Converting 16S Amplicon Reads to CFU Equivalents in Processed Foods by Viable Target Metagenomics

Using a viability-resolved metagenomics protocol coupled with copy-number-corrected absolute quantification, we report three findings from a longitudinal study of eight ready-to-eat (RTE) seafood matrices subjected to combined pasteurization and high-pressure processing (HPP). First, we demonstrate that 16S amplicon relative abundances can be converted into absolute cell counts concordant with ISO culture methods (Lin's CCC = 0.94; Bland-Altman bias = −0.25 log₁₀, non-significant; 93% within ±1 log₁₀). This establishes that the three principal barriers to quantitative amplicon metagenomics — compositional bias, copy-number distortion, and dead-cell DNA contamination — can be jointly overcome within a single analytical workflow. Second, we provide the first community-scale quantification of viable but non-culturable (VBNC) populations in processed foods: 60% of indicator groups with negative culture harbored molecular loads of 10³–10⁷ cells/g. The discrepancy scaled with predicted membrane resilience — maximal for sporulating clostridia (+5.9 log₁₀), intermediate for Gram-negative Enterobacteriaceae (+4.0 log₁₀), minimal for lactic acid bacteria — implicating differential DNase impermeability as a biological mechanism rather than an algorithmic artifact. Third, we uncovered a post-treatment microbial succession qualitatively distinct from that described for HPP alone. Whereas HPP-only products are typically dominated by mesophilic Leuconostoc and Lactobacillus, the combined thermal-barometric treatment selected spore-formers (Clostridium spp., Sporosarcina), the thermo-barotolerant lactic acid bacterium Carnobacterium as dominant LAB, and post-process recontamination psychrotrophs (Psychrobacter, Acinetobacter). Combining lethal barriers thus reconfigures surviving community structure rather than merely reducing it. These findings were enabled by DELOREAN (Deep Estimation of Live Organisms by Read Equivalence to Agar Numbers), a framework that integrates an original sample preparation protocol — Viable Target Metagenomics (vtMG) — with a quantitative conversion algorithm. vtMG enriches DNA from membrane-intact cells through differential lysis and DNase treatment as an enzymatic alternative to PMA; the algorithm then anchors copy-number-corrected relative abundances to fluorimetric total DNA quantification via empirical scaling factors. Calibration factors were derived in a prior, independent pilot study and applied without modification to the validation dataset, constituting a legitimate out-of-distribution test. The framework is classifier-agnostic, platform-independent, and designed for progressive refinement through collaborative calibration.