I predict that as the value of those other projects rise, and as the capital required to produce a drug decreases, that those other projects will really start to blossom. And I look forward to it.
1,124 karma · joined February 3, 2017
I predict that as the value of those other projects rise, and as the capital required to produce a drug decreases, that those other projects will really start to blossom. And I look forward to it.
In the biotech space part of that incubation/culture can come in the form of shared lab space. Here are a few (in the Bay Area):
- MBC (née QB3) https://mbcbiolabs.com/
- JLabs https://jlabs.jnjinnovation.com/
- StartX https://startx.com/med
- IndieBio https://indiebio.co/
- Bonneville Labs https://bonnevillelabs.com/
There are a number of other governments and entities that are trying to replicate and improve on the model.
Portland has OTRADI https://www.otradi.org/
(help add to the list?)
Small community around here too - there's a lot we can learn from each other.
The really big difference is that biology computes at overlapping time and distance scales, simultaneously. There are biological computational processes that occur at microseconds, to millennia, from fractions of a nanometer to kilometers all happing in concert and referencing each other. In the building of our own computational tools we generally try to avoid mixing physical scales like that. The analogies to computers aren't inherently wrong, they just need to mix in a lot more complexity.
[My company is one - we have pure software engineers on our team, we build synthetic therapeutic proteins]
Check out companies like Zymergen, Benchling, Synthego, Bolt Threads, Gingko, Riffyn, & Teselagen.
In terms of pure software, helping open source scientific libraries, image processing for science, and genomics software would help out what is otherwise an under-funded field.
It's a thankless job to do all of the comparisons/reviews of proteins with similar functions. And then even more of a challenge to take that hard-earned data and make it accessible and immediately useful. But it is foundational to moving the field forward.
Thank you, and keep up the good work.
1) It binds to DNA based on where a template RNA strand matches DNA in a genome. That RNA strand has 2 pieces - a piece that attaches to the Cas9, and a piece that matches whatever sequence of DNA you want to bind.
2) It cuts the DNA it has bound to.
(The first property is very special to Cas9. The second property is actually pretty common. The common intention in using Cas9 is to cut DNA at a place that needs editing and hope the cell's own repair machinery fix it properly.)
Important to understand about biology/chemistry, things rarely happen "IFF and only IF", but more often, happen at a rate (i.e. 1 event per microsecond).
So better more true functions of Cas9 are actually:
1) Cas9 spends a larger fraction of time near its target sequence than it does around random sequences.
2) Cas9 cuts DNA ever 1/N timeperiods, and that might be sped up when it is attached to DNA.
So Cas9 should hang out around its target sequence, most of the time, and that the cutting event happens relatively randomly. So _in general_ Cas9 will cut at its site of interest, however, it will also cut elsewhere, purely statistically speaking. And if you want to be guaranteed a cut at your spot of interest, you're likely to get cuts elsewhere ("off-target" cuts to DNA. These are undesired as you really don't want random changes to your DNA that you're not asking for...).
----- now comes the paper -----
If you make it so Cas9 cannot cut because the homing device is kinda kinked or boxy or otherwise not quite right (but it is still able to home in on particular sequences of DNA), you can make it so Cas9 runs around and finds where its supposed to be, but just hangs out there; Function 1 still works, but function 2 is turned off. These scientists made a special version of RNA that only permits the Cas9 to work when light is shined. So the RNA absorbs the light from a laser, breaks a seal, and the Cas9 snips right then and only then (in a matter of seconds). And any Cas9 molecules that did not get light cannot cut - they just continue to hang out and don't do any damage that they otherwise might do, statistically.
If you're trying to cut a specific sequence and only a specific sequence, this increases the statistical chance you are correct by shortening the time period (and spatial localization) when Cas9 can actually take its second, cutting action.
A clinical lab that is used to running these kinds of (very common) protocols will see no difference in this protocol from others they commonly run (from a chain of custody, sample integrity, etc. perspective), just with a slight change to their reagents to specifically test for COVID. Their handling should be no different.
A surface full of massacred microorganisms might be 'sterile' - nothing there can support life, even if given sugar, water, energy, etc. But it's also certainly not clean. If any of the debris from those dead microorganisms could trigger your immune system, were poisonous, or were chemically active they could alter the outcome of a chemistry experiment or trigger an immune response.
Disinfectants by definition kill organisms, but don't remove the constituent components of the organisms from the area. Bleach & alcohol in high concentrations (but not pure!) will also destroy most any organisms (but will not in itself remove the debris of those dead organisms).
Soaps will link chemicals and molecules to water that is flowed over them, and will remove all of those constituent components along with the water. And if the soap is strong enough, it will also dissolve and destroy smaller organisms in the process. A surface washed with soap will no longer have any debris on it.
https://www.history.com/news/why-was-it-called-the-spanish-f...
Those who can put those various discoveries together are those that will be the ones that use those tools in conjunction in order to benefit everyone. But how are they to know about them if the discoveries themselves 'are not news'?
We are! (Serotiny): https://serotiny.bio
Synthego: https://www.synthego.com/
Mammoth: https://mammoth.bio/
Zymergen: https://www.zymergen.com/
Boston:
Arbor: https://arbor.bio/
Asimov (kind of): https://www.asimov.io/
Ginkgo: https://www.ginkgobioworks.com/
Also just happy to chat about the (very interesting, vibrant, if still tiny) intersection of software & synbio.
Industry: Synthetic Biology, Biotherapeutics, Bioinformatics, Genetics
Location: San Francisco
Current Stack: Javascript (Ember) front-end, REST API written in Go
Role: Front-end and data-visualization engineer - design, code, and deploy novel interfaces for protein design that interact with our custom API.
Perks: Small credentialed team, flexibility, community engagement
Benefits: Health, Dental, Vision
Compensation: $100-150k + Equity
https://serotiny.bio/careers/#Software%20Engineer%20-%20Fron...
Happy to chat. My name is Justin, and my email address is my name at serotiny.bio
Also curious about your interaction with CLSA - they're a pretty cool group that, as you mention, serves as a node or hub in the community. What does your interaction with them look like? To some extent they already provide some portal into the larger lab suppliers. It's not on the payment side, but more on the buying power itself.
Helping comply with government-approved accounting would also be a very nice feature for those of us that make use of SBIR-type grants. Though I suspect that that would mostly be true for much smaller biotech startups.
Serotiny is a synthetic biology design firm that invents custom proteins to cure cancers and genetic diseases. We help design proteins involved in CAR-T therapies, CRISPR systems and other multi-domain protein therapeutics. See https://serotiny.bio/notes/proteins/
Industry: Synthetic Biology, Biotherapeutics, Bioinformatics, Genetics
Location: San Francisco
Current Stack: Javascript (Ember) front-end, REST API written in Go
Role: Front-end and data-visualization engineer - design, code, and deploy novel interfaces for protein design that interact with our custom API.
Perks: Small credentialed team, flexibility, community engagement
Benefits: Health, Dental, Vision
Compensation: $100-150k + Equity
https://serotiny.bio/careers/#Software%20Engineer%20-%20Fron...
Happy to chat. My name is Justin, and my email address is my name at serotiny.bio
The red chunks are its DNA. But they're 'chunky' because the 'whole genome' is partitioned into 23 chunk - each chunk is a 'chromosome'. And each chromosome comes as a pair. And in the movie you can see the cell split the pairs, where one set goes to one cell, and the other set goes to the other.
If you notice, in the cells just prior to 'condensing', the nuclei (red stuff) looks kind of brain-like in its topology. Those are the chromosomes as well, just relaxed and spread out.
Most organisms are exceedingly energy efficient. [Build me an humanoid-like robot with all its attendant capabilities that can be powered on 2000 calories of snickers bars and apples...]
In order for these things to put of the kind of wattage we're familiar with even in a candle, you'd have to be feeding those plants some really crazy food (not what they usually do), or be charging them up with some super crazy laser (kinda defeats the point of a bio-light).
However, it's still super cool. And you could probably find all sorts of ways to actually charge up a plant in the long run, and as technology matures. Maybe have a whole 'forest' providing energy to a single 'lamp', or be able to provide some direct reservoir of maple syrup the plants can tap into for fuel, or store up energy over a few days for a few hours of light. The energy can come from somewhere else, but it does have to come form somewhere.
But yep - there are some basic laws of physics around energy expenditures that need to be taken into account here.
Serotiny is a synthetic biology design firm that invents custom proteins to cure cancers and genetic diseases. We help design proteins involved in CAR-T therapies, CRISPR systems and other multi-domain protein therapeutics. See https://serotiny.bio/notes/proteins/
Industry: Synthetic Biology, Biotherapeutics, Bioinformatics, Genetics
Location: San Francisco
Stack: Javascript (Ember) front-end, REST API written in Go
Role: Front-end and data-visualization engineer - design, code, and deploy novel interfaces for protein design that interact with our custom API.
Perks: Small credentialed team, flexibility, community engagement
Benefits: Health, Dental, Vision
Compensation: $100-150k + Equity
https://serotiny.bio/careers/#Software%20Engineer%20-%20Fron...
Happy to chat. My name is Justin, and my email address is my name at serotiny.bio
"...ordered by {time spent there}->(how long it was on the front page)"
It has a fossil layer in addition to the geographic features. I have always been curious about actually visualizing the 3D layers of geographical time, including the access to what was living at the time.
And it has an API in addition to its pretty nice layered map overlays.
> Anich says that Jon Martin—a forestry professor and coauthor on the paper—was exploring a Wisconsin forest at night, using a UV flashlight to scan the canopy for lichens, fungi, plants, and frogs that occasionally fluoresce. “One evening,” says Anich, “he heard the chirp of a flying squirrel at a bird feeder, pointed the flashlight at it, and was amazed to see pink fluorescence.”
I like that we're literally hunting for fluorescent organisms. I suspect that kind of bioprospecting for high-value exotic genetic traits will become more and more interesting as we move forward with our biological engineering capabilities.
DNA seems to be able to detect lesions and mis-matches based on conductivity of electrons down the double-strands themselves [1].
[1] Meta-Meta-Article: https://www.bakerlab.org/index.php/2019/01/02/nature-article...
[2] Actual paper: https://www.nature.com/articles/s41586-018-0509-0
Transcription Factor + GFP -> green transcription factor -> codon-optimized plasmid
Membrane tag + light-activated conformational change + cytoskeleton -> optogenetic mechanotransduction
Small-molecule-activated degradation domain + transcription factor -> chemically-induced genetic switch.
And though there's still a bit of trial and error to debug which/how those components go together, it's a common enough thing to be reasonably accessible.
Always looking for good work. The field is growing rapidly right now. You've got a good combination of talents to help.