Daily Archives: November 22, 2020

Discovery of shape of the SARS-CoV-2 genome after infection could inform new COVID-19 treatments.

Scientists at the University of Cambridge, in collaboration with Justus-Liebig University, Germany, have uncovered how the genome of SARS-CoV-2 the coronavirus that causes COVID-19 uses genome origami to infect and replicate successfully inside host cells. This could inform the development of effective drugs that target specific parts of the virus genome, in the fight against COVID-19.

SARS-CoV-2 is one of many coronaviruses. All share the characteristic of having the largest single-stranded RNA genome in nature. This genome contains all the genetic code the virus needs to produce proteins, evade the immune system, and replicate inside the human body. Much of that information is contained in the 3D structure adopted by this RNA genome when it infects cells.

The researchers say most current work to find drugs and vaccines for COVID-19 is focused on targeting the proteins of the virus. Because the shape of the RNA molecule is critical to its function, targeting the RNA directly with drugs to disrupt its structure would block the lifecycle and stop the virus replicating.

In a study published recently in the journal Molecular Cell, the team uncovered the entire structure of the SARS-CoV-2 genome inside the host cell, revealing a network of RNA-RNA interactions spanning very long sections of the genome. Different functional parts along the genome need to work together despite the great distance between them, and the new structural data shows how this is accomplished to enable the coronavirus life cycle and cause disease.

The RNA genome of coronaviruses is about three times bigger than an average viral RNA genome its huge, said lead author Dr. Omer Ziv at the University of Cambridges Wellcome Trust/Cancer Research UK Gurdon Institute.

He added: Researchers previously proposed that long-distance interactions along coronavirus genomes are critical for their replication and for producing the viral proteins, but until recently we didnt have the right tools to map these interactions in full. Now that we understand this network of connectivity, we can start designing ways to target it effectively with therapeutics.

In all cells the genome holds the code for the production of specific proteins, which are made when a molecular machine called a ribosome runs along the RNA reading the code until a stop sign tells it to terminate. In coronaviruses, there is a special spot where the ribosome only stops 50% of the times in front of the stop sign. In the other 50% of cases, a unique RNA shape makes the ribosome jump over the stop sign and produce additional viral proteins. By mapping this RNA structure and the long-range interactions involved, the new research uncovers the strategies by which coronaviruses produce their proteins to manipulate our cells.

We show that interactions occur between sections of the SARS-CoV-2 RNA that are very long distances apart, and we can monitor these interactions as they occur during early SARS-CoV-2 replication, said Dr. Lyudmila Shalamova, a co-lead investigator at Justus-Liebig University, Germany.

Dr. Jon Price, a postdoctoral associate at the Gurdon Institute and co-lead of this study, has developed a free, open-access interactive website hosting the entire RNA structure of SARS-CoV-2. This will enable researchers world-wide to use the new data in the development of drugs to target specific regions of the viruss RNA genome.

The genome of most human viruses is made of RNA rather than DNA. Ziv developed methods to investigate such long-range interactions across viral RNA genomes inside the host cells, in work to understand the Zika virus genome. This has proved a valuable methodological basis for understanding SARS-CoV-2.

Reference: The short- and long-range RNA-RNA Interactome of SARS-CoV-2 by Omer Ziv, Jonathan Price, Lyudmila Shalamova, Tsveta Kamenova, Ian Goodfellow, Friedemann Weber and Eric A. Miska, 5 November 2020, Molecular Cell.DOI: 10.1016/j.molcel.2020.11.004

This research is a collaborative study between the group of Professor Eric Miska at the University of Cambridges Gurdon Institute and Department of Genetics, and the group of Professor Friedemann Weber from the Institute for Virology, Justus-Liebig University, Gieen, Germany. The authors are grateful for the support of the Biochemistry Department at the University of Cambridge, who provided specialist laboratory facilities for performing part of this research.

The work was funded by Cancer Research UK, Wellcome, and Deutsche Forschungsgemeinschaft (DFG).

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SARS-CoV-2 Uses Genetic Origami to Infect and Replicate Inside Host Cells Discovery Could Lead to New COVID-19 Treatments - SciTechDaily

Irene Blat, a senior director at Genuity Science, discusses how the intersection of data, engineering, genetics and more will be crucial to the future of healthcare.

The future of healthcare will need the right mix of skills and cross-disciplinary collaboration. Irene Blat, senior director of data products and analytics at Genuity Science, is particularly familiar with that. Throughout her career, she has worked with clinicians, geneticists, software engineers and more to drive progress in genomics.

Here, she discusses her passion for problem solving and why mentors have been crucial to her journey.

One of the biggest surprises has been realising the value of collaborative teamwork in tackling these different spaces IRENE BLAT

I have had a passion for life sciences since my early years. I loved experimenting in science class and being able to test, learn and improve. What really solidified my path into life sciences was an undergraduate experience I had working in an immunology lab. We would modify genetic sequences to better understand how immune cells were able to adapt their responses depending on the invaders they were fighting.

The way we measured the response was by looking at thousands of cells with a laser to see how the markers they expressed on their surface had changed based on the genetic changes to their sequence. This generated a lot of data that we then had to analyse.

One of the best aspects of experimenting was recording the data and then looking for and identifying patterns. The thrill of gaining insights into one more piece of the puzzle was what really drove me to continue my career in exploring genetics to better understand and potentially treat diseases.

My interest in genetics was what led me to my first job working at the Broad Institute in Cambridge, Massachusetts. At the time, it was an early data revolution in the life sciences where the human genome had just been sequenced a few years earlier and we were learning a wealth of information about healthy and disease states.

My role was to generate thousands of gene expression profiles of cells that had been treated with different drugs and then look for patterns in the cells responses to the drugs. We were looking for ways to link these genetic patterns to diseases to match them to a potential therapeutic compound. Here, I learned that the human cell is a very complex system and requires combing through lots of data to better understand how all the subtle changes in a cell work together to produce altered states.

Working with these large datasets put me on a path to look for opportunities where I could leverage the power of data to better understand complex biological systems.

For me, my career path has not been linear. I have taken risks and explored new opportunities to expand my experience where I could be impactful. Since joining Genuity, I have been fortunate to contribute to the R&D, product management and commercial aspects of the business with, at times, steep learning curves that have taken me out of my comfort zone.

What I have learned about myself is that I enjoy the challenge of learning something new and being able to leverage previous experiences to bring an original perspective to the company needs. While the subject matter might change, the concepts and learnings are still applicable across the organisation.

One of the biggest surprises has been realising the value of collaborative teamwork in tackling these different spaces. In graduate school, my work was focused on a very specific topic and in my career Ive been hired into very specific roles. But what has enabled me to move between different fields has really been collaborating and learning from other people.

Ive learned not to be afraid to ask questions and really take the opportunity to learn from others in the field. Then I have to take time to synthesise all these learnings to put forward a hypothesis that I can share with my colleagues for feedback and input. Basically, its a team effort and the more diverse the team the better the ideas.

I have had the good fortune of having many outstanding mentors throughout my career who see potential in me through my work ethic and dedication. I am grateful for having mentors who have encouraged me to take on bigger risks by giving me their vote of confidence. In particular, I have had strong female mentors who are excellent leaders and have leaned in throughout their careers.

Being able to learn from their experiences and listening to their guidance has been valuable in helping me decide where to go next in my career. The best mentors are the ones that give the gift of their time and my career has been shaped by the time of several great mentors in my life.

I really enjoy problem solving. In this role, I spend a lot of time thinking of creative ways to solve new problems. I also enjoy working through these problems in collaboration with our talented team. I have a deep appreciation for the value of sharing ideas and approaches with others from different backgrounds.

At Genuity Science, I have worked in teams with clinicians, geneticists, software engineers, bioinformaticians and data scientists who each bring their own expertise to the table. These types of cross-functional teams enable problem solving in a way that would not be possible if we all worked in silos.

What is even more exciting is that our team grows when we engage in collaborations with our customers. Our customers bring strong experiences in drug development that nicely complement our internal expertise in genomics discovery to help advance new therapies to the clinic. There are so many people to learn from both internal and external to our organisation and thats what makes my job exciting Im always learning!

I am a passionate learner. As I look back on how I landed at Genuity Science, the common thread is that every role I have had provided me the opportunity to learn. In this role, we are working at the cutting edge of how to analyse large clinical and genomic datasets. We have to iterate and adapt our analytical tools to solve increasingly complex biological problems.

My flexibility in adapting with the needs of the problem has also helped me in looking at problems in different ways. Since my early days in the lab, I recognised I had a lot of perseverance and grit. Sometimes you have to try multiple approaches before you find a path forward, but it is incredibly rewarding when you gain a new insight into a problem that was unsolved. Thats what keeps me motivated to continue trying.

At Genuity Science, the leadership team has encouraged me to explore the commercial boundaries which are well outside my original scientific training. Being able to inform commercial engagements with my deep scientific understanding has significantly broadened my skillset and resulted in exciting partnerships for the company.

Genuity has supported me in attending trainings and conferences where I was able to learn more about the commercial space as well as gain the opportunity to observe others in action. This has been a great development opportunity for me.

If you enjoy a challenge and like to learn, then a career in data analytics will not disappoint you. You have to be willing to take risks and fail but also learn from the failures and apply the lessons to the next challenge. The greatest reward is seeing how this work can ultimately have an impact on patient lives.

More here:
The role of a data-analytics director in genomic discovery - Siliconrepublic.com

This article was originally published here

Sci Rep. 2020 Nov 20;10(1):20243. doi: 10.1038/s41598-020-76791-y.

ABSTRACT

Lung cancer is the leading causes of cancer-related death worldwide. Precise treatment based on next-generation sequencing technology has shown advantages in the diagnosis and treatment of lung cancer. This cohort study included 371 lung cancer patients. The lung cancer subtype was related to the smoking status and sex of the patients. The most common mutated genes were TP53 (62%), EGFR (55%), and KRAS (11%). The mutation frequencies of EGFR, TP53, PIK3CA, NFE2L2, KMT2D, FGFR1, CCND1, and CDKN2A were significantly different between lung adenocarcinoma and lung squamous cell carcinoma. We identified the age-associated mutations in ALK, ERBB2, KMT2D, RBM10, NRAS, NF1, PIK3CA, MET, PBRM1, LRP2, and CDKN2B; smoking-associated mutations in CDKN2A, FAT1, FGFR1, NFE2L2, CCNE1, CCND1, SMARCA4, KEAP1, KMT2C, and STK11; tumor stage-associated mutations in ARFRP1, AURKA, and CBFB; and sex-associated mutations in EGFR. Tumor mutational burden (TMB) is associated with tumor subtype, age, sex, and smoking status. TMB-associated mutations included CDKN2A, LRP1B, LRP2, TP53, and EGFR. EGFR amplification was commonly detected in patients with acquired lcotinib/gefitinib resistance. DNMT3A and NOTCH4 mutations may be associated with the benefit of icotinib/gefitinib treatment.

PMID:33219256 | DOI:10.1038/s41598-020-76791-y

Continue reading here:
Comprehensive genomic profile of Chinese lung cancer patients and mutation characteristics of individuals resistant to icotinib/gefitinib - DocWire...

Dublin, Nov. 19, 2020 (GLOBE NEWSWIRE) -- The "Genomic Cancer Panel and Profiling Markets by Cancer and Germline/Somatic Type with Screening Potential Market Size, Customized Forecasting/Analysis, and Executive and Consultant Guides 2021-2025" report has been added to ResearchAndMarkets.com's offering.

This report provides data that analysts and planners can use. Hundreds of pages of information including a complete list of Current 2020 United States Medicare Fee Payment Schedules to help understand test pricing in detail.

Forecast demand for new testing regimes or technologies. Make research investment decisions. Existing laboratories and hospitals can use the information directly to forecast and plan for clinical facilities growth.

Cancer Gene Panels and Genomic Profiling are quickly changing the diagnosis and treatment of cancers. The market is moving out of a specialized niche and going mainstream as Oncologists begin routinely using information on the hundreds of genes related to cancer. The market is exploding as physicians use all the information they can get in the battle against cancer. And there is a lot of information to be had. But the COVID-19 Pandemic has impacted the market.

Comprehensive panels, genomic profiling, high-risk breast cancer panels. Learn all about how players are jockeying for position in a market that is being created from scratch. And some players are already taking the lead. It is a dynamic market situation with enormous opportunity where the right diagnostic with the right support can command premium pricing. And the science is developing at the same time creating new opportunities with regularity. And the cost of sequencing continues to fall.

The report includes detailed breakouts for 18 Countries and 4 Regions.

Key Topics Covered:

Cancer Panel Market - Strategic Situation Analysis & COVID Update

1. Introduction and Market Definition 1.1 What are Cancer Gene Panels and Profiling? 1.2 The Sequencing Revolution 1.3 Market Definition 1.4 Methodology 1.5 A Spending Perspective on Clinical Laboratory Testing 1.5.1 An Historical Look at Clinical Testing

2. Market Overview 2.1 Players in a Dynamic Market 2.1.1 Academic Research Lab 2.1.2 Diagnostic Test Developer2.1.3 Instrumentation Supplier 2.1.4 Distributor and Reagent Supplier 2.1.5 Independent Testing Lab2.1.6 Public National/regional lab 2.1.7 Hospital lab 2.1.8 Physician Office Labs 2.1.9 Audit Body 2.1.10 Certification Body2.2 Oncogenomics2.2.1 Carcinogenesis2.2.2 Chromosomes, Genes and Epigenetics 2.2.2.1 Chromosomes 2.2.2.2 Genes 2.2.2.3 Epigenetics 2.2.3 Cancer Genes 2.2.4 Germline vs Somatic 2.2.5 Gene Panels, Single Gene Assays and Multiplexing 2.2.6 Genomic Profiling 2.2.7 The Comprehensive Assay 2.2.8 Changing Clinical Role 2.2.9 The Cancer Screening Market Opportunity2.3 Cancer Management vs. Diagnosis 2.3.1 The Role of Risk Assessment 2.3.2 Diagnosis 2.3.3 Managing 2.3.4 Monitoring 2.4 Phases of Adoption - Looking into The Future 2.5 Structure of Industry Plays a Part 2.5.1 Hospital Testing Share 2.5.2 Economies of Scale2.5.2.1 Hospital vs. Central Lab 2.5.3 Physician Office Lab's 2.5.4 Physician's and POCT

3. Market Trends3.1 Factors Driving Growth3.1.1 Level of Care 3.1.2 Companion Dx 3.1.3 Immuno-oncology 3.1.4 Liability3.1.5 Aging Population3.2 Factors Limiting Growth3.2.1 State of knowledge3.2.2 Genetic Blizzard. 3.2.3 Protocol Resistance3.2.4 Regulation and coverage 3.3 Instrumentation and Automation 3.3.1 Instruments Key to Market Share 3.3.2 Bioinformatics Plays a Role 3.4 Diagnostic Technology Development3.4.1 Next Generation Sequencing Fuels a Revolution 3.4.2 Single Cell Genomics Changes the Picture 3.4.3 Pharmacogenomics Blurs Diagnosis and Treatment3.4.4 CGES Testing, A Brave New World 3.4.5 Biochips/Giant magnetoresistance based assay

4. Cancer Panels & Profiles Recent Developments 4.1 Recent Developments - Importance and How to Use This Section 4.1.1 Importance of These Developments 4.1.2 How to Use This Section

5. Profiles of Key Players

6. The Global Market for Cancer Gene Panels and Profiles

7. Global Cancer Gene Panels & Profiles Markets - By Type of Cancer 7.1 Comprehensive Panels & Profiles 7.2 Breast Cancer Gene Testing 7.3 Colorectal Cancer Gene Testing7.4 Gynecological Cancer Gene Testing 7.5 Blood Cancer Gene Testing 7.6 Prostate Cancer Gene Testing 7.7 Lung Cancer Gene Testing7.8 Other Cancer Gene Testing

8. Global Cancer Gene Testing Markets - Germline and Somatic 8.1 Global Market Somatic 7.3 Global Market Germline

9. Potential Market Opportunity Sizes 9.1 Potential Cancer Screening by Country: Lung, Breast & Colorectal 9.2 Potential Cancer Screening by Country: Prostate, Other Cancer & All Cancer 9.3 Potential Market Size - Cancer Diagnosis 9.4 Potential Market Size - Therapy Selection

Appendices

For more information about this report visit https://www.researchandmarkets.com/r/5bx3ai

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

See the rest here:
Global Genomic Cancer Panel and Profiling Markets Report 2021-2025: The Market is Moving Out of a Specialized Niche and Going Mainstream -...

Hidden in plain sight, a group of scientists in Porirua some wearing lab coats, some more at home in jeans carry out some of the most important work in the fight against Covid-19.

Genomic sequencing is at the heart of contact tracing, although most New Zealanders hadnt heard those words until after the first wave.

ESR Bioinformatics lead Dr Joep de Ligt and his team, Dr Una Ren and Matt Storey, work around the clock to map the chain of transmission for every single case of Covid-19 in New Zealand.

Their building is straight out of the 1980s, a warren of corridors and stairwells. There are drawings by de Ligts kids on the bookshelf, a small 3D model of a coronavirus molecule on the next shelf.

READ MORE:* Covid-19: Covid Tracer app is a form of protection, expert says* Covid-19: How Auckland's 'mystery' coronavirus case was genome sequenced* Covid-19: Non-stop late nights, public pressure for genome sequencing team tracing coronavirus cases

ROSA WOODS/Stuff

ESR bioinformatics lead Dr Joep de Ligt demonstrates the software which maps the chains of transmission of local cases, just like a complex family tree.

These scientists knew from the beginning this work would be important. During the first lockdown they tested samples, mapped chains of transmission, and added to their database, funding it all themselves.

Then they laid all their data on the table at the Ministry of Health, and explained how they could help.

The ministry now relies on this work, and funds it jointly with the Ministry of Business, Innovation and Employments Covid-19 Innovation Acceleration Fund.

At the moment, ESR in Wellington is the main player in this field. Samples can be sequenced elsewhere, but the results are usually sent to Wellington for analysis and mapping.

ROSA WOODS/Stuff

The robot responsible for pipetting and mixing solutions with the inert virus capable of doing 84 at a time at the ESR lab in Porirua.

Equipment is easy to obtain, but the people with expertise are invaluable, and scarce.

New Zealand can say weve sequenced nearly every case, de Ligt said. That meant a near-conclusive map of cases, with every chain of transmission shown as a line on a diagram, like a family tree.

Other countries around the world were doing this too. Australia and some smaller Pacific islands were also able to track every case and map them.

But for countries overwhelmed with thousands of cases a day, it wasnt a priority. The United Kingdom was sequencing about 30 per cent of its cases, de Ligt said impressive considering its volume of daily cases could reach more than 20,000.

New Zealand was in a sweet spot; a manageable amount of cases, with real value to be gained by knowing where they came from.

Dom Thomas/Getty Images

Joep de Ligt talks to Prime Minister Jacinda Ardern about the different Covid-19 genomes in New Zealand, during an ESR tour in August. (File photo)

The first sequence was produced on March 9. Since then, ESR had done the bulk of the work 1289 of a total 1296 sequences with one other by Otago University, and sic by Massey University.

The case of the Auckland AUT student who tested positive on November 12 was the fastest turnaround so far in New Zealand and, according to de Ligt, likely the fastest in the world.

Overseas, a sample could take anywhere from 24 to 48 hours to sequence. In New Zealand, with the pedal to the floor, it took around 10 hours.

Since samples often travelled from around the country to the lab in Wellington, ESR is planning to equip and train the teams in its Christchurch and Auckland centres to perform the same service, to shorten delivery times even further.

This would also provide alternatives if something happened to the Wellington base, be it disastrous like an earthquake or fire, or simple as a power outage.

ROSA WOODS/Stuff

A Covid-19 molecule, shown here as an enlarged 3D replica, has spikes on the outside which attach themselves to a human cell, and transfer their contents RNA.

When a coronavirus sample lands in the hands of ESR scientists, taken by swabbing the nose and throat of a person with symptoms, it has already tested positive for Covid-19.

The person it came from should already be in self-isolation, and perhaps there is already some indication of whom they caught it from.

Or perhaps everyone is scratching their heads, workplaces thrust into lockdown, and staff at the Ministry of Health are calling hushed, hurried meetings.

RNA, like DNA, is a long ladder of chemical compounds; adenine (A), uracil (U), guanine (G) and cytosine (C). They pair up to form a double helix structure, A always joining with U, and C with G.

These letters change due to mutation. Because of the way Covid-19 RNA mutates, scientists know they can expect a change in the code once every two weeks.

The closer one persons virus resembles another known case, the more likely it is they caught it from that person.

Last week, the AUT students sample was identical to another known case.

ROSA WOODS/Stuff

De Ligt and his team spend most of their time in the office rather than the lab, comparing one sequence to the next.

A positive sample begins its quest for an answer by being turned from a live form of the virus, into one which cannot infect people.

According to ESR chief scientist Dr Brett Cowan, we explode it, and then we cook it. Simple, when you put it like that.

Cowan spends a lot of his time explaining things in layman's terms. While it can be interesting to the public, more importantly, it helps if those co-ordinating health responses and contact tracing understand the process.

The membrane around the outside of the virus is burst open, spilling the genetic data. The spikes on the membranes surface are the parts that latch onto human cells, and allow the RNA, the code of the virus, to transfer and infect. Without the membrane, the RNA cant enter a cell.

The sample is then heated to a temperature that will damage everything but the RNA a second line of defence.

ROSA WOODS/Stuff

ESR chief scientist Dr Brett Cowan, holding a 3D printed replica of the virus Covid-19, is well-versed in explaining the science of viruses to the public.

Once the sample is no longer infectious, the RNA is isolated from the other junk collected in a sample pollen, dust, or bacteria in the nose of the test subject.

The only part of the sample they were interested in, said de Ligt, was the RNA. We dont want to learn about the person.

In any sample, there isnt enough RNA present to produce a result at this stage. The RNA needs to be replicated millions, if not billions of times.

Then a robot transfers the virus into a cocktail of chemicals. This machine, which costs around $30,000, can transfer up to 84 samples at a time thats a sample of inert Covid-19 RNA from 84 different people.

For a country like New Zealand, which rarely had more than a handful of positive cases a day, the robot was not intended to speed up the process.

Rather, it meant everything was done systematically, with no risk of mixed-up samples. Some samples are still pipetted by hand such as the single case of the AUT student.

The next stage is to run it through a machine called a GridION, which costs around $100,000, and can sequence the RNA into the string of As, Us, Cs, and Gs.

The machine spits out the code, and the scientists move in to analyse the results.

ROSA WOODS

Coding is a big part of the process. Here, de Ligt enters the data from the machine into the mapping program, to see the bigger picture of community transmission.

By comparing one sequence with every other on file, they can pinpoint the person it most closely resembles, and then the epidemiologists and contact tracing teams take over.

We take data, and turn it into actionable intelligence, Cowan said. We have the end of the chain, and sequencing gives us the beginning.

Link:
Covid-19: Behind the scenes of genomic sequencing in Wellington's own backyard - Stuff.co.nz