scholarly journals Novel microbial community composition and carbon biogeochemistry emerge over time following saltwater intrusion in wetlands

2018 ◽  
Vol 25 (2) ◽  
pp. 549-561 ◽  
Author(s):  
Chansotheary Dang ◽  
Ember M. Morrissey ◽  
Scott C. Neubauer ◽  
Rima B. Franklin
2021 ◽  
Vol 11 ◽  
Author(s):  
Janneke Schreuder ◽  
Francisca C. Velkers ◽  
Alex Bossers ◽  
Ruth J. Bouwstra ◽  
Willem F. de Boer ◽  
...  

Associations between animal health and performance, and the host’s microbiota have been recently established. In poultry, changes in the intestinal microbiota have been linked to housing conditions and host development, but how the intestinal microbiota respond to environmental changes under farm conditions is less well understood. To gain insight into the microbial responses following a change in the host’s immediate environment, we monitored four indoor flocks of adult laying chickens three times over 16 weeks, during which two flocks were given access to an outdoor range, and two were kept indoors. To assess changes in the chickens’ microbiota over time, we collected cloacal swabs of 10 hens per flock and performed 16S rRNA gene amplicon sequencing. The poultry house (i.e., the stable in which flocks were housed) and sampling time explained 9.2 and 4.4% of the variation in the microbial community composition of the flocks, respectively. Remarkably, access to an outdoor range had no detectable effect on microbial community composition, the variability of microbiota among chickens of the same flock, or microbiota richness, but the microbiota of outdoor flocks became more even over time. Fluctuations in the composition of the microbiota over time within each poultry house were mainly driven by turnover in rare, rather than dominant, taxa and were unique for each flock. We identified 16 amplicon sequence variants that were differentially abundant over time between indoor and outdoor housed chickens, however none were consistently higher or lower across all chickens of one housing type over time. Our study shows that cloacal microbiota community composition in adult layers is stable following a sudden change in environment, and that temporal fluctuations are unique to each flock. By exploring microbiota of adult poultry flocks within commercial settings, our study sheds light on how the chickens’ immediate environment affects the microbiota composition.


2020 ◽  
Vol 40 ◽  
pp. 675-676
Author(s):  
P.G. Brasiel ◽  
T. Costa de Almeida ◽  
N. Lins de Andrade ◽  
L. da Roza Corguinha ◽  
B. Siqueira Lima da Silva ◽  
...  

2021 ◽  
Author(s):  
Ludwig Jardillier ◽  
Gwendoline David ◽  
Philippe Deschamps ◽  
Paola Bertolino ◽  
David Moreira ◽  
...  

<p>Small freshwater ecosystems are highly diverse, widely distributed, may be identified as major actors in greenhouse gas fluxes and are potential stocks of freshwater for human usages. In principle, they are more sensitive to environmental disturbance than large aquatic ecosystems because their small volumes provide low buffering capacity. However, little is yet known about their microbial biodiversity and function and how it is structured over time. Yet, understanding the structuring of microbial primary producers, predators, parasites and degraders in these ecosystems is essential to appreciate and model their functioning in the next decades. We investigated the spatial distribution and temporal dynamics of microorganisms of the three domains of life (bacteria, archaea, microbial eukaryotes) at the intra- (seasonal) and inter-annual (pluri-annual) scale in five small freshwater ecosystems. We focused on four ponds and a brook located in northwestern France under temperate climate that we studied for eight years (2011-2019) at seasonal frequency. Microbial diversity was assessed through Illumina MiSeq sequencing of 16S and 18S rDNA amplicons. Several abiotic parameters (physical and chemical) were measured<em> in situ</em> and in the laboratory to characterise the environmental conditions. Multivariate statistical analyses were conducted to identify temporal patterns and link them to environment changes. Microbial communities differed among the ecosystems despite their spatial proximity, likely due to differences in local environmental conditions. Microbial eukaryotic and prokaryotic communities exhibited seasonal temporal patterns and a shift in composition over the years. Microbial communities experienced a strong turnover at the seasonal scale leading to a low fraction (< 2%) of recurrent taxa. In each ecosystem, the measured physico-chemical parameters slightly influenced the microbial community variance over time. These results suggest that biotic interactions but also dormancy, immigration and genetic evolution superimpose to environmental selection through time. Understanding their interplay will be essential to explain microbial community composition change in these ecosystems.<span> </span></p>


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.


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