scholarly journals Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments

2021 ◽  
Vol 22 (10) ◽  
pp. 5309
Author(s):  
Rebecca Ansorge ◽  
Giovanni Birolo ◽  
Stephen A. James ◽  
Andrea Telatin
Keyword(s):  
Statistical Analysis ◽  
Bacterial Communities ◽  
Its Region ◽  
Amplicon Sequencing ◽  
Bioinformatic Analysis ◽  
Taxonomic Composition ◽  
New Approach ◽  
Clustering Approach ◽  
Taxonomic Markers ◽  
Generation Sequencing

The taxonomic composition of microbial communities can be assessed using universal marker amplicon sequencing. The most common taxonomic markers are the 16S rDNA for bacterial communities and the internal transcribed spacer (ITS) region for fungal communities, but various other markers are used for barcoding eukaryotes. A crucial step in the bioinformatic analysis of amplicon sequences is the identification of representative sequences. This can be achieved using a clustering approach or by denoising raw sequencing reads. DADA2 is a widely adopted algorithm, released as an R library, that denoises marker-specific amplicons from next-generation sequencing and produces a set of representative sequences referred to as ‘Amplicon Sequence Variants’ (ASV). Here, we present Dadaist2, a modular pipeline, providing a complete suite for the analysis that ranges from raw sequencing reads to the statistics of numerical ecology. Dadaist2 implements a new approach that is specifically optimised for amplicons with variable lengths, such as the fungal ITS. The pipeline focuses on streamlining the data flow from the command line to R, with multiple options for statistical analysis and plotting, both interactive and automatic.

scholarly journals The Potential use of Bacterial Diversity Analysis of Soft Rotted Potato Tubers and Their Geocaulospheres

2021 ◽  
Author(s):  
Sanja Marković ◽  
Tatjana Popović ◽  
Tanja Berić ◽  
Ivica Dimkić ◽  
Aleksandra Jelušić ◽  
...  
Keyword(s):  
Bacterial Communities ◽  
Soft Rot ◽  
Diversity Analysis ◽  
Potato Tubers ◽  
Soft Or ◽  
New Approach ◽  
Next Generation Sequencing Ngs ◽  
Potential Use ◽  
Generation Sequencing ◽  
Potential Antimicrobial Activity

Abstract The soft rot caused by Pectobacterium and Dickeya spp. is among the most important potato disease, responsible for outbreaks worldwide. In 2018, potato tubers (cultivar Lady Claire) with and without visible soft rot symptom, together with their geocaulospheres were sampled from the field in Bačka region (Serbia). The 16S rRNA Next Generation Sequencing (NGS) of tubers with and without soft rot symptom and their corresponding soils was performed to detect differences in microbial diversity and, using this data to predict causal agent(s) of disease and which samples are potentially best for isolating biocontrol strains. The ubiquitous soil bacteria from the phyla Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were dominant in all samples. The sequences identified as Pectobacterium aroidearum, P. carotovorum, and P. polaris were present in all tested samples and it can be hypothesized that they caused soft rot. The K3 sample showed the presence of genera with potential antimicrobial activity (Pseudomonas, Arthrobacter, Chryseobacterium, Bacillus, and Exiguobacterium). This result shows that diversity analysis could be used for checking for the presence of potential antagonistic bacteria at infected sites. Also, following the presence or absence of particular taxa could point out a capacity of soil to endure a growth season without an outbreak of soft or to maintain it without significant losses. This is a new approach to interpreting the results of the diversity of bacterial communities of tubers and can be useful for screening the health status of the soil.

scholarly journals Metagenomic, Metabolomic, and Functional Evaluation of Kimchi Broth Treated with Light-Emitting Diodes (LEDs)

Metabolites ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 472
Author(s):  
Yeong-Ji Oh ◽  
Ye-Rin Park ◽  
Jungil Hong ◽  
Do-Yup Lee
Keyword(s):  
Amplicon Sequencing ◽  
Taxonomic Composition ◽  
Metabolic Phenotype ◽  
Rrna Gene ◽  
Functional Evaluation ◽  
Initial Condition ◽  
Microbial Composition ◽  
Light Emitting ◽  
Blue Led ◽  
Red Led

The light-emitting diode (LED) has been widely used in the food industry, and its application has been focused on microbial sterilization, specifically using blue-LED. The investigation has been recently extended to characterize the biotic and abiotic (photodynamic) effects of different wavelengths. Here, we investigated LED effects on kimchi fermentation. Kimchi broths were treated with three different colored-LEDs (red, green, and blue) or kept in the dark as a control. Multiomics was applied to evaluate the microbial taxonomic composition using 16S rRNA gene amplicon sequencing, and the metabolomic profiles were determined using liquid chromatography–Orbitrap mass spectrometry. Cell viability was tested to determine the potential cytotoxicity of the LED-treated kimchi broths. First, the amplicon sequencing data showed substantial changes in taxonomic composition at the family and genus levels according to incubation (initial condition vs. all other groups). The differences among the treated groups (red-LED (RLED), green-LED (GLED), blue-LED (BLED), and dark condition) were marginal. The relative abundance of Weissella was decreased in all treated groups compared to that of the initial condition, which coincided with the decreased composition of Lactobacillus. Compositional changes were relatively high in the GLED group. Subsequent metabolomic analysis indicated a unique metabolic phenotype instigated by different LED treatments, which led to the identification of the LED treatment-specific and common compounds (e.g., luteolin, 6-methylquinoline, 2-hydroxycinnamic acid, and 9-HODE). These results indicate that different LED wavelengths induce characteristic alterations in the microbial composition and metabolomic content, which may have applications in food processing and storage with the aim of improving nutritional quality and the safety of food.

Recent and Planned Developments of the Program OxCal

Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 720-730 ◽  
Author(s):  
Christopher Bronk Ramsey ◽  
Sharen Lee
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Software Package ◽  
Model Averaging ◽  
Data Sets ◽  
Radiocarbon Dates ◽  
New Approach ◽  
New Models ◽  
Multiphase Models ◽  
Deposition Models

OxCal is a widely used software package for the calibration of radiocarbon dates and the statistical analysis of 14C and other chronological information. The program aims to make statistical methods easily available to researchers and students working in a range of different disciplines. This paper will look at the recent and planned developments of the package. The recent additions to the statistical methods are primarily aimed at providing more robust models, in particular through model averaging for deposition models and through different multiphase models. The paper will look at how these new models have been implemented and explore the implications for researchers who might benefit from their use. In addition, a new approach to the evaluation of marine reservoir offsets will be presented. As the quantity and complexity of chronological data increase, it is also important to have efficient methods for the visualization of such extensive data sets and methods for the presentation of spatial and geographical data embedded within planned future versions of OxCal will also be discussed.

Back calculation of parent austenite orientation using a clustering approach

2013 ◽  
Vol 46 (1) ◽  
pp. 210-215 ◽  
Author(s):  
V. Tari ◽  
A. D. Rollett ◽  
H. Beladi
Keyword(s):  
Face Centered Cubic ◽  
Orientation Relationships ◽  
New Approach ◽  
Austenite Grain ◽  
Parent Orientation ◽  
Back Calculation ◽  
Clustering Approach ◽  
Face Centered ◽  
Parent Austenite ◽  
Good Agreement

A new approach is presented for calculating the parent orientation from sets of variants of orientations produced by phase transformation. The parent austenite orientation is determined using the orientations of bainite variants that transformed from a single parent austenite grain. In this approach, the five known orientation relationships are used to back transform each observed bainite variant to all their potential face-centered-cubic (f.c.c.) parent orientations. A set of potential f.c.c. orientations has one representative from each bainite variant, and each set is assembled on the basis of minimum mutual misorientation. The set of back-transformed orientations with the minimum summation of mutual misorientation angle (SMMA) is selected as the most probable parent (austenite) orientation. The availability of multiple sets permits a confidence index to be calculated from the best and next best fits to a parent orientation. The results show good agreement between the measured parent austenite orientation and the calculated parent orientation having minimum SMMA.

scholarly journals Uncontrolled Diabetes Mellitus Has No Major Influence on the Platelet Transcriptome

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Thomas G. Nührenberg ◽  
Marco Cederqvist ◽  
Federico Marini ◽  
Christian Stratz ◽  
Björn A. Grüning ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Next Generation Sequencing ◽  
Platelet Reactivity ◽  
Platelet Rich Plasma ◽  
Expression Profiles ◽  
Bioinformatic Analysis ◽  
Differentially Expressed ◽  
Major Influence ◽  
Next Generation ◽  
Generation Sequencing

Background. Diabetes mellitus (DM) has been associated with increased platelet reactivity as well as increased levels of platelet RNAs in plasma. Here, we sought to evaluate whether the platelet transcriptome is altered in the presence of uncontrolled DM. Methods. Next-generation sequencing (NGS) was performed on platelet RNA for 5 patients with uncontrolled DM (HbA1c 9.0%) and 5 control patients (HbA1c 5.5%) with otherwise similar clinical characteristics. RNA was isolated from leucocyte-depleted platelet-rich plasma. Libraries of platelet RNAs were created separately for long RNAs after ribosomal depletion and for small RNAs from total RNA, followed by next-generation sequencing. Results. Platelets in both groups demonstrated RNA expression profiles characterized by absence of leukocyte-specific transcripts, high expression of well-known platelet transcripts, and in total 6,343 consistently detectable transcripts. Extensive statistical bioinformatic analysis yielded 12 genes with consistently differential expression at a lenient FDR < 0.1, thereof 8 protein-coding genes and 2 genes with known expression in platelets (MACF1 and ITGB3BP). Three of the four differentially expressed noncoding genes were YRNAs (RNY1, RNY3, and RNY4) which were all downregulated in DM. 23 miRNAs were differentially expressed between the two groups. Of the 13 miRNAs with decreased expression in the diabetic group, 8 belonged to the DLK1–DIO3 gene region on chromosome 14q32.2. Conclusions. In this study, uncontrolled DM had a remote impact on different components of the platelet transcriptome. Increased expression of MACF1, together with supporting predicted mRNA-miRNA interactions as well as reduced expression of RNYs in platelets, may reflect subclinical platelet activation in uncontrolled DM.

scholarly journals Relative and quantitative rhizosphere microbiome profiling result in distinct abundance patterns

2021 ◽  
Author(s):  
Hamed Azarbad ◽  
Julien Tremblay ◽  
Luke D. Bainard ◽  
Etienne Yergeau
Keyword(s):  
Water Stress ◽  
Relative Abundance ◽  
Its Region ◽  
Cost Effective ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Real Time Quantitative Pcr ◽  
Rhizosphere Microbiome ◽  
History Of ◽  
Almost All

AbstractNext-generation sequencing is recognized as one of the most popular and cost-effective way of characterizing microbiome in multiple samples. However, most of the currently available amplicon sequencing approaches are inherently limited, as they are often presented based on the relative abundance of microbial taxa, which may not fully represent actual microbiome profiles. Here, we combined amplicon sequencing (16S rRNA gene for bacteria and ITS region for fungi) with real-time quantitative PCR (qPCR) to characterize the rhizosphere microbiome of wheat. We show that the increase in relative abundance of major microbial phyla does not necessarily result in an increase in abundance. One striking observation when comparing relative and quantitative abundances was a substantial increase in the abundance of almost all phyla associated with the rhizosphere of plants grown in soil with no history of water stress as compared with the rhizosphere of plants growing in soil with a history of water stress, which was in contradiction with the trends observed in the relative abundance data. Our results suggest that the estimated absolute abundance approach gives a different perspective than the relative abundance approach, providing complementary information that helps to better understand the rhizosphere microbiome.

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