Autobioluminescent cellular models are emerging tools for drug discovery that rely on the expression of a synthetic, eukaryotic‐optimized luciferase that does not require an exogenous chemical substrate to produce its resultant output signal. These models can therefore self‐modulate their output signals in response to metabolic activity dynamics and avoid the sample destruction and intermittent data acquisition limitations of traditional fluorescent or chemically stimulated bioluminescent approaches. While promising for reducing drug discovery costs and increasing data acquisition relative to alternative approaches, these models have remained relatively untested for drug discovery applications due to their recent emergence within the field. This chapter presents a history and background of these autobioluminescent cellular models to offer investigators a generalized point of reference for understanding their capabilities and limitations and provides side‐by‐side comparisons between autobioluminescent and traditional, substrate‐requiring toxicology screening platforms for pharmaceutically relevant three‐dimensional and high‐throughput screening applications to introduce investigators to autobioluminescence as a potential new drug discovery toolset.
- high‐throughput screening
- three‐dimensional cell culture
- drug discovery
1. Introduction to autobioluminescence
1.1. A brief overview of autobioluminescence
Autobioluminescence is defined as the ability of a cell to self‐initiate the production of a luminescent signal using only endogenously supplied substrates to perform the enzymatic reactions necessary for signal generation. In this regard, it is separate from traditional bioluminescence in that it is not dependent on the exogenous addition of a chemical substrate to supplement the metabolic cosubstrates that are naturally present within cells expressing an associated luciferase protein. Interestingly, under this definition, there are many examples of autobioluminescence in nature that can be found across a diverse array of organisms such as bacteria, dinoflagellates, fungi, and beetles . However, of these natural autobioluminescent systems, only that of the bacteria (commonly referred to as the
The successfully transitioned bacterial
1.2. History of autobioluminescent cellular model development
Due to its bacterial origin, the
However, despite the initial challenges associated with transitioning the bacterial
Further advances were made to the
These difficulties were later overcome by Xu et al. in 2014, who re‐optimized the system for expression from a single promoter and therefore allowed it to be expressed from a single plasmid . This approach, which substituted viral 2A elements in place of the previously employed IRES elements, allowed the full autobioluminescent DNA cassette to be manipulated as a single gene and significantly increased the signal output level to the point where it could be detected from the low numbers of cells that are commonly used in high throughput screening applications. Using the new expression format, Xu and her colleagues were able to demonstrate the use of autobioluminescent reporters for tracking cellular metabolic dynamics, population sizes, and promoter activation events, finally demonstrating the use of autobioluminescence for the same applications as traditional bioluminescent reporter systems [19, 20].
1.3. Comparison of autobioluminescent, traditional bioluminescent, and fluorescent optical imaging approaches
Unlike alternative bioluminescent and fluorescent reporter systems, which have been widely employed for drug discovery for many years, the autobioluminescent system is relatively new and thus has not been used by as many investigators as have the traditional systems. It is therefore important to briefly define the primary differences between these systems and detail the advantages and disadvantages of each as potential optical imaging targets. Fluorescent systems, with green fluorescent protein (
Bioluminescent reporters, on the other hand, express high signal‐to‐noise ratios due to the near absence of natural bioluminescent production from host tissues and can be sourced from a variety of different organisms with different substrates and output wavelengths to allow for reporter multiplexing within a single system. However, similar to fluorescent reporters, the luciferase proteins can remain active following genetic downregulation or cell death. In addition, the introduction of the activating chemical substrate has the potential to unexpectedly influence the cellular system under study and requires the destruction of the sample to efficiently interact with the genetically expressed luciferase .
Autobioluminescent reporters somewhat bridge these two systems by combining the favorable high signal‐to‐noise ratios of traditional bioluminescent systems and the nondestructive nature of the fluorescent systems. However, while their reliance on only endogenously produced substrates eliminates concerns over phototoxicity or substrate interference, it also reduces their total bioluminescent output levels relative to chemically stimulated systems. In addition, there is currently only a single variant, and thus only a single output signal wavelength, available for use . Therefore, in the absence of a system that overcomes all limitations, investigators must weigh the pros and cons of each approach to determine which is the most appropriate for gathering their required data.
2. The use of autobioluminescent cellular models for high throughput compound screening
2.1. Advantages of autobioluminescent cellular models for high throughput screening
Despite their output limitations relative to chemically stimulated bioluminescent systems, autobioluminescent cellular models are particularly well suited for cytotoxicity assays and tier I drug development screening because of their ability to endogenously synthesize and regenerate the luminogenic substrates and cofactors (FMNH2 and O2) required for light production. This autonomous signal production potential eliminates costly reagents and minimizes the complexity of traditional assays formats, offering a simplified and cost‐effective high throughput approach that reduces hands‐on human interaction and error. In practice, the inherent high signal‐to‐noise ratio of the autobioluminescent signal is able to overcome the relatively reduced total output flux to allow these models to function similarly to their chemically stimulated counterparts [19, 25, 26]. This provides a significant advantage for their use in
While this low background advantage is shared by traditional bioluminescent cellular models, the unstimulated production of light that is unique to the autobioluminescent system provides an additional advantage in that it allows for longitudinal data acquisition without sample destruction. The presence of a continuous output signal that can represent real‐time metabolic activity dynamics offers enhanced temporal resolution for assaying the cytotoxicity of therapeutic compounds in high throughput screening formats and provides for standardization without the need to tailor each assay to the unknown kinetics of novel compounds . The typical chemically stimulated, bioluminescent‐based
2.2. Previously published examples of autobioluminescent cellular models for high throughput screening
Because of the reduction in cost and complexity and increase in data acquisition afforded by continuous imaging, autobioluminescent cellular models are becoming increasingly employed as tools for early stage therapeutic compound cytotoxicity screening. Recently, researchers at the National Institutes of Health performed a competitive evaluation of autobioluminescent and commonly applied ATP content, alamarBlue, CyQUANT, and MTS metabolic activity assays using a multi-time point study approach and reported that the IC50 data of known cytotoxic compounds were consistent across each system . In this comparison, the continuous data output of the autobioluminescent cellular models was specifically investigated by comparing a single sample set against individually prepared sample sets that were sacrificed at each time point, and it was determined that repeated assessment of a single sample correlated well with the individually prepared samples of the alternative assays.
More in‐depth comparisons have also been performed that contrasted the use of autobioluminescent and chemically stimulated bioluminescent reporter systems to assess the pharmacological effects of compounds on human cellular models
2.3. Incorporation of autobioluminescent cellular models into existing drug discovery workflows
Although it has not been the primary focus of any previously published autobioluminescent work, an interesting observation from the existing literature is that autobioluminescent cellular models can often be substituted into existing bioluminescent and fluorescent assay workflows without significant changes to the original assay protocols. This interoperability results from the similarity of the autobioluminescent output signal to those from the chemically simulated bioluminescent systems for which the protocols and existing detection equipment were originally designed. Because in both cases the output signals are light in the visible wavelength, the only major considerations when switching between systems have been the variation in output signal intensity and the necessary imaging parameter adjustments needed to achieve minimum signal detection thresholds. This minimizes the level of hardware optimization required to shift between assay modalities in both
A review of the literature suggests that the primary method for optimizing minimum signal detection thresholds during this transition has been to employ larger numbers of cells to overcome the difference in signal output between chemically stimulated and autobioluminescent systems. In autobioluminescent systems, signal detection has been demonstrated from population sizes down to 20,000 cells/well in a 24‐well plate format, and from as few as 25,000 cells following subcutaneous injection into a mouse model . While these are significantly larger numbers of cells than are required for chemically stimulated bioluminescent systems, the low background associated with bioluminescence has nonetheless been shown to retain sufficient sensitivity for use in whole‐animal imaging experiments [28, 31]. It is important to note, however, that in some cases the use of increased cell numbers is not possible, such as for studies specifically focused on very small numbers of cells, such as early stage colonizing tumors. In these scenarios, the primary optimization employed must focus on adjustment of the imaging parameters, such as the use of longer acquisition times or increased luminescent pixel binning sizes.
3. Correlating the data output of autobioluminescent cellular models to classical assay formats
Since the generation of autobioluminescence relies upon the cell's capability to express the synthetic bacterial luciferase cassette as well as the availability of endogenous metabolites (e.g., O2 and FMNH2) for the synthesis of the required substrates, the autobioluminescent light output of these models correlates very strongly with the overall cellular metabolic activity level. As such, autobioluminescent cellular models represent excellent indicators for cytotoxicity following exposure to a compound of interest. Unlike conventional cytotoxicity assays that often require cellular destruction concurrent with data acquisition, autobioluminescent cellular models continuously self‐modulate their light output in response to metabolic activity dynamics across the full lifetime of the host, thus allowing for the noninvasive visualization of metabolic activity at any time point throughout the entire exposure period. As a result, the nondestructive autobioluminescence assay generates more data similar to that obtained by traditional assays while simultaneously reducing the number of samples and investigator interaction time required per run. As an example of these capabilities, a side‐by‐side comparison between an autobioluminescent HEK293 cell model and the classic 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) cytotoxicity assay was performed over a 96‐hour exposure period. In this evaluation, the autobioluminescent model system demonstrated similar toxicity response data across the full set of compound exposure concentrations, and correlated strongly with the MTT assay (
Furthermore, it was possible to leverage the nondestructive nature of the autobioluminescent HEK293 model to multiplex the real‐time cytotoxicity assay with other downstream assays in order to further elucidate the specific toxicity pathways that were activated. To illustrate this application, following evaluation for metabolic activity by autobioluminescent output, the cells were then immediately assayed to measure intracellular glutathione levels using a GSH‐Glo assay or for the presence of reactive oxygen species using a ROS‐Glo assay. In these evaluations, the GSH‐Glo and ROS‐Glo assays, respectively, identified a reduction in glutathione concentration and an increase in reactive oxygen species level, indicating oxidative stress. However, only the reduction in glutathione concentration was determined to be dose responsive, and correlated with the reduction in autobioluminescent output with an
4. Variability of autobioluminescent responses resulting from system expression in different cellular hosts
4.1. Demonstrated autobioluminescent cellular model systems
Thus far, only four autobioluminescent cellular models have been demonstrated: human kidney cells (HEK293) [10, 18], human liver cells (HepG2), immortalized breast cancer cells (T‐47D) [19, 32], and colorectal cancer cells (HCT116) . The most well documented of these models has been the HEK293 cell line, which underwent validation by the National Institutes of Health as a pharmaceutical screening tool . Less documentation is available for the T‐47D, HepG2, and HCT116 cell lines; however, an analysis of their previous use has indicated that their average autobioluminescent output levels are lower than that of their autobioluminescent HEK293 counterpart , likely due to differences in their basal metabolic activity levels. Nonetheless, the signals from these alternative models have proven to be easily detectable , and their tumorigenic lineage has made them useful beyond the straightforward toxicology/metabolic activity screening applications that have emerged as the primary role for the autobioluminescent HEK293 model.
In particular, the autobioluminescent T‐47D model has found utility as a biomonitor for the detection of endocrine disruptor activity due to its natural proliferative rate increase following estrogenic compound exposure. Since estrogenic compounds are defined by their stimulation of cell reproduction, this model has been harnessed to assay for increases in autobioluminescent output as a function of cellular proliferation to track a compound's ability to function as an endocrine disruptor using automated imaging equipment [19, 32]. In this role, autobioluminescent T‐47D cells were shown to exhibit output signals proportional to their total population size (
4.2. Variability of autobioluminescent responses across differential cellular models
Because the autobioluminescent phenotype is closely related to the metabolic activity level of the host cell expressing the synthetic bacterial luciferase cassette, it is possible that significant variances in signal output potential can exist among available cellular models. This concern is compounded by the nascent state of the technology, which has limited the number of cellular hosts documented in the literature and made it difficult to determine how consistent the reporter signal output strength will be upon expression in previously untested cell lines or tissues. The uncertainty surrounding this variability is concerning given that choosing an appropriate cellular model is particularly crucial in drug discovery applications where the same compound can exert variable toxicological responses in different cell lines or tissue types . Due to the lack of published data on this topic, experiments were performed to compare the autobioluminescent responses of the HEK293, T‐47D, and HepG2 cell lines following exposure to the common chemotherapeutic agent doxorubicin. Due to the nondestructive, continuous nature of these autobioluminescent cellular models, it was possible to track the impact of doxorubicin exposure on metabolic activity dynamics over a 72‐hour exposure period. In this example, a typical sigmoidal dose response was observed from the HEK293 cells at each assay time point with an estimated IC50 value of 2 × 10−8 M (20 nM) at 72‐hour postexposure (Figure 3A). However, doxorubicin treatment at concentrations higher than 5 × 10−7 M (500 nM) reduced autobioluminescent output by more than 95% within 72 hours of treatment. In contrast, both the T‐47D and HepG2 models were less susceptible to doxorubicin than the HEK293 cells, and neither produced a sigmoidal dose response (Figure 3B and C). For these models, autobioluminescence reductions of greater than 95% were only observed by 72 hours following the start of doxorubicin treatment at concentrations ≥ 5 μM, whereas treatment with concentrations lower than 20 nM resulted in less than a 10% reduction in autobioluminescence output. Interestingly, however, doxorubicin treatment at 500 nM and 1 μM induced an increase in autobioluminescent output in both the T‐47D and HepG2 models over the course of the exposure period, with a peak at 48‐hour posttreatment. These differential autobioluminescent responses are hypothesized to be the result of the varying cellular metabolic background activities and differential gene expression patterns exerted by each cell's activated toxicity pathways, thus demonstrating a clear emphasis on the importance of choosing a cellular model with an appropriate metabolic background for each specific application.
5. The use of autobioluminescent cellular models for three‐dimensional cell culture applications
5.1. Common three‐dimensional scaffold materials for
in vitrodrug discovery assays
This transition has provided investigators with a variety of different 3D cell culture scaffold materials to choose from, many of which differ vastly in composition and, therefore, appropriateness to specific culture conditions. Collagen, a ubiquitous, naturally occurring protein polymer, has become frequently used for generalized
Synthetic polymers such as polycaprolactone, a comparatively basic example that is biodegradable and commonly used in medical applications, have also been widely applied toward 3D cell culture . These synthetic 3D culture materials are becoming a popular option for
5.2. The advantages of autobioluminescent systems for cellular screening in three‐dimensional cell culture applications
Both fluorescent and bioluminescent imaging systems are easily employed for interrogating cellular structures and activities in traditional monolayer cultures, but the utility of both is handicapped within 3D cell culture systems [26, 53]. Fluorescent reporters are limited primarily by the materials used in 3D culture systems, most of which display high levels of autofluorescence as the scaffold material responds to the excitation signal, or in some cases, to the presence of ambient light . This effect manifests as strong background noise that can completely eclipse the desired signal and is especially prevalent for collagen or collagen‐coated scaffolds, which display autofluorescence around 420–460 nm . Further compounding the use of fluorescent technologies in 3D culture are the effects of phototoxicity and photobleaching. The repeated bombardment of samples with excitation photon energy has been shown to increase the prevalence of reactive oxygen species, which in turn can damage cellular components and skew assay results to the point where the cells may no longer be representative of their true
Because of these multiple hurdles to using fluorescent reporters in 3D culture systems, bioluminescence has become more prevalent as an imaging system under these conditions [54, 57]. However, traditional chemically stimulated bioluminescent systems are similarly limited by the tendency of the 3D scaffold material to induce heterogeneous substrate distribution. Unlike monolayer cultures, where the activating chemical can be evenly distributed to all cells in a population, the presence of the 3D scaffold material, and the variations in construct size, cell density, and matrix configuration across the scaffold, results in the uneven distribution of the activating chemical and its required cosubstrates . Consequently, cells on the exterior of the scaffold have more efficient access to the activating chemical than those on the interior and therefore can initiate a luminescent signal with altered timing and kinetics. This can lead to ambiguous bioluminescent measurements across the population of cells under study and misrepresentations of the true state of the system .
Unlike these fluorescent and chemically stimulated bioluminescent systems, autobioluminescent cellular models produce their luminescent signals independent of any external stimulation, and therefore are not subject to limitations imposed by activating chemical diffusion dynamics, excitatory photon penetration, or phototoxicity and photobleaching. As a result, every cell in the population is continuously producing an autobioluminescent signal representative of its current metabolic activity level. Therefore, even if an asymmetric autobioluminescent signal is measured from a 3D construct, that distribution itself is of significant value to the investigator because it is an objective report on a cell's state at any given position in the construct. The primary physical limitation to the use of autobioluminescent cellular models within 3D culture conditions is the physical absorption and dispersion of the autobioluminescent signal as it interacts with the structural material. As with the alternative systems, this can be mediated through the selection of amenable scaffolding material or by increasing signal acquisition times in order to obtain increased photon counts, although it cannot be completely eliminated as it is a fundamental limitation of the use of 3D structures within the culture system itself.
5.3. Using autobioluminescent cellular models to elucidate metabolic activity and drug responsiveness in monolayer and three‐dimensional culture systems
The choice between a traditional monolayer and a 3D cell culture platform can strongly influence the basal metabolic activity of the cells under study. In monolayer formats, the metabolic state of the cells is constantly in flux as they are continuously passaged until senescence. In contrast, cells seeded into a natural or synthetic 3D scaffold may proliferate initially but, over time, their growth rate will slow and they will enter a stabilized metabolic equilibrium [42, 59]. This growth format is more representative of the cells’ natural state, as their proliferation rates, morphology, and gene expression more closely resemble their
Given the contrasting metabolic conditions between monolayer and 3D cell culture systems, autobioluminescent cellular models are uniquely positioned to assess cellular health in ways other imaging modalities cannot. Since autobioluminescent cells produce light as a function of their individual metabolic state without a dependence on externally supplied activating chemicals or excitatory photon stimulation, cross‐platform comparisons can be performed with limited uncontrollable variability and using sample preparation scales that are logistically tractable. Indeed, an investigation of these contrasts using autobioluminescent HEK293 cells seeded onto polycaprolactone 3D culture scaffolds demonstrated a higher proliferation rate and basal metabolic activity level than when an identical number of cells was seeded and grown in monolayers on polystyrene plates or in suspension culture . Similarly, when a range of cellular concentrations were either plated in monolayers or encapsulated in collagen hydrogels and examined for autobioluminescence, only the output signals from the collagen‐encapsulated 3D cultures remained tightly correlated with the initial cell density measurements after 48 hours of incubation. This suggests that, compared to traditional monolayer culture approaches, collagen‐encapsulated 3D culture allows for longer term measurements of a wide range of cell population sizes.
Further interrogation indicated that the differences in basal metabolic levels induced by scaffold composition were significant enough to influence how the cells responded to xenobiotic challenges [42, 65], demonstrating that these emerging methods of 3D culture and adequate tools for evaluating cellular health are essential to modern drug discovery models. These results were not limited to only a single cell type, as breast, pancreatic and colon cancer cellular models all showed alterations to their proliferation and metabolic rates in the presence of stiffer 3D matrices, and were consequently found to be less sensitive to paclitaxel and gemcitabine treatment . This was corroborated through a direct interrogation of collagen‐encapsulated autobioluminescent HEK293 cells, which were observed to be more resistant to treatment with a metabolic inhibitor relative to their monolayer‐grown counterparts. Together, these examples demonstrate how
5.4. The use of autobioluminescent cellular models for continuous cellular tracking within three‐dimensional culture scaffolds
Unlike fluorescent and chemically stimulated bioluminescent cellular models that require repeated, invasive stimulatory inputs to activate their output signals, autobioluminescent cellular models are amenable to continuous monitoring and dynamic metabolic activity tracking because their autobioluminescent output signals are continuously active. The on‐demand availability and noninvasive nature of this output therefore makes these models highly amenable to repeated or continuous monitoring approaches that are not feasible with the traditional systems due to logistical or economical concerns. This offers significant utility for tumor xenograft tracking, which has traditionally relied upon repeated activating chemical injections, photonic stimulations, or physical measurements to track tumor volume, all of which are invasive and subject to large read‐to‐read variation [66, 67]. Autobioluminescent cellular models, in contrast, allow for low variation, high‐resolution cellular tracking and viability monitoring.
As a demonstration of their utility for continuous monitoring, autobioluminescent HEK293 models have been grown on 3D polycaprolactone scaffolds and measured continuously for 24 hours via repeated light output measurements taken at 15‐minute intervals using an automated system. Similarly, using magnetic‐based 3D culture approaches, these same models have been monitored repeatedly for experiments lasting up to 45 days without the need to sacrifice samples or concerns related to sample‐to‐sample variability . When employed in more complex
6. Advantages of autobioluminescent cellular models for assaying the metabolic effects of nontraditional stressors
The autobioluminescent system's ability to initiate and self‐modulate its signal generation without cellular destruction or exogenous substrate input gives it the ability to function fully intracellularly, which is significantly different than the majority of
In the course of this study, the autobioluminescent cellular system was compared to two other bioluminescence assays, the ATP‐dependent CellTiter‐Glo metabolic activity assay and the ROS‐Glo hydrogen peroxide‐dependent reactive oxygen species assay, in order to determine the most reliable method for assessing
Using the autobioluminescent cellular model, the investigators were able to determine the minimum bacterial population threshold required to induce reductions in host cell metabolic activity to between 5 × 105 and 1 × 106 colony forming units. Additionally, the authors were able to leverage the nondestructive nature of the autobioluminescent cellular model to monitor the ability of the host cells to recover from
7. Expression of autobioluminescence using alternative host systems
Although not directly relevant to drug discovery, it is nonetheless important to note the significantly larger body of autobioluminescent work that has been performed in nonhuman model systems. Because the autobioluminescent gene cassette used for this work is the same as the one used for human cellular expression, only with alternative supporting genetic elements and codon optimization, it is highly likely that the techniques developed in these alternative models will eventually make their way into the autobioluminescent human cellular models as well. Based on historical development patterns, it is likely that the most impending modification to be constructed will be a chemically activated promoter system for compound‐specific activation of autobioluminescent output. This approach has been used in both bacterial and yeast‐based autobioluminescent models to assess transcriptional activity from reporter system‐fused promoters , to monitor autobioluminescently tagged populations in the environment , and to detect environmental pollutants for bioremediation [71, 72].
The classical examples of this system are the
Although autobioluminescent cellular models are a new technology, they have emerged as promising tools for drug discovery. Their ability to reduce the number of required sample preparation steps and reagent requirements for existing assay formats positions them well to lower assay costs, while their high signal‐to‐noise ratios can allow them to fill the nondestructive imaging gaps left by fluorescent systems with complicating levels of background autofluorescence. Similarly, their natural compatibility to work within complex 3D culture systems should, at least in the near term, make them robust against the upcoming shift toward this growth system for early stage compound evaluation. However, their ultimate utility as drug discovery tools will rely on their adoption by the investigators routinely performing these assays. Without widespread use, and therefore sufficient validation within the field, it will be difficult for these models to take hold regardless of the advantages they offer.
The authors acknowledge research funding provided by the U.S. National Institutes of Health under award numbers NIGMS‐1R43GM112241‐01A1, NIGMS‐1R41GM116622‐01, NIEHS‐1R43ES026269‐01, and NIEHS‐2R44ES022567‐02, the U.S. National Science Foundation under award number CBET‐1530953, and the Oak Ridge National Laboratory Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.