Elisa Bellei

High-abundance proteins depletion for serum proteomic analysis: concomitant removal of non-targeted proteins

In clinical and pharmaceutical proteomics, serum and plasma are frequently used for detection of early diagnostic biomarkers for therapeutic targets. Although obtaining these body fluid samples is non-invasive and easy, they contain some abundant proteins that mask other protein components present at low concentrations. The challenge in identifying serum biomarkers is to remove the abundant proteins, uncovering and enriching at the same time the low-abundance ones. The depletion strategies, however, could lead to the concomitant removal of some non-targeted proteins that may be of potential interest. In this study, we compared three different methods aimed to deplete high-abundance proteins from human serum, focusing on the identification of non-specifically bound proteins which might be eventually removed. A Cibacron blue-dye-based method for albumin removal, an albumin and IgG immunodepletion method and an immunoaffinity column (Multiple Affinity Removal System) that simultaneously removes a total of six high-abundance proteins, were investigated. The bound proteins were eluted, separated by two-dimensional gel electrophoresis and identified by Nano LC-CHIP-MS system. Flow-through fractions and bound fractions were also analysed with the ProteinChip technology SELDI-TOF-MS. Our results showed that the methods tested removed not only the targeted proteins with high efficiency, but also some non-targeted proteins. We found that the Multiple Affinity Removal Column improved the intensity of low-abundance proteins, displayed new protein spots and increased resolution. Notably, the column showed the lowest removal of untargeted proteins, proved to be the most promising depletion approach and a reliable method for serum preparation prior to proteomic studies.

Proteomic analysis of early urinary biomarkers of renal changes in type 2 diabetic patients

Diabetic nephropathy (DN) is a complication associated with diabetes, leading to end‐stage renal disease (ESRD). Despite significant progress in understanding DN, the cellular mechanisms leading to the renal damage are incompletely defined. In this study, with the aim to identify urine biomarkers for the early renal alterations in type 2 diabetes mellitus (T2D), we performed urinary proteomic analysis of 10 normoalbuminuric patients with T2D, 12 patients with type 2 DN (T2DN), and 12 healthy subjects. Proteins were separated by 2‐DE and identified with ESI‐Q‐TOF MS/MS. Comparing the patients proteomic profiles with those of normal subjects, we identified 11 gradually differently changed proteins. The decreased proteins were the prostatic acid phosphatase precursor, the ribonuclease and the kallikrein‐3. Eight proteins were progressively increased in both patients groups: transthyretin precursor, Ig κ chain C region, Ig κ chain V‐II region Cum, Ig κ‐chain V‐III region SIE, carbonic anhydrase 1, plasma retinol‐binding protein, β‐2‐microglobulin precursor, β‐2‐glycoprotein 1.

Enriched sera protein profiling for detection of non-small cell lung cancer biomarkers

BackgroundNon Small Cell Lung Cancer (NSCLC) is the major cause of cancer related-death. Many patients receive diagnosis at advanced stage leading to a poor prognosis. At present, no satisfactory screening tests are available in clinical practice and the discovery and validation of new biomarkers is mandatory. Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-ToF-MS) is a recent high-throughput technique used to detect new tumour markers. In this study we performed SELDI-ToF-MS analysis on serum samples treated with the ProteoMiner™ kit, a combinatorial library of hexapeptide ligands coupled to beads, to reduce the wide dynamic range of protein concentration in the sample. Serum from 44 NSCLC patients and 19 healthy controls were analyzed with IMAC30-Cu and H50 ProteinChip Arrays.ResultsComparing SELDI-ToF-MS protein profiles of NSCLC patients and healthy controls, 28 protein peaks were found significantly different (p < 0.05), and were used as predictors to build decision classification trees. This statistical analysis selected 10 protein peaks in the low-mass range (2-24 kDa) and 6 in the high-mass range (40-80 kDa). The classification models for the low-mass range had a sensitivity and specificity of 70.45% (31/44) and 68.42% (13/19) for IMAC30-Cu, and 72.73% (32/44) and 73.68% (14/19) for H50 ProteinChip Arrays.ConclusionsThese preliminary results suggest that SELDI-ToF-MS protein profiling of serum samples pretreated with ProteoMiner™ can improve the discovery of protein peaks differentially expressed between NSCLC patients and healthy subjects, useful to build classification algorithms with high sensitivity and specificity. However, identification of the significantly different protein peaks needs further study in order to provide a better understanding of the biological nature of these potential biomarkers and their role in the underlying disease process.

The effect of chronic kidney disease on the urine proteome in the domestic cat (Felis catus).

Chronic kidney disease (CKD) is a major cause of mortality in cats, but sensitive and specific biomarkers for early prediction and monitoring of CKD are currently lacking. The present study aimed to apply proteomic techniques to map the urine proteome of the healthy cat and compare it with the proteome of cats with CKD. Urine samples were collected by cystocentesis from 23 healthy young cats and 17 cats with CKD. One-dimensional sodium-dodecyl-sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) was conducted on 4-12% gels. Two-dimensional electrophoresis (2DE) was applied to pooled urine samples from healthy cats (n = 4) and cats with CKD (n = 4), respectively. Sixteen protein bands and 36 spots were cut, trypsin-digested and identified by mass spectrometry. 1D-SDS-PAGE yielded an overall view of the protein profile and the separation of 32 ± 6 protein bands in the urine of healthy cats, while CKD cats showed significantly fewer bands (P < 0.01). 2-DE was essential in fractionation of the complex urine proteome, producing a reference map that included 20 proteins. Cauxin was the most abundant protein in urine of healthy cats. Several protease inhibitors and transport proteins that derive from plasma were also identified, including alpha-2-macroglobulin, albumin, transferrin, haemopexin and haptoglobin. There was differential expression of 27 spots between healthy and CKD samples (P < 0.05) and 13 proteins were unambiguously identified. In particular, increased expression of retinol-binding protein, cystatin M and apolipoprotein-H associated with decreased expression of uromodulin and cauxin confirmed tubular damage in CKD cats suggesting that these proteins are candidate biomarkers.

The omics in migraine

The term omics consist of three main areas of molecular biology, such as genomics, proteomics and metabolomics. The omics synergism recognise migraine as an ideal study model, due to its multifactorial nature. In this review, the plainly research data featuring in this complex network are reported and analyzed, as single or multiple factor in pathophysiology of migraine. The future of migraine biomolecular research shall be focused on networking among these different and hierarchical disciplines. We have to look for its Ariadne’s tread, in order to see the whole painting of migraine molecular biology.

Inflammation: an important parameter in the search of prostate cancer biomarkers

BackgroundA more specific and early diagnostics for prostate cancer (PCa) is highly desirable. In this study, being inflammation the focus of our effort, serum protein profiles were analyzed in order to investigate if this parameter could interfere with the search of discriminating proteins between PCa and benign prostatic hyperplasia (BPH).MethodsPatients with clinical suspect of PCa and candidates for trans-rectal ultrasound guided prostate biopsy (TRUS) were enrolled. Histological specimens were examined in order to grade and classify the tumor, identify BPH and detect inflammation. Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (SELDI-ToF-MS) and two-dimensional gel electrophoresis (2-DE) coupled with Liquid Chromatography-MS/MS (LC-MS/MS) were used to analyze immuno-depleted serum samples from patients with PCa and BPH.ResultsThe comparison between PCa (with and without inflammation) and BPH (with and without inflammation) serum samples by SELDI-ToF-MS analysis did not show differences in protein expression, while changes were only observed when the concomitant presence of inflammation was taken into consideration. In fact, when samples with histological sign of inflammation were excluded, 20 significantly different protein peaks were detected. Subsequent comparisons (PCa with inflammation vs PCa without inflammation, and BPH with inflammation vs BPH without inflammation) showed that 16 proteins appeared to be modified in the presence of inflammation, while 4 protein peaks were not modified. With 2-DE analysis, comparing PCa without inflammation vs PCa with inflammation, and BPH without inflammation vs the same condition in the presence of inflammation, were identified 29 and 25 differentially expressed protein spots, respectively. Excluding samples with inflammation the comparison between PCa vs BPH showed 9 unique PCa proteins, 4 of which overlapped with those previously identified in the presence of inflammation, while other 2 were new proteins, not identified in our previous comparisons.ConclusionsThe present study indicates that inflammation might be a confounding parameter during the proteomic research of candidate biomarkers of PCa. These results indicate that some possible biomarker-candidate proteins are strongly influenced by the presence of inflammation, hence only a well-selected protein pattern should be considered for potential marker of PCa.

Non-bacterial protein expression in periodontal pockets by proteome analysis.

OBJECTIVES To compare the proteomic profile of inter-proximal pocket tissues with inter-proximal healthy tissues in the same subject to reveal proteins associated with periodontal disease in sites where periodontopathogenic bacteria were not detectable. METHODS Twenty-five healthy patients, with moderate-to-advanced chronic periodontitis and presenting with at least one intra-bony defect next to a healthy inter-proximal site were enrolled. The periodontal defects were treated with osseous resective surgery, and the flap design included both the periodontal pockets and the neighbouring inter-proximal healthy sites. Pocket-associated and healthy tissues were harvested for proteomic analyses. RESULTS Fifteen proteins were differently expressed between pathological and healthy tissues. In particular, annexin A2, actin cytoplasmic 1, carbonic anhydrase 1 & 2; Ig kappa chain C region (two spots) and flavinreductase were overexpressed, whereas 14-3-3 protein sigma and zeta/delta, heat-shock protein beta -1 (two spots), triosephosphateisomerase, peroxiredoxin-1, fatty acid-binding protein-epidermal, and galectin-7 were underexpressed in pathological tissue. CONCLUSIONS The unbalanced functional network of proteins involved could hinder adequate tissue response to pathogenic noxa. The study of periodontal pocket tissue proteomic profile would be crucial to better understand the pathogenesis of and the therapeutic strategies for periodontitis.

Optimizing protein recovery yield from serum samples treated with beads technology

Proteomics studies are often complicated by the wide dynamic range of the biological fluids, in which few highly abundant proteins obscure the signal of low abundant ones. To overcome this problem, several techniques have been developed on the basis of “depletion principles,” namely immuno‐subtraction with specific antibodies against the most‐abundant proteins. Unfortunately, the probability of codepletion is a noteworthy drawback associated with these strategies. The ProteoMiner™ (PM) technology is a novel approach, consisting of a combinatorial library of hexapeptide ligands coupled to beads, that allows the capture of all species present in a proteome, but at much reduced protein concentration differences, simultaneously enhancing the concentration of the most dilute species. In this study, we evaluated the compatibility of the PM kits elution reagent with 2‐DE analysis, comparing five different purification methods on serum samples eluted from the beads: the “ReadyPrep 2‐D Clean‐up kit” and precipitation with organic solvents, as acetone/methanol, TCA/acetone, ACN, and chloroform/methanol. Considering protein recovery yield (quantity) and 2‐DE spot pattern (quality), precipitation with ACN offered the most promising approach, showing the best spot resolution in all regions of the pH gradient and the greatest number of protein spots visualized on 2‐D gels.

Discovery by a proteomic approach of possible early biomarkers of drug-induced nephrotoxicity in medication-overuse headache

BackgroundMedication-overuse headache (MOH) is a chronic headache condition that results from the overuse of analgesics drugs, triptans, or other antimigraine compounds. The epidemiology of drug-induced disorders suggests that medication overuse could lead to nephrotoxicity, particularly in chronic patients. The aim of this work was to confirm and extend the results obtained from a previous study, in which we analyzed the urinary proteome of 3 MOH patients groups: non-steroidal anti-inflammatory drugs (NSAIDs), triptans and mixtures abusers, in comparison with non-abusers individuals (controls).MethodsIn the present work we employed specialized proteomic techniques, namely two-dimensional gel electrophoresis (2-DE) coupled with mass spectrometry (MS), and the innovative Surface-Enhanced Laser Desorption/Ionization Time-of-Flight mass spectrometry (SELDI-TOF-MS), to discover characteristic proteomic profiles associated with MOH condition.ResultsBy 2-DE and MS analysis we identified 21 over-excreted proteins in MOH patients, particularly in NSAIDs abusers, and the majority of these proteins were involved in a variety of renal impairments, as resulted from a literature search. Urine protein profiles generated by SELDI-TOF-MS analysis showed different spectra among groups. Moreover, significantly higher number of total protein spots and protein peaks were detected in NSAIDs and mixtures abusers.ConclusionsThese findings confirm the presence of alterations in proteins excretion in MOH patients. Analysis of urinary proteins by powerful proteomic technologies could lead to the discovery of early candidate biomarkers, that might allow to identify MOH patients prone to develop potential drug overuse-induced nephrotoxicity.

New horizon in dialysis depuration: Characterization of a polysulfone membrane able to break the ‘albumin wall’

The uremic syndrome is attributed to the progressive retention of a large number of toxins, which under normal conditions are excreted by the healthy kidneys. Standard dialytic membranes do not purify middle-high molecular weight toxins. Haemodiafiltration with endogenous reinfusion coupled with a highly permeable membrane could break the limit of the ‘albumin wall’ improving the dialytic depuration without loss of important nutrients. The aim of this study was to evaluate the performance of a new polysulfone membrane, Synclear 0.2, to remove uremic molecules. Surface Enhanced Laser Desorption Ionization-Time of Flight was employed to evaluate the proteomic profile of ultrafiltrate and Electrospray Ionization-Quadruple-ToF coupled with on-chip elution was used for proteins identification. A high and specific permeability for middle-high molecular weight molecules was revealed by mass spectrometry for the investigated membrane. The identified proteins are mostly uremic toxins: their relative abundance, estimated in the ultrafiltrate by exponentially modified protein abundance index, showed a high purification efficiency of the new membrane when compared with conventional ones. In conclusion, Synclear 0.2, used as convective membrane in hemodiafiltration with endogenous reinfusion treatment, permits to break the ‘albumin wall’, clearing middle-high molecular weight uremic toxins, improving the dialytic treatment purification efficiency.