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

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 systems
• Most proteins are biomarkers
• We need more proteome-scale data over space and time to find new biomarkers

Learn more about biomarkers.

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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 scales
• Complex, multiomic interactions can only be understood over time and space
• We need to properly collect, annotate, and share omics-level data in order to understand the rules that govern complex biology

Let us know what you think about the podcast.