skip to main content


Search for: All records

Creators/Authors contains: "Meredith, Laura K."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline calledvolcalcthat uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate howvolcalcmight be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. Withvolcalc, we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. Thevolcalcpackage is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems.

     
    more » « less
  2. Use this package to calculate estimated relative volatility index values for organic compounds based on functional group contributions. Calculation uses the SIMPOL.1 method (Prankow and Asher, 2008) or modified SIMPOL.1 method as in Meredith et al. (2023). 
    more » « less
  3. Abstract

    Drought can affect the capacity of soils to emit and consume biogenic volatile organic compounds (VOCs). Here we show the impact of prolonged drought followed by rewetting and recovery on soil VOC fluxes in an experimental rainforest. Under wet conditions the rainforest soil acts as a net VOC sink, in particular for isoprenoids, carbonyls and alcohols. The sink capacity progressively decreases during drought, and at soil moistures below ~19%, the soil becomes a source of several VOCs. Position specific13C-pyruvate labeling experiments reveal that soil microbes are responsible for the emissions and that the VOC production is higher during drought. Soil rewetting induces a rapid and short abiotic emission peak of carbonyl compounds, and a slow and long biotic emission peak of sulfur-containing compounds. Results show that, the extended drought periods predicted for tropical rainforest regions will strongly affect soil VOC fluxes thereby impacting atmospheric chemistry and climate.

     
    more » « less
  4. Abstract

    Drought impacts on microbial activity can alter soil carbon fate and lead to the loss of stored carbon to the atmosphere as CO2and volatile organic compounds (VOCs). Here we examined drought impacts on carbon allocation by soil microbes in the Biosphere 2 artificial tropical rainforest by tracking13C from position-specific13C-pyruvate into CO2and VOCs in parallel with multi-omics. During drought, efflux of13C-enriched acetate, acetone and C4H6O2(diacetyl) increased. These changes represent increased production and buildup of intermediate metabolites driven by decreased carbon cycling efficiency. Simultaneously,13C-CO2efflux decreased, driven by a decrease in microbial activity. However, the microbial carbon allocation to energy gain relative to biosynthesis was unchanged, signifying maintained energy demand for biosynthesis of VOCs and other drought-stress-induced pathways. Overall, while carbon loss to the atmosphere via CO2decreased during drought, carbon loss via efflux of VOCs increased, indicating microbially induced shifts in soil carbon fate.

     
    more » « less
  5. null (Ed.)
    Soils harbor complex biological processes intertwined with metabolic inputs from microbes and plants. Measuring the soil metabolome can reveal active metabolic pathways, providing insight into the presence of specific organisms and ecological interactions. A subset of the metabolome is volatile; however, current soil studies rarely consider volatile organic compounds (VOCs), contributing to biases in sample processing and metabolomic analytical techniques. Therefore, we hypothesize that overall, the volatility of detected compounds measured using current metabolomic analytical techniques will be lower than undetected compounds, a reflection of missed VOCs. To illustrate this, we examined a peatland metabolomic dataset collected using three common metabolomic analytical techniques: nuclear magnetic resonance (NMR), gas chromatography-mass spectroscopy (GC-MS), and fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). We mapped the compounds to three metabolic pathways (monoterpenoid biosynthesis, diterpenoid biosynthesis, and polycyclic aromatic hydrocarbon degradation), chosen for their activity in peatland ecosystems and involvement of VOCs. We estimated the volatility of the compounds by calculating relative volatility indices (RVIs), and as hypothesized, the average RVI of undetected compounds within each of our focal pathways was higher than detected compounds ( p < 0.001). Moreover, higher RVI compounds were absent even in sub-pathways where lower RVI compounds were observed. Our findings suggest that typical soil metabolomic analytical techniques may overlook VOCs and leave missing links in metabolic pathways. To more completely represent the volatile fraction of the soil metabolome, we suggest that environmental scientists take into consideration these biases when designing and interpreting their data and/or add direct online measurement methods that capture the integral role of VOCs in soil systems. 
    more » « less
  6. Trace gas cycling is an important feature of the soil system [...] 
    more » « less
  7. Abstract. The uptake of carbonyl sulfide (COS) by terrestrial plants is linked tophotosynthetic uptake of CO2 as these gases partly share the sameuptake pathway. Applying COS as a photosynthesis tracer in models requires anaccurate representation of biosphere COS fluxes, but these models have notbeen extensively evaluated against field observations of COS fluxes. In thispaper, the COS flux as simulated by the Simple Biosphere Model, version 4(SiB4), is updated with the latest mechanistic insights and evaluated with siteobservations from different biomes: one evergreen needleleaf forest, twodeciduous broadleaf forests, three grasslands, and two crop fields spread overEurope and North America. We improved SiB4 in several ways to improve itsrepresentation of COS. To account for the effect of atmospheric COS molefractions on COS biosphere uptake, we replaced the fixed atmospheric COS molefraction boundary condition originally used in SiB4 with spatially andtemporally varying COS mole fraction fields. Seasonal amplitudes of COS molefractions are ∼50–200 ppt at the investigated sites with aminimum mole fraction in the late growing season. Incorporating seasonalvariability into the model reduces COS uptake rates in the late growingseason, allowing better agreement with observations. We also replaced theempirical soil COS uptake model in SiB4 with a mechanistic model thatrepresents both uptake and production of COS in soils, which improves thematch with observations over agricultural fields and fertilized grasslandsoils. The improved version of SiB4 was capable of simulating the diurnal andseasonal variation in COS fluxes in the boreal, temperate, and Mediterraneanregion. Nonetheless, the daytime vegetation COS flux is underestimated onaverage by 8±27 %, albeit with large variability across sites. On aglobal scale, our model modifications decreased the modeled COS terrestrialbiosphere sink from 922 Gg S yr−1 in the original SiB4 to753 Gg S yr−1 in the updated version. The largest decrease influxes was driven by lower atmospheric COS mole fractions over regions withhigh productivity, which highlights the importance of accounting forvariations in atmospheric COS mole fractions. The change to a different soilmodel, on the other hand, had a relatively small effect on the globalbiosphere COS sink. The secondary role of the modeled soil component in theglobal COS budget supports the use of COS as a global photosynthesis tracer. Amore accurate representation of COS uptake in SiB4 should allow for improvedapplication of atmospheric COS as a tracer of local- to global-scaleterrestrial photosynthesis. 
    more » « less
  8. Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyze 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical, and gene neighborhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter. 
    more » « less