Bacterial Emission Factors: A Foundation for the Terrestrial-Atmospheric Modeling of Bacteria Aerosolized by Wildland Fires.

Wildland fire is a major global driver in the exchange of aerosols between terrestrial environments and the atmosphere. This exchange is commonly quantified using emission factors or the mass of a pollutant emitted per mass of fuel burned. However, emission factors for microbes aerosolized by fire have yet to be determined. Using bacterial cell concentrations collected on unmanned aircraft systems over forest fires in Utah, USA, we determine bacterial emission factors (BEFs) for the first time. We estimate that 1.39 × 1010 and 7.68 × 1011 microbes are emitted for each Mg of biomass consumed in fires burning thinning residues and intact forests, respectively. These emissions exceed estimates of background bacterial emissions in other studies by 3-4 orders of magnitude. For the ∼2631 ha of similar forests in the Fishlake National Forest that burn each year on average, an estimated 1.35 × 1017 cells or 8.1 kg of bacterial biomass were emitted. BEFs were then used to parametrize a computationally scalable particle transport model that predicted over 99% of the emitted cells were transported beyond the 17.25 x 17.25 km model domain. BEFs can be used to expand understanding of global wildfire microbial emissions and their potential consequences to ecosystems, the atmosphere, and humans.

Transitional dynamics from mercury to cyanide-based processing in artisanal and small-scale gold mining: Social, economic, geochemical, and environmental considerations.

Artisanal and small-scale gold mining (ASGM) is the leading global source of anthropogenic mercury (Hg) release to the environment. Top-down mercury reduction efforts have had limited results, but a bottom-up embrace of cyanide (CN) processing could eventually displace mercury amalgamation for gold recovery. However, ASGM transitions to cyanidation nearly always include an overlap phase, with mercury amalgamation then cyanidation being used sequentially. This paper uses a transdisciplinary approach that combines natural and social sciences to develop a holistic picture of why mercury and cyanide converge in gold processing and potential impacts that may be worse than either practice in isolation. We show that socio-economic factors drive the comingling of mercury and cyanide practices in ASGM as much or more so than technical factors. The resultant Hg-CN complexes have been implicated in increasing the mobility of mercury, compared to elemental mercury used in Hg-only processing. To support future inquiry, we identify key knowledge gaps including the role of Hg-CN complexes in mercury oxidation, transport, and fate, and possible links to mercury methylation. The global extent and increase of mercury and cyanide processing in ASGM underscores the importance of further research. The immediacy of the problem also demands interim policy responses while research advances, though ultimately, the well-documented struggles of mercury reduction efforts in ASGM temper optimism about policy responses to the mercury-cyanide transition.

Statistical Learning and Uncommon Soil Microbiota Explain Biogeochemical Responses after Wildfire.

Wildfires are a perennial event globally, and the biogeochemical underpinnings of soil responses at relevant spatial and temporal scales are unclear. Soil biogeochemical processes regulate plant growth and nutrient losses that affect water quality, yet the response of soil after variable intensity fire is difficult to explain and predict. To address this issue, we examined two wildfires in Colorado, United States, across the first and second postfire years and leveraged statistical learning (SL) to predict and explain biogeochemical responses. We found that SL predicts biogeochemical responses in soil after wildfire with surprising accuracy. Of the 13 biogeochemical analytes analyzed in this study, 9 are best explained with a hybrid microbiome + biogeochemical SL model. Biogeochemical-only models best explain 3 features, and 1 feature is explained equally well with the hybrid and biogeochemical-only models. In some cases, microbiome-only SL models are also effective (such as predicting NH4+). Whenever a microbiome component is employed, selected features always involve uncommon soil microbiota (i.e., the "rare biosphere" [existing at <1% mean relative abundance]). Here, we demonstrate that SL paired with DNA sequence and biogeochemical data predicts environmental features in postfire soils, although this approach could likely be applied to any biogeochemical system. IMPORTANCE Soil biogeochemical processes are critical to plant growth and water quality and are substantially disturbed by wildfire. However, soil responses to fire are difficult to predict. To address this issue, we developed a large environmental data set that tracks postfire changes in soil and used statistical learning (SL) to build models that exploit complex data to make predictions about biogeochemical responses. Here, we show that SL depends upon uncommon microbiota in soil (the "rare biosphere") to make surprisingly accurate predictions about soil biogeochemical responses to wildfire. Using SL to explain variation in a natively chaotic environmental system is mechanism independent. Likely, the approach that we describe for combining SL with microbiome and biogeochemical parameters has practical applications across a range of issues in the environmental sciences where predicting responses would be useful.

A Real-Time Multiplexed Microbial Growth Intervalometer for Capturing High-Resolution Growth Curves.

Batch cultures are a low maintenance and routine culturing method in microbiology. Automated tools that measure growth curves from microorganisms grown in traditional laboratory glassware, such as Balch-type tubes, are not commercially available. Here, we present a new MicrobiAl Growth Intervalometer (MAGI) that measures optical density as it correlates to microbial growth by utilizing photo-conduction as opposed to photo-attenuation used by traditional OD measurement equipment. Photo-attenuation occurs when biomass in suspension within a medium blocks and/or diffuses light directed at the detector, such that an increase in biomass results in a decrease in the measured signal. Photo-conduction differs in which the biomass contained in a medium conducts light from the emitter to the detector, where an increase in the biomass results in a corresponding increase in the measured signal. MAGI features software-driven automation that provides investigators with a highly sensitive, low-background noise growth measurement instrument with added capabilities for remote visualization and data acquisition. It is a low maintenance, cost effective, versatile, and robust platform for aerobic/anaerobic cultivation. We demonstrate the versatility of this device by obtaining growth curves from two common laboratory organisms Escherichia coli K-12 and Bacillus subtilis. We show that growth rates and generation times in E. coli K-12 are reproducible to previously published results and that morphological changes of B. subtilis during growth can be detected as a change in the slope of the growth curve, which is a function of the effects of cell size on photo-conduction through the medium. We also test MAGI to capture growth curves from an environmental organism, Intrasporangium calvum C5, under various media compositions. Our results demonstrate that the MAGI platform accurately measures growth curves in media under various redox conditions (aerobic, microaerobic, and anaerobic), complex and minimal medias, and resolving diauxic growth curves when I. calvum is grown on a disaccharide. Lastly, we demonstrate that the device can resolve growth curves for µM concentrations of resources that yield low biomass. This research advances the tools available to microbiologists aiming to monitor growth curves in a variety of disciplines, such as environmental microbiology, clinical microbiology, and food sciences.

Resource Concentration Modulates the Fate of Dissimilated Nitrogen in a Dual-Pathway Actinobacterium.

Respiratory ammonification and denitrification are two evolutionarily unrelated dissimilatory nitrogen (N) processes central to the global N cycle, the activity of which is thought to be controlled by carbon (C) to nitrate (NO3 -) ratio. Here we find that Intrasporangium calvum C5, a novel dual-pathway denitrifier/respiratory ammonifier, disproportionately utilizes ammonification rather than denitrification when grown under low C concentrations, even at low C:NO3 - ratios. This finding is in conflict with the paradigm that high C:NO3 - ratios promote ammonification and low C:NO3 - ratios promote denitrification. We find that the protein atomic composition for denitrification modules (NirK) are significantly cost minimized for C and N compared to ammonification modules (NrfA), indicating that limitation for C and N is a major evolutionary selective pressure imprinted in the architecture of these proteins. The evolutionary precedent for these findings suggests ecological importance for microbial activity as evidenced by higher growth rates when I. calvum grows predominantly using its ammonification pathway and by assimilating its end-product (ammonium) for growth under ammonium-free conditions. Genomic analysis of I. calvum further reveals a versatile ecophysiology to cope with nutrient stress and redox conditions. Metabolite and transcriptional profiles during growth indicate that enzyme modules, NrfAH and NirK, are not constitutively expressed but rather induced by nitrite production via NarG. Mechanistically, our results suggest that pathway selection is driven by intracellular redox potential (redox poise), which may be lowered when resource concentrations are low, thereby decreasing catalytic activity of upstream electron transport steps (i.e., the bc1 complex) needed for denitrification enzymes. Our work advances our understanding of the biogeochemical flexibility of N-cycling organisms, pathway evolution, and ecological food-webs.

Coordinated downregulation of the photosynthetic apparatus as a protective mechanism against UV exposure in the diatom Corethron hystrix.

The effect of ultraviolet radiation (UVR) on photosynthetic efficiency and the resulting mechanisms against UV exposure employed by phytoplankton are not completely understood. To address this knowledge gap, we developed a novel close-coupled, wavelength-configurable platform designed to produce precise and repeatable in vitro irradiation of Corethron hystrix, a member of a genera found abundantly in the Southern Ocean where UV exposure is high. We aimed to determine its metabolic, protective, and repair mechanisms as a function of varying levels of specific electromagnetic energy. Our results show that the physiological responses to each energy level of UV have a negative linear decrease in the photosynthetic efficiency of photosystem II proportional to UV intensity, corresponding to a large increase in the turnover time of quinone reoxidation. Gene expression changes of photosystem II-related reaction center proteins D1, CP43, and CP47 showed coordinated downregulation whereas the central metabolic pathway demonstrated mixed expression of up and downregulated transcripts after UVR exposure. These results suggest that while UVR may damage photosynthetic machinery, oxidative damage may limit production of new photosynthetic and electron transport complexes as a result of UVR exposure.

rRNA Gene Expression of Abundant and Rare Activated-Sludge Microorganisms and Growth Rate Induced Micropollutant Removal.

The role of abundant and rare taxa in modulating the performance of wastewater-treatment systems is a critical component of making better predictions for enhanced functions such as micropollutant biotransformation. In this study, we compared 16S rRNA genes (rDNA) and rRNA gene expression of taxa in an activated-sludge-treatment plant (sequencing batch membrane bioreactor) at two solids retention times (SRTs): 20 and 5 days. These two SRTs were used to influence the rates of micropollutant biotransformation and nutrient removal. Our results show that rare taxa (<1%) have disproportionally high ratios of rRNA to rDNA, an indication of higher protein synthesis, compared to abundant taxa (≥1%) and suggests that rare taxa likely play an unrecognized role in bioreactor performance. There were also significant differences in community-wide rRNA expression signatures at 20-day SRT: anaerobic-oxic-anoxic periods were the primary driver of rRNA similarity. These results indicate differential expression of rRNA at high SRTs, which may further explain why high SRTs promote higher rates of micropollutant biotransformation. An analysis of micropollutant-associated degradation genes via metagenomics and direct measurements of a suite of micropollutants and nutrients further corroborates the loss of enhanced functions at 5-day SRT operation. This work advances our knowledge of the underlying ecosystem properties and dynamics of abundant and rare organisms associated with enhanced functions in engineered systems.

Disturbance opens recruitment sites for bacterial colonization in activated sludge.

Little is known about the role of immigration in shaping bacterial communities or the factors that may dictate success or failure of colonization by bacteria from regional species pools. To address these knowledge gaps, the influence of bacterial colonization into an ecosystem (activated sludge bioreactor) was measured through a disturbance gradient (successive decreases in the parameter solids retention time) relative to stable operational conditions. Through a DNA sequencing approach, we show that the most abundant bacteria within the immigrant community have a greater probability of colonizing the receiving ecosystem, but mostly as low abundance community members. Only during the disturbance do some of these bacterial populations significantly increase in abundance beyond background levels and in few cases become dominant community members post-disturbance. Two mechanisms facilitate the enhanced enrichment of immigrant populations during disturbance: (i) the availability of resources left unconsumed by established species and (ii) the increased availability of niche space for colonizers to establish and displace resident populations. Thus, as a disturbance decreases local diversity, recruitment sites become available to promote colonization. This work advances our understanding of microbial resource management and diversity maintenance in complex ecosystems.

Disturbance and temporal partitioning of the activated sludge metacommunity.

The resilience of microbial communities to press disturbances and whether ecosystem function is governed by microbial composition or by the environment have not been empirically tested. To address these issues, a whole-ecosystem manipulation was performed in a full-scale activated sludge wastewater treatment plant. The parameter solids retention time (SRT) was used to manipulate microbial composition, which started at 30 days, then decreased to 12 and 3 days, before operation was restored to starting conditions (30-day SRT). Activated sludge samples were collected throughout the 313-day time series in parallel with bioreactor performance ('ecosystem function'). Bacterial small subunit (SSU) rRNA genes were surveyed from sludge samples resulting in a sequence library of >417,000 SSU rRNA genes. A shift in community composition was observed for 12- and 3-day SRTs. The composition was altered such that r-strategists were enriched in the system during the 3-day SRT, whereas K-strategists were only present at SRTs⩾12 days. This shift corresponded to loss of ecosystem functions (nitrification, denitrification and biological phosphorus removal) for SRTs⩽12 days. Upon return to a 30-day SRT, complete recovery of the bioreactor performance was observed after 54 days despite an incomplete recovery of bacterial diversity. In addition, a different, yet phylogenetically related, community with fewer of its original rare members displaced the pre-disturbance community. Our results support the hypothesis that microbial ecosystems harbor functionally redundant phylotypes with regard to general ecosystem functions (carbon oxidation, nitrification, denitrification and phosphorus accumulation). However, the impacts of decreased rare phylotype membership on ecosystem stability and micropollutant removal remain unknown.