Gian Gaetano Tartaglia

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Gian Gaetano Tartaglia (born 23 October 1976, Rome) is an Italian biophysicist and computational biologist. He is currently a Principal Investigator at the Italian Institute of Technology.

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Biography

After a PhD in biochemistry at the University of Zurich and a postdoc at the University of Cambridge in the chemistry department, in 2010 Gian Tartaglia became PI at the Centre for Genomic Regulation (CRG) in Barcelona. He was awarded a European Research Council grant in 2013 for his studies on the role of coding and non-coding transcripts in the regulation of amyloid genes (ERC 309545). [1] In 2014 Tartaglia was tenured in Catalonia as a professor of Life and Medical Sciences . [2] In December 2018, Tartaglia became a full professor of biochemistry in the Department of Biology at University La Sapienza [3] through a procedure of "chiara fama". In 2019 he started working at the Italian Institute of Technology (IIT) as a PI. In 2020, Tartaglia was awarded another ERC grant for the study on the composition of phase-separated assemblies. [4]

Research

The Tartaglia lab observed that the structural content in RNA molecules is correlated to the number of protein interactions. This reveals the existence of a regulation level that directly links RNA to proteins especially for genes that are highly active in cellular processes (Sanchez de Groot et al.) Rnaproteincontacts.png
The Tartaglia lab observed that the structural content in RNA molecules is correlated to the number of protein interactions. This reveals the existence of a regulation level that directly links RNA to proteins especially for genes that are highly active in cellular processes (Sanchez de Groot et al.)
The lab develop the CROSS method to compute the secondary structure profile of large transcripts1. Positive scores indicate double-stranded regions, while negative values are predicted to be single-stranded. Predictions for murine XIST are shown (repetitive regions are marked with coloured boxes). The area under the ROC curve of 0.75 (inset) indicates high agreement with experimental data (correlations with individual domains are reported; (Vandelli et al. )). Crossalgoritm.png
The lab develop the CROSS method to compute the secondary structure profile of large transcripts1. Positive scores indicate double-stranded regions, while negative values are predicted to be single-stranded. Predictions for murine XIST are shown (repetitive regions are marked with coloured boxes). The area under the ROC curve of 0.75 (inset) indicates high agreement with experimental data (correlations with individual domains are reported; (Vandelli et al. )).

Recent discoveries

Since 2020, the most exciting area in which the group works is the development of RNA aptamers. The lab discovered that these molecules can be used to detect aggregates and have the potential to inhibit progressive accumulation of TDP-43. [7] There is a great potential for two major applications that will push the scientific boundaries: diagnostics (i.e., identification of aggregates at the early stages) and therapeutics (i.e., intervention on aggregate development) in the context of Amyotrophic Lateral Sclerosis. [8]

Early contributions

Tartaglia's group discovered that RNA plays a central role in protein assembly. [5] They found that FMR1 mRNA [5] and Xist non-coding RNA [9] are able to trigger the formation of large phase-separated assemblies, [10] while other transcripts such as HSP70 mRNA can prevent the aggregation of specific proteins acting as `solubilizers'. [5] These observations strongly indicate that RNA-based molecules may be ideal candidates for the stabilisation of proteins in their native conformation by emulating the natural binding partners. More specifically, the Tartaglia lab found that messenger RNA is a potent solubilizer blocking the formation of toxic aggregates that are potentially toxic to our organisms. [5]

Discovering the interactions of long non-coding RNAs

In 2011, Tartaglia's group introduced a method to perform large-scale predictions of protein-RNA associations discovering the interactions of long non-coding RNA. The algorithm, 'fast predictions of RNA and protein interactions and domains at the Center for Genomic Regulation, Barcelona, Catalonia' (catRAPID [11] ), evaluates the interaction propensities of polypeptide and nucleotide chains using their physicochemical properties. [12] The algorithm shows performances comparable to experimental tools, as reported in recent surveys. [13]

The lab developed the catRAPID method (Bellucci et al., Agostini et al. .; Cirillo et al., ) methods to identify protein partners of non-coding transcripts such as XIST (18000 nt). Top: Predicted binding regions of different proteins, including PTBP1, LBR, SPEN, HNRNPK, HNRNPU and DKC1 (ranked by interaction propensity); Bottom: eCLIP validation of the binding regions. Protein DKC1 is used as a negative control. CatRapid predicions of Xist interactions validate by eCLIP.png
The lab developed the catRAPID method (Bellucci et al., Agostini et al. .; Cirillo et al., ) methods to identify protein partners of non-coding transcripts such as XIST (18000 nt). Top: Predicted binding regions of different proteins, including PTBP1, LBR, SPEN, HNRNPK, HNRNPU and DKC1 (ranked by interaction propensity); Bottom: eCLIP validation of the binding regions. Protein DKC1 is used as a negative control.

Solubility as an engine of evolution

In the period 2007–2010, Gian Tartaglia investigated the relationship between expression and solubility of gene. [17] He found a close link between mRNA expression levels and protein aggregation rates. The original observations were published in Trends in Biological Science Solubility as an engine of evolution. [18] An experimental follow up was published in Journal of the American Chemical Society. [19] Based on the experimental results, he developed an approach for prediction of heterologous expression in E. coli. [20]

Rationalizing the determinants of protein aggregation

In the period 2009-2012 Tartaglia studied the toxicity of protein aggregates in the cellular context and determined the fraction of proteome that interacts with insoluble aggregates. [21] He also studied interactions with molecular chaperones [20] and their role in preventing aggregation. [22]

In 2008 Tartaglia developed a method to predict the kinetics of aggregation under a variety of environmental conditions. For several years, the method has been one of the top cited articles in the Journal of Molecular Biology. [23] Importantly, Gian used the algorithm to design protein toxins that were expressed in the central nervous system of D. melanogaster (Biophysical Journal [24] and PLoS Biology [25] ).

In 2004–2005, Gian Tartaglia developed the first parameter-free set of equations to predict aggregation rates of proteins using physico-chemical properties. The method reproduces to a remarkable extent the changes of aggregation rates observed in vitro for a large set of peptide and proteins, including those associated with neurological disease. The articles are highly cited. [26] [27]

Key publications

References

  1. ↑ "The Role of Non-coding RNA in Protein Networks and Neurodegenerative Diseases | RIBOMYLOME Project | Fact Sheet | FP7". CORDIS | European Commission.
  2. ↑ "ICREA". www.icrea.cat.
  3. ↑ "Home | Sapienza Università di Roma". www.uniroma1.it.
  4. ↑ "List of Proposals selected for funding – Synergy 2019" (PDF). erc.europa.eu.
  5. 1 2 3 4 5 Sanchez De Groot, Natalia; Armaos, Alexandros; Graña-Montes, Ricardo; Alriquet, Marion; Calloni, Giulia; Vabulas, R. Martin; Tartaglia, Gian Gaetano (2019). "RNA structure drives interaction with proteins". Nature Communications. 10 (1): 3246. Bibcode:2019NatCo..10.3246S. doi:10.1038/s41467-019-10923-5. PMC   6642211 . PMID   31324771.
  6. ↑ Vandelli, andrea (2020). "CROSSalive: A Web Server for Predicting the in Vivo Structure of RNA Molecules". Bioinformatics. 36 (3): 940–941. doi:10.1093/bioinformatics/btz666. PMC   9883674 . PMID   31504168.
  7. ↑ Zacco, Elsa; Kantelberg, Owen; Milanetti, Edoardo; Armaos, Alexandros; Panei, Francesco Paolo; Gregory, Jenna; Jeacock, Kiani; Clarke, David J.; Chandran, Siddharthan; Ruocco, Giancarlo; Gustincich, Stefano; Horrocks, Mathew H.; Pastore, Annalisa; Tartaglia, Gian Gaetano (2022). "Probing TDP-43 condensation using an in silico designed aptamer". Nature Communications. 13 (1): 3306. Bibcode:2022NatCo..13.3306Z. doi:10.1038/s41467-022-30944-x. PMC   9226187 . PMID   35739092.
  8. ↑ Spence, Holly; Waldron, Fergal M.; Saleeb, Rebecca S.; Brown, Anna-Leigh; Rifai, Olivia M.; Gilodi, Martina; Read, Fiona; Roberts, Kristine; Milne, Gillian; Wilkinson, Debbie; o'Shaughnessy, Judi; Pastore, Annalisa; Fratta, Pietro; Shneider, Neil; Tartaglia, Gian Gaetano; Zacco, Elsa; Horrocks, Mathew H.; Gregory, Jenna M. (2024). "RNA aptamer reveals nuclear TDP-43 pathology is an early aggregation event that coincides with STMN-2 cryptic splicing and precedes clinical manifestation in ALS". Acta Neuropathologica. 147 (1): 50. doi:10.1007/s00401-024-02705-1. PMC   10914926 . PMID   38443601.
  9. ↑ Cerase, Andrea; Armaos, Alexandros; Neumayer, Christoph; Avner, Philip; Guttman, Mitchell; Tartaglia, Gian Gaetano (May 2019). "Phase separation drives X-chromosome inactivation: a hypothesis". Nature Structural & Molecular Biology. 26 (5): 331–334. doi:10.1038/s41594-019-0223-0. hdl: 11573/1279455 . PMID   31061525.
  10. ↑ "New Acquisitions on the Mechanism of Genetic Inheritance Associated with the X Chromosome".
  11. ↑ Bellucci, Matteo; Agostini, Federico; Masin, Marianela; Tartaglia, Gian Gaetano (June 2011). "Predicting protein associations with long noncoding RNAs". Nature Methods. 8 (6): 444–445. doi:10.1038/nmeth.1611. PMID   21623348.
  12. ↑ "CatRAPID, a guide to understand the role of non-coding RNAs".
  13. ↑ "Probe Noncoding RNA Biology with Protein-lncRNA Interaction Tools | Biocompare: The Buyer's Guide for Life Scientists".
  14. ↑ Bellucci, Matteo (2011). "Predicting Protein Associations With Long Noncoding RNAs". Nature Methods. 8 (6): 444–445. doi:10.1038/nmeth.1611. PMID   21623348.
  15. ↑ Agostini, Federico (2013). "X-inactivation: Quantitative Predictions of Protein Interactions in the Xist Network". Nucleic Acids Research. 41 (1): e31. doi:10.1093/nar/gks968. PMC   3592426 . PMID   23093590.
  16. ↑ Cirillo, Davive (2017). "Quantitative Predictions of Protein Interactions With Long Noncoding RNAs". Nature Methods. 14 (1): 5–6. doi:10.1038/nmeth.4100. PMID   28032625.
  17. ↑ "Life on the edge: a link between gene expression levels and aggregation rates of human proteins" (PDF). Trends in Biochemical Sciences.
  18. ↑ Tartaglia, Gian Gaetano; Pechmann, Sebastian; Dobson, Christopher M.; Vendruscolo, Michele (May 2007). "Life on the edge: a link between gene expression levels and aggregation rates of human proteins". Trends in Biochemical Sciences. 32 (5): 204–206. doi:10.1016/j.tibs.2007.03.005. PMID   17419062.
  19. ↑ Baldwin, Andrew J.; Knowles, Tuomas P. J.; Tartaglia, Gian Gaetano; Fitzpatrick, Anthony W.; Devlin, Glyn L.; Shammas, Sarah Lucy; Waudby, Christopher A.; Mossuto, Maria F.; Meehan, Sarah; Gras, Sally L.; Christodoulou, John; Anthony-Cahill, Spencer J.; Barker, Paul D.; Vendruscolo, Michele; Dobson, Christopher M. (14 September 2011). "Metastability of Native Proteins and the Phenomenon of Amyloid Formation". Journal of the American Chemical Society. 133 (36): 14160–14163. Bibcode:2011JAChS.13314160B. doi:10.1021/ja2017703. hdl: 11573/1451766 . PMID   21650202.
  20. 1 2 Tartaglia, Gian Gaetano; Pechmann, Sebastian; Dobson, Christopher M.; Vendruscolo, Michele (May 2009). "A Relationship between mRNA Expression Levels and Protein Solubility in E. coli". Journal of Molecular Biology. 388 (2): 381–389. doi:10.1016/j.jmb.2009.03.002. PMID   19281824.
  21. ↑ Olzscha, Heidi; Schermann, Sonya M.; Woerner, Andreas C.; Pinkert, Stefan; Hecht, Michael H.; Tartaglia, Gian G.; Vendruscolo, Michele; Hayer-Hartl, Manajit; Hartl, F. Ulrich; Vabulas, R. Martin (January 2011). "Amyloid-like Aggregates Sequester Numerous Metastable Proteins with Essential Cellular Functions". Cell. 144 (1): 67–78. doi:10.1016/j.cell.2010.11.050. hdl: 11573/1287804 . PMID   21215370.
  22. ↑ Calloni, Giulia; Chen, Taotao; Schermann, Sonya M.; Chang, Hung-chun; Genevaux, Pierre; Agostini, Federico; Tartaglia, Gian Gaetano; Hayer-Hartl, Manajit; Hartl, F. Ulrich (March 2012). "DnaK Functions as a Central Hub in the E. coli Chaperone Network". Cell Reports. 1 (3): 251–264. doi:10.1016/j.celrep.2011.12.007. hdl: 10230/24950 . PMID   22832197.
  23. ↑ Tartaglia, Gian Gaetano; Pawar, Amol P.; Campioni, Silvia; Dobson, Christopher M.; Chiti, Fabrizio; Vendruscolo, Michele (July 2008). "Prediction of Aggregation-Prone Regions in Structured Proteins". Journal of Molecular Biology. 380 (2): 425–436. doi:10.1016/j.jmb.2008.05.013. PMID   18514226.
  24. ↑ Brorsson, Ann-Christin; Bolognesi, Benedetta; Tartaglia, Gian Gaetano; Shammas, Sarah L.; Favrin, Giorgio; Watson, Ian; Lomas, David A.; Chiti, Fabrizio; Vendruscolo, Michele; Dobson, Christopher M.; Crowther, Damian C.; Luheshi, Leila M. (April 2010). "Intrinsic Determinants of Neurotoxic Aggregate Formation by the Amyloid β Peptide". Biophysical Journal. 98 (8): 1677–1684. Bibcode:2010BpJ....98.1677B. doi:10.1016/j.bpj.2009.12.4320. PMC   2856165 . PMID   20409489.
  25. ↑ Luheshi, Leila M.; Tartaglia, Gian Gaetano; Brorsson, Ann-Christin; Pawar, Amol P.; Watson, Ian E.; Chiti, Fabrizio; Vendruscolo, Michele; Lomas, David A.; Dobson, Christopher M.; Crowther, Damian C. (October 30, 2007). "Systematic in vivo analysis of the intrinsic determinants of amyloid Beta pathogenicity". PLOS Biology. 5 (11): e290. doi: 10.1371/journal.pbio.0050290 . PMC   2043051 . PMID   17973577.
  26. ↑ Tartaglia, Gian Gaetano; Cavalli, Andrea; Pellarin, Riccardo; Caflisch, Amedeo (July 4, 2004). "The role of aromaticity, exposed surface, and dipole moment in determining protein aggregation rates". Protein Science. 13 (7): 1939–1941. doi:10.1110/ps.04663504. PMC   2279921 . PMID   15169952.
  27. ↑ Tartaglia, Gian Gaetano; Cavalli, Andrea; Pellarin, Riccardo; Caflisch, Amedeo (October 4, 2005). "Prediction of aggregation rate and aggregation-prone segments in polypeptide sequences". Protein Science. 14 (10): 2723–2734. doi:10.1110/ps.051471205. PMC   2253302 . PMID   16195556.
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