scholarly journals Temperature and soil moisture control microbial community composition in an arctic–alpine ecosystem along elevational and micro-topographic gradients

2019 ◽  
Vol 13 (8) ◽  
pp. 2031-2043 ◽  
Author(s):  
K. Frindte ◽  
R. Pape ◽  
K. Werner ◽  
J. Löffler ◽  
C. Knief
2015 ◽  
Vol 12 (8) ◽  
pp. 2585-2596 ◽  
Author(s):  
L. Ma ◽  
C. Guo ◽  
X. Lü ◽  
S. Yuan ◽  
R. Wang

Abstract. Global environmental factors impact soil microbial communities and further affect organic matter decomposition, nutrient cycling and vegetation dynamic. However, little is known about the relative contributions of climate factors, soil properties, vegetation types, land management practices and spatial structure (which serves as a proxy for underlying effects of temperature and precipitation for spatial variation) on soil microbial community composition and biomass at large spatial scales. Here, we compared soil microbial communities using phospholipid fatty acid method across 7 land use types from 23 locations at a regional scale in northeastern China (850 × 50 km). The results showed that soil moisture and land use changes were most closely related to microbial community composition and biomass at the regional scale, while soil total C content and climate effects were weaker but still significant. Factors such as spatial structure, soil texture, nutrient availability and vegetation types were not important. Higher contributions of gram-positive bacteria were found in wetter soils, whereas higher contributions of gram-negative bacteria and fungi were observed in drier soils. The contributions of gram-negative bacteria and fungi were lower in heavily disturbed soils than historically disturbed and undisturbed soils. The lowest microbial biomass appeared in the wettest and driest soils. In conclusion, dominant climate and soil properties were not the most important drivers governing microbial community composition and biomass because of inclusion of irrigated and managed practices, and thus soil moisture and land use appear to be primary determinants of microbial community composition and biomass at the regional scale in northeastern China.


LWT ◽  
2021 ◽  
pp. 111694
Author(s):  
Xiaoxi Chen ◽  
Qin Chen ◽  
Yaxin Liu ◽  
Bin Liu ◽  
Xubo Zhao ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Raiza Hasrat ◽  
Jolanda Kool ◽  
Wouter A. A. de Steenhuijsen Piters ◽  
Mei Ling J. N. Chu ◽  
Sjoerd Kuiling ◽  
...  

AbstractThe low biomass of respiratory samples makes it difficult to accurately characterise the microbial community composition. PCR conditions and contaminating microbial DNA can alter the biological profile. The objective of this study was to benchmark the currently available laboratory protocols to accurately analyse the microbial community of low biomass samples. To study the effect of PCR conditions on the microbial community profile, we amplified the 16S rRNA gene of respiratory samples using various bacterial loads and different number of PCR cycles. Libraries were purified by gel electrophoresis or AMPure XP and sequenced by V2 or V3 MiSeq reagent kits by Illumina sequencing. The positive control was diluted in different solvents. PCR conditions had no significant influence on the microbial community profile of low biomass samples. Purification methods and MiSeq reagent kits provided nearly similar microbiota profiles (paired Bray–Curtis dissimilarity median: 0.03 and 0.05, respectively). While profiles of positive controls were significantly influenced by the type of dilution solvent, the theoretical profile of the Zymo mock was most accurately analysed when the Zymo mock was diluted in elution buffer (difference compared to the theoretical Zymo mock: 21.6% for elution buffer, 29.2% for Milli-Q, and 79.6% for DNA/RNA shield). Microbiota profiles of DNA blanks formed a distinct cluster compared to low biomass samples, demonstrating that low biomass samples can accurately be distinguished from DNA blanks. In summary, to accurately characterise the microbial community composition we recommend 1. amplification of the obtained microbial DNA with 30 PCR cycles, 2. purifying amplicon pools by two consecutive AMPure XP steps and 3. sequence the pooled amplicons by V3 MiSeq reagent kit. The benchmarked standardized laboratory workflow presented here ensures comparability of results within and between low biomass microbiome studies.


Sign in / Sign up

Export Citation Format

Share Document