scholarly journals Spatial and Temporal Constraints on the Composition of Microbial Communities in Subsurface Boreholes of the Edgar Experimental Mine

Author(s):  
Patrick H. Thieringer ◽  
Alexander S. Honeyman ◽  
John R. Spear

The Edgar Experimental Mine, Idaho Springs, CO, provides inexpensive and open access to borehole investigations for subsurface microbiology studies. Understanding how microbial processes in the near subsurface are connected to surface hydrological influences is lacking.

2016 ◽  
Author(s):  
Kenta Suzuki ◽  
Katsuhiko Yoshida ◽  
Yumiko Nakanishi ◽  
Shinji Fukuda

AbstractMapping the network of ecological interactions is key to understanding the composition, stability, function and dynamics of microbial communities. In recent years various approaches have been used to reveal microbial interaction networks from metagenomic sequencing data, such as time-series analysis, machine learning and statistical techniques. Despite these efforts it is still not possible to capture details of the ecological interactions behind complex microbial dynamics.We developed the sparse S-map method (SSM), which generates a sparse interaction network from a multivariate ecological time-series without presuming any mathematical formulation for the underlying microbial processes. The advantage of the SSM over alternative methodologies is that it fully utilizes the observed data using a framework of empirical dynamic modelling. This makes the SSM robust to non-equilibrium dynamics and underlying complexity (nonlinearity) in microbial processes.We showed that an increase in dataset size or a decrease in observational error improved the accuracy of SSM whereas, the accuracy of a comparative equation-based method was almost unchanged for both cases and equivalent to the SSM at best. Hence, the SSM outperformed a comparative equation-based method when datasets were large and the magnitude of observational errors were small. The results were robust to the magnitude of process noise and the functional forms of inter-specific interactions that we tested. We applied the method to a microbiome data of six mice and found that there were different microbial interaction regimes between young to middle age (4-40 week-old) and middle to old age (36-72 week-old) mice.The complexity of microbial relationships impedes detailed equation-based modeling. Our method provides a powerful alternative framework to infer ecological interaction networks of microbial communities in various environments and will be improved by further developments in metagenomics sequencing technologies leading to increased dataset size and improved accuracy and precision.


2020 ◽  
Author(s):  
Daniel Tajmel ◽  
Carla Cruz Paredes ◽  
Johannes Rousk

<p>Terrestrial biogeochemical cycles are regulated by soil microorganisms. The microbial carbon release due to respiration and carbon sequestration through microbial growth determine whether soils become sources or sinks for carbon. Temperature i​s one of the most important environmental factors controlling both microbial growth and respiration. Therefore, to understand the influence of temperature on microbial processes is crucial. One strategy to predict how ecosystems will respond to warming is to use geographical ecosystem differences, in space-for-time (SFT) substitution approaches. We hypothesized (1) that microbes should be adapted to their environmental temperature leading to microbial communities with warm-shifted temperature relationships in warmer environments, and vice versa. Furthermore, we hypothesized  (2) that other factors should not influence microbial temperature relationships, and (3) that the temperature sensitivity of microbial processes (Q10) should be linked to the microbial temperature relationships.</p><p> </p><p>In this project, we investigated the effects of environmental temperature on microbial temperature relationships for microbial growth and respiration along a natural climate gradient along a transect across Europe to predict the impact of a warming climate. The transect was characterized by mean annual temperature (MAT) ranging from - 4 degrees Celsius (Greenland) to 18 degrees Celsius (Southern Spain), while other environmental factor ranges were broad and unrelated to climate, including pH from 4.0 to 8.8, C/N ratio from 7 to 50, SOM from 4% to 94% and plant communities ranging from arctic tundra to Mediterranean grasslands. More than 56 soil samples were analyzed and microbial temperature relationships were determined using controlled short-term laboratory incubations from 0 degrees Celsius to 45 degrees Celsius. The link between microbial temperature relationship and the climate was assessed by using the relationship between the environmental temperature and indices for microbial temperature relationships including the minimum (T<sub>min</sub>), optimum (T<sub>opt</sub>) and maximum temperature (T<sub>max</sub>) for microbial growth as well as for respiration. To estimate the T<sub>min</sub>, T<sub>opt </sub>and T<sub>max </sub>the square root equation, the Ratkowsky model was used.</p><p> </p><p>We found that microbial communities were adapted to their environmental temperature. The microbial temperature relationship was stronger for microbial growth than for respiration. For 1 degrees Celsius rise in MAT, T<sub>min </sub>increased 0.22 degrees Celsius for bacterial and 0.28 degrees Celsius for fungal growth, while T<sub>min </sub>for respiration increased by 0.16 per 1 degrees Celsius rise. T<sub>min </sub>was also found to be universally linked to Q10, such that higher T<sub>min </sub>resulted in higher Q10. Other environmental factors (pH, C/N ratio, SOM, vegetation cover) did not influence the temperature relationships. By incorporating the determined relationships between environmental temperature and microbial growth and respiration into large scale ecosystem models, we can get a better understanding of the influence of microbial adaptation to warmer climate on the C-exchange between soils and atmosphere.</p>


1984 ◽  
Vol 30 (11) ◽  
pp. 1408-1414 ◽  
Author(s):  
Akira Furutani ◽  
John W. M. Rudd ◽  
C. A. Kelly

A method has been developed for studying direct and indirect responses of microbial processes in lake sediments to environmental perturbations. Responses of the entire microbial community as well as specific members of the community were studied using in vitro sediment systems for periods of weeks or months under control and experimentally perturbed conditions. Effects of perturbations at the community level were determined by comparing rates of organic matter decomposition (CO2 + CH4 production) in the control and test (acidified) systems. At the same time and under the same conditions, rates of specific processes such as mercury methylation and sulfate and nitrate reduction were assayed to see if these processes responded in the same manner as did the activity of the entire community. Acidification (lowering from pH 6.3 to 4.2) did not affect either community activity or nitrate reduction. However, decreases were observed in sulfate reduction and mercury methylation which were independent of community activity, suggesting that acidification may affect these two specific processes directly. Use of this method provides comprehensive information about the interaction of sediment microbial processes as they respond to environmental perturbations.


Author(s):  
Amit Kumar ◽  
Daphne H. P. Ng ◽  
Sakcham Bairoliya ◽  
Bin Cao

Microbial communities play an essential role in maintaining a healthy aquatic ecosystem. For example, in surface water reservoirs, microorganisms produce oxygen, break down toxic contaminants, and remove excess nitrogen.


Author(s):  
Marta Cerruti ◽  
Bing Guo ◽  
Robert Delatolla ◽  
Nadieh de Jonge ◽  
Aleida Hommes - de Vos van Steenwijk ◽  
...  

The wastewater treatment sector embraces mixed-culture biotechnologies for sanitation, environmental protection, and resource recovery. Bioprocess design, monitoring and control thrive on microbial processes selected in complex microbial communities. Microbial ecology...


2020 ◽  
Vol 11 ◽  
Author(s):  
Alexander S. Savvichev ◽  
Vitaly V. Kadnikov ◽  
Igor I. Rusanov ◽  
Alexey V. Beletsky ◽  
Elena D. Krasnova ◽  
...  

2015 ◽  
Vol 28 (3) ◽  
pp. 211-211

MPMI has played a leading role in disseminating new insights into plant-microbe interactions and promoting new approaches. Articles in this Focus Issue highlight the power of genomic studies in uncovering novel determinants of plant interactions with microbial symbionts (good), pathogens (bad), and complex microbial communities (unknown). Many articles also illustrate how genomics can support translational research by quickly advancing our knowledge of important microbes that have not been widely studied. Click on Next Article or Table of Contents above to view the articles in this Focus Issue. (From the mobile site, go to the MPMI March 2015 issue.)


2021 ◽  
Author(s):  
Junhui Li ◽  
Chongjian Jia ◽  
Qihong Lu ◽  
Bruce A Hungate ◽  
Paul Dijkstra ◽  
...  

Even though microbial communities can be more effective at degrading xenobiotics than cultured micro-organisms, yet little is known about the microbial strategies that underpin xenobiotic biodegradation by microbial communities. Here, we employ metagenomic community sequencing to explore the mechanisms that drive the development of 49 xenobiotic-degrading microbial communities, which were enriched from 7 contaminated soils or sediments with a range of xenobiotic compounds. We show that multiple microbial strategies likely co-drive the development of xenobiotic degrading communities, notably (i) presence of genes encoding catabolic enzymes to degrade xenobiotics; (ii) presence of genes encoding efflux pumps; (iii) auxiliary catabolic genes on plasmids; and (iv) positive interactions dominate microbial communities with efficient degradation. Overall, the integrated analyses of microbial ecological strategies advance our understanding of microbial processes driving the biodegradation of xenobiotics and promote the design of bioremediation systems.


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