Asimov Appoints Synthetic Biology Pioneer James J Collins as Inaugural Member of Scientific Advisory Board


Cambridge, MA – January 11, 2019.

Asimov, the synthetic biology company building a genetic design platform for molecular manufacturing and therapeutic applications, announced today it has appointed Dr. James J. Collins as its inaugural Scientific Advisory Board member.

Dr. Collins is the Termeer Professor of Medical Engineering & Science and Professor of Biological Engineering at the Massachusetts Institute of Technology (MIT). He is a prolific bioengineer, having published more than 200 scientific papers and patents including the seminal synthetic biology publication, “Construction of a genetic toggle switch in Escherichia coli”. A recipient of numerous awards including a MacArthur Genius Award and a Rhodes Scholarship, Dr. Collins is an elected member of all three national academies: the National Academy of Sciences, the National Academy of Engineering, and the National Academy of Medicine.

“We are thrilled to have Jim join us, as he is quite simply one of the most influential and visionary bioengineers of all time,” said Alec Nielsen, Ph.D., Asimov co-founder and CEO. “He established the field of synthetic biology and has consistently driven the cutting edge across multiple scientific domains. Jim’s deep expertise in genetic circuit design, systems biology, and machine learning aligns perfectly with Asimov’s mission to build the world’s most powerful genetic design platform.”

Dr. Collins joins the 15-person synthetic biology company, headquartered in Cambridge, Massachusetts. The team also includes MIT professor Christopher Voigt, Boston University professor Douglas Densmore, and MIT Ph.D. Raja Srinivas as co-founders.

“I’m delighted to join Asimov, which is bridging the synthetic biology and machine learning domains,” said Dr. Collins. “To achieve true predictive design of biology, we require radical advances in both the computational and genetic engineering toolchains. I look forward to helping guide development of Asimov’s platform.”

ABOUT ASIMOV. Asimov is a synthetic biology company combining genetic engineering, artificial intelligence, and design automation. Asimov’s interdisciplinary team is building an advanced genetic design platform for next-generation therapeutics and molecular manufacturing. For more information visit

Tweet: Synthetic biology startup @asimov_io announces it has appointed Jim Collins, synbio pioneer and creator of the seminal genetic toggle switch, to its Scientific Advisory Board.

VPN-less Authentication with Google IAP, K8s, and Ambassador

Asimov's mission is to program living cells to create previously impossible biotechnologies. We have created a cell engineering platform combining synthetic biology, artificial intelligence and design automation.

As a new startup, one of our first challenges was setting up a software infrastructure where building, launching and scaling services is a simple process for developers. To this end, we chose to launch a managed Kubernetes cluster atop Google's Kubernetes Engine (GKE).

Kubernetes makes it quite easy to deploy Docker containers and expose them as services to the internet at large, and to scale that instance over time, using a concept called “Ingress”. However, in many situations we will want to launch services with limited access, such as Asimov employees accessing internal tools or dashboards.

Traditionally, securing an application like this is achieved through some combination of the following technologies:

  • Virtual Private Network (VPN): Users connect to the cluster, provide some credentials and are then able to access internal tools.

  • Single Sign-On: A tool like Kerberos allows you to use the same account across various components.

  • Home-grown user accounts: You implement an authentication system and users have a separate username/password for your computing infrastructure.

However, following the BeyondCorp security model, we’d like to support access to our infrastructure from any machine, without installing VPN clients, Kerberos clients, etc. For this, we can use Google Identity-Aware Proxy (IAP).

IAP is a beta service which requires requests to your service to authenticate with a Google Account. Once a user has authenticated and has their account checked against an authorized list, the request is forwarded to your service.

Finally, we want this process to scale as we create additional publicly available web applications. When it comes to URLs, we’ll want to be able to host an arbitrary amount of applications at * domains. We also want to make sure that we can reuse this authentication and certificate infrastructure for each new endpoint. For this, we’ll use Ambassador, a Kubernetes API gateway by Datawire.


Publicly facing Kubernetes applications are typically exposed through a resource called an Ingress. An Ingress is an abstraction for a gateway pointed at some Service in your cluster. Cloud providers of managed Kubernetes typically implement a controller using primitives available on their platform, such as Load Balancers. An example of a typical Ingress declaration might look like this:

apiVersion: extensions/v1beta1
kind: Ingress
 name: internal-ingress
   serviceName: my-service
   servicePort: 80

This is a very basic Ingress that is backed by an HTTPLoadBalancer.

The LoadBalancer will receive a dynamic IP address - you can visit your service by entering that address into your browser URL. The IP address can be found using kubectl get ingress internal-ingress or by locating the load balancer in your cloud console.


The next step is to create and import certificates. Certificates will help us ensure that:

  1. A user’s browser session is secure.

  2. Our load balancer is a candidate for IAP, as it requires a load balancer.

There are a variety of Certificate Authorities who can provide these certificates. We'll use Let's Encrypt, a free provider of certificates. This organization is simple to use, but we have some prerequisite tasks before we can request our certificates.


We mentioned earlier that we want to support a potentially very large number of applications hosted at * domains. Rather than create a certificate for each subdomain, we can create a “wildcard certificate”, which will be valid for all subdomains of Let’s Encrypt offers such certificates, on the condition that you can prove you own the parent domain.

Additionally, we plan to route traffic for each subdomain through a single Ingress, so we need to make sure that requests to <subdomain> end up hitting the same Ingress. As a result, we’ll have to do some configuration to stabilize our IP Addresses.

Static IP Address

First, we need to give our Ingress a reserved IP Address (for more on reserved addresses, see this document). By default, an Ingress is assigned an ephemeral address, which may change as provisioning events occur, such as recreating your Ingress. A static address is a reserved address which your Ingress can always have assigned to it.

This is DNS-provider specific, but for Google Cloud, you can go to "External IP Addresses", find the one with your Ingress name, and change the type to "Static". You can then give the IP address a name, and change your Ingress to get that address. Kubernetes Engine has an annotation which allows you to get the address by name rather than specifying the IP address directly. For example, check out the annotation used below:

apiVersion: extensions/v1beta1
kind: Ingress
 name: internal-ingress
 annotations: "internal-asimov"
   serviceName: my-service
   servicePort: 80

Domain Routing

At this step, we have an address which won't change. We also need to update our DNS to route to that static address. We created an A record which resolves the DNS name * to the static IP address we reserved above. This way, any address ending in will be routed to our Ingress.


Relevant documentation:

Ok, at this point we have a domain that, when we visit it, points to our internal cluster. We're getting pretty close!

Next, we need to actually get the certificates. It's possible to upload and bind certificates manually. However, there is a tool called cert-manager which allows us to declare our certificate information and have it automatically renewed and imported as a secret. This is convenient, as an Ingress can terminate HTTPS connections by declaring the secret in the Ingress config.

So how do we get set up to create certificates from Let’s Encrypt?

cert-manager accomplishes this by creating resources on Kubernetes. The resources of interest are issuers and certificates.

Here's our issuer, which is responsible for creating/renewing certificates and updating the related secrets:

kind: Issuer
 name: letsencrypt
 namespace: default

   # Name of a secret used to store the ACME account private key
     name: letsencrypt

   # ACME DNS-01 provider configurations

     # Here we define a list of DNS-01 providers that can solve DNS challenges

       - name: prod-dns
           # A secretKeyRef to a google cloud json service account
             name: cert-dns-service-account
             key: cert-manager-key.json
           # The project in which to update the DNS zone
           project: my-project

The prod-dns provider declares a provider with name "prod-dns", and tells the issuer where to find the secrets that allow that provider to manipulate DNS records. This service account must be able to modify the cloud DNS records to prove to Let's Encrypt that we own the domain.

A note on providers: Let's Encrypt requires DNS01 challenges, which limits the cloud providers one can use for wildcard certificates. Other certificates can use a much broader range of challenges. See this doc for a listing of supported providers.

Next, let's look at a certificate:

kind: Certificate
 name: wildcard-asimov-io-tls
 secretName: wildcard-asimov-io-tls
   name: letsencrypt
   - '*'
   - dns01:
       provider: prod-dns
     - '*'

This resource declares a certificate. We tell it to store certificates in a secret named “wildcard-asimov-io-tls”, that the issuer responsible for this certificate is named “letsencrypt”, to get us a wildcard cert for the “*” subdomain, and to use the provider named “prod-dns” (see above) for that domain.

Once these resources are configured and the certificate has been imported as a secret, we can update our Ingress to terminate HTTPS connections:

apiVersion: extensions/v1beta1
kind: Ingress
 name: internal-ingress
 annotations: "internal-asimov"
 - secretName: wildcard-asimov-io-tls
   serviceName: my-service
   servicePort: 80

By adding this tls section, our Ingress will now support HTTPS connections.

Authentication (IAP)

Relevant documentation:

Now that we have HTTPS and a domain, our Ingress is eligible for IAP!

Go to "Identity-Aware Proxy" in your cloud console. The left panel should list all "eligible" endpoints, essentially LoadBalancers which are of the type HTTPS. On the right panel, you can control who has access to resources protected by IAP. You can add individual users, or an entire organization. We've added "" so that anybody with an account in our organization can access these systems.

You can toggle the IAP button to "on" for your ingress (ours is labeled "my-service", which you can see as the configured backend in our Ingress).

Routing and Verifying Requests

Relevant documentation: Verifying that requests came from IAP, Ambassador Mappings, Ambassador Auth Guide

So we're done, right? Not quite. We need to verify that requests are coming from IAP.

The linked document has some examples of how to do this. However, we're setting ourselves up for a process that isn't very scalable. For each exposed service, we have to create an Ingress (which takes time), turn on IAP, and implement verification of the request? This isn't great.

If you're anything like me, your yak shaving instincts have already pushed you down the path of designing and implementing a proxy server. You'll have your Ingress point to that service, that service will verify the request, and then route the request to the system behind it. But then you start thinking that how maybe it's not the right idea to reinvent the wheel, and about how you're going to fan requests out to the appropriate backend services, and how somebody else must have had this problem...

Thankfully, somebody has. Datawire has an excellent tool called Ambassador which does all of these things and more:

  • Dynamic routing

  • Authentication hook

  • TLS termination

  • Rate limiting

  • Statistics gathering

I consider Ambassador the key piece which makes IAP a scalable authentication system. Here's how we use it at Asimov:

Instead of putting each backend service behind an Ingress, we put an Ambassador service behind it. Then, each new service we spin up which needs to be exposed on the public internet requires only two steps:

  • Add an Ambassador annotation to the service definition.

  • Add the new subdomain to the IAP console (this under "Edit Oath Client" in the IAP page).

Here's an example of a service with an ambassador annotation:

apiVersion: v1
kind: Service
 name: landing-page
 annotations: |
     apiVersion: ambassador/v0
     kind: Mapping
     name: landing-page-mapping
     prefix: /
     service: landing-page.default.svc.cluster.local.:4567
 - protocol: TCP
   port: 4567
   app: landing-page

Here, we're creating a service that is backed by pods with the label app: landing-page. The ambassador config says "any request that is trying to access a route on the domain '' should be routed to the service 'landing-page.'" There are many flexible routing options, but our use case is typically to use host routing.

Heimdall (Authentication Server)

Now, I mentioned that Ambassador supports an authentication hook - this doesn't mean that Ambassador performs request verification for us. The details surrounding request authentication vary by implementation, so we need to write some custom logic for our configuration. Ambassador allows us to supply a service that receives the headers for each request, and tells Ambassador whether that request is authenticated or not.

We created a "reusable" service for this called Heimdall. Heimdall is a configurable Java service which listens for authentication requests and performs the work of verifying a JWT token (IAP sends a signed JSON Web Token (JWT) containing authentication information that must be parsed and validated).

We have a repository containing an implementation of Heimdall here.

While most of the implementation is straightforward (in fact, the authentication code itself is a slightly modified version of the excellent example here), I'll walk through some considerations for running it.


The application requires an environment variable called "", which is in the form of: /projects/PROJECT_NUMBER/global/backendServices/SERVICE_ID. You can get this audience by visiting the IAP page. Next to the resource you've secured, click the dropdown and click "Signed Header JWT Audience". You can set this environment variable in your deployment spec.

Ambassador Config

Here is the service definition for Heimdall:

apiVersion: v1
kind: Service
 name: heimdall
 annotations: |
     apiVersion: ambassador/v0
     kind: AuthService
     name: authentication
     auth_service: "heimdall.default.svc.cluster.local.:8080"
     - "x-iap-user-email"
 - protocol: TCP
   port: 8080
   app: heimdall

This is fairly similar to most Ambassador configs; although this config is not a route definition, but a declaration that an auth service is backed by the "Heimdall" service. Depending on your namespacing requirements, you may want to adjust the “auth_service” route. We also add an “allowed_headers” section, because Heimdall sets the “x-iap-user-email” header to the authenticated user's email for convenience.


This is mentioned in the README, but the health check situation bears explanation. Heimdall has "three" routes:


This route is to support the health checks Google Cloud makes against its load balancers. By returning 200, we're letting this request in to a service listening on this route that returns 200 OK to the health check.

By default, Google Cloud sends their healthcheck to ‘/’ on the backing service. This isn’t compatible with routing services behind a proxy server which performs authentication, because:

  1. Most systems will want authentication on their ‘/’ route.

  2. The health check does not include authentication.

This is why Heimdall supports a separate “passthrough” which skips authentication. As a result it is necessary to adjust the destination of the load balancer health checks to equal this route - by default it hits '/' which will mean that you can't turn on authentication for requests to that same URL, which probably isn't desirable.

It is also necessary to have some system backing this route. If you don't, the load balancer will stop serving traffic, even if your other services are doing fine. The easiest path to making this change that I’ve found is:

  1. Go to "Load Balancing".

  2. Click the name of the balancer containing your ingress name.

  3. Under “backend services”, click the “health check” link to the right.

  4. Edit the path to be “/load-balancer-health” and save.


This is a simple health check for the system to prove it is up.

“Everything else”

By default, every other route is a request for authentication. Ambassador will forward requests that come in for your proxied resources to this route, which will unpack and verify the JWT tokens.

Parting Thoughts

This infrastructure has made exposing various web interfaces a breeze, and the components involved have been impressively robust. We ended up with something like this:


There are still some ways this setup could improve:


  • The IAP access list is a great start for controlling access to resources, but if you need more granular control on a per route basis, you'll need to invest in a more flexible solution.

  • It would be really nice if IAP could be modified programmatically. As of this writing, there's not a great way to set up IAP via the API.

    • It can be turned on, but you have to generate the oath credentials yourself.

    • Additionally, you can't modify the "supported routes" to add a new route to the backend via the API.

  • is a great resource for managing the authentication session for more dynamic setups such as applications making use of AJAX; we see occasional hiccups with third-party software with dynamic interfaces.


  • Ambassador is excellent and improving every day, but we do wish we could turn off or down the access logs - Google Cloud health checks generate very frequent traffic, so these logs are fairly verbose.

  • We also found that the statsd container that ships with Ambassador causes issues for our DNS if we don't have a stats sink deployed. They recommend removing the container if you aren't collecting stats, and I'd reinforce that point.

Future Work

  • Oathkeeper is an interesting self-hosted alternative to IAP for more granular control with less vendor lock-in.

  • Communications between services within the cluster should also be secured.


Finally, if you'd like to discuss infrastructure or are interested in an engineering position at Asimov, feel free to reach out to me at "brian at asimov dot io".

MIT Startup Exchange Names Asimov to STEX25


Cambridge, MA – May 15, 2018.

Asimov, a company that programs living cells with genetic circuits, has been named to STEX25 by the Massachusetts Institute of Technology Startup Exchange (MIT Startup Exchange).

MIT Startup Exchange promotes collaboration and partnerships between more than 1,400 MIT-connected startups and members of the university’s Industrial Liaison Program (ILP). STEX25 comprises 25 industry-ready startups that receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 240+ member companies.

“Asimov has deep connections to MIT, so it’s an honor to be named to STEX25. We look forward to growing our relationships with industry partners and connecting with other esteemed startups from the MIT community,” said Alec Nielsen, PhD, Asimov CEO and co-founder. “Our cell programming platform allows us to engineer next-generation therapeutics and create previously impossible biotechnologies. We’re excited to scale our commercial efforts.”

MIT Startup Exchange and the ILP are integrated programs of MIT Corporate Relations.

“Startups selected for STEX25 exhibit the high-caliber talent and cutting-edge technology that are hallmarks of MIT, and feedback from industry partners is that MIT Startup Exchange is one of the most effective filters for emerging tech startups,” said Executive Director of MIT Corporate Relations Karl Koster.

“We are very pleased to have Asimov join STEX25,” said Marcus Dahllöf, MIT Startup Exchange Program Director. “They represent the next generation of life sciences startups emerging from MIT.  Life sciences has been a historic strength of MIT, and it’s great to see that represented in STEX25.”

In 2017, Asimov received seed funding in a round led by Andreessen Horowitz, with participation by Data Collective, Pillar, and AME Cloud Ventures.

ABOUT ASIMOV. Asimov programs living cells to create previously impossible biotechnologies. The company’s cell programming platform combines synthetic biology, artificial intelligence, and design automation. Four bioengineering pioneers founded Asimov: Massachusetts Institute of Technology Professor Christopher Voigt, Boston University Professor Douglas Densmore, and MIT Biological Engineering PhDs Alec Nielsen and Raja Srinivas. For more information visit

Tweet: Genetic circuit engineers @asimov_io named to @MITSTEX #STEX25program, which has included other companies from the MIT community like @ginkgoo, @twoXAR, and @Path_AI.

Genetic Circuits Startup Asimov Raises Seed Round Led by Andreessen Horowitz


Cambridge, MA – December 19, 2017.

Asimov, a startup using computer-aided design to engineer biology, announced today that it has raised $4.7 million in seed funding in a round led by Andreessen Horowitz, with participation by Data Collective, Pillar, and AME Cloud Ventures.

“In nature, biology has evolved sophisticated genetic circuits to do incredible things like self-organize into multicellular patterns, construct atomically-precise materials, and protect against sickness. However, genetic circuits aren’t harnessed in biotechnology today because engineering them is a technical challenge. Solving that problem would unlock advanced biotechnologies that seem like science fiction: intelligent therapeutics that sense and respond to disease, molecular assembly lines for biomanufacturing, and living materials that heal and adapt to their environment,” said Alec Nielsen, PhD, co-founder and Chief Executive Officer. “Asimov’s products are custom-built genetic circuits: DNA sequences that encode new cellular functions. Our circuits enable customers to create next-generation biotechnologies in health, manufacturing, and consumer goods. This seed funding allows us to quickly scale and partner with customers in diverse areas.”

Asimov’s software and genetics platform was originally developed at the Massachusetts Institute of Technology and Boston University. Funded by the Office of Naval Research and the Defense Advanced Research Projects Agency (DARPA), the research was published in ScienceNature Methods, and Nature Chemical Biology. The company’s industry-grade version of the platform combines state-of-the-art synthetic biology, biophysical simulations, and machine learning-based design.

“Asimov’s approach to engineering biology has transformative potential across many areas that touch and improve people’s lives. We are thrilled to partner with the Asimov team,” said Vijay Pande, PhD, general partner at Andreessen Horowitz. “Just as semiconductor companies today depend on electronic design automation to build their chips, computer-aided design is playing an increasingly important role in bioengineering. We’ve reached an inflection point in terms of what can be reliably built. This has profound implications.”

ABOUT ASIMOV. Asimov empowers the creation of previously impossible biotechnologies. The company’s design platform enables them to precisely engineer genetic circuits for customers in diverse sectors. The company was founded by four biological engineering pioneers, Massachusetts Institute of Technology Professor Christopher Voigt, Boston University Professor Douglas Densmore, and MIT Biological Engineering PhDs Alec Nielsen and Raja Srinivas. For more information visit

The Circuitry in Our Cells

If you’re reading this, you’re probably biological.

As you sit quietly, trillions of cells in your body are performing a frenetic dance of biochemical computation that makes your existence possible.

Consider this: You were once a single cell – a fertilized egg. This single cell was equipped with a genetic program capable of assembling atomically-precise molecular machines, replicating and distributing copies of its genetic program through cell division, and self-organizing multicellular structures into a human shape with specialized cell types, tissues, and organs.

And now here you are, reading this: Your eyes scanning these words while your brain interprets them. You built yourself from scratch.

Illustration of the molecular milieu inside a white blood cell. Cells are complex biochemical entities capable of sophisticated computation. (David Goodsell)

Illustration of the molecular milieu inside a white blood cell. Cells are complex biochemical entities capable of sophisticated computation. (David Goodsell)

Biology computes with genetic circuits

The remarkable ability of biology to create patterns, perform specialized tasks, and adapt to changing environments is made possible with genetic circuits – networks of interacting genes that perform computation.

Genetic circuits appear literally everywhere in nature. In a lone bacterium as it "tumbles and runs" toward food. In a California redwood as it constructs itself into the sky. And in your immune system as it wards off cancer and infection. In fact, every single thing that civilization sources from biology – food, materials, drugs – was built by nature using genetic circuits to exert fine spatiotemporal control over biochemistry.

Yet despite their ubiquity in nature, genetic circuits are not harnessed in most biotechnology today. Instead, the state-of-the-art is constant overproduction of a few genes, whether they be enzymes, pesticides, or peptides.

Future biotechnologies will seem like science fiction: Intelligent therapeutics programmed to sense disease in the human body and trigger a therapeutic response. Living materials that can heal and react to their surroundings. Smart plants that can modify their physiology to withstand extreme cold or drought. To make these biotechnologies a reality, we need to be able to engineer genetic circuits.

From discovery to design

Natural genetic circuits have been studied for more than half a century. In 1961, the French scientists François Jacob and Jacques Monod published a landmark paper describing the genetic circuit in E. coli that senses and eats lactose [1]. Their description of how the appropriate metabolic genes are regulated (known as the lac operon model) was the first of its kind.

The lac operon genetic circuit. In response to glucose and lactose availability, E. coli regulates the expression of genes involved in lactose metabolism. (Wikimedia Commons)

The lac operon genetic circuit. In response to glucose and lactose availability, E. coli regulates the expression of genes involved in lactose metabolism. (Wikimedia Commons)

A few months later, they predicted that similar regulatory processes could explain cell differentiation in multicellular organisms, like humans. Without mincing words, they wrote, “Moreover, it is obvious from the analysis of these mechanisms that their known elements could be connected into a wide variety of ‘circuits’, endowed with any desired degree of stability” [2]. For their work, they were awarded the Nobel Prize for Physiology or Medicine in 1965 along with André Lwoff.

François Jacob (front) and Jacques Monod (back) in their lab at the Institut Pasteur in 1971. (HO/Agence France-Presse)

François Jacob (front) and Jacques Monod (back) in their lab at the Institut Pasteur in 1971. (HO/Agence France-Presse)

In the years since that seminal discovery, scientists have further illuminated the myriad ways biological systems achieve behavior – from everyday tasks to exceptional feats. Indeed, entire books have been written on natural genetic circuits. (Check out the classic, “A Genetic Switch” by Mark Ptashne [3], which describes how the bacterial virus lambda phage regulates its life cycle.) The panoply of molecular mechanisms that power biological computation is vast and diverse, and reverse engineering natural genetic circuits is a field of intense ongoing research.

Armed with insights from nature, biological engineers began to design synthetic genetic circuits from the ground up. Back-to-back publications in Nature in 2000 are considered by many to be the first examples in the field (a genetic oscillator [4] and toggle switch [5]).

Over the past two decades, the ability to engineer increasingly complex and precise genetic circuits has advanced rapidly. Progress has resulted from several factors: thousands of sequenced genomes (and metagenomes) from which to “mine” useful genes, faster and cheaper DNA synthesis and sequencing, an improved understanding of cell biophysics to enable simulation, the ability to make targeted genomic modifications using CRISPR, and last but not least, years of compounded genetic engineering experience distilled into guiding design principles.

We are truly in the early days of a golden era for engineering biology.

Yet despite our progress so far, genetic circuit design has often been characterized by a manual and failure-prone process. Engineers often spend years creating a functional design through trial-and-error.

Automating genetic circuit design

How might this process of genetic circuit design be systematized and made more reliable? The semiconductor industry has completely transformed society, and its evolution offers a case study in transitioning from artisanal to automated.

Electronic circuits being manually laid out on Rubylith masking film, circa 1970. (Intel Corporation)

Electronic circuits being manually laid out on Rubylith masking film, circa 1970. (Intel Corporation)

Early on, electronics engineers would painstakingly design and lay out circuit diagrams by hand. Then, the 1970s brought with it the first taste of automation: “place and route” techniques developed to position all of the electronic components and wires.

In the 1980s, the advent of electronic design automation (EDA) enabled programming languages that could be compiled down to patterns in silicon. One of the early publications describing this capability, “Introduction to VLSI Systems” by Carver Mead and Lynn Conway, is a holy text of EDA [6]. This breakthrough drove rapid increases in electronic chip complexity, and EDA became an entire industry in itself.

Today, chip designers use sophisticated EDA software that automates the entire workflow (design, simulation, and manufacturing). Software was truly brought to bear on electronic circuit design, and was one of the key enablers of Moore’s law.

Modern electronic design automation software, Virtuoso Layout Suite XL. (Cadence Design Systems)

Modern electronic design automation software, Virtuoso Layout Suite XL. (Cadence Design Systems)

Drawing inspiration from this evolution, we built a genetic circuit design automation platform, Cello (short for “Cell Logic”) [7]. We even used a common electronic hardware description language (Verilog) from electronics design to write our circuit specifications.

By combining concepts from digital logic synthesis, cell biophysics, and synthetic biology, we were able to build genetic circuits with up to 10 interacting genes. That’s state-of-the-art for an engineered cell behavior in 2017, but it still pales in comparison to nature. For reference, the E. coli genome employs roughly 300 genes called transcription factors to control metabolism, survival, and replication. Human cells have about an order of magnitude more. (While this may seem paltry compared to the billions of transistors in a modern CPU, it’s an apple and oranges comparison. The point isn’t to compete with silicon – the point is to program biology with new functions.) 

A tremendous amount of engineering lies ahead before we achieve genome-scale design with comparable complexity, elegance, and subtlety to what nature has evolved. We’re working on that. On the other hand, we have reached a point where genetic circuit engineering is reliable enough that we can program cell functions for previously impossible biotechnologies.

Overview of the original Cello platform [7]. A Verilog specification is automatically compiled to a DNA sequence that encodes a genetic circuit.

Overview of the original Cello platform [7]. A Verilog specification is automatically compiled to a DNA sequence that encodes a genetic circuit.

Introducing Asimov

In the same way that electronic circuits have become ubiquitous in the world – from cars to mobile phones to smart refrigerators – the same will become true for engineered genetic circuits. They will begin to appear in many aspects of daily life, from therapeutics to agriculture to consumer goods.

To help lay the foundation, I’m proud to announce the launch of Asimov with my co-founders Chris Voigt, Doug Densmore, and Raja Srinivas. Building upon our initial work on Cello, we’re developing a platform for professional genetic circuit design. We strive for Asimov to be the go-to resource for designing biological computation as biotechnology steadily becomes a fully-fledged engineering discipline.

I personally hope that this technology one day improves our ability to cure disease, empowers clean and sustainable manufacturing, and helps nourish a growing global population.

I look forward to keeping you updated on our progress.

Alec A.K. Nielsen
Founder & CEO, Asimov

[1] Jacob, F. & Monod, J. Genetic regulatory mechanisms in the synthesis of proteins. J. Mol. Biol. 3, 318–356 (1961).
[2] Monod, J. & Jacob, F. General Conclusions: Teleonomic Mechanisms in Cellular Metabolism, Growth, and Differentiation. Cold Spring Harb. Symp. Quant. Biol. 26, 389–401 (1961).[3] Ptashne, M. A. A genetic switch: Gene control and phage lambda. (1986).
[4] Elowitz, M. B. & Leibler, S. A synthetic oscillatory network of transcriptional regulators. Nature 403, 335–338 (2000).
[5] Gardner, T. S., Cantor, C. R. & Collins, J. J. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339–342 (2000).
[6] Mead, C. & Conway, L. Introduction to VLSI systems. (1980).
[7] Nielsen, A. A. K. et al. Genetic circuit design automation. Science 352, aac7341-aac7341 (2016).