Since the discovery and application of green fluorescent protein for use as an optical tag, fluorescent proteins (FPs) have changed the way we observe biological signals and processes. FP and fluorescent biosensor design has continued to advance, facilitated by new technologies and developments in chemistry, physics, engineering and screening technologies. We summarize some of the recent developments in FP engineering, focusing on insights that have led to improved photostability or longer wavelengths, among other improvements, highlighting mScarlet as a case study. We also discuss the engineering of new fluorescent biosensors, focusing on the ways in which screening, quantitative imaging, spatial resolution and multiplexing have been improved in recent years. Finally, we conclude with a perspective on what the future holds for the next generation of FPs and biosensors. This Review summarizes recent developments in fluorescent protein technology, including the engineering of fluorescent biosensors.

Candida species are fungal pathogens whose rapidly increasing antifungal resistance poses a substantial public health challenge. High-throughput CRISPR-based screening could accelerate antifungal target discovery, yet its application in Candida has been limited by low DNA transformation efficiency. Chemical transformation exposes cells to environmental stresses to permit DNA uptake, but the physiological constraints on transformability remain poorly defined. Here, we show that genetic transformability in C. albicans is governed by the cellular capacity to withstand and recover from transformation-induced stress. By systematically manipulating preculture conditions and transformation chemistry to modulate cellular stress tolerance, we developed a fungal advanced chemical transformation (FACT) method. The FACT method improves transformation efficiency over 100-fold across diverse Candida species and enables robust pooled CRISPR screening. Systems-level proteomic and physiological analyses reveal that nutrient limitation and optimized lithium acetate formulations prime cells for tolerance to transformation stress, with transformation efficiency strongly correlating with the expression of oxidative stress response proteins. This work overcomes a critical barrier to high‑throughput functional genomics and provides a mechanistic blueprint for enabling genetic manipulation of recalcitrant fungi.

Syngas conversion to carboxylic acids can be achieved through the combined actions of acetogens and chain elongators. Mixed cultures enriched with these functional groups can serve as robust and resilient catalysts for bio-based production, but developing efficient and stable communities remains challenging. In this study, we aimed to enrich a mixed microbial culture for efficient syngas-driven chain elongation using carbon monoxide (CO) and acetate as substrates. Three strategies were employed: (i) conventional enrichment using anaerobic sludge only, (ii) sludge augmentation with known syngas fermenters (Clostridium autoethanogenum, Clostridium carboxidivorans, Eubacterium limosum, and Acetobacterium wieringae) to enhance carboxydotrophic activity, and (iii) sludge augmentation with chain elongator Clostridium kluyveri to stimulate chain elongation. Enrichments were performed in batch cultures with stepwise increases in CO partial pressure across successive transfers until a 100% CO (170 kPa) headspace was reached. Ultimately, all enrichments grew under a 100% CO headspace, simultaneously utilizing CO and acetate, with butyrate as main product. 16S rRNA gene and metagenomic analyses revealed that Eubacterium became predominant. Several genera (Aminobacterium, Anaerotignum, Oscillibacter, and Proteiniphilum) not known to ferment CO, were also enriched. Based on physiological and metagenomic analyses, we hypothesize that Eubacterium consumes CO and acetate, producing butyrate and extracellular polymeric substance (EPS)-like material. Metagenomic data further suggests that components derived from this EPS-like material may serve as substrate for the other enriched genera. This study demonstrates that augmentation can steer mixed microbial communities toward targeted product formation and highlights the critical role of initial culture conditions in shaping community composition and functionality. 

A decade has passed since the initial description of cytosine base editors in 2016. This new class of gene editors, utilizing DNA damage intermediates beyond double-stranded DNA breaks, fundamentally shifted the paradigm of gene editing from stochastic disruption to precise chemical correction. Since then, the field has rapidly matured, with the development of optimized base editors with improved editing efficiency, targeting scope, precision and specificity, as well as the subsequent generation of adenine base editors and prime editors. Base editors have not only become widely used research tools but have served as foundational platforms for biotechnology companies developing human therapies. Today, base editors are being deployed in trials for a diverse list of indications including sickle cell disease, alpha-1 antitrypsin deficiency, inborn errors of metabolism, leukaemias and cardiovascular indications. This Review critically examines the ‘bench-to-bedside’ trajectory of base editors, detailing their mechanistic evolution and expanding role in treating human disease. Base editing, a gene editing technology capable of installing point mutations with high efficiency and precision, was first reported a decade ago. This Review examines the evolution of base editors and their road to clinical translation, highlighting key advances, ongoing challenges and the current clinical trial landscape.

Nitrogen-fixing cyanobacteria are important sources of bioavailable nitrogen on Earth. Some nitrogen-fixing cyanobacteria are endosymbionts of algae, and recently one of them, UCYN-A2, was shown to be an early-stage organelle (nitroplast) of haptophytes. These biological associations are important models for studying co-evolution and organellogenesis. Endosymbioses between Rhopalodiaceae diatoms and nitrogen-fixing cyanobacteria (spheroid bodies, SBs) are widespread in marine and freshwater ecosystems, but their adaptation and evolution remain unclear. We found that the genomes and metabolic characteristics of marine and freshwater SBs are remarkably similar. Purifying selection pressures dominated SB diversification both within marine and freshwater habitats and across habitat boundaries. The metabolic characteristics and genome reduction of SBs are substantially different from UCYN-A, suggesting different evolutionary journeys for the endosymbionts influenced by different hosts. We estimated that the marine SBs diversified ~185 Mya (95% highest posterior density (HPD): 340-88 Mya), which was within a prolonged oligotrophic period in the ocean, during which UCYN-A also diversified. The freshwater SBs diversified from the marine SBs ~137 Mya (95% HPD: 258-66 Mya) and further diversified ~80 Mya (95% HPD: 157-31 Mya), when sea level was increasing. Our study reveals the genetic and metabolic underpinnings characterizing the nitrogen-fixing cyanobacterial endosymbionts of Rhopalodiaceae diatoms.

Antimicrobial peptides (AMP) represent promising candidates for combating multidrug-resistant bacterial infections; however, their clinical translation has been hampered by inherent limitations, including poor proteolytic and serum stability, unfavorable pharmacokinetic profiles, and cytotoxicity or hemolytic effects. In recent years, artificial intelligence (AI)-driven peptide design has emerged as a transformative strategy to accelerate AMP discovery and optimization by navigating vast sequence spaces and predicting multi-objective properties. Nevertheless, existing AMP databases predominantly catalog sequence and activity information, with insufficient annotation of non-natural amino acid and chemical modifications. In this update, the Data Repository of Antimicrobial Peptides (DRAMP) introduces a novel FASTS format, which incorporates SMILES representations into FASTA annotation lines, enabling the simultaneous storage of sequence and structural information within a single text file. This unified format allows accurate representation of peptides containing non-natural residues and chemical modifications, facilitates structure-aware sequence analysis, and supports AI/ML-based peptide prediction and design. DRAMP 5.0 currently contains 32,296 entries (2,036 newly added). In addition, 22,298 peptide sequences have been annotated in the newly proposed FASTS format. The updated DRAMP provides an enhanced resource for AMP research, cheminformatics, and AI-driven peptide discovery, and remains freely available at https://dramp.cpu-bioinfor.org/.