Therapeutic prediction of HIV-1 DNA decay: a multicenter longitudinal cohort study.

BACKGROUND: Factors predicting peripheral blood total HIV-1 DNA size in chronically infected patients with successfully suppressed viremia remain unclear. Prognostic power of such factors are of clinical significance for making clinical decisions. METHODS: Two sets of study populations were included: 490 China AIDS Clinical Trial (CACT) participants (Training cohort, followed up for 144 to 288 weeks) and 117 outpatients from Peking Union Medical College Hospital (PUMCH) (Validation cohort, followed up for more than 96 weeks). All patients were chronically HIV-1-infected and achieved successful HIV-1 plasma RNA suppression within week 48. Total HIV-1 DNA in blood at baseline, 12, 24, 48, 96, 144 and 288 weeks after combined antiretroviral therapy (cART) initiation were quantified. Generalized estimating equations and logistic regression methods were used to derive and validate a predictive model of total HIV-1 DNA after 96 weeks of cART. RESULTS: The total HIV-1 DNA rapidly decreased from baseline [median = 3.00 log10 copies/106 peripheral blood mononuclear cells (PBMCs)] to week 24 (median = 2.55 log10 copies/106 PBMCs), and leveled off afterwards. Of the 490 patients who had successful HIV-1 plasma RNA suppression by 96 w post-cART, 92 (18.8%) had a low total HIV-1 DNA count (< 100 copies/106 PBMCs) at week 96. In the predictive model, lower baseline total HIV-1 DNA [risk ratio (RR) = 0.08, per 1 log10 copies/106 PBMCs, P < 0.001] and higher baseline CD4+ T cell count (RR = 1.72, per 100 cells/µL, P < 0.001) were significantly associated with a low total HIV-1 DNA count at week 96. In an independent cohort of 117 patients, this model achieved a sensitivity of 75.00% and specificity of 69.52%. CONCLUSIONS: Baseline total HIV-1 DNA and CD4+ T cell count are two independent predictors of total HIV-1 DNA after treatment. The derived model based on these two baseline factors provides a useful prognostic tool in predicting HIV-1 DNA reservoir control during cART.

Deep Coverage Tissue and Cellular Proteomics Revealed IL-1ß Can Independently Induce the Secretion of TNF-Associated Proteins from Human Synoviocytes.

Synovitis is a key contributor to the inflammatory environment in osteoarthritis (OA) joints. Currently, the biological therapy of OA is not satisfactory in multiple single-target trials on anti-TNF agents, or IL-1 antagonists. Systems biological understanding of the phosphorylation state in OA synovium is warranted to direct further therapeutic strategies. Therefore, in this study, we compared the human synovial phosphoproteome of the OA with the acute joint fracture subjects. We found that OA synovium had significantly more phosphoproteins, and 82 phosphoproteins could only be specifically found in all the OA samples. Differentially expressed proteins of the OA synovium were focusing on endoplasmic reticulum-/Golgi-associated secretion and negative regulation of cell proliferation, which was verified through an IL-1ß-treated human synoviocyte (HS) in vitro model. With data-independent acquisition-based mass spectrometry, we found that IL-1ß could induce HS to secrete proteins that were significantly associated with the endosomal/vacuolar pathway, endoplasmic reticulum/Golgi secretion, complement activation, and collagen degradation. Especially, we found that while specifically suppressing HS endocytosis, IL-1ß could activate the secretion of 25 TNF-associated proteins, and the change of SERPINE2 and COL3A1 secretion was verified by immunoblotting. In conclusion, our results suggest that OA synovium has a polarized phosphoproteome to inhibit proliferation and maintain active secretion of HS, whereas IL-1ß alone can transform HS to produce a synovitis-associated secretome, containing numerous TNF-associated secretory proteins in a TNF-independent mode.

Genome-Wide and Experimental Resolution of Relative Translation Elongation Speed at Individual Gene Level in Human Cells.

In the process of translation, ribosomes first assemble on mRNAs (translation initiation) and then translate along the mRNA (elongation) to synthesize proteins. Elongation pausing is deemed highly relevant to co-translational folding of nascent peptides and the functionality of protein products, which positioned the evaluation of elongation speed as one of the central questions in the field of translational control. By integrating three types of RNA-seq methods, we experimentally and computationally resolved elongation speed, with our proposed elongation velocity index (EVI), a relative measure at individual gene level and under physiological condition in human cells. We successfully distinguished slow-translating genes from the background translatome. We demonstrated that low-EVI genes encoded more stable proteins. We further identified cell-specific slow-translating codons, which might serve as a causal factor of elongation deceleration. As an example for the biological relevance, we showed that the relatively slow-translating genes tended to be associated with the maintenance of malignant phenotypes per pathway analyses. In conclusion, EVI opens a new view to understand why human cells tend to avoid simultaneously speeding up translation initiation and decelerating elongation, and the possible cancer relevance of translating low-EVI genes to gain better protein quality.

Motile hepatocellular carcinoma cells preferentially secret sugar metabolism regulatory proteins via exosomes.

Exosomes are deliverers of critically functional proteins, capable of transforming target cells in numerous cancers, including hepatocellular carcinoma (HCC). We hypothesize that the motility of HCC cells can be featured by comparative proteome of exosomes. Hence, we performed the super-SILAC-based MS analysis on the exosomes secreted by three human HCC cell lines, including the non-motile Hep3B cell, and the motile 97H and LM3 cells. More than 1400 exosomal proteins were confidently quantified in each MS analysis with highly biological reproducibility. We justified that 469 and 443 exosomal proteins represented differentially expressed proteins (DEPs) in the 97H/Hep3B and LM3/Hep3B comparisons, respectively. These DEPs focused on sugar metabolism-centric canonical pathways per ingenuity pathway analysis, which was consistent with the gene ontology analysis on biological process enrichment. These pathways included glycolysis I, gluconeogenesis I and pentose phosphate pathways; and the DEPs enriched in these pathways could form a tightly connected network. By analyzing the relative abundance of proteins and translating mRNAs, we found significantly positive correlation between exosomes and cells. The involved exosomal proteins were again focusing on sugar metabolism. In conclusion, motile HCC cells tend to preferentially export more sugar metabolism-associated proteins via exosomes that differentiate them from non-motile HCC cells.

Detergent-Insoluble Proteome Analysis Revealed Aberrantly Aggregated Proteins in Human Preeclampsia Placentas.

Preeclampsia (PE) is a placenta disease, featured by hypertension, proteinuria, and other multiorgan dysfunctions, and its etiology is unclear. We and others have shown that intensive endoplasmic reticulum (ER) stress and unfolded protein response (UPR) occur in the PE placenta. In this study, we isolated detergent-insoluble proteins (DIPs) from human placenta tissues, which were enriched with protein aggregates, to characterize the placenta UPR in PE. With data-independent acquisition (DIA) mass spectrometry, we identified 2066 DIPs across all normal (n = 10) and PE (n = 10) placenta samples, among which 110 and 108 DIPs were significantly up- and down-regulated in PE, respectively. Per clustering analysis, differential DIPs could generally distinguish PE from normal placentas. We verified the MS quantitation of endoglin and vimentin by immunoblotting. In addition, we observed that PE placenta tissues have remarkably more endoglin in the cytoplasm. Furthermore, we found that DIPs were evenly distributed across different chromosomes and could be enriched in diversified gene ontology terms, while differential DIPs avoided to distribute on X-chromosome. Significantly up-regulated DIPs in PE were focused on the top functions of lipid metabolism, while 23 of these DIPs could form the top network regulating cellular movement, development, growth, and proliferation. Our results implicate that human PE placentas have disease-relevant differential DIPs, which reflect aberrantly aggregated proteins of placental tissues. The mass spectrometry proteomics data have been deposited to ProteomeXchange consortium with the data set identifier PXD006654, and iProX database (accession number: IPX0000948000).

Phosphoproteome Characterization of Human Colorectal Cancer SW620 Cell-Derived Exosomes and New Phosphosite Discovery for C-HPP.

Identification of all phosphorylation forms of known proteins is a major goal of the Chromosome-Centric Human Proteome Project (C-HPP). Recent studies have found that certain phosphoproteins can be encapsulated in exosomes and function as key regulators in tumor microenvironment, but no deep coverage phosphoproteome of human exosomes has been reported to date, which makes the exosome a potential source for the new phosphosite discovery. In this study, we performed highly optimized MS analyses on the exosomal and cellular proteins isolated from human colorectal cancer SW620 cells. With stringent data quality control, 313 phosphoproteins with 1091 phosphosites were confidently identified from the SW620 exosome, from which 202 new phosphosites were detected. Exosomal phosphoproteins were significantly enriched in the 11q12.1-13.5 region of chromosome 11 and had a remarkably high level of tyrosine-phosphorylated proteins (6.4%), which were functionally relevant to ephrin signaling pathway-directed cytoskeleton remodeling. In conclusion, we here report the first high-coverage phosphoproteome of human cell-secreted exosomes, which leads to the identification of new phosphosites for C-HPP. Our findings provide insights into the exosomal phosphoprotein systems that help to understand the signaling language being delivered by exosomes in cell-cell communications. The mass spectrometry proteomics data have been deposited to the ProteomeXchange consortium with the data set identifier PXD004079, and iProX database (accession number: IPX00076800).

Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific.

As a well-known phenomenon, total mRNAs poorly correlate to proteins in their abundances as reported. Recent findings calculated with bivariate models suggested even poorer such correlation, whereas focusing on the translating mRNAs (ribosome nascent-chain complex-bound mRNAs, RNC-mRNAs) subset. In this study, we analysed the relative abundances of mRNAs, RNC-mRNAs and proteins on genome-wide scale, comparing human lung cancer A549 and H1299 cells with normal human bronchial epithelial (HBE) cells, respectively. As discovered, a strong correlation between RNC-mRNAs and proteins in their relative abundances could be established through a multivariate linear model by integrating the mRNA length as a key factor. The R(2) reached 0.94 and 0.97 in A549 versus HBE and H1299 versus HBE comparisons, respectively. This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed. We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs. These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.

Resolving chromosome-centric human proteome with translating mRNA analysis: a strategic demonstration.

Chromosome-centric human proteome project (C-HPP) aims at differentiating chromosome-based and tissue-specific protein compositions in terms of protein expression, quantification, and modification. We previously found that the analysis of translating mRNA (mRNA attached to ribosome-nascent chain complex, RNC-mRNA) can explain over 94% of mRNA-protein abundance. Therefore, we propose here to use full-length RNC-mRNA information to illustrate protein expression both qualitatively and quantitatively. We performed RNA-seq on RNC-mRNA (RNC-seq) and detected 12,758 and 14,113 translating genes in human normal bronchial epithelial (HBE) cells and human colorectal adenocarcinoma Caco-2 cells, respectively. We found that most of these genes were mapped with >80% of coding sequence coverage. In Caco-2 cells, we provided translating evidence on 4180 significant single-nucleotide variations. While using RNC-mRNA data as a standard for proteomic data integration, both translating and protein evidence of 7876 genes can be acquired from four interlaboratory data sets with different MS platforms. In addition, we detected 1397 noncoding mRNAs that were attached to ribosomes, suggesting a potential source of new protein explorations. By comparing the two cell lines, a total of 677 differentially translated genes were found to be nonevenly distributed across chromosomes. In addition, 2105 genes in Caco-2 and 750 genes in HBE cells are expressed in a cell-specific manner. These genes are significantly and specifically clustered on multiple chromosomes, such as chromosome 19. We conclude that HPP/C-HPP investigations can be considerably improved by integrating RNC-mRNA analysis with MS, bioinformatics, and antibody-based verifications.

Systematic analysis of missing proteins provides clues to help define all of the protein-coding genes on human chromosome 1.

Our first proteomic exploration of human chromosome 1 began in 2012 (CCPD 1.0), and the genome-wide characterization of the human proteome through public resources revealed that 32-39% of proteins on chromosome 1 remain unidentified. To characterize all of the missing proteins, we applied an OMICS-integrated analysis of three human liver cell lines (Hep3B, MHCC97H, and HCCLM3) using mRNA and ribosome nascent-chain complex-bound mRNA deep sequencing and proteome profiling, contributing mass spectrometric evidence of 60 additional chromosome 1 gene products. Integration of the annotation information from public databases revealed that 84.6% of genes on chromosome 1 had high-confidence protein evidence. Hierarchical analysis demonstrated that the remaining 320 missing genes were either experimentally or biologically explainable; 128 genes were found to be tissue-specific or rarely expressed in some tissues, whereas 91 proteins were uncharacterized mainly due to database annotation diversity, 89 were genes with low mRNA abundance or unsuitable protein properties, and 12 genes were identifiable theoretically because of a high abundance of mRNAs/RNC-mRNAs and the existence of proteotypic peptides. The relatively large contribution made by the identification of enriched transcription factors suggested specific enrichment of low-abundance protein classes, and SRM/MRM could capture high-priority missing proteins. Detailed analyses of the differentially expressed genes indicated that several gene families located on chromosome 1 may play critical roles in mediating hepatocellular carcinoma invasion and metastasis. All mass spectrometry proteomics data corresponding to our study were deposited in the ProteomeXchange under the identifiers PXD000529, PXD000533, and PXD000535.

Functional proteomics revealed IL-1ß amplifies TNF downstream protein signals in human synoviocytes in a TNF-independent manner.

IL-1ß is readily detectable in numerous joint inflammations. It can change the transcriptomic signature of fibroblast-like synoviocytes (FLS) of arthritis toward promoting migration and invasion that are relevant to arthritis progression. We hypothesize that IL-1ß partially contributes to the onset of osteoarthritis (OA). We compared the tissue samples from OA and fracture subjects and found that IL-1ß expression was significantly higher in the OA synovium, while TNF-α expression showed no significance. We demonstrated that IL-1ß significantly increases the IL-6 and IL-8 secretions of human normal FLS; however, IL-1ß does not induce TNF secretion. With metabolic labeling based proteomics and pathway analysis, we found that IL-1ß significantly increases the TNF downstream protein expression in FLS even with complete absence of TNF and/or blocking of the NF-κB pathway. Among these proteins, we verified that p62 can differentiate the OA from fracture synovitis. In conclusion, we demonstrated that IL-1ß can amplify the TNF downstream protein signals in human synoviocytes in a TNF-independent manner; in addition, p62 is a potential FLS biomarker for synovitis.

Prediction of strand-specific and cell-type-specific G-quadruplexes based on high-resolution CUT&Tag data.

G-quadruplex (G4), a non-classical deoxyribonucleic acid structure, is widely distributed in the genome and involved in various biological processes. In vivo, high-throughput sequencing has indicated that G4s are significantly enriched at functional regions in a cell-type-specific manner. Therefore, the prediction of G4s based on computational methods is necessary instead of the time-consuming and laborious experimental methods. Recently, G4 CUT&Tag has been developed to generate higher-resolution sequencing data than ChIP-seq, which provides more accurate training samples for model construction. In this paper, we present a new dataset construction method based on G4 CUT&Tag sequencing data and an XGBoost prediction model based on the machine learning boost method. The results show that our model performs well within and across cell types. Furthermore, sequence analysis indicates that the formation of G4 structure is greatly affected by the flanking sequences, and the GC content of the G4 flanking sequences is higher than non-G4. Moreover, we also identified G4 motifs in the high-resolution dataset, among which we found several motifs for known transcription factors (TFs), such as SP2 and BPC. These TFs may directly or indirectly affect the formation of the G4 structure.

Identification of DNA-binding proteins by Kernel Sparse Representation via L2,1-matrix norm.

An understanding of DNA-binding proteins is helpful in exploring the role that proteins play in cell biology. Furthermore, the prediction of DNA-binding proteins is essential for the chemical modification and structural composition of DNA, and is of great importance in protein functional analysis and drug design. In recent years, DNA-binding protein prediction has typically used machine learning-based methods. The prediction accuracy of various classifiers has improved considerably, but researchers continue to spend time and effort on improving prediction performance. In this paper, we combine protein sequence evolutionary information with a classification method based on kernel sparse representation for the prediction of DNA-binding proteins, and based on the field of machine learning, a model for the identification of DNA-binding proteins by sequence information was finally proposed. Based on the confirmation of the final experimental results, we achieved good prediction accuracy on both the PDB1075 and PDB186 datasets. Our training result for cross-validation on PDB1075 was 81.37%, and our independent test result on PDB186 was 83.9%, both of which outperformed the other methods to some extent. Therefore, the proposed method in this paper is proven to be effective and feasible for predicting DNA-binding proteins.

Systems crosstalk between antiviral response and cancerous pathways via extracellular vesicles in HIV-1-associated colorectal cancer.

HIV-1 associated colorectal cancer (HA-CRC) is one of the most understudied non-AIDS-defining cancers. In this study, we analyzed the proteome of HA-CRC and the paired remote tissues (HA-RT) through data-independent acquisition mass spectrometry (MS). The quantified proteins could differentiate the HA-CRC and HA-RT groups per PCA or cluster analyses. As a background comparison, we reanalyzed the MS data of non-HIV-1 infected CRC (non-HA-CRC) published by CPTAC. According to the GSEA results, we found that HA-CRC and non-HA-CRC shared similarly over-represented KEGG pathways. Hallmark analysis suggested that terms of antiviral response were only significantly enriched in HA-CRC. The network and molecular system analysis centered the crosstalk of IFN-associated antiviral response and cancerous pathways, which was favored by significant up-regulation of ISGylated proteins as detected in the HA-CRC tissues. We further proved that defective HIV-1 reservoir cells as represented by the 8E5 cells could activate the IFN pathway in human macrophages via horizonal transfer of cell-associated HIV-1 RNA (CA-HIV RNA) carried by extracellular vesicles (EVs). In conclusion, HIV-1 reservoir cells secreted and CA-HIV RNA-containing EVs can induce IFN pathway activation in macrophages that contributes to one of the mechanistic explanations of the systems crosstalk between antiviral response and cancerous pathways in HA-CRC.

Establishment of a simplified dichotomic size-exclusion chromatography for isolating extracellular vesicles toward clinical applications.

Size-exclusion chromatography (SEC) is a widely adopted method for the isolation of extracellular vesicles (EVs) from complex samples. SEC can efficiently remove high-abundant proteins, while often requires multiple fractionation operation using diversified column settings. In this study, we aim to establish a simplified SEC method to acquire high quality EVs. In comparison of all three cross-linked Sepharose resins with the sample types of FBS and human serum (HS), CL-6B and CL-4B showed superior performance in regular SEC to CL-2B in terms of significantly narrower EV and protein peaks, higher resolutions and EV purity. By increasing their bed volumes to 20 ml, the resolutions of CL-6B and CL-4B columns could be significantly improved, while the CL-6B column had the best performance with higher particle yields and tighter EV peaks. With the CL-6B 20 ml column, we further established a simplified dichotomic SEC method that only requires two bulk elutions to acquire EVs in the Eluate 1 and proteins in the Eluate 2. We further justified that such CL-6B columns were reusable for at least 10 consecutive times, and the dichotomic SEC was applicable to EV isolations from HS and FBS-free supernatants of fluorescently labelled and unlabelled SW620 cells. The proteomics analysis implicated that although the two methods had dissimilar abilities in removing different co-isolating contaminant proteins from EVs, the dichotomic SEC and ultracentrifugation could isolate EVs from human plasma with comparable purity. This dichotomic SEC has its intriguing potential to be used for EV preparation toward clinical testing and/or basic research.

Proteogenomic Analyses Revealed Favorable Metabolism Pattern Alterations in Rotifer Brachionus plicatilis Fed with Selenium-rich Chlorella.

Organoselenium have garnered attention because of their potential to be used as ingredients in new anti-aging and antioxidation medicines and food. Rotifers are frequently used as a model organism for aging research. In this study, we used Se-enriched Chlorella (Se- Chlorella), a novel organoselenium compound, to feed Brachionus plicatilis to establish a rotifer model with a prolonged lifespan. The results showed that the antioxidative effect in Se-enriched rotifer was associated with an increase in guaiacol peroxidase (GPX) and catalase (CAT). The authors then performed the first proteogenomic analysis of rotifers to understand their possible metabolic mechanisms. With the de novo assembly of RNA-Seq reads as the reference, we mapped the proteomic output generated by iTRAQ-based mass spectrometry. We found that the differentially expressed proteins were primarily involved in antireactive oxygen species (ROS) and antilipid peroxidation (LPO), selenocompound metabolism, glycolysis, and amino acid metabolisms. Furthermore, the ROS level of rotifers was diminished after Se- Chlorella feeding, indicating that Se- Chlorella could help rotifers to enhance their amino acid metabolism and shift the energy generating metabolism from tricarboxylic acid cycle to glycolysis, which leads to reduced ROS production. This is the first report to demonstrate the anti-aging effect of Se- Chlorella on rotifers and to provide a possible mechanism for this activity. Thus, Se- Chlorella is a promising novel organoselenium compound with the potential to prolong human lifespans.

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC.

Cytoskeleton-centric protein transportation by exosomes transforms tumor-favorable macrophages.

The exosome is a key initiator of pre-metastatic niche in numerous cancers, where macrophages serve as primary inducers of tumor microenvironment. However, the proteome that can be exosomally transported from cancer cells to macrophages has not been sufficiently characterized so far. Here, we used colorectal cancer (CRC) exosomes to educate tumor-favorable macrophages. With a SILAC-based mass spectrometry strategy, we successfully traced the proteome transported from CRC exosomes to macrophages. Such a proteome primarily focused on promoting cytoskeleton rearrangement, which was biologically validated with multiple cell lines. We reproduced the exosomal transportation of functional vimentin as a proof-of-concept example. In addition, we found that some CRC exosomes could be recognized by macrophages via Fc receptors. Therefore, we revealed the active and necessary role of exosomes secreted from CRC cells to transform cancer-favorable macrophages, with the cytoskeleton-centric proteins serving as the top functional unit.