Comprehensive Proteomic Analysis Research Articles

Integrative proteomics highlight presynaptic alterations and c-Jun misactivation as convergent pathomechanisms in ALS

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease mainly affecting upper and lower motoneurons. Several functionally heterogeneous genes have been associated with the familial form of this disorder (fALS), depicting an extremely complex pathogenic landscape. This heterogeneity has limited the identification of an effective therapy, and this bleak prognosis will only improve with a greater understanding of convergent disease mechanisms. Recent evidence from human post-mortem material and diverse model systems has highlighted the synapse as a crucial structure actively involved in disease progression, suggesting that synaptic aberrations might represent a shared pathological feature across the ALS spectrum. To test this hypothesis, we performed the first comprehensive analysis of the synaptic proteome from post-mortem spinal cord and human iPSC-derived motoneurons carrying mutations in the major ALS genes. This integrated approach highlighted perturbations in the molecular machinery controlling vesicle release as a shared pathomechanism in ALS. Mechanistically, phosphoproteomic analysis linked the presynaptic vesicular phenotype to an accumulation of cytotoxic protein aggregates and to the pro-apoptotic activation of the transcription factor c-Jun, providing detailed insights into the shared pathobiochemistry in ALS. Notably, sub-chronic treatment of our iPSC-derived motoneurons with the fatty acid docosahexaenoic acid exerted a neuroprotective effect by efficiently rescuing the alterations revealed by our multidisciplinary approach. Together, this study provides strong evidence for the central and convergent role played by the synaptic microenvironment within the ALS spinal cord and highlights a potential therapeutic target that counteracts degeneration in a heterogeneous cohort of human motoneuron cultures.

Identification of gravity-responsive proteins in the femur of spaceflight mice using a quantitative proteomic approach

Although the microgravity (μ-g) environment that astronauts encounter during spaceflight can cause severe acute bone loss, the molecular mechanism of this bone loss remains unclear. To investigate the gravity-response proteins involved in bone metabolism, it is important to comprehensively determine which proteins exhibit differential abundance associated with mechanical stimuli. However, comprehensive proteomic analysis using small bone samples is difficult because protein extraction in mineralized bone tissue is inefficient. Here, we established a high-sensitivity analysis system for mouse bone proteins using data-independent acquisition mass spectrometry. This system successfully detected 40 proteins in the femoral diaphysis showing differential abundance between mice raised in a μ-g environment, where the bone mass was reduced by gravity unloading, and mice raised in an artificial 1-gravity environment on the International Space Station. Additionally, 22 proteins, including noncollagenous bone matrix proteins, showed similar abundance between the two groups in the mandible, where bone mass was unaltered due to mastication stimuli, suggesting that these proteins are responsive to mechanical stimuli. One of these proteins, SPARCL1, is suggested to promote osteoclastogenesis induced by receptor activator of nuclear factor-κB ligand. We expect these findings to lead to new insights into the mechanisms of bone metabolism induced by mechanical stimuli. SignificanceWe aimed to investigate the gravity-response proteins involved in bone metabolism. To this end, we established a comprehensive analysis system for mouse bone proteins using data-independent acquisition mass spectrometry, which is particularly useful in comprehensively analyzing the bone proteome using small sample volumes. In addition, a comprehensive proteomic analysis of the femoral diaphysis and mandible, which exhibit different degrees of bone loss in mice raised on the International Space Station, identified proteins that respond to mechanical stimuli. SPARCL1, a mechanical stimulus-responsive protein, was consequently suggested to be involved in osteoclast differentiation associated with bone remodeling. Our findings represent an important step toward elucidating the molecular mechanism of bone metabolism induced by mechanical stimuli.

Protein interactome of 3',5'-cyclic adenosine monophosphate reveals its role in regulating the actin cytoskeleton.

Identification of protein interactors is ideally suited for the functional characterization of small molecules. Cyclic adenosine monophosphate (3',5'-cAMP) is an evolutionary ancient signaling metabolite largely uncharacterized in plants. To tap into the physiological roles of 3',5'-cAMP, we used a novel chemo-proteomics approach, thermal proteome profiling (TPP), for the unbiased identification of 3',5'-cAMP protein targets. TPP measures shifts in the protein thermal stability upon ligand binding. Comprehensive proteomics analysis yielded a list of 51 proteins significantly altered in their thermal stability upon incubation with 3',5'-cAMP. The list contained metabolic enzymes, ribosomal subunits, translation initiation factors, and proteins associated with the regulation of plant growth such as CELL DIVISION CYCLE 48. To functionally validate obtained results, we focused on the role of 3',5'-cAMP in regulating the actin cytoskeleton suggested by the presence of actin among the 51 identified proteins. 3',5'-cAMP supplementation affected actin organization by inducing actin-bundling. Consistent with these results, the increase in 3',5'-cAMP levels, obtained either by feeding or by chemical modulation of 3',5'-cAMP metabolism was sufficient to partially rescue the short hypocotyl phenotype of the actin2 actin7 mutant, severely compromised in actin level. The observed rescue was specific to 3',5'-cAMP, as demonstrated using a positional isomer 2',3'-cAMP, and true for the nanomolar 3',5'-cAMP concentrations reported for plant cells. In vitro characterization of the 3',5'-cAMP - actin pairing argues against a direct interaction between actin and 3',5'-cAMP. Alternative mechanisms by which 3',5'-cAMP would affect actin dynamics, such as by interfering with calcium signaling, are discussed. In summary, our work provides a novel resource, 3',5'-cAMP interactome, and a new functional insight into the 3',5'-cAMP-mediated regulation in plants.

Data-independent acquisition-based mass spectrometry(DIA-MS) for quantitative analysis of patients with chronic hepatitis B

Chronic hepatitis B is a significant public health problem and complex pathologic process, and unraveling the underlying mechanisms and pathophysiology is of great significance. Data independent acquisition mass spectrometry (DIA-MS) is a label-free quantitative proteomics method that has been successfully applied to the study of a wide range of diseases. The aim of this study was to apply DIA-MS for proteomic analysis of patients with chronic hepatitis B. We performed comprehensive proteomics analysis of protein expression in serum samples from HBV patients and healthy controls by using DIA-MS. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein network analysis were performed on differentially expressed proteins and were further combined with literature analysis. We successfully identified a total of 3786 serum proteins with a high quantitative performance from serum samples in this study. We identified 310 differentially expressed proteins (DEPs) (fold change > 1.5 and P value < 0.05 as the criteria for a significant difference) between HBV and healthy samples. A total of 242 upregulated proteins and 68 downregulated proteins were among the DEPs. Some protein expression levels were significantly elevated or decreased in patients with chronic hepatitis B, indicating a relation to chronic liver disease, which should be further investigated.

Integrating analysis of proteome profile and drug screening identifies therapeutic potential of MET pathway for the treatment of malignant peripheral nerve sheath tumor

ABSTRACT Background Malignant peripheral nerve sheath tumor (MPNST) is an aggressive sarcoma with a poor prognosis that requires novel therapeutic agents. Proteome information is useful for identifying new therapeutic candidates because it directly reflects the biological phenotype. Additionally, in vitro drug screening is an effective tool to identify candidate drugs for common cancers. Hence, we attempted to identify novel therapeutic candidates for MPNST by integrating proteomic analysis and drug screening. Methods We performed comprehensive proteomic analysis on 23 MPNST tumor samples using liquid chromatography – tandem mass spectrometry to identify therapeutic targets. We also conducted drug screening of six MPNST cell lines using 214 drugs. Results Proteomic analysis revealed that the MET and IGF pathways were significantly enriched in the local recurrence/distant metastasis group of MPNST, whereas drug screening revealed that 24 drugs showed remarkable antitumor effects on the MPNST cell lines. By integrating the results of these two approaches, MET inhibitors, crizotinib and foretinib, were identified as novel therapeutic candidates for the treatment of MPNST. Conclusions We successfully identified novel therapeutic candidates for the treatment of MPNST, namely crizotinib and foretinib, which target the MET pathway. We hope that these candidate drugs will contribute to the treatment of MPNST.

Automated Proteomics Workflows for High-Throughput Library Generation and Biomarker Detection Using Data-Independent Acquisition.

Sequential window acquisition of all theoretical mass spectra-mass spectrometry underpinned by advanced bioinformatics offers a framework for comprehensive analysis of proteomes and the discovery of robust biomarkers. However, the lack of a generic sample preparation platform to tackle the heterogeneity of material collected from different sources may be a limiting factor to the broad application of this technique. We have developed universal and fully automated workflows using a robotic sample preparation platform, which enabled in-depth and reproducible proteome coverage and characterization of bovine and ovine specimens representing healthy animals and a model of myocardial infarction. High correlation (R2 = 0.85) between sheep proteomics and transcriptomics datasets validated the developments. The findings suggest that automated workflows can be employed for various clinical applications across different animal species and animal models of health and disease.

Comprehensive Proteome and Acetyl-Proteome Atlas Reveals Hepatic Lipid Metabolism in Layer Hens with Fatty Liver Hemorrhagic Syndrome.

The feeding of high-energy and low-protein diets often induces fatty liver hemorrhagic syndrome (FLHS) in laying hens. However, the mechanism of hepatic fat accumulation in hens with FLHS remains uncertain. In this research, a comprehensive hepatic proteome and acetyl-proteome analysis was performed in both normal and FLHS-affected hens. The results indicated that the upregulated proteins were primarily associated with fat digestion and absorption, the biosynthesis of unsaturated fatty acids, and glycerophospholipid metabolism, while the downregulated proteins were mainly related to bile secretion and amino acid metabolism. Furthermore, the significant acetylated proteins were largely involved in ribosome and fatty acid degradation, and the PPAR signaling pathway, while the significant deacetylated proteins were related to valine, leucine, and isoleucine degradation in laying hens with FLHS. Overall, these results demonstrate that acetylation inhibits hepatic fatty acid oxidation and transport in hens with FLHS, and mainly exerts its effects by affecting protein activity rather than expression. This study provides new nutritional regulation options to alleviate FLHS in laying hens.

In vitro Characterization of a novel murine model of cancerous progression

To evaluate a potentially valuable tool to study cancer progression and metastasis, we characterized a novel murine model composed of a parental oncogene-transformed embryonic fibroblast line and five cell lines isolated from progressively advanced tumors. Lines derived from distant metastases displayed significantly greater rates of motility, invasiveness, and extracellular acidification than lines derived from a primary tumor or local metastases. A comprehensive proteomic analysis of these cells showed numerous oncogenes to be upregulated and tumor suppressors to be downregulated in the advanced lines, and provided novel targets for future examination. The first cell line capable of extravasation displayed particularly high proteomic variation, which could provide insight into its epithelial to mesenchymal transition. The proteomic variation was less than that of an established human breast cancer model, indicating that the observed differences are more likely contributive to tumorigenesis. In total, we validated a novel cell model for the study of tumorigenesis, while providing a robust proteomic data set to guide future research.

Comprehensive single-cell transcriptomic and proteomic analysis reveals NK cell exhaustion and unique tumor cell evolutionary trajectory in non-keratinizing nasopharyngeal carcinoma

BackgroundNonkeratinizing nasopharyngeal carcinoma (NK-NPC) has a strong association with Epstein-Barr virus (EBV) infection. The role of NK cells and the tumor cell evolutionary trajectory in NK-NPC remain unclear. In this study, we aim to investigate the function of NK cell and the evolutionary trajectory of tumor cells in NK-NPC by single-cell transcriptomic analysis, proteomics and immunohistochemistry.MethodsNK-NPC (n = 3) and normal nasopharyngeal mucosa cases (n = 3) were collected for proteomic analysis. Single-cell transcriptomic data of NK-NPC (n = 10) and nasopharyngeal lymphatic hyperplasia (NLH, n = 3) were obtained from Gene Expression Omnibus (GSE162025 and GSE150825). Quality control, dimension reduction and clustering were based on Seurat software (v4.0.2) process and batch effects were removed by harmony (v0.1.1) software. Normal cells of nasopharyngeal mucosa and tumor cells of NK-NPC were identified using copykat software (v1.0.8). Cell-cell interactions were explored using CellChat software (v1.4.0). Tumor cell evolutionary trajectory analysis was performed using SCORPIUS software (v1.0.8). Protein and gene function enrichment analyses were performed using clusterProfiler software (v4.2.2).ResultsA total of 161 differentially expressed proteins were obtained between NK-NPC (n = 3) and normal nasopharyngeal mucosa (n = 3) by proteomics (log2 fold change > 0.5 and P value < 0.05). Most of proteins associated with the nature killer cell mediated cytotoxicity pathway were downregulated in the NK-NPC group. In single cell transcriptomics, we identified three NK cell subsets (NK1-3), among which NK cell exhaustion was identified in the NK3 subset with high ZNF683 expression (a signature of tissue-resident NK cell) in NK-NPC. We demonstrated the presence of this ZNF683 + NK cell subset in NK-NPC but not in NLH. We also performed immunohistochemical experiments with TIGIT and LAG3 to confirm NK cell exhaustion in NK-NPC. Moreover, the trajectory analysis revealed that the evolutionary trajectory of NK-NPC tumor cells was associated with the status of EBV infection (active or latent). The analysis of cell-cell interactions uncovered a complex network of cellular interactions in NK-NPC.ConclusionsThis study revealed that the NK cell exhaustion might be induced by upregulation of inhibitory receptors on the surface of NK cells in NK-NPC. Treatments for the reversal of NK cell exhaustion may be a promising strategy for NK-NPC. Meanwhile, we identified a unique evolutionary trajectory of tumor cells with active status of EBV-infection in NK-NPC for the first time. Our study may provide new immunotherapeutic targets and new sight of evolutionary trajectory involving tumor genesis, development and metastasis in NK-NPC.

Small and Large Extracellular Vesicles Derived from Pleural Mesothelioma Cell Lines Offer Biomarker Potential

Pleural mesothelioma, previously known as malignant pleural mesothelioma, is an aggressive and fatal cancer of the pleura, with one of the poorest survival rates. Pleural mesothelioma is in urgent clinical need for biomarkers to aid early diagnosis, improve prognostication, and stratify patients for treatment. Extracellular vesicles (EVs) have great potential as biomarkers; however, there are limited studies to date on their role in pleural mesothelioma. We conducted a comprehensive proteomic analysis on different EV populations derived from five pleural mesothelioma cell lines and an immortalized control cell line. We characterized three subtypes of EVs (10 K, 18 K, and 100 K), and identified a total of 4054 unique proteins. Major differences were found in the cargo between the three EV subtypes. We show that 10 K EVs were enriched in mitochondrial components and metabolic processes, while 18 K and 100 K EVs were enriched in endoplasmic reticulum stress. We found 46 new cancer-associated proteins for pleural mesothelioma, and the presence of mesothelin and PD-L1/PD-L2 enriched in 100 K and 10 K EV, respectively. We demonstrate that different EV populations derived from pleural mesothelioma cells have unique cancer-specific proteomes and carry oncogenic cargo, which could offer a novel means to extract biomarkers of interest for pleural mesothelioma from liquid biopsies.

Age-associated differences in the human lung extracellular matrix.

Extracellular matrix (ECM) remodeling has been associated with chronic lung diseases. However, information about specific age-associated differences in lung ECM is currently limited. In this study, we aimed to identify and localize age-associated ECM differences in human lungs using comprehensive transcriptomic, proteomic, and immunohistochemical analyses. Our previously identified age-associated gene expression signature of the lung was re-analyzed limiting it to an aging signature based on 270 control patients (37-80 years) and focused on the Matrisome core geneset using geneset enrichment analysis. To validate the age-associated transcriptomic differences on protein level, we compared the age-associated ECM genes (false discovery rate, FDR < 0.05) with a profile of age-associated proteins identified from a lung tissue proteomics dataset from nine control patients (49-76 years) (FDR < 0.05). Extensive immunohistochemical analysis was used to localize and semi-quantify the age-associated ECM differences in lung tissues from 62 control patients (18-82 years). Comparative analysis of transcriptomic and proteomic data identified seven ECM proteins with higher expression with age at both gene and protein levels: COL1A1, COL6A1, COL6A2, COL14A1, FBLN2, LTBP4, and LUM. With immunohistochemistry, we demonstrated higher protein levels with age for COL6A2 in whole tissue, parenchyma, airway wall, and blood vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in lung parenchyma. Our study revealed that higher age is associated with lung ECM remodeling, with specific differences occurring in defined regions within the lung. These differences may affect lung structure and physiology with aging and as such may increase susceptibility to developing chronic lung diseases.NEW & NOTEWORTHY We identified seven age-associated extracellular matrix (ECM) proteins, i.e., COL1A1, COL6A1, COL6A2 COL14A1, FBLN2, LTBP4, and LUM with higher transcript and protein levels in human lung tissue with age. Extensive immunohistochemical analysis revealed significant age-associated differences for COL6A2 in whole tissue, parenchyma, airway wall, and vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in parenchyma. Our findings lay a new foundation for the investigation of ECM differences in age-associated chronic lung diseases.

Comprehensive proteomic analysis of autophagosomes derived from Leishmania-infected macrophages.

Recently, autophagy has been implicated as a host defense mechanism against intracellular pathogens. On the other hand, certain intracellular pathogens such as Leishmania can manipulate the host's autophagy to promote their survival. Our recent findings regarding the regulation of autophagy by Leishmania donovani indicate that this pathogen induces non-classical autophagy in infected macrophages, independent of regulation by the mammalian target of rapamycin complex 1. This suggests the fine-tuning of autophagy to optimally promote parasite survival, possibly by the sequestration or modulation of specific autophagosome-associated proteins. To investigate how Leishmania potentially manipulates the composition of host-cell autophagosomes, we undertook a quantitative proteomic study of the human monocytic cell line THP-1 following infection with L. donovani. We used stable isotope labeling by amino acid in cell culture and liquid chromatography-tandem mass spectrometry to compare expression profiles between autophagosomes isolated from THP-1 cells infected with L. donovani or treated with known autophagy inducers. Selected proteomic results were validated by Western blotting. In this study, we showed that L. donovani modulates the composition of macrophage autophagosomes during infection when compared to autophagosomes induced by either rapamycin (selective autophagy) or starvation (non-selective autophagy). Among 1787 proteins detected in Leishmania-induced autophagosomes, 146 were significantly modulated compared to the proteome of rapamycin-induced autophagosomes, while 57 were significantly modulated compared to starvation-induced autophagosomes. Strikingly, 23 Leishmania proteins were also detected in the proteome of Leishmania-induced autophagosomes. Together, our data provide the first comprehensive insight into the proteome dynamics of host autophagosomes in response to Leishmania infection and demonstrate the complex relations between the host and pathogen at the molecular level. A comprehensive analysis of the Leishmania-induced autophagosome proteome will be instrumental in the advancement of understanding leishmaniasis.

Abstract 953: Development of a predictive biomarker signature for the highly potent SIK3 inhibitor OMX-0407

Abstract Using the iOTarg genetic screening platform, salt-inducible kinase 3 (SIK3), a serine/threonine kinase of the AMP-activated protein kinase (AMPK) family was recently identified as a novel cell signaling modulator in cancer biology. OMX-0407, an orally available, single-digit nanomolar inhibitor of SIK3 was shown to inhibit tumor growth in a distinct panel of tumor models in vitro as well as in vivo by decreasing downstream pro-survival signaling of SIK3, enhancing caspase-mediated apoptosis and repolarizing the tumor microenvironment by decreasing regulatory T cells. In a comprehensive viability screening, more than 200 murine and human cancer cell lines and patient derived tumor models of different indications were used to identify a distinct subset of cancers highly sensitive towards OMX-0407. Representative for these tumors, OMX-0407 demonstrated dose-dependent anti-tumor efficacy in the renal cell carcinoma model RENCA, the squamous non-small cell lung cancer model (sqNSCLC) KLN205 and the murine colorectal tumor model MC38. With significantly prolonged overall survival of more than 60% tumor growth inhibition in all tumor models, OMX-0407 demonstrated equivalent or superior efficacy compared to anti-PD-1 monotherapy. In addition, OMX-0407 enhances the therapeutic potential of the standard of care chemotherapy in a broad range of human cancer cells and murine tumor models of sqNSCLC. Using comprehensive transcriptomics and proteomics analyses the selective activity profile of OMX-0407 on individual cancer cell lines and PDX models was used to identify and validate a predictive biomarker signature. With this gene signature, 84% of the selected cancer cells lines are correctly classified and would benefit from OMX-0407 therapy. The predictive biomarker will be evaluated in the clinical Phase I trial of OMX-0407 scheduled to start enrollment shortly. In summary, OMX-0407, a first-in-class oral SIK3 inhibitor, demonstrates potent monotherapy efficacy in tumor indications with high unmet medical need equal or superior to anti-PD-1 checkpoint blockade. By screening sensitive and non-sensitive tumor cell lines and PDX models, we identified a response-prediction biomarker signature. In upcoming clinical studies, this predictive biomarker signature will be evaluated for it’s potential to enrich for patients highly responsive to OMX-0407 therapy. Citation Format: Ilona-Petra Maser, Sonja Lacher, Vincent Piras, Barbara Kracher, Kai Zanziger, Murray Yule, Hannes Loferer, Stefan Bissinger. Development of a predictive biomarker signature for the highly potent SIK3 inhibitor OMX-0407 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 953.

Abstract 5305: Detection and quantification of proteins using protein identification by short-epitope mapping (PrISM)

Abstract Introduction: Here, we demonstrate Protein Identification by Short-epitope Mapping (PrISM), which aims to provide comprehensive proteome analysis with broad dynamic range at single-molecule resolution by interrogating immobilized, intact proteins in parallel using multi-affinity probes. Improving the dynamic range and scale for protein analyses will enable a deeper understanding of low abundant protein in all stages of cancer progression. In addition, enabling the interrogation of single-molecules will provide a deeper understanding of protein diversity, such as the proteoforms resulting from non-canonical post-translational modifications inherent to cancer1. The combination of single-molecule sensitivity with comprehensive proteome coverage could also open the door for highly sensitive and specific diagnostics. Methods: PrISM uses non-traditional affinity reagents with high affinity and low specificity that bind to short epitopes in multiple proteins. Sample proteins were conjugated to DNA nanoparticles and deposited on a high-density patterned flow cell at optically resolvable locations. Multi-affinity probes were applied to sample proteins over multiple cycles to generate binding patterns for each single-molecule protein, which are translated to protein identifications and quantities using a custom machine learning approach. We acquired PrISM data on native biological and control samples using dozens of multi-affinity probes targeting trimer or tetramer sequences. Results: We report single-molecule deposition of over 1 billion DNA nanoparticle complexes on a flow cell. We demonstrate how the PrISM methodology identifies individual protein molecules through iterative probing with our multi-affinity probes. Further, we provide an analytical assessment of the sensitivity and specificity of PrISM and demonstrate the ability to accurately estimate the false identification rate of these proteins using a target-decoy based statistical approach. Conclusions: Combining single-molecule analysis, intact (non-digested) proteins, and iterative probing, PrISM provides a new tool for quantitative proteomics. We demonstrate linear and reproducible quantification of proteins using PrISM, potentially enabling detection of low abundant proteins and proteoforms associated with cancer. The ability to make comprehensive measurements of intact proteins at single-molecule resolution could accelerate basic cancer research through to the clinic.

Online 2D High-pH and Low-pH Reversed-Phase Nano-LC-MS/MS System for Deep Proteome Analysis.

In bottom-up proteomic profiling, the complexity of proteome composition and wide dynamic range has created challenges on the limited number of protein identification and proteome coverage, especially in sample input-limited nanoflow (nano) LC-MS/MS analysis. Herein, we developed a fully automatic online 2D nano-LC-MS/MS system using both high-pH and low-pH reverse phase (RP) LCs on a single LC instrument toward comprehensive proteomics analysis. Compared to conventional microflow 2D-LC, the high-pH RP trapping column demonstrated a low sample requirement of cellular protein digest at the μg level with good fractionation resolution of >90% peptides in a single fraction. Compared to the offline 2D RP-RP nano-LC-QTOF using C18-HPLC column and C18-Stage Tip, and 1D nano-LC-QTOF system, superior coverage was observed on the higher number of identified protein groups/unique peptides by 1.35-/1.68-, 1.46-/1.75-, and 3.21-/4.35-fold, respectively, using an online 2D RP-RP nano-LC-QTOF mass spectrometer. On the evolution of quantitation performance, the online 2D high-/low-pH RP data-independent acquisition (DIA) showed a higher reproducibility in protein groups intensity (R2 > 0.977) and more quantified proteins than that obtained using the offline 2D high-/low-pH RP DIA approach. Using an advanced Orbitrap Exploris 480 mass spectrometer, ∼1.9-fold higher proteome coverage was also observed in our 2D online RP-RP system (6039 protein groups) compared to the 1D nano-LC system (3133 protein groups). In summary, the online 2D nano-LC-MS/MS platform can be a sensitive and robust approach compatible with conventional nano-LC instruments for deep proteome coverage of trace amounts of samples.

Differential Activation of NRF2 Signaling Pathway in Renal-Cell Carcinoma Caki Cell Lines

Renal-cell carcinoma (RCC) is a heterogeneous disease consisting of several subtypes based on specific genomic profiles and histological and clinical characteristics. The subtype with the highest prevalence is clear-cell RCC (ccRCC), next is papillary RCC (pRCC), and then chromophobe RCC (chRCC). The ccRCC cell lines are further subdivided into prognostic expression-based subtypes ccA or ccB. This heterogeneity necessitates the development, availability, and utilization of cell line models with the correct disease phenotypic characteristics for RCC research. In this study, we focused on characterizing proteomic differences between the Caki-1 and Caki-2 cell lines that are commonly used in ccRCC research. Both cells are primarily defined as human ccRCC cell lines. Caki-1 cell lines are metastatic, harboring wild-type VHL, whereas Caki-2 are considered as the primary ccRCC cell lines expressing wild-type von Hippel-Lindau protein (pVHL). Here, we performed a comprehensive comparative proteomic analysis of Caki-1 and Caki-2 cells using tandem mass-tag reagents together with liquid chromatography mass spectrometry (LC/MS) for the identification and quantitation of proteins in the two cell lines. Differential regulation of a subset of the proteins identified was validated using orthogonal methods including western blot, q-PCR, and immunofluorescence assays. Integrative bioinformatic analysis identifies the activation/inhibition of specific molecular pathways, upstream regulators, and causal networks that are uniquely regulated and associated with the two cell lines and RCC subtypes, and potentially the disease stage. Altogether, we have identified multiple molecular pathways, including NRF2 signaling, which is the most significantly activated pathway in Caki-2 versus Caki-1 cells. Some of the differentially regulated molecules and signaling pathways could serve as potential diagnostic and prognostic biomarkers and therapeutic targets amongst ccRCC subtypes.

Transcriptome and Proteome Analysis Revealed That Hormone and Reactive Oxygen Species Synergetically Regulate Dormancy of Introgression Line in Rice (Oryza sativa L.)

Dormancy is a complex agronomy phenotype controlled by multiple signaling and a key trait repressing pre-harvest sprouting (PHS). However, the signaling network of dormancy remains unclear. In this study, we used Zhonghua11 (ZH11) with a weak dormancy, and Introgression line (IL) with a strong dormancy to study the mechanism of hormones and reactive oxygen species (ROS) crosstalk regulating rice dormancy. The germination experiment showed that the germination rate of ZH11 was 76.86%, while that of IL was only 1.25%. Transcriptome analysis showed that there were 1658 differentially expressed genes (DEGs) between IL and ZH11, of which 577 were up-regulated and 1081 were down-regulated. Additionally, DEGs were mainly enriched in oxidoreductase activity, cell periphery, and plant hormone signal transduction pathways. Tandem mass tags (TMT) quantitative proteomics analysis showed 275 differentially expressed proteins (DEPs) between IL and ZH11, of which 176 proteins were up-regulated, 99 were down-regulated, and the DEPs were mainly enriched in the metabolic process and oxidation-reduction process. The comprehensive transcriptome and proteome analysis showed that their correlation was very low, and only 56 genes were co-expressed. Hormone content detection showed that IL had significantly lower abscisic acid (ABA) contents than the ZH11 while having significantly higher jasmonic acid (JA) contents than the ZH11. ROS content measurement showed that the hydrogen peroxide (H2O2) content of IL was significantly lower than the ZH11, while the production rate of superoxide anion (O2.-) was significantly higher than the ZH11. These results indicate that hormones and ROS crosstalk to regulate rice dormancy. In particular, this study has deepened our mechanism of ROS and JA crosstalk regulating rice dormancy and is conducive to our precise inhibition of PHS.

Integrative transcriptome and proteome analysis reveals maize responses to Fusarium verticillioides infection inside the stalks.

Fusarium stalk rot caused by Fusarium verticillioides is one of the most devastating diseases of maize that causes significant yield losses and poses potential security concerns for foods worldwide. The underlying mechanisms of maize plants regulating defence against the disease remain poorly understood. Here, integrative proteomic and transcriptomic analyses were employed to identify pathogenesis-related protein genes by comparing differentially expressed proteins (DEPs) and differentially expressed genes (DEGs) in maize stalks after inoculation with F.verticillioides. Functional enrichment analysis showed that DEGs and DEPs were mainly enriched in glutathione metabolism, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, linoleic acid metabolism, and phenylpropanoid biosynthesis. Fourteen DEGs and DEGs that were highly elevated after inoculation with F.verticillioides were confirmed with parallel reaction monitoring and reverse transcription-quantitative PCR, demonstrating the accountability and reliability of proteomic and transcriptomic data. We also assessed the potential roles of defence-related genes ZmCTA1, ZmWIP1, and ZmLOX2, identified from the multi-omics analysis, during the process of F.verticillioides infection through virus-induced gene silencing. The elevation of stalk rot symptomatic characteristics in the silenced plants revealed their contribution to resistance. We further functionally characterized the roles of ZmLOX2 expression in the defence response of maize plants conditioning fungal invasion via the salicylic acid-dependent pathway. Collectively, this study provides a comprehensive analysis of transcriptome and proteome of maize stalks following F.verticillioides inoculation, and defence-related genes that could inform selection of new genes as targets in breeding strategies.

Neofunctionalization of tandem duplicate genes encoding putative β-L-arabinofuranosidases in Arabidopsis.

Tandem duplication, one of the major types of duplication, provides the raw material for the evolution of divergent functions. In this study, we identified 1 pair of tandem duplicate genes (AT5G12950 and AT5G12960) in Arabidopsis (Arabidopsis thaliana) that originated within the last 16 million years after the split of Arabidopsis from the Capsella-Boechera ancestor. We systematically used bioinformatic tools to redefine their putative biochemical function as β-L-arabinofuranosidases that release L-Arabinose from the β-L-Araf-containing molecules in Arabidopsis. Comprehensive transcriptomic and proteomic analyses using various datasets showed divergent expression patterns among tissues between the 2 duplicate genes. We further collected phenotypic data from 2 types of measurements to indicate that AT5G12950 and AT5G12960 have different roles resulting in divergent phenotypic effects. Overall, AT5G12950 and AT5G12960 represent putative β-L-arabinofuranosidase encoding genes in Arabidopsis. After duplication, 1 duplicate copy developed diverged biological functions and contributed to a different phenotypic evolution in Arabidopsis.

Refining Classification of Cholangiocarcinoma Subtypes via Proteogenomic Integration Reveals New Therapeutic Prospects

Intrahepatic cholangiocarcinomas (iCCs) are characterized by their rarity, difficult diagnosis, and overall poor prognosis. The iCC molecular classification for developing precision medicine strategies was investigated. Comprehensive genomic, transcriptomic, proteomic, and phosphoproteomic analyses were performed on treatment-naïve tumor samples from 102 patients with iCC who underwent surgical resection with curative intent. An organoid model was constructed for testing therapeutic potential. Three clinically supported subtypes (stem-like, poorly immunogenic, and metabolism) were identified. NCT-501 (ALDH1A1 inhibitor) exhibited synergism with nab-paclitaxel in the organoid model for stem-like subtype. The oncometabolite dysregulations were associated with different clinical outcomes in stem-like and metabolism subtypes. Poorly immunogenic subtype harbors the non-T-cell tumor infiltration. Integrated multiomics analysis reproduced not only the three subtypes but also showed heterogeneity in iCC. This large-scale proteogenomic analysis provides information beyond that obtained with genomic analysis, allowing the functional impact of genomic alterations to be discerned. These findings may assist in the stratification of patients with iCC and in developing rational therapeutic strategies.