Translation

Millions of people die every year from chronic diseases. Traditional drug discovery has failed in identifying solutions to many of these persistent health challenges. Functional genomics is offering a way forward by identifying gene networks and enabling the development of drugs with very specific targets. But, rather than just relying on gene targets within humans, Linda and her company, Fauna Bio, is casting a wider net across the animal kingdom. Extreme adaptation is common across many mammals, giving us an incredible pool of potential targets to go after. Whereas a single heart attack can kill a person, certain animals not only survive 25 heart attacks a year but also go on to thrive, living 2x longer than other mammals their size. By identifying and understanding the gene networks underlying these extreme adaptations, Fauna can identify novel targets across 415 different species, map them to human genes, and develop drugs that exploit our natural protective physiological mechanisms.

The expression of genes in our genome to produce proteins and non-coding RNAs, the building blocks of life, is critical to enable life and human biology. So, the ability to predict how much of a gene is expressed based on that gene’s regulatory DNA, or promoter sequence, would help us both understand gene expression, regulation, and evolution, and would also help us design new, synthetic genes for better cell therapies, gene therapies, and other genomic medicines in bioengineering.

However, the process by which gene transcription is regulated is incredibly complex; thus, prediction transcriptional regulation has been an open problem in the field for over half a century. In his work, Eeshit used neural networks to predict the levels of gene expression based on promoter sequences. Then, he reverse engineered the model to design specific sequences that can elicit desired expression levels. Eeshit’s work developing a sequence-to-expression oracle also provided a framework to model and test theories of gene evolution.

In this very special episode of Translation, Seth is joined by Ash Trotman-Grant to demystify spinning out from academia. Much of this knowledge has so far only been available to select groups of academics and PhD founders are at a disadvantage – some potentially breakthrough technologies never saw the light of day and didn’t get a chance to have a real impact. We want to bring the power of the tech transfer process back to entrepreneurial scientists.

Enter the Spinout Playbook – your complete guide to spinning out of academia. In this episode, we chat about the Playbook’s content and share useful tips for entrepreneurial academics eager to spin out their research into an impactful company. Ash shares his experience from spinning out Notch Therapeutics and, together with Seth, they offer brilliant insights into navigating the (up until now) stormy waters of the spinout process.

Chimeric antigen receptors, or CARs, repurpose the build-in targeting and homing signals of our immune system to direct T cells to find and eliminate cancers. Although CAR-T cells have transformed the care of liquid tumors in the circulating blood, like B cell leukemia and lymphoma, CAR-T therapy has shown limited efficacy against solid tumors. To unlock the full potential of CAR-T therapies, better receptor designs are needed. Unfortunately, the space of potential designs is too large to check one by one. To design better CARs, Dan and his co-author Camillia Azimi developed CAR Pooling, an approach to multiplex CAR designs by testing many at once with different immune costimulatory domains. They select the CARs that exhibit the best anti-tumor response and develop novel CARs that endow the T cells with better anti-tumor properties. Their methods and designs may help us develop therapies for refractory, treatment-resistant cancers, and may enable CAR-T cells to cure infectious diseases, autoimmunity, and beyond.

DNA is an ideal molecule for storing information in our genomes because it’s stable, programmable, and well understood. The same qualities make DNA a great building block or construction material for nanoscale biomolecular structures that have nothing to do with our genome, like molecular scaffolds created by folding DNA into 2D and 3D shapes. This technology is known as DNA origami.

However, the practical applications of DNA origami are limited by spontaneous growth and poor reaction yields. Anastasia developed a method that uses crisscross DNA polymerization of single-stranded DNA slats or DNA origami tiles to assemble DNA structures in a seed-dependent manner. This work may be useful to produce ultrasensitive, next-generation diagnostics or in programmable biofabrication at the multi-micron scale.

Technologies like next-generation sequencing allow us to understand which RNA transcripts and proteins are expressed in biological tissues. However, it’s often equally important to understand how cells or molecules are positioned relative to one another! Whether it be a cell changing its shape, an organelle ramping up a metabolic process, or a DNA molecule traveling across the nucleus, understanding spatial context is critical. Current approaches for spatial sequencing are limited by cost, complicated equipment, sample damage, or low resolution. Recognizing this challenge, Josie and team developed Light-seq, a cheap and accessible method to combine sequencing and imaging in intact biological samples. Not only is the method inexpensive, but Light-seq can also achieve unprecedented spatial resolution by using light to add genetic barcodes to any RNA, allowing scientists to determine exactly where sequencing should occur with extreme precision. By helping researchers to understand spatial context, Light-seq-driven insights may illuminate cancer, neurodegeneration, and autoimmunity.

Antibodies are one of the greatest tools we have in our therapeutic arsenal and have transformed the way we treat cancer and autoimmunity. But we still largely develop these drugs using guess and check methods, massively slowing down the process. However, our own B cells are constantly making new antibodies against the pathogens and diseases we routinely suffer from, creating a gold mine of drugs floating around inside all of us. We just need to find them! Recognizing this challenge, Nima and his team at Avail Bio have leveraged their deep experience in computation and systems immunology to build a platform that massively screens the antibody repertoire of patients who have successfully cleared a disease. With it, they find ready-to-deploy antibody drugs that could treat everything from cancer to autoimmunity and even reprogram our own immune system!

Imagine if every graphics design company built its own version of Photoshop in-house. That’s exactly what’s happening today in biology research. Ten-fold increases in data every two years are forcing every biology team to build out their own, in-house bioinformatics stack to store, clean, pipe, and manage the massive volumes of data generated by their experiments. All that work has to happen even before teams can analyze the results! Recognizing this obstacle to high-throughput biology research, Alfredo, Kenny and Kyle built LatchBio to bring the modern computing stack to biotech. By uniting wet lab experiments with dry lab processing, storage, and analyses, LatchBio is democratizing access to top-notch bioinformatics and empowering biologists to derive relevant insights from their data that can move our world forward. Tune in to learn more about their journey from Berkeley dropouts to entrepreneurs building no-code tools to power the biocomputing revolution.

Evolution is happening even at the cellular scale. Whether it's a virus, a bacterial pathogen, or a cancer cell, disease-causing agents are responding to the therapies we throw at them, updating their genes and molecular pathways to resist death. As a trained microbiologist, Nick Goldner and his co-founder Chris Bulow spent their years in grad school using -omics data to overcome antibiotic resistance in bacteria which led to their first company Viosera. As they struggled with the harsh realities of the antibiotics market, they stumbled upon the connection between bacterial and cancer resistance mechanisms. With this, they started resistanceBio which combines sophisticated tumoroids, intense patient sampling, and multi-omics to mimic the evolution of real tumors and ultimately find therapies that are irresistible.

When COVID-19 hit and society decided to use mRNA vaccines for the first time, many questions remained about whether RNA itself was ready for the challenge. But three scientists at Stanford University who had never worked with each other before the pandemic realized that RNA’s limitations were merely a design challenge and not an issue with the substrate itself. Through emails and zooms, Kathrin, Gun, and Hannah built a tool to massively test RNA designs. With it, they screened for RNA with better functionality, increasing the stability and expression of the protein they encode and ultimately creating a platform to improve these life-saving vaccines.