Comparative analysis of chicken cecal microbial diversity and taxonomic composition in response to dietary variation using 16S rRNA amplicon sequencing

AbstractAbundance is a key parameter in microbial ecology, and important to estimates of potential metabolite flux, impacts of dispersal, and sensitivity of samples to technical biases such as laboratory contamination. However, modern amplicon-based sequencing techniques by themselves typically provide no information about the absolute abundance of microbes. Here, we use fluorescence microscopy and quantitative PCR as independent estimates of microbial abundance to test the hypothesis that microbial symbionts have enabled ants to dominate tropical rainforest canopies by facilitating herbivorous diets, and compare these methods to microbial diversity profiles from 16S rRNA amplicon sequencing. Through a systematic survey of ants from a lowland tropical forest, we show that the density of gut microbiota varies across several orders of magnitude among ant lineages, with median individuals from many genera only marginally above detection limits. Supporting the hypothesis that microbial symbiosis is important to dominance in the canopy, we find that the abundance of gut bacteria is positively correlated with stable isotope proxies of herbivory among canopy-dwelling ants, but not among ground-dwelling ants. Notably, these broad findings are much more evident in the quantitative data than in the 16S rRNA sequencing data. Our results help to resolve a longstanding question in tropical rainforest ecology, and have broad implications for the interpretation of sequence-based surveys of microbial diversity.

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Inference based PICRUSt accuracy varies across sample types and functional categories

10.1101/655746 ◽

2019 ◽

Cited By ~ 3

Author(s):

Shan Sun ◽

Roshonda B. Jones ◽

Anthony A. Fodor

Keyword(s):

16S Rrna ◽

Gene Prediction ◽

Amplicon Sequencing ◽

Taxonomic Composition ◽

Inference Models ◽

16S Rrna Amplicon Sequencing ◽

Gene Profiles ◽

Metagenome Sequencing ◽

The Cost ◽

Functional Profiles

AbstractBackgroundDespite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition, and PICRUSt is the most widely used of these techniques. In this study, we evaluated the performance of PICRUSt by comparing the significance of the differential abundance of functional gene profiles predicted with PICRUSt to those from shotgun metagenome sequencing across different environments.ResultsWe selected 7 datasets of human, non-human animal and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between gene compositions predicted with PICRUSt and measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the sample labels were shuffled. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of algorithms like PICRUSt. As an alternative, we compared the performance of PICRUSt predicted genes to metagenome genes in inference models associated with metadata within each dataset. With this method, we found reasonable performance for human datasets, with PICRUSt performing better for inference on genes related to “house-keeping” functions. However, the performance of PICRUSt degraded sharply outside of human datasets when used for inference.ConclusionWe conclude that the utility of PICRUSt for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted.

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Identification of the microbial diversity after fecal microbiota transplantation therapy for chronic intractable constipation using 16s rRNA amplicon sequencing

PLoS ONE ◽

10.1371/journal.pone.0214085 ◽

2019 ◽

Vol 14 (3) ◽

pp. e0214085 ◽

Cited By ~ 8

Author(s):

Tadashi Ohara

Keyword(s):

16S Rrna ◽

Microbial Diversity ◽

Fecal Microbiota Transplantation ◽

Amplicon Sequencing ◽

Fecal Microbiota ◽

Intractable Constipation ◽

16S Rrna Amplicon Sequencing ◽

Transplantation Therapy

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Comparative Analysis of Chicken Cecal Microbial Diversity and Taxonomic Composition in Response to Dietary Variation using 16S rRNA Amplicon Sequencing

10.21203/rs.3.rs-201124/v1 ◽

2021 ◽

Author(s):

Zubia Rashid ◽

Muhammad Zubair Yousaf ◽

Syed Muddassar Hussain Gilani ◽

Sitwat Zehra ◽

Ashaq Ali ◽

...

Keyword(s):

Microbial Community ◽

16S Rrna ◽

Organic Acids ◽

Microbial Diversity ◽

Relative Abundance ◽

Microbial Community Composition ◽

Amplicon Sequencing ◽

Feed Additives ◽

Poultry Feed ◽

16S Rrna Amplicon Sequencing

Abstract Antibiotic resistance poses a serious threat to human and animal health. As a consequence, their use in conventional poultry feed may be replaced by non-antibiotic additives (alternatives to antibiotics, ATAs). Phytogenic feed additives and organic acids have been gaining considerable attention that could abate the proliferation of pathogenic bacteria and strengthen gut function in broiler chickens. The aim of this study was to evaluate the effects of phytogenic feed additives and organic acids on cecal microbial diversity using 16S rRNA amplicon sequencing of the V3-V4 region. In this study, 240 chicks were divided into five treatments comprising: a controlled basal diet (CON), antibiotic group (AB), phytogenic feed additives (PHY), organic acids (ORG) and a combination of PHY + ORG (COM). A distinctive microbial community structure was observed amongst different treatments with an increased microbial diversity in AB, ORG and COM (p < 0.05). The synergistic effects of PHY and ORG increased the population of beneficial bacteria that belonged to the phyla: Firmicutes, Bacteroides and Proteobacteria in the cecum. The presence of the species Akkermansia muciniphila (involved in mucin degradation) and Bacillus safensis (a probiotic bacterium) were noticed in COM and PHY, respectively. Clustering analysis revealed a higher relative abundance of similar microbial community composition between AB and ORG groups. In conclusion, treatments with PHY and ORG modified the relative abundance and presence/absence of specific microbiota in the chicken cecum. Hence, cecal microbiota modulation through diet is a promising strategy to reduce cross-contamination of zoonotic poultry pathogens.

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Inference based accuracy of metagenome prediction tools varies across sample types and functional categories

10.21203/rs.2.20233/v1 ◽

2020 ◽

Author(s):

Shan Sun ◽

Roshonda B. Jones ◽

Anthony A. Fodor

Keyword(s):

16S Rrna ◽

Gene Prediction ◽

Amplicon Sequencing ◽

Taxonomic Composition ◽

Inference Models ◽

Prediction Tools ◽

16S Rrna Amplicon Sequencing ◽

Metagenome Sequencing ◽

The Cost ◽

Functional Profiles

Abstract Background: Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition. In this study, we evaluated the performance of three commonly used metagenome prediction tools (PICRUSt, PICRUSt2 and Tax4Fun) by comparing the significance of the differential abundance of predicted functional gene profiles to those from shotgun metagenome sequencing across different environments. Results: We selected 7 datasets of human, non-human animal and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between predicted gene compositions and gene relative abundance measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the abundance of genes were permuted across samples. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of metagenome prediction tools. As an alternative, we compared the performance of genes predicted with PICRUSt, PICRUSt2 and Tax4Fun to sequenced metagenome genes in inference models associated with metadata within each dataset. With this approach, we found reasonable performance for human datasets, with the metagenome prediction tools performing better for inference on genes related to “house-keeping” functions. However, their performance degraded sharply outside of human datasets when used for inference. Conclusion: We conclude that the utility of PICRUSt, PICRUSt2 and Tax4Fun for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted.

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Multiomic Approach to Analyze Infant Gut Microbiota: Experimental and Analytical Method Optimization

Biomolecules ◽

10.3390/biom11070999 ◽

2021 ◽

Vol 11 (7) ◽

pp. 999

Author(s):

Helena Torrell ◽

Adrià Cereto-Massagué ◽

Polina Kazakova ◽

Lorena García ◽

Héctor Palacios ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

Variable Region ◽

Amplicon Sequencing ◽

Taxonomic Composition ◽

Intestinal Microbiome ◽

Fecal Samples ◽

16S Rrna Amplicon Sequencing ◽

Method Optimization ◽

Feature Selection Approach

Background: The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples. Methods: Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis. Results: The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile. Conclusion: A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.

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Bacterial Diversity of Breast Milk in Healthy Spanish Women: Evolution from Birth to Five Years Postpartum

Nutrients ◽

10.3390/nu13072414 ◽

2021 ◽

Vol 13 (7) ◽

pp. 2414

Author(s):

Laura Sanjulián ◽

Alexandre Lamas ◽

Rocío Barreiro ◽

Alberto Cepeda ◽

Cristina A. Fente ◽

...

Keyword(s):

Breast Milk ◽

16S Rrna ◽

Human Milk ◽

Alpha Diversity ◽

Amplicon Sequencing ◽

Maternal Body Mass Index ◽

16S Rrna Amplicon Sequencing ◽

Spanish Women ◽

Calcium Magnesium ◽

Abundant Genus

The objective of this work was to characterize the microbiota of breast milk in healthy Spanish mothers and to investigate the effects of lactation time on its diversity. A total of ninety-nine human milk samples were collected from healthy Spanish women and were assessed by means of next-generation sequencing of 16S rRNA amplicons and by qPCR. Firmicutes was the most abundant phylum, followed by Bacteroidetes, Actinobacteria, and Proteobacteria. Accordingly, Streptococcus was the most abundant genus. Lactation time showed a strong influence in milk microbiota, positively correlating with Actinobacteria and Bacteroidetes, while Firmicutes was relatively constant over lactation. 16S rRNA amplicon sequencing showed that the highest alpha-diversity was found in samples of prolonged lactation, along with wider differences between individuals. As for milk nutrients, calcium, magnesium, and selenium levels were potentially associated with Streptococcus and Staphylococcus abundance. Additionally, Proteobacteria was positively correlated with docosahexaenoic acid (DHA) levels in breast milk, and Staphylococcus with conjugated linoleic acid. Conversely, Streptococcus and trans-palmitoleic acid showed a negative association. Other factors such as maternal body mass index or diet also showed an influence on the structure of these microbial communities. Overall, human milk in Spanish mothers appeared to be a complex niche shaped by host factors and by its own nutrients, increasing in diversity over time.

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Connecting structure to function with the recovery of over 1000 high-quality metagenome-assembled genomes from activated sludge using long-read sequencing

Nature Communications ◽

10.1038/s41467-021-22203-2 ◽

2021 ◽

Vol 12 (1) ◽

Cited By ~ 2

Author(s):

Caitlin M. Singleton ◽

Francesca Petriglieri ◽

Jannie M. Kristensen ◽

Rasmus H. Kirkegaard ◽

Thomas Y. Michaelsen ◽

...

Keyword(s):

16S Rrna ◽

Wastewater Treatment Plants ◽

In Situ Hybridisation ◽

Amplicon Sequencing ◽

Rrna Genes ◽

Fluorescence In Situ Hybridisation ◽

Sequencing Data ◽

High Quality ◽

16S Rrna Amplicon Sequencing ◽

Long Read

AbstractMicroorganisms play crucial roles in water recycling, pollution removal and resource recovery in the wastewater industry. The structure of these microbial communities is increasingly understood based on 16S rRNA amplicon sequencing data. However, such data cannot be linked to functional potential in the absence of high-quality metagenome-assembled genomes (MAGs) for nearly all species. Here, we use long-read and short-read sequencing to recover 1083 high-quality MAGs, including 57 closed circular genomes, from 23 Danish full-scale wastewater treatment plants. The MAGs account for ~30% of the community based on relative abundance, and meet the stringent MIMAG high-quality draft requirements including full-length rRNA genes. We use the information provided by these MAGs in combination with >13 years of 16S rRNA amplicon sequencing data, as well as Raman microspectroscopy and fluorescence in situ hybridisation, to uncover abundant undescribed lineages belonging to important functional groups.

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