Stable, high-expressing cell lines are a critical component in commercial manufacturing of therapeutic proteins and vaccines. But the time and cost of developing these lines is exacerbated by the increasing need to express complex, multisubunit proteins requiring fine control of gene expression ratios. Traditional plasmid-based random integration and viral transduction techniques have limitations that include low rate of delivery, constrained cargo size, poor stability, heterogenous populations, and poor productivity due to gene rearrangements and silencing, all of which hamper the development of efficient production workflows.

Transposon-based vectors have emerged as suitable DNA transfer tools for gene discovery and recombinant gene delivery applications, including stable cell line development, which address some of the shortcomings of traditional plasmid-based transfection systems. Atum’s Leap-In™ transposases and transposons constitute a gene delivery system that delivers uniform and high-frequency integration resulting in high productivity levels—already at the stable pool level—leading to reduced cell line development times and predictable outcomes.

Stable integration system

The Atum system includes a transposase mRNA and a vector containing the gene(s) of interest, selection markers, regulatory elements, etc., flanked by the transposon cognate inverted terminal repeats (ITRs) and the transposition recognition motif (TTAT). Upon co-transfection of vector DNA and transposase mRNA, the transiently expressed enzyme catalyzes high-efficiency and precise integration of the transposon cassette (all sequences between the ITRs) at 1 – 60 sites across the genome of the host cell.1

The number of integrated transgenes can be controlled by adjusting the amount of transposon transfected and the selection stringency. Targeted locus amplification (TLA) analysis of the sites of transgene integration indicates that the vast majority of Leap-In-mediated integrations are single-copy events and maintain the structural integrity of the expression construct.

Analyses of integration sites in stable clones have indicated that >97% of integrations are single-copy events, and depending on selection stringency, 80–90% of the integrations target transcriptionally active, gene-rich genomic segments. This is in sharp contrast to random integration technologies where the integrations can occur at any location in the genome. Random integrations also typically result in a high frequency of concatemers, truncations, and other unstable or nonproductive genetic insertions.

Shortens process development timelines

Atum Bioprocess Tutorial Fig 1
Figure 1. Abundance of high-expressing cells in Leap-In stable pools. Chart shows a characteristic clonal productivity distribution in a Leap-In-mediated stable pool. The productivity range was divided into four equal quartiles, and the fraction of clones in each quartile was calculated.

As a direct consequence of preferential integration in transcriptionally active chromatin regions, the majority of clones in a Leap-In stable pool are high producers. A characteristic clonal distribution in a stable pool, as shown in Figure 1, indicates that ~60% of the cells are within the highest production quartile, and only 4% of the cells are in the lowest quartile. The strong bias in the pool for high-producing clones results in stable pools that have productivities exceeding clonal yields achieved by most random integration technologies. Examples of typical productivity levels reached by Leap-In-mediated stable pools expressing IgG at 14 days post-transfection, in non-optimized small-scale shake flask or deep-well cultures, are shown in the Table.

Autum Bioprocessing tutorial table

Protein productivity and the quality attributes of the clones are consistent with those of the pools they are derived from. Figure 2 shows an example of a stable pool and three of its derivative clones, which all exhibit highly comparable charge distribution and glycan profiles. Thus, process and analytical development can be initiated already at the pool stage, shortening the CMC development timeline.

Because of the distribution of high-producing clones in stable pools (Figure 2), only a small number of monoclonal clones (<200) need to be established and ranked to isolate sufficient numbers of high-producing clones. Screening, characterization, and ranking of clones, therefore, does not require expensive high-throughput instrumentation. This innovation also facilitates simultaneous management of multiple cell line development projects with limited additional labor.

Atum Bioprocessing Tutorial Figure 2
Figure 2. Comparison of charge groups and glycan profiles derived from a stable pool of clones and three randomly selected derivative stable clones. PerkinElmer’s LabChip® was used to estimate the fraction of charge groups (basic, main, and acidic). Glycan profiles (G0, G0F, G1Fa, G1Fb, and GF2) were determined by hydrophilic interaction liquid chromatography (HILIC). Clonality was confirmed using Solentim’s VIPS™ system

Genetic and functional stability of Leap-In cell lines

Genetic stability was assessed in 79 final Leap-In clones, from six cell line development programs, by measuring the transgene copy number and volumetric productivity at PD60. More than 90% of the clones maintained time 0 (T0) levels of copy number and volumetric productivity at PD60, and none of the values dropped below 70% of the T0 values, demonstrating the remarkable genetic stability of the Leap-In-mediated integrations (Figure 3).

Atum Bioprocessing Tutorial Figure 3
Figure 3. Productivity and copy number stability in Leap-In-mediated stable clones. Chart shows the fraction of clones for which copy number and productivity values at PD60 are 100%, 90–100%, 80–90%, and 70–80% of the T0 value, based on an analysis of 79 stable lines.

Control of expression levels

Transposon-based integration systems can successfully deliver a large cargo (up to 100 kb) of genetic information,2 making it possible to introduce multiple genes, each under the control of its own promoter, on the same expression construct. Moreover, since the

integrated transgenes maintain their structural and functional integrity upon genomic integration, the constructs express their different open reading frames (ORFs) at the intended ratio.

Figure 4 shows an example of expression ratio control in 2-ORF-expressing constructs. Independent control of gene expression levels, within the same construct, guarantees that every clone derived from a stable pool expresses the subunits at identical ratios.

Atum Bioprocessing Tutorial Figure 4
Figure 4. Control-of-expression ratios for 2-ORF Leap-In transposon constructs. Chart presents a ratio control experiment for two ORFs coding for two secreted proteins expressed by 14 different Leap-In constructs. The expression levels were assessed from clarified harvests using the ForteBio’s Octet platform. The pink and blue bars show the relative expression of the two proteins; the gray line indicates their ratio.

Compared to conventional, random integration-based technologies, Leap-In-transposase-mediated stable cell line development provides an array of beneficial features, including multiple single-copy integration events per cell preferentially targeting transcriptionally active sites. The integrated transgenes faithfully maintain their structure and functional activity, leading to a strong bias toward high-producing clones in Leap-In-mediated stable pools and high comparability between stable pools and derivative clones. These features directly translate to increased productivity, improved product quality, and shortened CMC development timelines.

 

References
1. Hottentot QP, van Min M, Splinter, E, White, SJ. Targeted Locus Amplification and Next-Generation Sequencing. In Genotyping: Methods and Protocols. White SJ, Cantsilieris S, eds: 185–196. (New York, NY: Springer): 2017. pp. 185–196.
2. Rostovskaya, M, Fu J, Obst, M, Baer, I, Weidlich, S, Wang, H, Smith, AJH, Anastassiadis, K, Stewart, AF. Transposon-mediated BAC transgenesis in human ES cells. Nucleic Acids Res. 2012; 40: e150–e150.

 

The following researchers from Atum contributed to this article: Sowmya  Balasubramanian, PhD, cell line development scientist; Jessica Choi, cell line development associate; Sowmya Rajendran, cell line development associate; Harpreet Kaur, cell line development associate; Maggie Lee, research associate; Claudia Sepulveda, production associate; Calvin Tang, production associate; Vivi Truong, production associate; Divya Vavilala, PhD, expression technologies scientist; Lynn Webster, cell line development senior scientist; Bo Zhang, cell line development associate;  Ferenc Boldog, PhD (fboldog@atum.bio), director of cell line development.

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