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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.

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 informarion 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 electrontransfer 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.

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.

Laser beam scanning driven by an acousto-optical deflector (AOD) is presented for multimicrochannel laser-induced fluorescence (LIF) detection during microchip-based electrophoresis. While fast laser beam scanning for LIF detection on capillary or microchannel arrays can been achieved with galvanometric scanning or a translating stage, it can also be accomplished by using acoustic waves to deflect the laser beam in a manner that is dependent on the acoustic frequency. AOD scanning differs from other approaches in that no moving parts are required, and the scan frequency is faster than conventional approaches. Using a digital/analog (D/A) converter to provide addressing voltages to a voltage/frequency converter, rapidly changing the frequency input to the AOD allows the laser beam to be addressed accurately on a microchip. With the ability to change the frequency on the nanosecond time scale, scanning rates as high as 30 Hz for Windows-based LabView programming are possible, with much faster scan rates achievable if a microprocessor-embedded system is utilized. In addition to spatial control, temporal control is easily attainable via raster scanning or random addressing, allowing for the scanning process to be self-aligning. Since the D/A output voltages drive the scanning of the laser beam over all channels, the software can define addressing voltages corresponding to the microchannel centers and, subsequently, fluorescence data can be collected from only those locations. This method allows for flexible, high-speed, serf-align scanning for fluorescence detection in capillary or microchip electrophoresis and has the potential to be applied to a number of applications.

Articles that were published from Oct., 1994 to Oct., 1996 concerning the application of liquid chromatography, Fourier transform infrared spectroscopy and mass spectrometry in protein analysis were discussed. Articles on the separation of proteins and aggregates by size exclusion chromatography and reversed phase-high-performance chromatography were outlined in M.E. Himmel et al.'s 'Handbook of Size Exclusion Chromatography'. Furthermore, articles about the nonenzymatic posttranslational modification of proteins were also published by B.S. Chang et al.

A review of literature on the separation and analysis of peptides and proteins published during the period 1993-1994 is presented. The areas considered are analytical and preparative high-performance liquid chromatography, fluorescence spectroscopy, capillary electrophoresis, circular dichroism, nuclear magnetic resonance and Fourier transform infrared. A special chapter on the on-line coupling of separation methods to mass spectrometry is also included.

Several silica coatings have been evaluated for replicate PCR product analysis in capillaries and electrophoretic microchips. Silica coatings are an essential component to many electrophoretic separations, and this importance is magnified in microchips, where separation distances are minimized. Increasing the resistance of coatings to separation conditions improves the reproducibility and longevity of the coated microchip, which allows for the full potential of these devices (rapid separations, high throughput, and longevity) to be realized. In this study, several coating parameters have been evaluated experimentally and through the literature to produce a coating with high resistance to the separation conditions of interest, neat PCR product separations. Coating degradation induced under these conditions was tested for several coatings, and the influence of surface hydroxylation, surface hydration, silanization solvent, silanizing reagent, catalysis, endcapping, and polymerization procedure are discussed. Under the testing conditions, a coating (coating E) prepared by silanization with chlorodimethyloctylsilane in toluene with a polymer layer of poly(vinylpyrrolidone) attached by a hydrogen abstraction method [Srinivasan, K.; Pohl, C.; Avdalovic, N. Anal Chem. 1997, 69, 2798-2805] was most resistant. This coating was tested for longevity on electrophoretic microchips and was compared to the traditional coating of polyacrylamide. The coatings produced similar resolution and efficiencies; however, coating E provided more reproducible migration times and had performed for 635 analyses when testing was terminated. This procedure provides a reproducible, resistant surface coating, thus allowing for replicate analysis of neat PCR product on microchips.

Spermiogenesis is a series of poorly understood morphological, physiological and biochemical processes that occur during the transition of immotile spermatids into motile, fertilization-competent spermatozoa. Here, we identified a Serpin (serine protease inhibitor) family protein (As̱SRP-1) that is secreted from spermatids during nematode Ascaris suum spermiogenesis (also called sperm activation) and we showed that As̱SRP-1 has two major functions. First, As̱SRP-1 functions in cis to support major sperm protein (MSP)-based cytoskeletal assembly in the spermatid that releases it, thereby facilitating sperm motility acquisition. Second, As̱SRP-1 released from an activated sperm inhibits, in trans, the activation of surrounding spermatids by inhibiting vas deferens-derived As̱TRY-5, a trypsin-like serine protease necessary for sperm activation. Because vesicular exocytosis is necessary to create fertilization-competent sperm in many animal species, components released during this process might be more important modulators of the physiology and behavior of surrounding sperm than was previously appreciated. [ABSTRACT FROM AUTHOR]

Lipids comprise the bulk of the dry mass of the brain. In addition to providing structural integrity to membranes, insulation to cells and acting as a source of energy, lipids can be rapidly converted to mediators of inflammation or to signaling molecules that control molecular and cellular events in the brain. The advent of soft ionization procedures such as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) have made it possible for compositional studies of the diverse lipid structures that are present in brain. These include phospholipids, ceramides, sphingomyelin, cerebrosides, cholesterol and their oxidized derivatives. Lipid analyses have delineated metabolic defects in disease conditions including mental retardation, Parkinson's Disease (PD), schizophrenia, Alzheimer's Disease (AD), depression, brain development, and ischemic stroke. In this review, we examine the structure of the major lipid classes in the brain, describe methods used for their characterization, and evaluate their role in neurological diseases. The potential utility of characterizing lipid markers in the brain, with specific emphasis on disease mechanisms, will be discussed. Additionally, we describe several proteomic strategies for characterizing lipid-metabolizing proteins in human cerebrospinal fluid (CSF). These proteins may be potential therapeutic targets since they transport lipids required for neuronal growth or convert lipids into molecules that control brain physiology. Combining lipidomics and proteomics will enhance existing knowledge of disease pathology and increase the likelihood of discovering specific markers and biochemical mechanisms of brain diseases. [ABSTRACT FROM AUTHOR]

Comparative glycosylation analysis of biopharmaceuticals requires the development of methods that deliver the necessary throughput, support structural elucidation and relative quantitation of glycans released from therapeutics. The current study presents the development and applicability assessment of a twoplex approach using light and heavy isotopolouges of 3-aminobenzenesulfonic acid (3-ASA) under wet labeling conditions followed by UHPLC-MS analysis in data dependent acquisition mode. Excellent labelling efficiency, >90%, was achieved for both the light and heavy variants of the reagent. Glycan distributions of two human IgG lots labeled by light and heavy isotopolouges were identical, demonstrating no labeling bias introduced by either of the isotopologues. Peak area distributions of glycan profiles of two human IgG lots were compared to 2-aminobenzamide (2-AB) and RapiFluor-MS protocols. The comparison led to identical results in peak area distribution across the three dyes, but differences in chromatographic selectivity attributed to the different tags. MS 1 based relative quantitation was further validated by releasing glycans from the same lot of human IgG, with glycan pools obtained labeled with light and heavy isotopologues separately, followed by mixing and clean-up of the same amount of light and heavy labeled glycan pools. MS analyses of each glycan resulted in a ratio of light and heavy XIC in the range of 0.97 ≤ x ≤ 1.05, demonstrating the method is amenable for the relative quantitation of glycans. Excellent correlation between the relative quantitation data of N-glycans from two human IgG N-glycan pools using the twoplex approach and ratios from peak area distribution calculated from the fluorescent chromatogram was observed (r = 0.986), further corroborating the reliability of the method and its potential applicability in the biopharmaceutical industry. Highly informative HCD-MS 2 spectra dominated mostly by Y- and Z-type single and double glycosidic fragment ions facilitate structural interpretation of the oligosaccharides., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Z. Szabo, S.H. Khan, P.J. Widdowson, R. Viner and A. Huhmer are employees of Thermo Fisher Scientific, the corporation that develops and produces Vanquish UHPLC systems and Orbitrap mass spectrometers. Beyond this, the authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this article., (Copyright © 2019 Elsevier B.V. All rights reserved.)