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.

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.

Amelioration of binge eating by nucleus accumbens shell deep brain stimulation in mice involves D2 receptor modulation.

Hedonic overconsumption contributing to obesity involves altered activation within the mesolimbic dopamine system. Dysregulation of dopamine signaling in the nucleus accumbens shell (NAS) has been implicated in reward-seeking behaviors, such as binge eating, which contributes to treatment resistance in obesity (Wise, 2012). Direct modulation of the NAS with deep brain stimulation (DBS), a surgical procedure currently under investigation in humans for the treatment of major depression, obsessive-compulsive disorder, and addiction, may also be effective in ameliorating binge eating. Therefore, we examined the ability of DBS of the NAS to block this behavior in mice. c-Fos immunoreactivity was assessed as a marker of DBS-mediated neuronal activation. NAS DBS was found to reduce binge eating and increased c-Fos levels in this region. DBS of the dorsal striatum had no influence on this behavior, demonstrating anatomical specificity for this effect. The dopamine D2 receptor antagonist, raclopride, attenuated the action of DBS, whereas the D1 receptor antagonist, SCH-23390, was ineffective, suggesting that dopamine signaling involving D2 receptors underlies the effect of NAS DBS. To determine the potential translational relevance to the obese state, chronic NAS DBS was also examined in diet-induced obese mice and was found to acutely reduce caloric intake and induce weight loss. Together, these findings support the involvement of the mesolimbic dopamine pathways in the hedonic mechanisms contributing to obesity, and the efficacy of NAS DBS to modulate this system.

Time and frequency characteristics of Purkinje cell complex spikes in the awake monkey performing a nonperiodic task.

A number of studies have been interpreted to support the view that the inferior olive climbing fibers send periodic signals to the cerebellum to time and pace behavior. In a direct test of this hypothesis in macaques performing nonperiodic tasks, we analyzed continuous recordings of complex spikes from the lateral cerebellar hemisphere. We found no periodicity outside of a 100-ms relative refractory period.

Alpha-chloralose is a suitable anesthetic for chronic focal cerebral ischemia studies in the rat: a comparative study.

alpha-Chloralose is widely used as an anesthetic in studies of the cerebrovasculature because it provides robust metabolic and hemodynamic responses to functional stimulation. However, there have been no controlled studies of focal ischemia in the rat under alpha-chloralose anesthesia. Artificially ventilated rats were prepared using 1.2-1.5% isoflurane anesthesia for filament occlusion of the right middle cerebral artery (MCA), and anesthesia was either switched to alpha-chloralose (60 mg/kg bolus, 30 mg/kg/h; n=10) or was maintained on 1% isoflurane (n=10). Following temporary MCA occlusion EEG was monitored from a screw electrode and changes in cerebral blood flow (rCBF) measured with a laser Doppler probe placed over the ischemic cortex. This study shows that alpha-chloralose is a safe anesthetic for ischemia studies and provides excellent survival. Compared with isoflurane, the cortical and total infarct volumes are larger in the alpha-chloralose-anesthetized animals, while the functional outcome at 72 h is similar. The total duration of peri-infarct flow transients (PIFTs) is also significantly longer in alpha-chloralose-anesthetized animals. The average amplitude of the flow transients showed a good correlation with the extent of edema in all animals as did the total duration of non-convulsive seizures (NCS) in the alpha-chloralose-anesthetized animals.

Implementation of dual simultaneous microelectrode recording systems during deep brain stimulation surgery for Parkinson's disease: technical note.

OBJECTIVE: Microelectrode recording during deep brain stimulation surgery improves the likelihood of successful target localization and enables the electrophysiological characterization of human neural structures. Many clinical recording systems do not support the ability to capture research-quality recordings. Established clinical centers already using such equipment may be prevented from acquiring human intracranial data because of the need to completely change recording systems to obtain research-quality recordings. This technical note describes the novel design and implementation of a recording system that significantly improves research capabilities without disrupting the existing clinical setup. METHODS: This design introduces a second recording system (including pre-amplifier, differential amplifier, analog-to-digital converter, and computer with analysis software) that divides the microelectrode signal into two independent streams. RESULTS: This design preserves the existing intraoperative recording setup, but significantly improves research-level recording, data storage, and analysis capabilities. CONCLUSION: We provide the first description of such a system using components that are all commercially available and relatively inexpensive. This approach presents an appealing alternative to the purchase of an entirely new system for surgical teams that already perform intraoperative recordings to assist in stereotactic target localization, yet wish to expand their neurophysiological recording capabilities.

Tolerance and adaptation of ethanologenic yeasts to lignocellulosic inhibitory compounds.

Synthetic mixtures of predominant lignocellulosic hexose sugars were supplemented with separate aliquots of three inhibitory compounds (furfural, hydroxymethylfurfural (HMF), and acetic acid) in a series of concentrations and fermented by the spent sulfite liquor (SSL)-adapted yeast strain Tembec T1 and the natural isolate Saccharomyces cerevisiae (S. cerevisiae) Y-1528 to compare tolerance and assess fermentative efficacy. The performance of Y-1528 exceeded that of Tembec T1 by a significant margin, with faster hexose sugar consumption, higher ethanol productivity, and in the case of furfural and HMF, faster inhibitor consumption. Nevertheless, furfural had a dose-proportionate effect on sugar consumption rate and ethanol productivity in both strains, but did not substantially affect ethanol yield. HMF had a similar effect on sugar consumption rate and ethanol productivity, and also lowered ethanol yield. Surprisingly, acetic acid had the least impact on sugar consumption rate and ethanol productivity, and stimulated ethanol yield at moderate concentrations. Sequential iterations of softwood (SW) and hardwood (HW) SSL were subsequently inoculated with the two yeast strains in order to compare adaptation to, and performance in lignocellulosic substrates in a cell recycle batch fermentation (CRBF) regime. Both strains were severely affected by the HW SSL, which was attributed to specific syringyl lignin-derived degradation products and synergistic interactions between inhibitors. Though ethanologenic capacity was preserved, a net loss of performance was evident from both strains, indicating the absence of adaptation to the substrates, regardless of the sequence in which the SSL types were employed.