Self-organization of an oscillatory neural system

Hebbian dynamics is used to derive the differential equations for the synaptic strengths in the neural circuitry of the locomotive oscillator. Initially, neural connection are random. Under a specified arborization hypothesis relating to the density of neural connections, the differential equations are shown to model the self-organization and the stability of the oscillator.     

A common landscape for membrane‐active peptides

Three families of membrane‐active peptides are commonly found in nature and are classified according to their initial apparent activity. Antimicrobial peptides are ancient components of the innate immune system and typically act by disruption of microbial membranes leading to cell death. Amyloid peptides contribute to the pathology of diverse diseases from Alzheimer's to type II diabetes. Preamyloid states of these peptides can act as toxins by binding to and permeabilizing cellular membranes. Cell‐penetrating peptides are natural or engineered short sequences that can spontaneously translocate across a membrane. Despite these differences in classification, many similarities in sequence, structure, and activity suggest that peptides from all three classes act through a small, common set of physical principles. Namely, these peptides alter the Brownian properties of phospholipid bilayers, enhancing the sampling of intrinsic fluctuations that include membrane defects. A complete energy landscape for such systems can be described by the innate membrane properties, differential partition, and the associated kinetics of peptides dividing between surface and defect regions of the bilayer. The goal of this review is to argue that the activities of these membrane‐active families of peptides simply represent different facets of what is a shared energy landscape.     

Formation of a copper specific binding site in non-native states of beta-2-microglobulin

A debilitating complication of long-term hemodialysis is the deposition of beta-2-microglobulin (beta2m) as amyloid plaques in the joint space. We have recently shown that Cu(2+) can be a contributing, if not causal, factor at concentrations encountered during dialysis therapy. The basis for this effect is destabilization and incorporation of beta2m into amyloid fibers upon binding of Cu(2+). In this work, we demonstrate that while beta2m binds Cu(2+) specifically in the native state, it is binding of Cu(2+) by non-native states of beta2m which is responsible for destabilization. Mutagenesis of potential coordinating groups for Cu(2+) shows that native state binding of Cu(2+) is mediated by residues and structures that are different than those which bind in non-native states. An increased affinity for copper by non-native states compared to that of the native state gives rise to overall destabilization. Using mass spectrometry, NMR, and fluorescence techniques, we show that native state binding is localized to H31 and W60 and is highly specific for Cu(2+) over Zn(2+) and Ni(2+). Binding of Cu(2+) in non-native states of beta2m is mediated by residues H13, H51, and H84, but not H31. Although denatured beta2m has characteristics of a globally unfolded state, it nevertheless demonstrates the following strong specificity of binding: Cu(2+) > Zn(2+) > Ni(2+). This requires the existence of a well-defined structure in the unfolded state of this protein. As Cu(2+) effects are reported in many other amyloidoses, e.g., PrP, alpha-synuclein, and Abeta, our results may be extended to the emerging field of divalent ion-associated amyloidosis.     

Islet amyloid: phase partitioning and secondary nucleation are central to the mechanism of fibrillogenesis

Islet amyloid polypeptide (IAPP) contributes to the pathogenesis of type II diabetes by depositing as cytotoxic amyloid fibers in the endocrine pancreas. Fiber formation occurs with a marked conformational change from an unstructured precursor. Using real-time quantitative kinetic methods, fibrillogenesis was characterized as a function of protein, denaturant, and seed concentration. Several observations are in sharp contrast to the expectations for nucleation-dependent polymerization. First, the half-time of conversion for both de novo and seeded kinetics were found to be independent of protein concentration. Second, while elongation kinetics scale linearly with protein concentration, they are relatively insensitive to changes in the total seed concentration. Third, seeded bypass of de novo fiber formation kinetics shows a lag phase. The seeded lag phase is eliminated by a time delay before the introduction of seed to a de novo reaction. Last, conversion is highly cooperative, with the time required for 10-90% conversion occurring much faster than the lag time. At a minimum, four kinetic steps are required to describe these observations: activation, fiber independent nucleation, fiber-dependent nucleation, and elongation. Furthermore, we invoke a phase transition in which protein initially forms an off-pathway dispersion. This single construct allows us to model both the concentration independence of the de novo reaction time and the first-order concentration dependence of the elongation kinetics. Marked acceleration of this reaction by hexafluoro-2-propanol reinforces this view by altering the relative solubility of the two phases and/or by stabilizing hydrogen-bonded structures in the transition states of the reaction pathway.     

Direct measurement of islet amyloid polypeptide fibrillogenesis by mass spectrometry

A novel method for monitoring fibrillogenesis is developed and applied to the amyloidogenic peptide, islet amyloid polypeptide (IAPP). The approach, based on electrospray ionization mass spectrometry, is complementary to existing assays of fibril formation as it monitors directly the population of precursor rather than product molecules. We are able to monitor fiber formation in two modes: a quenched mode in which fibril formation is halted by dilution into denaturant and a real time mode in which fibril formation is conducted within the capillary of the electrospray source. Central to the method is the observation that fibrillar IAPP does not compromise the ionization of monomeric IAPP. Furthermore, under mild ionization conditions, fibrillar IAPP does not dissociate and contribute to the monomeric signal. Critically, we introduce an internal standard, rat IAPP, for analysis on the mass spectrometer. This standard is sufficiently similar in sequence in that it ionizes identically to human IAPP. Furthermore, the sequence is sufficiently different in that it does not form fibrils and is distinguishable on the basis of mass. Applied to IAPP fibrillogenesis, our technique reveals that precursor consumption in seeded reactions obeys first-order kinetics. Furthermore, a consistent level of monomer persists in both seeded and unseeded experiments after the fibril formation is complete. Given the inherent stability of fibrils, we expect this approach to be applicable to other amyloid systems.     

Modeling the clonal heterogeneity of stem cells

Recent experimental studies suggest that tissue stem cell pools are composed of functionally diverse clones. Metapopulation models in ecology concentrate on collections of populations and their role in stabilizing coexistence and maintaining selected genetic or epigenetic variation. Such models are characterized by expansion and extinction of spatially distributed populations. We develop a mathematical framework derived from the multispecies metapopulation model of Tilman et al (1994) to study the dynamics of heterogeneous stem cell metapopulations. In addition to normal stem cells, the model can be applied to cancer cell populations and their response to treatment. In our model disturbances may lead to expansion or contraction of cells with distinct properties, reflecting proliferation, apoptosis, and clonal competition. We first present closed-form expressions for the basic model which defines clonal dynamics in the presence of exogenous global disturbances. We then extend the model to include disturbances which are periodic and which may affect clones differently. Within the model framework, we propose a method to devise an optimal strategy of treatments to regulate expansion, contraction, or mutual maintenance of cells with specific properties.     

Biclustering as a method for RNA local multiple sequence alignment

Motivations: Biclustering is a clustering method that simultaneously clusters both the domain and range of a relation. A challenge in multiple sequence alignment (MSA) is that the alignment of sequences is often intended to reveal groups of conserved functional subsequences. Simultaneously, the grouping of the sequences can impact the alignment; precisely the kind of dual situation biclustering is intended to address. RESULTS: We define a representation of the MSA problem enabling the application of biclustering algorithms. We develop a computer program for local MSA, BlockMSA, that combines biclustering with divide-and-conquer. BlockMSA simultaneously finds groups of similar sequences and locally aligns subsequences within them. Further alignment is accomplished by dividing both the set of sequences and their contents. The net result is both a multiple sequence alignment and a hierarchical clustering of the sequences. BlockMSA was tested on the subsets of the BRAliBase 2.1 benchmark suite that display high variability and on an extension to that suite to larger problem sizes. Also, alignments were evaluated of two large datasets of current biological interest, T box sequences and Group IC1 Introns. The results were compared with alignments computed by ClustalW, MAFFT, MUCLE and PROBCONS alignment programs using Sum of Pairs (SPS) and Consensus Count. Results for the benchmark suite are sensitive to problem size. On problems of 15 or greater sequences, BlockMSA is consistently the best. On none of the problems in the test suite are there appreciable differences in scores among BlockMSA, MAFFT and PROBCONS. On the T box sequences, BlockMSA does the most faithful job of reproducing known annotations. MAFFT and PROBCONS do not. On the Intron sequences, BlockMSA, MAFFT and MUSCLE are comparable at identifying conserved regions. AVAILABILITY: BlockMSA is implemented in Java. Source code and supplementary datasets are available at http://aug.csres.utexas.edu/msa/     

Intrinsic Protein Fluorescence Interferes with Detection of Tear Glycoproteins in SDS-Polyacrylamide Gels Using Extrinsic Fluorescent Dyes

Intrinsic protein fluorescence may interfere with the visualization of proteins after SDS-polyacrylamide electrophoresis. In an attempt to analyze tear glycoproteins in gels, we ran tear samples and stained the proteins with a glycoprotein-specific fluorescent dye. The fluorescence detected was not limited to glycoproteins. There was strong intrinsic fluorescence of proteins normally found in tears after soaking the gels in 40% methanol plus 1-10% acetic acid and, to a lesser extent, in methanol or acetic acid alone. Nanograms of proteins gave visible native fluorescence and interfere with extrinsic fluorescent dye detection. Poly-L-lysine, which does not contain intrinsically fluorescent amino acids, did not fluoresce.