Radically different
For decades, the ability to precisely rewrite bacterial genomes has been largely confined to a single workhorse organism: Escherichia coli. That limitation has slowed efforts to study pathogens, engineer sustainable biomanufacturing strains, and probe how microbes influence human health. While genome editing tools have transformed eukaryotic biology, most high‑efficiency bacterial editors simply haven’t worked outside E. coli.
A new study from the Gladstone Institutes aims to change that. In a large, nine‑lab collaboration, researchers have translated a retron‑based DNA editing system from E. coli into 14 additional bacterial species spanning three major phyla. The work, published in Nature Biotechnology and titled “Genome editing of phylogenetically distinct bacteria using cross-species retron-mediated recombineering,” demonstrates that retrons, bacterial immune elements that continuously produce short DNA strands, can be engineered into portable genome editing modules the authors call recombitrons. “Recombitrons—a genome editing tool created by pairing modified, donor-producing bacterial retrons with single-stranded binding and annealing proteins—have increased the efficiency of recombineering to install flexible, precise edits in the prokaryotic chromosome,” the authors wrote.
Retrons normally function as part of a viral defense system, generating DNA fragments that help bacteria detect and respond to infection. Seth Shipman, PhD, a Gladstone Investigator and senior author of the study, has spent years repurposing this machinery. “We’ve been easily editing E. coli genomes using retrons for years now, which has substantially increased the pace of our fundamental biology and our molecular technology development,” he said. “But we kept hearing from the broader field, asking when there would be a version of this technology that could be put to work in other bacterial species that matter for the environment, industrial processes, or human health.”
Shipman’s lab previously showed that retrons can act as cellular DNA-making factories, generating the donor strands needed for genome editing. In bacteria, the resulting editing tool built by pairing modified retrons with single‑stranded DNA–binding and annealing proteins is known as a recombitron. Until now, however, functional recombitrons existed only in E. coli.
To test whether the architecture could travel, the team designed a panel of 10 retron-based editing systems and partnered with other labs specializing in diverse bacterial species. “We designed all the molecular parts at Gladstone, then sent them to the collaborators, where they ran the experiment in their labs,” said first author Alejandro González‑Delgado, PhD. Samples were then returned to Gladstone for centralized analysis.
The results show broad functionality. The recombitrons worked in all 15 species tested, including clinically relevant pathogens such as Klebsiella pneumoniae and Pseudomonas aeruginosa, as well as fast‑growing biotechnology strains like Vibrio natriegens and Pseudomonas putida. Editing efficiencies varied widely—from fractions of a percent to more than 90%—but the team demonstrated that modifying retron structure or other system components could boost performance in lower‑efficiency hosts.
“Each retron worked differently in different bacteria,” González‑Delgado noted. “This reinforces why it’s important to have lots of different retrons, so scientists can choose the ones best suited to their favorite bacterial species.”
The study provides a roadmap for expanding genome editing into species that have historically been difficult to engineer. Researchers studying microbial pathogenesis, gut ecology, or industrial bioproduction can now match retron systems to their organism of interest.
“My lab builds molecular technology, and we want these technologies to be used as broadly as possible to uncover new biology and intervene in disease,” Shipman said. “We hope it will continue to spread from here.”
The post Retron-Powered Approach Enables Genome Editing Across Diverse Bacterial Species appeared first on GEN – Genetic Engineering and Biotechnology News.
After a yearslong legal feud, Elon Musk and OpenAI CEO Sam Altman are heading to trial this week in Northern California in a case that could have sweeping consequences. Ahead of OpenAI’s highly anticipated IPO, the court could rule on whether the company is allowed to exist as a for-profit enterprise and might even oust its current executive leadership, including Altman.
Musk is suing OpenAI, alleging that Altman and OpenAI president Greg Brockman deceived him into bankrolling the company in its early days by promising to maintain it as a nonprofit dedicated to developing AI that benefits humanity, only to later restructure the company to operate a for-profit subsidiary. Musk cofounded OpenAI with Altman and others in 2015, but he left in 2018 after a bitter power struggle.
Musk is seeking as much as $134 billion in damages from OpenAI and Microsoft, one of OpenAI’s biggest financial backers. He is also asking the court to remove Altman and Brockman from their roles and to restore OpenAI as a nonprofit. Musk has asked the court to award any damages to OpenAI’s nonprofit rather than to him personally.
Nine jurors will deliver an advisory verdict, a non-binding recommendation, to guide the judge in deciding Musk’s claims against Altman. Musk, Altman, and Brockman will take the stand. Former OpenAI chief scientist Ilya Sutskever, former OpenAI CTO Mira Murati, and Microsoft CEO Satya Nadella are also expected to testify. Cringey texts, raw diary entries, and endless scheming behind the founding and growth of OpenAI are expected to come to light.
In an industry enveloped in secrecy, the trial will be a rare opportunity for the public to look behind the curtain and find out what’s going on in the companies creating the most transformative technology ever built.
When OpenAI was originally founded as a nonprofit, backed by a $38 million donation from Musk, the company vowed to create open-source technology for the public’s benefit, unconstrained by a need to generate financial returns. But over the years, the company began to claim that intensifying competition could make it dangerous to share how it develops its AI models and that a nonprofit structure could not raise enough money to keep building AI. (MIT Technology Review was first to report on OpenAI’s internal conflicts around its mission.)
The court has already found that in 2017 Altman and Brockman wanted to establish a for-profit arm, while Musk proposed merging OpenAI with his electric-car company, Tesla. When Musk threatened to stop funding, Altman and Brockman told him that they were committed to keeping the company a nonprofit. Musk alleges that they pursued plans to pivot to a for-profit without informing him. According to OpenAI, Musk agreed that the company needed a for-profit entity and even wanted to be its CEO.
But even if Musk proves he was duped by Altman and Brockman, he may not have standing in the first place to sue them for restructuring the company to operate a for-profit subsidiary. Some legal scholars are puzzled over why the judge allowed him to bring this claim. “The idea that Elon Musk can sue because he was a donor or used to be on the board is pretty puzzling,” says Jill Horwitz, a law professor who studies nonprofit law at Northwestern University. “Typically, it’s up to the attorneys general to bring such a claim to enforce the charitable purposes. And that’s already happened.”
In October 2025, state attorneys general of California, where OpenAI is headquartered, and Delaware, where OpenAI is incorporated, struck a deal with OpenAI to approve its new corporate structure on a series of conditions. For example, a safety and security committee at the nonprofit would review safety-related decisions made by the for-profit subsidiary. Critics of the restructuring, including Musk, AI safety advocates, and civil society groups, have tried to stop it.
California’s attorney general has declined to join Musk’s lawsuit, saying that the office did not see how his action serves the public interest.
Still, whether the deal holds OpenAI to its nonprofit mission is an open question. “Elon Musk should have to show … what the deficiencies are in what’s been agreed to by OpenAI with the attorneys general,” says Rose Chan Loui, the director of the UCLA School of Law’s philanthropy and nonprofit program. Even with the terms in place, holding OpenAI to them depends on “how much they can enforce it and how much transparency they get into OpenAI’s work.”
More importantly, legal experts say the case is being considered under the wrong body of law. Musk argues that Altman and Brockman breached OpenAI’s charitable trust by creating a closed-source, for-profit subsidiary. As a result, the court has been analyzing the claim under the law of trusts. “But OpenAI is not a trust. OpenAI is a corporation. And so really they should be looking at … the law of charitable nonprofit organizations,” says Chan Loui.
Despite all the legal muddiness, the outcome of the trial could upend the AI race. Any one of the remedies that Musk seeks could cripple OpenAI as it races to go public by the end of the year. OpenAI, which is valued at over $850 billion, has described the litigation with Musk as a potential risk to its business. Musk’s rival company xAI, which makes the chatbot Grok, is expected to go public as a part of his rocket company SpaceX as early as June. If Musk prevails, xAI, which in combination with SpaceX is valued at $1.25 trillion, could get a big advantage in the AI race.
And the trial has helped expose the bitter schism between Musk and the company he once helped to found. An OpenAI spokesperson referred MIT Technology Review to a post on X: “This lawsuit has always been a baseless and jealous bid to derail a competitor.” Although Musk’s lawyers did not immediately respond to a request for comment, he has posted on X that “Scam Altman lies as easily as he breathes.”
MIT Technology Review will have ongoing coverage of Musk v. Altman until its conclusion. Follow @techreview or @michelletomkim on X for up-to-the-minute reporting.
Background: Depression affects more than 300 million people worldwide and is a leading contributor to the global disease burden. Traditional diagnostic methods, such as structured clinical interviews, are reliable but impractical for frequent or large-scale screening. Self-report tools like the Patient Health Questionnaire-8 (PHQ-8) require disclosure and clinician oversight, limiting accessibility. Recent artificial intelligence–based approaches leverage multimodal behavioral cues (linguistic, acoustic, and visual) for automated depression detection but remain constrained by limited adaptability, scarce annotated data, weak emotional expression in real-world settings, and the high computational cost of deployment of socially assistive robots (SARs). Objective: This study introduces Depression Social Assistant Robot (DEPRESAR)-Fusion, a lightweight multimodal depression detection framework designed for natural interactions with emotion-aware SARs. The objective of this study was to enhance detection accuracy in everyday conversations while addressing the challenges of data scarcity, weak emotional cues, and computational efficiency. Methods: DEPRESAR-Fusion integrates acoustic, linguistic, and visual features with an emotion-aware response module powered by large language models to adapt conversational strategies dynamically. To stimulate richer emotional expression, participants were exposed to emotionally evocative videos before SAR interactions. To overcome data scarcity, we augmented training with (1) public depression-related social media corpora and (2) synthetic samples generated via large language models. The proposed multimodal fusion architecture was evaluated on benchmark clinical datasets for both binary depression classification and PHQ-8 regression tasks. Performance was compared against prior multimodal baselines using root mean square error, mean absolute error, and standard classification metrics. Results: Participants who viewed emotional stimuli before interacting with SARs exhibited significantly higher emotional expressiveness, leading to improved model performance. Regression tasks showed lower root mean square error and mean absolute error, while classification tasks achieved significantly higher accuracy than the nonstimulus condition. DEPRESAR-Fusion outperformed prior multimodal baselines across multiple benchmark datasets, achieving state-of-the-art performance in both binary classification and PHQ-8 regression. The system maintained a lightweight architecture suitable for real-time deployment on SARs. Conclusions: DEPRESAR-Fusion demonstrates that integrating emotion induction, data augmentation, and lightweight multimodal fusion can enable accurate and scalable depression detection in naturalistic SAR interactions. By bridging the gap between structured clinical assessments and everyday conversations, this approach highlights the potential of SAR-based systems as nonintrusive, artificial intelligence–driven tools for proactive mental health support.
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A new U.S. policy that recommends offering hepatitis B vaccine at birth only to babies perceived to be at risk of neonatal infection will lead to increased numbers of infected infants and more cases of chronic hepatitis B infection in children that will generate millions of extra dollars in health care costs, two studies published Monday project.
“Avoiding an increase in neonatal infections under the targeted recommendation would require historically unattained levels of maternal [hepatitis B] screening or birth-dose coverage among infants of unscreened mothers,” said one of the studies, from researchers at Boston University, the University of Florida, and Johns Hopkins University.
WASHINGTON — The Supreme Court seemed divided Monday over whether to block thousands of lawsuits alleging the maker of the weedkiller Roundup failed to warn people it could cause cancer.
The case came before the justices after a tidal wave of litigation that included some multibillion-dollar verdicts against the global agrochemical manufacturer Bayer, which owns Roundup maker Monsanto.