bioRxiv Science⌕ Search

Biology subjects

Savinov, A.

Publications and source records attributed to Savinov, A..

3 recordsLinked to original sources

Mapping functional regions of essential bacterial proteins with dominant-negative protein fragments

Massively-parallel measurements of dominant negative inhibition by protein fragments have been used to map protein interaction sites and discover peptide inhibitors. However, the underlying principles governing fragment-based inhibition have thus far remained unclear. Here, we adapt a high-throughput inhibitory fragment assay for use in Escherichia coli, applying it to a set of ten essential proteins. This approach yielded single amino acid-resolution maps of inhibitory activity, with peaks localized to functionally important interaction sites, including oligomerization interfaces and folding contacts. Leveraging these data, we perform a systematic analysis to uncover principles of fragment-based inhibition. We determine a robust negative correlation between susceptibility to inhibition and cellular protein concentration, demonstrating that inhibitory fragments likely act primarily by titrating native protein interactions. We also characterize a series of trade-offs related to fragment length, showing that shorter peptides allow higher-resolution mapping but suffer from lower inhibitory activity. We employ an unsupervised statistical analysis to show that the inhibitory activities of protein fragments are largely driven not by generic properties such as charge, hydrophobicity, and secondary structure, but by the more specific characteristics of their bespoke macromolecular interactions. AlphaFold computational modeling of peptide complexes with one protein shows that the inhibitory activity of peptides is associated with their predicted ability to form native-like interactions. Overall, this work demonstrates fundamental characteristics of inhibitory protein fragment function and provides a foundation for understanding and controlling protein interactions in vivo. Significance StatementPeptide fragments derived from protein sequences can inhibit interactions of their parental proteins, providing a promising avenue for drug development. Here we employ a massively-parallel assay to measure in vivo inhibition by fragments that tile the full sequences of ten essential bacterial proteins. We leverage these data to decipher principles of fragment-based inhibition, showing how parental protein concentration drives activity and how protein fragment length interplays with activity and specificity. We employ statistical analysis to parse the roles of biophysical properties in fragment-to-fragment variation, and AlphaFold modeling to determine the relationship between measured inhibitory activity and predicted native-like binding. These results provide a path towards rational design of peptide inhibitors and broader principles of protein-protein interactions in living cells.

microbiology↗

Use of Induced Pluripotent Stem Cells to Build Isogenic Systems and Investigate Type 1 Diabetes

Type 1 diabetes is a disease that arises due to complex immunogenetic mechanisms. Key cell-cell interactions involved in the pathogenesis of T1D are activation of autoreactive T cells by dendritic cells (DC), migration of T cells across endothelial cells (EC) lining capillary walls into the islets of Langerhans, interaction of T cells with macrophages in the islets, and killing of {beta}-cells by autoreactive CD8+ T cells. Overall, pathogenic cell-cell interactions are likely regulated by the individuals collection of genetic T1D-risk variants. To accurately model the role of genetics, it is essential to build systems to interrogate single candidate genes in isolation during the interactions of cells that are essential for disease development. However, obtaining single-donor matched cells relevant to T1D is a challenge. Sourcing these genetic variants from human induced pluripotent stem cells (iPSC) avoids this limitation. Herein, we have differentiated iPSC from one donor into DC, macrophages, EC, and {beta}-cells. Additionally, we also engineered T cell avatars from the same donor to provide an in vitro platform to study genetic influences on these critical cellular interactions. This proof of concept demonstrates the ability to derive an isogenic system from a single donor to study these relevant cell-cell interactions. Our system constitutes an interdisciplinary approach with a controlled environment that provides a proof-of-concept for future studies to determine the role of disease alleles (e.g. IFIH1, PTPN22, SH2B3, TYK2) in regulating cell-cell interactions and cell-specific contributions to the pathogenesis of T1D.

immunology↗

Effects of sequence motifs in the yeast 3' untranslated region determined from massively-parallel assays of random sequences

The 3' untranslated region (UTR) plays critical roles in determining the level of gene expression, through effects on activities such as mRNA stability and translation. The underlying functional elements within this region have largely been identified through analyses of the limited number of native genes. To explore the effects of sequence elements when not present in biologically evolved sequence backgrounds, we analyzed hundreds of thousands of random 50-mers inserted into the 3' UTR of a reporter gene in the yeast Saccharomyces cerevisiae. We determined relative protein expression levels from the fitness of a library of transformants in a growth selection. We find that the consensus 3' UTR efficiency element significantly boosts expression, independent of sequence context; on the other hand, the consensus positioning element has only a small effect on expression. Some sequence motifs that are binding sites for Puf proteins substantially increase expression in this random library, despite these proteins generally being associated with post-transcriptional downregulation when bound to native mRNAs. Thus, the regulatory effects of 3' UTR sequence features like the positioning element and Puf binding sites appear to be strongly dependent on their context within native genes, where they exist alongside co-evolved sequence features. Our measurements also allowed a systematic examination of the effects of point mutations within efficiency element motifs across diverse sequence backgrounds. These mutational scans reveal the relative in vivo importance of individual bases in the efficiency element, which likely reflects their roles in binding the Hrp1 protein involved in cleavage and polyadenylation.

genomics↗