Metabolic reactions in living cells are limited by diffusion of reagents in the cytoplasm. Any attempt to quantify the kinetics of biochemical reactions in the cytosol should be preceded by careful measurements of the physical properties of the cellular interior. The cytoplasm is a complex, crowded fluid characterized by effective viscosity dependent on its structure at a nanoscopic length scale. In this work, we present and validate the model describing the cytoplasmic nanoviscosity, based on measurements in seven human cell lines, for nanoprobes ranging in diameters from 1 to 150 nm. Irrespective of cell line origin (epithelial-mesenchymal, cancerous-noncancerous, male-female, young-adult), we obtained a similar dependence of the viscosity on the size of the nanoprobes, with characteristic length-scales of 20 ± 11 nm (hydrodynamic radii of major crowders in the cytoplasm) and 4.6 ± 0.7 nm (radii of intercrowder gaps). Moreover, we revealed that the cytoplasm behaves as a liquid for length scales smaller than 100 nm and as a physical gel for larger length scales.
Metabolic reactions in living cells are limited by diffusion of reagents in the cytoplasm. Any attempt to quantify the kinetics of biochemical reactions in the cytosol should be preceded by careful measurements of the physical properties of the cellular interior. The cytoplasm is a complex, crowded fluid characterized by effective viscosity dependent on its structure at a nanoscopic length scale. In this work, we present and validate the model describing the cytoplasmic nanoviscosity, based on measurements in seven human cell lines, for nanoprobes ranging in diameters from 1 to 150 nm. Irrespective of cell line origin (epithelial-mesenchymal, cancerous-noncancerous, male-female, young-adult), we obtained a similar dependence of the viscosity on the size of the nanoprobes, with characteristic length-scales of 20 ± 11 nm (hydrodynamic radii of major crowders in the cytoplasm) and 4.6 ± 0.7 nm (radii of intercrowder gaps). Moreover, we revealed that the cytoplasm behaves as a liquid for length scales smaller than 100 nm and as a physical gel for larger length scales.
Metabolism at the cellular level
is considered as a network of reactions between biomolecules.[1,2] These reactions maintain a balance where any prolonged disturbance
can lead to pathological changes, including cell death or systemic
diseases.[3,4] From the physical point of view, a reaction
can occur when molecules of reagents approach each other. In an equilibrium-state
solution, Brownian motion (free diffusion) is a source of the movement
of particles, and an increase of diffusion rate increases the probability
of molecular encounters leading to biochemical reactions. The cytoplasm
is a complex and crowded medium, where diffusion of biomolecules is
hindered, and therefore diffusion can be treated as a factor limiting
reaction rates in a cell.[5,6] Decrease of diffusion
rates would decrease rates of metabolic reactions and could lead to
cell damage.[7]According to the Stokes–Sutherland–Einstein
relation,[8,9] the diffusion coefficient depends inversely
on hydrodynamic drag, f = 6πηeffrp, where rp is the hydrodynamic
radius of a probe and ηeff is an effective viscosity
of the medium. Many reports show that viscosity of the cytoplasm is
not constant, but rather spatially heterogeneous.[10−12] Additionally,
according to our research, scale-dependent heterogeneity of cytoplasmic
viscosity is even more pronounced.[13−15] We found that objects
of different sizes can experience different viscosity: the viscosity
increases with the increasing size of the object.[13] It is an outcome of the complex composition of cytoplasm—various
components provide obstacles at different length-scales: the only
obstacle of similar or smaller size can hinder the diffusion of a
probe (see Figure : I). Our previous, detailed works on polymer and colloidal solutions
resulted in a comprehensive model of length-scale dependent viscosity
(LSDV), applicable for complex fluids[13,16−19]where η0 is the viscosity
of a reference buffer, A is a pre-exponential factor of the order
of 1, ξ and RH are length scales
characteristic for a given system, and a is an exponent
of the order of unity. RH can be interpreted
as a hydrodynamic radius of the main crowders, while ξ refers
to an effective intercrowder gap, including a weak interactions factor.[18,20] In such a fluid, small molecules (rp ≪ ξ) experience viscosity of the solvent, while big
tracers (rp ≫ RH) experience viscosity measurable by macroscopic methods.
To distinguish viscosity experienced by nanoobjects, we introduce
a term of nanoviscosity. We further presented applicability of this
model to complex biological fluids, like cytosol of prokaryotic and
eukaryotic cells,[5,13] and we experimentally proved
and applied this model for determination of oligomerization state
of proteins in living cells.[15,21]
Figure 1
Principle of the research
on cytoplasmic nanoviscosity. (I) Assumptions
of the length-scale dependent viscosity (LSDV) model: (Ia) cytoplasm
is a complex liquid containing components of various sizes. Thus,
diffusion of the probes of different hydrodynamic radii (rp) is hindered by different cytoplasmic obstacles. In
the result (Ib), effective viscosity (ηeff) probed
by tracers of different sizes increase with the size of the tracer.
(II) To examine ηeff, fluorescently labeled tracers
are introduced to the cytoplasm—the mode of introduction is
optimized for a given probe. (III) Next, FCS measurements are performed:
(IIIa) Confocal spot is positioned in the cytoplasmic area of the
cell, and fluorescence fluctuations are registered, (IIIb) autocorrelation
curve (ACC) is calculated for the acquired data, and (IIIc) ACC is
fitted with a proper diffusion model, and diffusion coefficient of
the tracer is derived. (IV) Data collected for a set of tracers in
a given cell line is used for quantitative description of the LSDV
model: (IVa) ηeff experienced by the given probe
is calculated from the diffusion coefficient, and rp (IVb) results are plotted and fitted with eq ; (IVc) LSDV profiles are compared
between different cell lines.
Principle of the research
on cytoplasmic nanoviscosity. (I) Assumptions
of the length-scale dependent viscosity (LSDV) model: (Ia) cytoplasm
is a complex liquid containing components of various sizes. Thus,
diffusion of the probes of different hydrodynamic radii (rp) is hindered by different cytoplasmic obstacles. In
the result (Ib), effective viscosity (ηeff) probed
by tracers of different sizes increase with the size of the tracer.
(II) To examine ηeff, fluorescently labeled tracers
are introduced to the cytoplasm—the mode of introduction is
optimized for a given probe. (III) Next, FCS measurements are performed:
(IIIa) Confocal spot is positioned in the cytoplasmic area of the
cell, and fluorescence fluctuations are registered, (IIIb) autocorrelation
curve (ACC) is calculated for the acquired data, and (IIIc) ACC is
fitted with a proper diffusion model, and diffusion coefficient of
the tracer is derived. (IV) Data collected for a set of tracers in
a given cell line is used for quantitative description of the LSDV
model: (IVa) ηeff experienced by the given probe
is calculated from the diffusion coefficient, and rp (IVb) results are plotted and fitted with eq ; (IVc) LSDV profiles are compared
between different cell lines.The LSDV model relies on RH and ξ
parameters, which reflect the length scales characterizing the structure
of the fluid. For the simplest case of complex fluid—a single
polymer in a continuous solvent—RH is defined as a hydrodynamic radius of polymer molecules, while
ξ is mesh size or distance between intersections of polymer
chains.[19] In the case of the cytoplasm,
there are different types of crowders (proteins, macromolecular complexes,
organelles, or cytoskeleton), and thus only effective RH,eff and ξeff can be derived. These
parameters seemed to be unique for every cell type and culture conditions.
Cells of different types differ in terms of morphology, function,
or gene expression. These differences can also have an impact on nanoviscosity-like
numbers, and types of metabolites and proteins would vary.In
this paper, we present a systematic, experimental study on nanoviscosity
profiles of seven different cell types. The principle of this work
is shown in Figure . Biologically inert tracers (dye molecules, fluorescent proteins,
fluorescently labeled polymers, and nanoparticles) of size rp were introduced into cells, and their diffusion
coefficients were measured by fluorescence correlation spectroscopy
(FCS). Many works utilize FCS or its variants in cells;[10,22−30] however, the systematic study on the nanoviscosity at different
length scales—necessary for proper data analysis—is
still needed. Performance of FCS in living cells enabled reliable
results achievable in mild, physiologically relevant conditions.[14,15,31] Tracers were chosen to cover
all length scales essential for cell physiology (diameters from 1
to 150 nm): metabolites, macromolecular complexes, proteins, nucleic
acids, and vesicles. Cell lines were chosen to cover representatives
of each group: cancerous or normal; epithelial or mesenchymal; male
or female donor. Effective viscosity was measured at different length
scales in every cell line, and it was confirmed that effective viscosity
of cytoplasm is length-scale dependent on the majority of human cell
lines.
Length-Scale Dependent Viscosity of Cytoplasm
The LSVD
model predicts that tracers of different hydrodynamic
radii would experience different effective viscosity of cytoplasm,
as only those obstacles which are of similar or smaller size than
the tracer would have an impact on ηeff (Figure , panel I). To confirm
this prediction, tracers of defined hydrodynamic radii, ranging from
0.65 to 81 nm, were introduced to cytoplasmic area of cells via microinjection
(dextrans and nanoparticles), passive inflow (Calcein-AM), or biosynthesis
upon transfection (proteins) (Figure , panel II). We applied the core–shell type
of nanoparticles to avoid the impact of nanoparticle size on FCS measurements.[32,33] Full information on tracers used in the experiments is presented
in Supporting Information 1 and 2 (SI 1, SI 2). Cells filled with tracers at final concentrations of 1–100
nM in the cytoplasm were further examined under the confocal microscope.
Focal volume was positioned in the cytoplasmic area of viable cells,
and FCS data was acquired (Figure , panel III). Each FCS experiment was preceded with
careful calibration (see SI 1).[14,34] Diffusion coefficients were derived for each type of probe (see SI 3 for details), and results were averaged
for each of the cell lines considered in this study. Diffusion coefficients
obtained in the cytoplasm (D) were compared to diffusion
coefficients measured in water (D0) for
the same probes and temperature. Following the Stokes–Sutherland–Einstein
relation, relative viscosity was calculated as follows: ηeff/η0 = D0/D. ηeff/η0 experienced
by the probe was plotted against rp for
each of the cell lines (Figure , panel IV).The results obtained for six cell lines
(HeLa, HepG2, MCF-7, A549,
HSAEC, and U2-Os) are compiled in Figure . Error bars represent standard deviations
reflecting the intercellular variability of the results. Possible
intracellular variability was neglected, as discussed in SI 4. For each of the cell lines listed above,
the effective viscosity of the cytoplasm is increasing with the size
of the probing tracer. Although absolute values of ηeff slightly differ in particular cell lines, the trend is common in
all cells of this group. The results were fitted with the LSDV model
(eq ), with following
parameters: RH = 20 ± 11 nm, ξ
= 4.6 ± 0.7 nm, a = 0.57 ± 0.14. A was
fixed to 1.3 following our previous results.[13] The values of the parameters of the LSDV model provide information
regarding the rheological structure of the cytosol.[19] Exponent a < 1 is characteristic for
entangled polymer solutions.[18,19]RH is attributed to the size of major crowders in the complex
liquid. RH = 20 nm suggests that major
crowders are of diameters ∼40 nm, which correspond to large
cytoplasmic structures, such as vesicles, mRNA molecules, or ribosomes.[35−37] The length-scale ξ is defined as an average radius of a mesh
created by major crowders.[19] ξ ≈
4.6 nm corresponds to the size of proteins. Thus, diffusion of proteins
is affected by big crowders in the cytoplasm, while smaller metabolites
experience viscosity of the solvent.
Figure 2
Nanoviscosity measured in six different
cell lines. Experimental
results are presented as scatter. Each point represents the average
value obtained from at least 10 cells from two independent inoculations.
Error bars correspond to standard deviations. Dashed line represents
LSDV model (eq ) fitted
to experimental data with the following parameters: A = 1.3 (fixed), RH = 20 ± 11 nm,
ξ = 4.6 ± 0.7 nm, a = 0.57 ± 0.14.
Shading represents the error of the model calculated using the total
differential method.
Nanoviscosity measured in six different
cell lines. Experimental
results are presented as scatter. Each point represents the average
value obtained from at least 10 cells from two independent inoculations.
Error bars correspond to standard deviations. Dashed line represents
LSDV model (eq ) fitted
to experimental data with the following parameters: A = 1.3 (fixed), RH = 20 ± 11 nm,
ξ = 4.6 ± 0.7 nm, a = 0.57 ± 0.14.
Shading represents the error of the model calculated using the total
differential method.Our results, presented
in Figure , were compared
to measurements reported by other groups.[10,13,30,38−40] The results of the comparison are shown in SI5 (Figure SI5). In general, our results are in good
agreement with scattered data reported by other groups, with mismatches
that could be attributed to different methods of measurements.
Gel-like
Structure of Cytoplasm
Diffusion coefficients of the probes
of hydrodynamic radii smaller
than 50 nm could have been measured in the cytoplasm using FCS. Larger
probes, however, were more challenging: only a few autocorrelation
curves were interpretable, and it was much too little for proper data
analysis. We decided to support the FCS technique with its variant—Raster
Image Correlation Spectroscopy (RICS).[41]Fluorescent nanoparticles of diameters exceeding 100 nm were
introduced
via microinjection to the cytoplasm of HeLa cells and fibroblasts,
and RICS analysis was performed. It turned out that no diffusion-dependent
correlation could have been detected using RICS. Frame-by-frame analysis
of the pictures revealed that long time and range translational diffusion
could not be detected for nanoparticles of rp > 50 nm (see Supplementary Movie). On the contrary, nanoparticles are trapped and oscillating in
single spots. It seems like large cytoplasmic structures—like
cytoskeleton or endoplasmic reticulum—create a gel-like structure
of the mesh size ∼100 nm. The size of the mesh differs in different
cells or regions, as nanoparticles of rp = 68 nm exhibited free diffusion (proper FCS autocorrelation curves)
in several cases in HeLa cells. On the other hand, the majority of
image series of nanoparticles of rp =
68 or 81 nm revealed particle trapping. Our observation of a gel-like
structure filled with a liquid phase is in good correlation with previous
atomic force microscopy measurements.[38]
Nanoviscosity in Different Cells
There is striking compliance
of the nanoviscosity profiles obtained
for different cell lines (Figure a–d). It seems that the LSDV model is universal
regardless of the original tissue, type of the cell, gender, or age
of the donor. Although values of nanoviscosity for given length scales
can slightly differ between different cells, the overall trend is
similar—the nanoviscosity is length-scale dependent. The majority
of batteries used in the study exhibit cytoplasmic viscosity of approximately
2 viscosities of water for probes of rp < 1 nm, while for probes of rp >
20 nm the nanoviscosity reaches the value of approximately 10 viscosities
of water. We assumed four factors that could impact nanometabolism
via nanoviscosity of the cytoplasm: tissue type (epithelial or mesenchymal),
disease (cancerous or noncancerous), gender of the donor (male or
female), and age of the donor (young or adult); see SI 6. No differences could have been spotted between the cell
groups in any of the four categories. Additionally, for our further
work, we profiled nanoviscosity of other cell lines (primary mammary
epithelium and triple-negative breast cancer cells; data not shown),
and their nanoviscosity is comparable with the values presented in Figure . Stability of the
cytoplasmic nanoviscosity is particularly surprising for the case
of cancer and healthy cells, which are reported to differ in terms
of microscopic rheological parameters.[42,43]
Figure 3
Comparison
of nanoviscosity in different cell types. Graphs represent
average relative nanoviscosity measured in the cytoplasm of different
cells and plotted against hydrodynamic radii of the tracers probing
the viscosity (data consistent with Figure ) (a–d) Cell lines used in the study
were divided into groups (see SI 5), according
to (a) tissue origin, (b) disease, (c) gender of donor, or (d) age
of donor. No deviations of the viscosity could have been observed
between these groups. (e) Fibroblasts were the only cell line in which
nanoviscosity was found to differ from the major trend for small probes
(rp < 10 nm).
Comparison
of nanoviscosity in different cell types. Graphs represent
average relative nanoviscosity measured in the cytoplasm of different
cells and plotted against hydrodynamic radii of the tracers probing
the viscosity (data consistent with Figure ) (a–d) Cell lines used in the study
were divided into groups (see SI 5), according
to (a) tissue origin, (b) disease, (c) gender of donor, or (d) age
of donor. No deviations of the viscosity could have been observed
between these groups. (e) Fibroblasts were the only cell line in which
nanoviscosity was found to differ from the major trend for small probes
(rp < 10 nm).The presented results show that nanoviscosity is somehow conserved
in human cells, apart from the viscosity of the cytoplasmic matrix
of small molecules (rp < 1 nm); the
LSDV profiles—depending on the abundance of organelles and
macromolecules—are also the same. This stability is a surprising
result, in terms of widely reported variability in cell sizes,[44] as well as protein expression levels.[45] In our previous work,[31] we presented that nanoviscosity sensed by EGFP (rp = 2.3 nm) is also constant (with a slight, 30% increase
during S phase) during the whole cell cycle of HeLa cells. These results,
together with those presented in the present work, provide a picture
of stable nanoviscosity in human cells. Future questions arise from
these observations: whether nanoviscosity has a biological impact
and is conserved on a level optimal for cell homeostasis.
Fibroblasts Exhibit
Different Nanoviscosity than Other Cells
Primary skin fibroblasts
are the only cells for which nanoviscosity
profile is not length-scale dependent in the range of length scales
of 1 nm < rp < 20 nm. Thus, the
nanoviscosity profile of fibroblasts deviates from the results for
all other cell lines (Figure : e). It is a surprising result, as other mesenchymal (Figure : a) or noncancerous
(Figure : b) cells
exhibited “usual” LSDV profiles. On the other hand,
cytoplasmic viscosities were similar in fibroblasts and other cells
for the probes larger than 20 nm. The nanoviscosity for smaller probes
in the cytoplasm of fibroblasts was independent of the passage number
(see SI 7).To investigate a potential
source of differences in nanoviscosity,
we imaged large cytoplasmic obstacles (cytoskeleton: actin and tubulin,
and endoplasmic reticulum, ER) in fibroblasts, HeLa, A549, and U2-Os
cells (Figure ). Fibroblasts
were imaged as cells of interest, according to their extraordinary
nanoviscosity. HeLa and A549 were chosen as control cancer epithelial
cells, while U2-Os were selected as control cancer mesenchymal cells.
In the first experiment (Figure : a), actin and tubulin were stained using ligands
specific for these proteins (phalloidin-based and paclitaxel-based,
respectively). At least ten cells were imaged for every cell type.
No distinct differences in cytoskeleton abundances were observed.
The second experiment (Figure : b) included the immunostaining of ER. Again, at least ten
cells were imaged for every cell type. In this variant, it was observed
that the ER is much more abundant in fibroblasts than other cells.
The abundance of the stained ER was quantified (see SI 8), and results are presented in Figure . We decided to take into account the total
size of the ER, rather than the signal intensity, which may vary from
cell to cell according to different protein expression levels.[46] A significant difference in ER abundance was
observed between fibroblasts and other cells: ER covered an average
of 67% of the cytoplasmic area in fibroblasts, while in A549, HeLa,
and U2-Os, it was 37%, 43%, and 38%, respectively. As a complement,
the cytosol (liquid phase of cytoplasm) of the fibroblasts was compressed
into 33% of the cytoplasmic volume, while in other cells, it is an
average of 61%.
Figure 4
Confocal images of subcellular structures of four cell
lines: A549,
HeLa, U2-Os, and Fibroblasts. (a) Staining of cytoskeletal proteins
(actin and tubulin) showed no particular differences between cell
types. (b) Immunostaining of endoplasmic reticulum (ER) revealed a
high abundance of ER in fibroblasts comparing to three other cell
lines. Scale bars correspond to 10 μm.
Figure 5
Quantification
of ER abundance in different cell types. (a) Example
confocal images of ER in different cells. (b) Average abundance of
ER (white pixels) and cytosol (black pixels) in cells of various types.
Confocal images of subcellular structures of four cell
lines: A549,
HeLa, U2-Os, and Fibroblasts. (a) Staining of cytoskeletal proteins
(actin and tubulin) showed no particular differences between cell
types. (b) Immunostaining of endoplasmic reticulum (ER) revealed a
high abundance of ER in fibroblasts comparing to three other cell
lines. Scale bars correspond to 10 μm.Quantification
of ER abundance in different cell types. (a) Example
confocal images of ER in different cells. (b) Average abundance of
ER (white pixels) and cytosol (black pixels) in cells of various types.From the diffusion point of view, the endoplasmic
reticulum is
a set of membrane walls crossing the medium. Its presence is included
in the ηeff measured in our FCS experiments. The
focal volume has a cross section of diameter ∼400 nm, which
can consist of ER cisterna or other membrane obstacles (such as mitochondria,
lysosomes, etc.). With the higher ER or organelle abundance, the number
of membrane walls increases. There is a known phenomenon of near-wall
diffusion hindrance,[47] causing an increase
of effective viscosity. Also, our previous studies on lamellar phases
revealed an increase of continuous phase viscosity, comparing to the
same solvent with no lamella.[48] These observations
are consistent with our measurements in fibroblasts—more abundant
ER can possibly cause matrix viscosity increase. This effect is less
pronounced for bigger length scales—for tracers of rp > 20 nm, cytoplasmic viscosities of fibroblasts
reach values similar to every other cell line examined in this study.To conclude, we performed a systematic study on cytoplasmic nanostructure
in seven different cell types. Cell lines used in this study represented
different origins (epithelial or mesenchymal, cancer or healthy, male
or female, young or adult). We probed cytoplasmic nanoviscosity at
length scales in the range of 1–150 nm, revealing length-scale
dependent viscosity profiles present in the majority of cells. We
provided the model equation describing nanoviscosity, and derived
length scales characteristic for the cytoplasm. It was shown that
mRNA, ribosomes, and vesicles are major cytoplasmic crowders. It was
also demonstrated that nanoparticles of diameters bigger than 100
nm are unable to diffuse freely through the cytoplasm, suggesting
a critical length scale crossover to gel-like structure in the cytoplasm.The cytoplasmic nanoviscosity is conserved in the majority of human
cell lines. The only cells differing from the major trend are fibroblasts.
The potential source of this discrepancy can be the abundance of intracellular
membrane structures, which we identified at the example of the endoplasmic
reticulum. Though, the length-scale dependent viscosity model seems
to be universal for human cells, regardless of age, disease, or type
of tissue. Moreover, in our previous work,[31] we presented the stability of cytoplasmic viscosity for the whole
cell cycle. All these results indicate that nanoviscosity can play
a vital role in cellular homeostasis maintenance, and some unknown
mechanism keeps it stable in single cells and between cell types.
These observations open a new field of questions about the role and
regulation of the physical properties of cells.
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