The development of genetically encoded dopamine sensors such as dLight has provided a new approach to measuring slow and fast dopamine dynamics both in brain slices and in vivo, possibly enabling dopamine measurements in areas like the dorsolateral striatum (DLS) where previously such recordings with fast-scan cyclic voltammetry (FSCV) were difficult. To test this, we first evaluated dLight photometry in mouse brain slices with simultaneous FSCV and found that both techniques yielded comparable results, but notable differences in responses to dopamine transporter inhibitors, including cocaine. We then used in vivo fiber photometry with dLight in mice to examine responses to cocaine in DLS. We also compared dopamine responses during Pavlovian conditioning across the striatum. We show that dopamine increases were readily detectable in DLS and describe transient dopamine kinetics, as well as slowly developing signals during conditioning. Overall, our findings indicate that dLight photometry is well suited to measuring dopamine dynamics in DLS. Genetically encoded dopamine sensors have emerged as an alternative to voltammetry for in vivo dopamine measurements. Here, the authors compare these two methods directly, and document dopamine responses during Pavlovian conditioning across the striatum. Midbrain dopaminergic neurons provide extensively branching axons to the striatum. The dopamine released from these afferents produces neuromodulation with key roles in neuronal function, synaptic plasticity, and behavior. The rodent striatum has several subregions that are part of associative , limbic , and sensorimotor  circuits that have different roles in learning, movement control, and reward6. Thus, understanding the dynamics of dopamine release in different striatal subregions is important for a full understanding of the function of these striatal regions in the context of different brain circuits.Dopamine is a catecholamine neurotransmitter found throughout the mammalian nigrostriatal and cortical-mesolimbic circuit with critical roles in many psychiatric and neurological disorders including Parkinson’s Disease, psychosis, schizophrenia, and addiction e.g., refs. 7. Variants of microdialysis can also be used to estimate the absolute dopamine concentration in a brain region. However, this technique has a relatively slow sampling time, typically 5–20 min per sample that does not allow for precise correlation of dopamine levels with discrete behavioral events. Fast-scan cyclic voltammetry is an electrochemical method that can be used to measure phasic release of catecholamines at sampling rates of 10 Hz or higher8. Thus, FSCV allows for real-time measurement of dopamine release in response to stimuli in brain slices, as well as in vivo detection of sub-second changes in neurotransmitter release in relation to behavioral events. Indeed, real-time dopamine measurements with FSCV revolutionized the study of fast dopamine changes and motivated behaviors for well over a decade. However, FSCV has limitations. Conventional FSCV discerns fast signals from a recent baseline or pre-stimulus period, and thus this technique cannot measure absolute dopamine concentrations and is not well suited to measurement of slow changes in dopamine levels. In addition, FSCV cannot distinguish between different catecholamine neurotransmitters. In practice, FSCV measurements of in vivo dopamine have been made mainly in the rat Nucleus accumbens, although a few studies have examined the rat DMS and DLS10. Unfortunately, in vivo measurements in mouse dorsal striatum, and the DLS in particular, are lacking. This is presumably due to difficulties in detecting small changes accompanied by contaminating signals.Dopamine release has been measured in isolated cells, brain slices, and in vivo with techniques including microdialysis sampling coupled with electrochemical detection and variants of fast-scan cyclic voltammetry (FSCV). Microdialysis allows for precise chemical identification and concurrent measurements of multiple neurotransmitters from each sample12. These membrane-targeted, G-protein-coupled receptor (GPCR)-based sensors employ modified dopamine receptors inactive for intracellular signaling that have had a circular permuted Green Fluorescence Protein (cpGFP) molecule in place of the third intracellular loop. The sensors work by coupling the dopamine induced conformational changes to changes in cpGFP emission intensity. Although fluorescent dopamine sensors cannot measure absolute concentrations of dopamine, they can be used to simultaneously detect slow and fast (or phasic) changes in dopamine relative to baseline levels15. These sensors also have the sensitivity to measure dopamine in brain regions where such measurements were previously difficult e.g., cerebral cortex11. Using genetically encoded fluorescent dopamine sensors allows for the real-time measurement of dopamine dynamics in relation to distinct behaviors in areas such as DLS.Genetically encoded fluorescent biosensors for dopamine were recently developedIn the current study, we first evaluated the ability of the genetically encoded dopamine sensor dLight to detect stimulation-induced dopamine in dorsal striatum using brain slice photometry with simultaneous FSCV. We found many similarities in indices of regulation of dopamine release using both methods. We also noted differences in cocaine-induced effects on dorsal striatal dopamine release measured with dLight photometry and FSCV that challenge the tacitly accepted, but controversial, notion that cocaine enhances dopamine release in vitro. Next, we examined striatal dopamine dynamics using in vivo fiber photometry with dLight to assess slow and fast/phasic dopamine changes in DLS in comparison to other striatal subregions. In Pavlovian conditioning driven by a natural food reinforcer, we also found distinct characteristics of phasic dopamine dynamics in DLS compared to other striatal subregions. These findings improve our understanding of dopamine dynamics in dorsal striatum, and should promote further physiological and behavioral studies in dopamine dynamics throughout the striatum.p = 0.0022, FSCV t = 2.512, p = 0.0458, df = 6).We first wanted to examine the characteristics of dLight under conditions where dopamine is readily detected even in DLS. Thus, we performed simultaneous recordings using a PMT-based photometer and traditional FSCV in acutely prepared brain slices Fig. . Electrip < 0.05, F = 5.257) and FSCV  = 7.63) across several stimulation intensities Fig. To ensure that the electrically evoked dLight fluorescence transients were attributable to dopamine release from midbrain neurons, we used a viral strategy to genetically ablate substantia nigra dopamine neurons. We infused a Cre-dependent Caspase3-encoding virus into the substantia nigra and dLight virus into the dorsal striatum of DAT Cre mice Fig. . At leasp = 0.076, df = 8). Having shown that dLight signals could be decreased, we assessed whether they could be increased by increasing extracellular calcium levels, which would enhance dopamine release. Indeed, increasing extracellular calcium increased dLight fluorescent responses  demonstrating that dLight signals are truly dynamic. Further, these results demonstrate comparable performance between dLight photometry and FSCV measurements in terms of sensitivity to presynaptic inhibition and excitability induced changed in dopamine release.We next assessed whether dLight and FSCV signals would show similar dynamics during manipulations that decrease or increase dopamine release. Thus, we applied the D2 dopamine receptor agonist, quinpirole, to slices to inhibit dopamine release (via activation of presynaptic D2 dopamine autoreceptors). We found that 30 nM quinpirole inhibited dopamine release equally with both methods  inhibitor-mediated increases in DA release published using FSCV. However, in Patriarchi, et al.nts Fig. . We founnts Fig. . CocaineWe next determined whether a more specific DAT inhibitor, nomifensine (1 µM), would have effects similar to cocaine. Like cocaine, nomifensine increased the peak transient amplitude measured with FSCV Fig. , but not20. As expected, nomifensine (1 µM) effects measured with dLight photometry were not affected by the waveform modification  to peak at +1.0 V instead of +1.2 V Fig. . This waion Fig. . Note thWhen we assessed evoked dopamine release before and after application of nomifensine (1 µM) using the modified triangle waveform for FSCV measurements, we found that DAT inhibition increased dopamine transient duration Fig.  consiste21. To evaluate this hypothesis, we again performed simultaneous dLight photometry and FSCV recordings during which cocaine was applied to dorsal striatum brain slices from DAT KO mouse expressing dLight , it was posited that cocaine acted via a DAT-independent mechanismght Fig. . In DAT ice Fig. . Cocaine26. Thus, in a given space, the sampling volume obtained with FSCV is limited to the distance that dopamine can diffuse to the CFE surface. Under conditions of impaired DAT function, however, the diffusion distance of dopamine increases , the rate-limiting step in catecholamine synthesis and GFP to label dLight in mouse dorsal striatum. We found putative dopamine axons  juxtaposed to dLight/GFP Fig. , suggest29. We measured dLight fluorescence from the DLS of mice treated with cocaine (15 mg/kg i.p.) after a 10 min observation period in their home cage. We found that cocaine produced an increase in fluorescence that plateaued after 20 min  and amplitude . Furthermore, we found that cocaine increased the decay time constant of spontaneous dopamine transients .To determine the utility of dLight for measuring dopamine dynamics in DLS in vivo, we expressed the sensor in this striatal subregion and measured the fluorescence intensity profile using a custom-built in vivo fiber photometry system based on TCSPC principles Fig. . The in min Fig. , c. We amin Fig. . To exammin Fig. . We thenmin Fig. . We founTo determine if the fluorescence changes observed during our recordings originated from dLight and to ensure that the observed changes in fluorescence were due to dopamine actions on dLight , we further analyzed the fluorescence signals in eGFP-expressing mice . Figure p < 0.0001).Next, we characterized the phasic DA profiles in the DLS using in vivo dLight photometry, and assessed regional differences in dopamine transients during Pavlovian conditioning as this training paradigm produces clear behavioral changes associated with consistent and reliable phasic DA release in NAc. We trained animals in a well-established conditioning paradigm for a food reinforcer using a tone as the conditioned stimulus Fig. . During 30, we observed dopamine transients in NAc with a short latency after reinforcer delivery that gradually shifted to a short latency after the presentation of the CS+ during the conditioning  = 4.682). For example, in the NAc and DMS there was a gradual and significant increase in the dopamine transient from the early to late training phase . Some animals exhibited a CS + -associated dopamine transient during the first few conditioning trials  sometimes used in FSCV. Several observations indicated that the electrical stimulation-induced changes in fluorescence we observed were indeed due to dLight activation by dopamine released from nigrostriatal afferents. The transients were blocked by a D1R antagonist, strongly reduced following virally expressed Caspase3 ablation of DAT Cre+ substantia nigra neurons, and no responses were observed in slices expressing eGFP in place of dLight. We next sought to determine if regulation of dopamine release by the D2 autoreceptor would be similar when comparing the two methods and found that application of quinpirole (D2 dopamine receptor agonist) resulted in a similar average inhibition of evoked dopamine release measured with both techniques.We first used dLight photometry to examine electrical stimulation-induced dopamine increases, with simultaneous FSCV in brain slice experiments. In general, we found similar responses with both techniques across a range of stimulus intensities. We did detect photometric signals at slightly lower stimulus intensities, but still within the range where FSCV signals are observed in some studies0 or 500 nM DA per µm3). Thus, the fundamentally different sampling volumes for each method preclude statements about direct differences in sensitivity. Nonetheless, the inherently greater sampling volumes in in vivo and in vitro photometric methods facilitate the detection of dopamine (or any “volume” neurotransmitter) in a way that is not possible with single electrode voltammetric methods. We must emphasize, however, that our findings do not indicate that dLight is a more sensitive technique for detecting dopamine release. Findings with the two techniques cannot be compared directly, given factors including differences in the locations of dopamine detection and the carbon fiber dimensions. However, it seems safe to say that dLight photometry has a detection capability comparable to FSCV.Interestingly, evoked photometric responses were nearly maximal at stimulation intensities yielding a ~50% maximal voltammetric response. It is difficult to compare the sensitivity of the two techniques, as one needs to account for differences in sampling volumes that yield a response value per unit of measurement , or both35. Slow and phasic dopamine play distinct roles in behavior and motivation38. Microdialysis sampling with electrochemical detection techniques allows for measurement of absolute concentrations of dopamine that reach the probe (at least when using variants such as no-net-flux). Assessment of tonic dopamine levels within and between test sessions can also be obtained with microdialysis, but cannot be used to assess phasic changes in dopamine levels on a behaviorally-relevant time scale.Striatal  dopamine operates on multiple time scales and dopamine levels, including tonic as well as slow and fast/phasic changes39; can be used to measure slower changes in dopamine, but requires slower data acquisition (10 s of sec) that precludes simultaneous measurement of phasic dopamine changes. Given these limitations, dLight (and other fluorescent biosensors) represents a technological advance. As we demonstrate here, dLight allows for simultaneous assessment of slow and phasic dopamine changes within an in vivo testing session. This was evident in our experiments examining the effect of acute cocaine treatment on DLS dopamine levels where we observed an increase in baseline dopamine levels that developed over several minutes following cocaine administration. This was accompanied by increased amplitude, frequency, and duration of phasic dopamine transients. In contrast to our in vitro work, we observed a cocaine-induced increase in transient amplitude in vivo. This is likely due to the slower sampling rates used for our in vivo recordings (20 Hz) which may slightly underestimate phasic responses to the highest burst firing frequencies of dopamine neurons (up to 100 Hz) which are thought to underlie phasic dopamine transients41. Indirect cocaine effects may also contribute to increased transient amplitudes in vivo. For example, cocaine could alter midbrain dopaminergic neuron firing in vivo, and this could also contribute to transient amplitudes42. The dopamine transients in DLS preferentially reflect locomotion in naturalistic motor behaviors43 and even after cocaine injections13. Increased locomotion induced by cocaine injection may also contribute to increases in transient amplitude and frequency. Such effects would not contribute to dopamine release in brain slices.Like FSCV, dLight photometry cannot measure the absolute tonic extracellular dopamine concentration. The subsecond sampling in FSCV allows for measurement of phasic dopamine levels but due to the need to subtract a recent baseline signal, it is generally not useful for determining slow changes in dopamine levels. A variant of FSCV using an altered waveform known as FSCAV47. Thus, the ability to simultaneously assess slow and phasic changes in dopamine release in freely behaving animals will be of great use to the field.An understanding of the significance of slow and fast/phasic dopamine changes is important. Changes in phasic dopamine release can occur in the absence of slower changes in dopamine levels and vice versa. Also, tonic and slow, long-lasting changes in dopamine levels may serve to influence global striatal activity or metaplasticity. For example, the chronic  dopamine deficiency observed in PD models is often accompanied by changes in synaptic plasticity or altered cellular physiology48. Thus, it is possible that sampling at 200 Hz with dLight1.1 will yield a large data set that would not differ practically from a data set collected at 100 or even 20 Hz. These fluorescence kinetics may also limit interpretation of transient rise times or modeling of decay kinetics, as the fluorescent signal may not actually represent the termination of neuromodulator signaling but rather the off rate of the sensor. Thus, consideration of the experimental question and the type of data that can be collected should be considered when choosing a fluorescent biosensor49.Sampling rates can be much faster with photometry than with FSCV. FSCV sampling is inherently limited by the electrochemical properties of the triangle waveform (~8 ms) and the time required for desorption of dopamine from the CFE surface, resulting in a maximum practical sampling rate of up to ~50 Hz . In contrast, the sampling rates for photometric methods are limited by the binding and unbinding rates of the sensor and the digitization rate of the data acquisition hardware used. Our in vitro photometric responses were collected at 100 Hz or 1000 Hz, although rates up to 20,000 Hz are possible with our hardware configuration. In vivo fiber photometry sampling rates with most available systems can also exceed 100 Hz. However, given the known time course of dopamine signaling and dLight kinetics we chose to perform our recordings at 20 Hz. It is important to note that, with photometric methods, the fluorescent on/off rates of dLight (or other biosensors) will limit the utility of high sampling rate data. For example, the on and off rates for dLight1.1 are ~10 and 100 ms, respectively52 utilized an indirect electrophysiological approach to measure GIRK-mediated currents activated by D2 dopamine receptors. Like the dLight method we used, this approach likely represents a mixture of synaptic and extrasynaptic actions of dopamine, but is not amenable to in vivo use. More recent work from the Williams lab used two photon excitation with dLight to measure dopamine release at spatially discrete sites in the midbrain53. These authors concluded that the time course of D2 receptor-mediated responses was dictated largely by dopamine release and not diffusion. Given the sparsity of dopamine release sites in midbrain, it is possible that these spatially discrete sites represent dopamine synapses. Thus, the use of dLight with high-resolution imaging methods may allow for measurement of synaptic dopamine release. Furthermore, with dual color fluorescence imaging methods, synaptic markers could be employed to allow for labeling of pre- or post-synaptic elements to colocalize with dLight (or other biosensor) signals, facilitating measurement of truly synaptic neuromodulator release.Using dLight it may be possible to assess truly “synaptic” dopamine release. That is to say, both microdialysis and FSCV are methods that measure dopamine overflow out of the synapse collected or detected at a site distant from most release sites. Because of the size of the probes, sampling of dopamine at synaptic release sites has not been possible with either of these methods. In this context, dLight represents another advance for the field because it can be genetically targeted to distinct cellular compartments. For example, dLight sensors are integral membrane proteins so they will only be expressed in membranes. We confirmed this with our electron microscopy work and show that indeed, dLight traffics strongly to plasma membrane, Golgi, and ER compartments of the neuron Fig. . Further55. Cocaine increases the duration of evoked dopamine transients measured with FSCV. Interestingly, measurements with FSCV show that cocaine (and other DAT blockers) also increase the observed dopamine transient peak amplitude in brain slices. This is often interpreted to mean that DAT blockers enhance or facilitate electrically evoked dopamine release in slice. From a pharmacological perspective, this is not intuitive as dopamine release should not be affected by DAT inhibition. Interestingly, Patriarchi et al.11 noted that there was no increase in dLight dopamine transient peak amplitude in response to cocaine application. Following up on this, we examined cocaine effects on dopamine transient peak amplitude and duration in our simultaneous dLight and FSCV recordings. Similar to previous work, we observed a large cocaine-induced increase in dopamine transient peak amplitude with FSCV but only modest or no effects with dLight . This should result in prolonged phasic dopamine transients and, in regions where the DAT function is the primary mechanism of dopamine clearance, increases in tonic dopamine levels. Indeed, with microdialysis, the expected increases in tonic dopamine have been confirmedght Fig. . With boght Fig. . We posi24.In a follow-up experiment, we applied cocaine to dorsal striatal brain slices from DAT KO mice. We did not observe any cocaine-induced increase in dopamine release Fig.  in DAT K56, but under conditions of impaired DAT function  the diffusional spread of dopamine from its release site is increased26. This would effectively increase the sampling volume of CFEs allowing for greater FSCV detection of dopamine (and increased dopamine transient peak heights) in the absence of an actual increase in release. Further, because the sampling volume used in photometric methods is already much larger than with FSCV methods, the cocaine-induced increase in dopamine diffusion from its release site has a more negligible effect on dLight/photometric dopamine transients. Thus, we believe that dLight more faithfully reflects dopamine release spatial dynamics than FSCV, especially under conditions where dopamine overflow or uptake may be affected.Altogether, our data do not support the idea of DAT blocker-induced increases in dopamine release. Therefore, we posit the following alternative interpretation of the observed DAT blocker-induced increases in dopamine transient peaks using FSCV. Rather than increasing or facilitating dopamine release, DAT blockers by virtue of their inhibition of dopamine clearance allow for an increase in the point diffusion of dopamine from its release site. That is to say, under normal conditions, the diffusion of dopamine is limited by several factors, most notably DAT62. However, there is to date little information about subregional differences in dopamine transients driven by environmental stimuli or associated with behavior and measured in vivo.We compared dopamine transients across the three striatal subregions: the NAc, DMS, and DLS as animals learned a Pavlovian association between a CS+ and reward. We found that dopamine transient decay times were faster in DLS than in NAc, with intermediate levels in DMS. These findings are consistent with the kinetics of electrical stimulation-induced dopamine transients measured in brain slices and in vivo64. The sustained elevation between CS+ delivery and reward is not always observed, but has been seen in past studies that used FSCV or dLight fiber photometry during performance of in vivo learning tasks36. In our experiments this increase appeared to be tied to expectation of reward delivery  laser or light emitting diode (LED), the MHz pulsed laser system used in the TCPSC measurement also minimizes the period of light exposure to the fiber cladding and has a high-pass filtering effect that reduces the likelihood of fiber bending-based artifacts. This system does not include the “isosbestic” excitation control used in several fiber photometry systems65. Instead, using eGFP alone fluorescent controls in the current study and in previous work from the lab we observed no evidence of artifactual changes in fluorescence29. For these reasons we are confident that the dLight signals we measured in vivo with TCSPC truly indicate changes in striatal dopamine. Likewise, several control experiments including recordings with eGFP alone, blockade of the signal by SCH23390 and loss of signal after lesioning SNc neurons indicate that the stimulus-induced fluorescence increases we observed in brain slices reflect dopamine increases, and these findings are consistent with data from our previous studies indicating that photometry signals using this approach are not contaminated by endogenous fluorescence or other non-sensor sources67.In vivo fiber photometry technical difficulties include potential artifacts related to fiber bending which can result in light exposure to fiber cladding, usually related to animal movement. Thus, it is important to include crucial analyses and control procedures that can detect such contaminating signals. We and others have used time-correlated single photon counting-based fiber photometry to measure signals with a variety of genetically-encoded sensors in tasks including the open field, operant lever pressing, and the accelerating rotarod69. The findings in NAc and DMS in the Brown et al.9 study are similar to those that we observe with dLight fiber photometry in well-trained mice. However, measurements with FSCV in DLS show little-to-no fast dopamine release in response to unexpected food reward or a positive discriminative stimulus (DS+), and a non-significant slower-developing increase that persists for a few seconds after DS+ presentation. The behavioral correlate of this late, slow component of dopamine release is unclear, but it might be related to movement. From this study it was not clear if the lack of dopamine changes in DLS were due to the inability of FSCV to detect dopamine in this region or if DLS dopamine increases are not produced by reward or predictive stimuli. Our findings indicate that both stimulus and reward-related dopamine increases can be detected in DLS in mouse using dLight fiber photometry, consistent the former conclusion. It should also be noted that Brown and coworkers did not provide information regarding the time course of dopamine release changes over the course of training, as we have been able to do with dLight fiber photometry. In the Howe et al.68 study, gradual “ramping” increases in dopamine were observed in DLS on less than half the trials as rats approached the goal in a Y-maze task, but no fast/phasic changes in dopamine were observed. The Klanker et al.69 study showed small increases in DLS that appeared to be related to movement initiation in a well-learned operant task, while van Elzelingen et al.70 showed dopamine signals in rat DLS during Pavlovian conditioning behavior. These responses were not followed over the course of initial training, but were examined during the course of reversal training. Willuhn and coworkers10 were able to detect fast/phasic dopamine increases in rat DLS that developed over the course of cocaine self-administration using FSCV. However, the prolongation of dopamine increases produced by this DAT blocker likely facilitated detection of this increase. It should now be clear that past studies showed dopamine detection in rat DLS, but our findings provide detailed information on responses to drugs and environmental events in this important striatal subregion in mouse, as well as evidence that we can measure both slow and fast changes in dopamine simultaneously throughout the course of pharmacological and extended behavioral studies.Dopamine release in DLS was measured previously using FSCV in rat conditioning and y-maze paradigms71 mice were obtained from the Sara Jones laboratory at Wake Forest University. Male and female DAT-IRES-Cre and DAT KO transgenic mice were used in all experiments. All mice were housed with 2–4 mice per cage and maintained on a 12:12 h light cycle and ad libitum access to food and water.Three-month-old, male C57BL/6J mice were obtained from the Jackson Laboratory (Strain 000664) and pair-housed in the vivarium for at least 1 week before any experimental use. DAT-IRES-Cre mice were obtained from the Jackson Laboratory (Strain 006660) and bred in house. DAT KOAll procedures performed in this work follow the guidelines of the Institutional Animal Care and Use Committee of the Division of Intramural Clinical and Biological Research, National Institute on Alcohol Abuse and Alcoholism, and the animal care and use protocol (# LIN-DL-1) was approved by this committee.11 vg/mL) or purchased from Addgene . AAV9-CAG-dLight1.1 are only partially used in Fig. 13 vg/mL).The Caspase3-coding virus (AAV1-EF1a-FLEX-taCasp3-TEVp) was custom packaged by Vigene Biosciences and a gift from Dr. Huaibin Cai, National Institute on Aging. dLight1.1 viruses were used for in vitro experiments and were either generated in the Tian laboratory and sent to NIAAA , nucleus accumbens  or substantia nigra  and a 1 µL Neuros Hamilton Syringe was lowered slowly to the desired depth from the brain surface . For in vivo experiments, viruses were injected in the following coordinates. NAc , DMS , DLS  where AP and ML in mm from Bregma, DV in mm from the brain surface. Virus infusion volumes were 300 nL for dorsal striatum and 500 nL for VTA and viruses were infused at 50 nL/min. After infusions were completed, the syringe was left in place for 10 min before withdrawal and the incisions were closed with VetBond. Mice recovered for at least 3 weeks before being used for in vitro experiments or fiber optic implantation for in vivo experiments.72 method using CFE. For brain slice preparation, mice were anesthetized with isoflurane, rapidly decapitated. Then brains were extracted and immersed in ice-cold, carbogen-saturated (95% O2/5% CO2) ACSF. Next, 300 µm thick coronal sections prepared on a vibratome (Leica VT 1200S). The slices were hemisected and inspected to ensure viral expression of dLight in the region of interest using an epifluorescent Zeiss AxioZoom microscope equipped with a GFP filter set . Then the slices were incubated at 32 °C for 30 min before being moved to room temperature for one hour before beginning experiments.Photometric measurement was conducted using dLight1.1 or dLight1.3b and simultaneous voltametric recording was performed by a traditional FSCV73 and placed in the tissue in the center of the recording region of interest under ×4 magnification. Slices were then visualized with ×40 objective (0.8 NA) and the field of view (~180 µm × 180 µm) was adjusted so the stimulating electrode was just outside the field of view and the CFE was in the center of the field of view. Under ×40 magnification, the focus was adjusted to a focal layer beneath the slice surface where fluorescent cells could be identified. Fluorescent transients were quantified with a PMT-based system (PTI D-104 photometer) coupled with a Digidata 1322A (Molecular Devices LLC) to digitize the PMT signal (100–1000 Hz). Clampex v9 software was used to collect photometry data and synchronize photometric and voltammetric recordings through the Digidata. A mechanical shutter (Uniblitz V25) was used to limit exposure to fluorophore-exciting light to discrete periods and minimize photobleaching of the dLight between recordings. FSCV recordings73 were carried out using a following protocol. A triangle waveform voltage was applied to the CFE beginning at −0.4 V to +1.2 V and back to −0.4 V. This scan was applied at 400 V/s and repeated at 10 Hz. Dopamine was identified electrochemically by the oxidation peak at +0.6 V on the ascending phase of the triangle ramp. Dopamine release was evoked with electrical stimulation delivered every 3 min using a constant current stimulus isolator (DigiTimer DS3). Input–output (IO) curves were generated to examine evoked dopamine release measured with both techniques across varying electrical stimulation intensities . For pharmacological experiments, a stimulation intensity yielding ~30–60% of the maximal responses with both methods was used to ensure that any subsequent treatments were not limited by floor or ceiling response effects. Baseline responses were collected for 12–20 min before drugs (dissolved in ACSF) were bath applied as indicated for each experiment.Brain slices with dLight expression were moved to an upright Zeiss AxioSkop2 microscope mounted on a XY translational stage and equipped with a GFP filter set. Oxygenated ACSF was perfused at 1.5–2 mL/min and warmed to 30–32 °C. The recording region of interest was located under ×4 magnification and fluorescent illumination to ensure dLight expression in the region of interest. Then a stainless steel twisted bipolar stimulating electrode (P1 Technologies) was placed on the tissue surface near the area of dLight expression. For simultaneous photometry-voltammetry recordings, glass-encased carbon fiber electrodes (80–120 µm exposed length and 7 µm tip diameter) were created by aspirating a 1.2 mm glass capillary under microscope inspection29. First, mice were anesthetized and mounted into the stereotaxic apparatus and an incision was made in the scalp along the skull midline as before. The skull was cleaned with a 3% H2O2 solution to remove any connective tissue and the skull was scored several times with a scalpel to create a better surface for the dental cement headcap at the end of the procedure. Craniotomies were made over the brain region of interest and two distal sites for anchor screw placement. Fiber implants  were placed in the following coordinates: NAc , DMS , DLS  where AP and ML in mm from Bregma, DV in mm from the brain surface. The anchor screws were placed before proceeding to the fiber optic placement. To ensure optimal fiber optic placement, fluorescence intensity was monitored intraoperatively using a custom designed fiber photometry system consisting of a 473 nm picosecond pulsed laser, a HPM-100-40 hybrid detector, and a SPC-130EM time-correlated single photon counting (TCSPC) module and software (Becker & Hickl). The measurement rate for the fluorescence lifetime and intensity profile was set at 20 Hz during all animal experiments. The output was a custom multimode patch cord from Thor labs with a 0.22NA and 200 µm fiber core diameter terminating in a 2.5 mm ceramic ferrule. The patch cord ferrule was connected to the fiber optic cannula  to be implanted with a ceramic mating sleeve. The implantable fiber optic cannula was lowered slowly into the craniotomy over the brain region of interest while the fluorescence intensity at the desired emission wavelengths (~500–540 nm) was monitored. The fluorescence intensity typically increased as the fiber optic approached the area of dLight expression. Once fluorescence intensity plateaued, typically ~300–500 µm dorsal to the virus infusion site, the fiber optic cannula was cemented in place and the surgical site was closed around the dental cement headcap. Mice recovered for at least 2 weeks before further experiments.At least 3 weeks after virus infusion surgeries, mice used for in vivo experiments underwent a second surgery to implant the optical fiberFor the Pavlovian conditioning experiment, the TCSPC system was synchronized to the operant behavior boxes (with MED-PC4 software) through a TTL channel, in which the TTL pulse generated by MED-PC controller was used to trigger the TCSPC system acquisition for 10 s prior to each trial (CS+ or CS−) and maintained 60 s of data acquisition. The pulsed laser was continuously turned on and sustained stable laser illumination during the entire session. In vivo pharmacology measurements were continuously recorded for 60 min. Before the recording, the animals were tethered with an optical patch cord with laser illumination, and habituated for 20 min in the open-field arena without recording.To test the possibility of patch cable vibration effects on fluorescent signals captured with TCSPC we devised a benchtop testing system . No stimulus cue was provided during these sessions. After 3 days of food restriction and pre-training, mice underwent Pavlovian conditioning sessions. The discrimination training entailed two conditioned stimuli; one conditioned stimulus (CS+) was a high-frequency auditory cue followed by the unconditioned stimulus  as a reinforcer, and a second stimulus (CS−) was a low-frequency auditory cue which was not accompanied by a reinforcer delivery. Within a single session, mice received 20 CS+ trials and 20 CS− trials. In the operant conditioning box within sound and light attenuating enclosures, the auditory cue was presented for 4 s with random intertrial intervals (60–120 s). In the CS+ trials, an US reinforcer was delivered to a pellet receptacle 1 s after the CS+ cue offset. In vivo photometry measurements were conducted every other day during the training, but the mice underwent the same continuous daily Pavlovian training sessions while tethered to an optical patch cord  even if photometry measurements were not conducted. Therefore, DLS and DMS mice received 10 weeks of consecutive daily Pavlovian training. NAc mice received 4 weeks of Pavlovian training. All animals received the behavior training with 24 (+/−2) hours of interval at their own designated time, and animals were acclimated to the behavior room for at least 1 h before all training sessions.After completion of behavioral experiments, mice were transcardially perfused with PBS followed by 4% paraformaldehyde. The brains were then extracted and postfixed overnight in 4% paraformaldehyde. The following day, brains were transferred to PBS until sectioning. 100-µm-thick sections were prepared through the anterior to posterior axis of the striatum on a vibratome . These sections were then processed for GFP immunofluorescence. First, the sections were washed four times for 10 min each in PBS. Then the sections were incubated in PBS containing 5% BSA/0.2% Triton X for two hours before an overnight incubation at four degrees in a 0.5% BSA/0.2% Triton X/PBS solution containing a 1:2000 dilution of a Chicken anti-GFP antibody . The following day, the sections were rinsed four times for 10 min each in PBS before incubation in a secondary antibody solution containing a 1:2000 dilution of Donkey anti Chicken-AlexaFluor488  in a 0.5%BSA/0.2% Triton X/PBS solution for two hours at room temperature. The sections were washed again four times for 10 min each in PBS before being slide mounted and coverslipped with DAPI Fluoromount-G . Once dried slides were imaged on a Zeiss AxioZoom microscope and Zeiss Zen Black v3 software. Representative histology images can be found in Supplementary Fig. For anatomical studies, dLight virus injected mice were deeply anesthetized with chloral hydrate (35 mg per 100 g), and perfused transcardially with 4% (wt/vol) paraformaldehyde (PFA) with 0.15% (vol/vol) glutaraldehyde and 15% (vol/vol) picric acid in 0.1 M phosphate buffer . Brains were left in this fixative solution for 2 h at 4 °C, solution was replaced with 2% PFA and left overnight at 4 °C. Brains were rinsed with PB, and cut into coronal serial sections (40-μm thick) with a vibratome (Leica). All animal procedures were approved by the National Institute on Drug Abuse Animal Care and Use Committee.Free floating coronal vibratome sections were incubated for 1 h in PB supplemented with 4% bovine serum albumin (BSA) and 0.3% Triton X-100. Sections were then incubated with mouse anti-tyrosine hydroxylase (TH) primary antibody  and guinea pig anti-GFP  overnight at 4 °C. After rinsing 3 × 10 min in PB, sections were incubated in Alexa Fluor 594-affiniPure donkey anti-mouse  and Alexa Fluor 488-affiniPure Donkey anti-guinea pig  for 2 h at room temperature. After rinsing, sections were mounted on slides and air-dried. Fluorescent images were collected with Zeiss LSM880 Airyscan Confocal System . Images were taken with 20× objectives and z-axis stacks were collected at 1 µm. The confocal images were collected from 3 mice.2O2 in PB for 5–10 min. Sections were rinsed in PB, and then in double-distilled water, followed by silver enhancement of the gold particles with the Nanoprobe Silver Kit  for 7 min at room temperature. Next, sections were rinsed with PB and fixed with 0.5% osmium tetroxide in PB for 25 min, washed in PB followed by double-distilled water and then contrasted in freshly prepared 1% uranyl acetate for 35 min. Sections were dehydrated through a series of graded alcohols and with propylene oxide. Afterward, they were flat embedded in Durcupan ACM epoxy resin . Resin-embedded sections were polymerized at 60 °C for 2 days. Sections of 65 nm were cut from the outer surface of the tissue with an ultramicrotome UC7  using a diamond knife . The sections were collected on formvar-coated single slot grids and counterstained with Reynolds lead citrate. Sections were examined and photographed using a Tecnai G2 12 transmission electron microscope  equipped with a digital micrograph OneView camera .Vibratome tissue sections were rinsed with PB, incubated with 1% sodium borohydride in PB for 30 min to inactivate free aldehyde groups, rinsed in PB, and then incubated with blocking solution  for 30 min. Sections were then incubated with guinea pig anti-GFP primary antibody ; or both guinea pig anti-GFP (1:500 dilution) and mouse anti-TH (1:1000 dilution) for 24 h at 4 °C. Sections were rinsed and incubated overnight at 4 °C in the secondary antibody goat anti-guinea pig IgG Fab fragment coupled to 1.4 nm gold ; or the corresponding secondary antibodies: biotinylated goat anti-guinea pig antibody  and secondary antibody goat anti-mouse IgG coupled to 1.4 nm gold . Sections were incubated in avidin-biotinylated horseradish peroxidase complex in PB for 2 h at room temperature and washed. Peroxidase activity was detected with 0.025% 3,3′-diaminobenzidine (DAB) and 0.003% H74. Type I synapses, here referred as asymmetric synapses, were defined by the presence of contiguous synaptic vesicles within the presynaptic axon terminal and a thick postsynaptic density (PSD) greater than 40 nm. Type II synapses, here referred as symmetric synapses, were defined by the presence of contiguous synaptic vesicles within the presynaptic axon terminal and a thin PSD. Serial sections were obtained to determine the type of synapse. In the serial sections, a terminal or dendrite containing greater than 5 immunogold particles were considered as immuno-positive terminal or dendrite. Pictures were adjusted to match contrast and brightness by using Adobe Photoshop . The frequency of gold particles for GFP signals near to asymmetric synapses was counted from 3 mice. This experiment was successfully repeated three times.Serial thin sections of dorsal striatum of the mice were used in this study. Synaptic contacts were classified according to their morphology and immuno-label and photographed at a magnification of ×6800–13,000. We used the following morphological criteria for identification and classification of cellular components0) and stimulation-induced increases in fluorescence (dF) values were obtained. Most photometric data are presented as dF/F0 values to compensate for differences in basal fluorescence or dLight expression differences between slices. Voltammetric data were acquired in DEMON Voltammetry Software suite57, exported to Excel for organization, and plotted and analyzed in GraphPad Prism 9.In vitro photometric data were acquired in Clampex 9 and initially analyzed using Clampfit v9 or v10 (Axon Instruments/Molecular Devices), exported to Excel for organization, and plotted and analyzed in GraphPad Prism 7. The PMT readout was offset corrected to zero (with the shutter closed) before basal fluorescence (Fraw) values were plotted as a function of time. Then, these fluorescence time series were converted to dF/F0 in two ways. For the segmented photometry data  obtained from operant conditioning sessions, F0 was set to a moving average of each point before the onset of CS+, using a sliding window of +/−15 s, similar to previously published methods11. Therefore, the baseline was normalized across all measurements such that only phasic dopamine transients were quantified. Occasionally, there was a negligible bleaching effect (<0.1% of F0 degradation) within the 60-s of acquisition in our measurement setup even without the moving average normalization. For the continuous photometry measurements over 60 min duration in the in vivo pharmacology experiments, actual recording was performed after a 20 min initial bleaching period without recording. The F0 was estimated by a curve fitting method. We first validated that the degradation of fluorescence intensity was well predicted by an exponential decaying model. For this validation, we used control mice virally transduced to express GFP in dorsal striatum and dLight expressing mice having no drug injection to confirm the baseline prediction method. Then, for the actual experimental animals with cocaine and saline injections, the baseline curves of F0 were estimated from the 20-min baseline measurement prior to the i.p. injection. Once the F0 baseline was estimated, dF/F0 was calculated using the standard method, in which dF = Fraw − F0 and F0 is the predicted baseline by exponential curve fitting.In vivo fiber photometry data were collected using the SPCM64 9.8 Software (Becker & Hickl). The raw photon counts were exported in ascii format for analysis with custom Python or MATLAB scripts. First, the fluorescence (F0) was normalized to the maximum intensity. The data points following the maximum intensity peak were fit using a double exponential decay model. In the fitted curve, the time point where the normalized fluorescence profile passed under 36.8% of the maximum intensity was selected as the transient decay time (or lifetime) of the phasic dopamine activity in each brain regions.For each CS+ trial, maximum peak location was identified using custom Matlab code. Then the fluorescence profile , nomifensine, quinpirole-HCl, and SCH23390 were purchased from Tocris Bioscience. Dopamine-HCl was purchased from Sigma-Aldrich. All drugs were dissolved in ACSF. All other drugs and reagents, unless otherwise indicated, were obtained from Sigma-Aldrich.GraphPad Prism 9.2 was used for all data analysis and statistics. For I-O curve comparison, two-way ANOVA (method and stimulation intensity) was used. For the analysis of the caspase lesion curves, a mixed effects model was used (genotype and stimulation intensity factors). For the quinpirole inhibition and high calcium experiments, unpaired two-tailed t-tests were used. For data comparing in vivo transient amplitude, frequency, and decay constant changes, unpaired two-tailed t-tests were used. For analysis of the dorsal striatum subregion changes in decay constant, one-way ANOVA was used. Unless otherwise indicated, all data represent the mean ± SEM.Further information on research design is available in the Supplementary InformationReporting SummarySource Data


The disciplinary identity of molecular biology has frequently been called into question. Although the debates might sometimes have been more about creating or debunking myths, defending intellectual territory and the distribution of resources, there are interesting underlying questions about this area of biology and how it is conceptually organized. By looking at the history of molecular biology, its origins and development, I examine the possible criteria for its status as a scientific discipline. Doing so allows us to answer the title question in such a way that offers a reasonable middle ground, where molecular biology can be properly viewed as a viable interdisciplinary program that can very well be called a discipline in its own right, even if no strict boundaries can be established. In addition to this historical analysis, a couple of systematic issues from a philosophy of science perspective allow for some assessment of the current situation and the future of molecular biology. YNO1), I never actually got to publish on the historical and philosophical trajectory of molecular biology. This special issue “in honor of Prof. Michael Breitenbach” is now a welcome opportunity to finally do so. Thank you, Michael, for your broad and thorough scientific and philosophical interests!) The answer that I develop and defend here is as follows. If by “discipline” one means a stringent and uniform theory or a closed and uniform framework of institutions, methods, theories, etc., then molecular biology would not be a discipline of its own. However, the same negative assertion would then also apply to numerous other domains of research that are usually considered disciplines without any controversy. Hardly any of the many fields, such as medicine, meteorology, geology, philosophy, etc., that we ordinarily do refer to as “disciplines”, would fall under such a narrow conception of what constitutes a discipline. We may thus rightfully ask what the criteria are to justifiably calling something a discipline. Ideally, such a notion would not be so narrow as to exclude its intended extension. On the other hand, when taking into account that in practically all areas of biological research molecular aspects play an essential role, one might ask whether the boundaries are totally blurred and whether any biology nowadays would be molecular. That is to say, “molecular biology” might be considered a pleonasm like “round circle”, “unmarried bachelor” or “dead corpse”. Putting “molecular” in front of “biology” would thus be verbally redundant.The main question of this paper is whether and why molecular biology can be considered a discipline of its own. . Addressing this question is not merely a fight about semantics and which terms can be applied—these questions are crucial for navigating the present, past and future of molecular biology, upon which a number of scientific, historical and philosophical questions depend.This paper will proceed as follows. First, I will argue in real science”.Whereas it would be difficult to find anyone openly denying the worth of history of science in general, there are mixed opinions about its value for the everyday practice of science. Why should someone working at the lab bench have to deal with old chestnuts or dig up old, dusty journals and lab notebooks? One might say: “Shouldn’t we push the frontiers of science instead of stirring up old stories and outdated ideas that didn’t hold up to today’s scientific standards? There are better things to do, researchers are busy surviving in their precarious publish-or-perish environment anyway. Let the historians and philosophers have their fun—at least they won’t be in the way and prevent us from doing Such an attitude would certainly be detrimental to science and its progress. Just imagine that no one ever cared about the results from a certain Augustinian monk who bred peas in his garden. However, apart from such spectacular examples such as the rediscovery of Mendel’s observations by de Vries, Correns and Tschermak in 1900 One way in which history of science can benefit scientists is also by letting go of some illusions: “the delight of demystifying science of its more pretentious claims to rationality and orderly procedure, the delight of revealing for once, or seeming to reveal, what scientists “really do”—which turns out to include coffee breaks and gossip”  (p. 26).“Self-improvement, illuminating science and making it betterEfficiency, avoiding and learning from past mistakesPerspective, providing judgment and clarity and therefore making science betterImagination, offering a wider repertoire of ideas to choose fromEducation, improving public understanding of science and scientific literacy”  (p. 342)Maienschein and colleagues distinguish at least five general categories in which the history of science matters for scientists:There is some awareness of the importance of history in contemporary research and teaching practice, as a welcome example from a recent textbook shows: “we have continued to present the field in a historical context, with the intent of sensitizing and inspiring students (and others) to the realities of how research progress unfolds and how ideas develop and attain maturity—or not. We have refrained wherever possible from unadulterated dogma and from presenting the field […] as anywhere near total clarification. While we are aware of presenting viewpoints that are sometimes controversial and even conflicting, we trust that readers, especially students, are not unduly confused or frustrated by our reluctance to always provide the final word, as it were. Rather, it is our hope that such controversies and complexities will inspire further studies”  . Taken To be transparent about my aims here: I want to argue that studying the history—not only of one’s own discipline—enriches the everyday business of systematic researchers. In doing so, one should not only consider the already established and easily accessible resources but also those that might have received less attention. Who knows what kind of treasures are still buried in the archives? The value that the history of molecular biology has to offer—in addition to the general reasons outlined above—also lies in the fact that biology is a dynamic and rapidly evolving domain of research. In order not to float aimlessly alongside the latest trends without any orientation, studying some history provides an important perspective. Finally, there is the title question of this paper: where to define the place of molecular biology as a scientific discipline?“The biggest difficulty in discussing the history of molecular biology is in knowing just what the term means, and what lines of demarcation can be drawn between it and other fields of biology. Of course biology is multidisciplinary, and its area of interest lies at the interface between several established fields […] and the question arises what distinctive element there is in the approach of molecular biologists to justify a special name”  (p. 5).Before tackling the multi-faceted question about molecular biology’s status as a scientific discipline, let us start with the most basic question: what is molecular biology?x?” questions are often the most difficult to answer and often how philosophical debates get started. When asked by family or friends what one’s area of scientific work centers around, one often has to first clarify that “microbiology” and “molecular biology” are different terms and different fields. With that out of the way, you might then have to explain to your increasingly confused conversation partner that it is a kind of mixture of biology, physics, chemistry, genetics, etc., that studies the processes of living organisms on the molecular level. You may go on to highlight, for example, the particular protein or pathway your lab is working on—and how it might in the future contribute to understanding a certain disease. Frequently, that will be acknowledged with some interest and skepticism. Sooner or later, however, the inevitable question on an afternoon walk will come up: “which kind of plant or animal is that? Aren’t you a biologist? You should know!” Unless by lucky chance you can answer this question, your opposite will feel confirmed in their skepticism. “This one wants to be a biologist? They don’t even know the animals/plants  heterogeneous areas are assembled under this umbrella term” t has become next to impossible for a single mind fully to command more than a small specialized portion of it.I can see no other escape from this dilemma (lest our true aim be lost for ever) than that some of us should venture to embark on a synthesis of facts and theories, albeit with second-hand and incomplete knowledge of some of them—and at the risk of making fools of ourselves”  (p. 1).What has now been the reason for the great popularity and attractiveness of this book? M. Morange puts it as follows: “Schrödinger presented the new results of genetics in a lively, compelling way—much better than the biologists had. Fifty years later, the book has lost none of its seductiveness: its clarity and simplicity make it a pleasure to read.A modern molecular biologist would feel quite at home reading Schrödinger’s book”  (p. 74).F. Jacob’s analysis of the time and spirit make clear what made Schrödinger’s book so “timely”: “After the Second World War, many young physicists were shocked by the military use made of atomic energy. Some of them, moreover, were dissatisfied with the direction taken by experiments in nuclear physics, by their slowness and by the complexity inherent in the use of large machines. They saw in this the end of a science, and looked around for other activities. Some turned to biology with a mixture of anxiety and hope: anxiety, because all they usually knew about living organisms consisted of vague recollections of zoology and botany acquired at school; hope because some of their most celebrated elders pointed to biology as a science full of promise. Niels Bohr saw it as the source of new laws of physics awaiting discovery. Schrödinger also prophesied a new and exhilarating era for biology, particularly in the field of heredity. Just to hear one of the leaders in quantum mechanics asking “What is life?” and then describing heredity in terms of molecular structures, inter-atomic bonds and thermodynamic stability was enough to fire the enthusiasm of certain young physicists and to bestow some sort of legitimacy on biology. Their ambition and interest were limited to a single problem: the physical basis of genetic information”  covered”  (p. 75).al myth”  (p. 8).foundational myth , it , it founyth (cf.  (p. 101)Despite all that, however, it must not be overlooked that a physical perspective did not and does not exhaust the methodological approaches in biology. This is now also widely accepted by philosophers of science: “It [biology] knows questions and modes of explanation that do not exist anywhere else. A philosophy of science that is exclusively oriented towards physics cannot do justice to biology and thus the entirety of science” , my tranideal gas assumptions are common, to conceptualize an ideal organism does not seem appropriate for all kinds of reasons. The term alone appears to summon the wraiths of vitalism and eugenics. However, there is a deeper problem. Biological regularities are substantially different from physical laws. The latter often claim unrestricted validity for all times and spaces. Biology, on the other hand, deals with a restricted subject area, where generalized claims are regularities and tendencies that are full of exceptions and limitations. By comparing biology to the ideals of physics, one could be tempted to ask with J. J. C. Smart: “Can Biology Be an Exact Science?”  several non-trivial difficulties with [Crick’s] version of that research program, his strategy as a whole has by no means been refuted. It is doubtful, moreover that it is even possible to refute a strategy […].In any case, [Crick’s] program is not utterly without antecedents […] [molecular biology] makes sufficient improvement on those antecedents that, as long as we consider [the “central dogma”] as a program rather than a doctrine, we can hope that some way can be found for it to triumph over the difficulties we have noted.In the meantime we have [several] programs of [biological] research […] As programs of research perhaps neither should be reviled as dogma” Now that we have established interdisciplinarity as an intrinsic feature of molecular biology—held together by a common epistemic interest that tries to understand biological phenomena by studying the interactions of molecules in and between cells—we can proceed to answer the title question.narrow sense). However, for practical and organizational reasons, for academic research and teaching, and for reasons of a common epistemic interest, it is indeed a subject area that might justifiably be called a discipline in a wider sense, acknowledging the vagueness of applying the term loosely.My answer is this: molecular biology has always been more of an interdisciplinary framework and thus not a separate scientific discipline of its own ”  and the apparent signs of death as a discipline—absence of new chairs and journals—is meaningless. It was created as a research area, which is still fully active”  (p. 40).Besides all that, however, I argue that the framework of molecular biology as a discipline (in a wider sense) offers enough space and possibilities for new developments to be included in its epistemic interest. Only if that were not the case, one could hold dogmatism against molecular biology. Even if science  has become more conservative  and less“[S]ystems and synthetic biology, […] are, ultimately, more a continuation and culmination of long-standing research programmes in biology than revolutionary new approaches”  (p. S42)Putting on a new disciplinary label would hardly bring any significant innovation or improvement to biology. Instead, I think it would be beneficial to use the term “biology” in a more inclusive, interdisciplinary semantic meaning, as it has already been the case for “molecular biology” from the start. Perhaps the expression “life sciences” is the most inclusive one that embraces the plurality of (sub)disciplines at work. Rigid disciplinary boundaries and habitual adherence to assumptions and principles, of which no one knows exactly when—and for what reason—they became established, have certainly promoted scientific progress less often than those phases where new approaches, methods, and technologies were used to open new scientific horizons. These are lessons one can take from the history and philosophy of molecular biology.The obscurity and large sizes of scientific projects can be overwhelming and call for particular emphasis on interdisciplinary collaborations. This cannot just be a temporary meeting of representatives of different disciplines in the same room or the publication of articles between the same two book covers without really having reached any understanding and afterwards everyone proceeding in their field as before. To reach a proper understanding and progress, “science needs philosophy” .My aim in this paper was to show that the history and philosophy of science offer important lessons and can contribute to a proper understanding of the disciplinary status of molecular biology as well as its current situation and future developments. I argued that “molecular biology” is neither a pleonasm nor a discipline in a narrow sense but that we should acknowledge its interdisciplinary past and open future. One essential insight in that respect is “that we turn away from the perspective of a more or less well-defined disciplinary matrix of twentieth century biology”  (p. 34).In addition, learning from the past about one’s area of research—irrespective of any labels seemingly demarcating separate disciplines—can be informative for contemporary researchers forging their own path, which often might not follow any clear demarcation lines either. Life scientists of the twenty-first century will be well advised to be open to new technologies and experimental techniques from different directions instead of defending any disciplinary territory. In fact, it may be exactly this openness that facilitated molecular biology as a scientific discipline in the first place—properly understood as an epistemic interest to study biological phenomena at the molecular and cellular level—while implementing a diverse set of techniques that allow us to manipulate and study the relevant macromolecules at play. In my opinion, this is what qualified molecular biology as a discipline in the past, still does at present, and will continue to do so in the future.


Neurodevelopmental disorders (NDDs) are a widespread and growing public health challenge, affecting as many as 17% of children in the United States. Recent epidemiological studies have implicated ambient exposure to pyrethroid pesticides during pregnancy in the risk for NDDs in the unborn child. Using a litter-based, independent discovery–replication cohort design, we exposed mouse dams orally during pregnancy and lactation to the Environmental Protection Agency's reference pyrethroid, deltamethrin, at 3 mg/kg, a concentration well below the benchmark dose used for regulatory guidance. The resulting offspring were tested using behavioral and molecular methods targeting behavioral phenotypes relevant to autism and NDD, as well as changes to the striatal dopamine system. Low-dose developmental exposure to the pyrethroid deltamethrin (DPE) decreased pup vocalizations, increased repetitive behaviors, and impaired both fear conditioning and operant conditioning. Compared with control mice, DPE mice had greater total striatal dopamine, dopamine metabolites, and stimulated dopamine release, but no difference in vesicular dopamine capacity or protein markers of dopamine vesicles. Dopamine transporter protein levels were increased in DPE mice, but not temporal dopamine reuptake. Striatal medium spiny neurons showed changes in electrophysiological properties consistent with a compensatory decrease in neuronal excitability. Combined with previous findings, these results implicate DPE as a direct cause of an NDD-relevant behavioral phenotype and striatal dopamine dysfunction in mice and implicate the cytosolic compartment as the location of excess striatal dopamine. A significant portion of risk for neurodevelopmental disorders (NDD) is environmental, yet very few environmental causes have been identified. Ambient exposure to pyrethroid pesticides during pregnancy has been implicated as a potential risk factor for NDD in the unborn child. Using a mouse model, we demonstrate here that low-dose developmental exposure to the pyrethroid deltamethrin causes an NDD-relevant behavioral phenotype, along with related changes in the dopamine system in the brain. These findings suggest a causal role for developmental pyrethroid pesticide exposure in NDD risk.Neurodevelopmental disorders are pervasive, often incurable disorders affecting as many as 17% of children in the United States . For insAlthough ASD is often considered a hereditary disorder, environmental causes contribute 38–58% of the variance in autism diagnosis . While oOne potential environmental cause of interest is developmental pyrethroid pesticide exposure. Pesticides are biocidal chemicals commonly used as household insecticides and are critical for the agriculture industry and public health control of mosquitoes . PyrethrCritically, evidence from recent epidemiology and longitudinal studies suggests that ambient prenatal exposure to pyrethroid pesticides poses a risk for autism, developmental delay, and neurodevelopmental disorders in general , 32–34. Dopamine dysregulation is a common toxic property of environmental contaminants that may underlie the link between exposure and neurological disorders . In humaRecent evidence from mouse models indicates that developmental exposure to the Environmental Protection Agency (EPA) reference pyrethroid, deltamethrin (DPE), at doses far below the EPA benchmark dose lower confidence limit (10.1 mg/kg), is sufficient to cause permanent alterations to dopamine neurotransmission in dorsal and ventral striata, including altered levels of dopamine, dopamine transporter (DAT), and dopamine D1 receptor expression . These cNeither the full spectrum of behavioral changes caused by DPE nor the alterations in dopamine storage, release, trafficking, and signaling are completely understood. One critical question is whether developmental exposure to low-dose pyrethroid pesticides causes a behavioral phenotype broader than that associated with ADHD, including behaviors relevant to autism, intellectual disability, and NDD in general. Further, whether the developmental changes in striatal dopamine function are related to changes in vesicular, synaptic, cytosolic, or extracellular dopamine is unknown, and each outcome would alter the potential pharmacological and neurological treatment approaches.To examine the effects of DPE in mouse, we exposed three independent cohorts of mouse dams to the pyrethroid pesticide, deltamethrin, at a dose well below the EPA-determined benchmark dose throughout pregnancy and lactation. We then performed behavioral and molecular assays on the resulting offspring using a litter-based design. We employed a broad behavioral battery encompassing several behavioral domains with multiple tests for each domain, including assays for social behaviors, restrictive and repetitive behaviors, communication, and cognition. Two cohorts were used as discovery cohorts for behavioral tests and a third cohort as a replication cohort. We further examined the effects of pesticide exposure on the striatal dopamine system by measuring total striatal dopamine, stimulated dopamine release and reuptake, dopamine vesicle protein markers, striatal DAT expression and function, and postsynaptic response kinetics. We hypothesized that DPE would cause an autism- and NDD-relevant behavioral phenotype and compartment-specific changes in dopamine that could be detected using these approaches.Exposures in the dams and behavior tests in the offspring followed the experimental timeline outlined in Fig. F = 4.5, P = 0.043; post hoc t test, P = 0.048]. Acoustic features of pup calls were unchanged by DPE  in mouse pups were assessed as a measure relevant to communication behavior Fig. . Male DPt test, discovery: P = 0.0016, replication: P = 0.019; Fig. U, P = 0.03; Fig. Marble burying and repetitive grooming/circling were used as measures relevant to repetitive behaviors Fig. . Adult DP > 0.1 for all measures; see Table Various assays of mouse social behavior were used as measures relevant to social functioning. There were no observed differences between control and DPE mice on measures of social behavior taken during assays for juvenile play, three-chamber social approach, social interaction, or social fear transmission  or fear acquisition . Nonetheless, DPE mice showed less freezing during fear recall , with 100% of control mice acquiring the operant response . There were no differences between groups in measures of tau (P > 0.1). We then quantified dopamine, its metabolites, and its cysteinyl adducts in striatal tissue using high-performance liquid chromatography (HPLC) , P = 0.0063; 3-methoxytyramine (3-MT), P = 0.019; Fig. χ2 test, P = 0.13; cys-DOPAC, χ2 test, P = 0.28). Cys-l-DOPA was detected in all samples but there were no differences between groups (P = 0.31).Stimulated dopamine release in the dorsal and ventral striata was quantified using fast-scan cyclic voltammetry Fig. . CompareLC) Fig. . DPE mict test, N = 12 per group, t = −0.79, P = 0.44).We assessed total dopamine uptake into striatal vesicles using a vesicular loading assay Fig. . There wF = 2.2, P = 0.037]. While action potential (AP) threshold and amplitude remained the same between groups (P > 0.1), action potentials in neurons from DPE mice had shorter durations . Nucleus accumbens core (NAc) neurons from DPE mice had a more pronounced inward rectifier current than those from control mice [MANOVA, exposure × IKir ratio, F = 4.7, P = 0.035; Fig. P > 0.1), suggesting a possible decrease in neuronal excitability.We measured electrophysiological properties of medium spiny neurons (MSNs) in the ventral striatum via whole-cell patch clamp recordings Fig. . There wF1,1 = 2.2, PF1,1 = 2.2, PF1,1 = 2.2, PThe critical question these experiments were designed to answer was whether developmental exposure to the pyrethroid pesticide, deltamethrin, which was identified as a risk factor for NDD when pregnant women are exposed , 32, is The primary strategy we used for behavior testing was to use behavioral batteries across the lifespan. There are some concerns with this approach, in particular the possibility that exposure to earlier assays may influence behavior in later assays. We sought to minimize these effects by organizing behavioral assays from least to most stressful; by testing the most stressful assays (fear conditioning and operant conditioning) in separate animals; by replicating every finding in an independent cohort; and by using separate animals for biological assays; all of which are the gold standard approaches . NonetheDPE mice showed multiple distinct repetitive behaviors in the marble burying and observation assays, which reduces concern over measure-specific confounds. Marble burying alone as an outcome measure is not without controversy. Marble-burying behavior is common in mouse models of autism, is correlated with repetitive digging, and may serve as a proxy for repetitive behavior in general , 53, 54.In the contingency degradation task with the discovery cohort, DPE animals failed more frequently at the initial operant training phase, ultimately invalidating the results from contingency degradation. This finding prompted the inclusion of operant conditioning in the replication cohort. Similarly, fear-conditioned DPE siblings used as stimulus animals for the social fear transmission task showed a decrease in freezing during fear recall, prompting the inclusion of classic fear conditioning in the replication cohort. The complementary deficits observed in these two very different tasks reduce concerns over potential task-specific confounds. Fear conditioning and operant conditioning classically rely on very different brain mechanisms, suggesting broader neurological changes than the striatum-specific effects described here, but one potential overlap is that both behaviors rely on dopamine released from dopamine neurons in the ventral tegmental area, a critical part of the mesolimbic dopamine pathway .Importantly, we did not detect any differences in the social behavior domain in DPE mice in juvenile social interaction, adult social interaction, social approach, or social fear transmission. Several of the most common mouse models of autism also lack social deficits, including most genetic knockouts of neuroligin, neurexin, and Shank1 . HoweverA major strength of this study is the use of discovery and replication cohorts, as well as multiple measures of each phenotypical element, which dramatically increases confidence that the observed differences are real. Additionally, different cohorts were tested in different facilities at Emory University and used mice from different origins due to facility restrictions , demonstrating the robustness of the replicated results and the generalizability across strains and testing conditions.Elevated levels of dopamine and dopamine metabolites were detected in the dorsal and ventral striata of DPE mice, along with an increase in stimulated dopamine release. One critical question for determination of downstream molecular effects and treatment strategies is which compartment contains this excess dopamine. Previous reports showed a decrease in extracellular dopamine in the striatum of DPE mice, potentially caused by an increase in striatal DAT . Total vO-methyltransferase (COMT) and monoamine oxidase (MAO), which modify different motifs on the dopamine molecule  was one of the earliest potential biomarkers associated with autism and is consistently identified in metabolomics studies of autistic individuals . Here, wmolecule . When domolecule , 67. Themolecule .IKir), which plays a key role in both action potential duration and neuronal excitability. There is evidence associating gain-of-function channelopathy in at least two subtypes of inward-rectifying potassium channels (Kir2.1 and Kir4.1) with autism, and Kir2.1 is highly expressed in striatal neurons, making this an interesting target for future investigation , with normal action potential threshold and amplitude. Action potential repolarization is primarily driven by potassium conductance, with a fast decay suggesting an increased conductance. Consistently, these neurons in DPE mice also showed an increased inward-rectifying potassium current  male and female offspring of female C57BL6/J or C57BL6/CR mouse dams. Virgin dams were kept on a 12/12 light cycle and given access to water and high-fat breeder diet  ad libitum. Dams were housed in female pairs, then in trios with a male sire until 3 days prior to birth, and then singly housed through birth and weaning. Offspring were weaned at P20–22 into same-sex cages and received water and standard mouse diet  ad libitum. A subset of offspring was weaned into mixed litter same-sex cages for use in operant conditioning. All procedures were approved by the Emory University IACUC and performed in accordance with the US Animal Welfare Act.The experimental design consisted of two groups: developmental deltamethrin exposure (DPE) and control. Female mouse dams were exposed to deltamethrin (or control) during preconception, pregnancy, and lactation as described below Fig. A. The daN = 1. In all experiments, each test subject was a representative animal chosen from its litter, so the N for each experiment represents both the number of animals and the number of litters. Patch clamp was the exception; the experimental unit was the neuron, with 2–3 neurons per animal recorded from a representative animal from its litter. To minimize cross-interference between tests, different animals from the same litter were used for behavior tests involving foot shocks , food restriction (contingency degradation and operant conditioning), and tissue collection; no animal experienced more than one of these. Because the primary effects of DPE on learning outcomes and molecular outcomes were previously observed in males  tested in the Emory University Whitehead animal facility. Discovery cohort B and the replication cohort consisted of the offspring of female C57BL6/J mouse dams  tested in the Emory University Yerkes National Primate Center animal facility. Colony housing conditions and care were otherwise identical among cohorts.N = 4; DPE, N = 5). In discovery cohort B, 20 females were offered doses; two were eliminated for insufficient consumption and two did not produce a litter, leaving 16 litters . In the replication cohort, 40 females were offered doses; three were eliminated for insufficient consumption and two did not produce a litter, leaving 35 litters . One litter in the replication cohort contained only a single male, and another litter contained only two males; these males were divided between operant conditioning  and fear conditioning , leaving 33 litters for all other tests . There were no differences between groups in eliminations.Dams that did not consistently consume the deltamethrin (as described below), or that did not give birth within 28 days of being housed with a sire, were eliminated a priori. In discovery cohort A, 12 females were offered doses of deltamethrin as described below. Two females were eliminated for insufficient consumption and one female did not produce a litter within the specified time frame, leaving nine litters  with a significance threshold of α = 0.05. Parametric data points greater than 3 SD from the mean were defined a priori as outliers, but no outliers were identified in any of our data.The analysis strategy for behavioral experiments was to use discovery cohorts to select primary outcome measures of interest and a directional hypothesis for each measure, which were then tested using an independent replication cohort. When possible, one-tailed statistical tests were used in the replication cohort because the only outcome of scientific interest was whether the effect from the discovery cohort was replicated. Cohorts were then combined using ANCOVAs, with cohort as a covariate, for the determination of combined Deltamethrin , the reference pyrethroid selected by the EPA , was disµL/3 g mouse, ∼6–10 µL average) was mixed with JIF peanut butter  to achieve the desired dose. Experimenters were blind to the contents of the corn oil mixture during exposures. The mixture was transferred onto the wire food hopper such that the dam could voluntarily consume it without additional handling stress and in a position where offspring would not have access. Home cage barriers were used during feedings to ensure individual dosing in the presence of adult cagemates. Dams that failed to consume 90% of the peanut butter during 90% of the feedings were eliminated from the study. Offspring were only exposed to deltamethrin indirectly through the dam. Offspring were weaned from the dam as above and received no additional exposure.Mice were developmentally exposed to the pyrethroid pesticide deltamethrin as described previously . StartinMultiple complementary behavioral assays were selected to address each of four multiple domains relevant to autism and NDD across the lifespan: social behavior, restrictive and repetitive behaviors, communication, and cognition Tables . To miniOffspring in the discovery cohorts were challenged with one of three different behavioral batteries: (i) contingency degradation only (with operant conditioning phase); (ii) a fixed-order behavioral battery consisting of (a) separation-induced USVs, (b) maternal potentiation of USVs, (c) juvenile play, (d) marble burying, (e) three-chamber social approach, (f) social interaction (with a novel cage observation phase), and (g) classic fear conditioning; or (iii) the same battery as in (ii) but with social fear conditioning instead of classic fear conditioning. We selected primary outcome measures of interest based on these experiments in the discovery cohort and challenged the offspring in the replication cohort with either (i) operant conditioning or (ii) a fixed-order behavioral battery consisting of (a) separation-induced USVs, (b) marble burying, (c) novel cage observation, and (d) classic fear conditioning. Methods for the behavioral assays conducted on the discovery cohorts appear in the Supplementary Methods, and results for these assays are summarized in Table N = 14 control litters and N = 17 DPE litters. The sex of pups was determined by the presence or absence of a black spot on the abdomen of males and/or inguinal teats in females. The order of testing was counterbalanced across sex. After the home cage was moved to the experimental room, one pup was transferred to a testing cup that was then placed in a soundproof recording chamber . Recordings were taken using a one-fourth-inch microphone attached to a conditioning amplifier  and controlled with MATLAB software . USVs were recorded for 5 min. The second pup from the same litter was tested in the same manner.Separation-induced USVs were observed at postnatal day 6 and 7 in one male pup and one female pup per litter from the replication cohort. Two litters were eliminated when their sessions failed to record, resulting in data from t tests were used to compare exposures within each sex.Call number was selected as the primary measure of interest and was compared between groups using a 2×2 ANOVA, with exposure (control or DPE) as a between-subject factor and sex  as a within-subject factor. Post hoc one-tailed N = 14 litters; DPE, N = 19 litters) were placed alone in an empty cage and digitally recorded for 10 min. Recordings were scored manually using The Observer software , with self-grooming as the primary outcome of interest. Self-grooming was compared between groups using a one-tailed t test.Adult male subjects in the replication cohort  were tested for marble-burying behavior as previously described  were each placed alone in a conditioning chamber . Their activity was recorded for 7.5 min in context A as they were exposed to a fear conditioning protocol consisting of a 3-min habituation period followed by five presentations of a tone  co-terminating with a mild foot shock  with 30-s intertrial intervals. On day 2, mice were returned to the conditioning chamber under context B and were exposed to an identical protocol without foot shocks. The primary outcome measure was freezing behavior during tone presentations on day 2. Descriptive data on baseline freezing and within-session fear acquisition from day 1 were collected and analyzed.The fear conditioning protocol was optimized to detect a decrease in cued fear recall in the experimental group. Immediately prior to the test, one subject was eliminated for fighting. On day 1, the remaining adult mice in the replication cohort  were trained to nose poke for food as previously described  and vesicular loading assay . Animals were rapidly decapitated, brains were dissected and placed on a chilled aluminum block , and the striatum  was isolated using razor blades. Striatal samples were placed in Eppendorf tubes, flash frozen in liquid nitrogen, and stored at −80°C until needed.A randomly selected subset of behaviorally naïve male mice was sacrificed at adulthood via rapid decapitation for tissue collection for HPLC  were rapidly decapitated, and striatal sections were immediately collected via vibratome as previously described. For dorsal striatum, dopamine release was evoked by a single, rectangular, electrical pulse ; for ventral striatum, five pulses were delivered at 60 Hz. Five recordings were taken at each of three sites in the dorsal striatum and three sites in the ventral striatum, with a 5-min rest interval between each stimulation. Electrodes were calibrated to known dopamine standards to produce estimated dopamine concentrations. Maximal dopamine release at dorsal and striatal sites were averaged separately and compared using a two-way ANOVA, with region as a within-subject factor and exposure as a between-subject factor.Dopamine release and reuptake kinetics were quantified using fast-scan cyclic voltammetry as previously described , 87. RanN = 7, DPE N = 9) to measure dopamine, its metabolites, and its cysteinyl adducts as described previously  assay. These concentrations  were compared between groups using N = 3, DPE = 5; replication: control N = 12, DPE N = 12) as previously described  were used for electrophysiology experiments. Brain slices containing the NAc were prepared using a previously described method (2/CO2 oxygenated “cutting solution” with the following components: NaCl (130 mM), NaHCO3 (30 mM), KCl (3.50 mM), KH2PO4 (1.10 mM), MgCl2 (6.0 mM), CaCl2 (1.0 mM), glucose (10 mM), and kynurenic acid (2.0 mM). Coronal sections with thickness of 300 µm containing the nucleus accumbens were cut using a vibratome  and were kept in oxygenated cutting solution in an incubation chamber at 32°C for 1 h. Slices were then transferred to regular artificial cerebrospinal fluid (ACSF) containing the following components: NaCl (130 mM), NaHCO3 (30 mM), KCl (3.50 mM), KH2PO4 (1.10 mM), MgCl2 (1.30 mM), CaCl2 (2.50 mM), and glucose (10 mM). Slices were kept in ACSF at room temperature for at least 30 min before recording.Whole-cell patch clamp electrophysiology was used to measure properties of ventral striatal MSNs. Adult male mice , phosphocreatine (5 mM), K-ATP (2 mM), and 0NaGTP (0.2 mM) with pH adjusted to 7.3 with KOH and an osmolarity of 280–290 mOsm. Whole-cell recordings were performed with a Multiclamp 700B amplifier  using pClamp 10.4 software and an Axon Digidata 1550 A-D interface (Molecular Devices Corporation). NAc MSNs were visually identified by their medium soma size and confirmed by their membrane properties (a antagonist SR 95531 (5 µM) and were captured continuously for 2 min, and EPSC events were detected offline using the MiniAnalysis program 6.0 . t tests were used to compare results between exposure groups. The experimenter remained blind to the identity of all mice until all analyses were completed.For whole-cell patch clamp recording, slices were moved to the recording chamber and continuously perfused by gravity-fed oxygenated ACSF at 32°C (∼2 mL/min). Individual neurons in the NAc were visualized using differential interference contrast optics and infrared (IR) illumination with an IR-sensitive charge-coupled device (CCD) camera  mounted on a Leica DM6000FS microscope . Patch pipettes were pulled from borosilicate glass with resistance between 4 and 6 MΩ and were filled with patch solution containing the following: K-gluconate (130 mM), KCl (2 mM), HEPES (10 mM), MgCloperties . Whole-coperties . A lineapgad085_Supplementary_DataClick here for additional data file.