Browsing by Author "Workentine, Matthew L"

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    A database for ITS2 sequences from nematodes
    (2020-07-10) Workentine, Matthew L; Chen, Rebecca; Zhu, Shawna; Gavriliuc, Stefan; Shaw, Nicolette; Rijke, Jill d; Redman, Elizabeth M; Avramenko, Russell W; Wit, Janneke; Poissant, Jocelyn; Gilleard, John S
    Abstract Background Marker gene surveys have a wide variety of applications in species identification, population genetics, and molecular epidemiology. As these methods expand to new types of organisms and additional markers beyond 16S and 18S rRNA genes, comprehensive databases are a critical requirement for proper analysis of these data. Results Here we present an ITS2 rDNA database for marker gene surveys of both free-living and parasitic nematode populations and the software used to build the database. This is currently the most complete and up-to-date ITS2 database for nematodes and is able to reproduce previous analysis that used a smaller database. Conclusions This database is an important resource for researchers working on nematodes and also provides a tool to create ITS2 databases for any given taxonomy.
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    Benchmarking hybrid assemblies of Giardia and prediction of widespread intra-isolate structural variation
    (2020-02-28) Pollo, Stephen M J; Reiling, Sarah J; Wit, Janneke; Workentine, Matthew L; Guy, Rebecca A; Batoff, G. W; Yee, Janet; Dixon, Brent R; Wasmuth, James D
    Abstract Background Currently available short read genome assemblies of the tetraploid protozoan parasite Giardia intestinalis are highly fragmented, highlighting the need for improved genome assemblies at a reasonable cost. Long nanopore reads are well suited to resolve repetitive genomic regions resulting in better quality assemblies of eukaryotic genomes. Subsequent addition of highly accurate short reads to long-read assemblies further improves assembly quality. Using this hybrid approach, we assembled genomes for three Giardia isolates, two with published assemblies and one novel, to evaluate the improvement in genome quality gained from long reads. We then used the long reads to predict structural variants to examine this previously unexplored source of genetic variation in Giardia. Methods With MinION reads for each isolate, we assembled genomes using several assemblers specializing in long reads. Assembly metrics, gene finding, and whole genome alignments to the reference genomes enabled direct comparison to evaluate the performance of the nanopore reads. Further improvements from adding Illumina reads to the long-read assemblies were evaluated using gene finding. Structural variants were predicted from alignments of the long reads to the best hybrid genome for each isolate and enrichment of key genes was analyzed using random genome sampling and calculation of percentiles to find thresholds of significance. Results Our hybrid assembly method generated reference quality genomes for each isolate. Consistent with previous findings based on SNPs, examination of heterozygosity using the structural variants found that Giardia BGS was considerably more heterozygous than the other isolates that are from Assemblage A. Further, each isolate was shown to contain structural variant regions enriched for variant-specific surface proteins, a key class of virulence factor in Giardia. Conclusions The ability to generate reference quality genomes from a single MinION run and a multiplexed MiSeq run enables future large-scale comparative genomic studies within the genus Giardia. Further, prediction of structural variants from long reads allows for more in-depth analyses of major sources of genetic variation within and between Giardia isolates that could have effects on both pathogenicity and host range.
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    Spatial distributions of Pseudomonas fluorescens colony variants in mixed-culture biofilms
    (BioMed Central, 2013-07-28) Workentine, Matthew L; Wang, Siyuan; Ceri, Howard; Turner, Raymond J
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    The effects of inhaled aztreonam on the cystic fibrosis lung microbiome
    (2017-05-05) Heirali, Alya A; Workentine, Matthew L; Acosta, Nicole; Poonja, Ali; Storey, Douglas G; Somayaji, Ranjani; Rabin, Harvey R; Whelan, Fiona J; Surette, Michael G; Parkins, Michael D
    Abstract Background Aztreonam lysine for inhalation (AZLI) is an inhaled antibiotic used to treat chronic Pseudomonas aeruginosa infection in CF. AZLI improves lung function and quality of life, and reduces exacerbations-improvements attributed to its antipseudomonal activity. Given the extremely high aztreonam concentrations achieved in the lower airways by nebulization, we speculate this may extend its spectrum of activity to other organisms. As such, we sought to determine if AZLI affects the CF lung microbiome and whether community constituents can be used to predict treatment responsiveness. Methods Patients were included if they had chronic P. aeruginosa infection and repeated sputum samples collected before and after AZLI. Sputum DNA was extracted, and the V3-hypervariable region of the 16S ribosomal RNA (rRNA) gene amplified and sequenced. Results Twenty-four patients naïve to AZLI contributed 162 samples. The cohort had a median age of 37.1 years, and a  median FEV1 of 44% predicted. Fourteen patients were a priori defined as responders for achieving ≥3% FEV1 improvement following initiation. No significant changes in alpha diversity were noted following AZLI. Furthermore, beta diversity demonstrated clustering with respect to patients, but had no association with AZLI use. However, we did observe a decline in the relative abundance of several individual operational taxonomic units (OTUs) following AZLI initiation suggesting that specific sub-populations of organisms may be impacted. Patients with higher abundance of Staphylococcus and anaerobic organisms including Prevotella and Fusobacterium were less likely to respond to therapy. Conclusions Results from our study suggest potential alternate/additional mechanisms by which AZLI functions. Moreover, our study suggests that the CF microbiota may be used as a biomarker to predict patient responsiveness to therapy suggesting the microbiome may be harnessed for the personalization of therapies.