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At least 55 records · Page 3

Non-photosynthetic lineages sibling to Cyanobacteria associate with eukaryotes in the open ocean

Margulisbacteria are elusive uncultivated bacteria that have illuminated evolutionary transitions in the progenitor of Cyanobacteria, the latter being a critically important phylum that underpins oxygenic photosynthesis. The non-photosynthetic Margulisbacteria were discovered in a sulfidic spring and later in other habitats. Currently, this candidate phylum partitions into the Riflemargulisbacteria, primarily from sediments and groundwater, the Termititenax from insect gut microbiomes, and the Marinamargulisbacteria, from marine samples. We found that Marinamargulisbacteria amplicons were unusually distributed in size-fractionated samples from the sunlit photic and dark twilight zones of the ocean. Further, sequencing of wild marine protists rendered genomic information for distinct marinamargulisbacterial clades co-associated with uncultivated, non-photosynthetic Stramenopila and Opisthokonta protists. Phylogenomic analyses combining these data and available metagenome-assembled genomes (MAGs) and single-amplified genomes (SAGs) from sorted bacteria revealed new Marinamargulisbacteria lineages. The lineages delineate by their environment, forming clades comprising freshwater, marine pelagic, or sediment/hypoxic taxa. In conclusion, the remarkable diversity of Margulisbacteria indicates success in colonizing various habitats, potentially in a conserved strategy involving eukaryotic cells.

59 BASIC BIOLOGICAL SCIENCES↗

Protocol for single-cell isolation and genome amplification of environmental microbial eukaryotes for genomic analysis

We describe environmental microbial eukaryotes (EMEs) sample collection, single-cell isolation, lysis, and genome amplification, followed by the rDNA amplification and OTU screening for recovery of high-quality species-specific genomes for de novo assembly. These protocols are part of our pipeline that also includes bioinformatic methods. The pipeline and its application on a wide range of phyla of different sample complexity are described in our complementary paper. In addition, this protocol describes optimized lysis, genome amplification, and OTU screening steps of the pipeline. For complete details on the use and execution of this protocol, please refer to Ciobanu et al. (2021).

59 BASIC BIOLOGICAL SCIENCES↗

Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes

Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.

59 BASIC BIOLOGICAL SCIENCES↗

Structural basis for the calmodulin-mediated activation of eukaryotic elongation factor 2 kinase

Translation is a tightly regulated process that ensures optimal protein quality and enables adaptation to energy/nutrient availability. The α-kinase eukaryotic elongation factor 2 kinase (eEF-2K), a key regulator of translation, specifically phosphorylates the guanosine triphosphatase eEF-2, thereby reducing its affinity for the ribosome and suppressing the elongation phase of protein synthesis. eEF-2K activation requires calmodulin binding and autophosphorylation at the primary stimulatory site, T348. Biochemical studies predict a calmodulin-mediated activation mechanism for eEF-2K distinct from other calmodulin-dependent kinases. Here, we resolve the atomic details of this mechanism through a 2.3-Å crystal structure of the heterodimeric complex of calmodulin and the functional core of eEF-2K (eEF-2K TR ). This structure, which represents the activated T348-phosphorylated state of eEF-2K TR , highlights an intimate association of the kinase with the calmodulin C-lobe, creating an “activation spine” that connects its amino-terminal calmodulin-targeting motif to its active site through a conserved regulatory element.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural Diversity in Eukaryotic Photosynthetic Light Harvesting

Photosynthesis has been using energy from sunlight to assimilate atmospheric CO 2 for at least 3.5 billion years. Through evolution and natural selection, photosynthetic organisms have flourished in almost all aquatic and terrestrial environments. This is partly due to the diversity of light-harvesting complex (LHC) proteins, which facilitate photosystem assembly, efficient excitation energy transfer, and photoprotection. Structural advances have provided angstrom-level structures of many of these proteins and have expanded our understanding of the pigments, lipids, and residues that drive LHC function. In this review, we compare and contrast recently observed cryo-electron microscopy structures across photosynthetic eukaryotes to identify structural motifs that underlie various light-harvesting strategies. We discuss subtle monomer changes that result in macroscale reorganization of LHC oligomers. Additionally, we find recurring patterns across diverse LHCs that may serve as evolutionary stepping stones for functional diversification. Advancing our understanding of LHC protein–environment interactions will improve our capacity to engineer more productive crops.

60 APPLIED LIFE SCIENCES↗

Inhibition of the eukaryotic initiation factor-2α kinase PERK decreases risk of autoimmune diabetes in mice

Preventing the onset of autoimmune type 1 diabetes (T1D) is feasible through pharmacological interventions that target molecular stress–responsive mechanisms. Cellular stresses, such as nutrient deficiency, viral infection, or unfolded proteins, trigger the integrated stress response (ISR), which curtails protein synthesis by phosphorylating eukaryotic translation initiation factor-2α (eIF2α). In T1D, maladaptive unfolded protein response (UPR) in insulin-producing β cells renders these cells susceptible to autoimmunity. We found that inhibition of the eIF2α kinase PKR-like ER kinase (PERK), a common component of the UPR and ISR, reversed the mRNA translation block in stressed human islets and delayed the onset of diabetes, reduced islet inflammation, and preserved β cell mass in T1D-susceptible mice. Single-cell RNA-Seq of islets from PERK-inhibited mice showed reductions in the UPR and PERK signaling pathways and alterations in antigen-processing and presentation pathways in β cells. Spatial proteomics of islets from these mice showed an increase in the immune checkpoint protein programmed death-ligand 1 (PD-L1) in β cells. Golgi membrane protein 1, whose levels increased following PERK inhibition in human islets and EndoC-βH1 human β cells, interacted with and stabilized PD-L1. Collectively, our studies show that PERK activity enhances β cell immunogenicity and that inhibition of PERK may offer a strategy for preventing or delaying the development of T1D.

Research & Experimental Medicine↗

Data for "Design of Diverse, Functional Mitochondrial Targeting Sequences Across Eukaryotic Organisms Using Variational Autoencoder"

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

AI/ML↗

Targeting tRNA-synthetase interactions towards novel therapeutic discovery against eukaryotic pathogens

The development of chemotherapies against eukaryotic pathogens is especially challenging because of both the evolutionary conservation of drug targets between host and parasite, and the evolution of strain-dependent drug resistance. There is a strong need for new nontoxic drugs with broad-spectrum activity against trypanosome parasites such as Leishmania and Trypanosoma. A relatively untested approach is to target macromolecular interactions in parasites rather than small molecular interactions, under the hypothesis that the features specifying macromolecular interactions diverge more rapidly through coevolution. We computed tRNA Class-Informative Features in humans and independently in eight distinct clades of trypanosomes, identifying parasite-specific informative features, including base pairs and base mis-pairs, that are broadly conserved over approximately 250 million years of trypanosome evolution. Validating these observations, we demonstrated biochemically that tRNA:aminoacyl-tRNA synthetase (aaRS) interactions are a promising target for anti-trypanosomal drug discovery. From a marine natural products extract library, we identified several fractions with inhibitory activity toward Leishmania major alanyl-tRNA synthetase (AlaRS) but no activity against the human homolog. These marine natural products extracts showed cross-reactivity towards Trypanosoma cruzi AlaRS indicating the broad-spectrum potential of our network predictions. We also identified Leishmania major threonyl-tRNA synthetase (ThrRS) inhibitors from the same library. We discuss why chemotherapies targeting multiple aaRSs should be less prone to the evolution of resistance than monotherapeutic or synergistic combination chemotherapies targeting only one aaRS.

59 BASIC BIOLOGICAL SCIENCES↗

Optimization of Energy Flow through Synthetic Metabolic Modules and Regulatory Networks in a Model Photosynthetic Eukaryotic Microbe

Photosynthetic organisms have recently gained considerable attention for a role in development of renewable energy sources. Genome-enabled systems biology methods, coupled with functional and synthetic genomics, present opportunities to develop sustainable and economical applications such as fuel production within the next 10 to 15 years. However, optimization of light-driven metabolism for biomass or biofuel production will require a detailed systems biology understanding of photosynthetic processes and cellular metabolism. Genome-scale metabolic models (GEMs) are at the core of systems analysis of cellular processes and form a common organizational framework for analyses of data resulting from functional genomics experimental work and computational studies. Therefore, there is a clear demand for high quality photosynthetic model organisms and the appropriate computational tools that enable systems analysis of light-driven metabolism. Through research conducted we expanded the currently available repertoire of photosynthetic GEMs to include the commercially valuable model diatom Phaeoctylum tricornutum. Diatoms have a peculiar and distinct evolutionary footprint and represent a major eukaryotic lineage that is taxonomically and functionally distinct from green and red algae and vascular plants. Therefore, the true potential for light-driven metabolism aimed at biofuel production remains poorly understood at a systems level for a large subset of the global diversity of photosynthetic organisms. The metabolic capabilities of P. tricornutum were comparatively modeled with those from other photosynthetic groups in order to elucidate the occurrence of metabolic traits within and between phototrophs. Additionally, this research resulted in significant extension of the COnstraints Based Reconstruction and Analysis (COBRA) Toolbox to accommodate the crucial need for infrastructure required for ‘omics data integration and analysis in the context of genome-scale models. Therefore, the proposed research achieved two important goals. First, within the broad scope of photosynthetic organisms, we functionally compared and, as a result, identified cellular processes that require optimization in order to enable deployment as biofuel feedstock. Second, the proposed research resulted in development of key computational infrastructure, which can be further extended to other biological systems, that is currently lacking but necessary for multiple ‘omics data integration.

59 BASIC BIOLOGICAL SCIENCES↗

gRNA-SeqRET: a universal tool for targeted and genome-scale gRNA design and sequence extraction for prokaryotes and eukaryotes

High-throughput genetic screening is frequently employed to rapidly associate gene with phenotype and establish sequence-function relationships. With the advent of CRISPR technology, and the ability to functionally interrogate previously genetically recalcitrant organisms, non-model organisms can be investigated using pooled guide RNA (gRNA) libraries and sequencing-based assays to quantitatively assess fitness of every targeted locus in parallel. To aid the construction of pooled gRNA assemblies, we have developed an in silico design workflow for gRNA selection using the gRNA Sequence Region Extraction Tool (gRNA-SeqRET). Built upon the previously developed CCTop, gRNA-SeqRET enables automated, scalable design of gRNA libraries that target user-specified regions or whole genomes of any prokaryote or eukaryote. Additionally, gRNA-SeqRET automates the bulk extraction of any regions of sequence relative to genes or other features, aiding in the design of homology arms for insertion or deletion constructs. We also assess in silico the application of a designed gRNA library to other closely related genomes and demonstrate that for very closely related organisms Average Nucleotide Identity (ANI) > 95% a large fraction of the library may be of relevance. The gRNA-SeqRET web application pipeline can be accessed at https://grna.jgi.doe.gov. The source code is comprised of freely available software tools and customized Python scripts, and is available at https://bitbucket.org/berkeleylab/grnadesigner/src/master/ under a modified BSD open-source license (https://bitbucket.org/berkeleylab/grnadesigner).

59 BASIC BIOLOGICAL SCIENCES↗

Rapid Cis–Trans Coevolution Driven by a Novel Gene Retroposed from a Eukaryotic Conserved CCR4–NOT Component in Drosophila

Young, or newly evolved, genes arise ubiquitously across the tree of life, and they can rapidly acquire novel functions that influence a diverse array of biological processes. Previous work identified a young regulatory duplicate gene in Drosophila, Zeus that unexpectedly diverged rapidly from its parent, Caf40, an extremely conserved component in the CCR4–NOT machinery in post-transcriptional and post-translational regulation of eukaryotic cells, and took on roles in the male reproductive system. This neofunctionalization was accompanied by differential binding of the Zeus protein to loci throughout the Drosophila melanogaster genome. However, the way in which new DNA-binding proteins acquire and coevolve with their targets in the genome is not understood. Here, by comparing Zeus ChIP-Seq data from D. melanogaster and D. simulans to the ancestral Caf40 binding events from D. yakuba, a species that diverged before the duplication event, we found a dynamic pattern in which Zeus binding rapidly coevolved with a previously unknown DNA motif, which we term Caf40 and Zeus-Associated Motif (CAZAM), under the influence of positive selection. Interestingly, while both copies of Zeus acquired targets at male-biased and testis-specific genes, D. melanogaster and D. simulans proteins have specialized binding on different chromosomes, a pattern echoed in the evolution of the associated motif. Using CRISPR-Cas9-mediated gene knockout of Zeus and RNA-Seq, we found that Zeus regulated the expression of 661 differentially expressed genes (DEGs). Our results suggest that the evolution of young regulatory genes can be coupled to substantial rewiring of the transcriptional networks into which they integrate, even over short evolutionary timescales. Our results thus uncover dynamic genome-wide evolutionary processes associated with new genes.

59 BASIC BIOLOGICAL SCIENCES↗

Oxygen as a factor in eukaryote evolution - Some effects of low levels of oxygen on Saccharomyces cerevisiae

A comparative study of the effects of varying levels of oxygen on some of the metabolic functions of the primitive eukaryote, Saccharomyces cerevisiae, has shown that these cells are responsive to very low levels of oxygen: the level of palmitoyl-Co A desaturase was greatly enhanced by only 0.03 vol % oxygen. Similarly, an acetyl-CoA synthetase associated predominantly with anaerobic growth was stimulated by as little as 0.1% oxygen, while an isoenzyme correlated with aerobic growth was maximally active at much higher oxygen levels (greater than 1%). Closely following this latter pattern were three mitochondrial enzymes that attained maximal activity only under atmospheric levels of oxygen.

Jahnke, L.↗

Evolution of prokaryote and eukaryote lines inferred from sequence evidence

This paper describes the evolution of prokaryotes and early eukaryotes, including their symbiotic relationships, as inferred from phylogenetic trees of bacterial ferredoxin, 5S ribosomal RNA, ribulose-1,5-biphosphate carboxylase large chain, and mitochondrial cytochrome oxidase polypeptide II.

Hunt, L. T.↗

Microsatellites in the Eukaryotic DNA Mismatch Repair Genes as Modulators of Evolutionary Mutation Rate

All "minor" components of the human DNA mismatch repair (MMR) system-MSH3, MSH6, PMS2, and the recently discovered MLH3-contain mononucleotide microsatellites in their coding sequences. This intriguing finding contrasts with the situation found in the major components of the DNA MMR system-MSH2 and MLH1-and, in fact, most human genes. Although eukaryotic genomes are rich in microsatellites, non-triplet microsatellites are rare in coding regions. The recurring presence of exonal mononucleotide repeat sequences within a single family of human genes would therefore be considered exceptional.

Chang, Dong Kyung↗

The evolution of transcriptional regulation in eukaryotes

Gene expression is central to the genotype-phenotype relationship in all organisms, and it is an important component of the genetic basis for evolutionary change in diverse aspects of phenotype. However, the evolution of transcriptional regulation remains understudied and poorly understood. Here we review the evolutionary dynamics of promoter, or cis-regulatory, sequences and the evolutionary mechanisms that shape them. Existing evidence indicates that populations harbor extensive genetic variation in promoter sequences, that a substantial fraction of this variation has consequences for both biochemical and organismal phenotype, and that some of this functional variation is sorted by selection. As with protein-coding sequences, rates and patterns of promoter sequence evolution differ considerably among loci and among clades for reasons that are not well understood. Studying the evolution of transcriptional regulation poses empirical and conceptual challenges beyond those typically encountered in analyses of coding sequence evolution: promoter organization is much less regular than that of coding sequences, and sequences required for the transcription of each locus reside at multiple other loci in the genome. Because of the strong context-dependence of transcriptional regulation, sequence inspection alone provides limited information about promoter function. Understanding the functional consequences of sequence differences among promoters generally requires biochemical and in vivo functional assays. Despite these challenges, important insights have already been gained into the evolution of transcriptional regulation, and the pace of discovery is accelerating.

Review, Academic↗