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Record W4387616233 · doi:10.3897/aca.6.e108135

Surface reactivity of the iron and manganese-oxidizing bacterium Leptothrix cholodnii SP-6

2023· article· en· W4387616233 on OpenAlexaff
M. Adelina Santos Araujo, Daniela Gutierrez Rueda, Yuhao Li, Janice Kenney, Daniel S. Alessi, Kurt O. Konhauser

Bibliographic record

VenueARPHA Conference Abstracts · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsMacEwan UniversityUniversity of Alberta
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsChemistryOxidizing agentAdsorptionAqueous solutionExtracellular polymeric substanceManganeseBiomineralizationChemical engineeringBacteriaBiofilmBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Surfaces of prokaryotic cells play a significant role in the adsorption of metals from aqueous solution and the formation of authigenic minerals (Konhauser 2006). Although most studies focus on the cell wall, it is known that many bacteria synthesise an extracellular layer of polysaccharides and proteins, including what are known as sheaths. It has been shown that the cyanobacterium Calothrix sp. produces as sheath which is neutrally charged at circumneutral pH values, and it was hypothesized that such a sheath might allow the cyanobacterium to survive in geothermal settings with high silicification rates (Phoenix et al. 2002). Specifically, the dominance of hydroxyl sites on Calothrix ’s sheath surface facilitates hydrogen bonding with aqueous silica species, inducing the precipitation of amorphous silica on the sheath and thus protecting the underlying cell (Phoenix et al. 2002). Leptothrix cholodnii is a sheathed, iron and manganese-oxidizing bacterium that frequently inhabits minerals seeps, where Fe 2+ and Mn 2+ discharge into oxygenated surface waters (Spring et al. 1996). As a result, the sheath becomes encrusted with Fe(III) and Mn(IV) oxyhydroxides while the underlying cells are protected from mineralization (Emerson and Ghiorse 1992, Emerson et al. 2010). However, unlike Calothrix, Leptothrix’ s sheath composition suggests that it might behave differently at circumneutral pH (Emerson and Ghiorse 1993). To investigate the surface reactivity of Leptothrix 's sheath and cell wall we analyzed isolated sheaths, sheathless cells, and intact filaments of L. cholodnii SP-6. We studied these components using potentiometric titration, zeta-potential, Cd-adsorption, and Fourier transform infrared (FTIR) spectroscopy to elucidate changes in surface charge between the cell wall and sheath. For the isolated sheaths and intact filaments, titration data were fit using a two-site protonation model, resulting in the following pKa values: 6.05 (±0.29) and 9.34 (±0.11); and 7.77 (±0.17) and 10.50 (±0.20), respectively. For the sheathless cells, the best fit was obtained by using a three-site protonation model, resulting in the following pKa values: 5.40 (±0.59), 8.11 (±1.64) and 10.73 (±0.45). Total proton-active site concentrations were lower in isolated sheaths compared to intact filaments. Additionally, at circumneutral pH, net negative charge was lower for sheathless cells compared to intact filaments and isolated sheaths (Fig. 1). This information agrees with the Cd adsorption behaviour found for the three materials (Fig. 2). Thus, our preliminary results suggest that Leptothrix ’s sheath is less reactive than the intact filaments at circumneutral pH, leading us to hypothesize that the outermost layer would sequester relatively lower amounts of cations, including Mn 2+ , from solution and potentially would protect the underlaying cell from deleterious mineralization. In addition to that, the less reactive sheath’s surface would also contribute to cell attachment, which is important for a species commonly found in streams (Phoenix et al. 2002, Emerson et al. 2010).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.221
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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