Complete Genome Sequence of
            <i>Pelosinus</i>
            sp. Strain UFO1 Assembled Using Single-Molecule Real-Time DNA Sequencing Technology

Brown, Steven D.; Utturkar, Sagar M.; Magnuson, Timothy S.; Ray, Allison E.; Poole, Farris L.; Lancaster, W. Andrew; Thorgersen, Michael P.; Adams, Michael W. W.; Elias, Dwayne A.

doi:10.1128/genomea.00881-14

Cited by 19 publications

(19 citation statements)

References 18 publications

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“…The need for a completeness-independent sieving approach Although we are able to obtain complete or nearcomplete genomes more readily than before, due to recently emerging long-read sequencing technologies such as single-molecule, real-time (SMRT) and Oxford Nanopore MinION sequencing [34][35][36][37], it is still difficult to Fig. 8 Sieving performance on metagenome-assembled genomes (MAGs).…”

Section: Discussionmentioning

confidence: 99%

A completeness-independent method for pre-selection of closely related genomes for species delineation in prokaryotes

Zhou

Zheng

et al. 2020

BMC Genomics

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Background: Whole-genome approaches are widely preferred for species delineation in prokaryotes. However, these methods require pairwise alignments and calculations at the whole-genome level and thus are computationally intensive. To address this problem, a strategy consisting of sieving (pre-selecting closely related genomes) followed by alignment and calculation has been proposed.Results: Here, we initially test a published approach called "genome-wide tetranucleotide frequency correlation coefficient" (TETRA), which is specially tailored for sieving. Our results show that sieving by TETRA requires > 40% completeness for both genomes of a pair to yield > 95% sensitivity, indicating that TETRA is completenessdependent. Accordingly, we develop a novel algorithm called "fragment tetranucleotide frequency correlation coefficient" (FRAGTE), which uses fragments rather than whole genomes for sieving. Our results show that FRAGTE achieves~100% sensitivity and high specificity on simulated genomes, real genomes and metagenome-assembled genomes, demonstrating that FRAGTE is completeness-independent. Additionally, FRAGTE sieved a reduced number of total genomes for subsequent alignment and calculation to greatly improve computational efficiency for the process after sieving. Aside from this computational improvement, FRAGTE also reduces the computational cost for the sieving process. Consequently, FRAGTE extremely improves run efficiency for both the processes of sieving and after sieving (subsequent alignment and calculation) to together accelerate genome-wide species delineation.Conclusions: FRAGTE is a completeness-independent algorithm for sieving. Due to its high sensitivity, high specificity, highly reduced number of sieved genomes and highly improved runtime, FRAGTE will be helpful for whole-genome approaches to facilitate taxonomic studies in prokaryotes.

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Section: Discussionmentioning

confidence: 99%

A completeness-independent method for pre-selection of closely related genomes for species delineation in prokaryotes

Zhou

Zheng

et al. 2020

BMC Genomics

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“…Peptides were analyzed using a Bruker Daltonics Autoflex MALDI-time of flight mass spectrometer in reflection mode using positive ion detection. The mass list was analyzed using Mascot's peptide mass fingerprint tool (version 2.1, Matrix Science) against the published genome sequence of strain UFO1 (11).…”

Section: Methodsmentioning

confidence: 99%

“…This strictly anaerobic fermentative firmicute was isolated from an uncontaminated background well at the Oak Ridge Reservation (ORR) in Tennessee (10), one of the DOE facilities that has areas of uranium contamination (3). The genome of strain UFO1 has been sequenced (11). Although the organism was not grown in the presence of added uranium, cell suspensions of strain UFO1 were previously shown to sequester uranium in two different oxidation states (12).…”

mentioning

confidence: 99%

A Highly Expressed High-Molecular-Weight S-Layer Complex of Pelosinus sp. Strain UFO1 Binds Uranium

Thorgersen

Lancaster

Rajeev

et al. 2017

Appl Environ Microbiol

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Cell suspensions of Pelosinus sp. strain UFO1 were previously shown, using spectroscopic analysis, to sequester uranium as U(IV) complexed with carboxyl and phosphoryl group ligands on proteins. The goal of our present study was to characterize the proteins involved in uranium binding. Virtually all of the uranium in UFO1 cells was associated with a heterodimeric protein, which was termed the uranium-binding complex (UBC). The UBC was composed of two S-layer domain proteins encoded by UFO1_4202 and UFO1_4203. Samples of UBC purified from the membrane fraction contained 3.3 U atoms/heterodimer, but significant amounts of phosphate were not detected. The UBC had an estimated molecular mass by gel filtration chromatography of 15 MDa, and it was proposed to contain 150 heterodimers (UFO1_4203 and UFO1_4202) and about 500 uranium atoms. The UBC was also the dominant extracellular protein, but when purified from the growth medium, it contained only 0.3 U atoms/heterodimer. The two genes encoding the UBC were among the most highly expressed genes within the UFO1 genome, and their expressions were unchanged by the presence or absence of uranium. Therefore, the UBC appears to be constitutively expressed and is the first line of defense against uranium, including by secretion into the extracellular medium. Although S-layer proteins were previously shown to bind U(VI), here we showed that U(IV) binds to S-layer proteins, we identified the proteins involved, and we quantitated the amount of uranium bound.IMPORTANCE Widespread uranium contamination from industrial sources poses hazards to human health and to the environment. Herein, we identified a highly abundant uranium-binding complex (UBC) from Pelosinus sp. strain UFO1. The complex makes up the primary protein component of the S-layer of strain UFO1 and binds 3.3 atoms of U(IV) per heterodimer. While other bacteria have been shown to bind U(VI) on their S-layer, we demonstrate here an example of U(IV) bound by an S-layer complex. The UBC provides a potential tool for the microbiological sequestration of uranium for the cleaning of contaminated environments.KEYWORDS contamination, uranium sequestration, uranium-binding protein U ranium is highly toxic and is also a radionuclide with a long half-life (1). Uranium mining, milling, and other anthropogenic industrial activities have led to widespread environmental contamination with associated hazards to human health and to the environment (2). In the United States, the U.S. Department of Energy (DOE) oversees the monitoring and restoration of waste sites at 12 facilities contaminated with uranium (3). Uranium is present in oxic fresh water as highly soluble U(VI). At pH values lower than 5.0, U(VI) is predominantly found as the free uranyl ion (UO 2 2ϩ ), and between pH values of 5.0 and 7.5, U(VI) is predominantly complexed with carbonate. At pH values

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“…In terms of throughput per run, read length and accuracy, each platform has different specific features that make them useful for particular applications. Moreover, the newly emerged third-generation sequencing techniques, such as PacBio (Brown et al, 2014) and MinION (Quick et al, 2014), are performed on a single-molecule basis with no necessary initial DNA amplification step. These newer technologies can produce much longer reads compared with the second-generation sequencing platforms and have the potential to be less costly and less time-consuming.…”

Section: Characterization Of the Microbiome Using High-throughput Tecmentioning

confidence: 99%

Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine

et al. 2016

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It has been experimentally shown that host-microbial interaction plays a major role in shaping the wellness or disease of the human body. Microorganisms coexisting in human tissues provide a variety of benefits that contribute to proper functional activity in the host through the modulation of fundamental processes such as signal transduction, immunity and metabolism. The unbalance of this microbial profile, or dysbiosis, has been correlated with the genesis and evolution of complex diseases such as cancer. Although this latter disease has been thoroughly studied using different high-throughput (HT) technologies, its heterogeneous nature makes its understanding and proper treatment in patients a remaining challenge in clinical settings. Notably, given the outstanding role of host-microbiome interactions, the ecological interactions with microorganisms have become a new significant aspect in the systems that can contribute to the diagnosis and potential treatment of solid cancers. As a part of expanding precision medicine in the area of cancer research, efforts aimed at effective treatments for various kinds of cancer based on the knowledge of genetics, biology of the disease and host-microbiome interactions might improve the prediction of disease risk and implement potential microbiota-directed therapeutics. In this review, we present the state of the art of sequencing and metabolome technologies, computational methods and schemes in systems biology that have addressed recent breakthroughs of uncovering relationships or associations between microorganisms and cancer. Together, microbiome studies extend the horizon of new personalized treatments against cancer from the perspective of precision medicine through a synergistic strategy integrating clinical knowledge, HT data, bioinformatics, and systems biology.

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Complete Genome Sequence of Pelosinus sp. Strain UFO1 Assembled Using Single-Molecule Real-Time DNA Sequencing Technology

Cited by 19 publications

References 18 publications

A completeness-independent method for pre-selection of closely related genomes for species delineation in prokaryotes

A completeness-independent method for pre-selection of closely related genomes for species delineation in prokaryotes

A Highly Expressed High-Molecular-Weight S-Layer Complex of Pelosinus sp. Strain UFO1 Binds Uranium

Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine

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