Biology subjects

Fuhrman, J.

Publications and source records attributed to Fuhrman, J..

14 recordsLinked to original sources

bioRxiv2026

Estimating Gene Prevalence with Incomplete Genomes: Application to the Prochlorococcus Pangenome

Gene prevalence is an essential statistic in population genomics, defined as the proportion of a population carrying at least one ortholog of a given gene family. Common approaches to estimating gene prevalence either assume complete genomes or exclude genomes below a completeness threshold, resulting in biased and high variance estimates that fail to take advantage of all available data. Here we developed a maximum-likelihood framework that explicitly models genome completeness in order to estimate gene prevalence and associated confidence intervals from collections of complete and incomplete genomes. We applied the methodology to marine Prochlorococcus, a globally abundant photosynthetic bacterium for which the majority of available genomes are incomplete. Our methodology produced gene prevalence estimates with associated confidence intervals for a total of 52,500 gene families, more than 4 times the number quantifiable using complete genomes alone. We find a core of 714 genes are likely universal to the Prochlorococcus genus and a substantial majority of 49,828 gene families occur at low prevalence. Our results reveal a Prochlorococcus pangenome dominated by rare flexible genes and provide a general framework for incorporating incomplete genomes into quantitative analyses of microbial genomic diversity.

microbiology↗

bioRxiv2026

Estimating absolute microbial abundances from metabarcoding anchored to cytometry data

Over the past decades, metabarcoding and automated cell-counting approaches have greatly advanced our understanding of marine microbial communities. Metabarcoding provides high taxonomic resolution and comprehensive community characterization, typically as relative gene abundances, whereas flow cytometry provides absolute cell abundances but lower taxonomic coverage. Here, we assess whether concurrent flow-cytometry observations can calibrate metabarcoding data to derive absolute gene abundances across four basin-scale Atlantic and Pacific Ocean transects. We first show that flow-cytometry-anchored calibration reproduces absolute abundances of Prochlorococcus and Synechococcus with performance comparable (R2 = 0.87) to internal DNA standard-based quantification. For datasets lacking internal standards, the choice of cytometric "anchor" species introduces systematic offsets in absolute abundance estimates, although spatial patterns remain robust. These offsets may reflect underestimation of cytometric counts or variation in rRNA gene copy numbers among actively dividing cells. We therefore recommend the use of multiple anchors where possible to diagnose systematic uncertainty. Applying this framework, we derive absolute gene concentrations for diverse plankton taxa from compositional metabarcoding data. For taxa with known rRNA gene copy numbers, calibration further enables estimation of absolute cell concentrations. We also resolve ecotype-level absolute abundances of Prochlorococcus along a longitudinal temperature gradient, revealing ecological patterns not apparent from compositional or cytometric data alone. Our results demonstrate that calibrated metabarcoding provides a practical quantitative bridge between molecular and cytometric observations, yielding high taxonomic resolution together with absolute gene concentrations and quantified uncertainties.

ecology↗

bioRxiv2026

Expansive Diversity and Temporal Dynamics of Emerging Polinton-like Viruses in a Marine Ecosystem

Polinton-like viruses (PLVs) are an emerging group of double-stranded DNA viruses of microbial eukaryotes whose ecological roles in marine ecosystems remain poorly understood. Using a five-year monthly viromic time series from the San Pedro Ocean Time-series (SPOT), we investigated the diversity, temporal dynamics, and functional potential of PLVs in a coastal marine ecosystem. We identified 2,355 distinct PLV populations, revealing PLVs to be a highly abundant and diverse component of the marine virosphere. Phylogenetic analyses resolved multiple major PLV clades, including abundant Group X/Trimcap PLVs characterized by triplicate major capsid proteins, supporting the widespread occurrence of this unusual viral architecture in marine PLVs. Approximately half of PLV populations exhibited significant repeatable seasonal dynamics, partitioning into numerous chronotypes that reflect highly modular temporal niches. PLV abundance correlated positively with multiple productivity-linked environmental variables, including nitrate, particulate organic carbon, and primary productivity, suggesting close coupling between PLVs and seasonal ecosystem productivity. Functional analyses further identified diverse auxiliary metabolic genes in many PLV genomes involved in carbohydrate, lipid, redox, and nucleotide metabolism, with strong phylogenetic structuring across PLV clades. Together, these findings demonstrate that PLVs are abundant, functionally diverse, and ecologically dynamic members of marine viral communities, and suggest they are important yet underappreciated regulators of protist ecology and evolution in marine ecosystems.

microbiology↗

bioRxiv2025

Induced pathogenicity toward open-ocean diatoms by a newly isolated filterable bacterium Ekhidna algicida sp. nov.

Phytoplankton are the base of marine food webs. They form intricate interactions with heterotrophic bacteria ranging from mutualistic to pathogenic that together impact oceanic carbon and nutrient cycling. Our understanding of these interactions in marine environments remains primarily limited to laboratory-based studies of model organisms. Here, we report the discovery and characterization of Ekhidna algicida sp. nov. strain To15, isolated from the oligotrophic Pacific Ocean (16{degrees}N, 140{degrees}W) based on its algicidal effect on the pelagic diatom Thalassiosira oceanica. Subsequent co-culture experiments demonstrate that E. algicida is lethal within days to a diverse array of diatoms, with the effect mediated by bacterial exudates that remain algicidal on their own against axenic T. oceanica cultures. Twenty additional algicidal Ekhidna strains were subsequently isolated from the Pacific Ocean. Our findings reveal E. algicida as a potentially widespread pathogen of diatoms, that can alter microbial community composition dynamics in pelagic ecosystems. TeaserA newly discovered Pacific Ocean bacterium can kill diatoms, revealing a hidden pathogenic role in open-ocean ecosystems.

ecology↗

bioRxiv2025

A Multidomain Lens on the Temporal Dynamics of Surface Microbial Communities in the Southern Ocean (2013-2019)

Marine microorganisms are vital to biogeochemical cycles and food web dynamics, with their community structure shaped by environmental factors such as temperature, light, and salinity. While microbial dynamics in the western Antarctic Peninsula are relatively well- studied, the northwestern region remains underexplored, particularly in long-term, multidomain analyses. To fill this gap, we investigated microbial communities encompassing all three domains of life (Bacteria, Archaea, and Eukarya) in the Northwestern Antarctic Peninsula. Using the universal primer set 515Y/926R, we sequenced unfractionated seawater from ten sites over a six-year period (2013-2019). Environmental parameters, temperature and salinity, showed minimal variation across the study. However, microbial diversity and composition, especially among eukaryotic phytoplankton, displayed significant temporal changes among seasons and years. The prokaryotic community, by contrast, was relatively stable, with Gammaproteobacteria-- particularly the Nitrincolaceae family--maintaining high relative abundance throughout all sampling periods, but a few distinct ASVs. In contrast, no eukaryotic group exhibited consistently high relative abundance across sampling periods. The summer of 2016, marked by a strong El Nino event, presented the most distinct microbial community structure, underscoring the sensitivity of these communities to extreme climatic conditions. These results highlight the importance of integrated, long-term studies to better understand the dynamics, interactions, and resilience of microbial ecosystems in the rapidly changing Antarctic environment. IMPORTANCEThis study provides a unique long-term perspective on microbial community dynamics in the Northwestern Antarctic Peninsula, a region still poorly explored through a multidomain lens. By investigating the temporal variability of Bacteria, Archaea, and Eukaryotes over six years, we reveal distinct stability patterns between these groups, with phytoplankton showing the highest variability and prokaryotes remaining relatively stable. The strong response of the microbial community to the 2016 El Nino event highlights its sensitivity to extreme climate conditions, reinforcing the importance of understanding how Antarctic ecosystems will respond to future climate shifts. The consistent presence of Nitrincolaceae, a key bacterial taxon, suggests its ecological relevance in the region, while fluctuations in phytoplankton composition may impact food web dynamics. These findings emphasize the need for continued long-term monitoring to predict how microbial communities will adapt to environmental changes, which is crucial for assessing the future functioning of polar marine ecosystems.

microbiology↗

bioRxiv2025

Characterizing organisms from three domains of life with universal primers from throughout the global ocean

We introduce the Global rRNA Universal Metabarcoding Plankton database (GRUMP), which consists of 1194 samples that were collected from 2003-2020 and cover extensive latitudinal and longitudinal transects, as well as depth profiles in all major ocean basins. DNA from unfractionated (> 0.2{micro}m) seawater samples was amplified using the 515Y/926R universal three- domain rRNA gene primers, simultaneously quantifying the relative abundance of amplicon sequencing variants (ASVs) from bacteria, archaea, eukaryotic nuclear 18S, and eukaryotic plastid 16S. Thus, the ratio between taxa in one sample is directly comparable to the ratio in any other GRUMP sample, regardless of gene copy number differences. This obviates a problem in prior global studies that used size-fractionation and different rRNA gene primers for bacteria, archaea, and eukaryotes, precluding comparisons across size fractions or domains. On average, bacteria contributed 71%, eukaryotes 19%, and archaea 8% to rRNA gene abundance, though eukaryotes contributed 32% at latitudes > 40{degrees}. GRUMP is publicly available on the Simons Collaborative Marine Atlas Project (CMAP), promoting the global comparison of marine microbial dynamics.

ecology↗

bioRxiv2024

Variational inference for microbiome survey data with application to global ocean data

Linking sequence-derived microbial taxa abundances to host (patho-)physiology or habitat characteristics in a reproducible and interpretable manner has remained a formidable challenge for the analysis of microbiome survey data. Here, we introduce a flexible probabilistic modeling framework, VI-MIDAS (Variational Inference for MIcrobiome survey DAta analysiS), that enables joint estimation of context-dependent drivers and broad patterns of associations of microbial taxon abundances from microbiome survey data. VI-MIDAS comprises mechanisms for direct coupling of taxon abundances with covariates and taxa-specific latent coupling which can incorporate spatio-temporal information and taxon-taxon interactions. We leverage mean-field variational inference for posterior VI-MIDAS model parameter estimation and illustrate model building and analysis using Tara Ocean Expedition survey data. Using VI-MIDAS latent embedding model and tools from network analysis, we show that marine microbial communities can be broadly categorized into five modules, including SAR11-, Nitrosopumilus-, and Alteromondales-dominated communities, each associated with specific environmental and spatiotemporal signatures. VI-MIDAS also finds evidence for largely positive taxon-taxon associations in SAR11 or Rhodospirillales clades, and negative associations with Alteromonadales and Flavobacteriales classes. Our results indicate that VI-MIDAS provides a powerful integrative statistical analysis framework for discovering broad patterns of associations between microbial taxa and context-specific covariate data from microbiome survey data.

bioinformatics↗

bioRxiv2022

Symbiotic diazotrophic UCYN-A strains co-occurred with El Ni&ntildeo, relaxed upwelling, and varied eukaryotes over 10 years off Southern California Bight

Biological nitrogen fixation, the conversion of N2 gas into a more bioavailable form, is vital to sustaining marine primary production. Studies have shifted beyond traditionally studied tropical diazotrophs. Candidatus Atelocyanobacterium thalassa (or UCYN-A) has emerged as a research focal point due to its streamlined metabolism, intimate partnership with a haptophyte host, and broad distribution. Here, we explore the abiotic factors that govern UCYN-As presence at the San Pedro Ocean Time-series (SPOT), its partner fidelity, and statistical interactions with non-symbiotic eukaryotes. 16S and 18S rRNA sequences were amplified by "universal primers" from monthly samples and resolved into Amplicon Sequence Variants, allowing us to observe multiple UCYN-A symbioses. UCYN-A1 relative abundances increased following the 2015-2016 El Nino event. When this "open ocean ecotype" was present, coastal upwelling ceased, and Ekman transport brought tropical waters into the region. Network analyses reveal all strains of UCYN-A co-occur with dinoflagellates including Lepidodinium, a potential predator, and parasitic Syndiniales. UCYN-A2 appeared to pair with multiple hosts and was not tightly coupled to its predominate host, while UCYN-A1 maintained a strong host-symbiont relationship. These biological relationships are particularly important to study in the context of climate change, which will alter UCYN-A distribution patterns both locally and globally.

microbiology↗

bioRxiv2021

DeepMicrobeFinder sorts metagenomes into prokaryotes, eukaryotes and viruses, with marine applications

Sequence classification reduces the complexity of metagenomes and facilitates a fundamental understanding of the structure and function of microbial communities. Binary metagenomic classifiers offer an insufficient solution because environmental metagenomes are typically derived from multiple sequence sources, including prokaryotes, eukaryotes and the viruses of both. Here we introduce a deep-learning based (as opposed to alignment-based) sequence classifier, DeepMicroClass, that classifies metagenomic contigs into five sequence classes, i.e., viruses infecting prokaryotic or eukaryotic hosts, eukaryotic or prokaryotic chromosomes, and prokaryotic plasmids. At different sequence lengths, DeepMicroClass achieved area under the receiver operating characteristic curve (AUC) scores >0.98 for most sequence classes, with the exception of distinguishing plasmids from prokaryotic chromosomes (AUC scores{approx} 0.97). By benchmarking on 20 designed datasets with variable sequence class composition, we showed that DeepMicroClass obtained average accuracy scores of [~]0.99, [~]0.97, and [~]0.99 for eukaryotic, plasmid and viral contig classification, respectively, which were significantly higher than the other state-of-the-art individual predictors. Using a 1-300 {micro}m daily time-series metagenomic dataset sampled from coastal Southern California as a case study, we showed that metagenomic read proportions recruited by eukaryotic contigs could be doubled with DeepMicroClasss classification compared to the counterparts of other alignment-based classifiers. With its inclusive modeling and unprecedented performance, we expect DeepMicroClass will be a useful addition to the toolbox of microbial ecologists, and will promote metagenomic studies of under-appreciated sequence types.

bioinformatics↗

bioRxiv2021

HiCzin: Normalizing metagenomic Hi-C data and detecting spurious contacts using zero-inflated negative binomial regression

High-throughput chromosome conformation capture (Hi-C) has recently been applied to natural microbial communities and revealed great potential to study multiple genomes simultaneously. Several extraneous factors may influence chromosomal contacts rendering the normalization of Hi-C contact maps essential for downstream analyses. However, the current paucity of metagenomic Hi-C normalization methods and the ignorance for spurious inter-species contacts weaken the interpretability of the data. Here, we report on two types of biases in metagenomic Hi-C experiments: explicit biases and implicit biases, and introduce HiCzin, a parametric model to correct both types of biases and remove spurious inter-species contacts. We demonstrate that the normalized metagenomic Hi-C contact maps by HiCzin result in lower biases, higher capability to detect spurious contacts, and better performance in metagenomic contig clustering. The HiCzin software and Supplementary Material are available at https://github.com/dyxstat/HiCzin.

bioinformatics↗

bioRxiv2020

Metagenomics and quantitative 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 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 demonstrate the ability of a local seed community of degraders at the Port of LA to incorporate carbon from naphthalene, leading to a quick shift in the microbial community composition to be dominated by these normally rare taxa. 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 those genomes and even when combining genes from the entire microbial community. We analyze metabolic pathways identified in 29 genomes whose abundance increased in the presence of naphthalene to generate metagenomic-based recommendations for future optimization of PAHs bioremediation. ImportanceOil spills in the marine environment have a devastating effect on marine life and biogeochemical cycles. Oil-degrading bacteria occur naturally in the ocean, especially where they are supported by chronic inputs of oil, and have a significant role in degradation of oil spills. The most recalcitrant and toxic component of oil is polycyclic aromatic hydrocarbons. Therefore, the bacteria who can break those molecules down are of particular importance. We identified such bacteria at the port of Los Angeles, one of the busiest ports worldwide, and characterized their metabolic capabilities. Based on those analyses we proposed chemical targets to stimulate the activity of these bacteria in case of an oil spill in the port of LA.

microbiology↗

bioRxiv2019

Benchmarking metagenomic marine microbial growth prediction from codon usage bias and peak-to-trough ratios

Growth rates are fundamental to all organisms and essential for characterizing microbial ecologies. Despite this, we do not know the instantaneous nor maximum growth rates of most naturally-occurring microorganisms. Recent reports indicate DNA replication rates can be estimated from metagenomic coverage, and maximum growth rates can be estimated from genomic characteristics. We tested these approaches with native marine bacteria (<0.6 um size fraction) as 10% inoculum grown in unamended virus-free seawater from the San Pedro Channel, California. This allowed microbial growth without grazing and with greatly reduced viral infection. At multiple time points up to 48 h, we sampled for cell abundances and metagenomic analyses. We generated 101 unique Metagenome-assembled genomes (MAGs) including , {beta}, and {gamma} Proteobacteria, Flavobacteria, Actinobacteria, Verrucomicrobia, Marine Group A/SAR406, MGII archaea, and others. We tracked the growth of each as the fraction of total metagenomic reads mapped to each MAG normalized with length, completeness, and total cell counts. Some MAGs did not grow appreciably, but those we could estimate had growth rates ranging from 0.08 to 5.99 d-1; these are the first reported growth rates for several of the groups. These metagenome-determined growth rates, which often changed within experiments, were compared to (a) DNA replication estimates from the peak-to-trough ratio (PTR) as determined by three different approaches, and (b) maximum growth rates predicted from codon usage bias (CUB). For the large majority of taxa, observed growth rates were not correlated to PTR indices (r ~ -0.26 - 0.08), with exceptions being rapidly growing Oceanospirillales and Saccharospirillaceae (r ~ 0.63 - 0.92). However, CUB was moderately well correlated to observed maximum growth rates (r = 0.57). This suggests that maximum growth rates can be reasonably well-estimated from genomic information alone, but current PTR approaches poorly predict actual growth of most marine planktonic bacteria in unamended seawater.

microbiology↗

bioRxiv2018

Mosaic patterns of B-vitamin synthesis and utilization in a natural marine microbial community

Aquatic environments contain diverse microbial communities whose complex interactions mediate the cycling of major and trace nutrients such as vitamins. B-vitamins are essential coenzymes that many organisms cannot synthesize. Thus their exchange among de-novo synthesizers and auxotrophs is expected to play an important role in the microbial consortia and explain some of the temporal and spatial changes observed in diversity. In this study, we analyzed metatranscriptomes of a natural coastal microbial community, diel sampled-quarterly over one year to try to identify the potential major B-vitamin synthesizers and consumers. Our transcriptomic data show that the best-represented taxa dominated the expression of synthesis genes for some B-vitamins but lacked transcripts for others. For instance, Rhodobacterales dominated the expression of vitamin-B12 synthesis, but not of vitamin-B7, whose synthesis transcripts were mainly represented by Flavobacteria.In contrast, bacterial groups that constituted less than 4% of the community (e.g., Verrucomicrobia) accounted for most of the vitamin-B1 synthesis transcripts. Furthermore, ambient vitamin-B1 concentrations were higher in samples collected during the day, and were positively correlated with chlorophyll-a concentration. Our analysis supports the hypothesis that the mosaic of metabolic interdependencies through B-vitamin synthesis and exchange are key processes that contribute to shaping microbial communities in nature.

microbiology↗

bioRxiv2017

Taxon disappearance from microbiome analysis indicates need for mock communities as a standard in every sequencing run

Mock communities have been used in microbiome method development to help estimate biases introduced in PCR amplification, sequencing, and to optimize pipeline outputs. Nevertheless, the necessity of routine mock community analysis beyond initial method development is rarely, if ever, considered. Here we report that our routine use of mock communities as internal standards allowed us to discover highly aberrant and strong biases in the relative proportions of multiple taxa in a single Illumina HiSeqPE250 run. In this run, an important archaeal taxon virtually disappeared from all samples, and other mock community taxa showed >2-fold high or low abundance, whereas a rerun of those identical amplicons (from the same reaction tubes) on a different date yielded \"normal\" results. Although obvious from the strange mock community results, due to natural variation of microbiomes at our site, we easily could have missed the problem had we not used the mock communities. The \"normal\" results were validated over 4 MiSeqPE300 runs and 3 HiSeqPE250 runs, and run-to-run variation was usually low (Bray-Curtis distance was 0.12{+/-}0.04). While validating these \"normal\" results, we also discovered some mock microbial taxa had relatively modest, but consistent, differences between sequencing platforms. We suggest that using mock communities in every sequencing run is essential to distinguish potentially serious aberrations from natural variations. Such mock communities should have more than just a few members and ideally at least partly represent the samples being analyzed, to detect problems that show up only in some taxa, as we observed.\n\nImportanceDespite the routine use of standards and blanks in virtually all chemical or physical assays and most biological studies (a kind of \"control\"), microbiome analysis has traditionally lacked such standards. Here we show that unexpected problems of unknown origin can occur in such sequencing runs, and yield completely incorrect results that would not necessarily be detected without the use of standards. Assuming that the microbiome sequencing analysis works properly every time risks serious errors that can be avoided by the use of suitable mock communities.

microbiology↗