Methods in molecular biology最新文献

{"title":"Concepts and Methods for Predicting Viral Evolution.","authors":"Matthijs Meijers, Denis Ruchnewitz, Jan Eberhardt, Malancha Karmakar, Marta Łuksza, Michael Lässig","doi":"10.1007/978-1-0716-4326-6_14","DOIUrl":"10.1007/978-1-0716-4326-6_14","url":null,"abstract":"<p><p>The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein hemagglutinin targeted by human antibodies. Here, we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to 1 year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available at https://previr.app .</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2890 ","pages":"253-290"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073650","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":"GMP Compliant Production of Therapeutic Components of Autologous Adipose Tissue.","authors":"Mustafa Uguten, Joeri van Boxtel, Hieronymus P Stevens, Martin C Harmsen, Joris A van Dongen","doi":"10.1007/978-1-0716-4510-9_24","DOIUrl":"https://doi.org/10.1007/978-1-0716-4510-9_24","url":null,"abstract":"<p><p>Adipose tissue is a popular source of tissue for cellular therapy in the field of regenerative medicine. The regenerative potential is often ascribed to the presence of stromal vascular fraction (SVF) containing extracellular matrix and multipotent stromal cells secreting a plethora of growth factors to create a regenerative environment. SVF can be isolated by means of enzymatic or mechanical isolation procedures and expanded in culture or directly used intraoperatively. Depending on the clinical use of SVF, specific regulatory requirements are demanded and might classify SVF as an advanced therapy medicinal product (ATMP). As an ATMP, SVF must be manufactured, processed, and controlled according to good manufacturing practice (GMP) guidelines to ensure safety and quality. Subsequently, the GMP standards require extensive validation, process control, and characterization of SVF. Here we report a GMP-compliant production of clinical grade tissue (tSVF) by means of fractionation of adipose tissue (FAT) procedure. Previous validation studies demonstrated tSVF to be safe and feasible for clinical use intraoperatively according to GMP standards with the appropriate release criteria. The presented procedures can be used as a template for the development of an investigational medicinal product dossier to be enclosed in future clinical trials (Fig. 1).</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2922 ","pages":"307-323"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143972048","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":"A Current Perspective of Medical Informatics Developments for a Clinical Translation of (Non-coding)RNAs and Single-Cell Technologies.","authors":"Alexandra Baumann, Najia Ahmadi, Markus Wolfien","doi":"10.1007/978-1-0716-4290-0_2","DOIUrl":"10.1007/978-1-0716-4290-0_2","url":null,"abstract":"<p><p>The journey from laboratory research to clinical practice is marked by significant advancements in the fields of single-cell technologies and non-coding RNA (ncRNA) research. This convergence may reshape our approach to personalized medicine, offering groundbreaking insights and treatments in various clinical settings. This chapter discusses advancements in (nc)RNAs in the clinics, innovations in single-cell technologies and algorithms, and the impact on actual precision medicine, showing the integration of single-cell and ncRNA research can have a tangible impact on precision medicine. Case studies in Oncology, Immunology, and other fields demonstrate how these technologies can guide treatment decisions, tailor therapies to individual patients, and improve outcomes. This approach is particularly potent in addressing diseases with high inter- and intra-tumor heterogeneity. The final sections address standardization, data integration, and analysis challenges because the complexity and volume of data generated by single-cell and ncRNA research poses significant challenges. Medical Informatics is not just a support tool but could be seen as a pivotal component in advancing clinical applications of single-cell and ncRNA research by bridging the gap between bench and bedside. The future of personalized medicine depends on our ability to harness the power of these technologies, and Medical Informatics in combination with ncRNA and single-cell technologies may stand at the forefront of this endeavor.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2883 ","pages":"31-51"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142864794","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":"Discovering Novel Proteoforms Using Proteogenomic Workflows Within the Galaxy Bioinformatics Platform.","authors":"Praveen Kumar, James E Johnson, Thomas McGowan, Matthew C Chambers, Mohammad Heydarian, Subina Mehta, Caleb Easterly, Timothy J Griffin, Pratik D Jagtap","doi":"10.1007/978-1-0716-4152-1_7","DOIUrl":"10.1007/978-1-0716-4152-1_7","url":null,"abstract":"<p><p>Proteogenomics is a growing \"multi-omics\" research area that combines mass spectrometry-based proteomics and high-throughput nucleotide sequencing technologies. Proteogenomics has helped in genomic annotation for organisms whose complete genome sequences became available by using high-throughput DNA sequencing technologies. Apart from genome annotation, this multi-omics approach has also helped researchers confirm expression of variant proteins belonging to unique proteoforms that could have resulted from single-nucleotide polymorphism (SNP), insertion and deletions (Indels), splice isoforms, or other genome or transcriptome variations.A proteogenomic study depends on a multistep informatics workflow, requiring different software at each step. These integrated steps include creating an appropriate protein sequence database, matching spectral data against these sequences, and finally identifying peptide sequences corresponding to novel proteoforms followed by variant classification and functional analysis. The disparate software required for a proteogenomic study is difficult for most researchers to access and use, especially those lacking computational expertise. Furthermore, using them disjointedly can be error-prone as it requires setting up individual parameters for each software. Consequently, reproducibility suffers. Managing output files from each software is an additional challenge. One solution for these challenges in proteogenomics is the open-source Web-based computational platform Galaxy. Its capability to create and manage workflows comprised of disparate software while recording and saving all important parameters promotes both usability and reproducibility. Here, we describe a workflow that can perform proteogenomic analysis on a Galaxy-based platform. This Galaxy workflow facilitates matching of spectral data with a customized protein sequence database, identifying novel protein variants, assessing quality of results, and classifying variants along with visualization against the genome.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2859 ","pages":"109-128"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469686","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":"Detection and Characterization of Antiviral Proteins Against Bunyaviruses in Mosquito-Derived Cells.","authors":"P Böhmer, M Reuter, M Altinli, E Schnettler","doi":"10.1007/978-1-0716-4338-9_7","DOIUrl":"10.1007/978-1-0716-4338-9_7","url":null,"abstract":"<p><p>Viruses of the class Bunyaviricetes are often transmitted by arthropods, including mosquitoes. The innate immune response in mosquitoes comprises several pathways, including sequence-specific degradation through RNA interference (RNAi). It is known that bunyavirus infections are targeted by the innate immune response in mosquitoes and derived cells; however, detailed information is often still missing. In this chapter, we describe a detailed protocol to determine if a protein of interest acts antiviral against bunyavirus infection in mosquito-derived cells. In line, we also describe a detailed protocol to investigate the effect of overexpression of a mosquito-encoded protein or analysis of mutant proteins on bunyavirus infection.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2893 ","pages":"73-84"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818559","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":"A Computational Pipeline for Identifying Gene Regulatory Networks: A Case Study of Response to Exercise.","authors":"Nadia Moore, Jeffrey Page, William E Kraus, Kim M Huffman, Gordon Broderick","doi":"10.1007/978-1-0716-4200-9_13","DOIUrl":"10.1007/978-1-0716-4200-9_13","url":null,"abstract":"<p><p>Gene regulatory networks are foundational in the control of virtually all biological processes. These networks orchestrate a myriad of cell functions ranging from metabolic rate to the response to a drug or other intervention. The data required to accurately identify these control networks remains very cost and labor intensive typically leading to relatively sparse time course data that is largely incompatible with conventional data-driven model identification techniques. In this work, we combine empirical identification of gene-gene interactions with constraints describing the expected dynamic behavior of the network to infer regulatory dynamics from under-sampled data. We apply this to the identification of gene regulatory subnetworks recruited in groups of subjects participating in several different exercise interventions. Intervention-specific response networks are compared to one another and control actions driving differences are identified. We propose that this approach can extract statistically robust and biologically meaningful insights into gene regulatory dynamics from a dataset consisting of a small number of participants with very limited longitudinal sampling, for example pre- and post- intervention only.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2868 ","pages":"247-264"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142639339","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":"Trabecular Meshwork Regeneration for Glaucoma Treatment Using Stem Cell-Derived Trophic Factors.","authors":"Ajay Kumar, Enzhi Yang, Yiqin Du","doi":"10.1007/978-1-0716-4087-6_4","DOIUrl":"10.1007/978-1-0716-4087-6_4","url":null,"abstract":"<p><p>Glaucoma is one of the leading causes of irreversible blindness. Stem cell therapy has shown promise in the treatment of primary open-angle glaucoma in animal models. Stem cell-free therapy using stem cell-derived trophic factors might be in demand in patients with high-risk conditions or religious restrictions. In this chapter, we describe methods for trabecular meshwork stem cell (TMSC) cultivation, secretome harvesting, and protein isolation, as well as assays to ensure the health of TMSC post-secretome harvesting and for secretome periocular injection into mice for therapeutic purposes.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2848 ","pages":"59-71"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11971979/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Isolation of High-Quality RNA from Mammalian Spermatozoa for Transcriptome Studies.","authors":"Bijayalaxmi Sahoo, Mukesh Kumar Gupta","doi":"10.1007/978-1-0716-4406-5_34","DOIUrl":"https://doi.org/10.1007/978-1-0716-4406-5_34","url":null,"abstract":"<p><p>Mammalian spermatozoa contain a suite of RNA, including mRNA and miRNAs, that may serve as molecular markers of male fertility. The whole transcriptome analysis also identified a few full-length mRNA transcripts in mammalian spermatozoa. However, the isolation of spermatozoal RNA (spRNA) is challenging due to its extremely low concentration and highly condensed nucleo-protamine complex in spermatozoa. Further, chemical agents used for the lysis of cells decrease the total yield and quality of RNAs. Here, we provide an optimized protocol for extracting high-quality spRNA suitable for both short-read (e.g., Illumina™ sequencing) and long-read (e.g., Nanopore™ sequencing) RNA sequencing (RNA-seq). The protocol involves the treatment of semen samples with a lysis solution to remove somatic cells, followed by treatment with a monophasic solution of guanidium thiocyanate (GITC) and 1,4-Dithiothreitol (DTT) to obtain a high-yield of high-quality spRNA.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2897 ","pages":"517-521"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811729","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":"Race Characterization of Puccinia striiformis f. sp. tritici and P. striiformis f. sp. hordei in the United States.","authors":"Xianming Chen, Meinan Wang","doi":"10.1007/978-1-0716-4378-5_2","DOIUrl":"https://doi.org/10.1007/978-1-0716-4378-5_2","url":null,"abstract":"<p><p>Stripe rust (also called yellow rust, Yr) of wheat is caused by Puccinia striiformis f. sp. tritici (Pst), and stripe rust of barley is caused by Puccinia striiformis f. sp. hordei (Psh). These fungal pathogens continually produce new virulent races that may circumvent race-specific resistance genes in commercially grown cultivars of the crops. To effectively develop new resistant cultivars and manage diseases, it is essential to monitor virulence changes and characterize the races of the pathogen. This chapter describes the protocols used to identify races of the pathogens in the United States. Currently, a set of 18 Yr single-gene lines is used to differentiate races of Pst, and a set of 12 barley genotypes is used to differentiate races of Psh. As both Pst and Psh can infect other cereal crops and grasses, some Pst races can infect few barley varieties, and some Psh races may infect few wheat varieties, a scheme we have been using to address the across virulence issue is presented and discussed.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2898 ","pages":"23-39"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143812032","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":"Race Characterization of Puccinia triticina, the Causal Agent of Wheat Leaf Rust, in Canada.","authors":"Brent McCallum, Tanya Copley, Adam Foster, Miao Liu, Chami Amarasinghe, Silvia Barcellos Rosa","doi":"10.1007/978-1-0716-4378-5_1","DOIUrl":"https://doi.org/10.1007/978-1-0716-4378-5_1","url":null,"abstract":"<p><p>Wheat leaf rust, caused by Puccinia triticina Eriks., is one of the most widespread and destructive diseases of wheat in Canada and worldwide. Commonly used control measures include host genetic resistance and fungicide application. Genetic resistance has proven to be very effective and can also be durable when the right combinations of resistance genes are incorporated into wheat cultivars. However, P. triticina is a highly variable pathogen with diverse populations over large geographic areas. This often leads to the evolution of virulence toward resistance genes that are widely used in wheat cultivars. These virulent races are then rapidly selected by wheat cultivars that depend on these now ineffective resistance genes for protection. It is critical to detect these virulent races as quickly as possible to alert producers when some cultivars which were formerly resistant are now susceptible so that they can switch to other, more resistant cultivars or chemical control options. Similarly, wheat breeders need to be alerted that certain resistance genes and cultivars have lost their effectiveness to enable them to select alternative resistance genes and gene combinations for which virulence has not been detected. The purpose of this chapter is to describe the detailed methods required to reliably determine the virulence phenotype, or race, for isolates of P. triticina.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2898 ","pages":"3-21"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143812034","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}