Category Archives: Transhuman News

Monkeypox is suddenly on everyones radar, having gone from a handful of cases outside of the area where it is endemic to over 1,600 cases in mere weeks. Given the horrors that COVID brought, it is hardly surprising that people are wondering if this is another pandemic in the making.

Monkeypox, despite its name, is more commonly found in rodents and squirrels in west and central Africa. Why, people have asked, is it spreading in areas where there is no natural animal reservoir? Has the virus mutated to become more efficient at spreading from human to human?

Of course, we are all too familiar with variants that SARS-CoV-2 (the virus that causes COVID) has spawned: alpha, beta, gamma, delta, omicron not to mention the sub-variants. So whats to stop a virus that was once more at home in the tropics from adapting to new environments or becoming better at spreading?

A key difference between monkeypox and coronavirus is that the former is a DNA virus and the latter an RNA virus. In short, RNA viruses make more mistakes in their genetic code when replicating than DNA viruses. More mistakes mean more mutations, and hence more chance to come up with a new design that is better (more fit in a Darwinian sense) than the older version that spawned it. (Of course, many new variants are less adapted to their environment and so fizzle out without us even knowing they existed.)

DNA viruses such as monkeypox are more stable. They are able to proof read their genomes, so mistakes (read: variants) are more often spotted. This doesnt mean DNA viruses cant change at all, but that the likelihood of any changes is less than with RNA viruses.

Poxviruses that can infect humans include smallpox (now extinct in the wild thanks to vaccines), cowpox, molluscum contagiosum and monkeypox, but not chickenpox, which is neither a pox virus nor found in chickens. They are a remarkably stable group of viruses that cause characteristic pustules pox being from the Old English pocc meaning pustule, blister or ulcer.

With any virus, particularly those that only infect a few people each year, it is difficult to know the full extent of symptoms. With the increase of cases, we are starting to see what we would term atypical presentations of the virus. This means that people are not displaying the typical pustules covering the entire body. Instead, we are seeing small sores in the areas of contact with infected people.

This atypical presentation is probably not due to significant changes in the virus, as a genetic sequence of the virus from a patient in Portugal did not find significant changes in the virus compared with previous outbreaks in 2018 and 2019. Instead, the atypical presentation is probably because we are seeing many more infections and therefore a wider range of symptoms.

One other possible reason for the change is that the strain (called a clade) of monkeypox (west African) currently circulating in non-endemic countries tends to produce milder infections than the central African strain.

Given what we know about other pox viruses and the stability of DNA viruses, it is likely that the monkeypox virus will be slow to change. This is not the only reason for cautious optimism. We also have a vaccine that is about 85% effective against monkeypox. Regardless of how many people are infected, the vaccine will still be effective, due to the low rate of mutation compared with RNA viruses. In other words, variants that can escape the vaccine are unlikely to emerge.

This vaccine, together with public health measures such as contact tracing, will hopefully be enough to contain this outbreak.

More here:
Monkeypox is a DNA virus unlike coronavirus here's what that means for the virus and us - The Conversation

The closure of the Texas location comes as the company begins a strategic transformation to focus on their business operations and expand their oncology portfolio and testing services in California.

IRVINE, Calif., June 15, 2022 /PRNewswire/ -- Artemis DNA, Inc.("Artemis DNA" or the "company"),a leading global diagnostic laboratory company, announced today that they have made the difficult decision to close their Houston, Texas facility.

"This was certainly one of the most difficult decision I have had to make with Artemis DNA," commented Ms. Emylee Thai, Founder of Artemis DNA. "As our first location, the Houston facility has played an incredibly important role in the Artemis DNA story, and I will be forever grateful to every team members and their invaluable contributions to the company while wishing the team the best in all their endeavors."

The facility, which is located at 900 S Loop, Ste 170, Houston, Texas will be closed effective June 13, 2022. "Theoptimization of the company's infrastructure and logistics are an essential part of their becoming a more sustainably profitable business and tobetter meet the needs of the customers," commented Ms. Emylee Thai, Founder of Artemis DNA.

Artemis DNA has been growing at a rapid pace since it inception in 2019, and despite the announcement of the Houston facility closure, the firm continues to grow strategically, including a recent international expansion into the Vietnammarket and expanding the firm'sin-depth oncology portfolio:

Vietnam was also chosen to be the first country for Artemis DNA's global expansion because of the Founder's tribute to her Vietnamese father and mother, who both passed away from cancer.

About Artemis DNA

Artemis DNAis a full service, Clinical Laboratory Improvement Amendments (CLIA) certified, College of American Pathologists (CAP) accredited, high-complexity clinical diagnostic laboratory company that provides proprietaryNext Generation Sequencing (NGS)genetic testing and diagnostic laboratory services for a wide variety of medical specialties, including cardiology, oncology, immunology, neurology, reproductive health and pharmacogenomics.

Artemis DNA's testing enhances the delivery of "personalized medicine" by assessing a patient's own genetic makeup and clinical characteristics which allows for informed decision making in prevention and treatment choices. Artemis DNA also provides pre- and post-testing genetic education and counseling services, as well as conducting research and development to discover and develop additional novel diagnostic services. Artemis DNA is headquartered in Irvine, California. For more information, visithttps://www.artemisdna.com.

PRESS CONTACT

Public Relations(888) 883-6288, Extension 8http://www.artemisdna.com

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Artemis DNA to Wind-Down Texas Operations and Shift Focus to Expand Oncology Portfolio in California - PR Newswire

Griswold MG, Fullman N, Hawley C, Arian N, Zimsen SRM, Tymeson HD, et al. Alcohol use and burden for 195 countries and territories, 19902016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2018;392:101535.

Article Google Scholar

Udo T, Vasquez E, Shaw BA. A lifetime history of alcohol use disorder increases risk for chronic medical conditions after stable remission. Drug Alcohol Depend. 2015;157:6874.

PubMed Article Google Scholar

Westman J, Wahlbeck K, Laursen TM, Gissler M, Nordentoft M, Hallgren J, et al. Mortality and life expectancy of people with alcohol use disorder in Denmark, Finland and Sweden. Acta Psychiatr Scand. 2015;131:297306.

CAS PubMed Article Google Scholar

Koh SH, Choi SH, Jeong JH, Jang JW, Park KW, Kim EJ, et al. Telomere shortening reflecting physical aging is associated with cognitive decline and dementia conversion in mild cognitive impairment due to Alzheimers disease. Aging-Us. 2020;12:440723.

CAS Article Google Scholar

Lindqvist D, Epel ES, Mellon SH, Penninx BW, Revesz D, Verhoeven JE, et al. Psychiatric disorders and leukocyte telomere length: Underlying mechanisms linking mental illness with cellular aging. Neurosci Biobehav R. 2015;55:33364.

CAS Article Google Scholar

Ma HX, Zhou ZY, Wei S, Liu ZS, Pooley KA, Dunning AM, et al. Shortened Telomere Length Is Associated with Increased Risk of Cancer: A Meta-Analysis. Plos One. 2011;6:e20466.

CAS PubMed PubMed Central Article Google Scholar

Nilsson PM, Tufvesson H, Leosdottir M, Melander O. Telomeres and cardiovascular disease risk: an update 2013. Transl Res. 2013;162:37180.

CAS PubMed Article Google Scholar

Rosoff DB, Charlet K, Jung J, Lee J, Muench C, Luo A, et al. Association of High-Intensity Binge Drinking With Lipid and Liver Function Enzyme Levels. JAMA Netw Open. 2019;2:e195844.

PubMed PubMed Central Article Google Scholar

Rosoff DB, Smith GD, Mehta N, Clarke TK, Lohoff FW. Evaluating the relationship between alcohol consumption, tobacco use, and cardiovascular disease: A multivariable Mendelian randomization study. Plos Med. 2020;17:e1003410.

PubMed PubMed Central Article Google Scholar

Wang JQ, Liu YR, Xia QR, Xia Q, Wang BS, Yang CC, et al. Potential roles of telomeres and telomerase in neurodegenerative diseases. Int J Biol Macromol. 2020;163:106078.

CAS PubMed Article Google Scholar

Luo A, Jung J, Longley M, Rosoff DB, Charlet K, Muench C, et al. Epigenetic aging is accelerated in alcohol use disorder and regulated by genetic variation in APOL2. Neuropsychopharmacology. 2020;45:32736.

CAS PubMed Article Google Scholar

Rosen AD, Robertson KD, Hlady RA, Muench C, Lee J, Philibert R, et al. DNA methylation age is accelerated in alcohol dependence. Transl Psychiatry. 2018;8:182.

PubMed PubMed Central Article CAS Google Scholar

Lohoff FW. Pharmacotherapies and personalized medicine for alcohol use disorder: a review. Pharmacogenomics. 2020;21:111738.

CAS PubMed PubMed Central Article Google Scholar

Wang JF, Dong X, Cao L, Sun YY, Qiu Y, Zhang Y, et al. Association between telomere length and diabetes mellitus: A meta-analysis. J Int Med Res. 2016;44:115673.

PubMed PubMed Central Article Google Scholar

Xu C, Wang ZQ, Su XQ, Da M, Yang ZC, Duan WW, et al. Association between leucocyte telomere length and cardiovascular disease in a large general population in the United States. Sci Rep. 2020;10:80.

CAS PubMed PubMed Central Article Google Scholar

Zhao JZ, Miao K, Wang HR, Ding H, Wang DW. Association between Telomere Length and Type 2 Diabetes Mellitus: A Meta-Analysis. Plos One. 2013;8:e79993.

PubMed PubMed Central Article Google Scholar

Shammas MA. Telomeres, lifestyle, cancer, and aging. Curr Opin Clin Nutr Metab Care. 2011;14:2834.

CAS PubMed PubMed Central Article Google Scholar

Chen BH, Carty CL, Kimura M, Kark JD, Chen W, Li SX, et al. Leukocyte telomere length, T cell composition and DNA methylation age. Aging-Us. 2017;9:198395.

CAS Article Google Scholar

Armanios M. Telomeres and age-related disease: how telomere biology informs clinical paradigms. J Clin Investig. 2013;123:9961002.

CAS PubMed PubMed Central Article Google Scholar

Broer L, Codd V, Nyholt DR, Deelen J, Mangino M, Willemsen G, et al. Meta-analysis of telomere length in 19 713 subjects reveals high heritability, stronger maternal inheritance and a paternal age effect. Eur J Hum Genet. 2013;21:11638.

CAS PubMed PubMed Central Article Google Scholar

Hjelmborg JB, Dalgard C, Moller S, Steenstrup T, Kimura M, Christensen K, et al. The heritability of leucocyte telomere length dynamics. J Med Genet. 2015;52:297302.

CAS PubMed Article Google Scholar

Honig LS, Kang MS, Cheng R, Eckfeldt JH, Thyagarajan B, Leiendecker-Foster C, et al. Heritability of telomere length in a study of long-lived families. Neurobiol Aging. 2015;36:278590.

CAS PubMed PubMed Central Article Google Scholar

de Carvalho LM, Wiers CE, Manza P, Sun H, Schwandt M, Wang GJ, et al. Effect of alcohol use disorder on cellular aging. Psychopharmacology. 2019;236:324555.

Article CAS Google Scholar

Dixit S, Whooley MA, Vittinghoff E, Roberts JD, Heckbert SR, Fitzpatrick AL, et al. Alcohol consumption and leukocyte telomere length. Sci Rep. 2019;9:1404.

PubMed PubMed Central Article CAS Google Scholar

Navarro-Mateu F, Husky M, Cayuela-Fuentes P, Alvarez FJ, Roca-Vega A, Rubio-Aparicio M, et al. The association of telomere length with substance use disorders: a systematic review and meta-analysis of observational studies. Addiction. 2021;116:195472.

PubMed Article Google Scholar

Strandberg TE, Strandberg AY, Saijonmaa O, Tilvis RS, Pitkala KH, Fyhrquist F. Association between alcohol consumption in healthy midlife and telomere length in older men. The Helsinki Businessmen Study. Eur J Epidemiol. 2012;27:81522.

PubMed Article Google Scholar

Montpetit AJ, Alhareeri AA, Montpetit M, Starkweather AR, Elmore LW, Filler K, et al. Telomere Length A Review of Methods for Measurement. Nurs Res. 2014;63:28999.

PubMed PubMed Central Article Google Scholar

Lu AT, Seeboth A, Tsai PC, Sun D, Quach A, Reiner AP, et al. DNA methylation-based estimator of telomere length. Aging (Albany NY). 2019;11:5895923.

CAS Article Google Scholar

Lohoff FW, Roy A, Jung J, Longley M, Rosoff DB, Luo A, et al. Epigenome-wide association study and multi-tissue replication of individuals with alcohol use disorder: evidence for abnormal glucocorticoid signaling pathway gene regulation. Mol Psychiatr. 2021;26:222437.

CAS Article Google Scholar

Lohoff FW, Sorcher JL, Rosen AD, Mauro KL, Fanelli RR, Momenan R, et al. Methylomic profiling and replication implicates deregulation of PCSK9 in alcohol use disorder. Mol Psychiatry. 2018;23:111.

Article CAS Google Scholar

Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019;11:30327.

CAS Article Google Scholar

Lu AT, Xue L, Salfati EL, Chen BH, Ferrucci L, Levy D, et al. GWAS of epigenetic aging rates in blood reveals a critical role for TERT. Nat Commun. 2018;9:387.

PubMed PubMed Central Article CAS Google Scholar

Sobell LC, Sobell MB Timeline Follow-Back. In: Litten RZ, Allen JP, editors. Measuring Alcohol Consumption: Psychosocial and Biochemical Methods. Totowa, NJ: Humana Press; 1992, pp 4172.

Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991;86:111927.

CAS PubMed Article Google Scholar

Houseman EA, Kile ML, Christiani DC, Ince TA, Kelsey KT, Marsit CJ. Reference-free deconvolution of DNA methylation data and mediation by cell composition effects. BMC Bioinforma. 2016;17:259.

Article CAS Google Scholar

Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:R115.

PubMed PubMed Central Article Google Scholar

Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10:57391.

Article Google Scholar

Horvath S, Oshima J, Martin GM, Lu AT, Quach A, Cohen H, et al. Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies. Aging (Albany NY). 2018;10:175875.

CAS Article Google Scholar

Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013;49:35967.

CAS PubMed Article Google Scholar

Tippmann S. Programming Tools: Adventures with R. Nature. 2015;517:10910.

CAS PubMed Article Google Scholar

Das S, Forer L, Schonherr S, Sidore C, Locke AE, Kwong A, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:12847.

CAS PubMed PubMed Central Article Google Scholar

Genomes Project C, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al. A global reference for human genetic variation. Nature. 2015;526:6874.

Article CAS Google Scholar

Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:9049.

CAS PubMed Article Google Scholar

Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet. 2008;40:1619.

CAS PubMed PubMed Central Article Google Scholar

Uhlen M, Oksvold P, Fagerberg L, Lundberg E, Jonasson K, Forsberg M, et al. Towards a knowledge-based Human Protein Atlas. Nat Biotechnol. 2010;28:124850.

CAS PubMed Article Google Scholar

Trabzuni D, Ryten M, Walker R, Smith C, Imran S, Ramasamy A, et al. Quality control parameters on a large dataset of regionally dissected human control brains for whole genome expression studies (vol 119, pg 275, 2011). J Neurochemistry. 2012;120:473473.

CAS Article Google Scholar

Fischl B. FreeSurfer. Neuroimage. 2012;62:77481.

PubMed Article Google Scholar

Destrieux C, Fischl B, Dale A, Halgren E. Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage. 2010;53:115.

PubMed Article Google Scholar

Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. Ieee T Med Imaging. 1998;17:8797.

CAS Article Google Scholar

Segonne F, Dale AM, Busa E, Glessner M, Salat D, Hahn HK, et al. A hybrid approach to the skull stripping problem in MRI. Neuroimage. 2004;22:106075.

CAS PubMed Article Google Scholar

Navrady LB, Wolters MK, MacIntyre DJ, Clarke TK, Campbell AI, Murray AD, et al. Cohort Profile: Stratifying Resilience and Depression Longitudinally (STRADL): a questionnaire follow-up of Generation Scotland: Scottish Family Health Study (GS:SFHS). Int J Epidemiol. 2018;47:1314g.

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Alcohol use disorder is associated with DNA methylation-based shortening of telomere length and regulated by TESPA1: implications for aging |...

A St. Paul man has been charged after DNA from a left-behind item linked him to a gas station robbery.

Christian Allan Gorr, 22, is charged via warrant with first-degree aggravated robbery. He was not yet in custody as of Tuesday morning.

A criminal complaint states law enforcement was called to investigate a robbery at a gas station in St. Paul at around 5:30 p.m. on Nov. 21, 2021. The suspect was wearing black clothing and an Aeropostale sweatshirt while carrying a revolver and a black bag.

About an hour later, authorities learned a Super USA gas station in Inver Grove Heights was robbed at gunpoint by a person with the same description.

The complaint states the suspect left behind a bag at the St. Paul robbery, and the bag contained a white surgical mask and a pair of gloves. When the items were sent to the Minnesota Bureau of Criminal Apprehension for DNA testing, the results matched the profile of Gorr and his brother, who was in Nashville at the time.

According to the complaint, Gorr is a suspect in several other robberies in the east metro that are similar in nature. However, he currently faces just one count of aggravated robbery.

With a conviction, first-degree aggravated robbery carries a maximum penalty of 20 years in prison and a $35,000 fine.

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Man linked to Inver Grove Heights robbery by DNA; suspect in others - KSTP

Astronomers have unveiled the most detailed survey of the Milky Way, revealing thousands of starquakes and stellar DNA, and helping to identify the most habitable corners of our home galaxy.

The observations from the European Space Agencys Gaia probe cover almost two billion stars about 1% of the total number in the galaxy and are allowing astronomers to reconstruct our home galaxys structure and find out how it has evolved over billions of years.

Previous surveys by Gaia, a robotic spacecraft launched in 2013, have pinpointed the motion of the stars in our home galaxy in exquisite detail. By rewinding these movements astronomers can model how our galaxy has morphed over time. The latest observations add details of chemical compositions, stellar temperatures, colours, masses and ages based on spectroscopy, where starlight is split into different wavelengths.

These measurements unexpectedly revealed thousands of starquakes, cataclysmic tsunami-like events on the surface of stars. Starquakes teach us a lot about stars notably, their internal workings, said Conny Aerts of KU Leuven in Belgium, who is a member of the Gaia collaboration. Gaia is opening a goldmine for asteroseismology of massive stars.

Dr George Seabroke, senior research associate at Mullard space science laboratory at University College London, said: If you can see these stars changing in brightness halfway across the Milky Way, if you were anywhere near them, it would be like the sun changing shape in front of your eyes.

Gaia is fitted with a 1bn pixel camera the largest ever in space complete with more than 100 electronic detectors. The latest dataset represents the largest chemical map of the galaxy to date, cataloguing the composition of six million stars, ten times the number measured in previous ground-based catalogues.

What stars are made of can tell us about their birthplace and their journey afterwards, and help unravel the history of the Milky Way. The first primordial stars, formed shortly after the Big Bang, only had light elements hydrogen and helium available. These produced the first supernovae that enriched galaxies with metals and elements such as carbon and oxygen, and with successive generations of stars more heavy elements became available. A stars chemical composition is a bit like its DNA, giving us crucial information about its origin.

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Gaia revealed that some stars in our galaxy are made of primordial material, while others like our Sun are made of matter enriched by previous generations of stars. Stars that are closer to the centre and plane of our galaxy are richer in metals than stars at larger distances. Gaia also identified stars that originally came from different galaxies than our own, based on their chemical composition.

Our galaxy is a beautiful melting pot of stars, said Alejandra Recio-Blanco of the Observatoire de la Cte dAzur in France, who is a member of the Gaia collaboration. This diversity is extremely important, because it tells us the story of our galaxys formation.

Seabroke said that tracing the metallicity gradient through the galaxy can help pin down habitable regions of the Milky Way. If the Sun was born in a region with much higher metallicity, there would be many more supernovae going off, presenting a risk to life on Earth, he said.

The headline of this article was amended on 13 June 2022. The original version referred to stella DNA. The correct spelling is stellar.

Read more here:
Gaia probe reveals stellar DNA and unexpected starquakes - The Guardian

In an interview at the American Society of Clinical Oncology (ASCO) 2022 Annual Meeting, Bruce Feinberg, DO, vice president and chief medical officer at Cardinal Health Specialty Solutions, discussed the use of circulating tumor DNA (ctDNA) and how it can be used in colorectal cancer. Although it has clear benefits when monitoring and managing cancer, Feinberg said more widespread use of this testing method will take time.

Your research found that nearly half of respondents did not use ctDNA to make treatment decisions in colorectal cancer. Why is this?

Bruce Feinberg, DO: So, this is going to be something that would likely be trending over time. And this is not unusual for our research. There's just a certain learning curve, and a certain amount of time that it takes for new science to get fully adopted, and often in that first wave of data there's a little bit of hesitancy. Is there enough data? Do I need to see a confirmatory study? Was the study performed large enough? Do I want to see it in a different tumor type? And so, there will be physicians who will be early adopters and understand the science and want to start using it. And there will be physicians who will be a little bit on the fence, and also physicians who will say, This is not ready for primetime. It's fascinating, you know, but come back to me in 10 years, and we'll see. And we saw some of that.

I would say that we saw the 50% maybe in a more favorable light. So, we saw the glass half full, not half empty, given the fact it really is a single tumor type. That's one, although the research is much broader, but one that's come into the mainstream with a large well-defined trial, in which multiple experts in the field have weighed in. We thought that that speaks favorably to the recognition that this is something which could move forward and move forward quickly. I still think it could be 5 to 10 years for it really to replace more traditional ways of assessing treatment response. I think we're going to see it sooner in blood malignancies, multiple myeloma in particular. But even now that we're using it, in areas like blood-based cancers, like multiple myeloma, there still is hesitancy to base the full decision making on the result and we're still doing the traditional processes in addition to that test, but they're always at a point of transition. And I think we're well on our way now. Because the science is there, the science has been validated, it's just going to take a little bit of time to kind of move that needle, where we'll have the full adoption.

Is ctDNA used in other diseases, and how widespread is this use?

Bruce Feinberg, DO: So, in the hematologic malignancies I would say it is already primetime. It's used, but we haven't gotten to the next step, which is at what point is its effectiveness in being able to measure the amount of cancer? So let's just say that we determined that we had 2 consecutive readings, in which there is no measurable cancer and, again, at this level, you know, we're down to far below anything that could be seen on an X-ray. At what point do we say, okay, based on that we're no longer going to treat, as opposed to, Oh, that's great. And we're going to continue treatment anyway. So, we're not quite there, where we're basing our full decisions on that and that's going to take more time.

So, you'll see a study will be done in which patients who had, let's say, 2 consecutive levels which were unmeasurable on minimal residual disease down to multiple logs down of a tumor regression, and well actually discontinue half of those patients on further therapy, the other half will continue. And then we'll see over 2 years what the outcomes are. That's what's going to start to happen. Now, how do we now take this tool which has been validated, which is being used, and then start to apply it where it really will influence the way in which we treat the patient going forward?

What steps could be taken to improve utilization of ctDNA in colorectal cancer?

Bruce Feinberg, DO: What made medicine modern is the concept of the randomized controlled clinical trial, the idea that we weren't going to make decisions based on anecdote. I observe this, so I'm going to try this again on this patient, I thought it seemed to work in that patient, I'm going to tell my colleague, and there's this groundswell. I write a letter to the editor, a case study of 3 patients, and suddenly it starts to be adopted. That was the world of medicine up until the mid-1980s, to some degree. The introduction of randomized controlled clinical trials really elevated it. We're going to remove all biases of the observer, you're not going to know if the patient got the treatment or they got the sham, if they got the experimental drug or they got the standard of care. And patients won't know and doctors won't knowdouble blinded. And we're going to have independent assessments done, what's called blinded independent review of the X-rays of the pathology. So, again, we're going to have a central source looking at everything and looking with the same eyes. So, we don't have all these different investigators with their own little ways of doing things. And we introduced a rigor to the process. Now, there were problems with that, and the problems were that it took time and it took money. Now we're finding ways to expedite and accelerate those processes, but they still represent a scientific rigor which we need to continue. And that's what's going to be done with ctDNA. It's going to be applying, now that we know that the science is sound, doing those kinds of studies as accelerated as we can do them, in order to prove the effectiveness of it as a tool that's going to directly impact the care of the patient, as opposed to information for informations sake.

What does implementation of ctDNA look like in the community setting versus the hospital setting? What are the benefits or obstacles of this environment for ctDNA testing?

Bruce Feinberg, DO: So, fortunately, the ctDNA technology is readily available now. And there are multiple commercial labs that do it. And so, it's no longer something which can only be done in an academic institution, by that hospital or a sophisticated laboratory. So, it's readily available to all providers in whatever sphere they're working in. And therefore, it's a readily available tool for the management of all patients. So, I don't think we have any barriers to access of the technology. I think the barrier will be really overcoming what are reasonable health care provider reservations with a new technology.

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Expert: Increasing Use of Circulating Tumor DNA in Oncology Will Take Time - Pharmacy Times

Cloning, expression and purification

ORC, Cdc6, Mcm27Cdt1, DDK, CDK, Sld2, Sld3Sld7, Cdc45, Dpb11, Pol , Pol exo-, Pol , TopoI, Mcm10 and yeast histone octamer were purified on the basis of previously established protocols1,11,24,33,48,49,50,51.

Designed DNA fragments (Supplementary Table 1) were subcloned from pMA vectors (Supplementary Table 2) to pRS shuttle vectors (Supplementary Table 2), which were used to generate yeast strains (Supplementary Table 3) used to overexpress Mcm27Cdt1 mutants. The oMG25 DNA fragment was subcloned from pMG39 to pAM38 using MluI and XbaI restriction sites to obtain pMG69, which was integrated into the yJF21 yeast strain, thus generating the yAE164 strain that was used to overexpress the Mcm2 6A mutant (Mcm2 V580A/K582A/P584A/K587A/W589A/K633A). The oMG27 DNA fragment was subcloned from pMG43 to pJF4 using BsiWI and SphI restriction sites to obtain pMG53, followed by the integration of pMG53 into the yAM20 strain, yielding the yAE160 strain, which was used for overexpression of the Mcm6 2E mutant (Mcm6 T423E/R424E). The oMG28 DNA fragment was subcloned from plasmid pMG44 to pJF4 using BsiWI and SphI restriction sites, thus obtaining plasmid pMG54. The pMG54 plasmid was integrated into the yAM20 strain, yielding the yAE161 strain that was used to overexpress the Mcm6 5E mutant (Mcm6 T408E/Q409E/L410E/G411E/L412E). All Mcm27Cdt1 mutants were purified essentially as wild type50.

A gene block encoding a twin-strep tag and the first three codons of Psf3 was amplified and cloned into pFJD5 by restriction-free cloning techniques. A list of primers and gene blocks used is included in Supplementary Table 1. BL21(DE3)-CodonPlus-RIL cells (Agilent) were transformed with GINS expression plasmid (pJL003). Transformant colonies were inoculated into a 250-ml LB culture containing kanamycin (50gml1) and chloramphenicol 35gml1), which was grown overnight at 37C with shaking at 200rpm. The following morning, the culture was diluted 100-fold into 6 1l of LB with kanamycin (100gml1) and chloramphenicol (35gml1). The cultures were left to grow at 37C until an optical density at 600nm (OD600nm) of 0.5 was reached; 0.5mM isopropyl -d-1-thiogalactopyranoside (IPTG) was added to induce expression and cells were left shaking for 3h. Cells were collected by centrifugation at 4,000rpm for 20min in a JS.4.2 rotor (Beckman). For lysis, cell pellets were resuspended in 120ml of lysis buffer (100mM Tris-HCl pH 8.0, 10% glycerol, 0.02% NP-40, 1mM EDTA, 200mM NaCl, Roche protease inhibitor tablets and 1mM dithiothreitol (DTT) + 0.7mM phenylmethylsulfonyl fluoride(PMSF). The lysate was sonicated for 120s (5s on, 5s off) at 40% on a Sonics Vibra-Cell sonicator. Insoluble material was removed by centrifugation at 20,000rpm for 30min in a JS.25.50 rotor (Beckman). The supernatant was loaded by gravity onto a 1-ml Strep-TactinXT column (IBA). The resin was washed extensively with wash buffer (100mM Tris-HCl pH 8.0, 10% glycerol, 1mM DTT and 1mM EDTA). GINS was eluted by the addition of 6ml of 1 buffer BXT (IBA) supplemented with 10% glycerol and 1mM DTT. The GINS-containing fractions were pooled and dialysed overnight in gel filtration buffer (25mM HEPES-KOH pH 7.6, 10% glycerol, 0.02% NP-40, 200mM potassium acetate and 1mM DTT). The sample was concentrated and loaded onto a HiLoad 16/600 Superdex 200 equilibrated in the same buffer. GINS-containing fractions were pooled, aliquoted and snap-frozen in liquid N2. About 22mg GINS was purified from a 6-litre culture.

The codon-optimized expression sequence for MH containing a HRV 3C protease cleavage site followed by a twin-strep tag was synthesized and cloned into pET302 by GeneWiz Synthesis (pJL004). T7 express cells (NEB) were transformed with pJL004. Transformant colonies were inoculated into a 250-ml LB culture with ampicillin (100gml1), which was grown overnight at 37C with shaking at 200rpm. The following morning, the culture was diluted 100-fold into 6 1l of LB with ampicillin (100gml1). The cultures were left to grow at 37C until an OD600nm of 0.5 was reached; 0.5mM IPTG was added to induce expression and cells were left shaking for 3h. Cells were collected by centrifugation at 4,000rpm for 20min in a JS.4.2 rotor (Beckman). For lysis, cell pellets were resuspended in 80ml of lysis buffer (20mM Tris-HCl pH 8.5, 10% glycerol 0.5mM EDTA, 500mM KCl, Roche protease inhibitor tablets and 2mM tris(2-carboxyethyl)phosphine (TCEP)) + 0.7mM PMSF. The lysate was sonicated for 120s (5s on, 5s off) at 40% on a Sonics Vibra-Cell sonicator. Insoluble material was removed by centrifugation at 20,000rpm for 30min in a JS.25.50 rotor (Beckman). The supernatant was loaded by gravity onto a 5-ml Strep-TactinXT column (IBA). The resin was washed extensively with lysis buffer. MH was eluted by the addition of 12ml of 1 BXT (IBA) supplemented with 10% glycerol and 1mM DTT. The MH-containing fractions were pooled and loaded onto a HiLoad 16/600 Superdex 75 equilibrated in gel filtration buffer (20mM Tris-HCl pH 8.5, 10% glycerol 0.5mM EDTA, 100mM KCl and 0.5mM TCEP). MH-containing fractions were pooled, aliquoted and snap-frozen in liquid N2. About 36mg MH was purified from a 6-litre culture.

The native ARS1 origin of replication flanked by Widom 601 and 603 sites or MH-flanked was amplified by PCR and purified as previously described24. The 6 ARS1 array (pSSH005) was assembled by inserting an array of 6 ARS1 origins with 40-bp spacing flanked by MH sites using NEBuilder HiFi assembly. The 6 ARS1 origin array was amplified from pSSH005 using primer oSSH038 and concentrated by ethanol precipitation. A list of primers and DNAs used is included in Supplementary Table 1.

Soluble yeast nucleosomes were reconstituted from octamers and DNA by salt gradient dialysis in several steps from 2 to 0.2 M NaCl as previously described24. Following nucleosome refolding, a final dialysis step was performed into loading buffer (25mM HEPES-KOH pH 7.6, 80mM KCl, 100mM sodium acetate, 0.5mM TCEP) and loaded onto a Superose 6 Increase 3.2/300 column equilibrated in the same buffer. Fractions containing ARS1 origin DNA bound by 2 nucleosomes were pooled, concentrated, and stored at 4C. Reconstitution conditions were optimized by small-scale titration and nucleosomes checked by 6% native PAGE.

The conjugation of MH with origin substrates was performed in 50mM Tris-HCl pH 8.0, 1mM EDTA and 0.5mM 2-mercaptoethanol supplemented with 100M S-adenosylmethionine (NEB). The reaction was carried out overnight at 30C, with a 10:1 molar ratio of MH:DNA. After conjugation, reactions were centrifuged at 14,680rpm for 5min and loaded onto a 1ml RESOURCE-Q column equilibrated into DNA buffer (50mM Tris-HCl pH 8.0 and 5mM 2-mercaptoethanol). MH-conjugated DNA was eluted in a linear gradient of DNA buffer B (50mM Tris-HCl pH 8.0, 5mM 2-mercaptoethanol and 2M NaCl) over 24column volumes. Fractions containing MH-conjugated DNA were pooled, concentrated and stored at 80C. Conjugations were checked by 6% native PAGE.

The conjugation of MH with origin substrates was performed in 25mM Tris-HCl pH 7.5, 10mM magnesium acetate, 50mM potassium acetate and 1mgml1 BSA supplemented with 150M S-adenosylmethionine (NEB). The reaction was carried out at 32C for 1h then overnight at 4C, with a 20:1 molar ratio of MH:DNA. After conjugation, reactions were centrifuged at 14,680rpm for 5min and loaded onto a Superose 6 Increase 10/300 column equilibrated into array buffer (25mM HEPES-KOH pH 7.5, 200mM NaCl and 1mM DTT). Fractions containing MH-conjugated array DNA were pooled, concentrated and stored at 4C. Conjugations were checked by 6% native PAGE.

The 616-bp ARS1 circles were assembled and prepared as previously described1 with the following modifications. The dephosphorylation step was performed with the use of quickCIP, instead of Antarctic phosphatase, for 30min at 37C followed by enzyme inactivation at 80C for 2min. After the ligation step, the DNA was concentrated as described and incubated with T5 exonuclease (NEB; 37C for 1h) to eliminate non-ligated DNA. Ethanol precipitation, agarose electrophoresis and electroelution were omitted; instead, phenol/chloroform/isoamyl-alcohol extraction was performed, followed by ethanol precipitation using sodium acetate (pH 5.1) and the neutral carrier GeneElute Linear Polymer (LPA, MERCK).

ARS1 nucleosome-flanked origin DNA (20nM) was incubated with 52nM ORC, 52nM Cdc6 and 110nM Mcm27Cdt1 for 30min at 24C in loading buffer (25mM HEPES-KOH pH 7.6, 100mM potassium glutamate, 10mM magnesium acetate, 0.02% NP-40 and 0.5mM TCEP) + 5mM ATP. The reaction was supplemented with 80nM DDK, and incubation continued for a further 10min at 24C. Nucleoprotein complexes were isolated by incubation with 5l MagStrep type3 XT beads (IBA) pre-washed in 1 loading buffer for 30min at 24C. The beads were washed three times with 100l wash buffer (25mM HEPES-KOH pH 7.6, 105mM potassium glutamate, 5mM magnesium acetate, 0.02% NP-40 and 500mM NaCl) and once with 100l loading buffer. Loaded, phosphorylated double hexamers were eluted in 20l elution buffer (25mM HEPES-KOH pH 7.6, 105mM potassium glutamate, 10mM magnesium acetate, 0.02% NP-40, 0.5mM TCEP, 27mM biotin and 5mM ATP) for 10min at 24C. The remaining supernatant was removed and incubated with 200nM CDK for 5min at 30C. A mix of firing factors was then added to a final concentration of 30nM Dpb11, 100nM GINS, 80nM Cdc45, 20nM Pol , 30nM Sld3Sld7 and 50nM Sld2. After 30min of incubation, the reaction was applied directly to grids or diluted fivefold in 1 loading buffer for ReconSil experiments.

MH-capped ARS1 array DNA (5nM) was incubated with 52nM ORC, 52nM Cdc6 and 110nM Mcm27Cdt1 for 30min at 24C in loading buffer (25mM HEPES-KOH pH 7.6, 100mM potassium glutamate, 10mM magnesium acetate, 0.02% NP-40 and 0.5mM TCEP) + 5mM ATP. The reaction was supplemented with 80nM DDK, and incubation continued for a further 10min at 24C. Nucleoprotein complexes were isolated by incubation with 5l MagStrep type3 XT beads (IBA) pre-washed in 1 loading buffer for 30min at 24C. The beads were washed three times with 100l wash buffer (25mM HEPES-KOH pH 7.6, 105mM potassium glutamate, 5mM magnesium acetate, 0.02% NP-40 and 500mM NaCl) and once with 100l loading buffer. Loaded, phosphorylated double hexamers were eluted in 20l elution buffer (25mM HEPES-KOH pH 7.6, 105mM potassium glutamate, 10mM magnesium acetate, 0.02% NP-40, 0.5mM TCEP, 27mM biotin and 5mM ATP) for 10min at 24C. The remaining supernatant was removed and incubated with 200nM CDK for 5min at 30C. A mix of firing factors was then added to a final concentration of 90nM Dpb11, 300nM GINS, 240nM Cdc45, 60nM Pol , 90nM Sld3Sld7 and 150nM Sld2. After 30min of incubation, the reaction was diluted fivefold in 1 loading buffer and applied to grids.

For experiments in which DNA was partially digested after the CMG formation reaction, MseI (NEB) was added at a concentration of 0.1U diluted in 1 loading buffer. Incubation was performed for 10min at 30C before applying to EM grids.

Replication assays were performed as described previously52. The reactions were incubated in a ThermoMixer at 30C with 1,250rpm shaking. The reaction buffer was as follows: 25mM HEPES-KOH pH 7.6, 10mM magnesium acetate, 2mM DTT, 0.02% NP-40, 100mM potassium glutamate and 5mM ATP. MCM helicase loading reaction (5l) contained 30nM ORC, 30nM Cdc6, 60nM Mcm27Cdt1 (or MCM mutants) and either 4nM ARS-containing 10.6kb supercoiled plasmid (pJY22; Supplementary Table 2) or 40nM ARS-containing short linear DNA (flanked by nucleosomes or MH; Supplementary Table 2) as for Fig. 1. After 20min, DDK was added to a final concentration of 50nM and further incubated for 20min. Next, the reaction volume was doubled (final volume was 10l) by adding proteins (20nM Pol , 30nM Dpb11, 20nM GINS, 50nM Cdc45, 20nM CDK, 50nM RPA, 10nM TopoI, 100nM Pol , 25nM Sld3Sld7, 10nM Mcm10 and 50nM Sld2) and nucleotides (200M CTP, 200M GTP, 200M UTP, 80M dCTP, 80M dGTP, 80M dTTP, 80M dATP and 50nM 32P-dCTP). For replication reactions with linear DNA (Fig. 1) Pol exo- was used instead of Pol wild type to reduce end labelling and the concentration of deoxynucleotides was modified (that is, 30M dCTP, 30M dGTP, 30M dTTP, 30M dATP and 100nM 32P-dCTP). The reactions were stopped by EDTA after 15 and 30min for reactions with 10.6-kb supercoiled DNA or after 20min for reactions with short linear DNA substrates and processed as described51,52. The replication products were separated using 0.8% agarose alkaline gel for 17h at 25V for reactions with 10.6-kb supercoiled DNA. For reactions with short DNA substrates, samples were separated using 2% agarose alkaline gel for 4h at 38V. The image signal from Fig. 1e was background-subtracted in Fiji using the subtract background algorithm in Fiji v.2.0.0 (ref. 53).

The experiment was performed as described previously1. The concentrations of proteins were as follows: 10nM ORC, 50nM Cdc6, 100nM Mcm27Cdt1 (or Mcm mutants), 80nM DDK for the helicase loading step (5l) and 20nM Pol , 30nM Dpb11, 40nM GINS, 50nM Cdc45, 30nM CDK, 10nM TopoI, 25nM Sld37, 5nM Mcm10, 50nM Sld2 for the helicase activation step (10l). Radiolabelled 616-bp circular DNA (25fmol) was used. After processing the reactions as described previously1, Ficoll 400 (final concentration was 2.5%) and Orange G were used to load the sample onto a native 3.5% bis-polyacrylamide gel (1 TBE) and separation was carried out for 21h at 90V using Protean II XL Cell apparatus (Bio-Rad) at room temperature. The 0.7-mm gel was dried (without fixation) at 80C for 105min, exposed to a phosphor screen and scanned with the use of Typhoon phosphor imager.

NS-EM sample preparation was performed on 400-mesh copper grids with carbon film (Agar Scientific). Grids were glow-discharged for 30s at 45mA using a K100X glow discharge unit (Electron Microscopy Sciences) before a 4-l sample was applied to the grids and incubated for 2min. Grids were stained by two successive applications of 4l 2% (w/v) uranyl acetate with blotting between the first and second application. Stained grids were blotted after 20s to remove excess stain. Unless described otherwise, data collection was carried out on a Tecnai LaB6 G2 Spirit transmission electron microscope (FEI) operating at 120keV. A 2K2K GATAN Ultrascan 100 camera was used to collect micrographs at a nominal magnification of 30,000 (with a physical pixel size of 3.45 per pixel) within a 0.5 to 2.0m defocus range.

A subset of particles was manually picked using RELION-3.1 (ref. 26) and used as a training dataset for Topaz training53. Subsequent image processing was performed using RELION-3.1. The CTF of each micrograph was estimated using Gctf (ref. 54) and particles were extracted and subjected to reference-free 2D classification in RELION-3.1.

For ReconSil experiments, image processing was carried out as detailed above. Reference-free 2D classification in RELION generates both 2D class averages and star files detailing the class assignment, particle coordinates and transformations (translations and rotations) applied to the raw particles for alignment.2D averages are superposed on the raw micrographs, overlaid on the particles that contributed to their generation. This yieldedsignal-enhanced ReconSiled micrographs reconstituting the contextof complete origins of replication. ReconSiled micrographs were used for the selection and rejection of origin nucleoproteins for further analysis.

ReconSiled origins were analysed as previously described24. In brief, ReconSiled micrographs were used to re-extract particles of interest in RELION. Selected particles were manually classified for statistical analysis. Measurements of ReconSiled origins were performed manually using Fiji55 and plotted in GraphPad Prism v.9.2.0.

CMG assembly reactions (reconstituted as described in In vitro CMG assembly on short chromatinized origins) were frozen on 400-mesh lacey grids with a layer of ultra-thin carbon (Agar Scientific). All grids were freshly glow-discharged for 1min at 45mA using a K100X glow discharge unit (Electron Microscopy Sciences) before plunge freezing. Samples were prepared by applying 4l of undiluted CMG assembly reactions for 2min on a grid equilibrated to 25C in 90% humidity. The grid was blotted for 4.5s and plunged into liquid ethane. Data collection was performed on an in-house Thermo Fisher Scientific Titan Krios transmission electron microscope operated at 300kV, equipped with a Gatan K2 direct electron detector camera (Gatan) and a GIF Quantum energy filter (Gatan). Images were collected automatically using the EPU software (Thermo Fisher Scientific) in counting mode with a physical pixel size of 1.08 per pixel, with a total electron dose of 51.4 electrons per 2 during a total exposure time of 10s dose-fractionated into 32 movie frames (Extended Data Table 1). We used a slit width of 20eV on the energy filter and a defocus range of 2.0 to 4.4m. A total of 65,286 micrographs were collected from two separate sessions.

Data processing was performed using RELION-3.1 (ref. 26) and cryoSPARC v.3.2 (ref. 56) (Extended Data Fig. 3). The movies for each micrograph were first corrected for drift and dose-weighted using MotionCorr2 (ref. 57). CTF parameters were estimated for the drift-corrected micrographs using Gctf within RELION-3.1 (ref. 54). Dataset one was first processed separately and combined with dataset two at a later stage.

For the first dataset, particles were picked using a manually curated particle set as a template in crYOLO v.1.7.5 (ref. 58). These particles were binned by 2 and extracted with a box size of 360 pixels for 2D and 3D classification. A subset of 1,600 representative particles across the entire defocus range was selected. Picks in areas of obvious particle aggregation were removed along with particles located on the carbon lace. A Topaz53 model was then iteratively trained on the remaining particles. All particles were re-picked with the Topaz model with the default score threshold of 0 for particle prediction. The two datasets were combined and a total of 927,109 particles were picked, binned by 2 and extracted with a box size of 360 pixels. We carried out 2D classification to remove remaining smaller particles and contaminants. We subjected the remaining particles to 3D multi-reference classification with four sub-classes, angular sampling of 7.5, a regularization parameter T of 5 using low-pass-filtered initial models from previous ab initio and processing steps on dataset 1 of dCMGE complexes, and double hexamer model generated from EMD-3960 (Extended Data Fig. 3). The resulting 133,262 (trans-dCMGE) and 46,049 (cis-dCMGE) particles with density corresponding to Pol on both CMG molecules were un-binned and refined to yield maps with resolutions of 7.7 and 14.4. C2 symmetry imposition did not improve the quality of the maps. The 133,262 trans-dCMGE particles were imported into cryoSPARC and subjected to multiple rounds of non-uniform refinement, heterogenous 3D classification and non-uniform local refinement, yielding a map at approximately 8 (Extended Data Fig. 3). Attempts to improve cis-dCMGE were unsuccessful given the limited particle numbers. As expected, these reconstructions do not show secondary structural features owing to the conformational heterogeneity between the two CMGE molecules bound by flexible DNA. We applied a C2 symmetry expansion procedure to both trans- and cis-dCMGE particles (179,311) with re-centring on one CMGE in RELION and combined all particles. We also downsized the box size to 512 pixels during this process to speed up downstream processing. Following this, masked 3D refinement with local searches in C1 of the centred single CMGE (consisting of 358,622 particles) was refined to 4.2- resolution. These particles were subjected to several rounds of CTF refinement and two rounds of Bayesian polishing. After this, CTF-refined and polished particles were refined with local searches in C1 with a mask encompassing the entire CMGE density to 3.6- resolution. To better resolve the DNA inside the MCM central channel, densities corresponding to Cdc45, GINS and Pol were subtracted in RELION. Signal-subtracted particles were analysed by 3D variability analysis in cryoSPARC (ref. 56). A subset of 71,348 particles was selected based on the quality of DNA density. These signal-subtracted particles were subsequently reverted to the original particles and refined using local searches in C1 using local searches to 3.5- resolution.

All refinements were performed using fully independent data half-sets and resolutions are reported based on the Fourier shell correlation (FSC)=0.143 criterion (Extended Data Fig. 2). FSCs were calculated with a soft mask. Maps were corrected for the modulation transfer function of the detector and sharpened by applying a negative B-factor as determined by the post-processing function of RELION or in cryoSPARC. The final RELION half-maps were used to produce a density modified map using the PHENIX Resolve CryoEM (refs. 28,59). This 3.4- map showed significant improvements for side chain and DNA density as well as for overall interpretability. Local-resolution estimates were determined using PHENIX or cryoSPARC (Extended Data Fig. 2f,j). The conversions between cryoSPARC and RELION files were performed using the UCSF pyem v.0.5 package60.

CMG (from PDB 6SKL)31, Pol2 subunit (from PDB 6HV9)33 and a homology model of the N-terminal domain of Dpb2 obtained from the Phyre2 server61 were docked initially into the cryo-EM map produced from Resolve CryoEM, using USCF Chimera, and refined against the map using Namdinator62 as a starting point for modelling with Coot v.0.9.1 (ref. 63). The DNA and the MCM5 winged helix domain were built de novo. The register of origin DNA engagement of dCMGE is heterogeneous because MCM double hexamers can slide along duplex DNA before dCMGE is formed. For this reason we could not build the origin DNA sequence with certainty and modelled polyA:polyT DNA instead. The resulting model was then subjected to an iterative process of real-space refinement using Phenix.real_space_refinement64 with geometry and secondary structure restraints and base-pairing and base-stacking restraints where appropriate, followed by manual inspection and adjustments in Coot. The geometries of the atomic model were evaluated by the MolProbity webserver65.

Maps were visualized in UCSF Chimera66 and ChimeraX67 and all model illustrations and morphs were prepared using ChimeraX or PyMOL.

Statistical analysis was performed using a two-tailed Welchs t-test in GraphPad Prism v.9.2.0. No statistical methods were used to predetermine sample size. The experiments were not randomized, and investigators were not blinded to allocation during experiments and outcome assessment.

Further information on research design is available in theNature Research Reporting Summary linked to this paper.

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Mechanism of replication origin melting nucleated by CMG helicase assembly - Nature.com