Microglia – An Update on How to Define this Multifaceted Cell Population

Written by Maria-Luisa Wiesinger; Pediatric low-grade glioma research at the German Cancer Research Center, Heidelberg

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What if the brain’s resident immune cells could act like chameleons, changing their colors depending on their environment? That’s exactly what microglia do – and scientists are moving beyond old labels to capture their full complexity. Let’s examine how microglia have historically been classified and highlight the key factors that now guide a more accurate and comprehensive definition.

Other than their name suggests – “micro” (= small) and “glia” (= glue) – they are not static but rather dynamic and mobile. In fact, microglia are the busy bees of the brain – as master caretakers, they regulate a plethora of important processes, including synapse remodeling / pruning, neuronal maturation, phagocytosis, inflammatory responses, blood-brain-barrier permeability, as well as neurovascular physiology ^1–5. In contrast to other immune cells originating from the hematopoietic lineage, microglia are derived from early mesodermal erythromyeloid progenitor cells residing in the yolk sac and migrate to the central nervous system during embryonic development, prior to the formation of the blood-brain barrier ⁶. They make up to 5-15 % of the total adult brain cell population ⁷.

Need for unifying nomenclature

Since their official description by Pío del Río-Hortega in 1939, microglia continue to draw attention due to their dynamic roles in homeostatic and disease states ⁸.

Over the years, microglial cells have been subject to dichotomic categorizations. They were labeled as either “resting” (homeostatic) versus “activated” (disease-associated), “M2” (anti-inflammatory) versus “M1” (pro-inflammatory), or described morphologically as “ramified” (branched) versus “amoeboid” (rounded). While these classifications were useful for early functional studies and some of their macrophage counterparts, they paint a rigid, black-and-white picture of microglia as either “good” or “bad” ⁹.

As highlighted above, this dichotomic view is far too reductionistic. With the growing availability of advanced experimental tools, researchers are now acknowledging that microglia can adopt a wide range of highly diverse, context-dependent states, shifting their identity in response to the surrounding environment. Here, the term “environment” should be interpreted broadly since microglial states are defined by many factors such as location in the brain, developmental age, sex, and disease, as extensively reviewed by Paolicelli and colleagues ⁹.

Despite their many functions and diverse states, well-defined microglia categories remain essential – they help us make sense of microglial complexity and provide a practical framework for designing new studies.

In short, a unified and updated nomenclature would help researchers from different fields understand microglial heterogeneity and speak the same language, fostering collaboration and a more holistic understanding of microglial biology – instead of confining studies to narrow, outdated labels.

How do we define microglial clusters?

A classical way to identify a particular cell type is by using “markers”, i.e., the differential enrichment of a selected group of genes or proteins. Prominent microglial markers include IBA1 (Ionized calcium-binding adapter molecule 1), CX3CR1 (CX3C motif chemokine receptor 1), P2RY12 (P2Y12 G protein-coupled purinergic receptor), TREM2 (Triggering receptor expressed on myeloid cells 2), and TMEM119 (Transmembrane protein 119). If you are curious about what these molecules do and where exactly they are located within the cells, have a look at one of our earlier articles.

But here lies the problem: To date, no single marker can uniquely distinguish microglia from brain border-associated or infiltrating macrophages.

This is further complicated by the fact that microglial marker gene expression changes significantly depending on local cues. For instance, while TMEM119 is typically associated with a homeostatic, surveillant-like state, it is downregulated in multiple sclerosis white matter lesions ¹⁰.

This means that markers reflect not only what microglia are, but also what they are doing at a given moment in a given environment. A single molecular nametag is rarely informative on its own – combinations of markers into “clusters” are much more useful for capturing the functional state of these highly dynamic cells.

Practical steps towards microglia identification

So, what should we consider if we want to define what makes a microglial cell unique? Microglia are complex and no single experimental method can capture all their facets.

That’s why researchers now take advantage of multiple characterization modalities such as transcriptomics, proteomics, epigenetics, metabolomics, and cell morphology to paint a full picture. For example, multi-omic platforms such as workflows that combine single-cell RNA-sequencing with DNA-barcoded antibodies (MultiPro^® Human Discovery Panel) can simultaneously map gene expression and hundreds of protein levels. Adding immunohistological staining on top provides crucial spatial context: Where exactly in the brain parenchyma do these microglial cells sit and what is in their direct vicinity?

Crucially, microglial identity cannot be defined in isolation – it is inseparably linked to context. The state a microglial cell adopts is shaped by a complex interplay of factors: its spatial location within the brain, the age and sex of the organism, disease stage, and even systemic metabolic cues ⁹. A microglial cluster in the cerebellum of a young, healthy brain may look entirely different from one in aged cortical tissue or within a neuroinflammatory lesion, even if they share a certain marker expression profile.

Failing to account for these contextual confounders risks mistaking a transient, adaptive state for a stable and distinct cell cluster. What appears to be a “new” microglial subtype may represent a temporary response to local signals rather than a genuinely different cluster.

By integrating the proteome on the single-cell level and the respective spatial location, Mrdjen and Cannon et al. propose that microglia span a continuum of immune activation states rather than rigid subtypes. In healthy brains, they vary by niche, showing lower immune marker expression in synapse-rich regions and higher immune activity in myelin-rich or astrocyte-dense areas. In Alzheimer’s disease (AD), this balance shifted: microglia were skewed toward a heightened state, with CD44 and CD33 upregulated and HLA-DR and P2RY12 reduced, reflecting a more diffuse, potentially dysfunctional phenotype that extends beyond AD-typical plaques ¹¹.

Defining microglial states becomes even more complex when considering their secretory repertoire. The very same cytokine can have opposing effects depending on the context: for instance, TNF-α supports neuroplasticity, myelination, and tissue repair in homeostasis, but may contribute to excitotoxicity, inflammation, and blood-brain barrier breakdown in neuroinflammatory diseases ¹². This duality underscores that microglial paracrine signals guide microglial state definition but must be interpreted within the cellular and environmental context.

These findings illustrate why moving beyond single-marker definitions is crucial: only the integration of multimodal approaches captures the true diversity of microglial states in health and disease.

Careful integration of environmental, physiological, and pathological context is therefore essential for developing a meaningful and reproducible nomenclature.

And perhaps most importantly, classification alone is never enough. No matter how refined clustering methods become, we always need to validate the biological function to understand what role microglia actually play – whether they protect, aggravate, or simply adapt to their current microenvironment.

Updated nomenclature consensus = Deeper insight into microglial biology

Microglia are far more than just the brain’s immune sentinels – they are dynamic cells constantly reacting to their direct surroundings. From their unique embryonic origin to their ability to adopt diverse, context-dependent states, they remain one of the most fascinating and versatile cell types in the brain. A unified and refined nomenclature is not just a matter of complicating terminology. It is a crucial step toward elucidating their true nature. Moving beyond historical, oversimplified labels and integrating multi-omics tools with functional validation will help us build a clearer, more accurate picture of microglial diversity that can exist on a continuum ¹³. This process is still in the making, and for the time being, descriptive terms such as microglial “clusters” and “states” reflecting microglia diversity and plasticity should be preferred over fixed categories such as “M1 / M2”.

And while this task is far from complete, that is exactly what makes it so exciting. Every new piece of data, every methodological advance, and every interdisciplinary collaboration adds to a shared framework that continues to evolve. Defining microglia is not about fixing them into rigid boxes, but about gradually piecing together a more nuanced and dynamic picture – one that grows richer with every study. In the coming years, this collective effort may allow us to link microglial states to their roles more specifically in diverse disease areas (e.g., neurodegenerative diseases or brain cancers), opening new avenues for understanding and therapeutic intervention ^14–16.

References:

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2. Brown, G. C. & Neher, J. J. Microglial phagocytosis of live neurons. Nature Reviews Neuroscience 2014 15:4 15, 209–216 (2014).

3. Gao, C., Jiang, J., Tan, Y. & Chen, S. Microglia in neurodegenerative diseases: mechanism and potential therapeutic targets. Signal Transduction and Targeted Therapy 2023 8:1 8, 1–37 (2023).

4. Haruwaka, K. et al. Dual microglia effects on blood brain barrier permeability induced by systemic inflammation. Nature Communications 2019 10:1 10, 1–17 (2019).

5. Bisht, K. et al. Capillary-associated microglia regulate vascular structure and function through PANX1-P2RY12 coupling in mice. Nature Communications 2021 12:1 12, 1–13 (2021).

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8. Rio-Hortega, P. Del. THE MICROGLIA. The Lancet 233, 1023–1026 (1939).

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10. Van Wageningen, T. A. et al. Regulation of microglial TMEM119 and P2RY12 immunoreactivity in multiple sclerosis white and grey matter lesions is dependent on their inflammatory environment. Acta Neuropathol Commun 7, 1–16 (2019).

11. Mrdjen, D. et al. Spatial proteomics of Alzheimer’s disease-specific human microglial states. Nature Immunology 2025 26:8 26, 1397–1410 (2025).

12. Gonzalez Caldito, N. Role of tumor necrosis factor-alpha in the central nervous system: a focus on autoimmune disorders. Front Immunol 14, 1213448 (2023).

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14. Tuddenham, J. F. et al. A cross-disease resource of living human microglia identifies disease-enriched subsets and tool compounds recapitulating microglial states. Nature Neuroscience 2024 27:12 27, 2521–2537 (2024).

15. Fumagalli, L. et al. Microglia heterogeneity, modeling and cell-state annotation in development and neurodegeneration. Nature Neuroscience 2025 28:7 28, 1381–1392 (2025).

16. Depp, C., Doman, J. L., Hingerl, M., Xia, J. & Stevens, B. Microglia transcriptional states and their functional significance: Context drives diversity. Immunity 58, 1052–1067 (2025).