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BACKGROUND: Teplizumab, a FcR non-binding anti-CD3 mAb, is approved to delay progression of type 1 diabetes (T1D) at-risk patients. Previous investigations described the immediate effects of the 14-day treatment, but longer-term effects of the drug remain unknown. METHODS: With an extended analysis of study participants, we found that 36% were undiagnosed or remained clinical diabetes free after 5 years suggesting operational tolerance. Using single cell RNA-seq, we compared the phenotypes, transcriptome, and repertoire of peripheral blood CD8+ T cells including autoreactive T cells from study participants before and after teplizumab and features of responders and non-responders. RESULTS: At 3 months, there were transcriptional signatures of cell activation in CD4+ and CD8+ T cells including signaling that was reversed at 18 months. At that time, there was reduced expression of genes in T cell receptor and activation pathways in clinical responders. In CD8+ T cells, we found increased expression of genes associated with exhaustion and immune regulation with teplizumab treatment. These transcriptional features were further confirmed in an independent cohort. Pseudotime analysis showed differentiation of CD8+ exhausted and memory cells with teplizumab treatment. IL7R expression was reduced and patients with lower expression of CD127 had longer diabetes free intervals. In addition, the frequency of autoantigen reactive CD8+ T cells, that expanded in the placebo group over 18 months, did not increase in the teplizumab group. CONCLUSION: These findings indicate that teplizumab promotes operational tolerance in T1D, involving activation followed by exhaustion and regulation and prevents expansion of autoreactive T cells. CLINICALTRIALS: gov: NCT01030861. FUNDING: NIDDK/NIH, Juvenile Diabetes Research Foundation.
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Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.
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Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.
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Linfócitos B , Vacinas contra Influenza , Análise de Célula Única , Humanos , Vacinas contra Influenza/imunologia , Linfócitos B/imunologia , Centro Germinativo/imunologia , Influenza Humana/imunologia , Influenza Humana/prevenção & controle , Vacinação , Anticorpos Antivirais/imunologia , Adjuvantes Imunológicos , Adjuvantes de Vacinas , Monócitos/imunologia , Polissorbatos , Esqualeno/imunologia , Imunidade Inata/imunologiaRESUMO
The identification of immune correlates of protection against infectious pathogens will accelerate the design and optimization of recombinant and subunit vaccines. Systematic analyses such as immunoprofiling including serological, cellular, and molecular assessments supported by computational tools are key to not only identify correlates of protection but also biomarkers of disease susceptibility. The current study expands our previous cellular and serological profiling of vaccine-induced responses to a whole parasite malaria vaccine. The irradiated sporozoite model was chosen as it is considered the most effective vaccine against malaria. In contrast to whole blood transcriptomics analysis, we stimulated peripheral blood mononuclear cells (PBMC) with sporozoites and enriched for antigen-specific cells prior to conducting transcriptomics analysis. By focusing on transcriptional events triggered by antigen-specific stimulation, we were able to uncover quantitative and qualitative differences between protected and non-protected individuals to controlled human malaria infections and identified differentially expressed genes associated with sporozoite-specific responses. Further analyses including pathway and gene set enrichment analysis revealed that vaccination with irradiated sporozoites induced a transcriptomic profile associated with Th1-responses, Interferon-signaling, antigen-presentation, and inflammation. Analyzing longitudinal time points not only post-vaccination but also post-controlled human malaria infection further revealed that the transcriptomic profile of protected vs non-protected individuals was not static but continued to diverge over time. The results lay the foundation for comparing protective immune signatures induced by various vaccine platforms to uncover immune correlates of protection that are common across platforms.
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Mordeduras e Picadas de Insetos , Vacinas Antimaláricas , Malária Falciparum , Malária , Animais , Humanos , Plasmodium falciparum/genética , Malária Falciparum/prevenção & controle , Leucócitos Mononucleares , Imunização/métodos , Vacinação/métodos , Malária/prevenção & controle , EsporozoítosRESUMO
Protective immunity following vaccination is sustained by long-lived antibody-secreting cells and resting memory B cells (MBCs). Responses to two-dose SARS-CoV-2 mRNA-1273 vaccination are evaluated longitudinally by multimodal single-cell analysis in three infection-naïve individuals. Integrated surface protein, transcriptomics, and B cell receptor (BCR) repertoire analysis of sorted plasmablasts and spike+ (S-2P+) and S-2P- B cells reveal clonal expansion and accumulating mutations among S-2P+ cells. These cells are enriched in a cluster of immunoglobulin G-expressing MBCs and evolve along a bifurcated trajectory rooted in CXCR3+ MBCs. One branch leads to CD11c+ atypical MBCs while the other develops from CD71+ activated precursors to resting MBCs, the dominant population at month 6. Among 12 evolving S-2P+ clones, several are populated with plasmablasts at early timepoints as well as CD71+ activated and resting MBCs at later timepoints, and display intra- and/or inter-cohort BCR convergence. These relationships suggest a coordinated and predictable evolution of SARS-CoV-2 vaccine-generated MBCs.
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Vacina de mRNA-1273 contra 2019-nCoV , COVID-19 , Humanos , SARS-CoV-2 , Vacinas contra COVID-19 , COVID-19/prevenção & controle , Linfócitos B , Anticorpos Antivirais , VacinaçãoRESUMO
Advances in multimodal single cell analysis can empower high-resolution dissection of human vaccination responses. The resulting data capture multiple layers of biological variations, including molecular and cellular states, vaccine formulations, inter- and intra-subject differences, and responses unfolding over time. Transforming such data into biological insight remains a major challenge. Here we present a systematic framework applied to multimodal single cell data obtained before and after influenza vaccination without adjuvants or pandemic H5N1 vaccination with the AS03 adjuvant. Our approach pinpoints responses shared across or unique to specific cell types and identifies adjuvant specific signatures, including pro-survival transcriptional states in B lymphocytes that emerged one day after vaccination. We also reveal that high antibody responders to the unadjuvanted vaccine have a distinct baseline involving a rewired network of cell type specific transcriptional states. Remarkably, the status of certain innate immune cells in this network in high responders of the unadjuvanted vaccine appear "naturally adjuvanted": they resemble phenotypes induced early in the same cells only by vaccination with AS03. Furthermore, these cell subsets have elevated frequency in the blood at baseline and increased cell-intrinsic phospho-signaling responses after LPS stimulation ex vivo in high compared to low responders. Our findings identify how variation in the status of multiple immune cell types at baseline may drive robust differences in innate and adaptive responses to vaccination and thus open new avenues for vaccine development and immune response engineering in humans.
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Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health.
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Acute viral infections can have durable functional impacts on the immune system long after recovery, but how they affect homeostatic immune states and responses to future perturbations remain poorly understood1-4. Here we use systems immunology approaches, including longitudinal multimodal single-cell analysis (surface proteins, transcriptome and V(D)J sequences) to comparatively assess baseline immune statuses and responses to influenza vaccination in 33 healthy individuals after recovery from mild, non-hospitalized COVID-19 (mean, 151 days after diagnosis) and 40 age- and sex-matched control individuals who had never had COVID-19. At the baseline and independent of time after COVID-19, recoverees had elevated T cell activation signatures and lower expression of innate immune genes including Toll-like receptors in monocytes. Male individuals who had recovered from COVID-19 had coordinately higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared with healthy male individuals and female individuals who had recovered from COVID-19, in part because male recoverees had monocytes with higher IL-15 responses early after vaccination coupled with elevated prevaccination frequencies of 'virtual memory'-like CD8+ T cells poised to produce more IFNγ after IL-15 stimulation. Moreover, the expression of the repressed innate immune genes in monocytes increased by day 1 to day 28 after vaccination in recoverees, therefore moving towards the prevaccination baseline of the healthy control individuals. By contrast, these genes decreased on day 1 and returned to the baseline by day 28 in the control individuals. Our study reveals sex-dimorphic effects of previous mild COVID-19 and suggests that viral infections in humans can establish new immunological set-points that affect future immune responses in an antigen-agnostic manner.
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COVID-19 , Imunidade Inata , Memória Imunológica , Vacinas contra Influenza , Caracteres Sexuais , Linfócitos T , Vacinação , Feminino , Humanos , Masculino , Linfócitos T CD8-Positivos/imunologia , COVID-19/imunologia , Vacinas contra Influenza/imunologia , Influenza Humana/imunologia , Influenza Humana/prevenção & controle , Interleucina-15/imunologia , Receptores Toll-Like/imunologia , Linfócitos T/citologia , Linfócitos T/imunologia , Monócitos , Imunidade Inata/genética , Imunidade Inata/imunologia , Análise de Célula Única , Voluntários SaudáveisRESUMO
Most studies of adaptive immunity to SARS-CoV-2 infection focus on peripheral blood, which may not fully reflect immune responses at the site of infection. Using samples from 110 children undergoing tonsillectomy and adenoidectomy during the COVID-19 pandemic, we identified 24 samples with evidence of previous SARS-CoV-2 infection, including neutralizing antibodies in serum and SARS-CoV-2-specific germinal center and memory B cells in the tonsils and adenoids. Single-cell B cell receptor (BCR) sequencing indicated virus-specific BCRs were class-switched and somatically hypermutated, with overlapping clones in the two tissues. Expanded T cell clonotypes were found in tonsils, adenoids and blood post-COVID-19, some with CDR3 sequences identical to previously reported SARS-CoV-2-reactive T cell receptors (TCRs). Pharyngeal tissues from COVID-19-convalescent children showed persistent expansion of germinal center and antiviral lymphocyte populations associated with interferon (IFN)-γ-type responses, particularly in the adenoids, and viral RNA in both tissues. Our results provide evidence for persistent tissue-specific immunity to SARS-CoV-2 in the upper respiratory tract of children after infection.
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COVID-19 , SARS-CoV-2 , Humanos , Criança , Pandemias , Imunidade Adaptativa , Tonsila Palatina , Anticorpos AntiviraisRESUMO
Multimodal single-cell profiling methods that measure protein expression with oligo-conjugated antibodies hold promise for comprehensive dissection of cellular heterogeneity, yet the resulting protein counts have substantial technical noise that can mask biological variations. Here we integrate experiments and computational analyses to reveal two major noise sources and develop a method called "dsb" (denoised and scaled by background) to normalize and denoise droplet-based protein expression data. We discover that protein-specific noise originates from unbound antibodies encapsulated during droplet generation; this noise can thus be accurately estimated and corrected by utilizing protein levels in empty droplets. We also find that isotype control antibodies and the background protein population average in each cell exhibit significant correlations across single cells, we thus use their shared variance to correct for cell-to-cell technical noise in each cell. We validate these findings by analyzing the performance of dsb in eight independent datasets spanning multiple technologies, including CITE-seq, ASAP-seq, and TEA-seq. Compared to existing normalization methods, our approach improves downstream analyses by better unmasking biologically meaningful cell populations. Our method is available as an open-source R package that interfaces easily with existing single cell software platforms such as Seurat, Bioconductor, and Scanpy and can be accessed at "dsb [ https://cran.r-project.org/package=dsb ]".
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Perfilação da Expressão Gênica , Software , Perfilação da Expressão Gênica/métodos , Análise de Célula Única/métodosRESUMO
Viral infections can have profound and durable functional impacts on the immune system. There is an urgent need to characterize the long-term immune effects of SARS-CoV-2 infection given the persistence of symptoms in some individuals and the continued threat of novel variants. Here we use systems immunology, including longitudinal multimodal single cell analysis (surface proteins, transcriptome, and V(D)J sequences) from 33 previously healthy individuals after recovery from mild, non-hospitalized COVID-19 and 40 age- and sex-matched healthy controls with no history of COVID-19 to comparatively assess the post-infection immune status (mean: 151 days after diagnosis) and subsequent innate and adaptive responses to seasonal influenza vaccination. Identification of both sex-specific and -independent temporally stable changes, including signatures of T-cell activation and repression of innate defense/immune receptor genes (e.g., Toll-like receptors) in monocytes, suggest that mild COVID-19 can establish new post-recovery immunological set-points. COVID-19-recovered males had higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared to healthy males and COVID-19-recovered females, partly attributable to elevated pre-vaccination frequencies of a GPR56 expressing CD8+ T-cell subset in male recoverees that are "poised" to produce higher levels of IFNγ upon inflammatory stimulation. Intriguingly, by day 1 post-vaccination in COVID-19-recovered subjects, the expression of the repressed genes in monocytes increased and moved towards the pre-vaccination baseline of healthy controls, suggesting that the acute inflammation induced by vaccination could partly reset the immune states established by mild COVID-19. Our study reveals sex-dimorphic immune imprints and in vivo functional impacts of mild COVID-19 in humans, suggesting that prior COVID-19, and possibly respiratory viral infections in general, could change future responses to vaccination and in turn, vaccines could help reset the immune system after COVID-19, both in an antigen-agnostic manner.
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SARS-CoV-2 infection triggers adaptive immune responses from both T and B cells. However, most studies focus on peripheral blood, which may not fully reflect immune responses in lymphoid tissues at the site of infection. To evaluate both local and systemic adaptive immune responses to SARS-CoV-2, we collected peripheral blood, tonsils, and adenoids from 110 children undergoing tonsillectomy/adenoidectomy during the COVID-19 pandemic and found 24 with evidence of prior SARS-CoV-2 infection, including detectable neutralizing antibodies against multiple viral variants. We identified SARS-CoV-2-specific germinal center (GC) and memory B cells; single cell BCR sequencing showed that these virus-specific B cells were class-switched and somatically hypermutated, with overlapping clones in the adenoids and tonsils. Oropharyngeal tissues from COVID-19-convalescent children showed persistent expansion of GC and anti-viral lymphocyte populations associated with an IFN-γ-type response, with particularly prominent changes in the adenoids, as well as evidence of persistent viral RNA in both tonsil and adenoid tissues of many participants. Our results show robust, tissue-specific adaptive immune responses to SARS-CoV-2 in the upper respiratory tract of children weeks to months after acute infection, providing evidence of persistent localized immunity to this respiratory virus.
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Over the years, structure-based design programs and specifically docking small molecules to proteins have become prominent in drug discovery. However, many of these computational tools have been developed to primarily dock enzyme inhibitors (and ligands to other protein classes) relying heavily on hydrogen bonds and electrostatic and hydrophobic interactions. In reality, many drug targets either feature metal ions, can be targeted covalently, or are simply not even proteins (e.g., nucleic acids). Herein, we describe several new features that we have implemented into Fitted to broaden its applicability to a wide range of covalent enzyme inhibitors and to metalloenzymes, where metal coordination is essential for drug binding. This updated version of our docking program was tested for its ability to predict the correct binding mode of drug-sized molecules in a large variety of proteins. We also report new datasets that were essential to demonstrate areas of success and those where additional efforts are required. This resource could be used by other program developers to assess their own software.
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Proteínas , Software , Ligação de Hidrogênio , Ligantes , Substâncias Macromoleculares/química , Simulação de Acoplamento Molecular , Ligação Proteica , Proteínas/químicaRESUMO
CD4+ T cells have a remarkable potential to differentiate into diverse effector lineages following activation. Here, we probe the heterogeneity present among naive CD4+ T cells before encountering their cognate antigen to ask whether their effector potential is modulated by pre-existing transcriptional and chromatin landscape differences. Single-cell RNA sequencing shows that key drivers of variability are genes involved in T cell receptor (TCR) signaling. Using CD5 expression as a readout of the strength of tonic TCR interactions with self-peptide MHC, and sorting on the ends of this self-reactivity spectrum, we find that pre-existing transcriptional differences among naive CD4+ T cells impact follicular helper T (TFH) cell versus non-TFH effector lineage choice. Moreover, our data implicate TCR signal strength during thymic development in establishing differences in naive CD4+ T cell chromatin landscapes that ultimately shape their effector potential.
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Linfócitos T CD4-Positivos/imunologia , Diferenciação Celular , Cromatina/fisiologia , Ativação Linfocitária/imunologia , Coriomeningite Linfocítica/imunologia , Receptores de Antígenos de Linfócitos T/imunologia , Linfócitos T Auxiliares-Indutores/imunologia , Animais , Linfócitos T CD4-Positivos/metabolismo , Feminino , Perfilação da Expressão Gênica , Coriomeningite Linfocítica/genética , Coriomeningite Linfocítica/metabolismo , Coriomeningite Linfocítica/virologia , Vírus da Coriomeningite Linfocítica/imunologia , Masculino , Camundongos Endogâmicos C57BL , Receptores de Antígenos de Linfócitos T/metabolismoRESUMO
COVID-19 exhibits extensive patient-to-patient heterogeneity. To link immune response variation to disease severity and outcome over time, we longitudinally assessed circulating proteins as well as 188 surface protein markers, transcriptome, and T cell receptor sequence simultaneously in single peripheral immune cells from COVID-19 patients. Conditional-independence network analysis revealed primary correlates of disease severity, including gene expression signatures of apoptosis in plasmacytoid dendritic cells and attenuated inflammation but increased fatty acid metabolism in CD56dimCD16hi NK cells linked positively to circulating interleukin (IL)-15. CD8+ T cell activation was apparent without signs of exhaustion. Although cellular inflammation was depressed in severe patients early after hospitalization, it became elevated by days 17-23 post symptom onset, suggestive of a late wave of inflammatory responses. Furthermore, circulating protein trajectories at this time were divergent between and predictive of recovery versus fatal outcomes. Our findings stress the importance of timing in the analysis, clinical monitoring, and therapeutic intervention of COVID-19.
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COVID-19/imunologia , Citocinas/metabolismo , Células Dendríticas/metabolismo , Expressão Gênica/imunologia , Células Matadoras Naturais/metabolismo , Índice de Gravidade de Doença , Adulto , Idoso , Idoso de 80 Anos ou mais , Biomarcadores/metabolismo , COVID-19/mortalidade , Estudos de Casos e Controles , Células Dendríticas/citologia , Feminino , Humanos , Células Matadoras Naturais/citologia , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Transcriptoma/imunologia , Adulto JovemRESUMO
Personalized cancer vaccines are a promising approach for inducing T cell immunity to tumor neoantigens. Using a self-assembling nanoparticle vaccine that links neoantigen peptides to a Toll-like receptor 7/8 agonist (SNP-7/8a), we show how the route and dose alter the magnitude and quality of neoantigen-specific CD8+ T cells. Intravenous vaccination (SNP-IV) induced a higher proportion of TCF1+PD-1+CD8+ T cells as compared to subcutaneous immunization (SNP-SC). Single-cell RNA sequencing showed that SNP-IV induced stem-like genes (Tcf7, Slamf6, Xcl1) whereas SNP-SC enriched for effector genes (Gzmb, Klrg1, Cx3cr1). Stem-like cells generated by SNP-IV proliferated and differentiated into effector cells upon checkpoint blockade, leading to superior antitumor response as compared to SNP-SC in a therapeutic model. The duration of antigen presentation by dendritic cells controlled the magnitude and quality of CD8+ T cells. These data demonstrate how to optimize antitumor immunity by modulating vaccine parameters for specific generation of effector or stem-like CD8+ T cells.
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Antígenos de Neoplasias/imunologia , Linfócitos T CD8-Positivos/imunologia , Vacinas Anticâncer/administração & dosagem , Fator 1-alfa Nuclear de Hepatócito/análise , Nanopartículas , Animais , Apresentação de Antígeno , Vacinas Anticâncer/imunologia , Células Dendríticas/imunologia , Feminino , Imunidade Inata , Camundongos , Camundongos Endogâmicos C57BL , VacinaçãoRESUMO
Responses to vaccination and to diseases vary widely across individuals, which may be partly due to baseline immune variations. Identifying such baseline predictors of immune responses and their biological basis is of broad interest, given their potential importance for cancer immunotherapy, disease outcomes, vaccination and infection responses. Here we uncover baseline blood transcriptional signatures predictive of antibody responses to both influenza and yellow fever vaccinations in healthy subjects. These same signatures evaluated at clinical quiescence are correlated with disease activity in patients with systemic lupus erythematosus with plasmablast-associated flares. CITE-seq profiling of 82 surface proteins and transcriptomes of 53,201 single cells from healthy high and low influenza vaccination responders revealed that our signatures reflect the extent of activation in a plasmacytoid dendritic cell-type I IFN-T/B lymphocyte network. Our findings raise the prospect that modulating such immune baseline states may improve vaccine responsiveness and mitigate undesirable autoimmune disease activity.
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Imunidade Adaptativa/genética , Formação de Anticorpos/genética , Vacinas contra Influenza/imunologia , Lúpus Eritematoso Sistêmico/imunologia , Transcriptoma , Vacina contra Febre Amarela/imunologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Linfócitos B , Criança , Pré-Escolar , Estudos de Coortes , Feminino , Perfilação da Expressão Gênica , Humanos , Influenza Humana/prevenção & controle , Lúpus Eritematoso Sistêmico/genética , Lúpus Eritematoso Sistêmico/patologia , Masculino , Pessoa de Meia-Idade , Transcriptoma/imunologia , Vacinação , Febre Amarela/prevenção & controle , Adulto JovemRESUMO
Disrupted molecular pathways are often robustly associated with disease outcome in cancer1-3. Although biologically informative transcriptional pathways can be revealed by RNA sequencing (RNA-seq) at up to hundreds of folds reduction in conventionally used coverage4-6, it remains unknown how low-depth sequencing datasets perform in the challenging context of developing transcriptional signatures to predict clinical outcomes. Here we assessed the possibility of cancer prognosis with shallow tumor RNA-seq, which would potentially enable cost-effective assessment of much larger numbers of samples for deeper biological and predictive insights. By statistically modeling the relative risk of an adverse outcome for thousands of subjects in The Cancer Genome Atlas7-13, we present evidence that subsampled tumor RNA-seq data with a few hundred thousand reads per sample provide sufficient information for outcome prediction in several types of cancer. Analysis of predictive models revealed robust contributions from pathways known to be associated with outcomes. Our findings indicate that predictive models of outcomes in cancer may be developed with dramatically increases in sample numbers at low cost, thus potentially enabling the development of more realistic predictive models that incorporate diverse variables and their interactions. This strategy could also be used, for example, in longitudinal analysis of multiple regions of a tumor alongside treatment for quantitative modeling and prediction of outcome in personalized oncology.
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Neoplasias/diagnóstico , Neoplasias/genética , Prognóstico , Análise de Sequência de RNA/métodos , Biologia Computacional/métodos , Perfilação da Expressão Gênica , Genoma Humano , Humanos , Modelos Lineares , Aprendizado de Máquina , Modelos Genéticos , Medicina de Precisão , Modelos de Riscos Proporcionais , RNA , Reprodutibilidade dos Testes , Resultado do TratamentoRESUMO
Lymphoid tissue inducer (LTi) cells are regarded as a subset of innate lymphoid cells (ILCs). However, these cells are not derived from the ILC common progenitor, which generates other ILC subsets and is defined by the expression of the transcription factor PLZF. Here, we examined transcription factor(s) determining the fate of LTi progenitors versus non-LTi ILC progenitors. Conditional deletion of Gata3 resulted in the loss of PLZF+ non-LTi progenitors but not the LTi progenitors that expressed the transcription factor RORγt. Consistently, PLZF+ non-LTi progenitors expressed high amounts of GATA3, whereas GATA3 expression was low in RORγt+ LTi progenitors. The generation of both progenitors required the transcriptional regulator Id2, which defines the common helper-like innate lymphoid progenitor (ChILP), but not cytokine signaling. Nevertheless, low GATA3 expression was necessary for the generation of functionally mature LTi cells. Thus, differential expression of GATA3 determines the fates and functions of distinct ILC progenitors.
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Fator de Transcrição GATA3/biossíntese , Células-Tronco/citologia , Subpopulações de Linfócitos T/citologia , Linfócitos T Auxiliares-Indutores/citologia , Linfócitos T Auxiliares-Indutores/imunologia , Animais , Linhagem da Célula/imunologia , Células Cultivadas , Fator de Transcrição GATA3/genética , Proteína 2 Inibidora de Diferenciação/metabolismo , Subunidade gama Comum de Receptores de Interleucina/genética , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Membro 3 do Grupo F da Subfamília 1 de Receptores Nucleares/biossíntese , Receptor de Morte Celular Programada 1/biossíntese , Proteína com Dedos de Zinco da Leucemia Promielocítica/biossíntese , Células-Tronco/imunologia , Subpopulações de Linfócitos T/imunologiaRESUMO
Nearly all chronic human infections are associated with alterations in the memory B cell (MBC) compartment, including a large expansion of CD19hiT-bethi MBC in the peripheral blood of HIV-infected individuals with chronic viremia. Despite their prevalence, it is unclear how these B cells arise and whether they contribute to the inefficiency of antibody-mediated immunity in chronic infectious diseases. We addressed these questions by characterizing T-bet-expressing B cells in lymph nodes (LN) and identifying a strong T-bet signature among HIV-specific MBC associated with poor immunologic outcome. Confocal microscopy and quantitative imaging revealed that T-bethi B cells in LN of HIV-infected chronically viremic individuals distinctly accumulated outside germinal centers (GC), which are critical for optimal antibody responses. In single-cell analyses, LN T-bethi B cells of HIV-infected individuals were almost exclusively found among CD19hi MBC and expressed reduced GC-homing receptors. Furthermore, HIV-specific B cells of infected individuals were enriched among LN CD19hiT-bethi MBC and displayed a distinct transcriptome, with features similar to CD19hiT-bethi MBC in blood and LN GC B cells (GCBC). LN CD19hiT-bethi MBC were also related to GCBC by B cell receptor (BCR)-based phylogenetic linkage but had lower BCR mutation frequencies and reduced HIV-neutralizing capacity, consistent with diminished participation in GC-mediated affinity selection. Thus, in the setting of chronic immune activation associated with HIV viremia, failure of HIV-specific B cells to enter or remain in GC may help explain the rarity of high-affinity protective antibodies.