Team:UCLA/Super Soldier Bacteria

Super Soldier Systems

Introduction

Antibiotic resistance is a renowned and pressing global health concern. In more recent times, there has been stagnation in discovering new classes of antibiotics, particularly for gram-negative bacteria. Throughout the mid-1900s, scientists were rapidly discovering the current major classes of antibiotics using the Waksman platform, which entailed systematically screening soil and fungal microbes for growth inhibition. However, the recurring problem of rediscovery and failure of subsequent high-throughput biochemical assays led many pharmaceutical companies to abandon their antibiotic development programs. Current antibiotics are generally broad-spectrum, acting against symbiotic gut flora in addition to pathogenic invaders. Therefore, specificity has recently become a target in modern antibiotic development in order to bypass challenges of both rediscovery and indiscriminate killing.

The core of antibiotic development lies in targeting a molecule or pathway essential for bacterial survival. Bacteria themselves have already developed several mechanisms to both communicate and compete with other bacterial strains occupying similar niches, which can be exploited for the creation of new antibiotic drugs. While some systems rely on secreted signaling molecules, direct cell-to-cell contact is also used to mediate intercellular interactions. Contact-dependent growth inhibition (CDI) is one such system that allows CDI+ bacterial strains to outcompete closely related CDI− siblings by synthesizing and translocating a toxin through the membrane of strains expressing the appropriate receptor. The CDI system is common in many strains of pathogenic gram-negative bacteria, such as Yersinia pseudotuberculosis and uropathogenic strains of Escherichia coli, making it a potentially suitable target for future antibiotics.

This type of growth inhibition was first seen in E. coli strain EC93, in which toxin delivery is mediated by the CdiA/CdiB two-partner secretion system and the outer membrane protein BamA, which is a conserved receptor among all strains of E. coli. EC93 is protected from its own toxin, located at the C-terminal region of CdiA (CdiA-CT), by the expression of a CdiI immunity protein that interacts directly with the toxin to neutralize its pore-forming capabilities. The CdiBAI cluster is common throughout most CDI+ strains, significantly varying only in CdiA-CT and CdiI sequences.

Our project focuses on the translocation of three different CDI systems from EC93 and Enterobacter aerogenes ATCC 13048 (containing two CDI loci) into one lab strain of E. coli to create a super-soldier organism that is able to selectively inhibit the growth of these strains. A lab strain containing CDIEC93, for instance, would be able to target all bacteria containing the corresponding receptor for CDIEC93, which would in this case be BamAEcoli. In order to target EC93 itself, however, we aim to switch CdiA-CTEC93 with a toxin from ATCC 13048 so that the immunity protein of EC93 does not prevent growth inhibition. It has previously been shown that CdiA-CT regions are modular, and systematically modularizing the toxin region using appropriate restriction sites is another goal of our project. While the CDI system in EC93 targets the BamAE. coli, the relevant receptors in other species of pathogens and even in other strains of E. coli is unknown. An additional facet to our project would be to find the receptors that each CDI system of ATCC 13048 targets by creating a transposon insertion library. Mutants that display a whole or partial CDI immunity phenotype will be sequenced to determine which genes have undergone transposon insertion, providing insight into which receptors may be targeted by ATCC 13048 CDI systems.



Super Soldier Systems

Methodology

In order to test the expression of foreign CDI systems in DH5-α and Enterobacter aerogenes, we need to express CDI systems on a plasmid. Our plan begins with two cosmids given to us by the Hayes lab located at the University of California, Santa Barbara. Each cosmid contained either the CDI system from EC93 or EC869 and was expressed in EPI100 or X90 (respectively). As a control, we performed aggregation assays and competition assays on these two bacteria. The next objective was to extract and express the cosmids in DH5-α to see if we could express foreign CDI systems in DH5-α. We would also perform competition and aggregation assays on the transformed DH5-α. Assuming this is successful, we would move on to expressing both CDI systems from Enterobacter aerogenes into DH5-α individually and performing the same set of assays. What is different about this set of experiments is that we would have to construct the plasmids ourselves. What we planned on doing was fusing the CDI system from Enterobacter aerogenes with a switched toxin and immunity region and a pSK33 backbone. All-in-all, this would require the use of advanced techniques like: Gibson assembly, PCR (colony and overlap), and electroporation.

Competition Assay

Our main method of testing whether our CDI systems is through a cell-based competition assay. It consists of the following cell types:

  • Inhibitory strain (CDI+): Bacterial Strain transformed with designated CDI system
  • Target Strain (CDI-): Native bacteria from which the CDI system comes from
  • Positive Control: Something that already has the designated CDI system expressed and can properly inhibit the Target
Protocol
  1. Grow all cells to correct growth phase in appropriate antibiotic
    1. Positive control to OD600 = 0.35 in 50 mL Luria-Bertani broth (LB) with antibiotic at 37 C
    2. Inhibitor to OD600 = 0.35 in 50 mL Luria-Bertani broth with antibiotic at 37 C
    3. Negative control to OD600 = 0.35 in 50 mL Luria-Bertani broth at 37 C
    4. Target overnight (16 hours) in 50 mL Luria-Bertani broth with antibiotic at 37 C (Target OD600 is not important)
  2. Mix inhibitor (or control) and target cell at a ratio of 10:1 (determined through concentration relation listed below) in LB without any antibiotic
    1. Multiply the Mass Attenuation Constant for the bacteria with the reading obtained from the OD600 to get the cellular density of the target, use this to prepare a 10:1 ratio of inhibitor to target cells.
  3. Incubate at 37 C at 225 rpm while plating samples at 0 and 4 hours after mixing
  4. Plate ten-fold serial dilutions from 1:1 up to 1,000,000 (experimentally determine which dilutions are best for your needs) in a M9 salt solution or SOC
    1. Plate 100 µL
  5. Count Colony Forming Units per mL of the co-culture
    1. Choose plates that haven’t formed lawns, you want easy to identify colonies ideally
    2. Count the number of colonies on that plate (choose a dilution in which all three co-cultures can be counted)
    3. Divide the number of colonies by the dilution factor to get the number of CFUs
    4. Divide that value by the fraction of mLs plated to get CFUs/mL
  6. Compare the CFUs of the inhibitor with the positive and negative control to determine if the inhibitor properly inhibits the target strain

For a list and description of all protocols use, visit our Protocols page here

Super Soldier Systems

Results

Aggregation assay (07/13/16)

We ran aggregation assays with the strains listed in Table 1 as a qualitative test to see if CDI systems were being properly expressed.

Considerations for replicating this experiment:

  • leave pellet undisturbed for entire 2 hour period to avoid re-suspension
Strain/Cosmid t=0hr t=2hr
ATCC 13048
DH5-alpha w/ EC-93
DH5-alpha w/ pSK33
X90 w/ EC93
**expected aggregation**
EPI100 w/ EC869

Table 1: Preliminary aggregation assay results: ATCC 13048, X90 w/ EC93 and EPI100 w/ EC869 strains all obtained from the Hayes lab in UCSB. DH5-alpha w/ pSK33 and DH5-alpha w/ EC93 created in Kosuri lab by UCLA iGEM team. EPI100 w/ EC869 and DH5-alpha w EC93 displayed observable autoaggregation after t = 2h. No aggregation was expected in DH5-alpha w/ pSK33 since it does not have a CDI system. We were uncertain as to whether or not ATCC 13048 would auto-aggregate or not as it has not been previously established, thus the lack of auto-aggregation does not necessarily indicate lack of CDI expression. X90 w/ EC93 did not auto-aggregate, suggesting there may be an issue expressing the CDI system.

Competition assay (07/29/16)

Due to the lack of auto-aggregation seen in EC93 during the auto-aggregation assay on 07/13/16, we conducted a competition assay to test for inhibitory activity in X90 w/ EC93 using EPI100 w/ EC869 as a CDI+ positive control and DH5-alpha w/ ampR as a CDI- negative control.

Considerations for replicating this experiment:

  • grow all cultures in antibiotic-free media for easier co-culturing (otherwise must do wash step)
  • for t = 0h, 1:1000, 1:10000, and 1:100000 dilutions produced readable plates in all co-cultures
  • for t = 2h, 1:100, 1:1000 produced readable plates in CDI + co-cultures and 1:100000, 1:1000000 produced readable plates for the negative control
  • t = 3h was an effective time to measure inhibition (t = 20h was also measured, but all plates were essentially unreadable due to lawn growth)
Strain t=0hr t=3hr
(+) control EPI100 1/ EC869 1.6 E 6 CFUs/mL 3.78 E 4 CFUs/mL
(-) control DH5-alpha ampR 1.53 E 6 CFUs/mL 3.78 E 8 CFUs/mL
Test X90 w/ EC93 1.26 E 6 CFUs/mL 7.11 E 3 CFUs/mL

Table 2: Competition assay results: quantitative results showing inhibitory activity in EPI100 w/ EC869 and X90 w/ EC93. No inhibitory activity observed in negative control.

Figure 1: Competition assay to verify expression of EC93 CDI cosmid in X90: Plot generated with Microsoft Excel. Inhibition observed in EPI100 w/ EC869 cosmid and X90 w/ EC93 cosmid. No inhibitory activity was observed in DH5-alpha w/ ampR (negative control). Data plotted is explicitly listed in Table 2.

Competition assay results (08/01/16)

To test the strains (i.e. DH5-alpha w/ EC869 and DH5-alpha w EC93) that we had created by transforming cosmids obtained from Dr. Christopher Hayes into DH5-alpha, we conducted another competition assay using DH5-alpha w/ ampR as a negative control.

Strain t=0hr t=3hr
DH5a w/ EC869 7.33 E 6 CFUs/mL 1.29 E 4 CFUs/mL
(DH5a w/ EC93 4.44 E 6 CFUs/mL 2.55 E 2 CFUs/mL
DH5a w/ ampR 3.28 E 6 CFUs/mL 1.30 E 8 CFUs/mL

Table 3: Competition assay results with UCLA iGEM team-made strains: Trial 1; quantitative results showing inhibitory activity in DH5-alpha w/ EC869 cosmid and DH5-alpha w/ EC93 cosmid. No inhibitory activity observed in negative control.

Figure 2: Competition assay results with UCLA iGEM team-made strains: Trial 1; Plot generated with Microsoft Excel. Inhibition observed in DH5-alpha w/ EC869 cosmid and DH5-alpha w/ EC93 cosmid. No inhibitory activity was observed in DH5-alpha w/ ampR (negative control). Data plotted is explicitly listed in Table 3.

Lambda-red knockout of CdiA in E. aerogenes

Made electrocompetent E. aerogenes (verified by isolating gDNA from plated colonies and attempting to PCR fragments from EBL1 using the isolated gDNA as template). Colonies 6 and 7 had positive results.

Unable to transform pTKRED into E. aerogenes thus far (all CPCR results negative).

Transposon mutagenesis-derived library for discovery of CDI-related proteins in E. aerogenes

Transposase activity successfully verified.

  • 2 μl Transposon DNA (117.57 μg/ml in TE Buffer)
  • 4 μl Transposes
  • 2 μl 100% glycerol
  • 8 μl Total reaction volume

Reacted formed transposomes with pUC19.

Unable to transform into E. aerogenes or DH5-alpha. Transformed DH5-alpha with transposed pUC19 to see if pre-formed transposomes were viable.

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Biobricks

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Lab Notebook