Biology subjects

Fuhrman, J. A.

Publications and source records attributed to Fuhrman, J. A..

16 recordsLinked to original sources

bioRxiv2025

The JEDI marker as a universal measure of planetary biodiversity

Despite its critical importance in the formation and maintenance of ecosystems and homeostasis on Earth, biodiversity remains a complex and non-unified concept. Consequently, standards for measuring global biodiversity are lacking, hindering our capacity to document Earths biota and track its change. Here, we propose the Joint, cellular life-Encompassing DIversity (JEDI) marker as a simple, effective and quantitative measure to assess and monitor biodiversity. The JEDI marker is a ribosomal RNA gene fragment that can be amplified from all domains of life using a single pair of PCR primers. We demonstrate the applicability and effectiveness of this approach for assessing biodiversity across ecological and biological scales, from holobionts to diverse ecosystems. In addition, we provide an automated bioinformatic workflow to support the standardised and reproducible analysis of the JEDI marker in future studies. While this approach is not free from trade-offs, we argue that its advantages outweigh its limitations by providing a unique, operational and scalable solution that builds on established infrastructure to integrate the microbial majority into biodiversity assessments and provide fundamental insights into organismal dynamics and associations across domains of life. Thus, the JEDI marker approach addresses the urgent need for a universal and standardised framework to effectively measure and monitor biodiversity at planetary scales in an era of profound global change.

ecology↗

bioRxiv2024

Phylogenetic proximity drives temporal succession of marine giant viruses in a five-year metagenomic time-series

Nucleocytoplasmic Large DNA Viruses (NCLDVs, also called giant viruses) are widespread in marine systems and infect a broad range of microbial eukaryotes (protists). Recent biogeographic work has provided global snapshots of NCLDV diversity and community composition across the worlds oceans, yet little information exists about the guiding rules underpinning their community dynamics over time. We leveraged a five-year monthly metagenomic time-series to quantify the community composition of NCLDVs off the coast of Southern California and characterize these populations temporal dynamics. NCLDVs were dominated by Algavirales (Phycodnaviruses, 59%) and Imitervirales (Mimiviruses, 36%). We identified clusters of NCLDVs with distinct classes of seasonal and non-seasonal temporal dynamics. Overall, NCLDV population abundances were often highly dynamic with a strong seasonal signal. The Imitervirales group had highest relative abundance in the more oligotrophic late summer and fall, while Algavirales did so in winter. Generally, closely related strains had similar temporal dynamics, suggesting that evolutionary history is a key driver of the temporal niche of marine NCLDVs. However, a few closely-related strains had drastically different seasonal dynamics, suggesting that while phylogenetic proximity often indicates ecological similarity, occasionally phenology can shift rapidly, possibly due to host-switching. Finally, we identified distinct functional content and possible host interactions of two major NCLDV orders-including connections of Imitervirales with primary producers like the diatom Chaetoceros and widespread marine grazers like Paraphysomonas and Spirotrichea ciliates. Together, our results reveal key insights on season-specific effect of phylogenetically distinct giant virus communities on marine protist metabolism, biogeochemical fluxes and carbon cycling.

ecology↗

bioRxiv2024

Predictable functional biogeography of marine microbial heterotrophs

Heterotrophic bacteria and archaea ( heteroprokaryotes) drive global carbon cycling, but how to quantitatively organize their functional complexity remains unclear. We generated a global-scale understanding of marine heteroprokaryotic functional biogeography by synthesizing genetic sequencing data with a mechanistic marine ecosystem model. We incorporated heteroprokaryotic diversity into the trait-based model along two axes: substrate lability and growth strategy. Using genetic sequences along three ocean transects, we compiled 21 heteroprokaryotic guilds and estimated their degree of optimization for rapid growth (copiotrophy). Data and model consistency indicated that gradients in grazing and substrate lability predominantly set biogeographical patterns, and identified deep-ocean slow copiotrophs whose ecological interactions control the surface accumulation of dissolved organic carbon.

ecology↗

bioRxiv2022

Benchmarking community-wide estimates of growth potential from metagenomes using codon usage statistics

Trait inference from mixed-species assemblages is a central problem in microbial ecology. Frequently, sequencing information from an environment is available, but phenotypic measurements from individual community members are not. With the increasing availability of molecular data for microbial communities, bioinformatic approaches that map metagenome to (meta)phenotype are needed. Recently, we developed a tool, gRodon, that 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 suggests that such predictors can be applied to mixed-species communities in order to derive estimates of the average community-wide maximum growth rate. Here, we present an improved maximum growth rate predictor designed for metagenomes that corrects a persistent GC bias in the original gRodon model for metagenomic prediction. We benchmark this predictor with simulated metagenomic datasets to show that it has superior performance on mixed-species communities relative to earlier models. We go on to provide guidance on data pre-processing, and show that calling genes from assembled contigs rather than directly from reads dramatically improves performance. Finally, we apply our predictor to large-scale metagenomic datasets from marine and human microbiomes to illustrate how community-wide growth prediction can be a powerful approach for hypothesis-generation. Altogether, we provide an updated tool with clear guidelines for users about the uses and pitfalls of metagenomic prediction of the average community-wide maximal growth rate.

bioinformatics↗

bioRxiv2021

Estimating the maximal growth rates of eukaryotic microbes from cultures and metagenomes via codon usage patterns

Microbial eukaryotes are ubiquitous in the environment and play important roles in key ecosystem processes, including accounting for a significant portion of global primary production. Yet, our tools for assessing the functional capabilities of eukaryotic microbes in the environment are quite limited because many microbes have yet to be grown in culture. Maximum growth rate is a fundamental parameter of microbial lifestyle that reveals important information about an organisms functional role in a community. We developed and validated a genomic estimator of maximum growth rate for eukaryotic microbes, enabling the assessment of growth potential for organisms and communities directly in the environment. We produced a database of over 700 maximum growth rate predictions from genomes, transcriptomes, and metagenome-assembled genomes. By comparing the maximal growth rates of existing culture collections with environmentally-derived genomes we found that, unlike for prokaryotes, culture collections of microbial eukaryotes are only minimally biased in terms of growth potential. We then extended our tool to make community-wide estimates of growth potential from over 500 marine metagenomes, mapping growth potential across the global oceans. We found that prokaryotic and eukaryotic communities have highly correlated growth potentials near the ocean surface, but there is no correlation in their genomic potentials deeper in the water column. This suggests that fast growing eukaryotes and prokaryotes thrive under similar conditions at the ocean surface, but that there is a decoupling of these communities as resources become scarce deeper in the water column.

microbiology↗

bioRxiv2020

Evaluating and Improving SSU rRNA PCR Primer Coverage via Metagenomes from Global Ocean Surveys

Small subunit ribosomal RNA (SSU rRNA) amplicon sequencing can quantitatively and comprehensively profile natural microbiomes, representing a critically important tool for studying diverse global ecosystems. However, results will only be accurate if PCR primers perfectly match the rRNA of all organisms present. To evaluate how well marine microorganisms across all 3 domains are detected by this method, we compared commonly-used primers with > 300 million rRNA gene sequences retrieved from globally-distributed marine metagenomes. The best-performing primers when comparing to 16S rRNA of Bacteria and Archaea were 515Y/926R and 515Y/806RB, which perfectly matched over 96% of all sequences. Considering Cyanobacteria and Chloroplast 16S rRNA, 515Y/926R had the highest coverage (99%), making this set ideal for quantifying marine primary producers. For eukaryotic 18S rRNA sequences, 515Y/926R also performed best (88%), followed by V4R/V4RB (18S rRNA-specific; 82%) - demonstrating that the 515Y/926R combination performs best overall for all 3 domains. Using Atlantic and Pacific Ocean samples, we demonstrate high correspondence between 515Y/926R amplicon abundances (generated for this study) and metagenomic 16S rRNA (median R2=0.98, n=272), indicating amplicons can produce equally accurate community composition data versus shotgun metagenomics. Our analysis also revealed that expected performance of all primer sets could be improved with minor modifications, pointing toward a nearly-completely universal primer set that could accurately quantify biogeochemically-important taxa in ecosystems ranging from the deep-sea to the surface. In addition, our reproducible bioinformatic workflow can guide microbiome researchers studying different ecosystems or human health to similarly improve existing primers and generate more accurate quantitative amplicon data. Significance StatementPCR amplification and sequencing of marker genes is a low-cost technique for monitoring prokaryotic and eukaryotic microbial communities across space and time, but will only work optimally if environmental organisms match PCR primer sequences exactly. In this study, we evaluated how well primers match globally-distributed short-read oceanic metagenomes. Our results demonstrate primer sets vary widely in performance, and that at least for marine systems, rRNA amplicon data from some primers lack significant biases compared to metagenomes. We also show that it is possible to create a nearly universal primer set for diverse saline environments by defining a specific mixture of a few dozen oligonucleotides and present a software pipeline that can guide rational design of primers for any environment with available metaomic data.

ecology↗

bioRxiv2020

Ribosome-linked mRNA-rRNA chimeras reveal active novel virus-host associations.

Viruses of prokaryotes greatly outnumber their hosts1 and impact microbial processes across scales, including community assembly, evolution, and metabolism1. Metagenomic discovery of novel viruses has greatly expanded viral sequence databases, but only rarely can viral sequences be linked to specific hosts. Here, we adapt proximity ligation methods to ligate ribosomal RNA to transcripts, including viral ones, during translation. We sequenced the resulting chimeras, directly linking marine viral gene expression to specific hosts by transcript association with rRNA sequences. With a sample from the San Pedro Ocean Time-series (SPOT), we found viral-host links to Cyanobacteria, SAR11, SAR116, SAR86, OM75, and Rhodobacteracae hosts, some being the first viruses reported for these groups. We used the SPOT viral and cellular DNA database to track abundances of multiple virus-host pairs monthly over 5 years, e.g. with Roseovarius phages tracking the host. Because the vast majority of proximity ligations should occur between an organisms ribosomes and its own transcripts, we validated our method by looking for self- vs non-self mRNA-rRNA chimeras, by read recruitment to marine single amplified genomes; verifiable non-self chimeras, suggesting off-target linkages, were very rare, indicating host-virus hits were very unlikely to occur by mistake. This approach in practice could link any transcript and its associated processes to specific microorganisms.

microbiology↗

bioRxiv2020

Immune Lag Is a Major Cost of Prokaryotic Adaptive Immunity During Viral Outbreaks

CRISPR-Cas adaptive immune systems enable bacteria and archaea to efficiently respond to viral pathogens by creating a genomic record of previous encounters. These systems are broadly distributed across prokaryotic taxa, yet are surprisingly absent in a majority of organisms, suggesting that the benefits of adaptive immunity frequently do not outweigh the costs. Here, combining experiments and models, we show that a delayed immune response which allows viruses to transiently redirect cellular resources to reproduction, which we call "immune lag", is extremely costly during viral outbreaks, even to completely immune hosts. Critically, the costs of lag are only revealed by examining the early, transient dynamics of a host-virus system occurring immediately after viral challenge. Lag is a basic parameter of microbial defense, relevant to all intracellular, post-infection antiviral defense systems, that has to-date been largely ignored by theoretical and experimental treatments of host-phage systems.

microbiology↗

bioRxiv2020

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator, and implement this estimator in an easy-to-use R package (gRodon), which outperforms the state-of-the-art growth estimator in multiple settings, including in a community context where we implement a novel species abundance correction for metagenomes. Additionally, we estimate maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity. We provide these compiled maximal growth rates in a publicly-available database (EGGO), which we use to illustrate how culture collections show a strong bias towards organisms capable of rapid growth. We demonstrate how this database can be used to propagate maximal growth rate predictions to organisms for which we lack genomic information, on the basis of 16S rRNA sequence alone. Finally, we observe a bias in growth predictions for extremely slow-growing organisms, ultimately leading us to suggest a novel evolutionary definition of oligotrophy based on the selective regime an organism occupies. SignificanceDespite the wide perception that microbes have rapid growth rates, many environments like seawater and soil are often dominated by microorganisms that can only grow very slowly. Our knowledge about growth is necessarily biased towards easily culturable organisms, which turn out to be those that tend to grow fast, because microbial growth rates have traditionally been measured using lab growth experiments. But how are potential growth rates distributed in nature? We developed a tool to predict maximum growth rate from an organisms genome sequence (gRodon). We predicted the growth rates of over 200,000 organisms and compiled these predictions in a publicly-available database (EGGO), which illustrates how current collections of cultured microbes are strongly biased towards fast-growing organisms.

microbiology↗

bioRxiv2019

Comprehensive single-PCR 16S and 18S rRNA community analysis validated with mock communities and denoising algorithms

Universal SSU rRNA primers allow comprehensive quantitative profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show all rRNA gene relative gene abundances, they are rarely used due to concerns about length bias against 18S amplicons and bioinformatic challenges converting mixed 16S/18S sequences into amplicon sequence variants. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this three-domain approach. To test for length biases, we mixed eukaryotic and prokaryotic mocks before PCR, and found consistent two-fold underestimation of longer 18S sequences due to sequencing but not PCR bias. Using these mocks, we show universal V4-V5 primers (515Y/926R) outperformed eukaryote-specific V4 primers in observed vs. expected abundance correlations and sequences with single mismatches to the primer were strongly underestimated (3-8 fold). A year of monthly time-series data from a protist-enriched 1.2-80 m size fraction yielded an average of 9% 18S, 17% chloroplast 16S, and 74% prokaryote 16S rRNA gene amplicons. These data demonstrate the potential for universal primers to generate quantitative and comprehensive microbiome profiles, although gene copy and genome size variability should be considered - as for any quantitative genetic analysis.

microbiology↗

bioRxiv2019

Metagenomics and stable isotope probing offer insights into metabolism of polycyclic aromatic hydrocarbons degraders in chronically polluted seawater

Bacterial biodegradation is a significant contributor to remineralization of polycyclic aromatic hydrocarbons (PAHs): toxic and recalcitrant components of crude oil as well as byproducts of partial combustion chronically introduced into seawater via atmospheric deposition. The Deepwater Horizon oil spill demonstrated the speed at which a seed PAH-degrading community maintained by low chronic inputs can respond to an acute pollution. We investigated the diversity and functional potential of a similar seed community in the Port of Los Angeles, a chronically polluted site, using stable isotope probing with naphthalene, deep-sequenced metagenomes and carbon incorporation rate measurements at the port and in two sites further into the San Pedro Channel. We show a switch in the composition of the PAH degrading community from diverse early-responding generalists to late-blooming specialized degraders. This switch demonstrates the ability of the local seed community of degraders at the Port of LA to incorporate carbon from PAHs independently of a labile-hydrocarbon degrading succession. We were able to directly show that assembled genomes belonged to naphthalene degraders by matching their 16S-rRNA gene with experimental stable isotope probing data. Surprisingly, we did not find a full PAH degradation pathway in any of those genomes and even when combining genes from the entire microbial community. We use metabolic pathways identified in those genomes to generate metagenomic-based recommendations for future optimization of PAHs bioremediation.

microbiology↗

bioRxiv2019

Influence of light on particulate organic matter utilization by attached and free-living marine bacteria

While the impact of light on primary productivity in aquatic systems has been studied for decades, the role light plays in the degradation of photosynthetically-produced biomass is less well understood. We investigated the patterns of light-induced particle breakdown and bacterial assimilation of detrital C and N using 13C and 15N labeled freeze-thawed diatom cells incubated in laboratory microcosms with a marine microbial community freshly-collected from the Pacific Ocean. Particles incubated in the dark resulted in increased bacterial counts and dissolved organic carbon concentrations compared to those incubated in the light. Light also influenced the attached and free-living microbial community structure as detected by 16S rRNA gene amplicon sequencing. For example, bacterial taxa from the Sphingobacteriia were enriched on dark-incubated particles and taxa from the family Flavobacteriaceae and the genus Pseudoalteromonas were numerically enriched on particles in the light. Isotope incorporation analysis by phylogenetic microarray and NanoSIMS (a method called Chip-SIP) identified free-living and attached microbial taxa able to incorporate N and C from the particles. Some taxa, including members of the Flavobacteriaceae and Cryomorphaceae, exhibited increased isotope incorporation in the light, suggesting the use of photoheterotrophic metabolisms. In contrast, some members of Oceanospirillales and Rhodospirillales showed decreased isotope incorporation in the light, suggesting that their heterotrophic metabolism, particularly when occurring on particles, might increase at night or may be inhibited by sunlight. These results show that light influences particle degradation and C and N incorporation by attached bacteria, suggesting that the transfer between particulate and free-living phases are likely affected by external factors that change with the light regime, such as time of day, depth and season.

ecology↗

bioRxiv2018

A network-based integrated framework for predicting virus-host interactions with applications

Metagenomic sequencing has greatly enhanced the discovery of viral genomic sequences; however it remains challenging to identify the host(s) of these new viruses. We developed VirHostMatcher-Net, a flexible, network-based, Markov random field framework for predicting virus-host interactions using multiple, integrated features: CRISPR sequences, sequence homology, and alignment-free similarity measures ([Formula] and WIsH). Evaluation of this method on a benchmark set of 1,075 known viruses-host pairs yielded host prediction accuracy of 62% and 85% at the genus and phylum levels, representing 12-27% and 10-18% improvement respectively over previous single-feature prediction approaches. We applied our host-prediction tool to three metagenomic virus datasets: human gut crAss-like phages, marine viruses, and viruses recovered from globally-distributed, diverse habitats. Host predictions were frequently consistent with those of previous studies, but more importantly, this new tool made many more confident predictions than previous tools, up to 6-fold more (n>60,000), greatly expanding the diversity of known virus-host interactions.

bioinformatics↗

bioRxiv2017

Marine proteorhodopsins rival photosynthesis in solar energy capture

All known phototrophic metabolisms on Earth are based on one of three energy-converting pigments: chlorophyll-a, bacteriochlorophyll-a, and retinal, which is the chromophore in rhodopsins [1]. While the contribution of chlorophylls to global energy flows and marine carbon cycling has been studied for decades, the role of retinal-based phototrophy remains largely unexplored [1,2]. We report the first vertical distributions of the three energy-converting pigments measured along a contrasting nutrient gradient through the Mediterranean Sea and the Eastern Atlantic Ocean. The highest proteorhodopsin concentrations were observed above the deep chlorophyll-a maxima, and their geographical distribution tended to be inversely related to that of chlorophyll-a. We further show that proteorhodopsins potentially absorb as much or more light energy than chlorophyll-a -based phototrophy and this energy is sufficient to sustain bacterial basal metabolism. Our results suggest that ubiquitous proteorhodopsin-containing heterotrophs are important contributors to the light energy captured in the sea.

ecology↗

bioRxiv2017

Dynamics of finely resolved, abundant symbiotic marine plankton and other interacting microbes via automated high-frequency sampling

Short time-scale observations are valuable for understanding microbial ecological processes. We assessed dynamics in relative abundance and potential activities by sequencing the small sub-unit ribosomal RNA gene (rRNA gene) and rRNA molecules (rRNA) of Bacteria, Archaea, and Eukaryota once to twice-daily between March 2014 and May 2014 from the surface ocean off Catalina Island, California. Typically Ostreococcus, Braarudosphaera, Teleaulax, and Synechococcus dominated phytoplankton sequences (including chloroplasts) while SAR11, Sulfitobacter, and Fluviicola dominated non-phytoplankton Bacteria and Archaea. We observed short-lived increases of diatoms, mostly Pseudo-nitzschia and Chaetoceros, with quickly responding Bacteria and Archaea including Flavobacteriaceae (Polaribacter & Formosa), Roseovarius, and Euryarchaeota (MGII), notably the exact amplicon sequence variants we observed responding similarly to another diatom bloom nearby, three years prior. We observed correlations representing known interactions among abundant phytoplankton rRNA sequences, demonstrating the biogeochemical and ecological relevance of such interactions: 1) The kleptochloroplastidic ciliate Mesodinium 18S rRNA gene sequences and a single Teleaulax taxon (via 16S rRNA gene sequences) were correlated (Spearman r =0.83) yet uncorrelated to a Teleaulax 18S rRNA gene OTU, or any other taxon (consistent with a kleptochloroplastidic or karyoklepty relationship) and 2) the photosynthetic prymnesiophyte Braarudosphaera bigelowii and two strains of diazotrophic cyanobacterium UCYN-A were correlated and each taxon was also correlated to other taxa, including B. bigelowii to a verrucomicrobium and a dictyochophyte phytoplankter (all r > 0.8). We also report strong correlations (r > 0.7) between various ciliates, bacteria, and phytoplankton, suggesting interactions via currently unknown mechanisms. These data reiterate the utility of high-frequency time-series to show rapid microbial reactions to stimuli, and provide new information about in-situ dynamics of previously recognized and hypothesized interactions.

microbiology↗

bioRxiv2017

Dynamic marine viral infections and major contribution to photosynthetic processes shown by regional and seasonal picoplankton metatranscriptomes

Viruses are an important top-down control on microbial communities, yet their direct study in natural environments has been hindered by culture limitations1-3. The advance of sequencing and bioinformatics over the last decade enabled the cultivation independent study of viruses. Many studies focus on assembling new viral genomes4-6 and studying viral diversity using marker genes amplified from free viruses7,8. We used cellular metatranscriptomics to study community-wide viral infections at three coastal California sites throughout a year. Generation of and recruitment to viral contigs (> 5kbp, N=66) allowed tracking of infection dynamics over time and space. Here we show that while these assemblies represent viral populations, they are likely biased towards clonal or low diversity assemblages. Furthermore, we demonstrate that published T4-like cyanophages (N=50) and pelagiphages (N=4), having genomic continuity between close relatives, are better tracked using marker genes. Additionally, we demonstrate determination of potential hosts by matching infection dynamics with microbial community composition. Finally, we quantify the relative contribution of various cyanobacteria and viruses to photosystem-II psbA expression in our study sites. We show sometimes >50% of all cyanobacterial+viral psbA expression we observed is of viral origin, which highlights the proportion of infected cells and makes viruses a remarkable contributor to photosynthesis and oxygen production.

ecology↗