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High-dimensional cell phenotyping is a powerful tool to study molecular and cellular changes in health and diseases. CyTOF enables high-dimensional cell phenotyping using tens of surface and intra-cellular markers. To utilize the full potential of CyTOF, we need advanced clustering and machine learning methodologies to enable automated gating of the complex data. Here we show that critical modifications to a machine learning based FlowSOM package and precise parameter optimization can enable us to reliably analyze the complex CyTOF data. We show the impact of key parameters on clustering outcomes while addressing bugs within the publicly available package. We modified the FlowSOM pipeline to fix the bugs, enable scalability to handle large datasets and perform parameter optimization. We further validated this modified pipeline on a substantial external immunological dataset demonstrating the need of data-specific tailored parameter optimization to ensure reliable definition and interrogation of immune cell populations associated with immune disorders. Optimized FlowSOM pipeline for reliable clustering of high-dimensional cytometry data. [ABSTRACT FROM AUTHOR]

High-dimensional cell phenotyping is a powerful tool to study molecular and cellular changes in health and diseases. CyTOF enables high-dimensional cell phenotyping using tens of surface and intra-cellular markers. To utilize the full potential of CyTOF, we need advanced clustering and machine learning methodologies to enable automated gating of the complex data. Here we show that critical modifications to a machine learning based FlowSOM package and precise parameter optimization can enable us to reliably analyze the complex CyTOF data. We show the impact of key parameters on clustering outcomes while addressing bugs within the publicly available package. We modified the FlowSOM pipeline to fix the bugs, enable scalability to handle large datasets and perform parameter optimization. We further validated this modified pipeline on a substantial external immunological dataset demonstrating the need of data-specific tailored parameter optimization to ensure reliable definition and interrogation of immune cell populations associated with immune disorders. [ABSTRACT FROM AUTHOR]

Seasonal influenza causes mild to severe respiratory infections and significant morbidity, especially in older adults. Transcriptomic analysis in populations across multiple flu seasons has provided insights into the molecular determinants of vaccine response. Still, the metabolic changes that underlie the immune response to influenza vaccination remain poorly characterized. We performed untargeted metabolomics to analyze plasma metabolites in a cohort of younger and older subjects before and after influenza vaccination to identify vaccine‐induced molecular signatures. Metabolomic and transcriptomic data were combined to define networks of gene and metabolic signatures indicative of high and low antibody response in these individuals. We observed age‐related differences in metabolic baselines and signatures of antibody response to influenza vaccination and the abundance of α‐linolenic and linoleic acids, sterol esters, fatty‐acylcarnitines, and triacylglycerol metabolism. We identified a metabolomic signature associated with age‐dependent vaccine response, finding increased tryptophan and decreased polyunsaturated fatty acids (PUFAs) in young high responders (HRs), while fatty acid synthesis and cholesteryl esters accumulated in older HRs. Integrated metabolomic and transcriptomic analysis shows that depletion of PUFAs, which are building blocks for prostaglandins and other lipid immunomodulators, in young HR subjects at Day 28 is related to a robust immune response to influenza vaccination. Increased glycerophospholipid levels were associated with an inflammatory response in older HRs to flu vaccination. This multi‐omics approach uncovered age‐related molecular markers associated with influenza vaccine response and provides insight into vaccine‐induced metabolic responses that may help guide development of more effective influenza vaccines. [ABSTRACT FROM AUTHOR]

Cerebrospinal fluid snapshot: The central nervous system (CNS) features mechanisms to protect against untoward inflammation yet allowing immune surveillance for pathogens. Pappalardo et al. profiled T cells in the cerebrospinal fluid (CSF) of healthy individuals and patients with multiple sclerosis (MS) using single-cell RNA and TCR sequences to define CNS immune homeostasis in both healthy donors and patients with MS. In healthy individuals, clonally expanded CSF T cells are largely distinct from those found in the blood with effector, IFNγ, and tissue adaptation signatures, whereas CSF T cells from patients with MS differ from healthy controls with a gene expression signature consistent with elevated activation and cytotoxicity. These findings provide insight into the unique immune environment in the CSF under normal and disease-associated conditions. T cells provide critical immune surveillance to the central nervous system (CNS), and the cerebrospinal fluid (CSF) is thought to be a main route for their entry. Further characterization of the state of T cells in the CSF in healthy individuals is important for understanding how T cells provide protective immune surveillance without damaging the delicate environment of the CNS and providing tissue-specific context for understanding immune dysfunction in neuroinflammatory disease. Here, we have profiled T cells in the CSF of healthy human donors and have identified signatures related to cytotoxic capacity and tissue adaptation that are further exemplified in clonally expanded CSF T cells. By comparing profiles of clonally expanded T cells obtained from the CSF of patients with multiple sclerosis (MS) and healthy donors, we report that clonally expanded T cells from the CSF of patients with MS have heightened expression of genes related to T cell activation and cytotoxicity. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) have been highly successful in the treatment of cancer. While PD-1 expression has been widely investigated, its role in CD4+ effector T cells in the setting of health and cancer remains unclear, particularly in the setting of glioblastoma multiforme (GBM), the most aggressive and common form of brain cancer. We examined the functional and molecular features of PD-1+CD4+CD25—CD127+Foxp3—effector cells in healthy subjects and in patients with GBM. In healthy subjects, we found that PD-1+CD4+ effector cells are dysfunctional: they do not proliferate but can secrete large quantities of IFNγ. Strikingly, blocking antibodies against PD-1 did not rescue proliferation. RNA-sequencing revealed features of exhaustion in PD-1+ CD4 effectors. In the context of GBM, tumors were enriched in PD-1+ CD4+ effectors that were similarly dysfunctional and unable to proliferate. Furthermore, we found enrichment of PD-1+TIM-3+ CD4+ effectors in tumors, suggesting that co-blockade of PD-1 and TIM-3 in GBM may be therapeutically beneficial. RNA-sequencing of blood and tumors from GBM patients revealed distinct differences between CD4+ effectors from both compartments with enrichment in multiple gene sets from tumor infiltrating PD-1—CD4+ effectors cells. Enrichment of these gene sets in tumor suggests a more metabolically active cell state with signaling through other co-receptors. PD-1 expression on CD4 cells identifies a dysfunctional subset refractory to rescue with PD-1 blocking antibodies, suggesting that the influence of immune checkpoint inhibitors may involve recovery of function in the PD-1—CD4+ T cell compartment. Additionally, co-blockade of PD-1 and TIM-3 in GBM may be therapeutically beneficial. [ABSTRACT FROM AUTHOR]

Motivation: Sources of variability in experimentally derived data include measurement error in addition to the physical phenomena of interest. This measurement error is a combination of systematic components, originating from the measuring instrument and random measurement errors. Several novel biological technologies, such as mass cytometry and single-cell RNA-seq (scRNA-seq), are plagued with systematic errors that may severely affect statistical analysis if the data are not properly calibrated. Results: We propose a novel deep learning approach for removing systematic batch effects. Our method is based on a residual neural network, trained to minimize the Maximum Mean Discrepancy between the multivariate distributions of two replicates, measured in different batches. We apply our method to mass cytometry and scRNA-seq datasets, and demonstrate that it effectively attenuates batch effects. [ABSTRACT FROM AUTHOR]

Analysis of multiplexed assays is highly important for clinical diagnostics and other analytical applications. Mass cytometry enables multi-dimensional, single-cell analysis of cell type and state. In mass cytometry, the rare earth metals used as reporters on antibodies allow determination of marker expression in individual cells. Barcode-based bioassays for CyTOF are able to encode and decode for different experimental conditions or samples within the same experiment, facilitating progress in producing straightforward and consistent results. Herein, an integrated protocol for automated sample preparation for barcoding used in conjunction with mass cytometry for clinical bioanalysis samples is described; we offer results of our work with barcoding protocol optimization. In addition, we present some points to be considered in order to minimize the variability of quantitative mass cytometry measurements. For example, we discuss the importance of having multiple populations during titration of the antibodies and effect of storage and shipping of labelled samples on the stability of staining for purposes of CyTOF analysis. Data quality is not affected when labelled samples are stored either frozen or at 4 °C and used within 10 days; we observed that cell loss is greater if cells are washed with deionized water prior to shipment or are shipped in lower concentration. Once the labelled samples for CyTOF are suspended in deionized water, the analysis should be performed expeditiously, preferably within the first hour. Damage can be minimized if the cells are resuspended in phosphate-buffered saline (PBS) rather than deionized water while waiting for data acquisition. [ABSTRACT FROM AUTHOR]

T cell-B cell interaction is the key immune response to protect the host from severe viral infection. However, how T cells support B cells to exert protective humoral immunity in humans is not well understood. Here, we use COVID-19 as a model of acute viral infections and analyze CD4+ T cell subsets associated with plasmablast expansion and clinical outcome. Peripheral helper T cells (Tph cells; denoted as PD-1highCXCR5–CD4+ T cells) are significantly increased, as are plasmablasts. Tph cells exhibit "B cell help" signatures and induce plasmablast differentiation in vitro. Interestingly, expanded plasmablasts show increased CXCR3 expression, which is positively correlated with higher frequency of activated Tph cells and better clinical outcome. Mechanistically, Tph cells help B cell differentiation and produce more interferon γ (IFNγ), which induces CXCR3 expression on plasmablasts. These results elucidate a role for Tph cells in regulating protective B cell response during acute viral infection. [Display omitted] • PD-1highCXCR5– Tph cells are increased in human acute viral infections • Expansions of Tph cells and plasmablasts (PBs) are features of early immune responses • Activated Tph cells and CXCR3+ PBs are linked to less severe clinical outcome • IFNγ from PD-1highCXCR5– Tph cells induces CXCR3 expression on PBs Asashima et al. report that peripheral helper T cells (denoted as PD-1highCXCR5–CD4+ T cells) are significantly increased in the acute phase of COVID-19, as are plasmablasts. Plasmablasts show increased CXCR3 expression, which is induced by IFNγ, and are positively correlated with activated Tph cells with better clinical outcome. [ABSTRACT FROM AUTHOR]

Leptospirosis causes significant morbidity and mortality worldwide; however, the role of the host immune response in disease progression and high case fatality (>10–50%) is poorly understood. We conducted a multi-parameter investigation of patients with acute leptospirosis to identify mechanisms associated with case fatality. Whole blood transcriptional profiling of 16 hospitalized Brazilian patients with acute leptospirosis (13 survivors, 3 deceased) revealed fatal cases had lower expression of the antimicrobial peptide, cathelicidin, and chemokines, but more abundant pro-inflammatory cytokine receptors. In contrast, survivors generated strong adaptive immune signatures, including transcripts relevant to antigen presentation and immunoglobulin production. In an independent cohort (23 survivors, 22 deceased), fatal cases had higher bacterial loads (P = 0.0004) and lower anti-Leptospira antibody titers (P = 0.02) at the time of hospitalization, independent of the duration of illness. Low serum cathelicidin and RANTES levels during acute illness were independent risk factors for higher bacterial loads (P = 0.005) and death (P = 0.04), respectively. To investigate the mechanism of cathelicidin in patients surviving acute disease, we administered LL-37, the active peptide of cathelicidin, in a hamster model of lethal leptospirosis and found it significantly decreased bacterial loads and increased survival. Our findings indicate that the host immune response plays a central role in severe leptospirosis disease progression. While drawn from a limited study size, significant conclusions include that poor clinical outcomes are associated with high systemic bacterial loads, and a decreased antibody response. Furthermore, our data identified a key role for the antimicrobial peptide, cathelicidin, in mounting an effective bactericidal response against the pathogen, which represents a valuable new therapeutic approach for leptospirosis. [ABSTRACT FROM AUTHOR]

The mechanisms whereby immune therapies affect progression of type 1 diabetes (T1D) are not well understood. Teplizumab, an FcR nonbinding anti-CD3 mAb, has shown efficacy in multiple randomized clinical trials. We previously reported an increase in the frequency of circulating CD8+ central memory (CD8CM) T cells in clinical responders, but the generalizability of this finding and the molecular effects of teplizumab on these T cells have not been evaluated. We analyzed data from two randomized clinical studies of teplizumab in patients with new- and recent-onset T1D. At the conclusion of therapy, clinical responders showed a significant reduction in circulating CD4+ effector memory T cells. Afterward, there was an increase in the frequency and absolute number of CD8CM T cells. In vitro, teplizumab expanded CD8CM T cells by proliferation and conversion of non-CM T cells. Nanostring analysis of gene expression of CD8CM T cells from responders and nonresponders versus placebo-treated control subjects identified decreases in expression of genes associated with immune activation and increases in expression of genes associated with T-cell differentiation and regulation. We conclude that CD8CM T cells with decreased activation and regulatory gene expression are associated with clinical responses to teplizumab in patients with T1D. [ABSTRACT FROM AUTHOR]

The article focuses findings of a study on role of functional inflammatory profiles in distinguishing myelin-reactive T cells from patients with multiple sclerosis. It states that libraries derived from the CCR6+ T cells from patients with MS exhibited significantly enhanced production of interferon gamma, and mentions that transcriptomes of myelin-specific CCR6+ T cells from patients with MS were distinct. It infers that myelin-reactive T cells may act to limit disease progression.

We evaluated in vivo innate immune responses in monocyte populations from 67 young (aged 21-30 years) and older (aged ≥65 years) adults before and after influenza vaccination. CD14+CD16+ inflammatory monocytes were induced after vaccination in both young and older adults. In classical CD14+CD16- and inflammatory monocytes, production of tumor necrosis factor α and interleukin 6, as measured by intracellular staining, was strongly induced after vaccination. Cytokine production was strongly associated with influenza vaccine antibody response; the highest levels were found as late as day 28 after vaccination in young subjects and were substantially diminished in older subjects. Notably, levels of the anti-inflammatory cytokine interleukin 10 (IL-10) were markedly elevated in monocytes from older subjects before and after vaccination. In purified monocytes, we found age-associated elevation in phosphorylated signal transducer and activator of transcription-3, and decreased serine 359 phosphorylation of the negative IL-10 regulator dual-specificity phosphatase 1. These findings for the first time implicate dysregulated IL-10 production in impaired vaccine responses in older adults. [ABSTRACT FROM AUTHOR]

HTm4 is a member of a newly defined family of human and murine proteins, the MS4 (membrane-spanning four) protein group, which has a distinctive four-transmembrane structure. MS4 protein functions include roles as cell surface signaling receptors and intracellular adapter proteins. We have previously demonstrated that HTm4 regulates the function of the KAP phosphatase, a key regulator of cell cycle progression. In humans, the expression of HTm4 is largely restricted to cells of the hematopoietic lineage, possibly reflecting a causal role for this molecule in differentiation/proliferation of hematopoietic lineage cells. In this study, we show that, like the human homologue, murine HTm4 is also predominantly a hematopoietic protein with distinctive expression patterns in developing murine embryos and in adult animals. In addition, we observed that murine HTm4 is highly expressed in the developing and adult murine nervous system, suggesting a previously unrecognized role in central and peripheral nervous system development. [ABSTRACT FROM AUTHOR]

Migration toward pathology is the first critical step in stem cell engagement during regeneration. Neural stem cells (NSCs) migrate through the parenchyma along nonstereotypical routes in a precise directed manner across great distances to injury sites in the CNS, where they might engage niches harboring local transiently expressed reparative signals. The molecular mechanisms for NSC mobilization have not been identified. Because NSCs seem to home similarly to pathologic sites derived from disparate etiologies, we hypothesized that the inflammatory response itself, a characteristic common to all, guides the behavior of potentially reparative cells. As proof of concept we show that human NSCs migrate in vivo (including from the contralateral hemisphere) toward an infarcted area (a representative CNS injury), where local astrocytes and endothelium up-regulate the inflammatory chemoattractant stromal cell-derived factor 1α (SDF-1α). NSCs express CXC chemokine receptor 4 (CXCR4), the cognate receptor for SDF-1α. Exposure of SDF-1α to quiescent NSCs enhances proliferation, promotes chain migration and transmigration, and activates intracellular molecular pathways mediating engagement CXCR4 blockade abrogates their pathology-directed chain migration, a developmentally relevant mode of tangential migration that if recapitulated, could explain homing along nonstereotypical paths. Our data implicate SDF-1α/CXCR4, representative of the inflammatory milieu characterizing many pathologies, as a pathway that activates NSC molecular programs during injury and suggest that inflammation may be viewed not simply as playing an adverse role but also as providing stimuli that recruit cells with a regenerative homeostasis-promoting capacity. CXCR4 expression within germinal zones suggests that NSC homing after injury and migration during development may invoke similar mechanisms. [ABSTRACT FROM AUTHOR]

Analyzes the impact of ethanol in the impairment of several tissues and the activation of protein kinase c in polymorphonuclear leukocyte superoxide anion production. Types of reagents used in the experiments done on the topic; Overview of protein kinase c activity; Potentiation of PMA-stimulated superoxide anion production by ethanol.

Given the heterogeneity seen in cell populations within biological systems, analysis of single cells is necessary for studying mechanisms that cannot be identified on a bulk population level. There are significant variations in the biological and physiological function of cell populations due to the functional differences within, as well as between, single species as a result of the specific proteome, transcriptome, and metabolome that are unique to each individual cell. Single-cell analysis proves crucial in providing a comprehensive understanding of the biological and physiological properties underlying human health and disease. Omics technologies can help to examine proteins (proteomics), RNA molecules (transcriptomics), and the chemical processes involving metabolites (metabolomics) in cells, in addition to genomes. In this review, we discuss the value of multiomics in drug discovery and the importance of single-cell multiomics measurements. We will provide examples of the benefits of applying single-cell omics technologies in drug discovery and development. Moreover, we intend to show how multiomics offers the opportunity to understand the detailed events which produce or prevent disease, and ways in which the separate omics disciplines complement each other to build a broader, deeper knowledge base. [ABSTRACT FROM AUTHOR]

The diagnosis and treatment of diseases such as cancer is becoming more accurate and specialized with the advent of precision medicine techniques, research and treatments. Reaching down to the cellular and even sub-cellular level, diagnostic tests can pinpoint specific, individual information from each patient, and guide providers to a more accurate plan of treatment. With this advanced knowledge, researchers and providers can better gauge the effectiveness of drugs, radiation, and other therapies, which is bound to lead to a more accurate, if not more positive, prognosis. As precision medicine becomes more established, new techniques, equipment, materials and testing methods will be required. Herein, we will examine the recent innovations in assays, devices and software, along with next generation sequencing in genomics diagnostics which are in use or are being developed for personalized medicine. So as to avoid duplication and produce the fullest possible benefit, all involved must be strongly encouraged to collaborate, across national borders, public and private sectors, science, medicine and academia alike. In this paper we will offer recommendations for tools, research and development, along with ideas for implementation. We plan to begin with discussion of the lessons learned to date, and the current research on pharmacogenomics. Given the steady stream of advances in imaging mass spectrometry and nanoLC-MS/MS, and use of genomic, proteomic and metabolomics biomarkers to distinguish healthy tissue from diseased cells, there is great potential to utilize pharmacogenomics to tailor a drug or drugs to a particular cohort of patients. Such efforts very well may bring increased hope for small groups of non-responders and those who have demonstrated adverse reactions to current treatments. [ABSTRACT FROM AUTHOR]

Correction for ‘Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting’ by Coleman Murray et al., Lab Chip, 2018, 18, 2396–2409. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Cathelicidin Insufficiency in Patients with Fatal Leptospirosis" that appeared in a previous issue.