scholarly journals Turnover in life strategies recapitulates microbial succession on synthetic marine particles

2021 ◽  
Author(s):  
Alberto Pascual-García ◽  
Julia Schwartzman ◽  
Tim N Enke ◽  
Arion Iffland-Stettner ◽  
Otto X Cordero ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Amplicon Sequencing ◽  
Trophic Chain ◽  
Microbial Succession ◽  
Ecological Processes ◽  
Shotgun Metagenomics ◽  
16S Rrna Amplicon Sequencing ◽  
Environmental Selection ◽  
Complex Matter ◽  
Uptake Of Nutrients

Particulate organic matter (POM) in the ocean sustains diverse communities of bacteria that mediate the remineralization of organic complex matter. However, the variability of these particles and of the environmental conditions surrounding them present a challenge to the study of the ecological processes shaping particle-associated communities and their function. In this work, we utilise data from experiments in which coastal water communities were grown on synthetic particles to ask which are the most important ecological drivers of their assembly and associated traits. Combining 16S rRNA amplicon sequencing with shotgun metagenomics, together with an analysis of the full genomes of a subset of isolated strains, we were able to identify two-to-three distinct community classes, corresponding to early vs. late colonizers. We show that these classes are shaped by environmental selection (early colonizers) and facilitation (late colonizers), and find distinctive traits associated with each class. While early colonizers have a larger proportion of genes related to uptake of nutrients, motility and environmental sensing with few pathways enriched for metabolism, late colonizers devote a higher proportion of genes for metabolism, comprising a wide array of different pathways including metabolism of carbohydrates, amino acids and xenobiotics We find evidence in selected metabolic pathways for the existence of a trophic-chain topology connecting both classes. The interpretation of these traits suggests a distinction between early and late colonizers analogous to other classifications found in the literature, and we discuss connections with the classical distinction between r- and K-strategists.

scholarly journals Alteration of Gut Microbiota After Antibiotic Exposure in Finishing Swine

2021 ◽  
Vol 12 ◽  
Author(s):  
Hee Eun Jo ◽  
Min-Sung Kwon ◽  
Tae Woong Whon ◽  
Doo Wan Kim ◽  
Misun Yun ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Metabolic Pathways ◽  
Amplicon Sequencing ◽  
Swine Industry ◽  
Commensal Microbiota ◽  
16S Rrna Amplicon Sequencing ◽  
Fiber Degradation ◽  
As Species ◽  
Diarrhea Incidence ◽  
Gut Microbial Community

Subclinical doses of antimicrobials are commonly used in the swine industry to control infectious diseases and growth performance. Accumulating evidence suggests that swine administered with antibiotics are susceptible to disease development due to disruption of the beneficial gut microbial community, which is associated with host immune regulation, nutrient digestion, and colonization resistance against pathogens. In this study, we found that finishing swine administered with lincomycin showed gut dysbiosis and increased diarrhea incidence compared with control swine. 16S rRNA amplicon sequencing was used to analyze the gut microbiota in finishing swine administered with lincomycin. The relative abundance of detrimental microbes, such as species of Clostridium, Aerococcus, Escherichia-Shigella, and Corynebacterium was increased in the feces of lincomycin-administered finishing swine, but that of bacteria associated with fiber degradation, such as species of Treponema, Succinivibrio, Fibrobacter, and Cellulosilyticum was decreased. Moreover, administration of lincomycin significantly increased the enrichment of metabolic pathways related to pathogenicity and deficiency of polysaccharide degradation. These results suggest that lincomycin treatment could cause severe disruption of the commensal microbiota in finishing swine.

scholarly journals Diversity and Succession of Microbiota during Fermentation of the Traditional Indian Food Idli

2019 ◽  
Vol 85 (13) ◽  
Author(s):  
Madhvi H. Mandhania ◽  
Dhiraj Paul ◽  
Mangesh V. Suryavanshi ◽  
Lokesh Sharma ◽  
Somak Chowdhury ◽  
...  
Keyword(s):  
Bacterial Diversity ◽  
Bacterial Population ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Antibiotic Sensitivity ◽  
Amplicon Sequencing ◽  
Microbial Succession ◽  
16S Rrna Amplicon Sequencing ◽  
Acid And Bile Tolerance ◽  
Indian Food ◽  
Culture Dependent

ABSTRACTIdli, a naturally fermented Indian food, is prepared from a mixture of rice and black gram (lentil). To understand its microbial community during fermentation, detailed analysis of the structural and functional dynamics of the idli microbiome was performed by culture-dependent and -independent approaches. The bacterial diversity and microbial succession were assessed at different times of fermentation by 16S rRNA amplicon sequencing. Results highlighted that most microbiota belonged to phylumFirmicutes(70%) andProteobacteria(22%). Denaturing gradient gel electrophoresis (DGGE) and quantitative PCR (qPCR) analysis confirmed the diversity and succession involved therein. A culture-dependent approach revealed that the microbially diverse populations were conserved across different geographical locations. The fermentation was primarily driven by lactic acid bacteria as they constitute 86% of the total bacterial population, and genusWeissellaemerged as the most important organism in fermentation. The natural microbiota of the grains mainly drives the fermentation, as surface sterilized grains did not show any fermentation. Growth kinetics of idli microbiota and physicochemical parameters corroborated the changes in microbial dynamics, acid production, and leavening occurring during fermentation. Using a metagenomic prediction tool, we found that the major metabolic activities of these microbial fermenters were augmented during the important phase of fermentation. The involvement of the heterofermentative hexose monophosphate (HMP) pathway in batter leavening was substantiated by radiolabeled carbon dioxide generated fromd-[1-14C]-glucose. Hydrolases degrading starch and phytins and the production of B vitamins were reported. Moreover, culturable isolates showing beneficial attributes, such as acid and bile tolerance, hydrophobicity, antibiotic sensitivity, and antimicrobial activity, suggest idli to be a potential dietary supplement.IMPORTANCEThis is a comprehensive analysis of idli fermentation employing modern molecular tools which provided valuable information about the bacterial diversity enabling its fermentation. The study has demonstrated the relationship between the bacterial population and its functional role in the process. The nature of idli fermentation was found to be more complex than other food fermentations due to the succession of the bacterial population. Further studies using metatranscriptomics and metabolomics may enhance the understanding of this complex fermentation process. Moreover, the presence of microorganisms with beneficial properties plausibly makes idli a suitable functional food.

scholarly journals mixMC: a multivariate statistical framework to gain insight into Microbial Communities

2016 ◽  
Author(s):  
Kim-Anh Le Cao ◽  
Mary-Ellen Costello ◽  
Vanessa Anne Lakis ◽  
Francois Bartolo ◽  
Xin-Yi Chua ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Biomarker Discovery ◽  
Amplicon Sequencing ◽  
Added Value ◽  
Statistical Tools ◽  
Multivariate Statistical ◽  
Shotgun Metagenomics ◽  
16S Rrna Amplicon Sequencing ◽  
Microbial Biomarkers ◽  
Culture Independent

Culture independent techniques, such as shotgun metagenomics and 16S rRNA amplicon sequencing have dramatically changed the way we can examine microbial communities. Recently, changes in microbial community structure and dynamics have been associated with a growing list of human diseases. The identification and comparison of bacteria driving those changes requires the development of sound statistical tools, especially if microbial biomarkers are to be used in a clinical setting. We present mixMC, a novel multivariate data analysis framework for metagenomic biomarker discovery. mixMC accounts for the compositional nature of 16S data and enables detection of subtle differences when high inter-subject variability is present due to microbial sampling performed repeatedly on the same subjects but in multiple habitats. Through data dimension reduction the multivariate methods provide insightful graphical visualisations to characterise each type of environment in a detailed manner. We applied mixMC to 16S microbiome studies focusing on multiple body sites in healthy individuals, compared our results with existing statistical tools and illustrated added value of using multivariate methodologies to fully characterise and compare microbial communities.

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 Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazutoshi Yoshitake ◽  
Gaku Kimura ◽  
Tomoko Sakami ◽  
Tsuyoshi Watanabe ◽  
Yukiko Taniuchi ◽  
...  
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Pacific Coast ◽  
Three Dimensional ◽  
Amplicon Sequencing ◽  
Metagenomic Data ◽  
Shotgun Metagenomics ◽  
Functional Features ◽  
Pacific Coast Of Japan ◽  
Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

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.

scholarly journals Reduced metagenome sequencing for strain-resolution taxonomic profiles

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Lars Snipen ◽  
Inga-Leena Angell ◽  
Torbjørn Rognes ◽  
Knut Rudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Good Alternative ◽  
Shotgun Sequencing ◽  
Least Square ◽  
Full Potential ◽  
Shotgun Metagenomics ◽  
Metagenome Sequencing ◽  
Reference Genomes

Abstract Background Studies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction-associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or not explore the full potential of RMS data. Results We suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock community datasets show the potential to clearly separate strains even when the 16S is 100% identical, and genome-wide differences is < 0.02, indicating RMS has a very high resolution. From a simulation study, we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real dataset of infant guts, we show that RMS is capable of detecting a strain diversity gradient for Escherichia coli across time. Conclusion We find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain level. Like shotgun metagenomics, it requires a good database of reference genomes and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS.

Advantage of 16S rRNA amplicon sequencing in Helicobacter pylori diagnosis

Helicobacter ◽  
2021 ◽  
Author(s):  
Boldbaatar Gantuya ◽  
Hashem B. El Serag ◽  
Batsaikhan Saruuljavkhlan ◽  
Dashdorj Azzaya ◽  
Takashi Matsumoto ◽  
...  
Keyword(s):  
Helicobacter Pylori ◽  
16S Rrna ◽  
Amplicon Sequencing ◽  
16S Rrna Amplicon Sequencing

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.

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