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Comment by jrkelly | Hacker News Reader

I'm Jason Kelly, one of the Ginkgo co-founders -- happy to answer questions!

A lot of press is singling out CRISPR as the game changer for Bio industry as a whole.

Is it particularly useful at Ginkgo, and how is it being used / what problem is it solving?

CRISPR makes it easier to edit genomes in a targeted fashion especially in organisms where engineering the genome has traditionally been really hard (plants, mammalian cells). We work in microbes that are a lot easier to engineer out of the gate so it's a little less of a game-changer for us. Still it is amazing technology -- I'm sure we'll make use of it along with most everyone that does biological engineering in the future. Though the synthetic biology crowd is currently poking fun at Wired's over-hyped CRISPR issue, check out #CRISPRfacts

I'm a statistical machine learning specialist who uses graphical models to model signaling and metabolic pathways from 'omics data. Some of it has involved writing domain specific languages for representing biological pathways, and I have seen other people who do that talk to the synthetic biology community. All my PhD research has focused on medical science, but I am hoping after finishing to move from a systems biology focus to a synthetic biology focus, as in designing artificial pathways and engineering them in experiments rather than designing experiments for reverse engineering natural pathways. Does that resonate with your work at Ginkgo? Or does my skill-set have no relevance to synth bio?

Where are the biggest needs for software in synthetic biology today? What type of software do you predict will have the biggest impact in 10 years?

Hi, I am Benjie, and I work on software at Ginkgo. Synthetic biology is a big field; Ginkgo applies synthetic biology to metabolic engineering and we develop software that are somewhat specific to that area.

For example, many people talk about omics data by themselves, but we develop and use tools that allow us to integrate genetic, transcriptomic, proteomic, and metabolomic data with genetic changes, strain culturing conditions, sample prep parameters, and instrument settings. We want the truth.

In 10 years, the biggest impact left by our software efforts will not be any single piece of software, but a set of forward engineering rules, gathered by our existing and future software, that enables true design automation and makes biology a great engineering platform.

Hi Jason, can I ask what a "designer organism" is? Is this just a more marketing-friendly term for a GMO?

Sure. To the general public GMO has become synonymous with genetically engineered food crops. At Ginkgo we genetically engineer microbes (brewer's yeast mostly) not plants. We also wanted to highlight that designers at Ginkgo spend time designing the microbes to specification for customers. So we went with designer organism as the term.

Thanks for the clear answer. Hopefully biotech communications with the general public will become easier to parse once people stop seeing genetic modification as some kind of dirty, unhealthy, dark magic.

Congrats on the successful round!

How does pricing work? I imagine you can estimate the difficulty of a metabolic engineering task up front, but it obviously has a tendency towards unexpected difficulties. Do customers ask for a very well defined phenotype ("makes >1g/l/hr paclitaxel", "expresses gfp in >1ppm arsenate across a wide range of ph, osmolarity") or do they ask for more well defined things like stable lines expressing some gene?

Congratulations Jason, you have an awesome company!

I've heard around the Boston scene that you guys have started firing or are about to fire a number of your employees as part of this funding round. Any truth or just mistaken rumors?

That sounds like an insane thing to do? Have no idea where that is from.

Glad to hear the rumors are false. Congrats on the raise!

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