Agents in Bioinformatics

The scope of the Technical Forum Group (TFG) on Agents in Bioinformatics (BIOAGENTS) was to inspire collaboration between the agent and bioinformatics communities with the aim of creating an opportunity to propose a different (agent-based) approach to the development of computational frameworks both for data analysis in bioinformatics and for system modelling in computational biology. During the day, the participants examined the future of research on agents in bioinformatics primarily through 12 invited talks selected to cover the most relevant topics. From the discussions, it became clear that there are many perspectives to the field, ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages for use by information agents, and to the use of Grid agents, each of which requires further exploration. The interactions between participants encouraged the development of applications that describe a way of creating agent-based simulation models of biological systems, starting from an hypothesis and inferring new knowledge (or relations) by mining and analysing the huge amount of public biological data. In this report we summarise and reflect on the presentations and discussions

PACMAS: A Personalized, Adaptive, and Cooperative MultiAgent System Architecture

In this paper, a generic architecture, designed to support the implementation of applications aimed at managing information among different and heterogeneous sources, is presented. Information is filtered and organized according to personal interests explicitly stated by the user. User pro- files are improved and refined throughout time by suitable adaptation techniques. The overall architecture has been called PACMAS, being a support for implementing Personalized, Adaptive, and Cooperative MultiAgent Systems. PACMAS agents are autonomous and flexible, and can be made personal, adaptive and cooperative, depending on the given application. The peculiarities of the architecture are highlighted by illustrating three relevant case studies focused on giving a support to undergraduate and graduate students, on predicting protein secondary structure, and on classifying newspaper articles, respectively

Structure of a bacterial type IV secretion core complex at subnanometre resolution

Type IV secretion (T4S) systems are able to transport DNAs and/or proteins through the membranes of bacteria. They form large multiprotein complexes consisting of 12 proteins termed VirB1-11 and VirD4. VirB7, 9 and 10 assemble into a 1.07 MegaDalton membrane-spanning core complex (CC), around which all other components assemble. This complex is made of two parts, the O-layer inserted in the outer membrane and the I-layer inserted in the inner membrane. While the structure of the O-layer has been solved by X-ray crystallography, there is no detailed structural information on the I-layer. Using high-resolution cryo-electron microscopy and molecular modelling combined with biochemical approaches, we determined the I-layer structure and located its various components in the electron density. Our results provide new structural insights on the CC, from which the essential features of T4S system mechanisms can be derived

The role of the N-acetylglucosamine phosphoenolpyruvate phosphotransferase system from Lactobacillus plantarum 8014 in the mechanism of action of glycocin F : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Biochemistry at Massey University, Manawatū, New Zealand

The rise in antibiotic-resistant bacteria is becoming a severe public health problem because of the shortage of new antibiotics to combat existing resistant bacterial pathogens. Should this trend of increasing bacterial drug resistance continue, the previously treatable conditions may once again become fatal. Using broad-spectrum antibiotics causes collateral damage to the commensal microbiota of the host leading to complications and a greater susceptibility to opportunistic pathogenic infection. As a result, narrow spectrum antibacterials effective against specific pathogens, are becoming increasingly sought after. Among the many alternative classes of narrow-spectrum antibiotics, is a diverse group of ribosomally-synthesised antimicrobial peptides known as bacteriocins. Glycocin F (GccF), a rare and uniquely diglycosylated bacteriocin produced by Lactobacillus plantarum KW80, appears to target a specific N-acetylglucosamine (GlcNAc) phosphotransferase system (PTS) and causes almost instant bacteriostasis by an as yet unknown mechanism. This thesis demonstrates how the GlcNAc-PTS is involved in the GccF mechanism of action and that the gccH gene provides immunity to GccF. Using transgenic and gene editing techniques, regions of the GlcNAc-PTS were either removed or altered to prevent normal function before being tested in vivo. The results demonstrated that only the EIIC domain of the GlcNAc-PTS is required in the GccF mechanism of action and that it acts like a "lure" that attracts the bacteriocin to the main target that is as yet unknown. Furthermore, the immunity gene was discovered, and using PTS knockout cell lines the immunity mechanism was shown to act independently of the GlcNAc-PTS. This work will form the foundation for the work needed to unravel the bacteriostatic mechanism of action of GccF, which may lead to the development a novel antimicrobial agent

LightDock: a new multi-scale approach to protein–protein docking

Computational prediction of protein–protein complex structure by docking can provide structural and mechanistic insights for protein interactions of biomedical interest. However, current methods struggle with difficult cases, such as those involving flexible proteins, low-affinity complexes or transient interactions. A major challenge is how to efficiently sample the structural and energetic landscape of the association at different resolution levels, given that each scoring function is often highly coupled to a specific type of search method. Thus, new methodologies capable of accommodating multi-scale conformational flexibility and scoring are strongly needed. We describe here a new multi-scale protein–protein docking methodology, LightDock, capable of accommodating conformational flexibility and a variety of scoring functions at different resolution levels. Implicit use of normal modes during the search and atomic/coarse-grained combined scoring functions yielded improved predictive results with respect to state-of-the-art rigid-body docking, especially in flexible cases.B.J-G was supported by a FPI fellowship from the Spanish Ministry of Economy and Competitiveness. This work was supported by I+D+I Research Project grants BIO2013-48213-R and BIO2016-79930-R from the Spanish Ministry of Economy and Competitiveness. This work is partially supported by the European Union H2020 program through HiPEAC (GA 687698), by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology (TIN2015-65316-P) and the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya, under project MPEXPAR: Models de Programaciói Entorns d’Execució Paral·lels (2014-SGR-1051).Peer ReviewedPostprint (author's final draft

Reverse engineering of drug induced DNA damage response signalling pathway reveals dual outcomes of ATM kinase inhibition

The DNA Damage Response (DDR) pathway represents a signalling mechanism that is activated in eukaryotic cells following DNA damage and comprises of proteins involved in DNA damage detection, DNA repair, cell cycle arrest and apoptosis. This pathway consists of an intricate network of signalling interactions driving the cellular ability to recognise DNA damage and recruit specialised proteins to take decisions between DNA repair or apoptosis. ATM and ATR are central components of the DDR pathway. The activities of these kinases are vital in DNA damage induced phosphorylational induction of DDR substrates. Here, firstly we have experimentally determined DDR signalling network surrounding the ATM/ATR pathway induced following double stranded DNA damage by monitoring and quantifying time dependent inductions of their phosphorylated forms and their key substrates. We next involved an automated inference of unsupervised predictive models of time series data to generate in silico (molecular) interaction maps. We characterized the complex signalling network through system analysis and gradual utilisation of small time series measurements of key substrates through a novel network inference algorithm. Furthermore, we demonstrate an application of an assumption-free reverse engineering of the intricate signalling network of the activated ATM/ATR pathway. We next studied the consequences of such drug induced inductions as well as of time dependent ATM kinase inhibition on cell survival through further biological experiments. Intermediate and temporal modelling outcomes revealed the distinct signaling profile associated with ATM kinase activity and inhibition and explained the underlying signalling mechanism for dual ATM functionality in cytotoxic and cytoprotective pathways