We developed POC1-mediated versatile genome-editing platforms and demonstrated efficient NHEJ-driven indel formation, adenine and cytosine base editing, and prime editing in rice. Our results establish that the AI-designed nuclease OpenCRISPR-1, following codon optimization, is compatible with multiple genome-editing modalities and achieves performance comparable to that of the naturally occurring SpCas9 across diverse target loci in rice. Although the OC1 exhibited significantly reduced off-target editing compared to SpCas9 in human cells, its off-target activity in plant systems remains to be evaluated. Similarly, the performance of OC1 should be assessed across a broader range of monocot and dicot species to support its wider adoption as an alternative to SpCas9. The expanding repertoire of AI-designed effectors, including nucleases and deaminases, is poised to unlock new opportunities in eukaryotic genome engineering by overcoming intrinsic limitations of naturally evolved systems.

Lakes are expected to experience longer summer stratification and shorter winter mixing due to climate-induced warming. These changes will impact biogeochemical cycles, but how shifts in mixing might influence lake nitrogen removal via denitrification remains unconstrained. Here we used 15N-tracer assays, molecular techniques and flux measurements to establish the seasonal dynamics of denitrification in a eutrophic lake in Switzerland. We find that denitrification was disproportionately active during the winter mixed regime, potentially driven by a previously unrecognized chitinolytic–denitrifying microbial consortium. Moreover, denitrification was strongly governed by the relative availabilities of particulate organic carbon and nitrate. Leveraging these insights enabled accurate simulation of denitrification in a lake model, revealing that a worst-case climate scenario may shorten the mixing period by ~27 days and reduce denitrification by 8–13%, increasing nitrogen export to downstream ecosystems. We conclude that lake microbial denitrification, and its associated denitrifying consortium, will be weakened by climate change. Denitrification is an essential process for the removal of excess nitrogen in aquatic ecosystems, and models informed by lake samples suggest that seasonal stratification changes could weaken the microbial communities responsible for this process.

The concept of a methanol-based circular bioeconomy envisions the conversion of greenhouse gases into one-carbon compounds, which are subsequently utilized to produce high-value-added products. However, the toxicity of intermediates limits the metabolic efficiency within chassis strains. Here a carbon metabolism reconfiguration strategy combined with adaptive laboratory evolution was applied to engineer an artificial methylotrophic yeast by accelerating the flux of toxic intermediates into the central carbon metabolism. After modifying the key gene Sfa1 identified by adaptive laboratory evolution and introducing a light-responsive switch to dynamically redirect the carbon flux, the engineered strain not only restored its growth in minimal medium with 2% methanol, but also synthesized chondroitin sulfate A driven by the dark reaction. Furthermore, we designed a 3′-phosphoadenosine-5′-phosphosulfate supply strategy and energy adapter to increase the sulfonation level. This study illustrates the exciting potential of methylotrophic Saccharomyces cerevisiae as a platform for biosynthesis. A methanol-based circular bioeconomy envisions the conversion of greenhouse gases into one-carbon compounds, which are subsequently utilized to enable sustainable biomanufacturing. Here a carbon metabolism reconfiguration strategy combined with adaptive laboratory evolution is adopted to obtain methylotrophic Saccharomyces cerevisiae capable of producing chondroitin sulfate A.

Our understanding of how depolymerase sequence and structure determine substrate specificity is fragmentary due to the limited number of experimentally characterized enzymes. Here we show DepoCatalog - an experimentally validated collection of 129 recombinantly prepared Klebsiella phage depolymerases (90 enzymes produced in this study and 39 homologs from the literature), with specificity spanning 75 KL-types. Enzymes originated from podo-, sipho-, myo-, jumbo phages, and prophages. Using activity profiling, structural modeling, and domain dissection, we propose a five‑class framework that captures the architectural and functional diversity of these enzymes. DepoCatalog uncovers cross-reactivity and taxa‑specific enzymes. Structural comparisons indicate that specificity switching or extension is associated with modifications to the C‑terminal domain. We further hypothesize that podoviruses encoding up to two RBPs show greater receptor adaptability than jumbo phages with multiple specialized RBPs. Finally, we develop a publicly accessible, DepoCat dataset (https://depocat.uwr.edu.pl) for specificity, structural classification and comparison of newly identified depolymerases. Phages can use enzymes (depolymerases) that degrade capsular polysaccharides to initiate infection of their bacterial hosts. Here, the authors characterize a diverse set of 129 Klebsiella phage depolymerases, defining five enzyme classes, revealing cross-reactivity, and linking enzyme’s specificity to structure.

Programmable CRISPR-Cas9 nucleases have become invaluable tools for genome editing. However, off-target cleavage by these nucleases can lead to unintended changes in the edited genome. Detection of off-target sites is critical to make genome editing technology safe and predictable. Although current in vitro methods for off-target detection can identify these sites, they are time-consuming and complex. Here, we present CROFT-Seq (CRISPR nuclease off-target detection by sequencing), a sensitive, rapid, and affordable assay for the genome-wide detection of Cas9 off-target sites in vitro. CROFT-Seq performs comparably to the commonly used in vitro methods and serves as a valuable and efficient tool for the rapid assessment of genome-editing nuclease specificity. Notably, a high proportion of the top-ranked off-target sites identified by CROFT-Seq were validated in cells, highlighting its strong predictive performance.

Rice paddies are essential to global food security but are significant contributors to greenhouse gas (GHG) emissions, particularly methane (CH4), a potent driver of climate change. Here, using three independent approaches—a data-driven model, a process-based ecosystem model and a meta-analysis of over 1,255 field experiment sites—we estimate that net GHG emissions from global rice paddies approximately doubled from 1961–1980 to 2001–2020, driven primarily by a 52% increase in soil CO2 emissions and a 44% rise in soil CH4 emissions. For the most recent decade (2010s), global rice paddies emitted 1,090 ± 350 Tg of CO2-equivalent emissions (CO2e) per year, with an emission intensity of 0.33 ± 0.08 MgCO2e per million kilocalories. Rice area expansion was the largest contributor to net GHG increases, with secondary drivers being the widespread adoption of intensified residue incorporation. East Asia experienced renewed CH4 increases linked to excessive straw incorporation, while Africa emerged as an important CH4 hotspot because of rapid paddy expansion. Mitigation strategies such as reducing excessive residue and nitrogen inputs alongside the adoption of optimal tillage and irrigation could reduce future total net GHG emissions by ~10% without yield loss. However, achieving further reductions will require stronger climate-smart policy frameworks. Rice paddies are crucial for food security but are also a major source of greenhouse gas (GHG) emissions. This study found that net soil GHG emissions nearly doubled from 1961–1980 to 2001–2020, mainly due to soil carbon stock change-derived CO2-equivalent emissions and soil methane emissions, underscoring the need for climate-smart management.

Bacterial gene expression is thought to involve tightly coupled transcription, translation and mRNA degradation. However, recent work has indicated that this is not always the case, leaving the generality and regulation of this coordination unclear. Here we use genetic, kinetic and spatial analyses in E. coli to show that transcription–translation coupling requires high translational activity and that nearly half of the transcriptome exhibits signatures consistent with partial uncoupling. We find that co-transcriptional mRNA degradation is rare due to membrane localization of RNase E, except for transcripts encoding inner-membrane proteins. Our results show that translation efficiency determines the level of premature transcription termination, which in turn shapes mRNA degradation patterns and kinetics. Comparative analyses in Bacillus subtilis and Caulobacter crescentus also reveal species-specific coordination strategies. This challenges the universality of co-transcriptional coupling and defines how spatial and genetic features coordinate bacterial gene expression. RNase E localization and translation initiation coordinate transcription, translation and mRNA degradation during the life cycle of an mRNA, explaining gene- and species-specific variations in this coordination in bacteria.

Plants are able to acclimate to heat stress (HS) at the level of individual cells and the whole organism. With extreme temperature events becoming more frequent owing to climate change, it is critical to understand the molecular responses of plants to HS. In this Review, we discuss how plants sense and signal HS, and how this leads to dynamic transcriptional and cellular responses. Plants plastically integrate high temperature signals with other environmental and endogenous cues. Across eukaryotes, heat shock factor transcription factors orchestrate transcriptional responses to HS and are delicately regulated. Recent emerging evidence showed a close link between HS sensing and responses with the formation of biomolecular condensates, as well as the chromatin-based HS memory. Ultimately, this knowledge may be harnessed to secure crop yields. Plants adapt to heat stress through coordinated sensing and response mechanisms driven by heat shock factors. This Review discusses recent insights into heat shock factor regulation, transcriptional reprogramming, and heat stress epigenetic memory and crosstalk with hormone signalling pathways.

Optogenetics which involves the use of light to control cell functions on a genetic level has found utility in studying cell physiology, biomaterials and metabolic engineering. S. cerevisiae is an industrially relevant model organism that is used in many applications, but due to the large number of genes required and issues relating to cross-activation between different colors, optogenetics for different wavelengths of light have not been multiplexed in S. cerevisiae. In this paper, we develop a compact red light responsive optogenetic system for S. cerevisiae that requires only a single gene and no exogenous cofactors. Through engineering modular protein domains, we reduce the cross-activation of our system by blue light. We integrate our red light optogenetic system with EL222 blue light optogenetics to establish dual channel optogenetics in S. cerevisiae and demonstrate its utility for engineering biology through the light-based control of flavonoid luteolin synthesis and flocculation for ease of product extraction. We also demonstrate our system’s potential for the development of living materials by producing dual-coloured optogenetic patterns using S. cerevisiae. This work expands optogenetic applications in S. cerevisiae from single-light to multi-light systems, introducing the potential to multiplex different colours of light for dynamic, orthogonal control of separate cell processes. Optogenetics has found utility in studying cell physiology, biomaterials and metabolic engineering. Here the authors integrate red and blue light optogenetic systems for dual-channel control of S. cerevisiae, demonstrating light-based control of luteolin synthesis and flocculation.