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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Birth of protein folds and functions in the virome

The rapid evolution of viruses generates proteins that are essential for infectivity and replication but with unknown functions, due to extreme sequence divergence. Here, using a database of 67,715 newly predicted protein structures from 4,463 eukaryotic viral species, we found that 62% of viral proteins are structurally distinct and lack homologues in the AlphaFold database. Among the remaining 38% of viral proteins, many have non-viral structural analogues that revealed surprising similarities between human pathogens and their eukaryotic hosts. Structural comparisons suggested putative functions for up to 25% of unannotated viral proteins, including those with roles in the evasion of innate immunity. In particular, RNA ligase T-like phosphodiesterases were found to resemble phage-encoded proteins that hydrolyse the host immune-activating cyclic dinucleotides 3',3'- and 2',3'-cyclic GMP-AMP (cGAMP). Experimental analysis showed that RNA ligase T homologues encoded by avian poxviruses similarly hydrolyse cGAMP, showing that RNA ligase T-mediated targeting of cGAMP is an evolutionarily conserved mechanism of immune evasion that is present in both bacteriophage and eukaryotic viruses. Together, the viral protein structural database and analyses presented here afford new opportunities to identify mechanisms of virus–host interactions that are common across the virome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions

The clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity. A software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed, we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from Burkholderia xenovorans , a TR of unknown function and predicted that this TR was related to the glycine, threonine and serine degradation. We tested the binding of metabolites in these pathways and for those that bound, their ability to modulate TR binding to its specific DNA operator sequence. Using rtPCR, we confirmed that methylglyoxal was an effector of Bxe_3018.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify coding regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

MbnH is a diheme MauG-like protein associated with microbial copper homeostasis

Methanobactins (Mbns) are ribosomally-produced, post-translationally modified peptidic copper-binding natural products produced under conditions of copper limitation. Genes encoding Mbn biosynthetic and transport proteins have been identified in a wide variety of bacteria, indicating a broader role for Mbns in bacterial metal homeostasis. Many of the genes in the Mbn operons have been assigned functions, but two genes usually present, mbnP and mbnH, encode uncharacterized proteins predicted to reside in the periplasm. MbnH belongs to the bacterial diheme cytochrome c peroxidase (bCcP)/MauG protein family, and MbnP contains no domains of known function. Here, we performed a detailed bioinformatic analysis of both proteins and have biochemically characterized MbnH from Methylosinus (Ms.) trichosporium OB3b. We note that the mbnH and mbnP genes typically co-occur and are located proximal to genes associated with microbial copper homeostasis. Our bioinformatics analysis also revealed that the bCcP/MauG family is significantly more diverse than originally appreciated, and that MbnH is most closely related to the MauG subfamily. A 2.6 Å resolution structure of Ms. trichosporium OB3b MbnH combined with spectroscopic data and peroxidase activity assays provided evidence that MbnH indeed more closely resembles MauG than bCcPs, although its redox properties are significantly different from those of MauG. The overall similarity of MbnH to MauG suggests that MbnH could post-translationally modify a macromolecule, such as internalized CuMbn or its uncharacterized partner protein, MbnP. Our results indicate that MbnH is a MauG-like diheme protein that is likely involved in microbial copper homeostasis and represents a new family within the bCcP/MauG superfamily.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO)

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Use of Modern Chemical Protein Synthesis and Advanced Fluorescent Assay Techniques to Experimentally Validate the Functional Annotation of Microbial Genomes

The objective of this research program was to prototype methods for the chemical synthesis of predicted protein molecules in annotated microbial genomes. High throughput chemical methods were to be used to make large numbers of predicted proteins and protein domains, based on microbial genome sequences. Microscale chemical synthesis methods for the parallel preparation of peptide-thioester building blocks were developed; these peptide segments are used for the parallel chemical synthesis of proteins and protein domains. Ultimately, it is envisaged that these synthetic molecules would be ‘printed’ in spatially addressable arrays. The unique ability of total synthesis to precision label protein molecules with dyes and with chemical or biochemical ‘tags’ can be used to facilitate novel assay technologies adapted from state-of-the art single molecule fluorescence detection techniques. In the future, in conjunction with modern laboratory automation this integrated set of techniques will enable high throughput experimental validation of the functional annotation of microbial genomes.

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

Structural basis of the amidase ClbL central to the biosynthesis of the genotoxin colibactin

Colibactin is a genotoxic natural product produced by select commensal bacteria in the human gut microbiota. The compound is a bis-electrophile that is predicted to form interstrand DNA cross-links in target cells, leading to double-strand DNA breaks. The biosynthesis of colibactin is carried out by a mixed NRPS–PKS assembly line with several noncanonical features. An amidase, ClbL, plays a key role in the pathway, catalyzing the final step in the formation of the pseudodimeric scaffold. ClbL couples α-aminoketone and β-ketothioester intermediates attached to separate carrier domains on the NRPS–PKS assembly. Here, the 1.9 Å resolution structure of ClbL is reported, providing a structural basis for this key step in the colibactin biosynthetic pathway. The structure reveals an open hydrophobic active site surrounded by flexible loops, and comparison with homologous amidases supports its unusual function and predicts macromolecular interactions with pathway carrier-protein substrates. Modeling protein–protein interactions supports a predicted molecular basis for enzyme–carrier domain interactions. Overall, the work provides structural insight into this unique enzyme that is central to the biosynthesis of colibactin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Functional Classification of Immune Regulatory Proteins

Members of the immunoglobulin superfamily (IgSF) control innate and adaptive immunity and are prime targets for the treatment of autoimmune diseases, infectious diseases, and malignancies. We describe a computational method, termed the Brotherhood algorithm, which utilizes intermediate sequence information to classify proteins into functionally related families. This approach identifies functional relationships within the IgSF and predicts additional receptor-ligand interactions. As a specific example, we examine the nectin/nectin-like family of cell adhesion and signaling proteins and propose receptor-ligand interactions within this family. We were guided by the Brotherhood approach and present the high-resolution structural characterization of a homophilic interaction involving the class-I MHC-restricted T-cell-associated molecule, which we now classify as a nectin-like family member. The Brotherhood algorithm is likely to have a significant impact on structural immunology by identifying those proteins and complexes for which structural characterization will be particularly informative.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Crystal structure of the toxin Msmeg_6760, the structural homolog of Mycobacterium tuberculosis Rv2035, a novel type II toxin involved in the hypoxic response

The structure of Msmeg_6760, a protein of unknown function, has been determined. Biochemical and bioinformatics analyses determined that Msmeg_6760 interacts with a protein encoded in the same operon, Msmeg_6762, and predicted that the operon is a toxin–antitoxin (TA) system. Structural comparison of Msmeg_6760 with proteins of known function suggests that Msmeg_6760 binds a hydrophobic ligand in a buried cavity lined by large hydrophobic residues. Access to this cavity could be controlled by a gate–latch mechanism. The function of the Msmeg_6760 toxin is unknown, but structure-based predictions revealed that Msmeg_6760 and Msmeg_6762 are homologous to Rv2034 and Rv2035, a predicted novel TA system involved in Mycobacterium tuberculosis latency during macrophage infection. The Msmeg_6760 toxin fold has not been previously described for bacterial toxins and its unique structural features suggest that toxin activation is likely to be mediated by a novel mechanism.

Bajaj, R. Alexandra↗
NASA NTRSDate not supplied

Maize Rough Endosperm6 (rgh6) Encodes A Predicted Dead-Box RNA Helicase and Affects Mirna Processing in Endosperm Development

Maize rough endosperm (rgh) mutants have defective kernels with a rough, etched, or pitted endosperm surface. Molecular genetic analysis of this mutant class has identified multiple RNA processing proteins critical to endosperm development. Here, we report on the developmental and molecular function of the rgh6 locus. The rgh6 mutant was isolated from the UniformMu transposon tagging population. Mutant kernels have reduced endosperm size and defective embryos that develop in a more apical position than typical for defective embryos. TB translocation crosses revealed that rgh6 mutant endosperm inhibits normal embryo development. Positional cloning of the rgh6 locus found that it encodes a predicted DEAD-box RNA helicase. Consistent with a predicted function for RNA processing, transient expression of a RGH6-GFP fusion protein is localized to nucleolus and nuclear speckles in Nicotiana benthamiana leaves. Rgh6 transcripts are highly expressed in endosperm epidermal cell types such as the aleurone, basal endosperm cell layer, embryo surrounding region, and endosperm adjacent to scutellum. Markers of these cell types show increased levels in rgh6 mutant kernels. Mutant endosperm tissues have increased precursor microRNA (pre-miRNA) and decreased mature miRNA relative to normal sibling endosperm, indicating that rgh6 is required for miRNA processing. The transcript levels for most miRNA target genes accumulate to a higher level in rgh6 mutant tissue. These results suggest that miRNA processing and regulation of miRNA target genes are required for normal endosperm development.

Plant Sciences↗
DOE OSTI2021

Proteins associated with the Arabidopsis thaliana plastid rhomboid-like protein RBL10

Rhomboid-like proteins are intramembrane proteases with a variety of regulatory roles in cells. Though many rhomboid-like proteins are predicted in plants, their detailed molecular mechanisms or cellular functions are not yet known. Of the 13 predicted rhomboids in Arabidopsis thaliana, one, RBL10, affects lipid metabolism in the chloroplast, because in the respective rbl10 mutant the transfer of phosphatidic acid through the inner envelope membrane is disrupted. Here we show that RBL10 is part of a high-molecular-weight complex of 250 kDa or greater in size. Nine likely components of this complex are identified by two independent methods and include Acyl Carrier Protein 4 (ACP4) and Carboxyltransferase Interactor1 (CTI1), which have known roles in chloroplast lipid metabolism. The acp4 mutant has decreased C16:3 fatty acid content of monogalactosyldiacylglycerol, similar to the rbl10 mutant, prompting us to offer a mechanistic model of how an interaction between ACP4 and RBL10 might affect chloroplast lipid assembly. We also demonstrate the presence of a seventh transmembrane domain in RBL10, refining the currently accepted topology of this protein. Taken together, the identity of possible RBL10 complex components as well as insights into RBL10 topology and distribution in the membrane provide a stepping-stone towards a deeper understanding of RBL10 function in Arabidopsis lipid metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

molecular replacement↗
DOE OSTI2025

Energy metric prediction for double insertion mutants via the RoseNet deep learning framework

Studying the structural and functional implications of protein mutations is an important task in computational biology and bioinformatics. We leverage our previously proposed RoseNet neural network architecture to predict energy metrics of proteins with double amino acid insertions or deletions (InDels). We train models on previously generated benchmark datasets containing the exhaustive double InDel mutations for three proteins, as well as an additional three proteins for which ∼145k random mutants, each with two InDels, have been generated. We expand on our previous work by evaluating three additional proteins and analyzing domain features that impact the prediction capabilities of RoseNet. These features include InDels into secondary structures and the solvent accessible surface area (SASA) scores of the residues. We uncover further evidence to support that RoseNet has a higher proficiency of generalizing to unseen residue combinations than unseen insertion positions. We also observe that RoseNet produces higher-quality predictions when inserting into a β-sheet over an α-helix. Additionally, when the insertions fall in an area of high SASA, RoseNet often displays better performance than inserting into areas of low SASA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A taxonomy of bacterial microcompartment loci constructed by a novel scoring method

Bacterial microcompartments (BMCs) are proteinaceous organelles involved in both autotrophic and heterotrophic metabolism. All BMCs share homologous shell proteins but differ in their complement of enzymes; these are typically encoded adjacent to shell protein genes in genetic loci, or operons. To enable the identification and prediction of functional (sub)types of BMCs, we developed LoClass, an algorithm that finds putative BMC loci and inventories, weights, and compares their constituent pfam domains to construct a locus similarity network and predict locus (sub)types. In addition to using LoClass to analyze sequences in the Non-redundant Protein Database, we compared predicted BMC loci found in seven candidate bacterial phyla (six from single-cell genomic studies) to the LoClass taxonomy. Together, these analyses resulted in the identification of 23 different types of BMCs encoded in 30 distinct locus (sub)types found in 23 bacterial phyla. These include the two carboxysome types and a divergent set of metabolosomes, BMCs that share a common catalytic core and process distinct substrates via specific signature enzymes. Furthermore, many Candidate BMCs were found that lack one or more core metabolosome components, including one that is predicted to represent an entirely new paradigm for BMC-associated metabolism, joining the carboxysome and metabolosome. By placing these results in a phylogenetic context, we provide a framework for understanding the horizontal transfer of these loci, a starting point for studies aimed at understanding the evolution of BMCs. This comprehensive taxonomy of BMC loci, based on their constituent protein domains, foregrounds the functional diversity of BMCs and provides a reference for interpreting the role of BMC gene clusters encoded in isolate, single cell, and metagenomic data. Many loci encode ancillary functions such as transporters or genes for cofactor assembly; this expanded vocabulary of BMC-related functions should be useful for design of genetic modules for introducing BMCs in bioengineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Identification of a cyclic-di-GMP-modulating response regulator that impacts biofilm formation in a model sulfate reducing bacterium

We surveyed the eight putative cyclic-di-GMP-modulating response regulators (RRs) in Desulfovibrio vulgaris Hildenborough that are predicted to function via two-component signaling. Using purified proteins, we examined cyclic-di-GMP (c-di-GMP) production or turnover in vitro of all eight proteins. The two RRs containing only GGDEF domains (DVU2067, DVU0636) demonstrated c-di-GMP production activity in vitro. Of the remaining proteins, three RRs with HD-GYP domains (DVU0722, DVUA0086, and DVU2933) were confirmed to be Mn2+-dependent phosphodiesterases (PDEs) in vitro and converted c-di-GMP to its linear form, pGpG. DVU0408, containing both c-di-GMP production (GGDEF) and degradation domains (EAL), showed c-di-GMP turnover activity in vitro also with production of pGpG. No c-di-GMP related activity could be assigned to the RR DVU0330, containing a metal-dependent phosphohydrolase HD-OD domain, or to the HD-GYP domain RR, DVU1181. Studies included examining the impact of overexpressed cyclic-di-GMP-modulating RRs in the heterologous host E. coli and led to the identification of one RR, DVU0636, with increased cellulose production. Evaluation of a transposon mutant in DVU0636 indicated that the strain was impaired in biofilm formation and demonstrated an altered carbohydrate:protein ratio relative to the D. vulgaris wild type biofilms. However, grown in liquid lactate/sulfate medium, the DVU0636 transposon mutant showed no growth impairment relative to the wild-type strain. Among the eight candidates, only the transposon disruption mutant in the DVU2067 RR presented a growth defect in liquid culture. Our results indicate that, of the two diguanylate cyclases (DGCs) that function as part of two-component signaling, DVU0636 plays an important role in biofilm formation while the function of DVU2067 has pertinence in planktonic growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Progress in the prediction of pKa values in proteins

The pKa-cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pKa values and protein electrostatics in general. The first round of the pKa -cooperative, which challenged computational labs to carry out blind predictions against pKas experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6-10, 2009). This paper serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here we briefly outline existing approaches for pKa calculations, emphasizing methods that were used by the participants in calculating the blind pKa values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pKa calculations.

electrostatics↗