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Karaiskos, S.

Publications and source records attributed to Karaiskos, S..

3 recordsLinked to original sources

Zika and Dengue Viruses Differentially Modulate Host mRNA Processing Factors Defining Its Virulence

Rising global temperatures coupled with increasing international travel, and trade are contributing to spread of vectors such as ticks and mosquitoes, resulting in a surge of vector-borne flavivirus infection in human population. Furthermore, this increase in flavivirus infection pose threat to the safety of biologics such as cell and gene therapy products as human-derived materials are commonly used during manufacturing of these drug products. In this study, we conducted time-course transcriptomic and protein analyses to uncover the host molecular factors driving the virulence of Zika virus (ZIKV) and Dengue virus (DENV) in the context of host defense mechanisms, as these two viruses have caused the most recent and significant flavivirus outbreaks. Compared to DENV, ZIKV exhibited stronger virulence and cytopathic effects. RNA sequencing analysis revealed differential expression of various cellular factors, including RNA processing factors. Further investigation identified cell-type and time-dependent upregulation nonsense-mediated RNA decay (NMD), RNA degradation factors and nuclear pore complex (NPC) transcripts. Protein analysis showed that ZIKV, unlike DENV, degrades NMD factors in host cells, which along with mis-regulation of RNA degradation factors resulted in accumulation in host intronic transcripts as revealed by RNA-seq data. We also found that active nuclear transport is required for ZIKV replication, suggesting that therapeutic targeting of the NPC could potentially be effective in controlling ZIKV infection. Furthermore, from our findings we hypothesize that, ZIKV, but not DENV, drives early host cell cytopathy through targeted protein degradation. Current studies are underway to develop novel strategies to detect ZIKV, DENV and other flaviviruses in biologics based on transcriptomics and proteomics. TeaserExploring the molecular basis of flavivirus virulence in host cells.

genomics↗

Application of Ensemble Machine Learning to Metabolomic Data Identifies Metabolites Associated with Macrophage Polarization

Towards developing quantitative models of anti-tumor activities of macrophages, we evaluated the effects of cytokines, tumor exosomes, and polarization states of macrophages in a tumor microenvironemnt using a system of differential equations. We modeled the non-linear dynamics of macrophage polarization states (M0/M1/M2), tumor cell killing by macrophages, and evasion of macrophage mediated killing by tumor originated extracellular vesicle decoys. Solving these coupled differential equations using numerical approaches, showed that the rate of macrophage polarization into the M1 state is the critical determinant of anti-tumor activity mediated by M1 polarized macrophages. To determine what metabolomic factors correlate with the polarization of naive macrophage into anti-tumor M1 or pro-tumor M2 phenotypes, we performed LC/MS-based untargeted metabolomic analysis. Statistical analysis using Python-Scikit-learn was performed on the metabolomic data from naive, M1 or M2 polarized murine macrophages followed by multiple feature selection methods. Application of ensemble machine learning methods to both secreted and cell associated metabolites revealed novel molecules of fatty acid metabolism to be the main mediators of polarization. Integration of ensemble machine learning feature-ranking tools into our analysis of metabolomic data identified new potential targets in macrophage metabolism for enhancing anti-tumor activities.

bioinformatics↗

Noncanonical Activity of Med4 as a Gatekeeper of Metastasis through Epigenetic Control of Integrin Signaling

Long term survival of breast cancer patients is limited due to recurrence from metastatic dormant cancer cells. However, the mechanisms by which these dormant breast cancer cells survive and awaken remain poorly understood. Our unbiased genome-scale genetic screen in mice identified Med4 as a novel cancer-cell intrinsic gatekeeper in metastatic reactivation. MED4 haploinsufficiency is prevalent in metastatic breast cancer patients and correlates with poorer prognosis. Syngeneic xenograft models revealed that Med4 enforces breast cancer dormancy. Contrary to the canonical function of the Mediator complex in activating gene expression, Med4 maintains 3D chromatin compaction and enhancer landscape, by preventing enhancer priming or activation through the suppression of H3K4me1 deposition. Med4 haploinsufficiency disrupts enhancer poise and reprograms the enhancer dynamics to facilitate extracellular matrix (ECM) gene expression and integrin-mediated mechano-transduction, driving metastatic growth. Our findings establish Med4 as a key regulator of cellular dormancy and a potential biomarker for high-risk metastatic relapse.

cancer biology↗