Peptide-mediated nanoengineering of inorganic particle surfaces: a general route toward surface functionalization via peptide adhesion domains.

The peptide-mediated functionalization of inorganic particle surfaces is demonstrated on gadolinium oxide (GdO) particles, revealing specific means to functionalize nano- or microparticles. Phage display screening is exploited to select 12mer peptides, which exhibit sequence-specific adhesion onto surfaces of GdO particles. These peptide adhesion domains are exploited to effectively decorate GdO particles with fluorescently labeled poly(ethylene oxide) (PEO), proving to result in a stable surface modification as shown by significant reduction of protein adsorption by 80%, compared to nonfunctionalized particles. Peptide adhesion and stability of the noncovalent coating are investigated by adsorption/elution experiments and Langmuir isotherms. Fluorescence microscopy, contact angle, and energy dispersive X-ray (EDX) measurements confirmed the sequence specificity of the interactions by comparing adhesion sequences with scrambled peptide sequences. Noncovalent, but specific modification of inorganic particle surfaces represents a generic strategy to modulate functionality and function of nano- or microparticle surfaces.

Targeted proteomics for Chlamydomonas reinhardtii combined with rapid subcellular protein fractionation, metabolomics and metabolic flux analyses.

In the era of fast genome sequencing a critical goal is to develop genome-wide quantitative molecular approaches. Here, we present a metaproteogenomic strategy to integrate proteomics and metabolomics data for systems level analysis in the recently sequenced unicellular green algae Chlamydomonas reinhardtii. To achieve a representative proteome coverage we analysed different growth conditions with protein prefractionation and shotgun proteomics. For protein identification, different genome annotations as well as new gene model predictions with stringent peptide filter criteria were used. An overlapping proteome coverage of 25%, consistent for all databases, was determined. The data are stored in a public mass spectral reference database ProMEX (http://www.promexdb.org/home.shtml). A set of proteotypic peptides comprising Calvin cycle, photosynthetic apparatus, starch synthesis, glycolysis, TCA cycle, carbon concentrating mechanisms (CCM) and other pathways was selected from this database for targeted proteomics (Mass Western). Rapid subcellular fractionation in combination with targeted proteomics allowed for measuring subcellular protein concentrations in attomole per 1000 cells. From the same samples metabolite concentrations and metabolic fluxes by stable isotope incorporation were analyzed. Differences were found in the growth-dependent crosstalk of chloroplastidic and mitochondrial metabolism. A Mass Western survey of all detectable carbonic anhydrases partially involved in carbon-concentrating mechanism (CCM) revealed highest internal cell concentrations for a specific low-CO2-inducible mitochondrial CAH isoform. This indicates its role as one of the strongest CO2-responsive proteins in the crosstalk of air-adapted mixotrophic chloroplast and mitochondrial metabolism in Chlamydomonas reinhardtii.

An automated GCxGC-TOF-MS protocol for batch-wise extraction and alignment of mass isotopomer matrixes from differential 13C-labelling experiments: a case study for photoautotrophic-mixotrophic grown Chlamydomonas reinhardtii cells.

Two dimensional gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOF-MS) is a promising technique to overcome limits of complex metabolome analysis using one dimensional GC-TOF-MS. Especially at the stage of data export and data mining, however, convenient procedures to cope with the complexity of GCxGC-TOF-MS data are still in development. Here, we present a high sample throughput protocol exploiting first and second retention index for spectral library search and subsequent construction of a high dimensional data matrix useful for statistical analysis. The method was applied to the analysis of (13)C-labelling experiments in the unicellular green alga Chlamydomonas reinhardtii. We developed a rapid sampling and extraction procedure for Chlamydomonas reinhardtii laboratory strain (CC503), a cell wall deficient mutant. By testing all published quenching protocols we observed dramatic metabolite leakage rates for certain metabolites. To circumvent metabolite leakage, samples were directly quenched and analyzed without separation of the medium. The growth medium was adapted to this rapid sampling protocol to avoid interference with GCxGC-TOF-MS analysis. To analyse batches of samples a new software tool, MetMax, was implemented which extracts the isotopomer matrix from stable isotope labelling experiments together with the first and second retention index (RI1 and RI2). To exploit RI1 and RI2 for metabolite identification we used the Golm metabolome database (GMD [1] with RI1/RI2-reference spectra and new search algorithms. Using those techniques we analysed the dynamics of (13)CO(2) and (13)C-acetate uptake in Chlamydomonas reinhardtii cells in two different steady states namely photoautotroph and mixotroph growth conditions.