Nitrite-oxidizing bacteria (NOB) play a critical role in the mitigation of nitrogen pollution by metabolizing nitrite to nitrate, which is removed via assimilation, denitrification, or anammox. Recent studies showed that NOB are phylogenetically and metabolically diverse, yet most of our knowledge of NOB comes from only a few cultured representatives. Using cultivation and genomic sequencing, we identified four putative Candidatus Nitrotoga NOB species from freshwater sediments and water column samples in Colorado, USA. Genome analyses indicated highly conserved 16S rRNA gene sequences, but broad metabolic potential including genes for nitrogen, sulfur, hydrogen, and organic carbon metabolism. Genomic predictions suggested that Ca. Nitrotoga can metabolize in low oxygen or anoxic conditions, which may support an expanded environmental niche for Ca. Nitrotoga similar to other NOB. An array of antibiotic and metal resistance genes likely allows Ca. Nitrotoga to withstand environmental pressures in impacted systems. Phylogenetic analyses highlighted a deeply divergent nitrite oxidoreductase alpha subunit (NxrA), suggesting a novel evolutionary trajectory for Ca. Nitrotoga separate from any other NOB and further revealing the complex evolutionary history of nitrite oxidation in the bacterial domain. Ca. Nitrotoga-like 16S rRNA gene sequences were prevalent in globally distributed environments over a range of reported temperatures. This work considerably expands our knowledge of the Ca. Nitrotoga genus and suggests that their contribution to nitrogen cycling should be considered alongside other NOB in wide variety of habitats.
Western honey bees (Apis mellifera) are important pollinators in natural and agricultural ecosystems, and yet are in significant decline due to several factors including parasites, pathogens, pesticides, and habitat loss. A new beehive construction called the FlowTM hive was developed in 2015 to allow honey to be harvested directly from the hive without opening it, resulting in an apparent decrease in stress to the bees. Here, we compared the Flow and traditional Langstroth hive constructions to determine if there were any significant differences in the bee microbiome. The bee-associated bacterial communities did not differ between hive constructions and varied only slightly over the course of a honey production season. Samples were dominated by taxa belonging to the Lactobacillus, Bifidobacterium, Bartonella, Snodgrassella, Gilliamella, and Frischella genera, as observed in previous studies. The top ten most abundant taxa made up the majority of the sequence data; however, many low abundance organisms were persistent across the majority of samples regardless of sampling time or hive type. We additionally compared different preparations of whole bee and dissected bee samples to elaborate on previous bee microbiome research. We found that bacterial sequences were overwhelming derived from the bee guts, and microbes on the bee surfaces (including pollen) contributed little to the overall microbiome of whole bees. Overall, the results indicate that different hive constructions and associated disturbance levels do not influence the bee gut microbiome, which has broader implications for supporting hive health.
Extremely acidic and metal-rich acid mine drainage (AMD) waters can have severe toxicological effects on aquatic ecosystems. AMD has been shown to completely halt nitrification, which plays an important role in transferring nitrogen to higher organisms and in mitigating nitrogen pollution. We evaluated the gene abundance and diversity of nitrifying microbes in AMD-impacted sediments: ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB), and nitrite-oxidizing bacteria (NOB). Samples were collected from the Iron Springs Mining District (Ophir, CO, United States) during early and late summer in 2013 and 2014. Many of the sites were characterized by low pH (<5) and high metal concentrations. Sequence analyses revealed AOA genes related to Nitrososphaera, Nitrosotalea, and Nitrosoarchaeum; AOB genes related to Nitrosomonas and Nitrosospira; and NOB genes related to Nitrospira. The overall abundance of AOA, AOB and NOB was examined using quantitative PCR (qPCR) amplification of the amoA and nxrB functional genes and 16S rRNA genes. Gene copy numbers ranged from 3.2 × 104 – 4.9 × 107 archaeal amoA copies ∗ μg DNA-1, 1.5 × 103 – 5.3 × 105 AOB 16S rRNA copies ∗ μg DNA-1, and 1.3 × 106 – 7.7 × 107 Nitrospira nxrB copies ∗ μg DNA-1. Overall, Nitrospira nxrB genes were found to be more abundant than AOB 16S rRNA and archaeal amoA genes in most of the sample sites across 2013 and 2014. AOB 16S rRNA and Nitrospira nxrB genes were quantified in sediments with pH as low as 3.2, and AOA amoA genes were quantified in sediments as low as 3.5. Though pH varied across all sites (pH 3.2–8.3), pH was not strongly correlated to the overall community structure or relative abundance of individual OTUs for any gene (based on CCA and Spearman correlations). pH was positivity correlated to the total abundance (qPCR) of AOB 16S rRNA genes, but not for any other genes. Metals were not correlated to the overall nitrifier community composition or abundance, but were correlated to the relative abundances of several individual OTUs. These findings extend our understanding of the distribution of nitrifying microbes in AMD-impacted systems and provide a platform for further research.
We present avidity sequencing, a sequencing chemistry that separately optimizes the processes of stepping along a DNA template and that of identifying each nucleotide within the template. Nucleotide identification uses multivalent nucleotide ligands on dye-labeled cores to form polymerase–polymer–nucleotide complexes bound to clonal copies of DNA targets. These polymer–nucleotide substrates, termed avidites, decrease the required concentration of reporting nucleotides from micromolar to nanomolar and yield negligible dissociation rates. Avidity sequencing achieves high accuracy, with 96.2% and 85.4% of base calls having an average of one error per 1,000 and 10,000 base pairs, respectively. We show that the average error rate of avidity sequencing remained stable following a long homopolymer.
We present avidity sequencing - a novel sequencing chemistry that separately optimizes the process of stepping along a DNA template and the process of identifying each nucleotide within the template. Nucleotide identification uses multivalent nucleotide ligands on dye-labeled cores to form polymerase-polymer nucleotide complexes bound to clonal copies of DNA targets. These polymer-nucleotide substrates, termed avidites, decrease the required concentration of reporting nucleotides from micromolar to nanomolar, and yield negligible dissociation rates. We demonstrate the use of avidites as a key component of a sequencing technology that surpasses Q40 accuracy and enables a diversity of applications that include single cell RNA-seq and whole human genome sequencing. We also show the advantages of this technology in sequencing through long homopolymers.
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