LRRC10 (Leucine-Rich Repeat Containing Protein 10) and REEP5 (Receptor Accessory Protein 5) as Novel Regulators of Cardiac Excitation-Contraction Coupling Structure and Function

Personalized transcriptome signatures in a cardiomyopathy stem cell biobank

BACKGROUND

There is growing evidence that pathogenic mutations do not fully explain hypertrophic (HCM) or dilated (DCM) cardiomyopathy phenotypes. We hypothesized that if a patient's genetic background was influencing cardiomyopathy this should be detectable as signatures in gene expression. We built a cardiomyopathy biobank resource for interrogating personalized genotype phenotype relationships in human cell lines.

METHODS

We recruited 308 diseased and control patients for our cardiomyopathy stem cell biobank. We successfully reprogrammed PBMCs (peripheral blood mononuclear cells) into induced pluripotent stem cells (iPSCs) for 300 donors. These iPSCs underwent whole genome sequencing and were differentiated into cardiomyocytes for RNA-seq. In addition to annotating pathogenic variants, mutation burden in a panel of cardiomyopathy genes was assessed for correlation with echocardiogram measurements. Line-specific co-expression networks were inferred to evaluate transcriptomic subtypes. Drug treatment targeted the sarcomere, either by activation with omecamtiv mecarbil or inhibition with mavacamten, to alter contractility.

RESULTS

We generated an iPSC biobank from 300 donors, which included 101 individuals with HCM and 88 with DCM. Whole genome sequencing of 299 iPSC lines identified 78 unique pathogenic or likely pathogenic mutations in the diseased lines. Notably, only DCM lines lacking a known pathogenic or likely pathogenic mutation replicated a finding in the literature for greater nonsynonymous SNV mutation burden in 102 cardiomyopathy genes to correlate with lower left ventricular ejection fraction in DCM. We analyzed RNA-sequencing data from iPSC-derived cardiomyocytes for 102 donors. Inferred personalized co-expression networks revealed two transcriptional subtypes of HCM. The first subtype exhibited concerted activation of the co-expression network, with the degree of activation reflective of the disease severity of the donor. In contrast, the second HCM subtype and the entire DCM cohort exhibited partial activation of the respective disease network, with the strength of specific gene by gene relationships dependent on the iPSC-derived cardiomyocyte line. ADCY5 was the largest hubnode in both the HCM and DCM networks and partially corrected in response to drug treatment.

CONCLUSIONS

We have a established a stem cell biobank for studying cardiomyopathy. Our analysis supports the hypothesis the genetic background influences pathologic gene expression programs and support a role for ADCY5 in cardiomyopathy.

Identification and characterization of the receptors of a microneme adhesive repeat domain of Eimeria maxima microneme protein 3 in chicken intestine epithelial cells

Eimeria maxima microneme protein 3 (EmMIC3) is pivotal in the initial recognition and attachment of E. maxima sporozoites to host cells. EmMIC3 comprises 5 tandem Type I microneme adhesive repeat (MAR) domains, among which MAR2 of EmMIC3 (EmMAR2) has been identified as the primary determinant of EmMIC3-mediated tissue tropism. Nonetheless, the mechanisms through which EmMAR2 guides the parasite to its invasion site through interactions with host receptors remained largely uncharted. In this study, we employed yeast two-hybrid (YTH) screening assays and shotgun LC-MS/MS analysis to identify EmMAR2 receptors in chicken intestine epithelial cells. ATPase H+ transporting V1 subunit G1 (ATP6V1G1), receptor accessory protein 5 (REEP5), transmembrane p24 trafficking protein (TMED2), and delta 4-desaturase sphingolipid 1 (DEGS1) were characterized as the 4 receptors of EmMAR2 by both assays. By blocking the interaction of EmMAR2 with each receptor using specific antibodies, we observed varying levels of inhibition on the invasion of E. maxima sporozoites, and the combined usage of all 4 antibodies resulted in the most pronounced inhibitory effect. Additionally, the spatio-temporal expression profiles of ATP6V1G1, REEP5, TMED2, and DEGS1 were assessed. The tissue-specific expression patterns of EmMAR2 receptors throughout E. maxima infection suggested that ATP6V1G1 and DEGS1 might play a role in early-stage invasion, whereas TMED2 could be involved in middle and late-stage invasion and REEP5 and DEGS1 may participate primarily in late-stage invasion. Consequently, E. maxima may employ a multitude of ligand-receptor interactions to drive invasion during different stages of infection. This study marks the first report of EmMAR2 receptors at the interface between E. maxima and the host, providing insights into the invasion mechanisms of E. maxima and the pathogenesis of coccidiosis.

The REEP family of proteins: molecular targets and role in pathophysiology

Receptor expression-enhancing proteins (REEPs) are an evolutionarily conserved protein family that is pivotal to the structure and function of the endoplasmic reticulum (ER). The REEP family can be classified into two major subfamilies in higher species, the REEP1-4 and REEP5-6 subfamilies. Within the REEP1-4 subfamily, REEP1 and REEP2 are closely related, and REEP3 and REEP4 are similarly related. The REEP family is widely distributed in various tissues. Recent studies indicate that the REEP family is involved in many pathological and physiological processes, such as ER morphogenesis and remodeling, microtubule cytoskeleton regulation, and the trafficking and expression of G protein-coupled receptors (GPCRs). Moreover, the REEP family plays crucial roles in the occurrence and development of many diseases, including neurological diseases, diabetes, retinal diseases, cardiac diseases, infertility, obesity, oligoarticular juvenile idiopathic arthritis (OJIA), COVID-19, and cancer. In the present review, we describe the distribution and structure of the REEP family. Furthermore, we summarize the functions and the associated diseases of this family. Based on the pleiotropic actions of the REEP family, the study of its family members is crucial to understanding the relevant pathophysiological processes and developing strategies to modulate and control these related diseases. AVAILABILITY OF DATA AND MATERIAL: The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

Identification of Important Modules and Biomarkers in Breast Cancer Based on WGCNA

Introduction

Breast cancer (BRCA) has the highest incidence among female malignancies, and the prognosis for these patients remains poor.

Materials and Methods

In this study, core modules and central genes related to BRCA were identified through a weighted gene co-expression network analysis (WGCNA). Gene expression profiles and clinical data of GSE25066 were obtained from the Gene Expression Omnibus (GEO) database. The result was validated with RNA-seq data from The Cancer Genome Atlas (TCGA) and Oncomine database. The top 30 key module genes with the highest intramodule connectivity were selected as the core genes (R² = 0.40).

Results

According to TCGA and Oncomine datasets, seven genes were selected as candidate hub genes. Following further experimental verification, four hub genes (FAM171A1, NDFIP1, SKP1, and REEP5) were retained.

Conclusion

We identified four hub genes as candidate biomarkers for BRCA. These hub genes may provide a theoretical basis for targeted therapy against BRCA.