Evidence for positive selection in phycoerythrin genes of red algae and cyanobacteria Prochlorococcus and Synechococcus

Because of the shortage of phycoerythrin (PE) gene sequences from rhodophytes, peBA encoding beta- and alpha-subunits of PE from three species of red algae (Ceramium boydenn, Halymenia sinensis, and Plocamium telfariae) were cloned and sequenced. Different selection forces have affected the evolution of PE lineages. 8.9 % of the codons were subject to positive selection within the PE lineages (excluding high-irradiance adapted Prochlorococcus). More than 40 % of the sites may be under positive selection, and nearly 20 % sites are weakly constraint sites in high-irradiance adapted Prochlorococcus. Sites most likely undergoing positive selection were found in the chromophore binding domains, suggesting that these sites have played important roles in environmental adaptation during PE diversification. Moreover, the heterogeneous distribution of positively selected sites along the PE gene was revealed from the comparison of low-irradiance adapted Prochlorococcus and marine Synechococcus, which firmly suggests that evolutionary patterns of PEs in these two lineages are significantly different.

Comparative molecular population genetics of phycoerythrin locus in Prochlorococcus

As the only remainder type of phycobiliproteins in Prochlorococcus, the actual role of phycoerythrin still remains unknown. Previous studies revealed that two different forms of phycoerythrin gene were found in two ecotypes of Prochlorococcus that are specifically adapted to either high light (HL) or low light (LL) conditions. Here we analyze patterns of phycoerythrin nucleotide variation in the HL- and LL-Prochlorococcus populations. Our analyses reveal a significantly greater number of non-synonymous fixed substitutions in peB and peA than expected based on interspecific comparisons. This pattern of excess non-synonymous fixed substitutions is not seen in other five phycoerythrin-related genes (peZ/V/Y/T/S). Several neutrality statistical tests indicate an excess of rare frequency polymorphisms in the LL-Prochlorococcus data, but an excess of intermediate frequency polymorphisms in the HL-Prochlorococcus data. Distributions of the positively selected sites identified using the likelihood ratio test, when mapped onto the phycoerythrin tertiary structure, reveal that HL- and LL-phycoerythrin should be under different selective patterns. These findings may provide insights into the likely role of selection at the phycoerythrin locus and motivate further research to unveil the function of phycoerythrin in Prochlorococcus.

Diel rhythmicity in amino acid uptake by Prochlorococcus

The marine cyanobacterium Prochlorococcus, the most abundant phototrophic organism on Earth, numerically dominates the phytoplankton in nitrogen (N)-depleted oceanic gyres. Alongside inorganic N sources such as nitrite and ammonium, natural populations of this genus also acquire organic N, specifically amino acids. Here, we investigated using isotopic tracer and flow cytometric cell sorting techniques whether amino acid uptake by Prochlorococcus is subject to a diel rhythmicity, and if so, whether this was linked to a specific cell cycle stage. We observed, in contrast to diurnally similar methionine uptake rates by Synechococcus cells, obvious diurnal rhythms in methionine uptake by Prochlorococcus cells in the tropical Atlantic. These rhythms were confirmed using reproducible cyclostat experiments with a light-synchronized axenic Prochlorococcus (PCC9511 strain) culture and S-35-methionine and H-3-leucine tracers. Cells acquired the tracers at lower rates around dawn and higher rates around dusk despite > 10(4) times higher concentration of ammonium in the medium, presumably because amino acids can be directly incorporated into protein. Leucine uptake rates by cells in the S+G(2) cell cycle stage were consistently 2.2 times higher than those of cells at the G(1) stage. Furthermore, S+G(2) cells upregulated amino acid uptake 3.5 times from dawn to dusk to boost protein synthesis prior to cell division. Because Prochlorococcus populations can account from 13% at midday to 42% at dusk of total microbial uptake of methionine and probably of other amino acids in N-depleted oceanic waters, this genus exerts diurnally variable, strong competitive pressure on other bacterioplankton populations.

Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus in the eastern Mediterranean Sea in March and April 2008 during SES_GR1

The dataset is based on samples collected in the framework of the project SESAME, in the Ionian, Libyan and Aegean Sea during March- April 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson).

Abundance and Biomass from heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus in the eastern Mediteranean Sea in October 2008 during SES_GR2

The HCMR_SES_LAGRANGIAN_GR2_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during October 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Heterotrophic Nanoflagellate abundance: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6?m and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Ciliate abundance: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Heterotrophic bacteria, Synechococcus, Prochlorococcus bacteria: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Abundance data were converted into C biomass using 250 fgC cell-1 (Kana & Glibert 1987) for Synechococcus, 50 fgC cell-1 (Campbell et al. 1994) for Prochlorococcus and 20fgC cell-1 (Lee & Fuhrman 1987) for heterotrophic bacteria. Heterotrophic Nanoflagellate biomass: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Abundance data were converted into C biomass using 183 fgC µm**3 (Caron et al. 1995). Ciliate biomass: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae using image analysis. For biomass estimation, the conversion factor 190 fgC µm**3 was used (Putt and Stoecker 1989).

Abundance and Biomass from heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus in the Aegean Sea in April 2008 during SES_GR1

The HCMR_SES_LAGRANGIAN_GR1_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during April 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Heterotrophic Nanoflagellate abundance: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Ciliate abundance: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Heterotrophic bacteria, Synechococcus, Prochlorococcus biomass: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Abundance data were converted into C biomass using 250 fgC cell-1 (Kana & Glibert 1987) for Synechococcus, 50 fgC cell-1 (Campbell et al. 1994) for Prochlorococcus and 20fgC cell-1 (Lee & Fuhrman 1987) for heterotrophic bacteria. Heterotrophic Nanoflagellate biomass: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Abundance data were converted into C biomass using 183 fgC µm**3 (Caron et al. 1995). Ciliate biomass: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae using image analysis. For biomass estimation, the conversion factor 190 fgC µm**3 was used (Putt and Stoecker 1989).

Comparative Analysis of Fatty Acid Desaturases in Cyanobacterial Genomes

Fatty acid desaturases are enzymes that introduce double bonds into the hydrocarbon chains of fatty acids. The fatty acid desaturases from 37 cyanobacterial genomes were identified and classified based upon their conserved histidine-rich motifs and phylogenetic analysis, which help to determine the amounts and distributions of desaturases in cyanobacterial species. The filamentous or N-2-fixing cyanobacteria usually possess more types of fatty acid desaturases than that of unicellular species. The pathway of acyl-lipid desaturation for unicellular marine cyanobacteria Synechococcus and Prochlorococcus differs from that of other cyanobacteria, indicating different phylogenetic histories of the two genera from other cyanobacteria isolated from freshwater, soil, or symbiont. Strain Gloeobacter violaceus PCC 7421 was isolated from calcareous rock and lacks thylakoid membranes. The types and amounts of desaturases of this strain are distinct to those of other cyanobacteria, reflecting the earliest divergence of it from the cyanobacterial line. Three thermophilic unicellular strains, Thermosynechococcus elongatus BP-1 and two Synechococcus Yellowstone species, lack highly unsaturated fatty acids in lipids and contain only one Delta 9 desaturase in contrast with mesophilic strains, which is probably due to their thermic habitats. Thus, the amounts and types of fatty acid desaturases are various among different cyanobacterial species, which may result from the adaption to environments in evolution. Copyright (c) 2008 Xiaoyuan Chi et al.