Candidate Genes and Pathways in Rice Co-Responding to Drought and Salt Identified by gcHap Network.

Drought and salinity stresses are significant abiotic factors that limit rice yield. Exploring the co-response mechanism to drought and salt stress will be conducive to future rice breeding. A total of 1748 drought and salt co-responsive genes were screened, most of which are enriched in plant hormone signal transduction, protein processing in the endoplasmic reticulum, and the MAPK signaling pathways. We performed gene-coding sequence haplotype (gcHap) network analysis on nine important genes out of the total amount, which showed significant differences between the Xian/indica and Geng/japonica population. These genes were combined with related pathways, resulting in an interesting mechanistic draft called the 'gcHap-network pathway'. Meanwhile, we collected a lot of drought and salt breeding varieties, especially the introgression lines (ILs) with HHZ as the parent, which contained the above-mentioned nine genes. This might imply that these ILs have the potential to improve the tolerance to drought and salt. In this paper, we focus on the relationship of drought and salt co-response gene gcHaps and their related pathways using a novel angle. The haplotype network will be helpful to explore the desired haplotypes that can be implemented in haplotype-based breeding programs.

Quantitative Proteome Profiling Reveals Cellobiose-Dependent Protein Processing and Export Pathways for the Lignocellulolytic Response in Neurospora crassa.

Filamentous fungi are intensively used for producing industrial enzymes, including lignocellulases. Employing insoluble cellulose to induce the production of lignocellulases causes some drawbacks, e.g., a complex fermentation operation, which can be overcome by using soluble inducers such as cellobiose. Here, a triple ß-glucosidase mutant of Neurospora crassa, which prevents rapid turnover of cellobiose and thus allows the disaccharide to induce lignocellulases, was applied to profile the proteome responses to cellobiose and cellulose (Avicel). Our results revealed a shared proteomic response to cellobiose and Avicel, whose elements included lignocellulases and cellulolytic product transporters. While the cellulolytic proteins showed a correlated increase in protein and mRNA levels, only a moderate correlation was observed on a proteomic scale between protein and mRNA levels (R2 = 0.31). Ribosome biogenesis and rRNA processing were significantly overrepresented in the protein set with increased protein but unchanged mRNA abundances in response to Avicel. Ribosome biogenesis, as well as protein processing and protein export, was also enriched in the protein set that showed increased abundance in response to cellobiose. NCU05895, a homolog of yeast CWH43, is potentially involved in transferring a glycosylphosphatidylinositol (GPI) anchor to nascent proteins. This protein showed increased abundance but no significant change in mRNA levels. Disruption of CWH43 resulted in a significant decrease in cellulase activities and secreted protein levels in cultures grown on Avicel, suggesting a positive regulatory role for CWH43 in cellulase production. The findings should have an impact on a systems engineering approach for strain improvement for the production of lignocellulases.IMPORTANCE Lignocellulases are important industrial enzymes for sustainable production of biofuels and bio-products. Insoluble cellulose has been commonly used to induce the production of lignocellulases in filamentous fungi, which causes a difficult fermentation operation and enzyme loss due to adsorption to cellulose. The disadvantages can be overcome by using soluble inducers, such as the disaccharide cellobiose. Quantitative proteome profiling of the model filamentous fungus Neurospora crassa revealed cellobiose-dependent pathways for cellulase production, including protein processing and export. A protein (CWH43) potentially involved in protein processing was found to be a positive regulator of lignocellulase production. The cellobiose-dependent mechanisms provide new opportunities to improve the production of lignocellulases in filamentous fungi.

Identification of cross-linked peptides from complex samples.

We have developed pLink, software for data analysis of cross-linked proteins coupled with mass-spectrometry analysis. pLink reliably estimates false discovery rate in cross-link identification and is compatible with multiple homo- or hetero-bifunctional cross-linkers. We validated the program with proteins of known structures, and we further tested it on protein complexes, crude immunoprecipitates and whole-cell lysates. We show that it is a robust tool for protein-structure and protein-protein-interaction studies.

Nematode sperm maturation triggered by protease involves sperm-secreted serine protease inhibitor (Serpin).

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 (As_SRP-1) that is secreted from spermatids during nematode Ascaris suum spermiogenesis (also called sperm activation) and we showed that As_SRP-1 has two major functions. First, As_SRP-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, As_SRP-1 released from an activated sperm inhibits, in trans, the activation of surrounding spermatids by inhibiting vas deferens-derived As_TRY-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.

A Robust Purity Method for Biotherapeutics Using New Peak Detection in an LC-MS-Based Multi-Attribute Method.

New peak detection (NPD), as part of the LC-MS-based multi-attribute method (MAM), allows for sensitive and unbiased detection of new or changing site-specific attributes between a sample and reference that is not possible with conventional UV or fluorescence detection-based methods. MAM with NPD can serve as a purity test that can establish whether a sample and the reference are similar. The broad implementation of NPD in the biopharmaceutical industry has been limited by the potential presence of false positives or artifacts, which increase the analysis time and can trigger unnecessary investigations of product quality. Our novel contributions to the success of NPD are the curation of false positives, use of the known peak list concept, pairwise analysis approach, and the development of a NPD system suitability control strategy. In this report, we also introduce a unique experimental design utilizing sequence variant co-mixes to measure NPD performance. We show that NPD has superior performance relative to conventional control system methods in the detection of an unexpected change as compared with the reference. NPD is a new frontier in purity testing that reduces subjectivity, need for analyst intervention, and potential for missing unexpected product quality changes.

Mass spectrometry-based multi-attribute method in protein therapeutics product quality monitoring and quality control.

The multi-attribute method (MAM), a liquid chromatography-mass spectrometry (LC-MS)-based peptide mapping method, has gained increased interest and applications in the biopharmaceutical industry. MAM can, in one method, provide targeted quantitation of multiple site-specific product quality attributes, as well as new peak detection. In this review, we focus on the scientific and regulatory considerations of using MAM in product quality attribute monitoring and quality control (QC) of therapeutic proteins. We highlight MAM implementation challenges and solutions with several case studies, and provide our perspective on the opportunities to use MS in QC for applications other than standard peptide mapping-based MAM.

Proteomics analysis of the cardiac myofilament subproteome reveals dynamic alterations in phosphatase subunit distribution.

Myofilament proteins are responsible for cardiac contraction. The myofilament subproteome, however, has not been comprehensively analyzed thus far. In the present study, cardiomyocytes were isolated from rodent hearts and stimulated with endothelin-1 and isoproterenol, potent inducers of myofilament protein phosphorylation. Subsequently, cardiomyocytes were "skinned," and the myofilament subproteome was analyzed using a high mass accuracy ion trap tandem mass spectrometer (LTQ Orbitrap XL) equipped with electron transfer dissociation. As expected, a small number of myofilament proteins constituted the majority of the total protein mass with several known phosphorylation sites confirmed by electron transfer dissociation. More than 600 additional proteins were identified in the cardiac myofilament subproteome, including kinases and phosphatase subunits. The proteomic comparison of myofilaments from control and treated cardiomyocytes suggested that isoproterenol treatment altered the subcellular localization of protein phosphatase 2A regulatory subunit B56alpha. Immunoblot analysis of myocyte fractions confirmed that beta-adrenergic stimulation by isoproterenol decreased the B56alpha content of the myofilament fraction in the absence of significant changes for the myosin phosphatase target subunit isoforms 1 and 2 (MYPT1 and MYPT2). Furthermore, immunolabeling and confocal microscopy revealed the spatial redistribution of these proteins with a loss of B56alpha from Z-disc and M-band regions but increased association of MYPT1/2 with A-band regions of the sarcomere following beta-adrenergic stimulation. In summary, we present the first comprehensive proteomics data set of skinned cardiomyocytes and demonstrate the potential of proteomics to unravel dynamic changes in protein composition that may contribute to the neurohormonal regulation of myofilament contraction.

Multi-attribute Raman spectroscopy (MARS) for monitoring product quality attributes in formulated monoclonal antibody therapeutics.

Rapid release of biopharmaceutical products enables a more efficient drug manufacturing process. Multi-attribute methods that target several product quality attributes (PQAs) at one time are an essential pillar of the rapid-release strategy. The novel, high-throughput, and nondestructive multi-attribute Raman spectroscopy (MARS) method combines Raman spectroscopy, design of experiments, and multivariate data analysis (MVDA). MARS allows the measurement of multiple PQAs for formulated protein therapeutics without sample preparation from a single spectroscopic scan. Variable importance in projection analysis is used to associate the chemical and spectral basis of targeted PQAs, which assists in model interpretation and selection. This study shows the feasibility of MARS for the measurement of both protein purity-related and formulation-related PQAs; measurements of protein concentration, osmolality, and some formulation additives were achieved by a generic multiproduct model for various protein products containing the same formulation components. MARS demonstrates the potential to be a powerful methodology to improve the efficiency of biopharmaceutical development and manufacturing, as it features fast turnaround time, good robustness, less human intervention, and potential for automation.

Multi-attribute method performance profile for quality control of monoclonal antibody therapeutics.

Multi-attribute method (MAM) using peptide map analysis with high resolution mass spectrometry is increasingly common in product characterization and the identification of critical quality attributes (CQAs) of biotherapeutic proteins. Capable of providing structural information specific to amino acid residues, quantifying relative abundance of product variants or degradants, and detecting profile changes between product lots, a robust MAM can replace multiple traditional methods that generate profile-based information for product release and stability testing. In an effort to provide informative and efficient analytical monitoring for monoclonal antibody (mAb) products, from early development to manufacturing quality control, we describe the desired MAM performance profile and address the major scientific challenges in MAM method validation. Furthermore, to support fast speed investigational product development, we describe a platform method validation strategy and results of an optimized MAM workflow. This strategy is applied to support the use of MAM for multiple mAb products with similar structures and physicochemical properties, requiring minimal product-specific method validation activities. Three mAb products were used to demonstrate MAM performance for common and representative product quality attributes. Method validation design and acceptance criteria were guided by the Analytical Target Profile concept, as well as relevant regulatory guidelines to ensure the method is fit-for-purpose. A comprehensive system suitability control strategy was developed, and reported here, to ensure adequate performance of the method including sample preparation, instrument operation, and data analysis. Our results demonstrated sufficient method performance for the characteristics required for quantitative measurement of product variants and degradants.

Analysis of the trypanosome flagellar proteome using a combined electron transfer/collisionally activated dissociation strategy.

The use of electron-transfer dissociation as an alternative peptide ion activation method for generation of protein sequence information is examined here in comparison with the conventional method of choice, collisionally activated dissociation, using a linear ion trapping instrument. Direct comparability between collisionally and electron-transfer-activated product ion data were ensured by employing an activation-switching method during acquisition, sequentially activating precisely the same precursor ion species with each fragmentation method in turn. Sequest (Thermo Fisher Scientific, San Jose, CA) searching of product ion data generated an overlapping yet distinct pool of polypeptide identifications from the products of collisional and electron-transfer-mediated activation products. To provide a highly confident set of protein recognitions, identification data were filtered using parameters that achieved a peptide false discovery rate of 1%, with two or more independent peptide assignments required for each protein. The use of electron transfer dissociation (ETD) has allowed us to identify additional peptides where the quality of product ion data generated by collisionally activated dissociation (CAD) was insufficient to infer peptide sequence. Thus, a combined ETD/CAD approach leads to the recognition of more peptides and proteins than are achieved using peptide analysis by CAD- or ETD-based tandem mass spectrometry alone.

A review of modification of carbon electrode material in capacitive deionization.

Capacitive deionization (CDI) technology has attracted wide attention since its advent and is considered as one of the most promising technologies in the field of desalination and ion recycling. It is constructed with an electric field by applying a low voltage of direct-current to make ions migrate directionally in solution to achieve the purpose of ion separation and removal. The performance of CDI is heavily dependent on the electrode material. Carbon is widely used as CDI electrode material because of its lower price and better stability. To enhance the adsorption capacity, extensive research efforts have been made for the modification of carbon material. In this review, we enumerate and analyze four modification methods of carbon material including element doping, metal oxide modification, chemical treatment and surface coating. The influence of each modification method on CDI performance is concluded in the perspective mechanism and some constructive advice is put forward on how to effectively enhance the performance of CDI by the decoration of carbon materials.

Statistical characterization of therapeutic protein modifications.

Peptide mapping with liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an important analytical method for characterization of post-translational and chemical modifications in therapeutic proteins. Despite its importance, there is currently no consensus on the statistical analysis of the resulting data. In this manuscript, we distinguish three statistical goals for therapeutic protein characterization: (1) estimation of site occupancy of modifications in one condition, (2) detection of differential site occupancy between conditions, and (3) estimation of combined site occupancy across multiple modification sites. We propose an approach, which addresses these goals in terms of summarizing the quantitative information from the mass spectra, statistical modeling, and model-based analysis of LC-MS/MS data. We illustrate the approach using an LC-MS/MS experiment from an antibody-drug conjugate and its monoclonal antibody intermediate. The performance was compared to a 'naïve' data analysis approach, by using computer simulation, evaluation of differential site occupancy in positive and negative controls, and comparisons of estimated site occupancy with orthogonal experimental measurements of N-linked glycoforms and total oxidation. The results demonstrated the importance of replicated studies of protein characterization, and of appropriate statistical modeling, for reproducible, accurate and efficient site occupancy estimation and differential analysis.

Electron transfer dissociation in conjunction with collision activation to investigate the Drosophila melanogaster phosphoproteome.

Better understanding how cells are regulated and adapt to their environment based on the reversible phosphorylation of proteins is a key question of current molecular and systems biology research. In this study, an advanced mass spectrometry based approach leveraging the electron transfer dissociation (ETD) technique in combination with CID using a linear ion trap mass spectrometer is described. The technique was applied, for the first time, to the identification of phosphorylated peptides isolated from the Drosophila melanogaster Kc167 cell line. We demonstrate that the method is particularly useful for the characterization of large phosphopeptides, including those with multiple phosphorylation sites, as extensive series of c' and z fragment-ions were observed. Finally, we have applied a directed tandem mass spectrometric workflow using inclusion lists to increase the number of identified peptides.

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.,