N-terminal Imine Derivatization for Enhanced De Novo Peptide Sequencing: A Study of the Fragmentation Pattern Generated from CID of Peptide-Imines

In this work, the fragmentation pattern derived from model peptides derivatized to create N-terminal imines (Schiff bases) were evaluated. Collision-induced dissociation of the protonated peptide-imines ([M+H]+) generally produced complete series of the sequence informative an and bn ions, now undoubtedly characteristic of the peptide ion species. A novel product ion was also observed, denoted the yǂ ion, determined by IRMPD spectroscopy and density functional theory to be generated from the elimination of the N-terminal amino acid residue despite the N-terminal modification. It was concluded the pathway involved a nucleophilic attack by an amide nitrogen and the possible formation of an imidazole-4-one intermediate, which collapses to generate a truncated, protonated peptide-imine with a conserved primary sequence. N-terminal imine-modification was also observed to eliminate sequence scrambling events, presumably by eliminating the macrocyclic b ion mechanism implicated in the sequence rearrangements. Additionally, the CID mass spectra of Ag-cationized imine-modified peptides were obtained. An apparent even-electron, [M-H]+ peptide ion was observed, determined to be generated by the loss of AgH. The hydrogen abstraction was explicitly identified to originate from the imine-carbon of the argentinated modified peptide. CID of the [M–H]+ ions generated sequence ions analogous to those produced from the [M+H]+ species of imine-modified peptides, however less extensively

Whole blood transcript and protein abundance of the vascular endothelial growth factor family relate to cognitive performance

The vascular endothelial growth factor (VEGF) family of genes has been implicated in the clinical development of Alzheimer's Disease (AD). A previous study identified associations between gene expression of VEGF family members in the prefrontal cortex and cognitive performance and AD pathology. This study explored if those associations were also observed in the blood. Consistent with previous observations in brain tissue, higher blood gene expression of placental growth factor (PGF) was associated with a faster rate of memory decline (p=0.04). Higher protein abundance of FMS-related receptor tyrosine kinase 4 (FLT4) in blood was associated with biomarker levels indicative of lower amyloid and tau pathology, opposite the direction observed in brain. Also, higher gene expression of VEGFB in blood was associated with better baseline memory (p=0.008). Notably, we observed that higher gene expression of VEGFB in blood was associated with lower expression of VEGFB in the brain (r=-0.19, p=0.02). Together, these results suggest that the VEGFB, FLT4, and PGF alterations in the AD brain may be detectable in the blood compartment

Evaluating cPILOT Data toward Quality Control Implementation

Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets