Engineering topics

Swenson, Tami L.

Publications and source records attributed to Swenson, Tami L..

5 records

DOE OSTI2022

Tracing Carbon Metabolism with Stable Isotope Metabolomics Reveals the Legacy of Diverse Carbon Sources in Soil

Tracking the metabolic activity of whole soil communities can improve our understanding of the transformation and fate of carbon in soils. For this work, we used stable isotope metabolomics to trace 13 C from nine labeled carbon sources into the water-soluble metabolite pool of an agricultural soil over time. Soil was amended with a mixture of all nine sources, with one source isotopically labeled in each treatment. We compared changes in the 13 C enrichment of metabolites with respect to carbon source and time over a 48-day incubation and contrasted differences between soluble sources (glucose, xylose, amino acids, etc.) and insoluble sources (cellulose and palmitic acid). Whole soil metabolite profiles varied singularly by time, while the composition of 13 C-labeled metabolites differed primarily by carbon source (R 2 = 0.68) rather than time (R 2 = 0.07), with source-specific differences persisting throughout incubations. The 13 C labeling of metabolites from insoluble carbon sources occurred slower than that from soluble sources but yielded a higher average atom percent (atom%) 13 C in metabolite markers of biomass (amino acids and nucleic acids). The 13 C enrichment of metabolite markers of biomass stabilized between 5 and 15 atom% 13 C by the end of incubations. Temporal patterns in the 13 C enrichment of tricarboxylic acid cycle intermediates, nucleobases (uracil and thymine), and by-products of DNA salvage (allantoin) closely tracked microbial activity. Our results demonstrate that metabolite production in soils is driven by the carbon source supplied to the community and that the fate of carbon in metabolites do not generally converge over time as a result of ongoing microbial processing and recycling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Substrate Utilization and Competitive Interactions Among Soil Bacteria Vary With Life-History Strategies

Microorganisms have evolved various life-history strategies to survive fluctuating resource conditions in soils. However, it remains elusive how the life-history strategies of microorganisms influence their processing of organic carbon, which may affect microbial interactions and carbon cycling in soils. Here, we characterized the genomic traits, exometabolite profiles, and interactions of soil bacteria representing copiotrophic and oligotrophic strategists. Isolates were selected based on differences in ribosomal RNA operon ( rrn ) copy number, as a proxy for life-history strategies, with pairs of “high” and “low” rrn copy number isolates represented within the Micrococcales, Corynebacteriales, and Bacillales. We found that high rrn isolates consumed a greater diversity and amount of substrates than low rrn isolates in a defined growth medium containing common soil metabolites. We estimated overlap in substrate utilization profiles to predict the potential for resource competition and found that high rrn isolates tended to have a greater potential for competitive interactions. The predicted interactions positively correlated with the measured interactions that were dominated by negative interactions as determined through sequential growth experiments. This suggests that resource competition was a major force governing interactions among isolates, while cross-feeding of metabolic secretion likely contributed to the relatively rare positive interactions observed. By connecting bacterial life-history strategies, genomic features, and metabolism, our study advances the understanding of the links between bacterial community composition and the transformation of carbon in soils.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Long-read metagenomics of soil communities reveals phylum-specific secondary metabolite dynamics

Abstract Microbial biosynthetic gene clusters (BGCs) encoding secondary metabolites are thought to impact a plethora of biologically mediated environmental processes, yet their discovery and functional characterization in natural microbiomes remains challenging. Here we describe deep long-read sequencing and assembly of metagenomes from biological soil crusts, a group of soil communities that are rich in BGCs. Taking advantage of the unusually long assemblies produced by this approach, we recovered nearly 3,000 BGCs for analysis, including 712 full-length BGCs. Functional exploration through metatranscriptome analysis of a 3-day wetting experiment uncovered phylum-specific BGC expression upon activation from dormancy, elucidating distinct roles and complex phylogenetic and temporal dynamics in wetting processes. For example, a pronounced increase in BGC transcription occurs at night primarily in cyanobacteria, implicating BGCs in nutrient scavenging roles and niche competition. Taken together, our results demonstrate that long-read metagenomic sequencing combined with metatranscriptomic analysis provides a direct view into the functional dynamics of BGCs in environmental processes and suggests a central role of secondary metabolites in maintaining phylogenetically conserved niches within biocrusts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Characteristics of Wetting-Induced Bacteriophage Blooms in Biological Soil Crust

Biological soil crusts (biocrusts) are photosynthetic “hot spots” in deserts and cover ~12% of the Earth’s terrestrial surface, and yet they face an uncertain future given expected shifts in rainfall events. Laboratory wetting of biocrust communities is known to cause a bloom of Firmicutes which rapidly become dominant community members within 2 days after emerging from a sporulated state. We hypothesized that their bacteriophages (phages) would respond to such a dramatic increase in their host’s abundance. In our experiment, wetting caused Firmicutes to bloom and triggered a significant depletion of cyanobacterial diversity. We used genome-resolved metagenomics to link phage to their hosts and found that the bloom of the genus Bacillus correlated with a dramatic increase in the number of Caudovirales phages targeting these diverse spore-formers ( r = 0.762). After 2 days, we observed dramatic reductions in the relative abundances of Bacillus , while the number of Bacillus phages continued to increase, suggestive of a predator-prey relationship. We found predicted auxiliary metabolic genes (AMGs) associated with sporulation in several Caudovirales genomes, suggesting that phages may influence and even benefit from sporulation dynamics in biocrusts. Prophage elements and CRISPR-Cas repeats in Firmicutes metagenome-assembled genomes (MAGs) provide evidence of recent infection events by phages, which were corroborated by mapping viral contigs to their host MAGs. Combined, these findings suggest that the blooming Firmicutes become primary targets for biocrust Caudovirales phages, consistent with the classical “kill-the-winner” hypothesis. This work forms part of an overarching research theme studying the effects of a changing climate on biological soil crust (biocrust) in the Southwestern United States. To our knowledge, this study was the first to characterize bacteriophages in biocrust and offers a view into the ecology of phages in response to a laboratory wetting experiment. The phages identified here represent lineages of Caudovirales , and we found that the dynamics of their interactions with their Firmicutes hosts explain the collapse of a bacterial bloom that was induced by wetting. Moreover, we show that phages carried host-altering metabolic genes and found evidence of proviral infection and CRISPR-Cas repeats within host genomes. Our results suggest that phages exert controls on population density by lysing dominant bacterial hosts and that they further impact biocrust by acquiring host genes for sporulation. Future research should explore how dominant these phages are in other biocrust communities and quantify how much the control and lysis of blooming populations contributes to nutrient cycling in biocrusts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Learning representations of microbe–metabolite interactions

Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We illustrate with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.

59 BASIC BIOLOGICAL SCIENCES↗