1038/icb.2017.16
Kao HP, Verkman AS (1994) Tracking of single fluorescent particles in three dimensions: use of cylindrical optics to encode particle position. Biophys J 67(3):1291–1300. https://doi.org/10.1016/S0006-3495(94)80601-0
Kentner D, Sourjik V (2010) Use of fluorescence microscopy to study intracellular signaling in bacteria. Annu Rev Microbiol 64:373–390. https://doi.org/10.1146/annurev.micro.112408.134205
Koley D, Ramsey MM, Bard AJ et al (2011) Discovery of a biofilm electrocline using real-time 3D metabolite analysis. Proc Natl Acad Sci U S A 108(50):19996–20001. https://doi.org/10.1073/pnas.1117298108
Kopf SH, Sessions AL, Cowley ES et al (2016) Trace incorporation of heavy water reveals slow and heterogeneous pathogen growth rates in cystic fibrosis sputum. Proc Natl Acad Sci U S A 113(2):E110–E116. https://doi.org/10.1073/pnas.1512057112
Lakowicz JR (2006) Principles of fluorescence spectroscopy, 3rd edn. Springer Science and Business Media, Berlin. https://doi.org/10.1007/978-0-387-46312-4
Laplante C, Huang F, Tebbs IR, Bewersdorf J, Pollard TD (2016) Molecular organization of cytokinesis nodes and contractile rings by super-resolution fluorescence microscopy of live fission yeast. Proc Natl Acad Sci U S A 113(40):E5876–E5885
Li G, Neuert G (2019) Multiplex RNA single molecule FISH of inducible mRNAs in single yeast cells. Sci Data 6(1):94. https://doi.org/10.1038/s41597-019-0106-6.
Li M, Xu J, Romero-Gonzalez M et al (2012) Single cell Raman spectroscopy for cell sorting and imaging. Curr Opin Biotechnol 23:56–63
Liu X, Ramseyb MM, Chena X et al (2011a) Real-time mapping of a hydrogen peroxide concentration profile across a polymicrobial bacterial biofilm using scanning electrochemical microscopy. Proc Natl Acad Sci U S A 108(7):72668–72673. https://doi.org/10.1073/pnas.1018391108
Liu Y, Aubrey W, Martin K et al (2011b) The analysis of yeast cell morphology features in exponential and stationary phase. J Biol Syst 19:561–575. https://doi.org/10.1142/S0218339011003968
Liu C, Liu YL, Perillo EP, Dunn AK, Yeh HC (2016) Single-molecule tracking and its application in biomolecular binding detection. IEEE J Sel Top Quantum Electron 22(4):6804013
Lower SK (2011) Atomic force microscopy to study intermolecular forces and bonds associated with bacteria. Adv Exp Med Biol 715:285–299. https://doi.org/10.1007/978-94-007-0940-9_18
Lu X, Al-Qadiri HM, Lin M et al (2011) Application of mid-infrared and Raman spectroscopy to the study of bacteria. Food Bioprocess Technol 4:919–935. https://doi.org/10.1007/s11947-011-0516-8
McIlvenna D, Huang WE, Davison P et al (2016) Continuous cell sorting in a flow based on single cell resonance Raman spectra. Lab Chip 16(8):1420–1429. https://doi.org/10.1039/c6lc00251j
Minoshima M, Kikuchi K (2017) Photostable and photoswitching fluorescent dyes for super-resolution imaging. J Biol Inorg Chem 22(5):639–652. https://doi.org/10.1007/s00775-016-1435-y
Mulvihill DP (2017) Live cell imaging in fission yeast. Cold Spring Harb Protoc 2017(10):pdb.top090621. https://doi.org/10.1101/pdb.top090621
Musat N, Halm H, Winterholler B et al (2008) A single-cell view on the ecophysiology of anaerobic phototrophic bacteria. Proc Natl Acad Sci U S A 105(46):17861–17866. https://doi.org/10.1073/pnas.0809329105
Musat N, Foster R, Vagner T et al (2012) Detecting metabolic activities in single cells, with emphasis on nanoSIMS. FEMS Microbiol Rev 36(2):486–511. https://doi.org/10.1111/j.1574-6976.2011.00303.x
Musat N, Musat F, Weber PK et al (2016) Tracking microbial interactions with NanoSIMS. Curr Opin Biotechnol 4:114–121. https://doi.org/10.1016/j.copbio.2016.06.007
Negishi T, Nogami S, Ohya Y (2009) Multidimensional quantification of subcellular morphology of Saccharomyces cerevisiae using CalMorph, the high-throughput image-processing program. J Biotechnol 141:109–117. https://doi.org/10.1016/j.jbiotec.2009.03.014
Neugebauer U, Schmid U, Baumann K et al (2007) Towards a detailed understanding of bacterial metabolism – spectroscopic characterization of Staphylococcus epidermidis. ChemPhysChem 8(1):124–137
Niven GW, Fuks T, Morton JS et al (2006) A novel method for measuring lag times in division of individual bacterial cells using image analysis. J Microbiol Methods 65:311–317. https://doi.org/10.1016/j.mimet.2005.08.006
Nketia TA, Sailem H, Rohde G, Machiraju R, Rittscher J (2017) Analysis of live cell images: methods, tools and opportunities. Methods 115:65–79. https://doi.org/10.1016/j.ymeth.2017.02.007
Nogami S, Ohya Y, Yvert G (2007) Genetic complexity and quantitative trait loci mapping of yeast morphological traits. PLoS Genet 3:e31
Nuñez J, Renslow R, Cliff JB 3rd et al (2017) Nano SIMS for biological applications: current practices and analyses. Biointerphases 13(3):03B301. https://doi.org/10.1116/1.4993628
Ogawa M, Tani K, Ochiai N et al (2005) Multicolour digital image analysis system for identification of bacteria and concurrent assessment of their respiratory activity. J Appl Microbiol 98:1101–1106. https://doi.org/10.1111/j.1365-2672.2005.02551.x
Ohtani M, Saka A, Sano F et al (2004) Development of image processing program for yeast cell morphology. J Bioinform Computat Biol 1:695–709. https://doi.org/10.1142/S0219720004000363
Ohya Y, Sese J, Yukawa M et al (2005) High-dimensional and large-scale phenotyping of yeast mutants. Proc Natl Acad Sci U S A 102(52):19015–19020. https://doi.org/10.1073/pnas.0509436102
Okagaki LH, Strain AK, Nielsen JN et al (2010) Cryptococcal cell morphology affects host cell interactions and pathogenicity. PLoS Pathog 6(6):e1000953. https://doi.org/10.1371/annotation/1b59fd9e-9ac9-4ea8-a083-14c413c80b03
Ott W, Jobst MA, Schoeler C et al (2017) Single-molecule force spectroscopy on polyproteins and receptor-ligand complexes: the current toolbox. J Struct Biol 197(1):3–12. https://doi.org/10.1016/j.jsb.2016.02.011
Pahlow S, Meisel S, Cialla-May D et al (2015) Isolation and identification of bacteria by means of Raman spectroscopy. Adv Drug Deliv Rev 89:105–120. https://doi.org/10.1016/j.addr.2015.04.006
Pett-Ridge J, Weber PK (2012) NanoSIP: NanoSIMS applications for microbial biology. Methods Mol Biol 881:375–408. https://doi.org/10.1007/978-1-61779-827-6_13
Phanse Y, Ramer-Tait AE, Friend SL et al (2012) Analyzing cellular internalization of nanoparticles and bacteria by multi-spectral imaging flow cytometry. J Vis Exp 8(64):e3884. https://doi.org/10.3791/3884
Phillips ZF, Chen M, Waller L (2017) Single-shot quantitative phase microscopy with color-multiplexed differential phase contrast (cDPC). PLoS One 12(2):e0171228
Pina-Vaz C, Costa-Oliveira S, Rodrigues AG et al (2004) Novel method using a laser scanning cytometer for detection of mycobacteria in clinical samples. J Clin Microbiol 42(2):906–908
Polisetti S, Bible AN, Morrell-Falvey JL et al (2016) Raman chemical imaging of the rhizosphere bacterium Pantoea sp. YR343 and its co-culture with Arabidopsis thaliana. Analyst 141:2175–2182. https://doi.org/10.1039/c6an00080k
Pozarowski P, Holden E, Darzynkiewicz Z (2013) Laser scanning cytometry: principles and applications-an update. Methods Mol Biol 931:187–212. https://doi.org/10.1007/978-1-62703-056-4_11
Puchkov EO (2013) Intracellular viscosity: methods of measurement and role in metabolism. Biochemistry (Moscow) Suppl Ser A Membr Cell Biol 7(4):270–279. https://doi.org/10.1134/s1990747813050140
Puchkov EO (2014) Computer image analysis as a tool for microbial viability assessment: examples of use and prospects. J Biosci Med 2:1–6. https://doi.org/10.4236/jbm.2014.23001
Puchkov E (2016a) Image analysis in microbiology: a review. J Comput Commun 4:8–32
Puchkov E (2016b) Microfluorimetry of single yeast cells by fluorescence microscopy combined with digital photography and computer image analysis. In: Berhardt LV (ed) Advances in medicine and biology, vol 98. Nova Science Publishers, New York, pp 69–90
Regina VR, Poulsen M, Søhoel H et al (2012) Quantification of bacteria on abiotic surfaces by laser scanning cytometry: an automated approach to screen the antifouling properties of new surface coatings. J Lab Autom 17(4):293–301. https://doi.org/10.1177/2211068212450013
Saito TL, Ohtani M, Sawai H et al (2004) SCMD: Saccharomyces cerevisiae morphological database. Nucleic Acid Res 32:D319–D322. https://doi.org/10.1093/nar/gkh113
Sanderson MJ, Smith I, Parker I, Bootman MD (2014) Fluorescence microscopy. Cold Spring Harb Protoc 2014(10):pdb.top071795. https://doi.org/10.1101/pdb.top071795
Santos MI, Gerbino E, Tymczyszyn E et al (2015) Applications of infrared and Raman spectroscopies to probiotic investigation. Foods 4(3):283–305. https://doi.org/10.3390/foods4030283
Saurabh S, Perez AM, Comerci CJ, Shapiro L, Moerner WE (2016) Super-resolution imaging of live bacteria cells using a genetically directed, highly photostable fluoromodule. J Am Chem Soc 138(33):10398–10401. https://doi.org/10.1021/jacs.6b05943
Sbalzarini IF (2016) Seeing is believing: quantifying is convincing: computational image analysis in biology. Adv Anat Embryol Cell Biol 219:1–39. https://doi.org/10.1007/978-3-319-28549-8_1.
Schneider JP, Basler M (2016) Shedding light on biology of bacterial cells. Phil Trans R Soc B 371:20150499. https://doi.org/10.1098/rstb.2015.0499
Schulze K, López DA, Tillich UM et al (2011) A simple viability analysis for unicellular cyanobacteria using a new autofluorescence assay, automated microscopy, and image J. BMC Biotechnol 11:118–125. https://doi.org/10.1186/1472-6750-11-118
Shapiro HM (2000) Microbial analysis at the single-cell level: tasks and techniques. J Microbiol Methods 42(1):3–16
Silge A, Abdou E, Schneider K et al (2015) Shedding light on host niches: label-free in situ detection of Mycobacterium gordonae via carotenoids in macrophages by Raman microspectroscopy. Cell Microbiol 17:832–842. https://doi.org/10.1111/cmi.12404
Smirnov A, Solga MD, Lannigan J et al (2017) High-throughput particle uptake analysis by imaging flow cytometry. Curr Protoc Cytom 80:11.22.1–11.22.17. https://doi.org/10.1002/cpcy.19
Snapp E (2005) Design and use of fluorescent fusion proteins in cell biology. Curr Protocols Cell Biol Unit–21.4. https://doi.org/10.1002/0471143030.cb2104s27
Solden L, Lloyd K, Wrighton K (2016) The bright side of microbial dark matter: lessons learned from the uncultivated majority. Curr Opin Microbiol 31:217–226. https://doi.org/10.1016/j.mib.2016.04.020
Song Y, Yin H, Huang WE (2016) Raman activated cell sorting. Curr Opin Chem Biol 33:1–8. https://doi.org/10.1016/j.cbpa.2016.04.002
Song Y, Kaster AK, Vollmers J et al (2017) Single-cell genomics based on Raman sorting reveals novel carotenoid-containing bacteria in the Red Sea. Microb Biotechnol 10(1):125–137. https://doi.org/10.1111/1751-7915.12420
Stagge F, Mitronova GY, Belov VN, Wurm CA, Jakobs S (2013) Snap-, CLIP- and halo-tag labelling of budding yeast cells. PLoS One 8(10):e78745. https://doi.org/10.1371/journal.pone.0078745
Stracy M, Kapanidis AN (2017) Single-molecule and super-resolution imaging of transcription in living bacteria. Methods 120:103–114. https://doi.org/10.1016/j.ymeth.2017.04.001
Stuart BH (2004) Infrared spectroscopy: fundamentals and applications. Wiley, Chichester. https://doi.org/10.1002/0470011149
Sutter M, Faulkner M, Aussignargues C et al (2016) Visualization of bacterial microcompartment facet assembly using high-speed atomic force microscopy. Nano Lett 16(3):1590–1595. https://doi.org/10.1021/acs.nanolett.5b04259
Suzuki G, Sawai H, Ohtani M, Nogami S, Sano-Kumagai F, Saka A, Yukawa M, Saito TL, Sese J, Hirata D, Morishita S, Ohya Y (2006) Evaluation of image processing programs for accurate measurement of budding and fission yeast morphology. Curr Genet 49(4):237–247
Taniguchi Y, Choi PJ, Li GW et al (2010) Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science 329(5991):533–538. https://doi.org/10.1126/science.1188308
Terahara N, Kodera N, Uchihashi T et al (2017) Na+-induced structural transition of MotPS for stator assembly of the Bacillus flagellar motor. Sci Adv 3(11):eaao4119. https://doi.org/10.1126/sciadv.aao4119
Tsien RY (1998) The green fluorescent protein. Annu Rev Biochem 67:509–544
Uphoff S (2016) Super-resolution microscopy and tracking of DNA-binding proteins in bacterial cells. Methods Mol Biol 1431:221–234. https://doi.org/10.1007/978-1-4939-3631-1_16
Van Der Hofstadt M, Hüttener M, Juárez A et al (2015) Nanoscale imaging of the growth and division of bacterial cells on planar substrates with the atomic force microscope. Ultramicroscopy 154:29–36. https://doi.org/10.1016/j.ultramic.2015.02.018
Vanhee LM, D’Haese E, Cools I et al (2010) Detection and quantification of bacteria and fungi using solid-phase cytometry. In: Viola Magni M (ed) Detection of bacteria, viruses, parasites and fungi. NATO science for peace and security series a: chemistry and biology. Springer, Dordrecht, pp 25–41
Wallace CT, Jessup M, Bernas T, Peña KA, Calderon MJ, Loughran PA (2018) Basics of digital microscopy. Curr Protoc Cytom 83:12.2.1–12.2.14. https://doi.org/10.1002/cpcy.31
Wang Y, Hammes F, Boon N et al (2009) Isolation and characterization of low nucleic acid (LNA)-content bacteria. ISME J 3(8):889–902. https://doi.org/10.1038/ismej.46
Wang P, Robert L, Pelletier J et al (2010a) Robust growth of Escherichia coli. Curr Biol 20(12):1099–1103. https://doi.org/10.1016/j.cub.2010.04.045
Wang Y, Hammes F, De Roy K et al (2010b) Past, present and future applications of flow cytometry in aquatic microbiology. Trends Biotechnol 28(8):416–424. https://doi.org/10.1016/j.tibtech.2010.04.006
Wang R, Kamgoue A, Normand C, Léger-Silvestre I, Mangeat T, Gadal O (2016) High resolution microscopy reveals the nuclear shape of budding yeast during cell cycle and in various biological states. J Cell Sci 129(24):4480–4495. https://doi.org/10.1242/jcs.188250
Wang Y, Huang WE, Cui L et al (2016a) Single cell stable isotope probing in microbiology using Raman microspectroscopy. Curr Opin Biotechnol 41:34–42. https://doi.org/10.1016/j.copbio.2016.04.018
Wang Y, Song Y, Tao Y et al (2016b) Reverse and multiple stable isotope probing to study bacterial metabolism and interactions at the single cell level. Anal Chem 88(19):9443–9450
Wollman A, Hedlund EG, Shashkova S, Leake MC (2020) Towards mapping the 3D genome through high speed single-molecule tracking of functional transcription factors in single living cells. Methods 170:82–89. https://doi.org/10.1016/j.ymeth.2019.06.021
Yaginuma H, Kawai S, Tabata KV et al (2014) Diversity in ATP concentrations in a single bacterial cell population revealed by quantitative single-cell imaging. Sci Rep 4:6522. https://doi.org/10.1038/srep06522
Yamaguchi M, Ohkusu M, Biswas SK et al (2007) Cytological study of cell cycle of the pathogenic yeast Cryptococcus neoformans. Nippon Ishinkin Gakkai Zasshi 48(4):147–152
Yao Z, Carballido-López R (2014) Fluorescence imaging for bacterial cell biology: from localization to dynamics, from ensembles to single molecules. Annu Rev Microbiol 68:459–476. https://doi.org/10.1146/annurev-micro-091213-113034
Yu BY, Elbuken C, Ren CL et al (2011) Image processing and classification algorithm for yeast cell morphology in a microfluidic chip. J Biomed Opt 16:066008. https://doi.org/10.1117/1.3589100
Zoski CG (2016) Review–advances in scanning electrochemical microscopy (SECM). J Electrochem Soc 163(4):H3088–H3100. https://doi.org/10.1149/2.0141604jes
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd
About this entry
Cite this entry
Puchkov, E. (2021). Analytical Techniques for Single-Cell Studies in Microbiology. In: Santra, T.S., Tseng, FG. (eds) Handbook of Single Cell Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-10-4857-9_17-3
Download citation
DOI: https://doi.org/10.1007/978-981-10-4857-9_17-3
Received:
Accepted:
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-4857-9
Online ISBN: 978-981-10-4857-9
eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering
Publish with us
Chapter history
-
Latest
Analytical Techniques for Single-Cell Studies in Microbiology- Published:
- 28 October 2020
DOI: https://doi.org/10.1007/978-981-10-4857-9_17-3
-
Analytical Techniques for Single-Cell Studies in Microbiology
- Published:
- 02 July 2019
DOI: https://doi.org/10.1007/978-981-10-4857-9_17-2
-
Original
Analytical Techniques for Single-Cell Studies in Microbiology- Published:
- 26 March 2019
DOI: https://doi.org/10.1007/978-981-10-4857-9_17-1