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Results for “protein function prediction”

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At least 739 records · Page 41

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DOE OSTI2015

Computational modeling of the N-terminus of the human dopamine transporter and its interaction with PIP 2 -containing membranes: Modeling of DAT N-Terminus/PIP 2 Interactions

The dopamine transporter (DAT) is a transmembrane protein belonging to the family of neurotransmitter:sodium symporters (NSS). Members of the NSS are responsible for the clearance of neurotransmitters from the synaptic cleft, and for their translocation back into the presynaptic nerve terminal. The DAT contains long intracellular N- and C-terminal domains that are strongly implicated in the transporter function. The N-terminus (N-term), in particular, regulates the reverse transport (efflux) of the substrate through DAT. Currently, the molecular mechanisms of the efflux remain elusive in large part due to lack of structural information on the N-terminal segment. Here we report a computational model of the N-term of the human DAT (hDAT), obtained through an ab initio structure prediction, in combination with extensive atomistic molecular dynamics (MD) simulations in the context of a lipid membrane. Our analysis reveals that whereas the N-term is a highly dynamic domain, it contains secondary structure elements that remain stable in the long MD trajectories of interactions with the bilayer (totaling >2.2 μs). Combining MD simulations with continuum mean-field modeling we found that the N-term engages with lipid membranes through electrostatic interactions with the charged lipids PIP 2 (phosphatidylinositol 4,5-Biphosphate) or PS (phosphatidylserine) that are present in these bilayers. We identify specific motifs along the N-term implicated in such interactions and show that differential modes of N-term/membrane association result in differential positioning of the structured segments on the membrane surface. These results will inform future structure-based studies that will elucidate the mechanistic role of the N-term in DAT function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Origin of replication discovery for environmentally isolated Pantoea strain enables expression of heterologous proteins, pathways and products

Leveraging predicted origin sequences from a previously characterized groundwater plasmidome, we constructed a barcoded plasmid library to screen for previously unknown origins. Testing this library against a panel of representative bacterial strains led to the identification of 3 previously unknown origins that replicate in gram-negative bacteria not previously associated with these origin sequences. Experimental validation confirmed that a plasmid bearing origin 6911 as the sole origin could replicate with a copy number of 9 (±2) in Pantoea sp. MT58, a fast growing and metal tolerant, environmentally important bacterium. Plasmids based on this new origin were used to express the reporter protein GFP, and non-native metabolite pathways for the natural product indigoidine and the terpenoid compound isoprenol. Functional previously unknown origins of replication in such non-model organisms can expand the toolkit for genetic manipulations of both model and less-studied bacteria.

molecular biology↗

DOE OSTI2011

Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients

Terrestrial ecosystems are receiving elevated inputs of nitrogen (N) from anthropogenic sources and understanding how these increases in N availability affect soil microbial communities is critical for predicting the associated effects on belowground ecosystems. We used a suite of approaches to analyze the structure and functional characteristics of soil microbial communities from replicated plots in two long-term N fertilization experiments located in contrasting systems. Pyrosequencingbased analyses of 16S rRNA genes revealed no significant effects of N fertilization on bacterial diversity, but significant effects on community composition at both sites; copiotrophic taxa (including members of the Proteobacteria and Bacteroidetes phyla) typically increased in relative abundance in the high N plots, with oligotrophic taxa (mainly Acidobacteria) exhibiting the opposite pattern. Consistent with the phylogenetic shifts under N fertilization, shotgun metagenomic sequencing revealed increases in the relative abundances of genes associated with DNA/RNA replication, electron transport and protein metabolism, increases that could be resolved even with the shallow shotgun metagenomic sequencing conducted here (average of 75 000 reads per sample). We also observed shifts in the catabolic capabilities of the communities across the N gradients that were significantly correlated with the phylogenetic and metagenomic responses, indicating possible linkages between the structure and functioning of soil microbial communities. Overall, our results suggest that N fertilization may, directly or indirectly, induce a shift in the predominant microbial life-history strategies, favoring a more active, copiotrophic microbial community, a pattern that parallels the often observed replacement of K-selected with r-selected plant species with elevated N.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Steroid responsiveness in alcohol-associated hepatitis is linked to glucocorticoid metabolism, mitochondrial repair, and heat shock proteins

Alcohol-associated hepatitis (AH) is one of the clinical presentations of alcohol-associated liver disease. AH has poor prognosis, and corticosteroids remain the mainstay of drug therapy. However, ~40% of patients do not respond to this treatment, and the mechanisms underlying the altered response to corticosteroids are not understood. The current study aimed to identify changes in hepatic protein expression associated with responsiveness to corticosteroids and prognosis in patients with AH. Patients with AH were enrolled based on the National Institute on Alcohol Abuse and Alcoholism inclusion criteria for acute AH and further confirmed by a diagnostic liver biopsy. Proteomic analysis was conducted on liver samples acquired from patients with AH grouped as nonresponders (AH-NR, n = 7) and responders (AH-R, n = 14) to corticosteroids, and nonalcohol-associated liver disease controls (n = 10). The definition of responders was based on the clinical prognostic model, the Lille Score, where a score < 0.45 classified patients as AH-R and a score > 0.45 as AH-NR. Primary outcomes used to assess steroid response were Lille Score (eg, improved liver function) and survival at 24 weeks. Reduced levels of the glucocorticoid receptor and its transcriptional co-activator, glucocorticoid modulatory element-binding protein 2, were observed in the hepatic proteome of AH-NR versus AH-R. The corticosteroid metabolizing enzyme, 11-beta-hydroxysteroid dehydrogenase 1, was increased in AH-NR versus AH-R along with elevated mitochondrial DNA repair enzymes, while several proteins of the heat shock pathway were reduced. Analysis of differentially expressed proteins in AH-NR who survived 24 weeks relative to AH-NR nonsurvivors revealed several protein expression changes, including increased levels of acute phase proteins, elevated coagulation factors, and reduced mast cell markers. This study identified hepatic proteomic changes that may predict responsiveness to corticosteroids and mortality in patients with AH.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Polymer crowding and shape distributions in polymer-nanoparticle mixtures

Macromolecular crowding can influence polymer shapes, which is important for understanding the thermodynamic stability of polymer solutions and the structure and function of biopolymers (proteins, RNA, DNA) under confinement. We explore the influence of nanoparticle crowding on polymer shapes via Monte Carlo simulations and free-volume theory of a coarse-grained model of polymer-nanoparticle mixtures. Exploiting the geometry of random walks, we model polymer coils as effective penetrable ellipsoids, whose shapes fluctuate according to the probability distributions of the eigenvalues of the gyration tensor. Accounting for the entropic cost of a nanoparticle penetrating a larger polymer coil, we compute the crowding-induced shift in the shape distributions, radius of gyration, and asphericity of ideal polymers in a theta solvent. With increased nanoparticle crowding, we find that polymers become more compact (smaller, more spherical), in agreement with predictions of free-volume theory. Our approach can be easily extended to nonideal polymers in good solvents and used to model conformations of biopolymers in crowded environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Identification and characterization of proteins of unknown function (PUFs) in Clostridium thermocellum DSM 1313 strains as potential genetic engineering targets

Abstract Background Mass spectrometry-based proteomics can identify and quantify thousands of proteins from individual microbial species, but a significant percentage of these proteins are unannotated and hence classified as proteins of unknown function (PUFs). Due to the difficulty in extracting meaningful metabolic information, PUFs are often overlooked or discarded during data analysis, even though they might be critically important in functional activities, in particular for metabolic engineering research. Results We optimized and employed a pipeline integrating various “guilt-by-association” (GBA) metrics, including differential expression and co-expression analyses of high-throughput mass spectrometry proteome data and phylogenetic coevolution analysis, and sequence homology-based approaches to determine putative functions for PUFs in Clostridium thermocellum . Our various analyses provided putative functional information for over 95% of the PUFs detected by mass spectrometry in a wild-type and/or an engineered strain of C. thermocellum . In particular, we validated a predicted acyltransferase PUF (WP_003519433.1) with functional activity towards 2-phenylethyl alcohol, consistent with our GBA and sequence homology-based predictions. Conclusions This work demonstrates the value of leveraging sequence homology-based annotations with empirical evidence based on the concept of GBA to broadly predict putative functions for PUFs, opening avenues to further interrogation via targeted experiments.

09 BIOMASS FUELS↗

DOE OSTI2016

Insights from the Structure of Mycobacterium tuberculosis Topoisomerase I with a Novel Protein Fold

The DNA topoisomerase I enzyme of Mycobacterium tuberculosis (MtTOP1) is essential for the viability of the organism and survival in a murine model. This topoisomerase is being pursued as a novel target for the discovery of new therapeutic agents for the treatment of drug-resistant tuberculosis. In this study, we succeeded in obtaining a structure of MtTOP1 by first predicting that the C-terminal region of MtTOP1 contains four repeated domains that do not involve the Zn-binding tetracysteine motifs seen in the C-terminal domains of Escherichia coli topoisomerase I. A construct (amino acids A2-T704), MtTOP1-704t, that includes the N-terminal domains (D1-D4) and the first predicted C-terminal domain (D5) of MtTOP1 was expressed and found to retain DNA cleavage-religation activity and catalyze single-stranded DNA catenation. MtTOP1-704t was crystallized, and a structure of 2.52 angstrom resolution limit was obtained. The structure of the MtTOP1 N-terminal domains has features that have not been observed in other previously available bacterial topoisomerase I crystal structures. The first C-terminal domain D5 forms a novel protein fold of a four-stranded antiparallel beta-sheet stabilized by a crossing-over alpha-helix. Since there is only one type IA topoisomerase present in Mycobacteriaceae and related Actinobacteria, this subfamily of type IA topoisomerase may be required for multiple functions in DNA replication, transcription, recombination, and repair. The unique structural features observed for MtTOP1 may allow these topoisomerase I enzymes to carry out physiological functions associated with topoisomerase III enzyme in other bacteria.

crystallization↗

DOE OSTI2015

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond those of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.

Bioinformatics, Visualisation, Transcription, Regu↗

DOE OSTI2013

Comparative effects of sodium channel blockers in short term rat whole embryo culture

This study was undertaken to examine the effect on the rat embryonic heart of two experimental drugs (AZA and AZB) which are known to block the sodium channel Nav1.5, the hERG potassium channel and the L-type calcium channel. The sodium channel blockers bupivacaine, lidocaine, and the L-type calcium channel blocker nifedipine were used as reference substances. The experimental model was the gestational day (GD) 13 rat embryo cultured in vitro. In this model the embryonic heart activity can be directly observed, recorded and analyzed using computer assisted image analysis as it responds to the addition of test drugs. The effect on the heart was studied for a range of concentrations and for a duration up to 3 h. The results showed that AZA and AZB caused a concentration-dependent bradycardia of the embryonic heart and at high concentrations heart block. These effects were reversible on washout. In terms of potency to cause bradycardia the compounds were ranked AZB > bupivacaine > AZA > lidocaine > nifedipine. Comparison with results from previous studies with more specific ion channel blockers suggests that the primary effect of AZA and AZB was sodium channel blockage. The study shows that the short-term rat whole embryo culture (WEC) is a suitable system to detect substances hazardous to the embryonic heart. - Highlights: • Study of the effect of sodium channel blocking drugs on embryonic heart function • We used a modified method rat whole embryo culture with image analysis. • The drugs tested caused a concentration dependent bradycardia and heart block. • The effect of drugs acting on multiple ion channels is difficult to predict. • This method may be used to detect cardiotoxicity in prenatal development.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Mammalian O-mannosylation of cadherins and plexins is independent of protein O-mannosyltransferases 1 and 2

Protein O-mannosylation is found in yeast and metazoans, and a family of conserved orthologous protein O-mannosyltransferases is believed to initiate this important post-translational modification. We recently discovered that the cadherin superfamily carries O-linked mannose (O-Man) glycans at highly conserved residues in specific extracellular cadherin domains, and it was suggested that the function of E-cadherin was dependent on the O-Man glycans. Deficiencies in enzymes catalyzing O-Man biosynthesis, including the two human protein O-mannosyltransferases, POMT1 and POMT2, underlie a subgroup of congenital muscular dystrophies designated α-dystroglycanopathies, because deficient O-Man glycosylation of α-dystroglycan disrupts laminin interaction with α-dystroglycan and the extracellular matrix. To explore the functions of O-Man glycans on cadherins and protocadherins, we used a combinatorial gene-editing strategy in multiple cell lines to evaluate the role of the two POMTs initiating O-Man glycosylation and the major enzyme elongating O-Man glycans, the protein O-mannose β-1,2-N-acetylglucosaminyltransferase, POMGnT1. Surprisingly, O-mannosylation of cadherins and protocadherins does not require POMT1 and/or POMT2 in contrast to α-dystroglycan, and moreover, the O-Man glycans on cadherins are not elongated. Thus, the classical and evolutionarily conserved POMT O-mannosylation pathway is essentially dedicated to α-dystroglycan and a few other proteins, whereas a novel O-mannosylation process in mammalian cells is predicted to serve the large cadherin superfamily and other proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

Abstract Motivation Multiple sequence alignments (MSAs) of homologous sequences contain information on structural and functional constraints and their evolutionary histories. Despite their importance for many downstream tasks, such as structure prediction, MSA generation is often treated as a separate pre-processing step, without any guidance from the application it will be used for. Results Here, we implement a smooth and differentiable version of the Smith–Waterman pairwise alignment algorithm that enables jointly learning an MSA and a downstream machine learning system in an end-to-end fashion. To demonstrate its utility, we introduce SMURF (Smooth Markov Unaligned Random Field), a new method that jointly learns an alignment and the parameters of a Markov Random Field for unsupervised contact prediction. We find that SMURF learns MSAs that mildly improve contact prediction on a diverse set of protein and RNA families. As a proof of concept, we demonstrate that by connecting our differentiable alignment module to AlphaFold2 and maximizing predicted confidence, we can learn MSAs that improve structure predictions over the initial MSAs. Interestingly, the alignments that improve AlphaFold predictions are self-inconsistent and can be viewed as adversarial. This work highlights the potential of differentiable dynamic programming to improve neural network pipelines that rely on an alignment and the potential dangers of optimizing predictions of protein sequences with methods that are not fully understood. Availability and implementation Our code and examples are available at: https://github.com/spetti/SMURF. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Extracellular nucleotide signaling in plants

Over the life of this funded project, our research group identified and characterized two key receptor proteins in plants; one mediating the innate immunity response to chitin and the other elucidating the key receptor for extracellular ATP. In the case of chitin recognition, we recently described the quaternary structure of this receptor, shedding light on how the receptor functions. Perhaps more importantly, we demonstrated that all plants have the ability to recognize both chitin oligomers and lipochitooligosacchardes, fundamentally changing how the community views the evolution of these systems and strategies that might be used, for example, to extend symbiotic nitrogen fixation to non-legumes. Our discovery of DORN1 opens a new chapter in plant physiology documenting conclusively that eATP is an important extracellular signal in plants, as it is in animals. At this point, we cannot predict just how far reaching this discovery may prove to be but we are convinced that eATP signaling is fundamental to plant growth and development and, hence, we believe that the future will be very exciting for the study of DORN1 and its overall function in plants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

SAA1 is transcriptionally activated by STAT3 and accelerates renal interstitial fibrosis by inducing endoplasmic reticulum stress

Renal interstitial fibrosis (RIF) is the common irreversible pathway by which chronic kidney disease (CKD) progresses to the end stage. The transforming growth factor-β (TGF-β)/signal transducer and activator of transcription 3 (STAT3) signaling pathway is a common factor leading to inflammation-mediated RIF, but its downstream regulatory mechanism is still unclear. Bioinformatics analysis predicted that serum amyloid A protein 1 (SAA1) was one of the target genes for transcriptional activation of STAT3 signaling. As an acute phase reaction protein, SAA1 plays an important role in many inflammatory reactions, and research has suggested that SAA1 is significantly elevated in the serum of patients with CKD. In this research, multiple experiments were performed to investigate the role of SAA1 in the process of RIF. SAA1 was abnormally highly expressed in kidney tissue from individuals who underwent unilateral ureteral obstruction (UUO) and TGF-β-induced HK2 cells, and the abnormal expression was directly related to the transcriptional activation of STAT3. Additionally, SAA1 can directly target and bind valosin-containing protein (VCP)-interacting membrane selenoprotein (VIMP) to inhibit the function of the Derlin-1/VCP/VIMP complex, preventing the transportation and degradation of the misfolded protein, resulting in endoplasmic reticulum (ER) stress characterized by an increase in glucose-regulated protein 78 (GRP78) levels and ultimately promoting the occurrence and development of RIF.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

The effects of intrinsic noise on the behaviour of bistable cell regulatory systems under quasi-steady state conditions

We analyse the effect of intrinsic fluctuations on the properties of bistable stochastic systems with time scale separation operating under quasi-steady state conditions. We first formulate a stochastic generalisation of the quasi-steady state approximation based on the semi-classical approximation of the partial differential equation for the generating function associated with the chemical master equation. Such approximation proceeds by optimising an action functional whose associated set of Euler-Lagrange (Hamilton) equations provides the most likely fluctuation path. We show that, under appropriate conditions granting time scale separation, the Hamiltonian can be re-scaled so that the set of Hamilton equations splits up into slow and fast variables, whereby the quasi-steady state approximation can be applied. We analyse two particular examples of systems whose mean-field limit has been shown to exhibit bi-stability: an enzyme-catalysed system of two mutually inhibitory proteins and a gene regulatory circuit with self-activation. Our theory establishes that the number of molecules of the conserved species is order parameters whose variation regulates bistable behaviour in the associated systems beyond the predictions of the mean-field theory. This prediction is fully confirmed by direct numerical simulations using the stochastic simulation algorithm. This result allows us to propose strategies whereby, by varying the number of molecules of the three conserved chemical species, cell properties associated to bistable behaviour (phenotype, cell-cycle status, etc.) can be controlled.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Biochemical and structural analyses reveal that the tumor suppressor neurofibromin (NF1) forms a high-affinity dimer

Neurofibromin is a tumor suppressor encoded by the NF1 gene, which is mutated in Rasopathy disease neurofibromatosis type I. Defects in NF1 lead to aberrant signaling through the RAS–mitogen-activated protein kinase pathway due to disruption of the neurofibromin GTPase-activating function on RAS family small GTPases. Very little is known about the function of most of the neurofibromin protein; to date, biochemical and structural data exist only for its GAP domain and a region containing a Sec-PH motif. To better understand the role of this large protein, here we carried out a series of biochemical and biophysical experiments, including size-exclusion chromatography–multiangle light scattering (SEC-MALS), small-angle X-ray and neutron scattering, and analytical ultracentrifugation, indicating that full-length neurofibromin forms a high-affinity dimer. We observed that neurofibromin dimerization also occurs in human cells and likely has biological and clinical implications. Analysis of purified full-length and truncated neurofibromin variants by negative-stain EM revealed the overall architecture of the dimer and predicted the potential interactions that contribute to the dimer interface. We could reconstitute structures resembling high-affinity full-length dimers by mixing N- and C-terminal protein domains in vitro. The reconstituted neurofibromin was capable of GTPase activation in vitro, and co-expression of the two domains in human cells effectively recapitulated the activity of full-length neurofibromin. Taken together, these results suggest how neurofibromin dimers might form and be stabilized within the cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

MicroFisher: Fungal taxonomic classification for metatranscriptomic and metagenomic data using multiple short hypervariable markers

AbstractProfiling the taxonomic and functional composition of microbes using metagenomic (MG) and metatranscriptomic (MT) sequencing is advancing our understanding of microbial functions. However, the sensitivity and accuracy of microbial classification using genome– or core protein-based approaches, especially the classification of eukaryotic organisms, is limited by the availability of genomes and the resolution of sequence databases. To address this, we propose the MicroFisher, a novel approach that applies multiple hypervariable marker genes to profile fungal communities from MGs and MTs. This approach utilizes the hypervariable regions of ITS and large subunit (LSU) rRNA genes for fungal identification with high sensitivity and resolution. Simultaneously, we propose a computational pipeline (MicroFisher) to optimize and integrate the results from classifications using multiple hypervariable markers. To test the performance of our method, we applied MicroFisher to the synthetic community profiling and found high performance in fungal prediction and abundance estimation. In addition, we also used MGs from forest soil and MTs of root eukaryotic microbes to test our method and the results showed that MicroFisher provided more accurate profiling of environmental microbiomes compared to other classification tools. Overall, MicroFisher serves as a novel pipeline for classification of fungal communities from MGs and MTs.

Wang, Haihua↗

DOE OSTI2024

CyanoCyc cyanobacterial web portal

CyanoCyc is a web portal that integrates an exceptionally rich database collection of information about cyanobacterial genomes with an extensive suite of bioinformatics tools. It was developed to address the needs of the cyanobacterial research and biotechnology communities. The 277 annotated cyanobacterial genomes currently in CyanoCyc are supplemented with computational inferences including predicted metabolic pathways, operons, protein complexes, and orthologs; and with data imported from external databases, such as protein features and Gene Ontology (GO) terms imported from UniProt. Five of the genome databases have undergone manual curation with input from more than a dozen cyanobacteria experts to correct errors and integrate information from more than 1,765 published articles. CyanoCyc has bioinformatics tools that encompass genome, metabolic pathway and regulatory informatics; omics data analysis; and comparative analyses, including visualizations of multiple genomes aligned at orthologous genes, and comparisons of metabolic networks for multiple organisms. CyanoCyc is a high-quality, reliable knowledgebase that accelerates scientists’ work by enabling users to quickly find accurate information using its powerful set of search tools, to understand gene function through expert mini-reviews with citations, to acquire information quickly using its interactive visualization tools, and to inform better decision-making for fundamental and applied research.

59 BASIC BIOLOGICAL SCIENCES↗