Scientists Are Growing an Edible Cholera Vaccine in Rice
The world's attention has been focused on the coronavirus crisis but Yemen, Bangladesh and many others countries in Asia and Africa are also in the grips of another pandemic: cholera. The current cholera pandemic first emerged in the 1970s and has devastated many communities in low-income countries. Each year, cholera is responsible for an estimated 1.3 million to 4 million cases and 21,000 to 143,000 deaths worldwide.
Immunologist Hiroshi Kiyono and his team at the University of Tokyo hope they can be part of the solution: They're making a cholera vaccine out of rice.
"It is much less expensive than a traditional vaccine, by a long shot."
Cholera is caused by eating food or drinking water that's contaminated by the feces of a person infected with the cholera bacteria, Vibrio cholerae. The bacteria produces the cholera toxin in the intestines, leading to vomiting, diarrhea and severe dehydration. Cholera can kill within hours of infection if it if's not treated quickly.
Current cholera vaccines are mainly oral. The most common oral are given in two doses and are made out of animal or insect cells that are infected with killed or weakened cholera bacteria. Dukoral also includes cells infected with CTB, a non-harmful part of the cholera toxin. Scientists grow cells containing the cholera bacteria and the CTB in bioreactors, large tanks in which conditions can be carefully controlled.
These cholera vaccines offer moderate protection but it wears off relatively quickly. Cold storage can also be an issue. The most common oral vaccines can be stored at room temperature but only for 14 days.
"Current vaccines confer around 60% efficacy over five years post-vaccination," says Lucy Breakwell, who leads the U.S. Centers for Disease Control and Prevention's cholera work within Global Immunization Division. Given the limited protection, refrigeration issue, and the fact that current oral vaccines require two disease, delivery of cholera vaccines in a campaign or emergency setting can be challenging. "There is a need to develop and test new vaccines to improve public health response to cholera outbreaks."
A New Kind of Vaccine
Kiyono and scientists at Tokyo University are creating a new, plant-based cholera vaccine dubbed MucoRice-CTB. The researchers genetically modify rice so that it contains CTB, a non-harmful part of the cholera toxin. The rice is crushed into a powder, mixed with saline solution and then drunk. The digestive tract is lined with mucosal membranes which contain the mucosal immune system. The mucosal immune system gets trained to recognize the cholera toxin as the rice passes through the intestines.
The cholera toxin has two main parts: the A subunit, which is harmful, and the B subunit, also known as CTB, which is nontoxic but allows the cholera bacteria to attach to gut cells. By inducing CTB-specific antibodies, "we might be able to block the binding of the vaccine toxin to gut cells, leading to the prevention of the toxin causing diarrhea," Kiyono says.
Kiyono studies the immune responses that occur at mucosal membranes across the body. He chose to focus on cholera because he wanted to replicate the way traditional vaccines work to get mucosal membranes in the digestive tract to produce an immune response. The difference is that his team is creating a food-based vaccine to induce this immune response. They are also solely focusing on getting the vaccine to induce antibodies for the cholera toxin. Since the cholera toxin is responsible for bacteria sticking to gut cells, the hope is that they can stop this process by producing antibodies for the cholera toxin. Current cholera vaccines target the cholera bacteria or both the bacteria and the toxin.
David Pascual, an expert in infectious diseases and immunology at the University of Florida, thinks that the MucoRice vaccine has huge promise. "I truly believe that the development of a food-based vaccine can be effective. CTB has a natural affinity for sampling cells in the gut to adhere, be processed, and then stimulate our immune system, he says. "In addition to vaccinating the gut, MucoRice has the potential to touch other mucosal surfaces in the mouth, which can help generate an immune response locally in the mouth and distally in the gut."
Cost Effectiveness
Kiyono says the MucoRice vaccine is much cheaper to produce than a traditional vaccine. Current vaccines need expensive bioreactors to grow cell cultures under very controlled, sterile conditions. This makes them expensive to manufacture, as different types of cell cultures need to be grown in separate buildings to avoid any chance of contamination. MucoRice doesn't require such an expensive manufacturing process because the rice plants themselves act as bioreactors.
The MucoRice vaccine also doesn't require the high cost of cold storage. It can be stored at room temperature for up to three years unlike traditional vaccines. "Plant-based vaccine development platforms present an exciting tool to reduce vaccine manufacturing costs, expand vaccine shelf life, and remove refrigeration requirements, all of which are factors that can limit vaccine supply and accessibility," Breakwell says.
Kathleen Hefferon, a microbiologist at Cornell University agrees. "It is much less expensive than a traditional vaccine, by a long shot," she says. "The fact that it is made in rice means the vaccine can be stored for long periods on the shelf, without losing its activity."
A plant-based vaccine may even be able to address vaccine hesitancy, which has become a growing problem in recent years. Hefferon suggests that "using well-known food plants may serve to reduce the anxiety of some vaccine hesitant people."
Challenges of Plant Vaccines
Despite their advantages, no plant-based vaccines have been commercialized for human use. There are a number of reasons for this, ranging from the potential for too much variation in plants to the lack of facilities large enough to grow crops that comply with good manufacturing practices. Several plant vaccines for diseases like HIV and COVID-19 are in development, but they're still in early stages.
In developing the MucoRice vaccine, scientists at the University of Tokyo have tried to overcome some of the problems with plant vaccines. They've created a closed facility where they can grow rice plants directly in nutrient-rich water rather than soil. This ensures they can grow crops all year round in a space that satisfies regulations. There's also less chance for variation since the environment is tightly controlled.
Clinical Trials and Beyond
After successfully growing rice plants containing the vaccine, the team carried out their first clinical trial. It was completed early this year. Thirty participants received a placebo and 30 received the vaccine. They were all Japanese men between the ages of 20 and 40 years old. 60 percent produced antibodies against the cholera toxin with no side effects. It was a promising result. However, there are still some issues Kiyono's team need to address.
The vaccine may not provide enough protection on its own. The antigen in any vaccine is the substance it contains to induce an immune response. For the MucoRice vaccine, the antigen is not the cholera bacteria itself but the cholera toxin the bacteria produces.
"The development of the antigen in rice is innovative," says David Sack, a professor at John Hopkins University and expert in cholera vaccine development. "But antibodies against only the toxin have not been very protective. The major protective antigen is thought to be the LPS." LPS, or lipopolysaccharide, is a component of the outer wall of the cholera bacteria that plays an important role in eliciting an immune response.
The Japanese team is considering getting the rice to also express the O antigen, a core part of the LPS. Further investigation and clinical trials will look into improving the vaccine's efficacy.
Beyond cholera, Kiyono hopes that the vaccine platform could one day be used to make cost-effective vaccines for other pathogens, such as norovirus or coronavirus.
"We believe the MucoRice system may become a new generation of vaccine production, storage, and delivery system."
Two years, six million deaths and still counting, scientists are searching for answers to prevent another COVID-19-like tragedy from ever occurring again. And it’s a gargantuan task.
Our disturbed ecosystems are creating more favorable conditions for the spread of infectious disease. Global warming, deforestation, rising sea levels and flooding have contributed to a rise in mosquito-borne infections and longer tick seasons. Disease-carrying animals are in closer range to other species and humans as they migrate to escape the heat. Bats are thought to have carried the SARS-CoV-2 virus to Wuhan, either directly or through another host animal, but thousands of novel viruses are lurking within other wild creatures.
Understanding how climate change contributes to the spread of disease is critical in predicting and thwarting future calamities. But the problem is that predictive models aren’t yet where they need to be for forecasting with certainty beyond the next year, as we could for weather, for instance.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers