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Figure 2.1 Graphical overview of genome engineering technologies (upper panel) and methods (lower panel) developed during the latest 27 years. A schematic representation of the different technologies or methods is presented, respectively, above or under the timeline arrow.

2.3 BAC Recombineering

      The use of recombineering has been particularly important for functional genomics programmes where BAC transgenes or Gene Targeting constructs have been engineered at large scale to generate animal models of disease or to develop libraries of gene tagging. The European Conditional Mouse Mutagenesis (EUCOMM) and Knock‐Out Mouse Programme (KOMP) contributed to the large‐scale generation of conditional gene KO mice that have been extensively used in Drug Discovery. In particular, Skarnes and colleagues developed a large conditional knock‐out mouse library in the framework of the EUCOMM programme by using a high‐throughput gene‐targeting pipeline based on Recombineering (Skarnes et al. 2011). This gene‐targeting pipeline has been greatly facilitated by the development of a high‐throughput strategy of DNA engineering where “recombineered” targeting constructs were used to engineer C57BL/6N mouse embryonic stem cell for the generation of KO mice. This mouse library has been instrumental to understand the function of genes encoded by the mammalian genomes (In vivo) and to validate drug targets.

      Another particular relevant example of Recombineering applications in Drug Discovery/Development is the remarkable work by scientists at Regeneron Pharmaceuticals aimed to engineer a humanized mouse model producing human–mouse hybrid antibodies. Their VelociGene platform (Murphy 1998) allowed the generation of multiple knock‐out/knock‐in by an high‐throughput recombineering & gene targeting approach where “recombineered” BACs are inserted in mESC using sequential homologous recombination steps. This led to the replacement of mouse immune genes with human orthologs (Valenzuela et al. 2003).

      Finally, a very relevant application of Recombineering is the generation of tagged genes libraries. Gene tagging can potentially overcome the use of high‐affinity antibodies to detect gene expression, but it is limited by the lack of faithful gene activity of tagged protein generated with the use of overexpressed cDNA vectors. BAC transgenes guarantee a quas‐physiological level of gene expression maintaining transgene regulatory element and promoters, although the tagged gene is not integrated in its endogenous locus but in a so‐called third allele. The generation of tagged BAC libraries at scale was greatly simplified by selecting recombineering events in liquid bacterial culture. The potential of this system is exemplified by the generation of genome‐wide BAC libraries for the analysis of protein localization in Daino Rerio and Caenorhabditis elegans (Sarov et al. 2006).

2.4 Metabolic Engineering

      The highly diverse chemical structures of Natural Products isolated from microbes or derived semisynthetically from natural intermediates allowed the development of a broad range of different drug activities, including antibiotics and chemotherapeutics.

      Genome sequencing data facilitated by the development of Next Generation sequencing platforms indicate that microbial genomes contain an untapped resource of biosynthetic gene cluster that can be exploited to generate novel functions.

      Unfortunately, most of these gene clusters are not expressed under normal laboratory growth conditions even when it is possible to grow the natural host in lab environment. In addition, the size of the Biosynthetic gene clusters (reaching up to 200kb) renders the in vitro manipulation of this large clusters difficult (Smanski et al. 2016).

      Recombineering or Recombineering‐derived strategies have therefore been an ideal method to characterize and to engineer long gene clusters. In fact, specific gene clusters can be inserted in an heterologous host to facilitate the genetic manipulation of the genes present in these clusters.

      An alternative strategy would be the use of endogenous recombineering systems from different hosts to manipulate the particular genes present in the gene cluster (Yin et al. 2015).

Recombineering is rapidly becoming the method of choice to manipulate biosynthetic gene clusters but it is also increasingly used to evolve the bacterial genome as pioneered by the work of Church´s group. Hang HH, Isaacs FJ et al. in their landmark paper of 2019 described the use of recombineering to accelerate bacterial genome evolution by an automated multiplex recombineering strategy that they named MAGE (Wang et al. 2009). MAGE is using a pool of ssDNA oligonucleotide coupled with the expression of a ssDNA‐binding protein to install thousands of functionalized genome variants in E. coli genome. MAGE has been recently applied to lower Eukaryotes such as Saccharomyces cerevisiae (Si et al. 2017).

      One of the problems associated with high‐throughput Recombineering is the need to select for the functional variant because there is usually no selective advantage for the recombined bacterial cell. To overcome this limitation, several strategies have been developed to combine the precision and efficiency of Recombineering with the strong selection pressure that occurs in bacteria after the generation of DSB caused by endonucleases like Cas9/CRISPR (Jiang et al. 2013; Jiang et al. 2015; Baker et al. 2016). Despite the large success of Recombineering applied to E. coli genetic engineering, the engineering of large biosynthetic pathways is still inefficient in endogenous hosts where a Recombineering system is not efficient or where Homologous Recombination is not efficient. Therefore, alternative strategies need to be developed to overcome this limitation. One possibility would be to exploit alternative pathways (Su et al. 2016) of DNA recombination/repair such as non‐homologous end joining (NHEJ) as previously done in mammalian cells (Maresca et al. 2013). A more promising approach relies on the recently described integration system by Transposon‐encoded CRISPR‐Cas (Klompe et al. 2019; Strecker et al. 2020). These strategies can facilitate genome engineering of bacteria and can possibly be implemented for the genetic manipulation of Eukaryotic genomes that are less prone to homologous recombination as described in the next section.

2.5 Genetic Engineering in Higher Eukaryotes

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