Beyond the Billion: Dose-Response Immunophenotyping and Machine Learning Classification of Live versus Heat-Inactivated Gram-Positive Probiotic Strains in Human Peripheral Blood Mononuclear Cells

Abstract

Probiotic research is constrained by three pervasive yet insufficiently challenged assumptions: the requirement for a minimum of one billion colony-forming units for efficacy, the necessity for gut colonization, and the inherent superiority of live over heat-treated preparations. This study addresses these gaps through a fully factorial experimental design evaluating ten Gram-positive probiotic strains in both viable (Active Fluorescent Units, AFU) and heat-treated (Total Fluorescent Units, TFU) forms across three flow cytometry-verified concentrations (105, 106, 107 cells/well per ISO 19344:2015) in primary human peripheral blood mononuclear cells (PBMC) from a single healthy male Caucasian donor (58 years), with simultaneous quantification of 17 cytokines by BioPlex suspension array. Viable preparations induced profoundly greater absolute cytokine responses than heat-treated preparations across 16 of 17 analytes, heat-treated preparations demonstrated stronger dose-response correlations (mean within-strain Spearman {rho} up to 1.00) for 13 of 17 cytokines, a finding we attribute to the uncontrolled proliferation of live bacteria during 24-hour co-culture compressing the effective concentration range. Six of ten viable strains exhibited monotonically increasing profiles; two strains displayed non-monotonic bell-shaped kinetics with peak activity at 106 AFU/well and significant attenuation at 107, directly falsifying the assumption that dose escalation uniformly increases immunological activity. MCP-1 was the sole cytokine showing no significant difference between viability states at the observation level (p = 0.61, fold-change 1.0), providing an internal methodological control. In this single-donor model, unsupervised hierarchical clustering identified three immunological phenotype clusters, requiring multi-donor validation before these groupings can be treated as generalizable biological phenotypes, with Random Forest classification achieving 83.3% internal partition-recovery consistency (clusters derived from the same data; not an estimate of generalization to novel strains) versus 33.3% chance; In this single-donor experiment, IL-12p70, IL-13, and IFN-{gamma}, not IL-6 or IL-1{beta}, were the primary discriminators of strain identity; generalizability of this ranking requires multi-donor validation. Heat-treated preparations achieved [≥]70% functional equivalence relative to viable preparations at 107 TFU/well for the majority of responsive strains (Functional Equivalence Dose, FED70), while one strain showed strongly attenuated activity in heat-treated form across all concentrations, a finding subject to the caveat that no positive control stimulus was included to formally verify PBMC functional competence on the experimental day. These findings establish a methodological framework integrating flow cytometric standardization, multiplex immunophenotyping, and machine learning for evidence-based dose characterization, postbiotic functional equivalence assessment, and data-driven strain classification in probiotic research (all p-values are descriptive within a single-donor experimental context).