The lag phase of commercial gene synthesis

From synthetic biology’s earliest days, DNA synthesis, and more specifically gene synthesis, has been touted as the central, enabling technology of the field.  Gene synthesis is part of what lets us make the leap from the ad hoc, cut and paste of genetic engineering to the systematic design that is [or will be] the hallmark of synthetic biology.  Given its central importance, it’s not surprising that many of us in the field keep a close eye on both gene synthesis technology and the gene synthesis industry as a whole.  Yet most of the discussion focuses just on the cost of gene synthesis.  Cost is important.  But I’d argue that turn times are equally important in terms of how gene synthesis is used in the field – more on this below.

Below is a chart summarizing turn times versus length for DNA orders at Ginkgo.  On the y-axis is the turn around time (in days) and on the x-axis is the length of the synthetic DNA (or synthon) in base pairs.  [I refer to all of synthesized DNA fragments as synthons rather than genes since we don’t only synthesize genes.] Data points are colored by gene synthesis provider.

First, a few caveats:

  • Orders at the three providers weren’t placed contemporaneously and we didn’t place orders for the same synthon at multiple providers.  A more controlled experiment would of course be to place orders for a large set of identical synthons at multiple providers simultaneously and compare turn times.  We didn’t do that.
  • We design all our synthons using in house software – so the measured turn times reflect only ability of providers to build our synthons and not the quality of their gene design tools.
  • By design, nearly all of our synthons pass all provider sequence checks and qualify as “low complexity” sequences from a synthesis standpoint.
  • Almost none of the cloned synthons result in protein expression which might adversely impact clonability by providers.
  • To calculate turn time, I “start the clock” when we input the order to the provider website or send it to their sales rep and I “stop the clock” on the day the provider ships the gene back to me.  So if there is a delay in order processing by the provider or rep, that counts against their turn time.
  • We rarely pay the 2X+ price premium to synthesize genes at DNA2.0 – hence the limited number of datapoints for them.
  • There are a handful of synthons that providers couldn’t synthesize and/or clone.  The 500 bp/80 day outlier for Blue Heron is one but there are also three others from IDT (unmarked).  For those failures, I “stopped the clock” when the provider emailed me to say that they couldn’t make the synthon and weren’t going to try any longer.

OK caveats finished.  What can we infer from this chart?  Here are two takeaways.

Lesson 1: Gene synthesis can’t be a part of the design-build-test loop until turn times improve dramatically

Based on our data, turn times are highly variable and show little to no correlation with length overall.  This means that when you place an order, you have no idea if you’ll get it back in 2 weeks or 5 weeks.  From an engineering process standpoint, I’d argue that the unpredictably long turn times mean that it is crazy to include outsourced commercial gene synthesis in the design-build-test loop as you try to engineer an organism.  Instead, do gene synthesis orders up front as a batch (thereby hopefully eliminating gene synthesis from your cycle time) and then mix and match the synthesized parts via a DNA assembly technology with a faster turn time.  Or alternatively, try to achieve faster turn times by doing gene synthesis in house from oligos.

Lesson #2: Different providers specialize at different orders

IDT appears to be quite fast at making sub-500bp synthons.  This is not too surprising given that IDT leverages their ultramer oligo synthesis tech to offer flat rate pricing on so-called minigenes (< 400bp synthons).  At that length scale, you can also opt to stitch together oligos to make the part yourself.  But between the costs of oligos, cloning reagents, sequencing and your own time, you might not do much better than the cost of a minigene (even factoring in cheap grad student/postdoc labor!).  For synthons in the 500-1500 bp range, Blue Heron seems to be a reasonable compromise choice in terms of turn times versus costs.  You get industry competitive pricing with decent turn times.   Overall, DNA2.0 appears to have the best turn times for >1 kb synthons.  Admittedly this is based on a very limited sample size but anecdotal rumors from folks in the field back it up.  So if you’re in a rush and can tolerate the 2X price difference, DNA2.0 could be the way to go.

I’ll close by saying that this post is in no way an attempt to rag on gene synthesis providers.  Building DNA is tough.  And building DNA for customers is even tougher.  But it’s important to think hard about what the realities of costs and turn times of commercial gene synthesis mean for developing best practices for engineering organisms going forward.

Posted By: Reshma Shetty

  1. Hey, thanks for the data! It’s valuable to see how large-volume clients such as Ginkgo fare with their orders. It’s also very interesting to me to see the variability in lead-times; I’ve only ordered synthesised genes twice, and I thought that a month lead time was pretty much the norm, but your graph has a lot more variability.

    I have two questions, if you’d be so kind?
    1) Have you any intentions of releasing this in-house software? It sounds excellent, and it could really help smaller players such as myself advance our own work, which would in turn help advance the pace of the whole field.
    2) Have you any estimates on how long in-house oligosynthesis tends to take per-nucleotide? You suggest in-house oligos as an alternative to outsourcing, but what’s the comparison on money and time spent? Reliability? I had always figured that outsourcing was valuable precisely because you don’t have to concern yourself with quality control or complications in synthesis; once it’s paid, its their problem.

    1. Thanks for your comments.

      Regarding (1), we have no current plans to release our gene design software but there are lots of options already available. Most commercial gene synthesis providers offer free-to-use gene design software – DNA2.0 and Geneart look to have some of the more sophisticated offerings. There is also software by folks at Johns Hopkins. Finally, Brad Chapman has made various python libraries available if you are interested in developing your own software. There’s of course also a pretty extensive literature on different codon optimization/randomization strategies.

      Regarding (2), to clarify, I was suggesting in house gene synthesis as an alternative to outsourced, commercial gene synthesis – not in-house oligo synthesis. Turn times on commercial oligo synthesis are quite fast – depending on your location, it could be same day or next day [if you’re willing to pay for it]. Previously in Tom Knight’s lab at MIT, we used to synthesize our own oligos. It was convenient in that we could get ~20nt oligos within 4-6 hours but at the time we were generally using the oligos for PCR or Sanger sequencing – not gene synthesis. When you are using oligos for gene synthesis, error rates are significantly more important and therefore if I had to bet, I’d say that achieving error rates via in house oligo synthesis comparable to outsourced, commercial options would require a significant development effort.

      Best of luck with your work!

  2. Thanks for sharing the data! Do you see any palpable improvement over time? Most synthetic biology “gurus” argue that the exponential improvement of DNA synthesis is a key factor to the field. What is your view on that?

    1. I’m afraid that I haven’t seen any obvious trend of improvement of turn times over time but I haven’t done a rigorous analysis. I think when most people in synthetic biology discuss improvements in DNA synthesis technology over time, they are referring to either (a) total throughput (i.e. total number of bp synthesized per unit time) or (b) cost (i.e. cost per bp). As far as I know, most people/groups either don’t collect or don’t release data on the turn times that they see so I haven’t seen a lot of discussion on that point.

  3. Great to see turn times in such a clear data.
    Unfortunately gene synthesis is still on this pace. The few experience we have shows exactly the same: too much time and lack of pattern. Thanks for sharing! It is also great to have “empiric” information about providers versus bp!

  4. Hi Reshma,
    Thanks for the analysis, it’s very helpful. I’ve been in touch with some of the synthesis vendors and they have mentioned that turn around times can be shortened and better estimates of those times can be made if endusers work closely with the synthesis scientists/technicians early in the design process. Essentially, a close relationship speeds synthesis up and makes things more predictable. Have you found this to be the case? Do you have close ties and good relationships inside the synthesis groups? Thanks again.

  5. I would be curious to know how the improvements in oligo synthesize have led to improvements in gene synthesis. Many years ago, basic synthesizers could produce at a rate of 10 bases per hour. It seems with the advancements in oligo synthesis, this would translate into shorter times for gene synthesis as well.


    1. It’s unlikely that turn times on oligo synthesis are a dominant factor for turn times for gene synthesis. Turn around times for oligo synthesis are very consistently just a few days (versus a few weeks for genes) and are dominated by shipping times rather than by the oligo synthesis itself.

      Error rates in oligo synthesis are a more likely significant factor for gene synthesis turn around times. High error rates in oligos increase the likelihood of errors in full length gene fragments which in turn increases the likelihood that either (a) additional clones will need to be screened, (b) errors need to be corrected or (c) the entire gene synthesis process needs to be re-started in order to produce a sequence perfect gene.

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