Oxidative Formation and Removal of Complexed Mn(III) by Pseudomonas Species

Wright, Mitchell Henry; Geszvain, Kati; Oldham, Véronique E.; Luther, George W.; Tebo, Bradley M.

doi:10.3389/fmicb.2018.00560

Cited by 31 publications

(23 citation statements)

References 43 publications

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“…[9][10] The ability of strain GSL-010 T to form and remove of Mn(III)-L complexes has only recently been investigated and published by the authors. 10 The isolation of strain GSL-010 T highlights the first instance of a bacterium obtained through the observation of Mn(IV) oxide formation from Mn(III)-L oxidation. The results of phenotypical and physiological characterization are given in Table 1 and in the species description.…”

Section: Methods and Resultsmentioning

confidence: 99%

“…Purification of genomic DNA was achieved using the Wizard ® Genomic DNA Purification Kit (Promega) as per the manufacturer's instructions and confirmed as previously described. 10 The 16S rRNA gene was amplified with the primer set 27F (5'-AGA GTT TGA TCC TGG CTC AG-3') and 1492R (5'-CGG TTA CCT TGT TAC GAC TT-3') using the GoTaq ® Green Master Mix (Promega) as previously described. 12 The 16S rRNA PCR amplicon was sequenced using primers 27F, 1492R, 785F (5'-GGA TTA GAT ACC CTG GTA-3') and 518R (5'-GTA TTA CCG CGG CTG CTG G-3').…”

Section: Methods and Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Pseudomonas laurentiana sp. nov., an Mn(III)-oxidizing Bacterium Isolated from the St. Lawrence Estuary

Wright¹,

Hanna²,

Pica³

et al. 2018

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Introduction: An aerobic, Mn(III)-oxidizing, Gram-negative, motile bacterium (strain GSL-010T) was isolated from deep waters of the St Lawrence Estuary (Canada) and subjected to a polyphasic taxonomic study. Results: Cells were mostly curved, motile rods (1.75-2.2 x 0.5-0.7 µm) with growth observed at 10-37 ºC (optimum at 30 ºC), pH 5-10 (optimum at 7.0-7.5) and with 0-3% (w/v) NaCl (optimum at 0.5%). Phylogenetic analysis based on 16S rRNA gene sequencing revealed strain GSL-010 T as a member of the genus Pseudomonas, most closely related to the type strains of Pseudomonas plecoglossicida (98.9%) and Pseudomonas japonica (98.6%). The major cellular fatty acids of strain GSL-010 T are a combination of C 16:1 ω7c and/or iso-C 15:1 2-OH, C 16:0 and C 18:1 ω7c. The G+C mol content of the chromosomal DNA is 59.7%. The DNA-DNA hybridization values between strain GSL-010 T and P. plecoglossicida (32.0%) and P. japonica (34.4%) confirm the assignment of the bacterium to a new species. Conclusion: On the basis of phylogenetic analysis, DNA-DNA hy-bridization and physiological and biochemical characterization, strain GSL-010 T is clearly a unique bacterium and since it was isolated from the waters of the St. Lawrence estuary, the name Pseudomonas laurentiana sp. nov. is proposed.

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Section: Methods and Resultsmentioning

confidence: 99%

Section: Methods and Resultsmentioning

confidence: 99%

Pseudomonas laurentiana sp. nov., an Mn(III)-oxidizing Bacterium Isolated from the St. Lawrence Estuary

Wright¹,

Hanna²,

Pica³

et al. 2018

View full text Add to dashboard Cite

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“…However, recent studies have proposed that at least some siderophores may also bind to other metals. For example, the siderophore ferrioxamine was shown to bind manganese 57,58 , and Ybt was shown to bind copper as a means to evade toxicity 59 and to scavenge copper in vitro 60 . Nevertheless, the extent and biological relevance for siderophores binding to other metals remains largely unknown.…”

Section: Discussionmentioning

confidence: 99%

Siderophore-mediated zinc acquisition enhances enterobacterial colonization of the inflamed gut

Zhi

Behnsen

Aron

et al. 2020

Preprint

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Zinc is an essential cofactor for bacterial metabolism, and many Enterobacteriaceae express the zinc transporters ZnuABC and ZupT to acquire this metal in the host. Unexpectedly, the probiotic bacterium Escherichia coli Nissle 1917 exhibited appreciable growth in zinc-limited media even when these transporters were deleted. By utilizing in vitro and in vivo studies, as well as native spray metal infusion mass spectrometry and ion identity molecular networking, we discovered that Nissle utilizes yersiniabactin as a zincophore. Indeed, yersiniabactin enables Nissle to scavenge zinc in zinc-limited media, to resist calprotectin-mediated zinc sequestration, and to thrive in the inflamed gut. Moreover, we discovered that yersiniabactin’s affinity for iron or zinc changes in a pH-dependent manner, with higher affinity for zinc as the pH increased. Altogether, we demonstrate that siderophore metal affinity can be influenced by the local environment and reveal a mechanism of zinc acquisition available to many commensal and pathogenic Enterobacteriaceae.

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“…In the following, we denote ordering in each split or a priori as “Order (split)” and “Order (once),” respectively. We implemented both ordering schemes in the package (Wright, 2018). The package uses only plain R to allow easy modification of the RF splitting algorithm which is required for the Order (split) method.…”

Section: Methodsmentioning

confidence: 99%

Splitting on categorical predictors in random forests

Wright

König

2019

PeerJ

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One reason for the widespread success of random forests (RFs) is their ability to analyze most datasets without preprocessing. For example, in contrast to many other statistical methods and machine learning approaches, no recoding such as dummy coding is required to handle ordinal and nominal predictors. The standard approach for nominal predictors is to consider all 2k − 1 − 1 2-partitions of the k predictor categories. However, this exponential relationship produces a large number of potential splits to be evaluated, increasing computational complexity and restricting the possible number of categories in most implementations. For binary classification and regression, it was shown that ordering the predictor categories in each split leads to exactly the same splits as the standard approach. This reduces computational complexity because only k − 1 splits have to be considered for a nominal predictor with k categories. For multiclass classification and survival prediction no ordering method producing equivalent splits exists. We therefore propose to use a heuristic which orders the categories according to the first principal component of the weighted covariance matrix in multiclass classification and by log-rank scores in survival prediction. This ordering of categories can be done either in every split or a priori, that is, just once before growing the forest. With this approach, the nominal predictor can be treated as ordinal in the entire RF procedure, speeding up the computation and avoiding category limits. We compare the proposed methods with the standard approach, dummy coding and simply ignoring the nominal nature of the predictors in several simulation settings and on real data in terms of prediction performance and computational efficiency. We show that ordering the categories a priori is at least as good as the standard approach of considering all 2-partitions in all datasets considered, while being computationally faster. We recommend to use this approach as the default in RFs.

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Oxidative Formation and Removal of Complexed Mn(III) by Pseudomonas Species

Cited by 31 publications

References 43 publications

Pseudomonas laurentiana sp. nov., an Mn(III)-oxidizing Bacterium Isolated from the St. Lawrence Estuary

Pseudomonas laurentiana sp. nov., an Mn(III)-oxidizing Bacterium Isolated from the St. Lawrence Estuary

Siderophore-mediated zinc acquisition enhances enterobacterial colonization of the inflamed gut

Splitting on categorical predictors in random forests

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