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Taxonomic classification of the thousands–millions of 16S rRNA gene sequences generated in microbiome studies is often achieved using a naïve Bayesian classifier (for example, the Ribosomal Database Project II (RDP) classifier), due to favorable trade-offs among automation, speed and accuracy. The resulting classification depends on the reference sequences and taxonomic hierarchy used to train the model; although the influence of primer sets and classification algorithms have been explored in detail, the influence of training set has not been characterized. We compared classification results obtained using three different publicly available databases as training sets, applied to five different bacterial 16S rRNA gene pyrosequencing data sets generated (from human body, mouse gut, python gut, soil and anaerobic digester samples). We observed numerous advantages to using the largest, most diverse training set available, that we constructed from the Greengenes (GG) bacterial/archaeal 16S rRNA gene sequence database and the latest GG taxonomy. Phylogenetic clusters of previously unclassified experimental sequences were identified with notable improvements (for example, 50% reduction in reads unclassified at the phylum level in mouse gut, soil and anaerobic digester samples), especially for phylotypes belonging to specific phyla (Tenericutes, Chloroflexi, Synergistetes and Candidate phyla TM6, TM7). Trimming the reference sequences to the primer region resulted in systematic improvements in classification depth, and greatest gains at higher confidence thresholds. Phylotypes unclassified at the genus level represented a greater proportion of the total community variation than classified operational taxonomic units in mouse gut and anaerobic digester samples, underscoring the need for greater diversity in existing reference databases.

Anaerobic digestion is the most successful bioenergy technology worldwide with, at its core, undefined microbial communities that have poorly understood dynamics. Here, we investigated the relationships of bacterial community structure (>400,000 16S rRNA gene sequences for 112 samples) with function (i.e., bioreactor performance) and environment (i.e., operating conditions) in a yearlong monthly time series of nine full-scale bioreactor facilities treating brewery wastewater (>20,000 measurements). Each of the nine facilities had a unique community structure with an unprecedented level of stability. Using machine learning, we identified a small subset of operational taxonomic units (OTUs; 145 out of 4,962), which predicted the location of the facility of origin for almost every sample (96.4% accuracy). Of these 145 OTUs, syntrophic bacteria were systematically overrepresented, demonstrating that syntrophs rebounded following disturbances. This indicates that resilience, rather than dynamic competition, played an important role in maintaining the necessary syntrophic populations. In addition, we explained the observed phylogenetic differences between all samples on the basis of a subset of environmental gradients (using constrained ordination) and found stronger relationships between community structure and its function rather than its environment. These relationships were strongest for two performance variables— methanogenic activity and substrate removal efficiency— both of which were also affected by microbial ecology because these variables were correlated with community evenness (at any given time) and variability in phylogenetic structure (over time), respectively. Thus, we quantified relationships between community structure and function, which opens the door to engineer communities with superior functions.

Microbial chain elongation pathways in open-culture biotechnology systems can be utilized to convert organic waste and industrial side streams into valuable industrial chemicals. Here, we investigated the microbiota and metabolic pathways that produce medium-chain carboxylates (MCCs), including n -caproate (C6) and n -caprylate (C8), in reactors with in-line product extraction. Although the reactors in this study were operated similarly, different microbial communities dominated and were responsible for chain elongation. We found that different microbiota were responsible for n -caproate or n -caprylate production, and this can inform engineers on how to operate the systems better. We also observed which changes in operating conditions steered the production toward and away from n -caprylate, but more work is necessary to ascertain a mechanistic understanding that could be predictive. This study provides pertinent research questions for future work.

The aqueous photochemistry of four pharmaceutical compounds detected in surface waters (naproxen, diclofenac, ibuprofen, and clofibric acid) was investigating in purified (Milli-Q) water and in Mississippi River water (MRW). Both direct photolysis and hydroxyl radical-mediated indirect photolysis (using a combination of probe and quencher experiments) were studied. Singlet oxygenation was also investigated for naproxen. Second-order rate constants for reaction with hydroxyl radical were determined using Fenton's reagent. Naproxen was rapidly transformed via direct photolysis in sunlight in both Milli-Q and MRW. The radical quencher isopropyl alcohol (IPA), had a similar effect in both systems, and this effect was interpreted as a reaction of a carboxyl radical intermediate of naproxen. Diclofenac was found to undergo rapid direct photolysis under sunlight, confirming the results of prior studies. Addition of IPA led to more rapid transformation, possibly due to formation of other radical species or photoreduction with IPA serving as the H-source. When irradiated under natural sunlight, slow direct photolysis of clofibric acid is observed in Milli-Q water, and a combination of direct photolysis and radical mediated indirect processes appear responsible for clofibric acid photolysis in MRW. The dominant photochemical loss process for ibuprofen irradiated with a medium pressure Hg-vapor lamp was identified as reaction with photo-generated radicals. These results suggest that photolytic processes are important removal mechanisms for pharmaceutical compounds discharged into sunlit surface waters.[PUBLICATION ABSTRACT]

The respiratory tract of cystic fibrosis (CF) patients harbor persistent microbial communities (CF airway microbiome) with Pseudomonas aeruginosa emerging as a dominant pathogen. Within a polymicrobial infection, interactions between co-habitant microbes can be important for pathogenesis, but even when considered, these interactions are not well understood. Here, we show with in vitro experiments that, compared with glucose, common fermentation products from co-habitant bacteria significantly increase virulence factor production, antimicrobial activity and biofilm formation of P. aeruginosa . The maximum stimulating effect was produced with the fermentation product 2,3-butanediol, which is a substrate for P. aeruginosa , resulting in a metabolic relationship between fermenters and this pathogen. The global transcription regulator LasI LasR, which controls quorum sensing, was upregulated threefold with 2,3-butanediol, resulting in higher phenazine and exotoxin concentrations and improved biofilm formation. This indicates that the success of P. aeruginosa in CF airway microbiomes could be governed by the location within the food web with fermenting bacteria. Our findings suggest that interbacterial metabolite transfer in polymicrobial infections stimulates virulence of P. aeruginosa and could have a considerable impact on disease progression.

This paper contributes new information to the body of evidence for Middle Stone Age tool-use in Tanzania. Magubike rocksheiter is located in an archaeologically unexplored region of the south-central part of the country, and thus fills a significant geographical gap between sites further to the north and those to the south in Zambia and Mozambique. Early analysis of a portion of the lithic materials demonstrates parallel changes in lithic reduction intensity, raw material preference and typology. This article explores possible explanations for this pattern, including the possibility that they reflect changes to local environment, and suggests avenues for future research. Cet article apporte de nouvelles informations à l'ensemble des preuves sur rutilisationd'outille de l'âge de pierre moyen en Tanzanie. L'abris sous roches de Magubike est situé dansune région archéologique inexplorée de la partie sud-centrale du pays, et remplit ainsi unespace géographique entre les sites plus au nord et celles du sud en Zambie et au Mozambique. L'analyse préliminaire d'une partie des matériaux lithiques démontre des changementsparallèles dans l'intensité de réduction lithique, la préférence des matières premières et de latypologie. Cet article explore les explications possibles de ce modèle, y compris la possibilitéqu'elles reflètent des changements de l'environnement local, et propose des pistes pour larecherche future.

Anaerobic digestion is the most successful bioenergy technology worldwide with, at its core, undefined microbial communities that have poorly understood dynamics. Here, we investigated the relationships of bacterial community structure (>400,000 16S rRNA gene sequences for 112 samples) with function (i.e., bioreactor performance) and environment (i.e., operating conditions) in a yearlong monthly time series of nine full-scale bioreactor facilities treating brewery wastewater (>20,000 measurements). Each of the nine facilities had a unique community structure with an unprecedented level of stability. Using machine learning, we identified a small subset of operational taxonomic units (OTUs; 145 out of 4,962), which predicted the location of the facility of origin for almost every sample (96.4% accuracy). Of these 145 OTUs, syntrophic bacteria were systematically overrepresented, demonstrating that syntrophs rebounded following disturbances. This indicates that resilience, rather than dynamic competition, played an important role in maintaining the necessary syntrophic populations. In addition, we explained the observed phylogenetic differences between all samples on the basis of a subset of environmental gradients (using constrained ordination) and found stronger relationships between community structure and its function rather than its environment. These relationships were strongest for two performance variables—methanogenic activity and substrate removal efficiency—both of which were also affected by microbial ecology because these variables were correlated with community evenness (at any given time) and variability in phylogenetic structure (over time), respectively. Thus, we quantified relationships between community structure and function, which opens the door to engineer communities with superior functions.

Medium-chain carboxylates are used in various industrial applications. These chemicals are typically extracted from palm oil, which is deemed not sustainable. Recent research has focused on microbial chain elongation using reactors to produce medium-chain carboxylates, such as n-caproate (C6) and n-caprylate (C8), from organic substrates such as wastes. Even though the production of n-caproate is relatively well-characterized, bacteria and metabolic pathways that are responsible for n-caprylate production are not. Here, three 5-L reactors with continuous membrane-based liquid-liquid extraction (i.e., pertraction) were fed ethanol and acetate and operated for an operating period of 234 days with different operating conditions. Metagenomic and metaproteomic analyses were employed. n-Caprylate production rates and reactor microbiomes differed between reactors even when operated similarly due to differences in H2 and O2 between the reactors. The complete reverse β-oxidation pathway was present and expressed by several bacterial species in the Clostridia class. Several Oscillibacter spp., including Oscillibacter valericigenes, were positively correlated with n-caprylate production rates, while Clostridium kluyveri was positively correlated with n-caproate production. Pseudoclavibacter caeni, which is a strictly aerobic bacterium, was abundant across all the operating periods, regardless of n-caprylate production rates. This study provides insight into microbiota that are associated with n-caprylate production in open-culture reactors and provides ideas for further work. Microbial chain elongation pathways in open-culture biotechnology systems can be utilized to convert organic waste and industrial side streams into valuable industrial chemicals. Here, we investigated the microbiota and metabolic pathways that produce medium-chain carboxylates, including n-caproate (C6) and n-caprylate (C8), in reactors with in-line product extraction. Although the reactors in this study were operated similarly, different microbial communities dominated and were responsible for chain elongation. We found that different microbiota were responsible for n-caproate or n-caprylate production, and this can inform engineers on how to operate the systems better. We also observed which changes in operating conditions steered the production toward and away from n-caprylate, but more work is necessary to ascertain a mechanistic understanding that could be predictive. This study provides pertinent research questions for future work.