A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes.

Cross-talk between genes, transcripts, and proteins is the key to cellular responses; hence, analysis of molecular levels as distinct entities is slowly being extended to integrative studies to enhance the understanding of molecular dynamics within cells. Current tools for the visualization and integration of proteomics with other omics datasets are inadequate for large-scale studies. Furthermore, they only capture basic sequence identify, discarding post-translational modifications and quantitation. To address these issues, we developed PoGo to map peptides with associated post-translational modifications and quantification to reference genome annotation. In addition, the tool was developed to enable the mapping of peptides identified from customized sequence databases incorporating single amino acid variants. While PoGo is a command line tool, the graphical interface PoGoGUI enables non-bioinformatics researchers to easily map peptides to 25 species supported by Ensembl genome annotation. The generated output borrows file formats from the genomics field and, therefore, visualization is supported in most genome browsers. For large-scale studies, PoGo is supported by TrackHubGenerator to create web-accessible repositories of data mapped to genomes that also enable an easy sharing of proteogenomics data. With little effort, this tool can map millions of peptides to reference genomes within only a few minutes, outperforming other available sequence-identity based tools. This protocol demonstrates the best approaches for proteogenomics mapping through PoGo with publicly available datasets of quantitative and phosphoproteomics, as well as large-scale studies.

Diaminothiazoles modify Tau phosphorylation and improve the tauopathy in mouse models.

Although Tau accumulation is a feature of several neurodegenerative conditions, treatment options for these conditions are nonexistent. Targeting Tau kinases represents a potential therapeutic approach. Small molecules in the diaminothiazole class are potent Tau kinase inhibitors that target CDK5 and GSK3ß. Lead compounds from the series have IC50 values toward CDK5/p25 and GSK3ß in the low nanomolar range and no observed toxicity in the therapeutic dose range. Neuronal protective effects and decreased PHF-1 immunoreactivity were observed in two animal models, 3×Tg-AD and CK-p25. Treatment nearly eliminated Sarkosyl-insoluble Tau with the most prominent effect on the phosphorylation at Ser-404. Treatment also induced the recovery of memory in a fear conditioning assay. Given the contribution of both CDK5/p25 and GSK3ß to Tau phosphorylation, effective treatment of tauopathies may require dual kinase targeting.

Pleiotropic effects of miR-183~96~182 converge to regulate cell survival, proliferation and migration in medulloblastoma.

Medulloblastomas are the most common malignant brain tumors in children. Several large-scale genomic studies have detailed their heterogeneity, defining multiple subtypes with unique molecular profiles and clinical behavior. Increased expression of the miR-183~96~182 cluster of microRNAs has been noted in several subgroups, including the most clinically aggressive subgroup associated with genetic amplification of MYC. To understand the contribution of miR-183~96~182 to the pathogenesis of this aggressive subtype of medulloblastoma, we analyzed global gene expression and proteomic changes that occur upon modulation of miRNAs in this cluster individually and as a group in MYC-amplified medulloblastoma cells. Knockdown of the full miR-183~96~182 cluster results in enrichment of genes associated with apoptosis and dysregulation of the PI3K/AKT/mTOR signaling axis. Conversely, there is a relative enrichment of pathways associated with migration, metastasis and epithelial to mesenchymal transition, as well as pathways associated with dysfunction of DNA repair in cells with preserved miR-183 cluster expression. Immunocytochemistry and FACS analysis confirm induction of apoptosis upon knockdown of the miR-183 cluster. Importantly, cell-based migration and invasion assays verify the positive regulation of cell motility/migration by the miR-183 cluster, which is largely mediated by miR-182. We show that the effects on cell migration induced by the miR-183 cluster are coupled to the PI3K/AKT/mTOR pathway through differential regulation of AKT1 and AKT2 isoforms. Furthermore, we show that rapamycin inhibits cell motility/migration in medulloblastoma cells and phenocopies miR-183 cluster knockdown. Thus, the miR-183 cluster regulates multiple biological programs that converge to support the maintenance and metastatic potential of medulloblastoma.

mz5: space- and time-efficient storage of mass spectrometry data sets.

Across a host of MS-driven-omics fields, researchers witness the acquisition of ever increasing amounts of high throughput MS data and face the need for their compact yet efficiently accessible storage. Addressing the need for an open data exchange format, the Proteomics Standards Initiative and the Seattle Proteome Center at the Institute for Systems Biology independently developed the mzData and mzXML formats, respectively. In a subsequent joint effort, they defined an ontology and associated controlled vocabulary that specifies the contents of MS data files, implemented as the newer mzML format. All three formats are based on XML and are thus not particularly efficient in either storage space requirements or read/write speed. This contribution introduces mz5, a complete reimplementation of the mzML ontology that is based on the efficient, industrial strength storage backend HDF5. Compared with the current mzML standard, this strategy yields an average file size reduction to ∼54% and increases linear read and write speeds ∼3-4-fold. The format is implemented as part of the ProteoWizard project and is available under a permissive Apache license. Additional information and download links are available from http://software.steenlab.org/mz5.

Interaction of survival of motor neuron (SMN) and HuD proteins with mRNA cpg15 rescues motor neuron axonal deficits.

Spinal muscular atrophy (SMA), caused by the deletion of the SMN1 gene, is the leading genetic cause of infant mortality. SMN protein is present at high levels in both axons and growth cones, and loss of its function disrupts axonal extension and pathfinding. SMN is known to associate with the RNA-binding protein hnRNP-R, and together they are responsible for the transport and/or local translation of ß-actin mRNA in the growth cones of motor neurons. However, the full complement of SMN-interacting proteins in neurons remains unknown. Here we used mass spectrometry to identify HuD as a novel neuronal SMN-interacting partner. HuD is a neuron-specific RNA-binding protein that interacts with mRNAs, including candidate plasticity-related gene 15 (cpg15). We show that SMN and HuD form a complex in spinal motor axons, and that both interact with cpg15 mRNA in neurons. CPG15 is highly expressed in the developing ventral spinal cord and can promote motor axon branching and neuromuscular synapse formation, suggesting a crucial role in the development of motor axons and neuromuscular junctions. Cpg15 mRNA previously has been shown to localize into axonal processes. Here we show that SMN deficiency reduces cpg15 mRNA levels in neurons, and, more importantly, cpg15 overexpression partially rescues the SMN-deficiency phenotype in zebrafish. Our results provide insight into the function of SMN protein in axons and also identify potential targets for the study of mechanisms that lead to the SMA pathology and related neuromuscular diseases.

libfbi: a C++ implementation for fast box intersection and application to sparse mass spectrometry data.

MOTIVATION: Algorithms for sparse data require fast search and subset selection capabilities for the determination of point neighborhoods. A natural data representation for such cases are space partitioning data structures. However, the associated range queries assume noise-free observations and cannot take into account observation-specific uncertainty estimates that are present in e.g. modern mass spectrometry data. In order to accommodate the inhomogeneous noise characteristics of sparse real-world datasets, point queries need to be reformulated in terms of box intersection queries, where box sizes correspond to uncertainty regions for each observation. RESULTS: This contribution introduces libfbi, a standard C++, header-only template implementation for fast box intersection in an arbitrary number of dimensions, with arbitrary data types in each dimension. The implementation is applied to a data aggregation task on state-of-the-art liquid chromatography/mass spectrometry data, where it shows excellent run time properties. AVAILABILITY: The library is available under an MIT license and can be downloaded from http://software.steenlab.org/libfbi. CONTACT: marc.kirchner@childrens.harvard.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Phosphoproteomics.

Current analytical protein methods show phosphorylation to be the most ubiquitous, evolutionary conserved post-translational modification Post-Translational Modification (PTM). The reversible and transient nature of protein phosphorylation allows signal transduction pathways to carry out diverse cellular functions. From bacteria to humans, phosphorylation serves to modify protein function by altering protein stability, cellular location, substrate affinity, complex formation, and activity; thus allowing essential events such as cell cycle and growth to occur at precise times and locations. Phosphorylation controls a variety of events at many biological levels including: housekeeping activities controlled by single cells such as DNA transcription, cell-cycle regulation, and energy metabolism; and cellular processes that involve signaling between cells or the environment including such as neuronal migration and immune system recognition. This review summarizes state-of-the-art proteomics technologies available to study phosphorylation in biological systems. We highlight the tremendous steps the field has made in the last 5 years which allow quantitative global analyses while pointing out caveats in experimentation.

Estimating the confidence of peptide identifications without decoy databases.

Using decoy databases to compute the confidence of peptide identifications has become the standard procedure for mass spectrometry driven proteomics. While decoy databases have numerous advantages, they double the run time and are not applicable to all peptide identification problems such as error-tolerant or de novo searches or the large-scale identification of cross-linked peptides. Instead, we propose a fast, simple and robust mixture modeling approach to estimate the confidence of peptide identifications without the need for decoy database searches, which automatically checks whether its underlying assumptions are fulfilled. This approach is then evaluated on 41 LC/MS data sets of varying complexity and origin. The results are very similar to those of the decoy database strategy at a negligible computational cost. Our approach is applicable not only to standard protein identification workflows, but also to proteomics problems for which meaningful decoy databases cannot be constructed.

Deuteration distribution estimation with improved sequence coverage for HX/MS experiments.

MOTIVATION: Time-resolved hydrogen exchange (HX) followed by mass spectrometry (MS) is a key technology for studying protein structure, dynamics and interactions. HX experiments deliver a time-dependent distribution of deuteration levels of peptide sequences of the protein of interest. The robust and complete estimation of this distribution for as many peptide fragments as possible is instrumental to understanding dynamic protein-level HX behavior. Currently, this data interpretation step still is a bottleneck in the overall HX/MS workflow. RESULTS: We propose HeXicon, a novel algorithmic workflow for automatic deuteration distribution estimation at increased sequence coverage. Based on an L(1)-regularized feature extraction routine, HeXicon extracts the full deuteration distribution, which allows insight into possible bimodal exchange behavior of proteins, rather than just an average deuteration for each time point. Further, it is capable of addressing ill-posed estimation problems, yielding sparse and physically reasonable results. HeXicon makes use of existing peptide sequence information, which is augmented by an inferred list of peptide candidates derived from a known protein sequence. In conjunction with a supervised classification procedure that balances sensitivity and specificity, HeXicon can deliver results with increased sequence coverage. AVAILABILITY: The entire HeXicon workflow has been implemented in C++ and includes a graphical user interface. It is available at http://hci.iwr.uni-heidelberg.de/software.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MGFp: an open Mascot Generic Format parser library implementation.

Despite the efforts of the mass spectrometry (MS) community to migrate data representation toward modern file formats, legacy text formats still play an important role in MS data processing workflows. We provide a formal grammar and a portable, efficient C++ implementation for a Mascot Generic Format (MGF) parser. Software and technical documentation are available from http://software.steenlab.org/mgfp/.

Computational protein profile similarity screening for quantitative mass spectrometry experiments.

MOTIVATION: The qualitative and quantitative characterization of protein abundance profiles over a series of time points or a set of environmental conditions is becoming increasingly important. Using isobaric mass tagging experiments, mass spectrometry-based quantitative proteomics deliver accurate peptide abundance profiles for relative quantitation. Associated data analysis workflows need to provide tailored statistical treatment that (i) takes the correlation structure of the normalized peptide abundance profiles into account and (ii) allows inference of protein-level similarity. We introduce a suitable distance measure for relative abundance profiles, derive a statistical test for equality and propose a protein-level representation of peptide-level measurements. This yields a workflow that delivers a similarity ranking of protein abundance profiles with respect to a defined reference. All procedures have in common that they operate based on the true correlation structure that underlies the measurements. This optimizes power and delivers more intuitive and efficient results than existing methods that do not take these circumstances into account. RESULTS: We use protein profile similarity screening to identify candidate proteins whose abundances are post-transcriptionally controlled by the Anaphase Promoting Complex/Cyclosome (APC/C), a specific E3 ubiquitin ligase that is a master regulator of the cell cycle. Results are compared with an established protein correlation profiling method. The proposed procedure yields a 50.9-fold enrichment of co-regulated protein candidates and a 2.5-fold improvement over the previous method. AVAILABILITY: A MATLAB toolbox is available from http://hci.iwr.uni-heidelberg.de/mip/proteomics.

When less can yield more - Computational preprocessing of MS/MS spectra for peptide identification.

The effectiveness of database search algorithms, such as Mascot, Sequest and ProteinPilot is limited by the quality of the input spectra: spurious peaks in MS/MS spectra can jeopardize the correct identification of peptides or reduce their score significantly. Consequently, an efficient preprocessing of MS/MS spectra can increase the sensitivity of peptide identification at reduced file sizes and run time without compromising its specificity. We investigate the performance of 25 MS/MS preprocessing methods on various data sets and make software for improved preprocessing of mgf/dta-files freely available from http://hci.iwr.uni-heidelberg.de/mip/proteomics or http://www.childrenshospital.org/research/steenlab.

The mechanism and pattern of yolk consumption provide insight into embryonic nutrition in Xenopus.

Little is known about how metabolism changes during development. For most animal embryos, yolk protein is a principal source of nutrition, particularly of essential amino acids. Within eggs, yolk is stored inside large organelles called yolk platelets (YPs). We have gained insight into embryonic nutrition in the African clawed frog Xenopus laevis by studying YPs. Amphibians follow the ancestral pattern in which all embryonic cells inherit YPs from the egg cytoplasm. These YPs are consumed intracellularly at some point during embryogenesis, but it was not known when, where or how yolk consumption occurs. We have identified the novel yolk protein Seryp by biochemical and mass spectrometric analyses of purified YPs. Within individual YPs, Seryp is degraded to completion earlier than the major yolk proteins, thereby providing a molecular marker for YPs engaged in yolk proteolysis. We demonstrate that yolk proteolysis is a quantal process in which a subset of dormant YPs within embryonic cells are reincorporated into the endocytic system and become terminal degradative compartments. Yolk consumption is amongst the earliest aspects of differentiation. The rate of yolk consumption is also highly tissue specific, suggesting that nutrition in early amphibian embryos is tissue autonomous. But yolk consumption does not appear to be triggered by embryonic cells declining to a critically small size. Frog embryos offer a promising platform for the in vivo analysis of metabolism.

NITPICK: peak identification for mass spectrometry data.

BACKGROUND: The reliable extraction of features from mass spectra is a fundamental step in the automated analysis of proteomic mass spectrometry (MS) experiments. RESULTS: This contribution proposes a sparse template regression approach to peak picking called NITPICK. NITPICK is a Non-greedy, Iterative Template-based peak PICKer that deconvolves complex overlapping isotope distributions in multicomponent mass spectra. NITPICK is based on fractional averaging, a novel extension to Senko's well-known averaging model, and on a modified version of sparse, non-negative least angle regression, for which a suitable, statistically motivated early stopping criterion has been derived. The strength of NITPICK is the deconvolution of overlapping mixture mass spectra. CONCLUSION: Extensive comparative evaluation has been carried out and results are provided for simulated and real-world data sets. NITPICK outperforms pepex, to date the only alternate, publicly available, non-greedy feature extraction routine. NITPICK is available as software package for the R programming language and can be downloaded from (http://hci.iwr.uni-heidelberg.de/mip/proteomics/).

Different phosphorylation states of the anaphase promoting complex in response to antimitotic drugs: a quantitative proteomic analysis.

The anaphase promoting complex (APC) controls the degradation of proteins during exit from mitosis and entry into S-phase. The activity of the APC is regulated by phosphorylation during mitosis. Because the phosphorylation pattern provides insights into the complexity of regulation of the APC, we studied in detail the phosphorylation patterns at a single mitotic state of arrest generated by various antimitotic drugs. We examined the phosphorylation patterns of the APC in HeLa S3 cells after they were arrested in prometaphase with taxol, nocodazole, vincristine, or monastrol. There were 71 phosphorylation sites on nine of the APC subunits. Despite the common state of arrest, the various antimitotic drug treatments resulted in differences in the phosphorylation patterns and phosphorylation stoichiometries. The relative phosphorylation stoichiometries were determined by using a method adapted from the isotope-free quantitation of the extent of modification (iQEM). We could show that during drug arrest the phosphorylation state of the APC changes, indicating that the mitotic arrest is not a static condition. We discuss these findings in terms of the variable efficacy of antimitotic drugs in cancer chemotherapy.

Temporal variations of the postnatal rat urinary proteome as a reflection of systemic maturation.

The rat kidney matures during the first 2 wk of life, suggesting that temporal variations in the urinary proteome may occur during this period. We describe the urine proteome during postnatal development in the rat and demonstrate specific proteomic changes corresponding to developmental milestones. Urine was collected from 30 rats at five postnatal (P) days of life (P1, P3, P7, P14, and >P30) by bladder aspiration. The proteome was assessed by nano-ESI-LC-MS/MS. For identification, we used stringent criteria to provide a 1% false positive rate at the peptide level. The proteins in common at each time interval decreased during postnatal maturation. When comparing all five developmental times, six proteins were ubiquitously present. We detected 14 proteins involved with cellular adhesion, structure, or proliferation and differentiation only during neonatal development. Additionally, 30 proteins were specific to adults, of which 13 originated from the prostate or seminal vesicle. This is the first MS characterization of the normal urinary proteome in early postnatal rodent development that demonstrates distinct differences correlating with different stages of tissue maturation. Further characterization of the normal urinary proteome may provide the basis for identification of urinary biomarkers of diseases of the urinary tract.

Global methods for protein glycosylation analysis by mass spectrometry.

Mass spectrometry has been an analytical tool of choice for glycosylation analysis of individual proteins. Over the last 5 years several previously and newly developed mass spectrometry methods have been extended to global glycoprotein studies. In this review we discuss the importance of these global studies and the advances that have been made in enrichment analyses and fragmentation methods. We also briefly describe relevant sample preparation methods that have been used for the analysis of a single glycoprotein that could be extrapolated to global studies. Finally this review covers aspects of improvements and advances on the instrument front which are important to future global glycoproteomic studies.

Brain-specific phosphorylation of MeCP2 regulates activity-dependent Bdnf transcription, dendritic growth, and spine maturation.

Mutations or duplications in MECP2 cause Rett and Rett-like syndromes, neurodevelopmental disorders characterized by mental retardation, motor dysfunction, and autistic behaviors. MeCP2 is expressed in many mammalian tissues and functions as a global repressor of transcription; however, the molecular mechanisms by which MeCP2 dysfunction leads to the neural-specific phenotypes of RTT remain poorly understood. Here, we show that neuronal activity and subsequent calcium influx trigger the de novo phosphorylation of MeCP2 at serine 421 (S421) by a CaMKII-dependent mechanism. MeCP2 S421 phosphorylation is induced selectively in the brain in response to physiological stimuli. Significantly, we find that S421 phosphorylation controls the ability of MeCP2 to regulate dendritic patterning, spine morphogenesis, and the activity-dependent induction of Bdnf transcription. These findings suggest that, by triggering MeCP2 phosphorylation, neuronal activity regulates a program of gene expression that mediates nervous system maturation and that disruption of this process in individuals with mutations in MeCP2 may underlie the neural-specific pathology of RTT.