Читать книгу Pathology of Genetically Engineered and Other Mutant Mice - Группа авторов - Страница 75

The traditional approach to determining gene function has been to work up spontaneous mutations in mice. An example was the allelic series of desmoglein 4 (Dsg4) mutations found first in mice [43, 44]. These were initially compared to human Netherton's syndrome because occasionally abnormal hairs (trichorrhexis invaginata), pathognomonic for Netherton's syndrome, were found in these mice. However, the mutated gene in human Netherton's syndrome was later found to be serine peptidase inhibitor, Kazal type 5 (SPINK5) [45], which did not map to the location of the mouse mutation, making it obvious that another mechanism was involved. Desmoglein 4 was later identified as the genetic basis of the mouse lanceolate hair phenotype. Soon thereafter, the orthologous human disease was found to be the result of mutations in the human DSG4 gene [46]. Not only was the mouse disease identified first, but by finding more than one disease had a so‐called “pathognomonic lesion,” it demonstrated how that concept, of a lesion specific for a disease, can be misleading.

Another example where the concept of “pathognomonic lesion” is an over‐simplification is with hair disease characterized by decreased levels of sulfur containing proteins (trichothiodystrophy, illustrated in Chapter 10, Skin). Trichothiodystrophy was a term used for a specific human disease [47, 48]. Hair shaft structural defects are quite common in mice with a number of mutations and most have low sulfur levels, making that a phenotype not, a pathognomic lesion. Trichothiodystrophy is now considered to be a heterogeneous group of autosomal recessive disorders that share sulfur‐deficient brittle hairs in humans [49]. Many of these defects are due to mutations in specific keratin genes or genes that regulate keratin expression (such as the forkhead box N1 gene causing the nude mouse [Foxn1^nu] and human ortholog [FOXN1]), especially the hard keratins that are high in sulfur containing amino acids [50].

Two main strategies to generate mouse models at scale have been developed based on forward and reverse genetics. The aim of both being to make mutations experimentally, and then characterize the resulting phenotypes.

The forward genetic approaches define the phenotype and aim to identify mouse orthologs of genes responsible for human disorders through cross‐species phenotypic similarity. These can utilize mice carrying spontaneous mutations [51], those that are the result of chemical mutagenesis [52–56] or other means, such as radiation induced mutation. In addition to identifying null gene mutations, forward genetics approaches often identify hypomorphic, gain‐of function, and dominant‐negative mutations. For example, The Jackson Laboratory utilized whole‐exome sequencing to identify the genes responsible for numerous spontaneous mutations in 124 inbred mouse strains [57, 58].

Such programs, especially ENU, have proved their long‐term success but depend very much on having targeted phenotype screens that can be carried out at high throughput and strategies for recovery of the mutated gene. This has become much easier with the development of next‐generation sequencing technologies and successful sperm freezing techniques. Two of the first projects were set up in 1997 at the Helmholtz Institute in Munich and the Medical Research Council (MRC) Mammalian genome unit in the United Kingdom. These have been followed by similar projects in Australia, the United States, and Japan and to date more than 20 projects have been run worldwide [59, 60]. These projects have yielded a steady stream of novel mouse models, often generating very useful allelic series across a wide range of domains [55]. Particularly notable is the innate immunity screen set up in Bruce Beutler's laboratory with an innovative methodology for rapidly identifying the mutated allele associated with an immunological phenotype [53].

The work involved in identifying mutant alleles from ENU screens gave rise to the second strategy for randomized mutation – that of using insertional mutagenesis making use of the insertion of transposons, such as Sleeping Beauty or Piggy‐Bac, which has high mutagenesis efficiency and makes recovery of mutant alleles relatively straightforward [61].

The most comprehensive strategy, however, has been a reverse genetic strategy to individually knockout every protein‐coding gene in the mouse genome one by one, and to phenotype the subsequent strains. The first of these very ambitious projects began in 2007 with the International Knockout Mouse Consortium using a set of tailored constructs for embryonic stem cell (ES cell) mediated homologous recombination, which has been followed up by the use of the much faster CRISPR/Cas9 technology which has sped up this process and completely replaced the various molecular technologies that generated traditional null mutations. CRISPR/Cas9 is capable of generating very precise mutations that can and do mimic polymorphisms found in human populations [42, 62–65].

Unfortunately, results often varied between laboratories, most likely due to differences in environment, genetic background, and experimental approaches. Moreover, many laboratories lacked pathology support. The transition to large scale, partially blind approaches using more standardized methodologies, has greatly expanded and speeded up this process. Early, large‐scale, industrialized programs were designed to identify novel drug targets but also proved useful in predicting human disease mutations [66]. Currently the international public sector program, the US NIH Knockout Mouse Program (KOMP) and the International Mouse Phenotyping Consortium (IMPC), has systematically inactivated one gene at a time with a standardized phenotyping program [67]. Development of the comprehensive high throughput phenotyping has been critical in using these mutants to discover information about gene function and to establish new mouse models for human diseases [67, 68] To date more than 18 000 genes have been conditionally knocked out and more than 6000 of these mutant ES cells turned into mouse strains and phenotyped [69]. Combined, these programs have identified many new diseases in mice and humans [70–73].

The importance of phenotype in the approach to model discovery is critical and this has consequently lead to computational approaches to identify candidate genes for human diseases from mouse mutants by comparing phenotypes of patients with unknown lesions, to those of mice with known knockouts. Advances in biosemantics have led to the development of several platforms supporting this approach, based on semantic similarity between phenotypes of two or more species [74–76]. While the approach is able to recapitulate known gene–phenotype relationships most of the time, there remains some concern about the ability of such algorithms to identify new genes due to perceived overfitting of training sets. In addition, the IMPC report that comparing phenotypes from International Knockout Mouse Consortium (IKMC) mutants, made on a C57BL/6N background, to those already in the mouse genome informatics (MGI) database created through hypothesis‐driven research showed that only 40% had any phenotype in common at all [68]. While this figure could be due to incomplete or biased phenotyping by investigators, or incorrect phenotyping calls by the IMPC, the likelihood is that it represents strain background effects, an issue that reinforces the need for careful and detailed phenotyping on multiple backgrounds in order to find useful models.