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As part of their iGEM 2014 project, Team University of Pennsylvania characterized a fascinating and underused organism: Magnetospirillum magneticum (AMB-1), a bacterium that aligns with magnetic fields. By developing, testing, and optimizing protocols for its growth and transformation, and then making them easily accessible in a convenient Strain Spec Sheet, they tried to establish AMB-1 as an easily engineered organism.
As part of their human practices, they contacted other iGEM teams participating that year to compile characterization and protocols data if they were working with unconventional organisms too. They designed a “biological chassis specification sheet” that contained necessary information and protocols for the successful growth and engineering of the organisms.
With very similar ideas and intentions, and much bigger ambition, we created an open source database of characterization and protocols data for unconventional chassis organisms.
The blueprint of the data collected for each chassis entry is as given below.

• Scientific name (genus, species, and strain) and taxonomy
• Biosafety level
• A description of what makes the host special for synthetic biology applications.
• Genotype
• Growth characteristics
• Culture sources for obtaining the organism
• Maintenance protocols
• Transformation protocols
• Other protocols
• Biobrick parts for this organism
• Vectors for the organism
• Metabolic models
• Genome sequence

We’ve tried to keep it compact yet comprehensive, taking feedback from the stakeholders, people who’ve worked with new chassis and filled data on the database.
In an effort to make our database a one-stop solution to working with chassis, we added tools that can help in working with the biochemical and genomics of the chassis. We plan to develop an assortment of tools to make it easier to work with a new chassis.
Currently, our biggest tool achievement has been the development of an interactive codon optimizer which can be used to manually edit the optimized sequence to remove restriction sites or reduce GC content, using a drop-down menu that shows codons that can be used to replace the current codon without changing the amino acid.
In the future, we plan to develop more chassis tools such as those for genome analysis and metabolic simulations.
Thus, we improved on University of Pennsylvania Team’s idea of creating “biological chassis specification sheet” and turned it into a much bigger version with multiple useful tools for engineering them.