Bridging data management platforms and visualization tools to enable ad-hoc and smart analytics in life sciences

The nucleolar granular component mediates genome-nucleolus interactions and establishes their repressive chromatin states

Repressive chromatin domains often localize to the nuclear lamina or nucleolus. Although nucleolar-associated domains (NADs) have recently been mapped, their mechanisms of nucleolar association and functional significance remain unclear. Here, we show that nucleophosmin (NPM1), a factor located in the granular component of the nucleolus, mediates NAD association in mouse embryonic stem cells. NPM1 binds NADs, interacts with the histone methyltransferase G9a (EHMT2), and is required for establishing H3K9me2 at NADs. Loss of NPM1 or expression of a DNA-binding-deficient mutant disrupts NAD-nucleolus association and reduces H3K9me2 specifically at NADs. G9a is dispensable for NAD-nucleolus contacts, indicating that H3K9me2 is acquired after NADs associate with NPM1 at nucleoli. These findings reveal mechanistic insights into how genomic domains associate with nucleoli and form repressive chromatin and indicate that the nucleolus not only serves as a scaffold for positioning repressive domains but also plays a direct role in establishing their repressive chromatin states.

The landscape of renal protein S-acylation in mice with lipid-induced nephrotoxicity

Excess fat intake is associated with kidney toxicity and dysfunction. Because fatty acids can also be reversibly attached onto cysteine residues and modulate the function of several membrane-bound proteins, we studied the effect of high-fat diet (HFD) on the S-acylated proteome of mouse kidneys to uncover novel biochemical changes that might contribute to lipid-induced nephrotoxicity. We compared the S-acylated proteome of kidneys from mice fed a chow diet (CD) or a HFD. HFD caused albuminuria. The HFD intervention induced a large-scale repression of protein S-acylation as well as of the most abundant ceramides and sphingomyelin species, which are highly suggestive of a reduction in acyl-CoA availability. The HFD-induced S-acylation repression mostly affected proteins involved in endocytosis and intracellular transport. Notably, the kidneys of mice fed a HFD displayed a marked decrease in the total amount and in the S-acylated form of megalin, the main tubular protein retrieval system. Further in vitro experiments indicated that S-acylation inhibition results in a reduction of megalin protein level. We conclude that diet-induced derangement of fatty acid metabolism modifies the renal landscape of the S-acylated proteome during the early stages of the kidney injury, which might reduce the efficiency of protein reabsorption by the proximal tubule.

prolfquapp ─ A User-Friendly Command-Line Tool Simplifying Differential Expression Analysis in Quantitative Proteomics

Mass spectrometry is a cornerstone of quantitative proteomics, enabling relative protein quantification and differential expression analysis (DEA) of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, interactive differential expression analysis tools become impractical. The prolfquapp addresses this challenge by providing a command-line interface that simplifies DEA, making it accessible to nonprogrammers and seamlessly integrating it into workflow management systems. Prolfquapp streamlines data processing and result visualization by generating dynamic HTML reports that facilitate the exploration of differential expression results. These reports allow for investigating complex experiments, such as those involving repeated measurements or multiple explanatory variables. Additionally, prolfquapp supports various output formats, including XLSX files, SummarizedExperiment objects and rank files, for further interactive analysis using spreadsheet software, the exploreDE Shiny application, or gene set enrichment analysis software, respectively. By leveraging advanced statistical models from the prolfqua R package, prolfquapp offers a user-friendly, integrated solution for large-scale quantitative proteomics studies, combining efficient data processing with insightful, publication-ready outputs.

An inhibitory segment within G-patch activators tunes Prp43-ATPase activity during ribosome assembly

Mechanisms by which G-patch activators tune the processive multi-tasking ATP-dependent RNA helicase Prp43 (DHX15 in humans) to productively remodel diverse RNA:protein complexes remain elusive. Here, a comparative study between a herein and previously characterized activators, Tma23 and Pxr1, respectively, defines segments that organize Prp43 function during ribosome assembly. In addition to the activating G-patch, we discover an inhibitory segment within Tma23 and Pxr1, I-patch, that restrains Prp43 ATPase activity. Cryo-electron microscopy and hydrogen-deuterium exchange mass spectrometry show how I-patch binds to the catalytic RecA-like domains to allosterically inhibit Prp43 ATPase activity. Tma23 and Pxr1 contain dimerization segments that organize Prp43 into higher-order complexes. We posit that Prp43 function at discrete locations on pre-ribosomal RNA is coordinated through toggling interactions with G-patch and I-patch segments. This could guarantee measured and timely Prp43 activation, enabling precise control over multiple RNA remodelling events occurring concurrently during ribosome formation.

Interaction proteomics analysis to provide insight into TFAMoplex-mediated transfection

In an earlier investigation, our group introduced the TFAMoplex, a transfection agent based on the mitochondrial transcription factor A (TFAM) protein, which complexes DNA into nanoparticles. The original TFAMoplex further contained a bacterial phospholipase to achieve endosomal escape, and the vaccinia-related kinase 1 (VRK1), which significantly boosted the transfection efficiency of the system by an unknown mechanism. This study aims at replacing VRK1 within the TFAMoplex with dynein light chain proteins, specifically RP3, to directly tether the complexes to the dynein motor complex for enhanced cytosolic transport. To confirm the interaction between the dynein complex and the resulting fusion protein, we examined the binding kinetics of TFAM-RP3 to the dynein intermediate chains 1 and 2. Furthermore, we established a proteomics-based assay to compare cytosolic protein interactions of different TFAMoplex variants, including the RP3-modified version and the original VRK1-containing system. In the group of the VRK1-containing TFAMoplex, significant shifts of protein interactors were observed, especially for nucleolar proteins. Leveraging this knowledge, we incorporated one of these nuclear proteins, leucine-rich repeat-containing protein 59 (LRRC59), into the TFAMoplex, resulting in a significant improvement of transfection properties compared to the RP3-modified system and comparable levels versus the original, VRK1-containing version. This study not only advances our comprehension of the TFAMoplex system but also offers broader insights into the potential of protein engineering for designing effective gene delivery systems.

Leonhard Med, a trusted research environment for processing sensitive research data

This paper provides an overview of the development and operation of the Leonhard Med Trusted Research Environment (TRE) at ETH Zurich. Leonhard Med gives scientific researchers the ability to securely work on sensitive research data. We give an overview of the user perspective, the legal framework for processing sensitive data, design history, current status, and operations. Leonhard Med is an efficient, highly secure Trusted Research Environment for data processing, hosted at ETH Zurich and operated by the Scientific IT Services (SIS) of ETH. It provides a full stack of security controls that allow researchers to store, access, manage, and process sensitive data according to Swiss legislation and ETH Zurich Data Protection policies. In addition, Leonhard Med fulfills the BioMedIT Information Security Policies and is compatible with international data protection laws and therefore can be utilized within the scope of national and international collaboration research projects. Initially designed as a "bare-metal" High-Performance Computing (HPC) platform to achieve maximum performance, Leonhard Med was later re-designed as a virtualized, private cloud platform to offer more flexibility to its customers. Sensitive data can be analyzed in secure, segregated spaces called tenants. Technical and Organizational Measures (TOMs) are in place to assure the confidentiality, integrity, and availability of sensitive data. At the same time, Leonhard Med ensures broad access to cutting-edge research software, especially for the analysis of human -omics data and other personalized health applications.

A synthetic methylotrophic Escherichia coli as a chassis for bioproduction from methanol

Methanol synthesized from captured greenhouse gases is an emerging renewable feedstock with great potential for bioproduction. Recent research has raised the prospect of methanol bioconversion to value-added products using synthetic methylotrophic Escherichia coli, as its metabolism can be rewired to enable growth solely on the reduced one-carbon compound. Here we describe the generation of an E. coli strain that grows on methanol at a doubling time of 4.3 h-comparable to many natural methylotrophs. To establish bioproduction from methanol using this synthetic chassis, we demonstrate biosynthesis from four metabolic nodes from which numerous bioproducts can be derived: lactic acid from pyruvate, polyhydroxybutyrate from acetyl coenzyme A, itaconic acid from the tricarboxylic acid cycle and p-aminobenzoic acid from the chorismate pathway. In a step towards carbon-negative chemicals and valorizing greenhouse gases, our work brings synthetic methylotrophy in E. coli within reach of industrial applications.

Stepwise assembly and release of Tc toxins from Yersinia entomophaga

Tc toxins are virulence factors of bacterial pathogens. Although their structure and intoxication mechanism are well understood, it remains elusive where this large macromolecular complex is assembled and how it is released. Here we show by an integrative multiscale imaging approach that Yersinia entomophaga Tc (YenTc) toxin components are expressed only in a subpopulation of cells that are 'primed' with several other potential virulence factors, including filaments of the protease M66/StcE. A phage-like lysis cassette is required for YenTc release; however, before resulting in complete cell lysis, the lysis cassette generates intermediate 'ghost' cells, which may serve as assembly compartments and become packed with assembled YenTc holotoxins. We hypothesize that this stepwise mechanism evolved to minimize the number of cells that need to be killed. The occurrence of similar lysis cassettes in diverse organisms indicates a conserved mechanism for Tc toxin release that may apply to other extracellular macromolecular machines.

Metadata integrity in bioinformatics: Bridging the gap between data and knowledge

In the fast-evolving landscape of biomedical research, the emergence of big data has presented researchers with extraordinary opportunities to explore biological complexities. In biomedical research, big data imply also a big responsibility. This is not only due to genomics data being sensitive information but also due to genomics data being shared and re-analysed among the scientific community. This saves valuable resources and can even help to find new insights in silico. To fully use these opportunities, detailed and correct metadata are imperative. This includes not only the availability of metadata but also their correctness. Metadata integrity serves as a fundamental determinant of research credibility, supporting the reliability and reproducibility of data-driven findings. Ensuring metadata availability, curation, and accuracy are therefore essential for bioinformatic research. Not only must metadata be readily available, but they must also be meticulously curated and ideally error-free. Motivated by an accidental discovery of a critical metadata error in patient data published in two high-impact journals, we aim to raise awareness for the need of correct, complete, and curated metadata. We describe how the metadata error was found, addressed, and present examples for metadata-related challenges in omics research, along with supporting measures, including tools for checking metadata and software to facilitate various steps from data analysis to published research.

Interferon restores replication fork stability and cell viability in BRCA-defective cells via ISG15

DNA replication and repair defects or genotoxic treatments trigger interferon (IFN)-mediated inflammatory responses. However, whether and how IFN signaling in turn impacts the DNA replication process has remained elusive. Here we show that basal levels of the IFN-stimulated gene 15, ISG15, and its conjugation (ISGylation) are essential to protect nascent DNA from degradation. Moreover, IFNβ treatment restores replication fork stability in BRCA1/2-deficient cells, which strictly depends on topoisomerase-1, and rescues lethality of BRCA2-deficient mouse embryonic stem cells. Although IFNβ activates hundreds of genes, these effects are specifically mediated by ISG15 and ISGylation, as their inactivation suppresses the impact of IFNβ on DNA replication. ISG15 depletion significantly reduces cell proliferation rates in human BRCA1-mutated triple-negative, whereas its upregulation results in increased resistance to the chemotherapeutic drug cisplatin in mouse BRCA2-deficient breast cancer cells, respectively. Accordingly, cells carrying BRCA1/2 defects consistently show increased ISG15 levels, which we propose as an in-built mechanism of drug resistance linked to BRCAness.

prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis

Mass spectrometry is widely used for quantitative proteomics studies, relative protein quantification, and differential expression analysis of proteins. There is a large variety of quantification software and analysis tools. Nevertheless, there is a need for a modular, easy-to-use application programming interface in R that transparently supports a variety of well principled statistical procedures to make applying them to proteomics data, comparing and understanding their differences easy. The prolfqua package integrates essential steps of the mass spectrometry-based differential expression analysis workflow: quality control, data normalization, protein aggregation, statistical modeling, hypothesis testing, and sample size estimation. The package makes integrating new data formats easy. It can be used to model simple experimental designs with a single explanatory variable and complex experiments with multiple factors and hypothesis testing. The implemented methods allow sensitive and specific differential expression analysis. Furthermore, the package implements benchmark functionality that can help to compare data acquisition, data preprocessing, or data modeling methods using a gold standard data set. The application programmer interface of prolfqua strives to be clear, predictable, discoverable, and consistent to make proteomics data analysis application development easy and exciting. Finally, the prolfqua R-package is available on GitHub https://github.com/fgcz/prolfqua, distributed under the MIT license. It runs on all platforms supported by the R free software environment for statistical computing and graphics.

Proteomic profiling of canine fibrosarcoma and adjacent peritumoral tissue

Fibrosarcoma (FSA) are rare soft tissue tumors that display aggressive local behavior and invasive growth leading to high rates of tumor recurrence. While the low incidence in humans hampers detailed understanding of the disease, FSA are frequent in dogs and present potential models for the human condition. However, a lack of in-depth molecular characterization of FSA and unaffected peritumoral tissue (PTT) in both species impedes the translational potential of dogs. To address this shortcoming, we characterized canine FSA and matched skeletal muscle, adipose and connective tissue using laser-capture microdissection (LCM) and LC-MS/MS in 30 formalin-fixed paraffin embedded (FFPE) specimens. Principal component analysis of 3'530 different proteins detected across all samples clearly separates the four tissues, with several targets strongly differentiating tumor from all three PTTs. 25 proteins were exclusively found in tumor tissue in ≥80% of cases. Among these, CD68 (a macrophage marker), Optineurin (OPTN), Nuclear receptor coactivator 5 (NCOA5), RAP1GDS1 (Rap1 GTPase-GDP dissociation stimulator 1) and Stromal cell derived factor 2 like 1 (SDF2L1) were present in ≥90% of FSA. Protein expression across all FSA was highly homogeneous and characterized by MYC and TP53 signaling, hyperactive EIF2 and immune-related changes as well as strongly decreased oxidative phosphorylation and oxidative lipid metabolism. Finally, we demonstrate significant molecular homology between canine FSA and human soft-tissue sarcomas, emphasizing the relevance of studying canine FSA as a model for human FSA. In conclusion, we provide the first detailed overview of proteomic changes in FSA and surrounding PTT with relevance for the human disease.