Ученые разрабатывают биологическое оружие из РНК для уничтожения огненных муравьев в Австралии

Key points Fire ants are invasive pests that, if spread unchecked across Australia, could surpass the annual damage of feral cats, wild dogs, foxes, camels, rabbits and cane toads combined. CSIRO is exploring RNAi technologies that turn fire ant genes against themselves as a precise, safe and scalable way to control fire ant colonies. The approach could inform future control of other invasive species. Fire ants have earned their reputation as one of Australia's most damaging invasive pests. From ruined picnics to serious impacts on agriculture, biodiversity and public health they are notoriously difficult to control. CSIRO researchers are exploring a new approach to help tackle fire ant colonies in a more precise and environmentally considerate way: using a gene silencing technology called RNA interference (RNAi). The research is still underway, but these advances in biological-based technologies could change the future of pest control. RNAi-based fire ant baits can be an additional eco-friendly tool in the toolbox to tackle this difficult pest. Turning the ant's biology against them RNAi is a natural biological process that can be used to interrupt the genetic instructions cells use to make essential proteins. CSIRO researcher Dr Kumaran Nagalingam has been working in pest management for over 15 years and thinks RNAi could make a huge difference for pest control. "Genes act like instruction manuals. When a gene is active, it produces messenger RNA, which tells the cell how to build a specific protein. RNAi works by introducing a matching complementary RNA molecule blocking that instruction and preventing the protein from being produced," Dr Nagalingam explained. "If you silence the right gene, the organism can no longer function normally. "We are not changing the ant's DNA permanently; we are temporarily interrupting messages that tell the ant how to function. The key is choosing the right message to block." Precision pest control RNAi is complex, but Dr Nagalingam finds comparing it to a computer virus helps people understand the basic concept. "Traditional pesticides are a bit like wiping your entire hard drive to get rid of a computer virus. It eliminates the threat, but it affects everything else on the computer too," he said. "By contrast, RNAi is like a highly specific software patch. It's coded to find and neutralise only the malicious virus, leaving your other programs and files running smoothly." "Both approaches are important because different circumstances call for different tools: broad treatments can be essential when fast, wide-ranging control is needed, while highly targeted options may be better when precision and minimising unintended effects are the priority." Finding the needle in a haystack (of needles) Fire ants have tens of thousands of genes, many of which are essential for basic survival. The challenge is identifying which ones to target to achieve the desired result. Dr Amol Bharat Ghodke has been working on RNAi technology for over a decade and has focused on fire ants since 2022. "Our first step is to focus on small sections of genes that are unique to fire ants. Working with specific gene fragments increases precision and reduces the risk of affecting other species. Once a fragment is selected, it is recreated in the laboratory to produce a complementary double stranded RNA molecule," Dr Ghodke said. Multiple gene fragment targets have been tested, and in some cases combined, to explore whether stronger or more consistent effects can be achieved. "We're looking at genes controlling wide range of functions like reproduction, communication, feeding and digestion. "With every trial we've conducted, the results have improved," Dr Ghodke shared. Importantly, Dr Ghodke explained they do not just look at whether a gene can be silenced. They need to study what happens next. "Silencing a gene on its own does not mean much, unless it leads to a measurable impact. We are looking at how gene silencing affects survival, behaviour, reproduction and development in fire ants," Dr Ghodke said. Getting the science where it needs to go One of the biggest challenges when working with social insects is the delivery of the treatment molecule. "Delivery is just as important as the genetics," Dr Nagalingam says. "If the molecule cannot survive the journey being carried by the ant, it will never reach the rest of the colony." The RNAi-based bait must survive environmental exposure, remain stable in an ant's digestive system all the way back to the nest and be able to be transferred and ingested by the rest of the colony. To ensure stable delivery, the team are using a patented RNAi molecule developed at CSIRO. These molecules are expected to improve their chances of travelling through the colony intact and to have greater efficacy than traditional molecules. This focus on delivery and stability is central to making any future RNAi‑based solution practical and scalable. "We're confident that once we have the right formulation, it could be implemented as affordable off the shelf fire ant baits. That's an important part of our research – there's no point creating something effective if it can't be easily distributed and used," Dr Nagalingam said. The ultimate group project While early trials have shown promising results, further work is needed before CSIRO's gene‑silencing approach can be tested outside the laboratory. By building strong scientific foundations now, CSIRO researchers are laying the groundwork for smarter, more targeted biosecurity solutions. CSIRO's fire ant RNAi research is funded by CSIRO's strategic funding, the National Fire Ant Eradication Program and the US Department of Defence through the University of Berkeley. /Public Release. This material from the originating organization/author(s) might be of the point-in-time nature, and edited for clarity, style and length. Mirage.News does not take institutional positions or sides, and all views, positions, and conclusions expressed herein are solely those of the author(s).View in full here.