Simon Mallal

Background: HIV cure is limited by persistence of long lived latently infected CD4+ T cells. Latently infected cell lines are widely used in vitro to study HIV latency. We identified and tested the stability of HIV integration sites in latently infected cell lines, using a newly developed high throughput method. Method: To determine assay sensitivity/efficiency, genomic DNA of seven latent HIV cell lines (20 cells each) were isolated and mixed with genomic DNA from one million HIV negative PBMCs. Additionally, the latently infected cell lines ACH-2, U1 and J1.1 containing replication competent HIV and J-Lat 8.4, 9.2, 10.6 and 15.4 cell lines that contain a single replication deficient HIV were passed. DNA, isolated after passage 0, 2, 4, 6 and 8 was enzymatically cut to random sized fragments. These were end-repaired and a linker was ligated to the fragments. The fragments were subjected to LTR based nested PCR with barcoded nested primers and prepared for Miseq sequencing. Chromosomal alignment was determined using the Blat-UCSC Genome Browser (GRCH38/hg38). Results: The efficiency was 35% and detected one HIV integration site in 50,000 uninfected PBMCs. J-Lat cell lines showed single integration sites. ACH-2, U1 and J1.1 demonstrated multiple distinct HIV integration sites per 150,000 cells (74, 42 and 93 respectively). J1.1, which is reported to have a single integrated copy per cell, demonstrated two major integration sites in equal frequency. ACH-2 cells, when passaged, demonstrated a 2-fold increase in unique HIV integration sites found across the human genome. Conclusion: Cell lines latently infected with replication competent HIV demonstrated multiple unique HIV integration sites indicating these cell lines are not clonal. Furthermore, the increase and change in sites of HIV integration observed in ACH-2 cells over time is suggestive of low level virus replication. These findings have implications for the use of latently infected cell lines as models of HIV latency.

Next generation Sequencing (NGS) has enabled high throughput analysis of T cell receptor (TCR) repertoires, which are useful for monitoring antigen- specific T cell responses. Integrating TCR sequencing with expression levels of genes that characterise T cell phenotype at the single cell level allows comprehensive analysis of T cell function and specificity. Single cell TCR sequencing on the Illumina platform enables the identification of paired TCR α/β chains and T cell phenotype from sorted antigen-specific T cell populations. Here we highlight novel techniques available for T cell phenotyping and TCR repertoire analysis.