Biology subjects

Wu, C. C.

Publications and source records attributed to Wu, C. C..

15 recordsLinked to original sources

bioRxiv2026

Hepatic huntingtin loss drives an acute phase response and liver injury in multiple mouse models

Multiple therapeutic strategies are being developed to slow Huntingtons disease (HD) progression through targeted reduction of huntingtin (HTT) protein or mRNA. Despite HTTs discovery over 30 years ago, its cellular functions remain incompletely understood, and the long-term consequences of HTT-lowering therapies remain unclear. We previously demonstrated that hepatic HTT loss in mice disrupts hepatocyte zonation and metabolism. Here, we investigate the physiological consequences of hepatic Htt loss. Across multiple models of Htt loss--including ubiquitous and hepatocyte-specific genetic knockouts and a therapeutically relevant Htt-targeting siRNA--there was elevated expression of IL-6/STAT3-driven acute phase response genes. Single-nucleus RNA sequencing reveals a zonal pattern of hepatocyte stress, most highly upregulated in pericentral hepatocytes, and identifies a distinct pericentral cluster of stressed hepatocytes that was enriched [~]9.6-fold following Htt knockout. Histological examination reveals that Htt loss results in increased hepatic pathology, including hepatic intranuclear inclusions, apoptosis, and necrosis, as well as prevalence of granulomas. Transcriptomic analysis reveals significant upregulation of metallothionein genes following Htt loss, as confirmed by elevated plasma metallothionein-1 (MT1) levels in knockout mice. These findings underscore important safety considerations for HTT-lowering therapies and suggest candidate biomarkers for monitoring hepatic off-target effects in clinical trials.

molecular biology↗

bioRxiv2026

Circulating extracellular vesicles in plasma carry accessible molecular signatures of aging in mice

Cells release membrane-bound extracellular vesicles into the bloodstream laden with proteins that may reflect their physiological state. How this circulating EV proteome changes across life remains poorly understood. Identifying molecular signatures of aging in accessible biofluids could facilitate earlier intervention and monitoring of age-related disease. Many circulating aging proteome studies rely on affinity-based platforms which suffer from poor cross-species translation, ambiguous signal attribution, and inconsistent agreement between platforms. Here, we present a characterization of the aging plasma EV proteome from a cross-sectional cohort of 86 male and female C57BL/6J mice (5-31 months). We leveraged a species-agnostic EV enrichment (Mag-Net) and mass spectrometry to detect 2,575 protein groups from 15,969 peptides. Protein abundance heterogeneity increased with age and the abundance of 272 proteins were significantly correlated with chronological age including established senescence and frailty markers. Proteins increasing with age were enriched in genome maintenance pathways, while those decreasing were associated with the extracellular matrix organization and lipid metabolism. Notably, several of the strongest age-increased proteins converged on Alzheimers and Parkinsons disease pathology. We observed sexual divergence in the aging EV proteome not previously characterized at this resolution. A proteomic clock built from this data accurately predicts chronological age, and peptide-level analysis reveals aging signals invisible at protein-level. These findings demonstrate that EV-enriched plasma proteomics can identify known aging markers, reveal novel sex-specific age-related changes, and generate predictive models of chronological age. This study provides a species-agnostic foundation for proteomic clocks that complement epigenetic approaches to monitor aging and evaluate healthspan.

molecular biology↗

bioRxiv2026

A quantitative proteomics dataset for assessment and prediction of low dose X-ray radiation exposure in mice.

Ionizing radiation induces molecular responses that may be used to estimate exposure when physical dosimeters are unavailable. Here we present two large-scale proteomics datasets generated from mouse dorsal skin punch samples collected following controlled X-ray exposures spanning multiple doses, dose rates, and post-exposure time points. Experiment 1 comprised 96 samples (including 16 reference samples) collected 6 days after exposure to 0-75 cGy delivered at either 30 or 300 cGy/min. Experiment 2 comprised 936 samples (including 236 reference samples) exposed to 0-100 cGy at either 3 or 28 cGy/min dose rates and harvested between 7 and 150 days post-exposure. All samples were processed using a standardized workflow involving automated bead-based digestion and data-independent acquisition mass spectrometry. The datasets include multiple pooled reference sample types, process controls, and system suitability standards ensuring high quality data. All data presented are available via ProteomeXchange at several levels of processing, from raw files through normalized peptide- and protein-level abundance matrices suitable for biomarker discovery and machine learning applications. This dataset will facilitate generation of new insights into the biological changes and molecular signatures resulting from X-ray exposure in mice and may also help inform future studies in humans.

biochemistry↗

bioRxiv2026

Serum proteomics reveals distinct phenotypic signatures to IL-6 blockade between two immunotherapies

A recent clinical study tested the effects of two different monoclonal antibodies (mAbs) (siltuximab, anti-IL6; tocilizumab, anti-IL6R) on the fate and function of T-cells in people with type 1 diabetes. While both mAbs affect the response of T-cells to stimulation, they have very different, sometimes opposing mechanisms. Here, we use mass-spectrometry based proteomics to analyze longitudinal serum samples (baseline and two weeks post-treatment) from 20 clinical trial participants to examine the effects of siltuximab and tocilizumab on extracellular vesicles. To accomplish this, serum samples were enriched for extracellular vesicles with Mag-Net and analyzed by LC-MS/MS to identify significantly differentially abundant protein groups and pathways. Proteome analysis confirmed highly reproducible measurements across multiple draw dates. In total, we quantified >3300 protein groups of which 46 protein groups had significantly altered abundance after mAb treatment. Tocilizumab altered pathways associated with proteostasis (neddylation) and pre-notch transcription and translation. Siltuximab altered FCGR activation pathway members. In addition, quantitation of the monoclonal antibody therapies themselves enabled the measurement of the correlation between drug amounts and impacted proteins. Taken together, this work demonstrates the utility of the Mag-Net method to evaluate the impacts of therapeutic interventions on serum extracellular vesicles.

biochemistry↗

bioRxiv2026

Is Protein Quantification and Physical Normalization Always Necessary in Proteomics?

Dogma suggests protein quantification is a pre-requisite to LC-MS/MS based proteomics studies. Such quantification allows a standardized ratio of sample to digestion enzyme and enables physical normalization of protein digest loaded onto the mass spectrometer for analysis. Most proteomics studies include these steps. However, there are significant costs in time, money and experimental complexity, associated with performing protein quantification and physical normalization for every sample, especially for larger studies. Proteomics data analysis pipelines typically include computational normalization strategies to compensate for unavoidable systematic biases. These strategies also have the potential to compensate for avoidable variation such as omitting sample amount normalization. Here we investigate the effects of either physically normalizing the amount of protein for each individual sample or leaving it unnormalized. Our results show the relationship between increased protein amount variation in sample input, and the variance of quantified relative abundances of peptides and proteins output after data analysis. The experiments presented here suggest that protein quantification and physical normalization steps can be omitted from some quantitative proteomic experiments without incurring an unacceptable increase in measurement variability after computational normalization has been applied. This work will enable important time and cost saving optimizations to be made to many proteomics workflows.

biochemistry↗

bioRxiv2025

Evaluation of an Orbitrap Astral Zoom mass spectrometer prototype for quantitative proteomics - beyond identification lists

Mass spectrometry instrumentation continues to evolve rapidly yet quantifying these advances beyond conventional peptide and protein detections remain challenging. Here, we evaluate a modified Orbitrap Astral Zoom mass spectrometer (MS) prototype and compare its performance to the standard Orbitrap Astral MS. Across a range of acquisition methods and sample inputs, the prototype instrument outperformed the standard Orbitrap Astral MS in precursor and protein identifications, ion beam utilization, and quantitative precision. To enable meaningful cross-platform comparisons, we implemented an ion calibration framework that converts signal intensity from arbitrary units to ion per second. This benchmarking strategy showed that the prototype sampled 30% more ions per peptide than the original Orbitrap Astral MS. This increase in the ion beam utilization resulted in improved sensitivity and quantitative precision. To make these metrics broadly accessible, we added new metrics to the Skyline document grid to report the number of ions measured in a spectrum at the apex of the elution peak or the sum of ions between the peak integration boundaries. Taken together, our results demonstrate the prototype Orbitrap Astral Zoom as a high-performance platform for DIA proteomics and establish a generalizable framework for evaluation of mass spectrometer performance based on the number of ions detected for each analyte. Data are available on Panorama Public and on ProteomeXchange under the identifier PXD064536.

biochemistry↗

bioRxiv2025

The two-step purification method ViREn identifies a single NSUN6-mediated 5-methylcytosine modification promoting dengue virus RNA genome turnover

Chemical modifications on cellular and viral RNAs are new layers of post-transcriptional regulation of cellular processes including RNA stability and translation. Although advances in analytical methods have improved detection sensitivity, the precise mapping of RNA modifications at single-base resolution remains challenging. Especially for low abundant viral RNAs extracted from infected cells, requirements for sensitivity and purity limit accuracy and reproducibility. Here we report the two-step method ViREn for the enrichment of the genomic RNA (gRNA) of dengue virus (DENV), a positive-sense single-stranded RNA virus. This approach enabled the preparation of gRNA with significantly increased purity and led to the identification of a high-confidence 5-methylcytosine (m5C) site in DENV gRNA, orthogonally validated by Illumina-based bisulfite sequencing and direct RNA sequencing by Nanopore Oxford Technologies. Strikingly, this m5C modification was exclusively detected in gRNA extracted from infected cells but not in gRNA extracted from viral particles. We identified NSUN6 as the host methyltransferase catalyzing this modification and demonstrated a role for m5C in regulating DENV gRNA turnover. ViREn thus enables the mapping of m5C on low abundance viral gRNA with unprecedented precision and sensitivity and facilitates mechanistic studies into the role of RNA modification in virus replication.

biochemistry↗

bioRxiv2024

Development of highly multiplex targeted proteomics assays in biofluids using the Stellar mass spectrometer

The development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument. The scale of these assays is achievable with the StellarTM mass spectrometer through the accommodation of shifting retention times by real-time alignment, while being sensitive and fast enough to handle many concurrent targets. Assays were constructed using precursor information from gas-phase fractionated (GPF) data-independent acquisition (DIA). We demonstrate the ability to schedule methods from an orbitrap and linear ion trap acquired GPF DIA library and compare the quantification of a matrix-matched calibration curve from orbitrap DIA and linear ion trap parallel reaction monitoring (PRM). Two applications of these proposed workflows are shown with a cerebrospinal fluid (CSF) neurodegenerative disease protein PRM assay and with a Mag-Net enriched plasma extracellular vesicle (EV) protein survey PRM assay.

biochemistry↗

bioRxiv2024

A transformer model for de novo sequencing of data-independent acquisition mass spectrometry data

A core computational challenge in the analysis of mass spectrometry data is the de novo sequencing problem, in which the generating amino acid sequence is inferred directly from an observed fragmentation spectrum without the use of a sequence database. Recently, deep learning models have made significant advances in de novo sequencing by learning from massive datasets of high-confidence labeled mass spectra. However, these methods are primarily designed for data-dependent acquisition (DDA) experiments. Over the past decade, the field of mass spectrometry has been moving toward using data-independent acquisition (DIA) protocols for the analysis of complex proteomic samples due to their superior specificity and reproducibility. Hence, we present a new de novo sequencing model called Cascadia, which uses a transformer architecture to handle the more complex data generated by DIA protocols. In comparisons with existing approaches for de novo sequencing of DIA data, Cascadia achieves state-of-the-art performance across a range of instruments and experimental protocols. Additionally, we demonstrate Cascadias ability to accurately discover de novo coding variants and peptides from the variable region of antibodies.

bioinformatics↗

bioRxiv2023

Terpenoid balance in Aspergillus nidulans unveiled by heterologous squalene synthase expression

Filamentous fungi produce numerous uncharacterized natural products (NPs) that are often challenging to characterize due to cryptic expression in laboratory conditions. Previously, we have successfully isolated novel NPs by expressing fungal artificial chromosomes (FACs) from a variety of fungal species into Aspergillus nidulans. Here, we demonstrate a new twist to FAC utility wherein heterologous expression of a Pseudogymnoascus destructans FAC in A. nidulans altered endogenous terpene biosynthetic pathways. In contrast to wildtype, the FAC transformant produced increased levels of squalene and aspernidine type compounds, including three new nidulenes (1-2, 5), and lost nearly all ability to synthesize the major A. nidulans characteristic terpene, austinol. Deletion of a squalene synthase gene in the FAC restored wildtype chemical profiles. The altered squalene to farnesyl pyrophosphate ratio leading to synthesis of nidulenes and aspernidines at the expense of farnesyl pyrophosphate derived austinols provides unexpected insight into routes of terpene synthesis in fungi. TeaserReshaping terpenes: Heterologous FAC expression reroutes terpene pathways.

microbiology↗

bioRxiv2023

Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent [~]1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 L plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimers disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinsons disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 {+/-} 0.06.

biochemistry↗

bioRxiv2023

Evaluating the performance of the Astral mass analyzer for quantitative proteomics using data independent acquisition

We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data independent acquisition, the Thermo Scientific Orbitrap Astral mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific Orbitrap mass spectrometers, which have long been the gold standard for high resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high quality quantitative measurements across a wide dynamic range. We also use a newly developed extra-cellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5,000 plasma proteins in a 60-minute gradient with the Orbitrap Astral mass spectrometer.

biochemistry↗

bioRxiv2022

Dynamic Data Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment

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.

bioinformatics↗

bioRxiv2021

Can we put Humpty Dumpty back together again? What does protein quantification mean in bottom-up proteomics?

Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. In bottom-up proteomics, protein parsimony and protein inference derived from these measured peptides are important for determining which protein coding genes are present. However, given the complexity of RNA splicing processes, and how proteins can be modified post-translationally, it is overly simplistic to assume that all peptides that map to a singular protein coding gene will demonstrate the same quantitative response. Accordingly, by assuming all peptides from a protein coding sequence are representative of the same protein we may be missing out on detecting important biological differences. To better account for the complexity of the proteome we need to think of new or better ways of handling peptide data.

biochemistry↗

bioRxiv2018

Human sensory Long-Term Potentiation (LTP) predicts visual memory performance and is modulated by the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism

BackgroundLong-Term Potentiation (LTP) is recognised as a core neuronal process underlying long-term memory. However, a direct relationship between LTP and human memory performance is yet to be demonstrated. The first aim of the current study was thus to assess the relationship between LTP and human long-term memory performance. With this also comes an opportunity to explore factors thought to mediate the relationship between LTP and long-term memory, and to gain additional insight into variations in memory function and memory decline. The second aim of the current study was to explore the relationship between LTP and memory in groups differing with respect to BDNF Val66Met; a single nucleotide polymorphism implicated in memory function.\n\nMethods28 participants (15 female) were split into three genotype groups (Val/Val, Val/Met, Met/Met) and were presented with both an EEG paradigm for inducing LTP-like enhancements of the visually-evoked response, and a test of visual memory.\n\nResultsThe magnitude of LTP 40 minutes after induction was predictive of long-term memory performance. Additionally, the BDNF Met allele was associated with both reduced LTP and reduced memory performance.\n\nConclusionsThe current study not only presents the first evidence for a relationship between sensory LTP and human memory performance, but also demonstrates how targeting this relationship can provide insight into factors implicated in variation in human memory performance. It is anticipated that this will be of utility to future clinical studies of disrupted memory function.

neuroscience↗