bioRxiv Science⌕ Search

bioRxiv · 10.1101/2023.08.03.550501

Essential role of proline synthesis and the one-carbon metabolism pathways for systemic virulence of Streptococcus pneumoniae

Abstract

Previous virulence screens have indicated potential roles during Streptococcus pneumoniae infection for the one-carbon metabolism pathway component Fhs and proline synthesis mediated by ProABC. To define how these metabolic pathways affect S. pneumoniae virulence we have investigated phenotypes and transcription profiles of {Delta}fhs and {Delta}proABC strain mutants. S. pneumoniae capsular serotype 6B BHN418 {Delta}fhs and {Delta}proABC mutant strains were markedly reduced virulence in mouse models of systemic infection and pneumonia, but were still able to colonise the nasopharynx. Although the {Delta}fhs and {Delta}proABC mutant strains grew normally in complete media, both mutant strains had markedly impaired growth in chemically defined medium, human serum and human CSF. The {Delta}proABC strain also had impaired growth under conditions of osmotic and oxidative stress. When transferred to the serotype 2 D39 S. pneumoniae strain background, the {Delta}fhs mutation replicated the virulence and growth in serum phenotype of the BHN418 mutation. In contrast, the D39 {Delta}proABC mutant could cause septicaemia and grow in human serum, indicating the role of this genetic locus during virulence is strain-specific. In human sera the {Delta}fhs and {Delta}proABC mutants both had major derangements in global gene transcription affecting multiple but different metabolic pathways, identifying the corresponding S. pneumoniae metabolic functions affected by these genes under infection-related conditions. Our data demonstrate an essential role for the S. pneumoniae one- carbon metabolism and a strain-conditional role for proline biosynthesis for growth in physiological fluids and therefore systemic infection, and further demonstrate the vital importance of bacterial metabolism for disease pathogenesis. ImportanceRapid adaptation to grow within the physiological conditions found in the host environment is an essential but poorly understood virulence requirement for systemic pathogens such as Streptococcus pneumoniae. We have now demonstrated an essential role for the one-carbon metabolism pathway and a conditional role depending on strain background for proline biosynthesis for S. pneumoniae growth in serum or CSF and therefore for systemic virulence. RNAseq data demonstrated that loss of one carbon metabolism or proline biosynthesis both have profound but differing effects on S. pneumoniae metabolism in human serum, identifying the metabolic processes dependent on each pathway during systemic infection. These data provide a more detailed understanding of the adaptations required by systemic bacterial pathogens in order to cause infection, and demonstrate that the requirement for some of these adaptations vary between strains from the same species and could therefore underpin strain variations in virulence potential.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ramos Sevillano, E., Ercoli, G., Betts, M., Guerra-Assuncao, J. A., Partridge, F., Silva Entrudo Fernandes, V., Wall, E., Gordon, S., Ferreira, D. S., Heyderman, R., Brown, J. S.. 2023-08-03. Essential role of proline synthesis and the one-carbon metabolism pathways for systemic virulence of Streptococcus pneumoniae. https://doi.org/10.1101/2023.08.03.550501

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A population-scale landscape of the subgingival microbiome reveals divergent routes to periodontal dysbiosis

Periodontitis is an archetypical mucosal inflammatory disease in which microbiome dysbiosis at the tooth-epithelial interface interacts with host genetic and behavioral risk factors to drive immune-mediated tissue destruction. Although subgingival microbiome compositional shifts are thought to parallel disease severity, microbiome variation at the population-level and its relationship to periodontal clinical phenotypes and disease-modifying factors remain poorly defined. Here, we use unsupervised manifold learning to map the compositional landscape of the subgingival microbiome in 1,355 adults spanning periodontal health to severe periodontitis. We identified eight latent microbiome states organized along a branching continuum from eubiosis to dysbiosis. An intermediate microbial configuration marked ecological destabilization and bifurcation into two distinct periodontitis-associated dysbiotic trajectories, distinguished by links to gingival inflammation and smoking. Although the microbiome trajectories broadly tracked periodontal destruction, a minority of individuals showed discordant microbiome-clinical phenotypes, with some individuals with periodontitis retaining otherwise eubiotic microbiomes enriched for low-abundance pathobionts, while some cases of health or mild disease had highly dysbiotic communities, suggesting distinct host susceptibility. Together, these findings define a population-scale ecological landscape of the subgingival microbiome, reveal divergent trajectories to periodontal dysbiosis, and highlight heterogeneity in the relationship between microbial community structure and clinical disease expression.

microbiology↗

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗

Taxonomic and functional concordance between full-length ONT 16S and ONT shotgun metagenomics in the canine gut microbiome

Background: Full-length Oxford Nanopore Technologies (ONT) 16S rRNA sequencing provides a scalable view of microbial community composition and can support phylogeny-based functional prediction, but it is not equivalent to shotgun metagenomics. We asked which biological conclusions are preserved when the same canine fecal specimens are profiled by full-length ONT 16S and ONT whole-genome shotgun (WGS) sequencing, and how their agreement depends on analytical scale, reference representation and classifier. Methods: Ninety-seven fecal specimens from 51 dogs were profiled with both assays from the same DNA extract. Functional profiles predicted from NanoASV/NanoPredict with PICRUSt2 were compared with WGS-supported KEGG Ortholog (KO) profiles generated by Kadath. Taxonomy was benchmarked in a source-genome-matched RefSeq universe and in a host-specific DogMAG universe using minitax and Kraken2. Agreement was evaluated at whole-profile, feature-abundance, detection, between-sample structure and biological-inference scales. Age-associated transfer was assessed with dog-aware continuous mixed models, grouped signed-score analyses and paired/dog-blocked PERMANOVA. Results: Functional whole-profile concordance was high: median within-sample CLR Spearman correlations ranged from 0.781 to 0.860 across developmental strata, while between-sample functional structure remained significant by Mantel (rho=0.543) and Procrustes (r=0.693; both p=0.001). Feature-wise transfer was substantially weaker (median KO-wise CLR Spearman=0.318). Continuous age-associated KO slopes showed substantial cross-assay concordance (Spearman=0.727; signed-score Spearman=0.753; direction agreement=77.9%), although 1,290/5,258 eligible KOs retained significant assay-by-age interactions. Taxonomically, exact genus/species abundance agreement was much lower than agreement in between-sample ecological structure. Host-specific DogMAG improved species-level median Spearman from 0.261 to 0.656 for minitax SpeciesEstimate and from 0.181 to 0.512 for Kraken2. The classifier effect was independent of reference choice: under both RefSeq and DogMAG, minitax yielded stronger 16S-WGS concordance than Kraken2, with all eight prespecified RefSeq paired genus/species endpoints and all 10 DogMAG primary paired endpoints significant after BH correction. The same ordering extended to developmental inference, with DogMAG genus/species age-slope concordance of 0.795/0.799 for SpeciesEstimate versus 0.693/0.702 for Kraken2. Taxonomic Aitchison PERMANOVA detected age-associated structure in every assay/reference/classifier/rank combination, whereas age-by-assay interactions were consistently significant but small (R2 approximately 1.1 to 2.2%). Stricter NanoASV identity thresholds removed substantial 16S abundance without improving species-level agreement. Conclusions: The extent of cross-assay agreement depends on the level of analysis. Full-length ONT 16S preserves broad functional organization, ecological structure and much of the direction of age-associated change, but exact fine-rank composition, individual-feature abundance and effect magnitude remain assay dependent. Host-specific reference representation substantially narrows the taxonomic gap, and classifier choice exerts an additional independent effect: within the same matched reference set, minitax consistently yields stronger 16S-WGS concordance than Kraken2 across abundance, detection, ecological-distance and developmental-inference endpoints. Full-length ONT 16S is therefore well suited to broad ecological screening and hypothesis generation, whereas WGS remains preferable when conclusions depend on quantitative fine-rank composition, directly supported gene content or precise feature-level effect estimates.

microbiology↗