Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles

Abstract

Label-free characterization of single biomolecules aims to complement fluorescence microscopy in situations where labeling compromises data interpretation, is technically challenging or even impossible. However, existing methods require the investigated species to bind to a surface to be visible, thereby leaving a large fraction of analytes undetected. Here, we present nanofluidic scattering microscopy (NSM), which overcomes these limitations by enabling label-free, real-time imaging of single biomolecules diffusing inside a nanofluidic channel. NSM facilitates accurate determination of molecular weight from the measured optical contrast and of the hydrodynamic radius from the measured diffusivity, from which information about the conformational state can be inferred. Furthermore, we demonstrate its applicability to the analysis of a complex biofluid, using conditioned cell culture medium containing extracellular vesicles as an example. We foresee the application of NSM to monitor conformational changes, aggregation and interactions of single biomolecules, and to analyze single-cell secretomes.

Simultaneous Sizing and Refractive Index Analysis of Heterogeneous Nanoparticle Suspensions

“…As an alternative route, similar enhanced nanoparticle sizing performances have recently been achieved by either recording small imaging volumes at very high acquisition frame rates 18 or by combining high acquisition frame rates with 1D confinement inside a nanochannel. 19 It is important to remark that neither of these routes are mutually exclusive, i.e., large imaging volumes and high frame rate acquisition, and the main difference between them is how the track length increase scales with respect to the approach. In the case of volume extension, the average increase in trajectory length scales quadratically, whereas improving the temporal resolution does so linearly.…”

“…In principle, holoNTA is entirely compatible with high temporal resolution. Despite having an overall temporal resolution on the order of 10 ms, as determined by the frame time of the camera, all experiments were performed with sensor integration times of 20–100 μs, analogous to Kashkanova et al 18 and Špačková et al, 19 which directly translates to >10 kHz frame rates. Our approach uses off-the-shelf industrial sensors and does not require nanofabrication, and as such we envision direct applications of our methodology for routine quantification and sizing in diverse fields of both fundamental and applied nature, ranging from heterogeneous catalysis over fundamental biology into the clinic.…”

“…These particles rapidly traverse the quasi two-dimensional observation plane of a conventional microscope within a few camera frames, which dramatically degrades the sizing precision. Solutions to the issue of finite track lengths have been explored in the form of high speed acquisitions, 18 volume confinement via nanofluidic channels, 19 or lock-on detection. 20 However, in the absence of specialized hardware, holographic sensing-platforms with immobilized particles are often the only option for sizing small NPs.…”

Single planar photonic chip with tailored angular transmission for multiple-order analog spatial differentiator

“…This dielectric multilayer structure does not require precise nanofabrication procedures and can be manufactured on a large scale at low cost. The chip working as spatial differentiator offers the advantage of a multifunctional wave-based analogue computing ability, thus it will provide a route for designing fast, power-efficient, compact and low-cost devices used in edge detection and optical image processing, and offers opportunities for the rapid developing research field where the engineered substrates are proposed to enhance the imaging performance of the conventional optical microscope 12,[42][43][44][45][46][47][48] .…”

Single-shot self-supervised object detection in microscopy

“…Thus, acquiring the needed experimental datasets in house is often the only viable option, but it comes with its own burdens in terms of time and effort. As a consequence, most deep-learning methods for object detection rely on synthetic data [7][8][9][10][11] . However, accurate synthetic replication of experimental data is very challenging, even for relatively simple transmission microscopes 2 .…”