Guixue Hou

Systematic Analyses of the Transcriptome, Translatome, and Proteome Provide a Global View and Potential Strategy for the C‑HPP

To estimate the potential of the state-of-the-art proteomics technologies on full coverage of the encoding gene products, the Chinese Human Chromosome Proteome Consortium (CCPC) applied a multiomics strategy to systematically analyze the transciptome, translatome, and proteome of the same cultured hepatoma cells with varied metastatic potential qualitatively and quantitatively. The results provide a global view of gene expression profiles. The 9064 identified high confident proteins covered 50.2% of all gene products in the translatome. Those proteins with function of adhesion, development, reproduction, and so on are low abundant in transcriptome and translatome but absent in proteome. Taking the translatome as the background of protein expression, we found that the protein abundance plays a decisive role and hydrophobicity has a greater influence than molecular weight and isoelectric point on protein detectability. Thus, the enrichment strategy used for low-abundant transcription factors helped to identify missing proteins. In addition, those peptides with single amino acid polymorphisms played a significant role for the disease research, although they might negligibly contribute to new protein identification. The proteome raw and metadata of proteome were collected using the iProX submission system and submitted to ProteomeXchange (PXD000529, PXD000533, and PXD000535). All detailed information in this study can be accessed from the Chinese Chromosome-Centric Human Proteome Database.

Biomarker Discovery and Verification of Esophageal Squamous Cell Carcinoma Using Integration of SWATH/MRM

We propose an efficient integration of SWATH with MRM for biomarker discovery and verification when the corresponding ion library is well established. We strictly controlled the false positive rate associated with SWATH MS signals and carefully selected the target peptides coupled with SWATH and MRM. We collected 10 samples of esophageal squamous cell carcinoma (ESCC) tissues paired with tumors and adjacent regions and quantified 1758 unique proteins with FDR 1% at protein level using SWATH, in which 467 proteins were abundance-dependent with ESCC. After carefully evaluating the SWATH MS signals of the up-regulated proteins, we selected 120 proteins for MRM verification. MRM analysis of the pooled and individual esophageal tissues resulted in 116 proteins that exhibited similar abundance response modes to ESCC that were acquired with SWATH. Because the ESCC-related proteins consisted of a high percentile of secreted proteins, we conducted the MRM assay on patient sera that were collected from pre- and postoperation. Of the 116 target proteins, 42 were identified in the ESCC sera, including 11 with lowered abundances postoperation. Coupling SWATH and MRM is thus feasible and efficient for the discovery and verification of cancer-related protein biomarkers.

Omics evidence: single nucleotide variants transmissions on chromosome 20 in liver cancer cell lines.

Cancer genomics unveils many cancer-related mutations, including some chromosome 20 (Chr.20) genes. The mutated messages have been found in the corresponding mRNAs; however, whether they could be translated to proteins still requires more evidence. Herein, we proposed a transomics strategy to profile the expression status of human Chr.20 genes (555 in Ensembl v72). The data of transcriptome and translatome (the mRNAs bound with ribosome, translating mRNAs) revealed that ∼80% of the coding genes on Chr.20 were detected with mRNA signals in three liver cancer cell lines, whereas of the proteome identified, only ∼45% of the Chr.20 coding genes were detected. The high amount of overlapping of identified genes in mRNA and RNC-mRNA (ribosome nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent distribution of the abundance averages of mRNA and RNC-mRNA along the Chr.20 subregions in three liver cancer cell lines indicate that the mRNA information is efficiently transmitted from transcriptional to translational stage, qualitatively and quantitatively. Of the 457 genes identified in mRNAs and RNC-mRNA, 136 were found to contain SNVs with 213 sites, and >40% of these SNVs existed only in metastatic cell lines, suggesting them as the metastasis-related SNVs. Proteomics analysis showed that 16 genes with 20 SNV sites were detected with reliable MS/MS signals, and some SNVs were further validated by the MRM approach. With the integration of the omics data at the three expression phases, therefore, we are able to achieve the overall view of the gene expression of Chr.20, which is constructive in understanding the potential trend of encoding genes in a cell line and exploration of a new type of markers related to cancers.

Expansion of the ion library for mining SWATH-MS data through fractionation proteomics.

The strategy of sequential window acquisition of all theoretical fragment ion spectra (SWATH) is emerging in the field of label-free proteomics. A critical consideration for the processing of SWATH data is the quality of the ion library (or mass spectrometric reference map). As the availability of open spectral libraries that can be used to process SWATH data is limited, most users currently create their libraries in-house. Herein, we propose an approach to construct an expanded ion library using the data-dependent acquisition (DDA) data generated by fractionation proteomics. We identified three critical elements for achieving a satisfactory ion library during the iterative process of our ion library expansion, including a correction of the retention times (RTs) gained from fractionation proteomics, appropriate integrations of the fractionated proteomics into an ion library, and assessments of the impact of the expanded ion libraries to data mining in SWATH. Using a bacterial lysate as an evaluation material, we employed sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to fractionate the lysate proteins and constructed the expanded ion library using the fractionation proteomics data. Compared with the ion library built from the unfractionated proteomics, approximately 20% more peptides were extracted from the expanded ion library. The extracted peptides, moreover, were acceptable for further quantitative analysis.

Quantitative Evaluation of the Mitochondrial Proteomes of Drosophila melanogaster Adapted to Extreme Oxygen Conditions

Mitochondria are the primary organelles that consume oxygen and provide energy for cellular activities. To investigate the mitochondrial mechanisms underlying adaptation to extreme oxygen conditions, we generated Drosophila strains that could survive in low- or high-oxygen environments (LOF or HOF, respectively), examined their mitochondria at the ultrastructural level via transmission electron microscopy, studied the activity of their respiratory chain complexes, and quantitatively analyzed the protein abundance responses of the mitochondrial proteomes using Isobaric tag for relative and absolute quantitation (iTRAQ). A total of 718 proteins were identified with high confidence, and 55 and 75 mitochondrial proteins displayed significant differences in abundance in LOF and HOF, respectively, compared with the control flies. Importantly, these differentially expressed mitochondrial proteins are primarily involved in respiration, calcium regulation, the oxidative response, and mitochondrial protein translation. A correlation analysis of the changes in the levels of the mRNAs corresponding to differentially regulated mitochondrial proteins revealed two sets of proteins with different modes of regulation (transcriptional vs. post-transcriptional) in both LOF and HOF. We believe that these findings will not only enhance our understanding of the mechanisms underlying adaptation to extreme oxygen conditions in Drosophila but also provide a clue in studying human disease induced by altered oxygen tension in tissues and cells.

The levels of serine proteases in colon tissue interstitial fluid and serum serve as an indicator of colorectal cancer progression

The proteins in tissue interstitial fluids (TIFs) can spread into the blood and have been proposed as an ideal material to find blood biomarkers. The colon TIFs were collected from 8-, 13-, 18-, and 22-week ApcMin/+, a typical mouse model of colorectal cancer (CRC), and wild-type mice. iTRAQ-based quantification proteomics was conducted to survey the TIF proteins whose abundance appeared to depend on tumor progression. A total of 46 proteins that exhibited consecutive changes in abundance were identified, including six serine proteases, chymotrypsin-like elastase 1 (CELA1), chymotrypsin-like elastase 2A (CEL2A), chymopasin, chymotrypsinogen B (CTRB1), trypsin 2 (TRY2), and trypsin 4 (TRY4). The observed increases in the abundance of serine proteases were supported in another quantitative evaluation of the individual colon TIFs using a multiple reaction monitor (MRM) assay. Importantly, the increases in the abundance of serine proteases were also verified in the corresponding sera. The quantitative verification of the serine proteases was further extended to the clinical sera, revealing significantly higher levels of CELA1, CEL2A, CTRL/chymopasin, and TRY2 in CRC patients. The receiver operating characteristic analysis illustrated that the combination of CELA1 and CTRL reached the best diagnostic performance, with 90.0% sensitivity and 80.0% specificity. Thus, the quantitative target analysis demonstrated that some serine proteases are indicative of CRC progression.

Discovery of potential colorectal cancer serum biomarkers through quantitative proteomics on the colonic tissue interstitial fluids from the AOM–DSS mouse model

UNLABELLED Quantitative proteomic analysis was performed using iTRAQ to discover colorectal cancer (CRC)-related proteins in tissue interstitial fluids (TIFs). A typical inflammation-related CRC mouse model was generated using azoxymethane-dextran sodium sulfate (AOM-DSS), and TIFs were collected from these mice in four stages during CRC development. Using stringent criteria, a total of 144 proteins displayed changes in their abundances during tumor growth, including 45 that consecutively increased, 17 that consecutively decreased and 82 that changed irregularly. Of these 144 proteins, 24 of the consecutively changed proteins were measured using MRM in individual TIF samples, and 18 were verified. Twelve proteins verified to be consecutively increased in TIFs were examined using MRM to evaluate changes in their abundance in individual mouse serum samples. The abundances of leucine-rich alpha-2-glycoprotein 1 (LRG1), tubulin beta-5 chain (TUBB5) and immunoglobulin J chain (IGJ) were significantly higher in CRC mice than in control mice. Using clinical samples and MRM, we further verified that LRG1 and TUBB5 are potential CRC serum biomarkers. These data demonstrate that coupling dynamic TIF proteomics with targeted serum proteomics in an animal model is a promising avenue for pursuing the discovery of tumor serum biomarkers. BIOLOGICAL SIGNIFICANCE Colorectal cancer (CRC) is one of the most dangerous diseases worldwide. However, few of CRC biomarkers possess satisfied specificity and sensitivity in clinical practices. Exploration of more CRC biomarkers, especially in serum, is an urgent and also a time-consuming campaign in the CRC study. Our study demonstrates that quantitatively evaluating the phase-dependent proteins in colonic tissue interstitial fluids from AOM-DSS mice is a feasible and effective way for exploration of the CRC-related proteins and the potential serum biomarkers. We identified two proteins, LRG1 and TUBB5, which may be practicable in human clinical samples as CRC serum biomarkers. To sum up, this study provides a novel angle to explore the critical factors in tumorigenesis and a new pipeline for potential serum biomarker discovery and verification.

Lipidomic profiling reveals distinct differences in plasma lipid composition in healthy, prediabetic, and type 2 diabetic individuals

Abstract The relationship between dyslipidemia and type 2 diabetes mellitus (T2D) has been extensively reported, but the global lipid profiles, especially in the East Asia population, associated with the development of T2D remain to be characterized. Liquid chromatography coupled to tandem mass spectrometry was applied to detect the global lipidome in the fasting plasma of 293 Chinese individuals, including 114 T2D patients, 81 prediabetic subjects, and 98 individuals with normal glucose tolerance (NGT). Both qualitative and quantitative analyses revealed a gradual change in plasma lipid features with T2D patients exhibiting characteristics close to those of prediabetic individuals, whereas they differed significantly from individuals with NGT. We constructed and validated a random forest classifier with 28 lipidomic features that effectively discriminated T2D from NGT or prediabetes. Most of the selected features significantly correlated with diabetic clinical indices. Hydroxybutyrylcarnitine was positively correlated with fasting plasma glucose, 2-hour postprandial glucose, glycated hemoglobin, and insulin resistance index (HOMA-IR). Lysophosphatidylcholines such as lysophosphatidylcholine (18:0), lysophosphatidylcholine (18:1), and lysophosphatidylcholine (18:2) were all negatively correlated with HOMA-IR. The altered plasma lipidome in Chinese T2D and prediabetic subjects suggests that lipid features may play a role in the pathogenesis of T2D and that such features may provide a basis for evaluating risk and monitoring disease development.

A Comprehensive Investigation toward the Indicative Proteins of Bladder Cancer in Urine: From Surveying Cell Secretomes to Verifying Urine Proteins

Urine is an ideal material to study the cancer-related protein biomarkers in bladder, whereas exploration to these candidates is confronting technique challenges. Herein, we propose a comprehensive strategy of searching the urine proteins related with bladder cancer. The strategy consists of three core combinations, screening the biomarker candidates in the secreted proteins derived from the bladder cancer cell lines and verifying them in patient urines, defining the differential proteins through two-dimensional electrophoresis (2DE) and isobaric tags for relative and absolute quantitation (iTRAQ) coupled with LC-MS/MS, and implementing quantitative proteomics of profiling and targeting analysis. With proteomic survey, a total of 700 proteins were found with their abundance of secreted proteins in cancer cell lines different from normal, while 87 proteins were identified in the urine samples. The multiple reaction monitoring (MRM)-based quantification was adapted in verifying the bladder cancer related proteins in individual urine samples, resulting in 10 differential urine proteins linked with the cancer. Of these candidates, receiver operating characteristic analysis revealed that the combination of CO3 and LDHB was more sensitive as the cancer indicator than other groups. The discovery of the bladder cancer indicators through our strategy has paved an avenue to further biomarker validation.

Lipidomics profiling reveals the role of glycerophospholipid metabolism in psoriasis

Abstract Psoriasis is a common and chronic inflammatory skin disease that is complicated by gene–environment interactions. Although genomic, transcriptomic, and proteomic analyses have been performed to investigate the pathogenesis of psoriasis, the role of metabolites in psoriasis, particularly of lipids, remains unclear. Lipids not only comprise the bulk of the cellular membrane bilayers but also regulate a variety of biological processes such as cell proliferation, apoptosis, immunity, angiogenesis, and inflammation. In this study, an untargeted lipidomics approach was used to study the lipid profiles in psoriasis and to identify lipid metabolite signatures for psoriasis through ultra-performance liquid chromatography-tandem quadrupole mass spectrometry. Plasma samples from 90 participants (45 healthy and 45 psoriasis patients) were collected and analyzed. Statistical analysis was applied to find different metabolites between the disease and healthy groups. In addition, enzyme-linked immunosorbent assay was performed to validate differentially expressed lipids in psoriatic patient plasma. Finally, we identified differential expression of several lipids including lysophosphatidic acid (LPA), lysophosphatidylcholine (LysoPC), phosphatidylinositol (PI), phosphatidylcholine (PC), and phosphatidic acid (PA); among these metabolites, LPA, LysoPC, and PA were significantly increased, while PC and PI were down-regulated in psoriasis patients. We found that elements of glycerophospholipid metabolism such as LPA, LysoPC, PA, PI, and PC were significantly altered in the plasma of psoriatic patients; this study characterizes the circulating lipids in psoriatic patients and provides novel insight into the role of lipids in psoriasis.