Meloidogyne graminicola hijacks host metabolism and suppresses immunity: insights from DIA-based proteomics in rice

Background: Identification of circulating biomarkers in cancer has proven utility in applications for early detection, differential diagnosis, predicting pre-treatment response to therapy, and treatment monitoring. More recently, circulating proteomic biomarkers have been evaluated as surrogate endpoints for early indication of benefit for immunotherapies. This last application is especially relevant during immunotherapy development where the optimal endpoint, overall survival (OS), can take longer to mature. Here, we present an unbiased survey of the circulating proteome of subjects with NSCLC to identify candidate biomarkers that may have utility in multiple stages of patient care. Methods: Unbiased, data-independent acquisition (DIA) mass spectrometry was used to analyze plasma samples from subjects with Stage III-IV non-small cell lung cancer (NSCLC, n = 15) and age matched healthy donors (n = 15), enabling simultaneous sequencing and quantification of plasma proteins. Samples were prepared for mass spectrometry and spiked with a panel of standards covering 500 plasma proteins. All samples were analyzed using 1h gradients on a C18 column coupled to a Thermo Scientific Q Exactive HF mass spectrometer. Data were extracted using Spectronaut (Biognosys) with a sample specific spectral library and statistical analysis was conducted to identify disease associated biomarker candidates. Pathway analysis highlights dysregulated biologic functions and predicts upstream regulatory pathways. Results: A protein library was created containing 771 unique proteins. In DIA acquisition, 462 proteins were quantified across all samples. Univariate statistical testing identified 26 dysregulated proteins (20 up-regulated and 6 down-regulated; q-value > 0.05 and log2 fold change > 0.58). Multivariate (PLS-DA) analysis identified c-reactive protein (CRP) and serum amyloid a (SAA1/SAA2), complement C9, S100A8/S100A9, and leucine rich glycoprotein 1 (LRG1) as the most significantly changed proteins across sample groups. Receiver operator analysis (ROC) identified S100A8 and complement C9 as the markers with the greatest diagnostic power at 93% sensitivity and 93% specificity. Significantly enriched pathways include acute phase response, complement system as well as IL-12 and IL-6 signaling. Similarly, upstream activated candidate pathways included STAT3, IL-6, and EZ2H. Conclusions: 26 proteins were identified as candidate biomarkers and reflect the host immune response via acute phase response signaling, innate immune response (complement system), and other proinflammatory stimuli. Several of these markers have been linked to patient outcomes and poor prognosis. Accurate monitoring of these proteins offers the possibility to define surrogate, molecular-based markers with multiple modes of utility. Citation Format: Nicholas Dupuis, Jakob Vowinckel, Daniel Heinzmann, Claudia Escher. A survey of circulating biomarkers in subjects with NSCLC using library-based data independent acquisition mass spectrometry reveals host immune response mechanisms [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B010.

mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry

On infection, plant‐parasitic nematodes establish feeding sites in roots from which they take up carbohydrates among other nutrients. Knowledge on how carbohydrates are supplied to the nematodes’ feeding sites is limited. Here, gene expression analyses showed that RNA levels of OsSWEET11 to OsSWEET15 were extremely low in both Meloidogyne graminicola (Mg)‐caused galls and noninoculated roots. All the rice sucrose transporter genes, OsSUT1 to OsSUT5, were either down‐regulated in Mg‐caused galls compared with noninoculated rice roots or had very low transcript abundance. OsSUT1 was the only gene up‐regulated in galls, at 14 days postinoculation (dpi), after being highly down‐regulated at 3 and 7 dpi. OsSUT4 was down‐regulated at 3 dpi. No noticeable OsSUTs promoter activities were detected in Mg‐caused galls of pOsSUT1 to ‐5::GUS rice lines. Loading experiments with carboxyfluorescein diacetate (CFDA) demonstrated that symplastic connections exist between phloem and Mg‐caused giant cells (GCs). According to data from OsGNS5‐ and OsGSL2‐overexpressing rice plants that had decreased and increased callose deposition, respectively, callose negatively affected Mg parasitism and sucrose supply to Mg‐caused GCs. Our results suggest that plasmodesmata‐mediated sucrose transport plays a pivotal role in sucrose supply from rice root phloem to Mg‐caused GCs, and OsSWEET11 to ‐15 and OsSUTs are not major players in it, although further functional analysis is needed for OsSUT1 and OsSUT4.

Purpose: Pulmonary inflammation is an adverse consequence of radiation therapy in breast cancer. The aim of this study was to elucidate biological pathways leading to this pathology.Materials and methods: Lung endothelial cells were isolated 24 h after thorax-irradiation (sham or 10 Gy X-ray) from female C57Bl/6 mice and cultivated for 6 days.Results: Quantitative proteomic analysis of lung endothelial cells was done using data independent acquisition (DIA) mass spectrometry. The data were analyzed using Ingenuity Pathway Analysis and STRINGdb. In total, 4220 proteins were identified using DIA of which 60 were dysregulated in the irradiated samples (fold change ≥2.00 or ≤0.50; q-value <0.05). Several (12/40) upregulated proteins formed a cluster of inflammatory proteins with STAT1 and IRF3 as predicted upstream regulators. The several-fold increased expression of STAT1 and STAT-associated ISG15 was confirmed by immunoblotting. The expression of antioxidant proteins SOD1 and PRXD5 was downregulated suggesting radiation-induced oxidative stress. Similarly, the phosphorylated (active) forms of STING and IRF3, both members of the cGAS/STING pathway, were downregulated.Conclusions: These data suggest the involvement of JAK/STAT and cGas/STING pathways in the genesis of radiation-induced lung inflammation. These pathways may be used as novel targets for the prevention of radiation-induced lung damage.

CysQuant: Simultaneous quantification of cysteine oxidation and protein abundance using data dependent or independent acquisition mass spectrometry

Data Independent Acquisition (DIA) Mass Spectrometry (MS) workflows allow unbiased measurement of all detectable peptides from complex proteomes, but require ion libraries for interrogation of peptides of interest. These DIA ion libraries can be theoretical or built from peptide identification data from Data Dependent Acquisition (DDA) MS workflows. However, DDA libraries derived from empirical data rely on confident peptide identification, which can be challenging for peptides carrying complex post-translational modifications. Here, we present DIALib, software to automate the construction of peptide and glycopeptide Data Independent Acquisition ion Libraries. We show that DIALib theoretical ion libraries can identify and measure diverse N- and O-glycopeptides from yeast and mammalian glycoproteins without prior knowledge of the glycan structures present. We present proof-of-principle data from a moderately complex yeast cell wall glycoproteome and a simple mixture of mammalian glycoproteins. We also show that DIALib libraries consisting only of glycan oxonium ions can quickly and easily provide a global compositional glycosylation profile of the detectable "oxoniome" of glycoproteomes. DIALib will help enable DIA glycoproteomics as a complementary analytical approach to DDA glycoproteomics.

Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. Here, we introduce an experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in a proteomics experiment. These coordinates calibrate protein databases or spectrum libraries to a specific mass spectrometer and chromatography setup, facilitating DIA-only pipelines and the reuse of global resource libraries. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect 20–25% more peptides from DIA experiments than with data dependent acquisition-based spectrum libraries alone.

SWATH data independent acquisition mass spectrometry for screening of xenobiotics in biological fluids: Opportunities and challenges for data processing

Amino acid sequences of immunodominant domains of hemagglutinin (HA) on the surface of influenza A virus (IAV) evolve rapidly, producing viral variants. HA mediates receptor recognition, binding and cell entry, and serves as the target for IAV vaccines. Glycosylation, a post-translational modification that places large branched polysaccharide molecules on proteins, can modulate the function of HA and shield antigenic regions allowing for viral evasion from immune responses. Our previous work showed that subtle changes in the HA protein sequence can have a measurable change in glycosylation. Thus, being able to quantitatively measure glycosylation changes in variants is critical for understanding how HA function may change throughout viral evolution. Moreover, understanding quantitatively how the choice of viral expression systems affects glycosylation can help in the process of vaccine design and manufacture. Although IAV vaccines are most commonly expressed in chicken eggs, cell-based vaccines have many advantages, and the adoption of more cell-based vaccines would be an important step in mitigating seasonal influenza and protecting against future pandemics. Here, we have investigated the use of data-independent acquisition (DIA) mass spectrometry for quantitative glycoproteomics. We found that DIA improved the sensitivity of glycopeptide detection for four variants of A/Switzerland/9715293/2013 (H3N2): WT and mutant, each expressed in embryonated chicken eggs and Madin–Darby canine kidney cells. We used the Tanimoto similarity metric to quantify changes in glycosylation between WT and mutant and between egg-expressed and cell-expressed virus. Our DIA site-specific glycosylation similarity comparison of WT and mutant expressed in eggs confirmed our previous analysis while achieving greater depth of coverage. We found that sequence variations and changing viral expression systems affected distinct glycosylation sites of HA. Our methods can be applied to track glycosylation changes in circulating IAV variants to bolster genomic surveillance already being done, for a more complete understanding of IAV evolution.

Zinc is central to the function of many proteins, yet the mechanisms of zinc homeostasis and their interplay with other cellular systems remain underexplored. In this study, we employ data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to investigate proteome changes in Pseudomonas aeruginosa under conditions of different zinc availability. Using these methods, we detected 2143 unique proteins, 1578 of which were identified by both DDA and DIA. We demonstrated that most of the previously described Zn homeostasis systems exhibit proteomic responses that follow similar trends to those seen in transcriptomics studies. However, some proteins that are considered instrumental in Zn homeostasis, notably those in Zn transporter ZnuABC, were not detected by our methods, although other proteins of other uptake systems were abundant. Furthermore, changes in abundance of multiple Zn-metalloproteins and Zn-independent homologs were clearly observable, with respective increases and decreases when Zn was provided, though the magnitude of these changes varied. Most of the Zn-metalloproteins observed were located in one of two Zur-regulated operons between PA5534 and PA5541. This study provides a view of Zn homeostasis mechanisms that is complementary to existing transcriptomics investigations: as gene transcripts are not strictly proportional to the actual distribution of proteins within a cell, analysis of the proteome offers another way to assess the relative use and importance of similar or ostensibly redundant systems in different conditions and can highlight shifts in metal prioritization between metalloproteins.

Zinc is central to the function of many proteins, yet the mechanisms of zinc homeostasis and their interplay with other cellular systems remain underexplored. In this study, we employ data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to investigate proteome changes in Pseudomonas aeruginosa under conditions of different zinc availability. Using both methods, we detected a combined 2143 unique proteins, 1578 of which were identified by both DDA and DIA. We demonstrated that most of the previously described Zn homeostasis systems exhibit proteomic responses that follow similar trends to those seen in transcriptomics studies. Furthermore, changes in abundance of multiple Zn-metalloproteins and Zn-independent homologs were clearly observable, with respective increases and decreases when Zn was provided, though the magnitude of these changes varied. Most of the Zn-metalloproteins observed were located in one of two Zur-regulated operons between PA5534 and PA5541. This study provides a view of Zn homeostasis mechanisms that is complementary to existing transcriptomics investigations: as gene transcripts are not strictly proportional to the actual distribution of proteins within a cell, analysis of the proteome offers another way to assess the relative use and importance of similar or ostensibly redundant systems in different conditions and can highlight shifts in metal prioritization between metalloproteins.

Background CanPathPro is designed to build and validate a combined experimental and systems biology platform, which will be used in testing cancer signaling hypotheses. It combines highly defined mouse and organotypic experimental systems, high-dimensional data including next generation sequencing and quantitative proteomics, and computational models for data integration, visualization and modelling. Mouse cancer models are characterized by quantitative transcriptome, quantitative mass spectrometry including phospho-proteome, histopathology and histochemistry. Phospho-proteomic data has been obtained using data independent acquisition (DIA) and used to refine signaling models in the mouse cell lines. Currently, the model integrates modules of the signal transduction pathways Egfr/Erbb2, Fgfr, insulin, Akt, Mtor, Myc, Ras, Hippo, Met, Tgfbr, Il6, integrin, Wnt, apoptosis and cell cycle regulation integrating in total about 380 different genes as well as related proteins and phospho-proteins Methods Two mouse mammary gland model cell lines, (Cdh1-fl/AKT1[E17K] and Cdh1-fl + PTEN-fl) were each treated with DMSO, a Pik3ca inhibitor (Wortmannin), or an Akt inhibitor (MK-2206). Cells were lysed and proteins were denatured, followed by reduction, alkylation and digestion with trypsin. The resulting peptides were desalted and enriched for phosphopeptides with TiO2 beads and cleaned up for mass spectrometry. A phosphopeptide library was generated from pooled phosphoenriched samples using LC-MS/MS shotgun measurements and included 22,893 phosphosites from 3,549 protein groups. DIA data was acquired on a Q Exactive HF mass spectrometer with a gradient length of 60 - 120 minutes on a C18 Easy LC 1200 nano-liquid chromatography system. The DIA data was extracted and processed with Spectronaut 11 (Biognosys) for analysis. Results In the AKT1[E17K] samples, 13,396 peptides (21,862 phospho-peptides) were quantified in the DIA runs and 12,297 peptides (19,928 phospho-peptides) were quantified in PTEN-fl samples. Under treatment with MK2206 and Wortmanin, 859 phosphopeptides from 548 protein groups were significantly changed across all comparisons in the AKT1[E17K] samples and with the same treatments 2,276 phosphopeptides from 976 proteins were significantly changed in the PTEN-fl cells. Based on this data 11 functionally relevant new phosphosites have been added to the model including ones on: EIF4B, FOX03, MAP2K4, PAK1, RAF1, and ULK1. Conclusions Phospho-proteomic profiling of cell lines using DIA mass spectrometry enables deep characterization of the phospho-signaling cascades modulated through small molecule inhibitors. Citation Format: Magdalena Bober, Monika Banko-Bielecka, Daniel Heinzmann, Oliver Rinner, Nicholas Dupuis, Christoph Wierling, Huaibiao Li, Thomas Kessler, Artur Muradyan, Louisa Krützfeldt, Moritz Schütte, Felix Dreher, Aspasia Ploubidou, Bodo Lange. Unbiased phospho-proteomic profiling of mouse breast cancer models with DIA mass spectrometry refines CanPath prototype, a platform for predictive cancer pathway modeling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3916.

Background CanPathPro is designed to build and validate a combined experimental and systems biology platform, which will be used in testing cancer signaling hypotheses. It combines highly defined mouse and organotypic experimental systems, high-dimensional data including next generation sequencing and quantitative proteomics, and computational models for data integration, visualization and modelling. Mouse cancer models are characterized by quantitative transcriptome, quantitative mass spectrometry including phospho-proteome, histopathology and histochemistry. Phospho-proteomic data has been obtained using data independent acquisition (DIA) and used to refine signaling models in the mouse cell lines. Currently, the model integrates modules of the signal transduction pathways Egfr/Erbb2, Fgfr, insulin, Akt, Mtor, Myc, Ras, Hippo, Met, Tgfbr, Il6, integrin, Wnt, apoptosis and cell cycle regulation integrating in total about 380 different genes as well as related proteins and phospho-proteins Methods Two mouse mammary gland model cell lines, (Cdh1-fl/AKT1[E17K] and Cdh1-fl + PTEN-fl) were each treated with DMSO, a Pik3ca inhibitor (Wortmannin), or an Akt inhibitor (MK-2206). Cells were lysed and proteins were denatured, followed by reduction, alkylation and digestion with trypsin. The resulting peptides were desalted and enriched for phosphopeptides with TiO2 beads and cleaned up for mass spectrometry. A phosphopeptide library was generated from pooled phosphoenriched samples using LC-MS/MS shotgun measurements and included 22,893 phosphosites from 3,549 protein groups. DIA data was acquired on a Q Exactive HF mass spectrometer with a gradient length of 60 - 120 minutes on a C18 Easy LC 1200 nano-liquid chromatography system. The DIA data was extracted and processed with Spectronaut 11 (Biognosys) for analysis. Results In the AKT1[E17K] samples, 13,396 peptides (21,862 phospho-peptides) were quantified in the DIA runs and 12,297 peptides (19,928 phospho-peptides) were quantified in PTEN-fl samples. Under treatment with MK2206 and Wortmanin, 859 phosphopeptides from 548 protein groups were significantly changed across all comparisons in the AKT1[E17K] samples and with the same treatments 2,276 phosphopeptides from 976 proteins were significantly changed in the PTEN-fl cells. Based on this data 11 functionally relevant new phosphosites have been added to the model including ones on: EIF4B, FOX03, MAP2K4, PAK1, RAF1, and ULK1. Conclusions Phospho-proteomic profiling of cell lines using DIA mass spectrometry enables deep characterization of the phospho-signaling cascades modulated through small molecule inhibitors. Citation Format: Magdalena Bober, Monika Banko-Bielecka, Daniel Heinzmann, Oliver Rinner, Nicholas Dupuis, Christoph Wierling, Huaibiao Li, Thomas Kessler, Artur Muradyan, Louisa Krutzfeldt, Moritz Schutte, Felix Dreher, Aspasia Ploubidou, Bodo Lange. Unbiased phospho-proteomic profiling of mouse breast cancer models with DIA mass spectrometry refines CanPath prototype, a platform for predictive cancer pathway modeling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3916.

It has been a challenge to analyze minute amounts of proteomic samples in a facile and robust manner. Herein, we developed a quantitative proteomics workflow by integrating suspension trapping (S-Trap)-based sample preparation and label-free data-independent acquisition (DIA) mass spectrometry and then applied it for the analysis of microgram and even nanogram amounts of exosome samples. S-Trap-based sample preparation outperformed the traditional in-solution digestion-based approach and the commonly used filter-aided sample preparation (FASP)-based approach with regard to the number of proteins and peptides identified. Moreover, S-Trap-based sample preparation coupled with DIA mass spectrometry also showed the highest reproducibility for protein quantification. In addition, this approach allowed for identification and quantification of exosome proteins with low starting amounts (down to 50 ~ 200ng). Finally, the proposed method was successfully applied to label-free quantification of exosomal proteins extracted from MDA-MB-231 breast cancer cells and MCF-10A non-tumorigenic epithelial breast cells. Prospectively, we envision the integrated S-Trap sample preparation coupled with DIA quantification strategy as a promising alternative for highly efficient and sensitive analysis of trace amounts of proteomic samples (e.g., exosomal samples).

Mass spectrometry is the driving force behind current brain proteome analysis. In a typical proteomics approach, a protein isolate is digested into tryptic peptides and then analyzed by liquid chromatography–mass spectrometry. The recent advancements in data independent acquisition (DIA) mass spectrometry provide higher sensitivity and protein coverage than the classic data dependent acquisition. DIA cycles through a pre-defined set of peptide precursor isolation windows stepping through 400–1,200 m/z across the whole liquid chromatography gradient. All peptides within an isolation window are fragmented simultaneously and detected by tandem mass spectrometry. Peptides are identified by matching the ion peaks in a mass spectrum to a spectral library that contains information of the peptide fragment ions' pattern and its chromatography elution time. Currently, there are several reports on DIA in brain research, in particular the quantitative analysis of cellular and synaptic proteomes to reveal the spatial and/or temporal changes of proteins that underlie neuronal plasticity and disease mechanisms. Protocols in DIA are continuously improving in both acquisition and data analysis. The depth of analysis is currently approaching proteome-wide coverage, while maintaining high reproducibility in a stable and standardisable MS environment. DIA can be positioned as the method of choice for routine proteome analysis in basic brain research and clinical applications.