Biology subjects

Rice, K. M.

Publications and source records attributed to Rice, K. M..

6 recordsLinked to original sources

bioRxiv2026

The galectin-3 carbohydrate recognition domain maintains plasma membrane phosphatidylserine required for KRAS function

KRAS is a small GTPase essential for cellular proliferation, differentiation, and survival. It is predominantly localized to the plasma membrane (PM), where it forms nanoclusters essential for signal transduction. This PM binding and nanoclustering strictly depend on phosphatidylserine (PtdSer), an anionic phospholipid enriched in the inner PM leaflet. Galectin-3 (Gal-3), a {beta}-galactoside-binding lectin implicated in cell growth, migration and tumor progression, has been shown to regulate KRAS PM binding and nanoclustering. Here, we demonstrate that Gal-3 knockout (KO) or inhibition of its carbohydrate recognition domain (CRD) depletes KRAS and PtdSer from the PM. Exogenous PtdSer supplementation fully restores PM PtdSer and partially restores KRAS PM binding, indicating that Gal-3 promotes KRAS PM binding in part by maintaining PM PtdSer content. Total cellular PtdSer, PM PI4P, cholesterol and GM3 are unchanged, excluding these established regulators of PM PtdSer. Instead, Gal-3 CRD inhibition disrupts the cellular balance of sphingomyelin (SM) and ceramide, alters intracellular SM distribution, and impairs the endocytic and recycling transport of PtdSer, SM, and epidermal growth factor receptor (EGFR). Together, our findings demonstrate that Gal-3 CRD activity sustains PM PtdSer content through endocytic trafficking, providing the PM lipid composition required for KRAS PM spatial organization.

cell biology↗

bioRxiv2025

eIF2B Selectively Anchors and Activates Mutant KRAS

Much is known about how RAS oncoproteins regulate mRNA translation factors, but the reverse relationship, how translation factors influence RAS activity, has remained largely unexplored. At the plasma membrane (PM), Son of Sevenless (SOS) acts as the canonical guanine nucleotide exchange factor (GEF) for RAS proteins, yet mechanisms governing its specificity for individual RAS isoforms remain unknown. Here, we show that the translation initiation factor eIF2B, best known for its GEF function in translation initiation, forms a distinct complex with SOS and mutant KRAS at the PM, but not with other oncogenic RAS variants. Mechanistically, eIF2B acts as an allosteric regulator of SOS, selectively enhancing GDP-GTP exchange on mutant KRAS. This specificity arises from the translational activity of eIF2B, which upregulates glycosphingolipid (GSL) biosynthesis to remodel PM lipids and preferentially anchor mutant KRAS. Together, our results uncover an unexpected moonlighting function of eIF2B: acting both as a direct activator of SOS and as a regulator of GSL pathway that shapes the membrane landscape, both required for mutant KRAS activation. These insights redefine our understanding of eIF2B and mutant KRAS functions in cancer and have profound implications for KRAS-driven oncogenesis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/686860v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1f50934org.highwire.dtl.DTLVardef@2f55b9org.highwire.dtl.DTLVardef@1a51e39org.highwire.dtl.DTLVardef@1634aac_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIeIF2B interacts with mutant KRAS and SOS at the plasma membrane (PM). C_LIO_LIThe eIF2B:SOS complex promotes the GTP-bound active state of mutant KRAS. C_LIO_LIeIF2B enhances the translation of B4GALT5 mRNA, encoding a key enzyme of glycosphingolipid (GSL) biosynthesis. C_LIO_LIUpregulation of the GSL metabolites, ganglioside GM3 and sulfatide SM4, remodels PM lipid composition to facilitate eIF2B:SOS:KRAS complex formation and mutant KRAS nanoclustering. C_LIO_LIThrough its interaction with SOS and stimulation of GSL synthesis, eIF2B selectively activates mutant KRAS at the PM among RAS isoforms. C_LIO_LIeIF2B is required for the development of mKRAS-driven lung adenocarcinoma in mice. C_LIO_LIeIF2B is a marker of poor prognosis in mutant KRAS-driven cancers. C_LI

cancer biology↗

bioRxiv2020

Type 2 and interferon inflammation strongly regulate SARS-CoV-2 related gene expression in the airway epithelium

Coronavirus disease 2019 (COVID-19) outcomes vary from asymptomatic infection to death. This disparity may reflect different airway levels of the SARS-CoV-2 receptor, ACE2, and the spike protein activator, TMPRSS2. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci (eQTL) for both ACE2 and TMPRSS2, that vary in frequency across world populations. Importantly, we find TMPRSS2 is part of a mucus secretory network, highly upregulated by T2 inflammation through the action of interleukin-13, and that interferon response to respiratory viruses highly upregulates ACE2 expression. Finally, we define airway responses to coronavirus infections in children, finding that these infections upregulate IL6 while also stimulating a more pronounced cytotoxic immune response relative to other respiratory viruses. Our results reveal mechanisms likely influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.

genomics↗

bioRxiv2020

Population Stratification at the Phenotypic Variance level and Implication for the Analysis of Whole Genome Sequencing Data from Multiple Studies

In modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term variance stratification. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We also illustrate the variance stratification problem, its solutions, and a corresponding diagnostic procedure in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI.

genetics↗

bioRxiv2020

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

BackgroundGenome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To better understand etiological pathways that might lead to discovery of new treatments or prevention strategies, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome while also exploring associations with common variants. Methods and ResultsUsing samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR=1.80, 95% confidence interval: 1.43, 2.27; P=7.12 x 10-7). Three common variants, rs9349379 in PHACTR1, and rs1333048 and rs4977574 in the 9p21 region, were significantly associated with prevalent CHD. Four common variants (rs4977574, rs10757278, rs1333049, and rs1333048) within the 9p21 locus were significantly associated with incident MI. We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) [≥] 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. ConclusionThis study confirmed previously reported loci influencing heart disease risk, and one single variant and three genes associated with MI and CHD were newly identified and warrant future investigation.

genetics↗

bioRxiv2018

A Fully-Adjusted Two-Stage Procedure for Rank Normalization in Genetic Association Studies

When testing genotype-phenotype associations using linear regression, departure of the trait distribution from normality can impact both Type I error rate control and statistical power, with worse consequences for rarer variants. While it has been shown that applying a rank-normalization transformation to trait values before testing may improve these statistical properties, the factor driving them is not the trait distribution itself, but its residual distribution after regression on both covariates and genotype. Because genotype is expected to have a small effect (if any) investigators now routinely use a two-stage method, in which they first regress the trait on covariates, obtain residuals, rank-normalize them, and then secondly use the rank-normalized residuals in association analysis with the genotypes. Potential confounding signals are assumed to be removed at the first stage, so in practice no further adjustment is done in the second stage. Here, we show that this widely-used approach can lead to tests with undesirable statistical properties, due to both a combination of a mis-specified mean-variance relationship, and remaining covariate associations between the rank-normalized residuals and genotypes. We demonstrate these properties theoretically, and also in applications to genome-wide and whole-genome sequencing association studies. We further propose and evaluate an alternative fully-adjusted two-stage approach that adjusts for covariates both when residuals are obtained, and in the subsequent association test. This method can reduce excess Type I errors and improve statistical power.

genetics↗