Hello and welcome. My name is Michele Trott,
and I am a scientific content writer here at Izon Science.
As you probably know,
a wide range of analytical methods are used within the fields of nanoparticle and extracellular vesicle research.
But are these technologies suited to the analysis of complex, biological samples?
And what are the limitations of these techniques?
Today, I will be discussing a study that tackles these questions.
This work was a collaborative effort by researchers from across six countries
and was published in the Journal of Extracellular Vesicles in January 2021.
Today, I will cover the study’s rationale, the study approach, and a few key results.
So, what prompted the study?
Well, there is a lot of academic, industry and public interest in nanoparticles.
With the massive global issue of plastic overload,
there are questions around what regulations can be brought in to help.
Work is underway to quantify and understand the impact of plastic nanoparticles on our health and the environment.
Researchers are interested in naturally existing extracellular vesicles (or EVs) for their therapeutic and diagnostic potential.
Synthetic nanoformulations are being pursued for drug delivery purposes,
as well as other nanoparticle-based applications.
To make progress in these areas, we need to accurately and confidently characterise complex samples.
And not just samples where all the particles are about the same size.
I mean heterogenous, polydisperse samples where particles might have a different charge, shape, size, or composition.
To provide researchers in the field with insights on the merits and drawbacks of different platforms,
the group decided to take a closer look at common methods used for nanoparticle analysis.
How was this study executed?
It is probably best summarised by breaking down the title.
Here, you can see that particle concentration was measured.
There were multimodal samples, meaning samples contained particles of different size.
The study included both synthetic particles and extracellular vesicles.
And, orthogonal methods were used
these are methods that are based on fundamentally different principles.
The methods compared were tunable resistive pulse sensing, or TRPS.
Nanoparticle tracking analysis, NTA.
Multi-angle dynamic light scattering, MADLS.
Nano flow cytometry.
Centrifugal liquid sedimentation,
or CLS,
and asymmetrical flow field flow fractionation coupled with multi-angle light scattering,
or AF4-MALS.
Analytical techniques were put to the test using a four-stage,
stepwise approach,
where sample complexity was increased incrementally.
The simplest analytes were monomodal samples of NIST-traceable polystyrene particles
so all particles were the same size.
To mimic the size distribution of an EV-containing plasma sample,
the group used bimodal, trimodal,
and quadrimodal mixtures of polystyrene particles.
Then, to validate the protocols with traceable standards,
the group included a well-characterised,
monodisperse, liposome sample.
Finally, an EV-containing plasma sample was prepared using size exclusion chromatography.
Measurements were evaluated using plasma samples containing EVs across two size ranges,
80-250 and 50-400 nm.
Moving onto the results.
First, I want to share a few key findings from the analysis of synthetic particles.
Not all techniques could provide accurate size and concentration measurements,
and their limitations were revealed at different levels of complexity.
For monomodal samples, where particles were the same size, all techniques performed similarly.
However, this was not the case for the more complex, polydisperse samples.
For example, when MADLS was used to analyse a bimodal sample of 100 and 200 nm particles,
the results did not reflect what was actually in the sample.
Rather than showing two peaks representative of different subpopulations,
MADLS showed a broad distribution of particles.
For AF4-MALS, the expected 1:1 ratio of 100 and 200 nm particles was skewed.
A trimodal mixture containing equal parts of 60, 100,
and 150 nm particles could only be fully resolved using TRPS and nano flow cytometry.
For this particular trimodal mixture, NTA massively underestimated the proportion of 60 nm particles.
Instead of confirming a 1:1:1 ratio
(with each particle size comprising 33.3% of the population),
NTA underestimated the proportion of 60 nm particles to be only 2-5%,
and this happened on multiple occasions.
Meanwhile, AF4-MALS completely failed to detect the 60 nm particles.
When faced with a quadrimodal mixture, it was only TRPS, CLS,
and AF4-MALS that clearly resolved the subpopulations.
While nano flow cytometry was able to resolve the quadrimodal mixture,
a size shift across repeated measurements caused resolution to be lost when results were averaged.
Overall, this part of the study included ten samples comprising polystyrene particles of varying sizes,
ratios, and number of subpopulations.
With these synthetic samples,
TRPS showed good repeatability,
with concentration measurements falling within 10% of the nominal concentration,
compared to 60% for NTA.
This figure shows the concentration of particles plotted against particle diameter.
TRPS data is shown at the top, with four, clearly defined subpopulations.
NTA data is in the middle, where only three subpopulations were detected with poor resolution.
At the bottom, MADLS shows no evidence of the four subpopulations in the sample.
Now, moving onto the liposome analysis.
Here, the theoretical number-based concentration was in good agreement
with the mean concentration value derived from TRPS,
NTA and AF4-MALS.
These three techniques also produced similar size values that were within 10% of the nominal diameter.
Although AF4-MALS did produce precise size and concentration measurements for the liposomes,
the authors noted a high level of uncertainty with this technique.
That is because nanoparticle optical properties are taken into account when calculating a concentration value for AF4-MALS.
Specifically, this is the refractive index of the nanoparticles,
and it is a value that is difficult to calculate for non-uniform biological samples such as those containing EVs.
So, it’s important to note that slight changes to the refractive index estimate
can change the calculated concentration value by an order of magnitude for AF4-MALS.
CLS could not characterise the liposome sample,
partly because the difference in density between liposome particles and sucrose gradient was insufficient for analysis.
Nano flow cytometry underestimated liposome concentration and particle diameter.
And now, for the most complex sample analysed in the study, we have results from the EV-containing plasma sample.
Here, the most repeatable measurements were obtained using TRPS,
where triplicate measurements produced a coefficient of variation of less than 10%.
This contrasts with NTA, where the CV was closer to 20%.
And we can’t comment on the nano flow cytometry repeatability because it was only performed once.
Again, not all techniques produced sound measurements of the plasma sample.
Given that MADLS failed to resolve a quadrimodal sample containing particles in the size range of EV isolates,
plasma analysis was not attempted.
EV concentration could not be measured using AF4-MALS, as the authors could not obtain a sample recovery above 70%.
This was somewhat surprising as authors from two different lab groups followed a recently published protocol that should have enabled the measurement of EV isolates.
One possible explanation is that the EV concentration was too low for AF4-MALS on this occasion.
CLS concentration measurements were two orders of magnitude higher than values for TRPS, NTA and nano flow cytometry.
The authors put this down to the fact that CLS measurements require a substantial amount of post-processing.
To achieve this, the sample composition and size range needs to be known in advance.
In this case, a high level of noise in the primary data may have led to artefacts in
particle size distribution for the CLS assessment of EV isolates.
In summary
To bring nanoparticle and EV-related applications to life,
size and concentration must be measured in a way that is standardised and reproducible.
The methods used should be well suited to analysing the sample in question.
Here, Vogel and colleagues revealed critical limitations,
such as the inability of NTA to detect 60 nm particles,
and the critical lack of resolution shown by NTA and MADLS when faced with quadrimodal samples.
Other limitations include the need for prior knowledge of particle density when working with CLS,
and the size shift observed across repeat analysis with nano flow cytometry.
Overall TRPS gave a very strong performance,
enabling reproducible size and concentration measurements to be obtained
for polystyrene mixtures, liposomes, and EV isolates.
To finish, I would like to thank you for watching and I encourage you to read the full text and the written summary of this study.
Both of these can be found by following the links below..