Effects of nitrogen and phosphorus addition on microbial community composition and element cycling in a grassland soil

Subtropical and tropical broadleaf forests play important roles in conserving biodiversity and regulating global carbon cycle. Nonetheless, knowledge about soil microbial diversity, community composition, turnover and microbial functional structure in sub- and tropical broadleaf forests is scarce. In this study, high-throughput sequencing was used to profile soil microbial community composition, and a micro-array GeoChip 5.0 was used to profile microbial functional gene distribution in four sub- and tropical broadleaf forests (HS, MES, HP and JFL) in southern China. The results showed that soil microbial community compositions differed dramatically among all of four forests. Soil microbial diversities in JFL were the lowest (5.81–5.99) and significantly different from those in the other three forests (6.22–6.39). Furthermore, microbial functional gene interactions were the most complex and closest, likely in reflection to stress associated with the lowest nitrogen and phosphorus contents in JFL. In support of the importance of environmental selection, we found selection (78–96%) dominated microbial community assembly, which was verified by partial Mantel tests showing significant correlations between soil phosphorus and nitrogen content and microbial community composition. Taken together, these results indicate that nitrogen and phosphorus are pivotal in shaping soil microbial communities in sub- and tropical broadleaf forests in southern China. Changes in soil nitrogen and phosphorus, in response to plant growth and decomposition, will therefore have significant changes in both microbial community assembly and interaction.

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Soil carbonyl sulfide exchange in relation to microbial community composition: Insights from a managed grassland soil amendment experiment

Soil Biology and Biochemistry ◽

10.1016/j.soilbio.2019.04.005 ◽

2019 ◽

Vol 135 ◽

pp. 28-37 ◽

Cited By ~ 4

Author(s):

Florian Kitz ◽

María Gómez-Brandón ◽

Bernhard Eder ◽

Mohammad Etemadi ◽

Felix M. Spielmann ◽

...

Keyword(s):

Microbial Community ◽

Community Composition ◽

Soil Amendment ◽

Microbial Community Composition ◽

Carbonyl Sulfide ◽

Grassland Soil

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Exoenzymes as a Signature of Microbial Response to Marine Environmental Conditions

mSystems ◽

10.1128/msystems.00290-20 ◽

2020 ◽

Vol 5 (2) ◽

Author(s):

Manoj Kamalanathan ◽

Shawn M. Doyle ◽

Chen Xu ◽

Amanda M. Achberger ◽

Terry L. Wade ◽

...

Keyword(s):

Microbial Community ◽

Organic Carbon ◽

Community Composition ◽

Marine Environment ◽

Strong Correlation ◽

Microbial Community Composition ◽

Community Control ◽

Nitrogen And Phosphorus ◽

Carbon And Nitrogen ◽

Factors Associated

ABSTRACT Microbial heterotopic metabolism in the ocean is fueled by a supply of essential nutrients acquired via exoenzymes catalyzing depolymerization of high-molecular-weight compounds. Although the rates of activity for a variety of exoenzymes across various marine environments are well established, the factors regulating the production of these exoenzymes, and to some extent their correlation with microbial community composition, are less known. This study focuses on addressing these challenges using a mesocosm experiment that compared a natural seawater microbial community (control) and exposed (to oil) treatment. Exoenzyme activities for β-glucosidase, leucine aminopeptidase (LAP), and lipase were significantly correlated with dissolved nutrient concentrations. We measured correlations between carbon- and nitrogen-acquiring enzymes (β-glucosidase/lipase versus LAP) and found that the correlation of carbon-acquiring enzymes varies with the chemical nature of the available primary carbon source. Notably, a strong correlation between particulate organic carbon and β-glucosidase activity demonstrates their polysaccharide depolymerization in providing the carbon for microbial growth. Last, we show that exoenzyme activity patterns are not necessarily correlated with prokaryotic community composition, suggesting a redundancy of exoenzyme functions among the marine microbial community and substrate availability. This study provides foundational work for linking exoenzyme function with dissolved organic substrate and downstream processes in marine systems. IMPORTANCE Microbes release exoenzymes into the environment to break down complex organic matter and nutrients into simpler forms that can be assimilated and utilized, thereby addressing their cellular carbon, nitrogen, and phosphorus requirements. Despite its importance, the factors associated with the synthesis of exoenzymes are not clearly defined, especially for the marine environment. Here, we found that exoenzymes associated with nitrogen and phosphorus acquisition were strongly correlated with inorganic nutrient levels, while those associated with carbon acquisition depended on the type of organic carbon available. We also show a linear relationship between carbon- and nitrogen-acquiring exoenzymes and a strong correlation between microbial biomass and exoenzymes, highlighting their significance to microbial productivity. Last, we show that changes in microbial community composition are not strongly associated with changes in exoenzyme activity profiles, a finding which reveals a redundancy of exoenzyme activity functions among microbial community. These findings advance our understanding of previously unknown factors associated with exoenzyme production in the marine environment.

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The relationship between land cover and microbial community composition in European lakes

10.1101/2021.11.17.468820 ◽

2021 ◽

Author(s):

Theodor Sperlea ◽

Jan Philip Schenk ◽

Hagen Dreßler ◽

Daniela Beisser ◽

Georges Hattab ◽

...

Keyword(s):

Machine Learning ◽

Microbial Community ◽

Land Cover ◽

Community Composition ◽

Microbial Community Composition ◽

Environmental Parameters ◽

Amplicon Sequencing ◽

Learning Approaches ◽

Element Cycling ◽

The Relationship

Microbes such as bacteria, archaea, and protists are essential for element cycling and ecosystem functioning, but many questions central to the understanding of the role of microbes in ecology are still open. Here, we analyze the relationship between lake microbiomes and the land cover surrounding the lakes. By applying machine learning methods, we quantify the covariance between land cover categories and the microbial community composition recorded in the largest amplicon sequencing dataset of European lakes available to date. We identify microbial bioindicators for these land cover categories. Combining land cover and physico-chemical bioindicators identified from the same amplicon sequencing dataset, we develop two novel similarity metrics that facilitate insights into the ecology of the lake microbiome. We show that the bioindicator network, i.e., the graph linking OTUs indicative of the same environmental parameters, corresponds to microbial co-occurrence patterns. Taken together, we demonstrate the strength of machine learning approaches to identify correlations between microbial diversity and environmental factors, potentially opening new approaches to integrate environmental molecular diversity into monitoring and water quality assessments.

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