Analysis of the microbial community associated with a bioprocess system for bioremediation of thiocyanate- and cyanide-laden mine water effluents

Gold extraction by cyanidation from refractory gold ores results in the formation of thiocyanate- and cyanide-contaminated wastewater effluents that must be treated before recycle or discard. Activated sludge processes, such as ASTER™, can be used for biodegradation of these effluent streams. The destruction of these compounds is catalyzed by a mixed microbial culture, however, very little is known about the community composition and metabolic potential of the thiocyanate- and cyanide-degrading microorganisms within the community. Here we describe our on-going attempts to better understand the key microorganisms, within the ASTER™ bioprocess, that contribute to the destruction of thiocyanate and cyanide, and how this knowledge relates to further process optimisation

Multi-scale Characterization and Prediction of Coupled Subsurface Biogeochemical-Hydrological Processes

To advance solutions needed for remediation of DOE contaminated sites, approaches are needed that can elucidate and predict reactions associated with coupled biological, geochemical, and hydrological processes over a variety of spatial scales and in heterogeneous environments. Our previous laboratory experimental experiments, which were conducted under controlled and homogeneous conditions, suggest that geophysical methods have the potential for elucidating system transformations that often occur during remediation. Examples include tracking the onset and aggregation of precipitates associated with sulfate reduction using seismic and complex resistivity methods (Williams et al., 2005; Ntarlagiannis et al., 2005) as well as estimating the volume of evolved gas associated with denitrification using radar velocity. These exciting studies illustrated that geophysical responses correlated with biogeochemical changes, but also that multiple factors could impact the geophysical signature and thus a better understanding as well as integration tools were needed to advance the techniques to the point where they can be used to provide quantitative estimates of system transformations

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS

Inter-species interconnections in acid mine drainage microbial communities

Metagenomic studies are revolutionizing our understanding of microbes in the biosphere. They have uncovered numerous proteins of unknown function in tens of essentially unstudied lineages that lack cultivated representatives. Notably, few of these microorganisms have been visualized, and even fewer have been described ultra-structurally in their essentially intact, physiologically relevant states. Here, we present cryogenic transmission electron microscope (cryo-TEM) 2D images and 3D tomographic datasets for archaeal species from natural acid mine drainage (AMD) microbial communities. Ultrastructural findings indicate the importance of microbial interconnectedness via a range of mechanisms, including direct cytoplasmic bridges and pervasive pili. The data also suggest a variety of biological structures associated with cell-cell interfaces that lack explanation. Some may play roles in inter-species interactions. Interdependences amongst the archaea may have confounded prior isolation efforts. Overall, the findings underline knowledge gaps related to archaeal cell components and highlight the likely importance of co-evolution in shaping microbial lineages

Host translation machinery is not a barrier to phages that interact with both CPR and non-CPR bacteria.

Here, we profiled putative phages of Saccharibacteria, which are of particular importance as Saccharibacteria influence some human oral diseases. We additionally profiled putative phages of Gracilibacteria and Absconditabacteria, two Candidate Phyla Radiation (CPR) lineages of interest given their use of an alternative genetic code. Among the phages identified in this study, some are targeted by spacers from both CPR and non-CPR bacteria and others by both bacteria that use the standard genetic code as well as bacteria that use an alternative genetic code. These findings represent new insights into possible phage replication strategies and have relevance for phage therapies that seek to manipulate microbiomes containing CPR bacteria

Biophysical characterization of microbial rhodopsins with DSE motif.

Microbial rhodopsins are photoreceptive transmembrane proteins that transport ions or regulate other intracellular biological processes. Recent genomic and metagenomic analyses found many microbial rhodopsins with unique sequences distinct from known ones. Functional characterization of these new types of microbial rhodopsins is expected to expand our understanding of their physiological roles. Here, we found microbial rhodopsins having a DSE motif in the third transmembrane helix from members of the Actinobacteria. Although the expressed proteins exhibited blue-green light absorption, either no or extremely small outward H+ pump activity was observed. The turnover rate of the photocycle reaction of the purified proteins was extremely slow compared to typical H+ pumps, suggesting these rhodopsins would work as photosensors or H+ pumps whose activities are enhanced by an unknown regulatory system in the hosts. The discovery of this rhodopsin group with the unique motif and functionality expands our understanding of the biological role of microbial rhodopsins

Consistent Metagenome-Derived Metrics Verify and Delineate Bacterial Species Boundaries.

Longstanding questions relate to the existence of naturally distinct bacterial species and genetic approaches to distinguish them. Bacterial genomes in public databases form distinct groups, but these databases are subject to isolation and deposition biases. To avoid these biases, we compared 5,203 bacterial genomes from 1,457 environmental metagenomic samples to test for distinct clouds of diversity and evaluated metrics that could be used to define the species boundary. Bacterial genomes from the human gut, soil, and the ocean all exhibited gaps in whole-genome average nucleotide identities (ANI) near the previously suggested species threshold of 95% ANI. While genome-wide ratios of nonsynonymous and synonymous nucleotide differences (dN/dS) decrease until ANI values approach ∼98%, two methods for estimating homologous recombination approached zero at ∼95% ANI, supporting breakdown of recombination due to sequence divergence as a species-forming force. We evaluated 107 genome-based metrics for their ability to distinguish species when full genomes are not recovered. Full-length 16S rRNA genes were least useful, in part because they were underrecovered from metagenomes. However, many ribosomal proteins displayed both high metagenomic recoverability and species discrimination power. Taken together, our results verify the existence of sequence-discrete microbial species in metagenome-derived genomes and highlight the usefulness of ribosomal genes for gene-level species discrimination.IMPORTANCE There is controversy about whether bacterial diversity is clustered into distinct species groups or exists as a continuum. To address this issue, we analyzed bacterial genome databases and reports from several previous large-scale environment studies and identified clear discrete groups of species-level bacterial diversity in all cases. Genetic analysis further revealed that quasi-sexual reproduction via horizontal gene transfer is likely a key evolutionary force that maintains bacterial species integrity. We next benchmarked over 100 metrics to distinguish these bacterial species from each other and identified several genes encoding ribosomal proteins with high species discrimination power. Overall, the results from this study provide best practices for bacterial species delineation based on genome content and insight into the nature of bacterial species population genetics

Genome-Resolved Proteomic Stable Isotope Probing of Soil Microbial Communities Using 13CO2 and 13C-Methanol.

Stable isotope probing (SIP) enables tracking the nutrient flows from isotopically labeled substrates to specific microorganisms in microbial communities. In proteomic SIP, labeled proteins synthesized by the microbial consumers of labeled substrates are identified with a shotgun proteomics approach. Here, proteomic SIP was combined with targeted metagenomic binning to reconstruct metagenome-assembled genomes (MAGs) of the microorganisms producing labeled proteins. This approach was used to track carbon flows from 13CO2 to the rhizosphere communities of Zea mays, Triticum aestivum, and Arabidopsis thaliana. Rhizosphere microorganisms that assimilated plant-derived 13C were capable of metabolic and signaling interactions with their plant hosts, as shown by their MAGs containing genes for phytohormone modulation, quorum sensing, and transport and metabolism of nutrients typical of those found in root exudates. XoxF-type methanol dehydrogenases were among the most abundant proteins identified in the rhizosphere metaproteomes. 13C-methanol proteomic SIP was used to test the hypothesis that XoxF was used to metabolize and assimilate methanol in the rhizosphere. We detected 7 13C-labeled XoxF proteins and identified methylotrophic pathways in the MAGs of 8 13C-labeled microorganisms, which supported the hypothesis. These two studies demonstrated the capability of proteomic SIP for functional characterization of active microorganisms in complex microbial communities