Hypergraph models of metabolism

In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterise a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks

Network motif frequency vectors reveal evolving metabolic network organisation

At the systems level many organisms of interest may be described by their patterns of interaction, and as such, are perhaps best characterised via network or graph models. Metabolic networks, in particular, are fundamental to the proper functioning of many important biological processes, and thus, have been widely studied over the past decade or so. Such investigations have revealed a number of shared topological features, such as a short characteristic path-length, large clustering coefficient and hierarchical modular structure. However, the extent to which evolutionary and functional properties of metabolism manifest via this under- lying network architecture remains unclear. In this paper, we employ a novel graph embedding technique, based upon low-order network motifs, to compare metabolic network structure for 383 bacterial species categorised according to a number of biological features. In particular, we introduce a new global significance score which enables us to quantify important evolutionary relationships that exist between organisms and their physical environments. Using this new approach, we demonstrate a number of significant correlations between environmental factors, such as growth conditions and habitat variability, and network motif structure, providing evidence that organism adaptability leads to increased complexities in the resultant metabolic network

Can linear collocation ever beat quadratic?

Computational approaches are becoming increasingly important in neuroscience, where complex, nonlinear systems modelling neural activity across multiple spatial and temporal scales are the norm. This paper considers collocation techniques for solving neural field models, which typically take the form of a partial integro-dfferential equation. In particular, we investigate and compare the convergence properties of linear and quadratic collocation on both regular grids and more general meshes not fixed to the regular Cartesian grid points. For regular grids we perform a comparative analysis against more standard techniques, in which the convolution integral is computed either by using Fourier based methods or via the trapezoidal rule. Perhaps surprisingly, we find that on regular, periodic meshes, linear collocation displays better convergence properties than quadratic collocation, and is in fact comparable with the spectral convergence displayed by both the Fourier based and trapezoidal techniques. However, for more general meshes we obtain superior convergence of the convolution integral using higher order methods, as expected

A numerical simulation of neural fields on curved geometries

Despite the highly convoluted nature of the human brain, neural field models typically treat the cortex as a planar two-dimensional sheet of neurons. Here, we present an approach for solving neural field equations on surfaces more akin to the cortical geometries typically obtained from neuroimaging data. Our approach involves solving the integral form of the partial integro-differential equation directly using collocation techniques alongside efficient numerical procedures for determining geodesic distances between neural units. To illustrate our methods, we study localised activity patterns in a two-dimensional neural field equation posed on a periodic square domain, the curved surface of a torus, and the cortical surface of a rat brain, the latter of which is constructed using neuroimaging data. Our results are twofold: Firstly, we find that collocation techniques are able to replicate solutions obtained using more standard Fourier based methods on a flat, periodic domain, independent of the underlying mesh. This result is particularly significant given the highly irregular nature of the type of meshes derived from modern neuroimaging data. And secondly, by deploying efficient numerical schemes to compute geodesics, our approach is not only capable of modelling macroscopic pattern formation on realistic cortical geometries, but can also be extended to include cortical architectures of more physiological relevance. Importantly, such an approach provides a means by which to investigate the influence of cortical geometry upon the nucleation and propagation of spatially localised neural activity and beyond. It thus promises to provide model-based insights into disorders like epilepsy, or spreading depression, as well as healthy cognitive processes like working memory or attention

Accelerated Evolution of the ASPM Gene Controlling Brain Size Begins Prior to Human Brain Expansion

Primary microcephaly (MCPH) is a neurodevelopmental disorder characterized by global reduction in cerebral cortical volume. The microcephalic brain has a volume comparable to that of early hominids, raising the possibility that some MCPH genes may have been evolutionary targets in the expansion of the cerebral cortex in mammals and especially primates. Mutations in ASPM, which encodes the human homologue of a fly protein essential for spindle function, are the most common known cause of MCPH. Here we have isolated large genomic clones containing the complete ASPM gene, including promoter regions and introns, from chimpanzee, gorilla, orangutan, and rhesus macaque by transformation-associated recombination cloning in yeast. We have sequenced these clones and show that whereas much of the sequence of ASPM is substantially conserved among primates, specific segments are subject to high Ka/Ks ratios (nonsynonymous/synonymous DNA changes) consistent with strong positive selection for evolutionary change. The ASPM gene sequence shows accelerated evolution in the African hominoid clade, and this precedes hominid brain expansion by several million years. Gorilla and human lineages show particularly accelerated evolution in the IQ domain of ASPM. Moreover, ASPM regions under positive selection in primates are also the most highly diverged regions between primates and nonprimate mammals. We report the first direct application of TAR cloning technology to the study of human evolution. Our data suggest that evolutionary selection of specific segments of the ASPM sequence strongly relates to differences in cerebral cortical size

A role for non-B DNA forming sequences in mediating microlesions causing human inherited disease

Missense/nonsense mutations and micro-deletions/micro-insertions of <21bp together represent ~76% of all mutations causing human inherited disease. Previous studies have shown that their occurrence is influenced by sequences capable of non-B DNA formation (direct, inverted and mirror repeats; G-quartets). We found that a greater than expected proportion (~21%) of both micro-deletions and micro-insertions occur within direct repeats and are explicable by slipped misalignment. A novel mutational mechanism, non-B DNA triplex formation followed by DNA repair, is proposed to explain ~5 % of micro-deletions and micro-insertions at mirror repeats. Further, G-quadruplex-forming sequences, direct and inverted repeats appear to play a prominent role in mediating missense mutations, whereas only direct and inverted repeats mediate nonsense mutations. We suggest a mutational mechanism involving slipped strand mispairing, slipped structure formation and DNA repair, to explain ~15% of missense and ~12% of nonsense mutations leading to the formation of perfect direct repeat s from imperfect repeats, or to the extension of existing direct repeats. Similar proportions of missense and nonsense mutations were explicable by the mechanism of hairpin loop formation and DNA repair leading to the formation of perfect inverted repeats from imperfect repeats. The proposed mechanisms provide new insights into mutagenesis underlying pathogenic micro-lesions

Behavior Change through Innovation Adoption: A Case Study of Alternative Mobility Solutions

The sustainability of urban transportation is becoming one of the biggest concerns in the field of mobility. Transportation behavior of urban citizens is highly car dependent. Alternative mobility solutions (AMS) like car-sharing services are seen as a potential innovative way to improve the environmental situation in cities. Despite AMS are present in the market, there are challenges for people to adopt this type of services and change their behavior towards more sustainable urban living. To address this challenge, it is important to identify What are the factors influencing an individual decision to adopt AMS innovation and change user behavior. There is no coherent framework to study innovation adoption in transportation related to AMS. This study aims at providing a fresh perspective on innovation adoption and behavior change in modern urban transportation with the focus on AMS. This includes synthesis of three theories to introduce a framework that presents factors which can be taken into account when developing an intervention in the transportation sector. The factors of the proposed framework are tested and validated in this research through multiple case studies in the form of interviews with transportation experts (N=8) in Finland. Findings demonstrate an importance of understanding influential elements in an ecosystem that affect innovation adoption. These elements include involvement of every stakeholder in addressing individual behavior change, particularly, peers that individuals trust, and government representation. As a part of this study, the innovation characteristics are specifically emphasized as factors with an important role in AMS innovation adoption decision. For instance, minimum complexity, opportunity to try an innovation before making the adoption decision, competitive pricing, and compatibility to prior experiences were listed as the most influential characteristics. The results of the study serve as a basis for the research on the development of interventions in the transportation sector with a particular focus on alternative mobility solutions (AMS)