scholarly journals Uncovering the Competences of Commonly Used Nutrient Media, Multi-primer Approach and Reference Databases in the Identification of Microalgae Diversity from Environmental Samples

2021 ◽  
Author(s):  
Amal A. Badr ◽  
Walid M. Fouad
Keyword(s):  
Molecular Level ◽  
The Other ◽  
Reference Database ◽  
Morphological Identification ◽  
Rrna Gene ◽  
Genus Level ◽  
Reference Databases ◽  
Primer Sets ◽  
Abundance And Diversity ◽  
Level Identification

Abstract Microalgae are highly diverse microorganisms and have a variety of benefits and use across different fields. On the other hand, their overgrowth can be extremely dangerous to our environment, thus, making it particularly important to continuously manage and track their abundance and diversity to oversee any potential of extinction or overgrowth. The vast diversity of microalgae imposes the challenge of their identification through the most common and economical identification method, morphological identification, and the more recent molecular-level identification tools. To enhance the identification of microalgae, we targeted enrichment of total microalgae diversity present in an environmental sample using four different enrichment media (BG-11, BBM, Modified media (MM), and half-strength Murashige and Skoog medium (MS)). Morphological identification of the enriched microalgae diversity was conducted every 4-days to monitor the population dynamics. After 14-day the DNA was extracted from the enriched population for molecular-level identification using 16S rRNA gene regions V1-V3 and V4-V5 and 18 rRNA gene V4 region. To further enhance microalgae identification through molecular-level identification, we evaluated three reference databases (SILVA, Greengenes, and Protist Ribosomal Reference (PR2)) to reveal their competence in microalgae diversity identification. A total of 38 microalgae were identified morphologically to the genus level, and the highest number of microalgae were identified through MM media (36), followed by BG-11 and BBM, 31 and 26, respectively. While sequencing the three-primer sets using the three databases, 87 microalgae were identified to the genus level. The highest diversity was identified using the MM media (71 genera) followed by BG-11 (69 genera), BBM (67 genera). Our multiple-media, primer, and reference database approach enabled us to identify a high microalgae diversity that would have been missed if a single approach was used over the other.

scholarly journals Ichthyoplankton metabarcoding as a tool for studying fish reproductive dynamics

2021 ◽  
Vol 4 ◽  
Author(s):  
Daniel Teixeira ◽  
Heron Hilário ◽  
Gustavo Rosa ◽  
Guilherme Santos ◽  
Gilmar Santos ◽  
...  
Keyword(s):  
Fish Assemblages ◽  
Fish Larvae ◽  
Reference Sequence ◽  
12S Rrna ◽  
Morphological Identification ◽  
Rrna Gene ◽  
Fish Eggs ◽  
Migration Routes ◽  
Dna Metabarcoding ◽  
Primer Sets

The study of ichthyoplankton composition, abundance and distribution is paramount to understand the reproductive dynamics of local fish assemblages. The analysis of these parameters allows the identification of spawning sites, nursery areas and migration routes. However, due to the lack of characters in early life stages, the morphological identification of ichthyoplankton is often impractical and many studies identify only fish larvae. Additionally, its accuracy shows great variation between taxonomists and laboratories according to their experience and specialty. DNA barcoding emerged as an alternative to provide assertive identification of fish eggs and larvae, but it becomes too expensive and laborious when the study demands the processing of huge amounts of organisms. DNA metabarcoding can overcome these limitations as a rapid, cost-effective, broad and accurate taxonomy tool, allowing the identification of multiple individuals simultaneously. Here, we present the identification of a sample containing 68 fish eggs and another containing 293 fish larvae from a single site in the São Francisco River Basin, Eastern Brazil, through DNA metabarcoding. We used a low-cost saline DNA extraction followed by PCR amplification with three primer sets targeting the 12S rRNA gene: MiFish (~170bp), Teleo_1 (~60bp), and NeoFish (~190bp). The latter was recently developed by our research group specifically for the identification of Neotropical fishes. All the amplified samples were sequenced in a single multiplexed Illumina MiniSeq run. We performed the filtering steps and assigned Amplicon Sequence Variants (ASVs) using a DADA2/Phyloseq based pipeline and a custom 12S reference sequence database including 101 species and 70 genera from the Jequitinhonha and São Francisco basins. The species Cyphocharax gilbert, Leporinus taeniatus, Megaleporinus elongatus, Prochilodus argenteus, P. costatus and Psalidodon fasciatus were detected by all three primer sets in the larva pool, while Pterygoplichthys etentaculatus was detected solely by NeoFish (Fig. 1). Within the egg pool, all three markers detected the species Characidium zebra, Curimatella lepidura, M. elongatus, Pimelodus fur and P. costatus, but Brycon orthotaenia was detected only by NeoFish, P. maculatus only by Teleo, and P. pohli by MiFish and Teleo (Fig. 1). The consistency in species detection among all three markers underpins the credibility of this method to accurately describe the sample composition. Considering that most of species were exclusive to the larvae or egg pool, our experiment highlights the importance of including the identification of fish eggs in reproduction studies, as it can provide additional information about which species are spawning in an area. Furthermore, the application of DNA metabarcoding to the study of ichthyoplankton can help decision makers create more informed guidelines for conservation of economically and ecologically important fish species.

scholarly journals Evaluation of 16S rRNA Gene-Based PCR Assays for Genus-Level Identification of Helicobacter Species

2008 ◽  
Vol 46 (5) ◽  
pp. 1867-1869 ◽  
Author(s):  
H. Moyaert ◽  
F. Pasmans ◽  
R. Ducatelle ◽  
F. Haesebrouck ◽  
M. Baele
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Rrna Gene ◽  
Genus Level ◽  
Pcr Assays ◽  
Level Identification

scholarly journals Species level resolution of female bladder microbiota from marker gene surveys

2020 ◽  
Author(s):  
Carter Hoffman ◽  
Nazema Y Siddiqui ◽  
Ian Fields ◽  
W. Thomas Gregory ◽  
Holly Simon ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
Variable Region ◽  
16S Rrna Gene Sequencing ◽  
Species Level ◽  
Reference Database ◽  
Rrna Gene ◽  
Rrna Gene Sequencing ◽  
Level Identification

AbstractThe human bladder contains bacteria in the absence of infection. Interest in studying these bacteria and their association with bladder conditions is increasing, but the chosen experimental method can limit the resolution of the taxonomy that can be assigned to the bacteria found in the bladder. 16S rRNA gene sequencing is commonly used to identify bacteria, but is typically restricted to genus-level identification. Our primary aim was to determine if accurate species-level identification of bladder bacteria is possible using 16S rRNA gene sequencing. We evaluated the ability of different classification schemes, each consisting of combinations of a 16S rRNA gene variable region, a reference database, and a taxonomic classification algorithm to correctly classify bladder bacteria. We show that species-level identification is possible, and that the reference database chosen is the most important component, followed by the 16S variable region sequenced.ImportanceSpecies-level information may deepen our understanding of associations between bladder microbiota and bladder conditions, such as lower urinary tract symptoms and urinary tract infections. The capability to identify bacterial species depends on large databases of sequences, algorithms that leverage statistics and available computer hardware, and knowledge of bacterial genetics and classification. Taken together, this is a daunting body of knowledge to become familiar with before the simple question of bacterial identity can be answered. Our results show the choice of taxonomic database and variable region of the 16S rRNA gene sequence makes species level identification possible. We also show this improvement can be achieved through the more careful application of existing methods and use of existing resources.

scholarly journals Evaluation of Metabarcoding Primers for Analysis of Soil Nematode Communities

Diversity ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 388
Author(s):  
Md. Maniruzzaman Sikder ◽  
Mette Vestergård ◽  
Rumakanta Sapkota ◽  
Tina Kyndt ◽  
Mogens Nicolaisen
Keyword(s):  
18S Rrna ◽  
Method Development ◽  
Soil Samples ◽  
The Other ◽  
Coi Gene ◽  
Reference Database ◽  
Soil Nematode ◽  
Extraction Step ◽  
Primer Sets ◽  
Mock Communities

While recent advances in next-generation sequencing technologies have accelerated research in microbial ecology, the application of high throughput approaches to study the ecology of nematodes remains unresolved due to several issues, e.g., whether to include an initial nematode extraction step or not, the lack of consensus on the best performing primer combination, and the absence of a curated nematode reference database. The objective of this method development study was to compare different primer sets to identify the most suitable primer set for the metabarcoding of nematodes without initial nematode extraction. We tested four primer sets for amplicon sequencing: JB3/JB5 (mitochondrial, I3-M11 partition of COI gene), SSU_04F/SSU_22R (18S rRNA, V1-V2 regions), and Nemf/18Sr2b (18S rRNA, V6-V8 regions) from earlier studies, as well as MMSF/MMSR (18S rRNA, V4-V5 regions), a newly developed primer set. We used DNA from 22 nematode taxa, 10 mock communities, 20 soil samples, 4 root samples, and one bulk soil. We amplified the target regions from the DNA samples with the four different primer combinations and sequenced the amplicons on an Illumina MiSeq sequencing platform. We found that the Nemf/18Sr2b primer set was superior for detecting soil nematodes compared to the other primer sets based on our sequencing results and on the annotation of our sequence reads at the genus and species ranks. This primer set generated 74% reads of Nematoda origin in the soil samples. Additionally, this primer set did well with the mock communities, detecting all the included specimens. It also worked better in the root samples than the other primer set that was tested. Therefore, we suggest that the Nemf/18Sr2b primer set could be used to study rhizosphere soil and root associated nematodes, and this can be done without an initial nematode extraction step.

scholarly journals First reported quantitative microbiota in different livestock manures used as organic fertilizers in the Northeast of Thailand

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lampet Wongsaroj ◽  
Ratmanee Chanabun ◽  
Naruemon Tunsakul ◽  
Pinidphon Prombutara ◽  
Somsak Panha ◽  
...  
Keyword(s):  
Pathogenic Bacteria ◽  
Organic Fertilizer ◽  
The Other ◽  
Organic Fertilizers ◽  
Rrna Gene ◽  
Bacterial Composition ◽  
Physiochemical Properties ◽  
Nutrient Profiles ◽  
Soil Recovery ◽  
Local Farmers

AbstractNortheastern Thailand relies on agriculture as a major economic activity, and has used high levels of agrochemicals due to low facility, and salty sandy soil. To support soil recovery and sustainable agriculture, local farmers have used organic fertilizers from farmed animal feces. However, knowledge about these animal fecal manures remains minimal restricting their optimal use. Specifically, while bacteria are important for soil and plant growth, an abundance and a diversity of bacterial composition in these animal fecal manures have not been reported to allow selection and adjustment for a more effective organic fertilizer. This study thereby utilized metagenomics combined with 16S rRNA gene quantitative PCR (qPCR) and sequencing to analyze quantitative microbiota profiles in association with nutrients (N, P, K), organic matters, and the other physiochemical properties, of the commonly used earthworm manure and other manures from livestock animals (including breed and feeding diet variations) in the region. Unlike the other manures, the earthworm manure demonstrated more favorable nutrient profiles and physiochemical properties for forming fertile soil. Despite low total microbial biomass, the microbiota were enriched with maximal OTUs and Chao richness, and no plant pathogenic bacteria were found based on the VFDB database. The microbial metabolic potentials supported functions to promote crop growth, such as C, N and P cyclings, xenobiotic degradation, and synthesis of bioactive compounds. Pearson’s correlation analyses indicated that the quantitative microbiota of the earthworm manure were clustered in the same direction as N, and conductivity, salinity, and water content were essential to control the microbiota of animal manures.

scholarly journals Adaptability of Ultrasonic Lamb Wave Touchscreen to the Variations in Touch Force and Touch Area

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1736
Author(s):  
Zengchong Yang ◽  
Xiucheng Liu ◽  
Bin Wu ◽  
Ren Liu
Keyword(s):  
Lamb Wave ◽  
Weight Coefficient ◽  
The Self ◽  
Reference Database ◽  
Learning Method ◽  
Improved Method ◽  
Large Area ◽  
Localization Model ◽  
Reference Databases ◽  
First Time

Previous studies on Lamb wave touchscreen (LWT) were carried out based on the assumption that the unknown touch had the consistent parameters with acoustic fingerprints in the reference database. The adaptability of LWT to the variations in touch force and touch area was investigated in this study for the first time. The automatic collection of the databases of acoustic fingerprints was realized with an experimental prototype of LWT employing three pairs of transmitter–receivers. The self-adaptive updated weight coefficient of the used transmitter–receiver pairs was employed to successfully improve the accuracy of the localization model established based on a learning method. The performance of the improved method in locating single- and two-touch actions with the reference database of different parameters was carefully evaluated. The robustness of the LWT to the variation of the touch force varied with the touch area. Moreover, it was feasible to locate touch actions of large area with reference databases of small touch areas as long as the unknown touch and the reference databases met the condition of equivalent averaged stress.

PSIX-3 Comparison of 16S rRNA gene profiles of rumen microbiome from Raramuri Criollo, European and Criollo x European lineages

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 441-442
Author(s):  
Adrian Maynez-Perez ◽  
Francisco Jahuey-Martinez ◽  
Jose A Martinez-Quintana ◽  
Michael E Hume ◽  
Robin C Anderson ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Beta Diversity ◽  
Chihuahuan Desert ◽  
Reference Database ◽  
Rrna Gene ◽  
Linear Discriminant ◽  
Microbiome Composition ◽  
Northern Mexico ◽  
Rumen Microbiome

Abstract Raramuri Criollo cattle from the Chihuahuan desert in northern Mexico have been described as an ecological ecotype due to their enormous advantage in land grass utilization and their capacity to diversify their diet with cacti, forbs and woody plants. This diversification in diet utilization, could reflect upon their microbiome composition. The aim of this study was to characterize the rumen microbiome of Raramuri criollo cattle and to compare it to other lineages that graze in the same area. A total of 28 cows representing three linages [Criollo (n = 13), European (n = 9) and Criollo x European Crossbred (n = 6)] were grazed without supplementation for 45 days. DNA was extracted from ruminal samples and the V4 region of the 16S rRNA gene was sequenced on an Illumina platform. Data were analyzed with the QIIME2 software package and DADA2 plugin and the amplicon sequence variants were taxonomically classified with naïve Bayesian using the SILVA 16S rRNA gene reference database (version 132). Statistical analysis was performed by ANOVA and PERMANOVA for alpha and beta diversity indexes, respectively, and the non-strict version of linear discriminant analysis effect size (LEfSe) was used to determine significantly different taxa among lineages. Differences in beta diversity indexes (P < 0.05) were found in ruminal microbiome composition between Criollo and European groups, whereas the Crossbred showed intermediate values when compared to the pure breeds (Table 1). LEfSe analysis identified a total of 20 bacterial groups that explained differences between lineages, including one for Crossbreed, ten for European and nine for Criollo. These results show ruminal microbiome differences between Raramuri criollo cattle and the mainstream European breeds used in the northern Mexico Chihuahuan desert and reflect that those differences could be a consequence of dissimilar grazing behavior.

scholarly journals Matrix-assisted Laser Desorption Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS) as a Reliable Tool to Identify Species of Catalase-negative Gram-positive Cocci not Belonging to the Streptococcus Genus

2016 ◽  
Vol 10 (1) ◽  
pp. 202-208 ◽  
Author(s):  
Marisa Almuzara ◽  
Claudia Barberis ◽  
Viviana Rojas Velázquez ◽  
Maria Soledad Ramirez ◽  
Angela Famiglietti ◽  
...  
Keyword(s):  
Extraction Methods ◽  
Species Level ◽  
Ionization Time ◽  
Maldi Tof Ms ◽  
Genus Level ◽  
Maldi Tof ◽  
Flight Mass Spectrometry ◽  
Level Identification ◽  
Gram Positive Cocci ◽  
Tof Ms

Objective:To evaluate the performance of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) by using 190 Catalase-negative Gram-Positive Cocci (GPC) clinical isolates.Methods:All isolates were identified by conventional phenotypic tests following the proposed scheme by Ruoff and Christensen and MALDI-TOF MS (Bruker Daltonics, BD, Bremen, Germany). Two different extraction methods (direct transfer formic acid method on spot and ethanol formic acid extraction method) and different cut-offs for genus/specie level identification were used. The score cut-offs recommended by the manufacturer (≥ 2.000 for species-level, 1.700 to 1.999 for genus level and <1.700 no reliable identification) and lower cut-off scores (≥1.500 for genus level, ≥ 1.700 for species-level and score <1.500 no reliable identification) were considered for identification. A minimum difference of 10% between the top and next closest score was required for a different genus or species.MALDI-TOF MS identification was considered correct when the result obtained from MS database agreed with the phenotypic identification result.When both methods gave discordant results, the 16S rDNA orsodAgenes sequencing was considered as the gold standard identification method. The results obtained by MS concordant with genes sequencing, although discordant with conventional phenotyping, were considered correct. MS results discordant with 16S orsodA identification were considered incorrect.Results:Using the score cut-offs recommended by the manufacturer, 97.37% and 81.05% were correctly identified to genus and species level, respectively. On the other hand, using lower cut-off scores for identification, 97.89% and 94.21% isolates were correctly identified to genus and species level respectively by MALDI-TOF MS and no significant differences between the results obtained with two extraction methods were obtained.Conclusion:The results obtained suggest that MALDI-TOF MS has the potential of being an accurate tool for Catalase-negative GPC identification even for those species with difficult diagnosis asHelcococcus,Abiotrophia,Granulicatella, among others. Nevertheless, expansion of the library, especially including more strains with different spectra on the same species might overcome potential “intraspecies” variability problems. Moreover, a decrease of the identification scores for species and genus-level identification must be considered since it may improve the MALDI-TOF MS accuracy.

scholarly journals Intestinal Taxa Abundance and Diversity in Inflammatory Bowel Disease Patients: An Analysis including Covariates and Confounders

Nutrients ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 260
Author(s):  
Adelaide Teofani ◽  
Irene Marafini ◽  
Federica Laudisi ◽  
Daniele Pietrucci ◽  
Silvia Salvatori ◽  
...  
Keyword(s):  
Dairy Products ◽  
Dietary Habits ◽  
Rrna Gene ◽  
Disease Extent ◽  
Intestinal Dysbiosis ◽  
Gene Sequence Analysis ◽  
Bowel Diseases ◽  
Inflammatory Bowel ◽  
Abundance And Diversity ◽  
The Impact

Intestinal dysbiosis has been widely documented in inflammatory bowel diseases (IBDs) and is thought to influence the onset and perpetuation of gut inflammation. However, it remains unclear whether such bacterial changes rely in part on the modification of an IBD-associated lifestyle (e.g., smoking and physical activity) and diet (e.g., rich in dairy products, cereals, meat and vegetables). In this study, we investigated the impact of these habits, which we defined as confounders and covariates, on the modulation of intestinal taxa abundance and diversity in IBD patients. 16S rRNA gene sequence analysis was performed using genomic DNA extracted from the faecal samples of 52 patients with Crohn’s disease (CD) and 58 with ulcerative colitis (UC), which are the two main types of IBD, as well as 42 healthy controls (HC). A reduced microbial diversity was documented in the IBD patients compared with the HC. Moreover, we identified specific confounders and covariates that influenced the association between some bacterial taxa and disease extent (in UC patients) or behaviour (in CD patients) compared with the HC. In particular, a PERMANOVA stepwise regression identified the variables “age”, “eat yogurt at least four days per week” and “eat dairy products at least 4 days per week” as covariates when comparing the HC and patients affected by ulcerative proctitis (E1), left-sided UC (distal UC) (E2) and extensive UC (pancolitis) (E3). Instead, the variables “age”, “gender”, “eat meat at least four days per week” and “eat bread at least 4 days per week” were considered as covariates when comparing the HC with the CD patients affected by non-stricturing, non-penetrating (B1), stricturing (B2) and penetrating (B3) diseases. Considering such variables, our analysis indicated that the UC extent differentially modulated the abundance of the Bifidobacteriaceae, Rikenellaceae, Christensenellaceae, Marinifilaceae, Desulfovibrionaceae, Lactobacillaceae, Streptococcaceae and Peptostreptococcaceae families, while the CD behaviour influenced the abundance of Christensenellaceae, Marinifilaceae, Rikenellaceae, Ruminococcaceae, Barnesiellaceae and Coriobacteriaceae families. In conclusion, our study indicated that some covariates and confounders related to an IBD-associated lifestyle and dietary habits influenced the intestinal taxa diversity and relative abundance in the CD and UC patients compared with the HC. Indeed, such variables should be identified and excluded from the analysis to characterize the bacterial families whose abundance is directly modulated by IBD status, as well as disease extent or behaviour.

scholarly journals Bioconductor workflow for microbiome data analysis: from raw reads to community analyses

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1492 ◽  
Author(s):  
Ben J. Callahan ◽  
Kris Sankaran ◽  
Julia A. Fukuyama ◽  
Paul J. McMurdie ◽  
Susan P. Holmes
Keyword(s):  
High Throughput Sequencing ◽  
Linear Models ◽  
Reference Database ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Nonparametric Testing ◽  
Abundance Estimates ◽  
Taxonomic Markers ◽  
Microbiome Data ◽  
Microbiome Data Analysis

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, including both parameteric and nonparametric methods. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests, partial least squares and linear models as well as nonparametric testing using community networks and the ggnetwork package.

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