Biology subjects

Dehio, C.

Publications and source records attributed to Dehio, C..

4 recordsLinked to original sources

bioRxiv2018

A role for VPS35 in Brucella intracellular replication revealed by genome-wide siRNA screening

Brucella, the causing agent of brucellosis, is a major zoonotic pathogen with worldwide distribution. Brucella resides and replicates inside infected host cells in membrane-bound compartments called BCVs (Brucella-containing vacuoles). Following uptake, Brucella resides in eBCVs (endosomal BCVs) that gradually mature from early to late endosomal features. Through a poorly understood process that is key to the intracellular lifestyle of Brucella, the eBCV escapes fusion with lysosomes by transitioning to the rBCV (replicative BCV), a replicative niche directly connected to the endoplasmic reticulum (ER). Despite the notion that this complex intracellular lifestyle must depend on a multitude of host factors, a holistic view on which of these components control Brucella cell entry, trafficking and replication is still missing. Here we used a systematic cell-based siRNA knockdown screen in HeLa cells infected with Brucella abortus and identified 425 components of the human infectome for Brucella infection. These include multiple components of pathways involved in central processes such as cell cycle, actin cytoskeleton dynamics or vesicular trafficking. Using assays for pathogen entry, knockdown complementation and co-localization at single-cell resolution, we identified the requirement of the VPS retromer for Brucella to escape the lysosomal degradative pathway and to establish its intracellular replicative niche. We thus validated a component of the VPS retromer as novel host factor critical for Brucella intracellular trafficking. Further, our genome-wide data shed light on the interplay between central host processes and the biogenesis of the Brucella replicative niche.\n\nImportanceWith >300,000 new cases of human brucellosis annually, Brucella is regarded as one of the most important zoonotic bacterial pathogen worldwide. The causing agent of brucellosis resides inside host cells within vacuoles termed Brucella containing vacuoles (BCVs). Although few host components required to escape the degradative lysosomal pathway and to establish the ER-derived replicative BCV (rBCV) have already been identified, the global understanding of this highly coordinated process is still partial and many factors remain unknown. To gain a deeper insight into these fundamental questions we performed a genome-wide RNA interference (RNAi) screen aiming at discovering novel host factors involved in the Brucella intracellular cycle. We identified 425 host proteins that contribute to Brucella cellular entry, intracellular trafficking, and replication. Together, this study sheds light on previously unknown host pathways required for the Brucella infection cycle and highlights the VPS retromer components as critical factors for the establishment of the Brucella intracellular replicative niche.

microbiology↗

bioRxiv2018

Genomic, Proteomic and Phenotypic Heterogeneity in HeLa Cells across Laboratories: Implications for Reproducibility of Research Results

The independent reproduction of research results is a cornerstone of experimental research, yet it is beset by numerous challenges, including the quality and veracity of reagents and materials. Much of life science research depends on life materials, including human tissue culture cells. In this study we aimed at determining the degree of variability in the molecular makeup and the ensuing phenotypic consequences in commonly used human tissue culture cells. We collected 14 stock HeLa aliquots from 13 different laboratories across the globe, cultured them in uniform conditions and profiled the genome-wide copy numbers, mRNAs, proteins and protein turnover rates via genomic techniques and SWATH mass spectrometry, respectively. We also phenotyped each cell line with respect to the ability of transfected Let7 mimics to modulate Salmonella infection.\n\nWe discovered significant heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto variety. We also observed progressive divergence within a specific cell line over 50 successive passages. From the aggregate multi-omic datasets we quantified the response of the cells to genomic variability across the transcriptome and proteome. We discovered organelle-specific proteome remodeling and buffering of protein abundance by protein complex stoichiometry, mediated by the adaptation of protein turnover rates. By associating quantitative proteotype and phenotype measurements we identified protein patterns that explained the varying response of the different cell lines to Salmonella infection.\n\nAltogether the results indicate a striking degree of genomic variability, the rapid evolution of genomic variability in culture and its complex translation into distinctive expressed molecular and phenotypic patterns. The results have broad implications for the interpretation and reproducibility of research results obtained from HeLa cells and provide important basis for a general discussion of the value and requirements for communicating research results obtained from human tissue culture cells.

systems biology↗

bioRxiv2018

Improved pathway reconstruction from RNA interference screens by exploiting off-target effects

Pathway reconstruction has proven to be an indispensable tool for analyzing the molecular mechanisms of signal transduction underlying cell function. Nested effects models (NEMs) are a class of probabilistic graphical models designed to reconstruct signalling pathways from high-dimensional observations resulting from perturbation experiments, such as RNA interference (RNAi). NEMs assume that the short interfering RNAs (siRNAs) designed to knockdown specific genes are always on-target. However, it has been shown that most siRNAs exhibit strong off-target effects, which further confound the data, resulting in unreliable reconstruction of networks by NEMs. Here, we present an extension of NEMs called probabilistic combinatorial nested effects models (pc-NEMs), which capitalize on the ancillary siRNA off-target effects for network reconstruction from combinatorial gene knockdown data. Our model employs an adaptive simulated annealing search algorithm for simultaneous inference of network structure and error rates inherent to the data. Evaluation of pc-NEMs on simulated data with varying number of phenotypic effects and noise levels demonstrates improved reconstruction compared to classical NEMs. Application to Bartonella henselae infection RNAi screening data yielded an eight node network largely in agreement with previous works, and revealed novel binary interactions of direct impact between established components.\n\nAvailability: The software used for the analysis is freely available as an R package at https://github.com/cbg-ethz/pcNEM.git\n\nContact: niko.beerenwinkel@bsse.ethz.ch

bioinformatics↗

bioRxiv2017

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations.\n\nOur strategy towards accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics dataset against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and variants identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin, and release iPtgxDBs for B. henselae, Bradyrhozibium diazoefficiens and Escherichia coli as well as the software to generate such proteogenomics search databases for any prokaryote.

genomics↗