Declining numbers of insects, coupled with climate change, can have devastating effects for people in more ways than one. But clever use of technologies like AI could keep them buzzing.
And because many insects serve as food for other species—bats, birds and freshwater fish—they’re an integral part of the ecosystem’s food chain. “If you like to eat good food, you should thank an insect,” says Scott Hoffman Black, an ecologist and executive director of the Xerces Society for Invertebrate Conservation in Portland, Oregon. “And if you like birds in your trees and fish in your streams, you should be concerned with insect conservation.”
Deforestation, urbanization, and agricultural spread have eaten away at large swaths of insect habitat. The increasingly poorly controlled use of insecticides, which harms unintended species, and the proliferation of invasive insect species that disrupt native ecosystems compound the problem.
“There is not a single reason why insects are in decline,” says Jessica L. Ware, associate curator in the Division of Invertebrate Zoology at the American Museum of Natural History in New York, and president of the Entomological Society of America. “There are over one million described insect species, occupying different niches and responding to environmental stressors in different ways.”
Jessica Ware, an entomologist at the American Museum of Natural History, is using DNA methods to monitor insects.
Credit:D.Finnin/AMNH
In addition to habitat loss fueling the decline in insect populations, the other “major drivers” Ware identified are invasive species, climate change, pollution, and fluctuating levels of nitrogen, which play a major role in the lifecycle of plants, some of which serve as insect habitants and others as their food. “The causes of world insect population declines are, unfortunately, very easy to link to human activities,” Lehmann says.
Climate change will undoubtedly make the problem worse. “As temperatures start to rise, it can essentially make it too hot for some insects to survive,” says Emily McDermott, an assistant professor in the Department of Entomology and Plant Pathology at the University of Arkansas. “Conversely in other areas, it could potentially also allow other insects to expand their ranges.”
Without Pollinators Humans Will Starve
We may not think much of our planet’s getting warmer by only one degree Celsius, but it can spell catastrophe for many insects, plants, and animals, because it’s often accompanied by less rainfall. “Changes in precipitation patterns will have cascading consequences across the tree of life,” says David Wagner, a professor of ecology and evolutionary biology at the University of Connecticut. Insects, in particular, are “very vulnerable” because “they’re small and susceptible to drying.”
For instance, droughts have put the monarch butterfly at risk of being unable to find nectar to “recharge its engine” as it migrates from Canada and New England to Mexico for winter, where it enters a hibernation state until it journeys back in the spring. “The monarch is an iconic and a much-loved insect,” whose migration “is imperiled by climate change,” Wagner says.
Warming and drying trends in the Western United States are perhaps having an even more severe impact on insects than in the eastern region. As a result, “we are seeing fewer individual butterflies per year,” says Matt Forister, a professor of insect ecology at the University of Nevada, Reno.
There are hundreds of butterfly species in the United States and thousands in the world. They are pollinators and can serve as good indicators of other species’ health. “Although butterflies are only one group among many important pollinators, in general we assume that what’s bad for butterflies is probably bad for other insects,” says Forister, whose research focuses on butterflies. Climate change and habitat destruction are wreaking havoc on butterflies as well as plants, leading to a further indirect effect on caterpillars and butterflies.
Different insect species have different levels of sensitivity to environmental changes. For example, one-half of the bumblebee species in the United States are showing declines, whereas the other half are not, says Christina Grozinger, a professor of entomology at the Pennsylvania State University. Some species of bumble bees are even increasing in their range, seemingly resilient to environmental changes. But other pollinators are dwindling to the point that farmers have to buy from the rearing facilities, which is the case for the California almond industry. “This is a massive cost to the farmer, which could be provided for free, in case the local habitats supported these pollinators,” Lehmann says.
For bees and other insects, climate change can harm the plants they depend on for survival or have a negative impact on the insects directly. Overly rainy and hot conditions may limit flowering in plants or reduce the ability of a pollinator to forage and feed, which then decreases their reproductive success, resulting in dwindling populations, Grozinger explains.
“Nutritional deprivation can also make pollinators more sensitive to viruses and parasites and therefore cause disease spread,” she says. “There are many ways that climate change can reduce our pollinator populations and make it more difficult to grow the many fruit, vegetable and nut crops that depend on pollinators.”
Disease-Causing Insects Can Bring More Outbreaks
While some much-needed insects are declining, certain disease-causing species may be spreading and proliferating, which is another reason for human concern. Many mosquito types spread malaria, Zika virus, West Nile virus, and a brain infection called equine encephalitis, along with other diseases as well as heartworms in dogs, says Michael Sabourin, president of the Vermont Entomological Society. An animal health specialist for the state, Sabourin conducts vector surveys that identify ticks and mosquitoes.
Scientists refer to disease-carrying insects as vector species and, while there’s a limited number of them, many of these infections can be deadly. Fleas were a well-known vector for the bubonic plague, while kissing bugs are a vector for Chagas disease, a potentially life-threatening parasitic illness in humans, dogs, and other mammals, Sabourin says.
As the planet heats up, some of the creepy crawlers are able to survive milder winters or move up north. Warmer temperatures and a shorter snow season have spawned an increasing abundance of ticks in Maine, including the blacklegged tick (Ixodes scapularis), known to transmit Lyme disease, says Sean Birkel, an assistant professor in the Climate Change Institute and Cooperative Extension at the University of Maine.
Coupled with more frequent and heavier precipitation, rising temperatures bring a longer warm season that can also lead to a longer period of mosquito activity. “While other factors may be at play, climate change affects important underlying conditions that can, in turn, facilitate the spread of vector-borne disease,” Birkel says.
For example, if mosquitoes are finding fewer of their preferred food sources, they may bite humans more. Both male and female mosquitoes feed on sugar as part of their normal behavior, but if they aren’t eating their fill, they may become more bloodthirsty. One recent paper found that sugar-deprived Anopheles gambiae females go for larger blood meals to stay in good health and lay eggs. “More blood meals equals more chances to pick up and transmit a pathogen,” McDermott says, He adds that climate change could reduce the number of available plants to feed on. And while most mosquitoes are “generalist sugar-feeders” meaning that they will likely find alternatives, losing their favorite plants can make them hungrier for blood.
Similar to the effect of losing plants, mosquitoes may get turned onto people if they lose their favorite animal species. For example, some studies found that Culex pipiens mosquitoes that transmit the West Nile virus feed primarily on birds in summer. But that changes in the fall, at least in some places. Because there are fewer birds around, C. pipiens switch to mammals, including humans. And if some disease-carrying insect species proliferate or increase their ranges, that increases chances for human infection, says McDermott. “A larger concern is that climate change could increase vector population sizes, making it more likely that people or animals would be bitten by an infected insect.”
Science Can Help Bring Back the Buzz
To help friendly insects thrive and keep the foes in check, scientists need better ways of trapping, counting, and monitoring insects. It’s not an easy job, but artificial intelligence and molecular methods can help. Ware’s lab uses various environmental DNA methods to monitor freshwater habitats. Molecular technologies hold much promise. The so-called DNA barcodes, in which species are identified using a short string of their genes, can now be used to identify birds, bees, moths and other creatures, and should be used on a larger scale, says Wagner, the University of Connecticut professor. “One day, something akin to Star Trek’s tricorder will soon be on sale down at the local science store.”
Scientists are also deploying artificial intelligence, or AI, to identify insects in agricultural systems and north latitudes where there are fewer bugs, Wagner says. For instance, some automated traps already use the wingbeat frequencies of mosquitoes to distinguish the harmless ones from the disease-carriers. But new technology and software are needed to further expand detection based on vision, sound, and odors.
“Because of their ubiquity, enormity of numbers, and seemingly boundless diversity, we desperately need to develop molecular and AI technologies that will allow us to automate sampling and identification,” says Wagner. “That would accelerate our ability to track insect populations, alert us to the presence of new disease vectors, exotic pest introductions, and unexpected declines.”
Basecamp Research is using portable labs like this one to gather samples from ecosystems around the world.
Clark works for Basecamp Research, a biotech company headquartered in London, and his job is to collect samples from ecosystems around the world. By extracting DNA from soil, water, plants, microbes and other organisms, Basecamp is building an extensive database of the Earth’s proteins. While DNA itself isn’t a protein, the information stored in DNA is used to create proteins, so extracting, sequencing, and annotating DNA allows for the discovery of unique protein sequences.
Using what they’re finding in the middle of the Atlantic and beyond, Basecamp’s detailed database is constantly growing. The outputs could be essential for cleaning up the damage done by toxic chemicals and finding alternatives to these chemicals.
Catalysts for change
Proteins provide structure and function in all living organisms. Some of these functional proteins are enzymes, which quite literally make things happen.
“Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development. Biocatalysis is providing advantages, both to make more complex drugs and to be more sustainable, reducing the pollution and toxicity of conventional chemistry," says Ahir Pushpanath, who heads partnerships for Basecamp.
“Enzymes are perfectly evolved catalysts,” says Ahir Pushpanath, a partnerships lead at Basecamp. ”Enzymes are essentially just a polymer, and polymers are made up of amino acids, which are nature’s building blocks.” He suggests thinking about it like Legos — if you have a bunch of Lego pieces and use them to build a structure that performs a function, “that’s basically how an enzyme works. In nature, these monuments have evolved to do life’s chemistry. If we didn’t have enzymes, we wouldn’t be alive.”
In our own bodies, enzymes catalyze everything from vision to digesting food to regrowing muscles, and these same types of enzymes are necessary in the pharmaceutical, agrochemical and fine chemical industries. But industrial conditions differ from those inside our bodies. So, when scientists need certain chemical reactions to create a particular product or substance, they make their own catalysts in their labs — generally through the use of petroleum and heavy metals.
These petrochemicals are effective and cost-efficient, but they’re wasteful and often hazardous. With growing concerns around sustainability and long-term public health, it's essential to find alternative solutions to toxic chemicals. “Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development,” Pushpanath says.
Basecamp is trying to replace lab-created catalysts with enzymes found in the wild. This concept is called biocatalysis, and in theory, all scientists have to do is find the right enzymes for their specific need. Yet, historically, researchers have struggled to find enzymes to replace petrochemicals. When they can’t identify a suitable match, they turn to what Pushpanath describes as “long, iterative, resource-intensive, directed evolution” in the laboratory to coax a protein into industrial adaptation. But the latest scientific advances have enabled these discoveries in nature instead.
Marlon Clark, a research scientist at Basecamp Research, looks for novel biochemistries in the Azores.
Glen Gowers
Enzyme hunters
Whether it’s Clark and a colleague setting off on an expedition, or a local, on-the-ground partner gathering and processing samples, there’s a lot to be learned from each collection. “Microbial genomes contain complete sets of information that define an organism — much like how letters are a code allowing us to form words, sentences, pages, and books that contain complex but digestible knowledge,” Clark says. He thinks of the environmental samples as biological libraries, filled with thousands of species, strains, and sequence variants. “It’s our job to glean genetic information from these samples.”
“We can actually dream up new proteins using generative AI," Pushpanath says.
Basecamp researchers manage this feat by sequencing the DNA and then assembling the information into a comprehensible structure. “We’re building the ‘stories’ of the biota,” Clark says. The more varied the samples, the more valuable insights his team gains into the characteristics of different organisms and their interactions with the environment. Sequencing allows scientists to examine the order of nucleotides — the organic molecules that form DNA — to identify genetic makeups and find changes within genomes. The process used to be too expensive, but the cost of sequencing has dropped from $10,000 a decade ago to as low as $100. Notably, biocatalysis isn’t a new concept — there have been waves of interest in using natural enzymes in catalysis for over a century, Pushpanath says. “But the technology just wasn’t there to make it cost effective,” he explains. “Sequencing has been the biggest boon.”
AI is probably the second biggest boon.
“We can actually dream up new proteins using generative AI,” Pushpanath says, which means that biocataylsis now has real potential to scale.
Glen Gowers, the co-founder of Basecamp, compares the company’s AI approach to that of social networks and streaming services. Consider how these platforms suggest connecting with the friends of your friends, or how watching one comedy film from the 1990s leads to a suggestion of three more.
“They’re thinking about data as networks of relationships as opposed to lists of items,” says Gowers. “By doing the same, we’re able to link the metadata of the proteins — by their relationships to each other, the environments in which they’re found, the way those proteins might look similar in sequence and structure, their surrounding genome context — really, this just comes down to creating a searchable network of proteins.”
On an Azores island, this volcanic opening may harbor organisms that can help scientists identify enzymes for biocatalysis to replace toxic chemicals.
Emma Bolton
Uwe Bornscheuer, professor at the Institute of Biochemistry at the University of Greifswald, and co-founder of Enzymicals, another biocatalysis company, says that the development of machine learning is a critical component of this work. “It’s a very hot topic, because the challenge in protein engineering is to predict which mutation at which position in the protein will make an enzyme suitable for certain applications,” Bornscheuer explains. These predictions are difficult for humans to make at all, let alone quickly. “It is clear that machine learning is a key technology.”
Benefiting from nature’s bounty
Biodiversity commonly refers to plants and animals, but the term extends to all life, including microbial life, and some regions of the world are more biodiverse than others. Building relationships with global partners is another key element to Basecamp’s success. Doing so in accordance with the access and benefit sharing principles set forth by the Nagoya Protocol — an international agreement that seeks to ensure the benefits of using genetic resources are distributed in a fair and equitable way — is part of the company's ethos. “There's a lot of potential for us, and there’s a lot of potential for our partners to have exactly the same impact in building and discovering commercially relevant proteins and biochemistries from nature,” Clark says.
Bornscheuer points out that Basecamp is not the first company of its kind. A former San Diego company called Diversa went public in 2000 with similar work. “At that time, the Nagoya Protocol was not around, but Diversa also wanted to ensure that if a certain enzyme or microorganism from Costa Rica, for example, were used in an industrial process, then people in Costa Rica would somehow profit from this.”
An eventual merger turned Diversa into Verenium Corporation, which is now a part of the chemical producer BASF, but it laid important groundwork for modern companies like Basecamp to continue to scale with today’s technologies.
“To collect natural diversity is the key to identifying new catalysts for use in new applications,” Bornscheuer says. “Natural diversity is immense, and over the past 20 years we have gained the advantages that sequencing is no longer a cost or time factor.”
This has allowed Basecamp to rapidly grow its database, outperforming Universal Protein Resource or UniProt, which is the public repository of protein sequences most commonly used by researchers. Basecamp’s database is three times larger, totaling about 900 million sequences. (UniProt isn’t compliant with the Nagoya Protocol, because, as a public database, it doesn’t provide traceability of protein sequences. Some scientists, however, argue that Nagoya compliance hinders progress.)
“Eventually, this work will reduce chemical processes. We’ll have cleaner processes, more sustainable processes," says Uwe Bornscheuer, a professor at the University of Greifswald.
With so much information available, Basecamp’s AI has been trained on “the true dictionary of protein sequence life,” Pushpanath says, which makes it possible to design sequences for particular applications. “Through deep learning approaches, we’re able to find protein sequences directly from our database, without the need for further laboratory-directed evolution.”
Recently, a major chemical company was searching for a specific transaminase — an enzyme that catalyzes a transfer of amino groups. “They had already spent a year-and-a-half and nearly two million dollars to evolve a public-database enzyme, and still had not reached their goal,” Pushpanath says. “We used our AI approaches on our novel database to yield 10 candidates within a week, which, when validated by the client, achieved the desired target even better than their best-evolved candidate.”
Basecamp’s other huge potential is in bioremediation, where natural enzymes can help to undo the damage caused by toxic chemicals. “Biocatalysis impacts both sides,” says Gowers. “It reduces the usage of chemicals to make products, and at the same time, where contamination sites do exist from chemical spills, enzymes are also there to kind of mop those up.”
So far, Basecamp's round-the-world sampling has covered 50 percent of the 14 major biomes, or regions of the planet that can be distinguished by their flora, fauna, and climate, as defined by the World Wildlife Fund. The other half remains to be catalogued — a key milestone for understanding our planet’s protein diversity, Pushpanath notes.
There’s still a long road ahead to fully replace petrochemicals with natural enzymes, but biocatalysis is on an upward trajectory. "Eventually, this work will reduce chemical processes,” Bornscheuer says. “We’ll have cleaner processes, more sustainable processes.”
In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”