Background:
Lymphoid tissues are important sites of the HIV-1 reservoir that contribute to viral rebound after analytical treatment interruption (ATI). We hypothesize that different immune cell subsets exhibit distinct immune signatures during early versus late viral rebound. Understanding these immune signatures and their respective immune cell subsets throughout viral rebound provides mechanisms for immune control.
Methods:
From 2 female rhesus macaques intravaginally infected with SIVmac239 and treated with suppressive antiretroviral therapy (ART) for 6 months from 4 days post-challenge, we obtained 2 mesenteric lymph nodes each at 4 days and 24 days after ATI. These lymph nodes were SIV+ by targeted PET-CT. To resolve lymphoid cell heterogeneity and their respective immune responses, particularly in the context of spatial interactions, we applied deterministic barcoding in tissues (DBiT-seq) to profile transcriptomes from 10 μm x 10 μm pixels. This state-of-the-art platform allows the closest estimate of single-cell transcriptomes at a genome-wide scale compared with currently available platforms. We used machine learning algorithms to assign cell type identities to pixels, created spatial maps overlaying the pixels on tissue images, and determined gene set enrichment in early versus late viral rebound with GSEA.
Results:
To identify early and late viral rebound immune signatures, we profiled 9822 10 μm x 10 μm pixels. We captured a median of 265 RNA reads and 163 genes per pixel. At 4 days after ATI, we found enrichment in gene signatures for Tregs (GSE37605, leading edge genes: IGFBP6, TAGLN, FHL1, MGP, HSBP1), cytotoxic macrophages (GSE26912: LPL, FASN, RRAS, S100A1, SPARC; GSE22935: MYL9, GSN, LPL, FABP4, WFDC1), Tfh cells (GSE21379: FHL1, DGAT2, S100A1, LAMB2, AKAP12), and expanding CD4+ T cells (GSE32533: HSBP6, IGF2, MLIXPL, CRIP2, NEXN; GSE9316: GSN, TNXB, VCL, LDB2). At 24 days after ATI, we found upregulated gene signatures of stimulated neutrophils (GSE2405: ACTG1, C3, CORO1A, CLU, RPL35) and vaccine responses to Leishmania (Osman: CXCL9, CD74, CTSH, LYZ, C3), VEEV (Erwin Cohen: LYZ, IFI27, RPL35, IFI6, CD52), influenza (Nakaya: CTSH, ITGB2, SPN, PSAP, CD84, LCK), and HIV-1 (Zak MRKAd5: C1QB, IFI27, IFI6, TNFRSF1B, TCIRG1).
Conclusions:
We identified CD4+ T cell and macrophage signatures early and immune effector cell responses later during viral rebound in lymph nodes. Further spatial analysis and validation could provide targets to improve immune control and function during rebound.