Bacterial Fe(II) oxidation distinguished by long‐range correlation in redox potential

Enright, Allison; Ferris, F. G.

doi:10.1002/2015jg003306

Cited by 11 publications

(7 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The variation between α values indicates that biological processes give rise to stronger correlation of time series measurements of fluctuations in redox potential in the systems studied here. This is consistent with results of correlation analysis recently reported for low biomass and high biomass circumneutral, microaerophilic Fe(II)oxidizing systems (Enright and Ferris, 2016), where the low biomass condition gave rise to a scaling exponent of 1.67, and the high biomass condition gave rise to a scaling exponent of 1.89 (Enright and Ferris, 2016).…”

Section: Biogeochemical Significancesupporting

confidence: 92%

Fluctuation Analysis of Redox Potential to Distinguish Microbial Fe(II) Oxidation

Enright¹,

Ferris²

2017

Preprint

View full text Add to dashboard Cite

We developed a novel method for distinguishing abiotic and biological iron oxidation in liquid media using oxidation-reduction (redox) potential time series data. The instrument and processing algorithm were tested by immersing the tip of a Pt electrode with an Ag-AgCl reference electrode, into an active iron-oxidizing biofilm in a groundwater discharge zone, as well as in two abiotic systems: a killed sample and a chemical control from the same site. We used detrended fluctuation analysis to characterize average root-mean-square fluctuation behaviour, which was distinct in the live system. The calculated α value scaling exponents determined by detrended fluctuation analysis were significantly different at p < 0.001. This indicates that time series of electrode response data may be used to distinguish live and abiotic chemical reaction pathways. Due to the simplicity, portability, and small size, it may be suitable for characterization of extraterrestrial environments where water has been observed, such as Mars and Europa.

show abstract

Section: Biogeochemical Significancesupporting

confidence: 92%

Fluctuation Analysis of Redox Potential to Distinguish Microbial Fe(II) Oxidation

Enright¹,

Ferris²

2017

Preprint

View full text Add to dashboard Cite

show abstract

“…In more recent times, other studies have targeted the investigation of soil biogeochemistry and transient redox conditions caused by the water table fluctuations [20] and observed a decreasing soil Eh after the addition of glucose [21]. Enright et al [22,23] demonstrated a distinguishable biological signal by immersing a pair of electrodes in an iron-oxidizing biofilm. Graphite electrode experiments have also been used to investigate the rates of anaerobic microbial activity in a diversity of anoxic sediments [24].…”

Section: Introductionmentioning

confidence: 99%

Metabolt: An In-Situ Instrument to Characterize the Metabolic Activity of Microbial Soil Ecosystems Using Electrochemical and Gaseous Signatures

Nazarious

Zorzano

Martín-Torres

2020

Sensors

View full text Add to dashboard Cite

Metabolt is a portable soil incubator to characterize the metabolic activity of microbial ecosystems in soils. It measures the electrical conductivity, the redox potential, and the concentration of certain metabolism-related gases in the headspace just above a given sample of regolith. In its current design, the overall weight of Metabolt, including the soils (250 g), is 1.9 kg with a maximum power consumption of 1.5 W. Metabolt has been designed to monitor the activity of the soil microbiome for Earth and space applications. In particular, it can be used to monitor the health of soils, the atmospheric-regolith fixation, and release of gaseous species such as N2, H2O, CO2, O2, N2O, NH3, etc., that affect the Earth climate and atmospheric chemistry. It may be used to detect and monitor life signatures in soils, treated or untreated, as well as in controlled environments like greenhouse facilities in space, laboratory research environments like anaerobic chambers, or simulating facilities with different atmospheres and pressures. To illustrate its operation, we tested the instrument with sub-arctic soil samples at Earth environmental conditions under three different conditions: (i) no treatment (unperturbed); (ii) sterilized soil: after heating at 125 °C for 35.4 h (thermal stress); (iii) stressed soil: after adding 25% CaCl2 brine (osmotic stress); with and without addition of 0.5% glucose solution (for control). All the samples showed some distinguishable metabolic response, however there was a time delay on its appearance which depends on the treatment applied to the samples: 80 h for thermal stress without glucose, 59 h with glucose; 36 h for osmotic stress with glucose and no significant reactivation in the pure water case. This instrument shows that, over time, there is a clear observable footprint of the electrochemical signatures in the redox profile which is complementary to the gaseous footprint of the metabolic activity through respiration.

show abstract

“…While informative, these results only hint at the underlying mechanisms and bioenergetic capacity of FeOB to catalyze otherwise spontaneous abiotic Fe(II) oxidation rates. More recently, the statistical dependence (i.e., long-range correlation, also known as memory or persistence) of temporal fluctuations in electrochemical measurements of redox potential on a time scale of minutes to seconds were found to distinguish bacterial and abiotic Fe(II) oxidation 7,25 . Long-range correlation in a time series implies that any measured value is statistically dependent on preceding values, and can take the form of positive correlation (a past increasing trend will continue to increase into the future) or negative correlation (an increasing trend is likely to be followed by a decreasing trend) 26,27 .…”

Section: Introductionmentioning

confidence: 99%

“…Long-range correlation in a time series implies that any measured value is statistically dependent on preceding values, and can take the form of positive correlation (a past increasing trend will continue to increase into the future) or negative correlation (an increasing trend is likely to be followed by a decreasing trend) 26,27 . Such correlative dependence has proven to be consistently more pronounced for bacterial Fe(II) oxidation than abiotic Fe(II) oxidation 25 ; thus, the parameter of correlation strength, measured by detrended fluctuation analysis (DFA) scaling exponents ( α ), can feasibly be used to distinguish microbially-catalyzed Fe(II) oxidation from homogenous and heterogeneous chemical oxidation. This new approach to investigating bacterial Fe(II) oxidation is compelling in light of the fact that the Gibbs free energy (Δ G r ) of an oxidation-reduction reaction is an explicit thermodynamic function of redox potential.…”

Section: Introductionmentioning

confidence: 99%

Long Range Correlation in Redox Potential Fluctuations Signals Energetic Efficiency of Bacterial Fe(II) Oxidation

Enright

Edwards

Ferris

2019

Sci Rep

Self Cite

View full text Add to dashboard Cite

Differentiating biotic and abiotic processes in nature remains a persistent challenge, specifically in evaluating microbial contributions to geochemical processes through time. Building on previous work reporting that biologically-influenced systems exhibit stronger long-range correlation than abiotic systems, this study evaluated the relationship between long-range correlation of redox potential and oxidation rates of circumneutral microaerophilic bacterial Fe(II) oxidation using a series of batch microcosms with bacteriogenic iron oxides (BIOS). Initial detrended fluctuation analysis (DFA) scaling exponents of the abiotic microcosms were lower (ca. 1.20) than those of the biotic microcosms (ca. 1.80). As Fe(II) oxidation proceeded, correlation strength decayed as a logistic function of elapsed reaction time, exhibiting direct dependence on the free energy of reaction. Correlation strength for all microcosms decayed sharply from strong correlation to uncorrelated fluctuations. The decay rates are greater for abiotic microcosms than biotic microcosms. The ΔGm relaxation edges for biotic microcosms were lower, indicating less remaining free energy for Fe(II) oxidation than abiotic systems, with the implication that biologically-catalyzed reactions are likely more energetically efficient than abiotic reactions. These results strengthen the case for employing novel DFA techniques to distinguish in situ microbial metabolic activity from abiotic processes, as well as to potentially differentiate metabolisms among different chemoautotrophs.

show abstract

Bacterial Fe(II) oxidation distinguished by long‐range correlation in redox potential

Abstract: The kinetics of bacterial Fe(II) - Index Terms0412 Biogeochemical kinetics and reaction modelling 0448 Geomicrobiology

Cited by 11 publications

References 50 publications

Fluctuation Analysis of Redox Potential to Distinguish Microbial Fe(II) Oxidation

Fluctuation Analysis of Redox Potential to Distinguish Microbial Fe(II) Oxidation

Metabolt: An In-Situ Instrument to Characterize the Metabolic Activity of Microbial Soil Ecosystems Using Electrochemical and Gaseous Signatures

Long Range Correlation in Redox Potential Fluctuations Signals Energetic Efficiency of Bacterial Fe(II) Oxidation

Contact Info

Product

Resources

About