Plasma Membrane Organization of Epidermal Growth Factor Receptor in Resting and Ligand-Bound States

AbstractThe spatial arrangement of the epidermal growth factor receptor (EGFR) on the cellular plasma membrane is one of the prime factors that control its downstream signaling pathways and related functions. However, the molecular organization, which spans the scale from nanometers to micrometer-size clusters, has not been resolved in detail, mainly due to a lack of techniques with the required spatiotemporal resolution. Therefore, we used imaging total internal reflection-fluorescence correlation spectroscopy to investigate EGFR dynamics on live CHO-K1 plasma membranes in resting and ligand-bound states. In combination with the fluorescence correlation spectroscopy diffusion law, this provides information on the subresolution organization of EGFR on cell membranes. We found that overall EGFR organization is sensitive to both cholesterol and the actin cytoskeleton. EGFR in the resting state is partly trapped in cholesterol-containing domains, whereas another fraction exhibits cholesterol independent trapping on the membrane. Disruption of the cytoskeleton leads to a broader range of EGFR diffusion coefficients and a reduction of hop diffusion. In the ligand-bound state we found a dose-dependent behavior. At 10 ng/mL EGF the EGFR is endocytosed and recycled to the membrane, whereas diffusion and organization do not change significantly. At 100 ng/mL EGF the EGFR forms clusters, which are subsequently internalized, whereas outside the clusters diffusivity increases and the organization of the receptor remains unchanged. After disruption of cholesterol-containing domains or actin cytoskeleton, EGF induces microscopic EGFR clusters on the membrane and endocytosis is inhibited

Membrane destabilization by monomeric hIAPP observed by imaging fluorescence correlation spectroscopy

Monomeric hIAPP significantly destabilizes both model and live cell membranes by increasing membrane fluidity. This interaction with membranes happens via carpet formation followed by lipid extraction in a concentration dependent manner and thus we propose that hIAPP aggregation prior to membrane interaction may not be necessary for its cytotoxicity

Long-range formation of the Bicoid gradient requires multiple dynamic modes that spatially vary across the embryo

Morphogen gradients provide essential positional information to gene networks through their spatially heterogeneous distribution, yet how they form is still hotly contested, with multiple models proposed for different systems. Here, we focus on the transcription factor Bicoid (Bcd), a morphogen that forms an exponential gradient across the anterior-posterior (AP) axis of the early Drosophila embryo. Using fluorescence correlation spectroscopy we find there are spatial differences in Bcd diffusivity along the AP axis, with Bcd diffusing more rapidly in the posterior. We establish that such spatially varying differences in Bcd dynamics are sufficient to explain how Bcd can have a steep exponential gradient in the anterior half of the embryo and yet still have an observable fraction of Bcd near the posterior pole. In the nucleus, we demonstrate that Bcd dynamics are impacted by binding to DNA. Addition of the Bcd homeodomain to eGFP::NLS qualitatively replicates the Bcd concentration profile, suggesting this domain regulates Bcd dynamics. Our results reveal how a long-range gradient can form while retaining a steep profile through much of its range

Selective influence of Sox2 on POU transcription factor binding in embryonic and neural stem cells

Embryonic stem cell (ESC) identity is orchestrated by co-operativity between the transcription factors (TFs) Sox2 and the class V POU-TF Oct4 at composite Sox/Oct motifs. Neural stem cells (NSCs) lack Oct4 but express Sox2 and class III POU-TFs Oct6, Brn1 and Brn2. This raises the question of how Sox2 interacts with POU-TFs to transcriptionally specify ESCs versus NSCs. Here, we show that Oct4 alone binds the Sox/Oct motif and the octamer-containing palindromic MORE equally well. Sox2 binding selectively increases the affinity of Oct4 for the Sox/Oct motif. In contrast, Oct6 binds preferentially to MORE and is unaffected by Sox2. ChIP-Seq in NSCs shows the MORE to be the most enriched motif for class III POU-TFs, including MORE subtypes, and that the Sox/Oct motif is not enriched. These results suggest that in NSCs, co-operativity between Sox2 and class III POU-TFs may not occur and that POU-TF-driven transcription uses predominantly the MORE cis architecture. Thus, distinct interactions between Sox2 and POU-TF subclasses distinguish pluripotent ESCs from multipotent NSCs, providing molecular insight into how Oct4 alone can convert NSCs to pluripotency. EMBO Rep 2015 Sep; 16(9):1177-91

Dynamic changes in Sox2 spatio-temporal expression promote the second cell fate decision through <i>Fgf4/Fgfr2</i> signaling in preimplantation mouse embryos

Oct4 and Sox2 regulate the expression of target genes such as Nanog, Fgf4, and Utf1, by binding to their respective regulatory motifs. Their functional cooperation is reflected in their ability to heterodimerize on adjacent cis regulatory motifs, the composite Sox/Oct motif. Given that Oct4 and Sox2 regulate many developmental genes, a quantitative analysis of their synergistic action on different Sox/Oct motifs would yield valuable insights into the mechanisms of early embryonic development. In the present study, we measured binding affinities of Oct4 and Sox2 to different Sox/Oct motifs using fluorescence correlation spectroscopy. We found that the synergistic binding interaction is driven mainly by the level of Sox2 in the case of the Fgf4 Sox/Oct motif. Taking into account Sox2 expression levels fluctuate more than Oct4, our finding provides an explanation on how Sox2 controls the segregation of the epiblast and primitive endoderm populations within the inner cell mass of the developing rodent blastocyst. Biochem J 2018 Mar 20;475(6):1075-1089

Bayesian Model Selection Applied to the Analysis of Fluorescence Correlation Spectroscopy Data of Fluorescent Proteins in Vitro and in Vivo

Fluorescence correlation spectroscopy (FCS) is a powerful technique to investigate molecular dynamics with single molecule sensitivity. In particular, in the life sciences it has found widespread application using fluorescent proteins as molecularly specific labels. However, FCS data analysis and interpretation using fluorescent proteins remains challenging due to typically low signal-to-noise ratio of FCS data and correlated noise in autocorrelated data sets. As a result, naive fitting procedures that ignore these important issues typically provide similarly good fits for multiple competing models without clear distinction of which model is preferred given the signal-to-noise ratio present in the data. Recently, we introduced a Bayesian model selection procedure to overcome this issue with FCS data analysis. The method accounts for the highly correlated noise that is present in FCS data sets and additionally penalizes model complexity to prevent over interpretation of FCS data. Here, we apply this procedure to evaluate FCS data from fluorescent proteins assayed in vitro and in vivo. Consistent with previous work, we demonstrate that model selection is strongly dependent on the signal-to-noise ratio of the measurement, namely, excitation intensity and measurement time, and is sensitive to saturation artifacts. Under fixed, low intensity excitation conditions, physical transport models can unambiguously be identified. However, at excitation intensities that are considered moderate in many studies, unwanted artifacts are introduced that result in nonphysical models to be preferred. We also determined the appropriate fitting models of a GFP tagged secreted signaling protein, Wnt3, in live zebrafish embryos, which is necessary for the investigation of Wnt3 expression and secretion in development. Bayes model selection therefore provides a robust procedure to determine appropriate transport and photophysical models for fluorescent proteins when appropriate models are provided, to help detect and eliminate experimental artifacts in solution, cells, and in living organisms.National Science Foundation (U.S.). Physics of Living Systems ProgramNational Institute of Mental Health (U.S.) (Award U01MH106011

Weak Glycolipid Binding of a Microdomain-Tracer Peptide Correlates with Aggregation and Slow Diffusion on Cell Membranes

10.1371/journal.pone.0051222PLoS ONE712

Splitting the Difference: Sorting Photons to Improve Quantitative Measurements in Correlation Spectroscopy

10.1016/j.bpj.2020.08.017BIOPHYSICAL JOURNAL11971268-126