Ongoing Projects

    San Pedro Ocean Time Series Microbial Observatory

    The San Pedro Ocean Time-series (SPOT) is an ongoing collection of oceanographic data from the San Pedro Channel, off the coast of Los Angeles. The Fuhrman lab has been studying the ecological patterns of the microbial community composition at SPOT for over 20 years.

    Global Marine Biogeographies through CBIOMES

    The Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems (CBIOMES) seeks to develop and apply quantitative models of the structure and function of marine microbial communities at seasonal and basin scales. Our CBIOMES project focus is on microbial growth, interactions and biogeographies from ‘omics data.

    515/916 Primer Validation

    Our 515-926 primer pair not only amplifies the ssu rRNA (16S or 18S) of the vast majority of known organisms in all three domains, but testing with our prokaryotic mock communities shows that the results are remarkably quantitative.

    For a set of recommendations on how to use the Fuhrman Lab’s mock communities and PCR primers , please see our Methods or selected publications: Parada et al. 2015, Needham and Fuhrman 2016, Walters et al. 2016, Yeh et al 2018.

    Virus/Host Community Dynamics

    Bacterial and archaeal populations are shaped by resource availability as well as viral lysis and protist grazing. Bottom-up and top-down controls are ultimately equally important. We use dilution experiments, time-series data, network analysis, and statistical tools to simultaneously assess top-down and bottom-up regulation on community-wide abundance and diversity.

    Selected publications: Dart, et al. 2023, Ignacio-Espinoza, et al. 2019, Ahlgren, et al. 2019, Cram et al. 2016

    Growth rate predictions from metagenomic data

    Maximum growth rate is a fundamental characteristic of microbial species that can give us a great deal of insight into their ecological role. The recently developed a tool, gRodon, enables the prediction of the maximum growth rate of an organism from genomic data on the basis of codon usage patterns. Our work and that of other groups suggest that such predictors can be applied to mixed-species communities in order to derive estimates of the average community-wide maximum growth rate.

    Selected publications: Weissman, et al. 2021 and Weissman, et al. 2022

    MIM: Machine Learning, Systems Modeling, and Experimental Approaches to Understand the Universal Rules of Life of Microbiota Using Marine Time Series Data

    In collaboration with Fengzhu Sun

    Metagenomics and Metatranscriptomics

    Our time-series samples offer unique opportunities to “go back in time” and re-analyze archived material using the most modern techniques. Using metagenomics and bioinformatics tools such as Anvi’o, we are addressing questions such as “How do genomic variants change over time?” in ways that can resolve these changes at the gene or allele level.

    In concert with metagenomics, we are also mapping parallel metatranscriptomes to observe changing patterns of gene expression between adjacent sites and also over seasons. better understand what functions particular organisms are performing under different conditions.

    Reference  Sieradzki et al 2019

    Recent Work and Data Availabilty

    An overview of recent work in our lab can be found on this poster from the 2022 Marine Microbes Gordon Conference.

    Much of the lab’s published data is publicly available through BCO-DMO.

    Archival Projects

    • To study how anthropogenic inputs affect the microbial community composition and function, we analyze samples from the Port of Los Angeles, with from the SPOT site  and also a nearshore site near Catalina Island as minimally impacted controls. Using a variety of tools, we are assessing the resistance of the naturally occurring community to pollutants like heavy metals and various aromatic hydrocarbons.

      We also apply a cutting edge combination of Stable Isotope Probing (SIP) and high throughput sequencing to reveal which of the community members can metabolize pollutants and incorporate them into their biomass, directly linking diversity and function.

    • We have fully sequenced one such culture, named Candidatus Nitrosomarinus catalina SPOT01, a novel strain that is less warm-temperature tolerant than other cultivated Thaumarchaeota. Using metagenomic recruitment, strain SPOT01 comprises a major portion of Thaumarchaeota (4–54%) in temperate Pacific waters.

      We are currently investigating archaeal global distributions and virus infectivity, among other aspects.

      Reference: Ahlgren et al. 2017

    • A major issue in microbial ecology research is how to best cluster similarly-functioning related organisms together and how to split ones that are related but ecologically different. This is essentially trying to define ecological species. While microbiologists frequently use marker genes and apply standard cutoffs of similarity, e.g. 99% similar 16S rRNA (or, 97%, which we consider too coarse), it is not clear what levels are truly most appropriate for ecological research, and how it may differ depending on the environment and scientific questions at hand.

      By taking advantage of the most recent sequencing capabilities, and combining time-series data and information from the literature and major databases, we are able to address questions relating to suitable genes for study and the level of resolution needed to relate diversity to ecological processes without excessive lumping or splitting. These are not expected to be the same for all questions and for all organisms. For example, we expect that resource utilization may be studied at a coarser sequence resolution than viral susceptibility.  This work uses both marker genes and metagenomes.

      Reference: Needham et al 2017