McLean Craig

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  • Article
    Carbon assimilation strategies in ultrabasic groundwater: clues from the integrated study of a serpentinization-influenced aquifer
    (American Society for Microbiology, 2020-03-10) Seyler, Lauren M. ; Brazelton, William J. ; McLean, Craig ; Putman, Lindsay I. ; Hyer, Alex ; Kubo, Michael D. Y. ; Hoehler, Tori M. ; Cardace, Dawn ; Schrenk, Matthew O.
    Serpentinization is a low-temperature metamorphic process by which ultramafic rock chemically reacts with water. Such reactions provide energy and materials that may be harnessed by chemosynthetic microbial communities at hydrothermal springs and in the subsurface. However, the biogeochemistry mediated by microbial populations that inhabit these environments is understudied and complicated by overlapping biotic and abiotic processes. We applied metagenomics, metatranscriptomics, and untargeted metabolomics techniques to environmental samples taken from the Coast Range Ophiolite Microbial Observatory (CROMO), a subsurface observatory consisting of 12 wells drilled into the ultramafic and serpentinite mélange of the Coast Range Ophiolite in California. Using a combination of DNA and RNA sequence data and mass spectrometry data, we found evidence for several carbon fixation and assimilation strategies, including the Calvin-Benson-Bassham cycle, the reverse tricarboxylic acid cycle, the reductive acetyl coenzyme A (acetyl-CoA) pathway, and methylotrophy, in the microbial communities inhabiting the serpentinite-hosted aquifer. Our data also suggest that the microbial inhabitants of CROMO use products of the serpentinization process, including methane and formate, as carbon sources in a hyperalkaline environment where dissolved inorganic carbon is unavailable.
  • Article
    AutoTuner: high fidelity and robust parameter selection for metabolomics data processing
    (American Chemical Society, 2020-03-26) McLean, Craig ; Kujawinski, Elizabeth B.
    Untargeted metabolomics experiments provide a snapshot of cellular metabolism but remain challenging to interpret due to the computational complexity involved in data processing and analysis. Prior to any interpretation, raw data must be processed to remove noise and to align mass-spectral peaks across samples. This step requires selection of dataset-specific parameters, as erroneous parameters can result in noise inflation. While several algorithms exist to automate parameter selection, each depends on gradient descent optimization functions. In contrast, our new parameter optimization algorithm, AutoTuner, obtains parameter estimates from raw data in a single step as opposed to many iterations. Here, we tested the accuracy and the run-time of AutoTuner in comparison to isotopologue parameter optimization (IPO), the most commonly used parameter selection tool, and compared the resulting parameters’ influence on the properties of feature tables after processing. We performed a Monte Carlo experiment to test the robustness of AutoTuner parameter selection and found that AutoTuner generated similar parameter estimates from random subsets of samples. We conclude that AutoTuner is a desirable alternative to existing tools, because it is scalable, highly robust, and very fast (∼100–1000× speed improvement from other algorithms going from days to minutes). AutoTuner is freely available as an R package through BioConductor.
  • Article
    Distinct siderophores contribute to iron cycling in the mesopelagic at Station ALOHA
    (Frontiers Media, 2018-03-01) Bundy, Randelle M. ; Boiteau, Rene M. ; McLean, Craig ; Turk-Kubo, Kendra A. ; McIlvin, Matthew R. ; Saito, Mak A. ; Van Mooy, Benjamin A. S. ; Repeta, Daniel J.
    The distribution of dissolved iron (Fe), total organic Fe-binding ligands, and siderophores were measured between the surface and 400 m at Station ALOHA, a long term ecological study site in the North Pacific Subtropical Gyre. Dissolved Fe concentrations were low throughout the water column and strong organic Fe-binding ligands exceeded dissolved Fe at all depths; varying from 0.9 nmol L−1 in the surface to 1.6 nmol L−1 below 150 m. Although Fe does not appear to limit microbial production, we nevertheless found siderophores at nearly all depths, indicating some populations of microbes were responding to Fe stress. Ferrioxamine siderophores were most abundant in the upper water column, with concentrations between 0.1 and 2 pmol L−1, while a suite of amphibactins were found below 200 m with concentrations between 0.8 and 11 pmol L−1. The distinct vertical distribution of ferrioxamines and amphibactins may indicate disparate strategies for acquiring Fe from dust in the upper water column and recycled organic matter in the lower water column. Amphibactins were found to have conditional stability constants (log KcondFeL1,Fe′) ranging from 12.0 to 12.5, while ferrioxamines had much stronger conditional stability constants ranging from 14.0 to 14.4, within the range of observed L1 ligands by voltammetry. We used our data to calculate equilibrium Fe speciation at Station ALOHA to compare the relative concentration of inorganic and siderophore complexed Fe. The results indicate that the concentration of Fe bound to siderophores was up to two orders of magnitude higher than inorganic Fe, suggesting that even if less bioavailable, siderophores were nevertheless a viable pathway for Fe acquisition by microbes at our study site. Finally, we observed rapid production of ferrioxamine E by particle-associated bacteria during incubation of freshly collected sinking organic matter. Fe-limitation may therefore be a factor in regulating carbon metabolism and nutrient regeneration in the mesopelagic.
  • Thesis
    A metabolic lens on phytoplankton physiology
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2021-09) McLean, Craig
    Phytoplankton are communities of diverse groups of prokaryotic and eukaryotic single-celled organisms responsible for nearly 50% of global primary production. The relative abundance of individual groups changes dynamically in response to environmental perturbations. Recent studies suggest that such changes are primarily driven by the distinct physiological responses employed by each group towards a particular perturbation. Although knowledge of some of these responses has come to light in recent years, many aspects of their metabolisms remain unknown. We attempt to address this gap by studying the metabolism of several phytoplankton groups using metabolomics. Firstly, we developed a method to enhance the analysis of untargeted metabolomics data. Secondly, we constructed two conceptual models describing how metabolism of the raphidophyte Heterosigma akashiwo responds to phosphorus and nitrogen stress. These conceptual models revealed several new stress response mechanisms not previously reported in other phytoplankton. Finally, we compared the metabolic changes of several distinct phytoplankton groups to uncover possible adaptation and acclimations that distinguish them. This analysis revealed several pathways and metabolites that represent the studied groups. The contributions of these pathways and metabolites towards physiology may support the ecological fitness of these organisms.