scholarly journals Microbial Diversity Analysis of Sediment from Yeosu New Harbor of South Korea Using 16S rRNA Gene Amplicon Sequencing

2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Junho Lee ◽  
Ilwon Jeong ◽  
Jong-Oh Kim ◽  
Kyunghoi Kim

ABSTRACT The Yeosu New Harbor in the South Korean benthic environment shows a mesotrophic environment affected by the Tsushima Current and the Seomjin River. Here, we report microbial diversity in sediments of Yeosu New Harbor based on 16S rRNA gene amplicon sequencing. The dominant bacterial phylum was Proteobacteria (relative abundance, 72.5 to 78.1%).


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Sandra Reitmeier ◽  
Thomas C. A. Hitch ◽  
Nicole Treichel ◽  
Nikolaos Fikas ◽  
Bela Hausmann ◽  
...  

Abstract16S rRNA gene amplicon sequencing is a popular approach for studying microbiomes. However, some basic concepts have still not been investigated comprehensively. We studied the occurrence of spurious sequences using defined microbial communities based on data either from the literature or generated in three sequencing facilities and analyzed via both operational taxonomic units (OTUs) and amplicon sequence variants (ASVs) approaches. OTU clustering and singleton removal, a commonly used approach, delivered approximately 50% (mock communities) to 80% (gnotobiotic mice) spurious taxa. The fraction of spurious taxa was generally lower based on ASV analysis, but varied depending on the gene region targeted and the barcoding system used. A relative abundance of 0.25% was found as an effective threshold below which the analysis of spurious taxa can be prevented to a large extent in both OTU- and ASV-based analysis approaches. Using this cutoff improved the reproducibility of analysis, i.e., variation in richness estimates was reduced by 38% compared with singleton filtering using six human fecal samples across seven sequencing runs. Beta-diversity analysis of human fecal communities was markedly affected by both the filtering strategy and the type of phylogenetic distances used for comparison, highlighting the importance of carefully analyzing data before drawing conclusions on microbiome changes. In summary, handling of artifact sequences during bioinformatic processing of 16S rRNA gene amplicon data requires careful attention to avoid the generation of misleading findings. We propose the concept of effective richness to facilitate the comparison of alpha-diversity across studies.



2020 ◽  
Vol 178 ◽  
pp. 115815 ◽  
Author(s):  
Theo Y.C. Lam ◽  
Ran Mei ◽  
Zhuoying Wu ◽  
Patrick K.H. Lee ◽  
Wen-Tso Liu ◽  
...  




2015 ◽  
Author(s):  
Alfonso Benítez-Páez ◽  
Kevin J. Portune ◽  
Yolanda Sanz

AbstractBackgroundThe miniaturised and portable DNA sequencer MinIONTM has been released to the scientific community within the framework of an early access programme to evaluate its application for a wide variety of genetic approaches. This technology has demonstrated great potential, especially in genome-wide analyses. In this study, we tested the ability of the MinIONTM system to perform amplicon sequencing in order to design new approaches to study microbial diversity using nearly full-length 16S rDNA sequences.ResultsUsing R7.3 chemistry, we generated more than 3.8 million events (nt) during a single sequencing run. These data were sufficient to reconstruct more than 90% of the 16S rRNA gene sequences for 20 different species present in a mock reference community. After read mapping and 16S rRNA gene assembly, consensus sequences and 2d reads were recovered to assign taxonomic classification down to the species level. Additionally, we were able to measure the relative abundance of all the species present in a mock community and detected a biased species distribution originating from the PCR reaction using ‘universal’ primers.ConclusionsAlthough nanopore-based sequencing produces reads with lower per-base accuracy compared with other platforms, the MinIONTM DNA sequencer is valuable for both high taxonomic resolution and microbial diversity analysis. Improvements in nanopore chemistry, such as minimising base-calling errors and the nucleotide bias reported here for 16S amplicon sequencing, will further deliver more reliable information that is useful for the specific detection of microbial species and strains in complex ecosystems.



Diversity ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 494
Author(s):  
Camila G. C. Lemes ◽  
Morghana M. Villa ◽  
Érica B. Felestrino ◽  
Luiza O. Perucci ◽  
Renata A. B. Assis ◽  
...  

The Iron Quadrangle (IQ) is one of the main iron ore producing regions of the world. The exploitation of its reserves jeopardizes the high biological endemism associated with this region. This work aimed to understand the diversity and bacterial potential associated with IQ caves. Floor and ceiling samples of seven ferruginous caves and one quartzite cave were collected, and their microbial relative abundance and diversity were established by 16S rRNA gene amplicon sequencing data. The results showed that ferruginous caves present higher microbial abundance and greater microbial diversity compared to the quartzite cave. Many species belonging to genera found in these caves, such as Pseudonocardia and Streptacidiphilus, are known to produce biomolecules of biotechnological interest as macrolides and polyketides. Moreover, comparative analysis of microbial diversity and metabolic potential in a biofilm in pendant microfeature revealed that the microbiota associated with this structure is more similar to the floor rather than ceiling samples, with the presence of genera that may participate in the genesis of these cavities, for instance, Ferrovum, Geobacter, and Sideroxydans. These results provide the first glimpse of the microbial life in these environments and emphasize the need of conservation programs for these areas, which are under intense anthropogenic exploration.



2020 ◽  
Vol 9 (22) ◽  
Author(s):  
John A. Kyndt

ABSTRACT Hell Creek’s watershed is a historically important native land area located in Omaha, Nebraska, that includes Hell Creek and an adjacent flood plain. This initial microbial analysis showed that even though samples were isolated from the same watershed area, there were significant differences between the creek itself and the nearby pond.



2019 ◽  
Author(s):  
Peter Rubbens ◽  
Ruben Props ◽  
Frederiek-Maarten Kerckhof ◽  
Nico Boon ◽  
Willem Waegeman

AbstractMicrobial flow cytometry allows to rapidly characterize microbial communities. Recent research has demonstrated a moderate to strong connection between the cytometric diversity and taxonomic diversity based on 16S rRNA gene amplicon sequencing data. This creates the opportunity to integrate both types of data to study and predict the microbial community diversity in an automated and efficient way. However, microbial flow cytometry data results in a number of unique challenges that need to be addressed. The results of our work are threefold: i) We expand current microbial cytometry fingerprinting approaches by proposing and validating a model-based fingerprinting approach based upon Gaussian Mixture Models, which we called PhenoGMM. ii) We show that microbial diversity can be rapidly estimated by PhenoGMM. In combination with a supervised machine learning model, diversity estimations based on 16S rRNA gene amplicon sequencing data can be predicted. iii) We evaluate our method extensively by using multiple datasets from different ecosystems and compare its predictive power with a generic binning fingerprinting approach that is commonly used in microbial flow cytometry. These results demonstrate the strong connection between the genetic make-up of a microbial community and its phenotypic properties as measured by flow cytometry. Our workflow facilitates the study of microbial diversity and community dynamics using flow cytometry in a fast and quantitative way.ImportanceMicroorganisms are vital components in various ecoystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA. Flow cytometry has been proposed as an alternative technique to characterize microbial community diversity and dynamics. It is an optical technique, able to rapidly characterize a number of phenotypic properties of individual cells. So-called fingerprinting techniques are needed in order to describe microbial community diversity and dynamics based on flow cytometry data. In this work, we propose a more advanced fingerprinting strategy based on Gaussian Mixture Models. When samples have been analyzed by both flow cytometry and 16S rRNA gene amplicon sequencing, we show that supervised machine learning models can be used to find the relationship between the two types of data. We evaluate our workflow on datasets from different ecosystems, illustrating its general applicability for the analysisof microbial flow cytometry data. PhenoGMM facilitates the rapid characterization and predictive modelling of microbial diversity using flow cytometry.



2021 ◽  
Vol 10 (19) ◽  
Author(s):  
Hee-eun Woo ◽  
Junho Lee ◽  
Jong-Oh Kim ◽  
In-Cheol Lee ◽  
Seokjin Yoon ◽  
...  

ABSTRACT The Taehwa River Estuary is one of the largest enclosed bays in east Korea. In order to understand the environment of the Taehwa River Estuary, the microbial diversity in the sediment of the estuary was investigated through 16S rRNA gene sequencing. The predominant phyla in all locations were Proteobacteria and Bacteroidetes.



Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Janis R. Bedarf ◽  
Naiara Beraza ◽  
Hassan Khazneh ◽  
Ezgi Özkurt ◽  
David Baker ◽  
...  

Abstract Background Recent studies suggested the existence of (poly-)microbial infections in human brains. These have been described either as putative pathogens linked to the neuro-inflammatory changes seen in Parkinson’s disease (PD) and Alzheimer’s disease (AD) or as a “brain microbiome” in the context of healthy patients’ brain samples. Methods Using 16S rRNA gene sequencing, we tested the hypothesis that there is a bacterial brain microbiome. We evaluated brain samples from healthy human subjects and individuals suffering from PD (olfactory bulb and pre-frontal cortex), as well as murine brains. In line with state-of-the-art recommendations, we included several negative and positive controls in our analysis and estimated total bacterial biomass by 16S rRNA gene qPCR. Results Amplicon sequencing did detect bacterial signals in both human and murine samples, but estimated bacterial biomass was extremely low in all samples. Stringent reanalyses implied bacterial signals being explained by a combination of exogenous DNA contamination (54.8%) and false positive amplification of host DNA (34.2%, off-target amplicons). Several seemingly brain-enriched microbes in our dataset turned out to be false-positive signals upon closer examination. We identified off-target amplification as a major confounding factor in low-bacterial/high-host-DNA scenarios. These amplified human or mouse DNA sequences were clustered and falsely assigned to bacterial taxa in the majority of tested amplicon sequencing pipelines. Off-target amplicons seemed to be related to the tissue’s sterility and could also be found in independent brain 16S rRNA gene sequences. Conclusions Taxonomic signals obtained from (extremely) low biomass samples by 16S rRNA gene sequencing must be scrutinized closely to exclude the possibility of off-target amplifications, amplicons that can only appear enriched in biological samples, but are sometimes assigned to bacterial taxa. Sequences must be explicitly matched against any possible background genomes present in large quantities (i.e., the host genome). Using close scrutiny in our approach, we find no evidence supporting the hypothetical presence of either a brain microbiome or a bacterial infection in PD brains.



2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jun-ichi Kanatani ◽  
Masanori Watahiki ◽  
Keiko Kimata ◽  
Tomoko Kato ◽  
Kaoru Uchida ◽  
...  

Abstract Background Legionellosis is caused by the inhalation of aerosolized water contaminated with Legionella bacteria. In this study, we investigated the prevalence of Legionella species in aerosols collected from outdoor sites near asphalt roads, bathrooms in public bath facilities, and other indoor sites, such as buildings and private homes, using amoebic co-culture, quantitative PCR, and 16S rRNA gene amplicon sequencing. Results Legionella species were not detected by amoebic co-culture. However, Legionella DNA was detected in 114/151 (75.5%) air samples collected near roads (geometric mean ± standard deviation: 1.80 ± 0.52 log10 copies/m3), which was comparable to the numbers collected from bathrooms [15/21 (71.4%), 1.82 ± 0.50] but higher than those collected from other indoor sites [11/30 (36.7%), 0.88 ± 0.56] (P < 0.05). The amount of Legionella DNA was correlated with the monthly total precipitation (r = 0.56, P < 0.01). It was also directly and inversely correlated with the daily total precipitation for seven days (r = 0.21, P = 0.01) and one day (r = − 0.29, P < 0.01) before the sampling day, respectively. 16S rRNA gene amplicon sequencing revealed that Legionella species were detected in 9/30 samples collected near roads (mean proportion of reads, 0.11%). At the species level, L. pneumophila was detected in 2/30 samples collected near roads (the proportion of reads, 0.09 and 0.11% of the total reads number in each positive sample). The three most abundant bacterial genera in the samples collected near roads were Sphingomonas, Streptococcus, and Methylobacterium (mean proportion of reads; 21.1%, 14.6%, and 1.6%, respectively). In addition, the bacterial diversity in outdoor environment was comparable to that in indoor environment which contains aerosol-generating features and higher than that in indoor environment without the features. Conclusions DNA from Legionella species was widely present in aerosols collected from outdoor sites near asphalt roads, especially during the rainy season. Our findings suggest that there may be a risk of exposure to Legionella species not only in bathrooms but also in the areas surrounding asphalt roads. Therefore, the possibility of contracting legionellosis in daily life should be considered.



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