2.1.

Constructs and Cell Culture

Expression vectors encoding EGFP-tagged uPAR or D2D3 were constructed using conventional cloning procedures by inserting the fluorescent protein regions between the third domain of uPAR (D3) and the GPI-anchoring signal. To avoid possible artifacts caused by intrinsic dimerization of the EGFP-moiety, the monomeric A206K variant was used.²⁶ The expression vectors, based on the pEGFP-N1 (Clontech, Mountain View, California) backbone, were transfected into HEK293, and stable clones were isolated by G418 selection and limited dilution. In the isolated clones, the expression levels were evaluated by flow cytometry, and the number of receptors by binding assays using $\mathrm{Eu}3+$ -labeled pro-uPA. The uPAR-G clone used in the FCS/PCH experiments expressed $(12\pm 2)\times {10}^4$ receptors/cell. A clone of D2D3-G cells with a comparable expression level was selected by flow cytometry. Cells were cultured at $37°\mathrm{C}$ and 5% ${\mathrm{CO}}_2$ in high glucose DMEM, 10% fetal bovine serum, glutamine $\left(5\mathrm{mM}\right)$ , penicillin $(100\mathrm{U}∕\mathrm{ml})$ and streptomycin $(100\mathrm{mg}∕\mathrm{ml})$ . Cells plated in glass bottom WillCo $35\text{-}\mathrm{mm}$ wells (WillCo Well BV, Amsterdam, Netherlands) were used at subconfluence. All experiments were performed at $27°\mathrm{C}$ and in serum-rich buffered medium.

2.2.

Instrumentation and Data Analysis

We used a dual-channel confocal fluorescence correlation spectrometer (ALBA by ISS, Inc., Champaign, Illinois). ALBA was equipped with avalanche photodiodes and interfaced to a Nikon TE300 inverted microscope. The objective was a $60\times$ Plan Apo (1.2 NA, water immersion). A BG39 optical filter (Chroma Technology, Rockingham, Vermont) was placed before the ALBA unit. A mode-locked titanium-sapphire laser (Tsunami, Spectra-Physics, Mountain View, California) provided two-photon excitation at $920\mathrm{nm}$ . Every day, the power of the light after the objective in the absence of any immersion liquid was adjusted at $1\mathrm{mW}$ . An $x$ , $y$ , $z$ computer-controlled piezoelectric actuator with a step resolution of less than $50\mathrm{nm}$ warranted the nanometric positioning. An ISS, Inc., acquisition card received the data stream from the detectors. Data were stored for further processing by VISTA (ISS, Inc.) and simFCS (Laboratory for Fluorescence Dynamics, UCI, Irvine, California). Acquisition was in the time mode, and the sampling frequency was $20\mathrm{kHz}$ . The waist $\left({\omega }_0\right)$ of the excitation beam was calibrated each day before experiments by measuring the autocorrelation function (ACF) of $10\mathrm{nM}$ fluorescein/ $0.01\mathrm{M}$ $\mathrm{NaOH}$ , using a diffusion coefficient²¹ of $300\mathrm{\mu }{\mathrm{m}}^2∕\mathrm{s}$ . Typical ${\omega }_0$ values were 0.35 to $0.41\mathrm{\mu }\mathrm{m}$ ; thus, the effective volume as obtained from the Gaussian-Lorentzian fit²¹ was $0.08\mathrm{\mu }{\mathrm{m}}^3$ $(\pm 9\%)$ .

ACFs were best-fitted by the anomalous diffusion model³⁰:

Photon counting histograms were analyzed according to Chen, ²³ assuming a Gaussian-Lorentzian excitation volume. Local PCH analysis for deriving local brightness and local number of molecules was performed as described in Sec. 3.

2.3.

Statistical Analysis

Statistical analysis was performed with Graphic-Pad Prism (GraphPad Software, Inc., San Diego, California).

3.1.

Generation of the First Functional Fluorescent Model for uPAR

Fluorescence imaging and micro-spectroscopy in live cells is mainly based on the use of fluorescent protein-tagged chimeras either transiently or stably expressed in cells. The main assumption is that the insertion of a fluorescent protein in the sequence of the target protein does not alter the correct folding, sorting, and biological activity of the protein under study. This assumption arises from the fact that fluorescent proteins are relatively small and compact beta-barrel proteins of $27\mathrm{kDa}$ , which may form an additional independent domain in the chimeric sequence.

The correct intracellular translocation of the chimeric protein is a generally accepted condition for assuming retention of function. However, this condition might not be sufficient in the case of receptors with complex functions such as uPAR. The biological activity of uPAR depends on the correct folding and exposure of its three ecto-domains, termed D1, D2, and D3 [Fig. 1b, scheme on the right]. The peculiar folding, only recently described,³¹ of the three domains endows uPAR with several biological functions. uPAR binds the physiological ligand pro-uPA, which is converted to active uPA, promoting pericellular plasminogen activity as well as the cleavage of uPAR itself at the D1 domain. The resulting GPI-anchored truncated form of the receptor, D2D3, is biologically inactive.^{27, 28} In addition, uPAR functions also depend on the interactions with the extracellular matrix protein, vitronectin (Vn),²⁸ and are modulated by the internalization and recycling induced by uPA-PAI-1.^{32, 33} Last, the receptor is partly recovered in the detergent resistant membrane fractions (DRM) similarly to other GPI-anchored proteins,³⁴ and also cleaved from the GPI-anchor.³⁵ These functions are reproduced by our functional EGFP-tagged uPAR.²⁹ In fact, we constructed the EGFP-tagged uPAR by inserting the sequence encoding EGFP between the third domain of uPAR and the GPI-anchoring sequence [Fig. 1b, scheme on the right], at a position where we had previously epitope-tagged uPAR without disrupting receptor function.³⁴

We also took into account the well-known intrinsic property of fluorescent proteins to dimerize that might introduce significant biases in dynamic studies of membrane proteins and, particularly, of GPI-anchored proteins.^{36, 37} For GPI-anchored proteins, the monomer-dimer/oligomer dynamics might constitute a regulatory mechanism of their biological activity, diffusion properties (i.e., segregation in membrane micro-domains), and localization at the cell surface. The monomer-dimer dynamics are particularly relevant for uPAR. It was shown that dimerization regulates the biological activity of this receptor by determining differential ligand binding and lipid raft partitioning, since DRM fractions were enriched in uPAR dimers and coincided with higher Vn-binding activity.³⁴ We minimized the tendency of EGFP to dimerize by introducing the A206K point mutation that does not significantly alter the spectral properties of the fluorophore.²⁶

uPAR-G was expressed in HEK293, because these cells do not produce wt-uPAR and do not secrete pro-uPA. The expression of wt-uPAR in HEK293 induces changes in cell morphology, migration, and signaling, as documented in our previous work.³⁸ These changes were well reproduced by uPAR-G, confirming retention of activity.²⁹ In HEK293/uPAR-G cells, the receptor localized heterogeneously at the cell surface and in intracellular vesicles, staining intense patches at the basal membrane, lamellipodia, and filopodia [compare Fig. 1b left and right panels, and Ref. 29].

We have also produced a biologically inactive model by expressing in the same HEK293 cell line the truncated form of uPAR, D2D3, which is also generated in vivo. After binding uPAR, uPA cleaves the receptor at the D1 domain, leaving the truncated form D2D3-GPI in the membrane. The fluorescent chimera of the truncated receptor, D2D3-G, cannot bind uPA, uPA-PAI-1, or Vn, and it does not promote pericellular plasminogen activity, but it is correctly sorted at the plasma membrane [Figure 1c] and partitions in DRM fractions similarly to the active uPAR-G (data not shown). D2D3-G stained the cell surface more homogenously than uPAR-G; it was not recruited at the basal side and did not form clusters [Fig. 1c, left panel], but it was present in filopodia and in membrane ruffles [Fig. 1c, right panel].

Having established the correct functionality of uPAR-G in HEK293 cells and generated a second cell line with a similar GPI-anchored protein, the D2D3-G, lacking uPAR activity, we have undertaken extensive subcloning of the cell lines, with the aim of selecting clones with low and similar expression uPAR-G or D2D3-G, suitable for two-photon fluorescence correlation spectroscopy (FCS) and photon counting histogram (PCH) analyses.

It has been demonstrated that a local concentration not higher than 10 molecules/volume is ideal for avoiding instrumental noise that overtakes the fluorescence fluctuations in the sample.²¹ Unfortunately, the induced expression of proteins in cells by conventional methods cannot be well controlled, and the expression levels of the exogenous protein vary significantly in a transfected cellular pool. When using a heterogeneous transfected pool, on the one hand, quite a lot of time must be spent to search cells with “optimal” counts, and as a consequence, the effort of acquiring a statistically significant number of measurements is almost prohibitive. On the other hand, variable levels of the protein can introduce biological drawbacks. As in the case of uPAR, the cellular phenotype can change, or the protein aggregates or it can be missorted in intracellular compartments, precluding any biological significance of the measurements. Thus, we used flow cytometry (data not shown) for evaluating the expression levels of uPAR-G and D2D3-G in each subclone and for selecting two subclones with low and comparable expression. The HEK293/uPAR-G clone used in the FCS and PCH experiments expressed $(12\pm 2)\times {10}^4$ receptors/cell as determined by binding assays using ${\mathrm{Eu}}^{3+}$ -labeled pro-uPA.²⁹

3.2.

Autocorrelation Functions and Molecular Brightness

To acquire fluorescence intensity traces, cells were first imaged, and then the fluorescence intensity was recorded after positioning the beam in specific regions on the in-focus plane. Representative regions are shown in Figs. 1b and 1c $(+)$ , and representative records are reported in Figs. 2 and 3 . We avoided collecting data in regions with punctuate structures such those visible in Figs. 1b and 1c (apical panels, $○$ ). These structures were often either vesicles or forming protrusions of the membrane (ruffles), in which the intensity was too high for FCS/PCH analysis (i.e., number of molecules $>5$ ). Interestingly, apical ruffles were significantly stained by D2D3-G, because this inactive form of uPAR was not engaged in the cell adhesion mechanism, and was not recruited at the basal side by the interaction with Vn [compare left and right panels in Figs. 1b and 1c]. We neglected regions in swinging filopodia [Figs. 1b and 1c, basal panels, $○$ ] and limited our experiments to more regular regions in the membranes.

Fig. 2

Combined FCS and PCH analysis of uPAR-G. Representative examples of fluorescence intensity records acquired in the apical membrane of three different cells (left panels), ACFs (middle panels), and photon counting histograms (right panels), showing a stationary record (a), a record in which large increases of intensity were observed (b), and a record in which a deep intensity drift occurred during the measurement (c). The black ACFs curves and histograms refer to the entire record. The record segments colored in blue and red (segments 1 and 2) were analyzed separately. The result of each analysis is reported in Table 1. (Color online only.)

Fig. 3

Combined FCS and PCH analysis of D2D3-G. Representative examples of fluorescence intensity traces acquired in the apical membrane of three different cells (left panels), ACFs (middle panels), and photon counting histograms (right panels), showing a stationary record (a), a record in which large increases of intensity were observed (b), and a record in which a deep intensity drift occurred during the measurement (c). The black ACFs curves and histograms refer to the entire record. The record segments colored in blue and red (segments 1 and 2) were analyzed separately. The result of each analysis is reported in Table 1. (Color online only.)

Furthermore, in HEK293/uPAR-G cells, we evaluated the brightness of the receptor only in apical membranes. As we have recently shown,²⁹ due to the direct interaction of uPAR-G with Vn, not only is the receptor recruited in intense clusters at the basal side of the cell [Fig. 1b, basal panel, $◻$ ], but also a fraction of it is immobile. Immobilization would reduce the molecular brightness values either by contributing a nonfluctuating fluorescent species or by bleaching the oligomers. Both processes would reduce the recovered brightness. We have indeed observed photobleaching in the basal regions of these cells²⁹ (that was never observed in HEK293/D2D3-G), and therefore we have not attempted to derive any conclusion about brightness from post-bleaching segments.

In each chosen region, we prolonged the acquisition of the fluorescence intensity for 200 to $300\mathrm{s}$ , at $20\mathrm{kHz}$ , since membrane proteins^{39, 40} diffuse in the range of $D=0.1–1\mathrm{\mu }{\mathrm{m}}^2∕\mathrm{s}$ .

Cells were analyzed at subconfluence, and in the best physiological conditions (i.e., in serum-rich medium). Under these conditions, cell movements as well as intracellular sorting of vesicles to the cell membrane were not abolished. Despite that, some intensity records were stable, and the average intensity was constant for 200 to $300\mathrm{s}$ [Fig. 2a, left panel]. In these cases, the ACF could be obtained using the entire data record, $6\times {10}^6$ data points [Fig. 2a, middle panel, black curve].

We also aimed at obtaining information on the aggregation state of the diffusing proteins. This information is important, since previous studies have shown that uPAR is present at the cell surface as monomers and dimers and suggested that dimerization might regulate the biological activity of the receptor by determining differential ligand binding and partition in membrane microdomains.³⁴ In principle, FCS analysis can resolve a mixture of fluorescent species by differences in their diffusion coefficient. Yet FCS lacks sensitivity when the molecular weight of two species differs by less than a factor of 5 to 8 (Ref. 41). Even in solution, the autocorrelation approach cannot separate a mixture of uPAR dimers and monomers.

Alternatively, the analysis of the brightness can provide information on the oligomerization state of the diffusing receptors.²⁴ The brightness of any fluorophore (i.e., the number of photons emitted per second per fluorophore at a given level of excitation) is an intrinsic molecular property of a molecule. The total brightness of a group of codiffusing fluorophores is the sum of the individual molecular brightness, in the absence of any electronic interactions among the fluorophores. Thus, brightness can be used to quantify the number of protein molecules moving together. The PCH can extract the molecular brightness from fluorescence fluctuation experiments by determining experimentally the probability distribution of the photon counts.²³ This method has been shown to be also a very powerful tool for the analysis of the brightness of molecules in the cellular environment.^{25, 42, 43}

Figure 2 (right panels) illustrates the PCHs for three representative analyses of apical membrane regions in HEK293/uPAR-G cells. The average brightness values (in a Gaussian-Lorentzian excitation volume) obtained from the histograms are reported in Table 1 . Chen and colleagues²⁵ demonstrated that integral PCH analysis (i.e., the analysis of the whole record) overestimates the molecular brightness due to drifts of intensity and showed how a segmentation procedure of the original data set (termed local PCH analysis) can provide the correct average brightness. By this procedure, the data record of an experiment is broken into small data sets, and the analysis is performed on each data segment to extract the particle concentration, $N$ , and the molecular brightness, ${\epsilon }_{local}$ . In the last step, the average of each parameter over all segments is determined to get the final parameters, $⟨N_{local}⟩$ and $⟨{\epsilon }_{local}⟩$ . The procedure was shown to work well for experiments²⁵ lasting typically few tens of seconds $(\sim 50\mathrm{s})$ and for data segments of 1 to $2\mathrm{s}$ . We have applied the same procedure on much longer records (200 to $300\mathrm{s}$ ), segmented the data in intervals of $9\mathrm{s}$ , and derived the average number of molecules, $⟨N_{local}⟩$ and $⟨{\epsilon }_{local}⟩$ (Table1). Overall, local PCH estimated lower values of molecular brightness, but when records were stationary, such as that in Fig. 2a, integral and local PCH were in good agreement. Nevertheless, due to the length of the experiments, stationary records were not as frequent as those showing large fluctuations [Fig. 2b] or intensity drifts [Fig. 2c]. This was not surprising, since cell movements and recycling of the receptor in vesicles, occurring in the time range of seconds, can corrupt the data. Thus, we inspected each record for determining which data segment could be considered for deriving diffusion coefficients and average molecular brightness.

Table 1

Representative analysis of molecular brightness of uPAR-G and D2D3-G.

The example in Fig. 2b illustrates an irregular record with sharp increases of intensity lasting 25 to $30\mathrm{s}$ [Fig. 2b, left panel, segment 2], and a stable segment [Fig. 2b, left panel, segment 1]. The ACF of the entire record [Fig. 2b, middle panel, black curve] was not acceptable for FCS analysis. This was mainly due to the contribution of the unsteady data segment [Fig. 2b, middle panel, red curve]. As a consequence, the average molecular brightness values obtained from integral and local PCH analyses were in disagreement (Table 1). The instability of the signal in subsets like segment 2, in fact, leads to artificially high estimates of the brightness [Table 1 and Fig. 2b, right panel, red curve]. Since in the same segment, ACF was far from equilibrium [Fig. 2b middle panel, red curve], we discarded both the integral and the local PCH analysis of the entire data set. Using only the data subset 1, the ACF reached equilibrium [Fig. 2b, middle panel, blue curve], and the integral and local PCH gave the same average molecular brightness (Table 1). Thus, in similar cases, we always limited our analysis to the most stationary data segment of the record.

We also observed intensity drifts likely due to out-of-focus effects [Fig. 2c, left panel]. The ACF over the entire record was not satisfactory [Fig. 2c, middle panel, black curve], and integral and local PCH analyses gave different estimates of the average brightness [Fig. 2c, right panel, black and blue histograms, and Table 1]. The brightness derived by the integral analysis was always higher than that obtained by local PCH (which had an uncertainty as high as 40%). Limiting both local and integral PCH analyses to the more stationary segment [segment 1 in Fig. 2c, left panel], we obtained again comparable values of the average molecular brightness (with less than 20% standard deviation). In similar cases, the out-of-focus segment contributed an apparent brightness significantly lower than that obtained in the best in-focus condition [Table 1 and Fig. 2c, right panel, red curve].

We performed the same analysis on HEK293/D2D3-G cells (Fig. 3 and Table 1). These cells adhered equally well to the dish when cultured in serum-rich medium. However, due to the lack of interaction with Vn, D2D3-G stained the cell membrane homogenously and did not accumulate in the basal side [Fig. 1c]. We used these cells as a control for the in-focus and out-of-focus effects on the molecular brightness. The laser beam was positioned on the central regions of the basal membrane and took in-focus [Fig. 4a , left and middle panel] and out-of-focus records [Fig. 4b, left and middle panels]. Also in these experiments, we selected the stationary segments of the data records for the integral and local PCH analyses. The out-of-focus brightness estimated by both analyses was remarkably lower than that derived in the best in-focus condition (Table 1 and Fig. 4). Therefore, we inspected each record and extracted the longer and stationary segment that fulfilled the necessary equilibrium conditions for ACF, in which, at the same time, ${\epsilon }_{local}$ was minimized and $⟨N_{local}⟩$ was less or equal to 5.

Fig. 4

In-focus and out-of-focus measurements on D2D3-G. The basal membrane of a D2D3-G cell was imaged in focus (a), and a region $(+)$ was chosen for acquiring a measurement [(a), middle panel]. The acquisition was repeated after moving the $z$ position of $1.2\mathrm{\mu }\mathrm{m}$ out of focus [(b), left and middle panels]. Photon count histograms [PCH A and PCH B, right panels] were computed using stationary in-focus and out-of-focus segments. The result of each analysis is reported in Table 1.

In D2D3-G cells, with the exception of filopodia and ruffles, we could explore all membrane regions having a homogenous staining. The $⟨{\epsilon }_{local}⟩$ values derived from these experiments are reported in Fig. 5 . The membrane thickness can be rather different among the basal and the apical membranes and the membrane junctions. Nevertheless, the distribution of $⟨{\epsilon }_{local}⟩$ in HEK293/D2D3-G cells did not reveal any significant dependence on the membrane region.

Fig. 5

Brightness of D2D3-G in different membrane regions. Average local brightness of D2D3-G in apical and basal regions of the cell membrane and in cell junctions. Number of measurements: apical=14; middle=9; basal=9. Measurements per cell=3 to 4.

In uPAR-G cells, confining our study to the apical membranes, we have shown that the complex uPA-PAI-1, a physiological inhibitor of uPAR, clearly modifies the brightness distribution.²⁹ The brightness distribution in the presence of the inhibitor [Fig. 6a ] was associated with that of monomeric uPAR-G also because FRET was abolished in HEK293 cells co-transfected with uPAR-G and the FRET acceptor uPAR-mRFP1-GPI.²⁹ Conversely, $⟨{\epsilon }_{local}⟩$ observed in the absence of the inhibitor in uPAR-G cells and in steady-state conditions was as high as twofold that of monomeric uPAR-G [Fig. 6b and Ref. 29]. A similar average brightness distribution was observed for the inactive form D2D3-G [Fig. 6c].

Fig. 6

Average molecular brightness of uPAR-G and D2D3-G in unperturbed cells. (a) Distribution of local brightness $\left({\epsilon }_{local}\right)$ of monomeric uPAR-G in apical membranes of HEK293 cells, in the presence of the inhibitor uPA-PAI-1. Inset: means $(⟨{\epsilon }_{local}⟩)$ , and minimum and maximum values for each measurement. Incubation with $8\mathrm{nM}$ uPA-PAI-1 was performed for $30\min$ , at $37°\mathrm{C}$ in DMEM, 0.1% BSA, $25\mathrm{mM}$ HEPES buffer. Records were inspected as described in the text, and stationary segments were submitted to local PCH analysis using $2.5\text{-}\mathrm{s}$ intervals (or $9\text{-}\mathrm{s}$ intervals, not shown). $⟨N_{local}⟩$ was less or equal to 5 in each measurement. Number or measurements=32, with 3 to 4 measurements per cell. (b) Average local brightness ratio for uPAR-G in unperturbed HEK293 cells. The ratio was computed between the values measured in the absence of uPA-PAI-1 and $⟨{\epsilon }_{local}⟩=4475\mathrm{cpsm}$ , which is the mean of 32 experiments in the presence of the inhibitor (a). The gray area was obtained considering the uncertainty on the distribution observed in the presence of the inhibitor: 25% percentile= $3338\mathrm{cpsm}$ , and 75% percentile= $5660\mathrm{cpsm}$ . Number of measurements=43, with 3 to 4 measurements per cell. (c) Average local brightness ratio for D2D3-G in unperturbed HEK293 cells computed as in (b), using the average brightness of uPAR-G in the presence of the inhibitor. The gray area was obtained as in (b). Number of measurements=32, with 3 to 4 measurements per cell.

The data indicate that both uPAR-G and D2D3-G undergo homotypic interactions leading to mixtures of diffusing monomers and dimers at the cell membrane. The two receptors clearly differ for the interaction with the extracellular matrix proteins, since the inactive D2D3-G does not accumulate in the basal membrane and is not irreversibly photobleached. It is also evident, however, that PCH analysis is not useful for studying the molecular forms of uPAR-G engaged in the interaction with Vn in basal membranes. This interesting point requires further investigation, which, however, is beyond the aim of this work.

3.3.

Diffusional Analysis of uPAR-G and D2D3-G at the Surface of Unperturbed HEK293 Cells

Using the preceding procedure for selecting suitable data segments, we analyzed in parallel the autocorrelation functions to determine the diffusion coefficients uPAR-G and D2D3-G in the cell membrane. The diffusion of both proteins was well represented only by the anomalous diffusion model [Sec. 2, Eq. 1 and Refs. 30, 44, 45], as shown by the representative fittings in Figs. 7a and 7b . Recently, we have discussed the diffusion models that best fit the ACFs of uPAR-G in the membrane of HEK293 cells and showed that the diffusion of the receptor could not be described by single- or two-component Brownian diffusion.²⁹ Diffusion [Fig. 7c] and anomality coefficients alpha [Fig. 7c, inset] from replicate experiments describe comparable behaviors of uPAR-G and D2D3-G.

Fig. 7

Diffusion and anomality coefficients $\alpha$ of uPAR-G and D2D3-G in unperturbed cells. Representative ACFs for uPAR-G (a) and D2D3-G (b) acquired in apical membranes. ACFs: black lines; fitted curves: red lines; residuals: blue lines. (c) Distribution of diffusion and alpha (inset) coefficients. Box-whisker plots show minimum, 25th percentile, median, 75th percentile, and maximum values. Number of measurements: uPAR-G=43; D2D3-G=32. (Color online only.)

Overall, the data suggest that the inactive and the active forms of the receptor have comparable features in the cell membrane: similar anomalous diffusion and diffusion coefficients, and similar distribution of monomeric and dimeric forms of the mobile fractions. Thus, neither the dimerization nor the diffusion anomality of uPAR-G can be simply related to the active form of the receptor in the cell membrane (with the exception of the basal membrane discussed earlier), in steady-state conditions and in the absence of extracellular ligands.

However, by combining FCS and PCH analyses on the same data segments, we could notice that only the diffusion coefficient of uPAR-G depends on the brightness (Fig. 8 ). The observed dependence is counter intuitive, since slow diffusion was associated with low brightness [Fig. 8a]. On the other hand, the diffusion coefficients of the inactive receptor did not depend on $⟨{\epsilon }_{local}⟩$ [Fig. 8b]. The difference in the slopes of the two correlations [shown superimposed in Fig. 8c] was statistically significant and could not be ascribed to differences in the anomality coefficients [Figs. 8d and 8e]; the alpha coefficients for both proteins were, in fact, brightness-independent [Fig. 8f].

Fig. 8

Dependence of diffusion coefficients on brightness for uPAR-G and D2D3-G in unperturbed cells. Diffusion coefficients of uPAR-G (a) and D2D3-G (b) versus average molecular brightness. Continuous lines: best-fitted linear correlation; inset: residuals. Correlation statistics for uPAR-G: $\mathrm{P}=0.01$ (deviation of the slope from zero is significant); $n=43$ . Correlation statistics for D2D3-G: $\mathrm{P}=0.83$ (deviation of the slope from zero is not significant); $n=32$ . The two best-fitted lines are superimposed in (c), and the 95% confidence band of each regression line is shown: uPAR-G—continuous line and $(\mid )$ ; D2D3-G—bold dashed line and (- - -). Alpha coefficients of uPAR-G (d) and D2D3-G (e) versus average molecular brightness. Continuous lines: best-fitted linear correlation; inset: residuals. Correlation statistics for uPAR-G: $\mathrm{P}=0.14$ (deviation of the slope from zero is not significant); $n=43$ . Correlation statistics for D2D3-G: $\mathrm{P}=0.32$ (deviation of the slope from zero is not significant); $n=32$ . The two best-fitted lines are superimposed in (f), and the 95% confidence band of each regression line is shown: uPAR-G—continuous line and $(\mid )$ ; D2D3-G—bold dashed line and (- - -).

Collectively, the data demonstrate that the active and inactive forms of uPAR are present as mixtures of monomers and dimers at the plasma membrane of live and unperturbed cells. Both GPI-anchored proteins diffuse anomalously; however, only the active form of uPAR shows fractions enriched in monomers that diffuse more slowly.