Reliability in the Identification of Midbrain Dopamine Neurons

Brain regions typically contain intermixed subpopulations of neurons with different connectivity and neurotransmitters. This complicates identification of neuronal phenotypes in electrophysiological experiments without using direct detection of unique molecular markers. A prime example of this difficulty is the identification of dopamine (DA) neurons in the midbrain ventral tegmental area (VTA). Although immunocytochemistry (ICC) against tyrosine hydroxylase (TH) is widely used to identify DA neurons, a high false negative rate for TH ICC following ex vivo electrophysiology experiments was recently reported, calling into question the validity of comparing DA and non-DA VTA neurons based on post-hoc ICC. However, in whole cell recordings from randomly selected rat VTA neurons we have found that TH labeling is consistently detected in ∼55% of neurons even after long recording durations (range: 2.5–150 min). This is consistent with our prior anatomical finding that 55% of VTA neurons are TH(+). To directly estimate a false negative rate for our ICC method we recorded VTA neurons from mice in which EGFP production is driven by the TH promoter. All 12 EGFP(+) neurons recorded with a K-gluconate internal solution (as used in our rat recordings) were strongly labeled by TH ICC (recording duration 16.6±1.8 min). However, using recording electrodes with an internal solution with high Cl− concentration reduced the intensity of TH co-labeling, in some cases to background (recording duration 16.7±0.9 min; n = 10). Thus TH is a highly reliable molecular marker for DA neurons in VTA patch clamp recordings provided compatible microelectrode solutions are used

Reliability in the identification of midbrain dopamine neurons.

Brain regions typically contain intermixed subpopulations of neurons with different connectivity and neurotransmitters. This complicates identification of neuronal phenotypes in electrophysiological experiments without using direct detection of unique molecular markers. A prime example of this difficulty is the identification of dopamine (DA) neurons in the midbrain ventral tegmental area (VTA). Although immunocytochemistry (ICC) against tyrosine hydroxylase (TH) is widely used to identify DA neurons, a high false negative rate for TH ICC following ex vivo electrophysiology experiments was recently reported, calling into question the validity of comparing DA and non-DA VTA neurons based on post-hoc ICC. However, in whole cell recordings from randomly selected rat VTA neurons we have found that TH labeling is consistently detected in ∼55% of neurons even after long recording durations (range: 2.5-150 min). This is consistent with our prior anatomical finding that 55% of VTA neurons are TH(+). To directly estimate a false negative rate for our ICC method we recorded VTA neurons from mice in which EGFP production is driven by the TH promoter. All 12 EGFP(+) neurons recorded with a K-gluconate internal solution (as used in our rat recordings) were strongly labeled by TH ICC (recording duration 16.6±1.8 min). However, using recording electrodes with an internal solution with high Cl(-) concentration reduced the intensity of TH co-labeling, in some cases to background (recording duration 16.7±0.9 min; n = 10). Thus TH is a highly reliable molecular marker for DA neurons in VTA patch clamp recordings provided compatible microelectrode solutions are used

Whole cell recording solution composition influences the preservation of TH in VTA neurons.

<p>Recordings were made in VTA EGFP-expressing neurons in tissue from mice where EGFP is expressed under the TH promoter. With the K-gluconate internal solution, TH was strongly detected in all recorded neurons, regardless of recording duration, but not with a KCl internal solution. Examples of K-gluconate filled cells and ICC against EGFP and TH following brief (A), medium (B) and longer (C) duration recordings show clear TH labeling. Examples of KCl filled cells show that the TH signal in these neurons can be discernable (D), very weak (E), or undetectable (F). (G) A within section relative TH ICC intensity was calculated for each filled cell (eq. 1); while neurons recorded with the KCl solution lose TH intensity, neurons recorded with K-gluconate maintain TH intensity.</p

The percent of TH(+) neurons does not decrease with increased recording duration.

<p>Examples of rat VTA neurons in which brief whole cell recordings were made (<3 min) and post-hoc immunocytochemical detection revealed that example neuron (A) was TH(+) and example neuron (B) was TH(−). (C) The raw distributions of recording times among neurons determined to be TH(+) or TH(−) with post-hoc TH ICC are similar. (D) The ratio of TH(+) to TH(−) neurons is not related to recording duration, but is very similar to the previously published determination that 55% of all neurons in the VTA (labeled with a NeuN antibody) are TH(+) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0015222#pone.0015222-Margolis1" target="_blank">[1]</a>.</p

False negative immunocytochemical data do not contaminate our prior data.

<p>(A) Among NAc-projecting VTA neurons, we previously demonstrated that TH(+) neurons exhibited longer duration action potentials than TH(−) neurons <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0015222#pone.0015222-Cameron1" target="_blank">[6]</a>. Here we show this finding is independent of recording duration. (B) The same physiological data plotted under the premise that TH(−) neurons arise from a random technical failure. We used a time-independent probability of 0.19 for TH(−) neurons consistent with the actual data presented in (A). (C) The same data replotted utilizing a time dependent model of TH degradation (eq. 2). The probability that a neuron was TH(+) or TH(−) was modeled by a single exponential decay, and for each neuron the probability that it would be TH(+) was calculated based on the recording duration (right). A random number was then generated to determine whether a neuron fell on the TH(+) or TH(−) side of the probability plot.</p