Syringe-push membrane absorption as a simple rapid method of urine preparation for clinical proteomics

Background

The analysis of urinary proteome might reveal biomarkers of clinical value. However, current methods of urine preparation for down-stream proteomic analysis are complicated, time-consuming, and/or expensive. This study aims to develop a robust, simple, inexpensive and readily accessible urine preparation method to facilitate clinical proteomic workflow.

Result

Syringe-push membrane absorption (SPMA) was successfully developed by a combination of 5-ml medical syringe and protein-absorbable membrane. Comparing three membranes i.e., nitrocellulose, polyvinylidene difluoride (PVDF) and Whatman no.1, nitrocellulose combined with SPMA (nitrocellulose-SPMA) provided the greatest quality of proteome profile as demonstrated by 2-DE. The quality of the proteome profile and the performance of nitrocellulose-SPMA were systematically compared with three current methods of urine preparation (i.e., ultrafiltration, dialysis/lyophilization and precipitation). While different methods of urine preparation provided comparable proteome quality, nitrocellulose-SPMA had better working performance due to acceptable recovery yield, less workload, short working time, high accessibility and low unit cost. In addition, protein absorbed on nitrocellulose harvested from the SPMA procedure could be stored as a dried membrane at room temperature for at least 1-month without protein degradation or modification.

Conclusions

SPMA is a simple rapid method of preparing urine for downstream proteomic analysis. Because of it is highly accessible and has long storage duration, this technique holds potential benefit for large-scale multi-center research and future development of clinical investigation based upon urinary proteomic analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9087-4) contains supplementary material, which is available to authorized users.     

Development of a high-throughput method for the systematic identification of human proteins nuclear translocation potential

Background  

Important clues to the function of novel and uncharacterized proteins can be obtained by identifying their ability to translocate in the nucleus. In addition, a comprehensive definition of the nuclear proteome undoubtedly represents a key step toward a better understanding of the biology of this organelle. Although several high-throughput experimental methods have been developed to explore the sub-cellular localization of proteins, these methods tend to focus on the predominant localizations of gene products and may fail to provide a complete catalog of proteins that are able to transiently locate into the nucleus.     

Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

Background

Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration ≥5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82).

Methodology/Principal Findings

Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient''s subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients.

Conclusions

These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin.     

Dual targeted mitochondrial proteins are characterized by lower MTS parameters and total net charge

Background

In eukaryotic cells, identical proteins can be located in different subcellular compartments (termed dual-targeted proteins).

Methodology/Principal Findings

We divided a reference set of mitochondrial proteins (published single gene studies) into two groups: i) Dual targeted mitochondrial proteins and ii) Exclusive mitochondrial proteins. Mitochondrial proteins were considered dual-targeted if they were also found or predicted to be localized to the cytosol, the nucleus, the endoplasmic reticulum (ER) or the peroxisome. We found that dual localized mitochondrial proteins have i) A weaker mitochondrial targeting sequence (MitoProtII score, hydrophobic moment and number of basic residues) and ii) a lower whole-protein net charge, when compared to exclusive mitochondrial proteins. We have also generated an annotation list of dual-targeted proteins within the predicted yeast mitochondrial proteome. This considerably large group of dual-localized proteins comprises approximately one quarter of the predicted mitochondrial proteome. We supported this prediction by experimental verification of a subgroup of the predicted dual targeted proteins.

Conclusions/Significance

Taken together, these results establish dual targeting as a widely abundant phenomenon that should affect our concepts of gene expression and protein function. Possible relationships between the MTS/mature sequence traits and protein dual targeting are discussed.     

High throughput profile-profile based fold recognition for the entire human proteome

Background  

In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power.     

Urine proteome of autosomal dominant polycystic kidney disease patients

Background

Autosomal dominant polycystic kidney disease (ADPKD) is responsible for 10% of cases of the end stage renal disease. Early diagnosis, especially of potential fast progressors would be of benefit for efficient planning of therapy. Urine excreted proteome has become a promising field of the search for marker patterns of renal diseases including ADPKD. Up to now however, only the low molecular weight fraction of ADPKD proteomic fingerprint was studied. The aim of our study was to characterize the higher molecular weight fraction of urinary proteome of ADPKD population in comparison to healthy controls as a part of a general effort aiming at exhaustive characterization of human urine proteome in health and disease, preceding establishment of clinically useful disease marker panel.

Results

We have analyzed the protein composition of urine retentate (>10 kDa cutoff) from 30 ADPKD patients and an appropriate healthy control group by means of a gel-free relative quantitation of a set of more than 1400 proteins. We have identified an ADPKD-characteristic footprint of 155 proteins significantly up- or downrepresented in the urine of ADPKD patients. We have found changes in proteins of complement system, apolipoproteins, serpins, several growth factors in addition to known collagens and extracellular matrix components. For a subset of these proteins we have confirmed the results using an alternative analytical technique.

Conclusions

Obtained results provide basis for further characterization of pathomechanism underlying the observed differences and establishing the proteomic prognostic marker panel.     

In-depth analysis of the chicken egg white proteome using an LTQ Orbitrap Velos

Background

Hen's egg white has been the subject of intensive chemical, biochemical and food technological research for many decades, because of its importance in human nutrition, its importance as a source of easily accessible model proteins, and its potential use in biotechnological processes. Recently the arsenal of tools used to study the protein components of egg white has been complemented by mass spectrometry-based proteomic technologies. Application of these fast and sensitive methods has already enabled the identification of a large number of new egg white proteins. Recent technological advances may be expected to further expand the egg white protein inventory.

Results

Using a dual pressure linear ion trap Orbitrap instrument, the LTQ Orbitrap Velos, in conjunction with data analysis in the MaxQuant software package, we identified 158 proteins in chicken egg white with two or more sequence unique peptides. This group of proteins identified with very high confidence included 79 proteins identified in egg white for the first time. In addition, 44 proteins were identified tentatively.

Conclusions

Our results, apart from identifying many new egg white components, indicate that current mass spectrometry technology is sufficiently advanced to permit direct identification of minor components of proteomes dominated by a few major proteins without resorting to indirect techniques, such as chromatographic depletion or peptide library binding, which change the composition of the proteome.     

Serum Proteome and Cytokine Analysis in a Longitudinal Cohort of Adults with Primary Dengue Infection Reveals Predictive Markers of DHF

Background

Infections caused by dengue virus are a major cause of morbidity and mortality in tropical and subtropical regions of the world. Factors that control transition from mild forms of disease such as dengue fever (DF) to more life-threatening forms such as dengue hemorrhagic fever (DHF) are poorly understood. Consequently, there are no reliable methods currently available for early triage of DHF patients resulting in significant over-hospitalization.

Methodology/Principal Findings

We have systematically examined the proteome, cytokines and inflammatory markers in sera from 62 adult dengue patients (44 DF; 18 DHF) with primary DENV infection, at three different times of infection representing the early febrile, defervescence and convalescent stages. Using fluorescent bioplex assays, we measured 27 cytokines in these serum samples. Additionally, we used multiple mass spectrometry methods for iTRAQ-based comparative analysis of serum proteome as well as measurements of protein adducts- 3-nitrotyrosine and 3-chlorotyrosine as surrogate measures of free radical activity. Using multiple methods such as OPLS, MRMR and MSVM-RFE for multivariate feature selection and classification, we report molecular markers that allow prediction of primary DHF with sensitivity and specificity of >80%.

Conclusions/Significance

This report constitutes a comprehensive analysis of molecular signatures of dengue disease progression and will help unravel mechanisms of dengue disease progression. Our analysis resulted in the identification of markers that may be useful for early prediction of DHF during the febrile phase. The combination of highly sensitive analytical methods and novel statistical approaches described here forms a robust platform for biomarker discovery.     

Identification of low-abundance proteins via fractionation of the urine proteome with weak anion exchange chromatography

Background  

Low-abundance proteins are difficultly observed on the two-dimensional gel electrophoresis (2-DE) maps of urine proteome, because they are usually obscured by high-abundance proteins such as albumin and immunoglobulin. In this study, a novel fractionation method was developed for enriching low-abundance proteins by removing high-abundance proteins and progressive elution with salts of various concentrations.     

Urinary Collagen Fragments Are Significantly Altered in Diabetes: A Link to Pathophysiology

Background

The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D).

Methodology/Principal Findings

Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92–95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81–94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81–88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed.

Conclusions/Significance

These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling.     

Quantifying raft proteins in neonatal mouse brain by 'tube-gel' protein digestion label-free shotgun proteomics

Background  

The low concentration and highly hydrophobic nature of proteins in lipid raft samples present significant challenges for the sensitive and accurate proteomic analyses of lipid raft proteins. Elimination of highly enriched lipids and interfering substances from raft samples is generally required before mass spectrometric analyses can be performed, but these procedures often lead to excessive protein loss and increased sample variability. For accurate analyses of the raft proteome, simplified protocols are needed to avoid excessive sample handling and purification steps.     

Proteomic profiling of urine for the detection of colon cancer

Background

Colorectal cancer is the second most common cause of cancer related death in the developed world. To date, no blood or stool biomarkers with both high sensitivity and specificity for potentially curable early stage disease have been validated for clinical use. SELDI and MALDI profiling are being used increasingly to search for biomarkers in both blood and urine. Both techniques provide information predominantly on the low molecular weight proteome (<15 kDa). There have been several reports that colorectal cancer is associated with changes in the serum proteome that are detectable by SELDI and we hypothesised that proteomic changes would also be detectable in urine.

Results

We collected urine from 67 patients with colorectal cancer and 72 non-cancer control subjects, diluted to a constant protein concentration and generated MALDI and SELDI spectra. The intensities of 19 peaks differed significantly between cancer and non-cancer patients by both t-tests and after adjusting for confounders using multiple linear regressions. Logistic regression classifiers based on peak intensities identified colorectal cancer with up to 78% sensitivity at 87% specificity. We identified and independently quantified 3 of the discriminatory peaks using synthetic stable isotope peptides (an 1885 Da fragment of fibrinogen and hepcidin-20) or ELISA (β2-microglobulin).

Conclusion

Changes in the urine proteome may aid in the early detection of colorectal cancer.     

High abundance proteins depletion vs low abundance proteins enrichment: comparison of methods to reduce the plasma proteome complexity

Background

To date, the complexity of the plasma proteome exceeds the analytical capacity of conventional approaches to isolate lower abundance proteins that may prove to be informative biomarkers. Only complex multistep separation strategies have been able to detect a substantial number of low abundance proteins (<100 ng/ml). The first step of these protocols is generally the depletion of high abundance proteins by the use of immunoaffinity columns or, alternatively, the enrichment of by the use of solid phase hexapeptides ligand libraries.

Methodology/Principal Findings

Here we present a direct comparison of these two approaches. Following either approach, the plasma sample was further fractionated by SCX chromatography and analyzed by RP-LC-MS/MS with a Q-TOF mass spectrometer. The depletion of the 20 most abundant plasma proteins allowed the identification of about 25% more proteins than those detectable following low abundance proteins enrichment. The two datasets are partially overlapping and the identified proteins belong to the same order of magnitude in terms of plasma concentration.

Conclusions/Significance

Our results show that the two approaches give complementary results. However, the enrichment of low abundance proteins has the great advantage of obtaining much larger amount of material that can be used for further fractionations and analyses and emerges also as a cheaper and technically simpler approach. Collectively, these data indicate that the enrichment approach seems more suitable as the first stage of a complex multi-step fractionation protocol.     

Short term optical defocus perturbs normal developmental shifts in retina/RPE protein abundance

Background

Myopia (short-sightedness) affects approximately 1.4 billion people worldwide, and prevalence is increasing. Animal models induced by defocusing lenses show striking similarity with human myopia in terms of morphology and the implicated genetic pathways. Less is known about proteome changes in animals. Thus, the present study aimed to improve understanding of protein pathway responses to lens defocus, with an emphasis on relating expression changes to no lens control development and identifying bidirectional and/or distinct pathways across myopia and hyperopia (long-sightedness) models.

Results

Quantitative label-free proteomics and gene set enrichment analysis (GSEA) were used to examine protein pathway expression in the retina/RPE of chicks following 6 h and 48 h of myopia induction with ??10 dioptre (D) lenses, hyperopia induction with +10D lenses, or normal no lens rearing. Seventy-one pathways linked to cell development and neuronal maturation were differentially enriched between 6 and 48 h in no lens chicks. The majority of these normal developmental changes were disrupted by lens-wear (47 of 71 pathways), however, only 11 pathways displayed distinct expression profiles across the lens conditions. Most notably, negative lens-wear induced up-regulation of proteins involved in ATP-driven ion transport, calcium homeostasis, and GABA signalling between 6 and 48 h, while the same proteins were down-regulated over time in normally developing chicks. Glutamate and bicarbonate/chloride transporters were also down-regulated over time in normally developing chicks, and positive lens-wear inhibited this down-regulation.

Conclusions

The chick retina/RPE proteome undergoes extensive pathway expression shifts during normal development. Most of these pathways are further disrupted by lens-wear. The identified expression patterns suggest close interactions between neurotransmission (as exemplified by increased GABA receptor and synaptic protein expression), cellular ion homeostasis, and associated energy resources during myopia induction. We have also provided novel evidence for changes to SLC-mediated transmembrane transport during hyperopia induction, with potential implications for signalling at the photoreceptor-bipolar synapse. These findings reflect a key role for perturbed neurotransmission and ionic homeostasis in optically-induced refractive errors, and are predicted by our Retinal Ion Driven Efflux (RIDE) model.

     

MOTIPS: Automated Motif Analysis for Predicting Targets of Modular Protein Domains

Background  

Many protein interactions, especially those involved in signaling, involve short linear motifs consisting of 5-10 amino acid residues that interact with modular protein domains such as the SH3 binding domains and the kinase catalytic domains. One straightforward way of identifying these interactions is by scanning for matches to the motif against all the sequences in a target proteome. However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy.     

Urinary Calprotectin and Posttransplant Renal Allograft Injury

Objective

Current methods do not predict the acute renal allograft injury immediately after kidney transplantation. We evaluated the diagnostic performance of urinary calprotectin for predicting immediate posttransplant allograft injury.

Methods

In a multicenter, prospective-cohort study of 144 incipient renal transplant recipients, we postoperatively measured urinary calprotectin using an enzyme-linked immunosorbent assay and estimated glomerular filtration rate (eGFR) after 4 weeks, 6 months, and 12 months.

Results

We observed a significant inverse association of urinary calprotectin concentrations and eGFR 4 weeks after transplantation (Spearman r = −0.33; P<0.001). Compared to the lowest quartile, patients in the highest quartile of urinary calprotectin had an increased risk for an eGFR less than 30 mL/min/1.73 m² four weeks after transplantation (relative risk, 4.3; P<0.001; sensitivity, 0.92; 95% CI, 0.77 to 0.98; specificity, 0.48; 95% CI, 0.31 to 0.66). Higher urinary calprotectin concentrations predicted impaired kidney function 4 weeks after transplantation, as well as 6 months and 12 months after transplantation. When data were analyzed using the urinary calprotectin/creatinine-ratio similar results were obtained. Urinary calprotectin was superior to current use of absolute change of plasma creatinine to predict allograft function 12 months after transplantation. Urinary calprotectin predicted an increased risk both in transplants from living and deceased donors. Multivariate linear regression showed that higher urinary calprotectin concentrations and older donor age predicted lower eGFR four weeks, 6 months, and 12 months after transplantation.

Conclusions

Urinary calprotectin is an early, noninvasive predictor of immediate renal allograft injury after kidney transplantation.     

Urinary and Dietary Analysis of 18,470 Bangladeshis Reveal a Correlation of Rice Consumption with Arsenic Exposure and Toxicity

Background

We utilized data from the Health Effects of Arsenic Longitudinal Study (HEALS) in Araihazar, Bangladesh, to evaluate the association of steamed rice consumption with urinary total arsenic concentration and arsenical skin lesions in the overall study cohort (N=18,470) and in a subset with available urinary arsenic metabolite data (N=4,517).

Methods

General linear models with standardized beta coefficients were used to estimate associations between steamed rice consumption and urinary total arsenic concentration and urinary arsenic metabolites. Logistic regression models were used to estimate prevalence odds ratios (ORs) and their 95% confidence intervals (CIs) for the associations between rice intake and prevalent skin lesions at baseline. Discrete time hazard models were used to estimate discrete time (HRs) ratios and their 95% CIs for the associations between rice intake and incident skin lesions.

Results

Steamed rice consumption was positively associated with creatinine-adjusted urinary total arsenic (β=0.041, 95% CI: 0.032-0.051) and urinary total arsenic with statistical adjustment for creatinine in the model (β=0.043, 95% CI: 0.032-0.053). Additionally, we observed a significant trend in skin lesion prevalence (P-trend=0.007) and a moderate trend in skin lesion incidence (P-trend=0.07) associated with increased intake of steamed rice.

Conclusions

This study suggests that rice intake may be a source of arsenic exposure beyond drinking water.