Browsing by Author "Martin, Darren Patrick"

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    High Degree of HIV-1 group M Genetic Diversity within Circulating Recombinant Forms: Insight into the Early Events of HIV-1M Evolution
    (American Society of Microbiology, 2016-03-15) Tongo, Marcel; Dorfman, Jeffrey Robert; Martin, Darren Patrick
    The existence of various highly divergent HIV-1 lineages and of recombination-derived sequence tracts of indeterminate origin within established circulating recombinant forms (CRFs) strongly suggests that HIV-1 group M (HIV-1M) diversity is not fully represented under the current classification system. Here we used a fully exploratory screen for recombination on a set of 480 near-full-length genomes representing the full known diversity of HIV-1M. We decomposed recombinant sequences into their constituent parts and then used maximum-likelihood phylogenetic analyses of this mostly recombination-free data set to identify rare divergent sequence lineages that fall outside the major named HIV-1M taxonomic groupings. We found that many of the sequence fragments occurring within CRFs (including CRF04_cpx, CRF06_cpx, CRF11_cpx, CRF18_cpx, CRF25_cpx, CRF27_cpx, and CRF49_cpx) are in fact likely derived from divergent unclassified parental lineages that may predate the current subtypes, even though they are presently identified as derived from currently defined HIV-1M subtypes. Our evidence suggests that some of these CRFs are descended predominantly from what were or are major previously unidentified HIV-1M lineages that were likely epidemiologically relevant during the early stages of the HIV-1M epidemic. The restriction of these divergent lineages to the Congo basin suggests that they were less infectious and/or simply not present at the time and place of the initial migratory wave that triggered the global epidemic. IMPORTANCE HIV-1 group M (HIV-1M) likely spread to the rest of the world from the Congo basin in the mid-1900s (N. R. Faria et al., Science 346:56-61, 2014, http://dx.doi.org/10.1126/science.1256739) and is today the principal cause of the AIDS pandemic. Here, we show that large sequence fragments from several HIV-1M circulating recombinant forms (CRFs) are derived from divergent parental lineages that cannot reasonably be classified within the nine established HIV-1M subtypes. These lineages are likely to have been epidemiologically relevant in the Congo basin at the onset of the epidemic. Nonetheless, they appear not to have undergone the same explosive global spread as other HIV-1M subtypes, perhaps because they were less transmissible. Concerted efforts to characterize more of these divergent lineages could allow the accurate inference and chemical synthesis of epidemiologically key ancestral HIV-1M variants so as to directly test competing hypotheses relating to the viral genetic factors that enabled the present pandemic.
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    Maize Streak Virus: diversity and virulence
    (2000) Martin, Darren Patrick; Rybicki, Ed
    Zea mays was first introduced to Africa in Ghana by Portuguese traders in the 16th century. The steady spread of maize cultivation since then has made it the most important cereal crop in Africa today. Whereas improved maize genotypes and agricultural techniques enable yearly yields above 10 tons hectare-1 in the developed world, yearly yields across Africa have remained low at about 1 ton hectare-1 in most countries. Although outmoded agricultural practices are the main reason for poor yields, maize pathogens inflict substantial additional losses. Of the many pathogens currently confronting maize farmers in Africa, Maize streak virus (MSV) is the most significant.
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    Phylogenetic exploration of nosocomial transmission chains of 2009 influenza A/H1N1 among children admitted at Red Cross War Memorial Children's Hospital, Cape Town, South Africa in 2011
    (Public Library of Science, 2015) Valley-Omar, Ziyaad; Nindo, Fredrick; Mudau, Maanda; Hsiao, Marvin; Martin, Darren Patrick
    Traditional modes of investigating influenza nosocomial transmission have entailed a combination of confirmatory molecular diagnostic testing and epidemiological investigation. Common hospital-acquired infections like influenza require a discerning ability to distinguish between viral isolates to accurately identify patient transmission chains. We assessed whether influenza hemagglutinin sequence phylogenies can be used to enrich epidemiological data when investigating the extent of nosocomial transmission over a four-month period within a paediatric Hospital in Cape Town South Africa. Possible transmission chains/channels were initially determined through basic patient admission data combined with Maximum likelihood and time-scaled Bayesian phylogenetic analyses. These analyses suggested that most instances of potential hospital-acquired infections resulted from multiple introductions of Influenza A into the hospital, which included instances where virus hemagglutinin sequences were identical between different patients. Furthermore, a general inability to establish epidemiological transmission linkage of patients/viral isolates implied that identified isolates could have originated from asymptomatic hospital patients, visitors or hospital staff. In contrast, a traditional epidemiological investigation that used no viral phylogenetic analyses, based on patient co-admission into specific wards during a particular time-frame, suggested that multiple hospital acquired infection instances may have stemmed from a limited number of identifiable index viral isolates/patients. This traditional epidemiological analysis by itself could incorrectly suggest linkage between unrelated cases, underestimate the number of unique infections and may overlook the possible diffuse nature of hospital transmission, which was suggested by sequencing data to be caused by multiple unique introductions of influenza A isolates into individual hospital wards. We have demonstrated a functional role for viral sequence data in nosocomial transmission investigation through its ability to enrich traditional, non-molecular observational epidemiological investigation by teasing out possible transmission pathways and working toward more accurately enumerating the number of possible transmission events.
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    SDT: a virus classification tool based on pairwise sequence alignment and identity calculation
    (Public Library of Science, 2014) Muhire, Brejnev Muhizi; Varsani, Arvind; Martin, Darren Patrick
    The perpetually increasing rate at which viral full-genome sequences are being determined is creating a pressing demand for computational tools that will aid the objective classification of these genome sequences. Taxonomic classification approaches that are based on pairwise genetic identity measures are potentially highly automatable and are progressively gaining favour with the International Committee on Taxonomy of Viruses (ICTV). There are, however, various issues with the calculation of such measures that could potentially undermine the accuracy and consistency with which they can be applied to virus classification. Firstly, pairwise sequence identities computed based on multiple sequence alignments rather than on multiple independent pairwise alignments can lead to the deflation of identity scores with increasing dataset sizes. Also, when gap-characters need to be introduced during sequence alignments to account for insertions and deletions, methodological variations in the way that these characters are introduced and handled during pairwise genetic identity calculations can cause high degrees of inconsistency in the way that different methods classify the same sets of sequences. Here we present Sequence Demarcation Tool (SDT), a free user-friendly computer program that aims to provide a robust and highly reproducible means of objectively using pairwise genetic identity calculations to classify any set of nucleotide or amino acid sequences. SDT can produce publication quality pairwise identity plots and colour-coded distance matrices to further aid the classification of sequences according to ICTV approved taxonomic demarcation criteria. Besides a graphical interface version of the program for Windows computers, command-line versions of the program are available for a variety of different operating systems (including a parallel version for cluster computing platforms).