Continuing the scientific theme of adding fluorescent proteins to everything that moves, this time spiders found themselves at the pointy end of the CRISPR-Cas9 injection needle. In a study by researchers at the University of Bayreuth, common house spiders (Parasteatoda tepidariorum) had a gene inserted for a red fluorescent protein in addition to having an existing gene for eye development disabled. This was the first time that spiders have been subjected to this kind of gene-editing study, mostly due to how fiddly they are to handle as well as their genome duplication characteristics.

In the research paper in Angewandte Chemie the methods and results are detailed, with the knock-out approach of the sine oculis (C1) gene being tried first as a proof of concept. The CRISPR solution was injected into the ovaries of female spiders, whose offspring then carried the mutation. With clear deficiencies in eye development observable in this offspring, the researchers moved on to adding the red fluorescent protein gene with another CRISPR solution, which targets the major ampullate gland where the silk is produced.

Ultimately, this research serves to demonstrate that it is possible to not only study spiders in more depth these days using tools like CRISPR-Cas9, but also that it is possible to customize and study spider silk production.

While tools like CRISPR have blown the field of genome hacking wide open, being able to predict what will happen when you tinker with the code underlying the living things on our planet is still tricky. Researchers at Stanford hope their new Evo 2 DNA generative AI tool can help.

Trained on a dataset of over 100,000 organisms from bacteria to humans, the system can quickly determine what mutations contribute to certain diseases and what mutations are mostly harmless. An “area we are hopeful about is using Evo 2 for designing new genetic sequences with specific functions of interest.”

To that end, the system can also generate gene sequences from a starting prompt like any other LLM as well as cross-reference the results to see if the sequence already occurs in nature to aid in predicting what the sequence might do in real life. These synthetic sequences can then be made using CRISPR or similar techniques in the lab for testing. While the prospect of building our own Moya is exciting, we do wonder what possible negative consequences could come from this technology, despite the hand-wavy mention of not training the model on viruses to “to prevent Evo 2 from being used to create new or more dangerous diseases.”

We’ve got you covered if you need to get your own biohacking space setup for DNA gels or if you want to find out more about powering living computers using electricity. If you’re more curious about other interesting uses for machine learning, how about a dolphin translator or discovering better battery materials?