scholarly journals MutRank: an R shiny web-application for exploratory targeted mutual rank-based coexpression analyses integrated with user-provided supporting information

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10264
Author(s):  
Elly Poretsky ◽  
Alisa Huffaker
Keyword(s):  
Hypothesis Testing ◽  
Predictive Value ◽  
Web Application ◽  
Biosynthetic Pathway ◽  
Gene Clusters ◽  
Transcript Abundance ◽  
Specialized Metabolites ◽  
Genes Encoding ◽  
R Shiny ◽  
Mutual Rank

The rapid assignment of genotypes to phenotypes has been a historically challenging process. The discovery of genes encoding biosynthetic pathway enzymes for defined plant specialized metabolites has been informed and accelerated by the detection of gene clusters. Unfortunately, biosynthetic pathway genes are commonly dispersed across chromosomes or reside in genes clusters that provide little predictive value. More reliably, transcript abundance of genes underlying biochemical pathways for plant specialized metabolites display significant coregulation. By rapidly identifying highly coexpressed transcripts, it is possible to efficiently narrow candidate genes encoding pathway enzymes and more easily predict both functions and functional associations. Mutual Rank (MR)-based coexpression analyses in plants accurately demonstrate functional associations for many specialized metabolic pathways; however, despite the clear predictive value of MR analyses, the application is uncommonly used to drive new pathway discoveries. Moreover, many coexpression databases aid in the prediction of both functional associations and gene functions, but lack customizability for refined hypothesis testing. To facilitate and speed flexible MR-based hypothesis testing, we developed MutRank, an R Shiny web-application for coexpression analyses. MutRank provides an intuitive graphical user interface with multiple customizable features that integrates user-provided data and supporting information suitable for personal computers. Tabular and graphical outputs facilitate the rapid analyses of both unbiased and user-defined coexpression results that accelerate gene function predictions. We highlight the recent utility of MR analyses for functional predictions and discoveries in defining two maize terpenoid antibiotic pathways. Beyond applications in biosynthetic pathway discovery, MutRank provides a simple, customizable and user-friendly interface to enable coexpression analyses relating to a breadth of plant biology inquiries. Data and code are available at GitHub: https://github.com/eporetsky/MutRank.

scholarly journals Genome analysis suggests the bacterial family Acetobacteraceae is a source of undiscovered specialized metabolites

2021 ◽  
Author(s):  
Juan Guzman ◽  
Andreas Vilcinskas
Keyword(s):  
Hot Springs ◽  
In Silico Analysis ◽  
Gene Clusters ◽  
Acetic Acid Bacteria ◽  
Specialized Metabolites ◽  
The Family ◽  
Genes Encoding ◽  
Peptide Biosynthesis ◽  
Taxonomic Groups ◽  
Type 3

AbstractAcetobacteraceae is an economically important family of bacteria that is used for industrial fermentation in the food/feed sector and for the preparation of sorbose and bacterial cellulose. It comprises two major groups: acetous species (acetic acid bacteria) associated with flowers, fruits and insects, and acidophilic species, a phylogenetically basal and physiologically heterogeneous group inhabiting acid or hot springs, sludge, sewage and freshwater environments. Despite the biotechnological importance of the family Acetobacteraceae, the literature does not provide any information about its ability to produce specialized metabolites. We therefore constructed a phylogenomic tree based on concatenated protein sequences from 141 type strains of the family and predicted the presence of small-molecule biosynthetic gene clusters (BGCs) using the antiSMASH tool. This dual approach allowed us to associate certain biosynthetic pathways with particular taxonomic groups. We found that acidophilic and acetous species contain on average ~ 6.3 and ~ 3.4 BGCs per genome, respectively. All the Acetobacteraceae strains encoded proteins involved in hopanoid biosynthesis, with many also featuring genes encoding type-1 and type-3 polyketide and non-ribosomal peptide synthases, and enzymes for aryl polyene, lactone and ribosomal peptide biosynthesis. Our in silico analysis indicated that the family Acetobacteraceae is a potential source of many undiscovered bacterial metabolites and deserves more detailed experimental exploration.

scholarly journals Genome Analysis Suggests The Bacterial Family Acetobacteraceae is a Source of Undiscovered Specialized Metabolites

2021 ◽  
Author(s):  
Juan David Guzman ◽  
Andreas Vilcinskas
Keyword(s):  
Hot Springs ◽  
Gene Clusters ◽  
Acetic Acid Bacteria ◽  
Specialized Metabolites ◽  
The Family ◽  
Genes Encoding ◽  
Peptide Biosynthesis ◽  
Taxonomic Groups ◽  
Type 3

Abstract Acetobacteraceae is an economically important family of bacteria that is used for industrial fermentation in the food/feed sector and for the preparation of sorbose and bacterial cellulose. It comprises two major groups: acetous species (acetic acid bacteria) associated with flowers, fruits and insects, and acidophilic species, a phylogenetically basal and physiologically heterogeneous group inhabiting acid or hot springs, sludge, sewage and freshwater environments. Despite the biotechnological importance of the family Acetobacteraceae, the literature does not provide any information about its ability to produce specialized metabolites. We therefore constructed a phylogenomic tree based on concatenated protein sequences from 127 type strains of the family and predicted the presence of small-molecule biosynthetic gene clusters (BGCs) using the antiSMASH tool. This dual approach allowed us to associate certain biosynthetic pathways with particular taxonomic groups. We found that acidophilic and acetous species contain on average ~6 and ~3.4 BGCs per genome, respectively. All the Acetobacteraceae strains encoded proteins associated involved in hopanoid biosynthesis, with many also featuring genes encoding type-1 and type-3 polyketide and non-ribosomal peptide synthases, and enzymes for aryl polyene, lactone and ribosomal peptide biosynthesis. Our in silico analysis indicated that the family Acetobacteraceae is a potential source of many undiscovered bacterial metabolites and deserves more detailed experimental exploration.

scholarly journals Bagremycin Antibiotics and Ferroverdin iron-chelators are synthetized by the Same Gene Cluster

2019 ◽  
Author(s):  
Loïc Martinet ◽  
Aymeric Naômé ◽  
Benoit Deflandre ◽  
Marta Maciejewska ◽  
Déborah Tellatin ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Biosynthetic Pathway ◽  
Gene Clusters ◽  
Iron Chelators ◽  
Hydroxybenzoic Acid ◽  
Iron Availability ◽  
Biosynthetic Gene ◽  
Single Family ◽  
Biosynthetic Gene Clusters ◽  
Specialized Metabolites

AbstractBiosynthetic gene clusters (BGCs) are organized groups of genes involved in the production of specialized metabolites. Typically, one BGC is responsible for the production of one or several similar compounds with bioactivities that usually only vary in terms of strength and/or specificity. Here we show that the previously described ferroverdins and bagremycins, which are families of metabolites with different bioactivities, are produced from the same BGC, whereby the fate of the biosynthetic pathway depends on iron availability. Under conditions of iron depletion, the monomeric bagremycins are formed, which are amino-aromatic antibiotics resulting from the condensation of 3-amino-4-hydroxybenzoic acid with p-vinylphenol. Conversely, when iron is abundantly available, the biosynthetic pathway additionally produces a molecule based on p-vinylphenyl-3-nitroso-4-hydroxybenzoate, which complexes iron to form the trimeric ferroverdins that have anticholesterol activity. Thus our work challenges the concept that BGCs should produce a single family of molecules with one type of bioactivity, the occurrence of the different metabolites being triggered by the environmental conditions.

scholarly journals Visualizing the Costs and Benefits of Correcting P-Values for Multiple Hypothesis Testing in Omics Data

2021 ◽  
Author(s):  
Steven R. Shuken ◽  
Margaret W. McNerney
Keyword(s):  
Hypothesis Testing ◽  
Web Application ◽  
Multiple Testing ◽  
Test Group ◽  
Multiple Hypothesis Testing ◽  
P Value ◽  
Critical Element ◽  
Costs And Benefits ◽  
Multiple Hypothesis ◽  
R Shiny

AbstractThe multiple hypothesis testing problem is inherent in high-throughput quantitative genomic, transcriptomic, proteomic, and other “omic” screens. The correction of p-values for multiple testing is a critical element of quantitative omic data analysis, yet many researchers are unfamiliar with the sensitivity costs and false discovery rate (FDR) benefits of p-value correction. We developed models of quantitative omic experiments, modeled the costs and benefits of p-value correction, and visualized the results with color-coded volcano plots. We developed an R Shiny web application for further exploration of these models which we call the Simulator of P-value Multiple Hypothesis Correction (SIMPLYCORRECT). We modeled experiments in which no analytes were truly differential between the control and test group (all null hypotheses true), all analytes were differential, or a mixture of differential and non-differential analytes were present. We corrected p-values using the Benjamini-Hochberg (BH), Bonferroni, and permutation FDR methods and compared the costs and benefits of each. By manipulating variables in the models, we demonstrated that increasing sample size or decreasing variability can reduce or eliminate the sensitivity cost of p-value correction and that permutation FDR correction can yield more hits than BH-adjusted and even unadjusted p-values in strongly differential data. SIMPLYCORRECT can serve as a tool in education and research to show how p-value adjustment and various parameters affect the results of quantitative omics experiments.

scholarly journals Evidence of the Involvement of a Cyclase Gene in the Biosynthesis of Ochratoxin A in Aspergillus carbonarius

Toxins ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 892
Author(s):  
Massimo Ferrara ◽  
Antonia Gallo ◽  
Carla Cervini ◽  
Lucia Gambacorta ◽  
Michele Solfrizzo ◽  
...  
Keyword(s):  
Ochratoxin A ◽  
Biosynthetic Pathway ◽  
Gene Clusters ◽  
Wide Distribution ◽  
Ring Closure ◽  
Fungal Genome ◽  
Great Utility ◽  
Genes Encoding ◽  
Food And Feed ◽  
First Time

Ochratoxin A (OTA) is a well-known mycotoxin with wide distribution in food and feed. Fungal genome sequencing has great utility for identifying secondary metabolites gene clusters for known and novel compounds. A comparative analysis of the OTA-biosynthetic cluster in A. steynii, A. westerdijkiae, A. niger, A. carbonarius, and P. nordicum has revealed a high synteny in OTA cluster organization in five structural genes (otaA, otaB, ota, otaR1, and otaD). Moreover, a recent detailed comparative genome analysis of Aspergilli OTA producers led to the identification of a cyclase gene, otaY, located in the OTA cluster between the otaA and otaB genes, encoding for a predicted protein with high similarity to SnoaLs domain. These proteins have been shown to catalyze ring closure steps in the biosynthesis of polyketide antibiotics produced in Streptomyces. In the present study, we demonstrated an upregulation of the cyclase gene in A. carbonarius under OTA permissive conditions, consistent with the expression trends of the other OTA cluster genes and their role in OTA biosynthesis by complete gene deletion. Our results pointed out the involvement of a cyclase gene in OTA biosynthetic pathway for the first time. They represent a step forward in the understanding of the molecular basis of OTA biosynthesis in A. carbonarius.

scholarly journals Specialized Metabolites from Ribosome Engineered Strains of Streptomyces clavuligerus

Metabolites ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 239
Author(s):  
Arshad Ali Shaikh ◽  
Louis-Felix Nothias ◽  
Santosh K. Srivastava ◽  
Pieter C. Dorrestein ◽  
Kapil Tahlan
Keyword(s):  
In Silico Analysis ◽  
Cost Effective ◽  
Gene Clusters ◽  
Streptomyces Clavuligerus ◽  
Strain Engineering ◽  
Ribosome Recycling Factor ◽  
Metabolic Potential ◽  
Putative Gene ◽  
Specialized Metabolites ◽  
Streptomyces Spp

Bacterial specialized metabolites are of immense importance because of their medicinal, industrial, and agricultural applications. Streptomyces clavuligerus is a known producer of such compounds; however, much of its metabolic potential remains unknown, as many associated biosynthetic gene clusters are silent or expressed at low levels. The overexpression of ribosome recycling factor (frr) and ribosome engineering (induced rpsL mutations) in other Streptomyces spp. has been reported to increase the production of known specialized metabolites. Therefore, we used an overexpression strategy in combination with untargeted metabolomics, molecular networking, and in silico analysis to annotate 28 metabolites in the current study, which have not been reported previously in S. clavuligerus. Many of the newly described metabolites are commonly found in plants, further alluding to the ability of S. clavuligerus to produce such compounds under specific conditions. In addition, the manipulation of frr and rpsL led to different metabolite production profiles in most cases. Known and putative gene clusters associated with the production of the observed compounds are also discussed. This work suggests that the combination of traditional strain engineering and recently developed metabolomics technologies together can provide rapid and cost-effective strategies to further speed up the discovery of novel natural products.

scholarly journals Genome Reduction and Secondary Metabolism of the Marine Sponge-Associated Cyanobacterium Leptothoe

Marine Drugs ◽  
2021 ◽  
Vol 19 (6) ◽  
pp. 298
Author(s):  
Despoina Konstantinou ◽  
Rafael V. Popin ◽  
David P. Fewer ◽  
Kaarina Sivonen ◽  
Spyros Gkelis
Keyword(s):  
Natural Products ◽  
Microbial Communities ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Marine Sponges ◽  
Genome Reduction ◽  
Extracellular Polysaccharides ◽  
Comparative Genomic ◽  
Symbiotic Relationships ◽  
Genes Encoding

Sponges form symbiotic relationships with diverse and abundant microbial communities. Cyanobacteria are among the most important members of the microbial communities that are associated with sponges. Here, we performed a genus-wide comparative genomic analysis of the newly described marine benthic cyanobacterial genus Leptothoe (Synechococcales). We obtained draft genomes from Le. kymatousa TAU-MAC 1615 and Le. spongobia TAU-MAC 1115, isolated from marine sponges. We identified five additional Leptothoe genomes, host-associated or free-living, using a phylogenomic approach, and the comparison of all genomes showed that the sponge-associated strains display features of a symbiotic lifestyle. Le. kymatousa and Le. spongobia have undergone genome reduction; they harbored considerably fewer genes encoding for (i) cofactors, vitamins, prosthetic groups, pigments, proteins, and amino acid biosynthesis; (ii) DNA repair; (iii) antioxidant enzymes; and (iv) biosynthesis of capsular and extracellular polysaccharides. They have also lost several genes related to chemotaxis and motility. Eukaryotic-like proteins, such as ankyrin repeats, playing important roles in sponge-symbiont interactions, were identified in sponge-associated Leptothoe genomes. The sponge-associated Leptothoe stains harbored biosynthetic gene clusters encoding novel natural products despite genome reduction. Comparisons of the biosynthetic capacities of Leptothoe with chemically rich cyanobacteria revealed that Leptothoe is another promising marine cyanobacterium for the biosynthesis of novel natural products.

Antidiabetic agent pioglitazone enhances adipocyte differentiation of 3T3-F442A cells

1993 ◽  
Vol 264 (6) ◽  
pp. C1600-C1608 ◽  
Author(s):  
T. Sandouk ◽  
D. Reda ◽  
C. Hofmann
Keyword(s):  
Cell Differentiation ◽  
Energy Homeostasis ◽  
Combined Treatment ◽  
Transcript Abundance ◽  
Dependent Manner ◽  
Antidiabetic Agent ◽  
Triglyceride Accumulation ◽  
Genes Encoding ◽  
Lower Plasma Glucose ◽  
Triglyceride Content

Adipocytes play an important role in normal physiology as a major site for systemic energy homeostasis. In disorders such as diabetes, adipocyte function is markedly altered. In this study, we investigated the effect of pioglitazone, a novel antidiabetic agent known to lower plasma glucose in animal models of diabetes mellitus, on cellular differentiation and expression of adipose-specific genes. Treatment of confluent 3T3-F442A preadipocyte cultures for 7 days with pioglitazone (Pio; 1 microM) and insulin (Ins; 0.17 microM) resulted in > 95% cell differentiation into lipid-accumulating adipocytes in comparison with 60-80% cell differentiation by treatment with either agent alone. Analysis of triglyceride accumulation showed increases of triglyceride content over time above untreated preadipocytes by treatment of the cells with Ins, Pio, and especially with Ins + Pio. Basal glucose transport, as measured by cellular uptake of 2-deoxy-D-[14C]glucose, was likewise enhanced in a time-dependent manner by treatment of preadipocytes with Ins, Pio, or Ins + Pio, such that a synergistic effect resulted from the combined treatment with both agents. It was further determined that RNA transcript abundance for genes encoding glucose transporters GLUT-1 and GLUT-4, as well as the adipose-specific genes encoding adipsin and aP2, were increased by the Ins, Pio, or Ins + Pio treatment. Taken together, these findings indicate that pioglitazone is a potent adipogenic agent. By promoting differentiation, this agent may move cells into a state active for glucose uptake, storage, and metabolism.

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