Red, Cryptomonad and Glaucocystophyte Algal Phycobiliproteins

Efficient Green Light Acclimation of the Green Algae Picochlorum sp. Triggering Geranylgeranylated Chlorophylls

In analogy to higher plants, eukaryotic microalgae are thought to be incapable of utilizing green light for growth, due to the “green gap” in the absorbance profiles of their photosynthetic pigments. This study demonstrates, that the marine chlorophyte Picochlorum sp. is able to grow efficiently under green light emitting diode (LED) illumination. Picochlorum sp. growth and pigment profiles under blue, red, green and white LED illumination (light intensity: 50–200 μmol m⁻² s⁻¹) in bottom-lightened shake flask cultures were evaluated. Green light-treated cultures showed a prolonged initial growth lag phase of one to 2 days, which was subsequently compensated to obtain comparable biomass yields to red and white light controls (approx. 0.8 g_DW L⁻¹). Interestingly, growth and final biomass yields of the green light-treated sample were higher than under blue light with equivalent illumination energies. Further, pigment analysis indicated, that during green light illumination, Picochlorum sp. formed unknown pigments (X1-X4). Pigment concentrations increased with illumination intensity and were most abundant during the exponential growth phase. Mass spectrometry and nuclear magnetic resonance data indicated, that pigments X1-X2 and X3-X4 are derivatives of chlorophyll b and a, which harbor C=C bonds in the phytol side chain similar to geranylgeranylated chlorophylls. Thus, for the first time, the natural accumulation of large pools (approx. 12 mg g_DW⁻¹) of chlorophyll intermediates with incomplete hydrogenation of their phytyl chains is demonstrated for algae under monochromatic green light (Peak λ 510 nm, full width at half maximum 91 nm). The ability to utilize green light offers competitive advantages for enhancing biomass production, particularly under conditions of dense cultures, long light pathways and high light intensity. Green light acclimation for an eukaryotic microalgae in conjunction with the formation of new aberrant geranylgeranylated chlorophylls and high efficiency of growth rates are novel for eukaryotic microalgae. Illumination with green light could enhance productivity in industrial processes and trigger the formation of new metabolites–thus, underlying mechanisms require further investigation.

The supramolecular architecture, function, and regulation of thylakoid membranes in red algae: an overview

Red algae are a group of eukaryotic photosynthetic organisms. Phycobilisomes (PBSs), which are composed of various types of phycobiliproteins and linker polypeptides, are the main light-harvesting antennae in red algae, as in cyanobacteria. Two morphological types of PBSs, hemispherical- and hemidiscoidal-shaped, are found in different red algae species. PBSs harvest solar energy and efficiently transfer it to photosystem II (PS II) and finally to photosystem I (PS I). The PS I of red algae uses light-harvesting complex of PS I (LHC I) as a light-harvesting antennae, which is phylogenetically related to the LHC I found in higher plants. PBSs, PS II, and PS I are all distributed throughout the entire thylakoid membrane, a pattern that is different from the one found in higher plants. Photosynthesis processes, especially those of the light reactions, are carried out by the supramolecular complexes located in/on the thylakoid membranes. Here, the supramolecular architecture, function and regulation of thylakoid membranes in red algal are reviewed.

Predicting protein interaction interfaces from protein sequences: case studies of subtilisin and phycocyanin

Identification of protein interaction interfaces is very important for understanding the molecular mechanisms underlying biological phenomena. Here, we present a novel method for predicting protein interaction interfaces from sequences by using PAM matrix (PIFPAM). Sequence alignments for interacting proteins were constructed and parsed into segments using sliding windows. By calculating distance matrix for each segment, the correlation coefficients between segments were estimated. The interaction interfaces were predicted by extracting highly correlated segment pairs from the correlation map. The predictions achieved an accuracy 0.41-0.71 for eight intraprotein interaction examples, and 0.07-0.60 for four interprotein interaction examples. Compared with three previously published methods, PIFPAM predicted more contacting site pairs for 11 out of the 12 example proteins, and predicted at least 34% more contacting site pairs for eight proteins of them. The factors affecting the predictions were also analyzed. Since PIFPAM uses only the alignments of the two interacting proteins as input, it is especially useful when no three-dimensional protein structure data are available.