Optimizing Spectronaut Search Parameters to Improve Data Quality with Minimal Proteome Coverage Reductions in DIA Analyses of Heterogeneous Samples.

Data-independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimized to minimize the occurrence of false positives across different samples. Using an immunological infection model system to demonstrate the impact of adjusting search settings, we analyzed Mus musculus macrophages and compared their proteome to macrophages spiked withCandida albicans. This experimental system enabled the identification of "false positives" as Candida albicans peptides and proteins should not be present in the Mus musculus-only samples. We show that adjusting the search parameters reduced "false positive" identifications by 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimized parameters incurred a moderate cost, only reducing the overall number of "true positive" identifications across each biological replicate by <6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any DIA experiment analyzing heterogeneous populations of cell types or tissues.

Quantitative proteomics reveals tissue-specific, infection-induced and species-specific neutrophil protein signatures.

Neutrophils are one of the first responders to infection and are a key component of the innate immune system through their ability to phagocytose and kill invading pathogens, secrete antimicrobial molecules and produce extracellular traps. Neutrophils are produced in the bone marrow, circulate within the blood and upon immune challenge migrate to the site of infection. We wanted to understand whether this transition shapes the mouse neutrophil protein landscape, how the mouse neutrophil proteome is impacted by systemic infection and perform a comparative analysis of human and mouse neutrophils. Using quantitative mass spectrometry we reveal tissue-specific, infection-induced and species-specific neutrophil protein signatures. We show a high degree of proteomic conservation between mouse bone marrow, blood and peritoneal neutrophils, but also identify key differences in the molecules that these cells express for sensing and responding to their environment. Systemic infection triggers a change in the bone marrow neutrophil population with considerable impact on the core machinery for protein synthesis and DNA replication along with environmental sensors. We also reveal profound differences in mouse and human blood neutrophils, particularly their granule contents. Our proteomics data provides a valuable resource for understanding neutrophil function and phenotypes across species and model systems.

Extensive acute and sustained changes to neutrophil proteomes post-SARS-CoV-2 infection.

BACKGROUND: Neutrophils are important in the pathophysiology of coronavirus disease 2019 (COVID-19), but the molecular changes contributing to altered neutrophil phenotypes following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are not fully understood. We used quantitative mass spectrometry-based proteomics to explore neutrophil phenotypes immediately following acute SARS-CoV-2 infection and during recovery. METHODS: Prospective observational study of hospitalised patients with PCR-confirmed SARS-CoV-2 infection (May to December 2020). Patients were enrolled within 96 h of admission, with longitudinal sampling up to 29 days. Control groups comprised non-COVID-19 acute lower respiratory tract infection (LRTI) and age-matched noninfected controls. Neutrophils were isolated from peripheral blood and analysed using mass spectrometry. COVID-19 severity and recovery were defined using the World Health Organization ordinal scale. RESULTS: Neutrophil proteomes from 84 COVID-19 patients were compared to those from 91 LRTI and 42 control participants. 5800 neutrophil proteins were identified, with >1700 proteins significantly changed in neutrophils from COVID-19 patients compared to noninfected controls. Neutrophils from COVID-19 patients initially all demonstrated a strong interferon signature, but this signature rapidly declined in patients with severe disease. Severe disease was associated with increased abundance of proteins involved in metabolism, immunosuppression and pattern recognition, while delayed recovery from COVID-19 was associated with decreased granule components and reduced abundance of metabolic proteins, chemokine and leukotriene receptors, integrins and inhibitory receptors. CONCLUSIONS: SARS-CoV-2 infection results in the sustained presence of circulating neutrophils with distinct proteomes suggesting altered metabolic and immunosuppressive profiles and altered capacities to respond to migratory signals and cues from other immune cells, pathogens or cytokines.

DIA label-free proteomic analysis of murine bone-marrow-derived macrophages.

Here, we describe an optimized protocol to analyze murine bone-marrow-derived macrophages using label-free data-independent acquisition (DIA) proteomics. We provide a complete step-by-step protocol describing sample preparation utilizing the S-Trap approach for on-column digestion and peptide purification. We then detail mass spectrometry data acquisition and approaches for data analysis. Single-shot DIA protocols achieve comparable proteomic depth with data-dependent MS approaches without the need for fractionation. This allows for better scaling for large sample numbers with high inter-experimental reproducibility. For complete details on the use and execution of this protocol, please refer to Ryan et al. (2022).

Nrf2 activation reprograms macrophage intermediary metabolism and suppresses the type I interferon response.

To overcome oxidative, inflammatory, and metabolic stress, cells have evolved cytoprotective protein networks controlled by nuclear factor-erythroid 2 p45-related factor 2 (Nrf2) and its negative regulator, Kelch-like ECH associated protein 1 (Keap1). Here, using high-resolution mass spectrometry we characterize the proteomes of macrophages with altered Nrf2 status revealing significant differences among the genotypes in metabolism and redox homeostasis, which were validated with respirometry and metabolomics. Nrf2 affected the proteome following lipopolysaccharide (LPS) stimulation, with alterations in redox, carbohydrate and lipid metabolism, and innate immunity. Notably, Nrf2 activation promoted mitochondrial fusion. The Keap1 inhibitor, 4-octyl itaconate remodeled the inflammatory macrophage proteome, increasing redox and suppressing type I interferon (IFN) response. Similarly, pharmacologic or genetic Nrf2 activation inhibited the transcription of IFN-ß and its downstream effector IFIT2 during LPS stimulation. These data suggest that Nrf2 activation facilitates metabolic reprogramming and mitochondrial adaptation, and finetunes the innate immune response in macrophages.

Tissue environment, not ontogeny, defines murine intestinal intraepithelial T lymphocytes.

Tissue-resident intestinal intraepithelial T lymphocytes (T-IEL) patrol the gut and have important roles in regulating intestinal homeostasis. T-IEL include both induced T-IEL, derived from systemic antigen-experienced lymphocytes, and natural T-IEL, which are developmentally targeted to the intestine. While the processes driving T-IEL development have been elucidated, the precise roles of the different subsets and the processes driving activation and regulation of these cells remain unclear. To gain functional insights into these enigmatic cells, we used high-resolution, quantitative mass spectrometry to compare the proteomes of induced T-IEL and natural T-IEL subsets, with naive CD8+ T cells from lymph nodes. This data exposes the dominant effect of the gut environment over ontogeny on T-IEL phenotypes. Analyses of protein copy numbers of >7000 proteins in T-IEL reveal skewing of the cell surface repertoire towards epithelial interactions and checkpoint receptors; strong suppression of the metabolic machinery indicating a high energy barrier to functional activation; upregulated cholesterol and lipid metabolic pathways, leading to high cholesterol levels in T-IEL; suppression of T cell antigen receptor signalling and expression of the transcription factor TOX, reminiscent of chronically activated T cells. These novel findings illustrate how T-IEL integrate multiple tissue-specific signals to maintain their homeostasis and potentially function.

-------A type I IFN, prothrombotic hyperinflammatory neutrophil signature is distinct for COVID-19 ARDS--.

Background: Acute respiratory distress syndrome (ARDS) is a severe critical condition with a high mortality that is currently in focus given that it is associated with mortality caused by coronavirus disease 2019 (COVID-19). Neutrophils play a key role in the lung injury characteristic of non-COVID-19 ARDS and there is also accumulating evidence of neutrophil mediated lung injury in patients who succumb to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: We undertook a functional proteomic and metabolomic survey of circulating neutrophil populations, comparing patients with COVID-19 ARDS and non-COVID-19 ARDS to understand the molecular basis of neutrophil dysregulation. Results: Expansion of the circulating neutrophil compartment and the presence of activated low and normal density mature and immature neutrophil populations occurs in ARDS, irrespective of cause. Release of neutrophil granule proteins, neutrophil activation of the clotting cascade and upregulation of the Mac-1 platelet binding complex with formation of neutrophil platelet aggregates is exaggerated in COVID-19 ARDS. Importantly, activation of components of the neutrophil type I interferon responses is seen in ARDS following infection with SARS-CoV-2, with associated rewiring of neutrophil metabolism, and the upregulation of antigen processing and presentation. Whilst dexamethasone treatment constricts the immature low density neutrophil population, it does not impact upon prothrombotic hyperinflammatory neutrophil signatures. Conclusions: Given the crucial role of neutrophils in ARDS and the evidence of a disordered myeloid response observed in COVID-19 patients, this work maps the molecular basis for neutrophil reprogramming in the distinct clinical entities of COVID-19 and non-COVID-19 ARDS.

Erosion of human X chromosome inactivation causes major remodeling of the iPSC proteome.

X chromosome inactivation (XCI) is a dosage compensation mechanism in female mammals whereby transcription from one X chromosome is repressed. Analysis of human induced pluripotent stem cells (iPSCs) derived from female donors identified that low levels of XIST RNA correlated strongly with erosion of XCI. Proteomic analysis, RNA sequencing (RNA-seq), and polysome profiling showed that XCI erosion resulted in amplified RNA and protein expression from X-linked genes, providing a proteomic characterization of skewed dosage compensation. Increased protein expression was also detected from autosomal genes without an mRNA increase, thus altering the protein-RNA correlation between the X chromosome and autosomes. XCI-eroded lines display an ∼13% increase in total cell protein content, with increased ribosomal proteins, ribosome biogenesis and translation factors, and polysome levels. We conclude that XCI erosion in iPSCs causes a remodeling of the proteome, affecting the expression of a much wider range of proteins and disease-linked loci than previously realized.

Population-scale proteome variation in human induced pluripotent stem cells.

Human disease phenotypes are driven primarily by alterations in protein expression and/or function. To date, relatively little is known about the variability of the human proteome in populations and how this relates to variability in mRNA expression and to disease loci. Here, we present the first comprehensive proteomic analysis of human induced pluripotent stem cells (iPSC), a key cell type for disease modelling, analysing 202 iPSC lines derived from 151 donors, with integrated transcriptome and genomic sequence data from the same lines. We characterised the major genetic and non-genetic determinants of proteome variation across iPSC lines and assessed key regulatory mechanisms affecting variation in protein abundance. We identified 654 protein quantitative trait loci (pQTLs) in iPSCs, including disease-linked variants in protein-coding sequences and variants with trans regulatory effects. These include pQTL linked to GWAS variants that cannot be detected at the mRNA level, highlighting the utility of dissecting pQTL at peptide level resolution.

Quantitative analysis of T cell proteomes and environmental sensors during T cell differentiation.

Quantitative mass spectrometry reveals how CD4+ and CD8+ T cells restructure proteomes in response to antigen and mammalian target of rapamycin complex 1 (mTORC1). Analysis of copy numbers per cell of >9,000 proteins provides new understanding of T cell phenotypes, exposing the metabolic and protein synthesis machinery and environmental sensors that shape T cell fate. We reveal that lymphocyte environment sensing is controlled by immune activation, and that CD4+ and CD8+ T cells differ in their intrinsic nutrient transport and biosynthetic capacity. Our data also reveal shared and divergent outcomes of mTORC1 inhibition in naïve versus effector T cells: mTORC1 inhibition impaired cell cycle progression in activated naïve cells, but not effector cells, whereas metabolism was consistently impacted in both populations. This study provides a comprehensive map of naïve and effector T cell proteomes, and a resource for exploring and understanding T cell phenotypes and cell context effects of mTORC1.

Multibatch TMT Reveals False Positives, Batch Effects and Missing Values.

Multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent, tandem mass tags (TMT) in particular. Here we used a large iPSC proteomic experiment with twenty-four 10-plex TMT batches to evaluate the effect of integrating multiple TMT batches within a single analysis. We identified a significant inflation rate of protein missing values as multiple batches are integrated and show that this pattern is aggravated at the peptide level. We also show that without normalization strategies to address the batch effects, the high precision of quantitation within a single multiplexed TMT batch is not reproduced when data from multiple TMT batches are integrated.Further, the incidence of false positives was studied by using Y chromosome peptides as an internal control. The iPSC lines quantified in this data set were derived from both male and female donors, hence the peptides mapped to the Y chromosome should be absent from female lines. Nonetheless, these Y chromosome-specific peptides were consistently detected in the female channels of all TMT batches. We then used the same Y chromosome specific peptides to quantify the level of ion coisolation as well as the effect of primary and secondary reporter ion interference. These results were used to propose solutions to mitigate the limitations of multi-batch TMT analyses. We confirm that including a common reference line in every batch increases precision by facilitating normalization across the batches and we propose experimental designs that minimize the effect of cross population reporter ion interference.

Antigen receptor control of methionine metabolism in T cells.

Immune activated T lymphocytes modulate the activity of key metabolic pathways to support the transcriptional reprograming and reshaping of cell proteomes that permits effector T cell differentiation. The present study uses high resolution mass spectrometry and metabolic labelling to explore how murine T cells control the methionine cycle to produce methyl donors for protein and nucleotide methylations. We show that antigen receptor engagement controls flux through the methionine cycle and RNA and histone methylations. We establish that the main rate limiting step for protein synthesis and the methionine cycle is control of methionine transporter expression. Only T cells that respond to antigen to upregulate and sustain methionine transport are supplied with methyl donors that permit the dynamic nucleotide methylations and epigenetic reprogramming that drives T cell differentiation. These data highlight how the regulation of methionine transport licenses use of methionine for multiple fundamental processes that drive T lymphocyte proliferation and differentiation.

The Encyclopedia of Proteome Dynamics: the KinoViewer.

SUMMARY: The Encyclopedia of Proteome Dynamics (EPD) 'KinoViewer' is an interactive data visualization tool designed for analysis and exploration of both protein and transcript data, showing expression of kinase genes in either human or mouse cells and tissues. The KinoViewer provides a comprehensive, updated graphical display of all human/mouse kinases and an open access analysis tool for the community with a user-friendly graphical interface. AVAILABILITY AND IMPLEMENTATION: The KinoViewer is based on a manually drawn SVG, which is utilized with D3.js to create a dynamic visualization. It can be accessed at: https://peptracker.com/epd/analytics/. The KinoViewer is currently only accessible through the EPD, it is open access and can be used either to view internal datasets, or used to upload and visualize external user datasets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Proteome-wide analysis of protein abundance and turnover remodelling during oncogenic transformation of human breast epithelial cells.

Background: Viral oncogenes and mutated proto-oncogenes are potent drivers of cancer malignancy. Downstream of the oncogenic trigger are alterations in protein properties that give rise to cellular transformation and the acquisition of malignant cellular phenotypes. Developments in mass spectrometry enable large-scale, multidimensional characterisation of proteomes. Such techniques could provide an unprecedented, unbiased view of how oncogene activation remodels a human cell proteome. Methods: Using quantitative MS-based proteomics and cellular assays, we analysed how transformation induced by activating v-Src kinase remodels the proteome and cellular phenotypes of breast epithelial (MCF10A) cells. SILAC MS was used to comprehensively characterise the MCF10A proteome and to measure v-Src-induced changes in protein abundance across seven time-points (1-72 hrs). We used pulse-SILAC MS ( Boisvert et al., 2012), to compare protein synthesis and turnover in control and transformed cells. Follow-on experiments employed a combination of cellular and functional assays to characterise the roles of selected Src-responsive proteins. Results: Src-induced transformation changed the expression and/or turnover levels of ~3% of proteins, affecting ~1.5% of the total protein molecules in the cell. Transformation increased the average rate of proteome turnover and disrupted protein homeostasis. We identify distinct classes of protein kinetics in response to Src activation. We demonstrate that members of the polycomb repressive complex 1 (PRC1) are important regulators of invasion and migration in MCF10A cells. Many Src-regulated proteins are present in low abundance and some are regulated post-transcriptionally. The signature of Src-responsive proteins is highly predictive of poor patient survival across multiple cancer types. Open access to search and interactively explore all these proteomic data is provided via the EPD database ( www.peptracker.com/epd). Conclusions: We present the first comprehensive analysis measuring how protein expression and protein turnover is affected by cell transformation, providing a detailed picture at the protein level of the consequences of activation of an oncogene.

The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics.

Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS files and processed peptide and protein identifications. MS-based proteomics technology is also used increasingly to measure additional protein properties affecting cellular function and disease mechanisms, including post-translational modifications, protein-protein interactions, subcellular and tissue distributions. Consequently, biologists and clinicians need innovative tools to conveniently analyse, visualize and explore such large, complex proteomics data and to integrate it with genomics and other related large-scale datasets. We have created the Encyclopedia of Proteome Dynamics (EPD) to meet this need (https://peptracker.com/epd/). The EPD combines a polyglot persistent database and web-application that provides open access to integrated proteomics data for >30 000 proteins from published studies on human cells and model organisms. It is designed to provide a user-friendly interface, featuring graphical navigation with interactive visualizations that facilitate powerful data exploration in an intuitive manner. The EPD offers a flexible and scalable ecosystem to integrate proteomics data with genomics information, RNA expression and other related, large-scale datasets.