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HIV-1 recurrently targets active genes and integrates in the proximity of the nuclear pore compartment in CD4 + T cells. However, the genomic features of these genes and the relevance of their transcriptional activity for HIV-1 integration have so far remained unclear. Here we show that recurrently targeted genes are proximal to super-enhancer genomic elements and that they cluster in specific spatial compartments of the T cell nucleus. We further show that these gene clusters acquire their location during the activation of T cells. The clustering of these genes along with their transcriptional activity are the major determinants of HIV-1 integration in T cells. Our results provide evidence of the relevance of the spatial compartmentalization of the genome for HIV-1 integration, thus further strengthening the role of nuclear architecture in viral infection. HIV-1 usually targets active genes and integrates near the nuclear pore compartment. Here the authors show that recurrently targeted genes are proximal to super-enhancer genomic elements, which cluster in specific spatial compartments of the T cell nucleus, suggesting a role for nuclear organisation in viral infection.

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causing coronavirus disease 2019 (COVID-19) has reached over five million confirmed cases worldwide, and numbers are still growing at a fast rate. Despite the wide outbreak of the infection, a remarkable asymmetry is observed in the number of cases and in the distribution of the severity of the COVID-19 symptoms in patients with respect to the countries/regions. In the early stages of a new pathogen outbreak, it is critical to understand the dynamics of the infection transmission, in order to follow contagion over time and project the epidemiological situation in the near future. While it is possible to reason that observed variation in the number and severity of cases stems from the initial number of infected individuals, the difference in the testing policies and social aspects of community transmissions, the factors that could explain high discrepancy in areas with a similar level of healthcare still remain unknown. Here, we introduce a binary classifier based on an artificial neural network that can help in explaining those differences and that can be used to support the design of containment policies. We found that SARS-CoV-2 infection frequency positively correlates with particulate air pollutants, and specifically with particulate matter 2.5 (PM2.5), while ozone gas is oppositely related with the number of infected individuals. We propose that atmospheric air pollutants could thus serve as surrogate markers to complement the infection outbreak anticipation.

Regulatory CD4 + T cells (Treg) prevent tumor clearance by conventional T cells (Tconv) comprising a major obstacle of cancer immune-surveillance. Hitherto, the mechanisms of Treg repertoire formation in human cancers remain largely unclear. Here, we analyze Treg clonal origin in breast cancer patients using T-Cell Receptor and single-cell transcriptome sequencing. While Treg in peripheral blood and breast tumors are clonally distinct, Tconv clones, including tumor-antigen reactive effectors (Teff), are detected in both compartments. Tumor-infiltrating CD4 + cells accumulate into distinct transcriptome clusters, including early activated Tconv, uncommitted Teff, Th1 Teff, suppressive Treg and pro-tumorigenic Treg. Trajectory analysis suggests early activated Tconv differentiation either into Th1 Teff or into suppressive and pro-tumorigenic Treg. Importantly, Tconv, activated Tconv and Treg share highly-expanded clones contributing up to 65% of intratumoral Treg. Here we show that Treg in human breast cancer may considerably stem from antigen-experienced Tconv converting into secondary induced Treg through intratumoral activation. The mechanisms that shape the regulatory T cell repertoire in patients with cancer are not completely understood. Here, the authors observe that, in breast cancer patients, tumor-resident regulatory T cells do not show clonal relationship with their circulating counterpart, but share a common origin with intratumoral antigen-experienced conventional T cells.

An adeno-associated virus (AAV) vector encoding a variant of human lipoprotein lipase was recently approved in Europe as the first gene therapy for the treatment of LPL deficiency. Here Manfred Schmidt and his colleagues report their analysis of AAV integration sites after injection of the gene therapy construct in LPL-deficient patients and in mice. The clinical application of adeno-associated virus vectors (AAVs) is limited because of concerns about AAV integration–mediated tumorigenicity. We performed integration-site analysis after AAV1-LPL S447X intramuscular injection in five lipoprotein lipase–deficient subjects, revealing random nuclear integration and hotspots in mitochondria. We conclude that AAV integration is potentially safe and that vector breakage and integration may occur from each position of the vector genome. Future viral integration-site analyses should include the mitochondrial genome.

Integration site profiling and clonality analysis of viral vector distribution in gene therapy is a key factor to monitor the fate of gene-corrected cells, assess the risk of malignant transformation, and establish vector biosafety. We developed the Genome Integration Site Analysis Pipeline (GENE-IS) for highly time-efficient and accurate detection of next-generation sequencing (NGS)-based viral vector integration sites (ISs) in gene therapy data. It is the first available tool with dual analysis mode that allows IS analysis both in data generated by PCR-based methods, such as linear amplification method PCR (LAM-PCR), and by rapidly evolving targeted sequencing (e.g., Agilent SureSelect) technologies. GENE-IS makes use of trimming strategies, customized reference genome, and soft-clipped information with sequential filtering steps to provide annotated IS with clonality information. It is a scalable, robust, precise, and reliable tool for large-scale pre-clinical and clinical data analysis that provides users complete flexibility and control over analysis with a broad range of configurable parameters. GENE-IS is available at https://github.com/G100DKFZ/gene-is.

In vivo reprogramming of somatic cells into induced pluripotent stem cells (iPSC) holds vast potential for basic research and regenerative medicine. However, it remains hampered by a need for vectors to express reprogramming factors (Oct-3/4, Klf4, Sox2, c-Myc; OKSM) in selected organs. Here, we report OKSM delivery vectors based on pseudotyped Adeno-associated virus (AAV). Using the AAV-DJ capsid, we could robustly reprogram mouse embryonic fibroblasts with low vector doses. Swapping to AAV8 permitted to efficiently reprogram somatic cells in adult mice by intravenous vector delivery, evidenced by hepatic or extra-hepatic teratomas and iPSC in the blood. Notably, we accomplished full in vivo reprogramming without c-Myc. Most iPSC generated in vitro or in vivo showed transcriptionally silent, intronic or intergenic vector integration, likely reflecting the increased host genome accessibility during reprogramming. Our approach crucially advances in vivo reprogramming technology, and concurrently facilitates investigations into the mechanisms and consequences of AAV persistence. In vivo reprogramming of somatic cells is hampered by the need for vectors to express the OKSM factors in selected organs. Here the authors report new AAV-based vectors capable of in vivo reprogramming at low doses.

[...]to design a platform independent from gene transfer conditions, the authors implemented their third generation of FGB, which is comprised of an optimal combination of six mono- and bicistronic vectors that, in addition, have been marked by a color-specific molecular barcode upstream of the 3′ long terminal repeat (LTR) (Figure 1). [...]both studies further extend the potential of fluorescent barcoding. [...]using a genetic barcoding system that incorporates combinations of unique molecular identifiers may improve the accuracy of clonal quantification and assure independence from normal intracellular gene expression regulation.

Background Advances in biotechnology offer a fast growing variety of high-throughput data for screening molecular activities of genomic, transcriptional, post-transcriptional and translational observations. However, to date, most computational and algorithmic efforts have been directed at mining data from each of these molecular levels (genomic, transcriptional, etc.) separately. In view of the rapid advances in technology (new generation sequencing, high-throughput proteomics) it is important to address the problem of analyzing these data as a whole, i.e. preserving the emergent properties that appear in the cellular system when all molecular levels are interacting. We analyzed one of the (currently) few datasets that provide both transcriptional and post-transcriptional data of the same samples to investigate the possibility to extract more information, using a joint analysis approach. Results We use Factor Analysis coupled with pre-established knowledge as a theoretical base to achieve this goal. Our intention is to identify structures that contain information from both mRNAs and miRNAs, and that can explain the complexity of the data. Despite the small sample available, we can show that this approach permits identification of meaningful structures, in particular two polycistronic miRNA genes related to transcriptional activity and likely to be relevant in the discrimination between gliosarcomas and other brain tumors. Conclusions This suggests the need to develop methodologies to simultaneously mine information from different levels of biological organization, rather than linking separate analyses performed in parallel.

Recombinant adeno-associated viral vectors (rAAV) currently constitute a real therapeutic strategy for the sustained correction of diverse genetic conditions. Though a wealth of preclinical and clinical studies have been conducted with rAAV, the oncogenic potential of these vectors is still controversial, particularly when considering liver-directed gene therapy. Few preclinical studies and the recent discovery of incomplete wild-type AAV2 genomes integrated in human hepatocellular carcinoma biopsies have raised concerns on rAAV safety. In the present study, we have characterized the integration of both complete and partial rAAV2/5 genomes in nonhuman primate tissues and clinical liver biopsies from a trial aimed to treat acute intermittent porphyria. We applied a new multiplex linear amplification-mediated polymerase chain reaction (PCR) assay capable of detecting integration events that are originated throughout the rAAV genome. The integration rate was low both in nonhuman primates and patient's samples. Importantly, no integration clusters or events were found in genes previously reported to link rAAV integration with hepatocellular carcinoma development, thus showing the absence of genotoxicity of a systemically administered rAAV2/5 in a large animal model and in the clinical context.