Biology subjects

Meyers, R. M.

Publications and source records attributed to Meyers, R. M..

7 recordsLinked to original sources

bioRxiv2025

Interactions Between Dietary Metabolites and Regulatory Risk Variants for Human Colon Cancer

Interactions between genetic variants and environmental factors influence malignancy risk, including for colorectal cancer (CRC). Prevalent CRC susceptibility loci reside predominantly in noncoding regulatory DNA where they may interact with dietary influences to dysregulate expression of specific genes predisposing to neoplasia. The impacts of CRC protective and risk dietary metabolites, butyrate and deoxycholic acid, were thus studied on the transcription-directing activity of 3703 regulatory CRC-associated variants via massively parallel reporter assays (MPRA) in human colonic cells. 1595 variant-dietary metabolite interactions were identified, pointing to dysregulation of MED13L, NKD2, and several modulators of Wnt/{beta}-catenin signaling in potential CRC gene-environment interactions (GxE). Opposing impacts of butyrate and deoxycholic acid were also uncovered, indicating dietary influences may converge on common CRC risk loci and nominating FOSL1 and SP1 as mediators of these opposing responses. Coupling MPRA to relevant environmental factors offers an approach to extend insight into GxE in common human cancers.

genomics↗

bioRxiv2025

The Adhesion GPCR ADGRL2 engages Gα13 to Enable Epidermal Differentiation

Homeostasis relies on signaling networks controlled by cell membrane receptors. Although G-protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors, their specific roles in the epidermis are not fully understood. Dual CRISPR-Flow and single cell Perturb-seq knockout screens of all epidermal GPCRs were thus performed, uncovering an essential requirement for adhesion GPCR ADGRL2 (latrophilin 2) in epidermal differentiation. Among potential downstream guanine nucleotide-binding G proteins, ADGRL2 selectively activated G13. Perturb-seq of epidermal G proteins and follow-up tissue knockouts verified that G13 is also required for epidermal differentiation. A cryo-electron microscopy (cryo-EM) structure in lipid nanodiscs showed that ADGRL2 engages with G13 at multiple interfaces, including via a novel interaction between ADGRL2 intracellular loop 3 (ICL3) and a G13-specific QQQ glutamine triplet sequence in its GTPase domain. In situ gene mutation of this interface sequence impaired epidermal differentiation, highlighting an essential new role for an ADGRL2-G13 axis in epidermal differentiation.

cell biology↗

bioRxiv2024

Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis

Identifying noncoding single nucleotide variants (SNVs) in regulatory DNA linked to polygenic disease risk, the transcription factors (TFs) they bind, and the target genes they dysregulate is a goal in polygenic disease research. Massively parallel reporter gene analysis (MPRA) of 3,451 SNVs linked to risk for polygenic skin diseases characterized by disrupted epidermal homeostasis identified 355 differentially active SNVs (daSNVs). daSNV target gene analysis, combined with daSNV editing, underscored dysregulated epidermal differentiation as a pathomechanism shared across common polygenic skin diseases. CRISPR knockout screens of 1772 human TFs revealed 108 TFs essential for epidermal progenitor differentiation, uncovering novel roles for ZNF217, CXXC1, FOXJ2, IRX2 and NRF1. Population sampling CUT&RUN of 27 homeostatic TFs identified allele-specific DNA binding (ASB) differences at daSNVs enriched near epidermal homeostasis and monogenic skin disease genes, with notable representation of SP/KLF and AP-1/2 TFs. This resource implicates dysregulated differentiation in risk for diverse polygenic skin diseases.

genetics↗

bioRxiv2022

Glucose modulates transcription factor dimerization to enable tissue differentiation

Glucose is a universal energy currency for living organisms, however, its non-energetic functions in processes such as differentiation are undefined. In epidermis, differentiating cells exhibit dynamic changes in gene expression1-4 driven by specific transcription factors (TFs)5-9. The interplay between such TFs and biomolecules that also change in this process is not understood. Metabolomic analyses revealed that increased intracellular glucose accompanies differentiation of epidermal keratinocytes. This elevation also occurred in differentiating cells from other tissues and was verified in epidermal tissue engineered with glucose sensors, which detected a glucose gradient that peaked in the outermost differentiated layers. Free glucose accumulation, unaccompanied by its increased metabolism, was essential for epidermal differentiation and required GLUT1, GLUT3, and SGLT1 transporters. Glucose affinity chromatography and azido-glucose click chemistry uncovered glucose binding to diverse regulatory proteins, including the IRF6 TF, whose epidermal knockout confirmed its requirement in glucose-dependent differentiation. Direct glucose binding enabled IRF6 dimerization, DNA binding, genomic localization, and induction of IRF6 target genes, including essential pro-differentiation TFs GRHL1, GRHL3, HOPX and PRDM1. The IRF6R84C mutant found in undifferentiated cancers was unable to bind glucose. These data identify a new role for glucose as a gradient morphogen that modulates protein multimerization in cellular differentiation.

molecular biology↗

bioRxiv2021

Modified forms of easyCLIP

The easyCLIP protocol describes a method for both normal CLIP library construction and the absolute quantification of RNA cross-linking rates, data which could be usefully combined to analyze RNA-protein interactions. Using these cross-linking metrics, significant interactions could be defined relative to a set of random non-RBPs. The original easyCLIP protocol did not use index reads, required custom sequencing primers, and did not have an easily reproducible analysis workflow. This short paper attempts to amend these deficiencies. It also includes some additional technical experiments and investigates the usage of alternative adapters. The results here are intended to allow more options to easily perform and analyze easyCLIP.

molecular biology↗

bioRxiv2019

A genome-wide almanac of co-essential modules assigns function to uncharacterized genes

A central remaining question in the post-genomic era is how genes interact to form biological pathways. Measurements of gene dependency across hundreds of cell lines have been used to cluster genes into co-essential pathways, but this approach has been limited by ubiquitous false positives. Here, we develop a statistical method that enables robust identification of gene co-essentiality and yields a genome-wide set of functional modules. This almanac recapitulates diverse pathways and protein complexes and predicts the functions of 102 uncharacterized genes. Validating top predictions, we show that TMEM189 encodes plasmanylethanolamine desaturase, the long-sought key enzyme for plasmalogen synthesis. We also show that C15orf57 binds the AP2 complex, localizes to clathrin-coated pits, and enables efficient transferrin uptake. Finally, we provide an interactive web tool for the community to explore the results (coessentiality.net). Our results establish co-essentiality profiling as a powerful resource for biological pathway identification and discovery of novel gene functions.

genomics↗

bioRxiv2017

Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells

The CRISPR-Cas9 system has revolutionized gene editing both on single genes and in multiplexed loss-of-function screens, enabling precise genome-scale identification of genes essential to proliferation and survival of cancer cells. However, previous studies reported that an anti-proliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, particularly in the setting of copy number gain1-4. We performed genome-scale CRISPR-Cas9 essentiality screens on 342 cancer cell lines and found that this effect is common to all lines, leading to false positive results when targeting genes in copy number amplified regions. We developed CERES, a computational method to estimate gene dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy-number-specific effect, as well as variable sgRNA activity. We applied CERES to sets of screens performed with different sgRNA libraries and found that it reduces false positive results and provides meaningful estimates of sgRNA activity. As a result, the application of CERES improves confidence in the interpretation of genetic dependency data from CRISPR-Cas9 essentiality screens of cancer cell lines.

genomics↗