CLAUDIO: automated structural analysis of cross-linking data

MOTIVATION

Cross-linking mass spectrometry has made remarkable advancements in the high-throughput characterization of protein structures and interactions. The resulting pairs of cross-linked peptides typically require geometric assessment and validation, given the availability of their corresponding structures.

RESULTS

CLAUDIO (Cross-linking Analysis Using Distances and Overlaps) is an open-source software tool designed for the automated analysis and validation of different varieties of large-scale cross-linking experiments. Many of the otherwise manual processes for structural validation (i.e. structure retrieval and mapping) are performed fully automatically to simplify and accelerate the data interpretation process. In addition, CLAUDIO has the ability to remap intra-protein links as inter-protein links and discover evidence for homo-multimers.

AVAILABILITY AND IMPLEMENTATION

CLAUDIO is available as open-source software under the MIT license at https://github.com/KohlbacherLab/CLAUDIO.

The Celiac-Disease Superantigen Oligomerizes and Increases Permeability in an Enterocyte Cell Model

Celiac disease (CeD) is an autoimmune disorder triggered by gluten proteins, affecting approximately 1 % of the global population. The 33-mer deamidated gliadin peptide (DGP) is a metabolically modified wheat-gluten superantigen for CeD. Here, we demonstrate that the 33-mer DGP spontaneously assembles into oligomers with a diameter of approximately 24 nm. The 33-mer DGP oligomers present two main secondary structural motifs-a major polyproline II helix and a minor β-sheet structure. Importantly, in the presence of 33-mer DGP oligomers, there is a statistically significant increase in the permeability in the gut epithelial cell model Caco-2, accompanied by the redistribution of zonula occludens-1, a master tight junction protein. These findings provide novel molecular and supramolecular insights into the impact of 33-mer DGP in CeD and highlight the relevance of gliadin peptide oligomerization.

Training an automated circulating tumor cell classifier when the true classification is uncertain

Circulating tumor cell (CTC) and tumor-derived extracellular vesicle (tdEV) loads are prognostic factors of survival in patients with carcinoma. The current method of CTC enumeration relies on operator review and, unfortunately, has moderate interoperator agreement (Fleiss' kappa 0.60) due to difficulties in classifying CTC-like events. We compared operator review, ACCEPT automated image processing, and refined the output of a deep-learning algorithm to identify CTC and tdEV for the prediction of survival in patients with metastatic and nonmetastatic cancers. Operator review is only defined for CTC. Refinement was performed using automatic contrast maximization CM-CTC of events detected in cancer and in benign samples (CM-CTC). We used 418 samples from benign diseases, 6,293 from nonmetastatic breast, 2,408 from metastatic breast, and 698 from metastatic prostate cancer to train, test, optimize, and evaluate CTC and tdEV enumeration. For CTC identification, the CM-CTC performed best on metastatic/nonmetastatic breast cancer, respectively, with a hazard ratio (HR) for overall survival of 2.6/2.1 vs. 2.4/1.4 for operator CTC and 1.2/0.8 for ACCEPT-CTC. For tdEV identification, CM-tdEV performed best with an HR of 1.6/2.9 vs. 1.5/1.0 with ACCEPT-tdEV. In conclusion, contrast maximization is effective even though it does not utilize domain knowledge.

MuDoGeR: Multi-Domain Genome recovery from metagenomes made easy

Several computational frameworks and workflows that recover genomes from prokaryotes, eukaryotes and viruses from metagenomes exist. Yet, it is difficult for scientists with little bioinformatics experience to evaluate quality, annotate genes, dereplicate, assign taxonomy and calculate relative abundance and coverage of genomes belonging to different domains. MuDoGeR is a user-friendly tool tailored for those familiar with Unix command-line environment that makes it easy to recover genomes of prokaryotes, eukaryotes and viruses from metagenomes, either alone or in combination. We tested MuDoGeR using 24 individual-isolated genomes and 574 metagenomes, demonstrating the applicability for a few samples and high throughput. While MuDoGeR can recover eukaryotic viral sequences, its characterization is predominantly skewed towards bacterial and archaeal viruses, reflecting the field's current state. However, acting as a dynamic wrapper, the MuDoGeR is designed to constantly incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field. MuDoGeR is open-source software available at https://github.com/mdsufz/MuDoGeR. Additionally, MuDoGeR is also available as a Singularity container.

Diversity and Evolutionary History of Ti Plasmids of "tumorigenes" Clade of Rhizobium spp. and Their Differentiation from Other Ti and Ri Plasmids

Agrobacteria are important plant pathogens responsible for crown/cane gall and hairy root diseases. Crown/cane gall disease is associated with strains carrying tumor-inducing (Ti) plasmids, while hairy root disease is caused by strains harboring root-inducing (Ri) plasmids. In this study, we analyzed the sequences of Ti plasmids of the novel "tumorigenes" clade of the family Rhizobiaceae ("tumorigenes" Ti plasmids), which includes two species, Rhizobium tumorigenes and Rhizobium rhododendri. The sequences of reference Ti/Ri plasmids were also included, which was followed by a comparative analysis of their backbone and accessory regions. The "tumorigenes" Ti plasmids have novel opine signatures compared with other Ti/Ri plasmids characterized so far. The first group exemplified by pTi1078 is associated with production of agrocinopine, nopaline, and ridéopine in plant tumors, while the second group comprising pTi6.2 is responsible for synthesis of leucinopine. Bioinformatic and chemical analyses, including opine utilization assays, indicated that leucinopine associated with pTi6.2 most likely has D,L stereochemistry, unlike the L,L-leucinopine produced in tumors induced by reference strains Chry5 and Bo542. Most of the "tumorigenes" Ti plasmids have conjugative transfer system genes that are unusual for Ti plasmids, composed of avhD4/avhB and traA/mobC/parA regions. Next, our results suggested that "tumorigenes" Ti plasmids have a common origin, but they diverged through large-scale recombination events, through recombination with single or multiple distinct Ti/Ri plasmids. Lastly, we showed that Ti/Ri plasmids could be differentiated based on pairwise Mash or average amino-acid identity distance clustering, and we supply a script to facilitate application of the former approach by other researchers.

Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint

Diatoms represent one of the morphologically and taxonomically most diverse groups of microscopic eukaryotes. Light microscopy-based taxonomic identification and enumeration of frustules, the silica shells of these microalgae, is broadly used in aquatic ecology and biomonitoring. One key step in emerging digital variants of such investigations is segmentation, a task that has been addressed before, but usually in manually captured megapixel-sized images of individual diatom cells with a mostly clean background. In this paper, we applied deep learning-based segmentation methods to gigapixel-sized, high-resolution scans of diatom slides with a realistically cluttered background. This setup requires large slide scans to be subdivided into small images (tiles) to apply a segmentation model to them. This subdivision (tiling), when done using a sliding window approach, often leads to cropping relevant objects at the boundaries of individual tiles. We hypothesized that in the case of diatom analysis, reducing the amount of such cropped objects in the training data can improve segmentation performance by allowing for a better discrimination of relevant, intact frustules or valves from small diatom fragments, which are considered irrelevant when counting diatoms. We tested this hypothesis by comparing a standard sliding window / fixed-stride tiling approach with two new approaches we term object-based tile positioning with and without object integrity constraint. With all three tiling approaches, we trained Mask-R-CNN and U-Net models with different amounts of training data and compared their performance. Object-based tiling with object integrity constraint led to an improvement in pixel-based precision by 12-17 percentage points without substantially impairing recall when compared with standard sliding window tiling. We thus propose that training segmentation models with object-based tiling schemes can improve diatom segmentation from large gigapixel-sized images but could potentially also be relevant for other image domains.

InterPro in 2022

The InterPro database (https://www.ebi.ac.uk/interpro/) provides an integrative classification of protein sequences into families, and identifies functionally important domains and conserved sites. Here, we report recent developments with InterPro (version 90.0) and its associated software, including updates to data content and to the website. These developments extend and enrich the information provided by InterPro, and provide a more user friendly access to the data. Additionally, we have worked on adding Pfam website features to the InterPro website, as the Pfam website will be retired in late 2022. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB. Moreover, we report the development of a card game as a method of engaging the non-scientific community. Finally, we discuss the benefits and challenges brought by the use of artificial intelligence for protein structure prediction.

Are n-3 PUFAs from Microalgae Incorporated into Membrane and Storage Lipids in Pig Muscle Tissues?-A Lipidomic Approach

For the study of molecular mechanisms of to lipid transport and storage in relation to dietary effects, lipidomics has been rarely used in farm animal research. A feeding study with pigs (German Landrace sows) and supplementation of microalgae (Schizochytrium sp.) was conducted. The animals were allocated to the control group (n = 15) and the microalgae group (n = 16). Shotgun lipidomics was applied. This study enabled us to identify and quantify 336 lipid species from 15 different lipid classes in pig skeletal muscle tissues. The distribution of the lipid classes was significantly altered by microalgae supplementation, and ether lipids of phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidic acid (PA) were significantly decreased. The total concentration of triacylglycerides (TAGs) was not affected. TAGs with high degree of unsaturation (TAG 56:7, TAG 56:6, TAG 54:6) were increased in the microalgae group, and major abundant species like TAG 52:2 and TAG 52:1 were not affected by the diet. Our results confirmed that dietary DHA and EPA are incorporated into storage and membrane lipids of pig muscles, which further led to systemic changes in the lipidome composition.

Molecular and Structural Parallels between Gluten Pathogenic Peptides and Bacterial-Derived Proteins by Bioinformatics Analysis

Gluten-related disorders (GRDs) are a group of diseases that involve the activation of the immune system triggered by the ingestion of gluten, with a worldwide prevalence of 5%. Among them, Celiac disease (CeD) is a T-cell-mediated autoimmune disease causing a plethora of symptoms from diarrhea and malabsorption to lymphoma. Even though GRDs have been intensively studied, the environmental triggers promoting the diverse reactions to gluten proteins in susceptible individuals remain elusive. It has been proposed that pathogens could act as disease-causing environmental triggers of CeD by molecular mimicry mechanisms. Additionally, it could also be possible that unrecognized molecular, structural, and physical parallels between gluten and pathogens have a relevant role. Herein, we report sequence, structural and physical similarities of the two most relevant gluten peptides, the 33-mer and p31-43 gliadin peptides, with bacterial pathogens using bioinformatics going beyond the molecular mimicry hypothesis. First, a stringent BLASTp search using the two gliadin peptides identified high sequence similarity regions within pathogen-derived proteins, e.g., extracellular proteins from Streptococcus pneumoniae and Granulicatella sp. Second, molecular dynamics calculations of an updated α-2-gliadin model revealed close spatial localization and solvent-exposure of the 33-mer and p31-43 peptide, which was compared with the pathogen-related proteins by homology models and localization predictors. We found putative functions of the identified pathogen-derived sequence by identifying T-cell epitopes and SH3/WW-binding domains. Finally, shape and size parallels between the pathogens and the superstructures of gliadin peptides gave rise to novel hypotheses about activation of innate immunity and dysbiosis. Based on our structural findings and the similarities with the bacterial pathogens, evidence emerges that these pathologically relevant gluten-derived peptides could behave as non-replicating pathogens opening new research questions in the interface of innate immunity, microbiome, and food research.

LAMP3 deficiency affects surfactant homeostasis in mice

Lysosome-associated membrane glycoprotein 3 (LAMP3) is a type I transmembrane protein of the LAMP protein family with a cell-type-specific expression in alveolar type II cells in mice and hitherto unknown function. In type II pneumocytes, LAMP3 is localized in lamellar bodies, secretory organelles releasing pulmonary surfactant into the extracellular space to lower surface tension at the air/liquid interface. The physiological function of LAMP3, however, remains enigmatic. We generated Lamp3 knockout mice by CRISPR/Cas9. LAMP3 deficient mice are viable with an average life span and display regular lung function under basal conditions. The levels of a major hydrophobic protein component of pulmonary surfactant, SP-C, are strongly increased in the lung of Lamp3 knockout mice, and the lipid composition of the bronchoalveolar lavage shows mild but significant changes, resulting in alterations in surfactant functionality. In ovalbumin-induced experimental allergic asthma, the changes in lipid composition are aggravated, and LAMP3-deficient mice exert an increased airway resistance. Our data suggest a critical role of LAMP3 in the regulation of pulmonary surfactant homeostasis and normal lung function.

LAMP3 is a protein of unknown molecular function with highest expression in alveolar type II cells. In alveolar type II cells, LAMP3 localizes to lamellar bodies, specific lysosome-related organelles that play an important role in secreting pulmonary surfactant, a mixture of hydrophobic proteins and lipids lowering the surface tension between the gas and the liquid phase of the lung in order to prevent alveoli from collapsing. To decipher the physiological function of LAMP3, we generated Lamp3 knockout mice, which are viable and show no apparent phenotype. Under basal conditions, both the protein and lipid composition of pulmonary surfactant are altered, but do not affect the physiological function of the lung. However, under diseased conditions of experimental allergic asthma, changes in the lipid composition are aggravated and are associated with an impaired lung function, suggesting an important role of LAMP3 in the homeostasis of pulmonary surfactant.

GUNC: detection of chimerism and contamination in prokaryotic genomes

Genomes are critical units in microbiology, yet ascertaining quality in prokaryotic genome assemblies remains a formidable challenge. We present GUNC (the Genome UNClutterer), a tool that accurately detects and quantifies genome chimerism based on the lineage homogeneity of individual contigs using a genome's full complement of genes. GUNC complements existing approaches by targeting previously underdetected types of contamination: we conservatively estimate that 5.7% of genomes in GenBank, 5.2% in RefSeq, and 15-30% of pre-filtered "high-quality" metagenome-assembled genomes in recent studies are undetected chimeras. GUNC provides a fast and robust tool to substantially improve prokaryotic genome quality.

Short linear motif candidates in the cell entry system used by SARS-CoV-2 and their potential therapeutic implications

The first reported receptor for SARS-CoV-2 on host cells was the angiotensin-converting enzyme 2 (ACE2). However, the viral spike protein also has an RGD motif, suggesting that cell surface integrins may be co-receptors. We examined the sequences of ACE2 and integrins with the Eukaryotic Linear Motif (ELM) resource and identified candidate short linear motifs (SLiMs) in their short, unstructured, cytosolic tails with potential roles in endocytosis, membrane dynamics, autophagy, cytoskeleton, and cell signaling. These SLiM candidates are highly conserved in vertebrates and may interact with the μ2 subunit of the endocytosis-associated AP2 adaptor complex, as well as with various protein domains (namely, I-BAR, LC3, PDZ, PTB, and SH2) found in human signaling and regulatory proteins. Several motifs overlap in the tail sequences, suggesting that they may act as molecular switches, such as in response to tyrosine phosphorylation status. Candidate LC3-interacting region (LIR) motifs are present in the tails of integrin β3 and ACE2, suggesting that these proteins could directly recruit autophagy components. Our findings identify several molecular links and testable hypotheses that could uncover mechanisms of SARS-CoV-2 attachment, entry, and replication against which it may be possible to develop host-directed therapies that dampen viral infection and disease progression. Several of these SLiMs have now been validated to mediate the predicted peptide interactions.

SMART: recent updates, new developments and status in 2020

SMART (Simple Modular Architecture Research Tool) is a web resource (https://smart.embl.de) for the identification and annotation of protein domains and the analysis of protein domain architectures. SMART version 9 contains manually curated models for more than 1300 protein domains, with a topical set of 68 new models added since our last update article (1). All the new models are for diverse recombinase families and subfamilies and as a set they provide a comprehensive overview of mobile element recombinases namely transposase, integrase, relaxase, resolvase, cas1 casposase and Xer like cellular recombinase. Further updates include the synchronization of the underlying protein databases with UniProt (2), Ensembl (3) and STRING (4), greatly increasing the total number of annotated domains and other protein features available in architecture analysis mode. Furthermore, SMART's vector-based protein display engine has been extended and updated to use the latest web technologies and the domain architecture analysis components have been optimized to handle the increased number of protein features available.

Automated 3D light-sheet screening with high spatiotemporal resolution reveals mitotic phenotypes

3D cell cultures enable the in vitro study of dynamic biological processes such as the cell cycle, but their use in high-throughput screens remains impractical with conventional fluorescent microscopy. Here, we present a screening workflow for the automated evaluation of mitotic phenotypes in 3D cell cultures by light-sheet microscopy. After sample preparation by a liquid handling robot, cell spheroids are imaged for 24 h in toto with a dual-view inverted selective plane illumination microscope (diSPIM) with a much improved signal-to-noise ratio, higher imaging speed, isotropic resolution and reduced light exposure compared to a spinning disc confocal microscope. A dedicated high-content image processing pipeline implements convolutional neural network-based phenotype classification. We illustrate the potential of our approach using siRNA knockdown and epigenetic modification of 28 mitotic target genes for assessing their phenotypic role in mitosis. By rendering light-sheet microscopy operational for high-throughput screening applications, this workflow enables target gene characterization or drug candidate evaluation in tissue-like 3D cell culture models.

Extensive transmission of microbes along the gastrointestinal tract

The gastrointestinal tract is abundantly colonized by microbes, yet the translocation of oral species to the intestine is considered a rare aberrant event, and a hallmark of disease. By studying salivary and fecal microbial strain populations of 310 species in 470 individuals from five countries, we found that transmission to, and subsequent colonization of, the large intestine by oral microbes is common and extensive among healthy individuals. We found evidence for a vast majority of oral species to be transferable, with increased levels of transmission in colorectal cancer and rheumatoid arthritis patients and, more generally, for species described as opportunistic pathogens. This establishes the oral cavity as an endogenous reservoir for gut microbial strains, and oral-fecal transmission as an important process that shapes the gastrointestinal microbiome in health and disease.