This study focuses on the specific problems of protein extraction from recalcitrant plant tissues and evaluates several methods to bypass them. Sample preparation is a critical step in a two-dimensional gel electrophoresis proteome approach and is absolutely essential for good results. We evaluated four methods: the classical trichloroacetic acid (TCA)/acetone precipitation, TCA/acetone precipitation and fractionation, an alternative based on fractionation and without precipitation, and phenol extraction methanol/ammonium acetate precipitation. We optimized the phenol extraction protocol for small amounts of tissue, which is essential when the study material is limited. The protocol was optimized for banana (Musa spp.) and was subsequently applied to two other plant species: apple (Malus domestica L.) and potato (Solanum tuberosum L.). Banana (Musa spp.) is a good representative of a "difficult" plant species since it contains many interfering metabolites. Only classical TCA/acetone precipitation and phenol extraction methods proved useful as standard methods. Both methods are associated with a minor but reproducible loss of proteins. Every extraction method and the subsequent analytical procedure have their physicochemical limitations; both methods should be investigated before selecting an appropriate protocol. The study, which is presented in this paper, is useful for guiding the experimental setup of many other nonmodel species, containing various interfering elements.

No abstract

No abstract

Arbuscular mycorrhizal fungi (AMF) are obligate root symbionts that can protect their host plant against biotic stress factors such as plant-parasitic nematode (PPN) infection. PPN consist of a wide range of species with different life styles that can cause major damage in many important crops worldwide. Various mechanisms have been proposed to play a role in the biocontrol effect of AMF against PPN. This review presents an overview of the different mechanisms that have been proposed, and discusses into more detail the plausibility of their involvement in the biocontrol against PPN specifically. The proposed mechanisms include enhanced plant tolerance, direct competition for nutrients and space, induced systemic resistance (ISR) and altered rhizosphere interactions. Recent studies have emphasized the importance of ISR in biocontrol and are increasingly placing rhizosphere effects on the foreground as well, both of which will be the focal point of this review. Though AMF are not yet widely used in conventional agriculture, recent data help to develop a better insight into the modes of action, which will eventually lead toward future field applications of AMF against PPN. The scientific community has entered an exciting era that provides the tools to actually unravel the underlying molecular mechanisms, making this a timely opportunity for a review of our current knowledge and the challenges ahead.

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.