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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Deep representation learning improves prediction of LacI-mediated transcriptional repression

Significance The understanding of protein function increases with new experimental and evolutionary datasets. A major challenge is to apply machine learning to these datasets to capture essential features of protein function. Here, we analyze the experimentally determined repression function for tens of thousands of mutants of the LacI protein. This study provides a continuous, noncategorical repression value across a majority of all single mutations and for thousands of higher-order mutations. To develop a top-performing model for the prediction of repression by LacI, we compare several leading variant effect prediction algorithms. A deep representation learning paradigm, first trained across millions of proteins from all known protein families and then fine-tuned using LacI experimental data, offers the highest predictive performance of repression function.

42 ENGINEERING↗
DOE OSTI2024

Multiple horizontal gene transfer events have shaped plant glycosyl hydrolase diversity and function

Plant glycosyl hydrolases (GHs) play a crucial role in selectively breaking down carbohydrates and glycoconjugates during various cellular processes, such as reserve mobilization, pathogen defense, and modification/disassembly of the cell wall. In this study, we examined the distribution of GH genes in the Archaeplastida supergroup, which encompasses red algae, glaucophytes, and green plants. We identified that the GH repertoire expanded from a few tens of genes in early archaeplastidians to over 400 genes in modern angiosperms, spanning 40 GH families in land plants. Our findings reveal that major evolutionary transitions were accompanied by significant changes in the GH repertoire. Specifically, we identified at least 23 GH families acquired by green plants through multiple horizontal gene transfer events, primarily from bacteria and fungi. We found a significant shift in the subcellular localization of GH activity during green plant evolution, with a marked increase in extracellular-targeted GH proteins associated with the diversification of plant cell wall polysaccharides and defense mechanisms against pathogens. In conclusion, our study sheds light on the macroevolutionary processes that have shaped the GH repertoire in plants, highlighting the acquisition of GH families through horizontal transfer and the role of GHs in plant adaptation and defense mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Heterologous expression of Arabidopsis laccase2, laccase4 and peroxidase52 driven under developing xylem specific promoter DX15 improves saccharification in populus

Secondary cell wall holds considerable potential as it has gained immense momentum to replace the lignocellulosic feedstock into fuels. Lignin one of the components of secondary cell wall tightly holds the polysaccharides thereby enhancing the recalcitrance and complexity in the biomass. Laccases (LAC) and peroxidases (PRX) are the major phenyl-oxidases playing key functions during the polymerization of monolignols into lignin. Yet, the functions of laccase and peroxidases gene families remained largely unknown. Hence, the objective of this conducted study is to understand the role of specific LAC and PRX in Populus wood formation and to further investigate how the altered Lac and Prx expression affects biomass recalcitrance and plant growth. This study of heterologous expression of Arabidopsis Lac and Prx genes was conducted in poplar to avoid any otherwise occurring co-suppression mechanism during the homologous overexpression of highly expressed native genes. In the pursuit of optimizing lignocellulosic biomass for biofuel production, the present study focuses on harnessing the enzymatic potential of Arabidopsis thaliana Laccase2, Laccase4, and Peroxidase52 through heterologous expression. We overexpressed selected Arabidopsis laccase2 (AtLac2), laccase4 (AtLac4), and peroxidase52 (AtPrx52) genes, based on their high transcript expression respective to the differentiating xylem tissues in the stem, in hybrid poplar (cv. 717) expressed under the developing xylem tissue-specific promoter, DX15 characterized the transgenic populus for the investigation of growth phenotypes and recalcitrance efficiency. Bioinformatics analyses conducted on AtLac2 and AtLac4 and AtPrx52, revealed the evolutionary relationship between the laccase gene and peroxidase gene homologs, respectively. Transgenic poplar plant lines overexpressing the AtLac2 gene (AtLac2-OE) showed an increase in plant height without a change in biomass yield as compared to the controls; whereas AtLac4-OE and AtPrx52-OE transgenic lines did not show any such observable growth phenotypes compared to their respective controls. The changes in the levels of lignin content and S/G ratios in the transgenic poplar resulted in a significant increase in the saccharification efficiency as compared to the control plants. Overall, saccharification efficiency was increased by 35–50%, 21–42%, and 8–39% in AtLac2-OE, AtLac4-OE, and AtPrx52-OE transgenic poplar lines, respectively, as compared to their controls. Moreover, the bioengineered plants maintained normal growth and development, underscoring the feasibility of this approach for biomass improvement without compromising overall plant fitness. This study also sheds light on the potential of exploiting regulatory elements of DX15 to drive targeted expression of lignin-modifying enzymes, thereby providing a promising avenue for tailoring biomass for improved biofuel production. These findings contribute to the growing body of knowledge in synthetic biology and plant biotechnology, offering a sustainable solution to address the challenges associated with lignocellulosic biomass recalcitrance.

09 BIOMASS FUELS↗
DOE OSTI2021

Molecular phylogenetic analysis of the Paguristes tortugae Schmitt, 1933 complex and selected other Paguroidea (Crustacea: Decapoda: Anomura)

Morphological characters, as presently applied to describe members of the Paguristes tortugae Schmitt, 1933 species complex, appear to be of limited value in inferring phylogenetic relationships within the genus, and may have similarly misinformed understanding of relationships between members of this complex and those presently assigned to the related genera Areopaguristes Rahayu & McLaughlin, 2010 and Pseudopaguristes McLaughlin, 2002. Previously undocumented observations of similarities and differences in color patterns among populations additionally suggest genetic divergences within some species, or alternatively seem to support phylogenetic groupings of some species. In the present study, a Maximum Likelihood (ML) phylogenetic analysis was undertaken based on the H3, 12S mtDNA, and 16S mtDNA sequences of 148 individuals, primarily representatives of paguroid species from the western Atlantic. This molecular analysis supported a polyphyletic Diogenidae Ortmann, 1892, although incomplete taxonomic sampling among the genera of Diogenidae limits the utility of this finding for resolving family level relationships. Several hypotheses regarding the evolutionary relationships among hermit crab genera were refuted by the Kishino-Hasegawa (KH). ShimodairaHasegawa (SH) and Approximately Unbiased (AU) tree topology tests, among them the hypothesis that Areopaguristes is monophyletic. A lack of support for the monophyly of Areopaguristes calls into question the phylogenetic validity of gill number for the differentiation of Paguristes, Areopaguristes, and Pseudopaguristes. The study was inconclusive with regard to the relationships among these three genera, but previously unknown diversity within both Paguristes and Areopaguristes was demonstrated. Existence of an undescribed species confounded under the name Paguristes tortugae Schmitt, 1933 was supported by genetics, morphology, and coloration. A second undescribed species with remarkable similarity to Areopaguristes hummi Wass, 1955 was discovered based on genetics and coloration.

12S↗
DOE OSTI2020

The Plant Microbiome: From Ecology to Reductionism and Beyond

Methodological advances over the past two decades have propelled plant microbiome research, allowing the field to comprehensively test ideas proposed over a century ago and generate many new hypotheses. Studying the distribution of microbial taxa and genes across plant habitats has revealed the importance of various ecological and evolutionary forces shaping plant microbiota. In particular, selection imposed by plant habitats strongly shapes the diversity and composition of microbiota and leads to microbial adaptation associated with navigating the plant immune system and utilizing plant-derived resources. Reductionist approaches have demonstrated that the interaction between plant immunity and the plant microbiome is, in fact, bidirectional and that plants, microbiota, and the environment shape a complex chemical dialogue that collectively orchestrates the plantmicrobiome. Finally, the next stage in plant microbiome research will require the integration of ecological and reductionist approaches to establish a general understanding of the assembly and function in both natural and managed environments.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Orthologs, paralogs and genome comparisons

During the past decade, ancient gene duplications were recognized as one of the main forces in the generation of diverse gene families and the creation of new functional capabilities. New tools developed to search data banks for homologous sequences, and an increased availability of reliable three-dimensional structural information led to the recognition that proteins with diverse functions can belong to the same superfamily. Analyses of the evolution of these superfamilies promises to provide insights into early evolution but are complicated by several important evolutionary processes. Horizontal transfer of genes can lead to a vertical spread of innovations among organisms, therefore finding a certain property in some descendants of an ancestor does not guarantee that it was present in that ancestor. Complete or partial gene conversion between duplicated genes can yield phylogenetic trees with several, apparently independent gene duplications, suggesting an often surprising parallelism in the evolution of independent lineages. Additionally, the breakup of domains within a protein and the fusion of domains into multifunctional proteins makes the delineation of superfamilies a task that remains difficult to automate.

Non-NASA Center↗
DOE OSTI2020

Common origin of ornithine–urea cycle in opisthokonts and stramenopiles

Eukaryotic complex phototrophs exhibit a colorful evolutionary history. At least three independent endosymbiotic events accompanied by the gene transfer from the endosymbiont to host assembled a complex genomic mosaic. Resulting patchwork may give rise to unique metabolic capabilities; on the other hand, it can also blur the reconstruction of phylogenetic relationships. The ornithine–urea cycle (OUC) belongs to the cornerstone of the metabolism of metazoans and, as found recently, also photosynthetic stramenopiles. We have analyzed the distribution and phylogenetic positions of genes encoding enzymes of the urea synthesis pathway in eukaryotes. We show here that metazoan and stramenopile OUC enzymes share common origins and that enzymes of the OUC found in primary algae (including plants) display different origins. The impact of this fact on the evolution of stramenopiles is discussed here.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional–structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional–structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

From wolves to humans: oral microbiome resistance to transfer across mammalian hosts

The mammalian mouth is colonized by complex microbial communities, adapted to specific niches, and in homeostasis with the host. Individual microbes interact metabolically and rely primarily on nutrients provided by the host, with which they have potentially co-evolved along the mammalian lineages. The oral environment is similar across mammals, but the diversity, specificity, and evolution of community structure in related or interacting mammals are little understood. Here, we compared the oral microbiomes of dogs with those of wild wolves and humans. In dogs, we found an increased microbial diversity relative to wolves, possibly related to the transition to omnivorous nutrition following domestication. This includes a larger diversity of Patescibacteria than previously reported in any other oral microbiota. The oral microbes are most distinct at bacterial species or strain levels, with few if any shared between humans and canids, while the close evolutionary relationship between wolves and dogs is reflected by numerous shared taxa. More taxa are shared at higher taxonomic levels including with humans, supporting their more ancestral common mammalian colonization followed by diversification. Phylogenies of selected oral bacterial lineages do not support stable human-dog microbial transfers but suggest diversification along mammalian lineages (apes and canids). Therefore, despite millennia of cohabitation and close interaction, the host and its native community controls and limits the assimilation of new microbes, even if closely related. Higher resolution metagenomic and microbial physiological studies, covering a larger mammalian diversity, should help understand how oral communities assemble, adapt, and interact with their hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Impacts of directed evolution and soil management legacy on the maize rhizobiome

Domestication and agricultural intensification dramatically altered maize and its cultivation environment. Changes in maize genetics (G) and environmental (E) conditions increased productivity under high-synthetic-input conditions. However, novel selective pressures on the rhizobiome may have incurred undesirable tradeoffs in organic agroecosystems, where plants obtain nutrients via microbially mediated processes including mineralization of organic matter. Using twelve maize genotypes representing an evolutionary transect (teosintes, landraces, inbred parents of modern elite germplasm, and modern hybrids) and two agricultural soils with contrasting long-term management, here we integrated analyses of rhizobiome community structure, potential microbe-microbe interactions, and N-cycling functional genes to better understand the impacts of maize evolution and soil management legacy on rhizobiome recruitment. We show complex shifts in rhizobiome communities during directed evolution of maize (defined as the transition from teosinte to modern hybrids), with a larger effect of domestication (teosinte to landraces) than modern breeding (inbreds to hybrids) on rhizobiome structure and greater impacts of modern breeding on potential microbe-microbe interactions. Rhizobiome structure was significantly correlated with plant nutrient composition. Furthermore, plant biomass and nutrient content were affected by G x E interactions in which teosinte and landrace genotypes had better relative performance in the organic legacy soil than inbred and modern genotypes. The abundance of six N-cycling genes of relevance for plant nutrition and N loss pathways did not significantly differ between teosinte and modern rhizospheres in either soil management legacy. These results provide insight into the potential for improving maize adaptation to organic systems and contribute to interdisciplinary efforts toward developing resource-efficient, biologically based agroecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗
DOE OSTI2020

Rapid adaptation (or not) in restored plant populations

Abstract Mismatches between the traits of a colonizing population and a novel habitat can generate strong selection, potentially resulting in rapid adaptation. However, for most colonization events, it can be difficult to detect rapid adaptation or distinguish it from nonadaptive evolutionary changes. Here, I take advantage of a replicated prairie restoration experiment to compare recently established plant populations in two closely located restored prairies to each other and to their shared source population to test for rapid adaptation. Using a reciprocal transplant experiment six years after the populations were established, I found that one restored plant population showed evidence of adaptation, outperforming the other restored population when grown at its home site. In contrast, I detected no evidence for adaptation at the other site. These findings demonstrate that while rapid adaptation can occur in colonizing plant populations, it may not be the rule. Better understanding of when adaptation may or may not occur in these contexts may help us use evolution to our advantage, potentially improving establishment of desirable species in restored habitats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Comparative genomic and phenotypic characterization of invasive non-typhoidal Salmonella isolates from Siaya, Kenya

Non-typhoidal Salmonella (NTS) is a major global health concern that often causes bloodstream infections in areas of the world affected by malnutrition and comorbidities such as HIV and malaria. Developing a strategy to control the emergence and spread of highly invasive and antimicrobial resistant NTS isolates requires a comprehensive analysis of epidemiological factors and molecular pathogenesis. Here, we characterize 11 NTS isolates that caused bloodstream infections in pediatric patients in Siaya, Kenya from 2003–2010. Nine isolates were identified as S . Typhimurium sequence type 313 while the other two were S . Enteritidis. Comprehensive genotypic and phenotypic analyses were performed to compare these isolates to those previously identified in sub-Saharan Africa. We identified a S . Typhimurium isolate referred to as UGA14 that displayed novel plasmid, pseudogene and resistance features as compared to other isolates reported from Africa. Notably, UGA14 is able to ferment both lactose and sucrose due to the acquisition of insertion elements on the pKST313 plasmid. These findings show for the first time the co-evolution of plasmid-mediated lactose and sucrose metabolism along with cephalosporin resistance in NTS further elucidating the evolutionary mechanisms of invasive NTS phenotypes. These results further support the use of combined genomic and phenotypic approaches to detect and characterize atypical NTS isolates in order to advance biosurveillance efforts that inform countermeasures aimed at controlling invasive and antimicrobial resistant NTS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Generative $β$-hairpin design using a residue-based physicochemical property landscape

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the -hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial -hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Evolutionary flexibility and rigidity in the bacterial methylerythritol phosphate (MEP) pathway

Terpenoids are a diverse class of compounds with wide-ranging uses including as industrial solvents, pharmaceuticals, and fragrances. Efforts to produce terpenoids sustainably by engineering microbes for fermentation are ongoing, but industrial production still largely relies on nonrenewable sources. The methylerythritol phosphate (MEP) pathway generates terpenoid precursor molecules and includes the enzyme Dxs and two iron–sulfur cluster enzymes: IspG and IspH. IspG and IspH are rate limiting-enzymes of the MEP pathway but are challenging for metabolic engineering because they require iron–sulfur cluster biogenesis and an ongoing supply of reducing equivalents to function. Therefore, identifying novel alternatives to IspG and IspH has been an on-going effort to aid in metabolic engineering of terpenoid biosynthesis. We report here an analysis of the evolutionary diversity of terpenoid biosynthesis strategies as a resource for exploration of alternative terpenoid biosynthesis pathways. Using comparative genomics, we surveyed a database of 4,400 diverse bacterial species and found that some may have evolved alternatives to the first enzyme in the pathway, Dxs making it evolutionarily flexible. In contrast, we found that IspG and IspH are evolutionarily rigid because we could not identify any species that appear to have enzymatic routes that circumvent these enzymes. The ever-growing repository of sequenced bacterial genomes has great potential to provide metabolic engineers with alternative metabolic pathway solutions. With the current state of knowledge, we found that enzymes IspG and IspH are evolutionarily indispensable which informs both metabolic engineering efforts and our understanding of the evolution of terpenoid biosynthesis pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence–function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ~400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Artificial Intelligence Transforming Post-Translational Modification Research

Post-Translational Modifications (PTMs) are covalent changes to amino acids that occur after protein synthesis, including covalent modifications on side chains and peptide backbones. Many PTMs profoundly impact cellular and molecular functions and structures, and their significance extends to evolutionary studies as well. In light of these implications, we have explored how artificial intelligence (AI) can be utilized in researching PTMs. Initially, rationales for adopting AI and its advantages in understanding the functions of PTMs are discussed. Then, various deep learning architectures and programs, including recent applications of language models, for predicting PTM sites on proteins and the regulatory functions of these PTMs are compared. Finally, our high-throughput PTM-data-generation pipeline, which formats data suitably for AI training and predictions is described. We hope this review illuminates areas where future AI models on PTMs can be improved, thereby contributing to the field of PTM bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genome-scale phylogeny and comparative genomics of the fungal order Sordariales

The order Sordariales is taxonomically diverse, and harbours many species with different lifestyles and large economic importance. Despite its importance, a robust genome-scale phylogeny, and associated comparative genomic analysis of the order is lacking. In this study, we examined whole-genome data from 99 Sordariales, including 52 newly sequenced genomes, and seven outgroup taxa. We inferred a comprehensive phylogeny that resolved several contentious relationships amongst families in the order, and cleared-up intrafamily relationships within the Podosporaceae. Extensive comparative genomics showed that genomes from the three largest families in the dataset (Chaetomiaceae, Podosporaceae and Sordariaceae) differ greatly in GC content, genome size, gene number, repeat percentage, evolutionary rate, and genome content affected by repeat-induced point mutations (RIP). All genomic traits showed phylogenetic signal, and ancestral state reconstruction revealed that the variation of the properties stems primarily from within-family evolution. Together, the results provide a thorough framework for understanding genome evolution in this important group of fungi.

59 BASIC BIOLOGICAL SCIENCES↗