Interference Disturbance Analysis Enables Single-Cell Level Growth and Mobility Characterization for Rapid Antimicrobial Susceptibility Testing.

To support the emerging battle against antimicrobial resistance (AMR), detection methods that allow fast and accurate antimicrobial susceptibility testing (AST) are urgently needed. The early identification and application of an appropriate antibiotic treatment leads to lower mortality rates and substantial cost savings and prevents the development of resistant pathogens. In this work, we present a diffraction-based method, which is capable of quantitative bacterial growth, mobility, and susceptibility measurements. The method is based on the temporal analysis of the intensity of a light diffraction peak, which arises due to interference at a periodic pattern of gold nanostructures. The presence of bacteria disturbs the constructive interference, leading to an intensity decrease and thus allows the monitoring of bacterial growth in very low volumes. We demonstrate the direct correlation of the decrease in diffraction peak intensity with bacterial cell number starting from single cells and show the capability for rapid high-throughput AST measurements by determining the minimum inhibitory concentration for three different antimicrobials in less than 2-3 h as well as the susceptibility in less than 30-40 min. Furthermore, bacterial mobility is obtained from short-term fluctuations of the diffraction peak intensity and is shown to decrease by a factor of 3 during bacterial attachment to a surface. This multiparameter detection method allows for rapid AST of planktonic and of biofilm-forming bacterial strains in low volumes and in real-time without the need of high initial cell numbers.

Single-Cell Optical Distortion Correction and Label-Free 3D Cell Shape Reconstruction on Lattices of Nanostructures.

Imaging techniques can be compromised by aberrations. Especially when imaging through biological specimens, sample-induced distortions can limit localization accuracy. In particular, this phenomenon affects localization microscopy, traction force measurements, and single-particle tracking, which offer high-resolution insights into biological tissue. Here we present a method for quantifying and correcting the optical distortions induced by single, adherent, living cells. The technique uses periodically patterned gold nanostructures as a reference framework to quantify optically induced displacements with micrometer-scale sampling density and an accuracy of a few nanometers. The 3D cell shape and a simplified geometrical optics approach are then utilized to remap the microscope image. Our experiments reveal displacements of up to several hundred nanometers, and in corrected images these distortions are reduced by a factor of 3. Conversely, the relationship between cell shape and distortion provides a novel method of 3D cell shape reconstruction from a single image, enabling label-free 3D cell analysis.

Exponential size distribution of von Willebrand factor.

Von Willebrand Factor (VWF) is a multimeric protein crucial for hemostasis. Under shear flow, it acts as a mechanosensor responding with a size-dependent globule-stretch transition to increasing shear rates. Here, we quantify for the first time, to our knowledge, the size distribution of recombinant VWF and VWF-eGFP using a multilateral approach that involves quantitative gel analysis, fluorescence correlation spectroscopy, and total internal reflection fluorescence microscopy. We find an exponentially decaying size distribution of multimers for recombinant VWF as well as for VWF derived from blood samples in accordance with the notion of a step-growth polymerization process during VWF biosynthesis. The distribution is solely described by the extent of polymerization, which was found to be reduced in the case of the pathologically relevant mutant VWF-IIC. The VWF-specific protease ADAMTS13 systematically shifts the VWF size distribution toward smaller sizes. This dynamic evolution is monitored using fluorescence correlation spectroscopy and compared to a computer simulation of a random cleavage process relating ADAMTS13 concentration to the degree of VWF breakdown. Quantitative assessment of VWF size distribution in terms of an exponential might prove to be useful both as a valuable biophysical characterization and as a possible disease indicator for clinical applications.

Tracing cell lineages in videos of lens-free microscopy.

In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it an inexpensive tool for label-free, continuous live cell imaging, yet there is only little work on analysing such time-lapse image sequences. We propose (1) a cell detector for LFM images based on fully convolutional networks and residual learning, and (2) a probabilistic model based on moral lineage tracing that explicitly handles multiple detections and temporal successor hypotheses by clustering and tracking simultaneously. (3) We benchmark our method in terms of detection and tracking scores on a dataset of three annotated sequences of several hours of LFM, where we demonstrate our method to produce high quality lineages. (4) We evaluate its performance on a somewhat more challenging problem: estimating cell lineages from the LFM sequence as would be possible from a corresponding fluorescence microscopy sequence. We present experiments on 16 LFM sequences for which we acquired fluorescence microscopy in parallel and generated annotations from them. Finally, (5) we showcase our methods effectiveness for quantifying cell dynamics in an experiment with skin cancer cells.