Metagenomic binning is essential for reconstructing prokaryotic genomes from metagenomic samples. We benchmarked various binning tools using Critical Assessment of Metagenome Interpretation (CAMI)-simulated, custom-simulated, and real metagenomic datasets, primarily focusing on short-read sequencing data. Our analysis highlights critical factors influencing binning efficacy: (i) Sequencing depth and taxonomic complexity strongly impact binning performance, while CAMI-simulated benchmarking datasets exhibit substantially lower complexity than human gut and environmental metagenomes, (ii) Chimeric genome rates vary widely across tools, (iii) Multi-sample binning is most effective with about 20 samples, as using too few or too many samples can reduce its benefits, and (iv) Binning efficacy was lower for single-end sequencing samples due to reduced contig quality and assembly fragmentation. Neural network-based tools consistently outperformed others in genome recovery from both real samples and simulated samples with realistic taxonomic complexity, though at higher computational cost. By integrating and refining genome bins from the top three binning tools, we recovered >30% more high-quality genomes than previous methods. This study provides practical guidance for improving metagenomic binning to facilitate the reconstruction of prokaryotic genomes. Benchmarking metagenomic binning tools with simulated and real datasets reveals factors affecting genome recovery and provides practical guidelines for improving metagenome assembled genome reconstruction.

The gut microbiome governs aspects of human growth and development. While human milk's primary purpose is metabolism, it also provides nonnutritious biologics and macromolecules. This mixture includes the human milk oligosaccharides (HMOs), which are indigestible and survive the low pH of the stomach and small intestine, reaching the large intestine intact. Here, HMOs serve as prebiotics for beneficial bacteria, providing a competitive growth advantage over potential pathogens. Upon metabolizing HMOs, commensals generate short-chain fatty acids and metabolites that enhance the gut community. Therefore, HMOs work to develop and sustain the gut microbial community as a living therapeutic that prevents illness from potential microbial pathogens and modulates development of the infant gut. The goal of this targeted review is to characterize the roles HMOs play in governing bacterial and viral members of the infant gut microbiome, describing how HMOs both define a healthy microbiota and prevent microbial dysbiosis.

Solar-driven biosynthesis from carbon dioxide can facilitate sustainable chemical manufacturing. However, cell-density limits and contamination susceptibility have seriously hampered its practical implementation. Here we develop a solar–chemical hybrid-driven biosynthesis (SCHB) strategy integrating wastewater-based phosphorus recovery into biological photosynthetic metabolism for chemical production. Specifically, we incorporate the phosphite oxidation pathway into cyanobacteria to supplement additional electrons to stimulate bacterial growth. This strategy conferred contamination resistance and enabled the utilization of phosphite-rich wastewater. A series of chemicals including raspberry ketone, indigo and its derivatives were effectively synthesized via SCHB, and the synthesis efficiency was promoted by a factor of up to 305%. Furthermore, the scalability of SCHB was demonstrated at the 500-litre level with real wastewater, which synchronized chemical production with nutrient recovery. Life-cycle assessment and techno-economic analysis indicated notable environmental benefits and economic feasibility. This study potentially opens a viable approach for the sustainable biosynthesis of chemicals. Bio-photosynthesis has the potential to achieve sustainable chemical production, but technical challenges remain. This work proposes a solar–chemical hybrid-driven biosynthesis strategy to achieve efficient chemical production from wastewater and carbon dioxide.

The gut microbiota contributes to cholesterol homeostasis by converting cholesterol into coprostanol, a non-absorbable sterol excreted in the feces. However, the enzymes mediating this process remain poorly defined. Here, we identify spiR, a steroid Δ5-4 isomerase/3-keto reductase from Eubacterium coprostanoligenes that catalyzes the initial oxidation of cholesterol to cholestenone, a requisite step in coprostanol production. We confirm that SpiR oxidizes both cholesterol and pregnenolone, and stereospecifically reduces 3-keto-steroids to 3β-hydroxylated forms. We show that SpiR preferentially binds to cholesterol over related steroids and functions as an NAD(H)-dependent homodimer. Through phylogenetic analysis, we show that spiR clusters with known Δ5-4 isomerases and is restricted to an uncultured clade within Acutalibacteraceae, where it frequently co-occurs with species encoding ismA, a gene previously implicated in cholesterol conversion. We analyze a multi-omic dataset from three human cohorts and find that spiR homologs were strongly enriched in individuals exhibiting cholesterol conversion. We also show that spiR homologs have a greater predictive power for cholesterol conversion than ismA homologs, establishing them as superior markers of microbial cholesterol metabolism. Our findings refine the enzymatic model of cholesterol metabolism in the gut and establish spiR as a critical biomarker and mechanistic driver for microbiome-mediated cholesterol reduction. Here, the authors identify SpiR, a gut bacterial enzyme that converts cholesterol, exclusively in a clade of uncultured gut bacteria, and show it is a superior predictor of microbial cholesterol metabolism in humans.

Group I introns are catalytic RNAs capable of self-splicing and generating circular RNAs, processes central to RNA metabolism and biotechnology. Yet, full-length ribozyme structures containing entire exon sequences and the structural basis of postsplicing circularization have remained limited. Using cryo-electron microscopy, we resolved multiple conformational states of the full-length Anabaena tRNA(Leu) precursor, capturing key intermediates of splicing and cyclization. In the apo state, the exons preassemble into a mature tRNA-like conformation that promotes P1 helix formation. Transitions through the splicing states involve substantial rearrangements essential for catalysis. Unlike other group I introns, the Anabaena intron circularizes without sequence loss, using its guanosine-binding site as the catalytic center. Mutational analyses confirm that G37 reorientation and a conserved wobble receptor motif precisely position the circularization site, driving efficient cyclization even in engineered PIE systems. These findings uncover unique mechanisms of RNA catalysis and establish structure-based optimization for advancing RNA circularization technologies. This study reveals how a group I intron from an Anabaena pre-tRNA undergoes structural changes to splice RNA and form circular RNA. The structures define key catalytic steps and offer a blueprint for engineering more efficient circular RNA systems.

Our double-stranded DNA (dsDNA) genomes are famously compacted by proteins in the nuclei of our cells, resulting in meters of dsDNA being confined in micron-sized volumes. The most prevalent form of viral genomes, however, is single-stranded RNA (ssRNA), which is compacted at significantly higher density in protective protein shells with nanometer dimensions. In this review, we discuss the special nature of ssRNA that allows it to be spontaneously packaged in this way by co-self-assembly with viral capsid protein (CP). We focus on the few viruses whose nucleocapsids can be reconstituted from their purified CP and ssRNA genomes and whose CPs can spontaneously package heterologous RNA into virus-like particles (VLPs). These VLPs are then compared with their cell-synthesized versions, with lentivirus and adeno-associated virus vector particles, and with nucleocapsids formed by nonviral proteins whose messenger RNAs are put under directed evolutionary pressure to be packaged by them in cellulo.

Genome-scale and multigene transcriptional regulation are crucial technologies in metabolic engineering. However, in E. coli, a stable and universal tool for whole-genome transcriptional activation, and an in situ tool for multigene regulation remain lacking. Here, we present CAGER, a versatile clustered regularly interspaced short palindromic repeats-associated transposases (CAST)-mediated gene regulation toolkit. Through rational mutagenesis, we mitigate the intrinsic transcriptional interference in the left end of CAST system derived from Vibrio cholerae. Using promoters or terminators as cargoes, CAGER constructs the genome-wide activation (3272 genes) or termination (3339 genes) libraries, from which new activation or inhibition targets relevant to cellular acetic acid assimilation are identified. Furthermore, with the aid of M13 phage and the promoter library, CAGER facilitates rapid in situ multigene expression diversification. Applied to lycopene synthesis, a library targeting seven genomic sites is constructed within 24 h, achieving a 73.6-fold yield increase. This work highlights the modifiability of CAST elements and broadens CAST’s application in transcriptional regulation.

The production of methane, a potent greenhouse gas, by ruminants during feed digestion is designated enteric methane emissions (EME) and is mainly produced by the rumen microbiome. Reliably recording EME in large populations is currently cost-prohibitive, hampering farming decisions aimed at reducing EME. Here, we perform comprehensive analyses on host genetics, KEGG orthology groups (KOs) from the rumen metagenome, and EME of more than 800 cows from Australia and Spain. We report that the rumen microbiome explains up to 34% of the EME variance, and when combined with the host genome, the variance explained is up to 59% with prediction accuracies of up to 0.40. The results support a recursive model, where both the host genome and rumen metagenome explain EME. The isometric log-ratio transformation of KOs may potentially better capture relationships between host genetics and the rumen microbiome than the centered log-ratio transformation, and BayesR yielded slightly higher microbe‑explained EME variance than best linear unbiased prediction. A forward simulation estimated to reach 90% of EME prediction accuracy with 6,000 animals with rumen microbiomes and host genomes, which could open opportunities for developing strategies to reduce EME. Our study contributes to the foundation for reducing EME, supporting global warming mitigation. Ruminal microbial genes and cattle (Bos taurus) genetics predict about 60% of enteric methane emission variation between animals, supporting strategies aimed at reducing these emissions.