Simple Genomic Traits Predict Rates of Polysaccharide Biodegradation

Natural and chemically modified polysaccharides are extensively employed across a wide array of industries, leading to their prevalence in the waste streams of industrialized societies. With projected increasing demand, a pressing challenge is to swiftly assess and predict their biodegradability to inform the development of new sustainable materials. In this study, we developed a scalable method to evaluate polysaccharide breakdown by measuring microbial growth and analyzing microbial genomes. Our approach, applied to polysaccharides with various structures, correlates strongly with well-established regulatory methods based on oxygen demand. We show that modifications to the polysaccharide structure decreased degradability and favored the growth of microbes adapted to break down chemically modified sugars. More broadly, we discovered two main types of microbial communities associated with different polysaccharide structuresone dominated by fast-growing microbes and another by specialized degraders. Surprisingly, we were able to predict biodegradation rates based only on two genomic features that define these communities: the abundance of genes related to rRNA (indicating fast growth) and the abundance of glycoside hydrolases (enzymes that break down polysaccharides), which together predict nearly 70% of the variation in polysaccharide breakdown. This suggests a trade-off, whereby microbes are either adapted for fast growth or for degrading complex polysaccharide chains, but not both. Finally, we observe that viral elements (prophages) encoded in the genomes of degrading microbes are induced in easily degradable polysaccharides, leading to complex dynamics in biomass accumulation during degradation. In summary, our work provides a practical approach for efficiently assessing polymer degradability and offers genomic insights into how microbes break down polysaccharides.