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PubMed2000

Analysis and prediction of functional sub-types from protein sequence alignments.

The increasing number and diversity of protein sequence families requires new methods to define and predict details regarding function. Here, we present a method for analysis and prediction of functional sub-types from multiple protein sequence alignments. Given an alignment and set of proteins grouped into sub-types according to some definition of function, such as enzymatic specificity, the method identifies positions that are indicative of functional differences by comparison of sub-type specific sequence profiles, and analysis of positional entropy in the alignment. Alignment positions with significantly high positional relative entropy correlate with those known to be involved in defining sub-types for nucleotidyl cyclases, protein kinases, lactate/malate dehydrogenases and trypsin-like serine proteases. We highlight new positions for these proteins that suggest additional experiments to elucidate the basis of specificity. The method is also able to predict sub-type for unclassified sequences. We assess several variations on a prediction method, and compare them to simple sequence comparisons. For assessment, we remove close homologues to the sequence for which a prediction is to be made (by a sequence identity above a threshold). This simulates situations where a protein is known to belong to a protein family, but is not a close relative of another protein of known sub-type. Considering the four families above, and a sequence identity threshold of 30 %, our best method gives an accuracy of 96 % compared to 80 % obtained for sequence similarity and 74 % for BLAST. We describe the derivation of a set of sub-type groupings derived from an automated parsing of alignments from PFAM and the SWISSPROT database, and use this to perform a large-scale assessment. The best method gives an average accuracy of 94 % compared to 68 % for sequence similarity and 79 % for BLAST. We discuss implications for experimental design, genome annotation and the prediction of protein function and protein intra-residue distances.

Adenylyl Cyclases↗
PubMed2026

Circular RNAs orchestrate integrated post-transcriptional responses to combined heat and drought stress in rice.

Circular RNAs (circRNAs) are emerging post-transcriptional regulators, yet their landscape and functional roles in rice under combined abiotic stress remain largely unexplored. Here, we systematically reanalyzed strand-specific RNA-seq data to characterize circRNAs responsive to simultaneous heat and drought stress. Following quality control, read mapping, and dual-algorithm prediction using CIRI2 and CIRCexplorer2, we identified 208 high-confidence circRNAs distributed across all 12 chromosomes. Comparative profiling revealed 83 circRNAs uniquely expressed in control samples, 51 in stressed samples, and 74 shared between conditions, indicating stress-dependent circularization. Junction-read analysis highlighted a spectrum of circularization strength, ranging from highly abundant circRNAs with dominant junction reads to low-confidence candidates masked by linear transcript background. Genomic annotation showed that circRNAs primarily originated from exonic and intergenic regions, with a pronounced negative-strand bias; several genes generated multiple circRNA isoforms via alternative back-splicing. Functional enrichment of host genes suggested involvement in protein folding, nutrient reservoir activity, RNA degradation, and branched-chain amino acid catabolism, implicating roles in stress adaptation and metabolic regulation. Differential expression analysis identified seven circRNAs specifically induced under combined stress conditions. Network topology analysis pinpointed key miRNAs-including osa-miR414, osa-miR1439, and osa-miR2919-as candidate topological hubs within the predicted network. Their predicted target genes, such as those encoding stress-responsive transcription factors and signaling proteins, suggest potential roles in coordinating post-transcriptional responses to combined stress. Network topology analysis pinpointed key miRNAs-including osa-miR414, osa-miR1439, and osa-miR2919-as candidate topological hubs within the predicted network. Their predicted target genes, such as those encoding stress-responsive transcription factors and signaling proteins, suggest potential roles in coordinating post-transcriptional responses to combined stress. Overall, this study provides a comprehensive map of circRNAs in rice under combined heat and drought stress, suggests their potential as ceRNAs based on predictive analysis, and lays a foundation for future experimental validation of circRNA-mediated regulation.

Oryza↗
PubMed2005

Data mining for protein-protein interactions in invertebrate model organisms.

Well-annotated genome databases are available for many invertebrate species, notably the fruitfly, Drosophila melanogaster, and the nematode, Caenorhabditis elegans. An adequate interpretation of this information at the biological level requires the exploration of the interactions between the gene products. Knowledge of protein interactions and the components of cell signalling pathways in the fly and worm are particularly valuable as hypotheses can be rapidly tested using the powerful genetic toolkits available. Invertebrates offer additional experimental advantages when attempting to characterise protein-protein interactions (PPIs). Their relatively small genome size compared to mammals helps to reduce missed interactions due to redundancy, and their function can be addressed using forward (mutants) and reverse (RNA interference) genetics. However, the researcher looking for evidence of PPIs for a protein of interest is faced with the challenge of extracting interaction data from sources that are highly varied, such as the results of microarray experiments in the unstructured text of research papers. This challenge is greatly reduced by a range of public databases of curated information, as well as publicly available, enhanced search engines, which can provide either direct experimental evidence for a PPI, or valuable clues for generating new hypotheses.

Animals↗
PubMed2004

Encoding microbial metabolic logic: predicting biodegradation.

Prediction of microbial metabolism is important for annotating genome sequences and for understanding the fate of chemicals in the environment. A metabolic pathway prediction system (PPS) has been developed that is freely available on the world wide web (http://umbbd.ahc.umn.edu/predict/), recognizes the organic functional groups found in a compound, and predicts transformations based on metabolic rules. These rules are designed largely by examining reactions catalogued in the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD) and are generalized based on metabolic logic. The predictive accuracy of the PPS was tested: (1) using a 113-member set of compounds found in the database, (2) against a set of compounds whose metabolism was predicted by human experts, and (3) for consistency with experimental microbial growth studies. First, the system correctly predicted known metabolism for 111 of the 113 compounds containing C and H, O, N, S, P and/or halides that initiate existing pathways in the database, and also correctly predicted 410 of the 569 known pathway branches for these compounds. Second, computer predictions were compared to predictions by human experts for biodegradation of six compounds whose metabolism was not described in the literature. Third, the system predicted reactions liberating ammonia from three organonitrogen compounds, consistent with laboratory experiments showing that each compound served as the sole nitrogen source supporting microbial growth. The rule-based nature of the PPS makes it transparent, expandable, and adaptable.

Bacteria↗
PubMed2004

A preliminary investigation of the Nostoc punctiforme proteome.

Nostoc punctiforme ATCC 29133 is a filamentous terrestrial cyanobacterium (prokaryote) that expresses several different phenotypes in response to environmental cues. When grown in nitrogen-deficient media the most abundant proteins in addition to phycobiliproteins were superoxide dismutase, ATP synthase, and peptidyl-prolyl cis-trans isomerases. A methylated peptide from an akinete marker protein was also identified, suggesting that methylation could potentially play a regulatory role through signaling. C-phycocyanin alpha-chain was methylated at the C-terminal end of the protein and tandem mass spectrometric data also identified peptides that were deamidated. Since a significant number of putative polyketide/non-ribosomal peptide synthase genes are present in the annotated genome, an analysis of a methanolic extract of whole cells was also performed, and a series of nostopeptolides were identified.

Amino Acid Sequence↗
PubMed2006

Biochemical properties and cellular localization of Plasmodium falciparum protein disulfide isomerase.

We have previously reported the isolation of a 52,000 M(r) protein (Pf52) displaying consensus sequences for thiol:disulfide oxidoreductases. Pf52 therefore represents the plasmodial protein disulfide isomerase (PDI). It has been renamed PfPDI and correlates to MAL8P1.17 in the annotated genome of P. falciparum (3D7 strain). Antibodies were raised against recombinant (His)(6)-tagged forms of PfPDI devoid of its signal peptide sequence, demonstrating a major co-localization of PfPDI with endoplasmic reticulum-resident proteins, PfBIP and PfERC, but not with the Golgi marker PfERD2. Recombinant PfPDI displayed typical biochemical functions of PDIs: oxidase/isomerase and reductase activities, as well as a chaperone-like behavior on the denaturated protein rhodanese. These activities were comparable to those measured for the purified native bovine PDI and the human recombinant PDI. The antiplasmodial compound DS61 does inhibit the recombinant PfPDI oxidase/isomerase activity but not that of the human recombinant PDI, suggesting structural differences between both enzymes. However, a discrepancy between the inhibitory activity of DS61 on the recombinant PfPDI (IC(50) of 430 microM) and its in vitro antiplasmodial activity (IC(50) of 0.1 microM) was observed, suggesting that PfPDI is not the only target of DS61. Taking into account its biochemical properties and its intracellular localization, the involvement of PfPDI in the parasite protein folding is discussed, as well as its potential for the development of alternative antimalarial chemotherapy strategies.

Animals↗
PubMed2006

Evolution of enzyme superfamilies.

Enzyme evolution is often constrained by aspects of catalysis. Sets of homologous proteins that catalyze different overall reactions but share an aspect of catalysis, such as a common partial reaction, are called mechanistically diverse superfamilies. The common mechanistic steps and structural characteristics of several of these superfamilies, including the enolase, Nudix, amidohydrolase, and haloacid dehalogenase superfamilies have been characterized. In addition, studies of mechanistically diverse superfamilies are helping to elucidate mechanisms of functional diversification, such as catalytic promiscuity. Understanding how enzyme superfamilies evolve is vital for accurate genome annotation, predicting protein functions, and protein engineering.

Binding Sites↗
PubMed2006

Plasmodium falciparum: Co-dependent expression and co-localization of the PfCCp multi-adhesion domain proteins.

In Plasmodium falciparum, a family of six secreted proteins having a conserved architecture of multiple adhesive domains was recently identified by genome annotation. Three of the proteins, termed PfCCp1, PfCCp2, and PfCCp3 due to a common LCCL domain, are expressed inside the gametocyte parasitophorous vacuole and released during gamete emergence, where they relocate extracellularly surrounding exflagellation complexes. In this study we show that the three PfCCp proteins are co-expressed at the gametocyte surface. Abrogation of PfCCp3 in gene disruptant parasites leads to the loss of PfCCp1 and PfCCp2 protein but not transcript, indicating a co-dependent protein expression. In view of these data we propose that the three PfCCp proteins interact during gametocytogenesis by formation of a protein complex.

Animals↗
PubMed2003

EMMA: a platform for consistent storage and efficient analysis of microarray data.

As a high throughput technique, microarray experiments produce large data sets, consisting of measured data, laboratory protocols, and experimental settings. We have implemented the open source platform EMMA to store and analyze these data. The system provides automated pipelines for data processing and has a modular architecture that can be easily extended. EMMA features detailed reports about spots and their corresponding measurements. In addition to routine data analysis algorithms, the system can be integrated with other components that contain additional data sources (e.g. genome annotation systems).

Algorithms↗
PubMed2026

Detoxification-driven recovery of nitrogen removal under high linear alkylbenzene sulfonate stress by immobilized Pseudomonas sp. LM2.

Linear alkylbenzene sulfonate (LAS) is a widely used anionic surfactant that can inhibit microbial activity and destabilize biological wastewater treatment systems under high loading conditions. In this study, a sequencing batch reactor (SBR) was exposed to increasing LAS concentrations (0-100 mg/L) to define the collapse trajectory of activated sludge and evaluate recovery following bioaugmentation with immobilized Pseudomonas sp. LM2. The system remained stable at 20 mg/L LAS, deteriorated after prolonged exposure to 50 mg/L, and developed severe sludge disintegration with near-complete nitrification failure at 100 mg/L. In the LM reactor, LAS removal increased from 25.4% to 53.1% after bioaugmentation, together with improved nitrogen-removal performance. Blank carriers did not restore reactor performance. Genome annotation showed that LM2 encoded genes associated with LAS degradation and denitrification but lacked nitrification genes. Thus, the observed nitrification recovery was likely indirect and associated with lower LAS stress and recovery of indigenous nitrifiers. Quantitative PCR and amplicon analyses showed enrichment of Nitrospira and Thauera and a shift toward more deterministic community assembly after bioaugmentation. The carrier-only control showed taxonomic recovery but persistent functional inhibition under high residual LAS exposure. Overall, the results indicate that immobilized bioaugmentation can support partial recovery of nitrogen removal under severe LAS stress.

Bioaugmentation↗
PubMed2004

A combined transmembrane topology and signal peptide prediction method.

An inherent problem in transmembrane protein topology prediction and signal peptide prediction is the high similarity between the hydrophobic regions of a transmembrane helix and that of a signal peptide, leading to cross-reaction between the two types of predictions. To improve predictions further, it is therefore important to make a predictor that aims to discriminate between the two classes. In addition, topology information can be gained when successfully predicting a signal peptide leading a transmembrane protein since it dictates that the N terminus of the mature protein must be on the non-cytoplasmic side of the membrane. Here, we present Phobius, a combined transmembrane protein topology and signal peptide predictor. The predictor is based on a hidden Markov model (HMM) that models the different sequence regions of a signal peptide and the different regions of a transmembrane protein in a series of interconnected states. Training was done on a newly assembled and curated dataset. Compared to TMHMM and SignalP, errors coming from cross-prediction between transmembrane segments and signal peptides were reduced substantially by Phobius. False classifications of signal peptides were reduced from 26.1% to 3.9% and false classifications of transmembrane helices were reduced from 19.0% to 7.7%. Phobius was applied to the proteomes of Homo sapiens and Escherichia coli. Here we also noted a drastic reduction of false classifications compared to TMHMM/SignalP, suggesting that Phobius is well suited for whole-genome annotation of signal peptides and transmembrane regions. The method is available at as well as at

Membrane Proteins↗
PubMed2004

Enzyme/non-enzyme discrimination and prediction of enzyme active site location using charge-based methods.

Calculations of charge interactions complement analysis of a characterised active site, rationalising pH-dependence of activity and transition state stabilisation. Prediction of active site location through large DeltapK(a)s or electrostatic strain is relevant for structural genomics. We report a study of ionisable groups in a set of 20 enzymes, finding that false positives obscure predictive potential. In a larger set of 156 enzymes, peaks in solvent-space electrostatic properties are calculated. Both electric field and potential match well to active site location. The best correlation is found with electrostatic potential calculated from uniform charge density over enzyme volume, rather than from assignment of a standard atom-specific charge set. Studying a shell around each molecule, for 77% of enzymes the potential peak is within that 5% of the shell closest to the active site centre, and 86% within 10%. Active site identification by largest cleft, also with projection onto a shell, gives 58% of enzymes for which the centre of the largest cleft lies within 5% of the active site, and 70% within 10%. Dielectric boundary conditions emphasise clefts in the uniform charge density method, which is suited to recognition of binding pockets embedded within larger clefts. The variation of peak potential with distance from active site, and comparison between enzyme and non-enzyme sets, gives an optimal threshold distinguishing enzyme from non-enzyme. We find that 87% of the enzyme set exceeds the threshold as compared to 29% of the non-enzyme set. Enzyme/non-enzyme homologues, "structural genomics" annotated proteins and catalytic/non-catalytic RNAs are studied in this context.

Binding Sites↗
PubMed2026

iMTSS: an integrated framework for biology- and patient-driven prognosis in myelofibrosis undergoing transplantation.

BACKGROUND: Allogeneic hematopoietic cell transplantation is the only curative treatment for myelofibrosis, but failure occurs by two mechanistically distinct routes: relapse of the neoplasm, which reflects its underlying genetics, and non-relapse mortality, which reflects whether the patient and graft tolerate the procedure. Established prognostic systems either lack molecular granularity or were derived in the non-transplant setting, and all collapse these two routes into a single survival estimate. None can indicate why an individual patient is at risk, or which class of intervention might reduce that risk. OBJECTIVE: To determine why an individual patient is at risk and to develop and validate an integrated framework that quantifies biology- and patient-driven prognosis. STUDY DESIGN: We analyzed 1,550 adults undergoing first allogeneic transplantation for primary or secondary myelofibrosis across international centers, the largest genomically annotated transplant cohort in this disease. The cohort was split into development (n=930) and validation (n=620) sets. Overall survival was modeled by Cox regression; relapse and non-relapse mortality were modeled as competing events by Fine-Gray subdistribution-hazard regression at 2 years. Discrimination was assessed by the concordance index with bootstrap confidence intervals. The molecular contribution was quantified by variance decomposition of, and robustness to the analytic choices was examined by resampling. RESULTS: A genetically defined disease-intrinsic axis, including TP53 allelic state, RAS pathway mutations, ASXL1 and driver genotype, blasts and blood counts, predicted 2 year relapse incidence (validation concordance 0.69, 95% CI 0.63 to 0.74), whereas a non-overlapping host and structural axis, including portal vein thrombosis, donor type, patients' performance status, and age predicted 2-year non-relapse mortality (0.63, 95% CI 0.59 to 0.68). The two scores shared only 3.4% of their variance, indicating that a patient's disease genetics carried almost no information about non-relapse mortality. Variance decomposition showed that TP53 allelic state alone accounted for 30% of the relapse score. Recombined, the framework discriminated overall survival (concordance 0.640, 95% CI 0.616 to 0.662) better than every established prognostic system. For proof of concept, 3 risk groups separated in the validation cohort, with 5 year survival of 72%, 58%, and 39% (P<0.001), and the models were well calibrated. CONCLUSIONS: Relapse and non-relapse mortality after transplantation for myelofibrosis are governed by distinct dimensions. Estimating both outcomes independently with genetic and clinical information, in addition to overall survival, establishes an individualized basis for transplant decision-making. The calculator is openly available (https://imtss-calculator.com).

mortality↗
PubMed2004

Identification of the mammalian Not gene via a phylogenomic approach.

Despite the great morphological diversity of early embryos, the underlying mechanisms of gastrulation are known to be broadly conserved in vertebrates. However, a number of genes characterized as fulfilling an essential function in this process in several model organisms display no clear ortholog in mammalian genomes. We have devised an in silico phylogenomic approach, based on exhaustive similarity searches in vertebrate genomes and subsequent bayesian phylogenetic analyses, to identify such missing genes, presumed to be highly divergent. This approach has been used to identify mammalian orthologs of Not, an homeodomain containing gene previously characterized in Xenopus, chick and zebrafish as playing a critical role in the formation of the notochord. This attempt led to the identification of a highly divergent mammalian Not-related gene in the mouse, human and rat. The results from phylogenetic reconstructions, synteny analyses, expression pattern analyses in wild-type and mutant mouse embryos, and overexpression experiments in Xenopus embryos converge to confirm these genes as representatives of the Not family in mammals. The identification of the mammalian Not gene delivers an important component for the understanding of the genetics underlying notochord formation in mammals and its evolution among vertebrates. The phylogenomic method used to retrieve this gene thus provides a tool, which can complement or validate genome annotations in situations when they are weakly supported.

Amino Acid Sequence↗
PubMed2026

Comparative phylogenomics and transcriptional regulatory networks of AQPs, HSPs, and LEA proteins in salt-stressed Portulaca oleracea.

Soil salinization severely threatens global food security, necessitating systematic investigations of halophytes like Portulaca oleracea to decode the molecular mechanisms of environmental resilience. Utilizing an integrated framework of deep learning-based genome annotation (58,817 predicted genes; 96.5% BUSCO completeness), multi-tissue RNA-Seq, phylogenomics, and gene regulatory network (GRN) inference, the synergistic orchestration of 78 aquaporins (AQPs), 525 heat shock proteins (HSPs), and 119 late embryogenesis abundant (LEA) proteins was elucidated. The active transcriptome, encompassing 39,065 expressed loci, revealed a systemic growth-defense trade-off. Tissues displayed distinct adaptive mechanisms: leaves modulated intracellular water balance via specialized AQPs, whereas adult roots maintained proteostasis through robust HSP20/HSP70 induction. Phylogenomic clustering across 154 species demonstrated that salinity tolerance constitutes an evolutionary mosaic, identifying 81 halophyte-exclusive orthogroups and 1129 species-specific clusters. Comparative topology across six independent GRNs (4.2M-5.3&#x202f;M edges) unmasked a highly modular transcriptional reprogramming strategy governed by a core apparatus of 22 stress-exclusive regulators, with functional enrichment heavily prioritizing protein dimerization and chromatin remodeling. Theoretically, the distinct convergence of Trihelix transcription factors with guard cell differentiation pathways offers a candidate transcriptomic framework to explain the plant's characteristic C4-CAM photosynthetic plasticity under severe osmotic pressure. Practically, these evolutionary blueprints and specific master switches transcend single-gene transgenic limitations. Utilizing these root-sustained and stress-inducible targets under localized promoters provides a naturally optimized, network-level precision engineering roadmap to transfer robust, compartmentalized halotolerance to sensitive glycophytic crops.

Gene Regulatory Networks↗
PubMed2005

Sulfate requirement for heterotrophic growth of "Ferroplasma acidarmanus" strain fer1.

Growth of the acidophilic archaeon, "Ferroplasma acidarmanus" strain fer1, in a laboratory medium (primary constituents, FeSO4 72 mM and 0.02% yeast extract) is minimal. A survey of the annotated genome revealed metabolic transporters for Ni2+, sugars, and amino acids. Accordingly, the concentration of yeast extract was increased to 0.1% and the addition of 2 mM Ni(NH4)2(SO4)2 significantly enhanced the cultivation of strain fer1. The maximum optical density in the modified fer1 medium (mfer) was OD(492)=0.27 with 10(10) viable cells/ml as determined by a most-probable-number method, which exceeds previously reported viable cells/ml by >100-fold. Strain fer1 displayed chemolithotrophic growth with Fe2+ in mfer containing 100 mM FeSO4 or FeCl2. In the absence of Fe2+, heterotrophic growth occurred with one of the following salts (100 mM): ZnSO4, MnSO4, MgSO4, (NH4)2SO4, or Fe2(SO4)3, and did not occur with (100 mM): ZnCl2, MnCl2, MgCl2, NH4Cl, or FeCl3. Escaping headspace gas from strain fer1 cultures formed a precipitate in a zinc acetate trap. Sulfide was absent in the precipitate but zinc and sulfur were detected. These data demonstrate that SO4 is required for heterotrophic growth of strain fer1 and may have a role in the global sulfur cycle.

Archaea↗
PubMed2005

How to broaden enzyme substrate specificity: strategies, implications and applications.

For identification of mutations associated with the broadening of enzyme substrate specificity, three strategies, including directed enzyme evolution, are described for selected examples. Implications concerning enzyme models are highlighted. Applications to the field of biocatalysis are discussed. A bidimensional map for the classification of enzyme activities is suggested so as to improve genome annotations.

Catalysis↗
PubMed2006

In silico analysis and characterization of GntR family of regulators from Mycobacterium tuberculosis.

The genome of Mycobacterium tuberculosis contains a large number of hypothetical and poorly characterized proteins including the proteins belonging to the GntR family. The regulators of this family show a conserved N-terminal DNA-binding domain but have a highly diverse C-terminal domain involved in the effector-binding and/or oligomerization. This heterogeneity has led to a further classification of this family into various subfamilies. The sequence analysis of the M. tuberculosis genome revealed that five genes encode for FadR-like regulators, one gene for HutC-like regulator and one for YtrA-like regulator. This classification was also consistent with specific secondary structural features known to be associated with FadR, HutC and YtrA subfamilies. Out of the five FadR-like regulators three of the regulators were further subclassified into FadR group and two of them into the VanR group. Interestingly Rv3060c, a FadR-like regulator, was shown to have an unusual size which led us to demonstrate it as a product of a gene duplication and fusion event. Thus this study extends the genome annotation of M. tuberculosis and provides important leads for initiating experimental characterization of these proteins, which in turn will enrich our knowledge of their role in cellular physiology.

Bacterial Proteins↗