PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: Small tropical islands with dense human population: differences in water quality of near-shore waters are associated with distinct bacterial communities
items: The ΦBT1 large serine recombinase catalyzes DNA integration at pseudo-attB sites in the genus Nocardia
items: Repurposing drugs to fast-track therapeutic agents for the treatment of cryptococcosis
items: EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation
items: Temporally-aware algorithms for the classification of anuran sounds
items: The pitfalls of short-range endemism: high vulnerability to ecological and landscape traps
items: IL-6 and TNF-α salivary levels according to the periodontal status in Portuguese pregnant women
items: DNA metabarcoding of littoral hard-bottom communities: high diversity and database gaps revealed by two molecular markers
items: Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network
items: Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer

Small tropical islands with dense human population: differences in water quality of near-shore waters are associated with distinct bacterial communities
type: item
type: AcademicArticle
description: Water quality deterioration caused by an enrichment in inorganic and organic matter due to anthropogenic inputs is one of the major local threats to coral reefs in Indonesia. However, even though bacteria are important mediators in coral reef ecosystems, little is known about the response of individual taxa and whole bacterial communities to these anthropogenic inputs. The present study is the first to investigate how bacterial community composition responds to small-scale changes in water quality in several coral reef habitats of the Spermonde Archipelago including the water column, particles, and back-reef sediments, on a densely populated and an uninhabited island. The main aims were to elucidate if (a) water quality indicators and organic matter concentrations differ between the uninhabited and the densely populated island of the archipelago, and (b) if there are differences in bacterial community composition in back-reef sediments and in the water column, which are associated with differences in water quality. Several key water quality parameters, such as inorganic nitrate and phosphate, chlorophyll a, and transparent exopolymer particles (TEP) were significantly higher at the inhabited than at the uninhabited island. Bacterial communities in sediments and particle-attached communities were significantly different between the two islands with bacterial taxa commonly associated with nutrient and organic matter-rich conditions occurring in higher proportions at the inhabited island. Within the individual reef habitats, variations in bacterial community composition between the islands were associated with differences in water quality. We also observed that copiotrophic, opportunistic bacterial taxa were enriched at the inhabited island with its higher chlorophyll a, dissolved organic carbon and TEP concentrations. Given the increasing strain on tropical coastal ecosystems, this study suggests that effluents from densely populated islands lacking sewage treatment c…
format: application/pdf
format: text/html
creator: Hauke F. Kegler
creator: Christiane Hassenrück
creator: Pia Kegler
creator: Tim C. Jennerjahn
creator: Muhammad Lukman
creator: Jamaluddin Jompa
creator: Astrid Gärdes
subject: Biodiversity
subject: Marine Biology
subject: Microbiology
subject: Environmental Impacts
description: doi:10.7717/peerj.4555
publisher: PeerJ Inc.
rights: © 2018 Kegler et al.
abstract: Water quality deterioration caused by an enrichment in inorganic and organic matter due to anthropogenic inputs is one of the major local threats to coral reefs in Indonesia. However, even though bacteria are important mediators in coral reef ecosystems, little is known about the response of individual taxa and whole bacterial communities to these anthropogenic inputs. The present study is the first to investigate how bacterial community composition responds to small-scale changes in water quality in several coral reef habitats of the Spermonde Archipelago including the water column, particles, and back-reef sediments, on a densely populated and an uninhabited island. The main aims were to elucidate if (a) water quality indicators and organic matter concentrations differ between the uninhabited and the densely populated island of the archipelago, and (b) if there are differences in bacterial community composition in back-reef sediments and in the water column, which are associated with differences in water quality. Several key water quality parameters, such as inorganic nitrate and phosphate, chlorophyll a, and transparent exopolymer particles (TEP) were significantly higher at the inhabited than at the uninhabited island. Bacterial communities in sediments and particle-attached communities were significantly different between the two islands with bacterial taxa commonly associated with nutrient and organic matter-rich conditions occurring in higher proportions at the inhabited island. Within the individual reef habitats, variations in bacterial community composition between the islands were associated with differences in water quality. We also observed that copiotrophic, opportunistic bacterial taxa were enriched at the inhabited island with its higher chlorophyll a, dissolved organic carbon and TEP concentrations. Given the increasing strain on tropical coastal ecosystems, this study suggests that effluents from densely populated islands lacking sewage treatment c…
bibliographic citation: Kegler et al. (2018) Small tropical islands with dense human population: differences in water quality of near-shore waters are associated with distinct bacterial communities. PeerJ 6:e4555 https://doi.org/10.7717/peerj.4555
date submitted: 2017-12-14
date accepted: 2018-03-09
issued: 2018-05-07
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Kegler
  given name: Hauke F.
author list: Agent
  family name: Hassenrück
  given name: Christiane
author list: Agent
  family name: Kegler
  given name: Pia
author list: Agent
  family name: Jennerjahn
  given name: Tim C.
author list: Agent
  family name: Lukman
  given name: Muhammad
author list: Agent
  family name: Jompa
  given name: Jamaluddin
author list: Agent
  family name: Gärdes
  given name: Astrid
doi: 10.7717/peerj.4555
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-07
copyright: © 2018 Kegler et al.
attribution name: Kegler et al.

The ΦBT1 large serine recombinase catalyzes DNA integration at pseudo-attB sites in the genus Nocardia
type: item
type: AcademicArticle
description: Plasmid vectors based on bacteriophage integrases are important tools in molecular microbiology for the introduction of foreign DNA, especially into bacterial species where other systems for genetic manipulation are limited. Site specific integrases catalyze recombination between phage and bacterial attachment sites (attP and attB, respectively) and the best studied integrases in the actinomycetes are the serine integrases from the Streptomyces bacteriophages ΦC31 and ΦBT1. As this reaction is unidirectional and highly stable, vectors containing phage integrase systems have been used in a number of genetic engineering applications. Plasmids bearing the ΦBT1 integrase have been used to introduce DNA into Streptomyces and Amycolatopsis strains; however, they have not been widely studied in other actinobacterial genera. Here, we show that vectors based on ΦBT1 integrase can stably integrate into the chromosomes of a range of Nocardia species, and that this integration occurs despite the absence of canonical attB sites in these genomes. Furthermore, we show that a ΦBT1 integrase-based vector can insert at multiple pseudo-attB sites within a single strain and we determine the sequence of a pseudo-attB motif. These data suggest that ΦBT1 integrase-based vectors can be used to readily and semi-randomly introduce foreign DNA into the genomes of a range of Nocardia species. However, the precise site of insertion will likely require empirical determination in each species to avoid unexpected off-target effects.
format: application/pdf
format: text/html
creator: Marion Herisse
creator: Jessica L. Porter
creator: Romain Guerillot
creator: Takehiro Tomita
creator: Anders Goncalves Da Silva
creator: Torsten Seemann
creator: Benjamin P. Howden
creator: Timothy P. Stinear
creator: Sacha J. Pidot
subject: Genetics
subject: Microbiology
subject: Molecular Biology
description: doi:10.7717/peerj.4784
publisher: PeerJ Inc.
rights: © 2018 Herisse et al.
abstract: Plasmid vectors based on bacteriophage integrases are important tools in molecular microbiology for the introduction of foreign DNA, especially into bacterial species where other systems for genetic manipulation are limited. Site specific integrases catalyze recombination between phage and bacterial attachment sites (attP and attB, respectively) and the best studied integrases in the actinomycetes are the serine integrases from the Streptomyces bacteriophages ΦC31 and ΦBT1. As this reaction is unidirectional and highly stable, vectors containing phage integrase systems have been used in a number of genetic engineering applications. Plasmids bearing the ΦBT1 integrase have been used to introduce DNA into Streptomyces and Amycolatopsis strains; however, they have not been widely studied in other actinobacterial genera. Here, we show that vectors based on ΦBT1 integrase can stably integrate into the chromosomes of a range of Nocardia species, and that this integration occurs despite the absence of canonical attB sites in these genomes. Furthermore, we show that a ΦBT1 integrase-based vector can insert at multiple pseudo-attB sites within a single strain and we determine the sequence of a pseudo-attB motif. These data suggest that ΦBT1 integrase-based vectors can be used to readily and semi-randomly introduce foreign DNA into the genomes of a range of Nocardia species. However, the precise site of insertion will likely require empirical determination in each species to avoid unexpected off-target effects.
bibliographic citation: Herisse et al. (2018) The ΦBT1 large serine recombinase catalyzes DNA integration at pseudo-attB sites in the genus Nocardia. PeerJ 6:e4784 https://doi.org/10.7717/peerj.4784
date submitted: 2018-02-23
date accepted: 2018-04-27
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Herisse
  given name: Marion
author list: Agent
  family name: Porter
  given name: Jessica L.
author list: Agent
  family name: Guerillot
  given name: Romain
author list: Agent
  family name: Tomita
  given name: Takehiro
author list: Agent
  family name: Goncalves Da Silva
  given name: Anders
author list: Agent
  family name: Seemann
  given name: Torsten
author list: Agent
  family name: Howden
  given name: Benjamin P.
author list: Agent
  family name: Stinear
  given name: Timothy P.
author list: Agent
  family name: Pidot
  given name: Sacha J.
doi: 10.7717/peerj.4784
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: © 2018 Herisse et al.
attribution name: Herisse et al.

Repurposing drugs to fast-track therapeutic agents for the treatment of cryptococcosis
type: item
type: AcademicArticle
description: Many infectious diseases disproportionately affect people in the developing world. Cryptococcal meningitis is one of the most common mycoses in HIV-AIDS patients, with the highest burden of disease in sub-Saharan Africa. Current best treatment regimens still result in unacceptably high mortality rates, and more effective antifungal agents are needed urgently. Drug development is hampered by the difficulty of developing effective antifungal agents that are not also toxic to human cells, and by a reluctance among pharmaceutical companies to invest in drugs that cannot guarantee a high financial return. Drug repurposing, where existing drugs are screened for alternative activities, is becoming an attractive approach in antimicrobial discovery programs, and various compound libraries are now commercially available. As these drugs have already undergone extensive optimisation and passed regulatory hurdles this can fast-track their progress to market for new uses. This study screened the Screen-Well Enzo library of 640 compounds for candidates that phenotypically inhibited the growth of Cryptococcus deuterogattii. The anthelminthic agent flubendazole, and L-type calcium channel blockers nifedipine, nisoldipine and felodipine, appeared particularly promising and were tested in additional strains and species. Flubendazole was very active against all pathogenic Cryptococcus species, with minimum inhibitory concentrations of 0.039–0.156 μg/mL, and was equally effective against isolates that were resistant to fluconazole. While nifedipine, nisoldipine and felodipine all inhibited Cryptococcus, nisoldipine was also effective against Candida, Saccharomyces and Aspergillus. This study validates repurposing as a rapid approach for finding new agents to treat neglected infectious diseases.
format: application/pdf
format: text/html
creator: Megan Truong
creator: Leigh G. Monahan
creator: Dee A. Carter
creator: Ian G. Charles
subject: Microbiology
subject: Mycology
subject: Drugs and Devices
subject: Infectious Diseases
description: doi:10.7717/peerj.4761
publisher: PeerJ Inc.
rights: © 2018 Truong et al.
abstract: Many infectious diseases disproportionately affect people in the developing world. Cryptococcal meningitis is one of the most common mycoses in HIV-AIDS patients, with the highest burden of disease in sub-Saharan Africa. Current best treatment regimens still result in unacceptably high mortality rates, and more effective antifungal agents are needed urgently. Drug development is hampered by the difficulty of developing effective antifungal agents that are not also toxic to human cells, and by a reluctance among pharmaceutical companies to invest in drugs that cannot guarantee a high financial return. Drug repurposing, where existing drugs are screened for alternative activities, is becoming an attractive approach in antimicrobial discovery programs, and various compound libraries are now commercially available. As these drugs have already undergone extensive optimisation and passed regulatory hurdles this can fast-track their progress to market for new uses. This study screened the Screen-Well Enzo library of 640 compounds for candidates that phenotypically inhibited the growth of Cryptococcus deuterogattii. The anthelminthic agent flubendazole, and L-type calcium channel blockers nifedipine, nisoldipine and felodipine, appeared particularly promising and were tested in additional strains and species. Flubendazole was very active against all pathogenic Cryptococcus species, with minimum inhibitory concentrations of 0.039–0.156 μg/mL, and was equally effective against isolates that were resistant to fluconazole. While nifedipine, nisoldipine and felodipine all inhibited Cryptococcus, nisoldipine was also effective against Candida, Saccharomyces and Aspergillus. This study validates repurposing as a rapid approach for finding new agents to treat neglected infectious diseases.
bibliographic citation: Truong et al. (2018) Repurposing drugs to fast-track therapeutic agents for the treatment of cryptococcosis. PeerJ 6:e4761 https://doi.org/10.7717/peerj.4761
date submitted: 2018-03-20
date accepted: 2018-04-21
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Truong
  given name: Megan
author list: Agent
  family name: Monahan
  given name: Leigh G.
author list: Agent
  family name: Carter
  given name: Dee A.
author list: Agent
  family name: Charles
  given name: Ian G.
doi: 10.7717/peerj.4761
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: © 2018 Truong et al.
attribution name: Truong et al.

EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation
type: item
type: AcademicArticle
description: During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet.
format: application/pdf
format: text/html
creator: Afshine Amidi
creator: Shervine Amidi
creator: Dimitrios Vlachakis
creator: Vasileios Megalooikonomou
creator: Nikos Paragios
creator: Evangelia I. Zacharaki
subject: Bioinformatics
subject: Computational Biology
subject: Genomics
subject: Computational Science
description: doi:10.7717/peerj.4750
publisher: PeerJ Inc.
rights: © 2018 Amidi et al.
abstract: During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet.
bibliographic citation: Amidi et al. (2018) EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation. PeerJ 6:e4750 https://doi.org/10.7717/peerj.4750
date submitted: 2017-07-25
date accepted: 2018-04-21
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Amidi
  given name: Afshine
author list: Agent
  family name: Amidi
  given name: Shervine
author list: Agent
  family name: Vlachakis
  given name: Dimitrios
author list: Agent
  family name: Megalooikonomou
  given name: Vasileios
author list: Agent
  family name: Paragios
  given name: Nikos
author list: Agent
  family name: Zacharaki
  given name: Evangelia I.
doi: 10.7717/peerj.4750
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: © 2018 Amidi et al.
attribution name: Amidi et al.

Temporally-aware algorithms for the classification of anuran sounds
type: item
type: AcademicArticle
description: Several authors have shown that the sounds of anurans can be used as an indicator of climate change. Hence, the recording, storage and further processing of a huge number of anuran sounds, distributed over time and space, are required in order to obtain this indicator. Furthermore, it is desirable to have algorithms and tools for the automatic classification of the different classes of sounds. In this paper, six classification methods are proposed, all based on the data-mining domain, which strive to take advantage of the temporal character of the sounds. The definition and comparison of these classification methods is undertaken using several approaches. The main conclusions of this paper are that: (i) the sliding window method attained the best results in the experiments presented, and even outperformed the hidden Markov models usually employed in similar applications; (ii) noteworthy overall classification performance has been obtained, which is an especially striking result considering that the sounds analysed were affected by a highly noisy background; (iii) the instance selection for the determination of the sounds in the training dataset offers better results than cross-validation techniques; and (iv) the temporally-aware classifiers have revealed that they can obtain better performance than their non-temporally-aware counterparts.
format: application/pdf
format: text/html
creator: Amalia Luque
creator: Javier Romero-Lemos
creator: Alejandro Carrasco
creator: Luis Gonzalez-Abril
subject: Bioinformatics
subject: Computational Biology
subject: Data Mining and Machine Learning
subject: Climate Change Biology
description: doi:10.7717/peerj.4732
publisher: PeerJ Inc.
rights: © 2018 Luque et al.
abstract: Several authors have shown that the sounds of anurans can be used as an indicator of climate change. Hence, the recording, storage and further processing of a huge number of anuran sounds, distributed over time and space, are required in order to obtain this indicator. Furthermore, it is desirable to have algorithms and tools for the automatic classification of the different classes of sounds. In this paper, six classification methods are proposed, all based on the data-mining domain, which strive to take advantage of the temporal character of the sounds. The definition and comparison of these classification methods is undertaken using several approaches. The main conclusions of this paper are that: (i) the sliding window method attained the best results in the experiments presented, and even outperformed the hidden Markov models usually employed in similar applications; (ii) noteworthy overall classification performance has been obtained, which is an especially striking result considering that the sounds analysed were affected by a highly noisy background; (iii) the instance selection for the determination of the sounds in the training dataset offers better results than cross-validation techniques; and (iv) the temporally-aware classifiers have revealed that they can obtain better performance than their non-temporally-aware counterparts.
bibliographic citation: Luque et al. (2018) Temporally-aware algorithms for the classification of anuran sounds. PeerJ 6:e4732 https://doi.org/10.7717/peerj.4732
date submitted: 2017-12-19
date accepted: 2018-04-18
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Luque
  given name: Amalia
author list: Agent
  family name: Romero-Lemos
  given name: Javier
author list: Agent
  family name: Carrasco
  given name: Alejandro
author list: Agent
  family name: Gonzalez-Abril
  given name: Luis
doi: 10.7717/peerj.4732
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: © 2018 Luque et al.
attribution name: Luque et al.

The pitfalls of short-range endemism: high vulnerability to ecological and landscape traps
type: item
type: AcademicArticle
description: Ecological traps attract biota to low-quality habitats. Landscape traps are zones caught in a vortex of spiralling degradation. Here, we demonstrate how short-range endemic (SRE) traits may make such taxa vulnerable to ecological and landscape traps. Three SRE species of mygalomorph spider were used in this study: Idiommata blackwalli, Idiosoma sigillatum and an undescribed Aganippe sp. Mygalomorphs can be long-lived (>43 years) and select sites for permanent burrows in their early dispersal phase. Spiderlings from two species, I. blackwalli (n = 20) and Aganippe sp. (n = 50), demonstrated choice for microhabitats under experimental conditions, that correspond to where adults typically occur in situ. An invasive veldt grass microhabitat was selected almost exclusively by spiderlings of I. sigillatum. At present, habitat dominated by veldt grass in Perth, Western Australia, has lower prey diversity and abundance than undisturbed habitats and therefore may act as an ecological trap for this species. Furthermore, as a homogenising force, veldt grass can spread to form a landscape trap in naturally heterogeneous ecosystems. Selection of specialised microhabitats of SREs may explain high extinction rates in old, stable landscapes undergoing (human-induced) rapid change.
format: application/pdf
format: text/html
creator: Leanda D. Mason
creator: Philip W. Bateman
creator: Grant W. Wardell-Johnson
subject: Animal Behaviour
subject: Biodiversity
subject: Biogeography
subject: Conservation Biology
subject: Ecology
description: doi:10.7717/peerj.4715
publisher: PeerJ Inc.
rights: © 2018 Mason et al.
abstract: Ecological traps attract biota to low-quality habitats. Landscape traps are zones caught in a vortex of spiralling degradation. Here, we demonstrate how short-range endemic (SRE) traits may make such taxa vulnerable to ecological and landscape traps. Three SRE species of mygalomorph spider were used in this study: Idiommata blackwalli, Idiosoma sigillatum and an undescribed Aganippe sp. Mygalomorphs can be long-lived (>43 years) and select sites for permanent burrows in their early dispersal phase. Spiderlings from two species, I. blackwalli (n = 20) and Aganippe sp. (n = 50), demonstrated choice for microhabitats under experimental conditions, that correspond to where adults typically occur in situ. An invasive veldt grass microhabitat was selected almost exclusively by spiderlings of I. sigillatum. At present, habitat dominated by veldt grass in Perth, Western Australia, has lower prey diversity and abundance than undisturbed habitats and therefore may act as an ecological trap for this species. Furthermore, as a homogenising force, veldt grass can spread to form a landscape trap in naturally heterogeneous ecosystems. Selection of specialised microhabitats of SREs may explain high extinction rates in old, stable landscapes undergoing (human-induced) rapid change.
bibliographic citation: Mason et al. (2018) The pitfalls of short-range endemism: high vulnerability to ecological and landscape traps. PeerJ 6:e4715 https://doi.org/10.7717/peerj.4715
date submitted: 2018-02-09
date accepted: 2018-04-16
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Mason
  given name: Leanda D.
author list: Agent
  family name: Bateman
  given name: Philip W.
author list: Agent
  family name: Wardell-Johnson
  given name: Grant W.
doi: 10.7717/peerj.4715
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: © 2018 Mason et al.
attribution name: Mason et al.

IL-6 and TNF-α salivary levels according to the periodontal status in Portuguese pregnant women
type: item
type: AcademicArticle
description: Background Periodontitis is associated with increased concentration of inflammatory markers and saliva has been proposed as a non-invasive diagnostic fluid in oral and systemic diseases. The levels of salivary biomarkers, such as cytokines, could potentially be used to distinguish periodontal healthy individuals from subjects with periodontal disease. The purpose of this study was to characterize the salivary levels of two inflammatory biomarkers associated with periodontitis, interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α), in order to assess whether these cytokines salivary levels could potentially be used to complement periodontitis pregnant women diagnose. Methods Forty-four pregnant women were distributed into three groups, according to their periodontal status: healthy, mild/moderate periodontitis and severe periodontitis. Unstimulated saliva was collected and analysis of TNF-α and IL-6 salivary levels were performed with Immulite®. Results Women with periodontitis exhibited significantly higher levels (p = 0.001) of salivary IL-6 and TNF-α compared with the healthy group: 25.1 (±11.2) pg/mL vs. 16.3 (±5.0) pg/mL and 29.7 (±17.2) pg/mL vs. 16.2 (±7.6) pg/mL, approximately 1.5 and 1.8 times more, respectively. Additionally, cytokines were significantly increased (p < 0.05) in severe periodontitis compared to periodontal healthy pregnant women. Conclusions These results revealed that IL-6 and TNF-α salivary biomarkers provide high discriminatory capacity for distinguishing periodontal disease from periodontal health in pregnant women.
format: application/pdf
format: text/html
creator: Vanessa Machado
creator: Maria Fernanda Mesquita
creator: Maria Alexandra Bernardo
creator: Ester Casal
creator: Luís Proença
creator: José João Mendes
subject: Dentistry
subject: Epidemiology
subject: Immunology
subject: Nursing
description: doi:10.7717/peerj.4710
publisher: PeerJ Inc.
rights: © 2018 Machado et al.
abstract: Background Periodontitis is associated with increased concentration of inflammatory markers and saliva has been proposed as a non-invasive diagnostic fluid in oral and systemic diseases. The levels of salivary biomarkers, such as cytokines, could potentially be used to distinguish periodontal healthy individuals from subjects with periodontal disease. The purpose of this study was to characterize the salivary levels of two inflammatory biomarkers associated with periodontitis, interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α), in order to assess whether these cytokines salivary levels could potentially be used to complement periodontitis pregnant women diagnose. Methods Forty-four pregnant women were distributed into three groups, according to their periodontal status: healthy, mild/moderate periodontitis and severe periodontitis. Unstimulated saliva was collected and analysis of TNF-α and IL-6 salivary levels were performed with Immulite®. Results Women with periodontitis exhibited significantly higher levels (p = 0.001) of salivary IL-6 and TNF-α compared with the healthy group: 25.1 (±11.2) pg/mL vs. 16.3 (±5.0) pg/mL and 29.7 (±17.2) pg/mL vs. 16.2 (±7.6) pg/mL, approximately 1.5 and 1.8 times more, respectively. Additionally, cytokines were significantly increased (p < 0.05) in severe periodontitis compared to periodontal healthy pregnant women. Conclusions These results revealed that IL-6 and TNF-α salivary biomarkers provide high discriminatory capacity for distinguishing periodontal disease from periodontal health in pregnant women.
bibliographic citation: Machado et al. (2018) IL-6 and TNF-α salivary levels according to the periodontal status in Portuguese pregnant women. PeerJ 6:e4710 https://doi.org/10.7717/peerj.4710
date submitted: 2018-02-21
date accepted: 2018-04-16
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Machado
  given name: Vanessa
author list: Agent
  family name: Mesquita
  given name: Maria Fernanda
author list: Agent
  family name: Bernardo
  given name: Maria Alexandra
author list: Agent
  family name: Casal
  given name: Ester
author list: Agent
  family name: Proença
  given name: Luís
author list: Agent
  family name: Mendes
  given name: José João
doi: 10.7717/peerj.4710
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: ©2018 Machado et al.
attribution name: Machado et al.

DNA metabarcoding of littoral hard-bottom communities: high diversity and database gaps revealed by two molecular markers
type: item
type: AcademicArticle
description: Biodiversity assessment of marine hard-bottom communities is hindered by the high diversity and size-ranges of the organisms present. We developed a DNA metabarcoding protocol for biodiversity characterization of structurally complex natural marine hard-bottom communities. We used two molecular markers: the “Leray fragment” of mitochondrial cytochrome c oxidase (COI), for which a novel primer set was developed, and the V7 region of the nuclear small subunit ribosomal RNA (18S). Eight different shallow marine littoral communities from two National Parks in Spain (one in the Atlantic Ocean and another in the Mediterranean Sea) were studied. Samples were sieved into three size fractions from where DNA was extracted separately. Bayesian clustering was used for delimiting molecular operational taxonomic units (MOTUs) and custom reference databases were constructed for taxonomic assignment. Despite applying stringent filters, we found high values for MOTU richness (2,510 and 9,679 MOTUs with 18S and COI, respectively), suggesting that these communities host a large amount of yet undescribed eukaryotic biodiversity. Significant gaps are still found in sequence reference databases, which currently prevent the complete taxonomic assignment of the detected sequences. In our dataset, 85% of 18S MOTUs and 64% of COI MOTUs could be identified to phylum or lower taxonomic level. Nevertheless, those unassigned were mostly rare MOTUs with low numbers of reads, and assigned MOTUs comprised over 90% of the total sequence reads. The identification rate might be significantly improved in the future, as reference databases are further completed. Our results show that marine metabarcoding, currently applied mostly to plankton or sediments, can be adapted to structurally complex hard bottom samples. Thus, eukaryotic metabarcoding emerges as a robust, fast, objective and affordable method to comprehensively characterize the diversity of marine benthic communities dominated by macroscopic s…
format: application/pdf
format: text/html
creator: Owen S. Wangensteen
creator: Creu Palacín
creator: Magdalena Guardiola
creator: Xavier Turon
subject: Biodiversity
subject: Ecology
subject: Marine Biology
description: doi:10.7717/peerj.4705
publisher: PeerJ Inc.
rights: © 2018 Wangensteen et al.
abstract: Biodiversity assessment of marine hard-bottom communities is hindered by the high diversity and size-ranges of the organisms present. We developed a DNA metabarcoding protocol for biodiversity characterization of structurally complex natural marine hard-bottom communities. We used two molecular markers: the “Leray fragment” of mitochondrial cytochrome c oxidase (COI), for which a novel primer set was developed, and the V7 region of the nuclear small subunit ribosomal RNA (18S). Eight different shallow marine littoral communities from two National Parks in Spain (one in the Atlantic Ocean and another in the Mediterranean Sea) were studied. Samples were sieved into three size fractions from where DNA was extracted separately. Bayesian clustering was used for delimiting molecular operational taxonomic units (MOTUs) and custom reference databases were constructed for taxonomic assignment. Despite applying stringent filters, we found high values for MOTU richness (2,510 and 9,679 MOTUs with 18S and COI, respectively), suggesting that these communities host a large amount of yet undescribed eukaryotic biodiversity. Significant gaps are still found in sequence reference databases, which currently prevent the complete taxonomic assignment of the detected sequences. In our dataset, 85% of 18S MOTUs and 64% of COI MOTUs could be identified to phylum or lower taxonomic level. Nevertheless, those unassigned were mostly rare MOTUs with low numbers of reads, and assigned MOTUs comprised over 90% of the total sequence reads. The identification rate might be significantly improved in the future, as reference databases are further completed. Our results show that marine metabarcoding, currently applied mostly to plankton or sediments, can be adapted to structurally complex hard bottom samples. Thus, eukaryotic metabarcoding emerges as a robust, fast, objective and affordable method to comprehensively characterize the diversity of marine benthic communities dominated by macroscopic s…
bibliographic citation: Wangensteen et al. (2018) DNA metabarcoding of littoral hard-bottom communities: high diversity and database gaps revealed by two molecular markers. PeerJ 6:e4705 https://doi.org/10.7717/peerj.4705
date submitted: 2017-11-22
date accepted: 2018-04-15
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Wangensteen
  given name: Owen S.
author list: Agent
  family name: Palacín
  given name: Creu
author list: Agent
  family name: Guardiola
  given name: Magdalena
author list: Agent
  family name: Turon
  given name: Xavier
doi: 10.7717/peerj.4705
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: ©2018 Wangensteen et al.
attribution name: Wangensteen et al.

Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network
type: item
type: AcademicArticle
description: Background Gastric cancer (GC) is one of the most common cancers with high mortality globally. However, the molecular mechanisms of GC are unclear, and the prognosis of GC is poor. Therefore, it is important to explore the underlying mechanisms and screen for novel prognostic markers and treatment targets. Methods The genetic and clinical data of GC patients in The Cancer Genome Atlas (TCGA) was analyzed by weighted gene co-expression network analysis (WGCNA). Modules with clinical significance and preservation were distinguished, and gene ontology and pathway enrichment analysis were performed. Hub genes of these modules were validated in the TCGA dataset and another independent dataset from the Gene Expression Omnibus (GEO) database by t-test. Furthermore, the significance of these genes was confirmed via survival analysis. Results We found a preserved module consisting of 506 genes was associated with clinical traits including pathologic T stage and histologic grade. PDGFRB, COL8A1, EFEMP2, FBN1, EMILIN1, FSTL1 and KIRREL were identified as candidate genes in the module. Their expression levels were correlated with pathologic T stage and histologic grade, also affected overall survival of GC patients. Conclusion These candidate genes may be involved in proliferation and differentiation of GC cells. They may serve as novel prognostic markers and treatment targets. Moreover, most of them were first reported in GC and deserved further research.
format: application/pdf
format: text/html
creator: Jian Chen
creator: Xiuwen Wang
creator: Bing Hu
creator: Yifu He
creator: Xiaojun Qian
creator: Wei Wang
subject: Bioinformatics
subject: Genetics
subject: Oncology
description: doi:10.7717/peerj.4692
publisher: PeerJ Inc.
rights: © 2018 Chen et al.
abstract: Background Gastric cancer (GC) is one of the most common cancers with high mortality globally. However, the molecular mechanisms of GC are unclear, and the prognosis of GC is poor. Therefore, it is important to explore the underlying mechanisms and screen for novel prognostic markers and treatment targets. Methods The genetic and clinical data of GC patients in The Cancer Genome Atlas (TCGA) was analyzed by weighted gene co-expression network analysis (WGCNA). Modules with clinical significance and preservation were distinguished, and gene ontology and pathway enrichment analysis were performed. Hub genes of these modules were validated in the TCGA dataset and another independent dataset from the Gene Expression Omnibus (GEO) database by t-test. Furthermore, the significance of these genes was confirmed via survival analysis. Results We found a preserved module consisting of 506 genes was associated with clinical traits including pathologic T stage and histologic grade. PDGFRB, COL8A1, EFEMP2, FBN1, EMILIN1, FSTL1 and KIRREL were identified as candidate genes in the module. Their expression levels were correlated with pathologic T stage and histologic grade, also affected overall survival of GC patients. Conclusion These candidate genes may be involved in proliferation and differentiation of GC cells. They may serve as novel prognostic markers and treatment targets. Moreover, most of them were first reported in GC and deserved further research.
bibliographic citation: Chen et al. (2018) Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network. PeerJ 6:e4692 https://doi.org/10.7717/peerj.4692
date submitted: 2018-01-23
date accepted: 2018-04-11
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Chen
  given name: Jian
author list: Agent
  family name: Wang
  given name: Xiuwen
author list: Agent
  family name: Hu
  given name: Bing
author list: Agent
  family name: He
  given name: Yifu
author list: Agent
  family name: Qian
  given name: Xiaojun
author list: Agent
  family name: Wang
  given name: Wei
doi: 10.7717/peerj.4692
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: ©2018 Chen et al.
attribution name: Chen et al.

Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer
type: item
type: AcademicArticle
description: Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer.
format: application/pdf
format: text/html
creator: Jianing Tang
creator: Deguang Kong
creator: Qiuxia Cui
creator: Kun Wang
creator: Dan Zhang
creator: Qianqian Yuan
creator: Xing Liao
creator: Yan Gong
creator: Gaosong Wu
subject: Bioinformatics
description: doi:10.7717/peerj.4674
publisher: PeerJ Inc.
rights: © 2018 Tang et al.
abstract: Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer.
bibliographic citation: Tang et al. (2018) Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer. PeerJ 6:e4674 https://doi.org/10.7717/peerj.4674
date submitted: 2018-02-09
date accepted: 2018-04-06
issued: 2018-05-04
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tang
  given name: Jianing
author list: Agent
  family name: Kong
  given name: Deguang
author list: Agent
  family name: Cui
  given name: Qiuxia
author list: Agent
  family name: Wang
  given name: Kun
author list: Agent
  family name: Zhang
  given name: Dan
author list: Agent
  family name: Yuan
  given name: Qianqian
author list: Agent
  family name: Liao
  given name: Xing
author list: Agent
  family name: Gong
  given name: Yan
author list: Agent
  family name: Wu
  given name: Gaosong
doi: 10.7717/peerj.4674
volume: 6
issn: 2167-8359
publication name: PeerJ
publication date: 2018-05-04
copyright: ©2018 Tang et al.
attribution name: Tang et al.

PeerJ
type: Periodical
uri: PeerJ
issn: 2167-8359