Microglia, the principal neuroimmune sentinels of the brain, continuously sense changes in their environment and respond to invading pathogens, toxins and cellular debris. Microglia exhibit plasticity and can assume neurotoxic or neuroprotective priming states that determine their responses to danger. We used direct RNA sequencing, without amplification or cDNA synthesis, to determine the quantitative transcriptomes of microglia of healthy adult and aged mice. We validated our findings by fluorescent dual in-situ hybridization, unbiased proteomic analysis and quantitative PCR. We report here that microglia have a distinct transcriptomic signature and express a unique cluster of transcripts encoding proteins for sensing endogenous ligands and microbes that we term the “sensome”. With aging, sensome transcripts for endogenous ligand recognition are downregulated, whereas those involved in microbe recognition and host defense are upregulated. In addition, aging is associated with an overall increase in expression of microglial genes involved in neuroprotection.

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The microglial sensome revealed by direct RNA sequencing

Background Vaccines to prevent coronavirus disease 2019 (Covid-19) are urgently needed. The effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines on viral replica...

https://www.nejm.org/doi/pdf/10.1056/NEJMoa2024671

Evaluation of the mRNA-1273 Vaccine against SARS-CoV-2 in Nonhuman Primates.

The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish previously unknown and orthologous neuronal subtypes as well as regional identity and transcriptomic heterogeneity within the human brain.

https://science.sciencemag.org/content/sci/352/6293/1586.full.pdf

Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain.

https://www.cell.com/immunity/pdf/S1074-7613(19)30126-8.pdf

Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species.

Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues detailing the transcriptomes of individual cells. Unsupervised clustering is of central importance for the analysis of these data, as it is used to identify putative cell types. However, there are many challenges involved. We discuss why clustering is a challenging problem from a computational point of view and what aspects of the data make it challenging. We also consider the difficulties related to the biological interpretation and annotation of the identified clusters.

Allissa Nielson

Papers

RNAscope: A Novel in Situ RNA Analysis Platform for Formalin-Fixed, Paraffin-Embedded Tissues