scholarly journals Extensive Reannotation of the Genome of the Model Streptomycete Streptomyces lividans TK24 Based on Transcriptome and Proteome Information

2021 ◽  
Vol 12 ◽  
Author(s):  
Julian Droste ◽  
Christian Rückert ◽  
Jörn Kalinowski ◽  
Mohamed Belal Hamed ◽  
Jozef Anné ◽  
...  
Keyword(s):  
Secondary Metabolite ◽  
Regulatory Networks ◽  
Streptomyces Coelicolor ◽  
Gene Clusters ◽  
Regulatory Elements ◽  
Streptomyces Lividans ◽  
Model Organisms ◽  
Promoter Regions ◽  
Gene Characterization ◽  
Novel Transcripts

Streptomyces lividans TK24 is a relevant Gram-positive soil inhabiting bacterium and one of the model organisms of the genus Streptomyces. It is known for its potential to produce secondary metabolites, antibiotics, and other industrially relevant products. S. lividans TK24 is the plasmid-free derivative of S. lividans 66 and a close genetic relative of the strain Streptomyces coelicolor A3(2). In this study, we used transcriptome and proteome data to improve the annotation of the S. lividans TK24 genome. The RNA-seq data of primary 5′-ends of transcripts were used to determine transcription start sites (TSS) in the genome. We identified 5,424 TSS, of which 4,664 were assigned to annotated CDS and ncRNAs, 687 to antisense transcripts distributed between 606 CDS and their UTRs, 67 to tRNAs, and 108 to novel transcripts and CDS. Using the TSS data, the promoter regions and their motifs were analyzed in detail, revealing a conserved -10 (TAnnnT) and a weakly conserved -35 region (nTGACn). The analysis of the 5′ untranslated region (UTRs) of S. lividans TK24 revealed 17% leaderless transcripts. Several cis-regulatory elements, like riboswitches or attenuator structures could be detected in the 5′-UTRs. The S. lividans TK24 transcriptome contains at least 929 operons. The genome harbors 27 secondary metabolite gene clusters of which 26 could be shown to be transcribed under at least one of the applied conditions. Comparison of the reannotated genome with that of the strain Streptomyces coelicolor A3(2) revealed a high degree of similarity. This study presents an extensive reannotation of the S. lividans TK24 genome based on transcriptome and proteome analyses. The analysis of TSS data revealed insights into the promoter structure, 5′-UTRs, cis-regulatory elements, attenuator structures and novel transcripts, like small RNAs. Finally, the repertoire of secondary metabolite gene clusters was examined. These data provide a basis for future studies regarding gene characterization, transcriptional regulatory networks, and usage as a secondary metabolite producing strain.

scholarly journals Elucidating the Regulatory Elements for Transcription Termination and Posttranscriptional Processing in the Streptomyces clavuligerus Genome

mSystems ◽  
2021 ◽  
Vol 6 (3) ◽  
Author(s):  
Soonkyu Hwang ◽  
Namil Lee ◽  
Donghui Choe ◽  
Yongjae Lee ◽  
Woori Kim ◽  
...  
Keyword(s):  
Secondary Metabolite ◽  
Transcription Termination ◽  
Gene Clusters ◽  
Streptomyces Clavuligerus ◽  
Regulatory Elements ◽  
Regulation Of Transcription ◽  
Content Type ◽  
Transcriptional Regulatory Elements ◽  
Transcriptional Regulatory ◽  
Posttranscriptional Processing

ABSTRACT Identification of transcriptional regulatory elements in the GC-rich Streptomyces genome is essential for the production of novel biochemicals from secondary metabolite biosynthetic gene clusters (smBGCs). Despite many efforts to understand the regulation of transcription initiation in smBGCs, information on the regulation of transcription termination and posttranscriptional processing remains scarce. In this study, we identified the transcriptional regulatory elements in β-lactam antibiotic-producing Streptomyces clavuligerus ATCC 27064 by determining a total of 1,427 transcript 3′-end positions (TEPs) using the term-seq method. Termination of transcription was governed by three classes of TEPs, of which each displayed unique sequence features. The data integration with transcription start sites and transcriptome data generated 1,648 transcription units (TUs) and 610 transcription unit clusters (TUCs). TU architecture showed that the transcript abundance in TU isoforms of a TUC was potentially affected by the sequence context of their TEPs, suggesting that the regulatory elements of TEPs could control the transcription level in additional layers. We also identified TU features of a xenobiotic response element (XRE) family regulator and DUF397 domain-containing protein, particularly showing the abundance of bidirectional TEPs. Finally, we found that 189 noncoding TUs contained potential cis- and trans-regulatory elements that played a major role in regulating the 5′ and 3′ UTR. These findings highlight the role of transcriptional regulatory elements in transcription termination and posttranscriptional processing in Streptomyces sp. IMPORTANCE Streptomyces sp. is a great source of bioactive secondary metabolites, including antibiotics, antifungal agents, antiparasitic agents, immunosuppressant compounds, and other drugs. Secondary metabolites are synthesized via multistep conversions of the precursor molecules from primary metabolism, governed by multicomplex enzymes from secondary metabolite biosynthetic gene clusters. As their production is closely related with the growth phase and dynamic cellular status in response to various intra- and extracellular signals, complex regulatory systems tightly control the gene expressions related to secondary metabolism. In this study, we determined genome-wide transcript 3′-end positions and transcription units in the β-lactam antibiotic producer Streptomyces clavuligerus ATCC 27064 to elucidate the transcriptional regulatory elements in transcription termination and posttranscriptional processing by integration of multiomics data. These unique features, such as transcript 3′-end sequence, potential riboregulators, and potential 3′-untranslated region (UTR) cis-regulatory elements, can be potentially used to design engineering tools that can regulate the transcript abundance of genes for enhancing secondary metabolite production.

scholarly journals Phosphorylated AbsA2 Negatively Regulates Antibiotic Production in Streptomyces coelicolor through Interactions with Pathway-Specific Regulatory Gene Promoters

2007 ◽  
Vol 189 (14) ◽  
pp. 5284-5292 ◽  
Author(s):  
Nancy L. McKenzie ◽  
Justin R. Nodwell
Keyword(s):  
Response Regulator ◽  
Antibiotic Production ◽  
Streptomyces Coelicolor ◽  
Regulatory Gene ◽  
Gene Clusters ◽  
Negative Regulator ◽  
Gene Promoters ◽  
Promoter Regions ◽  
Calcium Dependent

ABSTRACT The AbsA two-component signal transduction system, comprised of the sensor kinase AbsA1 and the response regulator AbsA2, acts as a negative regulator of antibiotic production in Streptomyces coelicolor, for which the phosphorylated form of AbsA2 (AbsA2∼P) is the agent of repression. In this study, we used chromatin immunoprecipitation to show that AbsA2 binds the promoter regions of actII-ORF4, cdaR, and redZ, which encode pathway-specific activators for actinorhodin, calcium-dependent antibiotic, and undecylprodigiosin, respectively. We confirm that these interactions also occur in vitro and that the binding of AbsA2 to each gene is enhanced by phosphorylation. Induced expression of actII-ORF4 and redZ in the hyperrepressive absA1 mutant (C542) brought about pathway-specific restoration of actinorhodin and undecylprodigiosin production, respectively. Our results suggest that AbsA2∼P interacts with as many as four sites in the region that includes the actII-ORF4 promoter. These data suggest that AbsA2∼P inhibits antibiotic production by directly interfering with the expression of pathway-specific regulators of antibiotic biosynthetic gene clusters.

scholarly journals In silico analysis of promoter region and regulatory elements of mitogenome co-expressed trn gene clusters encoding for bio-pesticide in entomopathogenic fungus, Metarhizium anisopliae: strain ME1

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Getachew Bantihun ◽  
Mulugeta Kebede
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Entomopathogenic Fungi ◽  
Metarhizium Anisopliae ◽  
In Silico ◽  
Promoter Region ◽  
Gene Clusters ◽  
Regulatory Elements ◽  
Predictive Score ◽  
Promoter Regions

Abstract Background Pest control strategies almost entirely rely on chemical insecticides, which cause environmental problems such as biosphere deterioration and emergence of resistant pests. Bio-pesticide is an alternative approach, which uses organisms such as entomopathogenic fungi, Metarhizium anisopliae, to control pests. Screening such potential organism at a molecular level and understanding their gene regulation mechanism is an important approach to reduce emergence of pesticide resistance and worsening of the biosphere. Understanding promoter regions which play a pivotal role in gene regulation is crucial. In particular, identification of the promoter regions in M. anisopliae Strain ME1 remains poorly understood. To our knowledge, the mitogenome trn gene clusters of M. anisopliae Strain ME1 were not characterized. Here, we used machine learning approach to identify and characterize the promoter regions, regulatory elements, and CpG island densities of 15 protein coding genes of entomopathogenic fungi, M. anisolpliae Strain ME1. Results The current analysis revealed multiple transcription start sites (TSS) for all utilized sequences, except for promoter region genes of Pro-cob and Pro-nad5. With reference to the start codon (ATG), 85.3% of TSS was located above – 500 bp. Based on the standard predictive score at cut off value of 0.8a, the current study revealed 54.7% of predictive score greater than or equal from 0.9 promoter prediction score. Expectation maximization algorithm output identified five candidate motifs. Nonetheless, of all candidate motifs, MtrnI was revealed as the common promoter region motif with a value of 76.9% both in terms of size of binding sites and with an E value of 9.1E−054. Accordingly, we perceived that MtrnI serve as the binding site for tryptophan cluster with P value 0.0044 and C4 type zinc fingers functions as the binding site to regulate gene expression of M. anisopliae Strain ME1. The analysis revealed that mitogenome trn gene clusters of M. anisopliae Strain ME1 showed homologues evolutionary ancestor supported with a bootstrap value of 100%. Conclusion Identified common candidate motifs and binding transcription factors through in silico approach are likely expected to contribute for better understanding of gene expression and strain improvement of M. anisopliae Strain ME1 for its bio-pesticides role.

scholarly journals Conservation of dynamic characteristics of transcriptional regulatory elements in periodic biological processes

2020 ◽  
Author(s):  
Francis C. Motta ◽  
Robert C. Moseley ◽  
Bree Cummins ◽  
Anastasia Deckard ◽  
Steven B. Haase
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Large Fraction ◽  
Regulatory Elements ◽  
Natural World ◽  
Model Systems ◽  
Model Organisms ◽  
Core Network ◽  
The Core ◽  
Gene Regulatory

AbstractCell and circadian cycles control a large fraction of cell and organismal physiology by regulating large periodic transcriptional programs that encompass anywhere from 15-80% of the genome. The gene-regulatory networks (GRNs) controlling these programs were largely identified by genetics and chromosome mapping approaches in model systems, yet it is unlikely that we have identified all of the core GRN components. Moreover, large periodic transcriptional programs controlling a variety of processes certainly exist in important non-model organisms where genetic approaches to identifying networks are expensive, time-consuming or intractable. Ideally, the core network components could be identified using data-driven approaches on the transcriptome dynamics data already available. Previous work used dynamic gene expression features to identify sets of genes with periodic behavior; our work goes further to distinguish genes by role: core versus their non-regulatory outputs. Here we present a quantitative approach that can identify nodes of GRNs controlling cell or circadian cycles across taxa. There are practical applications of the approach for network biologists, but our findings reveal something unexpected—that there are quantifiable and fundamental shared features of these unrelated GRNs controlling disparate periodic phenotypes.Author summaryCircadian rhythms, cellular division, and the developmental cycles of a multitude of living creatures, including those responsible for infectious diseases, are among the many dynamic phenomena in the natural world that are known to be the eventual output of gene regulatory networks. Identifying the small number of specialized genes that control these dynamic behaviors is of fundamental importance to our understanding of life, and our treatment of disease, but is difficult because of the sheer size of the genomes. We show that the core genes in organisms separated by millions of years of evolution have remarkable similarities that can be used to identify them.

scholarly journals Genome-Wide Analysis Reveals Transcription Factors Regulated by Spider-Mite Feeding in Cucumber (Cucumis sativus)

Plants ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1014
Author(s):  
Jun He ◽  
Harro J. Bouwmeester ◽  
Marcel Dicke ◽  
Iris F. Kappers
Keyword(s):  
Transcription Factors ◽  
Regulatory Networks ◽  
Spider Mite ◽  
Induced Defense ◽  
Regulatory Elements ◽  
Spider Mites ◽  
Promoter Regions ◽  
Cis Acting ◽  
Genes Encoding ◽  
Mite Feeding

To gain insight into the regulatory networks that underlie the induced defense in cucumber against spider mites, genes encoding transcription factors (TFs) were identified in the cucumber (Cucumissativus) genome and their regulation by two-spotted spider mite (Tetranychusurticae) herbivory was analyzed using RNA-seq. Of the total 1212 annotated TF genes in the cucumber genome, 119 were differentially regulated upon spider-mite herbivory during a period of 3 days. These TF genes belong to different categories but the MYB, bHLH, AP2/ERF and WRKY families had the highest relative numbers of differentially expressed genes. Correlation analysis of the expression of TF genes with defense-associated genes during herbivory and pathogen infestation, and in different organs resulted in the putative identification of regulators of herbivore-induced terpenoid and green-leaf-volatile biosynthesis. Analysis of the cis-acting regulatory elements (CAREs) present in the promoter regions of the genes responsive to spider-mite feeding revealed potential TF regulators. This study describes the TF genes in cucumber that are potentially involved in the regulation of induced defense against herbivory by spider mites.

scholarly journals Transcription of Cystathionine β-lyase (MetC) is Repressed by HeuR in Campylobacter jejuni and Methionine Biosynthesis Facilitates Colonocyte Invasion

2021 ◽  
Author(s):  
Brittni R. Kelley ◽  
Sean M. Callahan ◽  
Jeremiah G. Johnson
Keyword(s):  
Campylobacter Jejuni ◽  
Regulatory Protein ◽  
Direct Interaction ◽  
Gene Clusters ◽  
Regulatory Elements ◽  
Methionine Biosynthesis ◽  
Promoter Regions ◽  
Susceptible Host ◽  
Transcriptional Regulatory ◽  
In The Wild

A previously identified transcriptional regulator in C. jejuni, termed HeuR, was found to positively regulate heme utilization. Additionally, transcriptomic work demonstrated the putative operons, CJJ81176_1390-1394 and CJJ81176_1214-1217, were upregulated in a HeuR mutant, suggesting HeuR negatively regulates expression of these genes. Because genes within these clusters include a cystathionine β-lyase (metC) and a methionine synthase (metE), it appeared HeuR negatively regulates C. jejuni methionine biosynthesis. To address this, we confirmed mutation of HeuR reproducibly results in metC overexpression under nutrient-replete conditions, but did not affect expression of metE, while metC expression in the wild-type increased to heuR mutant levels during iron-limitation. We subsequently determined that both gene clusters are operonic and demonstrated the direct interaction of HeuR with the predicted promoter regions of these operons. Using DNase-footprinting assays, we were able to show that HeuR specifically binds within the predicted -35 region of the CJJ81176_1390-1394 operon. As predicted based on transcriptional results, the HeuR mutant was able to grow and remain viable in a defined media with and without methionine, but we identified significant impacts on growth and viability in metC and metE mutants. Additionally, we observed decreased adherence, invasion, and persistence of metC and metE mutants when incubated with human colonocytes, while the heuR mutant exhibited increased invasion. Taken together, these results suggest that HeuR regulates methionine biosynthesis in an iron-responsive manner and that the ability to produce methionine is an important factor for adhering to and invading the gastrointestinal tract of a susceptible host. Importance As the leading cause of bacterial-derived gastroenteritis worldwide, Campylobacter jejuni has a significant impact on human health. Investigating colonization factors that allow C. jejuni to successfully infect a host furthers our understanding of genes and regulatory elements necessary for virulence. In this study, we have begun to characterize the role of the transcriptional regulatory protein, HeuR, on methionine biosynthesis in C. jejuni. When the ability to synthesize methionine is impaired, detrimental impacts on growth and viability are observed during growth in limited media lacking methionine and/or iron. Additionally, mutations in the methionine biosynthetic pathway result in decreased adhesion, invasion, and intracellular survival of C. jejuni when incubated with human colonocytes, indicating the importance of regulating methionine biosynthesis.

scholarly journals Primary transcriptome and translatome analysis determines transcriptional and translational regulatory elements encoded in the Streptomyces clavuligerus genome

2019 ◽  
Vol 47 (12) ◽  
pp. 6114-6129 ◽  
Author(s):  
Soonkyu Hwang ◽  
Namil Lee ◽  
Yujin Jeong ◽  
Yongjae Lee ◽  
Woori Kim ◽  
...  
Keyword(s):  
Secondary Metabolite ◽  
Genome Sequence ◽  
Regulatory Networks ◽  
Streptomyces Clavuligerus ◽  
Regulatory Elements ◽  
Biosynthetic Gene Cluster ◽  
Precise Determination ◽  
Ribosome Profiling ◽  
Translation Efficiency ◽  
Data Types

AbstractDetermining transcriptional and translational regulatory elements in GC-rich Streptomyces genomes is essential to elucidating the complex regulatory networks that govern secondary metabolite biosynthetic gene cluster (BGC) expression. However, information about such regulatory elements has been limited for Streptomyces genomes. To address this limitation, a high-quality genome sequence of β-lactam antibiotic-producing Streptomyces clavuligerus ATCC 27 064 is completed, which contains 7163 newly annotated genes. This provides a fundamental reference genome sequence to integrate multiple genome-scale data types, including dRNA-Seq, RNA-Seq and ribosome profiling. Data integration results in the precise determination of 2659 transcription start sites which reveal transcriptional and translational regulatory elements, including −10 and −35 promoter components specific to sigma (σ) factors, and 5′-untranslated region as a determinant for translation efficiency regulation. Particularly, sequence analysis of a wide diversity of the −35 components enables us to predict potential σ-factor regulons, along with various spacer lengths between the −10 and −35 elements. At last, the primary transcriptome landscape of the β-lactam biosynthetic pathway is analyzed, suggesting temporal changes in metabolism for the synthesis of secondary metabolites driven by transcriptional regulation. This comprehensive genetic information provides a versatile genetic resource for rational engineering of secondary metabolite BGCs in Streptomyces.

Computational approaches to study transcriptional regulation

2008 ◽  
Vol 36 (4) ◽  
pp. 758-765 ◽  
Author(s):  
M. Madan Babu
Keyword(s):  
Transcriptional Regulation ◽  
Regulatory Networks ◽  
Regulatory Elements ◽  
Model Organisms ◽  
Emerging Pathogens ◽  
Transcriptional Regulatory Networks ◽  
Regulatory Interactions ◽  
Regulatory Circuits ◽  
Transcriptional Regulatory ◽  
The Individual

In recent years, a number of technical and experimental advances have allowed us to obtain an unprecedented amount of information about living systems on a genomic scale. Although the complete genomes of many organisms are available due to the progress made in sequencing technology, the challenge to understand how the individual genes are regulated within the cell remains. Here, I provide an overview of current computational methods to investigate transcriptional regulation. I will first discuss how representing protein–DNA interactions as a network provides us with a conceptual framework to understand the organization of regulatory interactions in an organism. I will then describe methods to predict transcription factors and cis-regulatory elements using information such as sequence, structure and evolutionary conservation. Finally, I will discuss approaches to infer genome-scale transcriptional regulatory networks using experimentally characterized interactions from model organisms and by reverse-engineering regulatory interactions that makes use of gene expression data and genomewide location data. The methods summarized here can be exploited to discover previously uncharacterized transcriptional pathways in organisms whose genome sequence is known. In addition, such a framework and approach can be invaluable to investigate transcriptional regulation in complex microbial communities such as the human gut flora or populations of emerging pathogens. Apart from these medical applications, the concepts and methods discussed can be used to understand the combinatorial logic of transcriptional regulation and can be exploited in biotechnological applications, such as in synthetic biology experiments aimed at engineering regulatory circuits for various purposes.

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