Engineering Life:
Synthetic Biology at National Laboratories

The genetic code is 3.8 billion years old. It took evolution that long to arrive at the cells you have. Scientists at DOE National Laboratories are rewriting it in months.

Synthetic biology — the engineering of living systems from designed DNA sequences — is producing breakthroughs that make the old biotech industry look slow. Microbes engineered to eat plastic. Enzymes designed on a computer that break down cellulose 400 times faster than anything evolution produced. Yeasts that ferment carbon dioxide directly into sustainable aviation fuel.

This is not academic. It's happening now at Argonne, ORNL, LBNL, INL, and PNNL. The DOE has committed over $250 million to synthetic biology programs since 2020. And because this work sits at the intersection of biology, chemistry, data science, and engineering, laboratories are actively looking for exactly the kind of interdisciplinary students reading this newsletter.

What's Happening at the Labs

Joint Genome Institute (LBNL) — The World's Microbial Census

The Joint Genome Institute at Lawrence Berkeley National Lab runs something that sounds impossible: they sequence and annotate more microbial DNA than almost any institution on Earth. The JGI's Community Science Program has sequenced over 350,000 organisms from environments ranging from Yellowstone hot springs to deep ocean sediment — building a library of every natural enzyme, metabolic pathway, and genetic tool that evolution has ever produced.

What students do there: bioinformatics analysis, pipeline development, data annotation, computational biology research. The JGI is one of the few national lab facilities where a biology student with Python skills is an immediate asset.

Career paths: Bioinformatics Scientist, Computational Biologist, Research Associate (Sequencing), Data Scientist (Genomics)

Agile BioFoundry (Multi-Lab DOE Consortium)

The Agile BioFoundry is a DOE consortium spanning Argonne, LBNL, NREL, ORNL, PNNL, and Sandia. Its mission: make biological manufacturing of chemicals, fuels, and materials faster, cheaper, and more reliable.

The ABF has automated DNA assembly, high-throughput cell culturing, and machine learning-guided design in a single workflow. A student working here isn't pipetting in isolation — they're part of a "build-test-learn" cycle where AI models predict which genetic constructs to test next, robotic platforms build them, and automated screening reads the results overnight.

Current priorities: engineering yeast and bacteria to produce drop-in biofuels from CO₂ and agricultural waste; building microbes that capture nitrogen without synthetic fertilizers; designing enzymes that degrade plastics in days instead of centuries.

Career paths: Metabolic Engineer, Bioprocess Engineer, Automation Scientist, ML/Bio Integration Researcher

ORNL Biosciences Division — Carbon to Carbon

Oak Ridge National Lab's Biosciences Division works on the most important carbon cycle problem of our time: can we use biology to capture atmospheric CO₂ at scale?

ORNL has redesigned the enzyme RuBisCO — responsible for almost all photosynthesis on Earth, and notoriously inefficient — producing variants that capture carbon up to twice as fast in certain conditions. They've also developed engineered poplar trees with modified lignin, reducing lignin content by 40% without harming the plant, making it dramatically easier to convert into biofuel.

Career paths: Plant Biologist, Biochemist, Structural Biologist, Computational Biologist, Chemical Engineer (bioprocessing)

Idaho National Laboratory — Bugs That Clean Up Messes

INL applies synthetic biology to a problem unique among national labs: nuclear and industrial waste remediation. INL researchers engineer microorganisms that survive in high-radiation, high-chemical-stress environments and perform metabolic work no other organism could.

One active program: developing bacteria that reduce soluble uranium (U⁶⁺, which moves freely through groundwater) into insoluble uranium (U⁴⁺, which stays locked in place). This has been demonstrated at the bench and is moving toward field deployment at former DOE waste sites. INL also runs programs in bioenergy from agricultural waste and algae-based CO₂ capture systems for integration with next-generation nuclear plants.

Career paths: Environmental Microbiologist, Biogeochemist, Research Scientist (Bioremediation), Chemical Engineer

Argonne's Center for Molecular Engineering — AI-Designed Proteins

Argonne's Center for Molecular Engineering is where synthetic biology meets AI at the deepest level. Researchers use AlphaFold, diffusion models, and custom ML architectures to design proteins that have never existed in nature — then use Argonne's Advanced Photon Source (APS) to verify their 3D structure experimentally.

The practical applications are broad: new catalysts for clean chemistry, biosensors for environmental monitoring, therapeutic proteins. One recent project: designing an enzyme that breaks down PFAS ("forever chemicals") — a molecule that evolution has never encountered and therefore has no natural solution for.

Career paths: Structural Biologist, Protein Engineer, Computational Chemist, Research Scientist (ML for Biology)

The Core Skill Stack

How to Get In

SULI and CCI are your direct pathways. The JGI at LBNL, ORNL Biosciences, INL Biological Systems, and Argonne's Center for Molecular Engineering all take student researchers through these programs. You don't need to be a PhD student — undergraduate and community college students do meaningful work in these facilities.

For biology students: prioritize Python and basic bioinformatics. For data science students: prioritize understanding the biology domain alongside your quantitative skills. The most competitive applicants are genuinely interdisciplinary.

What to include in your application:

• Any bioinformatics coursework or self-study — even working through a NCBI tutorial demonstrates initiative
• Python experience, especially with data analysis libraries (pandas, NumPy, matplotlib)
• A clear statement about which program's work interests you and why — "I want to work on JGI's metagenomic pipeline" is better than "I'm interested in biology"
• For wet lab positions: any laboratory coursework (even general chemistry lab) demonstrates familiarity with lab protocols

The genetic code took 3.8 billion years to write. The labs are now editing it. The students who get into this field now will help define what biological manufacturing looks like in 2040. The door is open — through SULI, through CCI, through NSF REU programs at universities doing related work. You don't need to wait for a PhD to start.

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Resources to Go Deeper

• DOE SULI Applications — For undergraduates. Target: LBNL JGI, ORNL Biosciences, INL Biological Systems, Argonne CME.
• DOE CCI Applications — For community college students with biology, chemistry, or data science backgrounds.
• JGI IMG Database — The Integrated Microbial Genomes database. Free to access — exploring it shows genuine interest in the field.
• AlphaFold Database — Protein structure predictions for virtually every known protein. Understanding how to use and interpret this database is increasingly a baseline skill.
• NCBI SRA — Sequence Read Archive. Primary repository for raw sequencing data — where bioinformatics projects start.