Improved enzyme functional annotation prediction using contrastive learning with structural inference
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59 BASIC BIOLOGICAL SCIENCES↗
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The Local Topological Free Energy of the SARS-CoV-2 Spike Protein
The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its Spike protein. Understanding protein rearrangement and identifying specific amino acids where mutations affect protein rearrangement has attracted much attention for drug development. In this manuscript, we use a mathematical method to characterize the local topology/geometry of the SARS-CoV-2 Spike protein backbone. Our results show that local conformational changes in the FP, HR1, and CH domains are associated with global conformational changes in the RBD domain. The SARS-CoV-2 variants analyzed in this manuscript (alpha, beta, gamma, delta Mink, G614, N501) show differences in the local conformations of the FP, HR1, and CH domains as well. Finally, most mutations of concern are either in or in the vicinity of high local topological free energy conformations, suggesting that high local topological free energy conformations could be targets for mutations with significant impact of protein function. Namely, the residues 484, 570, 614, 796, and 969, which are present in variants of concern and are targeted as important in protein function, are predicted as such from our model.
60 APPLIED LIFE SCIENCES↗
The 1 → 3 massive splitting functions from QCD factorization and SCET
Splitting functions are universal functions describing the collinear dynamics of gauge theories, and as such are crucial ingredients for a wide variety of calculations in perturbative QCD. We present analytic results for the triple collinear splitting functions in QCD with a single massive parton. We derive the splitting functions using two distinct methods; first by expanding the squared matrix elements in the collinear limit, and secondly by using soft-collinear effective theory with massive quarks. We find agreement between these two approaches, providing a strong check of our results. Additionally, we also check all iterated and soft limits of our results, finding agreement with predictions from factorization. Our results provide an important ingredient for higher order perturbative calculations involving massive partons, and for the description of the collinear dynamics of heavy flavor jets.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Design and Characterization of a Transcriptional Repression Toolkit for Plants
Regulation of gene expression is essential for all life. Tools to manipulate the gene expression level have therefore proven to be very valuable in efforts to engineer biological systems. However, there are few well-characterized genetic parts that reduce gene expression in plants, commonly known as transcriptional repressors. We characterized the repression activity of a library consisting of repression motifs from approximately 25% of the members of the largest known family of repressors. Combining sequence information with our trans-regulatory function data, we next generated a library of synthetic transcriptional repression motifs with function predicted in advance. After characterizing our synthetic library, we demonstrated not only that many of our synthetic constructs were functional as repressors but also that our advance predictions of repression strength were better than random guesses. Finally, we assessed the functionality of known transcriptional repression motifs from a wide range of eukaryotes. Our study represents the largest plant repressor motif library experimentally characterized to date, providing unique opportunities for tuning transcription in plants.
59 BASIC BIOLOGICAL SCIENCES↗
Schizophyllum commune has an extensive and functional alternative splicing repertoire
Recent genome-wide studies have demonstrated that fungi possess the machinery to alternatively splice pre-mRNA. However, there has not been a systematic categorization of the functional impact of alternative splicing in a fungus. We investigate alternative splicing and its functional consequences in the model mushroom forming fungus Schizophyllum commune. Alternative splicing was demonstrated for 2,285 out of 12,988 expressed genes, resulting in 20% additional transcripts. Intron retentions were the most common alternative splicing events, accounting for 33% of all splicing events, and 43% of the events in coding regions. On the other hand, exon skipping events were rare in coding regions (1%) but enriched in UTRs where they accounted for 57% of the events. Specific functional groups, including transcription factors, contained alternatively spliced genes. Alternatively spliced transcripts were regulated differently throughout development in 19% of the 2,285 alternatively spliced genes. Notably, 69% of alternatively spliced genes have predicted alternative functionality by loss or gain of functional domains, or by acquiring alternative subcellular locations. S. commune exhibits more alternative splicing than any other studied fungus. Finally, taken together, alternative splicing increases the complexity of the S. commune proteome considerably and provides it with a rich repertoire of alternative functionality that is exploited dynamically.
59 BASIC BIOLOGICAL SCIENCES↗
Allosteric prediction via convolutional neural networks and protein structural and dynamical features
Allostery is the phenomenon whereby a binding event or covalent modification at one site in a protein modulates function at a distal site, thus changing a protein’s functional state. As such, it is a ubiquitous aspect of protein functional regulation. Computationally predicting allosteric states is important as part of the broader challenge of functional annotation, but it also has practical implications for drug development, as targeting an allosteric site often affords greater specificity compared with targeting an orthosteric site. This study introduces a machine learning approach to predict the allosteric functional state using the small G-protein KRas as the model system, due to its implication in many types of cancer and being well studied as a result with many x-ray crystallographic structures of KRas available with different mutations and ligands bound. Using structural and dynamical features that can be cast as images, namely interatomic distances, contact maps, covariance, and mutual information, supervised learning was performed using convolutional neural networks. Two pretrained convolutional neural network architectures, GoogLeNet and ResNet18, were fine-tuned to classify KRas into active or inactive states based on these features. Across training regimes, atomic contact maps emerged as the most effective structural feature, whereas linearized mutual information outperformed covariance in capturing dynamical correlations relevant to allostery. Models achieved significant validation accuracy, with atomic contact maps yielding up to 90% accuracy. In conclusion, the findings suggest that integrating global structural rearrangements and correlated motion patterns with deep learning can reliably predict protein allosteric states, offering a promising framework for understanding allosteric regulation and developing targeted therapeutics.
Rajeshwar T., Rajitha [Oak Ridge National Laborato↗
Multi-head attention-based U-Nets for predicting protein domain boundaries using 1D sequence features and 2D distance maps
Abstract The information about the domain architecture of proteins is useful for studying protein structure and function. However, accurate prediction of protein domain boundaries (i.e., sequence regions separating two domains) from sequence remains a significant challenge. In this work, we develop a deep learning method based on multi-head U-Nets (called DistDom) to predict protein domain boundaries utilizing 1D sequence features and predicted 2D inter-residue distance map as input. The 1D features contain the evolutionary and physicochemical information of protein sequences, whereas the 2D distance map includes the structural information of proteins that was rarely used in domain boundary prediction before. The 1D and 2D features are processed by the 1D and 2D U-Nets respectively to generate hidden features. The hidden features are then used by the multi-head attention to predict the probability of each residue of a protein being in a domain boundary, leveraging both local and global information in the features. The residue-level domain boundary predictions can be used to classify proteins as single-domain or multi-domain proteins. It classifies the CASP14 single-domain and multi-domain targets at the accuracy of 75.9%, 13.28% more accurate than the state-of-the-art method. Tested on the CASP14 multi-domain protein targets with expert annotated domain boundaries, the average per-target F1 measure score of the domain boundary prediction by DistDom is 0.263, 29.56% higher than the state-of-the-art method.
59 BASIC BIOLOGICAL SCIENCES↗
Beneath the surface: Unsolved questions in soil virus ecology
Soil virus ecology is an exciting but still nascent field of research in soil microbiology. While there has been a recent surge in soil virus research studies, many fundamental questions remain unanswered, and a range of technical and bioinformatic challenges need to be overcome. In this perspective article, we present a series of key questions that highlight fruitful research areas for ongoing and future efforts. These include describing the challenges involved in understanding soil viral abundance and activity, spatiotemporal dynamics, life strategy prevalence, virus-mediated biogeochemical impacts, viral protein function, host prediction, and soil RNA virus discovery. In the near term, combining approaches (e.g., cultivation-based, meta-omics, biogeochemical, experimental, and bioinformatic) will be key to assessing the ecological and biogeochemical impacts of soil viruses from the microscopic to the field and global scales. Still, we stress that results must be tempered by current methodological limitations and highlight knowledge gaps that are most pressing to fill via new methods or measurements, such as the prevalence of different viral replication strategies across soils, the fate of microbial necromass carbon after viral lysis, the frequency of virus-host encounters that do not lead to successful infections yet could be bioinformatically mistaken as infections, and the diversity and ecological impacts of RNA viruses in soil.
59 BASIC BIOLOGICAL SCIENCES↗
Characterization of Indole-3-acetic Acid Biosynthesis and the Effects of This Phytohormone on the Proteome of the Plant-Associated Microbe Pantoea sp. YR343
Here, indole-3-acetic acid (IAA) plays a central role in plant growth and development, and many plant-associated microbes produce IAA using tryptophan as the precursor. Using genomic analyses, we predicted that Pantoea sp. YR343, a microbe isolated from Populus deltoides , synthesizes IAA using the indole-3-pyruvate (IPA) pathway. To better understand IAA biosynthesis and the effects of IAA exposure on cell physiology, we characterized proteomes of Pantoea sp. YR343 grown in the presence of tryptophan or IAA. Exposure to IAA resulted in upregulation of proteins predicted to function in carbohydrate and amino acid transport and exopolysaccharide (EPS) biosynthesis. Metabolite profiles of wild-type cells showed the production of IPA, IAA, and tryptophol, consistent with an active IPA pathway. Finally, we constructed an ΔipdC mutant that showed the elimination of tryptophol, consistent with a loss of IpdC activity, but was still able to produce IAA (20% of wild-type levels). Although we failed to detect intermediates from other known IAA biosynthetic pathways, this result suggests the possibility of an alternate pathway or the production of IAA by a nonenzymatic route in Pantoea sp. YR343. The Δ ipdC mutant was able to efficiently colonize poplar, suggesting that an active IPA pathway is not required for plant association.
59 BASIC BIOLOGICAL SCIENCES↗
New CRISPR–Cas systems from uncultivated microbes
We present that CRISPR-Cas systems provide microbes with adaptive immunity by employing short DNA sequences, termed spacers, that guide Cas proteins to cleave foreign DNA. Class 2 CRISPR-Cas systems are streamlined versions, in which a single RNA-bound Cas protein recognizes and cleaves target sequences. The programmable nature of these minimal systems has enabled researchers to repurpose them into a versatile technology that is broadly revolutionizing biological and clinical research. However, current CRISPR-Cas technologies are based solely on systems from isolated bacteria, leaving the vast majority of enzymes from organisms that have not been cultured untapped. Metagenomics, the sequencing of DNA extracted directly from natural microbial communities, provides access to the genetic material of a huge array of uncultivated organisms. Here, using genome-resolved metagenomics, we identify a number of CRISPR-Cas systems, including the first reported Cas9 in the archaeal domain of life, to our knowledge. This divergent Cas9 protein was found in little-studied nanoarchaea as part of an active CRISPR-Cas system. In bacteria, we discovered two previously unknown systems, CRISPR-CasX and CRISPR-CasY, which are among the most compact systems yet discovered. Notably, all required functional components were identified by metagenomics, enabling validation of robust in vivo RNA-guided DNA interference activity in Escherichia coli. Lastly, interrogation of environmental microbial communities combined with in vivo experiments allows us to access an unprecedented diversity of genomes, the content of which will expand the repertoire of microbe-based biotechnologies.
59 BASIC BIOLOGICAL SCIENCES↗
Standardized benchmarking in the quest for orthologs
Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision–recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.
59 BASIC BIOLOGICAL SCIENCES↗
Computational identification of HCV neutralizing antibodies with a common HCDR3 disulfide bond motif in the antibody repertoires of infected individuals
Despite recent success in hepatitis C virus (HCV) treatment using antivirals, an HCV vaccine is still needed to prevent reinfections in treated patients, to avert the emergence of drug-resistant strains, and to provide protection for people with no access to the antiviral therapeutics. The early production of broadly neutralizing antibodies (bNAbs) associates with HCV clearance. Several potent bNAbs bind a conserved HCV glycoprotein E2 epitope using an unusual heavy chain complementarity determining region 3 (HCDR3) containing an intra-loop disulfide bond. Isolation of additional structurally-homologous bNAbs would facilitate the recognition of key determinants of such bNAbs and guide rational vaccine design. Here we report the identification of new antibodies containing an HCDR3 disulfide bond motif using computational screening with the Rosetta software. Using the newly-discovered and already-known members of this antibody family, we review the required HCDR3 amino acid composition and propose determinants for the bent versus straight HCDR3 loop conformation observed in these antibodies.
59 BASIC BIOLOGICAL SCIENCES↗
An engineered opsin monomer scrambles phospholipids
The G protein-coupled receptor opsin is a phospholipid scramblase that facilitates rapid transbilayer phospholipid exchange in liposomes. The mechanism by which opsin scrambles lipids is unknown. It has been proposed that lipid translocation may occur at protein-protein interfaces of opsin dimers. To test this possibility, we rationally engineered QUAD opsin by tryptophan substitution of four lipid-facing residues in transmembrane helix 4 (TM4) that is known to be important for dimerization. Atomistic molecular dynamics simulations of wild type and QUAD opsins combined with continuum modeling revealed that the tryptophan substitutions lower the energetically unfavorable residual hydrophobic mismatch between TM4 and the membrane, reducing the drive of QUAD opsin to dimerize. We purified thermostable wild type and QUAD opsins, with or without a SNAP tag for fluorescence labeling. Single molecule fluorescence measurements of purified SNAP-tagged constructs revealed that both proteins are monomers. Fluorescence-based activity assays indicated that QUAD opsin is a fully functional scramblase. However, unlike wild type opsin which dimerizes en route to insertion into phospholipid vesicles, QUAD opsin reconstitutes as a monomer. We conclude that an engineered opsin monomer can scramble phospholipids, and that the lipid-exposed face of TM4 is unlikely to contribute to transbilayer phospholipid exchange.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Structural and mechanistic basis for redox sensing by the cyanobacterial transcription regulator RexT
Abstract Organisms have a myriad of strategies for sensing, responding to, and combating reactive oxygen species, which are unavoidable consequences of aerobic life. In the heterocystous cyanobacterium Nostoc sp. PCC 7120, one such strategy is the use of an ArsR-SmtB transcriptional regulator RexT that senses H 2 O 2 and upregulates expression of thioredoxin to maintain cellular redox homeostasis. Different from many other members of the ArsR-SmtB family which bind metal ions, RexT has been proposed to use disulfide bond formation as a trigger to bind and release DNA. Here, we present high-resolution crystal structures of RexT in the reduced and H 2 O 2 -treated states. These structures reveal that RexT showcases the ArsR-SmtB winged-helix-turn-helix fold and forms a vicinal disulfide bond to orchestrate a response to H 2 O 2 . The importance of the disulfide-forming Cys residues was corroborated using site-directed mutagenesis, mass spectrometry, and H 2 O 2 -consumption assays. Furthermore, an entrance channel for H 2 O 2 was identified and key residues implicated in H 2 O 2 activation were pinpointed. Finally, bioinformatics analysis of the ArsR-SmtB family indicates that the vicinal disulfide “redox switch” is a unique feature of cyanobacteria in the Nostocales order, presenting an interesting case where an ArsR-SmtB protein scaffold has been evolved to showcase peroxidatic activity and facilitate redox-based regulation.
54 ENVIRONMENTAL SCIENCES↗
Unexpected host dependency of Antarctic Nanohaloarchaeota
In hypersaline environments, Nanohaloarchaeota (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaeota [DPANN] superphylum) are thought to be free-living microorganisms. We report cultivation of 2 strains of Antarctic Nanohaloarchaeota and show that they require the haloarchaeon Halorubrum lacusprofundi for growth. By performing growth using enrichments and fluorescence-activated cell sorting, we demonstrated successful cultivation of Candidatus Nanohaloarchaeum antarcticus, purification of Ca. Nha. antarcticus away from other species, and growth and verification of Ca. Nha. antarcticus with Hrr. lacusprofundi ; these findings are analogous to those required for fulfilling Koch’s postulates. We use fluorescent in situ hybridization and transmission electron microscopy to assess cell structures and interactions; metagenomics to characterize enrichment taxa, generate metagenome assembled genomes, and interrogate Antarctic communities; and proteomics to assess metabolic pathways and speculate about the roles of certain proteins. Metagenome analysis indicates the presence of a single species, which is endemic to Antarctic hypersaline systems that support the growth of haloarchaea. The presence of unusually large proteins predicted to function in attachment and invasion of hosts plus the absence of key biosynthetic pathways (e.g., lipids) in metagenome assembled genomes of globally distributed Nanohaloarchaeota indicate that all members of the lineage have evolved as symbionts. Our work expands the range of archaeal symbiotic lifestyles and provides a genetically tractable model system for advancing understanding of the factors controlling microbial symbiotic relationships.
Science & Technology - Other Topics↗
Challenges in Leveraging Functional Information to Evaluate Predicted Protein-Ligand Interactions
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Biological and medical sciences↗
Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure
We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues – The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches.
59 BASIC BIOLOGICAL SCIENCES↗
Deep Green: Structural and Functional Genomic Characterization of Conserved Unannotated Green Lineage Proteins
Our overall objective is to improve and increase functional and structural predictions for a growing number of plant proteins of unknown structure and function (the Deep Green proteins), and to make our predictive data useful and accessible to the larger research community. The project is divided into five major objectives which include 1) Assembly and curation of Deep Green candidate protein sets; 2) in silico structural and functional predictions and network analyses; 3) assembly and validation of reverse genetic resources in Chlamydomonas reinhardtii (Chlamydomonas); 4) high throughput functional genomics characterization and prioritization in Chlamydomonas; and 5) structural validation of selected candidates and functional validation in two important reference plant species, Arabidopsis thaliana (Arabidopsis) and Setaria viridis (Setaria).
59 BASIC BIOLOGICAL SCIENCES↗