Choosing identity markers in nervous tissue that survive activation: why an s100b antibody, an s100 antibody and an s100 beta antibody name overlapping reagents against a family whose members are shared between glia and other cell types, what a dcx antibody or doublecortin antibody reports about immaturity rather than lineage, how a ctip2 antibody, a brn3a antibody, an isl1 antibody, an hb9 antibody, a pax6 antibody, a pax7 antibody, a pax2 antibody, an insm1 antibody, an olfm4 antibody and an rbpms antibody define populations by transcription factor rather than by shape, where an nse antibody, a neurofilament antibody, an nf-h antibody, a pgp9.5 antibody with its pgp 9.5 antibody and pgp9 5 antibody spellings, an stmn2 antibody and an rbfox3 antibody mark neurons generally, what a myelin basic protein antibody, a galc antibody, an eaat1 antibody, an aldh1l1 antibody and a tspo antibody report in glia, and why an npas4 antibody and an arc antibody read activity rather than identity

Building an identity panel

1. Pair a state independent marker with a state sensitive one. Counting cells needs a marker that does not change with activation. Reporting state needs one that does. Using a single marker for both jobs is how apparent cell loss is reported where there was a phenotype change.
2. Optimise retrieval per reagent. Nuclear transcription factors in fixed tissue frequently need retrieval to be visible, and the optimum differs between reagents. Optimise on tissue known to be positive rather than on the experimental sections.
3. Check the family, not just the member. Several of these targets belong to families whose members share sequence and are expressed in other cell types. Read the immunogen and check the datasheet for family cross reactivity before assigning a cell type.
4. Use morphology as a control on the marker. In tissue, the shape and position of a stained cell is independent evidence. A marker signal in cells with the wrong morphology is a warning, not a discovery.
5. Count with a defined rule and a blinded scorer. Cell counting in sections is dominated by sampling and by scoring rules. Define the region, the section interval and the inclusion criteria in advance, and score blind.

Identity and state are entangled

The markers used to name cells in nervous tissue were mostly discovered because they are strongly expressed, and strong expression is frequently regulated. That entanglement is the central difficulty of the field and it is not solved by a better reagent.

It is solved by panels: one marker chosen for stability, one for state, and morphology as a third line of evidence.

Sections are sampled, not measured

A count from a section is an estimate that depends on section thickness, interval, region definition and how partial cells are treated. Two studies reporting different numbers frequently differ in sampling rather than in biology.

State the sampling scheme with the result. It is what allows the numbers to be compared with anyone else's.

Common questions

Does a reduced marker mean cell loss?

Not on its own. Activation, injury and maturation all change marker expression, so a second marker with different regulation, or a nuclear count, is what distinguishes loss from a state change.

Why is my transcription factor stain weak?

Retrieval, usually. Nuclear targets in cross linked tissue need conditions optimised per reagent, and a weak nuclear stain is far more often a retrieval problem than a reagent problem.

Can one marker define a glial population?

Rarely. Family members are shared with other cell types and expression shifts with state. Two markers plus morphology is the practical minimum for a population claim.

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