Barriers to Clinical Translation of Microbiome Research in Surgical Site Infections: A Methodological Appraisal

Authors:
Divya Kewalramani, Kaustav Chattopadhyay, Tyler Loftus, Alexander Wurtz, Oluwaseun Adeyemi, Kiloni Quiles, Justin Benton, Rachel Choron, Keith Kaye, W. Evan Johsnon, Marc G. Jeschke, Lillian S. Kao, Robert G. Sawyer, Jeffrey S. Upperman, David P. Blake, John C. Alverdy, E. Patchen Dellinger, Philip S. Barie, Mayur Narayan

Body of Abstract:
Background: Most surgical site infections (SSIs) arise from endogenous microbial reservoirs, yet perioperative prevention tactics remain focused on exogenous contamination and environmental control. The specific role of various microbiomes in SSI pathogenesis is still being defined. Existing SSI–microbiome studies are mostly observational and heterogeneous in design and reporting, limiting synthesis and translation into clinical practice. We hypothesized that methodologic appraisal of SSI–microbiome studies would reveal consistent gaps that currently impede analysis.

Methods: We conducted a scoping review (2005–2025) of human studies linking the skin, gut, or biliary microbiome to SSI using culture- or sequencing-based approaches. Eighteen eligible studies encompassing 3,170 patients and 482 SSIs were identified. Each study was evaluated using a novel six-domain methods-quality framework: (D1) Study design and sampling, (D2) laboratory and contamination control, (D3) sequencing and bioinformatics, (D4) statistics for compositional data, (D5) clinical covariates, and (D6) SSI outcome definitions.

Results: In D1, only 5.6% (n=2) reported a priori power calculations, 44.4% (n=8) relied on single-timepoint designs, limiting the ability to distinguish preoperative colonization from infection-induced microbial changes. In D2, culture-based methods dominated (66.7%, n=12), but only 41.7% (n=5/12) reported any quality-control measures. Among sequencing studies (33.3%, n=6), all described quality control, yet only 50.0% (n=3) assessed contamination or batch effects explicitly. D3 was not applicable to culture based studies and sequencing approaches were highly variable in targeted regions, pipelines, and reference databases, and strain-level resolution was rare. In D4, culture studies leaned on simple hypothesis testing, whereas only half of sequencing studies (50.0%, n=3) performed differential abundance analysis. For D5, 83% (n=15) reported at least one covariate, but across 126 distinct data elements assessed, antibiotic prophylaxis was under-captured (n=3). Finally, D6 definitions were not uniform: only 55.6% (n=10) used standardized Altemeier criteria, while 38.9% (n=7) relied on clinical judgment and 5.6% (n=1) on culture positivity alone. Surveillance windows spanned 30–730 days.

Conclusion: Current SSI–microbiome studies are constrained by fragmented methods and non-standardized reporting across six defined reporting domains. Documented gaps in statistical power, contamination control, sequencing and analytic methods, covariate capture, and SSI outcome definitions underscore the need for standardized design and reporting to enable reproducible and translatable SSI–microbiome research.