Commonality despite exceptional diversity in the baseline human antibody repertoire.

In principle, humans can produce an antibody response to any non-self-antigen molecule in the appropriate context. This flexibility is achieved by the presence of a large repertoire of naive antibodies, the diversity of which is expanded by somatic hypermutation following antigen exposure1. The diversity of the naive antibody repertoire in humans is estimated to be at least 1012 unique antibodies2. Because the number of peripheral blood B cells in a healthy adult human is on the order of 5 × 109, the circulating B cell population samples only a small fraction of this diversity. Full-scale analyses of human antibody repertoires have been prohibitively difficult, primarily owing to their massive size. The amount of information encoded by all of the rearranged antibody and T cell receptor genes in one person-the 'genome' of the adaptive immune system-exceeds the size of the human genome by more than four orders of magnitude. Furthermore, because much of the B lymphocyte population is localized in organs or tissues that cannot be comprehensively sampled from living subjects, human repertoire studies have focused on circulating B cells3. Here we examine the circulating B cell populations of ten human subjects and present what is, to our knowledge, the largest single collection of adaptive immune receptor sequences described to date, comprising almost 3 billion antibody heavy-chain sequences. This dataset enables genetic study of the baseline human antibody repertoire at an unprecedented depth and granularity, which reveals largely unique repertoires for each individual studied, a subpopulation of universally shared antibody clonotypes, and an exceptional overall diversity of the antibody repertoire.

Quantification of transgene expression in GSH AAVS1 with a novel CRISPR/Cas9-based approach reveals high transcriptional variation.

Genomic safe harbors (GSH) are defined as sites in the host genome that allow stable expression of inserted transgenes while having no adverse effects on the host cell, making them ideal for use in basic research and therapeutic applications. Silencing and fluctuations in transgene expression would be highly undesirable effects. We have previously shown that transgene expression in Jurkat T cells is not silenced for up to 160 days after CRISPR-Cas9-mediated insertion of reporter genes into the adeno-associated virus site 1 (AAVS1), a commonly used GSH. Here, we studied fluctuations in transgene expression upon targeted insertion into the GSH AAVS1. We have developed an efficient method to generate and validate highly complex barcoded plasmid libraries to study transgene expression on the single-cell level. Its applicability is demonstrated by inserting the barcoded transgene Cerulean into the AAVS1 locus in Jurkat T cells via the CRISPR-Cas9 technology followed by next-generation sequencing of the transcribed barcodes. We observed large transcriptional variations over two logs for transgene expression in the GSH AAVS1. This barcoded transgene insertion model is a powerful tool to investigate fluctuations in transgene expression at any GSH site.

Transcriptome profiles of latently- and reactivated HIV-1 infected primary CD4+ T cells: A pooled data-analysis.

The main obstacle to cure HIV-1 is the latent reservoir. Antiretroviral therapy effectively controls viral replication, however, it does not eradicate the latent reservoir. Latent CD4+ T cells are extremely rare in HIV-1 infected patients, making primary CD4+ T cell models of HIV-1 latency key to understanding latency and thus finding a cure. In recent years several primary CD4+ T cell models of HIV-1 latency were developed to study the underlying mechanism of establishing, maintaining and reversing HIV-1 latency. In the search of biomarkers, primary CD4+ T cell models of HIV-1 latency were used for bulk and single-cell transcriptomics. A wealth of information was generated from transcriptome analyses of different primary CD4+ T cell models of HIV-1 latency using latently- and reactivated HIV-1 infected primary CD4+ T cells. Here, we performed a pooled data-analysis comparing the transcriptome profiles of latently- and reactivated HIV-1 infected cells of 5 in vitro primary CD4+ T cell models of HIV-1 latency and 2 ex vivo studies of reactivated HIV-1 infected primary CD4+ T cells from HIV-1 infected individuals. Identifying genes that are differentially expressed between latently- and reactivated HIV-1 infected primary CD4+ T cells could be a more successful strategy to better understand and characterize HIV-1 latency and reactivation. We observed that natural ligands and coreceptors were predominantly downregulated in latently HIV-1 infected primary CD4+ T cells, whereas genes associated with apoptosis, cell cycle and HLA class II were upregulated in reactivated HIV-1 infected primary CD4+ T cells. In addition, we observed 5 differentially expressed genes that co-occurred in latently- and reactivated HIV-1 infected primary CD4+ T cells, one of which, MSRB2, was found to be differentially expressed between latently- and reactivated HIV-1 infected cells. Investigation of primary CD4+ T cell models of HIV-1 latency that mimic the in vivo state remains essential for the study of HIV-1 latency and thus providing the opportunity to compare the transcriptome profile of latently- and reactivated HIV-1 infected cells to gain insights into differentially expressed genes, which might contribute to HIV-1 latency.

HIV-1 promoter is gradually silenced when integrated into BACH2 in Jurkat T-cells.

BACKGROUND: The persistence of the latent HIV-1 reservoir is a major obstacle to curing HIV-1 infection. HIV-1 integrates into the cellular genome and some targeted genomic loci are frequently detected in clonally expanded latently HIV-1 infected cells, for instance, the gene BTB domain and CNC homology 2 (BACH2). METHODS: We investigated HIV-1 promoter activity after integration into specific sites in BACH2 in Jurkat T-cells. The HIV-1-based vector LTatCL[M] contains two fluorophores: (1) Cerulean, which reports the activity of the HIV-1 promoter and (2) mCherry driven by a constitutive promotor and flanked by genetic insulators. This vector was inserted into introns 2 and 5 of BACH2 of Jurkat T-cells via CRISPR/Cas9 technology in the same and convergent transcriptional orientation of BACH2, and into the genomic safe harbour AAVS1. Single cell clones representing active (Cerulean+/mCherry+) and inactive (Cerulean-/mCherry+) HIV-1 promoters were characterised. RESULTS: Upon targeted integration of the 5.3 kb vector LTatCL[M] into BACH2, the HIV-1 promoter was gradually silenced as reflected by the decrease in Cerulean expression over a period of 162 days. Silenced HIV-1 promoters could be reactivated by TNF-α and Romidepsin. This observation was independent of the targeted intron and the transcriptional orientation. BACH2 mRNA and protein expression was not impaired by mono-allelic integration of LTatCL[M]. CONCLUSION: Successful targeted integration of the HIV-1-based vector LTatCL[M] allows longitudinal analyses of HIV-1 promoter activity.

Spontaneous reactivation of latent HIV-1 promoters is linked to the cell cycle as revealed by a genetic-insulators-containing dual-fluorescence HIV-1-based vector.

Long-lived latently HIV-1-infected cells represent a barrier to cure. We developed a dual-fluorescence HIV-1-based vector containing a pair of genetic insulators flanking a constitutive fluorescent reporter gene to study HIV-1 latency. The protective effects of these genetic insulators are demonstrated through long-term (up to 394 days) stable fluorescence profiles in transduced SUP-T1 cells. Analysis of 1,941 vector integration sites confirmed reproduction of HIV-1 integration patterns. We sorted monoclonal cells representing latent HIV-1 infections and found that both vector integration sites and integrity of the vector genomes influence the reactivation potentials of latent HIV-1 promoters. Interestingly, some latent monoclonal cells exhibited a small cell subpopulation with a spontaneously reactivated HIV-1 promoter. Higher expression levels of genes involved in cell cycle progression are observed in these cell subpopulations compared to their counterparts with HIV-1 promoters that remained latent. Consistently, larger fractions of spontaneously reactivated cells are in the S and G2 phases of the cell cycle. Furthermore, genistein and nocodazole treatments of these cell clones, which halted cells in the G2 phase, resulted in a 1.4-2.9-fold increase in spontaneous reactivation. Taken together, our HIV-1 latency model reveals that the spontaneous reactivation of latent HIV-1 promoters is linked to the cell cycle.