Trotti Research

Name: Davide Trotti, PhD
Position: Professor, Department of Neuroscience
Organization: Sidney Kimmel Medical College
Contact Number(s):

Our laboratory – as integral part of the Weinberg ALS Center - is dedicated to deciphering the molecular and cellular mechanisms driving neurodegenerative diseases, particularly ALS and FTD. We leverage cutting-edge models, including patient iPSC-derived neurons, 3D neural cultures, and mouse models, combined with advanced imaging and computational analysis. Our aim is to uncover novel therapeutic targets and biomarkers, paving the way for effective treatments for these debilitating conditions. 

Our laboratory is dedicated to unraveling the complex and multifaceted mechanisms underlying Amyotrophic Lateral Sclerosis (ALS), with a particular focus on identifying novel therapeutic targets. To achieve this, we employ advanced 3D cortical organoid models, which allow us to simulate and study the human brain environment in a more physiologically relevant manner. These models are instrumental in investigating the role of neuroinflammation, a critical factor in ALS progression, and how it contributes to the deterioration of motor neurons. By combining these innovative approaches with other cutting-edge techniques, we aim to uncover key insights into the pathogenesis of ALS, ultimately guiding the development of effective therapeutic strategies.

Key Research Areas

Transposable Elements & Innate Immunity

In our research on transposable elements and innate immunity, we focus on the complex interplay between mobile genetic elements and the body's innate immune responses. Notably, we have identified a novel pathway in Alzheimer’s disease and ALS that links aberrant HERVK activation, RNA-DNA hybrid formation, and cGAS-STING-mediated neuroinflammation. This discovery highlights how transposable elements, traditionally viewed as contributors to genomic instability, can also drive immune responses that exacerbate neurodegeneration. Our work aims to further unravel these mechanisms, offering potential new targets for therapeutic intervention in ALS and other related disorders.

Extracellular Vesicles (EVs) & Neuroinflammation

We investigate the critical role EVs play in transmitting disease-associated factors in ALS. Our studies focus on how these vesicles contribute to neuroinflammation, particularly in the context of C9ORF72 mutations. We also explore the potential of EVs as therapeutic carriers, aiming to harness their properties to mitigate disease progression. By understanding the impact of EVs in ALS, we strive to uncover new therapeutic strategies that could offer relief to those affected by this debilitating condition.

Senescence & Neurodegenerative Disease

In our lab, we study senescence in the context of neurodegenerative diseases by investigating how the accumulation of senescent cells within the nervous system contributes to disease progression. We utilize a combination of cellular models, including patient-derived iPSCs and brain organoids, to recreate the neurodegenerative environment and induce senescence in specific cell types, such as neurons and glial cells. Advanced techniques like single-cell RNA sequencing, imaging, and biomarker analysis allow us to identify and characterize senescent cells, focusing on their secretory phenotype and its impact on surrounding tissues. Additionally, we explore the role of senescence-associated pathways, such as the p53 and p16INK4a pathways, in driving neuroinflammation and cellular dysfunction. Our goal is to understand the molecular mechanisms by which senescence exacerbates neurodegeneration and to identify potential interventions that could mitigate these effects, ultimately contributing to the development of therapeutic strategies for diseases like ALS and FTD.

Computational Biology

At the ALS Center, our team of scientists specializing in Computational Biology, and Bioinformatics is dedicated to supporting data analysis and data visualization across a wide range of experiments and research studies. Leveraging cutting-edge methodologies, we develop robust data processing pipelines for single-cell and spatial multi-omics, as well as transcriptomic, proteomic, and complex imaging analyses. This integrated approach is crucial for identifying predictive biomarkers and uncovering novel therapeutic targets.