Enzymatic Activation Of Alkanes Constraints And Prospects Fastpitch

Individual cognitive processes and limitations, the experimental method, and a. Cell fermentation systems and enzyme-based approaches as well as. Gene activation and deactivation; and how specific cell and tissue structures. Discussion of the reactions of alkanes, alkenes, alkynes, and alkyl halides. Mauser serial number lookup. Rinaldo Poli was born in Barga, Italy, on August 17, 1956. He has received the Laurea degree from the University of Pisa in 1981 and the Perfezionamento degree from the Scuola Normale Superiore, Pisa, in 1985, under the direction of Fausto Calderazzo.

Results Here, we describe the metabolic potential and in situ activity of microbial communities obtained from the Jiangsu Oil Reservoir (China) by an integrated metagenomics and metatranscriptomics approach. Almost complete genome sequences obtained by differential binning highlight the distinct capability of different community members to degrade hydrocarbons under oxic or anoxic condition. Transcriptomic data delineate active members of the community and give insights that Acinetobacter species completely oxidize alkanes into carbon dioxide with the involvement of oxygen, and Archaeoglobus species mainly ferment alkanes to generate acetate which could be consumed by Methanosaeta species. Furthermore, nutritional requirements based on amino acid and vitamin auxotrophies suggest a complex network of interactions and dependencies among active community members that go beyond classical syntrophic exchanges; this network defines community composition and microbial ecology in oil reservoirs undergoing secondary recovery.

Microorganisms have been detected in oil reservoirs, pipelines, and crude oil processing facilities for decades [, ]. Their presence has long been associated with their metabolic capability of degrading crude oil hydrocarbons, under both oxic and anoxic conditions [, ]. While oil reservoirs are generally considered anoxic, molecular oxygen present in water injected into the reservoir during secondary recovery can play an important role as electron acceptor and can facilitate activation of otherwise chemically inert hydrocarbons [ ]. Microorganisms associated to taxa consisting of predominately aerobic members have been detected and associated to the degradation of hydrocarbon in oil reservoirs undergoing secondary recovery [ ]. Over the past decades, we have gained in depth knowledge, mainly through laboratory experiments, about how hydrocarbons are metabolized under oxic and anoxic conditions [, ].

Furthermore, recent advances into molecular biology and metabolomics have enabled elucidation of the metabolic potential of microbial communities existing in oil reservoirs [ ]. Currently, however, we lack a deeper understanding of which members of the community are active in oil reservoirs and if these organisms are contributing to the degradation of crude oil in situ concurrently. Here, we analyze the aerobic and anaerobic microbial communities obtained from three wells of the Jiangsu Oil Reservoir (China) by an integrated metagenomic and metatranscriptomic approach to gain insight into the activity of specific microbes in situ. We annotate (almost complete) genomes from these samples and determine different activation mechanisms deployed during hydrocarbon degradation. Furthermore, we reveal nutritional requirements of oil reservoir microorganisms, such as amino acids and vitamins, hinting at a complex network of microbial interactions beyond syntrophy present in oil reservoirs. Shotgun metagenomic sequencing of DNA obtained from wells W2-71, W9-18, and W15-5 in the Jiangsu Oil Reservoir (Jiangsu, China) generated ~ 9,200,000, ~ 10,900,000, and ~ 7,700,000 quality-controlled paired-end reads (2 × 75 bp), respectively (see Additional file: Table S1).

In the remainder of this article, the three samples will be denoted as W2, W9 and W15. Sequence coverage was high for all three samples, ranging from 80 to 94% completion (see Additional file: Table S2) as estimated by Nonpareil [ ]. Taxonomic classification from unassembled reads using MetaPhlAn2 and Metaxa2 yielded improved resolution over the assembled 16S rRNA gene sequences (Fig.

The biased estimation of taxonomic diversity is probably due to the low number of OTUs (13/17/16 (W2/W9/W15) clustered from 39/39/25 16S rRNA gene sequences) that were obtained from separately assembled contigs of the three samples (see Additional file: Table S3). As highlighted in Fig., the most abundant bacterial orders in all three samples were Pseudomonadales, followed by Alteromonadales, Campylobacterales, and Thermodesulfobacteriales (Fig. MetaPhlAn2 analysis revealed different proportions of Archaea compared to Metaxa2. This disaccord is expected since different biomarkers are used by these two tools to evaluate taxonomic information from metagenomes. Archaea sequences were dominated by members of the Methanosarcinales and Archaeoglobales. The overall microbial composition of three samples are similar except that members of Thermodesulfobacteriales and Thermoanaerobacterales were not detected in W2 samples, and relative low abundance of Methanosarcinales was found in W2 compared to other two samples. This is probably due to the lowest sequence coverage of W2 among the three samples, which affects abundance of minor members in microbial community, such as Archaeal members and minor community members of Bacteria.