Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam principles)

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed upon two primary needs for the wide use of quality metrics: (i) an evolving list of comprehensive quality metrics and (ii) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in Proteomics, Proteomics Clinical Applications, Journal of Proteome Research, and Molecular and Cellular Proteomics, as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.     

A Bovine PeptideAtlas of milk and mammary gland proteomes

Proteome information resources of farm animals are lagging behind those of the classical model organisms despite their important biological and economic relevance. Here, we present a Bovine PeptideAtlas, representing a first collection of Bos taurus proteome data sets within the PeptideAtlas framework. This database was built primarily as a source of information for designing selected reaction monitoring assays for studying milk production and mammary gland health, but it has an intrinsic general value for the farm animal research community. The Bovine PeptideAtlas comprises 1921 proteins at 1.2% false discovery rate (FDR) and 8559 distinct peptides at 0.29% FDR identified in 107 samples from six tissues. The PeptideAtlas web interface has a rich set of visualization and data exploration tools, enabling users to interactively mine information about individual proteins and peptides, their prototypic features, genome mappings, and supporting spectral evidence.     

From proteomics data representation to public data flow: a report on the HUPO-PSI workshop September 2011, Geneva, Switzerland

The plenary session of the Proteomics Standards Initiative (PSI) of the Human Proteome Organization at the Tenth annual HUPO World Congress updated the delegates on the ongoing activities of this group. The Molecular Interactions workgroup described the success of the PSICQUIC web service, which enables users to access multiple interaction resources with a single query. One user instance is the IMEx Consortium, which uses the service to enable users to access a non-redundant set of protein-protein interaction records. The mass spectrometry data formats, mzML for mass spectrometer output files and mzIdentML for the output of search engines, are now successfully established with increasing numbers of implementations. A format for the output of quantitative proteomics data, mzQuantML, and also TraML, for SRM/MRM transition lists, are both currently nearing completion. The corresponding MIAPE documents are being updated in line with advances in the field, as is the shared controlled vocabulary PSI-MS. In addition, the mzTab format was introduced, as a simpler way to report MS proteomics and metabolomics results. Finally, the ProteomeXchange Consortium, which will supply a single entry point for the submission of MS proteomics data to multiple data resources including PRIDE and PeptideAtlas, is currently being established.     

Cloning, mutagenesis, and characterization of the microalga Parietochloris incisa acetohydroxyacid synthase, and its possible use as an endogenous selection marker

Parietochloris incisa is an oleaginous fresh water green microalga that accumulates an unusually high content of the valuable long-chain polyunsaturated fatty acid (LC-PUFA) arachidonic acid within triacylglycerols in cytoplasmic lipid bodies. Here, we describe cloning and mutagenesis of the P. incisa acetohydroxyacid synthase (PiAHAS) gene for use as an herbicide resistance selection marker for transformation. Use of an endogenous gene circumvents the risks and regulatory difficulties of cultivating antibiotic-resistant organisms. AHAS is present in plants and microorganisms where it catalyzes the first essential step in the synthesis of branched-chain amino acids. It is the target enzyme of the herbicide sulfometuron methyl (SMM), which effectively inhibits growth of bacteria and plants. Several point mutations of AHAS are known to confer herbicide resistance. We cloned the cDNA that encodes PiAHAS and introduced a W605S point mutation (PimAHAS). Catalytic activity and herbicide resistance of the wild-type and mutant proteins were characterized in the AHAS-deficient E. coli, BUM1 strain. Cloned PiAHAS wild-type and mutant genes complemented AHAS-deficient bacterial growth. Furthermore, bacteria expressing the mutant PiAHAS exhibited high resistance to SMM. Purified PiAHAS wild-type and mutant proteins were assayed for enzymatic activity and herbicide resistance. The W605S mutation was shown to cause a twofold decrease in enzymatic activity and in affinity for the Pyruvate substrate. However, the mutant exhibited 7 orders of magnitude higher resistance to the SMM herbicide than that of the wild type.     

Kinetics and mechanics of two-dimensional interactions between T cell receptors and different activating ligands

Adaptive immune responses are driven by interactions between T cell antigen receptors (TCRs) and complexes of peptide antigens (p) bound to Major Histocompatibility Complex proteins (MHC) on the surface of antigen-presenting cells. Many experiments support the hypothesis that T cell response is quantitatively and qualitatively dependent on the so-called strength of TCR/pMHC association. Most available data are correlations between binding parameters measured in solution (three-dimensional) and pMHC activation potency, suggesting that full lymphocyte activation required a minimal lifetime for TCR/pMHC interaction. However, recent reports suggest important discrepancies between the binding properties of ligand-receptor couples measured in solution (three-dimensional) and those measured using surface-bound molecules (two-dimensional). Other reports suggest that bond mechanical strength may be important in addition to kinetic parameters. Here, we used a laminar flow chamber to monitor at the single molecule level the two-dimensional interaction between a recombinant human TCR and eight pMHCs with variable potency. We found that 1), two-dimensional dissociation rates were comparable to three-dimensional parameters previously obtained with the same molecules; 2), no significant correlation was found between association rates and activating potency of pMHCs; 3), bond mechanical strength was partly independent of bond lifetime; and 4), a suitable combination of bond lifetime and bond strength displayed optimal correlation with activation efficiency. These results suggest possible refinements of contemporary models of signal generation by T cell receptors. In conclusion, we reported, for the first time to our knowledge, the two-dimensional binding properties of eight TCR/pMHC couples in a cell-free system with single bond resolution.     

Mechanical modulation of receptor-ligand interactions at cell-cell interfaces

Cell surface receptors have been extensively studied because they initiate and regulate signal transduction cascades leading to a variety of functional cellular outcomes. An important class of immune receptors (e.g., T-cell antigen receptors) whose ligands are anchored to the surfaces of other cells remain poorly understood. The mechanism by which ligand binding initiates receptor phosphorylation, a process termed “receptor triggering”, remains controversial. Recently, direct measurements of the (two-dimensional) receptor-ligand complex lifetimes at cell-cell interface were found to be smaller than (three-dimensional) lifetimes in solution but the underlying mechanism is unknown. At the cell-cell interface, the receptor-ligand complex spans a short intermembrane distance (15 nm) compared to long surface molecules (LSMs) whose ectodomains span >40 nm and these LSMs include phosphatases (e.g., CD45) that dephosphorylate the receptor. It has been proposed that size-based segregation of LSMs from a receptor-ligand complex is a mechanism of receptor triggering but it is unclear whether the mechanochemistry supports such small-scale segregation. Here we present a nanometer-scale mathematical model that couples membrane elasticity with the compressional stiffness and lateral mobility of LSMs. We find robust supradiffusive segregation of LSMs from a single receptor-ligand complex. The model predicts that LSM redistribution will result in a time-dependent tension on the complex leading to a decreased two-dimensional lifetime. Interestingly, the model predicts a nonlinear relationship between the three- and two-dimensional lifetimes, which can enhance the ability of receptors to discriminate between similar ligands.     

Dynamical compensation in physiological circuits

Biological systems can maintain constant steady‐state output despite variation in biochemical parameters, a property known as exact adaptation. Exact adaptation is achieved using integral feedback, an engineering strategy that ensures that the output of a system robustly tracks its desired value. However, it is unclear how physiological circuits also keep their output dynamics precise—including the amplitude and response time to a changing input. Such robustness is crucial for endocrine and neuronal homeostatic circuits because they need to provide a precise dynamic response in the face of wide variation in the physiological parameters of their target tissues; how such circuits compensate their dynamics for unavoidable natural fluctuations in parameters is unknown. Here, we present a design principle that provides the desired robustness, which we call dynamical compensation (DC). We present a class of circuits that show DC by means of a nonlinear feedback loop in which the regulated variable controls the functional mass of the controlling endocrine or neuronal tissue. This mechanism applies to the control of blood glucose by insulin and explains several experimental observations on insulin resistance. We provide evidence that this mechanism may also explain compensation and organ size control in other physiological circuits.