Project Description

a brief overview

Abstract

The World Health Organization has declared antimicrobial resistance (AMR) as the biggest global public health threat of the 21st century. AMR occurs when microorganisms evolve to resist antibiotics, rendering traditional treatments ineffective– a process exacerbated by the current misuse of antibiotics in agriculture and healthcare. To combat AMR, Lambert iGEM created SHIELD: a versatile toolbox used to develop novel antimicrobials that can combat antibiotic-resistant diseases.

SHIELD uses the CRISPR-interference system to silence critical genes in the target organism, alongside a toehold biosensor to measure the extent of gene silencing. We also developed SWORD: a machine learning software tool that optimizes toehold design, and LabPilot: a frugal liquid handler to aid with experimentation.

SHIELD enables researchers to rapidly develop multiple antimicrobials for a single disease by targeting several genes, circumventing the emergence of resistance in a single gene without compromising overall treatment effectiveness. SHIELD empowers researchers to outpace antibiotic resistance. Defining The Problem Antimicrobials were one of the most transformative medical discoveries of the 20th century, given that they were responsible for many of modern medicine’s miracles including safe surgical procedures, effective cancer therapies, and organ transplants. This revolutionary technology, which previously extended the average human lifespan by 23 years, now faces the stark reality of reversing decades of medical progress (Hutchings, 2019).

AMR has directly led to over 1.27 million deaths in 2019, with this figure expected to surpass 39 million by 2050, ultimately exceeding cancer to become the global leading cause of death (O’Neill, 2016; Naghavi, 2024).

Antimicrobial resistance (AMR) occurs when microbes evolve to resist antibiotics – rendering traditional treatments ineffective. The emergence of these drug resistant pathogens lead to the inability to treat common infections.

Antibiotic resistance is a multifaceted issue fueled by the misuse of antibiotics in both the healthcare and agriculture industries.

Healthcare

The perceived “magic” power of antibiotics to combat any bacterial diseases often leads to their overuse by both healthcare providers and patients. Despite stricter prescription guidelines, responsibility falls on the patient to prevent misuse of antibiotics. Something as simple as a patient not completing a full prescription of antibiotics can contribute to antimicrobial resistance. This seemingly inconsequential action gradually undermines the effectiveness of modern medicine. Ultimately, emphasizing patient education in healthcare is not just important – but crucial for protecting the future of medicine.

Agriculture

The overuse of antibiotics in agriculture presents a complex, interconnected problem rooted in improper agricultural practices. The soil serves as a reservoir for a vast number of microbial populations. However, when antimicrobials are introduced into this environment (via runoff from watersheds or other sources) bacteria develop resistance genes which then begin to proliferate among microbial communities due to selective pressures. In Georgia, an estimated 102 billion livestock animals annually release 600,000 kg of antibiotics into the soil, contaminating local drinking water through runoff (Tian et al., 2021). Human consumption of poultry and water contaminated by fecal runoff from antibiotic-treated chickens results in exposure to residual drugs, fostering further antibiotic resistance and diminishing the efficacy of existing medications in human populations.

Current Solutions

Most current approaches to combating antimicrobial resistance involve developing novel antibiotics or optimizing them to keep up with the rapidly evolving pathogens (Parmanik et al., 2022). However, developing a new antibiotic costs over $1 billion USD, while only yielding a mere 10% in revenue annually (Nature, 2024). In addition to low returns, the developmental process is a time-consuming 10 to 15 year journey riddled with obstacles, starting from the initial research stage to getting FDA approved. Several novel methods for combating antimicrobial resistance are currently being researched (Jayaseelan Murugaiyan et al., 2022; Uddin et al., 2020):

Antimicrobial Peptides are less likely to induce resistance than traditional antibiotics but have high production costs, possible toxicity, and can be unstable in vivo.

Bacteriophage Therapy uses viruses to kill microbes but also has the possibility for phage resistance and can induce immune responses in the host.

CRISPR/Cas9 technology can remove antimicrobial resistance genes and allow previously ineffective antibiotics to work. However, they can cause unintended genomic alterations and have unknown long-term consequences.

While novel antimicrobial approaches show promise, they still face limitations and remain vulnerable to the same resistance issues that plague traditional antimicrobials.

Our Approach

After months of extensive research and conversations with antimicrobial resistance (AMR) experts, Lambert iGEM adopted a multifaceted approach to address this pressing global and local issue.

While traditional antibiotics remain static against evolving microbes, modern vaccines are constantly updated to combat the change in viral strains. Rather than seeking a therapy that is unaffected by resistance, we took inspiration from modern mRNA vaccines – vaccines that can be quickly constructed using only the pathogen’s genetic code– and shifted our focus to developing SHIELD (Silencing Harmful Immunogenic Effector Links to Disease): a versatile toolbox for a rapid response to an ever changing threat.

Inspired by the CRISPR-Cas approach to antimicrobial therapy, SHIELD utilizes a CRISPR-interference (CRISPRi) system to suppress critical infectious genes without altering the genome. To facilitate rapid validation and testing of various CRISPRi therapies, we developed a toehold-based testing pipeline that can swiftly validate new CRISPRi systems, enhancing SHIELD’s capacity for quick adaptation. By using a cell-free system coupled with these assays, linear DNA can be utilized, eliminating the time-consuming process of cloning plasmids. As we faced challenges in designing effective toehold switches, we developed a machine learning-based software to optimize the toehold design process. To further enhance SHIELD’s abilities and ensure precise and consistent execution of our experiments, we completed the development of Labpilot, a frugal automated liquid handler, which we began in our 2023 project.

Collectively, our CRISPRi system, toehold testing pipeline, software, and automated liquid handler form a comprehensive toolkit that enables the swift development and testing of new antimicrobial therapies. As a proof of concept for SHIELD, we chose to create an antimicrobial therapy for M. Tuberculosis and its critical gene INHA.

CRISPRi

CRISPR interference (CRISPRi) is a gene silencing technique that uses a deactivated Cas9 protein (dCas9) to silence target genes without altering the genetic code by blocking transcription. Unlike traditional CRISPR, which permanently modifies genes by cutting DNA, the reversible nature of CRISPRi enables doctors to stop treatment if any adverse effects occur without permanent changes in patients. CRISPRi also demonstrates fewer off-target effects than CRISPR, increasing its specificity and safety when implemented in medical settings (Gilbert et al., 2014). CRISPR-based therapeutics have already shown promise in combating AMR diseases, including our proof-of-concept target, Mycobacterium tuberculosis (M. tb) (Rubin et al., 2018). While these studies utilized traditional CRISPR, they validate the potential of our CRISPRi approach, as both techniques target specific genes to combat bacterial resistance. To apply this system to a new disease of interest, researchers only need to design a few single-guide RNAs (sgRNAs) targeting a critical gene. These sgRNAs can be rapidly tested and optimized using cell-free systems, allowing for quick, cost-effective screening of multiple sgRNA, making SHIELD a more convenient option for researchers. Once promising target genes are identified, they can be validated in vivo in the target organism and tested with the chosen delivery mechanism, significantly reducing the time and resources required to develop new antimicrobial treatments. By taking advantage of CRISPRi’s reversibility, its significant potency against AMR, and the simplicity of the development process, the SHIELD toolbox allows for versatile, adaptable, and safe treatment of diseases.

INHA and Justification

As a proof of concept for SHIELD, we developed a CRISPRi antimicrobial targeting Mycobacterium tuberculosis (M. TB). We chose M. TB due to its significant contribution to the growing AMR epidemic, with drug-resistant strains accounting for approximately 29% of total AMR-related deaths in 2023 (Antimicrobial Resistance).

We chose the inhA gene for several reasons:

Low mutation rate: reduces the likelihood of rapid resistance developing. Critical role in Tuberculosis Pathogenicity and survival: establishing the effects of inhibiting inhA Uniqueness to the Mycobacterium genus: reducing off-target effects with its specificity.

By using our CRISPRi system to inhibit inhA, we aim to disable M. tuberculosis’s pathogenicity and demonstrate how we could eliminate the bacteria without relying on traditional antibiotics, ultimately proving SHIELD’s potential as a novel, adaptable strategy for combating antimicrobial resistance.

Toehold Biosensors

After designing and testing sgRNAs in a cell-free environment, researchers need to validate whether the treatment effectively silences the gene in vivo. However, instead of simply adding a fluorescent reporter like GFP into the organism’s genome, they can use SHIELD to rapidly design toehold switches – RNA-based biosensors that detect the presence of specific mRNA sequences and trigger a measurable output, such as the translation of a reporter protein. This allows researchers to determine whether the antimicrobial treatment successfully silences the gene of interest within the organism. If the target gene’s mRNA is unable to be detected by the toehold switches, it indicates that the CRISPRi system worked as intended, signaling to researchers that they can move on to clinical testing in patients.

Modeling

Simulations

Choosing between CRISPR and CRISPRi for our wet lab project presented our team with a dilemma. While CRISPRi seemed like the ideal solution due to its reversibility, our team found no published research of its efficacy on inhibiting genes. Therefore, we created an ordinary differential equation (ODE) model simulating Cas9 and dCas9 with different target constructs, including inhA and GFP, to validate CRISPRi as a suitable alternative to CRISPR. The model demonstrated similar results between CRISPR and CRISPRi, mirroring their efficacy and providing support for the use of CRISPRi in the experiments. From here, we developed a baseline model for CRISPRi results to help guide experimentation. During this process, we also created simulations that varied in concentrations of sgRNAs to help optimize wetlab outcomes. Using our results, we updated our baseline model with our empirical parameters to create a representative graph which can help future researchers utilizing CRISPRi.

SWORD

To effectively design toehold switches for our project, we created SWORD - a machine learning-based software tool that accurately predicts the secondary structure of nucleotide sequences. Unlike existing generative models such as NUPACK, SWORD encompasses a broader set of parameters, including sequence features and binding motifs, allowing for more accurate predictions. SWORD uses two approaches to develop accurate and effective toehold switches: a predictive model, which analyzes the nucleotide sequence to forecast the on-off states of the toehold switch, and a generative model, which creates new, optimized toehold sequences. By integrating SWORD into the SHIELD toolbox, researchers will be able to more easily develop and implement toehold switches to analyze the efficacy of CRISPRi within the cell. SWORD allows for faster, more specific, and effective design of toehold switches.

LabPilot

To manage the large number of reactions needed for the development of our CRISPRi-based mechanism, Lambert iGEM created LabPilot, an automated pipetting system that effectively manages multiple reactions, minimizing the possibility of human error and the time spent on manual pipetting. LabPilot accelerates experimental processes by automating time-consuming procedures, allowing researchers to focus on more crucial experimental aspects, such as designing and optimizing the antimicrobial itself. This system increases output and makes it possible to produce therapies quickly and consistently.

References

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