Garwin Pichler

Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells

Mass spectrometry (MS)-based proteomics typically employs multistep sample-preparation workflows that are subject to sample contamination and loss. We report an in-StageTip method for performing sample processing, from cell lysis through elution of purified peptides, in a single, enclosed volume. This robust and scalable method largely eliminates contamination or loss. Peptides can be eluted in several fractions or in one step for single-run proteome analysis. In one day, we obtained the largest proteome coverage to date for budding and fission yeast, and found that protein copy numbers in these cells were highly correlated (R2 = 0.78). Applying the in-StageTip method to quadruplicate measurements of a human cell line, we obtained copy-number estimates for 9,667 human proteins and observed excellent quantitative reproducibility between replicates (R2 = 0.97). The in-StageTip method is straightforward and generally applicable in biological or clinical applications.

Establishment of a robust single axis of cell polarity by coupling multiple positive feedback loops

Establishment of cell polarity—or symmetry breaking—relies on local accumulation of polarity regulators. Although simple positive feedback is sufficient to drive symmetry breaking, it is highly sensitive to stochastic fluctuations typical for living cells. Here, by integrating mathematical modelling with quantitative experimental validations, we show that in the yeast Saccharomyces cerevisiae a combination of actin- and guanine nucleotide dissociation inhibitor-dependent recycling of the central polarity regulator Cdc42 is needed to establish robust cell polarity at a single site during yeast budding. The guanine nucleotide dissociation inhibitor pathway consistently generates a single-polarization site, but requires Cdc42 to cycle rapidly between its active and inactive form, and is therefore sensitive to perturbations of the GTPase cycle. Conversely, actin-mediated recycling of Cdc42 induces robust symmetry breaking but cannot restrict polarization to a single site. Our results demonstrate how cells optimize symmetry breaking through coupling between multiple feedback loops.

Genetic diagnosis of Mendelian disorders via RNA sequencing.

Across a variety of Mendelian disorders, ∼50–75% of patients do not receive a genetic diagnosis by exome sequencing indicating disease-causing variants in non-coding regions. Although genome sequencing in principle reveals all genetic variants, their sizeable number and poorer annotation make prioritization challenging. Here, we demonstrate the power of transcriptome sequencing to molecularly diagnose 10% (5 of 48) of mitochondriopathy patients and identify candidate genes for the remainder. We find a median of one aberrantly expressed gene, five aberrant splicing events and six mono-allelically expressed rare variants in patient-derived fibroblasts and establish disease-causing roles for each kind. Private exons often arise from cryptic splice sites providing an important clue for variant prioritization. One such event is found in the complex I assembly factor TIMMDC1 establishing a novel disease-associated gene. In conclusion, our study expands the diagnostic tools for detecting non-exonic variants and provides examples of intronic loss-of-function variants with pathological relevance.

Ultra-deep and quantitative saliva proteome reveals dynamics of the oral microbiome

BackgroundThe oral cavity is home to one of the most diverse microbial communities of the human body and a major entry portal for pathogens. Its homeostasis is maintained by saliva, which fulfills key functions including lubrication of food, pre-digestion, and bacterial defense. Consequently, disruptions in saliva secretion and changes in the oral microbiome contribute to conditions such as tooth decay and respiratory tract infections. Here we set out to quantitatively map the saliva proteome in great depth with a rapid and in-depth mass spectrometry-based proteomics workflow.MethodsWe used recent improvements in mass spectrometry (MS)-based proteomics to develop a rapid workflow for mapping the saliva proteome quantitatively and at great depth. Standard clinical cotton swabs were used to collect saliva form eight healthy individuals at two different time points, allowing us to study inter-individual differences and interday changes of the saliva proteome. To accurately identify microbial proteins, we developed a method called “split by taxonomy id” that prevents peptides shared by humans and bacteria or between different bacterial phyla to contribute to protein identification.ResultsMicrogram protein amounts retrieved from cotton swabs resulted in more than 3700 quantified human proteins in 100-min gradients or 5500 proteins after simple fractionation. Remarkably, our measurements also quantified more than 2000 microbial proteins from 50 bacterial genera. Co-analysis of the proteomics results with next-generation sequencing data from the Human Microbiome Project as well as a comparison to MALDI-TOF mass spectrometry on microbial cultures revealed strong agreement. The oral microbiome differs between individuals and changes drastically upon eating and tooth brushing.ConclusionRapid shotgun and robust technology can now simultaneously characterize the human and microbiome contributions to the proteome of a body fluid and is therefore a valuable complement to genomic studies. This opens new frontiers for the study of host–pathogen interactions and clinical saliva diagnostics.

Proteomics Analysis of Monocyte-Derived Hepatocyte-Like Cells Identifies Integrin Beta 3 as a Specific Biomarker for Drug-Induced Liver Injury by Diclofenac

Idiosyncratic drug-induced liver injury (iDILI) is a major cause of acute liver failure resulting in liver transplantation or death. Prediction and diagnosis of iDILI remain a great challenge, as current models provide unsatisfying results in terms of sensitivity, specificity, and prognostic value. The absence of appropriate tools for iDILI detection also impairs the development of reliable biomarkers. Here, we report on a new method for identification of drug-specific biomarkers. We combined the advantages of monocyte-derived hepatocyte-like (MH) cells, able to mimic individual characteristics, with those of a novel mass spectrometry-based proteomics technology to assess potential biomarkers for Diclofenac-induced DILI. We found over 2,700 proteins differentially regulated in MH cells derived from individual patients. Herefrom, we identified integrin beta 3 (ITGB3) to be specifically upregulated in Diclofenac-treated MH cells from Diclofenac-DILI patients compared to control groups. Finally, we validated ITGB3 by flow cytometry analysis of whole blood and histological staining of liver biopsies derived from patients diagnosed with Diclofenac-DILI. In summary, our results show that biomarker candidates can be identified by proteomics analysis of MH cells. Application of this method to a broader range of drugs in the future will exploit its full potential for the development of drug-specific biomarkers. Data are available via ProteomeXchange with identifier PXD008918.