T cells residing in mucosal tissues play important roles in homeostasis and defense against microbial pathogens. The gut and female reproductive tract (FRT) are both tolerogenic environments, but they differ in the kinds of foreign Ags they need to tolerate. How these different environments influence the properties of their T cells is poorly understood, but important for understanding women’s health. We recruited antiretroviral therapy–suppressed women living with HIV who donated, within one visit, blood and tissue samples from the ileum, colon, rectosigmoid, endometrium, endocervix, and ectocervix. With these samples, we conducted 36-parameter cytometry by time of flight phenotyping of T cells. Although gut and FRT T cells shared features discriminating them from their blood counterparts, they also harbored features distinguishing them from one another. These included increased proportions of CD69+ T resident memory cells of the T effector memory phenotype, as well as preferential coexpression of CD69 and CD103, on the gut-derived cells. In contrast, CD69+CD103+ T resident memory CD8+ T cells from FRT, but not those from gut, preferentially expressed PD1. We further determined that a recently described population of CXCR4+ T inflammatory mucosal cells differentially expressed multiple other chemokine receptors relative to their blood counterparts. Our findings suggest that T cells resident in different tolerogenic mucosal sites take on distinct properties.

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T cells play important roles in antiviral immunity, including within mucosal tissues where many viral pathogens initiate infection. Although knowledge of human T cells has historically mostly derived from studies of peripheral blood for practical reasons, recent studies utilizing postmortem specimens have markedly increased our understanding of T cells residing within mucosal tissues. For example, T cells within the gut have been shown to express the T resident memory (Trm) markers CD69 and CD103, to consist mostly of T effector memory (Tem) cells, and to exhibit other distinguishing phenotypic features such as low surface expression of the costimulatory molecule CD28 (13). Such postmortem studies, however, have not interrogated T cell features within the female reproductive tract (FRT), the gateway tissue in women for sexually transmitted pathogens.

That being said, T cells from the lower FRT (cervical and vaginal tissues) of women undergoing hysterectomy were recently characterized. These studies, which used a combination of flow cytometry and RNA sequencing to characterize both CD4+ and CD8+ T cells, revealed unique features of multiple populations of genital T cells. For example, CD4+ T cells expressing the Trm markers CD69 and CD103 were shown to preferentially express the effector markers PD1 and CCR5 relative to their CD69CD103 counterparts, and to harbor a Th17 signature (4). It was also demonstrated that cervicovaginal CD69CD103 CD8+ T cells exhibit unique phenotypic, inflammatory, cytotoxic, and migratory features, and that these “T inflammatory mucosal” (Tim) cells expand during HIV infection (5).

These studies, in addition to revealing interesting features of mucosal T cells, also bring up the notion of whether there may be differences between the gut and FRT mucosa that may reflect the different foreign Ags they need to tolerate—the gastrointestinal microbiome and food Ags passing through the digestive system in the case of the gut, and the vaginal microbiome, male Ags, and an allogeneic fetus in the case of the FRT. At the same time, there are many parallels between these two mucosal sites: they are both colonized by endogenous flora, secrete mucus that contributes to barrier function, are responsive to sex steroids, and harbor MALT structures (6). The aforementioned T cell characterization studies, unfortunately, did not allow for a direct in-depth comparison between the gut and FRT, because the gut and FRT specimens were not taken from the same women. In addition, previous studies of the FRT did not take into account cycle phase and menopausal status, which can very much affect immune responses, and did not include the upper FRT, in particular the endometrium, which is highly hormonally responsive and serves as the site of embryo implantation but also as a potential site for viral invasion (7, 8).

We performed a study where we recruited five HIV+, antiretroviral therapy (ART)–suppressed women who donated, within the same study visit, blood together with biopsies from three gut sites (ileum, colon, and rectosigmoid) and samples from three areas of the FRT (biopsies from the endometrium and ectocervix, plus endocervical curettage). None of the women was postmenopausal, and they were all sampled during the midluteal phase of the ovulatory cycle. Cells from the specimens were all phenotyped without ever having gone through any cryopreservation. Phenotyping was conducted using cytometry by time of flight (CyTOF), enabling deep 36-parameter single-cell characterization of differentiation, activation, and homing properties of both CD4+ and CD8+ T cells from the specimens. Overall, we found expected phenotypic differences between blood and tissue T cells, and furthermore discovered both shared and unique features between T cells from the gut and FRT. Our results support the notion that T cells resident within different mucosal sites can take on distinct properties, presumably to help tailor their activities to their surrounding milieu.

Five participants were enrolled at the University of California San Francisco from the Women’s Interagency HIV Study (WIHS), described elsewhere (9), and now known as the Multicenter AIDS Cohort Study (MACS)-WIHS Combined Cohort Study (10). Peripheral blood and specimens from the gut (ileum, colon, rectosigmoid) and FRT (endometrium, endocervix, and ectocervix) were obtained during the midluteal phase of the ovulatory cycle, as established by urine luteinizing hormone detection. Hormone phase was further verified by blood progesterone levels. None of the women was postmenopausal as defined by the Stages of Reproductive Aging Workshop (STRAW) criteria (11). All blood, gut, and FRT specimens were obtained at the same study visit, between May 2017 and October 2019. Aliquots of these specimens were previously analyzed for HIV DNA and RNA levels (12). The study was approved by the University of California San Francisco Institutional Review Board, and each participant provided written informed consent prior to participation in the study.

All specimens were processed the day of collection. PBMCs were isolated from blood specimens through Ficoll-Paque density gradient sedimentation. Whole blood was diluted with FACS buffer (PBS with 2% FBS and 2 mM EDTA), after which Ficoll (STEMCELL Technologies) was slowly added to the bottom of the diluted specimen at a ratio (v/v) of 1 Ficoll/4 FACS buffer. Specimens were then centrifuged at 2000 rpm at room temperature, without braking, using an Allegra X‐12 (Beckman Coulter, Brea, CA). The layer corresponding to PBMCs was transferred to a new tube, washed three times with FACS buffer, and treated for 10 min at room temperature with red lysis buffer (BioLegend). The cells were then washed twice with RPMI 1640 media and prepared for CyTOF as described further below.

Tissue specimens were processed into single‐cell suspensions as previously described (12). Briefly, each tissue specimen was first incubated with intraepithelial lymphocyte (IEL) digestion buffer (PBS supplemented with 10 mM DTT [Sigma‐Aldrich], 5 mM EDTA [Thermo Fisher Scientific], 10 mM HEPES [Thermo Fisher Scientific], and 5% FBS) for 20 min at 37°C, to collect IELs from the supernatant fraction. The remaining tissues were then transferred to MACS C tubes (Miltenyi Biotec) in digestion solution (6 ml of RPMI 1640, 10 mM HEPES, 5% FBS, 6 mg of CLSPA collagenase [Worthington Biochemical], and 7.5 μg/ml DNAse [Sigma‐Aldrich]) and incubated for 30 min at 37°C. The tubes were then put through a gentleMACS dissociator (Miltenyi Biotec, program m_spleen), followed by further dissociation by 10 passes through a blunt 20G needle (Becton Dickinson). Cells were washed, treated for 30 min at 4°C with DNase solution (RPMI 1640, 10 mM HEPES, 5% FBS, and 7.5 μg/ml DNAse [Sigma‐Aldrich]), and combined with the IEL fraction. All cells were filtered through 70-μm strainers (Fisher Scientific) prior to CyTOF staining.

To validate our ability to detect HIV-infected cells, we generated HIV-infected primary cells. CCR5-tropic F4.HSA virus was produced from F4.HSA plasmid (13) as described (14) and exposed at a final concentration of 100–200 ng/ml p24Gag to human lymphoid aggregate cultures generated from tonsils similar to recently described methods (15). Control cultures received media lacking F4.HSA. Infections were allowed to proceed for 4 d, after which cultures were processed for CyTOF analysis as described below.

CyTOF was conducted similar to methods recently described (14, 16, 17). Single-cell suspensions of the blood and tissue specimens, as well as in vitro–infected tonsils, were treated with 25 μM cisplatin (Sigma-Aldrich) for 60 s to enable subsequent live/dead discrimination. The cells were then quenched with CyFACS buffer (PBS supplemented with 0.1% BSA and 0.1% sodium azide) and fixed for 10 min with 2% paraformaldehyde (PFA; Electron Microscopy Sciences). Next, the fixed cells were washed twice with CyFACS and then frozen at −80°C until CyTOF Ab staining. Of note, this processing protocol enables analysis of cells that never underwent cryopreservation.

Immediately prior to Ab staining, all blood and tissue cells from each participant were barcoded using the Cell‐ID 20‐plex Pd barcoding kit (Fluidigm, South San Francisco, CA) and combined into a single specimen. These cells were then then blocked for 15 min at 4°C with 1.5% mouse and rat sera (both from Thermo Fisher Scientific) and 0.3% human AB sera (Sigma‐Aldrich). The cells were then washed twice with CyFACS and stained for 45 min at 4°C with the cell surface Abs listed in Table II. Abs were either purchased preconjugated from Fluidigm, or self-conjugated using the MaxPAR conjugation kit (Fluidigm). Cells were then washed with CyFACS and fixed overnight at 4°C in 2% PFA. The next day, the cells were permeabilized for 30 min with FOXP3 fixation/permeabilization buffer (Fisher Scientific), washed twice with permeabilization buffer (Fisher Scientific), and blocked for 15 min at 4°C with mouse and rat sera diluted in permeabilization buffer. After two washes with permeabilization buffer, cells were stained for 45 min at 4°C with the intracellular Abs listed in Table II. Cells were then incubated for 20 min with a 1:500 dilution DNA intercalator (Fluidigm), washed twice with CyFACS, once with cell acquisition solution (Fluidigm), and resuspended in 1× EQ four element calibration beads (Fluidigm) diluted in cell acquisition solution. Cells were analyzed on a CyTOF 2 instrument (Fluidigm) at the University of California San Francisco Parnassus Flow Cytometry Core.

The levels of HIV DNA and RNA were obtained from a recently published study (12), which describes the ddPCR-based approaches for quantitating these nucleic acid products. Spearman correlations were calculated using the scipy “spearmanr” function (18) and depicted as heatmaps.

CyTOF datasets were normalized to EQ calibration beads to minimize variability in intramachine performance. The numbers of live, singlet T cells collected for each type of sample ranged from 70,177 to 315,125 for blood (median 95,927), from 1,484 to 10,439 for gut (median 3,894), and from 792 to 35,304 for FRT (median 5,835). T cells were manually gated using the FlowJo software (BD Biosciences) for CD4+ T cells (CD3+CD19CD8 or CD3+CD19CD4+CD8 cells as indicated), memory CD4+ T cells (CD3+CD19CD4+CD8CD45RO+CD45RA cells), CD8+ T cells (CD3+CD19CD4CD8+ cells), or memory CD8+ T cells (CD3+CD19CD4CD8+CD45RO+CD45RA cells), as well as other subsets defined within the Results. tSNE (t-distributed stochastic neighbor embedding) visualizations of the datasets were performed in Cytobank, with the following settings: iteration, 16,000; perplexity, 45; and Θ, 0.5. FlowSOM (19) was used to identify clusters from the high-dimensional CyTOF datasets. When comparing blood, gut and FRT, the following FlowSOM settings were used: hierarchical consensus; metaclusters, 20; clusters, 225; and iterations, 10. When clustering just the gut and FRT specimens together, FlowSOM was performed in Cytobank, using the following settings: hierarchical consensus; metaclusters, 10; clusters, 225; and iterations, 10.

The participants were five women living with HIV (WLWH) and on ART (Table I). We used a cutoff of <200 HIV-1 RNA copies/ml to include only participants without evidence of virological failure. The Department of Health and Human Services guidelines and the AIDS Clinical Trials Group (ACTG) define virological failure as a confirmed viral load of >200 HIV-1 RNA copies/ml, a threshold that eliminates most cases of apparent viremia caused by viral load blips or assay variability. For each participant, whole blood and ileum, colon, rectosigmoid, endometrium, endocervix, and ectocervix specimens were obtained. For the tissue specimens, we implemented a protocol that uses gentle digestion to maintain high lymphocyte recovery while preserving the integrity of many T cell surface Ags (20). Immediately after isolating the single-cell suspensions, we stained cells with cisplatin as a viability dye, fixed them with PFA, and then analyzed the cells by CyTOF (Table II). This approach enabled establishing the phenotypes of cells that had never undergone cryopreservation. Raw CyTOF datasets are available for download through the following public repository link: https://doi.org/10.7272/Q6HM56P8. Aliquots of these specimens were set aside for HIV RNA and DNA quantitation, which are published elsewhere (12).

Table I.

Clinical parameters by donor

HIV+ ART-Treated Cisgender Women
Donor ADonor BDonor CDonor DDonor ESummary
Age (y) 43.2 51.4 48.5 40.8 52.3 48.5 (40.8–52.3) 
Time since HIV diagnosis (y) 23 15.5 7.4 7.4 23.5 15.5 (7.4–23.5) 
Time on ART (y) 18.4 13.5 7.3 7.3 23 13.5 (7.3–23) 
Viral load (HIV-1 RNA cp/ml plasma) 50 185 91 20 20 50 (20–185) 
Nadir CD4 (cell/mm3216 263 356 338 328 328 (216–356) 
Absolute CD4 count (cell/mm3682 878 998 1062 1092 998 (682–1092) 
Percentage CD4 55 42 43 37 39 42 (37–55) 
CD4/CD8 ratio, median (range) 2.4 1.4 0.9 0.7 1.1 1.1 (0.7–2.4) 
HIV+ ART-Treated Cisgender Women
Donor ADonor BDonor CDonor DDonor ESummary
Age (y) 43.2 51.4 48.5 40.8 52.3 48.5 (40.8–52.3) 
Time since HIV diagnosis (y) 23 15.5 7.4 7.4 23.5 15.5 (7.4–23.5) 
Time on ART (y) 18.4 13.5 7.3 7.3 23 13.5 (7.3–23) 
Viral load (HIV-1 RNA cp/ml plasma) 50 185 91 20 20 50 (20–185) 
Nadir CD4 (cell/mm3216 263 356 338 328 328 (216–356) 
Absolute CD4 count (cell/mm3682 878 998 1062 1092 998 (682–1092) 
Percentage CD4 55 42 43 37 39 42 (37–55) 
CD4/CD8 ratio, median (range) 2.4 1.4 0.9 0.7 1.1 1.1 (0.7–2.4) 

ART, antiretroviral therapy.

Live, singlet cell events were exported from the CyTOF datasets and gated separately for CD4+ and CD8+ T cells. As an original goal of this study was to try to characterize HIV-infected cells that persist in WLWH (e.g., due to diminished ART drug concentrations within tissues), we first assessed whether we could identify any HIV-infected cells from our specimens. Although we could detect a population of HIV Gag+ cells among in vitro–infected T cells, which had downregulated cell-surface CD4 as expected (21) (Fig. 1A), Gag-expressing cells were absent from any of our patient specimens (Fig. 1B). These results suggest that ART fully suppressed HIV protein expression in our cohort of WLWH including within the tissue compartment (although HIV RNA was detectable [12]), and/or that the numbers of T cells we obtained from the specimens were too low to detect infected cells. Therefore, for the remainder of the study we focused on comparing the phenotypes of total CD4+ T cells (CD3+CD4+CD8) or CD8+ T cells (CD3+CD4CD8+) between the different sampling sites.

FIGURE 1.

No HIV-infected cells were detectable in blood or tissue specimens from five ART-suppressed women living with HIV. (A) Validation of HIV-1 Gag protein detection reagents. Tonsils from HIV-uninfected donors were mock treated (left) or infected in vitro (right) with a CCR5-tropic HIV-1 reporter virus (F4.HSA) and analyzed by CyTOF. Events corresponding to live, singlet CD3+CD8 cells were then exported and visualized as two-dimensional dot plots for expression of CD4 and Gag as assessed by a mixture of multiple anti-Gag Ab clones (Table II). The blue gate shows a clear population of Gag+ cells that had downregulated cell-surface CD4 in the infected sample. That population is absent in the uninfected sample. The histogram plots on the right demonstrate that Gag+ cells identified in this manner also bound the anti-Gag Ab KC57 labeled for detection on a different CyTOF channel (blue histogram). The red histograms correspond to the circled populations of CD4+Gag cells on the two-dimensional dot plots and serve as a negative control for populations that should not stain for KC57. (B) No Gag+ cells were detectable in blood or tissue specimens from HIV+ participants. Live, singlet CD3+CD8 cells from blood, ileum, right colon, rectosigmoid, endometrium, endocervix, and ectocervix from a representative donor demonstrate no detectable Gag+ cells in these specimens. Similar results were observed for the remaining four donors.

FIGURE 1.

No HIV-infected cells were detectable in blood or tissue specimens from five ART-suppressed women living with HIV. (A) Validation of HIV-1 Gag protein detection reagents. Tonsils from HIV-uninfected donors were mock treated (left) or infected in vitro (right) with a CCR5-tropic HIV-1 reporter virus (F4.HSA) and analyzed by CyTOF. Events corresponding to live, singlet CD3+CD8 cells were then exported and visualized as two-dimensional dot plots for expression of CD4 and Gag as assessed by a mixture of multiple anti-Gag Ab clones (Table II). The blue gate shows a clear population of Gag+ cells that had downregulated cell-surface CD4 in the infected sample. That population is absent in the uninfected sample. The histogram plots on the right demonstrate that Gag+ cells identified in this manner also bound the anti-Gag Ab KC57 labeled for detection on a different CyTOF channel (blue histogram). The red histograms correspond to the circled populations of CD4+Gag cells on the two-dimensional dot plots and serve as a negative control for populations that should not stain for KC57. (B) No Gag+ cells were detectable in blood or tissue specimens from HIV+ participants. Live, singlet CD3+CD8 cells from blood, ileum, right colon, rectosigmoid, endometrium, endocervix, and ectocervix from a representative donor demonstrate no detectable Gag+ cells in these specimens. Similar results were observed for the remaining four donors.

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Table II.

List of Ags analyzed by CyTOF

Ag TargetCloneElemental IsotopeVendorMarker of
HLA-DR TU36 Qdot (112Cd) Life Technologies Activation 
RORγδa AFKJS-9 115In In-house Lineage 
CD49d (α4) 9F10 141Pr Fluidigm Trafficking 
CD19 HIB19 142Nd Fluidigm Lineage 
CD57 HNK-1 143Nd In-house Differentiation 
CCR5 NP6G4 144Nd Fluidigm Trafficking 
CD8 RPA-T8 146Nd Fluidigm Lineage 
CD7 CD76B7 147Sm Fluidigm Differentiation 
ICOS C398.4A 148Nd Fluidigm Activation 
T-beta 4B10 149Sm In-house Lineage 
Gag (KC57)a FH190-1-1 150Nd In-house HIV infection 
CD103 Ber-ACT8 151Eu Fluidigm Trafficking 
TCRγδ 11F2 152Sm Fluidigm Lineage 
CD62L DREG56 153Eu Fluidigm Trafficking 
TIGIT MBSA43 154Sm Fluidigm Exhaustion 
CCR6 11A9 155Gd In-house Trafficking 
CD29 (β1) TS2/16 156Gd Fluidigm Trafficking 
OX40 ACT35 158Gd Fluidigm Activation 
CCR7 G043H7 159Tb Fluidigm Lineage/trafficking 
CD28 CD28.2 160Gd Fluidigm Activation 
CD45RO UCHL1 161Dy In-house Lineage 
CD69 FN50 162Dy Fluidigm Activation/residence 
CRTH2 BM16 163Dy Fluidigm Lineage 
PD1 EH12.1 164Dy In-house Activation/exhaustion 
CD127 A019D5 165Ho Fluidigm Differentiation 
CXCR5 RF8B2 166Er In-house Lineage/trafficking 
CD27 L128 167Er Fluidigm Lineage 
CD30 BERH8 168Er In-house Activation 
CD45RA HI100 169Tm Fluidigm Lineage 
CD3 UCHT1 170Er Fluidigm Lineage 
Gag (mixture)a 71-31, 91-5, 241-D, AG3.0 171Yb In-house HIV infection 
CD38 HIT2 172Yb Fluidigm Activation 
α4β7 Act1 173Yb In-house Trafficking 
CD4 SK3 174Yb Fluidigm Lineage 
CXCR4 12G5 175Lu Fluidigm Trafficking 
CD25 M-A251 176Yb In-house Activation 
Ag TargetCloneElemental IsotopeVendorMarker of
HLA-DR TU36 Qdot (112Cd) Life Technologies Activation 
RORγδa AFKJS-9 115In In-house Lineage 
CD49d (α4) 9F10 141Pr Fluidigm Trafficking 
CD19 HIB19 142Nd Fluidigm Lineage 
CD57 HNK-1 143Nd In-house Differentiation 
CCR5 NP6G4 144Nd Fluidigm Trafficking 
CD8 RPA-T8 146Nd Fluidigm Lineage 
CD7 CD76B7 147Sm Fluidigm Differentiation 
ICOS C398.4A 148Nd Fluidigm Activation 
T-beta 4B10 149Sm In-house Lineage 
Gag (KC57)a FH190-1-1 150Nd In-house HIV infection 
CD103 Ber-ACT8 151Eu Fluidigm Trafficking 
TCRγδ 11F2 152Sm Fluidigm Lineage 
CD62L DREG56 153Eu Fluidigm Trafficking 
TIGIT MBSA43 154Sm Fluidigm Exhaustion 
CCR6 11A9 155Gd In-house Trafficking 
CD29 (β1) TS2/16 156Gd Fluidigm Trafficking 
OX40 ACT35 158Gd Fluidigm Activation 
CCR7 G043H7 159Tb Fluidigm Lineage/trafficking 
CD28 CD28.2 160Gd Fluidigm Activation 
CD45RO UCHL1 161Dy In-house Lineage 
CD69 FN50 162Dy Fluidigm Activation/residence 
CRTH2 BM16 163Dy Fluidigm Lineage 
PD1 EH12.1 164Dy In-house Activation/exhaustion 
CD127 A019D5 165Ho Fluidigm Differentiation 
CXCR5 RF8B2 166Er In-house Lineage/trafficking 
CD27 L128 167Er Fluidigm Lineage 
CD30 BERH8 168Er In-house Activation 
CD45RA HI100 169Tm Fluidigm Lineage 
CD3 UCHT1 170Er Fluidigm Lineage 
Gag (mixture)a 71-31, 91-5, 241-D, AG3.0 171Yb In-house HIV infection 
CD38 HIT2 172Yb Fluidigm Activation 
α4β7 Act1 173Yb In-house Trafficking 
CD4 SK3 174Yb Fluidigm Lineage 
CXCR4 12G5 175Lu Fluidigm Trafficking 
CD25 M-A251 176Yb In-house Activation 
a

Intracellular Abs.

We first visualized all of the datasets together by tSNE. Not surprisingly, blood T cells resided in distinct areas of the tSNE relative to gut and FRT T cells, within both the CD4+ (Fig. 2A, left) and CD8+ (Fig. 2B, left) compartments. A large overlap between the gut and FRT T cells within this tSNE space suggested shared features between T cells from these mucosal sites. However, when the tSNE was repeated with only the tissue specimens, it became apparent that T cells from the gut and FRT segregated apart from each other, within both the CD4+ (Fig. 2A, right) and CD8+ (Fig. 2B, right) compartments. Of note, for both the blood and tissue T cells, some heterogeneity was also observed between donors. Since the three gut sites largely overlapped with one another, as did the three FRT sites, for the remainder of the study we combined the three sites from each tissue unless otherwise indicated, which gave us larger numbers of cells for our analyses. Overall, this initial view of the datasets suggests both shared and distinct features between T cells from the gut versus FRT of WLWH, as well as some heterogeneity between donors.

FIGURE 2.

T cells from gut and FRT exhibit both common and distinguishing features and are distinct from T cells from blood. Donor-matched T cells from blood, three gut sites (ileum, right colon, and rectosigmoid) and three FRT sites (endometrium, endocervix, and ectocervix) were obtained from five ART-suppressed women living with HIV (WLWH) and phenotyped by CyTOF. (A and B) Datasets corresponding to CD4+ (A) or CD8+ (B) T cells from each of the sites were visualized by tSNE. Analysis of the blood specimens within the same tSNE space as the tissue specimens (left side of panels) suggests shared features between gut and FRT T cells distinguishing them from blood T cells, as gut and FRT cells reside in a shared region of the tSNE distinct from the region occupied by the blood cells. In contrast, tSNE analysis of the tissue specimens alone (right side of panels) unveils phenotypic differences between gut and FRT cells, as gut and FRT cells reside in distinct areas. Each donor is shown in a separate column, but for each analysis all donors were analyzed within the same tSNE space. The source of cells from each donor is indicated in the colored key at the top. Missing entries correspond to tissue sites where not enough T cells were isolated for CyTOF analysis. As the phenotypes of T cells were overall similar between the three gut sites, and between the three FRT sites, for the remainder of the study we combined the datasets for the three gut sites together and the three FRT sites together.

FIGURE 2.

T cells from gut and FRT exhibit both common and distinguishing features and are distinct from T cells from blood. Donor-matched T cells from blood, three gut sites (ileum, right colon, and rectosigmoid) and three FRT sites (endometrium, endocervix, and ectocervix) were obtained from five ART-suppressed women living with HIV (WLWH) and phenotyped by CyTOF. (A and B) Datasets corresponding to CD4+ (A) or CD8+ (B) T cells from each of the sites were visualized by tSNE. Analysis of the blood specimens within the same tSNE space as the tissue specimens (left side of panels) suggests shared features between gut and FRT T cells distinguishing them from blood T cells, as gut and FRT cells reside in a shared region of the tSNE distinct from the region occupied by the blood cells. In contrast, tSNE analysis of the tissue specimens alone (right side of panels) unveils phenotypic differences between gut and FRT cells, as gut and FRT cells reside in distinct areas. Each donor is shown in a separate column, but for each analysis all donors were analyzed within the same tSNE space. The source of cells from each donor is indicated in the colored key at the top. Missing entries correspond to tissue sites where not enough T cells were isolated for CyTOF analysis. As the phenotypes of T cells were overall similar between the three gut sites, and between the three FRT sites, for the remainder of the study we combined the datasets for the three gut sites together and the three FRT sites together.

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To compare the subset distribution of the donor-matched T cells between the blood, gut, and FRT compartments, we first performed manual gating. CD4+ and CD8+ T cells were gated for T naive, T central memory (Tcm), Tem, T transitional memory, and two populations of Trm cells: those expressing CD69 (CD69+ Trm), and those coexpressing CD69 and CD103 (CD69+CD103+ Trm) (Supplemental Fig. 1). CD4+ T cells were additionally gated for T follicular helper, Th1, Th17, and Th1/Th17 cells (Supplemental Fig. 1A). Memory CD4+ and CD8+ T cells were more frequent in both tissues relative to blood, with gut harboring the highest frequencies (Fig. 3). Correspondingly, naive T cells were less frequent in the tissues, particularly the gut. Within both the CD4+ and CD8+ compartments, Tcm cells were more abundant in the blood than in either tissue, which harbored negligible numbers of these cells. Also, within both the CD4+ and CD8+ compartments, CD69+ Trm cells were more abundant in either tissue as compared with blood. Interestingly, although a subset of these CD69+ Trm cells from gut coexpressed CD103, such cells were rare in the FRT. These results overall suggest that relative to blood T cells, gut and FRT T cells are enriched for memory T cells, including Trm cells, but disenriched for cells of the Tcm phenotype.

FIGURE 3.

Frequencies of canonical T cell subsets in blood, gut, and FRT. (A and B) T cell subsets defined in Supplemental Fig. 1 were assessed for relative frequencies among CD4+ (A) and CD8+ (B) T cells from the blood and indicated tissue compartments. Each colored dot corresponds to a different donor (n = 5 donors). *p < 0.05, ** p < 0.01 as determined by a Kruskal–Wallis test with Dunn’s correction.

FIGURE 3.

Frequencies of canonical T cell subsets in blood, gut, and FRT. (A and B) T cell subsets defined in Supplemental Fig. 1 were assessed for relative frequencies among CD4+ (A) and CD8+ (B) T cells from the blood and indicated tissue compartments. Each colored dot corresponds to a different donor (n = 5 donors). *p < 0.05, ** p < 0.01 as determined by a Kruskal–Wallis test with Dunn’s correction.

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We then delved deeper into the CyTOF datasets by taking advantage of phenotyping markers beyond those corresponding to the canonical subsets. Comparison of the mean signal intensity of all the T cell Ags revealed some differentially expressed Ags between T cells from blood, gut, and FRT (Supplemental Fig. 2). For example, among CD4+ T cells, CD27 and CD30 were both significantly elevated in the blood relative to both tissues, whereas CD69 was elevated within tissues, consistent with the manual gating data.

As the amount of HIV DNA and RNA within the blood, gut, and FRT of these donors had previously been quantified (12), we looked for potential correlations between the donors’ T cell populations and reservoir size. To this end, we compared frequencies of any manually gated subset or CyTOF phenotyping Ag levels (as assessed by mean signal intensity) to levels of total HIV DNA, and to levels of initiated (based on levels of HIV transactivation response) or 5′ elongated (based on levels of “long LTR” [R-U5-pre-Gag]) HIV RNA in the same tissues. No correlations were statistically significant, likely due to the limited number of participants analyzed. However, the specimens from the three gut sites tended to exhibit similar patterns; for example, the donors with the highest levels of HIV transcriptional elongation also had the lowest proportions of regulatory T cells and of CD8+CD69+ and CD69+CD103+ Trm cells in the rectosigmoid, as well as rectum and ileum (Supplemental Fig. 3). These results suggest the possibility that within the gut, the transcriptionally active reservoir resides outside the regulatory T cell population of memory CD4+ T cells (22), although further studies are needed to directly test this.

To distinguish the T cells from the three different sites in a more unbiased manner, we performed FlowSOM clustering (19). Depiction of the cluster distribution as pie graphs revealed limited variations between the donors relative to the tissue-associated signatures (Fig. 4A, 4B, pie charts). In particular, some clusters were overrepresented in blood relative to tissues whereas others were overrepresented in tissues (Fig. 4A, 4B, bar graphs).

FIGURE 4.

Clustering reveals phenotypic differences between T cells from blood versus tissues. (A and B) CD4+ (A) and CD8+ (B) T cells from blood, gut, and FRT were separated into 20 clusters each (A1–A20 and B1–B20) by FlowSOM. The top portions of the two panels show cluster distributions depicted as pie charts, separated by donor. The bottom portions of the two panels depict bar graphs of clusters that were significantly overrepresented in the indicated blood or tissue compartment. (C and D) Validation of markers defining tissue CD4+ (C) and CD8+ (D) T cells was then performed by selecting Ags differentially expressed in the clusters enriched in tissues and conducting manual gating. This analysis demonstrated that relative to blood, gut and FRT CD4+ T cells are preferentially CD27lowCD25lowCD62LlowCD28lowCD49dlowCD30low. Relative to blood, gut and FRT CD8+ T cells are preferentially CCR5highCXCR5lowTIGITlowCD27lowCRTH2highCD28lowCD7highICOShigh. *p < 0.05, ** p < 0.01 as determined by a Kruskal–Wallis test with Dunn’s correction (n = 5 donors).

FIGURE 4.

Clustering reveals phenotypic differences between T cells from blood versus tissues. (A and B) CD4+ (A) and CD8+ (B) T cells from blood, gut, and FRT were separated into 20 clusters each (A1–A20 and B1–B20) by FlowSOM. The top portions of the two panels show cluster distributions depicted as pie charts, separated by donor. The bottom portions of the two panels depict bar graphs of clusters that were significantly overrepresented in the indicated blood or tissue compartment. (C and D) Validation of markers defining tissue CD4+ (C) and CD8+ (D) T cells was then performed by selecting Ags differentially expressed in the clusters enriched in tissues and conducting manual gating. This analysis demonstrated that relative to blood, gut and FRT CD4+ T cells are preferentially CD27lowCD25lowCD62LlowCD28lowCD49dlowCD30low. Relative to blood, gut and FRT CD8+ T cells are preferentially CCR5highCXCR5lowTIGITlowCD27lowCRTH2highCD28lowCD7highICOShigh. *p < 0.05, ** p < 0.01 as determined by a Kruskal–Wallis test with Dunn’s correction (n = 5 donors).

Close modal

To better define the phenotypic features of the tissue T cells, we assessed which Ags were differentially expressed among the tissue-enriched CD4+ (A15 and A16) and CD8+ (B3 and B5) clusters. Consistent with the notion that T cells within tissues are primarily memory cells, all four of these clusters expressed high levels of the memory marker CD45RO and low levels of the naive marker CD45RA (Supplemental Fig. 4A–D). Clusters A15 and B3 preferentially expressed CD69 but not CD103, whereas clusters A16 and B5 included both cells expressing CD69 in the absence of CD103, as well as CD69+CD103+ cells (Supplemental Fig. 4A–D). These results suggest enrichment of multiple types of Trm cells within the tissues.

Multiple chemokine receptors as well as other surface Ags were also differentially expressed among these clusters as compared with total T cells. For instance, markers differentially expressed in both of the tissue-associated CD4+ T cell clusters (A15 and A16) included CD27, CD25, CD62L, CD28, CD49d, and CD30, all of which were expressed at lower levels in these two clusters compared with total CD4+ T cells from all sampled sites (Supplemental Fig. 4A, 4B). To validate whether cells expressing low levels of these Ags were indeed preferentially present within the tissues, we gated on CD4+ T cells that were CD27lowCD25lowCD62LlowCD28lowCD49dlowCD30low. The frequency of these cells was indeed lower in the blood than in either tissue compartment (Fig. 4C), thereby validating these phenotypic features as shared features of gut/FRT T cells that distinguish them from their blood counterparts. A similar analysis among the tissue-associated CD8+ T cell cluster B5 revealed CCR5, CRTH2, CD7, and ICOS to be expressed at higher levels, whereas CXCR5, TIGIT, CD27, and CD28 were expressed at lower levels in these two clusters as compared with total CD8+ T cells (Supplemental Fig. 4C, 4D). Manual gating validation demonstrated that CD8+ T cells that were CCR5highCXCR5lowTIGITlowCD27lowCRTh2highCD28lowCD7highICOShigh were indeed more frequent in both gut and FRT as compared with blood (Fig. 4D).

Having demonstrated and described some phenotypic features of T cells shared between the gut and FRT, we next wanted to better characterize the differences between these two compartments’ T cells. We repeated the FlowSOM clustering of the CD4+ and CD8+ T cells using just the tissue specimens and found different cluster distributions between the two tissue sites, along with some donor-dependent features (Figure 5A, 5B, pie charts). Moreover, for both CD4+ and CD8+ T cells, some clusters were enriched in the gut, and others in the FRT (Figure 5A, 5B, bar graphs). The gut-associated clusters from CD4+ and CD8+ T cells (C2 and D2) shared phenotypic features of memory (CD45RO+) cells expressing high levels of Trm marker CD69 and low levels of Tcm markers CCR7 and CD27 (Supplemental Fig. 4E, 4F). Manual gating of CD45ROhighCD69highCCR7lowCD27low cells within both the CD4+ and CD8+ T cell subsets revealed these cells to be significantly enriched in the gut as compared with the FRT (Fig. 5C, 5D). These results suggest that CD69+ Trm cells of the effector memory (CCR7lowCD27low) phenotype are more prevalent in the gut than FRT.

FIGURE 5.

Clustering reveals phenotypic differences between T cells from gut versus FRT. (A and B) CD4+ (A) and CD8+ (B) T cells from gut and FRT were reclustered (C1–C9 and D1–D10) by FlowSOM, after removal of the blood specimens’ data. The top portions of the two panels show cluster distributions depicted as pie charts, separated by donor. The bottom portions of the two panels depict bar graphs of clusters that were significantly over-represented in gut or FRT. (C and D) Validation of markers preferentially expressed on gut CD4+ (C) and CD8+ (D) T cells was then performed by selecting Ags differentially expressed in the clusters enriched in the gut as compared with FRT (C2 and D2), and conducting manual gating. This analysis demonstrated that relative to their FRT counterparts, both CD4+ and CD8+ T cells from gut are preferentially CD45ROhighCD69highCCR7lowCD27low. *p < 0.05, **p < 0.01 as determined by a Mann–Whitney U test (n = 5 donors).

FIGURE 5.

Clustering reveals phenotypic differences between T cells from gut versus FRT. (A and B) CD4+ (A) and CD8+ (B) T cells from gut and FRT were reclustered (C1–C9 and D1–D10) by FlowSOM, after removal of the blood specimens’ data. The top portions of the two panels show cluster distributions depicted as pie charts, separated by donor. The bottom portions of the two panels depict bar graphs of clusters that were significantly over-represented in gut or FRT. (C and D) Validation of markers preferentially expressed on gut CD4+ (C) and CD8+ (D) T cells was then performed by selecting Ags differentially expressed in the clusters enriched in the gut as compared with FRT (C2 and D2), and conducting manual gating. This analysis demonstrated that relative to their FRT counterparts, both CD4+ and CD8+ T cells from gut are preferentially CD45ROhighCD69highCCR7lowCD27low. *p < 0.05, **p < 0.01 as determined by a Mann–Whitney U test (n = 5 donors).

Close modal

A recent study reported that among CD4+ T cells within the lower FRT, CD69+CD103+ Trm cells exhibited unique transcriptional and phenotypic features, including preferential expression of PD1 and CCR5, relative to their CD69CD103 counterparts (4). We confirmed within our FRT datasets that CD69+CD103+ CD4+ Trm cells expressed higher levels of both PD1 and CCR5 than did CD69CD103 CD4+ T cells, and furthermore we discovered this to be true among CD8+ T cells as well (Fig. 6A, 6C). When we assessed the gut compartment in a similar manner, we found that as in the FRT, CD69+CD103+ Trm cells preferentially expressed CCR5 (Fig. 6B, 6D). Surprisingly, however, PD1 was not preferentially expressed on CD69+CD103+ Trm cells, and in fact was expressed at lower levels relative to their CD69CD103 counterparts (Fig. 6B, 6D). These results suggest that the unique phenotypic features of CD69+CD103+ Trm cells are dependent on the mucosal site.

FIGURE 6.

Phenotypic features of CD69+CD103+ Trm cells in tissues. (A and B) FRT (A) and gut (B) CD69+CD103+ Trm cells express higher levels of PD1 and CCR5 relative to their respective CD69CD103 T memory (Tm) counterparts. Shown are overlaid histograms from the CD4+ (left) and CD8+ (right) T cell subsets, corresponding to concatenated events from all donors. Ags significantly (p < 0.05) overexpressed among the CD69+CD103+ populations are in blue font, and those underexpressed are in red font. The p values were determined by a Student paired t test and adjusted for multiple testing using the Benjamini–Hochberg for FDR. (C and D) The proportions of CD69CD103 versus CD69+CD103+ Tm cells from FRT (C) or gut (D) were compared by manual gating for the percentages of cells expressing PD1 or CCR5. **p < 0.01 as determined by a Mann–Whitney U test (n = 5 donors).

FIGURE 6.

Phenotypic features of CD69+CD103+ Trm cells in tissues. (A and B) FRT (A) and gut (B) CD69+CD103+ Trm cells express higher levels of PD1 and CCR5 relative to their respective CD69CD103 T memory (Tm) counterparts. Shown are overlaid histograms from the CD4+ (left) and CD8+ (right) T cell subsets, corresponding to concatenated events from all donors. Ags significantly (p < 0.05) overexpressed among the CD69+CD103+ populations are in blue font, and those underexpressed are in red font. The p values were determined by a Student paired t test and adjusted for multiple testing using the Benjamini–Hochberg for FDR. (C and D) The proportions of CD69CD103 versus CD69+CD103+ Tm cells from FRT (C) or gut (D) were compared by manual gating for the percentages of cells expressing PD1 or CCR5. **p < 0.01 as determined by a Mann–Whitney U test (n = 5 donors).

Close modal

FRT-derived CD69CD103 CD8+ T cells, termed Tim cells, were recently reported to harbor unique phenotypic features relative to their blood counterparts (5). More specifically, these cells were shown to exhibit inflammatory and cytotoxic features, and to preferentially express CXCR4, a chemokine receptor that can direct immune cells to tissue sites of inflammation. We confirmed preferential expression of CXCR4 on CD8+ Tim cells from the FRT, and further demonstrated that this preferential expression occurred among CD69CD103 T cells from both the CD4+ and CD8+ compartments, and in a manner also observed in the gut (Fig. 7A–D). As Tim cells have been suggested to have distinct migratory patterns, we further assessed whether other chemokine receptors were differentially expressed on these cells. Similar to CXCR4, CCR5 was overexpressed on CD69CD103 T cells in both tissue sites as compared with blood, and among both CD4+ and CD8+ T cells (Fig. 7A–D). In contrast, CCR6 was underexpressed on CD69CD103 T cells in both tissue sites as compared with blood, and this was true among both CD4+ and CD8+ T cells (Fig. 7A–D). Taken together, these results suggest that CD69CD103 T cells from tissues are preferentially CCR5+CCR6, which we confirmed by manual gating (Fig. 7E). We conclude that Tim cells may not be unique to the CD8 compartment or to the FRT, but rather may be a common subset persisting in multiple mucosal tissues.

FIGURE 7.

Differential expression of chemokine receptors in tissue- as compared with blood-derived CD69CD103 T cells. (A and B) CD4+ (A) and CD8+ (B) CD69CD103 Tm cells from FRT and gut were compared with those in blood for expression levels of CXCR4, CCR5, and CCR6, and depicted as overlaid histograms concatenated from all donors. Ags significantly (p < 0.05) overexpressed among the gut/FRT relative to blood CD69CD103 Tm cells are in red font, and those underexpressed are in blue font. The p values were determined by a Student paired t test and adjusted for multiple testing using the Benjamini–Hochberg for FDR. (C and D) The proportions of CD4+ (C) and CD8+ (D) CD69CD103 Tm cells from FRT and gut were compared by manual gating to their counterparts in blood for percentages of cells expressing CXCR4, CCR5, or CCR6. The p values were determined by a Mann–Whitney U test. *p < 0.05, ** p < 0.01 (n = 5 donors). (E) The overrepresentation of CCR5+CCR6 cells among CD69CD103 Tm cells in tissues as compared with blood was validated by manual gating. The p values were determined by a Kruskal–Wallis test with Dunn’s correction. * p < 0.05, ** p < 0.01 (n = 5 donors).

FIGURE 7.

Differential expression of chemokine receptors in tissue- as compared with blood-derived CD69CD103 T cells. (A and B) CD4+ (A) and CD8+ (B) CD69CD103 Tm cells from FRT and gut were compared with those in blood for expression levels of CXCR4, CCR5, and CCR6, and depicted as overlaid histograms concatenated from all donors. Ags significantly (p < 0.05) overexpressed among the gut/FRT relative to blood CD69CD103 Tm cells are in red font, and those underexpressed are in blue font. The p values were determined by a Student paired t test and adjusted for multiple testing using the Benjamini–Hochberg for FDR. (C and D) The proportions of CD4+ (C) and CD8+ (D) CD69CD103 Tm cells from FRT and gut were compared by manual gating to their counterparts in blood for percentages of cells expressing CXCR4, CCR5, or CCR6. The p values were determined by a Mann–Whitney U test. *p < 0.05, ** p < 0.01 (n = 5 donors). (E) The overrepresentation of CCR5+CCR6 cells among CD69CD103 Tm cells in tissues as compared with blood was validated by manual gating. The p values were determined by a Kruskal–Wallis test with Dunn’s correction. * p < 0.05, ** p < 0.01 (n = 5 donors).

Close modal

By recruiting five well-matched, ART-suppressed WLWH to donate blood and tissue specimens from six sites of the gut and FRT in the same study visit for CyTOF phenotyping, we were able to conduct an in-depth comparison of T cells from circulation to T cells from these two major mucosal sites. Despite being generated from a relatively small cohort of women, we believe that our reference dataset— downloadable via a link provided in Materials and Methods—will be of use to the field because 1) our participants were clinically well matched (all women not on hormonal contraceptives, and all sampled during the mid-luteal phase of the menstrual cycle); 2) each set of participant specimens came from the same study visit, thus excluding differences due to longitudinal sampling; 3) our specimens were obtained purely for research purposes, and therefore tissues were not removed due to disease or a treatment-related procedure; and 4) our specimens were all analyzed without ever having gone through any cell cryopreservation. Implementation of our 36-parameter T cell–centric CyTOF panel on these specimens allowed for an in-depth comparison of T cells from the sampled sites. Overall, we found both common and distinguishing T cell features between the gut and FRT mucosa, as well as between CD4+ and CD8+ T cells within each site.

That commonalities exist between gut and FRT T cells was evidenced by these cells residing in overlapping areas of the tSNE distinct from their blood counterparts, by their sharing expression patterns of multiple T cell Ags, and by their harboring different distributions of T cell subsets relative to blood T cells. For example, relative to T cells in circulation, those from gut and FRT both expressed low levels of CD28, and manually identified subsets of CD4+ and CD8+ T cells validated to be enriched within mucosal sites were CD28low. T cells expressing low levels of CD28 were previously described from the gut mucosa as those that had recently undergone signaling through the TCR (2), and our data suggest that such sustained activation through the TCR likely also occurs in the FRT.

A second conserved feature between T cells from the two mucosal sites was the population of Tim cells, recently described CD8+ T cells exhibiting a CD69CD103 phenotype. These proinflammatory cells identified from the FRT were reported to express CXCR4 at higher levels than CD69CD103 CD8+ T cells from blood (5), data that we confirmed. We further demonstrated that preferential expression of CXCR4 also occurred on CD8+ Tim cells from the gut, and that within both FRT and gut, CD69CD103 CD4+ T cells also preferentially expressed CXCR4. Interestingly, other chemokine receptors were also differentially expressed on mucosal CD4+ and CD8+ Tim cells, including higher expression of CCR5 and lower expression of CCR6 relative to their blood CD69CD103 counterparts. As CXCR4 and CCR5 are coreceptors for HIV, these observations also suggest that CD4+ Tim cells may be important targets for HIV infection, and may help explain the high susceptibility of mucosal CD4+ T cells to HIV infection (17).

We also found that relative to blood, gut and FRT preferentially harbored Trm cells and were devoid of Tcm cells, consistent with prior studies (15, 23, 24). The tissue Trm cells from gut and FRT shared phenotypic features including preferential expression of CCR5, consistent with the notion of a “core signature” of Trm cells shared between different tissue sites (3). At the same time, we also found interesting differences in the quantity and quality of Trm cells from the gut versus FRT. Although CD69+ Trm cells were present in both gut and FRT, they were more abundant in the gut. These cells were of the Tem phenotype (CCR7lowCD27low), and indeed memory CD69+ Tem cells were significantly higher in gut as compared with FRT, among both CD4+ and CD8+ T cells. Furthermore, although the subset of CD69+ Trm cells expressing CD103 were clearly present in gut, they were detected at very low levels in the FRT. The reason for the overrepresentation of CD69+CD103+ Trm cells in the gut as compared with FRT is unclear, but may in part be due to the high abundance of TGF-β1 in the gut, which upregulates CD103 expression (25). Of note, however, CD69+CD103+ CD4+ Trm cells are more abundant in vaginal than cervical sites of the FRT (4). Given that the vaginal tract (not examined in our study) and gut are both sites highly colonized by microbiota, it is possible that CD69+CD103+ Trm cells are elevated in tissues with high microbiome load. Interestingly, CD69+CD103+ CD4+ Trm cells exhibit Th17 signatures and can induce IL-17 (4), which can elicit antibacterial responses (26). Together with observations that IL-17 levels associate with responses to intestinal bacteria (27, 28), these results suggest a potential role for CD69+CD103+ Trm cells in tolerating or responding to commensal microbiota, although future studies are necessary to directly test this hypothesis.

In addition to quantitative differences in Trm cells between the gut and FRT, we also found phenotypic differences. In the FRT, CD69+CD103+ Trm cells preferentially expressed PD1 relative to CD69CD103 cells, consistent with what was previously reported (4). In the gut, however, we found that CD69+CD103+ CD4+ Trm cells do not preferentially express PD1, and that CD69+CD103+ CD8+ Trm cells in fact express lower levels of PD1 relative to their CD69CD103 counterparts. The molecular basis and functional outcome of this observation is unclear, but it could suggest a higher need for PD1-mediated checkpoint inhibition in CD69+CD103+ Trm cells in the FRT than is necessary in the gut. As the organ supporting the development of an allogeneic fetus, we postulate that perhaps the FRT requires more tolerogenic mechanisms as compared with the gut, and that PD1-mediated tolerance may be particularly important.

Our study has limitations. We only analyzed a small cohort of women, although we made efforts to clinically match them including by cycle phase. Despite that, some heterogeneity was observed between T cells within each site. This highlights that even attempts to match participants can still result in phenotypic heterogeneity, a challenge that stems from the diversity of even well-matched participants. As sex steroids can influence immune cell distribution and functions, future studies should investigate to what extent the T cell phenotypes we described in the gut and FRT differ during other phases of the menstrual cycle, as well as after menopause and in women taking oral contraceptives. In addition, to what extent the phenotypes described in the present study among ART-suppressed WLWH are generalizable to HIV-uninfected women should be established. A second limitation of our study is that limited numbers of T cells could be isolated for immunophenotyping. This may have been one reason for our inability to identify any productively infected cells in the specimens, although we cannot rule out complete suppression of viral protein expression by ART as another possibility. The low cell yield in some specimens also meant that some biopsies did not have enough cells for meaningful T cell analysis by CyTOF. Although most donors had enough cells from all three gut sites, the endometrium was the only site of the FRT that yielded enough cells from all donors for both CD4+ and CD8+ T cell analysis. The limited numbers of cells from some of the mucosal sites, particularly the endocervix and ectocervix, may have limited our ability to detect phenotypic differences between different sampling sites within each type of mucosa (gut versus FRT). Future studies using specimens allowing for higher cell yields, for example from postmortem HIV+ donors participating in end-of-life studies (29), would be highly valuable in that regard.

We gratefully acknowledge the contributions of the study participants and dedication of the staff at the MACS/WIHS Combined Cohort Study (MWCCS) sites. We thank N. Lazarus and E. Butcher for the Act1 antibody, S. Tamaki, T.K. Peech, and C. Bispo for CyTOF assistance at the Parnassus Flow Core, T. Roberts and G. Maki for Graphics assistance, F. Chanut for editorial assistance, and R. Givens for administrative assistance.

This work was supported by National Institutes of Health (NIH) Grants R01AI127219, R01AI147777, UM1AI164567, P01AI131374, and UM1AI164559 (to N.R.R.); U01HL146242 (to N.R.R. and P.C.T.); W16036 (to N.R.R. and S.A.Y.); U01AI034989 (to R.M.G. and S.A.Y.); and R01DK108349, R01AI132128, and R01DK120387 (to S.A.Y.); as well as by the amfAR Institute for HIV Cure Research (Grant 109301). This work was also supported by the Center for AIDS Research (Grant P30AI027763) and the James B. Pendleton Charitable Trust. The Parnassus Flow Cytometry Core (RRID:SCR_018206) assisted in cytometry by time of flight data acquisition, enabled by an instrument that was supported in part by Diabetes Research Center/NIH Grants P30 DK063720 and NIH S10 1S10OD018040. The work was also supported by the MACS/WIHS Combined Cohort Study (MWCCS) Data Analysis and Coordination Center (Gypsyamber D’Souza, Stephen Gange, and Elizabeth Golub), Grant U01-HL146193 and the MWCCS Northern California site (Bradley Aouizerat, Jennifer Price, and Phyllis Tien), Grant U01-HL146242. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The contents of this publication are solely the responsibility of the authors and do not represent the official views of the NIH.

G.X. designed and conducted experiments, performed data analysis, and edited the manuscript; K.Y. conducted experiments; S.M.-L., D.A.S., and S.A.L. conducted data analysis; A.P. recruited participants and provided samples and clinical data; J.C. provided oversight of field operations; R.M.G., P.C.T., and S.A.Y. designed the study, obtained funding, and conducted supervision; N.R.R. designed the study, obtained funding, conducted data analysis, and wrote the manuscript. All authors have read and accepted the final manuscript.

The CyTOF datasets presented in this article have been submitted to Dryad (https://doi.org/10.7272/Q6HM56P8).

The online version of this article contains supplemental material.

Abbreviations used in this article:

ART

antiretroviral therapy

CyTOF

cytometry by time of flight

FRT

female reproductive tract

IEL

intraepithelial lymphocyte

PFA

paraformaldehyde

Tcm

T central memory

Tem

T effector memory

Tim

T inflammatory mucosal

Trm

T resident memory

tSNE

t-distributed stochastic neighbor embedding

WLWH

women living with HIV

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The authors have no financial conflicts of interest.