Silicon-based computers have taken us far, but they hit a wall when trying to simulate the complexity of biological systems. Biology operates in ways that defy traditional logic gates—it’s noisy, stochastic, and adaptive. So what if, instead of simulating biology, we harness it directly?

The Big Idea: Bacteria as Scalable, Programmable Cores

Imagine engineering bacteria to act as computational units. These “bacterial cores” could:

•	Perform logical operations using genetic circuits.

•	Self-regulate population size via quorum sensing to prevent runaway growth.

•	Manage mutation rates for computational fidelity while allowing controlled evolution.

These cores wouldn’t just mimic computers—they’d act as living, self-scaling black boxes that could test millions of possibilities in parallel.

Real-World Applications

1.	MRSA and Antibiotic Resistance:

Simulate thousands of drug interactions or engineer precision phages (viruses targeting harmful bacteria) without harming beneficial microbes.

2.	Prion Diseases:

Explore protein folding landscapes to identify inhibitors that prevent prion aggregation or design proteins to neutralize their toxic effects.

3.	Drug Discovery:

Use bacterial cores to explore vast chemical spaces, generating novel drug candidates or protein structures, accelerating discovery processes.

Open Questions

This is just a thought experiment, but it feels like it could be impactful. I’d love to hear your thoughts:

•	How feasible is this integration of genetic circuits, quorum sensing, and mutation management?

•	What challenges would we face in turning bacterial populations into reliable, scalable computational systems?

•	Could this idea serve as a foundation for building “biological black boxes” in pharmacology or protein engineering?

I’m not a synthetic biologist, but I think this concept could spark ideas. How can we refine this vision and make it a reality?

TL;DR:

Can we engineer bacteria to act as self-scaling computational cores that solve problems silicon-based systems can’t—like tackling MRSA, prion diseases, or accelerating drug discovery? Let’s discuss the challenges and possibilities!

Hello all, please let me start by saying I know nothing about the field like you all do, I'm just a nursing student who went down a rabbit hole during my free time on my computer and ended up with an idea. I was looking into trying to change a certain protein's amino acid sequence to make a better, stronger version to protect against autoimmune diseases related to myelination. I know what I have is nothing compared to your vast knowledge, but without tooting my own horn, I want to say I am pretty proud of what I have written so far, whether possible one day or not. If anyone would be able or willing to read what I have and give feedback such as the possibility of concepts, fallacies in logic, next steps if possible, etc? It would be very much appreciated, but please don't be too quick to judge if it's naive, this is all my own free time for fun because I'm interested in it. I do not have immediate intentions to publish or anything, it could be a cool possibility down the road, but currently looking for some current and next-step advice. If you are interested in reading, please message me, and I will send you the link!

INTRODUCTION
Zooming out, fermentation can be broken down into two major components: The Organism and Fermentation facility (+ feedstock)

Synbio adds another layer to this by using AI/ML to re-design the organism to produce more efficiently/effectively. Zoomed out, Synbio components looks like this:

1. Computers + ML/AI DBTL
2. Organism
3. Fermentation Facility

Problem
No matter how good your AI is, no matter how much you modify the organism (let's use yeast) - You will only be able to utilize 4/6 carbons from sugar. There is a hard wall here that every platform will eventually hit.

Solution
Create a "new" organism, a chimera that allows you to utilize 5/6 carbons from sugar. Make it somewhat a Xenobot that can interact with inputs from the fermentation facility (like an instantpot with settings). The company I am referring to put the stomach of a bacteria into yeast to accomplish this.

Problem 2
You would need an extreme amount of data to be able to be able to create this chimera.

Problem 3
After creating the chimera, you would need to start your DBTL all over again with this new organism.

It's easy math. Utilizing more carbons instantly boosts efficiency. This is the most important thing I have gathered from researching synbio companies and I think more awareness of this pitfall will help out others.

Hey! At MIT from 10/25 to 10/27, our student groups are hosting a research event at MIT uniting interdisciplinary minds to explore how emerging new scientific paradigms can address the age-old inscrutability of aging and biological complexity. Michael Levin PhD at Tufts comes to mind as an inspiration.

This event is focused on rigorously formalizing new states of cognition and biology across humans and other organisms, like planarians. Let me know what you think and if there's any questions!

Curt from Theories of Everything is joining and has covered experts across biology, AI, physics, and cognitive science extensively on his podcast. He's had Michael Levin and Karl Friston on many occasions and went in-depth on their research. RSVP for free and more info here: https://lu.ma/minds

Hi all,

I graduated 1.5 years ago with a bachelors in Design from The School of Visual Arts.

Didn’t enjoy what I was doing even in college but I was in too deep and decided to finish the degree. I now run a family business in which I will make more than I ever will as a designer living in New York City.

One thing crossed my mind recently this year. I will regret not pursuing a career in the sciences when I’m 60, specifically synthetic biology. I make a good living, but i want to delve into this multidisciplinary field nonetheless while I’m still relatively young.

I turned 23 a couple months ago, and I know I might need a masters. I’ve seen a lot of people advising that computer science is the way to go. Some also mention bioinformatics, then the clapback to that is it’s better to complete either biology or computer science individually, then take a biotech/bioenginnering/bioinformatics master degree after. I left out biochemistry and biochemical engineering, but please feel free to let me know which is ideal based on what freedoms I expressed below:

In terms of creativity and the ability to touch every aspect of manipulation in this field, which bachelors is the best foundation in this context.

I appreciate any help

I've been going on a synth bio perseveration cycle since my son is starting his multi-disciplinary bio course and i've noticed a lot of sites and resources have gone quiet without much explanation. Is there something nefarious going on or is it just the same lack of initiative i witnessed at my local hackerspace diybio group driving it along with normal internet decay?

Hello, I am a Master Student working on a project that involves using and modifying a kinetic SBML model. I need to add a few reactions but also run optimization tasks. My lab uses a python package for this, MEWpy, but I found it quite cumbersome to use, it works on python 3.9, and sometimes the dependencies are difficult to set up, it also fails to work on certain models for some unknown reason. I found some better alternatives to simulating the model like libroadrunner (far better performance), but I can't find anything usefull for the optimization part, which is implemented in MEWpy using evolutionary algorithms. The only reasonable alternative for it that I found was COPASI, but I was wondering if there are better options? Any recommendations?

I am in the final stages of my PhD in computational biology. My thesis is on the mathematical modelling of gene regulatory networks where I simulate ordinary differential equation models to generate synthetic data and then analyse this data to understand the role of network structure and parameters in determining network function (protein expression pattern in response to a stimulus). This kind of analyses give a theoretical understanding of the design space when synthetic biologists design genetic circuits.

I have decided to join industry preferably in a R&D role after my PhD and not opt for a post doc. I want to understand what kind of opportunities are available in the industry given that my skills are mathematical modelling, Python programming and application of basic ML algorithms to analyse data. Most computational biology opportunities I find deal with genomics data and synthetic biology opportunities turn out to be wet lab related rather than the computational aspects of synthetic biology. Any leads on companies that do computational synthetic biology would be really helpful.

Hi everyone! I'm new to synthetic biology and very interested in protein engineering, particularly how it's being used for things like biosensor development, diagnostics, or creating novel protein functions. I’d love to learn more about labs that are making an impact in this space.

Could you point me to any research groups or academic programs that are well-known for their work in protein engineering? I’m also curious about any recent breakthroughs or impactful studies in this field—especially if there’s work being done with advanced techniques like directed evolution, synthetic biology, or genetic code expansion.

Some specific questions I have:

• Are there any labs particularly focused on evolving proteins for new functions or biosensing applications?
• What are some examples of recent impactful work in protein engineering? (e.g., improving biosensors, creating novel enzymes, etc.)
• Are there academic programs or graduate schools that focus heavily on synthetic biology with a protein engineering focus?

I’m hoping to learn more about where the cutting-edge research is happening, so I can explore potential research programs or labs to follow. Thanks in advance for any suggestions or insights!

As a student, I really resonated with Ginkgo's mission, and from the outside it seemed like a really great and promising company. Having interned there, I saw firsthand how mismanaged and misguided everything there was. However, in my head it is sorta the chicken or the egg scenario–did Ginkgo become mismanaged because the business model and mission was no good, or is the company failing to work because of the mismanagement?

Curious to get thoughts on this because the business model and idea behind the company seems valid and smart if executed correctly! Anyone disagree?

I am in a situation where I want to apply for a research position with a scientist who specializes in synthetic biology. Currently, I have no background in synthetic biology, but I am very interested in the field. To demonstrate my commitment and interest, I plan to design a synthetic gene circuit and propose a research plan, even though I am starting from scratch.

To help me get started, I am seeking study materials and tutorials on synthetic biology and gene circuit design

please help

Answer - A synthetic biologist!

Troubleshooting Y1H bait plasmid positive control.I have cloned an empty bait plasmid (pAbAi) into Yeast Gold Strain and got colonies on the SD-Ura DO plate. When I plate this same yeast construct with empty pAbAi on SD-leu DO plate (no prey plasmid (pGADT7) I am still getting colonies. Similarly, when p53AbAi control plasmid transformed in Y1H gold strain is plated on SD-leu DO plate (no prey plasmid (pGADT7) I am still getting colonies. I have also tested Y1H yeast gold strain without any construct on both, SD-Ura DO plate and SD-Leu DO plate, no growth was observed in either case. Is this normal? To have growth of pAbAi vector on the SD-leu plate without co-transformation?

Thankyou for taking out the time to reply to this!

I'm new to bioengineering and I'm trying to genetically modify a yeast plasmid to produce indoxyl sulfate. I looked on GenBank for DNA nucleotide sequences for indoxyl sulfate but I am getting a lot of different results. For instance, one is 23 bp and another is 390 bp. Also, none of the bp in the 23 long bp sequence overlap with the 390 bp sequence. I am not sure exactly which one I am supposed to choose or what I am supposed to look for.

Is there any hope for companies like Solugen, Lanzatech, Zero Acres, etc. or are they all going the way of Ginkgo, Amyris, Zymergen…

Ask me all your cloning and synthetic biology questions and I’ll do my best to answer them.

Qualifications:

Current grad student at a top 10 program in US, Prior research tech at MSKCC, Synthetic Biology Enthusiast

This might be a very basic question but I am writing a research proposal. I have never worked in a synbio setting so I'm trying to go as basic as I can.

I writing for an investigative study of an engineered strain to see its impacts on a particular disease in vivo. How does one decide which strain to go with? There are many engineered e.coli strains for example, but you can only acquire a few, right? So if I am going with a well studied strain that can easily be purchased online, it will likely already have been studied for the disease that I want to study it for.

So,

is it possible to carry on the research of someone from another part of the world using their strain? how do you acquire such a strain?

This might be a very basic question but I am writing a research proposal. I have never worked in a synbio setting so I'm trying to go as basic as I can.

I writing for an investigative study of an engineered strain to see its impacts on a particular disease in vivo. How does one decide which strain to go with? There are many engineered e.coli strains for example, but you can only acquire a few, right? So if I am going with a well studied strain that can easily be purchased online, it will likely already have been studied for the disease that I want to study it for.

So,

is it possible to carry on the research of someone from another part of the world using their strain? how do you acquire such a strain?

Hello!

We are a group of students trying to localise a fusion protein (https://pubmed.ncbi.nlm.nih.gov/34938905/). We are doing this because we were unable to recreate the before mentioned paper in our lab, and we got some interesting results on the way. The protein is supposed to be expressed on the outer membrane, though we were already skeptical due to the pelB signal sequence.

(1) Blotting the fusion protein has been hell, the only times we could see it on a blot has been in the wells, prompting us to think it might be aggregated in inclusion bodies. We replicated Zhu et al's protocol and we have not been able to get the bands.

(2) enzymatic activity was still observed, but at a considerably lower level, which prompted us to think that the protein might be located periplasmically insteaf of on the OM.

so yesterday, after inducing the BL21 with IPTG, we extracted with B-PER. Theoretically, the proteins should solubilise in the supernatant. We ran affinity chromatography on the fusion's his tag, then a bradford assay. In here we analysed both the pellet and the supernatant. What was surprising to us, is that the pellets had concentrations of 50-90.1 ug/ml, while the supernatant 5-6 ug/ml.

This has prompted us to review the inclusion body hypothesis. Technically, these results indicate that the protein might just as well be OM-bound, but considering the blotting results of the past with aggregates in the wells, we want to investigate this further.

We were thinking of running a native gel on the pellet samples (i.e. high conc samples insoluble) and we think this way we could further conclude on aggregation.

Are there other ways to test whether the protein is expressed mostly in inclusion bodies? Please shoot any ideas, this protein has been sending us a bit cookoo over the last couple of months.

As a programmer I find the fact that ribosome is RNA-based a bit unappealing (Bootstrapping (compilers) - Wikipedia). Especially since at this point many "parts" of it are actually protein based (transcription factors and such). Any thoughts on designing a more satisfying ribosome+tRNAs, which are actually made of proteins?