Multi-omics integration of scRNA-seq time series data predicts new intervention points for Parkinson's disease.

Parkinson's disease (PD) is a complex neurodegenerative disorder without a cure. The onset of PD symptoms corresponds to 50% loss of midbrain dopaminergic (mDA) neurons, limiting early-stage understanding of PD. To shed light on early PD development, we study time series scRNA-seq datasets of mDA neurons obtained from patient-derived induced pluripotent stem cell differentiation. We develop a new data integration method based on Non-negative Matrix Tri-Factorization that integrates these datasets with molecular interaction networks, producing condition-specific "gene embeddings". By mining these embeddings, we predict 193 PD-related genes that are largely supported (49.7%) in the literature and are specific to the investigated PINK1 mutation. Enrichment analysis in Kyoto Encyclopedia of Genes and Genomes pathways highlights 10 PD-related molecular mechanisms perturbed during early PD development. Finally, investigating the top 20 prioritized genes reveals 12 previously unrecognized genes associated with PD that represent interesting drug targets.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts.

BACKGROUND: A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials. METHODS: Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors. RESULTS: We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components. CONCLUSIONS: Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Calcium oscillations optimize the energetic efficiency of mitochondrial metabolism.

Energy transduction is central to living organisms, but the impact of enzyme regulation and signaling on its thermodynamic efficiency is generally overlooked. Here, we analyze the efficiency of ATP production by the tricarboxylic acid cycle and oxidative phosphorylation, which generate most of the chemical energy in eukaryotes. Calcium signaling regulates this pathway and can affect its energetic output, but the concrete energetic impact of this cross-talk remains elusive. Calcium enhances ATP production by activating key enzymes of the tricarboxylic acid cycle while calcium homeostasis is ATP-dependent. We propose a detailed kinetic model describing the calcium-mitochondria cross-talk and analyze it using nonequilibrium thermodynamics: after identifying the effective reactions driving mitochondrial metabolism out of equilibrium, we quantify the mitochondrial thermodynamic efficiency for different conditions. Calcium oscillations, triggered by extracellular stimulation or energy deficiency, boost the thermodynamic efficiency of mitochondrial metabolism, suggesting a compensatory role of calcium signaling in mitochondrial bioenergetics.

Early-to-mid stage idiopathic Parkinson's disease shows enhanced cytotoxicity and differentiation in CD8 T-cells in females.

Neuroinflammation in the brain contributes to the pathogenesis of Parkinson's disease (PD), but the potential dysregulation of peripheral immunity has not been systematically investigated for idiopathic PD (iPD). Here we showed an elevated peripheral cytotoxic immune milieu, with more terminally-differentiated effector memory (TEMRA) CD8 T, CD8+ NKT cells and circulating cytotoxic molecules in fresh blood of patients with early-to-mid iPD, especially females, after analyzing > 700 innate and adaptive immune features. This profile, also reflected by fewer CD8+FOXP3+ T cells, was confirmed in another subcohort. Co-expression between cytotoxic molecules was selectively enhanced in CD8 TEMRA and effector memory (TEM) cells. Single-cell RNA-sequencing analysis demonstrated the accelerated differentiation within CD8 compartments, enhanced cytotoxic pathways in CD8 TEMRA and TEM cells, while CD8 central memory (TCM) and naïve cells were already more-active and transcriptionally-reprogrammed. Our work provides a comprehensive map of dysregulated peripheral immunity in iPD, proposing candidates for early diagnosis and treatments.

Mechanistic multiscale modelling of energy metabolism in human astrocytes reveals the impact of morphology changes in Alzheimer's Disease.

Astrocytes with their specialised morphology are essential for brain homeostasis as metabolic mediators between blood vessels and neurons. In neurodegenerative diseases such as Alzheimer's disease (AD), astrocytes adopt reactive profiles with molecular and morphological changes that could lead to the impairment of their metabolic support and impact disease progression. However, the underlying mechanisms of how the metabolic function of human astrocytes is impaired by their morphological changes in AD are still elusive. To address this challenge, we developed and applied a metabolic multiscale modelling approach integrating the dynamics of metabolic energy pathways and physiological astrocyte morphologies acquired in human AD and age-matched control brain samples. The results demonstrate that the complex cell shape and intracellular organisation of energetic pathways determine the metabolic profile and support capacity of astrocytes in health and AD conditions. Thus, our mechanistic approach indicates the importance of spatial orchestration in metabolism and allows for the identification of protective mechanisms against disease-associated metabolic impairments.

Formate promotes invasion and metastasis in reliance on lipid metabolism.

Metabolic rewiring is essential for cancer onset and progression. We previously showed that one-carbon metabolism-dependent formate production often exceeds the anabolic demand of cancer cells, resulting in formate overflow. Furthermore, we showed that increased extracellular formate concentrations promote the in vitro invasiveness of glioblastoma cells. Here, we substantiate these initial observations with ex vivo and in vivo experiments. We also show that exposure to exogeneous formate can prime cancer cells toward a pro-invasive phenotype leading to increased metastasis formation in vivo. Our results suggest that the increased local formate concentration within the tumor microenvironment can be one factor to promote metastases. Additionally, we describe a mechanistic interplay between formate-dependent increased invasiveness and adaptations of lipid metabolism and matrix metalloproteinase activity. Our findings consolidate the role of formate as pro-invasive metabolite and warrant further research to better understand the interplay between formate and lipid metabolism.

Seizure-induced increase in microglial cell population in the developing zebrafish brain.

Epilepsy is a chronic brain disorder characterized by unprovoked and recurrent seizures, of which 60% are of unknown etiology. Recent studies implicate microglia in the pathophysiology of epilepsy. However, their role in this process, in particular following early-life seizures, remains poorly understood due in part to the lack of suitable experimental models allowing the in vivo imaging of microglial activity. Given the advantage of zebrafish larvae for minimally-invasive imaging approaches, we sought for the first time to describe the microglial responses after acute seizures in two different zebrafish larval models: a chemically-induced epileptic model by the systemic injection of kainate at 3 days post-fertilization, and the didys552 genetic epilepsy model, which carries a mutation in scn1lab that leads to spontaneous epileptiform discharges. Kainate-treated larvae exhibited transient brain damage as shown by increased numbers of apoptotic nuclei as early as one day post-injection, which was followed by an increase in the number of microglia in the brain. A similar microglial phenotype was also observed in didys552-/- mutants, suggesting that microglia numbers change in response to seizure-like activity in the brain. Interestingly, kainate-treated larvae also displayed a decreased seizure threshold towards subsequent pentylenetetrazole-induced seizures, as shown by higher locomotor and encephalographic activity in comparison with vehicle-injected larvae. These results are comparable to kainate-induced rodent seizure models and suggest the suitability of these zebrafish seizure models for future studies, in particular to elucidate the links between epileptogenesis and microglial dynamic changes after seizure induction in the developing brain, and to understand how these modulate seizure susceptibility.

Systematic analysis and optimization of early warning signals for critical transitions using distribution data.

Abrupt shifts between alternative regimes occur in complex systems, from cell regulation to brain functions to ecosystems. Several model-free early warning signals (EWS) have been proposed to detect impending transitions, but failure or poor performance in some systems have called for better investigation of their generic applicability. Notably, there are still ongoing debates whether such signals can be successfully extracted from data in particular from biological experiments. In this work, we systematically investigate properties and performance of dynamical EWS in different deteriorating conditions, and we propose an optimized combination to trigger warnings as early as possible, eventually verified on experimental data from microbiological populations. Our results explain discrepancies observed in the literature between warning signs extracted from simulated models and from real data, provide guidance for EWS selection based on desired systems and suggest an optimized composite indicator to alert for impending critical transitions using distribution data.

Single-cell transcriptomics of NRAS-mutated melanoma transitioning to drug resistance reveals P2RX7 as an indicator of early drug response.

Treatment options for patients with NRAS-mutant melanoma are limited and lack an efficient targeted drug combination that significantly increases overall and progression-free survival. In addition, targeted therapy success is hampered by the inevitable emergence of drug resistance. A thorough understanding of the molecular processes driving cancer cells' escape mechanisms is crucial to tailor more efficient follow-up therapies. We performed single-cell RNA sequencing of NRAS-mutant melanoma treated with MEK1/2 plus CDK4/6 inhibitors to decipher transcriptional transitions during the development of drug resistance. Cell lines resuming full proliferation (FACs [fast-adapting cells]) and cells that became senescent (SACs [slow-adapting cells]) over prolonged treatment were identified. The early drug response was characterized by transitional states involving increased ion signaling, driven by upregulation of the ATP-gated ion channel P2RX7. P2RX7 activation was associated with improved therapy responses and, in combination with targeted drugs, could contribute to the delayed onset of acquired resistance in NRAS-mutant melanoma.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts.

Background: A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials. Methods: Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA-sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors. Results: We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components. Conclusions: Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Buffering variability in cell regulation motifs close to criticality.

Bistable biological regulatory systems need to cope with stochastic noise to fine tune their function close to bifurcation points. Here, we study stability properties of this regime in generic systems to demonstrate that cooperative interactions buffer system variability, hampering noise-induced regime shifts. Our analysis also shows that, in the considered cooperativity range, impending regime shifts can be generically detected by statistical early warning signals from distributional data. Our generic framework, based on minimal models, can be used to extract robustness and variability properties of more complex models and empirical data close to criticality.

Single-Cell Transcriptional Profiling and Gene Regulatory Network Modeling in Tg2576 Mice Reveal Gender-Dependent Molecular Features Preceding Alzheimer-Like Pathologies.

Alzheimer's disease (AD) onset and progression is influenced by a complex interplay of several environmental and genetic factors, one of them gender. Pronounced gender differences have been observed both in the relative risk of developing AD and in clinical disease manifestations. A molecular level understanding of these gender disparities is still missing, but could provide important clues on cellular mechanisms modulating the disease and reveal new targets for gender-oriented disease-modifying precision therapies. We therefore present here a comprehensive single-cell analysis of disease-associated molecular gender differences in transcriptomics data from the neocortex, one of the brain regions most susceptible to AD, in one of the most widely used AD mouse models, the Tg2576 model. Cortical areas are also most commonly used in studies of post-mortem AD brains. To identify disease-linked molecular processes that occur before the onset of detectable neuropathology, we focused our analyses on an age with no detectable plaques and microgliosis. Cell-type specific alterations were investigated at the level of individual genes, pathways, and gene regulatory networks. The number of differentially expressed genes (DEGs) was not large enough to build context-specific gene regulatory networks for each individual cell type, and thus, we focused on the study of cell types with dominant changes and included analyses of changes across the combination of cell types. We observed significant disease-associated gender differences in cellular processes related to synapse organization and reactive oxygen species metabolism, and identified a limited set of transcription factors, including Egr1 and Klf6, as key regulators of many of the disease-associated and gender-dependent gene expression changes in the model. Overall, our analyses revealed significant cell-type specific gene expression changes in individual genes, pathways and sub-networks, including gender-specific and gender-dimorphic changes in both upstream transcription factors and their downstream targets, in the Tg2576 AD model before the onset of overt disease. This opens a window into molecular events that could determine gender-susceptibility to AD, and uncovers tractable target candidates for potential gender-specific precision medicine for AD.

Elucidating tumour-associated microglia/macrophage diversity along glioblastoma progression and under ACOD1 deficiency.

In glioblastoma (GBM), tumour-associated microglia/macrophages (TAMs) represent the major cell type of the stromal compartment and contribute to tumour immune escape mechanisms. Thus, targeting TAMs is emerging as a promising strategy for immunotherapy. However, TAM heterogeneity and metabolic adaptation along GBM progression represent critical features for the design of effective TAM-targeted therapies. Here, we comprehensively study the cellular and molecular changes of TAMs in the GL261 GBM mouse model, combining single-cell RNA-sequencing with flow cytometry and immunohistological analyses along GBM progression and in the absence of Acod1 (also known as Irg1), a key gene involved in the metabolic reprogramming of macrophages towards an anti-inflammatory phenotype. Similarly to patients, we identify distinct TAM profiles, mainly based on their ontogeny, that reiterate the idea that microglia- and macrophage-like cells show key transcriptional differences and dynamically adapt along GBM stages. Notably, we uncover decreased antigen-presenting cell features and immune reactivity in TAMs along tumour progression that are instead enhanced in Acod1-deficient mice. Overall, our results provide insight into TAM heterogeneity and highlight a novel role for Acod1 in TAM adaptation during GBM progression.

Combinatorial analysis reveals highly coordinated early-stage immune reactions that predict later antiviral immunity in mild COVID-19 patients.

While immunopathology has been widely studied in patients with severe COVID-19, immune responses in non-hospitalized patients have remained largely elusive. We systematically analyze 484 peripheral cellular or soluble immune features in a longitudinal cohort of 63 mild and 15 hospitalized patients versus 14 asymptomatic and 26 household controls. We observe a transient increase of IP10/CXCL10 and interferon-ß levels, coordinated responses of dominant SARS-CoV-2-specific CD4 and fewer CD8 T cells, and various antigen-presenting and antibody-secreting cells in mild patients within 3 days of PCR diagnosis. The frequency of key innate immune cells and their functional marker expression are impaired in hospitalized patients at day 1 of inclusion. T cell and dendritic cell responses at day 1 are highly predictive for SARS-CoV-2-specific antibody responses after 3 weeks in mild but not hospitalized patients. Our systematic analysis reveals a combinatorial picture and trajectory of various arms of the highly coordinated early-stage immune responses in mild COVID-19 patients.

Generation of two human induced pluripotent stem cell lines from fibroblasts of Parkinson's disease patients carrying the ILE368ASN mutation in PINK1 (LCSBi002) and the R275W mutation in Parkin (LCSBI004).

Mutations in PINK1 and Parkin are two of the main causes of recessive early-onset Parkinson's disease (PD). We generated human induced pluripotent stem cells (hiPSCs) from fibroblasts of a 64-year-old male patient with a homozygous ILE368ASN mutation in PINK1, who experienced disease onset at 33 years, and from fibroblasts of a 61-year-old female patient heterozygous for the R275W mutation in Parkin, who experienced disease onset at 44 years. Array comparative genomic hybridization (aCGH) determined genotypic variation in each line. The cell lines were successfully used to generate midbrain dopaminergic neurons, the neuron type primarily affected in PD.

Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis.

Continuous surveillance of COVID-19 diffusion remains crucial to control its diffusion and to anticipate infection waves. Detecting viral RNA load in wastewater samples has been suggested as an effective approach for epidemic monitoring and the development of an effective warning system. However, its quantitative link to the epidemic status and the stages of outbreak is still elusive. Modelling is thus crucial to address these challenges. In this study, we present a novel mechanistic model-based approach to reconstruct the complete epidemic dynamics from SARS-CoV-2 viral load in wastewater. Our approach integrates noisy wastewater data and daily case numbers into a dynamical epidemiological model. As demonstrated for various regions and sampling protocols, it quantifies the case numbers, provides epidemic indicators and accurately infers future epidemic trends. Following its quantitative analysis, we also provide recommendations for wastewater data standards and for their use as warning indicators against new infection waves. In situations of reduced testing capacity, our modelling approach can enhance the surveillance of wastewater for early epidemic prediction and robust and cost-effective real-time monitoring of local COVID-19 dynamics.

Microglia phenotypes are associated with subregional patterns of concomitant tau, amyloid-ß and α-synuclein pathologies in the hippocampus of patients with Alzheimer's disease and dementia with Lewy bodies.

The cellular alterations of the hippocampus lead to memory decline, a shared symptom between Alzheimer's disease (AD) and dementia with Lewy Bodies (DLB) patients. However, the subregional deterioration pattern of the hippocampus differs between AD and DLB with the CA1 subfield being more severely affected in AD. The activation of microglia, the brain immune cells, could play a role in its selective volume loss. How subregional microglia populations vary within AD or DLB and across these conditions remains poorly understood. Furthermore, how the nature of the hippocampal local pathological imprint is associated with microglia responses needs to be elucidated. To this purpose, we employed an automated pipeline for analysis of 3D confocal microscopy images to assess CA1, CA3 and DG/CA4 subfields microglia responses in post-mortem hippocampal samples from late-onset AD (n = 10), DLB (n = 8) and age-matched control (CTL) (n = 11) individuals. In parallel, we performed volumetric analyses of hyperphosphorylated tau (pTau), amyloid-ß (Aß) and phosphorylated α-synuclein (pSyn) loads. For each of the 32,447 extracted microglia, 16 morphological features were measured to classify them into seven distinct morphological clusters. Our results show similar alterations of microglial morphological features and clusters in AD and DLB, but with more prominent changes in AD. We identified two distinct microglia clusters enriched in disease conditions and particularly increased in CA1 and DG/CA4 of AD and CA3 of DLB. Our study confirms frequent concomitance of pTau, Aß and pSyn loads across AD and DLB but reveals a specific subregional pattern for each type of pathology, along with a generally increased severity in AD. Furthermore, pTau and pSyn loads were highly correlated across subregions and conditions. We uncovered tight associations between microglial changes and the subfield pathological imprint. Our findings suggest that combinations and severity of subregional pTau, Aß and pSyn pathologies transform local microglia phenotypic composition in the hippocampus. The high burdens of pTau and pSyn associated with increased microglial alterations could be a factor in CA1 vulnerability in AD.

Stress hormone signalling inhibits Th1 polarization in a CD4 T-cell-intrinsic manner via mTORC1 and the circadian gene PER1.

Stress hormones are believed to skew the CD4 T-cell differentiation towards a Th2 response via a T-cell-extrinsic mechanism. Using isolated primary human naïve and memory CD4 T cells, here we show that both adrenergic- and glucocorticoid-mediated stress signalling pathways play a CD4 naïve T-cell-intrinsic role in regulating the Th1/Th2 differentiation balance. Both stress hormones reduced the Th1 programme and cytokine production by inhibiting mTORC1 signalling via two parallel mechanisms. Stress hormone signalling inhibited mTORC1 in naïve CD4 T cells (1) by affecting the PI3K/AKT pathway and (2) by regulating the expression of the circadian rhythm gene, period circadian regulator 1 (PER1). Both stress hormones induced the expression of PER1, which inhibited mTORC1 signalling, thus reducing Th1 differentiation. This previously unrecognized cell-autonomous mechanism connects stress hormone signalling with CD4 T-cell differentiation via mTORC1 and a specific circadian clock gene, namely PER1.

The benefits, costs and feasibility of a low incidence COVID-19 strategy.

In the summer of 2021, European governments removed most NPIs after experiencing prolonged second and third waves of the COVID-19 pandemic. Most countries failed to achieve immunization rates high enough to avoid resurgence of the virus. Public health strategies for autumn and winter 2021 have ranged from countries aiming at low incidence by re-introducing NPIs to accepting high incidence levels. However, such high incidence strategies almost certainly lead to the very consequences that they seek to avoid: restrictions that harm people and economies. At high incidence, the important pandemic containment measure 'test-trace-isolate-support' becomes inefficient. At that point, the spread of SARS-CoV-2 and its numerous harmful consequences can likely only be controlled through restrictions. We argue that all European countries need to pursue a low incidence strategy in a coordinated manner. Such an endeavour can only be successful if it is built on open communication and trust.

Single-cell transcriptomics of human iPSC differentiation dynamics reveal a core molecular network of Parkinson's disease.

Parkinson's disease (PD) is the second-most prevalent neurodegenerative disorder, characterized by the loss of dopaminergic neurons (mDA) in the midbrain. The underlying mechanisms are only partly understood and there is no treatment to reverse PD progression. Here, we investigated the disease mechanism using mDA neurons differentiated from human induced pluripotent stem cells (hiPSCs) carrying the ILE368ASN mutation within the PINK1 gene, which is strongly associated with PD. Single-cell RNA sequencing (RNAseq) and gene expression analysis of a PINK1-ILE368ASN and a control cell line identified genes differentially expressed during mDA neuron differentiation. Network analysis revealed that these genes form a core network, members of which interact with all known 19 protein-coding Parkinson's disease-associated genes. This core network encompasses key PD-associated pathways, including ubiquitination, mitochondrial function, protein processing, RNA metabolism, and vesicular transport. Proteomics analysis showed a consistent alteration in proteins of dopamine metabolism, indicating a defect of dopaminergic metabolism in PINK1-ILE368ASN neurons. Our findings suggest the existence of a network onto which pathways associated with PD pathology converge, and offers an inclusive interpretation of the phenotypic heterogeneity of PD.