Combinatorial biosynthesis of antimicrobials and other natural products

Combinatorial biosynthesis utilizes the enzymes from antibiotic (and other natural product) biosynthetic pathways to create novel chemical structures. The manipulation of modular polyketide synthases (PKSs) has been the major focus of this effort and has led to the production of, for example, several erythromycin analogs. Many new tools for manipulating and studying these multifunctional enzymes have been developed. These include multiple hosts and expression systems, enzymology tools for in vitro study, and ways to engineer pre-PKS and post-PKS pathways. The result is more rational and faster methods of engineering new compounds for the development of chemotherapeutic agents from natural products. The most significant recent advances in combinatorial biosynthesis are outlined.     

Genomic and proteomic perspectives in cell culture engineering.

In the last few years, the number of biologics produced by mammalian cells have been steadily increasing. The advances in cell culture engineering science have contributed significantly to this increase. A common path of product and process development has emerged in the last decade and the host cell lines frequently used have converged to only a few. Selection of cell clones, their adaptation to a desired growth environment, and improving their productivity has been key to developing a new process. However, the fundamental understanding of changes during the selection and adaptation process is still lacking. Some cells may undergo irreversible alteration at the genome level, some may exhibit changes in their gene expression pattern, while others may incur neither genetic reconstruction nor gene expression changes, but only modulation of various fluxes by changing nutrient/metabolite concentrations and enzyme activities. It is likely that the selection of cell clones and their adaptation to various culture conditions may involve alterations not only in cellular machinery directly related to the selected marker or adapted behavior, but also those which may or may not be essential for selection or adaptation. The genomic and proteomic research tools enable one to globally survey the alterations at mRNA and protein levels and to unveil their regulation. Undoubtedly, a better understanding of these cellular processes at the molecular level will lead to a better strategy for 'designing' producing cells. Herein the genomic and proteomic tools are briefly reviewed and their impact on cell culture engineering is discussed.     

Deconvolution of targeted protein-protein interaction maps

Current proteomic techniques allow researchers to analyze chosen biological pathways or an ensemble of related protein complexes at a global level via the measure of physical protein-protein interactions by affinity purification mass spectrometry (AP-MS). Such experiments yield information-rich but complex interaction maps whose unbiased interpretation is challenging. Guided by current knowledge on the modular structure of protein complexes, we propose a novel statistical approach, named BI-MAP, complemented by software tools and a visual grammar to present the inferred modules. We show that the BI-MAP tools can be applied from small and very detailed maps to large, sparse, and much noisier data sets. The BI-MAP tool implementation and test data are made freely available.     

Biosynthesis and combinatorial biosynthesis of pikromycin-related macrolides in Streptomyces venezuelae

Pikromycin-related macrolides have recently attracted significant research interest because they are structurally related to the semisynthetic ketolide antibiotics that have demonstrated promising potential in combating multi-drug-resistant respiratory pathogens. Cloning and in-depth studies of the pikromycin biosynthetic gene cluster from Streptomyces venezuelae have led to new avenues in modular polyketide synthases, deoxysugar biosynthesis, cytochrome P450 hydroxylase, secondary metabolite gene regulation, and antibiotic resistance. Moreover, the knowledge and tools used for these studies are proving to be valuable in the development of advanced technologies for combinatorial biosynthesis of new macrolide antibiotics. This review summarizes these new developments and introduces S. venezuelae as a powerful new system for secondary metabolite pathway engineering from bench-top genetic manipulation to product fermentation.     

Proteomics applied to exercise physiology: a cutting-edge technology

Exercise research has always drawn the attention of the scientific community because it can be widely applied to sport training, health improvement, and disease prevention. For many years numerous tools have been used to investigate the several physiological adaptations induced by exercise stimuli. Nowadays a closer look at the molecular mechanisms underlying metabolic pathways and muscular and cardiovascular adaptation to exercise are among the new trends in exercise physiology research. Considering this, to further understand these adaptations as well as pathology attenuation by exercise, several studies have been conducted using molecular investigations, and this trend looks set to continue. Through enormous biotechnological advances, proteomic tools have facilitated protein analysis within complex biological samples such as plasma and tissue, commonly used in exercise research. Until now, classic proteomic tools such as one- and two-dimensional polyacrylamide gel electrophoresis have been used as standard approaches to investigate proteome modulation by exercise. Furthermore, other recently developed in gel tools such as differential gel electrophoresis (DIGE) and gel-free techniques such as the protein labeling methods (ICAT, SILAC, and iTRAQ) have empowered proteomic quantitative analysis, which may successfully benefit exercise proteomic research. However, despite the three decades of 2-DE development, neither classic nor novel proteomic tools have been convincingly explored by exercise researchers. To this end, this review gives an overview of the directions in which exercise-proteome research is moving and examines the main tools that can be used as a novel strategy in exercise physiology investigation.     

Genetic manipulation of non-ribosomal peptide synthetases to generate novel bioactive peptide products

Non-ribosomal peptide synthetases (NRPS) are large modular enzymes that govern the synthesis of numerous biotechnologically relevant products. Their mode of action is frequently compared to an assembly line, in which each module acts in a semi-autonomous but coordinated manner to add a specific monomer to a growing peptide chain, unfettered by ribosomal constraints. The modular nature of these systems offers tantalising prospects for synthetic biology, wherein the assembly line is re-engineered at a genetic level to generate a specific or combinatorial modified product. However, despite some success stories, a “one size fits all” approach to NRPS synthetic biology remains elusive. This review examines both rational and random mutagenesis strategies that have been employed to modify NRPS function, in an attempt to highlight key points that should be considered when seeking to re-engineer an NRPS biosynthetic template.     

Where chemistry meets biology: the chemoenzymatic synthesis of nonribosomal peptides and polyketides

Intensive studies on modular biosynthetic assembly line machinery have provided researchers with a profound knowledge of how nonribosomal peptides and polyketides used in different therapeutic areas are produced in nature. This has opened the door for projects aiming to manipulate the assembly of these small molecules by directed and combinatorial approaches to produce novel compounds both in vivo and in vitro. Here, we highlight a set of recent chemoenzymatic attempts towards the synthesis of nonribosomal peptides and polyketides that aim to generate these structurally demanding compounds through the combined utilization of synthetic chemical tools and recombinant natural product metabolic enzymes.     

Bioinformatics tools for genome mining of polyketide and non-ribosomal peptides

Microbial natural products have played a key role in the development of clinical agents in nearly all therapeutic areas. Recent advances in genome sequencing have revealed that there is an incredible wealth of new polyketide and non-ribosomal peptide natural product diversity to be mined from genetic data. The diversity and complexity of polyketide and non-ribosomal peptide biosynthesis has required the development of unique bioinformatics tools to identify, annotate, and predict the structures of these natural products from their biosynthetic gene clusters. This review highlights and evaluates web-based bioinformatics tools currently available to the natural product community for genome mining to discover new polyketides and non-ribosomal peptides.     

Tools for Selective Enzyme Reaction Steps in the Synthesis of Laboratory Chemicals

The need for more selective reactions steps and the compatibility between process steps which follow on from each other has been a major driving force for organic synthesis. The synthesis of chiral compounds, metabolites, new chemical entities and natural products by a combination of chemical and enzyme reaction steps has become well established, due the existence of stable enzymes as selective catalysts which are inherently chiral by nature. Auxiliary tools such as suitable transfer reagents for reaching complete conversion, easy and robust reaction control as well as tools for straightforward workup and purification of the final product have been developed. Selective enzyme reaction steps in the area of hydrolyses, oxidation steps including hydroxylation and the Baeyer‐Villiger oxidation, carbon‐carbon bond formation and glycosylation reactions have compared favorably with existing methods of classical organic synthesis. The tools developed during optimization and scale‐up of these enzyme reaction steps have the potential to shorten development time. The introduction of selective enzyme reactions into an entire synthetic process has resulted in harmonization of improvements in economic efficiency with resultant solutions to health, safety and environment problems. This will become even more important in industrial synthetic chemistry in the future, for convenient solutions to certain intractable synthetic problems and for expanding the repertoire of chemistry by modular biocatalysts. Efficient isolation procedures for the final product are essential to take full advantage of the biocatalytic conversion to obtain high product yields.     

新颖的黏细菌模块化天然产物装配线

黏细菌的显著特征之一是能够合成结构多样、功能丰富的天然产物．模块化聚酮合酶(PKS)和非核糖体肽合成酶(NRPS)途径是黏细菌合成天然产物的主要方式．与经典模块PKS/NRPS相比,黏细菌来源的模块化PKS/NRPS常表现出新颖的装配特征,显示出多样化的遗传加工潜能和装配产物结构多样性．本文综合归类分析了黏细菌来源的模块化PKS/NRPS遗传装配线类型及其对应化合物的生化结构特征,图文并茂地呈现了黏细菌在遗传、生化、组合生物合成、进化和药物开发领域的生机和潜能,并展望了基因组学时代带来的契机．     

Gel-free mass spectrometry-based high throughput proteomics: tools for studying biological response of proteins and proteomes

Revolutionary advances in biological mass spectrometry (MS) have provided a basic tool to make possible comprehensive proteomic analysis. Traditionally, two-dimensional gel electrophoresis has been used as a separation method coupled with MS to facilitate analysis of complex protein mixtures. Despite the utility of this method, the many challenges of comprehensive proteomic analysis has motivated the development of gel-free MS-based strategies to obtain information not accessible using two-dimensional gel separations. These advanced strategies have enabled researchers to dig deeper into complex proteomes, gaining insights into the composition, quantitative response, covalent modifications and macromolecular interactions of proteins that collectively drive cellular function. This review describes the current state of gel-free, high throughput proteomic strategies using MS, including (i) the separation approaches commonly used for complex mixture analysis; (ii) strategies for large-scale quantitative analysis; (iii) analysis of post-translational modifications; and (iv) recent advances and future directions. The use of these strategies to make new discoveries at the proteome level into the effects of disease or other cellular perturbations is discussed in a variety of contexts, providing information on the potential of these tools in electromagnetic field research.     

Tools and challenges for diversity-driven proteomics in Brazil

Our current knowledge in biology has been mostly derived from studying model organisms and cell lines in which only a small fraction of all described species have been extensively studied. Although these model organisms are amenable to genetic manipulations, this blinds researchers to the true variability of life. Groundbreaking discoveries are often achieved by analyzing "noncanonical" species; for example, the characterization of Taq polymerase from Thermus aquaticus ultimately led to a revolution in the field of molecular biology. Brazil possesses a rich biodiversity and a considerable fraction of Brazilian groups use current proteomic techniques to explore this natural treasure-trove. However, in our opinion, much more than the widely adopted peptide spectrum match approach is required to explore this rich "proteomosphere." Here, we provide a critical overview of the available strategies for the analysis of proteomic data from "noncanonical" biological samples (e.g. proteins from unsequenced genomes or genomes with high levels of polymorphisms), and demonstrate some limitations of existing approaches for large-scale protein identification and quantitation. An understanding of the premises behind these computational tools is necessary to properly deal with their limitations and draw accurate conclusions.     

Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with all compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Overall, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.     

From proteomics toward systems biology: integration of different types of proteomics data into network models

Living organisms are comprised of various systems at different levels, i.e., organs, tissues, and cells. Each system carries out its diverse functions in response to environmental and genetic perturbations, by utilizing biological networks, in which nodal components, such as, DNA, mRNAs, proteins, and metabolites, closely interact with each other. Systems biology investigates such systems by producing comprehensive global data that represent different levels of biological information, i.e., at the DNA, mRNA, protein, or metabolite levels, and by integrating this data into network models that generate coherent hypotheses for given biological situations. This review presents a systems biology framework, called the 'Integrative Proteomics Data Analysis Pipeline' (IPDAP), which generates mechanistic hypotheses from network models reconstructed by integrating diverse types of proteomic data generated by mass spectrometry-based proteomic analyses. The devised framework includes a serial set of computational and network analysis tools. Here, we demonstrate its functionalities by applying these tools to several conceptual examples.     

DomPep--a general method for predicting modular domain-mediated protein-protein interactions

Protein-protein interactions (PPIs) are frequently mediated by the binding of a modular domain in one protein to a short, linear peptide motif in its partner. The advent of proteomic methods such as peptide and protein arrays has led to the accumulation of a wealth of interaction data for modular interaction domains. Although several computational programs have been developed to predict modular domain-mediated PPI events, they are often restricted to a given domain type. We describe DomPep, a method that can potentially be used to predict PPIs mediated by any modular domains. DomPep combines proteomic data with sequence information to achieve high accuracy and high coverage in PPI prediction. Proteomic binding data were employed to determine a simple yet novel parameter Ligand-Binding Similarity which, in turn, is used to calibrate Domain Sequence Identity and Position-Weighted-Matrix distance, two parameters that are used in constructing prediction models. Moreover, DomPep can be used to predict PPIs for both domains with experimental binding data and those without. Using the PDZ and SH2 domain families as test cases, we show that DomPep can predict PPIs with accuracies superior to existing methods. To evaluate DomPep as a discovery tool, we deployed DomPep to identify interactions mediated by three human PDZ domains. Subsequent in-solution binding assays validated the high accuracy of DomPep in predicting authentic PPIs at the proteome scale. Because DomPep makes use of only interaction data and the primary sequence of a domain, it can be readily expanded to include other types of modular domains.     

Biosynthetic engineering of nonribosomal peptide synthetases

From the evolutionary melting pot of natural product synthetase genes, microorganisms elicit antibiotics, communication tools, and iron scavengers. Chemical biologists manipulate these genes to recreate similarly diverse and potent biological activities not on evolutionary time scales but within months. Enzyme engineering has progressed considerably in recent years and offers new screening, modelling, and design tools for natural product designers. Here, recent advances in enzyme engineering and their application to nonribosomal peptide synthetases are reviewed. Among the nonribosomal peptides that have been subjected to biosynthetic engineering are the antibiotics daptomycin, calcium‐dependent antibiotic, and gramicidin S. With these peptides, incorporation of unnatural building blocks and modulation of bioactivities via various structural modifications have been successfully demonstrated. Natural product engineering on the biosynthetic level is not a reliable method yet. However, progress in the understanding and manipulation of biosynthetic pathways may enable the routine production of optimized peptide drugs in the near future. Copyright © 2016 European Peptide Society and John Wiley & Sons, Ltd.