Microplastics and nanoplastics pollution (MNPP) is a major environmental issue due to its small size, long-lasting nature, and potentially harmful impacts on ecosystems and human health. Plastics can be degraded in nature by physical, chemical, and biological processes. Plastic biodegradation is a potential sustainable solution to MNPP, but understanding the fitness of potential plastic-degrading proteins (PPDPs) across environments requires comparative resources. Here, we introduce the Plastic-Degrading Clusters of Orthologous Groups (PDCOGs) database, available at https://phylobone.com/microworld/PDCOG  The resource includes 625,616 PPDPs from free-living prokaryotes classified in 51 PDCOGs. The PDCOG database is a robust resource that improves understanding of plastic biodegradation and supports research on global MNPP challenges. Overall, PDPPs represent 3.5% of proteins in prokaryotes and are widely distributed across the Earth, spanning across most prokaryotic species and environments. Nearly all prokaryotic species (>95%) have the potential to biodegrade at least one polymer type.

Steel corrosion is an extensive problem worldwide, substantially impacting marine infrastructures. In this study, the influence of steel on bacterial succession and corrosion was investigated by culturing marine water samples with and without steel coupons for 14 days. Compared to abiotic controls, oxygen levels were rapidly depleted in biotic cultures. Fe levels increased in controls compared to biotic cultures, potentially due to anoxic conditions and the incorporation of Fe in the biofilm. Proteobacteria dominated the initial cultures, but over 14 days the number of phylogenetic groups decreased overall in abundance. Taxons that increased in abundance included Clostridiaceae, Fusobacteriaceae, Flavobacteriaceae and Prolixibacteraceae, some members of which can utilize Fe. While initially in low abundance, Arcobacteraceae, Pseudoalteromonadaceae, Rhodobacteraceae and Rhizobiaceae numbers increased over time. Sites 1 and 2 cultures displayed localised deep pitting corrosion on coupon surfaces, consistent with microbial action, with an increase in Bacteroidetes, suggesting this phylum facilitates corrosion. In contrast, Site 3 cultures displayed uniform, superficial corrosion, with Clostridiaceae being the dominating family by Day 14, suggesting corrosion inhibition through biofilm formation. By identifying bacteria associated with corrosion, targeted approaches to corrosion reduction may be developed through identifying significant metabolic pathways by transcriptomics and the application of metabolic inhibitors.

Bacterial transcription initiation is a tightly regulated process that canonically relies on sequence-specific promoter recognition by dedicated sigma (σ) factors, leading to functional DNA engagement by RNA polymerase (RNAP). Although the seven σ factors in E. coli have been extensively characterized, Bacteroidetes species encode dozens of specialized, extracytoplasmic function σ factors (σE) whose precise roles are unknown, pointing to additional layers of regulatory potential. Here we uncover an unprecedented mechanism of RNA-guided gene activation involving the coordinated action of σE factor in complex with nuclease-dead Cas12f (dCas12f). We screened a large set of genetically-linked dCas12f and σE homologs in E. coli using RIP-seq and ChIP-seq experiments, revealing systems that exhibited robust guide RNA enrichment and DNA target binding with a minimal 5ʹ-G target-adjacent motif (TAM). Recruitment of σE was dependent on dCas12f and guide RNA (gRNA), suggesting direct protein-protein interactions, and co-expression experiments demonstrated that the dCas12f-gRNA-σE ternary complex was competent for programmable recruitment of the RNAP holoenzyme. Remarkably, dCas12f-RNA-σE complexes drove potent gene expression in the absence of any requisite promoter motifs, with de novo transcription start sites defined exclusively by the relative distance from the dCas12f-mediated R-loop. Our findings highlight a new paradigm of RNA-guided transcription (RGT) that embodies natural features reminiscent of CRISPRa technology developed by humans.

Cis-regulatory elements (CREs), such as enhancers and promoters, control gene expression by binding regulatory proteins. In contrast to their bacterial counterparts, eukaryotic CREs typically bind transcription factors with short recognition motifs across multiple functional yet often weak binding sites. The evolutionary origin of this genetic architecture remains unclear. Here we study adaptive evolution of entire CREs under selection for controllable gene expression. In a biophysical toy model that recapitulates the essential nonlinearities of eukaryotic regulation, a regulatory phenotype requires a gene to be active when its CRE binds cognate TFs, yet inactive in the presence of noncognate TFs that can cause deleterious crosstalk. We explore CRE evolutionary outcomes utilizing "optimize-to-adapt" approach suggested by the theory presented in a companion paper. In this approach, CRE evolution is simulated explicitly at the sequence level, while the parameters of the biophysical model itself -- i.e., the properties of the replicated genotype-phenotype map -- are numerically optimized for CRE evolvability. In the optimal regime, selection navigates the tradeoff between slowly evolving strong and long binding sites (which guarantee low crosstalk), and rapidly evolving multiple short and weak binding sites (which necessitate diffuse selection against excessive noncognate binding across the entire CRE). When we further explore various scenarios for cooperative regulation, we find that the optimal regime predicts a diversity of strong and weak, yet always short, binding sites and favors "synergistic activation" of transcription, as reported empirically for eukaryotes. These results showcase how information theory can link evolutionary dynamics with biophysical constraints to rationalize -- and possibly even predict -- optimal regulatory architectures.