Methods & Resources
- Ultrasensitive proteome analysis using paramagnetic bead technology
- Christopher S Hughes1,
- Sophia Foehr1,
- David A Garfield1,
- Eileen E Furlong1,
- Lars M Steinmetz1 and
- Jeroen Krijgsveld*,1
- ↵*Corresponding author. Tel: +49 6221 3878560; E‐mail: jeroen.krijgsveld{at}embl.de
A new proteomic sample preparation protocol allows fast, efficient and ultra‐sensitive analyses. The method is illustrated by profiling proteomes from sub‐microgram amounts of material, including the first proteome screen of Drosophila development at a single‐embryo resolution.
Synopsis
A new proteomic sample preparation protocol allows fast, efficient and ultra‐sensitive analyses. The method is illustrated by profiling proteomes from sub‐microgram amounts of material, including the first proteome screen of Drosophila development at a single‐embryo resolution.
A novel protocol using paramagnetic beads, termed Single‐Pot Solid‐Phase‐enhanced Sample Preparation (SP3) is presented.
SP3 enables protein and peptide enrichment, cleanup, digestion, chemical isotope labeling and fractionation in a single tube, without limitations arising from reagent compatibility.
SP3 allows unmatched ultra‐sensitive proteome profiling from sub‐microgram amounts of material, as low as 1,000 HeLa cells or a single fly embryo.
The first quantitative analysis of early Drosophila development at a single‐embryo resolution reveals dynamic trends in the developmental proteome.
Mol Syst Biol. (2014) 10: 757
- Received July 27, 2014.
- Revision received October 1, 2014.
- Accepted October 7, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- A ‘resource allocator’ for transcription based on a highly fragmented T7 RNA polymerase
- Thomas H Segall‐Shapiro1,
- Adam J Meyer2,
- Andrew D Ellington2,
- Eduardo D Sontag3 and
- Christopher A Voigt*,1
- 1Department of Biological Engineering, Synthetic Biology Center Massachusetts Institute of Technology, Cambridge, MA, USA
- 2Institute for Cellular and Molecular Biology University of Texas at Austin, Austin, TX, USA
- 3Department of Mathematics, Rutgers University, Piscataway, NJ, USA
- ↵*Corresponding author. Tel: +1 617 324 4851; E‐mail: cavoigt{at}gmail.com
The T7 RNA polymerase is split into two to four fragments that retain activity when co‐expressed. These parts provide a toolbox to allocate resources to a genetic system, set its transcriptional activity and partition it between multiple orthogonal promoters.
Synopsis
The T7 RNA polymerase is split into two to four fragments that retain activity when co‐expressed. These parts provide a toolbox to allocate resources to a genetic system, set its transcriptional activity and partition it between multiple orthogonal promoters.
T7 RNA polymerase is bisected at five distinct regions and combinations of these fragments yield active three‐ and four‐piece polymerases.
Specificity loop mutations introduced to the C‐terminal fragment, create variable “σ fragments” that bind to the remaining conserved “core fragment” and activate orthogonal promoters.
Using the σ and core fragments, a resource allocator is built that can regulate the total transcriptional activity of a synthetic system and dynamically partition it between promoters.
Further splits and mutations are used to build positive and negative regulators of the resource allocator, enabling more complex system architectures.
Mol Syst Biol. (2014) 10: 742
- Received March 21, 2014.
- Revision received June 5, 2014.
- Accepted June 24, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Synthetic biology: the many facets of T7 RNA polymerase
Split T7 RNA polymerase provides new avenues for creating synthetic gene circuits that are decoupled from host regulatory processes—but how many times can this enzyme be split, yet retain function? New research by Voigt and colleagues (Segall‐Shapiro et al, 2014) indicates that it may be more than you think.
See also: TH Segall‐Shapiro et al (July 2014)
How many times can T7 RNA polymerase be split, yet retain function? A tripartite T7 RNAP presented by Voigt and colleagues, expands the utility of the enzyme in orthogonal gene circuits that are decoupled from host regulatory processes.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Measuring error rates in genomic perturbation screens: gold standards for human functional genomics
- 1Donnelly Centre and Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada
- 2Campbell Family Cancer Research Institute, Ontario Cancer Institute, Princess Margaret Hospital University Health Network, Toronto, ON, Canada
- 3Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- 4Division of Rheumatology, Department of Medicine, St. Michael's Hospital, Toronto, ON, Canada
- 5Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- ↵*Corresponding author. Tel: +1 416 978 4019; E‐mail: j.moffat{at}utoronto.ca
This study provides a gold‐standard set for essential and nonessential human genes in cancer cell lines. The ‘Daisy model’ for core versus context‐specific essentiality provides a method to evaluate data quality in genome‐scale RNAi and CRISPR screens.
Synopsis
This study provides a gold‐standard set for essential and nonessential human genes in cancer cell lines. The ‘Daisy model’ for core versus context‐specific essentiality provides a method to evaluate data quality in genome‐scale RNAi and CRISPR screens.
Gold‐standard reference sets of human essential and nonessential genes are leveraged to improve analyses of RNAi and CRISPR screens.
Characteristics of human essential genes are derived from the cumulative analysis of RNAi screens.
The Daisy model of gene essentiality is derived from the difference between core and context‐specific cell line essentials.
A computational framework is presented for the prediction of human essential genes from reverse genetic screening data.
Mol Syst Biol. (2014) 10: 733
- Received February 20, 2014.
- Revision received April 10, 2014.
- Accepted April 24, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- The Good, the Bad, and the Ugly: in search of gold standards for assessing functional genetic screen quality
Variable screen quality, off‐target effects, and unclear false discovery rates often hamper large‐scale functional genomic screens in mammalian cells. Hart et al (2014) introduce gold standard reference sets of essential and non‐essential genes, aiming at standardizing the analysis of genome‐wide screens. This work provides a framework to compare both the quality and analysis methods of functional genetic screens.
See also: T Hart et al (2014)
Variable screen quality, off‐target effects and unclear false discovery rates often hamper large‐scale functional genomic screens. Hart et al (2014) introduce gold standard reference sets of essential and non‐essential genes, aiming at standardizing the analysis of genome‐wide screens.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Efficient search, mapping, and optimization of multi‐protein genetic systems in diverse bacteria
- Iman Farasat1,
- Manish Kushwaha2,
- Jason Collens2,
- Michael Easterbrook1,
- Matthew Guido1 and
- Howard M Salis*,1,2
- 1Department of Chemical Engineering, Pennsylvania State University, University Park, PA, USA
- 2Department of Biological Engineering, Pennsylvania State University, University Park, PA, USA
- ↵*Corresponding author. Tel: +1 814 865 1931; E‐mail: salis{at}psu.edu
A computational approach for designing multi‐enzyme pathways is presented that combines sequence optimization, kinetic modeling, and accurate expression prediction. The method is illustrated for the direct forward engineering of robust circuits with targeted activities.
Synopsis
A computational approach for designing multi‐enzyme pathways is presented that combines sequence optimization, kinetic modeling and accurate expression prediction. The method is illustrated for the direct forward engineering of robust circuits with targeted activities.
Biophysical modeling and computational design are combined to create predictive sequence‐expression‐activity maps (SEAMAP) for multi‐protein genetic systems.
The algorithm designs the smallest number of variants with expression levels covering the largest part of the multi‐protein expression space.
The predictions are validated using 646 genetic system variants, encoded on plasmids and genomes and expressed in gram‐negative and gram‐positive bacteria
A SEAMAP of a 3‐enzyme biosynthesis pathway is used to optimize the pathway's sequences and expression levels for different design objectives.
Mol Syst Biol. (2014) 10: 731
- Received November 1, 2013.
- Revision received April 27, 2014.
- Accepted May 6, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Screen for mitochondrial DNA copy number maintenance genes reveals essential role for ATP synthase
- Atsushi Fukuoh1,2,3,†,
- Giuseppe Cannino1,†,
- Mike Gerards1,
- Suzanne Buckley1,
- Selena Kazancioglu1,
- Filippo Scialo1,
- Eero Lihavainen4,
- Andre Ribeiro4,
- Eric Dufour1 and
- Howard T Jacobs*,1,5
- 1BioMediTech and Tampere University Hospital, University of Tampere, Tampere, Finland
- 2Department of Clinical Chemistry and Laboratory Medicine, Kyushu University Graduate school of Medical Sciences, Fukuoka, Japan
- 3Department of Medical Laboratory Science, Junshin Gakuen University, Fukuoka, Japan
- 4Department of Signal Processing, Tampere University of Technology, Tampere, Finland
- 5Research Program of Molecular Neurology, University of Helsinki, Helsinki, Finland
- ↵*Corresponding author. Tel: +358 3 3551 7731, +358 50 341 2894; E‐mail: howard.t.jacobs{at}uta.fi
-
↵† These authors equally contributed to this work.
An RNAi screen for genes needed in mtDNA copy number maintenance in Drosophila yielded 97 positives, including previously characterized mtDNA maintenance proteins, subunits of the cytoribosome, proteasome, and ATP synthase.
Synopsis
An RNAi screen for genes needed in mtDNA copy number maintenance in Drosophila yielded 97 positives, including previously characterized mtDNA maintenance proteins, subunits of the cytoribosome, proteasome, and ATP synthase.
An RNAi screen for genes needed in mtDNA copy number maintenance in Drosophila yielded 97 positives.
These included previously characterized components of the mtDNA maintenance machinery.
Other major classes of positives were the cytoribosome, proteasome, and ATP synthase.
ATP synthase deficiency results in increased ROS and activation of mitochondrial turnover by pathway(s) distinct from classical autophagy.
Mol Syst Biol. (2014) 10: 734
- Received January 12, 2014.
- Revision received May 2, 2014.
- Accepted May 2, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Cell cycle population effects in perturbation studies
- Eoghan O'Duibhir1,†,
- Philip Lijnzaad1,†,
- Joris J Benschop1,
- Tineke L Lenstra1,
- Dik van Leenen1,
- Marian JA Groot Koerkamp1,
- Thanasis Margaritis1,
- Mariel O Brok1,
- Patrick Kemmeren1 and
- Frank CP Holstege*,1
- ↵*Corresponding author. Tel: +31 88 755 5874; Fax: +31 88 756 8531; E‐mail: f.c.p.holstege{at}umcutrecht.nl
-
↵† These authors contributed equally to this work
Genetic, stress or nutrient perturbation of yeast resulting in slower growth yields a common expression signature, previously known as the environmental stress response. This is largely due to a cell cycle population shift and is relevant to many perturbation‐based studies.
Synopsis
Genetic, stress, or nutrient perturbation of yeast resulting in slower growth yields a common expression signature, previously known as the environmental stress response. This is largely due to a cell cycle population shift and is relevant to many perturbation‐based studies.
Yeast deletion strains with slower growth exhibit a common gene expression signature proportional to their degree of slow growth.
The slow growth signature is also found in wild‐type cells subjected to various environmental perturbations that result in slow growth including the environmental stress response (ESR).
The ESR and the genetic perturbation slow growth signature can largely be explained by a redistribution of cells over cell cycle phases.
Transformation of slow growth‐affected data enriches for finding direct targets of the original perturbation.
Mol Syst Biol. (2014) 10: 732
- Received February 1, 2014.
- Revision received May 8, 2014.
- Accepted May 12, 2014.
- © 2014 The Authors. Published under the terms of the CC BY 4.0 license
This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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