scholarly journals Molecular Characterization of Mycobiota and Aspergillus Species from Eupolyphaga sinensis Walker Based on High-Throughput Sequencing of ITS1 and CaM

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Ling Bai ◽  
Liu He ◽  
Penghao Yu ◽  
Jiaoyang Luo ◽  
Meihua Yang ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Fungal Species ◽  
Efficient Production ◽  
Sequencing Data ◽  
Toxigenic Fungi ◽  
Fungal Identification ◽  
Plating Method ◽  
Animal Medicine

Eupolyphaga sinensis Walker is a valuable traditional Chinese animal medicine first recorded in Shennong Bencao. Previous research has shown that E. sinensis is easily contaminated by aflatoxins (AFs), which are highly toxic mycotoxins, during harvest, storage, and transport, thereby posing a considerable threat to consumer health. Most often, these AFs are produced by Aspergillus species. In this study, we contrast the traditional culture-based dilution plating method to the high-throughput sequencing (HTS) technology for fungal identification in TCM E. sinensis. Both of the methods used internal transcribed spacer 1 (ITS1) and calmodulin (CaM) sequencing for fungal molecular identification. The new CaM primer we designed in the study is suitable for MiSeq PE300 sequencing used for identification of Aspergillus species in community DNA samples. More fungal species were found in the E. sinensis samples based on HTS than those found using the culture-based dilution plating method. Overall, combining the sequencing power of ITS1 and CaM is an effective method for the detection and monitoring of potential toxigenic Aspergillus species in E. sinensis. In conclusion, HTS can be used to obtain a large amount of sequencing data about fungi contaminating animal medicine, allowing earlier detection of potential toxigenic fungi and ensuring the efficient production and safety of E. sinensis.

Strengths and Biases of High-Throughput Sequencing Data in the Characterization of Freshwater Ciliate Microbiomes

2016 ◽  
Vol 73 (4) ◽  
pp. 865-875 ◽  
Author(s):  
Vittorio Boscaro ◽  
Alessia Rossi ◽  
Claudia Vannini ◽  
Franco Verni ◽  
Sergei I. Fokin ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
High Throughput Sequencing Data

scholarly journals Global diversity and geography of planktonic marine fungi

2020 ◽  
Vol 63 (2) ◽  
pp. 121-139 ◽  
Author(s):  
Brandon T. Hassett ◽  
Tobias R. Vonnahme ◽  
Xuefeng Peng ◽  
E.B. Gareth Jones ◽  
Céline Heuzé
Keyword(s):  
Baltic Sea ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Marine Fungi ◽  
Fungal Species ◽  
Latitudinal Gradients ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
The Baltic ◽  
Biological Patterns

AbstractGrowing interest in understanding the relevance of marine fungi to food webs, biogeochemical cycling, and biological patterns necessitates establishing a context for interpreting future findings. To help establish this context, we summarize the diversity of cultured and observed marine planktonic fungi from across the world. While exploring this diversity, we discovered that only half of the known marine fungal species have a publicly available DNA locus, which we hypothesize will likely hinder accurate high-throughput sequencing classification in the future, as it does currently. Still, we reprocessed >600 high-throughput datasets and analyzed 4.9 × 109 sequences (4.8 × 109 shotgun metagenomic reads and 1.0 × 108 amplicon sequences) and found that every fungal phylum is represented in the global marine planktonic mycobiome; however, this mycobiome is generally predominated by three phyla: the Ascomycota, Basidiomycota, and Chytridiomycota. We hypothesize that these three clades are the most abundant due to a combination of evolutionary histories, as well as physical processes that aid in their dispersal. We found that environments with atypical salinity regimes (>5 standard deviations from the global mean: Red Sea, Baltic Sea, sea ice) hosted higher proportions of the Chytridiomycota, relative to open oceans that are dominated by Dikarya. The Baltic Sea and Mediterranean Sea had the highest fungal richness of all areas explored. An analysis of similarity identified significant differences between oceanographic regions. There were no latitudinal gradients of marine fungal richness and diversity observed. As more high-throughput sequencing data become available, expanding the collection of reference loci and genomes will be essential to understanding the ecology of marine fungi.

scholarly journals Characterization of oral bacterial diversity of irradiated patients by high-throughput sequencing

2013 ◽  
Vol 5 (1) ◽  
pp. 21-25 ◽  
Author(s):  
Yue-Jian Hu ◽  
Qian Wang ◽  
Yun-Tao Jiang ◽  
Rui Ma ◽  
Wen-Wei Xia ◽  
...  
Keyword(s):  
Bacterial Diversity ◽  
High Throughput ◽  
High Throughput Sequencing

scholarly journals Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding

MycoKeys ◽  
2018 ◽  
Vol 39 ◽  
pp. 29-40 ◽  
Author(s):  
Sten Anslan ◽  
R. Henrik Nilsson ◽  
Christian Wurzbacher ◽  
Petr Baldrian ◽  
Leho Tedersoo ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Computation Time ◽  
Potential Effect ◽  
Data Sets ◽  
Sequencing Data ◽  
Operational Taxonomic Units ◽  
High Throughput Sequencing Data ◽  
Recent Developments

Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.

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