FluShuffle and FluResort: new algorithms to identify reassorted strains of the influenza virus by mass spectrometry

Background: Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths. We have developed and tested new computer algorithms, FluShuffle and FluResort, which enable reassorted viruses to be identified by the most rapid and direct means possible. These algorithms enable reassorted influenza, and other, viruses to be rapidly identified to allow prevention strategies and treatments to be more efficiently implemented.Results: The FluShuffle and FluResort algorithms were tested with both experimental and simulated mass spectra of whole virus digests. FluShuffle considers different combinations of viral protein identities that match the mass spectral data using a Gibbs sampling algorithm employing a mixed protein Markov chain Monte Carlo (MCMC) method. FluResort utilizes those identities to calculate the weighted distance of each across two or more different phylogenetic trees constructed through viral protein sequence alignments. Each weighted mean distance value is normalized by conversion to a Z-score to establish a reassorted strain.Conclusions: The new FluShuffle and FluResort algorithms can correctly identify the origins of influenza viral proteins and the number of reassortment events required to produce the strains from the high resolution mass spectral data of whole virus proteolytic digestions. This has been demonstrated in the case of constructed vaccine strains as well as common human seasonal strains of the virus. The algorithms significantly improve the capability of the proteotyping approach to identify reassorted viruses that pose the greatest pandemic risk. © 2012 Lun et al.; licensee BioMed Central Ltd.Link_to_subscribed_fulltex

GiRaF: robust, computational identification of influenza reassortments via graph mining

Reassortments in the influenza virus—a process where strains exchange genetic segments—have been implicated in two out of three pandemics of the 20th century as well as the 2009 H1N1 outbreak. While advances in sequencing have led to an explosion in the number of whole-genome sequences that are available, an understanding of the rate and distribution of reassortments and their role in viral evolution is still lacking. An important factor in this is the paucity of automated tools for confident identification of reassortments from sequence data due to the challenges of analyzing large, uncertain viral phylogenies. We describe here a novel computational method, called GiRaF (Graph-incompatibility-based Reassortment Finder), that robustly identifies reassortments in a fully automated fashion while accounting for uncertainties in the inferred phylogenies. The algorithms behind GiRaF search large collections of Markov chain Monte Carlo (MCMC)-sampled trees for groups of incompatible splits using a fast biclique enumeration algorithm coupled with several statistical tests to identify sets of taxa with differential phylogenetic placement. GiRaF correctly finds known reassortments in human, avian, and swine influenza populations, including the evolutionary events that led to the recent ‘swine flu’ outbreak. GiRaF also identifies several previously unreported reassortments via whole-genome studies to catalog events in H5N1 and swine influenza isolates

Exploring the phylodynamics, genetic reassortment and RNA secondary structure formation patterns of orthomyxoviruses by comparative sequence analysis

RNA viruses are among the most virulent microorganisms that threaten the health of humans and livestock. Among the most socio-economically important of the known RNA viruses are those found in the family Orthomyxovirus. In this era of rapid low-cost genome sequencing and advancements in computational biology techniques, many previously difficult research questions relating to the molecular epidemiology and evolutionary dynamics of these viruses can now be answered with ease. Using sequence data together with associated meta-data, in chapter two of this dissertation I tested the hypothesis that the Influenza A/H1N1 2009 pandemic virus was introduced multiple times into Africa, and subsequently dispersed heterogeneously across the continent. I further tested to what degree factors such as road distances and air travel distances impacted the observed pattern of spread of this virus in Africa using a generalised linear modelbased approach. The results suggested that their were multiple simultaneous introductions of 2009 pandemic A/H1N1 into Africa, and geographical distance and human mobility through air travel played an important role towards dissemination. In chapter three, I set out to test two hypotheses: (1) that there is no difference in the frequency of reassortments among the segments that constitute influenza virus genomes; and (2) that there is epochal temporal reassortment among influenza viruses and that all geographical regions are equally likely sources of epidemiologically important influenza virus reassortant lineages. The findings suggested that surface segments are more frequently exchanges than internal genes and that North America/Asia, Oceania, and Asia could be the most likely source locations for reassortant Influenza A, B and C virus lineages respectively. In chapter four of this thesis, I explored the formation of RNA secondary structures within the genomes of orthomyxoviruses belonging to five genera: Influenza A, B and C, Infectious Salmon Anaemia Virus and Thogotovirus using in silico RNA folding predictions and additional molecular evolution and phylogenetic tests to show that structured regions may be biologically functional. The presence of some conserved structures across the five genera is likely a reflection of the biological importance of these structures, warranting further investigation regarding their role in the evolution and possible development of antiviral resistance. The studies herein demonstrate that pathogen genomics-based analytical approaches are useful both for understanding the mechanisms that drive the evolution and spread of rapidly evolving viral pathogens such as orthomyxoviruses, and for illuminating how these approaches could be leveraged to improve the management of these pathogens

A Survey of Combinatorial Methods for Phylogenetic Networks

The evolutionary history of a set of species is usually described by a rooted phylogenetic tree. Although it is generally undisputed that bifurcating speciation events and descent with modifications are major forces of evolution, there is a growing belief that reticulate events also have a role to play. Phylogenetic networks provide an alternative to phylogenetic trees and may be more suitable for data sets where evolution involves significant amounts of reticulate events, such as hybridization, horizontal gene transfer, or recombination. In this article, we give an introduction to the topic of phylogenetic networks, very briefly describing the fundamental concepts and summarizing some of the most important combinatorial methods that are available for their computation

Network and Algebraic Topology of Influenza Evolution

Evolution is a force that has molded human existence since its divergence from chimpanzees about 5.4 million years ago. In that same amount of time, an influenza virus, which replicates every six hours, would have undergone an equivalent number of generations over only a hundred years. The fast replication times of influenza, coupled with its high mutation rate, make the virus a perfect model to study real-time evolution at a mega-Darwin scale, more than a million times faster than human evolution. While recent developments in high-throughput sequencing provide an optimal opportunity to dissect their genetic evolution, a concurrent growth in computational tools is necessary to analyze the large influx of complex genomic data. In my thesis, I present novel computational methods to examine different aspects of influenza evolution. I first focus on seasonal influenza, particularly the problems that hamper public health initiatives to combat the virus. I introduce two new approaches: 1. The q2-coefficient, a method of quantifying pathogen surveillance, and 2. FluGraph, a technique that employs network topology to track the spread of seasonal influenza around the world. The second chapter of my thesis examines how mutations and reassortment combine to alter the course of influenza evolution towards pandemic formation. I highlight inherent deficiencies in the current phylogenetic paradigm for analyzing evolution and offer a novel methodology based on algebraic topology that comprehensively reconstructs both vertical and horizontal evolutionary events. I apply this method to viruses, with emphasis on influenza, but foresee broader application to cancer cells, bacteria, eukaryotes, and other taxa

Inference of evolutionary and ecological processes from reticulate evolution in RNA viruses

RNA viruses have the fastest evolutionary rates amongst protein-coding organisms on the planet. Ease of sequencing, advanced techniques of analysis and global health and economic concerns have all contributed to the recognition of RNA viruses as a robust research platform. Phylogenetic methods have been at the forefront of analytical techniques used to understand the dynamics of RNA viruses - during natural circulation in populations and in individual hosts, within epidemics, across species barriers and over billions of years that viruses have been around. Most of the work presented in this thesis employs phylogenetic incongruity arising from reassortment and recombination to gain insights into the genomes and populations of RNA viruses. Chapter 2 explores the selection regimes Ebola virus has experienced following a year of circulation in humans inWest Africa, as well as its recent history. Chapter 3 investigates the extent of recombination in MERS-CoV, a novel human pathogen with an obscure epidemiology, which is suggestive of frequent co-infection of some hosts. Chapter 4, on the other hand, documents a pattern of non-intuitive linkage between some segments of the human-endemic influenza B virus genome and explores its potential to speciate. Chapter 5 builds upon chapter 4 and attempts to describe small-scale reassortment between two segments of influenza B virus and the overall migration patterns of influenza B virus in Scotland. Chapter 6 exploits the independence of segments of influenza D virus, a recently described cattle pathogen, and coalescent theory to disentangle the origins of this virus. This thesis exemplifies the success of modern sequencing methods, which, together with the use of sophisticated analytical techniques, have uncovered a wealth of information hidden away in molecular sequences of RNA viruses. The work presented herein demonstrates how reticulate evolution can be exploited as a reliable, and sometimes indispensable, marker to improve inference of evolutionary forces in RNA viruses

Phylogenetic characterisation of the Palyam serogroup orbiviruses and development of a real-time RT-PCR

The Palyam serogroup of the genus Orbivirus and family Reoviridae are arthropodborne viruses that have been isolated in Africa, Australia and Asia. They are associated with abortion and teratogenesis in cattle and other ruminants. There are currently 13 serotypes recognized by the International Committee on Taxonomy of Viruses (ICTV) including Palyam, Kasba, Vellore, Abadina, D’Aguilar, Nyabira, CSIRO Village, Marrakai, Gweru, Bunyip Creek, Petevo, Marondera and Kindia. Although Palyam viruses had been isolated previously, it was only after an outbreak of congenital abnormalities in cattle in Japan from November 1985 to April 1986 that their pathogenic importance began to be investigated. Of the 13 different serotypes that have been identified, the full genome sequence of only one, Kasba, has been published. Sequences for certain genome segments of the serotypes from Japan, Australia and Zimbabwe are available but not the complete genome data. The few molecular studies that have been done on the Palyam serogroup viruses, focused mainly on Kasba virus and little is known about the other serotypes. In general, not much is published on Palyam viruses, their occurrence or prevalence, and the impact of their epidemiology in South Africa or elsewhere is unknown. The objective of this project was to perform phylogenetic analysis of the different serotypes of the Palyam viruses to enable a better understanding of the genomic features of the Palyam serogroup of orbiviruses, their relation to each other as well as to other orbiviruses. The study is presented in two parts. The aim of the first part was to obtain the full genome sequences of the different Palyam serotypes and Apies River virus, as well as selected field isolates from Africa in order to perform phylogenetic analysis. The aim of the second part was to develop a rapid diagnostic test to detect the Palyam viruses. In the first part, the viruses were propagated and after full-length amplification of cDNA (FLAC) the amplicons were sequenced on an Illumina® Mi-Seq sequencer, using the Nextera XT DNA sample preparation kit and 300-bp paired-end V3 Illumina chemistry. Sequence data generated by Illumina sequencing were analyzed using the CLC Genomics Main workbench, version, 8.0.1. De novo assembly of sequence reads was performed and contig sequences prepared. Sequences were aligned and converted into nexus and phylips files. Data-display networks (neighbour-networks) were constructed with SplitsTree 4 and the phylips files were used to initiate model estimation via jModel test2, by using the online portal Cipres Science gateway. Bayesian analyses was performed in MrBayes version 3. During analysis of the amino acid sequences of the separate genes of the Palyam serogroup serotypes, the gene encoding Viral Protein (VP) 7 (Segment 7) was found to be the most conserved. The amino acid sequences for VP2 and VP5 showed the highest degree of variation, with VP2 being the most variable of the two. Phylogenetic analysis indicated that the Palyam virus group was most closely related to AHSV, and EEV showed the most distant evolutionary relationship to the Palyam viruses. When comparing the different serotypes within the Palyam serogroup viruses, a high degree of sequence identity was found for isolates from the same geographical region. The phylogenetic analysis revealed two clades, which were supported by strong bootstrap values of 100 and a posterior probability value of 1. The African serotypes were all very closely related in one clade, with identical sequences for several gene segments. The second clade contained the Australian and Asian serotypes and one African serotype, Petevo. The high percentage sequence identity (85.6% - 77,5%) that exists between the viruses from Australia and Asia may suggest that there has been some gene flow between the serotypes. It was clear from the sequence data that the geographical origin of Palyam serogroup viruses played an important role in the development of the different serotypes. In the second part of the study, the sequence data obtained in the phylogenetic analysis was used to develop primers and a probe to detect all the Palyam serogroup serotypes in a real-time RT-PCR. The same viruses used in the first part of the study as well as other orbiviruses were propagated and RNA was extracted and tested in a real-time RT-PCR. The real-time RT-PCR was able to detect all the Palyam serogroup serotypes, but further validation is necessary for it to be used as a diagnostic test. The sequence data generated during this study could enable further investigation into molecular evolution of the Palyam serogroup viruses such as reassortment, genetic drift and intragenic recombination. The developed real-time RT-PCR could be a valuable diagnostic tool for both the detection and exclusion of Palyam serogroup viruses during outbreaks involving relevant symptoms.Dissertation (MSc)--University of Pretoria, 2018.Veterinary Tropical DiseasesMScUnrestricte

Marine oomycetes of the genus halophytophthora harbor viruses related to bunyaviruses

We investigated the incidence of RNA viruses in a collection of Halophytophthora spp. from estuarine ecosystems in southern Portugal. The first approach to detect the presence of viruses was based on the occurrence of dsRNA, typically considered as a viral molecule in plants and fungi. Two dsRNA-banding patterns (∼7 and 9 kb) were observed in seven of 73 Halophytophthora isolates tested (9.6%). Consequently, two dsRNA-hosting isolates were chosen to perform stranded RNA sequencing for de novo virus sequence assembly. A total of eight putative novel virus species with genomic affinities to members of the order Bunyavirales were detected and their full-length RdRp gene characterized by RACE. Based on the direct partial amplification of their RdRp gene by RT-PCR multiple viral infections occur in both isolates selected. Likewise, the screening of those viruses in the whole collection of Halophytophthora isolates showed that their occurrence is limited to one single Halophytophthora species. To our knowledge, this is the first report demonstrating the presence of negative (-) ssRNA viruses in marine oomycetes.Project Phytophthora Research Centre CZ.02.1.01/0.0/0.0/15_003/0000453info:eu-repo/semantics/publishedVersio

Transmission dynamics of Avian Influenza A virus

Influenza A virus (AIV) has an extremely high rate of mutation. Frequent exchanges of gene segments between different AIV (reassortment) have been responsible for major pandemics in recent human history. The presence of a wild bird reservoir maintains the threat of incursion of AIV into domestic birds, humans and other animals. In this thesis, I addressed unanswered questions of how diverse AIV subtypes (classified according to antigenicity of the two surface proteins, haemagglutinin and neuraminidase) evolve and interact among different bird populations in different parts of the world, using Bayesian phylogenetic methods with large datasets of full genome sequences. Firstly, I explored the reassortment patterns of AIV internal segments among different subtypes by quantifying evolutionary parameters including reassortment rate, evolutionary rate and selective constraint in time-resolved Bayesian tree phylogenies. A major conclusion was that reassortment rate is negatively associated with selective constraint and that infection of wild rather than domestic birds was associated with a higher reassortment rate. Secondly, I described the spatial transmission pattern of AIV in China. Clustering of related viruses in particular geographic areas and economic zones was identified from the viral phylogeographic diffusion networks. The results indicated that Central China and the Pearl River Delta are two main sources of viral out flow; while the East Coast, especially the Yangtze River delta, is the major recipient area. Simultaneously, by applying a general linear model, the predictors that have the strongest impact on viral spatial diffusion were identified, including economic (agricultural) activity, climate, and ecology. Thirdly, I determined the genetic and phylogeographic origin of a recent H7N3 highly pathogenic avian influenza outbreak in Mexico. Location, subtype, avian host species and pathogenicity were modelled as discrete traits and jointly analysed using all eight viral gene segments. The results indicated that the outbreak AIV is a novel reassortant carried by wild waterfowl from different migration flyways in North America during the time period studied. Importantly, I concluded that Mexico, and Central America in general, might be a potential hotspot for AIV reassortment events, a possibility which to date has not attracted widespread attention. Overall, the work carried out in this thesis described the evolutionary dynamics of AIV from which important conclusions regarding its epidemiological impact in both Eurasia and North America can be drawn