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Cell Systems

Colm J Ryan, Susan Kennedy, Ilirjana Bajrami, David Matallanas, Christopher J Lord
Protein complexes are responsible for the bulk of activities within the cell, but how their behavior and abundance varies across tumors remains poorly understood. By combining proteomic profiles of breast tumors with a large-scale protein-protein interaction network, we have identified a set of 285 high-confidence protein complexes whose subunits have highly correlated protein abundance across tumor samples. We used this set to identify complexes that are reproducibly under- or overexpressed in specific breast cancer subtypes...
October 10, 2017: Cell Systems
Emanuel Gonçalves, Athanassios Fragoulis, Luz Garcia-Alonso, Thorsten Cramer, Julio Saez-Rodriguez, Pedro Beltrao
Copy-number variations (CNVs) are ubiquitous in cancer and often act as driver events, but the effects of CNVs on the proteome of tumors are poorly understood. Here, we analyze recently published genomics, transcriptomics, and proteomics datasets made available by CPTAC and TCGA consortia on 282 breast, ovarian, and colorectal tumor samples to investigate the impact of CNVs in the proteomes of these cells. We found that CNVs are buffered by post-transcriptional regulation in 23%-33% of proteins that are significantly enriched in protein complex members...
October 9, 2017: Cell Systems
James T Yurkovich, Benjamin J Yurkovich, Andreas Dräger, Bernhard O Palsson, Zachary A King
With the rapid adoption of computational tools in the life sciences, scientists are taking on the challenge of developing their own software libraries and releasing them for public use. This trend is being accelerated by popular technologies and platforms, such as GitHub, Jupyter, R/Shiny, that make it easier to develop scientific software and by open-source licenses that make it easier to release software. But how do you build a software library that people will use? And what characteristics do the best libraries have that make them enduringly popular? Here, we provide a reference guide, based on our own experiences, for developing software libraries along with real-world examples to help provide context for scientists who are learning about these concepts for the first time...
October 4, 2017: Cell Systems
Mehmet Gönen, Barbara A Weir, Glenn S Cowley, Francisca Vazquez, Yuanfang Guan, Alok Jaiswal, Masayuki Karasuyama, Vladislav Uzunangelov, Tao Wang, Aviad Tsherniak, Sara Howell, Daniel Marbach, Bruce Hoff, Thea C Norman, Antti Airola, Adrian Bivol, Kerstin Bunte, Daniel Carlin, Sahil Chopra, Alden Deran, Kyle Ellrott, Peddinti Gopalacharyulu, Kiley Graim, Samuel Kaski, Suleiman A Khan, Yulia Newton, Sam Ng, Tapio Pahikkala, Evan Paull, Artem Sokolov, Hao Tang, Jing Tang, Krister Wennerberg, Yang Xie, Xiaowei Zhan, Fan Zhu, Tero Aittokallio, Hiroshi Mamitsuka, Joshua M Stuart, Jesse S Boehm, David E Root, Guanghua Xiao, Gustavo Stolovitzky, William C Hahn, Adam A Margolin
We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors...
October 3, 2017: Cell Systems
Jie Lin, Ariel Amir
Establishing a quantitative connection between the population growth rate and the generation times of single cells is a prerequisite for understanding evolutionary dynamics of microbes. However, existing theories fail to account for the experimentally observed correlations between mother-daughter generation times that are unavoidable when cell size is controlled for, which is essentially always the case. Here, we study population-level growth in the presence of cell size control and corroborate our theory using experimental measurements of single-cell growth rates...
October 3, 2017: Cell Systems
Minho Noh, Seung Min Yoo, Won Jun Kim, Sang Yup Lee
Escherichia coli gene expression knockdown using synthetic small RNA (sRNA) can be fine-tuned by altering sRNA sequences to modulate target mRNA-binding ability, but this requires thorough checking for off-target effects. Here, we present an sRNA gene expression knockdown system fine-tuned by using different promoters to modulate synthetic sRNA abundance. Our approach entails selecting knockdown target genes resulting from in silico flux response analysis and those related to product biosynthesis then screening strains transformed with a library of synthetic sRNA-promoter combinations for enhanced production...
September 26, 2017: Cell Systems
Julia B Carleton, Kristofer C Berrett, Jason Gertz
Multiple regulatory regions have the potential to regulate a single gene, yet how these elements combine to affect gene expression remains unclear. To uncover the combinatorial relationships between enhancers, we developed Enhancer-interference (Enhancer-i), a CRISPR interference-based approach that uses 2 different repressive domains, KRAB and SID, to prevent enhancer activation simultaneously at multiple regulatory regions. We applied Enhancer-i to promoter-distal estrogen receptor α binding sites (ERBS), which cluster around estradiol-responsive genes and therefore may collaborate to regulate gene expression...
September 26, 2017: Cell Systems
Olga Ponomarova, Natalia Gabrielli, Daniel C Sévin, Michael Mülleder, Katharina Zirngibl, Katsiaryna Bulyha, Sergej Andrejev, Eleni Kafkia, Athanasios Typas, Uwe Sauer, Markus Ralser, Kiran Raosaheb Patil
Many microorganisms live in communities and depend on metabolites secreted by fellow community members for survival. Yet our knowledge of interspecies metabolic dependencies is limited to few communities with small number of exchanged metabolites, and even less is known about cellular regulation facilitating metabolic exchange. Here we show how yeast enables growth of lactic acid bacteria through endogenous, multi-component, cross-feeding in a readily established community. In nitrogen-rich environments, Saccharomyces cerevisiae adjusts its metabolism by secreting a pool of metabolites, especially amino acids, and thereby enables survival of Lactobacillus plantarum and Lactococcus lactis...
September 26, 2017: Cell Systems
Patrick S Stumpf, Rosanna C G Smith, Michael Lenz, Andreas Schuppert, Franz-Josef Müller, Ann Babtie, Thalia E Chan, Michael P H Stumpf, Colin P Please, Sam D Howison, Fumio Arai, Ben D MacArthur
Pluripotent stem cells can self-renew in culture and differentiate along all somatic lineages in vivo. While much is known about the molecular basis of pluripotency, the mechanisms of differentiation remain unclear. Here, we profile individual mouse embryonic stem cells as they progress along the neuronal lineage. We observe that cells pass from the pluripotent state to the neuronal state via an intermediate epiblast-like state. However, analysis of the rate at which cells enter and exit these observed cell states using a hidden Markov model indicates the presence of a chain of unobserved molecular states that each cell transits through stochastically in sequence...
September 27, 2017: Cell Systems
Thalia E Chan, Michael P H Stumpf, Ann C Babtie
While single-cell gene expression experiments present new challenges for data processing, the cell-to-cell variability observed also reveals statistical relationships that can be used by information theory. Here, we use multivariate information theory to explore the statistical dependencies between triplets of genes in single-cell gene expression datasets. We develop PIDC, a fast, efficient algorithm that uses partial information decomposition (PID) to identify regulatory relationships between genes. We thoroughly evaluate the performance of our algorithm and demonstrate that the higher-order information captured by PIDC allows it to outperform pairwise mutual information-based algorithms when recovering true relationships present in simulated data...
September 27, 2017: Cell Systems
Yaron Orenstein, Robert Puccinelli, Ryan Kim, Polly Fordyce, Bonnie Berger
Sequence libraries that cover all k-mers enable universal, unbiased measurements of binding to both oligonucleotides and peptides. While the number of k-mers grows exponentially in k, space on all experimental platforms is limited. Here, we shrink k-mer library sizes by using joker characters, which represent all characters in the alphabet simultaneously. We present the JokerCAKE (joker covering all k-mers) algorithm for generating a short sequence such that each k-mer appears at least p times with at most one joker character per k-mer...
September 27, 2017: Cell Systems
Borislav H Hristov, Mona Singh
A central goal in cancer genomics is to identify the somatic alterations that underpin tumor initiation and progression. While commonly mutated cancer genes are readily identifiable, those that are rarely mutated across samples are difficult to distinguish from the large numbers of other infrequently mutated genes. We introduce a method, nCOP, that considers per-individual mutational profiles within the context of protein-protein interaction networks in order to identify small connected subnetworks of genes that, while not individually frequently mutated, comprise pathways that are altered across (i...
September 27, 2017: Cell Systems
Sai Zhang, Hailin Hu, Jingtian Zhou, Xuan He, Tao Jiang, Jianyang Zeng
Ribosome stalling is manifested by the local accumulation of ribosomes at specific codon positions of mRNAs. Here, we present ROSE, a deep learning framework to analyze high-throughput ribosome profiling data and estimate the probability of a ribosome stalling event occurring at each genomic location. Extensive validation tests on independent data demonstrated that ROSE possessed higher prediction accuracy than conventional prediction models, with an increase in the area under the receiver operating characteristic curve by up to 18...
September 27, 2017: Cell Systems
Sheng Wang, Zhen Li, Yizhou Yu, Jinbo Xu
Computational elucidation of membrane protein (MP) structures is challenging partially due to lack of sufficient solved structures for homology modeling. Here, we describe a high-throughput deep transfer learning method that first predicts MP contacts by learning from non-MPs and then predicts 3D structure models using the predicted contacts as distance restraints. Tested on 510 non-redundant MPs, our method has contact prediction accuracy at least 0.18 better than existing methods, predicts correct folds for 218 MPs, and generates 3D models with root-mean-square deviation (RMSD) less than 4 and 5 Å for 57 and 108 MPs, respectively...
September 27, 2017: Cell Systems
Luca Mariani, Kathryn Weinand, Anastasia Vedenko, Luis A Barrera, Martha L Bulyk
Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs...
September 27, 2017: Cell Systems
(no author information available yet)
This Cell Systems Call features invited summaries of 32 of the 38 papers accepted for presentation in the "regular track" at the 2017 Research in Computational Molecular Biology conference. The editors have categorized the summaries into cancer genomics, genetics, mass spectrometry, metagenomics, network analysis, phylogenetics, sequence annotation, sequence informatics, single-cell data analysis, and structural biology.
September 27, 2017: Cell Systems
Rune Rasmussen, Andrew J Samson
Anatomy, physiology, proteomics, and genomics reveal the prospect of distinct highly specialized astrocyte subtypes within neural circuits.
September 27, 2017: Cell Systems
N Moris, A Martinez Arias
An integrated approach unifies experimental observations and mathematical modeling to represent differentiation dynamics as discrete transition events underpinned by stochastic transitions between hidden states.
September 27, 2017: Cell Systems
Mansi Arora, Sabrina L Spencer
Live-cell imaging demonstrates that a subset of neuroblastoma cells evades chemotherapy-induced death if they are in early G1 phase of the cell cycle at the time of drug treatment and have sufficiently high levels of MYCN.
September 27, 2017: Cell Systems
(no author information available yet)
This month: relating single cells to populations (Cao/Packer, Wu/Altschuler, O'Brien, Friedman), an excess of ribosomes (Barkai), human pathology atlas (Uhlen), signatures of feedback (Rahi), and major genome redesign (Baumgart).
September 27, 2017: Cell Systems
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