18 research outputs found

    Exploring Free Energy Landscapes of Large Conformational Changes: Molecular Dynamics with Excited Normal Modes

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    Proteins are found in solution as ensembles of conformations in dynamic equilibrium. Exploration of functional motions occurring on micro- to millisecond time scales by molecular dynamics (MD) simulations still remains computationally challenging. Alternatively, normal mode (NM) analysis is a well-suited method to characterize intrinsic slow collective motions, often associated with protein function, but the absence of anharmonic effects preclude a proper characterization of conformational distributions in a multidimensional NM space. Using both methods jointly appears to be an attractive approach that allows an extended sampling of the conformational space. In line with this view, the MDeNM (molecular dynamics with excited normal modes) method presented here consists of multiple-replica short MD simulations in which motions described by a given subset of low-frequency NMs are kinetically excited. This is achieved by adding additional atomic velocities along several randomly determined linear combinations of NM vectors, thus allowing an efficient coupling between slow and fast motions. The relatively high-energy conformations generated with MDeNM are further relaxed with standard MD simulations, enabling free energy landscapes to be determined. Two widely studied proteins were selected as examples: hen egg lysozyme and HIV-1 protease. In both cases, MDeNM provides a larger extent of sampling in a few nanoseconds, outperforming long standard MD simulations. A high degree of correlation with motions inferred from experimental sources (X-ray, EPR, and NMR) and with free energy estimations obtained by metadynamics was observed. Finally, the large sets of conformations obtained with MDeNM can be used to better characterize relevant dynamical populations, allowing for a better interpretation of experimental data such as SAXS curves and NMR spectra

    Table2.DOCX

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    <p>Cyanobacteria tend to become the dominant phytoplankton component in eutrophic freshwater environments during warmer seasons. However, general observations of cyanobacterial adaptive advantages in these circumstances are insufficient to explain the prevalence of one species over another in a bloom period, which may be related to particular strategies and interactions with other components of the plankton community. In this study, we present an integrative view of a mixed cyanobacterial bloom occurring during a warm, rainy period in a tropical hydropower reservoir. We used high-throughput sequencing to follow temporal shifts in the dominance of cyanobacterial genera and shifts in the associated heterotrophic bacteria community. The bloom occurred during late spring-summer and included two distinct periods. The first period corresponded to Microcystis aeruginosa complex (MAC) dominance with a contribution from Dolichospermum circinale; this pattern coincided with high water retention time and low transparency. The second period corresponded to Cylindrospermopsis raciborskii and Synechococcus spp. dominance, and the reservoir presented lower water retention time and higher water transparency. The major bacterial phyla were primarily Cyanobacteria and Proteobacteria, followed by Actinobacteria, Bacteroidetes, Verrucomicrobia, and Planctomycetes. Temporal shifts in the dominance of cyanobacterial genera were not only associated with physical features of the water but also with shifts in the associated heterotrophic bacteria. The MAC bloom was associated with a high abundance of Bacteroidetes, particularly Cytophagales. In the second bloom period, Planctomycetes increased in relative abundance, five Planctomycetes OTUs were positively correlated with Synechococcus or C. raciborskii OTUs. Our results suggest specific interactions of the main cyanobacterial genera with certain groups of the heterotrophic bacterial community. Thus, considering biotic interactions may lead to a better understanding of the shifts in cyanobacterial dominance.</p

    Image2.TIF

    No full text
    <p>Cyanobacteria tend to become the dominant phytoplankton component in eutrophic freshwater environments during warmer seasons. However, general observations of cyanobacterial adaptive advantages in these circumstances are insufficient to explain the prevalence of one species over another in a bloom period, which may be related to particular strategies and interactions with other components of the plankton community. In this study, we present an integrative view of a mixed cyanobacterial bloom occurring during a warm, rainy period in a tropical hydropower reservoir. We used high-throughput sequencing to follow temporal shifts in the dominance of cyanobacterial genera and shifts in the associated heterotrophic bacteria community. The bloom occurred during late spring-summer and included two distinct periods. The first period corresponded to Microcystis aeruginosa complex (MAC) dominance with a contribution from Dolichospermum circinale; this pattern coincided with high water retention time and low transparency. The second period corresponded to Cylindrospermopsis raciborskii and Synechococcus spp. dominance, and the reservoir presented lower water retention time and higher water transparency. The major bacterial phyla were primarily Cyanobacteria and Proteobacteria, followed by Actinobacteria, Bacteroidetes, Verrucomicrobia, and Planctomycetes. Temporal shifts in the dominance of cyanobacterial genera were not only associated with physical features of the water but also with shifts in the associated heterotrophic bacteria. The MAC bloom was associated with a high abundance of Bacteroidetes, particularly Cytophagales. In the second bloom period, Planctomycetes increased in relative abundance, five Planctomycetes OTUs were positively correlated with Synechococcus or C. raciborskii OTUs. Our results suggest specific interactions of the main cyanobacterial genera with certain groups of the heterotrophic bacterial community. Thus, considering biotic interactions may lead to a better understanding of the shifts in cyanobacterial dominance.</p

    Table1.DOCX

    No full text
    <p>Cyanobacteria tend to become the dominant phytoplankton component in eutrophic freshwater environments during warmer seasons. However, general observations of cyanobacterial adaptive advantages in these circumstances are insufficient to explain the prevalence of one species over another in a bloom period, which may be related to particular strategies and interactions with other components of the plankton community. In this study, we present an integrative view of a mixed cyanobacterial bloom occurring during a warm, rainy period in a tropical hydropower reservoir. We used high-throughput sequencing to follow temporal shifts in the dominance of cyanobacterial genera and shifts in the associated heterotrophic bacteria community. The bloom occurred during late spring-summer and included two distinct periods. The first period corresponded to Microcystis aeruginosa complex (MAC) dominance with a contribution from Dolichospermum circinale; this pattern coincided with high water retention time and low transparency. The second period corresponded to Cylindrospermopsis raciborskii and Synechococcus spp. dominance, and the reservoir presented lower water retention time and higher water transparency. The major bacterial phyla were primarily Cyanobacteria and Proteobacteria, followed by Actinobacteria, Bacteroidetes, Verrucomicrobia, and Planctomycetes. Temporal shifts in the dominance of cyanobacterial genera were not only associated with physical features of the water but also with shifts in the associated heterotrophic bacteria. The MAC bloom was associated with a high abundance of Bacteroidetes, particularly Cytophagales. In the second bloom period, Planctomycetes increased in relative abundance, five Planctomycetes OTUs were positively correlated with Synechococcus or C. raciborskii OTUs. Our results suggest specific interactions of the main cyanobacterial genera with certain groups of the heterotrophic bacterial community. Thus, considering biotic interactions may lead to a better understanding of the shifts in cyanobacterial dominance.</p

    Image1.tif

    No full text
    <p>Cyanobacteria tend to become the dominant phytoplankton component in eutrophic freshwater environments during warmer seasons. However, general observations of cyanobacterial adaptive advantages in these circumstances are insufficient to explain the prevalence of one species over another in a bloom period, which may be related to particular strategies and interactions with other components of the plankton community. In this study, we present an integrative view of a mixed cyanobacterial bloom occurring during a warm, rainy period in a tropical hydropower reservoir. We used high-throughput sequencing to follow temporal shifts in the dominance of cyanobacterial genera and shifts in the associated heterotrophic bacteria community. The bloom occurred during late spring-summer and included two distinct periods. The first period corresponded to Microcystis aeruginosa complex (MAC) dominance with a contribution from Dolichospermum circinale; this pattern coincided with high water retention time and low transparency. The second period corresponded to Cylindrospermopsis raciborskii and Synechococcus spp. dominance, and the reservoir presented lower water retention time and higher water transparency. The major bacterial phyla were primarily Cyanobacteria and Proteobacteria, followed by Actinobacteria, Bacteroidetes, Verrucomicrobia, and Planctomycetes. Temporal shifts in the dominance of cyanobacterial genera were not only associated with physical features of the water but also with shifts in the associated heterotrophic bacteria. The MAC bloom was associated with a high abundance of Bacteroidetes, particularly Cytophagales. In the second bloom period, Planctomycetes increased in relative abundance, five Planctomycetes OTUs were positively correlated with Synechococcus or C. raciborskii OTUs. Our results suggest specific interactions of the main cyanobacterial genera with certain groups of the heterotrophic bacterial community. Thus, considering biotic interactions may lead to a better understanding of the shifts in cyanobacterial dominance.</p

    Image_2.tif

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    <p>Few studies investigate the major protein antigens targeted by the antibody diversity of infected mice with Trypanosoma cruzi. To detect global IgG antibody specificities, sera from infected mice were immunoblotted against whole T. cruzi extracts. By proteomic analysis, we were able to identify the most immunogenic T. cruzi proteins. We identified three major antigens as pyruvate phosphate dikinase, Hsp-85, and β-tubulin. The major protein band recognized by host IgG was T. cruzi β-tubulin. The T. cruzi β-tubulin gene was cloned, expressed in E. coli, and recombinant T. cruzi β-tubulin was obtained. Infection increased IgG reactivity against recombinant T. cruzi β-tubulin. A single immunization of mice with recombinant T. cruzi β-tubulin increased specific IgG reactivity and induced protection against T. cruzi infection. These results indicate that repertoire analysis is a valid approach to identify antigens for vaccines against Chagas disease.</p

    Image_1.tif

    No full text
    <p>Few studies investigate the major protein antigens targeted by the antibody diversity of infected mice with Trypanosoma cruzi. To detect global IgG antibody specificities, sera from infected mice were immunoblotted against whole T. cruzi extracts. By proteomic analysis, we were able to identify the most immunogenic T. cruzi proteins. We identified three major antigens as pyruvate phosphate dikinase, Hsp-85, and β-tubulin. The major protein band recognized by host IgG was T. cruzi β-tubulin. The T. cruzi β-tubulin gene was cloned, expressed in E. coli, and recombinant T. cruzi β-tubulin was obtained. Infection increased IgG reactivity against recombinant T. cruzi β-tubulin. A single immunization of mice with recombinant T. cruzi β-tubulin increased specific IgG reactivity and induced protection against T. cruzi infection. These results indicate that repertoire analysis is a valid approach to identify antigens for vaccines against Chagas disease.</p

    Bootstrapped phylogram of <i>Rhodnius prolixus</i> midgut lipocalins aligned with their best matches to the NR database.

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    <p>Bootstrap values above 50% are shown on the branches. The bottom line indicates 20% amino acid sequence divergence between the proteins. <i>R. prolixus</i> sequences are shown by the notation RP followed by a unique number. The remaining sequences, obtained from GenBank, are annotated with the first three letters of the genus name, followed by the first three letters of the species name, followed by their GenBank GI number. One thousand replicates were done for the bootstrap test using the neighbor joining test.</p

    Cladogram of insect Lysozymes from glycoside hydrolase Family 22.

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    <p>The <i>R. prolixus</i> sequences are shown by the notation RP- followed by a unique number. The remaining proteins were obtained from GenBank and they are annotated with accession number followed by species name. The dendrogram was generated with the UPGMA algorithm. The branches were statistically supported by bootstrap analysis (cut-off 40) based on 1,000 replicates.</p

    Bootstrapped phylogram of <i>Rhodnius prolixus</i> and other aspartyl proteinases.

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    <p>Bootstrap values above 50% are shown on the branches. The bottom line indicates 10% amino acid sequence divergence between the proteins. <i>R. prolixus</i> sequences are shown by the notation RP followed by a unique number and have a red circle preceding their names. The <i>Triatoma infestans</i> sequences from Balczun et. al. <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002594#pntd.0002594-Balczun1" target="_blank">[2]</a> have a green marker. The remaining sequences were obtained from GenBank and are annotated with the first three letters of the genus name, followed by the first three letters of the species name, followed by their GenBank GI number. One thousand replicates were done for the bootstrap test using the neighbor joining test.</p
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