Biology subjects

Richard, D. J.

Publications and source records attributed to Richard, D. J..

5 recordsLinked to original sources

bioRxiv2025

Age-related microbiome metabolites modulate splicing and chromatin accessibility in the brain

The gut microbiome generates diverse metabolites that can enter the bloodstream and alter host biology, including brain function. Hundreds of physiologically relevant, gut-brain signaling molecules likely exist; however, there has been no systematic, high-throughput effort to identify and validate them. Here, we integrate computational, in vitro, and in vivo approaches to pinpoint microbiome-derived metabolites whose blood levels change during aging, and that induce molecular changes in the mouse brain. First, we mine large-scale metabolomics datasets from human cohorts (each n [≥] 1200) to identify 30 microbiome-associated metabolites whose blood levels change with age. We then screen this panel in an in vitro transcriptomic assay to identify metabolites that perturb genes linked to age-related neurodegeneration. To assess in vivo relevance, we then test four metabolites in male mice by acute exposure, using multi-omic approaches to evaluate the metabolites impact on cellular functions in the brain. With RNA-seq, we confirm known effects of trimethylamine N-oxide (TMAO), including changes in mitochondrial pathways, and further discover its effects on the pathways of glycolysis, GABAergic signaling, and RNA splicing. Additionally, using both RNA- and ATAC-seq, we identify glycodeoxycholate (GDCA), a microbiome-derived secondary bile acid, as a potent regulator of chromatin accessibility and of genes involved in protecting the brain from age-related stressors. GDCA also acutely reduces locomotion in male but not female mice. In summary, we present a generalizable framework for identifying microbiome metabolites that impact host biology, and apply it to identify age-related microbial metabolites that affect processes related to brain aging and neurodegeneration.

neuroscience↗

bioRxiv2023

Epidermal Growth Factor potentiates EGFR(Y992/1173)-mediated therapeutic response of triple negative breast cancer cells to cold atmospheric plasma-activated medium

Cold atmospheric plasma (CAP) holds promise as a cancer-specific treatment that selectively kills basal-like breast cancer cells. We used CAP-activated media (PAM) to capture the multi-modal chemical species of CAP. Specific antibodies, small molecule inhibitors and CRISPR/Cas9 gene-editing approaches showed an essential role for receptor tyrosine kinases, especially epidermal growth factor (EGF) receptor, in mediating triple negative breast cancer (TNBC) cell responses to PAM. EGF also dramatically enhanced the sensitivity and specificity of PAM against TNBC cells. Site-specific phospho-EGFR analysis, signal transduction inhibitors and reconstitution of EGFR-depleted cells with EGFR-mutants confirmed the role of phospho-tyrosines 992/1173 and phospholipase C gamma signaling in upregulating levels of reactive oxygen species above the apoptotic threshold. EGF-triggered EGFR activation enhanced the sensitivity and selectivity of PAM effects on TNBC cells, such that a strategy based on the synergism of CAP and EGF therapy may provide new opportunities to improve the clinical management of TNBC.

cancer biology↗

bioRxiv2023

Mono-phosphorylation at Ser4 of Barrier-to-autointegration Factor (Banf1) significantly reduces its DNA binding capability by inducing critical changes in its local conformation and DNA binding surface

Barrier-to-Autointegration Factor (Banf1) is a small DNA-bridging protein. The binding status of Banf1 to DNA is regulated by its N-terminal phosphorylation and dephosphorylation, which plays a critical role in cell proliferation. Banf1 can be phosphorylated at Ser4 into mono-phosphorylated Banf1, which is further phosphorylated at Thr3 to form di-phosphorylated Banf1. It was observed decades ago that mono-phosphorylated Banf1 cannot bind to DNA. However, the underlying molecular- and atomic-level mechanisms remain unclear. A clear understanding of these mechanisms will aid in interfering with the cell proliferation process for better global health. Herein, we explored the detailed atomic bases of unphosphorylated Banf1-DNA binding and how mono- and di-phosphorylation of Banf1 impair these atomic bases to eliminate its DNA-binding capability, followed by exploring the DNA-binding capability of mono- and di-phosphorylation Banf1, using comprehensive and systematic molecular modelling and molecular dynamics simulations. This work presented in detail the residue-level binding energies, hydrogen bonds and water bridges between Banf1 and DNA, some of which have not been reported. Moreover, we revealed that mono-phosphorylation of Banf1 causes its N-terminal secondary structure changes, which in turn induce significant changes in Banf1s DNA binding surface, thus eliminating its DNA-binding capability. At the atomic level, we also uncovered the alterations in interactions due to the induction of mono-phosphorylation that result in the N-terminal secondary structure changes of Banf1. Additionally, our modelling showed that phosphorylated Banf1 with their dominant N-terminal secondary structures bind to DNA with a significantly lower affinity and the docked binding pose are not stable in MD simulations. These findings help future studies in predicting effect of mutations in Banf1 on its DNA-binding capability and open a novel avenue for the development of therapeutics such as cancer drugs, targeting cell proliferation by inducing conformational changes in Banf1s N-terminal domain.

biochemistry↗

bioRxiv2021

Deep learning-based pan-cancer classification model reveals cancer-specific gene expression signatures

The identification of cancer-specific biomarkers and therapeutic targets is one of the primary goals of cancer genomics. Thousands of cancer genomes, exomes, and transcriptomes have been sequenced to date. In this study, we conducted a pan-cancer analysis of transcriptome datasets from 37 cancer types provided by The Cancer Genome Atlas (TCGA) in an effort to identify cancer-specific gene expression signatures. We employed deep neural networks to train a model on the transcriptome profile datasets for all cancer types. The model was validated, and its predictive accuracy was determined using an independent dataset, achieving > 97% prediction accuracy across cancer types. This strongly suggests that there are distinct gene expression signatures associated with various cancer types. We interpreted the model using SHapley Additive exPlanations (SHAP) to identify specific gene signatures that significantly contributed to the classification of cancer types. In addition to known biomarkers, we identified several novel biomarkers in different cancer types. These cancer-specific gene signatures are valuable candidates for future studies of their potential utility as cancer biomarkers and putative therapeutic targets.

bioinformatics↗

bioRxiv2020

A biophysical and structural analysis of DNA binding by oligomeric hSSB1 (NABP2/OBFC2B)

The oxidative modification of DNA can result in the loss of genome integrity and must be repaired to maintain overall genomic stability. We have recently demonstrated that human single stranded DNA binding protein 1 (hSSB1/NABP2/OBFC2B) plays a crucial role in the removal of 8-oxo-7,8-dihydro- guanine (8-oxoG), the most common form of oxidative DNA damage. The ability of hSSB1 to form disulphide-bonded tetramers and higher oligomers in an oxidative environment is critical for this process. In this study, we have used nuclear magnetic resonance (NMR) spectroscopy and surface plasmon resonance (SPR) experiments to determine the molecular details of ssDNA binding by oligomeric hSSB1. We reveal that hSSB1 oligomers interact with single DNA strands containing damaged DNA bases; however, our data also show that oxidised bases are recognised in the same manner as undamaged DNA bases. We further demonstrate that oxidised hSSB1 interacts with ssDNA with a significantly higher affinity than its monomeric form confirming that oligomeric proteins such as tetramers can bind directly to ssDNA. NMR experiments provide evidence that oligomeric hSSB1 is able to bind longer ssDNA in both binding polarities using a distinct set of residues different to those of the related SSB from Escherichia coli.

biochemistry↗