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At least 199 records · Page 11

Exploring genetic diversity, population structure, and subgenome differences in the allopolyploid Camelina sativa : implications for future breeding and research studies

Abstract Camelina (Camelina sativa), an allohexaploid species, is an emerging aviation biofuel crop that has been the focus of resurgent interest in recent decades. To guide future breeding and crop improvement efforts, the community requires a deeper comprehension of subgenome dominance, often noted in allopolyploid species, “alongside an understanding of the genetic diversity” and population structure of material present within breeding programs. We conducted population genetic analyses of a C. sativa diversity panel, leveraging a new genome, to estimate nucleotide diversity and population structure, and analyzed for patterns of subgenome expression dominance among different organs. Our analyses confirm that C. sativa has relatively low genetic diversity and show that the SG3 subgenome has substantially lower genetic diversity compared to the other two subgenomes. Despite the low genetic diversity, our analyses identified 13 distinct subpopulations including two distinct wild populations and others putatively representing founders in existing breeding populations. When analyzing for subgenome composition of long non-coding RNAs, which are known to play important roles in (a)biotic stress tolerance, we found that the SG3 subgenome contained significantly more lincRNAs compared to other subgenomes. Similarly, transcriptome analyses revealed that expression dominance of SG3 is not as strong as previously reported and may not be universal across all organ types. From a global analysis, SG3 “was only significant higher expressed” in flower, flower bud, and fruit organs, which is an important discovery given that the crop yield is associated with these organs. Collectively, these results will be valuable for guiding future breeding efforts in camelina.

Agriculture↗

Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophilic species for this study and identified thermophily as the ancestral state of all three prominent families of thermophilic fungi. Thermophilic fungal genomes were found to encode various thermostable enzymes, including carbohydrate-active enzymes such as endoxylanases, which are useful for many industrial applications. At the same time, the overall gene counts, especially in gene families responsible for microbial defense such as secondary metabolism, are reduced in thermophiles compared to mesophiles. We also found a reduction in the core genome size of thermophiles in both the Chaetomiaceae family and the Eurotiomycetes class. The Gene Ontology terms lost in thermophilic fungi include primary metabolism, transporters, UV response, and O-methyltransferases. Comparative genomics analysis also revealed higher GC content in the third base of codons (GC3) and a lower effective number of codons in fungal thermophiles than in both thermotolerant and mesophilic fungi. Furthermore, using the Support Vector Machine classifier, we identified several Pfam domains capable of discriminating between genomes of thermophiles and mesophiles with 94% accuracy. Using AlphaFold2 to predict protein structures of endoxylanases (GH10), we built a similarity network based on the structures. We found that the number of disulfide bonds appears important for protein structure, and the network clusters based on protein structures correlate with the optimal activity temperature. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of thermophilic fungi while providing a parts list for bioengineering applications.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of the Function of the ASFV KP177R Gene, Encoding for Structural Protein p22, in the Process of Virus Replication and in Swine Virulence

African swine fever virus (ASFV) causes a devastating disease of swine that has caused outbreaks in Central Europe since 2007, spreading into Asia in 2018. ASFV is a large, structurally complex virus with a large dsDNA genome encoding for more than 160 genes, most of them still uncharacterized. p22, encoded by the ASFV gene KP177R, is an early transcribed, structural virus protein located in the ASFV particle. Although its exact function is unknown, p22 has recently been identified as an interacting partner of several host proteins. Here, we describe the development of a recombinant ASFV (ASFV-G-ΔKP177R) lacking the KP177R gene as a tool to evaluate the role of p22 in virus replication and virulence in swine. The recombinant ASFV-G-ΔKP177R demonstrated that the KP177R gene is non-essential for ASFV replication in primary swine macrophages, with virus yields similar to those of the parental, highly virulent field isolate Georgia2010 (ASFV-G). In addition, experimental infection of domestic pigs with ASFV-G-ΔKP177R produced a clinical disease similar to that caused by the parental ASFV-G. Therefore, and surprisingly, p22 does not seem to be involved in virus replication or virulence in swine.

59 BASIC BIOLOGICAL SCIENCES↗

RNA language models predict mutations that improve RNA function

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗

Genome resources for three modern cotton lines guide future breeding efforts

Cotton ( Gossypium hirsutum L.) is the key renewable fibre crop worldwide, yet its yield and fibre quality show high variability due to genotype-specific traits and complex interactions among cultivars, management practices and environmental factors. Modern breeding practices may limit future yield gains due to a narrow founding gene pool. Precision breeding and biotechnological approaches offer potential solutions, contingent on accurate cultivar-specific data. Here we address this need by generating high-quality reference genomes for three modern cotton cultivars (‘UGA230’, ‘UA48’ and ‘CSX8308’) and updating the ‘TM-1’ cotton genetic standard reference. Despite hypothesized genetic uniformity, considerable sequence and structural variation was observed among the four genomes, which overlap with ancient and ongoing genomic introgressions from ‘Pima’ cotton, gene regulatory mechanisms and phenotypic trait divergence. Differentially expressed genes across fibre development correlate with fibre production, potentially contributing to the distinctive fibre quality traits observed in modern cotton cultivars. These genomes and comparative analyses provide a valuable foundation for future genetic endeavours to enhance global cotton yield and sustainability.

59 BASIC BIOLOGICAL SCIENCES↗

kb_DRAM: annotation and metabolic profiling of genomes with DRAM in KBase

Microbial genome annotation is the process of identifying structural and functional elements in DNA sequences and subsequently attaching biological information to those elements. DRAM is a tool developed to annotate bacterial, archaeal, and viral genomes derived from pure cultures or metagenomes. DRAM goes beyond traditional annotation tools by distilling multiple gene annotations to genome level summaries of functional potential. Despite these benefits, a downside of DRAM is the requirement of large computational resources, which limits its accessibility. Further, it did not integrate with downstream metabolic modeling tools that require genome annotation. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated with the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point-and-click interface, as well as generate genome-scale metabolic models from DRAM annotations.

59 BASIC BIOLOGICAL SCIENCES↗

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗

Structure of a 28.5 kDa duplex-embedded G-quadruplex system resolved to 7.4 Å resolution with cryo-EM

Genomic regions with high guanine content can fold into non-B form DNA four-stranded structures known as G-quadruplexes (G4s). Extensive in vivo investigations have revealed that promoter G4s are transcriptional regulators. Little structural information exists for these G4s embedded within duplexes, their presumed genomic environment. Here, we report the 7.4 Å resolution structure and dynamics of a 28.5 kDa duplex-G4-duplex (DGD) model system using cryo-EM, molecular dynamics, and small-angle X-ray scattering (SAXS) studies. The DGD cryo-EM refined model features a 53° bend induced by a stacked duplex-G4 interaction at the 5’ G-tetrad interface with a persistently unstacked 3’ duplex. The surrogate complement poly dT loop preferably stacks onto the 3’ G-tetrad interface resulting in occlusion of both 5’ and 3’ tetrad interfaces. Structural analysis shows that the DGD model is quantifiably more druggable than the monomeric G4 structure alone and represents a new structural drug target. Our results illustrate how the integration of cryo-EM, MD, and SAXS can reveal complementary detailed static and dynamic structural information on DNA G4 systems.

59 BASIC BIOLOGICAL SCIENCES↗

The Importance of Solution Studies for the Structural Characterization of the Enterovirus 5’ Cloverleaf

Enteroviruses initiate genomic replication via a highly conserved mechanism that is controlled by an RNA platform, also known as the 5’ cloverleaf (5’CL). Here, we present a biophysical analysis of the 5’CL conformation of three enterovirus serotypes under various ionic conditions, utilizing CD spectroscopy, size-exclusion chromatography, and small-angle X-ray scattering. In general, a tendency toward a smaller monomeric hydrodynamic radius in the presence of salts was observed, but the exact structural signature of each 5’CL varied depending upon the serotype. Rhinovirus B14 (RVB14) exhibited at least two monomeric conformations and a low propensity for dimerization, while poliovirus 1 (PV1) showed a high propensity for dimerization, which was enhanced by the presence of salts. Enterovirus D70 was observed to be somewhat intermediate, with primarily a monomeric structure, but possessing some potential for dimerization. The equilibrium between the two monomeric and the dimeric conformations is also discussed. These results indicate that the 5’CL conformation may be more complex than the current literature suggests, thus underscoring the need for a combined crystal and solution approach for the accurate representation of the 5’CL conformation, and the conformation of other RNA structural elements, under native conditions.

Virology↗

Cryptic genetic structure and copy-number variation in the ubiquitous forest symbiotic fungus Cenococcum geophilum

Ectomycorrhizal (ECM) fungi associated with plants constitute one of the most successful symbiotic interactions in forest ecosystems. ECM support trophic exchanges with host plants and are important factors for the survival and stress resilience of trees. However, ECM clades often harbour morpho-species and cryptic lineages, with weak morphological differentiation. How this relates to intraspecific genome variability and ecological functioning is poorly known. Here, we analysed 16 European isolates of the ascomycete Cenococcum geophilum, an extremely ubiquitous forest symbiotic fungus with no known sexual or asexual spore-forming structures but with a massively enlarged genome. We carried out whole-genome sequencing to identify single-nucleotide polymorphisms. We found no geographic structure at the European scale but divergent lineages within sampling sites. Evidence for recombination was restricted to specific cryptic lineages. Lineage differentiation was supported by extensive copy-number variation. Finally, we confirmed heterothallism with a single MAT1 idiomorph per genome. Synteny analyses of the MAT1 locus revealed substantial rearrangements and a pseudogene of the opposite MAT1 idiomorph. Our study provides the first evidence for substantial genome-wide structural variation, lineage-specific recombination and low continent-wide genetic differentiation in C. geophilum. Our study provides a foundation for targeted analyses of intra-specific functional variation in this major symbiosis.

54 ENVIRONMENTAL SCIENCES↗

Rational Design of Nanoplasmonic Array Geometries for Biosensing

Background: Molecular diagnostics provide early and accurate diagnosis, which is essential for the prevention and treatment of infectious as well as chronic diseases. These tests are designed to detect disease-specific bioanalytes such as nucleic acid (DNA or RNA) or protein (antigens, antibodies) biomarkers. In the context of infectious disease diagnosis, nucleic acid-based detection methods are known to provide more specific and sensitive results. Here, the presence of a unique sequence belonging to the pathogenic genomic material is targeted to identify species, organism, genera and/or antimicrobial resistant gene markers. The majority of the common nucleic acid based diagnostic techniques require amplification (polymerase chain reaction, isothermal amplification etc.) of the pathogenic genetic material prior to detection impacting diagnostic speed, complexity, and cost thereby limiting ease of use. Thus, the development of simplified nucleic acid-based diagnostics that can be even used in resource-poor settings may hugely benefit patients across the globe. Nanopath is a molecular diagnostics company utilizing a solid-state nanosensor to enable sequence-specific detection of target nucleic acids without the need of amplification. These nanostructures enable ultra-sensitive biomarker detection using geometric, feature-dependent properties highly dependent on the local dielectric environment, allowing them to be sensitive to low concentration binding events. This paper describes an application of this approach to provide highly relevant clinical information within a single doctor’s office visit. Intro: The Nanopath team is in collaboration with NASA (National Aeronautics and Space Administration) and NIST (National Institute of Standards and Technology) to push the bounds of the fundamental physics associated with their biosensing platform. The ability of metals to support electromagnetic surface waves gives rise to surface plasmons when optically illuminated. This property, and its strong sensitivity to changes in the local refractive index, allows for the use of metal nanoparticles as ultra-sensitive transducers. In prior work by members of this team, ensembles of randomly oriented nanoparticles (i.e., colloidal nanorods dispersed on chip) were employed for sequence-specific nucleic acid sensing (1-3). While these particle sensors have the advantage of rapid fabrication, they suffer from low sensitivity and quality factor due to the random particle dispersity. In contrast, in this study we employ ordered array nanoparticle ensembles which can be used to improve sensor sensitivity and figure-of-merit. Study Methods Overview: In this talk, we detail the results of sensing experiments and computational simulations to outline a rational design of the structure of these plasmonic nanoparticle arrays for biomolecular sensing. Through simulation and experiment, we iteratively tailor nanostructure dimension to provide high quality signal and large resonance shifts upon modeled nucleic acid binding. In particular, full-wave electromagnetic simulations were conducted using Lumerical photonic simulation software in which periodic boundary conditions were applied in the x- and y- dimensions for each of the nanoplasmonic sensor geometries. To simulate the resonance response to changes in the bulk solution in contact with the sensor surface, the refractive index of the surrounding media was changed appropriately. Nucleic acid hybridization events were modeled using either using spherical structures approximating the relevant radius of genomic material as estimated by polymer models, or as conformal layers with the known refractive indices for nucleic acids. On the basis of initial simulations, nanosensors were fabricated using traditional electron-beam lithography protocols at NIST. To evaluate consensus between simulations and experiments, bulk sensing experiments were carried out in which the resonance peaks were obtained by submerging the sensors in refractive index standards. Key nanosensor characteristics including resonance peak locations, resonance peak shifts as a function of refractive index, and figure of merit (FOM) of extinction curves were examined between the experimental and simulation results prior to proceeding with simulations on additional geometries and more complex solution conditions, and further device fabrication. This iterative process is repeated toward a rational design of nanoplasmonic array geometries for biosensing optimizing response for targeted disease detection. In summary, this study puts forth a methodology for rational design and characterization of regularly spaced nanoparticle arrays for optics-based biosensing. The results of this study will allow for more informed design of nanostructure geometries towards sequence-specific nucleic acid detection. These improved designs have the potential to improve clinical sensitivity and limit-of-detection across disease indication.

sensor↗

Epitopes recognition of SARS-CoV-2 nucleocapsid RNA binding domain by human monoclonal antibodies

Coronavirus nucleocapsid protein (NP) of SARS-CoV-2 plays a central role in many functions important for virus proliferation including packaging and protecting genomic RNA. The protein shares sequence, structure, and architecture with nucleocapsid proteins from betacoronaviruses. The N-terminal domain (NP RBD ) binds RNA and the C-terminal domain is responsible for dimerization. After infection, NP is highly expressed and triggers robust host immune response. The anti-NP antibodies are not protective and not neutralizing but can effectively detect viral proliferation soon after infection. Two structures of SARS-CoV-2 NP RBD were determined providing a continuous model from residue 48 to 173, including RNA binding region and key epitopes. Five structures of NP RBD complexes with human mAbs were isolated using an antigen-bait sorting. Complexes revealed a distinct complement-determining regions and unique sets of epitope recognition. This may assist in the early detection of pathogens and designing peptide-based vaccines. Mutations that significantly increase viral load were mapped on developed, full length NP model, likely impacting interactions with host proteins and viral RNA.

59 BASIC BIOLOGICAL SCIENCES↗

Virus-Like Particle: Evolving Meanings in Different Disciplines

Virus-like particle (VLP) is a term that has been in use for about 80 years. Usually, VLP has meant a particle that is like a virus, generally by appearance, but without either proven or actual virus functionality. Initially VLP referred to particles seen in electron microscope images of tissues. More recently, VLP has come to mean other things to other researchers. A key divergence has been use of VLP in association with vaccine and biotechnology applications versus use of VLP in enumeration of viruses in environmental samples. To these viral ecologists, a VLP is a particle that is virus sized, has nucleic acid, and could be a functional virus. But to vaccine developers and biotechnology researchers a VLP instead is a viral structure that intentionally lacks a viral genome. Here, we look at the history of use of VLP, following changes in meaning as the technology to study VLPs changed.

59 BASIC BIOLOGICAL SCIENCES↗

Packaging “vegetable oils”: Insights into plant lipid droplet proteins

Abstract Plant neutral lipids, also known as “vegetable oils”, are synthesized within the endoplasmic reticulum (ER) membrane and packaged into subcellular compartments called lipid droplets (LDs) for stable storage in the cytoplasm. The biogenesis, modulation, and degradation of cytoplasmic LDs in plant cells are orchestrated by a variety of proteins localized to the ER, LDs, and peroxisomes. Recent studies of these LD-related proteins have greatly advanced our understanding of LDs not only as steady oil depots in seeds but also as dynamic cell organelles involved in numerous physiological processes in different tissues and developmental stages of plants. In the past 2 decades, technology advances in proteomics, transcriptomics, genome sequencing, cellular imaging and protein structural modeling have markedly expanded the inventory of LD-related proteins, provided unprecedented structural and functional insights into the protein machinery modulating LDs in plant cells, and shed new light on the functions of LDs in nonseed plant tissues as well as in unicellular algae. Here, we review critical advances in revealing new LD proteins in various plant tissues, point out structural and mechanistic insights into key proteins in LD biogenesis and dynamic modulation, and discuss future perspectives on bridging our knowledge gaps in plant LD biology.

Cai, Yingqi (ORCID:0000000203575809)↗

Rapid mini‐chromosome divergence among fungal isolates causing wheat blast outbreaks in Bangladesh and Zambia

Summary The fungal pathogen,Magnaporthe oryzae Triticumpathotype, causing wheat blast disease was first identified in South America and recently spread across continents to South Asia and Africa. Here, we studied the genetic relationship among isolates found on the three continents. Magnaporthe oryzaestrains closely related to a South American field isolate B71 were found to have caused the wheat blast outbreaks in South Asia and Africa. Genomic variation among isolates from the three continents was examined using an improved B71 reference genome and whole‐genome sequences. We found strong evidence to support that the outbreaks in Bangladesh and Zambia were caused by the introductions of genetically separated isolates, although they were all close to B71 and, therefore, collectively referred to as the B71 branch. In addition, B71 branch strains carried at least one supernumerary mini‐chromosome. Genome assembly of a Zambian strain revealed that its mini‐chromosome was similar to the B71 mini‐chromosome but with a high level of structural variation. Our findings show that while core genomes of the multiple introductions are highly similar, the mini‐chromosomes have undergone marked diversification. The maintenance of the mini‐chromosome and rapid genomic changes suggest the mini‐chromosomes may serve important virulence or niche adaptation roles under diverse environmental conditions.

Plant Sciences↗

Giant Virus Infection Signatures Are Modulated by Euphotic Zone Depth Strata and Iron Regimes of the Subantarctic Southern Ocean

Viruses can alter the abundance, evolution, and metabolism of microorganisms in the ocean, playing a key role in water column biogeochemistry and global carbon cycles. Large efforts to measure the contribution of eukaryotic microorganisms (e.g., protists) to the marine food web have been made, yet the in situ activities of the ecologically relevant viruses that infect these organisms are not well characterized. Viruses within the phylum Nucleocytoviricota (“giant viruses”) are known to infect a diverse range of ecologically relevant marine protists, yet how these viruses are influenced by environmental conditions remains under-characterized. By employing metatranscriptomic analyses of in situ microbial communities along a temporal and depthresolved gradient, we describe the diversity of giant viruses at the Southern Ocean Time Series (SOTS), a site within the subpolar Southern Ocean. Using a phylogeny-guided taxonomic assessment of detected giant virus genomes and metagenome-assembled genomes, we observed depth-dependent structuring of divergent giant virus families mirroring dynamic physicochemical gradients in the stratified euphotic zone. Analyses of transcribed metabolic genes from giant viruses suggest viral metabolic reprogramming of hosts from the surface to a 200-m depth. Lastly, using on-deck incubations reflecting a gradient of iron availability, we show that modulating iron regimes influences the activity of giant viruses in the field. Specifically, we show enhanced infection signatures of giant viruses under both iron-replete and iron-limited conditions. Collectively, these results expand our understanding of how the water column’s vertical biogeography and chemical surroundings affect an important group of viruses within the Southern Ocean

59 BASIC BIOLOGICAL SCIENCES↗