Project Description | Tec-Monterrey

The global landscape

Local Problem

Current solutions

Our solution

References

The global landscape

In 2019 an estimated 4.95 million people died from illness associated with antibiotic resistance, from which 1.27 million deaths were directly related to antibiotic resistance [1]. The most affected region in the world is the western saharan africa having a mortality of 27.3 deaths per 100,000 inhabitants while the Australian-Asian region is the least affected with 6.5 deaths per 100,000 inhabitants [1].

According to the CDC (2022) in the United States there are 2.8 million antibiotic resistant infections with a death toll of 35,000 people. In a study conducted by Murray et al. (2022) it was identified that lower respiratory infections accounted for 1.5 million deaths related to antibiotic resistance.

The CDC in 2022 listed the main causes of antibiotic resistance, among which included the over prescription of antibiotics together with an incomplete treatment and a poor infection control in hospitals and clinics. The latest cause is more common in developing countries due to a lack of resources for a proper sanitary control in hospitals.

The main pathogens that show an increased antibiotic resistance are Escherichia coli , followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa [1].

statisticsbacteria

Image obtained from Center For Disease Control and Prevention (2022)

The CDC in 2022 listed the main causes of antibiotic resistance, among which included the over prescription of antibiotics together with an incomplete treatment and a poor infection control in hospitals and clinics. The latest cause is more common in developing countries due to a lack of resources for a proper sanitary control in hospitals.

The local Problem

Mexican normativity has pointed out that antibiotics are the most used drugs in human health. Nevertheless, more than 50% of the prescribed antibiotics to people are not efficiently prescribed and even unnecessary. In this sense several key factors have been identified to constitute the origin of the antibiotic resistance problem. In our project we focused on the resistance generated in the Mexican healthcare system, specifically in nosocomial resistant infections.

community-system

According to Amabile-Cuevas (2010) there is a trend in antibiotic resistance in Mexican hospitals showing that Pseudomonas aeruginosa is one of the main pathogens that develop resistance against many drugs. Pseudomonas aeruginosa is also known to be the main pathogen responsible for hospital acquired infections, causing an increased healthcare cost, morbidity and mortality [4]. In 2018, Ponce de León, S. et. al., tracked the antibiotics resistance levels in a hospital network that significatively covered the entire Mexican territory, they found that P. aeruginosa was mainly resistant to meropenem (33%) and to ciprofloxacyn (20%). This microorganism receives special consideration for this matter since it belongs to the group of species that produces extended-spectrum beta-lactamases or carbapenemases [9]. This is the main reason why P. aeruginosa is a good candidate to be resensitized by our gene silencing system.

Current Solutions

An expensive solution to the problem is the development of new antibiotics such as tetracycline derivatives (eravacycline), fourth generation fluoroquinolones (delafloxacin), new combinations between one β-lactam and one β-lactamase inhibitor (meropenem and vaborbactam), siderophore cephalosporins (cefiderocol), new aminoglycosides (plazomicin), and agents in development for treating drug-resistant TB (pretomanid). These new drugs have limited use even in developed countries due to its high cost, making them even more unavailable in developing countries [5].

A recent way to combat intrinsic antibiotic resistance is the development of antibiotics adjuvants to combat antibiotic resistance aiming to bacterial non-essential targets. To date, three main types of antibiotic adjuvants have been developed to block the intrinsic mechanisms of antibiotic resistance: (a) beta-lactamase inhibitors, (b) efflux pumps inhibitors, and (c) outer membrane permeabilization [6]. Another strategy to combat antibiotic resistance is the modification of previously designed drugs, such as the example of erythromycin modified with fluoride to improve binding to the bacterial ribosome using protein engineering [7]. A novel strategy to combat antibiotic resistance infections has been the silencing of virulence genes in bacteria using gene editing tools such as CRISPR-cas9. This tool has high selectivity for pathogenic bacteria but its use is limited in respiratory infections due to delivery constraints, and also has off-target activity that could cause potential damage to either host or beneficial bacteria besides having high cytotoxicity for human cells. [8] To overcome these disadvantages, the use of bacteriophages to deliver sRNAs that target virulence or antibiotic resistance genes has been considered a promising alternative due to its higher specificity, increased stability of viral particles and selectivity for pathogenic bacteria (8)

Our Solution

As we analyzed this problem, we came to the conclusion that our solution should be able to efficiently silence antibiotic resistance genes in Pseudomonas aeruginosa making them susceptible to treatment with common antibiotics. The silencing is performed by computationally designed sRNAs that target antibiotic resistance genes.

The design of the sRNAs is based considering 2 different scores that are related to the thermodynamic interactions between our silencing RNA and the target mRNA, this ensures that the binding process would happen effortlessly and the Hfq protein will cleave to the complex ensuring the process. At the same time our sRNAs are evaluated through Machine Learning protocols to evaluate the regulation.

The delivery of the sRNAs to the Pseudomonas aeruginosa population present in the lungs of ill patients with pneumonia is done using M13 bacteriophages with a modified P3 protein with the ability to infect Pseudomonas aeruginosa. For the administration of the bacteriophages we designed a nebulizer that will deliver a liposome-bacteriophage complex. The liposomes will be manufactured using a microfluidic device capable of efficiently making liposomes of constant size with the ability to bind with the bacteriophages increasing their stability.

our-solution

References

Murray, C. J., Ikuta, K. S., Sharara, F., Swetschinski, L., Robles Aguilar, G., Gray, A., Han, C., Bisignano, C., Rao, P., Wool, E., Johnson, S. C., Browne, A. J., Chipeta, M. G., Fell, F., Hackett, S., Haines-Woodhouse, G., Kashef Hamadani, B. H., Kumaran, E. A. P., McManigal, B., . . . Naghavi, M. (2022, February). Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. The Lancet, 399(10325), 629–655. https://doi.org/10.1016/s0140-6736(21)02724-0
CDC’s Response to a Global Emerging Threat. (2022, March 16). Centers for Disease Control and Prevention. Retrieved October 8, 2022, from https://www.cdc.gov/drugresistance/solutions-initiative/stories/ar-global-threat.html
Amabile-Cuevas, C. (2010, January 4). Antibiotic resistance in Mexico: a brief overview of the current status and its causes. The Journal of Infection in Developing Countries, 4(03), 126–131. https://doi.org/10.3855/jidc.427
Castañeda-Montes, F., Avitia, M., Sepúlveda-Robles, O., Cruz-Sánchez, V., Kameyama, L., Guarneros, G., & Escalante, A. (2018, November). Population structure of Pseudomonas aeruginosa through a MLST approach and antibiotic resistance profiling of a Mexican clinical collection. Infection, Genetics and Evolution, 65, 43–54. https://doi.org/10.1016/j.meegid.2018.06.009
Terreni, M., Taccani, M., & Pregnolato, M. (2021, May 2). New Antibiotics for Multidrug-Resistant Bacterial Strains: Latest Research Developments and Future Perspectives. Molecules, 26(9), 2671.https://doi.org/10.3390/molecules26092671
Annunziato. (2019, November 21). Strategies to Overcome Antimicrobial Resistance (AMR) Making Use of Non-Essential Target Inhibitors: A Review. International Journal of Molecular Sciences, 20(23), 5844. https://doi.org/10.3390/ijms20235844
Rittner, A., Joppe, M., Schmidt, J. J., Mayer, L. M., Reiners, S., Heid, E., Herzberg, D., Sherman, D. H., & Grininger, M. (2022, July 25). Chemoenzymatic synthesis of fluorinated polyketides. Nature Chemistry, 14(9), 1000–1006. https://doi.org/10.1038/s41557-022-00996-z
Murugaiyan, J., Kumar, P. A., Rao, G. S., Iskandar, K., Hawser, S., Hays, J. P., Mohsen, Y., Adukkadukkam, S., Awuah, W. A., Jose, R. A. M., Sylvia, N., Nansubuga, E. P., Tilocca, B., Roncada, P., Roson-Calero, N., Moreno-Morales, J., Amin, R., Kumar, B. K., Kumar, A., . . . van Dongen, M. B. M. (2022, February 4). Progress in Alternative Strategies to Combat Antimicrobial Resistance: Focus on Antibiotics. Antibiotics, 11(2), 200. https://doi.org/10.3390/antibiotics11020200
Garza-González, E., Morfín-Otero, R., Mendoza-Olazarán, S., Bocanegra-Ibarias, P., Flores-Treviño, S., Rodríguez-Noriega, E., Ponce-de-León, A., Sanchez-Francia, D., Franco-Cendejas, R., Arroyo-Escalante, S., Velázquez-Acosta, C., Rojas-Larios, F., Quintanilla, L. J., Maldonado-Anicacio, J. Y., Martínez-Miranda, R., Ostos-Cantú, H. L., Gomez-Choel, A., Jaime-Sanchez, J. L., Avilés-Benítez, L. K., & Feliciano-Guzmán, J. M. (2019). A snapshot of antimicrobial resistance in Mexico. Results from 47 centers from 20 states during a six-month period. PLOS ONE, 14(3), e0209865. https://doi.org/10.1371/journal.pone.0209865