Unravelling the reasons for disproportion in the ratio of AOB and NOB in aerobic granular sludge

In this study, we analysed the nitrifying microbial community (ammonium-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB)) within three different aerobic granular sludge treatment systems as well as within one flocculent sludge system. Granular samples were taken from one pilot plant run on municipal wastewater as well as from two lab-scale reactors. Fluorescent in situ hybridization (FISH) and quantitative PCR (qPCR) showed that Nitrobacter was the dominant NOB in acetate-fed aerobic granules. In the conventional system, both Nitrospira and Nitrobacter were present in similar amounts. Remarkably, the NOB/AOB ratio in aerobic granular sludge was elevated but not in the conventional treatment plant suggesting that the growth of Nitrobacter within aerobic granular sludge, in particular, was partly uncoupled from the lithotrophic nitrite supply from AOB. This was supported by activity measurements which showed an approximately threefold higher nitrite oxidizing capacity than ammonium oxidizing capacity. Based on these findings, two hypotheses were considered: either Nitrobacter grew mixotrophically by acetate-dependent dissimilatory nitrate reduction (ping-pong effect) or a nitrite oxidation/nitrate reduction loop (nitrite loop) occurred in which denitrifiers reduced nitrate to nitrite supplying additional nitrite for the NOB apart from the AOB

Review of the algal biology program within the National Alliance for Advanced Biofuels and Bioproducts

In 2010, when the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortium began, little was known about the molecular basis of algal biomass or oil production. Very few algal genome sequences were available and efforts to identify the best-producing wild species through bioprospecting approaches had largely stalled after the U.S. Department of Energy's Aquatic Species Program. This lack of knowledge included how reduced carbon was partitioned into storage products like triglycerides or starch and the role played by metabolite remodeling in the accumulation of energy-dense storage products. Furthermore, genetic transformation and metabolic engineering approaches to improve algal biomass and oil yields were in their infancy. Genome sequencing and transcriptional profiling were becoming less expensive, however; and the tools to annotate gene expression profiles under various growth and engineered conditions were just starting to be developed for algae. It was in this context that an integrated algal biology program was introduced in the NAABB to address the greatest constraints limiting algal biomass yield. This review describes the NAABB algal biology program, including hypotheses, research objectives, and strategies to move algal biology research into the twenty-first century and to realize the greatest potential of algae biomass systems to produce biofuels

Methylobacterium Genome Sequences: A Reference Blueprint to Investigate Microbial Metabolism of C1 Compounds from Natural and Industrial Sources

Methylotrophy describes the ability of organisms to grow on reduced organic compounds without carbon-carbon bonds. The genomes of two pink-pigmented facultative methylotrophic bacteria of the Alpha-proteobacterial genus Methylobacterium, the reference species Methylobacterium extorquens strain AM1 and the dichloromethane-degrading strain DM4, were compared. Methodology/Principal Findings The 6.88 Mb genome of strain AM1 comprises a 5.51 Mb chromosome, a 1.26 Mb megaplasmid and three plasmids, while the 6.12 Mb genome of strain DM4 features a 5.94 Mb chromosome and two plasmids. The chromosomes are highly syntenic and share a large majority of genes, while plasmids are mostly strain-specific, with the exception of a 130 kb region of the strain AM1 megaplasmid which is syntenic to a chromosomal region of strain DM4. Both genomes contain large sets of insertion elements, many of them strain-specific, suggesting an important potential for genomic plasticity. Most of the genomic determinants associated with methylotrophy are nearly identical, with two exceptions that illustrate the metabolic and genomic versatility of Methylobacterium. A 126 kb dichloromethane utilization (dcm) gene cluster is essential for the ability of strain DM4 to use DCM as the sole carbon and energy source for growth and is unique to strain DM4. The methylamine utilization (mau) gene cluster is only found in strain AM1, indicating that strain DM4 employs an alternative system for growth with methylamine. The dcm and mau clusters represent two of the chromosomal genomic islands (AM1: 28; DM4: 17) that were defined. The mau cluster is flanked by mobile elements, but the dcm cluster disrupts a gene annotated as chelatase and for which we propose the name “island integration determinant” (iid).Conclusion/Significance These two genome sequences provide a platform for intra- and interspecies genomic comparisons in the genus Methylobacterium, and for investigations of the adaptive mechanisms which allow bacterial lineages to acquire methylotrophic lifestyles.Organismic and Evolutionary Biolog

Meta-omics approaches to understand and improve wastewater treatment systems

Biological treatment of wastewaters depends on microbial processes, usually carried out by mixed microbial communities. Environmental and operational factors can affect microorganisms and/or impact microbial community function, and this has repercussion in bioreactor performance. Novel high-throughput molecular methods (metagenomics, metatranscriptomics, metaproteomics, metabolomics) are providing detailed knowledge on the microorganisms governing wastewater treatment systems and on their metabolic capabilities. The genomes of uncultured microbes with key roles in wastewater treatment plants (WWTP), such as the polyphosphate-accumulating microorganism Candidatus Accumulibacter phosphatis, the nitrite oxidizer Candidatus Nitrospira defluvii or the anammox bacterium Candidatus Kuenenia stuttgartiensis are now available through metagenomic studies. Metagenomics allows to genetically characterize full-scale WWTP and provides information on the lifestyles and physiology of key microorganisms for wastewater treatment. Integrating metagenomic data of microorganisms with metatranscriptomic, metaproteomic and metabolomic information provides a better understanding of the microbial responses to perturbations or environmental variations. Data integration may allow the creation of predictive behavior models of wastewater ecosystems, which could help in an improved exploitation of microbial processes. This review discusses the impact of meta-omic approaches on the understanding of wastewater treatment processes, and the implications of these methods for the optimization and design of wastewater treatment bioreactors.Research was supported by the Spanish Ministry of Education and Science (Contract Project CTQ2007-64324 and CONSOLIDER-CSD 2007-00055) and the Regional Government of Castilla y Leon (Ref. VA038A07). Research of AJMS is supported by the European Research Council (Grant 323009

High sensitivity organic inorganic hybrid X-ray detectors with direct transduction and broadband response

X-ray detectors are critical to healthcare diagnostics, cancer therapy and homeland security, with many potential uses limited by system cost and/or detector dimensions. Current X-ray detector sensitivities are limited by the bulk X-ray attenuation of the materials and consequently necessitate thick crystals (~1 mm-1 cm), resulting in rigid structures, high operational voltages and high cost. Here we present a disruptive, flexible, low cost, broadband, and high sensitivity direct X-ray transduction technology produced by embedding high atomic number bismuth oxide nanoparticles in an organic bulk heterojunction. These hybrid detectors demonstrate sensitivities of 1712 µC mGy-1 cm-3 for "soft" X-rays and ~30 and 58 µC mGy-1 cm-3 under 6 and 15 MV "hard" X-rays generated from a medical linear accelerator; strongly competing with the current solid state detectors, all achieved at low bias voltages (-10 V) and low power, enabling detector operation powered by coin cell batteries