Overview: Silencing Antibiotic Resistance

By silencing the expression of genes responsible for antibiotic resistance, antibiotic-resistant bacteria can be converted to antibiotic-sensitive bacteria. In the case of MRSA, silencing the expression of mecA and its regulatory elements create a population of antibiotic-sensitive MRSA (Meng et al., 2006; Hou et al., 2007; Sakoulas et al., 2001). To model silencing in MRSA, our team aimed to silence YFP expression in S. epidermidis using CRISPRi and RNAi.

CRISPRi: Silencing Transcription

CRISPR systems (clustered regularly interspaced short palindromic sequences) are involved in the adaptive immune systems of bacteria and archaea. Mature CRISPR RNA (crRNA) binds to trans-activating crRNA (tracrRNA) to form a complex that is recognized by the CRISPR associated protein (Cas9). The Cas9 protein is directed to a target DNA site where it performs a double stranded break (Karginov and Hannon, 2010). An improvement to the original CRISPR system is the use of sgRNA which is a chimera of the crRNA and tracrRNA complex and this simplified version has been shown to be effective more (Jinek et al., 2012).

The CRISPR system can be modified further to regulate gene expression. The CRISPRi (CRISPR interference) system involves a catalytically dead Cas9 protein (dCas9) paired with a single guide RNA. Together, they are able to interfere with transcription and halt the expression of the target gene (Qi et al., 2013). This process is reversible and nonfatal; since dCas9 is catalytically dead, it does not cleave targeted DNA in the way an endonuclease normally would (Qi et al., 2013).

CRISPRi: dCas9-sgRNA complex binds to DNA and interferes with transcription.

Allowing the MRSA cells to survive is ironically in our favor; we want our silencing plasmid to propagate throughout the entire infected population exponentially and S. aureus cells that have been conjugated-into are also capable of conjugating the construct into others. The desired result is therefore a population in which most cells have been infected with the conjugative silencing plasmid, actively suppressing their chromosomal antibiotic resistance. Application of β-lactam antibiotics would then be effective against a previously resistant population.

We created a mathematical model of the CRISPRi system based on the network below, in which the bound complex has a repressive effect on YFP production. The purpose of the model was to examine the system for possible engineered improvements and to identify time-series repression data.

CRISPR Interference Network used to create Mathematical Model

The time series dynamics of the model showed that repression of YFP was acheivable, but incomplete. To improve our repression levels, we conducted a local and global sensitivity analysis of the model parameters. The sensitivity analysis informed us that changes to the mRNA degradation rate would have the greatest effect on overall repression efficiency.

The results of the sensitivity analysis inspired an investigation into silencing of the mRNA itself, i.e. RNAi.

sRNA: Silencing Translation

Gene regulation at the post-transcriptional level can be accomplished through RNA interference (RNAi) mechanisms (Aiba, 2007). RNAi occurs when bits of non-coding small interfering RNA (siRNA) - also known as microRNA (miRNA) - produced by the cell complements with targeted mRNA, regulating its translation (Shan, 2010). In bacteria, sRNA or small regulatory RNAs are members of a wide and divergent class of RNAi processes. Translation repression and/or target mRNA degradation occurs when sRNA binds in close proximity to the ribosomal binding site of its target mRNA (Yoo et al., 2013). This inhibits the initiation of translation by outcompeting the ribosome and subsequently leads to the destabilization of the target mRNA. Furthermore, in order for the sRNA to efficiently anneal its target mRNA in bacterial cells, a RNA chaperone protein, hfq, is required (Aiba, 2007). The translation repressing mechanism of hfq-dependent sRNA is shown in figure below.

CAPTION

We modelled the RNAi system to determine the amount of time it would take to repress YFP. The figure below is a time series graph of the concentration of YFP over time with our RNAi system.

Design

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Results and Future Work

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