Horgan, R. P., and Kenny, L. C. (2011) “Omic” technologies: genomics, transcriptomics, proteomics and metabolomics, Obstet. Gynaecol., 13, 189–195, doi: 10.1576/toag.13.3.189.27672.
Google Scholar
Geyer, P. E., Voytik, E., Treit, P. V., Doll, S., Kleinhempel A., Niu, L., Muller, J. B., Buchholtz, M., Bader, J. M. Teupser, D., Holdt, L. M., and Mann, M. (2019) Plasma proteome profiling to detect and avoid sample-related biases in biomarker studies, EMBO Mol. Med, doi: 10.15252/emmm.201910427.
Google Scholar
Banfalvi, G. (2011) Overview of cell synchronization Methods Mol. Biol., 761, 1–23, doi: 10.1007/978-1-61779-182-6-1.
CAS
PubMed
Article
PubMed Central
Google Scholar
Emmert-Buck, M. R., Bonner, R. F., Smith, P. D. Chuaqui, R. F., Zhuang, Z., Goldstein, S. R., Weiss, R. A. and Liotta, L. A. (1996) Laser capture microdissection Science, 274, 998–1001, doi: 10.1126/science.274.5289.998.
CAS
PubMed
Article
PubMed Central
Google Scholar
Ziegenhain, C., Vieth, B., Parekh, S., Reinius, B. Guillaumet-Adkins, A., Smets, M., Leonhardt, H., Heyn H., Hellmann, I., and Enard, W. (2017) Comparative analysis of single-cell RNA sequencing methods, Mol. Cell65, 631–643, doi: 10.1016/j.molcel.2017.01.023.
CAS
PubMed
Article
Google Scholar
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R. Yang, J. L., Ferrante, T. C., Terry, R., Jeanty, S. S. F., Li C., Amamoto, R., Peters, D. T., Turczyk, B. M. Marblestone, A. H., Inverso, S. A., Bernard, A., Mali, P. Rios, X., Aach, J., and Church, G. M. (2014) Highly multiplexed subcellular RNA sequencing in situ, Science, 343 1360–1363, doi: 10.1126/science.1250212.
CAS
PubMed
PubMed Central
Article
Google Scholar
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R. Ferrante, T. C., Terry, R., Turczyk, B. M., Yang, J. L., Lee H. S., Aach, J., Zhang, K., and Church, G. M. (2015) Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues, Nat. Protoc.10, 442–458, doi: 10.1038/nprot.2014.191.
CAS
PubMed
PubMed Central
Article
Google Scholar
Picelli, S., Faridani, O. R., Bjorklund, A. K., Winberg, G. Sagasser, S., and Sandberg, R. (2014) Full-length RNA-seq from single cells using Smart-seq2, Nat. Protoc., 9, 171–181, doi: 10.1038/nprot.2014.006.
CAS
PubMed
Article
Google Scholar
Valihrach, L., Androvic, P., and Kubista, M. (2018) Platforms for single-cell collection and analysis, Int. J. Mol. Sci., 19, E807, doi: 10.3390/ijms19030807.
PubMed
Article
CAS
Google Scholar
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P. Bent, Z. W., et al. (2017) Massively parallel digital transcriptional profiling of single cells, Nat. Commun., 8, 14049 doi: 10.1038/ncomms14049.
CAS
PubMed
PubMed Central
Article
Google Scholar
Islam, S., Zeisel, A., Joost, S., La Manno, G., Zajac, P. Kasper, M., Lonnerberg, P., and Linnarsson, S. (2014) Quantitative single-cell RNA-seq with unique molecular identifiers, Nat. Methods, 11, 163–166, doi: 10.1038/nmeth.2772.
CAS
PubMed
Article
PubMed Central
Google Scholar
Zhang, X., Li, T., Liu, F., Chen, Y., Yao, J., Li, Z. Huang, Y., and Wang, J. (2019) Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-seq systems, Mol. Cell, 73, 130–142, doi: 10.1016/j.molcel.2018.10.020.
CAS
PubMed
Article
PubMed Central
Google Scholar
Soldatov, R., Kaucka, M., Kastriti, M. E., Petersen, J. Chontorotzea, T., et al. (2019) Spatiotemporal structure of cell fate decisions in murine neural crest, Science, 364 9536, doi: 10.1126/science.aas9536.
Article
CAS
Google Scholar
La Manno, G., Soldatov, R., Zeisel, A., Braun, E. Hochgerner, H., Petukhov, V., Lidschreiber, K., Kastriti M. E., Lonnerberg, P., Furlan, A., Fan, J., Borm, L. E. Liu, Z., van Bruggen, D., Guo, J., He, X., Barker, R. Sundstrom, E., Castelo-Branco, G., Cramer, P. Adameyko, I., Linnarsson, S., and Kharchenko, P. V. (2018) RNA velocity of single cells, Nature, 560, 494–498 doi: 10.1038/s41586-018-0414-6.
PubMed
PubMed Central
Article
CAS
Google Scholar
Burgess, D. J. (2018) Full speed ahead for single-cell analysis, Nat. Rev. Genet., 19, 668–669, doi: 10.1038/s41576018-0049-3.
CAS
PubMed
Article
Google Scholar
Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A. Barkan, E. R., et al. (2019) Conserved cell types with divergent features in human versus mouse cortex, Nature, 573 61–68, doi: 10.1038/s41586-019-1506-7.
CAS
PubMed
PubMed Central
Article
Google Scholar
Khrameeva, E., Kurochkin, I., Han, D., Guijarro, P. Kanton, S., Santel, M., Qian, Z., Rong, S., Mazin, P. Bulat, M., Efimova, O., Tkachev, A., Guo, S., Sherwood C. C., Camp, J. G., Paabo, S., Treutlein, B., and Khaitovich, P. (2019) Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains bioRxiv, doi: 10.1101/764936.
Google Scholar
Shekhar, K., and Menon, V. (2019) Identification of cell types from single-cell transcriptomic data, Methods Mol. Biol., 1935, 45–77, doi: 10.1007/978-1-4939-9057-3-4.
CAS
PubMed
Article
Google Scholar
Archakov, A., Ivanov, Y., Lisitsa, A., and Zgoda, V. (2009) Biospecific irreversible fishing coupled with atomic force microscopy for detection of extremely low-abundant proteins Proteomics, 9, 1326–1343, doi: 10.1002/pmic.200800598.
CAS
PubMed
Article
Google Scholar
Aymoz, D., Wosika, V., Durandau, E., and Pelet, S. (2016) Real-time quantification of protein expression at the singlecell level via dynamic protein synthesis translocation reporters Nat. Commun., 7, 11304, doi: 10.1038/ncomms11304.
CAS
PubMed
PubMed Central
Article
Google Scholar
Fulwyler, M. J. (1965) Electronic separation of biological cells by volume, Science, 150, 910–911, doi: 10.1126/science.150.3698.910.
CAS
PubMed
Article
Google Scholar
Picot, J., Guerin, C. L., Le Van Kim, C., and Boulanger, C. M. (2012) Flow cytometry: retrospective, fundamentals and recent instrumentation, Cytotechnology, 64, 109–130 doi: 10.1007/s10616-011-9415-0.
PubMed
PubMed Central
Article
Google Scholar
Hughes, A. J., Spelke, D. P., Xu, Z., Kang, C.-C., Schaffer D. V., and Herr, A. E. (2014) Single-cell western blotting Nat. Methods, 11, 749–755, doi: 10.1038/nmeth.2992.
CAS
PubMed
PubMed Central
Article
Google Scholar
Bendall, S. C., Simonds, E. F., Qiu, P., Amir, el-A. D. Krutzik, P. O., Finck, R., Bruggner, R. V., Melamed, R. Trejo, A., Ornatsky, O. I., Balderas, R. S., Plevritis, S. K. Sachs, K., Pe’er, D., Tanner, S. D., and Nolan, G. P. (2011) Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum Science, 332, 687–696, doi: 10.1126/science.1198704.
CAS
PubMed
PubMed Central
Article
Google Scholar
Palii, C. G., Cheng, Q., Gillespie, M. A., Shannon, P. Mazurczyk, M., Napolitani, G., Price, N. D., Ranish, J. A., Morrissey, E., Higgs, D. R., and Brand, M. (2019) Single-cell proteomics reveal that quantitative changes in co-expressed lineage-specific transcription factors determine cell fate, Cell Stem Cell, 24, 812–820, doi: 10.1016/j.stem.2019.02.006.
CAS
PubMed
PubMed Central
Article
Google Scholar
Marcon, E., Jain, H., Bhattacharya, A., Guo, H., Phanse S. et al. (2015) Assessment of a method to characterize antibody selectivity and specificity for use in immunoprecipitation, Nat. Methods, 12, 725–731, doi: 10.1038/nmeth.3472.
CAS
PubMed
Article
Google Scholar
Coscia, F., Watters, K. M., Curtis, M., Eckert, M. A. Chiang, C. Y., Tyanova, S., Montag, A., Lastra, R. R. Lengyel, E., and Mann, M. (2016) Integrative proteomic profiling of ovarian cancer cell lines reveals precursor cell associated proteins and functional status, Nat. Commun., 7 12645, doi: 10.1038/ncomms12645.
CAS
PubMed
PubMed Central
Article
Google Scholar
Kaur, P., and O’Connor, P. B. (2007) Quantitative determination of isotope ratios from experimental isotopic distributions, Anal. Chem., 79, 1198–1204, doi: 10.1021/ac061535z.
CAS
PubMed
PubMed Central
Article
Google Scholar
Ho, B., Baryshnikova, A., and Brown, G. W. (2018) Unification of protein abundance datasets yields a quantitative Saccharomyces cerevisiae proteome, Cell Syst., 6 192–205, doi: 10.1016/j.cels.2017.12.004.
CAS
PubMed
Article
Google Scholar
Siwiak, M., and Zielenkiewicz, P. (2013) Transimulation–protein biosynthesis web service, PLoS One, 8, e73943, doi: 10.1371/journal.pone.0073943.
CAS
PubMed
PubMed Central
Article
Google Scholar
Virant-Klun, I., Leicht, S., Hughes, C., and Krijgsveld, J. (2016) Identification of maturation-specific proteins by single-cell proteomics of human oocytes, Mol. Cell. Proteomics15, 2616–2627, doi: 10.1074/mcp.M115.056887.
CAS
PubMed
PubMed Central
Article
Google Scholar
Sun, L., Dubiak, K. M., Peuchen, E. H., Zhang, Z., Zhu G., Huber, P. W., and Dovichi, N. J. (2016) Single cell proteomics using frog (Xenopus laevis) blastomeres isolated from early stage embryos, which form a geometric progression in protein content, Anal. Chem., 88, 6653–6657, doi: 10.1021/acs.analchem.6b01921.
CAS
PubMed
PubMed Central
Article
Google Scholar
Moroz, L. L. (2018) Neurosystematics and periodic system of neurons: model vs reference species at single-cell resolution, ACS Chem. Neurosci., 9, 1884–1903, doi: 10.1021/acschemneuro.8b00100.
CAS
PubMed
Article
PubMed Central
Google Scholar
Chesnokova, E., Zuzina, A., Bal, N., Vinarskaya, A. Roshchin, M., Artyuhov, A., Dashinimaev, E., Aseyev, N. Balaban, P., and Kolosov, P. (2019) Experiments with snails add to our knowledge about the role of aPKC subfamily kinases in learning, Int. J. Mol. Sci., 20, 2117, doi: 10.3390/ijms20092117.
CAS
PubMed Central
Article
Google Scholar
Thompson, A., Schafer, J., Kuhn, K., Kienle, S., Schwarz J., Schmidt, G., Neumann, T., Johnstone, R. Mohammed, A. K. A., and Hamon, C. (2003) Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS, Anal. Chem., 75, 1895–1904, doi: 10.1021/ac0262560.
CAS
PubMed
Article
PubMed Central
Google Scholar
Budnik, B., Levy, E., Harmange, G., and Slavov, N. (2018) SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation Genome Biol., 19, 161, doi: 10.1186/s13059-018-1547-5.
PubMed
PubMed Central
Article
CAS
Google Scholar
Huffman, R. G., Chen, A., Specht, H., and Slavov, N. (2019) DO-MS: data-driven optimization of mass spectrometry methods, J. Proteome Res., 18, 2493–2500, doi: 10.1021/acs.jproteome.9b00039.
CAS
PubMed
PubMed Central
Article
Google Scholar
Chen, A. T., Franks, A., and Slavov, N. (2019) DART-ID increases single-cell proteome coverage, PLOS Comput. Biol., 15, e1007082, doi: 10.1371/journal.pcbi.1007082.
PubMed
PubMed Central
Article
CAS
Google Scholar
Specht, H., Emmott, E., Perlman, D. H., Koller, A., and Slavov, N. (2019) High-throughput single-cell proteomics quantifies the emergence of macrophage heterogeneity bioRxiv, doi: 10.1101/665307.
Google Scholar
Dou, M., Clair, G., Tsai, C.-F., Xu, K., Chrisler, W. B. Sontag, R. L., Zhao, R., Moore, R. J., Liu, T., Pasa-Tolic L., Smith, R. D., Shi, T., Adkins, J. N., Qian, W.-J., Kelly R. T., Ansong, C., and Zhu, Y. (2019) High-throughput single cell proteomics enabled by multiplex isobaric labeling in a nanodroplet sample preparation platform, Anal. Chem., 91, 13119–13127, doi: 10.1021/acs.analchem.9b03349.
CAS
PubMed
Article
Google Scholar
Zhu, Y., Piehowski, P. D., Zhao, R., Chen, J., Shen, Y. Moore, R. J., Shukla, A. K., Petyuk, V. A., CampbellThompson, M., Mathews, C. E., Smith, R. D., Qian, W.J., and Kelly, R. T. (2018) Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells, Nat. Commun., 9, 882, doi: 10.1038/s41467-018-03367-w.
PubMed
PubMed Central
Article
CAS
Google Scholar
Schoof, E. M., Rapin, N., Savickas, S., Gentil, C. Lechman, E., Haile, J. S., auf dem Keller, U., Dick, J. E. and Porse, B. T. (2019) A quantitative single-cell proteomics approach to characterize an acute myeloid leukemia hierarchy, bioRxiv, doi: 10.1101/745679.
Google Scholar
Johansson, H. J., Socciarelli, F., Vacanti, N. M., Haugen M. H., Zhu, Y., Siavelis, I., Fernandez-Woodbridge, A. Aure, M. R., Sennblad, B., Vesterlund, M., Branca, R. M. Orre, L. M., Huss, M., Fredlund, E., Beraki, E., Garred O., Boekel, J., Sauer, T., Zhao, W., Nord, S., Hoglander, E. K., Jans, D. C., Brismar, H., Haukaas, T. H., Bathen, T. F. Schlichting, E., Naume, B., Consortia Oslo Breast Cancer Research Consortium (OSBREAC), Luders, T., Borgen E., Kristensen, V. N., Russnes, H. G., Lingjærde, O. C. Mills, G. B., Sahlberg, K. K., Borresen-Dale, A.-L., and Lehtio, J. (2019) Breast cancer quantitative proteome and proteogenomic landscape, Nat. Commun., 10, 1600, doi: 10.1038/s41467-019-09018-y.
PubMed
PubMed Central
Article
CAS
Google Scholar
Dimitrakopoulos, L., Prassas, I., Diamandis, E. P. Nesvizhskii, A., Kislinger, T., Jaffe, J., and Drabovich, A. (2016) Proteogenomics: opportunities and caveats, Clin. Chem., 62, 551–557, doi: 10.1373/clinchem.2015.247858.
CAS
PubMed
Article
Google Scholar
Smith, L. M., Kelleher, N. L., and Consortium for Top Down Proteomics (2013) Proteoform: a single term describing protein complexity, Nat. Methods, 10, 186–187 doi: 10.1038/nmeth.2369.
CAS
PubMed
PubMed Central
Article
Google Scholar
Simoes, A. E., Pereira, D. M., Amaral, J. D., Nunes, A. F. Gomes, S. E., Rodrigues, P. M., Lo, A. C., D’Hooge, R. Steer, C. J., Thibodeau, S. N., Borralho, P. M., and Rodrigues, C. M. (2013) Efficient recovery of proteins from multiple source samples after Trizol® or Trizol®LS RNA extraction and long-term storage, BMC Genomics, 14, 181 doi: 10.1186/1471-2164-14-181.
CAS
PubMed
PubMed Central
Article
Google Scholar
Mun, D. G., Bhin, J., Kim, S., Kim, H., Jung, J. H., et al. (2019) Proteogenomic characterization of human earlyonset gastric cancer, Cancer Cell, 35, 111–124, doi: 10.1016/j.ccell.2018.12.003.
CAS
PubMed
Article
Google Scholar
Poirion, O., Zhu, X., Ching, T., and Garmire, L. X. (2018) Using single nucleotide variations in single-cell RNA-seq to identify subpopulations and genotype-phenotype linkage, Nat. Commun., 9, 4892, doi: 10.1038/s41467-01807170-5.
PubMed
PubMed Central
Article
CAS
Google Scholar
Levitsky, L. I., Kliuchnikova, A. A., Kuznetsova, K. G. Karpov, D. S., Ivanov, M. V., Pyatnitskiy, M. A., Kalinina O. V., Gorshkov, M. V., and Moshkovskii, S. A. (2019) Adenosine-to-inosine RNA editing in mouse and human brain proteomes, Proteomics, 19, e1900195, doi: 10.1002/pmic.201900195.
PubMed
Article
CAS
Google Scholar
Ximerakis, M., Lipnick, S. L., Innes, B. T., Simmons, S. K., Adiconis, X., Dionne, D., Mayweather, B. A., Nguyen L., Niziolek, Z., Ozek, C., Butty, V. L., Isserlin, R. Buchanan, S. M., Levine, S. S., Regev, A., Bader, G. D. Levin, J. Z., and Rubin, L. L. (2019) Single-cell transcriptomic profiling of the aging mouse brain, Nat. Neurosci.22, 1696–1708, doi: 10.1038/s41593-019-0491-3.
CAS
PubMed
Article
PubMed Central
Google Scholar