Targeted Proteomics of Human Metapneumovirus in Clinical Samples

Sep 16, 2015 - The rapid, sensitive, and specific identification of infectious pathogens from clinical isolates is a critical need in the hospital set...
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Targeted proteomics of human metapneumovirus in clinical samples and viral cultures Matthew W Foster, Geoff C. Gerhardt, Lynda Robitaille, PierLuc PLante, Guy Boivin, Jacques Corbeil, and M. Arthur Moseley Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.5b01544 • Publication Date (Web): 16 Sep 2015 Downloaded from http://pubs.acs.org on September 17, 2015

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Targeted proteomics of human metapneumovirus in clinical samples and viral cultures Matthew W. Foster†,§, Geoff Gerhardt¶, Lynda Robitaille║, Pier-Luc Plante║ Guy Boivin║, Jacques Corbeil║& and M. Arthur Moseley†&



Proteomics and Metabolomics Shared Resource, and §Department of Medicine, Duke University Medical

Center, Durham NC 27710; ¶Waters Corporation, Milford MA;



Department of Molecular Medicine,

Department of Microbiology, Immunology and Infectious Diseases, Université Laval, Québec, Canada

& These authors contributed equally to this work. *To whom correspondence should be addressed: Email: [email protected]

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ABSTRACT The rapid, sensitive and specific identification of infectious pathogens from clinical isolates is a critical need in the hospital setting. Mass spectrometry (MS) has been widely adopted for identification of bacterial pathogens, although polymerase chain reaction remains the mainstay for the identification of viral pathogens. Here, we explored the capability of MS for the detection of human metapneumovirus (HMPV), a common cause of respiratory tract infections in children. Liquid chromatography, tandem mass spectrometry (LC-MS/MS) sequencing of a single HMPV reference strain (CAN97-83) was used to develop a multiple reaction monitoring (MRM) assay, that employed stable isotope-labeled peptide internal standards, for quantitation of HMPV. Using this assay, we confirmed the presence of HMPV in viral cultures from 10 infected patients and further assigned genetic lineage based on the presence/absence of variant peptides belonging to the viral matrix and nucleoproteins. Similar results were achieved for primary clinical samples (nasopharyngeal aspirates) from the same individuals. As validation, virus lineages, and variant coding sequences, were confirmed by nextgeneration sequencing of viral RNA obtained from the culture samples. Finally, separate dilution series of HMPV A and B lineages were used to further refine and assess the robustness of the assay, and to determine limits of detection in nasopharyngeal aspirates. Our results demonstrate the applicability of MRM for identification of HMPV, and assignment of genetic lineage, from both viral cultures and clinical samples. More generally, this approach should prove tractable as an alternative to nucleic-acid based sequencing for the multiplexed identification of respiratory virus infections.

KEYWORDS: paramyxovirus, influenza, selected reaction monitoring, proteotype, RNA-Seq 2

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INTRODUCTION The rapid, sensitive and specific diagnosis of respiratory and blood-borne pathogens is recognized to be critical for long-term improvements in patient care and to identify and respond to emerging pathogens and outbreaks. For example, tests that can provide rapid, point-of-care, and/or unambiguous discrimination of viral versus bacterial infection could minimize the unnecessary use of antibiotics such as vancomycin and help to prevent the spread of vancomycin-resistant enterococci. The lack of available point-of-care tests was also evident in the recent outbreaks of enterovirus D68 (EV-D68)1,2 and Ebola virus.3 There have been numerous advances in the use of polymerase chain reaction (PCR) and other nucleic-acid based technologies for the multiplexed detection of respiratory pathogens and associated antiviral and antimicrobial resistance genes.4,5 While immunoassays have been long-employed in pathogen detection, it has been less clear whether newer proteomic technologies can provide similar sensitivity and specificity. Mass spectrometry-based methods have recently gained a foothold in clinical detection of bacterial pathogens and are poised to become the new gold standard.6 Matrix-assisted laser desorption ionization–timeof-flight MS (MALDI-TOF-MS) is implemented in several commercial platforms (e.g. Bruker Biotyper; bioMérieux Vitek MS) for the identification of bacterial pathogens in cultures grown from clinical isolates. These instruments match intact peptide/protein MS spectra to a spectral database (i.e. peptide mass fingerprinting) and have identification rates and turnaround times that are on par with, or eclipse conventional microbiology workflows. MS has also been implemented for the identification of bacteria and viruses by polymerase chain reaction (PCR) coupled to electrospray ionization MS (ESI-MS).7 PCR/ESI-MS (e.g. Abbott Plex-ID) uses amplification of conserved regions of genomic DNA or cDNA followed by spectral matching species-specific identification. Alternatively, mass spectrometry-based comparative sequence analysis (MSCSA) utilizes PCR amplification and RNA transcription, followed by base-specific cleavage of RNA and MALDI-TOF MS for viral genotyping. The use of PCR amplification enables PCR/ESI-MS and MSCSA to be performed on clinical specimens without the requirement for viral or microbiological culturing. In contrast to the aforementioned techniques, bottom-up (“shotgun”) MS-based pathogen identification and quantitation have largely been confined to a few respiratory pathogens, namely influenza virus. Downard 3

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and colleagues have utilized trypsin digestion, followed by MALDI-TOF or MALDI fourier-transform ion cyclotron resonance (MALDI-FT-ICR) for the identification of influenza species, and subtypes, based on spectral matching to viral proteins (e.g. hemagglutinin (HA) and neuraminidase (NA)).8-12 Although this method appears suitable for proteotyping of virus purified from cultures, it is unclear how it would perform within the background of a complex biological matrix. Alternatively, Williams and colleagues have utilized multiple reaction monitoring (MRM) with stable isotope labeled (SIL) peptide standards (i.e. isotope dilution MS) for the quantification of strain-specific influenza HA and NA antigens that is a critical need for quality control and timely vaccine production.13-15 While MRM promises high specificity and sensitivity, based on the use of SIL standards and triple quadrupole tandem MS, it has not been applied to the identification and quantitation of viral pathogens in clinical specimens or in primary laboratory cultures. Human metapneumovirus (HMPV) is one of the leading causes of acute respiratory tract infections in young children and the elderly.16 HMPV replicates very slowly in cell culture, and development of cytopathic effects is highly cell-line dependent;17 these challenges have necessitated the development of alternative disgnostics (e.g. RT-PCR-based assays).18,19 Here, as a proof-of-concept, we sought to develop a novel MRM assay for HMPV and to determine whether this assay could detect HMPV infection in human clinical samples.

MATERIALS AND METHODS Samples. All studies were approved by the Laval University Institutional Review Board. Reference HMPV strains, CAN97-83 (NC_004148), C-8547320 and CAN98-7521 were used to infect LLC-MK2 cells (ATCC) grown in Opti-MEM (Life Technologies) and the supernatant containing the virus was collected and stored at 80 ºC. Plaque-forming units (PFU) and 50% cell culture infectious dose (TCID50) were determined by cytopathology using LLC-MK2 cells. Nasopharyngeal aspirates and corresponding viral cultures from HMPVpositive patients were obtained from the clinical virology laboratory at Centre Hospitalier Universitaire de Quebec in Quebec City, Canada. Viral cultures were obtained by inoculating LLC-MK2 cells in 1 ml of virus infection media (Opti-MEM containing 0.2% glucose, 0.1% bovine serum albumin, 0.0002% trypsin)20 with

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100 µl of nasopharyngeal aspirates (NPA). Virus-containing samples were heat inactivated (95 °C for 10 min)22 prior to handling for proteomic analysis and stored at -80 °C. Sample Preparation. Purified viruses were desalted using Zeba™ Spin 7K MCCO desalting columns (Life Technologies), and heat-inactivated NPA or virus culture media (VC; 200 µl each sample) were subjected to concentration and buffer exchange with ammonium bicarbonate, pH 8.0 (AmBic) by centrifugal filtration using an Amicon Ultra 0.5 ml filter with a 10 kDa cut-off (Millipore). After Bradford assay, 10 µgs of protein were denatured and reduced by adding 0.2% Rapigest SF (Waters) and 10 mM DTT followed by heating at 80 ºC for 10 min. Next, the samples were mixed with 20 mM iodoacetamide at room temperature in the dark for 30 min and then digested with Sequencing Grade Modified Trypsin (Promega) at 1:50 (w/w) trypsin:protein overnight at 37 ºC. After digestion, 50 fmol/µg of trypsinized yeast alcohol dehydrogenase 1 (MassPREP ADH, Waters) were added as a surrogate standard to each sample, and samples were acidified to 1% trifluoroacetic acid (TFA) then incubated at 60 ºC for 2 h. After centrifugation, samples were transferred to Maximum Recovery LC vials (Waters). To generate calibration curves, titrated HMPV lineage A (C-85473; 8 x 106 PFU/ml; 1.6 x 107 TCID50/ml) and lineage B (CAN98-75; 5 x 105 PFU/ml; 4 x 106 TCID50/ml) were desalted as above followed by a Bradford assay to determine PFU/µg of total protein. Next, 1000, 200, 100, 20, 10, 2, 1, 0.2, 0.1 and 0 PFU of HMPV A, and 100, 20, 10, 2, 1, 0.2, 0.1, 0.02, 0.01 and 0 PFU of HMPV B, were added to 2.5 µg NPA per sample, followed by reduction/alkylation and trypsin digestion as described above. Finally, digested Spiketides TQL peptides (JPT; Berlin, DE)23 and MassPREP ADH were added at final concentrations of 10 fmol per µg. LC-MS/MS sequencing of HMPV. One-dimensional liquid chromatography, tandem mass spectrometry (1DLC-MS/MS) was performed on 1 µg of HMPV tryptic digests using a nanoACQUITY UPLC system (Waters) coupled to a Synapt G2 HDMS (Waters) via a nanoelectrospray ionization source. Trapping used a Symmetry C18 300 mm × 180 mm column (5 µl/min at 99.9/0.1 v/v H2O/MeCN), and the analytical separation was performed with a 75 µm × 250 mm, 1.8 µm particle, ACQUITY HSS T3 column (Waters) using a 90 min gradient of 5 to 40% MeCN with 0.1% formic acid at a flow rate of 400 nl/min and column temperature of 55 °C. Data collection in data-dependent acquisition (DDA) mode used 0.6 s MS scan followed by MS/MS 5

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acquisition on the top 3 ions with charge greater than 1, and in ion-mobility assisted data-independent acquisition (HDMSE) mode used a 0.6 s alternating cycle time between low (6V) and high (27-50V) collision energy (CE). DDA data was processed using Mascot Distiller v2.4 (Matrix Science), and HDMSE data was searched using ProteinLynx Global Server v2.5.2 (PLGS; Waters). Database searches used a custom Swiss-Prot database with human taxonomy (downloaded on 04/25/13) and containing additional entries for yeast ADH1 and selected respiratory viruses, as well as an equal number of reverse entries for false discovery rate determination (40,878 total entries). Data was searched with fixed modification on Cys (carbamidomethyl) and variable modifications on Met (oxidation) and Asn/Gln (deamidation) and was annotated with a 1% peptide false-discovery rate in Scaffold (Proteome Software). Quantitation of viral proteins by multiple reaction monitoring (MRM). Five hundred ng of tryptic digests, containing SIL peptides, were separated using a nanoACQUITY UPLC (Waters) as described above except that a 30 min gradient of 5-40% ACN was used for the analytical separation. The LC was interfaced to a Waters Xevo TQ-S via a nanoelectrospray source. Method generation and data analysis were performed using Skyline.24 Transitions were selected based on a spectral library created from MS/MS analysis of SIL peptides. Default Skyline peptide and transition settings were used except for the following modifications: transition settings (monoisotopic mass) and peptide settings (structural modifications, carbamidomethyl Cys; isotope modifications, label:13C615N4-Arg and label:13C615N2-Lys). Experimentally-defined collision energy equations used a slope of 0.0377 and intercept of -1.066 for 2+ charge state precursors, and a slope of 0.0359 and intercept of -2.042 for 3+ charge state precursors. A 6 min wide scheduling window was employed for all targets, and the auto-dwell feature was enabled within MassLynx. Next-generation DNA sequencing of HMPV. Viral RNA was extracted from 200 µl of VC using Purelink Viral RNA/DNA Mini Kit (Invitrogen) and eluted in 40 µl of sterile H2O, and reverse transcription was performed on 10 µl of RNA using the SuperScript II Reverse Transcriptase (Invitrogen). Double stranded DNA was synthesized from 20 µl of the RT product using NEBNext Second Strand Synthesis Module (New England Biolabs) and purified using GenElute PCR Clean-up Kit (Sigma) followed by elution in 50 µl of H2O. DNA was quantified by Quantifluor (Promega) and diluted to 0.2 ng/µl (in 5 µl) for library prep using Nextera XT 6

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DNA Library Prep Kit (Illumina). Sequencing was performed using a MiSeq instrument (Illumina). The reads were assembled using Ray Meta assembler.25

RESULTS LC-MS/MS sequencing of HMPV. While the nominal masses of intact HMPV phosphoprotein and nucleoprotein have been measured by MALDI-TOF MS,26 the HMPV proteome has not been analyzed by bottom-up LC-MS/MS. In order to identify suitable peptides for targeted quantitation of HMPV, we analyzed tryptic digests of partially-purified HMPV CAN97-83 by 1D-LC-MS/MS, using both data-dependent and dataindependent acquisition strategies (see Methods). These analyses provided greater than 30% sequence coverage for five of the nine predicted HMPV gene products (Table S1). Initial MRM method development and validation. To develop an LC-MRM assay for quantifying HMPV in clinical isolates, Skyline was used to build a spectral library from DDA data and to visualize precursor (MS1) data. For method development, an MRM assay was developed against 7 of the highest intensity peptides (including Met and Cys containing peptides;27 and all identified transitions) from four of the five identified HMPV proteins (excluding the phosphoprotein). Since human NPA was to be utilized in the clinical assay, human serum albumin (HSA) peptides were also targeted to allow for normalization, as were peptides belonging to yeast ADH1, a surrogate standard. Trypsinized HMPV and yeast ADH1 were diluted into similarly digested NPA, and a final MRM assay was developed that targeted the native forms and three most intense transitions of 11 HMPV peptides, 3 HSA peptides and 3 ADH1 peptides (Table 1) using a 30 min UPLC gradient (1 h cycle time). To examine the dynamic range and linearity of HMPV peptide quantitation, HMPV was spiked into NPA at 1:10, 1:100, and 1:1000 (w/w), and these samples, along with neat NPA, were each analyzed in triplicate (Table S2 and Supporting Electronic Data). Area under the curve was determined for the summed transitions, and response curves were examined for each of the HMPV peptides. This analysis showed excellent signal to noise for all HMPV peptides up to 1:100 dilution in NPA, and some peptides were readily detectable at 1:1000 dilution (Fig. S1 and Supporting Electronic Data). These results suggested that a number of the selected 7

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peptides might be amenable for sensitive quantitation of HMPV in NPA from infected subjects, and we reasoned that the addition of stable-isotope labeled internal standards might help to improve assay sensitivity and specificity. In silico analysis of MRM assay specificity. Since we developed the MRM assay against a single HMPV strain, with high intensity peptides being the most important factor, we also investigated whether these peptides were specific to HMPV and whether any of them could distinguish HMPV lineage. A BLASTP analysis showed that none of the 11 peptides selected for targeted quantitation were shared with other human pathogens or human proteins (data not shown). However, three of the peptides are shared between human and avian metapneumoviruses, which are the only viruses belonging to the metapneumovirus genus (Table 1)28 The avian virus, however, is non-infectious to infect humans. We next performed a multiple sequence alignment of the target HMPV CAN97-83 peptides and the same regions in the >100 sequences that were present in the NCBI database (Table 2 and Fig. S2). For 8 out of 11 peptides, a vast majority of deposited sequences (>95%) were identical to the CAN97-83 genome within these regions (Table 2). As visualized by WebLogo analysis (Fig. S2), three of the HMPV CAN97-83 peptides—SFYDLVEQK and VPNTELFSAAESYAK of the nucleoprotein, and LTVCEVK of the matrix protein—were found in only ~60% of the sequences in the NCBI database. Variants differed by a single amino acid as compared to the CAN97-83 reference strain. Sequence analysis of HMPV isolates has shown the existence of two genetic clusters. Interestingly, the variant peptides specific to CAN97-83 appear to be exclusive to lineage A, and the (major) alternate variants are exclusive to lineage B.21 These data suggested that an MRM assay could be developed to both quantify total levels of HMPV and to determine genetic lineage. Deployment of an MRM assay for HMPV in viral cultures and clinical aspirates from infected patients. We next sought to determine whether MRM could be used to quantify HMPV in viral cultures (VC) and in clinical specimens obtained from NPA. We obtained matched samples of clinical aspirates from 10 patients who were positive for HMPV infection by cytopathic effects on LLC-MK2 cells and confirmed by immunofluorescence staining.29 After sample cleanup, yields of VC protein were consistent across samples (~100 µg per sample), whereas the recovery of NPA protein was considerably more variable (Table S3). One of 8

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the NPA samples had undetectable levels of protein, and another yielded only ~1 µg, but the remaining 8 samples had ample protein (>5 µgs each) for downstream MS analysis. After tryspinization and addition of stable isotope-labeled (SIL) peptides (see Methods), 500 ng of each sample was analyzed by a scheduled LCMRM assay. Analyses of the 10 VC samples and the 8 NPA samples were performed in sequential run blocks (Table S4 and Supporting Electronic Data). Within each block, samples were interspersed with QC pools for determining analytical reproducibility. Detection and relative quantitation of HMPV in VC and NPA samples using pan-HMPV peptides. We first used the MRM data for relative quantitation of the 8 pan-HMPV peptides in VC samples. Excellent signalto-noise was seen for all but one precursor (M21 FNHNYWSWPDR), and of the 7 remaining targets, the average percent coefficient of variation (%CV) across these pan-HMPV peptides was ~4% based on the ratios of native/SIL peptide intensities for the triplicate QC injections. Within the 10 individual VC samples, each of the 7 target peptides were observed (with native/SIL ratios of at least 0.1, or ~0.25 fmols of native peptide) except in one sample (VC8), in which both the Matrix peptide, TVYLTTMKPYGMVSK, and the M21 peptide, ADGLSIISGAGR, were not detected (Supporting Information). We hypothesized that variants in the HMPV genome might explain the absence of these native peptides, although no variants were found in the NCBI database (Table 2). To visualize relative expression of peptides across these samples, total levels of HMPV were also expressed as the aggregate sum of normalized native/SIL peptide ratios (an HMPV “metaprotein”), with the caveat that sample VC8 was represented by only 5 peptides (Fig. 1A). We performed a similar analysis of the QC pool data from the NPA analysis, and again we found that the 7 best pan-specific HMPV peptides exhibited high technical reproducibility (mean %CV of ~4% based on light/heavy ratios). Notably, the NPA samples were characterized by high levels of HSA as compared to the VC samples (Fig. 1B). However, one of the NPA samples (NPA5) had very little HSA, which correlated with a mucus-like substance in this sample that was recovered during sample concentration. Although the levels of native HMPV peptides in NPA samples were overall lower than in VC samples, we nonetheless achieved adequate signal-to-noise for quantitation of pan-HMPV peptides across 7 of the NPA samples (excluding

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NPA5; Fig. 1C). The corresponding low levels of native pan-HMPV peptides, and HSA, in the NPA5 sample, suggest that HSA content might be used to verify adequate sampling of the nasal airway lining fluid. Assignment of HMPV lineage by MRM. We next investigated the quantitation of lineage-specific peptides. Across the VC cohort, native levels of lineage A- and B-specific peptides were detected in the QC pools with adequate technical reproducibility (10x PFU/ml versus the CAN9875 virus). After trypsin digestion and addition of SIL peptides, each standard was analyzed in duplicate by MRM (Table S5 and Supporting Electronic Data). By visual inspection, we first excluded precursors and/or transitions that had poor signal-to-noise, or obvious interferences. Virus lineages were confirmed by the assay; however, the lineage B Matrix peptide, LTVCDVK, was also detected in samples containing large amounts of lineage A virus (due to an interferent; Supporting Electronic Data). Although this phenomenon was observed at HMPV levels that were likely outside of the range present in NPA, we nonetheless flagged the LTVCDVK/LTVCEVK pair as a poor target. In total, five pan-HMPV peptides and two pairs of variant peptides passed this initial QC step (Supporting Electronic Data). Notably, most of these optimized targets did not contain readily oxidizable residues (i.e.. Cys, Met) that might introduce variability in a quantitative assay. These remaining targets were further analyzed in Skyline using the QuaSAR plug-in,27,31 which fit the peak area ratio (i.e. light/heavy ratio) at the individual transition and precursor (sum of transitions) levels to the PFU of virus that was added to the NPA (Table S6). For the majority of the pan-HMPV peptides, response curves showed good linearity over at least 3 orders of magnitude of dynamic range (Table S6 and Figs. S5-S6), although the amount of HMPV protein per PFU was much greater for the HMPV A versus HMPV B virus (Fig. S7). Two of the best performing peptides, based on r2 values, were the M21 peptide, SNYLLNQLLR, and the NCAP peptide, SLFIEYGK (Table S6 and Fig. 3A and Fig. S8A). We used linear fittings to calculate PFUs in the VC and NPA samples. Using either the HMPV A or HMPV B standard curves, HMPV levels in all VC samples and 6 of the NPA samples were above limits of detection. The quantitation of HMPV by either the SNYLLNQLLR or SLFIEYGK peptides was further visualized by scatter-plot (Fig. 3B and Fig. S8B). This analysis demonstrated good correlation between 11

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these two peptides (from two different HMPV proteins) across a large concentration range. Collectively, these data more definitively establish parameters for robust identification of HMPV in human clinical samples.

DISCUSSION While multiple reaction monitoring has been previously used to quantify influenza virus, its use has been mostly limited to the verification of influenza HA and NA antigens in the setting of vaccine development. Here, we show that MRM can be used to readily quantify HMPV, and identify genetic lineage, from viral cultures obtained in a hospital setting. Given the difficulty in detecting HMPV from viral cultures, it may be possible that the standard culture time (which is at least two weeks) could be reduced by utilizing this MS-based approach. The MRM approach may have advantages over other viral proteotyping approaches that rely on peptide fingerprint matching for a number of reasons: the use of SIL peptides, which are easily obtained, enables high specificity; triple quadrupole mass spectrometers are common in clinical laboratories; and MRM assays exhibit high intralaboratory reproducibility.32 Here, we have also shown for the first time that targeted proteomics may be applied to the detection of a viral pathogen directly from primary specimens. While there appears to be some limitations in the application to NPA due to low and variable protein recovery, this might be overcome by enrichment of viral particles8 or immunocapture of target peptides prior to MS analysis.33,34 The rapid mutation of RNA viruses is a problem inherent to any immunologic/molecular techniques based either on the detection of specific protein epitopes, or on the amplification of cDNA using highly specific primer pairs. Indeed, RT-PCR-based assays for HMPV have undergone a number of revisions to correct for sequence mismatches due to the appearance of new variants of the major HMPV lineages.19,35,36 However, compared to other RNA viruses such as influenza, HMPV (and other paramoxyviruses) do have a slower rate of mutation and undergo relatively slow evolution over time.30 In addition, major polymorphic differences within the HMPV lineages are geographically clustered. Five of the pan-specific peptides that we quantified in our cohort were identical to a 20 year-old Canadian HMPV reference strain. This suggests that the regions we are monitoring by MRM have been slow to mutate, which could reflect their role in virus structure/function. While

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our assay does not account for rare mutations (including those identified in this study; Table 3), additional variants could easily be targeted without sacrificing the sensitivity or throughput of the assay. We have established the linearity of the MRM assay across at least three orders of magnitude of dynamic range. While we fit the dilution series data to PFUs of virus because it was the only unit of measure available, it is important to note that any presence of HMPV in NPA (including active or inactive virus) is indicative of infection, as there is no carrier state (i.e. infection without disease) for respiratory viruses. Therefore, HMPV need only be present above the limit of detection of the assay in order to unambiguisly suggest that the patient has an infection, be it waning or progressing. At the level of a single peptide(s), rigorous quantitation of HMPV relative to an external calibration curve confirmed the results that were obtained based solely on ratio to internal standard. Our analysis also showed that there was a poor between correlation between PFUs and the levels of HMPV proteins across the two standards. These results suggest that it might be more appropriate to instead calibrate the total levels of virus in the HMPV standard using an independent measure of viral protein. The highly multiplexible nature of MRM gives promise to the future development of an assay for detection of a panel of respiratory viruses analogous to multiplexed RT-PCR-based assays. Indeed, extension of this assay to to detect respiratory syncytial and influenza viruses would cover the majority of respiratory infections in children. Furthermore, although rudimentary, our multiplexed analysis of both HMPV and HSA in the NPA samples demonstrates the potential utility of MRM for simultaneous quantitation of multiple respiratory pathogens and of the host proteome response to infection. Additional discovery-based proteomics on biofluids from infected individuals, or on respiratory epithelial or other cells treated with specific pathogens, could be used to develop analogous MRM assays to simulatenously assess pathogen response and to identify the pathogen itself. Such analyses could provide important information on the severity of an infection or help to guide therapy.

ACKNOWLEDGEMENTS

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J.C. acknowledges the Canada Research Chair in Medical Genomics and G.B. acknowledges the Canada Research Chair in Emerging Viruses and Antiviral Resistance. Sequencing data assembly were performed on the Colosse supercomputer at Université Laval under the auspices of Calcul Québec and Compute Canada. The operations of Colosse is funded by the Canada Foundation for Innovation (CFI), the National Science and Engineering Research Council (NSERC), NanoQuébec, and the Fonds Québécois de Recherche sur la Nature et les Technologies (FQRNT).

FIGURE LEGENDS Figure 1. MRM quantitation of pan-HMPV peptides in viral cultures and NPA samples. MRM assays were performed on VC and NPA samples, and the expression levels of native pan-HMPV peptides (see Figure 1 and Table 1) were calculated by normalizing to SIL internal standards. A) HMPV “metaprotein” expression in each VC sample was visualized as the aggregate sum of 7 pan-HMPV peptides. B) Human serum albumin protein expression across NPA samples was visualized as the aggregate sum of 2 peptides. C) HMPV “metaprotein” expression in each NPA sample was visualized as the aggregate sum of 5 pan-HMPV peptides. N.A., samples were not analyzed due to insufficient protein recovery.

Figure 2. MRM quantitation of lineage-specific HMPV peptides. The levels of lineage-specific HMPV peptides were quantified as in Fig. 1. A) Lineage-specific HMPV metaprotein expression (aggregate sum of normalized peptide expression across all HMPV variant peptides) was plotted for HMPV lineage A (upper histogram) and HMPV lineage B (lower histogram) in viral culture samples. B) Lineage-specific HMPV metaprotein expression in NPA samples was plotted as in (A). N.A., samples were not analyzed due to insufficient protein recovery.

Figure 3. MRM analysis of HMPV standard curves. Titrated HMPV lineage A virus was diluted into NPA as described in the Methods. After trypsin digestion and addition of SIL peptides at 10 fmol/µg NPA , 0.5 µg from each sample was analyzed in duplicate by MRM and analyzed in Skyline using the QuaSAR plug-in. A) Peak 14

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area ratios (normalized to SIL standards) versus PFU were plotted for the M21 peptide, SNYLLNQLLR (sum of y5,y6,y7), and the NCAP peptide, SLFIEYGK (y6 transition) across the HMPV lineage A standard curve. B) HMPV PFU in VC and NPA samples were calculated from the response curves of the SNYLLNQLLR and SLFIEYGK peptides (Table S5), and the correlation of these two measurements for quantifying total HMPV using the HMPV A standard curve was compared using a scatterplot.

ASSOCIATED CONTENT. Supporting Information The Supporting Information is available free of charge on the ACS Publications website Links to Electronic Data; Label-free MRM assay; Multiple sequence alignments; Results of RNA-Seq analysis; Analysis of HMPV standard curves; Raw data filename associations; Protein assay data; HMPV standard curve fittings.

References. (1) Shaw, J.; Welch, T. R.; Milstone, A. M. JAMA Pediatr. 2014, 168, 981-982. (2) Lancet Infect. Dis. 2014, 14, 1023. (3) Guarner, J. Am. J. Clin. Pathol. 2014, 142, 428-430. (4) Zumla, A.; Al-Tawfiq, J. A.; Enne, V. I.; Kidd, M.; Drosten, C.; Breuer, J.; Muller, M. A.; Hui, D.; Maeurer, M.; Bates, M.; Mwaba, P.; Al-Hakeem, R.; Gray, G.; Gautret, P.; Al-Rabeeah, A. A.; Memish, Z. A.; Gant, V. Lancet Infect. Dis. 2014, 14, 1123-1135. (5) Raymond, F.; Carbonneau, J.; Boucher, N.; Robitaille, L.; Boisvert, S.; Wu, W. K.; De Serres, G.; Boivin, G.; Corbeil, J. J. Clin. Microbiol. 2009, 47, 743-750. (6) Kaleta, E. J.; Clark, A. E.; Cherkaoui, A.; Wysocki, V. H.; Ingram, E. L.; Schrenzel, J.; Wolk, D. M. Clin. Chem. 2011, 57, 1057-1067. (7) Wolk, D. M.; Kaleta, E. J.; Wysocki, V. H. J. Mol. Diagn. 2012, 14, 295-304. (8) Downard, K. M. Chem. Soc. Rev. 2013, 42, 8584-8595. (9) Nguyen, A. P.; Downard, K. M. Anal. Chem. 2013, 85, 1097-1105. 15

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(10) Schwahn, A. B.; Wong, J. W.; Downard, K. M. Anal. Chem. 2010, 82, 4584-4590. (11) Schwahn, A. B.; Wong, J. W.; Downard, K. M. Anal. Chem. 2009, 81, 3500-3506. (12) Schwahn, A. B.; Wong, J. W.; Downard, K. M. Eur. J. Mass Spectrom. 2010, 16, 321-329. (13) Santana, W. I.; Williams, T. L.; Winne, E. K.; Pirkle, J. L.; Barr, J. R. Anal. Chem. 2014, 86, 4088-4095. (14) Williams, T. L.; Pirkle, J. L.; Barr, J. R. Vaccine 2012, 30, 2475-2482. (15) Luna, L. G.; Williams, T. L.; Pirkle, J. L.; Barr, J. R. Anal. Chem. 2008, 80, 2688-2693. (16) Feuillet, F.; Lina, B.; Rosa-Calatrava, M.; Boivin, G. J. Clin. Virol. 2012, 53, 97-105. (17) Hamelin, M. E.; Abed, Y.; Boivin, G. Clin. Infect. Dis. 2004, 38, 983-990. (18) Cote, S.; Abed, Y.; Boivin, G. J. Clin. Microbiol. 2003, 41, 3631-3635. (19) Klemenc, J.; Asad Ali, S.; Johnson, M.; Tollefson, S. J.; Talbot, H. K.; Hartert, T. V.; Edwards, K. M.; Williams, J. V. J. Clin. Virol. 2012, 54, 371-375. (20) Hamelin, M. E.; Yim, K.; Kuhn, K. H.; Cragin, R. P.; Boukhvalova, M.; Blanco, J. C.; Prince, G. A.; Boivin, G. J. Virol. 2005, 79, 8894-8903. (21) Bastien, N.; Normand, S.; Taylor, T.; Ward, D.; Peret, T. C.; Boivin, G.; Anderson, L. J.; Li, Y. Virus Res. 2003, 93, 51-62. (22) Hamelin, M. E.; Couture, C.; Sackett, M. K.; Boivin, G. J. Gen. Virol. 2007, 88, 3391-3400. (23) Foster, M. W.; Thompson, J. W.; Ledford, J. G.; Dubois, L. G.; Hollingsworth, J. W.; Francisco, D.; Tanyaratsrisakul, S.; Voelker, D. R.; Kraft, M.; Moseley, M. A.; Foster, W. M. J. Proteome Res. 2014, 13, 3722-3732. (24) MacLean, B.; Tomazela, D. M.; Shulman, N.; Chambers, M.; Finney, G. L.; Frewen, B.; Kern, R.; Tabb, D. L.; Liebler, D. C.; MacCoss, M. J. Bioinformatics 2010, 26, 966-968. (25) Boisvert, S.; Raymond, F.; Godzaridis, E.; Laviolette, F.; Corbeil, J. Genome Biol. 2012, 13, R122. (26) Tedcastle, A. B.; Fenwick, F.; Ingram, R. E.; King, B. J.; Robinson, M. J.; Toms, G. L. J. Med. Virol. 2012, 84, 1061-1070. (27) Carr, S. A.; Abbatiello, S. E.; Ackermann, B. L.; Borchers, C.; Domon, B.; Deutsch, E. W.; Grant, R. P.; Hoofnagle, A. N.; Huttenhain, R.; Koomen, J. M.; Liebler, D. C.; Liu, T.; MacLean, B.; Mani, D. R.; Mansfield, 16

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E.; Neubert, H.; Paulovich, A. G.; Reiter, L.; Vitek, O.; Aebersold, R.; Anderson, L.; Bethem, R.; Blonder, J.; Boja, E.; Botelho, J.; Boyne, M.; Bradshaw, R. A.; Burlingame, A. L.; Chan, D.; Keshishian, H.; Kuhn, E.; Kinsinger, C.; Lee, J. S.; Lee, S. W.; Moritz, R.; Oses-Prieto, J.; Rifai, N.; Ritchie, J.; Rodriguez, H.; Srinivas, P. R.; Townsend, R. R.; Van Eyk, J.; Whiteley, G.; Wiita, A.; Weintraub, S. Mol. Cell. Proteomics 2014, 13, 907-917. (28) Njenga, M. K.; Lwamba, H. M.; Seal, B. S. Virus Res. 2003, 91, 163-169. (29) Manoha, C.; Bour, J. B.; Pitoiset, C.; Darniot, M.; Aho, S.; Pothier, P. J. Med. Virol. 2008, 80, 154-158. (30) Yang, C. F.; Wang, C. K.; Tollefson, S. J.; Piyaratna, R.; Lintao, L. D.; Chu, M.; Liem, A.; Mark, M.; Spaete, R. R.; Crowe, J. E., Jr.; Williams, J. V. Virol. J. 2009, 6, 138. (31) Mani, D. R.; Abbatiello, S. E.; Carr, S. A. BMC Bioinformatics 2012, 13 Suppl 16, S9. (32) Addona, T. A.; Abbatiello, S. E.; Schilling, B.; Skates, S. J.; Mani, D. R.; Bunk, D. M.; Spiegelman, C. H.; Zimmerman, L. J.; Ham, A. J.; Keshishian, H.; Hall, S. C.; Allen, S.; Blackman, R. K.; Borchers, C. H.; Buck, C.; Cardasis, H. L.; Cusack, M. P.; Dodder, N. G.; Gibson, B. W.; Held, J. M.; Hiltke, T.; Jackson, A.; Johansen, E. B.; Kinsinger, C. R.; Li, J.; Mesri, M.; Neubert, T. A.; Niles, R. K.; Pulsipher, T. C.; Ransohoff, D.; Rodriguez, H.; Rudnick, P. A.; Smith, D.; Tabb, D. L.; Tegeler, T. J.; Variyath, A. M.; Vega-Montoto, L. J.; Wahlander, A.; Waldemarson, S.; Wang, M.; Whiteaker, J. R.; Zhao, L.; Anderson, N. L.; Fisher, S. J.; Liebler, D. C.; Paulovich, A. G.; Regnier, F. E.; Tempst, P.; Carr, S. A. Nat. Biotechnol. 2009, 27, 633-641. (33) Anderson, N. L.; Anderson, N. G.; Haines, L. R.; Hardie, D. B.; Olafson, R. W.; Pearson, T. W. J. Proteome Res. 2004, 3, 235-244. (34) Zhao, L.; Whiteaker, J. R.; Pope, M. E.; Kuhn, E.; Jackson, A.; Anderson, N. L.; Pearson, T. W.; Carr, S. A.; Paulovich, A. G. J. Vis. Exp. 2011. (35) Choudhary, M. L.; Anand, S. P.; Sonawane, N. S.; Chadha, M. S. Arch. Virol. 2014, 159, 217-225. (36) Papenburg, J.; Carbonneau, J.; Isabel, S.; Bergeron, M. G.; Williams, J. V.; De Serres, G.; Hamelin, M. E.; Boivin, G. J. Clin. Virol. 2013, 58, 541-547.

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Table 1. Summary of MRM assays used in this study Protein

Peptide Sequence

CAN97-83 NCAP NCAP var. 1 CAN97-83 NCAP CAN97-83 NCAP NCAP var. 2 CAN97-83 MTRX MTRX var. 1 MTRX var. 2 CAN97-83 MTRX

SFYDLFEQK SFYELFLEK SLFIEYGKb VPNTELFSAAESYAK VPNTELFSAAESYAR LTVC[+57.0]EVK LTVC[+57.0]DVK LAVC[+57.0]DVK TVYLTTMKPYGMVSKb THDLIALC[+57.0]DFMDLEKa,

CAN97-83 MTRX

b b

Native (light) precursor m/z 588.78222 595.7900 478.7580 813.9041 827.9072 424.7309 427.7231 402.7178 573.6334 607.6234

r 2> 0.995

Charge state

Transitions (product ions)

2 2 2 2 2 2 2 2 3

y6+, y7+ y6+, y7+ y2+, y3+, y6+ y8+, y9+, y14++ y8+, y9+, y14++ y4+, y5+ y4+, y5+, y6+ y4+, y5+, y6+ y7+, y12++, y13++

sum y7 sum sum sum

y7+

y7

3 +

+

+

c

CAN97-83 FUS TELDLTK 410.2266 2 y2 , y3 , y5 CAN97-83 FUS TVSADQLARb 480.7591 2 y4+, y5+, y7+ sum CAN97-83 M21 FNHNYWSWPDRa,b 761.3365 2 y3+, y9++, y10++ CAN97-83 M21 SNYLLNQLLRa,b 617.3511 2 y5+, y6+, y7+ sum CAN97-83 M21 ADGLSIISGAGRb 558.8040 2 y5+, y8+ sum HSA SLHTLFGDK 509.2718 2 y4+, y6+ HSA LC[+57.0]TVATLR 467.2629 2 y4+, y5+, y6+ HSA ETC[+57.0]FAEEGK 535.7266 2 y5+, y6+, y7+ Yeast ADH1 ANELLINVK 507.3031 2 y4+, y5+, y6+ Yeast ADH1 VLGIDGGEGK 472.7560 2 y5+, y6+, y8+ Yeast ADH1 EALDFFAR 484.7454 2 y3+, y4+, y5+ a peptides with identity between human and avian metapneumovirus; bpan-HMPV peptides based on low (or zero) frequency variation across all sequenced HMPV strains (see Fig. 1 and Table 3); cindicates peptides (either the sum of transitions, or else single transitions) that had r2>0.995 for calibration curves of HMPV lineages spiked into NPA.

Table 2. CAN97-83 reference peptides and variants in NCBI database Protein CAN 97-83 Peptide Variantsa NCAP SFYDLFEQK (89) SFYELFEQK (45) NCAP SLFIEYGK (134) VPNTELFSAAESYAR NCAP VPNTELFSAAESYAK (89) (45) LTVCDVK (50) MTRX LTVCEVK (102) LAVCDVK (8) PHDLIALCDFMDLEK (1) THDLIALCDFMDLEE (3) THDLIALCDFMDLEK THDLIALCDFMNLEK MTRX (153) (1) THGLIALCDFMDLEK (1) TRDLIALCDFMDLEK (1) TVYLTTMKPYGMVSK MTRX TVYLTTMKPHGMVSKb (160) FUS TELDLTK (303) TELELTK (4) FUS

TVSADQLAR (304)

M21

FNHNYWSWPDR (152)

M21

SNYLLNQLLR (152)

TVSADQLAG (1) PVSADQLAR (1) TVSAGQLAR (1)

ADGLSTISGAGR (1) ADGLSTISGTGRb a numbers are identical sequences in NCBI database; bnovel variants identified in this study M21

ADGLSIISGAGR (151)

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Figure 1 28

HMPV metaprotein intesnity

A

SLFIEYGK_NCAP THDLIALCDFMDLEK_MTRX TVYLTTMKPYGMVSK_MTRX TVSADQLAR_FUS TELDLTK_FUS ADGLSIISGAGR_M21 SNYLLNQLLR_M21

24 20 16 12 8 4

10

9

V C

8

V C

V C

7

6

V C

V C

V C

5

4

3

V C

2

V C

B

V C

V C

1

0 3000 LCTVATLR_HSA SLHTLFGDK_HSA

HSA protein intesnity

2500 2000 1500 1000

. 10

.A A P N

N

P

9

.A

N A

N 7

A P

N

6

A P

N

5

A

N

P

A

4

P N

3

A P

N

2

A

N

P

A P

N

N

P

A

1

0

C

8

.

500

20 SLFIEYGK_NCAP TVSADQLAR_FUS TELDLTK_FUS ADGLSIISGAGR_M21 SNYLLNQLLR_M21

16

12

8

10

P

A

9

N N

8

N P

A

7 A

N P

6

N P

5

A

N P

A

4 A

N P

3

N P

2

A

N P

A

N P

A

1

0

A

N

.A . .A .

4

N P

HMPV metaprotein intesnity

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Figure 2

0.5

7

P A

0.5

1.0

1.5

Lineage B peptides 2.0

VPNTELFSAAESYAR SFYELFEQK

2.5

LTVCDVK

Lineage B HMPV expression

0.05 0.1 0.15 0.2 0.25 0.3

Lineage B peptides VPNTELFSAAESYAR SFYELFEQK LTVCDVK

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N

N

.A .

N

6

P A N

5 N

P A

4

P A N

3

P A N

P A N

1

P A N

P A N

9

10 V C

V C

8 V C

7 V C

6 V C

5 V C

4 V C

2

3 V C

1

V C

V C

0

2

0

0 0

2

10

1.0

4

9

1.5

P A

2.0

LTVCEVK

6

P A

LTVCEVK

SFYDLFEQK

N

SFYDLFEQK

2.5

VPNTELFSAAESYAK

8

N

VPNTELFSAAESYAK

Lineage A peptides

.A .

3.0

10

N .A . N .A .

B

Lineage A peptides

8

3.5

Lineage A HMPV expression

Lineage A HMPV expression

A

Lineage B HMPV expression

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Figure 3 A

Peak area ratio (log10)

100

SNYLLNQLLR SLFEIYGK

10 1 0.1 0.01 0.001

0.0001 0.01

0.1

1

10

100

1000

PFU HMPVA added per injection (log10)

B

PFU HMPVA (log10) from SNYLLNQLLR curve

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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100

NPA VC

10

1

0.1 0.1

1

10

PFU HMPVA (log10) from SLFIEYGK curve

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MRM

RNA-SEQ

1 light/heavy ratio

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1 2 3 4 5 7 8 9 10

VPNTELFSAAESYAK VPNTELFSAAESYAR

0.8 0.6 0.4 0.2 0

1

2

3

4

5

6

7

8

9 10

MYRGRVPNTELFSAAESYARSLKE MYRGRVPNTELFSAAESYARSLKE MYRGRVPNTELFSAAESYAKSLKE MYRGRVPNTELFSAAESYAKSLKE MYRGRVPNTELFSAAESYARSLKE MYRGRVPNTELFSAAESYARSLKE MYRGRVPNTELFSAAESYARSLKE MYRGRVPNTELFSAAESYARSLKE MYRGRVPNTELFSAAESYAKSLKE *******************:****

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