Quantitative analysis of SILAC data sets using spectral counting

We report a new quantitative proteomics approach that combines the best aspects of stable isotope labeling of amino acids in cell culture (SILAC) labeling and spectral counting. The SILAC peptide count ratio analysis (SPeCtRA, http://proteomics.mcw.edu/visualize ) method relies on MS² spectra rather than ion chromatograms for quantitation and therefore does not require the use of high mass accuracy mass spectrometers. The inclusion of a stable isotope label allows the samples to be combined before sample preparation and analysis, thus avoiding many of the sources of variability that can plague spectral counting. To validate the SPeCtRA method, we have analyzed samples constructed with known ratios of protein abundance. Finally, we used SPeCtRA to compare endothelial cell protein abundances between high (20 mM) and low (11 mM) glucose culture conditions. Our results demonstrate that SPeCtRA is a protein quantification technique that is accurate and sensitive as well as easy to automate and apply to high‐throughput analysis of complex biological samples.     

Exploring skyline for both MSE‐based label‐free proteomics and HRMS quantitation of small molecules

The MS^E (where MS^E is low energy (MS) and elevated energy (E) mode of acquisition) acquisition method commercialized by Waters on its Q‐TOF instruments is regarded as a unique data‐independent fragmentation approach that improves the accuracy and dynamic range of label‐free proteomic quantitation. Due to its special format, MS^E acquisition files cannot be independently analyzed with most widely used open‐source proteomic software specialized for processing data‐dependent acquisition files. In this study, we established a workflow integrating Skyline, a popular and versatile peptide‐centric quantitation program, and a statistical tool DiffProt to fulfill MS^E‐based proteomic quantitation. Comparison with the vendor software package for analyzing targeted phosphopeptides and global proteomic datasets reveals distinct advantages of Skyline in MS^E data mining, including sensitive peak detection, flexible peptide filtering, and transparent step‐by‐step workflow. Moreover, we developed a new procedure such that Skyline MS1 filtering was extended to small molecule quantitation for the first time. This new utility of Skyline was examined in a protein–ligand interaction experiment to identify multiple chemical compounds specifically bound to NDM‐1 (where NDM is New Delhi metallo‐β‐lactamase 1), an antibiotics‐resistance target. Further improvement of the current weaknesses in Skyline MS1 filtering is expected to enhance the reliability of this powerful program in full scan‐based quantitation of both peptides and small molecules.     

Label-free quantification and shotgun analysis of complex proteomes by one-dimensional SDS-PAGE/NanoLC-MS: evaluation for the large scale analysis of inflammatory human endothelial cells

To perform differential studies of complex protein mixtures, strategies for reproducible and accurate quantification are needed. Here, we evaluated a quantitative proteomic workflow based on nanoLC-MS/MS analysis on an LTQ-Orbitrap-VELOS mass spectrometer and label-free quantification using the MFPaQ software. In such label-free quantitative studies, a compromise has to be found between two requirements: repeatability of sample processing and MS measurements, allowing an accurate quantification, and high proteomic coverage of the sample, allowing quantification of minor species. The latter is generally achieved through sample fractionation, which may induce experimental bias during the label-free comparison of samples processed, and analyzed independently. In this work, we wanted to evaluate the performances of MS intensity-based label-free quantification when a complex protein sample is fractionated by one-dimensional SDS-PAGE. We first tested the efficiency of the analysis without protein fractionation and could achieve quite good quantitative repeatability in single-run analysis (median coefficient of variation of 5%, 99% proteins with coefficient of variation <48%). We show that sample fractionation by one-dimensional SDS-PAGE is associated with a moderate decrease of quantitative measurement repeatability while largely improving the depth of proteomic coverage. We then applied the method for a large scale proteomic study of the human endothelial cell response to inflammatory cytokines, such as TNFα, interferon γ, and IL1β, which allowed us to finely decipher at the proteomic level the biological pathways involved in endothelial cell response to proinflammatory cytokines.     

Two‐step OFFGEL approach for effective peptide separation compatible with iTRAQ labeling

Shotgun proteomic analyses are increasingly becoming methods of choice for complex samples. The development of effective methods for fractionating peptides to reduce the complexity of the sample before mass analysis is a key point in this strategy. The OFFGEL technology has recently become a tool of choice in proteomic analysis at peptide level. This OFFGEL electrophoresis (OGE) approach allows the in‐solution separation of peptides from various biological sources by isoelectric focusing in highly resolved 24 fractions. It was also demonstrated that OGE technology is a filtering tool for pI‐based validation of peptide identification. As peptide OGE is compatible with iTRAQ labeling, OGE is finding valuable applications in quantitative proteomics as well. The aim of this study is to explain a new 2D‐OGE approach that improves the proteomic coverage of complex mixtures such as colorectal cell line lysates, and which is compatible with iTRAQ labeling.     

Comparison of label-free and label-based strategies for proteome analysis of hepatoma cell lines

Within the past decade numerous methods for quantitative proteome analysis have been developed of which all exhibit particular advantages and disadvantages. Here, we present the results of a study aiming for a comprehensive comparison of ion-intensity based label-free proteomics and two label-based approaches using isobaric tags incorporated at the peptide and protein levels, respectively. As model system for our quantitative analysis we used the three hepatoma cell lines HepG2, Hep3B and SK-Hep-1. Four biological replicates of each cell line were quantitatively analyzed using an RPLC–MS/MS setup. Each quantification experiment was performed twice to determine technical variances of the different quantification techniques. We were able to show that the label-free approach by far outperforms both TMT methods regarding proteome coverage, as up to threefold more proteins were reproducibly identified in replicate measurements. Furthermore, we could demonstrate that all three methods show comparable reproducibility concerning protein quantification, but slightly differ in terms of accuracy. Here, label-free was found to be less accurate than both TMT approaches. It was also observed that the introduction of TMT labels at the protein level reduces the effect of underestimation of protein ratios, which is commonly monitored in case of TMT peptide labeling. Previously reported differences in protein expression between the particular cell lines were furthermore reproduced, which confirms the applicability of each investigated quantification method to study proteomic differences in such biological systems. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Evaluation of the accuracy of protein quantification using isotope TMPP‐labeled peptides

N‐succinimidyloxycarbonylmethyl tris(2,4,6‐trimethoxyphenyl) phosphonium bromide (TMPP‐Ac‐OSu) reacts rapidly, mildly, and specifically with the N‐terminals of proteins and peptides. Thus, it can be developed as an ideal isotope‐coded tag to be used in quantitative proteomics. Here, we present a strategy for light and heavy TMPP‐based quantitative proteomic analysis, in which peptides in a mixture can be quantified using an on‐tip TMPP derivatization approach. To demonstrate the accuracy of this strategy, light and heavy TMPP‐labeled peptides were combined at different ratios and subsequently analyzed by LC‐MS/MS. The MS spectra and scatter plots show that peptide and protein ratios were both consistent with the mixed ratios. We observed a linear correlation between protein ratios and the predicted ratios. In comparison with SILAC method, the TMPP labeling method produced similarly accurate quantitative results with low CVs. In conclusion, our results suggest that this isotope‐coded TMPP method achieved accurate quantification and compatibility with IEF‐based separation. With the inherent advantages of TMPP derivatization, we believe that it holds great promise for future applications in quantitative proteomics analysis.     

Chemical probes and tandem mass spectrometry: a strategy for the quantitative analysis of proteomes and subproteomes

Quantitative proteome profiling using mass spectrometry and stable isotope dilution is being widely applied for the functional analysis of biological systems and for the detection of clinical, diagnostic or prognostic marker proteins. Because of the enormous complexity of proteomes, their comprehensive analysis is unlikely to be routinely achieved in the near future. However, in recent years, significant progress has been achieved focusing quantitative proteomic analyses on specific protein classes or subproteomes that are rich in biologically or clinically important information. Such projects typically combine the use of chemical probes that are specific for a targeted group of proteins and may contain stable isotope signatures for accurate quantification with automated tandem mass spectrometry and bioinformatics tools for data analysis. In this review, we summarize technical and conceptual advances in quantitative subproteome profiling based on tandem mass spectrometry and chemical probes.     

Comprehensive Absolute Quantification of the Cytosolic Proteome of Bacillus subtilis by Data Independent,Parallel Fragmentation in Liquid Chromatography/Mass Spectrometry (LC/MSE)

In the growing field of systems biology, the knowledge of protein concentrations is highly required to truly understand metabolic and adaptational networks within the cells. Therefore we established a workflow relying on long chromatographic separation and mass spectrometric analysis by data independent, parallel fragmentation of all precursor ions at the same time (LC/MS^E). By prevention of discrimination of co-eluting low and high abundant peptides a high average sequence coverage of 40% could be achieved, resulting in identification of almost half of the predicted cytosolic proteome of the Gram-positive model organism Bacillus subtilis (>1,050 proteins). Absolute quantification was achieved by correlation of average MS signal intensities of the three most intense peptides of a protein to the signal intensity of a spiked standard protein digest. Comparative analysis with heavily labeled peptides (AQUA approach) showed the use of only one standard digest is sufficient for global quantification.The quantification results covered almost four orders of magnitude, ranging roughly from 10 to 150,000 copies per cell. To prove this method for its biological relevance selected physiological aspects of B. subtilis cells grown under conditions requiring either amino acid synthesis or alternatively amino acid degradation were analyzed. This allowed both in particular the validation of the adjustment of protein levels by known regulatory events and in general a perspective of new insights into bacterial physiology. Within new findings the analysis of “protein costs” of cellular processes is extremely important. Such a comprehensive and detailed characterization of cellular protein concentrations based on data independent, parallel fragmentation in liquid chromatography/mass spectrometry (LC/MS^E) data has been performed for the first time and should pave the way for future comprehensive quantitative characterization of microorganisms as physiological entities.In contrast to the rather static genome, composition of the proteome greatly varies with respect to environmental conditions (availability of nutrients, medium composition, stress, etc.) reflecting its key role in the adaptation of cells (1). Hence, proteome data for varying growth conditions should help to reach a comprehensive understanding of the physiology of adaptation to different nutritional conditions, which is the typical situation of bacterial cells in nature (2). In this context the availability of high quality absolute protein quantification data is of outstanding importance for the emerging field of systems biology because (a) proteins are major players for most biological processes and (b) their abundances decisively determine the adaptation rate of cellular processes. Additionally, an emerging set of theoretical and experimental works (reviewed in (3)) recently emphasized the importance of resource allocation in the growth rate management. Bacterial cells have to invest an available set of limited resources into biological processes to ensure growth and survival. Protein costs (or protein burden) of a biological process, defined as the total mass of proteins invested in the biological process, is then critical and must be finely tuned to sustain growth of bacteria. The determination of protein costs of different biological processes using genome-scale absolute protein quantification should thus represent a major breakthrough in understanding bacterial physiology and cellular design.For many years the gold standard for absolute protein quantification has been quantitative Western blotting and has been successfully applied, for example, to the yeast proteome (4). In recent years mass spectrometry based absolute proteome quantification techniques have become available allowing determination of cellular protein concentrations. The absolute protein amount can be precisely determined by spiking defined amounts of isotopically labeled synthetic peptides into a protein digest (5). Absolute protein amounts become available by detection and comparison of signal intensities of heavy and light peptides, but only for proteins related to the added synthetic peptides. This method was extended to a more global absolute quantification (AQUA)¹ by calibrating 2D gels with anchor proteins (6). Although the use of internal labeled standards for absolute protein quantification is very precise, availability and costs for such reference peptides are surely limiting. Therefore label free quantification techniques emerged. One of these methods is based on spectral counting. There, the number of sequenced peptides per protein is used to calculate the absolute quantity of one single protein in a complex sample (emPAI) (7). This can be refined by consideration of physicochemical properties of its peptides (APEX) (8, 9). Absolute protein quantification can also be achieved by comparing average signal intensities of the three most intense peptides per protein to an internally digested standard protein (Hi3 approach). Previous results showed that these average signal intensities per mole protein are constant within a tolerance of 10% (10). Recently the smart combination of AQUA technique and APEX approach was successfully applied to Leptospira interrogans covering about half of the proteome with an error less than threefold (11).In order to quantify the highest possible number of expressed proteins in an absolute manner mass spectrometry based methods seem to be the method of choice. Within the field of proteomics MS is often coupled with liquid chromatography to reduce sample complexity prior to MS analysis (LC/MS). Commonly applied data dependent acquisition (DDA) methods for peptide identification suffer from some limitations. Often low abundant peptides with a low MS signal intensity are discriminated and their isobaric precursor ions cannot be isolated leading to low scores in database search and wrong assignments (12, 13). These obstacles lead to lower protein sequence coverage in general and higher numbers of protein identifications based on a single peptide only. In contrast, with data independent acquisition (DIA) methods like LC/MS^E (14) all available precursor ions are fragmented in parallel without any selection by switching between low and high collision energy scans in high frequency. Therefore DIA can circumvent the disadvantages of DDA mentioned above. LC/MS^E utilizes chromatographic elution profiles of precursor masses to track the fragment ion spectra. Because all charge states and isotopic peaks of precursor ions are included for fragmentation (15) the LC/MS^E technique enables higher sequence coverage and has large advantages in the analysis of highly complex samples consisting of numerous co-eluting peptides (16). Combination of DIA methods with the approach based on Hi3 signal intensities was shown to be of potentially high performance for absolute protein quantification at global scale (17, 18) and is therefore used in this study.In this article, we applied a global absolute quantification approach based on the Hi3 method and data independent acquisition to the Gram-positive model bacterium Bacillus subtilis grown under two conditions for which large differences both in absolute protein amount per cell and in the predicted configurations of metabolic pathways were expected (19): a glucose and ammonia salts minimal medium (condition S) and a solely amino acid based medium (condition CH). This experimental set up enabled the physiologically meaningful comparison of profound consequences of growth under conditions requiring amino acid synthesis (S) or amino acid degradation (CH), as well as concerning the change between glycolytic (S) and gluconeogenic growth (CH). Moreover, as a model bacterium closely related to very important pathogens, B. subtilis is one of the best studied microorganisms. Particularly relevant for our study, the genomic organization of the chromosome, the regulatory network and metabolic pathways are well characterized. Based on this existing knowledge, global absolute protein quantification exemplary enabled (a) the large-scale investigation of protein distribution between cellular processes, (b) the systematic analysis of differential protein abundances for genes belonging to an operon (referred to as operon heterogeneity); and (c) the computation of the protein costs of cellular processes and of metabolic pathways in particular.     

Combination of online enzyme digestion with stable isotope labeling for high‐throughput quantitative proteome analysis

Various enzyme reactors and online enzyme digestion strategies have been developed in recent years. These reactors greatly enhanced the detection sensitivity and proteome coverage in qualitative proteomics. However, these devices have higher rates of miscleavage in protein digestion. Therefore, we investigated the effect of online enzyme digestion on the quantification accuracy of quantitative proteomics using chemical or metabolic isotope labeling approaches. The incomplete digestion would introduce some unexpected variations in comparative quantification when the samples are digested and then chemically isotope labeled in different aliquots. Even when identical protein aliquots are processed on these devices using post‐digestion chemical isotope labeling and the CVs of the ratios controlled to less than 50% in replicate analyses, about 10% of the quantified proteins have a ratio greater than two‐fold, whereas in theory the ratio is 1:1. Interestingly, the incomplete digestion with enzyme reactor is not a problem when metabolic isotope labeling samples were processed because the proteins are isotopically labeled in vivo prior to their simultaneous digestion within the reactor. Our results also demonstrated that both high quantification accuracy and high proteome coverage can be achieved in comparative proteome quantification using online enzyme digestion even when a limited amount of metabolic isotope labeling samples is used (1683 proteins comparatively quantified from 10⁵ Hela cells).     

Analysis of host-cell proteins in biotherapeutic proteins by comprehensive online two-dimensional liquid chromatography/mass spectrometry

Assays for identification and quantification of host-cell proteins (HCPs) in biotherapeutic proteins over 5 orders of magnitude in concentration are presented. The HCP assays consist of two types: HCP identification using comprehensive online two-dimensional liquid chromatography coupled with high resolution mass spectrometry (2D-LC/MS), followed by high-throughput HCP quantification by liquid chromatography, multiple reaction monitoring (LC-MRM). The former is described as a “discovery” assay, the latter as a “monitoring” assay. Purified biotherapeutic proteins (e.g., monoclonal antibodies) were digested with trypsin after reduction and alkylation, and the digests were fractionated using reversed-phase (RP) chromatography at high pH (pH 10) by a step gradient in the first dimension, followed by a high-resolution separation at low pH (pH 2.5) in the second dimension. As peptides eluted from the second dimension, a quadrupole time-of-flight mass spectrometer was used to detect the peptides and their fragments simultaneously by alternating the collision cell energy between a low and an elevated energy (MS^E methodology). The MS^E data was used to identify and quantify the proteins in the mixture using a proven label-free quantification technique (“Hi3” method). The same data set was mined to subsequently develop target peptides and transitions for monitoring the concentration of selected HCPs on a triple quadrupole mass spectrometer in a high-throughput manner (20 min LC-MRM analysis). This analytical methodology was applied to the identification and quantification of low-abundance HCPs in six samples of PTG1, a recombinant chimeric anti-phosphotyrosine monoclonal antibody (mAb). Thirty three HCPs were identified in total from the PTG1 samples among which 21 HCP isoforms were selected for MRM monitoring. The absolute quantification of three selected HCPs was undertaken on two different LC-MRM platforms after spiking isotopically labeled peptides in the samples. Finally, the MRM quantitation results were compared with TOF-based quantification based on the Hi3 peptides, and the TOF and MRM data sets correlated reasonably well. The results show that the assays provide detailed valuable information to understand the relative contributions of purification schemes to the nature and concentrations of HCP impurities in biopharmaceutical samples, and the assays can be used as generic methods for HCP analysis in the biopharmaceutical industry.Key words: host cell proteins, protein quantification, biotherapeutic proteins, mAbs, HCP     

A novel quantitative proteomics workflow by isobaric terminal labeling

Quantification by series of b, y fragment ion pairs generated from isobaric-labeled peptides in MS2 spectra has recently been considered an accurate strategy in quantitative proteomics. Here we developed a novel MS2 quantification approach named quantitation by isobaric terminal labeling (QITL) by coupling (18)O labeling with dimethylation. Trypsin-digested peptides were labeled with two (16)O or (18)O atoms at their C-termini in H(2)(16)O or H(2)(18)O. After blocking all ε-amino groups of lysines through guanidination, the N-termini of the peptides were accordingly labeled with formaldehyde-d(2) or formaldehyde. These indistinguishable, isobaric-labeled peptides in MS1 spectra produce b, y fragment ion pairs in the whole mass range of MS2 spectra that can be used for quantification. In this study, the feasibility of QITL was first demonstrated using standard proteins. An accurate and reproducible quantification over a wide dynamic range was achieved. Then, complex rat liver samples were used to verify the applicability of QITL for large-scale quantitative analysis. Finally, QITL was applied to profile the quantitative proteome of hepatocellular carcinoma (HCC) and adjacent non-tumor liver tissues. Given its simplicity, low-cost, and accuracy, QITL can be widely applied in biological samples (cell lines, tissues, and body fluids, etc.) for quantitative proteomic research.     

Reference map for liquid chromatography–mass spectrometry-based quantitative proteomics

The accurate mass and time (AMT) tag strategy has been recognized as a powerful tool for high-throughput analysis in liquid chromatography–mass spectrometry (LC–MS)-based proteomics. Due to the complexity of the human proteome, this strategy requires highly accurate mass measurements for confident identifications. We have developed a method of building a reference map that allows relaxed criteria for mass errors yet delivers high confidence for peptide identifications. The samples used for generating the peptide database were produced by collecting cysteine-containing peptides from T47D cells and then fractionating the peptides using strong cationic exchange chromatography (SCX). LC–tandem mass spectrometry (MS/MS) data from the SCX fractions were combined to create a comprehensive reference map. After the reference map was built, it was possible to skip the SCX step in further proteomic analyses. We found that the reference-driven identification increases the overall throughput and proteomic coverage by identifying peptides with low intensity or complex interference. The use of the reference map also facilitates the quantitation process by allowing extraction of peptide intensities of interest and incorporating models of theoretical isotope distribution.     

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high‐accuracy MS in combination with high‐resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism‐focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high‐resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.     

Targeted proteome investigation via selected reaction monitoring mass spectrometry

Due to the enormous complexity of proteomes which constitute the entirety of protein species expressed by a certain cell or tissue, proteome-wide studies performed in discovery mode are still limited in their ability to reproducibly identify and quantify all proteins present in complex biological samples. Therefore, the targeted analysis of informative subsets of the proteome has been beneficial to generate reproducible data sets across multiple samples. Here we review the repertoire of antibody- and mass spectrometry (MS) -based analytical tools which is currently available for the directed analysis of predefined sets of proteins. The topics of emphasis for this review are Selected Reaction Monitoring (SRM) mass spectrometry, emerging tools to control error rates in targeted proteomic experiments, and some representative examples of applications. The ability to cost- and time-efficiently generate specific and quantitative assays for large numbers of proteins and posttranslational modifications has the potential to greatly expand the range of targeted proteomic coverage in biological studies. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.     

Advances in quantitative proteomics via stable isotope tagging and mass spectrometry

The high-throughput identification and accurate quantification of proteins are essential components of proteomic strategies for studying cellular functions and processes. Techniques that are largely based on stable isotope protein or peptide labeling and automated tandem mass spectrometry are increasingly being applied in quantitative proteomic studies. Over the past year, significant progress has been made toward improving and diversifying these technologies with respect to the methods for stable isotope labeling, process automation and data processing and analysis. Advances in stable isotope protein labeling and recent biological studies that used stable isotope based quantitative proteomics techniques are reviewed.     

HTAPP: High‐throughput autonomous proteomic pipeline

Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab‐based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic data sets is critically important. The high‐throughput autonomous proteomic pipeline described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is composed of a software that controls the acquisition of mass spectral data along with automation of post‐acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user‐configurable lab‐based relational database. The software design of high‐throughput autonomous proteomic pipeline focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples.     

Development of advanced host cell protein enrichment and detection strategies to enable process relevant spike challenge studies

An orthogonal chromatography methodology for the enrichment of host cell protein (HCP) species relative to monoclonal antibody (mAb) products was developed and applied for the successful enrichment of HCP from post‐Protein A process pools for seven different mAb products. An advanced two‐dimensional liquid chromatography/mass spectrometry platform (2D‐LC/MS^E) was utilized to demonstrate that the HCP enriched material was representative, in terms of species content, to pre‐enriched process pools. The HCP enrichment methodology was scaled up for two different mAb products, and this process relevant enriched HCP material was used to conduct advanced spike challenge studies to demonstrate the utility of the approach for the understanding of (1) quantitative HCP clearance, (2) individual species clearance, and (3) species clearance redundancy across polishing chromatography steps. The combined ability to enrich process relevant HCP, detect individual HCP species with 2D‐LC/MS^E technology, and conduct advanced challenge studies with process relevant material surmounts prior limitations to high integrity process challenge study implementation, and facilitates significant process understanding for development of risk‐based control strategies and strategic process design. This also demonstrates implementation of a foundational strategy for conducting spike‐challenge studies using process‐relevant impurities isolated from processes of interest using orthogonal approaches. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:983–989, 2015