The underlying pathway structure of biochemical reaction networks

Bioinformatics is yielding extensive, and in some cases complete, genetic and biochemical information about individual cell types and cellular processes, providing the composition of living cells and the molecular structure of its components. These components together perform integrated cellular functions that now need to be analyzed. In particular, the functional definition of biochemical pathways and their role in the context of the whole cell is lacking. In this study, we show how the mass balance constraints that govern the function of biochemical reaction networks lead to the translation of this problem into the realm of linear algebra. The functional capabilities of biochemical reaction networks, and thus the choices that cells can make, are reflected in the null space of their stoichiometric matrix. The null space is spanned by a finite number of basis vectors. We present an algorithm for the synthesis of a set of basis vectors for spanning the null space of the stoichiometric matrix, in which these basis vectors represent the underlying biochemical pathways that are fundamental to the corresponding biochemical reaction network. In other words, all possible flux distributions achievable by a defined set of biochemical reactions are represented by a linear combination of these basis pathways. These basis pathways thus represent the underlying pathway structure of the defined biochemical reaction network. This development is significant from a fundamental and conceptual standpoint because it yields a holistic definition of biochemical pathways in contrast to definitions that have arisen from the historical development of our knowledge about biochemical processes. Additionally, this new conceptual framework will be important in defining, characterizing, and studying biochemical pathways from the rapidly growing information on cellular function.

Odor space and olfactory processing: Collective algorithms and neural implementation

Several basic olfactory tasks must be solved by highly olfactory animals, including background suppression, multiple object separation, mixture separation, and source identification. The large number N of classes of olfactory receptor cells—hundreds or thousands—permits the use of computational strategies and algorithms that would not be effective in a stimulus space of low dimension. A model of the patterns of olfactory receptor responses, based on the broad distribution of olfactory thresholds, is constructed. Representing one odor from the viewpoint of another then allows a common description of the most important basic problems and shows how to solve them when N is large. One possible biological implementation of these algorithms uses action potential timing and adaptation as the “hardware” features that are responsible for effective neural computation.

Proposed mechanism for stability of proteins to evolutionary mutations

It is shown that the sequence-ordering tendencies induced by design into different fast-folding, thermally stable native structures interfere. This interference results in a type of quasiorthogonality between optimal native structures, which divides sequence space into fast-folding, thermally stable families surrounded by slow-folding, low stability shells. A concrete example of this effect is provided by using a simple α carbon type model in which a complete correspondence is established between sequence and structure. It is speculated that gaps can occur in the space of protein-like sequences separating the sequence families and resulting in a mechanism for stability and diversity of protein sequence information.

Promotion of sleep mediated by the A2a-adenosine receptor and possible involvement of this receptor in the sleep induced by prostaglandin D2 in rats.

A 6-hr continuous infusion of 2-[p-(2-carboxyethyl)phenylethylamino]-5'-N-ethylcarboxamidoadenos ine (CGS21680), a selective A2a-adenosine agonist, into the subarachnoid space underlying the ventral surface region of the rostral basal forebrain, which has been defined as the prostaglandin (PG) D2-sensitive sleep-promoting zone, at rates of 0.02, 0.2, 2.0, and 12 pmol/min increased slow-wave sleep (SWS) and paradoxical sleep (PS) in a dose-dependent manner up to 183% and 202% of their respective baseline levels. The increments produced by the infusion of CGS21680 at 0.2 and 2.0 pmol/min were totally diminished when the rats had been pretreated with an i.p. injection of (E)-1,3-dipropyl-7-methyl-8-(3,4-dimethoxystyryl)xanthine (KF17837; 30 mg/kg of body weight), a selective A2-adenosine antagonist. In contrast, the infusion of N6-cyclohexyladenosine (CHA), a selective A1-adenosine agonist, at 2 pmol/min significantly suppressed SWS before causing an increase in SWS, and a decrease in PS was also markedly visible. Essentially the same effects of CGS21680 and CHA were observed when these compounds were administered to the parenchymal region of the rostral basal forebrain through chronically implanted microdialysis probes. Thus, we clearly showed that stimulation of A2a-adenosine receptors in the rostral basal forebrain promotes SWS and PS. Furthermore, i.p. injections of KF17837 at 30 and 100 mg/kg of body weight dose-dependently attenuated the magnitude of the SWS increase produced by the infusion of PGD2 into the subarachnoid space of the sleep-promoting zone, thus indicating that the A2a-adenosine receptors are crucial in the sleep-promoting process triggered by PGD2.

A sampling problem in molecular dynamics simulations of macromolecules.

Correlations in low-frequency atomic displacements predicted by molecular dynamics simulations on the order of 1 ns are undersampled for the time scales currently accessible by the technique. This is shown with three different representations of the fluctuations in a macromolecule: the reciprocal space of crystallography using diffuse x-ray scattering data, real three-dimensional Cartesian space using covariance matrices of the atomic displacements, and the 3N-dimensional configuration space of the protein using dimensionally reduced projections to visualize the extent to which phase space is sampled.

Hepatic expression of mature transforming growth factor beta 1 in transgenic mice results in multiple tissue lesions.

Aberrant expression of transforming growth factor beta 1 (TGF-beta 1) has been implicated in a number of disease processes, particularly those involving fibrotic and inflammatory lesions. To determine the in vivo effects of overexpression of TGF-beta 1 on the function and structure of hepatic as well as extrahepatic tissues, transgenic mice were generated containing a fusion gene (Alb/TGF-beta 1) consisting of modified porcine TGF-beta 1 cDNA under the control of the regulatory elements of the mouse albumin gene. Five transgenic lines were developed, all of which expressed the Alb/TGF-beta 1 transgene selectively in hepatocytes. The transgenic line 25 expressing the highest level of the transgene in the liver also had high (> 10-fold over control) plasma levels of TGF-beta 1. Hepatic fibrosis and apoptotic death of hepatocytes developed in all the transgenic lines but was more pronounced in line 25. The fibrotic process was characterized by deposition of collagen around individual hepatocytes and within the space of Disse in a radiating linear pattern. Several extrahepatic lesions developed in line 25, including glomerulonephritis and renal failure, arteritis and myocarditis, as well as atrophic changes in pancreas and testis. The results from this transgenic model strongly support the proposed etiological role for TGF-beta 1 in a variety of fibrotic and inflammatory disorders. The transgenic model may also provide an appropriate paradigm for testing therapeutic interventions aimed at neutralizing the detrimental effects of this important cytokine.