Protein analysis and gene expression indicate differential vulnerability of Iberian fish species under a climate change scenario

Current knowledge on the biological responses of freshwater fish under projected scenarios of climate change remains limited. Here, we examine differences in the protein configuration of two endemic Iberian freshwater fish species, Squalius carolitertii and the critically endangered S. torgalensis that inhabit in the Atlantic-type northern and in the Mediterranean-type southwestern regions, respectively. We performed protein structure modeling of fourteen genes linked to protein folding, energy metabolism, circadian rhythms and immune responses. Structural differences in proteins between the two species were found for HSC70, FKBP52, HIF1α and GPB1. For S. torgalensis, besides structural differences, we found higher thermostability for two proteins (HSP90 and GBP1), which can be advantageous in a warmer environment. Additionally, we investigated how these species might respond to projected scenarios of 3° climate change warming, acidification (ΔpH = -0.4), and their combined effects. Significant changes in gene expression were observed in response to all treatments, particularly under the combined warming and acidification. While S. carolitertii presented changes in gene expression for multiple proteins related to folding (hsp90aa1, hsc70, fkbp4 and stip1), only one such gene was altered in S. torgalensis (stip1). However, S. torgalensis showed a greater capacity for energy production under both the acidification and combined scenarios by increasing cs gene expression and maintaining ldha gene expression in muscle. Overall, these findings suggest that S. torgalensis is better prepared to cope with projected climate change. Worryingly, under the simulated scenarios, disturbances to circadian rhythm and immune system genes (cry1aa, per1a and gbp1) raise concerns for the persistence of both species, highlighting the need to consider multi-stressor effects when evaluating climate change impacts upon fish. This work also highlights that assessments of the potential of endangered freshwater species to cope with environmental change are crucial to help decision-makers adopt future conservation strategies.info:eu-repo/semantics/publishedVersio

Laforin, a Dual Specificity Phosphatase Involved in Lafora Disease, Is Present Mainly as Monomeric Form with Full Phosphatase Activity

Lafora Disease (LD) is a fatal neurodegenerative epileptic disorder that presents as a neurological deterioration with the accumulation of insoluble, intracellular, hyperphosphorylated carbohydrates called Lafora bodies (LBs). LD is caused by mutations in either the gene encoding laforin or malin. Laforin contains a dual specificity phosphatase domain and a carbohydrate-binding module, and is a member of the recently described family of glucan phosphatases. In the current study, we investigated the functional and physiological relevance of laforin dimerization. We purified recombinant human laforin and subjected the monomer and dimer fractions to denaturing gel electrophoresis, mass spectrometry, phosphatase assays, protein-protein interaction assays, and glucan binding assays. Our results demonstrate that laforin prevalently exists as a monomer with a small dimer fraction both in vitro and in vivo. Of mechanistic importance, laforin monomer and dimer possess equal phosphatase activity, and they both associate with malin and bind glucans to a similar extent. However, we found differences between the two states' ability to interact simultaneously with malin and carbohydrates. Furthermore, we tested other members of the glucan phosphatase family. Cumulatively, our data suggest that laforin monomer is the dominant form of the protein and that it contains phosphatase activity

Extent of Structural Asymmetry in Homodimeric Proteins: Prevalence and Relevance

Most homodimeric proteins have symmetric structure. Although symmetry is known to confer structural and functional advantage, asymmetric organization is also observed. Using a non-redundant dataset of 223 high-resolution crystal structures of biologically relevant homodimers, we address questions on the prevalence and significance of asymmetry. We used two measures to quantify global and interface asymmetry, and assess the correlation of several molecular and structural parameters with asymmetry. We have identified rare cases (11/223) of biologically relevant homodimers with pronounced global asymmetry. Asymmetry serves as a means to bring about 2∶1 binding between the homodimer and another molecule; it also enables cellular signalling arising from asymmetric macromolecular ligands such as DNA. Analysis of these cases reveals two possible mechanisms by which possible infinite array formation is prevented. In case of homodimers associating via non-topologically equivalent surfaces in their tertiary structures, ligand-dependent mechanisms are used. For stable dimers binding via large surfaces, ligand-dependent structural change regulates polymerisation/depolymerisation; for unstable dimers binding via smaller surfaces that are not evolutionarily well conserved, dimerisation occurs only in the presence of the ligand. In case of homodimers associating via interaction surfaces with parts of the surfaces topologically equivalent in the tertiary structures, steric hindrance serves as the preventive mechanism of infinite array. We also find that homodimers exhibiting grossly symmetric organization rarely exhibit either perfect local symmetry or high local asymmetry. Binding of small ligands at the interface does not cause any significant variation in interface asymmetry. However, identification of biologically relevant interface asymmetry in grossly symmetric homodimers is confounded by the presence of similar small magnitude changes caused due to artefacts of crystallisation. Our study provides new insights regarding accommodation of asymmetry in homodimers

Triose Phosphate Isomerase Deficiency Is Caused by Altered Dimerization–Not Catalytic Inactivity–of the Mutant Enzymes

Triosephosphate isomerase (TPI) deficiency is an autosomal recessive disorder caused by various mutations in the gene encoding the key glycolytic enzyme TPI. A drastic decrease in TPI activity and an increased level of its substrate, dihydroxyacetone phosphate, have been measured in unpurified cell extracts of affected individuals. These observations allowed concluding that the different mutations in the TPI alleles result in catalytically inactive enzymes. However, despite a high occurrence of TPI null alleles within several human populations, the frequency of this disorder is exceptionally rare. In order to address this apparent discrepancy, we generated a yeast model allowing us to perform comparative in vivo analyses of the enzymatic and functional properties of the different enzyme variants. We discovered that the majority of these variants exhibit no reduced catalytic activity per se. Instead, we observed, the dimerization behavior of TPI is influenced by the particular mutations investigated, and by the use of a potential alternative translation initiation site in the TPI gene. Additionally, we demonstrated that the overexpression of the most frequent TPI variant, Glu104Asp, which displays altered dimerization features, results in diminished endogenous TPI levels in mammalian cells. Thus, our results reveal that enzyme deregulation attributable to aberrant dimerization of TPI, rather than direct catalytic inactivation of the enzyme, underlies the pathogenesis of TPI deficiency. Finally, we discovered that yeast cells expressing a TPI variant exhibiting reduced catalytic activity are more resistant against oxidative stress caused by the thiol-oxidizing reagent diamide. This observed advantage might serve to explain the high allelic frequency of TPI null alleles detected among human populations

Using enhanced number and brightness to measure protein oligomerization dynamics in live cells

Protein dimerization and oligomerization are essential to most cellular functions, yet measurement of the size of these oligomers in live cells, especially when their size changes over time and space, remains a challenge. A commonly used approach for studying protein aggregates in cells is number and brightness (N&B), a fluorescence microscopy method that is capable of measuring the apparent average number of molecules and their oligomerization (brightness) in each pixel from a series of fluorescence microscopy images. We have recently expanded this approach in order to allow resampling of the raw data to resolve the statistical weighting of coexisting species within each pixel. This feature makes enhanced N&B (eN&B) optimal for capturing the temporal aspects of protein oligomerization when a distribution of oligomers shifts toward a larger central size over time. In this protocol, we demonstrate the application of eN&B by quantifying receptor clustering dynamics using electron-multiplying charge-coupled device (EMCCD)-based total internal reflection microscopy (TIRF) imaging. TIRF provides a superior signal-to-noise ratio, but we also provide guidelines for implementing eN&B in confocal microscopes. For each time point, eN&B requires the acquisition of 200 frames, and it takes a few seconds up to 2 min to complete a single time point. We provide an eN&B (and standard N&B) MATLAB software package amenable to any standard confocal or TIRF microscope. The software requires a high-RAM computer (64 Gb) to run and includes a photobleaching detrending algorithm, which allows extension of the live imaging for more than an hour

The Role of Oligomerization and Cooperative Regulation in Protein Function: The Case of Tryptophan Synthase

The oligomerization/co-localization of protein complexes and their cooperative regulation in protein function is a key feature in many biological systems. The synergistic regulation in different subunits often enhances the functional properties of the multi-enzyme complex. The present study used molecular dynamics and Brownian dynamics simulations to study the effects of allostery, oligomerization and intermediate channeling on enhancing the protein function of tryptophan synthase (TRPS). TRPS uses a set of α/β–dimeric units to catalyze the last two steps of L-tryptophan biosynthesis, and the rate is remarkably slower in the isolated monomers. Our work shows that without their binding partner, the isolated monomers are stable and more rigid. The substrates can form fairly stable interactions with the protein in both forms when the protein reaches the final ligand–bound conformations. Our simulations also revealed that the α/β–dimeric unit stabilizes the substrate–protein conformation in the ligand binding process, which lowers the conformation transition barrier and helps the protein conformations shift from an open/inactive form to a closed/active form. Brownian dynamics simulations with a coarse-grained model illustrate how protein conformations affect substrate channeling. The results highlight the complex roles of protein oligomerization and the fine balance between rigidity and dynamics in protein function

Detection and Functional Characterization of a 215 Amino Acid N-Terminal Extension in the Xanthomonas Type III Effector XopD

During evolution, pathogens have developed a variety of strategies to suppress plant-triggered immunity and promote successful infection. In Gram-negative phytopathogenic bacteria, the so-called type III protein secretion system works as a molecular syringe to inject type III effectors (T3Es) into plant cells. The XopD T3E from the strain 85-10 of Xanthomonas campestris pathovar vesicatoria (Xcv) delays the onset of symptom development and alters basal defence responses to promote pathogen growth in infected tomato leaves. XopD was previously described as a modular protein that contains (i) an N-terminal DNA-binding domain (DBD), (ii) two tandemly repeated EAR (ERF-associated amphiphillic repression) motifs involved in transcriptional repression, and (iii) a C-terminal cysteine protease domain, involved in release of SUMO (small ubiquitin-like modifier) from SUMO-modified proteins. Here, we show that the XopD protein that is produced and secreted by Xcv presents an additional N-terminal extension of 215 amino acids. Closer analysis of this newly identified N-terminal domain shows a low complexity region rich in lysine, alanine and glutamic acid residues (KAE-rich) with high propensity to form coiled-coil structures that confers to XopD the ability to form dimers when expressed in E. coli. The full length XopD protein identified in this study (XopD1-760) displays stronger repression of the XopD plant target promoter PR1, as compared to the XopD version annotated in the public databases (XopD216-760). Furthermore, the N-terminal extension of XopD, which is absent in XopD216-760, is essential for XopD type III-dependent secretion and, therefore, for complementation of an Xcv mutant strain deleted from XopD in its ability to delay symptom development in tomato susceptible cultivars. The identification of the complete sequence of XopD opens new perspectives for future studies on the XopD protein and its virulence-associated functions in planta

Sequence Motifs in MADS Transcription Factors Responsible for Specificity and Diversification of Protein-Protein Interaction

Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and network evolution

Predicted binding site information improves model ranking in protein docking using experimental and computer-generated target structures

BACKGROUND: Protein-protein interactions (PPIs) mediate the vast majority of biological processes, therefore, significant efforts have been directed to investigate PPIs to fully comprehend cellular functions. Predicting complex structures is critical to reveal molecular mechanisms by which proteins operate. Despite recent advances in the development of new methods to model macromolecular assemblies, most current methodologies are designed to work with experimentally determined protein structures. However, because only computer-generated models are available for a large number of proteins in a given genome, computational tools should tolerate structural inaccuracies in order to perform the genome-wide modeling of PPIs. RESULTS: To address this problem, we developed eRank(PPI), an algorithm for the identification of near-native conformations generated by protein docking using experimental structures as well as protein models. The scoring function implemented in eRank(PPI) employs multiple features including interface probability estimates calculated by eFindSite(PPI) and a novel contact-based symmetry score. In comparative benchmarks using representative datasets of homo- and hetero-complexes, we show that eRank(PPI) consistently outperforms state-of-the-art algorithms improving the success rate by ~10 %. CONCLUSIONS: eRank(PPI) was designed to bridge the gap between the volume of sequence data, the evidence of binary interactions, and the atomic details of pharmacologically relevant protein complexes. Tolerating structure imperfections in computer-generated models opens up a possibility to conduct the exhaustive structure-based reconstruction of PPI networks across proteomes. The methods and datasets used in this study are available at www.brylinski.org/erankppi