scholarly journals Unintentional Genomic Changes Endow Cupriavidus metallidurans with an Augmented Heavy-Metal Resistance

Genes ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 551 ◽  
Author(s):  
Felipe Millacura ◽  
Paul Janssen ◽  
Pieter Monsieurs ◽  
Ann Janssen ◽  
Ann Provoost ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sequence Data ◽  
Gene Clusters ◽  
Metal Resistance ◽  
Model Organisms ◽  
Mercury Resistance ◽  
Genome Comparison ◽  
Nucleotide Polymorphisms ◽  
Entire Genome ◽  
Cupriavidus Metallidurans

For the past three decades, Cupriavidus metallidurans has been one of the major model organisms for bacterial tolerance to heavy metals. Its type strain CH34 contains at least 24 gene clusters distributed over four replicons, allowing for intricate and multilayered metal responses. To gain organic mercury resistance in CH34, broad-spectrum mer genes were introduced in a previous work via conjugation of the IncP-1β plasmid pTP6. However, we recently noted that this CH34-derived strain, MSR33, unexpectedly showed an increased resistance to other metals (i.e., Co2+, Ni2+, and Cd2+). To thoroughly investigate this phenomenon, we resequenced the entire genome of MSR33 and compared its DNA sequence and basal gene expression profile to those of its parental strain CH34. Genome comparison identified 11 insertions or deletions (INDELs) and nine single nucleotide polymorphisms (SNPs), whereas transcriptomic analysis displayed 107 differentially expressed genes. Sequence data implicated the transposition of IS1088 in higher Co2+ and Ni2+ resistances and altered gene expression, although the precise mechanisms of the augmented Cd2+ resistance in MSR33 remains elusive. Our work indicates that conjugation procedures involving large complex genomes and extensive mobilomes may pose a considerable risk toward the introduction of unwanted, undocumented genetic changes. Special efforts are needed for the applied use and further development of small nonconjugative broad-host plasmid vectors, ideally involving CRISPR-related and advanced biosynthetic technologies.

scholarly journals Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

2019 ◽  
Author(s):  
E. Ng’oma ◽  
P.A. Williams-Simon ◽  
A. Rahman ◽  
E.G. King
Keyword(s):  
Gene Expression ◽  
Gene Networks ◽  
Sequence Data ◽  
Nutrient Sensing ◽  
Gene Set Enrichment Analysis ◽  
Tissue Type ◽  
Model Organisms ◽  
Laboratory Model ◽  
Fisher Exact Test ◽  
Tissue Samples

AbstractBackgroundEnvironmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear.ResultsTo describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2,471 genes) were significantly differentially expressed for the effect of diet, 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, Padj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (false discovery rate, FDR Padj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing a large number of cellular and nuclear processes (Fisher exact test, Padj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5, Rheb, and Sirt2 showed significant elevation in expression, known key genes such as InR, chico, insulin peptide genes, and the nutrient-sensing pathways were not observed.ConclusionsOur results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

scholarly journals Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

2019 ◽  
Author(s):  
Enoch Ng'oma ◽  
Patricka A. Williams-Simon ◽  
Aniqa Rahman ◽  
Elizabeth G. King
Keyword(s):  
Gene Expression ◽  
Gene Networks ◽  
Sequence Data ◽  
Nutrient Sensing ◽  
Gene Set Enrichment Analysis ◽  
Tissue Type ◽  
Model Organisms ◽  
Laboratory Model ◽  
Fisher Exact Test ◽  
Tissue Samples

Abstract Background: Environmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear. Results: To describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2,471 genes) were significantly differentially expressed for the effect of diet, 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, P adj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (false discovery rate, FDR P adj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing a large number of cellular and nuclear processes (Fisher exact test, P adj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5 , Rheb , and Sirt2 showed significant elevation in expression, known key genes such as InR , chico , insulin peptide genes, and the nutrient-sensing pathways were not observed. Conclusions: Our results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

scholarly journals An Integrated Pipeline of Open Source Software Adapted for Multi-CPU Architectures: Use in the Large-Scale Identification of Single Nucleotide Polymorphisms

2007 ◽  
Vol 2007 ◽  
pp. 1-7 ◽  
Author(s):  
B. Jayashree ◽  
Manindra S. Hanspal ◽  
Rajgopal Srinivasan ◽  
R. Vigneshwaran ◽  
Rajeev K. Varshney ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Sequence Data ◽  
Snp Genotyping ◽  
Model Organisms ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Web Interfaces

The large amounts of EST sequence data available from a single species of an organism as well as for several species within a genus provide an easy source of identification of intra- and interspecies single nucleotide polymorphisms (SNPs). In the case of model organisms, the data available are numerous, given the degree of redundancy in the deposited EST data. There are several available bioinformatics tools that can be used to mine this data; however, using them requires a certain level of expertise: the tools have to be used sequentially with accompanying format conversion and steps like clustering and assembly of sequences become time-intensive jobs even for moderately sized datasets. We report here a pipeline of open source software extended to run on multiple CPU architectures that can be used to mine large EST datasets for SNPs and identify restriction sites for assaying the SNPs so that cost-effective CAPS assays can be developed for SNP genotyping in genetics and breeding applications. At the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), the pipeline has been implemented to run on a Paracel high-performance system consisting of four dual AMD Opteron processors running Linux with MPICH. The pipeline can be accessed through user-friendly web interfaces at http://hpc.icrisat.cgiar.org/PBSWeb and is available on request for academic use. We have validated the developed pipeline by mining chickpea ESTs for interspecies SNPs, development of CAPS assays for SNP genotyping, and confirmation of restriction digestion pattern at the sequence level.

scholarly journals Cell Biology of the Trypanosome Genome

2010 ◽  
Vol 74 (4) ◽  
pp. 552-569 ◽  
Author(s):  
Jan-Peter Daniels ◽  
Keith Gull ◽  
Bill Wickstead
Keyword(s):  
Gene Expression ◽  
Cell Biology ◽  
Nuclear Organization ◽  
Nuclear Architecture ◽  
Gene Clusters ◽  
Model Organisms ◽  
Protein Coding ◽  
African Trypanosomes ◽  
Protein Coding Genes ◽  
A Genome

SUMMARY Trypanosomes are a group of protozoan eukaryotes, many of which are major parasites of humans and livestock. The genomes of trypanosomes and their modes of gene expression differ in several important aspects from those of other eukaryotic model organisms. Protein-coding genes are organized in large directional gene clusters on a genome-wide scale, and their polycistronic transcription is not generally regulated at initiation. Transcripts from these polycistrons are processed by global trans-splicing of pre-mRNA. Furthermore, in African trypanosomes, some protein-coding genes are transcribed by a multifunctional RNA polymerase I from a specialized extranucleolar compartment. The primary DNA sequence of the trypanosome genomes and their cellular organization have usually been treated as separate entities. However, it is becoming increasingly clear that in order to understand how a genome functions in a living cell, we will need to unravel how the one-dimensional genomic sequence and its trans-acting factors are arranged in the three-dimensional space of the eukaryotic nucleus. Understanding this cell biology of the genome will be crucial if we are to elucidate the genetic control mechanisms of parasitism. Here, we integrate the concepts of nuclear architecture, deduced largely from studies of yeast and mammalian nuclei, with recent developments in our knowledge of the trypanosome genome, gene expression, and nuclear organization. We also compare this nuclear organization to those in other systems in order to shed light on the evolution of nuclear architecture in eukaryotes.

scholarly journals The Transcriptomic Landscape of Cupriavidus metallidurans CH34 Acutely Exposed to Copper

Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1049
Author(s):  
Laurens Maertens ◽  
Natalie Leys ◽  
Jean-Yves Matroule ◽  
Rob Van Houdt
Keyword(s):  
Sulfur Metabolism ◽  
Model Organism ◽  
Gene Clusters ◽  
Resistance Mechanisms ◽  
Metal Resistance ◽  
Copper Resistance ◽  
Messenger Rnas ◽  
Antisense Transcripts ◽  
Cupriavidus Metallidurans Ch34 ◽  
Cupriavidus Metallidurans

Bacteria are increasingly used for biotechnological applications such as bioremediation, biorecovery, bioproduction, and biosensing. The development of strains suited for such applications requires a thorough understanding of their behavior, with a key role for their transcriptomic landscape. We present a thorough analysis of the transcriptome of Cupriavidus metallidurans CH34 cells acutely exposed to copper by tagRNA-sequencing. C. metallidurans CH34 is a model organism for metal resistance, and its potential as a biosensor and candidate for metal bioremediation has been demonstrated in multiple studies. Several metabolic pathways were impacted by Cu exposure, and a broad spectrum of metal resistance mechanisms, not limited to copper-specific clusters, was overexpressed. In addition, several gene clusters involved in the oxidative stress response and the cysteine-sulfur metabolism were induced. In total, 7500 transcription start sites (TSSs) were annotated and classified with respect to their location relative to coding sequences (CDSs). Predicted TSSs were used to re-annotate 182 CDSs. The TSSs of 2422 CDSs were detected, and consensus promotor logos were derived. Interestingly, many leaderless messenger RNAs (mRNAs) were found. In addition, many mRNAs were transcribed from multiple alternative TSSs. We observed pervasive intragenic TSSs both in sense and antisense to CDSs. Antisense transcripts were enriched near the 5′ end of mRNAs, indicating a functional role in post-transcriptional regulation. In total, 578 TSSs were detected in intergenic regions, of which 35 were identified as putative small regulatory RNAs. Finally, we provide a detailed analysis of the main copper resistance clusters in CH34, which include many intragenic and antisense transcripts. These results clearly highlight the ubiquity of noncoding transcripts in the CH34 transcriptome, many of which are putatively involved in the regulation of metal resistance.

scholarly journals Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data

2017 ◽  
Author(s):  
Basel Abu-Jamous ◽  
Steven Kelly
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Large Scale ◽  
Enrichment Analysis ◽  
Gene Clusters ◽  
Error Rates ◽  
Model Organisms ◽  
Expression Data ◽  
Clustering Methods ◽  
Automated Method

AbstractIdentification of co-expressed gene clusters can provide evidence for genetic or physical interactions between genes. Thus, co-expression clustering is a routine step in large-scale analyses of gene expression data. We show that commonly used clustering methods produce results that substantially disagree with each other, and do not match the biological expectations of co-expressed gene clusters. Furthermore, these clusters can contain up to 50% unreliably assigned genes. Consequently, downstream analyses of these clusters (e.g. functional term enrichment analysis) suffer from high error rates. We present clust, an automated method that solves these problems by extracting clusters that match the biological expectations of co-expressed genes. Using 100 datasets from five model organisms we demonstrate that clusters generated by clust are better than those produced by other methods, both numerically and for use in functional analysis. Finally, we show that clust can simultaneously cluster multiple datasets, enabling users to leverage the large quantity of public expression data for novel comparative analysis.

scholarly journals Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

2019 ◽  
Author(s):  
Enoch Ng'oma ◽  
Patricka A. Williams-Simon ◽  
Aniqa Rahman ◽  
Elizabeth G. King
Keyword(s):  
Gene Expression ◽  
Gene Networks ◽  
Sequence Data ◽  
Nutrient Sensing ◽  
Gene Set Enrichment Analysis ◽  
Tissue Type ◽  
Model Organisms ◽  
Laboratory Model ◽  
Fisher Exact Test ◽  
Tissue Samples

Abstract Background Environmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear. Results To describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2,471 genes) were significantly differentially expressed for the effect of diet, 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, Padj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (false discovery rate, FDR Padj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing a large number of cellular and nuclear processes (Fisher exact test, Padj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5, Rheb, and Sirt2 showed significant elevation in expression, known key genes such as InR, chico, insulin peptide genes, and the nutrient-sensing pathways were not observed. Conclusions Our results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

scholarly journals Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

2019 ◽  
Author(s):  
Enoch Ng'oma ◽  
Patricka A. Williams-Simon ◽  
Aniqa Rahman ◽  
Elizabeth G. King
Keyword(s):  
Gene Expression ◽  
Gene Networks ◽  
Sequence Data ◽  
Nutrient Sensing ◽  
Gene Set Enrichment Analysis ◽  
Tissue Type ◽  
Model Organisms ◽  
Laboratory Model ◽  
Fisher Exact Test ◽  
Tissue Samples

Abstract Background: Environmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear. Results: To describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2,471 genes) were significantly differentially expressed for the effect of diet, 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, Padj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (false discovery rate, FDR Padj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing a large number of cellular and nuclear processes (Fisher exact test, Padj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5, Rheb, and Sirt2 showed significant elevation in expression, known key genes such as InR, chico, insulin peptide genes, and the nutrient-sensing pathways were not observed. Conclusions: Our results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

scholarly journals Rearrangement analysis of multiple bacterial genomes

2019 ◽  
Vol 20 (S23) ◽  
Author(s):  
Mehwish Noureen ◽  
Ipputa Tada ◽  
Takeshi Kawashima ◽  
Masanori Arita
Keyword(s):  
Helicobacter Pylori ◽  
Gene Order ◽  
Time Course ◽  
Sequence Data ◽  
Point Mutations ◽  
Evolutionary Relationship ◽  
Orthologous Gene ◽  
Gene Clusters ◽  
Genome Rearrangements ◽  
Genome Comparison

Abstract Background Genomes are subjected to rearrangements that change the orientation and ordering of genes during evolution. The most common rearrangements that occur in uni-chromosomal genomes are inversions (or reversals) to adapt to the changing environment. Since genome rearrangements are rarer than point mutations, gene order with sequence data can facilitate more robust phylogenetic reconstruction. Helicobacter pylori is a good model because of its unique evolution in niche environment. Results We have developed a method to identify genome rearrangements by comparing almost-conserved genes among closely related strains. Orthologous gene clusters, rather than the gene sequences, are used to align the gene order so that comparison of large number of genomes becomes easier. Comparison of 72 Helicobacter pylori strains revealed shared as well as strain-specific reversals, some of which were found in different geographical locations. Conclusion Degree of genome rearrangements increases with time. Therefore, gene orders can be used to study the evolutionary relationship among species and strains. Multiple genome comparison helps to identify the strain-specific as well as shared reversals. Identification of the time course of rearrangements can provide insights into evolutionary events.

scholarly journals Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

2020 ◽  
Author(s):  
Enoch Ng'oma ◽  
Patricka A. Williams-Simon ◽  
Aniqa Rahman ◽  
Elizabeth G. King
Keyword(s):  
Gene Expression ◽  
Gene Networks ◽  
Sequence Data ◽  
Nutrient Sensing ◽  
Gene Set Enrichment Analysis ◽  
Tissue Type ◽  
Model Organisms ◽  
Laboratory Model ◽  
Fisher Exact Test ◽  
Tissue Samples

Abstract Background: Environmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear. Results: To describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2,471 genes) were significantly differentially expressed for the effect of diet, and 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, P adj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (FDR P adj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing many cellular and nuclear processes (Fisher exact test, P adj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5 , Rheb , and Sirt2 showed significant elevation in expression, many key genes such as InR , chico , most insulin peptide genes, and the nutrient-sensing pathways were not observed. Conclusions: Our results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

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