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Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence

View Article: PubMed Central - PubMed

ABSTRACT

Background: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence.

Results: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region.

Conclusions: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.

Electronic supplementary material: The online version of this article (doi:10.1186/s12864-017-3616-7) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

Genomic distribution of ATRs and the relA locus in N. meningitidis. a The intergenic region between grxB and relA. The integration site of a copy of an ATR repeat element upstream of relA (ATRrelA) in strain α522 is indicated with respect to the MC58 locus. The transcriptional start sites as determined by 5’-RACE in both strains are indicated along with the deduced −35 and −10 boxes and the computationally predicted promoter regions using PPP [117]. DR: direct repeat. b Alignment of both the MC58 (upper lane) and α522 (lower lane) genomes as visualized with the Artemis comparison tool based on a BLASTN comparison. The linearized MC58 and α522 genomes are shown in the upper and lower panel as gray bars, and regions syntenic in both genomes are connected via red and inverted regions via blue lines, respectively. The location of ATRs is indicated by small arrows in each genome, and the relA region is highlighted in yellow
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Fig7: Genomic distribution of ATRs and the relA locus in N. meningitidis. a The intergenic region between grxB and relA. The integration site of a copy of an ATR repeat element upstream of relA (ATRrelA) in strain α522 is indicated with respect to the MC58 locus. The transcriptional start sites as determined by 5’-RACE in both strains are indicated along with the deduced −35 and −10 boxes and the computationally predicted promoter regions using PPP [117]. DR: direct repeat. b Alignment of both the MC58 (upper lane) and α522 (lower lane) genomes as visualized with the Artemis comparison tool based on a BLASTN comparison. The linearized MC58 and α522 genomes are shown in the upper and lower panel as gray bars, and regions syntenic in both genomes are connected via red and inverted regions via blue lines, respectively. The location of ATRs is indicated by small arrows in each genome, and the relA region is highlighted in yellow

Mentions: The machinery of the stringent response pathway comprises several enzymes involved in the turnover of (p)ppGpp which is a signaling nucleotide that coordinates a variety of cellular activities in response to changes in nutritional abundance [76]. In E. coli, RelA is activated upon amino acid starvation and together with SpoT is able to catalyze pyrophosphoryl transfer from ATP to GTP or GDP to synthesize (p)ppGpp. Together with DnaK suppressor (DksA), (p)ppGpp directs transcription initiation at particular gene promoters through binding to the interface between the two RNA polymerase subunits β’ and ω [77, 78]. In part, (p)ppGpp and DksA act by promoting the interaction of RNA polymerase with alternative σ-factors such as σE or σH. When metabolic precursors are plentiful, SpoT instead degrades (p)ppGpp, and the vegetative σ-factor, σ70, directs RNA polymerase to genes that are crucial for bacterial replication. Whereas β’, ω, SpoT and DksA were identical in both strains they differed in the coding sequences and promoter region of RelA (Fig. 7a), and gene expression analyses via qRT-PCR further confirmed particular large and blood-specific cross-strain expression differences for relA but not for spoT or dksA (Additional file 1: Figure S3).Fig. 7


Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence
Genomic distribution of ATRs and the relA locus in N. meningitidis. a The intergenic region between grxB and relA. The integration site of a copy of an ATR repeat element upstream of relA (ATRrelA) in strain α522 is indicated with respect to the MC58 locus. The transcriptional start sites as determined by 5’-RACE in both strains are indicated along with the deduced −35 and −10 boxes and the computationally predicted promoter regions using PPP [117]. DR: direct repeat. b Alignment of both the MC58 (upper lane) and α522 (lower lane) genomes as visualized with the Artemis comparison tool based on a BLASTN comparison. The linearized MC58 and α522 genomes are shown in the upper and lower panel as gray bars, and regions syntenic in both genomes are connected via red and inverted regions via blue lines, respectively. The location of ATRs is indicated by small arrows in each genome, and the relA region is highlighted in yellow
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Fig7: Genomic distribution of ATRs and the relA locus in N. meningitidis. a The intergenic region between grxB and relA. The integration site of a copy of an ATR repeat element upstream of relA (ATRrelA) in strain α522 is indicated with respect to the MC58 locus. The transcriptional start sites as determined by 5’-RACE in both strains are indicated along with the deduced −35 and −10 boxes and the computationally predicted promoter regions using PPP [117]. DR: direct repeat. b Alignment of both the MC58 (upper lane) and α522 (lower lane) genomes as visualized with the Artemis comparison tool based on a BLASTN comparison. The linearized MC58 and α522 genomes are shown in the upper and lower panel as gray bars, and regions syntenic in both genomes are connected via red and inverted regions via blue lines, respectively. The location of ATRs is indicated by small arrows in each genome, and the relA region is highlighted in yellow
Mentions: The machinery of the stringent response pathway comprises several enzymes involved in the turnover of (p)ppGpp which is a signaling nucleotide that coordinates a variety of cellular activities in response to changes in nutritional abundance [76]. In E. coli, RelA is activated upon amino acid starvation and together with SpoT is able to catalyze pyrophosphoryl transfer from ATP to GTP or GDP to synthesize (p)ppGpp. Together with DnaK suppressor (DksA), (p)ppGpp directs transcription initiation at particular gene promoters through binding to the interface between the two RNA polymerase subunits β’ and ω [77, 78]. In part, (p)ppGpp and DksA act by promoting the interaction of RNA polymerase with alternative σ-factors such as σE or σH. When metabolic precursors are plentiful, SpoT instead degrades (p)ppGpp, and the vegetative σ-factor, σ70, directs RNA polymerase to genes that are crucial for bacterial replication. Whereas β’, ω, SpoT and DksA were identical in both strains they differed in the coding sequences and promoter region of RelA (Fig. 7a), and gene expression analyses via qRT-PCR further confirmed particular large and blood-specific cross-strain expression differences for relA but not for spoT or dksA (Additional file 1: Figure S3).Fig. 7

View Article: PubMed Central - PubMed

ABSTRACT

Background: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence.

Results: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region.

Conclusions: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.

Electronic supplementary material: The online version of this article (doi:10.1186/s12864-017-3616-7) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus