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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.

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 β-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.

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.

The attapulgite-iron oxide magnetic composites were synthesized by coprecipitation of iron oxides on attapulgite particles, and characterized by FTIR and XRD. The composites had the saturation magnetization value of 32.7 emu/g, which made the composites separate from aqueous solution easily using the magnetic separation method in large scale. The composites could preconcentrate Eu(III) efficiently from aqueous solutions. The sorption of Eu(III) on the composites was affected by pH and ionic strength obviously. The sorption isotherms were well simulated by Langmuir model, and the maximum sorption capacity was calculated to be 4.94 × 10 −4 mol/g at pH 5.0, which was much higher other materials.

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.

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.

In this study, several glycoproteins: bovine α1-acid glycoprotein, fetuin, and human α1-acid glycoprotein, were analyzed using nanoLC-MS/MS. The performance of three different stationary phases – C8, C18, and porous graphite – was systematically evaluated and optimized for glycopeptide separation. A porous graphite column was chosen as the optimum stationary phase for glycoprotein analysis. An LTQ Orbitrap XL hybrid mass spectrometer equipped with electron transfer dissociation (ETD) was used to acquire, within a single analysis, high-resolution, high-mass-accuracy full MS spectra, collision-induced dissociation (CID) MS/MS spectra for glycan composition analysis, and ETD MS/MS spectra for peptide structure information. As a result, characterization of glycopeptides was achieved within a single LC-MS/MS run.

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.

Two different Cd 2+ uptake systems were identified in Lactobacillus plantarum . One is a high-affinity, high-velocity Mn 2+ uptake system which also takes up Cd 2+ and is induced by Mn 2+ starvation. The calculated K m and V max are 0.26 μM and 3.6 μmol g of dry cell −1 min −1 , respectively. Unlike Mn 2+ uptake, which is facilitated by citrate and related tricarboxylic acids, Cd 2+ uptake is weakly inhibited by citrate. Cd 2+ and Mn 2+ are competitive inhibitors of each other, and the affinity of the system for Cd 2+ is higher than that for Mn 2+ . The other Cd 2+ uptake system is expressed in Mn 2+ -sufficient cells, and no K m can be calculated for it because uptake is nonsaturable. Mn 2+ does not compete for transport through this system, nor does any other tested cation, i.e., Zn 2+ , Cu 2+ , Co 2+ , Mg 2+ , Ca 2+ , Fe 2+ , or Ni 2+ . Both systems require energy, since uncouplers completely inhibit their activities. Two Mn 2+ -dependent L. plantarum mutants were isolated by chemical mutagenesis and ampicillin enrichment. They required more than 5,000 times as much Mn 2+ for growth as the parental strain. Mn 2+ starvation-induced Cd 2+ uptake in both mutants was less than 5% the wild-type rate. The low level of long-term Mn 2+ or Cd 2+ accumulation by the mutant strains also shows that the mutations eliminate the high-affinity Mn 2+ and Cd 2+ uptake system.

Cadmium (Cd), one of the most toxic metals to man and other forms of life, has no known biological function [1, 2]. Cadmium compounds enter the environment through a variety of industrial processes, such as mining, smelting and electroplating, and to a less extent, from natural weathering. The effects from human exposure via food chains in cadmium-polluted areas and the known lethality of the metal in case of extreme exposure [3] have focused attention on developing methods for its removal from polluted areas.