Ensuring genetic diversity of crops with the ability to modify plant mitochondrial DNA

A mitochondrial gene that causes cytoplasmic male infertility was deleted using a mitoTALENs technique. Infertile rice (right) stands straight, but fertile rice (left) bends under the weight of heavy seeds. Image by Tomohiko Kazama, CC-BY

Tool could ensure genetic diversity of crops

Researchers in Japan have edited plant mitochondrial DNA for the first time, which could lead to a more secure food supply.

Nuclear DNA was first edited in the early 1970s, chloroplast DNA was first edited in 1988, and animal mitochondrial DNA was edited in 2008. However, no tool previously successfully edited plant mitochondrial DNA.

Researchers used their technique to create four new lines of rice and three new lines of rapeseed (canola).

“We knew we were successful when we saw that the rice plant was more polite — it had a deep bow,” said Associate Professor Shin-ichi Arimura, joking about how a fertile rice plant bends under the weight of heavy seeds.

Arimura is an expert in plant molecular genetics at the University of Tokyo and led the research team, whose results were published in Nature Plants. Collaborators at Tohoku University and Tamagawa University also contributed to the research.

Genetic diversity for the food supply

Researchers hope to use the technique to address the current lack of mitochondrial genetic diversity in crops, a potentially devastating weak point in our food supply.

In 1970, a fungal infection arrived on Texas corn farms and was exacerbated by a gene in the corn’s mitochondria. All corn on the farms had the same gene, so none were resistant to the infection. Fifteen percent of the entire American corn crop was killed that year. Corn with that specific mitochondrial gene has not been planted since.

“We still have a big risk now because there are so few plant mitochondrial genomes used in the world. I would like to use our ability to manipulate plant mitochondrial DNA to add diversity,” said Arimura.

Plants without pollen

Most farmers do not save seeds from their harvest to replant next year. Hybrid plants, the first-generation offspring of two genetically different parents, are usually hardier and more productive.

To ensure farmers have fresh, first-generation hybrid seeds each season, agricultural supply companies produce seeds through a separate breeding process using two different parents. One of those parents is male infertile — it cannot make pollen.

Researchers refer to a common type of plant male infertility as cytoplasmic male sterility (CMS). CMS is a rare but naturally occurring phenomenon caused primarily by genes not in the nucleus of the cells, but rather the mitochondria.

Green beans, beets, carrots, corn, onions, petunia, rapeseed (canola) oil, rice, rye, sorghum, and sunflowers can be grown commercially using parents with CMS-type male infertility.

The plant mitochondria rapidly moving around the cell (Arabidopsis leaf epidermal cell) in this video were artificially made to glow green, but are shown at their actual speed. Plant mitochondria move about 10 times faster than mammalian or yeast mitochondria. Video by Shin-ichi Arimura CC-BY

Beyond green

Plants use sunlight to produce most of their energy, through photosynthesis in green-pigmented chloroplasts. However, chloroplasts’ fame is overrated, according to Arimura.

“Most of a plant isn’t green, only the leaves above the ground. And many plants don’t have leaves for half the year,” said Arimura.

Plants get a significant portion of their energy through the same “powerhouse of the cell” that produces energy in animal cells: the mitochondria.

“No plant mitochondria, no life,” said Arimura.

Mitochondria contain DNA completely separate from the cell’s main DNA, which is stored in the nucleus. Nuclear DNA is the long double-helix genetic material inherited from both parents. The mitochondrial genome is circular, contains far fewer genes, and is primarily inherited only from mothers.

The animal mitochondrial genome is a relatively small molecule contained in a single circular structure with remarkable conservation between species.

“Even a fish’s mitochondrial genome is similar to a human’s,” said Arimura.

Plant mitochondrial genomes are a different story.

“The plant mitochondrial genome is huge in comparison, the structure is much more complicated, the genes are sometimes duplicated, the gene expression mechanisms are not well-understood, and some mitochondria have no genomes at all – in our previous studies, we observed that they fuse with other mitochondria to exchange protein products and then separate again,” said Arimura.

Manipulating plant mitochondrial DNA

To find a way to manipulate the complex plant mitochondrial genome, Arimura turned to collaborators familiar with the CMS systems in rice and rapeseed (canola). Prior research strongly suggested that in both plants, the cause of CMS was a single, evolutionarily unrelated mitochondrial gene in rice and in rapeseed (canola): clear targets in the perplexing maze of plant mitochondrial genomes.

Arimura’s team adapted a technique that had previously edited mitochondrial genomes of animal cells growing in a dish. The technique, called mitoTALENs, uses a single protein to locate the mitochondrial genome, cut the DNA at the desired gene, and delete it.

“While deleting most genes creates problems, deleting a CMS gene solves a problem for plants. Without the CMS gene, plants are fertile again,” said Arimura.

The fully fertile four new lines of rice and three new lines of rapeseed (canola) that researchers created are a proof of concept that the mitoTALENs system can successfully manipulate even the complex plant mitochondrial genome.

“This is an important first step for plant mitochondrial research,” said Arimura.

Researchers will study the mitochondrial genes responsible for plant male infertility in more detail and identify potential mutations that could add much-needed diversity.

Learn more: Researchers can finally modify plant mitochondrial DNA

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Deep learning enables automatic neurological disease diagnosis

Figure 1: A new deep neural network system for automatic diagnosis of neurological diseases (MNet) is shown in the left panel and the result of the triplet classification of epilepsy, spinal cord injury, and healthy subjects is shown in the right panel. Conv: convolutional layer; Fc: fully connected layer; HS: healthy subjects; EP: patients with epilepsy; SCI: patients with spinal cord injury.
Credit: Jo Aoe

Analyzing brain waveforms using neuroimaging big data helps improve diagnosis accuracy

A team of researchers from Osaka University and The University of Tokyo developed MNet, an automatic diagnosis system for neurological diseases using magnetoencephalography (MEG) (Figure 1), demonstrating the possibility of making automatic neurological disease diagnoses using MEG. Their research results were published in Scientific Reports.

MEG and electroencephalography (EEG) are essential for diagnosing neurological diseases such as epilepsy. MEG allows for the acquisition of detailed temporal-spatial patterns of human brain activity through the measurement of electro-magnetic field associated with neural activity, extracting detailed time-series signals from 160 sensors. Although information obtained from these tests is important for diagnosis, time and expertise are necessary for reading and analyzing, and abnormal waveform patterns may be missed.

Deep Neural Network (DNN), also known as deep learning, is a subset of machine learning in artificial intelligence (AI) and has drawn attention in recent years as a means for classifying data on various images, videos, and sounds at a high accuracy through a machine learning process using big data.

The AI-powered automatic classification system MNet, which utilizes DNN as a computational framework, is based on a neural network called EnvNet (end-to-end convolutional neural network for environmental sound classification) and can be trained to extract and learn features of neuroimaging signals unique to various neurological diseases from a massive amount of time-series neuroimaging data.

The team expected that the use of DNN would allow for the system to learn the characteristics of neurological diseases from many signals and classify patients with neurological diseases more accurately than conventional methods using waveforms.

With MNet, they tried to classify neuroimaging big data on 140 patients with epilepsy, 26 patients with spinal cord injuries, and 67 healthy subjects. The trained MNet succeeded in classifying healthy subjects and those with the two neurological diseases with an accuracy of over 70% and patients with epilepsy and healthy subjects with an accuracy of nearly 90%. The classification accuracy was significantly higher than that obtained by a support vector machine (SVM), a conventional general machine learning method based on waveforms (relative band powers of EEG signal). Moving forward, this technique will be used for diagnosis of various neurological diseases, evaluation of severity, prognosis, and efficacy of treatment.

“Machine learning is constantly advancing, with new techniques being developed all the time. However, no matter how much analytical methods advance, if the quality of underlying data is poor, a sharp distinction cannot be drawn. We carried out the process of machine learning by utilizing DNN, which processed big data mainly from the Osaka University Hospital Epilepsy Center. We’d like to increase the number and the types of diseases to be diagnosed without sacrificing quality of data so that our technique will be helpful in clinical practice,” says researcher Jo Aoe of Osaka University.

Learn more: Automatic neurological disease diagnosis using deep learning

 

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A new process dramatically cleans up ammonia production and cuts costs substantially

This is the SWAP process in action. It efficiently converts 90 percent of raw material to ammonia in one go, whereas the Haber-Bosch process only converts 10 percent.
CREDIT: Yoshiaki Nishibayashi

UTokyo researchers dramatically clean up ammonia production and cut costs

Ammonia – a colorless gas essential for things like fertilizer – can be made by a new process which is far cleaner, easier and cheaper than the current leading method. UTokyo researchers use readily available lab equipment, recyclable chemicals and a minimum of energy to produce ammonia. Their Samarium-Water Ammonia Production (SWAP) process promises to scale down ammonia production and improve access to ammonia fertilizer to farmers everywhere.

In 1900, the global population was under 2 billion, whereas in 2019, it is over 7 billion. This population explosion was fueled in part by rapid advancements in food production, in particular the widespread use of ammonia-based fertilizers. The source of this ammonia was the Haber-Bosch process, and though some say it’s one of the most significant achievements of all time it comes with a heavy price.

The Haber-Bosch process only converts 10 percent of its source material per cycle so needs to run multiple times to use it all up. One of these source materials is hydrogen (H2) produced using fossil fuels. This is chemically combined with nitrogen (N2) at temperatures of about 400-600 degrees Celsius and pressures of about 100-200 atmospheres, also at great energy cost. Professor Yoshiaki Nishibayashi and his team from the University of Tokyo’s Department of Systems Innovation hope to improve the situation with their SWAP process.

“Worldwide, the Haber-Bosch process consumes 3 to 5 percent of all natural gas produced, around 1 or 2 percent of the world’s entire energy supply,” explained Nishibayashi. “In contrast, leguminous plants have symbiotic nitrogen-fixing bacteria that produce ammonia at atmospheric temperatures and pressures. We isolated this mechanism and reverse engineered its functional component – nitrogenase.”

Over many years, Nishibayashi and his team used lab-made catalysts to try and reproduce the way nitrogenase behaves. Others have tried but their catalysts only produce dozens to several hundred ammonia molecules before they expire. Nishibayashi’s special molybdenum-based catalyst produces 4,350 ammonia molecules in about four hours before it expires.

“Our SWAP process creates ammonia at 300-500 times the rate of the Haber-Bosch process and at 90 percent efficiency,” continued Nishibayashi. “Factor in the gargantuan energy savings in the process and sourcing of raw materials and the benefits really show.”

Anyone with the proper source materials can perform SWAP on a table-top chemistry lab, whereas the Haber-Bosch process requires large-scale industrial equipment. This could afford access to those who lack the capital to invest in such large, expensive equipment. The raw materials themselves are a huge saving in terms of cost and energy.

“A strong motivation was to make the SWAP process possible on a desktop scale. I hope to see this process democratize production of fertilizers,” said Nishibayashi. “So it’s not just about the upfront costs but also the continued cost and energy savings of raw materials. My team offers this idea to help agricultural practices in the places which need it the most.”

SWAP takes in nitrogen (N2) from the air – as the Haber-Bosch process does – but the special molybdenum-based catalyst combines this with protons (H+) from water and electrons (e-) from samarium (SmI2). Samarium – also known as Kagan’s reagent – is currently mined and is used up in the SWAP process. However samarium can be recycled with electricity to replenish its lost electrons and researchers aim to use cheap renewable sources for this in the future.

“I was pleasantly surprised when we found something as common as water could serve as the proton source; a molybdenum catalyst does not normally allow this, but ours is special,” concluded Nishibayashi. “It is the first artificial nitrogen-fixing reaction to reach a rate close to that we see nitrogenase produce in nature. And like the natural process, it is passive, too, so better for the environment. I hope my life’s work can be of great benefit to humanity.”

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Breakthrough in spintronics

UTokyo researchers created sample devices to aid future researchers explore potential applications.
Credit: The Institute for Solid State Physics

Electric currents drive all our electronic devices. The emerging field of spintronics looks to replace electric currents with what are known as spin currents.

Researchers from the University of Tokyo have made a breakthrough in this area. Their discovery of the magnetic spin Hall effect could lead to low-power, high-speed and high-capacity devices. They have created sample devices which can further research into potential applications.

“Electricity lit up the world and electronics connected it,” says Professor Yoshichika Otani from the Institute for Solid State Physics. “Spintronics will be the next step forward in this procession and we can only imagine what advances it may bring.”

So what is spintronics and why should we be excited?

“In essence spintronics is used to transfer information, something we have always used electric currents for,” continues Otani, “but spintronics offers a whole range of advantages, some of which we’re just starting to understand.”

Currently, power efficiency of electrical and electronic devices is a limiting factor in technological development. The problem lies in the nature of electric currents, the flow of charge in the form of electrons. As electrons traverse a circuit they lose some energy as waste heat. Spintronics improves upon the situation – instead of movement it exploits another property of electrons to transfer information, their angular momentum or “spin”.

“In spin currents electrons still move but far less than in a charge current,” explains Otani. “It’s the movement of electrons that typically leads to resistance and waste heat. As we reduce the need for so much electron movement we improve efficiency dramatically.”

To demonstrate this phenomenon researchers created a new kind of material called a ‘non-collinear antiferromagnet’ – Mn3Sn which is a special kind of magnet. In everyday magnets – or ferromagnets – such as you might find on fridge doors, the spins of the electrons within align in parallel which imbues the material with its magnetic effect. In this antiferromagnet the spins of the electrons line up in triangular arrangements such that no one direction is prevalent and the magnetic effect is effectively suppressed.

When a small electric current is fed into Mn3Sn and a magnetic field is applied to it in just the right way, the electrons order themselves according to their spin and electrical current flows. This is the magnetic spin Hall effect, and the process can be reversed with the magnetic inverse spin Hall effect to get an electric current from a spin current.

In Mn3Sn alike spins tend to accumulate on the surface of the material, so it’s cut into thin layers to maximize its surface area and thus the capacity of spin current a sample carries. The researchers have already embedded this material into a functional device to serve as a test bed for possible applications and are excited by the prospects.

“Power efficiency in electrical systems is enough to pique the interest of some, but the use of antiferromagnets to generate spin currents could improve other aspects of technology too,” says Otani. “Antiferromagnets more easily miniaturized, operate at higher frequencies and pack more densely than ferromagnets.”

But how do these ideas translate into applications?

“Miniaturization means spintronic devices could be made into microchips,” continues Otani. “High frequencies mean spintronic chips could outperform electronic ones in operation speed, and higher density leads to greater memory capacity. Also low dissipation in spin currents at room temperatures improves power efficiency further still.”

Devices based on the traditional spin Hall effect already exist in spintronics research but the magnetic spin Hall effect and novel materials used could vastly improve all kinds of technology.

“There is still much work to do including exploration of the underlying principles behind the phenomenon we investigate,” concludes Otani. “Driven by mysteries of exotic materials, I’m thrilled to be part of this technological revolution.”

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Electric fields and ultraviolet light set the stage for programming using chemistry

Columnar liquid crystals are similar in size to current semiconductor transistors. Image: Aida Group

Engineers from UTokyo and RIKEN perform computational logic with light

For the first time, researchers performed logic operations — the basis of computation — with a chemical device using electric fields and ultraviolet light. The device and the pioneering methods used open up research possibilities including low-power, high-performance computer chips.

Computers need an upgrade. From smartwatches to data centers, all computers feature similar kinds of components, including processors and memory. These semiconductor chips comprise minuscule electronic transistors on beds of silicon. Such devices cannot be made much smaller because of how matter behaves at the quantum scale they’re approaching. For this reason and more, engineers devise new ways and materials to perform logic and memory functions.

Doctoral student Keiichi Yano, Lecturer Yoshimitsu Itoh and Professor Takuzo Aida from the Department of Chemistry and Biotechnology at the University of Tokyo and their team developed a device which demonstrates functions useful to computation. Conventional computers use electric charge to represent binary digits (1’s and 0’s), but the engineers’ device uses electric fields and UV light. These allow for lower power operation and create less heat than logic based on electric charge.

The device is also vastly different from current semiconductor chips as it is chemical in nature, and it’s this property that gives rise to its potential usefulness in the future of computation. It’s not just the power and heat benefit; this device could be manufactured cheaply and easily too. The device features disk and rod-shaped molecules that self-assemble into spiral staircase-like shapes called columnar liquid crystals (CLC) in the right conditions.

“One thing I love about creating a device using chemistry is that it’s less about ‘building’ something; instead it’s more akin to ‘growing’ something,” says Itoh. “With delicate precision, we coax our compounds into forming different shapes with different functions. Think of it as programming with chemistry.”

Before a logic operation begins, the researchers sandwich a sample of CLCs between two glass plates covered in electrodes. Light that is polarized — always vibrates in a single plane — passes through the sample to a detector on the other side.

In the sample’s default state, the CLCs exist in a randomly oriented state which allows the light to reach the detector. When either the electric field or UV light is individually switched on then off, the detected output remains the same. But when the electric field and UV light are switched on together and then off again after about a second, the CLCs line up in a way which blocks the detector from the light.

If the “output” states of light and dark, and the “input” states of the electric field and UV light are all assigned binary digits to identify them, then the process has effectively performed what is called a logical AND function — all inputs to the function must be “1” for the output to be “1.”

“The AND function is one of several fundamental logic functions, but the most important one for computation is the NOT-AND or NAND function. This is one of several areas for further research,” explains Yano. “We also wish to increase the speed and density of the CLCs to make them more practical for use. I’m fascinated by how self-assembling molecules like those we use to make the CLCs give rise to phenomena such as logical functions.”

Learn more: Light up logic

 

 

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