Engineering Cyborg Pathogens through Intracellular Hydrogelation

Abstract

Synthetic biology primarily focuses on two kinds of cell chassis: living cells and nonliving systems. Living cells are autoreplicating systems that have active metabolism. Nonliving systems, including artificial cells and nanoparticles, are non-replicating systems typically lacking active metabolism. In recent work, Cyborg bacteria that are nonreplicating-but-metabolically active have been engineered through intracellular hydrogelation. Intracellular hydrogelation is conducted by infusing gel monomers and photoactivators into cells, followed by the activation of polymerization of the gel monomers inside the cells. However, the previous work investigated only Escherichia coli cells. Extending the Cyborg-Cell method to pathogenic bacteria could enable the exploitation of their pathogenic properties in biomedical applications. Here, we focus on different strains of Pseudomonas aeruginosa, Staphylococcus aureus, and Klebsiella pneumoniae. To synthesize the Cyborg pathogens, we first reveal the impact of different hydrogel concentrations on the metabolism, replication, and intracellular gelation of Cyborg pathogens. Next, we demonstrate that the Cyborg pathogens are taken up by macrophages in a similar magnitude as wild-type pathogens through confocal microscopy and real-time PCR. Finally, we show that the macrophage that takes up the Cyborg pathogen exhibits a similar phenotypic response to the wild-type pathogen. Our work generalizes the intracellular hydrogelation approach from lab strains of E. coli to bacterial pathogens. The new Cyborg pathogens could be applied in biomedical applications ranging from drug delivery to immunotherapy.

Graphical Abstract:

INTRODUCTION

Synthetic biology primarily uses genetic approaches to reprogram cells that perform computations, respond to environmental cues, and have a new intracellular architecture. This genetic approach offers promising advantages in achieving new synthetic cells for therapeutic applications, bioremediation, and drug delivery. In contrast, reprogramming cells through intracellular material-based approaches has generated considerable enthusiasm for broad biomedical applications. In such approaches, synthetic materials are infused or formed inside living cells to modulate cellular behavior. The material-based approach has led to applications in drug delivery,^1,2 cell transplantation,^3,4 tissue engineering,^5,6 cancer therapy,^7,8 and medical diagnostics and imaging.^9,10 Creating diverse biomaterial-based platforms has provided effective strategies for manipulating cells in vitro and in vivo.^11–16

Along the lines of a material-based approach, we have engineered Cyborg Escherichia coli BL21DE3, Nissle 1917, and MG1655 through intracellular hydrogelation in prior work.¹⁷ Cyborg bacteria are created through cross-linking hydrogel (i.e., poly(ethylene glycol) diacrylate) monomers within bacterial cytosol. These Cyborg bacteria exhibit a nonreplicative behavior while preserving their metabolic activity. Cyborg E. coli maintains vital functions like cellular metabolism, motility, and protein synthesis while being programmable by synthetic genetic circuits. Cyborg E. coli also gains abilities to resist H₂O₂ and specific antibiotics.¹⁷ However, Cyborg E. coli are laboratory strains that lack crucial machinery found in pathogenic bacteria, limiting their ability to interact with human hosts in biomedical applications.

In contrast, natural pathogens, such as Staphylococcus aureus, Klebsiella pneumoniae, and Pseudomonas aeruginosa, have several attractive properties as chassis of Cyborg bacteria. These pathogens possess virulence factors that can enhance therapeutic efficacy through targeted cell invasion, improved persistence, and modulation of host immune responses.^18–20 For instance, they can produce toxins or proteins that allow them to invade host cells more effectively than nonpathogenic E. coli. Additionally, these pathogens can evade the host’s immune system, avoiding detection or neutralization by immune cells.^19,21,22 They can also utilize various nutrients and adapt to different environments.²³ These features are potentially useful for targeted drug delivery systems.²⁴

Here, we engineer Cyborg versions of bacterial pathogenic strains, including P. aeruginosa, S. aureus, and K. pneumoniae, through intracellular hydrogelation. The hydrogel, comprising a poly(ethylene glycol) diacrylate monomer and a photoinitiator, resulted in distinct Cyborg populations with varying hydrogel densities. Flow cytometry analysis revealed that lower hydrogel densities result in a larger population of Cyborg pathogens. Notably, our intracellular hydrogelation protocol successfully produced nonreplicative-but-active Cyborg pathogens, confirmed through metabolic and colony-forming unit (CFU) assays. Furthermore, our investigation into the intracellular fate of Cyborg bacteria within macrophages demonstrated an equivalent uptake as wild-type bacteria. Quantitative assessments of the bacterial number, cytokine, and reactive oxygen production in macrophages infected with Cyborg bacteria revealed distinct responses, emphasizing the potential of these engineered pathogens for various biomedical applications. Our work demonstrates the feasibility and versatility of intracellular hydrogelation in generating hybrid entities from diverse microbial backgrounds.

RESULTS

Cyborg Bacterial Pathogens Are Nonreplicating-but-Metabolically Active.

We first created a Cyborg version of six bacterial pathogenic strains of P. aeruginosa, S. aureus, and K. pneumoniae using our published protocol with minor modifications¹⁷ (Table 1). We infused the bacterial pathogen with a chemically stable and nondegradable synthetic hydrogel characterized by low biological reactivity. The chosen hydrogel chemistry included a poly(ethylene glycol) diacrylate monomer (PEG-DA; Mn700) and 2-hydroxyl-4′-(2-hydroxyethoxy)-2-methylpropiophenone as the photoinitiator. Additionally, we incorporated fluorescein O′O–diacrylate as a fluorescent dye to assess the permeation of the hydrogel components into the bacteria and confirm the success of intracellular hydrogelation (Figure 1A). We selected four distinct hydrogel densities, ranging from 5 to 20% w/v (g/mL) for intracellular hydrogelation. The successful generation of Cyborg pathogens was measured using flow cytometry of fluorescein O′O–diacrylate, which was incorporated into the intracellular hydrogel (Figure 1B). Cyborg pathogens exhibited a green fluorescence intensity of fluorescein diacrylate when compared to wild-type cells (Figure 1B). In addition, lower hydrogel densities at 5 and 10% resulted in a larger population of Cyborg pathogens (Figure 1C,D). Across all six bacterial strains, at optimal gel densities, approximately 60–80% of the total population exhibited positive fluorescein signals (Figure 1D), indicating the successful formation of an intracellular hydrogel.

Table 1.

List of Bacterial Strains

	bacterial strains	Bei catalog number	source
1.	S. aureus MN8	HM-162D	clinical isolate
2.	S. aureus A980101	NR-45982	clinical isolate
3.	P. aeruginosa PA14	NR-50573	clinical isolate
4.	P. aeruginosa EmvKY2	NR-51330	soil isolate
5.	K. pneumoniae MRSN 28880	NR-55541	clinical isolate
6.	K. pneumoniae BIDMC 2A	NR-41916	clinical isolate

Figure 1.

Engineering Cyborg bacterial pathogens using intracellular hydrogelation. (A) Schematic workflow for intracellular hydrogelation. (B) Flow cytometry and fluorescence microscopy analysis depicting the detection of wild-type and Cyborg bacteria pathogens, including S. aureus, P. aeruginosa, and K. pneumoniae. The histogram illustrates the fluorescence signal obtained from two distinct markers: PEGDA–fluorescein Diacrylate, serving as an indicator of intracellular hydrogelation, and reductive chromogenic dye, a marker used to assess metabolic activity. The gray quadrant shows a population of hydrogelated cells that are metabolically active (n = 3 independent experiments). Fluorescence microscopy images of hydrogelated bacteria. The hydrogel was labeled with fluorescein (Methods Section M1) (Scale bar = 10 μm, n = 3 independent experiments). The data provide insights into the successful intracellular hydrogelation of the bacterial cells, thus creating Cyborg pathogens. (C) Representation of the percentage of hydrogelation and hydrogelated metabolically active cells in three distinct bacterial strains: S. aureus, P. aeruginosa, and K. pneumoniae while varying the hydrogelation percentages at 5, 10, 20, and 30%. Each bar within the graph represents the proportion of cells exhibiting intracellular hydrogelation (shown in blue) and the subset of these hydrogelated cells exhibiting metabolic activity (shown in magenta). The data offer insights into how different hydrogelation percentages impact the creation of Cyborg pathogens, allowing for an assessment of the most effective hydrogelation concentration for each strain. t tests were applied to confirm the statistical significance of the observed difference (n = 3 independent experiments). The error bar represents the standard deviation of the mean. (D) Representation of the comparative analysis of the rate of hydrogelation and metabolically active tracker across six distinct bacterial strains. The chart displays the hydrogelated and metabolically active populations at four different hydrogelation percentages: 5, 10, 20, and 30%. The grouped bar chart provides insights into the impact of varying hydrogelation percentages on the parameters within the bacterial population. This visualization aids in identifying the most favorable conditions, with 10% hydrogelation exhibiting the highest values among the examined percentages (n = 3 independent experiments). Error bar = standard deviation.

Next, we assessed the metabolic activity of Cyborg pathogens by staining them with 5-cyno-2,3-ditolyl tetrazolium chloride (CTC), a reductive chromogenic dye widely used to determine the respiratory activity of bacteria.²⁵ The flow cytometry results indicated that lower hydrogel densities (5 and 10%) resulted in a higher population of CTC-positive cells. Conversely, an increase in the hydrogel density led to a reduction in the metabolic activity of Cyborg pathogens (Figure 1D). Specifically, for strains S. aureus MN8 and A980101, CTC-positive cells were halved when the hydrogel density was elevated from 10 to 30%. Similarly, both strains of P. aeruginosa exhibited a decline in metabolically active cells, averaging a drop from 60 to 30% when the hydrogel density was increased from 5 to 30%. This trend, in which a higher hydrogel density decreased the metabolic activity of Cyborg pathogens, was consistently replicated in K. pneumoniae strains (Figure 1D). These findings show that optimal gelation conditions can create Cyborg pathogens with optimal metabolic activities, while not replicating.

We also investigated the nonreplicative ability of the Cyborg pathogens through a CFU assay (Methods 4, Figure 2A). Our intracellular hydrogelation protocol resulted in some bacteria that were not hydrogelated within the Cyborg bacterial population. To isolate the Cyborg population from wild-type bacteria, we used fluorescence-activated cell sorting (FACS) based on the intensity of fluorescein diacrylate (Figure 2B). Prior to FACS, the CFU count of the Cyborg bacterial population was around three log folds lower than that of the nonhydrogelated controls. Following FACS flow cytometry, the CFU count of Cyborg pathogens decreased to a nondetectable level (Figure 2B). The application of FACS flow cytometry successfully purified the Cyborg bacterial population. Despite being nonreplicable, the Cyborg pathogens remained active and intact after sorting. These results confirm the generation of Cyborg pathogens that cannot divide due to intracellular hydrogelation.

Figure 2.

Improving Cyborg pathogen purity via flow cytometry sorting. (A) Schematic workflow for intracellular hydrogelation and purification of the Cyborg pathogen by flow cytometry sorting. (B) CFUs of Cyborg S. aureus, P. aeruginosa, and K. pneumoniae. Flow cytometry-sorted Cyborg S. aureus, P. aeruginosa, and K. pneumoniae cells exhibit nondetectable CFU (below the detection limit) after sorting (black bars). This observation shows the successful elimination of nonhydrogelated and dividing cells within the bacterial Cyborg population (n = 3 independent experiments). Statistical significance was determined using a two-tailed t test with a significance threshold set at p < 0.05.

Cyborg Pathogens Were Taken Up by Macrophages.

Bacterial pathogens often encounter macrophages in vivo and are taken up or engulfed in the process. Macrophage–pathogen interactions necessitate specific molecular recognition and signaling events. Bacterial pathogens must possess pathogen-associated molecular patterns (PAMPs) that can be recognized by pattern recognition receptors (PRRs) on macrophage surfaces, triggering phagocytosis.²⁶ This process, crucial for engulfing and internalizing pathogens, relies on the pathogens being viable or “alive” to elicit a response from macrophages. Leveraging this understanding of the macrophage–bacteria interaction, we investigated the intracellular fate of Cyborg pathogens within macrophages. We first conducted the classical gentamicin protection assay using RAW 264.7 macrophages at multiplicities of infection (MOI) 1:50, for wild-type bacteria S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC 2A to investigate the ability of these pathogens to invade the macrophages (Figure 3A). CFU data showed that around 0.96 ± 0.14, 0.86 ± 0.07, and 0.41 ± 0.21% of live S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC 2A were successfully taken up by the macrophages (Figure 3B). Notably, E. coli BL21, which is an extracellular bacterium, did not show detectable CFUs, suggesting a lack of invasion or survival inside the macrophage (Figure 3B). Furthermore, confocal microscopy images (Figure 3C–E) demonstrated equal colocalization of both Cyborg and wild-type pathogens (depicted in green) within macrophages (red actin staining). Therefore, the intracellular hydrogelation had negligible effects on Cyborg bacterial uptake by macrophages.

Figure 3.

Visualization of bacterial uptake and intracellular localization in macrophage. (A) Schematic demonstration of the invasion assay. Macrophages (RAW 264.7) were infected with wild-type bacterial strains, including S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC 2A at an MOI of 50. Postinfection, gentamycin treatment was applied to eliminate extracellular bacteria. After gentamycin treatment, the infected cells underwent three rounds of thorough washing to remove the remaining extracellular bacteria. Subsequently, cell lysis was achieved using 0.5 mL of 0.1% Triton-X in PBS, followed by enumeration of the CFU. This assay quantifies surviving intracellular bacteria, corroborating their ability to persist within macrophages after uptake. (B) CFUs of wild-type S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC 2A were determined. The gentamicin protection assay was conducted on wild-type S. aureus, K. pneumoniae, and P. aeruginosa in the RAW 264.7 macrophage cell lines. This assay indicated the successful invasion of wild-type pathogens inside the macrophage cells. The experiment was performed with three biological replicates (n = 3). (C–E) Representative confocal images of bacterial uptake by macrophages. Wild-type S. aureus, P. aeruginosa, and K. pneumoniae were stained with the SYTO-24 dye. Cyborg bacteria were labeled by PEGDA-fluorescein diacrylate. Macrophages were stained with Phalloidin (shown in red) to visualize their actin structure. White arrows indicate the bacteria. Orange arrows highlight the colocalization of S. aureus (C), P. aeruginosa (D), and K. pneumoniae (E) with macrophage actin. Confocal imaging was performed on two biological replicates (n = 2), with three technical replicates each. Five images were acquired for each replicate (scale bar = 20 μm).

To better compare the uptake efficacy of Cyborg pathogens, we could not use the standard CFU assay due to their nonreplicative nature. Hence, we established a qPCR-based approach to measure the number of Cyborg pathogens (S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC 2A) inside macrophages. We first established correlation curves between optical density (OD@600 nm), colony-forming units per milliliter (CFU/mL), and DNA concentration (ng/μL). An OD of 0.1 at 600 nm corresponded to 2.65 (±1.5) × 10⁷ CFU/mL for S. aureus MN8, 6.45 (±1.5) × 10⁷ CFU/mL for P. aeruginosa PA14, and 7.41 (±1.5) × 10⁷ CFU/mL for K. pneumoniae BIDMC 2A. DNA concentrations at an OD600 of 0.1 were determined as 9.54 ng/μL (S. aureus MN8), 8.87 ng/μL (P. aeruginosa PA14), and 9.76 ng/μL (K. pneumoniae BIDMC). Subsequent 10-fold dilutions of bacterial DNA were used to construct standard curves for amplifying the 16s RNA gene. Melt-curve analysis consistently showed a melting temperature T_m of 84.5 °C for S. aureus MN8 (Figure 4A), 84 °C for P. aeruginosa PA14 (Figure 4B), and 87 °C for K. pneumoniae BIDMC 2A (Figure 4C), confirming single-product amplification. The resulting standard curves for Ct values against the DNA concentration exhibited high linearity (R² > 0.99) for all three bacteria, with PCR efficiency close to 100% (Figure 4D–F).

Figure 4.

Quantitative analysis of DNA amplification and bacterial uptake. (A–C) Melt-curve peaks are shown for DNA extracted from S. aureus, P. aeruginosa, and K. pneumoniae. (D–F) Linear standard curves of Ct (qPCR cycle threshold) against the log DNA concentration. R² values exceed 0.99 for S. aureus, P. aeruginosa, and K. pneumoniae. (G) Uptake of wild-type and Cyborg bacteria by macrophages was measured by the qPCR of extracted bacterial DNA, followed by conversion to CFUs using the standard curves.

After establishing the measurement protocol, we investigated the uptake of Cyborg bacteria into the macrophages. A minor but insignificant difference was observed in the intramacrophage count of wild-type and Cyborg P. aeruginosa PA14 (Figure 4G). Similar to PA, no major difference was observed in the intramacrophage count of wild-type and Cyborg S. aureus MN8 and K. pneumoniae BIDMC 2A (Figure 4G). These results indicate that intracellular hydrogelation did not affect the invasion or uptake of these bacterial pathogens by the macrophage.

Cyborg Bacterial Pathogens Caused the Production of Proinflammatory Cytokines and Reactive Oxygen Species in Macrophages.

Previous studies have established that macrophages infected with S. aureus, P. aeruginosa, and K. pneumoniae secrete proinflammatory cytokines as part of their response to control infections.^27–30 Here, we sought to determine whether Cyborg pathogens induce similar levels of cytokine production compared with their wild-type counterparts. The production of proinflammatory cytokines, specifically TNF-α, IL-17, and IFN-γ, was evaluated in murine macrophage cell lines (RAW264.7) infected with both wild-type and Cyborg versions of all three pathogenic strains using the ELISA (Figure 5D–F). Upon treating RAW 264.7 cells with P. aeruginosa PA14 (MOI 1:50) for 4 h, Cyborg bacterial infection resulted in a significant 1.8-fold higher TNF-α secretion compared to wild-type PA14-infected cells (Figure 5D). Conversely, both wild-type and Cyborg PA14-infected macrophages exhibited similar IL-17 levels (Figure 5E). Similarly, no significant difference in the IFN-γ level was observed in macrophages infected with Cyborg PA14 compared to those infected with wild-type PA14 (Figure 5F). Cyborg S. aureus MN8 also induced higher levels of TNF-α than their wild-type counterparts (Figure 5D). IL-17 and IFN-γ levels were similar in both Cyborg and wild-type SA-infected macrophages (Figure 5E,F). For K. pneumoniae, Cyborg bacteria-induced nearly double the level of TNF-α compared to the wild-type, indicating a heightened immune response (Figure 5D). However, no significant differences were observed in IL-17 and IFN-γ levels between Cyborg and wild-type-infected macrophages (Figure 5E,F). These findings underscore the distinctive cytokine profiles induced by Cyborg pathogens compared to those of their wild-type counterparts across different bacterial strains. The heightened TNF-α production by Cyborg pathogen-infected macrophages, despite similar IL-17 and IFN-γ levels to those of wild-type-infected macrophages, may result from selective activation of TNF-α-related pathways or unique interactions between Cyborg pathogens and macrophages.

Figure 5.

Inflammatory response of macrophages against Cyborg and wild-type pathogens. Macrophages (RAW 264.7) were subjected to infection with wild-type and Cyborg bacterial strains, encompassing S. aureus, K. pneumoniae, and P. aeruginosa, at an MOI of 50 for 4 h. Postinfection, supernatants were collected, and the levels of proinflammatory cytokines, including TNF-α, IL-17, and IFN-γ, were quantified using the ELISA, following the manufacturer’s instructions. (A–C) Standard curves for TNF-α, IL-17, and IFN-γ were developed as per manufacturer’s instructions. The standard curve was developed in biological replicates (n = 2). (D–F) TNF-α, IL-17, and IFN-γ from macrophages infected with S. aureus, P. aeruginosa, and K. pneumoniae. Assessed via the ELISA as per the manufacturer’s instruction. The assay was conducted using two biological replicates and two technical replicates. Error bar = standard deviation. * indicates P < 0.01 for TNF-α, IL-17, and IFN-γ. One sample two-tailed t test was applied.

We also assessed the capacity of both wild-type and Cyborg pathogens to elicit reactive oxygen species (ROS) as part of the immune response by macrophages. Prior research has established that immune cells, particularly macrophages, generate ROS to counter infections caused by pathogenic strains such as P. aeruginosa, S. aureus, and K. pneumoniae.^27,29,31 We evaluated the ROS levels produced by macrophages in response to Cyborg pathogens using 2′,7′-dichlorofluorescein (DCF), which formed a fluorescent compound (2′,7′-dichlorodihydrofluorescein diacetate (H₂DCFDA)) when it was reacted with ROS. The H2DCFDA (green) fluorescence intensity increased from the background level (Figure 6B, uninfected cells) when macrophages were infected with either wild-type or Cyborg pathogens. No statistically significant difference in ROS levels was observed in macrophages infected with Cyborg S. aureus and P. aeruginosa (Figure 6B), relative to their wild-type counterparts. However, macrophages infected with Cyborg K. pneumoniae exhibited a more pronounced release of ROS than that of wild-type bacteria (Figure 6B). These findings underscore the distinct ROS responses elicited by Cyborg pathogens, particularly in the context of K. pneumoniae infection.

Figure 6.

Intracellular level of total ROS in macrophages in response to Cyborg and wild-type pathogens. Total reactive oxygen species (ROS) levels were quantified in macrophages following infection with wild-type and Cyborg bacterial strains (S. aureus, P. aeruginosa, and K. pneumoniae) at an MOI of 50 for 4 h, utilizing the oxidant-sensitive probe H2DCFDA. (A) Histogram of the H2DCFDA (green) fluorescence channel, illustrating the marker gate used to identify cells positive for the H2DCFDA probe compared to stained uninfected cells. (B) Mean fluorescence intensity of the H2DCFDA probe in macrophages infected with wild-type and Cyborg pathogens, including S. aureus, P. aeruginosa, and K. pneumoniae. Unstained uninfected and stained uninfected cells are used as controls. n = 2. Error bars = SEM. Statistical significance was determined using one-way analysis of variance (ANOVA). **** indicates p-value <0.0001.

DISCUSSION

The research successfully extended the intracellular hydrogelation technique from lab-based E. coli strains to pathogenic bacteria, specifically S. aureus, K. pneumoniae, and P. aeruginosa, demonstrating its potential for biomedical applications. Intracellular hydrogelation involves the infusion and polymerization of gel monomers within bacterial cells, creating “Cyborg pathogens” that retain metabolic activity but are nonreplicating. This feature is significant because it allows the pathogens to maintain their invasive capabilities without the risk of proliferation, making them ideal candidates for further development as drug delivery and immunotherapy devices.³²

Flow cytometry analysis revealed significant insights into the generation of Cyborg pathogens from six bacterial strains. We selected a stable and nondegradable hydrogel system based on PEG-DA due to its low biological reactivity, which minimizes unintended cellular interactions. Additionally, lower hydrogel densities were chosen to form a porous scaffold that likely allows the molecular movements necessary for maintaining metabolic activity while preventing cell division. The integration of fluorescein diacrylate within the hydrogel matrix allowed for the quantitative assessment of hydrogelation efficiency, indicated by the fluorescence intensity (Figure 1B). This analysis demonstrated varying degrees of hydrogel incorporation across the strains, with S. aureus strains (MN8 and A980101) and P. aeruginosa strains (PA14 and EmvKY2) showing a notably higher percentage of hydrogelation compared to the K. pneumoniae strains (MRSN 28880 and BIDMC 2A) (Figure 1C). This observation may be due to the presence of capsule polysaccharide,²⁰ potentially reducing the uptake of the hydrogel components.

Moreover, the metabolic activity of these pathogens, as assessed by staining with CTC, a reductive chromogenic dye, varied with the hydrogel density. Lower hydrogel densities (5 and 10%) were more conducive to maintaining higher levels of metabolic activity, particularly in S. aureus and P. aeruginosa strains (Figure 1D). This trend was consistent across all strains, with a marked decrease in metabolic activity observed at higher hydrogel densities (20 and 30%) (Figure 1D). Previous studies with Cyborg E. coli Nissle demonstrated metabolic activity for up to 3 days,¹⁷ and we expect a similar period of activity in the current Cyborg pathogens, although further investigation is needed. These findings highlight the delicate balance between the hydrogel density and the preservation of vital cellular functions, suggesting the potential impact of intracellular hydrogel crowding on cellular metabolism.¹⁷

These engineered pathogens were effectively taken up by macrophages, similar to their wild-type counterparts, suggesting that intracellular hydrogelation does not impede their recognition and uptake by host immune cells (Figure 3C). Importantly, the interaction of Cyborg pathogens with macrophages did not significantly alter the immune response when compared to the response elicited by wild-type pathogens, indicating that the hydrogelated bacteria maintain crucial pathogenic features that are recognized by the host’s immune system. Additionally, the engineered pathogens induced comparable levels of proinflammatory cytokines and reactive oxygen species in macrophages as their wild-type counterparts, reinforcing their potential utility in biomedical applications where controlled immune stimulation is desired (Figures 5 and 6).

Although the Cyborg pathogens are derived from well-characterized bacteria, the specific processes governing the termination of cell division remain unclear. Previous studies propose that cell division is governed by replication activities as well as processes that do not involve replication.^33,34 We speculate that the presence of the hydrogel matrix might inhibit cell division by interfering with DNA replication, physically constraining cell growth, or potentially a combination of both factors. Future investigations could be carried out using cryo-electron microscopy, advanced microscopy techniques, and proteomic studies to understand how proteins interact with the intracellular hydrogel.

Our findings validate the versatility of intracellular hydrogelation for creating nonreplicative, metabolically active pathogens. The results also open new avenues for the development of synthetic bacteria in biomedical applications. The ability to manipulate pathogenic bacteria safely without compromising their native interactions with the host immune system offers a promising strategy for the development of novel therapeutic agents. One practical challenge is the use of FACS for isolating hydrogelated cells, which may restrict large-scale production. Improving the sorting efficiency and scalability will be crucial for extending the system to broader applications. Collectively, our research and the ensuing inquiries lay the groundwork for an emerging field that explores the interaction between intracellular hydrogels and biological molecules. The behavior of Cyborg pathogens within a living organism remains unexplored, raising the opportunity to study their long-term stability and interaction with the host immune system.

METHODS

Bacterial Strains and Cell Culture.

Methicillin-resistant S. aureus MN8 (MRSA HM-162D) and A98010 (MRSA NR-45982), P. aeruginosa EmvKY2 (NR-51330) and PA14 (NR-50573), K. pneumoniae BIDMC 2A (NR-41916) and MRSN 28880 (NR-55541), and E. coli Nissle were procured from BEI resources, managed by ATCC. All bacterial strains were cultured in the sterile LB broth. RAW 264.7 cells, gifted by Prof. Scott Simon of UC Davis, were cultured in 10 cm dishes at 37 °C with 5% CO₂. The medium used, the DMEM supplemented with 10% fetal bovine serum, supported their growth and maintenance.

Intracellular Hydrogelation of Bacterial strains.

The hydrogelation of bacterial strains was conducted in accordance with prior studies with minor modifications.¹⁷ In a concise description, 1 mL of the gelation buffer was prepared by mixing 160 μL of 2-hydroxy-4′-(2-hydroxyethoxy)-2-methylpropiophenone (1% w/v) and 800 μL of PEG700-DA (5% w/v). Concurrently, a 1 mL culture of bacterial strains grown overnight in the LB broth medium was subjected to centrifugation. For 5% hydrogelation, 67.5 μL of the hydrogel buffer was combined with the pellet along with 865 μL of LB media. Likewise, 135 μL for 10%, 270 μL for 20%, and 405 μL for 30% were introduced to the pellet, resulting in a final volume of 1 mL. For fluorescent labeling of the hydrogelated cells, fluorescein O,O′-diacrylate was incorporated into the gelation buffer. Following a 10 min incubation on a rotating rack at 37 °C, the samples were rapidly frozen in supercool methanol at −80 °C for 1–2 min and subsequently transferred for a 10 min incubation at −80 °C. After the freeze cycle, cell thawing was conducted at 30 °C using a dry bath. Cells were then centrifuged at 6.8 g for 5 min, with the supernatant discarded and the cells resuspended in 1 mL of LB media. The cells were subjected to 1600 nm irradiation using a UV oven (UVP Cross-linker, CL3000, USA). Following UV cross-linking, samples underwent centrifugation at 6.8 G for 5 min. The supernatant was discarded, and the resultant hydrogelated cells were collected and subsequently washed with PBS for subsequent analysis.

Flow Cytometry Analysis.

In the flow cytometry analysis for the successful generation of Cyborg bacteria, the hydrogelated bacterial pellet, obtained following the intracellular hydrogelation protocol detailed earlier, underwent a thorough washing with PBS to eliminate extracellular fluorescein. The percentage of the Cyborg bacteria population was determined with a focus on detecting the incorporation of fluorescein O’O–diacrylate within the synthetic hydrogel utilizing the FITC channel. To assess metabolic activity, Cyborg bacteria along with positive (wild-type) and negative controls (killed wild-type bacteria) were stained with CTC, a reductive chromogenic dye. Flow cytometry analysis was performed, and the percentage of Cyborg bacteria exhibiting metabolic activity was observed in the PerCp channel of the CytoFLEX flow cytometry system. This methodology allowed for a comprehensive evaluation of both the successful generation of Cyborg bacteria and their metabolic activity in comparison with relevant controls.

Fluorescence-Activated Cell Sorting and CFU Analysis.

The purification process focused on Cyborg bacteria, targeting the detection of fluorescein O′O-diacrylate integration into the synthetic hydrogel using the FITC fluorescence channel by FACS. The sorting criteria were established by referencing wild-type, nonfluorescent bacteria. Roughly one million cells were sorted based on their fluorescence. Following this, a CFU assay was conducted with the sorted and unsorted groups of one million bacteria each to assess the non-proliferative ability of the Cyborg pathogens.

Intracellular Survival of Cyborg Pathogens in Macrophages.

To determine Cyborg pathogen invasion and survival in RAW 264.7 (macrophages), a gentamicin protection assay was performed as described previously.³⁵ Both of the cells were seeded in the DMEM with 10% FBS. The plates were incubated at 37 °C in 5% CO2 for 24 h in the DMEM without antibiotics. Cells were pulsed with S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC Cyborg pathogens at an MOI of 50 at 37 °C for 45 min and then washed three times with PBS and treated with 100 μg/mL of gentamicin for 1.5 h to kill extracellular bacteria. The infected cells were washed three times to remove any extracellular bacteria. After washing, the cells were lysed with 0.5 mL of 0.1% Triton-X in PBS. Total DNA was extracted using a Qiagen total DNA extraction kit. DNA samples were eluted using 100 μL of the elution buffer. DNA was kept frozen at −20 °C until PCR amplification.

Real-Time qPCR for the Quantification of Cyborg Pathogens.

The wild-type strains of S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC 2A were utilized to establish a correlation between the amplification threshold cycle (Ct) and colony-forming units (CFU/ml). A 12–14 h-old bacterial culture was inoculated in the LB broth for CFU assessment, with its optical density (OD600) adjusted to 0.1 OD. Serial dilutions of 1 mL aliquots were spread-plated for CFU quantification. Concurrently, DNA isolation from a 1 mL aliquot was performed using a Qiagen genomic DNA extraction kit. Thermo Fisher Scientific Nanodrop 2000 was used to assess DNA purity and yield. The purity was gauged via the A260/280 absorbance ratios at 260 and 280 nm. The study established links between OD600, CFU/ml, and DNA concentration (ng/mL).

To construct the standard curve, DNA concentrations were observed from a 0.1 OD600 bacterial culture of each strain. Subsequently, 10-fold dilutions were executed to create standard curves for strain-specific genes. The reaction mixture, utilizing PowerUP SYBR Green Master Mix (Thermo Fisher Scientific), was prepared in a total of 10 μL volume. The mixture included 0.5 μL of each primer (a final concentration of 0.5 μM) and 5.0 μL of PowerUP SYBR Green Master Mix. For every bacterial strain, six serial DNA dilutions were generated from the 0.1 OD600 cultures of all three bacteria, serving as the foundation for the standard graph. Real-time PCR runs were conducted in triplicates, with Ct values graphed against the logarithm of the DNA concentration. This approach facilitated the determination of the standard curve equation, subsequently applicable for all ensuring calculations.

Immunofluorescence Confocal Microscopy.

RAW 264.7 cells (3 × 10⁵ cells) were seeded on coverslips placed in a four-chamber slide and incubated for 24 h in the DMEM with 10% FBS. Cells were infected with Cyborg and wild-type bacteria at an MOI of 50 at 37 °C for 1 h and then washed three times with PBS and treated with 100 μg/mL of gentamicin for 1.5 h to kill extracellular bacteria. The infected cells were again washed to remove extracellular bacteria. After incubating the cells with infected bacteria, cells were washed with PBS and stained with Phalloidin Alexa flour 555.

Estimation of the Cytokine Level.

The quantification of proinflammatory cytokine levels, including TNF-α, IL-17, and IFN-γ, was performed in the supernatants of murine macrophage cell lines (RAW264.7) inoculated with both wild-type and Cyborg variants of three pathogenic strains. Proinflammatory cytokines, TNF-α (TNF-α Mouse ELISA Kit, Catalog No. BMS607; Thermo Fisher Scientific), IFN-γ (IFN -γ Mouse ELISA Kit, Catalog No. BMS606; Thermo Fisher Scientific), and IL-17 (IL-17 Mouse ELISA Kit, Catalog No. BMS6001; Thermo Fisher Scientific), were estimated in the cell culture supernatant following the manufacturer’s protocols for the respective ELISA kits. Optical absorbance was measured at 450 nm using a microplate reader (Tecan, Infinite M1000 PRO), and protein concentrations were calculated by using standard curves provided with the ELISA kits.

Measurement of Reactive Oxygen Species.

Intracellular reactive oxygen species (ROS) were assessed using 5-(and-6)-chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate and acetyl ester (CM-H2DCFDA; Invitrogen). Macrophages were seeded in the DMEM with 10% FBS. The plates were incubated at 37 °C in 5% CO2 in the DMEM without antibiotics. Cells were pulsed with S. aureus MN8, P. aeruginosa PA14, and K. pneumoniae BIDMC wild-type and Cyborg pathogens at an MOI of 50 at 37 °C for 4 h. After infection, cells were washed to remove extracellular bacteria and then incubated with 4 μM CM-H2DCFDA in Hank’s balanced salt solution for 30 min at 37 °C. Following infection, cells were washed with PBS and then trypsinized and subjected to flow cytometer analysis using the CytoFLEX flow cytometry.