Facile Method for High-throughput Identification of Stabilizing Mutations

Characterizing the effects of mutations on stability is critical for understanding the function and evolution of proteins and improving their biophysical properties. High throughput folding and abundance assays have been successfully used to characterize missense mutations associated with reduced stability. However, screening for increased thermodynamic stability is more challenging since such mutations are rarer and their impact on assay readout is more subtle. Here, a multiplex assay for high throughput screening of protein folding was developed by combining deep mutational scanning, fluorescence-activated cell sorting, and deep sequencing. By analyzing a library of 2000 variants of Adenylate kinase we demonstrate that the readout of the method correlates with stability and that mutants with up to 13 °C increase in thermal melting temperature could be identified with low false positive rate. The discovery of many stabilizing mutations also enabled the analysis of general substitution patterns associated with increased stability in Adenylate kinase. This high throughput method to identify stabilizing mutations can be combined with functional screens to identify mutations that improve both stability and activity.     

From Never Born Proteins to Minimal Living Cells: Two Projects in Synthetic Biology

The Never Born Proteins (NBPs) and the Minimal Cell projects are two currently developed research lines belonging to the field of synthetic biology. The first deals with the investigation of structural and functional properties of de novo proteins with random sequences, selected and isolated using phage display methods. The minimal cell is the simplest cellular construct which displays living properties, such as self-maintenance, self-reproduction and evolvability. The semi-synthetic approach to minimal cells involves the use of extant genes and proteins in order to build a supramolecular construct based on lipid vesicles. Results and outlooks on these two research lines are shortly discussed, mainly focusing on their relevance to the origin of life studies. Presented at: National Workshop on Astrobiology: Search for Life in the Solar System, Capri, Italy 26 to 28 October, 2005.     

Characterization and designing of an SAM riboswitch to establish a high-throughput screening platform for SAM overproduction in Saccharomyces cerevisiae

S-adenosyl- l -methionine (SAM) is a high-value compound widely used in the treatment of various diseases. SAM can be produced through fermentation, but further enhancing the microbial production of SAM requires novel high-throughput screening methods for rapid detection and screening of mutant libraries. In this work, an SAM-OFF riboswitch capable of responding to the SAM concentration was obtained and a high-throughput platform for screening SAM overproducers was established. SAM synthase was engineered by semirational design and directed evolution, which resulted in the SAM2^{S203F,W164R,T251S,Y285F,S365R} mutant with almost twice higher catalytic activity than the parental enzyme. The best mutant was then introduced into Saccharomyces cerevisiae BY4741, and the resulting strain BSM8 produced a sevenfold higher SAM titer in shake-flask fermentation, reaching 1.25 g L⁻¹. This work provides a reference for designing biosensors to dynamically detect metabolite concentrations for high-throughput screening and the construction of effective microbial cell factories.     

Organelle size control systems: From cell geometry to organelle-directed medicine

Organelles are reaction vessels containing metabolic pathways. As in a chemical factory, the size of the reaction vessels limits the rate of product formation. Organelle size is tuned to metabolic needs, hence reprogramming organelle size could be a novel therapeutic strategy as well as a new tool for metabolic engineering.     

Protein Function Prediction: From Traditional Classifier to Deep Learning

Deep learning demonstrates greater competence over traditional machine learning techniques for many tasks. In last several years, deep learning has been applied to protein function prediction and a series of good achievements has been obtained. These findings extensively advanced our understanding of protein function. However, the accuracy of protein function prediction based upon deep learning still has yet to be improved. In article number 1900019, Issue 12, Zhang et al. construct DeepFunc, a deep learning framework using derived feature information of protein sequence and protein interactions network. They find that implementing DeepFunc for protein function prediction is more accurate than using DeepGO, a similar method reported previously. Meanwhile, they find that the method of combining multiple derived feature information in DeepFunc is much better than the method of using only single derived feature information. Due to its fully exploiting feature representation learning ability, deep learning with more derived feature information will enable it to be a promising method for solving more complicated protein function prediction problems and other bioinformatics challenges. Recent researches have provided some major insights into the value for using deep learning to protein function prediction problem.     

Plant cell packs: a scalable platform for recombinant protein production and metabolic engineering

Industrial plant biotechnology applications include the production of sustainable fuels, complex metabolites and recombinant proteins, but process development can be impaired by a lack of reliable and scalable screening methods. Here, we describe a rapid and versatile expression system which involves the infusion of Agrobacterium tumefaciens into three‐dimensional, porous plant cell aggregates deprived of cultivation medium, which we have termed plant cell packs (PCPs). This approach is compatible with different plant species such as Nicotiana tabacum BY2, Nicotiana benthamiana or Daucus carota and 10‐times more effective than transient expression in liquid plant cell culture. We found that the expression of several proteins was similar in PCPs and intact plants, for example, 47 and 55 mg/kg for antibody 2G12 expressed in BY2 PCPs and N. tabacum plants respectively. Additionally, the expression of specific enzymes can either increase the content of natural plant metabolites or be used to synthesize novel small molecules in the PCPs. The PCP method is currently scalable from a microtiter plate format suitable for high‐throughput screening to 150‐mL columns suitable for initial product preparation. It therefore combined the speed of transient expression in plants with the throughput of microbial screening systems. Plant cell packs therefore provide a convenient new platform for synthetic biology approaches, metabolic engineering and conventional recombinant protein expression techniques that require the multiplex analysis of several dozen up to hundreds of constructs for efficient product and process development.     

Human and viral membrane–associated E3 ubiquitin ligases MARCH1 and MIR2 recognize different features of CD86 to downregulate surface expression

Immune-stimulatory ligands, such as major histocompatibility complex molecules and the T-cell costimulatory ligand CD86, are central to productive immunity. Endogenous mammalian membrane-associated RING-CHs (MARCH) act on these and other targets to regulate antigen presentation and activation of adaptive immunity, whereas virus-encoded homologs target the same molecules to evade immune responses. Substrate specificity is encoded in or near the membrane-embedded domains of MARCHs and the proteins they regulate, but the exact sequences that distinguish substrates from nonsubstrates are poorly understood. Here, we examined the requirements for recognition of the costimulatory ligand CD86 by two different MARCH-family proteins, human MARCH1 and Kaposi''s sarcoma herpesvirus modulator of immune recognition 2 (MIR2), using deep mutational scanning. We identified a highly specific recognition surface in the hydrophobic core of the CD86 transmembrane (TM) domain (TMD) that is required for recognition by MARCH1 and prominently features a proline at position 254. In contrast, MIR2 requires no specific sequences in the CD86 TMD but relies primarily on an aspartic acid at position 244 in the CD86 extracellular juxtamembrane region. Surprisingly, MIR2 recognized CD86 with a TMD composed entirely of valine, whereas many different single amino acid substitutions in the context of the native TM sequence conferred MIR2 resistance. These results show that the human and viral proteins evolved completely different recognition modes for the same substrate. That some TM sequences are incompatible with MIR2 activity, even when no specific recognition motif is required, suggests a more complicated mechanism of immune modulation via CD86 than was previously appreciated.     

Deep Sequencing-guided Design of a High Affinity Dual Specificity Antibody to Target Two Angiogenic Factors in Neovascular Age-related Macular Degeneration

The development of dual targeting antibodies promises therapies with improved efficacy over mono-specific antibodies. Here, we engineered a Two-in-One VEGF/angiopoietin 2 antibody with dual action Fab (DAF) as a potential therapeutic for neovascular age-related macular degeneration. Crystal structures of the VEGF/angiopoietin 2 DAF in complex with its two antigens showed highly overlapping binding sites. To achieve sufficient affinity of the DAF to block both angiogenic factors, we turned to deep mutational scanning in the complementarity determining regions (CDRs). By mutating all three CDRs of each antibody chain simultaneously, we were able not only to identify affinity improving single mutations but also mutation pairs from different CDRs that synergistically improve both binding functions. Furthermore, insights into the cooperativity between mutations allowed us to identify fold-stabilizing mutations in the CDRs. The data obtained from deep mutational scanning reveal that the majority of the 52 CDR residues are utilized differently for the two antigen binding function and permit, for the first time, the engineering of several DAF variants with sub-nanomolar affinity against two structurally unrelated antigens. The improved variants show similar blocking activity of receptor binding as the high affinity mono-specific antibodies against these two proteins, demonstrating the feasibility of generating a dual specificity binding surface with comparable properties to individual high affinity mono-specific antibodies.     

Road to the future of systems biotechnology: CRISPR-Cas-mediated metabolic engineering for recombinant protein production

The rising potential for CRISPR–Cas-mediated genome editing has revolutionized our strategies in basic and practical bioengineering research. It provides a predictable and precise method for genome modification in a robust and reproducible fashion. Emergence of systems biotechnology and synthetic biology approaches coupled with CRISPR–Cas technology could change the future of cell factories to possess some new features which have not been found naturally. We have discussed the possibility and versatile potentials of CRISPR–Cas technology for metabolic engineering of a recombinant host for heterologous protein production. We describe the mechanisms involved in this metabolic engineering approach and present the diverse features of its application in biotechnology and protein production.     

Implications of aromatic–aromatic interactions: From protein structures to peptide models

With increasing structural information on proteins, the opportunity to understand physical forces governing protein folding is also expanding. One of the significant non‐covalent forces between the protein side chains is aromatic–aromatic interactions. Aromatic interactions have been widely exploited and thoroughly investigated in the context of folding, stability, molecular recognition, and self‐assembly processes. Through this review, we discuss the contribution of aromatic interactions to the activity and stability of thermophilic, mesophilic, and psychrophilic proteins. Being hydrophobic, aromatic amino acids tend to reside in the protein hydrophobic interior or transmembrane segments of proteins. In such positions, it can play a diverse role in soluble and membrane proteins, and in α‐helix and β‐sheet stabilization. We also highlight here some excellent investigations made using peptide models and several approaches involving aryl–aryl interactions, as an increasingly popular strategy in protein and peptide engineering. A recent survey described the existence of aromatic clusters (trimer, tetramer, pentamer, and higher order assemblies), revealing the self‐associating property of aryl groups, even in folded protein structures. The application of this self‐assembly of aromatics in the generation of modern bionanomaterials is also discussed.     

Quantitation of protein expression in a cell-free system: Efficient detection of yields and <Superscript>19</Superscript>F NMR to identify folded protein

We have developed an efficient and novel filter assay method, involving radioactive labelling and imaging, to quantify the expression of soluble proteins from a cell-free translation system. Here this method is combined with the conformational sensitivity of ¹⁹F NMR to monitor the folded state of the expressed protein. This report describes the optimisation of 6-fluorotryptophan incorporation in a His-tagged human serum retinol-binding protein (RBP), a disulphide bonded -barrel protein. Appropriate reagent concentrations for producing fluorine labelled RBP in a cell-free translation system are described. It is shown that ¹⁹F NMR is a suitable method for monitoring the production of correctly folded protein from a high-throughput expression system.     

Unraveling what makes a monoclonal antibody difficult-to-express: From intracellular accumulation to incomplete folding and degradation via ERAD

Although most therapeutic monoclonal antibodies (mAbs) can routinely be produced in the multigram per litre range, some mAb candidates turn out to be difficult-to-express (DTE). In addition, the class of more complex biological formats is permanently increasing and mammalian expression systems like Chinese hamster ovary (CHO) cell lines can show low performance. Hence, there is an urgent need to identify any rate limiting processing step during cellular synthesis. Therefore, we assessed the intracellular location of the DTE antibody mAb2 by fluorescence and electron microscopy (EM) and revealed an accumulation of the antibody, which led to an aberrant morphology of the endoplasmic reticulum (ER). Analysis of underlying cellular mechanisms revealed that neither aggregation nor antibody assembly, but folding represented the reason for hampered secretion. We identified that the disulfide bridge formation within the antibody light chain (LC) was impaired due to less recognition by protein disulfide isomerase (PDI). As a consequence, the DTE molecule was degraded intracellularly by the ubiquitin proteasome system via ER-associated degradation (ERAD). This study revealed that with the continuous emergence of DTE therapeutic protein candidates, special attention needs to be drawn to optimization processes to ensure manufacturability.     

Old and new glycopeptide antibiotics: From product to gene and back in the post-genomic era

Glycopeptide antibiotics are drugs of last resort for treating severe infections caused by multi-drug resistant Gram-positive pathogens. First-generation glycopeptides (vancomycin and teicoplanin) are produced by soil-dwelling actinomycetes. Second-generation glycopeptides (dalbavancin, oritavancin, and telavancin) are semi-synthetic derivatives of the progenitor natural products. Herein, we cover past and present biotechnological approaches for searching for and producing old and new glycopeptide antibiotics. We review the strategies adopted to increase microbial production (from classical strain improvement to rational genetic engineering), and the recent progress in genome mining, chemoenzymatic derivatization, and combinatorial biosynthesis for expanding glycopeptide chemical diversity and tackling the never-ceasing evolution of antibiotic resistance.     

Random circular permutation leading to chain disruption within and near alpha helices in the catalytic chains of aspartate transcarbamoylase: effects on assembly, stability, and function

A collection of circularly permuted catalytic chains of aspartate transcarbamoylase (ATCase) has been generated by random circular permutation of the pyrB gene. From the library of ATCases containing permuted polypeptide chains, we have chosen for further investigation nine ATCase variants whose catalytic chains have termini located within or close to an alpha helix. All of the variants fold and assemble into dodecameric holoenzymes with similar sedimentation coefficients and slightly reduced thermal stabilities. Those variants disrupted within three different helical regions in the wild-type structure show no detectable enzyme activity and no apparent binding of the bisubstrate analog N:-phosphonacetyl-L-aspartate. In contrast, two variants whose termini are just within or adjacent to other alpha helices are catalytically active and allosteric. As expected, helical disruptions are more destabilizing than loop disruptions. Nonetheless, some catalytic chains lacking continuity within helical regions can assemble into stable holoenzymes comprising six catalytic and six regulatory chains. For seven of the variants, continuity within the helices in the catalytic chains is important for enzyme activity but not necessary for proper folding, assembly, and stability of the holoenzyme.