Alternative hosts as the missing link for equitable therapeutic protein production

An important consideration when expressing mAbs in Escherichiacoli

Monoclonal antibodies (mAbs) are a driving force in the biopharmaceutical industry. Therapeutic mAbs are usually produced in mammalian cells, but there has been a push towards the use of alternative production hosts, such as Escherichia coli. When the genes encoding for a mAb heavy and light chains are codon-optimized for E. coli expression, a truncated form of the heavy chain can form along with the full-length product. In this work, the role of codon optimization in the formation of a truncated product was investigated. This study used the amino acid sequences of several therapeutic mAbs and multiple optimization algorithms. It was found that several algorithms incorporate sequences that lead to a truncated product. Approaches to avoid this truncated form are discussed.

CRISPR-Cas9 knockout screen informs efficient reduction of the Komagataella phaffii secretome

BACKGROUND

The yeast Komagataella phaffii is widely used for manufacturing recombinant proteins, but secreted titers of recombinant proteins could be improved by genetic engineering. In this study, we hypothesized that cellular resources could be redirected from production of endogenous proteins to production of recombinant proteins by deleting unneeded endogenous proteins. In non-model microorganisms such as K. phaffii, however, genetic engineering is limited by lack gene annotation and knowledge of gene essentiality.

RESULTS

We identified a set of endogenous secreted proteins in K. phaffii by mass spectrometry and signal peptide prediction. Our efforts to disrupt these genes were hindered by limited annotation of essential genes. To predict essential genes, therefore, we designed, transformed, and sequenced a pooled library of guide RNAs for CRISPR-Cas9-mediated knockout of all endogenous secreted proteins. We then used predicted gene essentiality to guide iterative disruptions of up to 11 non-essential genes. Engineered strains exhibited a ~20× increase in the production of human serum albumin and a twofold increase in the production of a monoclonal antibody.

CONCLUSIONS

We demonstrated that disruption of as few as six genes can increase production of recombinant proteins. Further reduction of the endogenous proteome of K. phaffii may further improve strain performance. The pooled library of secretome-targeted guides for CRISPR-Cas9 and knowledge of gene essentiality reported here will facilitate future efforts to engineer K. phaffii for production of other recombinant proteins and enzymes.

Fine-tuning the N-glycosylation of recombinant human erythropoietin using Chlamydomonas reinhardtii mutants

Microalgae are considered as attractive expression systems for the production of biologics. As photosynthetic unicellular organisms, they do not require costly and complex media for growing and are able to secrete proteins and perform protein glycosylation. Some biologics have been successfully produced in the green microalgae Chlamydomonas reinhardtii. However, post-translational modifications like glycosylation of these Chlamydomonas-made biologics have poorly been investigated so far. Therefore, in this study, we report on the first structural investigation of glycans linked to human erythropoietin (hEPO) expressed in a wild-type C. reinhardtii strain and mutants impaired in key Golgi glycosyltransferases. The glycoproteomic analysis of recombinant hEPO (rhEPO) expressed in the wild-type strain demonstrated that the three N-glycosylation sites are 100% glycosylated with mature N-glycans containing four to five mannose residues and carrying core xylose, core fucose and O-methyl groups. Moreover, expression in C. reinhardtii insertional mutants defective in xylosyltransferases A and B and fucosyltransferase resulted in drastic decreases of core xylosylation and core fucosylation of glycans N-linked to the rhEPOs, thus demonstrating that this strategy offers perspectives for humanizing the N-glycosylation of the Chlamydomonas-made biologics.

Challenges and opportunities in bringing nonbiological atoms to life with synthetic metabolism

The relatively narrow spectrum of chemical elements within the microbial 'biochemical palate' limits the reach of biotechnology, because several added-value compounds can only be produced with traditional organic chemistry. Synthetic biology offers enabling tools to tackle this issue by facilitating 'biologization' of non-canonical chemical atoms. The interplay between xenobiology and synthetic metabolism multiplies routes for incorporating nonbiological atoms into engineered microbes. In this review, we survey natural assimilation routes for elements beyond the essential biology atoms [i.e., carbon (C), hydrogen (H), nitrogen (N), oxygen (O), phosphorus (P), and sulfur (S)], discussing how these mechanisms could be repurposed for biotechnology. Furthermore, we propose a computational framework to identify chemical elements amenable to biologization, ranking reactions suitable to build synthetic metabolism. When combined and deployed in robust microbial hosts, these approaches will offer sustainable alternatives for smart chemical production.

Engineering Self-Assembling Protein Nanoparticles for Therapeutic Delivery

Despite remarkable advances over the past several decades, many therapeutic nanomaterials fail to overcome major in vivo delivery barriers. Controlling immunogenicity, optimizing biodistribution, and engineering environmental responsiveness are key outstanding delivery problems for most nanotherapeutics. However, notable exceptions exist including some lipid and polymeric nanoparticles, some virus-based nanoparticles, and nanoparticle vaccines where immunogenicity is desired. Self-assembling protein nanoparticles offer a powerful blend of modularity and precise designability to the field, and have the potential to solve many of the major barriers to delivery. In this review, we provide a brief overview of key designable features of protein nanoparticles and their implications for therapeutic delivery applications. We anticipate that protein nanoparticles will rapidly grow in their prevalence and impact as clinically relevant delivery platforms.

Novel Regioselective Approach to Cyclize Phage-Displayed Peptides in Combination with Epitope-Directed Selection to Identify a Potent Neutralizing Macrocyclic Peptide for SARS-CoV-2

Using the regioselective cyanobenzothiazole condensation reaction with an N-terminal cysteine and the chloroacetamide reaction with an internal cysteine, a phage-displayed macrocyclic 12-mer peptide library was constructed and subsequently validated. Using this library in combination with iterative selections against two epitopes from the receptor binding domain (RBD) of the novel severe acute respiratory syndrome virus 2 (SARS-CoV-2) Spike protein, macrocyclic peptides that strongly inhibit the interaction between the Spike RBD and angiotensin-converting enzyme 2 (ACE2), the human host receptor of SARS-CoV-2, were identified. The two epitopes were used instead of the Spike RBD to avoid selection of nonproductive macrocyclic peptides that bind RBD but do not directly inhibit its interactions with ACE2. Antiviral tests against SARS-CoV-2 showed that one macrocyclic peptide is highly potent against viral reproduction in Vero E6 cells with an EC50 value of 3.1 μM. The AlphaLISA-detected IC50 value for this macrocyclic peptide was 0.3 μM. The current study demonstrates that two kinetically controlled reactions toward N-terminal and internal cysteines, respectively, are highly effective in the construction of phage-displayed macrocyclic peptides, and the selection based on the SARS-CoV-2 Spike epitopes is a promising methodology in the identification of peptidyl antivirals.

Mucosal nanobody IgA as inhalable and affordable prophylactic and therapeutic treatment against SARS-CoV-2 and emerging variants

Anti-COVID antibody therapeutics have been developed but not widely used due to their high cost and escape of neutralization from the emerging variants. Here, we describe the development of VHH-IgA1.1, a nanobody IgA fusion molecule as an inhalable, affordable and less invasive prophylactic and therapeutic treatment against SARS-CoV-2 Omicron variants. VHH-IgA1.1 recognizes a conserved epitope of SARS-CoV-2 spike protein Receptor Binding Domain (RBD) and potently neutralizes major global SARS-CoV-2 variants of concern (VOC) including the Omicron variant and its sub lineages BA.1.1, BA.2 and BA.2.12.1. VHH-IgA1.1 is also much more potent against Omicron variants as compared to an IgG Fc fusion construct, demonstrating the importance of IgA mediated mucosal protection for Omicron infection. Intranasal administration of VHH-IgA1.1 prior to or after challenge conferred significant protection from severe respiratory disease in K18-ACE2 transgenic mice infected with SARS-CoV-2 VOC. More importantly, for cost-effective production, VHH-IgA1.1 produced in Pichia pastoris had comparable potency to mammalian produced antibodies. Our study demonstrates that intranasal administration of affordably produced VHH-IgA fusion protein provides effective mucosal immunity against infection of SARS-CoV-2 including emerging variants.

Controlling gene expression with deep generative design of regulatory DNA

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Using mutagenesis typically requires screening sizable random DNA libraries, which limits the designs to span merely a short section of the promoter and restricts their control of gene expression. Here, we prototype a deep learning strategy based on generative adversarial networks (GAN) by learning directly from genomic and transcriptomic data. Our ExpressionGAN can traverse the entire regulatory sequence-expression landscape in a gene-specific manner, generating regulatory DNA with prespecified target mRNA levels spanning the whole gene regulatory structure including coding and adjacent non-coding regions. Despite high sequence divergence from natural DNA, in vivo measurements show that 57% of the highly-expressed synthetic sequences surpass the expression levels of highly-expressed natural controls. This demonstrates the applicability and relevance of deep generative design to expand our knowledge and control of gene expression regulation in any desired organism, condition or tissue.

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Here the authors present EspressionGAN, a generative adversarial network that uses genomic and transcriptomic data to generate regulatory sequences.