Microbial Communities in Long-Term, Water-Flooded Petroleum Reservoirs with Different in situ Temperatures in the Huabei Oilfield, China

The distribution of microbial communities in the Menggulin (MGL) and Ba19 blocks in the Huabei Oilfield, China, were studied based on 16S rRNA gene analysis. The dominant microbes showed obvious block-specific characteristics, and the two blocks had substantially different bacterial and archaeal communities. In the moderate-temperature MGL block, the bacteria were mainly Epsilonproteobacteria and Alphaproteobacteria, and the archaea were methanogens belonging to Methanolinea, Methanothermobacter, Methanosaeta, and Methanocella. However, in the high-temperature Ba19 block, the predominant bacteria were Gammaproteobacteria, and the predominant archaea were Methanothermobacter and Methanosaeta. In spite of shared taxa in the blocks, differences among wells in the same block were obvious, especially for bacterial communities in the MGL block. Compared to the bacterial communities, the archaeal communities were much more conserved within blocks and were not affected by the variation in the bacterial communities

Challenges in microbial ecology: building predictive understanding of community function and dynamics.

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model-experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved