Biochemical reactions underlie all living processes. Like many systems, their web of interactions is difficult to fully capture and quantify with simple mathematical objects. Nonetheless, a huge volume of research has suggested many real-world systems–including biochemical systems–can be described simply as ‘scale-free’ networks, characterized by power-law degree distributions. More recently, rigorous statistical analyses upended this view, suggesting truly scalefree networks may be rare. We provide a first application of these newer methods across two distinct levels of biological organization: analyzing an ensemble of biochemical reaction networks generated from 785 ecosystem-level metagenomes and 1082 individual-level genomes (representing all domains of life). Our results confirm only a few percent of biochemical networks meet the criteria necessary to be more than super-weakly scale-free. We perform distinguishability tests across individual and ecosystem-level biochemical networks and find there is no sharp transition in the organization of biochemistry across distinct levels of the biological hierarchy–a result that holds across network projections. This suggests the existence of common organizing principles operating across different levels of biology, which can best be elucidated by analyzing all possible coarse-grained projections of biochemistry in tandem across scales.

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