@article{beri_kirkwood_muddiman_bereman_2018, title={A novel integrated strategy for the detection and quantification of the neurotoxin beta-N-methylamino-l-alanine in environmental samples}, volume={410}, ISSN={["1618-2650"]}, DOI={10.1007/s00216-018-0930-0}, abstractNote={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 ( 13 C 3 , 15 N 2 ) 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  13 C 3 , 15 N 2 -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. Graphical abstract Utilization of novel 13C3,15N2-BMAA and chip-based CE-MS/MS for detection and quantification of BMAA in environmental samples.}, number={10}, journal={ANALYTICAL AND BIOANALYTICAL CHEMISTRY}, author={Beri, Joshua and Kirkwood, Kaylie I. and Muddiman, David C. and Bereman, Michael S.}, year={2018}, month={Apr}, pages={2597–2605} }
 @article{bereman_beri_enders_nash_2018, title={Machine Learning Reveals Protein Signatures in CSF and Plasma Fluids of Clinical Value for ALS}, volume={8}, ISSN={["2045-2322"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85056076502&partnerID=MN8TOARS}, DOI={10.1038/s41598-018-34642-x}, abstractNote={Abstract}, number={1}, journal={SCIENTIFIC REPORTS}, author={Bereman, Michael S. and Beri, Joshua and Enders, Jeffrey R. and Nash, Tara}, year={2018}, month={Nov} }
 @article{beri_nash_martin_bereman_2017, title={Exposure to BMAA mirrors molecular processes linked to neurodegenerative disease}, volume={17}, number={17-18}, journal={Proteomics}, author={Beri, J. and Nash, T. and Martin, R. M. and Bereman, M. S.}, year={2017} }
 @article{bereman_beri_sharma_nathe_eckels_maclean_maccoss_2016, title={An Automated Pipeline to Monitor System Performance in Liquid Chromatography-Tandem Mass Spectrometry Proteomic Experiments}, volume={15}, ISSN={["1535-3907"]}, DOI={10.1021/acs.jproteome.6b00744}, abstractNote={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.}, number={12}, journal={JOURNAL OF PROTEOME RESEARCH}, author={Bereman, Michael S. and Beri, Joshua and Sharma, Vagisha and Nathe, Cory and Eckels, Josh and MacLean, Brendan and MacCoss, Michael J.}, year={2016}, month={Dec}, pages={4763–4769} }
 @article{beri_rosenblatt_strauss_urh_bereman_2015, title={Reagent for Evaluating Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) Performance in Bottom-Up Proteomic Experiments}, volume={87}, ISSN={["1520-6882"]}, DOI={10.1021/acs.analchem.5b04121}, abstractNote={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 ((13)C and (15)N) 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 parallel reaction monitoring experiments. Detection and linearity of the instrument routinely spanned three orders of magnitude across the gradient (500 fmol to 0.5 fmol on column) and no systematic trend was observed for MMA of targeted peptides as a function of abundance by analysis of variance analysis (p = 0.17). Detection and linearity of the fifth isotopologue (i.e., 0.05 fmol on column) was dependent on the peptide and instrument scan type (MS1 vs PRM). We foresee that this standard will serve as a powerful method to conduct both intra-instrument performance monitoring/evaluation, technology development, and inter-instrument comparisons.}, number={23}, journal={ANALYTICAL CHEMISTRY}, author={Beri, Joshua and Rosenblatt, Michael M. and Strauss, Ethan and Urh, Marjeta and Bereman, Michael S.}, year={2015}, month={Dec}, pages={11635–11640} }