Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells.
Yuichi Taniguchi,Paul J. Choi,Gene-Wei Li,Huiyi Chen,Mohan Babu,Jeremy Hearn,Andrew Emili,X. Sunney Xie +7 more
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TLDR
System-wide analyses of protein and mRNA expression in individual cells with single-molecule sensitivity using a newly constructed yellow fluorescent protein fusion library for Escherichia coli found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size.Abstract:
Protein and messenger RNA (mRNA) copy numbers vary from cell to cell in isogenic bacterial populations. However, these molecules often exist in low copy numbers and are difficult to detect in single cells. We carried out quantitative system-wide analyses of protein and mRNA expression in individual cells with single-molecule sensitivity using a newly constructed yellow fluorescent protein fusion library for Escherichia coli. We found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size. At high expression levels, the distributions are dominated by extrinsic noise. We found that a single cell's protein and mRNA copy numbers for any given gene are uncorrelated.read more
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Journal ArticleDOI
Tissue-based map of the human proteome
Mathias Uhlén,Mathias Uhlén,Linn Fagerberg,Björn M. Hallström,Cecilia Lindskog,Per Oksvold,Adil Mardinoglu,Åsa Sivertsson,Caroline Kampf,Evelina Sjöstedt,Evelina Sjöstedt,Anna Asplund,IngMarie Olsson,Karolina Edlund,Emma Lundberg,Sanjay Navani,Cristina Al-Khalili Szigyarto,Jacob Odeberg,Dijana Djureinovic,Jenny Ottosson Takanen,Sophia Hober,Tove Alm,Per-Henrik Edqvist,Holger Berling,Hanna Tegel,Jan Mulder,Johan Rockberg,Peter Nilsson,Jochen M. Schwenk,Marica Hamsten,Kalle von Feilitzen,Mattias Forsberg,Lukas Persson,Fredric Johansson,Martin Zwahlen,Gunnar von Heijne,Jens Nielsen,Jens Nielsen,Fredrik Pontén +38 more
TL;DR: In this paper, a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level.
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Insights into the regulation of protein abundance from proteomic and transcriptomic analyses
TL;DR: Current understanding of the major factors regulating protein expression is summarized to demonstrate a substantial role for regulatory processes occurring after mRNA is made in controlling steady-state protein abundances.
Journal ArticleDOI
On the Dependency of Cellular Protein Levels on mRNA Abundance.
TL;DR: It is concluded that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.
References
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Journal ArticleDOI
Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.
Pingzhao Hu,Sarath Chandra Janga,Sarath Chandra Janga,Mohan Babu,J. Javier Díaz-Mejía,J. Javier Díaz-Mejía,Gareth Butland,Wenhong Yang,Oxana Pogoutse,Xinghua Guo,Sadhna Phanse,Peter D Wong,Shamanta Chandran,Constantine C. Christopoulos,Anaies Nazarians-Armavil,Negin Karimi Nasseri,Gabriel Musso,Mehrab Ali,Nazila Nazemof,Veronika Eroukova,Ashkan Golshani,Alberto Paccanaro,Jack Greenblatt,Gabriel Moreno-Hagelsieb,Andrew Emili +24 more
TL;DR: An extensive proteomic survey using affinity-tagged E. coli strains is performed and comprehensive genomic context inferences are generated to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel.
Journal ArticleDOI
Single-Cell Transcriptional Analysis of Neuronal Progenitors
Ian Tietjen,Jason Rihel,Yanxiang Cao,Georgy Koentges,Georgy Koentges,Lisa Zakhary,Catherine Dulac +6 more
TL;DR: The technique provides a sensitive and reproducible representation of the single-cell transcriptome and shows that regional differences in gene expression can be predicted from transcriptional analysis of single neuronal precursors isolated by laser capture from defined areas of the developing brain.
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eSGA: E. coli synthetic genetic array analysis
Gareth Butland,Gareth Butland,Mohan Babu,J. Javier Díaz-Mejía,J. Javier Díaz-Mejía,Fedyshyn Bohdana,Sadhna Phanse,Barbara Gold,Wenhong Yang,Joyce Li,Alla Gagarinova,Oxana Pogoutse,Hirotada Mori,Barry L. Wanner,Henry Lo,Jas Wasniewski,Constantine C. Christopoulos,Mehrab Ali,Pascal Venn,Anahita Safavi-Naini,Natalie Sourour,Simone Caron,Ja-Yeon Choi,Ludovic Laigle,Anaies Nazarians-Armavil,Avnish Deshpande,Sarah Joe,Kirill A. Datsenko,Natsuko Yamamoto,Brenda J. Andrews,Charles Boone,Charles Boone,Huiming Ding,Bilal N. Sheikh,Gabriel Moreno-Hagelsieb,Jack Greenblatt,Andrew Emili +36 more
TL;DR: The development of a quantitative screening procedure for monitoring bacterial genetic interactions based on conjugation of Escherichia coli deletion or hypomorphic strains to create double mutants on a genome-wide scale is described.
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Random signal fluctuations can reduce random fluctuations in regulated components of chemical regulatory networks.
Johan Paulsson,Måns Ehrenberg +1 more
TL;DR: This work uses chemical master equations to analyze a negative feedback system where species X and S regulate each other's synthesis with standard intracellular kinetics and shows that signal noise can be necessary to reduce X-variation below a Poissonian limit.