Single-cell imaging of protein dynamics of paralogs reveals mechanisms of gene retention

Gene duplication is common across the tree of life, including yeast and humans, and contributes to genomic robustness. In this study, we examined changes in the subcellular localization and abundance of proteins in response to the deletion of their paralogs originating from the whole-genome duplication event, which is a largely unexplored mechanism of functional divergence. We performed a systematic single-cell imaging analysis of protein dynamics and screened subcellular redistribution of proteins, capturing their localization and abundance changes, providing insight into forces determining paralog retention. Paralogs showed dependency, whereby proteins required their paralog to maintain their native abundance or localization, more often than compensation. Network feature analysis suggested the importance of functional redundancy and rewiring of protein and genetic interactions underlying redistribution response of paralogs. Translation of non-canonical protein isoform emerged as a novel compensatory mechanism. This study provides new insights into paralog retention and evolutionary forces that shape genomes.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Abstract 6390: Chromosome arm aneuploidies as genetic vulnerabilities of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer which lacks the expression of key biomarkers, namely Estrogen and Progesterone receptors and HER2. Therefore, it lacks targeted therapies, resulting in the worst prognosis compared to other breast cancer subtypes. Chromosome 4p (chr4p) loss is recurrent in TNBC, correlates with poor prognosis, is an early event in tumor evolution, and confers a proliferative advantage onto cells. Here, we propose that chr4p loss can be leveraged as a genetic vulnerability of TNBC by identifying its specific synthetic lethal (SL) genetic interactions. An SL interaction occurs when the inactivation of individual genes is tolerated, however, the combined inactivation of the corresponding genes leads to a loss of cellular viability. SL interactions offer promising avenues for precision oncology therapeutic strategies of TNBC. We leveraged the publicly available CRISPR-mediated genome-wide gene inactivation screens (DepMap project) dataset to computationally predict pairwise SL interactions that are specific to individual genes within chr4p, as well as complex SL genetic interactions involving multiple genes spanning large segments of chr4p and the entire chromosome arm. We developed regression models to compare the inactivation effect of a given SL partner gene, between cell lines that harbor chr4p loss and those characterized by a copy-neutral status of chr4p, while effectively accounting for potential confounding effects. We integrated the putative SL interactions identified from these regression models with those identified using other methods, drugZ and MAGECK, therefore, resulting in a robust set of putative SL interactions. We have prioritized the SL interactions for their subsequent experimental validation in TNBC PDX-derived 2D and 3D cell models, which we will carry out using CRISPR-based gene editing. The prediction model and collective set of SL candidates identified in this study is a unique resource for the development of SL-based therapeutic strategies for TNBC and other cancers harboring chr4p loss.

Citation Format: Rohan Dandage, Michael Schwartz, Lynn Karam, Traver Hart, Elena Kuzmin. Chromosome arm aneuploidies as genetic vulnerabilities of triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6390.

Abstract 2947: Surveying the tumor suppressive genetic network underlying chr4p deletion in TNBC

Triple negative breast cancer (TNBC) is a breast cancer subtype lacking targetable biomarkers, resulting in the worst prognosis compared to other breast cancer subtypes. TNBC is characterized by many large copy number variants that result in the deletion and amplifications of many genes, with TP53 being the only common oncogenic driver. Using TCGA data and in-depth functional genomic analysis of TNBC patient-derived xenografts (PDX), our group showed that chr4p is a recurrently deleted region in basal breast cancer, which TNBC is an enriched subtype. This correlated with poor prognosis and a highly proliferative state. Here, we set out to survey the tumor suppressive genetic network underlying the TNBC-specific chr4pdeletion. Using an arrayed CRISPR-enCas12 screening approach, I will generate a panel of mutant cell lines deleted for all protein-coding genes residing within chr4p. MCF10A series of cell lines will be used for mutant cell line construction, because it is an established normal human breast epithelial model system with a normal karyotype to ensure the diploid state ofchr4p and includes other derivatives (MCF10A(-E7-Bcl2)) that show basal anchorage independent growth in 3D to assess cell transformation. The resulting panel of single gene deletion mutant cell lines will be characterized for their effects on proliferation, apoptosis, cell transformation and senescence. Additionally, the tumor suppressive genetic interaction network of chr4p will be mapped using a multiplexed CRISPR-enCas12 screening methodology. A dual guide-RNA library will be generated for all protein-coding genes to test all pairwise combinations for tumor suppressive genetic interactions. The proliferation due to double gene deletions will be monitored and compared to single gene deletions to identify tumor suppressive interactions. This study will be the first to systematically identify tumor suppressor genetic network underlying chr4p. Ultimately, it will provide an in-depth understanding of the genetic network of large copy number variants in TNBC and insight into new avenues for precision oncology.

Citation Format: Joseph Del Corpo, Rohan Dandage, Lea Harrington, Elena Kuzmin. Surveying the tumor suppressive genetic network underlying chr4p deletion in TNBC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2947.

Abstract 47: Identifying genetic vulnerabilities of chromosome 4p large copy number variants in triple negative breast cancer

Triple Negative Breast Cancer (TNBC) is characterized by the absence of common oncogenic drivers, limiting its treatment options; however, it exhibits recurrent large chromosomal deletions. We previously showed that chromosome 4p (chr4p) loss is a frequently observed large copy number variant in TNBC and is associated with poor prognosis. We also showed that chr4p deletion is an early event in tumor evolution and confers on cells a proliferative advantage. Here, we set out to uncover the genetic vulnerabilities associated with chr4p deletion in TNBC to identify novel therapeutic avenues for TNBC and enhance our understanding of the genetic mechanisms that maintain chr4p deletion in the genome. Whole genome sequence analysis of our TNBC Primary Tumor(PT)/Patient-Derived Xenograft (PDX) panel identified samples with copy neutral and deletion status of chr4p. These deletion regions span a large fraction of the chr4p arm. RNAseq analysis revealed that chr4p deletion is functionally significant since gene expression of ~80% of genes was reduced upon chr4p deletion. Chr4p deletion was associated with global transcriptomic changes and differentially expressed genes were enriched for proliferation, DNA replication, cell migration, activation of the innate immune response and protein translation. PDX-derived cell models from these samples showed lentiviral infectivity based on a control lentivirus expressing GFP. Additionally, these PDX cell models were shown to be editable using CRISPR-Cas9 through the targeting of core essential genes. We will use a pooled CRISPR-Cas9 approach to systematically screen for genetic vulnerabilities in TNBC PDX-derived cell models harbouring chr4p copy neutral or deletion state. To further investigate the genetic mechanisms buffering chr4p loss, we have leveraged publicly-available CRISPR-Cas9 genome-wide genetic screen data from the Cancer DepMap to identify putative synthetic lethal (pSL) partners with chr4p deletion in TNBC. This was accomplished by developing regression models and integrating them with results from established methods such as drugZ and MAGeCK. We identified pSL partners for chr4p at gene, segmental and arm levels. pSLs were enriched for mitochondrial, protein translation and proliferation pathways. We will validate the top candidates from these analyses in our cohort of chr4p deletion and chr4p copy neutral TNBC PDX-derived cell models and integrate them with the pooled CRISPR screens. Together, this work aims to reveal potential TNBC-specific therapeutic avenues for precision oncology.

Citation Format: Michael Schwartz, Rohan Dandage, Lynn Karam, Alain Pacis, Hellen Kuasne, Anne-Marie Fortier, Sidong Huang, Guillaume Bourque, Traver Hart, Elena Kuzmin, Morag Park. Identifying genetic vulnerabilities of chromosome 4p large copy number variants in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 47.

Deep Mutational Scanning of Protein-Protein Interactions Between Partners Expressed from Their Endogenous Loci In Vivo

Deep mutational scanning (DMS) generates mutants of a protein of interest in a comprehensive manner. CRISPR-Cas9 technology enables large-scale genome editing with high efficiency. Using both DMS and CRISPR-Cas9 therefore allows us to investigate the effects of thousands of mutations inserted directly in the genome. Combined with protein-fragment complementation assay (PCA), which enables the quantitative measurement of protein-protein interactions (PPIs) in vivo, these methods allow for the systematic assessment of the effects of mutations on PPIs in living cells. Here, we describe a method leveraging DMS, CRISPR-Cas9, and PCA to study the effect of point mutations on PPIs mediated by protein domains in yeast.

Identifying features of genome evolution to exploit cancer vulnerabilities

Cancer treatment strategies include exploiting genetic vulnerabilities offered by synthetic lethal (SL) interactions between paralogs. In this issue of Cell Systems, De Kegel et al. (2021) apply a machine learning approach to predict robust SL paralogs in the human genome, highlighting genome evolutionary features as key predictors.

Frequent Assembly of Chimeric Complexes in the Protein Interaction Network of an Interspecies Yeast Hybrid

Hybrids between species often show extreme phenotypes, including some that take place at the molecular level. In this study, we investigated the phenotypes of an interspecies diploid hybrid in terms of protein–protein interactions inferred from protein correlation profiling. We used two yeast species, Saccharomyces cerevisiae and Saccharomyces uvarum, which are interfertile, but yet have proteins diverged enough to be differentiated using mass spectrometry. Most of the protein–protein interactions are similar between hybrid and parents, and are consistent with the assembly of chimeric complexes, which we validated using an orthogonal approach for the prefoldin complex. We also identified instances of altered protein–protein interactions in the hybrid, for instance, in complexes related to proteostasis and in mitochondrial protein complexes. Overall, this study uncovers the likely frequent occurrence of chimeric protein complexes with few exceptions, which may result from incompatibilities or imbalances between the parental proteomes.

Similarities in biological processes can be used to bridge ecology and molecular biology

Much of the research in biology aims to understand the origin of diversity. Naturally, ecological diversity was the first object of study, but we now have the necessary tools to probe diversity at molecular scales. The inherent differences in how we study diversity at different scales caused the disciplines of biology to be organized around these levels, from molecular biology to ecology. Here, we illustrate that there are key properties of each scale that emerge from the interactions of simpler components and that these properties are often shared across different levels of organization. This means that ideas from one level of organization can be an inspiration for novel hypotheses to study phenomena at another level. We illustrate this concept with examples of events at the molecular level that have analogs at the organismal or ecological level and vice versa. Through these examples, we illustrate that biological processes at different organization levels are governed by general rules. The study of the same phenomena at different scales could enrich our work through a multidisciplinary approach, which should be a staple in the training of future scientists.

Paralog dependency indirectly affects the robustness of human cells

The protective redundancy of paralogous genes partly relies on the fact that they carry their functions independently. However, a significant fraction of paralogous proteins may form functionally dependent pairs, for instance, through heteromerization. As a consequence, one could expect these heteromeric paralogs to be less protective against deleterious mutations. To test this hypothesis, we examined the robustness landscape of gene loss-of-function by CRISPR-Cas9 in more than 450 human cell lines. This landscape shows regions of greater deleteriousness to gene inactivation as a function of key paralog properties. Heteromeric paralogs are more likely to occupy such regions owing to their high expression and large number of protein-protein interaction partners. Further investigation revealed that heteromers may also be under stricter dosage balance, which may also contribute to the higher deleteriousness upon gene inactivation. Finally, we suggest that physical dependency may contribute to the deleteriousness upon loss-of-function as revealed by the correlation between the strength of interactions between paralogs and their higher deleteriousness upon loss of function.

Differential strengths of molecular determinants guide environment specific mutational fates

Organisms maintain competitive fitness in the face of environmental challenges through molecular evolution. However, it remains largely unknown how different biophysical factors constrain molecular evolution in a given environment. Here, using deep mutational scanning, we quantified empirical fitness of >2000 single site mutants of the Gentamicin-resistant gene (GmR) in Escherichia coli, in a representative set of physical (non-native temperatures) and chemical (small molecule supplements) environments. From this, we could infer how different biophysical parameters of the mutations constrain molecular function in different environments. We find ligand binding, and protein stability to be the best predictors of mutants' fitness, but their relative predictive power differs across environments. While protein folding emerges as the strongest predictor at minimal antibiotic concentration, ligand binding becomes a stronger predictor of mutant fitness at higher concentration. Remarkably, strengths of environment-specific selection pressures were largely predictable from the degree of mutational perturbation of protein folding and ligand binding. By identifying structural constraints that act as determinants of fitness, our study thus provides coarse mechanistic insights into the environment specific accessibility of mutational fates.

Classification of chemical chaperones based on their effect on protein folding landscapes

Various small molecules present in biological systems can assist protein folding in vitro and are known as chemical chaperones. De novo design of chemical chaperones with higher activity than currently known examples is desirable to ameliorate protein misfolding and aggregation in multiple contexts. However, this development has been hindered by limited knowledge of their activities. It is thought that chemical chaperones are typically poor solvents for a protein backbone and hence facilitate native structure formation. However, it is unknown if different chemical chaperones can act differently to modulate folding energy landscapes. Using a model slow folding protein, double-mutant Maltose-binding protein (DM-MBP), we show that a canonical chemical chaperone, trimethylamine-N-oxide (TMAO), accelerates refolding by decreasing the flexibility of the refolding intermediate (RI). Among a number of small molecules that chaperone DM-MBP folding, proline and serine stabilize the transition state (TS) enthalpically, while trehalose behaves like TMAO and increases the rate of barrier crossing through nonenthalpic processes. We propose a two-group classification of chemical chaperones based upon their thermodynamic effect on RI and TS, which is also supported by single molecule Förster resonance energy transfer (smFRET) studies. Interestingly, for a different test protein, the molecular mechanisms of the two groups of chaperones are not conserved. This provides a glimpse into the complexity of chemical chaperoning activity of osmolytes. Future work would allow us to engineer synergism between the two classes to design more efficient chemical chaperones to ameliorate protein misfolding and aggregation problems.