Optofluidics, a research discipline combining optics with microfluidics, currently aspires to revolutionize the analysis of biological and chemical samples, e.g., for medicine, pharmacology, or molecular biology. In order to detect low concentrations of analytes in water, we have developed an optofluidic device containing a nanostructured substrate for surface enhanced Raman spectroscopy (SERS). The geometry of the gold surface allows localized plasmon oscillations to give rise to the SERS effect, in which the Raman spectral lines are intensified by the interaction of the plasmonic field with the electrons in the molecular bonds. The SERS substrate was enclosed in a microfluidic system, which allowed transport and precise mixing of the analyzed fluids, while preventing contamination or abrasion of the highly sensitive substrate. To illustrate its practical use, we employed the device for quantitative detection of persistent environmental pollutant 1,2,3-trichloropropane in water in submillimolar concentrations. The developed sensor allows fast and simple quantification of halogenated compounds and it will contribute towards the environmental monitoring and enzymology experiments with engineered haloalkane dehalogenase enzymes.

Selenium (Se) is an element with many commercial applications as well as an essential micronutrient. Dietary Se has antioxidant properties and it is known to play a role in cancer prevention. However, the general population often suffers from Se deficiency. Green algae, such as Chlorella vulgaris, cultivated in Se-enriched environment may be used as a food supplement to provide adequate levels of Se. We used Raman microspectroscopy (RS) for fast, reliable, and non-destructive measurement of Se concentration in living algal cells. We employed inductively coupled plasma-mass spectrometry as a reference method to RS and we found a substantial correlation between the Raman signal intensity at 252 cm⁻¹ and total Se concentration in the studied cells. We used RS to assess the uptake of Se by living and inactivated algae and demonstrated the necessity of active cellular transport for Se accumulation. Additionally, we observed the intracellular Se being transformed into an insoluble elemental form, which we further supported by the energy-dispersive X-ray spectroscopy imaging.

Enzyme cascades enable complex biochemical transformations, but optimizing them requires searching high-dimensional spaces of enzyme stoichiometry, reaction conditions, and buffer composition. Here we introduce CascadeMAP, an autonomous microfluidic platform for closed-loop optimization of enzyme cascades, integrating high-throughput microfluidics with Bayesian optimization and assisted by agentic analyses. We demonstrate the platform across two three-enzyme cascades: (i) a glycerol detection pathway monitored by fluorescence and (ii) a 1,2,3-trichloropropane degradation pathway monitored by label-free Raman spectroscopy, providing orthogonal detection modalities. Bayesian optimization reached comparable optima with threefold fewer experimental conditions than Design of Experiments. A multi-agent AI system automated processing 2.1 GB of experimental data, pattern recognition, and insight synthesis. Operating without human intervention for 7 days, CascadeMAP processed >295,000 reactions across ∼7,400 different conditions. This capability establishes a generalizable, resource-efficient framework for autonomously optimizing enzyme cascades and metabolic pathways and accelerates the development of biocatalytic and synthetic biological systems.

Photosensory protein function spans multiple time and length scales, demanding integrative approaches. We introduce 4–diacetylenyl–phenylalanine (DAF), a dual–purpose non–canonical amino acid (ncAA) that enables both chemical control and spectroscopic readout of photoreceptor dynamics. Genetically encoded in E. coli , DAF combines a reactive diyne for bioorthogonal ligations (thiols, azides, tetrazines) with a strong, solvatochromic Raman signal in the cell–silent region. Applied to the light–oxygen–voltage (LOV) transcription factor EL222, DAF enables multifaceted interrogation of its photocycle. We engineer a covalently cross–linked variant that suppresses light–driven conformational changes and DNA binding, and generate a donor–acceptor construct for Förster resonance energy transfer (FRET) tracking of photoinduced structural dynamics. Time–resolved stimulated Raman spectroscopy following flavin mononucleotide (FMN) excitation reveals additional processes —from vibrational energy transfer to local unfolding—spanning femtoseconds to milliseconds. DAF thus constitutes a versatile tool to resolve protein dynamics with high spatiotemporal resolution.

The genus Streptomyces is well known as a prolific source of many bioactive compounds. This review outlines the principles of Raman spectroscopy and its application to bacterial systems, with particular emphasis on the secondary metabolites produced by Streptomyces . Streptomyces are unparalleled chemical factories, producing over two‐thirds of all naturally derived antibiotics and bioactive molecules. Incorporating Raman spectroscopy into the study of these secondary metabolites offers a non‐destructive, label‐free method to monitor chemical diversity in real time. Here, we cover the strengths and limitations of Raman spectroscopy, and we focus on how recent advances bypass traditional detection limits, enabling sensitive, low‐concentration chemical analysis. We also examine integrated workflows that connect Raman spectral data with bioinformatics, digital microfluidics, and machine learning models. Using major antibiotic classes as practical examples, this work shows how Raman spectroscopy functions in chemical characterization, high‐throughput screening, and the direct tracking of biosynthetic pathways. These capabilities position Raman and SERS methodologies as key analytical tools for current microbial biotechnology and targeted antibiotic discovery.