TOX Regulates Growth, DNA Repair, and Genomic Instability in T-cell Acute Lymphoblastic Leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy of thymocytes. Using a transgenic screen in zebrafish, thymocyte selection–associated high mobility group box protein (TOX) was uncovered as a collaborating oncogenic driver that accelerated T-ALL onset by expanding the initiating pool of transformed clones and elevating genomic instability. TOX is highly expressed in a majority of human T-ALL and is required for proliferation and continued xenograft growth in mice. Using a wide array of functional analyses, we uncovered that TOX binds directly to KU70/80 and suppresses recruitment of this complex to DNA breaks to inhibit nonhomologous end joining (NHEJ) repair. Impaired NHEJ is well known to cause genomic instability, including development of T-cell malignancies in KU70- and KU80-deficient mice. Collectively, our work has uncovered important roles for TOX in regulating NHEJ by elevating genomic instability during leukemia initiation and sustaining leukemic cell proliferation following transformation

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Linear scalar quantization of wavelet image decomposition using joint optimization

International audienc

Contribution of InSAR coherence images to evaluate surface elevation change detected from multi-temporal photogrammetric imagery

International audienceThe landscape pattern and topography are affected by natural events and anthropic processes. Detecting and estimating these topographic changes is crucial for understanding the underlying processes (i.e. erosion, morphological changes, vegetation growth, anthropization …). Efficient change detection requires recurrent surveys of the area of interest, effective accuracy to identify and estimate the rate of change, and a reference frame for accuracy assessment (Cook, 2017). The combination of various datasets obtained from different remote sensing approaches, each with specific resolution, enables the 3D monitoring of surface elevation change.The aim of this work is to explore the potential of InSAR data to validate the detected changes in the 3D Earth surface, extracted from the photogrammetric approach. The study area is a watershed, known as Lebna, located in the coastal plain in northeastern Tunisia, inthe Cap Bon peninsula. This watershed is prone to soil erosion mostly enhanced by agricultural practices and Mediterranean climate (Desprats et al., 2013; Mekki et al., 2018). Additionally to a long-term agro-hydrological observatory implemented in the Lebna watershed, providing in-situ data (Molenat et al., 2018), the area of interest is also covered by tri-stereo Pléiades images acquired in 2015, 2018, and 2023, and Sentinel-1 SARinterferometric data from 2017 to 2022. The tri-stereo Pléiades images were processed using the Structure from Motion coupled with the Multi View Stereo (SfM-MVS) algorithms for 3D reconstruction performed with Agisoft Metashape Pro v. 1.6.3. The different processing steps follow the Time-SIFTapproach introduced by Feurer & Vinatier (2018). The DEM of Differences (DoD), calculated by subtracting the early epoch DEM from the following period DEM, allows detecting geomorphological changes between multi-epoch surveys. The InSAR imagery products were used to compare/validate the results derived from the photogrammetric approach. Interferometric coherence images enable the detection of changes of the surface’s scattering properties. The coherence value approaches zero in areas where ground variation occurs between two acquisitions and modifies the structure ofscattering targets, and one where the area is stable (Zebker and Villasenor, 1992). Although erosion is triggered by rainfall events, it is cumulative for long periods. In coherence images, it is expected to be defined as features continuously losing coherence with an expanded temporal baseline. For three coherence images spanning the period from 27/10/2018 to 02/12/2018 the coherence values, for an identified eroded area on the DoD, aregradually decreasing. For newly constructed buildings identified on the DoD, the coherence value abruptly decreases and the decoherence features show structured spatial patterns. However, the interpretation of the coherence variation should be approached carefully. Several components can contribute to its value, such as the viewing geometry, vegetation cover and soil moisture. Further investigation on the decomposition of the coherence according to the above mentioned decorrelation factors is required to explore the changes related to environmental processes such as erosion, by refining the extraction of the erosion information from other signals. To complement erosion detection from coherence images, integrating precipitation dataset helps in understanding the environmental conditions that contribute to soil erosion