Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.

Bendall SC; Simonds EF; Qiu P; Amir el-AD; Krutzik PO; Finck R; Bruggner RV; Melamed R; Trejo A; Ornatsky OI; Balderas RS; Plevritis SK; Sachs K; Pe'er D; Tanner SD; Nolan GP

doi:10.1126/science.1198704

Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.

Bendall SC, Simonds EF, Qiu P, Amir el-AD ... Sachs K, Pe'er D, Tanner SD, Nolan GP Bendall SC, Simonds EF, Qiu P, Amir el-AD, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe'er D, Tanner SD, Nolan GP

Science. 2011 May 6; 332(6030):687-96

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19 May 2011

Recommended

Etienne Joly
F1000 Immunology
IPBS CNRS Université Paul Sabatier, Toulouse, France.

Technical Advance

DOI: 10.3410/f.10641956.11516057

I have never been so awed by a technological advance: in my eyes, mass cytometry is to fluorescence-activated cell sorting (FACS) analysis what a modern computer would be to a typewriter.

By labelling antibodies with chelated rare isotopes (such as Gd156, Yb171, Nd144 and Sm154) rather than with fluorophores, and by replacing the lasers and photodetectors of a FACS machine by a mass spectrometer, Gary Nolan's group manages to perform quantitative single cell analyses for 34 parameters in parallel, at a rate of 1000 cells per second, with no problems of background or of signal overlap: 13 cell surface markers (cluster of differentiation [CD] antigens), 18 intra-cellular epitopes (phosphoproteins), DNA content, viability and relative cell size. For this inaugural paper, they simply validate the technology by recording the responses of human bone marrow cells obtained from two healthy donors to a panel of 13 different stimulations. A new type of analysis called Spanning-tree Progression Analysis of Density-normalized Events (SPADE) is required to tackle the 34 dimensions of the mind-boggling results. SPADE generates a hierarchical clustering of the cell phenotypes, which reveals a distribution into a myriad of subpopulations along a tree drawn according to minimum spanning. All the cell types of the hematopoietic lineage can easily be mapped on that tree, and they go on to show that the obtained tree indeed follows the differentiation process of B cells and that this type of data can be extremely useful for identifying the cell types affected by a drug and the pathways involved (in this case a broad spectrum kinase inhibitor used in cancer treatment).

My overall impression from reading this paper is that, despite the breadth of the data (there are over 900 supplementary figures!), this is actually only the beginning and we have seen nothing yet. Many more antibodies could be used in parallel, especially if secondary reagents of the Zenon type were to become available, and the coupling of a FACS upstream of the mass cytometer would certainly be a rather straightforward implementation that would allow us to record forward scatter (FSC) and side scatter (SSC) parameters and additional fluorescent-based signals, as well as to study very rare events without recording the data for all cells. However, no matter what software is developed to analyse the data, the rate-limiting factor already is, and will remain, the availability of brains to tackle such heaps of data.

Disclosures

None declared

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Joly E: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 19 May 2011; DOI: 10.3410/f.10641956.11516057. F1000Prime.com/10641956#eval11516057

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20 May 2011

Recommended

Linheng Li
F1000 Hematology
Stowers Institute for Medical Research, Kansas City, MO, USA.

Technical Advance

DOI: 10.3410/f.10641956.11536054

This study established a novel technology to analyze protein expression and signal transduction at the single-cell level.

In this proof-of-principle study, Bendall et al. established a novel technology of protein expression profiling at the single-cell level. They used a CyTOF mass cytometer to analyze human bone marrow cells that were labeled with 31 antibodies. The antibodies were conjugated with rare earth elements, which allowed clear separation of more than 30 signals without background autofluorescence. Mass cytometry combines the best of cytometry and mass spectrometry, and this is what the authors used to analyze expression of surface markers and phosphorylated signaling molecules in rare cell populations, such as hematopoietic stem cells. Compared with fluorochrome-based flow cytometry, which can separate up to 10 signals, mass cytometry has a significant advantage for single-cell analysis. The advance of single-cell technology including polymerase chain reaction (PCR) and staining has enabled researchers to obtain data about signaling pathways in rare cell populations. However, so far, it has been very difficult to obtain comprehensive data about gene and protein expression. Mass cytometry represents a breakthrough in stem cell biology where there is a limited cell number. With this technology, stem cell biologists can analyze details of signal transduction as well as novel surface markers in rare stem cell populations.

Acknowledgments

Ryohichi Sugimura

Disclosures

None declared

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Li L: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 20 May 2011; DOI: 10.3410/f.10641956.11536054. F1000Prime.com/10641956#eval11536054

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27 May 2011

Recommended

Markus Feuerer
F1000 Immunology
German Cancer Research Center (DKFZ), Heidelberg, Germany.

David Richards
F1000 Immunology
German Cancer Research Center (DKFZ), Heidelberg, Germany.

New Finding, Technical Advance

DOI: 10.3410/f.10641956.11681054

In this groundbreaking paper, the authors describe a novel technique, which they trademark CyTOF, that combines aspects of flow cytometry and mass spectrometry (MS) to monitor 30-100 parameters simultaneously on a single-cell level.

Although many flow cytometers can detect between 11 to 15 markers, most investigators are limited to 6 to 10 due to the spectral overlap between colors. With CyTOF, the fluorochromes are replaced by a series of rare earth elements, attached to antibodies through metal-chelator coupling reagents. The antibody labeled single-cell suspension is loaded into the machine, the cells flow through the instrument, are vaporized at 5500K, and the released tags are identified and quantified by time-of-flight MS.

The main advantage of this technique is obviously the large number of markers that can be simultaneously examined, here 34, and they claim it could be easily increased to over 100. This is mainly due to the precision of MS detection, which eliminates overlap between tags and the absence of background noise (there is no equivalent of “autofluorescence”).

The main limitation of this technique is the inability to physically sort cells. Additionally, there is currently a 1000 cell per second limit, no forward scatter (FSC) or side scatter (SSC) equivalents, and lower sensitivity compared to some fluorescent markers. Finally, the massive amount of data this technique generates will require new methods for analysis. The authors state that traditional analysis of these 31 surface markers would require greater than 450 biaxial dot plots. Even with interesting new analytical techniques described in the paper, there are over 900 pages of supplemental figures!

Overall, this is an exciting new technology that will allow for fast-paced examination of a large number of targets on a single-cell level, with the potential to discover and describe previously unrecognized sub-phenotypes of cell lineages.

Disclosures

None declared

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Feuerer M and Richards D: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 27 May 2011; DOI: 10.3410/f.10641956.11681054. F1000Prime.com/10641956#eval11681054

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31 May 2011

Recommended

Caetano Reis e Sousa
F1000 Immunology
London Research Institute, Cancer Research UK, London, UK.

Barbara Schraml
F1000 Immunology
London Research Institute, Cancer Research UK, London, UK.

Technical Advance

DOI: 10.3410/f.10641956.11758059

This paper uses an exciting novel technique combining flow cytometry and mass spectrometry (mass cytometry) to investigate the signalling behaviour of single cell populations in normal human bone marrow.

Mass cytometry is a technique that replaces fluorochrome-tagged antibodies, used in flow cytometry, with antibodies coupled to rare earth elements. Like in flow cytometry, cells are stained with a cocktail of labelled antibodies; however, as cells pass through the machine they are vaporized. The rare earth metal tags are then released from the cell and identified by time-of-flight-mass spectrometry. Using this technique, the authors were able to examine 34 parameters simultaneously in single cells from human bone marrow.

The biggest advantage of mass cytometry over flow cytometry is the absence of spectral overlap between the rare earth metals, thus eliminating the need for compensation. However, since cells are vaporized in mass cytometry they cannot be recovered for further analysis. The amount of data generated in a single experiment requires computerized data analysis allowing for unbiased gating and potentially allowing for more refined analyses. For instance Bendall et al. suggest that populations previously considered homogenous, such as naïve T cells, might in fact be phenotypically heterogeneous. It will also be important to discuss appropriate controls for staining specificity over non-specific antibody binding. In conclusion, this is an exciting new technique in its infancy that opens new doors to refining the analysis of cell populations and their signalling behaviours.

Disclosures

None declared

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Reis e Sousa C and Schraml B: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 31 May 2011; DOI: 10.3410/f.10641956.11758059. F1000Prime.com/10641956#eval11758059

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01 Jun 2011

Recommended

Toshihiro Nakajima
F1000 Rheumatology & Clinical Immunology
Tokyo Medical University, Tokyo, Japan.

Satoko Aratani
F1000 Rheumatology & Clinical Immunology
Tokyo Medical University, Tokyo, Japan.

Technical Advance

DOI: 10.3410/f.10641956.11628057

This article introduces a new technology for studying the immune system: single cell mass cytometry.

Current flow cytometry is an essential tool for the study of the immune system. However, use of fluorescence-based flow cytometry remains confined to the measurement of 10 simultaneous parameters. In contrast, mass cytometry can measure 34 parameters simultaneously in each single cell. This system allows for an algorithmically driven assembly of related cell types defined by surface antigen expression and cell signaling by intracellular molecules. It could also provide system-wide views of immune signaling in normal cells, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention. This new technology could be useful for studying entire pathways in cells.

Disclosures

None declared

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Cite this Recommendation

Nakajima T and Aratani S: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 01 Jun 2011; DOI: 10.3410/f.10641956.11628057. F1000Prime.com/10641956#eval11628057

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01 Jun 2011

Recommended

Donna Farber
F1000 Immunology
Columbia University Medical Center, New York, NY, USA.

Naomi Yudanin
F1000 Immunology
Columbia University Medical Center, New York, NY, USA.

Confirmation, Technical Advance

DOI: 10.3410/f.10641956.11745054

The authors have developed a new multiparameter approach, termed 'mass cytometry', for identifying discrete lineages and phenotypes of cell populations and tracing their progression during differentiation. Compared to conventional fluorescence-based flow cytometry, mass cytometry vastly increases the number of parameters that can be measured in single cells, up to 100 parameters per cell. This method also uses a frequent sequence-mining algorithm, spanning-tree progression analysis of density-normalized events (SPADE), to parse the data in a way that results in a clearer and more useful presentation of information than traditional dot plots. This technology provides a novel approach to study cell-environment interaction with an unprecedented level of resolution.

The authors present a novel technique for multi-parameter cellular analysis that combines the elements used in atomic mass spectrometry with flow cytometry-based analysis. Fluorescence-based flow cytometry is the gold standard for analysis of cellular immunology, but it is limited by the number of parameters that can be evaluated simultaneously. The authors have overcome this limit by using antibodies labelled with transition element isotopes not found in organic systems. These elements allow for simultaneous measurement of as many as 100 parameters per cell. By using these unique tags with a mass spectrometry system, they eliminated the spectral overlap and auto-fluorescence of dead cells frequently seen when using fluorescent antibodies. This led to a more precise characterization of their cell line of interest. The authors also applied a frequent sequence-mining algorithm, SPADE, to enable coordinate analysis of surface-expressed molecular markers, intracellular cell signaling pathways, and functional output.

As an example of the utility and power of mass spectrometry, the authors measured 34 parameters in each single cell of a human bone marrow sample. SPADE was used to analyze the data and cluster the cells into phenotypically similar groups determined by core surface markers. The authors then examined 13 surface markers most definitive of immune cell types and 18 intracellular markers to probe intracellular signalling pathways in healthy human bone marrow. The signalling response to 13 stimulation conditions, including some implicated in cancer, was surveyed and synopsized in a heat map. These results provide evidence of correlations between intracellular signalling events and surface marker-defined limits. Using this system, it will be possible to study the development of multiple immune cell lineages and to identify how variations in cell physiology relate to their development. Mass cytometry provides an exciting and powerful approach to deepen our understanding of immune system disorders by simultaneously analysing biochemical, functional, and differentiation pathways in a single cell. For further reading, see reference {1}.

References

SPADE: An Efficient Algorithm for Mining Frequent Sequences.

Zaki MJ Mach Learn 2001; 42:31-60 DOI:10.1023/A:1007652502315.

Disclosures

None declared

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Cite this Recommendation

Farber D and Yudanin N: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 01 Jun 2011; DOI: 10.3410/f.10641956.11745054. F1000Prime.com/10641956#eval11745054

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09 Jun 2011

Recommended

Frank Nestle
F1000 Dermatology
King's College London School of Medicine, London, UK.

Federica Villanova
F1000 Dermatology
King's College London School of Medicine, London, UK.

Technical Advance

DOI: 10.3410/f.10641956.12012058

I found this article interesting because it describes a new technology – mass cytometry – for the simultaneous analysis of many cellular parameters at a single cell level, overcoming some of the limitations of classic fluorescence-based flow cytometry. Mass cytometry uses transitional element isotypes, instead of fluorochromes, to label antibodies. Cells are then vaporized and analyzed by a time-of-flight (TOF) mass spectrometer. There is no need for compensation and there is no cell autofluorescence, allowing the detection of up to 100 parameters at the same time. In addition, this article reaches a new level of complexity for the analysis of healthy human bone marrow cells and introduces a new method to analyze and visualize multidimensional single-cell data.

Firstly, Bendall et al. compared mass cytometry and traditional flow cytometry, showing that the two techniques provide comparable information, although mass cytometry has the advantage of an increased dimensionality. Using mass cytometry, the authors simultaneously analysed 34 parameters in two samples of human bone marrow mononuclear cells. They designed an 'immunophenotyping' panel and a 'functional' panel, both sharing 13 core surface markers plus 18 different markers for specific cell subsets or intracellular epitopes, respectively. The cells were perturbed with a set of ex vivo stimuli and inhibitors, including those relevant in pathologies such as leukaemias and their treatment (e.g. dasatinib). This resulted in a detailed phenotypic and functional analysis of the hematopoietic cells, from progenitors to lineage-committed ones. The complex data set was analyzed and visualized by spanning-tree progression analysis of density-normalized events (SPADE), an algorithm that transforms the data into interconnected clusters of phenotypically similar cells (nodes). Using such analytic tool, bone marrow cells were displayed in a 2D tree plot showing different hematopoietic cell types and their signaling. This analysis revealed previously unappreciated cell subsets and signaling responses.

Taken together, this paper shows the importance of studying the immune system via a multidimensional approach. Mass cytometry is an excellent tool to study immunology in a highly multiplexed single-cell manner. As mass cytometry cells are destroyed during the analytical process, flow and mass cytometry should be complementary in the near future to further elucidate the phenotype and function of immune cells in health and disease.

Disclosures

None declared

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Nestle F and Villanova F: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 09 Jun 2011; DOI: 10.3410/f.10641956.12012058. F1000Prime.com/10641956#eval12012058

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27 Jul 2011

Recommended

Burckhard Seelig
F1000 Chemical Biology
University of Minnesota, Minneapolis, MN, USA.

Misha Golynskiy
F1000 Chemical Biology
University of Minnesota, Minneapolis, MN, USA.

Technical Advance

DOI: 10.3410/f.10641956.13234055

This publication pioneers an impressive application of 'mass cytometry' to simultaneously monitor over thirty intra- and extra-cellular events in human bone marrow. Unlike traditional flow cytometry that is limited by spectral resolution between fluorophores, antibodies are instead labelled with unique elemental isotopes. While mass cytometry is an inherently destructive method, it seems particularly well suited for tracking multiple biomarkers and studying pathways. It is thus poised to make a significant impact in many fields.

It would be interesting to see a tandem application of traditional flow cytometry with mass cytometry to further increase the maximum number of events that could be examined simultaneously.

Disclosures

None declared

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Cite this Recommendation

Seelig B and Golynskiy M: F1000Prime Recommendation of [Bendall SC et al., Science 2011, 332(6030):687-96]. In F1000Prime, 27 Jul 2011; DOI: 10.3410/f.10641956.13234055. F1000Prime.com/10641956#eval13234055

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Comment by: Etienne Joly, IPBS CNRS Université Paul Sabatier
Evaluator | 07 Jun 2011, 7:21 PM

You're absolutely right, this is exactly what I meant. Thank you for spotting this.

Disclosures: None declared.

Comment by: Ryan Duggan, University of Chicago
06 Jun 2011, 6:45 PM

"...mass cytometry is to fluorescence-activated cell sorting (FACS) analysis what a modern computer would be to a typewriter." Not so fast. Mass cytometry will never be able to sort seeing as the cells are completely ionized and therefore cannot be recovered for down-stream processing. You probably mean to compare it to flow cytometry, not FACS.

Disclosures: None declared.

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Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell "mass cytometry" to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.

DOI: 10.1126/science.1198704

PMID: 21551058

Abstract courtesy of PubMed: A service of the National Library of Medicine and the National Institutes of Health.

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