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Cell Systems

Congxin Li, François Cesbron, Michael Oehler, Michael Brunner, Thomas Höfer
Gene regulation is a complex non-equilibrium process. Here, we show that quantitating the temporal regulation of key gene states (transcriptionally inactive, active, and refractory) provides a parsimonious framework for analyzing gene regulation. Our theory makes two non-intuitive predictions. First, for transcription factors (TFs) that regulate transcription burst frequency, as opposed to amplitude or duration, weak TF binding is sufficient to elicit strong transcriptional responses. Second, refractoriness of a gene after a transcription burst enables rapid responses to stimuli...
February 12, 2018: Cell Systems
Eduardo Torre, Hannah Dueck, Sydney Shaffer, Janko Gospocic, Rohit Gupte, Roberto Bonasio, Junhyong Kim, John Murray, Arjun Raj
Although single-cell RNA sequencing can reliably detect large-scale transcriptional programs, it is unclear whether it accurately captures the behavior of individual genes, especially those that express only in rare cells. Here, we use single-molecule RNA fluorescence in situ hybridization as a gold standard to assess trade-offs in single-cell RNA-sequencing data for detecting rare cell expression variability. We quantified the gene expression distribution for 26 genes that range from ubiquitous to rarely expressed and found that the correspondence between estimates across platforms improved with both transcriptome coverage and increased number of cells analyzed...
February 7, 2018: Cell Systems
Peng Jiang, Winston Lee, Xujuan Li, Carl Johnson, Jun S Liu, Myles Brown, Jon Christopher Aster, X Shirley Liu
Identifying reliable drug response biomarkers is a significant challenge in cancer research. We present computational analysis of resistance (CARE), a computational method focused on targeted therapies, to infer genome-wide transcriptomic signatures of drug efficacy from cell line compound screens. CARE outputs genome-scale scores to measure how the drug target gene interacts with other genes to affect the inhibitor efficacy in the compound screens. Such statistical interactions between drug targets and other genes were not considered in previous studies but are critical in identifying predictive biomarkers...
February 6, 2018: Cell Systems
James T Robinson, Douglass Turner, Neva C Durand, Helga Thorvaldsdóttir, Jill P Mesirov, Erez Lieberman Aiden
Contact mapping experiments such as Hi-C explore how genomes fold in 3D. Here, we introduce Juicebox.js, a cloud-based web application for exploring the resulting datasets. Like the original Juicebox application, Juicebox.js allows users to zoom in and out of such datasets using an interface similar to Google Earth. Juicebox.js also has many features designed to facilitate data reproducibility and sharing. Furthermore, Juicebox.js encodes the exact state of the browser in a shareable URL. Creating a public browser for a new Hi-C dataset does not require coding and can be accomplished in under a minute...
February 5, 2018: Cell Systems
Steve O'Hagan, Marina Wright Muelas, Philip J Day, Emma Lundberg, Douglas B Kell
The expression levels of SLC or ABC membrane transporter transcripts typically differ 100- to 10,000-fold between different tissues. The Gini coefficient characterizes such inequalities and here is used to describe the distribution of the expression of each transporter among different human tissues and cell lines. Many transporters exhibit extremely high Gini coefficients even for common substrates, indicating considerable specialization consistent with divergent evolution. The expression profiles of SLC transporters in different cell lines behave similarly, although Gini coefficients for ABC transporters tend to be larger in cell lines than in tissues, implying selection...
February 5, 2018: Cell Systems
Elisa Donnard, Pranitha Vangala, Shaked Afik, Sean McCauley, Anetta Nowosielska, Alper Kucukural, Barbara Tabak, Xiaopeng Zhu, William Diehl, Patrick McDonel, Nir Yosef, Jeremy Luban, Manuel Garber
Most well-characterized enhancers are deeply conserved. In contrast, genome-wide comparative studies of steady-state systems showed that only a small fraction of active enhancers are conserved. To better understand conservation of enhancer activity, we used a comparative genomics approach that integrates temporal expression and epigenetic profiles in an innate immune system. We found that gene expression programs diverge among mildly induced genes, while being highly conserved for strongly induced genes. The fraction of conserved enhancers varies greatly across gene expression programs, with induced genes and early-response genes, in particular, being regulated by a higher fraction of conserved enhancers...
January 30, 2018: Cell Systems
Stephanie A Zlatic, Alysia Vrailas-Mortimer, Avanti Gokhale, Lucas J Carey, Elizabeth Scott, Reid Burch, Morgan M McCall, Samantha Rudin-Rush, John Bowen Davis, Cortnie Hartwig, Erica Werner, Lian Li, Michael Petris, Victor Faundez
Rare neurological diseases shed light onto universal neurobiological processes. However, molecular mechanisms connecting genetic defects to their disease phenotypes are elusive. Here, we obtain mechanistic information by comparing proteomes of cells from individuals with rare disorders with proteomes from their disease-free consanguineous relatives. We use triple-SILAC mass spectrometry to quantify proteomes from human pedigrees affected by mutations in ATP7A, which cause Menkes disease, a rare neurodegenerative and neurodevelopmental disorder stemming from systemic copper depletion...
January 30, 2018: Cell Systems
Jin Park, Marta Dies, Yihan Lin, Sahand Hormoz, Stephanie E Smith-Unna, Sofia Quinodoz, María Jesús Hernández-Jiménez, Jordi Garcia-Ojalvo, James C W Locke, Michael B Elowitz
In cells, specific regulators often compete for limited amounts of a core enzymatic resource. It is typically assumed that competition leads to partitioning of core enzyme molecules among regulators at constant levels. Alternatively, however, different regulatory species could time share, or take turns utilizing, the core resource. Using quantitative time-lapse microscopy, we analyzed sigma factor activity dynamics, and their competition for RNA polymerase, in individual Bacillus subtilis cells under energy stress...
January 29, 2018: Cell Systems
Fuqing Wu, Qi Zhang, Xiao Wang
Polycistronic architecture is common for synthetic gene circuits, however, it remains unknown how expression of one gene is affected by the presence of other genes/noncoding regions in the operon, termed adjacent transcriptional regions (ATR). Here, we constructed synthetic operons with a reporter gene flanked by different ATRs, and we found that ATRs with high GC content, small size, and low folding energy lead to high gene expression. Based on these results, we built a model of gene expression and generated a metric that takes into account ATRs...
January 26, 2018: Cell Systems
Ed Reznik, Augustin Luna, Bülent Arman Aksoy, Eric Minwei Liu, Konnor La, Irina Ostrovnaya, Chad J Creighton, A Ari Hakimi, Chris Sander
Tumor metabolism is reorganized to support proliferation in the face of growth-related stress. Unlike the widespread profiling of changes to metabolic enzyme levels in cancer, comparatively less attention has been paid to the substrates/products of enzyme-catalyzed reactions, small-molecule metabolites. We developed an informatic pipeline to concurrently analyze metabolomics data from over 900 tissue samples spanning seven cancer types, revealing extensive heterogeneity in metabolic changes relative to normal tissue across cancers of different tissues of origin...
January 26, 2018: Cell Systems
Han Fang, Yi-Fei Huang, Aditya Radhakrishnan, Adam Siepel, Gholson J Lyon, Michael C Schatz
Ribosome profiling (Ribo-seq) is a powerful technique for measuring protein translation; however, sampling errors and biological biases are prevalent and poorly understood. Addressing these issues, we present Scikit-ribo (, an open-source analysis package for accurate genome-wide A-site prediction and translation efficiency (TE) estimation from Ribo-seq and RNA sequencing data. Scikit-ribo accurately identifies A-site locations and reproduces codon elongation rates using several digestion protocols (r = 0...
January 17, 2018: Cell Systems
Brandon Ho, Anastasia Baryshnikova, Grant W Brown
Protein activity is the ultimate arbiter of function in most cellular pathways, and protein concentration is fundamentally connected to protein action. While the proteome of yeast has been subjected to the most comprehensive analysis of any eukaryote, existing datasets are difficult to compare, and there is no consensus abundance value for each protein. We evaluated 21 quantitative analyses of the S. cerevisiae proteome, normalizing and converting all measurements of protein abundance into the intuitive measurement of absolute molecules per cell...
January 17, 2018: Cell Systems
Karthickeyan Chella Krishnan, Zeyneb Kurt, Rio Barrere-Cain, Simon Sabir, Aditi Das, Raquel Floyd, Laurent Vergnes, Yuqi Zhao, Nam Che, Sarada Charugundla, Hannah Qi, Zhiqiang Zhou, Yonghong Meng, Calvin Pan, Marcus M Seldin, Frode Norheim, Simon Hui, Karen Reue, Aldons J Lusis, Xia Yang
The etiology of non-alcoholic fatty liver disease (NAFLD), the most common form of chronic liver disease, is poorly understood. To understand the causal mechanisms underlying NAFLD, we conducted a multi-omics, multi-tissue integrative study using the Hybrid Mouse Diversity Panel, consisting of ∼100 strains of mice with various degrees of NAFLD. We identified both tissue-specific biological processes and processes that were shared between adipose and liver tissues. We then used gene network modeling to predict candidate regulatory genes of these NAFLD processes, including Fasn, Thrsp, Pklr, and Chchd6...
January 17, 2018: Cell Systems
Brian D Piening, Wenyu Zhou, Kévin Contrepois, Hannes Röst, Gucci Jijuan Gu Urban, Tejaswini Mishra, Blake M Hanson, Eddy J Bautista, Shana Leopold, Christine Y Yeh, Daniel Spakowicz, Imon Banerjee, Cynthia Chen, Kimberly Kukurba, Dalia Perelman, Colleen Craig, Elizabeth Colbert, Denis Salins, Shannon Rego, Sunjae Lee, Cheng Zhang, Jessica Wheeler, M Reza Sailani, Liang Liang, Charles Abbott, Mark Gerstein, Adil Mardinoglu, Ulf Smith, Daniel L Rubin, Sharon Pitteri, Erica Sodergren, Tracey L McLaughlin, George M Weinstock, Michael P Snyder
Advances in omics technologies now allow an unprecedented level of phenotyping for human diseases, including obesity, in which individual responses to excess weight are heterogeneous and unpredictable. To aid the development of better understanding of these phenotypes, we performed a controlled longitudinal weight perturbation study combining multiple omics strategies (genomics, transcriptomics, multiple proteomics assays, metabolomics, and microbiomics) during periods of weight gain and loss in humans. Results demonstrated that: (1) weight gain is associated with the activation of strong inflammatory and hypertrophic cardiomyopathy signatures in blood; (2) although weight loss reverses some changes, a number of signatures persist, indicative of long-term physiologic changes; (3) we observed omics signatures associated with insulin resistance that may serve as novel diagnostics; (4) specific biomolecules were highly individualized and stable in response to perturbations, potentially representing stable personalized markers...
January 16, 2018: Cell Systems
Ira W Deveson, Marion E Brunck, James Blackburn, Elizabeth Tseng, Ting Hon, Tyson A Clark, Michael B Clark, Joanna Crawford, Marcel E Dinger, Lars K Nielsen, John S Mattick, Tim R Mercer
The human transcriptome is so large, diverse, and dynamic that, even after a decade of investigation by RNA sequencing (RNA-seq), we have yet to resolve its true dimensions. RNA-seq suffers from an expression-dependent bias that impedes characterization of low-abundance transcripts. We performed targeted single-molecule and short-read RNA-seq to survey the transcriptional landscape of a single human chromosome (Hsa21) at unprecedented resolution. Our analysis reaches the lower limits of the transcriptome, identifying a fundamental distinction between protein-coding and noncoding gene content: almost every noncoding exon undergoes alternative splicing, producing a seemingly limitless variety of isoforms...
January 2, 2018: Cell Systems
Daniel Schulz, Vito Riccardo Tomaso Zanotelli, Jana Raja Fischer, Denis Schapiro, Stefanie Engler, Xiao-Kang Lun, Hartland Warren Jackson, Bernd Bodenmiller
To build comprehensive models of cellular states and interactions in normal and diseased tissue, genetic and proteomic information must be extracted with single-cell and spatial resolution. Here, we extended imaging mass cytometry to enable multiplexed detection of mRNA and proteins in tissues. Three mRNA target species were detected by RNAscope-based metal in situ hybridization with simultaneous antibody detection of 16 proteins. Analysis of 70 breast cancer samples showed that HER2 and CK19 mRNA and protein levels are moderately correlated on the single-cell level, but that only HER2, and not CK19, has strong mRNA-to-protein correlation on the cell population level...
December 26, 2017: Cell Systems
Yang Liu, Perry Palmedo, Qing Ye, Bonnie Berger, Jian Peng
While genes are defined by sequence, in biological systems a protein's function is largely determined by its three-dimensional structure. Evolutionary information embedded within multiple sequence alignments provides a rich source of data for inferring structural constraints on macromolecules. Still, many proteins of interest lack sufficient numbers of related sequences, leading to noisy, error-prone residue-residue contact predictions. Here we introduce DeepContact, a convolutional neural network (CNN)-based approach that discovers co-evolutionary motifs and leverages these patterns to enable accurate inference of contact probabilities, particularly when few related sequences are available...
December 19, 2017: Cell Systems
Rune Rasmussen, Mogens H Jensen, Mathias L Heltberg
Previous studies have suggested that changes in extracellular ion concentrations initiate the transition from an activity state that characterizes sleep in cortical neurons to states that characterize wakefulness. However, because neuronal activity and extracellular ion concentrations are interdependent, isolating their unique roles during sleep-wake transitions is not possible in vivo. Here, we extend the Averaged-Neuron model and demonstrate that, although changes in extracellular ion concentrations occur concurrently, decreasing the conductance of calcium-dependent potassium channels initiates the transition from sleep to wakefulness...
December 12, 2017: Cell Systems
Christopher P Lapointe, Jonathan A Stefely, Adam Jochem, Paul D Hutchins, Gary M Wilson, Nicholas W Kwiecien, Joshua J Coon, Marvin Wickens, David J Pagliarini
Coenzyme Q (CoQ) is a redox-active lipid required for mitochondrial oxidative phosphorylation (OxPhos). How CoQ biosynthesis is coordinated with the biogenesis of OxPhos protein complexes is unclear. Here, we show that the Saccharomyces cerevisiae RNA-binding protein (RBP) Puf3p regulates CoQ biosynthesis. To establish the mechanism for this regulation, we employed a multi-omic strategy to identify mRNAs that not only bind Puf3p but also are regulated by Puf3p in vivo. The CoQ biosynthesis enzyme Coq5p is a critical Puf3p target: Puf3p regulates the abundance of Coq5p and prevents its detrimental hyperaccumulation, thereby enabling efficient CoQ production...
December 12, 2017: Cell Systems
Philippe Lucarelli, Marcel Schilling, Clemens Kreutz, Artyom Vlasov, Martin E Boehm, Nao Iwamoto, Bernhard Steiert, Susen Lattermann, Marvin Wäsch, Markus Stepath, Matthias S Matter, Mathias Heikenwälder, Katrin Hoffmann, Daniela Deharde, Georg Damm, Daniel Seehofer, Maria Muciek, Norbert Gretz, Wolf D Lehmann, Jens Timmer, Ursula Klingmüller
Upon stimulation of cells with transforming growth factor β (TGF-β), Smad proteins form trimeric complexes and activate a broad spectrum of target genes. It remains unresolved which of the possible Smad complexes are formed in cellular contexts and how these contribute to gene expression. By combining quantitative mass spectrometry with a computational selection strategy, we predict and provide experimental evidence for the three most relevant Smad complexes in the mouse hepatoma cell line Hepa1-6. Utilizing dynamic pathway modeling, we specify the contribution of each Smad complex to the expression of representative Smad target genes, and show that these contributions are conserved in human hepatoma cell lines and primary hepatocytes...
December 12, 2017: Cell Systems
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