Aria S. Hahn

MetaPathways v2.5: Quantitative functional, taxonomic, and usability improvements

Summary: Next-generation sequencing is producing vast amounts of sequence information from natural and engineered ecosystems. Although this data deluge has an enormous potential to transform our lives, knowledge creation and translation need software applications that scale with increasing data processing and analysis requirements. Here, we present improvements to MetaPathways, an annotation and analysis pipeline for environmental sequence information that expedites this transformation. We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure. Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications. Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database. Availability and implementation: MetaPathways v2.5 is available on GitHub: http://github.com/hallamlab/metapathways2. Contact: shallam@mail.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Rare taxa have potential to make metabolic contributions in enhanced biological phosphorus removal ecosystems

Enhanced biological phosphorus removal (EBPR) relies on diverse but specialized microbial communities to mediate the cycling and ultimate removal of phosphorus from municipal wastewaters. However, little is known about microbial activity and dynamics in relation to process fluctuations in EBPR ecosystems. Here, we monitored temporal changes in microbial community structure and potential activity across each bioreactor zone in a pilot-scale EBPR treatment plant by examining the ratio of small subunit ribosomal RNA (SSU rRNA) to SSU rRNA gene (rDNA) over a 120 day study period. Although the majority of operational taxonomic units (OTUs) in the EBPR ecosystem were rare, many maintained high potential activities based on SSU rRNA : rDNA ratios, suggesting that rare OTUs contribute substantially to protein synthesis potential in EBPR ecosystems. Few significant differences in OTU abundance and activity were observed between bioreactor redox zones, although differences in temporal activity were observed among phylogenetically cohesive OTUs. Moreover, observed temporal activity patterns could not be explained by measured process parameters, suggesting that other ecological drivers, such as grazing or viral lysis, modulated community interactions. Taken together, these results point towards complex interactions selected for within the EBPR ecosystem and highlight a previously unrecognized functional potential among low abundance microorganisms in engineered ecosystems.

Function and functional redundancy in microbial systems

Microbial communities often exhibit incredible taxonomic diversity, raising questions regarding the mechanisms enabling species coexistence and the role of this diversity in community functioning. On the one hand, many coexisting but taxonomically distinct microorganisms can encode the same energy-yielding metabolic functions, and this functional redundancy contrasts with the expectation that species should occupy distinct metabolic niches. On the other hand, the identity of taxa encoding each function can vary substantially across space or time with little effect on the function, and this taxonomic variability is frequently thought to result from ecological drift between equivalent organisms. Here, we synthesize the powerful paradigm emerging from these two patterns, connecting the roles of function, functional redundancy and taxonomy in microbial systems. We conclude that both patterns are unlikely to be the result of ecological drift, but are inevitable emergent properties of open microbial systems resulting mainly from biotic interactions and environmental and spatial processes.Microbial communities may often be composed of a wide diversity of taxa that perform similar functions. Here, the authors discuss the roles of function, functional redundancy and taxonomy in microbial community assembly and coexistence.

Draft Genome Sequence of the Pelagic Photoferrotroph Chlorobium phaeoferrooxidans

ABSTRACT Here, we report the draft genome sequence of Chlorobium phaeoferrooxidans, a photoferrotrophic member of the genus Chlorobium in the phylum Chlorobi. This genome sequence provides insight into the metabolic capacity that underpins photoferrotrophy within low-light-adapted pelagic Chlorobi.

Nutrient Acquisition and the Metabolic Potential of Photoferrotrophic Chlorobi

Anoxygenic photosynthesis evolved prior to oxygenic photosynthesis and harnessed energy from sunlight to support biomass production on the early Earth. Models that consider the availability of electron donors predict that anoxygenic photosynthesis using Fe(II), known as photoferrotrophy, would have supported most global primary production before the proliferation of oxygenic phototrophs at approximately 2.3 billion years ago. These photoferrotrophs have also been implicated in the deposition of banded iron formations, the world’s largest sedimentary iron ore deposits that formed mostly in late Archean and early Proterozoic Eons. In this work we present new data and analyses that illuminate the metabolic capacity of photoferrotrophy in the phylum Chlorobi. Our laboratory growth experiments and biochemical analyses demonstrate that photoferrotrophic Chlorobi are capable of assimilatory sulfate reduction and nitrogen fixation under sulfate and nitrogen limiting conditions, respectively. Furthermore, the evolutionary histories of key enzymes in both sulfur (CysH and CysD) and nitrogen fixation (NifDKH) pathways are convoluted; protein phylogenies, however, suggest that early Chlorobi could have had the capacity to assimilate sulfur and fix nitrogen. We argue, then, that the capacity for photoferrotrophic Chlorobi to acquire these key nutrients enabled them to support primary production and underpin global biogeochemical cycles in the Precambrian.

FragGeneScan-plus for scalable high-throughput short-read open reading frame prediction

A fundamental step in the analysis of environmental sequence information is the prediction of potential genes or open reading frames (ORFs) encoding the metabolic potential of individual cells and entire microbial communities. FragGeneScan, a software designed to predict intact and incomplete ORFs on short sequencing reads combines codon usage bias, sequencing error models and start/stop codon patterns in a hidden Markov model to find the most likely path of hidden states from a given input sequence, provides a promising route for gene recovery in environmental datasets with incomplete assemblies. However, the current implementation of FragGeneScan does not scale efficiently with increasing input data size. Thus, FragGeneScan cannot be applied to contemporary environmental datasets that can exceed 100s of Gb. Here, we present FragGeneScan-Plus, an improved implementation of the FragGeneScan gene prediction model that leverages algorithmic thread synchronization and efficient in-memory data management to utilize multiple CPU cores without blocking I/O operations. FragGeneScan-Plus can process data approximately 5-times faster than FragGeneScan using a single core and approximately 50-times faster using eight hyper-threaded cores when benchmarked against simulated and real world environmental datasets.

Metagenomes Reveal Global Distribution of Bacterial Steroid Catabolism in Natural, Engineered, and Host Environments

ABSTRACT Steroids are abundant growth substrates for bacteria in natural, engineered, and host-associated environments. This study analyzed the distribution of the aerobic 9,10-seco steroid degradation pathway in 346 publically available metagenomes from diverse environments. Our results show that steroid-degrading bacteria are globally distributed and prevalent in particular environments, such as wastewater treatment plants, soil, plant rhizospheres, and the marine environment, including marine sponges. Genomic signature-based sequence binning recovered 45 metagenome-assembled genomes containing a majority of 9,10-seco pathway genes. Only Actinobacteria and Proteobacteria were identified as steroid degraders, but we identified several alpha- and gammaproteobacterial lineages not previously known to degrade steroids. Actino- and proteobacterial steroid degraders coexisted in wastewater, while soil and rhizosphere samples contained mostly actinobacterial ones. Actinobacterial steroid degraders were found in deep ocean samples, while mostly alpha- and gammaproteobacterial ones were found in other marine samples, including sponges. Isolation of steroid-degrading bacteria from sponges confirmed their presence. Phylogenetic analysis of key steroid degradation proteins suggested their biochemical novelty in genomes from sponges and other environments. This study shows that the ecological significance as well as taxonomic and biochemical diversity of bacterial steroid degradation has so far been largely underestimated, especially in the marine environment. IMPORTANCE Microbial steroid degradation is a critical process for biomass decomposition in natural environments, for removal of important pollutants during wastewater treatment, and for pathogenesis of bacteria associated with tuberculosis and other bacteria. To date, microbial steroid degradation was mainly studied in a few model organisms, while the ecological significance of steroid degradation remained largely unexplored. This study provides the first analysis of aerobic steroid degradation in diverse natural, engineered, and host-associated environments via bioinformatic analysis of an extensive metagenome data set. We found that steroid-degrading bacteria are globally distributed and prevalent in wastewater treatment plants, soil, plant rhizospheres, and the marine environment, especially in marine sponges. We show that the ecological significance as well as the taxonomic and biochemical diversity of bacterial steroid degradation has been largely underestimated. This study greatly expands our ecological and evolutionary understanding of microbial steroid degradation. Microbial steroid degradation is a critical process for biomass decomposition in natural environments, for removal of important pollutants during wastewater treatment, and for pathogenesis of bacteria associated with tuberculosis and other bacteria. To date, microbial steroid degradation was mainly studied in a few model organisms, while the ecological significance of steroid degradation remained largely unexplored. This study provides the first analysis of aerobic steroid degradation in diverse natural, engineered, and host-associated environments via bioinformatic analysis of an extensive metagenome data set. We found that steroid-degrading bacteria are globally distributed and prevalent in wastewater treatment plants, soil, plant rhizospheres, and the marine environment, especially in marine sponges. We show that the ecological significance as well as the taxonomic and biochemical diversity of bacterial steroid degradation has been largely underestimated. This study greatly expands our ecological and evolutionary understanding of microbial steroid degradation.

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools.

FAST: Fast annotation with synchronized threads

FAST is a multi-threaded, I/O optimized Seed-and-Extend alignment program. FAST is extensible to nucleotide sequences making it comparable to both BLASTn and BLASTp, and also features several new usage flags reporting only HSPs meeting user defined e-value cut-offs. FASTs threaded database construction allows fast, low memory database construction e.g., RefSeq (9.4GB) can be indexed in under 5 minutes using 20 threads. The threaded database construction gives users the ability to create custom databases on demand which is useful for tasks requiring self-alignment, such as network construction [30]. Finally, FAST supports incremental database construction enabling users to keep their databases up-to-date by adding sequences without suffering the cost of reformatting the entire database. The FAST source is freely available through GitHub https:// github.com/hallamlab/FAST and test datasets can be found on Dropbox https://www.dropbox.com/sh/xvvavweuzgqybc4/ AAAWCrRnol67ZsXi2qLQWUuOa?

GutCyc: a Multi-Study Collection of Human Gut Microbiome Metabolic Models

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GUTCYC, a compendium of environmental pathway genome databases constructed from 418 assembled human microbiome datasets using METAPATHWAYS, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the PATHWAY TOOLS software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GUTCYC provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GUTCYC data products are searchable online, or may be downloaded and explored locally using METAPATHWAYS and PATHWAY TOOLS.