True. I came for the slime molds π¦ and stayed for the glycans π¦π‘πΊοΈβ¦οΈ
04.02.2026 13:07
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True. I came for the slime molds π¦ and stayed for the glycans π¦π‘πΊοΈβ¦οΈ
Setting up my new lab at the Medical University of Vienna. Exciting times! π§ͺπ¬
π¨ PhD position open! π¨
Join our team at the Medical University of Vienna to study glycan regulation in mammary organoids, milk, and breast cancer.
Details in the image β please share! π§¬β¨
Wir gratulieren @smereiter.bsky.social! ππ
Der Postdoc-Researcher an der #MedUniWien & am βͺ@imbavienna.bsky.social β¬erhΓ€lt einen FΓΆrderungs-Grant des @fwf-at.bsky.social. Mehr dazu ‡
1/23 Big news for the #ObenaufLab! So excited to finally share our new study providing another puzzle piece, why immunotherapy fails in many tumors, now out in @Nature π§΅π www.nature.com/articles/s41...
Feeling honored to work in a lab with two (!) of 2024βs most cited scientists: mentor Josef Penninger π§ and lab colleague Max Kellner π (@clarivate). Max (spot him sitting behind me in yesterdayβs lab meeting) is a PhD student π€―
please don't π
Hi Wouter. Could you please add me too ππ½ββοΈ
Thank you for organizing this starter pack! Would love to be added.
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Great collaboration between BOKU University, IMBA, MedUni Vienna, and Michigan University! Thank you, J. Helm and the amazing Stadlmann Lab for taking me on this ride!! Together, weβre uncovering new insights into glycans. π¦ π‘ πΊ π’ πΆ π¨
11/
In our paper, we showcase a scalable, LC-MS/MS data-driven method combining automated ID, non-targeted profiling, and isomer-sensitive glycan analysis. Dive into the details: doi.org/10.1038/s414...
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For those ready to dive deeper: We havenβt even started with the chromatography data! PGC allows us to differentiate N-glycans with the same mass but distinct structures, adding more layers of tissue-specific complexity.
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But waitβthere was more! After filtering non-glycan spectra and expected glycans, we found spectra representing unexpected glycan structures and mapped them across all tissues! π
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Next, we extended SNOG with eSNOG, extracting spectra with special fragment ions to compare glycan structural features like Ξ±-Gal, antennary Fuc, Neu5Ac, Neu5Gc, and oligo-Man across tissues.
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With SNOG-filtered data, we saw clear, tissue-specific glycan clusters emerge, with high technical reproducibility across replicates. This filtering step was a game-changer!
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First up: SNOG-filtering. This automated step removes contaminants (up to 75% in some tissues!) so we can focus on genuine N-glycan signals.
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Our approach had to be scalable, non-targeted (no pre-built mass lists, please!), and data-driven. Automated spectral ID would be the icing on the cake! π§ We combined PGC analysis with multiple profiling strategies for semi/quantitative N-glycomics.
4/
Faced with an overwhelming amount of LC-MS/MS data, we knew manual annotation was out of the question. Instead, we developed an βunconventionalβ approach to analyze our N-glycome data in a faster, smarter way. Hereβs what we did:
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So, we analyzed N-glycans from 20 mouse tissues, generating a comprehensive, structure-resolved N-glycome Atlas. Using PGC columns for isomer separation and an Orbitrap for high-res MS/MS, we assembled a mountain of data. Now what?
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Have you ever wondered how many unique N-glycan structures a single organism might create? Or if the sugars on your kidney cells differ from those in your brain?
We did too, and we set out to investigate!
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Hi π¦! Did you know? Glycansβcomplex sugar structuresβdecorate almost every protein processed by the ER/Golgi. These N-glycans coat our cells, playing critical roles in cell interactions and immune processes. π¬ Curious about how they vary? Letβs dive in! #GlycoTime
Great list & thanks for organizing! Would love to join.
Thank you for organizing! Would love to be added.
Could you also add me? Thanks a lot!