Abstract
Background: To fully exploit the potential of microalgae as commercial green hosts, the scientific community has to improve their understanding of these organisms from a systems biology perspective. Compared to other model organisms, our genomic knowledge of the microalgae model species Chlamydomonas reinhardtii is very limited. Currently, almost 90% of the functional annotated proteins of C. reinhardtii and of other microalgal proteins are homologs of Arabidopsis thaliana proteins, which suggests that for the most part only the metabolic core conserved between these species is properly annotated.
Objective: This review highlights how proteins outside of this core can be annotated by applying publically available tools and methods. These include the use of novel state-of-the-art prediction tools, combinations of these tools, and the use of metabolic modeling-assisted functional annotation. Furthermore, we discuss the need for data on the subcellular location of microalgal proteins. Finally, some remaining bottlenecks regarding functional annotation of microalgal proteins are discussed.
Conclusion: We conclude that both large dry-lab and wet-lab efforts are required to generate reliable functional annotations of microalgae.
Keywords: Microalgae, bioinformatics, systems biology, annotation, genomics, proteomics, protein function.
Graphical Abstract