Robust analytical methods for bis(monoacylglycero)phosphate profiling in health and disease
Dong, W.; Nyame, K.; Rawat, E. S.; Medoh, U. N.; Xiong, J.; Bonin, C. C.; Alsohybe, H. N.; Liu, H. Y.; Gomes, S.; Hsieh, T.; Arnold, M.; Hsieh, F.; Sammler, E.; Abu-Remaileh, M.
Show abstract
Bis(monoacylglycero)phosphate (BMP), a distinct anionic phospholipid predominantly found in late endosomes and lysosomes, plays a pivotal role in supporting lysosomal functions and maintaining metabolic homeostasis. Its impaired function is associated with an array of disorders, notably neurodegenerative diseases. However, the identification and quantitation of BMP remains difficult due to its structural similarity to isomer phosphatidylglycerol (PG), thus necessitating robust analytical methods for accurate and reliable BMP profiling. In this study, we present comprehensive liquid chromatography - tandem mass spectrometry (MS2) methodologies for the precise and systematic analysis of BMP species in biological samples. We detail LC/MS methods for both an untargeted Orbitrap mass spectrometer and a targeted triple quadrupole (QQQ) mass spectrometer. We utilize differences in polarity and structure to annotate BMPs and PGs based on retention time and positive mode MS2 fragmentation patterns, respectively. Further, we propose a new approach for overcoming common challenges in BMP profiling by leveraging the newly discovered biochemical function of CLN5 as the BMP synthase. Since genetic ablation of CLN5 leads to specific depletion of BMPs but not PGs, we use lipid extracts from CLN5 knockout (KO) and wild-type (WT) cells as biological standards to confidently annotate BMPs as targets with significantly low BMP Identification Index (BMPII), defined as BMPII = CLN5 KO / WT. We additionally propose the BMP enrichment score (BMPES) as a secondary validation metric, defined as lysosomal abundance of BMP / whole-cell abundance. Altogether, this approach constitutes a robust method for BMP profiling and annotation, furthering research into health and disease.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP 97%
- Direct, quantitative, and comprehensive analysis of tRNA acylation using intact tRNA liquid-chromatography mass-spectrometry 93%
- Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics 93%
Similar papers in this journal
- Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics 93%
- Measuring mitochondrial electron transfer complexes in previously frozen cardiac tissue from the offspring of sow: A model to assess exercise-induced mitochondrial bioenergetics changes 93%
- Isolation and Characterization of Human Adipocyte-derived Extracellular Vesicles Using Filtration and Ultracentrifugation 92%
Similar papers in this journal
- Heat n Beat: A universal high-throughput end-to-end proteomics sample processing platform in under an hour 96%
- High Throughput Single Cell Proteomic Analysis of Organ Derived Heterogeneous Cell Populations by Nanoflow Dual Trap Single Column Liquid Chromatography 95%
- Contaminant Spot Check and Removal Assay (ContamSPOT) for Mass Spectrometry Analysis 95%
Similar papers in this journal
- Metabolomic, proteomic and single cell proteomic analysis of cancer cells treated with the KRASG12D inhibitor MRTX1133 96%
- Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Clean-up Techniques 95%
- Development of an Adaptive, Economical, and Easy-to-Use SP3-TMT Automated Sample Preparation Workflow for Quantitative Proteomics 95%
Similar papers in this journal
- Optimizing In Situ Proximity Ligation Assays for Mitochondria, ER, or MERC Markers in Skeletal Muscle Tissue and Cells 92%
- Laser Capture Microdissection optimization for high-quality RNA in mouse brain tissue 91%
- Calling Cards: a customizable platform to longitudinally record protein-DNA interactions over time in cells and tissues 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.