Page 1,026«..1020..1,0251,0261,0271,028..1,0401,050..»

This Rwandan Engineer is Learning How to Manage Humanitarian Projects – IEEE Spectrum

After several years of volunteering for IEEE humanitarian technology projects, Samantha Mugeni Niyoyita decided she needed more than just technical skills to help underserved communities become more self-sufficient. The IEEE member from Kigali, Rwanda, participated in installing portable sinks in nearby rural markets to curb the spread of COVID-19 and provided clean water and sanitation services to people displaced by the Mount Nyiragongo volcano eruption in 2021.

Niyoyita wanted to learn how to tackle other issues such as access to quality health care, understanding different cultures, and becoming familiar with local policies. And she felt she needed to enhance her leadership and communications skills and learn how to manage projects.

Thanks to a scholarship from IEEE Smart Village, she is now getting that education through the masters degree program in development practice from Regis University, in Denver. The program, offered virtually and in person, combines theory and hands-on training on topics such as community outreach and engagement, health care, the environment, and sustainability. It teaches leadership and other soft skills.

In addition to bringing electricity to remote communities, IEEE Smart Village offers educational and employment opportunities. To be eligible for its scholarship, the students thesis project must support the programs mission.

Niyoyita, who attends classes remotely, is a process engineer at Africa Improved Foods, also in Kigali. AIF manufactures porridge from maize and other cereals and fortifies it with vitamins and minerals. She has worked there for more than four years.

Smart Village wants to empower its members so that we can implement projects in our local community knowing what the best practices are, she says.

She acknowledges she would not have been able to afford to attend Regis without help from IEEE.

Niyoyita is now in the second year of the degree program. Her research project is to assess the impact of digitizing the medical records of primary care clinics, known as health posts, in rural Rwanda.

The health post records are mostly paper-based, and transitioning to electronic records would improve patient outcomes, Niyoyita says. This provides easy access to records and improves coordination of care.

She plans to evaluate just how access to electronic records by health care professionals can improve patient care.

Her scholarship of US $5,045 was funded by donations to IEEE Smart Village. Since the educational program was launched in 2015, more than 30 individuals from 16 countries have participated.

I was fortunate to receive this scholarship, she says. It has helped me a lot when it comes to soft skills. As an engineer, normally we tend to be very technical. Expressing ourselves and sharing our skills and expertise are the kinds of things you can only learn through a social science masters degree.

As a youngster, Niyoyita was more interested in subjects that required her to reason and think creatively instead of memorizing information. She excelled at mathematics and physics.

That was how I got into engineering, she says, adding that she also was inspired by her brother, an engineer.

The degree from Regis is in addition to those Niyoyita already holds from the University of Applied Sciences and Arts, known as HES-SO Valais-Wallis, in Sion, Switzerland. She earned a bachelors degree in industrial systems engineering in 2015 and a masters in engineering with a concentration in mechatronics in 2017.

She chose to study industrial engineering, she says, because she finds it to be a discipline that offers numerous pathways to various fields and career opportunities. Im able to understand concept designswhich includes mechanical and electricalprogramming, and automation. You have a wealth of career opportunities and a chance to make an impact.

IEEE Smart Village wants to empower its members so that we can implement projects in our local community knowing what the best practices are.

At AIF, she analyzes the companys processes to identify bottlenecks in the manufacturing line, and she proposes ways to fix them.

We receive these cereals and clean and grind them, she says. We have a cooking section and fortify the cereals through mixing. Then we package and sell them.

She evaluates the production flow and checks on the performance of the equipment. In addition, she provides technological support when new products are being developed.

AIF is benefiting from the training shes receiving from the masters degree program, she says, as she is learning to lead teams, provide innovative solutions, and collaborate with others.

Niyoyita joined IEEE while a student at HES-SO Valais-Wallis because she needed access to its journals for her research papers. After she graduated, she continued her membership and started volunteering for IEEE Smart Village in 2019. She served as a secretary for its Africa Working Group team, which worked on humanitarian projects.

She also got involved in organizing conferences in Africa. Her first event was the 2019 PowerAfrica Conference, held in Abuja, Nigeria. It covered emerging power system technologies, applications, government policies, and regulatory frameworks. As a member of the conferences technical program committee, she helped develop the program and reviewed article submissions. She also was a speaker on the IEEE Women in Engineering panel.

Based on that positive experience, she says, she vowed to bring the conference to Rwandawhich she did last year. As cochair, she oversaw the budget, conference logistics, and other arrangements to ensure that local and foreign attendees had an excellent experience, she says. More than 300 people from 43 countries attended.

One project that Niyoyita has put on the back burner because of her work and school commitments is providing her countrys technicians with the skills they need to become entrepreneurs.

Many recent graduates of vocational technical schools in rural Rwanda have told her they want to start their own company, she says, but she has noticed they lack the skills to do so.

Even though they provide problem-solving products or ideas, they often lack the marketing skills and financial literacy to be able to sustain their project, she says. They also need to know how to pitch an idea and make a proposal so they can get funding.

She would like to create an after-school incubation hub to provide the technicians with training, access to the Internet so they can flesh out their ideas, mentorship opportunities, and advisors who can tell them where to find financing.

I was able to get some of the skills from the masters degree program, she says, but most of them I got from my work and also from my involvement in IEEE.

From Your Site Articles

Related Articles Around the Web

More:

This Rwandan Engineer is Learning How to Manage Humanitarian Projects - IEEE Spectrum

Read More..

Towards artificial photosynthesis with engineering of protein crystals … – Science Daily

In-cell engineering can be a powerful tool for synthesizing functional protein crystals with promising catalytic properties, show researchers at Tokyo Tech. Using genetically modified bacteria as an environmentally friendly synthesis platform, the researchers produced hybrid solid catalysts for artificial photosynthesis. These catalysts exhibit high activity, stability, and durability, highlighting the potential of the proposed innovative approach.

Protein crystals, like regular crystals, are well-ordered molecular structures with diverse properties and a huge potential for customization. They can assemble naturally from materials found within cells, which not only greatly reduces the synthesis costs but also lessens their environmental impact.

Although protein crystals are promising as catalysts because they can host various functional molecules, current techniques only enable the attachment of small molecules and simple proteins. Thus, it is imperative to find ways to produce protein crystals bearing both natural enzymes and synthetic functional molecules to tap their full potential for enzyme immobilization.

Against this backdrop, a team of researchers from Tokyo Institute of Technology (Tokyo Tech) led by Professor Takafumi Ueno has developed an innovative strategy to produce hybrid solid catalysts based on protein crystals. As explained in their paper published in Nano Letters on 12 July 2023, their approach combines in-cell engineering and a simple in vitro process to produce catalysts for artificial photosynthesis.

The building block of the hybrid catalyst is a protein monomer derived from a virus that infects the Bombyx mori silkworm. The researchers introduced the gene that codes for this protein into Escherichia coli bacteria, where the produced monomers formed trimers that, in turn, spontaneously assembled into stable polyhedra crystals (PhCs) by binding to each other through their N-terminal -helix (H1). Additionally, the researchers introduced a modified version of the formate dehydrogenase (FDH) gene from a species of yeast into the E. coli genome. This gene caused the bacteria to produce FDH enzymes with H1 terminals, leading to the formation of hybrid H1-FDH@PhC crystals within the cells.

The team extracted the hybrid crystals out of the E. coli bacteria through sonication and gradient centrifugation, and soaked them in a solution containing an artificial photosensitizer called eosin Y (EY). As a result, the protein monomers, which had been genetically modified such that their central channel could host an eosin Y molecule, facilitated the stable binding of EY to the hybrid crystal in large quantities.

Through this ingenious process, the team managed to produce highly active, recyclable, and thermally stable EYH1-FDH@PhC catalysts that can convert carbon dioxide (CO2) into formate (HCOO) upon exposure to light, mimicking photosynthesis. In addition, they maintained 94.4% of their catalytic activity after immobilization compared to that of the free enzyme. "The conversion efficiency of the proposed hybrid crystal was an order of magnitude higher than that of previously reported compounds for enzymatic artificial photosynthesis based on FDH," highlights Prof. Ueno. "Moreover, the hybrid PhC remained in the solid protein assembly state after enduring both in vivo and in vitro engineering processes, demonstrating the remarkable crystallizing capacity and strong plasticity of PhCs as encapsulating scaffolds."

Overall, this study showcases the potential of bioengineering in facilitating the synthesis of complex functional materials. "The combination of in vivo and in vitro techniques for the encapsulation of protein crystals will likely provide an effective and environmentally friendly strategy for research in the areas of nanomaterials and artificial photosynthesis," concludes Prof. Ueno.

Go here to read the rest:

Towards artificial photosynthesis with engineering of protein crystals ... - Science Daily

Read More..

The best way to show off your emerging A.I. skills to land a job: You dont need years of experience’ yet – CNBC

The job market for tech workers remains strong, and especially so for those picking up emerging artificial intelligence skills.

The U.S. in particular is leading the way in growing its AI workforce, with some 169,045 open jobs calling for the skill in June, according to the global search platform Adzuna, and another 3,575 focused on generative AI work. For comparison, India was hiring for 25,900 AI jobs and the UK was hiring for 16,825 roles involving the skill in June.

Generative AI jobs are a "hot area at the moment," says James Neave, Adzuna's head of data science, with more and more roles calling for candidates knowledgeable in large language models like ChatGPT, DALL-E, LLaMA, PALM 2 and others.

But given the emerging and quickly developing nature of the tools, it can be tricky to display your expertise in a particular AI skill as a job candidate, Neave says.

"This really only kicked off in the last 12 months," he says, with ChatGPT exploding onto the scene in late 2022, and so "it's such an emergent area, no one can claim to have years of experience in this thing because it hasn't existed that long."

With that being said, Neave recommends interested job applicants build up their AI skills and stand out from the competition in three key ways:

Some of the most common AI-related jobs employers are hiring for right now include software engineer, product designer, deep learning architect and data scientist.

AI could be a reliable skill in an unpredictable market that's seen some big-name tech layoffs in recent months, Neave says, and those looking for high-paying roles should keep a pulse on AI in the second half of the year in particular.

Want to be smarter and more successful with your money, work & life?Sign up for our new newsletter!

Take your business to the next level: Register for CNBC's freeSmall Business Playbook virtual eventon August 2 at 1 p.m. ET to learn from premier experts and entrepreneurs how you can beat inflation, hire top talent and get access to capital.

Check out: Stanford and MIT study: A.I. boosted worker productivity by 14%those who use it will replace those who dont

Originally posted here:

The best way to show off your emerging A.I. skills to land a job: You dont need years of experience' yet - CNBC

Read More..

CWDN series: DevEx D2iQ: The platform engineering experience – ComputerWeekly.com

This is a guest post for the Computer Weekly Developer Network written Deepak Goel, CTO of D2iQ.

With many pressures being put on them, DevOps teams simply cant keep up with the Ops demands.

This is why platform engineering is gaining momentum, as it advocates for building a centrally managed developer platform shared by multiple teams, instead of having each team build and run its own platform.

This approach ensures that critical infrastructure tasks like security, governance and observability are done once and done right, instead of being haphazard and duplicate efforts.

To maximise developer productivity, the platform engineering team must manage the infrastructure and create an internal platform for developers.

This removes much of the operational burden from the developers, allowing them to focus on building business applications. Platform engineering solves the complexity and skills gap challenges by providing a ready-made internal developer platform and golden path for DevOps teams, enabling them to devote their labor to creating business value rather than struggling to build a container management platform.

The workforce is no longer dependent on the infrastructure and there is one process for managing an organisations fleet instead of operational silos and duplicate efforts.

Deepak Goel, CTO of D2iQ.

Concurrently, the internal developer platform provides the abstraction and automation that helps developers build, test and deploy applications easily. Consider a scenario where there are multiple DevOps teams working on different projects within an organisation.

Each DevOps team will choose its own infrastructure, from the cloud to on-premise based on their needs. They will use their own tools and scripts to manage the lifecycle of the infrastructure, including provisioning and upgrades. They will also have their own measures for security, resulting in a structure that creates a self-service environment.

However, without platform engineering and internal developer platforms, it often leads to redundancy in operational efforts.

Each team has to execute the same lifecycle operations for their own infrastructure, creating silos that ultimately lead to the uneconomical use of infrastructure resources. Including DevOps within the framework of platform engineering brings standardisation and consistency, while maintaining the self-service environment DevOps teams have come to expect. In the above scenario, platform engineering teams centralise many of the operations needed to manage the lifecycle of the infrastructure, ensuring optimal use of the infrastructure resources by sharing them across various teams.

In addition, this approach provides a self-service internal developer platform environment within the security guardrails established by the platform engineering team.

Platform engineering makes developers more productive while simultaneously avoiding any pitfalls, improving an organizations overall ROI.

See original here:

CWDN series: DevEx D2iQ: The platform engineering experience - ComputerWeekly.com

Read More..

The lost art of cloud application engineering – InfoWorld

AI is changing the programming world, which has been evolving for several years. I could talk about how the emerging practice of using AI-driven coders increases speed and reduces costs, but there are some downsides that many fail to see.

Again, the question is not Can we? Its Should we? Lets go over a few core concerns.

AI-driven coders learn from existing code repositories. They often need a more contextual understanding of the code generated. They produce code that works but may need help to comprehend or maintain. This hinders developers control over their software and often causes mistakes when fixing or changing applications.

Moreover, the generated code must meet style conventions or best practices and include appropriate error handling. This can make debugging, maintenance, and collaboration difficult.

Remember that AI-driven code generation focuses on learning from existing code patterns to generate net-new code. Generative AI coders have a monkey see, monkey do approach to development, whereas the coding approaches are learned from the vast amount of code used as training data.

This approach is helpful for repetitive or standard tasks, which is much of what developers do, but enterprises may require more creativity and innovation for complex or unique problems. Using generative AI code can limit the potential for novel solutions and hinder the development of truly innovative applications.

Not sure if youve looked out there, but innovation is lacking. We seem to be building the same things over and over again.

My biggest concern is that code could be more efficient and optimized for the platform the application is deployed on. It takes sound engineering practices to understand how to optimize processors, memory, and storage management.

I think that many people will generate and deploy an application without understanding how it could leverage resources in a more optimized way. We end up with applications that are more expensive to run and have a much larger carbon footprint.

The shame is that, in most cases, just the fact that the application works is good enough for many. The applications operate for years, waste a great deal of money, and fail to return the optimal value to the business. Oh, well, people say, it works, doesnt it?

Another scary aspect of AI-driven development is that many security vulnerabilities are left within the application and go unnoticed until the postmortem after a breach. Again, we need human engineering to spot and fix those, albeit some helpful AI-driven scanning tools can be practical.

By removing humans from the development process, which many organizations are looking to do, we sacrifice the understanding needed to create practical applications. The appropriate answer is to find a balance between the value of AI in terms of speed and cost and the fact that many human skills still need to be involved. I fear that we wont understand that until its too late.

Visit link:

The lost art of cloud application engineering - InfoWorld

Read More..

Vijayasarathi Balasubramanian: At the Zenith of Data Insights and Invention Science Mastery – LatestLY

Vijayasarathi Balasubramanian

In the fast-paced world of data science and artificial intelligence, one name stands out as a true pioneer - Vijayasarathi Balasubramanian, popularly known as Vijay. With his remarkable contributions to the field of data insights and invention science, Vijay has emerged as a trailblazer, making significant strides in revolutionizing the way we approach data and AI. His journey from a young engineer to a Lead Data Scientist at Microsoft is nothing short of inspiring, and his accomplishments have earned him numerous accolades and awards from esteemed organizations.

Vijay's journey into the world of data science began with a Bachelor's degree in Electrical Engineering from Thiagarajar College of Engineering in Madurai, Tamil Nadu(India). It was during his early career that he first explored the power of AI, applying machine learning to create recommender systems for e-commerce and businesses. This groundbreaking work caught the attention of industry giants, and he soon found himself working in the IT divisions of fortune 50 companies like The Home Depot(USA), British Telecom(UK) and AT&T.

However, his thirst for knowledge and passion for data science led him to pursue a Masters in Data Science from the renowned University of Notre Dame in Indiana, USA. Armed with advanced techniques and algorithms, Vijay embarked on a journey to create enterprise-scale data products and solve real-world problems using cutting-edge machine-learning approaches.

What truly sets Vijay apart is his commitment to continuous learning and mentorship. With over 17 years of hands-on professional experience in data ingestion, insights, and inventive science, he has become a beacon for aspiring data scientists. Vijay's passion and expertise have empowered large corporations to harness machine learning on a massive scale, unlocking endless possibilities in the field. His pursuit of knowledge is evident through his impressive collection of 20+ technical certifications and awards from renowned institutions and platforms like Amazon Web Services, Microsoft Azure, Coursera, Udacity, and more.

Vijay's influence extends beyond the professional sphere, as he is a senior member of IEEE, a Fellow of the British Computer Society, and a member of the esteemed Forbes Technology Council. His dedication to mentorship shines through his involvement with platforms like ADPList and GrowthMentor, where he guides and nurtures the next generation of science start-up founders. Additionally, his passion for a positive societal impact is evident through his volunteer work with Friends of the Children and his association with Correlation One.

His remarkable achievements have not gone unnoticed, and in 2023, he was honored with the "IT Professional of the Year" award from GOLD GLOBEE and the prestigious "International Achievers Award" from IAF India.

With an indomitable spirit and an insatiable appetite for progress, Vijay plans to establish a cutting-edge Research Institute dedicated to advanced data analytics, machine learning, and invention science. Such an institute would position Vijay as a global leader in these fields, fostering innovation, driving groundbreaking research, and serving as a hub for technological advancements. Collaboration with academic institutions and industry partners would amplify the impact of this endeavor, further solidifying his legacy as a data science pioneer.

Read more:

Vijayasarathi Balasubramanian: At the Zenith of Data Insights and Invention Science Mastery - LatestLY

Read More..

Engineering faculty take on innovative climate resilience projects – University of California, Santa Cruz

From building more efficient greenhouses to improving wildfire management, Baskin Engineering professors are leading three major projects to address climate crisis issues with funding from UCSCs newly launched Center for Coastal Climate Resilience.

The Center recently announced a total of more than $4.6 million in award funding for efforts to fight climate change in coastal communities across California and beyond. All three of the projects led by engineering faculty are pilot awards, meaning they were previously unfunded efforts to address climate impacts and solutions.

We are very excited about these new initiatives as we continue to build capacity, expertise and partnerships, said Anne Criss, Assistant Dean of the Baskin School of Engineering who is coordinating climate change-related projects at the school. Engineering is here to provide meaningful contributions to improving our resilience to climate change, playing an essential role not only in finding technical solutions to reducing greenhouse gas emissions, but also in helping coastal communities adapt to our changing climate.

Coastal Monitoring

Principal Investigator: Professor of Computer Science and Engineering Alex PangCo-Investigators: Associate Research Professor of Institute of Marine Sciences Borja RegueroCollaborators: Professor of Environmental Studies and Director of the Coastal Science and Policy Program Anne Kapuscinski, Senior Scientist at NOAA Gregory Dusek, Research Geologist at USGS Jonathan Warrick, and David Gutierrez of Solutions and Services.

Sea level rise poses a great threat to coastal communities such as Santa Cruz, and a prerequisite for protecting those communities is a deep understanding of those threats and the risks they pose. This project will employ a machine learning-based algorithm to analyze changes in the Santa Cruz shoreline and nearshore dynamics such as rip currents using video from a network of webcams in the study area. The shoreline data captured at various time scales and rip current occurrence data can be used for climate modeling, prediction, and policy making, such as long-term studies on sea level rise and rip currents to help with beach safety. The software will be open source so it can be replicated for other settings and extended for future projects.

Greener Greenhouses

Principal Investigator: Professor of Computer Science and Engineering Katia ObraczkaCo-Investigators: Assistant Professor of Electrical and Computer Engineering Colleen Josephson, Professor of Environmental Studies Michael Loik, Assistant Professor of Electrical Engineering and Computer Science at UC Merced Wan Du

As extreme weather threatens agricultural production and about a third of the worlds population does not have access to adequate food, greenhouses are an important aspect of climate resilience in the global food production system. Katia Obraczka and her team will develop greenhouses equipped with an Internet of Things system that continuously monitors conditions such as airflow, temperature, humidity or light throughout the greenhouse to optimize resource usage such as water and fertilizer, while improving food production. The system will employ LiFi, a low-power wireless communication technology that uses light waves emitted by LEDs for ultra-low-power and efficient communication. LEDs will also be used to provide supplemental illumination for the plants as well as energy sources for the light-powered IoT sensing nodes. The LiFi IoT will also be used to control greenhouse elements such as vents, lights, and irrigation pumps. The LiFi-based IoT technology will be open source, making it accessible to small, local farmers. Ultimately, the team hopes to show that plants grow as well or better in greener greenhouses than current methods, while reducing the amount of water, electricity, and labor used to grow healthy food in addition to operating battery-free.

Firefighter Toolkits

Principal Investigator: Professor of Electrical and Computer Engineering Ricardo SanfeliceCo-Investigators: Director of the CITRIS Initiative for Drone Research Becca Fenwick, Associate Professor of Mechanical Engineering at UC Berkeley Michael Gollner, Professor of Computational Media Katherine Ibister, Assistant Professor of Electrical and Computer Engineering Steve McGuire, Professor of Computer Science and Engineering Katia Obraczka, Professor of Civil and Environmental Engineering at UC Berkeley Raja Sengupta (UCB), Professor of Civil and Environmental Engineering at UC Berkeley Kenichi Soga, and co-founder and director of the Monterey Bay Drone, Automation and Robotics Technology initiative Chris Bley.

Extreme wildfires have increasingly plagued communities throughout the US and across the world, from Santa Cruz to Canada to the Australian outback. And though wildfires are a natural element of a healthy ecosystem, droughts, climate change, and the buildup of fuels have made them more severe. Ricardo Sanfelice and his team plan to take advantage of recent technological advances to create an innovative system for wildfire prevention, prediction, management, and suppression using aviation, communication, sensing, and decision-making technology. The system will provide ongoing information about environmental factors including wind speed and direction, potential actions, and patterns. It will also efficiently guide the deployment of firefighters, their vehicles and resources, and other assets. The goal is to have these systems be easily integrated into existing toolkits used by firefighters, and to provide training curriculum and policy recommendations for its implementation. In the pilot phase of this project, the researchers will focus on developing a suite of software, deploying aircrafts for data collection in high-risk areas of California, and beginning the creation of curriculum and policy.

Continue reading here:

Engineering faculty take on innovative climate resilience projects - University of California, Santa Cruz

Read More..

Altair Expands Digital Engineering Technology with Acquisition of … – PR Newswire

TROY,Mich., July 27, 2023 /PRNewswire/ --Altair(Nasdaq: ALTR), a global leader in computational science and artificial intelligence (AI), acquired OmniV, a technology out of XLDyn, a product development software company based in southeast Michigan. OmniV empowers open model-based systems engineering (MBSE) practice across systems, simulation, test, product development, and controls engineering by formalizing the development, integration, and use of models to inform enterprise and program decision making.

OmniV eliminates the silos that occur between high-level system modeling and simulation, as well as detailed, domain-specific modeling and simulation. OmniV is vendor agnostic and can connect to various enterprise data stores and verification and validation methods including those from third-party vendors to support program goals. OmniV brings together cross-domain product development activities using the MBSE methodology in a fully integrated and easy-to-use tool.

With support for systems modeling language (SysML) a general purpose modeling language for systems engineering applications across a broad range of systems and systems-of-systems OmniV's SysML compliant diagrams that capture system architecture (structures, requirements, and behavior) can easily be shared and verified with product development teams. This allows the creation of multiple types of digital twins easier and earlier in the product development process, even before CAD models are created.

"Historically, organizations have had to wait until they have a physical prototype to see how a product performs. OmniV provides a holistic understanding of how a product functions much earlier in the process," said James R. Scapa, founder and chief executive officer, Altair. "Our goal is to connect the dots across the enterprise through an open, flexible, and purpose driven MBSE and digital twin integration. Regardless of what tools you use, OmniV allows customers to have an open architecture MBSE practice that provides a traceable ecosystem to track performance, cost, and mass of a product."

The technology will be available via Altair Units, integrated into Altair's digital twin solution set, and accessible via Altair One, Altair's cloud innovation gateway.

About AltairAltair is a global leader in computational science and artificial intelligence (AI) that provides software and cloud solutions in simulation, high-performance computing (HPC), data analytics, and AI. Altair enables organizations across all industries to compete more effectively and drive smarter decisions in an increasingly connected world all while creating a greener, more sustainable future. For more information, visit https://www.altair.com/.

Altair Europe/The Middle East/AfricaEvelyn Gebhardt+49 7031 6208 0[emailprotected]

SOURCE Altair

The rest is here:

Altair Expands Digital Engineering Technology with Acquisition of ... - PR Newswire

Read More..

Getting Nurses Comfortable With Big Data – HealthLeaders Media

How comfortable are nurses with mining Big Data?

"Zero, zero, zero, zero,"responds Roy Simpson, DNP, RN, DPNAP, FAAN, FACMI, assistant dean of technology management and clinical professor at the Emory University Nell Hodgson Woodruff School of Nursing.

Thats why Simpson and Vicki Stover Hertzberg, PhD, FASA, a professor and director of Emorys Center for Data Science, helped create an online, self-paced data science certificate programto help nurses use Big Data to solve problems in healthcare settings.

Big Data is a relatively new concept for nursingits been around two, perhaps three years, Simpson saysbut its capabilities are unlimited in developing patterns of patient care.

"To compare six patients and 10 patients and 30 patients and 400 patients is not a good indicator of evidence. You need large trillion data sets,"Simpson says.

"Large data gives you patterns; you cannot get patterns out of small data sets,"Simpson says. "So, if you're looking for whatever you're doing in nursing, whether it's getting a med, turning a patient, or deciding if it's the right room for them, you cannot gather evidence and research on small data sets today. You have to have large data sets to develop patterns of care."

For example, from Big Data, nurses know that new patients to a hospital who are over 65 and dehydrated will develop pressure ulcers, which can result in longer lengths of stay. Knowing that helps to develop a care plan.

"We're the only profession in the organization that is there 24 by 7every other healthcare provider is an episodic engager with the patientso we have to develop and understand care needs for our patients,"he says. "We have to know what interventions we need to do for patients to decrease length of stay for the patient because our goal is to get a patient out of a hospital."

Thats not only for the patients sake but for the organization, as well.

If a patient is admitted with a pressure ulcer or develops one while hospitalized, it becomes the responsibility of the healthcare organization to discharge that patient with no pressure ulcer; otherwise, the hospital will not be reimbursed, Simpson notes.

Despite the benefits of Big Data, nurses tend to be uncomfortable with it for a couple of reasons.

"Evidence is hard to accept for change,"he says.

Simpson referred to a recent announcement by a World Health Organization agency that artificial sweetener aspartame, used in low-calorie products such as Diet Coke, sugar-free gum, and tabletop sweeteners is "possibly carcinogenic to humans."

"I've had more people call me, asking, Should I drink Diet Cokes or not?"he says. "I say, If you drink 20 a day you probably shouldn't drink it, but if you're drinking three or four, you're probably ok."

"How do you translate the evidence?"he says. "That's not a human behavior to follow the true evidence; people's inquisitions are not that strong."

The newness of Big Data is also a factor. "You have early adopters,"he says, "and you have laggards and Big Data is a huge component."

The new certificate program provides students with access to Emory's own vast stores of dataProject NeLL,the School of Nursings "pioneering"suite of apps that provides access to 2.7 million de-identified patient records and more than 37 trillion data points, providing information on diverse populations, countless conditions, and a wide spectrum of care.

Project NeLL, which stands for Nurses Electronic Learning Library, is singular in its presentation of data, Simpson says.

"There are other large data sets, but they don't have the clinical text data transcribed into natural languages that can be retrieved,"Simpson says.

"For instance, MIMIC-III is a Massachusetts General data set which a lot of people use in research, but it is only data that is put in as data,"he says. "NeLL looks at other types of data sets, so it has a lot of uniqueness to the marketplace."

Emory nursing students who used NeLL to complete capstones and dissertations discovered racial disparities in opioid administration for breast cancer patients, a cost value associated with nurse anesthetists compared to other provider types, and predictors of death among patients with pressure ulcers, according to Emory University.

The new data science certificate program was conceived by Simpson and Hertzberg to move nurses forward in understanding Big Data and evidence and to advance Emorys Doctorate in Nursing program to include a focus on evidence and systems work, he says.

"What we learned was not all nurses are interested in getting doctoral degrees,"Simpson says. "They're looking at more scalable certificates as a way to advance their knowledge base and their criteria for work or being hired. We felt that more people wanted to understand informatics and Big Data before they decided whether they should go for degree granting in informatics."

Nurses completing the program will earn an Emory Nursing digital certificate and badge and receive continuing professional development contact hours.

Getting comfortable with Big Data can only help nurses in their clinical practice.

"Every specialty in nursing has a component of informatics, and the weakness of those disciplines is the lack of informatics in their discipline,"Simpson says.

Nurses need Big Data, Simpson says.

"Big Data is a new opportunity for the world at large, not just nursing,"he says. "But for nursing to be successful in the future, we have to embrace it. We have to understand it and know how to use it."

Carol Davisis the Nursing Editor at HealthLeaders, an HCPro brand.

Here is the original post:

Getting Nurses Comfortable With Big Data - HealthLeaders Media

Read More..

Discovery and rational engineering of PET hydrolase with both … – Nature.com

Discovery of a CaPETase with high PET hydrolytic activity and thermostability

To discover a PET hydrolase, we performed a sequence homology analysis using the National Center for Biotechnology Information (NCBI) database and selected 10 PETase candidates (see Methods for details). A phylogenetic tree was constructed for the 10 selected PETase candidates and 17 reported PET hydrolases. The 27 enzymes were divided into two groups: one group contained mesophilic enzymes, such as IsPETase, and the other group contained thermophilic enzymes, such as TfCut2 and LCC (Fig.1a, Supplementary Fig.1 and Supplementary Table1). The phylogenetic tree was further separated into 10 subgroups, and 3 selected PETase candidates, namely, RZL00883.1, KOX11336.1, and SHM40309.1, formed discrete lineages with low phylogenetic relationships to the reported PET hydrolases (Fig.1a). To characterize the 10 selected PETase candidates (PCs), we first attempted to produce them in a signal peptide-truncated form. Eight of the 10 PETase candidates were successfully produced, except for KOX11336.1 and MAM88718.1. We also measured the melting temperature (Tm) of the eight PETase candidates to determine the thermostability of these enzymes. The candidates exhibited a range of Tm values from 38.6C to 70.5C (Fig.1b and Supplementary Fig.2). We then checked PET hydrolytic activity of the eight PETase candidates at a wide range of temperatures from 30 to 60C using several PET samples, such as post-consumer transparent PET powder (PC-PETTransparent), semi-crystalline PET powder (Cry-PET, Goodfellow Cambridge Ltd) (Cat. No. ES306000), and amorphous PET film (AF-PET, Goodfellow Cambridge Ltd) (Cat. No. ES301445). Among these candidates, PC3, PC7, PC8 and PC10 showed relatively low or undetectable levels of PET hydrolytic activity across the tested conditions (Fig.1c and Supplementary Fig.3). PC6, which have the highest Tm value of 70.5C, produced only negligible amounts of PET hydrolysis products at 30C, but showed the optimal PET hydrolytic activity at 50C (Fig.1b, c and Supplementary Figs.2, 3). PC4 and PC5 showed relatively high PET hydrolytic activity at 50C and 40C, respectively (Fig.1c and Supplementary Fig.3). Surprisingly, compared to other PETase candidates, PC2 exhibited significantly high PET hydrolytic activity across a broad range of reaction conditions. Notably, PC2 exhibited superior activity at 30C and produced the highest amount of PET hydrolysis products across all three PET substrates conditions compared to other candidates. (Fig.1c and Supplementary Fig.3). In addition, the pH profile results for the eight PETase candidates also showed that PC2 showed the highest level of PET hydrolytic activity (Supplementary Fig.4). It is noteworthy that PC2 showed remarkable PET hydrolytic activity compared with the other enzymes, and also exhibited high thermostability with a Tm value of 66.8C (Fig.1b, c and Supplementary Fig.2). Moreover, PC2 had the highest soluble expression level compared with the other enzymes (Fig.1b). These results indicate that PC2 has excellent properties for efficient PET degradation, including enzyme activity, thermostability, and protein expression levels. Thus, we selected PC2 (accession code: SHM40309.1, PETase from Cryptosporangium aurantiacum, CaPETase) as the most robust PET hydrolase among the eight PETase candidates tested. The measurements of changes of the Tm value and activity by addition of metal ions showed that PC2 is not a metal ion-dependent enzyme (Supplementary Fig.5).

a Maximum likelihood phylogenetic tree and percentage identity matrix of the 10 selected PETase candidate (PC1PC10) and 17 reported PET hydrolase sequences. Bootstrap values for 1000 replications are shown at the branching edges. The colored bar represents the level of the percent identity of the enzymes, and detailed percent identity values are listed in Supplementary Fig.31. b Protein yield and the Tm values of the 8 PCs. c PET hydrolytic activity of the eight PCs. The reaction was performed with post-consumer transparent PET powder (PC-PETTransparent, 15mgmL1 with 500nM enzyme), semi-crystalline PET powder (Cry-PET, 15mgmL1 with 2M enzyme), and amorphous PET film (AF-PET, 15mgmL1 with 2M enzyme) in 50mM Glycine-NaOH pH 9.0 buffer at various temperatures (30C, 40C, 50C, 60C) for 3 days. Reactions were performed in triplicate; Data are presented as mean valuesSD. d Comparison of the PET hydrolytic activity of CaPETase, IsPETase, LCC, and TfCut2. The reaction was conducted with Cry-PET (15mgmL1 with 2M enzyme) in 50mM Glycine-NaOH (pH 9.0) at various temperatures (30C, 40C, 50C, 60C) for 12h. Reactions were performed in triplicate; Data are presented as mean valuesSD.

Next, we compared the PET hydrolytic activity of CaPETase with that of well-known PET hydrolases, such as IsPETase, TfCut2, and LCC, over a broad temperature range from 30 to 60C using Cry-PET as a substrate. In reactions at 30C, CaPETase showed significantly higher PET hydrolytic activity than LCC and TfCut2 (Fig.1d and Supplementary Fig.3). Moreover, CaPETase exhibited 1.4-fold higher activity than IsPETase, which is known to have the highest PET hydrolytic activity at ambient temperature among the reported PET hydrolases (Fig.1d)17. In particular, the PET hydrolytic activity of CaPETase was 3.1-fold higher than that of IsPETase at 40C (Fig.1d), likely because CaPETase has much higher thermostability than IsPETase. However, the PET hydrolytic activity of CaPETase at 60C dramatically decreased and reversed compared with that of LCC at temperatures of 50C and 60C (Fig.1d). These results indicate that CaPETase is a promising PET hydrolase that exhibits high PET decomposition ability and thermostability. Considering that it is important to make improvements without the loss of enzyme activity and thermostability in the development of superior PET-degrading enzymes37, we propose that CaPETase represents a more efficient template enzyme for enzyme engineering than other enzymes with extreme mesophilic and thermophilic properties, such as IsPETase and LCC, respectively.

To provide a structural basis for high PET hydrolytic activity of CaPETase, we determined its crystal structure at a resolution of 1.36 (Supplementary Table2). CaPETase shows an / hydrolase fold and a nine-stranded -sheet at the center surrounded by six -helices and two 310-helices (Fig.2a and Supplementary Fig.6). Sequence-independent pairwise superposition of CaPETase with three distinctive PET hydrolases, namely, IsPETase, LCC, and TfCut2, generated global root mean square deviation values of 0.69, 0.65, and 0.53, respectively. Formation of one conserved disulfide bond (DS, C279/C297) and lack of an extended loop in the substrate binding site of CaPETase suggest that the enzyme originated from an ancestor of TfCut2 and LCC rather than IsPETase (Supplementary Fig.7). Interestingly, CaPETase exhibits a somewhat different backbone structure at the active site compared with other PET hydrolases (Supplementary Fig.8). Because the structural comparison using a Cartesian coordinate system is known to be subjective for distinguishing the detailed structural differences of the main chains38, we further analyzed the - torsion angles of the main chains of these four PETases (Supplementary Fig.9) and found that there were local differences in backbone torsion angles between CaPETase and other PET hydrolases (Fig.2a and Supplementary Fig.10). Interestingly, CaPETase also showed significant differences in the backbone torsion angles at the five connecting loops (31, 42, 67, 74, and 85) that form an active site, whereas comparisons of the corresponding loops between the other three PET hydrolases exhibited less differences (Fig.2a and Supplementary Fig.11), suggesting that CaPETase has a unique active site conformation. There were some differences in the network of residues extending from the active site to the nearby spatial environment compared with that of the other PET hydrolases. Among them, we observed unique differences affecting the backbone torsion angles of these loops. Near the 31 loop, distinct residues positioned in the 42 loop and a W105L108G124 network force, which form a unique side-chain internal network, appear to influence the conformation of the 31 loop (Supplementary Fig.12). In fact, the 31 loop has high root mean square fluctuation values near the active sites of other PET hydrolases in molecular dynamic simulations39,40. A unique A192G212F248 network is formed under the 85 loop, where catalytic H246 is located (Supplementary Fig.13). At the corresponding F248 position in CaPETase, LCC and TfCut2 have an alanine residue, whereas IsPETase has a cysteine residue that forms a second disulfide bond. Therefore, the positioning of a bulky F248 might cause significant torsional differences in the 85 loop and 74 loop of CaPETase (Supplementary Fig.13). Finally, an R176W200F209 network appears to trigger conformational differences in the 3-helix and 67 loop (Supplementary Fig.14). Importantly, the 3-helix contains the catalytic S169, and the 67 loop was previously annotated as a wobbling tryptophan-containing loop in PETase from Rhizobacter gummiphilus (Supplementary Fig.14)41. We further analyzed backbone fluctuations of these four PET hydrolases using molecular dynamic simulations and CaPETase exhibits quite unique backbone fluctuation profile (Fig.2b and Supplementary Fig.15). CaPETase has more stable 67 and 74 loops than mesophilic IsPETase, and particularly, the enzyme shows high stability at the front region of the 85 catalytic loop where H246 is located (Fig.2b). However, the end region of 85 which corresponds to the extended loop of IsPETase, and the front region of 31 loop showed the highest and lowest flexibility among the four homologs, respectively (Fig.2b). To our interest, the differences of the backbone fluctuation profile was localized exactly to the unique internal network affecting the backbone torsion angles of these loops. Thus, we believe that the unique backbone conformation of CaPETase allows the enzyme to maintain high activity while stabilizing several flexible loops of the mesophilic PET hydrolase.

a Comparison of the backbone torsion angle differences between CaPETase and IsPETase, LCC, and TfCut2. The structure of five connecting loops forming the active site of CaPETase is displayed as a putty tube representation of the same diameter in PyMoL. The structure is colored according to the Euclidean distance values between the two Ramachandran points of the aligned residues. Colors of white to red designate low to high Euclidean distance values, respectively. The catalytic triad of CaPETase is shown as a stick model with a cyan-color circle. b MD simulations show unique backbone fluctuation profile of CaPETase. C atom root-mean-square fluctuations (RMSF, ) of the CaPETase, IsPETase, TfCut2, LCC during MD simulations. c Comparison of the residues forming the substrate binding cleft of CaPETase, LCC, and TfCut2. The highlighted residues are shown as a stick model. d Distinct residues in the substrate binding site of CaPETase. Distinct and conserved residues are presented in magenta and light blue, respectively. e PET hydrolytic activity of the variants. PC-PETTransparent (15mgmL1) were incubated with 500nM enzymes at 40C for 24h in 50mM Glycine-NaOH buffer pH 9.0. Total amount of released products and the Tm value of the variants are shown as bars and red-colored dots, respectively. Reactions were performed in triplicate; Data are presented as mean valuesSD.

In addition to the unique backbone conformation at the active site, residues forming the substrate binding cleft of CaPETase showed significant differences compared with other thermophilic PET hydrolases (Fig.2c, d). In the vicinity of the wobbling W194, CaPETase possesses unique G196 and L133 residues, where highly conserved residues are located in other PET hydrolases (Fig.2c, d and Supplementary Fig.7). Mutating these residues to the corresponding residues in other PET hydrolases, such as G196L, L133Y, and L133Q, had a negative effect on enzyme activity and/or thermostability (Fig.2e). However, the G196T mutation exhibited enhanced thermostability (Fig.2e), which may result from the formation of a hydrogen bond between G196T and N195. CaPETase also contains a unique I102 residue in the 31 loop showing the largest torsion differences, whereas other PET hydrolases contain a highly conserved threonine residue at the corresponding position, which probably enables CaPETase to form a relatively wider substrate binding cleft (Fig.2c, d and Supplementary Fig.16). Replacement of I102 with threonine resulted in decreased enzyme activity, confirming that the residue contributes to high enzyme activity (Fig.2e). Furthermore, CaPETase has unique residues, such as Q107, W168, and T250, at the regions of the 31 loop, 85 loop, and 3, whereas most of the corresponding residues are highly conserved in other thermophilic PET hydrolases (Fig.2c, d and Supplementary Fig.7). Mutating these residues to the conserved residues in other thermophilic PET hydrolases decreased enzymatic activity and/or stability, indicating that the combined positioning of these residues is necessary to create an optimal substrate binding site for CaPETase with a unique shape and polarity (Fig.2e). One exception was the Q107S mutation, which resulted in no noticeable differences in enzyme activity or thermostability (Fig.2e). Taken together, we suggest that along with unique backbone torsion angles, the positioning of distinct residues at the substrate binding site enable CaPETase to form an optimal substrate binding site for high PET hydrolytic activity.

Although CaPETase has high PET hydrolytic activity and thermostability, its performance is still insufficient for industrial applications. We conducted rational protein engineering of CaPETase to further enhance the PET hydrolytic activity and thermostability of the enzyme using various strategies, such as introducing disulfide bonds and hydrogen bonds and modifying the protein surface charge (Supplementary Fig.17). The thermostability of the variants was monitored by measuring Tm values, and the PET hydrolytic activity of the variants was measured using post-consumer transparent PET powder (PC-PETTransparent) at ambient temperature (40C). We introduced four disulfide bonds, namely, G76C/A143C (DS1), L180C/A202C (DS2), T204C/R233C (DS3), and R242C/S291C (DS4). The DS2 and DS4 mutations increased the Tm value by approximately 3C, whereas the DS1 and DS3 mutations decreased the Tm value compared with CaPETaseWT (Fig.3a and Supplementary Fig.18). Moreover, the introduction of the DS2 and DS4 mutations increased PET hydrolytic activity by more than 20% compared with CaPETaseWT (Fig.3a and Supplementary Fig.18). These results indicate that the DS2 and DS4 mutations were successfully formed in CaPETaseWT and exerted positive effects on enzyme activity and thermostability. We also attempted to improve the thermostability of CaPETase by introducing noncovalent bonds, such as hydrogen bonds and salt bridges, and designed seven mutations, namely, V129T (NC1), P136S (NC2), A192T (NC3), R198K (NC4), V203T (NC5), A252N (NC6), and A257S(NC7). Of these, the NC1 and NC4 mutations increased Tm values by approximately 2C and enhanced PET hydrolytic activity by 30% compared with CaPETaseWT (Fig.3a and Supplementary Fig.18). Finally, in an attempt to improve the protein adsorption ability to the PET surface by modifying the protein surface charge, we designed five mutations to render the protein surface hydrophobic, i.e., N109A (HP1), R151A (HP2), R157A (HP3), R160A (HP4), and R233A (HP5), and four mutations to render the protein surface positive, i.e., T86R (SC1), A155R (SC2), T275R (SC3), and M294R (SC4). Unfortunately, most mutations did not show significant changes or even negative effects on thermostability or enzyme activity; however, the HP1 mutation increased the Tm value by 3.2C, and the SC2 mutation enhanced PET hydrolytic activity by 20% compared with CaPETaseWT (Fig.3a and Supplementary Fig.18). Taken together, we introduced eight point-mutations that resulted in improved thermostability and PET hydrolytic activity, i.e., DS2, DS4, NC1, NC4, HP1, and SC2, among the 20 rationally designed mutations tested (Fig.3a and Supplementary Fig.18). There were also ambiguous mutations that only improved enzyme activity or thermostability, such as NC2, HP2, and HP5. We excluded these mutations from the final selection to develop a much superior variant without compromising enzymatic activity or thermostability (Fig.3a and Supplementary Fig.18)37.

a Single-point mutations of CaPETase. Released PET hydrolysis products and the Tm values of the single-point mutations are presented. The reactions were performed using 500nM enzymes with post-consumer transparent PET powder (PC-PETTransparent, 15mgmL1) as the substrate in 50mM Glycine-NaOH buffer (pH 9.0) for 24h at 40C. Reaction was carried out in triplicate; error bars represent the s.d. of the replicate measurement. b Combinatorial mutations of CaPETase. PET hydrolytic activity of the variants generated using the combinatorial strategy. Released PET hydrolysis products per hour and the Tm values of the combinatorial variants are presented. The reactions were performed using 500nM enzymes with PC-PET (15mgmL1) as the substrate in 100mM Glycine-NaOH buffer (pH 9.0) at 40C for 24h and 60C for 6h, respectively. Reaction was carried out in triplicate; error bars represent the s.d. of the replicate measurement. c Comparison of PET hydrolysis activity between CaPETaseM9 and LCCICCG at various temperatures. The reactions were carried out at different temperatures using PC-PETTransparent (12.5mgmL1) with 1M enzyme and Cry-PET (12.5mgmL1) with 4M enzyme under the 200mM Glycine-NaOH buffer pH 9.0. Reactions were performed in triplicate; Data are presented as mean valuesSD.

We sequentially integrated the six mutations described above to develop a superior CaPETase variant with higher thermostability and PET hydrolytic activity. First, we combined the DS2 and DS4 mutations, and the resulting CaPETaseDS2/DS4 variant showed a synergistic effect on thermostability with a Tm value of 74.3C (Tm=7.4C) (Fig.3b and Supplementary Fig.19). Moreover, the variant enhanced PET hydrolytic activity by 1.35- and 4.45-fold at 40C and 60C, respectively, compared with CaPETaseWT (Fig.3b and Supplementary Fig.19). Next, we set up CaPETaseDS2/DS4 as a scaffold for the next combination. We integrated the NC1/NC4, HP1, and SC2 mutations individually into CaPETaseDS2/DS4 using our engineering strategy. The addition of the NC1/NC4 mutation increased the Tm value significantly by 3.9C and increased PET hydrolytic activity at both 40C and 60C (Fig.3b and Supplementary Fig.19). It showed 3.8- and 17-fold enhanced activity at 60C compared with CaPETaseDS2/DS4 and CaPETaseWT, respectively (Fig.3b and Supplementary Fig.19). The addition of the HP1 mutation increased the Tm value by 2.7C and enhanced PET hydrolytic activity by 1.7-fold at 60C compared with CaPETaseDS2/DS4 (Fig.3b and Supplementary Fig.19). When the SC2 mutation was integrated into the CaPETaseDS2/DS4 variant, we observed no noticeable improvements in activity and thermostability; however, there was a slight increase in PET hydrolytic activity at 60C (Fig.3b and Supplementary Fig.19).

These results suggest that all four mutations (NC1, NC4, HP1, and SC2) had a positive effect on the thermostability and activity of CaPETaseDS2/DS4; thus, we combined the four mutations into CaPETaseDS2/DS4 to generate CaPETaseDS2/DS4/NC1/NC4/HP1/SC2 (CaPETaseM8). Surprisingly, when all four mutations were added to CaPETaseDS2/DS4, a synergistic effect on thermostability and enzyme activity was observed, and CaPETaseM8 exhibited significantly enhanced thermostability with a Tm value of 80.7C and 1.5- and 25.8-fold enhanced PET hydrolytic activity at 40C and 60C, respectively, compared with CaPETaseWT (Fig.3b and Supplementary Fig.19).

As mentioned above, the G196T mutation resulted in positive effects on both thermostability and enzyme activity (Fig.2e); thus, we finally generated CaPETaseDS2/DS4/NC1/NC4/HP1/SC2/G196T (CaPETaseM9) by integrating the G196T mutation into CaPETaseM8. CaPETaseM9 exhibited a Tm value of 83.2C, which corresponds to a 16.7C increase in Tm compared with CaPETaseWT. Moreover, the PET hydrolytic activity of CaPETaseM9 increased by 1.7- and 31.2-fold at 40C and 60C, respectively, compared with CaPETaseWT (Fig.3b and Supplementary Fig.19). These results indicate a positive effect of G196T on CaPETaseWT was applied similarly to CaPETaseM8.

CaPETaseM9 showed much higher activity at all temperature conditions from 30 to 70C, and particularly, showed 41.7-fold higher specific activity at 60C than CaPETaseWT (Supplementary Fig.20). The result was also reproduced in a scale-up system of 50-mL shaking flasks (Supplementary Fig.21). These results demonstrated the improved enzyme activity and reinforced thermostability of CaPETaseM9. The improved thermostability of the variant was further verified through heat inactivation experiments, where CaPETaseM9 maintained its activity even after incubation at 60C for 12h, whereas CaPETaseWT showed complete loss of activity within an hour (Supplementary Fig.22).

We then compared the PET hydrolytic activity of CaPETaseM9 with LCCICCG towards PC-PET and Cry-PET at temperatures ranging from 30 to 60C. CaPETaseM9 showed significantly higher PET hydrolytic activity compared to LCCICCG, at 30C and 40C (Fig.3c). At 50C and 60C, CaPETaseM9 showed quite similar activity compared with LCCICCG (Fig.3c).

To provide structural insights into the enhanced PET-degrading capacity of CaPETaseM9, we determined its crystal structure at a resolution of 1.53 (Fig.4 and Supplementary Table2). The formation of the introduced DS2 and DS4 disulfide bonds was clearly observed in CaPETaseM9, and the SS interatomic length of both disulfide bonds was within the optimal disulfide bond length range (Fig.4 and Supplementary Fig.23). Interestingly, DS4 was located in the vicinity of one of the calcium binding sites of Cut190 and the mutation point of IsPETase R280A42,43, and the formation of DS4 also caused significant changes in the surface electrostatic potential and neighboring region conformation (Fig.4 and Supplementary Figs.23 and 24). The side chain of the mutated V129T was flipped to form a hydrogen bond with the adjacent T131 and D132 residues, thereby further stabilizing the 43 connecting loop (Fig.4 and Supplementary Figs.23 and 25). With respect to R198K, the mutated lysine residue moved inward to form hydrogen bonds with the main chains of N195 and D222, thereby stabilizing the wobbly tryptophan-containing loop (Fig.4 and Supplementary Fig.23). The mutated G196T formed a water-mediated hydrogen bond with the adjacent N195 residue, resulting in further stabilization of the wobbly tryptophan-containing loop (Fig.4 and Supplementary Fig.23). The A155R mutation changed the hydrophobic surface to a positive charge, which seems to increase the attachment of the enzyme to the PET surface, as suggested by a previous report (Fig.4 and Supplementary Fig.23)44. Finally, the N109A mutation appeared to strengthen internal hydrophobic interactions (Fig.4 and Supplementary Figs.23 and 26).

The crystal structure of CaPETaseM9 is shown as a cartoon diagram, and the mutated residues are shown as a stick or a surface electrostatic potential model.

To evaluate the industrial applicability of CaPETaseM9, we conducted a PET decomposition experiment in a pH-stat bioreactor using PC-PETTransparent as a substrate (Supplementary Fig.27). The bioreactor was operated at 55C using 2.70 mgenzymegPET1, and the pH was continuously titrated at 8.0 by adding NaOH. The decomposition rate was measured by monitoring released amounts of MHET and TPA. After a short lag phase of an hour, which was required for initial hydrophilization, the PET degradation rate increased exponentially, and 50% of PC-PETTransparent was depolymerized within 4h (Fig.5a). In the second half of the reaction, the degradation rate slightly decreased because of a decrease in the amount of substrate; however, a final degradation rate of 94.1% was achieved after 12h (Fig.5a). This was a significant result in terms of showing that a high depolymerization rate of 90% or more could be achieved even at 55C, which is a temperature condition relatively lower than the Tg temperature. This result also indicated that CaPETaseM9 has significant PET hydrolytic activity and thermostability comparable to other benchmark biocatalysts. We also performed decomposition of a post-consumer colored PET powder (PC-PETColored), which is known to be relatively difficult to recycle because of the presence of colors, additives, multilayer structure, labels and other complexities45. Interestingly, the depolymerization rate of PC-PETColored was almost identical to that of PC-PETTransparent, showing 50% depolymerization within 4h (Fig.5b); however, the final depolymerization rate of PC-PETColored was 89.2% at 12h, which was slightly lower than that of PC-PETTransparent (Fig.5b). This is probably due to the impurities present in PC-PETColored. These results demonstrate that unlike other recycling methods, biorecycling of PET plastic can be achieved regardless of the color of PET plastic.

Decomposition of post-consumer transparent PET powder (PC-PETTransparent) (a) and post-consumer colored PET powder (PC-PETColored) (b) in a pH-stat bioreactor using CaPETaseM9. Reactions were performed in triplicate independently; Data are presented as mean valuesSD. c Complete degradation of a post-consumer PET container using CaPETaseM9 at 60C. Reactions were performed in triplicate; Data are presented as mean valuesSD.

Finally, we determined whether untreated post-consumer PET containers can be depolymerized by CaPETaseM9. As depolymerization proceeded, the PET film became opaque and thin, and the PET film disappeared completely in 3 days (Fig.5c). These results suggest that CaPETaseM9 can be utilized for decomposing PET plastics with various physical properties.

Original post:

Discovery and rational engineering of PET hydrolase with both ... - Nature.com

Read More..