Three-dimensional structure of tropism-switching Bordetella bacteriophage.

Bacteriophage BPP-1, which infects Bordetella species, can switch its specificity by mutations to the ligand-binding surface of its major tropism-determinant protein, Mtd. This targeted mutagenesis results from the activity of a phage-encoded diversity-generating retroelement. Purified Mtd binds its receptor with low affinity, yet BPP-1 binding and infection of Bordettella cells are efficient because of high-avidity binding between phage-associated Mtd and its receptor. Here, using an integrative approach of three-dimensional (3D) structural analyses of the entire phage by cryo-electron tomography and single-prticle cryo-electron microscopy, we provide direct localization of Mtd in the phage and the structural basis of the high-avidity binding of the BPP-1 phage. Our structure shows that each BPP-1 particle has a T = 7 icosahedral head and an unusual tail apparatus consisting of a short central tail "hub," six short tail spikes, and six extended tail fibers. Subtomographic averaging of the tail fiber maps revealed a two-lobed globular structure at the distal end of each long tail fiber. Tomographic reconstructions of immuno-gold-labeled BPP-1 directly localized Mtd to these globular structures. Finally, our icosahedral reconstruction of the BPP-1 head at 7A resolution reveals an HK97-like major capsid protein stabilized by a smaller cementing protein. Our structure represents a unique bacteriophage reconstruction with its tail fibers and ligand-binding domains shown in relation to its tail apparatus. The localization of Mtd at the distal ends of the six tail fibers explains the high avidity binding of Mtd molecules to cell surfaces for initiation of infection.

Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^

Development of a SPECT -based three-dimensional treatment planner for radionuclide therapy with iodine -131

Accurate calculation of absorbed dose to target tumors and normal tissues in the body is an important requirement for establishing fundamental dose-response relationships for radioimmunotherapy. Two major obstacles have been the difficulty in obtaining an accurate patient-specific 3-D activity map in-vivo and calculating the resulting absorbed dose. This study investigated a methodology for 3-D internal dosimetry, which integrates the 3-D biodistribution of the radionuclide acquired from SPECT with a dose-point kernel convolution technique to provide the 3-D distribution of absorbed dose. Accurate SPECT images were reconstructed with appropriate methods for noise filtering, attenuation correction, and Compton scatter correction. The SPECT images were converted into activity maps using a calibration phantom. The activity map was convolved with an $\sp{131}$I dose-point kernel using a 3-D fast Fourier transform to yield a 3-D distribution of absorbed dose. The 3-D absorbed dose map was then processed to provide the absorbed dose distribution in regions of interest. This methodology can provide heterogeneous distributions of absorbed dose in volumes of any size and shape with nonuniform distributions of activity. Comparison of the activities quantitated by our SPECT methodology to true activities in an Alderson abdominal phantom (with spleen, liver, and spherical tumor) yielded errors of $-$16.3% to 4.4%. Volume quantitation errors ranged from $-$4.0 to 5.9% for volumes greater than 88 ml. The percentage differences of the average absorbed dose rates calculated by this methodology and the MIRD S-values were 9.1% for liver, 13.7% for spleen, and 0.9% for the tumor. Good agreement (percent differences were less than 8%) was found between the absorbed dose due to penetrating radiation calculated from this methodology and TLD measurement. More accurate estimates of the 3-D distribution of absorbed dose can be used as a guide in specifying the minimum activity to be administered to patients to deliver a prescribed absorbed dose to tumor without exceeding the toxicity limits of normal tissues. ^

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

NHERF1 – New Modifier of Colorectal Cancer Progression

Colorectal cancer (CRC) develops from multiple progressive modifications of normal intestinal epithelium into adenocarcinoma. Loss of cell polarity has been implicated as an early event in this process, but the molecular players involved are not well known. NHERF1 (Na+/H+ Exchanger Regulatory Factor 1) is an adaptor protein with apical membrane localization in polarized epithelia. In this study, we tested our hypothesis that NHERF1 plays a role in CRC. We examined surgical CRC resection specimens for changes in NHERF1 expression, and modeled these changes in two- and three-dimensional (2D and 3D) Caco-2 CRC cell systems. NHERF1 had significant alterations from normal to adenoma and carcinoma transitions (2=38.5, d.f.=4, P<0.001), displaying apical membrane localization in normal tissue but loss of expression in adenoma and ectopic overexpression in carcinoma. In Caco-2 cell models, NHERF1 depletion induced epithelial-mesenchymal-transition in 2D cell monolayers and disruption of apical-basal polarity in 3D cyst system. The mesenchymal phenotype of NHERF1-depleted cells was fully restored by re-expression of NHERF1 at the apical membrane. Cytoplasmic and nuclear NHERF1 re-expression not only failed to restore the epithelial phenotype but led to more aggressive phenotypes. Our findings suggest that membrane NHERF1 is an important regulator of epithelial morphogenesis, and that changes in NHERF1 expression correlate with CRC progression. NHERF1 loss and ectopic expression that induce massive disruption of epithelial cell polarity may, thereby, mark important steps in CRC development.