Search bioRxiv⌕ Search

Biology subjects

Emanuelli, A.

Publications and source records attributed to Emanuelli, A..

2 recordsLinked to original sources

Use of TSAR, Thermal Shift Analysis in R, to identify Folic Acid as a Molecule that Interacts with HIV-1 Capsid

The thermal shift assay (TSA) is a versatile biophysical technique for studying protein-ligand interactions in vitro. Here, we report a free, open-source software tool, TSAR ("Thermal Shift Analysis in R"), to expedite the analysis of TSA data. The TSAR package incorporates multiple workflows that facilitate TSA analyses, returns publication-ready graphics, and includes an optional graphic user interface. The package is available at https://bioconductor.org/packages/TSAR/. Applying TSAR, we screened two chemical libraries and found multiple molecules that potentially interact in vitro with the capsid protein (CA) of human immunodeficiency virus type 1 (HIV-1). First, a library of vitamins exemplifies the different graphic outputs of TSAR, and we report a change in the 50% melting temperature ({Delta}Tm) for folic acid-treated CA hexamers (CAHEX). Since HIV-1 CAHEX interacts with host-derived acids like inositol hexaphosphate (IP6) or dNTPs, a second library was screened containing 96 organic, acidic metabolites; multiple anionic ligands caused a {Delta}Tm for CAHEX. Subsequent investigation of these interactions includes biolayer interferometry, antiviral activity against pseudotyped HIV-1, and endogenous reverse transcriptase assays that were used to validate and investigate the biological impact of these native ligands that thermally-stabilize CAHEX. One compound hit, gallic acid, exhibited anti-HIV-1 activity as previously reported, and we show interacts with CAHEX as a potentially novel mechanism. Overall, the TSAR package facilitated quick analysis of TSA data from multiple libraries to help identify a biologically relevant hit, gallic acid, as a molecule that can inhibit HIV-1 replication and targets CAHEX. ImportanceThe TSAR package is freely available (AGPL-3) and is designed for both experienced or new R users, having command-line code for handling large and challenging datasets while also including an optional GUI that enables easy use by non-programmers. This is the first TSA analysis program written in R, a free and open-source language; TSAR simplifies TSA analysis while maintaining diverse visualization options for small-to-large libraries and multidimensional analysis. Additionally, we report multiple endogenous metabolites that potentially interact with the HIV-1 capsid protein hexamers (CAHEX) in vitro, including folic acid, gallic acid, and multiple others, primarily from the tricarboxylic acid (TCA) cycle. Various methods validate gallic acid interactions with CAHEX, leading to a novel suggested mechanism of action, and in-line with previous reports, this metabolite has potential for natural-based treatments of HIV-1. Further, we advance the understanding of the potential mechanism(s) for HIV-1 inhibition by gallic acid treatment.

biochemistry↗

A multi-layered systems approach for renal cell carcinoma

Renal cell carcinoma (RCC) still lacks prognostic and predictive biomarkers to monitor the disease and the response to therapy. The usual strategy in translational research is to start from human samples, to identify molecular markers and gene networks and then to functionally validate them in vitro and in animal models. We devised herein a completely opposite strategy from "mouse to man" by performing an aggressiveness screen and used functional genomics, imaging, clinical data and computational approaches in order to discover molecular pathways and players in renal cancer development and metastasis. Multiple cell lines for primary tumor growth, survival in the blood circulation and lung metastasis or metastatic spread from the primary tumor were generated and analyzed using a multi-layered approach which includes large-scale transcriptome, genome and methylome analyses. Transcriptome and methylome analyses demonstrated distinct clustering in three different groups. Remarkably, DNA sequencing did not show significant genomic variations in the different groups which indicates absence of clonal selection during the in vivo amplification process. Transcriptome analysis revealed distinct signatures of tumor aggressiveness which were validated in patient cohorts. Methylome analysis of full-length DNA allowed clustering of the same groups and revealed clinically relevant signatures. Furthermore, we identified SAA2 and CFB as soluble prognostic and predictive biomarkers of the therapeutic response. We also uncovered IL34 as another soluble prognostic biomarker and key regulator of renal cell carcinoma (RCC) progression. This was also functionally validated in vivo, and a mathematical model of IL34-dependent primary tumor growth and metastasis development was provided. These results indicate that such multilayered analysis in a RCC animal model leads to meaningful results that are of translational significance. One Sentence SummaryAn aggressiveness screen with multilayer systems analysis to identify signatures and biomarkers for renal cell carcinoma aggressiveness.

cancer biology↗