Dynamic Light Scattering
How it works
Particles suspended in solution move constantly and randomly under Brownian motion, with smaller particles diffusing faster than larger ones. DLS illuminates the sample with a laser and records the scattered light at a fixed angle over time; because the particles are constantly moving, the scattered light intensity fluctuates, and the instrument computes an autocorrelation function of those fluctuations. Fast fluctuations decay the correlation function quickly and correspond to small, fast-diffusing particles; slow fluctuations decay it slowly and correspond to larger, slower particles. Fitting that decay to the Stokes-Einstein relationship converts the measured diffusion coefficient into a hydrodynamic radius — the radius of an equivalent sphere with the same diffusion behaviour — for each particle population present.
What you measure
The core output is a size distribution (intensity-weighted by default, since scattering intensity scales with the sixth power of particle diameter) reported as a Z-average hydrodynamic size and a polydispersity index (PDI): a PDI below roughly 0.1 indicates a highly monodisperse sample, below about 0.25 is generally considered acceptably monodisperse for most protein applications, and higher values flag a broad or multi-modal distribution. Because the intensity distribution is so heavily weighted toward larger particles, even a very small population of aggregates — invisible in a concentration or absorbance measurement — can appear as a distinct, well-separated peak, which is exactly what makes DLS such a sensitive first screen for aggregation.
A typical experiment
Samples are filtered (typically through a 0.2–0.45 µm membrane) immediately before measurement to remove dust and large debris that would otherwise dominate the intensity-weighted signal and distort the result, then equilibrated to the measurement temperature — inadequate thermal equilibration is one of the most common sources of poor reproducibility. A measurement itself takes on the order of a minute or two per sample and needs only a small volume, which is why DLS is used as a rapid, non-destructive check throughout a workflow — screening buffer conditions, following a purification, or monitoring a formulation over a stability time-course — rather than reserved for a single end-point measurement.
Applications
Aggregation screening & QC. DLS is the routine first check for protein and antibody aggregation across development and manufacturing, flagging samples that need slower, more resolving follow-up techniques such as AUC.
Formulation development. Comparing size and PDI across candidate buffers, pH values and excipients through pre-formulation and stability studies identifies conditions that keep a biologic monodisperse over time.
Refolding & process monitoring. DLS tracks inclusion-body solubilization and the refolding of recombinant proteins during downstream processing, and is used as an in-process check during vaccine and biologic manufacturing.
Nanoparticle & viral vector sizing. Beyond proteins, DLS sizes nanoparticle drug carriers and can flag aggregates in viral vector preparations such as AAV, alongside particle-count methods for confirmatory sizing.
Strengths & limitations
DLS cannot resolve two populations that differ in size by much less than a factor of roughly three to five, so closely spaced species (for instance monomer and a small conformational variant of similar size) may appear as one broadened peak rather than two distinct ones; and at higher sample concentrations, multiple scattering — light scattered more than once before reaching the detector — biases the apparent size and increases apparent polydispersity, an effect distinct from real aggregation that has to be recognized rather than mistaken for it. DLS also cannot identify what a detected species is chemically, only its apparent size — which is why a DLS flag is typically followed up with an identity- or count-resolving technique such as AUC or SEC. Its strength is the opposite side of that trade-off: minimal sample preparation, a measurement in minutes, and enough sensitivity to catch the first sign of trouble before it shows up anywhere else.
Frequently asked questions
How much sample do I need, and how concentrated?
Very little. The low-volume quartz cuvette takes 12 µl, the small disposable cuvettes 45 µl, and a standard measurement in a general-purpose cell around 70 µl. The sample comes back afterwards, since nothing is consumed.
Concentration scales inversely with size, because scattering rises steeply with particle volume. A working estimate for proteins is 1.44/MW(kDa) mg/ml as a lower limit: about 0.6 mg/ml for a 10 kDa protein, about 0.06 mg/ml for a 100 kDa one. Most people work between 0.5 and 2 mg/ml, and data quality improves with concentration until you reach the point where the particles start to interact and the apparent size begins to fall. For a new sample a two- or three-point concentration series is the safe way to check that you are not in that regime.
How should I prepare the sample?
Filter or spin it, then handle it as if it were an optics sample rather than a biochemistry sample.
Dust is the main enemy. A single 1 µm particle drifting through the beam scatters as much as a million 10 nm proteins and produces the spikes and jumping baselines that ruin a correlogram. Filter the buffer at 0.02-0.1 µm, filter or centrifuge the sample — 10 minutes at 15 000 g is often enough, and gentler than forcing a fragile complex through a membrane — and pipette slowly to avoid bubbles.
Cuvettes must be clean and handled by the frosted faces. Detergents left from washing show up as a micelle peak around 5-10 nm and look convincingly like a protein.
What do the results actually say?
The primary measurement is the intensity autocorrelation function. From it a cumulant fit gives the z-average hydrodynamic diameter and the polydispersity index PdI, and a distribution analysis gives peaks in intensity, which can be converted to volume and number distributions using the refractive index of the material.
For proteins the rules of thumb are: PdI below 0.1 means a monodisperse sample; 0.1-0.4 means moderately polydisperse and usually still interpretable; above 0.4 the distribution analysis is not meaningful and only the presence of large material can be reported. A percent polydispersity below 20% is the corresponding criterion in the protein-specific analysis.
The hydrodynamic diameter is the diameter of a sphere with the same diffusion coefficient as your particle, including its hydration shell. For an elongated or flexible protein this is systematically larger than the crystallographic dimensions, which is a property of the quantity and not an artefact.
Can DLS give me the molecular weight and the oligomeric state?
Not properly, and this is the most common misunderstanding about the technique.
DLS measures a diffusion coefficient. Converting it to a mass requires assuming a shape, and the standard conversion assumes a compact globular particle. For a well-behaved globular protein the estimate lands within a factor of two or so; for anything elongated, disordered, glycosylated or multi-domain it can be off by a factor of several. A monomer-dimer distinction needs a size ratio the method cannot deliver reliably, because two species have to differ by roughly a factor of 3-5 in diameter before DLS resolves them as separate peaks at all.
If oligomeric state is the question, SEC-MALS or AUC answers it. DLS is the right tool for a different question: is this sample aggregated, and how badly.
Why does a sample that looks clean on SDS-PAGE give a bad DLS result?
Because the two techniques weight the sample completely differently. Scattered intensity goes roughly as the sixth power of diameter, so a 100 nm aggregate scatters about a million times more than a 10 nm monomer. A contamination of 0.01% by mass in the form of large aggregates can dominate the intensity distribution and hide the monomer entirely.
This sensitivity is the point of the measurement, not a flaw. DLS is the cheapest way to find out, before you commit protein to a crystallisation screen, a cryo-EM grid or an SPR chip, that a fraction of your preparation is aggregated. A gel does not see it, and a SEC column may retain it on the frit.
Interpreting the numbers with this in mind: the intensity distribution tells you what is there, the volume distribution tells you how much of it there is, and the two often look very different for a sample with a small aggregate population.
What do you need to know about my buffer?
The viscosity and refractive index of the solvent, because the diffusion coefficient is converted to a size through the Stokes-Einstein relation and both enter directly. For standard aqueous buffers below 200 mM the water values are close enough.
Beyond that they are not. Ten percent glycerol raises viscosity by roughly 30%, and a size calculated with the water value would be 30% too large. Sucrose, high salt, urea and guanidinium all need their own values, so send the exact composition and we use tabulated or measured viscosities.
Detergents deserve a separate mention: above the CMC you will see the micelle population, typically 3-10 nm, alongside your protein. That is a genuine measurement of what is in the tube, but it can be mistaken for a protein species if nobody says the detergent is there.
Can you use DLS to test stability or find a better buffer?
A temperature ramp is one of the standard uses. Following size and count rate from 20 to 80 °C gives the aggregation onset temperature, and comparing that across buffers, pH values and additives is a fast way to rank formulations with milligram quantities of protein.
The same ramp distinguishes two failure modes that get confused: a protein that unfolds and then aggregates, and a protein that stays folded but aggregates colloidally at high concentration. Combining a DLS ramp with a nanoDSF melting curve on the same conditions separates conformational from colloidal stability, and the two do not always move in the same direction.
Isothermal measurements over hours also work for slow aggregation — a sample held at 37 °C and measured every ten minutes gives a growth curve.
What can you measure besides proteins?
Liposomes, nanodiscs, extracellular vesicles, virus-like particles, polymer and inorganic nanoparticles, micelles, nucleic acids and their complexes. The working range runs from roughly 0.3 nm to a few micrometres, with the upper end limited by sedimentation of the particles out of the beam during the measurement.
Zeta potential is available on the same instrument for colloidal samples. It needs more material — around 750 µl in a folded capillary cell — and low ionic strength, since a physiological salt buffer both screens the surface charge and heats up under the applied field. Samples are usually measured in 1-10 mM salt for that reason.
Membrane proteins in detergent are measurable, though the micelle signal has to be accounted for; a matched empty-micelle control is worth sending.
How long does it take, and do I get my sample back?
A single measurement is three runs of ten to fifteen seconds each, so under a minute of acquisition; with equilibration at temperature and cuvette handling, a few minutes per sample. A temperature ramp of 20-80 °C in 2 °C steps takes one to two hours.
The sample is untouched by the measurement and can be recovered, minus what stays in the cuvette. If it is precious, say so and we will use the quartz low-volume cell and return it.
Because the measurement is fast and cheap in material, it is worth running DLS as a first check on any sample that will then go into a longer experiment, and we often do it as a matter of course before ITC or SPR.
Can I run the measurements myself?
DLS is the easiest instrument here to learn to operate, and the hardest to interpret carelessly. A session or two covers cuvette handling, the standard operating procedures and the acquisition settings.
The part that takes longer is knowing when to distrust a result: number fluctuations from too few particles, a correlogram that does not decay to baseline, an intensity peak at 1000 nm that is one dust particle rather than a population, a second peak that the software reports at 45% because the volume conversion used the wrong refractive index. We go through those cases with the data rather than in the abstract.
Sending samples as a service works equally well, and the report includes the correlograms so that you can see for yourself whether the fit deserves belief.
Instruments
Zetasizer