Metabolic inequality in microbial communities

How metabolic activity is distributed among individuals determines the scaling of cellular physiology to higher levels of biological organization. Yet the mechanisms that generate this heterogeneity and shape its distribution remain largely unresolved. We quantified single-cell metabolism in microbial communities spanning aquatic, terrestrial, and host-associated ecosystems. Across more than one million cells, metabolic activity followed a long-tailed distribution best described by a lognormal model, with a small subset of individuals contributing disproportionately to community metabolism. In some cases, the most active 20% of cells accounted for over 90% of metabolic output, although this pattern became less pronounced in more productive environments. To assess the consequences of metabolic inequality, we developed a model linking single-cell activity to community respiration. Because respiration responds nonlinearly to enzyme activity, variation among cells does not translate proportionally into ecosystem-level fluxes. As a result, ignoring metabolic heterogeneity can bias estimates of community respiration by up to 60%. Our findings reveal a general pattern of metabolic inequality across microbial communities in disparate habitats. Accounting for this structure is critical for understanding how microorganisms shape ecosystem processes and for improving predictions of large-scale biogeochemical dynamics. SignificanceInequality is a common feature of social, economic, and physical systems. It also arises in nature, where a small fraction of individuals accounts for an outsized share of biological output, including reproduction, immunity, and diversity. Here, we show that metabolic activity in microbial communities follows a characteristic long-tailed distribution that consistently emerges across diverse ecosystems, including lakes, soils, ocean plankton, marine sediments, and mammalian guts. Rather than a rich-get-richer dynamic, metabolism becomes more evenly distributed among individuals in more productive environments. An explicit representation of metabolic inequality can improve predictions of how microbial communities, and the processes they support, respond to environmental change.