Proximity labeling rests on a deceptively simple idea. Instead of trying to capture fragile or transient interactions directly, researchers fuse an engineered enzyme to a molecule of interest and let that enzyme chemically tag everything nearby. The tagged neighbors can then be purified and identified by mass spectrometry or sequencing, producing a snapshot of the local molecular environment. Enzymes such as APEX2, which uses hydrogen peroxide to drive radical generation, and TurboID, an evolved derivative of biotin ligase, have transformed the study of protein complexes and organelle proteomes. Applying the same logic to RNA, however, has proven far more difficult, because RNA molecules are chemically distinct, often abundant, and embedded in ribonucleoprotein assemblies that are easily disrupted by harsh labeling conditions.

Lantern was developed to address precisely this gap. The enzyme is designed to label molecules in the immediate vicinity of a chosen RNA, generating a record of the proteins and other RNAs that associate with it in living cells. Early versions of the tool, like many first-generation proximity labeling systems, faced limitations in catalytic rate, background activity, and the conditions required to drive the labeling reaction. Slow enzymes require long labeling periods, during which the cell continues to change, blurring the temporal resolution of the resulting map. High background activity, meanwhile, can swamp genuine neighbors in a haze of nonspecific tags, obscuring the very interactions researchers hope to detect.

Directed evolution offers a systematic way out of this impasse. The approach mimics natural selection in the laboratory: researchers generate large libraries of enzyme variants carrying random mutations, screen or select the variants that perform best on a defined task, and then iterate the process, accumulating beneficial mutations over successive rounds. Applied to Lantern, this strategy allowed the team to interrogate enormous sequence space and identify combinations of mutations that jointly improved catalytic turnover, reduced background, and preserved the enzyme’s ability to function inside the complex chemical environment of a mammalian cell. The result is an evolved Lantern variant that labels proximal RNA and protein molecules far more rapidly than its predecessors.

The significance of speed in proximity labeling is difficult to overstate. Cellular states are not static; signaling events, stress responses, and cell-cycle transitions can remodel the interactome of an RNA within minutes. A labeling reaction that requires hours effectively averages over all of these changes, producing a composite picture that may not correspond to any real biological moment. A fast enzyme, by contrast, can capture a molecular neighborhood on a timescale that approaches the dynamics of the underlying biology. This temporal precision matters enormously for studying processes such as RNA granule assembly, stress granule formation, and the rapid redistribution of RNAs during cellular responses to external stimuli.

Dual labeling of both RNA and protein by the same enzyme is another defining feature of the evolved Lantern system. Most existing tools are specialized: some tag proteins efficiently but leave RNA untouched, while RNA-targeting approaches often rely on separate chemistries that are difficult to reconcile in a single experiment. A unified catalyst that marks both classes of molecules in the vicinity of a target simplifies experimental design and enables genuinely integrated maps of ribonucleoprotein architecture. Because RNA-binding proteins and their RNA partners form tightly interwoven networks, the ability to profile both sides of the interface from a single labeling event provides a more complete and internally consistent picture than combining results from separate, independently optimized systems.

The technical challenges that directed evolution had to overcome are worth appreciating in detail. An ideal proximity labeling enzyme must remain inactive until deliberately deployed, tolerate fusion to diverse RNA-targeting modules such as Cas proteins or RNA-binding domains, operate at physiological temperature and pH, and generate reactive intermediates that diffuse only over a short range before reacting with nearby molecules. Balancing these competing demands is not intuitive; mutations that boost catalytic activity often increase background or alter substrate specificity in undesirable ways. Screening strategies that evaluate variants directly in cellular contexts, rather than in simplified biochemical assays, are therefore essential for identifying enzymes that perform well where it matters, inside living cells rather than in a test tube.

Beyond its immediate technical achievements, the evolved Lantern system points toward broader applications across biology and medicine. Mapping the protein companions of disease-associated noncoding RNAs could reveal how long noncoding RNAs execute their regulatory functions and how mutations disrupt these interactions in conditions ranging from cancer to neurodegeneration. Viral RNAs, which recruit host factors into specialized replication and packaging complexes, could be profiled with unprecedented temporal resolution, illuminating points of vulnerability for antiviral therapeutics. In developmental biology, tracking the changing molecular neighborhoods of specific transcripts as cells differentiate could clarify how post-transcriptional regulation shapes cell fate decisions. The combination of speed, dual specificity, and genetic encodability makes the tool adaptable to virtually any RNA that can be targeted with a suitable binding module.

The study also contributes to a growing appreciation of directed evolution as an engine of innovation in chemical biology. Time and again, natural enzymes have proven to be starting points rather than finished solutions, and laboratory evolution has repeatedly delivered variants with properties that no rational design effort could have predicted. The Lantern work exemplifies this pattern: by letting mutation and selection explore sequence space under experimentally defined pressures, researchers obtained a catalyst whose performance characteristics reflect the specific demands of proximity labeling in living cells. As screening technologies improve and libraries grow larger and more diverse, the pace at which such optimized tools emerge is likely to accelerate, equipping the community with an ever-richer toolkit for interrogating molecular proximity.

For the field of RNA biology in particular, the arrival of a rapid, dual-function proximity labeling enzyme marks a meaningful step forward. The interactomes of RNAs have long been studied through laborious biochemical purification methods that require large quantities of material and inevitably perturb the very assemblies under investigation. A genetically encodable, fast-acting labeling system brings the study of RNA neighborhoods into the same experimental regime that has already revolutionized protein interaction mapping, with all the advantages of sensitivity, scalability, and compatibility with living systems. As researchers begin to apply evolved Lantern to their own questions, the coming years are likely to see a substantial expansion in our understanding of the molecular ecosystems that surround RNA, and of the roles those ecosystems play in health and disease.

Subject of Research: Directed evolution of the Lantern enzyme for rapid proximity labeling of RNA and proteins in living cells

Article Title: Directed evolution of Lantern enables rapid RNA and protein proximity labeling

Article References: Fang, Y., Ren, Z., Zheng, F., Wang, R., Zhao, S., Zhang, Y., Wang, W., Li, C., Liu-Yang, L., Lin, C., Liu, J., & Zou, P. (2026). Directed evolution of Lantern enables rapid RNA and protein proximity labeling. Nature Chemical Biology. https://doi.org/10.1038/s41589-026-02313-y

Image Credits: AI Generated

DOI: 10.1038/s41589-026-02313-y

Keywords: directed evolution, Lantern, proximity labeling, RNA biology, protein labeling, RNA-protein interactions, chemical biology, ribonucleoprotein complexes, enzyme engineering, molecular interactome, living cells, Nature Chemical Biology