Veit Schwämmle

Quantitative assessment of in-solution digestion efficiency identifies optimal protocols for unbiased protein analysis

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods.

Geomorphology: Solitary wave behaviour of sand dunes

Barchan sand dunes are highly mobile, crescent-shaped dunes that occur in areas where sand is sparse and the wind is unidirectional. Here we show mathematically how two such loose-grained dunes are able to pass through one another while still preserving their shape. The crucial parameters for this solitary-wave behaviour, which is consistent with field observations, are the heights of the two colliding dunes.

A simple and fast method to determine the parameters for fuzzy c–means cluster analysis

MOTIVATION Fuzzy c-means clustering is widely used to identify cluster structures in high-dimensional datasets, such as those obtained in DNA microarray and quantitative proteomics experiments. One of its main limitations is the lack of a computationally fast method to set optimal values of algorithm parameters. Wrong parameter values may either lead to the inclusion of purely random fluctuations in the results or ignore potentially important data. The optimal solution has parameter values for which the clustering does not yield any results for a purely random dataset but which detects cluster formation with maximum resolution on the edge of randomness. RESULTS Estimation of the optimal parameter values is achieved by evaluation of the results of the clustering procedure applied to randomized datasets. In this case, the optimal value of the fuzzifier follows common rules that depend only on the main properties of the dataset. Taking the dimension of the set and the number of objects as input values instead of evaluating the entire dataset allows us to propose a functional relationship determining the fuzzifier directly. This result speaks strongly against using a predefined fuzzifier as typically done in many previous studies. Validation indices are generally used for the estimation of the optimal number of clusters. A comparison shows that the minimum distance between the centroids provides results that are at least equivalent or better than those obtained by other computationally more expensive indices.

Dune formation under bimodal winds

The study of dune morphology represents a valuable tool in the investigation of planetary wind systems—the primary factor controlling the dune shape is the wind directionality. However, our understanding of dune formation is still limited to the simplest situation of unidirectional winds: There is no model that solves the equations of sand transport under the most common situation of seasonally varying wind directions. Here we present the calculation of sand transport under bimodal winds using a dune model that is extended to account for more than one wind direction. Our calculations show that dunes align longitudinally to the resultant wind trend if the angle θw between the wind directions is larger than 90°. Under high sand availability, linear seif dunes are obtained, the intriguing meandering shape of which is found to be controlled by the dune height and by the time the wind lasts at each one of the two wind directions. Unusual dune shapes including the “wedge dunes” observed on Mars appear within a wide spectrum of bimodal dune morphologies under low sand availability.

A Novel Method for the Simultaneous Enrichment, Identification, and Quantification of Phosphopeptides and Sialylated Glycopeptides Applied to a Temporal Profile of Mouse Brain Development

We describe a method that combines an optimized titanium dioxide protocol and hydrophilic interaction liquid chromatography to simultaneously enrich, identify and quantify phosphopeptides and formerly N-linked sialylated glycopeptides to monitor changes associated with cell signaling during mouse brain development. We initially applied the method to enriched membrane fractions from HeLa cells, which allowed the identification of 4468 unique phosphopeptides and 1809 formerly N-linked sialylated glycopeptides. We subsequently combined the method with isobaric tagging for relative quantification to compare changes in phosphopeptide and formerly N-linked sialylated glycopeptide abundance in the developing mouse brain. A total of 7682 unique phosphopeptide sequences and 3246 unique formerly sialylated glycopeptides were identified. Moreover 669 phosphopeptides and 300 formerly N-sialylated glycopeptides differentially regulated during mouse brain development were detected. This strategy allowed us to reveal extensive changes in post-translational modifications from postnatal mice from day 0 until maturity at day 80. The results of this study confirm the role of sialylation in organ development and provide the first extensive global view of dynamic changes between N-linked sialylation and phosphorylation.

Time-resolved quantitative phosphoproteomics: new insights into Angiotensin-(1-7) signaling networks in human endothelial cells.

Angiotensin-(1-7) [Ang-(1-7)] is an endogenous ligand of the Mas receptor and induces vasodilation, positive regulation of insulin, and antiproliferative and antitumorigenic activities. However, little is known about the molecular mechanisms behind these biological properties. Aiming to identify proteins involved in the Ang-(1-7) signaling, we performed a mass spectrometry-based time-resolved quantitative phosphoproteome study of human aortic endothelial cells (HAEC) treated with Ang-(1-7). We identified 1288 unique phosphosites on 699 different proteins with 99% certainty of correct peptide identification and phosphorylation site localization. Of these, 121 sites on 79 proteins had their phosphorylation levels significantly changed by Ang-(1-7). Our data suggest that the antiproliferative activity of Ang-(1-7) is due to the activation or inactivation of several target phosphoproteins, such as forkhead box protein O1 (FOXO1), mitogen-activated protein kinase 1 (MAPK), proline-rich AKT1 substrate 1 (AKT1S1), among others. In addition, the antitumorigenic activity of Ang-(1-7) is at least partially due to FOXO1 activation, since we show that this transcriptional factor is activated and accumulated in the nucleus of A549 lung adenocarcinoma cells treated with Ang-(1-7). Moreover, Ang-(1-7) triggered changes in the phosphorylation status of several known downstream effectors of the insulin signaling, indicating an important role of Ang-(1-7) in glucose homeostasis. In summary, this study provides new concepts and new understanding of the Ang-(1-7) signal transduction, shedding light on the mechanisms underlying Mas activation.

Modelling transverse dunes

Transverse dunes appear in regions of mainly unidirectional wind and high sand availability. A dune model is extended to two-dimensional calculation of the shear stress. It is applied to simulate dynamics and morphology of three-dimensional transverse dunes. In the simulations they seem to reach translational invariance and do not stop growing. Hence, simulations of two-dimensional dune fields have been performed. Characteristic laws were found for the time evolution of transverse dunes. Bagnolds law of the dune velocity is modified and reproduced. The interaction between transverse dunes led to the interesting conclusion that small dunes can travel over bigger ones. Copyright

Middle-down hybrid chromatography/tandem mass spectrometry workflow for characterization of combinatorial post-translational modifications in histones.

We present an integrated middle‐down proteomics platform for sensitive mapping and quantification of coexisting PTMs in large polypeptides (5–7 kDa). We combined an RP trap column with subsequent weak cation exchange–hydrophilic interaction LC interfaced directly to high mass accuracy ESI MS/MS using electron transfer dissociation. This enabled automated and efficient separation and sequencing of hypermodified histone N‐terminal tails for unambiguous localization of combinatorial PTMs. We present Histone Coder and IsoScale software to extract, filter, and analyze MS/MS data, including quantification of cofragmenting isobaric polypeptide species. We characterized histone tails derived from murine embryonic stem cells knockout in suppressor of zeste12 (Suz12−/−) and quantified 256 combinatorial histone marks in histones H3, H4, and H2A. Furthermore, a total of 713 different combinatorial histone marks were identified in purified histone H3. We measured a seven‐fold reduction of H3K27me2/me3 (where me2 and me3 are dimethylation and trimethylation, respectively) in Suz12−/− cells and detected significant changes of the relative abundance of 16 other single PTMs of histone H3 and other combinatorial marks. We conclude that the inactivation of Suz12 is associated with changes in the abundance of not only H3K27 methylation but also multiple other PTMs in histone H3 tails.

Consequences of the H theorem from nonlinear Fokker-Planck equations.

A general type of nonlinear Fokker-Planck equation is derived directly from a master equation, by introducing generalized transition rates. The H theorem is demonstrated for systems that follow those classes of nonlinear Fokker-Planck equations, in the presence of an external potential. For that, a relation involving terms of Fokker-Planck equations and general entropic forms is proposed. It is shown that, at equilibrium, this relation is equivalent to the maximum-entropy principle. Families of Fokker-Planck equations may be related to a single type of entropy, and so, the correspondence between well-known entropic forms and their associated Fokker-Planck equations is explored. It is shown that the Boltzmann-Gibbs entropy, apart from its connection with the standard--linear Fokker-Planck equation--may be also related to a family of nonlinear Fokker-Planck equations.

Assessment and improvement of statistical tools for comparative proteomics analysis of sparse data sets with few experimental replicates.

Large-scale quantitative analyses of biological systems are often performed with few replicate experiments, leading to multiple nonidentical data sets due to missing values. For example, mass spectrometry driven proteomics experiments are frequently performed with few biological or technical replicates due to sample-scarcity or due to duty-cycle or sensitivity constraints, or limited capacity of the available instrumentation, leading to incomplete results where detection of significant feature changes becomes a challenge. This problem is further exacerbated for the detection of significant changes on the peptide level, for example, in phospho-proteomics experiments. In order to assess the extent of this problem and the implications for large-scale proteome analysis, we investigated and optimized the performance of three statistical approaches by using simulated and experimental data sets with varying numbers of missing values. We applied three tools, including standard t test, moderated t test, also known as limma, and rank products for the detection of significantly changing features in simulated and experimental proteomics data sets with missing values. The rank product method was improved to work with data sets containing missing values. Extensive analysis of simulated and experimental data sets revealed that the performance of the statistical analysis tools depended on simple properties of the data sets. High-confidence results were obtained by using the limma and rank products methods for analyses of triplicate data sets that exhibited more than 1000 features and more than 50% missing values. The maximum number of differentially represented features was identified by using limma and rank products methods in a complementary manner. We therefore recommend combined usage of these methods as a novel and optimal way to detect significantly changing features in these data sets. This approach is suitable for large quantitative data sets from stable isotope labeling and mass spectrometry experiments and should be applicable to large data sets of any type. An R script that implements the improved rank products algorithm and the combined analysis is available.