Holden T. Maecker

The tetraspanin superfamily: molecular facilitators.

A legacy of molecular evolution is the formation of gene families encoding proteins that often serve related functions. One such family gaining recent attention is the tetraspanin superfamily, whose membership has grown to nearly 20 known genes since its discovery in 1990. All encode cell‐surface proteins that span the membrane four times, forming two extracellular loops. Some of these genes are found in organisms as primitive as schistosomes and nematodes. Alternately known as the transmembrane 4 (TM4) superfamily or the TM4SF, 4TM, or terraspan family, we propose here that the name tetraspanins be used for the purpose of standardization. What do the tetraspanins do? Awaiting definitive functional studies, we can only put together pieces of a puzzle that has been built by raising antibodies against these proteins and looking at their distribution, associations, and functions. A brief overview indicates that some tetraspanins are found in virtually all tissues (CD81, CD82, CD9, CD63), whereas others are highly restricted, such as CD37 (B cells) or CD53 (lymphoid and myeloid cells). Many of these proteins have a flair for promiscuous associations with other molecules, including lineage‐specific proteins, integrins, and other tetraspanins. In terms of function, they are involved in diverse processes such as cell activation and proliferation, adhesion and motility, differentiation, and cancer. We propose that these functions may all relate to their ability to act as “molecular facilitators,” grouping specific cell‐surface proteins and thus increasing the formation and stability of functional signaling complexes.—Maecker, H. T., Todd, S. C., Levy, S. The tetraspanin superfamily: molecular facilitators. FASEB J. 11, 428–442 (1997)

Use of overlapping peptide mixtures as antigens for cytokine flow cytometry

Intracellular cytokine staining and flow cytometry can be used to measure T-cell responses to defined antigens. Although CD8+ T-cell responses to soluble proteins are inefficiently detected by this approach, peptides can be used as antigens. Using overlapping peptides spanning an entire protein sequence, CD8+ T-cell responses can be detected to multiple epitopes, regardless of HLA type. In this study, overlapping peptide mixes of various lengths were compared and 15 amino acid peptides with 11 amino acid overlaps were found to stimulate both CD4+ and CD8+ T-cell responses. Such peptide mixes stimulated CD4+ T-cell responses equivalent to those observed with whole recombinant protein, while simultaneously stimulating CD8+ T-cell responses much higher than those observed with whole protein. Although 8-12 amino acid peptides produced the highest level of CD8+ T-cell responses, 15 amino acid peptides were still very effective. Peptides that were 20 amino acids in length, however, did not stimulate strong CD8+ T-cell responses at the same peptide dose. The cytokine responses to individual epitopes added up approximately to the response to the entire mix, demonstrating that large mixes can detect responses in a quantitative fashion. Unlike whole protein antigens, peptide mixes were effective at stimulating responses in both cryopreserved PBMC and blood stored for 24 h at room temperature. Thus, overlapping 15 amino acid peptide mixes may facilitate the analysis of antigen-specific CD4+ and CD8+ T-cell responses by cytokine flow cytometry, using clinical specimens that include shipped blood or cryopreserved PBMC.

Variation in the human immune system is largely driven by non-heritable influences

There is considerable heterogeneity in immunological parameters between individuals, but its sources are largely unknown. To assess the relative contribution of heritable versus non-heritable factors, we have performed a systems-level analysis of 210 healthy twins between 8 and 82 years of age. We measured 204 different parameters, including cell population frequencies, cytokine responses, and serum proteins, and found that 77% of these are dominated (>50% of variance) and 58% almost completely determined (>80% of variance) by non-heritable influences. In addition, some of these parameters become more variable with age, suggesting the cumulative influence of environmental exposure. Similarly, the serological responses to seasonal influenza vaccination are also determined largely by non-heritable factors, likely due to repeated exposure to different strains. Lastly, in MZ twins discordant for cytomegalovirus infection, more than half of all parameters are affected. These results highlight the largely reactive and adaptive nature of the immune system in healthy individuals.

Peanut oral immunotherapy results in increased antigen-induced regulatory T-cell function and hypomethylation of forkhead box protein 3 (FOXP3)

BACKGROUND The mechanisms contributing to clinical immune tolerance remain incompletely understood. This study provides evidence for specific immune mechanisms that are associated with a model of operationally defined clinical tolerance. OBJECTIVE Our overall objective was to study laboratory changes associated with clinical immune tolerance in antigen-induced T cells, basophils, and antibodies in subjects undergoing oral immunotherapy (OIT) for peanut allergy. METHODS In a phase 1 single-site study, we studied participants (n = 23) undergoing peanut OIT and compared them with age-matched allergic control subjects (n = 20) undergoing standard of care (abstaining from peanut) for 24 months. Participants were operationally defined as clinically immune tolerant (IT) if they had no detectable allergic reactions to a peanut oral food challenge after 3 months of therapy withdrawal (IT, n = 7), whereas those who had an allergic reaction were categorized as nontolerant (NT; n = 13). RESULTS Antibody and basophil activation measurements did not statistically differentiate between NT versus IT participants. However, T-cell function and demethylation of forkhead box protein 3 (FOXP3) CpG sites in antigen-induced regulatory T cells were significantly different between IT versus NT participants. When IT participants were withdrawn from peanut therapy for an additional 3 months (total of 6 months), only 3 participants remained classified as IT participants, and 4 participants regained sensitivity along with increased methylation of FOXP3 CpG sites in antigen-induced regulatory T cells. CONCLUSION In summary, modifications at the DNA level of antigen-induced T-cell subsets might be predictive of a state of operationally defined clinical immune tolerance during peanut OIT.

Genetic and Environmental Determinants of Human NK Cell Diversity Revealed by Mass Cytometry

Both genetics and environment contribute to human NK cell diversity. NK Cell Nature Versus Nurture Natural killer (NK) cells were first discovered because of their ability to kill tumor cells without any previous exposure. However, this population is actually quite heterogeneous: Different subgroups of NK cells express different combinations of activating and inhibiting receptors that govern their specificity. Now, Horowitz et al. use mass cytometry to examine NK cell diversity in humans. The authors examined 35 parameters simultaneously in 5 sets of monozygotic twins as well as 12 unrelated donors. They found up to 30,000 phenotypic NK cell populations in a given individual. What’s more, by comparing the twins versus unrelated donors, they determined that although genetics primarily determined inhibitory receptor expression, activating receptors were controlled by the environment. These data suggest that inhibitory receptors may contribute more to NK cell self-tolerance, whereas activating receptors may guide response to pathogens and tumors. Natural killer (NK) cells play critical roles in immune defense and reproduction, yet remain the most poorly understood major lymphocyte population. Because their activation is controlled by a variety of combinatorially expressed activating and inhibitory receptors, NK cell diversity and function are closely linked. To provide an unprecedented understanding of NK cell repertoire diversity, we used mass cytometry to simultaneously analyze 37 parameters, including 28 NK cell receptors, on peripheral blood NK cells from 5 sets of monozygotic twins and 12 unrelated donors of defined human leukocyte antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) genotype. This analysis revealed a remarkable degree of NK cell diversity, with an estimated 6000 to 30,000 phenotypic populations within an individual and >100,000 phenotypes in the donor panel. Genetics largely determined inhibitory receptor expression, whereas activation receptor expression was heavily environmentally influenced. Therefore, NK cells may maintain self-tolerance through strictly regulated expression of inhibitory receptors while using adaptable expression patterns of activating and costimulatory receptors to respond to pathogens and tumors. These findings further suggest the possibility that discrete NK cell subpopulations could be harnessed for immunotherapeutic strategies in the settings of infection, reproduction, and transplantation.

mTOR inhibition improves immune function in the elderly

mTOR inhibition by RAD001 improves immune responses in elderly volunteers receiving an influenza vaccination. mTOR and Human Aging Inhibition of mTOR signaling extends life span and delays the onset of aging-related diseases in all species studied to date. These findings suggest that the mTOR pathway regulates aging. However, it is unknown if mTOR inhibition has beneficial effects on aging in humans. To begin to address this question, Mannick et al. evaluated the effects of the mTOR inhibitor RAD001 on the decline in immune function that occurs during aging in humans. Their findings suggest that RAD001 improved immune function in elderly volunteers as assessed by response to influenza vaccination. It remains to be determined whether mTOR inhibition improves additional aging-related conditions in humans. Inhibition of the mammalian target of rapamycin (mTOR) pathway extends life span in all species studied to date, and in mice delays the onset of age-related diseases and comorbidities. However, it is unknown if mTOR inhibition affects aging or its consequences in humans. To begin to assess the effects of mTOR inhibition on human aging-related conditions, we evaluated whether the mTOR inhibitor RAD001 ameliorated immunosenescence (the decline in immune function during aging) in elderly volunteers, as assessed by their response to influenza vaccination. RAD001 enhanced the response to the influenza vaccine by about 20% at doses that were relatively well tolerated. RAD001 also reduced the percentage of CD4 and CD8 T lymphocytes expressing the programmed death-1 (PD-1) receptor, which inhibits T cell signaling and is more highly expressed with age. These results raise the possibility that mTOR inhibition may have beneficial effects on immunosenescence in the elderly.

Bacillus Calmette-Guérin Vaccination of Human Newborns Induces T Cells with Complex Cytokine and Phenotypic Profiles

The immune response to vaccination with bacillus Calmette-Guérin (BCG), the only tuberculosis vaccine available, has not been fully characterized. We used multiparameter flow cytometry to examine specific T cell cytokine production and phenotypic profiles in blood from 10-wk-old infants routinely vaccinated with BCG at birth. Ex vivo stimulation of whole blood with BCG for 12 h induced expression of predominantly IFN-γ, IL-2, and TNF-α in CD4+ T cells in seven distinct cytokine combinations. IL-4 and IL-10 expression was detected in CD4+ T cells at low frequencies and only in cells that did not coexpress type 1 cytokines. Specific CD8+ T cells were less frequent than CD4+ T cells and produced mainly IFN-γ and/or IL-2 and less TNF-α, IL-4, and IL-10. Importantly, many mycobacteria-specific CD4+ and CD8+ T cells did not produce IFN-γ. The predominant phenotype of BCG-specific type 1 T cells was that of effector cells, i.e., CD45RA−CCR7−CD27+, which may reflect persistence of Mycobacterium bovis BCG in infants until 10 wk of age. Among five phenotypic patterns of CD4+ T cells, central memory cells were more likely to be IL-2+ and effector cells were more likely to be IFN-γ+. We concluded that neonatal vaccination with BCG induces T cells with a complex pattern of cytokine expression and phenotypes. Measuring IFN-γ production alone underestimates the magnitude and complexity of the host cytokine response to BCG vaccination and may not be an optimal readout in studies of BCG and novel tuberculosis vaccination.

Frequencies of Memory T Cells Specific for Varicella-Zoster Virus, Herpes Simplex Virus, and Cytomegalovirus by Intracellular Detection of Cytokine Expression

Memory T cells specific for varicella-zoster virus (VZV), herpes simplex virus (HSV), and human cytomegalovirus (HCMV) were compared in immune adults by intracellular cytokine (ICC) detection. The mean percentages of CD4+ T cells were 0.11% for VZV and 0.22% for HSV by interferon (IFN)-gamma production; the frequency for HCMV was significantly higher at 1.21%. Percentages of VZV-, HSV-, and HCMV-specific CD4+ T cells were similar by use of tumor necrosis factor (TNF)-alpha. HCMV-stimulated CD8+ T cells produced IFN-gamma (1.11%) and TNF-alpha (1.71%); VZV- and HSV-specific CD8+ T cells were not detectable. VZV CD4+ T cell numbers were similar in young adults with natural or vaccine-induced immunity. VZV CD4+ T cells were significantly less frequent in older adults. Secondary varicella immunization did not increase VZV-specific CD4+ T cell frequencies by ICC assay. Numbers of memory T cells specific for herpesviruses may vary with sites of viral latency and with host age.

Standardization of cytokine flow cytometry assays

BackgroundCytokine flow cytometry (CFC) or intracellular cytokine staining (ICS) can quantitate antigen-specific T cell responses in settings such as experimental vaccination. Standardization of ICS among laboratories performing vaccine studies would provide a common platform by which to compare the immunogenicity of different vaccine candidates across multiple international organizations conducting clinical trials. As such, a study was carried out among several laboratories involved in HIV clinical trials, to define the inter-lab precision of ICS using various sample types, and using a common protocol for each experiment (see additional files online).ResultsThree sample types (activated, fixed, and frozen whole blood; fresh whole blood; and cryopreserved PBMC) were shipped to various sites, where ICS assays using cytomegalovirus (CMV) pp65 peptide mix or control antigens were performed in parallel in 96-well plates. For one experiment, antigens and antibody cocktails were lyophilised into 96-well plates to simplify and standardize the assay setup. Results (CD4+cytokine+ cells and CD8+cytokine+ cells) were determined by each site. Raw data were also sent to a central site for batch analysis with a dynamic gating template.Mean inter-laboratory coefficient of variation (C.V.) ranged from 17–44% depending upon the sample type and analysis method. Cryopreserved peripheral blood mononuclear cells (PBMC) yielded lower inter-lab C.V.s than whole blood. Centralized analysis (using a dynamic gating template) reduced the inter-lab C.V. by 5–20%, depending upon the experiment. The inter-lab C.V. was lowest (18–24%) for samples with a mean of >0.5% IFNγ + T cells, and highest (57–82%) for samples with a mean of <0.1% IFNγ + cells.ConclusionICS assays can be performed by multiple laboratories using a common protocol with good inter-laboratory precision, which improves as the frequency of responding cells increases. Cryopreserved PBMC may yield slightly more consistent results than shipped whole blood. Analysis, particularly gating, is a significant source of variability, and can be reduced by centralized analysis and/or use of a standardized dynamic gating template. Use of pre-aliquoted lyophilized reagents for stimulation and staining can provide further standardization to these assays.

Flow cytometry controls, instrument setup, and the determination of positivity

A frequent goal of flow cytometric analysis is to classify cells as positive or negative for a given marker, or to determine the precise ratio of positive to negative cells. This requires good and reproducible instrument setup, and careful use of controls for analyzing and interpreting the data. The type of controls to include in various kinds of flow cytometry experiments is a matter of some debate and discussion. In this tutorial, we classify controls in various categories, describe the options within each category, and discuss the merits of each option.