Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.A.G.-M. was supported by the SynBio3D project of the UK Engineering and Physical Sciences Research Council (EP/R019002/1) and the European CSA on biological standardization BIOROBOOST (EU grant number 820699). T.E.G. was supported by a Royal Society University Research Fellowship (grant UF160357) and BrisSynBio, a BBSRC/ EPSRC Synthetic Biology Research Centre (grant BB/L01386X/1). P.Z. was supported by the EPSRC Portabolomics project (grant EP/N031962/1). P.C. was supported by SynBioChem, a BBSRC/EPSRC Centre for Synthetic Biology of Fine and Specialty Chemicals (grant BB/M017702/1) and the ShikiFactory100 project of the European Union’s Horizon 2020 research and innovation programme under grant agreement 814408

Radius, girth and minimum degree

Funder: UK Research and Innovation; Id: http://dx.doi.org/10.13039/100014013Funder: Cambridge TrustFunder: University of Cambridge; Id: http://dx.doi.org/10.13039/501100000735Abstract: The objective of the present paper is to study the maximum radius r of a connected graph of order n , minimum degree δ ≥ 2 and girth at least g ≥ 4 . Erdős, Pach, Pollack and Tuza proved that if g = 4 , that is, the graph is triangle‐free, then r ≤ n − 2 δ + 12 , and noted that up to the value of the additive constant, this upper bound is tight. In this paper we shall determine the exact maximum. For larger values of g little is known. We settle the order of the maximum r for g = 6 , 8 and 12, and prove an upper bound for every even g , which we conjecture to be tight up to a constant factor. Finally, we show that our conjecture implies the so‐called Erdős girth conjecture

Raman scattering investigation and symmetry analysis of ferroelectric/ferroelastic Sb5O7I polytype 2MA

The polytype 2MA (beta-Sb5O7I) has the simplest acentric structure of the antimony oxideiodide family. It undergoes an antiferrodistortive phase transition at 438K and is both ferroelectric and ferroelastic below that temperature. The complete polarized Raman spectra in the ferroic phase have been measured and compared with those of the ferroelastic, centric polytype 2MC (agr-Sb5O7I). Several lines could be attributed to Sb—0 and Sb—I vibrations. A factor group analysis has been performed and compatibility relations have been established connecting phonon species in the low and high temperature phase. As a function of temperature the spectra revealed a strongly temperature dependent central line and several phonon lines whose intensities vanish aboveT c . Using these phonon line intensities the temperature variation of the order parameter could be determined. The experimental results indicate that the phase transition is of first order