Diversity and dynamics of microbial communities in brown planthopper at different developmental stages revealed by high‐throughput amplicon sequencing

2019 ◽  
Vol 27 (5) ◽  
pp. 883-894 ◽  
Author(s):  
Zheng‐Liang Wang ◽  
Tian‐Zhao Wang ◽  
Hang‐Feng Zhu ◽  
Hai‐Bo Pan ◽  
Xiao‐Ping Yu
Fuels ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 241-252
Author(s):  
Dyah Asri Handayani Taroepratjeka ◽  
Tsuyoshi Imai ◽  
Prapaipid Chairattanamanokorn ◽  
Alissara Reungsang

Extreme halophiles offer the advantage to save on the costs of sterilization and water for biohydrogen production from lignocellulosic waste after the pretreatment process with their ability to withstand extreme salt concentrations. This study identifies the dominant hydrogen-producing genera and species among the acclimatized, extremely halotolerant microbial communities taken from two salt-damaged soil locations in Khon Kaen and one location from the salt evaporation pond in Samut Sakhon, Thailand. The microbial communities’ V3–V4 regions of 16srRNA were analyzed using high-throughput amplicon sequencing. A total of 345 operational taxonomic units were obtained and the high-throughput sequencing confirmed that Firmicutes was the dominant phyla of the three communities. Halanaerobium fermentans and Halanaerobacter lacunarum were the dominant hydrogen-producing species of the communities. Spatial proximity was not found to be a determining factor for similarities between these extremely halophilic microbial communities. Through the study of the microbial communities, strategies can be developed to increase biohydrogen molar yield.


Foods ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1247
Author(s):  
Emiel Van Reckem ◽  
Christina Charmpi ◽  
David Van der Veken ◽  
Wim Borremans ◽  
Luc De Vuyst ◽  
...  

Insight into the microbial species diversity of fermented meats is not only paramount to gain control over quality development, but also to better understand the link with processing technology and geographical origin. To study the composition of the microbial communities, the use of culture-independent methods is increasingly popular but often still suffers from drawbacks, such as a limited taxonomic resolution. This study aimed to apply a previously developed high-throughput amplicon sequencing (HTS) method targeting the 16S rRNA and tuf genes to characterize the bacterial communities in European fermented meats in greater detail. The data obtained broadened the view on the microbial communities that were associated with the various products examined, revealing the presence of previously underreported subdominant species. Moreover, the composition of these communities could be linked to the specificities of individual products, in particular pH, salt content, and geographical origin. In contrast, no clear links were found between the volatile organic compound profiles of the different products and the country of origin, distinct processing conditions, or microbial communities. Future application of the HTS method offers the potential to further unravel complex microbial communities in fermented meats, as well as to assess the impact of different processing conditions on microbial consortia.


PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7608
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here, we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to six fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing toward a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


PLoS ONE ◽  
2015 ◽  
Vol 10 (11) ◽  
pp. e0141590 ◽  
Author(s):  
Anja Lange ◽  
Steffen Jost ◽  
Dominik Heider ◽  
Christina Bock ◽  
Bettina Budeus ◽  
...  

2019 ◽  
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to 6 fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing towards a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


2020 ◽  
Vol 15 (5) ◽  
pp. 503-514
Author(s):  
Xiaojing Ma ◽  
Sambhaji Balaso Thakar ◽  
Huimin Zhang ◽  
Zequan Yu ◽  
Li Meng ◽  
...  

Background: The rhizosphere microbiota are of vital importance for plant growth and health in terrestrial ecosystems. There have been extensive studies aiming to identify the microbial communities as well as their relationship with host plants in different soil types. Objective: In the present study, we have employed the high-throughput sequencing technology to investigate the composition and structure of rhizosphere microbiota prosperous at the root of Dangshan Su pear growing in sandy soil and clay soil. Methods: A high-throughput amplicon sequencing survey of the bacterial 16S rRNA genes and fungal ITS regions from rhizosphere microbiota was firstly performed. Subsequently, several common bacterial and fungal communities were found to be essential to Dangshan Su pear by using a series of bioinformatics and statistics tools. Finally, the soil-preferred microbiota were identified through variance analysis and further characterized in the genus level. Result: Dangshan Su pears host rich and diverse microbial communities in thin layer of soil adhering to their roots. The composition of dominant microbial phyla is similar across different soil types, but the quantity of each microbial community varies significantly. Specially, the relative abundance of Firmicutes increases from 9.69% to 61.66% as the soil ecosystem changes from clay to sandy, which can be not only conducive to the degradation of complex plant materials, but also responsible for the disinfestation of pathogens. Conclusion: Our results have a symbolic significance for the potential efforts of rhizosphere microbiota on the soil bioavailability and plant health. Through selecting soil types and altering microbial structures, the improvement of fruit quality of Dangshan Su pear is expected to be achieved.


2019 ◽  
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to 6 fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing towards a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


2019 ◽  
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosomes are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three reverse transcription enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized reverse transcription conditions. In our comparisons, we have observed up to 6 fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing towards a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazutoshi Yoshitake ◽  
Gaku Kimura ◽  
Tomoko Sakami ◽  
Tsuyoshi Watanabe ◽  
Yukiko Taniuchi ◽  
...  

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.


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