Indirect mediators of systemic health outcomes following nanoparticle inhalation exposure.

The growing field of nanoscience has shed light on the wide diversity of natural and anthropogenic sources of nano-scale particulates, raising concern as to their impacts on human health. Inhalation is the most robust route of entry, with nanoparticles (NPs) evading mucociliary clearance and depositing deep into the alveolar region. Yet, impacts from inhaled NPs are evident far outside the lung, particularly on the cardiovascular system and highly vascularized organs like the brain. Peripheral effects are partly explained by the translocation of some NPs from the lung into the circulation; however, other NPs largely confined to the lung are still accompanied by systemic outcomes. Omic research has only just begun to inform on the complex myriad of molecules released from the lung to the blood as byproducts of pulmonary pathology. These indirect mediators are diverse in their molecular make-up and activity in the periphery. The present review examines systemic outcomes attributed to pulmonary NP exposure and what is known about indirect pathological mediators released from the lung into the circulation. Further focus was directed to outcomes in the brain, a highly vascularized region susceptible to acute and longer-term outcomes. Findings here support the need for big-data toxicological studies to understand what drives these health outcomes and better predict, circumvent, and treat the potential health impacts arising from NP exposure scenarios.

Neuroinflammatory and Neurometabolomic Consequences From Inhaled Wildfire Smoke-Derived Particulate Matter in the Western United States.

Utilizing a mobile laboratory located >300 km away from wildfire smoke (WFS) sources, this study examined the systemic immune response profile, with a focus on neuroinflammatory and neurometabolomic consequences, resulting from inhalation exposure to naturally occurring wildfires in California, Arizona, and Washington in 2020. After a 20-day (4 h/day) exposure period in a mobile laboratory stationed in New Mexico, WFS-derived particulate matter (WFPM) inhalation resulted in significant neuroinflammation while immune activity in the peripheral (lung, bone marrow) appeared to be resolved in C57BL/6 mice. Importantly, WFPM exposure increased cerebrovascular endothelial cell activation and expression of adhesion molecules (VCAM-1 and ICAM-1) in addition to increased glial activation and peripheral immune cell infiltration into the brain. Flow cytometry analysis revealed proinflammatory phenotypes of microglia and peripheral immune subsets in the brain of WFPM-exposed mice. Interestingly, endothelial cell neuroimmune activity was differentially associated with levels of PECAM-1 expression, suggesting that subsets of cerebrovascular endothelial cells were transitioning to resolution of inflammation following the 20-day exposure. Neurometabolites related to protection against aging, such as NAD+ and taurine, were decreased by WFPM exposure. Additionally, increased pathological amyloid-beta protein accumulation, a hallmark of neurodegeneration, was observed. Neuroinflammation, together with decreased levels of key neurometabolites, reflect a cluster of outcomes with important implications in priming inflammaging and aging-related neurodegenerative phenotypes.

Serum peptidome: diagnostic window into pathogenic processes following occupational exposure to carbon nanomaterials.

BACKGROUND: Growing industrial use of carbon nanotubes and nanofibers (CNT/F) warrants consideration of human health outcomes. CNT/F produces pulmonary, cardiovascular, and other toxic effects in animals along with a significant release of bioactive peptides into the circulation, the augmented serum peptidome. While epidemiology among CNT/F workers reports on few acute symptoms, there remains concern over sub-clinical CNT/F effects that may prime for chronic disease, necessitating sensitive health outcome diagnostic markers for longitudinal follow-up. METHODS: Here, the serum peptidome was assessed for its biomarker potential in detecting sub-symptomatic pathobiology among CNT/F workers using label-free data-independent mass spectrometry. Studies employed a stratified design between High (> 0.5 µg/m3) and Low (< 0.1 µg/m3) inhalable CNT/F exposures in the industrial setting. Peptide biomarker model building and refinement employed linear regression and partial least squared discriminant analyses. Top-ranked peptides were then sequence identified and evaluated for pathological-relevance. RESULTS: In total, 41 peptides were found to be highly discriminatory after model building with a strong linear correlation to personal CNT/F exposure. The top-five peptide model offered ideal prediction with high accuracy (Q2 = 0.99916). Unsupervised validation affirmed 43.5% of the serum peptidomic variance was attributable to CNT/F exposure. Peptide sequence identification reveals a predominant association with vascular pathology. ARHGAP21, ADAM15 and PLPP3 peptides suggest heightened cardiovasculature permeability and F13A1, FBN1 and VWDE peptides infer a pro-thrombotic state among High CNT/F workers. CONCLUSIONS: The serum peptidome affords a diagnostic window into sub-symptomatic pathology among CNT/F exposed workers for longitudinal monitoring of systemic health risks.

Pulmonary delivery of the broad-spectrum matrix metalloproteinase inhibitor marimastat diminishes multiwalled carbon nanotube-induced circulating bioactivity without reducing pulmonary inflammation.

BACKGROUND: Multiwalled carbon nanotubes (MWCNT) are an increasingly utilized engineered nanomaterial that pose the potential for significant risk of exposure-related health outcomes. The mechanism(s) underlying MWCNT-induced toxicity to extrapulmonary sites are still being defined. MWCNT-induced serum-borne bioactivity appears to dysregulate systemic endothelial cell function. The serum compositional changes after MWCNT exposure have been identified as a surge of fragmented endogenous peptides, likely derived from matrix metalloproteinase (MMP) activity. In the present study, we utilize a broad-spectrum MMP inhibitor, Marimastat, along with a previously described oropharyngeal aspiration model of MWCNT administration to investigate the role of MMPs in MWCNT-derived serum peptide generation and endothelial bioactivity. RESULTS: C57BL/6 mice were treated with Marimastat or vehicle by oropharyngeal aspiration 1 h prior to MWCNT treatment. Pulmonary neutrophil infiltration and total bronchoalveolar lavage fluid protein increased independent of MMP blockade. The lung cytokine profile similarly increased following MWCNT exposure for major inflammatory markers (IL-1ß, IL-6, and TNF-α), with minimal impact from MMP inhibition. However, serum peptidomic analysis revealed differential peptide compositional profiles, with MMP blockade abrogating MWCNT-derived serum peptide fragments. The serum, in turn, exhibited differential potency in terms of inflammatory bioactivity when incubated with primary murine cerebrovascular endothelial cells. Serum from MWCNT-treated mice led to inflammatory responses in endothelial cells that were significantly blunted with serum from Marimastat-treated mice. CONCLUSIONS: Thus, MWCNT exposure induced pulmonary inflammation that was largely independent of MMP activity but generated circulating bioactive peptides through predominantly MMP-dependent pathways. This MWCNT-induced lung-derived bioactivity caused pathological consequences of endothelial inflammation and barrier disruption.

Carbon Nanotube Exposure Triggers a Cerebral Peptidomic Response: Barrier Compromise, Neuroinflammation, and a Hyperexcited State.

The unique physicochemical properties of carbon nanomaterials and their ever-growing utilization generate a serious concern for occupational risk. Pulmonary exposure to these nanoparticles induces local and systemic inflammation, cardiovascular dysfunction, and even cognitive deficits. Although multiple routes of extrapulmonary toxicity have been proposed, the mechanism for and manner of neurologic effects remain minimally understood. Here, we examine the cerebral spinal fluid (CSF)-derived peptidomic fraction as a reflection of neuropathological alterations induced by pulmonary carbon nanomaterial exposure. Male C57BL/6 mice were exposed to 10 or 40 µg of multiwalled carbon nanotubes (MWCNT) by oropharyngeal aspiration. Serum and CSFs were collected 4 h post exposure. An enriched peptide fraction of both biofluids was analyzed using ion mobility-enabled data-independent mass spectrometry for label-free quantification. MWCNT exposure induced a prominent peptidomic response in the blood and CSF; however, correlation between fluids was limited. Instead, we determined that a MWCNT-induced peptidomic shift occurred specific to the CSF with 292 significant responses found that were not in serum. Identified MWCNT-responsive peptides depicted a mechanism involving aberrant fibrinolysis (fibrinopeptide A), blood-brain barrier permeation (homeobox protein A4), neuroinflammation (transmembrane protein 131L) with reactivity by astrocytes and microglia, and a pro-degradative (signal transducing adapter molecule, phosphoglycerate kinase), antiplastic (AF4/FMR2 family member 1, vacuolar protein sorting-associated protein 18) state with the excitation-inhibition balance shifted to a hyperexcited (microtubule-associated protein 1B) phenotype. Overall, the significant pathologic changes observed were consistent with early neurodegenerative disease and were diagnostically reflected in the CSF peptidome.

Nanoparticle exposure driven circulating bioactive peptidome causes systemic inflammation and vascular dysfunction.

BACKGROUND: The mechanisms driving systemic effects consequent pulmonary nanoparticle exposure remain unclear. Recent work has established the existence of an indirect process by which factors released from the lung into the circulation promote systemic inflammation and cellular dysfunction, particularly on the vasculature. However, the composition of circulating contributing factors and how they are produced remains unknown. Evidence suggests matrix protease involvement; thus, here we used a well-characterized multi-walled carbon nanotube (MWCNT) oropharyngeal aspiration model with known vascular effects to assess the distinct contribution of nanoparticle-induced peptide fragments in driving systemic pathobiology. RESULTS: Data-independent mass spectrometry enabled the unbiased quantitative characterization of 841 significant MWCNT-responses within an enriched peptide fraction, with 567 of these factors demonstrating significant correlation across animal-paired bronchoalveolar lavage and serum biofluids. A database search curated for known matrix protease substrates and predicted signaling motifs enabled identification of 73 MWCNT-responsive peptides, which were significantly associated with an abnormal cardiovascular phenotype, extracellular matrix organization, immune-inflammatory processes, cell receptor signaling, and a MWCNT-altered serum exosome population. Production of a diverse peptidomic response was supported by a wide number of upregulated matrix and lysosomal proteases in the lung after MWCNT exposure. The peptide fraction was then found bioactive, producing endothelial cell inflammation and vascular dysfunction ex vivo akin to that induced with whole serum. Results implicate receptor ligand functionality in driving systemic effects, exemplified by an identified 59-mer thrombospondin fragment, replete with CD36 modulatory motifs, that when synthesized produced an anti-angiogenic response in vitro matching that of the peptide fraction. Other identified peptides point to integrin ligand functionality and more broadly to a diversity of receptor-mediated bioactivity induced by the peptidomic response to nanoparticle exposure. CONCLUSION: The present study demonstrates that pulmonary-sequestered nanoparticles, such as multi-walled carbon nanotubes, acutely upregulate a diverse profile of matrix proteases, and induce a complex peptidomic response across lung and blood compartments. The serum peptide fraction, having cell-surface receptor ligand properties, conveys peripheral bioactivity in promoting endothelial cell inflammation, vasodilatory dysfunction and inhibiting angiogenesis. Results here establish peptide fragments as indirect, non-cytokine mediators and putative biomarkers of systemic health outcomes from nanoparticle exposure.

Large Scale Identification of Variant Proteins in Glioma Stem Cells.

Glioblastoma (GBM), the most malignant of primary brain tumors, is a devastating and deadly disease, with a median survival of 14 months from diagnosis, despite standard regimens of radical brain tumor surgery, maximal safe radiation, and concomitant chemotherapy. GBM tumors nearly always re-emerge after initial treatment and frequently display resistance to current treatments. One theory that may explain GBM re-emergence is the existence of glioma stemlike cells (GSCs). We sought to identify variant protein features expressed in low passage GSCs derived from patient tumors. To this end, we developed a proteomic database that reflected variant and nonvariant sequences in the human proteome, and applied a novel retrograde proteomic workflow, to identify and validate the expression of 126 protein variants in 33 glioma stem cell strains. These newly identified proteins may harbor a subset of novel protein targets for future development of GBM therapy.

Combined Proteomic-Molecular Epidemiology Approach to Identify Precision Targets in Brain Cancer.

Primary brain tumors are predominantly malignant gliomas. Grade IV astrocytomas (glioblastomas, GBM) are among the most deadly of all tumors; most patients will succumb to their disease within 2 years of diagnosis despite standard of care. The grim outlook for brain tumor patients indicates that novel precision therapeutic targets must be identified. Our hypothesis is that the cancer proteomes of glioma tumors may contain protein variants that are linked to the aggressive pathology of the disease. To this end, we devised a novel workflow that combined variant proteomics with molecular epidemiological mining of public cancer data sets to identify 10 previously unrecognized variants linked to the risk of death in low grade glioma or GBM. We hypothesize that a subset of the protein variants may be successfully developed in the future as novel targets for malignant gliomas.

Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project.

This paper summarizes the recent activities of the Chromosome-Centric Human Proteome Project (C-HPP) consortium, which develops new technologies to identify yet-to-be annotated proteins (termed "missing proteins") in biological samples that lack sufficient experimental evidence at the protein level for confident protein identification. The C-HPP also aims to identify new protein forms that may be caused by genetic variability, post-translational modifications, and alternative splicing. Proteogenomic data integration forms the basis of the C-HPP's activities; therefore, we have summarized some of the key approaches and their roles in the project. We present new analytical technologies that improve the chemical space and lower detection limits coupled to bioinformatics tools and some publicly available resources that can be used to improve data analysis or support the development of analytical assays. Most of this paper's content has been compiled from posters, slides, and discussions presented in the series of C-HPP workshops held during 2014. All data (posters, presentations) used are available at the C-HPP Wiki (http://c-hpp.webhosting.rug.nl/) and in the Supporting Information.

Quantitative proteomics reveals protein-protein interactions with fibroblast growth factor 12 as a component of the voltage-gated sodium channel 1.2 (nav1.2) macromolecular complex in Mammalian brain.

Voltage-gated sodium channels (Nav1.1-Nav1.9) are responsible for the initiation and propagation of action potentials in neurons, controlling firing patterns, synaptic transmission and plasticity of the brain circuit. Yet, it is the protein-protein interactions of the macromolecular complex that exert diverse modulatory actions on the channel, dictating its ultimate functional outcome. Despite the fundamental role of Nav channels in the brain, information on its proteome is still lacking. Here we used affinity purification from crude membrane extracts of whole brain followed by quantitative high-resolution mass spectrometry to resolve the identity of Nav1.2 protein interactors. Of the identified putative protein interactors, fibroblast growth factor 12 (FGF12), a member of the nonsecreted intracellular FGF family, exhibited 30-fold enrichment in Nav1.2 purifications compared with other identified proteins. Using confocal microscopy, we visualized native FGF12 in the brain tissue and confirmed that FGF12 forms a complex with Nav1.2 channels at the axonal initial segment, the subcellular specialized domain of neurons required for action potential initiation. Co-immunoprecipitation studies in a heterologous expression system validate Nav1.2 and FGF12 as interactors, whereas patch-clamp electrophysiology reveals that FGF12 acts synergistically with CaMKII, a known kinase regulator of Nav channels, to modulate Nav1.2-encoded currents. In the presence of CaMKII inhibitors we found that FGF12 produces a bidirectional shift in the voltage-dependence of activation (more depolarized) and the steady-state inactivation (more hyperpolarized) of Nav1.2, increasing the channel availability. Although providing the first characterization of the Nav1.2 CNS proteome, we identify FGF12 as a new functionally relevant interactor. Our studies will provide invaluable information to parse out the molecular determinant underlying neuronal excitability and plasticity, and extending the relevance of iFGFs signaling in the normal and diseased brain.

Use of ENCODE resources to characterize novel proteoforms and missing proteins in the human proteome.

We describe the utility of integrated strategies that employ both translation of ENCODE data and major proteomic technology pillars to improve the identification of the "missing proteins", novel proteoforms, and PTMs. On one hand, databases in combination with bioinformatic tools are efficiently utilized to establish microarray-based transcript analysis and supply rapid protein identifications in clinical samples. On the other hand, sequence libraries are the foundation of targeted protein identification and quantification using mass spectrometric and immunoaffinity techniques. The results from combining proteoENCODEdb searches with experimental mass spectral data indicate that some alternative splicing forms detected at the transcript level are in fact translated to proteins. Our results provide a step toward the directives of the C-HPP initiative and related biomedical research.

Systematic identification of single amino acid variants in glioma stem-cell-derived chromosome 19 proteins.

Novel proteoforms with single amino acid variations represent proteins that often have altered biological functions but are less explored in the human proteome. We have developed an approach, searching high quality shotgun proteomic data against an extended protein database, to identify expressed mutant proteoforms in glioma stem cell (GSC) lines. The systematic search of MS/MS spectra using PEAKS 7.0 as the search engine has recognized 17 chromosome 19 proteins in GSCs with altered amino acid sequences. The results were further verified by manual spectral examination, validating 19 proteoforms. One of the novel findings, a mutant form of branched-chain aminotransferase 2 (p.Thr186Arg), was verified at the transcript level and by targeted proteomics in several glioma stem cell lines. The structure of this proteoform was examined by molecular modeling in order to estimate conformational changes due to mutation that might lead to functional modifications potentially linked to glioma. Based on our initial findings, we believe that our approach presented could contribute to construct a more complete map of the human functional proteome.

Integrated chromosome 19 transcriptomic and proteomic data sets derived from glioma cancer stem-cell lines.

One subproject within the global Chromosome 19 Consortium is to define chromosome 19 gene and protein expression in glioma-derived cancer stem cells (GSCs). Chromosome 19 is notoriously linked to glioma by 1p/19q codeletions, and clinical tests are established to detect that specific aberration. GSCs are tumor-initiating cells and are hypothesized to provide a repository of cells in tumors that can self-replicate and be refractory to radiation and chemotherapeutic agents developed for the treatment of tumors. In this pilot study, we performed RNA-Seq, label-free quantitative protein measurements in six GSC lines, and targeted transcriptomic analysis using a chromosome 19-specific microarray in an additional six GSC lines. The data have been deposited to the ProteomeXchange with identifier PXD000563. Here we present insights into differences in GSC gene and protein expression, including the identification of proteins listed as having no or low evidence at the protein level in the Human Protein Atlas, as correlated to chromosome 19 and GSC subtype. Furthermore, the upregulation of proteins downstream of adenovirus-associated viral integration site 1 (AAVS1) in GSC11 in response to oncolytic adenovirus treatment was demonstrated. Taken together, our results may indicate new roles for chromosome 19, beyond the 1p/19q codeletion, in the future of personalized medicine for glioma patients.

Cloud parallel processing of tandem mass spectrometry based proteomics data.

Data analysis in mass spectrometry based proteomics struggles to keep pace with the advances in instrumentation and the increasing rate of data acquisition. Analyzing this data involves multiple steps requiring diverse software, using different algorithms and data formats. Speed and performance of the mass spectral search engines are continuously improving, although not necessarily as needed to face the challenges of acquired big data. Improving and parallelizing the search algorithms is one possibility; data decomposition presents another, simpler strategy for introducing parallelism. We describe a general method for parallelizing identification of tandem mass spectra using data decomposition that keeps the search engine intact and wraps the parallelization around it. We introduce two algorithms for decomposing mzXML files and recomposing resulting pepXML files. This makes the approach applicable to different search engines, including those relying on sequence databases and those searching spectral libraries. We use cloud computing to deliver the computational power and scientific workflow engines to interface and automate the different processing steps. We show how to leverage these technologies to achieve faster data analysis in proteomics and present three scientific workflows for parallel database as well as spectral library search using our data decomposition programs, X!Tandem and SpectraST.

Partially sequenced organisms, decoy searches and false discovery rates.

Tandem mass spectrometry is commonly used to identify peptides, typically by comparing their product ion spectra with those predicted from a protein sequence database and scoring these matches. The most reported quality metric for a set of peptide identifications is the false discovery rate (FDR), the fraction of expected false identifications in the set. This metric has so far only been used for completely sequenced organisms or known protein mixtures. We have investigated whether FDR estimations are also applicable in the case of partially sequenced organisms, where many high-quality spectra fail to identify the correct peptides because the latter are not present in the searched sequence database. Using real data from human plasma and simulated partial sequence databases derived from two complete human sequence databases with different levels of redundancy, we could demonstrate that the mixture model approach in PeptideProphet is robust for partial databases, particularly if used in combination with decoy sequences. We therefore recommend using this method when estimating the FDR and reporting peptide identifications from incompletely sequenced organisms.

Protein expression dynamics during Escherichia coli glucose-lactose diauxie.

BACKGROUND: Escherichia coli is a well-studied anaerobic bacteria which is able to regulate metabolic pathways depending on the type of sugar presented in the medium. We have studied the glucose-lactose shift in E. coli at the protein level using a recently developed mass spectrometry platform. METHOD: Cells were grown in minimal medium containing two sugars (glucose and lactose) and analyzed using novel mass spectrometry cluster. The cluster combines the high resolving power and dynamic range of Fourier transform ion cyclotron resonance (FTICR) for accurate mass measurement and quantitation with multiple ion traps for fast and sensitive tandem mass spectrometry. The protein expression profile was followed in time across the glucose-lactose diauxic shift using label-free quantitation from the FTICR data. RESULTS AND CONCLUSION: The entire dataset was interrogated by KEGG pathway analysis, mapping measured changes in protein abundance onto known metabolic pathways. The obtained results were consistent with previously published gene expression data, with ß-galactosidase being the most strongly induced protein during the diauxic shift.

A novel mass spectrometry cluster for high-throughput quantitative proteomics.

We have developed and implemented a novel mass spectrometry (MS) platform combining the advantages of high mass accuracy and resolving power of Fourier transform ion cyclotron resonance (FTICR) with the economy and speed of multiple ion traps for tandem mass spectrometry. The instruments are integrated using novel algorithms and software and work in concert as one system. Using chromatographic time compression, a single expensive FTICR mass spectrometer can match the throughput of multiple relatively inexpensive ion trap instruments. Liquid chromatography (LC)-mass spectrometry data from the two types of spectrometers are aligned and combined to hybrid datasets, from which peptides are identified using accurate mass from the FTICR data and tandem mass spectra from the ion trap data. In addition, the high resolving power and dynamic range of a 12 tesla FTICR also allows precise label-free quantitation. Using two ion traps in parallel with one LC allows simultaneous MS/MS experiments and optimal application of collision induced dissociation and electron-transfer dissociation throughout the chromatographic separation for increased proteome coverage, characterization of post-translational modifications and/or simultaneous measurement in positive and negative ionization mode. An FTICR-ion trap cluster can achieve similar performance and sample throughput as multiple hybrid ion trap-FTICR instruments, but at a lower cost. We here describe the first such FTICR-ion trap cluster, its performance and the idea of chromatographic compression.