scholarly journals Ecosystem distribution profiling of bacteria from a unique hypersaline sediment (sabkha) reveals ecological specialization among communities in the environment

2017 ◽  
Author(s):  
Abdul-Matiin Wan ◽  
Antonio M. Martin-Platero ◽  
Areej Alsheikh-Hussain ◽  
Syafiq Kamarul Azman ◽  
Lina F. Yousef ◽  
...  
Keyword(s):  
Probability Distributions ◽  
Extreme Environments ◽  
Alpha Diversity ◽  
Ribosomal Gene ◽  
Ecological Specialization ◽  
Operational Taxonomic Units ◽  
Sequencing Technologies ◽  
Mangrove Soil ◽  
Coastal Sabkha ◽  
Bacterial Assemblages

Advances in genomic sequencing technologies resulted in massive microbial diversity data (16S ribosomal gene sequences, rDNA) being generated in every possible environment. However, the majority of microorganisms have never been cultured, and therefore, nor cataloged. This poses a problem for molecular microbial ecologists because a large portion of the marker sequences can not be taxonomically resolved past the phylum taxon level. This tells very little about who or what these microorganisms are doing in relation to their environment. Our study describes an approach to assist in drawing ecological information from a sample when the taxon resolution is poor. We generated 16S rDNA libraries from a hypersaline marine sediment (coastal Sabkha) and saline mangrove soil in Abu Dhabi and then compared the compositional features to a database of 20,470 publicly available microbial community profiles (comprising the entire Earth Microbiome Project, EMP) that were annotated with terms from the Environmental Ontology (EnvO). An accurate taxonomic classification was not possible for 80% of the Sabkha operational taxonomic units (OTUs) beyond phylum level with widely used taxonomy classification tools, but habitat profiling performed on the community revealed strong links to bacterial assemblages of soil and marine origins. To capture the notion of generalist vs. specialist formally, we developed an algorithm to derive empirical probability distributions of OTUs over ecosystems from observed occurrences in the sample database, which then give rise to OTU-specific ecosystem entropies. We observed very low average ecosystem entropy of the Sabkha in contrast to other environmental samples. Based on this concept, the Sabkha community, while of midrange alpha diversity, presented largely specialist characteristics, with most OTUs identified to be unique to the Sabkha habitat. This finding is further corroborated by the observation that the Sabkha sample is unique with respect to the EMP-derived dataset (which contains 74 hypersaline and thousands of marine samples), as a comprehensive UniFrac similarity search did not yield any significant matches. Finally, we show that the ecosystem entropy formalism, which intrinsically accounts for the ability of OTUs to cross ecosystem borders according to a context database, is a novel, informative tool to describe and identify extreme environments in addition to conventional ecological diversity measures.

scholarly journals Ecosystem distribution profiling of bacteria from a unique hypersaline sediment (sabkha) reveals ecological specialization among communities in the environment

2017 ◽  
Author(s):  
Abdul-Matiin Wan ◽  
Antonio M. Martin-Platero ◽  
Areej Alsheikh-Hussain ◽  
Syafiq Kamarul Azman ◽  
Lina F. Yousef ◽  
...  
Keyword(s):  
Probability Distributions ◽  
Extreme Environments ◽  
Alpha Diversity ◽  
Ribosomal Gene ◽  
Ecological Specialization ◽  
Operational Taxonomic Units ◽  
Sequencing Technologies ◽  
Mangrove Soil ◽  
Coastal Sabkha ◽  
Bacterial Assemblages

Advances in genomic sequencing technologies resulted in massive microbial diversity data (16S ribosomal gene sequences, rDNA) being generated in every possible environment. However, the majority of microorganisms have never been cultured, and therefore, nor cataloged. This poses a problem for molecular microbial ecologists because a large portion of the marker sequences can not be taxonomically resolved past the phylum taxon level. This tells very little about who or what these microorganisms are doing in relation to their environment. Our study describes an approach to assist in drawing ecological information from a sample when the taxon resolution is poor. We generated 16S rDNA libraries from a hypersaline marine sediment (coastal Sabkha) and saline mangrove soil in Abu Dhabi and then compared the compositional features to a database of 20,470 publicly available microbial community profiles (comprising the entire Earth Microbiome Project, EMP) that were annotated with terms from the Environmental Ontology (EnvO). An accurate taxonomic classification was not possible for 80% of the Sabkha operational taxonomic units (OTUs) beyond phylum level with widely used taxonomy classification tools, but habitat profiling performed on the community revealed strong links to bacterial assemblages of soil and marine origins. To capture the notion of generalist vs. specialist formally, we developed an algorithm to derive empirical probability distributions of OTUs over ecosystems from observed occurrences in the sample database, which then give rise to OTU-specific ecosystem entropies. We observed very low average ecosystem entropy of the Sabkha in contrast to other environmental samples. Based on this concept, the Sabkha community, while of midrange alpha diversity, presented largely specialist characteristics, with most OTUs identified to be unique to the Sabkha habitat. This finding is further corroborated by the observation that the Sabkha sample is unique with respect to the EMP-derived dataset (which contains 74 hypersaline and thousands of marine samples), as a comprehensive UniFrac similarity search did not yield any significant matches. Finally, we show that the ecosystem entropy formalism, which intrinsically accounts for the ability of OTUs to cross ecosystem borders according to a context database, is a novel, informative tool to describe and identify extreme environments in addition to conventional ecological diversity measures.

scholarly journals The Effects of Genetic Relatedness on the Preterm Infant Gut Microbiota

2021 ◽  
Vol 9 (2) ◽  
pp. 278
Author(s):  
Shen Jean Lim ◽  
Miriam Aguilar-Lopez ◽  
Christine Wetzel ◽  
Samia V. O. Dutra ◽  
Vanessa Bray ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Preterm Infant ◽  
Neonatal Intensive Care ◽  
Genetic Relatedness ◽  
Bovine Milk ◽  
Alpha Diversity ◽  
Neonatal Intensive Care Units ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Operational Taxonomic Units

The preterm infant gut microbiota is influenced by environmental, endogenous, maternal, and genetic factors. Although siblings share similar gut microbial composition, it is not known how genetic relatedness affects alpha diversity and specific taxa abundances in preterm infants. We analyzed the 16S rRNA gene content of stool samples, ≤ and >3 weeks postnatal age, and clinical data from preterm multiplets and singletons at two Neonatal Intensive Care Units (NICUs), Tampa General Hospital (TGH; FL, USA) and Carle Hospital (IL, USA). Weeks on bovine milk-based fortifier (BMF) and weight gain velocity were significant predictors of alpha diversity. Alpha diversity between siblings were significantly correlated, particularly at ≤3 weeks postnatal age and in the TGH NICU, after controlling for clinical factors. Siblings shared higher gut microbial composition similarity compared to unrelated individuals. After residualizing against clinical covariates, 30 common operational taxonomic units were correlated between siblings across time points. These belonged to the bacterial classes Actinobacteria, Bacilli, Bacteroidia, Clostridia, Erysipelotrichia, and Negativicutes. Besides the influence of BMF and weight variables on the gut microbial diversity, our study identified gut microbial similarities between siblings that suggest genetic or shared maternal and environmental effects on the preterm infant gut microbiota.

Update of use of dietary indices to control for diet in human gut microbiota studies

2020 ◽  
Author(s):  
Ruth Bowyer ◽  
Nitin Shivappa ◽  
Philippa M Wells ◽  
Tim D Spector ◽  
Ailsa A Welch ◽  
...  
Keyword(s):  
Inflammatory Disease ◽  
Association Studies ◽  
Alpha Diversity ◽  
Initial Study ◽  
Healthy Eating Index ◽  
Operational Taxonomic Units ◽  
Using Data ◽  
Study Designs ◽  
Dietary Indices

Abstract Background In our recent publication (DOI: https://doi.org/10.1186/s40168-018-0455-y ) we concluded that of the three dietary indices we studied the Healthy Eating Index (HEI) was the index of choice where researchers wish to account for the role of diet in microbiome association studies. Following correspondence from its creators, we replicated our initial study with an additional index, the Dietary inflammation index (DII ® ) using an updated data analysis pipeline for microbiota comparisons that incorporate the use of Amplicon Sequence Variants (ASVs) rather than the previously utilised Operational Taxonomic Units (OTUs). The energy-adjusted DII (E-DII) reflects the inflammatory potential of an individual’s diet, after controlling for total energy intake, which is of interest given the known association between the microbiota and inflammatory disease. Results Using data from 5047 participants of the TwinsUK cohort, we observed the E-DII to be a valid dietary measure within this cohort. The E-DII had a stronger association with frailty, a measure of health deficit, than the HEI (E-DII: β = 0.12, p < 0.001; HEI: β = −0.09, p < 0.001) But not with BMI (E-DII: β = 0.04, p <0.01, HEI: β = −0.07, p <0.001). In a subset of individuals (n = 1853) with existing microbiota data, the E-DII had a stronger association with measures of microbiota species (alpha) diversity; the HEI had a higher number of associations with differences of taxa abundance. Of interest are the differences where the two indexes do not overlap). For example, the genus with the strongest association with the E-DII but not significantly associated with the HEI was assigned as Escherichia/Shigella (logFC=0.692, q<0.001). Both indexes were associated with PCoAs of weighted UniFrac distances. Conclusion Both the E-DII and HEI are strong candidates for use as covariates in microbiota association studies where measures of the microbiota are captured using ASVs. The E-DII is an interesting alternative to the HEI particularly where study designs are looking to assess causality of the microbiota in driving inflammation and inflammatory disease.

scholarly journals Comparative analysis and characterization of the gut microbiota of four farmed snakes from southern China

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6658 ◽  
Author(s):  
Bing Zhang ◽  
Jing Ren ◽  
Daode Yang ◽  
Shuoran Liu ◽  
Xinguo Gong
Keyword(s):  
Gut Microbiota ◽  
Host Species ◽  
High Throughput Sequencing ◽  
Southern China ◽  
Alpha Diversity ◽  
Operational Taxonomic Units ◽  
Close Relationship ◽  
Elaphe Carinata ◽  
Deinagkistrodon Acutus

Background The gut microbiota plays an important role in host immunity and metabolic homeostasis. Although analyses of gut microbiotas have been used to assess host health and foster disease prevention and treatment, no comparative comprehensive study, assessing gut microbiotas among several species of farmed snake, is yet available. In this study, we characterized and compared the gut microbiotas of four species of farmed snakes (Naja atra, Ptyas mucosa, Elaphe carinata, and Deinagkistrodon acutus) using high-throughput sequencing of the 16S rDNA gene in southern China and tested whether there was a relationship between gut microbiotal composition and host species. Results A total of 629 operational taxonomic units across 22 samples were detected. The five most abundant phyla were Bacteroidetes, Proteobacteria, Firmicutes, Fusobacteria, and Actinobacteria, while the five most abundant genera were Bacteroides, Cetobacterium, Clostridium, Plesiomonas, and Paeniclostridium. This was the first report of the dominance of Fusobacteria and Cetobacterium in the snake gut. Our phylogenetic analysis recovered a relatively close relationship between Fusobacteria and Bacteroidetes. Alpha diversity analysis indicated that species richness and diversity were highest in the gut microbiota of D. acutus and lowest in that of E. carinata. Significant differences in alpha diversity were detected among the four farmed snake species. The gut microbiotas of conspecifics were more similar to each other than to those of heterospecifics. Conclusion This study provides the first comparative study of gut microbiotas among several species of farmed snakes, and provides valuable data for the management of farmed snakes. In farmed snakes, host species affected the species composition and diversity of the gut microbiota.

scholarly journals Meta-Analysis of Microbial Communities in Hot Springs: Recurrent Taxa and Complex Shaping Factors beyond pH and Temperature

2020 ◽  
Vol 8 (6) ◽  
pp. 906 ◽  
Author(s):  
Francisco L. Massello ◽  
Chia Sing Chan ◽  
Kok-Gan Chan ◽  
Kian Mau Goh ◽  
Edgardo Donati ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Metabolic Profile ◽  
Hot Springs ◽  
Meta Analysis ◽  
Extreme Environments ◽  
Alpha Diversity ◽  
Amplicon Sequencing ◽  
Phylogenetic Distance ◽  
Microbial Profile ◽  
The World

The study of microbial communities from extreme environments is a fascinating topic. With every study, biologists and ecologists reveal interesting facts and questions that dispel the old belief that these are inhospitable environments. In this work, we assess the microbial diversity of three hot springs from Neuquén, Argentina, using high-throughput amplicon sequencing. We predicted a distinct metabolic profile in the acidic and the circumneutral samples, with the first ones being dominated by chemolithotrophs and the second ones by chemoheterotrophs. Then, we collected data of the microbial communities of hot springs around the world in an effort to comprehend the roles of pH and temperature as shaping factors. Interestingly, there was a covariation between both parameters and the phylogenetic distance between communities; however, neither of them could explain much of the microbial profile in an ordination model. Moreover, there was no correlation between alpha diversity and these parameters. Therefore, the microbial communities’ profile seemed to have complex shaping factors beyond pH and temperature. Lastly, we looked for taxa associated with different environmental conditions. Several such taxa were found. For example, Hydrogenobaculum was frequently present in acidic springs, as was the Sulfolobaceae family; on the other hand, Candidatus Hydrothermae phylum was strongly associated with circumneutral conditions. Interestingly, some singularities related to sites featuring certain taxa were also observed.

scholarly journals Metabarcoding Analyses of Gut Microbiota of Nile Tilapia (Oreochromis niloticus) from Lake Awassa and Lake Chamo, Ethiopia

2020 ◽  
Vol 8 (7) ◽  
pp. 1040
Author(s):  
Negash Kabtimer Bereded ◽  
Manuel Curto ◽  
Konrad J. Domig ◽  
Getachew Beneberu Abebe ◽  
Solomon Workneh Fanta ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Oreochromis Niloticus ◽  
Nile Tilapia ◽  
Large Scale ◽  
Alpha Diversity ◽  
Illumina Miseq ◽  
Operational Taxonomic Units ◽  
Nile Tilapia Oreochromis Niloticus ◽  
Miseq Platform ◽  
Ethiopian Lakes

The Nile tilapia (Oreochromis niloticus) gut harbors a diverse microbial community; however, their variation across gut regions, lumen and mucosa is not fully elucidated. In this study, gut microbiota of all samples across gut regions and sample types (luminal content and mucosa) were analyzed and compared from two Ethiopian lakes. Microbiota were characterized using 16S rRNA Illumina MiSeq platform sequencing. A total of 2061 operational taxonomic units (OTUs) were obtained and the results indicated that Nile tilapia from Lake Chamo harbored a much more diversified gut microbiota than Lake Awassa. In addition, the gut microbiota diversity varied significantly across the gut region based on the Chao1, Shannon and Simpson index. The microbiome analyses of all samples in the midgut region showed significantly higher values for alpha diversity (Chao 1, Shannon and Simpson). Beta diversity analysis revealed a clear separation of samples according to sampling areas and gut regions. The most abundant genera were Clostridium_sensu_stricto and Clostridium_XI genera across all samples. Between the two sampling lakes, two phyla, Phylum Fusobacteria and Cyanobacteria, were found to be significantly different. On the other hand, six phyla (Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Proteobacteria and Cyanobacteria) were significantly different across gut regions. In this study, we found that all samples shared a large core microbiota, comprising a relatively large number of OTUs, which was dominated by Proteobacteria, Firmicutes, Cyanobacteria, Fusobacteria and Actinobacteria. This study has established the bases for future large-scale investigations of gut microbiota of fishes in Ethiopian lakes.

scholarly journals Exploring Eimeria Genomes to Understand Population Biology: Recent Progress and Future Opportunities

Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1103
Author(s):  
Damer P. Blake ◽  
Kate Worthing ◽  
Mark C. Jenkins
Keyword(s):  
Population Biology ◽  
Production Control ◽  
Current Knowledge ◽  
Eimeria Species ◽  
Vast Number ◽  
Profit Margins ◽  
Operational Taxonomic Units ◽  
Sequencing Technologies ◽  
Live Parasite ◽  
Review Current

Eimeria, protozoan parasites from the phylum Apicomplexa, can cause the enteric disease coccidiosis in all farmed animals. Coccidiosis is commonly considered to be most significant in poultry; due in part to the vast number of chickens produced in the World each year, their short generation time, and the narrow profit margins associated with their production. Control of Eimeria has long been dominated by routine chemoprophylaxis, but has been supplemented or replaced by live parasite vaccination in a minority of production sectors. However, public and legislative demands for reduced drug use in food production is now driving dramatic change, replacing reliance on relatively indiscriminate anticoccidial drugs with vaccines that are Eimeria species-, and in some examples, strain-specific. Unfortunately, the consequences of deleterious selection on Eimeria population structure and genome evolution incurred by exposure to anticoccidial drugs or vaccines are unclear. Genome sequence assemblies were published in 2014 for all seven Eimeria species that infect chickens, stimulating the first population genetics studies for these economically important parasites. Here, we review current knowledge of eimerian genomes and highlight challenges posed by the discovery of new, genetically cryptic Eimeria operational taxonomic units (OTUs) circulating in chicken populations. As sequencing technologies evolve understanding of eimerian genomes will improve, with notable utility for studies of Eimeria biology, diversity and opportunities for control.

Molecular Analysis of Skin Bacterial Assemblages from Codfish and Pollock after Dry-Salted Fish Production

2015 ◽  
Vol 78 (5) ◽  
pp. 983-989 ◽  
Author(s):  
NATÁLIA PEGORARO ◽  
RICARDO CALADO ◽  
LETÍCIA N. DUARTE ◽  
SÓNIA C. MANCO ◽  
FERNANDO J. FERNANDES ◽  
...  
Keyword(s):  
Gadus Morhua ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Hazard Analysis ◽  
Accurate Identification ◽  
Salted Fish ◽  
Operational Taxonomic Units ◽  
Critical Control Points ◽  
Gadus Macrocephalus ◽  
Gradient Gel Electrophoresis ◽  
Bacterial Assemblages

Dry-salted codfish and pollock are commercially important food products with a relatively long shelf life. To date, bacterial assemblages present in these products that are relevant for food safety have been monitored using only classical molecular and/or cultivation methods. The present study employed a rapid and accurate identification method involving PCR with denaturing gradient gel electrophoresis and pyrosequencing to characterize the bacterial assemblages in the skin of three closely related fishes: Gadus morhua, Gadus macrocephalus, and Theragra chalcogramma. This methodology can be crucial for timely identification of food spoilage, hazard analysis, and monitoring of critical control points during food production. Although all specimens were processed in the same factory, there were significant compositional differences in their skin bacterial communities. In general, the bacterial community was dominated by gram-negative species of the Gammaproteobacteria. Pyrosequencing yielded 90, 69, and 245 operational taxonomic units associated with G. morhua, G. macrocephalus, and T. chalcogramma, respectively. The most dominant operational taxonomic units were assigned in order to Pseudomonas sp., Serratia marcescens, Salinisphaera sp., and Psychrobacter pulmonis. Spoilage and pathogenic bacterial groups were detected in all the studied salted gadoid samples.

scholarly journals DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity

2015 ◽  
Vol 112 (7) ◽  
pp. 2076-2081 ◽  
Author(s):  
Matthieu Leray ◽  
Nancy Knowlton
Keyword(s):  
Large Scale ◽  
Size Fraction ◽  
Taxonomic Composition ◽  
Oyster Reefs ◽  
Ecological Studies ◽  
Marine Life ◽  
Operational Taxonomic Units ◽  
Sequencing Technologies ◽  
Ground Truthing ◽  
Eukaryotic Organisms

Documenting the diversity of marine life is challenging because many species are cryptic, small, and rare, and belong to poorly known groups. New sequencing technologies, especially when combined with standardized sampling, promise to make comprehensive biodiversity assessments and monitoring feasible on a large scale. We used this approach to characterize patterns of diversity on oyster reefs across a range of geographic scales comprising a temperate location [Virginia (VA)] and a subtropical location [Florida (FL)]. Eukaryotic organisms that colonized multilayered settlement surfaces (autonomous reef monitoring structures) over a 6-mo period were identified by cytochrome c oxidase subunit I barcoding (>2-mm mobile organisms) and metabarcoding (sessile and smaller mobile organisms). In a total area of ∼15.64 m2 and volume of ∼0.09 m3, 2,179 operational taxonomic units (OTUs) were recorded from 983,056 sequences. However, only 10.9% could be matched to reference barcodes in public databases, with only 8.2% matching barcodes with both genus and species names. Taxonomic coverage was broad, particularly for animals (22 phyla recorded), but 35.6% of OTUs detected via metabarcoding could not be confidently assigned to a taxonomic group. The smallest size fraction (500 to 106 μm) was the most diverse (more than two-thirds of OTUs). There was little taxonomic overlap between VA and FL, and samples separated by ∼2 m were significantly more similar than samples separated by ∼100 m. Ground-truthing with independent assessments of taxonomic composition indicated that both presence–absence information and relative abundance information are captured by metabarcoding data, suggesting considerable potential for ecological studies and environmental monitoring.

scholarly journals Accuracy of microbial community diversity estimated by closed- and open-reference OTUs

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3889 ◽  
Author(s):  
Robert C. Edgar
Keyword(s):  
Ribosomal Rna ◽  
De Novo ◽  
Community Diversity ◽  
Reference Database ◽  
Mock Community ◽  
Variable Regions ◽  
Operational Taxonomic Units ◽  
Sequencing Technologies ◽  
Generation Sequencing ◽  
Mock Communities

Next-generation sequencing of 16S ribosomal RNA is widely used to survey microbial communities. Sequences are typically assigned to Operational Taxonomic Units (OTUs). Closed- and open-reference OTU assignment matches reads to a reference database at 97% identity (closed), then clusters unmatched reads using a de novo method (open). Implementations of these methods in the QIIME package were tested on several mock community datasets with 20 strains using different sequencing technologies and primers. Richness (number of reported OTUs) was often greatly exaggerated, with hundreds or thousands of OTUs generated on Illumina datasets. Between-sample diversity was also found to be highly exaggerated in many cases, with weighted Jaccard distances between identical mock samples often close to one, indicating very low similarity. Non-overlapping hyper-variable regions in 70% of species were assigned to different OTUs. On mock communities with Illumina V4 reads, 56% to 88% of predicted genus names were false positives. Biological inferences obtained using these methods are therefore not reliable.

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