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Lipidomic profiling of single mammalian cells by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)

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Abstract

To better understand cell-to-cell heterogeneity, advanced analytical tools are in a growing demand for elucidating chemical compositions of each cell within a population. However, the progress of single-cell chemical analysis has been restrained by the limitations of small cell volumes and minute cellular concentrations. Here, we present a rapid and sensitive method for investigating the lipid profiles of isolated single cells using infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS). In this work, HeLa cells were dispersed onto a glass slide, and the cellular contents were ionized by IR-MALDESI and measured using a Q-Exactive HF-X mass spectrometer. Importantly, this approach does not require extraction and/or enrichment of analytes prior to MS analysis. Using this approach, 45 distinct lipid species, predominantly phospholipids, were detected and putatively annotated from the single HeLa cells. The proof-of-concept study demonstrates the feasibility and efficacy of IR-MALDESI-MS for rapid lipidomic profiling of single cells, which provides an important basis for future work on differentiation between normal and diseased cells at various developmental states, which can offer new insights into cellular metabolic pathways and pathological processes. Although not yet accomplished, we believe this approach can be readily used as an assessment tool to compare the number of identified species during source evolution and method optimization (intra-laboratory), and also disclose the complementary nature of different direct analytical approaches for the coverage of different types of endogenous analytes (inter-laboratory).

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References

  1. Comi TJ, Do TD, Rubakhin SS, Sweedler JV. Categorizing cells on the basis of their chemical profiles: progress in single-cell mass spectrometry. J Am Chem Soc. 2017;139:3920–9. https://doi.org/10.1021/jacs.6b12822.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Collins CA, Olsen I, Zammit PS, Heslop L, Petrie A, Partridge TA, et al. Stem cell function, self-renewal, and behavioral heterogeneity of cells from the adult muscle satellite cell niche. Cell. 2005;122:289–301. https://doi.org/10.1016/j.cell.2005.05.010.

    Article  PubMed  CAS  Google Scholar 

  3. Meacham CE, Morrison SJ. Tumour heterogeneity and cancer cell plasticity. Nature. 2013;501:328–37. https://doi.org/10.1038/nature12624.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Ackermann M. A functional perspective on phenotypic heterogeneity in microorganisms. Nat Rev Microbiol. 2015;13:497–508. https://doi.org/10.1038/nrmicro3491.

    Article  CAS  PubMed  Google Scholar 

  5. Candia J, Maunu R, Driscoll M, Biancotto A, Dagur P, McCoy JP, et al. From cellular characteristics to disease diagnosis: uncovering phenotypes with supercells. PLoS Comput Biol. 2013;9:1–10. https://doi.org/10.1371/journal.pcbi.1003215.

    Article  CAS  Google Scholar 

  6. Wang D, Bodovitz S. Single cell analysis: the new frontier in “omics”. Trends Biotechnol. 2010;28:281–90. https://doi.org/10.1016/j.tibtech.2010.03.002.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Heath JR, Ribas A, Mischel PS. Single-cell analysis tools for drug discovery and development. Nat Rev Drug Discov. 2016;15:204–16. https://doi.org/10.1038/nrd.2015.16.

    Article  PubMed  CAS  Google Scholar 

  8. Ong TH, Kissick DJ, Jansson ET, Comi TJ, Romanova EV, Rubakhin SS, et al. Classification of large cellular populations and discovery of rare cells using single cell matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Anal Chem. 2015;87:7036–42. https://doi.org/10.1021/acs.analchem.5b01557.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Lapainis T, Rubakhin SS, Sweedler JV. Capillary electrophoresis with electrospray ionization mass spectrometric detection for single-cell metabolomics. Anal Chem. 2009;81:5858–64. https://doi.org/10.1021/ac900936g.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Nemes P, Knolhoff AM, Rubakhin SS, Sweedler JV. Metabolic differentiation of neuronal phenotypes by single-cell capillary electrophoresis-electrospray ionization-mass spectrometry. Anal Chem. 2011;83:6810–7. https://doi.org/10.1021/ac2015855.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Liu JX, Aerts JT, Rubakhin SS, Zhang XX, Sweedler JV. Analysis of endogenous nucleotides by single cell capillary electrophoresis-mass spectrometry. Analyst. 2014;139:5835–42. https://doi.org/10.1039/c4an01133c.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Nemes P, Rubakhin SS, Aerts JT, Sweedler JV. Qualitative and quantitative metabolomic investigation of single neurons by capillary electrophoresis electrospray ionization mass spectrometry. Nat Protoc. 2013;8:783–99. https://doi.org/10.1038/nprot.2013.035.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Passarelli MK, Ewing AG, Winograd N. Single-cell lipidomics: characterizing and imaging lipids on the surface of individual Aplysia californica neurons with cluster secondary ion mass spectrometry. Anal Chem. 2013;85:2231–8. https://doi.org/10.1021/ac303038j.

    Article  PubMed  CAS  Google Scholar 

  14. Schober Y, Guenther S, Spengler B, Römpp A. Single cell matrix-assisted laser desorption/ionization mass spectrometry imaging. Anal Chem. 2012;84:6293–7. https://doi.org/10.1021/ac301337h.

    Article  PubMed  CAS  Google Scholar 

  15. Calvano CD, Monopoli A, Cataldi TRI, Palmisano F. MALDI matrices for low molecular weight compounds: an endless story? Anal Bioanal Chem. 2018;410:4015–38. https://doi.org/10.1007/s00216-018-1014-x.

    Article  PubMed  CAS  Google Scholar 

  16. Bergman HM, Lanekoff I. Profiling and quantifying endogenous molecules in single cells using nano-DESI MS. Analyst. 2017;142:3639–47. https://doi.org/10.1039/c7an00885f.

    Article  PubMed  CAS  Google Scholar 

  17. González-Serrano AF, Pirro V, Ferreira CR, Oliveri P, Eberlin LS, Heinzmann J, et al. Desorption electrospray ionization mass spectrometry reveals lipid metabolism of individual oocytes and embryos. PLoS One. 2013;8:1–11. https://doi.org/10.1371/journal.pone.0074981.

    Article  CAS  Google Scholar 

  18. Pirro V, Oliveri P, Ferreira CR, González-Serrano AF, Machaty Z, Cooks RG. Lipid characterization of individual porcine oocytes by dual mode DESI-MS and data fusion. Anal Chim Acta. 2014;848:51–60. https://doi.org/10.1016/j.aca.2014.08.001.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Pan N, Rao W, Kothapalli NR, Liu R, Burgett AWG, Yang Z. The single-probe: a miniaturized multifunctional device for single cell mass spectrometry analysis. Anal Chem. 2014;86:9376–80. https://doi.org/10.1021/ac5029038.

    Article  PubMed  CAS  Google Scholar 

  20. Liu R, Pan N, Zhu Y, Yang Z. T-probe: an integrated microscale device for online in situ single cell analysis and metabolic profiling using mass spectrometry. Anal Chem. 2018;90:11078–85. https://doi.org/10.1021/acs.analchem.8b02927.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Gong X, Zhao Y, Cai S, Fu S, Yang C, Zhang S, et al. Single cell analysis with probe ESI-mass spectrometry: detection of metabolites at cellular and subcellular levels. Anal Chem. 2014;86:3809–16. https://doi.org/10.1021/ac500882e.

    Article  PubMed  CAS  Google Scholar 

  22. Samarah LZ, Khattar R, Tran TH, Stopka SA, Brantner CA, Parlanti P, et al. Single-cell metabolic profiling: metabolite formulas from isotopic fine structures in heterogeneous plant cell populations. Anal Chem. 2020;92:7289–98. https://doi.org/10.1021/acs.analchem.0c00936.

    Article  PubMed  CAS  Google Scholar 

  23. Lee JK, Jansson ET, Nam HG, Zare RN. High-resolution live-cell imaging and analysis by laser desorption/ionization droplet delivery mass spectrometry. Anal Chem. 2016;88:5453–61. https://doi.org/10.1021/acs.analchem.6b00881.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Bokhart MT, Rosen E, Thompson C, Sykes C, Kashuba ADM, Muddiman DC. Quantitative mass spectrometry imaging of emtricitabine in cervical tissue model using infrared matrix-assisted laser desorption electrospray ionization. Anal Bioanal Chem. 2015;407:2073–84. https://doi.org/10.1007/s00216-014-8220-y.

    Article  PubMed  CAS  Google Scholar 

  25. Robichaud G, Barry JA, Muddiman DC. IR-MALDESI mass spectrometry imaging of biological tissue sections using ice as a matrix. J Am Soc Mass Spectrom. 2014;25:319–28. https://doi.org/10.1007/s13361-013-0787-6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Tu A, Muddiman DC. Internal energy deposition in infrared matrix-assisted laser desorption electrospray ionization with and without the use of ice as a matrix. J Am Soc Mass Spectrom. 2019;30:2380–91. https://doi.org/10.1007/s13361-019-02323-2.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  27. Sampson JS, Hawkridge AM, Muddiman DC. Generation and detection of multiply-charged peptides and proteins by matrix-assisted laser desorption electrospray ionization (MALDESI) Fourier transform ion cyclotron resonance mass spectrometry. J Am Soc Mass Spectrom. 2006;17:1712–6. https://doi.org/10.1016/j.jasms.2006.08.003.

    Article  PubMed  CAS  Google Scholar 

  28. Dixon RB, Muddiman DC. Study of the ionization mechanism in hybrid laser based desorption techniques. Analyst. 2010;135:880–2. https://doi.org/10.1039/b926422a.

    Article  PubMed  CAS  Google Scholar 

  29. Fideler J, Johanningsmeier SD, Ekelöf M, Muddiman DC. Discovery and quantification of bioactive peptides in fermented cucumber by direct analysis IR-MALDESI mass spectrometry and LC-QQQ-MS. Food Chem. 2019;271:715–23. https://doi.org/10.1016/j.foodchem.2018.07.187.

    Article  PubMed  CAS  Google Scholar 

  30. Nazari M, Muddiman DC. Polarity switching mass spectrometry imaging of healthy and cancerous hen ovarian tissue sections by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI). Analyst. 2016;141:595–605. https://doi.org/10.1039/c5an01513h.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Khodjaniyazova S, Hanne NJ, Cole JH, Muddiman DC. Mass spectrometry imaging (MSI) of fresh bones using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI). Anal Methods. 2019;11:5929–38. https://doi.org/10.1039/c9ay01886g.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Stutts WL, Knuth MM, Ekelöf M, Mahapatra D, Kullman SW, Muddiman DC. Methods for cryosectioning and mass spectrometry imaging of whole-body zebrafish. J Am Soc Mass Spectrom. 2020;31:768–72. https://doi.org/10.1021/jasms.9b00097.

    Article  PubMed  CAS  Google Scholar 

  33. Nazari M, Muddiman DC. Cellular-level mass spectrometry imaging using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) by oversampling. Anal Bioanal Chem. 2015;407:2265–71. https://doi.org/10.1007/s00216-014-8376-5.

    Article  PubMed  CAS  Google Scholar 

  34. Scientific T (2017) Thermo Scientific Q Exactive HF-X Hybrid Quadrupole-Orbitrap MS System. thermofisher.com/QExactiveHFX.

  35. Robichaud G, Barry JA, Garrard KP, Muddiman DC. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) imaging source coupled to a FT-ICR mass spectrometer. J Am Soc Mass Spectrom. 2013;24:92–100. https://doi.org/10.1007/s13361-012-0505-9.

    Article  PubMed  CAS  Google Scholar 

  36. Ekelöf M, Manni J, Nazari M, Bokhart M, Muddiman DC. Characterization of a novel miniaturized burst-mode infrared laser system for IR-MALDESI mass spectrometry imaging. Anal Bioanal Chem. 2018;410:2395–402. https://doi.org/10.1007/s00216-018-0918-9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Olsen JV, de Godoy LMF, Li G, Macek B, Mortensen P, Pesch R, et al. Parts per million mass accuracy on an orbitrap mass spectrometer via lock mass injection into a C-trap. Mol Cell Proteomics. 2005;4:2010–21. https://doi.org/10.1074/mcp.T500030-MCP200.

    Article  PubMed  CAS  Google Scholar 

  38. Kessner D, Chambers M, Burke R, Agus D, Mallick P. ProteoWizard: open source software for rapid proteomics tools development. Bioinformatics. 2008;24:2534–6. https://doi.org/10.1093/bioinformatics/btn323.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Schramm T, Hester A, Klinkert I, Both JP, Heeren RMA, Brunelle A, et al. ImzML - a common data format for the flexible exchange and processing of mass spectrometry imaging data. J Proteomics. 2012;75:5106–10. https://doi.org/10.1016/j.jprot.2012.07.026.

    Article  PubMed  CAS  Google Scholar 

  40. Race AM, Styles IB, Bunch J. Inclusive sharing of mass spectrometry imaging data requires a converter for all. J Proteomics. 2012;75:5111–2. https://doi.org/10.1016/j.jprot.2012.05.035.

    Article  PubMed  CAS  Google Scholar 

  41. Robichaud G, Garrard KP, Barry JA, Muddiman DC. MSiReader: an open-source interface to view and analyze high resolving power MS imaging files on matlab platform. J Am Soc Mass Spectrom. 2013;24:718–21. https://doi.org/10.1007/s13361-013-0607-z.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Bokhart MT, Nazari M, Garrard KP, Muddiman DC. MSiReader v1.0: evolving open-source mass spectrometry imaging software for targeted and untargeted analyses. J Am Soc Mass Spectrom. 2018;29:8–16. https://doi.org/10.1007/s13361-017-1809-6.

    Article  PubMed  CAS  Google Scholar 

  43. Ekelöf M, Garrard KP, Judd R, Rosen EP, Xie DY, Kashuba ADM, et al. Evaluation of digital image recognition methods for mass spectrometry imaging data analysis. J Am Soc Mass Spectrom. 2018;29:2467–70. https://doi.org/10.1007/s13361-018-2073-0.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Guijas C, Montenegro-Burke JR, Domingo-Almenara X, Palermo A, Warth B, Hermann G, et al. METLIN: a technology platform for identifying knowns and unknowns. Anal Chem. 2018;90:3156–64. https://doi.org/10.1021/acs.analchem.7b04424.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. HeLa Cells. In: Br. Soc. Immunol. 1951;https://www.immunology.org/hela-cells-1951. Accessed May 2020.

  46. Milo R, Phillips R. Cell biology by the numbers. New York: Garland Science; 2015.

    Google Scholar 

  47. Naguib A, Bencze G, Engle DD, Chio IIC, Herzka T, Watrud K, et al. P53 mutations change phosphatidylinositol acyl chain composition. Cell Rep. 2015;10:8–19. https://doi.org/10.1016/j.celrep.2014.12.010.

    Article  PubMed  CAS  Google Scholar 

  48. Brügger B. Lipidomics: analysis of the lipid composition of cells and subcellular organelles by electrospray ionization mass spectrometry. Annu Rev Biochem. 2014;83:79–98. https://doi.org/10.1146/annurev-biochem-060713-035324.

    Article  PubMed  CAS  Google Scholar 

  49. Yan F, Zhao H, Zeng Y. Lipidomics: a promising cancer biomarker. Clin Transl Med. 2018;7:21–3. https://doi.org/10.1186/s40169-018-0199-0.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Bandu R, Mok HJ, Kim KP. Phospholipids as cancer biomarkers: mass spectrometry-based analysis. Mass Spectrom Rev. 2018;37:107–38. https://doi.org/10.1002/mas.21510.

    Article  PubMed  CAS  Google Scholar 

  51. Milne S, Ivanova P, Forrester J, Alex Brown H. Lipidomics: an analysis of cellular lipids by ESI-MS. Methods. 2006;39:92–103. https://doi.org/10.1016/j.ymeth.2006.05.014.

    Article  PubMed  CAS  Google Scholar 

  52. Meier F, Garrard KP, Muddiman DC. Silver dopants for targeted and untargeted direct analysis of unsaturated lipids via infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI). Rapid Commun Mass Spectrom. 2014;28:2461–70. https://doi.org/10.1002/rcm.7041.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Dueñas ME, Essner JJ, Lee YJ. 3D MALDI mass spectrometry imaging of a single cell: spatial mapping of lipids in the embryonic development of zebrafish. Sci Rep. 2017;7:1–10. https://doi.org/10.1038/s41598-017-14949-x.

    Article  CAS  Google Scholar 

  54. Do TD, Comi TJ, Dunham SJB, Rubakhin SS, Sweedler JV. Single cell profiling using ionic liquid matrix-enhanced secondary ion mass spectrometry for neuronal cell type differentiation. Anal Chem. 2017;89:3078–86. https://doi.org/10.1021/acs.analchem.6b04819.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Chen F, Lin L, Zhang J, He Z, Uchiyama K, Lin JM. Single-cell analysis using drop-on-demand inkjet printing and probe electrospray ionization mass spectrometry. Anal Chem. 2016;88:4354–60. https://doi.org/10.1021/acs.analchem.5b04749.

    Article  PubMed  CAS  Google Scholar 

  56. Kompauer M, Heiles S, Spengler B. Atmospheric pressure MALDI mass spectrometry imaging of tissues and cells at 1.4-μm lateral resolution. Nat Methods. 2016;14:90–6. https://doi.org/10.1038/nmeth.4071.

    Article  PubMed  CAS  Google Scholar 

  57. Huang Q, Mao S, Khan M, Zhou L, Lin JM. Dean flow assisted cell ordering system for lipid profiling in single-cells using mass spectrometry. Chem Commun. 2018;54:2595–8. https://doi.org/10.1039/c7cc09608a.

    Article  CAS  Google Scholar 

  58. Garrard KP, Ekelöf M, Khodjaniyazova S, Bagley MC, Muddiman DC. A versatile platform for mass spectrometry imaging of arbitrary spatial patterns. J Am Soc Mass Spectrom. 2020. https://doi.org/10.1021/jasms.0c00128.

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Acknowledgments

This work was performed in part by the Molecular Education, Technology and Research Innovation Center (METRIC) at NC State University, which is supported by the State of North Carolina. The authors gratefully thank Dr. Crissi Martinez and Professor. Josh Pierce at NCSU for providing the cultured HeLa cells.

Funding

This work received financial support from the National Institutes of Health (R01GM087964).

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  1. Ying Xi and Anqi Tu contributed equally to this work.

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  1. FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA

    Ying Xi, Anqi Tu & David C. Muddiman

  2. Molecular Education, Technology and Research Innovation Center (METRIC), North Carolina State University, Raleigh, NC, 27695, USA

    David C. Muddiman

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  1. Ying Xi
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Xi, Y., Tu, A. & Muddiman, D.C. Lipidomic profiling of single mammalian cells by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI). Anal Bioanal Chem 412, 8211–8222 (2020). https://doi.org/10.1007/s00216-020-02961-6

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