Ginkgo Bioworks

This week, we’re launching E. coli Protein Expression, Purification & Quantification on Ginkgo’s Cloud Lab! We express and purify His-tagged proteins in E. coli. You get back quantification data using A280-based yield measurements and a purity readout using LabChip (capillary electrophoresis). Submit your protein designs here: cloud.ginkgo.bio/protocols/ecol…

Ever wish there was an @amazon Prime for designing antibodies and ordering data? Ginkgo partnered with @awscloud on the Amazon Bio Discovery Platform to do just that. Try it here: hubs.la/Q04ht_zs0

The Reconfigurable Automation Cart (RAC) is the quintessential unit of the autonomous lab. Dan Curhan, a Senior Mechatronics Engineer at Ginkgo, walks you through how these robots combine and recombine to run simultaneous experiments from a lab's worth of scientists. See Nebula, our autonomous lab in Boston, by booking a tour: hubs.la/Q04hhGjb0

Ginkgo Datapoints' own Rich Cohen sat down with the Helical Brew podcast to talk about what actually scales in biotech — and what doesn't. Spider silk, antibody AI, pharma data sharing, and why de novo drug design is still more hype than reality. Watch the full episode → hubs.la/Q04h6Y2z0

A new @statnews profile on Ginkgo and @jrkelly is today’s most-read story. His thesis on the competition between US and China biotech that’s reshaping the present and future of the industry 👇 “‘The ugly secret in biotech is that all the startups are moving to China,’ Kelly said on a walk through the buzzing shop floor of Ginkgo’s robot-staffed lab, which the company says is the largest in the world. ‘We need to embrace autonomy. We can’t compete on hands pipetting with China.’” Autonomous labs are the path forward to close this gap. More in the special report by @damiangarde: statnews.com/2026/05/18/bio…

Great article in @statnews by @damiangarde today covering schism in the biotech industry over the rise of Chinese biotech industry - notably no one will go on record but me😛 The US can easily stop the Chinese biotech industry whenever it chooses as the US consumer is responsible for 70% (!!!) of the drug industry profits. Thus the US gets to set the rules. It is a mistake to outsource this industry -- very simply: the technology of genetic engineering is a matter of national security and democracies should lead it. We would not feel good if the US wasn't leading AI today and trust me we will feel even worse if we are behind in genetic engineering in the future as the tech improves. If you talk to people privately in biotech they will say it's a Prisoner's dilemma where they wish the rules would change. If the rules stay as they are then to stay competitive venture capitalists need to move their $ to China and pharma companies need to buy their drug assets from Chinese startups instead of from startups in Kendall Square or South San Francisco (the current US hubs for drug discovery). To fix this we should take two approaches: (1) Offensive - make US biotech industry more competitive! * Reform phase 1 clinical trails in US to be as fast as China and Australia -- this is in progress now at @US_FDA . @DrSynbio congressional testimony on this was very helpful. (link below). * Replace manual laboratories with autonomous robotic laboratories via programs like NSF Cloud Labs program and @SenToddYoung 's Cloud Lab Bill so US scientists can compete with lower-cost scientific labor in China. Yes, @ginkgo is the leader in making this tech. Efforts from @WHOSTP44. @dariogila, @mkratsios47, @sriramk with the WH Genesis Mission are a big help here. * Fix our approach to biotech patents -- it is very easy for Chinese startups to fast-follow US companies that have scientific breakthroughs by easily working around patents, @john_evans3 has led in thinking here. (2) Defensive - slow the rise of the biotechnology industry in China * USG should add biotechnology to the COINS Act list of strategic technologies alongside AI, Quantum, Semiconductors, and Drones to prevent US investment from speeding Chinese development. * Other tools can be used in the future to easily penalize drug assets that originate from startups in China -- can do via regulatory pathway or via Medicare reimbursement. Genetic engineering is the most important technology to the future of humanity. Democracies should not give up on it! Let's fight for it!

Is it possible to manufacture medicines using the natural biological machinery found in a grain of wheat? Last year, @ARPA_H selected a team led by Ginkgo to find out. To kick off Year 2 of this project, called WHEAT (Wheat-Based High-efficiency Enzyme and API Technology), we hosted ARPA-H to update them on our progress and show them Nebula, our autonomous lab. Ginkgo Scientist Jama Hadji-Yusuf and CEO @jrkelly walked ARPA-H Portfolio Lead Captain James Coburn through the software that powers Nebula, called Catalyst. We don’t just have an autonomous lab. We’re running some of the coolest science in the world on top of it to solve some of the world’s biggest problems. We’re honored to work with ARPA-H and work towards using biology to support the public good. Book a tour of the autonomous lab: hubs.la/Q04gYT-s0

This week, the Cloud Lab is launching E. coli Protein Expression with His-tag Purification and Yield via A280. This protocol enables rapid, data-driven assessment of protein expressibility before you commit to larger-scale expression campaigns. Send us your AA or DNA templates and let Nebula express and purify His-tagged proteins. Protein yield is measured from the eluate via absorbance at 280 nm on the BMG PHERAstar You can expect the following outputs: Yield Quantification: Absorbance measurement at 280 nm reported per well, converted to protein concentration (mg/mL) using the protein's molar extinction coefficient Expression Confirmation: Fluorescence signal measurement to confirm construct expression relative to controls Assay Quality Metrics: Per-run quality summary including plate-level controls to ensure data reliability cloud.ginkgo.bio/protocols/ecol…

This week, the Cloud Lab is launching E. coli Protein Expression with His-tag Purification and Yield via A280. This protocol enables rapid, data-driven assessment of protein expressibility before you commit to larger-scale expression campaigns. Send us your AA or DNA templates and let Nebula express and purify His-tagged proteins. Protein yield is measured from the eluate via absorbance at 280 nm on the BMG PHERAstar You can expect the following outputs: Yield Quantification: Absorbance measurement at 280 nm reported per well, converted to protein concentration (mg/mL) using the protein's molar extinction coefficient Expression Confirmation: Fluorescence signal measurement to confirm construct expression relative to controls Assay Quality Metrics: Per-run quality summary including plate-level controls to ensure data reliability Get started here: hubs.la/Q04gP9x60

Oh hello 105 RACs 😍😍😍 Excited to get these booted up this week. Come check em out tonight at our happy hour!👇🍻🤖

Keith Robison (@OmicsOmicsBlog) is a computational biologist who has been writing about biology for decades. 35 years ago, Keith chose computational biology because he wasn't good in the lab. Today, he's using Nebula to get back in the lab. Join Keith for this series as he creates and debugs his first protocol on Nebula. Read Keith's writing: hubs.la/Q04gpmbR0 Try our cloud lab for as little as $39: hubs.la/Q04gppG80

Scientists are getting their own “Waymo” moment — autonomous labs that take the wheel so researchers can focus on the big ideas. @PharmaTechFocus interviewed @jrkelly on how our autonomous lab enables researchers to design, run, and iterate experiments at a scale and speed that manual science can't match. Read the full Q&A by @Frankie_GD_PT: hubs.la/Q04grlgW0

Ginkgo Bioworks has the largest autonomous lab in the world.

We had our Q1 2026 Earnings call last night. We shared our latest numbers and Jason gave a big update: we now have (over) 100 robots at our autonomous lab in Boston. Catch the full call here: hubs.ly/Q04fYW930

Today, we're launching a new Cloud Lab protocol: E. coli Protein Expression with HiBiT Quantification. This fully automated, end-to-end workflow takes your protein designs from sequence to quantified expression data using the Promega Corporation Nano-Glo® HiBiT Lytic Detection System for detection. Get a quantitative comparison of HiBiT-tagged protein expression across up to 384 constructs per run! As with all of our cloud lab protocols, we offer transparent pricing and visibility into each step and instrument used to run your sequences and deliver the following data outputs: 🧪 OD600 Growth Confirmation: Per-well absorbance readings confirming bacterial growth prior to pelleting. 💡 HiBiT Luminescence Values: Raw bcRLU per well from BMG PHERAstar luminescence reads. 📈 Normalized Expression Estimate: Per-construct expression levels normalized to an on-plate HiBiT standard curve. 📋 QC Report: PDF with per-construct results, process control outcomes, and pass/fail status; raw CSV available for download. Try it out here! cloud.ginkgo.bio/protocols/ecol…

Join us today on @YouTube for our Q1 2026 Update & Business Review call at 4:30pm Eastern here: youtube.com/live/gsPw85PfS… If you'd like your question answered during our Q&A, please tag your X post with #GinkgoResults or e-mail our investor inbox (investors@)!

Catch up on the weekend’s @TheTimes feature on Ginkgo and how AI and cloud labs are accelerating the pace of scientific discovery. In the story, @jrkelly shares what Ginkgo’s autonomous lab Nebula has achieved with @OpenAI’s models, the future of AI-driven science, and his reality check on biosafety risks. Read the full feature by @dannyforston: hubs.la/Q04fgvNy0 Use our Cloud Lab today: hubs.la/Q04fgBnh0