Detection of Sulfate-Reducing Bacteria as an Indicator for Successful Mitigation of Sulfide Production.

Sulfate-reducing bacteria (SRBs) are one of the main sources of biogenic H2S generation in oil reservoirs. Excess H2S production in these systems leads to oil biosouring, which causes operational risks and health hazards and can increase the cost of refining crude oil. Nitrate salts are often added to the system to suppress sulfidogenesis. Because SRB populations can persist in biofilms even after nitrate treatment, identifying shifts in the sessile community is crucial for successful mitigation. However, sampling the sessile community is hampered by its inaccessibility. Here, we use the results of a long-term (148 days) ex situ experiment to identify particular sessile community members from observations of the sample waste stream. Microbial community structure was determined for 731 samples across 20 bioreactors using 16S rRNA gene sequencing. By associating microbial community structure with specific steps in the mitigation process, we could distinguish between taxa associated with H2S production and mitigation. After initiation of nitrate treatment, certain SRB populations increased in the planktonic community during critical time points, indicating the dissociation of SRBs from the biofilm. Predicted relative abundances of the dissimilatory sulfate reduction pathway also increased during the critical time points. Here, by analyzing the planktonic community structure, we describe a general method that uses high-throughput amplicon sequencing, metabolic inferences, and cell abundance data to identify successful biofilm mitigation. We anticipate that our approach is also applicable to other systems where biofilms must be mitigated but cannot be sampled easily. IMPORTANCE Microbial biofilms are commonly present in many industrial processes and can negatively impact performance and safety. Within the oil industry, subterranean biofilms cause biosouring with implications for oil quality, cost, occupational health, and the environment. Because these biofilms cannot be sampled directly, methods are needed to indirectly assess the success of mitigation measures. This study demonstrates how the planktonic microbial community can be used to assess the dissociation of sulfate-reducing bacterium (SRB)-containing biofilms. We found that an increase in the abundance of a specific SRB population in the effluent after nitrate treatment can be used as a potential indicator for the successful mitigation of biofilm-forming SRBs. Moreover, a method for determining critical time points for detecting potential indicators is suggested. This study expands our knowledge of improving mitigation strategies for biosouring and could have broader implications in other systems where biofilms lead to adverse consequences.

Machine Learning Predicts Biogeochemistry from Microbial Community Structure in a Complex Model System.

Microbial community structure is influenced by the environment and in turn exerts control on many environmental parameters. We applied this concept in a bioreactor study to test whether microbial community structure contains information sufficient to predict the concentration of H2S as the product of sulfate reduction. Microbial sulfate reduction is a major source of H2S in many industrial and environmental systems and is often influenced by the existing physicochemical conditions. Production of H2S in industrial systems leads to occupational hazards and adversely affects the quality of products. A long-term (148 days) experiment was conducted in upflow bioreactors to mimic sulfidogenesis, followed by inhibition with nitrate salts and a resumption of H2S generation when inhibition was released. We determined microbial community structure in 731 samples across 20 bioreactors using 16S rRNA gene sequencing and applied a random forest algorithm to successfully predict different phases of sulfidogenesis and mitigation (accuracy = 93.17%) and sessile and effluent microbial communities (accuracy = 100%). Similarly derived regression models that also included cell abundances were able to predict H2S concentration with remarkably high fidelity (R2 > 0.82). Metabolic profiles based on microbial community structure were also found to be reliable predictors for H2S concentration (R2 = 0.78). These results suggest that microbial community structure contains information sufficient to predict sulfidogenesis in a closed system, with anticipated applications to microbially driven processes in open environments. IMPORTANCE Microbial communities control many biogeochemical processes. Many of these processes are impractical or expensive to measure directly. Because the taxonomic structure of the microbial community is indicative of its function, it encodes information that can be used to predict biogeochemistry. Here, we demonstrate how a machine learning technique can be used to predict sulfidogenesis, a key biogeochemical process in a model system. A distinction of this research was the ability to predict H2S production in a bioreactor from the effluent bacterial community structure without direct observations of the sessile community or other environmental conditions. This study establishes the ability to use machine learning approaches in predicting sulfide concentrations in a closed system, which can be further developed as a valuable tool for predicting biogeochemical processes in open environments. As machine learning algorithms continue to improve, we anticipate increased applications of microbial community structure to predict key environmental and industrial processes.

Understanding Microbial Community Dynamics in Up-Flow Bioreactors to Improve Mitigation Strategies for Oil Souring.

Oil souring occurs when H2S is generated in oil reservoirs. This not only leads to operational risks and health hazards but also increases the cost of refining crude oil. Sulfate-reducing microorganisms are considered to be the main source of the H2S that leads to oil souring. Substrate competition between nitrate-reducing and sulfate-reducing microorganisms makes biosouring mitigation via the addition of nitrate salts a viable strategy. This study explores the shift in microbial community across different phases of biosouring and mitigation. Anaerobic sand-filled columns wetted with seawater and/or oil were used to initiate the processes of sulfidogenesis, followed by mitigation with nitrate, rebound sulfidogenesis, and rebound control phases (via nitrate and low salinity treatment). Shifts in microbial community structure and function were observed across different phases of seawater and oil setups. Marine bacterial taxa (Marinobacter, Marinobacterium, Thalassolituus, Alteromonas, and Cycloclasticus) were found to be the initial responders to the application of nitrate during mitigation of sulfidogenesis in both seawater- and oil- wetted columns. Autotrophic groups (Sulfurimonas and Desulfatibacillum) were found to be higher in seawater-wetted columns compared to oil-wetted columns, suggesting the potential for autotrophic volatile fatty acid (VFA) production in oil-field aquifers when seawater is introduced. Results indicate that fermentative (such as Bacteroidetes) and oil-degrading bacteria (such as Desulfobacula toluolica) play an important role in generating electron donors in the system, which may sustain biosouring and nitrate reduction. Persistence of certain microorganisms (Desulfobacula) across different phases was observed, which may be due to a shift in metabolic lifestyle of the microorganisms across phases, or zonation based on nutrient availability in the columns. Overall results suggest mitigation strategies for biosouring can be improved by monitoring VFA concentrations and microbial community dynamics in the oil reservoirs during secondary recovery of oil.

Mitochondrial protein oxidation in yeast mutants lacking manganese-(MnSOD) or copper- and zinc-containing superoxide dismutase (CuZnSOD): evidence that MnSOD and CuZnSOD have both unique and overlapping functions in protecting mitochondrial proteins from oxidative damage.

Saccharomyces cerevisiae expresses two forms of superoxide dismutase (SOD): MnSOD, encoded by SOD2, which is located within the mitochondrial matrix, and CuZnSOD, encoded by SOD1, which is located in both the cytosol and the mitochondrial intermembrane space. Because two different SOD enzymes are located in the mitochondrion, we examined the relative roles of each in protecting mitochondria against oxidative stress. Using protein carbonylation as a measure of oxidative stress, we have found no correlation between overall levels of respiration and the level of oxidative mitochondrial protein damage in either wild type or sod mutant strains. Moreover, mitochondrial protein carbonylation levels in sod1, sod2, and sod1sod2 mutants are not elevated in cells harvested from mid-logarithmic and early stationary phases, suggesting that neither MnSOD nor CuZnSOD is required for protecting the majority of mitochondrial proteins from oxidative damage during these early phases of growth. During late stationary phase, mitochondrial protein carbonylation increases in all strains, particularly in sod1 and sod1sod2 mutants. By using matrix-assisted laser desorption ionization time-of-flight mass spectrometry, we have found that specific proteins become carbonylated in sod1 and sod2 mutants. We identified six mitochondrial protein spots representing five unique proteins that become carbonylated in a sod1 mutant and 19 mitochondrial protein spots representing 11 unique proteins that become carbonylated in a sod2 mutant. Although some of the same proteins are carbonylated in both mutants, other proteins are not. These findings indicate that MnSOD and CuZnSOD have both unique and overlapping functions in the mitochondrion.

A mechanism of oxygen sensing in yeast. Multiple oxygen-responsive steps in the heme biosynthetic pathway affect Hap1 activity.

Heme plays central roles in oxygen sensing and utilization in many living organisms. In yeast, heme mediates the effect of oxygen on the expression of many genes involved in using or detoxifying oxygen. However, a direct link between intracellular heme level and oxygen concentration has not been vigorously established. In this report, we have examined the relationships among oxygen levels, heme levels, Hap1 activity, and HAP1 expression. We found that Hap1 activity is controlled in vivo by heme and not by its precursors and that heme activates Hap1 even in anoxic cells. We also found that Hap1 activity exhibits the same oxygen dose-response curves as Hap1-dependent aerobic genes and that these dose-response curves have a sharp break at approximately 1 microM O2. The results show that the intracellular signaling heme level, reflected as Hap1 activity, is closely correlated with oxygen concentration. Furthermore, we found that bypass of all heme synthetic steps but ferrochelatase by deuteroporphyrin IX does not circumvent the need for oxygen in Hap1 full activation by heme, suggesting that the last step of heme synthesis, catalyzed by ferrochelatase, is also subjected to oxygen control. Our results show that multiple heme synthetic steps can sense oxygen concentration and provide significant insights into the mechanism of oxygen sensing in yeast.

Exposure of yeast cells to anoxia induces transient oxidative stress. Implications for the induction of hypoxic genes.

The mitochondrial respiratory chain is required for the induction of some yeast hypoxic nuclear genes. Because the respiratory chain produces reactive oxygen species (ROS), which can mediate intracellular signal cascades, we addressed the possibility that ROS are involved in hypoxic gene induction. Recent studies with mammalian cells have produced conflicting results concerning this question. These studies have relied almost exclusively on fluorescent dyes to measure ROS levels. Insofar as ROS are very reactive and inherently unstable, a more reliable method for measuring changes in their intracellular levels is to measure their damage (e.g. the accumulation of 8-hydroxy-2'-deoxyguanosine (8-OH-dG) in DNA, and oxidative protein carbonylation) or to measure the expression of an oxidative stress-induced gene, e.g. SOD1. Here we used these approaches as well as a fluorescent dye, carboxy-H(2)-dichloro-dihydrofluorescein diacetate (carboxy-H(2)-DCFDA), to determine whether ROS levels change in yeast cells exposed to anoxia. These studies reveal that the level of mitochondrial and cytosolic protein carbonylation, the level of 8-OH-dG in mitochondrial and nuclear DNA, and the expression of SOD1 all increase transiently during a shift to anoxia. These studies also reveal that carboxy-H(2)-DCFDA is an unreliable reporter of ROS levels in yeast cells shifted to anoxia. By using two-dimensional electrophoresis and mass spectrometry (matrix-assisted laser desorption ionization time-of-flight), we have found that specific proteins become carbonylated during a shift to anoxia and that some of these proteins are the same proteins that become carbonylated during peroxidative stress. The mitochondrial respiratory chain is responsible for much of this carbonylation. Together, these findings indicate that yeast cells exposed to anoxia experience transient oxidative stress and raise the possibility that this initiates the induction of hypoxic genes.