protein engineering

Season 3, Episode 5: Illuminating Immunity to COVID-19 with Susanna Elledge

First Author: Susanna Elledge

Episode Summary: COVID-19 tests have become synonymous with jamming a swab up our nose to find out whether we have an active infection. But as we progress through this pandemic, a test that tells us whether people have antibodies against the virus will be massively important to creating public health initiatives and deciding who to vaccinate next. Unfortunately, these serology tests are exceedingly tedious to perform, inhibiting their widespread use. Realizing this problem, Susana talks us through how she utilized protein engineering to create a novel serology test that is massively easier and quicker than traditional methods. Importantly, this test can be used in resource low settings to help end the pandemic worldwide.

About the Author

  • Susanna’s scientist parents and love for the natural world drove her to research biology and chemistry.

  • Susanna is most excited about adding new dimensions to biomolecules through bioconjugation to enhance their function.

Key Takeaways

  • A serology test is used to see whether a person has antibodies against a specific pathogen.

  • Positive serology tests can tell us whether getting the disease led to immunity, whether a vaccine worked, or whether a person is protected from new variants.

  • This could be massively useful to help understand who is protected and who to vaccinate next to finally beat the SARS-CoV-2 pandemic.

  • Traditional serology tests use hard to scale and overly laborious methods that hinder their adoption, especially in a low resource setting.

  • Susanna used protein engineering and leveraged the shape of antibodies to develop an entirely new serology test.

  • She engineered protein fusions that when simply mixed with a human sample such as serum or saliva, will generate light if antibodies against COVID-19 are present.

  • This much easier test as well as the variety of human samples it can use as inputs make it a much more approachable option and enables its use in low-resource settings.

Translation

  • Susanna and her colleagues are working to make this test available for field studies by making the protein easier to ship and making a handheld device that can measure the readout.

  • Productizing this test will require more research in how to stabilize the components, incorporate controls, and most importantly, make it high-throughput.

  • Susanna hopes to leverage this technology to help us beat the variants of SARS-CoV-2 and eventually rapidly test for other infectious diseases and autoimmunity.

Paper: Engineering luminescent biosensors for point-of-care SARS-CoV-2 antibody detection

Season 3, Episode 3: Phage Evolved Medicine with Travis Blum

First Author: Travis Blum

Episode Summary: Enzymes that break down other proteins, or proteases, could be used as a powerful therapeutic if they could specifically chew-up disease causing entities. However many proteases are non-specific, breaking any protein in their path, while the specific ones target proteins that would provide no therapeutic benefit. Travis and his colleagues developed a riff on the method known as PANCE that utilizes bacteria and bacterial viruses known as phages to evolve proteins toward a specific goal. With it, he retrains the sequence-specific protease, botulinum neurotoxin, toward new targets and away from its original ones. The novel enzymes Travis generates have the potential to not only stimulate nerve regeneration but also deliver itself to the correct cell types for a whole new type of therapy. 

About the Author

  • Travis is a postdoc who performed this work in the lab of Professor David Liu at Harvard University. The Liu lab is famous for engineering and evolving proteins that can be utilized as massively impactful tools for overcoming diverse diseases.  

  • Travis’s teachers fostered a curiosity that created a passion for chemistry and ultimately led him to engineer new biochemistries. 

Key Takeaways

  • Proteases are enzymes that cut up other proteins.

  • Proteases can either be non-specific, a nuke obliterating any protein in their path,  or sequence-specific, a heat-seeking missile only cutting very specific protein motifs.

  • Sequence-specific proteases that target disease-causing proteins would make great drugs but therapeutically useful proteases rarely exist in nature.

  • Travis focuses on re-engineering the sequence-specific protease known as botulinum neurotoxin so that it cuts an entirely new, therapeutically relevant protein sequence.

  • Using a method called PANCE that utilizes bacteria and bacterial viruses (phages), Travis trains botulinum neurotoxin toward cutting a new target and leaving its original target alone.

Translation

  • Botulinum neurotoxin has a cutting domain that Travis engineered toward a therapeutically relevant target, and a targeting domain that delivers the protein toward neurons.

  • The enzymes generated could be used to cure neural pathologies but the PANCE could also be applied to change which cell type the protease targets, creating a highly programmable therapeutic protease platform.

  • The platform has a ton of interest from industry and Travis is continuing to work on it outside of academia so that these proteases make it to the clinic and impact patient lives.

Paper: Phage-assisted evolution of botulinum neurotoxin proteases with reprogrammed specificity

Season 1, Episode 1: Low-N Protein Engineering with Surge Biswas

First Author: Surojit “Surge” Biswas

Episode Summary

Protein engineering has been dominated by two opposing paradigms; directed evolution, a massive screening technique, and rational design, a completely computational approach. Surge has fused these two paradigms by developing a machine learning technique that discovers an optimal protein design by training on a low number of engineered proteins. Here, Surge discusses how this hybrid method works, how it enabled the creation of better fluorophores and enzymes, and what this method will unlock next.

About the Author

  • Surge performed this work as a graduate student at Harvard in the lab of Professor George Church. George is one of the founding fathers of synthetic biology and the lab is known for developing high throughput methods to design, build, and test bioengineered parts.

  • As CEO and co-founder of Nabla Bio, Surge is now focused on pointing the algorithms and methods developed in his academic work toward building proteins that can improve human health or protect the environment.

Key Takeaways

  • Methods from natural language processing algorithms (like Siri or Alexa) are adapted to understand how nature builds proteins.

  • These machine learning algorithms distill fundamental structural, as well as  evolutionary and and biophysical properties about proteins.

  • Fusing these models with real world data enables us to make proteins with improved or novel functionality.

  • By checking how a few mutations (low-n) affect the function of a protein, Surge evolved proteins in a computer to make better fluorescent proteins and enzymes.

  • These models know a lot about proteins in general and can therefore be applied to a wide variety of tasks that improve human health and protect the environment.

Translation

  • This methodology dramatically reduces the time, cost, and labor of evolving proteins, making it a perfect tool to create commodity proteins.

  • Based on this technology, Surge co-founded Nabla Bio whose goal is to engineer supernatural proteins that enable biology to solve the world's biggest problems.

Paper: Low-N protein engineering with data-efficient deep learning. bioRxiV, 2020