Evaluation of mTOR-regulated mRNA translation.

mTOR, the mammalian target of rapamycin, regulates protein synthesis (mRNA translation) by affecting the phosphorylation or activity of several translation factors. Here, we describe methods for studying the impact of mTOR signalling on protein synthesis, using inhibitors of mTOR such as rapamycin (which impairs some of its functions) or mTOR kinase inhibitors (which probably block all functions).To assess effects of mTOR inhibition on general protein synthesis in cells, the incorporation of radiolabelled amino acids into protein is measured. This does not yield information on the effects of mTOR on the synthesis of specific proteins. To do this, two methods are described. In one, stable-isotope labelled amino acids are used, and their incorporation into new proteins is determined using mass spectrometric methods. The proportions of labelled vs. unlabeled versions of each peptide from a given protein provide quantitative information about the rate of that protein's synthesis under different conditions. Actively translated mRNAs are associated with ribosomes in polyribosomes (polysomes); thus, examining which mRNAs are found in polysomes under different conditions provides information on the translation of specific mRNAs under different conditions. A method for the separation of polysomes from non-polysomal mRNAs is describe

Whole cell proteome regulation by microRNAs captured in a pulsed SILAC mass spectrometry approach

Since gene expression is controlled on many different levels in a cell, capturing a comprehensive snapshot of all regulatory processes is a difficult task. One possibility to monitor effective changes within a cell is to directly quantify changes in protein synthesis, which reflects the accumulative impact of regulatory mechanisms on gene expression. Pulsed stable isotope labeling by amino acids in cell culture (pSILAC) has been shown to be a viable method to investigate de novo protein synthesis on a proteome-wide scale (Schwanhausser et al., Proteomics 9:205-209, 2009; Selbach et al., Nature 455:58-63, 2008). One application of pSILAC is to study the regulation of protein expression by microRNAs. Here, we describe how pSILAC in conjunction with shotgun mass spectrometry can assess differences in the protein profile between cells transfected with a microRNA and non-transfected cells

FANCD2–FANCI is a clamp stabilized on DNA by monoubiquitination of FANCD2 during DNA repair

Vertebrate DNA crosslink repair excises toxic replication-blocking DNA crosslinks. Numerous factors involved in crosslink repair have been identified, and mutations in their corresponding genes cause Fanconi anemia (FA). A key step in crosslink repair is monoubiquitination of the FANCD2-FANCI heterodimer, which then recruits nucleases to remove the DNA lesion. Here, we use cryo-EM to determine the structures of recombinant chicken FANCD2 and FANCI complexes. FANCD2-FANCI adopts a closed conformation when the FANCD2 subunit is monoubiquitinated, creating a channel that encloses double-stranded DNA (dsDNA). Ubiquitin is positioned at the interface of FANCD2 and FANCI, where it acts as a covalent molecular pin to trap the complex on DNA. In contrast, isolated FANCD2 is a homodimer that is unable to bind DNA, suggestive of an autoinhibitory mechanism that prevents premature activation. Together, our work suggests that FANCD2-FANCI is a clamp that is locked onto DNA by ubiquitin, with distinct interfaces that may recruit other DNA repair factors

Protein abundance profiling of the Escherichia coli cytosol

<p>Abstract</p> <p>Background</p> <p>Knowledge about the abundance of molecular components is an important prerequisite for building quantitative predictive models of cellular behavior. Proteins are central components of these models, since they carry out most of the fundamental processes in the cell. Thus far, protein concentrations have been difficult to measure on a large scale, but proteomic technologies have now advanced to a stage where this information becomes readily accessible.</p> <p>Results</p> <p>Here, we describe an experimental scheme to maximize the coverage of proteins identified by mass spectrometry of a complex biological sample. Using a combination of LC-MS/MS approaches with protein and peptide fractionation steps we identified 1103 proteins from the cytosolic fraction of the <it>Escherichia coli </it>strain MC4100. A measure of abundance is presented for each of the identified proteins, based on the recently developed emPAI approach which takes into account the number of sequenced peptides per protein. The values of abundance are within a broad range and accurately reflect independently measured copy numbers per cell.</p> <p>As expected, the most abundant proteins were those involved in protein synthesis, most notably ribosomal proteins. Proteins involved in energy metabolism as well as those with binding function were also found in high copy number while proteins annotated with the terms metabolism, transcription, transport, and cellular organization were rare. The barrel-sandwich fold was found to be the structural fold with the highest abundance. Highly abundant proteins are predicted to be less prone to aggregation based on their length, pI values, and occurrence patterns of hydrophobic stretches. We also find that abundant proteins tend to be predominantly essential. Additionally we observe a significant correlation between protein and mRNA abundance in <it>E. coli </it>cells.</p> <p>Conclusion</p> <p>Abundance measurements for more than 1000 <it>E. coli </it>proteins presented in this work represent the most complete study of protein abundance in a bacterial cell so far. We show significant associations between the abundance of a protein and its properties and functions in the cell. In this way, we provide both data and novel insights into the role of protein concentration in this model organism.</p

Protein abundance profiling of the Escherichia coli cytosol

<p>Abstract</p> <p>Background</p> <p>Knowledge about the abundance of molecular components is an important prerequisite for building quantitative predictive models of cellular behavior. Proteins are central components of these models, since they carry out most of the fundamental processes in the cell. Thus far, protein concentrations have been difficult to measure on a large scale, but proteomic technologies have now advanced to a stage where this information becomes readily accessible.</p> <p>Results</p> <p>Here, we describe an experimental scheme to maximize the coverage of proteins identified by mass spectrometry of a complex biological sample. Using a combination of LC-MS/MS approaches with protein and peptide fractionation steps we identified 1103 proteins from the cytosolic fraction of the <it>Escherichia coli </it>strain MC4100. A measure of abundance is presented for each of the identified proteins, based on the recently developed emPAI approach which takes into account the number of sequenced peptides per protein. The values of abundance are within a broad range and accurately reflect independently measured copy numbers per cell.</p> <p>As expected, the most abundant proteins were those involved in protein synthesis, most notably ribosomal proteins. Proteins involved in energy metabolism as well as those with binding function were also found in high copy number while proteins annotated with the terms metabolism, transcription, transport, and cellular organization were rare. The barrel-sandwich fold was found to be the structural fold with the highest abundance. Highly abundant proteins are predicted to be less prone to aggregation based on their length, pI values, and occurrence patterns of hydrophobic stretches. We also find that abundant proteins tend to be predominantly essential. Additionally we observe a significant correlation between protein and mRNA abundance in <it>E. coli </it>cells.</p> <p>Conclusion</p> <p>Abundance measurements for more than 1000 <it>E. coli </it>proteins presented in this work represent the most complete study of protein abundance in a bacterial cell so far. We show significant associations between the abundance of a protein and its properties and functions in the cell. In this way, we provide both data and novel insights into the role of protein concentration in this model organism.</p

Eic1 links Mis18 with the CCAN/Mis6/Ctf19 complex to promote CENP-A assembly.

CENP-A chromatin forms the foundation for kinetochore assembly. Replication-independent incorporation of CENP-A at centromeres depends on its chaperone HJURP(Scm3), and Mis18 in vertebrates and fission yeast. The recruitment of Mis18 and HJURP(Scm3) to centromeres is cell cycle regulated. Vertebrate Mis18 associates with Mis18BP1(KNL2), which is critical for the recruitment of Mis18 and HJURP(Scm3). We identify two novel fission yeast Mis18-interacting proteins (Eic1 and Eic2), components of the Mis18 complex. Eic1 is essential to maintain Cnp1(CENP-A) at centromeres and is crucial for kinetochore integrity; Eic2 is dispensable. Eic1 also associates with Fta7(CENP-Q/Okp1), Cnl2(Nkp2) and Mal2(CENP-O/Mcm21), components of the constitutive CCAN/Mis6/Ctf19 complex. No Mis18BP1(KNL2) orthologue has been identified in fission yeast, consequently it remains unknown how the key Cnp1(CENP-A) loading factor Mis18 is recruited. Our findings suggest that Eic1 serves a function analogous to that of Mis18BP1(KNL2), thus representing the functional counterpart of Mis18BP1(KNL2) in fission yeast that connects with a module within the CCAN/Mis6/Ctf19 complex to allow the temporally regulated recruitment of the Mis18/Scm3(HJURP) Cnp1(CENP-A) loading factors. The novel interactions identified between CENP-A loading factors and the CCAN/Mis6/Ctf19 complex are likely to also contribute to CENP-A maintenance in other organisms.L.S. was supported by an EC FP7 Marie Curie International Incoming Fellowship (PIIF-GA-2010-275280) and an EMBO Long Term Fellowship (ALTF 1491-2010). The Darwin Trust and a Principal's Career Development scholarship supported N.R.T.T. The Wellcome Trust supported the work of R.C.A. (095021 and 065061) and J.R. (084229) along with funding from the European Commission Network of Excellence EpiGeneSys (HEALTH-F4-2010-257082) to R.C.A. The Wellcome Trust Centre for Cell Biology (092076) and mass spectrometry instrumentation (091020) are supported by funding from the Wellcome Trust. R.C.A. is a Wellcome Trust Principal Research Fellow

Optimizing the Parameters Governing the Fragmentation of Cross-Linked Peptides in a Tribrid Mass Spectrometer

We compared the five different ways of fragmentation available on a tribrid mass spectrometer and optimized their collision energies with regard to optimal sequence coverage of cross-linked peptides. We created a library of bis­(sulfosuccinimidyl)­suberate (BS3/DSS) cross-linked precursors, derived from the tryptic digests of three model proteins (Human Serum Albumin, creatine kinase, and myoglobin). This enabled in-depth targeted analysis of the fragmentation behavior of 1065 cross-linked precursors using the five fragmentation techniques: collision-induced dissociation (CID), beam-type CID (HCD), electron-transfer dissociation (ETD), and the combinations ETciD and EThcD. EThcD gave the best sequence coverage for cross-linked <i>m</i>/<i>z</i> species with high charge density, while HCD was optimal for all others. We tested the resulting data-dependent decision tree against collision energy-optimized single methods on two samples of differing complexity (a mix of eight proteins and a highly complex ribosomal cellular fraction). For the high complexity sample the decision tree gave the highest number of identified cross-linked peptide pairs passing a 5% false discovery rate (on average ∼21% more than the second best, HCD). For the medium complexity sample, the higher speed of HCD proved decisive. Currently, acquisition speed plays an important role in allowing the detection of cross-linked peptides against the background of linear peptides. Enrichment of cross-linked peptides will reduce this role and favor methods that provide spectra of higher quality. Data are available via ProteomeXchange with identifier PXD006131

JAMI: a Java library for molecular interactions and data interoperability.

BACKGROUND: A number of different molecular interactions data download formats now exist, designed to allow access to these valuable data by diverse user groups. These formats include the PSI-XML and MITAB standard interchange formats developed by Molecular Interaction workgroup of the HUPO-PSI in addition to other, use-specific downloads produced by other resources. The onus is currently on the user to ensure that a piece of software is capable of read/writing all necessary versions of each format. This problem may increase, as data providers strive to meet ever more sophisticated user demands and data types. RESULTS: A collaboration between EMBL-EBI and the University of Cambridge has produced JAMI, a single library to unify standard molecular interaction data formats such as PSI-MI XML and PSI-MITAB. The JAMI free, open-source library enables the development of molecular interaction computational tools and pipelines without the need to produce different versions of software to read different versions of the data formats. CONCLUSION: Software and tools developed on top of the JAMI framework are able to integrate and support both PSI-MI XML and PSI-MITAB. The use of JAMI avoids the requirement to chain conversions between formats in order to reach a desired output format and prevents code and unit test duplication as the code becomes more modular. JAMI's model interfaces are abstracted from the underlying format, hiding the complexity and requirements of each data format from developers using JAMI as a library