Episódios
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On this special, year-end episode of Translating Proteomics, hosts Parag Mallick and Andreas Huhmer discuss three of their favorite proteomics publications from 2024. They'll cover one paper in each of the following topic areas:
Proteomics in pre-clinical researchProteomics in basic researchTechnology development in proteomicsSynopses of each of the papers can be found below and you can find many more insights in the podcast.
Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomicsIn 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.
Find the publication here.
Natural proteome diversity links aneuploidy tolerance to protein turnoverAs 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.
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Parag Mallick discusses the role of AI and machine learning in biotech with special guests Vijay Pande from Andreessen Horowitz and Matt McIlwain from Madrona Venture Group. Their fascinating conversation covers:
Advances that have enabled biotech to make use of AI and machine learningHow founders are applying AI and machine learning in biotechThe future of AI and machine learning in biotechChapters
00:00 - Introduction
04:37 - How did Vijay and Matt get into AI and ML
07:33 - The importance of structured data, advances in compute, and algorithmic advances in driving the boom in machine learning
18:44 - The Intersection of AI and biology
21:57 - The evolution of biological models
31:55 - The Complexity of biological data
39:42 - Ways founders and biotech startups are using AI
43:25 - Favorite/Impactful applications of AI/ML
47:00 - AI for experimental design
50:13 - The future of AI in bio/health
Resources
Learn more about Matt McIlwainLearn more about Vijay PandeFolding at HomeLearn about various types of machine learning on IBM's websiteLearn about autoencoders on IBM's websiteLearn more about transformers on NVIDIA's blogTranslating Proteomics Episode 6 - The Future of AI in Biomedicine
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On this episode of Translating Proteomics, host Andreas Huhmer discusses advances in Alzheimer’s research with special guest and Curie Bio Drug Maker in Residence, Sarah DeVos Ph.D. Their conversation focuses on:
The impact of molecular diagnostics on Alzheimer’s researchRecent Alzheimer’s drug approvalsThe future of Alzheimer’s research*Small edit on Sarah's background - She did her graduate work at Washington University in St. Louis and a Postdoc at Massachusetts General Hospital*
Chapters00:00 – Introduction
01:54 – Why Sarah began studying Alzheimer’s
03:39 – Current tools and needs for future Alzheimer’s diagnostics
09:52 – Recent drug approvals in the Alzheimer’s space and their relationship to diagnostics
14:26 – Is it possible to develop biomarkers that detect Alzheimer’s at its earliest stages?
16:36 – What is limiting the development of new Alzheimer’s biomarkers?
17:51 – The DIAN trials and learnings from studying dominantly inherited Alzheimer’s
19:33 – The genetics of Alzheimer’s
22:19 – Novel approaches to identifying and understanding Alzheimer’s pathology
25:54 – Where can proteomics advance Alzheimer’s research?
31:25 – The role of proteomics in Alzheimer’s animal models
34:33 – Sarah’s hopes for the next 10 years of Alzheimer’s research
41:39 - Outro
ResourcesDominant Inherited Alzheimer’s Network (DIAN) trials research updates
o In the DIAN trials, researchers work with families to study various clinical and basic science aspects of dominantly inherited Alzheimer’s disease.
Amyloid plaque reducing clinical trials:
o Two Randomized Phase 3 Studies of Aducanumab in Early Alzheimer's Disease (Haeberlein et al. 2022)
o Donanemab in Early Symptomatic Alzheimer Disease - The TRAILBLAZER-ALZ 2 Randomized Clinical Trial (Sims et al. 2023)
o Lecanemab in Early Alzheimer’s Disease (Van Duck et al. 2022)
Blood Biomarkers to Detect Alzheimer Disease in Primary Care and Secondary Car (Palmqvist et al. 2024)
o Clinical research into a new phospo-tau biomarker that can help physicians more effectively diagnose Alzheimer’s disease
Resurrecting the Mysteries of Big Tau (Fischer and Baas 2021)
o Review covering a potentially neuro-protective form of tau called “Big tau”
Integrated Proteomics to Understand the Role of Neuritin (NRN1) as a Mediator of Cognitive Resilience...
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
On this episode of Translating Proteomics, hosts Parag Mallick and Andreas Huhmer of Nautilus Biotechnology discuss the challenges and opportunities of plasma proteomics. Their conversation focuses on:
· Why blood plasma may be a good source of protein biomarkers
· Current methodologies and pitfalls in plasma proteomics
· The path forward for plasma proteomics
What is Plasma Proteomics?For those who are new to this topic, plasma is the liquid portion of the blood distinct from fractions containing red and white blood cells. Given the relatively non-invasive ways physicians can collect patient plasma, and the blood’s intimate association with tissues throughout the body, plasma is potentially an excellent source of protein biomarkers. Yet, it is quite difficult to measure the levels of all plasma proteins because their concentrations span over 12 orders of magnitude. This episode features an in-depth discussion of the ways plasma proteomics efforts have and have not lived up to the promise of biomarker discovery and what we can do to advance plasma biomarker discovery efforts in the future.
Chapters00:00 – 01:01 – Intro
01:02 – 4:55 – What is the promise of plasma proteomics?
04:55 – 07:23 – Is the plasma proteome really the best source of biomarkers?
07:23 – 10:16 – How do proteins get into the blood and what are the implications for biomarker discovery?
10:16 – 13:59 – Is it clear that proteins are the best candidates for blood biomarkers?
13:59 – 19:57 – Advances in and the future of comprehensive plasma proteomics
19:57 – 22:31 – Pros and cons of fractionating the plasma proteome to discover biomarkers
22:31 – 28:14 – Progress in identifying multiomic plasma biomarkers and the path forward
28:14 – End – Outro
ResourcesNano-omics: nanotechnology-based multidimensional harvesting of the blood-circulating cancerome (Gardner et al. 2022)
o Review from focused on the development multiomics liquid biopsies
Multicompartment modeling of protein shedding kinetics during vascularized tumor growth (Machiraju et al. 2020)
o Work from Parag’s Lab investigating tumor protein shedding
Simulation of the Protein-Shedding Kinetics of a Fully Vascularized Tumor (Frieboes et al. 2015)
o Tumor protein shedding work from Parag’s Lab
Mathematical model identifies blood biomarker-based early cancer detection strategies and limitations (Hori and Gambhir et al. 2011)
o Study modeling how much protein could be shed and detected from different size tumors
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
Proteins adopt a wide variety of functions depending upon factors like their location in the cell, their modifications, and the biomolecules they interact with. While many of us may have been taught that single genes produce single proteins that have single functions, protein function is far more dynamic than that. In this episode of Translating Proteomics, Nautilus Co-Founder and Chief Scientist Parag Mallick sits down with University of Cambridge Professor and proteomics expert Kathryn Lilley to discuss our evolving understanding of protein function. They cover:
How they came to realize protein function is more complex than one gene, one enzyme, one functionFactors that give rise to the dynamic complexity of protein function including proteoforms, protein localization, and moonlightingSteps we can take to better understand and teach others about the complexities of protein function
Research diving into the complexities of protein functionResearch from the Beltrao Lab using bioinformatics techniques to identify functional phosphosites (Ochoa et al. 2020)Work from the Lilley Lab integrating techniques to investigate ome-wide localization of both RNA and protein (Villanueva et al. 2024)Lilley Lab preprint investigated protein localization changes in a cancer cell line as a result of ionizing radiation treatment (Christopher et al. 2024).Collaborative work with the Lundberg Lab mapping subcellular proteomics (Thul et al. 2017).
Additional protein function resourcesMoonProt - A database for moonlight proteins from Professor Constance Jeffrey's LabTranslating Proteomics Episode 5 - Why the Biology Surrounding Biology's Central Dogma is Wrong
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
In our Translating Proteomics episode titled "Harnessing Proteoforms to Understand Life's Complexity", Parag and Andreas discussed why proteoforms are important in a theoretical sense. In this episode, Parag sits down with Northwestern University Professor and proteoform pioneer, Neil Kelleher to dive deep into the biology of proteoforms. They cover:
What proteoforms areExamples of the importance of proteoformsThe scale of and technological advances needed to meet the challenges of proteoform biology.
Some examples of the power of proteoforms covered in this episodeRecent work from Neil's lab showing blood proteoforms can help predict liver transplant success (Melani et al. 2022).Work form Ying Ge's lab showing changes in troponin proteoforms correlate with varying degrees of heart disease (Zhang et al. 2011).The BioTyper - a mass spectrometry-based device that can identify different kinds of microbes.
Additional proteoform resourcesThe Human Proteoform Atlas webpagePublication describing The Human Proteoform Atlas (Hollas et al. 2022)Publication discussing how many human proteoforms there are (Aebersold et al. 2018)Animation - Proteoform Analysis on the Nautilus Proteome Analysis Platform
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
Despite incredible leaps in our understanding of molecular biology, the majority of drug development efforts still fail, and those that succeed often fail to return investment dollars. Proteomics has the potential to change that by providing high-resolution views of the biochemical drivers of biological function - proteins. In this episode of Translating Proteomics, Parag and Andreas discuss how proteomics can help researchers identify good drug targets, personalize drug development, and advance precision medicine.
Chapters:
00:00 - How do we define good drug targets and "druggable" in the age of proteomics
08:16 - Advancing personalized medicine through proteomics
10:58 - How proteomics technologies have changed drug development
15:13 - New abilities next-generation proteomics technologies give us in drug development
Learn about proteomics and biomarker discovery:
https://youtu.be/8rcAxHSRGYs?si=kZ0UX42TJ8tWIaSN
Learn more about proteomics and precision medicine:
https://youtu.be/bzRlM45agBY?si=eop2XcGLc_oLeiVc
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
Proteins are far more than just the output of genes. They can be modified in myriad ways to produce millions of proteoforms with altered dynamics, localization, and function. For a comprehensive understanding of biology that will propel drug development and biomarker discovery forward, we need to be able to measure proteoforms routinely. In this episode, Parag and Andreas discuss the incredible value that will come from studying proteoforms and describe what it will take to make proteoform measurement a routine part of biology research.
Chapters:
00:00 - Introduction to proteoforms
09:38 - Evidence that proteoforms are important and how we can use proteoform data
19:28 - Technology advances needed to understand proteoform biology
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
AI might be the biggest buzz word of the decade, but the buzz is warranted in terms of its practical potential in biological research. In this episode of Translating Proteomics, Parag and Andreas discuss some of the early wins for AI in biology, practical ways AI can be applied to biology research in the near term, challenges in that application, and how proteomics researchers in particular can use AI to advance their work.
Chapters:
00:00 – Why now is the time to apply AI to biomedicine05:28 – Difficulties and potential solutions when applying AI to biology14:20 – How AI will impact the study of proteins19:34 – Risks of AI in biomedicine
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
From high school biology on up, we're taught the central dogma of biology - that biological information flows from DNA to RNA to proteins. This representation of the central dogma is, however, very much a simplification of its original formulation by Francis Crick and over-applying it can lead us down spurious paths and faulty conclusions. In this episode of Translating Proteomics, Parag and Andreas dive into the real meaning of the central dogma and discuss how modern biology research, including proteomics, shows we must drastically alter the ways we use and interpret the central dogma.
Chapters:
00:00 – What is the central dogma and how is it misinterpreted?
08:06 – Regulation and control in biology
11:58 – The need for new models in biology
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
Protein biomarkers are proteins measured as indicators of biological processes. People often hope biomarkers will take the form of elevated or decreased amounts of single proteins, but few single protein measurements provide specific and sensitive indications of biological processes. In this episode of Translating Proteomics, Parag and Andreas discuss why it is difficult to find new biomarkers and describe how new techniques can enable the development of multi-protein, multi-time point, and even multiomic biomarkers that have more potential than any single protein measurement.
Some key points of discussion:
Biomarkers are difficult to find because of the methods we use to find them and because there is a ton of variability in natural biological systemsMost proteins are biomarkersWe need more proteome-scale data over space and time to find new biomarkersLearn more about biomarkers.
Let us know what you think about the podcast.
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
It's no surprise that biological systems change dramatically over space and time, but we often ignore these dynamics when comparing biological samples. In the latest episode of Translating Proteomics, Parag and Andreas discuss why it's essential to take space and time into account and envision ways we can design experiments that explicitly incorporate spacial and temporal considerations.
Chapters:
00:00 - Biological systems as dynamic, adaptive systems
04:45 - How current experimental designs rarely take space and time into account
11:54 - The tools necessary to sufficiently measure biology in space and time
Some key takeaways from the conversation:
Different biological processes occur at very different time scalesComplex, multiomic interactions can only be understood over time and spaceWe need to properly collect, annotate, and share omics-level data in order to understand the rules that govern complex biologyLet us know what you think about the podcast.
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
Sure, proteomics may revolutionize precision medicine and biomarker discovery, but did you know it can help make better cheese? Listen to the latest episode of our new series, "Translating Proteomics" featuring Nautilus Co-Founder and Chief Scientist, Parag Mallick, and Nautilus Senior Director of Scientific Affairs and Alliance Management, Andreas Huhmer to learn the many ways we can put the proteome to work as the proteomics revolution begins to bear fruit.
Let us know what you think about the podcast.
Learn more about applications of proteomics
In this episode, Parag mentions work from Matthias Selbach's Lab. Learn more about the Selbach Lab here.
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Do you have a question you'd like answered on a future episode of Translating Proteomics? Send it to [email protected]!
The idea to measure the proteome to get a clear understanding of healthy and diseased tissues at the molecular level has been around for many years but has not come to fruition in a broadly accessible and applicable way. In this episode we discuss:
Why now is the time to make this goal a realityWhy past efforts to broadly leverage proteomics did not work outWhat we've learned from the pastWhat's changed in proteomics and science in general that makes a proteomics breakthrough possibleLearn more about proteomics
Let us know what you think about the podcast.
