Immunoresponsive gene 1 (Irg1) is highly expressed in mammalian macrophages during inflammation, but its biological function has not yet been elucidated. Here, we identify Irg1 as the gene coding for ...an enzyme producing itaconic acid (also known as methylenesuccinic acid) through the decarboxylation of cis -aconitate, a tricarboxylic acid cycle intermediate. Using a gain-and-loss-of-function approach in both mouse and human immune cells, we found Irg1 expression levels correlating with the amounts of itaconic acid, a metabolite previously proposed to have an antimicrobial effect. We purified IRG1 protein and identified its cis -aconitate decarboxylating activity in an enzymatic assay. Itaconic acid is an organic compound that inhibits isocitrate lyase, the key enzyme of the glyoxylate shunt, a pathway essential for bacterial growth under specific conditions. Here we show that itaconic acid inhibits the growth of bacteria expressing isocitrate lyase, such as Salmonella enterica and Mycobacterium tuberculosis . Furthermore, Irg1 gene silencing in macrophages resulted in significantly decreased intracellular itaconic acid levels as well as significantly reduced antimicrobial activity during bacterial infections. Taken together, our results demonstrate that IRG1 links cellular metabolism with immune defense by catalyzing itaconic acid production.
Microglia are specialized parenchymal‐resident phagocytes of the central nervous system (CNS) that actively support, defend and modulate the neural environment. Dysfunctional microglial responses are ...thought to worsen CNS diseases; nevertheless, their impact during neuroinflammatory processes remains largely obscure. Here, using a combination of single‐cell RNA sequencing and multicolour flow cytometry, we comprehensively profile microglia in the brain of lipopolysaccharide (LPS)‐injected mice. By excluding the contribution of other immune CNS‐resident and peripheral cells, we show that microglia isolated from LPS‐injected mice display a global downregulation of their homeostatic signature together with an upregulation of inflammatory genes. Notably, we identify distinct microglial activated profiles under inflammatory conditions, which greatly differ from neurodegenerative disease‐associated profiles. These results provide insights into microglial heterogeneity and establish a resource for the identification of specific phenotypes in CNS disorders, such as neuroinflammatory and neurodegenerative diseases.
Synopsis
Using single‐cell transcriptomics and multicolour flow cytometry this study presents comprehensive profiles of microglia in LPS‐injected mice, providing insight into microglia heterogeneity, and establishing a resource for the identification of specific phenotypes in CNS disorders.
Microglia homeostatic signatures are mainly lost upon acute systemic inflammation.
Inflammation‐induced microglia segregate into two distinct reactive states.
Inflammation‐induced microglia signatures are distinct from neurodegenerative disease‐associated profiles.
Using single‐cell transcriptomics and multicolour flow cytometry this study presents comprehensive profiles of microglia in LPS‐injected mice, providing insight into microglia heterogeneity, and establishing a resource for the identification of specific phenotypes in CNS disorders.
The hallmarks of Parkinson's disease Antony, Paul M. A.; Diederich, Nico J.; Krüger, Rejko ...
The FEBS journal,
December 2013, Letnik:
280, Številka:
23
Journal Article
Recenzirano
Odprti dostop
Since the discovery of dopamine as a neurotransmitter in the 1950s, Parkinson's disease (PD) research has generated a rich and complex body of knowledge, revealing PD to be an age‐related ...multifactorial disease, influenced by both genetic and environmental factors. The tremendous complexity of the disease is increased by a nonlinear progression of the pathogenesis between molecular, cellular and organic systems. In this minireview, we explore the complexity of PD and propose a systems‐based approach, organizing the available information around cellular disease hallmarks. We encourage our peers to adopt this cell‐based view with the aim of improving communication in interdisciplinary research endeavors targeting the molecular events, modulatory cell‐to‐cell signaling pathways and emerging clinical phenotypes related to PD.
Parkinson's disease (PD) is an age‐related multifactorial disease, influenced by both genetic and environmental factors. In this minireview, we propose a systems‐based approach, organizing the available information around cellular disease hallmarks. The aim of this cell‐based view is to improve communication in interdisciplinary research endeavors targeting the molecular events, modulatory cell‐to‐cell signaling pathways and emerging clinical phenotypes related to PD.
Aging is a key risk factor for chronic diseases of the elderly. MicroRNAs regulate post-transcriptional gene silencing through base-pair binding on their target mRNAs. We identified nonlinear changes ...in age-related microRNAs by analyzing whole blood from 1334 healthy individuals. We observed a larger influence of the age as compared to the sex and provide evidence for a shift to the 5' mature form of miRNAs in healthy aging. The addition of 3059 diseased patients uncovered pan-disease and disease-specific alterations in aging profiles. Disease biomarker sets for all diseases were different between young and old patients. Computational deconvolution of whole-blood miRNAs into blood cell types suggests that cell intrinsic gene expression changes may impart greater significance than cell abundance changes to the whole blood miRNA profile. Altogether, these data provide a foundation for understanding the relationship between healthy aging and disease, and for the development of age-specific disease biomarkers.
Personalized, precision, P4, or stratified medicine is understood as a medical approach in which patients are stratified based on their disease subtype, risk, prognosis, or treatment response using ...specialized diagnostic tests. The key idea is to base medical decisions on individual patient characteristics, including molecular and behavioral biomarkers, rather than on population averages. Personalized medicine is deeply connected to and dependent on data science, specifically machine learning (often named Artificial Intelligence in the mainstream media). While during recent years there has been a lot of enthusiasm about the potential of 'big data' and machine learning-based solutions, there exist only few examples that impact current clinical practice. The lack of impact on clinical practice can largely be attributed to insufficient performance of predictive models, difficulties to interpret complex model predictions, and lack of validation via prospective clinical trials that demonstrate a clear benefit compared to the standard of care. In this paper, we review the potential of state-of-the-art data science approaches for personalized medicine, discuss open challenges, and highlight directions that may help to overcome them in the future.
There is a need for an interdisciplinary effort, including data scientists, physicians, patient advocates, regulatory agencies, and health insurance organizations. Partially unrealistic expectations and concerns about data science-based solutions need to be better managed. In parallel, computational methods must advance more to provide direct benefit to clinical practice.
Researchers around the world join forces to reconstruct the molecular processes of the virus-host interactions aiming to combat the cause of the ongoing pandemic.
The phenotypic changes of microglia in brain diseases are particularly diverse and their role in disease progression, beneficial, or detrimental, is still elusive. High‐throughput molecular ...approaches such as single‐cell RNA‐sequencing can now resolve the high heterogeneity in microglia population for a specific physiological condition, however, the relation between the different microglial signatures and their surrounding brain microenvironment is barely understood. Thus, better tools to characterize the phenotypic variations of microglia in situ are needed, particularly for human brain postmortem samples analysis. To address this challenge, we developed MIC‐MAC, a Microglia and Immune Cells Morphologies Analyser and Classifier pipeline that semiautomatically segments, extracts, and classifies all microglia and immune cells labeled in large three‐dimensional (3D) confocal image stacks of mouse and human brain samples. Our imaging‐based approach enables automatic 3D‐morphology characterization and classification of thousands of individual microglia in situ and revealed species‐ and disease‐specific morphological phenotypes in mouse aging, human Alzheimer's disease, and dementia with Lewy Bodie's samples. MIC‐MAC is a precision diagnostic tool that allows a rapid, unbiased, and large‐scale analysis of microglia morphological states in mouse models and patient brain samples.
Main Points
MIC‐MAC is a new automated pipeline allowing for an unbiased morphological characterization and classification of thousands of microglia in mouse and human brain tissues.
MIC‐MAC is made available to the entire scientific community to measure precisely microglia modifications in brain diseases.
Abstract Chronic diseases (i.e., noncommunicable diseases), mainly cardiovascular disease, cancer, respiratory diseases and type-2-diabetes, are now the leading cause of death, disability and ...diminished quality of life on the planet. Moreover, these diseases are also a major financial burden worldwide, significantly impacting the economy of many countries. Healthcare systems and medicine have progressively improved upon the ability to address infectious diseases and react to adverse health events through both surgical interventions and pharmacology; we have become efficient in delivering reactive care (i.e., initiating interventions once an individual is on the verge of or has actually suffered a negative health event). However, with slowly progressing and often ‘silent’ chronic diseases now being the main cause of illness, healthcare and medicine must evolve into a proactive system, moving away from a merely reactive approach to care. Minimal interactions among the specialists and limited information to the general practitioner and to the individual receiving care lead to a fragmented health approach, non-concerted prescriptions, a scattered follow-up and a suboptimal cost-effectiveness ratio. A new approach in medicine that is predictive, preventive, personalized and participatory, which we label here as “P4” holds great promise to reduce the burden of chronic diseases by harnessing technology and an increasingly better understanding of environment-biology interactions, evidence-based interventions and the underlying mechanisms of chronic diseases. In this concept paper, we propose a ‘P4 Health Continuum’ model as a framework to promote and facilitate multi-stakeholder collaboration with an orchestrated common language and an integrated care model to increase the healthspan.
Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD ...pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at
http://minerva.uni.lu/pd_map
.
Common variants of about 20 genes contributing to AD risk have so far been identified through genome-wide association studies (GWAS). However, there is still a large proportion of heritability that ...might be explained by rare but functionally important variants. One of the so far identified genes with rare AD causing variants is ADAM10. Using whole-genome sequencing we now identified a single rare nonsynonymous variant (SNV) rs142946965 p.R215I in ADAM17 co-segregating with an autosomal-dominant pattern of late-onset AD in one family. Subsequent genotyping and analysis of available whole-exome sequencing data of additional case/control samples from Germany, UK, and USA identified five variant carriers among AD patients only. The mutation inhibits pro-protein cleavage and the formation of the active enzyme, thus leading to loss-of-function of ADAM17 alpha-secretase. Further, we identified a strong negative correlation between ADAM17 and APP gene expression in human brain and present in vitro evidence that ADAM17 negatively controls the expression of APP. As a consequence, p.R215I mutation of ADAM17 leads to elevated Aß formation in vitro. Together our data supports a causative association of the identified ADAM17 variant in the pathogenesis of AD.
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