High-throughput expression of C. elegans proteins

In silico characterization of fructosyl peptide oxidase properties from Eupenicillium terrenum

Fructosyl peptide oxidase (FPOX) enzyme from Eupenicillium terrenum has a high potential to be applied as a diagnostic enzyme. The aim of the present study is the characterization of FPOX from E. terrenum using different bioinformatics tools. The computational prediction of the RNA and protein secondary structures of FPOX, solubility profile in Escherichia coli, stability, domains, and functional properties were performed. In the FPOX protein, six motifs were detected. The d-amino acid oxidase motif was found as the most important motif that is a FAD-dependent oxidoreductase. The cysteines including 97, 154, 234, 280, and 360 showed a lower score than -10 that have a low possibility for participitation in the formation of the SS bond. The 56.52% of FPOX amino acids are nonpolar. Random coils are dominant in the FPOX sequence, followed by alpha-helix and extended strand. The fpox gene is capable of generating a stable RNA secondary structure (-423.90 kcal/mol) in E. coli. FPOX has a large number of hydrophobic amino acids. FPOX showed a low solubility in E. coli which has several aggregation-prone sites in its 3-D structure. According to the scores, the best mutation candidate for increasing solubility was the conversion of methionine 302 to arginine. The melting temperature of FPOX based on its amino acid sequence was 55°C to 65°C. The amounts of thermodynamic parameters for the FPOX enzyme were -137.4 kcal/mol, -3.59 kcal/(mol K), and -6.8 kcal/mol for standard folding enthalpy, heat capacity, and folding free energy, respectively. In conclusion, the in silico study of proteins can provide a valuable method for better understanding the protein properties and functions for use in our purposes.

Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit

While transcriptome- and proteome-wide technologies to assess processes in protein biogenesis are now widely available, we still lack global approaches to assay post-ribosomal biogenesis events, in particular those occurring in the eukaryotic secretory system. We here develop a method, SECRiFY, to simultaneously assess the secretability of >10⁵ protein fragments by two yeast species, S. cerevisiae and P. pastoris, using custom fragment libraries, surface display and a sequencing-based readout. Screening human proteome fragments with a median size of 50-100 amino acids, we generate datasets that enable datamining into protein features underlying secretability, revealing a striking role for intrinsic disorder and chain flexibility. The SECRiFY methodology generates sufficient amounts of annotated data for advanced machine learning methods to deduce secretability patterns. The finding that secretability is indeed a learnable feature of protein sequences provides a solid base for application-focused studies.

Developments and Applications of Functional Protein Microarrays

Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.

Hot CoFi Blot: A High-Throughput Colony-Based Screen for Identifying More Thermally Stable Protein Variants

Highly soluble and stable proteins are desirable for many different applications, from basic science to reaching a cancer patient in the form of a biological drug. For X-ray crystallography-where production of a protein crystal might take weeks and even months-a stable protein sample of high purity and concentration can greatly increase the chances of producing a well-diffracting crystal. For a patient receiving a specific protein drug, its safety, efficacy, and even cost are factors affected by its solubility and stability. Increased protein expression and protein stability can be achieved by randomly altering the coding sequence. As the number of mutants generated might be overwhelming, a powerful protein expression and stability screen is required. In this chapter, we describe a colony filtration technology, which allows us to screen random mutagenesis libraries for increased thermal stability-the Hot CoFi blot. We share how to create the random mutagenesis library, how to perform the Hot CoFi blot, and how to identify more thermally stable clones. We use the Tobacco Etch Virus protease as a target to exemplify the procedure.

Correlation Between Protein Primary Structure and Soluble Expression Level of HSA dAb in Escherichia coli

It is widely accepted that features such as pI, length, molecular mass and amino acid (AA) sequence have a significant influence on protein solubility. Here, we mainly focused on AA composition and explored those that most affected the soluble expression level of human serum albumin (HSA) domain antibody (dAb). The soluble expression and sequence of 65 dAb variants were analysed using clustering and linear modelling. Certain AAs significantly affected the soluble expression level of dAb, with the specific AA combinations being (S, R, N, D, Q), (G, R, C, N, S) and (R, S, G); these combinations respectively affected the dAb expression level in the broth supernatant, the level in the pellet lysate and total soluble dAb. Among the 20 AAs, R displayed a negative influence on the soluble expression level, whereas G and S showed positive effects. A linear model was built to predict the soluble expression level from the sequence; this model had a prediction accuracy of 80%. In summary, increasing the content of polar AAs, especially G and S, and decreasing the content of R, was helpful to improve the soluble expression level of HSA dAb.

Rational identification of aggregation hotspots based on secondary structure and amino acid hydrophobicity

Insolubility of proteins expressed in the Escherichia coli expression system hinders the progress of both basic and applied research. Insoluble proteins contain residues that decrease their solubility (aggregation hotspots). Mutating these hotspots to optimal amino acids is expected to improve protein solubility. To date, however, the identification of these hotspots has proven difficult. In this study, using a combination of approaches involving directed evolution and primary sequence analysis, we found two rules to help inductively identify hotspots: the α-helix rule, which focuses on the hydrophobicity of amino acids in the α-helix structure, and the hydropathy contradiction rule, which focuses on the difference in hydrophobicity relative to the corresponding amino acid in the consensus protein. By properly applying these two rules, we succeeded in improving the probability that expressed proteins would be soluble. Our methods should facilitate research on various insoluble proteins that were previously difficult to study due to their low solubility.

Successful completion of a semi-automated enzyme-free cloning method

Nowadays, in scientific fields such as Structural Biology or Vaccinology, there is an increasing need of fast, effective and reproducible gene cloning and expression processes. Consequently, the implementation of robotic platforms enabling the automation of protocols is becoming a pressing demand. The main goal of our study was to set up a robotic platform devoted to the high-throughput automation of the polymerase incomplete primer extension cloning method, and to evaluate its efficiency compared to that achieved manually, by selecting a set of bacterial genes that were processed either in the automated platform (330) or manually (94). Here we show that we successfully set up a platform able to complete, with high efficiency, a wide range of molecular biology and biochemical steps. 329 gene targets (99 %) were effectively amplified using the automated procedure and 286 (87 %) of these PCR products were successfully cloned in expression vectors, with cloning success rates being higher for the automated protocols respect to the manual procedure (93.6 and 74.5 %, respectively).

New and Improved Techniques for the Study of Pathogenic Fungi

Fungal pathogens pose serious threats to human, plant, and ecosystem health. Improved diagnostics and antifungal strategies are therefore urgently required. Here, we review recent developments in online bioinformatic tools and associated interactive data archives, which enable sophisticated comparative genomics and functional analysis of fungal pathogens in silico. Additionally, we highlight cutting-edge experimental techniques, including conditional expression systems, recyclable markers, RNA interference, genome editing, compound screens, infection models, and robotic automation, which are promising to revolutionize the study of both human and plant pathogenic fungi. These novel techniques will allow vital knowledge gaps to be addressed with regard to the evolution of virulence, host-pathogen interactions and antifungal drug therapies in both the clinic and agriculture. This, in turn, will enable delivery of improved diagnosis and durable disease-control strategies.

Plant-PrAS: a database of physicochemical and structural properties and novel functional regions in plant proteomes

Arabidopsis thaliana is an important model species for studies of plant gene functions. Research on Arabidopsis has resulted in the generation of high-quality genome sequences, annotations and related post-genomic studies. The amount of annotation, such as gene-coding regions and structures, is steadily growing in the field of plant research. In contrast to the genomics resource of animals and microorganisms, there are still some difficulties with characterization of some gene functions in plant genomics studies. The acquisition of information on protein structure can help elucidate the corresponding gene function because proteins encoded in the genome possess highly specific structures and functions. In this study, we calculated multiple physicochemical and secondary structural parameters of protein sequences, including length, hydrophobicity, the amount of secondary structure, the number of intrinsically disordered regions (IDRs) and the predicted presence of transmembrane helices and signal peptides, using a total of 208,333 protein sequences from the genomes of six representative plant species, Arabidopsis thaliana, Glycine max (soybean), Populus trichocarpa (poplar), Oryza sativa (rice), Physcomitrella patens (moss) and Cyanidioschyzon merolae (alga). Using the PASS tool and the Rosetta Stone method, we annotated the presence of novel functional regions in 1,732 protein sequences that included unannotated sequences from the Arabidopsis and rice proteomes. These results were organized into the Plant Protein Annotation Suite database (Plant-PrAS), which can be freely accessed online at http://plant-pras.riken.jp/.

Expression and solubility testing in a high-throughput environment

The expression and screening of the solubility of recombinant proteins is an important step in the high-throughput (HT) production of target proteins. For many applications, E. coli remains the most widely used expression system due to the relative ease of adapting it to HT pipelines. Herein is described a platform using a 96-well format for efficient expression and solubility screening of target proteins.

A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli

Background

Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods.

Results

This paper presents an extensive review of the existing models to predict protein solubility in Escherichia coli recombinant protein overexpression system. The models are investigated and compared regarding the datasets used, features, feature selection methods, machine learning techniques and accuracy of prediction. A discussion on the models is provided at the end.

Conclusions

This study aims to investigate extensively the machine learning based methods to predict recombinant protein solubility, so as to offer a general as well as a detailed understanding for researches in the field. Some of the models present acceptable prediction performances and convenient user interfaces. These models can be considered as valuable tools to predict recombinant protein overexpression results before performing real laboratory experiments, thus saving labour, time and cost.

C. elegans: an invaluable model organism for the proteomics studies of the cholesterol-mediated signaling pathway

With the availability of its complete genome sequence and unique biological features relevant to human disease, Caenorhabditis elegans has become an invaluable model organism for the studies of proteomics, leading to the elucidation of nematode gene function. A journey from the genome to proteome of C. elegans may begin with preparation of expressed proteins, which enables a large-scale analysis of all possible proteins expressed under specific physiological conditions. Although various techniques have been used for proteomic analysis of C. elegans, systematic high-throughput analysis is still to come in order to accommodate studies of post-translational modification and quantitative analysis. Given that no integrated C. elegans protein expression database is available, it is about time that a global C. elegans proteome project is launched through which datasets of transcriptomes, protein-protein interaction and functional annotation can be integrated. As an initial target of a pilot project of the C. elegans proteome project, the cholesterol-mediated signaling pathway will be an excellent example since, like in other organisms, it is one of the key controlling pathways in cell growth and development in C. elegans. As this field tends to broaden to functional proteomics, there is a high demand to develop the versatile proteome informatics tools that can mange many different data in an integrative manner.

ESPRESSO: a system for estimating protein expression and solubility in protein expression systems

Recombinant protein technology is essential for conducting protein science and using proteins as materials in pharmaceutical or industrial applications. Although obtaining soluble proteins is still a major experimental obstacle, knowledge about protein expression/solubility under standard conditions may increase the efficiency and reduce the cost of proteomics studies. In this study, we present a computational approach to estimate the probability of protein expression and solubility for two different protein expression systems: in vivo Escherichia coli and wheat germ cell-free, from only the sequence information. It implements two kinds of methods: a sequence/predicted structural property-based method that uses both the sequence and predicted structural features, and a sequence pattern-based method that utilizes the occurrence frequencies of sequence patterns. In the benchmark test, the proposed methods obtained F-scores of around 70%, and outperformed publicly available servers. Applying the proposed methods to genomic data revealed that proteins associated with translation or transcription have a strong tendency to be expressed as soluble proteins by the in vivo E. coli expression system. The sequence pattern-based method also has the potential to indicate a candidate region for modification, to increase protein solubility. All methods are available for free at the ESPRESSO server (http://mbs.cbrc.jp/ESPRESSO).

Development-specific differences in the proteomics of Angiostrongylus cantonensis

Angiostrongyliasis is an emerging communicable disease. Several different hosts are required to complete the life cycle of Angiostrongylus cantonensis. However, we lack a complete understanding of variability of proteins across different developmental stages and their contribution to parasite survival and progression. In this study, we extracted soluble proteins from various stages of the A. cantonensis life cycle [female adults, male adults, the fifth-stage female larvae (FL5), the fifth-stage male larvae (ML5) and third-stage larvae (L3)], separated those proteins using two-dimensional difference gel electrophoresis (2D-DIGE) at pH 4-7, and analyzed the gel images using DeCyder 7.0 software. This proteomic analysis produced a total of 183 different dominant protein spots. Thirty-seven protein spots were found to have high confidence scores (>95%) by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Comparative proteomic analyses revealed that 29 spots represented cytoskeleton-associated proteins and functional proteins. Eight spots were unnamed proteins. Twelve protein spots that were matched to the EST of different-stage larvae of A. cantonensis were identified. Two genes and the internal control 18s were chosen for quantitative real-time PCR (qPCR) and the qPCR results were consistent with those of the DIGE studies. These findings will provide a new basis for understanding the characteristics of growth and development of A. cantonensis and the host-parasite relationship. They may also assist searches for candidate proteins suitable for use in diagnostic assays and as drug targets for the control of eosinophilic meningitis caused by A. cantonensis.

Electrostatic mis-interactions cause overexpression toxicity of proteins in E. coli

A majority of E. coli proteins when overexpressed inhibit its growth, but the reasons behind overexpression toxicity of proteins remain unknown. Understanding the mechanism of overexpression toxicity is important from evolutionary, biotechnological and possibly clinical perspectives. Here we study sequence and functional features of cytosolic proteins of E. coli associated with overexpression toxicity to understand its mechanism. We find that number of positively charged residues is significantly higher in proteins showing overexpression toxicity. Very long proteins also show high overexpression toxicity. Among the functional classes, transcription factors and regulatory proteins are enriched in toxic proteins, while catalytic proteins are depleted. Overexpression toxicity could be predicted with reasonable accuracy using these few properties. The importance of charged residues in overexpression toxicity indicates that nonspecific electrostatic interactions resulting from protein overexpression cause toxicity of these proteins and suggests ways to improve the expression level of native and foreign proteins in E. coli for basic research and biotechnology. These results might also be applicable to other bacterial species.

Chaperone-interacting TPR proteins in Caenorhabditis elegans

The ATP-hydrolyzing molecular chaperones Hsc70/Hsp70 and Hsp90 bind a diverse set of tetratricopeptide repeat (TPR)-containing cofactors via their C-terminal peptide motifs IEEVD and MEEVD. These cochaperones contribute to substrate turnover and confer specific activities to the chaperones. Higher eukaryotic genomes encode a large number of TPR-domain-containing proteins. The human proteome contains more than 200 TPR proteins, and that of Caenorhabditis elegans, about 80. It is unknown how many of them interact with Hsc70 or Hsp90. We systematically screened the C. elegans proteome for TPR-domain-containing proteins that likely interact with Hsc70 and Hsp90 and ranked them due to their similarity with known chaperone-interacting TPRs. We find C. elegans to encode many TPR proteins, which are not present in yeast. All of these have homologs in fruit fly or humans. Highly ranking uncharacterized open reading frames C33H5.8, C34B2.5 and ZK370.8 may encode weakly conserved homologs of the human proteins RPAP3, TTC1 and TOM70. C34B2.5 and ZK370.8 bind both Hsc70 and Hsp90 with low micromolar affinities. Mutation of amino acids involved in EEVD binding disrupts the interaction. In vivo, ZK370.8 is localized to mitochondria in tissues with known chaperone requirements, while C34B2.5 colocalizes with Hsc70 in intestinal cells. The highest-ranking open reading frame with non-conserved EEVD-interacting residues, F52H3.5, did not show any binding to Hsc70 or Hsp90, suggesting that only about 15 of the TPR-domain-containing proteins in C. elegans interact with chaperones, while the many others may have evolved to bind other ligands.

Current state and recent advances in biopharmaceutical production in Escherichia coli, yeasts and mammalian cells

Almost all of the 200 or so approved biopharmaceuticals have been produced in one of three host systems: the bacterium Escherichia coli, yeasts (Saccharomyces cerevisiae, Pichia pastoris) and mammalian cells. We describe the most widely used methods for the expression of recombinant proteins in the cytoplasm or periplasm of E. coli, as well as strategies for secreting the product to the growth medium. Recombinant expression in E. coli influences the cell physiology and triggers a stress response, which has to be considered in process development. Increased expression of a functional protein can be achieved by optimizing the gene, plasmid, host cell, and fermentation process. Relevant properties of two yeast expression systems, S. cerevisiae and P. pastoris, are summarized. Optimization of expression in S. cerevisiae has focused mainly on increasing the secretion, which is otherwise limiting. P. pastoris was recently approved as a host for biopharmaceutical production for the first time. It enables high-level protein production and secretion. Additionally, genetic engineering has resulted in its ability to produce recombinant proteins with humanized glycosylation patterns. Several mammalian cell lines of either rodent or human origin are also used in biopharmaceutical production. Optimization of their expression has focused on clonal selection, interference with epigenetic factors and genetic engineering. Systemic optimization approaches are applied to all cell expression systems. They feature parallel high-throughput techniques, such as DNA microarray, next-generation sequencing and proteomics, and enable simultaneous monitoring of multiple parameters. Systemic approaches, together with technological advances such as disposable bioreactors and microbioreactors, are expected to lead to increased quality and quantity of biopharmaceuticals, as well as to reduced product development times.

Sweeping away protein aggregation with entropic bristles: intrinsically disordered protein fusions enhance soluble expression

Intrinsically disordered, highly charged protein sequences act as entropic bristles (EBs), which, when translationally fused to partner proteins, serve as effective solubilizers by creating both a large favorable surface area for water interactions and large excluded volumes around the partner. By extending away from the partner and sweeping out large molecules, EBs can allow the target protein to fold free from interference. Using both naturally occurring and artificial polypeptides, we demonstrate the successful implementation of intrinsically disordered fusions as protein solubilizers. The artificial fusions discussed herein have a low level of sequence complexity and a high net charge but are diversified by means of distinctive amino acid compositions and lengths. Using 6xHis fusions as controls, soluble protein expression enhancements from 65% (EB60A) to 100% (EB250) were observed for a 20-protein portfolio. Additionally, these EBs were able to more effectively solubilize targets compared to frequently used fusions such as maltose-binding protein, glutathione S-transferase, thioredoxin, and N utilization substance A. Finally, although these EBs possess very distinct physiochemical properties, they did not perturb the structure, conformational stability, or function of the green fluorescent protein or the glutathione S-transferase protein. This work thus illustrates the successful de novo design of intrinsically disordered fusions and presents a promising technology and complementary resource for researchers attempting to solubilize recalcitrant proteins.

PROSO II--a new method for protein solubility prediction

Many fields of science and industry depend on efficient production of active protein using heterologous expression in Escherichia coli. The solubility of proteins upon expression is dependent on their amino acid sequence. Prediction of solubility from sequence is therefore highly valuable. We present a novel machine-learning-based model called PROSO II which makes use of new classification methods and growth in experimental data to improve coverage and accuracy of solubility predictions. The classification algorithm is organized as a two-layered structure in which the output of a primary Parzen window model for sequence similarity and a logistic regression classifier of amino acid k-mer composition serve as input for a second-level logistic regression classifier. Compared with previously published research our model is trained on five times more data than used by any other method before (82 000 proteins). When tested on a separate holdout set not used at any point of method development our server attained the best results in comparison with other currently available methods: accuracy 75.4%, Matthew's correlation coefficient 0.39, sensitivity 0.731, specificity 0.759, gain (soluble) 2.263. In summary, due to utilization of cutting edge machine learning technologies combined with the largest currently available experimental data set the PROSO II server constitutes a substantial improvement in protein solubility predictions. PROSO II is available at http://mips.helmholtz-muenchen.de/prosoII.

Expression pattern analysis of regulatory transcription factors in Caenorhabditis elegans

Expression pattern data are fundamental to understanding transcriptional regulatory networks and the biological significance of such networks. For Caenorhabditis elegans, expression pattern analysis of transcription factor genes, with cellular resolution, typically involves generation of transcription factor gene/reporter gene fusions. This is followed by the creation of C. elegans strains transgenic for, and determination of expression patterns driven by, these fusions. Physiologically relevant regulatory relationships between transcription factors are both inferred from their expression patterns, in combination with protein-DNA interaction data, and evidenced from alterations of expression patterns when networks are disturbed.

A Gateway MultiSite recombination cloning toolkit

The generation of DNA constructs is often a rate-limiting step in conducting biological experiments. Recombination cloning of single DNA fragments using the Gateway system provided an advance over traditional restriction enzyme cloning due to increases in efficiency and reliability. Here we introduce a series of entry clones and a destination vector for use in two, three, and four fragment Gateway MultiSite recombination cloning whose advantages include increased flexibility and versatility. In contrast to Gateway single-fragment cloning approaches where variations are typically incorporated into model system-specific destination vectors, our Gateway MultiSite cloning strategy incorporates variations in easily generated entry clones that are model system-independent. In particular, we present entry clones containing insertions of GAL4, QF, UAS, QUAS, eGFP, and mCherry, among others, and demonstrate their in vivo functionality in Drosophila by using them to generate expression clones including GAL4 and QF drivers for various trp ion channel family members, UAS and QUAS excitatory and inhibitory light-gated ion channels, and QUAS red and green fluorescent synaptic vesicle markers. We thus establish a starter toolkit of modular Gateway MultiSite entry clones potentially adaptable to any model system. An inventory of entry clones and destination vectors for Gateway MultiSite cloning has also been established (www.gatewaymultisite.org).

Cloning, expression and purification of Pwo polymerase from Pyrococcus woesei

BACKGROUND AND OBJECTIVES

Pyrococcus woesei is a hyperthermophilic archaea and produces a heat stable polymerase (Pwo polymerase) that has proofreading activity.

MATERIALS AND METHODS

In this study, this microorganism was cultured, its DNA was extracted and the pwo gene polymerase was cloned, expressed and purified. The DNA sequence of the cloned gene was verified by sequencing. The pwo polymerase gene consists of 2,328 bps (775 amino acids with about 90 kD molecular weight). Cloning was done by GATEWAY™ Cloning System and for purification of recombinant protein; His6x-Tag was added to the C-terminus of the recombinant protein.

RESULTS AND CONCLUSION

We could purify Pwo polymerase enzyme by Ni-NTA resin. PCR assay showed that Pwo polymerase activity is comparable to a commercial Pfu polymerase activity.

A membrane-associated movement protein of Pelargonium flower break virus shows RNA-binding activity and contains a biologically relevant leucine zipper-like motif

Two small viral proteins (DGBp1 and DGBp2) have been proposed to act in a concerted manner to aid intra- and intercellular trafficking of carmoviruses though the distribution of functions and mode of action of each protein partner are not yet clear. Here we have confirmed the requirement of the DGBps of Pelargonium flower break virus (PFBV), p7 and p12, for pathogen movement. Studies focused on p12 have shown that it associates to cellular membranes, which is in accordance to its hydrophobic profile and to that reported for several homologs. However, peculiarities that distinguish p12 from other DGBps2 have been found. Firstly, it contains a leucine zipper-like motif which is essential for virus infectivity in plants. Secondly, it has an unusually long and basic N-terminal region that confers RNA binding activity. The results suggest that PFBV p12 may differ mechanistically from related proteins and possible roles of PFBV DGBps are discussed.

Recombinant expression and functional analysis of proteases from Streptococcus pneumoniae, Bacillus anthracis, and Yersinia pestis

Background

Uncharacterized proteases naturally expressed by bacterial pathogens represents important topic in infectious disease research, because these enzymes may have critical roles in pathogenicity and cell physiology. It has been observed that cloning, expression and purification of proteases often fail due to their catalytic functions which, in turn, cause toxicity in the E. coli heterologous host.

Results

In order to address this problem systematically, a modified pipeline of our high-throughput protein expression and purification platform was developed. This included the use of a specific E. coli strain, BL21(DE3) pLysS to tightly control the expression of recombinant proteins and various expression vectors encoding fusion proteins to enhance recombinant protein solubility. Proteases fused to large fusion protein domains, maltosebinding protein (MBP), SP-MBP which contains signal peptide at the N-terminus of MBP, disulfide oxidoreductase (DsbA) and Glutathione S-transferase (GST) improved expression and solubility of proteases. Overall, 86.1% of selected protease genes including hypothetical proteins were expressed and purified using a combination of five different expression vectors. To detect novel proteolytic activities, zymography and fluorescence-based assays were performed and the protease activities of more than 46% of purified proteases and 40% of hypothetical proteins that were predicted to be proteases were confirmed.

Conclusions

Multiple expression vectors, employing distinct fusion tags in a high throughput pipeline increased overall success rates in expression, solubility and purification of proteases. The combinatorial functional analysis of the purified proteases using fluorescence assays and zymography confirmed their function.

Specialized chromosomes and their uses in Caenorhabditis elegans

Research on Caenorhabditis elegans involves the use of a wide range of genetic and molecular tools consisting of chromosomal material captured and modified for specific purposes. These "specialized chromosomes" come in many forms ranging from relatively simple gene deletions to complex rearrangements involving endogenous chromosomes as well as transgenic constructs. In this chapter, we describe the specialized chromosomes that are available in C. elegans, their origins, practical considerations, and methods for generation and evaluation. We will summarize their uses for biological studies, and their contribution to our knowledge about chromosome biology.

A rapid protein folding assay for the bacterial periplasm

An array of genetic screens and selections has been developed for reporting protein folding and solubility in the cytoplasm of living cells. However, there are currently no analogous folding assays for the bacterial periplasm, despite the significance of this compartment for the expression of recombinant proteins, especially those requiring important posttranslational modifications (e.g., disulfide bond formation). Here, we describe an engineered genetic selection for monitoring protein folding in the periplasmic compartment of Escherichia coli cells. In this approach, target proteins are sandwiched between an N-terminal signal recognition particle (SRP)-dependent signal peptide and a C-terminal selectable marker, TEM-1 beta-lactamase. The resulting chimeras are localized to the periplasmic space via the cotranslational SRP pathway. Using a panel of native and heterologous proteins, we demonstrate that the folding efficiency of various target proteins correlates directly with in vivo beta-lactamase activity and thus resistance to ampicillin. We also show that this reporter is useful for the discovery of extrinsic periplasmic factors (e.g., chaperones) that affect protein folding and for obtaining folding-enhanced proteins via directed evolution. Collectively, these data demonstrate that our periplasmic folding reporter is a powerful tool for screening and engineering protein folding in a manner that does not require any structural or functional information about the target protein.

Learning to predict expression efficacy of vectors in recombinant protein production

Background

Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is to fuse a target protein into different vectors in Escherichia coli (E. coli). However, the production efficacy of different vectors varies for different target proteins. Trial-and-error is still the common practice to find out the efficacy of a vector for a given target protein. Previous studies are limited in that they assumed that proteins would be over-expressed and focused only on the solubility of expressed proteins. In fact, many pairings of vectors and proteins result in no expression.

Results

In this study, we applied machine learning to train prediction models to predict whether a pairing of vector-protein will express or not express in E. coli. For expressed cases, the models further predict whether the expressed proteins would be soluble. We collected a set of real cases from the clients of our recombinant protein production core facility, where six different vectors were designed and studied. This set of cases is used in both training and evaluation of our models. We evaluate three different models based on the support vector machines (SVM) and their ensembles. Unlike many previous works, these models consider the sequence of the target protein as well as the sequence of the whole fusion vector as the features. We show that a model that classifies a case into one of the three classes (no expression, inclusion body and soluble) outperforms a model that considers the nested structure of the three classes, while a model that can take advantage of the hierarchical structure of the three classes performs slight worse but comparably to the best model. Meanwhile, compared to previous works, we show that the prediction accuracy of our best method still performs the best. Lastly, we briefly present two methods to use the trained model in the design of the recombinant protein production systems to improve the chance of high soluble protein production.

Conclusion

In this paper, we show that a machine learning approach to the prediction of the efficacy of a vector for a target protein in a recombinant protein production system is promising and may compliment traditional knowledge-driven study of the efficacy. We will release our program to share with other labs in the public domain when this paper is published.

Comprehensive bioinformatics analysis of cell-free protein synthesis: identification of multiple protein properties that correlate with successful expression

High-throughput cell-free protein synthesis is being used increasingly in structural/functional genomics projects. However, the factors determining expression success are poorly understood. Here, we evaluated the expression of 3066 human proteins and their domains in a bacterial cell-free system and analyzed the correlation of protein expression with 39 physicochemical and structural properties of proteins. As a result of the bioinformatics analysis performed, we determined the 18 most influential features that affect protein amenability to cell-free expression. They include protein length; hydrophobicity; pI; content of charged, nonpolar, and aromatic residues;, cysteine content; solvent accessibility; presence of coiled coil; content of intrinsically disordered and structured (alpha-helix and beta-sheet) sequence; number of disulfide bonds and functional domains; presence of transmembrane regions; PEST motifs; and signaling sequences. This study represents the first comprehensive bioinformatics analysis of heterologous protein synthesis in a cell-free system. The rules and correlations revealed here provide a plethora of important insights into rationalization of cell-free protein production and can be of practical use for protein engineering with the aim of increasing expression success.-Kurotani, A., Takagi, T., Toyama, M., Shirouzu, M., Yokoyama, S., Fukami, Y., Tokmakov, A. A. Comprehensive bioinformatics analysis of cell-free protein synthesis: identification of multiple protein properties that correlate with successful expression.

Heterologous expression of L. major proteins in S. cerevisiae: a test of solubility, purity, and gene recoding

High level expression of many eukaryotic proteins for structural analysis is likely to require a eukaryotic host since many proteins are either insoluble or lack essential post-translational modifications when expressed in E. coli. The well-studied eukaryote Saccharomyces cerevisiae possesses several attributes of a good expression host: it is simple and inexpensive to culture, has proven genetic tractability, and has excellent recombinant DNA tools. We demonstrate here that this yeast exhibits three additional characteristics that are desirable in a eukaryotic expression host. First, expression in yeast significantly improves the solubility of proteins that are expressed but insoluble in E. coli. The expression and solubility of 83 Leishmania major ORFs were compared in S. cerevisiae and in E. coli, with the result that 42 of the 64 ORFs with good expression and poor solubility in E. coli are highly soluble in S. cerevisiae. Second, the yield and purity of heterologous proteins expressed in yeast is sufficient for structural analysis, as demonstrated with both small scale purifications of 21 highly expressed proteins and large scale purifications of 2 proteins, which yield highly homogeneous preparations. Third, protein expression can be improved by altering codon usage, based on the observation that a codon-optimized construct of one ORF yields three-fold more protein. Thus, these results provide direct verification that high level expression and purification of heterologous proteins in S. cerevisiae is feasible and likely to improve expression of proteins whose solubility in E. coli is poor.

Screening colonies of pooled ORFeomes (SCOOP): a rapid and efficient strategy for expression screening ORFeomes in Escherichia coli

We have designed and evaluated a novel strategy for screening large gene collections available as GATEWAY-adapted ORFeomes for soluble recombinant overexpression in Escherichia coli, called "Screening Colonies of ORFeome Pools" (SCOOP). From a large gene collection we could, without expensive multi-well based cloning and expression screening, determine which targets were suitable for large-scale expression and purification. Normalized bacterial overnight cultures of an ORF collection of entry clones derived from the Kaposi's sarcoma associated herpesvirus (KSHV) were pooled and used for the isolation of plasmid DNA. The resulting ORF library was subcloned into a prokaryotic expression vector in a single recombination reaction and was subsequently screened with the colony filtration (CoFi) blot for soluble recombinant overexpression in E. coli. ORFs determined to express soluble recombinant proteins were identified by sequencing and analysed by small-scale IMAC and SDS-PAGE. As a reference, we subcloned all ORFs individually using a traditional multi-well based procedure and screened them for soluble expression. Our results show that the two processes have a similar efficiency as 23 and 25 out of 74 assessable clones were identified as soluble expressers using SCOOP and the traditional multi-well procedure, respectively. Because SCOOP minimises costs for cloning and expression screening, it constitutes an interesting alternative for establishing expression of large gene collections. SCOOP also allows affordable screening in alternative vectors, expression strains and physical conditions, which is challenging in large-scale protein production programs. With this strategy in hand success rates for future proteome-wide protein production efforts can be significantly increased.

Generation of expression clone set for functional proteomics of human gastric and liver cancers

Two thousand sixty-eight multi-purpose expression clones for the 326 candidate genes related to gastric or liver cancers were constructed using the Gateway system. These clones can be expressed as His, Glutathione-S-transferase (GST) or Enhanced version of the green fluorescent protein (EGFP) fusion proteins in E. coli, insect cells or mammalian cells. For the 246 E. coli expression clones, the GST fusion proteins had greater expression efficiency and solubility than the His fusion proteins. Approximately 20% of the expressed proteins had unexpected molecular weights. A detailed sequence analysis of these clones revealed frameshift mutations resulting from insertion, deletion or substitution of nucleotides. The results indicate that these changes in the candidate genes may affect the occurrence of gastric or liver cancers. In addition, when 105 proteins, which were expressed in E. coli at very low or undetectable levels, were expressed in insect cells, 76% of the proteins were expressed very well and most were soluble. We also found that most of the 30 proteins prepared using EGFP mammalian expression clones were localized to cellular compartments expected by Gene ontology (GO) and this localization was unaffected if the EGFP-fusion was at the N-terminal or C-terminal region of the protein. Antibody production and subcellular localization analysis of the candidate genes as well as a screen of genes involved in carcinogenesis pathways are currently in progress using these expression clones. These studies provide a valuable resource for developing a better understanding of the molecular mechanism of carcinogenesis in both gastric and liver cancer and would be very helpful in diagnosis and therapeutic predictions.

SOLpro: accurate sequence-based prediction of protein solubility

MOTIVATION

Protein insolubility is a major obstacle for many experimental studies. A sequence-based prediction method able to accurately predict the propensity of a protein to be soluble on overexpression could be used, for instance, to prioritize targets in large-scale proteomics projects and to identify mutations likely to increase the solubility of insoluble proteins.

RESULTS

Here, we first curate a large, non-redundant and balanced training set of more than 17 000 proteins. Next, we extract and study 23 groups of features computed directly or predicted (e.g. secondary structure) from the primary sequence. The data and the features are used to train a two-stage support vector machine (SVM) architecture. The resulting predictor, SOLpro, is compared directly with existing methods and shows significant improvement according to standard evaluation metrics, with an overall accuracy of over 74% estimated using multiple runs of 10-fold cross-validation.

Generation of baculovirus vectors for the high-throughput production of proteins in insect cells

The baculovirus expression system is one of the most popular methods used for the production of recombinant proteins but has several complex steps which have proved inherently difficult to adapt to a multi-parallel process. We have developed a bacmid vector that does not require any form of selection pressure to separate recombinant virus from non-recombinant parental virus. The method relies on homologous recombination in insect cells between a transfer vector containing a gene to be expressed and a replication-deficient bacmid. The target gene replaces a bacterial replicon at the polyhedrin loci, simultaneously restoring a virus gene essential for replication. Therefore, only recombinant virus can replicate facilitating the rapid production of multiple recombinant viruses on automated platforms in a one-step procedure. Using this vector allowed us to automate the generation of multiple recombinant viruses with a robotic liquid handler and then rapidly screen infected insect cell supernatant for the presence of secreted proteins.

Proteome-Scale Analysis of Biochemical Activity

During the last 10 years, there has been a large increase in the number of genome sequences available for study, altering the way that the biology of organisms is studied. In particular, scientific attention has increasingly focused on the proteome, and specifically on the role of all the proteins encoded by the genome. We focus here on several aspects of this problem. We describe several technologies in widespread use to clone genes on a genome-wide scale, and to express and purify the proteins encoded by these genes. We also describe a number of methods that have been developed to analyze various biochemical properties of the proteins, with attention to the methodology and the limitations of the approaches, followed by a look at possible developments in the next decade.

Development of new tools for studying gene function in fungi based on the Gateway system

Genomic information of many fungi has been released but large scale functional genomic studies are still limited by a lack of high-throughput methods. The low rates of homologous recombination and low rates of transformation are limiting steps in filamentous fungi, but the molecular tools are also lagging behind. In this paper we describe two new high-throughput functional genomic tools for filamentous fungi that are based on the Gateway technology. One system is the Gateway RNAi vector for fungi that allows gene silencing in a high-throughput manner. The other system is a high-throughput deletion construct system. These systems were tested using the PAC1 gene of Colletotrichum gloeosporioides. Using these types of approaches, large scale functional genomics experiments can be performed in filamentous fungi.

The in vivo and in vitro aggregation properties of globular proteins correlate with their conformational stability: the SH3 case

Protein misfolding and deposition underlie an increasing number of debilitating human disorders and constitute a problem of major concern in biotechnology. In the last years, in vitro studies have provided valuable insights into the physicochemical principles underlying protein aggregation. Nevertheless, information about the determinants of protein deposition within the cell is scarce and only a few systematic studies comparing in vitro and in vivo data have been reported. Here, we have used the SH3 domain of alpha-spectrin as a model globular protein in an attempt to understand the relationship between protein aggregation in the test-tube and in the more complex cellular environment. The investigation of the aggregation in Escherichia coli of this domain and a large set of mutants, together with the analysis of their sequential and conformational properties allowed us to evaluate the contribution of different polypeptidic factors to the cellular deposition of globular proteins. The data presented here suggest that the rules that govern in vitro protein aggregation are also valid in in vivo contexts. They also provide relevant insights into intracellular protein deposition in both conformational diseases and recombinant protein production.

Pharmacogenomics in Alzheimer's disease

Pharmacological treatment in Alzheimer's disease (AD) accounts for 10-20% of direct costs, and fewer than 20% of AD patients are moderate responders to conventional drugs (donepezil, rivastigmine, galantamine, memantine), with doubtful cost-effectiveness. Both AD pathogenesis and drug metabolism are genetically regulated complex traits in which hundreds of genes cooperatively participate. Structural genomics studies demonstrated that more than 200 genes might be involved in AD pathogenesis regulating dysfunctional genetic networks leading to premature neuronal death. The AD population exhibits a higher genetic variation rate than the control population, with absolute and relative genetic variations of 40-60% and 0.85-1.89%, respectively. AD patients also differ in their genomic architecture from patients with other forms of dementia. Functional genomics studies in AD revealed that age of onset, brain atrophy, cerebrovascular hemodynamics, brain bioelectrical activity, cognitive decline, apoptosis, immune function, lipid metabolism dyshomeostasis, and amyloid deposition are associated with AD-related genes. Pioneering pharmacogenomics studies also demonstrated that the therapeutic response in AD is genotype-specific, with apolipoprotein E (APOE) 4/4 carriers the worst responders to conventional treatments. About 10-20% of Caucasians are carriers of defective cytochrome P450 (CYP) 2D6 polymorphic variants that alter the metabolism and effects of AD drugs and many psychotropic agents currently administered to patients with dementia. There is a moderate accumulation of AD-related genetic variants of risk in CYP2D6 poor metabolizers (PMs) and ultrarapid metabolizers (UMs), who are the worst responders to conventional drugs. The association of the APOE-4 allele with specific genetic variants of other genes (e.g., CYP2D6, angiotensin-converting enzyme [ACE]) negatively modulates the therapeutic response to multifactorial treatments affecting cognition, mood, and behavior. Pharmacogenetic and pharmacogenomic factors may account for 60-90% of drug variability in drug disposition and pharmacodynamics. The incorporation of pharmacogenetic/pharmacogenomic protocols to AD research and clinical practice can foster therapeutics optimization by helping to develop cost-effective pharmaceuticals and improving drug efficacy and safety.

Mining predicted essential genes of Brugia malayi for nematode drug targets

We report results from the first genome-wide application of a rational drug target selection methodology to a metazoan pathogen genome, the completed draft sequence of Brugia malayi, a parasitic nematode responsible for human lymphatic filariasis. More than 1.5 billion people worldwide are at risk of contracting lymphatic filariasis and onchocerciasis, a related filarial disease. Drug treatments for filariasis have not changed significantly in over 20 years, and with the risk of resistance rising, there is an urgent need for the development of new anti-filarial drug therapies. The recent publication of the draft genomic sequence for B. malayi enables a genome-wide search for new drug targets. However, there is no functional genomics data in B. malayi to guide the selection of potential drug targets. To circumvent this problem, we have utilized the free-living model nematode Caenorhabditis elegans as a surrogate for B. malayi. Sequence comparisons between the two genomes allow us to map C. elegans orthologs to B. malayi genes. Using these orthology mappings and by incorporating the extensive genomic and functional genomic data, including genome-wide RNAi screens, that already exist for C. elegans, we identify potentially essential genes in B. malayi. Further incorporation of human host genome sequence data and a custom algorithm for prioritization enables us to collect and rank nearly 600 drug target candidates. Previously identified potential drug targets cluster near the top of our prioritized list, lending credibility to our methodology. Over-represented Gene Ontology terms, predicted InterPro domains, and RNAi phenotypes of C. elegans orthologs associated with the potential target pool are identified. By virtue of the selection procedure, the potential B. malayi drug targets highlight components of key processes in nematode biology such as central metabolism, molting and regulation of gene expression.

A correlation analysis of protein characteristics associated with genome-wide high throughput expression and solubility of Streptococcus pneumoniae proteins

We have developed and evaluated a highly parallel protein expression and purification system using ORFs derived from the pathogenic bacterium Streptococcus pneumoniae as a representative test case in conjunction with the Gateway cloning technology. Establishing high throughput protein production capability is essential for genome-wide characterization of protein function. In this study, we focused on protein expression and purification outcomes generated from an expression vector which encodes an NH(2)-terminal hexa-histidine tag and a COOH-terminal S-tag. Purified recombinant proteins were validated by SDS-PAGE, followed by in-gel digestion and identification by MALDI-TOF/TOF analysis. Starting with 1360 sequence-validated destination clones we examined correlation analyses of expression and solubility of a wide variety of recombinant proteins. In total, 428 purified proteins (31%) were recovered in soluble form. We describe a semi-quantitative scoring method using an S-tag assay to improve the throughput and efficiency of expression and solubility studies for recombinant proteins. Given a relatively large dataset derived from proteins representing all functional groups in a microbial genome we correlated various protein characteristics as they relate to protein expression outcomes.