Team:NUS Singapore/Project/Wet Lab


Interactive Points | Codrops

INTRODUCING:

  1. RIOT Sensor
  2. RIOT Responder
  3. RIOT Invader

The RIOTsystem is a two-component spatial sensor for drug delivery to specific cell types. Using cancer cells as a model, we have engineered E. coli to detect specific characteristics that are present in a range of cancers.


Firstly, the RIOTsystem is designed to detect and survive only in areas of elevated lactate concentrations present in the microenvironment of certain cancer cells due to the Warburg effect. This specificity is conferred by introducing a bifunctional conjugate which consists of an anti-CD44v6 antibody linked to a hemophore, hasA (RIOT Transponder). This hemophore is responsible for triggering the has operon in the RIOTsystem (RIOT Responder) that will allow the engineered E. coli to specifically congregate at the cancer cells and initiate the RIOT Invader, which causes invasion of the cancer cell to deliver a reporter protein or therapeutic drug via expression of Invasin and Listeriolysin.

Part 1:
RIOT Sensor


We synthesized a series of RIOT sensors which is repressed by LldR and activated by L-lactate. Among them, Construct 7 and Construct 8 exhibited an increased sensitivity to lactate compared to the original sensors (namely, Construct 1 and 2).

To further enhance the specificity of our RIOT system, in the future, we may insert Construct 7 in a low-copy plasmid backbone to fine-tune the expression of ALR. This may reduce their growth in the bloodstream and keep them from attacking healthy cells, which do secrete some concentration of lactate.

BACKGROUND:

In order to survive and continually proliferate, cancer cells are found to have the ability to alter glucose metabolism. This is a common phenomenon known as the Warburg effect, where cancer cells have the ability to increase glucose uptake and undergo aerobic glycolysis followed by lactic acid fermentation in the cytosol, resulting in the elevated production and accumulation of lactate (Chen et al., 2007; Vander et al., 2009; Alfarouk et al., 2015). Besides malignancy, high lactate concentration, which is > 4 x 10-3 M (Kruse et al., 2011) in a number of studies, has been associated with increased mortality in sepsis, trauma and cardiac arrest (Andersen et al., 2013). Therefore, elevated lactate can serve as a useful indicator to identify patients and expedite further diagnostic workup. As a proof-of-concept, Escherichia coli was engineered to detect the increased level of lactate, hence, specifically distinguish cancer cells from normal cells.

We designed a collection of RIOT sensors which are responsive to L-lactate. Our RIOT sensors contain a reporter gene, either superfolded green fluorescent protein (sfGFP) or Alanine Racemase (ALR) under the control of a lactate sensitive promoter (Figure 1). ALR is an enzyme responsible for the synthesis of D-alanine, an essential amino acid required for bacterial survival (Walsh, 1989).

Figure 1. Working mechanism of RIOT sensor.

(A) In the absence of lactate, lldR binds to two operators in the promoter region and inhibit the expression of a superfolded green fluorescent protein (sfGFP). (B) In the presence of lactate, lactate binds lldR, preventing its binding to the operators. Consequently, sfGFP is expressed and the level of sfGFP can be quantified using fluorescence microscopy.

RIOT sensors using Alanine Racemase (ALR) as a reporter gene have similar working mechanism. In the presence of lactate, lldR is inhibited and ALR is expressed to catalyze the synthesis of D-Alanine which helps D-Alanine auxotrophic mutant bacteria to survive.

CAMr = Chloramphenicol resistant.

Since one of our goals is to detect the presence of L-lactate produced by cancer cells, the designed sensors have to be extremely sensitive to small changes in lactate concentration. Various studies have shown that normal physiologic range of lactate concentration in the blood is approximately at 0.5 – 2 x 10-3 M in healthy, resting individuals without exertions (Gollnick et al., 1986; McGee et al., 1992; Kennedy et al., 2013). Tissues that were completely exhausted like skeletal muscles when exercising contained higher lactate concentrations of up to 2.5 x 10-3 M (Mainwood & Renaud, 1985; Goodwin et al., 2007). Once the body stops exercising, the lactate concentrations would drop after 3 to 8 minutes post-exercise (Goodwin et al., 2007). This differs from the pathophysiologic lactate concentrations in tumors which range from normal lactate levels to concentrations as high as 4 x 10-2 M (Kennedy et al., 2013). Also, the elevated lactate levels in tumors were over a longer period of time as compared the concentrations of lactate in normal skeletal tissues when exercising. Therefore, our engineered sensor should have little or no basal expression and significant increase in reporter output (either by GFP or ALR) in the presence of lactate. Our strategy allows strict amount of reporter expression, thus increasing sensitivity of lactate detection, and minimise false positive result.

We minimise the basal expression of our reporter by linking different strength ribosomal binding sites (RBS) with a shorter version of the promoter region for the wild-type lldPRD operon (BBa_K1897037, derived from Part BBa_K822000), the engineered promoter (BBa_K1847008) or J23100: a high expression promoter in a high constitutive cassette (BBa_K314100). We obtained the coding sequence of ALR from the Biobrick plasmid (BBa_K1172901). The first two promoters, the coding sequence of sfGFP and the sequence of lambda t0 terminator were received from team ETH_Zurich 2015. Our general cloning strategy is demonstrated in our Notebook. A second stop codon was added at the end of ALR sequence to enhance the efficiency of the translational termination.


Part 2:
RIOT Responder


Here, we use the CD44v6 antibody, which is conjugated to a bacterial peptide called hasA. hasA is part of the Has operon system, which when bound to hasR (found on the surface of the bacterial cells) leads to a cascade of reactions within.

The Has operon is another critical sensor for the RIOTsystem. The proteins involved in the operon are hasA, hasR, hasS and hasI. hasA is an extracellular haemophore and it binds to bacterial cells expressing hasR, the hasA receptor. This binding causes a conformational change in hasS (an anti-sigma factor), which then releases hasI, a sigma factor. hasI then binds to its specific promoter (labelled as pHas) to trigger expression of genes under pHas. In the RIOT system, the gene expressed is luxR, which is required to activate the RIOT suppressor.

BACKGROUND:



In this case, we are using the Has operon to activate the luxR feedback system. In the bacteria cell, hasR, hasS and hasI will be constitutively expressed. hasR is expressed on the outer surface of the cell wall and acts as the receptor that binds to hasA. hasS will be found on the inner surface of the membrane of the cell.

Normally in the cell, hasI, which is a sigma factor, is bound to hasS, which is an anti-sigma factor. This prevents hasI from activating the production of luxR. But when hasR is bound by hasA, this leads to conformational changes that result in the release of hasI by hasS. hasI will then activate luxR production.

CD44 is a cell membrane protein involved in normal cell function (cell-cell and cell-matrix adhesion). However, one notable isoform, CD44v6, seems to play a major role in cancer progression, facilitating cell migration and invasion and is commonly upregulated on the surface of cancer cells. The RIOT system uses CD44v6 as a spatial marker, and recognition of this protein via a CD44v6 specific antibody allows anchoring of the engineered bacteria on the surface, triggering the expression of invasin and LLO for subsequent invasion.

Part III:
RIOT Invader

LuxR is under the control of pHas, which get activated via transponder circuit. The production LuxR will then induce the expression of LuxI, invasin, LLO (listeriolysin O) and GFP respectively. There is already a basal level of AHL in the bacteria. Upon LuxI expression, more AHL is produced, thus amplifying the loop of this positive-feedback mechanism.

Invasin helps the bacteria to get into cell endosome while LLO which is a pore-forming toxin will allow the bacteria to escape out of the endosome into cytosol. We use GFP as a marker to locate the bacteria and signal the successful activation of circuit.

BACKGROUND:



Invasin is derived from the bacteria Yersinia pestis which allows selective invasion of cells that express β1-integrins. Listeriolysin O (LLO) on the other hand, is expressed in Listeria monocytogenes and allows the bacteria to break out of the endosome after entry into mammalian cells. LLO is activated in the low pH enviroment (pH 5.5) of the endosome. Then, LLO will forms pores in the membrane of the endosome and results in the lysis of the endosome and the escape of the bacterium into the cytoplasm. Combining the traits of these two genes, our engineered bacteria is capable of entering the cytosol of cancer cells to potentially release a cytotoxic drug.

We aim to make a construct that is activated in the presence of a hasS-hasI complex that is formed in the presence of CD44v6 on the surface of cancer cells. The construct makes use of luxR and luxI to activate the production of invasin and listeriolysin O (LLO), as well as a designated drug that will be able to kill off the cancer cells.

The combination of both invasin and LLO allows the bacterium to invade mammalian cells and escape from the endosome into the cytoplasm of the cell. Once in the cytoplasm, the drug released from the bacterium can build up within the cell to result in the destruction of the cell. Combined with RIOT Sensor and RIOT Transponder, the bacterium can potentially target and eliminate cancer cells with minimal side effects.

Initially, small amounts of N-Acyl homoserine lactones (AHLs) produced by our engineered bacteria freely diffuse in and out of the cell. In tumor regions with an expected higher cell density, the concentration of AHL also increases. Past a threshold, LuxR binds to AHL and this LuxR-AHL complex will further activate expression of LuxI, producing more AHL. This creates a positive feedback loop that increases both the concentration of LuxI and of our desired proteins, invasin and LLO.

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References:


  • Alfarouk, K.O., Verduzco, D., Rauch, C., Muddathir, A.K., Bashir, A.H., Elhassan, G.O., Ibrahim, M.E., Orozco, J.D.P., Cardone, R.A., Reshkin, S.J. and Harguindey, S. (2015). Glycolysis, tumor metabolism, cancer growth and dissemination. A new pH-based etiopathogenic perspective and therapeutic approach to an old cancer question. Oncoscience, 2(4), p.317.
  • Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009). Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science, 324(5930), 1029-1033.
  • Andersen, L. W., Mackenhauer, J., Roberts, J. C., Berg, K. M., Cocchi, M. N., & Donnino, M. W. (2013). Etiology and therapeutic approach to elevated lactate levels. Mayo Clinic Proceedings. http://doi.org/10.1016/j.mayocp.2013.06.012
  • Chen, Z., Lu, W., Garcia-Prieto, C., & Huang, P. (2007). The Warburg effect and its cancer therapeutic implications. Journal of bioenergetics and biomembranes, 39(3), 267-274.
  • Gollnick, P.D., Bayly, W.M. and Hodgson, D.R. (1986) Exercise intensity, training, diet, and lactate concentration in muscle and blood. Medicine and Science in Sports and Exercise, 18(3), pp.334-340.
  • McGee, D., Jessee, T.C., Stone, M.H. and Blessing, D., 1992. Leg and Hip Endurance Adaptations to Three Weight-training Programs. The Journal of Strength & Conditioning Research, 6(2), pp.92-95.
  • Goodwin, M.L., Harris, J.E., Hernández, A. and Gladden, L.B. (2007) Blood lactate measurements and analysis during exercise: a guide for clinicians.Journal of diabetes science and technology, 1(4), pp.558-569.
  • Kennedy, K. M., Scarbrough, P. M., Ribeiro, A., Richardson, R., Yuan, H., Sonveaux, P., ... & Dewhirst, M. W. (2013). Catabolism of exogenous lactate reveals it as a legitimate metabolic substrate in breast cancer. PloS one, 8(9), e75154.
  • Kruse, Ole, Niels Grunnet, and Charlotte Barfod. "Blood lactate as a predictor for in-hospital mortality in patients admitted acutely to hospital: a systematic review." Scandinavian journal of trauma, resuscitation and emergency medicine 19.1 (2011): 1.
  • Walsh, C. T. (1989). Enzymes in the D-alanine branch of bacterial cell wall peptidoglycan assembly. Journal of biological chemistry, 264(5), 2393-2396.
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