Chemical innovation is essential for fungi to adapt to ever-changing ecological environments. However, the environmental and evolutionary drivers of fungal metabolic differentiation remain ambiguous. Here, we show the phylogeographic diversity of 1052 Aspergillus flavus strains across four continents, as conducted through phylogenetic and biogeographical analysis, including 544 newly sequenced strains from China. These strains exhibit varying levels of population-specific mycotoxin production, as determined by population metabolomics analysis. We report a toxigenic subpopulation from China, identified through comparative population genomics analysis. Pan-metabolome analysis reveals strong phylogeographic metabolic patterns associated with specific ecological niches. Low-mycotoxin production clades harbor distinct uncharacterized biosynthetic gene clusters and produce different specialized metabolites instead. This discrepancy is only partially explained by variation in biosynthetic pathway genes, and changes in regulation and primary metabolism appear to mainly drive differentiation of specialized metabolite profiles across fungal populations, as indicated by pangenome profiling, metabolites-genome-wide association study, genotype-environment association study, pan-transcriptome analysis, and gene knockout experiments. Altogether, our results reveal how environmental shifts drive the fungal metabolic evolution, and provide insights for predicting the risk of harmful fungal outbreaks and for biogeographically-informed, precise control measures. Drivers of fungal metabolic diversity are incompletely understood. Here, the authors conduct a global genomics study of over 1,000 pathogenic fungi to show that geography shapes the metabolic diversity in Aspergillus flavus revealing how climate drives fungal chemical adaptive evolution.

Diverse phage-bacteria communities coexist at high densities in environmental, agricultural, and human-associated microbiomes. Phage-bacteria coexistence is often attributed to coevolutionary processes mediated by complex, pairwise infection networks. Here, using in vitro experiments and mathematical models, we explore how higher-order interactions function as a complementary, ecological feedback mechanism to stabilize phage-bacteria communities. To do so, we examine an environmentally-derived, synthetic phage-bacteria community comprised of five marine heterotrophic bacteria (Cellulophaga baltica and Pseudoalteromonas strains) and five associated phage. We used Bayesian inference to reconstruct free phage production in one-step growth experiments and then forecasted pairwise phage-bacteria community dynamics over multiple infection cycles. In contrast to model predictions of rapid bacterial population collapse, each bacterial strain persisted in the community. We hypothesized and then experimentally validated the relevance of infection attenuation at relatively high viral densities. We extended models into a community context, corroborating complex coexistence of all phage and bacteria. Life history traits inferred in community fits often differed from those inferred in a pairwise context, implicating higher-order interactions as an additional, ecological stabilization mechanism. Follow-up experiments confirm that phage traits (including burst size) can shift when infecting single vs. multiple strains. More broadly, these findings suggest that complex community coexistence of phage and bacteria may be more common than anticipated when including feedback mechanisms outside of the growth-dominated regimes of fitted pairwise models that do not reflect the full scope of ecologically relevant contexts.

Type III CRISPR–Cas systems confer antiviral immunity via cyclic oligoadenylate (cOA) signaling. Here, we elucidate a cooperative bacterial defense strategy involving two cOA-activated CRISPR-associated Rossmann fold (CARF)-containing effectors, adenosine deaminase CAAD and ribonuclease Csx1, in Thermoanaerobaculum aquaticum. Genomic analyses indicate widespread co-occurrence of CRISPR-associated adenosine deaminase (CAAD) with ancillary CARF-containing effectors in type III CRISPR systems, suggesting that multiple CARF-containing proteins may contribute to a coordinated cOA-dependent defense. Biochemical and structural studies reveal the intrinsic dynamics of CAAD hexamer, and demonstrate that cA4/cA6 binding stabilizes CAAD hexamers, triggering metal-ion-dependent conversion of ATP into inosine triphosphate. Concurrently, the downstream Csx1 is exclusively activated by cA4 to cleave single-stranded RNA. Strikingly, we found that both effectors are capable of degrading cA4, suggesting that this CAAD–Csx1 pair may be cross-regulated and achieve immunity through a dual-targeting mechanism: in response to infection, Csx1 degrades viral RNA while CAAD disrupts nucleotide metabolism via ATP deamination, which can be relieved via cA4 degradation when infection has been eliminated. This study proposes an enhanced defense mechanism through coordinated activation and regulation of multiple CRISPR effectors by a single signaling molecule, unveiling unprecedented complexity in CRISPR immunoregulation.

The social behaviors of microbes provide unique opportunities for testing social evolution theories. How can altruistic behaviors arise by natural selection is a central challenge in biology. Green-beard effect has been proposed as a basic mechanism for the evolution of altruistic behaviors. Yet, green-beard genes are generally thought to be rare. Here, we find that the Schizosaccharomyces pombe gsf2 gene mediates flocculation-like aggregation, and flocculation is triggered by acid stresses. gsf2-expressing cells preferentially adhere to each other. The expression of gsf2 is costly, but gsf2-expressing cells preferentially adhere to each other and protect each other from external stress. Gsf2 is highly variable in natural populations, likely contributing to different flocculation intensity. These findings suggest that gsf2 is a gradient green-beard gene that drives the altruism among gsf2 carriers. Moreover, we find that gsf2 is a new gene that originated very recently. Our results provide insights into the origin and evolution of green-beard genes.

Gene regulation through promoter engineering is a cornerstone of synthetic biology, enabling precise control over transcriptional networks. However, experimental approaches remain labor-intensive. While artificial neural networks (ANNs) have improved regulatory element prediction, tools for promoter–transcription factor binding site (TFBS) recombination are still lacking. We present an ANN framework for context-aware design of synthetic promoters in Saccharomyces cerevisiae. The model predicts optimal TFBS insertion sites and the extent of promoter rewriting needed for successful integration. Applying this, we screened 6,011 native yeast promoters for compatibility with the TetR TFBS, generating a ranked list of high-confidence promoter–TFBS pairs. Experimental validation showed that model-designed promoters achieved repression rates up to 98.4%, without prior experimental characterization or tuning. We further rewired the yeast transcriptional network by introducing glucose-dependent regulation of an essential gene via Mig1 TFBS insertion. These results establish a scalable, predictive method for engineering regulatory sequences and reprogramming transcriptional logic.

Plasmids are the workhorses of molecular biology: fast, flexible, and often taken for granted. We clone, overexpress, tag, and mutate freely, assuming they will faithfully produce RNA transcripts that match the intended DNA sequence. This assumption is rarely tested and often invalidated. Sequences in plasmid backbones, epitope tags, and codon-optimized regions may inadvertently harbor cryptic promoters or splice sites. The resulting unexpected transcripts and proteins, while often undetected, can distort results and propagate false conclusions through papers, grants, and even clinical trials. In this perspective, we highlight published cases where plasmids have distorted results and misled interpretation. We examine the mechanisms and consequences of plasmid-associated expression artifacts and offer practical strategies to minimize them. Finally, we call for a revision of community standards for experiments using transgenes: deposit complete plasmid sequences and verify the resulting transcripts using RNA-seq.