For much of the past century, carbon dioxide (CO2) has received little attention scientifically outside of its role as a byproduct in the industrialization of the global economy. This trend has recently been upended where, due to mounting environmental concerns, CO2 has been brought squarely into the public consciousness. This surge in activity has contributed to a once unimaginable idea now pervading the scientific community: could CO2, a highly stable byproduct of hydrocarbon combustion, be recycled and converted back into useful chemicals and fuels? Owing to its ubiquitous nature and availability at truly massive quantities, it is thought that CO2-based products could offer a meaningful pathway toward lowering the environmental impact of many of the top industrial products while also enhancing supply chain diversification and resilience. In this manuscript we provide a holistic review of the pathways for CO2 conversion, the underlying chemistry and challenges involved in the transformation to products, and considerations for commercialization.

Promoters, containing multiple cis-regulatory elements, are crucial for plant gene expression. While constitutive promoters are widely used in stress-resistance engineering, their sustained strong expression can lead to metabolic waste and hinder growth. In contrast, inducible promoters enable precise, stage-specific gene activation, offering flexible regulation. Consequently, the development and application of inducible promoters have become a major focus in plant genetic engineering research. This paper reviews recent advances in plant stress-inducible promoters, including their structure, function, classification, associated functional elements, and interacting transcription factors. Furthermore, we discuss future research directions and application prospects, aiming to deepen the understanding of plant gene expression regulation and provide valuable promoter resources for genetic engineering and stress-tolerant crop improvement.

Flow cytometry is widely used for high-throughput single-cell analysis. However, its data analysis relies on either costly commercial software or programming-intensive open-source tools. To bridge this gap, we developed FlowWeb, a freely accessible, web-based platform that combines the flexibility of the R/Bioconductor ecosystem with an intuitive graphical user interface. FlowWeb enables integrated workflows for data handling, quality control, gating, visualization and statistical analysis within a unified environment. FlowWeb integrates raw data, metadata, and analytical state within synchronized Bioconductor structures, enabling coherent analysis and visualization workflows. FlowWeb supports both manual and automated data-driven gating workflows. To evaluate its performance, we applied FlowWeb to an in-house flow cytometry dataset and compared its automated cell cycle and gating workflows to established commercial tools. The automated cell cycle workflow of FlowWeb produced consistent and reproducible results across replicates and demonstrated high concordance with reference analyses, highlighting the robustness of the platform. Advanced visualization tools of FlowWeb include a wide range of fully customizable individual, overlay, and statistical plots. To enhance usability and reproducibility, the FlowWeb platform provides optional user-accounts that allow storage of reusable configurations, including quality control presets, gating definitions, and plot templates. By lowering technical barriers without compromising analytical rigor, FlowWeb facilitates accessible, reproducible, and scalable flow cytometry data analysis for a broad range of users in research and clinical settings.

Stabilizing microbial cocultures is a central challenge for bioproduction. While division of labor between strains can enhance efficiency, it often results in population instability over time. Classical strategies, including cross-feeding, quorum sensing, and toxin-antitoxin modules, often rely on complex ecological interactions that are difficult to predict or maintain under bioprocess conditions. We report the first implementation, to our knowledge, of a synthetic-niche–based coculture operated in a continuous bioreactor, using genetic toggle switches that couple growth to defined phenotypic states. We engineered two auxotrophic strains, TOGGLE_green and TOGGLE_yellow, in which growth is linked to either GFP- or YFP-expressing states and assessed their behavior under continuous bioreactor conditions using automated and reactive flow cytometry. Unexpectedly, the introduction of auxotrophic pressure reshaped circuit function, i.e., rather than maintaining bistability as typically reported in batch or microfluidic systems, toggle strains behaved as unidirectional inducible systems that reverted upon inducer withdrawal. This emergent behavior enabled simplified single-input control at the bioreactor scale, but also revealed a critical limitation for long-term operation, namely rapid mutational escape of the growth-impaired strain occurring within fewer than 10 generations in coculture, a markedly shorter time scale than the ∼50 generations typically reported in the literature. A simple repression-based ODE model recapitulated the reversible dynamics, capturing the effective inducible behavior observed under continuous cultivation, whereas deviations under prolonged operation highlighted the rapid evolutionary erosion of synthetic control. Our findings demonstrate both the potential and the limitations of synthetic niches as a scalable coculture control strategy.

Glycan biosynthesis relies on nucleotide-activated sugars, essential metabolites across all domains of life, yet their usage in microbes is poorly understood. Here we present SugarBase, a mass spectrometry and bioinformatic pipeline for untargeted exploration of microbial nucleotide sugar networks. SugarBase resolves the chemical complexity of microbial metabolism by combining narrow-window DIA fragmentation with a chemistry-informed parent ion identification algorithm. Applying SugarBase across a broad phylogenetic range of microbes revealed extensive, species-specific nucleotide sugar profiles, including many candidates with no existing annotation, generating the most comprehensive inventory of nucleotide sugars to date. SugarBase guided identification of gene clusters and allowed discrimination between pseudaminic- and legionaminic acid-producing strains, where genomic and proteomic data provided only ambiguous information. We resolved distinct nonulosonic acid profiles in several Campylobacter jejuni strains, sugars which may alter susceptibility towards distinct flagellotropic phages. We further identify previously undescribed CMP-activated higher-carbon ulosonic acids in Magnetospirillum, expanding the known chemical space in glycan biosynthesis. In summary, SugarBase supports scalable discovery of microbial nucleotide sugar pathways and enzymes, expanding access to chemically complex glycans and providing new targets for antimicrobial development.

β-Glucosidase (BGL), a pivotal enzyme in lignocellulosic saccharification, has been increasingly recognized as an “emerging green biocatalyst” in modern biorefinery processes. Here, Aspergillus niger An-BGL was rationally engineered to achieve high-level production of BGL under low-cost inducers. Corncob powder served as a cost-effective alternative inducer, enhancing BGL production to 14.2 U/mL. The knockout of CreA and the overexpression of XlnR increased the BGL yield by 75% and 27%, respectively. Combinatorial engineering of CreA and XlnR generated the XO–CK strain, which exhibited a derepression effect at high glucose concentrations. Supplementation with 1% glucose alleviated the delayed enzyme production in the engineered XO–CK strain, resulting in a BGL activity of 31.54 U/mL. Furthermore, integration of the bglA gene into the high-expression amyA site enhanced BGL to 40.68 U/mL. The rational modification strategy for A. niger strain established in this study offers an efficient and sustainable approach for transforming corncob agricultural waste into high-value enzymatic preparations.

High level of protein expression is usually welcomed in industry and research, and codon optimization is widely used to achieve high expression. Methods of implementing codon optimization can be divided into two branches, one is classical methods which develop cost functions based on empirical law, another is AI methods which learn the codon choice principles from endogenous genes with neural networks. Here we develop two codon optimization tools based on two branches respectively, namely OptimWiz 2.1 and OptimWiz 3.0. Results of fusion protein fluorescence detection indicate that both OptimWiz 2.1 and OptimWiz 3.0 are superior to all the other commercially available codon optimization tools. Principles of codon optimization are revealed in the process of machine learning on both tools.

Arabidopsis thaliana naturally occurs across a wide geographic range and displays extensive natural variation in several traits including adaptive responses to the abiotic environment (e.g. temperature, drought, salt). Quantitative techniques like Genome Wide Association Studies (GWAS) enable mapping the genetic basis of such environmental responses and benefits from extensive genetic variation, but the size of the chosen diversity panel is often limited by phenotyping capacity. Most studies therefore use subpanels, often based on maximization of genetic diversity. However, this type of selection may overrepresent cosmopolitan alleles and underrepresent rare environment-specific alleles. Here, we demonstrate that the genetic variation in a GWAS subpanel of Arabidopsis thaliana accessions depends almost entirely on the number of accessions in the panel and very little on the composition of the panel. We present the EcoCore panel designed by grouping accessions of the 1001 genomes (1001G; 1135 accessions) collection, based on their native collection environment and selecting an equal number of accessions from each environment. We assessed hypocotyl lengths of plants grown at control and ambient high temperatures (20C and 28C) for 913 accessions of the 1001G and mapped these traits with the full 1001G panel versus the EcoCore panel. The EcoCore panel revealed novel genetic associations with hypocotyl length which is attributed to enrichment of alleles from rare environments. We present the EcoCore panel as a manageable resource for studying phenotypic plasticity and the genetic basis of plant–environment interactions.

Bacterial ribosomal RNAs (rRNAs) are decorated with conserved nucleotide modifications, but the functionality of these modifications is often underexplored. MraW (RsmH) is a 16S rRNA methyltransferase that fine-tunes ribosomal function. We identified a loss-of-function allele in mraW that corrected a late-stage sporulation defect in Bacillus subtilis by bypassing a key sporulation checkpoint via altered translational regulation. Purified ribosomes isolated from ΔmraW cells displayed a ~2-fold decrease in translation efficiency; in vivo, ΔmraW cells produced decreased levels of the sporulation checkpoint protein CmpA. This regulation was mediated by sequences from the 5' untranslated region and the coding sequence of cmpA, which form a step-loop structure that occlude early codons of the mRNA. Proteomic analysis revealed that MraW directly or indirectly regulates the production of multiple proteins, some of which form similar structural elements as the cmpA transcript. We propose that MraW modification of 16S rRNA enhances translation efficiency in general, and that specific transcripts, whose gene products are likely required in limiting quantities, have evolved structural features that act as a regulatory mechanism to govern protein levels. This type of regulation may be most apparent in bacteria which exhibit uncoupled transcription and translation.

Citrate is a central intermediate metabolite linking the tricarboxylic acid cycle and lipid biosynthesis. Tools for monitoring of spatiotemporal citrate dynamics are critical for getting a better understanding of cellular metabolism. Here, we develope genetically encoded excitation ratiometric biosensors for citrate, based on our previous intensiometric green fluorescence protein-based citrate biosensor, Citron1. We find that a single mutation in the Citron1 chromophore-forming tripeptide provided an excitation ratiometric response. Further rounds of directed evolution yield highly responsive variants, exhibiting citrate-dependent fluorescence changes between two excitation peaks. When expressed in mammalian cells, these biosensors enable citrate dynamics to be monitored in both the cytosol and mitochondria. Comparative analysis across multiple human breast cancer cell lines uncovers cell line-specific differences in citrate levels and their heterogeneity, which could be linked to their malignancy. Furthermore, flow cytometry-based measurements in mouse embryonic stem cells demonstrate the proteomics signatures underlying the population-level variability in citrate concentrations and citrate rewiring during stem cell differentiation. Together, these results show that these excitation ratiometric citrate biosensors enable quantitative, compartment-resolved, and population-scale analysis of cellular metabolism.