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

Biomolecules ◽  
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.

scholarly journals Reversion of Gut Microbiota during the Recovery Phase in Patients with Asymptomatic or Mild COVID-19: Longitudinal Study

2021 ◽  
Vol 9 (6) ◽  
pp. 1237
Author(s):  
Han-Na Kim ◽  
Eun-Jeong Joo ◽  
Chil-Woo Lee ◽  
Kwang-Sung Ahn ◽  
Hyung-Lae Kim ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Gastrointestinal Symptoms ◽  
Amplicon Sequencing ◽  
Recovery Phase ◽  
Fecal Samples ◽  
Intestinal Microbes ◽  
Gut Dysbiosis ◽  
16S Rrna Amplicon Sequencing ◽  
Microbiome Data ◽  
Negative Conversion

Patients with COVID-19 have been reported to experience gastrointestinal symptoms as well as respiratory symptoms, but the effects of COVID-19 on the gut microbiota are poorly understood. We explored gut microbiome profiles associated with the respiratory infection of SARS-CoV-2 during the recovery phase in patients with asymptomatic or mild COVID-19. A longitudinal analysis was performed using the same patients to determine whether the gut microbiota changed after recovery from COVID-19. We applied 16S rRNA amplicon sequencing to analyze two paired fecal samples from 12 patients with asymptomatic or mild COVID-19. Fecal samples were selected at two time points: during SARS-CoV-2 infection (infected state) and after negative conversion of the viral RNA (recovered state). We also compared the microbiome data with those from 36 healthy controls. Microbial evenness of the recovered state was significantly increased compared with the infected state. SARS-CoV-2 infection induced the depletion of Bacteroidetes, while an abundance was observed with a tendency to rapidly reverse in the recovered state. The Firmicutes/Bacteroidetes ratio in the infected state was markedly higher than that in the recovered state. Gut dysbiosis was observed after infection even in patients with asymptomatic or mild COVID-19, while the composition of the gut microbiota was recovered after negative conversion of SARS-CoV-2 RNA. Modifying intestinal microbes in response to COVID-19 might be a useful therapeutic alternative.

scholarly journals The Effect of Lactobacillus plantarum BW2013 on The Gut Microbiota in Mice Analyzed by 16S rRNA Amplicon Sequencing

2021 ◽  
Vol 70 (2) ◽  
pp. 235-243
Author(s):  
TONG TONG ◽  
XIAOHUI NIU ◽  
QIAN LI ◽  
YUXI LING ◽  
ZUMING LI ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
Dose Group ◽  
Low Dose ◽  
Amplicon Sequencing ◽  
Control Group ◽  
High Dose ◽  
Treatment Groups ◽  
16S Rrna Amplicon Sequencing ◽  
Medium Dose

Lactobacillus plantarum BW2013 was isolated from the fermented Chinese cabbage. This study aimed to test the effect of this strain on the gut microbiota in BALB/c mice by 16S rRNA amplicon sequencing. The mice were randomly allocated to the control group and three treatment groups of L. plantarum BW2013 (a low-dose group of 108 CFU/ml, a medium-dose group of 109 CFU/ml, and a high-dose group of 1010 CFU/ml). The weight of mice was recorded once a week, and the fecal samples were collected for 16S rRNA amplicon sequencing after 28 days of continuous treatment. Compared with the control group, the body weight gain in the treatment groups was not significant. The 16S rRNA amplicon sequencing analysis showed that both the Chao1 and ACE indexes increased slightly in the medium-dose group compared to the control group, but the difference was not significant. Based on PCoA results, there was no significant difference in β diversity between the treatment groups. Compared to the control group, the abundance of Bacteroidetes increased in the low-dose group. The abundance of Firmicutes increased in the medium-dose group. At the genus level, the abundance of Alloprevotella increased in the low-dose group compared to the control group. The increased abundance of Ruminococcaceae and decreased abundance of Candidatus_Saccharimonas was observed in the medium-dose group. Additionally, the abundance of Bacteroides increased, and Alistipes and Candidatus_Saccharimonas decreased in the high-dose group. These results indicated that L. plantarum BW2013 could ameliorate gut microbiota composition, but its effects vary with the dose.

scholarly journals Inference based PICRUSt accuracy varies across sample types and functional categories

2019 ◽  
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.

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

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.

scholarly journals On the robustness of inference of association with the gut microbiota in stool, swab and mucosal tissue samples

2021 ◽  
Author(s):  
Shan Sun ◽  
Xiangzhu Zhu ◽  
Xiang Huang ◽  
Harvey J. Murff ◽  
Reid M. Ness ◽  
...  
Keyword(s):  
Microbial Community ◽  
Gut Microbiota ◽  
Community Composition ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Taxonomic Composition ◽  
Mucosal Tissue ◽  
Tissue Samples ◽  
16S Rrna Amplicon Sequencing ◽  
Functional Profiles

AbstractThe gut microbiota plays an important role in human health and disease. Stool, swab and mucosal tissue samples have been used in individual studies to survey the microbial community but the consequences of using these different sample types are not completely understood. We previously reported differences in microbial community composition with 16S rRNA amplicon sequencing between stool, swab and mucosal tissue samples. Here, we extended the previous study to a larger cohort and performed shotgun metagenome sequencing of 1,397 stool, swab and mucosal tissue samples from 240 participants. Consistent with previous results, taxonomic composition of stool and swab samples was distinct, but still more similar to each other than mucosal tissue samples, which had a substantially different community composition, characterized by a high relative abundance of the mucus metabolizers Bacteroides and Subdoligranulum, as well as bacteria with higher tolerance for oxidative stress such as Escherichia. As has been previously reported, functional profiles were more uniform across sample types than taxonomic profiles with differences between stool and swab samples smaller, but mucosal tissue samples remained distinct from the other two types. When the taxonomic and functional profiles of different sample types were used for inference in association with host phenotypes of age, sex, body mass index (BMI), antibiotics or non-steroidal anti-inflammatory drugs (NSAIDs) use, hypothesis testing using either stool or swab gave broadly similar results, but inference performed on mucosal tissue samples gave results that were generally less consistent with either stool or swab. Our study represents an important resource for the experimental design of studies aimed to understand microbiota perturbations specific to defined micro niches within the human intestinal tract.

scholarly journals Utility of a portable desiccant system for preservation of fecal samples for downstream 16S rRNA amplicon sequencing

2018 ◽  
Vol 146 ◽  
pp. 1-6 ◽  
Author(s):  
Philip J. Johnson ◽  
Leeza L. Hargreaves ◽  
Chelsea N. Zobrist ◽  
Aaron C. Ericsson
Keyword(s):  
16S Rrna ◽  
Amplicon Sequencing ◽  
Fecal Samples ◽  
16S Rrna Amplicon Sequencing

scholarly journals Efficacy of fecal sampling as a gut proxy in the study of chicken gut microbiota

2018 ◽  
Author(s):  
Wei Yan ◽  
Jiangxia Zheng ◽  
Chaoliang Wen ◽  
Congliang Ji ◽  
Dexiang Zhang ◽  
...  
Keyword(s):  
Small Intestine ◽  
Community Structure ◽  
Microbial Community ◽  
Gut Microbiota ◽  
Amplicon Sequencing ◽  
Fecal Microbiota ◽  
Fecal Samples ◽  
Community Membership ◽  
16S Rrna Amplicon Sequencing ◽  
Fecal Sampling

AbstractBackgroundDespite the convenience and noninvasiveness of fecal sampling, the fecal microbiota does not fully represent that of the gastrointestinal (GI) tract, and the efficacy of fecal sampling to accurately represent the gut microbiota in birds is poorly understood. In this study, we aim to identify the efficacy of feces as a gut proxy in birds using chickens as a model. We collected 1,026 samples from 206 chickens, including duodenum, jejunum, ileum, cecum and feces samples, for 16S rRNA amplicon sequencing analyses.ResultsIn this study, the efficacy of feces as a gut proxy was partitioned to microbial community membership and community structure. Most taxa in the small intestine (84.11 – 87.28%) and ceca (99.39%) could be identified in feces. Microbial community membership was reflected with a gut anatomic feature, but community structure was not. Excluding shared microbes, the small intestine and ceca contributed 34.12 and 5.83% of the total fecal members, respectively. The composition of Firmicutes members in the small intestine and that of Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria members in the ceca could be well mirrored by the observations in fecal samples (ρ = 0.54 – 0.71 and 0.71 – 0.78, respectively, P < 0.001). However, there were few significant correlations for each genus between feces and each of the 4 gut segments, and these correlations were not high (ρ = −0.2 – 0.4, P < 0.05) for most genera.ConclusionsOur results provide evidence that the good potential of feces to identify most taxa in chicken guts, but it should be interpreted with caution by using feces as a proxy for gut in microbial structure analyses. This work provides insights and future directions regarding the usage of fecal samples in studies of the gut microbiome.

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

Nutrients ◽  
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.

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

2021 ◽  
Vol 12 (1) ◽  
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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