Completed Infection & Immunity Genetics & Molecular Biology

Exploring Natures Silent Pharmacy

In plain English

AI plain-English summary

Fungi harbour thousands of silent gene clusters that could produce new antibiotics, but these pathways remain switched off under normal lab conditions. Researchers will extract these genetic instructions from ten diverse fungi—including insect pathogens, marine species, and soil dwellers—and transplant them into *Aspergillus oryzae*, a fungus that grows easily in the lab and at industrial scale. Each target fungus likely contains 40 to 60 such cryptic gene clusters, far more than previously suspected. This matters because antibiotic resistance is a growing crisis, and traditional drug-discovery programmes have largely exhausted the easily accessible compounds from fungi. The team will build plasmid vectors that can express up to 16 genes at once, then purify any new products and test them against clinically relevant bacteria, including strains with known resistance profiles. If successful, the pipeline could unlock a hidden reservoir of natural antibiotics, potentially yielding compounds with novel modes of action that bypass existing resistance mechanisms. This is fundamental science with a clear translational goal: finding new chemical scaffolds that pharmaceutical companies could develop into drugs. Even compounds that fail as antibiotics will reveal new biosynthetic chemistry, expanding our understanding of how fungi produce their molecular arsenal.

View original technical description
Fungi have proven to be an important source of bioactive compounds in the past, with penicillins, cephalosporins and statins amongst the best examples. Recent developments in the ease with which we can sequence the genomes of fungi have revealed that fungi house a hitherto unexpectedly large number of gene clusters which appear to encode pathways for secondary metabolites, yet their chemical products are unknown and have not been evaluated in drug-discovery programmes. This suggests that there are many beneficial products yet to be discovered and exploited and these may include new classes of antibiotic which could be deployed to help combat the ongoing problems with antibiotic resistance. Based on genome sequence data already available for selected target fungi, plus with generation of such data for other selected species of interest, we will develop a pipeline to quickly catalogue such gene clusters and to then design plasmid vectors to allow their expression in the fungus Aspergillus oryzae, a species which is very amenable to lab and industrial-scale cultivation. The use of a lab-friendly host fungus is necessary because our experience is that these gene clusters are usually cryptic; not usually expressed under laboratory conditions by the native fungus, and with products that cannot be predicted with any degree of confidence from genome data alone. The target fungi are each predicted to contain 40-60 such gene clusters based on what is typical for other fungi. The plasmid vectors will be constructed in a series of expression cassettes we have already developed and tested, and will be made using a combination of yeast-based homologous recombination cloning, augmented by Gibson Assembly where necessary. This will be achieved using PCR products derived directly from genomic DNA, or where this is not readily achievable, by use of synthetic DNA designed from genome data. Such approaches should be readily scalable for high throughput use if they prove to be successful in our studies. Our vector sets will allow coordinated expression of up to four genes per plasmid, with four different selectable markers available, meaning we can expect to readily express pathways comprising 16 genes, and could upgrade this system for additional genes should this prove necessary, which is ample capacity for the majority of pathways encountered in fungi. Transformants of A. oryzae will then be analysed to determine if a new product is produced, and if so, this will be purified by reverse-phase HPLC with analysis by MS and by nmr to elucidate the structure. Milligram quantities will be purified to allow antibacterial assays against a range of clinically-relevant pathogens to determine antibacterial efficacy for each compound. For compound displaying antibacterial properties, each compound will be evaluated against a range of bacteria displaying characterised resistance to antibiotics to quickly eliminate any compounds showing known modes of action or those where resistance is already prevalent. For products passing this evaluation, we aim to fully characterise the biosynthetic pathway, including isolation of the intermediate stages in their biosynthesis and to identify products suited to further chemical modification to support studies into structure-activity relationships in this group of compounds. Our aim is to design a production pipeline that will allow us to investigate every candidate gene cluster from an initial group of ten selected fungi. The isolates selected for this study have been chosen to span a range of differing lifestyles, including insect, fungal and plant pathogens, marine fungi and soil fungi. This would help to inform future choice of strains for a wider scale analysis in a second round of screening should there be time available.

View the original record at the funder ↗

Researchers

Andrew Bailey (Principal Investigator)Chris Willis (Co-Investigator)Colin Lazarus (Co-Investigator)Gary Foster (Co-Investigator)James Spencer (Co-Investigator)Matthew Avison (Co-Investigator)Paul Race (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

Unearthing fungal chemodiversity
Exploiting natural product assembly line genomics and synthetic biology for discovery and optimisation of novel agrochemicals
Exploring the metabolic diversity of engineered fungal non-ribosomal peptide synthetase-like enzymes for the development of novel antibiotics
Back to soil: awakening the production of cryptic antibiotics in Streptomyces strains
Mode-of-Action and Spectrum of a Novel Fungicide Target

Original classification

Research Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.