The evolutionary competition within phage–host systems led to the emergence of CRISPR–Cas defence mechanisms in bacteria and anti-CRISPR elements in bacteriophages. Although anti-CRISPR elements are well characterized, the role of bacterial factors that influence CRISPR–Cas efficacy has been comparatively overlooked. Type V CRISPR–Cas12 systems display striking functional and mechanistic diversity for nucleic acid targeting. Here we use a bioinformatic approach to identify Cas12p, a phage-associated nuclease that forms complexes with the bacterial thioredoxin protein TrxA to enable target DNA degradation. This represents an unexpected phage–bacteria interaction, in which the bacteriophage co-opts a bacterial factor to augment its own genome degradation machinery, potentially against competing phages. Biochemical characterization, cryo-EM-based structural analysis of the Cas12p–TrxA–sgRNA–dsDNA complex at 2.67 Å and bacterial defence assays reveal that TrxA directly binds and activates Cas12p, enabling its nuclease activity and subsequent CRISPR immunity. These findings expand our understanding of the multilayered intricacies of phage–bacteria molecular interactions. In an unexpected interaction, infecting phages co-opt a bacterial protein to potentially facilitate genome degradation of competing phages.

Small molecules can bind RNAs to regulate their fate and functions, providing promising opportunities for treating human diseases. However, current tools for predicting small molecule–RNA interactions (SRIs) require prior knowledge of RNA tertiary structures. Here we present SMRTnet, a deep learning method that uses multimodal data fusion to integrate two large language models with convolutional and graph attention networks to predict SRIs on the basis of RNA secondary structure. SMRTnet achieves high performance across multiple experimental benchmarks, substantially outperforming existing tools. SMRTnet predictions for ten disease-associated RNA targets identified 40 hits of RNA-targeting small molecules with nanomolar-to-micromolar dissociation constants. Focusing on the MYC internal ribosome entry site, SMRTnet-predicted small molecules showed binding scores correlated closely with observed validation rates. One predicted small molecule downregulated MYC expression, inhibited proliferation and promoted apoptosis in three cancer cell lines. Thus, by eliminating the need for RNA tertiary structures, SMRTnet expands the scope of feasible RNA targets and accelerates the discovery of RNA-targeting therapeutics. SMRTnet predicts compounds that bind to disease-associated RNA targets.

Detection of the off-target effects of base editors is important for identifying their safety risks but current methods for understanding their global activities have limitations in terms of sensitivity or bias by computationally selecting a subset of sites for experimental analysis. We present CHANGE-seq-BE, a method to assess the guide RNA-dependent off-target profile of both adenine and cytosine base editors that is simultaneously sensitive and unbiased. CHANGE-seq-BE relies on selective sequencing of base-editor-modified genomic DNA in vitro and provides comprehensive identification of genome-wide off-target mutations. We found that 98.8% of validated off-target sites were unique to ABE8e adenine base editors compared to Cas9 nuclease, suggesting substantially higher off-target activity of the former. We further applied CHANGE-seq-BE to support genotoxicity studies in an emergency investigational new drug application for customized adenine base editor treatment for a person with CD40L-deficient X-linked hyper IgM syndrome. Our results emphasize the importance of using a base-editor-specific method for identifying off-target activity. Base editor off-target effects are profiled with high precision in a tailored approach.

Generating biomaterials with controlled structure, morphology and physicochemical properties is a key enabler of modern bioengineering, with applications in areas ranging from tissue engineering to drug delivery. In this context, microgels — hydrogel particles with characteristic dimensions in the micrometre range — have become a foundational, modular and versatile platform for building biomaterials. Their design can be tailored across multiple length scales, integrating a range of scientific and engineering principles. In this Review, we focus on the power of droplet microfluidics to make materials drop by drop, and how this allows us to control and tailor the properties of microgels. We outline the basic principles of droplet microfluidics-enabled microgel fabrication and explore microfluidic strategies for the production of microgels and modulation of their physicochemical properties, extending beyond simple isotropic designs. We then review their applications, distinguishing between single microgels and their assemblies. We highlight how microgel features, such as size, porosity and modularity, enable unique opportunities in analytical chemistry, cell culture and drug delivery applications. Collective assemblies of microgels into jammed scaffolds are also discussed in the context of tissue engineering and biofabrication. Finally, we discuss current limitations in microgel fabrication and characterization, and outline emerging directions for future research in the field. Droplet microfluidics enables the precise fabrication of microgels, which are microscale hydrogel particles that serve as modular building blocks for biomaterials. This Review outlines principles of microfluidic microgel production, strategies for tailoring structure and functionality, and applications spanning drug delivery, cell culture and tissue engineering, while highlighting current challenges and future directions.

Biological nitrogen fixation through foliar application of nitrogen-fixing bacteria presents a promising route to reduce reliance on synthetic fertilizers but remains limited by challenges in bacterial adhesion and survival in the phyllosphere. We developed a nanocoated inoculant encapsulating Klebsiella variicola W12 using metal–phenolic networks and sodium alginate for enhanced nitrogen fixation under nitrogen-depleted conditions. The nanocoating improved bacterial resistance to UV radiation, oxidative stress, aerobic conditions and desiccation, enhancing adhesion and biofilm formation on leaf surfaces. Colonization increased 3.3-fold compared to non-coated bacteria at 14 days after application, improving epiphytic and endophytic persistence. The nanocoated bacteria contributed 27.89% of total plant nitrogen, over twice that of non-coated bacteria, resulting in a 1.4-fold increase in rice fresh weight after 54 days. Field trials demonstrated potential savings of chemical fertilizer of 74.38 kg N ha−1, highlighting a sustainable and effective strategy to improve crop productivity with reduced reliance on chemical nitrogen fertilizers and environmental impacts. Nitrogen-fixing bacteria offer a promising route to reduce reliance on synthetic fertilizers, but their effectiveness is hindered by environmental stresses that limit survival on leaf surfaces. This study introduces a nanocoating strategy that enables robust foliar colonization of Klebsiella variicola, enhancing nitrogen fixation and improving rice yield under low-fertilizer conditions.

Assessing the accuracy of long-read assemblies, especially from complex environmental metagenomes that include underrepresented organisms, is challenging. Here we benchmark four state-of-the-art long-read assembly software programs, HiCanu, hifiasm-meta, metaFlye and metaMDBG, on 21 PacBio HiFi metagenomes spanning mock communities, gut microbiomes and ocean samples. By quantifying read clipping events, in which long reads are systematically split during mapping to maximize the agreement with assembled contigs, we identify where assemblies diverge from their source reads. Our analyses reveal that long-read metagenome assemblies can include >40 errors per 100 million base pairs of assembled contigs, including multi-domain chimeras, prematurely circularized sequences, haplotyping errors, excessive repeats and phantom sequences. We provide an open-source tool and a reproducible workflow for rigorous evaluation of assembly errors, charting a path toward more reliable genome recovery from long-read metagenomes. Long-read sequence assemblies from metagenomes contain frequent errors.

Rewriting RNA information to alter function requires controllable tools to edit RNA sequences within a user-defined region. Here we report a single-strand deaminase-assisted platform for adjustable RNA information manipulation (AIM). AIM is composed of a loop-forming guide RNA bound to an RNA-targeting Cas protein and an evolved TadA. AIM induces a loop, flanked by paired regions, in the target RNA; the loop size can be adjusted to allow conversions of single and multiple bases. We evolve TadA to achieve A-to-I, C-to-U or simultaneous A+C editing in coding and noncoding regions. We apply AIM to suppress the ochre nonsense codon (UAA) in disease-relevant cell and animal models, in which the two As must be simultaneously edited to rewrite the coding information. Moreover, we use AIM to manipulate adjacent phosphorylation sites important for protein function. Collectively, AIM is a versatile platform for manipulating RNA information within user-defined regions, opening additional avenues for functional RNA modulation. A single-strand deaminase-assisted platform simultaneously rewrites multiple bases within a single RNA transcript.

The root nodule symbiosis of plants with nitrogen-fixing bacteria is phylogenetically restricted to a single clade of flowering plants, which calls for as yet unidentified trait acquisitions and genetic changes in the last common ancestor. Here we discovered—within the promoter of the transcription factor gene Nodule Inception (NIN)—a cis-regulatory element (PACE), exclusively present in members of this clade. PACE was essential for restoring infection threads in nin mutants of the legume Lotus japonicus. PACE sequence variants from root nodule symbiosis-competent species appeared functionally equivalent. Evolutionary loss or mutation of PACE is associated with loss of this symbiosis. During the early stages of nodule development, PACE dictates gene expression in a spatially restricted domain containing cortical cells carrying infection threads. Consistent with its expression domain, PACE-driven NIN expression restored the formation of cortical infection threads, also when engineered into the NIN promoter of tomato. Our data pinpoint PACE as a key evolutionary invention that connected NIN to a pre-existing symbiosis signal transduction cascade that governs the intracellular accommodation of arbuscular mycorrhiza fungi and is conserved throughout land plants. This connection enabled bacterial uptake into plant cells via intracellular support structures such as infection threads, a unique and unifying feature of this symbiosis. A key step in the evolution of the nitrogen-fixing root nodule symbiosis, occurring 100 million years ago, subjected the control of Nodule Inception (NIN) gene expression to a protein complex that regulated transcription much earlier in the arbuscular mycorrhiza symbiosis.

Different definitions of keystone taxa and functions agree that they have an outsized role in maintaining community composition, and thus, the keystone concept continues to attract attention even 50 years after its introduction. In this Perspective, we base our definition of microbial keystones on the original one to explore its implications and limitations. We review different mechanisms behind keystoneness, cover the strengths and weaknesses of current keystone prediction methods and present findings on keystones discovered in recent experiments. In addition, we suggest a new prediction method for keystones based on metabolic modelling. Finally, we discuss the role of keystones in community control strategies. Overall, the development of new prediction methods and the insights from recent experiments illustrate the continued relevance of the keystone concept for microbial communities. In this Perspective, Garza et al. revisit the keystone concept and discuss its relevance for microbial keystone taxa and functions. For this, they explore the different mechanisms behind keystoneness, cover the strengths and weaknesses of current keystone prediction methods, present recent findings on keystone taxa and functions and explore the role of keystones in community control.