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AlgaeOrtho, a bioinformatics tool for processing ortholog inference results in algae
Introduction: Microalgae constitute a prominent feedstock for producing biofuels and biochemicals by virtue of their prolific reproduction, high bioproduct accumulation, and the ability to grow in brackish and saline water. However, naturally occurring wild type algal strains are rarely optimal for industrial use; therefore, bioengineering of algae is necessary to generate superior performing strains that can address production challenges in industrial settings, particularly the bioenergy and bioproduct sectors. One of the crucial steps in this process is deciding on a bioengineering target: namely, which gene/protein to differentially express. These targets are often orthologs which are defined as genes/proteins originating from a common ancestor in divergent species. Although bioinformatics tools for the identification of protein orthologs already exist, processing the output from such tools is nontrivial, especially for a researcher with little or no bioinformatics experience. Methods: The present study introduces AlgaeOrtho, a user-friendly tool that builds upon the SonicParanoid orthology inference tool (based on an algorithm that identifies potential protein orthologs based on amino acid sequences) and the PhycoCosm database from JGI (Joint Genome Institute) to help researchers identify orthologs of their proteins of interest in multiple diverse algal species. Results: The output of this application includes a table of the putative orthologs of their protein of interest, a heatmap showing sequence similarity (%), and an unrooted tree of the putative protein orthologs. Notably, the tool would be instrumental in identifying novel bioengineering targets in different algal strains, including targets in not-fully annotated algal species, since it does not depend on existing protein annotations. We tested AlgaeOrtho using three case studies, for which orthologs of proteins relevant to bioengineering targets, were identified from diverse algal species, demonstrating its ease of use and utility for bioengineering researchers. Discussion: This tool is unique in the protein ortholog identification space as it can visualize putative orthologs, as desired by the user, across several algal species.
Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium toruloides
An oleaginous yeast Rhodosporidium toruloides is a promising host for converting lignocellulosic biomass to bioproducts and biofuels. In this work, we performed multi-omics analysis of lignocellulosic carbon utilization in R. toruloides and reconstructed the genome-scale metabolic network of R. toruloides . High-quality metabolic network models for model organisms and orthologous protein mapping were used to build a draft metabolic network reconstruction. The reconstruction was manually curated to build a metabolic model using functional annotation and multi-omics data including transcriptomics, proteomics, metabolomics, and RB-TDNA sequencing. The multi-omics data and metabolic model were used to investigate R. toruloides metabolism including lipid accumulation and lignocellulosic carbon utilization. The developed metabolic model was validated against high-throughput growth phenotyping and gene fitness data, and further refined to resolve the inconsistencies between prediction and data. We believe that this is the most complete and accurate metabolic network model available for R. toruloides to date.
Staphylococcus pseudintermedius 5'-nucleotidase suppresses canine phagocytic activity
Staphylococcus pseudintermedius is a major opportunistic bacterial pathogen and the leading cause of pyoderma in dogs. In canines it is also often associated with infections of the urinary system and wounds and occasionally infects people. Widespread antimicrobial resistance has made the development of alternative treatments a high priority. The development of a staphylococcal vaccine, however, has proven challenging. Identification of virulence factors that inhibit phagocytosis and avoid innate immunity may play a significant role in preventing or treating infection with S. pseudintermedius. In this study, we identified a putative 5'-nucleotidase provisionally named SpAdsA, a S. pseudintermedius cell- wall protein encoded by SpAdsA. SpAdsA shares approximately 52% identity with the orthologous protein of Staphylococcus aureus and 14.8% identity with that of Streptococcus suis type2. It catalyzes the dephosphorylation of adenosine triphosphate and attenuation of this enzyme with critical amino acid substitutions nearly eliminated its hydrolytic activity. Furthermore, exogenous adenosine inhibited phagocytosis of S. pseudintermedius by canine neutrophils and monocytes. Conversely, the addition of SpAdsA inhibitor or A2A adenosine receptor antagonist impaired the capacity of S. pseudintermedius to escape from killing by phagocytic cells. The neutralizing ability of canine antibody produced against SpAdsA-M was determined. Taken together, these results suggest that SpAdsA likely plays an important role in S. pseudintermedius virulence and that attenuated SpAdsA may be a good candidate for inclusion in a vaccine against S. pseudintermedius.
The Land–Sea Connection: Insights Into the Plant Lineage from a Green Algal Perspective
The colonization of land by plants generated opportunities for the rise of new heterotrophic life forms, including humankind. A unique event underpinned this massive change to earth ecosystems—the advent of eukaryotic green algae. Today, an abundant marine green algal group, the prasinophytes, alongside prasinodermophytes and nonmarine chlorophyte algae, is facilitating insights into plant developments. Genome-level data allow identification of conserved proteins and protein families with extensive modifications, losses, or gains and expansion patterns that connect to niche specialization and diversification. Here, we contextualize attributes according to Viridiplantae evolutionary relationships, starting with orthologous protein families, and then focusing on key elements with marked differentiation, resulting in patchy distributions across green algae and plants. We place attention on peptidoglycan biosynthesis, important for plastid division and walls; phytochrome photosensors that are master regulators in plants; and carbohydrate-active enzymes, essential to all manner of carbohydratebiotransformations. Together with advances in algal model systems, these areas are ripe for discovering molecular roles and innovations within and across plant and algal lineages.
Integrative Modeling and Analysis of Fungal Central Carbon Metabolism
Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity
Symmetry breaking and structural polymorphism in a bacterial microcompartment shell protein for chol
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Genome-scale model development and genomic sequencing of the oleaginous clade Lipomyces
The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, and 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces .
Reconstruction of Cysteine Biosynthesis Using Engineered Cysteine-Free and Methionine-Free Enzymes
Ten of the proteinogenic amino acids can be generated abiotically while the remaining thirteen require biology for their synthesis. Paradoxically, the biosynthesis pathways observed in nature require enzymes that are made with the amino acids they produce. For example, Escherichia coli produces cysteine from serine via two enzymes that contain cysteine. Here, we substituted alternate amino acids for cysteine and also methionine, which is biosynthesized from cysteine, in serine acetyl transferase (CysE) and O-acetylserine sulfhydrylase (CysM). CysE function was rescued by cysteine-and-methionine-free enzymes and CysM function was rescued by cysteine-free enzymes. Structural modeling suggests that methionine stabilizes CysM and is present in the active site of CysM. Cysteine is not conserved among CysE and CysM protein orthologs, suggesting that cysteine is not functionally important for its own synthesis. Engineering biosynthetic enzymes that lack the amino acids being synthesized provides insights into the evolution of amino acid biosynthesis and pathways for bioengineering.
VPF-Class: taxonomic assignment and host prediction of uncultivated viruses based on viral protein families
Abstract Motivation Two key steps in the analysis of uncultured viruses recovered from metagenomes are the taxonomic classification of the viral sequences and the identification of putative host(s). Both steps rely mainly on the assignment of viral proteins to orthologs in cultivated viruses. Viral Protein Families (VPFs) can be used for the robust identification of new viral sequences in large metagenomics datasets. Despite the importance of VPF information for viral discovery, VPFs have not yet been explored for determining viral taxonomy and host targets. Results In this work, we classified the set of VPFs from the IMG/VR database and developed VPF-Class. VPF-Class is a tool that automates the taxonomic classification and host prediction of viral contigs based on the assignment of their proteins to a set of classified VPFs. Applying VPF-Class on 731K uncultivated virus contigs from the IMG/VR database, we were able to classify 363K contigs at the genus level and predict the host of over 461K contigs. In the RefSeq database, VPF-class reported an accuracy of nearly 100% to classify dsDNA, ssDNA and retroviruses, at the genus level, considering a membership ratio and a confidence score of 0.2. The accuracy in host prediction was 86.4%, also at the genus level, considering a membership ratio of 0.3 and a confidence score of 0.5. And, in the prophages dataset, the accuracy in host prediction was 86% considering a membership ratio of 0.6 and a confidence score of 0.8. Moreover, from the Global Ocean Virome dataset, over 817K viral contigs out of 1 million were classified. Availability and implementation The implementation of VPF-Class can be downloaded from https://github.com/biocom-uib/vpf-tools. Supplementary information Supplementary data are available at Bioinformatics online.
GenomeDepot: data management system for microbial comparative genomics
Summary GenomeDepot is an open-source web-based platform for annotation, management, and comparative analysis of microbial genomic sequences and associated data including ortholog families, protein domains, operons, regulatory interactions, strain taxonomy, and sample metadata. GenomeDepot supports rapid creation of websites for user-defined genome collections that include bioinformatic tools for interactive genome browsing, Basic Local Alignment Search Tool (BLAST) search, annotation search, comparative genomic neighborhood visualization, and sequence download. Gene function annotations are generated by a customizable annotation pipeline. The pipeline runs annotation tools in Conda environments and can be easily extended with additional user-specified tools. Availability and implementation GenomeDepot is open source and distributed under the GNU General Public License via GitHub (https://github.com/aekazakov/genome-depot). GenomeDepot is implemented in Python and was tested in Ubuntu Linux. Full installation instructions and documentation are available at https://aekazakov.github.io/genome-depot/. GenomeDepot demo server is freely accessible at https://iseq.lbl.gov/demogd/.
GenomeDepot v1.0
GenomeDepot is a web-based platform for annotation, management, and comparative analysis of microbial genomic sequences and associated data including ortholog families, protein domains, operons, regulatory interactions, strain taxonomy, and sample metadata. GenomeDepot supports rapid creation of web-sites for user-defined genome collections that include bioinformatic tools for interactive genome browsing, BLAST search, annotation search, comparative genomic neighborhood visualization, and sequence download. Gene function annotations are generated by a customizable annotation pipeline. The pipeline runs annotation tools in Conda environments and can be easily extended with additional user-specified tools.
CyanoCyc cyanobacterial web portal
CyanoCyc is a web portal that integrates an exceptionally rich database collection of information about cyanobacterial genomes with an extensive suite of bioinformatics tools. It was developed to address the needs of the cyanobacterial research and biotechnology communities. The 277 annotated cyanobacterial genomes currently in CyanoCyc are supplemented with computational inferences including predicted metabolic pathways, operons, protein complexes, and orthologs; and with data imported from external databases, such as protein features and Gene Ontology (GO) terms imported from UniProt. Five of the genome databases have undergone manual curation with input from more than a dozen cyanobacteria experts to correct errors and integrate information from more than 1,765 published articles. CyanoCyc has bioinformatics tools that encompass genome, metabolic pathway and regulatory informatics; omics data analysis; and comparative analyses, including visualizations of multiple genomes aligned at orthologous genes, and comparisons of metabolic networks for multiple organisms. CyanoCyc is a high-quality, reliable knowledgebase that accelerates scientists’ work by enabling users to quickly find accurate information using its powerful set of search tools, to understand gene function through expert mini-reviews with citations, to acquire information quickly using its interactive visualization tools, and to inform better decision-making for fundamental and applied research.
Dynamic molecular architecture of the synaptonemal complex
During meiosis, pairing between homologous chromosomes is stabilized by the assembly of the synaptonemal complex (SC). The SC ensures the formation of crossovers between homologous chromosomes and regulates their distribution. However, how the SC regulates crossover formation remains elusive. We isolated an unusual mutation in Caenorhabditis elegans that disrupts crossover interference but not SC assembly. This mutation alters the unique C terminal domain of an essential SC protein, SYP-4, a likely ortholog of the vertebrate SC protein SIX6OS1. We use three-dimensional stochastic optical reconstruction microscopy (3D-STORM) to interrogate the molecular architecture of the SC from wild-type and mutant C. elegans animals. Using a probabilistic mapping approach to analyze super-resolution image data, we detect changes in the organization of the synaptonemal complex in wild-type animals that coincide with crossover designation. We also found that our syp-4 mutant perturbs SC architecture. Our findings add to growing evidence that the SC is an active material whose molecular organization contributes to chromosome-wide crossover regulation.
Determining protein polarization proteome-wide using physical dissection of individual Stentor coeruleus cells
Cellular components are non-randomly arranged with respect to the shape and polarity of the whole cell. Patterning within cells can extend down to the level of individual proteins and mRNA. But how much of the proteome is actually localized with respect to cell polarity axes? Proteomics combined with cellular fractionation has shown that most proteins localize to one or more organelles but does not tell us how many proteins have a polarized localization with respect to the large-scale polarity axes of the intact cell. Genome-wide localization studies in yeast found that only a few percent of proteins have a localized position relative to the cell polarity axis defined by sites of polarized cell growth. Here, we describe an approach for analyzing protein distribution within a cell with a visibly obvious global patterning - the giant ciliate Stentor coeruleus. Ciliates, including Stentor, have highly polarized cell shapes with visible surface patterning. A Stentor cell is roughly 2mmlong, allowing a ‘‘proteomic dissection’’ in which microsurgery is used to separate cellular fragments along the anterior-posterior axis, followed by comparative proteomic analysis. In our analysis, 25% of the proteome, including signaling proteins, centrin/SFI proteins, and GAS2 orthologs, shows a polarized location along the cell’s anterior-posterior axis. We conclude that a large proportion of all proteins are polarized with respect to global cell polarity axes and that proteomic dissection provides a simple and effective approach for spatial proteomics.
Metagenomic insights into the taxonomy, function, and dysbiosis of prokaryotic communities in octocorals
Background. In octocorals (Cnidaria Octocorallia), the functional relationship between host health and its symbiotic consortium has yet to be determined. Here, we employed comparative metagenomics to uncover the distinct functional and phylogenetic features of the microbiomes of healthy Eunicella gazella, Eunicella verrucosa, and Leptogorgia sarmentosa tissues, in contrast with the microbiomes found in seawater and sediments. We further explored how the octocoral microbiome shifts to a pathobiome state in E. gazella. Results. Multivariate analyses based on 16S rRNA genes, Clusters of Orthologous Groups of proteins (COGs), Protein families (Pfams), and secondary metabolite-biosynthetic gene clusters annotated from 20 Illumina-sequenced metagenomes each revealed separate clustering of the prokaryotic communities of healthy tissue samples of the three octocoral species from those of necrotic E. gazella tissue and surrounding environments. While the healthy octocoral microbiome was distinguished by so-far uncultivated Endozoicomonadaceae, Oceanospirillales, and Alteromonadales phylotypes in all host species, a pronounced increase of Flavobacteriaceae and Alphaproteobacteria, originating from seawater, was observed in necrotic E. gazella tissue. Increased abundances of eukaryotic-like proteins, exonucleases, restriction endonucleases, CRISPR/Cas proteins, and genes encoding for heat-shock proteins, inorganic ion transport, and iron storage distinguished the prokaryotic communities of healthy octocoral tissue regardless of the host species. An increase of arginase and nitric oxide reductase genes, observed in necrotic E. gazella tissues, suggests the existence of a mechanism for suppression of nitrite oxide production by which octocoral pathogens may overcome the host’s immune system. Conclusions. This is the first study to employ primer-less, shotgun metagenome sequencing to unveil the taxonomic, functional, and secondary metabolism features of prokaryotic communities in octocorals. Our analyses reveal that the octocoral microbiome is distinct from those of the environmental surroundings, is host genus (but not species) specific, and undergoes large, complex structural changes in the transition to the dysbiotic state. Host-symbiont recognition, abiotic-stress response, micronutrient acquisition, and an antiviral defense arsenal comprising multiple restriction endonucleases, CRISPR/Cas systems, and phage lysogenization regulators are signatures of prokaryotic communities in octocorals. We argue that these features collectively contribute to the stabilization of symbiosis in the octocoral holobiont and constitute beneficial traits that can guide future studies on coral reef conservation and microbiome therapy.
Iron Homeostasis in Yellowstone National Park Hot Spring Microbial Communities
It has been postulated that life may have originated on Earth, and possibly on Mars, in association with hydrothermal activity and high concentrations of ferrous iron. However, it is not clear how an iron-rich thermal hydrosphere could be hospitable to microbes, since reduced iron appears to stimulate oxidative stress in all domains of life and particularly in oxygenic phototrophs. Therefore, the study of microbial diversity in iron-depositing hot springs (IDHS) and the mechanisms of iron homeostasis and suppression of oxidative stress may help elucidate how Precambrian organisms could withstand the extremely high concentrations of reactive oxygen species (ROS) produced by interaction between environmental Fe(2+) and O2. Proteins and clusters of orthologous groups (COGs) involved in the maintenance of Fe homeostasis found in cyanobacteria (CB) inhabiting environments with high and low [Fe] were main target of this analysis. Preliminary results of the analysis suggest that the Chocolate Pots (CP) microbial community is heavily dominated by phototrophs from the cyanobacteria (CB), Chloroflexi and Chlorobi phyla, while the Mushroom Spring (MS) effluent channel harbors a more diverse community in which Chloroflexi are the dominant phototrophs. It is speculated that CB inhabiting IDHS have an increased tolerance to both high concentrations of Fe(2+) and ROS produced in the Fenton reaction. This hypothesis was explored via a comparative analysis of the diversity of proteins and COGs involved in Fe and redox homeostasis in the CP and MS microbiomes.
OrthoPhylo
This software builds on PHAME developed at LANL to generate phylogenetic trees of bacterial whole genome sequences. Where PHAME uses whole genome alignments to generate informative sites to base tress on, PHAME-OuS annotates bacterial genes, identifies orthologous sequences, aligns related proteins, uses those alignments to inform transcript alignments, then builds trees with several methods. The first is a conventional gene concatenation and ML tree estemation method. The second attempts to reconcile gene tree with a unified species tree using quartets (ASTRAL). Both methods allow filtering of gene lists on number of species represented, length, and gappiness in order to tune noise-to-signal for tree estimation