bioRxiv ScienceSearch

Biology subjects

McMahon, K. D.

Publications and source records attributed to McMahon, K. D..

7 recordsLinked to original sources

Extracellular electron transfer may be an overlooked contribution to pelagic respiration in humic-rich freshwater lakes

Humic lakes and ponds receive large amounts of terrestrial carbon and are important components of the global carbon cycle, yet how their redox cycling influences the carbon budget is not fully understood. Here we compared metagenomes obtained from a humic bog and a clearwater eutrophic lake, and found a much larger number of genes that might be involved in extracellular electron transfer (EET) for iron redox reactions and humic substance (HS) reduction in the bog than in the clearwater lake, consistent with the much higher iron and HS levels in the bog. These genes were particularly rich in the bogs anoxic hypolimnion, and were found in diverse bacterial lineages, some of which are relatives of known iron oxidizers or iron/HS reducers. We hypothesize that HS may be a previously overlooked electron acceptor and EET-enabled redox cycling may be important in pelagic respiration and greenhouse gas budget in humic-rich freshwater lakes.

ecology

Integrated ‘omic’ analyses provide evidence that a Ca. Accumulibacter phosphatis strain performs denitrification under micro-aerobic conditions

The unique and complex metabolism of Candidatus Accumulibacter phosphatis has been used for decades for efficiently removing phosphorus during wastewater treatment in reactor configurations that expose the activated sludge to cycles of anaerobic and aerobic conditions. The ability of Accumulibacter to grow and remove phosphorus during cyclic anaerobic and anoxic conditions has also been investigated as a metabolism that could lead to simultaneous removal of nitrogen and phosphorus by a single organism. However, although phosphorus removal under cyclic anaerobic and anoxic conditions has been demonstrated, elucidating the role of Accumulibacter in this process has been challenging, since experimental research describes contradictory findings and none of the published Accumulibacter genomes show the existence of a complete pathway for denitrification. In this study, we use an integrated omics analysis to elucidate the physiology of an Accumulibacter strain enriched in a reactor operated under cyclic anaerobic and micro-aerobic conditions. The reactors performance suggested the ability of the enriched Accumulibacter (clade IC) to simultaneously use oxygen and nitrate as electron acceptors under micro-aerobic conditions. A draft genome of this organism was assembled from metagenomic reads (hereafter referred to as Accumulibacter UW-LDO-IC) and used as a reference to examine transcript abundance throughout one reactor cycle. The genome of UW-LDO-IC revealed the presence of a full denitrification pathway. The observed patterns of transcript abundance showed evidence of co-regulation of the denitrifying genes along with a cbb3 cytochrome, which is characterized as having high affinity for oxygen, thus supporting the hypothesis that UW-LDO-IC can simultaneously respire nitrate and oxygen. Furthermore, we identified an FNR-like binding motif upstream of the coregulated genes, suggesting transcriptional level regulation of the expression of both denitrifying and respiratory pathways in Accumulibacter UW-LDO-IC. Taken together, the omics analysis provides strong evidence that Accumulibacter UW-LDO-IC simultaneously uses oxygen and nitrate as electron acceptors under micro-aerobic conditions.\n\nIMPORTANCECandidatus Accumulibater phosphatis is widely found in full-scale wastewater treatment plants, where it has been identified as the key organism for biological removal of phosphorus. Since aeration can account for 50% of the energy use during wastewater treatment, micro-aerobic conditions for wastewater treatment have emerged as a cost-effective alternative to conventional biological nutrient removal processes. Our study provides strong genomics-based evidence that Accumulibacter is not only the main organism contributing to phosphorus removal under micro-aerobic conditions, but also that this organism simultaneously respires nitrate and oxygen in this environment, consequently removing nitrogen and phosphorus from the wastewater. Such activity could be harnessed in innovative designs for cost-effective and energy-efficient optimization of wastewater treatment systems.

microbiology

Connections between freshwater carbon and nutrient cycles revealed through reconstructed population genomes

Metabolic processes at the microbial scale influence ecosystem functions because microbes are responsible for much of the carbon and nutrient cycling in freshwater. One approach to predict the metabolic capabilities of microbial communities is to search for functional marker genes in metagenomes. However, this approach does not provide context about co-occurrence with other metabolic traits within an organism or detailed taxonomy about those organisms. Here, we combine a functional marker gene analysis with metabolic pathway prediction of microbial population genomes (MAGs) assembled from metagenomic time series in eutrophic Lake Mendota and humic Trout Bog to identify how carbon and nutrient cycles are connected in freshwater. We found that phototrophy, carbon fixation, and nitrogen fixation pathways co-occurred in Cyanobacteria MAGs in Lake Mendota and in Chlorobiales MAGs in Trout Bog. Cyanobacteria MAGs also had strong temporal correlations to functional marker genes for nitrogen fixation in several years. Genes encoding steps in the nitrogen and sulfur cycles varied in abundance and taxonomy by lake, potentially reflecting the availability and composition of inorganic nutrients in these systems. We were also able to identify which populations contained the greatest density and diversity of genes encoding glycoside hydrolases. Populations with many glycoside hydrolases also encoded pathways for sugar degradation. By using both MAGs and marker genes, we were better able to link functions to specific taxonomic groups in our metagenomic time series, enabling a more detailed understanding of freshwater microbial carbon and nutrient cycling.

microbiology

TaxAss: Leveraging Custom Databases Achieves Fine-Scale Taxonomic Resolution

Taxonomy assignment of freshwater microbial communities is limited by the minimally curated phylogenies used for large taxonomy databases. Here we introduce TaxAss, a taxonomy assignment workflow that classifies 16S rRNA gene amplicon data using two taxonomy reference databases: a large comprehensive database and a small ecosystem-specific database rigorously curated by scientists within a field. We applied TaxAss to five different freshwater datasets using the comprehensive Silva database and the freshwater-specific FreshTrain database. TaxAss increased the percent of the dataset classified compared to using only Silva, especially at fine-resolution family-species taxa levels, while across the freshwater test-datasets classifications increased by as much as 11-40 percent of total reads. A similar increase in classifications was not observed in a control mouse gut dataset, which was not expected to contain freshwater bacteria. TaxAss also maintained taxonomic richness compared to using only the FreshTrain across all taxa-levels from phylum to species. Without TaxAss, most organisms not represented in the FreshTrain were unclassified, but at fine taxa levels incorrect classifications became significant. We validated TaxAss using simulated amplicon data with known taxonomy and found that 96-99% of test sequences were correctly classified at fine resolution. TaxAss splits a datasets sequences into two groups based on their percent identity to reference sequences in the ecosystem-specific database. Sequences with high similarity to sequences in the ecosystem-specific database are classified using that database, and the others are classified using the comprehensive database. TaxAss is free and open source, and available at www.github.com/McMahonLab/TaxAss.\n\nIMPORTANCEMicrobial communities drive ecosystem processes, but microbial community composition analyses using 16S rRNA gene amplicon datasets are limited by the lack of fine-resolution taxonomy classifications. Coarse taxonomic groupings at phylum, class, and order level lump ecologically distinct organisms together. To avoid this, many researchers define operational taxonomic units (OTUs) based on clustered sequences, sequence variants, or unique sequences. These fine-resolution groupings are more ecologically relevant, but OTU definitions are dataset-dependent and cannot be compared between datasets. Microbial ecologists studying freshwater have curated a small, ecosystem-specific taxonomy database to provide consistent and up-to-date terminology. We created TaxAss, a workflow that leverages this database to assign taxonomy. We found that TaxAss improves fine-resolution taxonomic classifications (family, genus and species). Fine taxonomic groupings are more ecologically relevant, so they provide an alternative to OTU-based analyses that is consistent and comparable between datasets.

bioinformatics

Small subsets of highly connected taxa predict compositional change in microbial communities

For decades, ecological theory has predicted that the complexity of communities should be related to their stability. However, this prediction has rarely been tested empirically, because of both the difficulty of finding suitable systems where the question is tractable and the trouble of defining \"stability\" in real systems. Microbial communities provide the opportunity to investigate a related question: how does community connectivity relate to the rate of compositional turnover? We used a newly developed metric called community \"cohesion\" to test how microbial community connectivity relates to Bray-Curtis dissimilarity through time. In three long-term datasets, we found that stronger connectivity corresponded to lower rates of compositional turnover. Using two case studies of disturbed and reference communities, we found that the predictive power of community connectivity was diminished by external disturbance. Finally, we tested whether the highly connected taxa were disproportionately important in explaining compositional turnover. We found that subsets of highly connected \"keystone\" taxa, generally comprising 1-5% of community richness, explained community turnover better than using all taxa. Our results suggest that stronger biotic interactions within microbial community dynamics are stabilizing to community composition, and that highly connected taxa are good indicators of pending community shifts.

microbiology

Genome-Enabled Insights Into The Ecophysiology Of The Comammox Bacterium Candidatus Nitrospira nitrosa

The recently discovered comammox bacteria have the potential to completely oxidize ammonia to nitrate. These microorganisms are part of the Nitrospira genus and are present in a variety of environments, including Biological Nutrient Removal (BNR) systems. However, the physiological traits within and between comammox- and nitrite oxidizing bacteria (NOB)-like Nitrospira species have not been analyzed in these ecosystems. In this study, we identified Nitrospira strains dominating the nitrifying community of a sequencing batch reactor (SBR) performing BNR under micro-aerobic conditions. We recovered metagenomes-derived draft genomes from two Nitrospira strains: (1) Nitrospira sp. UW-LDO-01, a comammox-like organism classified as Candidatus Nitrospira nitrosa, and (2) Nitrospira sp. UW-LDO-02, a nitrite oxidizing strain belonging to the Nitrospira defluvii species. A comparative genomic analysis of these strains with other Nitrospira-like genomes identified genomic differences in Ca. Nitrospira nitrosa mainly attributed to each strains niche adaptation. Traits associated with energy metabolism also differentiate comammox from NOB-like genomes. We also identified several transcriptionally regulated adaptive traits, including stress tolerance, biofilm formation and micro-aerobic metabolism, which might explain survival of Nitrospira under multiple environmental conditions. Overall, our analysis expanded our understanding of the genetic functional features of Ca. Nitrospira nitrosa, and identified genomic traits that further illuminate the phylogenetic diversity and metabolic plasticity of the Nitrospira genus.

microbiology

High-Throughput Metabolic Network Analysis and Metatranscriptomics of a Cosmopolitan and Streamlined Freshwater Lineage

An explosion in the number of available genome sequences obtained through metagenomics and single-cell genomics has enabled a new view of the diversity of microbial life, yet we know surprisingly little about how microbes interact with each other or their environment. In fact, the majority of microbial species remain uncultivated, while our perception of their ecological niches is based on reconstruction of their metabolic potential. In this work, we demonstrate how the \"seed set framework\", which computes the set of compounds that an organism must acquire from its environment (1), enables computational analysis of metabolic reconstructions, while providing new insights into a microbes metabolic capabilities, such as nutrient use and auxotrophies. We apply this framework to members of the ubiquitous freshwater Actinobacterial lineage acI, confirming and extending previous experimental and genomic observations implying that acI bacteria are heterotrophs reliant on peptides and saccharides. We also present the first metatranscriptomic study of the acI lineage, revealing high expression of transport proteins and the light-harvesting protein actinorhodopsin. Putative transport proteins complement predictions of nutrients and essential metabolites while providing additional support to the hypothesis that members of the acI are photoheterotrophs.\n\nImportanceThe metabolic activity of uncultivated microorganisms contributes to numerous ecosystem processes, ranging from nutrient cycling in the environment to influencing human health and disease. Advances in sequencing technology have enabled the assembly of genomes for these microorganisms, but our ability to generate reference genomes far outstrips our ability to analyze them. Common approaches to analyzing microbial metabolism require reconstructing the entirety of an organisms metabolic pathways, or performing targeted searches for genes involved in a specific process. This paper presents a third approach, in which draft metabolic reconstructions are used to identify compounds through which an organism may interact with its environment. These compounds can then guide more intensive metabolic reconstruction efforts, and also provide new hypotheses about the specific contributions microbes make to ecosystem-scale metabolic processes.

microbiology