Biology subjects

Huber, W.

Publications and source records attributed to Huber, W..

50 records · Page 3Linked to original sources

bioRxiv2019

Biological Plasticity Rescues Target Activity in CRISPR Knockouts

Gene knockouts (KOs) are efficiently engineered through CRISPR-Cas9-induced frameshift mutations. While DNA editing efficiency is readily verified by DNA sequencing, a systematic understanding of the efficiency of protein elimination has been lacking. Here, we devised an experimental strategy combining RNA-seq and triple-stage mass spectrometry (SPS-MS3) to characterize 193 genetically verified deletions targeting 136 distinct genes generated by CRISPR-induced frameshifts in HAP1 cells. We observed residual protein expression for about one third of the quantified targets, at variable levels from low to original, and identified two causal mechanisms, translation reinitiation leading to N-terminally truncated target proteins, or skipping of the edited exon leading to protein isoforms with internal sequence deletions. Detailed analysis of three truncated targets, BRD4, DNMT1 and NGLY1, revealed partial preservation of protein function. Our results imply that systematic characterization of residual protein expression or function in CRISPR-Cas9 generated KO lines is necessary for phenotype interpretation.

bioengineering↗

bioRxiv2019

Modelling asymmetric count ratios in CRISPR screens to decrease experiment size and improve phenotype detection

Pooled CRISPR screens are a powerful tool to probe genotype-phenotype relationships at genome-wide scale. However, criteria for optimal design are missing, and it remains unclear how experimental parameters affect results. Here, we report that random decreases in gRNA abundance are more likely than increases due to bottle-neck effects during the cell proliferation phase. Failure to consider this asymmetry leads to loss of detection power. We provide a new statistical test that addresses this problem and improves hit detection at reduced experiment size. The method is implemented in the open source package gscreend (submission to Bioconductor pending).

bioinformatics↗

bioRxiv2019

Orchestrating Single-Cell Analysis with Bioconductor

Recent developments in experimental technologies such as single-cell RNA sequencing have enabled the profiling a high-dimensional number of genome-wide features in individual cells, inspiring the formation of large-scale data generation projects quantifying unprecedented levels of biological variation at the single-cell level. The data generated in such projects exhibits unique characteristics, including increased sparsity and scale, in terms of both the number of features and the number of samples. Due to these unique characteristics, specialized statistical methods are required along with fast and efficient software implementations in order to successfully derive biological insights. Bioconductor - an open-source, open-development software project based on the R programming language - has pioneered the analysis of such high-throughput, high-dimensional biological data, leveraging a rich history of software and methods development that has spanned the era of sequencing. Featuring state-of-the-art computational methods, standardized data infrastructure, and interactive data visualization tools that are all easily accessible as software packages, Bioconductor has made it possible for a diverse audience to analyze data derived from cutting-edge single-cell assays. Here, we present an overview of single-cell RNA sequencing analysis for prospective users and contributors, highlighting the contributions towards this effort made by Bioconductor.

genomics↗

bioRxiv2019

Reduced proteasome activity in the aging brain results in ribosome stoichiometry loss and aggregation

A progressive loss of protein homeostasis is characteristic of aging and a driver of neurodegeneration. To investigate this process quantitatively, we characterized proteome dynamics during brain aging in the short-lived vertebrate Nothobranchius furzeri combining transcriptomics and proteomics. We detected a progressive reduction in the correlation between protein and mRNA, mainly due to post-transcriptional mechanisms that account for over 40% of the age-regulated proteins. These changes cause a progressive loss of stoichiometry in several protein complexes, including ribosomes, which show impaired assembly / dis-assembly and are enriched in protein aggregates in old brains. Mechanistically, we show that reduction of proteasome activity is an early event during brain aging and is sufficient to induce proteomic signatures of aging and loss of stoichiometry in vivo. Using longitudinal transcriptomic data, we show that the magnitude of early life decline in proteasome levels is the major risk factor for mortality. Our work defines causative events in the aging process that can be targeted to prevent loss of protein homeostasis and delay the onset of age-related neurodegeneration. HighlightsO_LIProgressive loss of stoichiometry affects multiple protein complexes C_LIO_LIRibosomes aggregate in old brains C_LIO_LIPartial reduction of proteasome activity is sufficient to induce loss of stoichiometry C_LIO_LIReduced proteasome levels are a major risk factor for early death in killifish C_LI

systems biology↗

bioRxiv2018

Proteome thermal stability reflects organ physiology and identifies drug-target engagement in vivo

Studying biological processes at a molecular level and monitoring drug-target interactions is established for simple cell systems but challenging in vivo. We introduce and apply a methodology for proteome-wide thermal stability measurements to characterize organ physiology and activity of many fundamental biological processes across tissues, such as energy metabolism and protein homeostasis. This method, termed tissue thermal proteome profiling (tissue-TPP), also enabled target and off-target identification and occupancy measurements in tissues derived from animals dosed with the non-covalent histone deacetylase inhibitor, panobinostat. Finally, we devised blood-CETSA, a thermal stability-based method to monitor target engagement in whole blood. Our study generates the first proteome-wide map of protein thermal stability in tissue and provides tools that will be of great impact for translational research.

cell biology↗

bioRxiv2018

Proteome-wide solubility and thermal stability profiling reveals distinct regulatory roles for ATP

Nucleotide triphosphates (NTPs) regulate numerous biochemical processes in cells as (co-)substrates, allosteric modulators, biosynthetic precursors, and signaling molecules1-3. Apart from its roles as energy source fueling cellular biochemistry, adenosine triphosphate (ATP), the most abundant NTP in cells, has been reported to affect macromolecular assemblies, such as protein complexes4,5 and membrane-less organelles6-8. Moreover, both ATP and guanosine triphosphate (GTP) have recently been shown to dissolve protein aggregates9. However, system-wide studies to characterize NTP-interactions under conditions approximating the native cellular environment are lacking, which limits our perspective of the diverse physiological roles of NTPs. Here, we have mapped and quantified proteome-wide NTP-interactions by assessing thermal stability and solubility of proteins using mechanically disrupted cells. Our results reveal diverse biological roles of ATP depending on its concentration. We found that ATP specifically interacts with proteins that utilize it as substrate or allosteric modulator at doses lower than 500 M, while it affects protein-protein interactions of protein complexes at mildly higher concentrations (between 1-2 mM). At high concentrations (> 2 mM), ATP modulates the solubility state of a quarter of the insoluble proteome, consisting of positively charged, intrinsically disordered, nucleic acid binding proteins, which are part of membrane-less organelles. The extent of solubilization depends on the localization of proteins to different membrane-less organelles. Furthermore, we uncover that ATP regulates protein-DNA interactions of the Barrier to autointegration factor (BANF1). Our data provides the first quantitative proteome-wide map of ATP affecting protein structure and protein complex stability and solubility, providing unique clues on its role in protein phase transitions.

systems biology↗

bioRxiv2018

Condensin II inactivation in interphase does not affect chromatin folding or gene expression

Condensin complexes have been proposed to play a prominent role in interphase chromatin organization and control of gene expression. Here, we report that the deletion of the central condensin II kleisin subunit Ncaph2 in differentiated mouse hepatocytes does not lead to significant changes in chromosome organization or in gene expression. Both observations challenge current views that implicate condensin in interphase chromosomal domain formation and in enhancer-promoter interactions. Instead, we suggest that the previously reported effects of condensin perturbation may result from their structural role during mitosis, which might indirectly impact the re-establishment of interphase chromosomal architecture after cell division.

genomics↗

bioRxiv2018

Non-Parametric 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 non-parametric 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 datasets 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. To facilitate access to a wide range of users, a freely available software implementation of NPARC is provided.

bioinformatics↗

bioRxiv2018

A combinatorial extracellular code tunes the intracellular signaling network activity to distinct cellular responses

Cells constantly survey a complex set of inputs that is processed by the intracellular signaling network, but little is known of how cells integrate input information from more than one cue. We employed a FRET biosensor-based imaging platform to study the effect of combinatorial growth factor levels on the signaling network in human cells. We found that pairwise stimuli caused distinct concentration- and ratio-dependent signaling states through signaling signatures such as antagonism, additivity and synergy. The unique signaling states correlated with differential gene expression and non-additive transcription patterns. We further elucidated how a signal-rich environment can fine-tune the signaling network and adjust physiological outcomes, by kinase and phosphatase activity profiling. We describe how complex extracellular conditions affect phospho-turnover and the basal phosphorylation status. Thus, we provide mechanistic insights into cellular processing of multiple cues and explain part of the complexity of cellular adaptation to changes in the extracellular environment.

cell biology↗

bioRxiv2018

MDM4 is an essential disease driver targeted by 1q gain in Burkitt lymphoma

Oncogenic MYC activation promotes cellular proliferation in Burkitt lymphoma (BL), but also induces cell cycle arrest and apoptosis mediated by TP53, a tumor suppressor gene that is mutated in 40% of BL cases. To identify therapeutic targets in BL, we investigated molecular dependencies in BL cell lines using RNAi-based, loss-of-function screening. By integrating genotypic and RNAi data, we identified a number of genotype-specific dependencies including the dependence of TCF3/ID3 mutant cell lines on TCF3 and of MYD88 mutant cell lines on TLR signaling. TP53 wild-type (TP53wt) BL were dependent on MDM4, a negative regulator of TP53. In BL cell lines, MDM4 knockdown induced cell cycle arrest and decreased tumor growth in a xenograft model in a p53-dependent manner, while small molecule inhibition of the MDM4-p53 interaction restored p53 activity resulting in cell cycle arrest. Consistent with the pathogenic effect of MDM4 upregulation in BL, we found that TP53wt BL samples were enriched for gain of chromosome 1q which includes the MDM4 locus. 1q gain was also enriched across non-BL cancer cell lines (n=789) without TP53 mutation (23% in TP53wt and 12% in TP53mut, p<0.001). In a set of 216 cell lines representing 19 cancer entities from the Achilles project, MDM4 was the strongest genetic dependency in TP53wt cell lines (p<0.001).\n\nOur findings show that in TP53wt BL, MDM4-mediated inhibition of p53 is a mechanism to evade cell cycle arrest. The data highlight the critical role of p53 as a tumor suppressor in BL, and identifies MDM4 as a key functional target of 1q gain in a wide range of cancers, which is therapeutically targetable.

cancer biology↗

bioRxiv2017

Multi-Omics factor analysis disentangles heterogeneity in blood cancer

Multi-omic studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous datasets are lacking. We present Multi-Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi-omic datasets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation, and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex-vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single-cell multiomics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation.

bioinformatics↗

bioRxiv2017

The small non-coding vault RNA1-1 acts as a riboregulator of autophagy

Vault RNAs (vtRNA) are small, 88-100nt non-coding RNAs found in many eukaryotes. Although they have been linked to drug resistance, apoptosis and nuclear transport, their function remains unclear. Here we show that a human vtRNA, RNA1-1, specifically binds to the autophagy receptor sequestosome-1/p62. Antisense-mediated depletion of vault RNA1-1 augments, whereas increased vault RNA1-1 expression restricts, autophagic flux in a p62-dependent manner. Bulk autophagy induced by starvation reduces the levels of vault RNA1-1 and the fraction of RNA-bound p62. These findings show that RNAs can act as riboregulators of biological processes by interacting with proteins, and assign a function to a vault RNA.

molecular biology↗

bioRxiv2017

Transcript Isoform Differences Across Human Tissues Are Predominantly Driven By Alternative Start And Termination Sites Of Transcription

Most human genes have multiple transcription start and polyadenylation sites, as well as alternatively spliced exons. Although such transcript isoform diversity contributes to the differentiation between cell types, the importance of contributions from the different isoform generating processes is unclear. To address this question, we used 798 samples from the Genotype-Tissue Expression (GTEx) to investigate cell type dependent differences in exon usage of over 18,000 protein-coding genes in 23 cell types. We found tissue-dependent isoform usage in about half of expressed genes. Overall, tissue-dependent splicing accounted only for a minority of tissue-dependent exon usage, most of which was consistent with alternative transcription start and termination sites. We verified this result on a second, independent dataset, Cap Analysis of Gene Expression (CAGE) data from the FANTOM consortium, which confirmed widespread tissue-dependent usage of alternative transcription start sites. Our analysis identifies transcription start and termination sites as the principal drivers of isoform diversity across tissues. Moreover, our results indicate that most tissue-dependent splicing involves untranslated exons and therefore may not have consequences at the proteome level.

genomics↗

bioRxiv2016

Two independent modes of chromosome organization are revealed by cohesin removal

The three-dimensional organization of chromosomes is tightly related to their biological function 1. Both imaging and chromosome conformation capture studies have revealed several layers of organization 2-4: segregation into active and inactive compartments at the megabase scale 5, and partitioning into domains (TADs) 6,7 and associated loops 8 at the sub-megabase scale. Yet, it remains unclear how these layers of genome organization form, interact with one another, and contribute to or result from genome activities. TADs seem to have critical roles in regulating gene expression by promoting or preventing interactions between promoters and distant cis-acting regulatory elements 9-14, and different architectural proteins, including cohesin, have been proposed to play central roles in their formation 15,16. However, experimental depletions of these proteins have resulted in marginal changes in chromosome organization 17-19. Here, we show that deletion of the cohesin-loading factor, Nipbl, leads to loss of chromosome-associated cohesin and results in dramatic genome reorganization. TADs and associated loops vanish globally, even in the absence of transcriptional changes. In contrast, segregation into compartments is preserved and even reinforced. Strikingly, the disappearance of TADs unmasks a finer compartment structure that accurately reflects the underlying epigenetic landscape. These observations demonstrate that the 3D organization of the genome results from the independent action of two distinct mechanisms: 1) cohesin-independent segregation of the genome into fine-scale compartment regions, defined by the underlying chromatin state; and 2) cohes-dependent formation of TADs possibly by the recently proposed loop extrusion mechanism 20,21, enabling long-range and target-specific activity of promiscuous enhancers. The interplay between these mechanisms creates an architecture that is more complex than a simple hierarchy of layers and can be central to guiding normal development.

genomics↗