Short-term microbial effects of a large-scale mine-tailing storage facility collapse on the local natural environment

Mixed heavy metal stress induces global iron starvation response

Multiple heavy metal contamination is an increasingly common global problem. Heavy metals have the potential to disrupt microbially mediated biogeochemical cycling. However, systems-level studies on the effects of combinations of heavy metals on bacteria are lacking. For this study, we focused on the Oak Ridge Reservation (ORR; Oak Ridge, TN, USA) subsurface which is contaminated with several heavy metals and high concentrations of nitrate. Using a native Bacillus cereus isolate that represents a dominant species at this site, we assessed the combined impact of eight metal contaminants, all at site-relevant concentrations, on cell processes through an integrated multi-omics approach that included discovery proteomics, targeted metabolomics, and targeted gene-expression profiling. The combination of eight metals impacted cell physiology in a manner that could not have been predicted from summing phenotypic responses to the individual metals. Exposure to the metal mixture elicited a global iron starvation response not observed during individual metal exposures. This disruption of iron homeostasis resulted in decreased activity of the iron-cofactor-containing nitrate and nitrite reductases, both of which are important in biological nitrate removal at the site. We propose that the combinatorial effects of simultaneous exposure to multiple heavy metals is an underappreciated yet significant form of cell stress in the environment with the potential to disrupt global nutrient cycles and to impede bioremediation efforts at mixed waste sites. Our work underscores the need to shift from single- to multi-metal studies for assessing and predicting the impacts of complex contaminants on microbial systems.

Microscale dynamics of dark zone alterations in anthropized karstic cave shows abrupt microbial community switch

Strong anthropization of karstic caves may result in formation of various wall alterations including dark zones, whose microbial community differs from that of non-altered surfaces nearby. Dark zones grow quickly and without gradual visual changes, leading to the hypothesis of a simple process rather than complex microbial successions, but this is counter-intuitive as underground microbial changes are typically slow and dark zones are microbiologically very distinct from unmarked surfaces. We tested this hypothesis in Paleolithic Lascaux Cave, across two years of microscale sampling. Indeed, Illumina MiSeq metabarcoding evidenced only three community stages for bacteria, fungi and all microeukaryotes together (i.e. unmarked surfaces, newly-formed dark zones and intermediate/old dark zones) and just two stages for archaea (unmarked surfaces vs dark zones), indicating abrupt community changes. The onset of dark zone formation coincided with the development of Ochroconis fungi, Bacteroidota and the bacterial genera Labrys, Nonomuraea and Sphingomonas, in parallel to Pseudomonas counter-selection. Modeling of community assembly processes highlighted that the dynamics of rare taxa in unmarked surfaces adjacent to dark zones and in newly-formed dark zones were governed in part by deterministic processes. This suggests that cooperative relationships between these taxa might be important to promote dark zone formation. Taken together, these findings indicate an abrupt community switch as these new alterations form on Lascaux cave walls.

Annual pulses of copper-enriched sediment in a North American river downstream of a large lake following the catastrophic failure of a mine tailings storage facility

Failures of mine tailings storage facilities (TSF) can have profound and long-lasting effects on the downstream receiving environment. Virtually all spills to date have been into river systems without large lakes that may buffer downstream impacts. In August 2014, the failure of the Mount Polley copper (Cu)-gold mine TSF in British Columbia, Canada, released ~25 × 10⁶ m³ of water and solids; globally, this is the second largest TSF spill in history. Over 18 × 10⁶ m³ was delivered to Quesnel Lake, which is ~9 km from the TSF and is the third deepest lake in North America, and a crucial habitat for Pacific salmon and trout populations. We determined the sediment-associated Cu concentrations and fluxes in Quesnel River, downstream of the lake, from August 2014 to February 2021 based on the analysis of >400 samples of sediment, mainly collected using a continuous-flow centrifuge. During each winter since the spill, Cu concentrations in the fluvial sediment in the upper reaches of the river (~35 km from the TSF) were elevated relative to regional background concentrations and samples collected before the spill. Maximum Cu concentrations were ~410 mg kg^-1 which exceeds Canadian sediment quality guidelines for the protection of aquatic organisms (197 mg kg^-1). Monitoring of Quesnel Lake since the spill shows that these annual pulses in the winter are due to resuspension of unconsolidated tailings and sediments at the bottom of Quesnel Lake, during autumnal lake turnover, which become mixed throughout the water column and subsequently flow into Quesnel River. Results show that while large lakes may buffer downstream aquatic systems from contaminated sediment, they may prolong the environmental impact. These findings are crucial in understanding how lake processes may modify the effects of TSF spills on downstream aquatic systems.

Relationships Between the Microbial Composition and the Geochemistry and Mineralogy of the Cobalt-Bearing Legacy Mine Tailings in Northeastern Ontario

Mine tailings host dynamic biogeochemical processes that can mobilize a range of elements from the host material and release them into the environment through acidic, neutral, or alkaline mine drainage. Here we use a combination of mineralogical, geochemical, and microbiological techniques that provide a better understanding of biogeochemical processes within the surficial layers of neutral cobalt and arsenic-rich tailings material at Cobalt, ON, Canada. Tailings material within 30-cm depth profiles from three tailings sites (sites A, B, and C) were characterized for their mineralogical, chemical and microbial community compositions. The tailings material at all sites contains (sulf)arsenides (safflorite, arsenopyrite), and arsenates (erythrite and annabergite). Site A contained a higher and lower amount of (sulf)arsenides and arsenates than site B, respectively. Contrary to site A and B, site C depicted a distinct zoning with (sulf)arsenides found in the deeper reduced zone, and arsenates occurring in the shallow oxidized zone. Variations in the abundance of Co+As+Sb+Zn (Co#), Fe (Fe#), total S (S#), and average valence of As indicated differences in the mineralogical composition of the tailings material. For example, material with a high Co#, lo Fe# and high average valence of As commonly have a higher proportion of secondary arsenate to primary (sulf)arsenide minerals. Microbial community profiling indicated that the Cobalt tailings are primarily composed of Actinobacteria and Proteobacteria, and known N, S, Fe, methane, and possible As-cycling bacteria. The tailings from sites B and C had a larger abundance of Fe and S-cycling bacteria (e.g., Sulfurifustis and Thiobacillus), which are more abundant at greater depths, whereas the tailings of site A had a higher proportion of potential As-cycling and -resistant genera (e.g., Methylocystis and Sphingomonas). A multi-variate statistical analysis showed that (1) distinct site-specific groupings occur for the Co # vs. Fe #, Co# vs. S#'s and for the microbial community structure and (2) microbial communities are statistically highly correlated to depth, S#, Fe#, pH and the average valence of As. The variation in As valence correlated well with the abundance of N, S, Fe, and methane-cycling bacteria. The results of this study provide insights into the complex interplay between minerals containing the critical element cobalt, arsenic, and microbial community structure in the Cobalt Mining Camp tailings.

Identifying indicator species in ecological habitats using Deep Optimal Feature Learning

Much of the current research on supervised modelling is focused on maximizing outcome prediction accuracy. However, in engineering disciplines, an arguably more important goal is that of feature extraction, the identification of relevant features associated with the various outcomes. For instance, in microbial communities, the identification of keystone species can often lead to improved prediction of future behavioral shifts. This paper proposes a novel feature extractor based on Deep Learning, which is largely agnostic to underlying assumptions regarding the training data. Starting from a collection of microbial species abundance counts, the Deep Learning model first trains itself to classify the selected distinct habitats. It then identifies indicator species associated with the habitats. The results are then compared and contrasted with those obtained by traditional statistical techniques. The indicator species are similar when compared at top taxonomic levels such as Domain and Phylum, despite visible differences in lower levels such as Class and Order. More importantly, when our estimated indicators are used to predict final habitat labels using simpler models (such as Support Vector Machines and traditional Artificial Neural Networks), the prediction accuracy is improved. Overall, this study serves as a preliminary step that bridges modern, black-box Machine Learning models with traditional, domain expertise-rich techniques.

Trace Metal Contamination Impacts Predicted Functions More Than Structure of Marine Prokaryotic Biofilm Communities in an Anthropized Coastal Area

Trace metal (TM) contamination in marine coastal areas is a worldwide threat for aquatic communities. However, little is known about the influence of a multi-chemical contamination on both marine biofilm communities' structure and functioning. To determine how TM contamination potentially impacted microbial biofilms' structure and their functions, polycarbonate (PC) plates were immerged in both surface and bottom of the seawater column, at five sites, along strong TM contamination gradients, in Toulon Bay. The PC plates were incubated during 4 weeks to enable colonization by biofilm-forming microorganisms on artificial surfaces. Biofilms from the PC plates, as well as surrounding seawaters, were collected and analyzed by 16S rRNA amplicon gene sequencing to describe prokaryotic community diversity, structure and functions, and to determine the relationships between bacterioplankton and biofilm communities. Our results showed that prokaryotic biofilm structure was not significantly affected by the measured environmental variables, while the functional profiles of biofilms were significantly impacted by Cu, Mn, Zn, and salinity. Biofilms from the contaminated sites were dominated by tolerant taxa to contaminants and specialized hydrocarbon-degrading microorganisms. Functions related to major xenobiotics biodegradation and metabolism, such as methane metabolism, degradation of aromatic compounds, and benzoate degradation, as well as functions involved in quorum sensing signaling, extracellular polymeric substances (EPS) matrix, and biofilm formation were significantly over-represented in the contaminated site relative to the uncontaminated one. Taken together, our results suggest that biofilms may be able to survive to strong multi-chemical contamination because of the presence of tolerant taxa in biofilms, as well as the functional responses of biofilm communities. Moreover, biofilm communities exhibited significant variations of structure and functional profiles along the seawater column, potentially explained by the contribution of taxa from surrounding sediments. Finally, we found that both structure and functions were significantly distinct between the biofilm and bacterioplankton, highlighting major differences between the both lifestyles, and the divergence of their responses facing to a multi-chemical contamination.

Adaption of microbial communities to the hostile environment in the Doce River after the collapse of two iron ore tailing dams

In November 2015, two iron ore tailing dams collapsed in the city of Mariana, Brazil. The dams' collapse generated a wave of approximately 50 million m³ of a mixture of mining waste and water. It was a major environmental tragedy in Brazilian history, which damaged rivers, and cities 660 km away in the Doce River basin until it reached the ocean coast. Shortly after the incident, several reports informed that the concentration of metals in the water was above acceptable legal limits under Brazilian laws. Here the microbial communities in samples of water, mud, foam, and rhizosphere of Eichhornia from Doce River were analyzed for 16S and 18S rRNA-based amplicon sequencing, along with microbial isolation, chemical and mineralogical analyses. Samples were collected one month and thirteen months after the collapse. Prokaryotic communities from mud shifted drastically over time (33% Bray-Curtis similarity), while water samples were more similar (63% Bray-Curtis similarity) in the same period. After 12 months, mud samples remained with high levels of heavy metals and a reduction in the diversity of microeukaryotes was detected. Amoebozoans increased in mud samples, reaching 49% of microeukaryote abundance, with Discosea and Lobosa groups being the most abundant. The microbial communities’ structure in mud samples changed adapting to the new environment condition. The characterization of microbial communities and metal-tolerant organisms from such impacted environments is essential for understanding the ecological consequences of massive anthropogenic impacts and strategies for the restoration of contaminated sites such as the Doce River.

The bacterial community of Quesnel Lake sediments impacted by a catastrophic mine tailings spill differ in composition from those at undisturbed locations - two years post-spill

The West Basin of Quesnel Lake (British Columbia, Canada) suffered a catastrophic disturbance event in August 2014 when mine tailings and scoured natural material were deposited into the lake’s West Basin due to an impoundment failure at the adjacent Mount Polley copper-gold mine. The deposit covered a significant portion of the West Basin floor with a thick layer of material. Since lake sediments host bacterial communities that play key roles in the geochemical cycling in lacustrine environments, it is important to understand which groups inhabit the newly deposited material and what this implies for the ecological function of the West Basin. Here we report a study conducted two years post-spill, comparing the bacterial communities from sediments of both disturbed and undisturbed sites. Our results show that sediments from disturbed sites differed in physical and chemical properties than those in undisturbed sites (e.g. higher pH, particle size and Cu concentration). Furthermore, bacterial communities from the disturbed sites appeared to be legacy communities from the tailings impoundment, with metabolic potential revolving mainly around the cycling of S and metals, whereas the ones from the undisturbed sites were associated with the cycling of N.

Changes in Bacterioplankton Communities Resulting From Direct and Indirect Interactions With Trace Metal Gradients in an Urbanized Marine Coastal Area

Unraveling the relative importance of both environmental conditions and ecological processes regulating bacterioplankton communities is a central goal in microbial ecology. Marine coastal environments are among the most urbanized areas and as a consequence experience environmental pressures. The highly anthropized Toulon Bay (France) was considered as a model system to investigate shifts in bacterioplankton communities along natural and anthropogenic physicochemical gradients during a 1-month survey. In depth geochemical characterization mainly revealed strong and progressive Cd, Zn, Cu, and Pb contamination gradients between the entrance of the Bay and the north-western anthropized area. On the other hand, low-amplitude natural gradients were observed for other environmental variables. Using 16S rRNA gene sequencing, we observed strong spatial patterns in bacterioplankton taxonomic and predicted function structure along the chemical contamination gradient. Variation partitioning analysis demonstrated that multiple metallic contamination explained the largest part of the spatial biological variations observed, but DOC and salinity were also significant contributors. Network analysis revealed that biotic interactions were far more numerous than direct interactions between microbial groups and environmental variables. This suggests indirect effects of the environment, and especially trace metals, on the community through a few taxonomic groups. These spatial patterns were also partially found for predicted bacterioplankton functions, thus indicating a limited functional redundancy. All these results highlight both potential direct influences of trace metals contamination on coastal bacterioplankton and indirect forcing through biotic interactions and cascading.