Antimicrobial resistance (AMR) is a significant threat to global public health that arises due to the misuse and overuse of antibiotics in humans, animals, and plants.1 In 2019, AMR was responsible for about 1.3 million deaths, with some researchers predicting that it will be responsible for over 10 million deaths by 2050.2
Despite the global burden of AMR, there remains a lack of drug discovery projects dedicated to discovering novel antibiotics that can effectively combat resistant pathogens.
In traditional antibiotic discovery studies, natural compounds originating from soil bacteria, fungi, and plants were screened for their potential antibiotic properties; however, this approach is associated with limited efficiency.
To overcome these challenges, researchers have turned to innovative solutions like digital mining to support modern antibiotic discovery endeavors.
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Why Bacteria are a Key Source of Antibiotics
Antibiosis between microbes was described well before the discovery of penicillin, including by Louis Pasteur, who proposed that microbes could secrete material to kill other bacteria.3”
The first clinical use of an antibiotic dates back to the 1890s, when scientists successfully employed pyocyanase extract from Pseudomonas aeruginosa to treat various pathogenic infections. By the 1930s, Selman Waksman identified the Actinomycetales group as a significant source of antimicrobial compounds, including neomycin and streptomycin—the latter later confirmed as effective against tuberculosis.³
Numerous natural antibiotics isolated from actinomycetes include aminoglycosides, tetracyclines, amphenicols, macrolides, glycopeptides, ansamycins, lincosamides, streptogramins, and cycloserine.⁴
Additionally, Waksman's research led to the discovery of the Streptomyces genus, notable for producing natural products and secondary metabolites active not only against bacteria but also fungi, viruses, nematodes, and insects. Remarkably, from 1945 to 1978, Streptomyces accounted for approximately 55% of all antibiotics discovered during that period.
Penicillin, originally isolated from the fungus Penicillium notatum, remains one of the most significant pharmaceutical discoveries of the last century. Following the identification of penicillin's β-lactam structure in 1945, researchers began exploring methods to create synthetic derivatives, greatly expanding therapeutic options.
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Techniques for Mining Bacterial Genomes
Traditionally, the discovery of novel natural antimicrobials relied on culturing bacteria to identify and isolate bioactive compounds. However, this approach is expensive and labor intensive, which has led researchers to utilize more advanced techniques to support the high-throughput screening of potential antimicrobials from natural products.
Genome mining involves the identification of genes that may contribute to the biosynthesis of natural product scaffold structures. Several companies like DNAnexus, Illumina, and SciBite offer bioinformatic tools, software, and services to support these efforts and prioritize certain gene clusters.
For example, Geneious Biologics offers a package of bioinformatics tools that allow researchers to extract crucial insights from next-generation sequencing (NGS), since cell, and Sanger datasets.6
When a natural compound is identified, significant time and effort are required to identify the molecular targets that may be affected by these products. To overcome this challenge and accelerate target identification, several analytical methods have been developed, some of which include nematic protein organization technique (NPOT), drug affinity responsive target stability (DARTS), stable isotope labeling with amino acids in cell culture, and pulse proteolysis (SILAC-PP), and the cellular thermal shift assay (CETSA).5
Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 technology utilizes guide ribonucleic acid (RNA) to target and insert, delete, or change a specific DNA sequence.
Recently, CRISPR-Cas9 has been used to activate biosynthetic gene clusters in Streptomyces to induce the production of novel metabolites that can be further investigated for their antimicrobial properties.6
CRISPR-Cas9 has also been used to silence genes that encode for specific antibiotics in several Actinomycete strains, which subsequently led to the production of novel and rare antibiotic variants, including amicetin, thiolactomycin, phenanthroviridin, and 5-chloro-3-formylindole.
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Recent Breakthroughs in Bacterial Antibiotic Discovery
Recent high throughput screening of bacteria from soil samples has led to the discovery of several novel antimicrobial compounds with broad activity against multidrug-resistant Gram-positive pathogens like MRSA, methicillin-resistant Streptococcus pneumoniae, and vancomycin-resistant Enterococci.
This effort led to the discovery of teixobactin, a lipid II antibiotic that binds to the wall teichoic acid (WTA) precursor, which allows this compound to induce lysis and killing of bacteria by digesting the cell wall.8
Teixobactin likely evolved to minimize the development of resistance by target microorganisms, thus suggesting that other natural compounds with similarly low susceptibility to resistance have yet to be discovered.
Many natural products can only be produced by the source organism when present in their natural habitat, thus limiting the ability of researchers in a laboratory to isolate bioactive compounds of interest from these microorganisms5 effectively.
To overcome this challenge, researchers have investigated novel cultivation techniques for previously unculturable soil bacteria, an example of which includes a newly designed diffusion bioreactor that can mimic the natural environment.9
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Challenges and Future Directions
There are several challenges associated with natural product-based drug discovery programs, which have led pharmaceutical companies to reduce their investments in bacteria and other natural sources for antimicrobial development.
Although the laws vary by each nation, naturally occurring products in their original form may not always be patentable, thus reducing financial incentives for large companies.
Recent advancements in artificial intelligence (AI) have also been applied to antibiotic drug discovery. For example, researchers from the Broad Institute of Harvard and MIT recently applied deep learning, a type of AI, to identify novel compounds and predict their potential potency against bacteria like methicillin-resistant Staphylococcus aureus (MRSA).7
Nevertheless, the evasiveness of AMR species and their deadly consequences emphasizes the crucial need for both academic and industrial research institutions to remain committed to the discovery of novel antibiotics.
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References
- “Antimicrobial resistance” [Online]. Available from: https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance.
- GBD 2021 Antimicrobial Resistance Collaborators. (2024). Global burden of bacterial antimicrobial resistance 1990-2021: a systematic analysis with forecasts to 2050. The Lancet. doi:10.1016/S0140-6736(24)01867-1.
- Hutchings, M. I., Truman, A. W., & Wilkinson, B. (2019). Antibiotics: past, present, and future. Current Opinion in Microbiology 51; 72-80. doi:10.1016/j.mib.2019.10.008.
- Pancu, D. F., Scurtu, A., Macasoi, I. G., et al. (2021). Antibiotics: Conventional Therapy and Natural Compounds with Antibacterial Activity- A Pharmaco-Toxicological Screening. Antibiotics10(4). doi:10.3390/antibiotics10040401.
- “Geneious Biologics” [Online]. Available from: https://www.geneious.com/features/biologics.
- Atanasov, A. G., Zotchev, S. B., Dirsch, V. M., et al. (2021). Natural products in drug discovery: advances and opportunities. Nature Reviews Drug Discovery 20; 200-216. doi:10.1038/s41573-020-00114-z.
- Wong, F., Zheng, E. J., Valeri, J. A., et al. (2024). Discovery of a structural class of antibiotics with explainable deep learning. Nature 626; 177-185. doi:10.1038/s41586-023-06887-8.
- Ling, L. L., Schneider, T., Peoples, A. J., et al. (2015). A new antibiotic kills pathogens without detectable resistance. Nature 517; 455-459. doi:10.1038/nature14098.
- Chaudhary, D. K., Khulan, A., & Kim, J. (2019). Development of a novel cultivation technique for uncultured soil bacteria. Scientific Reports 9; 6666. doi:10.1038/s41598-019-43182-x.
Further Reading