Biological research has focused in the past on model organisms and most of the functional genomics studies in the field of plant sciences are still performed on model species or species that are characterized to a great extent. However, numerous non-model plants are essential as food, feed, or energy resource. Some features and processes are unique to these plant species or families and cannot be approached via a model plant. The power of all proteomic and transcriptomic methods, that is, high-throughput identification of candidate gene products, tends to be lost in non-model species due to the lack of genomic information or due to the sequence divergence to a related model organism. Nevertheless, a proteomics approach has a great potential to study non-model species. This work reviews non-model plants from a proteomic angle and provides an outline of the problems encountered when initiating the proteome analysis of a non-model organism. The review tackles problems associated with (i) sample preparation, (ii) the analysis and interpretation of a complex data set, (iii) the protein identification via MS, and (iv) data management and integration. We will illustrate the power of 2DE for non-model plants in combination with multivariate data analysis and MS/MS identification and will evaluate possible alternatives.

Banana (Musa spp.) multiple shoot meristems are an excellent model to study the meristem proteome. Using a 2-DE protocol developed for small amounts of tissue and MS-based cross species polypeptide identification, we have revealed the meristem proteome and investigated the influence of sucrose-mediated osmotic stress in a dehydration-tolerant variety. Proteins that were significantly up- or down-regulated due to the high-sucrose treatment were classified using non-parametric univariate statistics. Our results suggest that the maintenance of an osmoprotective intracellular sucrose concentration, the enhanced expression of particular genes of the energy-conserving glycolysis and the conservation of the cell wall integrity are essential to maintain homeostasis, to acclimate and to survive dehydration. By comparing the dehydration-tolerant variety with a dehydration-sensitive variety, we were able to distinguish several genotype-specific proteins (isoforms), and could associate the dehydration-tolerant variety with proteins involved in energy metabolism (e.g., phosphoglycerate kinase, phosphoglucomutase, UDP-glucose pyrophosphorylase) and proteins that are associated with stress adaptation (e.g., OSR40-like protein, abscisic stress ripening protein-like protein). This work shows that proteome analysis can be used successfully to perform quantitative difference analysis and to characterize genetic variations in a recalcitrant crop.

There is no question that protein- and RNA-based measurements are complementary, but which approach has the highest return in the case of a non-model crop and what is the correlation between mRNA and proteins? We describe and evaluate in detail the advantages and pitfalls of both a proteomics and a transcriptomics approach. The information on the abundance of transcripts was obtained by serial analysis of gene expression (SAGE), while information on the abundance of proteins was obtained via two-dimensional gel electrophoresis.

No abstract

Background: Associations between sarcoidosis or sarcoid-like granulomatous lung disease and exposure to silica and other inorganic agents have been suggested in several studies. Cases:We describe granulomatous lung disease in two workers of a small production unit making metal-halide lamps. Initially, both were diagnosed with sarcoidosis.