scholarly journals The evolution of realized niches within freshwater Synechococcus

2019 ◽  
Author(s):  
Nicolas Tromas ◽  
Zofia E. Taranu ◽  
Mathieu Castelli ◽  
Juliana S. M. Pimentel ◽  
Daniel A. Pereira ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Environmental Parameters ◽  
Amplicon Sequencing ◽  
Fundamental Question ◽  
Rrna Gene ◽  
Biological Interactions ◽  
Sequencing Data ◽  
Evolutionary Time ◽  
Genus Level

SummaryUnderstanding how ecological traits have changed over evolutionary time is a fundamental question in biology. Specifically, the extent to which more closely-related organisms share similar ecological preferences due to phylogenetic conservation – or if they are forced apart by competition – is still debated. Here we explored the co-occurrence patterns of freshwater cyanobacteria at the sub-genus level to investigate whether more closely-related taxa share more similar niches, and to what extent these niches were defined by abiotic or biotic variables. We used deep 16S rRNA gene amplicon sequencing and measured several abiotic environmental parameters (nutrients, temperature, etc.) in water samples collected over time and space in Furnas Reservoir, Brazil. We found that relatively more closely-related Synechococcus (in the continuous range of 93-100% nucleotide identity in 16S) had an increased tendency to co-occur with one another (i.e. had similar realized niches). This tendency could not be easily explained by shared preferences for measured abiotic niche dimensions. Thus, commonly measured abiotic parameters might not be sufficient to characterize, nor to predict community assembly or dynamics. Rather, co-occurrence between Synechococcus and the surrounding community (whether or not they represent true biological interactions) may be a more sensitive measure of realized niches. Overall, our results suggest that realized niches are phylogenetically conserved, at least at the sub-genus level and at the resolution of the 16S marker. Determining how these results generalize to other genera and at finer genetic resolution merits further investigation.Originality-Significance StatementWe address a fundamental question in ecology and evolution: how do niche preferences change over evolutionary time? Using time-series analysis of 16S rRNA gene amplicon sequencing data, we develop an approach to highlight the importance of biotic factors in defining realized niches, and show how niche preferences change proportionally with the 16S gene molecular clock within the genus Synechococcus. Ours is also one of few studies on the ecology of freshwater Synechococcus, adding significantly to our knowledge about this abundant and widespread lineage of Cyanobacteria.

scholarly journals 16S rRNA Gene Amplicon Sequencing Data of Tailing and Nontailing Rhizosphere Soils of Mimosa pudica from a Heavy Metal-Contaminated Ex-Tin Mining Area

2020 ◽  
Vol 9 (42) ◽  
Author(s):  
Saidu Abdullahi ◽  
Hazzeman Haris ◽  
Kamarul Z. Zarkasi ◽  
Hamzah G. Amir
Keyword(s):  
Heavy Metal ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Sequence Data ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Mimosa Pudica ◽  
Sequencing Data ◽  
Content Type ◽  
Rhizosphere Soils

ABSTRACT The 16S rRNA gene amplicon sequence data from tailing and nontailing rhizosphere soils of Mimosa pudica from a heavy metal-contaminated area are reported here. Diverse bacterial taxa were represented in the results, and the most dominant phyla were Proteobacteria (41.2%), Acidobacteria (17.1%), and Actinobacteria (14.4%).

scholarly journals The archives are half-empty: a field-wide assessment of the availability of microbial community sequencing data

2020 ◽  
Author(s):  
Stephanie D. Jurburg ◽  
Maximilian Konzack ◽  
Nico Eisenhauer ◽  
Anna Heintz-Buschart
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Amplicon Sequencing ◽  
Data Reuse ◽  
Rrna Gene ◽  
Data Loss ◽  
Sequencing Data ◽  
Data Archiving ◽  
The 16S Rrna Gene ◽  
Over Time

AbstractThe sequencing revolution has resulted in the explosive growth of public genetic repositories. These repositories now hold invaluable collections of 16S rRNA gene amplicon sequences, but the extent to which the currently archived data is findable, accessible, and reusable has not been evaluated. We conducted a field-wide assessment of the availability and state of publicly archived 16S rRNA gene amplicon sequencing data. Using custom-built pattern-based text extraction algorithms, we searched 26,927 publications in 17 microbiology or microbial ecology journals, and identified 2,015 studies which performed 16S rRNA gene amplicon sequencing. We found, for example, that 7.2% of these had not been made public at the time of analysis, a trend which increased over time. Of the 635 studies targeting the V3-V4 region of the 16S rRNA gene, 40.3% contained data which was not available or not reusable, and for 25.5% of the studies, faults in data formatting or data labelling were likely to create obstacles in data reuse. Taken together, only 34% of these datasets had potentially reusable data. Our study reveals significant gaps in the availability of currently deposited community sequencing data, identifies major contributors to data loss, and offers suggestions for improving data archiving practices in the future.

scholarly journals 16S rRNA Gene Amplicon Sequencing Data of the Iron Quadrangle Ferruginous Caves (Brazil) Shows the Importance of Conserving This Singular and Threatened Geosystem

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 ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Diversity ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Metabolic Potential ◽  
Microbial Life ◽  
Iron Quadrangle ◽  
Abundance And Diversity

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.

scholarly journals 16S rRNA Gene Amplicon Sequencing Data from Flooded Rice Paddy Mesocosms Treated with Different Silicon-Rich Soil Amendments

2021 ◽  
Vol 10 (27) ◽  
Author(s):  
Gretchen E. Dykes ◽  
Clara S. Chan ◽  
Angelia L. Seyfferth
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Soil Amendments ◽  
16S Rrna Gene Sequencing ◽  
Amplicon Sequencing ◽  
Rice Paddy ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Flooded Rice ◽  
Rrna Gene Sequencing

How silicon-rich soil amendments impact the microbial community is unresolved. We report 16S rRNA gene sequencing data from flooded rice paddy mesocosms treated with different silicon amendments sampled over the growing season. We generated 11,678 operational taxonomic units (OTUs) and found that microbial communities were significantly different across treatments, time points, and biospheres.

scholarly journals Comparing Community Measures in Lake Microbial Ecology: Metagenomes and Metatranscriptomes and Amplicons, oh my!

2020 ◽  
Author(s):  
Julia Kristina Nuy ◽  
Till Bornemann ◽  
Daniela Beisser ◽  
Alexander J. Probst ◽  
Jens Boenigk
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Environmental Variables ◽  
Physicochemical Parameters ◽  
Redundancy Analysis ◽  
Environmental Parameters ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Lake Ecosystems

Abstract Lake ecosystems are hotspots on Earth for biogeochemical cycling yet linking their microbiome to physicochemical parameters remains a challenge. Here, we assess the quality of 16S rRNA gene-based metatranscriptomics, assembled metagenomics and 16S rRNA gene amplicon sequencing for 21 lake ecosystems across Europe. We identified method-dependent, massive differences between community composition and proportional activity for key taxa like Alphaproteobacteria suggesting different ecological conclusions for the same lake ecosystems. In redundancy analysis (RDA), environmental parameters explained the greatest amount of the variance in metatranscriptomes suggesting that the active community is heavily influenced by environmental parameters. While amplicon data recruited the least amount of environmental variables in RDA (pH and temperature), four additional parameters explained the sequenced metagenomes. These results suggest that metagenomes and metatranscriptomes are currently the best methods for linking lake microbiomes to physicochemical parameters and can be used as proxies for designing future ecological surveys.

scholarly journals Examining the Evidence for an Adult Healthy Middle Ear Microbiome

mSphere ◽  
2019 ◽  
Vol 4 (5) ◽  
Author(s):  
Jake Jervis-Bardy ◽  
Lex E. X. Leong ◽  
Lito E. Papanicolas ◽  
Kerry L. Ivey ◽  
Sharad Chawla ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Otitis Media ◽  
Middle Ear ◽  
Bacterial Colonization ◽  
Amplicon Sequencing ◽  
Molecular Techniques ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Analytical Approaches

ABSTRACT Otitis media (OM) is a cluster of diseases of the middle ear that commonly result from bacterial infection. OM subtypes in which the tympanic membrane is intact (acute otitis media and otitis media with effusion) are presumed to result from pathogen translocation through the eustachian tube. Recent molecular-based studies have suggested that a diverse middle ear microbiome exists in the absence of disease. These have been largely unsupported by culture and feature species that commonly contaminate low-biomass sequencing data. Combining culture-based and molecular techniques, we undertook a detailed investigation of the evidence for bacterial colonization of the healthy middle ear. Middle ear (ME), nasopharynx (NP), and external ear canal (EC) swabs were collected from a total of 25 adult patients undergoing cochlear implant, stapedotomy, or translabyrinthine vestibular schwannoma resection. Diagnostic culture, microscopy, quantitative PCR, and 16S rRNA gene amplicon sequencing were used to assess sample bacterial content. EC and NP microbiota were consistent with previous reports. In contrast, bacterial levels in ME samples were not significantly above those in unused control swabs. Commonly detected taxa were among recognized sequencing contaminants (Methylobacterium, Pseudomonas, and Acinetobacter). Linear regression of dominant ME taxa confirmed a negative relationship between relative abundance and bacterial load, consistent with contamination. No bacteria were detected by microscopy or diagnostic culture in any middle ear sample. Our findings cast substantial doubt on previous reports identifying a healthy middle ear microbiome using 16S amplicon sequencing. IMPORTANCE Recent molecular-based studies have suggested that a diverse middle ear microbiome in adults and children can exist in the absence of disease. These studies have been largely unsupported by culture and feature species that commonly contaminate low-biomass sequencing data. While 16S rRNA gene amplicon sequencing has proven to be a highly informative technique in many clinical contexts, it is susceptible to spurious signal arising from sequencing reagent contaminants where sample biomass is low. Combining culture-based and molecular techniques, we undertook a detailed investigation of the evidence for bacterial colonization of the healthy middle ear. In finding no evidence of viable bacterial cells in middle ear samples, our study further underlines the importance of careful consideration of amplicon sequence data derived from very-low-biomass contexts and the value of analytical approaches that combine culture and molecular techniques.

scholarly journals Minimizing spurious features in 16S rRNA gene amplicon sequencing

2018 ◽  
Author(s):  
Jing Wang ◽  
Qianpeng Zhang ◽  
Guojun Wu ◽  
Chenhong Zhang ◽  
Menghui Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Simulated Data ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Sequencing Data ◽  
The Real ◽  
Matthew’S Correlation Coefficient

The 16S rRNA gene amplicon sequencing is a widely used high-throughput method for the taxonomic inference in microbial communities. Many data analysis pipelines have been developed to enhance the accuracy in reflecting the real taxonomy, in order to better guide the downstream identification, isolation and mechanistic studies. Though rigorous quality filtration steps were adopted in these pipelines, with well-designed mock and simulated data sets, we found that there were still a widely divergent number of spurious features due to the “pseudo sequences” artificially generated during the PCR and sequencing process. These pseudo sequences were in low abundances, and were unreliable determined through a weighted re-sampling test. To minimize their influences on the characterization of taxonomy, we proposed an approach that contains two steps, an abundance filtering (AF) step and the subsequent AF-based OTU picking and remapping (AOR) step, which can efficiently decrease the spurious OTUs, sequences or oligotyping features, and improve Matthew's Correlation Coefficient (MCC) values in OTU clustering. The approach can be easily integrated with the popularly-used 16S rRNA sequencing data analysis pipelines, to make the number of OTUs, alpha and beta diversities from divergent pipelines more consistent with the real structure of microbial communities.

scholarly journals Minimizing spurious features in 16S rRNA gene amplicon sequencing

2018 ◽  
Author(s):  
Jing Wang ◽  
Qianpeng Zhang ◽  
Guojun Wu ◽  
Chenhong Zhang ◽  
Menghui Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Simulated Data ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Sequencing Data ◽  
The Real ◽  
Matthew’S Correlation Coefficient

The 16S rRNA gene amplicon sequencing is a widely used high-throughput method for the taxonomic inference in microbial communities. Many data analysis pipelines have been developed to enhance the accuracy in reflecting the real taxonomy, in order to better guide the downstream identification, isolation and mechanistic studies. Though rigorous quality filtration steps were adopted in these pipelines, with well-designed mock and simulated data sets, we found that there were still a widely divergent number of spurious features due to the “pseudo sequences” artificially generated during the PCR and sequencing process. These pseudo sequences were in low abundances, and were unreliable determined through a weighted re-sampling test. To minimize their influences on the characterization of taxonomy, we proposed an approach that contains two steps, an abundance filtering (AF) step and the subsequent AF-based OTU picking and remapping (AOR) step, which can efficiently decrease the spurious OTUs, sequences or oligotyping features, and improve Matthew's Correlation Coefficient (MCC) values in OTU clustering. The approach can be easily integrated with the popularly-used 16S rRNA sequencing data analysis pipelines, to make the number of OTUs, alpha and beta diversities from divergent pipelines more consistent with the real structure of microbial communities.

scholarly journals Much ado about nothing? Off-target amplification can lead to false-positive bacterial brain microbiome detection in healthy and Parkinson’s disease individuals

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Janis R. Bedarf ◽  
Naiara Beraza ◽  
Hassan Khazneh ◽  
Ezgi Özkurt ◽  
David Baker ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
False Positive ◽  
Gene Sequencing ◽  
Bacterial Biomass ◽  
16S Rrna Gene Sequencing ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Rrna Gene Sequencing

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.

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