Biology subjects

Siefert, J. C.

Publications and source records attributed to Siefert, J. C..

5 recordsLinked to original sources

bioRxiv2025

TRIM33 loss reduces Androgen Receptor transcriptional output and H2BK120 ubiquitination

The Androgen Receptor (AR) is a ligand-dependent transcription factor that drives prostate cancer development and progression. Although, a detailed effect on AR biology has been described for a number of interacting proteins, many AR coregulators remain to be characterized in relation to their distinct impact on AR function. Here, we describe TRIM33 as a conserved AR-interactor across multiple prostate cancer cell lines. We observed that TRIM33 and AR share overall chromatin interaction profiles, in which TRIM33 is involved in downstream responsive transcriptomic output. In contrast to prior reports, we show that TRIM33 does not impact AR protein stability, but instead propose a model in which TRIM33 facilitates maximal AR activity by interfering with H2BK120 ubiquitination levels.

molecular biology↗

bioRxiv2024

AHR activation accelerates the resolution of TGF-β1 induced fibroblast activation and promotes alveolar type 1 cell regeneration in alveolar organoids

Regeneration of the alveolar epithelium is necessary to restore tissue architecture and gas exchange capabilities in chronic pulmonary diseases such as fibrosing interstitial lung disease. While it is known alveolar type 2 (AT2) cells give rise to alveolar type 1 (AT1) cells to repair the alveolar epithelium after injury, methods to promote this process under pathological settings are poorly understood. Here, using a complex 3D organoid culture with TGF-{beta}1 dependent impaired AT1 spheroid formation, we performed a high-throughput screen (HTS) with [~]16,800 compounds to identify small molecules that increase number of AT1 spheroids. Longitudinal single cell RNA sequencing (scRNA-seq) revealed that DB-11-BE87 increased AT1 regeneration by reducing TGF-{beta}1 induced fibroblast activation, concurrently with AHR activation in those cells. These studies highlight a novel HTS system to identify factors that can promote AT1 differentiation and suggest AHR activation as a method to counteract pathological TGF-{beta}1 signaling in pulmonary disease.

cell biology↗

bioRxiv2022

Zebrafish Rif1 Impacts Zygotic Genome Activation, Replication Timing, and Sex Determination

Deregulated DNA replication causes human developmental disorders and cancer, but we know little about how DNA replication is coordinated with changes in transcription and chromatin structure. The initiation of replication forks follows a spatiotemporal pattern called the replication timing program. We have developed the zebrafish into a model system to study the mechanisms by which the replication timing program changes during the extensive changes in the cell cycle, transcription, chromatin organization, and nuclear structure that occur during development. Our previous studies identified changes in DNA replication timing patterns occurring from the onset of zygotic transcription through gastrulation in zebrafish embryos. Rif1 is required for DNA replication timing in a wide range of eukaryotes. The broader role of Rif1 in establishing the replication timing program and chromatin structure during early vertebrate development remains unknown. We have generated Rif1 mutant zebrafish and have performed RNA sequencing and whole-genome replication timing analyses on multiple developmental stages. Rif1 mutants were viable but had a defect in female sex determination. Surprisingly, Rif1 loss predominantly affected DNA replication timing after gastrulation, while its impacts on transcription were more substantial during zygotic genome activation. Our results indicate that Rif1 has distinct roles in DNA replication and transcription control that manifest at different stages of development.

cell biology↗

bioRxiv2022

Identifying commonalities between cell lines and tumors at the single cell level using Sobolev Alignment of deep generative models

Preclinical models are essential to cancer research, however, key biological differences with patient tumors result in reduced translatability to the clinic and high attrition rates in drug development. Variability among and between patients, preclinical models, and individual cells obscures commonalities which could otherwise be exploited therapeutically. To discover the shared biological processes between cell line models and clinical tumors we developed Sobolev Alignment, a computational framework which uses deep generative models to capture non-linear processes in single-cell RNA sequencing data and kernel methods to align and interpret these processes. We show that our approach faithfully captures shared processes on a set of three synthetic datasets. Exploiting two large panels of untreated non-small cell lung cancer cell lines and patients, we identify the similarities between cell lines and tumors and show the conservation of key mitotic and immune-related pathways. Employing our approach on a large in-vitro perturbation screen, we show that processes captured by our method faithfully recapitulate the known modes of action of clinically approved drugs and allow investigation into the mode of action of an uncharacterized drug.

bioinformatics↗

bioRxiv2020

Human Prostate Cancer-Associated Macrophage Subtypes with Prognostic Potential Revealed by Single-cell Transcriptomics

Macrophages in the tumor microenvironment are causally linked with prostate cancer development and progression, yet little is known about their composition in neoplastic human tissue. By performing single cell transcriptomic analysis of human prostate cancer resident macrophages, three distinct populations were identified in the diseased prostate. Unexpectedly, macrophages isolated from the tumor-adjacent site of the prostatectomy specimen were identical to those from the tumorous site. Markers associated with canonical M1 and M2 macrophage phenotypes were identifiable, however these were not the main factors defining unique subtypes. The genes selectively associated with each macrophage cluster were used to develop a gene signature which was highly associated with both recurrence-free and metastasis-free survival. These results highlight the relevance of tissue-specific macrophage subtypes in the tumour microenvironment for prostate cancer progression and demonstrates the utility of profiling single-cell transcriptomics in human tumor samples as a strategy to design gene classifiers for patient prognostication.

immunology↗