The unicellular green alga Chlamydomonas reinhardtii
(for brevity, in the following referred to as Chlamydomonas) is an important eukaryotic model organism for the study of photosynthesis and chloroplast development in higher plants as well as flagella development and other cellular processes, and has recently attracted substantial interest in the context of bio-fuel and hydrogen production [1
]. Because of its unique evolutionary position – it diverged from land-plants over a billion years ago – the genome and its gene catalogue have received much attention, especially since the recent publication of the draft genome [2
]. The genome of Chlamydomonas currently (version 3.1) contains about 14,500 protein-coding genes. Additionally, the mitochondrial and plastid genomes have been fully sequenced.
Although the Chlamydomonas genome is far from being completely annotated, e.g., there are more than 150,000 alternative gene models of unclear validity available in addition to the currently annotated genes, there is a fast growing need for a better understanding of the functional aspects of Chlamydomonas. Especially in the context of metabolic network analysis, missing enzymes have to be identified, so that a fully functional network can be obtained. Such demands can best be met by an integrated Systems Biology approach, which typically includes several 'Omics' technologies combined with bioinformatics and modelling methods.
Biochemical pathway maps composed of genes, proteins, and metabolites are powerful reference models for the compilation and presentation of information derived from genomic datasets [3
]. Currently, several Chlamydomonas-related web resources are available including the JGI genome browser [4
], the website of the Chlamydomonas consortium [2
], a database for small RNAs [5
] and the new, jointly developed ChlamyBase portal [6
]. But none of these Chlamydomonas-related databases or web resources listed above is capable of visualizing functional genomics data (e.g. expression data obtained by microarray analysis or proteomics) within the context of Chlamydomonas-specific biological pathways and reactions. Chlamydomonas metabolic pathway information, albeit incomplete, is currently only available from the KEGG [7
] database. Tools such as PathExpress [8
] and KEGG-spider [9
] provide the possibility to visualize gene expression data in the context of KEGG-based pathways, sub-pathways, and metabolites. Alternatively, MapMan is a visualization platform that has been developed for the display of metabolite and transcript data onto metabolic pathways of Arabidopsis and other plant genomes [10
] and thus features a special emphasis on plant-specific pathways.
In the post-genomic era of modern high-throughput technologies, sophisticated computational biology tools are essential to integrate the increasing amount of experimental data generated from experimental systems biology studies such as genomics, transcriptomics, proteomics, and metabolomics, for a comprehensive representation of cellular processes on all levels of molecular organization. The Pathway Tools software [15
] together with the MetaCyc database [16
] is a well-established method to annotate and curate high-throughput biological data in the context of metabolic pathways, gene regulation, and genomic sequences. It allows the automated generation of so-called Pathway/Genome databases (PGDBs) through functional assignment of genes and manual curation of pathways using a graphical user interface. MetaCyc consists of pathways, reactions, enzymes and metabolites together with literature information from more than 600 species, ranging from microbes to plants and human [17
]. To date, several PGDBs have been created for plants species, e.g., AraCyc (Arabidopsis thaliana
], RiceCyc (Rice) [19
], MedicCyc (Medicago trunculata
], or the newly established PlantCyc database [21
], a comprehensive plant biochemical pathway database, but up to now no PGDB for algae or related species has been developed.
ChlamyCyc is a model-organism specific, web-accessible pathway/genome database and web-portal [22
] that was developed as part of the German Systems Biology research initiative GoFORSYS (Golm FORschungseinheit SYStembiologie) [23
], a systems biology approach towards the study of photosynthesis and its regulation in response to selected environmental factors in the model algal system Chlamydomonas. ChlamyCyc serves as the central data repository and data analysis and visualization platform of cellular processes and molecular responses in Chlamydomonas within the GoFORSYS project. The integration with genome databases such as JGI [24
], PlantGDB [25
] and Genbank, as well as cross-links to secondary databases and annotation tools like PlntTFDB [26
], ProMEX [27
], Quantprime [28
], MapMan [10
] further increases the utility of the ChlamyCyc web-portal.