Biology subjects

Bhattacharya, D.

Publications and source records attributed to Bhattacharya, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Hot springs viruses at Yellowstone National Park have ancient origins and are adapted to their thermophilic hosts.

Geothermal springs in areas such as Yellowstone National Park (YNP), USA house unicellular red algae that dominate the microbial biomass. Little is known about the viruses that infect the biota. Here we used metagenomics to characterize the multi-kingdom infecting virus community associated with red algal mats in three neighboring habitats (creek, endolithic, soil) at Lemonade Creek, YNP to determine their taxonomic composition, predicted gene functions, extent of horizontal gene transfer, and potential links to hosts. We find that despite proximity, each habitat houses a unique collection of viruses, with the giant viruses, Megaviricetes, dominant in all three. The early branching phylogenetic position of genes encoded on metagenome assembled virus genomes (vMAGs) suggests that the YNP lineages are of ancient origins and not the result of multiple invasions from mesophilic habitats. The existence of genomic footprints of adaptation to thermophily in the vMAGs is consistent with this idea. Our study is the first analysis of viruses associated with polyextremophilic red algae that form extensive microbial mats in YNP and are common worldwide at geothermal sites. Although more recent than the earliest forms of prokaryotic life, these eukaryotic algal mats originated ca. 1.5 Bya, and therefore span a significant period of the planets history. Our data are therefore relevant to understanding biotic interactions on the early Earth.

evolutionary biology↗

bioRxiv2023

lociPARSE: a locality-aware invariant point attention model for scoring RNA 3D structures

A scoring function that can reliably assess the accuracy of a 3D RNA structural model in the absence of experimental structure is not only important for model evaluation and selection but also useful for scoring-guided conformational sampling. However, high-fidelity RNA scoring has proven to be difficult using conventional knowledge-based statistical potentials and currently-available machine learning-based approaches. Here we present lociPARSE, a locality-aware invariant point attention architecture for scoring RNA 3D structures. Unlike existing machine learning methods that estimate superposition-based root mean square deviation (RMSD), lociPARSE estimates Local Distance Difference Test (lDDT) scores capturing the accuracy of each nucleotide and its surrounding local atomic environment in a superposition-free manner, before aggregating information to predict global structural accuracy. Tested on multiple datasets including CASP15, lociPARSE significantly outperforms existing statistical potentials (rsRNASP, cgRNASP, DFIRE-RNA, and RASP) and machine learning methods (ARES and RNA3DCNN) across complementary assessment metrics. lociPARSE is freely available at https://github.com/Bhattacharya-Lab/lociPARSE.

bioinformatics↗

bioRxiv2023

YlaN is an iron(II) binding protein that functions to relieve Fur-mediated repression of gene expression in Staphylococcus aureus

Iron (Fe) is a trace nutrient required by nearly all organisms. As a result of the demand for Fe and the toxicity of non-chelated cytosolic ionic Fe, regulatory systems have evolved to tightly balance Fe acquisition and usage while limiting overload. In most bacteria, including the mammalian pathogen Staphylococcus aureus, the ferric uptake regulator (Fur) is the primary transcriptional regulator that controls the transcription of genes that code for Fe uptake and utilization proteins. YlaN was demonstrated to be essential in Bacillus subtilis unless excess Fe is added to the growth medium, suggesting a role in Fe homeostasis. Here, we demonstrate that YlaN is expendable in S. aureus; however, YlaN became essential upon Fe deprivation. A null fur allele bypassed the essentiality of YlaN. The transcriptional response of Fur derepression resulted in a reprogramming of metabolism to prioritize fermentative growth over respiratory growth. The absence of YlaN diminished the derepression of Fur-dependent transcription during Fe limitation. Bioinformatic analyses suggest that ylaN was recruited to Gram positive bacteria and once acquired was maintained in the genome as it co-evolved with Fur. Consistent with a role for YlaN in influencing Fur-dependent regulation, YlaN and Fur interacted in vivo. YlaN bound Fe(II) in vitro using oxygen or nitrogen ligands with an association constant that is consistent with a physiological role in Fe sensing and/or buffering. These findings have led to a model wherein YlaN is an Fe(II) binding protein that influences Fur-dependent regulation through direct interaction. ImportanceIron (Fe) is an essential nutrient for nearly all organisms. If Fe homeostasis is not maintained, Fe can accumulate in the cytosol where it is toxic. Questions remain about how cells efficiently balance Fe uptake and usage to prevent imbalance. Iron uptake and proper metalation of proteins are essential processes in the mammalian bacterial pathogen Staphylococcus aureus. Understanding the gene products involved in Fe ion regulation, uptake, and usage, as well as the physiological adaptations that S. aureus uses to survive in Fe-depleted conditions, will provide insight into the role that Fe has in pathogenesis. These data will also provide insight into the selective pressures imparted by the mammalian host.

microbiology↗

bioRxiv2023

EquiPNAS: improved protein-nucleic acid binding site prediction using protein-language-model-informed equivariant deep graph neural networks

Protein language models (pLMs) trained on a large corpus of protein sequences have shown unprecedented scalability and broad generalizability in a wide range of predictive modeling tasks, but their power has not yet been harnessed for predicting protein-nucleic acid binding sites, critical for characterizing the interactions between proteins and nucleic acids. Here we present EquiPNAS, a new pLM-informed E(3) equivariant deep graph neural network framework for improved protein-nucleic acid binding site prediction. By combining the strengths of pLM and symmetry-aware deep graph learning, EquiPNAS consistently outperforms the state-of-the-art methods for both protein-DNA and protein-RNA binding site prediction on multiple datasets across a diverse set of predictive modeling scenarios ranging from using experimental input to AlphaFold2 predictions. Our ablation study reveals that the pLM embeddings used in EquiPNAS are sufficiently powerful to dramatically reduce the dependence on the availability of evolutionary information without compromising on accuracy, and that the symmetry-aware nature of the E(3) equivariant graph-based neural architecture offers remarkable robustness and performance resilience. EquiPNAS is freely available at https://github.com/Bhattacharya-Lab/EquiPNAS.

bioinformatics↗

bioRxiv2023

Cholesterol-associated Locus EHBP1 Protects against NASH Fibrosis

SUMMARYHepatic free cholesterol contributes to fibrosis in nonalcoholic steatohepatitis (NASH), but how hepatic cholesterol metabolism becomes dysregulated in NASH is not completely understood. We show here that human fibrotic NASH livers have decreased EHBP1, a novel GWAS locus associated with LDL-cholesterol, and that the EHBP1 rs10496099 T>C variant in NASH patients is associated with decreased hepatic EHBP1 expression and augmented NASH fibrosis. Congruent with the human data, EHBP1 loss- and gain-of-function increases and decreases NASH fibrosis in mice, respectively. Mechanistic studies reveal that EHBP1 promotes sortilin (SORT1)-mediated PCSK9 secretion, leading to LDLR degradation, decreased LDL uptake, and reduced TAZ, a fibrogenic effector. Moreover, we show that the TNF/PPAR pathway suppresses EHBP1 in NASH. These data not only provide new mechanistic insight into the role of EHBP1 in cholesterol metabolism and NASH fibrosis by uncovering the interaction between EHBP1 and other cholesterol-related loci, including SORT1, PCSK9, and LDLR, but also elucidate a novel interplay between inflammation and EHBP1-mediated cholesterol metabolism. HighlightsHepatic EHBP1 is reduced in human and mouse fibrotic NASH EHBP1 rs10496099 T>C is associated with decreased hepatic EHBP1 and augmented NASH EHBP1 reduces LDLR, cholesterol uptake, and TAZ in hepatocytes EHBP1 promotes sortilin-mediated PCSK9 secretion in hepatocytes TNF suppresses EHBP1 expression in hepatocytes

pathology↗

bioRxiv2023

Engineering Human Pluripotent Stem Cell Lines to Evade Xenogeneic Transplantation Barriers

Allogeneic human pluripotent stem cell (hPSC)-derived cells and tissues for therapeutic transplantation must necessarily overcome immunological rejection by the recipient. To define these barriers and to create cells capable of evading rejection for preclinical testing in immunocompetent mouse models, we genetically ablated {beta}2m, Tap1, Ciita, Cd74, Mica, and Micb to limit expression of HLA-I, HLA-II, and natural killer cell activating ligands in hPSCs. Though these and even unedited hPSCs readily formed teratomas in cord blood-humanized immunodeficient mice, grafts were rapidly rejected by immunocompetent wild-type mice. Transplantation of these cells that also expressed covalent single chain trimers of Qa1 and H2-Kb to inhibit natural killer cells and CD55, Crry, and CD59 to inhibit complement deposition led to persistent teratomas in wild-type mice. Expression of additional inhibitory factors such as CD24, CD47, and/or PD-L1 had no discernible impact on teratoma growth or persistence. Transplantation of HLA-deficient hPSCs into mice genetically deficient in complement and depleted of natural killer cells also led to persistent teratomas. Thus, T cell, NK cell, and complement evasion are necessary to prevent immunological rejection of hPSCs and their progeny. These cells and versions expressing human orthologs of immune evasion factors can be used to refine tissue- and cell type-specific immune barriers, and to conduct preclinical testing in immunocompetent mouse models.

immunology↗

bioRxiv2023

Genome-wide transcriptome analysis reveals the diversity and function of long non-coding RNAs in dinoflagellates

Dinoflagellates are a diverse group of phytoplankton, ranging from harmful bloom-forming microalgae to photosymbionts that are critical for sustaining coral reefs. Genome and transcriptome data from dinoflagellates are revealing extensive genomic divergence and lineage-specific innovation of gene functions. However, most studies thus far have focused on protein-coding genes; long non-coding RNAs (lncRNAs), known to regulate gene expression in eukaryotes, are largely unexplored. Here, using both genome and transcriptome data, we identified a combined total of 48,039 polyadenylated lncRNAs in the genomes of three dinoflagellate species: the coral symbionts of Cladocopium proliferum and Durusdinium trenchii, and the bloom-forming Prorocentrum cordatum. These putative lncRNAs are shorter, and have fewer introns and lower G+C-content when compared to protein-coding sequences. Although 37,768 (78.6%) lncRNAs shared no significant similarity with one another, we classified all lncRNAs based on conserved sequence motifs (k-mers) into distinct clusters following properties of potential protein-binding and/or subcellular localisation. Interestingly, 3708 (7.7%) lncRNAs were differentially expressed in response to heat stress, lifestyle, and/or growth phases, and they shared co-expression patterns with protein-coding genes. Based on inferred triplex interactions between lncRNA and upstream (putative promoter) regions of protein-coding genes, we identified a combined 19,460 putative gene targets for 3,721 lncRNAs; 907 genes exhibit differential expression under heat stress. These results reveal for the first time the functional diversity of lncRNAs in dinoflagellates, and demonstrate how lncRNAs, often overlooked in transcriptome data, could regulate gene expression as a molecular response to heat stress in these ecologically important organisms.

genomics↗

bioRxiv2023

Intraspecies genomic divergence of coral algal symbionts shaped by gene duplication

Dinoflagellates of Order Suessiales include the diverse Family Symbiodiniaceae known for their role as essential coral reef symbionts, and the cold-adapted Polarella glacialis. These taxa inhabit a broad range of ecological niches and exhibit extensive genomic divergence, although their genomes are in the smaller size ranges (haploid size < 3 Gbp) compared to most other dinoflagellates. Different isolates of a species are known to form symbiosis with distinct hosts and exhibit different regimes of gene expression, but intraspecies whole-genome divergence remains little known. Focusing on three Symbiodiniaceae species (the free-living Effrenium voratum, and the symbiotic Symbiodinium microadriaticum and Durusdinium trenchii) and the free-living outgroup P. glacialis, all for which whole-genome data from multiple isolates are available, we assessed intraspecies genomic divergence at sequence and structural levels. Our analysis based on alignment and alignment-free methods revealed greater extent of intraspecies sequence divergence in symbiodiniacean species than in P. glacialis. Our results also reveal the implications of gene duplication in generating functional innovation and diversification of Symbiodiniaceae, particularly in D. trenchii for which whole-genome duplication was involved. Interestingly, tandem duplication of single-exon genes was found to be more prevalent in genomes of free-living species than in those of symbiotic species. These results in combination demonstrate the remarkable intraspecies genomic divergence in dinoflagellates under the constraint of reduced genome sizes, shaped by genetic duplications and symbiogenesis events during diversification of Symbiodiniaceae.

genomics↗

bioRxiv2023

Massive genome reduction occurred prior to the origin of coral algal symbionts

Dinoflagellates in the Family Symbiodiniaceae (Order Suessiales) are diverse, predominantly symbiotic lineages that associate with taxa such as corals and jellyfish. Their ancestor is believed to have been free-living, and the establishment of symbiosis (i.e., symbiogenesis) is hypothesised to have occurred multiple times during Symbiodiniaceae evolution. Among Symbiodiniaceae taxa, the genus Effrenium is an early diverging, free-living lineage that is phylogenetically positioned between two robustly supported groups of genera within which symbiotic taxa have emerged. The lack of symbiogenesis in Effrenium suggests that the ancestral features of Symbiodiniaceae may have been retained in this lineage. Here we present de novo assembled genomes and associated transcriptome data from three isolates of Effrenium voratum. We compared the Effrenium genomes (1.2-1.9 Gbp in size) and gene features with those of 16 Symbiodiniaceae taxa and other outgroup dinoflagellates. Surprisingly, we find that genome reduction, which is often associated with a symbiotic lifestyle, predates the origin of Symbiodiniaceae. We postulate that adaptation to an extreme habitat (e.g., as in Polarella glacialis) or life in oligotrophic conditions resulted in the Suessiales ancestor having a haploid genome size < 2Gbp, which was retained (or reduced) among all extant algae in this lineage. Nonetheless, our data reveal that the free-living lifestyle distinguishes Effrenium from symbiotic Symbiodiniaceae vis-a-vis their longer introns, more-extensive mRNA editing, fewer ([~]30%) lineage-specific gene families, and lower ([~]10%) level of pseudogenisation. These results demonstrate how genome reduction and the adaptation to symbiotic versus free-living lifestyles intersect, and have driven the diversification and genome evolution of Symbiodiniaceae.

genomics↗

bioRxiv2023

PIQLE: protein-protein interface quality estimation by deep graph learning of multimeric interaction geometries

Accurate modeling of protein-protein interaction interface is essential for high-quality protein complex structure prediction. Existing approaches for estimating the quality of a predicted protein complex structural model utilize only the physicochemical properties or energetic contributions of the interacting atoms, ignoring evolutionarily information or inter-atomic multimeric geometries, including interaction distance and orientations. Here we present PIQLE, a deep graph learning method for protein-protein interface quality estimation. PIQLE leverages multimeric interaction geometries and evolutionarily information along with sequence- and structure-derived features to estimate the quality of the individual interactions between the interfacial residues using a multihead graph attention network and then probabilistically combines the estimated quality of the interfacial residues for scoring the overall interface. Experimental results show that PIQLE consistently outperforms existing state-of-the-art methods on multiple independent test datasets across a wide range of evaluation metrics. Our ablation study reveals that the performance gains are connected to the effectiveness of the multihead graph attention network in leveraging multimeric interaction geometries and evolutionary information along with other sequence- and structure-derived features adopted in PIQLE. An open-source software implementation of PIQLE, licensed under the GNU General Public License v3, is freely available at https://github.com/Bhattacharya-Lab/PIQLE.

bioinformatics↗

bioRxiv2022

T-cell cellular stress and reticulocyte signatures, but not loss of naive T lymphocytes, characterize severe COVID-19 in older adults

In children and younger adults up to 39 years of age, SARS-CoV-2 usually elicits mild symptoms that resemble the common cold. Disease severity increases with age starting at 30 and reaches astounding mortality rates that are ~330 fold higher in persons above 85 years of age compared to those 18-39 years old. To understand age-specific immune pathobiology of COVID-19 we have analyzed soluble mediators, cellular phenotypes, and transcriptome from over 80 COVID-19 patients of varying ages and disease severity, carefully controlling for age as a variable. We found that reticulocyte numbers and peripheral blood transcriptional signatures robustly correlated with disease severity. By contrast, decreased numbers and proportion of naive T-cells, reported previously as a COVID-19 severity risk factor, were found to be general features of aging and not of COVID-19 severity, as they readily occurred in older participants experiencing only mild or no disease at all. Single-cell transcriptional signatures across age and severity groups showed that severe but not moderate/mild COVID-19 causes cell stress response in different T-cell populations, and some of that stress was unique to old severe participants, suggesting that in severe disease of older adults, these defenders of the organism may be disabled from performing immune protection. These findings shed new light on interactions between age and disease severity in COVID-19.

immunology↗

bioRxiv2022

E(3) equivariant graph neural networks for robust and accurate protein-protein interaction site prediction

Artificial intelligence-powered protein structure prediction methods have led to a paradigm-shift in computational structural biology, yet contemporary approaches for predicting the interfacial residues (i.e., sites) of protein-protein interaction (PPI) still rely on experimental structures. Recent studies have demonstrated benefits of employing graph convolution for PPI site prediction, but ignore symmetries naturally occurring in 3-dimensional space and act only on experimental coordinates. Here we present EquiPPIS, an E(3) equivariant graph neural network approach for PPI site prediction. EquiPPIS employs symmetry-aware graph convolutions that transform equivariantly with translation, rotation, and reflection in 3D space, providing richer representations for molecular data compared to invariant convolutions. EquiPPIS substantially outperforms state-of-the-art approaches based on the same experimental input, and exhibits remarkable robustness by attaining better accuracy with predicted structural models from AlphaFold2 than what existing methods can achieve even with experimental structures. Freely available at https://github.com/Bhattacharya-Lab/EquiPPIS, EquiPPIS enables accurate PPI site prediction at scale.

bioinformatics↗

bioRxiv2022

Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB

Bacterial cell division is a tightly regulated process that requires the formation of a dynamic multi-protein complex. In the Firmicutes phylum, GpsB is a membrane associated protein that coordinates peptidoglycan synthesis for cell growth and division. Although GpsB has been studied in several organisms, the structure, function, and interactome of Staphylococcus aureus GpsB is largely uncharacterized, despite being reported as uniquely essential for growth in this clinically relevant bacterium. To address this knowledge gap, we solved the crystal structure of the N-terminal domain of S. aureus GpsB. This structure reveals an atypical asymmetric dimer, and major conformational flexibility that can be mapped to a hinge region formed by a three-residue insertion exclusive to Staphylococci. When this three-residue insertion is excised, its thermal stability increases, and the mutant no longer produces a previously reported lethal phenotype when overexpressed in Bacillus subtilis. Furthermore, we provide the first biochemical, biophysical, and crystallographic evidence that the N-terminal domain of GpsB binds not only PBP4, but also FtsZ, through a conserved recognition motif located on their C-terminus, thus linking peptidoglycan synthesis with cell division. Taken together, the unique structure of S. aureus GpsB and its direct interaction with FtsZ/PBP4 provide deeper insight into the central role of GpsB in S. aureus cell division.

microbiology↗

bioRxiv2022

Novel transient cell clusters provide a possible link between early neural activity and angiogenesis in the neonatal mouse retina

Developing neurons become spontaneously active while growing blood vessels begin to irrigate their surroundings. However, surprising little is known about early interactions between neural activity and angiogenesis. In the neonatal mouse retina, spontaneous waves of impulses sweep across the ganglion cell layer (GCL), just underneath the growing superficial vascular plexus. We discovered clusters of transient auto-fluorescent cells in the GCL, forming an annulus that co-localizes with the frontline of the growing plexus. Blood vessel density is highest within cluster areas, suggesting their involvement in angiogenesis. Once the clusters and blood vessels reach the retinal periphery by the end of the first postnatal week, the clusters disappear, eliminated by microglial phagocytosis. Electrical imaging suggests that they have their own electrophysiological signature. Blocking Pannexin1 (PANX1) hemi-channels with probenecid blocks the waves and the fluorescent clusters disappear following prolonged exposure to the drug. Spontaneous waves initiation points follow a developmental center-to-periphery progression similar to the cluster cells. We suggest that these transient cells are specialized, hyperactive neurons residing in the GCL. They generate spontaneous activity hotspots, thereby triggering waves through purinergic paracrine signaling via PANX1 hemi-channels. The strong activity generated around these hotspots triggers angiogenesis, attracting new blood vessels that provide local oxygen supply. Signaling through PANX-1 attracts microglia that establish contact with these cells, eventually leading to their elimination by phagocytosis. These cluster cells may provide the first evidence that specialized transient neuronal populations guide angiogenesis in the developing CNS through neural activity.

neuroscience↗

bioRxiv2022

Evolution of resilience against heat stress in a red-tide dinoflagellate

"Red tides" are harmful algal blooms (HABs) caused by dinoflagellate microalgae that accumulate toxins lethal to other organisms, including humans via consumption of contaminated seafood. Increasingly frequent, HABs are driven by a combination of environmental factors including nutrient enrichment, particularly in warm waters. Here, we present the de novo assembled genome (~4.75 Gbp), transcriptome, proteome, and metabolome from Prorocentrum cordatum, a globally abundant, bloom-forming dinoflagellate. Using axenic algal cultures, we studied the molecular mechanisms that underpin response to temperature stress, which is relevant to current ocean warming trends. We discovered a complementary interplay between RNA editing and exon usage that regulates the expression and functional diversity of biomolecules, reflected by reduction in photosynthesis, central metabolism, and protein synthesis. Our multi-omics analyses uncover the molecular response to heat stress in an important HAB species, which is driven by complex gene structures in a large, high-G+C genome, combined with multi-level transcriptional regulation.

genomics↗

bioRxiv2022

Improved Cladocopium goreaui genome assembly reveals features of a facultative coral symbiont and the complex evolutionary history of dinoflagellate genes

Dinoflagellates of the family Symbiodiniaceae are crucial photosymbionts in corals and other marine organisms. Of these algae, Cladocopium goreaui is one of the most dominant symbiont species in the Indo-Pacific. Here, we present an improved genome assembly of C. goreaui combining new long-read sequence data with earlier generated short-read data. Incorporating new full-length transcripts to guide gene prediction, the C. goreaui genome (1.2 Gb) exhibits a high extent of completeness (82.4% based on BUSCO protein recovery) and better resolution of repetitive sequence regions; 45,322 gene models were predicted, and 327 putative, topologically associated domains of the chromosomes were identified. Comparison with other Symbiodiniaceae genomes revealed a prevalence of repeats and duplicated genes in C. goreaui, and lineage-specific genes indicating functional innovation. Incorporating 2,841,408 protein sequences from 96 broadly sampled eukaryotes and representative prokaryotes in a phylogenomic approach, we assessed the evolutionary history of C. goreaui genes. Of the 5,246 phylogenetic trees inferred from homologous protein sets containing two or more phyla, 35-36% have putatively originated via horizontal gene transfer (HGT), predominantly (19-23%) via an ancestral Archaeplastida lineage implicated in the endosymbiotic origin of plastids: 10-11% are of green algal origin, including genes encoding photosynthetic functions. Our results demonstrate the utility of long-read sequence data in resolving structural features of a dinoflagellate genome and highlight how genetic transfer has shaped genome evolution of a facultative symbiont, and more broadly of dinoflagellates.

genomics↗

bioRxiv2022

Lung spatial profiling reveals a T cell signature in COPD patients with fatal SARS-CoV-2 infection

RationalePeople with pre-existing lung diseases like chronic obstructive pulmonary disease (COPD) are more likely to get very sick from SARS-CoV-2 disease 2019 (COVID-19), but an interrogation of the immune response to COVID-19 infection, spatial throughout the lung structure is lacking in patients with COPD. ObjectivesTo profile the immune microenvironment of lung parenchyma, airways, and vessels of never- and ever-smokers with or without COPD, whom all died of COVID-19, using spatial transcriptomic and proteomic profiling. FindingsThe parenchyma, airways, and vessels of COPD patients, compared to control lungs had: 1) significant enrichment for lung resident CD45RO+ memory T cells; 2) downregulation of genes associated with T cell antigen-priming and memory T cell differentiation; 3) higher expression of proteins associated with SARS-CoV-2 entry and major receptor ubiquitously across the ROIs and in particular the lung parenchyma, despite similar SARS-CoV-2 structural gene expression levels. ConclusionsThe lung parenchyma, airways, and vessels of COPD patients have increased T-lymphocytes with a blunted memory T cell response and a more invasive SARS-CoV-2 infection pattern, and may underlie the higher death toll observed with COVID-19.

immunology↗

bioRxiv2022

Multiple waves of viral invasions in Symbiodiniaceae algal genomes

Dinoflagellates from the family Symbiodiniaceae are phototrophic marine protists that engage in symbiosis with diverse hosts. Their large and distinct genomes show pervasive gene duplication and large-scale retroposition events. However, little is known about the role and scale of horizontal gene transfer (HGT) in the genomic evolution of this algal family. In other dinoflagellates, higher levels of HGTs have been observed, linked to major genomic transitions, such as the appearance of a viral acquired nucleoprotein that originated via HGT from a large DNA algal virus. Previous work showed Symbiodiniaceae from different hosts being actively infected by several viral groups, such as giant DNA viruses and ssRNA viruses, that may play an important role in coral health. This includes a hypothetical latent viral infection, whereby viruses could persist in the cytoplasm or integrate into the host genome as a provirus. This hypothesis received some experimental support however, the cellular localization of putative latent viruses and their taxonomic affiliation are still unknown. In addition, despite the finding of viral sequences in some genomes of Symbiodiniaceae, viral origin, taxonomic breadth, and metabolic potential have not been explored. To address these questions, we searched for evidence of protein sequences of putative viral origin in 13 Symbiodiniaceae genomes. We found 59 candidate viral-derived HGTs that give rise to 12 phylogenies across 10 genomes. We also describe the taxonomic affiliation of these virus-related sequences, their structure, and genomic context. These results lead us to propose a model to explain the origin and fate of Symbiodiniaceae viral acquisitions.

evolutionary biology↗