Portal de Periódicos da CAPES

Advancing the High Throughput Identification of Liver Fibrosis Protein Signatures Using Multiplexed Ion Mobility Spectrometry

2014; Elsevier BV; Volume: 13; Issue: 4 Linguagem: Inglês

10.1074/mcp.m113.034595

1535-9484

Erin Baker, Kristin Burnum-Johnson, Jon Jacobs, Deborah L. Diamond, Roslyn N. Brown, Yehia Ibrahim, Danny Orton, Paul Piehowski, David E. Purdy, Ronald J. Moore, William Danielson, Matthew Monroe, Kevin L. Crowell, Gordon Slysz, Marina Gritsenko, John D. Sandoval, Brian Lamarche, Melissa M. Matzke, Bobbie‐Jo Webb‐Robertson, Brenna C. Simons, Brian J. McMahon, Renuka Bhattacharya, James D. Perkins, Robert L. Carithers, Susan Strom, Steven G. Self, Michael G. Katze, Gordon Anderson, Richard Smith,

Advanced Proteomics Techniques and Applications

Rapid diagnosis of disease states using less invasive, safer, and more clinically acceptable approaches than presently employed is a crucial direction for the field of medicine. While MS-based proteomics approaches have attempted to meet these objectives, challenges such as the enormous dynamic range of protein concentrations in clinically relevant biofluid samples coupled with the need to address human biodiversity have slowed their employment. Herein, we report on the use of a new instrumental platform that addresses these challenges by coupling technical advances in rapid gas phase multiplexed ion mobility spectrometry separations with liquid chromatography and MS to dramatically increase measurement sensitivity and throughput, further enabling future high throughput MS-based clinical applications. An initial application of the liquid chromatography - ion mobility spectrometry-MS platform analyzing blood serum samples from 60 postliver transplant patients with recurrent fibrosis progression and 60 nontransplant patients illustrates its potential utility for disease characterization. Rapid diagnosis of disease states using less invasive, safer, and more clinically acceptable approaches than presently employed is a crucial direction for the field of medicine. While MS-based proteomics approaches have attempted to meet these objectives, challenges such as the enormous dynamic range of protein concentrations in clinically relevant biofluid samples coupled with the need to address human biodiversity have slowed their employment. Herein, we report on the use of a new instrumental platform that addresses these challenges by coupling technical advances in rapid gas phase multiplexed ion mobility spectrometry separations with liquid chromatography and MS to dramatically increase measurement sensitivity and throughput, further enabling future high throughput MS-based clinical applications. An initial application of the liquid chromatography - ion mobility spectrometry-MS platform analyzing blood serum samples from 60 postliver transplant patients with recurrent fibrosis progression and 60 nontransplant patients illustrates its potential utility for disease characterization. To date pre-clinical and clinical applications of MS-based proteomic techniques analyzing complex biofluids have fallen short of expectations, largely due to deficiencies in both analytical sensitivity and throughput. These deficiencies result in measurements typically failing to confidently detect and quantify proteins at moderate to low concentrations, or not providing sufficient sample analysis throughput for statistical relevance. Targeted MS analyses with higher sensitivity are currently utilized to address these shortcomings (1Picotti P. Rinner O. Stallmach R. Dautel F. Farrah T. Domon B. Wenschuh H. Aebersold R. High-throughput generation of selected reaction-monitoring assays for proteins and proteomes.Nat. Methods. 2010; 7: 43-46Crossref PubMed Scopus (399) Google Scholar, 2Addona 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. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.Nat. Biotechnol. 2009; 27: 633-641Crossref PubMed Scopus (865) Google Scholar); however, these studies often only analyze a small list of proteins identified as biologically significant. While targeted MS measurements are increasingly common in clinical applications (3Roschinger W. Olgemoller B. Fingerhut R. Liebl B. Roscher A.A. Advances in analytical mass spectrometry to improve screening for inherited metabolic diseases.Eur. J. Pediatr. 2003; 162: S67-76Crossref PubMed Google Scholar, 4Gallien S. Duriez E. Domon B. Selected reaction monitoring applied to proteomics.J. Mass Spectrom. 2011; 46: 298-312Crossref PubMed Scopus (236) Google Scholar), the limited number of proteins they examine does not necessarily reflect the biodiversity across a population, making broad untargeted measurements essential in developing individual disease metrics for diagnosis (5Woodcock J. The prospects for "personalized medicine" in drug development and drug therapy.Clin. Pharmacol. Ther. 2007; 81: 164-169Crossref PubMed Scopus (143) Google Scholar). As the future of medicine proceeds toward a personal profiling approach (6Chan I.S. Ginsburg G.S. Personalized medicine: progress and promise.Annu. Rev. Genomics Hum. Genet. 2011; 12: 217-244Crossref PubMed Scopus (214) Google Scholar, 7Hutchinson L. Personalized cancer medicine: era of promise and progress.Nat. Rev. Clin. Oncol. 2011; 8: 121Crossref PubMed Scopus (9) Google Scholar), the potential for robust high throughput clinical measurements based upon MS is highly attractive, though only if its deficiencies can be addressed. An initial step in attaining broad untargeted measurements that increasingly retain the benefits of targeted analyses exploits technological advances such as faster separations, more effective ion sources, detectors with greater dynamic range, and MS measurements with both higher resolution and accuracy. Advanced liquid-phase separations have already been employed to provide a significant sensitivity increase as illustrated by the higher number of proteins detected in liquid chromatography (LC) 1The abbreviations used are:MSmass spectrometryIMSion mobility spectrometryLCliquid chromatographyTOFtime-of-flightm/zmass-to-charge ratiosHCVHepatitis C VirusNPnonprogressorsSPslow progressorsFPfast progressorsC4Acomplement component 4AECM1extracellular matrix proteinsLGALS3BPgalectin-3-binding proteinACTBcytoskeletal β-actinTGFBItransforming growth factor-β-induced protein ig-h3F12coagulation factor XIITGF-β1transforming growth factor βVTNvitronectinLUMlumicanF10coagulation factor XC5complement factor 5A1BGalpha-1B-glycoproteinCFHcomplement factor HIGFALSinsulin-like growth factor-binding protein complex acid labile subunitPROCvitamin K-dependent protein CRBP4retinol-binding protein 4HPXhemopexinA2Malpha-2-macroglobulinF2ProthrombinQSOX1sulfhydryl oxidase 1. 1The abbreviations used are:MSmass spectrometryIMSion mobility spectrometryLCliquid chromatographyTOFtime-of-flightm/zmass-to-charge ratiosHCVHepatitis C VirusNPnonprogressorsSPslow progressorsFPfast progressorsC4Acomplement component 4AECM1extracellular matrix proteinsLGALS3BPgalectin-3-binding proteinACTBcytoskeletal β-actinTGFBItransforming growth factor-β-induced protein ig-h3F12coagulation factor XIITGF-β1transforming growth factor βVTNvitronectinLUMlumicanF10coagulation factor XC5complement factor 5A1BGalpha-1B-glycoproteinCFHcomplement factor HIGFALSinsulin-like growth factor-binding protein complex acid labile subunitPROCvitamin K-dependent protein CRBP4retinol-binding protein 4HPXhemopexinA2Malpha-2-macroglobulinF2ProthrombinQSOX1sulfhydryl oxidase 1.-MS-based studies (8Shen Y.F. Zhao R. Berger S.J. Anderson G.A. Rodriguez N. Smith R.D. High-efficiency nanoscale liquid chromatography coupled on-line with mass spectrometry using nanoelectrospray ionization for proteomics.Anal. Chem. 2002; 74: 4235-4249Crossref PubMed Scopus (258) Google Scholar), however, the long LC separations most compatible with blood samples are extremely time-consuming. Fast gas-phase ion mobility spectrometry (IMS) separations that take place on the time scale of tens of milliseconds offer an additional separation stage and a way of reducing the need for extended LC separation times. In an IMS separation, ions subjected to an electric field while traveling through a buffer gas separate quickly based on ion shape, for example, compact species drift faster than those with extended structures (9Mason E. McDaniel E. Transport Properites of Ions in Gases. Wiley, New York1988Crossref Google Scholar, 10Guevremont R. Siu K.W. Wang J. Ding L. Combined ion mobility/time-of-flight mass spectrometry study of electrospray-generated ions.Anal. Chem. 1997; 69: 3959-3965Crossref PubMed Scopus (73) Google Scholar). IMS can be coupled between LC and orthogonal acceleration time-of-flight (TOF) MS stages. By combining these three orthogonal separations into a single LC-IMS-MS instrumentation platform, multidimensional high-resolution nested spectra are produced containing elution times, mass-to-charge ratios (m/z) and IMS drift times for all detectable ions in a sample (11Sowell R.A. Koeniger S.L. Valentine S.J. Moon M.H. Clemmer D.E. Nanoflow LC/IMS-MS and LC/IMS-CID/MS of protein mixtures.J. Am. Soc. Mass Spectrom. 2004; 15: 1341-1353Crossref PubMed Scopus (34) Google Scholar, 12Baker E.S. Livesay E.A. Orton D.J. Moore R.J. Danielson 3rd, W.F. Prior D.C. Ibrahim Y.M. LaMarche B.L. Mayampurath A.M. Schepmoes A.A. Hopkins D.F. Tang K. Smith R.D. Belov M.E. An LC-IMS-MS platform providing increased dynamic range for high-throughput proteomic studies.J. Proteome Res. 2010; 9: 997-1006Crossref PubMed Scopus (106) Google Scholar). The objective of this manuscript is to evaluate an LC-IMS-MS platform performance against an LC-MS only platform and determine how well it performs with clinical samples. mass spectrometry ion mobility spectrometry liquid chromatography time-of-flight mass-to-charge ratios Hepatitis C Virus nonprogressors slow progressors fast progressors complement component 4A extracellular matrix proteins galectin-3-binding protein cytoskeletal β-actin transforming growth factor-β-induced protein ig-h3 coagulation factor XII transforming growth factor β vitronectin lumican coagulation factor X complement factor 5 alpha-1B-glycoprotein complement factor H insulin-like growth factor-binding protein complex acid labile subunit vitamin K-dependent protein C retinol-binding protein 4 hemopexin alpha-2-macroglobulin Prothrombin sulfhydryl oxidase 1. mass spectrometry ion mobility spectrometry liquid chromatography time-of-flight mass-to-charge ratios Hepatitis C Virus nonprogressors slow progressors fast progressors complement component 4A extracellular matrix proteins galectin-3-binding protein cytoskeletal β-actin transforming growth factor-β-induced protein ig-h3 coagulation factor XII transforming growth factor β vitronectin lumican coagulation factor X complement factor 5 alpha-1B-glycoprotein complement factor H insulin-like growth factor-binding protein complex acid labile subunit vitamin K-dependent protein C retinol-binding protein 4 hemopexin alpha-2-macroglobulin Prothrombin sulfhydryl oxidase 1. Analysis of the 120 human serum samples was performed on an in-house built instrument that couples a 1-m ion mobility separation with an Agilent 6224 TOF MS upgraded to a 1.5 meter flight tube providing resolution of ∼25,000 in enhanced dynamic range mode (12Baker E.S. Livesay E.A. Orton D.J. Moore R.J. Danielson 3rd, W.F. Prior D.C. Ibrahim Y.M. LaMarche B.L. Mayampurath A.M. Schepmoes A.A. Hopkins D.F. Tang K. Smith R.D. Belov M.E. An LC-IMS-MS platform providing increased dynamic range for high-throughput proteomic studies.J. Proteome Res. 2010; 9: 997-1006Crossref PubMed Scopus (106) Google Scholar). The analysis of the spiked peptide samples and a small subset of the human serum samples was performed on both a Thermo Fisher Scientific LTQ Orbitrap Velos MS (Velos) (San Jose, CA, USA) operated in tandem MS (MS/MS) mode and the in-house built IMS-MS instrument. A fully automated in-house built 4-column HPLC system equipped with in-house packed capillary columns was used for both instruments with mobile phase A consisting of 0.1% formic acid in water and phase B comprised of 0.1% formic acid in acetonitrile (13Livesay E.A. Tang K. Taylor B.K. Buschbach M.A. Hopkins D.F. LaMarche B.L. Zhao R. Shen Y. Orton D.J. Moore R.J. Kelly R.T. Udseth H.R. Smith R.D. Fully automated four-column capillary LC−MS system for maximizing throughput in proteomic analyses.Anal. Chem. 2007; 80: 294-302Crossref PubMed Scopus (119) Google Scholar). A 100-min LC gradient was performed on the LTQ Orbitrap Velos MS (using 60 cm long columns with an o.d. of 360 μm, i.d. of 75 μm, and 3-μm C18 packing material), whereas only a 60-min gradient with shorter columns (30 cm long with same dimensions and packing) was used with the IMS-MS. Both gradients increased mobile phase B from 0 to 60% until the final 2-min of the run when B was purged at 95%. 5 μl of each sample was injected for both analyses and the HPLC was operated under a constant flow rate of 0.4 μl/min for the 100-min gradient and 1 μl/min for the 60-min gradient. The Velos MS data were collected from 400–2000 m/z at a resolution of 60,000 (automatic gain control (AGC) target: 1 × 106). IMS-MS data were collected from 100–3200 m/z. Detailed descriptions of the sample preparation, nanoHPLC, mass spectrometry, informatics approach and statistical analysis are available in Supplemental Methods. Practical use of IMS-MS was initially impeded by its low sensitivity due to significant ion losses at the IMS drift cell termini. This problem was solved with ion funnels by re-focusing both the ions exiting the source and those leaving the drift cell (Fig. 1A), making the addition of the IMS stage essentially lossless (14Tang K. Shvartsburg A.A. Lee H.N. Prior D.C. Buschbach M.A. Li F. Tolmachev A.V. Anderson G.A. Smith R.D. High-sensitivity ion mobility spectrometry/mass spectrometry using electrodynamic ion funnel interfaces.Anal. Chem. 2005; 77: 3330-3339Crossref PubMed Scopus (221) Google Scholar). However, the use of both efficient ion sources and interfaces with efficient ion accumulation between injections is problematic due to space charge constraints. Another limitation that has hindered widespread use of IMS-MS is its inherent low duty cycle. During traditional IMS experiments, ions are only pulsed into the drift cell after all ions from the previous packet exit, resulting in utilization of only a small percentage of the ions created in the source. To address this constraint, a multiplexing approach based on the Hadamard transform was developed so that discreet packets of ions could co-exist in the drift cell as long as they did not overlap due to diffusional broadening (Fig. 1B and 1C) (15Belov M.E. Buschbach M.A. Prior D.C. Tang K. Smith R.D. Multiplexed ion mobility spectrometry-orthogonal time-of-flight mass spectrometry.Anal. Chem. 2007; 79: 2451-2462Crossref PubMed Scopus (63) Google Scholar). This approach substantially circumvents space charge limitations, allows much higher IMS duty cycle, significantly increases measurement sensitivity, and deconvolution of its pseudorandom sequence has been shown to greatly reduce the noise in the spectra allowing a much higher signal to noise ratio for the resulting ions (16Clowers B.H. Belov M.E. Prior D.C. Danielson 3rd, W.F. Ibrahim Y. Smith R.D. Pseudorandom sequence modifications for ion mobility orthogonal time-of-flight mass spectrometry.Anal. Chem. 2008; 80: 2464-2473Crossref PubMed Scopus (42) Google Scholar). These improvements in addition to the reduced spectral congestion from the IMS separation have enabled faster LC gradient times, thereby increasing analyses throughput (12Baker E.S. Livesay E.A. Orton D.J. Moore R.J. Danielson 3rd, W.F. Prior D.C. Ibrahim Y.M. LaMarche B.L. Mayampurath A.M. Schepmoes A.A. Hopkins D.F. Tang K. Smith R.D. Belov M.E. An LC-IMS-MS platform providing increased dynamic range for high-throughput proteomic studies.J. Proteome Res. 2010; 9: 997-1006Crossref PubMed Scopus (106) Google Scholar). To take advantage of the faster sample analyses and higher sensitivity measurements, we developed a LC-IMS-MS analytical platform with the above sensitivity improvements for application to clinically focused large-scale proteomic measurements. In an initial evaluation of the new LC-IMS-MS platform, its performance was compared with an LC-MS platform (comprised of a commercially available LTQ Orbitrap Velos). Nine blood serum samples were analyzed on each platform, and a 100-min LC gradient was used for LC-MS, whereas a 60-min LC gradient was used for LC-IMS-MS. Even with the shorter analysis time, >20% more deisotoped spectral features (putative peptides) were detected with the LC-IMS-MS platform compared with the LC-MS platform (Fig. 1D), an observation attributed to the reduced spectral congestion from the additional IMS separation and the higher signal to noise ratios from multiplexing. These attributes allow detection of additional proteins not seen in the LC-MS experiments and additional coverage and confidence for peptides observed with significant differential abundance in the LC-IMS-MS analyses. To further understand why more features were observed in the LC-IMS-MS platform even with a reduced LC gradient, a follow-up limit of detection study was performed and involved both platforms analyzing three technical replicates of a normal human serum sample spiked with eight nonhuman peptides ranging in concentrations from 100 pg/ml to 100 ng/ml. Overall, the LC-IMS-MS platform detected peptides at concentrations ∼100× lower than the LC-MS platform with a linear correlation to concentrations, lower coefficient of variation (CV) values and modestly higher throughput (60-min versus 100-min) as shown by Table I and Fig. 1E. These advantages illustrate the potential gains in enhanced dynamic range, proteome coverage, and increased speed for the LC-IMS-MS platform. To allow direct comparison of the TOF MS (60-min LC separation) and LTQ Orbitrap Velos (100-min separation), the IMS drift cell was removed. Both instruments illustrated similar limits of detection (Table I) illustrating that the increased measurement sensitivity observed with the LC-IMS-MS platform can be attributed specifically to the IMS separation.Table IScaled abundance and coefficient of variation (CV) values for eight nonhuman peptides spiked into human serum for 60-min LC-IMS-TOF MS, 60-min LC-TOF MS, and 100-min LC-LTQ Orbitrap Velos analysesSpiking LevelPeptideNeutral MassMost Abundant Charge State(s)Peptide Scaled AbundanceaPeptide abundance values from 3 datasets were averaged and re-scaled to a range of 0 to 1000 for direct instrument comparison (by dividing the most abundant peptide value in each instrument and multiplying by 1000). and CV ValuesbCV values are in parenthesis.,cND = not detected.60-min LC-IMS-TOF MS60-min LC-TOF MS100-min LC-LTQ Orbitrap Velos100 pg/mlMelittin2844.754, 5NDNDND100 pg/mlDynorphin A Porcine (Frag 1–13)1602.9831.7 (18)NDND1 ng/mlDes Pro Ala Bradykinin920.50221 (12)NDND1 ng/mlLeucine Enkephalin555.27123 (10)NDND10 ng/ml3X FLAG Peptide2860.145115 (8)125 (20)ND10 ng/mlSubstance P1346.732126 (7)138 (18)112 (19)100 ng/ml[Ala92]-Peptide 62122.184868 (4)848 (11)841 (12)100 ng/mlMethionine Enkephalin573.2311000 (3)1000 (9)1000 (10)a Peptide abundance values from 3 datasets were averaged and re-scaled to a range of 0 to 1000 for direct instrument comparison (by dividing the most abundant peptide value in each instrument and multiplying by 1000).b CV values are in parenthesis.c ND = not detected. Open table in a new tab To more fully evaluate the applicability of the LC-IMS-MS platform, we utilized it in a study involving patients affected with chronic hepatitis C virus (HCV). HCV represents a worldwide public health concern affecting an estimated 130–170 million people (17Llovet J.M. Burroughs A. Bruix J. Hepatocellular carcinoma.Lancet. 2003; 362: 1907-1917Abstract Full Text Full Text PDF PubMed Scopus (3787) Google Scholar) and is the leading cause of liver transplants in the United States and Europe causing a major burden on healthcare services (18Charlton M. Ruppert K. Belle S.H. Bass N. Schafer D. Wiesner R.H. Detre K. Wei Y. Everhart J. Long-term results and modeling to predict outcomes in recipients with HCV infection: results of the NIDDK liver transplantation database.Liver Transpl. 2004; 10: 1120-1130Crossref PubMed Scopus (91) Google Scholar, 19Thomson B.J. Finch R.G. Hepatitis C virus infection.Clin. Microbiol. Infect. 2005; 11: 86-94Abstract Full Text Full Text PDF PubMed Scopus (99) Google Scholar). In this disease, the liver elicits a persistent inflammatory and repair response known as fibrosis, which is characterized by the formation of fibrous tissue and scarring on the liver. Because the prognosis of HCV patients is related to the development of fibrosis and the risk of cirrhosis and hepatocellular carcinoma, an accurate evaluation of fibrogenic progression is important for patient care. Currently, liver biopsies represent the primary technique for generating accurate information on the degree of fibrosis; however, they have multiple disadvantages, including risk of complications (i.e. major bleeding or inadvertent puncture of the lung, kidney, or colon), cost and occasionally inaccurate findings due to small specimen size and variability in the histology evaluation. These disadvantages have spurred the development of noninvasive methods that can reliably predict, diagnose and assess the degree of fibrosis (20Mukherjee S. Sorrell M.F. Noninvasive tests for liver fibrosis.Semin. Liver Dis. 2006; 26: 337-347Crossref PubMed Scopus (18) Google Scholar, 21Plebani M. Basso D. Non-invasive assessment of chronic liver and gastric diseases.Clin. Chim. Acta. 2007; 381: 39-49Crossref PubMed Scopus (21) Google Scholar). In this study, blood serum samples chosen from 60 HCV patients following liver transplantation at the University of Washington Medical Center were initially utilized to evaluate the LC-IMS-MS platform for clinical use (Fig. 2). These 60 samples represented 30 patients termed nonprogressors (NP) who showed no or mild return of fibrosis over a range of times postliver transplant (2 to 4 years), compared with 30 patients who developed "stage 3 to 4" fibrosis over a similar period of time and were stratified into either slow progressors (SP; stage 3–4 fibrosis at 3–4 years posttransplant) or fast progressors (FP; stage 3–4 fibrosis within 2 years posttransplant). The degree of fibrosis in these transplant patients was scored from 0 to 4 utilizing the Batts-Ludwig scoring system, and the serum samples were collected at a specific time point posttransplant (See supplemental Table S1 and Supplemental transplant sample data). Using a multivariate approach, patients were matched for donor age, cold ischemia time of the transplanted organ and time to biopsy, which are the most important clinical variables known to influence the risk of fibrosis progression associated with recurrent hepatitis C after liver transplantation. Final matching resulted in 30 patient pairs (progressor versus nonprogressor) and all samples were analyzed as technical replicates utilizing the LC-IMS-MS platform for global proteome evaluation of each patient sample. Following data acquisition of the 60 HCV liver transplant serum samples with LC-IMS-MS, overall statistical significance was assessed. Initially, peptides distinguishing NP, SP, and FP conditions with significant differential abundance were analyzed and then protein significance was evaluated by merging these peptides. To determine the significance of the peptides, PNNL's DAnTE software was utilized to convert the peak intensity values to a log2 scale and statistically compare them utilizing ANOVA for generation of p- and q-values (22Polpitiya A.D. Qian W.J. Jaitly N. Petyuk V.A. Adkins J.N. Camp 2nd, D.G. Anderson G.A. Smith R.D. DAnTE: a statistical tool for quantitative analysis of -omics data.Bioinformatics. 2008; 24: 1556-1558Crossref PubMed Scopus (328) Google Scholar). Our analysis only focused on significantly changing peptides with q-values 91% are observed with common abundance directionality, providing a strong orthogonal validation of core proteins based upon both transplant and nontransplant studies. Furthermore, of the 15 proteins uniquely significant in the nontransplant data, half have supporting significant peptides in the transplant data, but were excluded due to lack of multiple peptides per protein. (See supplemental Table S9C for protein overlap information). To provide further validation of the results from the LC-IMS-MS platform, a subset of Western blot immunoassays were performed on five proteins with significant differential abundance in both the transplant and nontransplant patients groups (F2, C4A, QSOX1, ECM1, and LGALS3BP). Within the LC-IMS-MS studies, F2 and C4A both decrease in patients with fibrosis while QSOX1, ECM1, and LGALS3BP increase. These results were essentially mirrored in the immunoassay blot results where two transplant NP-FP patient pair serum samples were blotted for each protein as shown in Fig. 5. Corresponding bar graphs representing the LC-IMS-MS measured protein values are also shown in Fig. 5. The Western blots provided orthogonal validation of the LC-IMS-MS platform with both techniques showing good agreement for all five proteins. Overall, the experiments performed in this manuscript illustrate that the multidimensional LC-IMS-MS platform greatly improves upon existing MS technologies in analytical sensitivity and specificity, enhances dynamic range of measurements, and provides reliable identification and quantitation of low abundance analyte species in highly complex biological matrices. Additionally the enhanced throughput of the new platform highlights the ability of this technology for pursuing large clinical-based global studies. Though we fully expect continued sensitivity and throughput advancements, the development and demonstration of the current platform sets a key foundational benchmark for further efforts. The results for the application of this platform to blood serum samples from stratified postliver transplant and nontransplant patients comparing both recurrent and persistent fibrosis progression illustrate that accurate detection and identification of larger panels of protein markers, rather than more limited individual biomarkers, is feasible with this platform and can potentially aid in the tracking and determination of disease progression. The pursuit of future medical techniques such as personal profiling will likely require a broadening of potential diagnostic metrics, as partially demonstrated in the current study, where greater levels of detection for proteins and associated platforms will be key drivers. For example, early disease onset may be better detected by correlating an individual's protein abundances to a baseline panel established specifically for that person prior to disease onset instead of attempting to correlate a specific protein abundance value defined for an entire population. This would of course require a broadly accepted protocol for routine serum collection and analysis of healthy people. Current MS approaches have technological advantages over immunoassays and/or similar technologies for analyzing multiple proteins simultaneously. Coupling the IMS separation to MS greatly increases measurement sensitivity while simultaneously reducing analysis time, leaving the IMS-MS platform as a key promoter of such an application in a clinical setting. However, we fully realize that this represents a paradigm shift in methodologies, and requires time and effort to develop the ancillary tools needed. We thank Michael Perkins and Nathan Johnson for assistance in preparing the figures, Ryan Sontag for help with immunoblots, and Penny Colton for technical editing of the manuscript. Download .zip (60.78 MB) Help with zip files