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Expression of recombinant proteins in mammalian cell factories relies on synthetic assemblies of genetic parts to optimally control flux through the product biosynthetic pathway. In comparison to other genetic part-types, there is a relative paucity of characterized signal peptide components, particularly for mammalian cell contexts. In this study, we describe a toolkit of signal peptide elements, created using bioinformatics-led and synthetic design approaches, that can be utilised to enhance production of biopharmaceutical proteins in Chinese Hamster Ovary cell factories. We demonstrate, for the first time in a mammalian cell context, that machine learning can be used to predict how discrete signal peptide elements will perform when utilised to drive ER translocation of specific single chain protein products. For more complex molecular formats, such as multichain monoclonal antibodies, we describe how a combination of in silico and targeted design rule-based in vitro testing can be employed to rapidly identify product-specific signal peptide solutions from minimal screening spaces. The utility of this technology is validated by deriving vector designs that increase product titres ≥ 1.8x, compared to standard industry systems, for a range of products, including a difficult-to-express monoclonal antibody. The availability of a vastly expanded toolbox of characterised signal peptide parts, combined with streamlined in silico/in vitro testing processes, will permit efficient expression vector re-design to maximise titres of both simple and complex protein products.

Next-generation DNA vectors for cancer immunotherapies and vaccine development require promoters eliciting predefined transcriptional activities specific to target cell types, such as dendritic cells (DCs), which underpin immune response. In this study, we describe the

BackgroundWe aimed to measure SARS-CoV-2 seroprevalence in a cohort of healthcare workers (HCWs) during the first UK wave of the COVID-19 pandemic, explore risk factors associated with infection, and investigate the impact of antibody titres on assay sensitivity.MethodsHCWs at Sheffield Teaching Hospitals NHS Foundation Trust (STH) were prospectively enrolled and sampled at two time points. SARS-CoV-2 antibodies were tested using an in-house assay for IgG and IgA reactivity against Spike and Nucleoprotein (sensitivity 99·47%, specificity 99·56%). Data were analysed using three statistical models: a seroprevalence model, an antibody kinetics model, and a heterogeneous sensitivity model.FindingsAs of 12th June 2020, 24·4% (n=311/1275) HCWs were seropositive. Of these, 39·2% (n=122/311) were asymptomatic. The highest adjusted seroprevalence was measured in HCWs on the Acute Medical Unit (41·1%, 95% CrI 30·0–52·9) and in Physiotherapists and Occupational Therapists (39·2%, 95% CrI 24·4–56·5). Older age groups showed overall higher median antibody titres. Further modelling suggests that, for a serological assay with an overall sensitivity of 80%, antibody titres may be markedly affected by differences in age, with sensitivity estimates of 89% in those over 60 years but 61% in those ≤30 years.InterpretationHCWs in acute medical units working closely with COVID-19 patients were at highest risk of infection, though whether these are infections acquired from patients or other staff is unknown. Current serological assays may underestimate seroprevalence in younger age groups if validated using sera from older and/or more symptomatic individuals.Research in contextEvidence before this studyWe searched PubMed for studies published up to March 6th 2021, using the terms “COVID”, “SARS-CoV-2”, “seroprevalence”, and “healthcare workers”, and in addition for articles of antibody titres in different age groups against coronaviruses using “coronavirus”, “SARS-CoV-2, “antibody”, “antibody tires”, “COVID” and “age”. We included studies that used serology to estimate prevalence in healthcare workers. SARS-CoV-2 seroprevalence has been shown to be greater in healthcare workers working on acute medical units or within domestic services. Antibody levels against seasonal coronaviruses, SARS-CoV and SARS-CoV-2 were found to be higher in older adults, and patients who were hospitalised.Added value of this studyIn this healthcare worker seroprevalence modelling study at a large NHS foundation trust, we confirm that those working on acute medical units, COVID-19 “Red Zones” and within domestic services are most likely to be seropositive. Furthermore, we show that physiotherapists and occupational therapists have an increased risk of COVID-19 infection. We also confirm that antibody titres are greater in older individuals, even in the context of non-hospitalised cases. Importantly, we demonstrate that this can result in age-specific sensitivity in serological assays, where lower antibody titres in younger individuals results in lower assay sensitivity.Implications of all the available evidenceThere are distinct occupational roles and locations in hospitals where the risk of COVID-19 infection to healthcare workers is greatest, and this knowledge should be used to prioritise infection prevention control and other measures to protect healthcare workers. Serological assays may have different sensitivity profiles across different age groups, especially if assay validation was undertaken using samples from older and/or hospitalised patients, who tend to have higher antibody titres. Future seroprevalence studies should consider adjusting for age-specific assay sensitivities to estimate true seroprevalence rates.Author Contributions

Expression of recombinant genes in HEK293 cells is frequently utilized for production of recombinant proteins and viral vectors. These systems frequently employ the cytomegalovirus (CMV) promoter to drive recombinant gene transcription. However, the mechanistic basis of CMV-mediated transcriptional activation in HEK293 cells is unknown and consequently there are no strategies to engineer CMV for controlled expression of recombinant genes. Extensive bioinformatic analyses of transcription factor regulatory elements (TFREs) within the human CMV sequence and transcription factor mRNAs within the HEK293 transcriptome revealed 80 possible regulatory interactions. Through in vitro functional testing using reporter constructs harboring discrete TFREs or CMV deletion variants we identified key TFRE components and clusters of TFREs (cis-regulatory modules) within the CMV sequence. Our data reveal that CMV activity in HEK293 cells is a function of the promoters various constituent TFREs including AhR:ARNT, CREB, E4F, Sp1, ZBED1, JunB, c-Rel, and NF-κB. We also identified critical Sp1-dependent upstream activator elements near the transcriptional start site that were required for efficient transcription and YY1 and RBP-Jκ binding sites that mediate transrepression. Our study shows for the first time that novel, compact CMV-derived promoters can be engineered that exhibit up to 50% higher transcriptional efficiency (activity per unit DNA sequence) or 14% increase in total activity compared to the wild-type counterpart.

Monoclonal antibodies (mAbs) are extremely complex due to the presence of structural modifications resulting from enzymatic and chemical reactions such as glycosylation, glycation, deamidation, isomerisation, oxidation, aggregation and fragmentation. Size and charge variants analysis are carried out from the early stages of drug development throughout product lifetime to investigate product degradation pathways and optimise process conditions. However, conventional analytical workstreams for size and charge variant characterization are both time and sample demanding, requiring the application of multiple analytical methods. This study presents the development of a novel 2D-LC/MS approach combining both aggregate and charge variant profiling of a mAb candidate in a single method. Aggregate quantification was performed in the first dimension (