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Volume 35 Issue 4
Jul.  2021
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Misevic Gradimir. Single-cell omics analyses with single molecular detection: challenges and perspectives[J]. The Journal of Biomedical Research, 2021, 35(4): 264-276. doi: 10.7555/JBR.35.20210026
Citation: Misevic Gradimir. Single-cell omics analyses with single molecular detection: challenges and perspectives[J]. The Journal of Biomedical Research, 2021, 35(4): 264-276. doi: 10.7555/JBR.35.20210026

Single-cell omics analyses with single molecular detection: challenges and perspectives

doi: 10.7555/JBR.35.20210026
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  • Corresponding author: Gradimir Misevic, Research and Development, Gimmune GmbH, Baarerstrasse 12, 6302 Zug, Switzerland. Tel/Fax: +41-76-411-6243/+41-76-411-6243, E-mail: gradimir@gimmune.com
  • Received: 2021-02-13
  • Accepted: 2021-03-16
  • Published: 2021-04-30
  • Issue Date: 2021-07-28
  • The ultimate goal of single-cell analyses is to obtain the biomolecular content for each cell in unicellular and multicellular organisms at different points of their life cycle under variable environmental conditions. These require an assessment of: a) the total number of cells, b) the total number of cell types, and c) the complete and quantitative single molecular detection and identification for all classes of biopolymers, and organic and inorganic compounds, in each individual cell. For proteins, glycans, lipids, and metabolites, whose sequences cannot be amplified by copying as in the case of nucleic acids, the detection limit by mass spectrometry is about 105 molecules. Therefore, proteomic, glycomic, lipidomic, and metabolomic analyses do not yet permit the assembly of the complete single-cell omes. The construction of novel nanoelectrophoretic arrays and nano in microarrays on a single 1-cm-diameter chip has shown proof of concept for a high throughput platform for parallel processing of thousands of individual cells. Combined with dynamic secondary ion mass spectrometry, with 3D scanning capability and lateral resolution of 50 nm, the sensitivity of single molecular quantification and identification for all classes of biomolecules could be reached. Further development and routine application of such technological and instrumentation solution would allow assembly of complete omes with a quantitative assessment of structural and functional cellular diversity at the molecular level.


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  • [1]
    Omics.org[EB/OL]. [2021-02-12]. http://omics.org/Main_Page.
    How many proteins are in a cell?[EB/OL]. [2021-02-12]. http://book.bionumbers.org/how-many-proteins-are-in-a-cell/.
    Bianconi E, Piovesan A, Facchin F, et al. An estimation of the number of cells in the human body[J]. Ann Hum Biol, 2013, 40(6): 463–471. doi: 10.3109/03014460.2013.807878
    Sender R, Fuchs S, Milo R. Revised estimates for the number of human and bacteria cells in the body[J]. PLoS Biol, 2016, 14(8): e1002533. doi: 10.1371/journal.pbio.1002533
    Sahl SJ, Hell SW, Jakobs S. Fluorescence nanoscopy in cell biology[J]. Nat Rev Mol Cell Biol, 2017, 18(11): 685–701. doi: 10.1038/nrm.2017.71
    Mahecic D, Gambarotto D, Douglass KM, et al. Homogeneous multifocal excitation for high-throughput super-resolution imaging[J]. Nat Methods, 2020, 17(7): 726–733. doi: 10.1038/s41592-020-0859-z
    Rust MJ, Bates M, Zhuang XW. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)[J]. Nat Methods, 2006, 3(10): 793–796. doi: 10.1038/nmeth929
    Matikonda SS, Götz R, McLaughlin R, et al. Conformationally restrained pentamethine cyanines and use in reductive single molecule localization microscopy[J]. Methods Enzymol, 2020, 641: 225–244. doi: 10.1016/bs.mie.2020.04.042
    Castellanos A, Ramirez CE, Michalkova V, et al. Three dimensional secondary ion mass spectrometry imaging (3D-SIMS) of Aedes aegypti ovarian follicles[J]. J Anal At Spectrom, 2019, 34(5): 874–883. doi: 10.1039/C8JA00425K
    Xi Y, Tu AQ, Muddiman DC. Lipidomic profiling of single mammalian cells by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)[J]. Anal Bioanal Chem, 2020, 412(29): 8211–8222. doi: 10.1007/s00216-020-02961-6
    Körsgen M, Pelster A, Vens-Cappell S, et al. Molecular ME-ToF-SIMS yield as a function of DHB matrix layer thicknesses obtained from brain sections coated by sublimation/deposition techniques[J]. Surf Interface Anal, 2016, 48(1): 34–39. doi: 10.1002/sia.5885
    How big is a human cell?[EB/OL]. [2021-02-12]. http://book.bionumbers.org/how-big-is-a-human-cell/.
    What is the macromolecular composition of the cell?[EB/OL]. [2021-02-12]. http://book.bionumbers.org/what-is-the-macromolecular-composition-of-the-cell/.
    Lynch M, Marinov GK. The bioenergetic costs of a gene[J]. Proc Natl Acad Sci U S A, 2015, 112(51): 15690–15695. doi: 10.1073/pnas.1514974112
    Picelli S, Faridani OR, Björklund ÅK, et al. Full-length RNA-seq from single cells using Smart-seq2[J]. Nat Protoc, 2014, 9(1): 171–181. doi: 10.1038/nprot.2014.006
    Cohen D, Dickerson JA, Whitmore CD, et al. Chemical cytometry: fluorescence-based single-cell analysis[J]. Annu Rev Anal Chem, 2008, 1: 165–190. doi: 10.1146/annurev.anchem.1.031207.113104
    Aebersold R, Goodlett DR. Mass spectrometry in proteomics[J]. Chem Rev, 2001, 101(2): 269–295. doi: 10.1021/cr990076h
    Nichols C, Zekavat B, Batoon P. Instrument Detection Limit at Ultrashort Dwell Times Demonstrated on the Agilent 6495C Triple Quadrupole LC/MS[EB/OL]. [2021-02-12]. https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/application::paper.paper/technicaloverview-idl-instrument-detection-limit-idl-ultrashort-dwell-times-6495-5994-1368en-agilent.pdf.
    Instrument Detection Limit (IDL)[EB/OL]. [2021-02-12]. https://www.agilent.com/en/products/mass-spectrometry/gc-ms-instruments/idl.
    Wells G, Prest H, Russ IV CW, et al. Signal, noise, and detection limits in mass spectrometry[R]. Wilmington, DE, USA: Agilent Technologies, Inc., 2011.
    Lombard-Banek C, Moody SA, Manzini MC, et al. Microsampling capillary electrophoresis mass spectrometry enables single-cell proteomics in complex tissues: developing cell clones in live Xenopus laevis and zebrafish embryos[J]. Anal Chem, 2019, 91(7): 4797–4805. doi: 10.1021/acs.analchem.9b00345
    Brunner AD, Thielert M, Vasilopoulou CG, et al. Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation[EB/OL]. [2020-12-20]. https://www.biorxiv.org/content/10.1101/2020.12.22.423933v2.
    How big are genomes?[EB/OL]. [2021-02-12]. http://book.bionumbers.org/how-big-are-genomes/.
    Navin N, Kendall J, Troge J, et al. Tumour evolution inferred by single-cell sequencing[J]. Nature, 2011, 472(7341): 90–94. doi: 10.1038/nature09807
    Shrestha B. Single-Cell Metabolomics by Mass Spectrometry[J]. Methods Mol Biol, 2020, 2064: 1–8.
    Cohen L, Cui NW, Cai YM, et al. Single molecule protein detection with attomolar sensitivity using droplet digital enzyme-linked immunosorbent assay[J]. ACS Nano, 2020, 14(8): 9491–9501. doi: 10.1021/acsnano.0c02378
    Misevic GN, BenAssayag G, Rasser B, et al. Design and construction of wall-less nano-electrophoretic and nano in micro array high throughput devices for single cell 'omics' single molecule detection analyses[J]. J Mol Struct, 2014, 1073: 142–149. doi: 10.1016/j.molstruc.2014.05.011
    Macchia E, Manoli K, Di Franco C, et al. Organic field-effect transistor platform for label-free, single-Molecule Detection of Genomic Biomarkers[J]. ACS Sensors, 2020, 5(6): 1822–1830. doi: 10.1021/acssensors.0c00694
    Klughammer N, Dekker C. Palladium zero-mode waveguides for optical single-molecule detection with nanopores[J]. Nanotechnology, 2021, 32(18): 18LT01. doi: 10.1088/1361-6528/abd976
    Pan SC, Yang C, Zhao XS. Affinity of Skp to OmpC revealed by single-molecule detection[J]. Sci Rep, 2020, 10(1): 14871. doi: 10.1038/s41598-020-71608-4
    Farka Z, Mickert MJ, Pastucha M, et al. Advances in optical single-molecule detection: en route to supersensitive bioaffinity assays[J]. Angew Chemie Int Ed, 2020, 59(27): 10746–10773. doi: 10.1002/anie.201913924
    Kang S, Nieuwenhuis AF, Mathwig K, et al. Electrochemical single-molecule detection in aqueous solution using self-aligned nanogap transducers[J]. ACS Nano, 2013, 7(12): 10931–10937. doi: 10.1021/nn404440v
    Vickaryous MK, Hall BK. Human cell type diversity, evolution, development, and classification with special reference to cells derived from the neural crest[J]. Biol Rev Camb Philos Soc, 2006, 81(3): 425–455. doi: 10.1017/S1464793106007068
    Sulston JE, Horvitz HR. Post-embryonic cell lineages of the nematode, Caenorhabditis elegans[J]. Dev Biol, 1977, 56(1): 110–156. doi: 10.1016/0012-1606(77)90158-0
    Sulston JE, Schierenberg E, White JG, et al. The embryonic cell lineage of the nematode Caenorhabditis elegans[J]. Dev Biol, 1983, 100(1): 64–119. doi: 10.1016/0012-1606(83)90201-4
    Sammut M, Cook SJ, Nguyen KCQ, et al. Glia-derived neurons are required for sex-specific learning in C. Elegans[J]. Nature, 2015, 526(7573): 385–390. doi: 10.1038/nature15700
    Navin NE. The first five years of single-cell cancer genomics and beyond[J]. Genome Res, 2015, 25(10): 1499–1507. doi: 10.1101/gr.191098.115
    Liu LQ, Liu CY, Quintero A, et al. Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity[J]. Nat Commun, 2019, 10(1): 470. doi: 10.1038/s41467-018-08205-7
    Eirew P, Steif A, Khattra J, et al. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution[J]. Nature, 2015, 518(7539): 422–426. doi: 10.1038/nature13952
    Gao R, Davis A, McDonald TO, et al. Punctuated copy number evolution and clonal stasis in triple-negative breast cancer[J]. Nat Genet, 2016, 48(10): 1119–1130. doi: 10.1038/ng.3641
    Xu X, Hou Y, Yin XY, et al. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor[J]. Cell, 2012, 148(5): 886–895. doi: 10.1016/j.cell.2012.02.025
    Lohr JG, Stojanov P, Carter SL, et al. Widespread genetic heterogeneity in multiple myeloma: Implications for targeted therapy[J]. Cancer Cell, 2014, 25(1): 91–101. doi: 10.1016/j.ccr.2013.12.015
    Hou Y, Song LT, Zhu P, et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm[J]. Cell, 2012, 148(5): 873–885. doi: 10.1016/j.cell.2012.02.028
    Gawad C, Koh W, Quake SR. Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics[J]. Proc Natl Acad Sci U S A, 2014, 111(50): 17947–17952. doi: 10.1073/pnas.1420822111
    McConnell MJ, Lindberg MR, Brennand KJ, et al. Mosaic copy number variation in human neurons[J]. Science, 2013, 342(6158): 632–637. doi: 10.1126/science.1243472
    Knouse KA, Wu J, Whittaker CA, et al. Single cell sequencing reveals low levels of aneuploidy across mammalian tissues[J]. Proc Natl Acad Sci U S A, 2014, 111(37): 13409–13414. doi: 10.1073/pnas.1415287111
    Rehen SK, McConnell MJ, Kaushal D, et al. Chromosomal variation in neurons of the developing and adult mammalian nervous system[J]. Proc Natl Acad Sci U S A, 2001, 98(23): 13361–13366. doi: 10.1073/pnas.231487398
    Svensson V, da Veiga Beltrame E, Pachter L. A curated database reveals trends in single-cell transcriptomics[J]. Database, 2020, 2020: baaa073. doi: 10.1093/database/baaa073
    mcSCRB-seq protocol[EB/OL]. [2021-02-12]. https://www.protocols.io/view/mcscrb-seq-protocol-p9kdr4w.
    scRNASeqDB[EB/OL]. [2021-02-12]. https://bioinfo.uth.edu/scrnaseqdb/.
    Home-GEO-NCBI[EB/OL]. [2021-02-12]. https://www.ncbi.nlm.nih.gov/geo/.
    The Human Cell Types. The human protein atlas[EB/OL]. [2021-02-12]. https://www.proteinatlas.org/humanproteome/celltype.
    Karamanos Y, Pottiez G. Proteomics and the blood-brain barrier: How recent findings help drug development[J]. Expert Rev Proteomics, 2016, 13(3): 251–258. doi: 10.1586/14789450.2016.1143780
    Budnik B, Levy E, Harmange G, et al. Mass-spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation[EB/OL]. [2021-02-12]. https://arxiv.org/abs/1808.00598v1.
    Budnik B, Levy E, Harmange G, et al. SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation[J]. Genome Biol, 2018, 19(1): 161. doi: 10.1186/s13059-018-1547-5
    Priyadharshini VS, Teran LM. Role of respiratory proteomics in precision medicine[M]//Faintuch J, Faintuch S. Precision medicine for investigators, practitioners and providers. 1st ed. San Diego: Academic Press, 2019: 255–261.
    Hu S, Zhang L, Krylov S, et al. Cell cycle-dependent protein fingerprint from a single cancer cell: Image cytometry coupled with single-cell capillary sieving electrophoresis[J]. Anal Chem, 2003, 75(14): 3495–3501. doi: 10.1021/ac034153r
    Sun LL, Dubiak KM, Peuchen EH, et al. Single cell proteomics using frog (Xenopus laevis) blastomeres isolated from early stage embryos, which form a geometric progression in protein content[J]. Anal Chem, 2016, 88(13): 6653–6657. doi: 10.1021/acs.analchem.6b01921
    Bandura DR, Baranov VI, Ornatsky OI, et al. Mass cytometry: Technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry[J]. Anal Chem, 2009, 81(16): 6813–6822. doi: 10.1021/ac901049w
    Fredriksson S, Gullberg M, Jarvius J, et al. Protein detection using proximity-dependent DNA ligation assays[J]. Nat Biotechnol, 2002, 20(5): 473–477. doi: 10.1038/nbt0502-473
    Li H, Li WW, Liu FZ, et al. Detection of tumor invasive biomarker using a peptamer of signal conversion and signal amplification[J]. Anal Chem, 2016, 88(7): 3662–3668. doi: 10.1021/acs.analchem.5b04423
    Assarsson E, Lundberg M, Holmquist G, et al. Homogenous 96-Plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability[J]. PLoS One, 2014, 9(4): e95192. doi: 10.1371/journal.pone.0095192
    Liebermeister W, Noor E, Flamholz A, et al. Visual account of protein investment in cellular functions[J]. Proc Natl Acad Sci U S A, 2014, 111(23): 8488–8493. doi: 10.1073/pnas.1314810111
    Adhikari S, Nice EC, Deutsch EW, et al. A high-stringency blueprint of the human proteome[J]. Nat Commun, 2020, 11(1): 5301. doi: 10.1038/s41467-020-19045-9
    Thul PJ, Åkesson L, Wiking M, et al. A subcellular map of the human proteome[J]. Science, 2017, 356(6340): eaal3321. doi: 10.1126/science.aal3321
    The human cell-The Human Protein Atlas[EB/OL]. [2021-02-12]. https://v19.proteinatlas.org/humanproteome/cell.
    Rudd P, Karlsson NG, Khoo KH, et al. Glycomics and glycoproteomics[M]. 3rd ed. Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press, 2017.
    Peng WJ, Zhu R, Zhou SY, et al. Integrated transcriptomics, proteomics, and glycomics reveals the association between up-regulation of sialylated N-glycans/Integrin and breast cancer brain metastasis[J]. Sci Rep, 2019, 9(1): 17361. doi: 10.1038/s41598-019-53984-8
    Varki A. Biological roles of glycans[J]. Glycobiology, 2017, 27(1): 3–49. doi: 10.1093/glycob/cww086
    Varki A, Schauer R. Sialic acids[M]//Varki A, Cummings RD, Esko JD, et al. Essentials of Glycobiology. New York: Cold Spring Harbor Laboratory Press, 2015.
    Glycan Repository[EB/OL]. [2021-02-12]. https://glytoucan.org/.
    Misevic G, Garbarino E. Glycan-to-glycan binding: molecular recognition through polyvalent interactions mediates specific cell adhesion[J]. Molecules, 2021, 26(2): 397. doi: 10.3390/molecules26020397
    Ferreira CR, Pirro V, Jarmusch AK, et al. Ambient lipidomic analysis of single mammalian oocytes and preimplantation embryos using desorption electrospray ionization (DESI) mass spectrometry[J]. Methods Mol Biol, 2020, 2064: 159–179. doi: 10.1007/978-1-4939-9831-9_13
    Shanta PV, Li BC, Stuart DD, et al. Plasmonic gold templates enhancing single cell lipidomic analysis of microorganisms[J]. Anal Chem, 2020, 92(9): 6213–6217. doi: 10.1021/acs.analchem.9b05285
    Lita A, Kuzmin AN, Pliss A, et al. Toward single-organelle lipidomics in live cells[J]. Anal Chem, 2019, 91(17): 11380–11387. doi: 10.1021/acs.analchem.9b02663
    Snowden SG, Fernandes HJR, Kent J, et al. Development and application of high-throughput single cell lipid profiling: a study of SNCA-A53T human dopamine neurons[J]. iScience, 2020, 23(11): 101703. doi: 10.1016/j.isci.2020.101703
    Rubakhin SS, Lanni EJ, Sweedler JV. Progress toward single cell metabolomics[J]. Curr Opin Biotechnol, 2013, 24(1): 95–104. doi: 10.1016/j.copbio.2012.10.021
    Ali A, Abouleila Y, Shimizu Y, et al. Single-cell metabolomics by mass spectrometry: Advances, challenges, and future applications[J]. TrAC Trends Anal Chem, 2019, 120: 115436. doi: 10.1016/j.trac.2019.02.033
    Klepárník K, Foret F. Recent advances in the development of single cell analysis-A review[J]. Anal Chim Acta, 2013, 800: 12–21. doi: 10.1016/j.aca.2013.09.004
    Kawai T, Ota N, Okada K, et al. Ultrasensitive single cell metabolomics by capillary electrophoresis-mass spectrometry with a thin-walled tapered emitter and large-volume dual sample preconcentration[J]. Anal Chem, 2019, 91(16): 10564–10572. doi: 10.1021/acs.analchem.9b01578
    Hiyama E, Ali A, Amer S, et al. Direct lipido-metabolomics of single floating cells for analysis of circulating tumor cells by live single-cell mass spectrometry[J]. Anal Sci, 2015, 31(12): 1215–1217. doi: 10.2116/analsci.31.1215
    Zhang XC, Zang QC, Zhao HS, et al. Combination of droplet extraction and Pico-ESI-MS allows the identification of metabolites from single cancer cells[J]. Anal Chem, 2018, 90(16): 9897–9903. doi: 10.1021/acs.analchem.8b02098
    Liu RM, Sun M, Zhang GW, et al. Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning[J]. Anal Chim Acta, 2019, 1092: 42–48. doi: 10.1016/j.aca.2019.09.065
    Ajit Varki. Biological roles of glycans[J]. Glycobiology, 2017, 27(1): 3–49. doi: 10.1093/glycob/cww086
    De Samber B, De Rycke R, De Bruyne M, et al. Effect of sample preparation techniques upon single cell chemical imaging: A practical comparison between synchrotron radiation based X-ray fluorescence (SR-XRF) and Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS)[J]. Anal Chim Acta, 2020, 1106: 22–32. doi: 10.1016/j.aca.2020.01.054
    Spampinato V, Dialameh M, Franquet A, et al. A correlative ToF-SIMS/SPM methodology for probing 3D devices[J]. Anal Chem, 2020, 92(16): 11413–11419. doi: 10.1021/acs.analchem.0c02406
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