Showing posts with label PMAT. Show all posts
Showing posts with label PMAT. Show all posts

Tuesday, January 16, 2024

Serotonin Research Marches On or Why the Michaelis-Menten Equation is Important to Psychiatrists

 

As the old saying goes – the demise of serotonin (5-HT) in the psychiatric literature has been greatly exaggerated. Another worthwhile proposition would be to get to know the detractors and their work as well as the basic scientists doing the research. The criticism is predictable after a while. I made a comment about this back in 2015 and charted the Medline references for major depression and serotonin. The update of that chart is below and there has not been a steep decline in references to serotonin in depression. There are roughly three times as many serotonin references per year for psychiatric disorders. When you read the introductions to these papers – there is generally a restatement of the importance of serotonin in psychiatric disorders up to stating that serotonergic signaling is indispensable in considering antidepressant drug development. The bulk of this research is not done by psychiatrists – but by basic scientists interested in the study of mental disorders. That is the focus of this post.

 

The paper today (1) was of great interest to me for several reasons.  First, it was focused on antidepressant mechanism of action and area that needs more work.  Second, it employed physical chemistry techniques (voltammetry and reaction kinetics) that have been of great interest to me since I was exposed to them as a Physical Chemistry (PChem) undergraduate.  Third, it discusses a system of 5-HT reuptake that is relatively unknown to most psychiatrists – but clearly important.  I hope to explain it all and provide the necessary references for further study.  And finally, it is the product of a lab and collaborators with a high level of expertise in physiological chemistry including the technology necessary for accurate measurement. I am referring to Hashemi Lab.  That contrasts significantly with many critics of serotonin work who have no similar expertise and typically do not do original research in the field.

Starting with the serotonergic systems – the paper is focused on extracellular 5-HT signaling as a common feature of antidepressant medications.  Models of this process have been around for a long time.  A basic assumption of the model is that presynaptic serotonin transporter (SERT) terminates serotonergic neurotransmission by reuptake 5-HT from the synaptic cleft to the intracellular space of the presynaptic neuron. One action of antidepressants studied over the past three decades has been to block that process.  When fluoxetine was initially marketed, there was an emphasis on this process and the term selective serotonin reuptake inhibitors (SSRIs) was born. As assays become more sensitive, it was shown that medications from some other classes of antidepressants also blocked 5-HT reuptake. 

The authors describe two uptake systems.  Uptake 1 consists of SERT and is characterized as a high affinity low-capacity system. Uptake 2 consists of norepinephrine transporter (NET), dopamine transporter (DAT), organic cation transporter (OCT), and plasma membrane monoamine transporter (PMAT) as a low affinity high-capacity system.  There has been a common view that transporters are restricted to blocking reuptake of the named substance (ie. DAT will only transport dopamine).  More recently it was discovered that these proteins are not specific and will transport other monoamines.  5-HT is taken up in both streams Uptake 1 via SERT and Uptake 2 by DAT, NET, OCT, and PMAT.  Characteristics of both systems are listed in the tables below.

Transporter

 

 

 

Uptake 1

SERT

 

 

 

Uptake 2

NET

 

 

 

DAT

 

 

 

OCT

 

 

 

PMAT

 

 

 

 

Despite observed clinical differences in antidepressants, physicians are generally taught to think of them by general class based on binding studies.  There is a tendency to view all antidepressants within a class as having the same mechanism of action.  That illusion of equivalency can give the impression that within a class – they are interchangeable apart from pharmacokinetic parameters (half-life, time to max concentration, etc) and side effects commonly attributed to effects at other receptors.

The more specific mechanism of action of antidepressants at the binding site is often not mentioned.  Reuptake proteins can be bound allosterically and orthosterically (3).  Orthosteric ligands bind to the protein at the site of the natural endogenous ligand of interest - in this case serotonin. Allosteric ligands or modulators bind to the protein at sites that are peripheral to the site of interest and can be positive, negative, or silent modulators based on their effect on their effect on the orthosteric ligand. In some cases, a molecule can be both an allosteric and orthosteric modulator. In the case of antidepressant medications that is true for escitalopram.  Studying the complexity of 5-HT reuptake systems has the potential to clarify mechanisms and potentially look at mechanisms that remain unclear such as antidepressant withdrawal symptoms.

The main technology used in this study was fast scan cyclic voltammetry (FSCV) to estimate the extracellular 5-HT in the hippocampus of mice where 5-HT release has been stimulated via the median forebrain bundle (MFB).  FSCV is a technique where an electrical current is applied and it oxidizes the compound in solution at the electrode surface.  Major neurotransmitters like 5-HT, dopamine (DA), and norepinephrine (NE) oxidize under these circumstances and the resulting current flow can be used to estimate concentration.  The lab involved in the study and principal investigator developed the measurement technology and calibrated it against standardized solutions of 5-HT (4) so that the control detection was a clean square wave signal in a flow cell.

The authors performed FSCV analysis – pre and post drug in the same mice and applied Michaelis-Menten (M-M) analysis of the resulting curves from these experiments.  The M-M equation was originally derived to study enzyme kinetics.  It shows the relationship between initial reaction velocity to maximal velocity for a certain enzyme and substrate.  The M-M equation is given below:



In enzyme work, M-M equations are typically analyzed graphically (y = mx + b) plotting vο vs [S ]  or the inverse of 1/vο vs 1/[S] to determine Vmax and KM.

In previous work the authors developed an expression for M-M kinetics for two reuptake mechanisms (7):

 





Where:

R(t) = rate of release

A(t) = fraction of stimulated autoreceptors

Vmax1, Vmax2 = M-M Vmax for each of the reuptake mechanisms (1-slow, 2-fast)

Km1, Km2 = Michaelis constant for each reuptake mechanism (1-slow, 2-fast)

α and β are constants to differentially weight the reuptake mechanisms individually and synergistically

 

In their paper the authors found that escitalopram, fluoxetine, reboxetine, and ketamine all decreased 5-HT reuptake and increased extracellular 5-HT.  They have an excellent graphic of their results as Figure S2 in the Supporting information (10).  Using the M-M analysis, fluoxetine followed an orthosteric Uptake 1 mechanism.  Reboxetine followed an Uptake 2 mechanism. Escitalopram did not fit the standard M-M analysis suggesting a more complex mechanism due to the combination of allosteric and orthosteric effects as well as SERT trafficking (overexpression and internalization). Ketamine indirectly increased extracellular 5-HT by effects of histamine.  In view of their results, the authors conclude that the direct measurement of serotonin may be an indicator of antidepressant potential.

To me this is a landmark work.  Just the brief list of references below indicates very active research in this area.  It shows the amount of complexity involved in signaling at the neuronal level. The authors speculate that in one case the suggested superior efficacy of escitalopram may reflect the unique mechanism of action that they suggest. It also suggests that a much more sophisticated approach is necessary when reading the antidepressant literature. Are the suggested mechanisms of action for ketamine through NMDA really the primary mechanism of action or is it the effects of inhibitory H3 receptors on 5-HT neurons?  And what about the issue of antidepressant withdrawal phenomenon?  Do the new pharmacodynamic insights provided by the research have implications for withdrawal?  That area has been primarily addressed by pharmacokinetics in the past.  Finally – even though we have been getting glimpses of the importance of 5-HT over the past 70 years, the complexity has not been sorted out. Contrary to some opinions – the is an exciting area of research and the people involved are doing brilliant work. It raises the bar for those engaged in clinical work interested in the associated pathophysiology and pharmacology.

 

George Dawson, MD, DFAPA

 

References:

1:   Witt CE, Mena S, Holmes J, Hersey M, Buchanan AM, Parke B, Saylor R, Honan LE, Berger SN, Lumbreras S, Nijhout FH, Reed MC, Best J, Fadel J, Schloss P, Lau T, Hashemi P. Serotonin is a common thread linking different classes of antidepressants. Cell Chem Biol. 2023 Dec 21;30(12):1557-1570.e6. doi: 10.1016/j.chembiol.2023.10.009. Epub 2023 Nov 21. PMID: 37992715.

2:  Hexter M, van Batenburg-Sherwood J, Hashemi P. Novel Experimental and Analysis Strategies for Fast Voltammetry: 2. A Troubleshoot-Free Flow Cell for FSCV Calibrations. ACS Meas Sci Au. 2023 Jan 11;3(2):120-126. doi: 10.1021/acsmeasuresciau.2c00059. PMID: 37090258; PMCID: PMC10120031.

3:  John CE, Jones SR. Fast Scan Cyclic Voltammetry of Dopamine and Serotonin in Mouse Brain Slices. In: Michael AC, Borland LM, editors. Electrochemical Methods for Neuroscience. Boca Raton (FL): CRC Press/Taylor & Francis; 2007. Chapter 4. Available from: https://www.ncbi.nlm.nih.gov/books/NBK2579/

4:  Stucky C, Johnson MA. Improved Serotonin Measurement with Fast-Scan Cyclic Voltammetry: Mitigating Fouling by SSRIs. J Electrochem Soc. 2022 Apr;169(4):045501. doi: 10.1149/1945-7111/ac5ec3. Epub 2022 Apr 11. PMID: 36157165; PMCID: PMC9491377.

5:  Jiang C, He X, Wang Y, Chen CJ, Othman Y, Hao Y, Yuan J, Xie XQ, Feng Z. Molecular Modeling Study of a Receptor–Orthosteric Ligand–Allosteric Modulator Signaling Complex. ACS Chemical Neuroscience. 2023 Jan 24;14(3):418-34.

6:  Weber BL, Beaver JN, Gilman TL. Summarizing studies using constitutive genetic deficiency to investigate behavioural influences of uptake 2 monoamine transporters. Basic Clin Pharmacol Toxicol. 2023 Nov;133(5):439-458. doi: 10.1111/bcpt.13810. Epub 2022 Nov 20. PMID: 36316031; PMCID: PMC10657738.

7:  Wood KM, Zeqja A, Nijhout HF, Reed MC, Best J, Hashemi P. Voltammetric and mathematical evidence for dual transport mediation of serotonin clearance in vivo. J Neurochem. 2014 Aug;130(3):351-9. doi: 10.1111/jnc.12733. Epub 2014 Apr 26. PMID: 24702305; PMCID: PMC4107184.

8:  Bunin MA, Wightman RM. Quantitative evaluation of 5-hydroxytryptamine (serotonin) neuronal release and uptake: an investigation of extrasynaptic transmission. J Neurosci. 1998 Jul 1;18(13):4854-60. doi: 10.1523/JNEUROSCI.18-13-04854.1998. PMID: 9634551; PMCID: PMC6792557.

9.  Matthäus F, Haddjeri N, Sánchez C, Martí Y, Bahri S, Rovera R, Schloss P, Lau T. The allosteric citalopram binding site differentially interferes with neuronal firing rate and SERT trafficking in serotonergic neurons. European Neuropsychopharmacology. 2016 Nov 1;26(11):1806-17.

10:  Supporting Information for Serotonin is the Common Thread Linking Different Classes of Antidepressants  (see Figures S1 and S2).