Quantitative proteomic analysis of Down syndrome in the umbilical cord blood using iTRAQ

Identification of C. elegans ASNA-1 domains and tissue requirements that differentially influence platinum sensitivity and growth control

ASNA1 plays an essential role in cisplatin chemotherapy response, type 2 diabetes, and heart disease. It is also an important biomarker in the treatment response of many diseases. Biochemically, ASNA1 has two mutually exclusive redox-modulated roles: a tail-anchored protein (TAP) targeting function in the reduced state and a holdase/chaperone function in the oxidized state. Assigning biochemical roles of mammalian ASNA1 to biomedical functions is crucial for successful therapy development. Our previous work showed the relevance of the C. elegans ASNA-1 homolog in modeling cisplatin response and insulin secretion. Here we analyzed two-point mutants in highly conserved residues in C. elegans ASNA-1 and determined their importance in separating the cisplatin response function from its roles in insulin secretion. asna-1(ΔHis164) and asna-1(A63V) point mutants, which both preferentially exist in the oxidized state, displayed cisplatin sensitivity phenotype as well as TAP insertion defect but not an insulin secretion defect. Further, using targeted depletion we analyzed the tissue requirements of asna-1 for C. elegans growth and development. Somatic depletion of ASNA-1 as well as simultaneous depletion of ASNA-1 in neurons and intestines resulted in an L1 arrest. We concluded that, targeting single residues in ASNA-1 affecting Switch I/Switch II domain function, in comparison to complete knockdown counteracted cisplatin resistance without jeopardizing other important biological functions. Taken together, our study shows that effects on health caused by ASNA1 mutations can have different biochemical bases.

Complement factors and alpha-fetoprotein as biomarkers for noninvasive prenatal diagnosis of neural tube defects

Neural tube defects (NTDs) are serious congenital malformations. In this study, we aimed to identify more specific and sensitive maternal serum biomarkers for noninvasive NTD screenings. We collected serum from 37 pregnant women carrying fetuses with NTDs and 38 pregnant women carrying normal fetuses. Isobaric tags for relative and absolute quantitation were conducted for differential proteomic analysis, and an enzyme-linked immunosorbent assay was used to validate the results. We then used a support vector machine (SVM) classifier to establish a disease prediction model for NTD diagnosis. We identified 113 differentially expressed proteins; of these, 23 were either up- or downregulated 1.5-fold or more, including five complement proteins (C1QA, C1S, C1R, C9, and C3); C3 and C9 were downregulated significantly in NTD groups. The accuracy rate of the SVM model of the complement factors (including C1QA, C1S, and C3) was 62.5%, with 60% sensitivity and 67% specificity, while the accuracy rate of the SVM model of alpha-fetoprotein (AFP, an established biomarker for NTDs) was 62.5%, with 75% sensitivity and 50% specificity. Combination of the complement factor and AFP data resulted in the SVM model accuracy of 75%, and receiver operating characteristic curve analysis showed 75% sensitivity and 75% specificity. These data suggest that a disease prediction model based on combined complement factor and AFP data could serve as a more accurate method of noninvasive prenatal NTD diagnosis.

Proteomic analysis of differentially expressed proteins in the serum of patients with acute renal allograft rejection using iTRAQ labelling technology

Transplantation is currently the best treatment for patients with end‑stage renal disease. However, acute rejection (AR) is the major source of failure in renal transplantation. The current best practice for the diagnosis of AR involves renal biopsy, but it is invasive, time‑consuming, costly and inconvenient. Sensitive and less invasive detection of AR episodes in renal transplant patients is essential to preserve allograft function. The present study applied isobaric tags for relative and absolute quantitation (iTRAQ) mass spectrometry to analyze serum protein expression in patients with AR and healthy controls. Overall, 1,399 proteins were identified. Using a cut‑off of Q<0.05 and a fold change of >1.2 for the variation in expression, 109 proteins were identified to be differentially expressed between the AR and control groups, 72 of which were upregulated and 37 were downregulated. Several proteins, including properdin, keratin 1, lipoprotein(a) and vitamin D‑binding protein, may have roles in the pathogenesis of AR. The present study focused on iTRAQ‑based proteomic profiling of serum samples in AR. Insight from the present study may help advance the understanding of the molecular mechanisms of AR and identify potential novel biomarkers of AR for further characterization.

Quantitative proteomic analysis of down syndrome biomarkers in maternal serum using isobaric tags for relative and absolute quantification (iTRAQ)

Prenatal diagnosis of Down syndrome (DS) is based on calculated risk involving maternal age, biochemical and ultrasonographic markers, and, more recently, cell-free DNA (cfDNA). The present study was designed to identify Down Syndrome biomarkers in maternal serum. We quantified the changes in maternal serum protein levels between 10 non-pregnant women, 10 pregnant women with healthy fetuses, and 10 pregnant women with DS fetuses using isobaric tags for relative and absolute quantification (iTRAQ). We subsequently conducted a Gene Ontology (GO) analysis. A total of 470 proteins were identified, 11 of which had significantly different serum levels between the DS fetus group and Healthy fetuses group. Our data shows the identified proteins may be relevant to DS and constitute potential DS biomarkers.

Peptidomics analysis of umbilical cord blood reveals potential preclinical biomarkers for neonatal respiratory distress syndrome

AIMS

The purpose of this study was to investigate the pathophysiology and discover novel predictors of neonatal respiratory distress syndrome (NRDS) from a peptidomics perspective.

MAIN METHODS

Comparative profiling of umbilical cord blood from NRDS and control patients was performed by liquid chromatography tandem mass spectrometry technology. The underlying biological functions of the differentially expressed peptides (DEPs) were predicted by Gene Ontology (GO) and KEGG pathway analyses. The interactions of DEPs and their precursor proteins were explored by ingenuity pathway analysis (IPA). The sources and stability of DEPs were determined by online databases, including UniProt, SMART and ProtParam tool.

KEY FINDINGS

A total of 251 DEPs were identified, of which 139 peptides were upregulated, and 112 peptides were downregulated (fold change ≥2.0, P < 0.05). These DEPs were predicted to be associated with respiratory failure, atelectasis, and morphogenesis of endothelial cells. These processes indicated that DEPs may play a role in NRDS. Among them, eleven stable DEPs might be used as preclinical biomarkers.

SIGNIFICANCE

Our findings improve our understanding of NRDS and facilitate the discovery of candidate diagnostic biomarkers for NRDS from the perspective of peptidomics.

Comparative proteomic analysis of human serum before and after liver transplantation using quantitative proteomics

Liver cancer is the second leading cause of cancer mortality worldwide. Safer and more effective diagnostic methods for liver cancer are desirable, and biomarkers represent a potentially alternative method for diagnosis. The present study was designed to identify liver cancer biomarkers. We quantified the changes in serum protein levels between liver transplantation and healthy (control) females using isobaric tags for relative and absolute quantitation (iTRAQ) as well as proteomic analysis. A total of 1399 proteins were identified; of these, three proteins showed significantly different concentrations between the before transplantation group and the control group. These proteins may thus be relevant to liver cancer and constitute potential liver cancer biomarkers.

Proteomics of reproduction: Prospects and perspectives

In recent years, proteomics has been used widely in reproductive research in order to understand the molecular mechanisms related to gametes at the cellular level and the role of proteins involved in fertilization. Network and pathway analysis using bioinformatic tools have paved way to obtain a wider picture on the possible pathways associated with the key differentially expressed proteins (DEPs) and its implication in various infertility scenarios. A brief overview of advanced techniques and bioinformatic tools used for reproductive proteomics is presented. Key findings of proteomic-based studies on male and female reproduction are also presented. Furthermore, the chapter sheds light on the cellular pathways and potential biomarkers associated with male and female infertility. Proteomics coupled with bioinformatic analysis provides an ideal platform for non-invasive management of infertility in couples.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

The Use of Proteomics in Assisted Reproduction

Despite the explosive increase in the use of Assisted Reproductive Technologies (ART) over the last 30 years, their success rates remain suboptimal. Proteomics is a rapidly-evolving technology-driven science that has already been widely applied in the exploration of human reproduction and fertility, providing useful insights into its physiology and leading to the identification of numerous proteins that may be potential biomarkers and/or treatment targets of a successful ART pregnancy. Here we present a brief overview of the techniques used in proteomic analyses and attempt a comprehensive presentation of recent data from mass spectrometry-based proteomic studies in humans, regarding all components of ARTs, including the male and female gamete, the derived zygote and embryo, the endometrium and, finally, the ART offspring both pre- and postnatally.

Integrated microRNA and protein expression analysis reveals novel microRNA regulation of targets in fetal down syndrome

Down syndrome (DS) is caused by trisomy of human chromosome 21 and is associated with a number of deleterious phenotypes. To investigate the role of microRNA (miRNA) in the regulation of DS, high‑throughput Illumina sequencing technology and isobaric tagging for relative and absolute protein quantification analysis were utilized for simultaneous expression profiling of miRNA and protein in fetuses with DS and normal fetuses. A total of 344 miRNAs were associated with DS. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to investigate the proteins found to be differentially expressed. Functionally important miRNAs were determined by identifying enriched or depleted targets in the transcript and the protein expression levels were consistent with miRNA regulation. The results indicated that GRB2, TMSB10, RUVBL2, the hsa‑miR‑329 and hsa‑miR‑27b, hsa‑miR‑27a targets, and MAPK1, PTPN11, ACTA2 and PTK2 or other differentially expressed proteins were connected with each other directly or indirectly. Integrative analysis of miRNAs and proteins provided an expansive view of the molecular signaling pathways in DS.