A Stenotrophomonas maltophilia TetR-Like Transcriptional Regulator Involved in Fatty Acid Metabolism Is Controlled by Quorum Sensing Signals.

Stenotrophomonas maltophilia is an environmental bacterium as well as an emerging opportunistic multidrug-resistant pathogen. They use the endogenous diffusible signal factor (DSF) quorum sensing (QS) system to coordinate population behavior and regulate virulence processes but can also respond to exogenous N-acyl-homoserine lactone (AHL) signals produced by neighboring bacteria. The effect of these QS signals on the global gene expression of this species remains, however, unknown. Whole-transcriptome sequencing analyses were performed for exponential cultures of S. maltophilia K279a treated with exogenous DSF or AHLs. Addition of DSF and AHLs signals resulted in changes in expression of at least 2-fold for 28 and 82 genes, respectively. Interestingly, 22 of these genes were found upregulated by both QS signals, 14 of which were shown to also be induced during the stationary phase. Gene functions regulated by all conditions included lipid and amino acid metabolism, stress response and signal transduction, nitrogen and iron metabolism, and adaptation to microoxic conditions. Among the common top upregulated QS core genes, a putative TetR-like regulator (locus tag SMLT2053) was selected for functional characterization. This regulator controls its own ß-oxidation operon (Smlt2053-Smlt2051), and it is found to sense long-chain fatty acids (FAs), including the QS signal DSF. Gene knockout experiments reveal that operon Smlt2053-Smlt2051 is involved in biofilm formation. Overall, our findings provide clues on the effect that QS signals have in S. maltophilia QS-related phenotypes and the transition from the exponential to the stationary phase and bacterial fitness under high-density growth. IMPORTANCE The quorum sensing system in Stenotrophomonas maltophilia, in addition to coordinating the bacterial population, controls virulence-associated phenotypes, such as biofilm formation, motility, protease production, and antibiotic resistance mechanisms. Biofilm formation is frequently associated with the persistence and chronic nature of nosocomial infections. In addition, biofilms exhibit high resistance to antibiotics, making treatment of these infections extremely difficult. The importance of studying the metabolic and regulatory systems controlled by quorum sensing autoinducers will make it possible to discover new targets to control pathogenicity mechanisms in S. maltophilia.

CNN-PepPred: an open-source tool to create convolutional NN models for the discovery of patterns in peptide sets-application to peptide-MHC class II binding prediction.

SUMMARY: The ability to unveil binding patterns in peptide sets has important applications in several biomedical areas, including the development of vaccines. We present an open-source tool, CNN-PepPred, that uses convolutional neural networks to discover such patterns, along with its application to peptide-HLA class II binding prediction. The tool can be used locally on different operating systems, with CPUs or GPUs, to train, evaluate, apply and visualize models. AVAILABILITY AND IMPLEMENTATION: CNN-PepPred is freely available as a Python tool with a detailed User's Guide at https://github.com/ComputBiol-IBB/CNN-PepPred. The site includes the peptide sets used in this study, extracted from IEDB (www.iedb.org). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CuBlock: a cross-platform normalization method for gene-expression microarrays.

MOTIVATION: Cross-(multi)platform normalization of gene-expression microarray data remains an unresolved issue. Despite the existence of several algorithms, they are either constrained by the need to normalize all samples of all platforms together, compromising scalability and reuse, by adherence to the platforms of a specific provider, or simply by poor performance. In addition, many of the methods presented in the literature have not been specifically tested against multi-platform data and/or other methods applicable in this context. Thus, we set out to develop a normalization algorithm appropriate for gene-expression studies based on multiple, potentially large microarray sets collected along multiple platforms and at different times, applicable in systematic studies aimed at extracting knowledge from the wealth of microarray data available in public repositories; for example, for the extraction of Real-World Data to complement data from Randomized Controlled Trials. Our main focus or criterion for performance was on the capacity of the algorithm to properly separate samples from different biological groups. RESULTS: We present CuBlock, an algorithm addressing this objective, together with a strategy to validate cross-platform normalization methods. To validate the algorithm and benchmark it against existing methods, we used two distinct datasets, one specifically generated for testing and standardization purposes and one from an actual experimental study. Using these datasets, we benchmarked CuBlock against ComBat (Johnson et al., 2007), UPC (Piccolo et al., 2013), YuGene (Lê Cao et al., 2014), DBNorm (Meng et al., 2017), Shambhala (Borisov et al., 2019) and a simple log2 transform as reference. We note that many other popular normalization methods are not applicable in this context. CuBlock was the only algorithm in this group that could always and clearly differentiate the underlying biological groups after mixing the data, from up to six different platforms in this study. AVAILABILITY AND IMPLEMENTATION: CuBlock can be downloaded from https://www.mathworks.com/matlabcentral/fileexchange/77882-cublock. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

On Quality Thresholds for the Clustering of Molecular Structures.

It has been recently suggested that diametral (so-called quality) similarity thresholds are superior to radial ones for the clustering of molecular three-dimensional structures (González-Alemán et al., 2020). The argument has been made for two clustering algorithms available in various software packages for the analysis of molecular structures from ensembles generated by computer simulations, attributed to Daura et al. (1999) (radial threshold) and Heyer et al. (1999) (diametral threshold). Here, we compare these two algorithms using the root-mean-squared difference (rmsd) between the Cartesian coordinates of selected atoms as pairwise similarity metric. We discuss formally the relation between these two methods and illustrate their behavior with two examples, a set of points in two dimensions and the coordinates of the tau polypeptide along a trajectory extracted from a replica-exchange molecular-dynamics simulation (Shea and Levine, 2016). We show that the two methods produce equally sized clusters as long as adequate choices are made for the respective thresholds. The real issue is not whether the threshold is radial or diametral but how to choose in either case a threshold value that is physically meaningful. We will argue that, when clustering molecular structures with the rmsd as a metric, the simplest best guess for a threshold is actually radial in nature.

On the Effect of the Various Assumptions and Approximations used in Molecular Simulations on the Properties of Bio-Molecular Systems: Overview and Perspective on Issues.

Computer simulations of molecular systems enable structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic or supra-molecular level and plays an increasingly important role in chemistry, biology and physics. To interpret the results of such simulations appropriately, the degree of uncertainty and potential errors affecting the calculated properties must be considered. Uncertainty and errors arise from (1) assumptions underlying the molecular model, force field and simulation algorithms, (2) approximations implicit in the interatomic interaction function (force field), or when integrating the equations of motion, (3) the chosen values of the parameters that determine the accuracy of the approximations used, and (4) the nature of the system and the property of interest. In this overview, advantages and shortcomings of assumptions and approximations commonly used when simulating bio-molecular systems are considered. What the developers of bio-molecular force fields and simulation software can do to facilitate and broaden research involving bio-molecular simulations is also discussed.

Interaction of camel Lactoferrin derived peptides with DNA: a molecular dynamics study.

BACKGROUND: Lactoferrampin (LFampin), Lactoferricin (LFcin), and LFchimera are three well-known antimicrobial peptides derived from Lactoferrin and proposed as alternatives for antibiotics. Although the intracellular activity of these peptides has been previously demonstrated, their mode of action is not yet fully understood. Here, we performed a molecular dynamics simulation study to understand the molecular interactions between camel Lactoferrin derived peptides, including CLFampin, CLFcin, and CLFchimera, and DNA as an important intracellular target. RESULTS: Our results indicate that all three peptides bind to DNA, albeit with different propensities, with CLFchimera showing the highest binding affinity. The secondary structures of the peptides, modeled on Lactoferrin, did not undergo significant changes during simulation, supporting their functional relevance. Main residues involved in the peptide-DNA interaction were identified based on binding free energy estimates calculated over 200 ns, which, as expected, confirmed strong electrostatic interactions between DNA phosphate groups and positively charged peptide side chains. Interaction between the different concentrations of CLFchimera and DNA revealed that after binding of four copies of CLFchimera to DNA, hydrogen bonds between the two strands of DNA start to break from one of the termini. CONCLUSIONS: Importantly, our results revealed that there is no DNA-sequence preference for peptide binding, in line with a broad antimicrobial activity. Moreover, the results showed that the strength of the interaction between DNA and CLFchimera is concentration dependent. The insight provided by these results can be used for the rational redesign of natural antimicrobial peptides targeting the bacterial DNA.

Advances in the Computational Identification of Allosteric Sites and Pathways in Proteins.

With the increasing difficulty to develop new drugs and the emergence of resistance to traditional orthosteric-site inhibitors, the search for alternatives is finally approaching the focus on allosteric sites. Allosteric sites offer opportunities to regulate many pharmacologically targeted pathways by inhibition or activation. In addition, allosteric sites tend to be less conserved than the functional site, which may facilitate the design of specific effectors in the protein families for which specific orthosteric inhibitors have proved difficult to design. Furthermore, recent evidence suggests that all proteins might be susceptible of allosteric regulation, increasing the space of druggable targets. Computational identification of allosteric sites has therefore become an active field of research. The problem can be approached from two sides: (1) the identification of allosteric-communication pathways between the functional site and potential allosteric sites and (2) the functional-site-independent identification of allosteric sites. While the first approach tends to be more laborious and thus restricted to a single protein, the second tends to be more amenable to larger-scale analysis, thus providing tools for the two drug discovery scenarios: the analysis of known targets and the screening for new potential targets. Here, I show some basic concepts and methods useful to the identification of allosteric sites and pathways, in line with these two approaches. I describe them in some detail to build a clear framework, at the risk of losing the interest of experts. Examples of recent studies involving these methods are also illustrated, focusing on the techniques rather than on their findings on allosterism.

Validation of Molecular Simulation: An Overview of Issues.

Computer simulation of molecular systems enables structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic, or supra-molecular level. To interpret results of such simulations appropriately, the quality of the calculated properties must be evaluated. This depends on the way the simulations are performed and on the way they are validated by comparison to values Qexp of experimentally observable quantities Q. One must consider 1) the accuracy of Qexp , 2) the accuracy of the function Q(rN ) used to calculate a Q-value based on a molecular configuration rN of N particles, 3) the sensitivity of the function Q(rN ) to the configuration rN , 4) the relative time scales of the simulation and experiment, 5) the degree to which the calculated and experimental properties are equivalent, and 6) the degree to which the system simulated matches the experimental conditions. Experimental data is limited in scope and generally corresponds to averages over both time and space. A critical analysis of the various factors influencing the apparent degree of (dis)agreement between simulations and experiment is presented and illustrated using examples from the literature. What can be done to enhance the validation of molecular simulation is also discussed.

Molecular dynamics simulation study of the effect of glycerol dialkyl glycerol tetraether hydroxylation on membrane thermostability.

Archaeal tetraether membrane lipids span the whole membrane width and present two C40 isoprenoid chains bound by two glycerol groups (or one glycerol and calditol). These lipids confer stability and maintain the membrane fluidity in mesophile to extremophile environments, making them very attractive for biotechnological applications. The isoprenoid lipid composition in archaeal membranes varies with temperature, which has placed these lipids in the focus of paleo-climatological studies for over a decade. Non-hydroxylated isoprenoid archaeal lipids are typically used as paleo-thermometry proxies, but recently identified hydroxylated (OH) derivatives have also been proposed as temperature proxies. The relative abundance of hydroxylated lipids increases at lower temperatures, but the physiological function of the OH moiety remains unknown. Here we present molecular dynamics simulations of membranes formed by the acyclic glycerol-dialkyl-glycerol-tetraether caldarchaeol (GDGT-0), the most widespread archaeal core lipid, and its mono-hydroxylated variant (OH-GDGT-0) to better understand the physico-chemical properties conferred to the membrane by this additional moiety. The molecular dynamics simulations indicate that the additional OH group forms hydrogen bonds mainly with the sugar moieties of neighbouring lipids and with water molecules, effectively increasing the size of the polar headgroups. The hydroxylation also introduces local disorder that propagates along the entire alkyl chains, resulting in a slightly more fluid membrane. These changes would help to maintain trans-membrane transport in cold environments, explaining why the relative abundance of hydroxylated Archaea lipids increases at lower temperatures. The in silico approach aids to understand the underlying physiological mechanisms behind the hydroxylated lipid based paleo-thermometer recently proposed.

A Bowman-Birk protease inhibitor purified, cloned, sequenced and characterized from the seeds of Maclura pomifera (Raf.) Schneid.

MAIN CONCLUSION: A new BBI-type protease inhibitor with remarkable structural characteristics was purified, cloned, and sequenced from seeds of Maclura pomifera , a dicotyledonous plant belonging to the Moraceae family. In this work, we report a Bowman-Birk inhibitor (BBI) isolated, purified, cloned, and characterized from Maclura pomifera seeds (MpBBI), the first of this type from a species belonging to Moraceae family. MpBBI was purified to homogeneity by RP-HPLC, total RNA was extracted from seeds of M. pomifera, and the 3'RACE-PCR method was applied to obtain the cDNA, which was cloned and sequenced. Peptide mass fingerprinting (PMF) analysis showed correspondence between the in silico-translated protein and MpBBI, confirming that it corresponds to a new plant protease inhibitor. The obtained cDNA encoded a polypeptide of 65 residues and possesses 10 cysteine residues, with molecular mass of 7379.27, pI 6.10, and extinction molar coefficient of 9105 M-1 cm-1. MpBBI inhibits strongly trypsin with K i in the 10-10 M range and was stable in a wide array of pH and extreme temperatures. MpBBI comparative modeling was applied to gain insight into its 3D structure and highlighted some distinguishing features: (1) two non-identical loops, (2) loop 1 (CEEESRC) is completely different from any known BBI, and (3) the amount of disulphide bonds is also different from any reported BBI from dicot plants.

PrionW: a server to identify proteins containing glutamine/asparagine rich prion-like domains and their amyloid cores.

Prions are a particular type of amyloids with the ability to self-perpetuate and propagate in vivo. Prion-like conversion underlies important biological processes but is also connected to human disease. Yeast prions are the best understood transmissible amyloids. In these proteins, prion formation from an initially soluble state involves a structural conversion, driven, in many cases, by specific domains enriched in glutamine/asparagine (Q/N) residues. Importantly, domains sharing this compositional bias are also present in the proteomes of higher organisms, thus suggesting that prion-like conversion might be an evolutionary conserved mechanism. We have recently shown that the identification and evaluation of the potency of amyloid nucleating sequences in putative prion domains allows discrimination of genuine prions. PrionW is a web application that exploits this principle to scan sequences in order to identify proteins containing Q/N enriched prion-like domains (PrLDs) in large datasets. When used to scan the complete yeast proteome, PrionW identifies previously experimentally validated prions with high accuracy. Users can analyze up to 10 000 sequences at a time, PrLD-containing proteins are identified and their putative PrLDs and amyloid nucleating cores visualized and scored. The output files can be downloaded for further analysis. PrionW server can be accessed at http://bioinf.uab.cat/prionw/.

Effect of Oxidative Damage on the Stability and Dimerization of Superoxide Dismutase 1.

During their life cycle, proteins are subject to different modifications involving reactive oxygen species. Such oxidative damage to proteins may lead to the formation of insoluble aggregates and cytotoxicity and is associated with age-related disorders including neurodegenerative diseases, cancer, and diabetes. Superoxide dismutase 1 (SOD1), a key antioxidant enzyme in human cells, is particularly susceptible to such modifications. Moreover, this homodimeric metalloenzyme has been directly linked to both familial and sporadic amyotrophic lateral sclerosis (ALS), a devastating, late-onset motor neuronal disease, with more than 150 ALS-related mutations in the SOD1 gene. Importantly, oxidatively damaged SOD1 aggregates have been observed in both familial and sporadic forms of the disease. However, the molecular mechanisms as well as potential implications of oxidative stress in SOD1-induced cytotoxicity remain elusive. In this study, we examine the effects of oxidative modification on SOD1 monomer and homodimer stability, the key molecular properties related to SOD1 aggregation. We use molecular dynamics simulations in combination with thermodynamic integration to study microscopic-level site-specific effects of oxidative "mutations" at the dimer interface, including lysine, arginine, proline and threonine carbonylation, and cysteine oxidation. Our results show that oxidative damage of even single residues at the interface may drastically destabilize the SOD1 homodimer, with several modifications exhibiting a comparable effect to that of the most drastic ALS-causing mutations known. Additionally, we show that the SOD1 monomer stability decreases upon oxidative stress, which may lead to partial local unfolding and consequently to increased aggregation propensity. Importantly, these results suggest that oxidative stress may play a key role in development of ALS, with the mutations in the SOD1 gene being an additional factor.

Deriving Structural Information from Experimentally Measured Data on Biomolecules.

During the past half century, the number and accuracy of experimental techniques that can deliver values of observables for biomolecular systems have been steadily increasing. The conversion of a measured value Qexp of an observable quantity Q into structural information is, however, a task beset with theoretical and practical problems: 1) insufficient or inaccurate values of Qexp , 2) inaccuracies in the function Q(r→) used to relate the quantity Q to structure r→ , 3) how to account for the averaging inherent in the measurement of Qexp , 4) how to handle the possible multiple-valuedness of the inverse r→(Q) of the function Q(r→) , to mention a few. These apply to a variety of observable quantities Q and measurement techniques such as X-ray and neutron diffraction, small-angle and wide-angle X-ray scattering, free-electron laser imaging, cryo-electron microscopy, nuclear magnetic resonance, electron paramagnetic resonance, infrared and Raman spectroscopy, circular dichroism, Förster resonance energy transfer, atomic force microscopy and ion-mobility mass spectrometry. The process of deriving structural information from measured data is reviewed with an eye to non-experts and newcomers in the field using examples from the literature of the effect of the various choices and approximations involved in the process. A list of choices to be avoided is provided.

PARS: a web server for the prediction of Protein Allosteric and Regulatory Sites.

The regulation of protein activity is a key aspect of life at the molecular level. Unveiling its details is thus crucial to understanding signalling and metabolic pathways. The most common and powerful mechanism of protein-function regulation is allostery, which has been increasingly calling the attention of medicinal chemists due to its potential for the discovery of novel therapeutics. In this context, PARS is a simple and fast method that queries protein dynamics and structural conservation to identify pockets on a protein structure that may exert a regulatory effect on the binding of a small-molecule ligand.

Two different rpf clusters distributed among a population of Stenotrophomonas maltophilia clinical strains display differential diffusible signal factor production and virulence regulation.

The quorum-sensing (QS) system present in the emerging nosocomial pathogen Stenotrophomonas maltophilia is based on the signaling molecule diffusible signal factor (DSF). Production and detection of DSF are governed by the rpf cluster, which encodes the synthase RpfF and the sensor RpfC, among other components. Despite a well-studied system, little is known about its implication in virulence regulation in S. maltophilia. Here, we have analyzed the rpfF gene from 82 S. maltophilia clinical isolates. Although rpfF was found to be present in all of the strains, it showed substantial variation, with two populations (rpfF-1 and rpfF-2) clearly distinguishable by the N-terminal region of the protein. Analysis of rpfC in seven complete genome sequences revealed a corresponding variability in the N-terminal transmembrane domain of its product, suggesting that each RpfF variant has an associated RpfC variant. We show that only RpfC-RpfF-1 variant strains display detectable DSF production. Heterologous rpfF complementation of ΔrpfF mutants of a representative strain of each variant suggests that RpfF-2 is, however, functional and that the observed DSF-deficient phenotype of RpfC-RpfF-2 variant strains is due to permanent repression of RpfF-2 by RpfC-2. This is corroborated by the ΔrpfC mutant of the RpfC-RpfF-2 representative strain. In line with this observations, deletion of rpfF from the RpfC-RpfF-1 strain leads to an increase in biofilm formation, a decrease in swarming motility, and relative attenuation in the Caenorhabditis elegans and zebrafish infection models, whereas deletion of the same gene from the representative RpfC-RpfF-2 strain has no significant effect on these virulence-related phenotypes.

antibacTR: dynamic antibacterial-drug-target ranking integrating comparative genomics, structural analysis and experimental annotation.

BACKGROUND: Development of novel antibacterial drugs is both an urgent healthcare necessity and a partially neglected field. The last decades have seen a substantial decrease in the discovery of novel antibiotics, which combined with the recent thrive of multi-drug-resistant pathogens have generated a scenario of general concern. The procedures involved in the discovery and development of novel antibiotics are economically challenging, time consuming and lack any warranty of success. Furthermore, the return-on-investment for an antibacterial drug is usually marginal when compared to other therapeutics, which in part explains the decrease of private investment. RESULTS: In this work we present antibacTR, a computational pipeline designed to aid researchers in the selection of potential drug targets, one of the initial steps in antibacterial-drug discovery. The approach was designed and implemented as part of two publicly funded initiatives aimed at discovering novel antibacterial targets, mechanisms and drugs for a priority list of Gram-negative pathogens: Acinetobacter baumannii, Escherichia coli, Helicobacter pylori, Pseudomonas aeruginosa and Stenotrophomonas maltophilia. However, at present this list has been extended to cover a total of 74 fully sequenced Gram-negative pathogens. antibacTR is based on sequence comparisons and queries to multiple databases (e.g. gene essentiality, virulence factors) to rank proteins according to their potential as antibacterial targets. The dynamic ranking of potential drug targets can easily be executed, customized and accessed by the user through a web interface which also integrates computational analyses performed in-house and visualizable on-site. These include three-dimensional modeling of protein structures and prediction of active sites among other functionally relevant ligand-binding sites. CONCLUSIONS: Given its versatility and ease-of-use at integrating both experimental annotation and computational analyses, antibacTR may effectively assist microbiologists, medicinal-chemists and other researchers working in the field of antibacterial drug-discovery. The public web-interface for antibacTR is available at 'http://bioinf.uab.cat/antibactr'.

Understanding the molecular determinants driving the immunological specificity of the protective pilus 2a backbone protein of group B streptococcus.

The pilus 2a backbone protein (BP-2a) is one of the most structurally and functionally characterized components of a potential vaccine formulation against Group B Streptococcus. It is characterized by six main immunologically distinct allelic variants, each inducing variant-specific protection. To investigate the molecular determinants driving the variant immunogenic specificity of BP-2a, in terms of single residue contributions, we generated six monoclonal antibodies against a specific protein variant based on their capability to recognize the polymerized pili structure on the bacterial surface. Three mAbs were also able to induce complement-dependent opsonophagocytosis killing of live GBS and target the same linear epitope present in the structurally defined and immunodominant domain D3 of the protein. Molecular docking between the modelled scFv antibody sequences and the BP-2a crystal structure revealed the potential role at the binding interface of some non-conserved antigen residues. Mutagenesis analysis confirmed the necessity of a perfect balance between charges, size and polarity at the binding interface to obtain specific binding of mAbs to the protein antigen for a neutralizing response.

Sheltering DNA in self-organizing, protein-only nano-shells as artificial viruses for gene delivery.

By recruiting functional domains supporting DNA condensation, cell binding, internalization, endosomal escape and nuclear transport, modular single-chain polypeptides can be tailored to associate with cargo DNA for cell-targeted gene therapy. Recently, an emerging architectonic principle at the nanoscale has permitted tagging protein monomers for self-organization as protein-only nanoparticles. We have studied here the accommodation of plasmid DNA into protein nanoparticles assembled with the synergistic assistance of end terminal poly-arginines (R9) and poly-histidines (H6). Data indicate a virus-like organization of the complexes, in which a DNA core is surrounded by a solvent-exposed protein layer. This finding validates end-terminal cationic peptides as pleiotropic tags in protein building blocks for the mimicry of viral architecture in artificial viruses, representing a promising alternative to the conventional use of viruses and virus-like particles for nanomedicine and gene therapy. FROM THE CLINICAL EDITOR: Finding efficient gene delivery methods still represents a challenge and is one of the bottlenecks to the more widespread application of gene therapy. The findings presented in this paper validate the application of end-terminal cationic peptides as pleiotropic tags in protein building blocks for "viral architecture mimicking" in artificial viruses, representing a promising alternative to the use of viruses and virus-like particles for gene delivery.

The Mla system and its role in maintaining outer membrane barrier function in Stenotrophomonas maltophilia.

Stenotrophomonas maltophilia are ubiquitous Gram-negative bacteria found in both natural and clinical environments. It is a remarkably adaptable species capable of thriving in various environments, thanks to the plasticity of its genome and a diverse array of genes that encode a wide range of functions. Among these functions, one notable trait is its remarkable ability to resist various antimicrobial agents, primarily through mechanisms that regulate the diffusion across cell membranes. We have investigated the Mla ABC transport system of S. maltophilia, which in other Gram-negative bacteria is known to transport phospholipids across the periplasm and is involved in maintaining outer membrane homeostasis. First, we structurally and functionally characterized the periplasmic substrate-binding protein MlaC, which determines the specificity of this system. The predicted structure of the S. maltophilia MlaC protein revealed a hydrophobic cavity of sufficient size to accommodate the phospholipids commonly found in this species. Moreover, recombinant MlaC produced heterologously demonstrated the ability to bind phospholipids. Gene knockout experiments in S. maltophilia K279a revealed that the Mla system is involved in baseline resistance to antimicrobial and antibiofilm agents, especially those with divalent-cation chelating activity. Co-culture experiments with Pseudomonas aeruginosa also showed a significant contribution of this system to the cooperation between both species in the formation of polymicrobial biofilms. As suggested for other Gram-negative pathogenic microorganisms, this system emerges as an appealing target for potential combined antimicrobial therapies.

Crystal structure of c5321: a protective antigen present in uropathogenic Escherichia coli strains displaying an SLR fold.

BACKGROUND: Increasing rates of antimicrobial resistance among uropathogens led, among other efforts, to the application of subtractive reverse vaccinology for the identification of antigens present in extraintestinal pathogenic E. coli (ExPEC) strains but absent or variable in non-pathogenic strains, in a quest for a broadly protective Escherichia coli vaccine. The protein coded by locus c5321 from CFT073 E. coli was identified as one of nine potential vaccine candidates against ExPEC and was able to confer protection with an efficacy of 33% in a mouse model of sepsis. c5321 (known also as EsiB) lacks functional annotation and structurally belongs to the Sel1-like repeat (SLR) family. Herein, as part of the general characterization of this potential antigen, we have focused on its structural properties. RESULTS: We report the 1.74 Å-resolution crystal structure of c5321 from CFT073 E. coli determined by Se-Met SAD phasing. The structure is composed of 11 SLR units in a topological organisation that highly resembles that found in HcpC from Helicobacter pylori, with the main difference residing in how the super-helical fold is stabilised. The stabilising effect of disulfide bridges in HcpC is replaced in c5321 by a strengthening of the inter-repeat hydrophobic core. A metal-ion binding site, uncharacteristic of SLR proteins, is detected between SLR units 3 and 4 in the region of the inter-repeat hydrophobic core. Crystal contacts are observed between the C-terminal tail of one molecule and the C-terminal amphipathic groove of a neighbouring one, resembling interactions between ligand and proteins containing tetratricopeptide-like repeats. CONCLUSIONS: The structure of antigen c5321 presents a mode of stabilization of the SLR fold different from that observed in close homologs of known structure. The location of the metal-ion binding site and the observed crystal contacts suggest a potential role in regulation of conformational flexibility and interaction with yet unidentified target proteins, respectively. These findings open new perspectives in both antigen design and for the identification of a functional role for this protective antigen.