TY - JOUR
AU - Hu, Wei-Shou
AB - Abstract The emergence of natural products and industrial microbiology nearly eight decades ago propelled an era of bioprocess innovation. Half a century later, recombinant protein technology spurred the tremendous growth of biologics and added mammalian cells to the forefront of industrial producing cells in terms of the value of products generated. This review highlights the process technology of natural products and protein biologics. Despite the separation in time, there is a remarkable similarity in their progression. As the new generation of therapeutics for gene and cell therapy emerges, its process technology development can take inspiration from that of natural products and biologics. Introduction In the past century, industrial microbiology has brought about tremendous benefits to our society and impacted many sectors of the industry ranging from food, environment, biochemicals to health care. As a scientific discipline, it has cultivated generations of industrial microbiologists that have transformed numerous biological discoveries into valuable products [23]. We trace the rise of modern industrial microbiology to the discovery of penicillin and the golden era of antibiotics that followed. The vibrant period of new natural product discovery coincided with the expansion of research efforts in both academia and industry and established industrial microbiology and biochemical engineering as two key pillars of industrial biotechnology. The emergence of recombinant DNA (rDNA) technology four decades ago opened another era that has impacted our society profoundly. It has brought the pharmaceutical industry from a century of natural products to an era of biologics. Early cloning and production of human proteins were done using Escherichia coli. But it quickly moved on to mammalian cells because many of the proteins, including tissue plasminogen activator (tPA) and Factor VIII, required glycosylation and other post-translational modifications that could not be done in E. coli. Now, the biologics account for over $200 bn per annum of commercial value, surpassing natural products by very high margins. Figure 1 illustrates the timeline of the introduction of a number of representative natural products (antibiotics, statins, anticancer drugs, etc.) and biologics. Over the course of six decades, more than 550 natural products were approved by the US FDA [58]. It is worth noting that it took ten years for penicillin to reach clinical trials after its discovery. It took even longer for Abbott, Merck, Squibb, and Pfizer to get involved in the manufacturing of penicillin [1]. Large efforts to screen for producers of new antibiotics followed. However, the advances of this new class of medicine were not without hiccups. Early antibiotic screening efforts quickly discovered cephalosporins and tetracyclines. By 1950s it was thought that all natural beta-lactam antibiotics that were present in nature had been found. Screening for other biological activities enriched the natural product repertoire. The product pipeline expanded to include enzyme inhibitors such as statins, proteases inhibitors such as darunavir, immunosuppressors like cyclosporine, and anticancer agents like mitomycin. Fig. 1 Open in new tabDownload slide a Timeline of the introduction of various classes of antibiotics and selected examples of other natural products. b Timeline of the introduction of few biologics produced using cell culture processes Compared to the introduction of penicillin, the first generation of biologics, human growth hormone, and insulin were introduced to market rather fast, only eight years after the invention of rDNA technology by Cohen and Boyer in 1973 [20]. The early recombinant cell culture products tPA (1987), EPO (1989) and a hybridoma antibody OKT3 (1986) were approved by the FDA in the second half of the 1980s. However, just like the antibiotics, these initial successes did not quickly balloon to a very large class of products. In 1992, Centoxin, a recombinant IgM antibody against sepsis developed by Centocor, failed to receive FDA approval. The event was taken by some as an obituary for monoclonal antibodies [50]. It was not until the second half of 1990, with the FDA approval of a number of antibody products (including Remicade, Humira, Avastin, and Rituxan), that we began to witness the robust growth of this new segment of medicine (Fig. 1b). Early products of therapeutic proteins, including insulin, tPA, and EPO, were native proteins used to treat patients who did not synthesize the correct form of the protein or did not produce them in a sufficient quantity. The emergence of antibody as a class of therapeutic agent changed drug discovery to a hypothesis-driven and design-based process. The discovery of antibiotics or other small molecule therapeutics relies on screening based on biological or binding activities. With biologics, once a target is identified, an antibody can be raised in animals by immunization and engineered to enhance its binding affinity; it can also be further engineered to become a smaller Fab fragment or a bispecific antibody. The success rate in developing biologics became higher than the screening of natural products. The introduction of recombinant DNA quickly led to led the founding of the first wave of biotech firms including Genentech, Biogen, Genzyme, Amgen, and Cetus. However, rapid growth in biologics came 20 years after the arrival of this transformative technology. The evolvement of antibiotics and cell culture biologics, although separated by five decades display a high degree of similarity. Importantly, the process technologies developed for natural products paved the way for the transformation of laboratory cell culture practices into manufacturing technology. In this article, we will review the parallels between the stories of antibiotics and protein biologics from the perspective of process technology. As new technologies begin to emerge, a look back to history may shed light on the ones coming. Production cells Strain improvement: an enduring effort and continuous enhancement For both natural products and protein biologics, a high producer is key to efficient production and commercial success. However, the way high producing cells are generated for the two classes of products is very different. The microorganisms used for the production of natural products are mostly derived from natural isolates. These isolates produce the product only in minute quantities. Extensive strain improvement involving mutagenesis is used to increase the productivity. A more than 1000-fold increase in titer over the life cycle of a product is not unusual. Over time, new production strains that have higher productivity and preferred growth characteristics continue to be isolated and introduced into the manufacturing process (Fig. 2a). Because of the extensive mutagenesis involved in strain improvement, it is not unusual that a production strain is morphologically and physiologically very different from the original isolate. With new producing strains, the medium composition and the process is adjusted to further increase the overall process performance. Fig. 2 Open in new tabDownload slide a Traditional process for discovery of natural products. b Genomics and pathway mining based natural product discovery. c Traditional cell line development process for recombinant protein manufacturing. d Next-gen cell line development through genome engineering In addition to increasing the product titer, strain improvement programs also aim to eliminate the degradation pathway. Even with extensive mutagenesis of the producing microorganisms, the identity of the product molecule is never in doubt as its structure, purity and any contaminating molecules can be fully characterized. Cell line development: product consistency as the overriding concern For protein biologics, product discovery occurs even before the producing cell line is generated. The protein needed for drug screening is often obtained by transient gene expression without establishing a cell line. After initial product screening, the selected protein molecule is engineered to enhance its product characteristics, for example, to increase its binding affinity and stability, before the gene of interest (GOI) is introduced into the host cell for cell line construction. After the integration of the vector containing the GOI into the host cell genome, an increased selective pressure is imposed to increase the copy number of the GOI in the genome to boost its productivity. After the amplification, the resulting cell population is very heterogeneous. Using a heterogeneous population for manufacturing poses a great risk. Some subpopulations may grow faster, thus changing the population distribution over time; this may alter the product characteristics (e.g., glycosylation pattern) over time. To alleviate such a risk, single cell cloning of the amplified producing cell pool must be performed to establish the cell line used for manufacturing. After that, the productivity, growth characteristics, and cell stability over long-term culture are evaluated, and the producing line population is selected. The selected production cell line is expanded in population, frozen in vials and stored in liquid nitrogen as a master cell bank and subsequent working cell banks. Although follow-up process improvement continues to enhance the productivity, the same cell line is used through the product life cycle. This is in stark contrast with antibiotic production for which a better strain continues to be generated over many years. In general, the identity of a natural product synthesized by different strains, species, or under different process conditions can be readily determined by their chemical structure. Establishing a complete structural identity is not as straightforward for biologics. Many protein products have very small quantities of various variants. For example, in a small fraction of the protein molecules, the amino group of some lysine residues may be chemically modified by glucose [59], or a small fraction of protein molecules may have amino acid misincorporation [40, 84]. The non-uniformity of the protein product is often reflected in the presence of charge and mass variants. The heterogeneity is even more profound in the glycosylation pattern [33]. The glycans on different molecules of a protein product are not structurally uniform. Under different conditions, subtle differences in protein folding status may occur. Nevertheless, these chemical characteristics are important product quality attributes and the level of their non-uniformity must be constrained within a bound. The recovery process of protein biologics inevitably leaves minute amounts of host cell proteins in the product. These must also be controlled within a tolerable range. Changing the process or the cell line is likely to cause changes in the host cell protein composition. To mitigate the risk posed by the heterogeneous nature of protein biologics, once a producing cell line is created, further genetic modification on the cell line requires extensive product characterization and comparability studies, as well as regulatory scrutiny. Therefore, in general, once a cell line is selected and banked, further enhancement of the productivity is largely confined to relatively smaller adjustment of the process and medium, rather than by genetically modifying the cell line as in microbial strain improvement. From random mutagenesis to targeted genetic alteration Mechanism of strain improvement through mutagenesis There have been a number of excellent reviews on strain improvement for natural product biosynthesis [3, 9, 24, 57]. The productivity of a secondary metabolite is affected by many factors, including the synthetic pathways of the product and the precursor(s), the pathway-specific and global regulatory elements, the signaling compounds (e.g., a-factor, gamma-butyrolactone) and their binding elements that trigger the onset of secondary metabolism, the gene(s) that confers the resistance to a producer’s own antibiotic, and the transporter that exports the antibiotic. In the early decades of the antibiotic, strain improvement relied heavily on empiricism. Higher producers were isolated through cycles of mutagenesis and screening (Fig. 2a). When molecular genetic tools became available, mechanisms contributing to the increased productivity were identified. In some cases, genes of the synthetic pathways were amplified. For example, an industrial kanamycin-overproducing derivative of S. kanamyceticus contained tandem amplification of the Kan gene cluster in an unusually large (145-kb) DNA segment [88]. Multiple copies (8–16 copies) of the penicillin biosynthesis gene cluster P. chrysogenum BW1890 resulted in about a 64-fold increase in penicillin production. Through a better understanding of the mechanisms that enhance antibiotic productivity, metabolic engineering of antibiotic biosynthesis began to take hold. Rational approaches to strain improvement With recombinant DNA technology, rational and gene-targeted engineering on the producing strain began to complement traditional mutagenesis (Fig. 2b). Amplification of the gene coding for the bottleneck enzyme expandase/hydroxylase resulted in overproduction of cephalosporin [72]. The rate limiting enzyme identified through a kinetic model, lysine epsilon-aminotransferase, was overexpressed to increase cephamycin production [49]. The supply of malonyl-CoA, the precursor for the production of polyketide, was enhanced by the overexpression of acetyl-CoA carboxylase complex (ACCase) [63, 91], blocking its channeling to competing pathways and eliminating the malonyl-CoA degrading pathways [92]. Overexpression of positive regulatory genes and disruption of negative regulatory genes of the biosynthetic pathways have been effective in increasing the productivity of natural products. Inserting a second copy of the positive regulatory gene tylR under a strong constitutive promoter enhanced the production of tylosin in an industrial strain [76]. Overexpression of the Streptomyces antibiotic regulatory proteins (SARP) using a high-copy-number vector resulted in a 6-fold and 16-fold increase of fredericamycin and mithramycin titers, respectively [15, 48]. Inactivating the transcriptional repressor ptmR1 improved the titer of platensimycin and platencin by 100-fold over the wild-type strain [73]. Other examples include production of spiramycin [28], avermectin [35, 47], lovastatin [39], nystatin [80], and rapamycin [90]. From empiricism to design based cell line development Constructing high producing cells In contrast to the wide range of species comprising the producing microorganisms of secondary metabolites, the producing cell lines of protein biologics are derived from only a few host cell lines, mostly derived from rodents and human. Over three-quarters of therapeutic proteins are produced using Chinese hamster ovary (CHO) cells. The other prominent host cells are derived from mouse myeloma (SP2/0, NS0) and Syrian hamster kidney (BHK) or human kidney (HEK293) cells. For the production of therapeutic proteins, the quality of the protein produced by the cell is of paramount importance. The glycan structure on the protein molecule is affected by the species and the tissue from which the producing cell was isolated. The glycans synthesized by CHO cells are similar to those from a human. Furthermore, generating a high producing cell line from CHO cell a is well established process. CHO cells thus have become the dominant cell line for biotherapeutic protein production. With only a very small number of host cells, more development effort can be devoted to modify or engineer them to expedite cell line development. An efficient protocol for introducing the GOI, a platform medium, and even a platform process can be established for each. To derive a new production cell line, the same platform can be used, thus saving development time [31]. Toward rational cell engineering After gene amplification, only a small fraction of the treated cells are higher producers. Extensive screening is carried out to identify those high producers. Even though the process is now largely automated, there was a strong desire to understand and possibly exploit the mechanisms that lead a cell to become a high producer. Transcriptomic and proteomic analyses were performed to study cells of different productivity and to examine the cultural conditions that give rise to different productivity. The data revealed that the high productivity of a recombinant cell line is a very complex trait and is unlikely to be the result of changing a “master” regulator. This is unlike the global and pathway-specific regulators seen in secondary metabolism that can influence high productivity. The path to a high productivity was linked to colossal alterations in gene expression [67]. To become a high producer, the transcript level of the GOI must be high, the balance of transcripts of different subunits (e.g., the heavy chain and the light chain transcript levels of IgG) must be in the right range, and the capacity of the secretory pathway, protein processing, and energy metabolism must also be elevated [65, 67, 68]. In contrast to the production of natural products, genetic manipulation of producing cells has not had a major boosting effect where metabolic engineering has been applied to increase the productivity. More success has been achieved in the genetic manipulation of the glycosylation pathway. The CHO cells express 2,3-sialyltransferase only, but not 2,6-sialyltransferase that is expressed in humans. Cloning of the latter into CHO cells allowed it to synthesize glycans that are closer to human form [94]. Many IgG products elicit antibody-dependent cellular cytotoxicity (ADCC) [37]. Their activity is strongly affected by the glycan structure at Asn297. If fucose is absent, the IgG elicits a nearly 50-fold higher ADCC activity in vitro [69]. There have been a number of approaches to remove the fucose residue, including knocking out the fucosyl transferase, and disrupting the pathway of fucose synthesis [52, 81, 87]. In other applications, anti-apoptotic genes have been expressed in producing cells to delay the cell death caused by adverse cultural conditions and prolong the production phase to increase the product titer [16, 25, 45]. There has been significant effort to modulate cell metabolism. The accumulation of lactate from glycolysis has long been correlated with productivity. Many have attempted to engineer glucose metabolism; for example, suppressing lactate dehydrogenase alone or in conjunction with other genes [42, 64, 95], channeling pyruvate into the mitochondria [36, 43], and expressing additional transporter to enable the utilization of alternative sugars [85]. However, no report of the implementation of any of those genetic alterations in industrial processes has emerged. Impact of genomics and genome engineering Genomics and natural products In the past decade, genomics has ushered the development of producer cells for both natural products and protein biologics into a new era. The availability and affordability of the high-throughput DNA sequencing have transformed our approach to product discovery and strain development. Analysis of Streptomyces genomes has revealed multiple cryptic secondary metabolite gene clusters which are not expressed in their secondary metabolome under routine fermentation analyses [6, 12, 38]. The expression of these poorly expressed products may be activated by the manipulation of transcriptional regulators [5], mutations in transcription machinery [56], chromatin modification [70, 82], by introducing stress [7, 51], or by expression in a heterologous host [10, 29]. The genome sequence of any economically valuable producing strain or cell line is readily attainable. Targeted genetic alterations are increasingly being pursued to increase the productivity of natural products. Deleting nonessential genes may increase the productivity by directing cellular resources toward product biosynthesis. E. coli and Streptomyces with a minimized genome have been proposed for use as heterologous hosts [44, 77]. Genome editing tools such as CRISPR present promising opportunities for complex genetic changes in the Actinomycetes [19, 34, 78]. Mixing genes from closely related product synthesis pathways from different producers may offer opportunities for producing a multitude of new analogs. One of the earliest demonstrations of this approach led to the discovery of two new antibiotic derivatives, mederrhodin A and dihydrogranatirhodin [32]. Combinatorial biosynthesis approaches have been applied to improve the diversity of natural products [61, 62, 75]. The new approaches for discovery and strain improvement in the post-genomic era are depicted in Fig. 2b. Genomics and cell line development The method of introducing GOI and generating high producing cells for biologics remained largely unchanged for thirty years as shown in Fig. 2c. Depending on the transfection and amplification method used, a hyper-producing cell line has about five to a few hundred copies of the GOI integrated at multiple locations of the cell’s genome. It is not known whether all those copies are actively transcribed, or if some are more active than others. As a comparison, the native antibody producing B cells in our body, through allele inactivation, have only one active copy of the immunoglobulin gene. In principle, a single copy of the GOI should be able to deliver a high productivity. Indeed a production cell line with a single integrated GOI was reported about a decade ago [30] using a mouse myeloma cell (NS0) as the host cell. Since then several reports have appeared that aimed to make CHO cells into hyper-producers using a single copy GOI [74]. It is desirable to ‘swap’ GOI in a hyper-producing cell with another GOI. The hyper-producing cell that has all the machinery necessary for hyper-production may readily become a hyper-producer of the product of the newly “swapped” GOI [93]. With the advances in genome engineering and in RMCE (recombinase mediated cassette exchange), many such efforts are underway (Fig. 2d). The process: fermentation, cell cultivation, and recovery From batch culture to fed-batch operation The progression of process technology for antibiotic production in the second half of the twentieth century has been masterfully summarized by Elander [26]. Similar and unique aspects of the evolvement of process technology between antibiotics and protein biologics are seen. Table 1 summarizes some aspects of the process technology of the two classes of products. Comparison of the processes of the production of antibiotics and protein biologics . Antibiotics . Biologics . Media Complex Serum supplement → chemically defined Sterilization Heat sterilization, continuous operation Membrane filtration, HTST (for microbial inactivation) Mode Batch → Fed-batch Batch → fed-batch/perfusion Cycling time (h) 120–200 200–300 Reactor (m3) 80–250 2–30 Titer (g/L) 0.5 → >40 0.5 → 10 Feeding Continuous feeding of glucose, precursor Stepwise concentrated Morphology Mycelial → pellet (non-newtonian) (newtonian) Suspension OUR (mol/L–h) 50–80 2–6 Recovery Filtration, extraction → whole broth extraction, fewer unit operations Membrane filtration, chromatography Computer Control glucose feeding, mechanical control, data logging Mechanical control, data logging Sensor Physical parameters, pH, DO mass spectrometer (off-gas analysis) Physical parameters, pH, DO Bulk cost ~$300/kg → $20/kg ~$2000/g → $100/g Others: Few manufacturing facilities, process R&D remain operational in USA Manufacturing capacity is stable, expansion of capacity occurs globally Lower technical barrier for manufacturing Nimble manufacturing facility with single-use bioreactors Product quality consistency as a primary concern . Antibiotics . Biologics . Media Complex Serum supplement → chemically defined Sterilization Heat sterilization, continuous operation Membrane filtration, HTST (for microbial inactivation) Mode Batch → Fed-batch Batch → fed-batch/perfusion Cycling time (h) 120–200 200–300 Reactor (m3) 80–250 2–30 Titer (g/L) 0.5 → >40 0.5 → 10 Feeding Continuous feeding of glucose, precursor Stepwise concentrated Morphology Mycelial → pellet (non-newtonian) (newtonian) Suspension OUR (mol/L–h) 50–80 2–6 Recovery Filtration, extraction → whole broth extraction, fewer unit operations Membrane filtration, chromatography Computer Control glucose feeding, mechanical control, data logging Mechanical control, data logging Sensor Physical parameters, pH, DO mass spectrometer (off-gas analysis) Physical parameters, pH, DO Bulk cost ~$300/kg → $20/kg ~$2000/g → $100/g Others: Few manufacturing facilities, process R&D remain operational in USA Manufacturing capacity is stable, expansion of capacity occurs globally Lower technical barrier for manufacturing Nimble manufacturing facility with single-use bioreactors Product quality consistency as a primary concern Open in new tab Comparison of the processes of the production of antibiotics and protein biologics . Antibiotics . Biologics . Media Complex Serum supplement → chemically defined Sterilization Heat sterilization, continuous operation Membrane filtration, HTST (for microbial inactivation) Mode Batch → Fed-batch Batch → fed-batch/perfusion Cycling time (h) 120–200 200–300 Reactor (m3) 80–250 2–30 Titer (g/L) 0.5 → >40 0.5 → 10 Feeding Continuous feeding of glucose, precursor Stepwise concentrated Morphology Mycelial → pellet (non-newtonian) (newtonian) Suspension OUR (mol/L–h) 50–80 2–6 Recovery Filtration, extraction → whole broth extraction, fewer unit operations Membrane filtration, chromatography Computer Control glucose feeding, mechanical control, data logging Mechanical control, data logging Sensor Physical parameters, pH, DO mass spectrometer (off-gas analysis) Physical parameters, pH, DO Bulk cost ~$300/kg → $20/kg ~$2000/g → $100/g Others: Few manufacturing facilities, process R&D remain operational in USA Manufacturing capacity is stable, expansion of capacity occurs globally Lower technical barrier for manufacturing Nimble manufacturing facility with single-use bioreactors Product quality consistency as a primary concern . Antibiotics . Biologics . Media Complex Serum supplement → chemically defined Sterilization Heat sterilization, continuous operation Membrane filtration, HTST (for microbial inactivation) Mode Batch → Fed-batch Batch → fed-batch/perfusion Cycling time (h) 120–200 200–300 Reactor (m3) 80–250 2–30 Titer (g/L) 0.5 → >40 0.5 → 10 Feeding Continuous feeding of glucose, precursor Stepwise concentrated Morphology Mycelial → pellet (non-newtonian) (newtonian) Suspension OUR (mol/L–h) 50–80 2–6 Recovery Filtration, extraction → whole broth extraction, fewer unit operations Membrane filtration, chromatography Computer Control glucose feeding, mechanical control, data logging Mechanical control, data logging Sensor Physical parameters, pH, DO mass spectrometer (off-gas analysis) Physical parameters, pH, DO Bulk cost ~$300/kg → $20/kg ~$2000/g → $100/g Others: Few manufacturing facilities, process R&D remain operational in USA Manufacturing capacity is stable, expansion of capacity occurs globally Lower technical barrier for manufacturing Nimble manufacturing facility with single-use bioreactors Product quality consistency as a primary concern Open in new tab The early production process of antibiotics in the 1950s was a batch operation. The production process soon evolved to fed-batch culture. By the time cell culture biologics started in the 1980s, virtually all antibiotic production was done in fed-batch mode. Batch operations were the norm for biologics production for almost a decade before fed-batch operation became commonly practiced. The fed-batch cultures of the faster-growing bacteria and fungi generally have a short cycling time of about a week, while a cell culture process often lasts 12–14 days. Some cell culture-produced biologics are labile or are produced at low concentrations. Those products, including Factor VIII, Protein C, and β-glucocerebrosidase, were produced in continuous cultures with cell retention that lasts from one to several months. This operation is called perfusion. Few natural products are manufactured in a continuous culture. The fed-batch culture practiced in the production of antibiotics and protein biologics are somewhat different. The fed-batch culture for natural products usually involves intermittent harvesting of 20–40% of total culture broth and refilling with the feed medium (a procedure called “batch-fill and withdraw”). The fed-batch culture for biologics is operated by starting at only 60–75% of total culture volume and filling up to the total volume through the addition of concentrated feed medium later in the cultivation. In the antibiotic fermentation, cells grow to reach a high-density again after the withdraw and fill, whereas in cell culture feeding typically occurs during the late growth stage or even the stationary phase. The cell culture medium is relatively dilute compared to a microbial culture medium. A low nutrient level to maintain an osmolality of around 300 mM is necessary for the growth of mammalian cells. Such low nutrient levels are not sufficient to support a high cell concentration. Thus, in the late stage of cell growth, more concentrated medium is added to allow cells to reach a much higher cell concentration, and to prolong the production phase. Media: complex vs. chemically defined Media for antibiotic manufacturing uses glucose and inexpensive nitrogen sources (eg. ammonium sulfate) and corn steep liquor. Cell culture media are complete with all twenty amino acids and glucose, plus vitamins, nucleotide precursors, some lipids, bulk salts (potassium phosphate, sodium chloride, etc.) and trace elements like selenium and zinc ions. Media containing fetal calf serum were widely used until the epidemic of bovine spongiform encephalopathy in the United Kingdom. In current processes, medium components derived from animals are not used in the manufacturing process of protein biologics. The manufacturing media used today are increasingly chemically defined. In cell culture processes the quality of the product, in terms of glycosylation pattern and the extent of chemical modifications of amino acids, may vary with the process. Using a chemically defined medium allows for an increased controllability of the product quality. Another difference with respect to media is the sterilization. While the large volume of microbial fermentation medium is sterilized by steam injection continuously in a tubular sterilizer, cell culture medium is sterilized using a microfiltration membrane. However, the sterilization membrane filter does not provide a barrier to viruses [18] or small bacterium like Liptospira licerasiae [14]. Some have opted to implement continuous HTST (high temperature short time) pasteurization to reduce the risk of contamination [13, 54, 66] in addition to filtration. Bioreactors: power input and oxygen delivery Compared to antibiotic manufacturing, cell culture bioreactors are smaller in size. Perfusion processes employ even smaller bioreactors because of their high-throughput per reactor volume. However, the most significant difference between microbial and cell culture bioreactors is probably their power consumption and oxygen transfer capacity. The oxygen uptake rate (OUR) in an antibiotic manufacturing reactor is in the range of 50–80 mol/L–h of oxygen, compared to 2–10 mol/L–h in cell culture bioreactors. The power input for mechanical agitation and the oxygen transfer capacity (K L a) required for cell culture processes are small. This has allowed disposable bioreactors to be adopted. The WAVE bioreactorTM, essentially a continuously rocking plastic bag, that appeared over two decades ago is now an industrial fixture [71]. The low power input in cell culture process also allowed a stirred tank bioreactor to be made from plastic and become disposable. This has spurred a trend of using small bioreactors in nimble manufacturing plants as will be discussed later. Process sensors and control The modern manufacturing plants for both microbial and cell culture processes are highly computerized for mechanical control of reactor operation and for data logging. However, with respect to sensors for chemical species, few new ones have been adopted in industrial processes in the past three decades. The primary online sensors are still limited to pH, temperature, and oxygen. A capacitance probe is sometimes used in bioprocessing to measure the viable cell concentration. It is deployed in many cell culture pilot plant settings and has been reported to be used in the fermentation of Streptomcyes clavuligerus [55]. Few notable online sensors used in the microbial processes are the oxygen and carbon dioxide sensors, the quardrupole mass spectrometry for measuring the difference of oxygen content in the gas inlet and outlet. However, use of such sensors in cell culture process is not widespread. Part of the reason is the low oxygen uptake rate in cell culture, thus requiring more effort to implement an accurate measurement. The online measurement of oxygen uptake rate allows for computer-coupled nutrient feeding according to the metabolic activity in penicillin production [53]. The computer controlled glucose feeding sustained the productivity while avoiding the catabolite repression of antibiotic biosynthesis [22]. Extensive research advanced the control of fermentation processes in the 1980s and 1990s. OUR measurement is often a key parameter used in the control. Online OUR measurement-based glucose feeding was used to manipulate glucose metabolism in hybridoma culture [96]. The cost of goods is generally a small fraction of the commercial value of biologic products and, thus, the potential benefit of a more sophisticated process control is often considered to outweigh the cost of implementing and validating the control algorithm in a manufacturing setting. The stepwise manual feeding is still the norm in a biologic manufacturing plant. Morphological features Manipulating cell morphology as a process strategy has been practiced for both natural products and biologics. At the peak of cell growth in an antibiotic fermentation, the dry biomass concentration reaches tens of grams per liter. At high concentrations of mycelial cells, the fluid viscosity is high and oxygen transfer efficiency in the reactor is low. To reduce the power consumption for agitation and enhance oxygen transfer, the mycelial microorganisms were adapted to grow as pellets to give more favorable fluid properties. Cells for biologic production mostly grow in suspension. However, sometimes morphological changes are introduced; instead of growing as singularly suspended cells, they grow as multiple cell aggregates to facilitate their retention in a perfusion bioreactor. In a perfusion culture, a device is used to retain the cells in the reactor while the medium is continuously perfused through the reactor. Cells are grown as aggregates or are attached to beads of 0.1–2 mm diameter to settle down faster in a sedimentation device [46]. These fast settling cell particles can be easily retained while the culture fluid passes through the settling device. The settled cell-concentrated stream is returned to the reactor while the cell-free or low-cell concentration stream is purged. Product recovery The recovery process of antibiotics has traditionally employed filtration to remove mycelia, followed by extraction to isolate and purify the product. As the technology evolved, the number of unit operations has reduced. The extraction is now carried out with whole broth, bypassing the filtration step [8]. Like antibiotics, over the years the number of unit operations involved in the recovery of protein biologics has reduced. The number of reciprocal extraction steps has also decreased. Centrifugation was used to remove mammalian cells, followed by microfiltration to remove small particulates, and ultrafiltration to concentrate the broth. This has been streamlined to a single microfiltration step to remove cells and particulates. The antibiotic industry helped drive the development of the extraction technology and is still stimulating the research on using “green” solvents for extraction. Protein biologics, on the other hand, facilitated the advances of process liquid chromatography and membrane separation. Manufacturing strategy Through the course of technology development, the cost of goods for both antibiotics and protein biologics decreased significantly. For penicillin G, the bulk cost went from ~US$300/kg in the 1950s to ~US$20/kg in 2000s. Over three decades, the cost of producing immunoglobulin G reduced from ~US$2000/g to ~US$200/g, while the titer increased from ~0.5 to ~10 g/L. The increase may not be as dramatic as that of penicillin (from 0.5 to >40 g/L), but the concentration of IgG achieved in culture is now higher than that in the blood or in mouse ascites fluid. In the past two decades, the antibiotic production capacity in the US has steadily declined. Bristol-Myer-Squib closed its antibiotic manufacturing facility in 2004. There are only a few such manufacturing facilities that remain operational in the US. Consequently, we saw a retreat in the process technology development. For biologics, after a period of rapid expansion of production facilities from the late 1990s to 2010s, the manufacturing capacity is largely stable. However, the pressure for a higher economic efficiency is unyielding. Industrial process research and development have become platform operations. Every step involved in bringing a protein molecule to clinics, from cell line construction and medium formulation to cell culture process and product recovery, has a standard platform protocol. The platform protocol may not be the best for every cell line and product, but it does yield a satisfactory overall process outcome. This approach reduces process development time for new products. The pharmaceutical industry adopted high-throughput technology for combinatorial chemistry and for natural product screening in the late 1990s. We see the same trend in biologics process development. The embrace of high-throughput technology accelerated with the drive to implement Quality by Design (QbD) in the mid-2000s [2, 60]. Statistically designed experiments are performed to identify the design space on key quality attributes. The same economic pressure that drove the antibiotic manufacturing capacity to leave the USA is prodding a comparable trend in biologic manufacturing. A manufacturing plant of biologics requires a huge capital investment to construct. At the time of financial commitment for plant construction, the final regulatory approval for a new drug candidate is far from certain. Constructing a new plant is a high-risk investment. To mitigate this significant financial risk, contract manufacturing organizations (CMOs) have sprung up in various parts of the world. Aside from CMOs, the wide application of disposable bioreactors and other auxiliary equipment have generated a large biomanufacturing service sector. The scale of their production has allowed disposable supplies and equipment to present the consistent quality necessary for drug manufacturing. An alternative approach of constructing a manufacturing plant has, thus, emerged. Instead of using large stainless steel bioreactor, plastic disposable bioreactors are used. The plastic materials used in its construction do not allow it to withstand the high temperature of steam sterilization or the high mechanical stress of agitation in large-scale operation. Thus, its maximum size is limited to a couple thousand liters. However, in such a plant, even some downstream processing equipment can be made for single use, making the plant modular and plug-and-play. The cost of plant construction is lower and the time to build a production facility is shorter. This has enabled distributed manufacturing; instead of having a large plant in a centralized location, a number of smaller facilities using single-use bioreactors are located in different regions of the world to take advantage of certain regional advantages including technical and economic strengths [83]. A plant that employs single-use bioreactors is smaller than a conventional manufacturing facility in terms of its total culture volume capacity. To meet the production need, the productivity per reactor volume needs to be enhanced. This has driven the use of membrane-based cell perfusion to increase the cell and product concentrations to levels higher than what is seen in the fed-batch culture. It has also reignited the interest in developing continuous processes to increase the throughput of the bioreactor. With the high antibody concentration achieved in some processes, the clarified culture fluid can be loaded directly into the chromatographic column. In the past few years, the implementation of multi-column semi-continuous operation of adsorption chromatography has become part of the effort to transform biomanufacturing process into continuous operation [83]. The advances in cell separation technology in the past decade employing hollow-fiber membranes have allowed a more stable and longer operation period. It is important to note that membrane technology is not entirely scalable over a large range of volume increases. The flux of the membrane is relatively constant for scaling up. In scaling up, the surface area (i.e., the number of units) of the membrane will have to increase proportionally to the volume of throughput. The adoption of disposable reactors and a nimble production facility set a different trend in biologic production from antibiotic manufacturing. It is worth remembering that the scale of production, in terms of both culture volume and the quantity of goods, is far higher for antibiotics than for biologics. Should the production need to increase to a level that rivals antibiotics, a fixed tank facility may still prevail. Systems Biotechnology and integrated biomanufacturing In the past decade, the alarming prominence of antibiotic resistance in hospital borne diseases has promoted renewed interest in antibiotic research and in the discovery of new antibiotics. For biologics, the continued thriving of traditional protein therapeutics is boosted by antibody drug conjugates and bispecific antibodies. Recent approval of the adeno-associated virus-based gene therapy product Glybera, and the promising outcomes of cell therapy and adaptive immunotherapy, have provided opportunities for a newer generation of therapeutics. Since the arrival of genomics at the turn of twenty-first century, we have witnessed increased use of transcriptomics, proteomics, and metabolomics in bioprocess research and development, for both microbial natural products and cell culture biologics [11, 17, 27, 41, 79, 86]. The adoption of those genome-wide analytical tools in bioprocess research has spurred efforts in taking systems approach for an integrated analysis. In the past decade, we also saw a renewed quest for advancing process analytical technologies (PAT) and for implementing QbD [2, 4]. While the –omic tools and systems analysis are primarily for cellular level understanding, they also provide a genome-wide view of cellular response to process conditions. We foresee the prospect of integrating systems analysis of cellular systems with PAT at the process level. Indeed, multiscale models integrating cellular physiology and bioreactor performance have begun to emerge recently [21, 89]. Both microbial and cell culture bioprocesses will benefit from a holistic systems approach to designing the producing cells and production processes that optimize both productivity and product quality. Concluding remarks Although separated by half a century the evolvement of process technology for antibiotic production and biologics manufacturing bears many similarities. The need for these two classes of medicine stimulated the development of new process technologies from the producing cell to the reactor, cell cultivation, and product recovery. The success of these two process technologies has brought important medicines for society and created an industrial sector that has had a major economic impact. Critical to the success of the bioprocess technology has been the pioneering work of many giants that guided the path of the technological development. Among those pioneers, Arny Demain is certainly one that will always leave his marks through the many seminal publications and the numerous biotechnologists whom he has mentored. One of us (WSH) has had the opportunity to serve in “Arny’s Army”, as his laboratory members proudly call themselves. This article is again a salute from one of its soldiers to the commander. References 1. (1999) Discovery and development of penicillin. http://www.acs.org/content/acs/en/education/whatischemistry/landmarks/flemingpenicillin.html 2. Abu-Absi SF , Yang L, Thompson P, Jiang C, Kandula S, Schilling B, Shukla AA Defining process design space for monoclonal antibody cell culture Biotechnol Bioeng 2010 106 894 905 10.1002/bit.22764 Google Scholar Crossref Search ADS PubMed WorldCat 3. Adrio JL , Demain AL Genetic improvement of processes yielding microbial products FEMS Microbiol Rev 2006 30 187 214 10.1111/j.1574-6976.2005.00009.x Google Scholar Crossref Search ADS PubMed WorldCat 4. Agarabi CD , Chavez BK, Lute SC, Read EK, Rogstad S, Awotwe-Otoo D, Brown MR, Boyne MT 2nd, Brorson KA Exploring the linkage between cell culture process parameters and downstream processing utilizing a plackett-burman design for a model monoclonal antibody Biotechnol Prog 2016 Google Scholar OpenURL Placeholder Text WorldCat 5. Aigle B , Corre C Waking up Streptomyces secondary metabolism by constitutive expression of activators or genetic disruption of repressors Methods Enzymol 2012 517 343 366 10.1016/B978-0-12-404634-4.00017-6 Google Scholar Crossref Search ADS PubMed WorldCat 6. Aigle B , Lautru S, Spiteller D, Dickschat JS, Challis GL, Leblond P, Pernodet JL Genome mining of Streptomyces ambofaciens J Ind Microbiol Biotechnol 2014 41 251 263 10.1007/s10295-013-1379-y Google Scholar Crossref Search ADS PubMed WorldCat 7. Amano SI , Sakurai T, Endo K, Takano H, Beppu T, Furihata K, Sakuda S, Ueda K A cryptic antibiotic triggered by monensin J Antibiot (Tokyo) 2011 64 703 10.1038/ja.2011.69 Google Scholar Crossref Search ADS PubMed WorldCat 8. Anderson EW , Lau EF Commercial extraction of unfiltered fermentation broth in the podbielniak contactor Chem Eng Prog 1955 51 7 Google Scholar OpenURL Placeholder Text WorldCat 9. Baltz RH Strain improvement in actinomycetes in the postgenomic era J Ind Microbiol Biotechnol 2011 38 657 666 10.1007/s10295-010-0934-z Google Scholar Crossref Search ADS PubMed WorldCat 10. Baltz RH Streptomyces and Saccharopolyspora hosts for heterologous expression of secondary metabolite gene clusters J Ind Microbiol Biotechnol 2010 37 759 772 10.1007/s10295-010-0730-9 Google Scholar Crossref Search ADS PubMed WorldCat 11. Carlage T , Hincapie M, Zang L, Lyubarskaya Y, Madden H, Mhatre R, Hancock WS Proteomic profiling of a high-producing Chinese hamster ovary cell culture Anal Chem 2009 81 7357 7362 10.1021/ac900792z Google Scholar Crossref Search ADS PubMed WorldCat 12. Challis GL Exploitation of the Streptomyces coelicolor A3(2) genome sequence for discovery of new natural products and biosynthetic pathways J Ind Microbiol Biotechnol 2014 41 219 232 10.1007/s10295-013-1383-2 Google Scholar Crossref Search ADS PubMed WorldCat 13. Chandra S , Groener A, Feldman F Effectiveness of alternative treatments for reducing potential viral contaminants from plasma-derived products Thromb Res 2002 105 391 400 10.1016/S0049-3848(02)00044-0 Google Scholar Crossref Search ADS PubMed WorldCat 14. Chen J , Bergevin J, Kiss R, Walker G, Battistoni T, Lufburrow P, Lam H, Vinther A Case study: a novel bacterial contamination in cell culture production-leptospira licerasiae PDA J Pharm Sci Technol 2012 66 580 591 10.5731/pdajpst.2012.00892 Google Scholar Crossref Search ADS PubMed WorldCat 15. Chen Y , Wendt-Pienkowski E, Shen B Identification and utility of FdmR1 as a Streptomyces antibiotic regulatory protein activator for fredericamycin production in Streptomyces griseus ATCC 49344 and heterologous hosts J Bacteriol 2008 190 5587 5596 10.1128/JB.00592-08 2519381 Google Scholar Crossref Search ADS PubMed WorldCat 16. Choi SS , Rhee WJ, Kim EJ, Park TH Enhancement of recombinant protein production in Chinese hamster ovary cells through anti-apoptosis engineering using 30Kc6 gene Biotechnol Bioeng 2006 95 459 467 10.1002/bit.21023 Google Scholar Crossref Search ADS PubMed WorldCat 17. Chong WP , Reddy SG, Yusufi FN, Lee DY, Wong NS, Heng CK, Yap MG, Ho YS Metabolomics-driven approach for the improvement of Chinese hamster ovary cell growth: overexpression of malate dehydrogenase II J Biotechnol 2010 147 116 121 10.1016/j.jbiotec.2010.03.018 Google Scholar Crossref Search ADS PubMed WorldCat 18. Cipriano D , Burnham M, Hughes JV Voynov V, Caravella AJ Effectiveness of various processing steps for viral clearance of therapeutic proteins: database analyses of commonly used steps Therapeutic proteins: methods and protocols 2012 Totowa, NJ Humana Press 277 292 Google Scholar Crossref Search ADS Google Preview WorldCat COPAC 19. Cobb RE , Wang Y, Zhao H High-efficiency multiplex genome editing of Streptomyces species using an engineered CRISPR/Cas system ACS Synth Biol 2015 4 723 728 10.1021/sb500351f Google Scholar Crossref Search ADS PubMed WorldCat 20. Cohen SN , Chang AC, Boyer HW, Helling RB Construction of biologically functional bacterial plasmids in vitro Proc Natl Acad Sci USA 1973 70 3240 3244 10.1073/pnas.70.11.3240 427208 Google Scholar Crossref Search ADS PubMed WorldCat 21. Cruz AJG , Silva AS, Araujo MLGC, Giordano RC, Hokka CO Modelling and optimization of the cephalosporin C production bioprocess in a fed-batch bioreactor with invert sugar as substrate Chem Eng Sci 1999 54 3137 3142 10.1016/S0009-2509(98)00364-9 Google Scholar Crossref Search ADS WorldCat 22. Demain AL Carbon source regulation of idiolite biosynthesis in actinomycetes 1989 Boca Raton CRC Press Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 23. Demain AL Importance of microbial natural products and the need to revitalize their discovery J Ind Microbiol Biotechnol 2014 41 185 201 10.1007/s10295-013-1325-z Google Scholar Crossref Search ADS PubMed WorldCat 24. Demain AL , Adrio JL Strain improvement for production of pharmaceuticals and other microbial metabolites by fermentation Progress in drug research Fortschritte der Arzneimittelforschung Progrès des recherches pharmaceutiques 2008 65 89 Google Scholar OpenURL Placeholder Text WorldCat 25. Dorai H , Kyung YS, Ellis D, Kinney C, Lin C, Jan D, Moore G, Betenbaugh MJ Expression of anti-apoptosis genes alters lactate metabolism of Chinese Hamster Ovary cells in culture Biotechnol Bioeng 2009 103 592 608 10.1002/bit.22269 Google Scholar Crossref Search ADS PubMed WorldCat 26. Elander RP Industrial production of beta-lactam antibiotics Appl Microbiol Biotechnol 2003 61 385 392 10.1007/s00253-003-1274-y Google Scholar Crossref Search ADS PubMed WorldCat 27. Gallo G , Renzone G, Alduina R, Stegmann E, Weber T, Lantz AE, Thykaer J, Sangiorgi F, Scaloni A, Puglia AM Differential proteomic analysis reveals novel links between primary metabolism and antibiotic production in Amycolatopsis balhimycina Proteomics 2010 10 1336 1358 10.1002/pmic.200900175 Google Scholar Crossref Search ADS PubMed WorldCat 28. Geistlich M , Losick R, Turner JR, Rao RN Characterization of a novel regulatory gene governing the expression of a polyketide synthase gene in Streptomyces ambofaciens Mol Microbiol 1992 6 2019 2029 10.1111/j.1365-2958.1992.tb01374.x Google Scholar Crossref Search ADS PubMed WorldCat 29. Gomez-Escribano JP , Bibb MJ Streptomyces coelicolor as an expression host for heterologous gene clusters Methods Enzymol 2012 517 279 300 10.1016/B978-0-12-404634-4.00014-0 Google Scholar Crossref Search ADS PubMed WorldCat 30. Hartman TE , Sar N, Genereux K, Barritt DS, He Y, Burky JE, Wesson MC, Tso JY, Tsurushita N, Zhou Wet al. Derivation and characterization of cholesterol-independent non-GS NS0 cell lines for production of recombinant antibodies Biotechnol Bioeng 2007 96 294 306 10.1002/bit.21099 Google Scholar Crossref Search ADS PubMed WorldCat 31. Hauser H Al-Rubeai M Cell line development Animal cell culture 2015 Cham Springer International Publishing 1 25 Google Scholar Crossref Search ADS Google Preview WorldCat COPAC 32. Hopwood DA , Malpartida F, Kieser HM, Ikeda H, Duncan J, Fujii I, Rudd BAM, Floss HG, Omura S Production of hybrid antibiotics by genetic-engineering Nature 1985 314 642 644 10.1038/314642a0 Google Scholar Crossref Search ADS PubMed WorldCat 33. Hossler P , Mulukutla BC, Hu WS Systems analysis of N-glycan processing in mammalian cells PLoS One 2007 2 e713 10.1371/journal.pone.0000713 1933599 Google Scholar Crossref Search ADS PubMed WorldCat 34. Huang H , Zheng G, Jiang W, Hu H, Lu Y One-step high-efficiency CRISPR/Cas9-mediated genome editing in Streptomyces Acta Biochim Biophys Sin (Shanghai) 2015 47 231 243 10.1093/abbs/gmv007 Google Scholar Crossref Search ADS PubMed WorldCat 35. Hwang YS , Kim ES, Biro S, Choi CY Cloning and analysis of a DNA fragment stimulating avermectin production in various Streptomyces avermitilis strains Appl Environ Microbiol 2003 69 1263 1269 10.1128/AEM.69.2.1263-1269.2003 143579 Google Scholar Crossref Search ADS PubMed WorldCat 36. Irani N , Wirth M, van Den Heuvel J, Wagner R Improvement of the primary metabolism of cell cultures by introducing a new cytoplasmic pyruvate carboxylase reaction Biotechnol Bioeng 1999 66 238 246 10.1002/(SICI)1097-0290(1999)66:4<238::AID-BIT5>3.0.CO;2-6 Google Scholar Crossref Search ADS PubMed WorldCat 37. Jefferis R Recombinant antibody therapeutics: the impact of glycosylation on mechanisms of action Trends Pharmacol Sci 2009 30 356 362 10.1016/j.tips.2009.04.007 Google Scholar Crossref Search ADS PubMed WorldCat 38. Ju KS , Gao J, Doroghazi JR, Wang KK, Thibodeaux CJ, Li S, Metzger E, Fudala J, Su J, Zhang JKet al. Discovery of phosphonic acid natural products by mining the genomes of 10,000 actinomycetes Proc Natl Acad Sci USA 2015 112 12175 12180 10.1073/pnas.1500873112 4593130 Google Scholar Crossref Search ADS PubMed WorldCat 39. Kennedy J , Auclair K, Kendrew SG, Park C, Vederas JC, Hutchinson CR Modulation of polyketide synthase activity by accessory proteins during lovastatin biosynthesis Science 1999 284 1368 1372 10.1126/science.284.5418.1368 Google Scholar Crossref Search ADS PubMed WorldCat 40. Khetan A , Huang YM, Dolnikova J, Pederson NE, Wen DY, Yusuf-Makagiansar H, Chen P, Ryll T Control of misincorporation of serine for asparagine during antibody production using CHO cells Biotechnol Bioeng 2010 107 116 123 10.1002/bit.22771 Google Scholar Crossref Search ADS PubMed WorldCat 41. Kim M , Yi JS, Lakshmanan M, Lee DY, Kim BG Transcriptomics-based strain optimization tool for designing secondary metabolite overproducing strains of Streptomyces coelicolor Biotechnol Bioeng 2016 113 651 660 10.1002/bit.25830 Google Scholar Crossref Search ADS PubMed WorldCat 42. Kim SH , Lee GM Down-regulation of lactate dehydrogenase-A by siRNAs for reduced lactic acid formation of Chinese hamster ovary cells producing thrombopoietin Appl Microbiol Biotechnol 2007 74 152 159 10.1007/s00253-006-0654-5 Google Scholar Crossref Search ADS PubMed WorldCat 43. Kim SH , Lee GM Functional expression of human pyruvate carboxylase for reduced lactic acid formation of Chinese hamster ovary cells (DG44) Appl Microbiol Biotechnol 2007 76 659 665 10.1007/s00253-007-1041-6 Google Scholar Crossref Search ADS PubMed WorldCat 44. Komatsu M , Uchiyama T, Omura S, Cane DE, Ikeda H Genome-minimized Streptomyces host for the heterologous expression of secondary metabolism Proc Natl Acad Sci USA 2010 107 2646 2651 10.1073/pnas.0914833107 2823899 Google Scholar Crossref Search ADS PubMed WorldCat 45. Krampe B , Al-Rubeai M Cell death in mammalian cell culture: molecular mechanisms and cell line engineering strategies Cytotechnology 2010 62 175 188 10.1007/s10616-010-9274-0 2932912 Google Scholar Crossref Search ADS PubMed WorldCat 46. Kyung YS , Peshwa MV, Gryte DM, Hu WS High density culture of mammalian cells with dynamic perfusion based on on-line oxygen uptake rate measurements Cytotechnology 1994 14 183 190 10.1007/BF00749615 Google Scholar Crossref Search ADS PubMed WorldCat 47. Lee J , Hwang Y, Kim S, Kim E, Choi C Effect of a global regulatory gene, afsR2, from Streptomyces lividans on avermectin production in Streptomyces avermitilis J Biosci Bioeng 2000 89 606 608 10.1016/S1389-1723(00)80065-1 Google Scholar Crossref Search ADS PubMed WorldCat 48. Lombo F , Brana AF, Mendez C, Salas JA The mithramycin gene cluster of Streptomyces argillaceus contains a positive regulatory gene and two repeated DNA sequences that are located at both ends of the cluster J Bacteriol 1999 181 642 647 93421 Google Scholar Crossref Search ADS PubMed WorldCat 49. Malmberg LH , Hu WS, Sherman DH Effects of enhanced lysine epsilon-aminotransferase activity on cephamycin biosynthesis in Streptomyces clavuligerus Appl Microbiol Biotechnol 1995 44 198 205 10.1007/BF00164502 Google Scholar Crossref Search ADS PubMed WorldCat 50. Marks L The birth pangs of monoclonal antibody therapeutics: the failure and legacy of Centoxin MAbs 2012 4 403 412 10.4161/mabs.19909 3355486 Google Scholar Crossref Search ADS PubMed WorldCat 51. Moore JM , Bradshaw E, Seipke RF, Hutchings MI, McArthur M Use and discovery of chemical elicitors that stimulate biosynthetic gene clusters in Streptomyces bacteria Methods Enzymol 2012 517 367 385 10.1016/B978-0-12-404634-4.00018-8 Google Scholar Crossref Search ADS PubMed WorldCat 52. Mori K , Kuni-Kamochi R, Yamane-Ohnuki N, Wakitani M, Yamano K, Imai H, Kanda Y, Niwa R, Iida S, Uchida Ket al. Engineering Chinese hamster ovary cells to maximize effector function of produced antibodies using FUT8 siRNA Biotechnol Bioeng 2004 88 901 908 10.1002/bit.20326 Google Scholar Crossref Search ADS PubMed WorldCat 53. Mou DG , Cooney CL Growth monitoring and control through computer-aided on-line mass balancing in a fed-batch penicillin fermentation Biotechnol Bioeng 1983 25 225 255 10.1002/bit.260250118 Google Scholar Crossref Search ADS PubMed WorldCat 54. Murphy M , Quesada GM, Chen DY Effectiveness of mouse minute virus inactivation by high temperature short time treatment technology: a statistical assessment Biologicals 2011 39 438 443 10.1016/j.biologicals.2011.07.001 Google Scholar Crossref Search ADS PubMed WorldCat 55. Neves AA , Pereira DA, Vieira LM, Menezes JC Real time monitoring biomass concentration in Streptomyces clavuligerus cultivations with industrial media using a capacitance probe J Biotechnol 2000 84 45 52 10.1016/S0168-1656(00)00325-4 Google Scholar Crossref Search ADS WorldCat 56. Ochi K , Tanaka Y, Tojo S Activating the expression of bacterial cryptic genes by rpoB mutations in RNA polymerase or by rare earth elements J Ind Microbiol Biotechnol 2014 41 403 414 10.1007/s10295-013-1349-4 Google Scholar Crossref Search ADS PubMed WorldCat 57. Parekh S , Vinci VA, Strobel RJ Improvement of microbial strains and fermentation processes Appl Microbiol Biotechnol 2000 Google Scholar OpenURL Placeholder Text WorldCat 58. Patridge E , Gareiss P, Kinch MS, Hoyer D An analysis of FDA-approved drugs: natural products and their derivatives Drug Discov Today 2016 21 204 207 10.1016/j.drudis.2015.01.009 Google Scholar Crossref Search ADS PubMed WorldCat 59. Quan C , Alcala E, Petkovska I, Matthews D, Canova-Davis E, Taticek R, Ma S A study in glycation of a therapeutic recombinant humanized monoclonal antibody: where it is, how it got there, and how it affects charge-based behavior Anal Biochem 2008 373 179 191 10.1016/j.ab.2007.09.027 Google Scholar Crossref Search ADS PubMed WorldCat 60. Rathore AS , Winkle H Quality by design for biopharmaceuticals Nat Biotechnol 2009 27 26 34 10.1038/nbt0109-26 Google Scholar Crossref Search ADS PubMed WorldCat 61. Reeves CD The enzymology of combinatorial biosynthesis Crit Rev Biotechnol 2003 23 95 147 10.1080/713609311 Google Scholar Crossref Search ADS PubMed WorldCat 62. Rix U , Fischer C, Remsing LL, Rohr J Modification of post-PKS tailoring steps through combinatorial biosynthesis Nat Prod Rep 2002 19 542 580 10.1039/b103920m Google Scholar Crossref Search ADS PubMed WorldCat 63. Ryu YG , Butler MJ, Chater KF, Lee KJ Engineering of primary carbohydrate metabolism for increased production of actinorhodin in Streptomyces coelicolor Appl Environ Microbiol 2006 72 7132 7139 10.1128/AEM.01308-06 1636169 Google Scholar Crossref Search ADS PubMed WorldCat 64. Sanfeliu A , Paredes C, Cairo JJ, Godia F Identification of key patterns in the metabolism of hybridoma cells in culture Enzyme Microb Technol 1997 21 421 428 10.1016/S0141-0229(97)00015-X Google Scholar Crossref Search ADS WorldCat 65. Schlatter S , Stansfield SH, Dinnis DM, Racher AJ, Birch JR, James DC On the optimal ratio of heavy to light chain genes for efficient recombinant antibody production by CHO cells Biotechnol Prog 2005 21 122 133 10.1021/bp049780w Google Scholar Crossref Search ADS PubMed WorldCat 66. Schleh M , Romanowski P, Bhebe P, Zhang L, Chinniah S, Lawrence B, Bashiri H, Gaduh A, Rajurs V, Rasmussen Bet al. Susceptibility of mouse minute virus to inactivation by heat in two cell culture media types Biotechnol Prog 2009 25 854 860 10.1002/btpr.181 Google Scholar Crossref Search ADS PubMed WorldCat 67. Seth G , Charaniya S, Wiaschin KF, Hu WS In pursuit of a super producer—alternative paths to high producing recombinant mammalian cells Curr Opin Biotechnol 2007 18 557 564 10.1016/j.copbio.2007.10.012 Google Scholar Crossref Search ADS PubMed WorldCat 68. Seth G , Hossler P, Yee JC, Hu WS Engineering cells for cell culture bioprocessing—physiological fundamentals Adv Biochem Eng Biotechnol 2006 101 119 164 Google Scholar PubMed OpenURL Placeholder Text WorldCat 69. Shields RL , Lai J, Keck R, O’Connell LY, Hong K, Meng YG, Weikert SH, Presta LG Lack of fucose on human IgG1 N-linked oligosaccharide improves binding to human Fcgamma RIII and antibody-dependent cellular toxicity J Biol Chem 2002 277 26733 26740 10.1074/jbc.M202069200 Google Scholar Crossref Search ADS PubMed WorldCat 70. Shwab EK , Bok JW, Tribus M, Galehr J, Graessle S, Keller NP Histone deacetylase activity regulates chemical diversity in Aspergillus Eukaryot Cell 2007 6 1656 1664 10.1128/EC.00186-07 2043372 Google Scholar Crossref Search ADS PubMed WorldCat 71. Singh V Disposable bioreactor for cell culture using wave-induced agitation Cytotechnology 1999 30 149 158 10.1023/A:1008025016272 3449934 Google Scholar Crossref Search ADS PubMed WorldCat 72. Skatrud PL , Tietz AJ, Ingolia TD, Cantwell CA, Fisher DL, Chapman JL, Queener SW Use of recombinant DNA to improve production of cephalosporin C by Cephalosporium acremonium Nat Biotech 1989 7 477 485 10.1038/nbt0589-477 Google Scholar Crossref Search ADS WorldCat 73. Smanski MJ , Peterson RM, Rajski SR, Shen B Engineered Streptomyces platensis strains that overproduce antibiotics platensimycin and platencin Antimicrob Agents Chemother 2009 53 1299 1304 10.1128/AAC.01358-08 2663125 Google Scholar Crossref Search ADS PubMed WorldCat 74. Spencer S , Gugliotta A, Koenitzer J, Hauser H, Wirth D Stability of single copy transgene expression in CHOK1 cells is affected by histone modifications but not by DNA methylation J Biotechnol 2015 195 15 29 10.1016/j.jbiotec.2014.12.009 Google Scholar Crossref Search ADS PubMed WorldCat 75. Staunton J , Wilkinson B Combinatorial biosynthesis of polyketides and nonribosomal peptides Curr Opin Chem Biol 2001 5 159 164 10.1016/S1367-5931(00)00185-X Google Scholar Crossref Search ADS PubMed WorldCat 76. Stratigopoulos G , Bate N, Cundliffe E Positive control of tylosin biosynthesis: pivotal role of TylR Mol Microbiol 2004 54 1326 1334 10.1111/j.1365-2958.2004.04347.x Google Scholar Crossref Search ADS PubMed WorldCat 77. Sung BH , Lee JH, Kim SC Lee SY Escherichia coli genome engineering and minimization for the construction of a bioengine Systems biology and biotechnology of Escherichia coli 2009 Netherlands, City Springer 19 40 Google Scholar Crossref Search ADS Google Preview WorldCat COPAC 78. Tong Y , Charusanti P, Zhang L, Weber T, Lee SY CRISPR-Cas9 based engineering of actinomycetal genomes ACS Synth Biol 2015 4 1020 1029 10.1021/acssynbio.5b00038 Google Scholar Crossref Search ADS PubMed WorldCat 79. Vishwanathan N , Le H, Jacob NM, Tsao YS, Ng SW, Loo B, Liu Z, Kantardjieff A, Hu WS Transcriptome dynamics of transgene amplification in Chinese hamster ovary cells Biotechnol Bioeng 2014 111 518 528 10.1002/bit.25117 Google Scholar Crossref Search ADS PubMed WorldCat 80. Volokhan O , Sletta H, Sekurova ON, Ellingsen TE, Zotchev SB An unexpected role for the putative 4′-phosphopantetheinyl transferase-encoding gene nysF in the regulation of nystatin biosynthesis in Streptomyces noursei ATCC 11455 FEMS Microbiol Lett 2005 249 57 64 10.1016/j.femsle.2005.05.052 Google Scholar Crossref Search ADS PubMed WorldCat 81. von Horsten HH , Ogorek C, Blanchard V, Demmler C, Giese C, Winkler K, Kaup M, Berger M, Jordan I, Sandig V Production of non-fucosylated antibodies by co-expression of heterologous GDP-6-deoxy-D-lyxo-4-hexulose reductase Glycobiology 2010 20 1607 1618 10.1093/glycob/cwq109 Google Scholar Crossref Search ADS PubMed WorldCat 82. Wang X , Sena Filho JG, Hoover AR, King JB, Ellis TK, Powell DR, Cichewicz RH Chemical epigenetics alters the secondary metabolite composition of guttate excreted by an atlantic-forest-soil-derived Penicillium citreonigrum J Nat Prod 2010 73 942 948 10.1021/np100142h 2878378 Google Scholar Crossref Search ADS PubMed WorldCat 83. Warikoo V , Godawat R, Brower K, Jain S, Cummings D, Simons E, Johnson T, Walther J, Yu M, Wright Bet al. Integrated continuous production of recombinant therapeutic proteins Biotechnol Bioeng 2012 109 3018 3029 10.1002/bit.24584 Google Scholar Crossref Search ADS PubMed WorldCat 84. Wen DY , Vecchi MM, Gu S, Su LH, Dolnikova J, Huang YM, Foley SF, Garber E, Pederson N, Meier W Discovery and investigation of misincorporation of serine at asparagine positions in recombinant proteins expressed in chinese hamster ovary cells J Biol Chem 2009 284 32686 32694 10.1074/jbc.M109.059360 2781684 Google Scholar Crossref Search ADS PubMed WorldCat 85. Wilkens CA , Altamirano C, Gerdtzen ZP Comparative metabolic analysis of lactate for CHO cells in glucose and galactose Biotechnol Bioproc E 2011 16 714 724 10.1007/s12257-010-0409-0 Google Scholar Crossref Search ADS WorldCat 86. Wu C , Du C, Gubbens J, Choi YH, van Wezel GP Metabolomics-driven discovery of a prenylated isatin antibiotic produced by Streptomyces species MBT28 J Nat Prod 2015 78 2355 2363 10.1021/acs.jnatprod.5b00276 Google Scholar Crossref Search ADS PubMed WorldCat 87. Yamane-Ohnuki N , Kinoshita S, Inoue-Urakubo M, Kusunoki M, Iida S, Nakano R, Wakitani M, Niwa R, Sakurada M, Uchida Ket al. Establishment of FUT8 knockout Chinese hamster ovary cells: an ideal host cell line for producing completely defucosylated antibodies with enhanced antibody-dependent cellular cytotoxicity Biotechnol Bioeng 2004 87 614 622 10.1002/bit.20151 Google Scholar Crossref Search ADS PubMed WorldCat 88. Yanai K , Murakami T, Bibb M Amplification of the entire kanamycin biosynthetic gene cluster during empirical strain improvement of Streptomyces kanamyceticus Proc Natl Acad Sci USA 2006 103 9661 9666 10.1073/pnas.0603251103 1475798 Google Scholar Crossref Search ADS PubMed WorldCat 89. Yongky A , Lee J, Le T, Mulukutla BC, Daoutidis P, Hu WS Mechanism for multiplicity of steady states with distinct cell concentration in continuous culture of mammalian cells Biotechnol Bioeng 2015 112 1437 1445 10.1002/bit.25566 Google Scholar Crossref Search ADS PubMed WorldCat 90. Yoo YJ , Hwang JY, Shin HL, Cui H, Lee J, Yoon YJ Characterization of negative regulatory genes for the biosynthesis of rapamycin in Streptomyces rapamycinicus and its application for improved production J Ind Microbiol Biotechnol 2015 42 125 135 10.1007/s10295-014-1546-9 Google Scholar Crossref Search ADS PubMed WorldCat 91. Zabala D , Brana AF, Florez AB, Salas JA, Mendez C Engineering precursor metabolite pools for increasing production of antitumor mithramycins in Streptomyces argillaceus Metab Eng 2013 20 187 197 10.1016/j.ymben.2013.10.002 Google Scholar Crossref Search ADS PubMed WorldCat 92. Zha W , Rubin-Pitel SB, Shao Z, Zhao H Improving cellular malonyl-CoA level in Escherichia coli via metabolic engineering Metab Eng 2009 11 192 198 10.1016/j.ymben.2009.01.005 Google Scholar Crossref Search ADS PubMed WorldCat 93. Zhang L , Inniss MC, Han S, Moffat M, Jones H, Zhang B, Cox WL, Rance JR, Young RJ Recombinase-mediated cassette exchange (RMCE) for monoclonal antibody expression in the commercially relevant CHOK1SV cell line Biotechnol Prog 2015 31 1645 1656 10.1002/btpr.2175 Google Scholar Crossref Search ADS PubMed WorldCat 94. Zhang XQ , Lok SHL, Kon OL Stable expression of human alpha-2,6-sialyltransferase in Chinese hamster ovary cells: functional consequences for human erythropoietin expression and bioactivity BBA Gen Subj 1998 1425 441 452 10.1016/S0304-4165(98)00095-6 Google Scholar Crossref Search ADS WorldCat 95. Zhou M , Crawford Y, Ng D, Tung J, Pynn AF, Meier A, Yuk IH, Vijayasankaran N, Leach K, Joly Jet al. Decreasing lactate level and increasing antibody production in Chinese Hamster Ovary cells (CHO) by reducing the expression of lactate dehydrogenase and pyruvate dehydrogenase kinases J Biotechnol 2011 153 27 34 10.1016/j.jbiotec.2011.03.003 Google Scholar Crossref Search ADS PubMed WorldCat 96. Zhou W , Rehm J, Hu WS High viable cell concentration fed-batch cultures of hybridoma cells through on-line nutrient feeding Biotechnol Bioeng 1995 46 579 587 10.1002/bit.260460611 Google Scholar Crossref Search ADS PubMed WorldCat © Society for Industrial Microbiology 2017 This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) © Society for Industrial Microbiology 2017
TI - Advancement in bioprocess technology: parallels between microbial natural products and cell culture biologics
JF - Journal of Industrial Microbiology and Biotechnology
DO - 10.1007/s10295-017-1913-4
DA - 2017-05-01
UR - https://www.deepdyve.com/lp/oxford-university-press/advancement-in-bioprocess-technology-parallels-between-microbial-ge0FtXPbU6
SP - 785
EP - 797
VL - 44
IS - 4-5
DP - DeepDyve
ER -