BloodSpot 3.0: a database of gene and protein expression data in normal and malignant haematopoiesis.

BloodSpot is a specialised database integrating gene expression data from acute myeloid leukaemia (AML) patients related to blood cell development and maturation. The database and interface has helped numerous researchers and clinicians to quickly get an overview of gene expression patterns in healthy and malignant haematopoiesis. Here, we present an update to our framework that includes protein expression data of sorted single cells. With this update we also introduce datasets broadly spanning age groups, which many users have requested, with particular interest for researchers studying paediatric leukaemias. The backend of the database has been rewritten and migrated to a cloud-based environment to accommodate the growth, and provide a better user-experience for our many international users. Users can now enjoy faster transfer speeds and a more responsive interface. In conclusion, the continuing popularity of the database and emergence of new data modalities has prompted us to rewrite and futureproof the back-end, including paediatric centric views, as well as single cell protein data, allowing us to keep the database updated and relevant for the years to come. The database is freely available at www.bloodspot.eu.

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 scMS 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 an MS2 injection time of 750 ms using a 2 h gradient.

High Sensitivity Limited Material Proteomics Empowered by Data-Independent Acquisition on Linear Ion Traps.

In recent years, the concept of cell heterogeneity in biology has gained increasing attention, concomitant with a push toward technologies capable of resolving such biological complexity at the molecular level. For single-cell proteomics using Mass Spectrometry (scMS) and low-input proteomics experiments, the sensitivity of an orbitrap mass analyzer can sometimes be limiting. Therefore, low-input proteomics and scMS could benefit from linear ion traps, which provide faster scanning speeds and higher sensitivity than an orbitrap mass analyzer, however at the cost of resolution. We optimized an acquisition method that combines the orbitrap and linear ion trap, as implemented on a tribrid instrument, while taking advantage of the high-field asymmetric waveform ion mobility spectrometry (FAIMS) pro interface, with a prime focus on low-input applications. First, we compared the performance of orbitrap- versus linear ion trap mass analyzers. Subsequently, we optimized critical method parameters for low-input measurement by data-independent acquisition on the linear ion trap mass analyzer. We conclude that linear ion traps mass analyzers combined with FAIMS and Whisper flow chromatography are well-tailored for low-input proteomics experiments, and can simultaneously increase the throughput and sensitivity of large-scale proteomics experiments where limited material is available, such as clinical samples and cellular subpopulations.

Basement membrane stiffness determines metastases formation.

The basement membrane (BM) is a special type of extracellular matrix and presents the major barrier cancer cells have to overcome multiple times to form metastases. Here we show that BM stiffness is a major determinant of metastases formation in several tissues and identify netrin-4 (Net4) as a key regulator of BM stiffness. Mechanistically, our biophysical and functional analyses in combination with mathematical simulations show that Net4 softens the mechanical properties of native BMs by opening laminin node complexes, decreasing cancer cell potential to transmigrate this barrier despite creating bigger pores. Our results therefore reveal that BM stiffness is dominant over pore size, and that the mechanical properties of 'normal' BMs determine metastases formation and patient survival independent of cancer-mediated alterations. Thus, identifying individual Net4 protein levels within native BMs in major metastatic organs may have the potential to define patient survival even before tumour formation. The ratio of Net4 to laminin molecules determines BM stiffness, such that the more Net4, the softer the BM, thereby decreasing cancer cell invasion activity.

Adaptive Laboratory Evolution Restores Solvent Tolerance in Plasmid-Cured Pseudomonas putida S12: a Molecular Analysis.

Pseudomonas putida S12 is inherently solvent tolerant and constitutes a promising platform for biobased production of aromatic compounds and biopolymers. The megaplasmid pTTS12 of P. putida S12 carries several gene clusters involved in solvent tolerance, and the removal of this megaplasmid caused a significant reduction in solvent tolerance. In this study, we succeeded in restoring solvent tolerance in plasmid-cured P. putida S12 using adaptive laboratory evolution (ALE), underscoring the innate solvent tolerance of this strain. Whole-genome sequencing identified several single nucleotide polymorphisms (SNPs) and a mobile element insertion enabling ALE-derived strains to survive and sustain growth in the presence of a high toluene concentration (10% [vol/vol]). We identified mutations in an RND efflux pump regulator, arpR, that resulted in constitutive upregulation of the multifunctional efflux pump ArpABC. SNPs were also found in the intergenic region and subunits of ATP synthase, RNA polymerase subunit ß', a global two-component regulatory system (GacA/GacS), and a putative AraC family transcriptional regulator, Afr. Transcriptomic analysis further revealed a constitutive downregulation of energy-consuming activities in ALE-derived strains, such as flagellar assembly, FoF1 ATP synthase, and membrane transport proteins. In summary, constitutive expression of a solvent extrusion pump in combination with high metabolic flexibility enabled the restoration of the solvent tolerance trait in P. putida S12 lacking its megaplasmid.IMPORTANCE Sustainable production of high-value chemicals can be achieved by bacterial biocatalysis. However, bioproduction of biopolymers and aromatic compounds may exert stress on the microbial production host and limit the resulting yield. Having a solvent tolerance trait is highly advantageous for microbial hosts used in the biobased production of aromatics. The presence of a megaplasmid has been linked to the solvent tolerance trait of Pseudomonas putida; however, the extent of innate, intrinsic solvent tolerance in this bacterium remained unclear. Using adaptive laboratory evolution, we successfully adapted the plasmid-cured P. putida S12 strain to regain its solvent tolerance. Through these adapted strains, we began to clarify the causes, origins, limitations, and trade-offs of the intrinsic solvent tolerance in P. putida This work sheds light on the possible genetic engineering targets to enhance solvent tolerance in Pseudomonas putida as well as other bacteria.

Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition.

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, single-cell proteomics by Mass Spectrometry (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 carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.

Transcription factor-driven coordination of cell cycle exit and lineage-specification in vivo during granulocytic differentiation : In memoriam Professor Niels Borregaard.

Differentiation of multipotent stem cells into mature cells is fundamental for development and homeostasis of mammalian tissues, and requires the coordinated induction of lineage-specific transcriptional programs and cell cycle withdrawal. To understand the underlying regulatory mechanisms of this fundamental process, we investigated how the tissue-specific transcription factors, CEBPA and CEBPE, coordinate cell cycle exit and lineage-specification in vivo during granulocytic differentiation. We demonstrate that CEBPA promotes lineage-specification by launching an enhancer-primed differentiation program and direct activation of CEBPE expression. Subsequently, CEBPE confers promoter-driven cell cycle exit by sequential repression of MYC target gene expression at the G1/S transition and E2F-meditated G2/M gene expression, as well as by the up-regulation of Cdk1/2/4 inhibitors. Following cell cycle exit, CEBPE unleashes the CEBPA-primed differentiation program to generate mature granulocytes. These findings highlight how tissue-specific transcription factors coordinate cell cycle exit with differentiation through the use of distinct gene regulatory elements.

Quantitative single-cell proteomics as a tool to characterize cellular hierarchies.

Large-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses. By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying ~1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we develop a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a foundation for implementing global single-cell proteomics studies across the world.

Mapping Physiological ADP-Ribosylation Using Activated Ion Electron Transfer Dissociation.

ADP-ribosylation (ADPr) is a post-translational modification that plays pivotal roles in a wide range of cellular processes. Mass spectrometry (MS)-based analysis of ADPr under physiological conditions, without relying on genetic or chemical perturbation, has been hindered by technical limitations. Here, we describe the applicability of activated ion electron transfer dissociation (AI-ETD) for MS-based proteomics analysis of physiological ADPr using our unbiased Af1521 enrichment strategy. To benchmark AI-ETD, we profile 9,000 ADPr peptides mapping to >5,000 unique ADPr sites from a limited number of cells exposed to oxidative stress and identify 120% and 28% more ADPr peptides compared to contemporary strategies using ETD and electron-transfer higher-energy collisional dissociation (EThcD), respectively. Under physiological conditions, AI-ETD identifies 450 ADPr sites on low-abundant proteins, including in vivo cysteine modifications on poly(ADP-ribosyl)polymerase (PARP) 8 and tyrosine modifications on PARP14, hinting at specialist enzymatic functions for these enzymes. Collectively, our data provide insights into the physiological regulation of ADPr.