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Costa, A. L.

Publications and source records attributed to Costa, A. L..

2 recordsLinked to original sources

Genomic profiling of HIV-1 integration in microglia links viral insertions to TAD organization

HIV-1 persists in anatomically distinct cellular and tissue reservoirs as a stably integrated provirus that is a major barrier to HIV-1 cure. Proviral insertions are largely characterized in blood cells, while HIV-1 integration patterns remain unexplored in microglia, the major brain reservoir. Here, we employ genomics approaches to obtain the first HIV-1 integration site (IS) profiling in microglia and perform in-depth analysis of transcriptome, specific histone signatures and chromatin accessibility on different genomic scales. We show that HIV-1 follows genic insertion patterns into introns of actively transcribed genes, characteristic of blood reservoirs. HIV-1 insertional hotspot analysis by non-negative matrix factorization (NMF)-based approach clusters IS signatures with genic- and super-enhancers. Chromatin accessibility transcription factor (TF) footprints reveal that increased CTCF binding marks latently infected microglia compared to productively infected one. We identify CTCF-enriched topologically associated domain (TAD) borders with signatures of active chromatin as a neighborhood for HIV-1 integration in microglia and CD4+ T cells. Our findings further strengthen the notion that HIV-1 follows the patterns of host cell genome organization to integrate and to establish the silent proviral state and reveal that these principles are largely conserved in different anatomical latent reservoirs.

genomics↗

An integrated pipeline and multi-model graphical user interface for accurate nano-dosimetry

Accurate dosing of nanoparticles is crucial for risk assessment and for their safe use in medical and other applications. Although it is well-known that nanoparticles sediment, diffuse and aggregate as they move through a fluid, and that therefore the effective dose perceived by cells may not necessarily be that initially administered, dose quantification remains a challenge. This is because to date, methods for accurate dose estimation are difficult to implement, involving precise characterization of the nanomaterial and the exposure system as well as complex mathematical operations. Here we present a pipeline for accurate nano-dosimetry of engineered nanoparticles on cell monolayers, based on an easy-to-use graphical software - DosiGUI - which integrates two well-established particokinetic and particodynamic models. DosiGUI is an open source tool which was developed to facilitate nano-dosimetrics. The pipeline includes methods for determining the stickiness index which describes the affinity between nanoparticles and cells. Our results show that accurate estimations of the effective dose cannot prescind from rigorous characterization of the stickiness index, which depends on both nanoparticle characteristics and cell type.

pharmacology and toxicology↗