An inducible genetic tool to track and manipulate specific microglial states reveals their plasticity and roles in remyelination.

Recent single-cell RNA sequencing studies have revealed distinct microglial states in development and disease. These include proliferative-region-associated microglia (PAMs) in developing white matter and disease-associated microglia (DAMs) prevalent in various neurodegenerative conditions. PAMs and DAMs share a similar core gene signature. However, the extent of the dynamism and plasticity of these microglial states, as well as their functional significance, remains elusive, partly due to the lack of specific tools. Here, we generated an inducible Cre driver line, Clec7a-CreERT2, that targets PAMs and DAMs in the brain parenchyma. Utilizing this tool, we profiled labeled cells during development and in several disease models, uncovering convergence and context-dependent differences in PAM and DAM gene expression. Through long-term tracking, we demonstrated microglial state plasticity. Lastly, we specifically depleted DAMs in demyelination, revealing their roles in disease recovery. Together, we provide a versatile genetic tool to characterize microglial states in CNS development and disease.

An inducible genetic tool for tracking and manipulating specific microglial states in development and disease.

Recent single-cell RNA sequencing studies have revealed distinct microglial states in development and disease. These include proliferative region-associated microglia (PAM) in developing white matter and disease-associated microglia (DAM) prevalent in various neurodegenerative conditions. PAM and DAM share a similar core gene signature and other functional properties. However, the extent of the dynamism and plasticity of these microglial states, as well as their functional significance, remains elusive, partly due to the lack of specific tools. Here, we report the generation of an inducible Cre driver line, Clec7a-CreERT2, designed to target PAM and DAM in the brain parenchyma. Utilizing this tool, we profile labeled cells during development and in several disease models, uncovering convergence and context-dependent differences in PAM/DAM gene expression. Through long-term tracking, we demonstrate surprising levels of plasticity in these microglial states. Lastly, we specifically depleted DAM in cuprizone-induced demyelination, revealing their roles in disease progression and recovery.

ABDS: tool suite for analyzing biologically diverse samples.

Motivation: Analytics tools are essential to identify informative molecular features about different phenotypic groups. Among the most fundamental tasks are missing value imputation, signature gene detection, and expression pattern visualization. However, most commonly used analytics tools may be problematic for characterizing biologically diverse samples when either signature genes possess uneven missing rates across different groups yet involving complex missing mechanisms, or multiple biological groups are simultaneously compared and visualized. Results: We develop ABDS tool suite tailored specifically to analyzing biologically diverse samples. Mechanism-integrated group-wise imputation is developed to recruit signature genes involving informative missingness, cosine-based one-sample test is extended to detect enumerated signature genes, and unified heatmap is designed to comparably display complex expression patterns. We discuss the methodological principles and demonstrate the conceptual advantages of the three software tools. We also showcase the biomedical applications of these individual tools. Implemented in open-source R scripts, ABDS tool suite complements rather than replaces the existing tools and will allow biologists to more accurately detect interpretable molecular signals among diverse phenotypic samples. Availability and implementation: The R Scripts of ABDS tool suite is freely available at https://github.com/niccolodpdu/ABDS.

Cosbin: cosine score-based iterative normalization of biologically diverse samples.

Motivation: Data normalization is essential to ensure accurate inference and comparability of gene expression measures across samples or conditions. Ideally, gene expression data should be rescaled based on consistently expressed reference genes. However, to normalize biologically diverse samples, the most commonly used reference genes exhibit striking expression variability and size-factor or distribution-based normalization methods can be problematic when the amount of asymmetry in differential expression is significant. Results: We report an efficient and accurate data-driven method-Cosine score-based iterative normalization (Cosbin)-to normalize biologically diverse samples. Based on the Cosine scores of cross-condition expression patterns, the Cosbin pipeline iteratively eliminates asymmetric differentially expressed genes, identifies consistently expressed genes, and calculates sample-wise normalization factors. We demonstrate the superior performance and enhanced utility of Cosbin compared with six representative peer methods using both simulation and real multi-omics expression datasets. Implemented in open-source R scripts and specifically designed to address normalization bias due to significant asymmetry in differential expression across multiple conditions, the Cosbin tool complements rather than replaces the existing methods and will allow biologists to more accurately detect true molecular signals among diverse phenotypic groups. Availability and implementation: The R scripts of Cosbin pipeline are freely available at https://github.com/MinjieSh/Cosbin. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

COT: an efficient and accurate method for detecting marker genes among many subtypes.

Motivation: Ideally, a molecularly distinct subtype would be composed of molecular features that are expressed uniquely in the subtype of interest but in no others-so-called marker genes (MGs). MG plays a critical role in the characterization, classification or deconvolution of tissue or cell subtypes. We and others have recognized that the test statistics used by most methods do not exactly satisfy the MG definition and often identify inaccurate MG. Results: We report an efficient and accurate data-driven method, formulated as a Cosine-based One-sample Test (COT) in scatter space, to detect MG among many subtypes using subtype expression profiles. Fundamentally different from existing approaches, the test statistic in COT precisely matches the mathematical definition of an ideal MG. We demonstrate the performance and utility of COT on both simulated and real gene expression and proteomics data. The open source Python/R tool will allow biologists to efficiently detect MG and perform a more comprehensive and unbiased molecular characterization of tissue or cell subtypes in many biomedical contexts. Nevertheless, COT complements not replaces existing methods. Availability and implementation: The Python COT software with a detailed user's manual and a vignette are freely available at https://github.com/MintaYLu/COT. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

AD-linked R47H-TREM2 mutation induces disease-enhancing microglial states via AKT hyperactivation.

The hemizygous R47H variant of triggering receptor expressed on myeloid cells 2 (TREM2), a microglia-specific gene in the brain, increases risk for late-onset Alzheimer's disease (AD). Using transcriptomic analysis of single nuclei from brain tissues of patients with AD carrying the R47H mutation or the common variant (CV)­TREM2, we found that R47H-associated microglial subpopulations had enhanced inflammatory signatures reminiscent of previously identified disease-associated microglia (DAM) and hyperactivation of AKT, one of the signaling pathways downstream of TREM2. We established a tauopathy mouse model with heterozygous knock-in of the human TREM2 with the R47H mutation or CV and found that R47H induced and exacerbated TAU-mediated spatial memory deficits in female mice. Single-cell transcriptomic analysis of microglia from these mice also revealed transcriptomic changes induced by R47H that had substantial overlaps with R47H microglia in human AD brains, including robust increases in proinflammatory cytokines, activation of AKT signaling, and elevation of a subset of DAM signatures. Pharmacological AKT inhibition with MK-2206 largely reversed the enhanced inflammatory signatures in primary R47H microglia treated with TAU fibrils. In R47H heterozygous tauopathy mice, MK-2206 treatment abolished a tauopathy-dependent microglial subcluster and rescued tauopathy-induced synapse loss. By uncovering disease-enhancing mechanisms of the R47H mutation conserved in human and mouse, our study supports inhibitors of AKT signaling as a microglial modulating strategy to treat AD.

Microglial microRNAs mediate sex-specific responses to tau pathology.

Sex is a key modifier of neurological disease outcomes. Microglia are implicated in neurological diseases and modulated by microRNAs, but it is unknown whether microglial microRNAs have sex-specific influences on disease. We show in mice that microglial microRNA expression differs in males and females and that loss of microRNAs leads to sex-specific changes in the microglial transcriptome and tau pathology. These findings suggest that microglial microRNAs influence tau pathogenesis in a sex-specific manner.

Single-Cell Transcriptomics Uncovers Glial Progenitor Diversity and Cell Fate Determinants during Development and Gliomagenesis.

The identity and degree of heterogeneity of glial progenitors and their contributions to brain tumor malignancy remain elusive. By applying lineage-targeted single-cell transcriptomics, we uncover an unanticipated diversity of glial progenitor pools with unique molecular identities in developing brain. Our analysis identifies distinct transitional intermediate states and their divergent developmental trajectories in astroglial and oligodendroglial lineages. Moreover, intersectional analysis uncovers analogous intermediate progenitors during brain tumorigenesis, wherein oligodendrocyte-progenitor intermediates are abundant, hyper-proliferative, and progressively reprogrammed toward a stem-like state susceptible to further malignant transformation. Similar actively cycling intermediate progenitors are prominent components in human gliomas with distinct driver mutations. We further unveil lineage-driving networks underlying glial fate specification and identify Zfp36l1 as necessary for oligodendrocyte-astrocyte lineage transition and glioma growth. Together, our results resolve the dynamic repertoire of common and divergent glial progenitors during development and tumorigenesis and highlight Zfp36l1 as a molecular nexus for balancing glial cell-fate decision and controlling gliomagenesis.

Developmental Heterogeneity of Microglia and Brain Myeloid Cells Revealed by Deep Single-Cell RNA Sequencing.

Microglia are increasingly recognized for their major contributions during brain development and neurodegenerative disease. It is currently unknown whether these functions are carried out by subsets of microglia during different stages of development and adulthood or within specific brain regions. Here, we performed deep single-cell RNA sequencing (scRNA-seq) of microglia and related myeloid cells sorted from various regions of embryonic, early postnatal, and adult mouse brains. We found that the majority of adult microglia expressing homeostatic genes are remarkably similar in transcriptomes, regardless of brain region. By contrast, early postnatal microglia are more heterogeneous. We discovered a proliferative-region-associated microglia (PAM) subset, mainly found in developing white matter, that shares a characteristic gene signature with degenerative disease-associated microglia (DAM). Such PAM have amoeboid morphology, are metabolically active, and phagocytose newly formed oligodendrocytes. This scRNA-seq atlas will be a valuable resource for dissecting innate immune functions in health and disease.

Paternal malnutrition programs breast cancer risk and tumor metabolism in offspring.

BACKGROUND: While many studies have shown that maternal factors in pregnancy affect the cancer risk for offspring, few studies have investigated the impact of paternal exposures on their progeny's risk of this disease. Population studies generally show a U-shaped association between birthweight and breast cancer risk, with both high and low birthweight increasing the risk compared with average birthweight. Here, we investigated whether paternal malnutrition would modulate the birthweight and later breast cancer risk of daughters. METHODS: Male mice were fed AIN93G-based diets containing either 17.7% (control) or 8.9% (low-protein (LP)) energy from protein from 3 to 10 weeks of age. Males on either group were mated to females raised on a control diet. Female offspring from control and LP fathers were treated with 7,12-dimethylbenz[a]anthracene (DMBA) to initiate mammary carcinogenesis. Mature sperm from fathers and mammary tissue and tumors from female offspring were used for epigenetic and other molecular analyses. RESULTS: We found that paternal malnutrition reduces the birthweight of daughters and leads to epigenetic and metabolic reprogramming of their mammary tissue and tumors. Daughters of LP fathers have higher rates of mammary cancer, with tumors arising earlier and growing faster than in controls. The energy sensor, the AMP-activated protein kinase (AMPK) pathway, is suppressed in both mammary glands and tumors of LP daughters, with consequent activation of mammalian target of rapamycin (mTOR) signaling. Furthermore, LP mammary tumors show altered amino-acid metabolism with increased glutamine utilization. These changes are linked to alterations in noncoding RNAs regulating those pathways in mammary glands and tumors. Importantly, we detect alterations in some of the same microRNAs/target genes found in our animal model in breast tumors of women from populations where low birthweight is prevalent. CONCLUSIONS: Our study suggests that ancestral paternal malnutrition plays a role in programming offspring cancer risk and phenotype by likely providing a metabolic advantage to cancer cells.