Omics · dataset · 2026
Relationship between antibiotic treatment and clinical outcome in people with bronchiectasis
Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.17034/32641824.v1
In bronchiectasis (BE), chronic bacterial infection contributes to pulmonary exacerbations, clinical decline, and increased morbidity and mortality.
Description
Bacterial load correlates with airway inflammation and exacerbation risk, supporting the use of long-term inhaled antibiotics. While microbial culture remains the gold standard for pathogen quantification, molecular methods such as quantitative PCR (qPCR) and next-generation sequencing (NGS) offer promising alternatives for assessing microbiological efficacy.<br><br>This thesis aimed to: (i) validate qPCR assays for respiratory pathogen detection and quantification; (ii) evaluate the impact of inhaled antibiotics on sputum bacterial density and clinical outcomes in BE; (iii) assess qPCR and NGS for monitoring microbial changes post-treatment; and (iv) determine the effect of saponin processing on microbial DNA recovery.
Total bacterial, Pseudomonas aeruginosa, and Haemophilus influenzae densities were measured using qPCR in sputum samples from clinical trials, with microbial composition assessed via 16S rRNA sequencing.<br><br>Treatment with tobramycin inhalation powder (TIP) and liposomal ciprofloxacin significantly reduced P. aeruginosa density, measured by quantitative culture, by >3.5 and >1.5 log₁₀ CFU/mL, respectively. Molecular analysis also revealed that TIP decreased total bacterial density and P. aeruginosa density and relative abundance, while promoting a more diverse lung microbiota.
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TIP-treated participants (n=63) were classified as responders or non-responders based on decrease in P. aeruginosa density; P. aeruginosa density decreased by ~4 log₁₀ in responders versus <1 log₁₀ in non-responders. In saponin treated sputum samples from the ORBIT4 trial of inhaled ciprofloxacin, qPCR failed to detect changes in P. aeruginosa density. Saponin (2.5%) caused a substantial loss in total and P. aeruginosa densities and altered microbial composition, effects that persisted after normalisation for volume differences.<br><br>These findings support integrating molecular methods with culture-based techniques in clinical trials, as both reliably track bacterial density changes.
However, saponin processing impairs microbial recovery and diversity, highlighting the need for optimized sample handling protocols.
Links
Where it is published
- DOI doi.org/10.17034/32641824.v1 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
Provenance · 3 source records, 16 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/32641824 | 7 d ago | JSON v1 |
| Deakin Research Online | oai:figshare.com:article/32641824 | 7 d ago | JSON v1 |
| DMU Figshare | oai:figshare.com:article/32641824 | 7 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[modality].local:modality:sequencing | mapping · figshare dmu ac uk | vocabulary-mapper@1.0.0 | keywords['next generation sequencing'] |
| concepts[modality].local:modality:sequencing | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['next generation sequencing'] |
| concepts[modality].local:modality:sequencing | mapping · dro deakin edu au | vocabulary-mapper@1.0.0 | keywords['next generation sequencing'] |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license_text | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |