Functional principal component data analysis: A new method for analysing microbial community fingerprints

Illian, Janine; Prosser, James I.; Baker, Kate; Rangel‐Castro, J. Ignacio

doi:10.1016/j.mimet.2009.08.010

Cited by 25 publications

(16 citation statements)

References 21 publications

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“…Principal component analysis was used to evaluate the carbon source metabolization of microbial communities in a certain environment ( Graham and Haynes, 2005 ; Kong et al, 2013 ). Some researchers had reported that PCA was applied in the multivariate analysis and enabled to clearly differentiate samples ( Felipe-Sotelo et al, 2008 ; Illian et al, 2009 ). After dimension reduction, the difference of metabolic characteristics in rice microbial communities were directly reflected by the position of the points in the principal vector space ( Graham and Haynes, 2005 ; Kim et al, 2017 ).…”

Section: Resultsmentioning

confidence: 99%

Analysis on Metabolic Functions of Stored Rice Microbial Communities by BIOLOG ECO Microplates

Gao

et al. 2018

Front. Microbiol.

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Microbial contamination has been a pervasive issue during the rice storage and triggers extensive researches. The metabolism of microorganisms was proved as an indicator to mirror the degree of microbial contamination. It is necessary to develop a scientific method to analyze the metabolism of rice microbial communities, thereby monitoring the microbial contamination. In this study, the metabolism of rice microbial communities in different storing-year were investigated by BIOLOG ECO microplates. The three rice samples were respectively stored for 1–3 years. The related indicators of BIOLOG ECO microplates were determined, including average well-color development (AWCD) of carbon sources and three metabolic functional diversity indices. The results showed that there were significant differences in the AWCD of all carbon sources among the three rice microbial communities (p < 0.05), and the functional diversity indices except Simpson index showed significant differences (p < 0.05). Additionally, the three rice microbial communities differed significantly in the metabolic utilization of carboxylic acids and miscellaneous (p < 0.05), and there were, however, no significant differences in the other four types of carbon sources. Furthermore, principal component analysis revealed that the microbial communities of stored rice had obviously different metabolic functions in different storage period. Therefore, the study indicated that the BIOLOG ECO microplate was applicable to evaluate the metabolic functions of rice microbial communities, and carboxylic acids and miscellaneous were two crucial parameters of carbon sources to identify the metabolic differences of microbial communities, a case in which it reflected the conditions of rice microbial contamination.

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Section: Resultsmentioning

confidence: 99%

Analysis on Metabolic Functions of Stored Rice Microbial Communities by BIOLOG ECO Microplates

Gao

et al. 2018

Front. Microbiol.

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“…To explore the differences in microbial community function among different samples, the PCA was applied to extract the main components, and the variance maximized orthogonal rotation [29][30]. The multivariate vectors were transformed into two uncorrelated principal component vectors.…”

Section: Pca Of Carbon Source Metabolizationmentioning

confidence: 99%

Soil Microbial Functional Diversity Responses to Different Revegetation Types in Baishilazi Nature Reserve

Deng¹,

Zhou²,

Bai³

et al. 2019

Pol. J. Environ. Stud.

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Soil microorganisms play important roles in the dynamic regulation of organic matter in the forest ecosystem and are affected by different revegetation types. To reveal the influence of different revegetation types on soil microorganisms, we examined soil properties, soil microbial activity and diversity in Baishilazi Nature Reserve, including two planted coniferous forests (LG: Larix gmelinii, PK: Pinus koraiensis), two natural secondary broadleaf forests (JM: Juglans mandshurica, QM: Quercus mongolica), and one conifer-broadleaf forest (CB). Biolog-Eco plates were used to study soil microbial functional diversity. We found that the content of soil total C and total N existed higher under the broadleaf forests (JM, QM) than conifer-broadleaf forest (CB) and coniferous forests (LG, PK). Carbon source utilization capacity and soil microbial activity showed significant variations among different revegetation types. Soil microbial activity of natural secondary forests was significantly higher than planted coniferous forests, and JM created the highest soil microbial activity. Heatmap and PCA plot clearly differentiated among the different samples. The broadleaf forests, conifer-broadleaf forest and coniferous forests were well separated from each other, especially along the PC1, and the position of conifer-broadleaf forest was intermediate. The findings of canonical correspondence analysis (CCA) suggested that soil total C and total N were the main factors affecting soil microbial functional diversity. This study investigated how shifts in soil microbial functional diversity affected by different revegetation types were operational indicators of soil quality

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“…These approaches certainly enhance objectivity and comprehensiveness compared with user-based explanations of population shifts, but they still need some caveats. A recent analysis of a non-rumen microbiome has documented an improvement to the standard principal components analysis for DGGE (Illian et al, 2009). Readers need to be aware that condensing common variance to a few principal components should improve the explanation of complex relationships or else it really makes little advance in our knowledge.…”

Section: Molecular Approaches To Integrate Microbial Ecology With Rummentioning

confidence: 99%

Reconsidering rumen microbial consortia to enhance feed efficiency and reduce environmental impact of ruminant livestock production systems

Firkins

2010

R. Bras. Zootec.

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Because cultivation-based approaches to assess rumen microbiology assess only the minority of microbial groups and can miss opportunities to assess important functions, molecular-based approaches have flourished in microbial ecology and have been adapted to the rumen. Current approaches are described herein, specifically for a robust adaptation to nutrition studies or future opportunities. These included automated profiling techniques, density gradient gel electrophoresis, and future adaption of microarray or high-throughput sequencing technologies. Based on current knowledge, a more holistic approach is needed to describe various functional groups of microbes within the context of how they influence, and are influenced by, the whole consortium (combination of microbial groups). Such a perspective is applied to issues related to increasing fiber digestibility when feeding concentrate or unsaturated fats to high producing beef and dairy cattle. These same microbial populations should help to provide growth factors for fibrolytic bacteria while competing against the hyperammonia-producing bacteria such that there would be less need for excessive rumen-degraded protein as a safety factor. Moreover, these same dietary conditions influence the processes of biohydrogenation and methanogenesis. After accounting for population structures of bacteria, protozoa, methanogenic archaea, and even fungi, efforts to integrate molecular-based rumen microbial ecology with dietary conditions should allow us to better explain and therefore predict conditions that will improve feed efficiency and reduce environmental impact of ruminant production systems.

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Functional principal component data analysis: A new method for analysing microbial community fingerprints

Cited by 25 publications

References 21 publications

Analysis on Metabolic Functions of Stored Rice Microbial Communities by BIOLOG ECO Microplates

Analysis on Metabolic Functions of Stored Rice Microbial Communities by BIOLOG ECO Microplates

Soil Microbial Functional Diversity Responses to Different Revegetation Types in Baishilazi Nature Reserve

Reconsidering rumen microbial consortia to enhance feed efficiency and reduce environmental impact of ruminant livestock production systems

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