Biology subjects

Porse, B. T.

Publications and source records attributed to Porse, B. T..

10 recordsLinked to original sources

bioRxiv2026

Cholesterol Biosynthesis is a Targetable Vulnerability of CEBPA-mutant Acute Myeloid Leukemia

Bi-allelic CEBPA mutations occur in 5-15% of acute myeloid leukemia (AML) patients. The precise molecular consequences of CEBPA mutations, especially in combination with frequently co-occurring mutations in TET2, WT1, and GATA2, remain incompletely understood. Here, we present a robust human model of CEBPA-mutant AML through gene editing of healthy bone marrow-derived hematopoietic stem cells. Loss of the CEBPA-p42 isoform expressed in healthy cells with concomitant upregulation of the leukemic CEBPA-p30 isoform resulted in a myeloproliferative phenotype. Concurrent loss-of-function mutations in TET2 or WT1 drove full leukemic transformation, while GATA2 haploinsufficiency promoted erythroid precursor accumulation without overt AML. Single-cell transcriptomics and low-input proteomics revealed enhanced myeloid output, increased interferon signaling and elevated cholesterol biosynthesis in leukemic cells. Targeting cholesterol synthesis enhanced chemosensitivity, highlighting a potential therapeutic vulnerability, particularly relevant for CEBPA-mutant patients harboring co-mutations in TET2 or WT1, which have poor outcomes. Statement of significanceInduction of CEBPA-p30 by CRISPR/Cas gene editing in healthy human BM HSCs drives overt AML in vivo. TET2 and WT1 loss accelerate leukemogenesis, while GATA2 haploinsufficiency redirects differentiation toward erythroid precursors potentially driving acute erythroid leukemia. CEBPA-p30 AML exhibits cholesterol biosynthesis dependency, revealing a therapeutic vulnerability to statins.

cancer biology↗

bioRxiv2025

Antibody-based signal amplification for single-cell proteomics by mass spectrometry

Single-cell proteomics by mass spectrometry (scp-MS) detects thousands of proteins per cell, yet low-abundant proteins routinely detected by antibody-based methods are challenging to quantify in the single-cell proteome. To address this, we developed antibody peptide tags (AbTags) - MS detectable tandem peptide barcodes coupled to antibodies which provide signal amplification, enable absolute quantification, and are quantified alongside endogenous proteomes by scp-MS. As proof-of-concept, AbTags quantify cytokine-induced PDL1 expression, undetectable by scp-MS.

systems biology↗

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

Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics

Single-cell transcriptomics (scRNA-seq) has enabled the characterization of cell state heterogeneity and recapitulation of differentiation trajectories. However, since proteins are the main functional entities in cells, the exclusive use of mRNA measurements comes at the risk of missing important biological information. Here we leverage recent technological advances in single-cell proteomics by Mass Spectrometry (scp-MS) to generate the first scp-MS dataset of an in vivo differentiation hierarchy encompassing over 2,500 human CD34+ hematopoietic stem and progenitor cells. Through integration with scRNA-seq, we identify proteins that are important for stem cell quiescence, which were not indicated by their mRNA transcripts, and demonstrate functional expression covariance during differentiation that is only detectable on protein level. Finally, we show that modeling translation dynamics can infer cell progression during differentiation and explain 45% more protein variation from mRNA than linear correlation. Our work serves as a framework for future single-cell multi-omics studies across biological systems.

cell biology↗

bioRxiv2024

Unraveling the proteome landscape of mouse hematopoietic stem and progenitor compartment with high sensitivity low-input proteomics

Proteins play a key role in defining cellular phenotypes, yet comprehensive proteomic analysis often requires substantial input material, posing challenges in studying rare populations in complex cell systems. Here, we present an accessible, label-free low-input proteomics workflow that allows for comprehensive proteome coverage reminiscent of classical bulk samples from only 500 cells and showcase its application in murine hematopoiesis. With this approach, we construct a proteomic map of hematopoietic stem and progenitor cell (HSPC) populations isolated by fluorescence-activated cell sorting (FACS) from the bone marrow of a single mouse, identifying approximately 7,000 proteins per cell population. Our study recapitulates the differentiation trajectories along the megakaryocytic-erythroid and granulocytic-monocytic lineages. We specifically focus on the dynamics of transcriptional regulators and provide insights into both known and novel population-specific factors. Furthermore, we extend our exploration to the most primitive stem and progenitor compartment, and identify ADP-Ribosyltransferase ART4 (CD297) as a novel cell surface marker that can potentially be used to enrich for long-term hematopoietic stem cells (LT-HSC). The low-input proteomics workflow presented here holds promise for overcoming the challenges associated with analyzing proteomes of rare cell populations, thereby paving the way for broader applications in biomedical research.

cell 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

TET2 lesions enhance the aggressiveness of CEBPA-mutant AML by rebalancing GATA2 expression

The myeloid transcription factor CEBPA is recurrently biallelically mutated (i.e., double mutated; CEBPADM) in acute myeloid leukemia (AML) with a combination of hypermorphic N-terminal mutations (CEBPANT), promoting expression of the leukemia-associated p30 isoform, and amorphic C-terminal mutations. The most frequently co-mutated genes in CEBPADM AML are GATA2 and TET2, however the molecular mechanisms underlying this co-mutational spectrum are incomplete. By combining transcriptomic and epigenomic analyses of CEBPA-TET2 co-mutated patients with models thereof, we identify GATA2 as a conserved target of the CEBPA-TET2 mutational axis, providing a rationale for the mutational spectra in CEBPADM AML. Elevated CEBPA levels, driven by CEBPANT, mediate recruitment of TET2 to the Gata2 distal hematopoietic enhancer thereby increasing Gata2 expression. Concurrent loss of TET2 in CEBPADM AML induces a competitive advantage by increasing Gata2 promoter methylation, thereby rebalancing GATA2 levels. Of clinical relevance, demethylating treatment of Cebpa-Tet2 co-mutated AML restores Gata2 levels and prolongs disease latency.

cancer biology↗

bioRxiv2022

Enhancing single-cell proteomics through tailored Data-Independent Acquisition and micropillar array-based chromatography

Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, mass spectrometry-based single-cell proteomics (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carried out comprehensive analysis of orbitrap-based data independent acquisition (DIA) for limited material proteomics. Notably, we found a fundamental difference between optimal DIA methods for high- and low-load samples. We further improved our low-input DIA method by relying on high-resolution MS1 quantification, thus more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we were able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we establish a complete experimental scp-MS workflow, combining DIA with accessible single-cell sample preparation and the latest chromatographic and computational advances and showcase our developments by profiling real single cells.

systems biology↗

bioRxiv2021

Real-Time Search Assisted Acquisition on a Tribrid Mass Spectrometer Improves Coverage in Multiplexed Single-Cell Proteomics

In the young field of single-cell proteomics (scMS), there is a great need for improved global proteome characterization, both in terms of proteins quantified per cell and quantitative performance thereof. The recently introduced real-time search (RTS) on the Orbitrap Eclipse Tribrid mass spectrometer in combination with SPS-MS3 acquisition has been shown to be beneficial for the measurement of samples that are multiplexed using isobaric tags. Multiplexed single-cell proteomics requires high ion injection times and high-resolution spectra to quantify the single-cell signal, however the carrier channel facilitates peptide identification and thus offers the opportunity for fast on-the-fly precursor filtering before committing to the time intensive quantification scan. Here, we compared classical MS2 acquisition against RTS-SPS-MS3, both using the Orbitrap Eclipse Tribrid MS with the FAIMS Pro ion mobility interface and present a new acquisition strategy termed RETICLE (RTS Enhanced Quant of Single Cell Spectra) that makes use of fast real-time searched linear ion trap scans to preselect MS1 peptide precursors for quantitative MS2 Orbitrap acquisition. We show that classical MS2 acquisition is outperformed by both RTS-SPS-MS3 through increased quantitative accuracy at similar proteome coverage, and RETICLE through higher proteome coverage, with the latter enabling the quantification of over 1000 proteins per cell at a MS2 injection time of 750ms using a 2h gradient.

biochemistry↗