Novel Mechanism for Surface Layer Shedding and Regenerating in Bacteria Exposed to Metal-Contaminated Conditions

Surface layers (S-layers) are components of the cell walls throughout the Bacteria and the Archaea that provide protection for microorganisms against diverse environmental stresses, including metal stress. We have previously characterized the process by which S-layers serve as a nucleation site for metal mineralization in an archaeon for which the S-layer represents the only cell wall component. Here, we test the hypothesis originally proposed in cyanobacteria that a “shedding” mechanism exists for replacing S-layers that have become mineral-encrusted, using Lysinibacillus sp. TchIII 20n38, metallotolerant gram-positive bacterium, as a model organism. We characterize for the first time a mechanism for resistance to metals through S-layer shedding and regeneration. S-layers nucleate the formation of Fe-mineral on the cell surface, depending on physiological state of the cells and metal exposure times, leading to the encrustation of the S-layer and changes in the cell morphology as observed by scanning electron microscopy. Using Nanoscale Secondary Ion Mass Spectrometry, we show that mineral-encrusted S-layers are shed by the bacterial cells after a period of latency (2 days under the conditions tested) in a heterogeneous fashion likely reflecting natural variations in metal stress resistance. The emerging cells regenerate new S-layers as part of their cell wall structure. Given the wide diversity of S-layer bearing prokaryotes, S-layer shedding may represent an important mechanism for microbial survival in metal-contaminated environments

IMGT, the international ImMunoGeneTics information system®

The international ImMunoGeneTics information system® (IMGT) (http://imgt.cines.fr), created in 1989, by the Laboratoire d'ImmunoGénétique Moléculaire LIGM (Université Montpellier II and CNRS) at Montpellier, France, is a high-quality integrated knowledge resource specializing in the immunoglobulins (IGs), T cell receptors (TRs), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune systems (RPI) that belong to the immunoglobulin superfamily (IgSF) and to the MHC superfamily (MhcSF). IMGT includes several sequence databases (IMGT/LIGM-DB, IMGT/PRIMER-DB, IMGT/PROTEIN-DB and IMGT/MHC-DB), one genome database (IMGT/GENE-DB) and one three-dimensional (3D) structure database (IMGT/3Dstructure-DB), Web resources comprising 8000 HTML pages (IMGT Marie-Paule page), and interactive tools. IMGT data are expertly annotated according to the rules of the IMGT Scientific chart, based on the IMGT-ONTOLOGY concepts. IMGT tools are particularly useful for the analysis of the IG and TR repertoires in normal physiological and pathological situations. IMGT is used in medical research (autoimmune diseases, infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research, biotechnology related to antibody engineering (phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (clonalities, detection and follow up of residual diseases) and therapeutical approaches (graft, immunotherapy and vaccinology). IMGT is freely available at http://imgt.cines.fr

Considering Transposable Element Diversification in De Novo Annotation Approaches

Transposable elements (TEs) are mobile, repetitive DNA sequences that are almost ubiquitous in prokaryotic and eukaryotic genomes. They have a large impact on genome structure, function and evolution. With the recent development of high-throughput sequencing methods, many genome sequences have become available, making possible comparative studies of TE dynamics at an unprecedented scale. Several methods have been proposed for the de novo identification of TEs in sequenced genomes. Most begin with the detection of genomic repeats, but the subsequent steps for defining TE families differ. High-quality TE annotations are available for the Drosophila melanogaster and Arabidopsis thaliana genome sequences, providing a solid basis for the benchmarking of such methods. We compared the performance of specific algorithms for the clustering of interspersed repeats and found that only a particular combination of algorithms detected TE families with good recovery of the reference sequences. We then applied a new procedure for reconciling the different clustering results and classifying TE sequences. The whole approach was implemented in a pipeline using the REPET package. Finally, we show that our combined approach highlights the dynamics of well defined TE families by making it possible to identify structural variations among their copies. This approach makes it possible to annotate TE families and to study their diversification in a single analysis, improving our understanding of TE dynamics at the whole-genome scale and for diverse species

An Induced Mutation in Tomato eIF4E Leads to Immunity to Two Potyviruses

BACKGROUND: The characterization of natural recessive resistance genes and Arabidopsis virus-resistant mutants have implicated translation initiation factors of the eIF4E and eIF4G families as susceptibility factors required for virus infection and resistance function. METHODOLOGY/PRINCIPAL FINDINGS: To investigate further the role of translation initiation factors in virus resistance we set up a TILLING platform in tomato, cloned genes encoding for translation initiation factors eIF4E and eIF4G and screened for induced mutations that lead to virus resistance. A splicing mutant of the eukaryotic translation initiation factor, S.l_eIF4E1 G1485A, was identified and characterized with respect to cap binding activity and resistance spectrum. Molecular analysis of the transcript of the mutant form showed that both the second and the third exons were miss-spliced, leading to a truncated mRNA. The resulting truncated eIF4E1 protein is also impaired in cap-binding activity. The mutant line had no growth defect, likely because of functional redundancy with others eIF4E isoforms. When infected with different potyviruses, the mutant line was immune to two strains of Potato virus Y and Pepper mottle virus and susceptible to Tobacco each virus. CONCLUSIONS/SIGNIFICANCE: Mutation analysis of translation initiation factors shows that translation initiation factors of the eIF4E family are determinants of plant susceptibility to RNA viruses and viruses have adopted strategies to use different isoforms. This work also demonstrates the effectiveness of TILLING as a reverse genetics tool to improve crop species. We have also developed a complete tool that can be used for both forward and reverse genetics in tomato, for both basic science and crop improvement. By opening it to the community, we hope to fulfill the expectations of both crop breeders and scientists who are using tomato as their model of study

A simple method to predict protein binding from aligned sequences - application to MHC superfamily and beta2-microglobulin

DOWNLOAD: http://www.lirmm.fr/mab/International audienceMotivation: The MHC superfamily (MhcSF) consists of immune system MHC class I (MHC-I) proteins, along with proteins with a MHC-I-like structure that are involved in a large variety of biological processes. Beta2-microglobulin (B2M) noncovalent binding to MHC-I proteins is required for their surface expression and function, while MHC-I-like proteins interact, or not, with B2M. This study was de-signed to predict B2M binding (or non-binding) of newly identified MhcSF proteins, in order to decipher their function, understand the molecular recognition mechanisms, and identify deleterious muta-tions. IMGT standardization of MhcSF protein domains provides a unique numbering of the multiple alignment positions, and conditions to develop such predictive tool. Method: We combine a simple-Bayes classifier with IMGT unique numbering. Our method involves two steps: (1) selection of discrimi-nant binary features, which associate an alignment position with an amino acid group; (2) learning of the classifier by estimating the frequencies of selected features, conditionally to the B2M binding property. Results: Our dataset contains aligned sequences of 806 allelic forms of 47 MhcSF proteins, corresponding to 9 receptor types and 4 mammalian species. 18 discriminant features are selected, be-longing to B2M contact sites, or stabilizing the molecular structure required for this contact. Three leave-one-out procedures are used to assess classifier performance, which corresponds to B2M binding prediction for: (1) new proteins, (2) species not represented in the dataset, and (3) new receptor types. The prediction accuracy is high, i.e. 98%, 94% and 70%, respectively. Application of our classifier to lower vertebrate MHC-I proteins indicates that these proteins bind to B2M and should then be expressed on the cellular surface by a process similar to that of mammalian MHC-I proteins. These results demonstrate the usefulness and accuracy of our (simple) approach, which should apply to other function or interaction prediction prob-lems. Availability: Data and MhcSF multiple alignment are available on the IMGT website (http://imgt.cines.fr), and supplementary material is downloadable at http://imgt.igh.cnrs.fr/MhcSF-B2M.html. Contact: [email protected], [email protected], [email protected]

Digging into the 3D Structure Predictions of AlphaFold2 with Low Confidence: Disorder and Beyond

International audienceAlphaFold2 (AF2) has created a breakthrough in biology by providing three-dimensional structure models for whole-proteome sequences, with unprecedented levels of accuracy. In addition, the AF2 pLDDT score, related to the model confidence, has been shown to provide a good measure of residue-wise disorder. Here, we combined AF2 predictions with pyHCA, a tool we previously developed to identify foldable segments and estimate their order/disorder ratio, from a single protein sequence. We focused our analysis on the AF2 predictions available for 21 reference proteomes (AFDB v1), in particular on their long foldable segments (>30 amino acids) that exhibit characteristics of soluble domains, as estimated by pyHCA. Among these segments, we provided a global analysis of those with very low pLDDT values along their entire length and compared their characteristics to those of segments with very high pLDDT values. We highlighted cases containing conditional order, as well as cases that could form well-folded structures but escape the AF2 prediction due to a shallow multiple sequence alignment and/or undocumented structure or fold. AF2 and pyHCA can therefore be advantageously combined to unravel cryptic structural features in whole proteomes and to refine predictions for different flavors of disorder

A sequence‐based foldability score combined with AlphaFold2 predictions to disentangle the protein order/disorder continuum

International audienceOrder and disorder govern protein functions, but there is a great diversity in disorder, from regions that are-and stay-fully disordered to conditional order. This diversity is still difficult to decipher even though it is encoded in the amino acid sequences. Here, we developed an analytic Python package, named pyHCA, to estimate the foldability of a protein segment from the only information of its amino acid sequence and based on a measure of its density in regular secondary structures associated with hydrophobic clusters, as defined by the hydrophobic cluster analysis (HCA) approach. The tool was designed by optimizing the separation between foldable segments from databases of disorder (DisProt) and order (SCOPe [soluble domains] and OPM [transmembrane domains]). It allows to specify the ratio between order, embodied by regular secondary structures (either participating in the hydrophobic core of well-folded 3D structures or conditionally formed in intrinsically disordered regions) and disorder. We illustrated the relevance of pyHCA with several examples and applied it to the sequences of the proteomes of 21 species ranging from prokaryotes and archaea to unicellular and multicellular eukaryotes, for which structure models are provided in the AlphaFold protein structure database. Cases of low-confidence scores related to disorder were distinguished from those of sequences that we identified as foldable but are still excluded from accurate modeling by Alpha-Fold2 due to a lack of sequence homologs or to compositional biases. Overall, our approach is complementary to AlphaFold2, providing guides to map structural innovations through evolutionary processes, at proteome and gene scales