Role of mobile genetic elements in the global network of bacterial horizontal gene transfer

Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. One grave consequence of this exchange is the rapid spread of antibiotic resistance determinants among bacterial communities across the world. In this thesis, I make use of large datasets of publicly available bacterial genomes and various analytical approaches to improve our understanding of the nature and the impact of HGT at a global scale. In the first part, I study the population structure and dynamics of over 10,000 bacterial plasmids. By reconstructing and analysing a network of plasmids based on their shared k-mer content, I was able to sort them into biologically meaningful clusters. This network-based analysis allowed me to make further inferences into global network of HGT and opened up prospect for a natural and exhaustive classification framework of bacterial plasmids. The second part focuses on global spreading of blaNDM – an important antibiotic resistance gene. To this end, I compiled a dataset of over 6000 bacterial genomes harbouring this element and developed a novel computational approach to track structural variants surrounding blaNDM across bacterial genomes. This facilitated identification of prevalent genomic contexts of blaNDM and reconstruction of key mobile genetic elements and events which led to its global dissemination. Taken together, my results highlight transposable elements as the main drivers of HGT at broad phylogenetic and geographical scales with plasmid exchange being much more spatially restricted due to the adaptation to specific bacterial hosts and evolutionary pressures

Large-scale network analysis captures biological features of bacterial plasmids

Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a network based on their shared k-mer content. We use a community detection algorithm to assign plasmids into cliques, which correlate with plasmid gene content, bacterial host range, GC content, and existing classifications based on replicon and mobility (MOB) types. Further analysis of plasmid population structure allows us to uncover candidates for yet undescribed replicon genes, and to identify transposable elements as the main drivers of HGT at broad phylogenetic scales. Our work illustrates the potential of network-based analyses of the bacterial ‘mobilome’ and opens up the prospect of a natural, exhaustive classification framework for bacterial plasmids

Coordinated neuronal ensembles in primary auditory cortical columns.

The synchronous activity of groups of neurons is increasingly thought to be important in cortical information processing and transmission. However, most studies of processing in the primary auditory cortex (AI) have viewed neurons as independent filters; little is known about how coordinated AI neuronal activity is expressed throughout cortical columns and how it might enhance the processing of auditory information. To address this, we recorded from populations of neurons in AI cortical columns of anesthetized rats and, using dimensionality reduction techniques, identified multiple coordinated neuronal ensembles (cNEs), which are groups of neurons with reliable synchronous activity. We show that cNEs reflect local network configurations with enhanced information encoding properties that cannot be accounted for by stimulus-driven synchronization alone. Furthermore, similar cNEs were identified in both spontaneous and evoked activity, indicating that columnar cNEs are stable functional constructs that may represent principal units of information processing in AI

Cognitive Learning and Memory Systems Using Spiking Neural Networks

Ph.DDOCTOR OF PHILOSOPH

Formal aspects of component software

This is the pre-proceedings of 6th International Workshop on Formal Aspects of Component Software (FACS'09)

Structure and dynamics of core-periphery networks

Recent studies uncovered important core/periphery network structures characterizing complex sets of cooperative and competitive interactions between network nodes, be they proteins, cells, species or humans. Better characterization of the structure, dynamics and function of core/periphery networks is a key step of our understanding cellular functions, species adaptation, social and market changes. Here we summarize the current knowledge of the structure and dynamics of "traditional" core/periphery networks, rich-clubs, nested, bow-tie and onion networks. Comparing core/periphery structures with network modules, we discriminate between global and local cores. The core/periphery network organization lies in the middle of several extreme properties, such as random/condensed structures, clique/star configurations, network symmetry/asymmetry, network assortativity/disassortativity, as well as network hierarchy/anti-hierarchy. These properties of high complexity together with the large degeneracy of core pathways ensuring cooperation and providing multiple options of network flow re-channelling greatly contribute to the high robustness of complex systems. Core processes enable a coordinated response to various stimuli, decrease noise, and evolve slowly. The integrative function of network cores is an important step in the development of a large variety of complex organisms and organizations. In addition to these important features and several decades of research interest, studies on core/periphery networks still have a number of unexplored areas.Comment: a comprehensive review of 41 pages, 2 figures, 1 table and 182 reference

On Computable Protein Functions

Proteins are biological machines that perform the majority of functions necessary for life. Nature has evolved many different proteins, each of which perform a subset of an organism’s functional repertoire. One aim of biology is to solve the sparse high dimensional problem of annotating all proteins with their true functions. Experimental characterisation remains the gold standard for assigning function, but is a major bottleneck due to resource scarcity. In this thesis, we develop a variety of computational methods to predict protein function, reduce the functional search space for proteins, and guide the design of experimental studies. Our methods take two distinct approaches: protein-centric methods that predict the functions of a given protein, and function-centric methods that predict which proteins perform a given function. We applied our methods to help solve a number of open problems in biology. First, we identified new proteins involved in the progression of Alzheimer’s disease using proteomics data of brains from a fly model of the disease. Second, we predicted novel plastic hydrolase enzymes in a large data set of 1.1 billion protein sequences from metagenomes. Finally, we optimised a neural network method that extracts a small number of informative features from protein networks, which we used to predict functions of fission yeast proteins

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Genomic analysis of diverse bacterial pathogens

Bacterial pathogens have been a historical scourge for the entirety of human existence but have been significantly thwarted since the 20th century due to the development of antibiotics. However, owing to the large selection pressure of antibiotics on bacterial populations, phenotypic antibiotic resistance from the development of vertically transmitted mutations and horizontally acquired antibiotic resistance genes (ARGs) is increasing. The sum has produced multidrug resistant organisms (MDROs) which have extremely limited treatment options. Epidemiological studies have determined that carbapenem resistant Enterobacteriaceae (CRE), Acinetobacter baumannii, and vancomycin resistant Enterococcus (VRE) are some of the most problematic MDRO infections. The advent of cost-effective and accurate next-generation sequencing has resulted in a proliferation of bacterial genomes available. ARGs, antibiotic resistance conferring single nucleotide polymorphism (SNPs), and virulence genes can be identified within an assembled genome by comparison to known databases. The combination of the genetic information encoded within the genome of an isolate along with metadata related to important phenotypes or clinical context can be used to identify trends in ARG carriage, evolution over time, and viii differences in gene burden. This information can also be used in understanding the effects of antibiotic treatment on multi organism infections such as bacterial vaginosis. My thesis intends to investigate features related to natural populations of bacterial isolates in the Enterobacteriaceae family and Acinetobacter baumannii in Chapters 2, 3, 4 and the Gram-positive organisms Enterococcus faecium, Gardnerella, and Corynebacterium in Chapters 5, 6, and 7. In Chapter 2 we identify the carbapenem resistance gene blaIMP-27 in a clinical isolate of carbapenem resistance Providencia rettgeri. We then acquired two blaIMP-27 bearing Proteus mirabilis and determine that one isolate (PM187) also has it on a plasmid. We were able to completely close the blaIMP-27 bearing plasmids pPR1 and pPM187 and determine that the local genetic context was similar but the background of the plasmids were different. In Chapter 3 we collect a cohort of longitudinally antibiotic resistant organisms recovered from hospital surfaces in the United States and Pakistan. We compare the phenotypic identification with the genomic identification to determine that several isolates represent novel taxonomic groups, we identify a severe degree of phenotypic antibiotic resistance in the collected important human pathogens and elucidate a network of ARGs common amongst the bacteria. Importantly, we demonstrate that E. faecium and A. baumannii co-occur greater than predicted by chance a lone and that laboratory strains of these organisms are capable of forming synergistic growth in biofilms. In Chapter 4 we collect a cohort of Klebsiella variicola from Washington University and use whole genome sequencing to determine the population structure of all publicly available K. variicola genomes and identify genes relevant for infection related phenotypes. We show that these differences may have a functional consequence as some K. variicola strains can be more competent uropathogens than Klebsiella pneumoniae. In Chapter 5 we compare linezolid resistance mechanisms within a cohort to VRE from the United States and Pakistan to determine that all of the US isolates were resistant due to SNPs in the 23S rRNA sequence, but the Pakistan isolates all had acquired ARGs. Two of six these ARGs were the limited scope efflux pumps optrA and poxtA but the other ARGs are novel variants of the cfr family. In Chapter 6 we analyze a set of publicly available Gardnerella vaginalis genomes and metatranscriptomes of women with bacterial vaginosis to determine that what is commonly considered a single species can be interpreted as 9 different species with differences in accessory genome function and varying presence in bacterial vaginosis cases. Different genomospecies are present at varying abundance and putative virulence genes have high expression values during infection. Finally, in chapter 7 we determine the effects of acquired daptomycin resistance on the biology of Corynebacterium striatum. In summation this work provides novel insights on the relatedness of important human pathogens to one another and the content of their genes relevant toward infection across a wide range of species