Tissue-like environments shape functional interactions of HIV-1 with immature dendritic cells.

Immature dendritic cells (iDCs) migrate in microenvironments with distinct cell and extracellular matrix densities in vivo and contribute to HIV-1 dissemination and mounting of antiviral immune responses. Here, we find that, compared to standard 2D suspension cultures, 3D collagen as tissue-like environment alters iDC properties and their response to HIV-1 infection. iDCs adopt an elongated morphology with increased deformability in 3D collagen at unaltered activation, differentiation, cytokine secretion, or responsiveness to LPS. While 3D collagen reduces HIV-1 particle uptake by iDCs, fusion efficiency is increased to elevate productive infection rates due to elevated cell surface exposure of the HIV-1-binding receptor DC-SIGN. In contrast, 3D collagen reduces HIV transfer to CD4 T cells from iDCs. iDC adaptations to 3D collagen include increased pro-inflammatory cytokine production and reduced antiviral gene expression in response to HIV-1 infection. Adhesion to a 2D collagen matrix is sufficient to increase iDC deformability, DC-SIGN exposure, and permissivity to HIV-1 infection. Thus, mechano-physical cues of 2D and 3D tissue-like collagen environments regulate iDC function and shape divergent roles during HIV-1 infection.

HIV- 1 lentivirus tethering to the genome is associated with transcription factor binding sites found in genes that favour virus survival.

Lentiviral vectors (LV) are attractive for permanent and effective gene therapy. However, integration into the host genome can cause insertional mutagenesis highlighting the importance of understanding of LV integration. Insertion site (IS) tethering is believed to involve cellular proteins such as PSIP1/LEDGF/p75, which binds to the virus pre-integration complexes (PICs) helping to target the virus genome. Transcription factors (TF) that bind both the vector LTR and host genome are also suspected influential to this. To determine the role of TF in the tethering process, we mapped predicted transcription factor binding sites (pTFBS) near to IS chosen by HIV-1 LV using a narrow 20 bp window in infected human induced pluripotent stem cells (iPSCs) and their hepatocyte-like cell (HLC) derivatives. We then aligned the pTFBS with these sequences found in the LTRs of native and self-inactivated LTRs. We found significant enrichment of these sequences for pTFBS essential to HIV-1 life cycle and virus survival. These same sites also appear in HIV-1 patient IS and in mice infected with HIV-1 based LV. This in silco data analysis suggests pTFBS present in the virus LTR and IS sites selected by HIV-1 LV are important to virus survival and propagation.

Systematic comparative study of computational methods for T-cell receptor sequencing data analysis.

High-throughput sequencing technologies have exposed the possibilities for the in-depth evaluation of T-cell receptor (TCR) repertoires. These studies are highly relevant to gain insights into human adaptive immunity and to decipher the composition and diversity of antigen receptors in physiological and disease conditions. The major objective of TCR sequencing data analysis is the identification of V, D and J gene segments, complementarity-determining region 3 (CDR3) sequence extraction and clonality analysis. With the advancement in sequencing technologies, new TCR analysis approaches and programs have been developed. However, there is still a deficit of systematic comparative studies to assist in the selection of an optimal analysis approach. Here, we present a detailed comparison of 10 state-of-the-art TCR analysis tools on samples with different complexities by taking into account many aspects such as clonotype detection [unique V(D)J combination], CDR3 identification or accuracy in error correction. We used our in silico and experimental data sets with known clonalities enabling the identification of potential tool biases. We also established a new strategy, named clonal plane, which allows quantifying and comparing the clonality of multiple samples. Our results provide new insights into the effect of method selection on analysis results, and it will assist users in the selection of an appropriate analysis method.

Recombinant AAV Integration Is Not Associated With Hepatic Genotoxicity in Nonhuman Primates and Patients.

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.

Presence of a trs-Like Motif Promotes Rep-Mediated Wild-Type Adeno-Associated Virus Type 2 Integration.

High-throughput integration site (IS) analysis of wild-type adeno-associated virus type 2 (wtAAV2) in human dermal fibroblasts (HDFs) and HeLa cells revealed that juxtaposition of a Rep binding site (RBS) and terminal resolution site (trs)-like motif leads to a 4-fold-increased probability of wtAAV integration. Electrophoretic mobility shift assays (EMSAs) confirmed binding of Rep to off-target RBSs. For the first time, we show Rep protein off-target nicking activity, highlighting the importance of the nicking substrate for Rep-mediated integration.

Generation of lentivirus-induced dendritic cells under GMP-compliant conditions for adaptive immune reconstitution against cytomegalovirus after stem cell transplantation.

BACKGROUND: Reactivation of latent viruses such as human cytomegalovirus (HCMV) after allogeneic hematopoietic stem cell transplantation (HSCT) results in high morbidity and mortality. Effective immunization against HCMV shortly after allo-HSCT is an unmet clinical need due to delayed adaptive T cell development. Donor-derived dendritic cells (DCs) have a critical participation in stimulation of naïve T cells and immune reconstitution, and therefore adoptive DC therapy could be used to protect patients after HSCT. However, previous methods for ex vivo generation of adoptive donor-derived DCs were complex and inconsistent, particularly regarding cell viability and potency after thawing. We have previously demonstrated in humanized mouse models of HSCT the proof-of-concept of a novel modality of lentivirus-induced DCs ("SmyleDCpp65") that accelerated antigen-specific T cell development. METHODS: Here we demonstrate the feasibility of good manufacturing practices (GMP) for production of donor-derived DCs consisting of monocytes from peripheral blood transduced with an integrase-defective lentiviral vector (IDLV, co-expressing GM-CSF, IFN-α and the cytomegalovirus antigen pp65) that were cryopreserved and thawed. RESULTS: Upscaling and standardized production of one lot of IDLV and three lots of SmyleDCpp65 under GMP-compliant conditions were feasible. Analytical parameters for quality control of SmyleDCpp65 identity after thawing and potency after culture were defined. Cell recovery, uniformity, efficacy of gene transfer, purity and viability were high and consistent. SmyleDCpp65 showed only residual and polyclonal IDLV integration, unbiased to proto-oncogenic hot-spots. Stimulation of autologous T cells by GMP-grade SmyleDCpp65 was validated. CONCLUSION: These results underscore further developments of this individualized donor-derived cell vaccine to accelerate immune reconstitution against HCMV after HSCT in clinical trials.

Joint analysis of transcriptional and post- transcriptional brain tumor data: searching for emergent properties of cellular systems.

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.

Common clonal origin of conventional T cells and induced regulatory T cells in breast cancer patients.

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.

VSeq-Toolkit: Comprehensive Computational Analysis of Viral Vectors in Gene Therapy.

Viral vector characterization and analysis are important components for the development of safe gene therapeutic products, elucidating the potential genotoxic and immunogenic effects of vectors and establishing their safety profiles. Here, we present VSeq-Toolkit, which offers varying analysis modes for viral gene therapy data. The first mode determines the undesirable known contaminants and their frequency in viral preparations or other sequencing data. The second mode is designed for the analysis of intra-vector fusion breakpoints and the third mode for unraveling the viral-host fusion events distribution. Analysis modes of our toolkit can be executed independently or together and allow the analysis of multiple viral vectors concurrently. It has been designed and evaluated for the analysis of short read high-throughput sequencing data, including whole-genome or targeted sequencing. VSeq-Toolkit is developed in Perl and Bash programming languages and is available at https://github.com/CompMeth/VSeq-Toolkit.

Spatial-Temporal Variations in Atmospheric Factors Contribute to SARS-CoV-2 Outbreak.

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.

Spatially clustered loci with multiple enhancers are frequent targets of HIV-1 integration.

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.

AAVvector-mediated in vivo reprogramming into pluripotency.

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.

Mapping Active Gene-Regulatory Regions in Human Repopulating Long-Term HSCs.

Genes that regulate hematopoietic stem cell (HSC) self-renewal, proliferation, and differentiation are tightly controlled by regulatory regions. However, mapping such regions relies on surface markers and immunophenotypic definition of HSCs. Here, we use γ-retroviral integration sites (γRV ISs) from a gene therapy trial for 10 patients with Wiskott-Aldrich syndrome to mark active enhancers and promoters in functionally defined long-term repopulating HSCs. Integration site clusters showed the highest ATAC-seq signals at HSC-specific peaks and strongly correlated with hematopoietic risk variants. Tagged genes were significantly enriched for HSC gene sets. We were able to map over 3,000 HSC regulatory regions in late-contributing HSCs, and we used these data to identify miR-10a and miR-335 as two miRNAs regulating early hematopoiesis. In this study, we show that viral insertion sites can be used as molecular tags to assess chromatin conformation on functionally defined cell populations, thereby providing a genome-wide resource for regulatory regions in human repopulating long-term HSCs.

GENE-IS: Time-Efficient and Accurate Analysis of Viral Integration Events in Large-Scale Gene Therapy Data.

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.

Lentiviral Vector Promoter is Decisive for Aberrant Transcript Formation.

Lentiviral vectors hold great promise for the genetic correction of various inherited diseases. However, lentiviral vector biology is still not completely understood and warrants the precise decoding of molecular mechanisms underlying integration and post-translational modification. This study investigated a series of self-inactivating (SIN) and full long terminal repeat (LTR) lentiviral vectors that contained different types of promoters with or without a transgene to gain deeper insights in lentiviral target site selection and potential perturbation of cellular gene expression. Using an optimized nonrestrictive linear amplification-mediated polymerase chain reaction (nrLAM-PCR) protocol, vector structure-dependent integration site profiles were observed upon transduction of mouse lin- hematopoietic progenitors in vitro. Initial target site selection mainly depended on the presence of the promoter while being independent of its nature. Despite the increased propensity for read-through transcription of SIN lentiviral vectors, the incidence of viral-cellular fusion transcript formation involving the canonical viral splice donor or cryptic splice sites was reduced in both unselected primary lin- cells and transformed 32D cells. Moreover, the strength of the internal promoter in vectors with SIN LTRs is decisive for in vitro selection and for the abundance of chimeric transcripts, which are decreased by moderately active promoters. These results will help to better understand vector biology and to optimize therapeutic vectors for future gene therapy applications.

Genetic subclone architecture of tumor clone-initiating cells in colorectal cancer.

A hierarchically organized cell compartment drives colorectal cancer (CRC) progression. Genetic barcoding allows monitoring of the clonal output of tumorigenic cells without prospective isolation. In this study, we asked whether tumor clone-initiating cells (TcICs) were genetically heterogeneous and whether differences in self-renewal and activation reflected differential kinetics among individual subclones or functional hierarchies within subclones. Monitoring genomic subclone kinetics in three patient tumors and corresponding serial xenografts and spheroids by high-coverage whole-genome sequencing, clustering of genetic aberrations, subclone combinatorics, and mutational signature analysis revealed at least two to four genetic subclones per sample. Long-term growth in serial xenografts and spheroids was driven by multiple genomic subclones with profoundly differing growth dynamics and hence different quantitative contributions over time. Strikingly, genetic barcoding demonstrated stable functional heterogeneity of CRC TcICs during serial xenografting despite near-complete changes in genomic subclone contribution. This demonstrates that functional heterogeneity is, at least frequently, present within genomic subclones and independent of mutational subclone differences.

Anti-gene peptide nucleic acid specifically inhibits MYCN expression in human neuroblastoma cells leading to cell growth inhibition and apoptosis.

We developed an anti-gene peptide nucleic acid (PNA) for selective inhibition of MYCN transcription in neuroblastoma cells, targeted against a unique sequence in the antisense DNA strand of exon 2 of MYCN and linked at its NH(2) terminus to a nuclear localization signal peptide. Fluorescence microscopy showed specific nuclear delivery of the PNA in six human neuroblastoma cell lines: GI-LI-N and IMR-32 (MYCN-amplified/overexpressed); SJ-N-KP and NB-100 (MYCN-unamplified/low-expressed); and GI-CA-N and GI-ME-N (MYCN-unamplified/unexpressed). Antiproliferative effects were observable at 24 hours (GI-LI-N, 60%; IMR-32, 70%) and peaked at 72 hours (GI-LI-N, 80%; IMR-32, 90%; SK-N-KP, 60%; NB-100, 50%); no reduction was recorded for GI-CA-N and GI-ME-N (controls). In MYCN-amplified/overexpressed IMR-32 cells and MYCN-unamplified/low-expressed SJ-N-KP cells, inhibition was recorded of MYCN mRNA (by real-time PCR) and N-Myc (Western blotting); these inhibitory effects increased over 3 days after single treatment in IMR-32. Anti-gene PNA induced G(1)-phase accumulation (39-53%) in IMR-32 and apoptosis (56% annexin V-positive cells at 24 hours in IMR-32 and 22% annexin V-positive cells at 48 hours in SJ-N-KP). Selective activity of the PNA was shown by altering three point mutations, and by the observation that an anti-gene PNA targeted against the noncoding DNA strand did not exert any effect. These findings could encourage research into development of an anti-gene PNA-based tumor-specific agent for neuroblastoma (and other neoplasms) with MYCN expression.

A Graph Based Framework to Model Virus Integration Sites.

With next generation sequencing thousands of virus and viral vector integration genome targets are now under investigation to uncover specific integration preferences and to define clusters of integration, termed common integration sites (CIS), that may allow to assess gene therapy safety or to detect disease related genomic features such as oncogenes. Here, we addressed the challenge to: 1) define the notion of CIS on graph models, 2) demonstrate that the structure of CIS enters in the category of scale-free networks and 3) show that our network approach analyzes CIS dynamically in an integrated systems biology framework using the Retroviral Transposon Tagged Cancer Gene Database (RTCGD) as a testing dataset.

Common integration sites of published datasets identified using a graph-based framework.

With next-generation sequencing, the genomic data available for the characterization of integration sites (IS) has dramatically increased. At present, in a single experiment, several thousand viral integration genome targets can be investigated to define genomic hot spots. In a previous article, we renovated a formal CIS analysis based on a rigid fixed window demarcation into a more stretchy definition grounded on graphs. Here, we present a selection of supporting data related to the graph-based framework (GBF) from our previous article, in which a collection of common integration sites (CIS) was identified on six published datasets. In this work, we will focus on two datasets, ISRTCGD and ISHIV, which have been previously discussed. Moreover, we show in more detail the workflow design that originates the datasets.