Written in sugar: Dr Rebeca Kawahara on bringing the glycan code into medicine
“It’s like a hidden layer of biology we’ve only just started to decode.”
Dr Rebeca Kawahara, a glycoproteomics researcher with dual affiliations at Griffith University’s Institute for Biomedicine and Glycomics and the Institute for Glyco-core Research (iGCORE) at Nagoya University, is working to decode one of biology’s most overlooked languages: the complex sugar structures, known as glycans, that coat every cell in the human body, shape how cells recognise one another, and may hold answers to some of medicine’s most persistent questions. Her journey from undergraduate proteomics to leading international glycome mapping initiatives spans three continents, several bold career pivots, and a growing conviction that the “glycan code” represents medicine’s next major frontier. Now at the centre of efforts to build a comprehensive atlas of human glycans, she is focused on making this hidden layer of biology readable and clinically meaningful for researchers worldwide.
Decoding the hidden language of cells
Rebeca’s work centres on something she calls the “glycan code” – the complex sugar structures, known as glycans, that attach to proteins and act as a kind of biological annotation system. Around half of all proteins in the human body are predicted to carry these attachments. Each cell presents its own unique glycan signature, shaped by multiple layers of regulation, from how genes are transcribed all the way through to how proteins are modified after they’re made.
That last step, post-translational modification, matters because a protein isn’t simply an inert structure once it exists. It can be switched on or off, directed to different parts of a cell, or made to interact with entirely different molecular partners, all depending on the modifications it carries. Glycosylation is one of the most widespread of these modifications, and yet it has historically been one of the hardest to study. Unlike DNA, glycans cannot be predicted from a genome sequence or amplified in a laboratory. Every measurement has to be made directly, from real biological samples, using highly sensitive and specialised techniques.
“It’s like a hidden layer of biology that we’ve only just started to decode,” Rebeca says. “I was fascinated by the idea that we might be missing a critical piece of the puzzle in understanding health and disease – that sense of uncovering something that’s been overlooked for so long.”
That difficulty is precisely what drew her in.
From gel to global initiative
Her entry into the field came through proteomics at a time when the technology was just beginning to mature. As an undergraduate, she joined a research group using mass spectrometry to explore the protein landscape of melanoma, and found herself captivated not just by the biology, but by the volume and resolution of information a single experiment could yield.
“I was immediately fascinated by the ability to generate large-scale biological data and, more importantly, to both identify and quantify hundreds of proteins in a single experiment,” she recalls. When researchers can measure hundreds of proteins simultaneously, patterns emerge that would otherwise be invisible: which proteins rise or fall together, which combinations are associated with a particular disease state, which shifts precede a change that might one day be detected in a blood test or a biopsy.
Photos by Kevin Chau at iGCORE, Nagoya University
That curiosity carried her into a PhD focused on discovering protein biomarkers in oral cancer. The practical stakes are straightforward: if you can identify a molecule that reliably signals the presence or progression of a cancer, you can potentially build a test around it: as an example, Rebeca envisions a saliva test during a routine dental visit, measuring a small panel of proteins known to be elevated in oral cancer, flagging a patient for further investigation before symptoms appear. “Potentially catching the disease much earlier,” she says, “when treatment is far more effective.” Her PhD work identified novel candidate biomarkers for oral cancer detection in patient saliva – work she’d later extend to prostate cancer in urine and colorectal cancer in blood plasma.
It was during this period that a pivotal realisation changed the direction of her career. Many of the proteins she was identifying as potential biomarkers were glycosylated, yet the proteomics methods she was using were largely blind to that fact. “I realised there was a missing layer of information that could be highly relevant to disease biology,” she says.
Supported by a FAPESP fellowship, she joined the lab of Prof Giuseppe Palmisano at the University of São Paulo for postdoctoral research in post-translational modifications, then spent a year at Macquarie University in Sydney, trained by glycoscience leaders Prof Morten Thaysen-Andersen and Prof Nicolle Packer. She subsequently secured an independent fellowship from the Cancer Institute NSW, during which one line of work crystallised what this field could actually deliver.
The sugar coat on a tumour cell
Working in colorectal cancer, Rebeca and her colleagues identified an enzyme called hexosaminidase B, which trims specific sugar structures on proteins and generates a distinctive glycan signature – short structures known as paucimannose glycans that are highly enriched in tumour cells compared to normal tissue.
What made the finding clinically significant was that the enzyme is not only present and active in tumours; it is also released into the bloodstream. That opened up a question: could its activity be measured in a simple blood test? Using a fluorescent assay, the team found that patients with higher levels of enzyme activity in their plasma had significantly poorer survival outcomes – roughly increasing up to twice the risk of death within five years compared to patients with lower levels.
When the enzyme was experimentally inhibited in colorectal cancer cells, the cells became less aggressive, showing reduced ability to migrate and invade – two of the hallmarks of cancer progression.
“It shows how understanding changes in sugar structures can translate into a real clinical tool – a blood-based prognostic marker – and at the same time point to a potential therapeutic target,” Rebeca says. “It’s a clear illustration that glycans are not just decorative modifications on proteins, but active players in disease that we can measure, understand, and potentially target.”
Making the invisible readable
If you ask most people whether they’ve heard of DNA or the genome, the answer is almost always yes – largely thanks to landmark efforts like the Human Genome Project, which transformed our understanding of biology and medicine. The Human Glycome Atlas Project and the Human Glycoproteomics Initiative (HGI) aim to do something analogous for glycans: systematically mapping the glycan code at a scale that hasn’t previously been possible.
“In many ways, these efforts are laying the groundwork for the next major leap in life sciences, similar to what the genome project achieved years ago.”
But mapping something first requires being able to read it reliably and, in 2021, that was still an open problem. Under the HGI, Rebeca led a landmark study published in Nature Methods evaluating the different software tools and analytical strategies researchers use to identify glycopeptides, the fragments of glycosylated proteins measured in mass spectrometry experiments. Results varied substantially depending on which software was used and how the analysis was configured. By systematically comparing approaches and defining key parameters for more reliable analysis, the study provided practical guidance for the community and helped inform the development of better tools going forward.
“I realised how much impact we could have by making these approaches more accessible and reproducible,” Rebeca reflects. It made her see her work differently: not just as a source of new biological insights, but as infrastructure for others. Enabling non-specialist labs to confidently study the glycoproteome became as important a goal as the discoveries themselves.
The sex-specific glycoproteome
One of her most significant recent projects, developed at iGCORE and supported by the Human Glycome Atlas Project in Japan, involved mapping the glycoproteome across 19 different tissues in mice, comparing males and females across each of them.
Sex turned out to be a major driver of tissue-specific differences in glycan signatures, with pronounced variation in the salivary gland, liver, and kidney. The brain, by contrast, showed remarkable consistency between the sexes. Just as importantly, these differences arose from coordinated regulation of the glycosylation machinery itself, reflecting systematic biological differences rather than incidental variation.
Rebeca breaks it down:
“If glycans help cells communicate and respond to their environment, then men and women may be using slightly different ‘dialects’ of the same biological language across different organs.”
Biomedical research has long treated male and female biology as largely interchangeable, or considered sex differences only at a broad level. “From a genomic perspective, males and females differ by just one chromosome,” Rebeca notes. But at the level of the glycan code, the differences are widespread and systematic across many tissues, which means that biomarkers or treatments developed without accounting for sex could be missing important signals or be less effective for part of the population. “It reinforces the need to design research and medical strategies that take sex into account from the beginning – not as an afterthought. In the long term, this could lead to more precise diagnostics and more personalised treatments that better reflect the biology of each individual.”
Completing the study required integrating transcriptomics, proteomics, glycomics, and glycoproteomics into a coherent analysis – a task that demanded close collaboration with bioinformatics specialists and robust computational frameworks to ensure the different data types were genuinely comparable. “Without this level of computational support, much of the underlying biological complexity would have been extremely difficult to interpret.”
In 2023, Rebeca was recruited to establish a dedicated Glycoproteomics Lab at iGCORE – a move that was, by any measure, a significant step. She was in Australia, approaching the end of an Early Career Fellowship, with a competitive grant application in progress and a stable research environment at Macquarie University. The offer from Japan arrived while the outcome of that application was still uncertain.
“It was a difficult decision,” she says. “Accepting the offer meant moving to a new country, adapting to a completely different culture, and taking my young family with me – my two boys were just one and four years old at the time.” The stability she had built felt real, and walking away from it felt like a genuine risk. In the end, she took the offer without knowing how things would unfold.
Photos by Kevin Chau at iGCORE, Nagoya University
“Looking back, it was one of the best decisions I’ve made. It pushed me out of my comfort zone, helped me grow in independence, and allowed me to build new international collaborations and expand my research profile. It wasn’t always easy, but that experience made me more resilient and more confident in my ability to take risks and create new opportunities.”
The experience also deepened something Rebeca has come to see as an underappreciated skill in science: the ability to work across cultures. Coordinating research between Japan, Australia, and Brazil meant learning, consciously, how different environments communicate, build trust, and make decisions. “In Australia, for example, communication tends to be quite direct and informal. In Japan, it is often more indirect and nuanced, with a stronger emphasis on building consensus and maintaining harmony.” What reads as efficiency in one context can read as bluntness in another. “Over time, I’ve learned to adapt; being more explicit when needed, more patient in consensus-building, and more intentional about building relationships.”
When it works well, she says, these collaborations become greater than the sum of their parts. “You’re not only combining expertise, but also diverse ways of thinking.”
Setting up the new lab also meant making deliberate choices about equipment and analytical infrastructure. For high-performance liquid chromatography, Rebeca sought out IonOpticks’ Aurora Series columns, which came well recommended by colleagues. “The performance has been outstanding,” Rebeca notes. Working with a Vanquish Neo coupled to an Orbitrap Exploris 240, the lab achieved sharp, reproducible chromatography – FWHM values under six seconds, stable across more than 500 runs.
“We were able to obtain excellent glycoproteome coverage, which was particularly important for our mouse tissue glycoproteome mapping studies.”
The frontier: one cell at a time
What keeps Rebeca up at night is the fact that, despite all the technical advancements in proteomics, “we are still not quite able to measure glycosylation at the single-cell level.”
The rapid development of single-cell proteomics, enabled by advances in automated cell sorting, next-generation chromatography, and increasingly sensitive mass spectrometry, is one of the most transformative shifts currently underway in her field. Instead of averaging a signal across millions of cells in a sample, researchers are beginning to measure individual cells directly. That matters because cells within the same tissue, even the same tumour, are not identical. The differences between them – not just in which genes they express, but in how their proteins are modified – may explain mechanisms of disease progression that bulk analysis has always obscured.
For glycoproteomics, this frontier is still just beyond reach:
“Glycosylation is so tightly regulated by the state of each individual cell,” Rebeca explains.” If we could truly map glycans at single-cell resolution, it would fundamentally transform our understanding of how individual cells generate their unique glycome and use it to communicate, interact, and function.”
If resources were no constraint, she would pursue exactly this: combining advanced cell sorting, multiplexed protein labelling, and comprehensive glycopeptide libraries to analyse hundreds or thousands of individual cells from cancer tissues directly. Alongside this, she would develop machine learning approaches to multi-omics integration: computational models trained on single-cell transcriptomic and proteomic data to predict glycosylation patterns at the single-cell level, linking gene expression, protein abundance, and glycan signatures within individual cells into a unified picture.
“This would allow us to capture cellular heterogeneity at an entirely new level,” she says, “revealing how glycosylation varies between individual cells within the same tumour and across diseases.” The downstream potential is substantial: more precise biomarkers, better understanding of how tumours evade the immune system, and more targeted therapeutic strategies.
On uncertainty and what it opens up
Beyond the methods and the publications, Rebeca is reflective about what a scientific career actually asks of a person.
“A career in science is inherently uncertain,” she says,”and that’s not something to fear, but to embrace. There’s rarely a straight or predictable path. Instead, it’s shaped by unexpected opportunities, challenges, and the people you meet along the way.”
Her own path has taken her across three countries and several disciplines, each transition requiring a willingness to sit with not-knowing long enough to find out what comes next.
The advice she would offer her younger self reinforces this idea: “Don’t be afraid to explore and to pioneer. Some of the most meaningful opportunities come from following curiosity into the unknown. Those moments of uncertainty are often exactly what open new paths and lead to the most exciting discoveries.”
It’s the same instinct that drew her to glycans in the first place – the conviction that the most important things are often the ones nobody has thought to look for yet.
Detailed Q&A
I am a mid-career researcher with a dual affiliation at the Institute for Biomedicine and Glycomics at Griffith University and the Institute for Glyco-core Research (iGCORE) at Nagoya University.
My research focuses on developing and applying integrated multi-omics approaches to better understand what we call the “glycan code” across different areas of life sciences, including immunology, cancer, and infectious diseases.
Glycans are complex sugar structures that can be attached to proteins, carrying an enormous amount of biological information. Around half of all proteins in our body are glycosylated, and each cell presents its own unique glycan signature, finely tuned by multiple layers of regulation — from RNA transcription to protein translation and post-translational modification.
Unlike the genetic code, the glycan code cannot be easily predicted or amplified, making it much more challenging to study, and at the same time, incredibly exciting. It’s like a hidden layer of biology that we’ve only just started to decode. What drew me into this area was the idea that we might be missing a critical piece of the puzzle in understanding health and disease — and that by studying glycans, we could reveal entirely new biological insights and opportunities for diagnostics and therapeutics.
A concrete example of what this field can deliver comes from our work in colorectal cancer. We identified an enzyme called hexosaminidase B, which trims specific sugar structures on proteins and generates a distinctive glycan signature — short structures known as paucimannose — that are highly enriched in tumour cells compared to normal tissue. This enzyme is also released into the bloodstream, which opened up the possibility of measuring its activity in a simple blood sample. Using a fluorescent assay, we found that patients with higher levels of this enzyme activity in their plasma had significantly poorer outcomes — about half the chance of surviving five years compared to patients with lower levels. When we experimentally inhibited this enzyme in colorectal cancer cells, the cells became less aggressive, showing reduced ability to migrate and invade. It’s a clear illustration that glycans are not just decorative modifications on proteins, but active players in disease that we can measure, understand, and potentially target.
My interest in proteomics started very early in my career, at a time when liquid chromatography–mass spectrometry (LC–MS/MS) was just emerging as a powerful technology to study proteins at scale. As an undergraduate student, I joined a research group using 2D gel electrophoresis followed by LC–MS/MS to explore the proteome of melanoma. I was immediately fascinated by the ability to generate large-scale biological data and, more importantly, to both identify and quantify hundreds of proteins in a single experiment — when you can measure hundreds of proteins simultaneously, patterns emerge that would otherwise be invisible, and those patterns are what ultimately point toward disease mechanisms and clinical opportunities.
Driven by this curiosity, I pursued a PhD in proteomics, trained by leading experts including Adriana Franco Paes Leme at LNBio/CNPEM and Michael MacCoss at the University of Washington, where I applied LC–MS/MS to discover new protein biomarkers in oral cancer. When we talk about finding protein biomarkers, what we really mean is identifying specific molecules that signal the presence or status of a disease. In practice, this could mean a saliva test during a routine dental visit — measuring a panel of proteins known to be elevated in oral cancer, flagging a patient for further investigation before symptoms appear, when treatment is far more effective. I discovered novel candidate protein biomarkers for oral cancer detection in patient saliva, work I later extended to prostate cancer in urine and colorectal cancer in blood plasma.
It was during my PhD that I had an important realisation: many of the protein biomarkers I was identifying were glycosylated, yet the proteomics approaches I was using were largely overlooking this critical modification. That moment was pivotal — it made me realise there was a missing layer of information that could be highly relevant to disease biology.
After my PhD, I joined the lab of Giuseppe Palmisano at the University of São Paulo for postdoctoral research in post-translational modifications, supported by a FAPESP fellowship. I also had the opportunity to be trained by internationally recognised leaders in glycosciences, Prof Morten Thaysen-Andersen and Prof Nicolle Packer at Macquarie University, where I spent a year applying glycomics and glycoproteomics to study prostate cancer tissues. I later secured an independent fellowship from the Cancer Institute NSW to lead research in colorectal cancer glycobiology, during which I identified distinct glycan signatures and glycosylation enzymes associated with disease progression and patient survival.
Building on this work, I developed strong international collaborations and, in 2023, was recruited to establish a Glycoproteomics Lab at iGCORE, where I continue as a Visiting Associate Professor. I am now involved in major international initiatives including the Human Glycome Atlas Project and the Human Glycoproteomics Initiative, both aiming to map and understand glycans at unprecedented scale.
One of the most significant recent projects I have been involved in is our sex-specific glycoproteome mapping of 19 murine tissues, developed at iGCORE and supported by the Human Glycome Atlas Project in Japan.
This study found that sex is a major determinant of tissue-specific glycoproteome differences across multiple organs, including the salivary gland, liver, and kidney, while the brain remains remarkably conserved between sexes. Crucially, these sex-specific glycan signatures are not random — they arise from coordinated regulation of the proteome and the glycosylation machinery, generating distinct and biologically meaningful glycosignatures.
For a non-technical audience, one way to think about it is this: if glycans help cells communicate and respond to their environment, then men and women may be using slightly different “dialects” of the same biological language across different organs. This has important implications for medicine. It suggests that diseases might develop differently, or progress at different rates, partly because of these molecular differences — and that biomarkers or treatments developed without considering sex could miss important signals or be less effective for part of the population. It reinforces the need to design research and medical strategies that take sex into account from the beginning, not as an afterthought. In the long term, this could lead to more precise diagnostics and more personalised treatments that better reflect the biology of each individual.
For a long time, biomedical research has often treated male and female biology as largely interchangeable, or considered sex differences only at a very broad level. From a genomic perspective, males and females differ by just one chromosome, which is often mainly associated with reproductive functions. However, what we showed is that even at a much finer level — the glycan patterns on proteins, or the “glycan code” — there are significant and widespread differences between males and females across many tissues.
If glycans help cells communicate and respond to their environment, then men and women may be using slightly different “dialects” of the same biological language across different organs. This has direct implications for how we approach medicine: diseases might develop differently or progress at different rates partly because of these molecular differences, and biomarkers or treatments developed without considering sex could miss important signals or be less effective for part of the population.
What this changes is our approach to research design. It reinforces the need to account for sex from the beginning — not as an afterthought. In the long term, this could lead to more precise diagnostics and more personalised treatments that better reflect the biology of each individual.
The goal of that work, led as part of the Human Glycoproteomics Initiative, was to evaluate different informatics solutions and strategies for identifying glycopeptides from LC–MS/MS data — essentially, to understand how reliably different software tools and analytical approaches could read the glycan code from mass spectrometry experiments.
What surprised me most was how variable the results could be depending on the software and search strategies used. By systematically comparing these approaches, we were able to define key parameters for more accurate and comprehensive glycopeptide identification, providing practical guidance for the community and helping inform the development of better tools.
That experience shifted my mindset. Glycoproteomics has long been seen as technically demanding and accessible mainly to specialist groups. I realised how much impact we could have by making these approaches more accessible and reproducible — enabling non-specialist labs to confidently study the glycoproteome became as important a goal as generating new biological insights. It reinforced my commitment to making glycoproteomics more impactful across the broader life sciences community.
The Human Glycome Atlas Project and the Human Glycoproteomics Initiative both share an ambitious goal: to make the knowledge of glycans more accessible — not only to scientists, but ultimately to society as a whole.
If you ask most people whether they’ve heard of DNA or the genome, the answer is almost always yes. That’s largely thanks to landmark efforts like the Human Genome Project, which transformed our understanding of biology and medicine. A well-known example is how identifying DNA mutations linked to cancer risk has enabled preventive strategies, even influencing public decisions such as those made by Angelina Jolie.
Glycans are another major layer of biology — complex sugar structures attached to proteins and cells, carrying essential information that helps regulate how our bodies function. However, compared to DNA and proteins, we still know relatively little about this “glycan code.” These initiatives aim to systematically map and understand glycans at a scale that hasn’t been possible before, essentially building the equivalent of a glycome atlas. By doing so, they provide the foundation to uncover how glycans influence health and disease.
In the long term, this knowledge has the potential to transform medicine, enabling new diagnostics, more precise disease monitoring, and innovative therapeutic and preventive strategies. In many ways, these efforts are laying the groundwork for the next major leap in life sciences — similar to what the Human Genome Project achieved years ago.
One of the most exciting recent developments is the rapid progress in single-cell analysis. Advances in highly efficient and automated cell sorting, together with next-generation chromatography systems and mass spectrometry technologies, are now enabling proteomic measurements at the level of individual cells with unprecedented sensitivity and depth.
This is particularly transformative because it allows us to capture cellular heterogeneity in a way that was not possible before. Instead of averaging signals across thousands or millions of cells, we can now start to understand how individual cells differ in their protein expression and regulation — generating far more detailed and dynamic maps of cellular function, and helping to uncover the subtle but critical changes that drive processes like cancer progression, immune responses, and infection.
From my perspective, this has a huge impact on glycoproteomics specifically. These technological advances are opening the door to detecting glycopeptides in extremely complex and low-abundance samples, and ultimately to mapping protein expression alongside post-translational modifications at single-cell resolution. I believe this will fundamentally change how we study biology and disease.
Despite all the technological advances in proteomics, we are still not quite able to measure glycosylation at the single-cell level. We need much more sensitive and precise strategies to detect glycans on specific proteins, especially in extremely limited material.
What makes this particularly challenging — and exciting — is that glycosylation is so tightly regulated by the state of each individual cell. If we could truly map glycans at single-cell resolution, it would fundamentally transform our understanding of how individual cells generate their unique glycome and use it to communicate, interact, and function across different biological contexts.
I often find myself thinking about how we can push the boundaries of current technologies — whether through more sensitive mass spectrometry, improved separation methods, or better integration of multi-omics data — to finally make single-cell glycoproteomics a reality.
I would aim to push the boundaries of single-cell glycoproteomics. I would combine advanced cell sorting with multiplexed TMT labelling and comprehensive glycopeptide libraries to analyse hundreds, if not thousands, of individual cells isolated directly from cancer tissues. In parallel, I would work closely with bioinformaticians to develop machine learning approaches for multi-omics integration — using single-cell transcriptomics and proteomics to predict glycosylation patterns at the level of individual cells, linking gene expression of glycosylation enzymes, protein abundance, and glycan expression within individual cells into a unified picture.
The goal would be to generate detailed, cell-specific glycoproteome maps across different cancer types, capturing cellular heterogeneity at an entirely new level and revealing how glycosylation varies between individual cells within the same tumour and across diseases. This could uncover previously hidden mechanisms of tumour progression, immune evasion, and cell–cell communication — opening the door to more precise biomarkers and targeted therapeutic strategies.
Coordinating international collaborations is both one of the most rewarding and most challenging parts of my work. What I’ve learned is that success really depends on understanding how different cultures communicate, build trust, and make decisions.
For example, in Australia, communication tends to be quite direct and informal — people are comfortable expressing opinions openly, and discussions can move quickly. In Japan, communication is often more indirect and nuanced, with a stronger emphasis on reading context, building consensus, and maintaining harmony within the group. A message that feels clear and efficient in one context might come across as too blunt in another, or too vague somewhere else.
In practice, this means not just focusing on the science, but also on how we communicate: setting clear expectations, checking for shared understanding, and creating space for different perspectives. Over time, I’ve learned to adapt — being more explicit when needed, more patient in consensus-building, and more intentional about building relationships. When it works well, these collaborations become incredibly powerful, because you’re not only combining expertise, but also diverse ways of thinking. For me, that diversity is a real strength — it pushes the science further and makes the whole process much more enriching.
I wish I had understood earlier that a career in science is inherently uncertain — and that’s not something to fear, but to embrace. There’s rarely a straight or predictable path. Instead, it’s shaped by unexpected opportunities, challenges, and the people you meet along the way.
One moment that really stands out for me was in 2022, towards the end of my Early Career Fellowship in Australia. I was applying for a highly competitive fellowship to continue my research, and while waiting for the outcome, I was unexpectedly offered the opportunity to establish a Glycoproteomics Lab at iGCORE in Japan. It was a difficult decision — accepting the offer meant moving to a new country, adapting to a completely different culture, and taking my young family with me; my two boys were just one and four years old at the time. In the end, I chose to take the opportunity without knowing how things would unfold. It wasn’t always easy, but it was one of the best decisions I’ve made. It pushed me out of my comfort zone, helped me grow in independence, and allowed me to build new international collaborations and expand my research profile.
Resilience and courage are just as important as technical skills. It often means stepping out of your comfort zone, taking risks, moving across disciplines or even countries, and being open to new ways of thinking. Don’t be afraid to explore and to pioneer — some of the most meaningful opportunities come from following curiosity into the unknown, and those moments of uncertainty are often exactly what open new paths and lead to the most exciting discoveries.
For glycoproteomics workflows, chromatography performance is critical — glycopeptides are highly complex and heterogeneous, so achieving sharp, reproducible peaks is essential for the depth of coverage you can obtain. When I was establishing the Glycoproteomics Lab at iGCORE in 2023, selecting the right columns was a priority.
After conversations with colleagues in the proteomics community and with the team at IonOpticks, whose Aurora Series columns had been gaining strong recognition, I decided to integrate them into our workflows. Using a Vanquish LC system coupled with a Thermo Fisher Exploris 240 mass spectrometer, we achieved very sharp peaks — full-width half-maximum values of less than six seconds — and highly reproducible chromatography that remained stable over more than 500 runs. That level of consistency was particularly important for our mouse tissue glycoproteome mapping studies, where depth of coverage and reproducibility across large sample sets were both essential.
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