We thank H. Fleming for critical reading and editing of the manuscript. This work was supported by a Misrock Postdoctoral fellowship (TD) and NDSEG graduate fellowship (AP). SNB is a HHMI Investigator.

1.	Cell Preparation
<ol>
 <li>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%. </li>
 <li>Incubate cells with 5 ml trypsin for 5 min, then add 5 ml RPMI medium + FBS to inactivate trypsin. </li>
 <li>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 &mu;l per flask. </li>
 <l...

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No conflicts of interest declared.

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 ...

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. typhimurium3-8. S. typhimurium has generated particular interest as they have exhibited safety and tolerance in a number of human clinical trials9-12. 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 resistance13-16. 
Now, synthetic biology may add programmable cargo production by utilizing computationally-designed genetic circuits that can perform advanced sensing and delivery17-20. 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.

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

measuring growth and gene expression dynamics of tumor-targeted s. typhimurium bacteria

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.

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...

Watch this Scientific Journal Video about Measuring Growth and Gene Expression Dynamics of Tumor-Targeted S. Typhimurium Bacteria at JoVE.com

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

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.

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

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

measuring-growth-gene-expression-dynamics-tumor-targeted-s

Research

JoVE Journal

Immunology and Infection

11.8K Görüntüleme.  Massachusetts Institute of Technology. Bu deneylerin amacı, zayıflatılmış büyümesi ve gen ekspresyonu dinamikleri üzerinde niceliksel zamana bağlı verilerini oluşturmak için bir S. typhimurium bakteri kolonileri. Bu video tümör hücre hazırlama ve implantasyonu, bakteri hazırlanması ve enjeksiyon, tam hayvan lüminesans görüntüleme, tümör eksizyonu ve bakteri kolonisi sayma kapsar.