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Giovanetti, S. M.

Publications and source records attributed to Giovanetti, S. M..

4 recordsLinked to original sources

Multiple domains of Mata1 transcription factor contribute to binding site specificity

Among homologous transcription factors with the same function, DNA-binding specificity can diverge. Mat1 is a high mobility group (HMG) box transcription factor in budding yeast whose Saccharomyces cerevisiae and Candida albicans homologs regulate -specific genes but bind distinct cis-regulatory sequences. To identify the protein features underlying this divergence, we generated structure-guided chimeras and measured their activity using species-specific reporters. Replacing any of the four Mat1 regions reduced activation of the S. cerevisiae reporter, while all chimeras retained activity on the C. albicans reporter. Thus, all four regions of Mat - not just the HMG box domain - are important for sequence specificity.

genetics↗

Combinatorial mosaics dissect the residue level basis of ACE2 binding divergence between SARS-CoV-2 and RaTG13

The spike proteins of SARS-CoV-2 and the closely related bat coronavirus RaTG13 differ in their binding affinity of human ACE2. This is due to differences in the receptor binding domain (RBD), the region primarily responsible for ACE2 binding, which are only 89% identical on the amino acid level, compared to 96% for the remainder of their genomes. Here, we constructed a combinatorial library of RBD mosaics containing combinations of 18 amino acid differences between SARS-CoV-2 and RaTG13 and measured human ACE2 binding using yeast surface display and fluorescence-activated cell sorting. The mosaics revealed a broad range of binding phenotypes. The effects on ACE2 binding were concentrated at eight positions, including all six variable positions that directly contact ACE2. Although the SARS-CoV-2 spike binds human ACE2 stronger than RaTG13 spike, the SARS-CoV-2 residues Q493 and Q498 each reduced ACE2 binding relative to RaTG13s tyrosines. By measuring the effects of these residues across many combinations of other sequence differences, we identified sequence context dependence for residues 493 and 498, finding that the deleterious effects of Q493 and Q498 were attenuated by the SARS-CoV-2 residues at positions 483, 484, and 494. Together, these results provide a residue-level account of the sequence differences underlying the difference in ACE2 binding by SARS-CoV-2 and RaTG13 RBDs, including which differences have the largest effect and which depend on sequence context. This work demonstrates that mosaic libraries provide a robust approach for resolving the contributions of sequence differences across diverse backgrounds.

genetics↗

Highly replicated experiments studying complex genotypes using nested DNA barcodes.

Many biological experiments involve studying the differences caused by genetic modifications, including genotypes composed of modifications at more than one locus. However, as the number and complexity of the genotypes increases, independently generating and tracking the necessary number of biological replicate samples becomes a major challenge. We developed a barcode-based method to track large numbers of independent replicates of combinatorial genotypes in a pooled format, enabling robust detection of subtle phenotypic differences. To construct a plasmid library of combinatorial genotypes, we utilized a nested serial cloning process to combine gene variants of interest that have associated DNA barcodes. The final plasmids each contain variants of multiple genes of interest, and a combined barcode that specifies the genotype of all the genes while also encoding a random sequence for tracking individual replicates. Sequencing of the pool of barcodes by next-generation sequencing allows the whole population to be studied in a single flask, enabling a high degree of replication even for complex genotypes. Using this approach, we tested the functionality of combinations of yeast, human, and null orthologs of the nucleotide excision repair factor I (NEF-1) complex and found that cells expressing all three yeast NEF-1 subunits had superior growth in DNA-damaging conditions. We also assessed the sensitivity of our method by simulating downsampling of barcodes across different degrees of phenotypic differentiation. Our results demonstrate the utility of NICR barcodes for high-throughput combinatorial genetic screens and provide a scalable framework for exploring complex genotype-phenotype relationships.

genetics↗

KTD1 is a yeast defense factor against K28 killer toxin

Secreted protein toxins are widely used weapons in conflicts between organisms. Killer yeast produce killer toxins that inhibit the growth of nearby sensitive yeast. We investigated variation in resistance to the killer toxin K28 across diverse natural isolates of the Saccharomyces cerevisiae population and discovered a novel defense factor, which we named KTD1, that is an important determinant of K28 toxin resistance. KTD1 is a member of the DUP240 gene family of unknown function. We uncovered a putative role of DUP240 proteins in killer toxin defense and identified a region that is undergoing rapid evolution and is critical to KTD1s protective ability. Our findings implicate KTD1 as a key factor in the defense against killer toxin K28.

genetics↗