Expression of the alpha 1-proteinase inhibitor gene family during evolution of the genus Mus

alpha 1-Proteinase inhibitors (alpha 1-PIs) are members of the serpin superfamily of proteinase inhibitors, and are important in the maintenance of homeostasis in a wide variety of animal taxa. Previous studies have shown that in mice (genus Mus), evolution of alpha 1-PIs is characterized by gene amplification, region-specific concerted evolution, and rapid accumulation of amino acid substitutions. The latter occurs primarily in the reactive center, which is the region of the alpha 1-PI molecule that determines the inhibitor's specificity for target proteinases. The P1 residue within the reactive center, which is methionine in so-called orthodox alpha 1-PIs and an amino acid other than methionine in unorthodox alpha 1-PIs, is a primary determinant of inhibitor specificity. In the present study, we find that the expression of mRNAs encoding unorthodox alpha 1-PIs is polymorphic within Mus species, i.e., among individuals or inbred strains. This is in striking contrast to mRNAs that encode orthodox alpha 1-PIs, whose concentrations are relatively invariant. The intraspecies variations in mRNA expression represent polymorphisms in the structure of the alpha 1- PI gene family. The results, taken together with previously described aspects of alpha 1-PI evolution, indicate that the dissimilar levels of polymorphism exhibited by orthodox and unorthodox alpha 1-PIs, which likely have distinct physiological functions, may reflect different levels of selective constraint. The significance of this finding to the evolution of gene families is discussed.      

A Consensus Data Mining secondary structure prediction by combining GOR V and Fragment Database Mining

The major aim of tertiary structure prediction is to obtain protein models with the highest possible accuracy. Fold recognition, homology modeling, and de novo prediction methods typically use predicted secondary structures as input, and all of these methods may significantly benefit from more accurate secondary structure predictions. Although there are many different secondary structure prediction methods available in the literature, their cross-validated prediction accuracy is generally <80%. In order to increase the prediction accuracy, we developed a novel hybrid algorithm called Consensus Data Mining (CDM) that combines our two previous successful methods: (1) Fragment Database Mining (FDM), which exploits the Protein Data Bank structures, and (2) GOR V, which is based on information theory, Bayesian statistics, and multiple sequence alignments (MSA). In CDM, the target sequence is dissected into smaller fragments that are compared with fragments obtained from related sequences in the PDB. For fragments with a sequence identity above a certain sequence identity threshold, the FDM method is applied for the prediction. The remainder of the fragments are predicted by GOR V. The results of the CDM are provided as a function of the upper sequence identities of aligned fragments and the sequence identity threshold. We observe that the value 50% is the optimum sequence identity threshold, and that the accuracy of the CDM method measured by Q(3) ranges from 67.5% to 93.2%, depending on the availability of known structural fragments with sufficiently high sequence identity. As the Protein Data Bank grows, it is anticipated that this consensus method will improve because it will rely more upon the structural fragments.     

An enhanced elastic network model to represent the motions of domain-swapped proteins

Domain swapping is a process where two (or more) protein molecules form a dimer (or higher oligomer) by exchanging an identical domain. In this article, based on the observation that domains are rigid and hinge loops are highly flexible, we propose a new Elastic Network Model, domain-ENM, for domain-swapped proteins. In this model, the rigidity of domains is taken into account by using a larger spring constant for intradomain contacts. The large-scale transition of domain swapping is then novelly decomposed into the relative motion between the rigid domains (only 6 degrees of freedom) plus the internal fluctuations of each domain. Consequently, this approach has the potential to produce much more meaningful transition pathways than other simulation approaches that try to find pathways in a search space of large numbers of dimensions. In this article, we also propose a new way to define the overlap measure. Past approaches used an inappropriate comparison of the large-scale conformation displacement against the computed infinitesimal motions of modes. Here, we propose an infinitesimal version of the large-scale conformation change and then compare it with the modes of motions. As a result, we obtain much better overlap values. Using this new overlap definition, we are also able for the first time to give a clear, intuitive explanation why "open" forms tend to produce better overlap values than "closed" forms with traditional ENMs. Finally, as an application, we present a simple approach to show how domain-ENM can be used to generated transition pathways for domain-swapped proteins.     

Application of flow cytometry to detection and characterization of Legionella spp.

Flow cytometry, using fluorescein-bound specific antibodies and propidium iodide, was shown to be effective in detecting Legionella spp. in cooling tower waters. The procedure was quicker and less labor intensive than fluorescent microscopy. The use of these procedures also identified qualitative differences, perhaps related to infectivity, in Legionella populations.     

Conformational Analysis of the Tachykinins in Solution: Substance P and Physalaemin

Abstract

A determination of the solution conformational behavior of two tachykinins, substance P and physalaemin, is described. Two-dimensional homonuclear Hartmann-Hahn (HOHAHA) and rotating-frame cross relaxation spectroscopy (ROESY) are used to obtain complete proton resonance assignments. Interproton distance restraints obtained from ROESY spectroscopy are used to characterize the conformational behavior. These data show that in solution both substance P and physalaemin exist in a mixture of conformational states, rather than as a single three-dimensional structure. In water both peptides prefer to be in an extended chain structure. In methanol, their behavior is described as a mixture of β-turn conformations in dynamic equilibrium. Solvent titration data and chemical shift temperature coefficients complement the NMR estimate of interproton distances by locating hydrogen bonds and serving to identify predominant conformational states. The C-terminal tetrapeptide segment has the same conformational behavior for both substance P and physalaemin. In physalaemin, the midsegment of the peptide may also be constrained by formation of a salt bridge. The conformational behavior of substance P and physalaemin is discussed in relation to potency and receptor binding properties.     

Differential effects of mutant SOD1 on protein structure of skeletal muscle and spinal cord of familial amyotrophic lateral sclerosis: Role of chaperone network

Protein misfolding is considered to be a potential contributing factor for motor neuron and muscle loss in diseases like Amyotrophic lateral sclerosis (ALS). Several independent studies have demonstrated using over-expressed mutated Cu/Zn-superoxide dismutase (mSOD1) transgenic mouse models which mimic familial ALS (f-ALS), that both muscle and motor neurons undergo degeneration during disease progression. However, it is unknown whether protein conformation of skeletal muscle and spinal cord is equally or differentially affected by mSOD1-induced toxicity. It is also unclear whether heat shock proteins (Hsp′s) differentially modulate skeletal muscle and spinal cord protein structure during ALS disease progression. We report three intriguing observations utilizing the f-ALS mouse model and cell-free in vitro system; (i) muscle proteins are equally sensitive to misfolding as spinal cord proteins despite the presence of low level of soluble and absence of insoluble G93A protein aggregate, unlike in spinal cord, (ii) Hsp′s levels are lower in muscle compared to spinal cord at any stage of the disease, and (iii) G93ASOD1 enzyme-induced toxicity selectively affects muscle protein conformation over spinal cord proteins. Together, these findings strongly suggest that differential chaperone levels between skeletal muscle and spinal cord may be a critical determinant for G93A-induced protein misfolding in ALS.     

Structure and function of LCI1: a plasma membrane CO2 channel in the Chlamydomonas CO2 concentrating mechanism

Microalgae and cyanobacteria contribute roughly half of the global photosynthetic carbon assimilation. Faced with limited access to CO₂ in aquatic environments, which can vary daily or hourly, these microorganisms have evolved use of an efficient CO₂ concentrating mechanism (CCM) to accumulate high internal concentrations of inorganic carbon (C_i) to maintain photosynthetic performance. For eukaryotic algae, a combination of molecular, genetic and physiological studies using the model organism Chlamydomonas reinhardtii, have revealed the function and molecular characteristics of many CCM components, including active C_i uptake systems. Fundamental to eukaryotic C_i uptake systems are C_i transporters/channels located in membranes of various cell compartments, which together facilitate the movement of C_i from the environment into the chloroplast, where primary CO₂ assimilation occurs. Two putative plasma membrane C_i transporters, HLA3 and LCI1, are reportedly involved in active C_i uptake. Based on previous studies, HLA3 clearly plays a meaningful role in HCO₃^? transport, but the function of LCI1 has not yet been thoroughly investigated so remains somewhat obscure. Here we report a crystal structure of the full‐length LCI1 membrane protein to reveal LCI1 structural characteristics, as well as in vivo physiological studies in an LCI1 loss‐of‐function mutant to reveal the C_i species preference for LCI1. Together, these new studies demonstrate LCI1 plays an important role in active CO₂ uptake and that LCI1 likely functions as a plasma membrane CO₂ channel, possibly a gated channel.