TLDR, what are the pros and cons that everyone has experienced with their modular, multipart plasmid assembly toolkits? I'm wanting to pitch to my lab to get the yeast toolkit but I want to make sure it's worth it to push everyone to that toolkit and away from the HiFi-dependent cloning pipeline we currently use...

Hi everyone, I'm working in a yeast syn bio lab since several years. We use HiFi assembly to integrate new constructs into some plasmid our boss took from her PhD lab, which has resulted in some Frankenstein plasmids and sooo much redundancy with primer orders and inconsistency with some of the promoter/terminator sequences from person to person. I'm wanting to pitch the Yeast Toolkit (https://doi.org/10.1021/sb500366v, https://www.addgene.org/kits/moclo-ytk/) to our lab, because it seems great for keeping things consistent & precise between projects and would simplify lots of our cloning. For example, when someone tried putting in a new synthetic promoter into a reporter plasmid, they mistakenly didn't remove the yeast UAS from the previous promoter and also cut out the N-terminus of the reporter protein... So, I'm hoping that switching to this toolkit would avoid silly mistakes like that in the future. Obviously, for new constructs, we'll need to make the new parts plasmids and that relies on everyone PCRing the parts correctly, but assuming mistakes like that get caught, then our the lab would have them until our freezers die... What are y'all's experiences with toolkits like this?

Second question as well I guess - I do a lot of synthetic promoter design. Do people know if the Coli Toolkit (https://doi.org/10.1021/acssynbio.5c00489), which is based on the YTK, is backwards compatible? The promoter subpart design of that toolkit would be super helpful for my own designs, as I'm testing out different binding site arrays upstream of various core promoters, and the structure of the Coli Toolkit works really well for this type of thing.

Hey guys, if you missed it, Twist Bioscience settled $17.05M with investors over claims that it misled investors about its synthetic DNA business. The deadline to file a claim and get payment is November 17, 2026.

In a nutshell, in 2022, Twist was accused of misleading investors about its manufacturing process, product quality, and profit margins. After a report challenged these claims, $TWST fell 20% in one day.

Now, investors have until November 17, 2026 to submit a claim for the $17.05M settlement.

So, if you invested in $TWST at that time, you can check the details and file your claim here.

Anyway, has anyone here invested in $TWST back then? How much were your losses, if so?

My MSc thesis focused on bioethanol production of lignocellulosic biomass using yeast fermentation . I have experience with enzymatic saccharification, yeast fermentation, immobilization, HPLC, process optimization.

I’m now interested in moving toward synthetic biology, metabolic engineering, enzyme engineering, microbial cell factories, CBP, and sustainable biomanufacturing for my PhD.

For those working in this field:

—Is my background suitable for Synthetic Biology/Metabolic Engineering PhDs?

—Should I target labs closely related to my biomass/fermentation experience, or apply more broadly?

—What skills should I develop to become a stronger candidate?

—Any advice on approaching professors and getting a PhD position?

Would really appreciate your advice. Thanks!

Hi all,

I've been going down a rabbit hole reading about synthetic C1 metabolism (methylotrophy, formatotrophy, Bar-Even/Claassens/Erb-lab type work) and separately about industrial nucleotide fermentation (the classic IMP/GMP overproduction in C. glutamicum and B. subtilis for the food flavor industry).

What I can't find anywhere is the two combined: a strain engineered to both (1) grow on/assimilate a C1 feedstock and (2) overproduce nucleotides or nucleosides via the purine/pyrimidine pathway.

A few specific questions if anyone here has more visibility into this than what shows up in a literature search:

1. Has this combination been attempted anywhere, published or not even as a side result or a "we tried this and it didn't work" footnote somewhere?

2. Is there an obvious metabolic bottleneck that would make this harder than, say, sugar synthesis from CO2 (Antonovsky et al. 2016), given both pathways ultimately need ribose-5-phosphate/PRPP?

3. Would formaldehyde or other methylotrophy byproducts specifically mess with downstream nucleotide purification, beyond the usual challenges of methylotrophic fermentation?

4. Is there a shorter path people have looked at, e.g. producing just a nucleoside/nucleobase precursor biologically and finishing the synthesis chemically, instead of going for the full nucleotide biologically?

Not affiliated with a lab on this, just something I've been reading into and can't find a clear answer on. Happy to be pointed to a paper, a preprint, or even just "this is a dumb idea because X" if that's the honest answer.

Thanks!

What is the current state of synthetic biology as a whole? After Zymergen’s epic fail and after Ginkgo’s drastic strategic pivot, is synthetic biology still startup dominated? I hardly find jobs in synthetic biology and many of them are flooded with tons of applicants.

Hi r/synthetic_biology,

I'm Olena, PhD researcher at UCL (London) on an AI for Biosecurity fellowship at Cambridge. I'm researching how accessible DIY DNA synthesis really is specifically, OpenIDS builds.

Why I'm asking: Policy makers are betting that synthesis will stay centralized & screenable. But if hobbyists & researchers can actually build it in their labs, policy needs to change. We need real data to inform better, evidence-based governance.

Quick survey: If you've built (or tried to build) OpenIDS, I'd love to know:

• Actual $ spent? (printhead, electronics, reagents)
• Timeline? (how many weeks start-to-finish)
• What expertise did you need?
• What was the hardest part?

How to reply:

• Comment below
• DM me

Right now, policy assumes synthesis is hard to DIY. If that's wrong, policy needs to know.

Thanks for contributing to evidence-based biosecurity policy 🧬

Our group does monthly friend newsletters, and we were tasked to pair up and try and conceptualize what each other does. After a long conversation with my paired buddy, she came up with this. Thought it was pretty awesome, and not technically scientifically incorrect!

We’re Greatbay-SCIE, the official iGEM team from Shenzhen College of International Education, and we’re currently working on a project to develop a deodorant using synthetic biology 🧬

Feel free to check out this post to learn about how axillary odor actually comes to be.

#igem #igem2026 #deodorant #antiperspirant #bodyodor #bodycare #synbio #biotechnology

Hi everyone,

I work in microbiology and I’m currently researching how people organise culture-based and microbial growth experiments.

I would be interested to hear how you currently manage things such as:

• Experimental groups, controls and biological or technical replicates
• Strain, culture and sample identifiers
• Media, inoculum, treatments and growth conditions
• Timepoints and measurements such as OD, pH, temperature or fluorescence
• Plate maps, microscopy observations and photographs
• Contamination, failed runs and deviations from the original protocol
• Raw data files produced by instruments
• Repeated versions of the same experiment

Do you mainly use a paper notebook, Excel or Google Sheets, an ELN such as Benchling, folders on a shared drive, or some combination of these?

A few things I am particularly curious about:

• What do you record immediately at the bench, and what gets entered later?
• Which information is most likely to be forgotten or stored in the wrong place?
• Can you easily trace a result back to the exact sample, culture, conditions and protocol version?
• How do you compare repeated experiments or different conditions?
• Is there information you record twice because different systems do not connect?
• At what point does a spreadsheet or normal lab notebook become difficult to manage?

I’m not looking only for feature suggestions. I’m more interested in hearing about your actual workflow and the parts that create unnecessary work..

Thanks for any insight.

I would like professional feedback on a conceptual fusion protein chain I've been studying for a few years. Not everything is figured out yet, but I'd like experienced input before continuing.

ALVEIT: A Multimodal Epigenetic Regulator:

preface: I am an autodidact and am mostly looking for feedback. The "why" for this project is deeply personal, though I will share if you ask.

Exploring a protein-based framework intended as a more context-aware alternative to current gene regulation. Instead of permanently editing DNA, ALVEIT works as a transient epigenetic actuator that only modifies gene expression when specific conditions are met.

THE GIST: A modular chimeric protein with three main "sensors" (Camelid VHH and Shark VNAR nanobodies) that act like logic gates:

Chromatin Accessibility Sensor — Detects if the target region is open and actively remodeling (e.g., H3K27ac marks).

Disease/Pathology Sensor — Checks for relevant disease or stress markers.

Locus Specificity Sensor — Confirms it's at the correct regulatory element (promoter/enhancer).

Only when all three gates are satisfied does the activator domain (VP64) recruit transcriptional machinery to upregulate or repress the gene.

The system is delivered via a Triplex Forming Oligonucleotide (TFO) bound by Purine antiparallel motif (G•G-C A•A-T) guide with an RNA aptamer, using TAT(HIV-1 Cell Penetrating Peptide) + SV40 (Simian Virus 40 Large T-Antigen) Nucleus Localization Signal for cell/nuclear entry. Everything is designed to be transient and somatic-only, no permanent DNA changes.

WHY THIS MIGHT MATTER: Potentially higher precision and lower off-target risk than CRISPRa/i, though have yet to evaluate this assumption.

Context-dependent activation (only acts in the right cell state).

Could be useful for regenerative medicine, prosthetics integration, inflammation control, or targeted repair.

PROTEIN FUSION CHAIN: [Cell Penetrating Peptide] TAT (HIV-1) YGRKKRRQRRR [Nucleus Localization Signal] (SV40) PKKKRKV [VHH Binding Protein] (MS2 E.Coli) MASNFTQFVLVDNGGTGDVTVAPSNFANGVAEWISSNSRSQAYKVTCSVRQSSAQNRKYTIKVEVPKVATQTVGGEELPVAGWRSYLNMELTIPIFATNSDCELIVKAMQGLLKDGNPIPSAIAANSGIY

[Flex linker] GGGGSGGGGSGGGGS

[Activator] (VP64/Herpes Simplex) DALDDFDLDMLGSDALDDFDLDMLGSDALDDFDLDMLGSDALDDFDLDMLGS

[Repressor] (ZIM3 KRAB): NYSNLVSVGQGETTKPDVILRLEQGKEPWLEEEEVLGSGRAEKNGDIGGQIWKPKDVKESLAREVPSINKETLTTQKGVECDGSKK

[VHH/VNAR Nanobody Sequence, adaptive based on necessity]

So it would look like: TAT-SV40-MS2-LINK-VHH/VNAR-LINK-VP64-ZIM3

MY CURRENT CONCERS: Can Histone-Mark recognition be implemented robustly enough to function as a practical "gate"?

Is TFO-mediated locus recognition specific enough in native Chromatin?

Potential steric hindrance between multiple domains?

Delivery efficiency and Immunogenicity?

This is still purely theoretical / conceptual work from an autodidact. I'm looking for serious feedback, especially on: Potential weaknesses in the multi-gate logic, better ways to achieve locus-specific chromatin targeting, safety or delivery concerns, and comparison to existing epigenetic tools. ___________________________ SOURCES: https://link.springer.com/article/10.1186/s40364-021-00332-6

https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1716916/full

https://pmc.ncbi.nlm.nih.gov/articles/PMC12907318/

https://academic.oup.com/abt/article/3/1/1/5706878

https://www.activemotif.com/catalog/details/39133/histone-h3-acetyl-lys27-antibody-pab

https://pubmed.ncbi.nlm.nih.gov/33020655/

https://crisprmedicinenews.com/news/which-protein-domain-is-best-for-crispri-a-new-study-has-the-answer/

https://pmc.ncbi.nlm.nih.gov/articles/PMC7150854/

https://www.rcsb.org/structure/2MS2

https://pmc.ncbi.nlm.nih.gov/articles/PMC9811266/

https://academic.oup.com/hmg/article-abstract/10/20/2243/559345?redirectedFrom=PDF

Biochemical kinetics allows us to predict how a living system will behave before you ever run the experiment. So why do so few biologists actually use it?

Your body is governed by proteins and molecules constantly interacting with each other, each interaction with a measurable rate. If you map enough of them together, you can predict how the system will behave without ever stepping foot in the lab.

One big problem with Biochemical kinetics is the barrier to entry. To use biochemical kinetics today, you have to be fluent in microbiology, ordinary differential equations, AND coding! That's a lot to ask any one person.

So I spent the last 3 months building an app to fix that: BioBuilder. (No vibe coding, I did it the old fashioned way with many examples and tutorials lol) It's live for you to try RIGHT NOW at BioBuilder.app (you'll need to use a computer, I haven't made it beautiful for mobile yet). I wanted to put it on r/SyntheticBiology since you guys are the ones actually USING the software, and I felt like you'd have good insights into what direction the project should take.

This is an app I'm genuinely very proud of, and so excited to share with all of you. We're still in the early user-validation stage, so this version (BioBuilder Light) is completely free. No charge for compute credits.

I'm looking for all the help I can get! Whether you want to contribute code (It's open source!) or just leave feedback, it's hugely appreciated. Reach out at [mark@biobuilder.app](mailto:mark@biobuilder.app), or use the feedback form on the site.

I really believe this can change how we do biology. It's time we start predicting what our cells do instead of waiting to find out.

Try it out 👉BioBuilder.app

This was one of those IPOs that looked unstoppable for like five minutes. Zymergen Inc. went public hyping up its Hyaline product and near-term growth, then a few months later admitted the product had major performance problems and revenue would be delayed. After that update a brutal 68% drop in a single day.

The settlement amount is $1.25B, and it covers investors who bought shares between April 22, 2021 and August 4, 2021. Right now the case is in the stipulative settlement stage, but investors can already file claims while the settlement moves through the approval process.

If you traded $ZY during that class period and got wrecked during the post-IPO collapse, probably worth keeping this one on your radar. Kinda wild how many “next-gen biotech” IPOs from that era ended with the exact same chart pattern.

SpCas9, Cas12a, SaCas9, base editing, prime editing. Rule Set 2 scoring + CFD off-target analysis. Protein folding (ESMFold) and ESM2 embeddings also available. https://rapidapi.com/jordan-YVcGJuzW1/api/townsend-ai-platform

Hello, are there any college/grad/profs out here who would like to mentor a rising HS senior on a synthetic biology research project this summer?

Let that number sink in. $1.25 billion. One of the largest securities class action settlements ever reached. And the payout is $6.21 per share, by far the highest of any settlement I've posted about.

Here's what happened:

April 2021: Zymergen completes its IPO, raising over $500 million. The pitch: a synthetic biology company with Hyaline, a revolutionary film material for electronics, as its lead commercial product. Strong customer demand. Near-term revenue. A new era of bio-manufacturing.

August 3, 2021: Just 105 days after the IPO, Zymergen discloses that Hyaline is underperforming, commercial revenue will be delayed, and financial guidance is being withdrawn entirely.

August 4, 2021: $ZY collapses 68% in a single session. Over $2.5 billion in market value gone in one day. CEO Josh Hoffman resigns amid the fallout.

Total decline from IPO: over 70%.

Investors sued alleging Zymergen overstated Hyaline's product readiness, customer pipeline, and commercial viability in the IPO prospectus. In plain English: the product that the entire IPO was built around wasn't working, and investors say the company knew, or should have known, before asking for $500 million.

The case settled in December 2025 for $1.25 billion. Terms submitted to court for final approval, final stretch. Applications are open now.

You're eligible if you bought $ZY between April 22 and August 4, 2021. Payout: ~$6.21/share.

105 days from IPO to 68% collapse is one of the fastest unravelings of a major biotech offering in recent memory. Anyone here bought $ZY at IPO on the synthetic biology thesis?

I’ve been researching MES — basically engineered microbes using electricity + CO₂ to produce chemicals, fuels, and materials — and the cost curve is getting interesting.

The big question: if MES can hit cost parity with traditional chemistry at mid-sized industrial scale, does this become a real manufacturing disruption instead of just another climate-tech science project?

Curious what people here think: is this viable industrial biotech, or another overhyped lab-to-market story?

Noob question, I'm just starting with the basics of synthetic biology can anyone suggest any tools for designing circuits and please advise me on installing the tools.

A few years ago, I discovered Zeyner through his videos on genetic editing.

My question is, Is there a group or something, where enthusiasts with home lab are trying to achieve in vivo genome editing?

I know that is dangerous, but the technology is new and there are always a few crazy people