probiologists.com Open in urlscan Pro
148.72.90.28  Public Scan

Form analysis
0 forms found in the DOM

Text Content

 * Home
 * About Us
 * Journals
 * Contact Us


CELL SIGNALING


ISSN : 2837-8253


ISSN : 2837-8253

 * Home
 * Editorial Board
 * Submit Manuscript
 * Articles
   * In Press
   * Current Issue
   * Archives
 * Author Guidelines
 * Editorial Policies
   * For Editors
   * For Reviewers
 * Special Issues
   * Guidelines
   * Open Issues
 * Contact

Commentary | Open Access | Volume 2 | Issue 1 | 2024 | DOI No.:
10.46439/signaling.2.041

SAMPLE MULTIPLEXING IN CYTOF: PATH TO OPTIMIZE SINGLE-CELL PROTEOMIC PROFILING

Muharrem Muftuoglu1,*, Michael Andreeff1

1Section of Molecular Hematology and Therapy, Department of Leukemia,The
University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA

*Corresponding Author:
Muharrem Muftuoglu
Section of Molecular Hematology and
Therapy, Department of Leukemia
The University of Texas MD Anderson
Cancer Center, Houston, TX, 77030, USA
E-mail: mmuftuoglu@mdanderson.org

Received date: June 06, 2024; Accepted date: July 10, 2024

Citation: Muftuoglu M, Andreeff M.Sample Multiplexing in CyTOF: Path to Optimize
Single-cell Proteomic Profiling. Cell Signal. 2024;2(1):113-119.

Copyright: © 2024 Muftuoglu M,et al. This is an open-access article distributed
under the terms of the Creative Commons Attribution License,which permits
unrestricted use,distribution, and reproduction in any medium, provided the
original author and source are credited.

 

ABSTRACT

Sample multiplexing significantly enhanced the depth of single-cell proteomic
analysis in CyTOF (Cytometry by Time-Of-Flight). New polymer-based chelators
have broadened the utility of metal isotopes, enabling improved tagging and
simultaneous analysis of multiple samples. These approaches minimize batch
effects, streamline experiments, conserve valuable samples, reduce costs,
enhance throughput, and increase the accuracy of biological data, thereby
facilitating novel discoveries.



BACKGROUND

In biomedical research, achieving single-cell resolution in investigation of
cellular systems is of paramount importance. Ongoing research efforts to explore
and decode the heterogeneity in cellular phenotype, functionality, genomics,
epigenetics, and transcriptomics in biological systems have propelled
significant technological advancements through innovative breakthroughs [1-3].
Among these advancements, mass cytometry, commonly referred to as CyTOF, was
developed as a highly multiplexed platform for single-cell proteomic analysis
[4,5]. Since its introduction over a decade ago, CyTOF has dramatically
transformed single-cell proteomic analysis, expanding our capability for
detailed examination and understanding of cellular heterogeneity and function.

CyTOF provides key advantages over traditional flow cytometry by enabling highly
multiplexed single-cell proteomic analyses without compensation for signal
spillover, effectively addressing spectral overlap issues and the capability to
measure a broad array of distinct cellular features [6,7]. Although
theoretically capable of detecting up to 135 unique metal isotopes, practical
applications usually involve around 60 distinct features, limited by the
availability of metal isotope tags and the complexity of conjugation chemistry
[8-10]. This gap has sparked increasing interest in expanding the measurable
parameters by incorporating additional metal isotopes, aiming to fully utilize
its capacity for more detailed single-cell analysis [11-13]. Additionally, the
standardization and uniformity of antibody conjugation methods facilitate the
seamless incorporation of specific antibodies into the analysis panel, enabling
the comprehensive interrogation of a wide range of cellular features [14,15].
CyTOF antibody conjugation is notably more streamlined, permitting the
attachment of a broad spectrum of metal isotopes via a consistent methodology.
Essentially, metal isotopes are loaded to a chelator, which is subsequently
linked to the antibody after introduction of functional groups into the antibody
structure. For instance, the maleimide-DTPA (diethylene triamine pentaacetic
acid)—the most prevalent polymeric chelator used for antibody
conjugation—captures all lanthanide isotopes (excluding lanthanum) as well as
additional trivalent metals such as indium and bismuth [9]. Once functional
thiol groups are exposed on the antibody maleimide group of maleimide-DTPA
reacts with these thiol groups. This uniform approach allows for the generation
and utilization of around 40 metal-tagged antibodies using a single methodology.
In contrast, constructing large panels for flow cytometry presents more
complexities since different fluorophores require distinct conjugation chemistry
and approach [16]. Moreover, the lack of commercially available kits for various
fluorophores further limits its utility in experimental setups.

The methodological superiority of CyTOF, underscored by the flexibility in panel
design and antibody conjugation, highly multiplexed analysis, minimal signal
spill-over, the availability of optimized sample multiplexing approaches, lack
of auto-fluorescence, and durability and stability of metal isotopes loaded to
chelators under harsh permeabilization conditions, has established it as a
critical tool in high-throughput single-cell proteomic analysis across various
biomedical fields [9,17]. It has been instrumental in advancing research in
oncology, immunology, infectious diseases, autoimmunity, neuroscience, stem cell
research, developmental biology, and drug discovery by enabling detailed
analysis of cellular populations through multiplexed and high-throughput
analysis, uncovering intricate cellular associations and driving discoveries
[7,18-20]. Beyond the application of metal-tagged antibodies, the integration of
probes equipped with unique metal reporters has further expanded the
capabilities of CyTOF, enabling detailed analyses of complex cellular functions.
This includes assessing antigen-specific immune responses using tetramers, the
detection of hypoxia, tracking of nanoparticle distribution, cell division,
measurement of protein synthesis, and monitoring of proteolytic enzyme
activities [21-28]. These advancements underscore the extensive utility of CyTOF
in probing complex biological systems and enabling in-depth exploration of
intricate cellular dynamics, functions, and interactions.

SAMPLE MULTIPLEXING IN CYTOF

A key advantage of CyTOF technology is the sample multiplexing capability,
allowing for the concurrent analysis of individual samples through various
strategies. These include the use of metal-conjugated antibodies, chelators
preloaded with metals that bind to specific targets, and specific metal
compounds such as thiol-reactive tellurium (TeMal), cisplatin, and osmium (Os)
and ruthenium (Ru) tetroxide [15,29-32]. These methods can be customized and
combined to meet particular research needs, streamlining workflows and enhancing
the scientific accuracy of cellular analysis by improving data quality, reducing
variability, and enabling high-throughput analysis of numerous sample types.

In CyTOF, lanthanides primarily serve as the metal group for antibody
conjugation to assess cellular features of interest [4,8,14]. Metal isotopes
selected for barcoding are carefully chosen to avoid interference with those
used for feature assessment, thus ensuring a seamless workflow. A significant
advantage of CyTOF barcoding is the ability to use combinatorial barcoding
schemes. These schemes allow a single sample to be tagged with various metals,
using a limited number of metals to create a large number of unique Mass Cell
Barcoding (MCB) combinations. For example, '6-choose-3' or '7-choose-3'
barcoding schemes can produce 20 or 35 unique MCBs, respectively. This
capability greatly enhances the capability for high throughput multiplexing in
cellular analysis, facilitating more comprehensive and efficient data
acquisition and analysis. CyTOF barcoding is typically divided into
intracellular and live-cell (surface) barcoding (Table 1).

Feature

Live-cell Barcoding

Intracellular Barcoding

Definition

Barcoding technique that labels cell surfaces with unique identifiers, either
metal-tagged antibodies or metal compounds prior to pooling and downstream
processing.

Barcoding technique that labels cells with unique mass-tag cell barcoding labels
after fixation and permeabilization.

Mass-tag Cell Barcodes
(MCBs)

Utilizes metal-tagged antibodies, RuO4, OsO4 and monoisotopic cisplatin and
TeMal compounds.

Monoisotopic TeMal and cisplatin compounds, RuO4, OsO4 and bifunctional
chelators loaded with Pd, In, rhodium or lanthanides.

Chelators

mDOTA, ITCBE, mDTPA and MCP9 are used for generation of metal-tagged antibodies.

mDOTA, ITCBE and BABE are used for generation of meta-loaded MCBs.

Targeted Groups

Targets specific abundant antigens such as CD45, beta-2-microglobulin, HLA-ABC,
CD298, CD29, and CD98, typically using species-specific antibodies.

Labels cellular components that contain amine or sulfhydryl groups, as well as
fatty acids and aromatic amino acids.

Cell Type

Requires species-specific antibodies tailored to unique antigens present on
cells of a specific species.

Non-species-specific; employs universal tags that indiscriminately bind to
generic cellular components.

Viability

Critical; cells must remain viable through the process to ensure accurate
subsequent downstream analysis.

Not applicable since cells are already fixed.

Feasibility

Less complex since it avoids the extensive cell preparation steps required for
intracellular barcoding.

More complex since it requires extensive cell preparation steps prior to
barcoding.

Advantages

Suitable for samples with low cell counts; allows streamlined downstream
analysis and facilitates multiplexed analysis through the use of multiple
panels.

Ideal for detailed studies of intracellular molecules; allows the generation of
a greater number of unique combinations as “k” increases beyond two.

Disadvantages

Potential alteration of cell behavior due to binding to target molecules;
reduced signal intensity and yield due to competition among MCBs targeting the
same antigenic epitopes; requires abundantly expressed antigens for effective
barcoding.

Fixation and permeabilization processes can modify antigenic epitopes, resulting
in diminished or entirely lost antibody binding capabilities; cell loss due to
complex nature of the procedure and numerous wash steps.

Abbreviations: ITCBE: Isothiocyanobenzyl-EDTA; mDOTA: Maleimido-mono-amide-DOTA;
BABE: Bromoacetamidobenzyl-EDTA; MCP9: Maleimido-Cyclohexyl-Phenyl-9; TeMal:
Tellurium Maleimide; RuO4: Ruthenium Tetroxide; OsO4: Osmium Tetroxide; Pd:
Palladium; In: Indium.

Table 1:Comparison of Live-cell Barcoding and Intracellular Barcoding
Techniques. This table compares two barcoding methods used in CyTOF, focusing on
their key features and applications.

INTRACELLULAR BARCODING

Intracellular barcoding in CyTOF is a methodological approach that labels cells
with unique barcodes after they have undergone fixation and permeabilization
[7,33] (Figure 1). This process allows barcoding reagents to effectively access
and mark various intracellular targets effectively. Originating from
multiplexing techniques initially developed for flow cytometry [34], this
approach employs covalent binding to amine groups on cellular proteins, a
principle shared by both methodologies. However, sample multiplexing techniques
in CyTOF have seen wider adoption compared to flow cytometry, where the
implementation of sample barcoding in flow cytometry has encountered several
challenges. Flow cytometry often suffers from signal spillover between barcoding
and analyte-specific channels, necessitating meticulous panel design and
sometimes leading to the exclusion of certain fluorophores, which compromises
the simultaneous assessment of multiple analytes [35,36]. Additionally, the
allocation of a specific number of fluorophores for barcoding inherently reduces
the number of available channels for analytic purposes in conventional flow
cytometry. This limitation is particularly important in studies requiring the
concomitant assessment of numerous cellular markers. In contrast, CyTOF provides
a versatile and extensive range of parameters with minimal signal spillover and
utilizes strategic metal isotope allocation that enhances cellular feature
assessment without interference between barcoding and analytes.



Figure 1: Overview of CyTOF Analysis and Sample Multiplexing Workflow. This
figure illustrates the sequential steps in CyTOF analysis, starting with the
preparation of single-cell suspension samples. 1) Single-cell suspensions are
prepared from fresh or frozen cells. 2) For live-cell barcoding,cells are
barcoded while viable using MCBs. For intracellular barcoding, cells are fixed,
permeabilized, and labeled with MCBs that primarily mark intracellular targets.
3) Barcoded cells are then pooled and stained with antibodies targeting surface
and intracellular molecules. 4) The pooled and stained samples undergo analysis
through the CyTOF machine, which is followed by a comprehensive bioinformatics
(5) analysis to interpret the high-dimensional data (Created with
BioRender.com).

Advances in intracellular barcoding approach

The pioneering intracellular barcoding strategy developed by Zunder et al. for
CyTOF employed a "6-choose-3" combinatorial scheme using Pd isotopes for MCBs
[33]. This method involved six specific Pd isotopes (102Pd, 104Pd, 105Pd, 106Pd,
108Pd and 110Pd) with each barcode comprising three distinct Pd isotopes to
produce 20 unique MCBs. A significant innovation in this approach is the use of
a chelator, isothiocyanobenzyl-EDTA (ITCBE), which captures bivalent Pd
isotopes. These barcodes are generated using monoisotopic Pd-loaded,
bi-functional chelators ITCBE, which contains amine-reactive moieties,
facilitating the covalent binding of the barcodes to cellular proteins. This
advancement extends the use of traditional trivalent metal isotopes in CyTOF,
broadening the spectrum of usable metals and enhancing sample multiplexing
capabilities for high-throughput single-cell proteomic analysis. Similar to this
foundational approach, subsequent strategies for intracellular barcoding have
been developed. Intracellular barcoding employs various bifunctional chelators,
including thiol-reactive bromoacetamidobenzyl-EDTA (BABE) [37] and
thiol-reactive maleimido-mono-amido-DOTA (mDOTA) [6]. These chelators are adept
at capturing metals and binding to intracellular proteins, similar to ITCBE
[33]. Bifunctional chelators (mDOTA, BABE, and ITCBE) contain one functional
group for creating a stable bond to the antibody and another group that captures
metal isotopes, enabling precise cell labeling for CyTOF barcoding applications
[15,33,37,38]. Furthermore, the integration of osmium and ruthenium tetroxides
(OsO4 and RuO4) provides a unique method by leveraging their ability to form
covalent bonds with fatty acids in cellular membranes and aromatic amino acids
in proteins, thereby expanding the toolkit available for sample barcoding [30].
The addition of TeMal and cisplatin has also enriched these barcoding approaches
[29,32]. Notably, OsO4, RuO4, TeMal, and cisplatin are versatile for use in both
intracellular and live-cell barcoding applications. However, the use of these
compounds requires meticulous consideration due to their propensity to influence
cellular behavior, a factor that is particularly critical in live-cell barcoding
scenarios.

Challenges

A primary challenge in intracellular barcoding involves the need to fix and
permeabilize cells before barcoding, which precedes both surface and
intracellular staining. The fixation and permeabilization process can cause
conformational changes in surface proteins, irreversibly altering antigenic
epitopes that antibodies recognize [39]. These conformational changes can alter
the tertiary structure of antigens which could lead to loss or masking of
epitopes recognized by antibodies. This results in reduced or loss of antibody
binding used for the detection of surface antigens which compromises the
accurate cell surface phenotyping in conjunction with intracellular barcoding
[40]. Thus, the fixation and permeabilization conditions required for
intracellular barcoding are not compatible with all antibodies. This limitation
can restrict the range of detectable antigens, necessitating extensive
validation of antibody panels. These challenges can be mitigated by performing
surface staining prior to the fixation and permeabilization steps required for
intracellular barcoding [40]. Furthermore, it is important to note that some
antigens, typically localized within intracellular granules, may also be
affected by these procedures. Some antigens are periodically internalized into
intracellular compartments before being recycled back to the surface or degraded
[41]. This dynamic process can skew the accurate estimation of surface antigen
expression, leading to potential misidentification of intracellular molecules as
being surface expressed, especially if the staining occurs
post-permeabilization. These challenges highlight the critical need for careful
method selection and protocol optimization to ensure precise results in studies
employing intracellular barcoding techniques.

Conclusion

In conclusion, intracellular barcoding is crucial for high-throughput
single-cell proteomic analysis in CyTOF, offering a more precise assessment of
cellular behavior. Despite its associated challenges, this method is highly
effective at accurately exploring and investigating intracellular pathways and
molecular interactions, facilitating groundbreaking discoveries. Its precise
application greatly improves the accuracy of single-cell proteomic analysis,
enriching our understanding of cellular functions and disease mechanisms. Thus,
intracellular barcoding is invaluable in advancing biological research and
contributing to scientific progress.

LIVE-CELL BARCODING

Live-cell barcoding is a technique employed at the initial steps of CyTOF
analysis. This process involves the labeling of cell surfaces with unique
identifiers, followed by pooling and downstream processing that includes both
surface and intracellular staining. This streamlined approach allows for the
simultaneous analysis of a large number of samples (Figure 1).

The ability of ITCBE to chelate bivalent Pd ions has notably broadened the
spectrum of metal isotopes used in CyTOF, catalyzing the development of novel
live-cell barcoding techniques that utilize monoisotopic Pd-tagged antibodies. A
notable progress in this area was achieved by Mei et al., who devised a strategy
using bifunctional ITCBE loaded with Pd isotopes and tagged to CD45, an antigen
ubiquitously expressed on hematopoietic cells [31]. Employing a '6-choose-3'
barcoding scheme, they successfully achieved the barcoding and pooling of 20
experimental conditions using this method.

However, despite these innovations, ITCBE has demonstrated poor solubility in
buffers conducive to effective conjugation, posing significant challenges and
limiting its practical application in labeling antibodies with Pd isotopes. This
shortcoming necessitated the exploration of alternative chelators, culminating
in the utilization of mDOTA [15] for live-cell barcoding. mDOTA is distinguished
by its excellent solubility in water and its capacity to chelate both bi- and
trivalent metal ions, thereby enabling more efficient antibody conjugation with
Pd isotopes and presenting a substantial improvement over ITCBE for live-cell
barcoding applications. Live-cell barcoding offers several distinct advantages
[42-44]: it provides more streamlined experiments and minimizes batch effects
through simultaneous processing of pooled samples. This method reduces technical
errors and enhances data interpretation, leading to more precise biological
insights. Furthermore, live-cell barcoding conserves valuable samples and is
cost-effective by reducing the number of antibodies and reagents needed, and
facilitates high-throughput analysis, thereby boosting the potential for new
discoveries.

Optimized live-cell barcoding approach

Traditional live-cell barcoding techniques using ITCBE, BABE and mDOTA, have
shown promise for incorporating Pd isotopes into CyTOF applications and various
studies have explored the use of these chelators in both intracellular and
live-cell barcoding approaches (Table 2). However, these monomeric chelators are
limited by their ability to bind only a small number of metal ions, leading to
lower signal intensities [31,42]. Additionally, in n-choose-3 barcoding schemes
that utilize three CD45 antibodies each tagged with a different metal isotope to
barcode a single sample, competitive binding at the same antigenic sites results
in diminished signal intensities due to multiple antibodies targeting identical
epitopes [31,44]. To address these limitations, we explored the use of MCP9, a
polymeric chelator initially developed for conjugating bivalent cadmium (Cd)
isotopes [42]. Notably, MCP9 is capable of binding a higher number of bivalent
metal ions given its polymeric structure, enhancing signal intensities and the
utility of barcoding techniques. Informed by prior developments in chelation
chemistry—such as mDTPA, which was initially tailored for lanthanide metals but
later found to effectively bind trivalent non-lanthanides like indium (113In and
115In) and bismuth (209Bi) [12,13]—we reasoned that MCP9 could similarly be
adapted to chelate bivalent Pd isotopes. Upon confirming that MCP9 can also
chelate Pd isotopes we developed a novel barcoding scheme incorporating MCP9 by
conjugating it with both Cd and Pd isotopes, utilizing seven Cd isotopes (106Cd,
110Cd, 111Cd, 112Cd, 113Cd, 114Cd, and 116Cd) and three Pd isotopes (104Pd,
105Pd, and 108Pd) to CD45 antibodies [42]. We implemented this approach in a
10-choose-2 combinatorial scheme, leveraging the ubiquitously expressed CD45
antigen on hematopoietic cells, which varies in abundance across different
subsets, to validate our barcoding strategy. The selection of CD45 for this
proof-of-concept reflects its widespread use in previous studies, underscoring
its reliability and effectiveness in validating our barcoding strategy.

Study

Type

Purpose

Chelator/
Compound

Isotope

Targeted Groups

Species

Zunder et al. [33]

Intracellular

Novel "6-choose-3" barcoding scheme

ITCBE

Pd

Amine groups

Any

Bodenmiller et al. [7]

Intracellular

High-throughput CyTOF method

mDOTA

Lanthanides

free sulfhydryl groups

Any

Sumatoh et al. [37]

Intracellular

Better chelator

BABE

Pd, In

free sulfhydryl groups

Any

Hartmann et al. [44]

Live

Universal live-cell barcoding

N/A

Pt

B2M, CD298

Human

Muftuoglu et al. [42]

Live

Extended live-cell barcoding

MCP9

Cd, Pd

CD45

Human

Mei et al. [31]

Live

First
live-cell barcoding

ITCBE

Pd, In

CD45

Human

Lai et al. [38]

Live

Lanthanide-based live-cell Barcoding

DN3

Lanthanides

CD45

Human

Charmsaz et al. [43]

Live

Murine live-cell
Barcoding

MCP9, X8

Cd, In

CD29, CD98, CD45

Mouse

McCarthy et al. [29]

Intracellular, Live

monoisotopic cisplatin-based

Cisplatin

Pt

free sulfhydryl groups

Any

Catena et al. [30]

Intracellular, Live

Enhanced multiplexing

RuO4
OsO4

Ru, Os

Fatty acids and aromatic amino acids

Any

Willis et al. [32]

Intracellular, Live

Tellurium-based

TeMal

Te

free sulfhydryl groups

Any

Abbreviations: ITCBE: Isothiocyanobenzyl-EDTA; mDOTA: Maleimido-mono-amide-DOTA;
BABE: Bromoacetamidobenzyl-EDTA; MCP9: Maleimido-Cyclohexyl-Phenyl-9; DN3: A
proprietary polymer used in CyTOF; X8: A proprietary polymer used in CyTOF;
TeMal: Tellurium Maleimide; RuO4: Ruthenium Tetroxide; OsO4: Osmium Tetroxide;
Cd: Cadmium; Pd: Palladium; In: Indium; Te: Tellurium; Ru: Ruthenium; Os:
Osmium.

Table 2: Key CyTOF studies that have developed and employed various barcoding
chemistries and isotopes to enhance cytometric analyses. The table highlights
the diversity of approaches tailored to different scientific needs and
biological specimens.

Advantages: This strategy allowed us to barcode and pool 45 experimental
conditions significantly streamlining our CyTOF experimentations, enhancing our
high throughput along with well-established benefits achieved through barcoding.

High-throughput: Opting for two different CD45 antibodies per sample, instead of
three, was a strategic decision to maintain optimal signal resolution and ensure
higher yields post-sample deconvolution [42]. By constructing each barcode from
any two out of ten possible isotopes and pooling, we can analyze numerous
samples simultaneously compared to traditional schemes [15,33,42]. This
capability is particularly crucial in experiments involving large numbers aimed
at generating comprehensive datasets. The strategic use of a combination of Cd
and Pd isotopes with MCP9 significantly enhances signal intensity and
resolution, which is essential for optimizing sample demultiplexing and
achieving higher yields by accurately assigning barcoded cells back to their
original identities. Moreover, the flexibility of the 10-choose-2 scheme allows
for precise tailoring of experiments to address specific research questions,
facilitating the exploration of a broader range of scientific hypotheses.

Improving cell yield after sample demultiplexing: This barcoding strategy also
optimizes the use of available resources by reducing the amount of antibodies
required, thereby cutting costs and minimizing resource consumption. In CyTOF
experiments, where substantial cell loss through multiple processing steps is
common—often necessitating 1-2 million cells per sample to ensure adequate
counts for analysis—our approach can markedly improve recovery rates. By pooling
multiple small samples into larger barcoded groups, we enhance the likelihood of
recovering adequate cell numbers for analysis. Additionally, the incorporation
of irrelevant or "carrier" cells during the staining process can further improve
recovery, particularly in instances of low starting cell numbers [45]. This
method proves especially beneficial given that our barcoding scheme allows for
the high-throughput processing of numerous features, thus maximizing the
effectiveness and efficiency of CyTOF analysis.

Enhanced high parametric analysis: Our barcoding and pooling strategy combines
numerous samples into a single mixture, which yields high initial cell counts
critical for robust downstream analysis. This mixture can be optionally divided
into multiple subsamples, each can be stained with a different panel. Despite
this division of pooled samples, it is possible to achieve a cell count of 5,000
to 20,000 cells per each barcoded sample after sample demultiplexing, a range
suitable for effective high-dimensional analysis. Achieving this cell number for
downstream analysis after demultiplexing is feasible since the initial cell
number per sample prior to barcoding typically ranges from 1 to 2 million.
Furthermore, the use of sample barcoding significantly reduces cell loss,
ensuring the desired cell count per subsample is consistently achieved. This
approach not only accommodates the inherent variability in sample heterogeneity
with regards to subset composition but also ensures that sufficient cell numbers
are maintained across various experimental conditions. By doing so, we enable
comprehensive and reliable high-dimensional profiling, maximizing the potential
for detailed biological insights. Notably, we can further optimize this process
and design panels in a way to share common surface markers, which act as anchors
for panel integration. Expressions of markers not directly measured in certain
panels can be inferred and imputed using computational approaches, enabling a
comprehensive assessment of cellular features. This integration streamlines
workflows, maximizes data extraction from each cell, and broadens the scope of
proteomic profiling.

Future directions

In our barcoding approach several strategic approaches can be utilized to
increase barcoding depth. In our barcoding scheme, we have not used the rare and
more expensive 102Pd isotope. Incorporating this isotope along with 89Y could
facilitate a 12-choose-2 scheme, enabling more in-depth demultiplexing.
Furthermore, universal barcoding approaches can be developed by integrating
antibodies against commonly expressed antigens such as B2M, CD298, and HLA-ABCs.
This method allows for the customization of barcoding, where antibodies can be
contextually replaced depending on specific analysis needs. This adaptation
would improve the versatility and efficiency of our barcoding techniques,
aligning our methods with the latest advancements in the field and broadening
the scope for future cellular analysis.

FUNDING

This work was supported in part by the Paul and Mary Haas Chair in Genetics, the
National Institutes of Health Cancer Center Support Grant (P30CA016672), and
CPRIT Grants RP130397 and RP121010.



REFERENCES

 1.  Schäfer PSL, Dimitrov D, Villablanca EJ, Saez-Rodriguez J. Integrating
     single-cell multi-omics and prior biological knowledge for a functional
     characterization of the immune system. Nat Immunol. 2024 Mar;25(3):405-17.
 2.  Vandereyken K, Sifrim A, Thienpont B, Voet T. Methods and applications for
     single-cell and spatial multi-omics. Nat Rev Genet. 2023 Aug;24(8):494-515.
 3.  Flynn E, Almonte-Loya A, Fragiadakis GK. Single-Cell Multiomics. Annu Rev
     Biomed Data Sci. 2023 Aug 10;6:313-37.
 4.  Bendall SC, Simonds EF, Qiu P, Amir el-AD, Krutzik PO, Finck R, et al.
     Single-cell mass cytometry of differential immune and drug responses across
     a human hematopoietic continuum. Science. 2011 May 6;332(6030):687-96.
 5.  Bandura DR, Baranov VI, Ornatsky OI, Antonov A, Kinach R, Lou X, et al.
     Mass cytometry: technique for real time single cell multitarget immunoassay
     based on inductively coupled plasma time-of-flight mass spectrometry. Anal
     Chem. 2009 Aug 15;81(16):6813-22.
 6.  Zivanovic N, Jacobs A, Bodenmiller B. A practical guide to multiplexed mass
     cytometry. Curr Top Microbiol Immunol. 2014;377:95-109.
 7.  Bodenmiller B, Zunder ER, Finck R, Chen TJ, Savig ES, Bruggner RV, et al.
     Multiplexed mass cytometry profiling of cellular states perturbed by
     small-molecule regulators. Nat Biotechnol. 2012 Sep;30(9):858-67.
 8.  Bendall SC, Nolan GP, Roederer M, Chattopadhyay PK. A deep profiler's guide
     to cytometry. Trends Immunol. 2012 Jul;33(7):323-32.
 9.  Iyer A, Hamers AAJ, Pillai AB. CyTOF® for the Masses. Front Immunol. 2022
     Apr 14;13:815828.
 10. Dempsey LA. CyTOF analysis of anti-tumor responses. Nat Immunol. 2017 Feb
     15;18(3):254.
 11. Shekhar K, Brodin P, Davis MM, Chakraborty AK. Automatic Classification of
     Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE). Proc Natl
     Acad Sci U S A. 2014 Jan 7;111(1):202-7.
 12. Behbehani GK, Samusik N, Bjornson ZB, Fantl WJ, Medeiros BC, Nolan GP. Mass
     Cytometric Functional Profiling of Acute Myeloid Leukemia Defines
     Cell-Cycle and Immunophenotypic Properties That Correlate with Known
     Responses to Therapy. Cancer Discov. 2015 Sep;5(9):988-1003.
 13. Han G, Chen SY, Gonzalez VD, Zunder ER, Fantl WJ, Nolan GP. Atomic mass tag
     of bismuth-209 for increasing the immunoassay multiplexing capacity of mass
     cytometry. Cytometry A. 2017 Dec;91(12):1150-63.
 14. Arnett LP, Rana R, Chung WW, Li X, Abtahi M, Majonis D, Bassan J, Nitz M,
     Winnik MA. Reagents for Mass Cytometry. Chem Rev. 2023 Feb
     8;123(3):1166-205.
 15. Han G, Spitzer MH, Bendall SC, Fantl WJ, Nolan GP. Metal-isotope-tagged
     monoclonal antibodies for high-dimensional mass cytometry. Nat Protoc. 2018
     Oct;13(10):2121-48.
 16. Baumgarth N, Roederer M. A practical approach to multicolor flow cytometry
     for immunophenotyping. J Immunol Methods. 2000 Sep 21;243(1-2):77-97.
 17. Chattopadhyay PK, Winters AF, Lomas WE 3rd, Laino AS, Woods DM.
     High-Parameter Single-Cell Analysis. Annu Rev Anal Chem (Palo Alto Calif).
     2019 Jun 12;12(1):411-30.
 18. Tognetti M, Gabor A, Yang M, Cappelletti V, Windhager J, Rueda OM, et al.
     Deciphering the signaling network of breast cancer improves drug
     sensitivity prediction. Cell Syst. 2021 May 19;12(5):401-18.e12.
 19. Palii CG, Cheng Q, Gillespie MA, Shannon P, Mazurczyk M, Napolitani G, et
     al. Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed
     Lineage-Specific Transcription Factors Determine Cell Fate. Cell Stem Cell.
     2019 May 2;24(5):812-20.e5.
 20. Bachas C, Duetz C, van Spronsen MF, Verhoeff J, Garcia Vallejo JJ, Jansen
     JH, et al. Characterization of myelodysplastic syndromes hematopoietic stem
     and progenitor cells using mass cytometry. Cytometry B Clin Cytom. 2023
     Mar;104(2):128-40.
 21. Simoni Y, Fehlings M, Newell EW. Multiplex MHC Class I Tetramer Combined
     with Intranuclear Staining by Mass Cytometry. Methods Mol Biol.
     2019;1989:147-58.
 22. Leong ML, Newell EW. Multiplexed Peptide-MHC Tetramer Staining with Mass
     Cytometry. Methods Mol Biol. 2015;1346:115-31.
 23. Newell EW, Sigal N, Nair N, Kidd BA, Greenberg HB, Davis MM. Combinatorial
     tetramer staining and mass cytometry analysis facilitate T-cell epitope
     mapping and characterization. Nat Biotechnol. 2013 Jul;31(7):623-9.
 24. Edgar LJ, Vellanki RN, Halupa A, Hedley D, Wouters BG, Nitz M.
     Identification of hypoxic cells using an organotellurium tag compatible
     with mass cytometry. Angew Chem Int Ed Engl. 2014 Oct 20;53(43):11473-7.
 25. Yang YS, Atukorale PU, Moynihan KD, Bekdemir A, Rakhra K, Tang L, et al.
     High-throughput quantitation of inorganic nanoparticle biodistribution at
     the single-cell level using mass cytometry. Nat Commun. 2017 Jan
     17;8:14069.
 26. Frei AP, Bava FA, Zunder ER, Hsieh EW, Chen SY, Nolan GP, et al. Highly
     multiplexed simultaneous detection of RNAs and proteins in single cells.
     Nat Methods. 2016 Mar;13(3):269-75.
 27. Bassan J, Willis LM, Vellanki RN, Nguyen A, Edgar LJ, Wouters BG, et al.
     TePhe, a tellurium-containing phenylalanine mimic, allows monitoring of
     protein synthesis in vivo with mass cytometry. Proc Natl Acad Sci U S A.
     2019 Apr 23;116(17):8155-60.
 28. Poreba M, Groborz KM, Rut W, Pore M, Snipas SJ, Vizovisek M, et al.
     Multiplexed Probing of Proteolytic Enzymes Using Mass Cytometry-Compatible
     Activity-Based Probes. J Am Chem Soc. 2020 Sep 30;142(39):16704-15.
 29. McCarthy RL, Mak DH, Burks JK, Barton MC. Rapid monoisotopic cisplatin
     based barcoding for multiplexed mass cytometry. Sci Rep. 2017 Jun
     19;7(1):3779.
 30. Catena R, Özcan A, Zivanovic N, Bodenmiller B. Enhanced multiplexing in
     mass cytometry using osmium and ruthenium tetroxide species. Cytometry A.
     2016 May;89(5):491-7.
 31. Mei HE, Leipold MD, Schulz AR, Chester C, Maecker HT. Barcoding of live
     human peripheral blood mononuclear cells for multiplexed mass cytometry. J
     Immunol. 2015 Feb 15;194(4):2022-31.
 32. Willis LM, Park H, Watson MWL, Majonis D, Watson JL, Nitz M.
     Tellurium-based mass cytometry barcode for live and fixed cells. Cytometry
     A. 2018 Jul;93(7):685-94.
 33. Zunder ER, Finck R, Behbehani GK, Amir el-AD, Krishnaswamy S, Gonzalez VD,
     et al. Palladium-based mass tag cell barcoding with a doublet-filtering
     scheme and single-cell deconvolution algorithm. Nat Protoc. 2015
     Feb;10(2):316-33.
 34. Krutzik PO, Nolan GP. Fluorescent cell barcoding in flow cytometry allows
     high-throughput drug screening and signaling profiling. Nat Methods. 2006
     May;3(5):361-8.
 35. Roederer M. Compensation in flow cytometry. Curr Protoc Cytom. 2002
     Dec;Chapter 1:Unit 1.14.
 36. McLaughlin BE, Baumgarth N, Bigos M, Roederer M, De Rosa SC, Altman JD, et
     al. Nine-color flow cytometry for accurate measurement of T cell subsets
     and cytokine responses. Part II: Panel performance across different
     instrument platforms. Cytometry A. 2008 May;73(5):411-20.
 37. Sumatoh HR, Teng KW, Cheng Y, Newell EW. Optimization of mass cytometry
     sample cryopreservation after staining. Cytometry A. 2017 Jan;91(1):48-61.
 38. Lai L, Ong R, Li J, Albani S. A CD45-based barcoding approach to multiplex
     mass-cytometry (CyTOF). Cytometry A. 2015 Apr;87(4):369-74.
 39. Behbehani GK, Thom C, Zunder ER, Finck R, Gaudilliere B, Fragiadakis GK, et
     al. Transient partial permeabilization with saponin enables cellular
     barcoding prior to surface marker staining. Cytometry A. 2014
     Dec;85(12):1011-9.
 40. Turaç G, Hindley CJ, Thomas R, Davis JA, Deleidi M, Gasser T, et al.
     Combined flow cytometric analysis of surface and intracellular antigens
     reveals surface molecule markers of human neuropoiesis. PLoS One. 2013 Jun
     24;8(6):e68519.
 41. Arancibia-Cárcamo IL, Fairfax BP, Moss SJ, Kittler JT. Studying the
     localization, surface stability and endocytosis of neurotransmitter
     receptors by antibody labeling and biotinylation approaches. In: Kittler
     JT, Moss SJ, Eds. The Dynamic Synapse: Molecular Methods in Ionotropic
     Receptor Biology. United Kingdom: CRC Press; 2006.
 42. Muftuoglu M, Li L, Liang S, Mak D, Lin AJ, Fang J, et al. Extended
     live-cell barcoding approach for multiplexed mass cytometry. Scientific
     Reports. 2021 Jun 11;11(1):12388.
 43. Charmsaz S, Gross N, Jaffee E, Ho WJ. A global live cell barcoding approach
     for multiplexed mass cytometry profiling of mouse tumors. JCI Insight. 2021
     Apr 8;6(7):e143283.
 44. Hartmann FJ, Simonds EF, Bendall SC. A Universal Live Cell
     Barcoding-Platform for Multiplexed Human Single Cell Analysis. Sci Rep.
     2018 Jul 17;8(1):10770.
 45. Wagar LE. Live Cell Barcoding for Efficient Analysis of Small Samples by
     Mass Cytometry. Methods Mol Biol. 2019;1989:125-35.

CELL SIGNALING


Contents
Register

EDITORIAL BOARD

Bangyan L. Stiles, Ph.D

Southern California

USA

Liang Liu, Ph.D.

Medical Center Boulevard Winston-Salem

USA

Amma Adomako-Bonsu,

University of Notttingham

UK


TWITTER FEED



PROBIOLOGISTS LIMITED

Our Locations
 * Europe
 * 63-66 Hatton Garden, London,
 * England, EC1N 8LE


 * Contact Us
 * Tel   : +1 302 261 2410
 * Whatsapp  : +1 302 261 2410
 * contact@probiologists.com

QUICK LINKS

 * Home           Author Guidelines
 * About Us     Policies
 * Journals       Online Submission
 * Articles         Contact US

©Copyright ProBiologists 2024