No abstract

Mass spectrometry, in the past five years, has increased in speed, accuracy and use. With the ability of the mass spectrometers to identify increasing numbers of proteins the identification of undesirable peptides (those not from the protein sample) has also increased. Most undesirable contaminants originate in the laboratory and come from either the user (e.g. keratin from hair and skin), or from reagents (e.g. trypsin), that are required to prepare samples for analysis. We found that a significant amount of MS instrument time was spent sequencing peptides from abundant contaminant proteins. While completely eliminating non-specific protein contamination is not feasible, it is possible to reduce the sequencing of these contaminants. For example, exclusion lists can provide a list of masses that can be used to instruct the mass spectrometer to ‘ignore’ the undesired contaminant peptides in the list. We empirically generated be-spoke exclusion lists for several model organisms (Homo sapiens, Caenorhabditis elegans, Saccharomyces cerevisiae and Xenopus laevis), utilising information from over 500 mass spectrometry runs and cumulative analysis of these data. Here we show that by employing these empirically generated lists, it was possible to reduce the time spent analysing contaminating peptides in a given sample thereby facilitating more efficient data acquisition and analysis.Biological significanceGiven the current efficacy of the Mass Spectrometry instrumentation, the utilisation of data from ~500 mass spec runs to generate be-spoke exclusion lists and optimise data acquisition is the significance of this manuscript.This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012].

Background: Regulation of the mRNA life cycle is central to gene expression control and determination of cell fate. miRNAs represent a critical mRNA regulatory mechanism, but despite decades of research, their mode of action is still not fully understood. Results: Here, we show that eIF4A2 is a major effector of the repressive miRNA pathway functioning via the Ccr4-Not complex. We demonstrate that while DDX6 interacts with Ccr4-Not, its effects in the mechanism are not as pronounced. Through its interaction with the Ccr4-Not complex, eIF4A2 represses mRNAs at translation initiation. We show evidence that native eIF4A2 has similar RNA selectivity to chemically inhibited eIF4A1. eIF4A2 exerts its repressive effect by binding purine-rich motifs which are enriched in the 5′UTR of target mRNAs directly upstream of the AUG start codon. Conclusions: Our data support a model whereby purine motifs towards the 3′ end of the 5′UTR are associated with increased ribosome occupancy and possible uORF activation upon eIF4A2 binding.

Summary Plant–pathogen interactions are complex associations driven by the interplay of host and microbe‐encoded factors. With secreted pathogen proteins (effectors) and immune signalling components found in the plant nucleus, this compartment is a battleground where susceptibility is specified. We hypothesized that, by defining changes in the nuclear proteome during infection, we can pinpoint vital components required for immunity or susceptibility.We tested this hypothesis by documenting dynamic changes in the tomato (Solanum lycopersicum) nuclear proteome during infection by the oomycete pathogen Phytophthora capsici. We enriched nuclei from infected and noninfected tissues and quantitatively assessed changes in the nuclear proteome. We then tested the role of candidate regulators in immunity through functional assays.We demonstrated that the host nuclear proteome dynamically changes during P. capsici infection. We observed that known nuclear immunity factors were differentially expressed and, based on this observation, selected a set of candidate regulators that we successfully implicated in immunity to P. capsici.Our work exemplifies a powerful strategy to gain rapid insight into important nuclear processes that underpin complex crop traits such as resistance. We have identified a large set of candidate nuclear factors that may underpin immunity to pathogens in crops.