Methods in molecular biology最新文献

{"title":"Assembly of a Full-Length Chimeric RNA Transcriptome.","authors":"Justin Elfman, Hui Li","doi":"10.1007/978-1-0716-5202-2_5","DOIUrl":"https://doi.org/10.1007/978-1-0716-5202-2_5","url":null,"abstract":"<p><p>Chimeric RNAs are a class of understudied transcripts, characterized by their possession of sequence from two unique annotated parental transcripts. Definitionally, chimeric RNAs exist within gaps in annotation, and most efforts to catalog chimeric RNAs at scale have leveraged short-read paired-end RNAseq. While these have successfully established putative \"chimeromes\" in different tissue and disease contexts, chimeric RNAs predicted via short-read sequencing are defined by the chimeric exon-exon junction, and cannot provide information on the full-length isoforms which contain this junction. These gaps can be remedied by integration of these predictions with full-length, single-molecule, long-read sequencing. In this chapter, we provide instruction on how to integrate long-read sequencing with existing chimeric RNA predictions to establish full-length annotations of long-read transcripts.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"3024 ","pages":"53-60"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148387772","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":"Application of Phage-Displayed Peptide Library for Epitope Mapping.","authors":"Belle Li Ling, Angela Chiew Wen Ch'ng, Yee Siew Choong, Theam Soon Lim","doi":"10.1007/978-1-0716-5249-7_9","DOIUrl":"https://doi.org/10.1007/978-1-0716-5249-7_9","url":null,"abstract":"<p><p>Antibodies, central components of the adaptive immune system, possess the remarkable ability to specifically recognize and bind to foreign substances known as antigens. This recognition occurs through the interaction of the antibody's antigen-binding site, or paratope, with a specific region on the antigen called the epitope. Understanding the precise nature of these interactions, particularly the identification and characterization of epitopes, is of paramount importance for a wide array of biomedical applications. The mapping of antibody epitopes, the process of experimentally identifying the binding site of an antibody on its target antigen, provides critical insights into antibody function and its diverse applications. Peptide phage display provides a convenient and rapid method to identify epitopes of specific monoclonal antibodies. This protocol highlights the use of a peptide phage display library for epitope identification of a recombinant monoclonal antibody.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"3030 ","pages":"139-153"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148387926","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":"Generation of a CDR H3 Randomized Monoclonal Antibody Library by Kunkel Mutagenesis.","authors":"Jia Xuan Yeoh, Yee Siew Choong, Theam Soon Lim","doi":"10.1007/978-1-0716-5249-7_4","DOIUrl":"https://doi.org/10.1007/978-1-0716-5249-7_4","url":null,"abstract":"<p><p>Complementary-determining regions (CDRs) are the primary factor that determines antibody diversity, while CDR H3 plays a central role in antigen binding. Randomization of this loop within a stable framework provides a powerful strategy for generating synthetic antibody libraries. This chapter outlines an approach that is Kunkel mutagenesis based, for constructing a monoclonal antibody library diversified at CDR H3. The method uses uracilated single-stranded DNA templates and degenerate oligonucleotides to introduce targeted variability while suppressing nonrecombinant background through strategically placed stop codons and restriction sites. The resulting repertoire is directly compatible with phage display for downstream selection. This streamlined protocol enables the generation of antibody libraries suitable for applications in affinity maturation, binder discovery, and antibody development.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"3030 ","pages":"55-71"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148388071","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":"High-Performance Computing in Tandem Mass Spectrometry (MS/MS) Peptide Identification.","authors":"Chuang Li, Qiang He, Tao Chen, Yanhua Wen","doi":"10.1007/978-1-0716-5249-7_15","DOIUrl":"https://doi.org/10.1007/978-1-0716-5249-7_15","url":null,"abstract":"<p><p>Tandem mass spectrometry (MS/MS) has become a cornerstone technology in large-scale proteomics, producing vast datasets that present considerable computational challenges for peptide identification. Conventional database-search-based approaches often exhibit limited efficiency, particularly as protein sequence repositories expand rapidly and experimental spectra grow increasingly complex. High-performance computing (HPC) offers a viable solution by supporting large-scale parallelization and algorithmic optimization. In this study, we introduce SW-Tandem, an efficient framework for peptide identification that implements parallelization of the spectrum dot product scoring algorithm on the Sunway TaihuLight supercomputer. Through the incorporation of memory-access optimization, double buffering, and vectorization techniques, SW-Tandem achieves marked improvements in computational performance while maintaining identification accuracy. Experimental evaluations reveal that SW-Tandem substantially accelerates peptide identification and surpasses existing state-of-the-art methods when deployed across multiple nodes. These findings underscore the potential of integrating HPC with algorithmic enhancements to advance large-scale bioinformatics research.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"3030 ","pages":"253-264"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148388145","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":"Structure and Disorder Predictions of Microproteins: Usage, Applications, and Pitfalls.","authors":"Lars A Eicholt","doi":"10.1007/978-1-0716-5013-4_10","DOIUrl":"10.1007/978-1-0716-5013-4_10","url":null,"abstract":"<p><p>In the past decade, computational predictions of protein structure and disorder have become widely accessible, achieving accuracy that, in some cases, rivals experimental results. These advances have been instrumental in identifying structural homologies, guiding protein design, and enhancing functional annotation. However, most prediction models are trained on \"classical proteins,\" favoring specific sequence lengths and patterns, leading to biases. Microproteins-small proteins with emerging roles in development and disease-function similarly across the tree of life and stand to benefit significantly from structure and disorder predictions. Yet, their short length and molecular interactions present unique challenges, making homology detection more difficult and requiring careful methodological considerations. Here, I outline workflows for predicting, analyzing, and refining microprotein structures and disorders, emphasizing key precautions to ensure reliable insights.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2992 ","pages":"129-150"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145530688","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 Practical Guide to Gene Regulatory Networks in Plants: From RNA Sequencing to Identification of Transcription Factor Binding Sites.","authors":"Joaquín Grau, José M Franco-Zorrilla","doi":"10.1007/978-1-0716-4972-5_13","DOIUrl":"10.1007/978-1-0716-4972-5_13","url":null,"abstract":"<p><p>Plant adaptive responses to their environment are orchestrated by transcriptional reprogramming, regulated by sequence-specific transcription factors (TFs) recognizing specific TF-binding sites (TFBSs), and understanding their regulatory grammar is crucial for unravelling plant adaptation mechanisms. Empirical data have contributed to the elucidation of TFBS sequence motifs involved in biological processes, but comprehensive experimental approaches may not be feasible, especially in non-model species. Different computational algorithms have facilitated the elucidation of TFBS sequence motifs and the construction of predictive models, shedding light on plant gene regulatory networks. In this context, the development of straightforward computational pipelines and easy-to-use bioinformatics tools is of particular relevance to make gene expression analysis accessible to the research community. This chapter presents a methodology to infer TF regulators applicable to 60 plant species from RNA sequencing (RNA-seq) data as the starting point. It includes RNA-seq analysis and quantification, gene clustering using WGCNA to identify co-regulated gene modules, and searching for enriched TFBSs associated with these modules. The methodology is illustrated using Arabidopsis RNA-seq data related to abiotic stress. By providing a user-friendly pipeline, researchers are empowered to unravel the molecular basis of gene expression dynamics in plants.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2985 ","pages":"193-211"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145948963","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 Use of Spiroplasma melliferum as a Model Organism to Study Potential Antimicrobials Against Phytoplasma.","authors":"Amir Fine, Luca Galtarossa, Katrin Janik","doi":"10.1007/978-1-0716-5104-9_16","DOIUrl":"10.1007/978-1-0716-5104-9_16","url":null,"abstract":"<p><p>Spiroplasma melliferum is a cultivable mollicute that can be used as a proxy model organism to test the inhibitory effects of filtrates, compounds, or substances against phytoplasma. In this protocol, we describe the use of the resazurin-based alamarBlue™ dye for the monitoring of Spiroplasma survival and growth in the presence of presumably inhibitory agents.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"3008 ","pages":"209-218"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145959381","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":"Protocols for Grapevine Transformation: Tissue Preparation, Protoplast Isolation, and Cultivation.","authors":"Rebeka Strah, Edoardo Bertini, Sara Zenoni, Maruša Pompe Novak, Mario Pezzotti, Marina Dermastia","doi":"10.1007/978-1-0716-5104-9_11","DOIUrl":"10.1007/978-1-0716-5104-9_11","url":null,"abstract":"<p><p>Grapevine is among the most important economic plants that are susceptible to phytoplasma disease. Tools and procedures for genetic manipulation of grapevine are cumbersome and sometimes difficult to replicate; therefore, most of the research on plant-phytoplasma interactions focuses on species with more established transformation procedures instead, even though they might not be hosts of the studied phytoplasma. Studying the mechanisms of plant-phytoplasma interactions directly in the host plants would bring new and more accurate insights into the disease mechanisms. In this chapter, we present the protocols to obtain transformation-competent grapevine material from different tissues and the procedures for protoplast isolation and cultivation.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"3008 ","pages":"133-149"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145959845","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":"Enhanced Detection of Homology Using Artificial Intelligence in Euglenids.","authors":"Mark C Field","doi":"10.1007/978-1-0716-5142-1_20","DOIUrl":"10.1007/978-1-0716-5142-1_20","url":null,"abstract":"<p><p>Identification of similarity between protein sequences is an important component for the assignment of function. With ever-growing databases of genome sequence, this becomes an increasing challenge, and especially in the detection of relationships between distantly related sequences, which is frequently an issue with euglenids. The introduction of artificial intelligence tools to the prediction of protein structure has been, without exaggeration, revolutionary. In particular, AlphaFold3 (AF3), the latest iteration of the AI predictor from DeepMind, a Google subsidiary, offers a potent combination of speed, accuracy, and ease-of-use, all free of charge. Here I will describe a basic workflow for the detection of low similarity between proteins, that is otherwise cryptic, using AF3, discuss how to interpret the predictions, and highlight examples of bizarre predictions or hallucinations.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"3013 ","pages":"401-409"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146106085","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":"Prioritization of Therapeutic Targets of Inflammation Using Proteomics, Bioinformatics, and In Silico Cell-Cell Interactomics.","authors":"Arsalan S Haqqani, Danica B Stanimirovic","doi":"10.1007/978-1-0716-4832-2_22","DOIUrl":"10.1007/978-1-0716-4832-2_22","url":null,"abstract":"<p><p>Protein-protein interactions play key roles in leukocyte extravasation process into the brain and have been attractive therapeutic targets for inhibiting brain inflammation using blocking (or neutralizing) antibodies. These targets include protein-protein interactions between cytokines (or chemokines) and their receptors on leukocytes and between adhesion molecules of leukocyte and brain endothelium. While a number of therapeutics against these targets are currently used in clinic for treatment of brain autoimmune and inflammatory disorders (e.g., multiple sclerosis), they are associated with side effects partly due to the off-target actions (i.e., nonspecific targets). There is a need for novel targets involved in the leukocyte extravasation process that are specific to leukocyte subsets or to individual inflammatory disorder and are amenable for drug development (i.e., druggable). We recently described the blood-brain barrier (BBB) Carta Project as a comprehensive collection of molecular \"maps\" consisting of multiple experimental omics (including RNA sequencing, proteomics, glycoproteomics, glycomics, and metabolomics) and in silico informatic analyses on a number of mammalian species from hundreds of internal, publicly available, or curated datasets. Utilizing the datasets and tools from the BBB Carta Project, we describe a methodology to identify novel \"druggable\" targets involving protein-protein interactions between activated leukocytes and brain endothelial cells using a combination of proteomics, bioinformatics, and in silico interactomics. The result is a prioritized list of protein-protein interactions in a network consisting of leukocyte-brain endothelial cell communication and contacts. These interactions can be further pursued for development of therapeutics such as neutralizing antibodies and their validation through preclinical testing. In addition to targeting brain inflammation, the method described here is applicable for peripheral inflammation and provides the opportunity to target important cell-cell interactions and communications that are more specific/selective for inflammatory disorders and improve currently available therapies.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2980 ","pages":"447-463"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145286522","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}