Parallel reaction monitoring (PRM) is an increasingly popular alternative to selected reaction monitoring (SRM) for targeted proteomics. PRM's strengths over SRM are that it monitors all product ions in a single spectrum, thus eliminating the need to select interference-free product ions prior to data acquisition, and that it is most frequently performed on highresolution instruments, such as quadrupole-orbitrap and quadrupole-time-of-flight instruments. Here, we show that the primary advantage of PRM is the ability to monitor all transitions in parallel and that high-resolution data are not necessary to obtain highquality quantitative data. We run the same scheduled PRM assay, measuring 432 peptides from 126 plasma proteins, multiple times on an Orbitrap Eclipse Tribrid mass spectrometer, alternating separate liquid chromatography-tandem mass spectrometry runs between the high-resolution Orbitrap and the unit resolution linear ion trap for PRM. We find that both mass analyzers have similar technical precision and that the linear ion trap's superior sensitivity gives it better lower limits of quantitation for over 62% of peptides in the assay.

One of the potential benefits of using data-independent acquisition (DIA) proteomics protocols is that information not originally targeted by the study may be present and discovered by subsequent analysis. Herein, we reanalyzed DIA data originally recorded for global proteomic analysis to look for isomerized peptides, which occur as a result of spontaneous chemical modifications to long-lived proteins. Examination of a large set of human brain samples revealed a striking relationship between Alzheimer's disease (AD) status and isomerization of aspartic acid in a peptide from tau. Relative to controls, a surprising increase in isomer abundance was found in both autosomal dominant and sporadic AD samples. To explore potential mechanisms that might account for these observations, quantitative analysis of proteins related to isomerization repair and autophagy was performed. Differences consistent with reduced autophagic flux in AD-related samples relative to controls were found for numerous proteins, including most notably p62, a recognized indicator of autophagic inhibition. These results suggest, but do not conclusively demonstrate, that lower autophagic flux may be strongly associated with loss of function in AD brains. This study illustrates that DIA data may contain unforeseen results of interest and may be particularly useful for pilot studies investigating new research directions. In this case, a promising target for future investigations into the therapy and prevention of AD has been identified.

Traditional medicinal plants are a rich source of antimicrobials; however, the bioactive peptide constituents of most ethnobotanical species remain largely unexplored. Herein, PepSAVI-MS, a mass spectrometry-based peptidomics pipeline, was implemented for antimicrobial peptide (AMP) discovery in the medicinal plant Amaranthus tricolor. This investigation revealed a novel 1.7 kDa AMP with strong activity against Escherichia coli ATCC 25922, deemed Atr-AMP1. Initial efforts to determine the sequence of Atr-AMP1 utilized chemical derivatization and enzymatic digestion to provide information about specific residues and post-translational modifications. EThcD (electron-transfer/higher-energy collision dissociation) produced extensive backbone fragmentation and facilitated de novo sequencing, the results of which were consistent with orthogonal characterization experiments. Additionally, multistage HCD (higher-energy collisional dissociation) facilitated discrimination between isobaric leucine and isoleucine. These results revealed a positively charged proline-rich peptide present in a heterogeneous population of multiple peptidoforms, possessing several post-translational modifications including a disulfide bond, methionine oxidation, and proline hydroxylation. Additional bioactivity screening of a simplified fraction containing Atr-AMP1 revealed activity against Staphylococcus aureus LAC, demonstrating activity against both a Gram-negative and a Gram-positive bacterial species unlike many known short chain proline-rich antimicrobial peptides.

Advances in library-based methods for peptide detection from data-independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high-quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico, but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate-controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide-window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.

We report a data independent acquisition (DIA) strategy that dynamically adjusts the tandem mass spectrometry (MS/MS) windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time- improving the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.