Detektion von Proteinmodifikationen durch rauschmodellbasierte Analysen von regulatorischer Information

In quantitative proteomics the amounts of individual peptides and proteins within differentially treated cells are compared by mass spectrometry. Occuring impreciseness of the measurements can adulterate the results and thus, formulation of hypotheses. Especially low signal intensities are affected since considerable percentages of those may be caused by noise. In this work, the observed intensity dependent noise within a defined quantitative mass spectrometry based workflow could be modelled by the development of a specific noise model. Both calculation of regulation factors of single peptides and calculation of such of peptide groups (e.g. all peptides identified within one protein) is derived from the noise model. In doing so, all calculations are weighted according to the robustness of the underlying data. The regulatory information obtained in this way, is visualised by likelihood curves presenting the likelihood of the most probable as well as alternative regulation factors. The reliability of the most suitable regulation factor - and consequently the robustness of the data - can be inferred from the shape of the curves. As the detection of novel post-translational modifications (PTM) is essential for the understanding of dynamic protein networks, many biological projects currently aim on quantitative analyses by mass spectrometry on the peptide level. Modified peptides appear regulated differentially due to the increase and decrease of the amounts of their modified and unmodified variants. The detection of differetially regulated peptides within the same protein is highly interesting for the investigation of new peptide modifications. For this purpose, besides calculation of regulatory information a clustering algorithm was developed in this work that is able to find differentially regulated peptides of a protein.In der quantitativen Proteomforschung werden durch massenspektrometrische Verfahren die vorhandenen Mengen einzelner Peptide und Proteine in unterschiedlich behandelten Zellen miteinander verglichen. Dabei kommt es zu Messungenauigkeiten, welche die Ergebnisse und somit die Hypothesenbildung verfälschen können. Davon betroffen sind hauptsächlich niedrige Signalintensitäten, bei welchen der Anteil des Rauschens einen signifikanten Anteil der gesamten Signalintensität ausmachen kann. In der vorliegenden Arbeit ist es gelungen, das beobachtete Rauschen innerhalb eines definierten Analyseablaufes mit Hilfe eines spezifischen Rauschmodelles zu beurteilen. Das Modell ermöglicht eine der Glaubwürdigkeit entsprechende Berechnung einzelner Peptidregulationsfaktoren sowie eine gewichtete Berechnung von Regulationsfaktoren für eine Gruppe von Peptiden, z.B. alle Peptide eines Proteins. Die so abgeleitete regulatorische Information wird durch Likelihoodkurven visualisiert, welche die Likelihood für den wahrscheinlichsten sowie alternative Regulationsfaktoren darstellen. Anhand der Gestalt einer Likelihoodkurve kann auf die Robustheit der zu Grunde liegenden Daten geschlossen werden. Da die Entdeckung neuer post-translationaler Modifikationen essentiell für das Verständnis dynamischer Proteinnetzwerke ist, sind quantitative massenspektrometrische Analysen auf der Peptidebene derzeit Ziel vieler biologischer Projekte. Modifizierte Peptide erscheinen infolge der Mengenzu- bzw. abnahme ihrer modifzierten bzw. unmodifizierten Form differentiell reguliert. Die Detektion solcher differentiell regulierten Peptide innerhalb eines Proteins ist von größtem Interesse, um so auf potentielle neue Modifikationen schließen zu können. Zu diesem Zweck ist in der vorliegenden Arbeit neben der Berechnung der regulatorischen Information ein Clusteringalgorithmus entwickelt worden, welcher (auf dieser basierend) nach differentiell regulierten Peptiden eines Proteins sucht

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4-2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in genera

Genome-wide association and functional follow-up reveals new loci for kidney function

Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

JVirGel: calculation of virtual two-dimensional protein gels

We developed JVirGel, a collection of tools for the simulation and analysis of proteomics data. The software creates and visualizes virtual two-dimensional (2D) protein gels based on the migration behaviour of proteins in dependence of their theoretical molecular weights in combination with their calculated isoelectric points. The utilization of all proteins of an organism of interest deduced from genes of the corresponding genome project in combination with the elimination of obvious membrane proteins permits the creation of an optimized calculated proteome map. The electrophoretic separation behaviour of single proteins is accessible interactively in a Java(TM) applet (small application in a web browser) by selecting a pI/MW range and an electrophoretic timescale of interest. The calculated pattern of protein spots helps to identify unknown proteins and to localize known proteins during experimental proteomics approaches. Differences between the experimentally observed and the calculated migration behaviour of certain proteins provide first indications for potential protein modification events. When possible, the protein spots are directly linked via a mouse click to the public databases SWISS-PROT and PRODORIC. Additionally, we provide tools for the serial calculation and visualization of specific protein properties like pH dependent charge curves and hydrophobicity profiles. These values are helpful for the rational establishment of protein purification procedures. The proteomics tools are available on the World Wide Web at http://prodoric.tu-bs.de/proteomics.php

Using eDNA to understand predator–prey interactions influenced by invasive species

Invasive predatory species may alter population dynamic processes of their prey and impact biological communities and ecosystem processes. Revealing biotic interactions, however, including the relationship between predator and prey, is a difficult task, in particular for species that are hard to monitor. Here, we present a case study that documents the utility of environmental DNA analysis (eDNA) to assess predator–prey interactions between two invasive fishes (Lepomis gibbosus, Pseudorasbora parva) and two potential amphibian prey species, (Triturus cristatus, Pelobates fuscus). We used species-specific TaqMan assays for quantitative assessment of eDNA concentrations from water samples collected from 89 sites across 31 ponds during three consecutive months from a local amphibian hotspot in Germany. We found a negative relationship between eDNA concentrations of the predators (fishes) and prey (amphibians) using Monte-Carlo tests. Our study highlights the potential of eDNA application to reveal predator–prey interactions and confirms the hypothesis that the observed local declines of amphibian species may be at least partly caused by recently introduced invasive fishes. Our findings have important consequences for local conservation management and highlight the usefulness of eDNA approaches to assess ecological interactions and guide targeted conservation action.ISSN:0029-8549ISSN:1432-193

Genome-wide association and functional follow-up reveals new loci for kidney function

Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD