Comparison of platform host cell protein ELISA to process-specific host cell protein ELISA.

During expression of biotherapeutic proteins, complex mixtures of additional proteins are also produced by normal expression machinery of the host cell (termed "host cell proteins," or HCP). HCPs pose a potential impact to patient safety and product efficacy, and therefore must be well-characterized and the ability of the process to clear these proteins must be demonstrated. Due to the complexity of HCP, the method(s) used for monitoring must be demonstrated to provide sufficient information about relevant proteins. The most commonly used analytical method for monitoring HCP is an enzyme-linked immunosorbent assay (ELISA). To ensure development of a suitable HCP ELISA, careful selection of critical reagents (anti-HCP antibodies and analytical standard) is crucial. During a recent major update to the manufacturing process of a biotherapeutic, we re-evaluated the suitability of the existing HCP ELISA for monitoring the HCP population in the updated process. In the evaluation, we compared a process-specific ELISA to a platform ELISA. Despite qualitative differences in the HCP profiles in 2D PAGE, LC-MS/MS showed that the HCP populations in the two analytical standards were similar. The process-specific HCP antibody had adequate HCP coverage, but was more sensitive to a few dominant proteins that were present in the upstream purification process. The platform HCP antibody had very broad coverage and additionally, could detect the majority of potential HCP impurities from this process. Furthermore, the platform HCP antibody was not biased toward a few dominant proteins and was more sensitive in the downstream purification process. Due to its broad HCP coverage and sensitivity, we conclude that our platform HCP ELISA method is superior to the process-specific HCP ELISA method.

Characterization of potential degradation products in a PEGylating reagent 20 kDa monomethoxy polyethylene glycol propionaldehyde by RP-HPLC, APCI-MS and NMR.

Ensuring quality of PEGylating reagents is essential for the successful development and manufacturing of PEGylated biopharmaceuticals. However, little is known about how to maintain and verify the quality of PEG raw materials for PEGylated protein manufacturing. In this study, monomethoxy polyethylene glycol propionaldehyde (mPEG-aldehyde) was subjected to conditions that mimic accelerated stability conditions. Separation of trace-level degradation products in the presence of mPEG-aldehyde was achieved by derivatization with 2,4-dinitrophenylhydrazine (DNPH), followed by reversed phase high performance liquid chromatography with ultraviolet detection (RP-HPLC-UV) at 355nm. Structural characterization by atmospheric pressure chemical ionization mass spectrometry (APCI-MS) identified formaldehyde, acetaldehyde, crotonaldehyde, acrolein, benzaldehyde, and tolualdehyde as major degradation products or process-related impurities. The presence of formaldehyde and acrolein was confirmed by (1)H NMR in the forced degraded mPEG-aldehyde samples without derivatization of mPEG-aldehyde. Findings from this study imply that reactive impurities could form as a result of inappropriate mPEG-aldehyde handling or storage. Further, a rapid screening method based on reversed phase HPLC was shown to be an effective screening assay used for routine screening of mPEG-aldehyde to ensure consistent PEGylated protein product quality.

Lymphatic endothelial murine chloride channel calcium-activated 1 is a ligand for leukocyte LFA-1 and Mac-1.

The lymphatic circulation mediates drainage of fluid and cells from the periphery through lymph nodes, facilitating immune detection of lymph-borne foreign Ags. The 10.1.1 mAb recognizes a lymphatic endothelial Ag, in this study purified by Ab-affinity chromatography. SDS-PAGE and mass spectrometry identified murine chloride channel calcium-activated 1 (mCLCA1) as the 10.1.1 Ag, a 90-kDa cell-surface protein expressed in lymphatic endothelium and stromal cells of spleen and thymus. The 10.1.1 Ab-affinity chromatography also purified LFA-1, an integrin that mediates leukocyte adhesion to endothelium. This mCLCA1-LFA-1 interaction has functional consequences, as lymphocyte adhesion to lymphatic endothelium was blocked by 10.1.1 Ab bound to endotheliumor by LFA-1 Ab bound to lymphocytes. Lymphocyte adhesion was increased by cytokine treatment of lymphatic endothelium in association with increased expression of ICAM-1, an endothelial surface protein that is also a ligand for LFA-1. By contrast, mCLCA1 expression and the relative contribution of mCLCA1 to lymphocyte adhesion were unaffected by cytokine activation, demonstrating that mCLCA1 and ICAM-1 interactions with LFA-1 are differentially regulated. mCLCA1 also bound to the LFA-1-related Mac-1 integrin that is preferentially expressed on leukocytes. mCLCA1-mediated adhesion of Mac-1- or LFA-1-expressing leukocytes to lymphatic vessels and lymph node lymphatic sinuses provides a target for investigation of lymphatic involvement in leukocyte adhesion and trafficking during the immune response.

Dynamic fluctuations of protein-carbohydrate interactions promote protein aggregation.

Protein-carbohydrate interactions are important for glycoprotein structure and function. Antibodies of the IgG class, with increasing significance as therapeutics, are glycosylated at a conserved site in the constant Fc region. We hypothesized that disruption of protein-carbohydrate interactions in the glycosylated domain of antibodies leads to the exposure of aggregation-prone motifs. Aggregation is one of the main problems in protein-based therapeutics because of immunogenicity concerns and decreased efficacy. To explore the significance of intramolecular interactions between aromatic amino acids and carbohydrates in the IgG glycosylated domain, we utilized computer simulations, fluorescence analysis, and site-directed mutagenesis. We find that the surface exposure of one aromatic amino acid increases due to dynamic fluctuations. Moreover, protein-carbohydrate interactions decrease upon stress, while protein-protein and carbohydrate-carbohydrate interactions increase. Substitution of the carbohydrate-interacting aromatic amino acids with non-aromatic residues leads to a significantly lower stability than wild type, and to compromised binding to Fc receptors. Our results support a mechanism for antibody aggregation via decreased protein-carbohydrate interactions, leading to the exposure of aggregation-prone regions, and to aggregation.

Gas-phase proton-transfer chemistry coupled with TOF mass spectrometry and ion mobility-MS for the facile analysis of poly(ethylene glycols) and PEGylated polypeptide conjugates.

Gas-phase ion/molecule chemistry has been combined with ion mobility separation and time-of-flight mass spectrometry to enable the characterization of large poly(ethylene glycol)s (PEGs) and PEGylated molecules (>40 kDa). A facile method is presented in which gas-phase superbases are reacted in the high-pressure source region of commercial TOF mass spectrometers to manipulate the charge states of large ions generated by electrospray ionization (ESI). Charge stripping decreases the spectral congestion typically observed in ESI mass spectra of high molecular weight polydisperse PEGylated molecules. From these data, accurate average molecular weights and molecular weight distributions for synthetic polymers and PEGylated proteins are determined. The average MW measured for PEGylated Granulocyte colony-stimulating factor (rh-GCSF, 40 726.2 Da) is in good agreement with the theoretical value, and a 16 Da mass shift is easily observed in the spectrum of an oxidized form of the heterogeneous PEGylated protein. Ion mobility separations can fractionate PEGs of different chain length; when coupled with charge stripping ion/molecule reactions, ion mobility mass spectrometry (IMMS) offers several analytical advantages over mass spectrometry alone for the characterization of large PEGylated molecules including enhanced dynamic range, increased sensitivity, and specificity. Low abundance free PEG in a PEGylated peptide preparation, which is not directly detectable by mass spectrometry, can be easily observed and accurately quantified with gas-phase ion/molecule chemistry combined with ion mobility mass spectrometry.

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

Assessing bias in experiment design for large scale mass spectrometry-based quantitative proteomics.

Mass spectrometry-based proteomics holds great promise as a discovery tool for biomarker candidates in the early detection of diseases. Recently much emphasis has been placed upon producing highly reliable data for quantitative profiling for which highly reproducible methodologies are indispensable. The main problems that affect experimental reproducibility stem from variations introduced by sample collection, preparation, and storage protocols and LC-MS settings and conditions. On the basis of a formally precise and quantitative definition of similarity between LC-MS experiments, we have developed Chaorder, a fully automatic software tool that can assess experimental reproducibility of sets of large scale LC-MS experiments. By visualizing the similarity relationships within a set of experiments, this tool can form the basis of systematic quality control and thus help assess the comparability of mass spectrometry data over time, across different laboratories, and between instruments. Applying Chaorder to data from multiple laboratories and a range of instruments, experimental protocols, and sample complexities revealed biases introduced by the sample processing steps, experimental protocols, and instrument choices. Moreover we show that reducing bias by correcting for just a few steps, for example randomizing the run order, does not provide much gain in statistical power for biomarker discovery.

Head-to-head comparison of serum fractionation techniques.

Multiple approaches for simplifying the serum proteome have been described. These techniques are generally developed across different laboratories, samples, mass spectrometry platforms, and analysis tools. Hence, comparing the available schemes is impossible from the existing literature because of confounding variables. We describe a head-to-head comparison of several serum fractionation schemes, including N-linked glycopeptide enrichment, cysteinyl-peptide enrichment, magnetic bead separation (C3, C8, and WCX), size fractionation, protein A/G depletion, and immunoaffinity column depletion of abundant serum proteins. Each technique was compared to results obtained from unfractionated human serum. The results show immunoaffinity subtraction is the most effective means for simplifying the serum proteome while maintaining reasonable sample throughput. The reported dataset is publicly available and provides a standard against which emergent technologies can be compared and evaluated for their contribution to serum-based biomarker discovery.

Antibody-based enrichment of peptides on magnetic beads for mass-spectrometry-based quantification of serum biomarkers.

A major bottleneck for validation of new clinical diagnostics is the development of highly sensitive and specific assays for quantifying proteins. We previously described a method, stable isotope standards with capture by antipeptide antibodies, wherein a specific tryptic peptide is selected as a stoichiometric representative of the protein from which it is cleaved, is enriched from biological samples using immobilized antibodies, and is quantitated using mass spectrometry against a spiked internal standard to yield a measure of protein concentration. In this study, we optimized a magnetic-bead-based platform amenable to high-throughput peptide capture and demonstrated that antibody capture followed by mass spectrometry can achieve ion signal enhancements on the order of 10(3), with precision (CVs <10%) and accuracy (relative error approximately 20%) sufficient for quantifying biomarkers in the physiologically relevant ng/mL range. These methods are generally applicable to any protein or biological fluid of interest and hold great potential for providing a desperately needed bridging technology between biomarker discovery and clinical application.

Normalization regarding non-random missing values in high-throughput mass spectrometry data.

We propose a two-step normalization procedure for high-throughput mass spectrometry (MS) data, which is a necessary step in biomarker clustering or classification. First, a global normalization step is used to remove sources of systematic variation between MS profiles due to, for instance, varying amounts of sample degradation over time. A probability model is then used to investigate the intensity-dependent missing events and provides possible substitutions for the missing values. We illustrate the performance of the method with a LC-MS data set of synthetic protein mixtures.

Quality control metrics for LC-MS feature detection tools demonstrated on Saccharomyces cerevisiae proteomic profiles.

Quantitative proteomic profiling using liquid chromatography-mass spectrometry is emerging as an important tool for biomarker discovery, prompting development of algorithms for high-throughput peptide feature detection in complex samples. However, neither annotated standard data sets nor quality control metrics currently exist for assessing the validity of feature detection algorithms. We propose a quality control metric, Mass Deviance, for assessing the accuracy of feature detection tools. Because the Mass Deviance metric is derived from the natural distribution of peptide masses, it is machine- and proteome-independent and enables assessment of feature detection tools in the absence of completely annotated data sets. We validate the use of Mass Deviance with a second, independent metric that is based on isotopic distributions, demonstrating that we can use Mass Deviance to identify aberrant features with high accuracy. We then demonstrate the use of independent metrics in tandem as a robust way to evaluate the performance of peptide feature detection algorithms. This work is done on complex LC-MS profiles of Saccharomyces cerevisiae which present a significant challenge to peptide feature detection algorithms.

Computational Proteomics Analysis System (CPAS): an extensible, open-source analytic system for evaluating and publishing proteomic data and high throughput biological experiments.

The open-source Computational Proteomics Analysis System (CPAS) contains an entire data analysis and management pipeline for Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) proteomics, including experiment annotation, protein database searching and sequence management, and mining LC-MS/MS peptide and protein identifications. CPAS architecture and features, such as a general experiment annotation component, installation software, and data security management, make it useful for collaborative projects across geographical locations and for proteomics laboratories without substantial computational support.

Signal maps for mass spectrometry-based comparative proteomics.

Mass spectrometry-based proteomic experiments, in combination with liquid chromatography-based separation, can be used to compare complex biological samples across multiple conditions. These comparisons are usually performed on the level of protein lists generated from individual experiments. Unfortunately given the current technologies, these lists typically cover only a small fraction of the total protein content, making global comparisons extremely limited. Recently approaches have been suggested that are built on the comparison of computationally built feature lists instead of protein identifications. Although these approaches promise to capture a bigger spectrum of the proteins present in a complex mixture, their success is strongly dependent on the correctness of the identified features and the aligned retention times of these features across multiple experiments. In this experimental-computational study, we went one step further and performed the comparisons directly on the signal level. First signal maps were constructed that associate the experimental signals across multiple experiments. Then a feature detection algorithm used this integrated information to identify those features that are discriminating or common across multiple experiments. At the core of our approach is a score function that faithfully recognizes mass spectra from similar peptide mixtures and an algorithm that produces an optimal alignment (time warping) of the liquid chromatography experiments on the basis of raw MS signal, making minimal assumptions on the underlying data. We provide experimental evidence that suggests uniqueness and correctness of the resulting signal maps even on low accuracy mass spectrometers. These maps can be used for a variety of proteomic analyses. Here we illustrate the use of signal maps for the discovery of diagnostic biomarkers. An imple-mentation of our algorithm is available on our Web server.

A novel mutation in the RDS/Peripherin gene causes adult-onset foveomacular dystrophy.

PURPOSE: To describe a novel mutation in the RDS/Peripherin gene that results in a moderately severe form of adult-onset foveomacular dystrophy. DESIGN: Observational case series. METHODS: Selected members of a family with adult-onset foveomacular dystrophy underwent complete ophthalmic evaluation, including fundus photography and fluorescein angiography, in a tertiary care referral center. The study population consisted of 12 members of a Caucasian kindred. After providing informed consent, patients donated blood for genomic DNA extraction and mutational screening using standard techniques. The main outcome measure were the presence of a RDS/Peripherin gene mutation in a patient with the disease and its absence in unaffected family members and controls. RESULTS: Eight affected family members and no unaffected family members demonstrated a single guanine base deletion at nucleotide 112 that led to premature termination at amino acid 38 of RDS/Peripherin polypeptide. This frameshift mutation results in truncation of nearly 90% of the gene product, thus probably representing a null allele. That results in a relatively severe phenotype, with choroidal neovascularization developing in two patients and geographic atrophy involving the macula in three patients. CONCLUSIONS: We describe a frameshift null mutation in the RDS/Peripherin gene associated with a relatively severe manifestation of adult-onset foveomacular dystrophy in affected family members.

Hydrogen/deuterium exchange and mass spectrometric analysis of a protein containing multiple disulfide bonds: Solution structure of recombinant macrophage colony stimulating factor-beta (rhM-CSFbeta).

Studies with the homodimeric recombinant human macrophage colony-stimulating factor beta (rhM-CSFbeta), show for the first time that a large number (9) of disulfide linkages can be reduced after amide hydrogen/deuterium (H/D) exchange, and the protein digested and analyzed successfully for the isotopic composition by electrospray mass spectrometry. Analysis of amide H/D after exchange-in shows that in solution the conserved four-helix bundle of (rhM-CSFbeta) has fast and moderately fast exchangeable sections of amide hydrogens in the alphaA helix, and mostly slow exchanging sections of amide hydrogens in the alphaB, alphaC, and alphaD helices. Most of the amide hydrogens in the loop between the beta1 and beta4 sheets exhibited fast or moderately fast exchange, whereas in the amino acid 63-67 loop, located at the interface of the two subunits, the exchange was slow. Solvent accessibility as measured by H/D exchange showed a better correlation with the average depth of amide residues calculated from reported X-ray crystallographic data for rhM-CSFalpha than with the average B-factor. The rates of H/D exchange in rhM-CSFbeta appear to correlate well with the exposed surface calculated for each amino acid residue in the crystal structure except for the alphaD helix. Fast hydrogen isotope exchange throughout the segment amino acids 150-221 present in rhM-CSFbeta, but not rhM-CSFalpha, provides evidence that the carboxy-terminal region is unstructured. It is, therefore, proposed that the anomalous behavior of the alphaD helix is due to interaction of the carboxy-terminal tail with this helical segment.