“Glycans have largely been missing from the single-cell revolution, and bringing glycomics into this space could reveal an entirely new layer of cellular heterogeneity. It also means that separation science will become increasingly important. Mass spectrometry is extraordinarily powerful, but it cannot resolve every form of molecular complexity on its own. I may be slightly biased, but I think this creates a very exciting future for CE-MS!”
What does your research focus on, and what problem are you trying to solve?
My research explores the fascinating complexity of glycosylation – the sugars decorating proteins and cells – and how it changes in diseases such as cancer. I have a particular passion for pushing CE-MS-based glyco(proteo)mics to new limits. In our group, we aim to reveal molecular details previously hidden from view, ultimately reaching individual cells and uncovering new biology along the way.
What aspect of your current research excites you most – and why is this an important moment for it?
What excites me most – and occasionally frustrates me – is that glycosylation never stops surprising us. Every time new technologies allow us to look deeper, we find answers, but also unexpected biology, previously unseen molecular species, and new questions.
Advances in sensitivity, separation technologies, and data analysis now let us explore this complexity at unprecedented depth, even moving toward individual cells. But the goal should not be simply to detect more; it is to uncover meaningful biology. As sensitivity increases, understanding what is real – including taking our blanks seriously! – becomes even more important. That unpredictability is part of the fun: in glycoscience, solving one puzzle often reveals three more.
Looking five to 10 years ahead, what emerging trend do you think will have the greatest impact on analytical science?
I think one of the biggest trends will be our ability to extract far richer molecular information from dramatically less material. Single-cell analysis is perhaps the most obvious example, but it goes beyond sensitivity. Simply detecting a molecule will increasingly not be enough; we want to distinguish isomers, linkages, and subtle structural differences that can completely change the biology.
For glycoscience, that is incredibly exciting. Glycans have largely been missing from the single-cell revolution, and bringing glycomics into this space could reveal an entirely new layer of cellular heterogeneity. It also means that separation science will become increasingly important. Mass spectrometry is extraordinarily powerful, but it cannot resolve every form of molecular complexity on its own. I may be slightly biased, but I think this creates a very exciting future for CE-MS!
At the same time, these technologies will generate an enormous wealth of information. The next challenge will be finding the hidden gems: integrating glycomics with other molecular layers and using computational tools and AI to uncover patterns we could never recognize manually.
But the analytical scientist remains essential. We still need to understand where our data come from, what their limitations are, and whether an exciting pattern actually makes chemical and biological sense.
What is the biggest challenge facing analytical science today?
Perhaps knowing what to trust and what is actually meaningful. We are becoming exceptionally good at generating data: more sensitivity, higher throughput, and increasingly complex datasets. AI provides tremendous opportunities to find patterns and interpret this information, but a convincing answer or beautiful pattern is not necessarily a correct or biologically relevant one.
As analytical scientists, we therefore need to remain critical: Where did the signal come from? How robust and reproducible is it? Does it make chemical and biological sense? I use AI myself and am excited about its possibilities, but transparency, validation, and understanding the limitations of both our measurements and computational tools will be essential. The challenge is no longer simply to measure more, but to know what to trust, what matters, and what we can learn from it.
Do you have any strong opinions with which the rest of the field tends to disagree?
More sensitivity and more data do not automatically mean better science! That might be a slightly dangerous thing to say as an analytical chemist working toward single-cell glycomics.
I love pushing technology to its limits, and I strongly believe in developing technologies even when we do not yet know exactly where they will take us; new capabilities can open doors to questions we have not even thought of yet. But the most sophisticated measurement is not automatically the most useful one. We should remain curious about what technology can reveal while also asking whether the additional sensitivity, complexity, or data actually add meaningful information.
What decision, opportunity, or unexpected event has had the greatest influence on your career so far?
Serendipity has played a surprisingly large role in my career. I was originally hired for my PhD to work on a different project, and we started using prostate-specific antigen (PSA) simply as a model glycoprotein to explore what CE could do for glycoproteomics.
That experiment changed everything: we discovered the remarkable separation power of CE for glycoforms carrying differently linked sialic acids, and what started as a “let’s just see what happens” experiment eventually reshaped my PhD into a thesis centered on glycosylation in prostate cancer.
That experience taught me to stay open to where the science takes you. Since then, several important steps in my career – including moving to the Barnett Institute in Boston and starting my own group in Groningen – have come from saying yes to opportunities without knowing exactly where they would lead. Of course, being in the right place at the right time only gets you so far; having supervisors, colleagues, and peers who gave me the confidence and freedom to explore those opportunities has been equally important.
Perhaps that first unexpected PSA experiment explains why I still enjoy exploring the unknown so much today. It shaped my enthusiasm for CE, but more importantly, it taught me that sometimes the experiment you did not plan to build your career around becomes the one that changes its direction completely.
Who has changed the way you think about science – or life more broadly – and how?
My PhD supervisor, Manfred Wuhrer, has had a major influence on how I approach science. He had confidence in me, gave me independence, and encouraged me to explore ideas and opportunities, even when we did not know exactly where they would lead.
Working alongside clinicians and clinical chemists during that time added another important perspective: developing exciting new analytical technologies can open doors we do not yet know exist, but understanding the biological and clinical context can completely change the questions we ask of them.
What I increasingly realize, though, is that this influence did not stop with one mentor. I learn constantly from my students, PhD candidates, postdocs, collaborators, and peers. I still regularly find myself in conversations thinking, “I really don’t know enough about this!” I used to find that uncomfortable – and in some cases I still feel that way – but I also now see it as one of the best parts of science. Be honest, ask questions, and surround yourself with people who know things you don’t.
Perhaps that is why I have come to believe so strongly that science progresses through people, not just ideas. I was fortunate to be given trust, freedom, and room to explore, and I try to create the same environment for the people I work with: one where we can ask seemingly simple questions, challenge each other – including me – try something new, make mistakes, and learn from them. That is usually where both the best science and the most enjoyable science happen.
What interest or skill outside science has made you a better researcher?
Creativity, especially finding ways to make complex science accessible and engaging. I love taking something complicated and finding a different way to look at it, whether that is a figure that suddenly makes a dataset click, teaching students, or explaining glycosylation to children using beads and coloring activities.
New tools, including AI, are giving us amazing possibilities to visualize data and communicate ideas, but for me, creativity goes beyond making something look good. It is about finding the story, deciding what really matters, and making someone curious enough to want to know more.
Finding that story often means stepping outside my own scientific perspective and trying to see it through someone else’s eyes. That process regularly makes me look differently at my own research as well. Sometimes finding a simple way to explain something, or being asked a wonderfully basic “why?”, is exactly what I need to see a problem from a completely new angle.
Guinevere Lageveen-Kammeijer is Assistant Professor of Analytical Biochemistry at the University of Groningen, the Netherlands
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