Proteomics: Technologies and Applications
eBook
Published: October 3, 2024
Credit: Technology Networks
The quest to understand complex diseases has driven significant advancements in proteomics, and researchers continue to make important discoveries by mapping the intricate networks of proteins at work in the body.
Through a collection of articles, guides and graphics, this eBook explores the pivotal role proteomics is playing in our understanding of health and disease.
Download this eBook to explore how proteomics is advancing:
- Drug discovery and pharmaceutical development
- Neurodegenerative disease research
- Diagnostic development and biomarker discovery
FOREWORD
The quest to understand complex diseases has driven significant advancements in
proteomics, and researchers continue to make important discoveries by mapping the
intricate networks of proteins at work in the body.
From uncovering disease mechanisms to advancing drug development, this eBook
illuminates the pivotal role of proteomics in understanding health and disease.
The efforts highlighted in this eBook demonstrate the power of interdisciplinary research
in driving breakthroughs, from understanding protein aggregation in Alzheimer’s and
Parkinson’s diseases to identifying new therapeutic targets and biomarkers that promise
earlier and more precise diagnoses.
Whether you are a seasoned researcher or a newcomer to the field, this eBook provides
valuable perspectives on the current trends and future directions of proteomics
technologies and applications.
The Technology Networks editorial team
The large-scale study of proteins, known as proteomics,
provides unique insights into the regulation of biological
processes and mechanisms of disease. Unlike the largescale study of genes (genomics), protein expression
changes over time, between cells and according to
environmental conditions, offering a much more
dynamic and complex picture.
“Proteomics gives you a valuable snapshot of what is
actually going on inside a biological system,” says Claire
Eyers, professor of Biological Mass Spectrometry in the
Department of Biochemistry, Cell and Systems Biology
and director of The Centre for Proteome Research
(CPR) at the University of Liverpool, UK. “It is relevant
to all areas of biology, there is no syndrome or disease
which will not benefit from proteomic analyses.”
However, studying the proteome is arguably more
challenging than analyzing the genome. Unlike
genomics and transcriptomics methods, proteins can’t
be amplified before their analysis. As Fabian Coscia,
group Leader at the Max Delbrück Center for Molecular
Medicine (MDC), Berlin, Germany, explains, there is
no PCR method equivalent in proteomics. “We need
to develop near lossless sample preparation methods
that allow us to deliver trace sample amounts to the
analytical device, but also highly sensitive analytical
tools and instruments that can robustly analyze them.”
Advances in proteomic methods and data analysis tools
are helping researchers identify and quantify more
proteins in smaller samples, faster and more robustly.
In this article, we explore some of the approaches that
scientists are using to find early markers of disease,
new drug targets and strategies to overcome resistance
to existing treatments. We also take a look at progress
in understanding the range of protein structures that
can arise from a single gene (proteoforms) and protein
sequencing, which will help take proteomics to the
next level.
PROTEOMICS
Dissecting the Proteome To
Understand Disease
Monica Hoyos Flight, PhD
4
Credit: iStock
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PROTEOMICS: TECHNOLOGIES AND APPLICATIONS 5
Insights from MS-based
approaches in proteomics
Of all the established methods to study proteomics,
mass spectrometry (MS)-based approaches are still the
most widely used to detect and quantify protein levels.
MS involves vaporizing samples under the influence
of high voltage to create charged ions, separating
them according to their mass-to-charge ratio and then
detecting and measuring the abundance of each.
“The sensitivity of MS has rapidly evolved in recent
years so now, for the first time, can analyze a couple of
thousands of proteins from very little sample amount,
including single cells,” Coscia says. Furthermore,
advances in robotics and artificial intelligence have
enabled the automation of workflows, making sample
preparation and analysis much more streamlined. “With
a robotics platform, the time and cost of processing
a serum sample has dramatically decreased and
reproducibility has improved,” says Eyers.
Eyers and her team are developing MS-based methods
to quantify specific protein modifications in disease
contexts. Post-translational modifications (PTMs),
such as phosphorylation and sulfation, change how
proteins behave and are associated with various
biochemical pathways involved in cancer and infection.
“The energy required to displace these small chemical
groups in the mass spectrometer is different, so you can
use different energetics to discriminate between the
two,” she explains.
Protein phosphorylation is a reversible and dynamic
PTM that can quickly affect protein–protein interactions
and cell signaling events. In collaboration with colleagues
at Newcastle University, Eyers has been exploring how
aberrant phosphorylation of the transcription factor NFκB in B cell lymphomas contributes to the development
of resistance to inhibitors of the DNA damage checkpoint
kinase CHK1. 1
This type of study could help identify
combination inhibitors to minimize cancer drug
resistance.
A recent pan-cancer study involving samples from over
1000 patients identified shared PTM profiles across
multiple cancer types linked to cancer-related processes
such as DNA repair and immune evasion. 2
These
patterns may have gone undetected in smaller cohorts
or by genomic studies. Further understanding how
PTMs affect the function of proteins will reveal new
mechanisms underlying disease that can potentially
lead to better diagnostics and treatments.
Progress in spatial proteomics
Coscia’s team is establishing methods for performing
high-resolution spatial proteomics to shed light on
cancer cell properties. Spatial proteomics is a branch of
proteomic research that allows researchers to examine
how proteins are spatially organized in cells and
tissues. This is particularly useful to study cancer cell
heterogeneity and the role that the microenvironment
plays in tumour development and progression.
“We know that some cells thwart the aggressive
behaviour of neighbouring cells, while others help
them to spread through the body, but this this dynamic
interplay is inadequately understood to date,” he Coscia
says. His team is using Deep Visual Proteomics to map
the proteins of cancer cells and of neighboring cells.
Deep Visual Proteomics involves four steps: (i) imaging
a tissue sample slice with a high-resolution microscope,
(ii) identifying and classifying cells by phenotype using
AI, (iii) isolating individual cells from the tissue with
an automated laser beam and (iv) performing ultrasensitive MS to determine the protein composition and
projecting the results onto the original image.
With this tool, researchers are able to examine how
the proteome is influenced by the type and state of
neighboring cells and learn how diverse cell interactions
are linked to disease outcomes and therapeutic
responses. “Such data are a true treasure trove for the
identification of novel therapeutic targets and diseasespecific biomarkers,” Coscia says.
Although the technique is currently used to
retrospectively analyze cancer patient samples,
they hope to apply it prospectively to aid treatment
decisions in the future. Importantly, Deep Visual
Proteomics could be useful to understand the role of cell
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PROTEOMICS: TECHNOLOGIES AND APPLICATIONS 6
interactions in other disease contexts such as infection
and neurodegeneration.
The promise of top-down
proteomics and single-molecule
sequencing
Depending on how proteins are processed, MS-based
methods are described as “bottom-up” or “top-down”.
In bottom-up approaches all proteins in the sample are
enzymatically or chemically digested into peptides that
serve as input to the mass spectrometer. The resulting
peptide sequences are compared to existing databases
to infer identity of the original proteins in the sample.
By contrast, top-down proteomics aims to identify
and profile intact proteoforms, so proteins in a sample
are first separated and then analyzed by MS as intact
protein ions.
Although the bottom-up approach remains the method
of choice for protein identification and characterization,
only a fraction of the total peptide population of a given
protein is identified and, hence, information on only a
portion of the protein sequence is obtained. 3
Top-down proteomics can provide access to the
complete protein sequence and has obvious advantages
when it comes to detecting protein isoforms,
degradation products and site-specific PTMs. However,
intact proteins (vs. the smaller peptides used in bottomup) are more difficult to efficiently fragment inside the
instrument and identify using current search algorithms.
Advances in separation technologies, MS instrumentation and data analysis tools are rapidly improving the
sensitivity and throughput of top-down proteomics. 4
In 2023, using a highly sensitive single-cell top–down
proteomics method, Jake Melby et al. were able to detect
multiple isoforms of a large motor protein that drives
muscle contraction and establish a direct relationship
between proteoforms and muscle fibre types.5
This
study highlights the potential of top-down proteomics
for understanding how proteoforms modify cell function.
Initiatives such as the Human Proteoform Project,
which aims to generate a definitive reference set of the
proteoforms produced from the genome, are expected
to revolutionize our understanding of human health and
disease. 6
At the time of writing, the Human Proteoform
Atlas, a resource linking experimentally identified
proteoforms to human cells, tissues and disease,
contains over 60,000 unique proteoforms.
Eyers is keeping a close eye on ways to identify
and characterize proteoforms. “MS may not be the
technology that ends up coming to the forefront,” she
says. Though still in early stages, non-MS-based singlemolecule methods, such as single-molecule sequencing,
enable researchers to detect all the different ways
individual proteins are modified.
Efforts to adapt nanopore-based sequencing to
proteins are starting to yield interesting results. Nova
et al. detected PTMs at the single-molecule level on
immunopeptide sequences with cancer-associated
phosphate variants. This was achieved by chemically
linking the peptides to a DNA oligonucleotide that
is translocated in a stepwise manner through a nanopore using a DNA motor enzyme, as in nanopore
DNA sequencing. 7
Meanwhile, Sauciuc et al. engineered an electroosmotic
flow that can translocate natural polypeptides across
nanopores, remarkably increasing the feasibility of
protein sequencing. 8
“My hope is that by combining
high-throughput cell-based
screening and single-cell
proteomics, we can move
towards both personalized
diagnostics and individualized
therapies. That is, at least,
where my lab is heading.”
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PROTEOMICS: TECHNOLOGIES AND APPLICATIONS 7
Despite great excitement around these developments,
there is a risk of spending time and money on using
a new technology that is not relevant to the problem
under investigation, Eyers points out. When it comes
to moving proteomics towards the clinic, methods need
to be robust and high-throughput. It’s not just about
being able to acquire precise data on clinically important
biomarkers but making sure the technology “fits” into
drug discovery and development pipelines, or that the
results be translated into new assays for use in a clinical
chemistry laboratory.
Professor Jennifer Van Eyk and her team at CedarsSinai Medical Centre in California are developing
and optimizing proteomic technologies for clinical
applications. They have established a standardized
MS-based workflow that can accommodate different
types of biofluid sample, while achieving the precision
and reproducibility required to develop translatable
clinical biomarkers.9
They are also contributing to the
development of best practice guidelines for performing,
benchmarking and reporting single-cell proteomics
experiments. 10
“My hope is that by combining high-throughput cellbased screening and single-cell proteomics, we can
move towards both personalized diagnostics and
individualized therapies. That is, at least, where my lab
is heading,” Van Eyk says.
ABOUT THE INTERVIEWEES
Dr. Claire Eyers is professor of Biological Mass Spectrometry in
the Department of Biochemistry, Cell and Systems Biology at the
University of Liverpool, UK, with an interest in proteomics method
development and application primarily in the area of cell signaling
and disease. She is also director of The Centre for Proteome
Research (CPR) and Associate Pro Vice Chancellor (Research and
Impact) for the Faculty of Health and Life Sciences at the University
of Liverpool.
Dr. Fabian Coscia is a group Leader at the Max Delbrück Center
for Molecular Medicine (MDC) in Berlin, Germany. In 2023 he
was awarded an European Research Council (ERC) grant to
establish methods for performing high-resolution spatial
proteomics and apply them to complex tumor tissue to understand
how cancer cells become drug resistant.
Professor Jennifer Van Eyk is an international leader in clinical
proteomics interested in the molecular basis behind a variety
of cardiovascular disorders. Her lab, affiliated with the CedarsSinai Smidt Heart Institute and the Advanced Clinical Biosystems
Research Institute at Smidt Heart Institute, in California, USA, is
developing large-scale quantitative mass spectrometry methods
to decipher the role of protein expression profiles on disease
progression.
REFERENCES
1. Hunter JE, Campbell AE, Butterworth JA, et al. Mutation
of the RelA(p65) Thr505 phosphosite disrupts the DNA
replication stress response leading to CHK1 inhibitor
resistance. Biochem J. 2022. doi: 10.1042/BCJ20220089
2. Geffen Y, Anand S, Akiyama Y, et al. Pan-cancer analysis
of post-translational modifications reveals shared
patterns of protein regulation. Cell. 2023;186(18):3945-
3967.e26. doi: 10.1016/j.cell.2023.07.013
3. Po A, Eyers CE. Top-down proteomics and the
challenges of true proteoform characterization. J
Proteome Res. 2023;22(12):3663-3675. doi: 10.1021/acs.
jproteome.3c00416
4. Catherman AD, Skinner OS, Kelleher NL. Top
Down proteomics: Facts and perspectives. BRRC.
2014;445(4):683-693. doi:10.1016/j.bbrc.2014.02.041
5. Melby JA, Brown KA, Gregorich ZR, et al. High
sensitivity top–down proteomics captures single
muscle cell heterogeneity in large proteoforms. PNAS.
2023;120(19):e2222081120. doi: 10.1073/pnas.2222081120
6. Smith LM, Agar JN, Chamot-Rooke J, et al. The human
proteoform project: Defining the human proteome. Sci
Adv. 2021. doi: 10.1126/sciadv.abk0734
7. Nova IC, Ritmejeris J, Brinkerhoff H, Koenig TJR, Gundlach
JH, Dekker C. Detection of phosphorylation posttranslational modifications along single peptides with
nanopores. Nat Biotechnol. 2023. doi: 10.1038/s41587-023-
01839-z
8. Sauciuc A, Morozzo della Rocca B, Tadema MJ. et al.
Translocation of linearized full-length proteins through an
engineered nanopore under opposing electrophoretic
force. Nat Biotechnol. 2023. doi: 10.1038/s41587-023-
01954-x
9. Mc Ardle A, Binek A, Moradian A, et al. Standardized
workflow for precise mid- and high-throughput
proteomics of blood biofluids. Clin Chem. 2022;68(3):450-
460. doi: 10.1093/clinchem/hvab202
10. Gatto L, Aebersold R, Cox J, et al. Initial
recommendations for performing, benchmarking
and reporting single-cell proteomics experiments. Nat
Methods. 2023;20(3):375-386. doi: 10.1038/s41592-023-
01785-3
8 PROTEOMICSCredit: iStock
Mass spectrometry imaging (MSI) technology has
existed in simple form for decades, but recent advances
in MS sensitivity and data analysis means it’s finally
coming of age.1
In this article, we explore how MSI is
evolving into a high-resolution spatial biology toolset
to transform the traditional model of drug discovery
and development.
The evolving role of MS in drug
development
MS technologies play a crucial role in drug discovery
and development, serving as effective tools for the swift
identification and quantification of complex molecules.2
Modern MS methods have greatly enhanced the ability
to analyze low levels of potential drug molecules
– from oligonucleotides, to peptides, proteins and
small molecules, and are now used across the drug
development pipeline from target discovery, compound
screening, and toxicity and quality control testing2
, as
outlined in Table 1.
Mass Spectrometry Imaging in
Pharmaceutical Development
Joanna Owens, PhD
Stage of
Drug R&D
Example applications
Discovery • MS-based proteomics and metabolomics
on clinical tissue samples are used for target
identification/validation and to gain insights
into a drug’s mechanism of action.3
• MS plays a pivotal role in determining the
structure and characteristics of potential drug compounds, many of which
are combinatorial-chemistry synthesis
products.2,3
• MS has increasingly become the method
of choice in high-throughput or ultra-highthroughput screening.3,4 Credit: iStock
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PROTEOMICS: TECHNOLOGIES AND APPLICATIONS 9
Many of these applications have traditionally involved
bulk analysis of cells or tissues, but advances in MSI
technologies mean it’s now possible to carry out
spatial chemical analysis at the single-cell level. This
advancement is paving the way for novel applications in
drug discovery and development.
What is MS imaging?
“Mass spectrometry imaging is a way to look at
metabolism in a spatial manner, which gives you much
more information than just analyzing the bulk tissue,”
explained Professor Brent Stockwell of Columbia
University, USA. “Traditionally, you would administer a
drug to an animal, analyze the bulk liver tissue and get a
concentration of the drug at a particular timepoint, and
this gives you useful information, but this cannot tell
you which cells the drug accumulates in and what the
impact of the drug was in terms of other metabolites and
measures of the cell state.”
MSI achieves this by chemically analyzing snapshots,
called a pixel, at a single point within a tissue. For each
pixel, molecules are extracted and introduced into
the ionization source of the MS instrument, which
separates every molecule by its mass-to-charge ratio
and determines their relative abundance in the sample.
From this, you can visualize the abundance of different
molecules across the tissue.
“There’s an inherent trade-off in the MS imaging
approach: if you use a bigger pixel size, you cover more
tissue but you get less spatial resolution to be able to see
how patterns vary,” said Stockwell.
“However, more sensitive MS instruments together
with better ionization methods are making it possible
to reliably detect minute amounts of sample. This,
combined with improved software for data analysis and
annotation, is expanding the uses for MS imaging.”
The evolution of MS imaging
MSI was first developed more than 50 years ago using
secondary ion mass spectrometry (SIMS), and the most
widely used MSI method today is MALDI.1
But despite
its widespread use, MALDI-based MSI is not without its
limitations – the fragmentation of biological molecules
and careful consideration of the matrix for each
study are a few examples.1
Other ionization methods
have been used for MS imaging, such as desorption
electrospray ionization (DESI) and nanoDESI which
make it possible to analyze non-volatile molecules
without fragmentation.1
Still, it was not until recently
that the technology matured to a point that allows for
high-impact studies.
“One downside to conventional MALDI methods is
the chemical preparation you need to use to be able to
detect certain molecules,” explained Professor David
Muddiman, of North Carolina State University, USA.
Muddiman has spent nearly two decades developing
a less destructive ionization approach called matrixassisted laser desorption electrospray ionization
(MALDESI) which makes it possible to directly analyze
a diverse range of biological molecules without requiring
chemical derivatization in a tissue.1
“For example,
neurotransmitters are tiny molecules that the matrix
in MALDI interferes with, so you need to treat them
Stage of
Drug R&D
Example applications
Development • In drug development, liquid
chromatography-mass spectrometry (LCMS) is an essential workhorse technology
used to identify and characterize the
active drug and its metabolites in different
tissue samples to establish the absorption,
distribution, metabolism and excretion
(ADME) profile of a drug candidate.5,6,7
• MS is also important for identifying,
monitoring and validating biomarkers
throughout drug development.8
Quality control • MS technologies are critical tools for
ensuring the quality of traditional smallmolecule drugs during formulation and
manufacturing.
• MS is increasingly used to confirm the
identity, biophysical properties and purity
of biopharmaceuticals such as monoclonal
antibodies.9,10
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PROTEOMICS: TECHNOLOGIES AND APPLICATIONS 10
with a reagent to bring them into a higher mass range.
With MALDESI-based MS imaging, you can analyze the
endogenous neurotransmitters in the tissue without any
pre-treatment.”
The same applies to glycans – carbohydrate groups
added co- and post-translationally to proteins that play
crucial roles in biology – which are easily fragmented
during conventional MALDI-MS. “If you look in the
literature at MS imaging using MALDI, there are
very few instances where analysis has been able to
identify sialic acids – terminal monosaccharides on
carbohydrates – and there’s no method to recover that
information through bioinformatics. This is because
there’s no way of knowing what the original molecule in
the sample was. With our method, we are reading back
authentically the biology that’s been presented to us.”
MS imaging opportunities in drug
development
The ability to track the single-cell pharmacokinetics
and pharmacodynamics of a drug using MS imaging has
been coined by Stockwell as “spatial pharmacology”.11
“Spatial biology methods such as spatial transcriptomics
or proteomics can give you information about the cell
types and cell communities and the state of individual
cells,” he explained. “But right now, there’s a layer of
information you can’t get directly from those methods
– and that’s the small-molecule products of those
metabolic reactions. But with MS imaging you can see
the abundance of those metabolites across the tissue in
a spatially defined manner.”
In the long term, there could be a potential application
for MSI in late-stage drug development, where
MALDI-based MS is currently the gold standard for
characterizing the distribution of drug candidates in
development. In the short term, there is a clear role for
MSI in the drug discovery pipeline. “I think the demand
right now for MS imaging is in looking at disease models
versus healthy normal tissues,” noted Stockwell. “It
can help to understand disease mechanisms, find new
targets and validate drug candidates from screening at
an early stage.”
As the technology becomes automated and higher
throughput, it becomes a more feasible choice for use
in drug screening. “Scientists in biopharma have
adapted IR-MALDESI to measure around 22 wells
per second for screens involving a simple enzymatic
metabolic readout12, and around 1–3 wells per second for
more complex high-content screens,” said Muddiman.
“It’s potentially turning the drug discovery pipeline on
its head – by starting with the experiment that really
matters – the phenotype of a drug candidate, whether
it hits its target and identifying any off-target effects.”
Only in the past few years has it become possible to
look at single-cell resolution using MSI and it’s still a
relatively specialized field. “As companies start to adopt
these latest advances that give single-cell resolution,
they will gain more useful information and find new
applications that will be commonly implemented into
their workflows,” said Stockwell.
“The cell is the fundamental unit of biology, it’s the
building block of organisms. If you can’t see the
individual cells, you’re always going to be somewhat
in the dark.”
ABOUT THE INTERVIEWEES
Brent R. Stockwell is chair of the department of biological sciences
and a professor at Columbia University in the departments of
biological science and chemistry. His research involves the
“The cell is the
fundamental unit of
biology, it’s the building
block of organisms. If you
can’t see the individual
cells, you’re always going
to be somewhat
in the dark.”
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PROTEOMICS: TECHNOLOGIES AND APPLICATIONS 11
discovery of small molecules that can be used to understand and
treat cancer and neurodegeneration, with a focus on biochemical
mechanisms governing cell death.
Dave Muddiman is the Jacob and Betty Belin Distinguished
Professor of Chemistry at NC State University. His group
focuses on the development of innovative mass spectrometry
measurements to solve important biological proble
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