Protein identification using a nanoUHPLC-AP-MALDI MS/MS workflow with CID of multiply charged proteolytic peptides

Liquid AP-MALDI can produce predominantly multiply charged ESI-like ions and stable durable analyte ion yields with samples allowing good shot-to-shot reproducibility and exhibiting self-healing properties during laser irradiation. In this study, LC-MALDI MS/MS workflows that utilize multiply charged ions are reported for the first time and compared with standard LC-ESI MS/MS for bottom-up proteomic analysis. The proposed method is compatible with trifluoroacetic acid as an LC ion pairing reagent and allows multiple MS/MS acquisitions of the LC-separated samples without substantial sample consumption. In addition, the method facilitates the storage of fully spotted MALDI target plates for months without significant sample degradation

Behavioral adaptation to polylectism in bees

Sterolic composition of pollen is highly variable among plant species. These compounds are known to be essential for bees as they play important roles in their metabolism such as molting hormone precursors . As they forage on many different plant species, polylectic bees could especially be impacted by this sterolic variability. This work aimed to investigate potential behavioral adaptation of polylectic bees to this variability by adding particular sterols during confection of pollen loads. By contrast, specialist species are expected to be adaptated to their host-plant and would not display such behavior

Investigation and optimization of parameters affecting the multiply charged ion yield in AP-MALDI MS

Liquid matrix-assisted laser desorption/ionization (MALDI) allows the generation of predominantly multiply charged ions in atmospheric pressure (AP) MALDI ion sources for mass spectrometry (MS) analysis. The charge state distribution of the generated ions and the efficiency of the ion source in generating such ions crucially depend on the desolvation regime of the MALDI plume after desorption in the AP-tovacuum inlet. Both high temperature and a flow regime with increased residence time of the desorbed plume in the desolvation region promote the generation of multiply charged ions. Without such measures the application of an electric ion extraction field significantly increases the ion signal intensity of singly charged species while the detection of multiply charged species is less dependent on the extraction field. In general, optimization of high temperature application facilitates the predominant formation and detection of multiply charged compared to singly charged ion species. In this study an experimental setup and optimization strategy is described for liquid AP-MALDI MS which improves the ionization effi- ciency of selected ion species up to 14 times. In combination with ion mobility separation, the method allows the detection of multiply charged peptide and protein ions for analyte solution concentrations as low as 2 fmol/lL (0.5 lL, i.e. 1 fmol, deposited on the target) with very low sample consumption in the low nL-range

Generalized host-plant feeding can hide sterol-specialized foraging behaviors in bee-plant interactions

peer reviewe

Making better food for larvae: do bee females modify sterol composition of pollen loads during foraging

Sterols are essential insect nutrients, involved in some key metabolic pathways. Insects cannot synthesize sterols and must instead draw them from food. For bees, pollen is the only source of sterols, mainly provided in structures with 28 or 29 carbons (i.e., phytosterols). Phytosterol composition of pollen is highly variable among plant species, challenging the physiology and survival of generalist bees. Previous studies have shown that the honey bee (Apis mellifera) is able to handle this variability by adding endogenous sterols to provide a suitable diet to larvae. Such behaviour has never been investigated in other bee species, although it is a key element for understanding bee conservation and evolution. Here, we assessed the sterolic compositions of pollen loads from A. mellifera and compared them to those from generalist (i.e., Bombus terrestris) and wild specialist bee species, as well as to floral pollen. A total of seven plant species from six families and their associated visitors were considered. these results show that some species are able to modify sterol composition of pollen. In some case this modification consist in addition of a peculiar sterol. Moreover this study opens the way to new insights in bee origin and the evolution of their interactions with flowering plants

Sterol addition during pollen collection by bees: another possible strategy to balance nutrient deficiencies?

peer reviewedCaractérisation des propriétés pharmacologiques de plantes mellifères pour les abeilles - Fédération Wallonie Bruxelle

OpenMS – An open-source software framework for mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry is an essential analytical technique for high-throughput analysis in proteomics and metabolomics. The development of new separation techniques, precise mass analyzers and experimental protocols is a very active field of research. This leads to more complex experimental setups yielding ever increasing amounts of data. Consequently, analysis of the data is currently often the bottleneck for experimental studies. Although software tools for many data analysis tasks are available today, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow.</p> <p>Results</p> <p>We present OpenMS, a software framework for rapid application development in mass spectrometry. OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis. This has already been demonstrated in several studies.</p> <p>Conclusion</p> <p>OpenMS is available under the Lesser GNU Public License (LGPL) from the project website at <url>http://www.openms.de</url>.</p

Optimal precursor ion selection for LC-MS/MS based proteomics

Shotgun proteomics with Liquid Chromatography (LC) coupled to Tandem Mass Spectrometry (MS/MS) is a key technology for protein identification and quantitation. Protein identification is done indirectly: detected peptide signals are fragmented byMS/MS and their sequence is reconstructed. Afterwards, the identified peptides are used to infer the proteins present in a sample. The problem of choosing the peptide signals that shall be identified with MS/MS is called precursor ion selection. Most workflows use data- dependent acquisition for precursor ion selection despite known drawbacks like data redundancy, limited reproducibility or a bias towards high-abundance proteins. In this thesis, we formulate optimization problems for different aspects of precursor ion selection to overcome these weaknesses. In the first part of this work we develop inclusion lists aiming at optimal precursor ion selection given different input information. We trace precursor ion selection back to known combinatorial problems and develop linear program (LP) formulations. The first method creates an inclusion list given a set of detected features in an LC-MS map. We show that this setting is an instance of the Knapsack Problem. The corresponding LP can be solved efficiently and yields inclusion lists that schedule more precursors than standard methods when the number of precursors per fraction is limited. Furthermore, we develop a method for inclusion list creation based on a list of proteins of interest. We employ retention time and detectability prediction to infer LC-MS features. Based on peptide detectability, we introduce protein detectabilities that reflect the likelihood of detecting and identifying a protein. By maximizing the sum of protein detectabilities we create an inclusion list of limited size that covers a maximum number of proteins. In the second part of the thesis, we focus on iterative precursor ion selection (IPS) with LC-MALDI MS/MS. Here, after a fixed number of acquired MS/MS spectra their identification results are evaluated and are used for the next round of precursor ion selection. We develop a heuristic which creates a ranked precursor list. The second method, IPS LP, is a combination of the two inclusion list scenarios presented in the first part. Additionally, a protein-based exclusion is part of the objective function. For evaluation, we compared both IPS methods to a static inclusion list (SPS) created before the beginning of MS/MS acquisition. We simulated precursor ion selection on three data sets of different complexity and show that IPS LP can identify the same number of proteins with fewer selected precursors. This improvement is especially pronounced for low abundance proteins. Additionally, we show that IPS LP decreases the bias to high abundance proteins. All presented algorithms were implemented in OpenMS, a software library for mass spectrometry. Finally, we present an online tool for IPS that has direct access to the instrument and controls the measurement