Metabolomics, the global, unbiased profiling of biochemicals in a complex system, looks at the widest possible range of pathways in a system to detect changes during cell growth related to the medium, feeding, or temperature shifts. By using metabolomics to understand the action of biochemicals present in a cell system, process development researchers can discover targets for pathway engineering, enhance the development and optimization of growth media, and refine the scale-up process. The technology also can be used to identify the critical quality attributes of a process in a Quality-by-Design approach to process development, or for later application of process analytical technology for ongoing process monitoring.

Identifying relevant biochemical markers in cell line selection and growth media development has traditionally been conducted using processes that are largely based on a trial-and-error methodology. Conventional approaches can be very costly, time-consuming, and ultimately frustrating for the researcher. A tool called metabolomics uses global biochemical analysis to gain mechanistic insight into biochemical and metabolite changes in cell systems and media, and greatly increases the speed with which process development researchers can find relevant biomarkers for optimizing their processes for more meaningful results.  

Historically, process development researchers have relied on a limited number of metabolites (such as lactate, ammonia, and glucose) to provide insight into the metabolic state of a cell and the performance of the culture in the bioreactor. Improvements in productivity and quality of results have been the target measurements. Even in the era of genomics, metabolites and phenotypic data (e.g., titer) are the principal benchmarks by which cell culture and process development scientists determine the success or failure of an experiment. Although scientists understand the powerful connections between metabolites and phenotype, the inability to study more than a few metabolites at a time has proven a severely limiting factor in advancing research.  

Using Metabolomics to Understand Cellular Phenotype

Small-molecule metabolites are the end products of cellular processes, and are considered the most accurate markers of how biological systems respond to genetic or environmental changes. Thus, biochemicals (metabolites) are the key to cellular phenotypes. There are approximately 2,900 biochemicals in the mammalian metabolome. Unlike macromolecules, metabolites represent focused, distilled changes in phenotype.  

Scientists developing a recombinant protein process typically look at about five metabolites during an experiment. Whether or not those particular metabolites are significant is not known until the experiment has run its course. The bias shown toward metabolites whose behaviors are chosen for observation during the experiment often excludes potentially relevant markers while generating little useful data. Thus, many iterations of an experiment can be conducted without identifying genuinely significant markers. 

Metabolomics, the global, unbiased profiling of biochemicals in a complex system, looks at the widest range of pathways in an experimental system for significant changes that occur during cell growth in a particular medium as well as in response to feeding or temperature shifts. This approach maximizes the chances for determining the relevant pathways associated with a poor product quality or a metabolic switch. In addition, the biochemical markers associated with the pathway can be used for further development and, eventually, in production. 

Using Metabolomics for Bioprocessing Studies

An overview of a typical metabolomics experiment for bioprocessing is shown in Figure 1. The experiment begins with the collection of samples from a shake flask or bioreactor over a period of time. For Chinese hamster ovary (CHO) cell experiments, this may mean sampling each day over a 14-day period. The cells are separated from spent media and flash frozen. Each sample is extracted to isolate the biochemicals and metabolites (typically with a molecular weight <1,500), then split into three portions and run across three mass spectrometry platforms (UHPLC–MS/MS + ESI, UHPLC–MS/MS - ESI, and GC–MS + EI) in which the collected data are analyzed by proprietary software. 

 Figure 1.  An overview of a typical metabolomics experiment for bioprocessing. The experiment begins with the collection of samples from a shake flask or bioreactor. The cells are separated from spent media and flash frozen. Each sample is extracted to isolate the biochemicals and metabolites, then split into three portions and run across three mass spectrometry (MS) platforms. Software processes the MS data. By comparing the retention time of the peak and the mass spectral information to a database of biochemical standards, the software can rapidly identify hundreds of analytes in a single sample. Then the data are statistically analyzed to determine significant changes at each time point compared to the baseline sample. These metabolic changes are grouped by pathway and color-coded to allow rapid determination of pathways altered. Because both cells and spent media are analyzed, changes in the media can be compared to changes in cellular metabolism. This allows researchers to monitor the effect of a media-depleted biochemical on the metabolism of the cell. Likewise, the effect of accumulation of toxic metabolites can be determined. 

The software processes the mass spectral data, detecting and integrating chromatographic peaks. Each peak is composed of a number of mass spectra (nominal mass and MS/MS fragmentation pattern). By comparing the retention time of the peak and the mass spectral information to a database of biochemical standards, the software can rapidly identify hundreds of analytes in a single sample. Then the data are statistically analyzed to determine significant changes at each time point compared to the baseline sample. These metabolic changes are grouped by pathway and color-coded to allow rapid determination of altered pathways. Because both cells and spent media are analyzed, changes in the media can be compared to changes in cellular metabolism. This allows researchers to monitor the effect of a media-depleted biochemical on the metabolism of the cell. Likewise, the effect of accumulation of toxic metabolites can be determined. 

Two general classes of applications have emerged using metabolomics technology in bioprocessing. The first is in finding targets for metabolic engineering, formulating growth media, and identifying areas for potential process development and improvement. For example, metabolomics can uncover a novel metabolism. It also can find blind spots in media requirements and help develop a rationale for a feeding strategy. The knowledge gained also can generate hypotheses for further testing. 

The other general application for metabolomics is biomarker discovery. By using the rich global information from this analysis, new markers can be discovered. These new markers can be used the way lactate or ammonia are currently used—at any point in cell culture development work. For example, the data may be used to determine selection criteria for clone selection or media development, process development monitoring, and other potential downstream uses (for example, to determine critical quality attributes for a Quality-by-Design approach to process development, and for later application of process analytical technology for ongoing process monitoring.). 

The following case studies illustrate the application of metabolomics in bioprocess optimization. 

Case Study 1: Biochemical Marker Discovery

In this study, investigators suspected cells were in an energy- deficient state and were not using glucose efficiently as the culture progressed. Glucose levels in the media were marginally informative of this suspicion. One goal of the study was to discover markers that are more robust and descriptive than glucose. Figure 2 shows the results of heat mapping generated through metabolomic analysis and the relevant changes discovered. 

Figure 2.  The results of heat mapping generated through metabolomic analysis and the relevant changes discovered. A heat map demonstrates the changes over time in metabolites from both the cells and the media (red areas reflect increases over time; green areas depict decreases). The expanded center section of the heat map shows critical changes, demonstrating that the sorbitol pathway of glucose use changed during the run. 

A heat map with a subset of metabolites detected in this study, shown at the left in Figure 2, demonstrates the changes over time from both the cells and the media (red areas reflect an increase over time; green areas depict a decrease). The expanded center section of the heat map shows critical changes, demonstrating that the sorbitol pathway of glucose use changed during the run. 

Figure 3 (top) is a simplified illustration describing how the sorbitol pathway is another route of glucose use. Sorbitol production can be induced in times of osmotic stress, and at high levels, it can induce apoptosis in some cell types. However, sorbitol is generally thought to be produced in the presence of elevated glucose levels. Consistent with this idea, the bottom of Figure 3 shows that sorbitol may be a marker of reduced glucose use by glycolytic pathways (this is not to say that a large proportion of glucose likely entered the sorbitol pathway, just that a reduced proportion may not be entering glycolysis).  

Figure 3.  Top: A simplified illustration describing how the sorbitol pathway is another route of glucose use. Sorbitol production can be induced in times of osmotic stress; at high levels, it can induce apoptosis in some cell types. However, sorbitol is generally thought to be produced in the presence of elevated glucose levels. Bottom: Sorbitol may be a marker of reduced glucose use by glycolytic pathways. 

In contrast to measuring glucose in the experimental media, the sorbitol signal is more pronounced with time. Thus, whether a marker of reduced glucose use by glycolysis or an indicator of osmotic changes, this metabolomic analysis demonstrated that sorbitol can be used as a robust marker of cellular changes. It may be possible to use sorbitol levels, in conjunction with glucose and lactate levels, as a measure of glucose-use efficiency. Clearly, measuring only standard markers would not have provided a conclusive view of what was actually occurring in the experiment. 

Figure 4. Changes over time in the heat map for data from the cells and the media (red reflects increases over time; green reflects decreases). The biochemical pathway on the bottom demonstrates that many lipid metabolites changed over time.  

Case Study 2: Platform Process Evaluation

In an effort to improve a developing platform process, the investigator sought greater knowledge into uncharted metabolic deficiencies that could be targets for cell culture performance. Figure 4 shows changes over time in the heat map for data from the cells and the media (again, red reflects an increase over time, and green reflects a decrease). Again, only a few of the biochemicals detected in the study are shown. The biochemical pathway on the right demonstrates that many lipid metabolites changed over time.  

Figure 5.  In this example, elevated glycerol and monoacylglycerols (possibly from lipid storage droplets) caused triacylglycerol lipolysis.  

Figure 5 illustrates that elevated glycerol and monoacylglycerols (possibly from lipid storage droplets) caused triacylglycerol lipolysis. By contrast, membrane phospholipid catabolites were reduced over time (Figure 6). Figure 7 shows that the changes caused loss of membrane integrity, demonstrated by the progressive accumulation of glucose-6-phosphate in the media instead of being sequestered in the cell. The large changes in lipids indicated some manner of lipid imbalance, which resulted in reduced cell membrane integrity and viability. 

Figure 6.  In contrast to what is seen in Figure 5, in this case, membrane phospholipid catabolites were reduced over time.  

Because choline is a major head-group of membrane phospholipids, it is possible that choline depletion in this experiment had an effect on membrane integrity and viability. Although there are other possibilities for the altered lipid metabolism, the use of global metabolic profiling uncovered an imbalance in lipid metabolism, proposed a possible source of the imbalance (i.e., choline reduction), and (at a minimum) reduced the design space for tackling optimization of this process. 

Figure 7.  Changes caused a loss of membrane integrity, demonstrated by the progressive accumulation of glucose-6-phosphate in the media instead of being sequestered in the cell. The large changes in lipids indicated some manner of lipid imbalance, which resulted in reduced cell membrane integrity and viability.  

Bioprocessing and cell culture development have historically been difficult because of the limitations on how much is known about the components of an experimental system. These systems involve hundreds of metabolites constantly changing during growth and in response to feeding and other environment modifications.  

Traditionally, monitoring of these processes has involved a handful of metabolites. In some cases, these metabolites give insight into metabolic changes. More often than not, however, other metabolites are more closely tied to the phenotypical changes of interest (cell viability, protein expression levels, product quality). Using metabolomics, the metabolic underpinnings of cellular changes can be rapidly pinpointed, directing scientists to key areas for optimization. 

 is the chief scientific officer at Metabolon, Inc., Research Triangle Park, NC, 919.572.1711, 

Articles

Through metabolomics, the metabolic underpinnings of cellular changes can be rapidly pinpointed, directing process development scientists to key areas for cell culture optimization.

Using Metabolic Profiling Technology to Advance Cell Culture Development

For a Phase 1 antibody project, the primary objective of our cell line development group is to deliver a stable, high performing, clonal cell line in an aggressive timeframe, leaving little time to react to the challenges associated with cell line instability, such as dramatically reduced product expression. Our current cell line development timeline allows for 6.5 months from transfection to the establishment of a cell bank for a lead clone, which is expected to deliver 1–3 g/L in a fed-batch process. Our cell line selection process consists of numerous rounds of successive screening, initially assessing hundreds of clones. During that time, clones are eliminated because of poor performance in scaled-down models of the fed-batch process or because of a loss of product expression over time. When such instability in product expression occurs for a lead clone at a late stage in the timeline, both upstream and downstream process groups must quickly identify alternatives so that the material needs of the project will be satisfied and deadlines are still met.   

This manuscript presents examples of cell line instability that we have encountered during Phase 1 antibody projects, and the operational consequences that have ensued. It describes the different types of instability we have observed, our attempts to analyze the presumptive underlying genotypic causes of these different types of instability, and the general methods and tools that we use to investigate cell line instability. Finally, we describe the recent development of an RT-PCR–based assay that allows us to eliminate potentially unstable cell lines from consideration early in the cell line development timeline.   

There are various approaches to developing a therapeutic antibody product, and many development organizations now use platform, or standard procedures, (see Figure 1 for an example) because this approach works well for achieving the objectives of delivering a stable, high performing, clonal cell line in a short timeframe. The goal of using a platform approach is to enable a greater number of molecular entities through the pipeline, and to decrease both the length of time and the level of investment in developing these molecular entities before they have proven efficacy in human clinical trials. Cell line development platforms rely primarily on multiple rounds of successive screening of large numbers of clones with the recognition that clones will be eliminated over the course of development because they have not performed sufficiently well in a scaled-down model of the fed-batch production process or they have lost expression of the protein product, even in the presence of selective pressure. During the cell line adaptation period shown in Figure 1, cell line expression characteristics can be evaluated and cell banks for each clone can be generated at some frequency. Hence, an enabling aspect of the design of the platform shown in Figure 1 is that the phenotypic stability of a clone can be established before its selection as the production cell line. By considering stability as part of the cell line selection and cell banking paradigm, we can ensure that the problems encountered and described here during the cell line development window are not observed during the clinical, or future commercial, manufacturing window.  

Although our cell line development group has been successful in meeting our project goal of generating Chinese hamster ovary (CHO) Phase 1 cell lines that can deliver >1 g/L in a platform production process, cell line instability occurring at a late stage in the adaptation period timeline has resulted in both upstream and downstream process groups scrambling to deal effectively with last-minute changes to meet deadlines. Hence, we have developed specific methods and approaches to enable an increased understanding of the root causes of our observed cell line instability. This knowledge potentially could be used for the early, proactive identification of unstable clones or the elimination of cell line instability altogether. This would be highly beneficial to the cell line and cell culture process development organization, thus ensuring sustainable success in meeting deliverables and timelines. 

This current work describes the types of instability we observe: "acute," a precipitous loss of product expression occurring over a short time span of approximately 2–4 weeks, and "gradual," a slow decline of product expression occurring over the months of the cell line adaptation period shown in Figure 1. In addition, we describe our attempts to analyze the presumptive underlying genotypic causes of these different manifestations of instability, which include, but are not limited to, DNA rearrangements and DNA methylation. We discuss the general methods and tools that we use to investigate cell line instability, including Southern and northern blot analysis, PCR-based methods, and an assay to detect methylated DNA, and how, when, and why we use these methods. Based on results from an intensive study examining the most frequent causes of cell line instability at the molecular level in our Phase 1 antibody projects, we have developed and implemented an RT-PCR–based cell line screening assay that enables the elimination of unstable cell lines from consideration early in the platform process.    

Figure 1.  A prototype platform cell line development timeline for a Phase 1 antibody project. Following transfection and selection procedures, clonal transfectants are isolated and subjected to successive high-throughput screens. The top performers from this screening process then undergo a cell line adaptation period, consisting of several months. During this time, cell line stability information is collected, and the clones are screened in a series of production fed batches, first at small scale, and then in benchtop bioreactors. A production clone is selected, the final production process is defined, and a master cell bank is generated. 

The Causes of Common Types of Cell Line Instability and Their Impact

Figure 2 shows the stability profiles for the 24 highest performing clones for a Phase 1 antibody project. These 24 clones were selected from hundreds of clones that were initially subjected to two rounds of high throughput clone screening. The figure illustrates not only the types of instability we observe (acute and gradual), but also shows how the performance of high-performing clones may change in even a very short amount of time. This is clearly seen for the nine clones, designated with red lines and symbols, where a 50% drop in expression occurred within two weeks, and product expression was completely lost within 50 days of continuous culturing. The ramifications of this lack of predictability in clone performance can affect the entire upstream and downstream process development teams during the critical period when they are striving to bring together the clone, the cell culture process, and the purification process to achieve the desired performance and product quality.    

Figure 2.  Cell line instability manifests itself in various forms. Plotted is the specific productivity (Qp, picograms/cell/day) for 24 clonal cell lines for a Phase 1 antibody project during 90 days of continuously culturing the cells. Cell lines showing a stable Qp profile are marked by black symbols, cell lines showing gradual instability are marked by blue symbols, and cell lines showing acute instability are marked by red symbols. 

To further emphasize this point regarding unpredictability, Table 1 shows the frequency of clones exhibiting acute and gradual instability for seven different antibody projects for which the same platform procedures were used. For each project, a total of 24 clones were assessed. The numbers illustrate that the level of instability is quite variable from project to project. This variability in instability emphasizes our inability to consistently predict how our system will perform. We therefore attempted to determine the causes of instability we observe, and to see if this information might enable us to take corrective action to reduce or eliminate instability from our cell line development process.     

Table 1. Frequency of acute and gradual instability in Phase 1 antibody projects. This table contains information on the number of clones demonstrating acute and gradual cell line instability in seven different Phase 1 antibody projects. For each project, 24 adapted clones were monitored over a similar length of time. 

The results presented in Figure 3 are representative of one type of instability that was observed in several Phase 1 antibody projects. Platform procedures, as outlined in Figure 1, were followed for all activities from transfection through cell line adaptation to cell banking. As shown in Figure 3A, a high producing clone from this project demonstrated a dramatic and eventually complete loss of antibody expression (as marked by the red line and triangles in Figure 3A). RNA was prepared at the time points marked by the black triangles in Figure 3A, and was run on the northern blot shown in Figure 3B, which was hybridized with a probe specific for the selectable marker dihydrofolate reductase (

). At the earlier time points, the expected heavy chain (HC)-

 bicistronic transcript (marked by an arrow, labeled "HC-

") was seen. Over time, however, there was a detectable loss of this HC-

 bicistronic transcript with the appearance of a smaller transcript (also marked by an arrow, labeled "rearranged-

"). To show that each lane contained equivalent amounts of RNA, the blot was subsequently hybridized with a probe encoding the housekeeping gene glyceraldehyde 3-phosphate dehydrogenase (

), and similar signal intensities were observed across all the lanes. Cloning and sequencing the smaller transcript demonstrated that it lacked any HC sequence, but it still contained an intact 

 and HC had become uncoupled: although this clone continued to synthesize 

 and to grow in the presence of methotrexate, it was no longer producing HC protein or intact antibody.  

Figure 3.  Rearranged DHFR in an unstable Phase 1 antibody cell line. A) The small red triangles mark the specific productivity (Qp, picograms/cell/day) for a Phase 1 antibody expressing cell line over 150 days in continuous culture. The large black triangles denote the time points (34, 62, 102, 119, and 147 days in culture) at which RNA was prepared for the northern blot shown in Panel B. B) Each lane was loaded with 3 Î¼g of isolated RNA, the gel was transferred to nitrocellulose, and the nitrocellulose was hybridized with probes encoding DHFR and GAPDH. Migration of HC-DHFR, rearranged DHFR, and GAPDH (control) are as indicated. 

In referring back to the timeline depicted in Figure 1, this clone had already made it through clone screening and small-scale productivity assessments, and its performance was in the process of being evaluated in benchtop bioreactors. It was considered to be a top performer and a favorite for being selected as the production clone for this project. However, because of its instability, this clone was immediately eliminated as a contender, and both the upstream and downstream groups began to focus their efforts on an alternative clone whose performance was adequate, but relatively inferior, compared to the unstable clone before it became unstable. Although deadlines and material needs were successfully met for this project, some additional bench-scale bioreactor work had to be performed at a late stage on the timeline to sufficiently assess the performance of the alternative clone.   

Following these results and additional work, alterations were made to our vector strategy. A head-to-head comparison of clones resulting from transfections with both the newly engineered vectors and the previously used ("old") vectors, with the same antibody molecule, showed no differences in recombinant protein expression or cell growth performance during clone screening before cell line adaptation (data not shown). High-producing clones from this head-to-head comparison were grown in continuous culture, and RNA was prepared at various time points and was run on a northern blot hybridized with probes encoding 

The results are shown in Figure 4A. The lane labeled "old vector clone" contained RNA prepared at a single time point from a single clone derived using the previous vector system, and showed that there was rearranged 

 transcript present. The other lanes (labeled 1, 2, 3, 4, 5) contained RNA from five clones arising from transfection with the newly engineered vectors at several time points (these time points ranged from 11 to 113 generations). None of these clones were found to have rearranged 

. Information contained in Figure 4B shows that of the 12 high-producing clones derived using the new vectors, none exhibited rearranged 

 transcripts, whereas 9 of the 12 high producing clones derived using the previous ("old") vectors demonstrated a loss of product expression during the same time period, and these latter clones were all found to have rearranged 

Figure 4.  Alterations in antibody vector constructs result in improved cell line stability. A) RNA was prepared at indicated time points (in generations) from five clones derived from a transfection using newly engineered vector constructs, and from a single clone derived from a transfection using previous "old" vector constructs. Each lane was loaded with 3 Î¼g of RNA, the gel was transferred to nitrocellulose, and the nitrocellulose was hybridized with probes encoding DHFR and GAPDH. Migration of HC-DHFR, rearranged DHFR, and GAPDH (control) are as indicated. B) Refer to text for explanation of table. 

Although the alternative vector strategy significantly reduced the frequency of 

 rearrangement, it did not completely eliminate the ability of cells to uncouple 

 and HC. This is represented by the data shown in Figure 5. Using the new vector strategy, platform procedures were followed for all activities from transfection through cell line adaptation to cell banking. Figure 5A shows the growth and productivity profiles for a clone that demonstrated a cell-specific productivity (Qp) of >30 picograms per cell per day out to 42 generations. From 42 generations onward, the growth rate (marked by the red line and triangles) of the clone appeared relatively stable, however, a precipitous drop in antibody expression (Qp shown in the black line and triangles) was observed starting at about 77 generations, resulting in a total loss of product expression by 107 generations. RNA was prepared at several time points (marked by blue generation numbers on Figure 5A) during the time that this clone was continuously cultured, and presented in Figure 5B is the northern blot of these RNA samples hybridized with a 

Figure 5.  DNA rearrangement in an unstable Phase 1 antibody cell line. A) A clone from a Phase 1 antibody project was continuously cultured for 107 generations. Plotted are the specific productivity (Qp, picograms/cell/day) designated by black triangles, and the growth rate (hr-1) designated by red triangles. RNA was isolated at the time points (19, 42, 63 and 100 generations) indicated on the graph. B) Each lane was loaded with 3 Î¼g of isolated RNA, the gel was transferred to nitrocellulose, and the nitrocellulose was hybridized with a probe encoding DHFR. The migration of rearranged DHFR is indicated. 

As shown, there was little change in the level of expected HC-

 bicistronic transcript from 19 to 63 generations. By 100 generations, however, there was a detectable loss of the expected HC-

 transcript concomitant with the appearance of an even smaller, rearranged 

 transcript than was previously observed (see Figures 3B and 4A). The cloning and sequencing of this smaller transcript demonstrated that it contained an intact 

-coding sequence and no HC sequence. Thus, the cells were able to grow in the presence of methotrexate by continuing to synthesize 

 By 107 generations, however, they were clearly expressing no HC protein and therefore, no intact antibody.   

Further investigation of other unstable clones, by Southern and northern blot analyses, RT-PCR, and cloning and sequencing, was performed to further characterize instances of 

 rearrangement. In all cases studied (data not shown), our results indicated that the HC gene had become deleted, or "looped out." As this phenomenon continued to be problematic, we developed the RT-PCR–based assay shown in Figure 6 to enable the early and efficient detection of rearranged 

 transcripts in cell line candidates.    

As depicted in Figure 6A, forward and reverse primers were designed to span the HC coding sequences lost as a result of rearrangement within our HC-

-containing vector. Using these primers, RT-PCR performed on RNA prepared from clones, which had not undergone HC rearrangement, would be expected to generate an RT-PCR product of approximately 2,700 bp. However, a rearrangement deleting any of the HC would give rise to an RT-PCR product of less than 2,700 bp, and depending on the extent of HC sequence deletion, a product as small as ~500 bp if only intact 

 coding sequences remained. Using this assay, referred to as the 

, we analyzed the RNA samples prepared from the clone described in Figure 5. As shown in Figure 6B, a ~500 bp PCR product, indicative of HC rearrangement, was detected in the RNA sample from 63 generations. As this rearrangement was not detected until the 100 generation time point by the northern blot in Figure 5B, LODA was more sensitive than the northern blot in detecting this rearrangement. Additionally, LODA detected the rearrangement before the time point at which instability was marked by a noticeable decline in Qp at ~77 generations in Figure 5A.  

Figure 6.  Development of the loop out detection assay (LODA). A) Schematic depicting the loop out detection assay. For a more detailed explanation, refer to the text. B) Samples from the same RNA preparations run in the northern blot shown in Figure 5B were subjected to the LODA depicted in Figure 6A. LODA samples were run on an agarose gel which was subsequently stained with ethidium bromide to visualize RT-PCR products. Expected intact product of 2.7 Kb and a smaller product (~500 bp), in which the HC has been "looped out," are marked by arrows. 

LODA, which is fairly high throughput, is now used at several key nodes during our cell line development platform timeline. This reduces the probability that the development team will be investing valuable time and resources in moving forward high producing clones that will eventually lose protein expression. In addition, LODA, coupled with sequencing, has enabled us to catalog the sites of the HC rearrangement. This information is being used to assess whether additional modifications to our vector strategy could result in further reductions in the frequency of HC-

The acute instability described above is most likely the consequence of a combination of factors. One cause may be our selection scheme, and another might be that CHO cells, although clearly a workhorse of biopharma, were not naturally designed to produce large amounts of recombinant protein. Nonetheless, with the screening procedures and tools we have put in place, the threat of instability to our clone selection process has been greatly reduced.   

Gradual Instability Caused by Gene Silencing 

In addition to the acute instability caused by DNA rearrangements, we also observe gradual instability which we believe results from epigenetic changes resulting in gene silencing. The scientific literature contains a great deal of information on gene silencing, which is marked by changes in chromatin structure, including the methylation of cytosine residues at specific CpG dinucleotides in DNA and changes in histone protein modifications.

  These events inhibit the binding of transcription factors, consequently shutting down transcription. Hence, we wished to ascertain whether DNA methylation might play a role in the gradual instability in our cell lines. A conventional method for determining whether DNA is methylated is to perform a restriction digest with an enzyme whose activity is inhibited by the presence of a methyl group in its CpG-containing recognition sequence, and then to analyze the digest by Southern blot.   

The phenotypic stability profile for cell line 16-6F, which was continuously cultured for more than 200 days, showed gradual declines in both titer and Qp. northern blots showed that HC and light chain (LC) transcript levels were decreased, and Southern blots of the coding region demonstrated that HC and LC gene copy number were unchanged (data not shown). Genomic DNA samples, prepared at various time points during the time the cells were cultured, were digested with AatII, which cuts the specific sequence 5'-GACGTC-3' only when the CpG dinucleotide in the sequence is unmethylated. If the sequence is methylated, AatII will not cut. The AatII digested DNA was run on a gel, transferred to nitrocellulose membranes, and hybridized with specific HC and LC probes. As shown in Figure 7, with increasing generations there was progressively less AatII digestion of the DNA, resulting in undigested DNA migrating high up in the lane. A conclusion from these results was that the decline in titer and Qp in the 16-6F cell line correlated with, and may have in part been caused by, DNA methylation.    

Figure 7.  Evidence for DNA methylation in an unstable cell line from a Phase 1 antibody project. Cell line 16-6F was continuously cultured for more than 211 days, and genomic DNA was prepared at various time points (45, 82, 117, 134, and 211 generations). The DNA was digested with AatII, 2 Î¼g were run on an agarose gel, and the gel was transferred to nitrocellulose, which was hybridized with probes encoding specific HC and LC genes. The lane labeled "CHO K1 + vector" contains 50 pg AatII digested specific plasmid DNA spiked into CHO K1 genomic DNA. The migration of both nonmethylated and methylated DNA is indicated. 

The drawbacks to performing this type of analysis are that it is dependent on the presence of specific enzyme restriction sites in the plasmid region of interest, it is fairly low throughput, it is labor intensive, and it requires the use of radioactivity to generate results of consistently high sensitivity and high quality.   

Methylated DNA Immunoprecipitation (MeDIP) 

As an alternative, we developed and now use a methylated DNA immunoprecipitation (MeDIP) procedure.

  This procedure is illustrated in Figure 8: DNA is denatured and digested, and is incubated with an antibody that specifically recognizes 5-methylcytidine. The resultant immune complexes are incubated with protein A/G beads, and following washing and centrifugation steps, the captured material is eluted and can be subjected to endpoint PCR, or, if quantitation is desired, to qPCR. The advantages of this procedure compared to a methylation-sensitive Southern blot are that it is high throughput, requires no radioactivity, allows for quantitative results using qPCR, and additionally, through the use of specific PCR primers, can enable a determination of which region(s) of DNA are methylated.    

Figure 8.  Schematic of the methylated DNA immunoprecipitation (MeDIP) procedure. For a more detailed explanation, refer to the text. 

Figure 9 shows the results of a MeDIP experiment on the same 16-6F genomic DNA from the Southern blot experiment shown in Figure 7. Endpoint PCR made use of primers directed to the promoter region of our transfected vector construct, and as expected, the results showed no detectable PCR product from untransfected CHO cells. Also as expected, the lane labeled "+control" showed a very strong signal for 

methylated DNA plasmid. The lane labeled "16-6F," which contained the MeDIP PCR product from the genomic DNA sample from the phenotypically unstable 16-6F cell line prepared at 211 generations (recall from Figure 7 that this DNA was not fully digested with the methylation sensitive enzyme AatII), showed a strong signal as well. Although the size of DNA fragments generated during the digestion step of the MeDIP procedure needs to be considered, these latter results suggested that at least a portion of the methylation is in the vicinity of the promoter region of our integrated transfected vector construct. The 16-6F cell line was later re-cloned, and genomic DNA from a resultant high-expressing subclone, 16-6F A5, whose protein expression profile was stable, was subjected to the same MeDIP and PCR assay conditions. Figure 9 shows that in the lane labeled "16-6F A5," there is a much reduced methylation signal. Taken together, these data indicated that recloning resulted in the isolation of a clone having reduced levels of expression vector methylation, and that the markedly reduced methylation in this clone correlated with its increased protein expression and increased stability.     

Figure 9.  MeDIP assay results of 16-6F and subclone 16-6F A5. Genomic DNA from the 211 generation time point of the unstable cell line 16-6F described by Figure 7 and associated text was subjected to the MeDIP procedure illustrated in Figure 8. Forward and reverse PCR primers were specific for 5' and 3' sequences just upstream and downstream of the promoter region of the transfected vector construct. The lane labeled "+ control" is in vitro methylated plasmid also subjected to the MeDIP procedure. 16-6F was later re-cloned, and a resultant stable subclone, A5, was also subjected to the MeDIP procedure. The arrow marks the migration of the methylated PCR product. 

The MeDIP assay allows us to increase our understanding of the methylation status of our integrated expression constructs. By applying it broadly to our Phase 1 antibody projects, the MeDIP assay will enable us to monitor the extent to which epigenetic changes of this nature occur in our cell lines and negatively affect the outcome of our cell line development efforts.  

By considering stability as part of the cell line selection and cell banking paradigm, we can ensure that instability problems are not observed during clinical or commercial manufacturing.

Managing Cell Line Instability and Its Impact During Cell Line Development

Cell culture medium plays a significant role in determining the cell density, viability, and productivity of a robust manufacturing process. Current regulatory requirements prefer bioprocesses that do not use any animal-derived components throughout cell line and cell culture development. However, using media containing serum for early stages of cell line development is still a common practice  for deriving stable production cell lines for manufacturing. The ideal medium should be able to support all activities in the cell line and process development stages for maintaining consistent cell populations and product quality. Here, we describe such performance by an in-house-developed, universal animal component free (ACF) medium that can support transfection, amplification, subcloning, banking, and production of the different Chinese hamster ovary (CHO) cell lines generally used for recombinant protein production. By using this ACF medium, designated as MTCM, there was an overall reduction in cell line development time for two distinct expression systems by eliminating the adaptation period between serum-containing medium to ACF medium. Furthermore, by using the same basal medium throughout cell line and process development, transitional changes in growth characteristics, productivity, and heterogeneity in the cell populations were simultaneously kept to a minimum. Finally, a robust and high yielding upstream production platform technology for human monoclonal antibodies (HuMAbs) was developed by using MTCM both as basal and feed media in fed batch cultures. This accelerated CHO cell culture optimization that led to 6 g/L HuMAb production and facilitated an efficient process integration of upstream and downstream. 

Productivity enhancement by CHO cell culture to several grams/L has been revolutionizing the biomanufacture of recombinant therapeutic antibodies.

  The development of antibodies and their derivatives with close to 200 clinical trials largely depends on the knowledge gathered about CHO expression systems, which has enabled the biotech industry to accelerate the development of its pipeline candidates. It is also forecasted that CHO production systems will play a crucial role in future biomanufacturing processes because of their capability to produce high expression titers,

  in some cases equivalent to those of transgenic animals (approximately 10 g/L), along with desirable post-translational modifications. 

The development of cell culture medium has been one of the major efforts contributing to the significant improvements in product titer in the past by supporting high cell densities and extending culture longevity in fed-batch mode. Often, production medium for high titer processes is different from that used during the earlier stages of cell line development, including transfection and subcloning, where single-cell derived colonies need to grow. Medium with serum is often used at these early cell line development stages for both adherent as well as suspension cell cultures. These recombinant cell lines are then slowly adapted to ACF media or chemically defined (CD) media during the later stages of development, for inoculum expansion and recombinant protein production. These transitional phases can take a considerable amount of time for cell lines to adapt to such medium shifts and for process development scientists to select stable, high producers from a diversified population. Here, we describe upstream process development using a proprietary medium throughout the cell line and process development phases. 

Transfections of different CHO host cell lines were carried out using a single expression plasmid containing the heavy and light chain genes of a human antibody. A BioRad Gene pulser was used to electroporate the DNA into either a 

Expression System II) CHO cell line. Transfected cells were plated in 96-well plates and antibody levels in media with selection pressure were measured using a human IgG kappa/gamma sandwich ELISA. The highest producing cell lines were expanded and single-cell cloned by limiting dilution.  

An aliquot of actively growing cells was diluted in complete growth media to yield 0.25, 0.5, or 1.0 cell/well, and 10–20 x 96-well flat-bottom tissue culture plates were plated. Distinct clones that were confirmed to have originated from single cell/well were evaluated to identify the highest IgG expressing clones. A clone possessing the highest productivity was expanded to prepare a research cell bank. Master cell banks and manufacturer's working cell banks were further established from research cell banks. 

Recombinant CHO cells were grown in shake flasks or 5- to 85-L scale stirred tank bioreactors (from Applikon, Bellco, or Bioengineering) in batch and fed-batch modes. The temperature and CO

 level were controlled for cell culture incubators. The pH, dissolved oxygen (DO), agitation, and gas flows were also controlled if cells were cultured in bioreactors. In fed-batch mode, feed media were added according to the feeding schedules that were tailored to the specific recombinant cell line. Cell density and cell viability were measured using Cedex (Innovatis), Vicell (Beckman Coulter) cell counters or by a manual hand count using the Trypan blue exclusion method. Antibody concentrations were determined by Protein A HPLC (Waters). 

Medarex proprietary media for research, development, and large-scale manufacturing were formulated in both powder and liquid forms from a media vendor.  

Genomic DNA was purified from transfected and untransfected CHO cell lines. Gene-specific primers and a fluorescent probe for a TAQman method were developed by Applied Biosystems using the following two assays. A murine 

 assay was used to determine the number of 

 copies of the expression plasmid integrated into the CHO genome. A rodent 

 assay was used to determine the number of genomes present in the same sample tested for 

 for normalization. The reactions were thermal cycled and data was collected using the ABI Prism 7300 Sequence Detection System (Applied Biosystems).  

A universal medium that can support transfection, selection, and amplification, along with cell culture optimization for high productivity, has time and cost advantages. Such a medium not only reduces overall timelines for cell culture development but also provides a uniform process development platform by minimizing the changes caused by intermittent adaptation processes. A concerted effort to develop a Medarex proprietary medium, MTCM A, as part of an integrated cell line and cell culture process development, was carried out for a HuMAb CHO production platform. This medium was further optimized by adjusting the levels of nutrient requirements for our cell lines, and an improved second-generation medium, MTCM B, was derived. These two versions of MTCM media, with minor changes in composition, can support transfection, amplification, subcloning, and production, and were successfully used for the development of different but related CHO cell lines for HuMAb production. The genealogy of the CHO host cell lines that are generally used for recombinant expression is depicted in Figure 1.  

Figure 1. Genealogy of commonly used CHO host cell lines 

Reduction in Cell Line Development Timelines

Standard transfection and amplification of a CHO 

 cell line are performed by plating cells in serum containing commercially available media after electroporation and subsequently increasing the methotrexate (MTX) concentration to 500 nM in the same 96-well plates. These cell lines may be further amplified to 2 μM MTX in batch cultures. The process has included two rounds of subcloning, occurring before and after adaptation to the serum-free commercially available medium, followed by adaptation to MTCM medium. This entire process takes approximately 12 months (Figure 2A).  

Figure 2.  Effect of using a single medium throughout cell line development for Expression Systems I and II 

Conditions were then developed to accelerate the process in the commercial medium without serum right from the initiation of cell line development, a process that included optimizing transfection efficiency. This shortened the cell line development timeline by up to four months and eliminated the need for a lengthy serum-weaning process and one round of subcloning (Figure 2A). However, using only MTCM media during the entire process of cell line development would eliminate media transitions and potentially reduce the timeline to seven months for a 2 μM MTX amplified cell line (Figure 2A). 

A similar process could be carried out with Expression System II, which does not require amplification. Initial protocols used serum in a commercially available medium at the transfection stage, which was then removed during adaptation. In a manner similar to Expression System I above, the conditions were optimized using the same commercially available medium without serum throughout transfection and subcloning. As Figure 2B indicates, by using only MTCM media, we could accelerate the cell line development timeline to five months. In addition, further reduction in the timeline by another month could be achieved using bulk transfection and selection methods.  

In both cases, pre-adapted host cell banks in MTCM media were generated in a serum-free freezing mixture. Transfection with these well-characterized host cell banks eliminated media transitions and reduced the timelines for cell line development, as illustrated in Figure 2.  

In a controlled experiment for Expression System I (Figure 3), CHO colonies in 96-well plates were gradually amplified to 1 μM MTX in a commercial medium (parental 1 μM) and subcloned (clone 1 μM). The parental line was heterogeneous, as indicated by the increase in gene copy number from 18 to 40 upon subcloning. On the other hand, the efficiency of MTCM media for amplification was monitored by amplifying up to 500 nm MTX and subcloned (Figure 3). This process yielded a cell line (clone 0.5 μM) with 23 gene copies and better volumetric productivity compared to the parental cell line (parental 0.5 μM). Several MTCM-derived clones were pooled and amplified to 2 μM MTX. The pooled culture was increased from an average of 29 gene copies per cell at 500 nm MTX (pool 0.5 μM) to 34 copies at 2 μM MTX (pool 2 μM). Subcloning of the bulk amplified pool resulted in cell lines (clone 2 μM) producing over 500 mg/L in batch culture with 47 and 54 gene copies per cell. Copy number analysis clearly demonstrated the increase in gene copies and productivities in correlation with increasing resistance to higher MTX concentration in MTCM medium. In addition, bulk amplification was also successful with MTCM media, as monitored by qPCR copy number analysis.  

Figure 3.  Productivity and gene copy number analysis during amplification and subcloning for a HuMAb cell line derived from Expression System I 

CHO-derived HuMAb cell lines were plated at 0.25, 0.5, and 1.0 cell/well and were used to measure the subcloning efficiency of MTCM first- and second-generation media. Even when plated at 0.25 cell/well, recombinant cell lines generated from both expression systems were able to grow to 10 to 90% cloning efficiency (Table 1). High-titer cell culture processes can be successfully developed further from these subclones after appropriate upstream process development. In a case of Expression System I using MTCM A medium, MTCM medium outperformed two commercially available ACF media when the same parental cell line was subcloned by limiting dilution. Approximately 227 colonies were obtained from MTCM medium by plating at 1.0 cell/well in 20 x 96 well plates (Table 1), whereas no colonies appeared in the other two commercial ACF media (not shown). As shown in Table 1, these two versions of MTCM media supported high efficiency cloning for CHO recombinant cell lines derived from both expression systems.  

Table 1.  Cloning efficiency of MTCM on recombinant cell lines derived from Expression Systems I and II 

Preparation of Cell Banks with MTCM Media 

Cryopreservation of cells for manufacturing was performed with the two versions of MTCM media for different recombinant cell lines. These banks were periodically monitored to check recovery of the cells for further subculturing and the inoculum expansion process for upstream manufacturing. Freezing the cells at varying densities, from 1 to 3 x 10

  cells/mL, was successful in a freezing mixture containing either MTCM A or MTCM B and dimethyl sulfoxide. These cells were thawed with >85% viability for all CHO cell lines tested (Table 2). One of the cell banks was evaluated for recovery and propagation after five years and was found to have the same performance as at the time of banking. To date, more than 20 recombinant CHO cell banks have been made in MTCM media and used in different manufacturing processes. Inoculum expansion processes for manufacturing are consistent and robust with the banks prepared and stored in these ACF basal media. Using ACF media from early stages of cell line development also reduces safety concerns from exogenous contaminants.  

Table 2. Use of MTCM for cell bank preparation of different CHO recombinant cell lines from Expression Systems I and II 

HuMAb batch processes with MTCM A and B were developed that can yield up to 1 g/L without feed addition. In general, MTCM B supports better cell growth and longevity of the culture, and as a result, leads to better productivity in batch and fed-batch processes. For example, Figure 4 shows that, cell culture processes in MTCM B not only reached higher peak cell density, but also expressed higher antibody levels for both batch and fed-batch compared to those in MTCM A.  

Figure 4.  Comparison of first and second generation MTCM basal media for a HuMAb production using Expression System I 

Feed formulations and feed strategies have been developed by tailoring them to one or two basic generic processes with MTCM A or B basal media to reach high expression levels. In most cases, when high productivity is demanded in short timelines, these processes only need minimal optimization time. These fed-batch processes range from 2 to 6 g/L HuMAb production with MTCM basal and feed media combinations for cell lines derived from these two expression systems, which can increase productivity up to 11 fold compared to batch cultures (Figures 5 and 6).  

Figure 5.  Fed-batch processes in bioreactors using Expression System II for two different HuMabs. A) MTCM B used as basal medium, combined with MTCM feeds for cell line 1 from Expression System II, with an 11-fold increase in productivity from batch to fed-batch. B) MTCM B used as basal medium, combined with MTCM feed for cell line 2 from Expression System II, with a 10-fold increase in productivity from batch to fed-batch. 

High yield processes also can be developed using commercially available chemically defined basal media along with MTCM feed media (Figure 7). Up to a 13-fold increase in productivity was observed when using commercial basal medium with MTCM feed and feed strategies from our generic processes. However, it is reported that there are usually only 2–5 fold productivity gains from media and process optimization efforts.

Figure 6.  Fed-batch processes in bioreactors for Expression System I for two different HuMAbs. MTCM B used as basal medium, combined with MTCM feeds for two cell lines from Expression System I, with a 7-fold increase in viable cell density from batch to fed-batch. 

Using MTCM as a feed medium in combination with commercial basal media from different vendors or using MTCM as a basal medium with different commercial feed media demonstrated the broad applicability of MTCM compositions for high yield upstream processes.  

Figure 7.  Combination of commercial chemically defined basal media with MTCM feed media for two different HuMAbs. A) Chemically defined CHO basal medium combined with MTCM feed for a cell line from Expression System I with 2,000 nm methotrexate (MTX), showing a 10-fold increase in productivity from batch to fed-batch. B) Chemically defined CHO basal medium combined with commercial feed, compared to MTCM feed for a cell line derived from Expression System II, showing a 3-fold and 13-fold increase, respectively, in productivity from batch to fed-batch. 

Process Development Strategies and Advantages

The biotechnology industry depends on robust manufacturing cell lines to produce biologics. The timelines for deriving a stable manufacturing cell line suitable for consistent process scale-up requires thorough screening and subcloning of the initial transfectant population. In the case of suspension 

 CHO cell cultures, amplification procedures using MTX prolongs this process. However, the recombinant cell lines derived from Expression System II have a more straightforward development time, which can take approximately seven months to adapt from serum-containing transfection to serum removal and subcloning. Through careful development of MTCM medium that can support different activities, we were able to significantly reduce the timeline from transfection to cell line selection for both expression systems (Figure 2). Recombinant cell lines derived from both expression systems can use the same medium without serum right from the transfection stage. Using one medium throughout all upstream process development phases also helps retain the higher productivity carried from early clones by eliminating media shifts. 

A robust CHO-based high yielding platform technology was established for HuMAb manufacturing. With this strategy, media inventory became much more streamlined for different process development stages as well as for manufacturing. Basal medium compositions can be manufactured in both liquid and powder formulations that support growth and production equally well. The powder form of both basal and feed media has been successfully manufactured up to the 450-kg scale and shown to be stable for more than two to three years, which has facilitated convenient inventory maintenance for multiple processes of different HuMAb molecules. Powder formulations provide a convenient means of transport and storage of large batches for commercial-scale manufacturing and also decrease the costs associated with testing and releasing multiple media lots. Overall, manufacturing efficiency and timelines are favorably influenced for a wide variety of antibody candidates and also resulted in more operation-friendly processes by using common media requirements for different CHO cell lines. In addition, knowledge of medium formulations provides better insights during upstream process optimization. Furthermore, using in-house media can significantly reduce the manufacturing cost of goods, and medium cost can be lowered as much as 60% compared to commercially available media (Table 3).  

ACF medium sped up cell-line development.

The Impact of Cell Culture Medium on Cell Line and Process Development Timelines and Strategies

Full-length antibodies have captured a significant fraction of the sales volume and value of the biopharmaceuticals market. With increasing knowledge, however, it has been recognized that full-length antibodies may not always be necessary or even desirable. Antibody fragments provide the opportunity for new therapeutic possibilities. Moreover, antibody fragments have the potential for simpler, high-yielding production processes, which can translate into a lower manufacturing cost-of-goods and extended therapeutic benefit. This article discusses the structure and production strategies available for various types of antibody fragment therapeutics.

With estimated sales of $30 billion in 2007, therapeutic antibodies as a class have validated the effectiveness of using highly specific binding properties as therapies.

  Most therapeutic antibodies today are full-length IgG molecules because they are structurally stable, have long 

 half-life and Fc-mediated biological properties. They have a number of drawbacks as therapeutics, however, which include:  

They  have high production costs arising from their expression in mammalian cells.

They are unsuitable for intracellular targets because of their size.

Binding can be variable depending on the protein targeted (best suited to relatively flat target surfaces).

Their size can lead to poor tissue penetration arising from their size, which can limit their effectiveness in cases such as tumor penetration.

The intellectual property landscape around antibody-based therapeutics discovery and development is complex. Prohibitive "royalty stacks" often affect the profitability of a resultant drug.

Antibody fragments, on the other hand, can provide highly specific binding as well as a number of therapeutic advantages including:  

flexibility in structure: a diverse range of binding structures can be assembled from antibody-binding domains giving bispecific or greater binding possibilities per molecule

enhanced penetration of tissues (particularly of solid tumors) because of their smaller size 

elimination of immunogenicity to the Fc region (fragment structures can be designed without an Fc region)

simpler production systems. Fragment antibody production is possible with microbial systems such as 

 and yeasts, translating into lower cost-of-goods (CoGs) and wider application of the benefits of such therapeutic molecules.

The therapeutic effectiveness of antibody fragments has been demonstrated by the licensure of the first antibody fragments. Genentech's Lucentis, a fragment of Avastin, was approved by the FDA in 2006 and is used for the treatment of wet age-related macular degeneration.

  In 2008, UCB Pharma's certolizumab pegol (Cimzia), a PEGylated antibody fragment, was approved for the treatment of Crohn's disease in the US.

  Table 1 shows examples of antibody fragment products that have been launched or are in development. This article discusses production strategies available for antibody fragment therapeutics.  

Table 1.  Examples of antibody fragment products on the market or in development 

The term antibody fragments covers a large number of molecular structures derived from full-length antibodies. Some clarification of structural types is useful before discussing production aspects. 

IgGs are the most abundant immunoglobulins in the blood and are commonly used as antibody therapeutics. They have a molecular weight of approximately 160 kDa comprising 12 domains of roughly equal size. They are made up of four separate peptide chains, two identical heavy (H) chain polypeptides and two identical light (L) chain polypeptides (Figure 1). The L and H chains are composed of two and four domains, respectively, with each domain having a similar  β-barrel structure and containing one disulfide bridge. The H and L chains are linked together by a combination of disulfide and non-covalent bonds.

  Each chain contains both variable and constant domains. The variable domains of the H and L chain (VH and VL) contain the variable complementarity-determining regions (CDRs). These regions of extremely variable amino acid sequences are located at the N-terminal part of the antibody molecule. Together, VH and VL form the unique antigen-recognition site. The amino acid sequences of the remaining C-terminal domains are much less variable.  

Figure 1.  An explanatory schematic of whole antibody domain structure 

is the nonantigen-binding part of the antibody molecule. Fc mediates several immunological functions, such as binding to receptors on target cells and triggering effector functions that eliminate the antigen. There are applications where the Fc-mediated effects are not required or are even desirable. The Fc fragment also is the site of glycosylation in IgGs. 

The unique antigen-binding site of an antibody consists of the H and L chain variable domains (VH and VL). Each domain contains four conserved framework regions and three CDR regions, which determine the specificity of the antibody. The VL and VH domains together form a binding site, which binds a specific antigen. 

A wide variety of functional antigen-binding fragments has been constructed from whole antibody domains, some of which are illustrated in Figure 2 (see also reference 5). Selected fragment types are discussed in detail below.  

Fab fragments (fragment antigen binding) are the antigen-binding domains of an antibody molecule, containing two amino acid chains composed of two domains, VH + CH1 and CL + VL. An interchain disulfide bond present at the C terminal of each constant domain links the CL and CH1 domains together, which gives a molecular weight of the heterodimer around 50 kDa.

  Lucentis and Cimzia are both examples of Fab antibody fragments. 

A single-chain Fv fragment (scFv) is the smallest fragment (~30 kDa) that still contains the complete antigen-binding site (VH + VL) of a whole IgG antibody.

  Linker sequences joining the VH and VL domains in a single amino acid chain have been used to overcome the fact that native scFv fragments are unstable and tend to dissociate from one another.  

Antibody Fab and scFv fragments, comprising both VH and VL domains, retain the specific monovalent antigen-binding affinity of the parent IgG while showing improved pharmokinetics for tissue penetration. However, these are not the smallest form of antibody fragments. 

The smallest antibody-derived binding structures are the separate variable domains. Earlier, isolated domains were not of practical interest because of poor solubility and low affinity compared to the parent antibody.

However, discoveries were made later that certain types of organisms, the camelids and cartilaginous fish, possessed high affinity single V-like domains mounted on an Fc equivalent domain structure as part of their immune system.

 The V-like domains (called VhH in camelids and V-NAR in sharks) typically display long surface loops, which allow penetration of cavities of target antigens. They also stabilize isolated VH domains by masking hydrophobic surface patches.

Human V domain variants have been designed using selection from phage libraries and other approaches that have resulted in stable, high binding VL- and VH-derived domains. 

Engineering the monovalent structures (Fab, scFv, V-domain) in multivalent structures can increase functional affinity (avidity). Such multispecific molecules allow direct association of two or more different targets engineered into dimeric, trimeric, or tetrameric conjugates, either chemically of genetically.

Other antibody-derived structures include Genentech's one-armed antibodies and Genmab's Unibody, which omit parts of the IgG structure to give specific therapeutic benefits.

Mammalian cell expression has been used extensively to produce full-length IgGs that have been appropriately glycosylated.  However, for antibody fragments, which lack the Fc region with its N-linked glycans, microbial systems are the most effective production system for the following reasons:

Microbial systems such as E. Coli and yeasts are most effective for producing antibody fragments.

BioPharm International-06-02-2009

Using Metabolic Profiling Technology to Advance Cell Culture Development

Managing Cell Line Instability and Its Impact During Cell Line Development

The Impact of Cell Culture Medium on Cell Line and Process Development Timelines and Strategies

Production Strategies for Antibody Fragment Therapeutics