Identification of a Wide Range of Motifs Inhibitory to Shiga Toxin by Affinity-Driven Screening of Customized Divalent Peptides Synthesized on a Membrane

Shiga toxin (Stx), a major virulence factor of enterohemorrhagic Escherichia coli, binds to target cells through a multivalent interaction between its B-subunit pentamer and the cell surface receptor globotriaosylceramide, resulting in a remarkable increase in its binding affinity. This phenomenon is referred to as the “clustering effect.” Previously, we developed a multivalent peptide library that can exert the clustering effect and identified Stx neutralizers with tetravalent peptides by screening this library for high-affinity binding to the specific receptor-binding site of the B subunit. However, this technique yielded only a limited number of binding motifs, with some redundancy in amino acid selectivity. In this study, we established a novel technique to synthesize up to 384 divalent peptides whose structures were customized to exert the clustering effect on the B subunit on a single cellulose membrane. By targeting Stx1a, a major Stx subtype, the customized divalent peptides were screened to identify high-affinity binding motifs. The sequences of the peptides were designed based on information obtained from the multivalent peptide library technique. A total of 64 candidate motifs were successfully identified, and 11 of these were selected to synthesize tetravalent forms of the peptides. All of the synthesized tetravalent peptides bound to the B subunit with high affinities and effectively inhibited the cytotoxicity of Stx1a in Vero cells. Thus, the combination of the two techniques results in greatly improved efficiency in identifying biologically active neutralizers of Stx.     

Identification and evaluation of a novel peptide binding to the cell surface of Staphylococcus aureus

Identification of short peptides that serve as specific ligands to biological materials such as microbial cell surfaces has major implications in better understanding the molecular recognition of cell surfaces. In this study we screened a commercially available random phage-display library against Staphylococcus aureus cells and identified peptides specifically binding to the bacteria. A synthetic peptide (SA5-1) representing the consensus sequence (VPHNPGLISLQG) of the bacteria-binding peptide was evaluated for its binding potential against S. aureus. Dot-blot, immunoblot assay and ELISA results revealed the SA5-1 peptide to be highly specific to S. aureus. The SA5-1 peptide binding was optimal between pH 6.0 and 8.0. Nanogold Transmission Electron Microscopy demonstrated that the SA5-1 binds to the outer membrane surface of S. aureus. Diagnostic potential of the SA5-1 peptide was evaluated in human platelet samples spiked with S. aureus and specific detection of the bacteria by biotinylated-SA5-1 and streptavidin-conjugated fluorescent quantum dots. Fluorometry results indicated that the peptide was able to detect ～100 organisms per ml in a spiked biological sample providing a proof-of-concept towards potential of this peptide as a S. aureus diagnostic tool that can be of use in different detection platforms.     

Classification and analysis of regulatory pathways using graph property, biochemical and physicochemical property, and functional property

Given a regulatory pathway system consisting of a set of proteins, can we predict which pathway class it belongs to? Such a problem is closely related to the biological function of the pathway in cells and hence is quite fundamental and essential in systems biology and proteomics. This is also an extremely difficult and challenging problem due to its complexity. To address this problem, a novel approach was developed that can be used to predict query pathways among the following six functional categories: (i) “Metabolism”, (ii) “Genetic Information Processing”, (iii) “Environmental Information Processing”, (iv) “Cellular Processes”, (v) “Organismal Systems”, and (vi) “Human Diseases”. The prediction method was established trough the following procedures: (i) according to the general form of pseudo amino acid composition (PseAAC), each of the pathways concerned is formulated as a 5570-D (dimensional) vector; (ii) each of components in the 5570-D vector was derived by a series of feature extractions from the pathway system according to its graphic property, biochemical and physicochemical property, as well as functional property; (iii) the minimum redundancy maximum relevance (mRMR) method was adopted to operate the prediction. A cross-validation by the jackknife test on a benchmark dataset consisting of 146 regulatory pathways indicated that an overall success rate of 78.8% was achieved by our method in identifying query pathways among the above six classes, indicating the outcome is quite promising and encouraging. To the best of our knowledge, the current study represents the first effort in attempting to identity the type of a pathway system or its biological function. It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area.     

A human synthetic combinatorial library of arrayable single-chain antibodies based on shuffling in vivo formed CDRs into general framework regions

We describe a novel approach for high-throughput screening of recombinant antibodies, based on their immobilization on solid cellulose-based supports. We constructed a large human synthetic single-chain Fv antibody library where in vivo formed complementarity determining regions were shuffled combinatorially onto germline-derived human variable-region frameworks. The arraying of library-derived scFvs was facilitated by our unique display/expression system, where scFvs are expressed as fusion proteins with a cellulose-binding domain (CBD). Escherichia coli cells expressing library-derived scFv-CBDs are grown on a porous master filter on top of a second cellulose-based filter that captures the antibodies secreted by the bacteria. The cellulose filter is probed with labeled antigen allowing the identification of specific binders and the recovery of the original bacterial clones from the master filter. These filters may be simultaneously probed with a number of antigens allowing the isolation of a number of binding specificities and the validation of specificity of binders. We screened the library against a number of cancer-related peptides, proteins, and peptide-protein complexes and yielded antibody fragments exhibiting dissociation constants in the low nanomolar range. We expect our new antibody phage library to become a valuable source of antibodies to many different targets, and to play a vital role in facilitating high-throughput target discovery and validation in the area of functional cancer genomics.     

Yeast display platform with expression of linear peptide epitopes for high-throughput assessment of peptide-MHC-II binding

Yeast display can serve as a powerful tool to assess the binding of peptides to the major histocompatibility complex (pMHC) and pMHC-T-cell receptor binding. However, this approach is often limited by the need to optimize MHC proteins for yeast surface expression, which can be laborious and may not yield productive results. Here we present a second-generation yeast display platform for class II MHC molecules (MHC-II), which decouples MHC-II expression from yeast-expressed peptides, referred to as “peptide display.” Peptide display obviates the need for yeast-specific MHC optimizations and increases the scale of MHC-II alleles available for use in yeast display screens. Because MHC identity is separated from the peptide library, a further benefit of this platform is the ability to assess a single library of peptides against any MHC-II. We demonstrate the utility of the peptide display platform across MHC-II proteins, screening HLA-DR, HLA-DP, and HLA-DQ alleles. We further explore parameters of selections, including reagent dependencies, MHC avidity, and use of competitor peptides. In summary, this approach presents an advance in the throughput and accessibility of screening peptide-MHC-II binding.     

Proline Is Not Uniquely Capable of Providing the Pivot Point for Domain Swapping in 2G12, a Broadly Neutralizing Antibody against HIV-1

The human monoclonal antibody 2G12 is a member of a small group of broadly neutralizing antibodies against human immunodeficiency virus type 1. 2G12 adopts a unique variable heavy domain-exchanged dimeric configuration that results in an extensive multivalent binding surface and the ability to bind with high affinity to densely clustered high mannose oligosaccharides on the “silent” face of the gp120 envelope glycoprotein. Here, we further define the amino acids responsible for this extraordinary domain-swapping event in 2G12.     

Misrepresentation of Randomized Controlled Trials in Press Releases and News Coverage: A Cohort Study

Background

Previous studies indicate that in published reports, trial results can be distorted by the use of “spin” (specific reporting strategies, intentional or unintentional, emphasizing the beneficial effect of the experimental treatment). We aimed to (1) evaluate the presence of “spin” in press releases and associated media coverage; and (2) evaluate whether findings of randomized controlled trials (RCTs) based on press releases and media coverage are misinterpreted.

Methods and Findings

We systematically searched for all press releases indexed in the EurekAlert! database between December 2009 and March 2010. Of the 498 press releases retrieved and screened, we included press releases for all two-arm, parallel-group RCTs (n = 70). We obtained a copy of the scientific article to which the press release related and we systematically searched for related news items using Lexis Nexis.“Spin,” defined as specific reporting strategies (intentional or unintentional) emphasizing the beneficial effect of the experimental treatment, was identified in 28 (40%) scientific article abstract conclusions and in 33 (47%) press releases. From bivariate and multivariable analysis assessing the journal type, funding source, sample size, type of treatment (drug or other), results of the primary outcomes (all nonstatistically significant versus other), author of the press release, and the presence of “spin” in the abstract conclusion, the only factor associated, with “spin” in the press release was “spin” in the article abstract conclusions (relative risk [RR] 5.6, [95% CI 2.8–11.1], p<0.001). Findings of RCTs based on press releases were overestimated for 19 (27%) reports. News items were identified for 41 RCTs; 21 (51%) were reported with “spin,” mainly the same type of “spin” as those identified in the press release and article abstract conclusion. Findings of RCTs based on the news item was overestimated for ten (24%) reports.

Conclusion

“Spin” was identified in about half of press releases and media coverage. In multivariable analysis, the main factor associated with “spin” in press releases was the presence of “spin” in the article abstract conclusion.     

Identification of mimotopes with diagnostic potential for Trypanosoma brucei gambiense variant surface glycoproteins using human antibody fractions

Background

At present, screening of the population at risk for gambiense human African trypanosomiasis (HAT) is based on detection of antibodies against native variant surface glycoproteins (VSGs) of Trypanosoma brucei (T.b.) gambiense. Drawbacks of these native VSGs include culture of infective T.b. gambiense trypanosomes in laboratory rodents, necessary for production, and the exposure of non-specific epitopes that may cause cross-reactions. We therefore aimed at identifying peptides that mimic epitopes, hence called “mimotopes,” specific to T.b. gambiense VSGs and that may replace the native proteins in antibody detection tests.

Methodology/Principal Findings

A Ph.D.-12 peptide phage display library was screened with polyclonal antibodies from patient sera, previously affinity purified on VSG LiTat 1.3 or LiTat 1.5. The peptide sequences were derived from the DNA sequence of the selected phages and synthesised as biotinylated peptides. Respectively, eighteen and twenty different mimotopes were identified for VSG LiTat 1.3 and LiTat 1.5, of which six and five were retained for assessment of their diagnostic performance. Based on alignment of the peptide sequences on the original protein sequence of VSG LiTat 1.3 and 1.5, three additional peptides were synthesised. We evaluated the diagnostic performance of the synthetic peptides in indirect ELISA with 102 sera from HAT patients and 102 endemic negative controls. All mimotopes had areas under the curve (AUCs) of ≥0.85, indicating their diagnostic potential. One peptide corresponding to the VSG LiTat 1.3 protein sequence also had an AUC of ≥0.85, while the peptide based on the sequence of VSG LiTat 1.5 had an AUC of only 0.79.

Conclusions/Significance

We delivered the proof of principle that mimotopes for T.b. gambiense VSGs, with diagnostic potential, can be selected by phage display using polyclonal human antibodies.     

THE LONDON LETTER

Animals subjected to seemingly insoluble conflicts of motivation and difficulties of adaptation develop persistent “neuroses” or “psychoses” characterized by dramatic manifestations of anxiety, phobias, compulsions, and “dereism”. Of all techniques of therapy investigated, the following were found to be variously effective in alleviating the disordered behaviour: (1) rest and change of milieu, (2) diminution of motivational stress, (3) spontaneous re-exploration, (4) forced solution of the conflict, (5) association with “normal” animals, (6) guided retraining and individualized re-experience, (7) drugs such as alcohol or the barbiturates that blunted or dissociated traumatic experiences, (8) cerebral electroshock, and (9) certain cerebral operations. Predictably, various combinations of these procedures were differently effective, depending on both the “constitution” and life experiences of the animal. The significance of these observations with regard to the biodynamics of clinical psychiatric treatment are discussed as well as those modes of psychotherapy which are “uniquely” human.     

围小丛壳Glomerella cingulata子囊孢子交配繁殖、生物学特性及致病性

炭疽叶枯病（Glomerella leaf spot）是我国苹果上新发现的一种病害。为了解围小丛壳Glomerella cingulata子囊孢子的交配方式、生物学特性和致病性,从安徽砀山、山东牟平等地采集病害样品,经分离培养和纯化获得单孢菌株。在适宜条件下单孢菌株可产生子囊和子囊孢子,经过毛细管破子囊壁后单孢分离,获得12个子囊,每个子囊有8个子囊孢子。其中10个子囊中有4个“正”孢子（+）和4个“负”孢子（-）,2个子囊中只有“负”孢子。子囊孢子单孢菌株培养72h,“正”菌株菌落白色,以营养生长为主;“负”菌株菌落灰白色,直径略小于正菌株,菌丝稀疏,边缘菌丝白色,中部有大量橙色的分生孢子堆。“正”、“负”菌株异宗配合后,可产生大量可育子囊壳;单独的“正”菌株有性生殖产生稀疏丛簇状的可育子囊壳;单个的“负”菌株只能产生分散且不育的子囊壳。“正”、“负”菌株菌落的生长速度没有差异,对温度、营养、光照和pH值的敏感性也没有差异,但“正”、“负”菌株的致病性存在差异。正菌株的有性生殖没有导致rDNA-ITS、β-tubulin基因碱基序列变异。     

Human intuition in the quantitative age

Modern computing power grants scientists the ability to crunch previously impossible amounts of data. Nevertheless, the human brain has not yet been replaced as the engine of design and discovery.Biologists first dipped their toes into the waters of mathematics when Gregor Mendel developed his laws of trait inheritance in the mid-nineteenth century. Since then, statistics and computation have come to play an important part in almost all aspects of applied and fundamental research. The power of number crunching has even led to questions about the role of traditional observation or insight in experimentation, with a concomitant concern that over-reliance on mathematics might lead researchers to lazily follow preconceived ideas, or to ignore inconvenient data that actually indicate that a theory needs modification.Lars Jensen, a group leader in Disease Systems Biology at the Novo Nordisk Foundation (NNF) Centre for Protein Research at the University of Copenhagen in Denmark, takes this position. “It is, in my opinion, a risk that has always been there and still is there in the mathematical era,” he commented. “If researchers have a preconceived idea about how the results of an experiment should be, they may be tempted to classify observations as outliers if they do not fit the expectations.”“If researchers have a preconceived idea about how the results of an experiment should be, they may be tempted to classify observations as outliers if they do not fit the expectations”As such, the risk that statistics trump observation has to be considered carefully, but should not turn back the tide of computation and analysis in biology. Jeremy Nicholson, head of the Department of Surgery and Cancer in the Faculty of Medicine at Imperial College London, UK, argues that only the application of mathematics can show if the results of an experiment are true. “The only proof of biological activity is either in statistics, which of course goes back a long way, or geometry, as used in physical anthropology,” he said.…almost every biological state […] has an associated pattern of relative molecular concentrations […] these signatures can be detected against the background of normal cellular functionThe role of mathematics in biological analysis is expanding, particularly with the advent of the various ‘omics'' fields. Multivariate statistics, for example, allows the simultaneous analysis of variables—such as the expression levels of several genes—which makes it possible to draw simple inferences from complex data sets. This analysis can be performed not only on the expression of the genes themselves, but also downstream, on the behaviour of the gene products; reflected, for example, in the molecular composition of a blood or tissue sample. This, Nicholson argues, has led to progress in the emerging field of surgical metabonomics, which he defines as a systems approach to examining changes in hundreds or thousands of low-molecular-weight metabolites in an intact tissue or biofluid. “Our biggest recent advances in thinking are in surgical metabonomics and real-time profiling,” he said, adding that these techniques will have a huge impact on diagnosis and surgical procedures.The key point is that almost every biological state—be it a specific cancer or a metabolic condition, such as diabetes—has an associated pattern of relative molecular concentrations in cells and tissues. In principle, these signatures can be detected against the background of normal cellular function. The data usually come from nuclear magnetic resonance or mass spectrometry analyses, which yield spectral peaks and troughs relating to the identity and relative proportions of the molecular constituents of the sample. The immediate objective is not to identify individual molecules, but to analyse the overall pattern of the components. The components are usually moieties of larger molecules, such as hydroxyl or amino groups, which yield characteristic peaks. However, because different molecules have groups in common, it is not immediately possible to identify the exact contents of a sample.…the mathematical tools underlying many […] methods are based on Bayes theorem [which] allows mathematicians to calculate the probability of a prior event on the basis of […] data that emerges afterwards“A typical example is where one is looking for biomarkers of a disease,” explained Tim Ebbels, a senior lecturer in computational bioinformatics at Imperial College London. “You compare profiles from normal people against those with the disease and ask the question: which molecules change in concentration between the two groups?”In the past, this analysis would have been done using a statistical technique such as a t-test, which compares just two variables at a time. The limitation is obvious: the test cannot detect small differences in concentration between many molecules. This is where modern, so-called ‘latent-variable'' techniques step in. “Not only do [latent-variable techniques] allow one to spot groups of metabolites changing together—as you might expect if they are involved in the same pathway, for instance—but they also provide simple and intuitive visualizations of the data,” Ebbels explained. “Visualization is a key part of the discovery process and would be hard to do without these kinds of tools. For instance, how do you visualize the levels of hundreds of metabolites changing over hundreds or thousands of individuals? You cannot just plot a scatter plot of the levels of metabolite one versus metabolite two. You need a tool that reduces the dimensionality of the data—this is what latent-variable methods do.”Recent advances have helped to take analysis to the next level by identifying individual molecules associated with a particular disease state from their spectral data. Such insight used to involve time-consuming literature searches to identify candidates associated with a particular pattern and specific experiments to provide proof. Now, the emerging technique of statistical correlation spectroscopy identifies precise patterns that appear repeatedly across a set of samples, which enables software to identify the molecules that are responsible with increasing levels of certainty.“…when you crunch large data sets, you accept that here and there you do make a mistake […] The idea is that, given the thousands of datapoints you can crunch, the few mistakes do not change the big picture”To a large extent, it is simply the availability of complex data sets spanning many variables that has driven progress in analytical biology, rather than advances in mathematics itself. Indeed, the mathematical tools underlying many of the recently developed methods are based on Bayes'' theorem, which was developed by the English Presbyterian minister Thomas Bayes and published after his death in 1763, by the Royal Society of London. The theorem allows mathematicians to calculate the probability of a previous event on the basis of evidence or data that emerges afterwards. In multivariate analyses, it identifies the event or condition most likely to be associated with a particular complex data set spanning many variables. In metabonomics it can identify the disease associated with a particular distribution of molecules with a high degree of accuracy. “Modern mathematical techniques in biology is a large subject, but you can think of the progress being based on Bayesian approaches,” noted Gael Yvert from the Laboratory of Molecular and Cellular Biology at the École Normale Supérieure, Lyon, France.Ultimately, whatever tools are available and whatever technological advances are made, innovation and originality of the human spirit will still determine what makes science brilliantYvert applies multivariate analysis to genetic mechanisms that underlie phenotypic differences between individuals within a species, focusing on the yeast Saccharomyces cerevisiae. Bayesian methods have had a profound effect on both the design and analysis of Yvert''s experiments. Essentially, Yvert has been able to strike a balance between statistical power and the cost of doing an experiment, which has helped him to minimize the number of microarrays needed to establish a link between a trait and a genetic background.For example, if you want to identify the genes responsible for a particular trait by analysing expression levels across the genomes of two yeast strains under different experimental conditions, Bayesian techniques can provide the answer to a certain level of probability, which can then be increased by repeating the experiment. For a given budget, that means either reducing the number of conditions tested or the number of yeast strains that can be analysed. This is necessary, Yvert pointed out, because it is pointless to compromise on statistical power, especially if the conclusions are unexpected. “It is often better to have many replicates than to explore more conditions, because then robust inferences are obtained,” he explained.There are other situations, though, in which modern analytical methods help scientists to understand biological mechanisms by revealing uncertainty. This is the case with interactions between proteins, which often depend on precise alignments of sites involving specific configurations of atoms. Until recently, the structure of such binding sites was obtained using X-ray or electron crystallography. These techniques have yielded increasingly accurate information about the position of atoms within a single protein or protein complex, but this is only a snapshot; it cannot reveal the extent of atomic flexibility within a complex molecule. Additionally, the crystal structures are based on the average positions of molecules, which might not be sufficient to predict the behaviour of the protein during interaction or binding. However, Russ Altman, chair of the Department of Bioengineering and director of the programme in Biomedical Informatics at Stanford University in the USA, explained that if you also know how much freedom each atom has to move within the structure, it becomes possible to predict how the molecule will interact during binding. Altman has applied computational modelling to determine the degree of uncertainty of the position of various atoms within a protein molecule.“I think the ability to represent the uncertainty in the position of individual atoms is critical and still not fully appreciated,” Altman said. “Crystal structures are fabulous, but crystals provide an environment that may encourage unrealistically low atomic positional deviations. The field of protein disorder and its importance for structure and function has exploded, and our work was an early indicator and demonstration of the importance of thinking about this.”This has helped researchers to work out the detailed mechanisms of protein binding, which depend not only on the average positions of atoms, but also on their freedom of movement. “Our results suggest that certain atoms within proteins can be positioned with great certainty, while others have great uncertainty,” Altman commented.This idea of representing the uncertainty of atoms has been scaled up to the study of binding between drugs and their targets, leading to the design of new therapeutic compounds that should be more effective. “We have recently shown that drug binding sites can be represented by a series of loosely interacting microenvironments,” Altman explained. “This representation allows us to recognize similar sites that might bind the same ligands, with similar microenvironments, but perhaps arranged slightly differently. These slight differences can be accommodated by flexibility in the ligand (Halperin et al, 2008).” Altman is applying this knowledge to designing kinase inhibitors. In theory, it should be possible to design drugs capable of targeting a broader range of related proteins, such as kinases, which often have key roles in inflammatory responses and disorders.Over the past decade or two, the role and use of analytical and computational techniques have developed rapidly, but they are still just tools that require human insight to draw conclusions. An important point is that as data sets become larger and more complex, the potential for errors and different interpretations becomes greater, even with the help of sophisticated statistical analysis. In this regard, Dieter Ebert, whose group at the University of Basel in Switzerland specializes in the evolution of host–parasite interactions, noted that, “when you crunch large data sets, you accept that here and there you do make a mistake […] The idea is that, given the thousands of datapoints you can crunch, the few mistakes do not change the big picture. Once you go into details, you may find the mistakes, but this needs often a sharp eye and experience.”A simple example is the widely applied technique of shotgun sequencing, to determine whole genomes by breaking up the DNA into random overlapping segments that are small enough to be sequenced individually. These segments are then read and assembled into a continuous whole sequence by a computer program. As Ebert noted, this process always misassembles a few of the sequences, even though the software is getting better all the time. Whether these errors matter depends on the application: whether the objective is to determine the broad structure and layout of a whole genome, or to focus more closely on sequences or even individual genes.“If your work is aimed at seeing the larger picture, you may live with error rates below a certain threshold. So if you compare a newly assembled genome with previous genomes, and you are looking for the overall patterns, you can ignore some errors,” Dieter said. “But if you pick out one section of the genome and you want to study the particular gene order in this region, I would strongly suggest you verify that this region was correctly assembled, even if the chance of misassembly is only 1 in 100.”The wider message is that as biology becomes more analytical and interdisciplinary, the skills required to design experiments and interpret results have inevitably changed. Nevertheless, one fundamental point remains: human skill and judgement are needed to determine whether a set of results confirms expectations, whether it indicates that further investigation is needed, or whether it requires revision of the existing orthodoxy. Ultimately, whatever tools are available and whatever technological advances are made, innovation and originality of the human spirit will still determine what makes science brilliant.     

A novel platform to produce human monoclonal antibodies: The next generation of therapeutic human monoclonal antibodies discovery

A new technology has been developed by immunologix that allows human antibodies to be quickly generated against virtually any antigen. Using a novel process, naïve human B cells are isolated from tonsil tissue and transformed with efficiency up to 85%, thus utilizing a large portion of the human VDJ/VJ repertoire. Through ex vivo stimulation, the B cells class switch and may undergo somatic hypermutation, thus producing a human “library” of different IgG antibodies that can then be screened against any antigen. Since diversity is generated ex vivo, sampling immunized or previously exposed individuals is not necessary. Cells producing the antibody of interest can be isolated through limiting dilution cloning and the human antibody from the cells can be tested for biological activity. No humanization is necessary because the antibodies are produced from human B cells. By eliminating immunization and humanization steps and screening a broadly diverse library, this platform should reduce both the cost and time involved in producing therapeutic monoclonal antibody candidates.Key words: human, antibody, monoclonal, novel platform, naïve, B cell, therapeutic     

Stochastic physics,complex systems and biology

In complex systems, the interplay between nonlinear and stochastic dynamics, e.g., J. Monod’s necessity and chance, gives rise to an evolutionary process in Darwinian sense, in terms of discrete jumps among attractors, with punctuated equilibria, spontaneous random “mutations” and “adaptations”. On an evolutionary time scale it produces sustainable diversity among individuals in a homogeneous population rather than convergence as usually predicted by a deterministic dynamics. The emergent discrete states in such a system, i.e., attractors, have natural robustness against both internal and external perturbations. Phenotypic states of a biological cell, a mesoscopic nonlinear stochastic open biochemical system, could be understood through such a perspective.     

A tethered bilayer assembled on top of immobilized calmodulin to mimic cellular compartmentalization

Background

Biomimetic membrane models tethered on solid supports are important tools for membrane protein biochemistry and biotechnology. The supported membrane systems described up to now are composed of a lipid bilayer tethered or not to a surface separating two compartments: a ”trans” side, one to a few nanometer thick, located between the supporting surface and the membrane; and a “cis” side, above the synthetic membrane, exposed to the bulk medium. We describe here a novel biomimetic design composed of a tethered bilayer membrane that is assembled over a surface derivatized with a specific intracellular protein marker. This multilayered biomimetic assembly exhibits the fundamental characteristics of an authentic biological membrane in creating a continuous yet fluid phospholipidic barrier between two distinct compartments: a “cis” side corresponding to the extracellular milieu and a “trans” side marked by a key cytosolic signaling protein, calmodulin.

Methodology/Principal Findings

We established and validated the experimental conditions to construct a multilayered structure consisting in a planar tethered bilayer assembled over a surface derivatized with calmodulin. We demonstrated the following: (i) the grafted calmodulin molecules (in trans side) were fully functional in binding and activating a calmodulin-dependent enzyme, the adenylate cyclase from Bordetella pertussis; and (ii) the assembled bilayer formed a continuous, protein-impermeable boundary that fully separated the underlying calmodulin (trans side) from the above medium (cis side).

Conclusions

The simplicity and robustness of the tethered bilayer structure described here should facilitate the elaboration of biomimetic membrane models incorporating membrane embedded proteins and key cytoplasmic constituents. Such biomimetic structures will also be an attractive tool to study translocation across biological membranes of proteins or other macromolecules.     

Highly selective end-tagged antimicrobial peptides derived from PRELP

Background

Antimicrobial peptides (AMPs) are receiving increasing attention due to resistance development against conventional antibiotics. Pseudomonas aeruginosa and Staphylococcus aureus are two major pathogens involved in an array of infections such as ocular infections, cystic fibrosis, wound and post-surgery infections, and sepsis. The goal of the study was to design novel AMPs against these pathogens.

Methodology and Principal Findings

Antibacterial activity was determined by radial diffusion, viable count, and minimal inhibitory concentration assays, while toxicity was evaluated by hemolysis and effects on human epithelial cells. Liposome and fluorescence studies provided mechanistic information. Protease sensitivity was evaluated after subjection to human leukocyte elastase, staphylococcal aureolysin and V8 proteinase, as well as P. aeruginosa elastase. Highly active peptides were evaluated in ex vivo skin infection models. C-terminal end-tagging by W and F amino acid residues increased antimicrobial potency of the peptide sequences GRRPRPRPRP and RRPRPRPRP, derived from proline arginine-rich and leucine-rich repeat protein (PRELP). The optimized peptides were antimicrobial against a range of Gram-positive S. aureus and Gram-negative P. aeruginosa clinical isolates, also in the presence of human plasma and blood. Simultaneously, they showed low toxicity against mammalian cells. Particularly W-tagged peptides displayed stability against P. aeruginosa elastase, and S. aureus V8 proteinase and aureolysin, and the peptide RRPRPRPRPWWWW-NH₂ was effective against various “superbugs” including vancomycin-resistant enterococci, multi-drug resistant P. aeruginosa, and methicillin-resistant S. aureus, as well as demonstrated efficiency in an ex vivo skin wound model of S. aureus and P. aeruginosa infection.

Conclusions/Significance

Hydrophobic C-terminal end-tagging of the cationic sequence RRPRPRPRP generates highly selective AMPs with potent activity against multiresistant bacteria and efficiency in ex vivo wound infection models. A precise “tuning” of toxicity and proteolytic stability may be achieved by changing tag-length and adding W- or F-amino acid tags.     

Cellular context and multiple channel domains determine cAMP sensitivity of HCN4 channels: Ligand-independent relief of autoinhibition in HCN4

Hyperpolarization-activated, cyclic nucleotide–sensitive (HCN) channels produce the I_f and I_h currents, which are critical for cardiac pacemaking and neuronal excitability, respectively. HCN channels are modulated by cyclic AMP (cAMP), which binds to a conserved cyclic nucleotide–binding domain (CNBD) in the C terminus. The unliganded CNBD has been shown to inhibit voltage-dependent gating of HCNs, and cAMP binding relieves this “autoinhibition,” causing a depolarizing shift in the voltage dependence of activation. Here we report that relief of autoinhibition can occur in the absence of cAMP in a cellular context- and isoform-dependent manner: when the HCN4 isoform was expressed in Chinese hamster ovary (CHO) cells, the basal voltage dependence was already shifted to more depolarized potentials and cAMP had no further effect on channel activation. This “pre-relief” of autoinhibition was specific both to HCN4 and to CHO cells; cAMP shifted the voltage dependence of HCN2 in CHO cells and of HCN4 in human embryonic kidney (HEK) cells. The pre-relief phenotype did not result from different concentrations of soluble intracellular factors in CHO and HEK cells, as it persisted in excised cell-free patches. Likewise, it did not arise from a failure of cAMP to bind to the CNBD of HCN4 in CHOs, as indicated by cAMP-dependent slowing of deactivation. Instead, a unique ∼300–amino acid region of the distal C terminus of HCN4 (residues 719–1012, downstream of the CNBD) was found to be necessary, but not sufficient, for the depolarized basal voltage dependence and cAMP insensitivity of HCN4 in CHO cells. Collectively, these data suggest a model in which multiple HCN4 channel domains conspire with membrane-associated intracellular factors in CHO cells to relieve autoinhibition in HCN4 channels in the absence of cAMP. These findings raise the possibility that such ligand-independent regulation could tune the activity of HCN channels and other CNBD-containing proteins in many physiological systems.     

The irreversible binding of amyloid peptide substrates to insulin-degrading enzyme: A biological perspective

Insulin-degrading enzyme (IDE) is a conserved Zn²⁺metalloendopeptidase involved in insulin degradation and in the maintenance of brain steady-state levels of amyloid β peptide (Aβ) of Alzheimer''s disease (AD). Our recent demonstration that IDE and Aβ are capable of forming a stoichiometric and extremely stable complex raises several intriguing possibilities regarding the role of this unique protein-peptide interaction in physiological and pathological conditions. These include a protective cellular function of IDE as a “dead-end chaperone” alternative to its proteolytic activity and the potential impact of the irreversible binding of Aβ to IDE upon its role as a varicella zoster virus receptor. In a pathological context, the implications for insulin signaling and its relationship to AD pathogenesis are discussed. Moreover, our findings warrant further research regarding a possible general and novel interaction between amyloidogenic peptides and other Zn²⁺metallopeptidases with an IDE-like fold and a substrate conformation-dependent recognition mechanism.Key words: amyloid, insulin-degrading enzyme, peptides, alzheimer''s disease, irreversible binding, metalloproteases     

Selection of Specific Protein Binders for Pre-Defined Targets from an Optimized Library of Artificial Helicoidal Repeat Proteins (alphaRep)

We previously designed a new family of artificial proteins named αRep based on a subgroup of thermostable helicoidal HEAT-like repeats. We have now assembled a large optimized αRep library. In this library, the side chains at each variable position are not fully randomized but instead encoded by a distribution of codons based on the natural frequency of side chains of the natural repeats family. The library construction is based on a polymerization of micro-genes and therefore results in a distribution of proteins with a variable number of repeats. We improved the library construction process using a “filtration” procedure to retain only fully coding modules that were recombined to recreate sequence diversity. The final library named Lib2.1 contains 1.7×10⁹ independent clones. Here, we used phage display to select, from the previously described library or from the new library, new specific αRep proteins binding to four different non-related predefined protein targets. Specific binders were selected in each case. The results show that binders with various sizes are selected including relatively long sequences, with up to 7 repeats. ITC-measured affinities vary with K_d values ranging from micromolar to nanomolar ranges. The formation of complexes is associated with a significant thermal stabilization of the bound target protein. The crystal structures of two complexes between αRep and their cognate targets were solved and show that the new interfaces are established by the variable surfaces of the repeated modules, as well by the variable N-cap residues. These results suggest that αRep library is a new and versatile source of tight and specific binding proteins with favorable biophysical properties.     

Engineering Bacteria to Search for Specific Concentrations of Molecules by a Systematic Synthetic Biology Design Method

Bacteria navigate environments full of various chemicals to seek favorable places for survival by controlling the flagella’s rotation using a complicated signal transduction pathway. By influencing the pathway, bacteria can be engineered to search for specific molecules, which has great potential for application to biomedicine and bioremediation. In this study, genetic circuits were constructed to make bacteria search for a specific molecule at particular concentrations in their environment through a synthetic biology method. In addition, by replacing the “brake component” in the synthetic circuit with some specific sensitivities, the bacteria can be engineered to locate areas containing specific concentrations of the molecule. Measured by the swarm assay qualitatively and microfluidic techniques quantitatively, the characteristics of each “brake component” were identified and represented by a mathematical model. Furthermore, we established another mathematical model to anticipate the characteristics of the “brake component”. Based on this model, an abundant component library can be established to provide adequate component selection for different searching conditions without identifying all components individually. Finally, a systematic design procedure was proposed. Following this systematic procedure, one can design a genetic circuit for bacteria to rapidly search for and locate different concentrations of particular molecules by selecting the most adequate “brake component” in the library. Moreover, following simple procedures, one can also establish an exclusive component library suitable for other cultivated environments, promoter systems, or bacterial strains.     

Proteolysis of Human Thrombin Generates Novel Host Defense Peptides

The coagulation system is characterized by the sequential and highly localized activation of a series of serine proteases, culminating in the conversion of fibrinogen into fibrin, and formation of a fibrin clot. Here we show that C-terminal peptides of thrombin, a key enzyme in the coagulation cascade, constitute a novel class of host defense peptides, released upon proteolysis of thrombin in vitro, and detected in human wounds in vivo. Under physiological conditions, these peptides exert antimicrobial effects against Gram-positive and Gram-negative bacteria, mediated by membrane lysis, as well as immunomodulatory functions, by inhibiting macrophage responses to bacterial lipopolysaccharide. In mice, they are protective against P. aeruginosa sepsis, as well as lipopolysaccharide-induced shock. Moreover, the thrombin-derived peptides exhibit helical structures upon binding to lipopolysaccharide and can also permeabilize liposomes, features typical of “classical” helical antimicrobial peptides. These findings provide a novel link between the coagulation system and host-defense peptides, two fundamental biological systems activated in response to injury and microbial invasion.