Alex Zhavoronkov, Fedor Galkin, Shan Chen, Feng Ren, Alex Aliper, Mikhail Durymanov, Denis Sidorenko, Hui Cui, Jing-Dong J. Han, Hao Xu, Xiaodong Liu, Zuojun Xu, Christoph Kuppe, M. Austin Argentieri, Kejun Ying, Ludger J. E. Goeminne, Mahdi Moqri, Alexander Tyshkovskiy, Vadim N. Gladyshev
{"title":"Integration of proteomic aging clocks in a phase 2a clinical trial supports simultaneous geroprotective assessment","authors":"Alex Zhavoronkov, Fedor Galkin, Shan Chen, Feng Ren, Alex Aliper, Mikhail Durymanov, Denis Sidorenko, Hui Cui, Jing-Dong J. Han, Hao Xu, Xiaodong Liu, Zuojun Xu, Christoph Kuppe, M. Austin Argentieri, Kejun Ying, Ludger J. E. Goeminne, Mahdi Moqri, Alexander Tyshkovskiy, Vadim N. Gladyshev","doi":"10.1038/s41587-026-03286-y","DOIUrl":"https://doi.org/10.1038/s41587-026-03286-y","url":null,"abstract":"Drugs for aging-related diseases may modulate aging itself, but standard clinical trial designs cannot detect such effects. Aging clocks could close this gap, but epigenetic models often yield inconsistent, hard-to-interpret results. In contrast, proteomic clocks, by tracking the immediate effectors of biological change, may excel in providing aging biomarkers or mechanistic insight. Here we compare six proteomic clocks (ProtAge, OrganAgemortality, OrganAgechrono, PAC, ipfP3GPT and PAOPAC) on serum proteomes from a published 12-week phase 2a trial of the candidate anti-fibrotic drug rentosertib in idiopathic pulmonary fibrosis. We measure the variance between the clocks and find that all six clocks consistently predicted lower biological age in treated arms. However, proteomic clocks alone cannot deconvolute aging- and disease-specific effects. We addressed this issue indirectly through pathway analyses that identified potential anti-aging shifts in senescence and metabolic processes alongside the anti-fibrotic activity of rentosertib. This work supports the goal of dual-purpose clinical trial designs that integrate aging endpoints into studies for specific disease indications.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"12 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Accelerating natural CO<sub>2</sub> removal from the atmosphere with ocean bacteria.","authors":"","doi":"10.1038/s41587-026-03287-x","DOIUrl":"https://doi.org/10.1038/s41587-026-03287-x","url":null,"abstract":"","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":" ","pages":""},"PeriodicalIF":44.5,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148888242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Linlin Yan, Lingyu Zhou, Qiang Gao, Lijuan Li, Lina Guo, Yidong Ran, Lixiao Zhang, Kang Zhang, Zhiwei Wang, Yan Li, Shengnan Li, Kevin Tianmeng Zhao
{"title":"Engineered genomic attachment sites for site-specific recombinases enable high-efficiency integration in plants and human cells.","authors":"Linlin Yan, Lingyu Zhou, Qiang Gao, Lijuan Li, Lina Guo, Yidong Ran, Lixiao Zhang, Kang Zhang, Zhiwei Wang, Yan Li, Shengnan Li, Kevin Tianmeng Zhao","doi":"10.1038/s41587-026-03294-y","DOIUrl":"https://doi.org/10.1038/s41587-026-03294-y","url":null,"abstract":"<p><p>Here we developed a DNA-centric strategy for optimizing site-specific recombination by rationally engineering chimeric attachment sites. The high-activity att variants enhance Bxb1-mediated integration efficiency in human cells and plants. Among these att variants, the engineered attB(V111) site achieved 51.9% integration efficiency in HEK293T cells (1.7-fold versus wild-type attB) and 35.6% in rice protoplasts (4.4-fold versus wild-type attB). When paired with an engineered single protein mutant in the Bxb1 catalytic domain, the optimized system achieved targeted integration efficiencies of 31% for a CD19 chimeric antigen receptor cassette and 25% for an ornithine transcarbamylase expression cassette in human cells. In rice, these engineered variants enabled integration of a 5.8 kb herbicide-resistance cassette at a targeted genomic locus, with stable integration detected in 24% of regenerated plants. Oxford Nanopore-based long-read sequencing of edited plants reveals complete and precise insertion with high specificity. Propagation of edited seedlings to T1 plants confirms heritable editing to future generations. This approach provides a safe, broadly applicable approach for recombinase-based genome editing.</p>","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":" ","pages":""},"PeriodicalIF":44.5,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148881104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Domiziana Cecchini, AkshatKumar Nigam, Ming Tang, Joana Reis, Matt Koop, Andrea Gottinger, Callum Robert Nicoll, Yao Wang, Abhilash Jayaraj, Süleyman Selim Çınaroglu, Ricarda Törner, Yehor Malets, Minko Gehev, Krishna M Padmanabha Das, Kelly Churion, Jongwan Kim, Nidhin Thomas, Yong Li, Hyuk-Soo Seo, Sirano Dhe-Paganon, Christopher Secker, Mohammad Haddadnia, Alexander Hasson, Minkai Li, Abhishek Kumar, Roni Levin-Konigsberg, Eun-Bee Choi, Geoffrey I Shapiro, Huel Cox, Luke Sebastian, Chelsea Braithwaite, Puspalata Bashyal, Dmytro S Radchenko, Aditya Kumar, Lei Yang, Pierre-Yves Aquilanti, Henry Gabb, Amr Alhossary, Eric O'Neill, Gerhard Wagner, Alán Aspuru-Guzik, Yurii S Moroz, Charalampos G Kalodimos, Konstantin Fackeldey, John D Schuetz, Andrea Mattevi, Haribabu Arthanari, Christoph Gorgulla
{"title":"AI-enhanced adaptive virtual screening of large libraries for ligand discovery.","authors":"Domiziana Cecchini, AkshatKumar Nigam, Ming Tang, Joana Reis, Matt Koop, Andrea Gottinger, Callum Robert Nicoll, Yao Wang, Abhilash Jayaraj, Süleyman Selim Çınaroglu, Ricarda Törner, Yehor Malets, Minko Gehev, Krishna M Padmanabha Das, Kelly Churion, Jongwan Kim, Nidhin Thomas, Yong Li, Hyuk-Soo Seo, Sirano Dhe-Paganon, Christopher Secker, Mohammad Haddadnia, Alexander Hasson, Minkai Li, Abhishek Kumar, Roni Levin-Konigsberg, Eun-Bee Choi, Geoffrey I Shapiro, Huel Cox, Luke Sebastian, Chelsea Braithwaite, Puspalata Bashyal, Dmytro S Radchenko, Aditya Kumar, Lei Yang, Pierre-Yves Aquilanti, Henry Gabb, Amr Alhossary, Eric O'Neill, Gerhard Wagner, Alán Aspuru-Guzik, Yurii S Moroz, Charalampos G Kalodimos, Konstantin Fackeldey, John D Schuetz, Andrea Mattevi, Haribabu Arthanari, Christoph Gorgulla","doi":"10.1038/s41587-026-03217-x","DOIUrl":"10.1038/s41587-026-03217-x","url":null,"abstract":"<p><p>Ultralarge virtual screenings (ULVSs) evaluate billions of molecules for drug discovery but face cost, flexibility and scalability limits. We introduce AdaptiveFlow, an open-source platform that makes ULVSs more accessible, scalable and efficient and supports artificial intelligence (AI) and machine learning (ML) method development. AdaptiveFlow provides a screening-ready version of the Enamine REAL Space, to our knowledge the largest library of ready-to-dock, drug-like molecules, comprising 69 billion compounds, also available in SELFIES format. An 18-dimensional grid of molecular properties prioritizes promising chemical subspaces, with optional active learning, reducing computational costs by orders of magnitude. AdaptiveFlow integrates >1,500 docking protocols, including GPU-accelerated and ML-based methods, and achieves near-linear scaling on up to 5.6 million CPUs in the Amazon Web Services cloud. We identified nanomolar inhibitors of two disease-relevant targets, ferroptosis suppressor protein 1 (FSP1) and poly(ADP-ribose) polymerase 1. Co-crystal structures provided mechanistic insights into FSP1 inhibition. AdaptiveFlow enables drug discovery at unprecedented scale and supports the development of AI-driven methods.</p>","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":" ","pages":""},"PeriodicalIF":44.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leming Shi, Wenjun Bao, Aedín C. Culhane, Xiang Fang, Cesare Furlanello, Ruixin Hao, Wendell D. Jones, Rebecca Kusko, Samir Lababidi, Christopher E. Mason, Andreas Scherer, Shraddha Thakkar, Weida Tong, Russell D. Wolfinger, Joshua Xu, Ying Yu, Rui Zhang, Yuanting Zheng
{"title":"Ensuring multiomics data reproducibility for artificial intelligence with reference materials as a common calibrator","authors":"Leming Shi, Wenjun Bao, Aedín C. Culhane, Xiang Fang, Cesare Furlanello, Ruixin Hao, Wendell D. Jones, Rebecca Kusko, Samir Lababidi, Christopher E. Mason, Andreas Scherer, Shraddha Thakkar, Weida Tong, Russell D. Wolfinger, Joshua Xu, Ying Yu, Rui Zhang, Yuanting Zheng","doi":"10.1038/s41587-026-03267-1","DOIUrl":"10.1038/s41587-026-03267-1","url":null,"abstract":"Reference materials should be adopted as a common calibrator for multiomics measurement and co‑profiled with study samples. Multiomics results should be reported as sample‑to‑reference ratios so that they are reproducible and suitable for artificial intelligence tools.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 9","pages":"1433-1436"},"PeriodicalIF":44.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A pervasive RT-qPCR artifact inflates RNA knockdown by RNA-targeting CRISPR.","authors":"Leslie Watkins, Alan Zhu, Bin Wu","doi":"10.1038/s41587-026-03291-1","DOIUrl":"https://doi.org/10.1038/s41587-026-03291-1","url":null,"abstract":"<p><p>Knockdown efficiency of RNA-targeting CRISPR systems is commonly measured by quantitative polymerase chain reaction with reverse transcription (RT-qPCR). Here we discovered that guide RNAs copurify during RNA extraction and inhibit RT-qPCR for amplicons spanning or upstream of the guide RNA binding site, resulting in overestimation of knockdown efficiency across all CRISPR systems tested. We recommend using a processive reverse transcriptase with strong strand-displacing activity, with orthogonal methods, to ensure accurate quantification when using RT-qPCR.</p>","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":" ","pages":""},"PeriodicalIF":44.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan C Villada, Yumary M Vasquez, Gitta Szabó, Ewan Whittaker-Walker, Miguel F Romero, Sarina Qin, Neha Varghese, Emiley A Eloe-Fadrosh, Nikos C Kyrpides, Axel Visel, Tanja Woyke, Frederik Schulz
{"title":"A genomic catalog of Earth's bacterial and archaeal symbionts.","authors":"Juan C Villada, Yumary M Vasquez, Gitta Szabó, Ewan Whittaker-Walker, Miguel F Romero, Sarina Qin, Neha Varghese, Emiley A Eloe-Fadrosh, Nikos C Kyrpides, Axel Visel, Tanja Woyke, Frederik Schulz","doi":"10.1038/s41587-026-03213-1","DOIUrl":"10.1038/s41587-026-03213-1","url":null,"abstract":"<p><p>Microbial symbiosis drives the functional and phylogenomic diversification of life on Earth yet remains underexplored because of culturing challenges. This study used machine learning (ML) to predict symbiotic lifestyles in more than a hundred thousand microbial genomes from diverse environmental metagenome samples and reference genomes. Predictions were performed using symclatron, an ML framework developed to identify genomic signatures of symbionts. Predictions were deposited in a catalog we established called Symbiont Genomes (SymGs). The results indicate that 15-23% of uncultivated microorganisms likely engage in symbiotic relationships with other organisms, categorized as host-associated or obligate intracellular lifestyles, and are present in half of all known bacterial and archaeal phyla. We also identify genomic signatures of symbiotic lifestyles, including the loss of certain metabolic functions and the differential presence of metabolic modules that may enable host-dependent living. The symclatron software and the SymGs catalog represent valuable resources for studying symbioses, potentially facilitating future mechanistic investigations and engineering of host-microorganism associations.</p>","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":" ","pages":""},"PeriodicalIF":44.5,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}