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The cell nucleus harbors a large number of proteins involved in transcription, RNA processing, chromatin remodeling, nuclear signaling, and ribosome assembly. The nuclear genome of the model alga Chlamydomonas reinhardtii P. A. Dang. was recently sequenced, and many genes encoding nuclear proteins, including transcription factors and transcription regulators, have been identified through computational discovery tools. However, elucidating the specific biological roles of nuclear proteins will require support from biochemical and proteomics data. Cellular preparations with enriched nuclei are important to assist in such analyses. Here, we describe a simple protocol for the isolation of nuclei from Chlamydomonas, based on a commercially available kit. The modifications done in the original protocol mainly include alterations of the differential centrifugation parameters and detergent-based cell lysis. The nuclei-enriched fractions obtained with the optimized protocol show low contamination with mitochondrial and plastid proteins. The protocol can be concluded within only 3 h, and the proteins extracted can be used for gel-based and non-gel-based proteomic approaches.
The understanding of environmentally induced changes in the biochemical composition of phytoplankton species is of great importance in both physiological studies and ecological food web research. In extensive laboratory experiments we tested the influence of two different temperatures (10 degrees C and 25 degrees C) and a phosphorus supply gradient on the sterol concentrations of the three freshwater phytoplankton species Scenedesmus quadricauda, Cryptomonas ovata and Cyclotella meneghiniana. The diatom C. meneghiniana was additionally exposed to a silicate gradient. In two separate experiments we analysed (1) possible interactive effects of temperature and phosphorus supply and (2) the effect of four phosphorus levels and three silicate levels on algal sterol concentrations. We observed that sterol concentrations were higher at 25 degrees C than at 10 degrees C in S. quadricauda and C. meneghiniana, but were not affected by temperature in C. ovata. Interactive effects of temperature and phosphorus supply on sterol concentrations were found in C. meneghiniana. This presumably was due to the bioconversion of one sterol (24-methylenecholesterol) into another (22-dihydrobrassicasterol). Increasing phosphorus supply resulted in species-specific effects on sterol concentrations, viz. an optimum curve response in S. quadricauda, a saturation curve response in C. meneghiniana and no change in sterol concentration in C. ovata. Effects of silicate supply on the sterols of C. meneghiniana equalled the effects of phosphorus supply. Albeit we did not observe a general trend in the three phytoplankton species tested, we conclude that sterol concentrations of phytoplankton are strongly affected by temperature and nutrient supply. Interactive effects point out the importance of taking into account more than just one environmental factor when assessing the effects of environmentally induced changes on phytoplankton sterol concentrations.
In most biodiversity studies, taxonomic diversity is the measure for the multiplicity of species and is often considered to represent functional diversity. However, trends in taxonomic diversity and functional diversity may differ, for example, when many functionally similar but taxonomically different species co-occur in a community. The differences between these diversity measures are of particular interest in diversity research for understanding diversity patterns and their underlying mechanisms. We analysed a temporally highly resolved 20-year time series of lake phytoplankton to determine whether taxonomic diversity and functional diversity exhibit similar or contrasting seasonal patterns. We also calculated the functional mean of the community in n-dimensional trait space for each sampling day to gain further insights into the seasonal dynamics of the functional properties of the community. We found an overall weak positive relationship between taxonomic diversity and functional diversity with a distinct seasonal pattern. The two diversity measures showed synchronous behaviour from early spring to mid-summer and a more complex and diverging relationship from autumn to late winter. The functional mean of the community exhibited a recurrent annual pattern with the most prominent changes before and after the clear-water phase. From late autumn to winter, the functional mean of the community and functional diversity were relatively constant while taxonomic diversity declined, suggesting competitive exclusion during this period. A further decline in taxonomic diversity concomitant with increasing functional diversity in late winter to early spring is seen as a result of niche diversification together with competitive exclusion. Under these conditions, several different sets of traits are suitable to thrive, but within one set of functional traits only one, or very few, morphotypes can persist. Taxonomic diversity alone is a weak descriptor of trait diversity in phytoplankton. However, the combined analysis of taxonomic diversity and functional diversity, along with the functional mean of the community, allows for deeper insights into temporal patterns of community assembly and niche diversification.
Introduction Flux phenotypes from different organisms and growth conditions allow better understanding of differential metabolic networks functions. Fluxes of metabolic reactions represent the integrated outcome of transcription, translation, and post-translational modifications, and directly affect growth and fitness. However, fluxes of intracellular metabolic reactions cannot be directly measured, but are estimated via metabolic flux analysis (MFA) that integrates data on isotope labeling patterns of metabolites with metabolic models. While the application of metabolomics technologies in photosynthetic organisms have resulted in unprecedented data from 13CO2-labeling experiments, the bottleneck in flux estimation remains the application of isotopically nonstationary MFA (INST-MFA). INST-MFA entails fitting a (large) system of coupled ordinary differential equations, with metabolite pools and reaction fluxes as parameters. Here, we focus on the Calvin-Benson cycle (CBC) as a key pathway for carbon fixation in photosynthesizing organisms and ask if approaches other than classical INST-MFA can provide reliable estimation of fluxes for reactions comprising this pathway.
Methods First, we show that flux estimation with the labeling patterns of all CBC intermediates can be formulated as a single constrained regression problem, avoiding the need for repeated simulation of time-resolved labeling patterns.
Results We then compare the flux estimates of the simulation-free constrained regression approach with those obtained from the classical INST-MFA based on labeling patterns of metabolites from the microalgae Chlamydomonas reinhardtii, Chlorella sorokiniana and Chlorella ohadii under different growth conditions.
Discussion Our findings indicate that, in data-rich scenarios, simulation-free regression-based approaches provide a suitable alternative for flux estimation from classical INST-MFA since we observe a high qualitative agreement (rs=0.89) to predictions obtained from INCA, a state-of-the-art tool for INST-MFA.