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. 2012 Feb;6(2):451-60.
doi: 10.1038/ismej.2011.91. Epub 2011 Aug 4.

"VSports app下载" Microbial gene functions enriched in the Deepwater Horizon deep-sea oil plume

Zhenmei Lu  1 , Ye Deng, Joy D Van Nostrand, Zhili He, James Voordeckers, Aifen Zhou, Yong-Jin Lee, Olivia U Mason, Eric A Dubinsky, Krystle L Chavarria, Lauren M Tom, Julian L Fortney, Regina Lamendella, Janet K Jansson, Patrik D'haeseleer, Terry C Hazen, Jizhong Zhou
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"V体育官网入口" Microbial gene functions enriched in the Deepwater Horizon deep-sea oil plume

"VSports app下载" Zhenmei Lu et al. ISME J. 2012 Feb.

V体育ios版 - Abstract

The Deepwater Horizon oil spill in the Gulf of Mexico is the deepest and largest offshore spill in the United State history and its impacts on marine ecosystems are largely unknown. Here, we showed that the microbial community functional composition and structure were dramatically altered in a deep-sea oil plume resulting from the spill VSports手机版. A variety of metabolic genes involved in both aerobic and anaerobic hydrocarbon degradation were highly enriched in the plume compared with outside the plume, indicating a great potential for intrinsic bioremediation or natural attenuation in the deep sea. Various other microbial functional genes that are relevant to carbon, nitrogen, phosphorus, sulfur and iron cycling, metal resistance and bacteriophage replication were also enriched in the plume. Together, these results suggest that the indigenous marine microbial communities could have a significant role in biodegradation of oil spills in deep-sea environments. .

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Figures

Figure 1
Figure 1
Hierarchical cluster analysis of all genes present in at least two out of the five samples. Results were generated in CLUSTER and visualized using TREEVIEW. Red indicates signal intensities above background, whereas black indicates signal intensities below background. Brighter red coloring indicates higher signal intensities. All oil plume samples clustered together and were well separated from non-plume samples.
Figure 2
Figure 2
CCA compares the GeoChip hybridization signal intensities (symbols) and environmental variables (arrows). Environmental variables were chosen based on significance calculated from individual CCA results and variance inflation factors (VIFs) calculated during CCA. The percentage of variation explained by each axis is shown, and the relationship is significant (P=0.026).
Figure 3
Figure 3
Variation partitioning based on CCA for all functional gene signal intensities. (a) General outline, (b) all functional genes. A CCA-based VIF was performed to identify common sets of oil composition and seawater variables important to the microbial community structure. Oil composition variables included fluorometer detection of oil, the concentration of total volatile HCs, xylenes and petroleum HCs—extractable (DRO). Seawater geochemical variables included temperature, dissolved oxygen (DO), Fe and phosphate.
Figure 4
Figure 4
The normalized signal intensity of the nahA genes (naphthalene 1,2-dioxygenase) for the initial oxidation of naphthalene. The signal intensity for each sequence was the average of the total signal intensity from all the replicates. Gene number is the protein ID number for each gene as listed in the GenBank database. All data are presented as mean±s.e. ***P<0.01, **P<0.05, *P<0.1.
Figure 5
Figure 5
The normalized signal intensity of bbs (β-oxidation of benzylsuccinate) genes for anaerobic toluene degradation. The signal intensity for each sequence was the average of the total signal intensity from all the replicates. Gene number is the protein ID number for each gene as listed in the GenBank database. All data are presented as mean±s.e. ***P<0.01, **P<0.05, *P<0.1. In total, seven probes were designed for bbs genes in GeoChip 4.0 and three probes were detected in the samples.
Figure 6
Figure 6
The relative changes of the detected genes involved in the N cycle in oil plume. The signal intensity for each gene detected was normalized by all detected gene sequences using the mean. The percentage of a functional gene in a bracket was the sum of signal intensity of all detected sequences of this gene divided by the grand sum of signal intensity of the detected N cycle genes, and weighted by the fold change of the signal intensity of this gene in plume to that in non-plume. For each functional gene, red indicates that this gene had a higher signal intensity in plume than in non-plume and their significance was indicated with two stars (**) at P<0.01, whereas blue indicates that this gene had a lower signal intensity in oil-plume than in non-plume. Grey-colored genes were not targeted by this GeoChip, or not detected in those samples. It remains unknown if nosZ homologs exist in nitrifiers. Description of the genes: (a) gdh, encoding glutamate dehydrogenase, ureC, encoding urease responsible for ammonification; (b) nasA, encoding nitrate reductase, NiR, encoding nitrite reductase, responsible for assimilatory N reduction; (c) nifH, encoding nitrogenase responsible for N2 fixation; (d) narG encoding nitrate reductase, nirS and nirK-D (with denitrification activity), encoding nitrite reductase; nosZ, encoding nitrous oxide reductase, norB, encoding nitric oxide reducatse, responsible for denitrification (e) napA, encoding periplasmic nitrate reductase, nrfA, encoding c-type cytochrome nitrite reducatse, responsible for dissimilatory N reduction to ammonium; (f) hao, encoding hydroxylamine oxidoreductase, and nirK-N encoding nitrite reductase for nitrifiers (an indication of nitrification activity), responsible for nitrification.
Figure 7
Figure 7
The normalized signal intensity of the replication genes for bacteriophage. The signal intensity for each sequence was the average of the total signal intensity from all the replicates. Gene number is the protein ID number for each gene as listed in the GenBank database. All data are presented as mean±s.e. ***P<0.01, **P<0.05, *P<0.1.
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