Engineering Translation in Mammalian Cell Factories to Increase Protein Yield: The Unexpected Use of Long Non-Coding SINEUP RNAs

Molecular biomarkers identification and applications in CHO bioprocessing

Biomarkers are valuable tools in clinical research where they allow to predict susceptibility to diseases, or response to specific treatments. Likewise, biomarkers can be extremely useful in the biomanufacturing of therapeutic proteins. Indeed, constraints such as short timelines and the need to find hyper-productive cells could benefit from a data-driven approach during cell line and process development. Many companies still rely on large screening capacities to develop productive cell lines, but as they reach a limit of production, there is a need to go from empirical to rationale procedures. Similarly, during bioprocessing runs, substrate consumption and metabolism wastes are commonly monitored. None of them possess the ability to predict the culture behavior in the bioreactor. Big data driven approaches are being adapted to the study of industrial mammalian cell lines, enabled by the publication of Chinese hamster and CHO genome assemblies which allowed the use of next-generation sequencing with these cells, as well as continuous proteome and metabolome annotation. However, if these different -omics technologies contributed to the characterization of CHO cells, there is a significant effort remaining to apply this knowledge to biomanufacturing methods. The correlation of a complex phenotype such as high productivity or rapid growth to the presence or expression level of a specific biomarker could save time and effort in the screening of manufacturing cell lines or culture conditions. In this review we will first discuss the different biological molecules that can be identified and quantified in cells, their detection techniques, and associated challenges. We will then review how these markers are used during the different steps of cell line and bioprocess development, and the inherent limitations of this strategy.

In-locus gene silencing in plants using genome editing

Gene silencing is crucial in crop breeding for desired trait development. RNA interference (RNAi) has been used widely but is limited by ectopic expression of transgenes and genetic instability. Introducing an upstream start codon (uATG) into the 5'untranslated region (5'UTR) of a target gene may 'silence' the target gene by inhibiting protein translation from the primary start codon (pATG). Here, we report an efficient gene silencing method by introducing a tailor-designed uATG-containing element (ATGE) into the 5'UTR of genes in plants, occupying the original start site to act as a new pATG. Using base editing to introduce new uATGs failed to silence two of the tested three rice genes, indicating complex regulatory mechanisms. Precisely inserting an ATGE adjacent to pATG achieved significant target protein downregulation. Through extensive optimization, we demonstrated this strategy substantially and consistently downregulated target protein expression. By designing a bidirectional multifunctional ATGE4, we enabled tunable knockdown from 19% to 89% and observed expected phenotypes. Introducing ATGE into Waxy, which regulates starch synthesis, generated grains with lower amylose, revealing the value for crop breeding. Together, we have developed a programmable and robust method to knock down gene expression in plants, with potential for biological mechanism exploration and crop enhancement.

Enhancing the productivity and proliferation of CHO-K1 cells by oncoprotein YAP (Yes-associated protein)

CHO cells are extensively employed in biological drug industry to manufacture therapeutic proteins. Nevertheless, production of biopharmaceuticals faces obstacles such as limited growth and inadequate productivity. Employing host cell engineering techniques for CHO cells serves as a valuable approach to address the constraints encountered in biologics manufacturing. Despite advancements, most techniques focus on specific genes to address individual cellular challenges. The significance of YAP, transcriptional co-activator, cannot be overstated due to its involvement in regulating organ size and tumor formation. YAP's influence extends to various cellular processes and is regulated by kinase cascade in the Hippo pathway, which phosphorylates serine residues in specific LATS recognition motifs. Activation of YAP has been observed to impact both the size and quantity of cells. This research investigates the effects of YAP5SA on proliferation, apoptosis, and productivity in CHO-K1 cells. YAP5SA, with mutations in all five LATS-target sites, is selected for its heightened activity and resistance to repression through the Hippo-LATS1/2 kinase signaling pathway. Plasmid harboring YAP5SA was transfected into EPO-CHO and the influence of YAP5SA overexpression was investigated. According to our findings, transfection of EPO-CHO cells with YAP5SA exhibited a substantial enhancement in CHO cell productivity, resulting in a 3-fold increase in total protein and EPO, as well as a 1.5-fold increase in specific productivity. Additionally, it significantly contributes in augmenting viability, size, and proliferation. Overall, the findings of this study exemplify the potential of utilizing YAP5SA to impact particular cellular mechanisms, thereby presenting an avenue for customizing cells to fulfill production demands. KEY POINTS: • YAP5SA in CHO cells boosts growth, reduces apoptosis, and significantly improves productivity. • YAP5SA regulates genes involved in proliferation, survival, and mTOR activation. • YAP5SA increases productivity by improving cell cycle, c-MYC expression, and mTOR pathway.

Cell factory engineering: Challenges and opportunities for synthetic biology applications

The production of high-quality recombinant proteins is critical to maintaining a continuous supply of biopharmaceuticals, such as therapeutic antibodies. Engineering mammalian cell factories presents a number of limitations typically associated with the proteotoxic stress induced upon aberrant accumulation of off-pathway protein folding intermediates, which eventually culminate in the induction of apoptosis. In this review, we will discuss advances in cell engineering and their applications at different hierarchical levels of control of the expression of recombinant proteins, from transcription and translational to posttranslational modifications and subcellular trafficking. We also highlight challenges and unique opportunities to apply modern synthetic biology tools to the design of programmable cell factories for improved biomanufacturing of therapeutic proteins.

Employing active learning in the optimization of culture medium for mammalian cells

Medium optimization is a crucial step during cell culture for biopharmaceutics and regenerative medicine; however, this step remains challenging, as both media and cells are highly complex systems. Here, we addressed this issue by employing active learning. Specifically, we introduced machine learning to cell culture experiments to optimize culture medium. The cell line HeLa-S3 and the gradient-boosting decision tree algorithm were used to find optimized media as pilot studies. To acquire the training data, cell culture was performed in a large variety of medium combinations. The cellular NAD(P)H abundance, represented as A450, was used to indicate the goodness of culture media. In active learning, regular and time-saving modes were developed using culture data at 168 h and 96 h, respectively. Both modes successfully fine-tuned 29 components to generate a medium for improved cell culture. Intriguingly, the two modes provided different predictions for the concentrations of vitamins and amino acids, and a significant decrease was commonly predicted for fetal bovine serum (FBS) compared to the commercial medium. In addition, active learning-assisted medium optimization significantly increased the cellular concentration of NAD(P)H, an active chemical with a constant abundance in living cells. Our study demonstrated the efficiency and practicality of active learning for medium optimization and provided valuable information for employing machine learning technology in cell biology experiments.

Development of a stable antibody production system utilizing an Hspa5 promoter in CHO cells

Chinese hamster ovary (CHO) cells are widely used for manufacturing antibody drugs. We attempted to clone a novel high-expression promoter for producing monoclonal antibodies (mAbs) based on transcriptome analysis to enhance the transcriptional abundance of mAb genes. The efficacy of conventional promoters such as CMV and hEF1α decrease in the latter phase of fed-batch cell culture. To overcome this, we screened genes whose expression was maintained or increased throughout the culture period. Since CHO cells have diverse genetic expression depending on the selected clone and culture medium, transcriptome analysis was performed on multiple clones and culture media anticipated to be used in mAb manufacturing. We thus acquired the Hspa5 promoter as a novel high-expression promoter, which uniquely enables mAb productivity per cell to improve late in the culture period. Productivity also improved for various IgG subclasses under Hspa5 promoter control, indicating this promoter’s potential universal value for mAb production. Finally, it was suggested that mAb production with this promoter is correlated with the transcription levels of endoplasmic reticulum stress-related genes. Therefore, mAb production utilizing the Hspa5 promoter might be a new method for maintaining protein homeostasis and achieving stable expression of introduced mAb genes during fed-batch culture.

High-Throughput Monoclonal Antibody Discovery from Phage Libraries: Challenging the Current Preclinical Pipeline to Keep the Pace with the Increasing mAb Demand

Simple Summary

Monoclonal antibodies are increasingly used for a broad range of diseases. Rising demand must face with time time-consuming and laborious processes to isolate novel monoclonal antibodies. Next-generation sequencing coupled to phage display provides timely and sustainable high throughput selection strategy to rapidly access novel target. Here, we describe the current NGS-guided strategies to identify potential binders from enriched sub-libraires by applying a user-friendly informatic pipeline to identify and discard false positive clones. Rescue step and strategies to boost mAb yield are also discussed to improve the limiting selection and screening steps.

Abstract

Monoclonal antibodies are among the most powerful therapeutics in modern medicine. Since the approval of the first therapeutic antibody in 1986, monoclonal antibodies keep holding great expectations for application in a range of clinical indications, highlighting the need to provide timely and sustainable access to powerful screening options. However, their application in the past has been limited by time-consuming and expensive steps of discovery and production. The screening of antibody repertoires is a laborious step; however, the implementation of next-generation sequencing-guided screening of single-chain antibody fragments has now largely overcome this issue. This review provides a detailed overview of the current strategies for the identification of monoclonal antibodies from phage display-based libraries. We also discuss the challenges and the possible solutions to improve the limiting selection and screening steps, in order to keep pace with the increasing demand for monoclonal antibodies.

Design and Delivery of SINEUP: A New Modular Tool to Increase Protein Translation

SINEUP is a new class of long non-coding RNAs (lncRNAs) which contain an inverted Short Interspersed Nuclear Element (SINE) B2 element (invSINEB2) necessary to specifically upregulate target gene translation. Originally identified in the mouse AS-Uchl1 (antisense Ubiquitin carboxyl-terminal esterase L1) locus, natural SINEUP molecules are oriented head to head to their sense protein coding, target gene (Uchl1, in this example). Peculiarly, SINEUP is able to augment, in a specific and controlled way, the expression of the target protein, with no alteration of target mRNA levels. SINEUP is characterized by a modular structure with the Binding Domain (BD) providing specificity to the target transcript and an effector domain (ED)-containing the invSINEB2 element-able to promote the loading to the heavy polysomes of the target mRNA. Since the understanding of its modular structure in the endogenous AS-Uchl1 ncRNA, synthetic SINEUP molecules have been developed by creating a specific BD for the gene of interest and placing it upstream the invSINEB2 ED. Synthetic SINEUP is thus a novel molecular tool that potentially may be used for any industrial or biomedical application to enhance protein production, also as possible therapeutic strategy in haploinsufficiency-driven disorders.Here, we describe a detailed protocol to (1) design a specific BD directed to a gene of interest and (2) assemble and clone it with the ED to obtain a functional SINEUP molecule. Then, we provide guidelines to efficiently deliver SINEUP into mammalian cells and evaluate its ability to effectively upregulate target protein translation.

Over-Production of Therapeutic Growth Factors for Articular Cartilage Regeneration by Protein Production Platforms and Protein Packaging Cell Lines

Simple Summary

Osteoarthritis (OA) is the most common form of arthritis across the world. Most of the existing drugs for OA treat the symptoms of pain and inflammation. There are no drugs that can dure the disease. There are a number of new treatments for OA including cell therapy and gene therapy. This articles outlines the concept behind TissueGene-C, a new biological drug for OA. This new treatment includes cartilage cells mixed with a genetically modified cell line called GP2-293, which is effectively a “drug factory”, over-producing the growth factors that are important for cartilage regeneration and changing the environment inside joints. The mixture is injected into the affected knee joint. These cells are designed to be short-lived and cannot reproduce. Therefore, after they have done their job, they die and are cleared by immune cells. This is a new and modern approach to treating OA and TissueGene-C is the prototype cell therapy for OA. In the future, it is entirely possible to combine different clones of genetically engineered cells like GP2-293 that have been designed to over-produce a growth factor or biological drug with cells from the cartilage endplate of the intervertebral disc to treat degeneration in the spine.

Abstract

This review article focuses on the current state-of-the-art cellular and molecular biotechnology for the over-production of clinically relevant therapeutic and anabolic growth factors. We discuss how the currently available tools and emerging technologies can be used for the regenerative treatment of osteoarthritis (OA). Transfected protein packaging cell lines such as GP-293 cells may be used as “cellular factories” for large-scale production of therapeutic proteins and pro-anabolic growth factors, particularly in the context of cartilage regeneration. However, when irradiated with gamma or x-rays, these cells lose their capacity for replication, which makes them safe for use as a live cell component of intra-articular injections. This innovation is already here, in the form of TissueGene-C, a new biological drug that consists of normal allogeneic primary chondrocytes combined with transduced GP2-293 cells that overexpress the growth factor transforming growth factor β1 (TGF-β1). TissueGene-C has revolutionized the concept of cell therapy, allowing drug companies to develop live cells as biological drug delivery systems for direct intra-articular injection of growth factors whose half-lives are in the order of minutes. Therefore, in this paper, we discuss the potential for new innovations in regenerative medicine for degenerative diseases of synovial joints using mammalian protein production platforms, specifically protein packaging cell lines, for over-producing growth factors for cartilage tissue regeneration and give recent examples. Mammalian protein production platforms that incorporate protein packaging eukaryotic cell lines are superior to prokaryotic bacterial expression systems and are likely to have a significant impact on the development of new humanized biological growth factor therapies for treating focal cartilage defects and more generally for the treatment of degenerative joint diseases such as OA, especially when injected directly into the joint.

Improving the expression of anti-IL-2Rα monoclonal antibody in the CHO cells through optimization of the expression vector and translation efficiency

The growing need for monoclonal antibodies (mAbs) necessitates the development of novel and efficient production approaches. Regulatory elements like ubiquitous chromatin-opening elements (UCOEs) have been employed for improvement of the mAb expression in the Chinese hamster ovary (CHO) cells. SINEUPs are a class of long non-coding RNAs, which can improve the translation of partly overlapping mRNAs. A combination of these two elements might lead to higher production of mAbs. Therefore, the current study was conducted to investigate the effects of SINEUPs and A2UCOE on the expression of an IgG1 in the CHO-K1 cells. Hence, after constructing the mAb, mAb-SINEUP, and mAb-UCOE vectors, four stable cell pools were generated through combining the above vectors. According to the expression analysis, antibody yields were higher in the mAb-SINEUP and mAb-UCOE cell pools compared to the mAb cells. In addition, the cells possessing both SINEUP and UCOE elements provided the best expression. Persistent mAb expression was observed for over 2 months in these cells, whilst the expression was decreased in the mAb pool. SINEUP and UCOE positively influenced the stable mAb expression. It can be concluded that the SINEUP and UCOE enhance the antibody stability and expression level separately and their combination improves the mAb production in the CHO cells.

Key Challenges in Designing CHO Chassis Platforms

Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines.

Expression and purification of recombinant G protein-coupled receptors: A review

Given their extensive role in cell signalling, GPCRs are significant drug targets; despite this, many of these receptors have limited or no available prophylaxis. Novel drug design and discovery significantly rely on structure determination, of which GPCRs are typically elusive. Progress has been made thus far to produce sufficient quantity and quality of protein for downstream analysis. As such, this review highlights the systems available for recombinant GPCR expression, with consideration of their advantages and disadvantages, as well as examples of receptors successfully expressed in these systems. Additionally, an overview is given on the use of detergents and the styrene maleic acid (SMA) co-polymer for membrane solubilisation, as well as purification techniques.

Locate-R: Subcellular localization of long non-coding RNAs using nucleotide compositions

Knowledge of the sub-cellular localization of the most diverse class of transcribed RNA, long non-coding RNAs (lncRNAs) will lead us to identify different types of cancers and other diseases as lncRNAs play key role in related cellular functions. In recent days with the exponential growth of known records, it becomes essential to establish new machine learning based techniques to identify the new one due to faster and cheaper solutions provided compared to laboratory methods. In this paper, we propose Locate-R, a novel method for predicting the sub-cellular location of lncRNAs. We have used only n-gapped l-mer composition and l-mer composition as features and select best 655 features to build the model. This model is based locally deep support vector machines which significantly enhance the prediction accuracy with respect to exiting state-of-the-art methods. Our predictor is readily available for use as a stand-alone web application from: http://locate-r.azurewebsites.net/.

Defining lncRNAs Correlated with CHO Cell Growth and IgG Productivity by RNA-Seq

How the long non-coding RNA (lncRNA) genome in recombinant protein producing Chinese hamster ovary (CHO) cell lines relates to phenotype is not well described. We therefore defined the CHO cell lncRNA transcriptome from cells grown in controlled miniature bioreactors under fed-batch conditions using RNA-Seq to identify lncRNAs and how the expression of these changes throughout growth and between IgG producers. We identify lncRNAs including Adapt15, linked to ER stress, GAS5, linked to mTOR signaling/growth arrest, and PVT1, linked to Myc expression, which are differentially regulated during fed-batch culture and whose expression correlates to productivity and growth. Changes in (non)-coding RNA expression between the seed train and the equivalent day of fed-batch culture are also reported and compared with existing datasets. Collectively, we present a comprehensive lncRNA CHO cell profiling and identify targets for engineering growth and productivity characteristics of CHO cells.

•

The CHO cell lncRNA transcriptome is defined using RNA-Seq

•

Correlations between lncRNA expression and CHO cell growth and IgG productivity found

•

Expression of lncRNAs involved in ER stress correlates to productivity

•

Expression of lncRNAs involved in mTOR signaling/growth arrest correlates to growth

iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC

Motivation

Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200 nucleotides. They have important functions in cell development and metabolism, such as genetic markers, genome rearrangements, chromatin modifications, cell cycle regulation, transcription and translation. Their functions are generally closely related to their localization in the cell. Therefore, knowledge about their subcellular locations can provide very useful clues or preliminary insight into their biological functions. Although biochemical experiments could determine the localization of lncRNAs in a cell, they are both time-consuming and expensive. Therefore, it is highly desirable to develop bioinformatics tools for fast and effective identification of their subcellular locations.

Results

We developed a sequence-based bioinformatics tool called 'iLoc-lncRNA' to predict the subcellular locations of LncRNAs by incorporating the 8-tuple nucleotide features into the general PseKNC (Pseudo K-tuple Nucleotide Composition) via the binomial distribution approach. Rigorous jackknife tests have shown that the overall accuracy achieved by the new predictor on a stringent benchmark dataset is 86.72%, which is over 20% higher than that by the existing state-of-the-art predictor evaluated on the same tests.

Availability and implementation

A user-friendly webserver has been established at http://lin-group.cn/server/iLoc-LncRNA, by which users can easily obtain their desired results.

Supplementary information

Supplementary data are available at Bioinformatics online.

Future Cell and Gene Therapy for Osteoarthritis (OA): Potential for Using Mammalian Protein Production Platforms, Irradiated and Transfected Protein Packaging Cell Lines for Over-Production of Therapeutic Proteins and Growth Factors

In this paper I provide a personal perspective on future prospects for cell and gene therapy for osteoarthritis (OA) and how mammalian protein production platforms, virally transfected and irradiated protein packaging cell lines may be used as "cellular factories" for over-production of therapeutic proteins and growth factors, particularly in the context of intra-articular regenerative therapies. I will also speculate on future opportunities and challenges in this area of research and how new innovations in biotechnology will impact on the field of cell and gene therapy for OA, related osteoarticular disorders and the broader discipline of regenerative medicine for musculoskeletal disorders. Mammalian protein production platforms are likely to have a significant impact on synovial joint diseases that are amenable to cell and gene therapy using therapeutic proteins and growth factors. Future cell and gene therapy for OA will need to re-consider the current strategies that employ primary, aged and senescent cells with feeble regenerative properties and seriously consider the use of mammalian protein production platforms.

Exaptation at the molecular genetic level

The realization that body parts of animals and plants can be recruited or coopted for novel functions dates back to, or even predates the observations of Darwin. S.J. Gould and E.S. Vrba recognized a mode of evolution of characters that differs from adaptation. The umbrella term aptation was supplemented with the concept of exaptation. Unlike adaptations, which are restricted to features built by selection for their current role, exaptations are features that currently enhance fitness, even though their present role was not a result of natural selection. Exaptations can also arise from nonaptations; these are characters which had previously been evolving neutrally. All nonaptations are potential exaptations. The concept of exaptation was expanded to the molecular genetic level which aided greatly in understanding the enormous potential of neutrally evolving repetitive DNA-including transposed elements, formerly considered junk DNA-for the evolution of genes and genomes. The distinction between adaptations and exaptations is outlined in this review and examples are given. Also elaborated on is the fact that such distinctions are sometimes more difficult to determine; this is a widespread phenomenon in biology, where continua abound and clear borders between states and definitions are rare.

Genome editing of upstream open reading frames enables translational control in plants

Translational regulation by upstream open reading frames (uORFs) is becoming established as a general mechanism for controlling the amount of protein that is synthesized from downstream primary ORFs (pORFs). We found that genome editing of endogenous uORFs in plants enabled the modulation of translation of mRNAs from four pORFs that are involved in either development or antioxidant biosynthesis. A single-guide RNA that targeted the region harboring a uORF initiation codon can produce multiple mutations. Following uORF editing, we observed varying amounts of mRNA translation in four pORFs. Notably, editing the uORF of LsGGP2, which encodes a key enzyme in vitamin C biosynthesis in lettuce, not only increased oxidation stress tolerance, but also increased ascorbate content by ∼150%. These data indicate that editing plant uORFs provides a generalizable, efficient method for manipulating translation of mRNA that could be applied to dissect biological mechanisms and improve crops.

Identification and comparison of long non-coding RNAs in the silk gland between domestic and wild silkworms

Under long-term artificial selection, the domestic silkworm (Bombyx mori) has increased its silk yield tremendously in comparison with its wild progenitor, Bombyx mandarina. However, the molecular mechanism of silk yield increase is still unknown. Comparative analysis of long non-coding RNAs (lncRNAs) may provide some insights into understanding this phenotypic variation. In this study, using RNA sequencing technology data of silk gland in domestic and wild silkworms, we identified 599 lncRNAs in the silk gland of the silkworm. Compared with protein-coding genes, the silk gland lncRNA genes tend to have fewer exon numbers, shorter transcript length and lower GC-content. Moreover, we found that three lncRNA genes are significantly and differentially expressed between domestic and wild silkworms. The potential targets of two differentially expressed lncRNAs (DELs) (dw4sg_0040 and dw4sg_0483) and the expression-correlated genes with the two DELs are mainly enriched in the related processes of silk protein translation. This implies that these DELs may affect the phenotypic variation in silk yield between the domestic and wild silkworms through the post-transcriptional regulation of silk protein.

The Long Non-Coding RNA Transcriptome Landscape in CHO Cells Under Batch and Fed-Batch Conditions

The role of non-coding RNAs in determining growth, productivity, and recombinant product quality attributes in Chinese hamster ovary (CHO) cells has received much attention in recent years, exemplified by studies into microRNAs in particular. However, other classes of non-coding RNAs have received less attention. One such class are the non-coding RNAs known collectively as long non-coding RNAs (lncRNAs). The authors have undertaken the first landscape analysis of the lncRNA transcriptome in CHO using a mouse based microarray that also provided for the surveillance of the coding transcriptome. The authors report on those lncRNAs present in a model host CHO cell line under batch and fed-batch conditions on two different days and relate the expression of different lncRNAs to each other. The authors demonstrate that the mouse microarray is suitable for the detection and analysis of thousands of CHO lncRNAs and validated a number of these by qRT-PCR. The authors then further analyzed the data to identify those lncRNAs whose expression changed the most between growth and stationary phases of culture or between batch and fed-batch culture to identify potential lncRNA targets for further functional studies with regard to their role in controlling growth of CHO cells. The authors discuss the implications for the publication of this rich dataset and how this may be used by the community.

Stable miRNA overexpression in human CAP cells: Engineering alternative production systems for advanced manufacturing of biologics using miR-136 and miR-3074

Chinese hamster ovary (CHO) cells still represent the major production host for therapeutic proteins. However, multiple limitations have been acknowledged leading to the search for alternative expression systems. CEVEC's amniocyte production (CAP) cells are human production cells demonstrated to enable efficient overexpression of recombinant proteins with human glycosylation pattern. However, CAP cells have not yet undergone any engineering approaches to optimize process parameters for a cheaper and more sustainable production of biopharmaceuticals. Thus, we assessed the possibility to enhance CAP cell production capacity via cell engineering using miRNA technology. Based on a previous high-content miRNA screen in CHO-SEAP cells, selected pro-productive miRNAs including, miR-99b-3p, 30a-5p, 329-3p, 483-3p, 370-3p, 219-1-3p, 3074-5p, 136-3p, 30e-5p, 1a-3p, and 484-5p, were shown to act pro-productive and product independent upon transient transfection in CAP and CHO antibody expressing cell lines. Stable expression of miRNAs established seven CAP cell pools with an overexpression of the pro-productive miRNA strand. Subsequent small-scale screening as well as upscaling batch experiments identified miR-136 and miR-3074 to significantly increase final mAb concentration in CAP-mAb cells. Transcriptomic changes analyzed by microarrays identified several lncRNAs as well as growth and apoptosis-related miRNAs to be differentially regulated in CAP-mAb-miR-136 and -miR-3074. This study presents the first engineering approach to optimize the alternative human expression system of CAP-cells.

Methods for Using Small Non-Coding RNAs to Improve Recombinant Protein Expression in Mammalian Cells

The ability to produce recombinant proteins by utilizing different “cell factories” revolutionized the biotherapeutic and pharmaceutical industry. Chinese hamster ovary (CHO) cells are the dominant industrial producer, especially for antibodies. Human embryonic kidney cells (HEK), while not being as widely used as CHO cells, are used where CHO cells are unable to meet the needs for expression, such as growth factors. Therefore, improving recombinant protein expression from mammalian cells is a priority, and continuing effort is being devoted to this topic. Non-coding RNAs are RNA segments that are not translated into a protein and often have a regulatory role. Since their discovery, major progress has been made towards understanding their functions. Non-coding RNA has been investigated extensively in relation to disease, especially cancer, and recently they have also been used as a method for engineering cells to improve their protein expression capability. In this review, we provide information about methods used to identify non-coding RNAs with the potential of improving recombinant protein expression in mammalian cell lines.

LncATLAS database for subcellular localization of long noncoding RNAs

The subcellular localization of long noncoding RNAs (lncRNAs) holds valuable clues to their molecular function. However, measuring localization of newly discovered lncRNAs involves time-consuming and costly experimental methods. We have created "lncATLAS," a comprehensive resource of lncRNA localization in human cells based on RNA-sequencing data sets. Altogether, 6768 GENCODE-annotated lncRNAs are represented across various compartments of 15 cell lines. We introduce relative concentration index (RCI) as a useful measure of localization derived from ensemble RNA-seq measurements. LncATLAS is accessible through an intuitive and informative webserver, from which lncRNAs of interest are accessed using identifiers or names. Localization is presented across cell types and organelles, and may be compared to the distribution of all other genes. Publication-quality figures and raw data tables are automatically generated with each query, and the entire data set is also available to download. LncATLAS makes lncRNA subcellular localization data available to the widest possible number of researchers. It is available at lncatlas.crg.eu.