Molecular Epidemiology of Clinical Infections Caused by <i>Serratia marcescens</i> Complex in a Tertiary Care Hospital System: Insights From Whole-Genome Sequencing
Bibliographic record
Abstract
BACKGROUND: Serratia marcescens is an opportunistic AmpC β-lactamase-producing Enterobacterales associated with intensive care unit outbreaks, causing high morbidity and mortality. The spatiotemporal dynamics of Serratia species and their implications for hospital infection prevention and control remain understudied. METHODS: We prospectively identified patient culture specimens in a multihospital academic healthcare system from 2022 to 2024. We included first-time isolates of S. marcescens identified via culture and confirmed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Isolates underwent whole-genome sequencing on the Illumina NextSeq 2000 platform. We queried assembled genomes using the Comprehensive Antibiotic Resistance Database to identify resistance genes and predict resistomes. We constructed a maximum-likelihood phylogenetic tree using GTDB-Tk-assigned taxonomies. We identified possible links between patients if there was a spatiotemporal overlap and the average nucleotide identity (ANI) of a sequence pair was > 99.0%. We collected relevant patient characteristics via retrospective chart review and analyzed data using descriptive statistics. RESULTS: Of 147 identified isolates, we included 125. Phenotypic testing suggested either inducible or derepressed AmpC expression in all isolates. Whole-genome sequencing found species-level discordance with MALDI-TOF MS in 64 (51.2%) isolates, suggesting the presence of multiple members of the recently described S. marcescens complex causing hospital- or community-associated infections. Only 1 isolate pair had a spatiotemporal link and ANI > 99.0%. CONCLUSIONS: Between-patient transmission of S. marcescens complex outside of outbreaks is likely rare. Current MALDI-TOF MS-based identification methods are insufficient to identify S. marcescens complex and laboratory reporting should be modified to report only to the level of the complex.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".