Spatial Proteomics with Fiona Ginty Ph.D.

On this episode of Translating Proteomics, host Parag Mallick discusses spatial proteomics with special guest Fiona Ginty Ph.D. Fiona is a Senior Principal Scientist in Precision Diagnostics at the GE Healthcare Technology & Innovation Center. She is a leader in the development of spatial proteomics technologies and their application in precision diagnostics and medicine.Their discussion covers:·      How Fiona began working in spatial proteomics·      Why spatial biology is important·      What the future holds for spatial biologyChapters:00:00 – Introduction01:54 – Fiona’s journey to biology05:26 – Fiona’s transition to tool development07:20 – Working at GE Research11:26 – Identifying the importance of spatial biology14:43 – How Cell DIVETM works18:25 – The importance of single cell23:01 - When Fiona realized the technology worked28:04 – Spatial biology projects Fiona is excited about30:08 – Fiona’s role in HuBMAP36:50 – Learnings from HuBMAP so far38:35 – The future of spatial proteomics in the clinic46:56 – Current limits on spatial proteomics49:56 – Current and future uses of AI in spatial proteomics53:30 – The most exciting thing Fiona learned in her spatial proteomics journey56:08 – OutroResources:Method of the Year 2024: Spatial ProteomicsPaper covering the spatial proteomics technology Fiona worked on at GE HealthcareHighly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissueHubMAP – Human BioMolecular Atlas ProgramHuman Tumor Atlas NetworkCell DIVE Multiplex Imaging SolutionPapers discussing what makes colorectal cancer cells undergo apoptosis in response to chemotherapyAn atlas of inter- and intra-tumor heterogeneity of apoptosis competency in colorectal cancer tissue at single-cell resolutionIntegrated multiplex analysis of cell death regulators in stage II colorectal cancer suggests patients with ‘persister’ cell profiles fail to benefit from adjuvant chemotherapyPaper discussing how the distance between tumor cells and cytotoxic t-cells correlates to caspase levelSpatial effects of infiltrating T cells on neighbouring cancer cells and prognosis in stage III CRC patients - Azimi - 2024 - The Journal of Pathology - Wiley Online LibraryPaper showing it takes 3 hits from cytotoxic...

On this special episode of Translating Proteomics, Parag and Andreas break down the basics of proteomics — perfect for anyone with a background in molecular biology looking to get started in the field.Seasoned experts: We hope you can share this episode as a teaching tool or to inspire others to explore proteomics.Parag and Andreas cover the following questions in the episode, and links to additional Nautilus resources can be found below each question.What is proteomics?Blog post –&nbsp;What is proteomics? Techniques, applications, and methodsWhat are key questions proteomics can answer?Blog category –&nbsp;Applications of proteomicsWhy is it important to measure the proteome?FAQ on the&nbsp;Nautilus Resources pageBlog post –&nbsp;Genomics vs. proteomics: Two complementary perspectives on lifeWhat can and can't you do with proteomics?Translating Proteomics episode –&nbsp;Plasma Proteomics: The Dream and the NightmareLearn how the Nautilus Platform is designed to enable comprehensive&nbsp;broadscale proteomics&nbsp;and&nbsp;targeted proteoform studiesWhat are key proteomics methods and techniques?Blog series –&nbsp;Traditional protein analysis methodsBlog series –&nbsp;Next-generation proteomics technologiesWhat are the major pitfalls when doing proteomics?What are the challenges in proteomic data analysis?Translating Proteomics episode –&nbsp;Biology in Space and TimeBlog post –&nbsp;What is multiomics?What are people excited about in proteomics?Translating Proteomics episode –&nbsp;Poised for a Proteomics BreakthroughTranslating Proteomics episode -&nbsp;US HUPO 2025 – Key Takeaways, Trends, and Future Directions for ProteomicsTranslating Proteomics episode –&nbsp;<a href="https://www.nautilus.bio/blog/translating-proteomics-episode-10-protein-function-201-with-kathryn-lilley/" rel="noopener noreferrer"...

If you listened to our episode focused on science communication featuring proteomics leaders Ben Orsburn Ph.D. and Ben Neely Ph.D., then you've already heard about their excellent podcast, The Proteomics Show. On The Proteomics Show, they interview researchers in the proteomics community to learn about their motivations, their backstories, and their work. Today, we're sharing an episode of The Proteomics Show where the Bens interview Translating Proteomics host Parag Mallick. Check it out to learn about Parag's journey to proteomics, his efforts advocating for open data sharing, and his work as a professional magician.After listening, be sure to check out more episodes of The Proteomics Show on their feed where you'll find over 70 interviews with many, many interesting people in the proteomics community. Find their feed here:https://us-hupo.org/Podcasts

On this episode of Translating Proteomics, hosts Parag Mallick and Andreas Huhmer discuss their recent experience at the 2025 US Human Proteome Organization conference or US HUPO. Their conversation covers:·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;The rising use of multiple proteomics platforms·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Advances in multiomicsAnd·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;What they hope to see at the next US HUPOChapters:00:00 – Introduction01:47 – Things Parag and Andreas were most excited about going into US HUPO06:19 - Trends Parag observed at US HUPO·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;A bifurcation between studies that focused on measuring&nbsp;many&nbsp;proteins and those that focused on a specific biological process·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;People increasingly using multiomics to wholistically understanding biology as opposed to a means of comparing the different omes·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;A shift to researchers using multiple proteomics platforms11:44 – The rising prominence of proteoforms at US HUPO15:50 – The future of proteomics as informed by US HUPO18:06 – What Parag and Andreas hope to see at the next US HUPO19:57 - Outro

On this episode of Translating Proteomics, host Parag Mallick speaks with special guests doctors Ben Neely and Ben Orsburn, leaders in the proteomics community and hosts of “The Proteomics Show” podcast. Their insightful conversation focuses on the role of communication in proteomics and covers:·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Impactful things they’ve learned while hosting The Proteomics Show·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;How their communication efforts have changed their research·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Barriers to proteomics becoming more popular in the life sciences and in the broader publicChapters:00:00 – 03:04 – Intro03:04 – 07:23 – Why the Bens created "The Proteomics Show"07:23 – 10:42 – Ways the proteomics show has impacted the Bens’ research10:42 – 16:44 – Every scientist is interesting!16:44 – 20:36 – Ways the Bens' communication efforts have changed their research20:36 – 25:08 – Trends in proteomics25:08 – 35:34 – Barriers to communication between the proteomics community and others in the life science34:34-48:34 - Barriers to communication between the proteomics community and the broader public48:34 - End - OutroResourcesThe Proteomics Show - Ben Neely and Ben Orsburn host this podcast sponsored by the Human Proteomics Organization. On it, they interview proteomics researchers in a “fireside chat” format. Their conversations cover not just the latest research, but also their guests’ motivations, hobbies, and histories. Definitely check it out!News in Proteomics Research - Ben Orsburn's blog on the latest developments in proteomics.Proteomics, the next truly massive investment opportunity - Forbes article on the potential of proteomics.The Magic School Bus Rides Again - Recently rebooted version of The Magic School Bus. Will we see an episode featuring proteomics?

On this episode of Translating Proteomics, hosts Parag Mallick and Andreas Huhmer discuss the many ways proteomics can impact our interactions with food. Some of the topics they touch upon in this wide-ranging conversation include:·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Proteomics and food quality·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Proteomics and food safety·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Developing new kinds of food with proteomicsChapters00:00 – 01:23 – Introduction01:23 – 03:27 – Proteomics and alcohol fermentation03:27 – 05:24 – Food properties and their relationship with molecular composition05:24 – 07: 42 – How can we use proteoforms to improve food quality?07:42 – 11:49 – Proteomics to aid plant and animal breeding11:49 – 14:35 – Proteomics, Food Safety, and Food Security14:35 – 17:05 – Proteomics and food authenticity17:05 – 20:36 – Proteomics and terroir20:36 – 22:48 – Proteomics, the microbiome, and health22:48 – 24:29 – A fun party trick24:29 – 30:24 – Creating new foods and flavors30:24 – 34:33 – Designing food for space34:33 – End – OutroResourcesThe post-translational modification landscape of commercial beers (Kerr et al. 2021)·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Paper looking at the ways post-translational modification differ between different beers and how protein content relates to the properties of foamHeat shock and structural proteins associated with meat tenderness in Nellore beef cattle, a Bos indicus breed (Carvalho et al. 2024)·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Paper looking at the relationship between proteins and meat tendernessComprehensive proteome analysis of bread dicphering the allergenic potential of bread wheat, spelt and rye (Zimmermann et al. 2021)·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Research measuring the levels of allergens in different kinds of breadDifferential proteomic analysis by SWATH-MS unravels the most dominant mechanisms underlying yeast adaptation to non-optimal temperatures under anaerobic conditions·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Study using proteomics to reveal how yeast adapt to growth at different temperatures

On this episode of Translating Proteomics, co-hosts Parag Mallick and Andreas Huhmer of Nautilus&nbsp;Biotechnology discuss the reproducibility crisis in biology and specifically focus on how we can enhance reproducibility in computational proteomics. Key topics they cover include:•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;What the reproducibility crisis is•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Factors that make it difficult to replicate multiomics research•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Steps we can take to make biology research more reproducibleChapters&nbsp;00:00 – 01:20 – Introduction01:20– 03:10 – What is reproducibility in research and why is it important?03:10 – 05:42 – Recent work from the Mallick Lab focused on computational proteomics reproducibility05:42 – 09:32 – Ways to help improve reproducibility in computational proteomics – More detailed documentation, moving beyond papers as our main form of documentation, and ensuring computational workflows are available,09:32 – 11:30 – Why Parag got interested reproducibility – Attempts to build AI layers on top of current workflows11:30 – 14:00 – The need to create repositories of analytical workflows codified in a structured way that AI can learn from14:00 – 15:24 – A role for dedicated data curators15:24 – 18:31 – Moving beyond the idea of study endpoints and recognizing data as part of a larger whole18:31 – 21:32 – How does AI fit into the continuous analysis and incorporation of new datasets21:32 – 23:36 – The role of AI in helping researchers design experiments23:36 – 27:25 – Three things we can do today to increase the reproducibility of computational proteomics experiments:·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Be clear about the stated hypothesis·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Document analyses through workflow engines and containerized workflows·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Advocate for support for funding for reproducibility and reproducibility tools27:25 – End – OutroResourcesParag’s Gilbert S. Omenn Computational Proteomics Award Lectureo&nbsp;&nbsp;&nbsp;In this lecture, Parag describes his vision for a more reproducible future in proteomicsNature Special on “Challenges in irreproducible research”o&nbsp;&nbsp;&nbsp;A list of articles and perspective pieces discussing the “reproducibility crisis” in researchWhy Most Published Research Findings Are False (Ioannidis 2005)o&nbsp;&nbsp;&nbsp;Article outlining many of the issues that make it difficult to reproduce research findingsReproducibility Project: Cancer Biologyo&nbsp;&nbsp;&nbsp;eLife initiative investigating reproducibility in preclinical cancer researchCenter for Open Science Preregistration Initiativeo&nbsp;&nbsp;&nbsp;Resources for preregistering a hypothesis as part of a studyNational Institute of Standards and Technology (NIST)o&nbsp;&nbsp;&nbsp;US government agency that aims to...

On this episode of Translating Proteomics, co-hosts Parag Mallick and Andreas Huhmer of Nautilus Biotechnology discuss how clinical researchers can leverage proteomics for drug development. Some of the themes covered in this episode include:·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Proteomics and pre-clinical models·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;How proteomics can drive patient selection·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Choosing the right end points in clinical trialsChapters00:00 – 01:06 – Introduction01:06 – 06:51 – Proteomics in pre-clinical studies06:51 – 11:40 – The importance of choosing the right model for preclinical work11:40 – 17:10 – How proteomics is used in Phase I/II clinical trials17:10 – 19:29 – Proteomics tools in patient selection19:29 – 24:33 – Useful information that we get from proteomics that we can’t get from genomics or transcriptomics24:33 – 28:14 – Proteomics in Phase III clinical trials and picking the best indications of drug efficacy28:14 – 29:19 - Understanding why clinical trials fail29:19 – End - Outro&nbsp;ResourcesThe National Cancer Institute’s webpage covering&nbsp;how clinical trials workPreprint on the miBrain model&nbsp;- An example of a new&nbsp;in vitro&nbsp;brain modelGeary et al., 2021 -&nbsp;Discovery and Evaluation of Protein Biomarkers as a Signature of Wellness in Late-Stage Cancer Patients in Early Phase Clinical TrialsWasko et al., 2024 -&nbsp;Tumour-selective activity of RAS-GTP inhibition in pancreatic cancerThe NCI-MATCH trail: Lessons for precision oncology&nbsp;– Report on a large-scale trial using genomic biomarkers to match cancer patients to treatmentsTumour-selective activity of RAS-GTP inhibition in pancreatic cancer&nbsp;– Study using proteomics to understand mechanisms of resistance to a cancer drug

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&nbsp;this work&nbsp;from&nbsp;Professor Bernhard Kuster’s Lab&nbsp;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&nbsp;previous episode of Translating Proteomics, genome alterations often fail to faithfully propagate to the proteome. In&nbsp;this work, researchers from the labs of&nbsp;Professor Judith Berman&nbsp;at Tel Aviv University and&nbsp;Professor Markus Ralser&nbsp;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.<a...

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 biotechChapters00:00 - Introduction04:37 - How did Vijay and Matt get into AI and ML07:33 - The importance of structured data, advances in compute, and algorithmic advances in driving the boom in machine learning18:44 - The Intersection of AI and biology21:57 - The evolution of biological models31:55 - The Complexity of biological data39:42 - Ways founders and biotech startups are using AI43:25 - Favorite/Impactful applications of AI/ML47:00 - AI for experimental design50:13 - The future of AI in bio/healthResourcesLearn more about Matt McIlwainLearn more about Vijay PandeFolding at HomeLearn about various&nbsp;types of machine learning&nbsp;on IBM's websiteLearn about&nbsp;autoencoders&nbsp;on IBM's websiteLearn more about&nbsp;transformers&nbsp;on NVIDIA's blogTranslating Proteomics Episode 6 - The Future of AI in Biomedicine