In this special, year-end episode of Translating Proteomics, hosts Parag Mallick and Andreas Huhmer discuss a few publications from 2024 that they believe are great examples of pre-clinical research using proteomics, basic research using proteomics, and technology development in proteomics. Below we provide brief synopses of each paper and encourage you to listen to the full episode to learn more!
Of course, there are many other great examples of proteomics research out there, and we’d love to hear about some of your favorites. Please share your favorite proteomics publications from 2024 in the comments on YouTube or by emailing them to us at translatingproteomics@nautilus.bio and we may feature them in a future episode.
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Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomics
In this work from Professor Bernhard Kuster’s Lab at the Technical University of Munich, researchers assess protein abundance changes that result from treating Jurkat acute T cell leukemia cells with 144 drugs over five drug doses. The researchers use their proteomic data to generate millions of dose response curves for the thousands of proteins measured and discover that the drugs impact many more proteins and pathways than those identified as drug targets. In addition, they checked how 7 of the drug treatments impacted the transcriptome and found there was often discordance between impacts at the mRNA level and the protein level. This works highlights the many ways drugs can impact biological systems and suggests that similar studies will help researchers understand the effects of drug treatments and may even aid in the development of more effective or more specific therapies.
Natural proteome diversity links aneuploidy tolerance to protein turnover
As we discussed on a previous episode of Translating Proteomics, genome alterations often fail to faithfully propagate to the proteome. In this work, researchers from the labs of Professor Judith Berman at Tel Aviv University and Professor Markus Ralser at the Charité – Universitätsmedizin Berlin, investigate the means through which yeast strains adapt to chromosome gains or losses (aneuploidy). They assess the concordance between changes in mRNA and protein expression in aneuploid yeast that were either found in nature or generated in the lab. The researchers observed dosage compensation, a tendency to return to expression levels associated with normal chromosome numbers, for both mRNAs and proteins expressed on aneuploid chromosomes. However, dosage compensation was much stronger at the protein level than the mRNA level and even stronger at the protein level in naturally aneuploid strains compared to lab-generated strains. This work suggests that multiomics efforts are necessary to determine the effects of genomic alterations. In addition, the authors find that protein degradation, as observed through increased ubiquitination, increased turnover of proteins encoded in aneuploid chromosomes, and the up regulation of the proteasome complex, is a key means of dosage compensation. Finally, because the naturally aneuploid strains achieved a higher level of dosage compensation than the lab-generated strains, the authors suggest there has been selection for natural aneuploid strains that down-regulate proteins causing detrimental effects.
Multi-pass, single-molecule nanopore reading of long protein strands
Single-molecule protein sequencing is a long sought after goal of the proteomics field. Nanopore-based sequencers thread single protein molecules through tiny pores imbedded in membranes. Changes in the electrical properties of the pores due to protein threading can theoretically be measured to sequence the threaded proteins. To date, the complex signals coming from full protein molecules cannot be effectively interpreted to determine complete protein sequences. In this work from Professor Jeff Nivala’s lab at the University of Washington, researchers bring the field one step closer to full protein sequencing by showing they can use nanopore-based devices to effectively conduct long reads and identify single amino acid substitutions in repetitive protein sequences with otherwise highly similar readouts. In addition, they develop a method that makes it possible to conduct repeated reads of the same protein molecule and thereby improve read accuracy. They leverage their methodology to show they can design protein barcodes, identify PTMs on otherwise identical protein molecules, and identify traces indicative of particular proteins. While they do not sequence full proteins, these researchers suggest their techniques can be used for proteoform identification and the creation of millions to billions of individually distinguishable barcodes.
Additional exciting work in proteomics in 2024
While not discussed in this podcast, Parag and Andreas also loved the papers listed below. Do you have any favorites that aren’t featured here? Please share them in the comments section on YouTube or email them to us at translatingproteomics@nautilus.bio. We can’t wait to hear from you!
Additional favorites from Parag and Andreas:
- Exploring structural diversity across the protein universe with the Encyclopedia of Domains
- Atlas of the plasma proteome in health and disease in 53,026 adults
- Integrating multiplexed imaging and multiscale modeling identifies tumor phenotype conversion as a critical component of therapeutic T cell efficacy
- Brain-wide alterations revealed by spatial transcriptomics and proteomics in COVID-19 infection
Find this episode on Apple Podcasts, Spotify, or YouTube.
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