Allelic effects on uromodulin aggregates drive autosomal dominant tubulointerstitial kidney disease

Missense mutations in the uromodulin (UMOD) gene cause autosomal dominant tubulointerstitial kidney disease (ADTKD), one of the most common monogenic kidney diseases. The unknown impact of the allelic and gene dosage effects and fate of mutant uromodulin leaves open the gap between postulated gain-of-function mutations, end-organ damage and disease progression in ADTKD. Based on two prevalent missense UMOD mutations with divergent disease progression, we generated UmodC171Y and UmodR186S knock-in mice that showed strong allelic and gene dosage effects on uromodulin aggregates and activation of ER stress and unfolded protein and immune responses, leading to variable kidney damage. Deletion of the wild-type Umod allele in heterozygous UmodR186S mice increased the formation of uromodulin aggregates and ER stress. Studies in kidney tubular cells confirmed differences in uromodulin aggregates, with activation of mutation-specific quality control and clearance mechanisms. Enhancement of autophagy by starvation and mTORC1 inhibition decreased uromodulin aggregates. These studies substantiate the role of toxic aggregates as driving progression of ADTKD-UMOD, relevant for therapeutic strategies to improve clearance of mutant uromodulin.

Morphogenesis and development of human telencephalic organoids in the absence and presence of exogenous extracellular matrix

The establishment and maintenance of apical-basal polarity is a fundamental step in brain development, instructing the organization of neural progenitor cells (NPCs) and the developing cerebral cortex. Particularly, basally located extracellular matrix (ECM) is crucial for this process. In vitro, epithelial polarization can be achieved via endogenous ECM production, or exogenous ECM supplementation. While neuroepithelial development is recapitulated in neural organoids, the effects of different ECM sources in tissue morphogenesis remain underexplored. Here, we show that exposure to a solubilized basement membrane matrix substrate, Matrigel, at early neuroepithelial stages causes rapid tissue polarization and rearrangement of neuroepithelial architecture. In cultures exposed to pure ECM components or unexposed to any exogenous ECM, polarity acquisition is slower and driven by endogenous ECM production. After the onset of neurogenesis, tissue architecture and neuronal differentiation are largely independent of the initial ECM source, but Matrigel exposure has long-lasting effects on tissue patterning. These results advance the knowledge on mechanisms of exogenously and endogenously guided morphogenesis, demonstrating the self-sustainability of neuroepithelial cultures by endogenous processes.

Defects in microvillus crosslinking sensitize to colitis and inflammatory bowel disease

Intestinal epithelial cells are covered by the brush border, which consists of densely packed microvilli. The Intermicrovillar Adhesion Complex (IMAC) links the microvilli and is required for proper brush border organization. Whether microvillus crosslinking is involved in the intestinal barrier function or colitis is currently unknown. We investigate the role of microvillus crosslinking in colitis in mice with deletion of the IMAC component CDHR5. Electron microscopy shows pronounced brush border defects in CDHR5-deficient mice. The defects result in severe mucosal damage after exposure to the colitis-inducing agent DSS. DSS increases the permeability of the mucus layer and brings bacteria in direct contact with the disorganized brush border of CDHR5-deficient mice. This correlates with bacterial invasion into the epithelial cell layer which precedes epithelial apoptosis and inflammation. Single-cell RNA sequencing data of patients with ulcerative colitis reveals downregulation of CDHR5 in enterocytes of diseased areas. Our results provide experimental evidence that a combination of microvillus crosslinking defects with increased permeability of the mucus layer sensitizes to inflammatory bowel disease.

Consistency across multi-omics layers in a drug-perturbed gut microbial community

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

Deconvoluting gene and environment interactions to develop an "epigenetic score meter" of disease

Human health is determined both by genetics (G) and environment (E). This is clearly illustrated in groups of individuals who are exposed to the same environmental factor showing differential responses. A quantitative measure of the gene-environment interactions (GxE) effects has not been developed and in some instances, a clear consensus on the concept has not even been reached; for example, whether cancer is predominantly emerging from "bad luck" or "bad lifestyle" is still debated. In this article, we provide a panel of examples of GxE interaction as drivers of pathogenesis. We highlight how epigenetic regulations can represent a common connecting aspect of the molecular bases. Our argument converges on the concept that the GxE is recorded in the cellular epigenome, which might represent the key to deconvolute these multidimensional intricated layers of regulation. Developing a key to decode this epigenetic information would provide quantitative measures of disease risk. Analogously to the epigenetic clock introduced to estimate biological age, we provocatively propose the theoretical concept of an "epigenetic score-meter" to estimate disease risk.

Multisite assessment of reproducibility in high-content cell migration imaging data

High-content image-based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high-quality open-access data sharing and meta-analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta-analysis of results from live-cell microscopy, have not been systematically investigated. Here, using high-content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta-analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image-based datasets of perturbation experiments. Thus, reproducible quantitative high-content cell image analysis of perturbation effects and meta-analysis depend on standardized procedures combined with batch correction.

SARS-CoV-2-related bat virus behavior in human-relevant models sheds light on the origin of COVID-19

Bat sarbecovirus BANAL-236 is highly related to SARS-CoV-2 and infects human cells, albeit lacking the furin cleavage site in its spike protein. BANAL-236 replicates efficiently and pauci-symptomatically in humanized mice and in macaques, where its tropism is enteric, strongly differing from that of SARS-CoV-2. BANAL-236 infection leads to protection against superinfection by a virulent strain. We find no evidence of antibodies recognizing bat sarbecoviruses in populations in close contact with bats in which the virus was identified, indicating that such spillover infections, if they occur, are rare. Six passages in humanized mice or in human intestinal cells, mimicking putative early spillover events, select adaptive mutations without appearance of a furin cleavage site and no change in virulence. Therefore, acquisition of a furin site in the spike protein is likely a pre-spillover event that did not occur upon replication of a SARS-CoV-2-like bat virus in humans or other animals. Other hypotheses regarding the origin of the SARS-CoV-2 should therefore be evaluated, including the presence of sarbecoviruses carrying a spike with a furin cleavage site in bats.

Decreased Immunoglobulin G Core Fucosylation, A Player in Antibody-dependent Cell-mediated Cytotoxicity, is Associated with Autoimmune Thyroid Diseases

Autoimmune thyroid diseases (AITD) are the most common group of autoimmune diseases, associated with lymphocyte infiltration and the production of thyroid autoantibodies, like thyroid peroxidase antibodies (TPOAb), in the thyroid gland. Immunoglobulins and cell-surface receptors are glycoproteins with distinctive glycosylation patterns that play a structural role in maintaining and modulating their functions. We investigated associations of total circulating IgG and peripheral blood mononuclear cells glycosylation with AITD and the influence of genetic background in a case-control study with several independent cohorts and over 3,000 individuals in total. The study revealed an inverse association of IgG core fucosylation with TPOAb and AITD, as well as decreased peripheral blood mononuclear cells antennary α1,2 fucosylation in AITD, but no shared genetic variance between AITD and glycosylation. These data suggest that the decreased level of IgG core fucosylation is a risk factor for AITD that promotes antibody-dependent cell-mediated cytotoxicity previously associated with TPOAb levels.

A Compact Quadrupole-Orbitrap Mass Spectrometer with FAIMS Interface Improves Proteome Coverage in Short LC Gradients

State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 min LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument, we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Reproducibility, Specificity and Accuracy of Relative Quantification Using Spectral Library-based Data-independent Acquisition

Currently data-dependent acquisition (DDA) is the method of choice for mass spectrometry-based proteomics discovery experiments, but data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirements to perform a DIA analysis is the availability of suitable spectral libraries for peptide identification and quantification. Several studies were performed addressing the evaluation of spectral library performance for protein identification in DIA measurements. But so far only few experiments estimate the effect of these libraries on the quantitative level.In this work we created a gold standard spike-in sample set with known contents and ratios of proteins in a complex protein matrix that allowed a detailed comparison of DIA quantification data obtained with different spectral library approaches. We used in-house generated sample-specific spectral libraries created using varying sample preparation approaches and repeated DDA measurement. In addition, two different search engines were tested for protein identification from DDA data and subsequent library generation. In total, eight different spectral libraries were generated, and the quantification results compared with a library free method, as well as a default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding DIA analysis results was inspected, but also the number of expected and identified differentially abundant protein groups and their ratios.We found, that while libraries of prefractionated samples were generally larger, there was no significant increase in DIA identifications compared with repetitive non-fractionated measurements. Furthermore, we show that the accuracy of the quantification is strongly dependent on the applied spectral library and whether the quantification is based on peptide or protein level. Overall, the reproducibility and accuracy of DIA quantification is superior to DDA in all applied approaches.Data has been deposited to the ProteomeXchange repository with identifiers PXD012986, PXD012987, PXD012988 and PXD014956.

The dimeric ectodomain of the alkali-sensing insulin receptor-related receptor (ectoIRR) has a droplike shape

Insulin receptor-related receptor (IRR) is a receptor tyrosine kinase of the insulin receptor family and functions as an extracellular alkali sensor that controls metabolic alkalosis in the regulation of the acid-base balance. In the present work, we sought to analyze structural features of IRR by comparing them with those of the insulin receptor, which is its closest homolog but does not respond to pH changes. Using small-angle X-ray scattering (SAXS) and atomic force microscopy (AFM), we investigated the overall conformation of the recombinant soluble IRR ectodomain (ectoIRR) at neutral and alkaline pH. In contrast to the well-known inverted U-shaped (or λ-shaped) conformation of the insulin receptor, the structural models reconstructed at different pH values revealed that the ectoIRR organization has a "droplike" shape with a shorter distance between the fibronectin domains of the disulfide-linked dimer subunits within ectoIRR. We detected no large-scale pH-dependent conformational changes of ectoIRR in both SAXS and AFM experiments, an observation that agreed well with previous biochemical and functional analyses of IRR. Our findings indicate that ectoIRR's sensing of alkaline conditions involves additional molecular mechanisms, for example engagement of receptor juxtamembrane regions or the surrounding lipid environment.

Biochemical and structural studies reveal differences and commonalities among cap-snatching endonucleases from segmented negative-strand RNA viruses

Viruses rely on many host cell processes, including the cellular transcription machinery. Segmented negative-strand RNA viruses (sNSV) in particular cannot synthesize the 5'-cap structure for their mRNA but cleave off cellular caps and use the resulting oligonucleotides as primers for their transcription. This cap-snatching mechanism, involving a viral cap-binding site and RNA endonuclease, is both virus-specific and essential for viral proliferation and therefore represents an attractive drug target. Here, we present biochemical and structural results on the putative cap-snatching endonuclease of Crimean-Congo hemorrhagic fever virus (CCHFV), a highly pathogenic bunyavirus belonging to the Nairoviridae family, and of two additional nairoviruses, Erve virus (EREV) and Nairobi sheep disease virus (NSDV). Our findings are presented in the context of other cap-snatching endonucleases, such as the enzymatically active endonuclease from Rift Valley fever virus (RVFV), from Arenaviridae and Bunyavirales, belonging to the His- and His+ endonucleases, respectively, according to the absence or presence of a metal ion-coordinating histidine in the active site. Mutational and metal-binding experiments revealed the presence of only acidic metal-coordinating residues in the active site of the CCHFV domain and a unique active-site conformation that was intermediate between those of His+ and His- endonucleases. On the basis of small-angle X-ray scattering (SAXS) and homology modeling results, we propose a protein topology for the CCHFV domain that, despite its larger size, has a structure overall similar to those of related endonucleases. These results suggest structural and functional conservation of the cap-snatching mechanism among sNSVs.