scholarly journals A meta-analysis reveals the environmental and host factors shaping the structure and function of the shrimp microbiota

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5382 ◽  
Author(s):  
Fernanda Cornejo-Granados ◽  
Luigui Gallardo-Becerra ◽  
Miriam Leonardo-Reza ◽  
Juan Pablo Ochoa-Romo ◽  
Adrian Ochoa-Leyva
Keyword(s):  
Developmental Stage ◽  
High Throughput Sequencing ◽  
Meta Analysis ◽  
Biological Factor ◽  
Rrna Gene ◽  
Wild Type ◽  
Biological Factors ◽  
Sequencing Data ◽  
Freshwater Environment ◽  
The Impact

The shrimp or prawn is the most valuable traded marine product in the world market today and its microbiota plays an essential role in its development, physiology, and health. The technological advances and dropping costs of high-throughput sequencing have increased the number of studies characterizing the shrimp microbiota. However, the application of different experimental and bioinformatics protocols makes it difficult to compare different studies to reach general conclusions about shrimp microbiota. To meet this necessity, we report the first meta-analysis of the microbiota from freshwater and marine shrimps using all publically available sequences of the 16S ribosomal gene (16S rRNA gene). We obtained data for 199 samples, in which 63.3% were from marine (Alvinocaris longirostris, Litopenaeus vannamei and Penaeus monodon), and 36.7% were from freshwater (Macrobrachium asperulum, Macrobrachium nipponense, Macrobranchium rosenbergii, Neocaridina denticulata) shrimps. Technical variations among studies, such as selected primers, hypervariable region, and sequencing platform showed a significant impact on the microbiota structure. Additionally, the ANOSIM and PERMANOVA analyses revealed that the most important biological factor in structuring the shrimp microbiota was the marine and freshwater environment (ANOSIM R = 0.54, P = 0.001; PERMANOVA pseudo-F = 21.8, P = 0.001), where freshwater showed higher bacterial diversity than marine shrimps. Then, for marine shrimps, the most relevant biological factors impacting the microbiota composition were lifestyle (ANOSIM R = 0.341, P = 0.001; PERMANOVA pseudo-F = 8.50, P = 0.0001), organ (ANOSIM R = 0.279, P = 0.001; PERMANOVA pseudo-F = 6.68, P = 0.001) and developmental stage (ANOSIM R = 0.240, P = 0.001; PERMANOVA pseudo-F = 5.05, P = 0.001). According to the lifestyle, organ, developmental stage, diet, and health status, the highest diversity were for wild-type, intestine, adult, wild-type diet, and healthy samples, respectively. Additionally, we used PICRUSt to predict the potential functions of the microbiota, and we found that the organ had more differentially enriched functions (93), followed by developmental stage (12) and lifestyle (9). Our analysis demonstrated that despite the impact of technical and bioinformatics factors, the biological factors were also statistically significant in shaping the microbiota. These results show that cross-study comparisons are a valuable resource for the improvement of the shrimp microbiota and microbiome fields. Thus, it is important that future studies make public their sequencing data, allowing other researchers to reach more powerful conclusions about the microbiota in this non-model organism. To our knowledge, this is the first meta-analysis that aims to define the shrimp microbiota.

scholarly journals 16S rRNA gene and 18S rRNA gene diversity in microbial mat communities in meltwater ponds on the McMurdo Ice Shelf, Antarctica

Polar Biology ◽  
2021 ◽  
Author(s):  
Eleanor E. Jackson ◽  
Ian Hawes ◽  
Anne D. Jungblut
Keyword(s):  
16S Rrna ◽  
18S Rrna ◽  
High Throughput Sequencing ◽  
Microbial Mats ◽  
Gene Diversity ◽  
Salinity Gradient ◽  
18S Rrna Gene ◽  
Rrna Gene ◽  
Ice Shelf ◽  
The Impact

AbstractThe undulating ice of the McMurdo Ice Shelf, Southern Victoria Land, supports one of the largest networks of ice-based, multiyear meltwater pond habitats in Antarctica, where microbial mats are abundant and contribute most of the biomass and biodiversity. We used 16S rRNA and 18S rRNA gene high-throughput sequencing to compare variance of the community structure in microbial mats within and between ponds with different salinities and pH. Proteobacteria and Cyanobacteria were the most abundant phyla, and composition at OTU level was highly specific for the meltwater ponds with strong community sorting along the salinity gradient. Our study provides the first detailed evaluation of eukaryote communities for the McMurdo Ice Shelf using the 18S rRNA gene. They were dominated by Ochrophyta, Chlorophyta and Ciliophora, consistent with previous microscopic analyses, but many OTUs belonging to less well-described heterotrophic protists from Antarctic ice shelves were also identified including Amoebozoa, Rhizaria and Labyrinthulea. Comparison of 16S and 18S rRNA gene communities showed that the Eukaryotes had lower richness and greater similarity between ponds in comparison with Bacteria and Archaea communities on the McMurdo Ice shelf. While there was a weak correlation between community dissimilarity and geographic distance, the congruity of microbial assemblages within ponds, especially for Bacteria and Archaea, implies strong habitat filtering in ice shelf meltwater pond ecosystems, especially due to salinity. These findings help to understand processes that are important in sustaining biodiversity and the impact of climate change on ice-based aquatic habitats in Antarctica.

PIK3CA Mutations and Their Impact on Survival Outcomes of Patients with Cervical Cancer: A Systematic Review

2020 ◽  
Vol 64 (6) ◽  
pp. 547-555
Author(s):  
Vasilios Pergialiotis ◽  
Christina Nikolaou ◽  
Dimitrios Haidopoulos ◽  
Maximos Frountzas ◽  
Nikolaos Thomakos ◽  
...  
Keyword(s):  
Systematic Review ◽  
Cervical Cancer ◽  
Cancer Progression ◽  
Meta Analysis ◽  
Current Evidence ◽  
Survival Outcomes ◽  
Cochrane Central Register ◽  
Wild Type ◽  
Pik3ca Mutations ◽  
The Impact

<b><i>Introduction:</i></b> Several studies have implicated the PIK3/AKT pathway in the pathophysiology of cancer progression as its activation seems to be aberrant in several forms of cancer. The purpose of the present systematic review is to evaluate the impact of PIK3CA mutations on survival outcomes of patients with cervical cancer. <b><i>Methods:</i></b> We used the Medline (1966–2020), Scopus (2004–2020), ClinicalTrials.gov (2008–2020), EMBASE (1980–2020), Cochrane Central Register of Controlled Trials (CENTRAL) (1999–2020), and Google Scholar (2004–2020) databases in our primary search along with the reference lists of electronically retrieved full-text papers. Statistical meta-analysis was performed with the RevMan 5.3 software. <b><i>Results:</i></b> Overall, 12 articles were included in the present study that comprised 2,196 women with cervical cancer. Of those, 3 studies did not report significant differences in survival outcomes among patients with mutated versus wild-type PIK3CA tumors, 5 studies reported decreased survival outcomes, and 3 studies revealed increased survival rates. The meta-analysis revealed that patients with the mutated PIK3CA genotypes had worse overall survival compared to patients with wild-type PIK3CA (HR 2.31; 95% CI: 1.51, 3.55; 95% PI: 0.54, 9.96; data from 3 studies) and the same was observed in the case of DFS rates (HR 1.82; 95% CI: 1.47, 2.25; 95% PI: 1.29, 2.56; data from 4 studies). <b><i>Conclusion:</i></b> Current evidence concerning the impact of PIK3CA mutations on survival outcomes of patients with cervical cancer is inconclusive, although the majority of included studies support a potential negative effect, primarily among those with squamous cell carcinoma tumors.

scholarly journals A Comprehensive Coexpression Network Analysis in Vibrio cholerae

mSystems ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Cory D. DuPai ◽  
Claus O. Wilke ◽  
Bryan W. Davies
Keyword(s):  
Network Analysis ◽  
Vibrio Cholerae ◽  
Rna Sequencing ◽  
High Throughput Sequencing ◽  
Model Organism ◽  
Coexpression Network ◽  
Sequencing Data ◽  
Content Type ◽  
The Impact ◽  
Coexpression Network Analysis

ABSTRACT Research into the evolution and pathogenesis of Vibrio cholerae has benefited greatly from the generation of high-throughput sequencing data to drive molecular analyses. The steady accumulation of these data sets now provides a unique opportunity for in silico hypothesis generation via coexpression analysis. Here, we leverage all published V. cholerae RNA sequencing data, in combination with select data from other platforms, to generate a gene coexpression network that validates known gene interactions and identifies novel genetic partners across the entire V. cholerae genome. This network provides direct insights into genes influencing pathogenicity, metabolism, and transcriptional regulation, further clarifies results from previous sequencing experiments in V. cholerae (e.g., transposon insertion sequencing [Tn-seq] and chromatin immunoprecipitation sequencing [ChIP-seq]), and expands upon microarray-based findings in related Gram-negative bacteria. IMPORTANCE Cholera is a devastating illness that kills tens of thousands of people annually. Vibrio cholerae, the causative agent of cholera, is an important model organism to investigate both bacterial pathogenesis and the impact of horizontal gene transfer on the emergence and dissemination of new virulent strains. Despite the importance of this pathogen, roughly one-third of V. cholerae genes are functionally unannotated, leaving large gaps in our understanding of this microbe. Through coexpression network analysis of existing RNA sequencing data, this work develops an approach to uncover novel gene-gene relationships and contextualize genes with no known function, which will advance our understanding of V. cholerae virulence and evolution.

Detection of markers predictive of macrolide and fluoroquinolone resistance in Mycoplasma genitalium from patients attending sexual health services in England

2017 ◽  
Vol 94 (1) ◽  
pp. 9-13 ◽  
Author(s):  
Rachel Pitt ◽  
Helen Fifer ◽  
Neil Woodford ◽  
Sarah Alexander
Keyword(s):  
Diagnostic Testing ◽  
Mycoplasma Genitalium ◽  
Macrolide Resistance ◽  
Fluoroquinolone Resistance ◽  
Resistance Testing ◽  
Rrna Gene ◽  
Reference Laboratory ◽  
Wild Type ◽  
Sequencing Data ◽  
The Uk

ObjectivesResistance to both macrolides and fluoroquinolones has been reported in Mycoplasma genitalium; however, due to limited diagnostics, studies are often small and confined to specific geographical areas. This study sought to determine the rate of predicted resistance in M. genitalium-positive specimens referred for diagnostic testing.MethodsSeventy-four M. genitalium-positive specimens, referred to the national reference laboratory (2010-2013) from 19 centres across England, were blinded and anonymised. Specimens were examined for markers predictive of resistance to macrolides and fluoroquinolones using PCR followed by sequence analysis of 23S rRNA gene, or gyrA and parC, respectively.Results23S rRNA gene PCR sequencing revealed that 82.4% (61/74) of specimens harboured a single nucleotide polymorphism (SNP) associated with macrolide resistance. Differences were observed between the rates of predicted macrolide resistance in male (95.1% (58/61)) and female (23.1% (3/13)) patients (P = <0.001). By contrast, all specimens for which sequencing data were available (73/74) yielded wild-type gyrA sequences; and 58/61 (95.1%) had wild-type parC genes. Three specimens (3/61 4.9%) had SNPs in the parC gene associated with fluoroquinolone treatment failure, and all three also had predicted resistance to macrolides.ConclusionsEighty-two per cent and 4.9% of M. genitalium specimens had SNPs associated with macrolide and fluoroquinolone resistance, respectively. Due to lack of widespread availability of testing for M. genitalium in the UK, this study sample was likely to be sourced from patients who may have already failed first-line macrolide therapy. Nevertheless, this study highlights the need for both greater access to M. genitalium diagnostics and genetic antimicrobial resistance testing.

scholarly journals Identification of Potential Prognostic Competing Triplets in High-Grade Serous Ovarian Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jian Zhao ◽  
Xiaofeng Song ◽  
Tianyi Xu ◽  
Qichang Yang ◽  
Jingjing Liu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
P53 Signaling ◽  
Oocyte Meiosis ◽  
The Difference ◽  
Division Cell ◽  
The Impact

Increasing lncRNA-associated competing triplets were found to play important roles in cancers. With the accumulation of high-throughput sequencing data in public databases, the size of available tumor samples is becoming larger and larger, which introduces new challenges to identify competing triplets. Here, we developed a novel method, called LncMiM, to detect the lncRNA–miRNA–mRNA competing triplets in ovarian cancer with tumor samples from the TCGA database. In LncMiM, non-linear correlation analysis is used to cover the problem of weak correlations between miRNA–target pairs, which is mainly due to the difference in the magnitude of the expression level. In addition, besides the miRNA, the impact of lncRNA and mRNA on the interactions in triplets is also considered to improve the identification sensitivity of LncMiM without reducing its accuracy. By using LncMiM, a total of 847 lncRNA-associated competing triplets were found. All the competing triplets form a miRNA–lncRNA pair centered regulatory network, in which ZFAS1, SNHG29, GAS5, AC112491.1, and AC099850.4 are the top five lncRNAs with most connections. The results of biological process and KEGG pathway enrichment analysis indicates that the competing triplets are mainly associated with cell division, cell proliferation, cell cycle, oocyte meiosis, oxidative phosphorylation, ribosome, and p53 signaling pathway. Through survival analysis, 107 potential prognostic biomarkers are found in the competing triplets, including FGD5-AS1, HCP5, HMGN4, TACC3, and so on. LncMiM is available at https://github.com/xiaofengsong/LncMiM.

scholarly journals noisyR: Enhancing biological signal in sequencing datasets by characterising random technical noise

2021 ◽  
Author(s):  
I. Moutsopoulos ◽  
L. Maischak ◽  
E. Lauzikaite ◽  
S. A. Vasquez Urbina ◽  
E. C. Williams ◽  
...  
Keyword(s):  
Background Noise ◽  
Regulatory Networks ◽  
High Throughput Sequencing ◽  
Noise Removal ◽  
Sequencing Data ◽  
Technical Noise ◽  
Transcript Quantification ◽  
Optimal Information ◽  
The Cost ◽  
The Impact

AbstractHigh-throughput sequencing enables an unprecedented resolution in transcript quantification, at the cost of magnifying the impact of technical noise. The consistent reduction of random background noise to capture functionally meaningful biological signals is still challenging. Intrinsic sequencing variability introducing low-level expression variations can obscure patterns in downstream analyses.We introduce noisyR, a comprehensive noise filter to assess the variation in signal distribution and achieve an optimal information-consistency across replicates and samples; this selection also facilitates meaningful pattern recognition outside the background-noise range. noisyR is applicable to count matrices and sequencing data; it outputs sample-specific signal/noise thresholds and filtered expression matrices.We exemplify the effects of minimising technical noise on several datasets, across various sequencing assays: coding, non-coding RNAs and interactions, at bulk and single-cell level. An immediate consequence of filtering out noise is the convergence of predictions (differential-expression calls, enrichment analyses and inference of gene regulatory networks) across different approaches.TeaserNoise removal from sequencing quantification improves the convergence of downstream tools and robustness of conclusions.

scholarly journals Genotype May Influence Bacterial Diversity in Bark and Bud of Vitis vinifera Cultivars Grown under the Same Environment

2020 ◽  
Vol 10 (23) ◽  
pp. 8405
Author(s):  
Murad Awad ◽  
Georgios Giannopoulos ◽  
Photini V. Mylona ◽  
Alexios N. Polidoros
Keyword(s):  
Bacterial Diversity ◽  
High Throughput Sequencing ◽  
Rrna Gene ◽  
Molecular Fingerprint ◽  
Microbial Inoculation ◽  
Yield And Quality ◽  
Agronomic Management ◽  
Microbiome Diversity ◽  
Ion Torrent Sequencing ◽  
The Impact

Viticulture is globally an important economic activity, and grapevine microbiomes hold a significant role in influencing yield and quality. Earlier studies showed that cultivar and agronomic management affect grapevine microbiome structure and, potentially, the quality of the end product. While microbial dynamics and ecology were established on some grapevine tissues, i.e., leaves and grapes, there is less knowledge deciphering microbiomes on other tissues, i.e., barks and buds. Moreover, although the impact on the microbiome of the so-called “vitivinicultural terroir” is well established, there are limited data considering microbiomes of genetically diverse cultivars within the same environment. Our study aims to explore microbiome diversity on bud and bark tissues of 37 different grapevine cultivars under the same environment and agronomic management. We targeted the V2-9 regions of the 16S rRNA gene of the microbiomes in bark and buds at the onset of new vegetation and bud expansion using Ion Torrent sequencing technology. Our results show that these tissues display high bacterial diversity regardless of cultivars’ use. Proteobacteria, Bacteroidetes, and Actinobacteria were the most prevalent among 11 detected phyla. The genotype of the cultivar seems to affect bacterial diversity and structure (p < 0.001) within the same environment. Our approach highlights the efficiency of high-throughput sequencing to unfold microbiomes of several grapevine parts that could be an important source of microbial inoculation and an important molecular fingerprint of the wine and grape end products.

scholarly journals Systematic processing of ribosomal RNA gene amplicon sequencing data

GigaScience ◽  
2019 ◽  
Vol 8 (12) ◽  
Author(s):  
Julien Tremblay ◽  
Etienne Yergeau
Keyword(s):  
Ribosomal Rna ◽  
High Performance ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Low Cost ◽  
Marker Gene ◽  
Fine Tuning ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Data Types

Abstract Background With the advent of high-throughput sequencing, microbiology is becoming increasingly data-intensive. Because of its low cost, robust databases, and established bioinformatic workflows, sequencing of 16S/18S/ITS ribosomal RNA (rRNA) gene amplicons, which provides a marker of choice for phylogenetic studies, has become ubiquitous. Many established end-to-end bioinformatic pipelines are available to perform short amplicon sequence data analysis. These pipelines suit a general audience, but few options exist for more specialized users who are experienced in code scripting, Linux-based systems, and high-performance computing (HPC) environments. For such an audience, existing pipelines can be limiting to fully leverage modern HPC capabilities and perform tweaking and optimization operations. Moreover, a wealth of stand-alone software packages that perform specific targeted bioinformatic tasks are increasingly accessible, and finding a way to easily integrate these applications in a pipeline is critical to the evolution of bioinformatic methodologies. Results Here we describe AmpliconTagger, a short rRNA marker gene amplicon pipeline coded in a Python framework that enables fine tuning and integration of virtually any potential rRNA gene amplicon bioinformatic procedure. It is designed to work within an HPC environment, supporting a complex network of job dependencies with a smart-restart mechanism in case of job failure or parameter modifications. As proof of concept, we present end results obtained with AmpliconTagger using 16S, 18S, ITS rRNA short gene amplicons and Pacific Biosciences long-read amplicon data types as input. Conclusions Using a selection of published algorithms for generating operational taxonomic units and amplicon sequence variants and for computing downstream taxonomic summaries and diversity metrics, we demonstrate the performance and versatility of our pipeline for systematic analyses of amplicon sequence data.

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