scholarly journals Biotin rescues mitochondrial dysfunction and neurotoxicity in a tauopathy model

2020 ◽  
Vol 117 (52) ◽  
pp. 33608-33618
Author(s):  
Kelly M. Lohr ◽  
Bess Frost ◽  
Clemens Scherzer ◽  
Mel B. Feany
Keyword(s):  
Mitochondrial Dysfunction ◽  
Metabolic Dysfunction ◽  
Biotin Deficiency ◽  
Aberrant Expression ◽  
A Genome ◽  
Human Neurons ◽  
Mitochondrial Pathology ◽  
B Vitamin ◽  
Genome Scale ◽  
Insight Into

Mitochondrial and metabolic dysfunction are often implicated in neurological disease, but effective mechanism-based therapies remain elusive. We performed a genome-scale forward genetic screen in a Drosophila model of tauopathy, a class of neurodegenerative disorders characterized by the accumulation of the protein tau, and identified manipulation of the B-vitamin biotin as a potential therapeutic approach in tauopathy. We show that tau transgenic flies have an innate biotin deficiency due to tau-mediated relaxation of chromatin and consequent aberrant expression of multiple biotin-related genes, disrupting both carboxylase and mitochondrial function. Biotin depletion alone causes mitochondrial pathology and neurodegeneration in both flies and human neurons, implicating mitochondrial dysfunction as a mechanism in biotin deficiency. Finally, carboxylase biotin levels are reduced in mammalian tauopathies, including brains of human Alzheimer’s disease patients. These results provide insight into pathogenic mechanisms of human biotin deficiency, the resulting effects on neuronal health, and a potential therapeutic pathway in the treatment of tau-mediated neurotoxicity.

scholarly journals Arabidopsis Genes Essential for Seedling Viability: Isolation of Insertional Mutants and Molecular Cloning

Genetics ◽  
2001 ◽  
Vol 159 (4) ◽  
pp. 1765-1778
Author(s):  
Gregory J Budziszewski ◽  
Sharon Potter Lewis ◽  
Lyn Wegrich Glover ◽  
Jennifer Reineke ◽  
Gary Jones ◽  
...  
Keyword(s):  
Large Scale ◽  
Protein Translocation ◽  
Gene Families ◽  
Mutant Phenotype ◽  
Lethal Mutant ◽  
A Genome ◽  
Genes Encoding ◽  
High Level ◽  
Mutant Lines ◽  
Genome Scale

Abstract We have undertaken a large-scale genetic screen to identify genes with a seedling-lethal mutant phenotype. From screening ~38,000 insertional mutant lines, we identified >500 seedling-lethal mutants, completed cosegregation analysis of the insertion and the lethal phenotype for >200 mutants, molecularly characterized 54 mutants, and provided a detailed description for 22 of them. Most of the seedling-lethal mutants seem to affect chloroplast function because they display altered pigmentation and affect genes encoding proteins predicted to have chloroplast localization. Although a high level of functional redundancy in Arabidopsis might be expected because 65% of genes are members of gene families, we found that 41% of the essential genes found in this study are members of Arabidopsis gene families. In addition, we isolated several interesting classes of mutants and genes. We found three mutants in the recently discovered nonmevalonate isoprenoid biosynthetic pathway and mutants disrupting genes similar to Tic40 and tatC, which are likely to be involved in chloroplast protein translocation. Finally, we directly compared T-DNA and Ac/Ds transposon mutagenesis methods in Arabidopsis on a genome scale. In each population, we found only about one-third of the insertion mutations cosegregated with a mutant phenotype.

scholarly journals Genomic Characterization Provides an Insight into the Pathogenicity of the Poplar Canker Bacterium Lonsdalea populi

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 246
Author(s):  
Xiaomeng Chen ◽  
Rui Li ◽  
Yonglin Wang ◽  
Aining Li
Keyword(s):  
Genome Sequence ◽  
Extracellular Enzymes ◽  
De Novo ◽  
Whole Genome Sequence ◽  
Hybrid Poplars ◽  
A Genome ◽  
Conserved Genes ◽  
Genomic Characterization ◽  
Molecular Bases ◽  
Insight Into

An emerging poplar canker caused by the gram-negative bacterium, Lonsdalea populi, has led to high mortality of hybrid poplars Populus × euramericana in China and Europe. The molecular bases of pathogenicity and bark adaptation of L. populi have become a focus of recent research. This study revealed the whole genome sequence and identified putative virulence factors of L. populi. A high-quality L. populi genome sequence was assembled de novo, with a genome size of 3,859,707 bp, containing approximately 3434 genes and 107 RNAs (75 tRNA, 22 rRNA, and 10 ncRNA). The L. populi genome contained 380 virulence-associated genes, mainly encoding for adhesion, extracellular enzymes, secretory systems, and two-component transduction systems. The genome had 110 carbohydrate-active enzyme (CAZy)-coding genes and putative secreted proteins. The antibiotic-resistance database annotation listed that L. populi was resistant to penicillin, fluoroquinolone, and kasugamycin. Analysis of comparative genomics found that L. populi exhibited the highest homology with the L. britannica genome and L. populi encompassed 1905 specific genes, 1769 dispensable genes, and 1381 conserved genes, suggesting high evolutionary diversity and genomic plasticity. Moreover, the pan genome analysis revealed that the N-5-1 genome is an open genome. These findings provide important resources for understanding the molecular basis of the pathogenicity and biology of L. populi and the poplar-bacterium interaction.

scholarly journals Predicting changes in renal metabolism after compound exposure with a genome-scale metabolic model

2021 ◽  
Vol 412 ◽  
pp. 115390
Author(s):  
Kristopher D. Rawls ◽  
Bonnie V. Dougherty ◽  
Kalyan C. Vinnakota ◽  
Venkat R. Pannala ◽  
Anders Wallqvist ◽  
...  
Keyword(s):  
Metabolic Model ◽  
Renal Metabolism ◽  
A Genome ◽  
Compound Exposure ◽  
Genome Scale

scholarly journals Anopheles gambiae Genome Conservation as a Resource for Rational Gene Drive Target Site Selection

Insects ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 97
Author(s):  
Nace Kranjc ◽  
Andrea Crisanti ◽  
Tony Nolan ◽  
Federica Bernardini
Keyword(s):  
Anopheles Gambiae ◽  
Data Storage ◽  
Genomic Variation ◽  
Malaria Vectors ◽  
Anopheles Coluzzii ◽  
Structural Constraints ◽  
Gene Drive ◽  
Genetic Traits ◽  
A Genome ◽  
Insight Into

The increase in molecular tools for the genetic engineering of insect pests and disease vectors, such as Anopheles mosquitoes that transmit malaria, has led to an unprecedented investigation of the genomic landscape of these organisms. The understanding of genome variability in wild mosquito populations is of primary importance for vector control strategies. This is particularly the case for gene drive systems, which look to introduce genetic traits into a population by targeting specific genomic regions. Gene drive targets with functional or structural constraints are highly desirable as they are less likely to tolerate mutations that prevent targeting by the gene drive and consequent failure of the technology. In this study we describe a bioinformatic pipeline that allows the analysis of whole genome data for the identification of highly conserved regions that can point at potential functional or structural constraints. The analysis was conducted across the genomes of 22 insect species separated by more than hundred million years of evolution and includes the observed genomic variation within field caught samples of Anopheles gambiae and Anopheles coluzzii, the two most dominant malaria vectors. This study offers insight into the level of conservation at a genome-wide scale as well as at per base-pair resolution. The results of this analysis are gathered in a data storage system that allows for flexible extraction and bioinformatic manipulation. Furthermore, it represents a valuable resource that could provide insight into population structure and dynamics of the species in the complex and benefit the development and implementation of genetic strategies to tackle malaria.

scholarly journals Genome-Scale Metabolic Network Analysis of the Opportunistic Pathogen Pseudomonas aeruginosa PAO1

2008 ◽  
Vol 190 (8) ◽  
pp. 2790-2803 ◽  
Author(s):  
Matthew A. Oberhardt ◽  
Jacek Puchałka ◽  
Kimberly E. Fryer ◽  
Vítor A. P. Martins dos Santos ◽  
Jason A. Papin
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Metabolic Network ◽  
Opportunistic Pathogen ◽  
Scale Model ◽  
Modeling Framework ◽  
Major Life ◽  
Metabolic Versatility ◽  
A Genome ◽  
Scale Properties ◽  
Genome Scale

ABSTRACT Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.

scholarly journals Evaluation of a Genome-ScaleIn SilicoMetabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

2012 ◽  
Vol 78 (24) ◽  
pp. 8735-8742 ◽  
Author(s):  
Yilin Fang ◽  
Michael J. Wilkins ◽  
Steven B. Yabusaki ◽  
Mary S. Lipton ◽  
Philip E. Long
Keyword(s):  
Proteomic Analysis ◽  
In Silico ◽  
Field Experiments ◽  
Metabolic Model ◽  
Geobacter Metallireducens ◽  
Content Type ◽  
Proteomic Data ◽  
Subsurface Environment ◽  
A Genome ◽  
Genome Scale

ABSTRACTAccurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within anin silicomodel using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model ofGeobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-basedin silicomodelof G. metallireducensrelates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637G. metallireducensproteins detected during the 2008 experiment were associated with specific metabolic reactions in thein silicomodel. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through thein silicomodel reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in thein silicomodel that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

scholarly journals A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Omid Oftadeh ◽  
Pierre Salvy ◽  
Maria Masid ◽  
Maxime Curvat ◽  
Ljubisa Miskovic ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Expression System ◽  
Biomass Composition ◽  
Industrial Biotechnology ◽  
Overflow Metabolism ◽  
Cellular Expression ◽  
A Genome ◽  
Wide Range ◽  
Eukaryotic Organisms ◽  
Genome Scale

AbstractEukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research.

scholarly journals A Genome-Scale Metabolic Model of Anabaena 33047 to Guide Genetic Modifications to Overproduce Nylon Monomers

Metabolites ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 168
Author(s):  
John I. Hendry ◽  
Hoang V. Dinh ◽  
Debolina Sarkar ◽  
Lin Wang ◽  
Anindita Bandyopadhyay ◽  
...  
Keyword(s):  
Electron Transport ◽  
Pyruvate Decarboxylase ◽  
Metabolic Model ◽  
Cell Types ◽  
Economic Feasibility ◽  
Nitrogen Fixing ◽  
Design Algorithm ◽  
A Genome ◽  
Anabaena Sp ◽  
Genome Scale

Nitrogen fixing-cyanobacteria can significantly improve the economic feasibility of cyanobacterial production processes by eliminating the requirement for reduced nitrogen. Anabaena sp. ATCC 33047 is a marine, heterocyst forming, nitrogen fixing cyanobacteria with a very short doubling time of 3.8 h. We developed a comprehensive genome-scale metabolic (GSM) model, iAnC892, for this organism using annotations and content obtained from multiple databases. iAnC892 describes both the vegetative and heterocyst cell types found in the filaments of Anabaena sp. ATCC 33047. iAnC892 includes 953 unique reactions and accounts for the annotation of 892 genes. Comparison of iAnC892 reaction content with the GSM of Anabaena sp. PCC 7120 revealed that there are 109 reactions including uptake hydrogenase, pyruvate decarboxylase, and pyruvate-formate lyase unique to iAnC892. iAnC892 enabled the analysis of energy production pathways in the heterocyst by allowing the cell specific deactivation of light dependent electron transport chain and glucose-6-phosphate metabolizing pathways. The analysis revealed the importance of light dependent electron transport in generating ATP and NADPH at the required ratio for optimal N2 fixation. When used alongside the strain design algorithm, OptForce, iAnC892 recapitulated several of the experimentally successful genetic intervention strategies that over produced valerolactam and caprolactam precursors.

Exploring genomes with a game engine

2014 ◽  
Vol 169 ◽  
pp. 443-453 ◽  
Author(s):  
Jeremiah J. Shepherd ◽  
Lingxi Zhou ◽  
William Arndt ◽  
Yan Zhang ◽  
W. Jim Zheng ◽  
...  
Keyword(s):  
Real Time ◽  
Video Game ◽  
Linear Structure ◽  
Structural Data ◽  
Game Engine ◽  
3D Genome ◽  
Genome Viewer ◽  
A Genome ◽  
Visualization Techniques ◽  
Insight Into

More and more evidence indicates that the 3D conformation of eukaryotic genomes is a critical part of genome function. However, due to the lack of accurate and reliable 3D genome structural data, this information is largely ignored and most of these studies have to use information systems that view the DNA in a linear structure. Visualizing genomes in real time 3D can give researchers more insight, but this is fraught with hardware limitations since each element contains vast amounts of information that cannot be processed on the fly. Using a game engine and sophisticated video game visualization techniques enables us to construct a multi-platform real-time 3D genome viewer. The game engine-based viewer achieves much better rendering speed and can handle much larger amounts of data compared to our previous implementation using OpenGL. Combining this viewer with 3D genome models from experimental data could provide unprecedented opportunities to gain insight into the conformation–function relationships of a genome.

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