Longitudinal dynamics of the nasopharyngal microbiome in response to SARS-CoV-2 Omicron variant and HIV infection in Kenyan women and their infants
Bibliographic record
Abstract
The nasopharynx and its microbiota are implicated in respiratory health and disease. The interplay between viral infection and the nasopharyngeal microbiome is an area of increased interest and of clinical relevance. The impact of SARS-CoV-2, the etiological agent of the Coronavirus Disease 2019 (COVID-19) pandemic, on the nasopharyngeal microbiome, particularly among individuals living with HIV, is not fully characterized. Here we describe the nasopharyngeal microbiome before, during and after SARS-CoV-2 infection in a longitudinal cohort of Kenyan women (21 living with HIV and 14 HIV-uninfected) and their infants (18 HIV-exposed, uninfected and 18 HIV-unexposed, uninfected), followed between September 2021 through March 2022. We show using genomic epidemiology that mother and infant dyads were infected with the same strain of the SARS-CoV-2 Omicron variant that spread rapidly across Kenya. Additionally, we used metagenomic sequencing to characterize the nasopharyngeal microbiome of 20 women and infants infected with SARS-CoV-2, 6 infants negative for SARS-CoV-2 but experiencing respiratory symptoms, and 34 timepoint matched SARS-CoV-2 negative mothers and infants. Since individuals were sampled longitudinally before and after SARS-CoV-2 infection, we could characterize the short- and long-term impact of SARS-CoV-2 infection on the nasopharyngeal microbiome. We found that mothers and infants had significantly different microbiome composition and bacterial load (p-values <.0001). However, in both mothers and infants, the nasopharyngeal microbiome did not differ before and after SARS-CoV-2 infection, regardless of HIV-exposure status. Our results indicate that the nasopharyngeal microbiome is resilient to SARS-CoV-2 infection and was not significantly modified by HIV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".