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1.
Nat Genet ; 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31676868

RESUMO

The early stages of type 1 diabetes (T1D) are characterized by local autoimmune inflammation and progressive loss of insulin-producing pancreatic ß cells. Here we show that exposure to proinflammatory cytokines reveals a marked plasticity of the ß-cell regulatory landscape. We expand the repertoire of human islet regulatory elements by mapping stimulus-responsive enhancers linked to changes in the ß-cell transcriptome, proteome and three-dimensional chromatin structure. Our data indicate that the ß-cell response to cytokines is mediated by the induction of new regulatory regions as well as the activation of primed regulatory elements prebound by islet-specific transcription factors. We find that T1D-associated loci are enriched with newly mapped cis-regulatory regions and identify T1D-associated variants disrupting cytokine-responsive enhancer activity in human ß cells. Our study illustrates how ß cells respond to a proinflammatory environment and implicate a role for stimulus response islet enhancers in T1D.

2.
Anal Chem ; 91(18): 11952-11962, 2019 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-31450886

RESUMO

We report on separations of ion isotopologues and isotopomers using ultrahigh-resolution traveling wave-based Structures for Lossless Ion Manipulations with serpentine ultralong path and extended routing ion mobility spectrometry coupled to mass spectrometry (SLIM SUPER IMS-MS). Mobility separations of ions from the naturally occurring ion isotopic envelopes (e.g., [M], [M+1], [M+2], ... ions) showed the first and second isotopic peaks (i.e., [M+1] and [M+2]) for various tetraalkylammonium ions could be resolved from their respective monoisotopic ion peak ([M]) after SLIM SUPER IMS with resolving powers of ∼400-600. Similar separations were obtained for other compounds (e.g., tetrapeptide ions). Greater separation was obtained using argon versus helium drift gas, as expected from the greater reduced mass contribution to ion mobility described by the Mason-Schamp relationship. To more directly explore the role of isotopic substitutions, we studied a mixture of specific isotopically substituted (15N, 13C, and 2H) protonated arginine isotopologues. While the separations in nitrogen were primarily due to their reduced mass differences, similar to the naturally occurring isotopologues, their separations in helium, where higher resolving powers could also be achieved, revealed distinct additional relative mobility shifts. These shifts appeared correlated, after correction for the reduced mass contribution, with changes in the ion center of mass due to the different locations of heavy atom substitutions. The origin of these apparent mass distribution-induced mobility shifts was then further explored using a mixture of Iodoacetyl Tandem Mass Tag (iodoTMT) isotopomers (i.e., each having the same exact mass, but with different isotopic substitution sites). Again, the observed mobility shifts appeared correlated with changes in the ion center of mass leading to multiple monoisotopic mobilities being observed for some isotopomers (up to a ∼0.04% difference in mobility). These mobility shifts thus appear to reflect details of the ion structure, derived from the changes due to ion rotation impacting collision frequency or momentum transfer, and highlight the potential for new approaches for ion structural characterization.

3.
J Chem Inf Model ; 59(9): 4052-4060, 2019 Sep 23.
Artigo em Inglês | MEDLINE | ID: mdl-31430141

RESUMO

The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.

4.
ISME J ; 13(11): 2690-2700, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31243331

RESUMO

In the last decade, extensive application of hydraulic fracturing technologies to unconventional low-permeability hydrocarbon-rich formations has significantly increased natural-gas production in the United States and abroad. The injection of surface-sourced fluids to generate fractures in the deep subsurface introduces microbial cells and substrates to low-permeability rock. A subset of injected organic additives has been investigated for their ability to support biological growth in shale microbial community members; however, to date, little is known on how complex xenobiotic organic compounds undergo biotransformations in this deep rock ecosystem. Here, high-resolution chemical, metagenomic, and proteomic analyses reveal that widely-used surfactants are degraded by the shale-associated taxa Halanaerobium, both in situ and under laboratory conditions. These halotolerant bacteria exhibit surfactant substrate specificities, preferring polymeric propoxylated glycols (PPGs) and longer alkyl polyethoxylates (AEOs) over polyethylene glycols (PEGs) and shorter AEOs. Enzymatic transformation occurs through repeated terminal-end polyglycol chain shortening during co-metabolic growth through the methylglyoxal bypass. This work provides the first evidence that shale microorganisms can transform xenobiotic surfactants in fracture fluid formulations, potentially affecting the efficiency of hydrocarbon recovery, and demonstrating an important association between injected substrates and microbial growth in an engineered subsurface ecosystem.

5.
Expert Rev Proteomics ; 16(7): 569-582, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31232620

RESUMO

Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is the administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage. Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review. Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely to be present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.

6.
Cell ; 177(6): 1600-1618.e17, 2019 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-31150625

RESUMO

Autism spectrum disorder (ASD) manifests as alterations in complex human behaviors including social communication and stereotypies. In addition to genetic risks, the gut microbiome differs between typically developing (TD) and ASD individuals, though it remains unclear whether the microbiome contributes to symptoms. We transplanted gut microbiota from human donors with ASD or TD controls into germ-free mice and reveal that colonization with ASD microbiota is sufficient to induce hallmark autistic behaviors. The brains of mice colonized with ASD microbiota display alternative splicing of ASD-relevant genes. Microbiome and metabolome profiles of mice harboring human microbiota predict that specific bacterial taxa and their metabolites modulate ASD behaviors. Indeed, treatment of an ASD mouse model with candidate microbial metabolites improves behavioral abnormalities and modulates neuronal excitability in the brain. We propose that the gut microbiota regulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.

7.
Anal Chem ; 91(7): 4346-4356, 2019 Apr 02.
Artigo em Inglês | MEDLINE | ID: mdl-30741529

RESUMO

High-throughput, comprehensive, and confident identifications of metabolites and other chemicals in biological and environmental samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent technological advances, metabolomics studies still result in the detection of a disproportionate number of features that cannot be confidently assigned to a chemical structure. This inadequacy is driven by the single most significant limitation in metabolomics, the reliance on reference libraries constructed by analysis of authentic reference materials with limited commercial availability. To this end, we have developed the in silico chemical library engine (ISiCLE), a high-performance computing-friendly cheminformatics workflow for generating libraries of chemical properties. In the instantiation described here, we predict probable three-dimensional molecular conformers (i.e., conformational isomers) using chemical identifiers as input, from which collision cross sections (CCS) are derived. The approach employs first-principles simulation, distinguished by the use of molecular dynamics, quantum chemistry, and ion mobility calculations, to generate structures and chemical property libraries, all without training data. Importantly, optimization of ISiCLE included a refactoring of the popular MOBCAL code for trajectory-based mobility calculations, improving its computational efficiency by over 2 orders of magnitude. Calculated CCS values were validated against 1983 experimentally measured CCS values and compared to previously reported CCS calculation approaches. Average calculated CCS error for the validation set is 3.2% using standard parameters, outperforming other density functional theory (DFT)-based methods and machine learning methods (e.g., MetCCS). An online database is introduced for sharing both calculated and experimental CCS values ( metabolomics.pnnl.gov ), initially including a CCS library with over 1 million entries. Finally, three successful applications of molecule characterization using calculated CCS are described, including providing evidence for the presence of an environmental degradation product, the separation of molecular isomers, and an initial characterization of complex blinded mixtures of exposure chemicals. This work represents a method to address the limitations of small molecule identification and offers an alternative to generating chemical identification libraries experimentally by analyzing authentic reference materials. All code is available at github.com/pnnl .

8.
J Proteome Res ; 18(3): 1426-1432, 2019 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-30667224

RESUMO

The use of mass-spectrometry-based techniques for global protein profiling of biomedical or environmental experiments has become a major focus in research centered on biomarker discovery; however, one of the most important issues recently highlighted in the new era of omics data generation is the ability to perform analyses in a robust and reproducible manner. This has been hypothesized to be one of the issues hindering the ability of clinical proteomics to successfully identify clinical diagnostic and prognostic biomarkers of disease. P-Mart ( https://pmart.labworks.org ) is a new interactive web-based software environment that enables domain scientists to perform quality-control processing, statistics, and exploration of large-complex proteomics data sets without requiring statistical programming. P-Mart is developed in a manner that allows researchers to perform analyses via a series of modules, explore the results using interactive visualization, and finalize the analyses with a collection of output files documenting all stages of the analysis and a report to allow reproduction of the analysis.

9.
J Proteome Res ; 18(2): 694-699, 2019 02 01.
Artigo em Inglês | MEDLINE | ID: mdl-30525668

RESUMO

Targeted proteomics experiments based on selected reaction monitoring (SRM) have gained wide adoption in the use of clinical biomarkers, cellular modeling, and numerous other biological experiments due to their highly accurate and reproducible quantification. The quantitative accuracy in targeted proteomics experiments is reliant on the stable-isotope, heavy-labeled peptide standards that are spiked into a sample and used as a reference when calculating the abundance of endogenous peptides. Therefore, the quality of measurement for these standards is a critical factor in determining whether data acquisition was successful. With improved mass spectrometry (MS) instrumentation that enables the monitoring of hundreds of peptides in hundreds to thousands of samples, quality assessment is increasingly important and cannot be performed manually. We present Q4SRM, a software tool that rapidly checks the signal from all heavy-labeled peptides and flags those that fail quality-control metrics. Using four metrics, the tool detects problems with both individual SRM transitions and the collective group of transitions that monitor a single peptide. The program's speed and simplicity enable its use at the point of data acquisition and can be ideally run immediately upon the completion of a liquid chromatography-SRM-MS analysis.

10.
Analyst ; 2018 Dec 03.
Artigo em Inglês | MEDLINE | ID: mdl-30507980

RESUMO

Mass-spectrometry based omics technologies - namely proteomics, metabolomics and lipidomics - have enabled the molecular level systems biology investigation of organisms in unprecedented detail. There has been increasing interest for gaining a thorough, functional understanding of the biological consequences associated with cellular heterogeneity in a wide variety of research areas such as developmental biology, precision medicine, cancer research and microbiome science. Recent advances in mass spectrometry (MS) instrumentation and sample handling strategies are quickly making comprehensive omics analyses of single cells feasible, but key breakthroughs are still required to push through remaining bottlenecks. In this review, we discuss the challenges faced by single cell MS-based omics analyses and highlight recent technological advances that collectively can contribute to comprehensive and high throughput omics analyses in single cells. We provide a vision of the potential of integrating pioneering technologies such as Structures for Lossless Ion Manipulations (SLIM) for improved sensitivity and resolution, novel peptide identification tactics and standards free metabolomics approaches for future applications in single cell analysis.

11.
J Cheminform ; 10(1): 52, 2018 Oct 26.
Artigo em Inglês | MEDLINE | ID: mdl-30367288

RESUMO

When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties-specifically NMR chemical shifts in this manuscript-via the open source, high-performance computational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model. The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries.

12.
N Engl J Med ; 379(22): 2131-2139, 2018 11 29.
Artigo em Inglês | MEDLINE | ID: mdl-30304647

RESUMO

BACKGROUND: Many patients remain without a diagnosis despite extensive medical evaluation. The Undiagnosed Diseases Network (UDN) was established to apply a multidisciplinary model in the evaluation of the most challenging cases and to identify the biologic characteristics of newly discovered diseases. The UDN, which is funded by the National Institutes of Health, was formed in 2014 as a network of seven clinical sites, two sequencing cores, and a coordinating center. Later, a central biorepository, a metabolomics core, and a model organisms screening center were added. METHODS: We evaluated patients who were referred to the UDN over a period of 20 months. The patients were required to have an undiagnosed condition despite thorough evaluation by a health care provider. We determined the rate of diagnosis among patients who subsequently had a complete evaluation, and we observed the effect of diagnosis on medical care. RESULTS: A total of 1519 patients (53% female) were referred to the UDN, of whom 601 (40%) were accepted for evaluation. Of the accepted patients, 192 (32%) had previously undergone exome sequencing. Symptoms were neurologic in 40% of the applicants, musculoskeletal in 10%, immunologic in 7%, gastrointestinal in 7%, and rheumatologic in 6%. Of the 382 patients who had a complete evaluation, 132 received a diagnosis, yielding a rate of diagnosis of 35%. A total of 15 diagnoses (11%) were made by clinical review alone, and 98 (74%) were made by exome or genome sequencing. Of the diagnoses, 21% led to recommendations regarding changes in therapy, 37% led to changes in diagnostic testing, and 36% led to variant-specific genetic counseling. We defined 31 new syndromes. CONCLUSIONS: The UDN established a diagnosis in 132 of the 382 patients who had a complete evaluation, yielding a rate of diagnosis of 35%. (Funded by the National Institutes of Health Common Fund.).

13.
J Vis Exp ; (135)2018 05 30.
Artigo em Inglês | MEDLINE | ID: mdl-29912205

RESUMO

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges, since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for the simultaneous extraction of metabolites, proteins, and lipids (MPLEx) from the same soil sample was created by adapting a solvent-based approach. This MPLEx protocol has proven to be both simple and robust for many sample types, even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.


Assuntos
Espectrometria de Massas/métodos , Metabolômica/métodos , Solo/química
14.
Int J Syst Evol Microbiol ; 68(6): 2116-2123, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29855404

RESUMO

There was an error in the proposed genus name in the published article, in that the genus 'Salinivirga' was effectively published while this article was in review. Therefore, the genus 'Salinivirga' should be replaced with 'Saliniramus'. For the convenience of future readers, we have included the complete corrected article below, in which all occurrences of the incorrect genus name have been amended: A halophilic bacterial strain, HL-109T, was isolated from the unicyanobacterial consortium UCC-O, which was obtained from the photosynthetic mat of Hot Lake (Washington, USA). A polyphasic approach using phenotypic, genotypic and chemotaxonomic data was used to classify the strain within the order Rhizobiales. The organism stained Gram-negative and was a moderate thermophile with a growth optimum of 45 °C. It was obligately aerobic, heterotrophic and halophilic, growing in both NaCl and MgSO4 brines. The novel isolate had a polymorphic cellular morphology of short rods with occasional branching, and cells were monotrichous. The major fatty acids detected were C18 : 1, C18 : 0, C16 : 0 and C18 : cyc. Phylogenetic analysis of the 16S rRNA gene placed the strain in the order Rhizobiales and it shared 94 % identity with the type strain of its nearest relative, Salinarimonas ramus. Morphological, chemotaxonomic and phylogenetic results did not affiliate the novel organism with any of the families in the Rhizobiales; therefore, HL-109T is representative of a new lineage, for which the name Saliniramus fredricksonii gen. nov., sp. nov. is proposed, with the type strain HL-109T (=JCM 31876T=DSM 102886T). In addition, examination of the phylogenetics of strain HL-109T and its nearest relatives, Salinarimonas ramus and Salinarimonasrosea, demonstrates that these halophiles form a clade distinct from the described families of the Rhizobiales. We further propose the establishment of a new family, Salinarimonadaceae fam. nov., to accommodate the genera Saliniramus and Salinarimonas (the type genus of the family).

15.
Mol Cell Proteomics ; 17(9): 1824-1836, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-29666158

RESUMO

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

16.
Am J Physiol Lung Cell Mol Physiol ; 315(1): L11-L24, 2018 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-29516783

RESUMO

Biochemical networks mediating normal lung morphogenesis and function have important implications for ameliorating morbidity and mortality in premature infants. Although several transcript-level studies have examined normal lung development, corresponding protein-level analyses are lacking. Here we performed proteomics analysis of murine lungs from embryonic to early adult ages to identify the molecular networks mediating normal lung development. We identified 8,932 proteins, providing a deep and comprehensive view of the lung proteome. Analysis of the proteomics data revealed discrete modules and the underlying regulatory and signaling network modulating their expression during development. Our data support the cell proliferation that characterizes early lung development and highlight responses of the lung to exposure to a nonsterile oxygen-rich ambient environment and the important role of lipid (surfactant) metabolism in lung development. Comparison of dynamic regulation of proteomic and recent transcriptomic analyses identified biological processes under posttranscriptional control. Our study provides a unique proteomic resource for understanding normal lung formation and function and can be freely accessed at Lungmap.net.

17.
Int J Syst Evol Microbiol ; 68(5): 1591-1598, 2018 May.
Artigo em Inglês | MEDLINE | ID: mdl-29580321

RESUMO

A halophilic bacterial strain, HL-109T, was isolated from the unicyanobacterial consortium UCC-O, which was obtained from the photosynthetic mat of Hot Lake (Washington, USA). A polyphasic approach using phenotypic, genotypic and chemotaxonomic data was used to classify the strain within the order Rhizobiales. The organism stained Gram-negative and was a moderate thermophile with a growth optimum of 45 °C. It was obligately aerobic, heterotrophic and halophilic, growing in both NaCl and MgSO4 brines. The novel isolate had a polymorphic cellular morphology of short rods with occasional branching, and cells were monotrichous. The major fatty acids detected were C18 : 1, C18 : 0, C16 : 0 and C18 : cyc. Phylogenetic analysis of the 16S rRNA gene placed the strain in the order Rhizobiales and it shared 94 % identity with the type strain of its nearest relative, Salinarimonas ramus. Morphological, chemotaxonomic and phylogenetic results did not affiliate the novel organism with any of the families in the Rhizobiales; therefore, HL-109T is representative of a new lineage, for which the name Salinivirga fredricksonii gen. nov., sp. nov. is proposed, with the type strain HL-109T (=JCM 31876T=DSM 102886T). In addition, examination of the phylogenetics of strain HL-109T and its nearest relatives, Salinarimonas ramus and Salinarimonasrosea, demonstrates that these halophiles form a clade distinct from the described families of the Rhizobiales. We further propose the establishment of a new family, Salinarimonadaceae fam. nov., to accommodate the genera Salinivirga and Salinarimonas (the type genus of the family).


Assuntos
Alphaproteobacteria/classificação , Cianobactérias/classificação , Lagos/microbiologia , Filogenia , Alphaproteobacteria/genética , Técnicas de Tipagem Bacteriana , Composição de Bases , Cianobactérias/genética , Cianobactérias/isolamento & purificação , DNA Bacteriano/genética , Ácidos Graxos/química , RNA Ribossômico 16S/genética , Análise de Sequência de DNA , Washington
18.
Am J Hum Genet ; 102(3): 494-504, 2018 03 01.
Artigo em Inglês | MEDLINE | ID: mdl-29478781

RESUMO

ATP synthase, H+ transporting, mitochondrial F1 complex, δ subunit (ATP5F1D; formerly ATP5D) is a subunit of mitochondrial ATP synthase and plays an important role in coupling proton translocation and ATP production. Here, we describe two individuals, each with homozygous missense variants in ATP5F1D, who presented with episodic lethargy, metabolic acidosis, 3-methylglutaconic aciduria, and hyperammonemia. Subject 1, homozygous for c.245C>T (p.Pro82Leu), presented with recurrent metabolic decompensation starting in the neonatal period, and subject 2, homozygous for c.317T>G (p.Val106Gly), presented with acute encephalopathy in childhood. Cultured skin fibroblasts from these individuals exhibited impaired assembly of F1FO ATP synthase and subsequent reduced complex V activity. Cells from subject 1 also exhibited a significant decrease in mitochondrial cristae. Knockdown of Drosophila ATPsynδ, the ATP5F1D homolog, in developing eyes and brains caused a near complete loss of the fly head, a phenotype that was fully rescued by wild-type human ATP5F1D. In contrast, expression of the ATP5F1D c.245C>T and c.317T>G variants rescued the head-size phenotype but recapitulated the eye and antennae defects seen in other genetic models of mitochondrial oxidative phosphorylation deficiency. Our data establish c.245C>T (p.Pro82Leu) and c.317T>G (p.Val106Gly) in ATP5F1D as pathogenic variants leading to a Mendelian mitochondrial disease featuring episodic metabolic decompensation.

19.
Infect Immun ; 86(5)2018 05.
Artigo em Inglês | MEDLINE | ID: mdl-29483291

RESUMO

Salmonella enterica elicits intestinal inflammation to gain access to nutrients. One of these nutrients is fructose-asparagine (F-Asn). The availability of F-Asn to Salmonella during infection is dependent upon Salmonella pathogenicity islands 1 and 2, which in turn are required to provoke inflammation. Here, we determined that F-Asn is present in mouse chow at approximately 400 pmol/mg (dry weight). F-Asn is also present in the intestinal tract of germfree mice at 2,700 pmol/mg (dry weight) and in the intestinal tract of conventional mice at 9 to 28 pmol/mg. These findings suggest that the mouse intestinal microbiota consumes F-Asn. We utilized heavy-labeled precursors of F-Asn to monitor its formation in the intestine, in the presence or absence of inflammation, and none was observed. Finally, we determined that some members of the class Clostridia encode F-Asn utilization pathways and that they are eliminated from highly inflamed Salmonella-infected mice. Collectively, our studies identify the source of F-Asn as the diet and that Salmonella-mediated inflammation is required to eliminate competitors and allow the pathogen nearly exclusive access to this nutrient.

20.
Proc Natl Acad Sci U S A ; 115(5): E1012-E1021, 2018 01 30.
Artigo em Inglês | MEDLINE | ID: mdl-29339515

RESUMO

Convergent evolution dictates that diverse groups of viruses will target both similar and distinct host pathways to manipulate the immune response and improve infection. In this study, we sought to leverage this uneven viral antagonism to identify critical host factors that govern disease outcome. Utilizing a systems-based approach, we examined differential regulation of IFN-γ-dependent genes following infection with robust respiratory viruses including influenza viruses [A/influenza/Vietnam/1203/2004 (H5N1-VN1203) and A/influenza/California/04/2009 (H1N1-CA04)] and coronaviruses [severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV)]. Categorizing by function, we observed down-regulation of gene expression associated with antigen presentation following both H5N1-VN1203 and MERS-CoV infection. Further examination revealed global down-regulation of antigen-presentation gene expression, which was confirmed by proteomics for both H5N1-VN1203 and MERS-CoV infection. Importantly, epigenetic analysis suggested that DNA methylation, rather than histone modification, plays a crucial role in MERS-CoV-mediated antagonism of antigen-presentation gene expression; in contrast, H5N1-VN1203 likely utilizes a combination of epigenetic mechanisms to target antigen presentation. Together, the results indicate a common mechanism utilized by H5N1-VN1203 and MERS-CoV to modulate antigen presentation and the host adaptive immune response.


Assuntos
Apresentação do Antígeno , Epigênese Genética , Virus da Influenza A Subtipo H5N1/patogenicidade , Coronavírus da Síndrome Respiratória do Oriente Médio/patogenicidade , Animais , Variação Antigênica , Linhagem Celular , Cercopithecus aethiops , Metilação de DNA , Cães , Regulação para Baixo , Histonas/química , Humanos , Células Madin Darby de Rim Canino , Complexo Principal de Histocompatibilidade , Mutação , Fases de Leitura Aberta , Proteômica , Células Vero
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