<div><div><div>Treating inherited diseases is one of the greatest challenges in modern medicine. In the future, targeted gene corrections at the earliest stages of embryonic development could help prevent certain inherited diseases from developing and being passed on to future generations. However, the safety of such approaches depends on how human embryos repair the DNA damage caused during gene editing and on the limitations of available technologies. These questions are addressed in a study published in the journal Nature, led by first author Štěpán Jeřábek, who is affiliated with both Columbia University and IOCB Prague. The research also involved two other IOCB Prague scientists, Iva Pichová and Michal Doležal.</div></div><div>Although DNA repair is one of the fundamental processes required for normal human embryonic development, little has been known about how it operates during the earliest stages of development. The new study is the first to provide a detailed comparison of how human embryos respond to two different types of DNA damage. “The study shows that early human embryos are able to effectively repair single-strand DNA damage, whereas the repair of double-strand breaks is significantly less reliable at this stage of development,” says the study’s first author, Štěpán Jeřábek.</div><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Studie_v_casopise_Nature_prinasi_prelomove_poznatky_o_moznostech_opravy_genetickych_chorob_v_ranem_embryonalnim_vyvoji_2_f9389b9db2.webp" alt="IOCHB Prague: A study in Nature sheds new light on DNA repair in early human embryos, with implications for future gene correction: The diagram illustrates the difference between CRISPR-Cas9 and base editing. The study shows that the method used to disrupt DNA affects the mechanism by which it is repaired in early human embryos. Credit: Adapted from Jeřábek et al., Nature, 2026." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_UOCHB_Studie_v_casopise_Nature_prinasi_prelomove_poznatky_o_moznostech_opravy_genetickych_chorob_v_ranem_embryonalnim_vyvoji_2_f9389b9db2.webp 245w," sizes="100vw" width="1620" height="911">To examine these repair mechanisms in detail, the researchers introduced targeted changes into two well-studied genes using two different genome-editing tools. Using CRISPR–Cas9, the researchers introduced double-strand breaks into embryonic DNA, while base editing produced only a single-strand nick. They then analyzed how the embryos' DNA repair mechanisms responded to each type of DNA damage.Michal Doležal and Iva Pichová from IOCB Prague contributed to the purification of the protein-based editors used in the study to introduce precisely defined single-strand DNA changes. “Collaboration on the study began as early as 2021, and over the following years we prepared several editor variants for experiments carried out by our colleagues at Columbia University. Some of these were ultimately used in the study. We found that delivering the editors directly into embryonic cells as proteins, rather than as mRNA, was compatible with normal embryonic development,” says Michal Doležal.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Studie_v_casopise_Nature_prinasi_prelomove_poznatky_o_moznostech_opravy_genetickych_chorob_v_ranem_embryonalnim_vyvoji_3_fc4dfcf14c.webp" alt="IOCHB Prague: A study in Nature sheds new light on DNA repair in early human embryos, with implications for future gene correction: A human embryo at the blastocyst stage, in whose DNA Dieter Egli's group performed base editing in the PCSK9 and HBG genes. Credit: Štěpán Jeřábek (Columbia University and IOCB Prague)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_UOCHB_Studie_v_casopise_Nature_prinasi_prelomove_poznatky_o_moznostech_opravy_genetickych_chorob_v_ranem_embryonalnim_vyvoji_3_fc4dfcf14c.webp 208w," sizes="100vw" width="1620" height="1215">One of the study’s key findings is that the researchers successfully isolated stem cells from the edited six-day-old embryos. The stem cells provide sufficient genetic material for detailed analyses, allowing the researchers to investigate the effects of gene editing in greater depth. In addition, they make it possible to study the consequences of introduced genetic changes in subsequent generations of cells.In addition to providing new insights into DNA repair, the study also highlights the limitations of current genome-editing technologies and the need for continuous research. “Our goal was not to develop a method for genetically modifying human embryos but rather to better understand, through basic research, how DNA repair mechanisms function in the early stages of human development. Although base editing represents a significant improvement over CRISPR–Cas9 in terms of DNA repair precision, our findings also show that many important questions regarding safety must be answered before these methods can be considered for clinical use in human embryos,” says Štěpán Jeřábek.The research was conducted in Dieter Egli's laboratory under the oversight of Columbia University's ethics committee. Even before publication, the study attracted international attention and was covered by leading global media, including The New York Times. Jan Konvalinka, IOCB Prague Director, emphasizes that this type of basic research is important not only scientifically but also from a broader societal perspective. “I consider the ethical debate surrounding studies like this to be both legitimate and necessary. The purpose of basic research is to expand the boundaries of knowledge while helping us better understand the possibilities and limitations of current technologies. That is precisely why this work represents an important contribution to both scientific and public debate.”The project was initially funded by IOCB Tech, the technology transfer office of IOCB Prague. After two years, the IOCB Tech Foundation took over funding for the project. “We supported this research because it was an exceptionally promising project by a talented IOCB Prague scientist at Columbia University. As we can now see, it has produced results of global significance,” says Milan Prášil, Director of IOCB Tech.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Studie_v_casopise_Nature_prinasi_prelomove_poznatky_o_moznostech_opravy_genetickych_chorob_v_ranem_embryonalnim_vyvoji_bb7bafc971.webp" alt="IOCHB Prague/Tomáš Belloň: A study in Nature sheds new light on DNA repair in early human embryos, with implications for future gene correction: First author of the study Štěpán Jeřábek (Columbia University) with co-authors Michal Doležal and Iva Pichová (IOCB Prague)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_UOCHB_Studie_v_casopise_Nature_prinasi_prelomove_poznatky_o_moznostech_opravy_genetickych_chorob_v_ranem_embryonalnim_vyvoji_bb7bafc971.webp 234w," sizes="100vw" width="810" height="540"><blockquote><h4>The original article</h4><h4><a target="_blank" rel="noopener noreferrer" href="https://www.nature.com/articles/s41586-026-11118-x">Highly efficient base editing at PCSK9 and normal human embryo development</a></h4>Stepan Jerabek, Chanju Jung, Michelle Kappy, Qiaojin Zhao, Julie Sung, Ning Wang, Euihyun Kim, Jimin Kim, Marcos Iuri Roos Kulmann, Madeleine Bliss King, Mitchell John McAndrew, Meng Li, Sakshi Bhatele, Melisa Isado, Hong-Su Jang, Michal Dolezal, Robert Prosser, Shuangyi Xu, Gue-Ho Hwang, Iva Pichova, Jia Xu, Diego Marin, Jae-Sung Woo, Sangsu Bae, Nathan Treff, Audrone Lapinaite &amp; Dieter EgliNature, 2026, doi: 10.1038/s41586-026-11118-x<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1038/s41586-026-11118-x">https://doi.org/10.1038/s41586-026-11118-x</a>&nbsp;</blockquote></div>

A study in Nature sheds new light on DNA repair in early human embryos, with implications for future gene correction

In this episode of Concentrating on Chromatography, host David Oliva is joined for the&nbsp;first time by co-host Candice (Candi) Gokey — PhD candidate at UC San Diego / San Diego State University and expert in LC-MS/MS method development for untargeted metabolomics to interview Jacob Russell, a third-year PhD student in the Riley Research Group at the University of Washington (Seattle).Jacob's research sits at the frontier of mass spectrometry-based intact glycoproteomics, where the goal is to keep glycans attached to peptides during analysis — preserving the biological information that is lost when glycans are enzymatically removed. His lab, led by Prof. Nick Riley, develops new methods to tackle every stage of glycoproteomic analysis, from sample preparation and enrichment through data acquisition and bioinformatics.<h4>WHAT WE COVER:</h4><ul><li>What is the glycocalyx, and why does glycoproteomics matter for cancer, immunity, and protein biology?</li><li>N-linked vs. O-linked glycosylation: why they require completely different fragmentation strategies (HCD vs. ETD/EThcD)</li><li>Autonomous Dissociation-type Selection (ADS): how real-time library searching (RTLS) of oxonium ion ratios (m/z 138 vs. 144) enables on-the-fly selection of the right fragmentation method for N- vs. O-glycopeptides — published in J. Proteome Research (Sutherland, Veth, Russell et al., 2024)</li><li>How XGBoost machine learning outperforms RTLS by classifying ~50 oxonium ions simultaneously, recovering Core 2 O-glycopeptides that the simpler ratio-based method misses</li><li>Casanovo Foundation: a transformer-based foundation model for tandem mass spectra and how deep learning is reshaping glycopeptide classification (Sanders et al., arXiv 2025)</li><li>LacNAc-ase enabled glycoproteomics: using endo-β-galactosidase (EBG) to "trim" poly-LacNAc chains on N-glycans — uncovering previously undetectable glycoforms (ASMS 2026 presentation)</li><li>Cutaneous vs. uveal melanoma: comparing poly-LacNAcylated glycoproteins (including galectin-3 binding partners like CD63, LAMP-2, and basigin) between cell lines —&nbsp;and why uveal melanoma has a ~50% distant metastasis rate vs. ~5% for cutaneous&nbsp;</li><li>The future of intelligent data acquisition and real-time mass spectrometry</li><li>Candi's parallel world of untargeted metabolomics, coral-algae chemical communication, and GNPS/MassQL — and the surprising overlap with glycoproteomics</li></ul><h3>Video Transcription</h3><h4>Why glycoproteomics is so challenging</h4>Glycans play fundamental roles throughout biology. They are involved in immune processes, cancer, protein folding, protein stability, and many other cellular functions. Every living cell studied to date carries a glycan-rich surface layer, making glycosylation an important component of biological regulation and disease.&nbsp;Studying glycoproteins, however, is considerably more complicated than conventional proteomics. One traditional way to simplify an experiment is to enzymatically remove glycans from proteins before analysis. While this makes the analytical problem easier, it also removes information about which amino acid carried a particular glycan.The Riley laboratory instead works extensively with intact glycoproteomics, retaining the glycan on the peptide so that both the peptide sequence and glycosylation information can be investigated together. This introduces challenges at virtually every stage of the workflow, from enrichment and sample preparation through mass spectrometric acquisition to bioinformatic interpretation.&nbsp;Russell emphasized that glycoproteomics still trails conventional proteomics in areas such as identification depth and standardized workflows. At the same time, these limitations provide opportunities for new analytical methods, including improved enrichment, acquisition strategies, instrumentation, and post-acquisition data processing.&nbsp;<h4>N- and O-glycopeptides require different analytical strategies</h4>One of the central complications is that N-linked and O-linked glycosylation behave differently.N-glycosylation occurs at a relatively well-defined amino-acid sequence motif involving an asparagine residue. This predictable localization means that collision-based fragmentation can often provide sufficient information for identifying N-glycopeptides.O-glycosylation presents a more difficult problem. O-glycans can occur at serine or threonine residues without an equivalent conserved sequence motif, and multiple O-glycans may be present on a single peptide. With conventional collision-based fragmentation, the glycan can be lost before sufficient peptide backbone information is generated, making it difficult to assign the modification to a specific amino acid.&nbsp;To preserve localization information, researchers can use electron-based fragmentation such as electron transfer dissociation (ETD). ETD preferentially fragments the peptide backbone while leaving the glycan attached. The Riley group also employs supplemental collisional activation, combining the benefits of electron- and collision-based fragmentation. This can help separate non-covalently associated fragments while also producing glycan-derived fragments known as oxonium ions, which provide additional information about glycan composition.&nbsp;The difficulty is therefore not simply detecting a glycopeptide. The instrument must ideally determine what kind of glycopeptide it is and select the most informative fragmentation strategy accordingly.<h4>Making fragmentation decisions in real time</h4>Earlier approaches to simultaneous N- and O-glycopeptide analysis often relied on product-dependent triggering. A collision-based MS/MS spectrum would first be acquired and examined for oxonium ions. If these characteristic glycan fragments were detected, the instrument would trigger an additional electron-based fragmentation event.The limitation, according to Russell, is that this approach essentially asks only whether a precursor is a glycopeptide. It does not determine whether the spectrum is more likely to originate from an N- or O-glycopeptide. As a result, slower electron-based scans may be triggered unnecessarily, consuming valuable acquisition time during an LC-MS experiment.&nbsp;To address this problem, the researchers developed an approach based on autonomous dissociation type selection and real-time spectral evaluation.The strategy initially uses real-time library searching to compare an acquired spectrum with reference patterns characteristic of N- and O-glycopeptides. Particular attention is paid to two oxonium-ion signals at m/z 138 and 144. Their relative intensities provide information that can help distinguish the two glycopeptide classes.If the acquired spectrum resembles an O-glycopeptide, the instrument can selectively trigger the more time-consuming electron-based fragmentation only where it is most useful. This makes more efficient use of instrument time and increases the amount of relevant information collected during a chromatographic run.&nbsp;<h4>From two diagnostic ions to machine learning</h4>Although the real-time library strategy improved acquisition efficiency, it still had limitations.Some O-glycans contain structural features that can make their oxonium-ion pattern resemble that of N-glycans. A classification based primarily on the 138/144 ratio can therefore misclassify certain O-glycopeptides and fail to trigger the appropriate fragmentation experiment.&nbsp;Machine learning offered a way to expand the decision beyond two diagnostic ions.Rather than considering only a small number of manually selected signals, the new approach can evaluate approximately 50 oxonium-ion intensities simultaneously. Published, well-annotated glycoproteomics datasets can then be used to train models capable of recognizing more complex spectral patterns associated with different glycopeptide classes.&nbsp;For this work, the group uses an in-house tool called GlyCounter to extract oxonium-ion intensities from spectra. These values are subsequently provided to an XGBoost machine-learning model.According to Russell, offline extraction with GlyCounter may take several minutes for a large dataset, while XGBoost itself can train and perform classifications extremely quickly. More importantly for intelligent acquisition, the pre-trained model can classify spectra on a millisecond timescale, making it suitable for real-time operation during LC-MS analysis.&nbsp;<h4>Machine learning improves glycopeptide classification</h4>The machine-learning work was performed in collaboration with the laboratory of William Noble at the University of Washington.When several machine- and deep-learning approaches were benchmarked against the earlier real-time library-searching strategy using a large published glycopeptide dataset, the learning-based methods substantially improved classification performance. Russell highlighted an especially important result: XGBoost was able to correctly recognize certain complex O-glycopeptide spectra that the simpler rule-based method had classified as N-glycopeptides.Recovering these spectra means that information previously missed during acquisition can now be retained and subjected to the more appropriate fragmentation strategy.&nbsp;Gokey drew parallels with challenges in untargeted metabolomics, where researchers also work with increasingly large spectral libraries and computational tools for interrogating characteristic fragments and mass-to-charge ratios. Their discussion highlighted a broader trend across mass spectrometry: analytical workflows are increasingly moving from acquiring everything first and interpreting it later toward using information generated during the experiment to guide what the instrument does next.&nbsp;<h4>Getting more information from the mass spectrometer</h4>Russell sees intelligent data acquisition as a way to make better use of modern instrumentation.Rather than treating an LC-MS method as a fixed sequence of predetermined events, real-time processing allows the instrument to react to the data it is generating. Classification or spectral interpretation can therefore influence which precursor is selected, what fragmentation method is used, or which additional experiment should be performed.He stressed that further development will depend on cooperation between academic researchers, industrial scientists, and instrument manufacturers, particularly through broader support for real-time mass spectrometry capabilities.&nbsp;Gokey noted that similar concepts could eventually be valuable in areas such as native mass spectrometry, where researchers may benefit from observing molecular behavior and adjusting analytical parameters while an experiment is still running. Both researchers see computing resources, software integration, and access to real-time instrument control as important factors determining how quickly such strategies become routine.&nbsp;<h4>Simplifying highly complex glycans</h4>Another part of Russell's research focuses on particularly large N-glycans containing poly-N-acetyllactosamine (poly-LacNAc) structures.These elongated glycans consist of repeating monosaccharide units and are biologically important, including in immune processes, tumor invasion, and metastasis. Their size and structural microheterogeneity, however, create major analytical problems. Large glycopeptides may ionize poorly, while the number of possible glycan configurations can make spectral interpretation difficult.&nbsp;The researchers are exploring an enzymatic approach that removes the extended repeating region without removing the entire glycan from the peptide. Using endo-β-galactosidase, the poly-LacNAc chain can be shortened while retaining enough of the glycan structure to preserve biologically relevant information.The resulting glycopeptides are easier to ionize and exhibit reduced microheterogeneity, simplifying intact glycoproteomic analysis. The concept had previously been demonstrated at the glycomics level, and the group has been investigating how to incorporate it into intact glycopeptide workflows.<h4>Exploring glycosylation in melanoma</h4>One application of this workflow is the comparison of cutaneous and uveal melanoma.The researchers are interested in whether differences in poly-LacNAc glycosylation could contribute to the markedly different metastatic behavior of these diseases. Russell explained that poly-LacNAc structures have previously been associated with tumor-cell invasion and migration, making them an interesting target for investigating biological differences between the two melanoma types.&nbsp;This work illustrates the wider motivation behind the development of new glycoproteomics technologies. Improvements in enrichment, fragmentation, intelligent acquisition, and computational interpretation are not only about generating more identifications. They can make previously inaccessible biological questions experimentally tractable.The discussion between Russell and Gokey ultimately points toward a future in which mass spectrometers become increasingly adaptive analytical systems. By combining real-time spectral information with machine learning and carefully designed chemical workflows, researchers may be able to make better fragmentation decisions, recover information that would otherwise be lost, and analyze increasingly complex biological systems with greater depth and efficiency.<blockquote>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</blockquote><blockquote><h4>Concentrating on Chromatography Podcast</h4>Dive into the frontiers of chromatography, mass spectrometry, and sample preparation with host David Oliva. Each episode features candid conversations with leading researchers, industry innovators, and passionate scientists who are shaping the future of analytical chemistry. From decoding PFAS detection challenges to exploring the latest in AI-assisted liquid chromatography, this show uncovers practical workflows, sustainability breakthroughs, and the real-world impact of separation science. Whether you’re a chromatographer, lab professional, or researcher you'll discover inspiring content!You can find Concentrating on Chromatography Podcast in podcast apps:<ul><li><a target="_blank" rel="noopener noreferrer" href="https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL">Spotify</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podcasts.apple.com/tz/podcast/concentrating-on-chromatography/id1788429185">Apple podcast</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podscan.fm/podcasts/concentrating-on-chromatography">podscan</a></li></ul>and on <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/@ChromatographyTalk/videos">YouTube channel</a></blockquote>

Decoding the Glycocode: AI-Powered Glycoproteomics & Cancer Research

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