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The efficacy and subsequent success of a pharmaceutical is strongly dependent on its shelf life and its stability under tar- geted solution conditions. A typical man- ifestation of formulation instability is an increase in particle size, due to aggrega- tion of the analyte or carrier. As the par- ticle size increases, efficacy is diminished, primarily due to the decrease in the active surface area. Because of the corre- lation between efficacy and size, particle sizing is quickly becoming a routine step in the development of more stable and effective formulations. Dynamic light scattering (DLS), also known as photon correlation spectroscopy (PCS) and quasi-elastic light scattering (QELS), provides many advantages as a particle size analysis method. DLS is a non- invasive technique that measures a large population of particles in a very short time period, with no manipulation of the sur- rounding medium. Modern DLS instru- ments, notably the Zetasizer Nano system (Malvern Instruments, Southborough,
The efficacy and subsequent success of a
pharmaceutical is strongly dependent on
its shelf life and its stability under tar-
geted solution conditions. A typical man-
ifestation of formulation instability is an
increase in particle size, due to aggrega-
tion of the analyte or carrier. As the par-
ticle size increases, efficacy is diminished,
primarily due to the decrease in the
active surface area. Because of the corre-
lation between efficacy and size, particle
sizing is quickly becoming a routine step
in the development of more stable and
effective formulations.
Dynamic light scattering (DLS), also
known as photon correlation spectroscopy
(PCS) and quasi-elastic light scattering
(QELS), provides many advantages as a
particle size analysis method. DLS is a non-
invasive technique that measures a large
population of particles in a very short time
period, with no manipulation of the sur-
rounding medium. Modern DLS instru-
ments, notably the Zetasizer Nano system
Malvern Instruments, Southborough,
MA), can measure particle sizes as small as
0.6 nm and as large as 6 µm across a wide
range of sample concentrations. Because of
the sensitivity to trace amounts of aggre-
gates and the ability to resolve multiple
particle sizes, DLS is ideally suited for
macromolecular applications necessitating
low sample concentration and volume,
such as the development of stable food,
drug, and surfactant formulations and in
the screening of protein samples for crys-
tallization trials.
Particles and macromolecules in solution
undergo Brownian motion. Brownian
motion arises from collisions between the
particles and the solvent molecules. As a
consequence of this particle motion, light
scattered from the particle ensemble will
fluctuate with time. In DLS, these fluctua-
tions are measured across very short time
intervals to produce a correlation curve,
from which the particle diffusion coeffi-
cient (and subsequently the particle size)
is extracted.
In contrast to separation techniques, where
particles are separated and then counted, in the
DLS technique, all of the size information for
the ensemble of particles is contained within a
single correlation curve. As such, particle size
resolution requires a deconvolution of the data
contained in the measured correlation curve.
While standard algorithms exist for transform-
ing the correlation curve to a particle size distri-
bution, an understanding of the precision and
accuracy of the distribution necessitates a solid
understanding of the underlying principles
behind the DLS technique itself. This article
presents a brief overview of the DLS tech-
nique, along with common algorithms used
to deconvolute the size distribution from
the measured correlation curve.
Dynamic light scattering
Light scattering is a consequence of the
interaction of light with the electric field
of a particle or small molecule. This in-
teraction induces a dipole in the particle
electric field that oscillates with the same
frequency as that of the incident light.
Inherent to the oscillating dipole is the
acceleration of charge, which leads to
the release of energy in the form of scat-
tered light.
For a collection of solution particles illu-
minated by a monochromatic light source
such as a laser, the scattering intensity
measured by a detector located at some
point in space will be dependent on the
relative positions of the particles within
the scattering volume. The scattering
volume is defined as the crossover section
of the light source and the detector
optics. The position dependence of the
scattering intensity arises from construc-
tive and destruction interference of the
scattered light waves. If the particles are
static, or frozen in space, then one would
expect to observe a scattering intensity
that is constant with time, as described in
Figure 1. In practice, however, the parti-
cles are diffusing according to Brownian
motion, and the scattering intensity fluc-
tuates about an average value equivalent
to the static intensity. As detailed in
Figure 1, these fluctuations are known as
the dynamic intensity.
Across a long time interval, the dynamic
signal appears to be representative of ran-
dom fluctuations about a mean value.
When viewed on a much smaller time
scale, however (
Figure 2), it is evident that
the intensity trace is in fact not random,
but rather comprising a series of continu-
ous data points. This absence of disconti-
nuity is a consequence of the physical
confinement of the particles in a position
very near to the position occupied a very
short time earlier. In other words, on short
time scales, the particles have had insufficient
time to move very far from their initial posi-
tions, and as such, the intensity signals are very
similar. The net result is an intensity trace that
is smooth, rather than discontinuous.
A Primer on Particle Sizing Using
Dynamic Light Scattering
by Kevin Mattison, Ana Morfesis, and Michael Kaszuba
Figure 1 Schematic detailing the scattering volume and subsequent static and
dynamic light scattering intensities.
Figure 2 Intensity time trace showing the lack of discontinuity expected for a
random signal when viewed across a short time interval.
Correlation is a second-order sta-
tistical technique for measuring
the degree of nonrandomness in
an apparently random data set.
When applied to a time-depend-
ent intensity trace, as measured
with DLS instrumentation, the
correlation coefficients,
G(τ), are
calculated as shown in Eq. (1),
t is the initial (start) time
τ is the delay time.
G(τ) =
I(t)I(t + τ)dt (1)
As a summation, the correlation equa-
tion can be expressed as shown in Eq.
(2), or expressed in a tabular format as
shown in
Table 1.
) =
+ τ
) (2)
Typically, the correlation coefficients
are normalized, such that
G() = 1.
For monochromatic laser light, this
normalization imposes an upper corre-
lation curve limit of 2 for
) and a
lower baseline limit of 1 for
G(). In
practice, however, the upper limit can
only be achieved for carefully opti-
mized optical systems. Typical experi-
mental upper limits are approx.
In DLS instrumentation, the correla-
tion summations are performed using
an integrated digital correlator,
which is a logic board comprising
operational amplifiers that continu-
ally add and multiply short time scale
fluctuations in the measured scatter-
ing intensity to generate the correla-
tion curve for the sample. Examples
of correlation curves measured for
two submicron particles are given in
Figure 3. For the smaller and hence
faster diffusing protein, the measured
correlation curve has decayed to
baseline within 100 µsec, while the
larger and slower diffusing silicon
dioxide particle requires nearly 1000
µsec before correlation in the signal is
completely lost.
Hydrodynamic size
All of the information regarding the
motion or diffusion of the particles in the
solution is embodied within the measured
correlation curve. For monodisperse samples,
consisting of a single particle size group, the
correlation curve can be fit to a single expo-
nential form as given in Eq. (3), where
B is
the baseline,
A is the amplitude, and D is the
diffusion coefficient. The scattering vector
q) is defined by Eq. (4), where ñ is the sol-
vent refractive index,
is the vacuum
wavelength of the laser, and
θ is the scatter-
ing angle.
G(τ) =
I(t)I(t + τ)dt =
+ A e
q = sin
The hydrodynamic radius is
defined as the radius of a hard
sphere that diffuses at the same
rate as the particle under exami-
nation. The hydrodynamic radius
is calculated using the particle
diffusion coefficient and the
Stokes-Einstein equation given in
Eq. (5), where
k is the Boltzmann
T is the temperature, and η
is the solvent viscosity.
A single exponential or Cumulant fit
of the correlation curve is the fitting
procedure recommended by the
International Standards Organization
(ISO). The hydrodynamic size ex-
tracted using this method is an aver-
age value, weighted by the particle
scattering intensity. Because of the
intensity weighting, the Cumulant
size is defined as the Z average or
intensity average.
While the Cumulant algorithm and the
Z average are useful for describing gen-
eral solution characteristics, for multi-
modal solutions, consisting of multiple
particle size groups, the Z average can be
misleading. For multimodal solutions, it
is more appropriate to fit the correlation
curve to a multiple exponential form,
using common algorithms such as CON-
TIN or Non Negative Least Squares
(NNLS). Consider, for example, the cor-
relation curve shown in
Figure 4. This
correlation curve, measured for a 10-
mg/mL lysozyme sample in 100 m
NaCl at 69 °C, clearly exhibits two ex-
ponential decays, one for the fast-mov-
ing monomer at 3.5 nm and one for the
slow-moving aggregate at 388 nm. The
size distribution shown in Figure 4 was
derived using the CONTIN algorithm.
When the single exponential Cumulant
algorithm is used, a Z average of 12.4 nm
is indicated, which is clearly inconsis-
tent with the distribution results.
System scope
The Zetasizer Nano system (Figure 5) includes
the hardware and software for combined dy-
namic, static, and electrophoretic light scatter-
ing measurements, giving the researcher a wide
range of sample properties, including the size,
molecular weight, and zeta potential. The sys-
tem was designed specifically to meet the low
concentration and sample volume requirements
typically associated with pharmaceutical and
biomolecular applications, along with the high
concentration requirements for colloidal appli-
cations. Satisfying this unique mix of require-
Table 1 Correlation coefficient equations for selected k index values
k Intensity Correlation coefficient
0 I(t
) G
) = I(t
) + I(t
) + I(t
) + + I(t
) G
) = I(t
) + I(t
) + I(t
) + + I(t
) G
) = I(t
) + I(t
) + I(t
) + + I(t
) G
) = I(t
Figure 3 Intensity correlation curves for ovalbumin and silicon dioxide, measured with a
Zetasizer Nano ZS static, dynamic, and electrophoretic light scattering instrument.
Figure 4 Correlation curve and CONTIN distribution for 10-mg/mL lysozyme in 100 mM
NaCl at 69 °C, measured with a Zetasizer Nano ZS static, dynamic, and electrophoretic light scat-
tering system. The Z average of 12.4 nm is indicated by the solid line in the distribution results.
Figure 5 The Zetasizer Nano, a combined static,
dynamic, and electrophoretic light scattering system.
ments was accomplished via the integration of a
backscatter optical system and the design of a
novel cell chamber. As a consequence of these
features, the system specifications for sample
size and concentration are noteworthy, with a
size range of 0.6 nm to 6 µm and a concentra-
tion range of 0.1 mg/mL lysozyme to 40%
wt/vol. Also, the Zetasizer hardware is self opti-
mizing, and the software includes a “one click”
measure, analyze, and report feature designed to
minimize the new user learning curve.
Additional reading
Benight AS, Wilson DH, Budzynski DM, Goldstein RF.
Dynamic light scattering investigations of RecA self-
assembly and interactions with single strand DNA.
Biochimie 1991; 73(2–3):143–55.
Brown RGW. Miniature laser light scattering instrumentation
for particle size analysis. Appl Opt 1990; 29(28):1.
D’Arcy A. Crystallizing proteins—a rational approach. Acta
Cryst 1994; D50:467–71.
Fusett F, Dijkstra BW. Purification and light-scattering analy-
sis of penicillin-binding protein 4 from
Escherichia coli.
Microbiol Drug Res 1996; 2(1):73–6.
Hutchinson FJ, Francis SE, Lyle IG, Jones MN. The charac-
terization of liposomes with covalently attached proteins.
Biochim Biophys Acta 1989; 978(1):17–24.
Moradian-Oldak J, Leung W, Fincham AG. Temperature and
pH-dependent supramolecular self-assembly of amelogenin
molecules: a dynamic light-scattering analysis. J Struct Biol
1998; 122(3):320–7.
Phillies GD. Quasielastic light scattering. Anal Chem 1990;
Pecora R. Dynamic light scattering: applications of photon cor-
relation spectroscopy. Plenum Press, 1985.
Piekenbrock T, Sackmann E. Quasielastic light scattering study
of thermal excitations of F-actin solutions and of growth
kinetics of actin filaments. Biopolymers 1992; 32(11):
Sam T, Pley C, Mandel M. A hydrodymanic study with quasi-
elastic light scattering and sedimentation of bacterial elongation
factor EF-Tu.guanosine-5
-diphosphate complex under nonas-
sociating conditions. Biopolymers 1990; 30(3–4):299–308.
Santos NC, Sousa AMA, Betbeder D, Prieto M, Castanho
MARB. Structural characterization of organized systems
of polysaccharides and phospholipids by light scattering,
spectroscopy, and electron microscopy. Carbohyd Res
1997; 300(1):31–40.
The authors are with
Malvern Instruments, 10 Southville Rd.,
Southborough, MA 01772, U.S.A.; tel.: 508-480-0200; fax:
508-460-9692; e-mail:; home page:
... As mentioned earlier, the purpose of this work is to examine the effect of the model employed in solving the inverse problem on the solutions obtained. To achieve this objective, then the experimentally measured scattering intensityĨ * will be simulated with the model for infinitely long cylinders by means of Eq. (17). Then a different scattering intensityĨ will be calculated using the Mie model for spherical particles. ...
... However, when the needle-like particles are aligned with the flow field, then the incoming monochromatic light will hit the particles within some restricted angles to their axes. This is because the flow cells typically used in the measurements have limited space for particle rotations, and the source of light illuminates the flow cell within some restricted angles depending on the design of the instrument [17]. Hence when the particles are aligned with the flow field (and hence the flow cell), then the incident angle of the incoming light to the particles will also be limited. ...
... In this case, the scattering coefficients in Eq.(17) are computed at a single angle ζ = 90 • which are then used to calculate the scattering matrix components T 1 , T 2 and T 3 to obtain the scattering ...
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Many industrial processes for the production of particulate products rely on the accurate measurement of the sizes of these particles during the production process. One particle sizing technique which is implemented in commercial instruments due to its wide use in the manufacturing (of particulate products) industry is the laser diffraction method. The estimation of particle sizes by this method requires the solution of an inverse problem using a suitable model which incorporates the size, shape and optical properties of the particles. However, the commercial instruments which implement this laser diffraction method typically employ a model designed for spherical particles to solve this inverse problem even though a significant number of materials occur as elongated particles in industrial processes. As the inverse problem is ill-posed, then the use of a spherical model could lead to very misleading results. In this work, we demonstrate that the use of this spherical model for the estimation of sizes of these elongated particles could lead to over estimation of the proportion of the small particles in the population. This effect could lead to an under estimation of the mean particle size by as much as a factor of 50%.
... Therefore, the average particle sizes were determined using Stokes-Einstein equation. Generally, the most important and frequently reported parameter is the d H [11]. ...
... This resulted to an increment in the rate of collision as a function of the systematic induced velocity (V). The systematic induced velocity is inversely proportional to the velocity of the particles been analyzed [11]. At this point, the average induced velocity gained by the material is a function of the experienced stochastic force at any microseconds which is detectable by the Zetasizer equipment. ...
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Background: The dependence of adsorption rate on the particulate behavior of adsorbents can be effectively studied using the concept of Brownian motion. Variation in settling time of particles at different temperatures could have effect on adsorption process. The dynamic light scattering (DLS) technique is based on the principle of Brownian motion, and thus is suitable for investigating the behavior of particles under different conditions. Objectives: In the present research, particulate behavior of modified kaolin was studied at varied temperature using DLS technique in Zetasizer Nano-S equipment. Methods: Local kaolin was characterized for its thermal stability, surface morphology, and crystallinity using Thermogravimetric analysis (TGA), high resolution scanning electron microscopy (HRSEM) and X-ray diffractometry (XRD) respectively. For adsorbent development purpose, the local kaolin was modified by acid activation process, and its properties were studied by DLS and XRD techniques. The DLS was also used to investigate the effect of temperature on the viscosity, refractive index, polydispersity index, and particle size of the adsorbent. Results: It was found that the intensities and sizes of particles increased with increase in temperature during the DLS experiment by the Zetasizer Nano-S equipment. Conclusion: The study therefore suggests that for effective adsorption process at varied temperature, there should be a stirring medium to increase the relaxation time of the adsorbent in a batch reactor.
... The scattering data is analyzed to determine the size of the particle responsible for creating the scattering pattern, by the application of the Mie theory. Mie theory predicts scattering intensity as a function of the angle at which light is scattered at the point of interaction with a spherical particle [72]. The cell size is then reported as a volume equivalent sphere diameter (d SE ). ...
The particle size and morphology of the particles represent key factors that significantly influence the physicochemical properties of biological materials and suspensions, the transport phenomena inside the bioreactors and consequently the bioperformances. Many in-situ and ex-situ techniques are used to characterize the distribution functions of these properties. However, each method has its own advantages and disadvantages in defined conditions, and some differences may exist between methods resulting in variations and deviations of morphological measurements. This article aims to compare five different techniques (morphogranulometry MG, laser light diffraction LLD, flow cytometry CYT, settling velocity TSL, and focused beam reflectance measurement FBRM) used to characterize the morphology and granulometry of biological matrices with increasing complexity (model spherical particles, elongated yeast cells, and complex lignocellulosic substrates). The results and their interpretations highlighted several critical and limiting points: principles of measurement, technological and metrological specifications, identification of relevant parameters (diameter, shape), choice of distribution functions (number, volume), and statistical comparisons of populations. The results and their interpretations pointed out several critical points and limitations: principles of measurement, technological and metrological specifications, identification of pertinent parameters (diameter, shape), choice of distribution functions (number, volume), and statistical comparisons of populations. Granulometric methods may hide the complexity of diameter definitions. Examining shape parameters is richer than granulometry, and more complex descriptors (length, width, aspect ratio …) could be addressed. However, all these techniques enable to describe and interpret the observed phenomena (dimorphism, enzymatic hydrolysis) considering either absolute or relative data.
... The required sample volume, or concentration is small. [87,88] Large-scale species crossing low nanometer to micrometer can be measured. ...
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... Therefore, the total extinction coefficient, µt, of 7.734 (g/ml) -1 mm -1 for diluted concentrations of ocean water at 638 nm and total extinction coefficient for shallow well water was µt = 127.6 mm -1 at 638 nm. These reported values of total extinction coefficient depended on wavelength [12] only. Therefore, the linearity of the result shows that Equation (1) related well in the range of concentrations considered in this study [15]. ...
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In the present work, we proposed for the first time a simple and low-cost fluorometric method based on digital image using a UV-LED chamber and a 3D platform made of biodegradable polyacid lactic (PLA) and carbon dots (CDs) obtained from rice functionalized with cuprizone for the determination of Cu²⁺ in sugar cane spirits, using a paper-based device. The synthesized CDs were characterized by the techniques of UV-Vis spectrophotometry, spectrofluorometry, dynamic light scattering, scanning electron microscopy, zeta potential. The CDs obtained using a green hydrothermal method from biomass proved to be selective for the determination of Cu²⁺ when functionalized with bis (cyclohexanone) oxaldihidrazone (CPZ). The mechanism of detection was based on the quenching of fluorescence emitted by the CDs due to the Cu²⁺. For excitation of the CDs/CPZ, a chamber was built with four UV-LED as radiation source with maximum emission at 370 nm. An opening at the top allows the smartphone to detect the fluorescence emitted by the CDs. The captured image was decomposed to red (R), green (G) and blue (B) values. The determination of Cu²⁺ in the sugar cane spirits samples was obtained in a linear range from 2.00 to 7.22 mg L⁻¹ with LD of 0.23 mg L‑1 for B channel with R² = 0.9993. Based on the recovery data from 87.60% to 112.4% the matrix effect was not found. Samples of sugar cane spirits were analyzed by the fluorescence digital image method and the atomic absorption spectrophotometry, and there are no significant differences for 95% confidence of the data obtained, and thus, the method developed was accurace for Cu²⁺ detection.
A monoclonal antibody exhibits a two- or three-peak elution behavior when loaded on the CEX resin POROS XS and eluted with a salt gradient. Two peaks are observed without a hold step while a third more strongly retained peak becomes noticeable with a hold time as low as 10 min. As the hold time is increased further, the first peak gradually disappears, the second peak initially increases and then decreases, and the third peak continuously increases. Dynamic light scattering shows that the third peak contains significant levels of aggregates formed in the column. Circular dichroism, HX-MS analyses of the eluted fraction, in-line fluorescence detection, and bound-state HX-MS analysis indicate that the aggregates derive from an unfolded intermediate that is slowly formed while the protein is bound to the resin. Aggregate formation does not occur on a different CEX resin, Nuvia HR-S, with similar particle size but with a more homogenous structure or when the sodium acetate load buffer is replaced with arginine acetate. The two early eluting peaks observed for POROS XS regardless of hold time are shown to comprise exclusively monomeric species. A set of biophysical measurements as well as mechanistic modeling support the hypothesis that these two peaks form as a result of the presence of weak and strong binding sites on the resin having, respectively, fast and slow binding kinetics.
This paper presents a simulation-guided regression approach for estimating the size distribution of nanoparticles with dynamic light scattering (DLS) measurements. The properties and functionalities exhibited by nanoparticles often depend on their sizes, so the precise quantification of the sizes is important for characterizing and monitoring the quality of a nanoparticle synthesis process. The state-of-the-art in the size quantification with DLS measurements is the CONTIN, which is based on a computationally ineffective numerical inversion. We propose a new approach that avoids the numerical inversion by reformulating the problem into a regularized regression problem with the basis functions generated by a computer simulation of dynamic light scattering measurements. For many simulation studies and one real data study, our method outperformed the CONTIN in terms of estimation accuracy and computational efficiency.
The explosion of interest in nanotechnology and its potential applications has brought with it many challenges in understanding and quantifying the behavior of materials operating in a nanoscale environment. Thus, the use of dynamic light scattering (DLS), combined with noninvasive backscatter technology is proving highly successful in providing a system that is not only sensitive enough to measure dilute or poorly scattering particles, but that also can measure samples at very high concentrations. This paper describes the system's technology and its application in the measurement of cadmium selenide nanocrystals and cluster molecules.
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Evidence for the molecular self-assembly of amelogenin proteins to form quasi-spherical particles ("nanospheres") in solution, both in vitro and in vivo, has recently been documented. A particle-size distribution analysis of dynamic light-scattering data was undertaken to investigate the influence of temperature on this molecular self-assembly process at three different pH's. The long-term objective was to correlate these observations to the unusual physiochemical characteristics of the protein, to improve understanding of the molecular mechanisms involved in the generation of amelogenin "nanospheres" and understanding of their putative relation to amelogenin function in vivo. We analyzed data using two different algorithms: Dynamics and DynaLS. It was found that at pH 8, in a temperature range between 5 and 25 degrees C, the size of the recombinant amelogenin nanospheres is monodisperse, giving rise to particles of 15-18 nm in hydrodynamic radius. However, heterogeneous distribution of particle size was observed at temperature ranges between 27 and 35 degrees C, becoming monodisperse again with larger particles (60-70 nm) after the temperature was elevated to 37-40 degrees C. We interpret these results to suggest that amelogenin molecular self-association possesses a second stage assembly process at temperatures of 30-35 degrees C, creating larger entities which apparently are structured and stable at 37-40 degreesC. The effect of pH on the size of amelogenin "aggregates" was much more noticeable at 37 degrees C compared to that at 25 degrees C. This observation suggests that at physiological temperature (i.e., 37 degrees C) amelogenin molecular self-assembly is extremely sensitive to pH changes. This finding supports the notion that local pH changes in the microenvironment of the enamel extracellular matrix may play critical roles in controlling the structural organization of the organic matrix framework.
In the twenty years since their inception, modern dynamic light-scattering techniques have become increasingly sophisticated, and their applications have grown exceedingly diverse. Applications of the techniques to problems in physics, chemistry, biology, medicine, and fluid mechanics have prolifer­ ated. It is probably no longer possible for one or two authors to write a monograph to cover in depth the advances in scattering techniques and the main areas in which they have made a major impact. This volume, which we expect to be the first of aseries, presents reviews of selected specialized areas by renowned experts. It makes no attempt to be comprehensive; it emphasizes a body of related applications to polymeric, biological, and colloidal systems, and to critical phenomena. The well-known monographs on dynamic light scattering by Berne and Pecora and by Chu were published almost ten years ago. They provided comprehensive treatments of the general principles of dynamic light scat­ tering and gave introductions to a wide variety of applications, but natu­ rally they could not treat the new applications and advances in older ones that have arisen in the last decade. The new applications include studies of interacting particles in solution (Chapter 4); scaling approaches to the dynamics of polymers, including polymers in semidilute solution (Chapter 5); the use of both Fabry-Perot interferometry and photon correlation spectroscopy to study bulk polymers (Chapter 6); studies of micelIes and microemulsions (Chapter 8); studies of polymer gels (Chapter 9).
Biovectors are recently developed nanoparticles intended to be used as drug carriers and in the formulation of vaccines. The Biovectors are composed of a polysaccharide core to which phospholipids and cholesterol can be added. The cores are prepared by disruption of a gel of cross-linked maltodextrins, and can have a positive, neutral or negative charge depending on the grafting ionic ligands used. In this study static and dynamic light scattering measurements were combined to characterize the structure of these Biovectors. Transmission electron microscopy was also used. The present work, carried out with positively charged Biovectors in PBS (phosphate buffer saline) and phosphate buffer, points towards a microgel like structure to the polysaccharide fragments of these Biovectors and a spherical geometry with radius ≈ 50 nm. The influence of lipid composition on Biovectors size and density was also studied. The use of transmission electron microscopy gives first evidence for a structure consisting of several phospholipid bilayers surrounding a polysaccharide core. This organized lipidic environment is suitable for hydrophobic drug interaction and membrane proteins insertion. The formulation of a stable, highly controlled drug delivery system or vaccine formulation is implicated.
We describe the design, construction, and testing of a miniature, all-solid state laser light scattering instrument for determination of particle sizes and distributions using photon correlation spectroscopy techniques (i.e., quasielastic or dynamic light scattering). Detailed comparative tests with standard photon correlation spectroscopy equipment are presented.
In the first part of this work we report quasielastic light scattering (QELS) studies of the internal dynamics of transient actin networks over a time range of 10⁻⁶–10⁻² s, scattering angles between ζ = 20° and 150°, and a concentration range of 0.015 (0.3) to 0.7 mg/mL (15 μM). We confirm our previous result that (1) the dynamic structure factor g(q, t) is determined by the thermally excited undulations of the actin filaments and (2) that the initial decay of g(q, t) scales as g(q, t)∝ exp(qαt) while the long time decay scales as g(q, t) ∝ exp[-(Aqαt)2/3] with α = 2.75. The deviation of α from the theoretical value of α = 3 predicted for Rouse-Zimm chains is similar to that found for high molecular weight macromolecular solutions by QELS. A refined analysis of the dynamic structure factor showed that it can be interpreted in terms of three relaxation processes (besides the contribution of the residual monomer diffusion): (1) the dominant Rouse-Zimm dynamics, which comprises between 65 (at high concentrations) and 85% of the signal; (2) a fast relaxation process with a decay constant of Γ = 9 × 10³ s⁻¹, which contributes at all concentrations with the same amplitude; and (3) a nonexponential ultraslow contribution of the form gus ∝ exp[(– Γust)] 1/4. The third contribution appears only at high concen-trations and increases strongly with decreasing scattering angles. It is thus attributed to fluctuations of the mesh size of the transient actin network.
Dynamic light scattering (DLS) measurements were performed on self-assembled solutions of RecA as a function of assembly time under strand exchange ionic strength conditions (10 mM MgCl2, 65 mM NaCl, 10 mM Tris-HCl, pH = 7.5, 1 mM DTT, 3-4 microM RecA) in the absence of ATP. These measurements yield distributions of the translational diffusion coefficients of the changing populations of assembling protein species. Interpretations of results of DLS measurements are made in terms of model hydrodynamic calculations that indicate, under the solution conditions employed, the smallest fundamental quaternary subunit of RecA is a hexamer in a toroidal or lock-washer configuration. Interactions of M13mp19 circular single strand DNA (ssDNA) with RecA assembled to different stages were also investigated. Additions of ssDNA to self-assembled solutions of RecA acts to dissociate the associated structures into hexamer subunits. However, the effect of ssDNA on assembled RecA is highly dependent on the RecA self-assembly state. The longer the assembly time, the less reversible the self-assembled structures of RecA become. Binding isotherms of titrated mixtures of ssDNA with RecA self-assembled to various stages were also determined. Evaluated dissociation constants of RecA/ssDNA complexes were found to increase with increases of the associated state of RecA. These results strongly suggest that, under the solvent conditions employed, the active ssDNA binding form of RecA is a hexamer.
The hydrodynamics of the bacterial elongation factor EF-Tu have been studied in the presence of its ligand guanosine-5'-diphosphate (GDP) by sedimentation in the ultracentrifuge and quasielastic light scattering. Sedimentation studies have made it possible to establish experimental conditions under which only negligible aggregation of the protein occurs (neutral pH, concentration less than 3 mg/mL). Analysis of the light intensity autocorrelation functions under these conditions revealed two independent scattering species with diffusion coefficients of 0.71 X 10(-6) and 0.04 X 10(-6) cm2 s-1. The material with the lower diffusion coefficient, i.e., the aggregates, represented less than 1% of the total number of EF-Tu particles. The other 99% diffused as monomeric molecules with a molar mass corresponding to the value calculated from the known primary structure of the protein. The hydrodynamic parameters derived from the experimental data suggest that EF-Tu.GDP in solution is close to a spherical particle.
The problem of characterising liposomes with covalently attached proteins has been analysed theoretically in terms of a normal weight distribution of liposome diameters. The polydispersity of protein conjugation is considered in terms of the width (standard deviation) of the liposome size distribution. It is shown that the weight-average number of proteins per liposome is a convenient parameter to use to define the protein content of proteoliposomes. Two types of proteoliposome have been prepared (small unilamellar vesicles and reverse phase evaporation vesicles) in which wheat germ agglutinin is covalently coupled to the liposomal surface. The liposomes cover a range of weight average diameter from 65 to 240 nm and of polydispersity (weight to number average diameter (dw/dn) from 2.6 to 11.4. The liposomes have been characterised by chemical analysis and photon correlation spectroscopy and the results are discussed in terms of the theoretical consequences of an equivalent normal weight distribution of diameters.
Penicillin binding protein 4 (PBP4) from Escherichia coli is a protein involved in the recycling and maturation of the bacterial cell wall and it is inhibited by beta-lactam antibiotics. PBP4 exhibits D-Ala-D-Ala-endopeptidase as well as D-Ala-D-Ala-carboxypeptidase activity. To provide a structural template for the design of new, more specific antibiotics we started X-ray crystallographic studies of penicillin binding protein 4 from Escherichia coli. PBP4 has been overexpressed in Escherichia coli as a His-tagged protein. A large-sclae purification scheme, yielding a very pure material, has been set up and crystallization experiments have been started. Dynamic light scattering experiments suggested that PBP4 exhibits aggregation behavior with a number of different precipitating agents and additives. Only by addition of EDTA, PEG 4000, and ammonium sulfate is the molecular mass about 110 kDa.