PubMed HealthSearch

PubMed · 42616031

Streptococcus pneumoniae adaptation to nutrient deprivation and immune modulation drives upper respiratory tract colonization.

Abstract

Streptococcus pneumoniae is a successful colonizer of the human upper respiratory tract; however, the mechanisms that enable its persistence in this nutrient-limited environment, with numerous immune mechanisms in place, remain enigmatic. Here, we examined how pneumococci adapt to upper respiratory tract conditions and how this affects host interactions. We measured intranasal metal ion and monosaccharide concentrations to create an in vivo-mimicking medium for studying pneumococcal adaptation. Growth in this medium was reduced compared to glucose-rich chemically defined media (CDM). Proteome analysis revealed a shift to galactose as the major carbohydrate source, and decreased levels of fatty acid biosynthesis proteins and pneumolysin, compared to other CDMs. Glycerophosphocholine accumulated extracellularly leading to decreased C-reactive protein and Immunoglobulin M binding to pneumococci. Pneumococci grown in in vivo-mimicking medium, compared to glucose-rich media, were more capable colonizers of primary epithelium and induced less epithelial cytokine release. Together, this shows how pneumococci adapt to the nutrient-limited respiratory environment, modulate epithelial cells, and evade humoral responses to facilitate persistent colonization.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Daan W Arends, Kristin Surmann, Lucille F van Beek, Robert S Jansen, Rob J Mesman, Jeroen D Langereis, Monique van Scherpenzeel, Manuela Gesell Salazar, Uwe Völker, Gerco den Hartog, Marien I de Jonge. 2026-01-14. Streptococcus pneumoniae adaptation to nutrient deprivation and immune modulation drives upper respiratory tract colonization.. https://doi.org/10.1093/ismejo%2Fwrag213

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

KEEP EXPLORING

Related citations

A reusable model of pangenome selection informs optimal surveillance strategies over vaccine introductions.

BACKGROUND: The human pathogen Streptococcus pneumoniae is a major cause of disease, including pneumonia and meningitis. The introduction of Pneumococcal Conjugate Vaccines (PCVs) initially reduced the burden of disease through a reduction of colonisation by vaccine-targeted serotypes. However, since PCVs only target a proportion of pneumococcal serotypes, they shift intraspecific competition, eventually allowing non-targeted types to 'replace' vaccine types. Understanding the host and pathogen factors causing replacement is important for future vaccine development. Mechanistic understanding of vaccine replacement dynamics is crucial for forecasting and optimisation of genomic surveillance strategies to evaluate realised vaccine effectiveness. METHODS: We developed a mathematical model of the genomic and demographic factors which explain vaccine replacement, used this model to replicate serotype-frequency changes, and investigated cost-effective genomic surveillance strategies. We extended a forward-time model based on the Wright-Fisher model, developing a user-friendly model framework that describes the post-vaccine dynamics of S. pneumoniae populations. Our model describes vaccine replacement as a function of vaccine impact, immigration of new strains, and negative frequency-dependent selection (NFDS) on the accessory genome content. RESULTS: We used our model to study vaccine replacement in newly sequenced genomic surveillance data from Kathmandu (Nepal), and existing data from Massachusetts (US) and Southampton (UK), with distinct surveillance strategies. We showed that the model with NFDS better replicates replacement dynamics than a null model without NFDS, and that NFDS likely only acts on part of the S. pneumoniae accessory genome. We found consistent estimates for vaccination effectiveness across the different study locations and region-specific genes under NFDS, highlighting the importance of conducting genomic surveillance in each country of interest. By simulating data from the model, we showed that an optimal surveillance strategy prioritises per-sampling sample size over sampling frequency for small sampling budgets. CONCLUSIONS: Our model can be used to predict vaccine replacement dynamics after PCV introduction, and can be easily reapplied to analyse new data from vaccine introductions or new regions. Our model is available in the R package Stubentiger (Studying Balancing Evolution (NFDS) To Investigate Genome Replacement) on GitHub https://github.com/bacpop/Stubentiger .

Streptococcus pneumoniae

Lineage structure and penicillin-binding protein variability in clinical Streptococcus pneumoniae isolates from Southwest China exhibiting reduced susceptibility to penicillin.

BACKGROUND: Reduced susceptibility to penicillin in Streptococcus pneumoniae is mediated primarily by alterations in penicillin-binding proteins (PBPs) and often coexists with multidrug resistance within successful lineages. The region-specific genomic characterization of clinically relevant pneumococci with reduced penicillin susceptibility in Southwest China remains limited. METHODS: We performed whole-genome sequencing of 204 clinical S. pneumoniae isolates collected from five institutions in Southwest China (2018-2022) that met our operational screening definition of reduced susceptibility to penicillin (PEN MIC ≥0.12 μg/mL). Molecular serotypes, MLST types, and Global Pneumococcal Sequence Clusters (GPSCs) were assigned; virulence and antimicrobial resistance determinants were profiled; and a core genome phylogeny was reconstructed with international contextualization through the use of PubMLST genomes meeting the same MIC criterion. Amino acid variability in PBP1a/PBP2b/PBP2x was quantified using TIGR4 numbering, and highly variable noncatalytic residues located within 15 Å of catalytic motifs were prioritized via structure-guided screening. RESULTS: The isolates showed a high burden of resistance to non-β-lactam antibiotics (erythromycin, 98.5%; tetracycline, 82.8%; trimethoprim-sulfamethoxazole, 64.7%), while fluoroquinolone susceptibility was largely preserved (≥97%), and vancomycin/linezolid resistance was not detected. Twenty-seven serotypes were identified, among which 19F (23.5%) and 19A (14.2%) were dominant, and the estimated PCV13 coverage was 69.6%. GPSC1 was the dominant lineage (36.8%), and the lineage composition among our isolates differed markedly from those in the PubMLST-USA and PubMLST-Thailand subsets. Virulence and resistance gene carriage differed markedly between GPSC1 and non-GPSC1 isolates, with enrichment of pilus operons, mef(A)/msr(D), and folA/folP in GPSC1. PBP variations were clustered in transpeptidase domains and motif-adjacent regions while essential catalytic residues were conserved; with the structure-guided filter, 12, 11, and 11 motif-proximal noncatalytic candidate sites were prioritized in PBP1a, PBP2b, and PBP2x, respectively. CONCLUSION: Clinical S. pneumoniae isolates with reduced penicillin susceptibility collected in Southwest China demonstrated resistance and accessory gene profiles that were strongly structured by a GPSC-defined lineage background. Our site-resolved, structure-guided PBP analysis provides a regional PBP variability landscape and a compact set of recurrent motif-proximal candidate substitutions to support surveillance and downstream functional validation.

Streptococcus pneumoniae

Alternative quadruplex real-time PCR reactions for detection and discrimination of Streptococcus pneumoniae serotypes within serogroup 6.

UNLABELLED: Streptococcus pneumoniae causes significant morbidity and mortality worldwide, and serotyping is important to assess the burden of disease that is vaccine preventable. For serotyping, the Centers for Disease Control and Prevention (CDC) use a series of 12 real-time multiplex PCRs (rmPCRs) performed in quadruplex reactions; however, rmPCR reaction 5 (rmPCR-5) for serotypes 6A, 6B, 6C, and 6D often failed at low DNA concentrations. This study investigated the cause of rmPCR-5 failure and provided alternative rmPCRs to resolve this issue. Quadruplex rmPCR target sequences were compared to S. pneumoniae reference genomes. Reactions rmPCR-5 [6ABCD, 6AB, 6BD, and 6CD] and rm-PCR-11 [37, 10F, 11BC, and 18CFBA] were compared to alternative reactions rmPCR-A1 [6ABCD, 10F, 11BC, and 18CFBA] and rmPCR-A2 [37, 6AB, 6BD, and 6CD]. All rmPCRs were tested using 10-fold serial dilutions of DNA from representative serotypes, and analytical specificity was assessed using DNA from other S. pneumoniae serotypes or various streptococci and Gram-positive cocci. Failure of rmPCR-5 was associated with overlapping 6ABCD and 6BD targets. Separation of these targets in the alternative rmPCRs-A1 and rmPCR-A2 allowed sensitive and specific detection and discrimination of serotypes 6A, 6B, 6C, and 6D, without impacting the detection of serotypes 10F, 11BC, 18CFBA, and 37. This study highlights the importance of rigorous author and peer-review to avoid manuscript errors and unintended consequences. By explaining what caused rmPCR-5 failure and proposing alternative reactions rmPCRs-A1 and rmPCR-A2, this study demonstrates the value of scientific collaboration to ensure molecular assays best serve the scientific community. IMPORTANCE: Streptococcus pneumoniae is a bacterium that can cause life-threatening infections like pneumonia and meningitis, leading to millions of deaths worldwide each year. A key feature enabling S. pneumoniae to cause disease is its sugar coating, allowing it to avoid the immune system. These surface sugars are the target of S. pneumoniae vaccines. However, vaccines only protect against some sugars and understanding which ones are on the surface of S. pneumoniae is called "serotyping." The Centers for Disease Control and Prevention (CDC) have protocols that allow us to predict S. pneumoniae serotypes by looking at its DNA. We found errors in the CDC protocols and provided a simple solution to fix them. Ultimately, having accurate serotyping protocols allows us to know how much disease is preventable by vaccine, allows us to monitor how well vaccine are working, and helps develop new vaccines if needed.

Streptococcus pneumoniae