Unravelling the molecular mechanisms of HIV associated neurocognitive disorders through mass spectrometry-based proteomics

A significant proportion of human immunodeficiency virus type 1 (HIV)-positive individuals are affected by the cognitive, motor and behavioural dysfunction that characterises HIV associated neurocognitive disorders. While the molecular aetiology of this important HIV complication remains largely uncharacterised, HIV transactivator of transcription (HIV-Tat) has been identified as a plausible aetiological cause. Here we have used mass spectrometry-based discovery proteomics to identify the quantitative, cell-wide changes that occur when non-transformed, differentiated human neurons are treated with HIV-Tat over time, as a novel cell culture model representing the initial progression of HIV associated neurocognitive disorders, and as a means to identify putative biomarkers for the illness. We found that our stem cell-based model system displayed morphological and functional neuronal properties and using a Q-Exactive mass spectrometer, we identified over 4000 protein groups (FDR < 0.01) in this system with 131,118 and 45 protein groups differentially expressed at 6, 24 and 48 hours post treatment, respectively. We found changes to the gene expression machinery (nucleic acid binding proteins), which suggests that HIV-Tat is involved in preparing the host cell for altered transcriptional and translational activity. We also found cytoskeletal dysregulation in response to HIV-Tat treatment. The 24-hour time point of the time course experiment was largely corroborated with a repeat experiment. A repeat of the entire time course experiment at a lower cell confluence showed that the effect of HIV-Tat treatment to the gene expression machinery was unchanged by cell confluence, while the effect to cytoskeletal proteins upon HIV-Tat treatment was present, but less prominent, in lower cell confluence samples. We hypothesise that the gene-expression-machinery effect may be a biphasic response. We further hypothesise that cytoskeletal dysregulation may form part of the molecular mechanism responsible for synaptic injury - as the cytoskeleton is crucial for synapse development and maintenance - and may contribute to memory impairment in HIV associated neurocognitive disorder patients

“Be sustainable”: EOSC‐Life recommendations for implementation of FAIR principles in life science data handling

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large‐scale data‐driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross‐disciplinary work done within the EOSC‐Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC‐Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive‐ and industry‐related resources, by means of cross‐disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences

Preprint: "Be Sustainable", Recommendations for FAIR Resources in Life Sciences research: EOSC-Life's Lessons

"Be SURE - Be SUstainable REcommendations" The main goals and challenges for the Life Science (LS) communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable LS resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European LS Research Infrastructures (RIs), it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable FAIR data management, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences. IN PRESS EMBO Journal: https://www.embopress.org/journal/14602075This research is mainly a product of the EOSC-Life European programme funding from the European Union's Horizon Europe research and innovation programme under grant agreement Nº824087. Complementary support was provided through EU funded project AgroServ (grant agreement Nº101058020), EU funded project BY-COVID (grant agreement Nº101046203), EU funded project DANUBIUS-IP (grant agreement Nº101079778), EU funded project EMPHASIS-GO (grant agreement Nº101079772), EU funded project FAIRplus (IMI grant agreement Nº802750), EU funded project FAIRsharing (Wellcome grant agreement Nº212930/Z/18/Z), EU funded project ISIDORe (grant agreement Nº101046133), EU funded project Precision Toxicology (grant agreement Nº965406), UKRI DASH (grant agreement NºMR/V038966/1). Special thanks to T. Biro and her radical collaboration team from Research Data Alliance who gave us great inspiration on how to lead this radical collaboration work