PLoS Genetics最新文献

The role of mitochondria in immunity is increasingly recognized, but it is unclear how variation in mitochondrial DNA (mtDNA) contributes to variable infection outcomes. To quantify the effect of mtDNA variation on humoral and cell-mediated innate immune responses, we utilized a panel of fruit fly Drosophila melanogaster cytoplasmic hybrids (cybrids), where unique mtDNAs (mitotypes) were introgressed into a controlled isogenic nuclear background. We observed substantial heterogeneity in infection outcomes within the cybrid panel upon bacterial, viral and parasitoid infections, driven by the mitotype. One of the mitotypes, mtKSA2 protected against bacterial, parasitoid, and to a lesser extent, viral infections. Enhanced survival was not a result of improved bacterial clearance, suggesting mtKSA2 confers increased disease tolerance. Transcriptome sequencing showed that the mtKSA2 mitotype had an upregulation of genes related to mitochondrial respiration and phagocytosis in uninfected flies. Upon infection, mtKSA2 flies exhibited infection type and duration specific transcriptomic changes. Furthermore, uninfected mtKSA2 larvae showed immune activation of hemocytes (immune cells), increased hemocyte numbers and ROS production, and enhanced encapsulation response against parasitoid wasp eggs and larvae. Our results show that mtDNA variation acts as an immunomodulatory factor in both humoral and cell-mediated innate immunity and that specific mitotypes can provide broad protection against infections.

Mutations in GBA (glucosylceramidase beta), which encodes the lysosomal enzyme glucocerebrosidase (GCase), are the strongest genetic risk factor for the neurodegenerative disorders Parkinson's disease (PD) and Lewy body dementia. Recent work has suggested that neuroinflammation may be an important factor in the risk conferred by GBA mutations. We therefore systematically tested the contributions of immune-related genes to neuropathology in a Drosophila model of GCase deficiency. We identified target immune factors via RNA-Seq and proteomics on heads from GCase-deficient flies, which revealed both increased abundance of humoral factors and increased macrophage activation. We then manipulated the identified immune factors and measured their effect on head protein aggregates, a hallmark of neurodegenerative disease. Genetic ablation of humoral (secreted) immune factors did not suppress the development of protein aggregation. By contrast, re-expressing Gba1b in activated macrophages suppressed head protein aggregation in Gba1b mutants and rescued their lifespan and behavioral deficits. Moreover, reducing the GCase substrate glucosylceramide in activated macrophages also ameliorated Gba1b mutant phenotypes. Taken together, our findings show that glucosylceramide accumulation due to GCase deficiency leads to macrophage activation, which in turn promotes the development of neuropathology.

Multivariate Mendelian randomization (MVMR) is a statistical technique that uses sets of genetic instruments to estimate the direct causal effects of multiple exposures on an outcome of interest. At genomic loci with pleiotropic gene regulatory effects, that is, loci where the same genetic variants are associated to multiple nearby genes, MVMR can potentially be used to predict candidate causal genes. However, consensus in the field dictates that the genetic instruments in MVMR must be independent (not in linkage disequilibrium), which is usually not possible when considering a group of candidate genes from the same locus. Here we used causal inference theory to show that MVMR with correlated instruments satisfies the instrumental set condition. This is a classical result by Brito and Pearl (2002) for structural equation models that guarantees the identifiability of individual causal effects in situations where multiple exposures collectively, but not individually, separate a set of instrumental variables from an outcome variable. Extensive simulations confirmed the validity and usefulness of these theoretical results. Importantly, the causal effect estimates remained unbiased and their variance small even when instruments are highly correlated, while bias introduced by horizontal pleiotropy or LD matrix sampling error was comparable to standard MR. We applied MVMR with correlated instrumental variable sets at genome-wide significant loci for coronary artery disease (CAD) risk using expression Quantitative Trait Loci (eQTL) data from seven vascular and metabolic tissues in the STARNET study. Our method predicts causal genes at twelve loci, each associated with multiple colocated genes in multiple tissues. We confirm causal roles for PHACTR1 and ADAMTS7 in arterial tissues, among others. However, the extensive degree of regulatory pleiotropy across tissues and the limited number of causal variants in each locus still require that MVMR is run on a tissue-by-tissue basis, and testing all gene-tissue pairs with cis-eQTL associations at a given locus in a single model to predict causal gene-tissue combinations remains infeasible. Our results show that within tissues, MVMR with dependent, as opposed to independent, sets of instrumental variables significantly expands the scope for predicting causal genes in disease risk loci with pleiotropic regulatory effects. However, considering risk loci with regulatory pleiotropy that also spans across tissues remains an unsolved problem.

Abnormal expression of the cell cycle inhibitor and p53 target CDKN1A/p21 has been associated with paradoxical outcomes, such as hyperproliferation in p53-deficient cancer cells or hypoproliferation that affects hematopoietic stem cell behavior, leading to bone marrow failure (BMF). Notably, p21 is known to be overexpressed in Fanconi anemia (FA), which is a rare syndrome that predisposes patients to BMF and cancer. However, why p21 is overexpressed in FA and how it contributes to the FA phenotype(s) are still poorly understood. Here, we revealed that while the upregulation of p21 is largely dependent on p53, it also depends on the transcription factor microphthalmia (MITF) as well as on its interaction with the nucleolar protein NPM1. Upregulation of p21 expression in FA cells leads to p21 accumulation in the chromatin fraction, p21 immunoprecipitation with PCNA, S-phase lengthening and genetic instability. p21 depletion in FA cells rescues the S-phase abnormalities and reduces their genetic instability. In addition, we observed that reactive oxygen species (ROS) accumulation, another key feature of FA cells, is required to trigger an increase in PCNA/chromatin-associated p21 and to impact replication progression. Therefore, we propose a mechanism by which p21 and ROS cooperate to induce replication abnormalities that fuel genetic instability.

Here, we demonstrate that single strand annealing (SSA) can be co-opted for the precise autocatalytic excision of a drive element. We have termed this technology Repeat Mediated Excision of a Drive Element (ReMEDE). By engineering direct repeats flanking the drive allele and inducing a double-strand DNA break (DSB) at a second endonuclease target site within the allele, we increased the utilization of SSA repair. ReMEDE was incorporated into the mutagenic chain reaction (MCR) gene drive targeting the yellow gene of Drosophila melanogaster, successfully replacing drive alleles with wild-type alleles. Sequencing across the Cas9 target site confirmed transgene excision by SSA after pair-mated outcrosses with yReMEDE females, revealing ~4% inheritance of an engineered silent TcG marker sequence. However, phenotypically wild-type flies with alleles of indeterminate biogenesis also were observed, retaining the TGG sequence (~16%) or harboring a silent gGG mutation (~0.5%) at the PAM site. Additionally, ~14% of alleles in the F2 flies were intact or uncut paternally inherited alleles, indicating limited maternal deposition of Cas9 RNP. Although ReMEDE requires further research and development, the technology has some promising features as a gene drive mitigation strategy, notably its potential to restore wild-type populations without additional transgenic releases or large-scale environmental modifications.

Nr2f transcription factors (TFs) are conserved regulators of vertebrate atrial cardiomyocyte (AC) differentiation. However, little is known about the mechanisms directing Nr2f expression in ACs. Here, we identified a conserved enhancer 3' to the nr2f1a locus, which we call 3'reg1-nr2f1a (3'reg1), that can promote Nr2f1a expression in ACs. Sequence analysis of the enhancer identified putative Lef/Tcf and Foxf TF binding sites. Mutation of the Lef/Tcf sites within the 3'reg1 reporter, knockdown of Tcf7l1a, and manipulation of canonical Wnt signaling support that Tcf7l1a is derepressed via Wnt signaling to activate the transgenic enhancer and promote AC differentiation. Similarly, mutation of the Foxf binding sites in the 3'reg1 reporter, coupled with gain- and loss-of-function analysis supported that Foxf1 promotes expression of the enhancer and AC differentiation. Functionally, we find that Wnt signaling acts downstream of Foxf1 to promote expression of the 3'reg1 reporter within ACs and, importantly, both Foxf1 and Wnt signaling require Nr2f1a to promote a surplus of differentiated ACs. CRISPR-mediated deletion of the endogenous 3'reg1 abrogates the ability of Foxf1 and Wnt signaling to produce surplus ACs in zebrafish embryos. Together, our data support that downstream members of a conserved regulatory network involving Wnt signaling and Foxf1 function on a nr2f1a enhancer to promote AC differentiation in the zebrafish heart.

Genome-wide association studies (GWAS) provide valuable insights into the genetic architecture of complex traits, yet interpreting their results remains challenging due to the polygenic nature of most traits. Gene set analysis offers a solution by aggregating genetic variants into biologically relevant pathways, enhancing the detection of coordinated effects across multiple genes. In this study, we present and evaluate a gene set prioritization approach utilizing Bayesian Linear Regression (BLR) models to uncover shared genetic components among different phenotypes and facilitate biological interpretation. Through extensive simulations and analyses of real traits, we demonstrate the efficacy of the BLR model in prioritizing pathways for complex traits. Simulation studies reveal insights into the model's performance under various scenarios, highlighting the impact of factors such as the number of causal genes, proportions of causal variants, heritability, and disease prevalence. Comparative analyses with MAGMA (Multi-marker Analysis of GenoMic Annotation) demonstrate BLR's superior performance, especially in highly overlapped gene sets. Application of both single-trait and multi-trait BLR models to real data, specifically GWAS summary data for type 2 diabetes (T2D) and related phenotypes, identifies significant associations with T2D-related pathways. Furthermore, comparison between single- and multi-trait BLR analyses highlights the superior performance of the multi-trait approach in identifying associated pathways, showcasing increased statistical power when analyzing multiple traits jointly. Additionally, enrichment analysis with integrated data from various public resources supports our results, confirming significant enrichment of diabetes-related genes within the top T2D pathways resulting from the multi-trait analysis. The BLR model's ability to handle diverse genomic features, perform regularization, conduct variable selection, and integrate information from multiple traits, genders, and ancestries demonstrates its utility in understanding the genetic architecture of complex traits. Our study provides insights into the potential of the BLR model to prioritize gene sets, offering a flexible framework applicable to various datasets. This model presents opportunities for advancing personalized medicine by exploring the genetic underpinnings of multifactorial traits.

Three RpoD-family sigma factors, RpoD, RpoS, and RpoH, play critical roles in transcriptional regulation in Salmonella enterica serovar Typhimurium under heat shock conditions. However, the genome-wide regulatory mechanisms of these sigma factors in response to heat stress have remained elusive. In this study, we comprehensively identified 2,319, 2,226, and 213 genome-wide binding sites for RpoD, RpoS, and RpoH, respectively, under sublethal heat shock conditions (42°C). Machine learning-based transcriptome analysis was employed to infer the relative activity of iModulons, providing valuable insights into the transcriptional impact of heat shock. Integrative data analysis enabled the reconstruction of the transcriptional regulatory network of sigma factors, revealing how they modulate gene expression to adapt to heat stress, including responses to anaerobic and oxidative stresses. Notably, we observed a significant expansion of the RpoS sigmulon from 97 to 301 genes in response to heat shock, underscoring the crucial role of RpoS in regulating various metabolic processes. Moreover, we uncovered a competition mechanism between RpoD and RpoS within RpoS sigmulons, where RpoS significantly increases its binding within promoter regions shared with RpoD under heat shock conditions. These findings illuminate how three RpoD-family sigma factors coordinate multiple cellular processes to orchestrate the overall response of S. Typhimurium to heat stress.

Centrosomes are the major microtubule organizing centers of animal cells. Supernumerary centrosomes are a common feature of human tumors and associated with karyotype abnormalities and aggressive disease, but whether they are cause or consequence of cancer remains controversial. Here, we analyzed the consequences of centrosome amplification by generating transgenic mice in which centrosome numbers can be increased by overexpression of the structural centrosome protein STIL. We show that STIL overexpression induces centrosome amplification and aneuploidy, leading to senescence, apoptosis, and impaired proliferation in mouse embryonic fibroblasts, and microcephaly with increased perinatal lethality and shortened lifespan in mice. Importantly, both overall tumor formation in mice with constitutive, global STIL overexpression and chemical skin carcinogenesis in animals with inducible, skin-specific STIL overexpression were reduced, an effect that was not rescued by concomitant interference with p53 function. These results suggest that supernumerary centrosomes impair proliferation in vitro as well as in vivo, resulting in reduced lifespan and delayed spontaneous as well as carcinogen-induced tumor formation.

DPAGT1-CDG is a Congenital Disorder of Glycosylation (CDG) that lacks effective therapies. It is caused by mutations in the gene DPAGT1 which encodes the first enzyme in N-linked glycosylation. We used a Drosophila rough eye model of DPAGT1-CDG with an improperly developed, small eye phenotype. We performed a drug repurposing screen on this model using 1,520 small molecules that are 98% FDA/EMA-approved to find drugs that improved its eye. We identified 42 candidate drugs that improved the DPAGT1-CDG model. Notably from this screen, we found that pharmacological and genetic inhibition of the dopamine D2 receptor partially rescued the DPAGT1-CDG model. Loss of both dopamine synthesis and recycling partially rescued the model, suggesting that dopaminergic flux and subsequent binding to D2 receptors is detrimental under DPAGT1 deficiency. This links dopamine signaling to N-glycosylation and represents a new potential therapeutic target for treating DPAGT1-CDG. We also genetically validate other top drug categories including acetylcholine-related drugs, COX inhibitors, and an inhibitor of NKCC1. These drugs and subsequent analyses reveal novel biology in DPAGT1 mechanisms, and they may represent new therapeutic options for DPAGT1-CDG.