Molecular Detection of Anaerobic Ammonium-Oxidizing (Anammox) Bacteria in High-Temperature Petroleum Reservoirs

Anaerobic ammonium-oxidizing (anammox) process plays an important role in the nitrogen cycle of the worldwide anoxic and mesophilic habitats. Recently, the existence and activity of anammox bacteria have been detected in some thermophilic environments, but their existence in the geothermal subterranean oil reservoirs is still not reported. This study investigated the abundance, distribution and functional diversity of anammox bacteria in nine out of 17 high-temperature oil reservoirs by molecular ecology analysis. High concentration (5.31–39.2 mg l−1) of ammonium was detected in the production water from these oilfields with temperatures between 55°C and 75°C. Both 16S rRNA and hzo molecular biomarkers indicated the occurrence of anammox bacteria in nine out of 17 samples. Most of 16S rRNA gene phylotypes are closely related to the known anammox bacterial genera Candidatus Brocadia, Candidatus Kuenenia, Candidatus Scalindua, and Candidatus Jettenia, while hzo gene phylotypes are closely related to the genera Candidatus Anammoxoglobus, Candidatus Kuenenia, Candidatus Scalindua, and Candidatus Jettenia. The total bacterial and anammox bacterial densities were 6.4 ± 0.5 × 103 to 2.0 ± 0.18 × 106 cells ml−1 and 6.6 ± 0.51 × 102 to 4.9 ± 0.36 × 104 cell ml−1, respectively. The cluster I of 16S rRNA gene sequences showed distant identity (<92%) to the known Candidatus Scalindua species, inferring this cluster of anammox bacteria to be a new species, and a tentative name Candidatus “Scalindua sinooilfield” was proposed. The results extended the existence of anammox bacteria to the high-temperature oil reservoirs

Thermal Adaptation of Dihydrofolate Reductase from the Moderate ThermophileGeobacillus stearothermophilus

The thermal melting temperature of dihydrofolate reductase from Geobacillus stearothermophilus (BsDHFR) is 30 °C higher than that of its homologue from the psychrophile Moritella profunda. Additional proline residues in the loop regions of BsDHFR have been proposed to enhance the thermostability of BsDHFR, but site-directed mutagenesis studies reveal that these proline residues contribute only minimally. Instead, the high thermal stability of BsDHFR is partly due to removal of water-accessible thermolabile residues such as glutamine and methionine, which are prone to hydrolysis or oxidation at high temperatures. The extra thermostability of BsDHFR can be obtained by ligand binding, or in the presence of salts or cosolvents such as glycerol and sucrose. The sum of all these incremental factors allows BsDHFR to function efficiently in the natural habitat of G. stearothermophilus, which is characterized by temperatures that can reach 75 °C

A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns

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

Phylogeny in Aid of the Present and Novel Microbial Lineages: Diversity in Bacillus

Bacillus represents microbes of high economic, medical and biodefense importance. Bacillus strain identification based on 16S rRNA sequence analyses is invariably limited to species level. Secondly, certain discrepancies exist in the segregation of Bacillus subtilis strains. In the RDP/NCBI databases, out of a total of 2611 individual 16S rDNA sequences belonging to the 175 different species of the genus Bacillus, only 1586 have been identified up to species level. 16S rRNA sequences of Bacillus anthracis (153 strains), B. cereus (211 strains), B. thuringiensis (108 strains), B. subtilis (271 strains), B. licheniformis (131 strains), B. pumilus (83 strains), B. megaterium (47 strains), B. sphaericus (42 strains), B. clausii (39 strains) and B. halodurans (36 strains) were considered for generating species-specific framework and probes as tools for their rapid identification. Phylogenetic segregation of 1121, 16S rDNA sequences of 10 different Bacillus species in to 89 clusters enabled us to develop a phylogenetic frame work of 34 representative sequences. Using this phylogenetic framework, 305 out of 1025, 16S rDNA sequences presently classified as Bacillus sp. could be identified up to species level. This identification was supported by 20 to 30 nucleotides long signature sequences and in silico restriction enzyme analysis specific to the 10 Bacillus species. This integrated approach resulted in identifying around 30% of Bacillus sp. up to species level and revealed that B. subtilis strains can be segregated into two phylogenetically distinct groups, such that one of them may be renamed