The large-scale global use of plastics has led to one of the greatest environmental issues of the 21st century. The incredible durability of these polymers, whilst beneficial for a wide range of purposes, makes them hard to break down. True recycling of plastics is difficult and expensive, leading to accumulation in the environment as waste. Recently, a new field of research has developed, aiming to use natural biological processes to solve this man-made problem. Incredibly, some microorganisms are able to produce enzymes with the capacity to chemically break down plastic polymers into their monomeric building blocks. At an industrial scale, this process could allow for a circular recycling economy, whereby plastics are broken down, then built back up into novel consumer plastics. As well as providing a solution for the removal of plastics from the environment, this would also eliminate the need for the creation of virgin plastics. Analytical techniques, such as those allowing quantification of depolymerisation activity and enzyme characterization, have underpinned this field and created a strong foundation for this nascent inter-disciplinary field. Recent advances in cutting-edge ‘omics approaches such as DNA and RNA sequencing, combined with machine learning strategies, provide in-depth analysis of genomic systems involved in degradation. In particular, this can provide understanding of the specific protein sequence of the enzymes involved in the process, as well as insights into the functional and mechanistic role of the enzymes within these microorganisms, allowing for potential high-throughput discovery and subsequent exploitation of novel depolymerases. Together, these cross-disciplinary analytical techniques offer a complete pipeline for the identification, validation, and upscaling of potential enzymatic solutions for industrial deployment. In this review, we provide a summary of the research within the field to date, the analytical techniques most commonly applied for enzyme discovery and industrial upscaling, and provide recommendations for a standardised approach to allow research conducted in this field to be benchmarked to ensure focus is on the discovery and characterisation of industrially relevant enzymes.

Mutation rates vary both within and between bacterial species, and understanding what drives this variation is essential for understanding the evolutionary dynamics of bacterial populations. In this study, we investigate two factors that are predicted to influence the mutation rate: ecology and genome size. We conducted mutation accumulation experiments on eight strains of the emerging zoonotic pathogen Streptococcus suis. Natural variation within this species allows us to compare tonsil carriage and invasive disease isolates, from both more and less pathogenic populations, with a wide range of genome sizes. We find that invasive disease isolates have repeatedly evolved mutation rates that are higher than those of closely related carriage isolates, regardless of variation in genome size. Independent of this variation in overall rate, we also observe a stronger bias towards G/C to A/T mutations in isolates from more pathogenic populations, whose genomes tend to be smaller and more AT-rich. Our results suggest that ecology is a stronger correlate of mutation rate than genome size over these timescales, and that transitions to invasive disease are consistently accompanied by rapid increases in mutation rate. These results shed light on the impact that ecology can have on the adaptive potential of bacterial pathogens.

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While mutation is often deleterious, it can also be adaptive. Mutation rates are therefore subject to a trade-off, and this might vary with both ecology and genome size. As bacterial pathogens must survive in challenging environments and often undergo genome reduction, both factors might lead them to evolve higher mutation rates. To investigate these predictions, we conducted mutation accumulation experiments on eight strains of the emerging zoonotic pathogen Streptococcus suis. Natural variation within this species allows us to compare tonsil carriage and invasive disease isolates, from both more and less pathogenic populations, with a wide range of genome sizes. We find that invasive disease isolates have repeatedly evolved mutation rates that are higher than those of closely related carriage isolates, regardless of variation in genome size. Independent of this variation in overall rate, we also observe a stronger bias towards G/C to A/T mutations in isolates from more pathogenic populations, whose genomes tend to be smaller and more AT-rich. Our results suggest that ecology is a stronger correlate of mutation rate than genome size over these timescales, and that transitions to invasive disease are consistently accompanied by rapid increases in mutation rate. These results shed light on the impact of ecology on the adaptive potential of bacterial pathogens.