Journal of Immunological Methods - elsevierscitech.com · a,b,⁎, Dmitry Banduraa,b, Vladimir...

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Journal of Immunological Methods xxx (2010) xxx–xxx

Q1

JIM-11115; No of Pages 20

Contents lists available at ScienceDirect

Journal of Immunological Methods

j ourna l homepage: www.e lsev ie r.com/ locate / j im

Review

Highly multiparametric analysis by mass cytometry

Olga Ornatsky a,b,⁎, Dmitry Bandura a,b, Vladimir Baranov a,b, Mark Nitz a,Mitchell A. Winnik a, Scott Tanner a,b

a Department of Chemistry, University of Toronto, 80 St. George St., Toronto ON, Canada M5S 3H6b DVS Sviences Inc., 70 Peninsula Cr., Richmond Hill ON, Canada L4S 1Z5

a r t i c l e i n f o

⁎ Corresponding author.E-mail address: [email protected] (O. Orn

0022-1759/$ – see front matter © 2010 Elsevier B.V.doi:10.1016/j.jim.2010.07.002

Please cite this article as: Ornatsky, O., et adoi:10.1016/j.jim.2010.07.002

a b s t r a c t

Article history:Received 29 January 2010Accepted in revised form 6 May 2010Accepted 8 July 2010Available online xxxx

This review paper describes a new technology, mass cytometry, that addresses applicationstypically run by flow cytometer analyzers, but extends the capability to highly multiparametricanalysis. The detection technology is based on atomic mass spectrometry. It offers quantitation,specificity and dynamic range of mass spectrometry in a format that is familiar to flowcytometry practitioners. The mass cytometer does not require compensation, allowing theapplication of statistical techniques; this has been impossible given the constraints offluorescence noise with traditional cytometry instruments. Instead of “colors” the masscytometer “reads” the stable isotope tags attached to antibodies using metal-chelating labelingreagents. Because there are many available stable isotopes, and the mass spectrometerprovides exquisite resolution between detection channels, many parameters can be measuredas easily as one. For example, in a single tube the technique allows for the ready detection andcharacterization of the major cell subsets in blood or bone marrow. Here we describe masscytometric immunophenotyping of human leukemia cell lines and leukemia patient samples,differential cell analysis of normal peripheral and umbilical cord blood; intracellular proteinidentification and metal-encoded bead arrays.

© 2010 Elsevier B.V. All rights reserved.

Keywords:Mass cytometryMetal-tagged antibodiesMetal-encoded beadsMultiparametric single cell assayFlow cytometryBead arrayImmunophenotype

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02. Materials and methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

2.1. Antibodies and reagents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.2. Cell samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

2.2.1. Human leukemia and pancreatic cell lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.2.2. Bone marrow, peripheral blood and umbilical cord mononuclear cells . . . . . . . . . . . . . . . . . . . . . 02.2.3. Leukemia patient samples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

2.3. Sample preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.3.1. Antibody conjugation to metal-containing polymer tags . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.3.2. Cell surface immunostaining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.3.3. Intracellular immunostaining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.3.4. Nucleic acid staining with metal-containing intercalators . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

2.4. Metal-encoded beads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.4.1. Bead synthesis and characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.4.2. Metal encoding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

atsky).

All rights reserved.

l., Highly multiparametric analysis by mass cytometry, J. Immunol. Methods (2010),

http://dx.doi.org/10.1016/j.jim.2010.07.002

mailto:[email protected]


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2 O. Ornatsky et al. / Journal of Immunological Methods xxx (2010) xxx–xxx

2.5. Mass cytometer and data processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.5.1. Instrument description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.5.2. Ion detection and signal handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02.5.3. Data processing for cell event detection and integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

3. Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 03.1. Antibody titration and quantitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 03.2. Multiparametric analysis of cell biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

3.2.1. Normal blood mononuclear cell (PBMc, CB, HSC) surface markers . . . . . . . . . . . . . . . . . . . . . 03.2.2. Leukemia cell line surface markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 03.2.3. Leukemia patient cell type sub-classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 03.2.4. Intracellular antigen analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

3.3. Live/dead cell discrimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 03.4. Analysis of metal-encoded beads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

3.4.1. Optimal metal loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 03.4.2. Construction of large metal-encoded bead libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 03.4.3. Metal-encoded bead bioassays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Conflict-of-interest disclosure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

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1. Introduction

Multiparametric analysis of individual cells by flowcytometry has become the method of choice for functionaland immunophenotypic analysis of cells in heterogeneouspopulations, particularly in the diagnosis of hematologicalmalignancies (Jennings and Foon, 1997; Kern et al., 2004;Pedreira et al., 2008; Perfetto and Roederer, 2004; Terstappenet al., 1992; Wood et al., 2007). In traditional flow cytometry,a cell sample is treated with a panel of antibodies, each typelabeled with a different fluorescent dye. The cell suspension,at an appropriate dilution, is then introduced into theinstrument in such a way that individual cells are registeredas they pass through a laser excitation region, withsimultaneous detection of their fluorescence emission. Mul-tiple lasers provide excitation of the different dyes at differentwavelengths, and multiple detectors capture light scatteringand fluorescent signals from the immunostained cells.

Unambiguous identification of cell populations in hetero-geneous samples such as blood, bonemarrow or tumor biopsyrequires quantitative determination of many biomarkerssimultaneously in individual cells (Chattopadhyay et al.,2008; Wood, 2007; Weir and Borowitz, 2001; Autissier et al.,2010). Current flow cytometers are generally limited to 10simultaneous measurements. However, in the research labo-ratory, polychromatic flow cytometry has reached the level ofmultiplexing 17 different antigens (Perfetto et al., 2004).While this is an impressive and important step forward, thepotential of fluorophore-based highly multiplexed assays iscomplicated by challenges inherent in fluorescence detection.The emission bands of fluorescent dyes are sufficiently broadthat spectral overlap is inevitable when one makes simulta-neous measurements with multiple dyes. Quantum dots havemore narrow emission bands, especially at shorter wave-lengths, which mitigates but does not eliminate the problem(Roederer et al., 2004; Chattopadhyay et al., 2006). As aconsequence, complex correction algorithms are needed todeconvolute the overlapped spectra. Furthermore, this type ofcompensation requires a large number of control samples

Please cite this article as: Ornatsky, O., et al., Highly multiparametdoi:10.1016/j.jim.2010.07.002

stained in multiple antibody combinations to optimize theassay (McLaughlin et al., 2008).

To address the increasing need for multiparametricanalysis, the method of simultaneous detection of multipleproteins in acidified biological samples by inductivelycoupled mass spectrometry (ICP-MS) using metal-taggedantibodies, was first suggested and demonstrated by Baranovet al. (Baranov et al., 2002; Quinn et al., 2002) and furtherinvestigated by several groups (Careri et al., 2007; Zhanget al., 2002; Zhang et al., 2004; Bettmer et al., 2006; Careri etal., 2009). ICP-MS is a tool designed for the analysis ofelements and is widely used in applications (mining andmetallurgy, the semiconductor industry), which demandprecise quantitation of element abundance. In ICP-MS,samples are atomized and ionized in plasma at temperaturesapproximating that of the surface of the sun (7000 K). Themass spectrometer then resolves and quantifies the variouselement isotopes. Key features of traditional ICP-MS instru-mentation include the absence of interference betweenmasses and a linear dynamic range of greater than 108

(Tanner et al., 2007).However, this technique could not be applied to multi-

target analysis of individual intact cells for several reasons.Firstly, the quadrupolemass analyzermost common in ICP-MS,has a settling time of ~50–200 μs, required for stabilization ofthe mass filter between individual isotopemeasurements. Thistime is comparable to the duration of the ion cloud produced inthe argon plasma from an individual microparticle or cell(Stewart and Olesik, 1999). Thus, the measurement of two ormore isotopes during a transient event of such short duration isvirtually impossible with available quadrupole mass spectro-meters. The required frequency of sampling of the cell-inducedtransient should be 50,000–100,000 spectra/s, to allow for tenor more individual spectra per cell so that the transients fromoverlapping particles can be discriminated. Thus, a new type ofinstrument is required to interrogate individual cells (Tanneret al., 2008).

In the ICP-MS solution bioassays that we have reported(Ornatsky et al., 2006; Baranov et al., 2002) directed at

ric analysis by mass cytometry, J. Immunol. Methods (2010),


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immunophenotyping human leukemia cell lines, variousantibodies were labeled with different lanthanides, witheachmetal serving as an element tag for a particular antibody.We focus on the lanthanide (Ln) series of elements because ofthe large number of stable resolvable isotopes having similarchemistry that facilitates their incorporation into the sametag structure. Lanthanides have low natural abundance, thusexhibiting a very low background signal in this type ofanalysis. In these experiments, we attached metal-chelatingpolymers to the antibodies to increase the signal associatedwith each sample. Each polymer carried about 30 atoms of alanthanide element, with several polymers attached to eachantibody. The large dynamic range was demonstrated by theability to quantify cell surface markers that differed inabundance by a factor of 500 in a single multiplexed assayof KG1a cells (Lou et al., 2007). Here we report a major stepforward with the extension of this methodology to cell-by-cell analysis using a mass cytometer (CyTOFTM), and metal-containing polymer tags (MAXPARTM) both from DVSSciences Inc., Richmond Hill, Canada. The instrument isbased on a non-optical physical principle of detection and adifferent chemical nature of labels. The fluorescent labels arereplaced by specially designedmulti-atom elemental tags anddetection takes advantage of the high resolution, sensitivity,and speed of analysis of Time-of-Flight Mass Spectrometry(TOF-MS). Sincemany available stable isotopes can be used astags, many proteins and gene transcripts can potentially bedetected simultaneously in individual cells.

In this review, we describe the basic principles of the masscytometry instrumentation, elemental tags, and linked immu-nological methods using as an example highly multiplex (over20 antibodies in one mixture) assays applied both to culturedhuman leukemia cell lines and patient samples. The results arecompared to those of traditionalfluorescence-based cytometricanalysis. Furthermore, we outline the next steps in thedevelopment of bead-array technology: synthesis, character-ization and application of metal-encoded beads as masscytometry standards and for bead arrays. Mass cytometry canbe scaled to higher multiplicity with the development of abroader array of elemental tags. The simplicity and efficiency ofthe approach demonstrate the potential of mass cytometry forbiological research and drug development.

2. Materials and methods

2.1. Antibodies and reagents

Primary monoclonal and polyclonal antibodies to cellsurface and intracellular antigens were obtained fromcommercial suppliers (BD Biosciences, San Jose, CA;BioLegend, San Diego, CA; Abcam Inc., Cambridge, MA;Cell Signaling Technology Inc, Danvers, MA.; Santa Cruz;Biotechnology Inc., Santa Cruz, CA; Millipore, Billerica, MA).All antibodies were bought as affinity purified salinesolutions without stabilizing proteins. Species-specificisotype immunoglobulins were used for negative controls.Antibodies were labeled with the MAXPAR™ reagents (DVSSciences, Richmond Hill, Canada; www.DVSsciences.com),based on metal-conjugated polymer tags. Hydrochloridecomplexes of La, Pr, Tb, Ho, and Tm (Sigma-Aldrich) wereused as these elements have a single high abundant


isotope. Oxides of the enriched (N98%) isotopes (142Nd,144Nd, 145Nd, 146Nd, 150Nd, 147Sm, 152Sm, 154Sm, 151Eu,153Eu, 156Gd, 158Gd, 160Gd, 164Dy, 166Er, 167Er, 168Er, 170Er,171Yb, 172Yb, 174Yb, 175Lu, 176Yb) (Trace Sciences Interna-tional Corp., Richmond Hill, Canada) were converted intosalts for use in the labeling protocols.

Assay reagents were obtained from commercial sources:phosphate-buffered saline (PBS) without calcium andmagnesium, 37% formaldehyde, Triton X-100 (Sigma-Aldrich, Oakville, Canada); concentrated 34% HCl (Baseline,Seastar Chemicals Inc., Sidney, BC, Canada.); methanol-free16% formaldehyde solution and TCEP (tris(2-carboxyethyl)phosphine hydrochloride) (Pierce Thermo, Rockford, IL).Instrument tuning solutions were prepared by sequentialdilution of the all-lanthanide standard (PE Pure PlusMultielement Calibration Standard 2, PerkinElmer Instru-ments, Shelton, CT) or single-element standards (SpexCertiPrep, Metuchen, NJ) in 2% HNO3 [Baseline, SeastarChemicals Inc., Sidney, BC, Canada] in deionized water(DIW) (Elix/Gradient water purification system, Millipore).

2.2. Cell samples

2.2.1. Human leukemia and pancreatic cell linesModel cell lines of different types of human acute myeloid

leukemia (KG1a, THP-1, HL-60, and U937), B-lymphoblastoidleukemia (Ramos) and acute T-cell leukemia (Jurkat) wereused for biomarker analysis and validation of metal-taggedantibodies. Panc-1 cells, representative of pancreatic carci-noma, were used to demonstrate intracellular antigenanalysis. Cells were obtained from the American Type CultureCollection (ATCC, Manassas, VA) and propagated understandard tissue culture conditions.

2.2.2. Bone marrow, peripheral blood and umbilical cordmononuclear cells

Samples of umbilical cord blood (CB) were obtainedaccording to procedures approved by the institutional reviewboard of Trillium Hospital (Mississauga, Ontario) and Univer-sity Health Network (UHN Toronto, Canada). Peripheral bloodand bone marrow were obtained from healthy volunteers atUHN. All sampleswere collected in heparin and centrifuged onFicoll-Hypaque (Pharmacia, Uppsala) to isolate mononuclearcells (PBMc and BM). Residual red blood cells were lysed withammonium chloride when necessary (Stem Cell Technologies,BC, Canada). Isolation of HSC from CB samples was performedas described (Guenechea et al., 2001). In brief, lineagedepletion (Lin−) and CD34+ enrichment were achieved bynegative selectionwith the StemSep™ system according to themanufacturer's protocol (Stem Cell Technologies, Vancouver,Canada). The antibody cocktail that was used removes cellsexpressing glycophorin A, CD2, CD3, CD14, CD16, CD19, CD24,CD41, CD56 and CD66b. The efficiency of primitive CD34+ cellenrichment, as determined by flow cytometric assessment,was 55–78%. Lin− cells were stored at −170 °C in 10% DMSOand 40% fetal bovine serum (Cansera, Rexdale, Canada).

2.2.3. Leukemia patient samplesBlood or bone marrow samples corresponding to acute

myeloid or lymphoid leukemia subtypes were collected frompatients on diagnosis at the Princess Margaret Hospital (PMH,


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Fig. 1. A schematic of the drawing of the chemical structure of a metal-containing polymer tag and labeled Ab.


Toronto, Canada) following research ethics board (REB)approved consent. The samples were stored in a viable stateat −170 °C. Frozen samples were marked only by a uniqueidentifier number. The work up of patients involved a historyand physical examination, peripheral blood assessment and abone marrow aspirate for morphology, flow cytometricanalysis, cytogenetic and molecular studies. Five frozensamples of mononuclear cells from bone marrowcorresponding to acute monoblastic/monocytic leukemiasubtype M5 were a generous gift from the Quebec LeukemiaCell Bank (http://www.bclq.gouv.qc.ca).

For immunostaining, the frozen cells were rapidly thawedin a 37 °C water bath and immediately diluted in mediumwith 40% FBS, pre-warmed to 37 °C. Cell viability andnumbers were obtained from the Vi-CellTM (Beckman CoulterInc., Fullerton, CA) automated cell counter. All samples wereat least 82% viable (Trypan blue-excluding cells). The cellswere centrifuged and incubated for 60 min in cell growthmedia at 37 °C for metabolic recovery.

2.3. Sample preparation

Cultured human cell lines were used for cell surfacestaining after washing once in PBS. Frozen leukemia patientsamples and isolatedmononuclear cells from peripheral adultblood and umbilical cord blood were stained after thawingand recovery in warm media. Sample preparation for themultiplexed analyses by mass cytometry begins with theconjugation of antibodies to elemental tags.

2.3.1. Antibody conjugation to metal-containing polymer tagsAn example of polymer tags bearing chelated metals has

been reported (Lou et al., 2007). The MAXPARTM tag isproduced by a proprietary method, but the overall structure issimilar. A schematic of the metal-containing polymer tag andlabeled Ab conjugate (Ab–Ln) is shown in Fig. 1. Briefly, anacrylic acid polymer having low chain-length dispersity isfunctionalized with NHS reactive groups. Functionalized DTPA(1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) isattached to these groups. An end-terminal thiol of the polymerchain allows linkage to bismaleimide which in turn attachesthe polymer to reduced thiols in the Fc fragment of theantibody. An antibody solution at a concentration N1 mg/mLand in the absence of bovine serum albumen (BSA) or gelatinis subjected to mild reduction using TCEP to convert thedisulfides to thiols. A solution of an isotopically enrichedlanthanide is added to the Ab–polymer conjugate andincubated for 30 min. The metal-tagged Ab–Ln is washedseveral times in a centrifugation filter device and stored for upto tenmonths at+4 °C. The strong chelation of the lanthanideby DTPA is resistant to leaching and there is no exchangebetween the differently tagged Abs in the multiple antibodystaining cocktail (Lou et al., 2007).

2.3.2. Cell surface immunostainingA master mix containing saturating amounts of all

element-tagged antibodies (0.5–2 μg/mL each) was preparedin 1% BSA/PBS and incubated with live cells for 30 min.Washed cells were fixed (2% formaldehyde) and incubatedwith the Ir-intercalator for nuclear staining (see below).Following several washes, the pelleted cells were resuspended


in a low salt buffer at 1×106cells/mL and analyzed by masscytometry. Data in FCS 3.0 format were used for cellpopulation analysis with FlowJoTM software (TreeStar Inc.,Ashland, OR).

2.3.3. Intracellular immunostainingFollowing surface staining of live cells, samples were fixed

in 1.6% formaldehyde and permeabilized in cold 80% ethanolor 100% methanol. Prior to staining with Ab–Ln againstintracellular antigens, non-specific binding groups wereblocked with 5% BSA/PBS for 1 h on ice. The Ab–Ln cocktailwas added to pelleted cells for at least 1 h on ice.

2.3.4. Nucleic acid staining with metal-containing intercalatorsNumerous studies have been devoted to the investigation

of binding of transition-metal polypyridyl complexes withDNA molecules (Chen et al., 1997; Chow and Barton, 1992).The reagents are indefinitely stable in the solid state and inaqueous solution. The synthesis and application of two suchstaining reagents [(1) Rhodium(III) Rh-intercalator (bis(phenanthrenequinone diimine)(bipyridyl)) and (2) Iridium(III) Ir-intercalator (pentamethylcyclopentadienyl-Iridium(III)-dipyridophenazine)] have been previously reported(Ornatsky et al., 2008b). Fig. 2 depicts their chemicalstructures. Stained and fixed/permeabilized cells were incu-bated in 250 nM Ir-intercalator or 800 nM Rh-intercalatorsolutions (1 mL per 1 million cells) and washed with PBS. Formass cytometry analysis, metallointercalator tagging of thecellular nucleic acids provides a convenient means ofidentifying a cellular event, and characterizing the integrityof that event, which triggers data flagging for subsequentinterpretation. The cell Ir content could also serve as an


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Fig. 2. Chemical structures of (1) the Rh(III)-intercalator and (2) the Ir(III)-intercalator used in the experiments described here.

ig. 3. SEM images for PS bead samples loadedwith 169Tm and synthesized ine presence of 1% TmCl3 added to the second stage of dispersionolymerization with AA: 2 wt.%/styrene (d=2.1 μm, CVd=1.8%).


internal standard for quantification of other concomitant(multiplex) metal tags conjugated to affinity reagents.Sequential staining of live cells first with the Ir-intercalatorfollowed by antibody staining, cell permeabilization andincubation with the second Rh-intercalator provides a meansof distinguishing live and dead cells in the sample.

2.4. Metal-encoded beads

The element-encoding approach allows for the creation ofhigh-throughput cytometric bead gene/protein arrays analo-gous to fluorescent bead arrays (Braeckmans et al., 2002;Elshal and Mccoy, 2006; Marquette and Blum, 2005; Meza,2000; Nolan and Mandy, 2006). Polystyrene beads can besynthesized to contain a number of lanthanide isotopes indistinctive concentration ratios. The bead surface can befunctionalized such that each distinguishable bead carries adifferent oligonucleotide (for genes) or antibody (for pro-teins) probe, where the identity of the probe is associatedwith the beadmetal encoding. Exposing a mixture of beads toa cell extract will cause the corresponding gene transcripts orantigens to bind to the specific probes on the beads. The beadsample can then be counterstained with a metal-tagged“reporter” molecule universally specific for the all boundanalytes, where the tag element can be the same for allreporters. Simultaneous determination of the bead encodingand reporter tag elements for individual beads describes theidentity (bead metal encoding) and quantity (reporter metaltag) of each biomarker. Measured at 1000 beads/s, a 30,000point array equivalent (e.g., 1000 genes with 30-foldredundancy) can be recorded in 30 s.

2.4.1. Bead synthesis and characterizationThe optimal bead diameters for the ICP ion source are in

the range from 1 to 5 μm. Smaller particles will not have asufficient amount of embedded metal to be detected, andlarger particles may not burn completely in the Ar plasma. Itis desirable to achieve uniform bead-to-bead Ln content(Hanley et al., 2007). Tomeet these requirements, beads weresynthesized by multiple-stage dispersion polymerization ofstyrene in ethanol with acrylic acid as co-monomer whichacts as a ligand to anchor the metal ions within the beads(Abdelrahman et al., 2010). The polystyrene beads containedcovalently grafted polyvinylpyrrolidone chains at the surfaceto suppress non-specific protein adsorption, and carboxylicacid groups for biomolecule conjugation. They also containedup to 107 Ln ions per particle as determined by conventionalICP-MS after microwave digestion in concentrated nitric acid


and by mass cytometry. These ions were introduced atdifferent concentrations to meet the enumeration encodingformalism. The beads were found to have insignificant releaseof lanthanide ions into aqueous solutions at different pH overa period of six months. The bead diameters and distributionswere determined from images obtainedwith a Hitachi S-5200FE-scanning electronmicroscope (SEM) (Fig. 3). Thesemetal-encoded beads were also verified for their use as standardsand for tuning the mass cytometer.

2.4.2. Metal encodingEncoding beads with n elements, for each of which there

are k concentrations, yields kn−1 distinguishable beads. Forexample, with 4 levels of concentration of 5 different metals,a thousand unique beads (45–1≈1000) are possible, and for10 different metals or isotopes, the variety of beads reachesone million (410–1≈106).

2.5. Mass cytometer and data processing

The CyTOFTM mass cytometer (DVS Sciences, RichmondHill, Canada), is a novel instrument for real time analysis ofsingle metal-encoded beads or cells stained with metal-tagged affinity reagents. It is based on the inductively coupledplasma time-of-flight mass spectrometer. Spectral generationfrequency of 76.8 kHz provides capability for collectingmultiple spectra from each particle-induced transient ioncloud, typically of 200–300 μs duration. A complete descrip-tion of the instrument can be found in a recent report(Bandura et al., 2009). Because the technology is new to thebiological community we provide a brief overview ofinstrument operation.

2.5.1. Instrument descriptionThe sample introduction system is very different from the

one used in flow cytometry and is designed to strip the bufferfrom cells or beads utilizing pneumatic nebulization (Fig. 4).This process leads to a stochastic and turbulent flow of cells,water droplets, anddriedmicroscopic salt particles in the argongas. The sample for nebulization is delivered in the formof a cellsuspension in liquid by flow injection and aspirated by a

Fthp



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Fig. 4. Pneumatic nebulization of cells in liquid suspension. The concentricnebulizer is shown in the centre. A syringe pump delivers cells suspended inliquid (low salt buffer) into the nebulizer. The turbulent gas flow containingdroplets with cells is dried (all water droplets without cells are vaporized)and converted into a laminar flow by argon gas.


Please cite this article as: Ornatsky, O., et al., Highly multipadoi:10.1016/j.jim.2010.07.002

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concentric nebulizer. For cell and bead analysis, the nebulizer isconnected to a heated spray chamber, to which a make-upargon gas flow (typically at 0.7 L/min Ar) is supplied via amassflow controller. In the spray chamber, the turbulent gas flowcontaining droplets with cells is dried (all water dropletswithout cells are vaporized) and converted into a laminar flow.

Cells or beads are then delivered into the central channelof the plasma by a laminar flow of argon. The argon plasma isinductively coupled to a 1.6 kW rf-power source (38 MHz)using a three-turn copper load coil (Fig. 5A). This energycoupling provides approximately 0.1% ionization of argon at7000 K, which is sufficient to atomize and ionize cells. Theargon plasma volume is approximately 16 cm3 and is formedat atmospheric pressure. A 20 L/min combined flow stream ofargon is constantly introduced through the quartz torch. Theflow of argon cools the torch and load coil preventing the hotplasma core from interacting with the assembly.

The particles (cells or beads) are delivered concentricallyto the plasma core (through a quartz injector positionedupstream within a few millimeters of the hot plasma) using~1 L/min Ar flow (combined nebulizer and make-up flow).The plasma state can be verified using a standard solution

ramet

containing cerium (Ce). The CeO+ ion has one of the highestbond energies, and the argon plasma is considered robustwhen the CeO+/Ce+ ratio is less than 3%.

Complete atomization and ionization of particles in the ICPsource is very important for reproducible analytical perfor-mance, and is discussed extensively in laser ablation techniqueslinked to ICP-MS. Nomizu et al. (1994) demonstrated thevaporization, atomization and ionization of individual ethanolfixed eukaryotic cells by inductively coupled plasma, and usedan optical emission ICP spectrometer to detect endogenouscalcium in individual air-born dried cells. The same group lateremployed ICP-MS for the detection of individual air-born zincparticles (Kaneco et al., 1995). A consensus model (Fig. 5A)considers a cell generating an ioncloud inplasmawhich rapidlydiffuses on itsway downstreamof the plasma core. Sampling ofthe ion cloud is a compromise between the requirements forcomplete ionization of the cell and diffusion dynamics of theion cloud. If the sampling is done too close to the injector, asignificant portion of the cell will not be ionized. Too fardownstream, and the diffusion process will reduce the ioncloud density, rapidly degrading sensitivity. In the case of themass cytometer, the sampling is done in the plasma regionwhere the plasma condition is robust (CeO+/Ce+ b3%). In thisregion, the ion cloud from an individual particle or cell is largeenough to produce a transient signal of ~200 μs. The resultingion cloud is much larger than the parent cell and is diffusionlimited. We speculate that variations in the cell size cannotsignificantly affect the ion cloud size and its duration, althoughthey influence the ion density and resultant sensitivity.Therefore, virus particles, bacteria, or cells produce transientsignals of similar duration but of different intensity.

Inmass cytometry, cells are introduced into the hot plasmaregion stochastically. Therefore, a longer than expected ioncloud indicates two or more particles coming together. Twooverlapping ion clouds generate a bimodal transient signal.This limits themaximum rate of cell introduction to ~1000 persecond. Two or more cells might be introduced into the hotplasma region simultaneously. This event can be observed as adoubling of DNA amount by the two-fold increase in theiridium signal from the Ir-intercalator.

2.5.2. Ion detection and signal handlingThe mass cytometry analyzer produces a full mass

spectrum of elemental tags with 76.8 kHz frequency. A fastTOF ion detector (Model 14882, ETP Electron Multipliers, SGEInternational Pty. Ltd., Ringwood, Victoria, Australia) is used forion detection. The output signal of the detector is amplified bya pre-amplifier and digitized by the analog-to-digital conver-sion (ADC) based 8-bit 1 GHz signal digitizer (PDA1000,Signatec, Inc., Newport Beach, CA). A trigger delay and therecording segment length can be set to allow digitization of thesegment of the waveform that corresponds to mass-to-charge,m/z=103–197, with 1 ns sampling resolution.

Dedicated software algorithms (CyTOF 5.1, DVS SciencesInc.) provide continuous recording of the consecutivesegments without data loss, time-to-mass conversion andcompression of the raw data by integration of each singlemass spectrum in mass-locked analyte mass channels. Thisresults in a compressed record of consecutive integratedsingle mass spectra, with each analyte signal represented byboth an integrated analog intensity value and an integrated



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Fig. 5. Ion detection and signal handling. (A) The Ar plasma is inductively coupled with an rf-power source using a three-turn copper RF load coil. The ion cloudfrom an individual cell is shown in yellow. The sampler interface aperture is seen on the left. (B) A transient signal for a given mass of an elemental tag coincideswith all other tag signals and has the same duration. Several “masses” are shown. (C) The gray plane perpendicular to the intensity axis depicts the detection limit.Here the low intensity “seventh mass” is below background. (D) Time-mass bi-variant projection of “C”. (E) A collection of a number of consecutive spectra. Thedata presentation is binary: the presence of an ion signal above the detection limit in a particular spectrum is represented as a point. Three transient eventsrepresenting metal-encoded beads are shown.


number of counted ions. The compressed record is furtherprocessed to detect and integrate cell-induced transients.

A particle-induced transient signal for a given mass of anelemental tag coincides with all other tag signals (Fig. 5B) andhas the same duration. However, like all other mass spectro-meters, the mass cytometer does not have 100% ion transmis-sion and detection. The detection limit is depicted in Fig. 5C asa gray plane perpendicular to the intensity axis. The detectionlimit is approximately the same for all elements of the tag, andsignals below the detection limit cannot be detected. As aresult, in the two dimensional (time-mass) projection(Fig. 5D) the cell event can be represented as a group of“middle aligned” signals of a slightly different duration.


The Fig. 5E projection is used for a quick preview of the dataduring sample acquisition prior to recording continuous rawdata. The horizontal scale represents the ion m/z, and thevertical scale is the spectrumof the appearance timeof samplesat 13 μs intervals. Fig. 5E represents a collection of a number ofconsecutive spectra. The data presentation is binary: thepresence of an ion signal above a detection limit in a particularspectrum is represented as a point. In this example, threetransient events representingmetal-encoded beads are shown,with short streaks of 130–390 μs duration at m/z=159, 165and 169. There is an almost continuous background signalbetween the short streaks at the same masses, which might beattributed to free lanthanide in the buffer with the beads. The



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Fig. 6. Antibody titration on normal bone marrowmononuclear cells by masscytometry. (A) Gating on granulocyte/monocyte fraction (CD15/CD45 plot)(B) Gating on progenitor stem/endothelial cells (CD34/CD45 plot). Satura-tion is reached at 0.6 μg/mL Ab. Illustrating examples of the two gated celpopulations are displayed in Fig. S1.


width of the streaks (horizontal, mass) is ~15–20 points (ns)and represents the width of the mass peaks at their base—amass channel corresponding to an elemental tag. The signalfrom the bead event is significantly higher than frombackground, and multiple sample washes improve signal-to-noise ratios.

2.5.3. Data processing for cell event detection and integrationThe compressed record of consecutive integrated single

mass spectra is produced “on-the-fly”, during samplemeasurement. The analog intensity and the ion countingdata are combined into “dual counting” data, wherein atsignal strength below a certain threshold (e.g. 3 single ioncounts per spectrum), ion counting data are used, andabove that threshold—analog data converted into ioncounts are used. The conversion coefficients are derived“on-the-fly” from the first 30 s of the data acquired for eachsample by comparing the analog and ion counting data forthe 0–2 counts/spectrum range.

The presence of a cell or bead event is detected bycomparing signals for the cell- or bead-specific analytes to apre-selected threshold. In case of cells, Rh- or Ir-containingnucleic acid intercalators are used to detect and examine cell-induced transients. The default algorithm for detecting cell-induced transients includes summation of Rh+ or 191Ir+ and193Ir+with signals for other labeling isotopes, and comparisonof the smoothed sum to a threshold. Varying the thresholdallows resolution of closely appearing cell events. Detected cellevents are integrated within the transient for each analyteseparately, and the record containing the duration of the cellevent (“cell length”), and a number of dual counts for eachanalyte for each cell, is produced. The data is not fundamentallydifferent from that of a typical flow cytometry experiment andis saved in FCS 3.0 format, compatiblewithflow cytometry dataprocessing software, for example, FlowJoTM.

The efficiency of the cell introduction system estimatedfrom the frequency of detected cell events for a given sampleintroduction rate (typically 60 μL/min) and the cell concen-tration (typically 0.5–1 million cells/mL), is currently 20–30%.

3. Results

3.1. Antibody titration and quantitation

After labeling antibodies with metal polymer tags wetested the conjugates for optimal staining concentrations andspecificity on human cell lines and primary cells. An exampleis shown in Fig. 6. A mononuclear cell fraction of normal bonemarrow was divided into four samples (1×106 cells/tube)and stained with a mixture of 22 metal-tagged antibodies at0.313 μg/mL, 0.625 μg/mL, 1.25 μg/mL or 2.5 μg/mL. Washedand fixed cells were then treated with the Ir-intercalator forDNA staining, and 80,000 cells per sample were analyzed byCyTOFTM. The intensity analog output of the CyTOFTM detector(Intensity) was processed using FlowJoTM software. Bivariatescatter diagrams identifying granulocytes/monocytes (CD15/CD45 gate in Fig. S1) and progenitor stem cells/endothelialcells (CD34/CD45 gate in Fig. S1) were used for each antibodyconcentration mix. The mean intensity of each element tagwas obtained within each gate and was used to plot titrationcurves (Fig. 6). For most of the antibodies (CD11b, CD15,

Please cite this article as: Ornatsky, O., et al., Highly multiparametric analysis by mass cytometry, J. Immunol. Methods (2010),doi:10.1016/j.jim.2010.07.002

.

l

CD45, CD133, and CD34) the saturating concentration wasreached at ca. 0.6 μg/mL and over 1.0 μg/mL for CD95, CD14,CD33, and CD117.

The average number ofmetal atoms per cell was quantifiedfor this concentration. Quantification is dependent on themean analog intensity multiplied by the intensity-to-countconversion factor, which is related to the detector-dataacquisition system response (ca. 0.02 for this set of experi-ments, Table 1C), and divided by the transmission coefficientfor a given lanthanide ion. The transmission coefficient isdefined as the number of ions that reach the detector pernumber of ions injected into the plasma and is determinedprior to experiment by tuning the instrument with a standardsolution of pure elements. Thus, each element in the antibodymix is assigned a transmission coefficient which is used tocalculate the number of metal atoms per cell. MAXPARTM tagcarries ca. 30 atomsof a given element and on average 4–5 tagsare attached to each antibody molecule. Specifically, theconcentration of each purified metal-tagged antibody wasmeasuredwith a Nanodrop UV/VIS spectrometer, yieldingmolAb/mL. Additionally, an aliquot of each antibody solution wasdiluted 1/100,000 in 2%HCl and analyzed by conventional ICP-MS, from which the metal concentration was determined inmol Ln/mL. Dividing the metal concentration by the antibodyconcentration yields an average of 120–160 metal atoms perantibody. Table 1 summarizes the average number of anti-bodies bound per cell (ABC) at saturation for the gatedpopulations of Gran/Mono (A) and Progenitor/Stem cells (B).The values are within the range for fluorochrome-conjugatedantibodies determined by flow cytometry and cited in theliterature (http://www.biolegend.com, Expression of CommonSurface Molecules on Blood Cells.pdf in Support).

http://www.biolegend.com


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Table 1t1:1

Average number of antibodies bound per cell (ABC) at antibody saturation for the populations of Gran/Mono (A) and Progenitor/Stem cells (B) in normal bonemarrow. Gated populations of Gran/Mono in CD15/CD45 plot and Progenitor/Stem cells in CD34/CD45 plot are shown in Supplemental Fig. S1. Intensity is theintensity analog output of the CyTOFTM detector. Atoms per cell are calculated from Intensity using the Intensity factors and Transmission coefficients (C) forlanthanides measured by CyTOFTM in the standard solution prior to sample analysis. ABC is calculated by dividing the number of atoms per cell by the number ofmetal atoms per antibody. See Section 3.1 for detailed description.

t1:2t1:3 A

t1:4 Progenitor CD117−Nd146 CD34−Tm169 CD133−Lu175 CD45−Tb159

t1:5 Intensity 1260 6014 4083 23,810t1:6 Atoms per cell 4.5E+06 7.3E+06 4.9E+06 2.4E+07t1:7 ABC 2.8E+04 6.1E+04 4.1E+04 2.0E+05t1:8t1:9 B

t1:10 Gran/Mono CD−Pr141 CD−Nd145 CD95−Eu151 CD45−Tb159 CD38−Ho165 CD15−Er166 CD11b−Sm154

t1:11 Intensity 6318 11,112 15,673 4820 6915 18,122 18,639t1:12 Atoms per cell 2.2E+07 3.9E+07 5.5E+07 4.9E+06 8.4E+06 2.2E+07 1.9E+07t1:13 ABC 1.2E+05 2.2E+05 3.1E+05 4.1E+04 7.0E+04 1.8E+05 1.6E+05t1:14t1:15 C

t1:16 Lanthanide 139La 159Tb 169Tm

t1:17 Transmission coefficient 6.21E−06 2.09E−05 1.90E−05t1:18 Intensity factor 2.20E−02 2.12E−02 2.30E−02

Q3 Q4


3.2. Multiparametric analysis of cell biomarkers

To date we have routinely used 30 elements, most of whichare stable isotopes of lanthanides, to label monoclonal andpolyclonal antibodies (mouse, rat, rabbit and goat) with theMAXPARTM polymer tag. The choice of element for a givenantibody is arbitrary, since there is no need for compensationand themass cytometer has a large dynamic range. The labeledantibodies are all combined together in one master mix at theoptimal concentration determined by titration.

3.2.1. Normal blood mononuclear cell (PBMc, CB, HSC)surface markers

Immunostained cells are delivered to the plasma and arevaporized and ionized. Raw and integrated per masssequential mass spectra data can be monitored on thecomputer screen as a continuously refreshed display of cellevents. An example of a screen shot captured during analysisof PBMc stained with a mixture of 24 metal-taggedantibodies and the Ir-intercalator is shown in Fig. 7. Thehorizontal scale represents the mass channels selected bythe user. The vertical scale resolves the sequential massspectra collected over the time course of the experiment,known as spectrum (push) number. The presence of an ionsignal at a particular mass channel in a particular single massspectrum is represented as a horizontal bar of one pixelheight, with its width representing the integrated signalstrength for the mass in the spectrum. The appearance of“oval-shaped” vertical streaks indicates detection of atransient ion cloud and is induced by elements present incells, e.g. as a cell event.

The almost continuous background signal at somemasses between cell events may be attributed to free Ab–Ln in solution either from dissociation from cells afterstaining or high concentration during staining. Xenon (Xe)isotopes observed are due to impurity present in the Ar gas.The data are further processed in order to identify


individual cell-induced (triggered by 191Ir and 193Ir content)transients and are saved in text and FCS 3.0 formats. Threetransient events representing three different cell types areindicated in Fig. 7. Specifically, a CD4+ T-cell lymphocyte isidentified by prominent expression of CD2, CD3, CD4, andCD45 (top). It is followed by a B-cell lymphocyte with itssignature CD19, CD20, CD38, HLA-DR, CD45 marker expres-sion, as well as low levels of CD40, CD45RA and CD71(middle). At the bottom of the screen a NK lymphocyte canbe seen, being most likely assessed by the presence of CD8,CD2, CD45 and CD45RA antigens, and the absence of CD3.Bivariate scatter pseudocolor diagrams (FlowJoTM software)demonstrate the distinct PBMc cell types identified by amixture of 24 Ab–Ln conjugates (Fig. 8). Differentiated cellsof the lymphoid and myeloid lineages can be clearlydistinguished by their surface markers. The CD34 surfacemarker is expressed on all hematopoietic stem/progenitorcells that constitute a heterogeneous population. However,these CD34+ cells make up only 0.14% (CD34/CD45 gate)and primitive stem cells with the CD34+CD38−CD45RA−immunophenotype only 0.04% of peripheral blood mono-nuclear cells. The same panel of antibodies was used toanalyze cell populations in the lineage depleted (Lin−)CD34+ enriched HSC sample, and the mononuclear fractionof CB. It is interesting to note that enrichment of primitiveCD34+ cells in the HSC sample reached 65% (Fig. S2, CD34/CD45 graph) which is well within the 55–78% rangedetermined by flow cytometric assessment according toGuenechea et al. (Guenechea et al., 2001). Candidatehematopoietic stem cells were enriched in the Lin−CD34+CD38− and in the Lin−CD34+CD38−CD90+CD45RA−fractions as demonstrated by in vivo transplantation studiesand complementary in vitro assays in Weissman's labora-tory (Majeti et al., 2007). The CD133 antigen is restricted toHSC (Shmelkov et al., 2005; Yin et al., 1997), and a smallsubset of CD133+/CD90+ cells (3.75%), comprising 0.5% ofhematopoietic stem cells within the CD34+CD45+ gate,



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Fig. 7.Q7 Real-time screen shot duringmass cytometric acquisition of adult PBMc sample (A). Cells were probedwithmetal-conjugated antibodies against 27 surfaceantigens. Each antibody was labeled with a different stable isotope (for example, CD2 is followed by the isotope used to tag the corresponding antibody, 175Lu).(B). Cellular DNA was labeled with an Ir-intercalator (used as a trigger for cell recognition); three different cells are indicated.


were identified. Multipotent progenitor/precursor cellswere found in the Lin−CD34+CD38+ subpopulations(Dick et al., 2001; Ishikawa et al., 2004).

TheCBsampleprofilediffers fromthatofbothHSCandPBMc(Fig. S3). The number of primitive CD34+ cells was higher at0.89%compared to0.14% inperipheralblood,while themajorityof cells displayed surface characteristics of lymphocytes. It isinteresting tonote thatpractically allCD3+Tcellswerepositivefor CD38, whereas only half of PBMc T cells were CD38+. TheCD34+CD38−CD90+CD45RA−CD133+ stem cell fractionconstituted approximately 0.002% in the CB sample.

3.2.2. Leukemia cell line surface markersTo demonstrate the power of mass cytometry and

specificity of metal-tagged antibodies, we present the resultsof four 22-plex assays. Biomarker expression levels of fourleukemia cell lines, KG1a, HL-60, Jurkat and Ramos, werecompared. Data for each sample were collected from analysisof at least 25,000 cells. KG1a is a CD34+ primitive leukemiacell line, while HL-60 was derived from a patient with acutepromyelocytic leukemia (Koeffler and Golde, 1980). Ramoscells are a B-lymphoblastoid cell line derived from Burkittlymphoma, and Jurkat cells are representative of acute T-cellleukemia.

We begin by comparing data from KG1a and HL-60 cells.Samples of approximately 1×106 cells were stained with acocktail of twenty two labeled antibodies, each carrying adifferent metal. The cells were then washed, fixed informaldehyde, and treated with Ir-intercalator. The data inFig. 9 are presented in the form of a logarithmic radial plot ofmean intensity values for each metal-tagged antibody. The

Fig. 8. Bivariate scatter diagrams of adult PBMc sample with 24 surface biomarkers usright corner.


individual antibodies and the associated lanthanide areindicated at the periphery of the plot. The order in whichthe antibodies are arranged is arbitrary. As an example,consider CD34, a prominent marker of primitive KG1a cells,should be absent in differentiated cells such as Jurkat, Ramosand HL-60. Indeed, KG1a cells showed positive reactivity withCD34–Tm169 and less reactivity with CD38−Ho165, CD44−Eu151, CD45RA−Eu153, and CD13−Er166 antibodies. How-ever, many antibodies, CD2−Lu175, CD20−Gd156, CD11c−Nd150 to name a few, did not bind to the KG1a cells. At thesame time all lines reacted with CD45−Tb159, a marker ofhematological cells. In contrast, Ramos cells are known toexpress high levels of CD19, CD20, and CD38. Indeed, masscytometry identified very high levels of CD38, high but lessintense levels of CD19 and CD20, while expression of CD34was at background level. The noise in mass detection is0.07 counts/s/cell event. Therefore, more than one count issignificant in a given mass channel if it occurs during the200 μs ion transient associated with passage of a cell throughthe plasma. Analysis of Ramos cells indicate that 6% of thecells show several counts for 169Tm, whereas 94% have nodetectable signal for this isotope. The Jurkat cells were foundto display hallmark CD2 and CD3 expressions, and HL-60showed high CD15 and CD33 levels. All 22 antigens tested foreach cell line are effectively quantified in a single masscytometry assay.

To address the question of the amount of metal-taggedantibody that is retained non-specifically on target cells, thefollowing experiment was set up using Ramos cells andCD20−Gd156 antibody. First, live Ramos (CD20+CD45+) andU937 (CD20−CD45+) were incubated with over-saturating

ingmass cytometry. The list of metal-tagged antibodies is shown in the upper




Please cite this article as: Ornatsky, O., et al., Highly multiparametric analysis by mass cytometry, J. Immunol. Methods (2010),doi:10.1016/j.jim.2010.07.002


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Fig. 9. Logarithmic radial plots of mean intensity values for 22 metal-tagged antibodies detected by mass cytometric analysis of human leukemia cell lines (KG1a,HL-60, Ramos, and Jurkat). All metal-labeled antibodies were combined in one mixture at predetermined concentrations.


amounts of primary CD20 antibody or mouse IgG (5 μg/mLper 1×106 cells). After washing, cells were stained with amixture of CD20−Gd156 and CD45−Tb159 (300 ng/mLper 1×106 cells). Finally, cells were fixed and stained withthe Ir-intercalator. Mass cytometry results (Fig. S4)revealed that Ramos cells treated with primary CD20prior to CD20−Gd156 generated a low intensity Gd156signal—only 0.8% of signal from Ramos cells treated withmouse IgG and metal-tagged CD20−Gd156. The CD20−negative U937 cells showed background Gd156 levels inboth cases. The amounts of CD45−Tb159 antibodiesdetected on Ramos and U937 were not influenced byincubation with primary CD20 or mouse IgG. Overall,assays on human leukemia cell lines demonstrated thespecificity and non-cross-reactivity of the metal-labeledantibodies, which were further used for multiparametricbiomarker analysis of leukemia patient samples.

3.2.3. Leukemia patient cell type sub-classificationBonemarrow samples from patients diagnosedwith acute

myeloid leukemia and patients with B-cell acute lymphoidleukemia were used to compare biomarker profiles obtainedby mass cytometry and flow cytometry. Samples wereimmunophenotyped for 11 markers with 4-color flowcytometry at UHN on a BD Biosciences LSR II instrument:CD34/19/10/20 mix, CD44/123/38/34 mix, CD15/14/38/34mix, CD38/90/19/34 mix, and CD45RA/90/38/34 mix. This setup required that the initial patient sample be split into atleast 10 fractions (including FMO, fluorochrome minus one,controls) at 1×106 cells per tube. Since there is no overlap indetection of masses by the mass cytometer and no compen-sation required, only one tube with 2×106 cells was used forstaining with a mixture of 20 antibodies labeled withMAXPARTM tags against the same markers (different clones)


plus 9 additional antibodies. FlowJoTM plots obtained bymassand flow cytometry were compared and are presented inFig. 10. Additional markers for three of the leukemia samplesidentified by mass cytometry are presented in a Supplemen-tal data file (Fig. S4). Overall the phenotypic profiles ofpatient samples are similar between the two methods. Weshould point out the seemingly poorer separation betweencell clusters in the mass plots compared to flow cytometry. Inflow cytometry, detectors are tuned individually to provideincreased separation of channels. The CyTOFTM instrumentregisters all mass channels with a single detector according tothe ion arrival time. Thus, although the detectors in flowcytometry need to be tuned and adjusted separately, thiscreates the possibility of presenting data from independentchannels withmaximal separation. The difference in reagentsas well as in the measurement of CVs may also contribute theeffect. This fundamental difference in data acquisition isbeing investigated further in comparative studies.

The fine tuning of leukemia sub-classification can beaccomplished by increasing the number of biomarkers. Anexample of the immunophenotypic profiles of three differentAML samples is presented. Frozen bone marrow samples (85–92% blasts) were received from the Quebec Leukemia Cell Bank(BCLQ), which classified samples #25, #65, and #80 as acutemonoblastic leukemia (M5A) using 20-marker two-color flowcytometry. In Fig. 11A, we compare these samples for theexpression of 20 antigens by mass cytometry. All express highlevels of the common leukocyte antigen CD45, but showdifferences in CD4, CD13, CD14, CD36, CD64 and HLA-DRexpression. However, the AML M5A #65 sample displayed amore differentiated phenotype with increased CD13, CD14,CD33andCD64, and lowerHLA-DR levels characteristic of acutemonocytic leukemia. An interesting feature of all samples wasthe detection of iodine (127I). This is likely due to the high



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Fig. 10. Comparison of immunophenotyping performed by flow (LSR II) and mass cytometry (CyTOF). Leukemia patient samples (AML and B-ALL) were screenedfor 11 markers with 4-color flow cytometry: screen 34/19/10/20 (shown); screen 44/123/38/34; screen 15/14/38/34; screen 38/90/19/34; screen 45RA/90/38/34.The same samples were probed with a mixture of 20 metal-tagged antibodies including those used in the flow cytometry screen.


content of iodine in the Ficoll-Hypaque isolation media.Hypaque is a nascent iodine supplement (Diatrizoate Sodium,sodium 3,5-diacetamido-2, 4, 6-triiodobenzoate) with 59.87%iodine, which could have been absorbed by the cells duringsample preparation. This leads us to speculate that otherelements, such as platinum in platinum-containing cytostaticdrugs, could also be identified and quantified on a per cell basis.We are currently performing experiments to demonstrateoxaliplatin accumulation in tumor cells from xenograft micetreated with different doses of the drug.

Cell population distributions obtained by flow and masscytometry for AML M5A #65 are shown in Fig. 11B. The flowcytometry screen returned data for 13 markers out of the 20tested. CyTOFTM data was collected for all antibodies. There isgoodagreement between the twomethods.Notable differencesare the higher CD14, CD36 and HLA-DR, and lower CD13percent of positive cells detected by mass cytometry. This maybe the result of antibody clone differences, sub-optimalcompensation settings or other factors related to acquisitionand data analysis in flow cytometry. A comprehensivecomparison with flow cytometry using the same antibodyclones and cell samples will be described in a separatepublication.

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3.2.4. Intracellular antigen analysisThe small size of the MAXPARTM tag (ca. 20 kDa) enables

metal-labeled antibodies to be used in intracellular biomarkeranalysis. We performed intracellular immunostaining of thePanc-1 cell line with antibodies against cell-cycle/prolifera-tion-associated proteins (CyclinA2, CyclinB1, CyclinD,CyclinE, pH3 (phospho-Histone3 (Ser10)), Ki67, pMPM2


(phospho-Ser/Thr-Pro mitotic protein monoclonal 2)) andcytoskeletal proteins (vimentin, cytokeratin). The optimalantibody concentrations (an example is given in Fig. S6) weredetermined by solution ICP-MS analysis (Ornatsky et al.,2008a). Fig. 12 displays a subset of bivariate scatter plots thatreveal heterogeneity of the cell population. For example, inthe CyclinA2/pMPM plot, themajority of cells (61%) are in theG0/G1 phase, while 3.8% are in S/M and 21% are in G2/Mphase. Vimentin is considered to be a mesenchymal inter-mediate filament protein and is known to replace cytoker-atins during an epithelial–mesenchymal transition. It isrecognized that some epithelial cells of the pancreas grownin vitro assume a mesenchymal phenotype and expressvimentin. In this experiment, over two thirds of Panc-1 cells(N60%) were found to have high vimentin levels (Ki67/Vimentin and pH3/Vimentin plots). Mitotic cells of this type(high pH3/high Vimentin in pH3/Vimentin plot) were mostlyin the G2-phase (CyclinB1/CyclinA2 graph on the right),whereas 18% of the high pH3/low Vimentin population werein the S-phase (CyclinB1/CyclinA2 graph on the left). Thus,mass cytometry is amenable to both surface and intracellularmultiparametric biomarker analysis.

3.3. Live/dead cell discrimination

Cell samples, especially after thawing, usually containsome non-viable cells and debris. Thus, there is a need for arigorous protocol to discriminate dead cell data from thatobtained with live cells. Typically, this is achieved with aTrypan blue test in conjunction with a cell counter. In masscytometry, this distinction is accomplished with an assay



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Fig. 11. Immunophenotyping of acute monoblastic M5A leukemia samples. (A) Logarithmic radial plots of the average expression levels of 20 different antigensdetected by mass cytometry. All 20 metal-labeled antibodies were combined in one mixture at predetermined concentrations. The Ir-intercalator (2) was used tostain DNA, and 127I was identified in all cells. (B) Comparison of the percentage of positive cell populations determined by mass cytometry (red—AML M5A #65MC) and by flow cytometry (blue—AMLM5A #65 FC). Absence of individual blue bars in the flow cytometry screen indicates that the corresponding antigens werenot determined.


based upon two DNA intercalators bearing different metals.For this purpose, we used the Rh(III) derivative (Fig. 2 chart(1)) and the Ir(III) derivative (Fig. 2 chart (2)), and tookadvantage of the fact that membranes of dead cells arepermeable to both of these intercalators, while live cellsremain impermeable even at molar concentrations (Ornatskyet al., 2008b). To demonstrate this principle, THP-1 cells werekilled by heat shock andmixedwith live culture to create 60%,80% and 95% live cell suspensions. Prior to immunostainingthe samples were treated with the Ir-intercalator, whichbound to nucleic acids of the dead cells and the cellfragments. The cells were then fixed/permeabilized andstained with the Rh-intercalator, which reacted with allcells (live and dead). In parallel, sample aliquots wereanalyzed by the Vi-CellTM automated Trypan blue cellexclusion method (Beckman Coulter, Brea, CA). The resultsof these experiments are presented in Fig. 13. Dead cellspicked up high amounts of the Ir-intercalator and form a


subpopulation shifted to the right. Fixation of the samplesrendered all cells permeant to the Rh-intercalator. Thefraction of live cells (LIVE gate) inferred from the masscytometry analysis is indicated on the graphs. Thecorresponding numbers obtained by Vi-CellTM are indicatedin red text on each plot. Thus, the mass cytometry identified57%, 84% and 95%, while the Trypan blue test was at 64%, 83%and 95% live cells for the same premixed samples. The valuesare extremely close and give confidence in the usefulness ofthe intercalators for distinguishing live and dead cells.

3.4. Analysis of metal-encoded beads

3.4.1. Optimal metal loadingBead synthesis was initiated by dispersion polymerization

of styrene in ethanol, and after approximately 10% monomerconversion, a known amount of LnCl3 in ethanol in thepresence of an excess of acrylic acid (AA) was added. The



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Fig. 12. Mass cytometric analysis of intracellular proteins in a pancreatic Panc-1 cell line. Cells were collected from culture flasks, fixed in 4% formaldehyde,permeabilized with 80% EtOH, and stainedwith amixture of metal-labeled antibodies against intracellular cytoskeletal and cell-cycle proteins. The upper left-handcorner describes the antibodies and metals used.


carboxylate group of AA is known to interact strongly withlanthanide ions. The synthesis was designed to investigate alevel of metal loading which would be close to saturating themass cytometry detector. Thulium-encoded beads wereprepared by addition of 1.0 wt.%/styrene TmCl3 and 2.0 wt.%/styrene AA in the second step. The 169Tm-beads (Fig. 3) have amean diameter d=2.1 μm with a narrow size distribution(CVd=1.7%). To examine the 169Tm content, this beadpreparation was washed by three cycles of centrifugationand resuspension in water. The resultant single bead suspen-sion (ca. 106beads/mL) was introduced into the masscytometer. The high temperature of the plasma was sufficientto vaporize, atomize and ionize the beads. In Fig. 14A, thepopulation distribution is presented for the 169Tm ion signalcollected for 3 min (ca. 4×105 beads). The x-axis of this plot isthe intensity analog output of the mass cytometry detectorand is considered here as a relative number. The mean 169Tmintensity is 81,700 corresponding to an average of 8×107


thulium ions per bead. This level of loading is close tosaturation (upper limit) of the detector as manifested by thesharp drop in the thulium integrated intensity distribution,represented by the red dashed line in Fig. 14A. Decreasing theamount of TmCl3 salt added in the second stage of dispersionpolymerization should result in lower metal loading perbead. Thus, another sample was prepared in the presence of2.0 wt.%/sty AA and ten times less thulium chloride, 0.1 wt.%/sty TmCl3. These beads were also monodisperse (CVd=1.9%)with a size (d=1.9 μm) similar to the high 169Tm-contentbeads. Fig. 14B shows the distribution of the integrated signalintensity for the low 169Tm-beads. The average value wasfound to be ca. 1.1×107 thulium atoms per bead. The metalcontent per bead was also independently verified andconfirmed using microwave acid digestion and conventionalICP-MS analysis (Abdelrahman et al., 2010). Thus, wedetermined that a total of ten million metal atoms per beadare adequate for mass cytometry measurements.



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Fig. 13. Comparisonof live/dead cell discrimination betweenmass cytometry andVi-CellTM automated Trypan blue cell exclusionmethod. Premixed live and dead THP-1 cellswerefirst stainedwith Rh-intercalator (1), followedby Ir-intercalator (2) staining offixed samples. The number of live cells is shown in each plot. Red labels referto values obtained by the Trypan blue test. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)


3.4.2. Construction of large metal-encoded bead librariesThe development of a high order multiplex bead array

requires the production of thousands of uniquely encodedbeads. The encoding strategy for mass cytometry relies on theincorporation of a variety of metals at a range of concentra-

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Fig. 14. Signal intensity distribution for populations of thulium encoded PSbeads. (A) Population of 169Tm-beads prepared with 1.0 wt.%/styrene TmCl3The red dashed line indicates the sharp cutoff at ca. 105 169Tm signal intensityindicating detector saturation. (B) Population of 169Tm-beads prepared with0.1 wt.%/styrene TmCl3. (For interpretation of the references to color in thisfigure legend, the reader is referred to the web version of this article.)

Please cite this article as: Ornatsky, O., et al., Highly multipadoi:10.1016/j.jim.2010.07.002

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tions into the polystyrene beads. To test the ability of masscytometry to detect and quantify different levels of metals, wesynthesized four sets of PS bead samples using five levels of Lnconcentration (0, 0.02, 0.05, 0.10, and 0.20 wt.%/styrene)introduced in the second step of the dispersion polymeriza-tion. In these reactions, four elements (La, Tb, Ho, and Tm) perbead were used simultaneously (Fig. S7). The panels aregrouped by element. The normalized peaks in each panel arelabeled “1”, “2”, “3”, and “4”, respectively, to indicate that theyoriginate from PS beads prepared in the presence of 0.02, 0.05,0.10, and 0.20 wt.% LnCl3/styrene. Data collected for severalthousand microspheres, demonstrate essentially baselineresolution in the ability to detect 169Tm, 159Tb, 165Ho, and139La over a concentration range of 3 orders of magnitude.Thus, the encoded microspheres can be distinguished suc-cessfully with minimal overlap. This example of encodedmicrospheres has a variability of 624 (i.e., 54–1). With a largernumber of elements or isotopes, such a metal-encoded beadlibrary opens the possibility to resolve an extremely largenumber of unique targets in gene expression analysis(Brenner et al., 2000; Marquette and Blum, 2005).

3.4.3. Metal-encoded bead bioassaysBioassays with metal-encoded beads require functionali-

zation of the bead surface for covalent attachment of proteins,antibodies, or oligonucleotide probes. A straightforwarddemonstration of this concept would be a sandwich-typeimmunoassay, where the protein on the bead surface isrecognized by a metal-labeled antibody. As a proof-of-principle experiment fully described in the work of Abdelrah-man and colleagues (Abdelrahman et al., 2010), we used139La and 169Tm-encoded beads synthesized by three-stepdispersion polymerization with a high amount of titratableCOOH groups per bead for covalently attaching mouseimmunoglobulins to the surface (Fig. 15). The presence andamount of mouse IgGswas detected by a goat anti-mouse Ab–141Pr. The effective binding of metal-tagged anti-mouseantibody to the metal-encoded beads coated with mouseIgG was measured by mass cytometry. It was demonstratedthat the praseodymium signal from the mouse IgG-coatedbeads was two orders of magnitude greater than that due tonon-specific adsorption to plain beads and one order ofmagnitude stronger than non-specific interaction with BSA-coated beads. This type of assay lends itself to multiplexing, inwhich beads bearing different antibodies are encoded with



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Fig. 15. (A) Scanning electron micrograph of 2 μm AA105 polystyrene beads (scale bar 5 μm) prepared by 3-stage dispersion polymerization in the presence ofLaCl3 (0.1 wt.%/styrene) and TmCl3 (0.1 wt.%/styrene). AA105 signal intensities for 139La and 169Tm are shown in the histograms. CVLa=13% and CVTm=11%.(B) Antigen capture and detection using metal-encoded beads and CyTOF. Carboxylated La, Tm-encoded beads, were conjugated to BSA or mouse IgG usingcarbodiimide chemistry (EDC). Microspheres were then washed and incubated with goat anti-mouse secondary antibodies that are labeled with a Pr-containingpolymer tag (anti-mouse-IgG-Pr) to identify the presence of attached proteins. Stringently washedmicrospheres were analyzed for concomitant signals of 139La,169Tm, and 141Pr as an indication of a successful immunoreaction. The bar graph represents CyTOF measurements (average intensity per bead) of protein-conjugated metal-encoded beads reacted with reporter, anti-mouse-IgG-Pr. The left-hand columns (AA105) show the result for non-specific adsorption ofreporter, in which AA105 beads without mouse IgG or BSA were exposed to anti-mouse-IgG-Pr (100 μg/mL). The Pr signal is very weak. The middle columns(AA105 BSA) report on the interaction of anti-mouse-IgG-Pr with the BSA-conjugated beads. The right-hand columns (AA105 mouse IgG) present data for theinteraction of anti-mouse-IgG-Pr with the beads conjugated to mouse IgG. The strong signal here indicates the successful binding and recognition of mouse IgG.


different metals at various concentrations. The metal signalsread by mass cytometry identify a bead code (La, Tm), andquantify the reporter metal (Pr) associated with the bead,thus providing information on the amounts and types ofanalytes in the test sample. This example suggests that themass cytometry technology coupled with functionalizedmetal-encoded beads can be used to design nucleic acid


hybridization assays, Western blot-like antibody assays andimmunoassays.

4. Discussion

Biomarker measurements relate the effects of therapeuticdrugs on molecular and cellular pathways to treatment



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outcomes and can help explain, for example, differences indrug metabolism during clinical trials (Atkinson et al., 2001).As such, tumor biomarkers contribute greatly to the selectionof appropriate personalized cancer therapy in clinical trials.Immunophenotyping of blood biomarkers using flow cyto-metry has played an important role in the diagnosis ofleukemia subtypes and selection of therapy. It is welldocumented that tumor progression in breast, prostate,bladder, and blood cancers, to name a few, invokes changesin the types and numbers of biomarkers expressed at eachstage of carcinogenesis (Celis et al., 1996; Ring et al., 2006;Guinn et al., 2007). Moreover, it is now widely accepted thatno single biomarker will have the sensitivity and specificitynecessary to the diagnosis and disease prognosis whenmeasured on its own. Many laboratories are applying a longterm approach to identify multiple biomarkers that can beused in clinical trials. For example, studies by Moreira et al.(2010) demonstrated that the combination of only twomarkers deregulated in bladder cancer had a much highercorrelation with grade and stage of disease than theindividual markers. The probability of rare cell populationidentification depends on the number of uncorrelatedparameters assayed. Even with 50% overlap between anytwo parameters, the probability of detecting a rare cellpopulation is increased dramatically with the number ofuncorrelated parameters (10 parameters is already less than0.1% probability for overlap; 30 parameters virtually elim-inates the overlap). This has been recently demonstrated inthe accurate measurement of dendritic cells in blood using asingle 12-color flow cytometry panel (Autissier et al., 2010).There is a critical need in the analysis of specific biomarkerson T cells in response to immunosuppressive drugs that areadministered to transplant recipients. Measurement of manyof these pharmacodynamic biomarkers which are stronglyrelated to the development of acute rejection will help tailordrug doses to individual patients (Barten and Gummert,2007; Barten et al., 2007). The discovery of increasing cross-talk among signal transduction molecules adds another layerof complexity to the evaluation of relevant cellular regula-tory pathways (Junttila et al., 2008). Simultaneous monitor-ing of numerous key nodes will provide researches withinsights into complex normal and disease cellular states.

The new mass cytometric technology for highly multi-parametric immunophenotyping of single cells overcomessome of the existing challenges in flow cytometry withregard to spectral interference, fluorescent dye quenchingand cellular autofluorescence. The advantages that thismethod brings to cytometry include high multiplicity ofbiomarker detection, absolute quantification, absence ofdetection channel overlap, no sample matrix effects, simpli-fied measurement protocols, and overall lower sample andreagent consumption. We anticipate that the limitationsbeing encountered in the first generation of mass cytometerssuch as speed of analysis, sensitivity related to metalmultiplicity of tag, and efficiency of sample introductionwill be improved as the technology matures. The maximumanalysis speed of 1000 cells/s is defined by the need toseparate ion clouds produced in the plasma ion source andhigher speeds are possible but result in significant numbersof cell pairs. This is significantly lower than most flowcytometry instrumentation but each cell is analyzed on 30


parameters rather than 5–10. The CyTOFTM developmentteam is working on significantly increasing the cell/beadintroduction efficiency. It is a difficult challenge sinceindividual cells/beads must be separated from the bufferand delivered intact into the argon plasma. The major losseshappen during this gas dynamic process. Currently, theintroduction efficiency is sufficient to detect 100,000 cellsduring 3 min running time and analyze more than 30parameters (N3e6 events per sample) from a sample of400,000 cells. Construction of isotope-binding polymer tagsfor a wider group of elements, as well as tags which containthousands of atoms (nanocrystals) that can be directlyattached to different proteins is an area vigorously pursuedby our team in collaboration with other research institutions.These constructs may allow 40–60-plex assays to be carriedout based on the available isotopes in the periodic table withlow biological background. Attaching nanocrystals to anti-bodies will dramatically improve the sensitivity of the assaypotentially allowing very small numbers of epitopes ortranscripts to be accurately quantified. Work continues onthe development of data collection and processing algo-rithms to obtain per cell results online. Multiparametric datarepresentation remains a challenge. The sheer volume ofdata produced by this method requires new and creativeways to visualize and analyze the multiparametric data.

In mass cytometry, cells and beads during analysis arecompletely consumed, and thus cannot be sorted on the basisof elemental tags. However, simultaneous labeling withfluorophores and element tags does permit pre-purificationby conventional FACS followed by multiparametric analysis, atandem approach that in some instances may improve theoverall throughput of the method.

We envision that with further development of theCYTOFTM in conjunction with novel element-tagged reagents(antibodies, nucleic acid probes, and intercalators), masscytometry will help open new avenues in human cancerresearch, in applied clinical practices such as tissue typing,transplantation, rare cell identification, minimal residualdisease monitoring; will be used in stem cell research, inmonitoring HIV/AIDS and pathogen detection; in cell signaltransduction research and drug screening.

Conflict-of-interest disclosure

Four of the six authors (O.O., D.B., V.B, and S.T.) are alsoprinciples of DVS Sciences, Inc., which manufactures theCyTOFTM mass cytometer and the MAXPARTM reagents.

Acknowledgements

This project was funded by Genome Canada through theOntario Genomics Institute, the Ontario Ministry of Researchand Innovation, the National Institutes of Health [NIH grantR01-GM076127], NSERC Canada, and DVS Sciences Inc.Special thanks is extended to Dr. Qing Chang, Ontario CancerInstitute/Princess Margaret Hospital, University of Toronto,Ontario for the Panc-1 cells, and Dr. M. Milavsky and Dr. J.Wang, University Health Network (Toronto General ResearchInstitute) for HSC and leukemia samples, respectively.Provision of leukemia bone marrow samples by the QuebecLeukemia Cell Bank (BCLQ) is gratefully acknowledged.



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Appendix A. Supplementary data

Supplementary data associated with this article can befound, in the online version, at doi: 10.1016/j.jim.2010.07.002.

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