The Experts below are selected from a list of 1149 Experts worldwide ranked by ideXlab platform

Masayuki Ishikawa - One of the best experts on this subject based on the ideXlab platform.

  • RESEARCH ARTICLE Viruses Roll the Dice: The Stochastic Behavior of Viral Genome Molecules Accelerates Viral Adaptation at the Cell and Tissue Levels
    2016
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral ge-nomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1– 20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were vali-dated experimentally by inoculating tobacco cells with a library of nucleotide sequence– tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteris

  • viruses roll the dice the stochastic behavior of viral genome molecules accelerates viral adaptation at the cell and tissue levels
    PLOS Biology, 2015
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral genomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1–20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were validated experimentally by inoculating tobacco cells with a library of nucleotide sequence–tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteristics enhance selection during tissue infection. The cell infection model also predicted a mechanism that enhances selection at the cellular level: a small difference in the replication abilities of coinfected variants results in a large difference in individual accumulation via the multiple-round formation of the replication complex (i.e., the replication machinery). Importantly, this predicted effect was observed in vivo. The cell infection model was robust to changes in the parameter values, suggesting that other viruses could adopt similar adaptation mechanisms. Taken together, these data reveal a comprehensive picture of viral infection processes including replication, cell-to-cell transmission, and evolution, which are based on the stochastic behavior of the viral genome molecules in each cell.

Shuhei Miyashita - One of the best experts on this subject based on the ideXlab platform.

  • RESEARCH ARTICLE Viruses Roll the Dice: The Stochastic Behavior of Viral Genome Molecules Accelerates Viral Adaptation at the Cell and Tissue Levels
    2016
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral ge-nomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1– 20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were vali-dated experimentally by inoculating tobacco cells with a library of nucleotide sequence– tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteris

  • viruses roll the dice the stochastic behavior of viral genome molecules accelerates viral adaptation at the cell and tissue levels
    PLOS Biology, 2015
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral genomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1–20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were validated experimentally by inoculating tobacco cells with a library of nucleotide sequence–tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteristics enhance selection during tissue infection. The cell infection model also predicted a mechanism that enhances selection at the cellular level: a small difference in the replication abilities of coinfected variants results in a large difference in individual accumulation via the multiple-round formation of the replication complex (i.e., the replication machinery). Importantly, this predicted effect was observed in vivo. The cell infection model was robust to changes in the parameter values, suggesting that other viruses could adopt similar adaptation mechanisms. Taken together, these data reveal a comprehensive picture of viral infection processes including replication, cell-to-cell transmission, and evolution, which are based on the stochastic behavior of the viral genome molecules in each cell.

Hirohisa Kishino - One of the best experts on this subject based on the ideXlab platform.

  • RESEARCH ARTICLE Viruses Roll the Dice: The Stochastic Behavior of Viral Genome Molecules Accelerates Viral Adaptation at the Cell and Tissue Levels
    2016
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral ge-nomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1– 20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were vali-dated experimentally by inoculating tobacco cells with a library of nucleotide sequence– tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteris

  • viruses roll the dice the stochastic behavior of viral genome molecules accelerates viral adaptation at the cell and tissue levels
    PLOS Biology, 2015
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral genomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1–20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were validated experimentally by inoculating tobacco cells with a library of nucleotide sequence–tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteristics enhance selection during tissue infection. The cell infection model also predicted a mechanism that enhances selection at the cellular level: a small difference in the replication abilities of coinfected variants results in a large difference in individual accumulation via the multiple-round formation of the replication complex (i.e., the replication machinery). Importantly, this predicted effect was observed in vivo. The cell infection model was robust to changes in the parameter values, suggesting that other viruses could adopt similar adaptation mechanisms. Taken together, these data reveal a comprehensive picture of viral infection processes including replication, cell-to-cell transmission, and evolution, which are based on the stochastic behavior of the viral genome molecules in each cell.

Kazuhiro Ishibashi - One of the best experts on this subject based on the ideXlab platform.

  • RESEARCH ARTICLE Viruses Roll the Dice: The Stochastic Behavior of Viral Genome Molecules Accelerates Viral Adaptation at the Cell and Tissue Levels
    2016
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral ge-nomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1– 20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were vali-dated experimentally by inoculating tobacco cells with a library of nucleotide sequence– tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteris

  • viruses roll the dice the stochastic behavior of viral genome molecules accelerates viral adaptation at the cell and tissue levels
    PLOS Biology, 2015
    Co-Authors: Shuhei Miyashita, Kazuhiro Ishibashi, Hirohisa Kishino, Masayuki Ishikawa
    Abstract:

    Recent studies on evolutionarily distant viral groups have shown that the number of viral genomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1–20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were validated experimentally by inoculating tobacco cells with a library of nucleotide sequence–tagged ToMV and analyzing the viral genomes that accumulated in each cell using a High-Throughput Sequencer. An additional simulation model revealed that these two characteristics enhance selection during tissue infection. The cell infection model also predicted a mechanism that enhances selection at the cellular level: a small difference in the replication abilities of coinfected variants results in a large difference in individual accumulation via the multiple-round formation of the replication complex (i.e., the replication machinery). Importantly, this predicted effect was observed in vivo. The cell infection model was robust to changes in the parameter values, suggesting that other viruses could adopt similar adaptation mechanisms. Taken together, these data reveal a comprehensive picture of viral infection processes including replication, cell-to-cell transmission, and evolution, which are based on the stochastic behavior of the viral genome molecules in each cell.

Ribeiro, Guilherme Menegói - One of the best experts on this subject based on the ideXlab platform.

  • Análise genômica de Mycobacterium massiliense GO 06
    2014
    Co-Authors: Ribeiro, Guilherme Menegói
    Abstract:

    As microbactérias de crescimento rápido (RGM) têm implicações importantes em patologias humanas, sendo relacionadas à infecções oportunistas. Desde sua descrição em 2004, os casos clínicos associados a Mycobacterium massiliense, uma espécie representativa do grupo das RGM, tem sido crescentemente reportados. Com o aumento dos surtos causados por essas bactérias, o desenvolvimento de novas técnicas de detecção de espécie e de predição de padrões de susceptibilidade e essencial para o controle e ciente de suas infecções. O objetivo deste trabalho e utilizar a genômica comparativa para traçar umperfil do funcionamento biológico e dos mecanismos de virulência de M. massiliense, facilitandoa descoberta de moléculas de interesse. A estirpe GO 06 de M. massiliensefoi isolada durante o surto ocorrido no período entre 2005 e 2007 em Goiás, na região central do Brasil, e teve seu genoma seqüenciado pela plataforma de seqüenciamento de alto desempenho 454 GS-FLX Titanium (Roche). Foi possível montar o genoma completo da estirpe GO 06, constituído por seu cromossomo e dois plasmídos, bem como anotar a maioria das suas ORFs preditas (3.491 ORFs, representando 84,5% do total identificado), com a identificação de 826 genes relacionados a virulência. Também foi possível identificar 46 tRNAs e um único operon de rRNA. As vias metabólicas relacionadas aos sistemas de secreção bacterianos e a bioissíntese de sideróforos de M. massiliense GO 06, geralmente envolvidas na patogenicidade microbacteriana, foram descritas in silico. 15 genes relacionados ao T7SS também foram identificados no genoma do isolado GO 06, sugerindo a existência dos sistemas ESX-3 e ESX-4. Os dados gerados neste projeto fornecem informações importantes para o desenvolvimento de estratégias de controle de surtos relacionados as RGM, sendo disponibilizados em uma página hospedada no domínio público da Universidade de Brasília. ______________________________________________________________________________ ABSTRACTRapid growing mycobacteria (RGM) have important implications in human diseases, being often related to opportunistic infections. Since its description in 2004, clinical cases related to Mycobacterium massiliense, a representative species of the RGM group, have been increasingly reported. With the increase of outbreaks related to these bacteria, the development of new species detection and susceptibility pattern prediction techniquesis essential for the efficient control of their infections. The goal of this project is touse comparative genomics to trace the biological functioning and virulence mechanisms pro_les of M. massiliense, facilitating the discovery of molecules of interest. The strain GO 06 of M. massiliense was isolated during the outbreak that occurred between 2005 and 2007 in Goias, in the midwest region of Brazil, and had its entire genome sequence dusing the 454 GS-FLX Titanium (Roche) High-Throughput Sequencer. It was possibleto construct strain GO 06's entire genome, which was comprised of its chromosome and two plasmids, and annotate the majority of its predicted ORFs (3.491 ORFs, 84,5% of all identified ORFs), with the identication of 826 genes related to virulence. It was also possible to identify 46 tRNAs and a single rRNA operon. M. massiliense GO 06'smetabolic pathways regarding bacterial secretion systems and siderophore biosynthesis,usually involved in mycobacterial pathogenicity, were described in silico. 15 genes related to T7SS were also identied in isolate GO 06's genome, suggesting the existence of ESX-3and ESX-4 systems. The data generated in this project represents useful information inthe development of control strategies of outbreaks related to RGM, being made availablein a webpage hosted in the public domain of University of Brasília

  • Análise genômica de Mycobacterium massiliense GO 06
    2014
    Co-Authors: Ribeiro, Guilherme Menegói
    Abstract:

    Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Biológicas, 2014.As microbactérias de crescimento rápido (RGM) têm implicações importantes em patologias humanas, sendo relacionadas à infecções oportunistas. Desde sua descrição em 2004, os casos clínicos associados a Mycobacterium massiliense, uma espécie representativa do grupo das RGM, tem sido crescentemente reportados. Com o aumento dos surtos causados por essas bactérias, o desenvolvimento de novas técnicas de detecção de espécie e de predição de padrões de susceptibilidade e essencial para o controle e ciente de suas infecções. O objetivo deste trabalho e utilizar a genômica comparativa para traçar umperfil do funcionamento biológico e dos mecanismos de virulência de M. massiliense, facilitandoa descoberta de moléculas de interesse. A estirpe GO 06 de M. massiliensefoi isolada durante o surto ocorrido no período entre 2005 e 2007 em Goiás, na região central do Brasil, e teve seu genoma seqüenciado pela plataforma de seqüenciamento de alto desempenho 454 GS-FLX Titanium (Roche). Foi possível montar o genoma completo da estirpe GO 06, constituído por seu cromossomo e dois plasmídos, bem como anotar a maioria das suas ORFs preditas (3.491 ORFs, representando 84,5% do total identificado), com a identificação de 826 genes relacionados a virulência. Também foi possível identificar 46 tRNAs e um único operon de rRNA. As vias metabólicas relacionadas aos sistemas de secreção bacterianos e a bioissíntese de sideróforos de M. massiliense GO 06, geralmente envolvidas na patogenicidade microbacteriana, foram descritas in silico. 15 genes relacionados ao T7SS também foram identificados no genoma do isolado GO 06, sugerindo a existência dos sistemas ESX-3 e ESX-4. Os dados gerados neste projeto fornecem informações importantes para o desenvolvimento de estratégias de controle de surtos relacionados as RGM, sendo disponibilizados em uma página hospedada no domínio público da Universidade de Brasília. ______________________________________________________________________________ ABSTRACTRapid growing mycobacteria (RGM) have important implications in human diseases, being often related to opportunistic infections. Since its description in 2004, clinical cases related to Mycobacterium massiliense, a representative species of the RGM group, have been increasingly reported. With the increase of outbreaks related to these bacteria, the development of new species detection and susceptibility pattern prediction techniquesis essential for the efficient control of their infections. The goal of this project is touse comparative genomics to trace the biological functioning and virulence mechanisms pro_les of M. massiliense, facilitating the discovery of molecules of interest. The strain GO 06 of M. massiliense was isolated during the outbreak that occurred between 2005 and 2007 in Goias, in the midwest region of Brazil, and had its entire genome sequence dusing the 454 GS-FLX Titanium (Roche) High-Throughput Sequencer. It was possibleto construct strain GO 06's entire genome, which was comprised of its chromosome and two plasmids, and annotate the majority of its predicted ORFs (3.491 ORFs, 84,5% of all identified ORFs), with the identication of 826 genes related to virulence. It was also possible to identify 46 tRNAs and a single rRNA operon. M. massiliense GO 06'smetabolic pathways regarding bacterial secretion systems and siderophore biosynthesis,usually involved in mycobacterial pathogenicity, were described in silico. 15 genes related to T7SS were also identied in isolate GO 06's genome, suggesting the existence of ESX-3and ESX-4 systems. The data generated in this project represents useful information inthe development of control strategies of outbreaks related to RGM, being made availablein a webpage hosted in the public domain of University of Brasília