Biology subjects

Finlay-Schultz, J.

Publications and source records attributed to Finlay-Schultz, J..

3 recordsLinked to original sources

bioRxiv2024

Maf1 Cooperates with Progesterone Receptor to Repress RNA Polymerase III Transcription of Select tRNAs

Progesterone receptors (PR) can regulate transcription by RNA Polymerase III (Pol III), which transcribes small non-coding RNAs, including all transfer RNAs (tRNAs). We have previously demonstrated that PR is associated with the Pol III complex at tRNA genes and that progestins downregulate tRNA transcripts in breast tumor models. To further elucidate the mechanism of PR-mediated regulation of Pol III, we studied the interplay between PR, the Pol III repressor Maf1, and TFIIIB, a core transcription component. ChIP-seq was performed for PR, the Pol III subunit POLR3A, the TFIIIB component Brf1, and Maf1 in breast cancer cells with or without progestin treatment. Upon progestin exposure, PR localized to approximately half of POLR3A-occupied tRNA genes, with Maf1 co-recruited to many of these PR-POLR3A sites. While progestin treatment did not significantly alter the number of tRNA genes occupied by Pol III or Brf1, Brf1 occupancy was stabilized, as indicated by increased peak amplitudes. Analysis of nascent tRNA transcription revealed a specific progestin-induced downregulation of approximately one-third of highly expressed tRNA genes. This repression was significantly reduced by Maf1 knockdown, indicating that Maf1 is necessary for PR-mediated tRNA transcription downregulation. Overall, these findings demonstrate a ligand-dependent PR-mediated repression of tRNA transcription through Maf1.

molecular biology↗

bioRxiv2024

Targeting aberrant fatty acid synthesis and storage in endocrine resistant breast cancer cells

BackgroundLipid metabolic reprogramming is increasingly recognized as a hallmark of endocrine resistance in estrogen receptor-positive (ER+) breast cancer. In this study, we investigated alterations in lipid metabolism in ER+ breast cancer cell lines with acquired resistance to common endocrine therapies and evaluated the efficacy of a clinically relevant fatty acid synthase (FASN) inhibitor. MethodsER+ breast cancer cell lines resistant to Tamoxifen (TamR), Fulvestrant (FulvR), and long-term estrogen withdrawal (EWD) were derived. Global gene expression and lipidomic profiling were performed to compare parental and endocrine resistant cells. Lipid storage was assessed using Oil Red O (ORO) staining. The FASN inhibitor TVB-2640 was tested for its impact on lipid storage and cell growth. 13C2-acetate tracing was used to evaluate FASN activity and the efficacy of TVB-2640. ResultsEndocrine resistant cells showed significant enrichment in lipid metabolism pathways and distinct lipidomic profiles, characterized by elevated triglyceride levels and enhanced cytoplasmic lipid droplets. 13C2-acetate tracing revealed increased FASN activity in endocrine resistant cells, which was effectively reduced by TVB-2640. While TVB-2640 reduced lipid storage in most but not all cell lines, this did not correlate with decreased cell growth. Polyunsaturated fatty acids (PUFAs) containing 6 or more double bonds were elevated in endocrine resistant cells and remained unaffected or increased with TVB-2640. ConclusionEndocrine resistant breast cancer cells undergo a metabolic shift toward increased triglyceride storage and PUFAs with high degrees of desaturation. While TVB-2640 reduced lipid storage in most conditions, it had limited effects on the growth of endocrine resistant breast cancer cells. Targeting specific lipid metabolic dependencies, particularly pathways that produce PUFAs, represents a potential therapeutic strategy in endocrine resistant breast cancer.

cancer biology↗

bioRxiv2018

Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries

Single-cell RNA sequencing (scRNA-seq) methods generate sparse gene expression profiles for thousands of single cells in a single experiment. The information in these profiles is sufficient to classify cell types by distinct expression patterns but the high complexity of scRNA-seq libraries often prevents full characterization of transcriptomes from individual cells. To extract more focused gene expression information from scRNA-seq libraries, we developed a strategy to physically recover the DNA molecules comprising transcriptome subsets, enabling deeper interrogation of the isolated molecules by another round of DNA sequencing. We applied the method in cell-centric and gene-centric modes to isolate cDNA fragments from scRNA-seq libraries. First, we resampled the transcriptomes of rare, single megakaryocytes from a complex mixture of lymphocytes and analyzed them in a second round of DNA sequencing, yielding up to 20-fold greater sequencing depth per cell and increasing the number of genes detected per cell from a median of 1,313 to 2,002. We similarly isolated mRNAs from targeted T cells to improve the reconstruction of their VDJ-rearranged immune receptor mRNAs. Second, we isolated CD3D mRNA fragments expressed across cells in a scRNA-seq library prepared from a clonal T cell line, increasing the number of cells with detected CD3D expression from 59.7% to 100%. Transcriptome resampling is a general approach to recover targeted gene expression information from single-cell RNA sequencing libraries that enhances the utility of these costly experiments, and may be applicable to the targeted recovery of molecules from other single-cell assays.

genomics↗