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Factors influencing the diversity of iron uptake systems in aquatic microorganisms.

Desai DK, Desai FD, Laroche J - Front Microbiol (2012)

Bottom Line: A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems.Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches.Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).

View Article: PubMed Central - PubMed

Affiliation: Biological Oceanography Division, Helmholtz-Zentrum für Ozeanforschung Kiel (GEOMAR) Kiel, Germany.

ABSTRACT
Iron (Fe) is an essential micronutrient for many processes in all living cells. Dissolved Fe (dFe) concentrations in the ocean are of the order of a few nM, and Fe is often a factor limiting primary production. Bioavailability of Fe in aquatic environments is believed to be primarily controlled through chelation by Fe-binding ligands. Marine microbes have evolved different mechanisms to cope with the scarcity of bioavailable dFe. Gradients in dFe concentrations and diversity of the Fe-ligand pool from coastal to open ocean waters have presumably imposed selection pressures that should be reflected in the genomes of microbial communities inhabiting the pelagic realm. We applied a hidden Markov model (HMM)-based search for proteins related to cellular iron metabolism, and in particular those involved in Fe uptake mechanisms in 164 microbial genomes belonging to diverse taxa and occupying different aquatic niches. A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems. Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches. Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).

No MeSH data available.


Phylogenetic trees of (A) RhbA, (B) RhbB, and (C) RhtX protein sequences from Open Ocean picocyanobacteria and eukaryotic phytoplankton recovered in our study. The tree was constructed using a Neighbor-Joining method, using the Jukes–Cantor correction and a bootstrap test was conducted with 1000 replicates. The scale bar represents 100% estimated sequence divergence.
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Figure 2: Phylogenetic trees of (A) RhbA, (B) RhbB, and (C) RhtX protein sequences from Open Ocean picocyanobacteria and eukaryotic phytoplankton recovered in our study. The tree was constructed using a Neighbor-Joining method, using the Jukes–Cantor correction and a bootstrap test was conducted with 1000 replicates. The scale bar represents 100% estimated sequence divergence.

Mentions: Recent surveys involving searches of NIS components represented by PFAM domains AlcB (Acetyl transferase) and IucA_IucC (siderophore synthetase for Aerobactin) suggest that none of the eukaryotic phytoplankton and only around 4% of marine picocyanobacteria possess this system (Hopkinson and Morel, 2009; Hopkinson and Barbeau, 2012). Here our HMM search utilized a more extensive set of NIS proteins involved in the biosynthesis of aerobactin, desferrioxamine, and rhizobactin 1021 siderophores (Challis, 2005; Table 1). NRPS was detected in picocyanobacteria P. marinus MIT9303 and NRPS along with the NIS component RhbB (a PLP dependent decarboxylase) were detected in P. marinus MIT 9303 and MIT 9313. It is possible that the high specificity of our HMM-ModE models led to a slight drop in sensitivity. To confirm whether the other components of this pathway were indeed present in the phototrophic genomes and were being missed due to this lowered sensitivity of HMM-ModE, we used the Search Tool for Interacting Genes/Proteins (STRING) database (Szklarczyk et al., 2011). For a given query sequence, this database identifies a set of proteins that repeatedly co-occur with the query in the genomes of many different organisms. In addition to P. marinus MIT9303 and MIT9313, using the S. meliloti RhbB sequence as the query, the STRING database showed the co-occurrence of RhbB and RhbA (diaminobutyrate aminotransferase involved in rhizobactin biosynthesis) in P. marinus CCMP1375, NATL1A, CCMP1986, MIT9211, MIT9515, MIT9215, MIT9312, NATL2A, AS9601, and MIT9301. A corresponding siderophore uptake gene was not detected in the Prochlorococcus genomes. Our profiles detected a putative gene for NRPS in eukaryotic phytoplankton A. anophagefferens, E. huxleyi, O. tauri, P. tricornutum, and T. pseudonana, and the NIS component RhbB in E. huxleyi, F. cylindrus, and O. lucimarinus. Using the STRING database we detected genes similar to rhizobactin biosynthesis components RhbA and RhbB in O. tauri, O. lucimarinus, T. pseudonana, and P. tricornutum along with RhtX, a special permease involved in the uptake of rhizobactin 1021. The sequences identified as RhbA, RhbB, and RhtX from these genomes shared 48.18, 35.48, and 30% identity at the protein level within each group, respectively. A neighbor-joining tree calculated from the multiple sequence alignments of these sequences showed a higher similarity of the Freshwater organisms with the Sinorhizobium genes while the eukaryotic sequences clustered with the Prochlorococcus sequences (Figure 2). We also detected the NRPS as well as NIS components in the metagenomes, though their abundances were low (Figure 1B).


Factors influencing the diversity of iron uptake systems in aquatic microorganisms.

Desai DK, Desai FD, Laroche J - Front Microbiol (2012)

Phylogenetic trees of (A) RhbA, (B) RhbB, and (C) RhtX protein sequences from Open Ocean picocyanobacteria and eukaryotic phytoplankton recovered in our study. The tree was constructed using a Neighbor-Joining method, using the Jukes–Cantor correction and a bootstrap test was conducted with 1000 replicates. The scale bar represents 100% estimated sequence divergence.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475125&req=5

Figure 2: Phylogenetic trees of (A) RhbA, (B) RhbB, and (C) RhtX protein sequences from Open Ocean picocyanobacteria and eukaryotic phytoplankton recovered in our study. The tree was constructed using a Neighbor-Joining method, using the Jukes–Cantor correction and a bootstrap test was conducted with 1000 replicates. The scale bar represents 100% estimated sequence divergence.
Mentions: Recent surveys involving searches of NIS components represented by PFAM domains AlcB (Acetyl transferase) and IucA_IucC (siderophore synthetase for Aerobactin) suggest that none of the eukaryotic phytoplankton and only around 4% of marine picocyanobacteria possess this system (Hopkinson and Morel, 2009; Hopkinson and Barbeau, 2012). Here our HMM search utilized a more extensive set of NIS proteins involved in the biosynthesis of aerobactin, desferrioxamine, and rhizobactin 1021 siderophores (Challis, 2005; Table 1). NRPS was detected in picocyanobacteria P. marinus MIT9303 and NRPS along with the NIS component RhbB (a PLP dependent decarboxylase) were detected in P. marinus MIT 9303 and MIT 9313. It is possible that the high specificity of our HMM-ModE models led to a slight drop in sensitivity. To confirm whether the other components of this pathway were indeed present in the phototrophic genomes and were being missed due to this lowered sensitivity of HMM-ModE, we used the Search Tool for Interacting Genes/Proteins (STRING) database (Szklarczyk et al., 2011). For a given query sequence, this database identifies a set of proteins that repeatedly co-occur with the query in the genomes of many different organisms. In addition to P. marinus MIT9303 and MIT9313, using the S. meliloti RhbB sequence as the query, the STRING database showed the co-occurrence of RhbB and RhbA (diaminobutyrate aminotransferase involved in rhizobactin biosynthesis) in P. marinus CCMP1375, NATL1A, CCMP1986, MIT9211, MIT9515, MIT9215, MIT9312, NATL2A, AS9601, and MIT9301. A corresponding siderophore uptake gene was not detected in the Prochlorococcus genomes. Our profiles detected a putative gene for NRPS in eukaryotic phytoplankton A. anophagefferens, E. huxleyi, O. tauri, P. tricornutum, and T. pseudonana, and the NIS component RhbB in E. huxleyi, F. cylindrus, and O. lucimarinus. Using the STRING database we detected genes similar to rhizobactin biosynthesis components RhbA and RhbB in O. tauri, O. lucimarinus, T. pseudonana, and P. tricornutum along with RhtX, a special permease involved in the uptake of rhizobactin 1021. The sequences identified as RhbA, RhbB, and RhtX from these genomes shared 48.18, 35.48, and 30% identity at the protein level within each group, respectively. A neighbor-joining tree calculated from the multiple sequence alignments of these sequences showed a higher similarity of the Freshwater organisms with the Sinorhizobium genes while the eukaryotic sequences clustered with the Prochlorococcus sequences (Figure 2). We also detected the NRPS as well as NIS components in the metagenomes, though their abundances were low (Figure 1B).

Bottom Line: A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems.Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches.Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).

View Article: PubMed Central - PubMed

Affiliation: Biological Oceanography Division, Helmholtz-Zentrum für Ozeanforschung Kiel (GEOMAR) Kiel, Germany.

ABSTRACT
Iron (Fe) is an essential micronutrient for many processes in all living cells. Dissolved Fe (dFe) concentrations in the ocean are of the order of a few nM, and Fe is often a factor limiting primary production. Bioavailability of Fe in aquatic environments is believed to be primarily controlled through chelation by Fe-binding ligands. Marine microbes have evolved different mechanisms to cope with the scarcity of bioavailable dFe. Gradients in dFe concentrations and diversity of the Fe-ligand pool from coastal to open ocean waters have presumably imposed selection pressures that should be reflected in the genomes of microbial communities inhabiting the pelagic realm. We applied a hidden Markov model (HMM)-based search for proteins related to cellular iron metabolism, and in particular those involved in Fe uptake mechanisms in 164 microbial genomes belonging to diverse taxa and occupying different aquatic niches. A multivariate statistical approach demonstrated that in phototrophic organisms, there is a clear influence of the ecological niche on the diversity of Fe uptake systems. Extending the analyses to the metagenome database from the Global Ocean Sampling expedition, we demonstrated that the Fe uptake and homeostasis mechanisms differed significantly across marine niches defined by temperatures and dFe concentrations, and that this difference was linked to the distribution of microbial taxa in these niches. Using the dN/dS ratios (which signify the rate of non-synonymous mutations) of the nucleotide sequences, we identified that genes encoding for TonB, Ferritin, Ferric reductase, IdiA, ZupT, and Fe(2+) transport proteins FeoA and FeoB were evolving at a faster rate (positive selection pressure) while genes encoding ferrisiderophore, heme and Vitamin B12 uptake systems, siderophore biosynthesis, and IsiA and IsiB were under purifying selection pressure (evolving slowly).

No MeSH data available.