Genome modification in budding yeast has been extremely successful largely due to its highly efficient homology-directed DNA repair machinery. Several methods for modifying the yeast genome have previously been described, many of them involving at least two-steps: insertion of a selectable marker and substitution of that marker for the intended modification. Here, we describe a CRISPR-Cas9 mediated genome editing protocol for modifying any yeast gene of interest (either essential or nonessential) in a single-step transformation without any selectable marker. In this system, the Cas9 nuclease creates a double-stranded break at the locus of choice, which is typically lethal in yeast cells regardless of the essentiality of the targeted locus due to inefficient non-homologous end-joining repair. This lethality results in efficient repair via homologous recombination using a repair template derived from PCR. In cases involving essential genes, the necessity of editing the genomic lesion with a functional allele serves as an additional layer of selection. As a motivating example, we describe the use of this strategy in the replacement of HEM2, an essential yeast gene, with its corresponding human ortholog ALAD.
In several systems, including budding yeast, cell cycle-dependent changes in the transcriptome are well studied. In contrast, few studies queried the proteome during cell division. There is also little information about dynamic changes in metabolites and lipids in the cell cycle. Here, the authors present such information for dividing yeast cells.
Despite over a billion years of evolutionary divergence, several thousand human genes possess clearly identifiable orthologs in yeast, and many have undergone lineage-specific duplications in one or both lineages. These duplicated genes may have been free to diverge in function since their expansion, and it is unclear how or at what rate ancestral functions are retained or partitioned among co-orthologs between species and within gene families. Thus, in order to investigate how ancestral functions are retained or lost post-duplication, we systematically replaced hundreds of essential yeast genes with their human orthologs from gene families that have undergone lineage-specific duplications, including those with single duplications (1 yeast gene to 2 human genes, 1:2) or higher-order expansions (1:>2) in the human lineage. We observe a variable pattern of replaceability across different ortholog classes, with an obvious trend toward differential replaceability inside gene families, and rarely observe replaceability by all members of a family. We quantify the ability of various properties of the orthologs to predict replaceability, showing that in the case of 1:2 orthologs, replaceability is predicted largely by the divergence and tissue-specific expression of the human co-orthologs, i.e., the human proteins that are less diverged from their yeast counterpart and more ubiquitously expressed across human tissues more often replace their single yeast ortholog. These trends were consistent with in silico simulations demonstrating that when only one ortholog can replace its corresponding yeast equivalent, it tends to be the least diverged of the pair. Replaceability of yeast genes having more than 2 human co-orthologs was marked by retention of orthologous interactions in functional or protein networks as well as by more ancestral subcellular localization. Overall, we performed >400 human gene replaceability assays, revealing 50 new human-yeast complementation pairs, thus opening up avenues to further functionally characterize these human genes in a simplified organismal context.
1Despite over a billion years of evolutionary divergence, several thousand human genes possess 2 clearly identifiable orthologs in yeast, and many have undergone lineage-specific duplications in 3 one or both lineages. The ortholog conjecture postulates that orthologous genes between species 4 retain ancestral functions despite divergence over vast timescales, but duplicated genes will be free 5 to diverge in function. However, the retention of ancestral functions among co-orthologs between 6 species and within gene families has been difficult to test experimentally at scale. In order to 7 investigate how ancestral functions are retained or lost post-duplication, we systematically 8 replaced hundreds of essential yeast genes with their human orthologs from gene families that have 9 undergone lineage-specific duplications, including those with single duplications (one yeast gene 10 to two human genes, 1:2) or higher-order expansions (1:>2) in the human lineage. We observe a 11 variable pattern of replaceability across different ortholog classes, with an obvious trend towards 12 differential replaceability inside gene families, rarely observing replaceability by all members of 13 a family. We quantify the ability of various properties of the orthologs to predict replaceability, 14showing that in the case of 1:2 orthologs, replaceability is predicted largely by the divergence and 15 tissue-specific expression of the human co-orthologs, i.e. the human proteins that are less diverged 16 from their yeast counterpart and more ubiquitously expressed across human tissues more often 17 replace their single yeast ortholog. These trends were consistent with in silico simulations 18demonstrating that when only one ortholog is replaceable, it tends to be the least diverged of the 19 pair. Replaceability of yeast genes having more than two human co-orthologs was marked by 20 retention of orthologous interactions in functional or protein networks as well as by more ancestral 21 subcellular localization. Overall, we performed >400 human gene replaceability assays revealing 22 56 new human-yeast complementation pairs, thus opening up avenues to further functionally 23 characterize these human genes in a simplified organismal context. 24 25 and are distinguished from those related by speciation, termed orthologs [8,9]. Importantly, an 46 expanded family of paralogs in one lineage may be co-orthologs to a single gene in another lineage. 47How ancestral functions are partitioned, lost, or retained between paralogs and orthologs during 48 these duplication events is a major topic of study for evolutionary biology. To address these 49 questions, the ortholog conjecture was put forth, a major thesis stating that orthologs are more 50 likely to retain function between species than paralogs, which will tend to diverge in function after 51 duplication due to drift and relaxed selection [10,11]. This conjecture underlies common methods 52 by which functions are assigned to newly discovered or understudied genes in un-annotated 53 4 genomes ...
The yeast Saccharomyces cerevisiae is a powerful tool for studying G protein-coupled receptors (GPCRs) as they can be functionally coupled to its pheromone response pathway. Yet some exogenous GPCRs, including the mu opioid receptor, are non-functional in yeast, which may be due to the presence of the fungal sterol ergosterol instead of the animal sterol cholesterol. We engineered yeast to produce cholesterol and introduced the human mu opioid receptor, creating an opioid biosensor capable of detecting the peptide DAMGO at an EC50 of 62 nM and the opiate morphine at an EC50 of 882 nM. Furthermore, introducing mu, delta and kappa opioid receptors from diverse vertebrates consistently yielded active opioid biosensors that both recapitulated expected agonist binding profiles with EC50s as low as 2.5 nM and were inhibited by the antagonist naltrexone. Additionally, clinically relevant human mu opioid receptor alleles, or variants with terminal mutations, resulted in biosensors that largely displayed the expected changes in activity. We also tested mu opioid receptor-based biosensors with systematically adjusted biosynthetic intermediates of cholesterol, enabling us to relate sterol profiles with biosensor sensitivity. Finally our cholesterol-producing biosensor background was applied to other human GPCRs, resulting in SSTR5, 5-HTR4, FPR1 and NPY1R signaling with varying degrees of cholesterol dependence. Our sterol-optimized platform will be a valuable tool in generating human GPCR-based biosensors, aiding in ongoing receptor deorphanization efforts, and providing a framework for high-throughput screening of receptors and effectors.
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