PPKs mediate direct signal transfer from phytochrome photoreceptors to transcription factor PIF3.

Upon light-induced nuclear translocation, phytochrome (phy) sensory photoreceptors interact with, and induce rapid phosphorylation and consequent ubiquitin-mediated degradation of, transcription factors, called PIFs, thereby regulating target gene expression and plant development. Nevertheless, the biochemical mechanism of phy-induced PIF phosphorylation has remained ill-defined. Here we identify a family of nuclear protein kinases, designated Photoregulatory Protein Kinases (PPK1-4; formerly called MUT9-Like Kinases (MLKs)), that interact with PIF3 and phyB in a light-induced manner in vivo. Genetic analyses demonstrate that the PPKs are collectively necessary for the normal light-induced phosphorylation and degradation of PIF3. PPK1 directly phosphorylates PIF3 in vitro, with a phosphosite pattern that strongly mimics the light-induced pattern in vivo. These data establish that the PPKs are directly involved in catalysing the photoactivated-phy-induced phosphorylation of PIF3 in vivo, and thereby are critical components of a transcriptionally centred signalling hub that pleiotropically regulates plant growth and development in response to multiple signalling pathways.

Proteomic analysis reveals O-GlcNAc modification on proteins with key regulatory functions in Arabidopsis.

Genetic studies have shown essential functions of O-linked N-acetylglucosamine (O-GlcNAc) modification in plants. However, the proteins and sites subject to this posttranslational modification are largely unknown. Here, we report a large-scale proteomic identification of O-GlcNAc-modified proteins and sites in the model plant Arabidopsis thaliana Using lectin weak affinity chromatography to enrich modified peptides, followed by mass spectrometry, we identified 971 O-GlcNAc-modified peptides belonging to 262 proteins. The modified proteins are involved in cellular regulatory processes, including transcription, translation, epigenetic gene regulation, and signal transduction. Many proteins have functions in developmental and physiological processes specific to plants, such as hormone responses and flower development. Mass spectrometric analysis of phosphopeptides from the same samples showed that a large number of peptides could be modified by either O-GlcNAcylation or phosphorylation, but cooccurrence of the two modifications in the same peptide molecule was rare. Our study generates a snapshot of the O-GlcNAc modification landscape in plants, indicating functions in many cellular regulation pathways and providing a powerful resource for further dissecting these functions at the molecular level.

The chromosome-centric human proteome project: a call to action.

The grand vision of the human proteome project (HPP) is moving closer to reality with the recent announcement by HUPO of the creation of the HPP consortium in charge of the development of a two-part HPP, one focused on the description of proteomes of biological samples or related to diseases (B/D-HPP) and the other dedicated to a systematic description of proteins as gene products encoded in the human genome (the C-HPP). This new initiative of HUPO seeks to identify and characterize at least one representative protein from every gene, create a protein distribution atlas and a protein pathway or network map. This vision for proteomics can be the roadmap of biological and clinical research for years to come if it delivers on its promises. The Industrial Advisory Board (IAB) to HUPO shares the visions of C-HPP. The IAB will support and critically accompany the overall project goals and the definitions of the critical milestones. The member companies are in a unique position to develop hardware and software, reagents and standards, procedures, and workflows to ensure a reliable source of tools available to the proteomics community worldwide. In collaboration with academia, the IAB member companies can and must develop the tools to reach the ambitious project goals. We offer to partner with and challenge the academic groups leading the C-HPP to define both ambitious and obtainable goals and milestones to make the C-HPP a real and trusted resource for future biology.

Charger: combination of signal processing and statistical learning algorithms for precursor charge-state determination from electron-transfer dissociation spectra.

Tandem mass spectrometry in combination with liquid chromatography has emerged as a powerful tool for characterization of complex protein mixtures in a high-throughput manner. One of the bioinformatics challenges posed by the mass spectral data analysis is the determination of precursor charge when unit mass resolution is used for detecting fragment ions. The charge-state information is used to filter database sequences before they are correlated to experimental data. In the absence of the accurate charge state, several charge states are assumed. This dramatically increases database search times. To address this problem, we have developed an approach for charge-state determination of peptides from their tandem mass spectra obtained in fragmentations via electron-transfer dissociation (ETD) reactions. Protein analysis by ETD is thought to enhance the range of amino acid sequences that can be analyzed by mass spectrometry-based proteomics. One example is the improved capability to characterize phosphorylated peptides. Our approach to charge-state determination uses a combination of signal processing and statistical machine learning. The signal processing employs correlation and convolution analyses to determine precursor masses and charge states of peptides. We discuss applicability of these methods to spectra of different charge states. We note that in our applications correlation analysis outperforms the convolution in determining peptide charge states. The correlation analysis is best suited for spectra with prevalence of complementary ions. It is highly specific but is dependent on quality of spectra. The linear discriminant analysis (LDA) approach uses a number of other spectral features to predict charge states. We train LDA classifier on a set of manually curated spectral data from a mixture of proteins of known identity. There are over 5000 spectra in the training set. A number of features, pertinent to spectra of peptides obtained via ETD reactions, have been used in the training. The loading coefficients of LDA indicate the relative importance of different features for charge-state determination. We have applied our model to a test data set generated from a mixture of 49 proteins. We search the spectra with and without use of the charge-state determination. The charge-state determination helps to significantly save the database search times. We discuss the cost associated with the possible misclassification of charge states.

On-line LC-MS approach combining collision-induced dissociation (CID), electron-transfer dissociation (ETD), and CID of an isolated charge-reduced species for the trace-level characterization of proteins with post-translational modifications.

We have expanded our recent on-line LC-MS platform for large peptide analysis to combine collision-induced dissociation (CID), electron-transfer dissociation (ETD), and CID of an isolated charge-reduced (CRCID) species derived from ETD to determine sites of phosphorylation and glycosylation modifications, as well as the sequence of large peptide fragments (i.e., 2000-10,000 Da) from complex proteins, such as beta-casein, epidermal growth factor receptor (EGFR), and tissue plasminogen activator (t-PA) at the low femtomol level. The incorporation of an additional CID activation step for a charge-reduced species, isolated from ETD fragment ions, improved ETD fragmentation when precursor ions with high m/z (approximately >1000) were automatically selected for fragmentation. Specifically, the identification of the exact phosphorylation sites was strengthened by the extensive coverage of the peptide sequence with a near-continuous product ion series. The identification of N-linked glycosylation sites in EGFR and an O-linked glycosylation site in t-PA were also improved through the enhanced identification of the peptide backbone sequence of the glycosylated precursors. The new strategy is a good starting survey scan to characterize enzymatic peptide mixtures over a broad range of masses using LC-MS with data-dependent acquisition, as the three activation steps can provide complementary information to each other. In general, large peptides can be extensively characterized by the ETD and CRCID steps, including sites of modification from the generated, near-continuous product ion series, supplemented by the CID-MS2 step. At the same time, small peptides (e.g.,

ChromAlign: A two-step algorithmic procedure for time alignment of three-dimensional LC-MS chromatographic surfaces.

We present an algorithmic approach to align three-dimensional chromatographic surfaces of LC-MS data of complex mixture samples. The approach consists of two steps. In the first step, we prealign chromatographic profiles: two-dimensional projections of chromatographic surfaces. This is accomplished by correlation analysis using fast Fourier transforms. In this step, a temporal offset that maximizes the overlap and dot product between two chromatographic profiles is determined. In the second step, the algorithm generates correlation matrix elements between full mass scans of the reference and sample chromatographic surfaces. The temporal offset from the first step indicates a range of the mass scans that are possibly correlated, then the correlation matrix is calculated only for these mass scans. The correlation matrix carries information on highly correlated scans, but it does not itself determine the scan or time alignment. Alignment is determined as a path in the correlation matrix that maximizes the sum of the correlation matrix elements. The computational complexity of the optimal path generation problem is reduced by the use of dynamic programming. The program produces time-aligned surfaces. The use of the temporal offset from the first step in the second step reduces the computation time for generating the correlation matrix and speeds up the process. The algorithm has been implemented in a program, ChromAlign, developed in C++ language for the .NET2 environment in WINDOWS XP. In this work, we demonstrate the applications of ChromAlign to alignment of LC-MS surfaces of several datasets: a mixture of known proteins, samples from digests of surface proteins of T-cells, and samples prepared from digests of cerebrospinal fluid. ChromAlign accurately aligns the LC-MS surfaces we studied. In these examples, we discuss various aspects of the alignment by ChromAlign, such as constant time axis shifts and warping of chromatographic surfaces.

Cerebrospinal fluid sodium increases in migraine.

BACKGROUND: Pharmaceuticals with calcium- or sodium-channel-blocking activity have proven useful for migraine prophylaxis, and calcium channel, sodium transporter, and sodium channel gene mutations have been found in familial hemiplegic migraine. However, it is not known whether calcium or sodium homeostasis is altered in migraine. OBJECTIVE: To compare levels of sodium, calcium, potassium, and magnesium in cerebrospinal fluid (CSF) and blood plasma between migraineurs and controls. METHODS: We recruited 20 migraineurs without aura and 11 controls prospectively, and studied migraineurs in sick (MH(+)) and well (MH(-)) states. We collected lumbar CSF and venous blood plasma, quantified elements with ion-selective electrodes or colorimetry, and determined osmolality by depression of freezing point. We compared levels of Na(+), Ca(2+), K(+), and Mg among and also within subjects who were studied in both MH(+) and MH(-) states. RESULTS: Mean CSF Na(+) levels were increased by 3 mmol/L in MH(+) compared with MH(-) and by 4 mmol/L compared to controls (P < 0.005). In 4 subjects who were sampled in both MH(+) and MH(-) states, mean CSF Na(+) concentration increased by 2 mmol/L in the MH(+) state compared with the MH(-) state (P < 0.05). Simultaneous plasma Na(+) levels did not differ among the 3 clinical groups, nor did osmolality, total Ca and Ca(2+), K(+), and total Mg levels in CSF. CONCLUSIONS: Compared to both controls and the MH(-) state, CSF Na(+) concentration increased in MH(+) independently from other clinical or pharmacological fluctuations, CSF concentrations of Ca(2+), Mg, and K(+), and blood plasma Na(+) levels. These results implicate a deviation of Na(+) homeostasis in migraine. The modestly elevated extracellular Na(+) in MH(+) may cause the neural changes that underlie clinical features of migraine.

Enhanced sequence coverage of proteins in human cerebrospinal fluid using multiple enzymatic digestion and linear ion trap LC-MS/MS.

The cerebrospinal fluid (CSF) provides a ready access into the health state of the central nervous system, and alterations in some CSF proteins have been documented in brain disease. However, the complete variety of proteins is not known and methods to identify protein components are still being developed. The goal of this study was to examine the sequence coverage obtained from human CSF digests produced with different proteases. Enzymatic digests of CSF proteins were obtained with arginine-C endopeptidase (ArgC), glutamic acid endopeptidase (GluC), chymotrypsin, trypsin and their combinations, and then examined using reverse phase chromatography and a Finnigan LTQ linear ion trap mass spectrometer. Peptide sequences were identified with BioWorks 3.1 and sequence coverage calculated for the 38 most confidently identified proteins. Trypsin and GluC yielded greater coverage than chymotrypsin, while ArgC had the least sequence coverage. Protein sequence coverage was affected only slightly over four orders of magnitude dynamic range of abundance. Combining the peptides derived from different proteases further increased the coverage. Maximal sequence coverage was achieved by combining digest results from both GluC and trypsin. These results have implications for future studies to identify CSF proteins and their post-translational modifications.

Analysis of the adenovirus type 5 proteome by liquid chromatography and tandem mass spectrometry methods.

We compared detection sensitivity and protein sequence coverage of the adenovirus type 5 proteome achievable by liquid chromatography and tandem mass spectroscopy (LC/MS/MS) using three sample preparation and clean up methods. Tryptic digestion was performed on either purified viral proteins or whole virus, and followed by shotgun sequencing using tandem mass spectrometry for peptide identification. We used a recombinant adenovirus type 5 as a test system. The methods included separation of adenoviral proteins by reversed-phase high-performance liquid chromatography followed by tryptic digestion and analysis by LC/MS/MS. Alternatively, the purified whole virus was digested with trypsin and the peptides separated either by one-dimensional (reversed-phase) or by two-dimensional (cation exchange and reversed-phase) chromatography and analyzed by tandem mass spectrometry. A total of 11 protein species were identified from 154 peptides. All of the major viral proteins were found. In addition, two minor proteins, the 23 kDa viral protease and the late L1 protein, were identified for the first time by chromatography based assays. The 23 kDa viral protease, present at only 10 copies per virus, and representing 0.2% of the protein content of the virus, was detected by the 2D LC/MS/MS analysis of the whole virus digest from a sample containing only 70 fmols of the protein. This demonstrates the high sensitivity and selectivity of the method. The 2D LC/MS/MS analysis of the whole virus digest was also able to detect all viral proteins with copy numbers at or above 10/virus particle, with broad coverage of the amino acid sequences. Coverage ranged from 2 to 54%, a majority between 20 and 35%, suggesting the possibility of using this analysis to assess the purity of the virus preparations. This broad coverage may also provide a useful approach to identify posttranslational modifications on the structural proteins of the adenovirus.