From a gene-centric to whole-proteome view of differentiation of T helper cell subsets

A primary human T-cell spectral library to facilitate large scale quantitative T-cell proteomics

Data independent analysis (DIA) exemplified by sequential window acquisition of all theoretical mass spectra (SWATH-MS) provides robust quantitative proteomics data, but the lack of a public primary human T-cell spectral library is a current resource gap. Here, we report the generation of a high-quality spectral library containing data for 4,833 distinct proteins from human T-cells across genetically unrelated donors, covering ~24% proteins of the UniProt/SwissProt reviewed human proteome. SWATH-MS analysis of 18 primary T-cell samples using the new human T-cell spectral library reliably identified and quantified 2,850 proteins at 1% false discovery rate (FDR). In comparison, the larger Pan-human spectral library identified and quantified 2,794 T-cell proteins in the same dataset. As the libraries identified an overlapping set of proteins, combining the two libraries resulted in quantification of 4,078 human T-cell proteins. Collectively, this large data archive will be a useful public resource for human T-cell proteomic studies. The human T-cell library is available at SWATHAtlas and the data are available via ProteomeXchange (PXD019446 and PXD019542) and PeptideAtlas (PASS01587).

Modulation of Allergic Sensitization and Allergic Inflammation by Staphylococcus aureus Enterotoxin B in an Ovalbumin Mouse Model

The superantigen Staphylococcus aureus (S. aureus) enterotoxin B (SEB) has been proposed a central player in the associations between S. aureus nasal colonization and the development of allergic asthma. Previously, SEB has been shown to aggravate allergic sensitization and allergic airway inflammation (AAI) in experimental mouse models. Aiming at understanding the underlying immunological mechanisms, we tested the hypothesis that intranasal (i.n.) SEB-treatment divergently modulates AAI depending on the timing and intensity of the SEB-encounter. In an ovalbumin-mediated mouse model of AAI, we treated mice i.n. with 50 ng or 500 ng SEB either together with the allergic challenge or prior to the peripheral sensitization. We observed SEB to affect different hallmark parameters of AAI depending on the timing and the dose of treatment. SEB administered i.n. together with the allergic challenge significantly modulated respiratory leukocyte accumulation, intensified lymphocyte activation and, at the higher dose, induced a strong type-1 and pro-inflammatory cytokine response and alleviated airway hyperreactivity in AAI. SEB administered i.n. prior to the allergic sensitization at the lower dose significantly boosted the specific IgE response while administration of the higher dose led to a significantly reduced recruitment of immune cells, including eosinophils, to the respiratory tract and to a significantly dampened Th-2 cytokine response without inducing a Th-1 or pro-inflammatory response. We show a remarkably versatile potential for SEB to either aggravate or alleviate different parameters of allergic sensitization and AAI. Our study thereby not only highlights the complexity of the associations between S. aureus and allergic asthma but possibly even points at prophylactic and therapeutic pathways.

Methrotexate Treatment Inmunomodulates Abnormal Cytokine Expression by T CD4 Lymphocytes Present in DMARD-Naïve Rheumatoid Arthritis Patients

CD4⁺T-lymphocytes are relevant in the pathogenesis of rheumatoid arthritis (RA), however, their potential involvement in early RA remains elusive. Methotrexate (MTX) is a commonly used disease-modifying antirheumatic drug (DMARD), but its mechanism has not been fully established. In 47 new-onset DMARD-naïve RA patients, we investigated the pattern of IFNγ, IL-4 and IL-17A expression by naïve (T_N), central (T_CM), effector memory (T_EM) and effector (T_E) CD4⁺ subsets; their STAT-1, STAT-6 and STAT-3 transcription factors phosphorylation, and the circulating levels of IFNγ, IL-4 and IL-17. We also studied the RA patients after 3 and 6 months of MTX treatment and according their clinical response. CD4⁺T-lymphocyte subsets and cytokine expression were measured using flow cytometry. New-onset DMARD-naïve RA patients showed a significant expansion of IL-17A⁺, IFNγ⁺ and IL-17A⁺IFNγ⁺ CD4⁺T-lymphocyte subsets and increased intracellular STAT-1 and STAT-3 phosphorylation. Under basal conditions, nonresponder patients showed increased numbers of circulating IL-17A producing T_N and T_MC CD4⁺T-lymphocytes and IFNγ producing T_N, T_CM, T_EM CD4⁺T-lymphocytes with respect to responders. After 6 months, the numbers of CD4⁺IL-17A⁺T_N remained significantly increased in nonresponders. In conclusion, CD4⁺T-lymphocytes in new-onset DMARD-naïve RA patients show IL-17A and IFNγ abnormalities in T_N, indicating their relevant role in early disease pathogenesis. Different patterns of CD4⁺ modulation are identified in MTX responders and nonresponders.

seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data

The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer the relative proportions of 10 major immune cells in mouse tissues from RNA-Seq data. The performance of seq-ImmuCC was evaluated among multiple computational algorithms, transcriptional platforms, and simulated and experimental datasets. The test results showed its stable performance and superb consistency with experimental observations under different conditions. With seq-ImmuCC, we generated the comprehensive landscape of immune cell compositions in 27 normal mouse tissues and extracted the distinct signatures of immune cell proportion among various tissue types. Furthermore, we quantitatively characterized and compared 18 different types of mouse tumor tissues of distinct cell origins with their immune cell compositions, which provided a comprehensive and informative measurement for the immune microenvironment inside tumor tissues. The online server of seq-ImmuCC are freely available at http://wap-lab.org:3200/immune/.

Cell-selective labelling of proteomes in Drosophila melanogaster

The specification and adaptability of cells rely on changes in protein composition. Nonetheless, uncovering proteome dynamics with cell-type-specific resolution remains challenging. Here we introduce a strategy for cell-specific analysis of newly synthesized proteomes by combining targeted expression of a mutated methionyl-tRNA synthetase (MetRS) with bioorthogonal or fluorescent non-canonical amino-acid-tagging techniques (BONCAT or FUNCAT). Substituting leucine by glycine within the MetRS-binding pocket (MetRS^LtoG) enables incorporation of the non-canonical amino acid azidonorleucine (ANL) instead of methionine during translation. Newly synthesized proteins can thus be labelled by coupling the azide group of ANL to alkyne-bearing tags through ‘click chemistry'. To test these methods for applicability in vivo, we expressed MetRS^LtoG cell specifically in Drosophila. FUNCAT and BONCAT reveal ANL incorporation into proteins selectively in cells expressing the mutated enzyme. Cell-type-specific FUNCAT and BONCAT, thus, constitute eligible techniques to study protein synthesis-dependent processes in complex and behaving organisms.

Mutated tRNA synthetases can incorporate non-canonical amino acids into proteins. Erdmann et al. exploit this property to metabolically label newly synthesized proteins in selected cell types in Drosophila, and demonstrate their detection using proteomics (BONCAT) and fluorescence imaging (FUNCAT).

A Combined Omics Approach to Generate the Surface Atlas of Human Naive CD4+ T Cells during Early T-Cell Receptor Activation

Naive CD4(+) T cells are the common precursors of multiple effector and memory T-cell subsets and possess a high plasticity in terms of differentiation potential. This stem-cell-like character is important for cell therapies aiming at regeneration of specific immunity. Cell surface proteins are crucial for recognition and response to signals mediated by other cells or environmental changes. Knowledge of cell surface proteins of human naive CD4(+) T cells and their changes during the early phase of T-cell activation is urgently needed for a guided differentiation of naive T cells and may support the selection of pluripotent cells for cell therapy. Periodate oxidation and aniline-catalyzed oxime ligation technology was applied with subsequent quantitative liquid chromatography-tandem MS to generate a data set describing the surface proteome of primary human naive CD4(+) T cells and to monitor dynamic changes during the early phase of activation. This led to the identification of 173 N-glycosylated surface proteins. To independently confirm the proteomic data set and to analyze the cell surface by an alternative technique a systematic phenotypic expression analysis of surface antigens via flow cytometry was performed. This screening expanded the previous data set, resulting in 229 surface proteins, which were expressed on naive unstimulated and activated CD4(+) T cells. Furthermore, we generated a surface expression atlas based on transcriptome data, experimental annotation, and predicted subcellular localization, and correlated the proteomics result with this transcriptional data set. This extensive surface atlas provides an overall naive CD4(+) T cell surface resource and will enable future studies aiming at a deeper understanding of mechanisms of T-cell biology allowing the identification of novel immune targets usable for the development of therapeutic treatments.