Biology subjects

Schilling, O.

Publications and source records attributed to Schilling, O..

29 records · Page 2Linked to original sources

bioRxiv2023

An EOMES induced epigenetic deflection initiates lineage commitment at mammalian gastrulation

Summary paragraph Different cell types are determined by cell lineage-specific transcriptional programmes and by epigenetic regulation of chromatin1, 2. Yet, the functional relationships between dynamically expressed transcription factors (TFs) and chromatin changes guiding lineage specification often remain elusive3. First mammalian embryonic lineages segregate when pluripotent cells become committed to either Mesoderm and Endoderm (ME) or Neuroectoderm (NE). NE forms by default in the absence of signalling-induced ME specification4, 5, resulting from global asymmetries in chromatin state favouring NE gene programme activation as recently demonstrated6-8. In this study, we unravel the initiation of ME lineage specification by the genome-wide, de novo formation of chromatin accessibility at ME enhancers that epigenetically deflects pluripotent cells from default NE differentiation. The Tbx TF Eomes, previously considered a transcriptional regulator, acts as global chromatin organizer that establishes ME lineage competence. EOMES recruits the canonical ATP-dependent chromatin remodelling complex SWI/SNF to broadly generate the chromatin- accessible ME enhancer landscape. This lineage competence is generated independently of ME gene transcription that fully depends on ME-inducing signalling pathways including Wnts and TGF{beta}/NODAL9. This study thus resolves the successive steps of ME lineage differentiation by globally establishing chromatin accessibility for lineage competence, followed by signal-encoded transcriptional regulation of different ME lineage-defining gene programmes.

developmental biology↗

bioRxiv2022

The Impact of Peri-implantitis on the Proteome Biology of Crevicular Fluid: A pilot study

BackgroundThe proteome of the peri-implant crevicular fluid (PICF) has not been systematically investigated. The aim of the present study was to reveal the proteome biology of dental implants affected with peri-implantitis. MethodsPatients with at least one diseased implant were included (probing depth [≥] 6 mm, [≥] 3 mm peri-implant radiological bone loss). Using sterile paper strips, samples were collected from healthy implants (I), healthy teeth (T) and peri-implantitis affected implants (P). Proteome analysis was performed using liquid chromatography - tandem mass spectrometry (LC-MS/MS) and data independent acquisition, allowing the identification and quantification of human and bacterial proteins as well as semi-specific peptides. Results38 samples from 13 patients were included in the study. 2332 different human proteins were identified across all samples. No differentially expressed proteins between T and I were found. Comparing P to I, 59 proteins were found upregulated and 31 downregulated in P with significance. Upregulated proteins included proinflammatory proteins such as immunoglobulins, dysferlin and S100P, as well as antimicrobial proteins, e.g. myeloperoxidase or azurocidin. Gene ontology analysis further revealed higher activity of immunological pathways. Proteolytic patterns indicated the activity of inflammatory proteins such as cathepsin G. 334 bacterial proteins were identified and quantified. Peri-implantitis showed elevated proteolytic activity. ConclusionI and T share similarities in their proteome, while diseased implants deviate strongly from healthy conditions. The PICF proteome of peri-implantitis affected sites exhibits an inflammatory fingerprint, dominated by neutrophile activity when compared to healthy implants. SummaryProteomic analysis of the peri-implant crevicular fluid revealed distinct proteome alterations in peri-implantitis when compared to healthy implants and teeth, while healthy teeth and implants share strong similarities.

molecular biology↗

bioRxiv2022

Targeted and Explorative Profiling of Kallikrein Proteases and Global Proteome Biology of Pancreatic Ductal Adenocarcinoma, Chronic Pancreatitis, and Normal Pancreas Highlights Disease-Specific Proteome Remodelling

Pancreatic ductal adenocarcinoma (PDAC) represents one of the most aggressive and lethal malignancies worldwide with an urgent need for new diagnostic and therapeutic strategies. One major risk factor for PDAC is the pre-indication of chronic pancreatitis (CP), which represents highly inflammatory pancreatic tissue. Kallikreins (KLKs) are secreted serine proteases that play an important role in various cancers as components of the tumor microenvironment. Previous studies of KLKs in solid tumors largely relied on either transcriptomics or immunodetection. We present one of the first targeted mass spectrometry profiling of kallikrein proteases in PDAC, CP, and normal pancreas. We show that KLK6 and KLK10 are significantly upregulated in PDAC (n=14) but not in CP (n=7) when compared to normal pancreas (n=21), highlighting their specific intertwining with malignancy. Additional explorative proteome profiling identified 5936 proteins in our pancreatic cohort and observed disease-specific proteome rearrangements in PDAC and CP. As such, PDAC features an enriched proteome motif for extracellular matrix (ECM) and cell adhesion while there is depletion of mitochondrial energy metabolism proteins, reminiscent of the Warburg effect. Although often regarded as a PDAC hallmark, the ECM fingerprint was also observed in CP, alongside with a prototypical inflammatory proteome motif as well as with an increased wound healing process and proteolytic activity, thereby possibly illustrating tissue autolysis. Proteogenomic analysis based on publicly accessible data sources identified 112 PDAC-specific and 32 CP-specific single amino acid variants, which among others affect KRAS and ANKHD1. Our study emphasizes the diagnostic potential of kallikreins and provides novel insights into proteomic characteristics of PDAC and CP.

cancer biology↗

bioRxiv2022

Changes in calpain-2 expression during glioblastoma progression predisposes tumor cells to temozolomide resistance by minimizing DNA damage and p53-dependent apoptosis

BackgroundGlioblastoma multiforme (GBM) is characterized by an unfavorable prognosis for patients affected. During standard-of-care chemotherapy using temozolomide (TMZ), tumors acquire resistance thereby causing tumor recurrence. Thus, deciphering essential molecular pathways causing TMZ resistance are of high therapeutic relevance. MethodsMass spectrometry based proteomics were used to study the GBM proteome. Immunohistochemistry staining of human GBM tissue for either calpain-1 or -2 was performed to locate expression of proteases. In vitro cell based assays were used to measure cell viability and survival of primary patient-derived GBM cells and established GBM cell lines after TMZ +/- calpain inhibitor administration. shRNA expression knockdowns of either calpain-1 or calpain-2 were generated to study TMZ sensitivity of the specific subunits. The Comet assay and {gamma}H2AX signal measurements were performed in order to assess the DNA damage amount and recognition. Finally, quantitative real-time PCR of target proteins was applied to differentiate between transcriptional and post-translational regulation. ResultsCalcium-dependent calpain proteases, in particular calpain-2, are more abundant in glioblastoma compared to normal brain and increased in patient-matched initial and recurrent glioblastomas. On the cellular level, pharmacological calpain inhibition increased the sensitivities of primary glioblastoma cells towards TMZ. A genetic knockdown of calpain-2 in U251 cells led to increased caspase-3 cleavage and sensitivity to neocarzinostatin, which rapidly induces DNA strand breakage. We hypothesize that calpain-2 causes desensitization of tumor cells against TMZ by preventing strong DNA damage and subsequent apoptosis via post-translational TP53 inhibition. Indeed, proteomic comparison of U251 control vs. U251 calpain-2 knockdown cells highlights perturbed levels of numerous proteins involved in DNA damage response and downstream pathways affecting TP53 and NF-{kappa}B signaling. TP53 showed increased protein abundance, but no transcriptional regulation. ConclusionTMZ-induced cell death in the presence of calpain-2 expression appears to favor DNA repair and promote cell survival. We conclude from our experiments that calpain-2 expression represents a proteomic mode that is associated with higher resistance via "priming" GBM cells to TMZ chemotherapy. Thus, calpain-2 could serve as a prognostic factor for GBM outcome.

cancer biology↗

bioRxiv2022

MaxQuant and MSstats in Galaxy enable reproducible cloud-based analysis of quantitative proteomics experiments for everyone

Quantitative mass spectrometry-based proteomics has become a high-throughput technology for the identification and quantification of thousands of proteins in complex biological samples. Two de facto standard tools, MaxQuant and MSstats, allow for the analysis of raw data and finding proteins with differential abundance between conditions of interest. To enable accessible and reproducible quantitative proteomics analyses in a cloud environment, we have integrated MaxQuant (including TMTpro 16/18plex), Proteomics Quality Control (PTXQC), MSstats and MSstatsTMT into the open-source Galaxy framework. This enables the web-based analysis of label-free and isobaric labeling proteomics experiments via Galaxys graphical user interface on public clouds. MaxQuant and MSstats in Galaxy can be applied in conjunction with thousands of existing Galaxy tools and integrated into standardized, sharable workflows. Galaxy tracks all metadata and intermediate results in analysis histories, which can be shared privately for collaborations or publicly, allowing full reproducibility and transparency of published analysis. To further increase accessibility, we provide detailed hands-on training materials. The integration of MaxQuant and MSstats into the Galaxy framework enables their usage in a reproducible way on accessible large computational infrastructures, hence realizing the foundation for high throughput proteomics data science for everyone.

biochemistry↗

bioRxiv2021

Proteome biology of primary colorectal carcinoma and corresponding liver metastases

Colorectal adenocarcinomas (CRC) are one of the most commonly diagnosed tumors worldwide. Colorectal adenocarcinomas primarily metastasize into the liver and (less often) into the peritoneum. Patients suffering from CRC-liver metastasis (CRC-LM) typically present with a dismal overall survival compared to non-metastasized CRC patients. The metastasis process and metastasis-promoting factors in patients with CRC are under intensive debate. However, CRC studies investigating the proteome biology are lacking. Formalin-fixed paraffin-embedded (FFPE) tissue specimens provide a valuable resource for comprehensive proteomic studies of a broad variety of clinical malignancies. The presented pilot study compares the proteome of primary CRC and patient-matched CRC-LM. The applied protocol allows a reproducible and straightforward identification and quantification of over 2,600 proteins within the dissected tumorous tissue. Subsequent unsupervised clustering reveals distinct proteome biologies of the primary CRC and the corresponding CRC-LM. Statistical analysis yields multiple differentially abundant proteins in either primary CRC or their corresponding liver metastases. A more detailed analysis of dysregulated biological processes suggests an active immune response in the liver metastases, including several proteins of the complement system. Proteins with structural roles, e.g. cytoskeleton organization or cell junction assembly appear to be less prominent in liver metastases as compared to primary CRC. Immunohistochemistry corroborates proteomic high expression levels of metabolic proteins in CRC-LM. We further assessed how the in vitro inhibition of two in CRC-LM enriched metabolic proteins affected cell proliferation and chemosensitivity. The presented proteomic investigation in a small clinical cohort promotes a more comprehensive understanding of the distinct proteome biology of primary CRC and their corresponding liver metastases.

cancer biology↗

bioRxiv2021

Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: A case study of an urothelial cancer cohort analyzed in the Galaxy framework

BackgroundMass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens. This allows for spatial characterization of molecular compositions of different tissue types and tumor subtypes, which bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of an urothelial carcinoma dataset. MethodsTryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle invasive urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. ResultsRigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle invasive tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: Stromal tissue was characterized by collagen type I peptides and tumor tissue by histone and heat shock protein beta-1 peptides. Intermediate filaments such as cytokeratins and vimentin were discriminative between the tumors with different muscle-infiltration status. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links. ConclusionHere, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.

cancer biology↗

bioRxiv2021

Democratizing Data-Independent Acquisition Proteomics Analysis on Public Cloud Infrastructures Via The Galaxy Framework

Data-independent acquisition (DIA) has become an important approach in global, mass spectrometric proteomic studies because it provides in-depth insights into the molecular variety of biological systems. However, DIA data analysis remains challenging due to the high complexity and large data and sample size, which require specialized software and large computing infrastructures. Most available open-source DIA software necessitate basic programming skills and cover only a fraction of the analysis steps, often yielding a complex of multiple software tools, severely limiting usability and reproducibility. To overcome this hurdle, we have integrated a suite of DIA tools in the Galaxy framework for reproducible and version-controlled data processing. The DIA suite includes OpenSwath, PyProphet, diapysef and swath2stats. We have compiled functional Galaxy pipelines for DIA processing, which provide a web-based graphical user interface to these pre-installed and pre-configured tools for their usage on freely accessible, powerful computational resources of the Galaxy framework. This approach also enables seamless sharing workflows with full configuration in addition to sharing raw data and results. We demonstrate usability of the all-in-one DIA pipeline in Galaxy by the analysis of a spike-in case study dataset. Additionally, extensive training material is provided, to further increase access for the proteomics community.

bioinformatics↗

bioRxiv2020

Discovery of a novel small protein factor involved in the coordinated degradation of phycobilisomes in cyanobacteria

Phycobilisomes are the major pigment-protein antenna complexes that perform photosynthetic light harvesting in cyanobacteria, rhodophyte and glaucophyte algae. Up to 50% of the cellular nitrogen can be stored in their giant structures. Accordingly, upon nitrogen depletion, phycobilisomes are rapidly degraded. This degradation is tightly coordinated, follows a genetic program and involves small proteins serving as proteolysis adaptors. Here, we describe the role of NblD, a novel factor in this process in cyanobacteria. NblD is a cysteine-rich, 66-amino acid small protein that becomes rapidly induced upon nitrogen starvation. Deletion of the nblD gene in the cyanobacterium Synechocystis prevents the degradation of phycobilisomes, leading to a nonbleaching (nbl) phenotype. Competition experiments provided direct evidence for the physiological importance of NblD. Complementation by a plasmid-localized gene copy fully restored the phenotype of the wild type. Overexpression of NblD under nitrogen-replete conditions showed no effect, in contrast to the unrelated proteolysis adaptors NblA1 and NblA2, which can trigger phycobilisome degradation ectopically. Transcriptome analysis revealed that nitrogen starvation correctly induces nblA1/2 transcription in the {Delta}nblD strain implying that NblD does not act as a transcriptional (co-)regulator. However, fractionation and coimmunoprecipitation experiments indicated the presence of NblD in the phycobilisome fraction and identified the {beta}-phycocyanin subunit as its target. These data add NblD as a new factor to the genetically programmed response to nitrogen starvation and demonstrate that it plays a crucial role in the coordinated dismantling of phycobilisomes when nitrogen becomes limiting. Significance StatementDuring genome analysis, genes encoding small proteins are frequently neglected. Accordingly, small proteins have remained underinvestigated in all domains of life. Based on a previous systematic search for such genes, we present the functional analysis of the small protein NblD in a photosynthetic cyanobacterium. We show that NblD plays a crucial role during the coordinated dismantling of phycobilisome light-harvesting complexes. This disassembly is triggered when the cells run low in nitrogen, a condition that frequently occurs in nature. Similar to the NblA proteins that label phycobiliproteins for proteolysis, NblD binds to phycocyanin polypeptides but has a different function. The results show that, even in a well-investigated process, crucial new players can be discovered if small proteins are taken into consideration.

microbiology↗

bioRxiv2019

Accessible and reproducible mass spectrometry imaging data analysis in Galaxy

BackgroundMass spectrometry imaging is increasingly used in biological and translational research as it has the ability to determine the spatial distribution of hundreds of analytes in a sample. Being at the interface of proteomics/metabolomics and imaging, the acquired data sets are large and complex and often analyzed with proprietary software or in-house scripts, which hinder reproducibility. Open source software solutions that enable reproducible data analysis often require programming skills and are therefore not accessible to many MSI researchers.\n\nFindingsWe have integrated 18 dedicated mass spectrometry imaging tools into the Galaxy framework to allow accessible, reproducible, and transparent data analysis. Our tools are based on Cardinal, MALDIquant, and scikit-image and enable all major MSI analysis steps such as quality control, visualization, preprocessing, statistical analysis, and image co-registration. Further, we created hands-on training material for use cases in proteomics and metabolomics. To demonstrate the utility of our tools, we re-analyzed a publicly available N-linked glycan imaging dataset. By providing the entire analysis history online, we highlight how the Galaxy framework fosters transparent and reproducible research.\n\nConclusionThe Galaxy framework has emerged as a powerful analysis platform for the analysis of MSI data with ease of use and access together with high levels of reproducibility and transparency.

bioinformatics↗

bioRxiv2017

HtrA1 activation is driven by an allosteric mechanism of inter-monomer communication

The human protease family HtrA is responsible for preventing protein misfolding and mislocalization, and a key player in several cellular processes. Among these, HtrA1 is implicated in several cancers, cerebrovascular disease and age-related macular degeneration. HtrA1 activation, although very relevant for drug-targeting this protease, remains poorly characterized. Our work provides a mechanistic step-by-step description of HtrA1 activation and regulation. We report that the HtrA1 trimer is regulated by an allosteric mechanism by which monomers relay the activation signal to each other, in a PDZ-domain independent fashion. Notably, we show that inhibitor binding is precluded if HtrA1 monomers cannot communicate with each other. Our study establishes how HtrA1 oligomerization plays a fundamental role in proteolytic activity. Moreover, it offers a structural explanation for HtrA1-defective pathologies as well as mechanistic insights into the degradation of complex extracellular fibrils such as tubulin, amyloid beta and tau that belong to the repertoire of HtrA1.\n\nHighlightsO_LIMonomeric HtrA1 is activated by a gating mechanism.\nC_LIO_LITrimeric HtrA1 is regulated by PDZ-independent allosteric monomer cross-talk.\nC_LIO_LIHtrA1 oligomerization is key for proteolytic activity.\nC_LIO_LISubstrate-binding is precluded if monomers cannot communicate with each other.\nC_LI

biophysics↗