Measuring Growth and Gene Expression Dynamics of Tumor-Targeted S. Typhimurium Bacteria

Summary

The goal of these experiments is to generate quantitative time-course data on the growth and gene expression dynamics of attenuated S. typhimurium bacterial colonies growing inside tumors. This video covers tumor cell preparation and implantation, bacteria preparation and injection, whole-animal luminescence imaging, tumor excision, and bacterial colony counting.

Abstract

The goal of these experiments is to generate quantitative time-course data on the growth and gene expression dynamics of attenuated S. typhimurium bacterial colonies growing inside tumors.

We generated model xenograft tumors in mice by subcutaneous injection of a human ovarian cancer cell line, OVCAR-8 (NCI DCTD Tumor Repository, Frederick, MD).

We transformed attenuated strains of S. typhimurium bacteria (ELH430:SL1344 phoPQ- ¹) with a constitutively expressed luciferase (luxCDABE) plasmid for visualization². These strains specifically colonize tumors while remaining essentially non-virulent to the mouse¹.

Once measurable tumors were established, bacteria were injected intravenously via the tail vein with varying dosage. Tumor-localized, bacterial gene expression was monitored in real time over the course of 60 hours using an in vivo imaging system (IVIS). At each time point, tumors were excised, homogenized, and plated to quantitate bacterial colonies for correlation with gene expression data.

Together, this data yields a quantitative measure of the in vivo growth and gene expression dynamics of bacteria growing inside tumors.

Introduction

Synthetic biology has progressed rapidly over the last decade and is now positioned to impact important problems in energy and health. However, expansion into the clinical arena has been slowed by safety concerns and an absence of developing design criteria for in vivo genetic circuits. Accelerating high impact medical applications will require utilizing methods that interface directly with medical infrastructure, genetic circuits that function outside of the controlled lab setting, and safe and clinically-accepted microbial hosts.

A number of strains have been investigated for cancer therapy due to their ability to grow preferentially in tumors. These have included C. novyi, E. coli, V. cholorae, B. longum, and S. typhimurium^3-8. S. typhimurium has generated particular interest as they have exhibited safety and tolerance in a number of human clinical trials^9-12. These bacteria were initially shown to create anti-tumor effects through stimulation of the host immune system and by depletion of nutrients required for cancer cell metabolism. Production of therapeutic cargo was later added through genetic modifications. While these studies represent important advances in the use of bacteria for tumor therapies, the majority of existing efforts have relied on high-level expression that typically results in the delivery of high dosages, off-target effects, and development of host resistance^13-16.

Now, synthetic biology may add programmable cargo production by utilizing computationally-designed genetic circuits that can perform advanced sensing and delivery^17-20. These circuits can be designed to act as delivery systems that sense tumor-specific stimuli and self-regulate cargo production as necessary. However, studying the function of these circuits in vivo has thus far been challenging.

Since plasmids are the common framework for synthetic circuits, we describe a method to characterize the dynamics of plasmid-based gene expression in vivo using a mouse model. These methods utilize time-lapse luminescence imaging and quantitative measurement of biodistribution. Together, these approaches provide a framework for studying plasmid-based networks in vivo for clinical applications.

Protocol

1. Cell Preparation

1. Passage cell lines using standard cell culture techniques. In this experiment, we used OVCAR-8 cells (NCI DCTD Tumor Repository, Frederick, MD). Grow cells to a target confluency of 80 - 100%.
2. Incubate cells with 5 ml trypsin for 5 min, then add 5 ml RPMI medium + FBS to inactivate trypsin.
3. Harvest and count cells on a hemocytometer. Resuspend in phenol red-free DMEM at a target concentration of 5 x 10⁷ cells/ml, or about 200 μl per flask.
4. Add 15% reduced growth factor Matrigel (BD Biosciences) and keep the cell suspension on ice until implantation.

2. Tumor Implantation

1. Anesthetize 4 week old female Ncr/Nu mice using 3% isoflurane and wait roughly 5 min to ensure deep anesthesia. Use vet ointment on eyes to prevent dryness while under anesthesia.
2. Load the cells (100 μl per tumor) in a 1 ml syringe and attach a 27 1/2 gauge needle.
3. For each of two bilateral hind flank injection sites, lift the skin gently with forceps to make a tent and inject cells at the base. Take care not to penetrate too deep, producing blood. Use tweezers to gently remove syringe without spatter.
4. Monitor tumor growth daily for 10 - 20 days until a tumor diameter of 2 - 4 mm is reached.

3. Bacteria Preparation

1. Start an overnight culture of bacteria in 3 ml LB media + Ampicillin from an -80 C freezer stock or refrigerated plate. In this experiment, we used S. typhimurium strain ELH430 (SL1344 PhoPQ- aroA-).
2. In the morning, dilute the culture 1:100 into filtered LB and grow to OD600 0.4 - 0.6.
3. Spin down and wash 3 times in phosphate buffered saline (PBS) and resuspend at a final OD600 of 0.1 (about 1 x 10⁷ cells/ml).

4. Bacteria Injection

1. Anesthetize the animal and position on its side with the tail pointing toward your dominant hand. Use vet ointment on eyes to prevent dryness while under anesthesia.
2. Dilate the tail vein using warm water or a heat lamp.
3. Load the bacteria (100 μl per mouse) in a 1 ml syringe and bend the tip just less than 90 degrees.
4. Align the syringe tip with the tail vein, penetrate at a shallow depth (should feel no resistance), and inject bacteria. Observe bloodflow displacement for a successful injection.

5. Mouse Imaging

1. Anesthetize animals in the induction chamber then place each mouse on the imaging platform. Use vet ointment on eyes to prevent dryness while under anesthesia. Maintain precise positioning to ensure quantitative results between time points.
2. Image animals using the IVIS Spectrum imaging system (Caliper Life Sciences). If imaging more than 1 animal, place light barriers between them to prevent cross-illumination. Animals should be imaged first on the ventral side to confirm localization of bacteria.
3. Image animals dorsally using IVIS every 2 hr for the duration of the experiment (36 hours). Generate a time course for a given ROI.

6. Quantifying Bacterial Biodistribution

1. Euthanize animals using CO₂ and place on the back on an absorbent diaper.
2. Turn the animal to expose the two hind flank subcutaneous tumors. Cut the surrounding skin tissue to separate and remove the tumors. Holding the tumor with tweezers, remove the skin using a reversed scissor motion. When the majority of the skin has been separated, fully remove the tumor using tweezers.
3. Place the organs in pre-weighed microcentrifuge tubes. Since the mass of these tubes can vary significantly it is important to pre-weigh them for quantitative results.

7. Quantifying Bacterial Biodistribution

1. For each time point, excise and weigh the tumors.
2. Add 500 μl PBS + 15% glycerol and homogenize using a Tissue-Tearor (BioSpec). Rinse the homogenizer 3 times with ethanol between samples.
3. Generate serial dilutions and plate for bacterial colony counting. To plate multiple dilutions on a single plate use pre-sectioned plates.

Results

Using this protocol, we are able to generate data on the in vivo growth and gene expression dynamics of tumor targeted bacteria. The overall workflow is summarized in Figure 1.

In the first stage, we inject bacteria (green) and image the animal using IVIS to measure gene expression with luminescence (blue) as a reporter.

Then, in the second stage, we excise, homogenize, and plate tumors for colony counts to determine the number of bacteri...

Discussion

Using this procedure, we are able to generate time courses for the growth and gene expression dynamics of bacteria colonizing tumors. While these measurements are routinely performed in vitro in batch culture or microfluidics devices, they are much more difficult to perform in vivo.

There are several modifications that can be applied to these methods. While we used the OVCAR-8 cell line to generate our mouse models, a number of other cell lines may be used equivalently. For ...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
1 ml syringe	BD Biosciences	309602
3/10 cc Insulin Syringe	BD Biosciences	309301
PrecisionGlide Needle	BD Biosciences	301629
RPMI Medium 1640 (1X), liquid, with L-glutamine	Invitrogen	11875-119
Ampicillin	Sigma Aldrich	A0166-5G
LB Agar Broth	Sigma Aldrich	L2897
Luria-Bertani broth	BD Biosciences	244610