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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data for FUN-PROSE: A Deep Learning Approach to Predict Condition-Specific Gene Expression in Fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

Genomics↗
DOE OSTI2018

Annotation of the Corymbia terpene synthase gene family shows broad conservation but dynamic evolution of physical clusters relative to Eucalyptus

Terpenes are economically and ecologically important phytochemicals. Their synthesis is controlled by the terpene synthase (TPS) gene family, which is highly diversified throughout the plant kingdom. The plant family Myrtaceae are characterised by especially high terpene concentrations, and considerable variation in terpene profiles. Many Myrtaceae are grown commercially for terpene products including the eucalypts Corymbia and Eucalyptus. Eucalyptus grandis has the largest TPS gene family of plants currently sequenced, which is largely conserved in the closely related E. globulus. However, the TPS gene family has been well studied only in these two eucalypt species. The recent assembly of two Corymbia citriodora subsp. variegata genomes presents an opportunity to examine the conservation of this important gene family across more divergent eucalypt lineages. Manual annotation of the TPS gene family in C. citriodora subsp. variegata revealed a similar overall number, and relative subfamily representation, to that previously reported in E. grandis and E. globulus. Many of the TPS genes were in physical clusters that varied considerably between Eucalyptus and Corymbia, with several instances of translocation, expansion/contraction and loss. Notably, there was greater conservation in the subfamilies involved in primary metabolism than those involved in secondary metabolism, likely reflecting different selective constraints. The variation in cluster size within subfamilies and the broad conservation between the eucalypts in the face of this variation are discussed, highlighting the potential contribution of selection, concerted evolution and stochastic processes. Finally, these findings provide the foundation to better understand terpene evolution within the ecologically and economically important Myrtaceae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Identification and selection of optimal reference genes for qPCR-based gene expression analysis in Fucus distichus under various abiotic stresses

Quantitative gene expression analysis is an important tool in the scientist’s belt. The identification of evenly expressed reference genes is necessary for accurate quantitative gene expression analysis, whether by traditional RT-PCR (reverse-transcription polymerase chain reaction) or by qRT-PCR (quantitative real-time PCR; qPCR). In the Stramenopiles (the major line of eukaryotes that includes brown algae) there is a noted lack of known reference genes for such studies, largely due to the absence of available molecular tools. Here we present a set of nine reference genes (Elongation Factor 1 alpha (EF1A), Elongation Factor 2 alpha (EF2A), Elongation Factor 1 beta (EF1B), 14-3-3 Protein, Ubiquitin Conjugating Enzyme (UBCE2), Glyceraldehyde-3-phosphate Dehydrogenase (GAPDH), Actin Related Protein Complex (ARP2/3), Ribosomal Protein (40s; S23), and Actin) for the brown alga Fucus distichus . These reference genes were tested on adult sporophytes across six abiotic stress conditions (desiccation, light and temperature modification, hormone addition, pollutant exposure, nutrient addition, and wounding). Suitability of these genes as reference genes was quantitatively evaluated across conditions using standard methods and the majority of the tested genes were evaluated favorably. However, we show that normalization genes should be chosen on a condition-by-condition basis. We provide a recommendation that at least two reference genes be used per experiment, a list of recommended pairs for the conditions tested here, and a procedure for identifying a suitable set for an experimenter’s unique design. With the recent expansion of interest in brown algal biology and accompanied molecular tools development, the variety of experimental conditions tested here makes this study a valuable resource for future work in basic biology and understanding stress responses in the brown algal lineage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Determining the Reliability of Measuring Mercury Cycling Gene Abundance with Correlations with Mercury and Methylmercury Concentrations

Methylmercury (MeHg) is a bioaccumulative toxic contaminant in many ecosystems but factors governing its production are poorly understood. Recent work has shown that the anaerobic microbial conversion of mercury (Hg) to MeHg requires the Hg-methylation genes hgcAB and that these genes can be used as biomarkers in PCR-based estimators of Hg-methylator abundance. In an effort to determine reliable methods for assessing hgcA abundance and diversity and linking it to MeHg concentrations, multiple approaches were compared including metagenomic shotgun sequencing, 16S rRNA gene pyrosequencing and cloning/sequencing hgcAB gene products. Hg-methylator abundance was also determined by quantitative hgcA qPCR amplification and metaproteomics for comparison to the above measurements. Samples from eight Hg-contaminated sites were examined over a range of total Hg (HgT; 0.03–14 mg kg-1 wet wt. soil) and MeHg (0.05–27 µg kg-1 wet wt. soil) concentrations. In the metagenome and amplicon sequencing of hgcAB diversity, the Deltaproteobacteria were the dominant Hg-methylators, while Firmicutes and methanogenic Archaea were typically ~50% less abundant. This was consistent with metaproteomics estimates where the Deltaproteobacteria were consistently higher. The 16S rRNA gene pyrosequencing did not have sufficient resolution to identify hgcAB+ species. Metagenomic and hgcAB results were similar for Hg-methylator diversity and showed a tractable relationship between Hg-methylating bacteria and soil Hg concentrations among similar environmental samples. However, clade-specific qPCR-based approaches for hgcA are only appropriate when comparing the abundance of a particular clade across various samples.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Abstract Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene overexpression, revealing that the fitness costs of copy-number variation can vary substantially with genetic background in a common-garden environment. But the interplay between copy-number variation tolerance and environment remains unexplored on a genomic scale. Here, we measured the tolerance to gene overexpression in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride stress. Overexpressed genes that are commonly deleterious during sodium chloride stress recapitulated those commonly deleterious under standard conditions. However, sodium chloride stress uncovered novel differences in strain responses to gene overexpression. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to sodium chloride stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to overexpression of specific genes. Although most genes were deleterious, hundreds were beneficial when overexpressed—remarkably, most of these effects were strain specific. Few beneficial genes were shared between the sodium chloride-sensitive isolates, implicating mechanistic differences behind their sodium chloride sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural copy-number variation of a sodium export pump that likely contributes to strain-specific responses to overexpression of other genes. Our results reveal extensive strain-by-environment interactions in the response to gene copy-number variation, raising important implications for the accessibility of copy-number variation-dependent evolutionary routes under times of stress.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Several steps of lateral gene transfer followed by events of ‘birth-and-death’ evolution shaped a fungal sorbicillinoid biosynthetic gene cluster

Background: Sorbicillinoids are a family of complex cyclic polyketides produced by only a small number of distantly related ascomycete fungi such as Trichoderma (Sordariomycetes) and Penicillium (Eurotiomycetes). In T. reesei, they are synthesized by a gene cluster consisting of eight genes including two polyketide synthases (PKS). To reconstruct the evolutionary origin of this gene cluster, we examined the occurrence of these eight genes in ascomycetes. Results: A cluster comprising at least six of them was only found in Hypocreales (Acremonium chrysogenum, Ustilaginoidea virens, Trichoderma species from section Longibrachiatum) and in Penicillium rubens (Eurotiales). In addition, Colletotrichum graminicola contained the two pks (sor1 and sor2), but not the other sor genes. A. chrysogenum was the evolutionary eldest species in which sor1, sor2, sor3, sor4 and sor6 were present. Sor5 was gained by lateral gene transfer (LGT) from P. rubens. In the younger Hypocreales (U. virens, Trichoderma spp.), the cluster evolved by vertical transfer, but sor2 was lost and regained by LGT from C. graminicola. SorB (=sor2) and sorD (=sor4) were symplesiomorphic in P. rubens, whereas sorA, sorC and sorF were obtained by LGT from A. chrysogenum, and sorE by LGT from Pestalotiopsis fici (Xylariales). The sorbicillinoid gene cluster in Trichoderma section Longibrachiatum is under strong purifying selection. The T. reesei sor genes are expressed during fast vegetative growth, during antagonism of other fungi and regulated by the secondary metabolism regulator LAE1. Conclusions: Our findings pinpoint the evolution of the fungal sorbicillinoid biosynthesis gene cluster. The core cluster arose in early Hypocreales, and was complemented by LGT. During further speciation in the Hypocreales, it became subject to birth and death evolution in selected lineages. In P. rubrens (Eurotiales), two cluster genes were symplesiomorphic, and the whole cluster formed by LGT from at least two different fungal donors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish

Numerous disease syndromes are associated with regions of copy number variation (CNV) in the human genome and, in most cases, the pathogenicity of the CNV is thought to be related to altered dosage of the genes contained within the affected segment. However, establishing the contribution of individual genes to the overall pathogenicity of CNV syndromes is difficult and often relies on the identification of potential candidates through manual searches of the literature and online resources. We describe here the development of a computational framework to comprehensively search phenotypic information from model organisms and single-gene human hereditary disorders, and thus speed the interpretation of the complex phenotypes of CNV disorders. There are currently more than 5000 human genes about which nothing is known phenotypically but for which detailed phenotypic information for the mouse and/or zebrafish orthologs is available. Here, we present an ontology-based approach to identify similarities between human disease manifestations and the mutational phenotypes in characterized model organism genes; this approach can therefore be used even in cases where there is little or no information about the function of the human genes. We applied this algorithm to detect candidate genes for 27 recurrent CNV disorders and identified 802 gene-phenotype associations, approximately half of which involved genes that were previously reported to be associated with individual phenotypic features and half of which were novel candidates. A total of 431 associations were made solely on the basis of model organism phenotype data. Additionally, we observed a striking, statistically significant tendency for individual disease phenotypes to be associated with multiple genes located within a single CNV region, a phenomenon that we denote as pheno-clustering. Many of the clusters also display statistically significant similarities in protein function or vicinity within the protein-protein interaction network. Our results provide a basis for understanding previously un-interpretable genotype-phenotype correlations in pathogenic CNVs and for mobilizing the large amount of model organism phenotype data to provide insights into human genetic disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Efficient CRISPR/Cas9-Mediated Gene Editing in Arabidopsis thaliana and Inheritance of Modified Genes in the T2 and T3 Generations

The newly developed CRISPR/Cas9 system for targeted gene knockout or editing has recently been shown to function in plants in both transient expression systems as well as in primary T1 transgenic plants. However, stable transmission of genes modified by the Cas9/single guide RNA (sgRNA) system to the T2 generation and beyond has not been demonstrated. Here we provide extensive data demonstrating the efficiency of Cas9/sgRNA in causing modification of a chromosomally integrated target reporter gene during early development of transgenic Arabidopsis plants and inheritance of the modified gene in T2 and T3 progeny. Efficient conversion of a nonfunctional, out-of-frame GFP gene to a functional GFP gene was confirmed in T1 plants by the observation of green fluorescent signals in leaf tissues as well as the presence of mutagenized DNA sequences at the sgRNA target site within the GFP gene. All GFP-positive T1 transgenic plants and nearly all GFP-negative plants examined contained mutagenized GFP genes. Analyses of 42 individual T2 generation plants derived from 6 different T1 progenitor plants showed that 50% of T2 plants inherited a single T-DNA insert. The efficiency of the Cas9/sgRNA system and stable inheritance of edited genes point to the promise of this system for facile editing of plant genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The Biogeographic Pattern of Microbial Functional Genes along an Altitudinal Gradient of the Tibetan Pasture

As the highest place of the world, the Tibetan plateau is a fragile ecosystem. Given the importance of microbial communities in driving soil nutrient cycling, it is of interest to document the microbial biogeographic pattern here. We adopted a microarray-based tool named GeoChip 4.0 to investigate grassland microbial functional genes along an elevation gradient from 3200 to 3800 m above sea level open to free grazing by local herdsmen and wild animals. Interestingly, microbial functional diversities increase with elevation, so does the relative abundances of genes associated with carbon degradation, nitrogen cycling, methane production, cold shock and oxygen limitation. The range of Shannon diversities (10.27-10.58) showed considerably smaller variation than what was previously observed at ungrazed sites nearby (9.95-10.65), suggesting the important role of livestock grazing on microbial diversities. Closer examination showed that the dissimilarity of microbial community at our study sites increased with elevations, revealing an elevation-decay relationship of microbial functional genes. Both microbial functional diversity and the number of unique genes increased with elevations. Furthermore, we detected a tight linkage of greenhouse gas (CO 2 ) and relative abundances of carbon cycling genes. Our biogeographic study provides insights on microbial functional diversity and soil biogeochemical cycling in Tibetan pastures.

altitudinal gradient↗
DOE OSTI2020

Use of virus‐induced gene silencing to characterize genes involved in modulating hypersensitive cell death in maize

Abstract Plant disease resistance proteins (R‐proteins) detect specific pathogen‐derived molecules, triggering a defence response often including a rapid localized cell death at the point of pathogen penetration called the hypersensitive response (HR). The maize Rp1‐D21 gene encodes a protein that triggers a spontaneous HR causing spots on leaves in the absence of any pathogen. Previously, we used fine mapping and functional analysis in a Nicotiana benthamiana transient expression system to identify and characterize a number of genes associated with variation in Rp1‐D21 ‐induced HR. Here we describe a system for characterizing genes mediating HR, using virus‐induced gene silencing (VIGS) in a maize line carrying Rp1‐D21 . We assess the roles of 12 candidate genes. Three of these genes, SGT1 , RAR1 , and HSP90 , are required for HR induced by a number of R‐proteins across several plant–pathogen systems. We confirmed that maize HSP90 was required for full Rp1‐D21 ‐induced HR. However, suppression of SGT1 expression unexpectedly increased the severity of Rp1‐D21 ‐induced HR while suppression of RAR1 expression had no measurable effect. We confirmed the effects on HR of two genes we had previously validated in the N. benthamiana system, hydroxycinnamoyltransferase and caffeoyl CoA O‐methyltransferase . We further showed the suppression the expression of two previously uncharacterized, candidate genes, IQ calmodulin binding protein ( IQM3 ) and vacuolar protein sorting protein 37 , suppressed Rp1‐D21 ‐induced HR. This approach is an efficient way to characterize the roles of genes modulating the hypersensitive defence response and other dominant lesion phenotypes in maize.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Population‐level gene expression can repeatedly link genes to functions in maize

SUMMARY Transcriptome‐wide association studies (TWAS) can provide single gene resolution for candidate genes in plants, complementing genome‐wide association studies (GWAS) but efforts in plants have been met with, at best, mixed success. We generated expression data from 693 maize genotypes, measured in a common field experiment, sampled over a 2‐h period to minimize diurnal and environmental effects, using full‐length RNA‐seq to maximize the accurate estimation of transcript abundance. TWAS could identify roughly 10 times as many genes likely to play a role in flowering time regulation as GWAS conducted data from the same experiment. TWAS using mature leaf tissue identified known true‐positive flowering time genes known to act in the shoot apical meristem, and trait data from a new environment enabled the identification of additional flowering time genes without the need for new expression data. eQTL analysis of TWAS‐tagged genes identified at least one additional known maize flowering time gene through trans ‐eQTL interactions. Collectively these results suggest the gene expression resource described here can link genes to functions across different plant phenotypes expressed in a range of tissues and scored in different experiments.

Torres‐Rodríguez, J. Vladimir↗
DOE OSTI2021

Hypergraph Models of Biological Networks to Identify Genes Critical to Pathogenic Viral Response

Motivation: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems such as protein complexes, metabolic reactions, and signal transduction pathways. Hypergraphs are generalizations of graphs that naturally model multi-way interactions in data, and we therefore seek to understand how they can more faithfully identify, and potentially predict, complex relationships in genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges are differentially expressed genes and vertices represent conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Our results demonstrate the utility of using hypergraphs to represent complex biological systems, and highlight potentially interesting biological results about host response to highly pathogenic viruses.

systems biology, hypergraph, viral infection, biol↗
DOE OSTI2016

Independent and parallel evolution of new genes by gene duplication in two origins of C4 photosynthesis provides new insight into the mechanism of phloem loading in C4 species

C4 photosynthesis is considered one of the most remarkable examples of evolutionary convergence in eukaryotes. However, it is unknown whether the evolution of C4 photosynthesis required the evolution of new genes. Genome-wide gene-tree species-tree reconciliation of seven monocot species that span two origins of C4 photosynthesis revealed that there was significant parallelism in the duplication and retention of genes coincident with the evolution of C4 photosynthesis in these lineages. Specifically, 21 orthologous genes were duplicated and retained independently in parallel at both C4 origins. Analysis of this gene cohort revealed that the set of parallel duplicated and retained genes is enriched for genes that are preferentially expressed in bundle sheath cells, the cell type in which photosynthesis was activated during C4 evolution. Moreover, functional analysis of the cohort of parallel duplicated genes identified SWEET-13 as a potential key transporter in the evolution of C4 photosynthesis in grasses, and provides new insight into the mechanism of phloem loading in these C4 species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Measuring semantic similarities by combining gene ontology annotations and gene co-function networks

Background: Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. Results: We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Conclusions: Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but are relevant in a taxon-specific manner become measurable when GO annotations are limited.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Gene expression analysis of precision-cut human liver slices indicates stable expression of ADME-Tox related genes

In the process of drug development it is of high importance to test the safety of new drugs with predictive value for human toxicity. A promising approach of toxicity testing is based on shifts in gene expression profiling of the liver. Toxicity screening based on animal liver cells cannot be directly extrapolated to humans due to species differences. The aim of this study was to evaluate precision-cut human liver slices as in vitro method for the prediction of human specific toxicity by toxicogenomics. The liver slices contain all cell types of the liver in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process. Previously we showed that toxicogenomic analysis of rat liver slices is highly predictive for rat in vivo toxicity. In this study we investigated the levels of gene expression during incubation up to 24 h with Affymetrix microarray technology. The analysis was focused on a broad spectrum of genes related to stress and toxicity, and on genes encoding for phase-I, -II and -III metabolizing enzymes and transporters. Observed changes in gene expression were associated with cytoskeleton remodeling, extracellular matrix and cell adhesion, but for the ADME-Tox related genes only minor changes were observed. PCA analysis showed that changes in gene expression were not associated with age, sex or source of the human livers. Slices treated with acetaminophen showed patterns of gene expression related to its toxicity. These results indicate that precision-cut human liver slices are relatively stable during 24 h of incubation and represent a valuable model for human in vitro hepatotoxicity testing despite the human inter-individual variability.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Extensive Intra-Kingdom Horizontal Gene Transfer Converging on a Fungal Fructose Transporter Gene

Comparative genomics revealed in the last decade a scenario of rampant horizontal gene transfer (HGT) among prokaryotes, but for fungi a clearly dominant pattern of vertical inheritance still stands, punctuated however by an increasing number of exceptions. In the present work, we studied the phylogenetic distribution and pattern of inheritance of a fungal gene encoding a fructose transporter (FSY1) with unique substrate selectivity. 109 FSY1 homologues were identified in two sub-phyla of the Ascomycota, in a survey that included 241 available fungal genomes. At least 10 independent inter-species instances of horizontal gene transfer (HGT) involving FSY1 were identified, supported by strong phylogenetic evidence and synteny analyses. The acquisition of FSY1 through HGT was sometimes suggestive of xenolog gene displacement, but several cases of pseudoparalogy were also uncovered. Moreover, evidence was found for successive HGT events, possibly including those responsible for transmission of the gene among yeast lineages. These occurrences do not seem to be driven by functional diversification of the Fsy1 proteins because Fsy1 homologues from widely distant lineages, including at least one acquired by HGT, appear to have similar biochemical properties. In summary, retracing the evolutionary path of the FSY1 gene brought to light an unparalleled number of independent HGT events involving a single fungal gene. We propose that the turbulent evolutionary history of the gene may be linked to the unique biochemical properties of the encoded transporter, whose predictable effect on fitness may be highly variable. In general, our results support the most recent views suggesting that inter-species HGT may have contributed much more substantially to shape fungal genomes than heretofore assumed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earth’s crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and surge in publicly available sequence data has made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition, iron redox cycling, iron storage, and magnetosome formation in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) based on genes related to iron acquisition, storage, and reduction/oxidation in Bacteria and Archaea. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate provided datasets with respect to iron-related genes and gene neighborhood. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. We validated FeGenie against a selected set of 28 isolate genomes and showcase its utility in exploring iron genes present in 27 metagenomes, 4 isolate genomes from human oral biofilms, and 17 genomes from candidate organisms, including members of the candidate phyla radiation. We show that FeGenie accurately identifies iron genes in isolates. Furthermore, analysis of metagenomes using FeGenie demonstrates that the iron gene repertoire and abundance of each environment is correlated with iron richness. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenie’s database will be maintained and continually updated as new genes are discovered.

59 BASIC BIOLOGICAL SCIENCES↗