Biology subjects

Terskikh, A.

Publications and source records attributed to Terskikh, A..

9 recordsLinked to original sources

bioRxiv2025

Oncogenic virus hijacks SOX18 pioneer function to enhance viral persistence

Kaposis sarcoma herpesvirus (KSHV) establishes lifelong oncogenic infection in lymphatic endothelial cells (LECs) by ensuring episomal maintenance of its genome via the viral protein LANA. Efficient viral genome maintenance typically involves host DNA replication and episome tethering, but the extent of cell-type-specific regulation remains unclear. Here, we identify that KSHV hijacks the pioneering function of the endothelial-specific transcription factor SOX18 to facilitate persistence of viral episomes. Upon infection, LANA co-opts SOX18 to recruit the SWI/SNF chromatin-remodeling complex via its ATPase subunit BRG1, enhancing chromatin accessibility and enabling efficient viral genome persistence. Disruption of SOX18 or BRG1--genetically or pharmacologically--leads to reduced episome load and attenuated hallmarks of virus infection. This work highlights how viruses can harness lineage-specific transcriptional regulators to establish persistent nuclear retention of their episome into the host genome.

molecular biology↗

bioRxiv2024

Age-associated modulation of TREM1/2- expressing macrophages promotes melanoma progression and metastasis

Aging is a known risk factor for melanoma, yet mechanisms underlying melanoma progression and metastasis in older populations remain largely unexplored. Among the current knowledge gaps is how aging alters phenotypes of cells in the melanoma microenvironment. Here we demonstrate that age enriches the immunosuppressor tumor microenvironment, which is linked to phenotypes associated with melanoma metastasis. Among cellular populations enriched by aging were macrophages with a tolerogenic phenotype expressing TREM2 and dysfunctional CD8-positive cells with an exhausted phenotype, while macrophages with profibrotic phenotype expressing TREM1 were depleted. Notably, TREM1 inhibition decreased melanoma growth in young but not old mice, whereas TREM2 inhibition prevented lung metastasis in aged mice. These data identify novel targets associated with melanoma metastasis and may guide aged-dependent immunotherapies.

cancer biology↗

bioRxiv2022

Microscopic Imaging of Epigenetic Age

Biomarkers of biological age that predict the risk of disease and expected lifespan better than chronological age are key to efficient and cost-effective healthcare1-3. To advance a personalized approach to healthcare, such biomarkers must perform on the individual rather than population level, demonstrate single cell resolution, and provide scalable and cost-effective measurements. We developed a novel approach - image-based chromatin and epigenetic age (ImAge), that utilizes image texture features based on the patterns of chromatin and epigenetic marks in single nuclei. We observed the emergence of intrinsic trajectories of ImAge using dimensionality reduction without regression on chronological age. ImAge was correlated with chronological age in all tissues and organs examined and was consistent with the expected acceleration and/or deceleration of biological age in chronologically identical mice treated with chemotherapy or following a caloric restriction regimen, respectively. ImAge from chronologically identical mice inversely correlated with their locomotor activity (greater activity for younger ImAge), consistent with the essential role of locomotion as an aging biomarker. Finally, we demonstrated that ImAge is reduced upon partial reprogramming in vivo following transient expression of OSKM cassette in the liver and skeletal muscles of old mice and validated the power of ImAge to assess the heterogeneity of reprogramming. We propose that ImAge represents the first-in-class individual-level biomarker of aging and rejuvenation with single-cell resolution.

systems biology↗

bioRxiv2022

Allosteric inhibitors of Zika virus NS2B-NS3 protease targeting protease in super-open conformation

Zika virus (ZIKV) is a member of the Flaviviridae family and is considered a major health threat causing cases of microcephaly in newborns and Guillain-Barre syndrome in adults. Here we targeted a transient deep and hydrophobic pocket of the super-open conformation of ZIKV NS2B-NS3 protease to overcome the limitations of the orthosteric inhibitors. After virtual docking screening of approximately 7 million compounds against the novel allosteric site we selected the top seven candidates and tested them in an enzymatic assay. Six out of seven top candidates selected by the docking screen inhibited ZIKV NS2B-NS3 protease proteolytic activity at low micromolar concentrations, as well as suppressing viral replication. These six compounds, targeting the selected protease pocket conserved in ZIKV as well as several other Flaviviruses, have opened an opportunity for a new kind of drug candidate that might be useful to treat several flaviviral infections.

pharmacology and toxicology↗

bioRxiv2022

Canonical BMP2/4 signaling degrades SOX2 in glioblastoma propagating cells.

The effect of Bone Morphogenetic Proteins (BMPs) on glioblastoma propagation cells (GPCs) is being debated [1-5]. We observed that exposure of GPCs to BMP2/4 initiates a rapid proteasomal degradation of the pluripotency factor SOX2 followed by the differentiation of GPCs into glial cells using 5 primary human glioblastoma lines tested. Enforced expression of SOX2 in GPCs antagonized BMP2/4-induced gliogenesis and reduction of proliferation. Both outcomes are consistent with the role of SOX2 in normal neurogenesis [6-8]. Using gene expression analysis, we observed that level of SOX2 in different glioblastoma lines tracks with the levels of oncogenes H/K/N-RAS and OLIG2. Our work provides support for BMP2/4-SOX2 axis in GPCs and points to the proteasome-regulated degradation of SOX2 that initiates glycogenic differentiation similar to that observed during normal development [6, 7]. Our work supports a potential for developing novel therapeutic strategies aimed at differentiation of GPC into non-tumorigenic glia.

cancer biology↗

bioRxiv2021

DUAL FUNCTION OF ZIKA VIRUS NS2B-NS3 PROTEASE

Zika virus (ZIKV) serine protease, indispensable for viral polyprotein processing and replication, is composed of the membrane-anchored NS2B polypeptide and the N-terminal domain of the NS3 polypeptide (NS3pro). The C-terminal domain of the NS3 polypeptide (NS3hel) is necessary for helicase activity and contains an ATP-binding site. We discovered that ZIKV NS2B-NS3pro can bind single-stranded RNA with a Kd of [~]0.3 M, suggesting a novel function. We tested various structural modifications of NS2B-NS3pro and observed that constructs stabilized in the recently discovered "super-open" conformation do not bind RNA. Likewise, stabilization of NS2B-NS3pro in the "closed" (proteolytically active) conformation using substrate inhibitors abolished RNA binding. We posit that RNA binding occurs when ZIKV NS2B-NS3pro adopts the "open" conformation, which we modeled using highly homologous dengue NS2B-NS3pro crystallized in the open conformation. We identified two positively charged fork-like structures present only in the open conformation of NS3pro. These forks are conserved across Flaviviridae family and could be aligned contiguously with the positively charged grove on NS3hel that binds RNA. This led us to propose the "reverse inchworm" model for a tightly intertwined NS2B-NS3 helicase-protease machinery, which suggests that the cycles of NS2B-NS3pro binding and releasing RNA enable the unlimited processivity of NS3hel. The transition to the closed conformation, likely induced by the substrate, enables the classical protease activity of NS2B-NS3pro.

immunology↗

bioRxiv2019

Improving drug discovery using image-based multiparametric analysis of epigenetic landscape.

With the advent of automatic cell imaging and machine learning, high-content phenotypic screening has become the approach of choice for drug discovery due to its ability to extract drug specific multilayered data and compare it to known profiles. In the field of epigenetics such screening approaches has suffered from the lack of tools sensitive to selective epigenetic perturbations. Here we describe a novel approach Microscopic Imaging of Epigenetic Landscapes (MIEL) that captures patterns of nuclear staining of epigenetic marks (e.g. acetylated and methylated histones) and employs machine learning to accurately distinguish between such patterns (1). We demonstrated that MIEL has superior resolution compared to conventional intensity thresholding techniques and enables efficient detection of epigenetically active compounds, function-based classification, flagging possible off-target effects and even predict novel drug function. We validated MIEL platform across multiple cells lines and using dose-response curves to insure the robustness of this approach for the high content high throughput drug discovery.

cell biology↗

bioRxiv2018

Multiparametric Signature of Glioblastoma Differentiation Revealed by Imaging of Cellular Epigenetic Landscapes

The resistance of Glioblastoma (GBM) to conventional cytotoxic drugs has prompted novel therapeutic strategies, including differentiating tumor propagating cells (TPCs) into less tumorigenic cells using small molecule inducers of TPC differentiation. However, high-throughput screening for such molecules is hampered by the lack of robust markers of GBM differentiation. To obtain a signature of differentiated TPCs, we developed \"Microscopic Imaging of Epigenetic Landscapes\" (MIEL), which captures patterns of nuclear staining for epigenetic marks to derive feature-fingerprints of individual cells. We confirmed MIELs ability to accurately distinguish multiple cell fates and identified a multiparametric epigenetic signature of differentiated TPCs. Critically, we validated epigenetic imaging-based signature using global gene expression thus providing the proof of principle for the MIELs ability to select and prioritize small molecules, which induce TPC differentiation.

cancer biology↗

bioRxiv2018

Modeling gene expression networks to predict interchromosomal organization during human embryonic stem cell differentiation

Cellular differentiation occurs through the regulation of lineage-specific gene expression networks that are facilitated by the spatial organization of the genome. Although techniques based on the chromatin conformation capture (3C) approach have yielded intrachromosomal genome-wide interaction maps, strategies to identify non-random interchromosomal associations is lacking. Therefore, we modeled the genomic organization of chromosomes based on the regulatory networks involved in the differentiation of pluripotent human embryonic stem cells (hESCs) to committed neuronal precursor cells (cNPCs). Importantly, transcriptional regulation has been demonstrated to be a driving force in non-random genome organization. Thus, we constructed coarse-grained in silico networks using gene expression data to identify potential physical associations among chromosomes occurring in situ and then analyzed the three-dimensional (3D) distribution of these chromosomes, assessing how their associations contribute to nuclear organization. Our analysis suggests that coordinate regulation of differentially expressed genes is correlated with the 3D organization of chromosomes in hESC nuclei induced to differentiate to cNPCs.\n\nAuthor SummaryThe cellular commitment and differentiation of stem cells is a hallmark of metazoan development. The ultimate fate of a stem cell is defined by the synergistic modulation of key gene regulatory networks within the nucleus. In our work, we formulate an in silico model describing how the similarity in the expression profile of differentially regulated gene networks is correlated with the higher-order organization of chromosomes during differentiation from human embryonic stem cells (hESCs) to committed neuronal precursor cells (cNPCs). Using graph statistics, we observe that the genome networks generated using the in silico model exhibit properties similar to real-world networks. In addition to modeling how gene expression relates to dynamic changes in chromosome organization, we test the model by calculating the relative proximity of multiple chromosome pairs using 3D fluorescence in situ hybridization (FISH). While various chromosomal properties, including gene density and overall length, have been attributed to chromosome organization, our previous work has identified the emergence of cell-type specific chromosomal topologies related to coordinate gene regulation during cellular differentiation. Here we extend these findings by determining whether our in silico model can predict chromosome association based upon coordinate gene expression. Our work supports the idea that gene co-regulation, in addition to inherent organizational constraints of the nucleus, influences three-dimensional chromosome organization.

systems biology↗