Fossil findings of insect feeding damage on plants are evidence that insects have been using plants as a food source for more than 400 million years. Researchers led by Roy Kirsch and Yannick Pauchet from the Department of Insect Symbiosis are investigating how herbivorous insects are able to break down the hard-to-digest components of their plant food in the first place. In earlier work, they had already shown that pectin-degrading enzymes are widespread in herbivorous beetle species. They were also able to demonstrate that these beetle enzymes were invariably of microbial origin. The question of the current study was therefore how important these enzymes are for the nutrition and fitness of the insect, in this case the mustard leaf beetle Phaedon cochleariae.

“Our goal was to better understand how herbivorous insects deal with the plant cell wall, which makes the bulk of their diet. Pectin is the matrix embedding cellulose and hemicellulose fibers within the plant cell wall, and it is the main constituent of the cell-connecting middle lamellae. Consequently, pectin must be digested first so that cellulase and hemicellulase enzymes can access their substrates and the plant cells are finally freed from their protective cell wall. In this context, the action of pectinases, i.e. pectin-degrading enzymes, are key to efficient digestion of a leaf beetle’s diet,” says first author Roy Kirsch.

To study the role of the pectinases, the researchers generated beetle lines in which these enzymes were not present. This initially turned out to be more difficult than expected.” “Not even a drastic reduction of pectinase activity through knockdown RNAi experiments in leaf beetle larvae was sufficient to effectively inhibit pectin digestion. We were only able to completely knock-out pectinase-encoding genes in the leaf beetles by applying CRISPR/Cas9 genome editing,” says study leader Yannick Pauchet, underlining the importance of the “genetic scissors,” a technology for which Emmanuelle Charpentier and Jennifer Doudna were awarded the 2020 Nobel Prize in Chemistry.

“Pectinase-null mutant” larvae generated in this way turned out to have low survival capacity. A further question now was whether the degradation products of pectin digestion would improve the survival rate of these beetles when applied orally to the beetle larvae. However, as feeding experiments showed, this was not the case. “On the one hand, this result was a bit of a surprise for us. But on the other hand, it was an important indicator that leaf beetles do not digest pectin to use its breakdown products for their own metabolism, but rather disrupt pectin, and likely other plant cell wall polysaccharides, to access the protein-rich cytoplasm of plant cells,” Roy Kirsch summarizes the results.

Research in recent years, including from Yannick Pauchet’s project group, has shown that the acquisition of microbial enzymes via horizontal gene transfer contributed to the abundance of leaf beetle species, but also of representatives of other insect families, such as weevils, bark beetles and stick insects. The appropriation of enzymes from other microbial organisms is like an evolutionary shortcut; in any case, it created the conditions for insects to open up pectin-rich plants as a food source in the first place. “There is perhaps some irony in the fact that pectinases probably first evolved in plants to dynamically adapt the pectin structure to the changing needs of the plant. These enzymes were then acquired by plant pathogenic microbes, which in turn donated them to herbivorous insects. Plant adaptation strategies apparently always involve risks and side effects,” says Roy Kirsch.

However, there are also leaf beetle species that harbor symbiotic bacteria that produce pectinases for their hosts. So-called “knockin” experiments, in which a pectinase gene is introduced into the beetle genome using CRISPR-Cas9, are now planned to show how this new beetle trait affects not only interactions between plants and insects, but also interactions between insects and their bacterial partners. Future studies will also focus on other enzymes that do not degrade pectin but other plant cell wall components. The work of Roy Kirsch, Yannick Pauchet and their team shows that for an insect to survive on a host plant, it is not only the adaptation to plant defenses, such as toxins and feeding inhibitors and other secondary metabolites, which is crucial. The scientists rather focus on the primary metabolism, which has been neglected in research on plant-insect interactions so far. “The ability of an insect to digest these primary metabolites is equally important for the evolutionary success of herbivorous insects,” says Yannick Pauchet.

Story Source:

Materials provided by Max Planck Institute for Chemical Ecology. Note: Content may be edited for style and length.

Perhaps that will change soon. Because the position and shape of the cavities are like a kind of fingerprint: they can be used to identify fossil plant remains. “Until now, it was not known how these cavities were formed,” explains Mahdieh Malekhosseini from the Institute of Geosciences at the University of Bonn. “For example, it was believed that they came from algae or pollen from other plants that somehow got onto the leaf during fossilization. But after analyzing hundreds of these structures, we can rule that out. Instead, we were able to show that calcium oxalate crystals are responsible for the depressions.”

Microlenses for better photosynthesis?

Calcium oxalate is formed by very many living plants; it is considered one of the most common biominerals. What functions it fulfills has not yet been conclusively clarified. However, it is suspected that the crystals serve as calcium stores. In addition, because they are formed in the leaf but often penetrate the leaf surface as they grow, they probably repel pests. “Many insects have an aversion to calcium oxalate — they don’t like to walk on it,” explains Prof. Dr. Jes Rust, who supervised the study. “Some plants also seem to use the crystals as microlenses to use sunlight more efficiently for photosynthesis.”

The crystals are very sensitive to acid. They therefore dissolve during fossilization and can no longer be detected in the millions of years old finds. Often, however, imprints remain in the places where they have sat (in biology one speaks of “druses”). Sometimes organic material or other minerals also accumulate in these depressions, which then sit like tiny beads in the fossil leaf.

“We studied the microstructure of the pits and their distribution on fossil leaves whose species affiliation we knew,” Malekhosseini explains. “In addition, we looked at calcium oxalate crystals in the leaves of present-day plants. We found clear parallels in closely related species. For example, the crystal imprints in a fossil ginkgo leaf strongly resemble the calcium oxalate deposits of a present-day ginkgo in distribution and structure.”

Important insights into evolution

It was already known from the fossils of bare-seeded plants such as firs or pines that they sometimes show imprints of calcium oxalate crystals. However, this was not known of angiosperms — which are most flowers and deciduous trees. “This is a completely new field of research,” explains Jes Rust. “Among other things, we now want to investigate how the ability to form calcium oxalate crystals has developed over the course of evolution.” In doing so, the researchers want to focus on periods when environmental conditions changed rapidly — such as temperature or the intensity of UV radiation. “If the distribution of the drusen also changes after such incisions, then we can draw conclusions about the biological function of the crystals,” says Rust.

Story Source:

Materials provided by University of Bonn. Note: Content may be edited for style and length.

The Russian invasion of Ukraine has highlighted the depth of Europe’s dependence on Russian natural gas imports. The REPowerEU plan, released by the European Commission, maps a European Union-wide pathway to reduce Russian natural imports by two-thirds by the end of 2022, with the complete elimination of Russian gas by 2027. Overall, there are only four main policy levers in the short term: increase pipeline gas and liquified natural gas imports from non-Russian sources, reduce gas demand in heating and industry, reduce gas-fired electricity generation and adopt flexible gas storage targets.

A research team including Binghamton University engineer Neha Patankar has created a power sector model for Europe and a gas network model to analyze multiple feasible pathways to secure full independence from Russian natural gas. Patankar is an operations research analyst with a research focus on energy system and power system modeling. Her research aims to provide insights for constructing a robust decision under parametric and structural uncertainty. Her research also includes the evaluation of low-carbon technologies and the effects of policy scenarios on energy systems.

The team modeled European natural gas and electricity systems to assess the feasibility and potential impact of a near-complete embargo on imports of Russian natural gas to Europe beginning in October.

It found that Europe can eliminate reliance on Russian natural gas by augmenting REPowerEU plans with a temporary boost in coal and recalibrated gas storage.

“All successful gas independence pathways increase reliance on coal-fired electricity generation but reduce overall greenhouse gas emissions due to offsets from lower gas demand,” said Patankar, assistant professor in Binghamton University’s Department of Systems Science and Industrial Engineering.

To be successful these actions will have to be sustained for the next two winters, Patankar said.

“Increasing renewables, electrification of heating and liquified natural gas imports will steadily replace the current policy levers and maintain Europe’s long-term energy transition,” she said.

Contributing to this research were Michael Lau, a second-year PhD student in the Department of Mechanical and Aerospace Engineering, Princeton University; Wilson Ricks, a fourth-year PhD student in the Department of Mechanical and Aerospace Engineering, Princeton University; Jesse Jenkins, an assistant professor of mechanical and aerospace engineering and the Andlinger Center for Energy and the Environment.

The commentary article, “Europe’s way out: Tools to rapidly eliminate imports of Russian natural gas,” was published in Joule.

Story Source:

Materials provided by Binghamton University. Note: Content may be edited for style and length.

IAV is responsible for 250,000-500,000 deaths per year worldwide. When IAV infects its host, an immunological response composed of a series of molecular processes begins. IAV can infect several different species, and physiological and genetic differences among these species can contribute to different host responses, although some responses are shared.

“Identifying key defense processes and key regulators in multiple species can facilitate the development of treatments for IAV in humans,” said Bin Zhang, PhD, Director of the Center for Transformative Disease Modeling, Willard T.C. Johnson Research Professor of Neurogenetics, and Professor of Genetics and Genomic Sciences at Icahn Mount Sinai, who led the study.

The study used RNA sequencing to analyze gene expression over time in cells and tissues collected from IAV-infected humans, ferrets, and mice, identifying multiple key defense processes specific to tissues and species. One gene found to play a key role in immunological defense mechanisms against IAV across all species was TDRD7, whichencodes a Tudor domain-containing protein, a type of protein shown to be involved in epigenetic regulation. In light of this discovery, the researchers conducted subsequent experiments inhibiting the function of TDRD7, resulting in an increase of virus replication in IAV-infected models.

“Identifying both common and species-specific responses to influenza is essential in developing effective therapies for the flu and can help inform future research of other respiratory infections, such as COVID-19,” said Christian Forst, PhD, Assistant Professor of Genetics and Genomic Sciences, and Microbiology, at Icahn Mount Sinai and a first author of the study.

Co-first authors on the research team also include Laura Martin-Sancho, PhD, Staff Scientist at Scripps Research, California, and Shashank Tripathi, PhD, Assistant Professor, Microbiology and Cell Biology, Centre for Infectious Disease Research, Indian Institute of Science, Bangalore.

Senior authors on the research team also include Adolfo García-Sastre, PhD, Irene and Dr. Arthur M. Fishberg Professor of Medicine and Director of the Global Health and Emerging Pathogens Institute at Icahn Mount Sinai in New York, and Elodie Ghedin, PhD, Chief of the Systems Genomics Section and Deputy Chief of the Laboratory of Parasitic Diseases at the National Institute of Allergy and Infectious Diseases, National Institutes of Health.

This study was supported by the National Institute of Allergy and Infectious Disease (NIAID) of the National Institutes of Health (NIH) under award numbers R21AI149013, U01AI111598, U19AI106754, U19AI135972, U19AI142733, and U19AI168631 and NIAID-funded Center for Research on Influenza Pathogenesis (CRIP) and Center of Excellence for Influenza Research and Response (CEIRR, contract #75N93021C00014).

The algorithms are unique in that they take a holistic approach to action anticipation, combining visual data — for example, where an athlete is located on the court — with information that is more implicit, like an athlete’s specific role on the team.

“Computer vision can interpret visual information such as jersey color and a player’s position or body posture,” said Silvia Ferrari, the John Brancaccio Professor of Mechanical and Aerospace Engineering, who led the research. “We still use that real-time information, but integrate hidden variables such as team strategy and player roles, things we as humans are able to infer because we’re experts at that particular context.”

Ferrari and doctoral students Junyi Dong and Qingze Huo trained the algorithms to infer hidden variables the same way humans gain their sports knowledge — by watching games. The algorithms used machine learning to extract data from videos of volleyball games, and then used that data to help make predictions when shown a new set of games.

The results were published Sept. 22 in the journal ACM Transactions on Intelligent Systems and Technology, and show the algorithms can infer players’ roles — for example, distinguishing a defense-passer from a blocker — with an average accuracy of nearly 85%, and can predict multiple actions over a sequence of up to 44 frames with an average accuracy of more than 80%. The actions included spiking, setting, blocking, digging, running, squatting, falling, standing and jumping.

Ferrari envisions teams using the algorithms to better prepare for competition by training them with existing game footage of an opponent and using their predictive abilities to practice specific plays and game scenarios.

Ferrari has filed for a patent and is now working with the Big Red men’s hockey team to further develop the software. Using game footage provided by the team, Ferrari and her graduate students, led by Frank Kim, are designing algorithms that autonomously identify players, actions and game scenarios. One goal of the project is to help annotate game film, which is a tedious task when performed manually by team staff members.

“Our program places a major emphasis on video analysis and data technology,” said Ben Russell, director of hockey operations for the Cornell men’s team. “We are constantly looking for ways to evolve as a coaching staff in order to better serve our players. I was very impressed with the research Professor Ferrari and her students have conducted thus far. I believe that this project has the potential to dramatically influence the way teams study and prepare for competition.”

Beyond sports, the ability to anticipate human actions bears great potential for the future of human-machine interaction, according to Ferrari, who said improved software can help autonomous vehicles make better decisions, bring robots and humans closer together in warehouses, and can even make video games more enjoyable by enhancing the computer’s artificial intelligence.

“Humans are not as unpredictable as the machine learning algorithms are making them out to be right now,” said Ferrari, who is also associate dean for cross-campus engineering research, “because if you actually take into account all of the content, all of the contextual clues, and you observe a group of people, you can do a lot better at predicting what they’re going to do.”

The research was supported by the Office of Naval Research Code 311 and Code 351, and commercialization efforts are being supported by the Cornell Office of Technology Licensing.

Story Source:

Materials provided by Cornell University. Original written by Syl Kacapyr, courtesy of the Cornell Chronicle. Note: Content may be edited for style and length.