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Advances in immunotherapy rely on targeting novel cell surface antigens, including therapeutically relevant peptide fragments presented by HLA molecules, collectively known as the actionable immunopeptidome. Although the immunopeptidome of classical HLA molecules is extensively studied, exploration of the peptide repertoire presented by non-classical HLA-E remains limited. Growing evidence suggests that HLA-E molecules present pathogen-derived and tumor-associated peptides to CD8 + T cells, positioning them as promising targets for universal immunotherapies due to their minimal polymorphism. This mini-review highlights recent developments in mass spectrometry (MS) technologies for profiling the HLA-E immunopeptidome in various diseases. We discuss the unique features of HLA-E, its expression patterns, stability, and the potential for identifying new therapeutic targets. Understanding the broad repertoire of actionable peptides presented by HLA-E can lead to innovative treatments for viral and pathogen infections and cancer, leveraging its monomorphic nature for broad therapeutic efficacy.

We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies. The cells of the immune system protect us by recognizing telltale molecules produced by damaged and diseased cells, or by infection-causing microorganisms (which are also called pathogens). To help with this process, the cells in our bodies display small fragments of proteins (called peptides) on their surface that are then checked by the immune cells. Collectively, these peptides are referred to as the ‘immunopeptidome’, and deciphering the complexity of the human immunopeptidome is important for both basic research and medical science. Such an achievement would help to guide the development of next-generation vaccines and therapies against autoimmune disorders, infectious diseases and cancers. In the past, immune peptides were mostly identified using a technique that is commonly called ‘shotgun’ mass spectrometry. However, this approach doesn't always provide reproducible results. In 2012, researchers reported the development of a new approach—which they called ‘SWATH’ mass spectrometry—that could yield more reproducible data. Now, Caron et al.—including many of the researchers involved in the 2012 study—have developed a large collection of standardized tests that use SWATH mass spectrometry to analyze the human immunopeptidome. The workflow and the computational and data resources developed as part of this international effort are the first steps toward highly reproducible and measurable analyses of the immunopeptidome across many samples. Moreover, the large repository of assays generated by the project has been made public and will serve a large community of researchers, which should enable better collaborations. In the future, SWATH mass spectrometry could be used as a robust technology for the reproducible detection and measurement of pathogen-specific or cancer-specific immune peptides. This could greatly help in the design of personalized immune-based therapies.

The mammalian target of rapamycin (mTOR) is a central regulator of cell growth and proliferation. mTOR signaling is frequently dysregulated in oncogenic cells, and thus an attractive target for anticancer therapy. Using CellDesigner, a modeling support software for graphical notation, we present herein a comprehensive map of the mTOR signaling network, which includes 964 species connected by 777 reactions. The map complies with both the systems biology markup language (SBML) and graphical notation (SBGN) for computational analysis and graphical representation, respectively. As captured in the mTOR map, we review and discuss our current understanding of the mTOR signaling network and highlight the impact of mTOR feedback and crosstalk regulations on drug‐based cancer therapy. This map is available on the Payao platform, a Web 2.0 based community‐wide interactive process for creating more accurate and information‐rich databases. Thus, this comprehensive map of the mTOR network will serve as a tool to facilitate systems‐level study of up‐to‐date mTOR network components and signaling events toward the discovery of novel regulatory processes and therapeutic strategies for cancer.

Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. Here we introduce a comprehensive computational framework incorporating a machine learning algorithm—MHCvalidator—to enhance mass spectrometry-based immunopeptidomics sensitivity. MHCvalidator identifies unique T-cell epitopes presented by the B7 supertype, including an epitope from a + 1-frameshift in a truncated Spike antigen, supported by ribosome profiling. Analysis of 100,512 COVID-19 patient proteomes shows Spike antigen truncation in 0.85% of cases, revealing frameshifted viral antigens at the population level. Our EpiTrack pipeline tracks global mutations of MHCvalidator-identified CD8 + T-cell epitopes from the BNT162b4 vaccine. While most vaccine epitopes remain globally conserved, an immunodominant A*01-associated epitope mutates in Delta and Omicron variants. This work highlights SARS-CoV-2 antigenic features and emphasizes the importance of continuous adaptation in T-cell vaccine development. The identification of T cell epitopes is a critical step in understanding the immune response to infection and in designing vaccine based approaches. Here the authors introduce a frame work of antigen discovery called MHCvalidator and Epitrack to identify new antigenic features for T-cell COVID-19 vaccines and characterise a novel non-canonical epitope from a truncated Spike variant and mutation of an immunodominant epitope in the BNT162b4 vaccine.

Mass spectrometry is the method of choice for deep and reliable exploration of the (human) proteome. Targeted mass spectrometry reliably detects and quantifies pre-determined sets of proteins in a complex biological matrix and is used in studies that rely on the quantitatively accurate and reproducible measurement of proteins across multiple samples. It requires the one-time, a priori generation of a specific measurement assay for each targeted protein. SWATH-MS is a mass spectrometric method that combines data-independent acquisition (DIA) and targeted data analysis and vastly extends the throughput of proteins that can be targeted in a sample compared to selected reaction monitoring (SRM). Here we present a compendium of highly specific assays covering more than 10,000 human proteins and enabling their targeted analysis in SWATH-MS datasets acquired from research or clinical specimens. This resource supports the confident detection and quantification of 50.9% of all human proteins annotated by UniProtKB/Swiss-Prot and is therefore expected to find wide application in basic and clinical research. Data are available via ProteomeXchange (PXD000953-954) and SWATHAtlas (SAL00016-35). Design Type(s) reference design • replicate design • protein expression profiling • quality control testing design Measurement Type(s) protein expression profiling Technology Type(s) mass spectrometry assay Factor Type(s) purification • Proteolysis Sample Characteristic(s) Homo sapiens • Monocyte • Neutrophil • Kidney • Muscle • Lung • Blood platelet • Gut • Blood plasma • 293 cell • THP-1 cell • U2 OS cell • HeLa cell • U2OS & HeLa • NCI60 • LNCAP cell • CAL-51 cell Machine-accessible metadata file describing the reported data (ISA-Tab format)

Laboratory-scale experiments were conducted to cast AA3003/AA4045 clad ingots via Fusion™ Technology, a novel process developed by Novelis Inc. for the production of aluminum clad materials such as brazing sheet. Experimental results were used to validate a steady-state thermofluids model of the Fusion™ Technology co-casting process. The numerical model was able to accurately predict the temperature field within the AA3003/AA4045 clad ingot as well as the shape of the AA3003 liquid sump. The model was also used to quantify the temperature, fraction solid, and velocity fields in a clad ingot cast with an asymmetrical molten metal-feeding system. Feeding of core and clad molten metals at opposite corners of the mold was found to reduce the risks of hot spots and liquid metal breakthrough from the core sump to the clad side of the Fusion™ Technology mold. The use of a diffuser for the AA3003 core molten metal and of a vertical feeding tube for the AA4045 clad produced different flow patterns and liquid sump shapes on either side of the mold. The quality of the metallurgical bond at the core/clad interface appeared good near the clad inlet and at the ingot centerline, but poor near the edges of the ingot. SEM–EDS analysis of the chemical composition across the interface showed that a 1 to 20- μ m-deep penetration of silicon from the AA4045 clad into the AA3003 core had occurred at visually acceptable interfaces, whereas silicon diffusion across poor interfaces was very limited. A study of the model-predicted fraction solid history at different points along the interface indicated that reheating of the AA3003 core is not required to form a visually acceptable metallurgical bond. However, a sufficient amount of interaction time between the solid AA3003 core shell and the silicon-rich AA4045 clad liquid is required to chemically dissolve the surface of the core and form a good metallurgical bond. An approximate dissolution depth of 750 to 1000  μ m was observed along the visually good interface. Partial dissolution of the Mn-rich AA3003 core led to the formation of Al(Mn,Fe)Si intermetallic particles in the AA4045 clad and an increased manganese concentration near the core/clad interface.

For the last 70 years, direct-chill (DC) casting has been the mainstay of the aluminum industry for the production of monolithic sheet and extruded products. Traditionally, clad aluminum sheet products have been made from separate core and clad DC cast ingots by an expensive roll-bonding process; however, in 2005, Novelis unveiled an innovative variant of the DC casting process called the Fusion™ Technology process that allows the production of multialloy ingots that can be rolled directly into laminated or clad sheet products. Of paramount importance for the successful commercialization of this new technology is a scientific and quantitative understanding of the Fusion™ casting process that will facilitate process optimization and aid in the future development of casting methodology for different alloy combinations and ingot and clad dimensions. In the current study, a numerical steady-state thermofluids model of the Fusion™ Technology casting process was developed and used to simulate the casting of rectangular bimetallic ingots made from the typical brazing sheet combination of AA3003 core clad with an AA4045 aluminum alloy. The analysis is followed by a parametric study of the process. The influence of casting speed and chill-bar height on the steady-state thermal field within the ingot is investigated. According to the criteria developed with the thermofluids model, the AA3003/AA4045 combination of aluminum alloys can be cast successfully with casting speeds up to 2.4 mm s −1 . The quality of the metallurgical bond between the core and the clad is decreased for low casting speeds and chill-bar heights >35 mm. These results can be used as a guideline for improving the productivity of the Fusion™ Technology process.

Thermal modeling of the direct-chill casting process requires accurate knowledge of (1) the different boundary conditions in the primary mold and secondary direct water-spray cooling regimes and (2) their variability with respect to process parameters. In this study, heat transfer in the primary cooling zone was investigated by using temperature measurements made with subsurface thermocouples in the mold as input to an inverse heat conduction algorithm. Laboratory-scale experiments were performed to investigate the primary cooling of AA3003 and AA4045 aluminum alloy ingots cast at speeds ranging between 1.58 and 2.10 mm/s. The average heat flux values were calculated for the steady-state phase of the casting process, and an effective heat-transfer coefficient for the global primary cooling process was derived that included convection at the mold surfaces and conduction through the mold wall. Effective heat-transfer coefficients were evaluated at different points along the mold height and compared with values from a previously derived computational fluid dynamics model of the direct-chill casting process that were based on predictions of the air gap thickness between the mold and ingot. The current experimental results closely matched the values previously predicted by the air gap models. The effective heat-transfer coefficient for primary cooling was also found to increase slightly with the casting speed and was higher near the mold top (up to 824 W/m 2 ·K) where the molten aluminum first comes in contact with the mold than near the bottom (as low as 242 W/m 2 ·K) where an air gap forms between the ingot and mold because of thermal contraction of the ingot. These results are consistent with previous studies.

Self/non‐self discrimination is a fundamental requirement of life. Endogenous peptides presented by major histocompatibility complex class I (MHC I) molecules represent the essence of self for CD8 T lymphocytes. These MHC I peptides (MIPs) are collectively referred to as the immunopeptidome. From a systems‐level perspective, very little is known about the origin, composition and plasticity of the immunopeptidome. Here, we show that the immunopeptidome, and therefore the nature of the immune self, is plastic and moulded by cellular metabolic activity. By using a quantitative high‐throughput mass spectrometry‐based approach, we found that altering cellular metabolism via the inhibition of the mammalian target of rapamycin results in dynamic changes in the cell surface MIPs landscape. Moreover, we provide systems‐level evidence that the immunopeptidome projects at the cell surface a representation of biochemical networks and metabolic events regulated at multiple levels inside the cell. Our findings open up new perspectives in systems immunology and predictive biology. Indeed, predicting variations in the immunopeptidome in response to cell‐intrinsic and ‐extrinsic factors could be relevant to the rational design of immunotherapeutic interventions. Quantitative mass spectrometry reveals changes in the peptides presented by major histocompatibility complex class I molecules when the mTOR pathway is perturbed. These data show that the immunopeptidome is plastic and provides information on the internal state of the cell. Synopsis Quantitative mass spectrometry reveals changes in the peptides presented by major histocompatibility complex class I molecules when the mTOR pathway is perturbed. These data show that the immunopeptidome is plastic and provides information on the internal state of the cell. Using a quantitative high‐throughput mass spectrometry‐based approach, we found that inhibition of the mammalian target of rapamycin (mTOR) results in dynamic changes in the composition of the MHC I immunopeptidome. We provide systems‐level evidence that the MHC I immunopeptidome projects at the cell surface a representation of biochemical networks and metabolic events regulated at multiple levels (transcriptional and co‐ or post‐translational level) inside the cell. We demonstrate that the composition of the MHC I immunopeptidome changes in response to metabolic perturbations and we provide insights into how mammalian cells communicate their metabolic status to the adaptive immune system.

An estimated one-third of the world's population is currently latently infected with Mycobacterium tuberculosis . Latent M. tuberculosis infection (LTBI) progresses into active tuberculosis (TB) disease in ~5 to 10% of infected individuals. Diagnostic and prognostic biomarkers to monitor disease progression are urgently needed to ensure better care for TB patients and to decrease the spread of TB. Biomarker development is primarily based on transcriptomics. Our understanding of biology combined with evolving technical advances in high-throughput techniques led us to investigate the possibility of additional platforms (epigenetics and proteomics) in the quest to (i) understand the biology of the TB host response and (ii) search for multiplatform biosignatures in TB. We engaged in a pilot study to interrogate the DNA methylome, transcriptome, and proteome in selected monocytes and granulocytes from TB patients and healthy LTBI participants. Our study provides first insights into the levels and sources of diversity in the epigenome and proteome among TB patients and LTBI controls, despite limitations due to small sample size. Functionally the differences between the infection phenotypes (LTBI versus active TB) observed in the different platforms were congruent, thereby suggesting regulation of function not only at the transcriptional level but also by DNA methylation and microRNA. Thus, our data argue for the development of a large-scale study of the DNA methylome, with particular attention to study design in accounting for variation based on gender, age, and cell type. IMPORTANCE DNA methylation modifies the transcriptional program of cells. We have focused on two major populations of leukocytes involved in immune response to infectious diseases, granulocytes and monocytes, both of which are professional phagocytes that engulf and kill bacteria. We have interrogated how DNA methylation, gene expression, and protein translation differ in these two cell populations between healthy individuals and patients suffering from TB. To better understand the underlying biologic mechanisms, we harnessed a statistical enrichment analysis, taking advantage of predefined and well-characterized gene sets. Not only were there clear differences on various levels between the two populations, but there were also differences between TB patients and healthy controls in the transcriptome, proteome, and, for the first time, DNA methylome in these cells. Our pilot study emphasizes the value of a large-scale study of the DNA methylome taking into account our findings. DNA methylation modifies the transcriptional program of cells. We have focused on two major populations of leukocytes involved in immune response to infectious diseases, granulocytes and monocytes, both of which are professional phagocytes that engulf and kill bacteria. We have interrogated how DNA methylation, gene expression, and protein translation differ in these two cell populations between healthy individuals and patients suffering from TB. To better understand the underlying biologic mechanisms, we harnessed a statistical enrichment analysis, taking advantage of predefined and well-characterized gene sets. Not only were there clear differences on various levels between the two populations, but there were also differences between TB patients and healthy controls in the transcriptome, proteome, and, for the first time, DNA methylome in these cells. Our pilot study emphasizes the value of a large-scale study of the DNA methylome taking into account our findings.