Proteomic research provides a global view of the processes underlying healthy and diseased cellular processes at the protein level.
Over the years, the sensitivity and accuracy of mass spectrometry have advanced to the point where proteins can be reliably detected, and various other proteomic techniques have been developed and optimized, ranging from microarrays to antibody-, gel- and chromatography-based methods.
Through a selection of articles, interviews and graphics, this eBook will provide readers with an overview of key advances in proteomics technologies and the applications of proteomics research.
Download this eBook to explore topics including:
- Recent applications of proteomics
- Single-cell proteomics
- Protein biomarkers and disease
Recent Applications of
Mass Spec vs Single-
How Collaboration and
Curiosity Make for a
Recent Applications of Proteomics 4
Single-Cell Proteomics: Mass Spec vs Single-Molecule Sequencing 8
Advances in Proteomics & Metabolomics 2023 10
Infographic: Applications of Mass Spectrometry 12
News Roundup: Protein Biomarkers and Disease 13
Infographic: Western Blotting Troubleshotting 15
How Collaboration and Curiosity Make for a Successful Scientist 16
Advancing Antigen Discovery With Microfluidics Automation
for Sparse Samples 19
Detecting Cancer From a Droplet of Blood 21
The advent of “omics” has changed the scale of life sciences
research. While transcriptomics provides a useful overview
of global gene expression, proteomics attempts to provide
a comprehensive insight into the expression, structure and
function of the entire set of proteins encoded by an organism
at a given time.1,2 Technological and methodological advances
in proteomics workflows have contributed to a linear
increase in proteomic investigations across different fields,
including medical research, drug discovery, microbiology
and plant biology (Figure 1). This listicle outlines basic
concepts of proteomic workflows and lists some of the latest
applications across different research disciplines.
METHODS AND TECHNIQUES
The proteomic era has recently blossomed thanks to the
advances in mass spectrometry (MS) technologies and data
analysis tools. The analysis of proteins can be grouped into
three main types:3
Recent Applications of Proteomics
Mariana Gil, PhD
1992 1997 2002 2007 2012 2017 2022
Number of publication
Figure 1: Growth in the number of publications using proteomic workflows. Data sourced from PubMed. Credit: Mariana Gil
Credit: iStock. TechnologyNetworks
Cell or Tissue Data Analysis
Cell or Tissue
• Expression proteomics measuring changes in the levels
of protein expression under different conditions
• Structural proteomics studying the three-dimensional
structure of proteins and how they change in response to
• Functional proteomics aiming to understand proteins’
function and their interactions.
Typically, proteomics workflows include four steps:3,4
1. Sample preparation methods depend on the sample and
the goal of the experiment. This is a critical step as its accuracy
can determine the success of the whole workflow.
2. Separation can be achieved using antibody-based
methods (i.e., western blotting and enzyme-linked immunosorbent
assay (ELISA)), gel-based methods (i.e.,
SDS-PAGE and 2D-DIGE) or chromatography-based
approaches (i.e., affinity chromatography, size exclusion
chromatography (SEC), ion-exchange chromatography
(IEXC) and liquid chromatography (LC)).
3. Identification of proteins can be achieved using MS,
Edman sequencing or protein microarrays.
4. Data analysis is typically performed using sequence database
searching software (e.g., Sequent, Mascot, Comet
This general workflow can be applied to top-down and bottom-
up approaches (Figure 2). In top-down proteomics, the
proteins in a sample are first separated before being individually
characterized.3,5 In contrast, in bottom-up proteomics, all
the proteins in a sample are first digested using trypsin and the
resulting mixture of peptides is then analyzed.3,5
Proteomics has revolutionized medical research and enables
researchers to identify novel biomarkers for the diagnosis and
treatment of different diseases, including cancer, neurodegenerative
disorders and infectious diseases.3 It is also extensively
used in drug discovery to understand the protein targets of
newly developed drugs and to monitor their effect on the
protein levels.3 YetNumber of publications of proteomics
go beyond human health. For example, it can be applied to
agriculture,6 animal husbandry,7 environmental science,8 food
science,9 forensics10 and astrobiology.11 Some of the latest
studies across different disciplines are explored below.
Autoimmune encephalitis (AE) includes a group of non-infectious
inflammatory conditions of the central nervous
system caused by an imbalanced immune response. In a
recent study, researchers used proteomics to understand the
complex pathophysiological mechanisms of this disease. Dr.
Saskia Räuber and colleagues compared the cerebrospinal flu-
Figure 2: Top-down and bottom-up
approaches for proteomics.
id protein profile of different types of AE patients and control
patients. They found that AE patients have a dysregulation
of proteins involved in inflammatory processes, synaptic
transmission, synaptogenesis, brain connectivity and neurodegeneration.
Moreover, patients with different AE subtypes
showed distinct protein profiles which may facilitate future
identification of disease-specific biomarkers.12
Small molecule therapeutics are used to treat a broad range of
diseases. However, their exact mechanism of action (MoA)
is not always known. Researchers have now developed a
high-throughput screening method that uses quantitative
proteomics to measure proteome-level changes induced by
drugs. Using this method, Dr. Dylan Mitchell and his team
screened a library of 875 small molecule drugs and quantified
more than 8,900 proteins. They then built a proteome
fingerprint database that can be used to elucidate the MoA
and off-target effects of several compounds.13 The routine
implementation of this type of method during early stages
of drug development is expected to increase efficiency of the
drug discovery pipeline.
Proteomics is also extensively used to characterize food
composition, quality and safety. Sturgeon meat is a rich
source of highly digestible protein. However, protein oxidation
during sturgeon fillets processing decreases the quality
of the meat.14 Low temperature vacuum heating (LTVH) is
an easy-to-use processing method that seems to improve the
processing quality of sturgeon meat.14 In a recent study, Dr.
Dan-dan Jiang and colleagues used a proteomic approach to
characterize protein oxidation of sturgeon meat after LTVH
treatment. The analysis of 733 proteins revealed that LTVH
produced mild oxidation and may provide a theoretical basis
to improve the processing of aquatic products.15
Plant biology and agriculture
Proteomics applied to plant biology is a powerful tool that
can help to develop new plant-based products, improve
plant health and increase crop yields. Soybean is one of
the most important economic crops worldwide, providing
an abundant source of plant protein and oil for humans
and livestock. The lysine 2-hydroxyisobutyrylation (Khib)
is a post-translational modification (PTM) described in
different organisms including several plant species.16 Dr. Wei
Zhao and colleagues recently used proteomics to identify Khib
-modified proteins in soybean leaves for the first time. The
analysis identified 4,251 Khib sites in 1,532 proteins involved
in a wide range of cellular processes (biosynthesis, central
carbon metabolism and photosynthesis).17 This data is useful
to gain insight into the regulatory mechanisms of Khib and
may help to improve soybean yields.
Animal husbandry and welfare
Animal welfare is a major concern in animal husbandry as
it can affect food quality and safety as well as determine
consumers’ preferences. Road transportation, for example,
is a common practice in the livestock industry, affecting both
animal welfare and meat quality.18,19 Proteomics analysis can
be applied to this area of research to support animal welfare
strategies. For example, Dr. Alessio Di Luca and colleagues
used a label-free LC-MS proteomic workflow to compare
the proteome of pigs after short or long road transportation.
The analysis of 1,464 proteins revealed that 66 were
expressed differentially in the 2 populations of animals.20 The
identification of these stress-related biomarkers may be used
to improve animal transportation conditions and ensure
Proteomics has also proved helpful in monitoring the effects of
pollution and climate change on ecosystems. For example, the
Mediterranean Sea is currently one of the major hotspots of microplastics
(MPs) pollution. In a recently published article, Dr.
Carola Murano and her team explored the effect of MPs on the
sea urchin immune cells proteome. They found that MPs exposure
altered the protein profile in a concentration-dependent
manner. MPs appear to increase the expression of metabolite
interconversion enzymes involved in cellular processes, indicating
a severe alteration of the cellular metabolic pathways.21 This
type of study provides new insights on the mode of action of
pollutants at the molecular and cellular level.
Proteome analysis is also useful in forensics to identify
individuals, assess evidence and solve crimes. Recent
studies show that it can be used to determine death due to
rattlesnake envenomization22 and abusive head trauma.23
Moreover, post-mortem analysis of the bone proteome has
proved useful to estimate the age-at-death and post-mortem
Although less common, proteomic analyses are also used in
space research aiming to support long-term space missions
and the establishment of life on other planets. NASA’s
planned mission to Mars will present several health challenges
to astronauts, including the exposure to ~350 mSv
of galactic cosmic radiation during each year of the mission.
Experiments in rodents suggest that exposure to this type
of space radiation impairs a variety of cognitive functions.
In a recent study, Dr. Evagelia Laiakis and her team studied
the proteomic profile of the medial prefrontal cortex of rats
exposed to space radiation. They identified several alterations
in pathways and proteins that correlate with the rats’
cognitive performance.26 In the future, these biomarkers
can potentially be targeted for development of appropriate
Proteomics is currently in the limelight and open to a myriad
of applications across the life sciences, from biomarker
discovery to space exploration. But the field is still evolving.
The future may see the rise of several promising technologies
for the high-throughput single-molecule sequencing of
proteins that are currently hampered by sensitivity, throughput
1. Wilkins MR, et al. Biotechnol Genet Eng Rev. 1996;13:19–50.
2. Beynon RJ. Brief Funct Genom. 2005;3(4):382–390.
3. Al-Amrani S, et al. World J Biol Chem. 2021;12(5):57–69.
4. Aslam B, et al. J Chromatogr Sci. 2017;55(2):182–196.
5. Timp W, Timp G. Sci Adv. 2020;6(2):eaax8978.
6. Eldakak M, et al. Front Plant Sci. 2013;4:35.
7. Chakraborty D, et al. Front Genet. 2022;13:774113.
8. Lacerda CMR, Reardon KF. Brief Func Genom. 2009;8(1):75–87.
9. Carrera M. Foods. 2021;10(11):2538.
10. Parker GJ, et al. Forensic Sci Int Genet. 2021;54:102529.
11. Somogyi Á, et al. Int J Mol Sci. 2016;17(4):439.
12. Räuber S, et al. J Autoimmun. 2023;135:102985.
13. Mitchell DC, et al. Nat Biotechnol. 2023;41(6):845–857.
14. Shen SK, et al. Food Chem X. 2022;15:100389.
15. Jiang DD, et al. J Sci Food Agric. 2023;103(6):2858–2866.
16. Dai L, et al. Nat Chem Biol. 2014;10(5):365–370.
17. Zhao W, et al. BMC Plant Biol. 2023;23(1):23.
18. Lammens V, et al. Meat Sci. 2007;75(3):381–387.
19. Shen QW, et al. Meat Sci. 2006;74(2):388–395.
20. Di Luca A, et al. PLoS One. 2022;17(11):e0277950.
21. Murano C, et al. Environ Pollut. 2023;320:121062.
22. Gallagher T, et al. J Forensic Sci. 2023;68(2):711–715.
23. Wiskott K, et al. Proteomics. 2023;23(3-4):e2200078.
24. Bonicelli A, et al. elife. 2022;11:e83658.
25. Gent L, et al. J Proteomics. 2023;271:104754.
26. Laiakis EC, et al. Front Physiol. 2022;13:971282. ww
Single-Cell Proteomics: Mass Spec
vs Single-Molecule Sequencing
Unlike bulk proteomics, which analyzes average protein
expression across a group of cells, single-cell proteomics explores
the heterogeneity and diversity of single cells. These
deeper insights offer a new understanding of cell biology,
cellular responses to stimuli and how complex signaling
pathways contribute to the cell’s function as a system. When
studying human health and disease, this field is set to have a
profound impact on how we diagnose and treat illnesses in
personalized medicine. Medical fields such as cancer research
are already benefiting from single-cell proteomics, which
can shed light on why certain cells within a tumor respond
to a specific therapy, while others may not, for example.
The single-cell proteomics toolbox continues to evolve,
with novel workflows combining a variety of analytical tools
being published frequently. The dominant setup for most
experiments involves the use of mass spectrometry (MS)
in some configuration. Lately, there has been excitement
surrounding single-molecule sequencing and its possible
applications in proteomics.
Dr. Ryan Kelly is an associate professor in the Department of
Chemistry and Biochemistry at Brigham Young University.
His research centers around the development of new
technological solutions for ultrasensitive biochemical
analyses, including single-cell profiling and high-resolution
proteome imaging. Technology Networks interviewed Kelly
to hear his thoughts on the single-cell proteomics landscape
and the potential impact of single-molecule analysis.
Q: For readers that are unfamiliar, how does single-
cell MS proteomics differ from single-molecule
A: Thousands of copies of a given peptide are needed to make
a confident measurement by MS, and this is what we do with
single-cell proteomics. The non-MS-based single-molecule
protein sequencing approaches (based on nanopores, etc.)
measure individual copies of each peptide, but these have
not been used to measure peptides or proteins in single cells
yet. The fields of single-cell proteomics and single-molecule
protein sequencing will converge at some point, but they
Q: Many MS vendors are creating instruments
that support single-cell MS proteomics. Why
would single-cell protein sequencing be
advantageous, given the advancements
in the MS space? Could this be adopted in
complement to single-cell MS proteomics, or
do you envision this could be a technology
that competes with MS?
A: Single-cell MS is more “ready for prime time”, while
single-molecule sequencing is generally still in a proof-ofconcept
stage. I suspect that as single-molecule sequencing
matures, there will be areas of complementarity and areas
of competition. For example, single-molecule sequencing
technologies by their very nature detect single molecules,
while MS requires a few thousand or tens of thousands of
copies to make a measurement. So sequencing approaches
could potentially fill in the gap on ultra-trace-level proteins,
particularly if those low-abundance species can be separated
from the higher abundance ones.
Q: What are the key challenges faced by
both single-cell MS proteomics and protein
A: Both technologies have dynamic range and measurement
throughput limitations. More effective sample preparation
and separations can also benefit both fields.
Q: You have previously said that you believe
“rumors of mass spectrometry’s demise have
been greatly exaggerated”. Can you expand
on this viewpoint?
A: The non-MS proteomics technologies tend to be purpose-
built for a given application or have a predefined panel
of target analytes. If you want to study something outside
of that range, you’re out of luck. In contrast, the same mass
spectrometer can be used to study protein digests, intact
proteins, post-translational modifications, lipids, carbohydrates,
etc., from all biological systems. It’s this versatility
that will allow MS to fill in the gaps even as other emerging
Q: How do you see the proteomics research
field evolving over the coming years?
A: If single-cell proteomics continues to advance to where it
becomes very high throughput and very sensitive, it could
become the default mode of proteome profiling. A similar
trend is already happening with transcriptomics. Measuring
populations of cells one at a time provides both that single-
cell granularity and population-level information at the
Dr. Ryan Kelly was speaking to Molly Campbell, Senior Science
Writer for Technology Networks.
This popular online event will once again
bring together leading scientists in the field
as they highlight the latest advancements in
translational proteomics and metabolomics.
Presentations will cover areas ranging from
uncovering the molecular mechanisms of
disease pathology, to the latest technological
developments in diagnostics and treatment.
Take a front row seat at our FREE Online Symposium
to hear more on:
• Cutting-edge technologies and collaborative strategies
• Innovations in separations and data acquisition for
• Advances in plasma lipidomics
• The evolution of next-generation protein sequencing
• Uncovering the latest fluid biomarker breakthroughs
advancing disease understanding
Technology Networks frequently host educational webinars that span the breadth of our scientific coverage, from coronavirus to
cannabis. Previous hosts include Nobel prize laureate Professor Jennifer Doudna and members of the team who pioneered the
Oxford/AstraZeneca COVID-19 vaccine. You can view all of our latest webinars HERE.
Advances in Proteomics &
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In the clinic, MS is becoming a vital tool, able to detect and quantitate trace levels of known and unknown targets
in complex samples. Advancements in areas such as ionization have helped to create growing applications of
MS in the clinic, including:
MS can identify bacterial
species rapidly and has
been used to detect
informing treatment plans
MS-based proteomics is
a powerful tool in disease
spanning conditions from
type 1 diabetes to chronic
By studying protein
expression profiles by MS
alongside genomic profiles,
clinicians are able to tailor
treatment plans to best suit
the responses of individuals
MS imaging (MSI)
offers great insights
on the localization
of biomolecules. For
example, in neuroscience,
it has been used to image
MS is a powerful and essential tool in the field of omics, specifically proteomics, metabolomics,
lipidomics and glycomics.
Among others, it provides insights for:
Investigating fundamental biology Identifying potential drug candidates
Understanding and predicting disease Process refinement in producing desirable products
Diagnosis of infectious and non-infectious disease Nutritional research
DOWNLOAD TO LEARN MORE
News Roundup: Protein
Biomarkers and Disease
Biomarkers can play a valuable role in understanding
the pathology of disease as well as helping to drive the
development of diagnostics and therapeutics.
From cancer to neurodegenerative disease, this roundup
explores recent protein biomarker discoveries.
New Protein Biomarker for Alzheimer’s Disease
In a study published in Genome Medicine, a team of
researchers from the Max Delbrück Center (MDC)
discovered a novel protein, called Arl8b, that builds up in the
brains of Alzheimer’s patients.
In Alzheimer’s disease, amyloid-beta peptides clump
together in the brain to form plaques that lead to
inflammation and eventually cause neuronal cell death. In
the study, the team genetically modified mice to have five
mutations that occur in individuals with familial Alzheimer’s
disease. They found that while amyloid-beta plaques
developed in the mice’s brains, Arl8b built up too.
Unlike brain tissue, cerebrospinal fluid is easily accessible
for diagnostic studies. “This means Arl8b is an interesting
candidate for a diagnostic marker,” said Dr. Annett
Böddrich, lead author of the study.
“Our work shows that proteomic research can
provide crucial information for identifying disease
mechanisms and markers, and thereby move
research forward. Also, this doesn’t just apply to
Alzheimer’s; it’s also relevant to other complex
neurodegenerative diseases such as Parkinson’s
and Huntington’s,” said Professor Erich Wanker, head
of the Proteomics and Molecular Mechanisms of
Neurodegenerative Diseases Lab at the MDC.
Reference: Boeddrich A, et al. Genome Med. 2023;15(1):50.
Protein Biomarkers Help To Predict Islet
Researchers at the Department of Energy’s Pacific
Northwest National Laboratory (PNNL) have identified
a set of altered proteins that predict islet autoimmunity, a
precursor for Type 1 diabetes.
Currently, there is no way to determine if or when either
islet autoimmunity or diabetes will occur in genetically
In the study, published in Cell Reports Medicine, PNNL
scientists analyzed blood plasma samples of almost 1,000
children from birth up to the age of 6. The researchers
identified a set of 83 proteins whose combination of changes
predicted which children went on to develop either islet
autoimmunity or Type 1 diabetes.
“What’s exciting about this work is that it opens the
door to detecting autoimmunity earlier than we can
right now,” said Dr. Thomas Metz, senior scientist,
PNNL. “This gives us an opportunity to learn more
about what causes the immune system to turn on the
body. This could help us tease out and understand
the mechanisms at play in the development of
diabetes better than we do currently and provide
potential targets for intervention.”
Reference: Nakayasu ES, et al. Cell Rep Med. 2023;4(7).
New Urine Tests May One Day Detect Early
Researchers from the University of Houston (UH)
have discovered new biomarkers for early detection of
The current gold standard for bladder cancer diagnosis,
cystoscopy, is associated with complications including pain,
urinary tract infection and blood in the urine. It also often
lacks the sensitivity to correctly identify the disease.
This study, published in BMC Medicine, demonstrates
the first and largest use of comprehensive aptamer-based
proteomic screening of urine samples from bladder cancer
patients to analyze the expression of over 1,300 proteins.
Using this screening method, the researchers were able to
identify 21 urine proteins discriminating bladder cancer
from urology clinic controls. One such protein, urine
D-dimer, displayed the highest accuracy and sensitivity.
“Using aptamer-based screening, we analyzed the
expression of 1,317 proteins in the urine of bladder
cancer patients and found that D-dimer - a protein
fragment from the breakdown of a blood clot - may
have a role in the initial diagnosis or detection of
cancer recurrence,” said Dr. Chandra Mohan, Hugh
Roy and Lillie Cranz Cullen Endowed Professor at UH.
Reference: Vanarsa K, et al. BMC Med. 2023;21(1):133.
Risk Biomarkers for Chronic Graft-Versus-Host
In a study published in Journal of Clinical Investigation,
researchers have identified three risk biomarkers that could
be measured long before a doctor would be able to make
a clinical diagnosis of chronic graft-versus-host-disease
Patients undergoing allogeneic hematopoietic cell
transplantation face the possibility of GVHD, where the
donated cells begin to attack the patient’s own healthy cells.
Severe GVHD can be quite debilitating and is a major cause
of death for patients.
The team of researchers identified three biomarkers that
could be measured at 90 days after transplantation. Two
of the biomarkers, MMP3 and DKK3, are associated
with fibrosis, the hardening or scarring of tissue due
to over-repair. The third marker, CXCL9, is a type of
protein that attracts particular immune cells into the
organs under attack.
“Current diagnosis is based on clinical signs that
may be confirmed by invasive biopsy of skin and
appendages, mouth, female genitalia, esophagus,
lungs, and connective tissues. Unfortunately, these
signs often reveal late-stage fibrotic lesions, as
opposed to early lesions that may be more amenable
to treatment,” the authors wrote.
Reference: Logan BR, et al. J Clin Invest. 2023;133(15).
New Prognostic Biomarker for Heart Failure
According to a study published in New England Journal of
Medicine Evidence, levels of endotrophin in the bloodstream
can be used to predict outcomes in patients with a common
form of heart failure.
In heart failure with preserved ejection fraction (HFpEF),
the heart loses pumping efficiency because its main pumping
muscle becomes too stiff to relax sufficiently between
pumping actions. This stiffening involves fibrosis, in which
normal muscle is replaced by scar-like tissue.
Animal studies suggest that endotrophin, a fragment
released during the formation of type VI collagen, is
related to the development of both fibrosis and metabolic
dysfunction. Both processes are thought to be important
In the study, the researchers analyzed endotrophin levels in
blood samples taken from 205 HFpEF patients at the outset
of a previous clinical trial. They split the patients into three
tiers according to their endotrophin levels, and compared
how they fared in the trial. Over a four-year follow-up
period, patients in the highest tier had a several fold
increased risk of having a heart attack, being hospitalized
for the management of heart failure or dying from any
“In addition to helping us gauge the risks faced by
HFpEF patients, endotrophin could give us important
clues to the biological processes underlying poor
outcomes in this form of heart failure—and might
even be a target for treatment,” said Dr. Julio
Chirinos, associate professor of Cardiovascular
Medicine at the University of Pennsylvania.
Reference: Chirinos JA, et al. NEJM Evidence. 2022;1(10).
Why a western blot ?
• Western blotting is a molecular
that allows the
presence (or absence), size and
abundance of a specific protein to
be determined, even within a
complex mixture of proteins from
cells or tissues.
• This means that the technique can
be used amongst other things to
verify the success of gene editing or
modification experiments using
protein expression, investigate
disease and detect tagged proteins.
• Western blotting
is similar to
Southern and northern blotting,
however these techniques are used
to detect DNA sequences and RNA
• This infographic will take you
through the multistep
blotting process and give some tips
to avoid poor results.
When loading samples
onto the gel, it’s good
practice to make a note
of what is in each well.
Before you begin, make
sure the electrodes are
the correct way round - if
not, you could lose your
sample in the buffer.
Mixture of proteins
Download to learn more
Credit: iStock. Dr. Birgit Schilling.
How Collaboration and Curiosity
Make for a Successful Scientist
Dr. Birgit Schilling studies the molecular mechanisms
that underlie aging processes and is particularly
passionate about research that could lead to novel
therapeutic interventions for human aging or disease.
At the Buck Institute for Research on Aging in Novato
near San Francisco, CA, she leads her laboratory in the
use of modern proteomics technologies – such as dataindependent
acquisition – to fulfill these research goals.
Key project examples from her lab include investigating
the dynamic role of post-translational modifications
(PTMs) during cell signaling, specifically in the context
of metabolic diseases, neurodegenerative diseases, cancer
Dr. Schilling studied chemistry at the University
of Hamburg in Germany and she also studied as an
undergraduate student in Southampton. After completing
her PhD in Germany, she started a postdoctoral fellowship
in 1998 at the University of California San Francisco
(UCSF). She has worked at the Buck Institute since 2000,
where she is also the director of the Mass Spectrometry
Technology Center. Dr. Schilling has a long-standing
scientific track-record in developing mass spectrometry
(MS)-based methodologies for quantitatively analyzing
complex samples. She is incredibly well respected in her field
and has collaborated with many scientists across the globe.
Technology Networks champions diversity in science and
embraces the opportunity to learn from women in science
about their journey – the challenges they may have faced,
how their research focuses evolved and the advice they
may offer young scientists eager to follow in their footsteps.
We recently had the pleasure of interviewing Dr. Schilling,
who talked about the “beauty in the chemistry that
generates life”, why science careers can be hard and the
importance of knowing when to change direction.
Dr. Birgit Schilling is a professor and director of
the Mass Spectrometry Technology Center at
the Buck Institute for Research on Aging.
Q: What inspired you to pursue a career in
A: I was always fascinated by the natural world around me
and how one could use science to try to explain natural
phenomena. I studied chemistry, and I really liked the logic
and elemental understanding of what is around us. Most of
all, I really love the multi-disciplinary aspects of science,
and how chemistry, biology, physics and medicine all
inform each other and often yield wonderful collaborations
between scientists from different backgrounds. Science
is highly collaborative, which I cherish, and those
collaborations can be national and international.
What intrigued me when I studied chemistry is how nature
has brought forward fascinating chemical structures
and molecules that “operate” and manifest life and often
show “healing” power. Quite a few pharmaceutical drugs
are based on natural products, and in some cases these
structures are synthesized and further optimized to
generate therapeutics that become medical interventions
for disease treatments – this is also referred to as “natural
product chemistry”. There is a beauty in the chemistry that
Q: Why did you decide to focus your research
on aging, specifically?
A: The aging process of life – how an organism develops,
grows and ages – is a fascinating field of research. We are
interested in “healthy aging”, meaning to extend what we
call “health span” so that humans have a longer span of
health throughout their life.
Interestingly, aging is closely related with many age-related
diseases, so a better understanding of aging will help to
tackle age-related diseases. Aging is also something that
we all will face, but understanding the complexity of this
biological process is important to implement interventions
– in lifestyle (exercise/diet) or pharmaceutically.
Connecting aging mechanisms with, for example,
neurodegenerative brain diseases, such as Alzheimer’s
disease – but also other devastating diseases, such as
cancer – is interesting from a scientific standpoint and will
contribute to the development of further interventions.
Q: As a woman in science, have you faced
any barriers in your career journey?
A: That is an interesting question. I have always been a
“strong” person. When I studied chemistry in my college
years, there were so few female students, it was really
surprising. But what counted was the science and I could
usually easily connect and interact with anybody. We were
good friends supporting each other – it did not matter
whether we were men or women. So that was not a problem.
Throughout my career, I was focused on my scientific work
and would try hard to showcase the skills and passion
that I had. I wanted to be “measured” based on that – the
good science I could contribute and the fact I was a good
collaborator. I did not get too much pushback, and when I
did, that was just not the direction I would pursue, I would
There are so many opportunities, if one thing does not
work out, I would look for other directions, or if I cared a
lot for something that led to me facing obstacles, I would
try to really show what I can do and convince those around
me with my good work. I found great supporters that
would help me move forward – but I also put in a large
amount of work to make my case! I have found many
scientists do support each other when they collaborate
well, and when they see how valuable the work of the other
Q: What qualities and values do you think
makes for a successful scientist?
A: Curiosity, persistency, enthusiasm and a fascination
with learning something new every single day – imagine
that! What is also important is having a keen eye for
understanding a scientific observation: many people may
observe the same thing, but it is the right interpretation of
an experimental outcome that sometimes reveals the most
interesting scientific results.
Being a scientist is not always easy because sometimes
experiments are challenging, but when things go well,
it is so rewarding. Finding the right collaborators, the
right projects to engage in, showing persistency but
also knowing when to change direction are incredibly
I think being a team player is key and being open to
embracing the joy of collaborating. Also, recognizing
how technology can help scientists is very important, in
addition to finding the “right” place to do your fun science.
Something to ask yourself if you are thinking of being a
scientist is: do you love nature – plants, animals, humans,
microbes or other? Are you interested in understanding
how life works? We can use science to help, for example, in
human diseases, or for other scientific purposes. An overall
appreciation for the complexity of life is a good quality for
scientists to have.
Q: Can you talk about women in science that
have inspired or supported you?
A: This is an interesting question – until I was >30 years
old, there were no women in science who had inspired
me. My history teacher in high school, who is a woman,
really inspired me with her strength and knowledge and
other interests outside of her school work (travel and
In my college years, there were no women professors in
Chemistry (in Germany at the time). When I was an early
postdoctoral fellow, I met Dr. Catherine (Cathy) Costello,
who is an amazing scientist and professor at Boston
University. She was so kind as to give me a ride from an
Asilomar Mass Spectrometry conference back to San
Francisco Airport. During the journey, we talked about
many things, both within and outside of science. That was
so important to me – to experience how somebody can be
such a highly respected and successful scientist, admired
by many (myself included!), but also be a kind person with
so much generosity on a personal level.
Other women scientists who have really supported me are
Dr. Jennifer Van Eyk at Cedars-Sinai in Los Angeles and
Dr. Ileana Cristea at Princeton. At the Buck Institute, I am
so lucky to work with Dr. Judith (Judy) Campisi and Dr.
Lisa Ellerby, who both are dear colleagues. We do great
science together and we support each other.
I also know a lot of male scientists who I admire greatly,
and who have helped me a lot in my career. I usually look
at the person (man or woman) – and then I connect with
them as a person and a scientist. It is the connection that
generates a great scientific colleague – somebody who I
support and who may support me.
Q: What advice would you give to someone
that wishes to pursue a career in science?
A: Follow your dreams. If science is what you like to
do – then go for it. It is hard at times – but also greatly
Dr. Birgit Schilling was speaking to Molly Campbell, Senior
Science Writer for Technology Networks.
The meta-array of micropillars in the microfluidics device for enhanced immunoaffinity purification of HLA-restricted peptides. Credit: Xiaokang Li.
Advancing Antigen Discovery
With Microfluidics Automation for
Dr. Xiaokang Li and Prof. Dr. Michal Bassani-Sternberg, Ludwig Institute for Cancer Research, Lausanne
Our group at the Ludwig Institute for Cancer Research
in Lausanne, Switzerland, has published an innovative
method in Cell Reports Methods for tumor antigen
discovery. Our automated and cost-effective workflow in
immunopeptidomics, utilizing microfluidics technology,
overcomes limitations in sample preparation, particularly
the immunoaffinity purification (IP) of human leukocyte
antigen (HLA)-restricted peptides. This novel method
enables sensitive detection of multiple immunogenic
tumor-associated antigens from small clinical tumor
biopsies, making it a powerful tool for antigen discovery in
Reducing sample loss to increase
Mass spectrometry (MS)-based immunopeptidomics
is a valuable method for identifying peptides presented
by HLA molecules on cell surfaces, which are essential
for T cell-mediated immune responses. The unique
immunopeptidomes of cancer cells offer potential targets
for immunotherapies like cancer vaccines and adoptive cell
transfer therapies. MS is crucial for comprehensive peptide
analysis, but current sample preparation methods for
immunopeptidomics are laborious and hinder large-scale
clinical applications. Existing alternatives, such as robotic
platforms, are costly, posing financial burdens for many
laboratories. The study aimed to develop an automated,
cost-effective and efficient microfluidics-based workflow
for sensitive immunopeptidomics to overcome these
Automated sample prep with a microfluidics
We developed an automated and cost-effective workflow
for immunopeptidomics by utilizing microfluidics
technology to overcome the limitations of existing
sample preparation methods, especially for the IP of
HLA-restricted peptides. We engineered a microfluidic
platform with a meta-array of micropillars to enhance
immunoaffinity interactions. The platform incorporated a
programmable fluidic control system for the IP procedure
and integrated C18 cartridges for sample clean-up. This
workflow streamlines the sample preparation process
and reduces material consumption, leading to enhanced
target purification. We demonstrated the performance
of our approach by analyzing low-input samples and
tumor biopsies, leveraging data-independent acquisition
computational methods for sensitive detection of tumor
antigens using MS. The novel microfluidics-based
workflow showed competitive performance over the
traditional one, offering an automated, cost-effective and
efficient solution for immunopeptidomics analysis.
The key findings of the paper were:
• An automated microfluidics system with enhanced
sensitivity for immunopeptidomics was created
• Data-independent acquisition computational
methods were able to provide in-depth and reliable
• A public spectral library constructed with published
MS files enabled comprehensive analyses
Reliable and sensitive peptide identification
The newly created microfluidics-based workflow
presents an automated and user-friendly system for
immunopeptidomics. This is achieved by reducing the
sample volume and integrating purification steps, resulting
in enhanced assay efficiency. Additionally, with continuing
developments allowing for scalability, larger-scale studies
and potential clinical applications can be pursued in the
future. Furthermore, in comparison to costly robotic liquid
handling platforms, the microfluidics approach offers a
cost-effective alternative, making immunopeptidomics
analysis accessible to a broader spectrum of research
The combination of microfluidics technology and dataindependent
acquisition computational approaches enables
sensitive and reliable identification of tumor antigens.
This can significantly contribute to the discovery of
cancer-specific peptide antigens, which are crucial for
developing targeted T cell-mediated cancer therapies,
including TCR-T therapy and cancer vaccines. The ability
to detect these antigens accurately and characterize them
can potentially lead to the development of more effective
personalized cancer treatments.
Microfluidics devices’ ability to handle sub-milliliter
sample volumes makes them suitable for analyzing limited
clinical samples such as liquid biopsies or small tumor
biopsies. This capability opens up opportunities for
studying immunopeptidomes in situations where sample
availability is limited. It can provide valuable insights
into cancer-specific peptide antigens and immunogenic
tumor-associated antigens, potentially leading to a better
understanding of immune responses in cancer and the
development of targeted therapies.
The impact of this study lies in its advancements in the field
of immunopeptidomics. By introducing an inexpensive,
automated and easy-to-operate workflow using
microfluidics technology, the study addresses bottlenecks
in sample preparation and enhances target purification.
This has significant implications for cancer research and
personalized cancer therapies. The study enables more
efficient and cost-effective analysis of tumor antigens,
leading to the discovery of cancer-specific peptide antigens
and immunogenic tumor-associated antigens. This
knowledge can potentially revolutionize the development
of targeted T cell-mediated cancer therapies, such as
TCR-T therapy and cancer vaccines. Moreover, the ability
to handle scarce clinical samples expands the possibilities
for studying immunopeptidomes and improving our
understanding of immune responses in cancer.
While the study on the automated microfluidics workflow
for immunopeptidomics brings significant advancements,
it also has certain limitations that should be acknowledged.
The evaluation of the workflow’s performance was mainly
conducted using low-input samples and tumor biopsies.
It is crucial to assess its applicability and performance
across a broader range of sample types, including different
cancer types and various biological fluids. Validation
studies on a larger scale and diverse patient cohorts are
necessary to establish the reliability and reproducibility of
the approach. Another limitation is that the study does not
address the potential challenges associated with analysis
of peptides restricted by other HLA classes, such as Class
II HLAs. Factors such as scalability, cost-effectiveness
and integration with existing clinical workflows need to
be considered for successful translation into large-scale
Expanding the scope of application
In the future, efforts should be directed towards scaling
up the assay throughput by incorporating multiple
microfluidics modules in a relatively cost-effective and
small footprint. An intuitive system control interface and
packaged chip devices should be implemented to allow
inexperienced users to handle the platform effortlessly.
To validate the clinical utility of the workflow, largescale
validation studies involving a substantial number of
patient samples should be conducted. This will enable the
assessment of its diagnostic and prognostic capabilities
and provide evidence for its effectiveness in personalized
Li X, et al. Cell Rep Methods. 2023;3(6):100479.
Detecting Cancer From a Droplet
In 2000, the Human Genome Project (HGP) announced it
had completed a working draft of the human genome
sequence – a genetic “blueprint” of a human being.
In the same year, a new project emerged, one that sought
to look “beyond the genome”: The Human Protein Atlas,
which aims to map all of the human proteins in cells,
tissues and organs. A cell, tissue or organism’s proteome
– the complete set of proteins it expresses at a given time
– reflects its dynamic state more accurately than its DNA
code. Genes could be turned “on” or “off”, proteins might
undergo post-translational modification – processes that
can determine, or perturb, a cell’s function.
“Proteins are the building blocks of all life on this
planet. They are also the targets for almost all drugs and
thus incredibly important commercially,” says Mathias
Uhlén, professor of microbiology at the Royal Institute of
Technology (KTH) and program director of the HPA. “The
holistic understanding of how proteins can execute all the
functions in human life is still surprisingly unknown and
thus a huge challenge for biomedical research.”
Officially launched in 2003, the HPA integrates
breakthrough technologies – including mass spectrometry
(MS)-based proteomics, antibody-based imaging,
transcriptomics and systems biology – to create an open
access resource, which is used in over 150 countries. Uhlén
adds: “The resource now consists of more than 5 million
web pages and is updated annually with new data and
features.” To date, the HPA has contributed to several
thousands of publications across the life science fields and
is recognized by ELIXIR as a “European core resource”.
The structure of the HPA
Over the last 20 years, the HPA has launched 10 different
sections that each focus on varying aspects of human
• Tissue – Showing the distribution of proteins across all
major tissues and organs in the body
• Brain – Exploring the distribution of proteins in various
regions of the mammalian brain
• Single-Cell Type – Studying expression of proteincoding
genes in single human cell types using single-cell
RNA sequencing (scRNA-seq)
• Tissue Cell Type – Studying expression of proteincoding
genes in human cell types based on bulk
• Pathology – Showing the impact of protein levels on the
survival of patients with cancer
• Immune Cell – Showing expression of protein-coding
genes in immune cell types
• Blood Protein – Describing proteins detected in blood
and secreted by human tissues
Credit: The Human Protein Atlas.
• Subcellular – Showing the subcellular localization of
proteins in single cells
• Cell Line – Showing expression of protein-coding genes
in human cell lines
• Metabolic – Exploring expression of protein-coding
genes in the context of the human metabolic network
“The ‘flagship’ Tissue Atlas was launched in 2015 with
more than 10 million microscope bioimages showing
proteins on a single cell level across all major tissues
and organs in the human body. The 2015 publication
in Science now has ~10,000 citations and it is thus one of
the most cited research publications in Europe during the
last 10 years,” says Uhlén.
In December 2022, version 22 of the HPA introduced two
new sections that reflect the increasing utility of artificial
intelligence (AI) and machine learning in proteomics
Detecting cancer-associated proteins from a
droplet of blood
Version 22* of the HPA also introduced a new Human
Disease Blood Atlas, which presents the results of a novel
pan-cancer strategy to explore the proteome signature in
blood samples obtained from cancer patients.
For a disease caused by changes to the DNA code, it
makes sense that genomics-based approaches have
dominated cancer research over recent years. “However,
to understand the consequences of these changes it is often
necessary to instead study the protein levels in the tumor,”
says Uhlén. This can be achieved using tumor biopsies,
but the procedure is invasive and can cause distress for the
patient. A blood-based test to explore protein expression is
a desirable alternative.
The researchers behind the Human Disease Blood
Atlas analyzed 1,463 proteins from over 1,400 cancer
patients. “We highlight proteins associated with each
of the analyzed cancer types based on differential
expression analysis as well as a machine-learning-based
disease prediction strategy. By combining the results
from all cancer types, a panel of proteins suitable for the
identification of individual cancer types based on a drop of
blood is presented,” Uhlén explains.
To achieve this panel, a combination of proximity
extension assay (PEA) technology and targeted proteomics
(MS) was used. MS has long been considered the “gold
standard” technology for high-throughput proteomics
analysis in research settings. However, assays have been
used in the clinical space for many years; examples of
their application include the detection of troponin, which
can indicate that a heart attack has occurred. “However,
these assays are based on analysis of a single protein, but
assays to detect and quantify multiple protein targets –
with a sensitivity needed for the minute concentrations of
proteins in the blood – have been lacking,” says Uhlén.
Figure 1: Towards next-generation cancer prediction medicine. The example shows the elevated levels of the protein GFAP
in the blood of patients with glioma.
The introduction of next-generation blood protein
profiling, based on parallel analyses of thousands of
proteins at once, is changing the game. “PEA has allowed
thousands of blood proteins to be analyzed from a small
drop of blood. These developments mean that we are
entering a new era for personalized medicine based on
detailed multiplex blood protein profiling,” Uhlén adds.
Such platforms are poised to have a major impact on the
cost of diagnosing and treating cancer, a disease with
a substantial economic burden.
Next-generation blood proteome profiling –
the future of clinical proteomics?
Uhlén emphasizes that, while the first version of the
Human Disease Atlas is focusing on cancer, the HPA
will explore other diseases using the same approach
in coming years, such as cardiovascular, infectious,
neurodegenerative and autoimmune conditions. “This will
make it possible to compare the blood profiles across major
diseases and thousands of individuals,” he says.
His words offer enthusiasm for a field that, despite
significant advancements over the last decade, is yet to
enter the clinical space on a widely adopted scale. “There
are several obstacles to make these new findings translate
into clinical practice. First, all potential tests based on
new analytical platforms must be validated in independent
cohorts and preferably with alternative analytical assays,”
says Uhlén. This is no easy feat – it requires thousands of
The second key obstacle, according to Uhlén, is the
regulatory requirements that are costly and timeconsuming.
“It might be difficult to obtain clinical
approval for panel tests measuring hundreds of proteins in
parallel,” he says. “In addition, even very specific tests can
give rise to ‘false positives’ causing unnecessary grief and
psychological burden for the patient.” Therefore, clinically
valuable tests must have secondary, independent tests
available to identify “true positives” for diagnosis. These
challenges aside, Uhlén is optimistic that with the rapid
development of next-generation proteome profiling, “we
will find ample applications in routine clinical practice in a
As for the future of the HPA, it will continue to host its
open-access resource to facilitate protein research around
the world, adding data to complement the body-wide
spatial profiling in cells, tissues and organs with data
focusing on structure, interactions, modifications and
Professor Mathias Uhlén was speaking to Molly Campbell,
Senior Science Writer for Technology Networks.
*Version 23 of the HPA was released in June of 2023.