Stem Cell Clinic

Novel Microfluidic Method Optimizes Stem Cell Extraction for … – Technology Networks

By Stem Cell Treatment

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Researchers from the Critical Analytics for Manufacturing Personalized-Medicine (CAMP) Interdisciplinary Research Group (IRG) of Singapore-MIT Alliance for Research and Technology (SMART), MITs research enterprise in Singapore, in collaboration with the Agency for Science, Technology and Research (A*STAR) Bioprocessing Technology Institute (BTI) and National University Health System (NUHS), have developed a groundbreaking technology capable of extracting mesenchymal stem cells (MSCs) directly from pure bone marrow also known as bone marrow aspirate (BMA), a pivotal source of MSCs without dilution.

Using a world-first continuous sorting technique on a multi-chip Deterministic Lateral Displacement (DLD) microfluidic platform, the new method doubles the quantity of MSCs obtained from bone marrow samples and shortens the time taken to around 20 minutes. It also reduces donor discomfort due to less bone marrow being extracted, speeds up cell production, and simplifies cell therapy manufacturing. This advancement represents a significant step toward more accessible and efficient advanced medical treatments that use MSCs including treatment for osteoarthritis, autoimmune and infectious diseases, and neurological disorders.

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Cell therapy is a field of medicine where cells are used as living drugs to fight diseases or restore and replace damaged cells. Advances in regenerative medicine and immunotherapy have benefited countless patients; they offer numerous new treatment alternatives to previously intractable diseases, with hundreds more in the developmental pipeline that gives new hope to patients. However, obtaining high-quality raw materials in this case, MSCs has long been a hurdle in cell therapy manufacturing, as traditional isolation methods such as centrifugation are inefficient and complex. In addition to a long processing time of around two to three hours, current methods result in low yield due to challenges such as osmotic stress and complex workflows. State-of-the-art sorting techniques such as fluorescence-activated cell sorting (FACS) rely on costly antibodies and intricate preparation, posing major limitations for manufacturing of these living medicines.

In a paper titled Scalable mesenchymal stem cell enrichment from bone marrow aspirate using DLD microfluidic sorting, recently published in the journal Lab on a Chip, SMART researchers have pioneered a revolutionary stem cell sorting platform, addressing the challenges of large-scale cell sorting and manufacturing. Using DLD microfluidic technology, a label-free cell sorting method which distinguishes between stem cells and blood cells, the platform processed small bone marrow samples (2.5mL) in just 20 minutes with double the stem cell yield compared to traditional methods, and bypasses costly reagents and complex processes.

In this method pioneered by SMART, human bone marrow samples that arrive at the laboratory undergo a simple filtration step to remove unwanted cells and tissues that could obstruct the chip. Samples are then loaded onto SMARTs sorting platform, and cells of interest (MSCs) are automatically sorted and collected in outlet reservoirs. These collected cells are then combined into a vial for further processing and quantification as needed.

This innovative breakthrough in cell sorting utilises microfluidic technologies, leveraging cells' natural properties and eliminating the necessity for labelling. With conventional methods, cells are sorted using fluorescent or magnetic tags to label certain cellular features. This is challenging as these labels could interfere with subsequent analysis and testing, or worse damage the cells. In comparison, passive techniques like the DLD method developed at SMART are user-friendly, gentle on cells and easily integrated into clinical sample processing workflows. MSCs are very sensitive to its external environment, and perturbations could alter the biology in unanticipated ways.

"This novel platform provides a fresh perspective for stem cell sorting through a more efficient, label-free and, importantly, seamless process integration into current industrial manufacturing pipeline. Our research team at SMART is excited about the possibilities this technology brings to the field of stem cell research and therapy. The successful demonstration of this technology gives us greater confidence to venture into other bioprocessing applications such as leukopheresis with great potential for clinical impact. This will significantly accelerate the development of cutting-edge treatments and improve accessibility for cell therapy," said Mr Nicholas Tan, Research Engineer at SMART CAMP and lead author of the paper.

Even though DLD cell sorting has previously been demonstrated, what is new in this work is that we were able to deploy the technique at a sufficiently high processing flow rate to impact real-world stem cell manufacturing workflow. Biomanufacturing and bioprocessing are areas in which I see much potential for applying microfluidics technology to improve overall efficiency and reduce the cost significantly, said Professor Jongyoon Han, Co-Lead Principal Investigator at SMART CAMP, Professor of Biological Engineering and Electrical Engineering at MIT and corresponding author of the paper.

Future efforts will focus on refining the technology by evaluating the quality of sorted MSCs from human bone marrow samples using methods such as reverse transcription polymerase chain reaction (RT-PCR) and differentiation assays. Simultaneously, CAMP is working towards increasing sorting speed and resolution, while refining the system's design for portability and user-friendliness, and increasing throughput to 10 ml per minute.

Our innovative approach marks a paradigm shift in cell sorting, a key process of cell therapy. By harnessing microfluidic technologies to capitalise on cells' intrinsic properties, we have eliminated the need for cumbersome and expensive labelling methods. It not only streamlines the sorting process but also ensures more accurate and reliable results in medical research. This breakthrough, driven by our commitment to advancing scientific frontiers, heralds a milestone in the realm of cellular studies," said Dr Kerwin Kwek, Research Scientist at SMART CAMP and co-lead author of the paper.

Reference:Tan Kwan Zen N, Zeming KK, Teo KL, et al. Scalable mesenchymal stem cell enrichment from bone marrow aspirate using deterministic lateral displacement (DLD) microfluidic sorting. Lab Chip. 2023;23(19):4313-4323. doi:10.1039/D3LC00379E

This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.

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Novel Microfluidic Method Optimizes Stem Cell Extraction for ... - Technology Networks

Priority Health Denied His Last Hope, CAR-T Cancer Treatment – ProPublica

By Stem Cell Treatment

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This story is part of a partnership with Scripps News.

Forrest VanPatten was 50 and strong after years as a molten-iron pourer when he learned in July 2019 that a hyperaggressive form of lymphoma had invaded his body. Chemotherapy failed. Because he was not in remission, a stem cell transplant wasnt an option. But his oncologist offered a lifeline: Dont worry, theres still CAR-T.

The cutting-edge therapy could weaponize VanPattens own cells to beat back his disease. It had extended the lives of hundreds of patients who otherwise had no chance. And VanPatten was a good candidate for treatment, with a fierce drive to stay alive for his wife of 25 years and their grown kids.

VanPatten didnt know it, but he also had the law on his side. His home state of Michigan had long required health insurers to cover clinically proven cancer drugs.

He and his family gripped tight to the hope that the treatment promised.

Then, his insurance company refused to approve it.

Across the country, health insurers are flouting state laws like the one in Michigan, created to guarantee access to critical medical care, ProPublica found. Fed up with insurers saying no too often, state legislators thought theyd solved the problem by passing hundreds of laws spelling out exactly what had to be covered. But companies have continued to dodge bills for pricey treatments, even as industry profits have risen. ProPublica identified dozens of cases in which plans refused to pay for high-stakes treatments or procedures from emergency surgeries to mammograms even though laws require insurers to cover them.

Companies can get away with this because the thinly staffed state agencies that oversee many insurers typically dont open investigations unless patients file complaints. Regulators acknowledge they catch only a fraction of violations. We are missing things, said Sebastian Arduengo, an assistant general counsel for Vermonts insurance department.

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In the 34 years since Michigan began to require cancer coverage, regulators there have never cited a company for violating the law.

Like most policyholders, VanPatten had no insight into the decision made by his insurer, a nonprofit called Priority Health that covers about a million Michigan residents.

He didnt know that around the time the therapy won the Food and Drug Administrations approval, executives at Priority Health had figured out a way to weasel out of paying for it.

Through interviews with former employees and a review of company emails and VanPattens medical records, ProPublica was able to crack through the usual secrecy and expose the health insurers calculations.

Former employees said the decision not to cover this treatment and a related one was driven almost entirely by their high price tags up to $475,000. Side effects that could land a patient in the hospital can push the bill over $1 million. Priority Health number crunchers calculated to the penny the monthly cost per policyholder if the company shifted the expense to them: 17 cents. But executives didnt raise premiums or absorb the extra cost. They decided to save that money.

Patients needs werent part of the equation, recalled Dr. John Fox, then Priority Healths associate chief medical officer. It was, This is really expensive, how do we stop payment?

Over Foxs objections, fellow executives came up with a semantic workaround: These cancer drugs arent technically drugs, they argued, theyre gene therapies. All Priority Health had to do was to exclude gene therapies from its policies, and it could say no every time.

Priority Health said in a written statement to ProPublica that it provides compassionate, high-quality, affordable coverage and spends 90 cents of every premium dollar on member care.

We are committed to making medical innovations available to members as quickly as possible, regardless of cost, as soon as they have been proven to be safe and effective, Mark Geary, a spokesperson, wrote. The company said it initially didnt cover CAR T-cell therapy because there was a lack of consensus about the treatments effectiveness.

Major life-threatening complications and side effects were common, with a high rate of relapse, the statement said.

At the time of VanPattens denial there was, in fact, already substantial consensus about the medication. In December 2017, the National Comprehensive Cancer Network, then an alliance of 27 leading U.S. cancer treatment centers, spelled out in its guidelines for B-cell lymphomas which patients should receive the therapy and when. VanPattens doctor said he met the criteria.

It was, This is really expensive, how do we stop payment?

VanPattens family signed a privacy waiver giving Priority Health permission to discuss his case with ProPublica. Nevertheless, Priority Health did not respond to questions about his case or whether the company had violated Michigans mandate to cover cancer drugs when it refused to pay for his therapy.

VanPatten was disappointed but tried to remain optimistic after the first denial in January 2020. He and his wife, Betty, who worked in medical billing, knew it often took an appeal to coax the insurer to approve care.

In early February, Dr. Stephanie Williams, then the head of the blood and marrow transplant program for Spectrum Health, came to see VanPatten in his hospital room on Grand Rapids Medical Mile. It had been more than six months since his diagnosis.

He was sitting up in bed hooked up to an IV. His face, once framed by reddish eyebrows and a signature goatee, was hairless and drained of color. Betty pasted on a tight smile.

Priority Health had denied the treatment again, Williams told them, though she vowed to keep fighting.

When she left the room, VanPatten swung his legs over the side of the hospital bed. He had remained resilient and good-humored through his illness. But at that moment, he felt like Priority Health was treating him like an expense, not a person. It got to him, the idea that the insurer he dutifully paid each month knew this was his only chance and was holding it just out of reach.

He grabbed a tissue box from a tray and hurled it against the wall.

Fox, whom Willams described as the conscience of the company, had long been the point person for oncology in Priority Healths medical department. In his earlier life as a practicing physician, he had trained at the Centers for Disease Control and Prevention as a chronic disease epidemiologist. When he joined Priority Health in 2000, he admired the companys focus on preventive care and the fact that his bosses encouraged him to build deep relationships with local hospitals and doctors.

CAR T-cell therapy was a breakthrough more than 20 years in the making, and Fox had tracked clinical trials and talked to oncologists about it. By genetically reengineering patients own white blood cells, then infusing them back into the body to fight cancer, the treatment helped most participants in clinical trials get into remission within three months.

He knew this would be a game changer for patients. He also knew the law. So when news of the FDAs approval of the first CAR-T medication, Kymriah, hit his inbox in August 2017, he recalled, I said, You know, were required to cover this. This is a treatment for cancer.

But the culture at Priority Health had shifted over the previous year under new leadership to focus on cost savings, Fox and four other former employees said in interviews. The company brought in a new chief medical officer, Dr. James Forshee, in late 2016 from Molina Healthcare, an insurer known for wringing profits out of Medicaid managed care plans.

In conversations about the new treatment, several former Priority Health employees recall, Forshee pointed out that the law required covering cancer drugs, and he argued that the new treatment actually wasnt a drug; it was a gene therapy. (Through a company spokesperson, Forshee declined to comment for this article.)

Fox thought this was ridiculous. He pressed company lawyers for an opinion. Priority Healths filings with the state indicate that we have to cover FDA approved cancer drugs, Fox wrote to two members of the legal department in a September 2017 email.

Senior counsel John Samalik responded, bolstering Forshees position that Priority Health didnt have to cover Kymriah: I believe legally we have a defensible argument that Kymriah is a gene therapy and not a drug. (Samalik declined to comment through a company spokesperson.)

Fox pointed out that the company already covered another gene therapy. He told ProPublica that he suggested asking state regulators whether the cancer-drug mandate applied to Kymriah, but Forshee and at least one other executive refused.

My inference being that, if we ask the state, they would say yes, so lets not ask, Fox said. Two other former Priority Health employees involved in the discussions confirmed Foxs recollections.

The FDA approved a second CAR T-cell medication, Yescarta, seven weeks after the first approval.

When ProPublica asked if the FDA considered CAR T-cell therapies drugs, an agency spokesperson said yes. She wrote in an email that they have been regulated as gene therapies, and that they are biological products and drugs under the Public Health Service Act (PHS Act) and the Federal Food, Drug and Cosmetic Act.

Fox continued to push Priority Health to cover them; Forshee didnt budge.

As they often did for new therapies, Priority Healths actuaries calculated the price tag. They estimated that each year, one patient would need Yescarta and one Kymriah. If spread across the companys members, the therapies would cost an extra 17 cents per member per month 8 cents for Yescarta and 9 cents for Kymriah, emails show.

If the company had chosen to absorb the cost rather than raise premiums, the extra expense potentially more than $1 million for each patient receiving the therapy could have hurt its bottom line. Other insurers had also balked at the cost of CAR-T and were slow to cover it.

Priority Health made a slight tweak to its 2018 filings to state regulators, one with life-changing implications for patients like VanPatten. As it had in the past, the company said it covered drugs for cancer therapy as required by state law. But the insurer slipped in a new sentence more than a dozen pages later: Gene therapy was not a Covered Service.

Watch the Scripps News Report Hope Denied

Meanwhile, regional and national health plans began approving the drugs. Kaiser Permanente started covering them within months of the FDAs approvals. Blue Cross Blue Shield of Michigan the states biggest health plan and Priority Healths main competitor paid for a cancer patient to receive CAR T-cell therapy in December 2017. (A spokesperson said in an email that the plan added coverage based on the treatments efficacy, without considering whether Michigans mandate applied. We would have covered these drugs irrespective of the law, she said.)

When the national Blue Cross Blue Shield Association made an announcement about CAR-T coverage later in 2018, employees at Priority Health forwarded it to one another. It was an I-told-you-so moment for Fox.

At a meeting that December, Fox made the case again that Priority Health should ask the state whether Michigans law required covering the new cancer treatments.

Forshee bristled. You dont trust our legal counsel? he responded, according to Fox and another executive who attended.

His own temper rising, Fox considered what would happen if the company maintained its position. Patients who needed these therapies would likely die. Fox and his team would have to sign the denial letters, knowing the despair and anger they would sow.

After working at Priority Health for more than 18 years, Fox had once thought hed retire there. He left that meeting certain he had to move on.

Health plans have a right to make money; were providing a service, Fox said. But we have to do that honestly and fairly, putting patients first, not profits or premiums first. To me, thats where we crossed the line.

About seven months later, on a sticky night in July 2019, Forrest and Betty VanPatten were sipping beers with friends at the local club of the Fraternal Order of Eagles.

When theyd moved to Sparta, a small Michigan town known for its apple orchards, this was where theyd found community. The club had hosted countless charity raffles and fundraisers, including a pink night for the American Cancer Society for which Forrest squeezed into a hot-pink minidress Betty sewed for him. (There wasnt much off-the-rack that could fit his almost 6-foot-8-inch frame.)

They were expecting biopsy results at any moment. Forrest had gone to the emergency room the previous weekend with intense pain. Hed made it through two previous bouts of lymphoma and suspected he was about to face another.

Forrests phone rang. It was the office of his primary oncologist, Dr. Brett Brinker. Oncologists meet hundreds of patients and their families, but Brinker had grown deeply fond of the VanPattens. Forrest was the guy who could talk to anyone, who made the party worth attending. Betty was his perfect foil. Their laughter and candor left a lasting impression.

The news was bad. Forrest had something called Richters transformation. It made his lymphoma significantly more aggressive and less likely to respond to conventional chemotherapy. After hanging up, Forrest typed Richters into his phone. Almost immediately, he proclaimed, This is a death sentence.

Betty needed to clear her head. She walked around the block, passing a restaurant where Forrests name was on the wall for completing a taco-eating challenge. When she got back, she urged Forrest to snap out of his defeatism.

He had just celebrated his 50th birthday and was determined to be around for his 51st. His kids, Donovan, 23, and Madison, 22, were in serious relationships, and he wanted to be there for their weddings.

So we went in and got a game plan, Betty said. Forrest would begin with chemotherapy, and, if the cancer went into remission, they would try for a stem cell transplant. If the cancer didnt go into remission, Brinker made it clear they werent out of options. He told them about CAR-T.

It felt reassuring at the time.

By January 2020, CAR-T was all they had left. Brinker said he thought the treatment could at least bring Forrests disease under control for a few years. Its hard to use the word cure when its acting like that, he said of Forrests cancer. But if they won some extra time, he said, theres always something in the wings you can hope for.

On Jan. 28, Williams, the doctor who ran the transplant program, worked with her team to submit a request for coverage to Priority Health. Williams knew the companys policy on CAR-T but thought the insurer might relent when faced with an actual patient who was certain to die without the treatment. Plus, by that point, the federal government was covering the therapies for Medicare patients, and insurers often follow its lead.

Knowing it could take weeks to grow the cells used in the treatment, his doctors prepared to extract his white blood cells. These are diseases where we dont have a lot of time to waste, Williams said.

Then Williams office found out that Priority Health had denied the request. Forrests doctors appealed but were turned down again, prompting Forrest to throw the tissue box at the wall.

Williams felt it, too. I was deflated. I was angry, she recalled. We kept trying to work it out, and we kept hitting roadblocks.

The VanPattens didnt have the money to pay out of pocket, and Forrest didnt want to saddle his family with medical debt. His medical team filed a third and final appeal, this one to an independent reviewer.

As that went forward, the VanPattens received a letter from Priority Health explaining its reasons for denying Forrests treatment. CAR-T cell therapy is not a covered benefit, and therefore, we are unable to approve this request, the letter stated. Somehow, seeing the words in writing conveyed a different finality, sending Forrest into a downward spiral.

Everybody deserves the chance of fighting, Betty said. Once you take somebodys hope away, you kill them you really, really do. It was evident with him. He was defeated, and he had never been defeated in his life, and that was hard to watch.

He was defeated, and he had never been defeated in his life, and that was hard to watch.

Their son, Donovan, took to social media to blast Priority Health for its decision, hoping to shame the company into a last-minute about-face. He included a screenshot of a text message from Forrest, who knew his insurer was an outlier. It should be noted that Blue Cross and Blue Shield of MI pays for Car T Cell! it read.

A reporter for Scripps News Grand Rapids, WXMI, a local TV news station, interviewed Forrest on Feb. 13 in the suede recliner hed long claimed as his chair in the familys living room.

I feel like Im being ignored, he said, tears streaming down his face. Left out to die, basically.

Days later, Forrest was back in Butterworth Hospital with shortness of breath. He is in acute distress, an emergency room doctor noted when he was admitted.

The following night, his heart stopped beating. Betty retreated to the back of the room as doctors and nurses swarmed in. Donovan sat in a chair outside, his head in his hands.

Madison raced through Grand Rapids snow-covered streets to join them. When she reached her fathers room, a member of the medical team was still pushing down on his chest. But, she recalled, it was clear he wasnt there anymore. The family told his doctors to end the resuscitation effort.

Forrest died on Feb. 17, before the independent medical reviewer had a chance to weigh in. Three weeks had passed since Williams and her team had asked Priority Health to cover the therapy.

Williams said that if Priority Health had approved the first request, Forrest could have received the infusion. Its unknowable whether the treatment would have given him more time, she said, but if hed had that chance, anything is possible.

Not long after Forrest died, his family received a handwritten card from a clinical coordinator who cared for him.

I am so so so sad that we didnt get the chance to put the rest of our plan into motion, she wrote. In honor of your kind (+very funny) husband, dad, friend, I promise to continue to push for Priority Health to cover CAR-T and to bring hope to all who need it.

In Priority Healths statement, Geary, the spokesperson, wrote that the company began covering the therapy after extensive clinical work improved the treatment. The company would not say when it began paying for the treatment or whether Forrests death influenced its decision.

It is devastating when a disease takes a members life, the statement said. We recognize the deep pain of losing someone you love.

To former state Sen. Joe Schwarz, now 86 and retired, the story of Priority Health and Forrest VanPatten is a painful echo of a problem he thought hed fixed.

More than 30 years ago, Schwarz helped write the Michigan law requiring insurers to pay for cancer drugs. Schwarz, a physician, still recalls what drove him to action: Insurance companies were refusing to pay for drugs given to make chemotherapy more effective, arguing they werent themselves chemotherapy. An op-ed in the Wall Street Journal by the head of the Association of Community Cancer Centers confirmed that insurers nationwide were denying coverage for cancer patients.

At a Senate hearing, Schwarz accused health plans of abandoning their policyholders based on a play on words. When ProPublica told Schwarz about Priority Healths gene-therapy argument, he let out a mirthless hah, scoffing at the wordplay.

You shouldnt split hairs between the term gene therapy and the term chemotherapy or the term radiation therapy or the term surgical therapy, he said. Theyre all cancer therapies and they should all be covered.

You shouldnt split hairs between the term gene therapy and the term chemotherapy or the term radiation therapy or the term surgical therapy. Theyre all cancer therapies and they should all be covered.

ProPublica gave Michigans Department of Insurance and Financial Services a detailed description of VanPattens case, as well as Priority Healths contention that it didnt have to cover CAR T-cell cancer therapies. We asked if Priority Health broke the state law on cancer treatments. Laura Hall, the departments communications director, wouldnt say. The agency can investigate if it spots a pattern of improper denials, but in general, she said, it only acts if a patient or their representative files a complaint.

The VanPattens didnt do that. And they didnt know about the Michigan law until ProPublica told them about it.

In the months after her husband died, Betty VanPatten was too weighed down by grief and anger to tangle with Priority Health through state insurance regulators. The days were a blur. Donovan and his partner, McKenzie, moved in with Betty, who threw herself into her job.

Id get up at 4, and Id have my laptop and I just worked until about 9 or 10 oclock, Betty said. And a lot of times Id just sit there and the tears are just running down my face.

The VanPattens still struggle with the sense that Forrest suffered an injustice and that Priority Health got away with it.

They lost sight of the patient, Betty said at a family dinner this July. Madison agreed.

Insurance is meant to protect people, she said, not to make them fight through the last day to get what they should.

Do You Have Insights Into Dental and Health Insurance Denials? Help Us Report on the System.

Insurers deny tens of millions of claims every year. ProPublica is investigating why claims are denied, what the consequences are for patients and how the appeal process really works.

Kirsten Berg contributed research.

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Priority Health Denied His Last Hope, CAR-T Cancer Treatment - ProPublica

Vor shares new data for stem cell therapy; Melinta partners with … – Endpoints News

By Stem Cell Treatment

Plus, news about BeiGene, Zymeworks, Rznomics, and Adicet:

Vor Bio shares early data for its gene-edited stem cell therapy: The company announced Thursday that its stem cell treatment seemed to engraft normally in seven patients with acute myeloid leukemia (AML) treated so far. Three patients who received Mylotarg Pfizers AML drug saw protection from deep cytopenias, or a steep drop in blood cell counts thats often seen as a side effect of the drug. Mylotarg targets CD33, an antigen found in high levels on leukemia cells but also expressed in some normal cells. Vor, founded on research led by Siddhartha Mukherjee, edits CD33 out of donor stem cells with the goal of sparing patients from the treatments side effects. More data are set to be presented at ASH, the company announced last week. Lei Lei Wu

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Vor shares new data for stem cell therapy; Melinta partners with ... - Endpoints News

Efficient protocol for the differentiation of kidney podocytes from … – Nature.com

By Induced Pluripotent Stem Cells

Human iPSC culture

All the experiments involving hiPSCs were approved by the ethics committee of Kansai Medical University (Approval Number: 2020197). We obtained the written informed consent of the donors from whom hiPSCs were derived. The study was performed according to the principles of the Declaration of Helsinki, as revised in 2013, and relevant institutional guidelines. Human iPSCs (585A1, 253G1, and HiPS-RIKEN-2F) were maintained with feeder-free cells using NutriStem hPSC XF (05-100-1A, Sartorius AG, Goettingen, Germany) on plates coated with iMatrix-511 silk (892021, Matrixome, Osaka, Japan) at 37C in a 5% CO2 incubator. Single cells were prepared from hiPSC colonies (7090% confluent) using Accutase (AT104, Innovative cell technologies, CA, USA) for subsequent passage and the induction of podocyte differentiation.

We generated podocytes from hiPSCs by modifying a previously reported differentiation protocol16 (Fig.1A). Human iPSCs were seeded at 3000 cells/well in 96 well low-cell-binding V-bottom plates, which were cultured in 200L NutriStem medium containing 10M Y27632 (FCS-10-2301-25, Focus biomolecules, PA, USA) at 37C for 24h. The medium was changed to DMEM Hams/F12 medium (048-29775, Fujifilm, Osaka, Japan) containing 2% B27 supplement (17504044, Thermo Fisher Scientific, MA, USA), 1ng/mL human activin A (338-AC, R&D Systems, MN, USA), and 20ng/mL fibroblast growth factor 2 (FGF2, 064-04541, Fujifilm). After 24h, cell aggregates were cultured for 6days in a medium (DMEM Hams/F12 medium) containing 2% B27 supplement and 10M CHIR99021 (10-1279, Focus biomolecules) that was changed every 2days. Subsequently, the medium was changed to one containing 10ng/mL human activin A, 3ng/mL human bone morphogenetic protein 4 (BMP4, PROTP12644, R&D System), 3M CHIR99021, and 100nM retinoic acid (RA, 302-79-4, Fujifilm). After a further 72h, this medium was switched to one containing 1M CHIR99021 and 10ng/mL FGF9 (273-F9, R&D Systems) without medium change to induce the differentiation of NPCs.

Differentiation of hiPSCs into podocyte. (A) Timeline and factors involved in the differentiation of hiPSCs into podocytes. (B) mRNA expression of podocyte-associated genes (NEPHRIN, PODOCIN, and SYNAPTOPODIN) during the 24days of culture. Results are shown as the meanSD of 6 samples. Statistical analysis was performed using one-way ANOVA with Bonferronis test. **p<0.01, ***p<0.001. (C) Immunostaining for markers of podocytes (NEPHRIN and PODOCIN) and F-Actin in differentiated cells, with nuclei stained with Hoechst. (D) mRNA expression of podocyte-associated genes (NEPHRIN, PODOCIN, and SYNAPTOPODIN) in hiPSCs, NPCs and differentiated podocytes. Results are shown as the meanSD of 6 samples. Statistical analysis was performed using one-way ANOVA with Bonferronis test. *p<0.05 (E) Protein expression of nephrin and podocin in hiPSCs, NPCs and differentiated podocytes, assessed using western blotting analysis. (F) Protein expression of undifferentiation stem cell marker (OCT-3/4) and nephron progenitor cell marker (SIX2) in hiPSCs, NPCs and differentiated podocytes, assessed using western blotting analysis. (G) Protein expression of nephron progenitor cell marker (SIX2) assessed using western blot analysis. Results are shown as the meanSD of 3 samples. Statistical significance was assessed using Students t-test. *p<0.05.

To generate podocytes, the medium was switched to one containing 3M CHIR99021, and after 24h, to one containing 2M IWR-1 (1127442-82-3, Fujifilm), 5M SB431542 (13031, Cayman Chemical, MI, USA), and 10M RA. After a further 24h, the differentiated cells were cultured for 11days in fresh medium containing 2M IWR-1 and 5M SB431542, which was replaced every 3days. Cell sorting was not performed at all steps.

To construct the monolayer cell culture, the cell aggregates were transferred to a 50-mL centrifuge tube, washed with PBS, then dissociated using Accutase. The cells (2,000 cells/cm2) were then seeded onto iMatrix-511 silk-coated dishes and cultured in DMEM Hams/F12 medium supplemented with 10M Y27632 and 2% B27 supplement. Cells were collected 24h after the treatment with DMEM Hams/F12 medium supplemented with Y27632 and B27 supplement.

To evaluate the involvement of the mTOR pathway in podocyte differentiation, rapamycin (R0161, LKT Laboratories, MN, USA) was administered at various times during the differentiation process and evaluated by mRNA expression using RT-PCR. In addition, S6 downstream of mTOR was inhibited using LY2584702 to further assess its involvement in the mTOR pathway.

RNA was extracted from the cells using ISOGEN II reagent (311-07361, Nippon gene, Tokyo, Japan), then a ReverTra Ace qPCR RT Master Mix (FSQ-201, Toyobo, Osaka, Japan) was used for reverse transcription. Real-time PCR was performed to quantify target mRNA expression using a Rotor-Gene Q (Qiagen) and Thunderbird SYBR qPCR Mix (QPS-201, Toyobo). The specific PCR primers used are listed (Table 1).

Cell lysates were collected using 4Bolt LDS Sample Buffer (B0007, Thermo Fisher Scientific), then electrophoresed on a 10% SDS polyacrylamide gel and blotted onto PVDF membranes. The membranes were incubated with anti-NEPHRIN (29070, Immuno-Biological Laboratories, Gunma, Japan), anti-PODOCIN (MBS9608910, Thermo Fisher Scientific), anti-Phospho-Akt (9271, Cell Signaling Technology, MA, USA), anti-Akt (9272, Cell Signaling Technology), anti-Phospho-mTOR (2971, Cell Signaling Technology), anti-mTOR (2972, Cell Signaling Technology), anti-Phospho-p70 S6 Kinase (9205, Cell Signaling Technology), anti-p70 S6 Kinase (2708, Cell Signaling Technology), anti-Phospho-S6 Ribosomal Protein (2211, Cell Signaling Technology), S6 Ribosomal Protein (2217, Cell Signaling Technology), anti-SIX2 (80170, Cell Signaling Technology), anti-OCT3/4 (611202, BD Biosciences, NJ, USA), and anti- actin (MAB8929, R&D Systems) primary antibodies, then further probed with anti-mouse IgG horseradish peroxidase-linked (A90-131P, Bethyl Laboratories, TX, US) secondary antibody. Specific protein bands were visualized using Pierce Western Blotting Substrate (NCI3106, Thermo Fisher Scientific).

Cultured cells were harvested after detachment using Accutase, then incubated for 30min at 4C with FITC-conjugated anti-PODOCIN antibody diluted 1:20. The cells were then centrifuged, the supernatants removed, and 500-L aliquots of PBS containing 2% StemSure Serum Replacement (191-18375, Fujifilm) added. Data were acquired using a BD FACS Canto II flow cytometer system (BD Biosciences).

Cells were fixed using 4% paraformaldehyde, and blocked with Blocking One (03953-95, Nacalai Tesque, Kyoto, Japan) for 60min at room temperature. Incubations were then performed at 4C overnight using primary anti-NEPHRIN, anti-PODOCIN antibody, and F-Actin (bs-1571R, Bioss Inc., MA, USA) antibody. Then, Alexa Fluor 488-tagged secondary antibody (ab150107, Abcam, Cambridge, UK) was applied for 30min at room temperature, and nuclei and F-actin were stained using 10g/mL Hoechst 33342 (346-07951, DOJINDO Laboratories, Kumamoto, Japan) and Phalloidin-iFluor 647 Conjugate (23127, AAT Bioquest, CA, USA), respectively. The stained cells were evaluated using fluorescence microscopy (BZ-X810, Keyence, Osaka, Japan).

Podocytes differentiated from hiPSCs were seeded at 2000 cells/cm2 onto Transwell inserts in six-well culture plates, pore size 0.4m (3450, Corning, AZ, USA) coated with iMatrix-511 silk. After 24h, DMEM Hams/F12 medium containing 2% B27 supplement, potassium chloride (5mM), urea (25mg/L), and human serum albumin (3g/dL) were added to the lower chambers, whereas the cells were incubated in a medium lacking the latter three substances in the upper chambers. After 24h, the media were collected from both of the chambers. The potassium concentration was measured using reagent for potassium measurement and electrode (EA09, A&T Corporation, Kanagawa, Japan). The urea nitrogen and albumin were measured using CicaLiquid-N UN reagent (77697, Kanto Chemical, Tokyo, Japan) and reagent of modified BCP method for albumin (30155001, Sekisui Medical, Tokyo, Japan), respectively, by an autoanalyzer (JCA-BM8020, JEOL Ltd., Tokyo, Japan).

Data are expressed as meanstandard deviation (SD). All experiments resulted by repeating the experiment three independent times. For the results shown in Figs.1B, 2A, and 3B, statistical analysis was performed using one-way ANOVA, followed by Bonferronis test; and Students t-tests were performed to compare the mean values of two groups for the data shown in Figs.2C and 5B. A p-value of<0.05 was considered to indicate statistical significance.

Effects of an mTOR inhibitor on podocyte differentiation. (A) Evaluation of the timing of rapamycin administration for protocol improvement: (a)13days treatment, (b)11days treatment and (c)7days treatment. (B) mRNA expression of podocyte-associated genes (NEPHRIN, PODOCIN, WT1, and MAFB) in cells treated with 100nM rapamycin at different times (a, b, c). Results are presented as meanSD of 6 samples. Statistical analysis was performed using one-way ANOVA with Bonferronis test. *p<0.05, **p<0.01. (C) mRNA expression of podocyte-associated genes (NEPHRIN, PODOCIN, SYNAPTOPODIN, WT1, and MAFB) in cells treated with various concentrations of rapamycin. Results are shown as the meanSD of 6 samples. Statistical analysis was performed using one-way ANOVA with Bonferronis test. *p<0.05, **p<0.01, ***p<0.001. (D) Protein expression of nephrin and podocin in differentiated podocytes, assessed using western blotting analysis. (E) Protein expression of nephrin and podocin assessed using western blot analysis. Results are shown as the meanSD of 3 samples. Statistical significance was assessed using Students t-test. *p<0.05. (F) Histograms for podocin-positive cells, quantified using FACS: (a) undifferentiated hiPSCs and (b) podocytes differentiated from hiPSCs.

Importance of the mTOR pathway for podocyte differentiation. (A) Protein expression of mTOR, p-mTOR, p70 S6K, p-p70 S6K, S6, p-S6, AKT, and p-AKT, assessed using western blotting analysis. (B) mRNA expression of podocyte-associated genes (NEPHRIN, PODOCIN, SYNAPTOPODIN, WT1, and MAFB) following the addition of the S6 inhibitor LY2584702. Results are shown as the meanSD of 6 samples. Statistical analysis was performed using one-way ANOVA with Bonferronis test. ***p<0.001.

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Efficient protocol for the differentiation of kidney podocytes from ... - Nature.com

A better way to study Parkinson’s disease in the lab could lead to … – EurekAlert

By Induced Pluripotent Stem Cells

image:

Lalitha Madhavan, MD, PhD, and her research team used induced pluripotent stem cell technology to reprogram adult skin cells into brain cells to study Parkinsons disease.

Credit: University of Arizona Health Sciences

A recent study published in Progress in Neurobiology and led by researchers at the University of Arizona College of Medicine Tucson has developed an improved method to study Parkinsons disease in the lab. Along the way, researchers also uncovered clues that may help scientists figure out how to detect Parkinsons earlier and point the way toward better treatments.

Around a million Americans are living with Parkinsons disease, a neurological disorder that causes difficulty in movement, balance and cognition. Symptoms worsen until tasks like walking, talking and swallowing present enormous challenges. While there is no cure, there are treatments that control symptoms but their effectiveness wanes over time and they are associated with unwanted side effects.

Its a slow-developing disorder. We only diagnose the disease at a late stage, when 60-70% of dopamine neurons are dysfunctional or have died off, said Lalitha Madhavan, MD, PhD, associate professor of neurology at the College of Medicine Tucson, part of UArizona Health Sciences. We have treatments, but at that point youre trying to throw a small glass of water on a raging fire. Being able to diagnose the condition at the earliest stages would be a big step.

Madhavans team used cells from Parkinsons patients to create a human-derived laboratory model to study the disease. Using induced pluripotent stem cell technology a powerful technique that transforms adult cells into embryo-like cells that can then mature into any cell type the lab reprogrammed adult skin cells called fibroblasts into brain cells.

Using the reprogrammed neurons, Madhavan Lab researchers discovered several changes in the cells from Parkinsons subjects that differentiated them from cells of healthy individuals. Madhavan hopes this finding can form the basis for better cell-culture systems for studying Parkinsons disease in the lab, potentially leading to improved diagnostics and treatments.

The experiments also showed that skin cells may act as a window into the brain. Skin cells dont cause neurological symptoms, but some of the same changes that damage brain cells might also affect skin cells, producing similar molecular signatures.

We wanted to make neurons from skin biopsies using this fantastic technology; however, we noted along the way that the fibroblasts themselves seemed to have signatures that differentiated individuals with Parkinsons. We started to dig deeper into that, Madhavan said. Its exciting that weve shown that connection, and that it tells us skin cells could perhaps be used to diagnose the disease early.

The team hopes that, in the future, doctors will be able to catch Parkinsons disease earlier by examining skin cells for signs that the disease is brewing.

This could be a system in which we could very carefully diagnose people at early stages, Madhavan said, adding that her team received a patent on a method for examining skin cells for molecular signs that correlate to Parkinsons disease.

They are now investigating how skin cells change over time to learn more about how the disease progresses and how to identify it early. Tech Launch Arizona, the University of Arizonas technology commercialization office, is helping protect the innovation and developing strategies to take it from the laboratory to the marketplace where it can impact the lives patients and their doctors.

Madhavan says that if we could catch Parkinsons disease earlier, doctors could prescribe currently available treatments that can slow disease progression. Simultaneously, scientists could work to develop next-generation Parkinsons drugs that target the disease in its early stages.

Because a patients skin cells are easy to access especially compared to brain cells Madhavan also hopes the system could be used for a precision-medicine approach, matching patients with optimized treatments based on a skin biopsy and lab test showing which drug might work best based on their unique genetic profile.

Weve been putting Parkinsons into one big bucket when actually different people express it differently, she said. This system would allow us to carefully classify Parkinsons and assess treatments more effectively based on such a classification.

The lead authors on the study were Mandi Corenblum, MS, senior research specialist, and Aiden McRobbie-Johnson, physiological sciences graduate student. Co-authors include Kelsey Bernard and Timothy Maley, graduate students in neuroscience and physiological sciences; Emma Carruth, undergraduate student in physiology; Moulun Luo, PhD, associate research professor of medicine; Lawrence Mandarino, PhD, professor of medicine; Maria Sans-Fuentes, PhD, BIO5 Institute statistician; Dean Billheimer, PhD, professor in the UArizona Mel and Enid Zuckerman College of Public Health and director of statistical consulting at the BIO5 Institute; and Erika Eggers, PhD, professor of physiology and member of the BIO5 Institute.

The study was supported mainly by a Michael J Fox Foundation grant (MJFF 18366) and in part by grants from the National Eye Institute, a division of the National Institutes of Health, under award nos. R01EY026027 and NSF1552184.

Progress in Neurobiology

Randomized controlled/clinical trial

Cells

Parallel neurodegenerative phenotypes in sporadic Parkinsons disease fibroblasts and midbrain dopamine neurons

22-Oct-2023

Declaration of Competing Interest None.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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A better way to study Parkinson's disease in the lab could lead to ... - EurekAlert

Lab-grown ‘small blood vessels’ point to potential treatment for major … – EurekAlert

By Induced Pluripotent Stem Cells

image:

Disease mural cells stained for calponin (mural cells marker, green), collagen IV (magenta) and DAPI (nuclei, blue)

Credit: Alessandra Granata/University of Cambridge

Cambridge scientists have grown small blood vessel-like models in the lab and used them to show how damage to the scaffolding that supports these vessels can cause them to leak, leading to conditions such as vascular dementia and stroke.

The study, published today in Stem Cell Reports, also identifies a drug target to plug these leaks and prevent so-called small vessel disease in the brain.

Cerebral small vessel disease (SVD) is a leading cause of age-related cognitive decline and contributes to almost half (45%) of dementia cases worldwide. It is also responsible for one in five (20%) ischemic strokes, the most common type of stroke, where a blood clot prevents the flow of blood and oxygen to the brain.

The majority of cases of SVD are associated with conditions such as hypertension and type 2 diabetes, and tend to affect people in their middle age. However, there are some rare, inherited forms of the disease that can strike people at a younger age, often in their mid-thirties. Both the inherited and spontaneous forms of the disease share similar characteristics.

Scientists at the Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, used cells taken from skin biopsies of patients with one of these rare forms of SVD, which is caused by a mutation in a gene called COL4.

By reprogramming the skin cells, they were able to create induced pluripotent stem cells cells that have the capacity to develop into almost any type of cell within the body. The team then used these stem cells to generate cells of the brain blood vessels and create a model of the disease that mimics the defects seen in patients brain vessels.

Dr Alessandra Granata from the Department of Clinical Neurosciences at Cambridge, who led the study, said: Despite the number of people affected worldwide by small vessel disease, we have little in the way of treatments because we dont fully understand what damages the blood vessels and causes the disease. Most of what we know about the underlying causes tends to come from animal studies, but they are limited in what they can tell us.

Thats why we turned to stem cells to generate cells of the brain blood vessels and create a disease model in a dish that mimics what we see in patients.

Our blood vessels are built around a type of scaffolding known as an extracellular matrix, a net-like structure that lines and supports the small blood vessels in the brain. The COL4 gene is important for the health of this matrix.

In their disease model, the team found that the extracellular matrix is disrupted, particularly at its so-called tight junctions, which zip cells together. This leads to the small blood vessels becoming leaky a key characteristic seen in SVD, where blood leaks out of the vessels and into the brain.

The researchers identified a class of molecules called metalloproteinases (MMPs) that play a key role in this damage. Ordinarily, MMPs are important for maintaining the extracellular matrix, but if too many of them are produced, they can damage the structure similar to how in The Sorcerers Apprentice, a single broom can help mop the floor, but too many wreak havoc.

When the team treated the blood vessels with drugs that inhibit MMPs an antibiotic and anti-cancer drug they found that these reversed the damage and stopped the leakage.

Dr Granata added: These particular drugs come with potentially significant side effects so wouldnt in themselves be viable to treat small vessel disease. But they show that in theory, targeting MMPs could stop the disease. Our model could be scaled up relatively easily to test the viability of future potential drugs.

The study was funded by the Stroke Association, British Heart Foundation and Alzheimers Society, with support from the NIHR Cambridge Biomedical Research Centre and the European Unions Horizon 2020 Programme.

Reference Al-Thani, M, Goodwin-Trotman, M. A novel human 1 iPSC model of COL4A1/A2 small vessel disease unveils a key pathogenic role of matrix metalloproteinases. Stem Cell Reports; 16 Nov 2023; DOI: https://doi.org/10.1016/j.stemcr.2023.10.014

Stem Cell Reports

Experimental study

Cells

A novel human 1 iPSC model of COL4A1/A2 small vessel disease unveils a key pathogenic role of matrix metalloproteinases

16-Nov-2023

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Lab-grown 'small blood vessels' point to potential treatment for major ... - EurekAlert

Vitamin B12 is a limiting factor for induced cellular plasticity and … – Nature.com

By Induced Pluripotent Stem Cells

Animal procedures

Animal experimentation at the IRB Barcelona was performed according to protocols approved by the Science Park of Barcelona (PCB) Ethics Committee for Research and Animal Welfare. Mice were housed in a specific pathogen-free facility on a 12-hour lightdark cycle at an ambient temperature of 2024C and humidity of 3070%. Adult mice were fed ad libitum with SAFE R40 pellet diet (https://safe-lab.com/safe_en/) containing 0.02mg per kg body weight vitamin B12. In general, mice of 816 weeks of age of both sexes were treated with 1mg ml1 doxycycline hyclate BioChemica (PanReac, A2951) in the drinking water (supplemented with 7.5% sucrose) for 7d. Antibiotic treatment was conducted using a broad-spectrum cocktail (1mg l1 each of ampicillin (BioChemica, A0839), neomycin sulfate and metronidazole (Sigma, M1547); 0.5mg l1 vancomycin (Cayman Chemical, CAY-15327) all dissolved in water supplemented with 7.5% sucrose) for 3 weeks before doxycycline initiation and was maintained during doxycycline treatment. Vitamin B12 (Sigma, V2876) supplementation was provided at 1.25mg l1 and folate supplementation was provided as folic acid (Sigma, F7876) at 40mg l1 in the drinking water, both for 7d concomitant with doxycycline treatment. For the B12 bolus experiment, mice were administered 5g vitamin B12 (Sigma, V2876) dissolved in water by oral gavage on day 6 after the start of doxycycline treatment, and blood samples were taken by submandibular collection just before and 24h after the bolus. OSKM transgenic mice are the i4F-B strain (derived on a C57/BL6J background and bred in house) described in ref. 3 and are available upon request. WT mice were i4F-B WT littermate controls where specified, or WT C57/BL6J (Charles River France).

Mice were treated with 2.5% (wt/vol) DSS, colitis grade (36,00050,000; MP Biomedicals, MFCD00081551) in drinking water for 5 consecutive days. On day 5, the DSS was removed and drinking water was supplemented with doxycycline hyclate BioChemica (1mg ml1; PanReac, A2951; with 7.5% sucrose) for 48h, after which regular water was returned. Mice in the B12 experimental group also received supplementation of vitamin B12 (1.25mg l1; Sigma, V2876) from the point of DSS removal (that is, day 5) until experimental endpoint. The MAT2Ai group received FIDAS-5 (MedChemExpres, HY-136144) and were dosed with 20mg per kg body weight per day dissolved in PEG400 by oral gavage as previously described79.

On day 9 (relative to the start of DSS administration), food was withdrawn from mice for 4h, after which mice were gavaged with FITCdextran (MW 4,000; Sigma-Aldrich, FD4) at a dose of 44mg per 100g of body weight dissolved in PBS. Food restriction was maintained for 3 additional hours, at which point blood was sampled by submandibular vein bleeding. Whole blood was diluted at a ratio of 1:4 in PBS, and 100l of blood/PBS mixture from each mouse was loaded into a 96-well plate. Fluorescence intensity was measured on a BioTek Synergy H1 Microplate Reader (excitation 490nm; emission 520nm).

Fresh stool samples were collected directly from mice and snap frozen. gDNA was isolated using a QIAamp DNA Stool Mini Kit (QIAGEN, 51504) according to the manufacturers protocols.

Libraries were prepared using the NEBNext Ultra DNA Library Prep Kit for Illumina (E7370L) according to the manufacturers protocol. Briefly, 50ng of DNA was fragmented to approximately 400bp and subjected to end repair plus A-tailing, ligation of NEB adaptor and Uracil excision by USER enzyme. Then, adaptor-ligated DNA was amplified for eight cycles by PCR using indexed primers. All purification steps were performed using AMPure XP Beads (A63881). Final libraries were analysed using an Agilent DNA 1000 chip to estimate the quantity and check size distribution, and were then quantified by qPCR using the KAPA Library Quantification Kit (KK4835, KapaBiosystems) before amplification with Illuminas cBot. Libraries were sequenced (2125bp) on Illuminas HiSeq 2500.

Reads were aligned to the mm10 genome using STAR 2.7.0a with default parameters80. DNA contaminated reads were filtered out from the analysis. The first and final ten bases of the non-contaminated reads were trimmed using DADA2 1.10.1 (ref. 81). Taxonomic assignments were carried out through Kaiju 1.7.0 (ref. 82) using the microbial subset of the NCBI BLAST non-redundant protein database (nr). Resulting sequencing counts were aggregated at genus level. Reads that could not be assigned to any specific genus were classified to the nearest known taxonomic rank (marked by the term _un). The gut microbial compositional plot displays the relative abundances (percentage) at genus level. Only the 17 most abundant taxa are shown, while the rest were moved to the others category. For all genera, the treatment effect (finish versus start) was compared between OSKM and control (WT) mice. This was accounted in a model with an interaction term (drug:treatment) using DESeq2 with default options83. The paired nature of the experimental design was taken into account in the model as an adjusting factor.

Decontamination from host and trimming was done following the same routines as for the taxonomic analysis. Cleaned sequences for all samples were assembled into contigs using megahit 1.2.4 (ref. 84), and prodigal 2.6.3 (ref. 85) was then used to predict the open reading frames inside the obtained contigs. Protein mapping and KEGG and COG annotations were obtained using the EggNOG mapper 2.0.0 (ref. 86). The abundance of the annotated genes was finally measured by counting aligned reads to them via Bowtie2, version 2.2.2, under default parameters87. Resulting counts data were aggregated at protein level. The treatment effect (finish versus start) was compared between OSKM and control (WT) mice. This was accounted in a model with an interaction term (drug:treatment) using DESeq2 with default options83. The paired nature of the experimental design was considered in the model as an adjusting factor. The top 500 protein hits from the fitted model (nondirectional set) as well as the top 200 positive hits and the top 200 negative hits (directional sets), in all cases ordered by statistical significance, were used to explore enrichment of functional annotations. In this regard, GO terms for bacteria and archaea were considered using the AmiGO 2 GO annotations database88, removing from the analysis gene sets with few genes (less than 8) and too many genes (more than 499). Statistically enriched GO terms were identified using the standard hypergeometric test. Significance was defined by the adjusted P value using the Benjamini and Hochberg multiple-testing correction. To take into consideration the compositional nature of the data, all DESeq2-based results were complemented with graphical representations of abundance log-ratio (between finish and start matched samples) rankings. This provides a scale invariant way (with regard to the total microbial load) to present the data89.

Blood was collected via submandibular vein bleed (D0, D2, D4) or intracardiac puncture following deep carbon dioxide anaesthetisation (D7) at approximately 12:0014:00h (46h into the light cycle) of each day. Whole blood was spun down for 10min at 3,381g at 4C and supernatant (serum) was separated and stored at 80C.

Acetonitrile (Sigma-Aldrich), isopropanol (Sigma-Aldrich), methanol (Sigma-Aldrich), chloroform (Sigma-Aldrich), acetic acid (Sigma-Aldrich), formic acid (Sigma-Aldrich), methoxyamine hydrochloride (Sigma-Aldrich), MSTFA (N-methyl-N-(trimethylsilyl) trifluoroacetamide; Sigma-Aldrich), pyridine (Sigma-Aldrich), 3-nitrophenylhydrazine (Sigma-Aldrich), N-(3-dimethylaminopropyl)-N-ethylcarbodiimide hydrochloride (EDC; Sigma-Aldrich) and sulfosalicylic acid (Sigma-Aldrich) as previously described90.

A volume of 25l of serum were mixed with 250l a cold solvent mixture with ISTD (methanol/water/chloroform, 9:1:1, 20C), into 1.5ml microtube, vortexed and centrifugated (10min at 15,000g, 4C). The upper phase of supernatant was split into three parts: 50l was used for gas chromatography coupled to mass spectrometry (GCMS) experiments in the injection vial, 30l was used for the short-chain fatty acid ultra-high performance liquid chromatography (UHPLC)MS method, and 50l was used for other UHPLCMS experiments.

The GCMS/MS method was performed on a 7890B gas chromatography system (Agilent Technologies) coupled to a triple-quadrupole 7000C (Agilent Technologies) equipped with a high-sensitivity electronic impact source (EI) operating in positive mode.

Targeted analysis was performed on an RRLC 1260 system (Agilent Technologies) coupled to a triple-quadrupole 6410 (Agilent Technologies) equipped with an electrospray source operating in positive mode. Gas temperature was set to 325C with a gas flow of 12l min1. Capillary voltage was set to 4.5kV.

Targeted analysis was performed on an RRLC 1260 system (Agilent Technologies) coupled to a triple-quadrupole 6410 (Agilent Technologies) equipped with an electrospray source operating in positive mode. The gas temperature was set to 350C with a gas flow of 12l min1. The capillary voltage was set to 3.5kV.

Targeted analysis was performed on an RRLC 1260 system (Agilent Technologies) coupled to a 6500+QTRAP (Sciex) equipped with an electrospray ion source.

The profiling experiment was performed with a Dionex Ultimate 3000 UHPLC system (Thermo Scientific) coupled to a Q-Exactive (Thermo Scientific) equipped with an electrospray source operating in both positive and negative mode and full scan mode from 100 to 1,200m/z. The Q-Exactive parameters were: sheath gas flow rate, 55 arbitrary units (a.u.); auxiliary gas flow rate, 15 a.u.; spray voltage, 3.3kV; capillary temperature, 300C; S-Lens RF level, 55V. The mass spectrometer was calibrated with sodium acetate solution dedicated to low mass calibration.

The peak areas (corrected to quality control) corresponding to each annotated metabolite identified in the serum of reprogrammable mice (n=6 per group) at day 5 and day 7 after doxycycline treatment were converted to log2 values. Data were represented as log2 fold change (log2 FC) values to each mouse at day 0 (before doxycycline administration). Metabolic pathway impact was calculated by Global ANOVA pathway enrichment and Out-degree Centrality Topology analysis through the MetaboAnalyst 4.0 software91, using KEGG library (2019) as a reference. The colour gradient from white to red indicates the P value, where red is most significant. Bubble size indicates the relative contribution of the detected metabolites in their respective KEGG pathway. Pathway impact scores the centrality of the detected metabolites in the pathway.

A total of 30l of mouse plasma was acidified with 3l solution of 15% phosphoric acid (vol/vol). Afterwards, 42l of methyl tert-butyl ether was added and vigorously mixed using a vortex. After 20min of reequilibration, samples were centrifuged for 10min at 21,130g at 4C. Next, 90l of acetonitrile were added to 10l of the aqueous phase to facilitate protein precipitation. After another cycle of centrifugation, the supernatant was transferred into a vial before LCMS analysis.

The extracts were analysed by a UHPLC system coupled to a 6490 triple-quadrupole mass spectrometer (QqQ, Agilent Technologies) with electrospray ion source (LCESIQqQ) working in positive mode. The injection volume was 3l. An ACQUITY UPLC BEH HILIC column (1.7m, 2.1150mm, Waters) and a gradient mobile phase consisting of water with 50mM ammonium acetate (phase A) and acetonitrile (phase B) were used for chromatographic separation. The gradient was as follows: isocratic for 2min at 98% B, from 2 to 9min decreased to 50% B, for 30s raised to 98%, and finally column equilibrated at 98% B until 13min. The flow rate was 0.4ml min1. The mass spectrometer parameters were as follows: drying and sheath gas temperatures, 270C and 400C, respectively; source and sheath gas flow rates, 15 and 11l min1, respectively; nebulizer flow, 35psi; capillary voltage, 3,000V; nozzle voltage, 1,000V; and iFunnel HRF and LRF, 130 and 100V, respectively. The QqQ worked in MRM mode using defined transitions. The transitions for doxycycline and the collision energy (CE(V)) were 445428(17), 44598(60).

In total, 25l of serum was mixed with 25l of TCEP and 70l of 1% formic acid in methanol. Samples were vortexed and left at 20C for 1h, centrifuged for 10min at 21,130g and 4C and transferred to glass vials for their analysis by LCMS.

LCMS was performed with a Thermo Scientific Vanquish Horizon UHPLC system interfaced with a Thermo Scientific Orbitrap ID-X Tribrid Mass Spectrometer.

Metabolites were separated by HILIC chromatography with an InfinityLab Poroshell 120 HILIC-Z 2.7m, 2.1mm100mm column (Agilent Technologies). The mobile phase A was 50mM ammonium acetate in water, and mobile phase B was acetonitrile. Separation was conducted under the following gradient: 02min, isocratic 90% B; 26min raised to 50% B; 67min, isocratic 50% B; 77.2min, increased to 90% B; 7.210.5min, reequilibration column 90% B. The flow rate was 0.4ml min1. The injection volume was 5l.

Samples were analysed in positive mode in targeted SIM mode and the following setting: isolation window (m/z), 4; spray voltage, 3,500V; sheath gas, 50 a.u.; auxiliary gas, 10 a.u.; ion transfer tube temperature, 300C; vaporizer temperature, 300C; Orbitrap resolution, 120,000; RF lens, 60%; AGC target, 2e5; maximum injection time, 200ms.

SAM (m/z 399.145) was monitored from 57min; Met (m/z 150.0583) from 3.25.2min; SAH (m/z 385.1289) from 46min; Hcy (m/z 136.0428) from 3.45.5min, as previously optimized using pure standards.

Approximately, 20mg of dry and pulverized stool samples were mixed with with 75l of TCEP and 210l of 1% formic acid in methanol. Samples were vortexed and subjected to three freezethaw cycles using liquid nitrogen. Subsequently, samples were left in ice for 1h, centrifuged for 10min at 21,130g and 4C and transferred to glass vials for their analysis by LCMS.

LCMS was performed with a Thermo Scientific Vanquish Horizon UHPLC system interfaced with a Thermo Scientific Orbitrap ID-X Tribrid Mass Spectrometer.

Metabolites were separated by HILIC chromatography with an InfinityLab Poroshell 120 HILIC-Z 2.7m, 2.1mm100mm column (Agilent Technologies). The mobile phase A was 50mM ammonium acetate in water, and mobile phase B was acetonitrile. Separation was conducted under the following gradient: 02min, isocratic 90% B; 26min raised to 50% B; 67min, isocratic 50% B; 77.2min, increased to 90% B; 7.210.5min, reequilibration column 90% B. The flow was 0.4ml min1. The injection volume was 5l.

Samples were analysed in positive mode in targeted SIM mode and the following setting: isolation window (m/z), 4; spray voltage, 3,500V; sheath gas, 50 a.u.; auxiliary gas, 10 a.u.; ion transfer tube temperature, 300C; vaporizer temperature, 300C; Orbitrap resolution, 120,000; RF lens, 60%; AGC target, 2e5; maximum injection time, 200ms. Cyanocobalamin was monitored from (m/z 1355.5747 and m/z 678.291) from 55.5min, as previously optimized using a pure standard.

Mouse serum was diluted at a 1:20 ratio in PBS and holotranscobalamin (holoTC) was measured using an ADVIA Centuar Immunoassay System (SIEMENS) with ADVIA Centuar Vitamin B12 Test Packs (07847260) according to the manufacturers instructions.

Cell pellets were mixed with 50l of TCEP and 140l of 1% formic acid in methanol (containing 150g l1 of Tryptophan-d5 as internal standard). Samples were vortexed and subjected to three freezethaw cycles using liquid nitrogen. Subsequently, samples were left at 20C for 1h, centrifuged for 10min at 21,130g and 4C and transferred to glass vials for their analysis by LCMS/MS.

Samples were analysed with an UHPLC 1290 Infinity II Series coupled to a QqQ/MS 6490 Series from Agilent Technologies (Agilent Technologies). The source parameters applied operating in positive electrospray ionization (ESI) were gas temperature: 270C; gas flow: 15l min1; nebulizer: 35psi; sheath gas heater, 400 a.u.; sheath gas flow, 11 a.u.; capillary, 3,000V; nozzle voltage: 1,000V.

The chromatographic separation was performed with an InfinityLab Poroshell 120 HILIC-Z 2.7m, 2.1mm100mm column (Agilent Technologies), starting with 90% B for 2min, 50% B from minute 2 to 6, and 90% B from minute 7 to 7.2. Mobile phase A was 50mM ammonium acetate in water, and mobile phase B was acetonitrile. The column temperature was set at 25C and the injection volume was 2l.

MRM transitions for SAM (RT: 6.1min) were 399298 (4V), 399250 (12V), 39997 (32V) and 399136 (24V) for M+0, and 400299 (4V), 400251 (12V), 40097 (32V), 400137 (24V), 400250 (12V) and 400136 (24V) for M+1.

Samples were fixed overnight at 4C with neutral buffered formalin (HT501128-4L, Sigma-Aldrich). Paraffin-embedded tissue sections (23m in thickness) were air-dried and further dried at 60C overnight for immunohistochemical staining.

Sections were stained with haematoxylin and eosin (H&E) for histological evaluation by a board-certified pathologist who was blinded to the experimental groups. Additionally, periodic acidSchiff staining (AR16592-2, Artisan, Dako, Agilent) was used to visualize mucus-producing cells on 34-m sections of colon that were counterstained with haematoxylin.

In the reprogramming model, the findings were evaluated by focusing mainly on the appearance of hyperplastic and dysplastic changes of the epithelial cells of the digestive mucosa and pancreatic acini. Inflammation and loss of the intestinal goblet cells were also reported. To document the severity and extension, a semi-quantitative grading system was used based on previously used histological criteria:

Gastric and colon mucosa inflammatory cell infiltrate and multifocal areas of crypt (large intestine) or glandular (stomach) epithelial cell dysplasia were scored from 0 to 5, where 0 indicates absence of lesion and 5 indicates very intense lesions.

Intestinal crypt hyperplasia: 1, slight; 2, twofold to threefold increase of the crypt length; 3, >threefold increase of the crypt length.

Goblet cell loss of the mucosa of the large intestine: 1, <10% loss; 2, 1050% loss; 3, >50% loss.

Histological total score was presented as a sum of all parameters scored for a given tissue.

In the colitis model, the following parameters were semi-quantitatively evaluated as previously described92 as follows:

Inflammation of the colon mucosa: 0, none; 1, slight, 2, moderate; 3, severe.

Depth of the injury: 0, none; 1, mucosa; 2, mucosa and submucosa; 3, transmural.

Crypt damage: 0, none; 1, basal and 1/3 damaged; 2, basal and 2/3 damaged; 3, only the surface epithelium intact; 4, entire crypt and epithelium lost.

Tissue involvement: 0, none; 1, 025%; 2, 2650%; 3, 5175%; 4, 76100%.

The score of each parameter was multiplied by the factor of tissue involvement and summed to obtain the total histological score.

Immunohistochemistry was performed using a Ventana discovery XT for NANOG and Sca1/Ly6A/E, the Leica BOND RX Research Advanced Staining System for H3K36me3, keratin 14 and vitamin B12, and manually for Ki67. Antigen retrieval for NANOG was performed with Cell Conditioning 1 buffer (950-124, Roche) and for Sca1/Ly6A/E with Protease 1 (5266688001, Roche) for 8min followed with the OmniMap anti-Rat HRP (760-4457, Roche) or OmniMap anti-Rb HRP (760-4311, Roche). Blocking was done with casein (760-219, Roche). Antigenantibody complexes were revealed with ChromoMap DAB Kit (760-159, Roche). For H3K36me3 and keratin 14, antigen retrieval was performed with BOND Epitope Retrieval 1 (AR9961, Leica) and for vit B12 with BOND Epitope Retrieval Solution 2 (Leica Biosystems, AR9640) for 20min, whereas for Ki67, sections were dewaxed as part of the antigen retrieval process using the low pH EnVision FLEX Target Retrieval Solutions (Dako) for 20min at 97C using a PT Link (Dako-Agilent). Blocking was performed with Peroxidase-Blocking Solution at room temperature (RT; S2023, Dako-Agilent) and 5% goat normal serum (16210064, Life technology) mixed with 2.5% BSA diluted in wash buffer for 10 and 60min at RT. Vitamin B12 also was blocked with Vector M.O.M. Blocking Reagent (MK-2213, Vector) following the manufacturers procedures for 60min. Primary antibodies were incubated for 30, 60 or 120min. The secondary antibody used was the BrightVision poly HRP-Anti-Rabbit IgG, incubated for 45min (DPVR-110HRP, ImmunoLogic) or the polyclonal goat Anti-Mouse at a dilution of 1:100 for 30min (Dako-Agilent, P0447). Antigenantibody complexes were revealed with 3-3-diaminobenzidine (K346811, Agilent or RE7230-CE, Leica). Sections were counterstained with haematoxylin (CS700, Dako-Agilent or RE7107-CE, Leica) and mounted with Mounting Medium, Toluene-Free (CS705, Dako-Agilent) using a Dako CoverStainer. Specificity of staining was confirmed by staining with a rat IgG (6-001-F, R&D Systems, Bio-Techne), a Rabbit IgG (ab27478, Abcam) or a mouse IgG1, kappa (Abcam, ab18443) isotype controls. See Supplementary Table 5 for primary antibody details.

Ready-to-use reagents from RNAscope 2.5 LS Reagent Kit-RED (322150, RNAScope, ACD Bio-Techne) were loaded onto the Leica Biosystems BOND RX Research Advanced Staining System according to the user manual (322100-USM). FFPE tissue sections were baked and deparaffinized on the instrument, followed by epitope retrieval (using Leica Epitope Retrieval Buffer 2 at 95C for 15min) and protease treatment (15min at 40C). Probe hybridization, signal amplification, colorimetric detection and counterstaining were subsequently performed following the manufacturers recommendations.

Hybridization was performed with the RNAscope LS 2.5 Probe - Mm-Lgr5 - Mus musculus leucine rich repeat containing G-protein-coupled receptor 5 (312178, RNAScope, ACD Bio-Techne). Control probe used was the RNAscope 2.5 LS Probe - Mm-UBC - Mus musculus ubiquitin C (Ubc), as a housekeeping gene (310778, RNAScope - ACD Bio-Techne). The bacterial probe RNAscope 2.5 LS Negative Control Probe_dapB was used as a negative control (312038, RNAScope - ACD Bio-Techne).

Brightfield images were acquired with a NanoZoomer-2.0 HT C9600 digital scanner (Hamamatsu) equipped with a 20 objective. All images were visualized with a gamma correction set at 1.8 in the image control panel of the NDP.view 2 U12388-01 software (Hamamatsu, Photonics).

Brightfield images of immunohistochemistry were quantified using QuPath software93 with standard detection methods. Where the percentage of tissue staining is calculated, pixels were classified as positive and negative using the Thresholder function. Where the percentage of cells is quantified, the Positive Cell Detection function was used.

MEFs were cultured in standard DMEM medium with 10% FBS (Gibco, LifeTechnologies, 10270106) with antibiotics (100U ml1 penicillinstreptomycin; Life Technologies, 11528876). Reprogramming of the doxycycline-inducible 4-Factor (i4F) MEFs with inducible expression of the four Yamanaka factors Oct4, Sox2, Klf4 and cMyc (OSKM) was performed as previously described3. Briefly, i4F MEFs were seeded at a density of 3105 cells per well in six-well tissue culture plates coated with gelatin and treated with doxycycline (PanReac, A2951) 1mg ml1 continuously to induce expression of the OSKM transcription factors in the presence of complete KSR media (15% (vol/vol) Knockout Serum Replacement (KSR, Invitrogen, 10828028) in DMEM with GlutaMax (Life Technologies, 31966047) basal media, with 1,000U ml1 LIF (Merck, 31966047), non-essential amino acids (Life Technologies, 11140035) and 100M beta-mercaptoethanol (Life Technologies, 31350010) plus antibiotics (penicillinstreptomycin, Gibco, 11528876)), which was replaced every 4872h. After 10d, iPS cell colonies were scored by alkaline phosphatase staining according to the manufacturers protocol (AP blue membrane substrate detection kit, Sigma, AB0300). Vitamin B12 (Sigma, V2876; 2M final), MAT2Ai PF-9366 (MedChemExpress, HY-107778; 2M final), SAM (S-(5-adenosyl)-l-methionine iodide, Merck, A4377; 100M final) and NSC636819 (Sigma-Aldrich, 5.31996; 10M final) were added continuously to the culture media and replaced every 4872h.

Reprogramming of WT MEFs was performed as previously described94. Briefly, HEK-293T (American Type Culture Collection, ATCC-CRL-3216) cells were cultured in DMEM supplemented with 10% FBS and antibiotics (penicillinstreptomycin, Gibco, 11528876). Around 5106 cells per 100-mm-diameter dish were transfected with the ecotropic packaging plasmid pCL-Eco (4g) together with one of the following retroviral constructs (4g): pMXs-Klf4, pMXs-Sox2, pMXs-Oct4 or pMXs-cMyc (obtained from Addgene) using Fugene-6 transfection reagent (Roche) according to the manufacturers protocol. The following day, media were changed and recipient WT MEFs to be reprogrammed were seeded (1.5105 cells per well of a six-well plate). Retroviral supernatants (10ml per plate/factor) were collected serially during the subsequent 48h, at 12-h intervals, each time adding fresh media to the 293T cells cells (10ml). After each collection, supernatant was filtered through a 0.45-m filter, and each well of MEFs received 0.5ml of each of the corresponding retroviral supernatants (amounting to 2ml total). Vitamin B12 supplementation (Sigma, V2876; 2M final concertation) began on the same day as viral transduction. This procedure was repeated every 12h for 2d (a total of four additions). After infection was completed, media were replaced by complete KSR media (see above). Cell pellets were harvested on day 5 (relative to the first infection) and histone extracts were processed for immunoblot as described below. On day 14 (relative to the first infection), iPS cell colonies were scored by alkaline phosphatase staining according to the manufacturers protocol (AP blue membrane substrate detection kit; Sigma, AB0300).

Doxycycline-inducible i4F MEFs were cultured as described in Cell culture above, with 1mg ml1 doxycycline, with without continuous vitamin B12 supplementation. At 72h after the addition of doxycycline, cells were transferred to complete KSR media containing a final concentration of 0.5mM l-Serine-13C3 (Sigma-Aldrich, 604887). This is the same concentration of unlabelled l-serine normally found in the complete KSR media, and was generated by ordering custom, serine-free DMEM (Life Technologies, ME22803L1) and custom, serine-free non-essential amino acid mixture (Life Technologies, ME22804L1). Six hours after the addition of labelled media, a subset of wells was harvested by scraping in PBS and centrifugation (300g for 5min); supernatant was removed and pellets were snap frozen. At 72h after the addition of the labelled media (that is, 6days into reprogramming), cells still in culture were transferred back to unlabelled complete KSR media, which was changed every 4872h. iPS cell colonies were analysed by alkaline phosphatase staining according to the manufacturers protocol (AP blue membrane substrate detection kit; Sigma, AB0300) on day 10. Doxycycline and vitamin B12 supplementation were continuous throughout the entire reprogramming protocol, and replenished with every media change (that is, every 4872h).

i4F MEFs were cultured in the presence doxycycline 2M of vitamin B12 over 3 or 10days (culture conditions as described above) and histone extracts were prepared using EpiQuik Total Histone Extraction Kit (EpiGentek, OP-0006-100) according to the manufacturers instructions. Around 200ng of total histone extract was used per well in the EpiQuik Histone H3 Modification Multiplex Assay Kit (Colorimetric; EpiGentek, P-3100) according to the manufacturers instructions.

Histone extracts were prepared using an EpiQuik Total Histone Extraction Kit (EpiGentek, OP-0006-100) according to the manufacturers instructions and quantified using DC Protein Assay Kit (Bio-Rad, 5000111). Whole-cell extracts were prepared in RIPA buffer (10mM Tris-HCl, pH 8.0; 1mM EDTA; 0.5mM EGTA; 1% Triton X-100; 0.1% sodium deoxycholate; 0.1% SDS; 140mM NaCl). A total of 10g of lysate was loaded per lane and hybridized using antibodies against H3K36me3, MS, vinculin, total histone H3 and LI-COR fluorescent secondary reagents (IRDye 800 CW anti-mouse, 926-32210; IRDye 680 CW anti-mouse, 926-68070; IRDye 800 CW anti-rabbit, 926-32211; IRDye 680 CW anti-mouse, 926-68071) all at a dilution of 1:10,000 according to manufacturers instructions. Immunoblots were visualized on an Odyssey FC Imaging System (LI-COR Biosciences). See Supplementary Table 5 for primary antibody details.

GSEAPreranked was used to perform a GSEA of annotations from MsigDB M13537, with standard GSEA and leading edge analysis settings. We used the RNA-seq gene list ranked by log2 fold change, selecting gene set as the permutation method with 1,000 permutations for KolmogorovSmirnoff correction for multiple testing95.

Genes belonging to the leading edge of the GSEA using the Met derivation signature (MsigDB, M13537) in the pancreas of reprogramming mice were selected. These genes were then compared to genes belonging to the leading edge of the same gene signature from i4F MEFs treated with doxycycline in vitro for 72h, as compared to OSKM MEFs treated with vitamin B12 (that is, genes in MsigDB M13537 whose upregulation was relieved by B12 supplementation in vitro). We selected 11 of these genes for which we had qPCR primers available.

Total RNA was extracted from MEFs with TRIzol (Invitrogen) according to the manufacturers instructions. Up to 5g of total RNA was reverse transcribed into cDNA using the iScript Advanced cDNA Synthesis Kit (Bio-Rad, 172-5038; pancreas) or iScript cDNA Synthesis Kit (Bio-Rad, 1708890; all other organs) for RTqPCR. Real-time qPCR was performed using GoTaq qPCR Master Mix (Promega, A6002) in a QuantStudio 6 Flex thermocycler (Applied Biosystem) or 7900HT Fast Real-Time PCR System (Thermo Fisher). See Supplementary Table 6 for primer sequences.

i4F MEFs were cultured in the presence or absence of doxycycline 2M of vitamin B12 (Merck, V2876) over 3days in six-well plates (culture conditions as described above). Cells were fixed with 1% (vol/vol) PFA (Fisher Scientific, 50980487) for 2min and then quenched with 750mM Tris (PanReac AppliChem, A2264) for 5min. Cells were washed twice with PBS, scraped, and spun down at 1,200g for 5min. Pellets were lysed with 100l (per well) lysis buffer (50mM HEPES-KOH pH 7.5, 140mM HCl, 1mM EDTA pH 8, 1% Triton X-100, 0.1% sodium deoxycholate, 0.1% SDS, protease inhibitor cocktail; Sigma, 4693159001) on ice for 10min, then sonicated using a Diagenode BioRuptor Pico (Diagenode, B01060010) for ten cycles (30s on, 30s off) at 4C. Lysates were clarified for 10min at 8,000g, 1% input samples were reserved, and supernatant was used for immunoprecipitation with Diagenode Protein A-coated Magnetic beads ChIPseq grade (Diagenode, C03010020-660) and H3K3me3 monoclonal antibody (Cell Signaling Technologies, 4909) with 0.1% BSA (Sigma, 10735094001). The following day, cells were washed once with each buffer: low salt (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM Tris-HCl pH 8.0, 150mM NaCl), high salt (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM Tris-HCl pH 8.0, 5,000mM NaCl), LiCl (0.25M LiCl, 1% NP-40, 1% sodium deoxycholate, 1mM EDTA, 10mM Tris-HCl pH 8.0) and eluted in 1% SDS, 100mM NaHCO3 buffer. Cross-links were reversed with RNase A (Thermo Fisher, EN0531), proteinase K (Merck, 3115879001) and sodium chloride (Sigma, 71376), and chromatin fragments were purified using QIAquick PCR purification kit (Qiagen, 28104).

i4F MEFs were cultured in the presence or absence of doxycycline and the indicated compounds over 3days in six-well plates (culture conditions as described above). After 72h, RNA was extracted using an RNeasy Kit (Qiagen, QIA74106) according to the manufacturers instructions.

The concentration of the DNA samples (inputs and immunoprecipitations) was quantified with a Qubit dsDNA HS kit, and fragment size distribution was assessed with the Bioanalyzer 2100 DNA HS assay (Agilent). Libraries for ChIPseq were prepared at the IRB Barcelona Functional Genomics Core Facility. Briefly, single-indexed DNA libraries were generated from 0.51.5ng of DNA samples using the NEBNext Ultra II DNA Library Prep kit for Illumina (New England Biolabs). Eleven cycles of PCR amplification were applied to all libraries.

The final libraries were quantified using the Qubit dsDNA HS assay (Invitrogen) and quality controlled with the Bioanalyzer 2100 DNA HS assay (Agilent). An equimolar pool was prepared with the 24 libraries and sequenced on a NextSeq 550 (Illumina). 78.9Gb of SE75 reads were produced from two high-output runs. A minimum of 23.97 million reads were obtained for all samples.

The concentration of total RNA extractions was quantified with the Nanodrop One (Thermo Fisher), and RNA integrity was assessed with the Bioanalyzer 2100 RNA Nano assay (Agilent). Libraries for RNA-seq were prepared at the IRB Barcelona Functional Genomics Core Facility. Briefly, mRNA was isolated from 1.5g of total RNA using the kit NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs). The isolated mRNA was used to generate dual-indexed cDNA libraries using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (New England Biolabs). Ten cycles of PCR amplification were applied to all libraries.

The final libraries were quantified using the Qubit dsDNA HS assay (Invitrogen) and quality controlled with the Bioanalyzer 2100 DNA HS assay (Agilent). An equimolar pool was prepared with the 12 libraries and submitted for sequencing at the Centre Nacional dAnlisi Genmica (CRG-CNAG). A final quality control by qPCR was performed by the sequencing provider before paired-end 50-nucleotide sequencing on a NovaSeq 6000 S2 (Illumina). Around 77.7Gb of PE50 reads were produced from three NovaSeq 6000 flow cells. A minimum of 55.7 million reads were obtained for all samples (Extended Data Fig. 7).

Total RNA extractions were quantified with a Nanodrop One (Thermo Fisher), and RNA integrity was assessed with the Bioanalyzer 2100 RNA Nano assay (Agilent). Libraries for RNA-seq were prepared at the IRB Barcelona Functional Genomics Core Facility. Briefly, mRNA was isolated from 1.2g of total RNA and used to generate dual-indexed cDNA libraries with the Illumina Stranded mRNA ligation kit (Illumina) and UD Indexes Set A (Illumina). Ten cycles of PCR amplification were applied to all libraries.

Sequencing-ready libraries were quantified using the Qubit dsDNA HS assay (Invitrogen) and quality controlled with the Tapestation HS D5000 assay (Agilent). An equimolar pool was prepared with the 15 libraries for SE75 sequencing on a NextSeq 550 (Illumina). Sequencing output was above 539 million 75-nucleotide single-end reads and a minimum of 28 million reads was obtained for all samples (Extended Data Fig. 7).

All analyses were performed in the R programming language (version 4.0.5)96 unless otherwise stated. Stranded paired-end reads were aligned to the Mus musculus reference genome version mm10 using STAR80 with default parameters. STAR indexes were built using the ENSEMBL annotation version GRC138.97. SAM files were converted to BAM and sorted using sambamba (version 0.6.7)97. Gene counts were obtained with the featureCounts function from the Rsubread package98 with the gtf file corresponding to ENSEMBL version GRC138.97 and parameters set to: isPairedEnd=TRUE and strandSpecific=2. Technical replicates were collapsed by adding the corresponding columns in the count matrix.

We obtained a reprogramming gene signature from published data48 and selected genes with false discovery rate (FDR) lower than 0.05 and fold change between MEF and d3-EFF larger than 2. The reprogramming score was defined as the average of all genes in the signature after scaling the rlog transformed matrix.

Exon counts were generated using the featureCounts function with parameters: isPairedEnd=TRUE, strandSpecific=2, GTF.featureType=exon, GTF.attrType=transcript_id, GTF.attrType.extra=gene_id, allowMultiOverlap=TRUE and useMetaFeatures=FALSE and the same GTF as for gene counts. Technical replicates were collapsed by adding the corresponding counts. For each gene, the longest annotated transcript was selected. Genes with less than four exons of RPKMs lower than exp(2) were discarded from the analysis. Intermediate exons were defined as those from the fourth to the penultimate. A total of 9,365 genes were used to compute the ratio between the intermediate and first exons. Fold changes between untreated and B12-treated samples were computed as the ratio between the exon ratios.

Genes were separated by their expression after transcript length and library size normalization (RPKM). For each sample, we computed the median ratios for genes in each decile.

Data were accessed from GSE131032. Reads were processed and ratios computed as previously described. log2 ratios for all transcripts were summarized through the median by sample. Comparisons between days were performed fitting a linear model to the medians using cage as a covariable. The function glht from the multcomp R package was used to find coefficients and P values.

To select genes most affected by the B12 treatment after reprogramming, we compared ratios between the doxy and MEF conditions and between the doxy and doxy+B12 conditions. Genes that increased the ratios in the first comparison (upper 25th percentile) and decreased the ratio in the second comparison (bottom 25%) were selected for functional enrichment analysis. A hypergeometric test was performed to find significant overlap between the defined gene set and the Biological Processes GO collection99.

Reads were aligned to the mm10 reference genome with bowtie100 version 0.12.9 with parameters --n 2 and --m 1 to keep reads with multiple alignments in one position. SAM files were converted to BAM and sorted using sambamba version 0.6.7.

For each sample, aligned reads were imported into R using the function scanBam from the Rsamtools package101. Whole-genome coverage was computed using the coverage function from the IRanges package102 and binned into 50-bp windows. Gene annotations were imported from Ensembl version GRCm38. The average coverage over gene bodies was computed using the normalizeToMatrix function from the EnrichedHeatmap package103 with parameters extend=1,000, mean_mode=w0 and w=50. Genes were filtered to coincide with those used in the exon ratio calculation from the RNA-seq data. Rows in the heat map were split by the average RNA-seq RPKM values in all samples.

BAM files were transformed to TDF files using the count function from IGVtools (version 2.12.2)104 with parameters --z 7, --w 25 and --e 250. Visualization of TDF files was generated using IGV (version 2.9.4)105.

Data were accessed from GSE109142. Reads were processed and ratios computed as previously described except using the ENSEMBL GRCm38.101 human gene annotation and the hg38 genome assembly version. The log2 ratios for all transcripts were summarized through the median by sample. Comparison between diagnosis status was performed fitting a linear model to the medians with sex and the expression quantiles as covariables. The model was fitted using the lm R function and coefficients and P values with the coeff function.

Unless otherwise specified, data are presented as the means.d. Statistical analysis was performed by Students t-test or one-way analysis of variance (ANOVA) as indicated, using GraphPad Prism v9.0.0, and specific statistical tests as indicated for each experiment for bioinformatic analyses. P values of less than 0.05 were considered as statistically significant. No statistical methods were used to predetermine sample size in the mouse studies, but our sample sizes are similar to those reported in previous publications3,9,16,17,19. Animals and data points were not excluded from analysis with the exception of the MEFs that failed to reprogram in the ChIP experiment, which is clearly detailed in the text. Mice were allocated at random to treatment groups, with attempts to balance initial body weight and sex as possible. The investigators were blinded during histological assessment of the mice; other data collection and analysis was not performed blind to the conditions of the experiments. Data distribution was assumed to be normal, but this was not formally tested. Figures were prepared using Illustrator CC 2019 (Adobe).

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Vitamin B12 is a limiting factor for induced cellular plasticity and ... - Nature.com

Using patients’ own cells, researchers examine connection between … – ND Newswire

By Induced Pluripotent Stem Cells

Although considered a rare disorder, fragile X syndrome is the most common genetic cause of intellectual disability in the world. Fragile X patients can have a range of mild to severe intellectual disability with the potential for other conditions such as autism, delayed motor development, hyperactivity, behavioral problems and seizures.

Although its well-known that fragile X is caused by the FMR1 gene, its less understood how the disorder physically affects brain development and function.

Christopher Patzke, the John M. and Mary Jo Boler Assistant Professor of Biological Sciences at the University of Notre Dame, is collaborating with fragile X patients and families to study the disorder.

My lab is hoping to find an explanation of the disease symptoms in humans, looking at the disorder at the cellular and molecular level, Patzke said.

By partnering with fragile X expert Dr. Elizabeth M. Berry-Kravis, professor of pediatrics at Rush University and a 1979 graduate of Notre Dame, the Patzke Lab has been able to collect patient tissue samples to create induced pluripotent stem cells. Because these stem cells mimic embryonic stem cells, the lab can then transform those cells into virtually any human cell the researchers want to study.

For this research, Patzke and his team are transforming pluripotent stem cells into brain cells that mimic neurons of someone with fragile X syndrome, creating a human model to study the genetic mutations effect on the brain.

Most of the genes associated with intellectual disability encode for proteins that do something with synapses, Patzke said. So making a cell culture of these fragile X neurons allows us, in a way, to zoom in to single cells and synapses, or the connections between neurons, and learn how these neurons communicate with one another.

The researchers then compare a patients cell culture sample to a corrected-cell culture sample, made via gene editing, to analyze the differences between how the synapses function with and without the FMR1 gene mutation.

Although research into fragile X syndrome is not uncommon, many researchers use animal models to study the FMR1 gene. While some of the research has led to clinical trials, those results have yet to translate into effective benefits for humans. By using tissue from fragile X patients, the goal is to overcome this gap in discovery.

In addition to fragile X syndrome, the Patzke Lab is also studying other disorders that cause intellectual disability including Down syndrome and Kabuki syndrome, another rare disorder.

Patzke is affiliated with Notre Dames Boler-Parseghian Center for Rare and Neglected Diseases, the first basic science rare disease research center in the nation. Focused on both basic and translational research, the center works with families affected by rare diseases to combine studies of patient data and tissue with fundamental biological research in order to better understand disease, identify molecular targets and develop new diagnostics and treatments.

Contact: Brandi Wampler, associate director of media relations, 574-631-2632, brandiwampler@nd.edu

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Seven Salk scientists named among best and most highly cited … – Salk Institute

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November 15, 2023 November 15, 2023

LA JOLLASalk Professors Joseph Ecker, Ronald Evans, Satchidananda Panda, Rusty Gage, and Kay Tye, as well as Assistant Professor Jesse Dixon, have been named to the Highly Cited Researchers list by Clarivate. The 2023 list includes 6,849 researchers from 67 countries, all of whom demonstrate significant and broad influence reflected in their publication of multiple highly cited papers over the last decade. This is the ninth consecutive year that Ecker and Gage have made the list. Joseph Nery, a research assistant II in the Ecker lab, was also included on the list.

The Highly Cited Researchers list identifies and celebrates exceptional individual researchers at Salk, whose significant and broad influence in their fields translates to impact in their research community and innovations that make the world healthier, more sustainable, and more secure, says David Pendlebury, Head of Research Analysis at the Institute for Scientific Information at Clarivate. Their contributions resonate far beyond their individual achievements, strengthening the foundation of excellence and innovation in research.

Joseph Ecker Ecker is a professor in the Plant Molecular and Cellular Biology Laboratory, the director of the Genomic Analysis Laboratory, the Salk International Council Chair in Genetics, and a Howard Hughes Medical Institute investigator. His current research focuses on genomic and epigenomic regulation in plants and mammals and the application of DNA sequencing technologies for genome-wide analysis of DNA methylation, chromatin conformation, transcription, and gene function in single cells.

Ronald Evans Evans is a professor, the director of the Gene Expression Laboratory, and the March of Dimes Chair in Molecular and Developmental Biology. An expert in the essential roles of hormone receptors in reproduction, growth, and metabolism, Evans has identified novel pathways involved in cancer and metabolic diseases that are targetable by drugs that activate these receptors. More than a dozen approved drugs have been developed with Evans' technology for the treatment of leukemia, prostate cancer, breast cancer, liver disease, diabetes, and hypertension.

Satchidananda Panda Panda is a professor in the Regulatory Biology Laboratory and the director of the Wu Tsai Human Performance Alliance at Salk. He aims to understand how diet, exercise, and sleep affect cells and molecules in our body and to leverage this knowledge to elevate performance and reduce chronic diseases.

Rusty Gage Gage is a professor in the Laboratory of Genetics, the Vi and John Adler Chair for Research on Age-Related Neurodegenerative Disease, and the former president of the Salk Institute. He is a neuroscientist who studies the plasticity, adaptability, and diversity of the brain. By reprogramming human skin cells and other cells from patients with neurologic and psychiatric diseases into induced pluripotent stem cells, induced neurons, and organoids, his work is deciphering the progression and mechanisms that lead to disorders such as Alzheimer's disease, Parkinsons disease, bipolar disease, depression, and autism spectrum disorder.

Kay Tye Tye is a professor in the Systems Neurobiology Laboratory and the Wylie Vale Chair. She seeks to understand the neural-circuit basis of emotion that leads to motivated behaviors such as social interaction, reward-seeking, and avoidance. Her findings may help to inform treatments for a multitude of neuropsychiatric conditions such as anxiety, depression, addiction, and impairments in social behavior.

Jesse Dixon Dixon, a physician-scientist, is an assistant professor in the Gene Expression Laboratory and a member of the Salk Cancer Center faculty. He is a molecular biologist who uses molecular and computational approaches to explore how our genomes are organized in cells and how abnormal genome folding leads to human diseases such as cancer. His team is also developing new methods to study gene organization and gene function in single cells.

Joseph Nery Nery is a research assistant in the Ecker lab. He has been at the Salk Institute since 2006, where he specializes in epigenetics and runs computational analyses for the lab.

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Perspectives of current understanding and therapeutics of Diamond … – Nature.com

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