GEN biotechnology最新文献

{"title":"Sweet Dreams are Made of This: An Interview with Carolyn Bertozzi","authors":"Carolyn Bertozzi, Alex Philippidis, Kevin Davies","doi":"10.1089/genbio.2023.29119.cbe","DOIUrl":"https://doi.org/10.1089/genbio.2023.29119.cbe","url":null,"abstract":"","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"399 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139022948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The RNA-Recognition Pathway: An Overlooked Transportation Mechanism for Extracellular and Therapeutic RNAs","authors":"Alice Ghidini, Aleksandra Singh","doi":"10.1089/genbio.2023.0049","DOIUrl":"https://doi.org/10.1089/genbio.2023.0049","url":null,"abstract":"","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"111 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139015491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Call for Special Issue Papers: Diversity, Equity, and Inclusion in Biotechnology","authors":"Brian Aguado, Karmella Haynes, Ana Maria Porras","doi":"10.1089/genbio.2023.29118.cfp","DOIUrl":"https://doi.org/10.1089/genbio.2023.29118.cfp","url":null,"abstract":"","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"32 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139262809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence-Mediated Computer-Aided Design of Viral Gene Therapies","authors":"Alireza Daneshvar, Stefan N. Lukianov","doi":"10.1089/genbio.2023.0014","DOIUrl":"https://doi.org/10.1089/genbio.2023.0014","url":null,"abstract":"Over 5% of newborns suffer from a genetic disease. These include single gene, polygenic, and chromosomal disorders. Many other noncongenital diseases with genetic components are activated by environmental triggers (autoimmune, cancer, and tissue injury). Sophisticated viral gene therapies could treat, and possibly cure, these diseases and significantly ease patient burden and improve quality of life. Current viral therapies are mostly limited to plasmid-based and adeno-associated virus variants with inefficient response rates and limited use, with some herpes, lenti, and retroviral modalities. Development is slow and expensive. Virtual prototyping of viral gene therapies through computational design, like in other engineering fields, may represent a useful process to accelerate and expand viral pipeline development by opening the human virome to therapeutic development and constructing specificity, potency, efficacy, and safety in silico. Contemporary computational tools (artificial intelligence, machine and deep learning, computer-aided design, high performance computing, cloud and edge computing, and physics-based modeling) now render this possibility feasible and, therefore, constitute powerful options for biopharma researchers to expand and accelerate precision medicine research and development for complex indications.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"28 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136311682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping the Spatial Proteome of Head and Neck Tumors: Key Immune Mediators and Metabolic Determinants in the Tumor Microenvironment","authors":"Niyati Jhaveri, Bassem Ben Cheikh, Nadezhda Nikulina, Ning Ma, Dmytro Klymyshyn, James DeRosa, Ritu Mihani, Aditya Pratapa, Yasmin Kassim, Sidharth Bommakanti, Olive Shang, Shannon Berry, Nicholas Ihley, Michael McLane, Yan He, Yi Zheng, James Monkman, Caroline Cooper, Ken O'Byrne, Bhaskar Anand, Michael Prater, Subham Basu, Brett G.M. Hughes, Arutha Kulasinghe, Oliver Braubach","doi":"10.1089/genbio.2023.0029","DOIUrl":"https://doi.org/10.1089/genbio.2023.0029","url":null,"abstract":"Head and neck squamous cell carcinomas (HNSCCs) are the seventh most common cancer and represent a global health burden. Immune checkpoint inhibitors (ICIs) have shown promise in treating recurrent/metastatic disease with durable benefit in ∼30% of patients. Current biomarkers for HNSCC are limited in their dynamic ability to capture tumor microenvironment (TME) features with an increasing need for deeper tissue characterization. Therefore, new biomarkers are needed to accurately stratify patients and predict responses to therapy. Here, we have optimized and applied an ultra-high plex, single-cell spatial protein analysis in HNSCC. Tissues were analyzed with a panel of 101 antibodies that targeted biomarkers related to tumor immune, metabolic and stress microenvironments. Our data uncovered a high degree of intra-tumoral heterogeneity intrinsic to HNSCC and provided unique insights into the biology of the disease. In particular, a cellular neighborhood analysis revealed the presence of six unique spatial neighborhoods enriched in functionally specialized immune subsets. In addition, functional phenotyping based on key metabolic and stress markers identified four distinct tumor regions with differential protein signatures. One region was marked by infiltration of CD8+ cytotoxic T cells and overexpression of BAK, a proapoptotic regulator, suggesting strong immune activation and stress. Another adjacent region within the same tumor had high expression of G6PD and MMP9, known drivers of tumor resistance and invasion, respectively. This dichotomy of immune activation-induced death and tumor progression in the same sample demonstrates the heterogenous niches and competing microenvironments that may underpin variable clinical responses. Our data integrate single-cell ultra-high plex spatial information with the functional state of the TME to provide insights into HNSCC biology and differential responses to ICI therapy. We believe that the approach outlined in this study will pave the way toward a new understanding of TME features associated with response and sensitivity to ICI therapies.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Engineering CRISPR Cures: An Interview with Fyodor Urnov","authors":"Fyodor D. Urnov, Jonathan D. Grinstein","doi":"10.1089/genbio.2023.29113.fdu","DOIUrl":"https://doi.org/10.1089/genbio.2023.29113.fdu","url":null,"abstract":"GEN BiotechnologyVol. 2, No. 5 Asked & AnsweredFree AccessEngineering CRISPR Cures: An Interview with Fyodor UrnovFyodor D. Urnov and Jonathan D. GrinsteinFyodor D. Urnov*Address correspondence to: Fyodor D. Urnov, Director of the Center for Translational Genomics at the Innovative Genomics Institute. E-mail Address: [email protected]Director of the Center for Translational Genomics at the Innovative Genomics Institute.Search for more papers by this author and Jonathan D. GrinsteinSenior Editor, GEN Media Group.Search for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29113.fduAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Fyodor Urnov, Director of the Center for Translational Genomics at the Innovative Genomics Institute (IGI)Fyodor Urnov is a pioneer in the field of genome editing and one of the scientists most invested in expanding the availability and utility of CRISPR-based therapies to the broadest possible population. He envisions a world in which genome editing can treat the nearly 400 million people who are suffering from one of the 7000 diseases brought on by gene mutations.After his PhD in 1996 from Brown University, Urnov worked as a postdoctoral fellow in the laboratory of Alan Wolffe at the National Institutes of Health (NIH). In 2000, Urnov joined Wolffe in moving to Sangamo Therapeutics in California. During his 16 years at Sangamo, Urnov and his colleagues performed the first demonstration using zinc-finger nucleases to modify DNA in human cells in 2005, coining the term “genome editing” in the process.1After that, Urnov led collaborative teams that created large-scale genome editing applications in crop genetics, model animal reverse genetics, and human somatic cell genetics. While at Sangamo, Urnov also led a cross-functional team from basic discovery to the initial design of the first-in-human clinical trials for sickle cell disease and beta-thalassemia, which are being conducted in collaboration with UCSF Benioff Children's Hospital and UCLA Broad Stem Cell Research Center.In 2019, Urnov became the Director of the Center for Translational Genomics at the Innovative Genomics Institute (IGI), working alongside Nobel laureate Jennifer Doudna, and a Professor in the Departments of Genetics, Genomics, and Development at the University of California, Berkeley. At the IGI, Urnov works in collaborative teams to develop first-in-human applications of experimental CRISPR-based therapeutics for sickle cell disease (with Mark Walters, UCSF), genetic disorders of the immune system (with Alexander Marson, UCSF/IGI), radiation injury (with Jonathan Weissman, MIT/Whitehead Institute), cystic fibrosis (with Ross Wilson, IGI), and neurological disorders (with Weill Neurohub and Roche/Genentech).In this exclusive interview, GEN Biotechnology talks to Urnov about his career in ","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135810519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond the Lab and Into the Hospital: An Outlook on the Clinical Utility of Spatial Omics Technologies","authors":"Dean M. Pucciarelli, Benjamin Y. Lu, Inti Zlobec, Marcello DiStasio","doi":"10.1089/genbio.2023.0030","DOIUrl":"https://doi.org/10.1089/genbio.2023.0030","url":null,"abstract":"Spatial omics technologies, including highly multiplexed histologic protein assays, nucleic acid abundance and/or sequence mapping, and spatial epigenetics assays, offer powerful tools for interrogating the complex biology of human tissues. These technologies have been broadly applied in basic and translational research, which presages deployment in clinical settings as well. In this article, we discuss spatial omics technologies with an emphasis on retrieval of disease-related information in single samples, with potential clinical applications in specialties such as oncology and immunology, and in the development of personalized treatment. Capable of localizing detailed molecular information within histologic structures, spatial omics technologies provide both cell-intrinsic information and microenvironmental interaction context. This will allow more precise diagnostic and prognostic classifications and more accurate predictions about treatment responses to be made. While technical and financial challenges to widespread deployment in clinical laboratories remain, spatial omics technologies are expected to dramatically expand actionable information obtained by human tissue sampling for pathologic analysis.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Omics Spotlights the Players in the Tumor Microenvironment","authors":"Sachin Rawat","doi":"10.1089/genbio.2023.29115.sro","DOIUrl":"https://doi.org/10.1089/genbio.2023.29115.sro","url":null,"abstract":"GEN BiotechnologyVol. 2, No. 5 News Feature: Spatial OmicsFree AccessSpatial Omics Spotlights the Players in the Tumor MicroenvironmentSachin RawatSachin Rawat*Address correspondence to: Sachin Rawat, Freelance Science Writer. E-mail Address: [email protected]Freelance Science Writer.Search for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29115.sroAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Researchers are using spatial omics to look deeper into the tumor microenvironment and unravel tumor heterogeneity with an eye on gleaning important clinical insights.Tumor immune microenvironment of human colorectal cancer. Cancer cells in green and immune cells in magenta. (Credit: NanoString Technologies)Many hard-to-treat cancers often recur months or years after successful treatment. “You could have one cell that escapes treatment and it's that one cell that will populate and be resistant and allow for a recurrence to happen,” said Jasmine Plummer, founding director of the Center for Spatial Omics at St. Jude Children's Research Hospital.Investigating such tumors with even single-cell omics technologies could miss these resistant cells. Before analysis, single-cell technologies destroy the cancer tissue to look at what's happening in the tissue as a whole. However, a lot of the interesting stuff inside tumors happens at the level of individual cells and depends on the context in which they exist. Single-cell technologies lose this spatial context when the cells are broken up.This is where spatial omics come in.With advances in omics technologies, cancer biologists have extensive information on the genes, proteins, and other metabolites that make up the messy environment of a tumor. Single-cell omics goes further, enabling the identification of all cell types in a tumor sample. This has only deepened our understanding of the extreme heterogeneity of tumor cells. Spatial omics technologies are placing these insights in the spatial context.Jasmine Plummer, Founding Director of the Center for Spatial Omics at St. Jude Children's Research HospitalTake gene expression, for example. Single-cell transcriptomics reveals which genes are being expressed across different cell types. But it doesn't say where these cells are in the tumor. Spatial transcriptomics technologies fill this gap by simultaneously recording spatial coordinates with gene expression data. This is the crux of the growing field of spatial omics: assigning pin codes to omics data.Spatial transcriptomics technologies such as in situ hybridization and in situ sequencing allow researchers to capture transcriptomes without losing spatial information. The former uses fluorescent, gene-specific probes that bind mRNAs, whereas the latter sequences the transcripts directly in a section of a fixed tissue.Complementing these imaging-ba","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion Evolution: New Artificial Intelligence Models Break Barriers in Protein Design","authors":"Fay Lin","doi":"10.1089/genbio.2023.29114.fli","DOIUrl":"https://doi.org/10.1089/genbio.2023.29114.fli","url":null,"abstract":"GEN BiotechnologyVol. 2, No. 5 News FeaturesFree AccessDiffusion Evolution: New Artificial Intelligence Models Break Barriers in Protein DesignFay LinFay LinE-mail Address: [email protected]Senior Editor, GEN BiotechnologySearch for more papers by this authorPublished Online:16 Oct 2023https://doi.org/10.1089/genbio.2023.29114.fliAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Diffusion models, a form of generative artificial intelligence, are a rising tool for protein design, showing improved experimental success and new potential for biotechnological applications.This protein fold is one of thousands designed from scratch using new machine learning methods. (Credit: Ian C. Haydon/UW Institute for Protein Design)In July 2023, scientists in David Baker's laboratory at the University of Washington (UW) published a report in Nature detailing a new deep-learning framework for de novo protein design called RoseTTAFold diffusion (RFdiffusion), in Nature.1 Since then, the scientific community has been buzzing about RFdiffusion's unprecedented experimental success rate and ease of use.David Juergens, a graduate student in Baker's laboratory and one of seven co-lead authors of the Nature article, shared an anecdote about a scientist working in a lab in China, who posted on social media how “they designed a protein in a browser, ordered the sequence, purified the protein, crystallized it, and then got a crystal structure that was half an angstrom away from the design that was on the computer. It was amazing!” Juergens told me.David Baker, Professor in Biochemistry and Director of the Institute for Protein Design at UWSome of the applications of RFdiffusion, documented with experimental validation in the Nature article, include design of symmetric oligomers for vaccine platforms and delivery vehicles and generation of high-affinity binders for therapeutics.1 In another project, the Baker laboratory has applied RFdiffusion to design proteins that bind peptide hormones—established biomarkers for clinical care and biomedical research—for diagnostic applications.2Box 1. Let's Generate interactionsGenerate: Biomedicines is a Boston-based therapeutics company at the intersection of machine learning, biological engineering, and medicine. Molly Gibson, cofounder and chief strategy and innovation officer, says the company focuses on designing protein–protein interactions for therapeutic applications.“If you think about biologics, the most important function that a protein takes is creating very specific and potent binding with its target. This could be things like an antibody where we know exactly where we want to neutralize a target, or where we want to agonize and potentiate function,” said Gibson.One project at Generate: Biomedicines has worked to create a broadly neutralizing antibody for coronavirus. Gibson notes that the virus activel","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technical Advances and Applications of Spatial Transcriptomics","authors":"Guohao Liang, Hong Yin, Fangyuan Ding","doi":"10.1089/genbio.2023.0032","DOIUrl":"https://doi.org/10.1089/genbio.2023.0032","url":null,"abstract":"Transcriptomics is one of the largest areas of research in biological sciences. Aside from RNA expression levels, the significance of RNA spatial context has also been unveiled in the recent decade, playing a critical role in diverse biological processes, from subcellular kinetic regulation to cell communication, from tissue architecture to tumor microenvironment, and more. To systematically unravel the positional patterns of RNA molecules across subcellular, cellular, and tissue levels, spatial transcriptomics techniques have emerged and rapidly became an irreplaceable tool set. Herein, we review and compare current spatial transcriptomics techniques on their methods, advantages, and limitations, as well as applications across a wide range of biological investigations. This review serves as a comprehensive guide to spatial transcriptomics for researchers interested in adopting this powerful suite of technologies.","PeriodicalId":73134,"journal":{"name":"GEN biotechnology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135811698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}