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Bullock, K.

Publications and source records attributed to Bullock, K..

7 recordsLinked to original sources

ANGPTL3 regulates the peroxisomal translocation of SmarcAL1 in response to cell growth states

AbstractAngiopoietin-like 3 (ANGPTL3) is a key regulator of lipoprotein metabolism, known for its potent inhibition on intravascular lipoprotein and endothelial lipase activities. Recent studies have shed light on the cellular functions of ANGPTL3. However, the precise mechanism underlying its regulation of cellular lipid metabolism remains elusive. We recently reported that ANGPTL3 interacts with the chromatin regulator SMARCAL1, which plays a pivotal role in maintaining cellular lipid homeostasis. Here, through a combination of in vitro and in vivo functional analyses, we provide evidence that ANGPTL3 indeed influences cellular lipid metabolism. Increased expression of Angptl3 prompted the formation of lipid droplets (LDs) in response to slow growth conditions. Notably, under the conditions, Angptl3 accumulated within cytoplasmic peroxisomes, where it interacts with SmarcAL1, which translocated from nucleus as observed previously. This translocation induced changes in gene expression favoring triglyceride (TG) accumulation. Indeed, ANGPTL3 gene knockout (KO) in human cells increased the expression of key lipid genes, which could be linked to elevated nuclear localization of SMARCAL1, whereas the expression of these genes decreased in SMARCAL1 KO cells. Consistent with these findings, the injection of Angptl3 protein to mice led to hepatic fat accumulation derived from circulating blood, a phenotype likely indicative of its long-term effect on blood TG, linked to SmarcAL1 activities. Thus, our results suggest that the Angptl3-SmarcAL1 pathway may confer the capacity for TG storage in cells in response to varying growth states, which may have broad implications for this pathway in regulating energy storage and trafficking.

cell biology↗

Genetic screening and metabolomics identify glial adenosine metabolism as a therapeutic target in Parkinson's disease

Neuronal alpha-synucleinopathies, including Parkinson's disease (PD) and dementia with Lewy bodies (DLB), lack disease-modifying therapies. We developed a Drosophila model for identifying novel glial-based therapeutic targets for alpha-synucleinopathies. In this model, human alpha-synuclein is expressed in neurons and individual genes are independently knocked down in glia. We performed a forward genetic screen, knocking down the entire Drosophila kinome in glia in alpha-synuclein expressing flies. Among the top hits were five genes (Ak1, Ak6, Adk1, Adk2, and awd) involved in adenosine metabolism. Knockdown of each gene increased brain adenosine levels, improved locomotor dysfunction, reduced alpha-synuclein oligomer levels, and rescued neurodegeneration. We determined that the mechanism of neuroprotection requires adenosine signaling through the neuronal adenosine receptor (AdoR) in Drosophila. These experiments support glial adenosine as a novel therapeutic target in PD.

neuroscience↗

Mct11 deficiency alters hepatic glucose metabolism and energy homeostasis

Genetic variation at the SLC16A11 locus contributes to the disproportionate impact of type 2 diabetes (T2D) on Latino populations. We recently demonstrated that T2D risk variants reduce SLC16A11 liver expression and function of MCT11, the monocarboxylate transporter encoded by the SLC16A11 gene. Here, we show that SLC16A11 expression within the liver is primarily localized to the low oxygen pericentral region, and that T2D risk variants disrupt oxygen-regulated SLC16A11 expression in human hepatocytes. Under physiologic oxygen conditions, MCT11 deficiency alters hepatocyte glucose metabolism, resulting in elevated intracellular lactate and a metabolic shift toward triacylglycerol accumulation. We also demonstrate an impact of Mct11 deficiency on glucose and lipid metabolism in Slc16a11 knockout mice, which display physiological changes that are observed in individuals with T2D. Our findings provide mechanistic insight into how SLC16A11 disruption impacts hepatic energy metabolism and T2D risk, and highlight MCT11-mediated regulation of lactate levels as a potential therapeutic target.

genetics↗

EDEM3 modulates plasma triglyceride level through its regulation of LRP1 expression

Human genetics studies have uncovered genetic variants that can be used to guide biological research and prioritize molecular targets for therapeutic intervention for complex diseases and metabolic conditions. We have identified a missense variant (P746S) in EDEM3 associated with lower blood triglyceride (TG) levels in >300,000 individuals. Functional analyses in cell and mouse models show that EDEM3 deficiency strongly increased the uptake of very low-density lipoprotein and thereby reduced the plasma TG level, as a result of up-regulated expression of LRP1 receptor. We demonstrate that EDEM3 deletion up-regulated the pathways for RNA and ER protein processing and transport, and consequently increased the cell surface mannose-containing glycoproteins, including LRP1. Metabolomics analyses reveal a cellular TG accumulation under EDEM3 deficiency, a profile consistent with individuals with carrying EDEM3 P746S. Our study identifies EDEM3 as a regulator of blood TG, and targeted inhibition of EDEM3 may provide a complementary approach for lowering elevated blood TG concentrations.

genetics↗

A prospective analysis of circulating plasma metabolomics and ovarian cancer risk

We assessed the association of pre-diagnostic plasma metabolites (N=420) with ovarian cancer risk. We included 252 cases and 252 matched controls from the Nurses Health Studies. Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) comparing the 90th-10th percentile in metabolite levels, using permutation tests to account for testing multiple correlated hypotheses. Weighted gene co-expression network analysis (WGCNA) modules (n=10) and metabolite set enrichment analysis (MSEA; n=23) were also evaluated. Pseudouridine had the strongest statistical association with ovarian cancer risk overall (OR=2.56, 95%CI=1.48-4.45; p=0.001/adjusted-p=0.15). C36:2 phosphatidylcholine (PC) plasmalogen had the strongest statistical association with lower risk (OR=0.11, 95%CI=0.03-0.35; p<0.001/adjusted-p=0.06) and pseudouridine with higher risk (OR=9.84, 95%CI=2.89-37.82; p<0.001/adjusted-p=0.07) of non-serous tumors. Seven WGCNA modules and 15 classes were associated with risk at FDR[&le;]0.20. Triacylglycerols (TAGs) showed heterogeneity by tumor aggressiveness (case-only heterogeneity-p<0.0001). TAG association with risk overall and serous tumors differed by acyl carbon content and saturation. Pseudouridine may be a novel risk factor for ovarian cancer. TAGs may also be important, particularly for rapidly fatal tumors, with associations differing by structural features. Validation in independent prospective studies and complementary experimental work to understand biological mechanisms is needed.

epidemiology↗

netome: a computational framework for metabolite profiling and omics network analysis

SummaryAdvances in metabolomics technologies have enabled comprehensive analyses of associations between metabolites and human disease and have provided a means to study biochemical pathways and processes in detail using model systems. Liquid chromatography tandem mass spectrometry (LC-MS) is an analytical technique commonly used by metabolomics labs to measure hundreds of metabolites of known identity and thousands of \"peaks\" from yet to be identified compounds that are tracked by their measured masses and chromatographic retention times. netome is a computational framework that provides tools for analyzing processed LC-MS data. In this framework, we develop and provide various computational resources including individual software modules to inspect and adjust trends in raw data, align unknown peaks between separately acquired data sets, and to remove redundancies in nontargeted LC-MS data arising from multiple ionization products of a single metabolite. These tools are deployed through computing resources such as web servers and virtual machines with detailed documentation in order to support researchers.\n\nAvailability and implementationnetome is publicly available with extensive documentation and support via issue tracker at https://broadinstitute.github.io/netome under the MIT license. netome includes a set of computational methods that have been designed to execute quality control and post-raw data processing tasks for metabolomics data (e.g. scaling and clustering metabolite abundances), as well as statistical association testing in a network manner (e.g., testing relationship between metabolites and microbes). Each individual tool is available with source code, workshop-oriented documentation which includes instructions for installation and using tools with demonstration examples, and a web server with all services. We also provide a complete image of the netome package with all pre-installed dependencies and support for Google Compute Engine and Amazon EC2. All tools and related services are maintained, and upon new developments, new modules will be added to the environment.\n\nContactrah@broadinstitute.org, clary@broadinstitute.org\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

Endospores and other lysis-resistant bacteria comprise a widely shared core community within the human microbiota

Endospore-formers in the human microbiota are well adapted for host-to-host transmission, and an emerging consensus points to their role in determining health and disease states in the gut. The human gut, more than any other environment, encourages the maintenance of endospore formation, with recent culture-based work suggesting that over 50% of genera in the microbiome carry genes attributed to this trait. However, there has been limited work on the ecological role of endospores and other stress-resistant cellular states in the human gut. In fact, there is no data to indicate whether organisms with the genetic potential to form endospores actually form endospores in situ and how sporulation varies across individuals and over time. Here, we applied a culture-independent protocol to enrich for endospores and other stress-resistant cells in human feces to identify variation in these states across people and within an individual over time. We see that cells with resistant states are more likely than those without to be shared among multiple individuals, which suggests that these resistant states are particularly adapted for cross-host dissemination. Furthermore, we use untargeted fecal metabolomics in 24 individuals and within a person over time to show that these organisms respond to shared environmental signals, and in particular, dietary fatty acids, that likely mediate colonization of recently disturbed human guts.

microbiology↗