Incorporation of Magnetic Nanoparticles into Protoplasts of Microalgae Haematococcus pluvialis: A Tool for Biotechnological Applications.

Intensive research on the use of magnetic nanoparticles for biotechnological applications of microalgae biomass guided the development of proper treatment to successfully incorporate them into these single-cell microorganisms. Protoplasts, as cells lacking a cell wall, are extensively used in plant/microalgae genetic manipulation as well as various biotechnological applications. In this work, a detailed study on the formation of protoplasts from Haematococcus pluvialis with the use of enzymatic and mechanical procedures was performed. The optimization of several parameters affecting the formation of protoplasmic cells and cell recovery was investigated. In the enzymatic treatment, a solution of cellulase was studied at different time points of incubation, whereas in the mechanical treatment, glass beads vortexing was used. Mechanical treatment gave better results in comparison to the enzymatic one. Concerning the cell recovery, after the protoplast formation, it was found to be similar in both methods used; cell viability was not investigated. To enhance the protoplast cell wall reconstruction, different "recovery media" with an organic source of carbon or nitrogen were used. Cell morphology during all treatments was evaluated by electron microscopy. The optimal conditions found for protoplast formation and cell reconstruction were successfully used to produce Haematococcus pluvialis cells with magnetic properties.

Coactivation of GR and NFKB alters the repertoire of their binding sites and target genes.

Glucocorticoid receptor (GR) exerts anti-inflammatory action in part by antagonizing proinflammatory transcription factors such as the nuclear factor kappa-b (NFKB). Here, we assess the crosstalk of activated GR and RELA (p65, major NFKB component) by global identification of their binding sites and target genes. We show that coactivation of GR and p65 alters the repertoire of regulated genes and results in their association with novel sites in a mutually dependent manner. These novel sites predominantly cluster with p65 target genes that are antagonized by activated GR and vice versa. Our data show that coactivation of GR and NFKB alters signaling pathways that are regulated by each factor separately and provide insight into the networks underlying the GR and NFKB crosstalk.

HuR-regulated mRNAs associated with nuclear hnRNP A1-RNP complexes.

Post-transcriptional regulatory networks are dependent on the interplay of many RNA-binding proteins having a major role in mRNA processing events in mammals. We have been interested in the concerted action of the two RNA-binding proteins hnRNP A1 and HuR, both stable components of immunoselected hnRNP complexes and having a major nuclear localization. Specifically, we present here the application of the RNA-immunoprecipitation (RIP)-Chip technology to identify a population of nuclear transcripts associated with hnRNP A1-RNPs as isolated from the nuclear extract of either HuR WT or HuR-depleted (KO) mouse embryonic fibroblast (MEF) cells. The outcome of this analysis was a list of target genes regulated via HuR for their association (either increased or reduced) with the nuclear hnRNP A1-RNP complexes. Real time PCR analysis was applied to validate a selected number of nuclear mRNA transcripts, as well as to identify pre-spliced transcripts (in addition to their mature mRNA counterpart) within the isolated nuclear hnRNP A1-RNPs. The differentially enriched mRNAs were found to belong to GO categories relevant to biological processes anticipated for hnRNP A1 and HuR (such as transport, transcription, translation, apoptosis and cell cycle) indicating their concerted function in mRNA metabolism.

Extracts from Chlorella vulgaris Protect Mesenchymal Stromal Cells from Oxidative Stress Induced by Hydrogen Peroxide.

Microalgae as unicellular eukaryotic organisms demonstrate several advantages for biotechnological and biological applications. Natural derived microalgae products demand has increased in food, cosmetic and nutraceutical applications lately. The natural antioxidants have been used for attenuation of mitochondrial cell damage caused by oxidative stress. This study evaluates the in vitro protective effect of Chlorella vulgaris bioactive extracts against oxidative stress in human mesenchymal stromal/stem cells (MSCs). The classical solid-liquid and the supercritical extraction, using biomass of commercially available and laboratory cultivated C. vulgaris, are employed. Oxidative stress induced by 300 µM H2O2 reduces cell viability of MSCs. The addition of C. vulgaris extracts, with increased protein content compared to carbohydrates, to H2O2 treated MSCs counteracted the oxidative stress, reducing reactive oxygen species levels without affecting MSC proliferation. The supercritical extraction was the most efficient extraction method for carotenoids resulting in enhanced antioxidant activity. Pre-treatment of MSCs with C. vulgaris extracts mitigates the oxidative damage ensued by H2O2. Initial proteomic analysis of secretome from licensed (TNFα-activated) MSCs treated with algal extracts reveals a signature of differentially regulated proteins that fall into clinically relevant pathways such as inflammatory signaling. The enhanced antioxidative and possibly anti-inflammatory capacity could be explored in the context of future cell therapies.

Second-Generation Escherichia coli SuptoxR Strains for High-Level Recombinant Membrane Protein Production.

Escherichia coli is one of the most widely utilized hosts for recombinant protein production, including that of membrane proteins (MPs). We have recently engineered a specialized E. coli strain for enhanced recombinant MP production, termed SuptoxR. By appropriately co-expressing the effector gene rraA, SuptoxR can suppress the high toxicity, which is frequently observed during the MP-overexpression process, and, at the same time, enhance significantly the cellular accumulation of membrane-incorporated and properly folded recombinant MP. The combination of these two beneficial effects results in dramatically enhanced volumetric yields for various prokaryotic and eukaryotic MPs. Here, we engineered second-generation SuptoxR strains with further improved properties, so that they can achieve even higher levels of recombinant MP production. We searched for naturally occurring RraA variants with similar or improved MP toxicity-suppressing and production-promoting effects to that of the native E. coli RraA of the original SuptoxR strain. We found that the RraA proteins from Proteus mirabilis and Providencia stuartii can be even more potent enhancers of MP productivity than the E. coli RraA. By exploiting these two newly identified RraAs, we constructed two second-generation SuptoxR strains, termed SuptoxR2.1 and SuptoxR2.2, whose MP-production capabilities often surpass those of the original SuptoxR significantly. SuptoxR2.1 and SuptoxR2.2 are expected to become widely useful expression hosts for recombinant MP production in bacteria.

Escherichia coli genome-wide promoter analysis: identification of additional AtoC binding target elements.

BACKGROUND: Studies on bacterial signal transduction systems have revealed complex networks of functional interactions, where the response regulators play a pivotal role. The AtoSC system of E. coli activates the expression of atoDAEB operon genes, and the subsequent catabolism of short-chain fatty acids, upon acetoacetate induction. Transcriptome and phenotypic analyses suggested that atoSC is also involved in several other cellular activities, although we have recently reported a palindromic repeat within the atoDAEB promoter as the single, cis-regulatory binding site of the AtoC response regulator. In this work, we used a computational approach to explore the presence of yet unidentified AtoC binding sites within other parts of the E. coli genome. RESULTS: Through the implementation of a computational de novo motif detection workflow, a set of candidate motifs was generated, representing putative AtoC binding targets within the E. coli genome. In order to assess the biological relevance of the motifs and to select for experimental validation of those sequences related robustly with distinct cellular functions, we implemented a novel approach that applies Gene Ontology Term Analysis to the motif hits and selected those that were qualified through this procedure. The computational results were validated using Chromatin Immunoprecipitation assays to assess the in vivo binding of AtoC to the predicted sites. This process verified twenty-two additional AtoC binding sites, located not only within intergenic regions, but also within gene-encoding sequences. CONCLUSIONS: This study, by tracing a number of putative AtoC binding sites, has indicated an AtoC-related cross-regulatory function. This highlights the significance of computational genome-wide approaches in elucidating complex patterns of bacterial cell regulation.

Magnetic Immobilization and Growth of Nannochloropsis oceanica and Scenedasmus almeriensis.

Microalgae are used in industrial and pharmaceutical applications. Their performance on biological applications may be improved by their immobilization. This study presents a way of cell immobilization using microalgae carrying magnetic properties. Nannochloropsis oceanica and Scenedasmus almeriensis cells were treated enzymatically (cellulase) and mechanically (glass beads), generating protoplasts as a means of incorporation of magnetic nanoparticles. Scanning electron microscopy images verified the successful cell wall destruction for both of the examined microalgae cells. Subsequently, protoplasts were transformed with magnetic nanoparticles by a continuous electroporation method and then cultured on a magnetic surface. Regeneration of transformed protoplasts was optimized using various organic carbon and amino acid supplements. Both protoplast preparation methods demonstrated similar efficiency. Casamino acids, as source of amino acids, were the most efficient compound for N. oceanica protoplasts regeneration in enzymatic and mechanical treatment, while for S. almeriensis protoplasts regeneration, fructose, as source of organic carbon, was the most effective. Protoplasts transformation efficiency values with magnetic nanoparticles after enzymatic or mechanical treatments for N. oceanica and S. almeriensis were 17.8% and 10.7%, and 18.6% and 15.7%, respectively. Finally, selected magnetic cells were immobilized and grown on a vertical magnetic surface exposed to light and without any supplement.

Computational Analysis of Transcriptomic and Proteomic Data for Deciphering Molecular Heterogeneity and Drug Responsiveness in Model Human Hepatocellular Carcinoma Cell Lines.

Hepatocellular carcinoma (HCC) is associated with high mortality due to its inherent heterogeneity, aggressiveness, and limited therapeutic regimes. Herein, we analyzed 21 human HCC cell lines (HCC lines) to explore intertumor molecular diversity and pertinent drug sensitivity. We used an integrative computational approach based on exploratory and single-sample gene-set enrichment analysis of transcriptome and proteome data from the Cancer Cell Line Encyclopedia, followed by correlation analysis of drug-screening data from the Cancer Therapeutics Response Portal with curated gene-set enrichment scores. Acquired results classified HCC lines into two groups, a poorly and a well-differentiated group, displaying lower/higher enrichment scores in a "Specifically Upregulated in Liver" gene-set, respectively. Hierarchical clustering based on a published epithelial-mesenchymal transition gene expression signature further supported this stratification. Between-group comparisons of gene and protein expression unveiled distinctive patterns, whereas downstream functional analysis significantly associated differentially expressed genes with crucial cancer-related biological processes/pathways and revealed concrete driver-gene signatures. Finally, correlation analysis highlighted a diverse effectiveness of specific drugs against poorly compared to well-differentiated HCC lines, possibly applicable in clinical research with patients with analogous characteristics. Overall, this study expanded the knowledge on the molecular profiles, differentiation status, and drug responsiveness of HCC lines, and proposes a cost-effective computational approach to precision anti-HCC therapies.

RNA-seq data analysis of stimulated hepatocellular carcinoma cells treated with epigallocatechin gallate and fisetin reveals target genes and action mechanisms.

Hepatocellular carcinoma (HCC) is an essentially incurable inflammation-related cancer. We have previously shown by network analysis of proteomic data that the flavonoids epigallocatechin gallate (EGCG) and fisetin (FIS) efficiently downregulated pro-tumor cytokines released by HCC through inhibition of Akt/mTOR/RPS6 phospho-signaling. However, their mode of action at the global transcriptome level remains unclear. Herein, we endeavor to compare gene expression alterations mediated by these compounds through a comprehensive transcriptome analysis based on RNA-seq in HEP3B, a responsive HCC cell line, upon perturbation with a mixture of prototypical stimuli mimicking conditions of tumor microenvironment or under constitutive state. Analysis of RNA-seq data revealed extended changes on HEP3B transcriptome imposed by test nutraceuticals. Under stimulated conditions, EGCG and FIS significantly modified, compared to the corresponding control, the expression of 922 and 973 genes, respectively, the large majority of which (695 genes), was affected by both compounds. Hierarchical clustering based on the expression data of shared genes demonstrated an almost identical profile in nutraceutical-treated stimulated cells which was virtually opposite in cells exposed to stimuli alone. Downstream enrichment analyses of the co-modified genes uncovered significant associations with cancer-related transcription factors as well as terms of Gene Ontology/Reactome Pathways and highlighted ECM dynamics as a nodal modulation point by nutraceuticals along with angiogenesis, inflammation, cell motility and growth. RNA-seq data for selected genes were independently confirmed by RT-qPCR. Overall, the present systems approach provides novel evidence stepping up the mechanistic understanding of test nutraceuticals, thus rationalizing their clinical exploitation in new preventive/therapeutic modalities against HCC.

XynDZ5: A New Thermostable GH10 Xylanase.

Xylanolytic enzymes have a broad range of applications in industrial biotechnology as biocatalytic components of various processes and products, such as food additives, bakery products, coffee extraction, agricultural silage and functional foods. An increasing market demand has driven the growing interest for the discovery of xylanases with specific industrially relevant characteristics, such as stability at elevated temperatures and in the presence of other denaturing factors, which will facilitate their incorporation into industrial processes. In this work, we report the discovery and biochemical characterization of a new thermostable GH10 xylanase, termed XynDZ5, exhibiting only 26% amino acid sequence identity to the closest characterized xylanolytic enzyme. This new enzyme was discovered in an Icelandic hot spring enrichment culture of a Thermoanaerobacterium species using a recently developed bioinformatic analysis platform. XynDZ5 was produced recombinantly in Escherichia coli, purified and characterized biochemically. This analysis revealed that it acts as an endo-1,4-ß-xylanase that performs optimally at 65-75°C and pH 7.5. The enzyme is capable of retaining high levels of catalytic efficiency after several hours of incubation at high temperatures, as well as in the presence of significant concentrations of a range of metal ions and denaturing agents. Interestingly, the XynDZ5 biochemical profile was found to be atypical, as it also exhibits significant exo-activity. Computational modeling of its three-dimensional structure predicted a (ß/α)8 TIM barrel fold, which is very frequently encountered among family GH10 enzymes. This modeled structure has provided clues about structural features that may explain aspects of its catalytic performance. Our results suggest that XynDZ5 represents a promising new candidate biocatalyst appropriate for several high-temperature biotechnological applications in the pulp, paper, baking, animal-feed and biofuel industries.

A Study on the Effect of Macro- and Micro- Nutrients on Nannochloropsis oceanica Growth, Fatty Acid Composition and Magnetic Harvesting Efficiency.

The effect of iron, manganese, phosphorus and nitrogen on growth and lipid synthesis of the microalgae Nannochloropsis oceanica CCMP1779, as well as their impact on the magnetic harvesting efficiency, are examined under their depriving cell culture conditions. Herein, it is demonstrated that nitrogen and manganese depletion primarily reduced cell growth while phosphorus and iron restriction led to higher dry biomass. Subsequently, the role of those nutrients on fatty acids profile was examined. Phosphorus and nitrogen restriction resulted in lower and higher lipid content, respectively. High amounts of polyunsaturated fatty acids like eicosapentaenoic acid are produced under iron and manganese depletion. Phosphorus deprivation favors monounsaturated fatty acids such as C18:1 and C16:1, while nitrogen restriction favors saturated fatty acid production like C14:0, C16:0 and C18:0. Since the presence/absence of macro- and micro-elements may affect the overall electrostatic charges on the outmost microalgae surface, it was also analyzed how these elements affect the magnetic harvesting efficiency. Results showed that phosphorus deprivation led to the best magnetic harvesting efficiency of N. oceanica cells (93%) as compared to other nutrient starvation as well as standard medium.

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

BACKGROUND: The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. RESULTS: We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. CONCLUSION: Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

KEGGconverter: a tool for the in-silico modelling of metabolic networks of the KEGG Pathways database.

BACKGROUND: The KEGG Pathway database is a valuable collection of metabolic pathway maps. Nevertheless, the production of simulation capable metabolic networks from KEGG Pathway data is a challenging complicated work, regardless the already developed tools for this scope. Originally used for illustration purposes, KEGG Pathways through KGML (KEGG Markup Language) files, can provide complete reaction sets and introduce species versioning, which offers advantages for the scope of cellular metabolism simulation modelling. In this project, KEGGconverter is described, implemented also as a web-based application, which uses as source KGML files, in order to construct integrated pathway SBML models fully functional for simulation purposes. RESULTS: A case study of the integration of six human metabolic pathways from KEGG depicts the ability of KEGGconverter to automatically produce merged and converted to SBML fully functional pathway models, enhanced with default kinetics. The suitability of the developed tool is demonstrated through a comparison with other state-of-the art relevant software tools for the same data fusion and conversion tasks, thus illustrating the problems and the relevant workflows. Moreover, KEGGconverter permits the inclusion of additional reactions in the resulting model which represent flux cross-talk with neighbouring pathways, providing in this way improved simulative accuracy. These additional reactions are introduced by exploiting relevant semantic information for the elements of the KEGG Pathways database. The architecture and functionalities of the web-based application are presented. CONCLUSION: KEGGconverter is capable of producing integrated analogues of metabolic pathways appropriate for simulation tasks, by inputting only KGML files. The web application acts as a user friendly shell which transparently enables the automated biochemically correct pathway merging, conversion to SBML format, proper renaming of the species, and insertion of default kinetic properties for the pertaining reactions. The tool is available at: http://www.grissom.gr/keggconverter.

Protective effects of mastic oil from Pistacia lentiscus variation chia against experimental growth of lewis lung carcinoma.

Mastic oil from Pistacia lentiscus variation chia, a traditionally used dietary flavoring agent with medicinal properties, has been shown to exert in vitro antitumor activities, but no study has addressed in vivo efficacy and mechanisms of action. Presently, we demonstrated that treatment of immunocompetent mice with mastic oil (45 mg/kg body weight, intraperitoneally, 3 times a wk for approximately 3 wk) significantly inhibited tumor growth (56.4% +/- 5.7 maximum reduction in tumor volumes) without toxicity. Analysis of tumors by immunohistochemistry and ELISA indicated that this effect is associated with increased apoptosis, reduced neovascularization, and inhibition of chemokine expression. Likewise mastic oil reduced vascular endothelial growth factor and chemokine release by Lewis lung carcinoma (LLC) cells. Furthermore, mastic oil administration decreased small guanosine triphosphatases (GTPases) Ras, RhoA and nuclear factor-kappa-B-dependent reporter gene expression in vivo and in vitro, indicating a mechanistic link between mastic oil activities and blocking of relevant signaling and transcription pathways. A dose-response comparison with perillyl alcohol and alpha-pinene, two of its components, revealed a higher efficacy of mastic oil, pointing to a beneficial collective interaction among its ingredients. Conclusively, our results provide novel in vivo evidence of mastic oil inhibitory effects on tumor growth and set a rational basis for its future application in cancer prevention.

ANASTASIA: An Automated Metagenomic Analysis Pipeline for Novel Enzyme Discovery Exploiting Next Generation Sequencing Data.

Metagenomic analysis of environmental samples provides deep insight into the enzymatic mixture of the corresponding niches, capable of revealing peptide sequences with novel functional properties exploiting the high performance of next-generation sequencing (NGS) technologies. At the same time due to their ever increasing complexity, there is a compelling need for ever larger computational configurations to ensure proper bioinformatic analysis, and fine annotation. With the aiming to address the challenges of such an endeavor, we have developed a novel web-based application named ANASTASIA (automated nucleotide aminoacid sequences translational plAtform for systemic interpretation and analysis). ANASTASIA provides a rich environment of bioinformatic tools, either publicly available or novel, proprietary algorithms, integrated within numerous automated algorithmic workflows, and which enables versatile data processing tasks for (meta)genomic sequence datasets. ANASTASIA was initially developed in the framework of the European FP7 project HotZyme, whose aim was to perform exhaustive analysis of metagenomes derived from thermal springs around the globe and to discover new enzymes of industrial interest. ANASTASIA has evolved to become a stable and extensible environment for diversified, metagenomic, functional analyses for a range of applications overarching industrial biotechnology to biomedicine, within the frames of the ELIXIR-GR project. As a showcase, we report the successful in silico mining of a novel thermostable esterase termed "EstDZ4" from a metagenomic sample collected from a hot spring located in Krisuvik, Iceland.

Studies on the catalytic behavior of a membrane-bound lipolytic enzyme from the microalgae Nannochloropsis oceanica CCMP1779.

The catalytic behavior of a membrane-bound lipolytic enzyme (MBL-Enzyme) from the microalgae Nannochloropsis oceanica CCMP1779 was investigated. The biocatalyst showed maximum activity at 50 °C and pH 7.0, and was stable at pH 7.0 and temperatures from 40 to 60 °C. Half-lives at 60 °C, 70 °C and 80 °C were found 866.38, 150.67 and 85.57 min respectively. Thermal deactivation energy was 68.87 kJ mol-1. The enzyme's enthalpy (ΔΗ*), entropy (ΔS*) and Gibb's free energy (ΔG*) were in the range of 65.86-66.27 kJ mol-1, 132.38-140.64 J mol-1 K-1 and 107.80-115.81 kJ mol-1, respectively. Among p-nitrophenyl esters of fatty acids tested, MBL-Enzyme exhibited the highest hydrolytic activity against p-nitrophenyl palmitate (pNPP). The Km and Vmax values were found 0.051 mM and of 0.054 mmole pNP mg protein-1 min-1, respectively with pNPP as substrate. The presence of Mn2+ increased lipolytic activity by 68.25%, while Fe3+ and Cu2+ ions had the strongest inhibitory effect. MBL-Enzyme was stable in the presence of water miscible (66% of the initial activity in ethanol) and water immiscible (71% of the initial activity in n-octane) solvents. Myristic acid was found to be the most efficient acyl donor in esterification reactions with ethanol. Methanol was the best acyl acceptor among the primary alcohols tested.

Publisher Correction: An integrated bacterial system for the discovery of chemical rescuers of disease-associated protein misfolding.

In the version of this Article originally published, in Fig. 1c-e, on the x axes, the lines labelled 'Aß42' and 'Aß42(F19S;L34P)' grouped the data incorrectly; the line labelled Aß42 should have grouped the data for Random 1-2 and Clones 1-10, and the line labelled Aß42(F19S;L34P) should have only grouped the data for Random 1-2 on the right end of the plots and blots. These figures have now been corrected in all versions of the Article.

Development of Escherichia coli Strains That Withstand Membrane Protein-Induced Toxicity and Achieve High-Level Recombinant Membrane Protein Production.

Membrane proteins perform critical cellular functions in all living organisms and constitute major targets for drug discovery. Escherichia coli has been the most popular overexpression host for membrane protein biochemical/structural studies. Bacterial production of recombinant membrane proteins, however, is typically hampered by poor cellular accumulation and severe toxicity for the host, which leads to low final biomass and minute volumetric yields. In this work, we aimed to rewire the E. coli protein-producing machinery to withstand the toxicity caused by membrane protein overexpression in order to generate engineered bacterial strains with the ability to achieve high-level membrane protein production. To achieve this, we searched for bacterial genes whose coexpression can suppress membrane protein-induced toxicity and identified two highly potent effectors: the membrane-bound DnaK cochaperone DjlA, and the inhibitor of the mRNA-degrading activity of the E. coli RNase E, RraA. E. coli strains coexpressing either djlA or rraA, termed SuptoxD and SuptoxR, respectively, accumulated markedly higher levels of final biomass and produced dramatically enhanced yields for a variety of prokaryotic and eukaryotic recombinant membrane proteins. In all tested cases, either SuptoxD, or SuptoxR, or both, outperformed the capabilities of commercial strains frequently utilized for recombinant membrane protein production purposes.

An integrated bacterial system for the discovery of chemical rescuers of disease-associated protein misfolding.

Protein misfolding and aggregation are common pathological features of several human diseases, including Alzheimer's disease and type 2 diabetes. Here, we report an integrated and generalizable bacterial system for the facile discovery of chemical rescuers of disease-associated protein misfolding. In this system, large combinatorial libraries of macrocyclic molecules are biosynthesized in Escherichia coli cells and simultaneously screened for their ability to rescue pathogenic protein misfolding and aggregation using a flow cytometric assay. We demonstrate the effectiveness of this approach by identifying drug-like, head-to-tail cyclic peptides that modulate the aggregation of the Alzheimer's disease-associated amyloid ß peptide. Biochemical, biophysical and biological assays using isolated amyloid ß peptide, primary neurons and various established Alzheimer's disease nematode models showed that the selected macrocycles potently inhibit the formation of neurotoxic amyloid ß peptide aggregates. We also applied the system to the identification of misfolding rescuers of mutant Cu/Zn superoxide dismutase-an enzyme linked with inherited forms of amyotrophic lateral sclerosis. Overall, the system enables the identification of molecules with therapeutic potential for rescuing the misfolding of disease-associated polypeptides.