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Clemson researcher Chris Saski admits sending the universitys iconic Tiger Paw to space aboard a SpaceX Dragon spacecraft is, quite literally, an out-of-this-world experience.

But its the potential for the experiments in the flight hardware to which the Paw is attached that truly excites him.

Saskis cotton regeneration research, adorned with Clemson stickers, intends to take off Dec. 21 from NASAs Kennedy Space Center in Florida bound for the International Space Station (ISS). Upon arrival, Saskis research project titled Unlocking the Cotton Genome to Precision Genetics will be conducted in microgravity with the goal of facilitating the ability to directly edit the genome of elite cotton varieties, quickly adding traits like disease resistance or drought tolerance without the need for the lengthy conventional breeding process that can take over a decade.

Understanding gene function and subsequent genome engineering technology has the potential to change the lives of everyone and everything on the planet.

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With no solution yet in place to satisfy a growing demand for fuel, food and fiber as the global population continues to expand, Saski believes this research is a large step in the right direction toward solving that problem.

Conducting these experiments in microgravity gives us a unique environment to disentangle the genetics of somatic embryogenesis regenerating a whole plant from a single cell and we believe we can translate this research into application, he said. This project will lead to new understanding of the genes involved. As we understand it now, this genetic program is encoded in all crop genomes, but it is suppressed. This research could ultimately allow us to switch on this genetic program in other crops and be able to do genome editing and engineering more readily and directly on commercial varieties and eventually provide an accelerated path to food, fuel and fiber for a growing population of people on Earth.

Food for thought or living on another planet

But if potentially addressing issues such as global hunger wasnt enough, the possibilities go far beyond, said Saski, who admitted he never imagined space missions would one day be part of his work.

When I started my position as a researcher here at Clemson, I quickly realized that there really are no boundaries to the questions that one can ask, he said. I just created a vision, worked hard and tried to set the bar high. I envision that translation of this research into application could enable deep space exploration missions, it could allow for plants to be stored as single cells and you could store and supply a diversity of plant species for astronauts that are doing research or even living on another planet.

Broadly, the project seeks to explore the cotton genome and how it reacts in microgravity and normal gravity. It was selected as a winner in the Cotton Sustainability Challenge, which was run by the Center for the Advancement of Science in Space (CASIS) and funded by Target Corporation, providing researchers and innovators the opportunity to propose solutions to improve crop production on Earth by sending their concepts to the ISS U.S. National Laboratory. CASIS is the organization tasked by NASA to manage the ISS National Lab.

One of Saskis collaborators is Jeremy Schmutz, faculty investigator at HudsonAlpha Institute for Biotechnology since 2008, who said the project aims to understand how callus cells divide and regenerate in space and how this affects the quality of transformed cells.

We have shown that cotton has very little diversity as a species, which greatly limits the possibilities of improving the sustainability of cotton through traditional breeding techniques, Schmutz said. Accelerating the speed at which we can transform cotton opens up the ability to rapidly test genes linked to beneficial traits and also make positive targeted modifications in important cotton lines for U.S. growers and the many industries that depend on high-quality cotton production.

Embryogenesis in microgravity

Conventional breeding process currently takes more than a decade

And why does conducting research in microgravity make a difference?

Microgravity is the condition in which people or objects appear weightless. Plants have evolved at a force of 1g the force of gravity on Earth, responsible for things such as keeping our feet planted firmly on the ground but without that force, or in microgravity, there can be a drastic effect on gene expression.

Studying developmental programs like embryogenesis in microgravity allows us to disentangle what genes are involved by comparing experiments on the ISS and on Earth, according to Saski.

Our experiment is aimed at understanding the genetic architecture and coordination of embryogenesis, he said. Understanding this program could facilitate the ability to directly edit the genome of elite breeding germplasm, adding traits such as disease resistance or drought tolerance without the need for the long conventional breeding process.

Don Jones, director of Breeding, Genetics and Biotechnology at Cotton Incorporated, echoed Saskis sentiment that this understanding could be a direct and immediate benefit of sending the project to space but said the potential for longer-term benefits is also vast.

Past space exploration has resulted in benefits for all of humanity that oftentimes far exceeds the expectations of those who were conducting the initial research. Conventional breeding now takes at least a decade to deliver improved varieties to cotton growers that can withstand drought and disease, both of which will increase with climate change, Jones said. Understanding and improving embryogenesis will allow such varieties to be developed significantly faster, and when the payoff is faster, more companies and institutions become interested in investing real dollars into cotton research with a shortened payoff time horizon.

Low Earth orbit: Falling around the planet

The effects of microgravity can be seen when astronauts and objects float in space. But the prefix micro- means very small, not nonexistent, so microgravity refers to the condition where gravity seems to be very small.

The ISS operates in Low Earth Orbit (LEO) or about 200 to 250 miles high. At that height, Earths gravity is still very strong, thus a person who weighs 100 pounds on the ground would weigh 90 pounds there.

Earths gravity pulls objects, including the space station, toward its surface. As a result, the ISS is constantly falling toward Earth. But the station also is moving very fast so fast it matches the curve of the Earths surface.

If you throw a baseball, gravity will cause it to curve down; it will hit the ground soon, Saski said. A spacecraft in orbit moves at the right speed so that the curve of its fall matches the curve of Earth. For the space station, that speed is 17,500 miles per hour. The spacecraft keeps falling toward the ground but never hits it. Instead, it falls around the planet. The moon stays in orbit around Earth for this same reason.

For the purposes of this research, however, that difference between 1g gravitational force and microgravity can have a significant effect.

Saski and Clemson postdoctoral research scientist Sonika Kumar are studying plant cells analogous to human stem cells; in this case, plants cells that are not de-differentiated not a certain part of the plant allowing for complementary experiments to disentangle the genetic architecture of somatic embryogenesis.

That disentanglement would enable scientists to turn on this programming in other crops and do genome editing and genome engineering more readily. The potential, then, is for growers to feed a growing and expanding population of people on Earth.

Genetic and epigenetic changes control the process of somatic embryogenesis, Kumar said. Discovering the mechanism and genetic factors behind somatic embryogenesis will open new avenues to stimulate the cellular reprogramming of somatic embryogenesis that will be helpful in fast delivery of cotton varieties having a combination of multiple traits like excellent fiber quality, climate resilience and tolerance to biotic and abiotic stresses. This project with the objective of cotton sustainability challenge will improve the social and economic development of growers, stakeholders and industries.

Power of the Paw

As for the Tiger Paw, Saski said the ISS-required custom flight and operations hardware the payload that will be aboard the SpaceX Dragon spacecraft looked largely bare and boring in its original state.

Mission Director Dave Reed and his team at Techshot, a company recently acquired by space infrastructure company Redwire, are converting Saskis experiments into a payload for space travel and designing the operational hardware they are also responsible for putting the Clemson stickers on the flight hardware.

The evolution from scientific proposal to spaceflight is typically referred to as payload development, and the Redwire payload development team has the challenging task of merging the scientific investigation with the capability of spaceflight hardware and the constraints of resources such as upmass, astronaut time and cold stowage return of harvested material.

On behalf of our whole payload development team, we are proud to be supporting this exciting investigation that promises to yield new discoveries for the benefit of life on Earth, Reed said. Much of our work on ISS is about exploring how microgravity can positively impact industries, people and systems back on Earth, and this investigation supports this mission.

Saskis project represents the first time that a plant tissue culture experiment will be performed on orbit in NASAs Advanced Plant Habitat, which is designed to provide sunlight-strength illumination in order to grow plants such as radishes, peppers and tomatoes.

Plant tissue culture requires very, very low daytime light levels, just enough to maintain a circadian rhythm in the culture and a tiny fraction of what Plant Habitat was designed to produce, Reed said. To provide such a low light level, Redwire engineers developed an elegantly simple sun shade akin to one you would find at a terrestrial plant nursery.

As the team began to work on developing a payload to such specifications, Saski also inquired about the possibility of putting a Tiger Paw sticker on any of the hardward a request Reed said was not trivial.

In spaceflight, labels are serious business. Everything from font size to color to label material is prescribed, Reed said. Our team worked with the label approval team to find a spot where the sticker could be acceptably placed. For Dr. Saski, it was all a part of the great revelation about the intricacies of the spaceflight experience.

Because competition for research space aboard the ISS, which is roughly the size of a football field, is on a global scale, the presence of the Paw is no small feat.

Being able to send the beloved Tiger Paw to space has been an amazing experience, Saski said. Being selected for this opportunity and conducting research and being able to put it out there as far as it could possibly go has been a vision of my research program and aspirations since Ive joined the faculty here at Clemson.

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Cotton in orbit: Clemson genome study bound for space station - The Times and Democrat

SAN DIEGO, Dec. 16, 2021 (GLOBE NEWSWIRE) -- Bionano Genomics, Inc. (BNGO), provider of optical genome mapping (OGM) solutions on the Saphyr system and the leading software for genomic data visualization, interpretation and reporting, today announced the launch of version 6.1 of BioDiscoverys NxClinical software with expanded capabilities for next-generation sequencing (NGS) data in genetic diseases and cancer. NxClinical is an industry-leading, platform-agnostic software solution, which integrates NGS and microarray data designed to provide analysis, visualization, interpretation and reporting of copy number variants (CNV), single-nucleotide variants and absence of heterozygosity across the genome in one consolidated view.

This new version is designed to address requests from our NxClinical customers around the world seeking to see more of what matters in their NGS data, commented Soheil Shams, PhD, Chief Informatics Officer of Bionano Genomics. We are committed to helping customers reveal more clinically relevant variants from genomic data across multiple platforms with a streamlined workflow that can allow for optimal turnaround time. This software upgrade represents another step further as we continue toward laying the groundwork for our goal of integrating OGM data with NGS data to provide what we believe can become the most comprehensive view of genome variation.

We believe version 6.1 significantly improves the ability of NxClinical to detect more clinically relevant variants from NGS data with the inclusion of uniparental disomy functionality and the expanded sequence knowledgebase for visualization and reporting of relevant genomic variants. In addition, data interpretation has been streamlined with the automated annotation of clinically relevant variants using the American College of Medical Genetics and Genomics (ACMG) technical standards. This feature automatically calculates the relevance for many of the evidence categories described by the ACMG technical standards for CNV interpretation, which can simplify data interpretation and reduce time to reportable result.

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At Bionano, we are working to transform the way the world sees the genome to elevate human health and wellness, said Erik Holmlin, PhD, President and CEO of Bionano Genomics. Software is the primary way our customers interact with their data and experience our products. Our goal is to increase the number of Bionano subscribers using NxClinical software to create a network effect where customers can obtain more meaningful results from their NGS and microarray data today so that in the future they can more easily implement OGM within the same software tool to see more genomic variants that matter.

About Bionano Genomics

Bionano is a provider of genome analysis solutions that can enable researchers and clinicians to reveal answers to challenging questions in biology and medicine. The Companys mission is to transform the way the world sees the genome through OGM solutions, diagnostic services and software. The Company offers OGM solutions for applications across basic, translational and clinical research. Through its Lineagen business, the Company also provides diagnostic testing for patients with clinical presentations consistent with autism spectrum disorder and other neurodevelopmental disabilities. Through its BioDiscovery business, the Company also offers an industry-leading, platform-agnostic software solution, which integrates next-generation sequencing and microarray data designed to provide analysis, visualization, interpretation and reporting of copy number variants, single-nucleotide variants and absence of heterozygosity across the genome in one consolidated view. For more information, visit http://www.bionanogenomics.com, http://www.lineagen.com or http://www.biodiscovery.com.

Forward-Looking Statements of Bionano Genomics

This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Words such as may, will, expect, plan, anticipate, estimate, intend and similar expressions (as well as other words or expressions referencing future events, conditions or circumstances) convey uncertainty of future events or outcomes and are intended to identify these forward-looking statements. Forward-looking statements include statements regarding our intentions, beliefs, projections, outlook, analyses or current expectations concerning, among other things: the ability and utility of NxClinical software to help visualize, interpret and report NGS data in genetic diseases and cancer; the ability of NxClinical software to integrate OGM data with NGS data to provide a comprehensive view of genome variation; the ability of NxClinical software to create a network effect that combines the synergies of NGS and microarray data to allow implementation of OGM within the same software. Each of these forward-looking statements involves risks and uncertainties. Actual results or developments may differ materially from those projected or implied in these forward-looking statements. Factors that may cause such a difference include the risks and uncertainties associated with: the impact of the COVID-19 pandemic on our business and the global economy; general market conditions; changes in the competitive landscape and the introduction of competitive products; failure of the new version of NxClinical to perform as intended; the effect on our software of cyber attacks, viruses and the like; changes in our strategic and commercial plans; our ability to obtain sufficient financing to fund our strategic plans and commercialization efforts; the ability of medical and research institutions to obtain funding to support adoption or continued use of our technologies; and the risks and uncertainties associated with our business and financial condition in general, including the risks and uncertainties described in our filings with the Securities and Exchange Commission, including, without limitation, our Annual Report on Form 10-K for the year ended December 31, 2020 and in other filings subsequently made by us with the Securities and Exchange Commission. All forward-looking statements contained in this press release speak only as of the date on which they were made and are based on managements assumptions and estimates as of such date. We do not undertake any obligation to publicly update any forward-looking statements, whether as a result of the receipt of new information, the occurrence of future events or otherwise.

CONTACTSCompany Contact:Erik Holmlin, CEOBionano Genomics, Inc.+1 (858) 888-7610eholmlin@bionanogenomics.com

Investor Relations:Amy ConradJuniper Point+1 (858) 366-3243amy@juniper-point.com

Media Relations:Michael SullivanSeismic+1 (503) 799-7520michael@teamseismic.com

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Bionano Genomics Announces the Launch of Version 6.1 of BioDiscoverys NxClinical Software for Genome Analysis with Expanded Capabilities for...

A team of researchers, led by the Agency for Science, Technology and Researchs (A*STAR) Genome Institute of Singapore (GIS), was awarded the prestigious Chan Zuckerberg Initiative (CZI) Ancestry Network Grant in support of their Asian Immune Diversity Atlas (AIDA) project. The project aims to build a map of cells from the blood of healthy Asian individuals spanning 20 distinct populations from eight Asian countries: Singapore, Japan, South Korea, India, Thailand, Russia, Pakistan and Sri Lanka.

Although Asia accounts for nearly 60 percent of the global population, samples from Asian individuals are under-represented in global genomic databases. AIDA, the flagship project of Human Cell Atlas (HCA) Asia, aims to correct this imbalance by studying how immune cells are affected by age, ethnicity, environment and geography.

With the support of the CZI Ancestry Network grant, AIDA will expand representation of diverse Asian population groups within the HCA, promote research participation across Asia, and maintain long-term community engagement to ensure that the project benefits participating communities. AIDA will also provide a baseline measurement of the immune system (the bodys defence mechanism) in healthy individuals, which will be essential for identifying the abnormalities that occur in diverse immune-related diseases, metabolic disorders and cancers.

The project will sequence millions of individual cells from over 1,000 individuals to study the expression of genes as well as the unique immune cell receptors that are involved in mounting a defence against invading pathogens. This will shed light on the properties of immune cells in healthy individuals and serve as a reference and comparison point for understanding immune aberrations in diseases.

Dr Shyam Prabhakar, Associate Director of Spatial and Single Cell Systems at GIS, said, AIDA is the first large-scale effort to characterise immune cell diversity in Asian populations. It will lay a foundation for Precision Medicine in Asia by facilitating therapies tailored to the specifics of the patient. The curated data will be deposited in public repositories for the benefit of the scientific and clinical communities.

Prof Patrick Tan, Executive Director of GIS, said, GIS is honoured to be part of this pioneering regional collaboration, working towards a unified goal of creating a large-scale map of representative traits of immune cells from healthy Asian individuals. It will help us define the changes that cause immune disorders and eventually develop new treatments.

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Scientists from the Genome Institute of Singa - EurekAlert

The crucial role of effective genomic surveillance

With the COVID-19 pandemic progressing, genomic surveillance, conducted in an efficient way, is essential to inform us of circulating viruses and response measures required. The sequencing of representative samples continuously collected in a standardized approach from patients meeting influenza-like illness, acute respiratory infection, and severe acute respiratory infection case definitions, allows us to monitor the evolving trends and relative proportions of existing and emerging genetic variants circulating in the community.

GISRS has monitored influenza viruses since 1952, and since March 2020, SARS-CoV-2 was added to GISRS. In February 2021, the Global Influenza Programme (GIP) published Operational considerations to expedite genomic sequencing component of GISRS surveillance of SARS-CoV-2, to improve the geographic, demographic and temporal representativeness of data, monitor the trends and prevalence of genetic variants, and better understand the associations among the genetic characteristics, transmission fitness and disease profiles of SARS-CoV-2. In October 2021, GIP hosted an e-consultation to update the Operational Considerations and incorporate them with the previously published guidance document Maintaining surveillance of influenza and monitoring SARS-CoV-2: adapting Global Influenza Surveillance and Response System (GISRS) and sentinel systems during COVID-19 pandemic. This new publication is due for publication soon.

GISAID has been an important partner of GISRS, and its EpiFlu database has been a key component of influenza surveillance since 2008. At the start of COVID-19 pandemic GISAID rapidly launched the EpiCoV platform, where the first complete genome of SARS-CoV-2 was shared globally, and various analytical tools were developed to support the rapid sharing and interpreting of SARS-CoV-2 data.

GISRS-GISAID collaboration on influenza has been expanded to other respiratory viruses including SARS-CoV-2 and Respiratory Syncytial Virus (RSV). A joint bioinformatics training programme was developed to support WHO Member States to expedite the effective genomic surveillance of SARS-CoV-2 using influenza surveillance systems.

Training workshops organized

To further strengthen GISRS genomic surveillance capacity, the WHO Global Influenza Programme and GISAID jointly organized a series of workshops with experts from National Influenza Centres (NICs) and National COVID-19 laboratories. The objectives of the training includes:

The course is divided into three modules, from basic to advanced levels.

Module 1 (Introductory) was recently completed. It was attended by more than 110 experts from over 40 countries across the world, from Algeria and Australia to the United States and Venezuela. It comprised online lectures with real-time demonstrations followed by offline exercises. The training was held over a period of several months and grouped into five small groups according to their time zone and language spoken.

The module covered the basics of virus sequencing; considerations for the genomic sequencing component of GISRS surveillance of SARS-CoV-2; and the submission, curation, annotation and basic interpretation of data using GISAID tools.

Module 2 (Intermediate) and Module 3 (Advanced) will be launched in the coming months.

As we have learnt from the COVID-19 pandemic, an effective genomic surveillance system using GISRS to monitor SARS-CoV-2, as well as for influenza, is a critical component of pandemic and post-pandemic response. WHO will continue to strengthen the global network of laboratories of GISRS.

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The essential task of strengthening genomic surveillance: WHO in collaboration with GISAID organizes training workshops for laboratory experts - World...

By Allison Proffitt

December 14, 2021 | Seven Bridges Genomics has launched a new subsidiary, the Unified Patient Network (UPN), to facilitate clinical research and collaboration between participating health systems and biopharma companies. The UPN will combine de-identified sequencing data and EHR content for five million patients and allow biopharma companies to license cohorts from that dataset for research. Licensing fees from biopharma will fund the network.

The Unified Patient Network is designed to leverage Seven Bridges unique capabilities in building ecosystems and bringing stakeholders together, William Moss, CEO of Seven Bridges, told Clinical Research News.

The UPN will harmonize 30x whole genome coverage for patients that opt-in with electronic health records from large health systems across the country. The UPNs objective is to include full datasets on five million participants within five years. Technical partners include Genome Medical, Amazon Web Services, the Broad Institute of MIT and Harvard, Illumina and others.

Moss serves as CEO of the UPN; David Ledbetter was named the Chief Clinical and Research Officer. Ledbetter was previously executive vice president and chief scientific officer at Geisinger Health System where he was the principal investigator for the MyCode biobank and precision health program that exceeded 175,000 patients with exome sequence data linked to rich, longitudinal EHR and other clinical data.

What makes the Unified Patient Network unique compared to any of the other programs that are out there that might be seen as somewhat similar is our focus on whole genome context, Moss explained. We are providingfrom a genomic perspective30x coverage whole genome data across the entire genome, utilizing similar techniques that we used in producing the content for the UK Biobank.

Connecting Health Systems, Patients, Pharma

The UPN will operate as a collaborative group of nonprofit academic health centers. Washington University School of Medicine in St. Louis and its affiliated health system, BJC HealthCare, is the first academic health system announced as a UPN member. Two others will be announced in the coming weeks, Moss said. These first three health system partners represent an addressable patient population of 20 million.

The UPN will operate across many disease states and therapeutic areas, including rare, complex neurodegenerative, psychiatric and autoimmune diseases and disorders, as well as cancer, cardiology and common diseases such as diabetes. Patients who volunteer for clinical research studies conducted as part of the UPN will need to provide informed consent to participate. A central institutional review board (IRB) will approve all studies.

From within the UPN, Biopharma companies can seek specific cohorts of patient data. Biopharma can actually tell us who they want, Moss said. They can say: were looking for 2,000 individuals with this type of cancer, who have received this treatment, and have either been responsive or non-responsivewhatever attributes those are.

Biopharma has the option of either using the deidentified EHR and genomic data from within the UPN, or re-contacting individual patients for more in-depth study through their health systems and physicians. The UPN does not have the capability of deidentifying patient records, Moss said. Those keys reside with the health systems, and physicians make initial contact with a patient.

A big part of what were doing is were embracing the health systems and the relationships between the health systems, the healthcare providers, and the patients, Moss said. We work with the health systems and the healthcare providers to find the participants who meet the needs of the biopharma, and theyre invited to participate in a research study.

Data licensing fees from biopharma support the UPN and go back to individual health systems to fund their own research as well. Companies have a six-to-nine-month embargo period on the data, Moss said, before it returns to the UPN and can be licensed and used by others. After the embargo period, that data becomes able to be licensed by other biopharmas. More importantly, that data becomes available to each of the health system members in order to enable them to enhance their precision medicine research and to actually be participating as learning health systems in precision medicine, he said.

The Data Plan

Only de-identified genomic and clinical EHR content will be made available via the database. The UPN is leveraging the secure Seven Bridges research and development ecosystem as the interoperability infrastructure for the community. The ARIA scientific intelligence system will enable exploration and analysis for complex cohort stratification across populations of millions of patients. Member health systems will be provided with a base-tier license of the Seven Bridges platform, Moss added.

Content will be made available only to credentialed researchers as part of IRB-approved research studies, as mutually agreed to by the UPN and the health system members, by leveraging Seven Bridges' proven security, authentication and authorization protocols and technologies.

Patients who previously provided consent for the UPN can opt at any time to have their de-identified genetic and clinical data removed from the network's database.

Counseling Commitment

Another foundational partner, Genome Medical, will provide genetics and genomics counseling for both participants and physicians. Sequencing findings will be returned to participantsthe specific list of returned results is still being decided, Moss saidand Genome Medical will also handle peer-to-peer counseling for physicians whose patients have new results.

This is about bringing along the population and the physician, and thats why we include peer-to-peer counseling, Moss said, so that the physician can learn from a genetics expert as to what are the meanings of the results and how does that get integrated into a care plan.

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Seven Bridges Launches the Unified Patient Network With Genomic, EHR Data - Bio-IT World

COLUMBUS, Ohio HIV replication in the human body requires that specific viral RNAs be packaged into progeny virus particles. A new study has found how a small difference in the RNA sequence canallow the viral RNA to be packaged for replication, creating potential targets for future HIV treatments.

The study, published last week in the Proceedings of the National Academy of Sciences, found that HIV chooses its viral RNA genome the source code that it injects into healthy human cells to infect them based on functions attributable to just two nucleotides.

Its just this two-nucleotide difference that makes such a dramatic effect, said Karin Musier-Forsyth, senior author of the study, Ohio Eminent Scholar and a professor of chemistry and biochemistry at The Ohio State University. If we can prevent it from packaging its own genome, we can prevent it from spreading inside the body.

The studys authors, who also include researchers from the National Cancer Institute, hoped to answer a long-standing question in HIV biology research: How does the virus know to package its specific viral RNA to be copied in human cells?

Just like we need a genome encoded by DNA, viruses have their own genomic DNA or RNA in the case of HIV its RNA and they have to package their genomic RNA and thats what this whole study is about, she said. Its an essential step for how we understand the replication of the virus.

RNA is a string of nucleotides, and it is present in some form or another in all living things, including viruses. In HIV, it carries the genetic information that allows the virus to copy itself inside a host the human body. HIV RNA comprises about 9,800 nucleotides.

We have lots of types of RNA in our cells as humans, including messenger RNA (mRNA), which is very abundant and which everyone has heard about now, thanks to COVID-19, Musier-Forsyth said. But the viral genome from HIV is made in small amounts, and it is very selectively packaged as genomic RNA, in addition to serving as mRNA to make viral proteins. How does the virus find this genomic RNA to package and not just package any old RNA in our cells?

Researchers believed if they could find an answer to that question, they might eventually be able to develop drugs that could block the virus from replicating and stop it from infecting healthy human cells.

The researchers examined the structures of two nearly identical HIV RNA strings and found that the virus used a two-nucleotide difference on the very end of the RNA strings to distinguish between genomic RNA and viral mRNA. One, they found, was more efficient at being packaged as a genome than the other due to the conformations, or structures, that it formed.

The findings could have implications for future HIV treatments that target RNA and would be different from current HIV treatments, which primarily target viral proteins. New HIV drugs based on this discovery are likely years away, but Musier-Forsyth said this finding is an important scientific step.

Now that we understand more about the structure of the RNA, we could develop therapeutics, whether they be small molecules or other new nucleic acid therapeutics, that could lock the RNA into a conformation that wouldnt be packaged. If it cant package its genome then it cant replicate, Musier-Forsyth said.

Other Ohio State researchers who contributed to this study include Shuohui Liu and Jonathan P. Kitzrow. This work was supported by the National Institutes of Health.

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CONTACT: Karin Musier-Forsyth, musier-forsyth.1@osu.edu

Written by Laura Arenschield, arenschield.2@osu.edu

Proceedings of the National Academy of Sciences

Selective packaging of HIV-1 RNA genome is guided by the stability of 5 untranslated region polyA stem

14-Dec-2021

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Study shows how HIV copies itself in the body - EurekAlert

Credit: Susanna Hamilton, Broad Communications

Researchers have boosted the efficiency of prime editing, a highly versatile CRISPR-based gene editing technology, and used the improved system to correct disease mutations in cells.

Scientists have developed a suite of molecular tools that increase the efficiency of a gene-editing technique called prime editing for a wide variety of cell types and target genes, expanding the scope of the technologys therapeutic and research applications. In two new studies, the researchers used the improved prime editing systems to correct mutations linked to various neurodegenerative, metabolic, and cardiovascular diseases.

First described in 2019, prime editing is a precise gene-editing method that has the potential to correct the vast majority of known disease-causing genetic variations. Researchers can use prime editing to make DNA substitutions, insertions, and deletions at targeted sites in human cells and animals. Editing efficiency, however, varies depending on the type of cell being edited and the target location in the genome.

To further develop the technology, scientists at the Broad Institute of MIT and Harvard engineered an improvement to a key component of the prime editing system called prime editing guide RNAs, or pegRNAs, which encode the intended edit and direct the prime editing machinery. In a study recently published in Nature Biotechnology, the researchers showed that pegRNAs can degrade in cells, resulting in truncated pegRNAs that interfere with prime editing. They developed new pegRNAs that are protected from degradation in cells, broadly increasing editing efficiency.

In a second study published recently in Cell, Broad researchers, collaborating with scientists at Princeton University and University of California, San Francisco (UCSF), identified cellular pathways that limit prime editing efficiency, and used these insights to develop next-generation prime editing systems.

The researchers on both studies demonstrated that the new systems could more efficiently edit mutations associated with Alzheimers disease, heart disease, sickle cell and prion diseases, type 2 diabetes, and other diseases, while producing fewer unwanted byproducts.

These improved prime editing efficiencies and product purities bring many edits from a regime in which they might be useful as research tools into a regime in which they may have potential as therapeutics, said David Liu, a senior author of both studies, Richard Merkin Professor and director of the Merkin Institute of Transformative Technologies in Healthcare at the Broad Institute, professor at Harvard University, and Howard Hughes Medical Institute investigator.

Credit: Broad Institute

Prime editing allows scientists to correct the vast majority of known disease-causing mutations including substitutions, insertions, or deletions of up to dozens of base pairs at specific sites in the genome. Unlike some other genome editing techniques, prime editing does not involve cutting both strands of DNA, and as a result reduces the chances of unwanted editing outcomes or undesired cellular responses. (See the infographic above for more on how prime editing works.) Hundreds of research groups are now using prime editing to study and correct mutations in a wide range of organisms including rice, wheat, zebrafish, and mice.

After first describing prime editing in 2019, Lius team continued to develop the technique. In the Nature Biotechnology study, they discovered a vulnerability in pegRNAs that decreased efficiency. They found that the long string of RNA at the end of the pegRNA that encodes the edit was susceptible to degradation by cellular enzymes. The degraded pegRNAs cannot mediate prime editing and also poison the prime editing system by blocking target sites from being accessed by intact pegRNAs.

The researchers next looked for protective structures that they could add to pegRNAs. They tested several different RNA sequences, identifying sequences that folded into knot-shaped structures that shield them from RNA-degrading enzymes. When they modified pegRNAs to include the knots and a connecting sequence, they observed a substantial increase in prime editing efficiency, indicating that the new structures preserved the RNA template for editing.

Using engineered pegRNAs, or epegRNAs, in a range of mammalian cell lines, the researchers saw that epegRNAs increased prime editing efficiency three- to four-fold on average, with greater improvements in cell lines in which prime editing had previously been more difficult.

In the Cell study, Lius team and their collaborators engineered the protein component of the prime editing system to further boost efficiency and minimize byproducts produced in a broad range of cell types, including cells from patients.

The researchers aimed to understand more comprehensively the cellular factors that determine prime editing outcomes so that they could design even more efficient systems. The team suspected that certain cellular proteins active during a key part of the prime editing process when the cell repairs DNA molecules created by prime editors could impede or even reverse editing and increase the production of unwanted byproducts. To test this hypothesis, the researchers collaborated with teams led by Britt Adamson, an assistant professor at Princeton University; and Jonathan Weissman, a professor at UCSF when the study began and now a professor at MIT, a member of the Whitehead Institute, and a Howard Hughes Medical Institute investigator. Using CRISPR interference-based screens, the teams systematically studied the effect of turning off each of 476 different DNA repair genes on prime editing.

Based on these results, the researchers focused on a process called mismatch repair, which occurs naturally in cells to correct DNA mismatches generated during DNA replication and repair. They found that mismatch repair interferes with prime editing, decreasing editing efficiency and increasing the fraction of unintended insertions or deletions.

Armed with this insight, the team developed new prime editing systems, which they called PE4 and PE5, that include a protein, MLH1dn, that the researchers engineered to temporarily inhibit one component of mismatch repair. In cells where mismatch repair occurs, the researchers found that PE4 and PE5 substantially increased editing efficiency and produced far fewer byproducts compared to the existing prime editing systems.

Finally, the scientists created PEmax, which optimized the architecture and amino acid sequence of the prime editing machinery. Combining improvements from the PE4 and PE5 systems, PEmax, and epegRNAs resulted in a 10- to 100-fold boost in editing efficiency compared to existing systems.

By combining the expertise of different research groups, we were able to figure out how prime editing works and optimize parts of the system, said Adamson. This study is a beautiful example of how fundamental understanding can drive experimental design.

Liu says that in many cases, the combined improvements of epegRNAs and PE4/5/max make it easier for scientists to create cell models of disease, a critical step toward developing therapeutics.

The team is now using these systems to treat cell and animal models of genetic disease, and will continue to probe the fundamental biology of these systems.

All of these innovations are synergistic, said Liu. With these improvements, weve been able to edit important cell types with an efficiency and cleanliness that may one day help patients who suffer from diseases with a genetic component. These findings also suggest that there are other strategies out there that can further improve prime editing.

References:

Enhanced prime editing systems by manipulating cellular determinants of editing outcomes by Peter J. Chen, Jeffrey A. Hussmann, Jun Yan, Friederike Knipping, Purnima Ravisankar, Pin-Fang Chen, Cidi Chen, James W. Nelson, Gregory A. Newby, Mustafa Sahin, Mark J. Osborn, Jonathan S. Weissman, Britt Adamson and David R. Liu, 14 October 2021, Cell.DOI: 10.1016/j.cell.2021.09.018

Engineered pegRNAs improve prime editing efficiency by James W. Nelson, Peyton B. Randolph, Simon P. Shen, Kelcee A. Everette, Peter J. Chen, Andrew V. Anzalone, Meirui An, Gregory A. Newby, Jonathan C. Chen, Alvin Hsu and David R. Liu, 4 October 2021, Nature Biotechnology.DOI: 10.1038/s41587-021-01039-7

This work was supported by the Merkin Institute of Transformative Technologies in Healthcare, the National Institutes of Health, the Howard Hughes Medical Institute, the Loulou Foundation, and the Bill & Melinda Gates Foundation.

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Next Generation Prime Gene Editing Systems Expands Technologys Therapeutic and Research Applications - SciTechDaily

Introduction

The Global Action Plan on Antimicrobial Resistance drafted by the World Health Organization1 states that there is a need to understand the impact of human activities on the environment, particularly the spread and transfer of antimicrobial resistance genes (ARGs) and strains. The isolation rates of antimicrobial-resistant bacteria (ARB) are lower in Japan than those in other countries, but are steadily increasing.2

In several countries, extended spectrum -lactamase (ESBL)-producing Escherichia coli or carbapenemase-producing organisms have been detected from water environments,3 wastewater treatment plants (WWTP), treated water,4,5 and hospital sewage,4,6 and Japan is no exception.7,8 In particular, hospital wastewater contaminated by ARB and residual antibiotics may generate selective pressure for the development of ARB,9,10 and is considered a hot spot for the growth and propagation of ARB.6

Similar to the general sewage system, hospital sewage is also discharged into a public WWTP and treated by filtering, microbiological treatment, and chlorination, after which the effluent is discharged into a nearby river. Although it is not yet clear whether the hospital wastewater-related ARB disseminate into the waterbodies, ARB is observed to exhibit deleterious effects on human health. In recent years, management strategies for ARB/ARGs and residual antibiotics discharged from hospitals have been studied in several countries.11,12

The aim of this study is to illustrate the contamination of hospital sewage with ARB harboring ARGs using comprehensive metagenomic sequencing.

In addition, this study was conducted in line with the relocation to a new hospital, and the formation of the bacterial flora in the new sewage tank was investigated. We also compared the whole genome sequence of extended spectrum -lactamase (ESBL)-producing organisms (EPOs) isolated from hospital sewage and clinical samples, and analyzed the relationship between clinical and sewage isolates.

The study was conducted at the Ohashi Medical Center in Toho University, located in Jonan area, Tokyo, Japan. The Ohashi Medical Center (35.652573N, 139.685833E), with a capacity of 430 beds, was opened in 1973 with a single East building (BE) and expanded to Central (BC), Administration (BA), and West (BW) buildings to increase patient capacity (Figure 1). Features of each building are as follows: there were intensive care wards in BW; the number of beds was the largest among the old hospital buildings in BC; BE included the highest number of outpatient departments; and many of the rooms in BA were available only for healthcare workers.

Figure 1 Outline of the Ohashi Medical Center, Toho University. Prior to relocation to the new building (BN), the hospital consisted of four buildings: West building (BW), Administration building (BA), Central building (BC), and East building (BE). Each building had respective sewage tanks: BW: STW, BA: STA, BC: STC, BE: STE, BN: STN.

As part of a renovation plan, a new hospital building (BN; 35.652578N, 139.683959E) with 319 beds was constructed approximately 50 m away from the old hospital and was inaugurated on June 20, 2018. Since May 2018, we introduced a policy of restricted hospitalization (Figure S1). We stopped providing services to outpatients from June 16 and transferred the 66 hospitalized patients to the BN on the same day (Figure S1). We started accepting patients on June 20. Both the old and new hospitals have a staff count of 2000. In BN, all outpatient departments and wards were integrated into one building (Figure 1).

In both old and new hospitals, stool and urine are stored in the underground sewage tanks without mixing with other drainage and are pumped to the sewage system several times a day (Figure 1). In the old hospital, each building had respective sewage tanks (sewage tank in BW: STW, in BA: STA, in BC: STC, and in BE: STE as shown in Figure 1); however, the new hospital had two connected storage tanks of 22.5 m3 collecting all the sewage (sewage tank in BN: STN shown in Figure 1). It was impossible to quantify daily inflow and outflow of sewage tanks as there is no system for regular measurement. The sewage discharged from the tanks is sent to the WWTP and treated using filtering, and microbiological and biochemical treatments, after which the effluent is discharged into the nearby river.

In the period between May 8 and June 12, 2018, sewage samples were collected from STW, STA, STC, and STE once a week. In the period from June 6 to July 17, 2018, sewage samples were collected from the STN once a week at 9 a.m. A 20 mL of sewage samples were collected in sterile bottles from manhole of the sewage tanks and processed for analysis within 2 h.

First, 5 mL of sewage was centrifuged at 5000 g for 5 min and the resultant cell pellet was vortexed with remaining 500 L of sewage water. Next, the cell suspension was mixed with 500 L of phenol/chloroform/isoamylalcohol (PCI) in a microcentrifuge tube with 2 mL of ZR BashingBead Lysis tube. Cell breaking was performed using GenoGrinder 2010 by shaking at 1500 rpm for 5 min. The PCI mixture was centrifuged at 8000 rpm for 5 min, followed by DNA purification using a Gel DNA Recovery Kit, Zymoclean-96 (ZYMO RESEARCH, Irvine, CA, USA). A metagenome DNA-seq library was prepared using the QIAseq FX DNA library prep kit (Qiagen, Venlo, Netherlands) and subsequently was performed using NextSeq 500 (Illumina) with the NextSeq 500 mid output kit v2.5 (300 cycles).

To obtain EPOs from hospital sewage, 2 L of sewage sample was mixed with 100 L phosphate-buffered saline (PBS), plated on CHROMagar ESBL (bioMrieux, Marcy-lEtoile, France) for selection of EPOs, and incubated at 36C overnight. Subsequently, first appearance of color formation on each colony suggested that dark pink and metallic blue colonies were in the ratio of 1:4, respectively. Eighty colonies (20 dark pink colonies: potential ESBL-producing E. coli; 60 metallic blue colonies: potential Klebsiella, Enterobacter, Citrobacter) were selected as potential EPOs to identify a unique isolate from the first selection on CHROMagar ESBL plate. Each isolate was used for genomic analysis as described above.

In addition, all bacteria colonies on a single agar plate were harvested and mixed with 1000 L of PBS. The cell suspension was used for metagenomic analysis as described above.

All 20 EPO clinical isolates obtained between May 8 and July 17, 2018, and reported as EPO were subjected to whole genome sequencing and comparative genomics. Among these isolates, 12 isolates were from outpatients and 11 isolates were from urology patients. They included urine, sputum, and central venous catheter samples (75%, 10%, and 10%, respectively). Some specimens were obtained from the same patient through subsequent diagnosis. The Ethics Committee of the Toho University Ohashi Medical Center waived the requirement for consent because the research was conducted without using identifiable biospecimens. Personal data related to clinical information were anonymized, and our procedure does not require a written consent from patients suffering from bacterial infections. Antimicrobial susceptibility was determined through screening (broth microdilution method) and confirmatory tests (the disk diffusion method) according to the Clinical and Laboratory Standards Institute (CLSI) recommendations (CLSI Performance Standards for antimicrobial disk susceptibility tests; Approved standard-13th edition CLSI document M02. Wayne, PA: Clinical and Laboratory Standards Institute; 2018).

The sequencing reads were analyzed using the MePIC2,13 Krona14 and MEGAN v6 software.15 EPO isolates were characterized using Krona,14 multi-locus sequence typing (MLST)16 and ResFinder.17

The sequenced reads were assigned to a taxonomic hierarchy using MEGAN v6 software based on a megaBLAST nucleic acid homology search.

Comparative genomics among obtained E. coli isolates (16 isolates from patients and 21 isolates from hospital sewage) were performed using BWA-MEM18 against the complete chromosome sequence of E. coli STN0717-11, which is the longest genome size among available complete genomes, followed by extraction of single nucleotide variants (SNVs) using VarScan v2.3.4.19 The prophage and repeat regions were predicted using PHASTER20 and MUMmer 3,21 respectively, and the detected SNVs in these regions were excluded. Regions of recombination in the chromosome were predicted using Gubbins v. 2.3.4,22 followed by masking of SNVs in the recombination regions. A maximum likelihood phylogenetic tree was constructed from SNV sites in the core genome region using FastTree2. De novo assembly was performed using SKESA v.2.3.023 with short reads of each strain, followed by analysis of sequence type, putative serotype, and AMR gene prediction using pubMLST (https://pubmlst.org/escherichia/), SeroTypeFinder,24 and Bacterial Antimicrobial Resistance Reference Gene Database (BioProject ID: PRJNA313047), respectively.

Thirty-nine drug components (Table 1) in the sewage samples were analyzed using solid-phase extraction (SPE) and ultra-performance liquid chromatographytandem mass spectrometry (LC-MS/MS) based on a previously described method25 with minor modifications. Briefly, the sample was filtered using a polyethersulfone membrane (0.22 m pore size, Merck) and 100 mL of the filtrate was spiked with 1 g/L ascorbic acid, 1 g/L EDTA, and a surrogate standard mixture, and then concentrated using SPE cartridge (Oasis HLB cartridges, 200 mg/6 cc, Waters, Japan). The analytes concentrated on the cartridge were extracted with 6 mL of methanol, following which they were measured using LC-MS/MS and quantified by the alternative surrogate method.25

Table 1 Concentrations of Chemical Compounds in the Hospital Sewage Tank

Metagenome DNA-seq analysis of sewage samples was conducted to elucidate the differential microbial flora in the hospital sewage tank. The dominant bacteria in the sewage were classified according to the metagenomic data (Supplemental Data Set S1), wherein the proportion of genera varied depending on the building (Figure S2a and S2b).

Similarity and diversity of bacterial population among tanks were analyzed using PCoA based on bacterial genus level (Figure 2). A total of 25 sewage samples from each tank excluding STA were used for PCoA, and the results showed that the STN and STW groups were closely plotted by the presence of Aeromonas, Citrobacter, and Comamonas.

Figure 2 PCoA plot based on NGS read counts detected by metagenome DNA-Seq. PCoA was performed according to Bray Curtis distance (the average linkage). The genera, Acinetobacter, Citrobacter, and Comamonas were frequently detected in STW and STN samples. Most severely ill inpatients were treated in the BW and BN; thus, their excretion may have a major impact on the bacterial content of the sewage tanks.

Metagenome next-generation sequence (NGS) reads corresponding to -lactamase genes were identified in original hospital sewage samples (Figure S3a) and EPOs from each tank selected on CHROMagar ESBL (Figure S3b). In the original hospital sewage samples, the blaIMP gene was detected in STC and STW samples, and the blaCTX-M gene was detected in STW and STN samples (Figure S3a). CHROMagar ESBL selection facilitated the detection of blaIMP and blaCTX-M from all sewage tanks (Figure S3b).

Whole genome sequencing was performed for 80 EPO isolates from STW0522 and STN0717, and 20 EPO clinical isolates (May 8 to July 17, 2018) for comparison of EPOs from sewage tanks and clinical sources. In sewage samples, E. coli, Klebsiella, Enterobacter, Citrobacter, and Achromobacter were detected (Table S1). Clinical isolates included only E. coli and Klebsiella spp.

A pairwise SNV analysis of the core genome was conducted for all E. coli strains (Figure 3). The E. coli STs included ST393, ST38, ST131, ST1011, ST12, ST73, ST9586, and ST224. E. coli ST12, ST73, ST131, and ST1011 were detected exclusively in clinical isolates (Table S2). Clinical isolates (THO-008 and 019 from the same patient) comprised ST393 harbouring blaCTX-M-27 and there was no difference in SNVs between these isolates and those obtained from sewage samples (14 isolates; STN0717-1 to 11, 14, 15, and 19) (Figure 3, Supplemental Data Set S2).

Figure 3 Core genome phylogeny using single-nucleotide variations (SNVs) of ESBL-producing E. coli isolates. Core genome phylogeny was constructed using ESBL-producing E. coli isolates; 20 clinical isolates (THO-number, orange highlighted), one sewage isolate from STW0522 (brown highlighted), and 20 sewage isolates from STN0717 (blue highlighted). The complete genome sequence of STN0717-11 was used as a genome reference and 39.48% of the genome sequence was used as core genome regions among all tested strains. Few clinical isolates were obtained from same patient (, patient No.8; , patient No.9; , patient No.7 in Supplement Data Set S2). Heatmap of pairwise differences of core genome SNVs are shown using a colour gradient with pink and red. The lower half part indicates core genome SNVs among all strains, and the upper half part shows core genome SNVs between indicated two strains. THO-008 and -019 from the same patient showed no SNVs with sewage isolates (14 isolates; STN0717-1 to 11, 14, 15, and 19). There were no identical clones between different patients.

In three ST38 clinical isolates (THO-002, THO-007 and THO-020) harboring blaCTX-M-14, SNV analysis revealed marked 21110 SNVs in the core genome. It was reported that molecular evolution of E. coli genome is possible with less than five SNVs within a 60-day duration.26 By contrast, ST38 sewage isolates harboring blaCTX-M-55 exhibited strict clonality with 3 SNVs, and 123 SNVs were detected in clinical isolates (Figure 3). Five ST131 clinical isolates harboring various CTX-M genes (blaCTX-M-15, CTX-M-27, CTX-M-44) were not identical (Figure 3). Among the 156 CHROMagar ESBL-positive strains from hospital sewage tanks (STW0522 and STN0717; Supplemental Data Set S2), carbapenemase gene (blaIMP-11) was identified only in Pseudomonas monteilii (Table 2).

Table 2 ESBL-Producer in Hospital Sewage and Clinical Isolate

The measurement of the concentrations of chemical contaminants in the tank (Table 1) showed that the most predominant antimicrobial agents were levofloxacin (32,500 ng/L) and clarithromycin (13,500 ng/L), although their concentrations were below minimal inhibitory concentration breakpoints. -Lactam antibiotics were not measured in this study; as they are known to be almost undetectable in environmental samples.27,28

The composition of bacterial flora in hospital sewage has been reported to comprise components of the human gut flora, including Bacteroides, Faecalibacterium, Bifidobacterium, and Blautia, in addition to Klebsiella, Aeromonas, and Enterobacter.6 The bacterial flora in each tank in the old hospital exhibited different bacterial compositions, and that of STC and STE mainly comprised the members of the human gut flora. However, the STW was mainly composed of Citrobacter and Acinetobacter, which are minimally detected in the gut of healthy individuals (Figure S2a and b).29,30 Furthermore, Comamonas and Arcobacter were detected in significant numbers in the STN. Comamonas is generally considered as environmental bacteria with less pathogenicity. Arcobacter spp. are detected in WWTP in several countries.31,32 The hospital sewage is influenced by the patients gut flora,29,33 but it is unclear whether the difference in the bacterial composition of each tank reflects the characteristics of the patients in each building.

Thus, the bacterial composition of STN appears similar to that of STW (Figure 3). BW and BN contain rooms where seriously ill patients are treated (Figure 1). The distribution of bacterial flora in the tanks can be strongly influenced by the severity of illness of the patients in the wards. Furthermore, bacterial flora in the tanks can be instantly affected by excrement because the bacterial composition of STN was comparable to that of STW within 1 month after the relocation. For monitoring department-specific ARB, it may be beneficial to install department-specific sewage tanks.

In Japan, the detection rate of EPO has been reported at 12.2% in healthy adult volunteers.34 Particularly, ST131 is an E. coli strain responsible for a worldwide pandemic and it carries a broad range of pathogenicity and ARGs, including a variety of -lactamase genes on a transferable plasmid.3537 In Japan, it has been reported that 92.9% of EPOs are blaCTX-M gene positive.38 The CTX-M genes (blaCTX-M-14, blaCTX-M-15, blaCTX-M-27 and blaCTX-M-2, listed in descending order of size)39 have been identified in Japan as well, and gene sequences obtained in this study are similar to that (Table 2).

A pairwise SNV analysis showed that the sequences of certain clinical EPO isolates had no difference compared to the SNVs of sewage isolates, suggesting that these sewage isolates may have originated from the patient. Fortunately, there was no strong evidence of a nosocomial outbreak associated with clinical EPOs (Figure 3). Monitoring of ARB/ARGs in hospital sewage may enable detection of latent carriers or nosocomial infections.

The carbapenemase gene (blaIMP-11) in the hospital sewage tanks (STW0522 and STN0717; Supplemental Data Set S2) was identified only in Pseudomonas monteilii (Table 2). P. monteilii was isolated from the environment,40 clinical samples,41 and hospital environment.40,42 P. monteilii is less pathogenic to humans, but may play a role as a metallo--lactamase (MBL) reservoir, and transfer of MBL genes to other species may be a cause of concern, especially in hospital sewage tanks.41,42 Many of these potential EPOs harboring ARGs in the sewage tanks were different from the clinical isolates. It is not clear whether these EPOs were excreted by healthy carriers or were transformed by acquiring the ARGs in the sewage tank.

The concentrations of ciprofloxacin and clarithromycin in hospital wastewater43,44 reported previously were similar to those in the present study. Hospital sewage tanks may promote the development of AMR by high selective pressure on bacteria,9,10,45 even at very low concentrations46 and provide optimal conditions47 for horizontal gene transfer, which is one of the mechanisms associated with the spread of AMR in the environment.48 It is known that the microbial gut flora function as a reservoir for ARGs and horizontal plasmid transfer between bacteria is common.49 This is plausible as sewage tanks consist of an accumulation of excrement and acquisition of resistance may occur frequently. We presume that selective pressure of antibiotics exists in our hospital sewage tanks; however, this will be verified in future studies.

In Japan, KPC-2-producing Klebsiella7 and NDM-5-coproducing E. coli8 were detected in the effluent of WWTP. Effective actions should be taken, including advanced wastewater treatment processes such as ozone and UV treatment11,50 and ultrafiltration51 to accelerate the removal of ARB in WWTP. However, even the above methods do not ensure a complete removal of ARB. Therefore, treatment processes may be introduced prior to the release of hospital sewage into the main sewage to reduce ARB. In Japan, there are a few reports of contamination of hospital sewage tanks with ARB/ARGs.52,53 Nevertheless, this study is the first comprehensive description of AMR in a hospital setting using metagenomic and whole genome analysis.

Our study reveals the presence of ARB/ARGs in the hospital sewage tanks and suggests that every hospital patient/staff/visitor can be a potential source of ARB. Monitoring of ARB/ARGs in hospital sewage is expected to identify the presence of carriers, and control nosocomial outbreaks and dissemination of ARB/ARGs in the environment.

The authors would like to thank Dr Yoshinobu Sumiyama, Chairman, Toho University and Dr Satoshi Iwabuchi, Hospital Director for giving us permission to conduct this research. We are grateful to Mr Umezu Masahiro for helping for sampling of hospital sewage. We gratefully acknowledge the staff members of the Laboratory of Bacterial Genomics, Pathogen Genomics Center, National Institute of Infectious Diseases, Tokyo, Japan.

The authors report no conflicts of interest in this work.

1. World Health Organization. Global action plan on antimicrobial resistance; 2016. Available from: https://www.who.int/publications/i/item/9789241509763. Accessed August 24, 2021.

2. Gekenidis MT, Qi W, Hummerjohann J, Zbinden R, Walsh F, Drissner D. Antibiotic-resistant indicator bacteria in irrigation water: high prevalence of extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli. PLoS One. 2018;13(11):e0207857. doi:10.1371/journal.pone.0207857

3. Nascimento T, Cantamessa R, Melo L, et al. International high-risk clones of Klebsiella pneumoniae KPC-2/CC258 and Escherichia coli CTX-M-15/CC10 in urban lake waters. Sci Total Environ. 2017;598:910915. doi:10.1016/j.scitotenv.2017.03.207

4. Proia L, Anzil A, Borrego C, et al. Occurrence and persistence of carbapenemases genes in hospital and wastewater treatment plants and propagation in the receiving river. J Hazard Mater. 2018;358:3343. doi:10.1016/j.jhazmat.2018.06.058

5. Makowska N, Philips A, Dabert M, et al. Metagenomic analysis of beta-lactamase and carbapenemase genes in the wastewater resistome. Water Res. 2020;170:115277. doi:10.1016/j.watres.2019.115277

6. Ng C, Tay M, Tan B, et al. Characterization of Metagenomes in Urban Aquatic Compartments Reveals High Prevalence of Clinically Relevant Antibiotic Resistance Genes in Wastewaters. Front Microbiol. 2017;8:2200. doi:10.3389/fmicb.2017.02200

7. Sekizuka T, Yatsu K, Inamine Y, et al. Complete Genome Sequence of a blaKPC-2-Positive Klebsiella pneumoniae Strain Isolated from the Effluent of an Urban Sewage Treatment Plant in Japan. mSphere. 2018;3(5). doi:10.1128/mSphere.00314-18.

8. Sekizuka T, Inamine Y, Segawa T, Kuroda M. Characterization of NDM-5- and CTX-M-55-coproducing Escherichia coli GSH8M-2 isolated from the effluent of a wastewater treatment plant in Tokyo Bay. Infect Drug Resist. 2019;12:22432249. doi:10.2147/IDR.S215273

9. Lien TQ, Lan PT, Chuc NTK, et al. Antibiotic Resistance and Antibiotic Resistance Genes in Escherichia coli Isolates from Hospital Wastewater in Vietnam. Int J Environ Res Public Health. 2017;14(7):699. doi:10.3390/ijerph14070699

10. Kummerer K, Henninger A. Promoting resistance by the emission of antibiotics from hospitals and households into effluent. Clin Microbiol Infect. 2003;9(12):12031214. doi:10.1111/j.1469-0691.2003.00739.x

11. Jager T, Hembach N, Elpers C, et al. Reduction of antibiotic resistant bacteria during conventional and advanced wastewater treatment, and the disseminated loads released to the environment. Front Microbiol. 2018;9:2599. doi:10.3389/fmicb.2018.02599

12. Paulus GK, Hornstra LM, Alygizakis N, Slobodnik J, Thomaidis N, Medema G. The impact of on-site hospital wastewater treatment on the downstream communal wastewater system in terms of antibiotics and antibiotic resistance genes. Int J Hyg Environ Health. 2019;222(4):635644. doi:10.1016/j.ijheh.2019.01.004

13. Takeuchi F, Sekizuka T, Yamashita A, Ogasawara Y, Mizuta K, Kuroda M. MePIC, metagenomic pathogen identification for clinical specimens. Jpn J Infect Dis. 2014;67(1):6265. doi:10.7883/yoken.67.62

14. Ondov BD, Bergman NH, Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinform. 2011;12:385. doi:10.1186/1471-2105-12-385

15. Huson DH, Beier S, Flade I, et al. MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data. PLoS Comput Biol. 2016;12(6):e1004957. doi:10.1371/journal.pcbi.1004957

16. Larsen MV, Cosentino S, Rasmussen S, et al. Multilocus sequence typing of total-genome-sequenced bacteria. J Clin Microbiol. 2012;50(4):13551361. doi:10.1128/JCM.06094-11

17. Zankari E, Hasman H, Cosentino S, et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother. 2012;67(11):26402644. doi:10.1093/jac/dks261

18. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26(5):589595. doi:10.1093/bioinformatics/btp698

19. Koboldt DC, Chen K, Wylie T, et al. VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics. 2009;25(17):22832285. doi:10.1093/bioinformatics/btp373

20. Arndt D, Grant JR, Marcu A, et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 2016;44(W1):W1621. doi:10.1093/nar/gkw387

21. Kurtz S, Phillippy A, Delcher AL, et al. Versatile and open software for comparing large genomes. Genome Biol. 2004;5(2):R12. doi:10.1186/gb-2004-5-2-r12

22. Croucher NJ, Page AJ, Connor TR, et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res. 2015;43(3):e15. doi:10.1093/nar/gku1196

23. Souvorov A, Agarwala R, Lipman DJ. SKESA: strategic k-mer extension for scrupulous assemblies. Genome Biol. 2018;19(1):153. doi:10.1186/s13059-018-1540-z

24. Joensen KG, Tetzschner AM, Iguchi A, Aarestrup FM, Scheutz F. Rapid and Easy In Silico Serotyping of Escherichia coli Isolates by Use of Whole-Genome Sequencing Data. J Clin Microbiol. 2015;53(8):24102426. doi:10.1128/JCM.00008-15

25. Narumiya M, Nakada N, Yamashita N, Tanaka H. Phase distribution and removal of pharmaceuticals and personal care products during anaerobic sludge digestion. J Hazard Mater. 2013;260:305312. doi:10.1016/j.jhazmat.2013.05.032

26. Lee K, Izumiya H, Iyoda S, Ohnishi M. Effective surveillance using multilocus variable-number tandem-repeat analysis and whole-genome sequencing for enterohemorrhagic Escherichia coli O157. Appl Environ Microbiol. 2019;85:17. doi:10.1128/AEM.00728-19

27. Li D, Yang M, Hu J, Zhang Y, Chang H, Jin F. Determination of penicillin G and its degradation products in a penicillin production wastewater treatment plant and the receiving river. Water Res. 2008;42(12):307317. doi:10.1016/j.watres.2007.07.016

28. Zhou LJ, Ying GG, Liu S, et al. Occurrence and fate of eleven classes of antibiotics in two typical wastewater treatment plants in South China. Sci Total Environ. 2013;452453:365376. doi:10.1016/j.scitotenv.2013.03.010

29. Tang WHW, Li DY, Hazen SL. Dietary metabolism, the gut microbiome, and heart failure. Nat Rev Cardiol. 2019;16(3):137154. doi:10.1038/s41569-018-0108-7

30. Kurokawa K, Itoh T, Kuwahara T, et al. Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes. DNA Res. 2007;14(4):169181. doi:10.1093/dnares/dsm018

31. Merga JY, Royden A, Pandey AK, Williams NJ. Arcobacter spp. isolated from untreated domestic effluent. Lett Appl Microbiol. 2014;59(1):122126. doi:10.1111/lam.12256

32. Ghaju Shrestha R, Sherchan SP, Kitajima M, Tanaka Y, Gerba CP, Haramoto E. Reduction of Arcobacter at Two Conventional Wastewater Treatment Plants in Southern Arizona, USA. Pathogens. 2019;8(4). doi:10.3390/pathogens8040175

33. Usami M, Miyoshi M, Yamashita H. Gut microbiota and host metabolism in liver cirrhosis. World J Gastroenterol. 2015;21(41):1159711608. doi:10.3748/wjg.v21.i41.11597

34. Higa S, Sarassari R, Hamamoto K, et al. Characterization of CTX-M type ESBL-producing Enterobacteriaceae isolated from asymptomatic healthy individuals who live in a community of the Okinawa Prefecture, Japan. J Infect Chemother. 2019;25(4):314317. doi:10.1016/j.jiac.2018.09.005

35. Bevan ER, Jones AM, Hawkey PM. Global epidemiology of CTX-M beta-lactamases: temporal and geographical shifts in genotype. J Antimicrob Chemother. 2017;72(8):21452155. doi:10.1093/jac/dkx146

36. Harris PNA, Ben Zakour NL, Roberts LW, et al. Whole genome analysis of cephalosporin-resistant Escherichia coli from bloodstream infections in Australia, New Zealand and Singapore: high prevalence of CMY-2 producers and ST131 carrying blaCTX-M-15 and blaCTX-M-27. J Antimicrob Chemother. 2018;73(3):634642. doi:10.1093/jac/dkx466

37. Noguchi T, Matsumura Y, Kanahashi T, et al. Role of TEM-1 beta-lactamase in the predominance of ampicillin-sulbactam-nonsusceptible Escherichia coli in Japan. Antimicrob Agents Chemother. 2019;63(2). doi:10.1128/AAC.02366-18.

38. Luvsansharav UO, Hirai I, Niki M, et al. Prevalence of fecal carriage of extended-spectrum beta-lactamase-producing Enterobacteriaceae among healthy adult people in Japan. J Infect Chemother. 2011;17(5):722725. doi:10.1007/s10156-011-0225-2

39. Nakane K, Kawamura K, Goto K, Arakawa Y. Long-term colonization by bla(CTX-M)-harboring Escherichia coli in healthy japanese people engaged in food handling. Appl Environ Microbiol. 2016;82(6):18181827. doi:10.1128/AEM.02929-15

40. Remold SK, Brown CK, Farris JE, Hundley TC, Perpich JA, Purdy ME. Differential habitat use and niche partitioning by Pseudomonas species in human homes. Microb Ecol. 2011;62(3):505517. doi:10.1007/s00248-011-9844-5

41. Ocampo-Sosa AA, Guzman-Gomez LP, Fernandez-Martinez M, et al. Isolation of VIM-2-producing Pseudomonas monteilii clinical strains disseminated in a tertiary hospital in northern Spain. Antimicrob Agents Chemother. 2015;59(2):13341336. doi:10.1128/AAC.04639-14

42. Scotta C, Juan C, Cabot G, et al. Environmental microbiota represents a natural reservoir for dissemination of clinically relevant metallo-beta-lactamases. Antimicrob Agents Chemother. 2011;55(11):53765379. doi:10.1128/AAC.00716-11

43. Wiest L, Chonova T, Berge A, et al. Two-year survey of specific hospital wastewater treatment and its impact on pharmaceutical discharges. Environ Sci Pollut Res Int. 2018;25(10):92079218. doi:10.1007/s11356-017-9662-5

44. Le TH, Ng C, Chen H, et al. Occurrences and characterization of antibiotic-resistant bacteria and genetic determinants of hospital wastewater in a tropical country. Antimicrob Agents Chemother. 2016;60(12):74497456. doi:10.1128/AAC.01556-16

45. Coutu S, Rossi L, Barry DA, Rudaz S, Vernaz N. Temporal variability of antibiotics fluxes in wastewater and contribution from hospitals. PLoS One. 2013;8(1):e53592. doi:10.1371/journal.pone.0053592

46. Gullberg E, Cao S, Berg OG, et al. Selection of resistant bacteria at very low antibiotic concentrations. PLoS Pathog. 2011;7(7):e1002158. doi:10.1371/journal.ppat.1002158

47. Acuna V, Casellas M, Font C, Romero F, Sabater S. Nutrient attenuation dynamics in effluent dominated watercourses. Water Res. 2019;160:330338. doi:10.1016/j.watres.2019.05.093

48. Bengtsson-Palme J, Kristiansson E, Larsson DGJ. Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiol Rev. 2018;42(1). doi:10.1093/femsre/fux053

49. Goren MG, Carmeli Y, Schwaber MJ, Chmelnitsky I, Schechner V, Navon-Venezia S. Transfer of carbapenem-resistant plasmid from Klebsiella pneumoniae ST258 to Escherichia coli in patient. Emerg Infect Dis. 2010;16(6):10141017. doi:10.3201/eid1606.091671

50. Krzeminski P, Schwermer C, Wennberg A, Langford K, Vogelsang C. Occurrence of UV filters, fragrances and organophosphate flame retardants in municipal WWTP effluents and their removal during membrane post-treatment. J Hazard Mater. 2017;323(Pt A):166176. doi:10.1016/j.jhazmat.2016.08.001

51. Hembach N, Alexander J, Hiller C, Wieland A, Schwartz T. Dissemination prevention of antibiotic resistant and facultative pathogenic bacteria by ultrafiltration and ozone treatment at an urban wastewater treatment plant. Sci Rep. 2019;9(1):12843. doi:10.1038/s41598-019-49263-1

52. Okubo T, Hasegawa T, Fukuda A, et al. Screening of hospital-manhole sewage using MacConkey agar with cefotaxime reveals extended-spectrum -lactamase (ESBL)-producing Escherichia coli. Int J Antimicrob Agents. 2019;54(6):831833. doi:10.1016/j.ijantimicag.2019.08.004

53. Azuma T, Otomo K, Kunitou M, et al. Environmental fate of pharmaceutical compounds and antimicrobial-resistant bacteria in hospital effluents, and contributions to pollutant loads in the surface waters in Japan. Sci Total Environ. 2019;657:476484. doi:10.1016/j.scitotenv.2018.11.433

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Antimicrobial resistant bacteria in the sewage of a hospital | IDR - Dove Medical Press

It's been a rough year for Cathie Wood's ARK Genomic Revolution ETF (NYSEMKT:ARKG). The exchange-traded fund has fallen more than 30% so far in 2021.In this Motley Fool Live video recorded on Dec. 1, Motley Fool contributors Keith Speights and Brian Orelli discuss whether or not the ETF is a buy after sinking so much.

Keith Speights: Brian, we also had a question on Monday about Cathie Wood's ARK Genomic Revolution ETF falling significantly this year. This ETF is down more than 30% year to date with roughly half of that drop coming over just the last few weeks. Why is this ETF sliding so much and do you think it's a good pick for investors now?

Brian Orelli: Yeah. The top holdings of the ETF are Teladocthat's TDOC, Exact Sciences, EXAS, Pacific Biosciences of Californiawhich is PACB, Fate Therapeutics which is FATE, and Ionis Pharmaceuticals,which is IONIS.

This is an actively managed ETF so it's not easy to track down what was held at the beginning of the year. But of those five only PacBio is up for the year. And it's up big -- 50% -- so perhaps it wasn't even in the top five at the beginning of the year.

Teladoc and Ionis are both down 48% for the year, Exact Sciences is down 27% and then Fate is only down 5%. Then the XBI, which is the SPDR S&P Biotech ETF, which is an index ETF so it doesn't change very often, is down 12% for the year.

It's been a bad year for biotech investors but Cathie Wood's is definitely losing to the broader biotech market for small companies. Should you buy genomics ETF versus investing in individual stocks? I mean, I own three of the top seven, so the sixth and seventh are Vertex Pharmaceuticalsand Twist Biosciences.

I'm kicking myself for not investing in PacBio after Illumina wasn't able to acquire it. That seemed like a good investment, and I didn't make it and definitely PacBio's jumped substantially this year.

I think she's a pretty good stock picker. I guess she is just been unlucky and picked the wrong biotechs this year. Personally, I'd rather know what I own rather than having a moving target owning and actively managed ETFs. But if you're looking for exposure to the biotech sector without needing to do research on a bunch of companies, investing in ARK ETFs seems reasonable, I guess.

Speights: Yeah. I think that's a good answer, Brian and you're right. Cathie Wood is a pretty good stock picker. Her ETFs in general have performed really well. I think several of her ETFs are in the top 10 performers over the last five years.

But the other thing is, don't look at just year-to-date performance. You mentioned quite a few biotechs that are the top holdings. Many, if not all of those, probably have great long-term prospects. This just has been a bad year for biotech, right?

Orelli: Yeah. I mean, of course, Teladoc is down just because there were high expectations of the stock and that's actually the largest holding. I think that's probably dropping the overall ETF return substantially. It's probably due to Teladoc's drop. Although I'm not sure if she's been adding Teladoc to that ETF over the year to get it up to being the top holding.

This article represents the opinion of the writer, who may disagree with the official recommendation position of a Motley Fool premium advisory service. Were motley! Questioning an investing thesis -- even one of our own -- helps us all think critically about investing and make decisions that help us become smarter, happier, and richer.

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Is Cathie Wood's Genomic ETF a Buy After Sinking This Year? - Motley Fool

Vingroup Big Data Institute (VinBigData) announced that it had completed the project on the Database of Genomic Variants for the Vietnamese Population.

With more than 1,000 genomes sequenced and over 40 million variants discovered, the research will lay the foundation for biomedical and precision medicine development, contributing to giving early treatment to each Vietnamese individual in the future.

The database, the first of its kind, also has enough annotations about biological functions and pathological risks.

Prof Ta Thanh Van, chairman of the Council of Hanoi Medical University, said the database would provide an invaluable reference to improve the efficiency of diagnosis and treatment in the country.

Launched in December 2018, the project drew the participation of over 40 scientists from leading universities and units worldwide as well as hundreds of experts and volunteers at home and abroad.

During the three years, they sequenced the genomes of over 1,000 unrelated adults aged 35 to 55 and discovered more than 40 million genetic variants.

Nearly two million of them were representative of the Vietnamese population.

The process was carried out at a lab meeting ISO 15189 standards at Vinmec International General Hospital, using advanced technologies by Google, Illumina and NVIDIA.

Part of the database is now available at genome.vinbigdata.org.

Several hi-speed analysis tools are also offered on trial at the site.

The pioneering project cost over US$4.5mil (RM18.9mil), the largest scale in Vietnam for such a project so far. Vietnam News/ANN

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Database of genomic variants for population completed in Vietnam - The Star Online