Label-free viability assay using in-line holographic video microscopy

Realtime particulate matter and bacteria analysis of peritoneal dialysis fluid using digital inline holography

This study developed a digital inline holography (DIH) system integrated with deep learning algorithms for real-time detection of particulate matter (PM) and bacterial contamination in peritoneal dialysis (PD) fluids. The system comprises a microfluidic sample delivery module and a DIH imaging module that captures holograms using a pulsed laser and a digital camera with a 40 × objective. Our data processing pipeline enhances holograms, reconstructs images, and employs a YOLOv8n-based deep learning model for particle identification and classification, trained on labeled holograms of generic PD particles, Escherichia coli (E. coli), and Pseudomonas aeruginosa (P. aeruginosa). The system effectively detected and classified generic particles in sterile PD fluids, revealing diverse morphologies predominantly sized 1-5 µm with an average concentration of 61 particles/µL. In PD fluid samples spiked with high concentrations of E. coli and P. aeruginosa, our system achieved high sensitivity (>90 %) in detecting and classifying these bacteria at clinically relevant low false positive rates (∼0.5 %). Further validation against standard colony-forming unit (CFU) methods using PD fluid spiked with bacterial concentrations from approximately 100 to 10,000 bacteria/mL demonstrated a clear one-to-one correspondence between our measurements and CFU counts. Our DIH system provides a rapid, accurate alternative to traditional culture-based methods for assessing bacterial contamination in PD fluids. By enabling real-time sterility monitoring, it can significantly improve patient outcomes in PD treatment, facilitate point-of-care fluid production, reduce logistical challenges, and be extended to quality control in pharmaceutical production.

Digital holographic microscopy is suitable for lipid accumulation analysis in single cells of Yarrowia lipolytica

Digital holographic microscopy (DHM) is a label-free analytical technique for the determination of the cells' volume and their cytosolic refractive index. Here, we demonstrate the suitability of DHM for the quantification of total lipid accumulation in the oleaginous yeast Yarrowia lipolytica. Presently, microbial lipids are gaining increasing attention due to their nutritional value in feed and food applications. Their microbiological synthesis in algae and yeast is subject to optimization studies, which necessitates rapid quantification of total lipids for faster progress and the possibility of process control. So far, quantification of the total intracellular long-chain fatty acid concentration in yeast cells is time-consuming though when common chromatography for a volumetric analysis or staining and flow cytometry for a single-cell based analysis are used. This study, however, demonstrates that 3D-DHM facilitates a quasi-real-time measurement that allows for a rapid quantification of total intracellular lipid accumulation on a single-cell level without cell staining. Data from wild-type and lipid overproducing Y. lipolytica strains with specific yields of long-chain fatty acids in a range between 70 and 360 mg/gCDW show a good correlation with the optical volume determined by DHM, as the total lipid accumulation in the cell is typically well correlated with the long-chain fatty acid concentration. The results further correlate with data obtained from gas chromatography and flow cytometry of Nile Red-stained cells, which proves the reliability of DHM for lipid quantification in Y. lipolytica.

Intracellular dry mass density increases under growth-induced pressure

Cells that proliferate in confined environments develop mechanical compressive stress, referred to as growth-induced pressure, which inhibits growth and division across various organisms. Recent studies have shown that in these confined spaces, the diffusivity of intracellular nanoparticles decreases. However, the physical mechanisms behind this reduction remain unclear. In this study, we use quantitative phase imaging to measure the refractive index and dry mass density of Saccharomyces cerevisiae cells proliferating under confinement in a microfluidic bioreactor. Our results indicate that the observed decrease in diffusivity could be attributed to the intracellular accumulation of macromolecules. Furthermore, the linear scaling between cell content and growth-induced pressure suggests that the concentrations of macromolecules and osmolytes are maintained proportionally under such pressure in S. cerevisiae.

Monitoring polysorbate 80 degradation in protein solutions using Total Holographic Characterization

The degradation of polysorbate surfactants can limit the shelf life of biologic pharmaceutical products. Polysorbate is susceptible to degradation via either oxidation or hydrolysis pathways which releases free fatty acids (FFA) and other complex polymers. Degradants from Polysorbate 80 (PS80) can form particles and impact drug product quality. PS80 degradation products appear at low concentrations, and their refractive indexes are similar to that of the buffer, making them very challenging to detect. Furthermore, aggregates of FFA are similar in size and refractive index to protein aggregates adding complexity to characterizing these particles in protein solutions. Total Holographic Characterization (THC) is used in this work to characterize FFA particles of oleic acid and linoleic acid, the two most common degradation products of PS80. We demonstrate that the characteristic THC profile of the FFA oleic acid emulsion droplets can be used to monitor the degradation of PS80. THC can detect oleic acid at a concentration down to less than 100 ng/mL. Using the characteristic THC signal of oleic acid as a marker, the degradation of PS80 in protein solutions can be monitored quantitatively even in the presence of other contaminants of the same size, including silicone oil emulsion droplets and protein aggregates.

On-Chip Photonic Detection Techniques for Non-Invasive In Situ Characterizations at the Microfluidic Scale

Microfluidics has emerged as a robust technology for diverse applications, ranging from bio-medical diagnostics to chemical analysis. Among the different characterization techniques that can be used to analyze samples at the microfluidic scale, the coupling of photonic detection techniques and on-chip configurations is particularly advantageous due to its non-invasive nature, which permits sensitive, real-time, high throughput, and rapid analyses, taking advantage of the microfluidic special environments and reduced sample volumes. Putting a special emphasis on integrated detection schemes, this review article explores the most relevant advances in the on-chip implementation of UV-vis, near-infrared, terahertz, and X-ray-based techniques for different characterizations, ranging from punctual spectroscopic or scattering-based measurements to different types of mapping/imaging. The principles of the techniques and their interest are discussed through their application to different systems.

Multispectral in-line hologram reconstruction with aberration compensation applied to Gram-stained bacteria microscopy

In multispectral digital in-line holographic microscopy (DIHM), aberrations of the optical system affect the repeatability of the reconstruction of transmittance, phase and morphology of the objects of interest. Here we address this issue first by model fitting calibration using transparent beads inserted in the sample. This step estimates the aberrations of the optical system as a function of the lateral position in the field of view and at each wavelength. Second, we use a regularized inverse problem approach (IPA) to reconstruct the transmittance and phase of objects of interest. Our method accounts for shift-variant chromatic and geometrical aberrations in the forward model. The multi-wavelength holograms are jointly reconstructed by favouring the colocalization of the object edges. The method is applied to the case of bacteria imaging in Gram-stained blood smears. It shows our methodology evaluates aberrations with good repeatability. This improves the repeatability of the reconstructions and delivers more contrasted spectral signatures in transmittance and phase, which could benefit applications of microscopy, such as the analysis and classification of stained bacteria.