Cramér-Rao Lower Bound for Point Based Image Registration With Heteroscedastic Error Model for Application in Single Molecule Microscopy.

The Cramér-Rao lower bound for the estimation of the affine transformation parameters in a multivariate heteroscedastic errors-in-variables model is derived. The model is suitable for feature-based image registration in which both sets of control points are localized with errors whose covariance matrices vary from point to point. With focus given to the registration of fluorescence microscopy images, the Cramér-Rao lower bound for the estimation of a feature's position (e.g., of a single molecule) in a registered image is also derived. In the particular case where all covariance matrices for the localization errors are scalar multiples of a common positive definite matrix (e.g., the identity matrix), as can be assumed in fluorescence microscopy, then simplified expressions for the Cramér-Rao lower bound are given. Under certain simplifying assumptions these expressions are shown to match asymptotic distributions for a previously presented set of estimators. Theoretical results are verified with simulations and experimental data.

Analysis of Point Based Image Registration Errors With Applications in Single Molecule Microscopy.

We present an asymptotic treatment of errors involved in point-based image registration where control point (CP) localization is subject to heteroscedastic noise; a suitable model for image registration in fluorescence microscopy. Assuming an affine transform, CPs are used to solve a multivariate regression problem. With measurement errors existing for both sets of CPs this is an errors-in-variable problem and linear least squares is inappropriate; the correct method being generalized least squares. To allow for point dependent errors the equivalence of a generalized maximum likelihood and heteroscedastic generalized least squares model is achieved allowing previously published asymptotic results to be extended to image registration. For a particularly useful model of heteroscedastic noise where covariance matrices are scalar multiples of a known matrix (including the case where covariance matrices are multiples of the identity) we provide closed form solutions to estimators and derive their distribution. We consider the target registration error (TRE) and define a new measure called the localization registration error (LRE) believed to be useful, especially in microscopy registration experiments. Assuming Gaussianity of the CP localization errors, it is shown that the asymptotic distribution for the TRE and LRE are themselves Gaussian and the parameterized distributions are derived. Results are successfully applied to registration in single molecule microscopy to derive the key dependence of the TRE and LRE variance on the number of CPs and their associated photon counts. Simulations show asymptotic results are robust for low CP numbers and non-Gaussianity. The method presented here is shown to outperform GLS on real imaging data.

IMAGE REGISTRATION ERROR ANALYSIS WITH APPLICATIONS IN SINGLE MOLECULE MICROSCOPY.

This paper is concerned with assessing localization errors emanating from the image registration of two monochromatic fluorescence microscopy images. Assuming an affine transform exists between images, registration in this setting typically involves using control points to solve a multivariate linear regression problem; however with measurement errors existing in both sets of variables the use of linear least squares is inappropriate. It is shown that image registration is an errors-in-variable problem and as such the correct method is to use generalized least squares. Traditionally this requires the measurement errors to be independent and identically distributed (iid); an assumption that is rarely satisfied in practical situations. An extension of the multivariate generalized least squares estimator that allows non-iid noise is applied. The distributional properties of the estimators are used to derive localization errors emanating from the image registration process in terms of photon counts and experimental parameters.

Measurement Errors in Fluorescence Microscopy Image Registration.

Image registration is an important processing step in fluorescence microscopy, for example in tracking or super-resolution methods. Precision localization of single fluorescent molecules from a quantum limited photon detection process, subject to Gaussian readout noise, is key to the use of single molecule microscopy. It is therefore important to know the effect that registration has on the accuracy of localizing a single molecule. Here we demonstrate a suitable approach to image registration that accounts for point-wise errors in localizing the control points typically used in fluorescence microscopy. This allows expressions for the localization errors caused by the registration process to be derived, showing dependence on the number of control points and their associated photon counts.

Noise suppression of point spread functions and its influence on deconvolution of three-dimensional fluorescence microscopy image sets.

The point spread function (PSF) is of central importance in the image restoration of three-dimensional image sets acquired by an epifluorescent microscope. Even though it is well known that an experimental PSF is typically more accurate than a theoretical one, the noise content of the experimental PSF is often an obstacle to its use in deconvolution algorithms. In this paper we apply a recently introduced noise suppression method to achieve an effective noise reduction in experimental PSFs. We show with both simulated and experimental three-dimensional image sets that a PSF that is smoothed with this method leads to a significant improvement in the performance of deconvolution algorithms, such as the regularized least-squares algorithm and the accelerated Richardson-Lucy algorithm.

Differences in promiscuity for antibody-FcRn interactions across species: implications for therapeutic antibodies.

Preclinical tests of therapeutic antibodies are frequently carried out in mice to evaluate pharmacokinetics and efficacy. However, the observation that mouse IgG are cleared rapidly from the human circulation suggests that mice may not always be an ideal model. The Fc receptor, FcRn, regulates the serum half-lives of IgG in mice and most likely has a similar function in humans. In the current study we have carried out an extensive analysis of the interaction of the human or mouse forms of FcRn with IgG from various species using surface plasmon resonance. We show that in contrast to mouse FcRn, human FcRn is surprisingly stringent in its binding specificity for IgG derived from different species. Human FcRn binds to human, rabbit and guinea pig IgG, but not significantly to rat, bovine, sheep or mouse IgG (with the exception of weak binding to mouse IgG2b). In contrast, mouse FcRn binds to all IgG analyzed. The lack of binding of human FcRn to mouse IgG1 has been confirmed using transfectants that have been engineered to express human FcRn on the cell surface. Our results provide a molecular explanation for the enigmatic observation that mouse IgG behave anomalously in humans. These studies have implications for the successful application of therapeutic antibodies.

The MHC class I-related receptor, FcRn, plays an essential role in the maternofetal transfer of gamma-globulin in humans.

The transfer of maternal gamma-globulin (IgG) provides the neonate with humoral immunity during early life. In humans, maternal IgG is transported across the placenta during the third trimester of pregnancy. The expression of the MHC class I-related receptor, FcRn, in the human placenta suggests that this Fc receptor might be involved in the delivery of maternal IgG, but direct evidence to support this is lacking. In the current study an ex vivo placental model has been used to analyze the maternofetal transfer of a recombinant, humanized (IgG1) antibody in which His435 has been mutated to alanine (H435A). In vitro binding studies using surface plasmon resonance indicate that the mutation ablates binding of the antibody to recombinant mouse and human FcRn. Relative to the wild-type antibody, the H435A mutant is deficient in transfer across the placenta. Significantly, the mutation does not affect binding to Fc gamma RIII, an FcR that has been suggested in earlier studies to mediate the transfer of maternal IgG. The analyses demonstrate that binding of an IgG to FcRn is a prerequisite for transport across the perfused placenta. FcRn therefore plays a central role in the maternofetal delivery of IgG and this has implications for the use of protein engineering to improve the properties of therapeutic antibodies.

Kinetics and thermodynamics of T cell receptor- autoantigen interactions in murine experimental autoimmune encephalomyelitis.

In the current study, cellular and molecular approaches have been used to analyze the biophysical nature of T cell receptor (TCR)-peptide MHC (pMHC) interactions for two autoreactive TCRs. These two TCRs recognize the N-terminal epitope of myelin basic protein (MBP1-11) bound to the MHC class II protein, I-A(u), and are associated with murine experimental autoimmune encephalomyelitis. Mice transgenic for the TCRs have been generated and characterized in other laboratories. These analyses indicate that the mice either develop encephalomyelitis spontaneously (172.10 TCR) or only if immunized with autoantigen in adjuvant (1934.4 TCR). Here, we show that the 172.10 TCR binds MBP1-11:I-A(u) with a 4-5-fold higher affinity than the 1934.4 TCR. Consistent with the higher affinity, 172.10 T hybridoma cells are significantly more responsive to autoantigen than 1934.4 cells. The interaction of the 172.10 TCR with cognate ligand is more entropically unfavorable than that of the 1934.4 TCR, indicating that the 172.10 TCR undergoes greater conformational rearrangements upon ligand binding. The studies therefore suggest a correlation between the strength and plasticity of a TCR-pMHC interaction and the frequency of spontaneous disease in the corresponding TCR transgenic mice. The comparative analysis of these two TCRs has implications for understanding autoreactive T cell recognition and activation.

A role for the region encompassing the c" strand of a TCR V alpha domain in T cell activation events.

The distinct strand topology of TCR V alpha domains results in a flatter surface in the region encompassing the c" strand than the corresponding region in Ig V domains. In the current study a possible role for this region in T cell activation has been investigated by inserting a potential glycosylation site at V alpha residue 82. This residue is in proximity to the c" strand and distal to the putative interaction site for cognate peptide:MHC ligand. An additional N-linked carbohydrate at this position would create a protrusion on the V alpha domain surface, and this may interfere with TCR aggregation and/or recruitment of signaling molecules. The modified TCR has been expressed in transfected T cells, and the phenotype following stimulation has been compared with that of cells expressing the wild-type TCR. The mutation has significant effects on activation-induced cell death and TCR internalization, but, unexpectedly, does not affect IL-2 secretion. Furthermore, analyses with tetrameric, peptide:MHC class II complexes suggest that the mutation decreases the ability of the TCR to aggregate into a configuration compatible with avid binding by these multivalent ligands.

The influence of signal noise on the accuracy of kinetic constants measured by surface plasmon resonance experiments.

An analysis is carried out to investigate the accuracy of kinetic parameters obtained using surface plasmon resonance methodology with a BIAcore instrument. The Cramer Rao lower bound for the least possible variance of an estimator of the kinetic parameters is determined. Using simulations it is shown that the standard least-squares estimation technique provides estimates that achieve this bound. The theoretical and simulation results are compared with experimental data obtained from an analysis of the interaction of the myc peptide with the anti-myc antibody, 9E10. This investigation indicates that the accuracy of the results depends on the signal level which has particular relevance to the design of experiments with low signal levels. It is shown how the accuracy of the estimates of the kinetic constants depends on the kinetic constants themselves and how the accuracy of the association constants depends on the concentration of the analyte that is used in the experiment. In addition, the effects of increasing the number of data points in the analysis of dissociation data on the accuracy of the estimates are quantitated. It is also demonstrated that signal averaging of data derived from repeat sensorgrams can result in a significant decrease in the standard deviation of the estimates.

The choice of reference cell in the analysis of kinetic data using BIAcore.

An important step in the analysis of sensorgram data for BIAcore experiments is the subtraction of reference cell data to remove the effects of the bulk shift on the sensorgram of interest. It is shown that this step can introduce errors in the measured kinetic constants. This phenomenon is investigated both theoretically and with experimental data.

Increasing the serum persistence of an IgG fragment by random mutagenesis.

The major histocompatibility complex (MHC) class I-related receptor FcRn is involved in regulating serum gammaglobulin (IgG) levels in mice. With the aim of increasing the serum half-life of a recombinant murine Fc gamma 1 fragment, the affinity for binding to FcRn at pH 6.0 has been increased by random mutagenesis of Thr252, Thr254, and Thr256 followed by selection using bacteriophage display. These residues were chosen as they are in proximity to the FcRn-IgG (Fc) interaction site. Two mutants with higher affinity (due to lower off-rates) than the wild-type Fc have been isolated and analyzed in pharmacokinetic studies in mice. The mutant with the highest affinity has a significantly longer serum half-life than the wild type fragment, despite its lower off-rate from FcRn at pH 7.4. The results provide support for the involvement of FcRn in the homeostasis of serum IgGs in mice. The indications that a homologous FcRn regulates IgG levels in humans suggest that this approach has implications for increasing the serum persistence of therapeutic antibodies.