Rapid Characterization of Antibodies via Automated Flow Injection Coupled with Online Microdroplet Reactions and Native-pH Mass Spectrometry.

Microdroplet reactions have aroused much interest due to significant reaction acceleration (e.g., ultrafast protein digestion in microdroplets could occur in less than 1 ms). This study integrated a microdroplet protein digestion technique with automated sample flow injection and online mass spectrometry (MS) analysis, to develop a rapid and robust method for structural characterization of monoclonal antibodies (mAbs) that is essential to assess the antibody drug's safety and quality. Automated sequential aspiration and mixing of an antibody and an enzyme (IdeS or IgdE) enabled rapid analysis with high reproducibility (total analysis time: 2 min per sample; reproducibility: ∼2% coefficient of variation). Spraying the sample in ammonium acetate buffer (pH 7) using a jet stream source allowed efficient digestion of antibodies and efficient ionization of resulting antibody subunits under native-pH conditions. Importantly, it also provided a platform to directly study specific binding of an antibody and an antigen (e.g., detecting the complexes mAb/RSFV antigen and F(ab')2/RSVF in this study). Furthermore, subsequent tandem MS analysis of a resulting subunit from microdroplet digestion enabled localizing post-translational modifications on particular domains of a mAb in a rapid fashion. In combination with IdeS digestion of an antibody, additional tris(2-carboxyethyl)phosphine (TCEP) reduction and N-glycosidase F (PNGase F) deglycosylation reactions that facilitate antibody analysis could be realized in "one-pot" spraying. Interestingly, increased deglycosylation yield in microdroplets was found, simply by raising the sample temperature. We expect that our method would have a high impact for rapid characterization of monoclonal antibodies.

Mobile Affinity Selection Chromatography Analysis of Therapeutic Monoclonal Antibodies.

Federal regulatory agencies require continuous verification of recombinant therapeutic monoclonal antibody (mAb) quality that is commonly achieved in a two-step process. First, the host-cell proteome and metabolome are removed from the production medium by protein A affinity chromatography. Second, following recovery from the affinity column with an acidic wash, mAb quality is assessed in multiple ways by liquid chromatography-mass spectrometry (LC-MS). However, lengthy sample preparation and the lack of higher-order structure analyses are limitations of this approach. To address these issues, this report presents an integrated approach for the analysis of two critical quality attributes of mAbs, namely titer and relative aggregate content. Integration of sample preparation and molecular-recognition-based analyses were achieved in a single step utilizing an isocratically eluted mobile affinity selection chromatography (MASC) column. MASC circumvents the protein A step, simplifying sample preparation. Within 10 min, (i) mAbs are fluorescently coded for specific detection, (ii) monomers and aggregates are resolved, (iii) the mAb titer is quantified, (iv) relative aggregate content is determined, (v) analytes are detected, and (vi) the column is ready for the next sample. It is suggested herein that this mode of rapid quality assessment will be of value at all stages of discovery (screening, clone selection, characterization), process R&D, and manufacturing. Rapid monitoring of variant formation is a critical element of quality evaluation.

Standard-Free Absolute Quantitation of Antibody Deamidation Degradation and Host Cell Proteins by Coulometric Mass Spectrometry.

Proteomic absolute quantitation strategies mainly rely on the use of synthetic stable isotope-labeled peptides or proteins as internal standards, which are highly costly and time-consuming to synthesize. To circumvent this limitation, we recently developed a coulometric mass spectrometry (CMS) approach for absolute quantitation of proteins without the use of standards, based on the electrochemical oxidation of oxidizable surrogate peptides, followed by mass spectrometry measurement of the peptide oxidation yield. Previously, CMS was only applied for single-protein quantitation. In this study, first, we demonstrated absolute quantitation of multiple proteins in a mixture (e.g., ß-lactoglobulin B, α-lactalbumin, and carbonic anhydrase) by CMS in one run, without using any standards. The CMS quantitation result was validated with a traditional isotope dilution method. Second, CMS can be used for absolute quantitation of a low-level target protein in a mixture; for instance, 500 ppm of PLBL2, a problematic host cell protein (HCP), in the presence of a highly abundant monoclonal antibody (mAb) was successfully quantified by CMS with no use of standards. Third, taking one step further, this study demonstrated the unprecedented quantitative analysis of deamidated peptide products arising from the mAb heavy chain deamidation reaction. In particular, absolute quantitation of the deamidation succinimide intermediate which had not been performed before due to the lack of standard was conducted by CMS, for the first time. Overall, our data suggest that CMS has potential utilities for quantitative proteomics and biotherapeutic drug discovery.

Microdroplet Ultrafast Reactions Speed Antibody Characterization.

Recently, microdroplet reactions have aroused much interest because the microdroplet provides a unique medium where organic reactions could be accelerated by a factor of 103 or more. However, microdroplet reactions of proteins have been rarely studied. We report the occurrence of multiple-step reactions of a large protein, specifically, the digestion, reduction, and deglycosylation of an intact antibody, which can take place in microseconds with high reaction yields in aqueous microdroplets at room temperature. As a result, fast structural characterization of a monoclonal antibody, essential for assessing its quality as a therapeutic drug, can be enabled. We found that the IgG1 antibody can be digested completely by the IdeS protease in aqueous microdroplets in 250 microseconds, a 7.5 million-fold improvement in speed in comparison to traditional digestion in bulk solution (>30 min). Strikingly, inclusion of the reductant tris(2-carboxyethyl)phosphine in the spray solution caused simultaneous antibody digestion and disulfide bond reduction. Digested and reduced antibody fragments were either collected or analyzed online by mass spectrometry. Further addition of PNGase F glycosylase into the spray solution led to antibody deglycosylation, thereby producing reduced and deglycosylated fragments of analytical importance. In addition, glycated fragments of IgG1 derived from glucose modification were identified rapidly with this ultrafast digestion/reduction technique. We suggest that microdroplets can serve as powerful microreactors for both exploring large-molecule reactions and speeding their structural analyses.

Desalting Paper Spay Mass Spectrometry (DPS-MS) for Rapid Detection of Glycans and Glycoconjugates.

The detection of glycans and glycoconjugates has gained increasing attention in biological fields. Traditional mass spectrometry (MS)-based methods for glycoconjugate analysis are challenged with poor intensity when dealing with complex biological samples. We developed a desalting paper spray mass spectrometry (DPS-MS) strategy to overcome the issue of signal suppression of carbohydrates in salted buffer. Glycans and glycoconjugates (i.e., glycopeptides, nucleotide sugars, etc.) in non-volatile buffer (e.g., Tris buffer) can be loaded on the paper substrate from which buffers can be removed by washing with ACN/H2O (90/10 v/v) solution. Glycans or glycoconjugates can then be eluted and spray ionized by adding ACN/H2O/formic acid (FA) (10/90/1 v/v/v) solvent and applying a high voltage (HV) to the paper substrate. This work also showed that DPS-MS is applicable for direct detection of intact glycopeptides and nucleotide sugars as well as determination of glycosylation profiling of antibody, such as NIST monoclonal antibody IgG (NISTmAb). NISTmAb was deglycosylated with PNGase F to release N-linked oligosaccharides. Twenty-six N-linked oligosaccharides were detected by DPS-MS within a 5-minute timeframe without the need for further enrichment or derivatization. This work demonstrates that DPS-MS allows fast and sensitive detection of glycans/oligosaccharides and glycosylated species in complex matrices and has great potential in bioanalysis.

Rapid and Simultaneous Characterization of Drug Conjugation in Heavy and Light Chains of a Monoclonal Antibody Revealed by High-Resolution Ion Mobility Separations in SLIM.

Antibody-drug conjugates (ADCs) have recently gained traction in the biomedical community due to their promise for human therapeutics and an alternative to chemotherapy for cancer. Crucial metrics for ADC efficacy, safety, and selectivity are their drug-antibody ratios (DARs). However, DAR characterization (i.e., determining the average number of conjugated drugs on the antibody) through analytical methods remains challenging due to the heterogeneity of drug conjugation as well as the numerous post-translational modifications possible in the monoclonal antibody. Herein, we report on the use of high-resolution ion mobility spectrometry separations in structures for lossless ion manipulations coupled to mass spectrometry (SLIM IMS-MS) for the rapid and simultaneous characterization of the drug load profile (i.e., stoichiometric distribution of the number of conjugated drugs present on the mAb), determination of the weighted average DAR in both the heavy and light chains of a model antibody-drug conjugate, and calculation of the overall DAR of the ADC. After chemical reduction of the ADC and a subsequent 31.5 m SLIM IMS separation, the various drug-bound antibody species could be well resolved for both chains. We also show significantly higher resolution separations were possible for these large ions with SLIM IMS as compared to ones performed on a commercially available (1 m) drift tube IMS-MS platform. We expect high-resolution SLIM IMS separations will augment the existing toolbox for ADC characterization, particularly to enable the rapid optimization of DAR for a given ADC and thus better understand its potential toxicity and potency.

Row versus column correlations: avoiding the ecological fallacy in RNA/protein expression studies.

Biomedical researchers are often interested in computing the correlation between RNA and protein abundance. However, correlations can be computed between rows of a data matrix or between columns, and the results are not the same. The belief that these two types of correlation are estimating the same phenomenon is a special case of a well-known logical error called the ecological fallacy. In this article, we review different uses of correlation found in the literature, explain the differences between row and column correlations and argue that one of them has an undesirable interpretation in most applications. Through simulation studies and theoretical derivations, we show that the commonly used Pearson's coefficient, computed from protein and transcript data from a single sample, is only loosely related to the biological correlation that most researchers will be interested in studying. Beyond our basic exploration of the ecological fallacy, we examine how correlations are affected by relative quantification proteomics data and common normalization procedures, finding that double normalization is capable of completely masking true correlative relationships. We conclude with guidelines for properly identifying and computing consistent correlation coefficients.

Micro-Data-Independent Acquisition for High-Throughput Proteomics and Sensitive Peptide Mass Spectrum Identification.

State-of-the-art strategies for proteomics are not able to rapidly interrogate complex peptide mixtures in an untargeted manner with sensitive peptide and protein identification rates. We describe a data-independent acquisition (DIA) approach, microDIA (µDIA), that applies a novel tandem mass spectrometry (MS/MS) mass spectral deconvolution method to increase the specificity of tandem mass spectra acquired during proteomics experiments. Using the µDIA approach with a 10 min liquid chromatography gradient allowed detection of 3.1-fold more HeLa proteins than the results obtained from data-dependent acquisition (DDA) of the same samples. Additionally, we found the µDIA MS/MS deconvolution procedure is critical for resolving modified peptides with relatively small precursor mass shifts that cause the same peptide sequence in modified and unmodified forms to theoretically cofragment in the same raw MS/MS spectra. The µDIA workflow is implemented in the PROTALIZER software tool which fully automates tandem mass spectral deconvolution, queries every peptide with a library-free search algorithm against a user-defined protein database, and confidently identifies multiple peptides in a single tandem mass spectrum. We also benchmarked µDIA against DDA using a 90 min gradient analysis of HeLa and Escherichia coli peptides that were mixed in predefined quantitative ratios, and our results showed µDIA provided 24% more true positives at the same false positive rate.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer.

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (∼80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis.

Label-free Quantitative Proteomics Reveals a Role for the Mycobacterium tuberculosis SecA2 Pathway in Exporting Solute Binding Proteins and Mce Transporters to the Cell Wall.

Mycobacterium tuberculosis is an example of a bacterial pathogen with a specialized SecA2-dependent protein export system that contributes to its virulence. Our understanding of the mechanistic basis of SecA2-dependent export and the role(s) of the SecA2 pathway in M. tuberculosis pathogenesis has been hindered by our limited knowledge of the proteins exported by the pathway. Here, we set out to identify M. tuberculosis proteins that use the SecA2 pathway for their export from the bacterial cytoplasm to the cell wall. Using label-free quantitative proteomics involving spectral counting, we compared the cell wall and cytoplasmic proteomes of wild type M. tuberculosis to that of a ΔsecA2 mutant. This work revealed a role for the M. tuberculosis SecA2 pathway in the cell wall localization of solute binding proteins that work with ABC transporters to import solutes. Another discovery was a profound effect of SecA2 on the cell wall localization of the Mce1 and Mce4 lipid transporters, which contribute to M. tuberculosis virulence. In addition to the effects on solute binding proteins and Mce transporter export, our label-free quantitative analysis revealed an unexpected relationship between SecA2 and the hypoxia-induced DosR regulon, which is associated with M. tuberculosis latency. Nearly half of the transcriptionally controlled DosR regulon of cytoplasmic proteins were detected at higher levels in the ΔsecA2 mutant versus wild type M. tuberculosis. By increasing the list of M. tuberculosis proteins known to be affected by the SecA2 pathway, this study expands our appreciation of the types of proteins exported by this pathway and guides our understanding of the mechanism of SecA2-dependent protein export in mycobacteria. At the same time, the newly identified SecA2-dependent proteins are helpful for understanding the significance of this pathway to M. tuberculosis virulence and physiology.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts.

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Modulation of B-cell exosome proteins by gamma herpesvirus infection.

The human gamma herpesviruses, Kaposi sarcoma-associated virus (KSHV) and EBV, are associated with multiple cancers. Recent evidence suggests that EBV and possibly other viruses can manipulate the tumor microenvironment through the secretion of specific viral and cellular components into exosomes, small endocytically derived vesicles that are released from cells. Exosomes produced by EBV-infected nasopharyngeal carcinoma cells contain high levels of the viral oncogene latent membrane protein 1 and viral microRNAs that activate critical signaling pathways in recipient cells. In this study, to determine the effects of EBV and KSHV on exosome content, quantitative proteomics techniques were performed on exosomes purified from 11 B-cell lines that are uninfected, infected with EBV or with KSHV, or infected with both viruses. Using mass spectrometry, 871 proteins were identified, of which ∼360 were unique to the viral exosomes. Analysis by 2D difference gel electrophoresis and spectral counting identified multiple significant changes compared with the uninfected control cells and between viral groups. These data predict that both EBV and KSHV exosomes likely modulate cell death and survival, ribosome function, protein synthesis, and mammalian target of rapamycin signaling. Distinct viral-specific effects on exosomes suggest that KSHV exosomes would affect cellular metabolism, whereas EBV exosomes would activate cellular signaling mediated through integrins, actin, IFN, and NFκB. The changes in exosome content identified in this study suggest ways that these oncogenic viruses modulate the tumor microenvironment and may provide diagnostic markers specific for EBV and KSHV associated malignancies.

Long noncoding RNAs are rarely translated in two human cell lines.

Data from the Encyclopedia of DNA Elements (ENCODE) project show over 9640 human genome loci classified as long noncoding RNAs (lncRNAs), yet only ~100 have been deeply characterized to determine their role in the cell. To measure the protein-coding output from these RNAs, we jointly analyzed two recent data sets produced in the ENCODE project: tandem mass spectrometry (MS/MS) data mapping expressed peptides to their encoding genomic loci, and RNA-seq data generated by ENCODE in long polyA+ and polyA- fractions in the cell lines K562 and GM12878. We used the machine-learning algorithm RuleFit3 to regress the peptide data against RNA expression data. The most important covariate for predicting translation was, surprisingly, the Cytosol polyA- fraction in both cell lines. LncRNAs are ~13-fold less likely to produce detectable peptides than similar mRNAs, indicating that ~92% of GENCODE v7 lncRNAs are not translated in these two ENCODE cell lines. Intersecting 9640 lncRNA loci with 79,333 peptides yielded 85 unique peptides matching 69 lncRNAs. Most cases were due to a coding transcript misannotated as lncRNA. Two exceptions were an unprocessed pseudogene and a bona fide lncRNA gene, both with open reading frames (ORFs) compromised by upstream stop codons. All potentially translatable lncRNA ORFs had only a single peptide match, indicating low protein abundance and/or false-positive peptide matches. We conclude that with very few exceptions, ribosomes are able to distinguish coding from noncoding transcripts and, hence, that ectopic translation and cryptic mRNAs are rare in the human lncRNAome.

Standards-Free Absolute Quantitation of Oxidizable Glycopeptides by Coulometric Mass Spectrometry.

Currently, glycopeptide quantitation is mainly based on relative quantitation due to absolute quantitation requiring isotope-labeled or standard glycopeptides which may not be commercially available or are very costly and time consuming to synthesize. To address this grand challenge, coulometric mass spectrometry (CMS), based on the combination of electrochemistry (EC) and mass spectrometry (MS), was utilized to quantify electrochemically active glycopeptides without the need of using standard materials. In this study, we studied tyrosine-containing glycopeptides, NYIVGQPSS(ß-GlcNAc)TGNL-OH and NYSVPSS(ß-GlcNAc)TGNL-OH, and successfully quantified them directly with CMS with a discrepancy of less than 5% between the CMS measured amount and the theoretical amount. Taking one step further, we applied this approach to quantify glycopeptides generated from the digestion of NIST mAb, a monoclonal antibody reference material. Through HILIC column separation, five N297 glycopeptides resulting from NIST mAb tryptic digestion were successfully separated and quantified by CMS for an absolute amount without the use of any standard materials. This study indicates the potential utility of CMS for quantitative proteomics research.

Comparison of the membrane proteome of virulent Mycobacterium tuberculosis and the attenuated Mycobacterium bovis BCG vaccine strain by label-free quantitative proteomics.

The Mycobacterium tuberculosis membrane is rich in antigens that are potential targets for diagnostics and the development of new vaccines. To better understand the mechanisms underlying MTB virulence and identify new targets for therapeutic intervention, we investigated the differential composition of membrane proteomes between virulent M. tuberculosis H37Rv (MTB) and the Mycobacterium bovis BCG vaccine strain. To compare the membrane proteomes, we used LC-MS/MS analysis in combination with label-free quantitative proteomics, utilizing the area under the curve of the extracted ion chromatograms of peptides obtained from m/z and retention time alignment of MS1 features. With this approach, we obtained relative abundance ratios for 2203 identified membrane-associated proteins in high confidence. Of these proteins, 294 showed statistically significant differences of at least two fold in relative abundance between MTB and BCG membrane fractions. Our comparative analysis detected several proteins associated with known genomic regions of difference between MTB and BCG as being absent, which validated the accuracy of our approach. In further support of our label-free quantitative data, we verified select protein differences by immunoblotting. To our knowledge, we have generated the first comprehensive and high-coverage profile of comparative membrane proteome changes between virulent MTB and its attenuated relative BCG, which helps elucidate the proteomic basis of the intrinsic virulence of the MTB pathogen.

Whole human genome proteogenomic mapping for ENCODE cell line data: identifying protein-coding regions.

BACKGROUND: Proteogenomic mapping is an approach that uses mass spectrometry data from proteins to directly map protein-coding genes and could aid in locating translational regions in the human genome. In concert with the ENcyclopedia of DNA Elements (ENCODE) project, we applied proteogenomic mapping to produce proteogenomic tracks for the UCSC Genome Browser, to explore which putative translational regions may be missing from the human genome. RESULTS: We generated ~1 million high-resolution tandem mass (MS/MS) spectra for Tier 1 ENCODE cell lines K562 and GM12878 and mapped them against the UCSC hg19 human genome, and the GENCODE V7 annotated protein and transcript sets. We then compared the results from the three searches to identify the best-matching peptide for each MS/MS spectrum, thereby increasing the confidence of the putative new protein-coding regions found via the whole genome search. At a 1% false discovery rate, we identified 26,472, 24,406, and 13,128 peptides from the protein, transcript, and whole genome searches, respectively; of these, 481 were found solely via the whole genome search. The proteogenomic mapping data are available on the UCSC Genome Browser at http://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeUncBsuProt. CONCLUSIONS: The whole genome search revealed that ~4% of the uniquely mapping identified peptides were located outside GENCODE V7 annotated exons. The comparison of the results from the disparate searches also identified 15% more spectra than would have been found solely from a protein database search. Therefore, whole genome proteogenomic mapping is a complementary method for genome annotation when performed in conjunction with other searches.

Reversible acetylation regulates acetate and propionate metabolism in Mycobacterium smegmatis.

Carbon metabolic pathways are important to the pathogenesis of Mycobacterium tuberculosis, the causative agent of tuberculosis. However, extremely little is known about metabolic regulation in mycobacteria. There is growing evidence for lysine acetylation being a mechanism of regulating bacterial metabolism. Lysine acetylation is a post-translational modification in which an acetyl group is covalently attached to the side chain of a lysine residue. This modification is mediated by acetyltransferases, which add acetyl groups, and deacetylases, which remove the acetyl groups. Here we set out to test whether lysine acetylation and deacetylation impact acetate metabolism in the model mycobacteria Mycobacterium smegmatis, which possesses 25 candidate acetyltransferases and 3 putative lysine deacetylases. Using mutants lacking predicted acetyltransferases and deacetylases we showed that acetate metabolism in M. smegmatis is regulated by reversible acetylation of acetyl-CoA synthetase (Ms-Acs) through the action of a single pair of enzymes: the acetyltransferase Ms-PatA and the sirtuin deacetylase Ms-SrtN. We also confirmed that the role of Ms-PatA in regulating Ms-Acs regulation depends on cAMP binding. We additionally demonstrated a role for Ms-Acs, Ms-PatA and Ms-SrtN in regulating the metabolism of propionate in M. smegmatis. Finally, along with Ms-Acs, we identified a candidate propionyl-CoA synthetase, Ms5404, as acetylated in whole-cell lysates. This work lays the foundation for studying the regulatory circuit of acetylation and deacetylation in the cellular context of mycobacteria.

Diagnostic utility of N-terminal TMPP labels for unambiguous identification of clipped sites in therapeutic proteins.

Protein therapeutics are susceptible to clipping via enzymatic and nonenzymatic mechanisms that create neo-N-termini. Typically, neo-N-termini are identified by chemical derivatization of the N-terminal amine with (N-Succinimidyloxycarbonylmethyl)tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP) followed by proteolysis and mass spectrometric analysis. Detection of the TMPP-labeled peptide is achieved by mapping the peptide sequence to the product ion spectrum derived from collisional activation. The site-specific localization of the TMPP tag enables unambiguous determination of the true N-terminus or neo-N-termini. In addition to backbone product ions, TMPP reporter ions at m/z 573, formed via collision-induced dissociation, can be diagnostic for the presence of a processed N-termini. However, reporter ions generated by collision-induced dissociation may be uninformative because of their low abundance. We demonstrate a novel high-throughput LC-MS method for the facile generation of the TMPP reporter ion at m/z 533 and, in some instances m/z 590, upon electron transfer dissociation. We further demonstrate the diagnostic utility of TMPP labeled peptides derived from a total cell lysate shows high degree of specificity towards selective N-terminal labeling over labeling of lysine and tyrosine and highly-diagnostic Receiver Operating Characteristic's (ROC) of TMPP reporter ions of m/z 533 and m/z 590. The abundant generation of these reporters enables subsequent MS/MS by intensity and m/z-dependent triggering of complementary ion activation modes such as collision-induced dissociation, high-energy collision dissociation, or ultraviolet photo dissociation for subsequent peptide sequencing.

"Lab of the Future"─Today: Fully Automated System for High-Throughput Mass Spectrometry Analysis of Biotherapeutics.

Here we describe a state-of-the-art, integrated, multi-instrument automated system designed to execute methods involved in mass spectrometry characterization of biotherapeutics. The system includes liquid and microplate handling robotics and utilities, integrated LC-MS, along with data analysis software, to perform sample purification, preparation, and analysis as a seamless integrated unit. The automated process begins with tip-based purification of target proteins from expression cell-line supernatants, which is initiated once the samples are loaded onto the automated system and the metadata are retrieved from our corporate data aggregation system. Subsequently, the purified protein samples are prepared for MS, including deglycosylation and reduction steps for intact and reduced mass analysis, and proteolytic digestions, desalting, and buffer exchange via centrifugation for peptide map analysis. The prepared samples are then loaded into the LC-MS instrumentation for data acquisition. The acquired raw data are initially stored on a local area network storage system that is monitored by watcher scripts that then upload the raw MS data to a network of cloud-based servers. The raw MS data are processed with the appropriately configured analysis workflows such as database search for peptide mapping or charge deconvolution for undigested proteins. The results are verified and formatted for expert curation directly in the cloud. Finally, the curated results are appended to sample metadata in the corporate data aggregation system to accompany the biotherapeutic cell lines in subsequent processes.