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The diversity of cyanobacterial metabolism: genome analysis of multiple phototrophic microorganisms.

Beck C, Knoop H, Axmann IM, Steuer R - BMC Genomics (2012)

Bottom Line: We describe genetic diversity found within cyanobacterial genomes, specifically with respect to metabolic functionality.Our results have direct implications for resource allocation and further sequencing projects.It can be extrapolated that the number of newly identified genes still significantly increases with increasing number of new sequenced genomes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Theoretical Biology, Humboldt-University of Berlin, Invalidenstr, 43, D-10115 Berlin, Germany.

ABSTRACT

Background: Cyanobacteria are among the most abundant organisms on Earth and represent one of the oldest and most widespread clades known in modern phylogenetics. As the only known prokaryotes capable of oxygenic photosynthesis, cyanobacteria are considered to be a promising resource for renewable fuels and natural products. Our efforts to harness the sun's energy using cyanobacteria would greatly benefit from an increased understanding of the genomic diversity across multiple cyanobacterial strains. In this respect, the advent of novel sequencing techniques and the availability of several cyanobacterial genomes offers new opportunities for understanding microbial diversity and metabolic organization and evolution in diverse environments.

Results: Here, we report a whole genome comparison of multiple phototrophic cyanobacteria. We describe genetic diversity found within cyanobacterial genomes, specifically with respect to metabolic functionality. Our results are based on pair-wise comparison of protein sequences and concomitant construction of clusters of likely ortholog genes. We differentiate between core, shared and unique genes and show that the majority of genes are associated with a single genome. In contrast, genes with metabolic function are strongly overrepresented within the core genome that is common to all considered strains. The analysis of metabolic diversity within core carbon metabolism reveals parts of the metabolic networks that are highly conserved, as well as highly fragmented pathways.

Conclusions: Our results have direct implications for resource allocation and further sequencing projects. It can be extrapolated that the number of newly identified genes still significantly increases with increasing number of new sequenced genomes. Furthermore, genome analysis of multiple phototrophic strains allows us to obtain a detailed picture of metabolic diversity that can serve as a starting point for biotechnological applications and automated metabolic reconstructions.

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Number of genes per cluster of likely ortholog genes (CLOGs). The majority of CLOGs consist of only one gene. CLOGs with 16 genes, indicated by the vertical line, are overrepresented. Only few clusters consist of more than 16 genes and almost no cluster consists of more than 32 genes.
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Figure 1: Number of genes per cluster of likely ortholog genes (CLOGs). The majority of CLOGs consist of only one gene. CLOGs with 16 genes, indicated by the vertical line, are overrepresented. Only few clusters consist of more than 16 genes and almost no cluster consists of more than 32 genes.

Mentions: Our algorithm results in 21238 distinct clusters of likely ortholog genes (CLOGs), distributed across all 16 strains (data in Additional File 1). Figure 1 shows a histogram of the number of assigned genes per CLOG. The majority of clusters, almost 60%, consists of a single gene (singletons), whereas only a small number of clusters have more than 30 or 40 members. CLOGs with exactly 16 members are overrepresented, indictated in Figure 1 by a vertical line. Overall, the distribution differs slightly from the results provided in the COG database [12,18]. Therein, considering only the two cyanobacterial strains (Syn6803 and Nos7120) included in the database, clusters of ortholog genes tend to be comprised of more genes, often including multiple genes from the same strain.


The diversity of cyanobacterial metabolism: genome analysis of multiple phototrophic microorganisms.

Beck C, Knoop H, Axmann IM, Steuer R - BMC Genomics (2012)

Number of genes per cluster of likely ortholog genes (CLOGs). The majority of CLOGs consist of only one gene. CLOGs with 16 genes, indicated by the vertical line, are overrepresented. Only few clusters consist of more than 16 genes and almost no cluster consists of more than 32 genes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3369817&req=5

Figure 1: Number of genes per cluster of likely ortholog genes (CLOGs). The majority of CLOGs consist of only one gene. CLOGs with 16 genes, indicated by the vertical line, are overrepresented. Only few clusters consist of more than 16 genes and almost no cluster consists of more than 32 genes.
Mentions: Our algorithm results in 21238 distinct clusters of likely ortholog genes (CLOGs), distributed across all 16 strains (data in Additional File 1). Figure 1 shows a histogram of the number of assigned genes per CLOG. The majority of clusters, almost 60%, consists of a single gene (singletons), whereas only a small number of clusters have more than 30 or 40 members. CLOGs with exactly 16 members are overrepresented, indictated in Figure 1 by a vertical line. Overall, the distribution differs slightly from the results provided in the COG database [12,18]. Therein, considering only the two cyanobacterial strains (Syn6803 and Nos7120) included in the database, clusters of ortholog genes tend to be comprised of more genes, often including multiple genes from the same strain.

Bottom Line: We describe genetic diversity found within cyanobacterial genomes, specifically with respect to metabolic functionality.Our results have direct implications for resource allocation and further sequencing projects.It can be extrapolated that the number of newly identified genes still significantly increases with increasing number of new sequenced genomes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Theoretical Biology, Humboldt-University of Berlin, Invalidenstr, 43, D-10115 Berlin, Germany.

ABSTRACT

Background: Cyanobacteria are among the most abundant organisms on Earth and represent one of the oldest and most widespread clades known in modern phylogenetics. As the only known prokaryotes capable of oxygenic photosynthesis, cyanobacteria are considered to be a promising resource for renewable fuels and natural products. Our efforts to harness the sun's energy using cyanobacteria would greatly benefit from an increased understanding of the genomic diversity across multiple cyanobacterial strains. In this respect, the advent of novel sequencing techniques and the availability of several cyanobacterial genomes offers new opportunities for understanding microbial diversity and metabolic organization and evolution in diverse environments.

Results: Here, we report a whole genome comparison of multiple phototrophic cyanobacteria. We describe genetic diversity found within cyanobacterial genomes, specifically with respect to metabolic functionality. Our results are based on pair-wise comparison of protein sequences and concomitant construction of clusters of likely ortholog genes. We differentiate between core, shared and unique genes and show that the majority of genes are associated with a single genome. In contrast, genes with metabolic function are strongly overrepresented within the core genome that is common to all considered strains. The analysis of metabolic diversity within core carbon metabolism reveals parts of the metabolic networks that are highly conserved, as well as highly fragmented pathways.

Conclusions: Our results have direct implications for resource allocation and further sequencing projects. It can be extrapolated that the number of newly identified genes still significantly increases with increasing number of new sequenced genomes. Furthermore, genome analysis of multiple phototrophic strains allows us to obtain a detailed picture of metabolic diversity that can serve as a starting point for biotechnological applications and automated metabolic reconstructions.

Show MeSH
Related in: MedlinePlus