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Results: 1 to 10 of 105

Publication Record


Response of Secondary Metabolism of Hypogean Actinobacterial Genera to Chemical and Biological Stimuli.
Covington BC, Spraggins JM, Ynigez-Gutierrez AE, Hylton ZB, Bachmann BO
(2018) Appl Environ Microbiol 84:
MeSH Terms: Actinobacteria, Bacterial Proteins, Biological Products, Caves, Genome, Bacterial, Magnetic Resonance Spectroscopy, Metabolomics, Multigene Family, Phylogeny, Polyketides, Secondary Metabolism
Show Abstract · Added March 26, 2019
Microorganisms within microbial communities respond to environmental challenges by producing biologically active secondary metabolites, yet the majority of these small molecules remain unidentified. We have previously demonstrated that secondary metabolite biosynthesis in actinomycetes can be activated by model environmental chemical and biological stimuli, and metabolites can be identified by comparative metabolomics analyses under different stimulus conditions. Here, we surveyed the secondary metabolite productivity of a group of 20 phylogenetically diverse actinobacteria isolated from hypogean (cave) environments by applying a battery of stimuli consisting of exposure to antibiotics, metals, and mixed microbial culture. Comparative metabolomics was used to reveal secondary metabolite responses from stimuli. These analyses revealed substantial changes in global metabolomic dynamics, with over 30% of metabolomic features increasing more than 10-fold under at least one stimulus condition. Selected features were isolated and identified via nuclear magnetic resonance (NMR), revealing several known secondary metabolite families, including the tetarimycins, aloesaponarins, hypogeamicins, actinomycins, and propeptins. One prioritized metabolite was identified to be a previously unreported aminopolyol polyketide, funisamine, produced by a cave isolate of when exposed to mixed culture. The production of funisamine was most significantly increased in mixed culture with species. The biosynthetic gene cluster responsible for the production of funisamine was identified via genomic sequencing of the producing strain, sp. strain KDCAGE35, which facilitated a deduction of its biosynthesis. Together, these data demonstrate that comparative metabolomics can reveal the stimulus-induced production of natural products from diverse microbial phylogenies. Microbial secondary metabolites are an important source of biologically active and therapeutically relevant small molecules. However, much of this active molecular diversity is challenging to access due to low production levels or difficulty in discerning secondary metabolites within complex microbial extracts prior to isolation. Here, we demonstrate that ecological stimuli increase secondary metabolite production in phylogenetically diverse actinobacteria isolated from understudied hypogean environments. Additionally, we show that comparative metabolomics linking stimuli to metabolite response data can effectively reveal secondary metabolites within complex biological extracts. This approach highlighted secondary metabolites in almost all observed natural product classes, including low-abundance analogs of biologically relevant metabolites, as well as a new linear aminopolyol polyketide, funisamine. This study demonstrates the generality of activating stimuli to potentiate secondary metabolite production across diverse actinobacterial genera.
Copyright © 2018 American Society for Microbiology.
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11 MeSH Terms
Drivers of genetic diversity in secondary metabolic gene clusters within a fungal species.
Lind AL, Wisecaver JH, Lameiras C, Wiemann P, Palmer JM, Keller NP, Rodrigues F, Goldman GH, Rokas A
(2017) PLoS Biol 15: e2003583
MeSH Terms: Alleles, Aspergillus fumigatus, Biological Evolution, Fungal Proteins, Fungi, Genetic Variation, Genome, Fungal, Genomics, Metabolic Networks and Pathways, Multigene Family, Mutation, Polymorphism, Genetic, Secondary Metabolism
Show Abstract · Added March 21, 2018
Filamentous fungi produce a diverse array of secondary metabolites (SMs) critical for defense, virulence, and communication. The metabolic pathways that produce SMs are found in contiguous gene clusters in fungal genomes, an atypical arrangement for metabolic pathways in other eukaryotes. Comparative studies of filamentous fungal species have shown that SM gene clusters are often either highly divergent or uniquely present in one or a handful of species, hampering efforts to determine the genetic basis and evolutionary drivers of SM gene cluster divergence. Here, we examined SM variation in 66 cosmopolitan strains of a single species, the opportunistic human pathogen Aspergillus fumigatus. Investigation of genome-wide within-species variation revealed 5 general types of variation in SM gene clusters: nonfunctional gene polymorphisms; gene gain and loss polymorphisms; whole cluster gain and loss polymorphisms; allelic polymorphisms, in which different alleles corresponded to distinct, nonhomologous clusters; and location polymorphisms, in which a cluster was found to differ in its genomic location across strains. These polymorphisms affect the function of representative A. fumigatus SM gene clusters, such as those involved in the production of gliotoxin, fumigaclavine, and helvolic acid as well as the function of clusters with undefined products. In addition to enabling the identification of polymorphisms, the detection of which requires extensive genome-wide synteny conservation (e.g., mobile gene clusters and nonhomologous cluster alleles), our approach also implicated multiple underlying genetic drivers, including point mutations, recombination, and genomic deletion and insertion events as well as horizontal gene transfer from distant fungi. Finally, most of the variants that we uncover within A. fumigatus have been previously hypothesized to contribute to SM gene cluster diversity across entire fungal classes and phyla. We suggest that the drivers of genetic diversity operating within a fungal species shown here are sufficient to explain SM cluster macroevolutionary patterns.
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13 MeSH Terms
A Global Coexpression Network Approach for Connecting Genes to Specialized Metabolic Pathways in Plants.
Wisecaver JH, Borowsky AT, Tzin V, Jander G, Kliebenstein DJ, Rokas A
(2017) Plant Cell 29: 944-959
MeSH Terms: Computational Biology, Gene Expression Profiling, Gene Expression Regulation, Plant, Metabolic Networks and Pathways, Multigene Family
Show Abstract · Added March 21, 2018
Plants produce diverse specialized metabolites (SMs), but the genes responsible for their production and regulation remain largely unknown, hindering efforts to tap plant pharmacopeia. Given that genes comprising SM pathways exhibit environmentally dependent coregulation, we hypothesized that genes within a SM pathway would form tight associations (modules) with each other in coexpression networks, facilitating their identification. To evaluate this hypothesis, we used 10 global coexpression data sets, each a meta-analysis of hundreds to thousands of experiments, across eight plant species to identify hundreds of coexpressed gene modules per data set. In support of our hypothesis, 15.3 to 52.6% of modules contained two or more known SM biosynthetic genes, and module genes were enriched in SM functions. Moreover, modules recovered many experimentally validated SM pathways, including all six known to form biosynthetic gene clusters (BGCs). In contrast, bioinformatically predicted BGCs (i.e., those lacking an associated metabolite) were no more coexpressed than the null distribution for neighboring genes. These results suggest that most predicted plant BGCs are not genuine SM pathways and argue that BGCs are not a hallmark of plant specialized metabolism. We submit that global gene coexpression is a rich, largely untapped resource for discovering the genetic basis and architecture of plant natural products.
© 2017 American Society of Plant Biologists. All rights reserved.
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5 MeSH Terms
CTDGFinder: A Novel Homology-Based Algorithm for Identifying Closely Spaced Clusters of Tandemly Duplicated Genes.
Ortiz JF, Rokas A
(2017) Mol Biol Evol 34: 215-229
MeSH Terms: Algorithms, Animals, Evolution, Molecular, Genes, Duplicate, Genetic Linkage, Genome, Genomics, Humans, Multigene Family, Phylogeny, Sequence Analysis, DNA, Sequence Homology, Nucleic Acid, Software, Synteny, Tandem Repeat Sequences
Show Abstract · Added April 6, 2017
Closely spaced clusters of tandemly duplicated genes (CTDGs) contribute to the diversity of many phenotypes, including chemosensation, snake venom, and animal body plans. CTDGs have traditionally been identified subjectively as genomic neighborhoods containing several gene duplicates in close proximity; however, CTDGs are often highly variable with respect to gene number, intergenic distance, and synteny. This lack of formal definition hampers the study of CTDG evolutionary dynamics and the discovery of novel CTDGs in the exponentially growing body of genomic data. To address this gap, we developed a novel homology-based algorithm, CTDGFinder, which formalizes and automates the identification of CTDGs by examining the physical distribution of individual members of families of duplicated genes across chromosomes. Application of CTDGFinder accurately identified CTDGs for many well-known gene clusters (e.g., Hox and beta-globin gene clusters) in the human, mouse and 20 other mammalian genomes. Differences between previously annotated gene clusters and our inferred CTDGs were due to the exclusion of nonhomologs that have historically been considered parts of specific gene clusters, the inclusion or absence of genes between the CTDGs and their corresponding gene clusters, and the splitting of certain gene clusters into distinct CTDGs. Examination of human genes showing tissue-specific enhancement of their expression by CTDGFinder identified members of several well-known gene clusters (e.g., cytochrome P450s and olfactory receptors) and revealed that they were unequally distributed across tissues. By formalizing and automating CTDG identification, CTDGFinder will facilitate understanding of CTDG evolutionary dynamics, their functional implications, and how they are associated with phenotypic diversity.
© The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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15 MeSH Terms
Regulation of Secondary Metabolism by the Velvet Complex Is Temperature-Responsive in Aspergillus.
Lind AL, Smith TD, Saterlee T, Calvo AM, Rokas A
(2016) G3 (Bethesda) 6: 4023-4033
MeSH Terms: Aspergillus, Cluster Analysis, Fungal Proteins, Gene Expression Profiling, Gene Expression Regulation, Fungal, Multigene Family, Secondary Metabolism, Temperature
Show Abstract · Added April 6, 2017
Sensing and responding to environmental cues is critical to the lifestyle of filamentous fungi. How environmental variation influences fungi to produce a wide diversity of ecologically important secondary metabolites (SMs) is not well understood. To address this question, we first examined changes in global gene expression of the opportunistic human pathogen, Aspergillus fumigatus, after exposure to different temperature conditions. We found that 11 of the 37 SM gene clusters in A. fumigatus were expressed at higher levels at 30° than at 37°. We next investigated the role of the light-responsive Velvet complex in environment-dependent gene expression by examining temperature-dependent transcription profiles in the absence of two key members of the Velvet protein complex, VeA and LaeA We found that the 11 temperature-regulated SM gene clusters required VeA at 37° and LaeA at both 30 and 37° for wild-type levels of expression. Interestingly, four SM gene clusters were regulated by VeA at 37° but not at 30°, and two additional ones were regulated by VeA at both temperatures but were substantially less so at 30°, indicating that the role of VeA and, more generally of the Velvet complex, in the regulation of certain SM gene clusters is temperature-dependent. Our findings support the hypothesis that fungal secondary metabolism is regulated by an intertwined network of transcriptional regulators responsive to multiple environmental factors.
Copyright © 2016 Lind et al.
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8 MeSH Terms
High-Resolution Mapping of RNA Polymerases Identifies Mechanisms of Sensitivity and Resistance to BET Inhibitors in t(8;21) AML.
Zhao Y, Liu Q, Acharya P, Stengel KR, Sheng Q, Zhou X, Kwak H, Fischer MA, Bradner JE, Strickland SA, Mohan SR, Savona MR, Venters BJ, Zhou MM, Lis JT, Hiebert SW
(2016) Cell Rep 16: 2003-16
MeSH Terms: Antineoplastic Agents, Azepines, Cell Line, Tumor, Chromosomes, Human, Pair 21, Chromosomes, Human, Pair 8, Clustered Regularly Interspaced Short Palindromic Repeats, DNA-Directed RNA Polymerases, Drug Resistance, Neoplasm, Enhancer Elements, Genetic, Gene Expression Regulation, Leukemic, High-Throughput Nucleotide Sequencing, Humans, Leukemia, Myeloid, Acute, MicroRNAs, Multigene Family, Myeloid Cell Leukemia Sequence 1 Protein, Promoter Regions, Genetic, Protein Isoforms, Proteins, Proto-Oncogene Proteins c-kit, Transcription, Genetic, Translocation, Genetic, Triazoles
Show Abstract · Added April 6, 2017
Bromodomain and extra-terminal domain (BET) family inhibitors offer an approach to treating hematological malignancies. We used precision nuclear run-on transcription sequencing (PRO-seq) to create high-resolution maps of active RNA polymerases across the genome in t(8;21) acute myeloid leukemia (AML), as these polymerases are exceptionally sensitive to BET inhibitors. PRO-seq identified over 1,400 genes showing impaired release of promoter-proximal paused RNA polymerases, including the stem cell factor receptor tyrosine kinase KIT that is mutated in t(8;21) AML. PRO-seq also identified an enhancer 3' to KIT. Chromosome conformation capture confirmed contacts between this enhancer and the KIT promoter, while CRISPRi-mediated repression of this enhancer impaired cell growth. PRO-seq also identified microRNAs, including MIR29C and MIR29B2, that target the anti-apoptotic factor MCL1 and were repressed by BET inhibitors. MCL1 protein was upregulated, and inhibition of BET proteins sensitized t(8:21)-containing cells to MCL1 inhibition, suggesting a potential mechanism of resistance to BET-inhibitor-induced cell death.
Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
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23 MeSH Terms
Threshold-Dependent Cooperativity of Pdx1 and Oc1 in Pancreatic Progenitors Establishes Competency for Endocrine Differentiation and β-Cell Function.
Henley KD, Stanescu DE, Kropp PA, Wright CVE, Won KJ, Stoffers DA, Gannon M
(2016) Cell Rep 15: 2637-2650
MeSH Terms: Animals, Basic Helix-Loop-Helix Transcription Factors, Cell Count, Cell Differentiation, Embryo, Mammalian, Gene Dosage, Gene Expression Regulation, Developmental, Gene Ontology, Gene Regulatory Networks, Glucose, Hepatocyte Nuclear Factor 6, Heterozygote, Homeodomain Proteins, Homeostasis, Insulin-Secreting Cells, Mice, Multigene Family, Nerve Tissue Proteins, Stem Cells, Trans-Activators, Weaning
Show Abstract · Added July 5, 2016
Pdx1 and Oc1 are co-expressed in multipotent pancreatic progenitors and regulate the pro-endocrine gene Neurog3. Their expression diverges in later organogenesis, with Oc1 absent from hormone+ cells and Pdx1 maintained in mature β cells. In a classical genetic test for cooperative functional interactions, we derived mice with combined Pdx1 and Oc1 heterozygosity. Endocrine development in double-heterozygous pancreata was normal at embryonic day (E)13.5, but defects in specification and differentiation were apparent at E15.5, the height of the second wave of differentiation. Pancreata from double heterozygotes showed alterations in the expression of genes crucial for β-cell development and function, decreased numbers and altered allocation of Neurog3-expressing endocrine progenitors, and defective endocrine differentiation. Defects in islet gene expression and β-cell function persisted in double heterozygous neonates. These results suggest that Oc1 and Pdx1 cooperate prior to their divergence, in pancreatic progenitors, to allow for proper differentiation and functional maturation of β cells.
Published by Elsevier Inc.
1 Communities
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21 MeSH Terms
Pulmonary Arterial Hypertension: A Current Perspective on Established and Emerging Molecular Genetic Defects.
Machado RD, Southgate L, Eichstaedt CA, Aldred MA, Austin ED, Best DH, Chung WK, Benjamin N, Elliott CG, Eyries M, Fischer C, Gräf S, Hinderhofer K, Humbert M, Keiles SB, Loyd JE, Morrell NW, Newman JH, Soubrier F, Trembath RC, Viales RR, Grünig E
(2015) Hum Mutat 36: 1113-27
MeSH Terms: Animals, Bone Morphogenetic Protein Receptors, Type II, Disease Models, Animal, Genetic Association Studies, Genetic Counseling, Genetic Predisposition to Disease, Genetic Variation, High-Throughput Nucleotide Sequencing, Humans, Hypertension, Pulmonary, Multigene Family, Mutation, Signal Transduction, Transforming Growth Factor beta
Show Abstract · Added February 21, 2017
Pulmonary arterial hypertension (PAH) is an often fatal disorder resulting from several causes including heterogeneous genetic defects. While mutations in the bone morphogenetic protein receptor type II (BMPR2) gene are the single most common causal factor for hereditary cases, pathogenic mutations have been observed in approximately 25% of idiopathic PAH patients without a prior family history of disease. Additional defects of the transforming growth factor beta pathway have been implicated in disease pathogenesis. Specifically, studies have confirmed activin A receptor type II-like 1 (ACVRL1), endoglin (ENG), and members of the SMAD family as contributing to PAH both with and without associated clinical phenotypes. Most recently, next-generation sequencing has identified novel, rare genetic variation implicated in the PAH disease spectrum. Of importance, several identified genetic factors converge on related pathways and provide significant insight into the development, maintenance, and pathogenetic transformation of the pulmonary vascular bed. Together, these analyses represent the largest comprehensive compilation of BMPR2 and associated genetic risk factors for PAH, comprising known and novel variation. Additionally, with the inclusion of an allelic series of locus-specific variation in BMPR2, these data provide a key resource in data interpretation and development of contemporary therapeutic and diagnostic tools.
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14 MeSH Terms
Oxidative cyclizations in orthosomycin biosynthesis expand the known chemistry of an oxygenase superfamily.
McCulloch KM, McCranie EK, Smith JA, Sarwar M, Mathieu JL, Gitschlag BL, Du Y, Bachmann BO, Iverson TM
(2015) Proc Natl Acad Sci U S A 112: 11547-52
MeSH Terms: Aminoglycosides, Anti-Bacterial Agents, Catalytic Domain, Crystallography, X-Ray, Cyclization, Hydrogen, Hygromycin B, Metals, Micromonospora, Multigene Family, Oligosaccharides, Open Reading Frames, Oxidation-Reduction, Oxygen, Oxygenases, Phylogeny, Protein Binding, Protein Structure, Secondary, Reproducibility of Results, Streptomyces
Show Abstract · Added April 1, 2019
Orthosomycins are oligosaccharide antibiotics that include avilamycin, everninomicin, and hygromycin B and are hallmarked by a rigidifying interglycosidic spirocyclic ortho-δ-lactone (orthoester) linkage between at least one pair of carbohydrates. A subset of orthosomycins additionally contain a carbohydrate capped by a methylenedioxy bridge. The orthoester linkage is necessary for antibiotic activity but rarely observed in natural products. Orthoester linkage and methylenedioxy bridge biosynthesis require similar oxidative cyclizations adjacent to a sugar ring. We have identified a conserved group of nonheme iron, α-ketoglutarate-dependent oxygenases likely responsible for this chemistry. High-resolution crystal structures of the EvdO1 and EvdO2 oxygenases of everninomicin biosynthesis, the AviO1 oxygenase of avilamycin biosynthesis, and HygX of hygromycin B biosynthesis show how these enzymes accommodate large substrates, a challenge that requires a variation in metal coordination in HygX. Excitingly, the ternary complex of HygX with cosubstrate α-ketoglutarate and putative product hygromycin B identified an orientation of one glycosidic linkage of hygromycin B consistent with metal-catalyzed hydrogen atom abstraction from substrate. These structural results are complemented by gene disruption of the oxygenases evdO1 and evdMO1 from the everninomicin biosynthetic cluster, which demonstrate that functional oxygenase activity is critical for antibiotic production. Our data therefore support a role for these enzymes in the production of key features of the orthosomycin antibiotics.
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MeSH Terms
Introduction: Metals in Biology: α-Ketoglutarate/Iron-Dependent Dioxygenases.
Guengerich FP
(2015) J Biol Chem 290: 20700-1
MeSH Terms: 5-Methylcytosine, AlkB Homolog 4, Lysine Demethylase, DNA, DNA Damage, DNA Repair, Dioxygenases, Epigenesis, Genetic, Gene Expression, Humans, Iron, Isoenzymes, Ketoglutaric Acids, Multigene Family, Oxidation-Reduction, Protein Processing, Post-Translational, Thymine
Show Abstract · Added March 14, 2018
Four minireviews deal with aspects of the α-ketoglutarate/iron-dependent dioxygenases in this eighth Thematic Series on Metals in Biology. The minireviews cover a general introduction and synopsis of the current understanding of mechanisms of catalysis, the roles of these dioxygenases in post-translational protein modification and de-modification, the roles of the ten-eleven translocation (Tet) dioxygenases in the modification of methylated bases (5mC, T) in DNA relevant to epigenetic mechanisms, and the roles of the AlkB-related dioxygenases in the repair of damaged DNA and RNA. The use of α-ketoglutarate (alternatively termed 2-oxoglutarate) as a co-substrate in so many oxidation reactions throughout much of nature is notable and has surprisingly emerged from biochemical and genomic analysis. About 60 of these enzymes are now recognized in humans, and a number have been identified as having critical functions.
© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
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16 MeSH Terms