Alanine Tails Signal Proteolysis in Bacterial Ribosome-Associated Quality Control.

In ribosome-associated quality control (RQC), Rqc2/NEMF closely supports the E3 ligase Ltn1/listerin in promoting ubiquitylation and degradation of aberrant nascent-chains obstructing large (60S) ribosomal subunits-products of ribosome stalling during translation. However, while Ltn1 is eukaryote-specific, Rqc2 homologs are also found in bacteria and archaea; whether prokaryotic Rqc2 has an RQC-related function has remained unknown. Here, we show that, as in eukaryotes, a bacterial Rqc2 homolog (RqcH) recognizes obstructed 50S subunits and promotes nascent-chain proteolysis. Unexpectedly, RqcH marks nascent-chains for degradation in a direct manner, by appending C-terminal poly-alanine tails that act as degrons recognized by the ClpXP protease. Furthermore, RqcH acts redundantly with tmRNA/ssrA and protects cells against translational and environmental stresses. Our results uncover a proteolytic-tagging mechanism with implications toward the function of related modifications in eukaryotes and suggest that RQC was already active in the last universal common ancestor (LUCA) to help cope with incomplete translation.

Quiescence Modulates Stem Cell Maintenance and Regenerative Capacity in the Aging Brain.

The function of somatic stem cells declines with age. Understanding the molecular underpinnings of this decline is key to counteract age-related disease. Here, we report a dramatic drop in the neural stem cells (NSCs) number in the aging murine brain. We find that this smaller stem cell reservoir is protected from full depletion by an increase in quiescence that makes old NSCs more resistant to regenerate the injured brain. Once activated, however, young and old NSCs show similar proliferation and differentiation capacity. Single-cell transcriptomics of NSCs indicate that aging changes NSCs minimally. In the aging brain, niche-derived inflammatory signals and the Wnt antagonist sFRP5 induce quiescence. Indeed, intervention to neutralize them increases activation of old NSCs during homeostasis and following injury. Our study identifies quiescence as a key feature of old NSCs imposed by the niche and uncovers ways to activate NSCs to repair the aging brain.

DNA methylation controls stemness of astrocytes in health and ischaemia.

Astrocytes are the most abundant cell type in the mammalian brain and provide structural and metabolic support to neurons, regulate synapses and become reactive after injury and disease. However, a small subset of astrocytes settles in specialized areas of the adult brain where these astrocytes instead actively generate differentiated neuronal and glial progeny and are therefore referred to as neural stem cells1-3. Common parenchymal astrocytes and quiescent neural stem cells share similar transcriptomes despite their very distinct functions4-6. Thus, how stem cell activity is molecularly encoded remains unknown. Here we examine the transcriptome, chromatin accessibility and methylome of neural stem cells and their progeny, and of astrocytes from the striatum and cortex in the healthy and ischaemic adult mouse brain. We identify distinct methylation profiles associated with either astrocyte or stem cell function. Stem cell function is mediated by methylation of astrocyte genes and demethylation of stem cell genes that are expressed later. Ischaemic injury to the brain induces gain of stemness in striatal astrocytes7. We show that this response involves reprogramming the astrocyte methylome to a stem cell methylome and is absent if the de novo methyltransferase DNMT3A is missing. Overall, we unveil DNA methylation as a promising target for regenerative medicine.

Cellular development and evolution of the mammalian cerebellum.

The expansion of the neocortex, a hallmark of mammalian evolution1,2, was accompanied by an increase in cerebellar neuron numbers3. However, little is known about the evolution of the cellular programmes underlying the development of the cerebellum in mammals. In this study we generated single-nucleus RNA-sequencing data for around 400,000 cells to trace the development of the cerebellum from early neurogenesis to adulthood in human, mouse and the marsupial opossum. We established a consensus classification of the cellular diversity in the developing mammalian cerebellum and validated it by spatial mapping in the fetal human cerebellum. Our cross-species analyses revealed largely conserved developmental dynamics of cell-type generation, except for Purkinje cells, for which we observed an expansion of early-born subtypes in the human lineage. Global transcriptome profiles, conserved cell-state markers and gene-expression trajectories across neuronal differentiation show that cerebellar cell-type-defining programmes have been overall preserved for at least 160 million years. However, we also identified many orthologous genes that gained or lost expression in cerebellar neural cell types in one of the species or evolved new expression trajectories during neuronal differentiation, indicating widespread gene repurposing at the cell-type level. In sum, our study unveils shared and lineage-specific gene-expression programmes governing the development of cerebellar cells and expands our understanding of mammalian brain evolution.

Direct competition between hnRNP C and U2AF65 protects the transcriptome from the exonization of Alu elements.

There are ~650,000 Alu elements in transcribed regions of the human genome. These elements contain cryptic splice sites, so they are in constant danger of aberrant incorporation into mature transcripts. Despite posing a major threat to transcriptome integrity, little is known about the molecular mechanisms preventing their inclusion. Here, we present a mechanism for protecting the human transcriptome from the aberrant exonization of transposable elements. Quantitative iCLIP data show that the RNA-binding protein hnRNP C competes with the splicing factor U2AF65 at many genuine and cryptic splice sites. Loss of hnRNP C leads to formation of previously suppressed Alu exons, which severely disrupt transcript function. Minigene experiments explain disease-associated mutations in Alu elements that hamper hnRNP C binding. Thus, by preventing U2AF65 binding to Alu elements, hnRNP C plays a critical role as a genome-wide sentinel protecting the transcriptome. The findings have important implications for human evolution and disease.

Centrosome linker diversity and its function in centrosome clustering and mitotic spindle formation.

The centrosome linker joins the two interphase centrosomes of a cell into one microtubule organizing center. Despite increasing knowledge on linker components, linker diversity in different cell types and their role in cells with supernumerary centrosomes remained unexplored. Here, we identified Ninein as a C-Nap1-anchored centrosome linker component that provides linker function in RPE1 cells while in HCT116 and U2OS cells, Ninein and Rootletin link centrosomes together. In interphase, overamplified centrosomes use the linker for centrosome clustering, where Rootletin gains centrosome linker function in RPE1 cells. Surprisingly, in cells with centrosome overamplification, C-Nap1 loss prolongs metaphase through persistent activation of the spindle assembly checkpoint indicated by BUB1 and MAD1 accumulation at kinetochores. In cells lacking C-Nap1, the reduction of microtubule nucleation at centrosomes and the delay in nuclear envelop rupture in prophase probably cause mitotic defects like multipolar spindle formation and chromosome mis-segregation. These defects are enhanced when the kinesin HSET, which normally clusters multiple centrosomes in mitosis, is partially inhibited indicating a functional interplay between C-Nap1 and centrosome clustering in mitosis.

Analyzing single-cell bisulfite sequencing data with MethSCAn.

Single-cell bisulfite sequencing (scBS) is a technique that enables the assessment of DNA methylation at single-base pair and single-cell resolution. The analysis of large datasets obtained from scBS requires preprocessing to reduce the data size, improve the signal-to-noise ratio and provide interpretability. Typically, this is achieved by dividing the genome into large tiles and averaging the methylation signals within each tile. Here we demonstrate that this coarse-graining approach can lead to signal dilution. We propose improved strategies to identify more informative regions for methylation quantification and a more accurate quantitation method than simple averaging. Our approach enables better discrimination of cell types and other features of interest and reduces the need for large numbers of cells. We also present an approach to detect differentially methylated regions between groups of cells and demonstrate its ability to identify biologically meaningful regions that are associated with genes involved in the core functions of specific cell types. Finally, we present the software tool MethSCAn for scBS data analysis ( https://anders-biostat.github.io/MethSCAn ).

Transcriptome and translatome co-evolution in mammals.

Gene-expression programs define shared and species-specific phenotypes, but their evolution remains largely uncharacterized beyond the transcriptome layer1. Here we report an analysis of the co-evolution of translatomes and transcriptomes using ribosome-profiling and matched RNA-sequencing data for three organs (brain, liver and testis) in five mammals (human, macaque, mouse, opossum and platypus) and a bird (chicken). Our within-species analyses reveal that translational regulation is widespread in the different organs, in particular across the spermatogenic cell types of the testis. The between-species divergence in gene expression is around 20% lower at the translatome layer than at the transcriptome layer owing to extensive buffering between the expression layers, which especially preserved old, essential and housekeeping genes. Translational upregulation specifically counterbalanced global dosage reductions during the evolution of sex chromosomes and the effects of meiotic sex-chromosome inactivation during spermatogenesis. Despite the overall prevalence of buffering, some genes evolved faster at the translatome layer-potentially indicating adaptive changes in expression; testis tissue shows the highest fraction of such genes. Further analyses incorporating mass spectrometry proteomics data establish that the co-evolution of transcriptomes and translatomes is reflected at the proteome layer. Together, our work uncovers co-evolutionary patterns and associated selective forces across the expression layers, and provides a resource for understanding their interplay in mammalian organs.

Scalable RT-LAMP-based SARS-CoV-2 testing for infection surveillance with applications in pandemic preparedness.

Throughout the SARS-CoV-2 pandemic, limited diagnostic capacities prevented sentinel testing, demonstrating the need for novel testing infrastructures. Here, we describe the setup of a cost-effective platform that can be employed in a high-throughput manner, which allows surveillance testing as an acute pandemic control and preparedness tool, exemplified by SARS-CoV-2 diagnostics in an academic environment. The strategy involves self-sampling based on gargling saline, pseudonymized sample handling, automated RNA extraction, and viral RNA detection using a semiquantitative multiplexed colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay with an analytical sensitivity comparable with RT-qPCR. We provide standard operating procedures and an integrated software solution for all workflows, including sample logistics, analysis by colorimetry or sequencing, and communication of results. We evaluated factors affecting the viral load and the stability of gargling samples as well as the diagnostic sensitivity of the RT-LAMP assay. In parallel, we estimated the economic costs of setting up and running the test station. We performed > 35,000 tests, with an average turnover time of < 6 h from sample arrival to result announcement. Altogether, our work provides a blueprint for fast, sensitive, scalable, cost- and labor-efficient RT-LAMP diagnostics, which is independent of potentially limiting clinical diagnostics supply chains.

Gene expression across mammalian organ development.

The evolution of gene expression in mammalian organ development remains largely uncharacterized. Here we report the transcriptomes of seven organs (cerebrum, cerebellum, heart, kidney, liver, ovary and testis) across developmental time points from early organogenesis to adulthood for human, rhesus macaque, mouse, rat, rabbit, opossum and chicken. Comparisons of gene expression patterns identified correspondences of developmental stages across species, and differences in the timing of key events during the development of the gonads. We found that the breadth of gene expression and the extent of purifying selection gradually decrease during development, whereas the amount of positive selection and expression of new genes increase. We identified differences in the temporal trajectories of expression of individual genes across species, with brain tissues showing the smallest percentage of trajectory changes, and the liver and testis showing the largest. Our work provides a resource of developmental transcriptomes of seven organs across seven species, and comparative analyses that characterize the development and evolution of mammalian organs.

Spatially Resolved Multi-Omics Single-Cell Analyses Inform Mechanisms of Immune Dysfunction in Pancreatic Cancer.

BACKGROUND & AIMS: As pancreatic ductal adenocarcinoma (PDAC) continues to be recalcitrant to therapeutic interventions, including poor response to immunotherapy, albeit effective in other solid malignancies, a more nuanced understanding of the immune microenvironment in PDAC is urgently needed. We aimed to unveil a detailed view of the immune micromilieu in PDAC using a spatially resolved multimodal single-cell approach. METHODS: We applied single-cell RNA sequencing, spatial transcriptomics, multiplex immunohistochemistry, and mass cytometry to profile the immune compartment in treatment-naïve PDAC tumors and matched adjacent normal pancreatic tissue, as well as in the systemic circulation. We determined prognostic associations of immune signatures and performed a meta-analysis of the immune microenvironment in PDAC and lung adenocarcinoma on single-cell level. RESULTS: We provided a spatially resolved fine map of the immune landscape in PDAC. We substantiated the exhausted phenotype of CD8 T cells and immunosuppressive features of myeloid cells, and highlighted immune subsets with potentially underappreciated roles in PDAC that diverged from immune populations within adjacent normal areas, particularly CD4 T cell subsets and natural killer T cells that are terminally exhausted and acquire a regulatory phenotype. Differential analysis of immune phenotypes in PDAC and lung adenocarcinoma revealed the presence of extraordinarily immunosuppressive subtypes in PDAC, along with a distinctive immune checkpoint composition. CONCLUSIONS: Our study sheds light on the multilayered immune dysfunction in PDAC and presents a holistic view of the immune landscape in PDAC and lung adenocarcinoma, providing a comprehensive resource for functional studies and the exploration of therapeutically actionable targets in PDAC.

Exploring dimension-reduced embeddings with Sleepwalk.

Dimension-reduction methods, such as t-SNE or UMAP, are widely used when exploring high-dimensional data describing many entities, for example, RNA-seq data for many single cells. However, dimension reduction is commonly prone to introducing artifacts, and we hence need means to see where a dimension-reduced embedding is a faithful representation of the local neighborhood and where it is not. We present Sleepwalk, a simple but powerful tool that allows the user to interactively explore an embedding, using color to depict original or any other distances from all points to the cell under the mouse cursor. We show how this approach not only highlights distortions but also reveals otherwise hidden characteristics of the data, and how Sleepwalk's comparative modes help integrate multisample data and understand differences between embedding and preprocessing methods. Sleepwalk is a versatile and intuitive tool that unlocks the full power of dimension reduction and will be of value not only in single-cell RNA-seq but also in any other area with matrix-shaped big data.

Analysing high-throughput sequencing data in Python with HTSeq 2.0.

SUMMARY: HTSeq 2.0 provides a more extensive application programming interface including a new representation for sparse genomic data, enhancements for htseq-count to suit single-cell omics, a new script for data using cell and molecular barcodes, improved documentation, testing and deployment, bug fixes and Python 3 support. AVAILABILITY AND IMPLEMENTATION: HTSeq 2.0 is released as an open-source software under the GNU General Public License and is available from the Python Package Index at https://pypi.python.org/pypi/HTSeq. The source code is available on Github at https://github.com/htseq/htseq. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis.

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.

Endothelial GATA4 controls liver fibrosis and regeneration by preventing a pathogenic switch in angiocrine signaling.

BACKGROUND & AIMS: Angiocrine signaling by liver sinusoidal endothelial cells (LSECs) regulates hepatic functions such as growth, metabolic maturation, and regeneration. Recently, we identified GATA4 as the master regulator of LSEC specification during development. Herein, we studied the role of endothelial GATA4 in the adult liver and in hepatic pathogenesis. METHODS: We generated adult Clec4g-icretg/0xGata4fl/fl (Gata4LSEC-KO) mice with LSEC-specific depletion of Gata4. Livers were analyzed by histology, electron microscopy, immunohistochemistry/immunofluorescence, in situ hybridization, and LSECs were isolated for gene expression profiling, ChIP- and ATAC-sequencing. Partial hepatectomy was performed to assess regeneration. We used choline-deficient, l-amino acid-defined (CDAA) diet and chronic carbon tetrachloride exposure to model liver fibrosis. Human single cell RNA-seq data sets were analyzed for endothelial alterations in healthy and cirrhotic livers. RESULTS: Genetic Gata4 deficiency in LSECs of adult mice caused perisinusoidal liver fibrosis, hepatopathy and impaired liver regeneration. Sinusoidal capillarization and LSEC-to-continuous endothelial transdifferentiation were accompanied by a profibrotic angiocrine switch involving de novo endothelial expression of hepatic stellate cell-activating cytokine PDGFB. Increased chromatin accessibility and amplification by activated MYC mediated angiocrine Pdgfb expression. As observed in Gata4LSEC-KO livers, CDAA diet-induced perisinusoidal liver fibrosis was associated with GATA4 repression, MYC activation and a profibrotic angiocrine switch in LSECs. Comparison of CDAA-fed Gata4LSEC-KO and control mice demonstrated that endothelial GATA4 indeed protects against dietary-induced perisinusoidal liver fibrosis. In human cirrhotic livers, GATA4-positive LSECs and endothelial GATA4 target genes were reduced, while non-LSEC endothelial cells and MYC target genes including PDGFB were enriched. CONCLUSIONS: Endothelial GATA4 protects against perisinusoidal liver fibrosis by repressing MYC activation and profibrotic angiocrine signaling at the chromatin level. Therapies targeting the GATA4/MYC/PDGFB/PDGFRß axis offer a promising strategy for prevention and treatment of liver fibrosis. LAY SUMMARY: The liver vasculature is supposed to play a major role in the development of liver fibrosis and cirrhosis, which can lead to liver failure and liver cancer. Herein, we discovered that structural and transcriptional changes induced by genetic deletion of the transcription factor GATA4 in the hepatic endothelium were sufficient to cause liver fibrosis. Activation of the transcription factor MYC and de novo expression of the "angiocrine" growth factor PDGFB were identified as downstream drivers of fibrosis and as potential therapeutic targets for this potentially fatal disease.

Nonparametric Analysis of Thermal Proteome Profiles Reveals Novel Drug-binding Proteins.

Detecting the targets of drugs and other molecules in intact cellular contexts is a major objective in drug discovery and in biology more broadly. Thermal proteome profiling (TPP) pursues this aim at proteome-wide scale by inferring target engagement from its effects on temperature-dependent protein denaturation. However, a key challenge of TPP is the statistical analysis of the measured melting curves with controlled false discovery rates at high proteome coverage and detection power. We present nonparametric analysis of response curves (NPARC), a statistical method for TPP based on functional data analysis and nonlinear regression. We evaluate NPARC on five independent TPP data sets and observe that it is able to detect subtle changes in any region of the melting curves, reliably detects the known targets, and outperforms a melting point-centric, single-parameter fitting approach in terms of specificity and sensitivity. NPARC can be combined with established analysis of variance (ANOVA) statistics and enables flexible, factorial experimental designs and replication levels. An open source software implementation of NPARC is provided.

Focused multidimensional scaling: interactive visualization for exploration of high-dimensional data.

BACKGROUND: Visualization is an important tool for generating meaning from scientific data, but the visualization of structures in high-dimensional data (such as from high-throughput assays) presents unique challenges. Dimension reduction methods are key in solving this challenge, but these methods can be misleading- especially when apparent clustering in the dimension-reducing representation is used as the basis for reasoning about relationships within the data. RESULTS: We present two interactive visualization tools, distnet and focusedMDS, that help in assessing the validity of a dimension-reducing plot and in interactively exploring relationships between objects in the data. The distnet tool is used to examine discrepancies between the placement of points in a two dimensional visualization and the points' actual similarities in feature space. The focusedMDS tool is an intuitive, interactive multidimensional scaling tool that is useful for exploring the relationships of one particular data point to the others, that might be useful in a personalized medicine framework. CONCLUSIONS: We introduce here two freely available tools for visually exploring and verifying the validity of dimension-reducing visualizations and biological information gained from these. The use of such tools can confirm that conclusions drawn from dimension-reducing visualizations are not simply artifacts of the visualization method, but are real biological insights.

Spatial aspects of oncogenic signalling determine the response to combination therapy in slice explants from Kras-driven lung tumours.

A key question in precision medicine is how functional heterogeneity in solid tumours informs therapeutic sensitivity. We demonstrate that spatial characteristics of oncogenic signalling and therapy response can be modelled in precision-cut slices from Kras-driven non-small-cell lung cancer with varying histopathologies. Unexpectedly, profiling of in situ tumours demonstrated that signalling stratifies mostly according to histopathology, showing enhanced AKT and SRC activity in adenosquamous carcinoma, and mitogen-activated protein kinase (MAPK) activity in adenocarcinoma. In addition, high intertumour and intratumour variability was detected, particularly of MAPK and mammalian target of rapamycin (mTOR) complex 1 activity. Using short-term treatment of slice explants, we showed that cytotoxic responses to combination MAPK and phosphoinositide 3-kinase-mTOR inhibition correlate with the spatially defined activities of both pathways. Thus, whereas genetic drivers determine histopathology spectra, histopathology-associated and spatially variable signalling activities determine drug sensitivity. Our study is in support of spatial aspects of signalling heterogeneity being considered in clinical diagnostic settings, particularly to guide the selection of drug combinations. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Orchestrating high-throughput genomic analysis with Bioconductor.

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.

Impaired response of the bronchial epithelium to inflammation characterizes severe equine asthma.

BACKGROUND: Severe equine asthma is a naturally occurring lung inflammatory disease of mature animals characterized by neutrophilic inflammation, bronchoconstriction, mucus hypersecretion and airway remodeling. Exacerbations are triggered by inhalation of dust and microbial components. Affected animals eventually are unable of aerobic performance. In this study transcriptomic differences between asthmatic and non-asthmatic animals in the response of the bronchial epithelium to an inhaled challenge were determined. RESULTS: Paired endobronchial biopsies were obtained pre- and post-challenge from asthmatic and non-asthmatic animals. The transcriptome, determined by RNA-seq and analyzed with edgeR, contained 111 genes differentially expressed (DE) after challenge between horses with and without asthma, and 81 of these were upregulated. Genes involved in neutrophil migration and activation were in central location in interaction networks, and related gene ontology terms were significantly overrepresented. Relative abundance of specific gene products as determined by immunohistochemistry was correlated with differential gene expression. Gene sets involved in neutrophil chemotaxis, immune and inflammatory response, secretion, blood coagulation and apoptosis were overrepresented among up-regulated genes, while the rhythmic process gene set was overrepresented among down-regulated genes. MMP1, IL8, TLR4 and MMP9 appeared to be the most important proteins in connecting the STRING protein network of DE genes. CONCLUSIONS: Several differentially expressed genes and networks in horses with asthma also contribute to human asthma, highlighting similarities between severe human adult and equine asthma. Neutrophil activation by the bronchial epithelium is suggested as the trigger of the inflammatory cascade in equine asthma, followed by epithelial injury and impaired repair and differentiation. Circadian rhythm dysregulation and the sonic Hedgehog pathway were identified as potential novel contributory factors in equine asthma.