{"title":"Generating Site Saturation Mutagenesis Libraries and Transferring Them to Broad Host-Range Plasmids Using Golden Gate Cloning.","authors":"Niels N Oehlmann, Johannes G Rebelein","doi":"10.1007/978-1-0716-4220-7_14","DOIUrl":"10.1007/978-1-0716-4220-7_14","url":null,"abstract":"<p><p>Protein engineering is an established method for tailoring enzymatic reactivity. A commonly used method is directed evolution, where the mutagenesis and natural selection process is mimicked and accelerated in the laboratory. Here, we describe a reliable method for generating saturation mutagenesis libraries by Golden Gate cloning in a broad host range plasmid containing the pBBR1 replicon. The applicability is demonstrated by generating a mutant library of the iron nitrogenase gene cluster (anfHDGK) of Rhodobacter capsulatus, which is subsequently screened for the improved formation of molecular hydrogen.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2850 ","pages":"251-264"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372271","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":"Golden Gate Cloning for the Standardized Assembly of Gene Elements with Modular Cloning in Chlamydomonas.","authors":"Peter Emelin, Sarah Abdul-Mawla, Felix Willmund","doi":"10.1007/978-1-0716-4220-7_25","DOIUrl":"10.1007/978-1-0716-4220-7_25","url":null,"abstract":"<p><p>Modern synthetic biology requires fast and efficient cloning strategies for the assembly of new transcription units or entire pathways. Modular Cloning (MoClo) is a standardized synthetic biology workflow, which has tremendously simplified the assembly of genetic elements for transgene expression. MoClo is based on Golden Gate Assembly and allows to combine genetic elements of a library through a hierarchical syntax-driven pipeline. Here we describe the assembly of a genetic cassette for transgene expression in the single-celled model alga Chlamydomonas reinhardtii.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2850 ","pages":"451-465"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372274","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":"Golden Gate Cloning of Synthetic CRISPR RNA Spacer Sequences.","authors":"Selina Rust, Lennart Randau","doi":"10.1007/978-1-0716-4220-7_16","DOIUrl":"10.1007/978-1-0716-4220-7_16","url":null,"abstract":"<p><p>Prokaryotes use CRISPR-Cas systems to interfere with viruses and other mobile genetic elements. CRISPR arrays comprise repeated DNA elements and spacer sequences that can be engineered for custom target sites. These arrays are transcribed into precursor CRISPR RNAs (pre-crRNAs) that undergo maturation steps to form individual CRISPR RNAs (crRNAs). Each crRNA contains a single spacer that identifies the target cleavage site for a large variety of Cas protein effectors. Precise manipulation of spacer sequences within CRISPR arrays is crucial for advancing the functionality of CRISPR-based technologies. Here, we describe a protocol for the design and creation of a minimal, plasmid-based CRISPR array to enable the expression of specific, synthetic crRNAs. Plasmids contain entry spacer sequences with two type IIS restriction sites and Golden Gate cloning enables the efficient exchange of these spacer sequences. Factors that influence the compatibility of the CRISPR arrays with native or recombinant Cas proteins are discussed.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2850 ","pages":"297-306"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372291","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}
Kenneth R Lyon, Tatsuya Morisaki, Timothy J Stasevich
{"title":"Imaging and Quantifying Ribosomal Frameshifting Dynamics with Single-RNA Precision in Live Cells.","authors":"Kenneth R Lyon, Tatsuya Morisaki, Timothy J Stasevich","doi":"10.1007/978-1-0716-4248-1_9","DOIUrl":"10.1007/978-1-0716-4248-1_9","url":null,"abstract":"<p><p>Recent advances in fluorescence microscopy have now made it possible to measure the translation dynamics of individual RNA in living cells and in multiple colors. Here we describe a protocol that exploits these recent advances to simultaneously image the translation of two open reading frames encoded on a single reporter RNA yet frameshifted with respect to each other. This enables precise measurements of frameshifting dynamics and efficiency from specific frameshift stimulatory sequences, all with single-RNA precision.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2875 ","pages":"99-110"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11633442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142623983","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":"Spatial Genomic Approaches to Investigate HOX Genes in Mouse Brain Tissues.","authors":"Ashish Shelar, Anasuya Dighe","doi":"10.1007/978-1-0716-4322-8_16","DOIUrl":"https://doi.org/10.1007/978-1-0716-4322-8_16","url":null,"abstract":"<p><p>Spatial transcriptomic tools are an upcoming and powerful way to investigate targeted gene expression patterns within tissues. These tools offer the unique advantage of visualizing and understanding gene expression while preserving tissue integrity, thereby maintaining the spatial context of genes. Curio is a robust spatial transcriptomic tool that facilitates high throughput comprehensive spatial gene expression analysis across the entir e transcriptome with high efficiency. Here, we present a bioinformatics protocol for performing whole transcriptome gene expression analysis of mouse brain tissue using Curio. Specifically, we demonstrate using computational techniques to visualize expression patterns of various HOX genes in the mouse brain.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2889 ","pages":"235-244"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915013","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":"Backtracking Cell Phylogenies in the Human Brain with Somatic Mosaic Variants.","authors":"Sara Bizzotto","doi":"10.1007/978-1-0716-4310-5_10","DOIUrl":"https://doi.org/10.1007/978-1-0716-4310-5_10","url":null,"abstract":"<p><p>Somatic mosaic variants, and especially somatic single nucleotide variants (sSNVs), occur in progenitor cells in the developing human brain frequently enough to provide permanent, unique, and cumulative markers of cell divisions and clones. Here, we describe an experimental workflow to perform lineage studies in the human brain using somatic variants. The workflow consists in two major steps: (1) sSNV calling through whole-genome sequencing (WGS) of bulk (non-single-cell) DNA extracted from human fresh-frozen tissue biopsies, and (2) sSNV validation and cell phylogeny deciphering through single nuclei whole-genome amplification (WGA) followed by targeted sequencing of sSNV loci.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2886 ","pages":"201-220"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915322","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":"Clonal Tracking in the Mouse Brain with Single-Cell RNA-Seq.","authors":"Michael Ratz, Leonie von Berlin","doi":"10.1007/978-1-0716-4310-5_6","DOIUrl":"https://doi.org/10.1007/978-1-0716-4310-5_6","url":null,"abstract":"<p><p>Lineage tracing methods enable the identification of all progeny generated by a single cell. High-throughput lineage tracing in the mammalian brain involves parallel labeling of thousands of progenitor cells with genetic barcodes in vivo followed by single-cell RNA-seq of lineage relations and cell types. Here we describe the generation of barcoded lentivirus, microinjections into the embryonic day 9.5 mouse forebrain, dissociation of 2-week-old mouse brain tissue, single-cell RNA-seq library preparation, and data analysis using a custom software. Compared to traditional methods based on sparse fluorophore labeling of progenitor cells, lineage tracing with genetic barcodes and single-cell RNA-seq has a >100-fold higher throughput while using >10 times fewer mice.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2886 ","pages":"103-137"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915340","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":"Computational Methods for Lineage Reconstruction.","authors":"Irepan Salvador-Martínez","doi":"10.1007/978-1-0716-4310-5_18","DOIUrl":"https://doi.org/10.1007/978-1-0716-4310-5_18","url":null,"abstract":"<p><p>The recent development of genetic lineage recorders, designed to register the genealogical history of cells using induced somatic mutations, has opened the possibility of reconstructing complete animal cell lineages. To reconstruct a cell lineage tree from a molecular recorder, it is crucial to use an appropriate reconstruction algorithm. Current approaches include algorithms specifically designed for cell lineage reconstruction and the repurposing of phylogenetic algorithms. These methods have, however, the same objective: to uncover the hierarchical relationships between cells and the sequence of cell divisions that have occurred during development. In this chapter, I will use the phylogenetic software FastTree to reconstruct a lineage tree, in a step-by-step manner, using data from a simulated CRISPR-Cas9 recorder. To ensure reproducibility, the code is presented as a Jupyter Notebook, available (together with the necessary input files) at https://github.com/irepansalvador/lineage_reconstruction_chapter .</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2886 ","pages":"355-373"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915343","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":"Multicolor Cell Lineage Tracing Using MAGIC Markers Strategies.","authors":"Laura Dumas, Jason Durand, Karine Loulier","doi":"10.1007/978-1-0716-4310-5_3","DOIUrl":"https://doi.org/10.1007/978-1-0716-4310-5_3","url":null,"abstract":"<p><p>Multicolor MAGIC Markers strategies are useful lineage tracing tools to study brain development at a multicellular scale. In this chapter, we describe an in utero electroporation method to simultaneously label multiple neighboring progenitors and their respective progeny using these multicolor reporters. In utero electroporation enables the introduction of any gene of interest into embryonic neural progenitors lining the brain ventricles through a simple pipeline consisting of a micro-injection followed by the application of electrical pulses. Successful in utero electroporation requires a concise yet complete understanding of each step of the surgical protocol, spanning from the preoperative preparation to the postoperative care, as well as the MAGIC Markers tool outlined in this study. Besides a detailed protocol, we present non-integrative and integrative approaches to demonstrate the range of cell and lineage tracking possibilities of multicolored progenitors and their descent over time.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2886 ","pages":"47-63"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915483","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}
M Figueres-Oñate, Jorge García-Marqués, A C Ojalvo-Sanz, Laura López-Mascaraque
{"title":"StarTrack: Mapping Cellular Fates with Inheritable Color Codes.","authors":"M Figueres-Oñate, Jorge García-Marqués, A C Ojalvo-Sanz, Laura López-Mascaraque","doi":"10.1007/978-1-0716-4310-5_16","DOIUrl":"https://doi.org/10.1007/978-1-0716-4310-5_16","url":null,"abstract":"<p><p>StarTrack is a powerful multicolor genetic tool designed to unravel cellular lineages arising from neural progenitor cells (NPCs). This innovative technique, based on retrospective clonal analysis and built upon the PiggyBac system, creates a unique and inheritable \"color code\" within NPCs. Through the stochastic integration of 12 distinct plasmids encoding six fluorescent proteins, StarTrack enables precise and comprehensive tracking of cellular fates and progenitor potentials. The versatility of this tool is further enhanced by the potential of combining multiple promoters. Whether through the use of fluorescent integrable constructs or driving the expression of the PiggyBac transposase, StarTrack broadens the horizons for lineage tracing from progenitors of multiple origins.StarTrack revolutionized our understanding of cellular origins and lineages, offering an invaluable resource for researchers in the field of neural development and lineage tracing. This protocol provides a comprehensive overview of the technique's capabilities and applications, shedding light on its significance within the scientific community.</p>","PeriodicalId":18490,"journal":{"name":"Methods in molecular biology","volume":"2886 ","pages":"311-325"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915496","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}