HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

Function of cofactor Akirin2 in the regulation of gene expression in model human Caucasian neutrophil-like HL60 cells

The Akirin family of transcription cofactors are involved throughout the metazoan in the regulation of different biological processes (BPs) such as immunity, interdigital regression, muscle and neural development. Akirin do not have catalytic or DNA-binding capability and exert its regulatory function primarily through interacting proteins such as transcription factors, chromatin remodelers, and RNA-associated proteins. In the present study, we focused on the human Akirin2 regulome and interactome in neutrophil-like model human Caucasian promyelocytic leukemia HL60 cells. Our hypothesis is that metazoan evolved to have Akirin2 functional complements and different Akirin2-mediated mechanisms for the regulation of gene expression. To address this hypothesis, experiments were conducted using transcriptomics, proteomics and systems biology approaches in akirin2 knockdown and wildtype (WT) HL60 cells to characterize Akirin2 gene/protein targets, functional complements and to provide evidence of different mechanisms that may be involved in Akirin2-mediated regulation of gene expression. The results revealed Akirin2 gene/protein targets in multiple BPs with higher representation of immunity and identified immune response genes as candidate Akirin2 functional complements. In addition to linking chromatin remodelers with transcriptional activation, Akirin2 also interacts with histone H3.1 for regulation of gene expression.

A genome-wide RNAi screen reveals essential therapeutic targets of breast cancer stem cells

Therapeutic resistance is a major clinical challenge in oncology. Evidence identifies cancer stem cells (CSCs) as a driver of tumor evolution. Accordingly, the key stemness property unique to CSCs may represent a reservoir of therapeutic target to improve cancer treatment. Here, we carried out a genome‐wide RNA interference screen to identify genes that regulate breast CSCs‐fate (bCSC). Using an interactome/regulome analysis, we integrated screen results in a functional mapping of the CSC‐related processes. This network analysis uncovered potential therapeutic targets controlling bCSC‐fate. We tested a panel of 15 compounds targeting these regulators. We showed that mifepristone, salinomycin, and JQ1 represent the best anti‐bCSC activity. A combination assay revealed a synergistic interaction of salinomycin/JQ1 association to deplete the bCSC population. Treatment of primary breast cancer xenografts with this combination reduced the tumor‐initiating cell population and limited metastatic development. The clinical relevance of our findings was reinforced by an association between the expression of the bCSC‐related networks and patient prognosis. Targeting bCSCs with salinomycin/JQ1 combination provides the basis for a new therapeutic approach in the treatment of breast cancer.

Modeling Modulation of the Tick Regulome in Response to Anaplasma phagocytophilum for the Identification of New Control Targets

Ticks act as vectors of pathogens affecting human and animal health worldwide, and recent research has focused on the characterization of tick-pathogen interactions using omics technologies to identify new targets for developing novel control interventions. The regulome (transcription factors-target genes interactions) plays a critical role in cell response to pathogen infection. Therefore, the application of regulomics to tick-pathogen interactions would advance our understanding of these molecular interactions and contribute to the identification of novel control targets for the prevention and control of tick infestations and tick-borne diseases. However, limited information is available on the role of tick regulome in response to pathogen infection. In this study, we applied complementary in silico approaches to modeling how Anaplasma phagocytophilum infection modulates tick vector regulome. This proof-of-concept research provided support for the use of network analysis in the study of regulome response to infection, resulting in new information on tick-pathogen interactions and potential targets for developing interventions for the control of tick infestations and pathogen transmission. Deciphering the precise nature of circuits that shape the tick regulome in response to pathogen infection is an area of research that in the future will advance our knowledge of tick-pathogen interactions, and the identification of new antigens for the control of tick infestations and pathogen infection/transmission.

Integrating molecular networks with genetic variant interpretation for precision medicine

More reliable and cheaper sequencing technologies have revealed the vast mutational landscapes characteristic of many phenotypes. The analysis of such genetic variants has led to successful identification of altered proteins underlying many Mendelian disorders. Nevertheless the simple one‐variant one‐phenotype model valid for many monogenic diseases does not capture the complexity of polygenic traits and disorders. Although experimental and computational approaches have improved detection of functionally deleterious variants and important interactions between gene products, the development of comprehensive models relating genotype and phenotypes remains a challenge in the field of genomic medicine. In this context, a new view of the pathologic state as significant perturbation of the network of interactions between biomolecules is crucial for the identification of biochemical pathways associated with complex phenotypes. Seminal studies in systems biology combined the analysis of genetic variation with protein–protein interaction networks to demonstrate that even as biological systems evolve to be robust to genetic variation, their topologies create disease vulnerabilities. More recent analyses model the impact of genetic variants as changes to the “wiring” of the interactome to better capture heterogeneity in genotype–phenotype relationships. These studies lay the foundation for using networks to predict variant effects at scale using machine‐learning or algorithmic approaches. A wealth of databases and resources for the annotation of genotype–phenotype relationships have been developed to support developments in this area. This overview describes how study of the molecular interactome has generated insights linking the organization of biological systems to disease mechanism, and how this information can enable precision medicine.

This article is categorized under:

Translational, Genomic, and Systems Medicine > Translational Medicine

Biological Mechanisms > Cell Signaling

Models of Systems Properties and Processes > Mechanistic Models

Analytical and Computational Methods > Computational Methods

Functional Evolution of Subolesin/Akirin

The Subolesin/Akirin constitutes a good model for the study of functional evolution because these proteins have been conserved throughout the metazoan and play a role in the regulation of different biological processes. Here, we investigated the evolutionary history of Subolesin/Akirin with recent results on their structure, protein-protein interactions and function in different species to provide insights into the functional evolution of these regulatory proteins, and their potential as vaccine antigens for the control of ectoparasite infestations and pathogen infection. The results suggest that Subolesin/Akirin evolved conserving not only its sequence and structure, but also its function and role in cell interactome and regulome in response to pathogen infection and other biological processes. This functional conservation provides a platform for further characterization of the function of these regulatory proteins, and how their evolution can meet species-specific demands. Furthermore, the conserved functional evolution of Subolesin/Akirin correlates with the protective capacity shown by these proteins in vaccine formulations for the control of different arthropod and pathogen species. These results encourage further research to characterize the structure and function of these proteins, and to develop new vaccine formulations by combining Subolesin/Akirin with interacting proteins for the control of multiple ectoparasite infestations and pathogen infection.