<p>  </p> <p>Infection by Marburgvirus (MARV) or the closely related Ebolavirus (EBOV) results in potentially lethal hemorrhagic fever in humans characterized by uncontrolled viremia, a systemic pro-inflammatory response, and multi-organ failure. Currently, there are no approved countermeasures to treat or prevent MARV infection, which leaves a critical need for development of antiviral therapies. One approach to develop antiviral therapies is exploit a virus’s dependency on the host cell and disrupt critical human-viral interactions. While multiple studies identified host-viral interactions involved in EBOV infection, we are currently limited in our knowledge of host-viral interactions that occur during MARV infection and how these interactions influence the viral replication cycle. Thus, the purpose of this research was to identify and further characterize the biological significance of human-MARV protein-protein interactions that occur during infection.</p> <p>Here, we used genome-wide yeast two-hybrid (Y2H) screens to identify directly interacting human-viral proteins. We identified 431 putative interactions with MARV and used a combination of a novel NanoLuc Y2H assay and confidence criteria to prioritize a final set of 396 interactions. Bioinformatic analysis revealed that the molecular functions of the interacting human genes were significantly enriched in RNA binding, cell adhesion, and cytoskeleton binding. </p> <p>MARV and EBOV have many similarities in their genomic organization, sequence, and protein structures that could facilitate interactions to common host factors during infection. Thus, to identify shared interactions between these related viruses, we compared the MARV interactions to EBOV interactions identified in a parallel Y2H screen. We identified 145 human proteins targeted by both MARV and EBOV. The majority (77%) of shared interactions occurred between homologous viral proteins. Additional bioinformatic analyses comparing MARV and EBOV interactions revealed that these viruses interact with different host factors with similar molecular functions (RNA binding, DNA binding, actin and microtubule binding. Together, these data support the notion that while MARV and EBOV target common host factors there are still differences in protein interactions that support functions specific to each virus. </p> <p>To investigate the biological significance of the identified interactions, we focused on host interactions with the viral matrix protein, VP40. VP40 is a multifunctional protein that facilitates viral assembly and budding from the host cell. Y2H assays using VP40 mutants revealed that the WW-containing host protein MAGI1 interacted with the late domain of VP40. This interaction was validated in mammalian cells using coimmunoprecipitation and GFP complementation assays. Based on multiple reports of WW-containing host proteins interacting with VP40, we predict that the interaction between MAGI1 and VP40 regulates viral budding.</p> <p>In conclusion, the work presented here successfully identified 396 novel human-MARV interactions, which furthers the field’s understanding of host factors involved in MARV infection. Additionally, we identified interactions shared by MARV and EBOV, which could be beneficial in the development of a broad antiviral therapy against filoviruses. Lastly, we validate the interaction between MAGI1 and VP40, which has a potential role in viral budding </p>

Breast cancer is the most common cancer type with a high annual death rate. Finding meaningful tissue-related or body-fluid-accessible biomarkers is necessary to characterize cancer subtype, predict tumor behavior, choose the most effective therapy, predict severe treatment-related toxicities, and also the opportunity to personalize treatments for each patient. There is increasing evidence that various kallikrein-related peptidases (Klk) gene family members can modulate the immune response and are differentially regulated in breast cancer, and therefore are proposed to be potential prognostic biomarkers. This work established and validated an experimental setup to study the roles of selected kallikrein-related peptidases (KLK5, KLK7, KLK14) in breast cancer in vivo using gene-deficient mouse models previously generated in our laboratory. We used the CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats) editing system to generate several E0771 cell line-based reporter and gene-deficient cell lines. These allowed enhanced monitoring of cancer progression in vivo and studying KLKs roles in tumor immune microenvironment of C57Bl/6N mice. Finally, we present the analysis of the initial in vivo experiments using these tools combined with established Klk-deficient mouse models. Our...