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      Agglutinin-Like Sequence ( ALS) Genes in the Candida parapsilosis Species Complex: Blurring the Boundaries Between Gene Families That Encode Cell-Wall Proteins

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          Abstract

          The agglutinin-like sequence (Als) proteins are best-characterized in Candida albicans and known for their role in adhesion of the fungal cell to host and abiotic surfaces. ALS sequences are often misassembled in whole-genome sequence data because each species has multiple ALS loci that contain similar sequences, most notably tandem copies of highly conserved repeated sequences. The Candida parapsilosis species complex includes Candida parapsilosis, Candida orthopsilosis, and Candida metapsilosis, three distinct but closely related species. Using publicly available genome resources, de novo genome assemblies, and laboratory experimentation including Sanger sequencing, five ALS genes were characterized in C. parapsilosis strain CDC317, three in C. orthopsilosis strain 90–125, and four in C. metapsilosis strain ATCC 96143. The newly characterized ALS genes shared similar features with the well-known C. albicans ALS family, but also displayed unique attributes such as novel short, imperfect repeat sequences that were found in other genes encoding fungal cell-wall proteins. Evidence of recombination between ALS sequences and other genes was most obvious in CmALS2265, which had the 5′ end of an ALS gene and the repeated sequences and 3′ end from the IFF/HYR family. Together, these results blur the boundaries between the fungal cell-wall families that were defined in C. albicans. TaqMan assays were used to quantify relative expression for each ALS gene. Some measurements were complicated by the assay location within the ALS gene. Considerable variation was noted in relative gene expression for isolates of the same species. Overall, however, there was a trend toward higher relative gene expression in saturated cultures rather than younger cultures. This work provides a complete description of the ALS genes in the C. parapsilosis species complex and a toolkit that promotes further investigations into the role of the Als proteins in host-fungal interactions.

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          AMPLIFICATION AND DIRECT SEQUENCING OF FUNGAL RIBOSOMAL RNA GENES FOR PHYLOGENETICS

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            Completing bacterial genome assemblies with multiplex MinION sequencing

            Illumina sequencing platforms have enabled widespread bacterial whole genome sequencing. While Illumina data is appropriate for many analyses, its short read length limits its ability to resolve genomic structure. This has major implications for tracking the spread of mobile genetic elements, including those which carry antimicrobial resistance determinants. Fully resolving a bacterial genome requires long-read sequencing such as those generated by Oxford Nanopore Technologies (ONT) platforms. Here we describe our use of the ONT MinION to sequence 12 isolates of Klebsiella pneumoniae on a single flow cell. We assembled each genome using a combination of ONT reads and previously available Illumina reads, and little to no manual intervention was needed to achieve fully resolved assemblies using the Unicycler hybrid assembler. Assembling only ONT reads with Canu was less effective, resulting in fewer resolved genomes and higher error rates even following error correction with Nanopolish. We demonstrate that multiplexed ONT sequencing is a valuable tool for high-throughput bacterial genome finishing. Specifically, we advocate the use of Illumina sequencing as a first analysis step, followed by ONT reads as needed to resolve genomic structure.
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              Bayes or bootstrap? A simulation study comparing the performance of Bayesian Markov chain Monte Carlo sampling and bootstrapping in assessing phylogenetic confidence.

              Bayesian Markov chain Monte Carlo sampling has become increasingly popular in phylogenetics as a method for both estimating the maximum likelihood topology and for assessing nodal confidence. Despite the growing use of posterior probabilities, the relationship between the Bayesian measure of confidence and the most commonly used confidence measure in phylogenetics, the nonparametric bootstrap proportion, is poorly understood. We used computer simulation to investigate the behavior of three phylogenetic confidence methods: Bayesian posterior probabilities calculated via Markov chain Monte Carlo sampling (BMCMC-PP), maximum likelihood bootstrap proportion (ML-BP), and maximum parsimony bootstrap proportion (MP-BP). We simulated the evolution of DNA sequence on 17-taxon topologies under 18 evolutionary scenarios and examined the performance of these methods in assigning confidence to correct monophyletic and incorrect monophyletic groups, and we examined the effects of increasing character number on support value. BMCMC-PP and ML-BP were often strongly correlated with one another but could provide substantially different estimates of support on short internodes. In contrast, BMCMC-PP correlated poorly with MP-BP across most of the simulation conditions that we examined. For a given threshold value, more correct monophyletic groups were supported by BMCMC-PP than by either ML-BP or MP-BP. When threshold values were chosen that fixed the rate of accepting incorrect monophyletic relationship as true at 5%, all three methods recovered most of the correct relationships on the simulated topologies, although BMCMC-PP and ML-BP performed better than MP-BP. BMCMC-PP was usually a less biased predictor of phylogenetic accuracy than either bootstrapping method. BMCMC-PP provided high support values for correct topological bipartitions with fewer characters than was needed for nonparametric bootstrap.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                26 April 2019
                2019
                : 10
                : 781
                Affiliations
                [1] 1Department of Pathobiology, University of Illinois at Urbana-Champaign , Urbana, IL, United States
                [2] 2Department of Biology, Millikin University , Decatur, IL, United States
                [3] 3Illinois Natural History Survey , Urbana, IL, United States
                [4] 4Seattle Structural Genomics Center for Infectious Disease, Seattle Children’s Hospital , Seattle, WA, United States
                [5] 5Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign , Urbana, IL, United States
                Author notes

                Edited by: Joshua D. Nosanchuk, Albert Einstein College of Medicine, United States

                Reviewed by: Maria Rapala-Kozik, Jagiellonian University, Poland; Renata Toth, University of Szeged, Hungary

                *Correspondence: Lois L. Hoyer, lhoyer@ 123456illinois.edu

                This article was submitted to Fungi and Their Interactions, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2019.00781
                6499006
                31105652
                bae27db4-6a4e-40ce-9b64-c97b338955ae
                Copyright © 2019 Oh, Smith, Miller, Staker, Fields, Hernandez and Hoyer.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 February 2019
                : 27 March 2019
                Page count
                Figures: 8, Tables: 3, Equations: 0, References: 56, Pages: 20, Words: 0
                Funding
                Funded by: National Institutes of Health 10.13039/100000002
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                agglutinin-like sequence genes,als family,candida species,adhesion,cell-wall proteins,fungi

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