Biology subjects

Fornelos, N.

Publications and source records attributed to Fornelos, N..

3 recordsLinked to original sources

bioRxiv2020

Using protein interaction networks to identify cancer dependencies from tumor genome data

Genes required for tumor proliferation and survival (dependencies) are challenging to predict from cancer genome data, but are of high therapeutic value. We developed an algorithm (network purifying selection [NPS]) that aggregates weak signals of purifying selection across a genes first order protein-protein interaction network. We applied NPS to 4,742 tumor genomes to show that a genes NPS score is predictive of whether it is a dependency and validated 58 NPS-predicted dependencies in six cancer cell lines. Importantly, we demonstrate that leveraging NPS predictions to execute targeted CRISPR screens is a powerful, highly cost-efficient approach for identifying and validating dependencies quickly, because it eliminates the substantial experimental overhead required for whole-genome screening.

cancer biology↗

bioRxiv2020

Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data

Combining genetic and cell-type-specific proteomic datasets can lead to new biological insights and therapeutic hypotheses, but a technical and statistical framework for such analyses is lacking. Here, we present an open-source computational tool called Genoppi that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data. We used Genoppi to analyze sixteen cell-type-specific protein interaction datasets of four proteins (TDP-43, MDM2, PTEN, and BCL2) involved in cancer and neurological disease. Through systematic quality control of the data and integration with published protein interactions, we show a general pattern of both cell-type-independent and cell-type-specific interactions across three cancer and one human iPSC-derived neuronal type. Furthermore, through the integration of proteomic and genetic datasets in Genoppi, our results suggest that the neuron-specific interactions of these proteins are mediating their genetic involvement in neurodevelopmental and neurodegenerative diseases. Importantly, our analyses indicate that human iPSC-derived neurons are a relevant model system for studying the involvement of TDP-43 and BCL2 in amyotrophic lateral sclerosis.

genetics↗

bioRxiv2020

The small DdrR protein directly interacts with the UmuDAb regulator to inhibit the mutagenic DNA damage response in Acinetobacter baumannii

Acinetobacter baumannii poses a great threat in healthcare settings worldwide with clinical isolates revealing an ever evolving multidrug-resistance. Here, we report the molecular mechanisms governing the tight repression of the error-prone DNA polymerase umuDC genes in this important bacterial human pathogen. We demonstrate that the small DdrR protein directly interacts with the UmuDAb transcription repressor, which possesses some similarities to LexA proteins from other bacteria, to increase the repressors affinity for target sequences in the umuDC operon. These data reveal that DdrR forms a stable complex with free UmuDAb but is released upon association of this repressor complex with target DNA. We show that DdrR also interacts with UmuD, a component of DNA polymerase V and that DdrR enhances the operator binding of LexA repressors from Clostridium difficile, Bacillus thuringiensis and Staphylococcus aureus. Our results suggest that proteins that assist the action of LexA-like transcription factors may be common to many, if not all, bacteria that mount the SOS response.

biochemistry↗