CLIPPER 2.0: Peptide level annotation and data analysis for positional proteomics.

Positional proteomics methodologies have transformed protease research, and have brought mass spectrometry (MS)-based degradomics studies to the forefront of protease characterization and system-wide interrogation of protease signaling. Considerable advancements in both sensitivity and throughput of liquid chromatography (LC)-MS/MS instrumentation enable the generation of enormous positional proteomics datasets of natural and protein termini and neo-termini of cleaved protease substrates. However, a concomitant progress has not been observed to the same extent in data analysis and post-processing steps, arguably constituting the largest bottleneck in positional proteomics workflows. Here, we present a computational tool, CLIPPER 2.0, that builds on prior algorithms developed for MS-based protein termini analysis, facilitating peptide level annotation and data analysis. CLIPPER 2.0 can be used with several sample preparation workflows and proteomics search algorithms, and enables fast and automated database information retrieval, statistical and network analysis, as well as visualization of terminomic datasets. We demonstrate the applicability of our tool by analyzing GluC and MMP9 cleavages in HeLa lysates. CLIPPER 2.0 is available at https://github.com/UadKLab/CLIPPER-2.0.

Lipid levels correlate with neuronal and dopaminergic markers during the differentiation of SH-SY5Y cells.

Parkinson's Disease (PD) is characterised by the loss of dopaminergic neurons and the deposition of protein inclusions called Lewy Bodies (LBs). LBs are heterogeneous structures composed of protein and lipid molecules and their main constituent is the presynaptic protein α-synuclein. SH-SY5Y cells are neuroblastoma cells commonly used to model PD because they express dopaminergic markers and α-synuclein and they can be differentiated into neuronal cells using established protocols. Despite increasing evidence pointing towards a role of lipids in PD, limited knowledge is available on the lipidome of undifferentiated and differentiated SH-SY5Y cells. Using a combination of lipidomics, proteomics, morphological and electrophysiological measurements, we identified specific lipids, including sphingolipids, whose levels are affected by the differentiation of SH-SY5Y neuroblastoma cells and found that the levels of these lipids correlate with those of neuronal and dopaminergic markers. These results provide a quantitative characterisation of the changes in lipidome associated with the differentiation of SH-SY5Y cells into more neuronal and dopaminergic-like phenotype and serve as a basis for further characterisation of lipid disruptions in association with PD and its risk factors in this dopaminergic-like neuronal cell model.

A proteomics-based survey reveals thrombospondin-4 as a ligand regulated by the mannose receptor in the injured lung.

Receptor-mediated cellular uptake of specific ligands constitutes an important step in the dynamic regulation of individual protein levels in extracellular fluids. With a focus on the inflammatory lung, we here performed a proteomics-based search for novel ligands regulated by the mannose receptor (MR), a macrophage-expressed endocytic receptor. WT and MR-deficient mice were exposed to lipopolysaccharide, after which the protein content in their lung epithelial lining fluid was compared by tandem mass tag-based mass spectrometry. More than 1200 proteins were identified in the epithelial lining fluid using this unbiased approach, but only six showed a statistically different abundance. Among these, an unexpected potential new ligand, thrombospondin-4 (TSP-4), displayed a striking 17-fold increased abundance in the MR-deficient mice. Experiments using exogenous addition of TSP-4 to MR-transfected CHO cells or MR-positive alveolar macrophages confirmed that TSP-4 is a ligand for MR-dependent endocytosis. Similar studies revealed that the molecular interaction with TSP-4 depends on both the lectin activity and the fibronectin type-II domain of MR and that a closely related member of the TSP family, TSP-5, is also efficiently internalized by the receptor. This was unlike the other members of this protein family, including TSPs -1 and -2, which are ligands for a close MR homologue known as urokinase plasminogen activator receptor-associated protein. Our study shows that MR takes part in the regulation of TSP-4, an important inflammatory component in the injured lung, and that two closely related endocytic receptors, expressed on different cell types, undertake the selective endocytosis of distinct members of the TSP family.

Evidence for an RNAi-independent role of Arabidopsis DICER-LIKE2 in growth inhibition and basal antiviral resistance.

Flowering plant genomes encode four or five DICER-LIKE (DCL) enzymes that produce small interfering RNAs (siRNAs) and microRNAs which function in RNA interference (RNAi). Different RNAi pathways in plants effect transposon silencing, antiviral defense and endogenous gene regulation. DCL2 acts genetically redundantly with DCL4 to confer basal antiviral defense. However, DCL2 may also counteract DCL4, since knockout of DCL4 causes growth defects that are suppressed by DCL2 inactivation. Current models maintain that RNAi via DCL2-dependent siRNAs is the biochemical basis of both effects. Here, we report that DCL2-mediated antiviral resistance and growth defects cannot be explained by the silencing effects of DCL2-dependent siRNAs. Both functions are defective in genetic backgrounds that maintain high levels of DCL2-dependent siRNAs, either with specific point mutations in DCL2 or with reduced DCL2 dosage because of heterozygosity for dcl2 knockout alleles. Intriguingly, all DCL2 functions require its catalytic activity, and the penetrance of DCL2-dependent growth phenotypes in dcl4 mutants correlates with DCL2 protein levels, but not with levels of major DCL2-dependent siRNAs. We discuss this requirement and correlation with catalytic activity, but not with resulting siRNAs, in light of other findings that reveal a DCL2 function in innate immunity activation triggered by cytoplasmic double-stranded RNA.

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.

Loss of the KN Motif and AnKyrin Repeat Domain 1 (KANK1) Leads to Lymphoid Compartment Dysregulation in Murine Model.

The KN Motif and AnKyrin Repeat Domain 1 (KANK1) is proposed as a tumour suppressor gene, as its expression is reduced or absent in several types of tumour tissue, and over-expressing the protein inhibited the proliferation of tumour cells in solid cancer models. We report a novel germline loss of heterozygosity mutation encompassing the KANK1 gene in a young patient diagnosed with myelodysplastic neoplasm (MDS) with no additional disease-related genomic aberrations. To study the potential role of KANK1 in haematopoiesis, we generated a new transgenic mouse model with a confirmed loss of KANK1 expression. KANK1 knockout mice did not develop any haematological abnormalities; however, the loss of its expression led to alteration in the colony forming and proliferative potential of bone marrow (BM) cells and a decrease in hematopoietic stem and progenitor cells (HSPCs) population frequency. A comprehensive marker expression analysis of lineage cell populations indicated a role for Kank1 in lymphoid cell development, and total protein analysis suggests the involvement of Kank1 in BM cells' cytoskeleton formation and mobility.

Hunting for the elusive target antigen in gestational alloimmune liver disease (GALD).

The prevailing concept is that gestational alloimmune liver disease (GALD) is caused by maternal antibodies targeting a currently unknown antigen on the liver of the fetus. This leads to deposition of complement on the fetal hepatocytes and death of the fetal hepatocytes and extensive liver injury. In many cases, the newborn dies. In subsequent pregnancies early treatment of the woman with intravenous immunoglobulin can be instituted, and the prognosis for the fetus will be excellent. Without treatment the prognosis can be severe. Crucial improvements of diagnosis require identification of the target antigen. For this identification, this work was based on two hypotheses: 1. The GALD antigen is exclusively expressed in the fetal liver during normal fetal life in all pregnancies; 2. The GALD antigen is an alloantigen expressed in the fetal liver with the woman being homozygous for the minor allele and the father being, most frequently, homozygous for the major allele. We used three different experimental approaches to identify the liver target antigen of maternal antibodies from women who had given birth to a baby with the clinical GALD diagnosis: 1. Immunoprecipitation of antigens from either a human liver cell line or human fetal livers by immunoprecipitation with maternal antibodies followed by mass spectrometry analysis of captured antigens; 2. Construction of a cDNA expression library from human fetal liver mRNA and screening about 1.3 million recombinants in Escherichia coli using antibodies from mothers of babies diagnosed with GALD; 3. Exome/genome sequencing of DNA from 26 presumably unrelated women who had previously given birth to a child with GALD with husband controls and supplementary HLA typing. In conclusion, using the three experimental approaches we did not identify the GALD target antigen and the exome/genome sequencing results did not support the hypothesis that the GALD antigen is an alloantigen, but the results do not yield basis for excluding that the antigen is exclusively expressed during fetal life., which is the hypothesis we favor.

TET2 lesions enhance the aggressiveness of CEBPA-mutant acute myeloid leukemia 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.

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.

Fibroblast-derived matrix models desmoplastic properties and forms a prognostic signature in cancer progression.

The desmoplastic reaction observed in many cancers is a hallmark of disease progression and prognosis, particularly in breast and pancreatic cancer. Stromal-derived extracellular matrix (ECM) is significantly altered in desmoplasia, and as such plays a critical role in driving cancer progression. Using fibroblast-derived matrices (FDMs), we show that cancer cells have increased growth on cancer associated FDMs, when compared to FDMs derived from non-malignant tissue (normal) fibroblasts. We assess the changes in ECM characteristics from normal to cancer-associated stroma at the primary tumor site. Compositional, structural, and mechanical analyses reveal significant differences, with an increase in abundance of core ECM proteins, coupled with an increase in stiffness and density in cancer-associated FDMs. From compositional changes of FDM, we derived a 36-ECM protein signature, which we show matches in large part with the changes in pancreatic ductal adenocarcinoma (PDAC) tumor and metastases progression. Additionally, this signature also matches at the transcriptomic level in multiple cancer types in patients, prognostic of their survival. Together, our results show relevance of FDMs for cancer modelling and identification of desmoplastic ECM components for further mechanistic studies.

Assessing the Role of Trypsin in Quantitative Plasma and Single-Cell Proteomics toward Clinical Application.

Mass spectrometry-based bottom-up proteomics is rapidly evolving and routinely applied in large-scale biomedical studies. Proteases are a central component of every bottom-up proteomics experiment, digesting proteins into peptides. Trypsin has been the most widely applied protease in proteomics due to its characteristics. With ever-larger cohort sizes and possible future clinical application of mass spectrometry-based proteomics, the technical impact of trypsin becomes increasingly relevant. To assess possible biases introduced by trypsin digestion, we evaluated the impact of eight commercially available trypsins in a variety of bottom-up proteomics experiments and across a range of protease concentrations and storage times. To investigate the universal impact of these technical attributes, we included bulk HeLa cell lysate, human plasma, and single HEK293 cells, which were analyzed over a range of selected reaction monitoring (SRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) instrument methods on three LC-MS instruments. The quantification methods employed encompassed both label-free approaches and absolute quantification utilizing spike-in heavy-labeled recombinant protein fragment standards. Based on this extensive data set, we report variations between commercial trypsins, their source, and their concentration. Furthermore, we provide suggestions on the handling of trypsin in large-scale studies.

Optimizing Linear Ion-Trap Data-Independent Acquisition toward Single-Cell Proteomics.

A linear ion trap (LIT) is an affordable, robust mass spectrometer that provides fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry (MS) measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on the column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.

Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .

Optimizing linear ion trap data independent acquisition towards single cell proteomics.

A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

Temporal phosphoproteomics reveals WEE1-dependent control of 53BP1 pathway.

Wee1-like protein kinase (WEE1) restrains activities of cyclin-dependent kinases (CDKs) in S and G2 phase. Inhibition of WEE1 evokes drastic increase in CDK activity, which perturbs replication dynamics and compromises cell cycle checkpoints. Notably, WEE1 inhibitors such as adavosertib are tested in cancer treatment trials; however, WEE1-regulated phosphoproteomes and their dynamics have not been systematically investigated. In this study, we identified acute time-resolved alterations in the cellular phosphoproteome following WEE1 inhibition with adavosertib. These treatments acutely elevated CDK activities with distinct phosphorylation dynamics revealing more than 600 potential uncharacterized CDK sites. Moreover, we identified a major role for WEE1 in controlling CDK-dependent phosphorylation of multiple clustered sites in the key DNA repair factors MDC1, 53BP1, and RIF1. Functional analysis revealed that WEE1 fine-tunes CDK activities to permit recruitment of 53BP1 to chromatin. Thus, our findings uncover WEE1-controlled targets and pathways with translational potential for the clinical application of WEE1 inhibitors.

Tropodithietic Acid, a Multifunctional Antimicrobial, Facilitates Adaption and Colonization of the Producer, Phaeobacter piscinae.

In the marine environment, surface-associated bacteria often produce an array of antimicrobial secondary metabolites, which have predominantly been perceived as competition molecules. However, they may also affect other hallmarks of surface-associated living, such as motility and biofilm formation. Here, we investigate the ecological significance of an antibiotic secondary metabolite, tropodithietic acid (TDA), in the producing bacterium, Phaeobacter piscinae S26. We constructed a markerless in-frame deletion mutant deficient in TDA biosynthesis, S26ΔtdaB. Molecular networking demonstrated that other chemical sulfur-containing features, likely related to TDA, were also altered in the secondary metabolome. We found several changes in the physiology of the TDA-deficient mutant, ΔtdaB, compared to the wild type. Growth of the two strains was similar; however, ΔtdaB cells were shorter and more motile. Transcriptome and proteome profiling revealed an increase in gene expression and protein abundance related to a type IV secretion system, and to a prophage, and a gene transfer agent in ΔtdaB. All these systems may contribute to horizontal gene transfer (HGT), which may facilitate adaptation to novel niches. We speculate that once a TDA-producing population has been established in a new niche, the accumulation of TDA acts as a signal of successful colonization, prompting a switch to a sessile lifestyle. This would lead to a decrease in motility and the rate of HGT, while filamentous cells could form the base of a biofilm. In addition, the antibiotic properties of TDA may inhibit invading competing microorganisms. This points to a role of TDA in coordinating colonization and adaptation. IMPORTANCE Despite the broad clinical usage of microbial secondary metabolites with antibiotic activity, little is known about their role in natural microbiomes. Here, we studied the effect of production of the antibiotic tropodithietic acid (TDA) on the producing strain, Phaeobacter piscinae S26, a member of the Roseobacter group. We show that TDA affects several phenotypes of the producing strain, including motility, cell morphology, metal metabolism, and three horizontal gene transfer systems: a prophage, a type IV secretion system, and a gene transfer agent. Together, this indicates that TDA participates in coordinating the colonization process of the producer. TDA is thus an example of a multifunctional secondary metabolite that can mediate complex interactions in microbial communities. This work broadens our understanding of the ecological role that secondary metabolites have in microbial community dynamics.

Recent advances in the field of single-cell proteomics.

The field of single-cell omics is rapidly progressing. Although DNA and RNA sequencing-based methods have dominated the field to date, global proteome profiling has also entered the main stage. Single-cell proteomics was facilitated by advancements in different aspects of mass spectrometry (MS)-based proteomics, such as instrument design, sample preparation, chromatography and ion mobility. Single-cell proteomics by mass spectrometry (scp-MS) has moved beyond being a mere technical development, and is now able to deliver actual biological application and has been successfully applied to characterize different cell states. Here, we review some key developments of scp-MS, provide a background to the field, discuss the various available methods and foresee possible future directions.

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.

Longitudinal Evaluation of Biomarkers in Wound Fluids from Venous Leg Ulcers and Split-thickness Skin Graft Donor Site Wounds Treated with a Protease-modulating Wound Dressing.

Venous leg ulcers represent a clinical challenge and impair the quality of life of patients. This study examines impaired wound healing in venous leg ulcers at the molecular level. Protein expression patterns for biomarkers were analysed in venous leg ulcer wound fluids from 57 patients treated with a protease-modulating polyacrylate wound dressing for 12 weeks, and compared with exudates from 10 acute split-thickness wounds. Wound healing improved in the venous leg ulcer wounds: 61.4% of the 57 patients with venous leg ulcer achieved a relative wound area reduction of ≥ 40%, and 50.9% of the total 57 patients achieved a relative wound area reduction of ≥ 60%. Within the first 14 days, abundances of S100A8, S100A9, neutrophil elastase, matrix metalloproteinase-2, and fibronectin in venous leg ulcer exudates decreased significantly and remained stable, yet higher than in acute wounds. Interleukin-1ß, tumour necrosis factor alpha, and matrix metalloproteinase-9 abundance ranges were similar in venous leg ulcers and acute wound fluids. Collagen (I) α1 abundance was higher in venous leg ulcer wound fluids and was not significantly regulated. Overall, significant biomarker changes occurred in the first 14 days before a clinically robust healing response in the venous leg ulcer cohort.