DNA2.0 partners with Newcastle U on B. subtillis system

MENLO PARK, Calif.—DNA2.0 last month announced acollaboration with Newcastle University to develop a protein expression systemfor Bacillus subtillis, with DNA2.0'sGeneGPS gene optimization technology serving as the basis for the developmentof enhanced gene synthesis algorithms for the bacterium.

The system will further the work of NewCastle Centre forBacterial Cell Biology and School of Computing Science Prof. Anil Wipat on thesynthetic biology applications of B. subtillis, the chief production host for industrial enzyme manufacturing and adominant bacterial workhorse for microbial fermentations.

Industrial applications include production of amylases,proteases, inosine, ribosides and amino acids. The organism, which isconsidered safe for humans, is also key to the production of soya-based nattoproduction in Japan. The understanding of the molecular biology and physiologyof this important gram-positive model organism is second only to Escherichiacoli. This makes B. subtillis an ideal host for industrial synthetic biology.

"Professor Wipat's lab at Newcastle is producing some of themost important research in synthetic biology today, and we are excited to becollaborating with him," said Dr. Jeremy Minshull, cofounder and CEO of DNA2.0,in a press release. "By combining our patented GeneGPS technology—which hasbeen proven to increase protein expression up to 100-fold—with Newcastle's deepexperience with B. subtillis, I'mconfident that we will develop a best-in-class solution for this importantbacterium for industrial biotechnology."

In addition to developing a robust expression system for B.subtillis, the two organizations expect that the gene design algorithms thatthey develop will be likely to mimic related gram positives that are also verypopular in industrial biotechnology. Industrially important organisms such as Clostridium,Lactobacillus and Geobacillus share similarities with B. subtilis in their development and genetics. As a result, theknowledge gained from optimizing expression for this organism promises to bemore widely applicable in an industrial context, according to the partners.