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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Investigating the human Calcineurin Interaction Network using the π$\phi$LxVP SLiM

Ser/thr phosphorylation is the primary reversible covalent modification of proteins in eukaryotes. As a consequence, it is the reciprocal actions of kinases and phosphatases that act as key molecular switches to fine tune cellular events. It has been well documented that ~400 human ser/thr kinases engage substrates via consensus phosphosite sequences. Strikingly, we know comparatively little about the mechanism by which ~40 human protein ser/thr phosphatases (PSPs) dephosphorylate ~15000 different substrates with high specificity. The identification of substrates of the essential PSP calcineurin (CN) has been exceptionally challenging and only a small fraction has been biochemically confirmed. It is now emerging that CN binds regulators and substrates via two short linear motifs (SLiMs), the well-studied PxIxIT SLiM and the LxVP SLiM, which remains controversial at the molecular level. Here we describe the crystal structure of CN in complex with its substrate NFATc1 and show that the LxVP SLiM is correctly defined as π$\phi$LxVP. Bioinformatics studies using the π$\phi$LxVP SLiM resulted in the identification of 567 potential CN substrates; a small subset was experimentally confirmed. This combined structural-bioinformatics approach provides a powerful method for dissecting the CN interaction network and for elucidating the role of CN in human health and disease.

Science & Technology - Other Topics↗
DOE OSTI2013

Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns

A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based on a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

Here, the complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique meta-graph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

An efficient algorithm for pairwise local alignment of protein interaction networks

Recently, researchers seeking to understand, modify, and create beneficial traits in organisms have looked for evolutionarily conserved patterns of protein interactions. Their conservation likely means that the proteins of these conserved functional modules are important to the trait's expression. In this paper, we formulate the problem of identifying these conserved patterns as a graph optimization problem, and develop a fast heuristic algorithm for this problem. We compare the performance of our network alignment algorithm to that of the MaWISh algorithm [Koyuturk M, Kim Y, Topkara U, Subramaniam S, Szpankowski W, Grama A, Pairwise alignment of protein interaction networks, J Comput Biol 13(2): 182-199, 2006.], which bases its search algorithm on a related decision problem formulation. We find that our algorithm discovers conserved modules with a larger number of proteins in an order of magnitude less time. In conclusion, the protein sets found by our algorithm correspond to known conserved functional modules at comparable precision and recall rates as those produced by the MaWISh algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Single Application of Compost Can Leave Lasting Impacts on Soil Microbial Community Structure and Alter Cross-Domain Interaction Networks

Our current understanding suggests that nutrient management strategies applied to agricultural soils over multiple years are required to cause major and stable shifts in soil microbial communities. However, some studies suggest that agricultural soils can benefit even from sporadic, single additions of organic matter. Here we investigate how single additions of high-quality organic matter can cause significant shifts in microbial soil communities over multiple cropping cycles. We grew radishes in a tropical Oxisol soil for six crop cycles after a single application of a high-nitrogen compost or urea. At planting and before biomass harvest, we sampled soils influenced by the radish rhizosphere and sequenced bacterial and archaeal 16S and fungal ITS rDNA marker genes. We measured microbial richness and diversity, community composition and structure, and constructed correlation networks to predict cross-domain microbial interactions. We found that a single application of compost, compared to urea or control, resulted in a persistent improved plant biomass response and led to sustained changes in the soil microbial community throughout the duration of the 227-day study. Compost altered the structure of both the fungal and prokaryotic microbial communities, introduced new microorganisms that persisted in the resident soil system, and altered soil microbial correlation network structure and hub taxa. In contrast, fertilization with urea did not significantly alter the structure of soil microbial communities compared to the control but reduced network complexity and altered hub taxa. This study highlights the significant impacts that high-quality organic matter fertilization can exert on agricultural soil microbiomes and adds to the growing body of knowledge on using organic fertilizers as a way to steer the soil microbiome toward a healthier soil.

Heisey, Steven↗
DOE OSTI2015

Towards a map of the Populus biomass protein-protein interaction network

Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of the fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in-depth characterizations. Characterizations involved both in vivo and in vitro independent methods to confirm protein-protein interactions and the evaluation of novel phenotypes resulting from creation of transgenic poplar and Arabidopsis plants engineered for increased or decreased expression of the selected genes. Transgenic poplar trees were studied in growth chamber, greenhouse, and two separate replicated field trials involving over 25 distinct wood-associated proteins. In-depth characterizations yielding positive results include the following. First, a NAC domain transcription factor (NAC154) that is a promoter of stress response and dormancy in trees was discovered. Increasing expression of NAC154 caused stunted growth and premature senescence, while decreasing expression led to both delayed bud and leaf expansion in spring and delayed leaf drop (i.e., prolonged leaf retention) in fall. Second, we discovered and characterized a new connection between a negative regulator of wood formation, the NAC domain transcription factor XND1, and an important regulator of cell division and cell differentiation, RBR. Third, we identified a new network of interacting wood-associated transcription factors belonging to the MYB and HD families. One of the HD family proteins, WOX13, was used to prepare transgenic poplar for high-level expression, resulting in significantly increased lateral branch growth. Finally, we modeled and performed in vitro analyses of the insect protein rubber resilin and we prepared transgenic Arabidopsis plants for expression of resilin to test the feasibility of using resilin to modify lignin cross-linking in wood and reduce recalcitrance and improve yield of fermentable sugars for biofuels production. Analysis of these and additional transgenics created with this support is continuing.

09 BIOMASS FUELS↗
DOE OSTI2024

Protein–Protein Interaction Networks Derived from Classical and Machine Learning-Based Natural Language Processing Tools

The study of protein-protein interactions (PPIs) provides insight into various biological mechanisms, including the binding of antibodies to antigens, enzymes to inhibitors or promoters, and receptors to ligands. Recent studies of PPIs have led to significant biological breakthroughs. For example, the study of PPIs involved in the human:SARS-CoV-2 viral infection mechanism aided in the development of the SARS-CoV-2 vaccines. Though several databases exist for the manual curation of PPI networks, text mining methods have been routinely demonstrated as useful alternatives for newly studied or understudied species where databases are incomplete. Here, the relationship extraction (RE) performance of several open-source classical text processing, machine learning (ML)-based natural language processing (NLP), and large language model (LLM)-based NLP tools were compared. Overall, our results indicated that networks derived from classical methods tend to have high true positive rates at the expense of having overconnected-networks, ML-based NLP methods have lower true positive rates but networks with the closest structures to the target network, and LLM-based NLP methods tend to exist in-between the two other approaches, with variable performances. Finally, the selection of a specific NLP approach should be tied to the needs of a study and text availability, as models varied in performance due to the amount of text provided.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A reversible Renilla luciferase protein complementation assay for rapid identification of protein-protein interactions reveals the existence of an interaction network involved in xyloglucan biosynthesis in the plant Golgi apparatus

A growing body of evidence suggests that protein–protein interactions (PPIs) occur amongst glycosyltransferases (GTs) required for plant glycan biosynthesis (e.g. cell wall polysaccharides and N-glycans) in the Golgi apparatus, and may control the functions of these enzymes. However, identification of PPIs in the endomembrane system in a relatively fast and simple fashion is technically challenging, hampering the progress in understanding the functional coordination of the enzymes in Golgi glycan biosynthesis. To solve the challenges, we adapted and streamlined a reversible Renilla luciferase protein complementation assay (Rluc-PCA), originally reported for use in human cells, for transient expression in Nicotiana benthamiana. We tested Rluc-PCA and successfully identified luminescence complementation amongst Golgi-localizing GTs known to form a heterodimer (GAUT1 and GAUT7) and those which homooligomerize (ARAD1). In contrast, no interaction was shown between negative controls (e.g. GAUT7, ARAD1, IRX9). Rluc-PCA was used to investigate PPIs amongst Golgi-localizing GTs involved in biosynthesis of hemicelluloses. Although no PPI was identified among six GTs involved in xylan biosynthesis, Rluc-PCA confirmed three previously proposed interactions and identified seven novel PPIs amongst GTs involved in xyloglucan biosynthesis. Notably, three of the novel PPIs were confirmed by a yeast-based split-ubiquitin assay. Finally, Gateway-enabled expression vectors were generated, allowing rapid construction of fusion proteins to the Rluc reporters and epitope tags. In conclusion, our results show that Rluc-PCA coupled with transient expression in N. benthamiana is a fast and versatile method suitable for analysis of PPIs between Golgi resident proteins in an easy and mid-throughput fashion in planta.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Isolation of three B-box zinc finger proteins that interact with STF1 and COP1 defines a HY5/COP1 interaction network involved in light control of development in soybean

LONG HYPOCOTYL5 (HY5) and STF1 (Soybean TGACG-motif binding Factor 1) are two related bZIP transcription factors that play a positive role in photomorphogenesis and hormonal signaling. In this study, we compared full length STF1 and truncated STF1 overexpression lines and found that the C-terminal 133 amino acids (194–306) possess all the HY5-like function in Arabidopsis. The STF1-DC1 mutant (1–306), with a 20 amino acid deletion at the carboxy terminus, failed to complement the hy5 mutant phenotype, which suggests an intact C-terminus is required for STF1 function. To understand the role of the C-terminal domain in photomorphogenesis we used a yeast two-hybrid screen to isolate proteins that bind to the STF1 C-terminus. We isolated three soybean cDNAs encoding the zinc-finger proteins GmSTO, GmSTH, and GmSTH2, which interact with STF1. These proteins belong to a family of B-box zinc finger proteins that include Arabidopsis SALT TOLERANCE (STO) and STO HOMOLOG (STH) and STH2, which play a role in light-dependent development and gene expression. The C-terminal 63 amino acids of STF1, containing a leucine zipper and the two N-terminal B-boxes, contains the domain involved in interactions between STF1 and GmSTO. In addition, we identified an interaction between soybean COP1 (GmCOP1) and GmSTO and GmSTH, as well as STF1, which strongly suggests the presence of a similar regulatory circuit for light signaling in soybean as in Arabidopsis. This study shows that photomorphogenic control requires complex molecular interactions among several different classes of transcription factors such as bZIP, B-box factors, and COP1, a ubiquitin ligase. - Highlights: • STF1 interact with GmSTO, GmSTH and GmSTH2. • The bZIP transcription factor STF1 requires an intact C-terminal domain for STF1 function. • STF1 and GmSTO are nuclear proteins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Incorporating seed fate into plant–frugivore networks increases interaction diversity across plant regeneration stages

Plant–animal mutualistic interactions, such as pollination and seed dispersal, affect ecosystem functioning by driving plant population dynamics. However, little is known of how the diversity of interactions in these mutualistic networks determines plant regeneration dynamics. To fill this gap, interaction networks should not only account for the number of seeds dispersed by animals, but also for seed fate after dispersal. Here, we compare plant–animal networks at both the seed dispersal and seedling recruitment stage to evaluate how interaction diversity, represented by different network metrics, changes throughout the process of plant regeneration. We focused on a system with six species of frugivorous birds and three species of fleshy‐fruited trees in the temperate secondary forest of the Cantabrian Range (northern Iberian Peninsula). We considered two plant cohorts corresponding to two fruiting years showing strong differences in fruit and frugivore abundance. Seed dispersal interactions were estimated from a spatially‐explicit, field‐validated model predicting tree and bird species‐specific seed deposition in different microhabitats. These interactions were further transformed into interactions at the seedling recruitment stage by accounting for plant‐ and microhabitat‐specific seed fates estimated from field sampling. We found that network interaction diversity varied across plant regeneration stages and cohorts, both in terms of the evenness and the number of paired interactions. Tree–bird interactions were more evenly distributed across species pairs at the recruitment stage than at the seed deposition stage, although some interactions disappeared in the seed‐to‐seedling transition for one plant cohort. The variations in interaction diversity were explained by between‐plant differences in post‐dispersal seed fate and in inter‐annual fruit production, rather than by differences between frugivores in seed deposition patterns. These results highlight the need for integrating plant traits and disperser quality to predict the functional outcome of plant–animal mutualistic networks.

Donoso, Isabel↗
DOE OSTI2020

NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families

Comparative network analysis provides effective computational means for gaining novel insights into the structural and functional compositions of biological networks. In recent years, various methods have been developed for biological network alignment, whose main goal is to identify important similarities and critical differences between networks in terms of their topology and composition. A major impediment to advancing network alignment techniques has been the lack of gold-standard benchmarks that can be used for accurate and comprehensive performance assessment of such algorithms. The original NAPAbench (network alignment performance assessment benchmark) was developed to address this problem, and it has been widely utilized by many researchers for the development, evaluation, and comparison of novel network alignment techniques. In this work, we introduce NAPAbench 2—a major update of the original NAPAbench that was introduced in 2012. NAPAbench 2 includes a completely redesigned network synthesis algorithm that can generate protein-protein interaction (PPI) network families whose characteristics closely match those of the latest real PPI networks. Furthermore, the network synthesis algorithm comes with an intuitive GUI that allows users to easily generate PPI network families with an arbitrary number of networks of any size, according to a flexible user-defined phylogeny. In addition, NAPAbench 2 provides updated benchmark datasets—created using the redesigned network synthesis algorithm—which can be used for comprehensive performance assessment of network alignment algorithms and their scalability.

42 ENGINEERING↗