T-Cell Artificial Focal Triggering Tools: Linking Surface Interactions with Cell Response

T-cell activation is a key event in the immune system, involving the interaction of several receptor ligand pairs in a complex intercellular contact that forms between T-cell and antigen-presenting cells. Molecular components implicated in contact formation have been identified, but the mechanism of activation and the link between molecular interactions and cell response remain poorly understood due to the complexity and dynamics exhibited by whole cell-cell conjugates. Here we demonstrate that simplified model colloids grafted so as to target appropriate cell receptors can be efficiently used to explore the relationship of receptor engagement to the T-cell response. Using immortalized Jurkat T cells, we monitored both binding and activation events, as seen by changes in the intracellular calcium concentration. Our experimental strategy used flow cytometry analysis to follow the short time scale cell response in populations of thousands of cells. We targeted both T-cell receptor CD3 (TCR/CD3) and leukocyte-function-associated antigen (LFA-1) alone or in combination. We showed that specific engagement of TCR/CD3 with a single particle induced a transient calcium signal, confirming previous results and validating our approach. By decreasing anti-CD3 particle density, we showed that contact nucleation was the most crucial and determining step in the cell-particle interaction under dynamic conditions, due to shear stress produced by hydrodynamic flow. Introduction of LFA-1 adhesion molecule ligands at the surface of the particle overcame this limitation and elucidated the low TCR/CD3 ligand density regime. Despite their simplicity, model colloids induced relevant biological responses which consistently echoed whole cell behavior. We thus concluded that this biophysical approach provides useful tools for investigating initial events in T-cell activation, and should enable the design of intelligent artificial systems for adoptive immunotherapy

Lysosomal protease deficiency or substrate overload induces an oxidative-stress mediated STAT3-dependent pathway of lysosomal homeostasis

How cells regulate their lysosomal proteolytic capacity is only partly understood. Here, the authors show that lysosomal protease deficiency or substrate overload induces lysosomal stress leading to activation of a STAT3-dependent, TFEB-independent pathway of lysosomal hydrolase expression

Effects of Intracellular Calcium and Actin Cytoskeleton on TCR Mobility Measured by Fluorescence Recovery

Background: The activation of T lymphocytes by specific antigen is accompanied by the formation of a specialized signaling region termed the immunological synapse, characterized by the clustering and segregation of surface molecules and, in particular, by T cell receptor (TCR) clustering. Methodology/Principal Findings: To better understand TCR motion during cellular activation, we used confocal microscopy and photo-bleaching recovery techniques to investigate the lateral mobility of TCR on the surface of human T lymphocytes under various pharmacological treatments. Using drugs that cause an increase in intracellular calcium, we observed a decrease in TCR mobility that was dependent on a functional actin cytoskeleton. In parallel experiments measurement of filamentous actin by FACS analysis showed that raising intracellular calcium also causes increased polymerization of the actin cytoskeleton. These in vitro results were analyzed using a mathematical model that revealed effective binding parameters between TCR and the actin cytoskeleton. Conclusion/Significance: We propose, based on our results, that increase in intracellular calcium levels leads to actin polymerization and increases TCR/cytoskeleton interactions that reduce the overall mobility of the TCR. In a physiological setting, this may contribute to TCR re-positioning at the immunological synapse

Accumulation of neutral lipids in peripheral blood mononuclear cells as a distinctive trait of Alzheimer patients and asymptomatic subjects at risk of disease

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease is the most common progressive neurodegenerative disease. In recent years, numerous progresses in the discovery of novel Alzheimer's disease molecular biomarkers in brain as well as in biological fluids have been made. Among them, those involving lipid metabolism are emerging as potential candidates. In particular, an accumulation of neutral lipids was recently found by us in skin fibroblasts from Alzheimer's disease patients. Therefore, with the aim to assess whether peripheral alterations in cholesterol homeostasis might be relevant in Alzheimer's disease development and progression, in the present study we analyzed lipid metabolism in plasma and peripheral blood mononuclear cells from Alzheimer's disease patients and from their first-degree relatives.</p> <p>Methods</p> <p>Blood samples were obtained from 93 patients with probable Alzheimer's disease and from 91 of their first-degree relatives. As controls we utilized 57, cognitively normal, over-65 year-old volunteers and 113 blood donors aged 21-66 years, respectively. Data are reported as mean ± standard error. Statistical calculations were performed using the statistical analysis software Origin 8.0 version. Data analysis was done using the Student t-test and the Pearson test.</p> <p>Results</p> <p>Data reported here show high neutral lipid levels and increased ACAT-1 protein in about 85% of peripheral blood mononuclear cells freshly isolated (<it>ex vivo</it>) from patients with probable sporadic Alzheimer's disease compared to about 7% of cognitively normal age-matched controls. A significant reduction in high density lipoprotein-cholesterol levels in plasma from Alzheimer's disease blood samples was also observed. Additionally, correlation analyses reveal a negative correlation between high density lipoprotein-cholesterol and cognitive capacity, as determined by Mini Mental State Examination, as well as between high density lipoprotein-cholesterol and neutral lipid accumulation. We observed great variability in the neutral lipid-peripheral blood mononuclear cells data and in plasma lipid analysis of the subjects enrolled as Alzheimer's disease-first-degree relatives. However, about 30% of them tend to display a peripheral metabolic cholesterol pattern similar to that exhibited by Alzheimer's disease patients.</p> <p>Conclusion</p> <p>We suggest that neutral lipid-peripheral blood mononuclear cells and plasma high density lipoprotein-cholesterol determinations might be of interest to outline a distinctive metabolic profile applying to both Alzheimer's disease patients and asymptomatic subjects at higher risk of disease.</p

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

Characterization techniques for studying the properties of nanocarriers for systemic delivery

Nanocarriers have attracted a huge interest in the last decade as efficient drug delivery systems and diagnostic tools. They enable effective, targeted, controlled delivery of therapeutic molecules while lowering the side effects caused during the treatment. The physicochemical properties of nanoparticles determine their in vivo pharmacokinetics, biodistribution and tolerability. The most analyzed among these physicochemical properties are shape, size, surface charge and porosity and several techniques have been used to characterize these specific properties. These different techniques assess the particles under varying conditions, such as physical state, solvents etc. and as such probe, in addition to the particles themselves, artifacts due to sample preparation or environment during measurement. Here, we discuss the different methods to precisely evaluate these properties, including their advantages or disadvantages. In several cases, there are physical properties that can be evaluated by more than one technique. Different strengths and limitations of each technique complicate the choice of the most suitable method, while often a combinatorial characterization approach is needed

Perspectives on tracking data reuse across biodata resources

c The Author(s) 2024. Published by Oxford University Press.Motivation: Data reuse is a common and vital practice in molecular biology and enables the knowledge gathered over recent decades to drive discovery and innovation in the life sciences. Much of this knowledge has been collated into molecular biology databases, such as UniProtKB, and these resources derive enormous value from sharing data among themselves. However, quantifying and documenting this kind of data reuse remains a challenge. Results: The article reports on a one-day virtual workshop hosted by the UniProt Consortium in March 2023, attended by representatives from biodata resources, experts in data management, and NIH program managers. Workshop discussions focused on strategies for tracking data reuse, best practices for reusing data, and the challenges associated with data reuse and tracking. Surveys and discussions showed that data reuse is widespread, but critical information for reproducibility is sometimes lacking. Challenges include costs of tracking data reuse, tensions between tracking data and open sharing, restrictive licenses, and difficulties in tracking commercial data use. Recommendations that emerged from the discussion include: development of standardized formats for documenting data reuse, education about the obstacles posed by restrictive licenses, and continued recognition by funding agencies that data management is a critical activity that requires dedicated resources

The Gene Ontology resource: enriching a GOld mine

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project