Functional and structural characterization of the first prokaryotic member of the L-amino acid transporter (LAT) family: a model for APC transporters

We have identified YkbA from Bacillus subtilis as a novel member of the L-amino acid transporter (LAT) family of amino acid transporters. The protein is approximately 30% identical in amino acid sequence to the light subunits of human heteromeric amino acid transporters. Purified His-tagged YkbA from Escherichia coli membranes reconstituted in proteoliposomes exhibited sodium-independent, obligatory exchange activity for L-serine and L-threonine and also for aromatic amino acids, albeit with less activity. Thus, we propose that YkbA be renamed SteT (Ser/Thr exchanger transporter). Kinetic analysis supports a sequential mechanism of exchange for SteT. Freeze-fracture analysis of purified, functionally active SteT in proteoliposomes, together with blue native polyacrylamide gel electrophoresis and transmission electron microscopy of detergent-solubilized purified SteT, suggest that the transporter exists in a monomeric form. Freeze-fracture analysis showed spherical particles with a diameter of 7.4 nm. Transmission electron microscopy revealed elliptical particles (diameters 6 x 7 nm) with a distinct central depression. To our knowledge, this is the first functional characterization of a prokaryotic member of the LAT family and the first structural data on an APC (amino acids, polyamines, and choline for organocations) transporter. SteT represents an excellent model to study the molecular architecture of the light subunits of heteromeric amino acid transporters and other APC transporters.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Dysfunctional 3D model based on structural and neuropsychological information

Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.

Bayesian model selection of structural explanatory models.

In this study we are proposing a Bayesian model selection methodology, where the best model from the list of candidate structural explanatory models is selected. The model structure is based on the Zellner's (1971)explanatory model with autoregressive errors. For the selection technique we are using a parsimonious model, where the model variables are transformed using Box and Cox (1964) class of transformations.

Bayesian model selection of structural explanatory models: Application to road accident data

Using the Bayesian approach as the model selection criteria, the main purpose in this study is to establish a practical road accident model that can provide a better interpretation and prediction performance. For this purpose we are using a structural explanatory model with autoregressive error term. The model estimation is carried out through Bayesian inference and the best model is selected based on the goodness of fit measures. To cross validate the model estimation further prediction analysis were done. As the road safety measures the number of fatal accidents in Spain, during 2000-2011 were employed. The results of the variable selection process show that the factors explaining fatal road accidents are mainly exposure, economic factors, and surveillance and legislative measures. The model selection shows that the impact of economic factors on fatal accidents during the period under study has been higher compared to surveillance and legislative measures.

The folded plate model in structural analysis. Elastic, plastic and dynamic formulations for nonprismatic structures

A specific numerical procedure for the analysis of arbitrary nonprismatic folded plate structures is presented. An elastic model is studied and compared with a harmonic solution for a prismatic structure. An extension to the plastic analysis is developed, and the influence of the structural geometry and loading pattern is analyzed. Nonprismatic practical cases, with arbitrary geometry and loading are shown, as well in the elastic range as in the plastic one. Finally, a dynamic formulation is outlined

A Polymer Model for the Structural Organization of Chromatin Loops and Minibands in Interphase Chromosomes

A quantitative model of interphase chromosome higher-order structure is presented based on the isochore model of the genome and results obtained in the field of copolymer research. G1 chromosomes are approximated in the model as multiblock copolymers of the 30-nm chromatin fiber, which alternately contain two types of 0.5- to 1-Mbp blocks (R and G minibands) differing in GC content and DNA-bound proteins. A G1 chromosome forms a single-chain string of loop clusters (micelles), with each loop ∼1–2 Mbp in size. The number of ∼20 loops per micelle was estimated from the dependence of geometrical versus genomic distances between two points on a G1 chromosome. The greater degree of chromatin extension in R versus G minibands and a difference in the replication time for these minibands (early S phase for R versus late S phase for G) are explained in this model as a result of the location of R minibands at micelle cores and G minibands at loop apices. The estimated number of micelles per nucleus is close to the observed number of replication clusters at the onset of S phase. A relationship between chromosomal and nuclear sizes for several types of higher eukaryotic cells (insects, plants, and mammals) is well described through the micelle structure of interphase chromosomes. For yeast cells, this relationship is described by a linear coil configuration of chromosomes.

Structural Analysis and Molecular Model of a Self-Incompatibility RNase from Wild Tomato1

Self-incompatibility RNases (S-RNases) are an allelic series of style glycoproteins associated with rejection of self-pollen in solanaceous plants. The nucleotide sequences of S-RNase alleles from several genera have been determined, but the structure of the gene products has only been described for those from Nicotiana alata. We report on the N-glycan structures and the disulfide bonding of the S3-RNase from wild tomato (Lycopersicon peruvianum) and use this and other information to construct a model of this molecule. The S3-RNase has a single N-glycosylation site (Asn-28) to which one of three N-glycans is attached. S3-RNase has seven Cys residues; six are involved in disulfide linkages (Cys-16-Cys-21, Cys-46-Cys-91, and Cys-166-Cys-177), and one has a free thiol group (Cys-150). The disulfide-bonding pattern is consistent with that observed in RNase Rh, a related RNase for which radiographic-crystallographic information is available. A molecular model of the S3-RNase shows that four of the most variable regions of the S-RNases are clustered on one surface of the molecule. This is discussed in the context of recent experiments that set out to determine the regions of the S-RNase important for recognition during the self-incompatibility response.

Role of hydrophobic interactions and desolvation in determining the structural properties of a model alpha beta peptide.

Model AB, a 20-amino acid peptide that was designed to adopt an alpha beta tertiary structure stabilized by hydrophobic interactions between residues in adjacent helical and extended segments, exhibited large pKa shifts of several ionizable groups and slow hydrogen/deuterium exchange rates of nearly all the peptide amide groups [Butcher, D. J., Bruch, M. D. & Moe, G. T. (1995) Biopolymers 36, 109-120]. These properties, which depend on structure and hydration, are commonly observed in larger proteins but are quite unusual for small peptides. To identify which of several possible features of the peptide design are most important in determining these properties, several closely related analogs of Model AB were characterized by CD and NMR spectroscopy. The results show that hydrophobic interactions between adjacent helical and extended segments are structure-determining and have the additional effect of altering water-peptide interactions over much of the peptide surface. These results may have important implications for understanding mechanisms of protein folding and for the design of independently folding peptides.

Transcriptional activation by protein-induced DNA bending: evidence for a DNA structural transmission model.

Integration host factor (IHF) is a DNA-bending protein that binds to an upstream activating sequence (UAS1) and, on a negatively supercoiled DNA template, activates transcription from the ilvPG promoter of the ilvG-MEDA operon of Escherichia coli. The transcriptional initiation site of the ilvGMEDA operon is located 92 bp downstream of UAS1. Activation is still observed when the orientation of the upstream IHF binding site is reversed. This manipulation places the IHF binding site on the opposite face of the DNA helix, directs the IHF-induced DNA bend in the opposite direction, and presents the opposite face of the nonsymmetrical, heterodimeric, IHF molecule to the downstream RNA polymerase. Lymphoid enhancer-binding factor, LEF-1, is a DNA-bending, lymphoid-specific, mammalian transcription factor that shares no amino acid sequence similarity with IHF. When the IHF site in UAS1 is replaced with a LEF-1 site, LEF-1 activates transcription from the downstream ilvPG promoter in E. coli as well as it is activated by its natural activator, IHF. These results suggest that specific interactions between IHF and RNA polymerase are not required for activation. The results of DNA structural studies show that IHF forms a protein-DNA complex in the UAS1 region that, in the absence of RNA polymerase, alters the structure of the DNA helix in the -10 hexanucleotide region of the downstream ilvPG promoter. The results of in vitro abortive transcription assays show that IIIF also increases the apparent rate of RNA polymerase isomerization from a closed to an open complex. We suggest, therefore, that IHF activates transcription by forming a higher-order protein-DNA complex in the UAS1 region that structurally alters the DNA helix in a way that facilitates open complex formation at the downstream ilvPG promoter site.

A mean field model of ligand-protein interactions: implications for the structural assessment of human immunodeficiency virus type 1 protease complexes and receptor-specific binding.

We propose a general mean field model of ligand-protein interactions to determine the thermodynamic equilibrium of a system at finite temperature. The method is employed in structural assessments of two human immuno-deficiency virus type 1 protease complexes where the gross effects of protein flexibility are incorporated by utilizing a data base of crystal structures. Analysis of the energy spectra for these complexes has revealed that structural and thermo-dynamic aspects of molecular recognition can be rationalized on the basis of the extent of frustration in the binding energy landscape. In particular, the relationship between receptor-specific binding of these ligands to human immunodeficiency virus type 1 protease and a minimal frustration principle is analyzed.