Although natural sources of enzymes are limited to protein and RNA, some artificial DNAs exhibit catalytic activities. Representative functions of such DNAs, i.e. DNAzymes, are cleavage and ligation of nucleic acids. Here we developed a minimal DNAzyme with an RNA-cleaving activity by in vitro selection and secondary structure-based design. Its catalytic and substrate cores are only two and three nucleotides, respectively. This DNAzyme showed strict Zn2+ dependence at optimal pH 7.0–7.5. To elucidate its catalytic mechanism, we determined its three-dimensional structure by X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. The results consistently showed a B-DNA-like structure with base pairing and stacking throughout the molecule, unlike the kinked structures of larger DNAzymes. Notably, an A-base in the catalytic loop and a G-base in the substrate loop formed a non-Watson–Crick base pair. The catalytic Zn2+ coordinates to N7 of that G-base, enabling the Zn2+-hydrated water molecules to contacts O2′ and O5′ at the cleavage site. Considering that Zn(OH)+ and Zn2+ co-exist at the enzyme’s optimal pH, we propose a catalytic mechanism whereby these ions act as the base withdrawing H+ from O2′ and the acid donating H+ to O5′, generating the cleaved ends with 2′,3′-cyclic phosphate and OH groups.

Cas9 nucleases defend bacteria against invading DNA and can be used with single guide RNAs (sgRNAs) as antimicrobials and genome-editing tools. However, bacterial applications are limited by incomplete knowledge of Cas9–target interactions. Here, we generated large-scale Staphylococcus aureus Cas9 (SaCas9)/sgRNA activity datasets in bacteria and trained a machine learning model (crispr macHine trAnsfer Learning) to predict SaCas9 activity. Incorporating downstream sequences flanking the canonical NNGRRN protospacer adjacent motif (PAM) at positions [+1] and [+2] improved predictive performance, with T-rich dinucleotides at these positions correlating with higher in vivo activity. Crucially, SaCas9 showed 10-fold reduced activity at sites containing a 5-NNGGAT[C]-3 PAM [+1] sequence in pooled sgRNA experiments in E. coli and Citrobacter rodentium. Plasmid cleavage assays in DNA adenine methyltransferase (DAM)-deficient E. coli confirmed that adenine methylation at GATC motifs inhibited SaCas9 activity. Removal of a DAM site within a PAM sequence enhanced cleavage, while introduction of a site reduced activity, directly linking adenine methylation to SaCas9 activity. These findings demonstrate that machine learning can uncover biologically relevant determinants of Cas9 activity. Avoidance of methylated PAMs may reflect an evolutionary adaptation by SaCas9 to discriminate self from nonself or to counter methylation as a phage and plasmid antirestriction strategy.

Plants live in close association with microbial communities that support their health and growth. Previous research has indicated that the composition of these communities can differ between genotypes of the same plant species. Host-related factors causing this variation are mostly unknown. Microbiome genes, or M genes in short, are host genes that are involved in shaping the microbiome. We hypothesized that specific M genes are responsible for microbiome variation between rice genotypes and that it is connected to plant metabolites controlled by these genes. Our study was aimed at identifying plant metabolites driving genotype-specific microbiome assembly and establishing a link to host genetics. Targeted metabolite quantification was combined with microbiome profiling of the rice phyllosphere microbiome, association analyses on single-nucleotide polymorphism (SNP) level, and genetic modifications to validate microbiome-shaping effects of the discovered M genes. Targeted metabolite quantifications revealed that phenylpropanoid concentrations in rice leaves can substantially differ among 110 representative genotypes grown under the same, controlled conditions. Redundancy analyses (RDA) showed that these metabolites can explain 35.6% of the variance in their microbiomes. Further verification experiments resulted in the identification of two M genes. OsC4H2 and OsPAL06 are both plant genes with microbiome-shaping effects, mainly via their role in ferulic acid biosynthesis. Targeted gene mutation experiments confirm that distinct phyllosphere-associated bacterial groups are highly responsive to the discovered M genes. This study provides detailed insights into the links between host genetics and microbiome variation in plants. Knowledge about host genes that are in control of the microbiome paves the way for microbiome engineering and targeted plant breeding approaches. 

Uneven translation rates resulting from mRNA context, tRNA abundance, nascent amino acid sequence or various external factors play a key role in controlling the expression level and folding of the proteome. Inverse toeprinting coupled to next-generation sequencing (iTP-seq) is a scalable in vitro method for characterizing bacterial translation landscapes, complementary to ribosome profiling (Ribo-seq), a widely used method for determining transcriptome-wide protein synthesis rates in vivo. In iTP-seq, ribosome-protected mRNA fragments known as inverse toeprints are generated by using RNase R, a highly processive 3′ to 5′ RNA exonuclease. Deep sequencing of these fragments reveals the position of the leading ribosome on each mRNA with codon resolution, as well as the full upstream coding regions translated by these ribosomes. Consequently, the method requires no a priori knowledge of the translated sequences, enabling work with fully customizable transcript libraries rather than previously sequenced genomes. As a standardized framework for inverse toeprint generation, amplification and sequencing, iTP-seq can be used in combination with different types of libraries, in vitro translation conditions and data-analysis pipelines tailored to address a range of biological questions. Here, we present a robust protocol for iTP-seq and show how it can be integrated into a broader workflow to enable the study of context-dependent translation inhibitors, such as antibiotics. The time required to complete this workflow is ~10 d, and the workflow can be carried out by an experienced molecular biologist, with data analysis also requiring a working knowledge of command-line tools and Python scripts. This protocol describes inverse toeprinting coupled to next-generation sequencing, an in vitro approach to characterize bacterial translation at codon resolution that can accommodate custom synthetic libraries and various translation perturbations.

Emerging fungal pathogens have detrimental impacts on crops, animals, and humans. Despite the mounting threat of these emerging fungal pathogens, little is known about their transition from saprotrophic to pathogenic lifestyles. To gain insights into fungal lifestyle transitions, we study the Trichosporonales order, which includes both saprotrophic species and opportunistic human pathogens, as a system to reveal evolutionary adaptations leading to virulence in fungi. Here we use comparative genome analyses and experimental assays to demonstrate that the transition from saprotroph to opportunistic human pathogen is facilitated by adaptive translation. Codon optimization of metabolic genes grants these fungi the ability to quickly adapt to new environments. In this study, we link genomic data with fungal physiology, highlighting the role of adaptive translation in colonizing different environments and suggesting that gene translation optimization plays a critical role in fungal lifestyle evolution. Emerging fungal pathogens have detrimental impacts on crops, animals, and humans, however little is known about their transition to a pathogenic lifestyle. This study demonstrates that the transition from saprotroph to opportunistic human pathogen is likely facilitated by adaptive translation.

Nicotinamide adenine dinucleotide (NAD(H)) and its phosphorylated form NADP(H) are vitamin B3-derived redox cofactors essential for numerous metabolic reactions and protein modifications. Various health conditions are associated with disturbances in NAD+ homeostasis. To restore NAD levels, the main biosynthetic pathways have been targeted, with nicotinamide (Nam), nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN) being the most prominent boosters. However, while many preclinical studies have examined the effects of these precursors, a direct comparison in humans is lacking, and recent rodent research suggests that the NAD+-boosting effects of NR and NMN may depend on their microbial conversion to nicotinic acid (NA), a mechanism not yet confirmed in humans. Here we show in a randomized, open-label, placebo-controlled study in 65 healthy participants that 14 days of supplementation with NR and NMN, but not Nam, comparably increases circulatory NAD+ concentrations in healthy adults. Unlike the chronic effect, only Nam acutely and transiently affects the whole-blood NAD+ metabolome. Using ex vivo fermentation with human microbiota, we identify that NR and NMN give rise to NA and specifically enhance microbial growth and metabolism. We further demonstrate ex vivo in whole blood that NA is a potent NAD+ booster, while NMN, NR and Nam are not. Ultimately, we propose a gut-dependent model for the modes of action of the three NAD+ precursors with NR and NMN elevating circulatory NAD+ via the Preiss–Handler pathway, while rapidly absorbed Nam acutely affects NAD+ levels via the salvage pathway. Overall, these results indicate a dual effect of NR and NMN and their microbially produced metabolite NA: a sustained increase in systemic NAD+ levels and a potent modulator of gut health. ClinicalTrials.gov identifier: NCT05517122 . A comparison of the effects of different NAD+ boosters is lacking. This clinical study compares the efficacy of the NAD+ boosters NR, NMN and Nam in increasing circulating NAD+ levels and analyses their effects on gut microbial metabolism.

CRISPR-Cas-based live-cell imaging has rapidly become a central technology for studying genome dynamics with high specificity and flexibility. By coupling nuclease-deactivated Cas (dCas) with programmable guide RNAs, genomic loci can be tracked in living cells, providing direct insights into nuclear organization and chromatin behavior. While repetitive regions such as telomeres and centromeres are readily visualized, labeling non-repetitive loci remains more challenging due to weak signals and high background. Recent advances, including multicolor labeling strategies, innovative amplification systems based on dCas9 and single-guide RNA (sgRNA) engineering, and integration with novel fluorescent reporters, have markedly expanded the applicability of CRISPR imaging across the genome. These developments have expanded the multiplexing capacity of CRISPR imaging, improved signal-to-background ratios, and even enabled the visualization of non-repetitive genomic loci. Nonetheless, key challenges remain, including cellular toxicity, replication stress, and genomic instability associated with prolonged CRISPR expression. In this review, we summarize recent advances in CRISPR live-cell imaging and highlight key design trade-offs and biological constraints.

Biomolecular condensates are essential for cellular organization, yet their formation dynamics and molecular content exchange properties remain poorly understood. Here we show that flow cytometry provides a high-throughput, solution-based platform for analyzing condensate behavior at the single-droplet level. Using self-interacting NPM1 condensates as a model, we demonstrate that this approach quantifies phase behavior across protein and salt conditions, measures the partitioning of diverse macromolecules—including antibodies, lipids, small-molecule drugs, and RNA—and detects molecular colocalization with high statistical precision. Importantly, we establish a high-throughput assay to track real-time molecular exchange between preformed condensates and newly added, orthogonally tagged protein. These measurements reveal that condensate aging significantly reduces molecular dynamisms, likely due to altered biophysical properties with time. Compared to conventional imaging techniques that require surface immobilization or complex instrumentation, our method enables rapid, quantitative characterization of condensate dynamics and molecular content, providing a scalable framework for probing condensate function. He, Ongwae, and colleagues show that flow cytometry provides a high-throughput, solution-based platform for analysing the behavior of biomolecular condensates at the single-droplet level. Using this approach, the authors quantify condensate formation and track molecular exchange in real-time, and they reveal that condensate aging reduces molecular dynamisms.