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High, A. A.

Publications and source records attributed to High, A. A..

7 recordsLinked to original sources

Ground Truth-Based Evaluation of False Discovery Rate and Statistical Power in DIA Proteomics

Data-independent acquisition (DIA) mass spectrometry enables rapid proteomic quantification, yet the reliability of statistical inference in DIA-based protein quantification remains incompletely understood. Here, we systematically evaluated missingness, false discovery rate (FDR), and statistical power, defined as true positive rate (i.e. sensitivity or recall), using technical replicates and a spike-in benchmark with known ground truth. Analysis of 18 HeLa replicates revealed persistent, abundance-dependent missingness. In the spike-in experiment with five replicates, human peptides were titrated against a stable yeast background, allowing fold changes (FCs) to be compared with expected values. Across comparisons with log2FCs ranging from 0.2 to 2.5, the nominal BH-FDR substantially underestimated the true FDR. For example, at a BH-FDR threshold of 0.05, the true FDR was [~]0.2. Statistical power was [~]40% for a log2FC of 0.2 and increased to nearly 100% for a log2FC of 2.5. Additional incorporation of FC thresholds improved the true FDR for large-FC comparisons, with slight loss of power, but markedly reduced sensitivity for small-FC comparisons. Together, these results indicate that nominal FDR does not necessarily reflect actual error rates in DIA proteomics and that DIA performance is influenced by protein abundance and expected fold changes. This study provides a framework for experimental design and data interpretation in DIA-based proteomic studies.

bioinformatics↗

JUMPlion improves quantitative DIA proteomics through ion-level recovery of missing values

Incomplete quantification remains a persistent challenge in data-independent acquisition (DIA) mass spectrometry (MS), particularly in low-input and single-cell analyses. In identification-driven workflows, missing protein quantities often arise not from true absence of the corresponding peptides, but from failure to retain low-abundance signals from precursor or product ions for quantification. Here we present JUMPlion (local inference of ion-level missingness), a DIA quantification framework that re-examines MS raw files to recover missing values at the ion level before protein quantification. JUMPlion re-extracts precursor- and production signals directly from raw data, infers ion-level measurements within precursor-specific local quantitative neighborhoods, and combines complementary precursor- and production signals into downstream quantification. Using benchmark datasets acquired on multiple DIA platforms, JUMPlion increased protein-level completeness, improved fold-change accuracy, and enhanced detection of differentially abundant proteins while maintaining low differential-abundance false discovery rates. These gains were most evident in low-input and single-cell DIA datasets. Together, these results show that addressing missingness at the ion level before protein-level summarization can improve DIA quantification in diverse acquisition settings.

bioinformatics↗

APOE is a presynaptic protein that accumulates with age and modulates neurotransmitter release

The synaptic vesicle (SV) cycle is the fastest membrane trafficking and protein sorting process in biology. It underlies neuronal communication and cognition, yet synaptic function declines during normal aging, increasing vulnerability to neurologic disease. How the SV cycle is maintained across the lifespan of a complex organism remains unclear. Here, we used wild-type mice (C57BL/6J) to define the age- and sex-stratified molecular landscape of SVs and identified apolipoprotein E (APOE) as an abundant presynaptic protein further enriched in aged female samples. Super-resolution imaging, cell-type selective expression, and protease protection assays demonstrate that APOE originates from astroglia and associates with the cytosolic face of SVs. Using iGluSnFR and pHluorin optophysiology, we find that both decreased and increased APOE levels impair neurotransmission during stimulus trains. Together, these findings place APOE at the synapse and establish it as a cell-nonautonomous regulator of the SV cycle.

neuroscience↗

Single Plaque Proteomics Reveals the Composition and Dynamics of the Amyloid Microenvironment in Alzheimer's Disease

Alzheimers disease (AD) is characterized by amyloid plaques that form complex microenvironments in the brain. However, the molecular composition of these plaques and their temporal regulation are not well defined. Here, we developed a sensitive workflow for quantitative proteomic profiling of single plaques using refined laser capture microdissection and data-independent acquisition mass spectrometry (LCM-DIA-MS). From >200 plaques and control regions in AD mouse models (5xFAD and APP-KI) and human brains, we quantified >7,000 proteins, revealing stage-dependent, cell-type-related remodeling of the amyloid proteome (amyloidome). Temporal profiling uncovered early immune and lysosomal activation followed by engagement of RNA processing and synaptic pathways. Cross-model and cross-species analyses determined a conserved amyloidome including APOE, MDK, PTN, and HTRA1, validated by co-localization in imaging analysis. Network analysis highlighted modules in lipid transport, vesicle organization, and autophagy. These findings establish amyloid plaques as conserved, dynamic multicellular hubs that link amyloid accumulation to downstream cellular events.

neuroscience↗

Cell type-resolved proteomics reveals intra- and intercellular signalingin Alzheimers disease

Alzheimers disease (AD) arises from pathological interactions among diverse brain cell types, but cell-specific proteomic changes remain underexplored. Here, we present deep proteomic profiling of sorted or proximity-labeled brain cells from AD mouse models (5xFAD and AppNL-G-F) at multiple ages, quantifying 13,411 proteins in microglia (three subtypes), astrocytes, oligodendrocyte precursor cells, and neurons. We identified 3,028 differentially abundant proteins across these cell types, the majority of which were not detected in bulk proteomic datasets, and constructed cell type-specific networks to define functional modules and hub proteins. Comparison with transcriptomic data revealed that [~]30% of proteomic changes are RNA-independent. Further analyses uncovered cross-cell type signaling proteins conserved in human AD brains, such as pleiotrophin (Ptn), which is transcriptionally enriched in astrocytes but accumulates in microglia. Importantly, recombinant PTN directly activates induced microglia-like (iMG) human cells. Thus, these findings provide a comprehensive cell type-resolved proteomic atlas of AD models, highlighting novel intra- and intercellular signaling events. HighlightsO_LIA high-resolution cell type-resolved proteomic atlas of Alzheimers disease mouse models C_LIO_LI[~]3,000 cell type-specific protein alterations identified beyond bulk tissue analyses C_LIO_LIProteomic profiling of microglial subtypes reveals subtype-specific changes in Alzheimers disease C_LIO_LIAstrocyte-microglia signaling is highlighted and validated through PTN-mediated interactions C_LI

neuroscience↗

SLFN11 Loss-Induced Chemoresistance is Associated with Overexpression of Glycerophospholipid Biosynthesis in Ewing Sarcoma.

Ewing sarcoma (EWS) is an aggressive cancer in adolescents and young adults with frequent relapse rates and poor outcomes in recurrent or metastatic cases. Schlafen family member 11 (SLFN11) gene is associated with the sensitivity to DNA-damaging agents (DDAs). The knockout of SLFN11 is associated with acquired chemoresistance in both cell lines and preclinical models. Here, we aimed to elucidate the metabolic underpinnings of SLFN11-loss associated chemoresistance in patient derived cell lines of EWS. Our integrated transcriptomic and metabolomic analyses revealed downregulation of mitochondrial glycerol-3-phosphate dehydrogenase 2 (GPD2) gene, which was accompanied by the upregulation of glycerophospholipid (GPL) biosynthesis pathway. Further, therapeutic targeting of lipid synthesis with the glycerol-3-phosphate acyltransferase 1 (GPAT1) inhibitor (FSG67) enhanced the efficacy of the DDA (SN-38) in SLFN11-/- cells. These findings indicate that SLFN11 loss-mediated chemoresistance can be targeted by blocking GPL biosynthesis in addition to DDA administration.

cancer biology↗

Midkine Attenuates Aβ Fibril Assembly and Amyloid Plaque Formation

Proteomic profiling of Alzheimers disease (AD) brains has identified numerous understudied proteins, including midkine (MDK), that are highly upregulated and correlated with A{beta} since the early disease stage, but their roles in disease progression are not fully understood. Here we present that MDK attenuates A{beta} assembly and influences amyloid formation in the 5xFAD amyloidosis mouse model. MDK protein mitigates fibril formation of both A{beta}40 and A{beta}42 peptides in Thioflavin T fluorescence assay, circular dichroism, negative stain electron microscopy, and NMR analysis. Knockout of Mdk gene in 5xFAD increases amyloid formation and microglial activation. Further comprehensive mass spectrometry-based profiling of whole proteome and detergent-insoluble proteome in these mouse models indicates significant accumulation of A{beta} and A{beta}-correlated proteins, along with microglial components. Thus, our structural and mouse model studies reveal a protective role of MDK in counteracting amyloid pathology in Alzheimers disease.

biochemistry↗