Nanoparticle tracking analysis (NTA) is a powerful technique for characterizing nanoparticles in suspension. It uses Brownian motion and light scattering principles to determine particle size, concentration, and distribution, making it invaluable for studying biological nanoparticles like extracellular vesicles and viruses.

NTA instrumentation combines laser illumination, microscope optics, and high-speed cameras to track individual particles. The technique offers high-resolution size distributions and sensitivity to small, dilute particles. However, it can face challenges with polydisperse samples and requires careful sample preparation for accurate results.

Principles of nanoparticle tracking analysis

• Nanoparticle tracking analysis (NTA) is a technique used to characterize nanoparticles in suspension, providing information on their size, concentration, and distribution
• NTA relies on the principles of Brownian motion, light scattering, and the relationship between particle size and scattering intensity to analyze nanoparticles in solution
• The technique is particularly useful in the field of nanobiotechnology for studying biological nanoparticles such as extracellular vesicles, viruses, and protein aggregates

Brownian motion of nanoparticles

• Nanoparticles in suspension undergo random motion due to collisions with solvent molecules, a phenomenon known as Brownian motion
• The velocity of Brownian motion is inversely proportional to particle size, with smaller particles exhibiting faster motion compared to larger particles
• NTA tracks the Brownian motion of individual nanoparticles over time to determine their diffusion coefficients and, subsequently, their hydrodynamic diameters using the Stokes-Einstein equation

Light scattering by nanoparticles

• When illuminated by a laser, nanoparticles scatter light in all directions due to their small size relative to the wavelength of the incident light
• The intensity of the scattered light depends on factors such as particle size, refractive index, and laser wavelength
• NTA detects the scattered light from individual nanoparticles using a microscope objective and a high-sensitivity camera, allowing for the visualization and tracking of nanoparticles in real-time

Particle size vs scattering intensity

• The relationship between particle size and scattering intensity is described by the Rayleigh scattering theory for particles much smaller than the wavelength of the incident light
• Scattering intensity is proportional to the sixth power of the particle diameter, meaning that larger particles scatter light more intensely than smaller particles
• This relationship allows NTA to estimate the size of nanoparticles based on their scattering intensity, although the exact relationship may vary depending on the particle material and refractive index

Limitations of light scattering methods

• Light scattering methods, including NTA, have some limitations in characterizing nanoparticles with certain properties
• Particles with low refractive index contrast relative to the solvent may exhibit weak scattering, making them difficult to detect and analyze
• Highly polydisperse samples containing a wide range of particle sizes can lead to biased results, as larger particles may dominate the scattering signal and mask the presence of smaller particles
• Samples with high background scattering, such as those containing protein aggregates or impurities, can interfere with the accurate detection and sizing of nanoparticles

Nanoparticle tracking analysis instrumentation

• NTA instrumentation typically consists of four main components: a laser illumination system, microscope optics, a high-speed digital camera, and software for particle tracking and analysis
• These components work together to enable the visualization, tracking, and characterization of nanoparticles in suspension
• Advances in NTA instrumentation have led to improved sensitivity, resolution, and throughput, expanding the range of applications in nanobiotechnology research

Laser illumination of nanoparticle suspensions

• A laser, typically with a wavelength in the visible or near-infrared range (405 nm, 488 nm, 532 nm, or 635 nm), is used to illuminate the nanoparticle suspension
• The laser beam is focused into a thin sheet or plane within the sample chamber, creating a small illumination volume where nanoparticles can be visualized
• The choice of laser wavelength depends on factors such as the optical properties of the nanoparticles, the presence of fluorescent labels, and the desired scattering intensity

Microscope optics for particle detection

• A microscope objective, typically with a magnification of 20x to 100x, is used to collect the scattered light from the illuminated nanoparticles
• The objective focuses the scattered light onto a high-sensitivity camera, allowing for the visualization of individual nanoparticles in real-time
• The numerical aperture of the objective determines the light-gathering power and the resolution of the system, with higher numerical apertures enabling the detection of smaller nanoparticles

High-speed digital camera for video capture

• A high-speed digital camera, capable of capturing video at frame rates ranging from 10 to 60 frames per second (fps), is used to record the motion of nanoparticles in the sample
• The camera sensor should have high sensitivity and low noise to enable the detection of weak scattering signals from small nanoparticles
• The field of view of the camera determines the number of particles that can be analyzed simultaneously, with larger fields of view enabling higher throughput analysis

Software for particle tracking and analysis

• Specialized software is used to process the captured video frames and track the motion of individual nanoparticles over time
• The software employs particle tracking algorithms to identify and locate nanoparticles in each frame, and then links their positions across consecutive frames to reconstruct their trajectories
• The software calculates various parameters such as particle size, concentration, and size distribution based on the tracked particle trajectories and the principles of Brownian motion and light scattering

Conducting nanoparticle tracking analysis

• Proper sample preparation, optimization of video capture settings, and careful execution of the analysis are crucial for obtaining accurate and reliable results from NTA
• The following steps outline the general procedure for conducting NTA, although specific details may vary depending on the instrument and the nature of the sample

Sample preparation and dilution

• Nanoparticle samples should be prepared in a suitable buffer or solvent that is compatible with the NTA instrument and does not interfere with the scattering signal
• Samples are typically diluted to a concentration range of $10^7$ to $10^9$ particles per mL to ensure optimal particle detection and tracking
• Dilution factors should be chosen carefully to avoid over-dilution (leading to low particle counts) or under-dilution (leading to particle overlap and tracking errors)
• Samples should be filtered or centrifuged to remove large aggregates or debris that may interfere with the analysis

Optimizing video capture settings

• Video capture settings, such as camera level, threshold, and focus, should be optimized for each sample to ensure optimal particle detection and tracking
• The camera level should be adjusted to maximize the contrast between the particles and the background while avoiding pixel saturation
• The threshold setting determines the minimum scattering intensity required for a particle to be detected and should be set to exclude background noise while retaining true particle signals
• The microscope focus should be adjusted to obtain sharp particle images and minimize motion blur

Video recording of nanoparticle motion

• Once the sample is loaded and the video capture settings are optimized, a video of the nanoparticle motion is recorded for a specified duration (typically 30 to 60 seconds)
• Multiple videos may be recorded for each sample to improve statistical accuracy and account for any variability in particle distribution
• Videos should be recorded in a stable environment to minimize vibrations and external disturbances that may affect particle motion

Particle identification and tracking algorithms

• After video recording, the particle identification and tracking algorithms are applied to the captured frames to extract particle trajectories
• The algorithms first identify candidate particles in each frame based on their scattering intensity and size, using techniques such as thresholding and centroid determination
• Particle positions are then linked across consecutive frames using nearest-neighbor or more advanced motion models to reconstruct particle trajectories
• Trajectories are filtered based on criteria such as minimum track length, maximum displacement, and linearity to exclude false positives and incomplete tracks

Data analysis in nanoparticle tracking

• Once particle trajectories have been extracted from the recorded videos, various data analysis steps are performed to characterize the size, concentration, and distribution of the nanoparticles in the sample
• These analyses provide quantitative information on the physical properties of the nanoparticles, which is essential for understanding their behavior and optimizing their performance in nanobiotechnology applications

Particle size distribution calculations

• Particle size distributions are calculated from the tracked particle trajectories using the principles of Brownian motion and the Stokes-Einstein equation
• The mean square displacement (MSD) of each particle is computed from its trajectory, and the diffusion coefficient is estimated from the slope of the MSD curve
• The hydrodynamic diameter of each particle is then calculated from the diffusion coefficient using the Stokes-Einstein equation, which relates particle size to diffusivity and temperature
• The resulting size distribution is typically presented as a histogram or a probability density function, showing the relative abundance of particles of different sizes

Concentration measurements of nanoparticles

• Nanoparticle concentrations are determined by counting the number of particles detected in a known volume of the sample, taking into account the dilution factor and the illumination volume
• The illumination volume is calibrated using standard nanoparticle suspensions of known concentration, allowing for the conversion of particle counts to concentration units (particles per mL)
• Concentration measurements are important for quantifying the total number of particles in a sample, assessing batch-to-batch variability, and comparing different preparation methods or formulations

Statistical analysis of size and concentration

• Statistical parameters such as mean, median, mode, and standard deviation are calculated from the particle size and concentration data to provide a summary of the sample properties
• These parameters can be used to compare different samples, assess the reproducibility of measurements, and monitor changes in particle size or concentration over time
• Advanced statistical tests, such as the Kolmogorov-Smirnov test or the Mann-Whitney U test, may be applied to determine whether two samples have significantly different size distributions or concentrations

Comparison to other sizing techniques

• NTA results are often compared to those obtained from other nanoparticle sizing techniques, such as dynamic light scattering (DLS), electron microscopy, or atomic force microscopy (AFM)
• These comparisons help to validate the accuracy of NTA measurements, identify any discrepancies or biases, and provide a more comprehensive understanding of the sample properties
• Each technique has its own strengths and limitations, and the choice of method depends on factors such as sample type, size range, concentration, and desired information (e.g., hydrodynamic size, core size, or surface properties)

Applications of nanoparticle tracking analysis

• NTA has found widespread applications in various fields of nanobiotechnology, including drug delivery, diagnostics, and biomarker discovery
• The ability of NTA to characterize nanoparticles in their native environment, without the need for extensive sample preparation or modification, makes it particularly suitable for studying biological nanoparticles and their interactions with biomolecules

Characterization of synthetic nanoparticles

• NTA is used to characterize the size, concentration, and polydispersity of synthetic nanoparticles such as liposomes, polymeric nanoparticles, and inorganic nanoparticles (gold, silver, iron oxide)
• These nanoparticles are often used as drug delivery vehicles, contrast agents, or biosensors, and their physical properties strongly influence their performance and safety
• NTA allows for the optimization of nanoparticle synthesis and formulation, ensuring that the desired size and concentration are achieved and that the particles remain stable over time

Extracellular vesicle and exosome analysis

• Extracellular vesicles (EVs), including exosomes, are cell-derived nanoparticles that play important roles in intercellular communication and have emerged as promising biomarkers and therapeutic agents
• NTA is widely used to characterize the size, concentration, and heterogeneity of EV preparations, providing valuable information on their biogenesis, cargo, and biological functions
• EV analysis by NTA has applications in cancer diagnosis, monitoring of disease progression, and development of EV-based therapies

Monitoring of nanoparticle stability

• NTA can be used to monitor the stability of nanoparticle suspensions over time, detecting changes in size distribution, concentration, or aggregation state
• Stability assessment is crucial for ensuring the quality and safety of nanoparticle-based products, such as nanomedicines or diagnostic reagents
• NTA measurements can be performed at different time points, storage conditions, or in the presence of various stressors (pH, temperature, ionic strength) to evaluate the robustness and shelf life of nanoparticle formulations

Quality control in nanomedicine development

• NTA is increasingly used as a quality control tool in the development and manufacturing of nanomedicines, such as liposomal drugs, protein nanoparticles, or gene delivery vectors
• By providing rapid and reliable characterization of nanoparticle size, concentration, and consistency, NTA helps to ensure that the manufactured products meet the required specifications and regulatory standards
• NTA can be integrated into the quality control workflow, allowing for the screening of raw materials, monitoring of the production process, and final product release testing

Advantages and limitations

• NTA offers several unique advantages over other nanoparticle characterization techniques, but it also has some limitations that should be considered when interpreting the results and designing experiments
• Understanding the strengths and weaknesses of NTA is essential for selecting the most appropriate method for a given application and for critically evaluating the data obtained

High resolution size distributions

• One of the main advantages of NTA is its ability to provide high-resolution size distributions of nanoparticles, with a typical size range of 10 nm to 2000 nm
• The individual particle tracking approach allows for the detection and sizing of nanoparticles that may be overlooked by ensemble techniques such as DLS, which are biased towards larger particles
• The high resolution of NTA is particularly valuable for studying polydisperse samples or for detecting small subpopulations of particles with distinct sizes

Measurements in native environments

• NTA can be performed directly in the native environment of the nanoparticles, such as cell culture media, plasma, or other biological fluids
• This capability is important for studying the behavior and interactions of nanoparticles in physiologically relevant conditions, without the need for extensive sample purification or dilution
• Measuring nanoparticles in their native environment helps to preserve their original size, shape, and surface properties, which may be altered by sample preparation steps required for other techniques

Sensitivity to small and dilute particles

• NTA is highly sensitive to small and dilute nanoparticles, with a lower detection limit of around $10^7$ particles per mL
• This sensitivity allows for the characterization of low-abundance nanoparticles, such as rare extracellular vesicles or protein aggregates, which may be difficult to detect by other methods
• The ability to analyze dilute samples is particularly useful for studying nanoparticles in biological fluids or for monitoring the early stages of nanoparticle formation or aggregation

Challenges with polydisperse samples

• While NTA provides high-resolution size distributions, the analysis of highly polydisperse samples can be challenging due to the limited dynamic range of the technique
• In samples containing a wide range of particle sizes, the scattering signal from larger particles may dominate and mask the presence of smaller particles, leading to an underestimation of their contribution to the size distribution
• Polydisperse samples may require multiple measurements at different dilutions or camera settings to capture the full size range, which can be time-consuming and may introduce additional variability

Need for careful sample preparation

• NTA measurements are sensitive to sample preparation conditions, such as dilution factor, buffer composition, and presence of impurities or aggregates
• Improper sample preparation can lead to artifacts in the size distribution, such as false peaks or shifts in the mean size, which may be misinterpreted as real sample properties
• Careful optimization of sample preparation protocols, including filtration, centrifugation, or buffer exchange, is necessary to ensure reliable and reproducible NTA results
• The need for sample-specific optimization can limit the throughput of NTA and may require significant method development efforts for new sample types