Biology subjects

Quay, S. C.

Publications and source records attributed to Quay, S. C..

4 recordsLinked to original sources

bioRxiv2025

Evaluation of Probiotic Bacteria for the Reduction of Urea, p-Cresol, and Indole Levels

IntroductionEnd-stage kidney disease (ESKD) is associated with the accumulation of uremic toxins such as urea, p-cresol, and indole, which significantly contribute to systemic complications such as inflammation, oxidative stress, and gut dysbiosis. Probiotics have demonstrated potential in modulating gut microbiota and reducing these toxins. We evaluated the in vitro efficacy of multiple probiotic strains of Lactobacillus, Bifidobacterium, Sterptococcus, Bacillus and others in degrading urea, p-cresol, and indole. MethodsThe probiotic strains were initially trained on toxin media prior to their evaluation of their toxin breakdown efficiency. Additionally microbiological methods using selective Christiansons broth/agar and Stuarts broth/agar were applied to assess urea breakdown. Liquid Chromatography-Mass Spectrometry (LC-MS) was utilized to quantify p-cresol and indole degradation. ResultsThe results indicated that all probiotic strains exhibited significant activity in reducing urea, p-cresol, and indole concentrations in the culture media. In urea breakdown we observed an oscillation urea/ammonia ratio at 24 hr intervals, although a complete elimination of the ammonium byproduct was not feasible. Among all tested probiotics, Lactobacillus species showed the highest efficiency in urea breakdown. Furthermore, the toxin removing efficacy of the probiotics was evaluated in a simulated gut environment using the TNO invitro gut model. ConclusionCumulatively, the findings suggest that probiotics could offer a promising strategy for the reduction of uremic toxins and their associated complications in ESKD patients.

microbiology↗

bioRxiv2024

Comparative analysis of Endoxifen, Tamoxifen and Fulvestrant: A Bioinformatics Approach to Uncover Mechanisms of Action in Breast Cancer

Breast cancer remains a significant health challenge, with estrogen receptor positive (ER+) subtypes being particularly prevalent forms of breast cancer. Current anti-estrogen therapies, such as tamoxifen and fulvestrant, have limitations, including partial agonist activity and resistance development, which evidence the need for more potent alternatives. Endoxifen, a metabolite of tamoxifen, has emerged as a promising breast cancer therapeutic candidate due to its superior anti-estrogenic effects and side effect profile. The omics signatures for endoxifen, tamoxifen and fulvestrant, obtained from publicly available datasets, were aggregated and harmonized by means of the PandaOmics platform, a commercially available target-discovery platform using multiple AI engines including generative pretrained transformers. Pathway enrichment analyses provided insight into these agents mechanisms of action (MOA) in breast cancer. The analyses revealed unexpected variances in several key pathways from expected interactions via estrogen-dependent and independent effects. All three drugs downregulated estrogen signaling and cell cycle-related pathways, such as E2F targets, G2-M checkpoints, Myc targets, and mitotic spindle, and stimulated apoptosis. Fulvestrant and tamoxifen activated pro-inflammatory and immune pathways and perturbed epithelial-mesenchymal transition (EMT). Endoxifen perturbed the PI3K/Akt/mTORC1 pathway, pursuant to distinct molecular mechanisms compared to its parent compound, tamoxifen, and fulvestrant. In summary, advanced AI-driven methodologies demonstrate the capacity to analyze multi-omics data in a comparative way to advance the understanding of endocrine therapy mechanisms in breast cancer. This insight into the distinct effects of endoxifen, tamoxifen, and fulvestrant may aid in selecting the most effective therapies for specific indications and in identifying drug-specific biomarkers.

cancer biology↗

bioRxiv2023

Identification of a novel HKU4-related coronavirus in single-cell datasets and clade viral host analysis

HKU4-related coronaviruses (CoVs) are merbecoviruses related to Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV). In 2022 and 2023, two HKU4-related CoV strains were discovered in Manis javanica (Malayan pangolin) metagenomic datasets derived from organ samples: HKU4-P251T and MjHKU4r-CoV-1. Together with the Tylonycteris robustula bat CoV 162275, which was discovered in 2022, pangolin CoVs HKU4-P251T and MjHKU4r-CoV-1 form a novel phylogenetic clade distinct from all previously documented HKU4-related CoVs. In this study, we identified a novel HKU4-related CoV in a pangolin single-cell sequencing dataset generated by BGI-Shenzhen in Shenzhen, Guangdong, China in 2020. The CoV phylogenetically belongs to the same newly identified clade. The single cell datasets were reported as generated from organ samples of a single pangolin that died of natural causes. 98% of the HKU4-related CoV reads were found in only one of the seven single cell datasets -- a large intestine cell dataset, cells of which exhibit low expression of DPP4. Bacterial contamination was found to be moderately correlated with HKU4-related CoV presence. We further identified with high confidence that the RNA-Seq dataset supporting one of four near identical variants of MjHKU4r-CoV-1 is a Sus scrofa (wild pig) metagenomic dataset, with only a trace level of Manis javanica genomic content. The presence of HKU4-related CoV reads in the dataset are almost certainly laboratory research-related and not from a premortal pangolin or pig infection. Our findings raise concerns about the provenance of the novel HKU4-related CoV we identify here, MjHKU4r-CoV-1 and its four near-identical variants.

genomics↗

bioRxiv2023

Discovery of a novel merbecovirus cDNA clone contaminating agricultural rice sequencing datasets from Wuhan, China

HKU4-related coronaviruses are a group of betacoronaviruses belonging to the same merbecovirus subgenus as Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV), which causes severe respiratory illness in humans with a mortality rate of over 30%. The high genetic similarity between HKU4-related coronaviruses and MERS-CoV makes them an attractive subject of research for modeling potential zoonotic spillover scenarios. In this study, we identify a novel coronavirus contaminating agricultural rice RNA sequencing datasets from Wuhan, China. The datasets were generated by the Huazhong Agricultural University in early 2020. We were able to assemble the complete viral genome sequence, which revealed that it is a novel HKU4-related merbecovirus. The assembled genome is 98.38% identical to the closest known full genome sequence, Tylonycteris pachypus bat isolate BtTp-GX2012. Using in silico modeling, we identified that the novel HKU4-related coronavirus spike protein likely binds to human dipeptidyl peptidase 4 (DPP4), the receptor used by MERS-CoV. We further identified that the novel HKU4-related coronavirus genome has been inserted into a bacterial artificial chromosome in a format consistent with previously published coronavirus infectious clones. Additionally, we have found a near complete read coverage of the spike gene of the MERS-CoV reference strain HCoV-EMC/2012, and identify the likely presence of a HKU4-related-MERS chimera in the datasets. Our findings contribute to the knowledge of HKU4-related coronaviruses and document the use of a previously unpublished HKU4 reverse genetics system in apparent MERS-CoV related gain-of-function research. Our study also emphasizes the importance of improved biosafety protocols in sequencing centers and coronavirus research facilities.

genomics↗