HowDirty: An R package to evaluate molecular contaminants in LC-MS experiments.

Contaminants derived from consumables, reagents, and sample handling often negatively affect LC-MS data acquisition. In proteomics experiments, they can markedly reduce identification performance, reproducibility, and quantitative robustness. Here, we introduce a data analysis workflow combining MS1 feature extraction in Skyline with HowDirty, an R-markdown-based tool, that automatically generates an interactive report on the molecular contaminant level in LC-MS data sets. To facilitate the interpretation of the results, the HTML report is self-contained and self-explanatory, including plots that can be easily interpreted. The R package HowDirty is available from https://github.com/DavidGZ1/HowDirty. To demonstrate a showcase scenario for the application of HowDirty, we assessed the impact of ultrafiltration units from different providers on sample purity after filter-assisted sample preparation (FASP) digestion. This allowed us to select the filter units with the lowest contamination risk. Notably, the filter units with the lowest contaminant levels showed higher reproducibility regarding the number of peptides and proteins identified. Overall, HowDirty enables the efficient evaluation of sample quality covering a wide range of common contaminant groups that typically impair LC-MS analyses, facilitating corrective or preventive actions to minimize instrument downtime.

Ionmob: a Python package for prediction of peptide collisional cross-section values.

MOTIVATION: Including ion mobility separation (IMS) into mass spectrometry proteomics experiments is useful to improve coverage and throughput. Many IMS devices enable linking experimentally derived mobility of an ion to its collisional cross-section (CCS), a highly reproducible physicochemical property dependent on the ion's mass, charge and conformation in the gas phase. Thus, known peptide ion mobilities can be used to tailor acquisition methods or to refine database search results. The large space of potential peptide sequences, driven also by posttranslational modifications of amino acids, motivates an in silico predictor for peptide CCS. Recent studies explored the general performance of varying machine-learning techniques, however, the workflow engineering part was of secondary importance. For the sake of applicability, such a tool should be generic, data driven, and offer the possibility to be easily adapted to individual workflows for experimental design and data processing. RESULTS: We created ionmob, a Python-based framework for data preparation, training, and prediction of collisional cross-section values of peptides. It is easily customizable and includes a set of pretrained, ready-to-use models and preprocessing routines for training and inference. Using a set of ≈21 000 unique phosphorylated peptides and ≈17 000 MHC ligand sequences and charge state pairs, we expand upon the space of peptides that can be integrated into CCS prediction. Lastly, we investigate the applicability of in silico predicted CCS to increase confidence in identified peptides by applying methods of re-scoring and demonstrate that predicted CCS values complement existing predictors for that task. AVAILABILITY AND IMPLEMENTATION: The Python package is available at github: https://github.com/theGreatHerrLebert/ionmob.

Modulation of cellular transcriptome and proteome composition by azidohomoalanine-implications on click chemistry-based secretome analysis.

The analysis of the secretome provides important information on proteins defining intercellular communication and the recruitment and behavior of cells in specific tissues. Especially in the context of tumors, secretome data can support decisions for diagnosis and therapy. The mass spectrometry-based analysis of cell-conditioned media is widely used for the unbiased characterization of cancer secretomes in vitro. Metabolic labeling using azide-containing amino acid analogs in combination with click chemistry facilitates this type of analysis in the presence of serum, preventing serum starvation-induced effects. The modified amino acid analogs, however, are less efficiently incorporated into newly synthesized proteins and may perturb protein folding. Combining transcriptome and proteome analysis, we elucidate in detail the effects of metabolic labeling with the methionine analog azidohomoalanine (AHA) on gene and protein expression. Our data reveal that 15-39% of the proteins detected in the secretome displayed changes in transcript and protein expression induced by AHA labeling. Gene Ontology (GO) analyses indicate that metabolic labeling using AHA leads to induction of cellular stress and apoptosis-related pathways and provide first insights on how this affects the composition of the secretome on a global scale. KEY MESSAGES: Azide-containing amino acid analogs affect gene expression profiles. Azide-containing amino acid analogs influence cellular proteome. Azidohomoalanine labeling induces cellular stress and apoptotic pathways. Secretome consists of proteins with dysregulated expression profiles.

AKT activity orchestrates marginal zone B cell development in mice and humans.

The signals controlling marginal zone (MZ) and follicular (FO) B cell development remain incompletely understood. Here, we show that AKT orchestrates MZ B cell formation in mice and humans. Genetic models that increase AKT signaling in B cells or abolish its impact on FoxO transcription factors highlight the AKT-FoxO axis as an on-off switch for MZ B cell formation in mice. In humans, splenic immunoglobulin (Ig) D+CD27+ B cells, proposed as an MZ B cell equivalent, display higher AKT signaling than naive IgD+CD27- and memory IgD-CD27+ B cells and develop in an AKT-dependent manner from their precursors in vitro, underlining the conservation of this developmental pathway. Consistently, CD148 is identified as a receptor indicative of the level of AKT signaling in B cells, expressed at a higher level in MZ B cells than FO B cells in mice as well as humans.

Targeting myeloid cell coagulation signaling blocks MAP kinase/TGF-ß1-driven fibrotic remodeling in ischemic heart failure.

Despite major advances in acute interventions for myocardial infarction (MI), adverse cardiac remodeling and excess fibrosis after MI causing ischemic heart failure (IHF) remain a leading cause of death worldwide. Here we identify a profibrotic coagulation signaling pathway that can be targeted for improved cardiac function following MI with persistent ischemia. Quantitative phosphoproteomics of cardiac tissue revealed an upregulated mitogen-activated protein kinase (MAPK) pathway in human IHF. Intervention in this pathway with trametinib improves myocardial function and prevents fibrotic remodeling in a murine model of non-reperfused MI. MAPK activation in MI requires myeloid cell signaling of protease-activated receptor 2 linked to the cytoplasmic domain of the coagulation initiator tissue factor (TF). They act upstream of pro-oxidant NOX2 NADPH oxidase, ERK1/2 phosphorylation, and activation of profibrotic TGF-ß1. Specific targeting with the TF inhibitor nematode anticoagulant protein c2 (NAPc2) starting 1 day after established experimental MI averts IHF. Increased TF cytoplasmic domain phosphorylation in circulating monocytes from patients with subacute MI identifies a potential thromboinflammatory biomarker reflective of increased risk for IHF and suitable for patient selection to receive targeted TF inhibition therapy.

Data-Independent Acquisition (DIA) Is Superior for High Precision Phospho-Peptide Quantification in Magnaporthe oryzae.

The dynamic interplay of signaling networks in most major cellular processes is characterized by the orchestration of reversible protein phosphorylation. Consequently, analytic methods such as quantitative phospho-peptidomics have been pushed forward from a highly specialized edge-technique to a powerful and versatile platform for comprehensively analyzing the phosphorylation profile of living organisms. Despite enormous progress in instrumentation and bioinformatics, a high number of missing values caused by the experimental procedure remains a major problem, due to either a random phospho-peptide enrichment selectivity or borderline signal intensities, which both cause the exclusion for fragmentation using the commonly applied data dependent acquisition (DDA) mode. Consequently, an incomplete dataset reduces confidence in the subsequent statistical bioinformatic processing. Here, we successfully applied data independent acquisition (DIA) by using the filamentous fungus Magnaporthe oryzae as a model organism, and could prove that while maintaining data quality (such as phosphosite and peptide sequence confidence), the data completeness increases dramatically. Since the method presented here reduces the LC-MS/MS analysis from 3 h to 1 h and increases the number of phosphosites identified up to 10-fold in contrast to published studies in Magnaporthe oryzae, we provide a refined methodology and a sophisticated resource for investigation of signaling processes in filamentous fungi.

Quantitative Proteome and Phosphoproteome Profiling in Magnaporthe oryzae.

The quality and consistency in every sample preparation procedure is crucial for any scientific output. Therefore, it is of utmost importance to have easy, economic, and robust sample preparation protocols. Here, we describe a simple and robust bottom-up proteomic sample preparation strategy for identification and label-free quantification (LFQ) of proteins and phosphoproteins. The presented workflow is designed for large-scale application and involves easy scalable and well-known robust sample preparation techniques, such as cell lysis with SDS buffer under heat, protein precipitation using methanol/chloroform, tryptic digest, and commercially available TiO2 phosphopeptide enrichment kits. Over a sample set of 48 samples of only 200 mg fungal mycelium each, we quantified a median of 2937 proteins after processing in the IsoQuant software. The median peptide count was 10 peptides per protein leading to a median 65% sequence coverage. In addition, we identified a median of 3324 phosphopeptides (corresponding to 998 phosphoproteins) with 4874 phosphosites per sample. Over all samples, we achieved a median phosphopeptide enrichment efficiency of 77%. The distribution of serine/threonine/tyrosine (S/T/Y) phosphosites was 78.1%/21.2%/0.6%.

Evidence of a New MoYpd1p Phosphotransferase Isoform in the Multistep Phosphorelay System of Magnaporthe oryzae.

Different external stimuli are perceived by multiple sensor histidine kinases and transmitted by phosphorylation via the phosphotransfer protein Ypd1p in the multistep phosphorelay system of the high osmolarity glycerol signaling pathway of filamentous fungi. How the signal propagation takes place is still not known in detail since multiple sensor histidine kinase genes in most filamentous fungi are coded in the genome, whereas only one gene for Ypd1p exists. That raises the hypothesis that various Ypd1p isoforms are produced from a single gene sequence, perhaps by alternative splicing, facilitating a higher variability in signal transduction. We found that the mRNA of MoYPD1 in the rice blast fungus Magnaporthe oryzae is subjected to an increased structural variation and amplified putative isoforms on a cDNA level. We then generated mutant strains overexpressing these isoforms, purified the products, and present here one previously unknown MoYpd1p isoform on a proteome level. Alternative splicing was found to be a valid molecular mechanism to increase the signal diversity in eukaryotic multistep phosphorelay systems.

Limited proteolysis by acrosin affects sperm-binding and mechanical resilience of the mouse zona pellucida.

The encounter of oocyte and sperm is the key event initiating embryonic development in mammals. Crucial functions of this existential interaction are determined by proteolytic enzymes, such as acrosin, carried in the sperm head acrosome, and ovastacin, stored in the oocyte cortical granules. Ovastacin is released upon fertilisation to cleave the zona pellucida, a glycoprotein matrix surrounding the oocyte. This limited proteolysis hardens the oocyte envelope, and thereby provides a definitive block against polyspermy and protects the developing embryo. On the other hand, acrosin, the renowned and most abundant acrosomal protease, has been thought to enable sperm to penetrate the oocyte envelope. Depending on the species, proteolytic cleavage of the zona pellucida by acrosin is either essential or conducive for fertilisation. However, the specific target cleavage sites and the resulting physiological consequences of this proteolysis remained obscure. Here, we treated native mouse zonae pellucidae with active acrosin and identified two cleavage sites in zona pellucida protein 1 (ZP1), five in ZP2 and one in ZP3 by mass spectrometry. Several of these sites are highly conserved in mammals. Remarkably, limited proteolysis by acrosin leads to zona pellucida remodelling rather than degradation. Thus, acrosin affects both sperm binding and mechanical resilience of the zona pellucida, as assessed by microscopy and nanoindentation measurements, respectively. Furthermore, we ascertained potential regulatory effects of acrosin, via activation of latent pro-ovastacin and inactivation of fetuin-B, a tight binding inhibitor of ovastacin. These results offer novel insights into the complex proteolytic network modifying the extracellular matrix of the mouse oocyte, which might apply also to other species.

Determination of low intrinsic clearance in vitro: the benefit of a novel internal standard in human hepatocyte incubations.

1. A novel method utilizing an internal standard in hepatocytes incubations has been developed and demonstrated to decrease the variability in the determination of intrinsic clearance (CLint) in this system. The reduced variability was shown to allow differentiation of lower elimination rate constants from noise. 2. The suggested method was able to compensate for a small but systematic error (0.5 µL/min/106 cells) caused by an evaporation of approximately 15% of the volume during the incubation time. 3. The approach was validated using six commercial drugs (ketoprofen, tolbutamide, phenacetin, etodolac and quinidine) which were metabolized by different pathways. 4. The suggested internal standard, MSC1815677, was extensively characterized and the acquired data suggest that it fulfills the requirements of an internal standard present during the incubation. The proposed internal standard was stable during the incubation and showed a low potential to inhibit drug metabolizing enzymes and transporters. With MSC1815677 we propose a novel simple, robust and cost-effective method to address the challenges in the estimation of low clearance in hepatocyte incubations.