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Fahrner, M.

Publications and source records attributed to Fahrner, M..

9 recordsLinked to original sources

STIM1 transmembrane helix dimerization captured by AI-guided transition path sampling

STIM1 is a Ca2+-sensing protein in the endoplasmic reticulum (ER) membrane. The depletion of ER Ca2+ stores induces a large conformational transition of the cytosolic STIM1 C-terminus, initiated by the dimerization of the transmembrane (TM) domain. We use the AI-guided transition path sampling algorithm aimmd to extensively sample the dimerization of STIM1-TM helices in an ER-mimicking lipid bilayer. In nearly 0.5 milliseconds of all-atom molecular dynamics simulations without bias potentials, we harvest over 170 transition paths, each about 1.2 {micro}s long on average. We find that STIM1 dimerizes into three distinct and coexisting configurations, which reconciles conflicting results from earlier crosslinking studies. The dominant X-shaped bound state centers around contacts supported by the SxxxG TM interfacial motif. Mutating residues in this contact interface allows us to tune the STIM1-dimerization propensity in fluorescence experiments. From the trained model of the committor probability of dimerization, we identify the transition state ensemble for TM-helix dimerization. At the transition state, interhelical contacts in the luminal halves of the two monomers dominate, which likely enables the luminal Ca2+-sensing domain in STIM1 to condition the dimerization of the TM helices. Our work demonstrates the unique power of AI-guided simulations to sample rare and slow molecular transitions, and to produce detailed atomistic insight into the mechanism of STIM1 TM-helix dimerization as a key step in ER Ca2+-sensing. SignificanceSTIM1 is a protein sensor that signals drops in the Ca2+ concentration inside the endoplasmic reticulum (ER) to the cytosol. As Ca2+ levels decrease, the STIM1 transmembrane (TM) helices dimerize. We sample this TM helix dimerization in AI-guided atomistic molecular simulations, revealing two distinct pathways of dimerization. We reconcile conflicting results of earlier crosslinking studies by showing that both reported dimer configurations coexist as the end points of distinct association pathways. The dominance of interhelical contacts on the luminal side at the transition state enables the luminal Ca2+-sensing domain to condition helix dimerization. AI-guided path sampling made it possible to sample rare helix dimerization events far outside the current reach of regular molecular simulations.

biophysics↗

Serum Proteome Profiling Identifies N-Cadherin and C-Met as Early Marker Candidates of Therapeutic Response to Neoadjuvant Chemotherapy in Breast Cancer

Breast cancer remains the most common cancer in women worldwide. Neoadjuvant chemotherapy (NACT) is often preferred to adjuvant chemotherapy to achieve tumour shrinkage, monitor response to therapy and facilitate surgical removal in the absence of metastases. In addition, there is strong evidence that pathological complete remission (pCR) is associated with prolonged survival. In this study, we sought to identify candidate markers that signal response or resistance to therapy. We present a retrospective longitudinal serum proteomic study of 22 breast cancer patients (11 with pCR and 11 with non-pCR) matched with 21 healthy controls. Serum was analysed by LC-MS/MS after depletion of abundant proteins by immunoaffinity, trypsinisation, isobaric labelling and fractionation by reversed-phase HPLC. We observed an inverse behaviour of the serum proteins c-Met and N-cadherin after the second cycle of chemotherapy with a high predictive value (AUC 0.93). More pronounced changes were observed after the 6th cycle of NACT, with significant changes in the intensity of the proteins contactin-1, centrosomal protein, sex hormone-binding globuline and cholinesterase. Our study highlights the possibility of monitoring response to NACT using serum as a liquid biopsy.

cancer biology↗

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↗

Galaxy Training: A Powerful Framework for Teaching!

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis and stewardship are still rarely taught in life science educational programs [1], resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org); an open access, community-driven framework for the collection of FAIR training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform [2]. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments.

bioinformatics↗

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↗

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↗

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↗

A series of Orai1 gating checkpoints in transmembrane and cytosolic regions requires clearance for CRAC channel opening/ Clearance and synergy of Orai1 gating checkpoints controls pore opening

The initial activation step in gating of ubiquitously expressed Orai1 Calcium (Ca2+) ion channels represents the store-dependent coupling to the Ca2+ sensor protein STIM1. An array of constitutively active Orai1 mutants gave rise to the hypothesis that STIM1 mediated Orai1 pore opening is accompanied by a global conformational change of all Orai TM helices within the channel complex. Here, we prove that a local conformational change spreads omnidirectionally within the Orai1 complex. Our results demonstrate that a global, opening-permissive allosteric communication of TM helices is indispensable for pore opening and requires clearance of a series of Orai1 gating checkpoints. We discovered these gating checkpoints in middle and cytosolic extended TM domain regions. Our findings are based on a library of double point mutants that contain each one loss-of-function (LoF) with one gain-of-function (GoF) point mutation in a series of possible combinations. We demonstrated that an array of LoF mutations act dominant over most GoF mutations within the same as well as of an adjacent Orai subunit. We further established inter- and intramolecular salt-bridge interactions of Orai subunits as a core element of an opening-permissive Orai channel architecture. Collectively, clearance and synergistic action of all these gating checkpoints is required to allow STIM1 coupling and Orai1 pore opening. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/207183v2_ufig1.gif" ALT="Figure 1"> View larger version (76K): org.highwire.dtl.DTLVardef@3f80f1org.highwire.dtl.DTLVardef@12a6a0aorg.highwire.dtl.DTLVardef@197b825org.highwire.dtl.DTLVardef@1bab109_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

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↗