Cellular Heterogeneity: Do Differences Make a Difference?
Open accessAbstract
A central challenge of biology is to understand how individual cells process information and respond to perturbations. Much of our knowledge is based on ensemble measurements. However, cell-to-cell differences are always present to some degree in any cell population, and the ensemble behaviors of a population may not represent the behaviors of any individual cell. Here, we discuss examples of when heterogeneity cannot be ignored and describe practical strategies for analyzing and interpreting cellular heterogeneity.
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Even cells of the same type can exhibit substantial heterogeneity, reflecting finer sub-types, regulated functional variation, or inherent stochasticity.
“even cells of the same ‘type’ can exhibit substantial heterogeneity, reflecting finer sub-types, regulated functional variation, or inherent stochasticity1–6”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [6]
Differences in regenerative potential between stem cells are traditionally viewed as the result of differences in the characteristics of stable cell phenotypes.
“These differences in regenerative potential between stem cells are traditionally viewed as the result of differences in the characteristics of stable cell phenotypes (Altschuler and Wu, 2010; Blau et al., 2015; Chakkalakal et al., 2012).”
From Aging induces aberrant state transition kinetics in murine muscle stem cells (2020) · cites this paper as Altschuler and Wu, 2010
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Cites
Stochastic Gene Expression in a Single Cell
Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441 · see citing works
Bacterial Persistence as a Phenotypic Switch
Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L., & Leibler, S. (2004) · Science · doi:10.1126/science.1099390 · Cited by 2,952 · see citing works
A Chromatin-Mediated Reversible Drug-Tolerant State in Cancer Cell Subpopulations
Sharma, S. V., Lee, D. Y., Li, B., Quinlan, M. P., Takahashi, F., Maheswaran, S., McDermott, U., Azizian, N., Zou, L., Fischbach, M. A., et al. (2010) · Cell · doi:10.1016/j.cell.2010.02.027 · Cited by 2,770 · see citing works
Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences
Raj, A., & van Oudenaarden, A. (2008) · Cell · doi:10.1016/j.cell.2008.09.050 · Cited by 2,593 · see citing works
Wilson, A., Laurenti, E., Oser, G., van der Wath, R. C., Blanco-Bose, W., Jaworski, M., Offner, S., Dunant, C. F., Eshkind, L., Bockamp, E., et al. (2008) · Cell · doi:10.1016/j.cell.2008.10.048 · Cited by 1,908 · see citing works
Kimura, M., & Weiss, G. H. (1964) · Genetics · doi:10.1093/genetics/49.4.561 · Cited by 1,744 · see citing works
Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data
Sachs, K., Perez, O. D., Pe’er, D., Lauffenburger, D. A., & Nolan, G. P. (2005) · Science · doi:10.1126/science.1105809 · Cited by 1,724 · see citing works
Regulation of noise in the expression of a single gene
Özbudak, E. M., Thattai, M., Kurtser, I., Grossman, A. D., & van Oudenaarden, A. (2002) · Nature Genetics · doi:10.1038/ng869 · Cited by 1,559 · see citing works
Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise
Newman, J. R. S., Ghaemmaghami, S., Ihmels, J., Breslow, D. K., Noble, M., DeRisi, J. L., & Weissman, J. S. (2006) · Nature · doi:10.1038/nature04785 · Cited by 1,483 · see citing works
Control of Stochasticity in Eukaryotic Gene Expression
Raser, J. M., & O'Shea, E. K. (2004) · Science · doi:10.1126/science.1098641 · Cited by 1,425 · see citing works
Transcriptome-wide noise controls lineage choice in mammalian progenitor cells
Chang, H. H., Hemberg, M., Barahona, M., Ingber, D. E., & Huang, S. (2008) · Nature · doi:10.1038/nature06965 · Cited by 1,067 · see citing works
The Biochemical Basis of an All-or-None Cell Fate Switch in <i>Xenopus</i> Oocytes
Ferrell, J. E., & Machleder, E. M. (1998) · Science · doi:10.1126/science.280.5365.895 · Cited by 1,052 · see citing works
Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis
Spencer, S. L., Gaudet, S., Albeck, J. G., Burke, J. M., & Sorger, P. K. (2009) · Nature · doi:10.1038/nature08012 · Cited by 1,023 · see citing works
Somatic mosaicism in neuronal precursor cells mediated by L1 retrotransposition
Muotri, A. R., Chu, V. T., Marchetto, M. C. N., Deng, W., Moran, J. V., & Gage, F. H. (2005) · Nature · doi:10.1038/nature03663 · Cited by 942 · see citing works
Gascoigne, K. E., & Taylor, S. S. (2008) · Cancer Cell · doi:10.1016/j.ccr.2008.07.002 · Cited by 832 · see citing works
L1 retrotransposition in human neural progenitor cells
Coufal, N. G., Garcia-Perez, J. L., Peng, G. E., Yeo, G. W., Mu, Y., Lovci, M. T., Morell, M., O’Shea, K. S., Moran, J. V., & Gage, F. H. (2009) · Nature · doi:10.1038/nature08248 · Cited by 814 · see citing works
Ever-fluctuating single enzyme molecules: Michaelis-Menten equation revisited
English, B. P., Min, W., van Oijen, A. M., Lee, K. T., Luo, G., Sun, H., Cherayil, B. J., Kou, S. C., & Xie, X. S. (2005) · Nature Chemical Biology · doi:10.1038/nchembio759 · Cited by 790 · see citing works
Multidimensional Drug Profiling By Automated Microscopy
Perlman, Z. E., Slack, M. D., Feng, Y., Mitchison, T. J., Wu, L. F., & Altschuler, S. J. (2004) · Science · doi:10.1126/science.1100709 · Cited by 660 · see citing works
Self-citationInterchromosomal Interactions and Olfactory Receptor Choice
Lomvardas, S., Barnea, G., Pisapia, D. J., Mendelsohn, M. M., Kirkland, J., & Axel, R. (2006) · Cell · doi:10.1016/j.cell.2006.06.035 · Cited by 633 · see citing works
Losick, R. M., & Desplan, C. (2008) · Science · doi:10.1126/science.1147888 · Cited by 627 · see citing works
Increased cell-to-cell variation in gene expression in ageing mouse heart
Bahar, R., Hartmann, C. H., Rodriguez, K. A., Denny, A. D., Busuttil, R. A., Dollé, M. E. T., Calder, R. B., Chisholm, G. B., Pollock, B. H., Klein, C. A., et al. (2006) · Nature · doi:10.1038/nature04844 · Cited by 603 · see citing works
Dynamic Proteomics of Individual Cancer Cells in Response to a Drug
Cohen, A., Geva‐Zatorsky, N., Eden, E., Frenkel‐Morgenstern, M., Issaeva, I., Sigal, A., Milo, R., Cohen‐Saidon, C., Liron, Y., Kam, Z., et al. (2008) · Science · doi:10.1126/science.1160165 · Cited by 594 · see citing works
Phototransduction Motifs and Variations
Yau, K., & Hardie, R. (2009) · Cell · doi:10.1016/j.cell.2009.09.029 · Cited by 488 · see citing works
Boland, M. V., & Murphy, R. F. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.12.1213 · Cited by 483 · see citing works
Brock, A., Chang, H. H., & Huang, S. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2556 · Cited by 481 · see citing works
Breast Tumor Heterogeneity: Cancer Stem Cells or Clonal Evolution?
Campbell, L. L., & Polyák, K. (2007) · Cell Cycle · doi:10.4161/cc.6.19.4914 · Cited by 417 · see citing works
Structural Sources of Robustness in Biochemical Reaction Networks
Shinar, G., & Feinberg, M. (2010) · Science · doi:10.1126/science.1183372 · Cited by 413 · see citing works
Population context determines cell-to-cell variability in endocytosis and virus infection
Snijder, B., Sacher, R., Rämö, P., Damm, E.-M., Liberali, P., & Pelkmans, L. (2009) · Nature · doi:10.1038/nature08282 · Cited by 401 · see citing works
Heppner, G. H. (1984) · PubMed · Cited by 374 · see citing works
Jones, T. R., Carpenter, A. E., Lamprecht, M. R., Moffat, J., Silver, S. J., Grenier, J. K., Castoreno, A. B., Eggert, U., Root, D. E., Golland, P., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0808843106 · Cited by 368 · see citing works
Automated high-dimensional flow cytometric data analysis.
Pyne, S., Hu, X., Wang, K., Rossin, E. J., Lin, T., Maier, L. M., Baecher‐Allan, C., McLachlan, G. J., Tamayo, P., Hafler, D. A., et al. (2009) · PubMed · doi:10.1073/pnas.0903028106 · Cited by 293 · see citing works
Architecture-Dependent Noise Discriminates Functionally Analogous Differentiation Circuits
Çağatay, T., Turcotte, M., Elowitz, M. B., et al. (2009) · Cell · doi:10.1016/j.cell.2009.07.046 · Cited by 260 · see citing works
Protocadherin family: diversity, structure, and function
Morishita, H., & Yagi, T. (2007) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2007.09.006 · Cited by 214 · see citing works
Characterizing heterogeneous cellular responses to perturbations
Slack, M. D., Martínez, E. D., Wu, L. F., & Altschuler, S. J. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0807038105 · Cited by 159 · see citing works
Self-citationSingh, D. K., Ku, C., Wichaidit, C., Steininger, R. J., Wu, L. F., & Altschuler, S. J. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.22 · Cited by 125 · see citing works
Self-citationIdentification of long-range regulatory elements in the protocadherin-α gene cluster
Ribich, S. A., Tasic, B., & Maniatis, T. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609445104 · Cited by 112 · see citing works
CellClassifier: supervised learning of cellular phenotypes
Rämö, P., Sacher, R., Snijder, B., Begemann, B., & Pelkmans, L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp524 · Cited by 84 · see citing works
Loo, L., Lin, H.-J., Singh, D. K., Lyons, K. M., Altschuler, S. J., & Wu, L. F. (2009) · The Journal of Cell Biology · doi:10.1083/jcb.200904140 · Cited by 72 · see citing works
Self-citationAn approach for extensibly profiling the molecular states of cellular subpopulations
Loo, L.-H., Lin, H.-J., Steininger, R. J., Wang, Y., Wu, L. F., & Altschuler, S. J. (2009) · Nature Methods · doi:10.1038/nmeth.1375 · Cited by 69 · see citing works
Self-citationOutline of a theory of cellular heterogeneity.
Elsasser, W. M. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.16.5126 · Cited by 63 · see citing works
The significance of biological heterogeneity
Rubin, H. (1990) · Cancer Metastasis Review · doi:10.1007/bf00047585 · Cited by 53 · see citing works
Yin, Z., Zhou, X., Bakal, C., Li, F., Sun, Y., Perrimon, N., & Wong, S. T. C. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-264 · Cited by 49 · see citing works
Context based mixture model for cell phase identification in automated fluorescence microscopy
Wang, M., Zhou, X., King, R. W., & Wong, S. T. C. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-32 · Cited by 36 · see citing works
Single Cell Analysis Technologies and Applications
Anselmetti, D. (2009) · Cited by 25 · see citing works
Predicting and controlling the reactivity of immune cell populations against cancer
Oved, K., Eden, E., Akerman, M., Noy, R., Wolchinsky, R., Izhaki, O., Schallmach, E., Kubi, A., Zabari, N., Schachter, J., et al. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.15 · Cited by 15 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Duda RO Hart PE Stork DG Pattern Classification 2001 Interscience Wiley 2 edn
Cited by
Sorted by citations
Bray, M.-A., Singh, S., Han, H., Davis, C. T., Borgeson, B., Hartland, C., Kost-Alimova, M., Gustafsdottir, S. M., Gibson, C. C., & Carpenter, A. E. (2016) · Nature Protocols · doi:10.1038/nprot.2016.105 · Cited by 1,090 · see citing works
Data-analysis strategies for image-based cell profiling
Caicedo, J. C., Cooper, S., Heigwer, F., Warchal, S., Qiu, P., Molnar, C., Vasilevich, A. S., Barry, J. D., Bansal, H. S., Kraus, O., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4397 · Cited by 739 · see citing works
Revealing the vectors of cellular identity with single-cell genomics
Wagner, A., Regev, A., & Yosef, N. (2016) · Nature Biotechnology · doi:10.1038/nbt.3711 · Cited by 632 · see citing works
Bet Hedging in Yeast by Heterogeneous, Age-Correlated Expression of a Stress Protectant
Levy, S. F., Ziv, N., & Siegal, M. L. (2012) · PLoS Biology · doi:10.1371/journal.pbio.1001325 · Cited by 371 · see citing works
Lombard‐Banek, C., Moody, S. A., & Nemes, P. (2016) · Angewandte Chemie International Edition · doi:10.1002/anie.201510411 · Cited by 214 · see citing works
Murine single-cell RNA-seq reveals cell-identity- and tissue-specific trajectories of aging
Kimmel, J. C., Penland, L., Rubinstein, N. D., Hendrickson, D. G., Kelley, D. R., & Rosenthal, A. Z. (2019) · Genome Research · doi:10.1101/gr.253880.119 · Cited by 184 · see citing works
“…have important implications for cell physiology and function, as explored in seminal studies of transcriptional noise in cell fate selection (Blake et al. 2006; Süel et al. 2007) and bet hedging (Cohen 1966; Slatkin 1974; Kussell et al. 2005; Beaumont et al. 2009; Altschuler and Wu 2010).”
BackgroundZhu, H., Wang, N., Yao, L., Chen, Q., Zhang, R., Qian, J., Hou, Y., Guo, W., Fan, S., Liu, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.04.014 · Cited by 182 · see citing works
Connexins: Key Mediators of Endocrine Function
Bosco, D., Haefliger, J.-A., & Meda, P. (2011) · Physiological Reviews · doi:10.1152/physrev.00027.2010 · Cited by 169 · see citing works
SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells
Han, K. Y., Kim, K.-T., Joung, J.-G., Son, D.-S., Kim, Y. J., Jo, A., Jeon, H.-J., Moon, H.-S., Yoo, C. E., Chung, W., et al. (2018) · Genome Research · doi:10.1101/gr.223263.117 · Cited by 143 · see citing works
Zhu, H., Zou, G., Wang, N., Zhuang, M., Xiong, W., & Huang, G. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1615557114 · Cited by 133 · see citing works
Bai, X., Fisher, D. E., & Flaherty, K. T. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0204-6 · Cited by 107 · see citing works
Aging induces aberrant state transition kinetics in murine muscle stem cells
Kimmel, J. C., Hwang, A. B., Scaramozza, A., Marshall, W. F., & Brack, A. S. (2020) · Development · doi:10.1242/dev.183855 · Cited by 95 · see citing works
Han, L., Zi, X., Garmire, L. X., Wu, Y., Weissman, S. M., Pan, X., & Fan, R. (2014) · Scientific Reports · doi:10.1038/srep06485 · Cited by 83 · see citing works
Exploring single cells in space and time during tissue development, homeostasis and regeneration
Mayr, U., Serra, D., & Liberali, P. (2019) · Development · doi:10.1242/dev.176727 · Cited by 63 · see citing works
High-Dimensional Phenotyping Identifies Age-Emergent Cells in Human Mammary Epithelia
Pelissier Vatter, F. A., Schapiro, D., Chang, H., Borowsky, A. D., Lee, J. K., Parvin, B., Stampfer, M. R., LaBarge, M. A., Bodenmiller, B., & Lorens, J. B. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.114 · Cited by 58 · see citing works
Kimmel, J. C., Chang, A. Y., Brack, A. S., & Marshall, W. F. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005927 · Cited by 54 · see citing works
Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise
Hinczewski, M., & Thirumalai, D. (2014) · Physical Review X · doi:10.1103/physrevx.4.041017 · Cited by 30 · see citing works
Short-term cellular memory tunes the signaling responses of the chemokine receptor CXCR4
Spinosa, P. C., Humphries, B. A., Lewin Mejia, D., Buschhaus, J. M., Linderman, J. J., Luker, G. D., & Luker, K. E. (2019) · Science Signaling · doi:10.1126/scisignal.aaw4204 · Cited by 31 · see citing works
Pais, D. A. M., Galrão, P. R. S., Kryzhanska, A., Barbau, J., Isidro, I. A., & Alves, P. M. (2020) · Processes · doi:10.3390/pr8040487 · Cited by 25 · see citing works
Song, G., Wang, L., Tang, J., Li, H., Pang, S., Li, Y., Liu, L., & Hu, J. (2023) · Metabolomics · doi:10.1007/s11306-023-02002-0 · Cited by 25 · see citing works
Dumeaux, V., Massahi, S., Bettauer, V., Mottola, A., Dukovny, A., Khurdia, S. S., Costa, A. C. B. P., Omran, R. P., Simpson, S., Xie, J. L., et al. (2023) · eLife · doi:10.7554/elife.81406 · Cited by 25 · see citing works
A statistical framework for high-content phenotypic profiling using cellular feature distributions
Pearson, Y. E., Kremb, S., Butterfoss, G. L., Xie, X., Fahs, H., & Gunsalus, K. C. (2022) · Communications Biology · doi:10.1038/s42003-022-04343-3 · Cited by 19 · see citing works
“Whether such aggregate estimators are suf fi cient, or too simplistic for characterizing phenotypic responses to perturbations, is not yet established and may depend on the biological system in question 27 .”
Sailem, H. Z., Rittscher, J., & Pelkmans, L. (2020) · Molecular Systems Biology · doi:10.15252/msb.20199083 · Cited by 16 · see citing works
Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
Gurdon, B., Yates, S. C., Csucs, G., Groeneboom, N. E., Hadad, N., Telpoukhovskaia, M., Ouellette, A., Ouellette, T., O’Connell, K. M. S., Singh, S., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-06242-1 · Cited by 15 · see citing works
Pre-existing Cell States Control Heterogeneity of Both EGFR and CXCR4 Signaling
Spinosa, P. C., Kinnunen, P. C., Humphries, B. A., Luker, G. D., Luker, K. E., & Linderman, J. J. (2021) · Cellular and Molecular Bioengineering · doi:10.1007/s12195-020-00640-1 · Cited by 10 · see citing works
- Authors
- Altschuler, S. J., & Wu, L. F.
- Affiliations
- Harold C. Simmons Comprehensive Cancer Center (US)
- Corresponding author
- Altschuler, Steven J.
- Wu, Lani F.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2010-05
- Volume
- 141
- Issue
- 4
- Pages
- 559-563
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC2918286
- OpenAlex
- W1974934611
- Cited by
- 1,214
- References
- 45
- Citations by year
- 2026: 87 · 2025: 75 · 2024: 101 · 2023: 98 · 2022: 85 · 2021: 97 · 2020: 118 · 2019: 109 · 2018: 92 · 2017: 78 · 2016: 68 · 2015: 50 · 2014: 63 · 2013: 32 · 2012: 32
- FWCI
- 12.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 1209 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM081549, R01GM085442)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Keywords
- cellular heterogeneity, cell-to-cell variability, single-cell analysis, perturbation response
- MeSH terms
- Animals, Bacteria, Cells, Cytological Techniques, Drosophila
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