Improving the comprehensiveness and sensitivity of sheathless capillary electrophoresis-tandem mass spectrometry for proteomic analysis

We describe a solid phase microextraction (SPME), multistep elution, transient isotachophoresis (tITP) capillary electrophoresis-tandem mass spectrometry (CE-MS/MS) procedure which employs a high sensitivity porous electrospray ionization (ESI) sprayer for the proteomic analysis of a moderately complex protein mixture. In order to improve comprehensiveness and sensitivity over a previously reported proteomic application of the ESI sprayer, we evaluated preconcentration with SPME and multistep elution prior to tITP stacking and CE separation. To maximize separation efficiency, we primarily employed electrokinetic methods for elution and separation after loading the sample by application of pressure. Conditions were developed for optimum simultaneous electrokinetic elution and sample stacking using a tryptic digest of 16 proteins to maximize peptide identifications and minimize band broadening. We performed comparative proteomic analysis of a dilution series using CE and nanoflow liquid chromatography (nLC). We found complementary peptide and protein identifications with larger quantities (100 ng) of a Pyrococcus furiosus tryptic digest, but with mass-limited amounts (5 ng) CE was 3 times more effective at identifying proteins. We attribute these gains in sensitivity to lower noise levels with the porous CE sprayer, illustrated by better signal-to-noise ratios of peptide precursor ions and associated higher XCorr values of identified peptides when compared directly to nLC. From comparative analysis of SPME-tITP-CE with direct injection CE, the SPME-tITP process improved comprehensiveness and sensitivity.

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.

Molecular mechanisms of chronic kidney transplant rejection via large-scale proteogenomic analysis of tissue biopsies

The most common cause of kidney transplant failure is the poorly characterized histopathologic entity interstitial fibrosis and tubular atrophy (IFTA). There are no known unifying mechanisms, no effective therapy, and no proven preventive strategies. Possible mechanisms include chronic immune rejection, inflammation, drug toxicity, and chronic kidney injury from secondary factors. To gain further mechanistic insight, we conducted a large-scale proteogenomic study of kidney transplant biopsies with IFTA of varying severity. We acquired proteomic data using tandem mass spectrometry with subsequent quantification, analysis of differential protein expression, validation, and functional annotations to known molecular networks. We performed genome-wide expression profiling in parallel. More than 1400 proteins with unique expression profiles traced the progression from normal transplant biopsies to biopsies with mild to moderate and severe disease. Multiple sets of proteins were mapped to different functional pathways, many increasing with histologic severity, including immune responses, inflammatory cell activation, and apoptosis consistent with the chronic rejection hypothesis. Two examples include the extensive population of the alternative rather than the classical complement pathway, previously not appreciated for IFTA, and a comprehensive control network for the actin cytoskeleton and cell signaling of the acute-phase response. In summary, this proteomic effort using kidney tissue contributes mechanistic insight into several biologic processes associated with IFTA.

Biomarkers for early and late stage chronic allograft nephropathy by proteogenomic profiling of peripheral blood

Background

Despite significant improvements in life expectancy of kidney transplant patients due to advances in surgery and immunosuppression, Chronic Allograft Nephropathy (CAN) remains a daunting problem. A complex network of cellular mechanisms in both graft and peripheral immune compartments complicates the non-invasive diagnosis of CAN, which still requires biopsy histology. This is compounded by non-immunological factors contributing to graft injury. There is a pressing need to identify and validate minimally invasive biomarkers for CAN to serve as early predictors of graft loss and as metrics for managing long-term immunosuppression.

Methods

We used DNA microarrays, tandem mass spectroscopy proteomics and bioinformatics to identify genomic and proteomic markers of mild and moderate/severe CAN in peripheral blood of two distinct cohorts (n = 77 total) of kidney transplant patients with biopsy-documented histology.

Findings

Gene expression profiles reveal over 2400 genes for mild CAN, and over 700 for moderate/severe CAN. A consensus analysis reveals 393 (mild) and 63 (moderate/severe) final candidates as CAN markers with predictive accuracy of 80% (mild) and 92% (moderate/severe). Proteomic profiles show over 500 candidates each, for both stages of CAN including 302 proteins unique to mild and 509 unique to moderate/severe CAN.

Conclusions

This study identifies several unique signatures of transcript and protein biomarkers with high predictive accuracies for mild and moderate/severe CAN, the most common cause of late allograft failure. These biomarkers are the necessary first step to a proteogenomic classification of CAN based on peripheral blood profiling and will be the targets of a prospective clinical validation study.