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.

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.

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.