Changes In Cell Type Composition Research Articles

Stem cell mTOR signaling directs region-specific cell fate decisions during intestinal nutrient adaptation.

The adult intestine is a regionalized organ, whose size and cellular composition are adjusted in response to nutrient status. This involves dynamic regulation of intestinal stem cell (ISC) proliferation and differentiation. How nutrient signaling controls cell fate decisions to drive regional changes in cell-type composition remains unclear. Here, we show that intestinal nutrient adaptation involves region-specific control of cell size, cell number, and differentiation. We uncovered that activation of mTOR complex 1 (mTORC1) increases ISC size in a region-specific manner. mTORC1 activity promotes Delta expression to direct cell fate toward the absorptive enteroblast lineage while inhibiting secretory enteroendocrine cell differentiation. In aged flies, the ISC mTORC1 signaling is deregulated, being constitutively high and unresponsive to diet, which can be mitigated through lifelong intermittent fasting. In conclusion, mTORC1 signaling contributes to the ISC fate decision, enabling regional control of intestinal cell differentiation in response to nutrition.

Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects

Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.

Accurate classification of major brain cell types using in vivo imaging and neural network processing.

Comprehensive analysis of tissue cell type composition using microscopic techniques has primarily been confined to ex vivo approaches. Here, we introduce NuCLear (Nucleus-instructed tissue composition using deep learning), an approach combining in vivo two-photon imaging of histone 2B-eGFP-labeled cell nuclei with subsequent deep learning-based identification of cell types from structural features of the respective cell nuclei. Using NuCLear, we were able to classify almost all cells per imaging volume in the secondary motor cortex of the mouse brain (0.25 mm3 containing approximately 25,000 cells) and to identify their position in 3D space in a noninvasive manner using only a single label throughout multiple imaging sessions. Twelve weeks after baseline, cell numbers did not change yet astrocytic nuclei significantly decreased in size. NuCLear opens a window to study changes in relative density and location of different cell types in the brains of individual mice over extended time periods, enabling comprehensive studies of changes in cell type composition in physiological and pathophysiological conditions.

TempShift Reveals the Sequential Development of Human Neocortex and Skewed Developmental Timing of Down Syndrome Brains.

Development is a complex process involving precise regulation. Developmental regulation may vary in tissues and individuals, and is often altered in disorders. Currently, the regulation of developmental timing across neocortical areas and developmental changes in Down syndrome (DS) brains remain unclear. The changes in regulation are often accompanied by changes in the gene expression trajectories, which can be divided into two scenarios: (1) changes of gene expression trajectory shape that reflect changes in cell type composition or altered molecular machinery; (2) temporal shift of gene expression trajectories that indicate different regulation of developmental timing. Therefore, we developed an R package TempShift to separates these two scenarios and demonstrated that TempShift can distinguish temporal shift from different shape (DiffShape) of expression trajectories, and can accurately estimate the time difference between multiple trajectories. We applied TempShift to identify sequential gene expression across 11 neocortical areas, which suggested sequential occurrence of synapse formation and axon guidance, as well as reconstructed interneuron migration pathways within neocortex. Comparison between healthy and DS brains revealed increased microglia, shortened neuronal migration process, and delayed synaptogenesis and myelination in DS. These applications also demonstrate the potential of TempShift in understanding gene expression temporal dynamics during different biological processes.

Single-cell transcriptomics of peripheral blood in the aging mouse.

Compositional and transcriptional changes in the hematopoietic system have been used as biomarkers of immunosenescence and aging. Here, we use single-cell RNA-sequencing to study the aging peripheral blood in mice and characterize the changes in cell-type composition and transcriptional profiles associated with age. We identified 17 clusters from a total of 14,588 single cells. We detected a general upregulation of antigen processing and presentation and chemokine signaling pathways and a downregulation of genes involved in ribosome pathways with age. In old peripheral blood, we also observed an increased percentage of cells expressing senescence markers (Cdkn1a, and Cdkn2a). In addition, we detected a cluster of activated T cells exclusively found in old blood, with lower expression of Cd28 and higher expression of Bcl2 and Cdkn2a, suggesting that the cells are senescent and resistant to apoptosis.

Lack of evidence for increased transcriptional noise in aged tissues.

Aging is often associated with a loss of cell type identity that results in an increase in transcriptional noise in aged tissues. If this phenomenon reflects a fundamental property of aging remains an open question. Transcriptional changes at the cellular level are best detected by single-cell RNA sequencing (scRNAseq). However, the diverse computational methods used for the quantification of age-related loss of cellular identity have prevented reaching meaningful conclusions by direct comparison of existing scRNAseq datasets. To address these issues we created Decibel, a Python toolkit that implements side-to-side four commonly used methods for the quantification of age-related transcriptional noise in scRNAseq data. Additionally, we developed Scallop, a novel computational method for the quantification of membership of single cells to their assigned cell type cluster. Cells with a greater Scallop membership score are transcriptionally more stable. Application of these computational tools to seven aging datasets showed large variability between tissues and datasets, suggesting that increased transcriptional noise is not a universal hallmark of aging. To understand the source of apparent loss of cell type identity associated with aging, we analyzed cell type-specific changes in transcriptional noise and the changes in cell type composition of the mammalian lung. No robust pattern of cell type-specific transcriptional noise alteration was found across aging lung datasets. In contrast, age-associated changes in cell type composition of the lung were consistently found, particularly of immune cells. These results suggest that claims of increased transcriptional noise of aged tissues should be reformulated.

Longitudinal profiling in patients undergoing cardiac surgery reveals postoperative changes in DNA methylation

BackgroundCardiac surgery and cardiopulmonary bypass induce a substantial immune and inflammatory response, the overactivation of which is associated with significant pulmonary, cardiovascular, and neurologic complications. Commensurate with the immune and inflammatory response are changes in the heart and vasculature itself, which together drive postoperative complications through mechanisms that are poorly understood. Longitudinal DNA methylation profiling has the potential to identify changes in gene regulatory mechanisms that are secondary to surgery and to identify molecular processes that predict and/or cause postoperative complications. In this study, we measure DNA methylation in preoperative and postoperative whole blood samples from 96 patients undergoing cardiac surgery on cardiopulmonary bypass.ResultsWhile the vast majority of DNA methylation is unchanged by surgery after accounting for changes in cell-type composition, we identify several loci with statistically significant postoperative changes in methylation. Additionally, two of these loci are associated with new-onset postoperative atrial fibrillation, a significant complication after cardiac surgery. Paired statistical analysis, use of FACS data to support sufficient control of cell-type heterogeneity, and measurement of IL6 levels in a subset of patients add rigor to this analysis, allowing us to distinguish cell-type variability from actual changes in methylation.ConclusionsThis study identifies significant changes in DNA methylation that occur immediately after cardiac surgery and demonstrates that these acute alterations in DNA methylation have the granularity to identify processes associated with major postoperative complications. This research also establishes methods for controlling for cell-type variability in a large human cohort that may be useful to deploy in other longitudinal studies of epigenetic marks in the setting of acute and chronic disease.

Maternal blood pressure associates with placental DNA methylation both directly and through alterations in cell-type composition

BackgroundMaternal blood pressure levels reflect cardiovascular adaptation to pregnancy and proper maternal-fetal exchanges through the placenta and are very sensitive to numerous environmental stressors. Maternal hypertension during pregnancy has been associated with impaired placental functions and with an increased risk for children to suffer from cardiovascular and respiratory diseases later on. Investigating changes in placental DNA methylation levels and cell-type composition in association with maternal blood pressure could help elucidate its relationships with placental and fetal development.MethodsTaking advantage of a large cohort of 666 participants, we investigated the association between epigenome-wide DNA methylation patterns in the placenta, measured using the Infinium HumanMethylation450 BeadChip, placental cell-type composition, estimated in silico, and repeated measurements of maternal steady and pulsatile blood pressure indicators during pregnancy.ResultsAt the site-specific level, no significant association was found between maternal blood pressure and DNA methylation levels after correction for multiple testing (false discovery rate < 0.05), but 5 out of 24 previously found CpG associations were replicated (p-value < 0.05). At the regional level, our analyses highlighted 64 differentially methylated regions significantly associated with at least one blood pressure component, including 35 regions associated with mean arterial pressure levels during late pregnancy. These regions were found enriched for genes implicated in lung development and diseases. Further mediation analyses show that a significant part of the association between steady blood pressure—but not pulsatile pressure—and placental methylation can be explained by alterations in placental cell-type composition. In particular, elevated blood pressure levels are associated with a decrease in the ratio between mesenchymal stromal cells and syncytiotrophoblasts, even in the absence of preeclampsia.ConclusionsThis study provides the first evidence that the association between maternal steady blood pressure during pregnancy and placental DNA methylation is both direct and partly explained by changes in cell-type composition. These results could hint at molecular mechanisms linking maternal hypertension to lung development and early origins of childhood respiratory problems and at the importance of controlling maternal blood pressure during pregnancy.

Insights gained from Single-Cell analysis of immune cells on Cyclosporine A treatment in autoimmune uveitis

Cyclosporine A (CsA) is a widely known immunosuppressive agent that is clinically important in autoimmune diseases owing to its selective suppression of T lymphocytes. Although it has long been recognized to inhibit T cell responses by blocking calcineurin, the potential targets and specific downstream mechanisms remain elusive. Herein, we built a comprehensive single-cell transcriptomic landscape of immune cells in the blank, untreated experimental autoimmune uveitis (EAU), and CsA-treated EAU mice. CsA reversed EAU-associated changes in cell type composition, genomic expression, cell trajectory, and cell–cell communication. We found that CsA reverses the proportion change of disease-related immune cells; regulates several crucial pathogenic factors (eg. IL1r1, CD48, and Bhlhe40) in T helper 17 cells (Th17), the transcription factor Bhlhe40 was also rescued in T helper 1 cells (Th1); and may differentiate Tregs into a state of enhanced immunosuppression. In addition, we revealed the rescued impact of CsA on all immune cell types, especially on plasma B cells differentiation and immunoglobulin secretion. Furthermore, comparisons with glucocorticoids showed that CsA might have a more premium rescue effect involved in attenuating the pathogenicity of autoreactive T cells. Our work provides a comprehensive single-cell transcriptional atlas of immune cells under CsA therapy, providing advanced insights into the mechanisms underlying CsA and a reference for developing new therapeutic strategies for autoimmune diseases.

Cell type-specific differential expression in Alzheimer’s disease and cancer using spatial transcriptomics

Abstract Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. The detection of genes that are differentially expressed across tissue context for cell types of interest is an essential challenge for dissecting pathological mechanisms. However, changes in cell type composition across space and measurement contamination from other cell types introduce complex statistical challenges. Here, we introduce a statistical method, Generalized Linear Admixture Models for Differential Expression (GLAMDE), that estimates cell type-specific patterns of differential gene expression while accounting for localization of other cell types. By modeling spatial transcriptomics gene expression as an additive mixture, across cell types, of generalized log-linear functions, we provide a unified framework for identifying gene expression changes for a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Our approach enables statistical inference across multiple samples and replicates. We demonstrate, through simulations and validation experiments on Slide-seq and MERFISH data, that our approach accurately identifies cell type-specific differential gene expression with valid uncertainty quantification. Lastly, we apply GLAMDE to characterize spatially-localized tissue changes in the context of disease. In an Alzheimer’s mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. GLAMDE is available within the spacexr R package. D.C. was supported by a Fannie and John Hertz Foundation Fellowship and an NSF Graduate Research Fellowship. This work was supported by an NIH Early Independence Award (DP5, 1DP5OD024583 to F.C.), the NHGRI (R01, R01HG010647 to F.C.), as well as the Burroughs Wellcome Fund, the Searle Scholars Award, and the Merkin Institute to F.C.. R.A.I. was supported by NIH grants R35GM131802 and R01HG005220.

Type 2 immune polarization is associated with cardiopulmonary disease in preterm infants.

Postnatal maturation of the immune system is poorly understood, as is its impact on illnesses afflicting term or preterm infants, such as bronchopulmonary dysplasia (BPD) and BPD-associated pulmonary hypertension. These are both cardiopulmonary inflammatory diseases that cause substantial mortality and morbidity with high treatment costs. Here, we characterized blood samples collected from 51 preterm infants longitudinally at five time points, 20 healthy term infants at birth and age 3 to 16 weeks, and 5 healthy adults. We observed strong associations between type 2 immune polarization in circulating CD3+CD4+ T cells and cardiopulmonary illness, with odds ratios up to 24. Maternal magnesium sulfate therapy, delayed hepatitis B vaccination, and increasing fetal, but not maternal, chorioamnionitis severity were associated with attenuated type 2 polarization. Blocking type 2 mediators such as interleukin-4 (IL-4), IL-5, IL-13, or signal transducer and activator of transcription 6 (STAT6) in murine neonatal cardiopulmonary disease in vivo prevented changes in cell type composition, increases in IL-1β and IL-13, and losses of pulmonary capillaries, but not gains in larger vessels. Thereby, type 2 blockade ameliorated lung inflammation, protected alveolar and vascular integrity, and confirmed the pathological impact of type 2 cytokines and STAT6. In-depth flow cytometry and single-cell transcriptomics of mouse lungs further revealed complex associations between immune polarization and cardiopulmonary disease. Thus, this work advances knowledge on developmental immunology and its impact on early life disease and identifies multiple therapeutic approaches that may relieve inflammation-driven suffering in the youngest patients.

Single-cell transcriptome analysis of Bisphenol A exposure reveals the key roles of the testicular microenvironment in male reproduction.

Testicular development during juvenile is crucial for subsequent male reproductive function. However, it remains poorly understood about the contribution of the testis microenvironment to human germ cell maturation. Therefore, we systematically analyzed scRNA-seq transcriptome and found the dramatic changes in cell-type composition in human testis during puberty. Then we constructed cell-cell communication networks between germ cells and somatic cells in the juvenile testis, which may be achieved via immune-related pathways. Our results showed that maturation-promoting factors are the switches of the Sertoli cells that drive sperm maturation. Furthermore, we found that Bisphenol A(BPA) enhanced the maturation and growth of germ cells through the Sertoli cell's secretory protein. Finally, our results indicate Bisphenol A would lead to the dysregulation of secreted protein expression in Sertoli cells during spermatogenesis, which in turn has direct cytotoxicity to Sertoli cells. Bisphenol A is one of the underlying causes of non-obstructive azoospermia (NOA). In summary, our results reveal the reproductive toxicity and molecular mechanism of Bisphenol A in Sertoli cells and male reproduction. Provide a reference for the toxicity of Bisphenol A to human reproduction.

Transcriptomic analysis of frontotemporal lobar degeneration with TDP-43 pathology reveals cellular alterations across multiple brain regions.

Frontotemporal lobar degeneration (FTLD) is a group of heterogeneous neurodegenerative disorders affecting the frontal and temporal lobes of the brain. Nuclear loss and cytoplasmic aggregation of the RNA-binding protein TDP-43 represents the major FTLD pathology, known as FTLD-TDP. To date, there is no effective treatment for FTLD-TDP due to an incomplete understanding of the molecular mechanisms underlying disease development. Here we compared postmortem tissue RNA-seq transcriptomes from the frontal cortex, temporal cortex, and cerebellum between 28 controls and 30 FTLD-TDP patients to profile changes in cell-type composition, gene expression and transcript usage. We observed downregulation of neuronal markers in all three regions of the brain, accompanied by upregulation of microglia, astrocytes, and oligodendrocytes, as well as endothelial cells and pericytes, suggesting shifts in both immune activation and within the vasculature. We validate our estimates of neuronal loss using neuropathological atrophy scores and show that neuronal loss in the cortex can be mainly attributed to excitatory neurons, and that increases in microglial and endothelial cell expression are highly correlated with neuronal loss. All our analyses identified a strong involvement of the cerebellum in the neurodegenerative process of FTLD-TDP. Altogether, our data provides a detailed landscape of gene expression alterations to help unravel relevant disease mechanisms in FTLD.

Predicting Lyme Disease From Patients' Peripheral Blood Mononuclear Cells Profiled With RNA-Sequencing.

Although widely prevalent, Lyme disease is still under-diagnosed and misunderstood. Here we followed 73 acute Lyme disease patients and uninfected controls over a period of a year. At each visit, RNA-sequencing was applied to profile patients' peripheral blood mononuclear cells in addition to extensive clinical phenotyping. Based on the projection of the RNA-seq data into lower dimensions, we observe that the cases are separated from controls, and almost all cases never return to cluster with the controls over time. Enrichment analysis of the differentially expressed genes between clusters identifies up-regulation of immune response genes. This observation is also supported by deconvolution analysis to identify the changes in cell type composition due to Lyme disease infection. Importantly, we developed several machine learning classifiers that attempt to perform various Lyme disease classifications. We show that Lyme patients can be distinguished from the controls as well as from COVID-19 patients, but classification was not successful in distinguishing those patients with early Lyme disease cases that would advance to develop post-treatment persistent symptoms.

Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer\u2019s Disease

Alzheimer’s disease (AD) brains are characterized by progressive neuron loss and gliosis. Previous studies of gene expression using bulk tissue samples often fail to consider changes in cell-type composition when comparing AD versus control, which can lead to differences in expression levels that are not due to transcriptional regulation. We mined five large transcriptomic AD datasets for conserved gene co-expression module, then analyzed differential expression and differential co-expression within the modules between AD samples and controls. We performed cell-type deconvolution analysis to determine whether the observed differential expression was due to changes in cell-type proportions in the samples or to transcriptional regulation. Our findings were validated using four additional datasets. We discovered that the increased expression of microglia modules in the AD samples can be explained by increased microglia proportions in the AD samples. In contrast, decreased expression and perturbed co-expression within neuron modules in the AD samples was likely due in part to altered regulation of neuronal pathways. Several transcription factors that are differentially expressed in AD might account for such altered gene regulation. Similarly, changes in gene expression and co-expression within astrocyte modules could be attributed to combined effects of astrogliosis and astrocyte gene activation. Gene expression in the astrocyte modules was also strongly correlated with clinicopathological biomarkers. Through this work, we demonstrated that combinatorial analysis can delineate the origins of transcriptomic changes in bulk tissue data and shed light on key genes and pathways involved in AD.

Abstract 3377: NSCLC subtype-associated molecular and cellular alterations in the normal-appearing bronchial epithelium

Abstract Rationale: We have previously identified lung cancer-associated gene expression alterations in normal bronchial airway epithelial cells of ever smokers with and without lung cancer. It is unclear, however, whether or not gene expression in the bronchial airway also reflects non-small cell lung cancer (NSCLC) subtypes. In this study, we sought to identify airway gene expression differences between patients with squamous (LUSC) and adenocarcinoma (LUAD) NSCLC and determine if these reflect changes in cell type composition or cell type-specific expression. Methods: Bronchial brushings from ever smokers with NSCLC from the AEGIS I (153 LUSC; 148 LUAD; 154 benign) &amp; II (82 LUSC; 102 LUAD; 74benign) trials were profiled by whole-genome microarrays. The NSCLC-associated gene expression alterations were identified using a linear model adjusting for smoking status in AEGIS I and confirmed in AEGIS II via GSEA. Enriched biological pathways were identified using EnrichR. In parallel, bronchial airway brushings collected from ever smokers undergoing bronchoscopy for suspect lung cancer (17 subjects) were profiled via scRNA-seq using the CEL-Seq2 protocol (3264 cells). Seurat was used to correct for batch effects and identify distinct cell populations. Genes differentially expressed between cell populations using a negative binomial model were clustered into gene sets using WGCNA. Per patient metagene scores were computed across the datasets for each gene set, and differences in these scores between NSCLC subtypes were evaluated using a linear model adjusting for smoking status. Results: 451 differentially expressed genes were found between LUSC v LUAD patients (FDR &amp;lt; 0.05). Genes involved in ciliary function were enriched among genes up-regulated in LUAD whereas keratinization and cancer-associated pathway genes were enriched among LUSC up-regulated genes (FDR &amp;lt; 0.05). In the scRNA-seq data, 15 populations of cells were identified that expressed known epithelial or immune cell type markers. Using WGCNA to cluster genes that distinguish the cell populations (5148 genes, FDR &amp;lt; 0.05) identified 12 gene sets (GS). In AEGIS I, LUSC patients had higher expression of a mitochondrial GS expressed highly in basal cells, a secretory-cell GS, and lower expression of a ionocyte-specific GS than LUAD patients (p = 0.041, 0.0043 and 2.06e-06 respectively). Both LUAD and LUSC patients have lower expression levels of the immune GSs than the benign patients (p = 0.00034 and 0.0008). Concordant results were found in the AEGIS II samples with the same methods. Conclusion: We leveraged bulk and single cell gene expression data and identified molecular differences in the airway field of injury among ever smokers with LUSC versus LUAD that are highly expressed specific cell populations. Our results suggest that there are different responses to injury in the normal-appearing airway that are associated with NSCLC subtype. Citation Format: Xingyi Shi, Jiarui Zhang, Steven Callori, Joshua Campbell, Denise Fine, Yaron Gesthalter, Gang Liu, Xiaohui Xiao, Avrum Spira, Marc Lenburg, Jennifer Beane. NSCLC subtype-associated molecular and cellular alterations in the normal-appearing bronchial epithelium [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3377.

Single-Cell Analysis of the Gene Expression Effects of Developmental Lead (Pb) Exposure on the Mouse Hippocampus.

Lead (Pb) exposure is ubiquitous with permanent neurodevelopmental effects. The hippocampus brain region is involved in learning and memory with heterogeneous cellular composition. The hippocampus cell type-specific responses to Pb are unknown. The objective of this study is to examine perinatal Pb treatment effects on adult hippocampus gene expression, at the level of individual cells. In mice perinatally exposed to control water or a human physiologically relevant level (32 ppm in maternal drinking water) of Pb, 2 weeks prior to mating through weaning, we tested for hippocampus gene expression and cellular differences at 5 months of age. We sequenced RNA from 5258 hippocampal cells to (1) test for treatment gene expression differences averaged across all cells, (2) compare cell cluster composition by treatment, and (3) test for treatment gene expression and pathway differences within cell clusters. Gene expression patterns revealed 12 hippocampus cell clusters, mapping to major expected cell types (eg, microglia, astrocytes, neurons, and oligodendrocytes). Perinatal Pb treatment was associated with 12.4% more oligodendrocytes (p = 4.4 × 10-21) in adult mice. Across all cells, Pb treatment was associated with expression of cell cluster marker genes. Within cell clusters, Pb treatment (q < 0.05) caused differential gene expression in endothelial, microglial, pericyte, and astrocyte cells. Pb treatment upregulated protein folding pathways in microglia (p = 3.4 × 10-9) and stress response in oligodendrocytes (p = 3.2 × 10-5). Bulk tissue analysis may be influenced by changes in cell type composition, obscuring effects within vulnerable cell types. This study serves as a biological reference for future single-cell toxicant studies, to ultimately characterize molecular effects on cognition and behavior.

Caloric Restriction Reprograms the Single-Cell Transcriptional Landscape of Rattus Norvegicus Aging

Aging causes a functional decline in tissues throughout the body that may be delayed by caloric restriction (CR). However, the cellular profiles and signatures of aging, as well as those ameliorated by CR, remain unclear. Here, we built comprehensive single-cell and single-nucleus transcriptomic atlases across various rat tissues undergoing agingand CR. CR attenuated aging-related changes in cell type composition, gene expression, and coretranscriptional regulatory networks. Immune cells were increased during aging, and CR favorablyreversed the aging-disturbed immune ecosystem. Computational prediction revealed that the abnormal cell-cell communication patterns observed during aging,including the excessive proinflammatory ligand-receptor interplay, were reversed by CR. Our work provides multi-tissue single-cell transcriptional landscapes associated with aging and CR in a mammal, enhances our understanding of the robustness of CR as a geroprotective intervention, and uncovers how metabolic intervention can act upon the immune system to modify the process of aging.

Metabolic fingerprinting of cell types in mouse skeletal muscle by combining TOF-SIMS with immunofluorescence staining.

Skeletal muscle tissue is composed of various muscle cell types which differ in physiological functions. Changes in cell type composition of skeletal muscle are associated with the development of metabolic diseases. Skeletal muscle cell types are currently distinguished by immunofluorescence (IF) staining based on myosin heavy chain (MHC) isoform difference. However, it remains a challenge to provide metabolic fingerprints of different muscle cell types by IF staining. Therefore, in this study, we proposed a method to examine metabolite distribution within different cell types by time-of-flight secondary ion mass spectrometry (TOF-SIMS) with high spatial resolution. Skeletal muscle samples from C57/BL6 mice were obtained by slicing. Cell types in TOF-SIMS images were labelled corresponding to IF images from the same region of serially cut sections. Mass spectra corresponding to individual muscle cells were extracted to compare metabolic fingerprints among cell types. Skeletal muscle cells were classified into two clusters based on the mass spectra of individual cells. Unsaturated diacylglycerol (DG) and fatty acid (FA) species were found to be distributed in a cell-type dependent manner. Moreover, relative quantification showed that the content of unsaturated DGs, oleic acid and linoleic acid was higher in type I and type IIA cells than in type IIB cells. TOF-SIMS in combination with IF enables us to directly visualize metabolite distribution in different cell types, to find potential biomarkers for cell type classification. TOF-SIMS imaging coupled with IF staining has been proved to be a promising tool for metabolic fingerprinting of different skeletal muscle cell types.

Food-type may jeopardize biomarker interpretation in mussels used in aquatic toxicological experimentation.

To assess the influence of food type on biomarkers, mussels (Mytilus galloprovincialis) were maintained under laboratory conditions and fed using 4 different microalgae diets ad libitum for 1 week: (a) Isochrysis galbana; (b) Tetraselmis chuii; (c) a mixture of I. galbana and T. chuii; and (d) a commercial food (Microalgae Composed Diet, Acuinuga). Different microalgae were shown to present different distribution and fate in the midgut. I. galbana (≈4 μm Ø) readily reached digestive cells to be intracellularly digested. T. chuii (≈10 μm Ø and hardly digestible) was retained in stomach and digestive ducts for long times and extracellularly digested. Based on these findings, it appeared likely that the presence of large amounts of microalgal enzymes and metabolites might interfere with biochemical determinations of mussel’s biomarkers and/or that the diet-induced alterations of mussels’ digestion could modulate lysosomal and tissue-level biomarkers. To test these hypotheses, a battery of common biochemical, cytological and tissue-level biomarkers were determined in the gills (including activities of pyruvate kinase, phosphoenolpyruvate carboxykinase and cytochrome c oxidase) and the digestive gland of the mussels (including protein, lipid, free glucose and glycogen total content, lysosomal structural changes and membrane stability, intracellular accumulation of neutral lipids and lipofuscins, changes in cell type composition and epithelial thinning, as well as altered tissue integrity). The type of food was concluded to be a major factor influencing biomarkers in short-term experiments though not all the microalgae affected biomarkers and their responsiveness in the same way. T. chuii seemed to alter the nutritional status, oxidative stress and digestion processes, thus interfering with a variety of biomarkers. On the other hand, the massive presence of I. galbana within digestive cells hampered the measurement of cytochemical biomarkers and rendered less reliable the results of biochemical biomarkers (as these could be attributed to both the mussel and the microalgae). Research to optimize dietary food type, composition, regime and rations for toxicological experimentation is urgently needed. Meanwhile, a detailed description of the food type and feeding conditions should be always provided when reporting aquatic toxicological experiments with mussels, as a necessary prerequisite to compare and interpret the biological responses elicited by pollutants.