Michael S. Bereman

We employ shotgun proteomics and data-independent acquisition (DIA) mass spectrometry to analyze cerebrospinal fluid longitudinally collected from 14 amyotrophic lateral sclerosis (ALS) patients (8 males and 6 females). We perform three main analyses of these data: (1) examine the intra- and inter-patient protein variability in CSF; (2) explore the association of inflammation with rate of disease progression; and (3) develop a mixed-effects model to best explain the decrease in ALS-Functional Rating Scale (ALS-FRS) score. Overall, the CSF protein abundances are tightly regulated with the intra-individual variability contributing just 4% to the overall variance. In four patients, a moderately significant correlation (p < 0.1) was observed between inflammation and rate of disease progression. Using a least absolute shrinkage and selection operator (LASSO) variable selection, we selected 55 viable peptides for mathematical modeling via a linear mixed-effects regression. We then employed forward selection to generate a final model by minimizing Akaike’s information criterion (AIC). The final model utilized changes in abundance from 28 peptides as fixed effects to model progression of the disease in these patients. These peptides were from proteins involved in stress response and innate immunity. Graphical abstract

We use shotgun proteomics to identify biomarkers of diagnostic and prognostic value in individuals diagnosed with amyotrophic lateral sclerosis. Matched cerebrospinal and plasma fluids were subjected to abundant protein depletion and analyzed by nano-flow liquid chromatography high resolution tandem mass spectrometry. Label free quantitation was used to identify differential proteins between individuals with ALS (n = 33) and healthy controls (n = 30) in both fluids. In CSF, 118 (p-value < 0.05) and 27 proteins (q-value < 0.05) were identified as significantly altered between ALS and controls. In plasma, 20 (p-value < 0.05) and 0 (q-value < 0.05) proteins were identified as significantly altered between ALS and controls. Proteins involved in complement activation, acute phase response and retinoid signaling pathways were significantly enriched in the CSF from ALS patients. Subsequently various machine learning methods were evaluated for disease classification using a repeated Monte Carlo cross-validation approach. A linear discriminant analysis model achieved a median area under the receiver operating characteristic curve of 0.94 with an interquartile range of 0.88–1.0. Three proteins composed a prognostic model (p = 5e-4) that explained 49% of the variation in the ALS-FRS scores. Finally we investigated the specificity of two promising proteins from our discovery data set, chitinase-3 like 1 protein and alpha-1-antichymotrypsin, using targeted proteomics in a separate set of CSF samples derived from individuals diagnosed with ALS (n = 11) and other neurological diseases (n = 15). These results demonstrate the potential of a panel of targeted proteins for objective measurements of clinical value in ALS.

We describe a set of new tools for the detection and quantification of β-N-methylamino-l-alanine (BMAA) which includes a novel stable isotope-labeled BMAA standard (¹³C₃,¹⁵N₂) and a chip-based capillary electrophoresis mass spectrometry platform for separation and detection. Baseline resolution of BMAA from its potentially confounding structural isomers N-2-aminoethylglycine (AEG) and 2,4-diaminobutyric acid (2,4-DAB) is achieved using the chip-based CE-MS system in less than 1 min. Detection and linearity of response are demonstrated across > 3.5 orders of dynamic range using parallel reaction monitoring (PRM). The lower limit of detection and quantification were calculated for BMAA detection at 40 nM (4.8 ng/mL) and 400 nM (48 ng/mL), respectively. Finally, the strategy was applied to detect BMAA in seafood samples purchased at a local market in Raleigh, NC where their harvest location was known. BMAA was detected in a sea scallop sample. Because the BMAA/stable isotope-labeled ¹³C₃,¹⁵N₂-BMAA (SIL-BMAA) ratio in the scallop sample was below the limit of quantification, a semiquantitative analysis of BMAA content was carried out, and BMAA content was estimated to be approximately 820 ng BMAA/1 g of wet scallop tissue. Identification was verified by high mass measurement accuracy of precursor (< 5 ppm) and product ions (< 10 ppm), comigration with SIL-BMAA spike-in standard, and conservation of ion abundance ratios for product ions between BMAA and SIL-BMAA. Interestingly, BMAA was not identified in the free protein fraction but only detected after protein hydrolysis which suggests that BMAA is tightly bound by and/or incorporated into proteins.

The goal of this study is to investigate the molecular pathways perturbed by in vitro exposure of beta‐methylamino‐L‐alanine (BMAA) to NSC‐34 cells via contemporary proteomics. Our analysis of differentially regulated proteins reveals significant enrichment (p < 0.01) of pathways related to ER stress, protein ubiquitination, the unfolded protein response, and mitochondrial dysfunction. Upstream regulator analysis indicates that exposure to BMAA induces activation of transcription factors (X‐box binding protein 1; nuclear factor 2 erythroid like 2; promyelocytic leukemia) involved in regulation of the UPR, oxidative stress, and cellular senescence. Furthermore, the authors examine the hypothesis that BMAA causes protein damage via misincorporation in place of L‐Serine. The authors are unable to detect misincorporation of BMAA into protein via analysis of cellular protein, secreted protein, targeted detection of BMAA after protein hydrolysis, or through the use of in vitro protein translation kits.

Carbon nanotubes (CNTs), a prototypical engineered nanomaterial, have been increasingly manufactured for a variety of novel applications over the past two decades. However, since CNTs possess fiber-like shape and cause pulmonary fibrosis in rodents, there is concern that mass production of CNTs will lead to occupational exposure and associated pulmonary diseases. The aim of this study was to use contemporary proteomics to investigate the mechanisms of cellular response in E10 mouse alveolar epithelial cells in vitro after exposure to multi-walled CNTs (MWCNTs) that were functionalized by atomic layer deposition (ALD). ALD is a method used to generate highly uniform and conformal nanoscale thin-film coatings of metals to enhance novel conductive properties of CNTs. We hypothesized that specific types of metal oxide coatings applied to the surface of MWCNTs by ALD would determine distinct proteomic profiles in mouse alveolar epithelial cells in vitro that could be used to predict oxidative stress and pulmonary inflammation. Uncoated (U)-MWCNTs were functionalized by ALD with zinc oxide (ZnO) to yield Z-MWCNTs or aluminum oxide (Al₂O₃) to yield A-MWCNTs. Significant differential protein expression was found in the following critical pathways: mTOR/eIF4/p70S6K signaling and Nrf-2 mediated oxidative stress response increased following exposure to Z-MWCNTs, interleukin-1 signaling increased following U-MWCNT exposure, and inhibition of angiogenesis by thrombospondin-1, oxidative phosphorylation, and mitochondrial dysfunction increased following A-MWCNT exposure. This study demonstrates that specific types of metal oxide thin film coatings applied by ALD produce distinct cellular and biochemical responses related to lung inflammation and fibrosis compared to uncoated MWCNT exposure in vitro.

We report the development of a completely automated pipeline to monitor system suitability in bottom-up proteomic experiments. LC–MS/MS runs are automatically imported into Skyline and multiple identification-free metrics are extracted from targeted peptides. These data are then uploaded to the Panorama Skyline document repository where metrics can be viewed in a web-based interface using powerful process control techniques, including Levey–Jennings and Pareto plots. The interface is versatile and takes user input, which allows the user significant control over the visualization of the data. The pipeline is vendor and instrument-type neutral, supports multiple acquisition techniques (e.g., MS 1 filtering, data-independent acquisition, parallel reaction monitoring, and selected reaction monitoring), can track performance of multiple instruments, and requires no manual intervention aside from initial setup. Data can be viewed from any computer with Internet access and a web browser, facilitating sharing of QC data between researchers. Herein, we describe the use of this pipeline, termed Panorama AutoQC, to evaluate LC–MS/MS performance in a range of scenarios including identification of suboptimal instrument performance, evaluation of ultrahigh pressure chromatography, and identification of the major sources of variation throughout years of peptide data collection.

Paper-based microfluidic techniques were explored to increase paper spray mass spectrometry's performance and versatility.

We present a novel proteomic standard for assessing liquid chromatography–tandem mass spectrometry (LC-MS/MS) instrument performance, in terms of chromatographic reproducibility and dynamic range within a single LC-MS/MS injection. The peptide mixture standard consists of six peptides that were specifically synthesized to cover a wide range of hydrophobicities (grand average hydropathy (GRAVY) scores of −0.6 to 1.9). A combination of stable isotope labeled amino acids (13C and 15N) were inserted to create five isotopologues. By combining these isotopologues at different ratios, they span four orders of magnitude within each distinct peptide sequence. Each peptide, from lightest to heaviest, increases in abundance by a factor of 10. We evaluate several metrics on our quadrupole orbitrap instrument using the 6 × 5 LC-MS/MS reference mixture spiked into a complex lysate background as a function of dynamic range, including mass measurement accuracy (MMA) and the linear range of quantitation of MS1 and paralle...