The current methods for diagnosis of acute and chronic infections are complex and skill-intensive. For complex clinical biofilm infections, it can take days from collecting and processing a patient's sample to achieving a result. These aspects place a significant burden on healthcare providers, delay treatment, and can lead to adverse patient outcomes. We report the development and application of a novel multi-excitation Raman spectroscopy-based methodology for the label-free and non-invasive detection of microbial pathogens that can be used with unprocessed clinical samples directly and provide rapid data to inform diagnosis by a medical professional. The method relies on the differential excitation of non-resonant and resonant molecular components in bacterial cells to enhance the molecular finger-printing capability to obtain strain-level distinction in bacterial species. Here, we use this strategy to detect and characterize the respiratory pathogens and as typical infectious agents associated with cystic fibrosis. Planktonic specimens were analyzed both in isolation and in artificial sputum media. The resonance Raman components, excited at different wavelengths, were characterized as carotenoids and porphyrins. By combining the more informative multi-excitation Raman spectra with multivariate analysis (support vector machine) the accuracy was found to be 99.75% for both species (across all strains), including 100% accuracy for drug-sensitive and drug-resistant . The results demonstrate that our methodology based on multi-excitation Raman spectroscopy can underpin the development of a powerful platform for the rapid and reagentless detection of clinical pathogens to support diagnosis by a medical expert, in this case relevant to cystic fibrosis. Such a platform could provide translatable diagnostic solutions in a variety of disease areas and also be utilized for the rapid detection of anti-microbial resistance.

Melioidosis caused by the facultative intracellular pathogen is difficult to treat due to poor intracellular bioavailability of antibiotics and antibiotic resistance. In the absence of novel compounds, polymersome (PM) encapsulation may increase the efficacy of existing antibiotics and reduce antibiotic resistance by promoting targeted, infection-specific intracellular uptake. In this study, we developed PMs composed of widely available poly(ethylene oxide)-polycaprolactone block copolymers and demonstrated their delivery to intracellular infection using multispectral imaging flow cytometry (IFC) and coherent anti-Stokes Raman scattering microscopy. Antibiotics were tightly sequestered in PMs and did not inhibit the growth of free-living . However, on uptake of antibiotic-loaded PMs by infected macrophages, IFC demonstrated PM colocalization with intracellular and a significant inhibition of their growth. We conclude that PMs are a viable approach for the targeted antibiotic treatment of persistent intracellular infection.

Superresolution (SR) optical microscopy has allowed the investigation of many biological structures below the diffraction limit; however, most of the techniques are hampered by the need for fluorescent labels. Nonlinear label-free techniques such as second-harmonic generation (SHG) provide structurally specific contrast without the addition of exogenous labels, allowing observation of unperturbed biological systems. We use the photonic nanojet (PNJ) phenomena to achieve SR-SHG. A resolution of with respect to the fundamental wavelength, that is, a -fold improvement over conventional or diffraction-limited SHG under the same imaging conditions is achieved. Crucially we find that the polarization properties of excitation are maintained in a PNJ. This is observed in experiment and simulations. This may have widespread implications to increase sensitivity by detection of polarization-resolved SHG by observing anisotropy in signals. These new, to the best of our knowledge, findings allowed us to visualize biological SHG-active structures such as collagen at an unprecedented and previously unresolvable spatial scale. Moreover, we demonstrate that the use of an array of self-assembled high-index spheres overcomes the issue of a limited field of view for such a method, allowing PNJ-assisted SR-SHG to be used over a large area. Dysregulation of collagen at the nanoscale occurs in many diseases and is an underlying cause in diseases such as lung fibrosis. Here we demonstrate that pSR-SHG allows unprecedented observation of changes at the nanoscale that are invisible by conventional diffraction-limited SHG imaging. The ability to nondestructively image SHG-active biological structures without labels at the nanoscale with a relatively simple optical method heralds the promise of a new tool to understand biological phenomena and drive drug discovery.

Microplastic pollution is an urgent global issue. While spectroscopic techniques have been widely used for the identification of plastics collected from aquatic environments, these techniques are often labor-intensive and time-consuming due to sample collection, preparation, and long measurement times. In this study, a method for the two-dimensional detection and classification of flowing microplastic and organic biotic particles with high spatial and temporal resolutions has been proposed based on the simultaneous detection of coherent anti-Stokes Raman scattering (CARS) and two-photon excited autofluorescence (TPEAF) signals. Poly(methyl methacrylate) (PMMA), polystyrene (PS), and low-density polyethylene (LDPE) particles with sizes ranging from several tens to hundreds of micrometers were selectively detected in flow with an average velocity of 4.17 mm/s by CARS line scanning. With the same flow velocity, flowing PMMA and alga particles were measured using a multimodal system of CARS and TPEAF signals. The average intensities of both PMMA and alga particles in the CARS signals at a frequency of 2940 cm were higher than the background level, while only algae emitted TPEAF signals. This allowed the classification of PMMA and alga particles to be successfully performed in flow by the simultaneous detection of CARS and TPEAF signals. With the proposed method, the monitoring of microplastics in a continuous water flow without collection or extraction is possible, which is game-changing for the current sampling-based microplastic analysis.

Tauopathies are a group of disorders in which the deposition of abnormally folded tau protein accompanies neurodegeneration. The development of methods for detection and classification of pathological changes in protein conformation are desirable for understanding the factors that influence the structural polymorphism of aggregates in tauopathies. We have previously demonstrated the utility of Raman spectroscopy for the characterization and discrimination of different protein aggregates, including tau, based on their unique conformational signatures. Building on this, in the present study, we assess the utility of Raman spectroscopy for characterizing and distinguishing different conformers of the same protein which in the case of tau are unique tau strains generated . We now investigate the impact of aggregation environment, cofactors, post-translational modification and primary sequence on the Raman fingerprint of tau fibrils. Using quantitative conformational fingerprinting and multivariate statistical analysis, we found that the aggregation of tau in different buffer conditions resulted in the formation of distinct fibril strains. Unique spectral markers were identified for tau fibrils generated using heparin or RNA cofactors, as well as for phosphorylated tau. We also determined that the primary sequence of the tau monomer influenced the conformational signature of the resulting tau fibril, including 2N4R, 0N3R, K18 and P301S tau variants. These results highlight the conformational polymorphism of tau fibrils, which is reflected in the wide range of associated neurological disorders. Furthermore, the analyses presented in this study provide a benchmark for the Raman spectroscopic characterization of tau strains, which may shed light on how the aggregation environment, cofactors and post-translational modifications influence tau conformation in future studies.