Biology subjects

Arrey, T. N.

Publications and source records attributed to Arrey, T. N..

13 recordsLinked to original sources

bioRxiv2026

High Resolution Multi-Pass Astral Analyzer Quantification Enables Highly Multiplexed 35-Plex Tandem Mass Tag Proteomics

Tandem mass tags (TMT) allow highly multiplexed and thus high-throughput, precisely quantitative proteomic analysis. Incorporation of additional deuterated reporter channels has near-doubled the multiplexation achieved with Thermo Scientific TMTpro reagents from 18 to 35-plex but requires extremely high [~]100k analyzer resolving power at m/z 128 to differentiate and quantify reporter ion channels, far beyond any single reflection time-of-flight analyzer, and exceeding the multi-reflection Thermo Scientific Astral analyzer in its standard operation. A multi-pass mode of Astral operation has been developed for the Thermo Scientific Orbitrap Astral Zoom mass spectrometer that triples the ion path to 90 m, more than doubling resolving power for a narrow m/z range. This "TMT HR mode" has been integrated into a new method of TMT proteomic analysis that splits regular MS2 analysis of labeled peptides into paired measurements comprising wide mass range scans for peptide identification, and TMT HR mode scans for reporter ion quantification. The method has been shown to accurately quantify 32-plex labeled HeLa protein lysate and provide far greater depth of analysis as state-of-the-art Orbitrap-only methods, while analysis of 11-plex labeled yeast showed no analytical depth sacrificed vs regular Orbitrap Astral TMT analysis. Further comparative measurements of a 2-cell line 35-plex sample demonstrated greater analytical depth, and similar quantitative precision, to "gold standard" Orbitrap MS3 methods.

biochemistry↗

bioRxiv2025

From HeLa to human blood: extending single-cell proteomics to the smallest immune cells

Single-cell proteomics (SCP) holds the promise of decoding cellular heterogeneity at the functional level, yet achieving deep and reproducible proteome coverage from individual cells has remained a formidable challenge. Here, we established a high-sensitivity, label-free SCP platform that surpasses previous limits in depth and reproducibility. By integrating optimized low-input sample processing, refined liquid chromatography, and the Orbitrap Astral Zoom mass spectrometer, our approach routinely quantified over 7,000 proteins per individual HeLa cell, capturing thousands of low-abundance proteins that eluded prior SCP studies. Applied to very small human peripheral blood mononuclear cells (PBMCs), we identified up to 4,000 proteins per cell, including key markers distinguishing monocytes, T cells, and activated lymphocytes within heterogeneous populations, underscoring that single-cell proteomics can now directly elucidate clinically relevant primary samples with both depth and precision.

cell biology↗

bioRxiv2025

Higher-Throughput Proteome Profiling Enabled by Parallelized Pre-Accumulation and Optimized Ion Processing in the Orbitrap Astral Zoom Mass Spectrometer

High-throughput proteomics is critical for understanding biological processes, enabling large-scale studies such as biomarker discovery and systems biology. However, current mass spectrometry technologies face limitations in speed, sensitivity, and scalability for analyzing large sample cohorts. The Thermo Scientific Orbitrap Astral Zoom mass spectrometer (MS) was developed to address these limitations by improving acquisition speed, ion utilization, and spectral processing, which are all essential for advancing proteome depth in high-throughput proteomics. The Orbitrap Astral Zoom MS achieves ultra-fast MS/MS scan rates of up to 270 Hz with enhanced ion utilization through pre-accumulation, enabling the identification of [~]100,000 unique peptides and >8,400 proteins in a single 300 samples-per-day (SPD) analysis of human cell lysate. The optimized system reduces analysis time by 40%, achieves near-complete proteome coverage (>12,000 proteins) in 2.7 hours, and enables ultra-high-throughput workflows, identifying >7,000 proteins in a 500 SPD method with exceptional reproducibility (Pairwise Pearson correlations >0.99). These advancements establish the Orbitrap Astral Zoom MS as a new benchmark in proteomics, significantly enhancing speed, sensitivity, and scalability, paving the way for routine large-scale proteome studies with applications in clinical research and systems biology. TeaserHigh-Speed Human Proteome Analysis using the Orbitrap Astral Zoom Mass Spectrometer

biochemistry↗

bioRxiv2025

Informed Data-Independent Acquisition Enables Targeted Quantification of Key Regulatory Proteins in Cell Fate Decision at Single-Cell Resolution

Low-abundance regulatory proteins, including transcription factors (TFs), remain largely inaccessible to direct quantification in single cells despite their central roles in cellular state transitions. Although single-cell proteomics by mass spectrometry (scp-MS) enables broad proteome profiling, current approaches often lack the sensitivity required to quantify these regulators at the protein level robustly. Here, we present informed data-independent acquisition (iDIA), a cross-instrument MS acquisition framework combining sensitive targeted measurements with global proteome profiling of the same cell. Thereby, iDIA significantly improves the sensitivity for predefined regulatory proteins, while preserving global proteome coverage. Applied to hematopoietic stem and progenitor cells, iDIA quantified 12 lineage-associated TFs, including GATA1 and SPI1, alongside the global proteome from single cells. Integrated analysis reconstructed the differentiation hierarchy and revealed protein-level states of early granulocytic-monocytic lineage priming and coordinated changes between erythroid TF abundance and cell-cycle progression. Thus, iDIA opens scp-MS to the regulatory architecture of cell state transitions.

systems biology↗

bioRxiv2024

Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS

Single-cell proteomics by mass spectrometry (scp-MS) holds the potential to provide unprecedented insights into molecular features directly linked to the cellular phenotype, while deconvoluting complex organisms into their basic building blocks. Tailored sample preparation that maximizes the extracted amount of material that is introduced into the mass spectrometer has rapidly propelled the field forward. However, the measured signal is still at the lower edge of detection approaching the sensitivity boundary of current instrumentation. Here, we investigate the capacity of the enhanced sensitivity of the Orbitrap Astral mass spectrometer to facilitate deeper proteome profiles from low-input to single-cell samples. We carry out a comprehensive data acquisition method survey to pinpoint which parameters provide most sensitivity. Furthermore, we explore the quantitative accuracy of the obtained measurements to ensure that the obtained abundances are in line with expected ground truth values. We culminate our technical exploration by generating small datasets from two cultured cell lines and a primary bone marrow sample, to showcase obtainable proteome coverage differences from different source materials. Finally, as a proof of concept we explore protein covariation to showcase how information on known protein complexes is captured inherently in our scp-MS data.

biochemistry↗

bioRxiv2024

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap Astral MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

biochemistry↗

bioRxiv2024

Challenging the Astral mass analyzer - going beyond 5200 proteins per single-cell at unseen quantitative accuracy to study cellular heterogeneity.

A detailed proteome map is crucial for understanding molecular pathways and protein functions. Despite significant advancements in sample preparation, instrumentation, and data analysis, single-cell proteomics is currently limited by proteomic depth and quantitative performance. We combine a zero dead-end volume chromatographic column running at high throughput with the Thermo Scientific Orbitrap Astral mass spectrometer running in DIA mode. We demonstrate unprecedented depth of proteome coverage as well as accuracy and precision for quantification of ultra-low input amounts. Using a tailored library, we identify up to 7400 protein groups from as little as 250 pg HeLa at a throughput of 50 samples per day (SPD). We benchmark multiple data analysis strategies, estimate their influence on FDR and show that FDR on protein level can easily be maintained at 1 %. Using a two-proteome mix, we check for optimal parameters of quantification and show that fold change differences of 2 can still be successfully determined at single-cell level inputs. Eventually, we apply our workflow to A549 cells yielding a proteome coverage of up to 5300 protein groups from a single cell, which allows the observation of heterogeneity in a cellular population and studying dependencies between cell size and cell-cycle phase. Additionally, our work-flow enables us to distinguish between in vitro analogs of two human blastocyst lineages: naive human pluripotent stem cells (epiblast) and trophectoderm (TE)-like cells. Gene Ontology analysis of enriched proteins in TE-like cells harmoniously aligns with transcriptomic data, indicating that single-cell proteomics possesses the capability to identify biologically relevant differences between these two lineages within the blastocyst.

biochemistry↗

bioRxiv2023

One-Hour Phosphoproteome Analysis with the Orbitrap Astral Mass Spectrometer

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology was benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We applied this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detected 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of novel phosphorylation events relevant to mitochondrial and brain biology.

systems biology↗

bioRxiv2023

Evaluating the capabilities of the Astral mass analyzer for single-cell proteomics

The complexity of human physiology arises from well-orchestrated interactions between trillions of single cells in the body. While single-cell RNA sequencing (scRNA-seq) has enhanced our understanding of cell diversity, gene expression alone does not fully characterize cell phenotypes. Additional molecular dimensions, such as proteins, are needed to define cellular states accurately. Mass spectrometry (MS)-based proteomics has emerged as a powerful tool for comprehensive protein analysis, including single-cell applications. However, challenges remain in terms of throughput and proteomic depth, in order to maximize the biological impact of single-cell proteomics by Mass Spectrometry (scp-MS) workflows. This study leverages a novel high-resolution, accurate mass (HRAM) instrument platform, consisting of both an Orbitrap and an innovative HRAM Asymmetric Track Lossless (Astral) analyzer. The Astral analyzer offers high sensitivity and resolution through lossless ion transfer and a unique flight track design. We evaluate the performance of the Thermo Scientific Orbitrap Astral MS using Data-Independent Acquisition (DIA) and assess proteome depth and quantitative precision for ultra-low input samples. Optimal DIA method parameters for single-cell proteomics are identified, and we demonstrate the ability of the instrument to study cell cycle dynamics in Human Embryonic Kidney (HEK293) cells, and cancer cell heterogeneity in a primary Acute Myeloid Leukemia (AML) culture model.

systems biology↗

bioRxiv2023

Narrow-window DIA: Ultra-fast quantitative analysis of comprehensive proteomes with high sequencing depth

Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here, we present an ultra-fast scanning data-independent acquisition (DIA) strategy consisting on 2-Th precursor isolation windows, dissolving the differences between data-dependent and independent methods. This is achieved by pairing a Quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer that provides >200 Hz MS/MS scanning speed, high resolving power and sensitivity, as well as low ppm-mass accuracy. Narrow-window DIA enables profiling of up to 100 full yeast proteomes per day, or [~]10,000 human proteins in half-an-hour. Moreover, multi-shot acquisition of fractionated samples allows comprehensive coverage of human proteomes in [~]3h, showing comparable depth to next-generation RNA sequencing and with 10x higher throughput compared to current state-of-the-art MS. High quantitative precision and accuracy is demonstrated with high peptide coverage in a 3-species proteome mixture, quantifying 14,000+ proteins in a single run in half-an-hour. TeaserAccurate and precise label-free quantification with comprehensive proteome coverage using narrow-window DIA

systems biology↗

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↗

bioRxiv2019

A Compact Quadrupole-Orbitrap Mass Spectrometer with FAIMS Interface Improves Proteome Coverage in Short LC Gradients

State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 unique peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 minute LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.

biochemistry↗

bioRxiv2019

Fast and accurate bacterial species identification in biological samples using LC-MS/MS mass spectrometry and machine learning

The identification of microbial species in biological samples is essential to many applications in health, food safety and environment. MALDI-TOF MS technology has become a tool of choice for microbial identification but it has several drawbacks including: it requires a long step of bacterial culture prior to analysis (24h), it has a low specificity and is not quantitative. We have developed a new strategy for identifying bacterial species in biological samples using specific LC-MS/MS peptidic signatures. In the first training step, deep proteome coverage of bacteria of interest is obtained in Data Independent Acquisition (DIA) mode, followed by the use of machine learning to define the peptides the most susceptible to distinguish each bacterial species from the others. Then, in the second step, this peptidic signature is monitored in biological samples using targeted proteomics. This method, which allows the bacterial identification from clinical specimens in less than 4h, has been applied to fifteen species representing 84% of all Urinary Tract Infections (UTI). More than 31000 peptides in 200 samples have been quantified by DIA and analyzed by machine learning to determine an 82 peptides signature and build prediction models able to classify the fifteen bacterial species. This peptidic signature was validated for its use in routine conditions using Parallel Reaction Monitoring on a capillary flow chromatography coupled to a Thermo Scientific Q Exactive HF-X instrument. Linearity and reproducibility of the method were demonstrated as well as its accuracy on donor specimens. Within 4h and without bacterial culture, our method was able to predict the predominant bacteria infecting a sample in 97% of cases and 100% above the 1x105 CFU/mL threshold commonly used by clinical laboratories. This work demonstrates the efficiency of our method for the rapid and specific identification of the bacterial species causing UTI and could be extended in the future to other biological specimens and to bacteria having specific virulence or resistance factors.

microbiology↗