Wide range of metabolic adaptations to the acquisition of the Calvin cycle revealed by comparison of microbial genomes is published in PLoS Computational Biology.
In this computational work, Johannes found one thousand non-cyanobacterial genomes containing the Calvin cycle, and compared them to close relatives that lacked the Calvin cycle. We wondered how bacteria integrate a newly-acquired Calvin cycle into their metabolism. Using multiple analyses, including a machine learning algorithm, he found some key differences in the abundance of genes and protein family domains between these two groups. The software he developed for this analysis is RedMAGPIE, for "Reductive pentose phosphate pathway Machine-Assisted Genomic Pattern Identification and Evaluation." Perhaps most interesting are genes and protein domains of unknown function that were revealed to be of high importance. Some of these likely play a role in regulating the Calvin cycle, and could be targets for metabolic engineering.
RedMAGPIE ranks genetic adaptations to the Calvin cycle to construct a recipe for an autotrophic microbe.