Eugenio F. Fornasiero (@euforna) 's Twitter Profile
Eugenio F. Fornasiero

@euforna

Interested in aging, molecular turnover, neurons, synapses, super-resolution microscopy, metabolic labeling and proteomics

ID: 2202313684

linkhttps://www.fornasierolab.uni-goettingen.de/ calendar_today30-11-2013 21:43:51

540 Tweet

521 Followers

454 Following

Human Technopole (@humantechnopole) 's Twitter Profile Photo

🚀The Milan #RNASalon is on! 21 labs working on RNA biology from 10 institutions in Milan meeting monthly for scientific talks, new collaborations, networking and much more. Kick-off 29 Nov at HT. Many thanks to The RNA Society and Lexogen for their support! humantechnopole.it/en/trainings/m…

🚀The Milan #RNASalon is on!
21 labs working on RNA biology from 10 institutions in Milan meeting monthly for scientific talks, new collaborations, networking and much more. Kick-off 29 Nov at HT. Many thanks to <a href="/RNASociety/">The RNA Society</a> and <a href="/lexogen/">Lexogen</a> for their support! humantechnopole.it/en/trainings/m…
Marina Mikhaylova (@marinamikhaylo8) 's Twitter Profile Photo

I am very happy to share our work revealing new aspects of the cell biology of neurons with the dendritic axon origin. It was a great pleasure to collaborate with Christophe Leterrier and his team! rupress.org/jcb/article/22…

Matthew Taliaferro (@jmtali) 's Twitter Profile Photo

Excited to share our latest work! We developed a new method for studying RNA localization via proximity labeling: OINC-seq! In contrast to other proximity methods, labels deposited on RNAs are read directly by sequencing without a need for biotinylation. biorxiv.org/cgi/content/sh…

Excited to share our latest work! We developed a new method for studying RNA localization via proximity labeling: OINC-seq! In contrast to other proximity  methods, labels deposited on RNAs are read directly by sequencing without a need for biotinylation. biorxiv.org/cgi/content/sh…
Mitch Guttman (@mitchguttman) 's Twitter Profile Photo

Gene regulation involves thousands of proteins that bind DNA, yet comprehensively mapping these is challenging. Our paper in Nature Genetics describes ChIP-DIP, a method for genome-wide mapping of hundreds of DNA-protein interactions in a single experiment. nature.com/articles/s4158…

Eugenio F. Fornasiero (@euforna) 's Twitter Profile Photo

Happy to announce the 8th Schram Foundation Symposium in Göttingen on the 25ht of March 2025 (satellite of the German Neuroscience society). Attendance is free and we have great speakers including Tomohisa Toda, Marlene Bartos Pawel Burkhardt Schaefer Lab Please circulate!

Happy to announce the 8th Schram Foundation Symposium  in Göttingen on the 25ht of March 2025 (satellite of the German Neuroscience society). Attendance is free and we have great speakers including <a href="/TomohisaToda/">Tomohisa Toda</a>, <a href="/bartos_marlene/">Marlene Bartos</a> <a href="/Pawel_Burkhardt/">Pawel Burkhardt</a> <a href="/lab_schaefer/">Schaefer Lab</a> Please circulate!
Andrew Payne (@andrew_c_payne) 's Twitter Profile Photo

E11 Bio is excited to share a major step towards brain mapping at 100x lower cost, making whole-brain connectomics at human & mouse scale feasible (🧠→🔬→💻). Critical for curing brain disorders, building human-like AI systems, and even simulating human brains. 1/N 🧵

Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

As we know, the human plasma🩸 proteome is crucial! The Matthias Mann Lab just published a fantastic study in Nature Genetics! And here is our News & Views highlighting the mapping of plasma protein QTLs and why #MassSpec remains a key player: nature.com/articles/s4158…. Am Soc for Mass Spec Human Proteome

Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

0/ Tissue proteomes are shaped by both protein abundance and lifetime. Using advanced quantitative proteomics (#DIA and #TMT) and stable isotope labeling, we mapped the abundance and turnover of 11,000 proteins and 40,000 phosphosites in 16 mouse tissue and brain regions. ⬇️

0/ Tissue proteomes are shaped by both protein abundance and lifetime. Using advanced quantitative proteomics (#DIA and #TMT) and stable isotope labeling, we mapped the abundance and turnover of 11,000 proteins and 40,000 phosphosites in 16 mouse tissue and brain regions. ⬇️
Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

1/ We show protein half-life is a critical factor defining tissue function. We developed a Heat-Circle (HC) plot, a powerful visualization integrating protein abundance & lifetime across tissues. It reveals how cellular proteomic energy expenditure varies at various levels. ⬇️

1/ We show protein half-life is a critical factor defining tissue function. We developed a Heat-Circle (HC) plot, a powerful visualization integrating protein abundance &amp; lifetime across tissues. It reveals how cellular proteomic energy expenditure varies at various levels. ⬇️
Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

2/ We uncovered distinct turnover rates for proteasome, lysosome, and E3 ligases across tissues! K48-linked ubiquitin (UPS-targeted) turns over more slowly than K63-linked ubiquitin (lysosomal degradation), suggesting distinct ubiquitin recycling strategies across tissues! ⬇️

2/ We uncovered distinct turnover rates for proteasome, lysosome, and E3 ligases across tissues! K48-linked ubiquitin (UPS-targeted) turns over more slowly than K63-linked ubiquitin (lysosomal degradation), suggesting distinct ubiquitin recycling strategies across tissues! ⬇️
Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

3/ Proteins in protein-protein interaction (PPI) networks exhibit highly coordinated turnover across tissues. Our data suggest that protein lifetime is constrained by tissue-specific PPI, and remarkably, protein lifetime across tissues can predict PPIs with high performance! ⬇️

3/ Proteins in protein-protein interaction (PPI) networks exhibit highly coordinated turnover across tissues. Our data suggest that protein lifetime is constrained by tissue-specific PPI, and remarkably, protein lifetime across tissues can predict PPIs with high performance! ⬇️
Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

4/ Using multi-omics, we discovered striking tissue-specific turnover diversity in peroxisomal proteins. Peroxisome proteins seem to be shorter-lived in tissues of fast turnover while longer-lived in tissues of slow turnover, likely adapting to metabolic and cellular demands. ⬇️

4/ Using multi-omics, we discovered striking tissue-specific turnover diversity in peroxisomal proteins. Peroxisome proteins seem to be shorter-lived in tissues of fast turnover while longer-lived in tissues of slow turnover, likely adapting to metabolic and cellular demands. ⬇️
Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

5/ We report site-specific phosphorylations dramatically alter protein lifetime in vivo. We identified key phosphorylation sites on neurodegeneration proteins, including Tau and α-synuclein, that stabilize or destabilize these proteins, potentially impacting their pathology! ⬇️

5/ We report site-specific phosphorylations dramatically alter protein lifetime in vivo. We identified key phosphorylation sites on neurodegeneration proteins, including Tau and α-synuclein, that stabilize or destabilize these proteins, potentially impacting their pathology! ⬇️
Yansheng Liu (@yanshen73854711) 's Twitter Profile Photo

6/ Explore our data through Turnover-PPT 🔗[yslproteomics.shinyapps.io/tissuePPT] This work would not have been possible without our collaborators in Junmin Peng Eugenio F. Fornasiero @shisheng2017🤝🤝, the hard work of our lab members Andy, and supportive environment at Yale University Yale West Campus.

6/ Explore our data through Turnover-PPT 🔗[yslproteomics.shinyapps.io/tissuePPT]
This work would not have been possible without our collaborators in <a href="/JunminPengLab/">Junmin Peng</a> <a href="/euforna/">Eugenio F. Fornasiero</a> @shisheng2017🤝🤝, the hard work of our lab members <a href="/Andy01230396/">Andy</a>, and supportive environment at <a href="/Yale/">Yale University</a> <a href="/YaleWestCampus/">Yale West Campus</a>.
Eugenio F. Fornasiero (@euforna) 's Twitter Profile Photo

🚀 Excited to share our latest work! Proud to have been part of this collaborative work on Protein turnover across several tissues and brain regions Cell with Yansheng Liu and Junmin Peng #proteomics authors.elsevier.com/c/1koBJL7PXuE9g

Eugenio F. Fornasiero (@euforna) 's Twitter Profile Photo

🚀 Excited to share our latest work! Proud to have been part of this collaborative work on Protein turnover across several tissues and brain regions Cell with Yansheng Liu and Junmin Peng and @NishaHemandha from the lab. Check it out👇 authors.elsevier.com/c/1koBJL7PXuE9g

🚀 Excited to share our latest work! Proud to have been part of this collaborative work on Protein turnover across several tissues and brain regions <a href="/CellCellPress/">Cell</a> with <a href="/Yanshen73854711/">Yansheng Liu</a> and <a href="/JunminPengLab/">Junmin Peng</a> and @NishaHemandha from the lab. Check it out👇 authors.elsevier.com/c/1koBJL7PXuE9g
Nature Neuroscience (@natureneuro) 's Twitter Profile Photo

A pair of methods papers for studying synapses: DELTA: a method for brain-wide measurement of synaptic protein turnover reveals localized plasticity during learning Boaz Mohar (@[email protected]) karel svoboda @rhodamine110 Nelson Spruston Eugenio F. Fornasiero HHMI | Janelia Allen Institute nature.com/articles/s4159…

Giordano Lippi (@lippilab) 's Twitter Profile Photo

Delighted to see our paper finally out in Neuron! Together with Ian MacRae, we developed a new toolbox to study microRNAs and used it to find new mechanisms of Purkinje cell development. Please see the tweetorial from researcher extraordinaire Nori Zolboot for details.