Sampling Design and Temporal Variation Constrain Inference of Human Gut Microbiome Recovery

Human gut microbiome recovery estimates depend on when samples are collected, which reference is used and how community differences are measured. We reanalyzed public profiles from three perturbation cohorts and two longitudinal comparison cohorts, then evaluated sampling designs under a scalar working model. Among 12 antibiotic-exposed participants, the median day-180 late-to-observed-acute displacement ratio was 0.874 (95% participant bootstrap interval 0.810–0.992). Environmental findings depended on distance geometry, and follow-up within 14 days after 23 diarrheal episodes did not establish return. Longer sampling intervals were associated with larger relative composition differences in nine Broad Institute-OpenBiome Microbiome Library (BIO-ML) donors and 19 Vandeputte participants. Sparse individual schedules could not identify all free recovery parameters. In an illustrative simulation with a 10-day recovery scale, residual displacement 0.20 and Gaussian noise standard deviation 0.08, reallocating six follow-ups from days 30–180 to days 2–180 increased estimates within 25% of truth from 25.4% to 69.0%. Confidence sets could contain truth while remaining too broad for useful inference. Weak signals and model misspecification could defeat additional observations. The findings support cohort-specific interpretation and scenario-dependent planning, without establishing a universal recovery law or sufficient sample count.