Biology subjects

Lara, J.

Publications and source records attributed to Lara, J..

3 recordsLinked to original sources

bioRxiv2020

Characterization of SOX2, OCT4 and NANOG in ovarian cancer tumor-initiating cells

Identification of tumor initiating cells (TICs) has traditionally relied on expression of surface markers such as CD133, CD44, and CD117 and enzymes such as aldehyde dehydrogenase (ALDH). Unfortunately, these markers are often cell type specific and not reproducible across patient samples. A more reliable indication of TICs may include elevated expression of stem cell transcription factors such as SOX2, OCT4, and NANOG that function to support long-term self-renewal, multipotency, and quiescence. RNA-sequencing studies presented here highlight a potential role for SOX2 in cell cycle progression in cells grown as 3-D spheroids, which are more tumorigenic and contain higher numbers of TICs than their 2-D monolayer cultured counterparts. SOX2, OCT4, and NANOG have not been comprehensively evaluated in ovarian cancer cell lines, although their expression is often associated with tumorigenic cells. We hypothesize that SOX2, OCT4, and NANOG will be enriched in ovarian TICs and will correlate with chemotherapy resistance, tumor initiation, and expression of traditional TIC markers. To investigate this hypothesis, we evaluated SOX2, OCT4, and NANOG in a panel of eight ovarian cancer cell lines grown as a monolayer in standard 2-D culture or as spheroids in TIC-enriching 3-D culture. Our data show that the high-grade serous ovarian cancer (HGSOC) lines CAOV3, CAOV4, OVCAR4, and OVCAR8 had longer doubling-times, greater resistance to chemotherapies, and significantly increased expression of SOX2, OCT4, and NANOG in TIC-enriching 3-D culture conditions. We also found that in vitro chemotherapy treatment enriches for cells with significantly higher expression of SOX2. We further show that the traditional TIC marker, CD117 identifies ovarian cancer cells with enhanced SOX2, OCT4, and NANOG expression. Tumor-initiation studies and analysis of The Cancer Genome Atlas (TCGA) suggest a stronger role for SOX2 in ovarian cancer relapse compared with OCT4 or NANOG. Overall, our study clarifies the expression of SOX2, OCT4, and NANOG in TICs from a variety of ovarian cancer cell lines. Our findings suggest that SOX2 expression is a stronger indicator of ovarian TICs with enhanced tumor-initiation capacity and potential for relapse. Improved identification of ovarian TICs will advance our understanding of TIC biology and facilitate the design of better therapies to eliminate TICs and overcome chemotherapy resistance and disease relapse.

cancer biology↗

bioRxiv2020

Quantitative differences between intra-host HCV populations from persons with recently established and persistent infections

BackgroundDetection of incident hepatitis C virus (HCV) infections is crucial for identification of outbreaks and development of public health interventions. However, there is no single diagnostic assay for distinguishing recent and persistent HCV infections. HCV exists in each infected host as a heterogeneous population of genomic variants, whose evolutionary dynamics remain incompletely understood. Genetic analysis of such viral populations can be applied to the detection of incident HCV infections and used to understand intra-host viral evolution. MethodsWe studied intra-host HCV populations sampled using next-generation sequencing from 98 recently and 256 persistently infected individuals. Genetic structure of the populations was evaluated using 245,878 viral sequences from these individuals and a set of selected parameters measuring their diversity, topological structure, complexity, strength of selection, epistasis, evolutionary dynamics, and physico-chemical properties. FindingsDistributions of the viral population parameters differ significantly between recent and persistent infections. A general increase in viral genetic diversity from recent to persistent infections is frequently accompanied by decline in genomic complexity and increase in structuredness of the HCV population, likely reflecting a high level of intra-host adaptation at later stages of infection. Using these findings, we developed a Machine Learning classifier for the infection staging, which yielded a detection accuracy of 95.22%, thus providing a higher accuracy than other genomic-based models. InterpretationThe detection of a strong association between several HCV genetic factors and stages of infection suggests that intra-host HCV population develops in a complex but regular and predictable manner in the course of infection. The proposed models may serve as a foundation of cyber-molecular assays for staging infection, that could potentially complement and/or substitute standard laboratory assays. FundingAZ and PS were supported by NIH grant 1R01EB025022. PIB was supported by GSU MBD fellowship.

bioinformatics↗

bioRxiv2020

Mycobacterium tuberculosis FasR senses long fatty acyl-CoA through a tunnel, inducing DNA-dissociation via a transmission spine

Mycobacterium tuberculosis is a pathogen with a unique cell envelope including very long fatty acids, implicated in bacterial resistance and host immune modulation. FasR is a two-domain transcriptional activator that belongs to the TetR family of regulators, and plays a central role in mycobacterial long-chain fatty acyl-CoA sensing and lipid biosynthesis regulation. We now disclose crystal structures of M. tuberculosis FasR in complex with acyl effector ligands and with DNA, uncovering its sensory and switching mechanisms. A long tunnel traverses the entire effector-binding domain, enabling long fatty acyl effectors to bind. Only when the tunnel is entirely occupied, the protein dimer adopts a rigid configuration, with its DNA-binding domains in an open state that leads to DNA dissociation. Structure-guided point-mutations further support this effector-dependent mechanism. The protein-folding hydrophobic core, connecting the two domains, is completed by the effector ligand into a continuous spine, explaining the allosteric flexible-to-ordered transition. The transmission spine is conserved in all TetR-like transcription factors, offering new opportunities for anti-tuberculosis drug discovery.

microbiology↗