Repeat or not repeat?—Statistical validation of tandem repeat prediction in genomic sequences

Tandem repeats (TRs) represent one of the most prevalent features of genomic sequences. Due to their abundance and functional significance, a plethora of detection tools has been devised over the last two decades. Despite the longstanding interest, TR detection is still not resolved. Our large-scale tests reveal that current detectors produce different, often nonoverlapping inferences, reflecting characteristics of the underlying algorithms rather than the true distribution of TRs in genomic data. Our simulations show that the power of detecting TRs depends on the degree of their divergence, and repeat characteristics such as the length of the minimal repeat unit and their number in tandem. To reconcile the diverse predictions of current algorithms, we propose and evaluate several statistical criteria for measuring the quality of predicted repeat units. In particular, we propose a model-based phylogenetic classifier, entailing a maximum-likelihood estimation of the repeat divergence. Applied in conjunction with the state of the art detectors, our statistical classification scheme for inferred repeats allows to filter out false-positive predictions. Since different algorithms appear to specialize at predicting TRs with certain properties, we advise applying multiple detectors with subsequent filtering to obtain the most complete set of genuine repeat

Longitudinal analyses of immune responses to Plasmodium falciparum derived peptides corresponding to novel blood stage antigens in coastal Kenya.

We have recently described 95 predicted alpha-helical coiled-coil peptides derived from putative Plasmodium falciparum erythrocytic stage proteins. Seventy peptides recognized with the highest level of prevalence by sera from three endemic areas were selected for further studies. In this study, we sequentially examined antibody responses to these synthetic peptides in two cohorts of children at risk of clinical malaria in Kilifi district in coastal Kenya, in order to characterize the level of peptide recognition by age, and the role of anti-peptide antibodies in protection from clinical malaria. Antibody levels from 268 children in the first cohort (Chonyi) were assayed against 70 peptides. Thirty-nine peptides were selected for further study in a second cohort (Junju). The rationale for the second cohort was to confirm those peptides identified as protective in the first cohort. The Junju cohort comprised of children aged 1-6 years old (inclusive). Children were actively followed up to identify episodes of febrile malaria in both cohorts. Of the 70 peptides examined, 32 showed significantly (p<0.05) increased antibody recognition in older children and 40 showed significantly increased antibody recognition in parasitaemic children. Ten peptides were associated with a significantly reduced odds ratio (OR) for an episode of clinical malaria in the first cohort of children and two of these peptides (LR146 and AS202.11) were associated with a significantly reduced OR in both cohorts. LR146 is derived from hypothetical protein PFB0145c in PlasmoDB. Previous work has identified this protein as a target of antibodies effective in antibody dependent cellular inhibition (ADCI). The current study substantiates further the potential of protein PFB0145c and also identifies protein PF11_0424 as another likely target of protective antibodies against P. falciparum malaria

Census of halide-binding sites in protein structures

Motivation: Halides are negatively charged ions of halogens, forming fluorides (F-), chlorides (Cl-), bromides (Br-) and iodides (I-). These anions are quite reactive and interact both specifically and non-specifically with proteins. Despite their ubiquitous presence and important roles in protein function, little is known about the preferences of halides binding to proteins. To address this problem, we performed the analysis of halide-protein interactions, based on the entries in the Protein Data Bank. Results: We have compiled a pipeline for the quick analysis of halide-binding sites in proteins using the available software. Our analysis revealed that all of halides are strongly attracted by the guanidinium moiety of arginine side chains, however, there are also certain preferences among halides for other partners. Furthermore, there is a certain preference for coordination numbers in the binding sites, with a correlation between coordination numbers and amino acid composition. This pipeline can be used as a tool for the analysis of specific halide-protein interactions and assist phasing experiments relying on halides as anomalous scatters

Identification of the Autochaperone Domain in the Type Va Secretion System (T5aSS):Prevalent Feature of Autotransporters with a β-Helical Passenger

Autotransporters (ATs) belong to a family of modular proteins secreted by the Type V, subtype a, secretion system (T5aSS) and considered as an important source of virulence factors in lipopolysaccharidic diderm bacteria (archetypical Gram-negative bacteria). While exported by the Sec pathway, the ATs are further secreted across the outer membrane via their own C-terminal translocator forming a β-barrel, through which the rest of the protein, namely the passenger, can pass. In several ATs, an autochaperone domain (AC) present at the C-terminal region of the passenger and upstream of the translocator was demonstrated as strictly required for proper secretion and folding. However, considering it was functionally characterised and identified only in a handful of ATs, wariness recently fells on the commonality and conservation of this structural element in the T5aSS. To circumvent the issue of sequence divergence and taking advantage of the resolved three-dimensional structure of some ACs, identification of this domain was performed following structural alignment among all AT passengers experimentally resolved by crystallography before searching in a dataset of 1523 ATs. While demonstrating that the AC is indeed a conserved structure found in numerous ATs, phylogenetic analysis further revealed a distribution into deeply rooted branches, from which emerge 20 main clusters. Sequence analysis revealed that an AC could be identified in the large majority of SAATs (self-associating ATs) but not in any LEATs (lipase/esterase ATs) nor in some PATs (protease autotransporters) and PHATs (phosphatase/hydrolase ATs). Structural analysis indicated that an AC was present in passengers exhibiting single-stranded right-handed parallel β-helix, whatever the type of β-solenoid, but not with α-helical globular fold. From this investigation, the AC of type 1 appears as a prevalent and conserved structural element exclusively associated to β-helical AT passenger and should promote further studies about the protein secretion and folding via the T5aSS, especially toward α-helical AT passengers

Δ133p53β isoform pro-invasive activity is regulated through an aggregation-dependent mechanism in cancer cells

International audienceAbstract The p53 isoform, Δ133p53β, is critical in promoting cancer. Here we report that Δ133p53β activity is regulated through an aggregation-dependent mechanism. Δ133p53β aggregates were observed in cancer cells and tumour biopsies. The Δ133p53β aggregation depends on association with interacting partners including p63 family members or the CCT chaperone complex. Depletion of the CCT complex promotes accumulation of Δ133p53β aggregates and loss of Δ133p53β dependent cancer cell invasion. In contrast, association with p63 family members recruits Δ133p53β from aggregates increasing its intracellular mobility. Our study reveals novel mechanisms of cancer progression for p53 isoforms which are regulated through sequestration in aggregates and recruitment upon association with specific partners like p63 isoforms or CCT chaperone complex, that critically influence cancer cell features like EMT, migration and invasion

Point mutations affecting yeast prion propagation change the structure of its amyloid fibrils

We investigated the effect of the point substitutions in the N-terminal domain of the yeast prion protein Sup35 (Sup35NMp) on the structure of its amyloid fibrils. As the objects of the study, proteins with mutations that have different influence on the [PSI+] prion propagation, but do not prevent the aggregation of Sup35NMp in vitro were chosen. The use of the wide range of physico-chemical methods allowed us to show significant differences in the structure of these aggregates, their physical size, clumping tendency. Also we demonstrated that the fluorescent probe thioflavin T (ThT) can be successfully used for investigation of subtle changes in the structural organization of fibrils formed from various Sup35NMp. The obtained results and our theoretical predictions allowed us to conclude that some of selected amino acid substitutions delimit the region of the protein that forms the core of amyloid fibrils, and change the fibrils structure. The relationship of structural features of in vitro Sup35NMp amyloid aggregates with the stability of the [PSI+] prion in vivo allowed us to suggest that oligopeptide repeats (R) of the amyloidogenic N-terminal domain of Sup35NMp from R0 to R2 play a key role in protein aggregation. Their arrangement rather than just presence is critical for propagation of the strong [PSI+] prion variants. The results confirm the suitability of the proposed combination of theoretical and empirical approaches for identifying changes in the amyloid fibrils structure, which, in turn, can significantly affect both the functional stability of amyloid fibrils and their pathogenicity.Laboratorio de Investigación y Desarrollo de Bioactivo

New PNM Mutation in SUP35

A number of [PSI+]-no-more (PNM) mutations, eliminating [PSI+] prion, were previously described in SUP35. In this study, we designed and analyzed a new PNM mutation based on the parallel in-register β-structure of Sup35 prion fibrils suggested by the known experimental data. In such an arrangement, substitution of non-charged residues by charged ones may destabilize the fibril structure. We introduced Q33K/A34K amino acid substitutions into the Sup35 protein, corresponding allele was called sup35-M0. The mutagenized residues were chosen based on ArchCandy in silico prediction of high inhibitory effect on the amyloidogenic potential of Sup35. The experiments confirmed that Sup35-M0 leads to the elimination of [PSI+] with high efficiency. Our data suggested that the elimination of the [PSI+] prion is associated with the decreased aggregation properties of the protein. The new mutation can induce the prion with very low efficiency and is able to propagate only weak [PSI+] prion variants. We also showed that Sup35-M0 protein co-aggregates with the wild-type Sup35 in vivo. Moreover, our data confirmed the utility of the strategy of substitution of non-charged residues by charged ones to design new mutations to inhibit a prion formationRFBR grant 19-04-00173, RFBR grant 17-54-150002, and PRC CNRS grant PRC1524,18-34-00536, RSF grant 18-14-0005

RepeatsDB in 2021: Improved data and extended classification for protein tandem repeat structures

The RepeatsDB database (URL: https://repeatsdb.org/) provides annotations and classification for protein tandem repeat structures from the Protein Data Bank (PDB). Protein tandem repeats are ubiquitous in all branches of the tree of life. The accumulation of solved repeat structures provides new possibilities for classification and detection, but also increasing the need for annotation. Here we present RepeatsDB 3.0, which addresses these challenges and presents an extended classification scheme. The major conceptual change compared to the previous version is the hierarchical classification combining top levels based solely on structural similarity (Class > Topology > Fold) with two new levels (Clan > Family) requiring sequence similarity and describing repeat motifs in collaboration with Pfam. Data growth has been addressed with improved mechanisms for browsing the classification hierarchy. A new UniProt-centric view unifies the increasingly frequent annotation of structures from identical or similar sequences. This update of RepeatsDB aligns with our commitment to develop a resource that extracts, organizes and distributes specialized information on tandem repeat protein structures.Fil: Paladin, Lisanna. Università di Padova; ItaliaFil: Bevilacqua, Martina. Università di Padova; ItaliaFil: Errigo, Sara. Università di Padova; ItaliaFil: Piovesan, Damiano. Università di Padova; ItaliaFil: Mičetić, Ivan. Università di Padova; ItaliaFil: Necci, Marco. Università di Padova; ItaliaFil: Monzon, Alexander Miguel. Università di Padova; ItaliaFil: Fabre, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; ArgentinaFil: López, José Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; ArgentinaFil: Nilsson, Juliet Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Ciencias Biológicas; ArgentinaFil: Ríos, Javier Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Lorenzano Menna, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Cabrera, Maia Diana Eliana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: González Buitrón, Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Gonçalves Kulik, Mariane. Johannes Gutenberg Universitat Mainz; AlemaniaFil: Fernández Alberti, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Fornasari, Maria Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Parisi, Gustavo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Lagares, Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Agrarias y Forestales. Departamento de Ciencias Biológicas; ArgentinaFil: Hirsh, Layla. Pontificia Universidad Católica de Perú; PerúFil: Andrade Navarro, Miguel A.. Johannes Gutenberg Universitat Mainz; AlemaniaFil: Kajava, Andrey V. Centre National de la Recherche Scientifique; FranciaFil: Tosatto, Silvio C E. Università di Padova; Itali

Origin and Evolution of GALA-LRR, a New Member of the CC-LRR Subfamily: From Plants to Bacteria?

The phytopathogenic bacterium Ralstonia solanacearum encodes type III effectors, called GALA proteins, which contain F-box and LRR domains. The GALA LRRs do not perfectly fit any of the previously described LRR subfamilies. By applying protein sequence analysis and structural prediction, we clarify this ambiguous case of LRR classification and assign GALA-LRRs to CC-LRR subfamily. We demonstrate that side-by-side packing of LRRs in the 3D structures may control the limits of repeat variability within the LRR subfamilies during evolution. The LRR packing can be used as a criterion, complementing the repeat sequences, to classify newly identified LRR domains. Our phylogenetic analysis of F-box domains proposes the lateral gene transfer of bacterial GALA proteins from host plants. We also present an evolutionary scenario which can explain the transformation of the original plant LRRs into slightly different bacterial LRRs. The examination of the selective evolutionary pressure acting on GALA proteins suggests that the convex side of their horse-shoe shaped LRR domains is more prone to positive selection than the concave side, and we therefore hypothesize that the convex surface might be the site of protein binding relevant to the adaptor function of the F-box GALA proteins. This conclusion provides a strong background for further functional studies aimed at determining the role of these type III effectors in the virulence of R. solanacearum

A structural biology community assessment of AlphaFold2 applications

Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods for protein structure predictions have reached the accuracy of experimentally determined models. Although this has been independently verified, the implementation of these methods across structural-biology applications remains to be tested. Here, we evaluate the use of AlphaFold2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modeling of interactions; and modeling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modeled when compared with homology modeling, identifying structural features rarely seen in the Protein Data Bank. AF2-based predictions of protein disorder and complexes surpass dedicated tools, and AF2 models can be used across diverse applications equally well compared with experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life-science research