Computational methods for identification of cell populations from polychromatic flow cytometry data are changing the paradigm of cytometry bioinformatics. Data clustering is the most common computational approach to unsupervised identification of cell populations from multidimensional cytometry data. However, interpretation of the identified data clusters is labor-intensive. Certain types of user-defined cell populations are also difficult to identify by fully automated data clustering analysis. Both are roadblocks before a cytometry lab can adopt the data clustering approach for cell population identification in routine use. We found that combining recursive data filtering and clustering with constraints converted from the user manual gating strategy can effectively address these two issues. We named this new approach DAFi: Directed Automated Filtering and Identification of cell populations. Design of DAFi preserves the data-driven characteristics of unsupervised clustering for identifying novel cell subsets, but also makes the results interpretable to experimental scientists through mapping and merging the multidimensional data clusters into the user-defined two-dimensional gating hierarchy. The recursive data filtering process in DAFi helped identify small data clusters which are otherwise difficult to resolve by a single run of the data clustering method due to the statistical interference of the irrelevant major clusters. Our experiment results showed that the proportions of the cell populations identified by DAFi, while being consistent with those by expert centralized manual gating, have smaller technical variances across samples than those from individual manual gating analysis and the nonrecursive data clustering analysis. Compared with manual gating segregation, DAFi-identified cell populations avoided the abrupt cut-offs on the boundaries. DAFi has been implemented to be used with multiple data clustering methods including K-means, FLOCK, FlowSOM, and the ClusterR package. For cell population identification, DAFi supports multiple options including clustering, bisecting, slope-based gating, and reversed filtering to meet various autogating needs from different scientific use cases. © 2018 International Society for Advancement of Cytometry.

DNA sequence-based typing at the HLA-A, -B, -C, -DPB1, -DQA1, -DQB1, and -DRB1 loci was performed on 714 healthy adult blood bank donors from Colombo, Sri Lanka, to characterize allele frequencies in support of studies on T cell immunity against pathogens, including Dengue virus. Deviations from Hardy Weinberg proportions were not detected at any locus. Several alleles were found in >30% of individuals, including the class II alleles DPB1 * 04:01, DPB1 * 02:01, DQB1 * 06:01 and DRB1 * 07:01, and the class I alleles A * 33:03 and A * 24:02. Genotype data will be available in the Allele Frequencies Net Database.

A diagnosis of motor Parkinson's disease (PD) is preceded by a prolonged premotor phase with accumulating neuronal damage. Here we examined the temporal relation between α-synuclein (α-syn) T cell reactivity and PD. A longitudinal case study revealed that elevated α-syn-specific T cell responses were detected prior to the diagnosis of motor PD, and declined after. The relationship between T cell reactivity and early PD in two independent cohorts showed that α-syn-specific T cell responses were highest shortly after diagnosis of motor PD and then decreased. Additional analysis revealed significant association of α-syn-specific T cell responses with age and lower levodopa equivalent dose. These results confirm the presence of α-syn-reactive T cells in PD and show that they are most abundant immediately after diagnosis of motor PD. These cells may be present years before the diagnosis of motor PD, suggesting avenues of investigation into PD pathogenesis and potential early diagnosis.

Background and objectives

Parkinson's disease (PD) is associated with a heightened inflammatory state, including activated T cells. However, it is unclear whether these PD T cell responses are antigen specific or more indicative of generalized hyperresponsiveness. Our objective was to measure and compare antigen-specific T cell responses directed towards antigens derived from commonly encountered human pathogens/vaccines in patients with PD and age-matched healthy controls (HC).

Methods

Peripheral blood mononuclear cells (PBMCs) from 20 PD patients and 19 age-matched HCs were screened. Antigen specific T cell responses were measured by flow cytometry using a combination of the activation induced marker (AIM) assay and intracellular cytokine staining.

Results

Here we show that both PD patients and HCs show similar T cell activation levels to several antigens derived from commonly encountered human pathogens/vaccines in the general population. Similarly, we also observed no difference between HC and PD in the levels of CD4 and CD8 T cell derived cytokines produced in response to any of the common antigens tested. These antigens encompassed both viral (coronavirus, rhinovirus, respiratory syncytial virus, influenza, cytomegalovirus) and bacterial (pertussis, tetanus) targets.

Conclusions

These results suggest the T cell dysfunction observed in PD may not extend itself to abnormal responses to commonly encountered or vaccine-target antigens. Our study supports the notion that the targets of inflammatory T cell responses in PD may be more directed towards autoantigens like α-synuclein (α-syn) rather than common foreign antigens.

Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state >4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (T_H17) cell-like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state-uniquely identifiable with multimodal analysis-from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.

Although only a small fraction will ever develop the active form of tuberculosis (ATB) disease, chemoprophylaxis treatment in latent TB infected (LTBI) individuals is an effective strategy to control pathogen transmission. Characterizing immune responses in LTBI upon chemoprophylactic treatment is important to facilitate treatment monitoring, and thus improve TB control strategies. Here, we studied changes in the blood transcriptome in a cohort of 42 LTBI and 8 ATB participants who received anti-TB therapy. Based on the expression of previously published gene signatures of progression to ATB, we stratified the LTBI cohort in two groups and examined if individuals deemed to be at elevated risk of developing ATB before treatment (LTBI-Risk) differed from others (LTBI-Other). We found that LTBI-Risk and LTBI-Other groups were associated with two distinct transcriptomic treatment signatures, with the LTBI-Risk signature resembling that of treated ATB patients. Notably, overlapping genes between LTBI-Risk and ATB treatment signatures were associated with risk of progression to ATB and interferon (IFN) signaling, and were selectively downregulated upon treatment in the LTBI-Risk but not the LTBI-Other group. Our results suggest that transcriptomic reprogramming following treatment of LTBI is heterogeneous and can be used to distinguish LTBI-Risk individuals from the LTBI cohort at large.

Zika virus (ZIKV) is a mosquito-borne pathogen that caused an epidemic in 2015-2016. ZIKV-specific T cell responses are functional in animal infection models, and helper CD4 T cells promote avid Abs in the vaccine context. The small volumes of blood available from field research limit the determination of T cell epitopes for complex microbes such as ZIKV. The goal of this project was efficient determination of human ZIKV CD4 T cell epitopes at the whole proteome scale, including validation of reactivity to whole pathogen, using small blood samples from convalescent time points when T cell response magnitude may have waned. Polyclonal enrichment of candidate ZIKV-specific CD4 T cells used cell-associated virus, documenting that T cells in downstream peptide analyses also recognize whole virus after Ag processing. Sequential query of bulk ZIKV-reactive CD4 T cells with pooled/single ZIKV peptides and molecularly defined APC allowed precision epitope and HLA restriction assignments across the ZIKV proteome and enabled discovery of numerous novel ZIKV CD4 T cell epitopes. The research workflow is useful for the study of emerging infectious diseases with a very limited human blood sample availability.

Antigen-specific CD4 and CD8 T cells are important components of the immune response to Mycobacterium tuberculosis, yet little information is currently known regarding how the breadth, specificity, phenotype, and function of M. tuberculosis-specific T cells correlate with M. tuberculosis infection outcome in humans. To facilitate evaluation of human M. tuberculosis-specific T cell responses targeting multiple different Ags, we sought to develop a high throughput and reproducible T cell response spectrum assay requiring low blood sample volumes. We describe here the optimization and standardization of a microtiter plate-based, diluted whole blood stimulation assay utilizing overlapping peptide pools corresponding to a functionally diverse panel of 60 M. tuberculosis Ags. Using IFN-γ production as a readout of Ag specificity, the assay can be conducted using 50 μl of blood per test condition and can be expanded to accommodate additional Ags. We evaluated the intra- and interassay variability, and implemented testing of the assay in diverse cohorts of M. tuberculosis-unexposed healthy adults, foreign-born adults with latent M. tuberculosis infection residing in the United States, and tuberculosis household contacts with latent M. tuberculosis infection in a tuberculosis-endemic setting in Kenya. The M. tuberculosis-specific T cell response spectrum assay further enhances the immunological toolkit available for evaluating M. tuberculosis-specific T cell responses across different states of M. tuberculosis infection, and can be readily implemented in resource-limited settings. Moreover, application of the assay to longitudinal cohorts will facilitate evaluation of treatment- or vaccine-induced changes in the breadth and specificity of Ag-specific T cell responses, as well as identification of M. tuberculosis-specific T cell responses associated with M. tuberculosis infection outcomes.