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Combining multiple therapeutic strategies in NRAS/BRAF mutant melanoma-namely MEK/BRAF kinase inhibitors, immune checkpoint inhibitors (ICIs), and targeted immunotherapies-may offer an improved survival benefit by overcoming limitations associated with any individual therapy. Still, optimal combination, order, and timing of administration remains under investigation. Here, we measure how MEK inhibition (MEKi) alters anti-tumor immunity by utilizing quantitative immunopeptidomics to profile changes in the peptide major histocompatibility molecules (pMHC) repertoire. These data reveal a collection of tumor antigens whose presentation levels are selectively augmented following therapy, including several epitopes present at over 1,000 copies per cell. We leveraged the tunable abundance of MEKi-modulated antigens by targeting four epitopes with pMHC-specific T cell engagers and antibody drug conjugates, enhancing cell killing in tumor cells following MEK inhibition. These results highlight drug treatment as a means to enhance immunotherapy efficacy by targeting specific upregulated pMHCs and provide a methodological framework for identifying, quantifying, and therapeutically targeting additional epitopes of interest.
Asunto(s)
Melanoma , Quinasas de Proteína Quinasa Activadas por Mitógenos , Humanos , Quinasas de Proteína Quinasa Activadas por Mitógenos/genética , Antígenos de Neoplasias/genética , Melanoma/tratamiento farmacológico , Melanoma/genética , Proteínas Proto-Oncogénicas B-raf/genética , EpítoposRESUMEN
Recent developments in nonequilibrium statistical mechanics suggest that the history of entropy production in a system determines the relative likelihood of competing processes. This presents the possibility of interpreting and predicting the self-organization of complex active systems, but existing theories rely on quantities that are challenging to obtain. Here, we address this issue for a general class of Markovian systems in which two types of self-replicating molecular assemblies (self-replicators) compete for a pool of limiting resource molecules within a nonequilibrium steady state. We derive exact relations that show that the relative fitness of these species depends on a path function, ψ, which is a sum of the entropy production and a relative-entropy term. In the limit of infinite path length, ψ reduces to the entropy production. We demonstrate use of the theory by numerically studying two models inspired by biological systems, including a simplified model of a competition between strains of the yeast prion Sup35 in the presence of driven disaggregation by the ATPase Hsp104.
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Vaccine-elicited T cell responses can contribute to immune protection against emerging infectious disease risks such as antimicrobials-resistant (AMR) microbial pathogens and viruses with pandemic potential, but rapidly identifying appropriate targets for T cell priming vaccines remains challenging. Mass spectrometry (MS) analysis of peptides presented on major histocompatibility complexes (MHCs) can identify potential targets for protective T cell responses in a proteome-wide manner. However, pathogen-derived peptides are outnumbered by self peptides in the MHC repertoire and may be missed in untargeted MS analyses. Here we present a novel approach, termed PathMHC, that uses computational analysis of untargeted MS data followed by targeted MS to discover novel pathogen-derived MHC peptides more efficiently than untargeted methods alone. We applied this workflow to identify MHC peptides derived from multiple microbes, including potential vaccine targets presented on MHC-I by human dendritic cells infected with Mycobacterium tuberculosis . PathMHC will facilitate antigen discovery campaigns for vaccine development.
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Vaccines and immunotherapies that target peptide-major histocompatibility complexes (peptide-MHCs) have the potential to address multiple unmet medical needs in cancer and infectious disease. Designing vaccines and immunotherapies to target peptide-MHCs requires accurate identification of target peptides in infected or cancerous cells or tissue, and may require absolute or relative quantification to identify abundant targets and measure changes in presentation under different treatment conditions. Internal standard parallel reaction monitoring (also known as 'SureQuant') can be used to validate and/or quantify MHC peptides previously identified by using untargeted methods such as data-dependent acquisition. SureQuant MHC has three main use cases: (i) conclusive confirmation of the identities of putative MHC peptides via comparison with an internal synthetic stable isotope labeled (SIL) peptide standard; (ii) accurate relative quantification by using pre-formed heavy isotope-labeled peptide-MHC complexes (hipMHCs) containing SIL peptides as internal controls for technical variation; and (iii) absolute quantification of each target peptide by using different amounts of hipMHCs loaded with synthetic peptides containing one, two or three SIL amino acids to provide an internal standard curve. Absolute quantification can help determine whether the abundance of a peptide-MHC is sufficient for certain therapeutic modalities. SureQuant MHC therefore provides unique advantages for immunologists seeking to confidently validate antigenic targets and understand the dynamics of the MHC repertoire. After synthetic standards are ordered (3-4 weeks), this protocol can be carried out in 3-4 days and is suitable for individuals with mass spectrometry experience who are comfortable with customizing instrument methods.
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Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is the leading cause of infectious disease death and lacks a vaccine capable of protecting adults from pulmonary TB. Studies have shown that Mtb uses a variety of mechanisms to evade host immunity. Secreted Mtb proteins such as Type VII secretion system substrates have been characterized for their ability to modulate anti-Mtb immunity; however, studies of other pathogens such as Salmonella Typhi and Staphylococcus aureus have revealed that outer membrane proteins can also interact with the innate and adaptive immune system. The Mtb outer membrane proteome has received relatively less attention due to limited techniques available to interrogate this compartment. We filled this gap by deploying protease shaving and quantitative mass spectrometry to identify Mtb outer membrane proteins which serve as nodes in the Mtb-host interaction network. These analyses revealed several novel Mtb proteins on the Mtb surface largely derived from the PE/PPE class of Mtb proteins, including PPE18, a component of a leading Mtb vaccine candidate. We next exploited the localization of PPE18 to decorate the Mtb surface with heterologous proteins and deliver these surface-engineered Mtb to the phagosome. Together, these studies reveal potential novel targets for new Mtb vaccines as well as facilitate new approaches to study difficult to study cellular compartments during infection.
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CD8+ T cell recognition of Mycobacterium tuberculosis (Mtb)-specific peptides presented on major histocompatibility complex class I (MHC-I) contributes to immunity to tuberculosis (TB), but the principles that govern presentation of Mtb antigens on MHC-I are incompletely understood. In this study, mass spectrometry (MS) analysis of the MHC-I repertoire of Mtb-infected primary human macrophages reveals that substrates of Mtb's type VII secretion systems (T7SS) are overrepresented among Mtb-derived peptides presented on MHC-I. Quantitative, targeted MS shows that ESX-1 activity is required for presentation of Mtb peptides derived from both ESX-1 substrates and ESX-5 substrates on MHC-I, consistent with a model in which proteins secreted by multiple T7SSs access a cytosolic antigen processing pathway via ESX-1-mediated phagosome permeabilization. Chemical inhibition of proteasome activity, lysosomal acidification, or cysteine cathepsin activity did not block presentation of Mtb antigens on MHC-I, suggesting involvement of other proteolytic pathways or redundancy among multiple pathways. Our study identifies Mtb antigens presented on MHC-I that could serve as targets for TB vaccines, and reveals how the activity of multiple T7SSs interacts to contribute to presentation of Mtb antigens on MHC-I.
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Presentación de Antígeno , Mycobacterium tuberculosis , Humanos , Mycobacterium tuberculosis/metabolismo , Antígenos Bacterianos , Antígenos de Histocompatibilidad Clase I/metabolismo , Péptidos/metabolismoRESUMEN
T cells must recognize pathogen-derived peptides bound to major histocompatibility complexes (MHCs) in order to initiate a cell-mediated immune response against an infection, or to support the development of high-affinity antibody responses. Identifying antigens presented on MHCs by infected cells and professional antigen-presenting cells (APCs) during infection may therefore provide a route toward developing new vaccines. Peptides bound to MHCs can be identified at whole-proteome scale using mass spectrometry-a technique referred to as "immunopeptidomics." This technique has emerged as a powerful tool for identifying potential vaccine targets in the context of many infectious diseases. In this review, we discuss the contributions immunopeptidomic studies have made to understanding antigen presentation and T cell priming in the context of infection and the potential for immunopeptidomics to inform the development of vaccines to address pressing global health problems in infectious disease.
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Bacterial response to transient physical stress is critical to their homeostasis and survival in the dynamic natural environment. Because of the lack of biophysical tools capable of delivering precise and localized physical perturbations to a bacterial community, the underlying mechanism of microbial signal transduction has remained unexplored. Here, we developed multiscale and structured silicon (Si) materials as nongenetic optical transducers capable of modulating the activities of both single bacterial cells and biofilms at high spatiotemporal resolution. Upon optical stimulation, we capture a previously unidentified form of rapid, photothermal gradient-dependent, intercellular calcium signaling within the biofilm. We also found an unexpected coupling between calcium dynamics and biofilm mechanics, which could be of importance for biofilm resistance. Our results suggest that functional integration of Si materials and bacteria, and associated control of signal transduction, may lead to hybrid living matter toward future synthetic biology and adaptable materials.