Soil Health to Human Health: Application of Soil Probiotics for a Sustainable Future in Agriculture—A Review

Agricultural intensification with synthetic fertilisers has systematically disrupted soil organic carbon (SOC), influenced rhizosphere networks, and affected human health via the soil–human microbial continuum. Plant Growth-Promoting Microorganisms (PGPMs) can restore biogeochemical cycles; however, field performance varies due to spatial stoichiometric variation. In order to visualise the problem and provide a potential solution, we use global soil carbon-to-nitrogen (C/N) ratio stratification over three depth profiles (0–5, 5–15, and 15–30 cm) to create a potential spatially explicit framework for site-specific PGPM application. In comparison to contemporary models that attribute stable soil organic matter creation mostly to microbial necromass buildup as mineral-associated organic matter (MAOM) via the microbial carbon pump, we assess diazotrophic nitrogen fixation, phosphate solubilisation, and glomalin-mediated aggregation. According to stoichiometric analysis, low C/N ratios (<10:1) increase organic matter mineralisation via priming effects, resulting in clay compaction and sandy soil desiccation, while wide ratios (>30:1) cause microbial nitrogen immobilisation (“nitrogen depression”). To mitigate these limitations, we proposed depth-stratified inoculation, applying chemotactic taxa (Variovorax paradoxus) at 15–30 cm in carbon-depleted subsoils; co-inoculating diazotrophs and arbuscular mycorrhizae (Rhizophagus irregularis) at 5–15 cm for stoichiometric balance and phosphorus acquisition and deploying exopolysaccharide-producing and 1-aminocyclopropane-1-carboxylate (ACC) deaminase-active taxa (Pseudomonas putida, Funneliformis mosseae) at 0–5 cm for erosion. In conclusion, in order to maximise fertiliser use efficiency, improve structural stability, and protect metabolic health within the interdisciplinary One Health framework, we assess the shift toward trait-based, multi-kingdom Synthetic Microbial Communities (SynComs), assembled via genomic metabolic reconstructions and machine learning. We explicitly acknowledge methodological limits in existing field applications, such as substantial spatial variability, equipment constraints, and biotic competition, putting scientific validity ahead of generalised efficacy.