A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation

ABSTRACTWine is a complex beverage, comprising hundreds of metabolites produced through the action of yeasts and bacteria in fermenting grape must. To ensure a robust and reliable fermentation, most commercial wines are produced via inoculation with commercial strains of the major wine yeast,Saccharomyces cerevisiae. However, there is a growing trend towards the use of uninoculated or “wild” fermentations, in which the yeasts and bacteria that are naturally associated with the vineyard and winery, perform the fermentation. In doing so, the varied metabolic contributions of the numerous non-Saccharomycesspecies in this microbial community are thought to impart complexity and desirable taste and aroma attributes to wild ferments in comparison to their inoculated counterparts.In order the map the microflora of spontaneous fermentation, metagenomic techniques were used to characterize and monitor the progression of fungal species in several wild fermentations. Both amplicon-based ITS phylotyping (meta-barcoding) and shotgun metagenomics were used to assess community structure. While providing a sensitive and highly accurate means of characterizing the wine microbiome, the shotgun metagenomic data also uncovered a significant over-abundance bias in the ITS phylotyping abundance estimations for the common non-Saccharomyceswine yeast genusMetschnikowia.

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Karst rocky desertification does not erode ectomycorrhizal fungal species richness but alters microbial community structure

Plant and Soil ◽

10.1007/s11104-019-04319-z ◽

2019 ◽

Vol 445 (1-2) ◽

pp. 383-396 ◽

Cited By ~ 1

Author(s):

Nan Hui ◽

Ningxiao Sun ◽

Hongmei Du ◽

Muhammad Umair ◽

Hongzhang Kang ◽

...

Keyword(s):

Species Richness ◽

Community Structure ◽

Microbial Community ◽

Microbial Community Structure ◽

Fungal Species ◽

Karst Rocky Desertification ◽

Rocky Desertification

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0996 - Metagenomic data shows different soil microbial community structure in two conservations parks of the Brazilian savannah

10.26226/morressier.5b5199c1b1b87b000ecee82b ◽

2018 ◽

Author(s):

Ricardo Kruger

Keyword(s):

Community Structure ◽

Microbial Community ◽

Microbial Community Structure ◽

Soil Microbial Community ◽

Metagenomic Data ◽

Soil Microbial Community Structure ◽

Soil Microbial ◽

Brazilian Savannah

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Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network

mBio ◽

10.1128/mbio.02691-19 ◽

2020 ◽

Vol 11 (2) ◽

Cited By ~ 2

Author(s):

Laís F. O. Lima ◽

Maya Weissman ◽

Micheal Reed ◽

Bhavya Papudeshi ◽

Amanda T. Alker ◽

...

Keyword(s):

Community Structure ◽

Microbial Community ◽

Dynamic Model ◽

Microbial Community Structure ◽

Environmental Changes ◽

Mucus Layer ◽

Shotgun Metagenomics ◽

Microbial Network ◽

Coral Microbiome ◽

Relative Abundances

ABSTRACT Host-associated microbial communities are shaped by extrinsic and intrinsic factors to the holobiont organism. Environmental factors and microbe-microbe interactions act simultaneously on the microbial community structure, making the microbiome dynamics challenging to predict. The coral microbiome is essential to the health of coral reefs and sensitive to environmental changes. Here, we develop a dynamic model to determine the microbial community structure associated with the surface mucus layer (SML) of corals using temperature as an extrinsic factor and microbial network as an intrinsic factor. The model was validated by comparing the predicted relative abundances of microbial taxa to the relative abundances of microbial taxa from the sample data. The SML microbiome from Pseudodiploria strigosa was collected across reef zones in Bermuda, where inner and outer reefs are exposed to distinct thermal profiles. A shotgun metagenomics approach was used to describe the taxonomic composition and the microbial network of the coral SML microbiome. By simulating the annual temperature fluctuations at each reef zone, the model output is statistically identical to the observed data. The model was further applied to six scenarios that combined different profiles of temperature and microbial network to investigate the influence of each of these two factors on the model accuracy. The SML microbiome was best predicted by model scenarios with the temperature profile that was closest to the local thermal environment, regardless of the microbial network profile. Our model shows that the SML microbiome of P. strigosa in Bermuda is primarily structured by seasonal fluctuations in temperature at a reef scale, while the microbial network is a secondary driver. IMPORTANCE Coral microbiome dysbiosis (i.e., shifts in the microbial community structure or complete loss of microbial symbionts) caused by environmental changes is a key player in the decline of coral health worldwide. Multiple factors in the water column and the surrounding biological community influence the dynamics of the coral microbiome. However, by including only temperature as an external factor, our model proved to be successful in describing the microbial community associated with the surface mucus layer (SML) of the coral P. strigosa. The dynamic model developed and validated in this study is a potential tool to predict the coral microbiome under different temperature conditions.

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Bayesian Inference of Microbial Community Structure from Metagenomic Data Using BioMiCo

Methods in Molecular Biology - Microbiome Analysis ◽

10.1007/978-1-4939-8728-3_17 ◽

2018 ◽

pp. 267-289

Author(s):

Katherine A. Dunn ◽

Katelyn Andrews ◽

Rana O. Bashwih ◽

Joseph P. Bielawski

Keyword(s):

Community Structure ◽

Microbial Community ◽

Bayesian Inference ◽

Microbial Community Structure ◽

Metagenomic Data

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A practical introduction to microbial community sequencing

Open Life Sciences ◽

10.2478/s11535-013-0155-8 ◽

2013 ◽

Vol 8 (5) ◽

pp. 399-409 ◽

Cited By ~ 1

Author(s):

Dominika Chmolowska

Keyword(s):

Community Structure ◽

Microbial Community ◽

Sample Preparation ◽

Community Ecology ◽

Microbial Community Structure ◽

Shotgun Metagenomics ◽

Genetic Tool ◽

Amplicon Library ◽

Microbial Community Ecology ◽

Sample Preparation Procedure

AbstractThe use of molecular methods is gaining popularity throughout the field of microbial community ecology studies thanks to their flexibility of application, which ranges from community structure to function and trait determination. Nonetheless, there are environmental microbiologists, who are new in the field and are just starting to get to grips with the genetic tool box. It is for them that this practitioner’s mini-review was compiled. The methods available for microbial community structure analysis are discussed, after which, the reader is introduced to sequencing, as this tool is the most appropriate and has seen the greatest development in recent years. A focus on the practical aspects of the methodology is maintained throughout. The sample preparation procedure from extraction to sequencing is described. Different applications and considerations of sequencing are briefly explained, including clone library sequencing vs. amplicon library sequencing, shotgun-metagenomics vs. metatranscriptomics and the ‘double RNA approach’.

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