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Neuroligins are cell-adhesion molecules involved in synapse formation and/or function. Neurons express four neuroligins (NL1–NL4), of which NL1 is specific to excitatory, and NL2 to inhibitory synapses. Excitatory and inhibitory synapses include numerous subtypes. However, it is unknown whether NL1 performs similar functions in all excitatory and NL2 in all inhibitory synapses, or whether they regulate the formation and/or function of specific subsets of synapses. To address this central question, we performed paired recordings in primary somatosensory cortex of mice lacking NL1 or NL2. Using this system, we examined neocortical microcircuits formed by reciprocal synapses between excitatory neurons and two subtypes of inhibitory interneurons, namely fast-spiking and somatostatin-positive interneurons. We find that the NL1 deletion had little effect on inhibitory synapses, whereas the NL2 deletion decreased (40–50%) the unitary (cell-to-cell) IPSC amplitude evoked from single fast-spiking interneurons. Strikingly, the NL2 deletion had no effect on IPSC amplitude evoked from single somatostatin-positive inhibitory interneurons. Moreover, the frequency of unitary synaptic connections between individual fast-spiking and somatostatin-positive interneurons and excitatory neurons was unchanged. The decrease in unitary IPSC amplitude originating from fast-spiking interneurons in NL2-deficient mice was due to a multiplicative and uniform down-scaling of the amplitude distribution, which in turn was mediated by a decrease in both synaptic quantal amplitude and quantal content – the latter inferred from an increase in the coefficient of variation. Thus, NL2 is not necessary for establishing unitary inhibitory synaptic connections, but is selectively required for “scaling up” unitary connections originating from a subset of interneurons.
Neuroligins (NLs) are postsynaptic cell adhesion molecules thought to play a role in synapse formation and/or function by binding, at least in part, to presynaptic neurexins (Ichtchenko et al., 1995 and 1996; Goda and Davis, 2003; Scheiffele, 2003; Yamagata et al., 2003; Hussain and Sheng, 2005; Levinson and El-Husseini, 2005; Ushkaryov et al., 1992; Song et al., 1999; Dean et al., 20003; Missler et al., 2003; Varoqueaux et al., 2004; Nam and Chen, 2005). The importance of neuroligins in brain function is indicated by the observation that mutations in NL3 and NL4 may cause autism (Jamain et al., 2003; Zoghbi, 2003; Laumonnier et al., 2004; Yan et al., 2005; Sudhof, 2008).
Vertebrates express 4 neuroligin genes – NL1 to NL4 (Ichtchenko et al., 1996; Bolliger et al., 2008). Overexpression of NL1, NL2, and NL3 increases synapse density in cultured neurons (Scheiffele et al., 2000; Prange et al., 2004; Chih et al., 2005; Chubykin et al., 2004; Boucard et al., 2005; Levinson et al., 2005). Knockouts (KOs) of NL1, NL2, and/or NL3 suggest that neuroligins act in organizing the functional properties of synapses, and not their initial establishment (Varoqueaux et al., 2006; Chubykin et al., 2007). Both anatomic and electrophysiological evidence indicate that NL1 preferentially functions at excitatory synapses, and NL2 preferentially at inhibitory synapses (Song et al., 1999; Graf et al., 2004; Varoqueaux et al., 2004; Chubykin et al., 2007), but this specificity is not observed in all studies (Prange et al., 2004; Levinson and El-Husseini, 2005). Moreover, immunocytochemistry suggests that alternative splicing of NL1 and NL2 determines their preferential effects on excitatory versus inhibitory synapses (Chih et al., 2005; Chih et al., 2006), but no such effect was detected in electrophysiological studies (Chubykin et al., 2007).
Measurements of evoked synaptic transmission have shown that deletion of NL2 impairs inhibitory synapse function (Chubykin et al., 2007). However, this study relied on extracellular stimulation to evoke inhibitory responses. With this approach, changes in other parameters, such as excitability of axons, might confound the results. Moreover, some synaptic properties, such as the frequency of unitary (cell-to-cell) connections, cannot be discerned with this method. Finally, there are different subtypes of inhibitory neurons with diverse characteristics (Freund and Buzsaki, 1996; Gonchar and Burkhalter, 1997), and extracellular stimulation will nonselectively excite all of these. Therefore, it is unknown how inhibitory synapses originating from different subtypes are regulated by NL2, or even perhaps by NL1.
To resolve these issues, we utilized KO mice lacking NL1 and NL2, and examined synaptic function between individual neighboring excitatory and inhibitory neurons in neocortex. We focused on connections associated with two different types of inhibitory neurons – fast-spiking (also known to be parvalbumin-positive inhibitory neurons) and somatostatin-positive neurons (Cauli et al., 1997; Galarreta and Hestrin, 1999; Gibson et al., 1999). Our data support the specificity of NL2 for inhibitory synapses, and – more importantly – show that NL2 function differs among the two subtypes of inhibitory neurons tested. Our data also suggest that NL2 is involved in the “scaling up” of unitary connections without changing their frequency distribution shape.
Three mouse lines were used. First, the “original” neuroligin 1/2 deletion line was used to determine the effects of both NL1 and NL2. The creation of this line has been described (Varoqueaux et al., 2006; Chubykin et al., 2007). This is a single line in which both NL1 and NL2 mutant alleles are maintained by continuously backcrossing mice that are heterozygous for each allele, resulting in a spectrum of genotypes from double KO (DKO) mice to wild-type (WT) mice. Data were divided into 4 genotypic groups (Fig. 1, Fig. 10, Fig. 11 and Supp. Fig 8): WT* (at least 1 WT allele each of NL1 and NL2), NL1 knockout (NL1 KO) which contained at least 1 WT NL2 allele, NL2 KO which contained at least 1 WT NL1 allele, and DKO.
For all other experiments, we focused on the effects of NL2, and all mice were homozygous WT for NL1. Except for experiments using the GFP mouse lines described below, the “original” line was always used (except WT for NL1). Genotypes were divided into two groups: +/+,+/− versus −/−. The symbols “+/+”,”+/−”, and “−/−” indicate homozygous, heterozygous, and KO for NL2, respectively, and the genotypic group +/+,+/− included both NL2 homozygous and heterozygous mice (we also refer to this group as NL2[+/+,+/−]). This grouping was reasonable since we observed no difference in unitary IPSC amplitude, short-term plasticity, or IPSC kinetics between NL2 homozygous and heterozygous mice (Fig. 5B; data not shown for last 2 properties).
A second mouse line was obtained by crossing the original line with mice that express EGFP in parvalbumin-positive inhibitory neurons (G42 crossed with CB6F1/J, kindly provided by Josh Huang, Cold Spring Harbor Laboratory) (Chattopadhyaya et al., 2004). Similarly, a third line was obtained by crossing the original line with mice that express EGFP in somatostatin-positive inhibitory neurons (GIN mice, Jackson Lab) (Oliva et al., 2000). Specificity for GFP expression in parvalbumin- and somatostatin-positive neurons in these lines has already been demonstrated (Chattopadhyaya et al., 2004; Oliva et al., 2000). Both GFP mouse lines reliably marked inhibitory neurons since no GFP-positive neuron ever elicited an EPSC. All GFP cells in the G42 line were fast-spiking, and EPSCs recorded in these cells had strongly depressing short-term dynamics and fast time courses – consistent with the properties of parvalbumin-positive neurons (Cauli et al., 1997; Reyes et al., 1998; Beierlein et al., 2003). Similarly, all GFP cells in the GIN line displayed all of the electrophysiological characteristics of somatostatin-positive neurons which, most saliently, included the highly facilitating EPSCs targeting these cells (Fig. 11; Reyes et al., 1998; Beierlein et al., 2003).
Consistent with previous results (Varoqueaux et al., 2006), the various KO mice exhibited differences in weight at the experimental ages used here (P13–16): 8.1±0.2, 7.1±0.4, 6.2±−0.3, 4.1±0.8 g for WT*, NL1 KO, NL2 KO, and DKO, respectively (n=25,6,9,4) (compared to WT*, the following weighed less: NL1 KO, p<0.04 and NL2 KO and DKO, p<0.0001).
Acute thalamocortical slices were prepared as previously described (Agmon and Connors, 1991). Briefly, mice (P13–P16) were anesthetized with Euthasol, and the brain removed following protocols approved by UT Southwestern. Slices of 350 µm thickness were cut at ~4° C in dissection buffer, placed in normal ACSF at 35° C for 30 minutes, and slowly cooled to 21° C over the next 45 minutes. Whole-cell recordings were performed at 21° C in either layer 4 or layer 2/3 of the barrel field in somatosensory cortex. An experiment was analyzed if postsynaptic series resistance was less than 18 MΩ, and if both series and input resistance did not change by more than 25% during the recording. Only experiments with a high seal resistance (> 3 GΩ) were analyzed. All data were collected and analyzed using Labview software (National Instruments). For a subset of experiments, cell capacitance was obtained using the fast decay constant observed in response to a voltage step in voltage clamp (Gibson et al., 2006). Decay constants were derived by applying a least squares fit of a double exponential (one fast and one slow time constant) to the first 10 ms of the transient response to a voltage step.
Layer 4 fast-spiking (FS) cells were identified by their large size, low input resistance (<300 MΩ), short duration spikes, and nonadapting, high firing rates (>200 Hz at 21° C) (Connors and Gutnick, 1990; Gibson et al., 1999). GFP fluorescence was not used to identify layer 4 FS neurons. To distinguish layer 4 FS cells from other inhibitory neuron types, any initially identified FS cells having spike widths at half-height >1 ms were not analyzed. Any initially identified FS cells evoking IPSCs with durations at half-height >11 ms were not analyzed since most of the population had durations between 6 to 10 ms, and non-FS inhibitory neurons typically had durations in the 11 to 15 ms range. Neocortical FS neurons have been shown to be parvalbumin-positive (Cauli et al., 1997; Galarreta and Hestrin, 1999; Gibson et al., 1999), and hence, sometimes these terms are used interchangeably. Layer 4 excitatory neurons had “regular-spiking” action potentials, and to further distinguish them reliably from inhibitory neurons, were only accepted for analysis if spike width was >1.8 ms at half-height and input resistance was >300 MΩ. Inhibitory neurons in layer 2/3 were simply identified through GFP expression, and layer 2/3 excitatory neurons identified by pyramidal shaped somas and “regular-spiking” action potentials.
ACSF contained (mM): 126 NaCl, 3 KCl, 1.25 NaH2PO4, 2 MgSO4, 26 NaHCO3, 25 dextrose, and 2 CaCl2. All slices were prepared in a sucrose dissection buffer as follows (mM): 75 sucrose, 87 NaCl, 3 KCl, 1.25 NaH2PO4, 7 MgSO4, 26 NaHCO3, 20 dextrose, and 0.5 CaCl2. All solutions were pH 7.4. ACSF was saturated with 95% O2 / 5% CO2. Low Cl− KGluc pipette solution consisted of (mM): 130 K-Gluconate, 4 KCl, 2 NaCl, 10 HEPES, 0.2 EGTA, 4 ATP-Mg, 0.3 GTP-Tris, 14 phosphocreatine-Tris, 10 sucrose. High Cl− KGluc pipette solution consisted of (mM): 79 K-Gluconate, 44 KCl, 6 NaCl, 10 HEPES, 0.2 EGTA, 4 ATP-Mg, 0.3 GTP-Tris, 14 phosphocreatine-Tris, 10 sucrose. KCl pipette solution consisted of (mM): 146 KCl, 2 NaCl, 10 HEPES, 0.2 EGTA, 4 ATP-Mg, 0.3 GTP-Tris, 14 phosphocreatine-Tris, 10 sucrose. All solutions were adjusted to pH 7.25 and 290 mOsm. Junction potentials were ~10 mV, 9, and 2 mV, respectively, and were left uncorrected in traces.
A unitary PSC is the response in a single postsynaptic neuron due to an action potential evoked in a single presynaptic neuron, and it can be mediated by a single or multiple release sties. Unitary EPSCs and IPSCs were measured at a holding potential of −60 mV and −55 mV, respectively. A connection was considered to exist when the average peak amplitude was greater than 2 pA. Average unitary amplitude refers to peak amplitude measured in 2 mM external [Ca2+], and this measurement includes response failures. Average “success” amplitude did not include failures. All PSC amplitudes were measured with respect to baseline immediately preceding the IPSC onset. Individual presynaptic action potentials were elicited with an 8 ms depolarizing voltage step (voltage-clamp recording, generally 15–25 mV) in some experiments and with an 8 ms current step in other experiments (current-clamp recording, generally 100–300 pA). Action potentials were able to be reliably elicited in voltage clamp probably due to the loss of voltage clamp in the cell compartment where the action potential was generated. Short-term plasticity (STP) was analyzed for connections whose average unitary IPSC was greater than 9 (Fig. 1, Fig. 10) and 10 pA (Fig. 5, Fig. 9, Fig. 11), and was quantified with an STP index using PSC amplitudes in the train: Average(Last 2 PSCs)/PSC1 except for EPSCs targeting somatostatin-positive neurons which was Average(PSC7,PSC8)/Average(PSC1,PSC2). PSC1 refers to the first PSC in the train. For IPSCs, preceding PSCs in the train were subtracted before measuring the amplitude for more accurate measurement.
The coefficient of variation (CV) was calculated as the standard deviation of IPSC1 amplitude divided by the average of IPSC1 amplitude (Faber and Korn, 1991). Unitary IPSCs with <2 pA average amplitude were not included in the CV analysis. Risetime for responses was defined as the time between the points where the response was 20% and 80% of peak. Duration was defined as the length of time at half height of the response.
The decay time constant of an IPSC was calculated by fitting the data to an exponential function with only 1 time constant using the Levenberg-Marquardt algorithm (Labview, National Instruments). Two time constants usually did not improve the fit for IPSCs in this study, and at the same time, the fit was more variable among experiments. Response latency was defined by the point in time where the line generated by the 20–80 percent rise slope of the IPSC intersected the baseline. The presynaptic reference time was the peak of the action potential. Both decay time constants and latency were derived from the average IPSC.
All recordings in figure 1, figure 10, and figure 11 were performed with the 6 mM Cl− KGluc pipette solution, and recordings in figure 3, figure 4, figure 5, figure 6, figure 7, and figure 9 were performed with the 50 mM Cl− KGluc pipette solution. Unitary IPSCs were measured at −55 mV and −70 mV for 6 mM and 50 mM Cl− KGluc pipette solutions, respectively. The 50 mM Cl− KGluc pipette solution made IPSCs an inward current and was used to better resolve IPSCs because of the greater driving force with respect to reversal potential.
Miniature IPSCs were measured with 1 µM TTX (Sigma), 20 µM DNQX (Sigma), and 100 µM APV (Sigma) in the bath and were analyzed using “Mini Analysis Program” (Synaptosoft). Cells were voltage clamped at −70 mV, and a threshold of 8 pA was used for detecting events. Data were collected in a 3 minute interval starting 2 minutes after attaining the intracellular recording. KCl pipette solution (148 mM Cl−) was used to increase the inhibitory synaptic current size. This solution was not used in the longer dual recording experiments because recordings became less stable and began to depolarize after 8 minutes of recording.
Strontium substitution experiments were performed with 50 mM Cl− internal solution. The external solution at the beginning of the experiment contained 2/2 mM CaCl2/MgSO4 which was subsequently replaced with 4/4 mM SrCl2/MgSO4 (Gil et al., 1999). Asynchronous release events were induced by trains of action potentials (15–30 APs at 20 Hz) and were measured in a 300–700 ms window following the offset of the train. This window was offset by 40–200 ms after the last action potential, and both window size and offset were picked for each individual experiment depending on when delayed events were both frequent and could be individually measured. Only individual, isolated events were analyzed, and IPSCs < 15 pA average amplitude (measured in 2 mM Ca2+ before switching to Sr2+ external solution) were not analyzed since measurements of asynchronous events at these connections were significantly contaminated by spontaneously occurring IPSCs (see spontaneously occurring IPSCs in Fig. 3). This contamination became an issue because weaker unitary connections displayed far fewer delayed, asynchronous events in Sr2+. The ACSF also contained 20 µM DNQX (Sigma) and 100 µM APV (Sigma).
Low Ca2+ experiments were performed with 50 mM Cl− internal solution and with external 2/2 mM CaCl2/MgSO4 replaced by 0.1/3.9 mM CaCl2/MgSO4. Long action potential trains were applied, and the number (80–200) and frequency (20–50 Hz) of APs were modified to reduce the percent of action potentials evoking an IPSC to < 20%. These IPSCs are referred to as “successes” and were only analyzed if they: 1) occurred within ±0.3 ms of the average IPSC latency (see “Unitary PSCs” above for latency definition), 2) were > 3 pA, 3) had a width at half-height > 1 and < 10 ms, and 4) had a peak latency ±2 ms with respect to the average peak latency. The successes are referred to as “putative” quantal events, and their amplitude was measured. Systematic error in these quantal amplitude measurements was calculated, and we estimate that our results may overestimate the actual difference in quantal amplitude between WT and NL2 KO mice (Fig. 4) by only 2.1% (See Supp. Fig. 1 for details of error calculation). In support of our measurement of “successes” actually reflecting quantal events, a plot of CV against the ratio of “success amplitude in 0.1 Ca2+” to ”amplitude in 2 Ca2+” (or “putative quantal size”/”unitary IPSC size” ratio) displays the expected monotonically increasing relationship (Supp. Fig. 6C). This suggests that our independent measurements of CV and quantal amplitude are consistent with each other and are fairly accurate. The ACSF also contained 20 µM DNQX (Sigma) and 100 µM APV (Sigma). Changing criterion #2 to >5 pA or >10 pA revealed similar decreases in quantal amplitude depicted in Fig. 4, and therefore, the results are robust to this particular criterion (26% and 24% decrease, respectively).
Mice (P21–27: G42 strain) were anesthetized with Euthasol and transcardially perfused following protocols approved by UT Southwestern. Perfusion rate was 1.7 mls/minute and began with ice cold saline for 1 minute followed by 15 minutes of 4% paraformaldehyde. The brain was then removed and postfixed in 4% paraformaldehyde for 30 minutes. Then it was mounted on a platform and 50 µm coronal sections through barrel cortex were cut on a vibrating slicer (Vibratome) in ice cold phosphate buffer saline (PBS). After 3 10 minute washes in PBS, slices were incubated in blocking solution (3% normal goat serum and 0.3 % triton in PBS) for 1 hour. Slices were then incubated in blocking solution with primary antibodies overnight at 4° C. Primary antibodies were for GFP (1:1500, chick, Aves lab, #GFP-1020) and vesicular GABA transporter (VGAT, 1:500, rabbit, Chemicon, #1AB5062P). After washing 3 times, 10 minutes each, in PBS, slices were incubated in blocking solution with secondary antibodies for 2 hours at room temperature (Alexa 488 Goat anti-chicken, 1:400, Invitrogen, #A11039; Alexa 555 Goat anti-rabbit, 1:500, Invitrogen, #A21430). After a final 3×10 minute wash, slices were mounted on slides using glycerol.
Images of layer 4 in somatosensory cortex were collected on an inverted LSM 510 confocal microscope (Zeiss, Inc.) with a 63× oil objective at 2× zoom. The pinhole was set to 1.5 airy disc units which corresponded to a 1.4 µm optical slice. A stack of 3 images with 1 um intervals was collected beginning at the surface of the slice and the second section was used for analysis. A single sample was obtained from a 213×213 µm square divided into 9 71×71 µm squares. The center square contained a single GFP-positive soma and puncta were counted in all other squares. This was considered 1 sample. Illumination intensity was always the same, but detection parameters were normalized (“Find” function in Zeiss software), and hence, absolute brightness could not be examined. The average detector gain for both VGAT and GFP imaging was decreased by 8% and 10% respectively in the NL2 KO, and the average offset was unchanged. Therefore, this normalization likely had little effect on our results. Images were analyzed using Metavue software. Images were first filtered with a linear bandpass kernel (0.17 to 1.8 cycles/µm which emphasized structures 0.28 to 3 µm in size along 1 dimension). Then puncta detection using a threshold 15 times the baseline signal was performed (Integrated Morphology Analysis module in Metavue). Minimum puncta area allowed was 0.04 µm2. Images were collected and analyzed blind to genotype.
When all four genotypes were compared, a one-way ANOVA followed by multiple comparisons (Fisher’s PLSD) was performed. When indicated, a 2-factor ANOVA was initially performed followed by the same multiple comparisons test. Two way comparisons were assessed with a Student’s t-test (two-way). A chi-square test was applied to determine changes in the percent of connected pairs, and a Fishers Exact P-value was used to determine significance. For unitary PSC data, sample number (n) is the number of recorded pairs. The number of mice used was on average 32% the number of all pairs tested (including non-connected pairs). Statistical significance was p<0.05 except for comparing connectivity between the 3 deletion genotypes and WT* where a Bonferonni correction was made (p<0.017). All error bars are standard error of the mean (SEM). Distributions of IPSCs (Fig. 3C, Fig. 4G, Fig. 5E,F and Fig. 6C,G) were compared using a Kolmogorov-Smirnov test (K–S test). Data are always presented in the following order by genotype: WT (or WT* or NL2[+/+,+/−]), NL1 KO, NL2 KO, and DKO.
All genotypes originated from the same litters. For comparisons among 4 genotypes, all 4 genotypes were usually not present in a single litter, but data from at least one WT* pup and another genotype in the same litter were required for a given litter to be included. For NL2 [+/+,+/−] versus NL2 KO comparisons, at least 1 of each genotype was used from a single litter. All experiments and analysis were performed blind to genotype except for those in figure 9.
We initially examined the effect of the NL1 and NL2 deletion on inhibition provided by individual fast-spiking (FS) inhibitory interneurons onto excitatory neurons using single and double KO mice lacking NL1 and/or NL2 (“original” line, see Methods). Paired recordings from these two neuron types were performed in layer 4 barrels of primary somatosensory cortex, and results from the four different genotypes were compared. The paired recordings were used to measure individual, cell-to-cell connections which are referred to as unitary connections.
A brief train of action potentials was evoked in the presynaptic FS inhibitory neuron (5 pulses, 20 Hz), and resulting inhibitory postsynaptic currents (IPSCs) were recorded in the excitatory neuron (Fig. 1A). Consistent with the hypothesis that NL2 functions at inhibitory synapses, the amplitude of the first IPSC in the train (IPSC1) was decreased by 51% in the NL2 KO mice (Fig. 1B; p<0.05 for the NL2 KO vs. WT*; 2-factor ANOVA followed by multiple-comparisons). As previously reported (Chubykin et al., 2007), this amplitude effect was specific to the NL2 deletion since the NL1 deletion had no detectable affect. The unitary connection frequency was unaltered for all genotypes (Chi-Square test, Fig. 1C), and while this measurement is neither a direct nor a precise measure of synapse number, it is consistent with unaltered total synapse number (see Discussion, “Mechanisms”). Both the NL1 and the NL2 deletion (but not the double KO) affected short-term plasticity by making synapses slightly more depressing – a phenomenon often associated with increases in release probability (Fig. 1D,E). Such a change cannot explain the decrease in unitary IPSC amplitude in the NL2 KO mice, since an increase in release probability would be expected to increase the unitary IPSC size. The change in short-term plasticity by the NL1 deletion also suggests that NL1 may also play a subtle role in regulating inhibitory synaptic function.
We next measured action-potential-independent synaptic events, or miniature IPSCs (mIPSCs, Fig. 2A), in excitatory layer 4 neurons from wild-type (WT) and NL2 KO mice. While the NL2 KO had no effect on the mIPSC frequency, the NL2 KO decreased the mIPSC amplitude by 25% (Fig. 2B; also see Supp. Fig. 2 for cumulative distributions). The decrease in mIPSC amplitude indicates a decrease in quantal amplitude – the size of a response, or the transmission efficacy, at individual synaptic release sites. Most of the mIPSCs probably originate from proximally located synapses (Soltesz et al., 1995), which in turn mostly originate from FS inhibitory neurons (Di Cristo et al., 2004; Somogyi et al., 1998). Therefore, the decrease in mIPSC amplitude could account for the decrease in unitary IPSC amplitude originating from FS neurons, but nevertheless, this assertion is limited by the fact that a significant portion of mIPSCs likely originate from inhibitory neuron subtypes other than FS interneurons.
To independently measure the quantal size of inhibitory transmission from FS neurons onto layer 4 excitatory neurons, we substituted Sr2+ for Ca2+ during the recording, which caused a delay in neurotransmitter release and produced measurable, single quantal events in the release process. Isolated and delayed quantal events were observed immediately after the offset of a train of action potentials evoked in the presynaptic FS neuron, which enabled us to measure the quantal amplitude of IPSCs originating from individual FS neurons (Fig. 3A). Importantly, only connections with strong unitary IPSCs (>15pA average amplitude measured in 2 mM Ca2+ before switching to Sr2+) were used since Sr2+-evoked events were significantly contaminated by spontaneously occurring IPSCs at weaker connections (see Methods, Fig. 3A3). Puzzlingly, we found that the quantal amplitude measured as Sr2+-evoked events was unchanged in the NL2 KO mice (Fig. 3B; 20.1±1.6 vs. 20.2±1.4, n=18,20).
The results with Sr2+-evoked mIPSCs are inconsistent with our conclusion of decreased quantal amplitude based on mIPSCs, but the limitation of the measurements of Sr2+-evoked mIPSCs to “strong” unitary connections may have introduced a bias that distorts the results. In support of this, we did not observe the change in average unitary IPSC amplitude (p=0.27; see Fig. 3C for the strong overlap in distribution) like we did in our initial experiments (Fig. 1A). In summary, the limitation to “stronger” connections may have made it less likely to observe changes in the NL2KO mice (Note the importance of weaker connections by the steeper slope in the <10 pA region of the cumulative distribution in Fig. 5E).
Thus, to further test the hypothesis that decreased quantal amplitude at synapses originating from FS inhibitory neurons mediates the decrease in IPSC amplitude in NL2 KO mice, we employed yet another approach. We measured the quantal amplitude under low release probability conditions (external [Ca2+] reduced to 0.1 mM, Fig. 4) (Fatt and Katz, 1952; Gil et al., 1999; Kraushaar and Jonas, 2000). Using this technique, we were able to measure the “putative” quantal amplitude at unitary connections with an average unitary amplitude as low as 2 pA (see Methods). We elicited trains of action potentials (APs) in the presynaptic FS neuron, and varied the number and frequency of the APs until evoked IPSCs (successes) occurred at a rate of less than 20% (Fig. 4B,C; see Methods). Under these low release conditions, it is likely that successes were mainly mediated by single release sites and were therefore, “putative” quantal events (Fatt and Katz, 1952; Gil et al., 1999; Kraushaar and Jonas, 2000). Quantal amplitude was derived by averaging the successes (Fig. 4D). Quantal amplitude was decreased by 28% in the NL2 KO mice (Fig. 4E; 23.3±1.9 vs. 16.9±1.2 pA, p<0.007). Note that, unlike the Sr2+ experiments, the mean IPSC amplitude is decreased in the NL2 KO mice and cumulative distributions are well separated (Figs. 4F,G). Therefore, by adding the population of weaker unitary IPSC connections, we were able to discern a decrease in both unitary and quantal amplitude. This result is consistent with the change observed with mIPSCs (Fig. 2; also note that different pipette solutions and event criteria were used in Fig. 2 and Fig. 3, Fig. 4, and therefore, absolute quantal amplitudes differ). These results show that the decreased efficacy at individual synapses plays a prominent role in the decreased inhibition provided by FS neurons in the NL2 KO mice.
In all layer 4 experiments performed with 50 mM Cl- pipette solution (including the Sr2+ and low external [Ca2+] experiments), a similar 51% reduction in unitary IPSC amplitude was observed (Fig. 5B, compare with Fig. 1B). Again, no change in connection frequency was detected (Chi-Square test, Fig. 5C). We observed no effect based on NL2 gene copy number or sex (Fig. 5B, Supp. Fig. 3).
The larger decrease in IPSC amplitude (~51% in Fig. 1, Fig. 5) than in quantal amplitude (25% and 28% for mIPSC and low Ca2+ experiments, respectively) suggests that the latter cannot completely account for by the former. In classical modeling of synaptic transmission, the amplitude of a unitary response is dependent on 2 factors: quantal amplitude (q) and quantal content (m) (Unitary amplitude=m*q; Johnston and Wu, 1995; also see Discussion). Quatal content (m) refers to the number of transmitter quanta released, and changes in quantal content can be measured by comparing the coefficient of variation (CV) of a response, where quantal content is inversely proportional to CV (Faber and Korn, 1991). Therefore, we examined the possibility that a decrease in quantal content contributes to the decrease in unitary IPSC amplitude found in the NL2 KO mice. If this were the case, the CV should be increased in the NL2 KO mice. Indeed, this was true (Fig. 5D; 0.60±0.03 vs. 0.71±0.05 pA, p<0.05). Consistent with this finding, when we estimated the quantal content for each connection by dividing the unitary IPSC amplitude (excluding failures) by the quantal amplitude (obtained in Sr2+ and low Ca2+ experiments), we observed a trend towards decreased quantal content in the NL2 KO mice (p=.066, Supp. Fig. 4).
A decrease in quantal content could be mediated either by a decrease in the total number of potential release sites or a decrease in release probability. To test the latter as a possibility, we observed that short-term depression was enhanced in NL2 KO mice (STP index: 0.82±0.05 vs. 0.68±0.04 pA, p<0.03), just as we showed in Figure 1. An increase in short-term depression usually suggests an increase in release probability which, in turn, eliminates a role for release probability in the quantal content decrease observed in the NL2 KO mice. On the other hand, studies indicate that the short-term plasticity at inhibitory synapses mediated by FS neurons is independent of release probability for short trains of action potentials, but is dependent on release probability for longer trains (Kraushaar and Jonas, 2000; Luthi et al., 2001). Therefore, we measured short-term plasticity during long stimulus trains (100 and 500 pulses, 20 Hz). However, short-term plasticity was still not detectably altered (Supp. Fig. 5). Therefore, these data suggest that the unitary IPSC decrease and the CV increase in the NL2 KO mice is not due to a decrease in release probability, and may involve an increase in total number of potential release sties (but see Discussion, “Mechanisms”).
Next, we determined the distribution of unitary IPSC amplitudes in NL2[+/+,+/−] (which include both wild-type and heterozygous NL2 KO mice) and NL2 KO mice. We plotted cumulative histograms of IPSCs for both NL2[+/+,+/−] and NL2 KO data (Fig. 5E). The distributions were different (p<0.002, K–S test), and a higher proportion of weaker connections existed in the KO.
Casual inspection of the plots suggest that the NL2 KO caused a multiplicative decrease of the NL2[+/+,+/−] distribution. To visualize this, we uniformly scaled the NL2[+/+,+/−] distribution down to 52% (a 48% decrease) – a value producing the least error sum of squares (Fig. 5F). This scaling accurately predicts the NL2 KO distribution by accounting for 99.3% of the variance in the NL2 KO distribution ( 100 * (1 - (Mean Square Error [KO,Scaled])/VarianceKO)) ), and no statistically significant difference exists between the scaled and the NL2 KO distributions (K–S test). This close match after scaling is only possible because the basic distribution shape for WT and KO are the same. Therefore, the decrease in unitary IPSC amplitude in the NL2 KO mouse represents a multiplicative decrease without a change in frequency distribution shape.
In scatterplots, it was apparent that the quantal amplitude and the CV were dependent upon the unitary IPSC amplitude (Figs. 6A,E,). We found that with an increasing unitary IPSC amplitude, the quantal amplitude increased and the CV decreased in both NL2[+/+,+/−] and NL2 KO mice (Figs. 6B,F; 2-factor ANOVA, unitary amplitude groupings, p<0.0001 for both quantal amplitude and CV). Moreover, there was no detectable change in these relationships in the NL2 KO mice (Figs. 6B,F; 2-factor ANOVA, genotype), which probably explains why we were unable to discern a difference in quantal amplitude in the Sr2+ experiments, since they were performed within a restricted range of IPSC amplitudes (Fig. 3).
Based on these observations, we should be able to predict the change in quantal amplitude and CV in the NL2 KO mice by using only the NL2[+/+,+/−] unitary amplitude frequency distribution (Figs. 6C,G). To test this hypothesis, we first plotted frequency histograms of the IPSC amplitudes for the quantal amplitude and CV experimental data (Figs. 6C,G). As in figure 5E, the NL2[+/+,+/−] and NL2 KO distributions were different (p<0.01 for both Figs. 6C,G, K–S test). Next, we performed a 52% scaling of the NL2[+/+,+/−] unitary IPSC amplitude distribution (Fig. 6C,G; in gray; points scaled below 2 pA were removed, which corresponded to the criterion for a detectable connection). Just as in figure 5F, these scaled distributions were not statistically different from the NL2 KO mice distribution (K–S test). We then multiplied corresponding points in graphs (Figs. 6B and C for quantal amplitude and Figs. 6F and G for CV) to obtain the average value (Figs. 6D,H). The average quantal amplitude and CV for the NL2[+/+,+/−] and NL2 KO mice calculated in this fashion were, as expected, almost identical to the exact averages (<2% error, and within the 95% confidence intervals of the exact averages which ranged ±11–15%; based on data in Fig. 4E and Fig. 5D). Finally, we obtained a prediction of the average quantal amplitude and CV in the NL2 KO mice by multiplying the NL2[+/+,+/−] distribution of these parameters (again, Figs. 6B,F, respectively) by the “NL2[+/+,+/−], 52% scaled” unitary amplitude distribution (Figs. 6C,G, respectively). This prediction, using no NL2 KO mouse data, very well approximated the NL2 KO values (<3% error, Figs. 6D,H; within the 95% confidence intervals of the NL2 KO data: ±15% and ±13% for quantal amplitude and CV, respectively). The actual IPSC amplitude decrease in the low Ca2+ quantal amplitude experiments was 38% (Fig. 4F). Even when the NL2[+/+,+/−] distribution is scaled by this value, the predicted quantal amplitude for NL2 KO mice is still fairly accurate (17.8 pA, 5% error and within the NL2 KO 95% confidence interval of ±15%).
In summary, the changes in quantal amplitude and the CV in NL2 KO mice can be accurately predicted by simply scaling down the NL2[+/+,+/−] unitary IPSC distribution.
We observed no changes in IPSC or IPSP response kinetics in NL2 KO mice (Fig. 7). In addition to parameters illustrated in figure 6, we observed no change in the exponential time constant of the decay or the latency of IPSCs in the NL2 KO mice (decay time constant: 8.9±0.3 vs. 8.6±0.3 ms; latency: 0.98±0.03 vs. 0.94±0.03 ms; n=23,30). These data suggest that no change occurred in the combined process of transmitter release and postsynaptic receptor activation. Because PSP kinetics are also shaped by the membrane properties of the postsynaptic neuron, the lack of a change in IPSP kinetics indicated that the membrane properties of layer 4 excitatory neurons were not significantly altered. Finally, the lack of change in IPSC kinetics suggests that the ratio of synchronous to asynchronous release from presynaptic terminals was not significantly altered.
One possibility for decreases in both unitary IPSCs and quantal amplitude in the NL2 KO mice is that synaptic release sites were located more distally in the dendrites. It is known that due to electrotonic attenuation, PSCs and PSPs mediated by more distally located synapses have a smaller amplitude when measured at the soma (this is also true for PSCs because of voltage escape in the dendrites; Johnston and Wu, 1995; Hausser and Roth, 1997; Yeckel et al., 1999; Walker et al., 2002; Williams and Mitchell, 2008). But if this was true for our data, we should also see a deceleration in both IPSC and IPSP risetime (and perhaps duration) since more distally located synapses are not only smaller in amplitude when measured at the soma, but also display longer duration kinetics (again, due to electrotonic and voltage escape reasons; Johnston and Wu, 1995; Hausser and Roth, 1997; Yeckel et al., 1999; Walker et al., 2002; Williams and Mitchell, 2008). The fact that we saw no changes in IPSC or IPSP kinetics (IPSC risetime: 0.63±0.02 vs. 0.69±0.06, IPSC duration: 8.1±0.2 vs. 7.8±0.2, IPSP risetime: 4.5±0.2 vs. 4. 9±0.2; Figs. 7C,D,E) suggests that no such systematic location shift occurred.
The increased CV of unitary IPSCs measured in the NL2 KO mice may be due to a decrease in the total number of release sites. The lack of change in unitary connection frequency suggests this may not be the case, but this observation is not a reliable indicator for total release site number. To test for a change in release site number, we counted presynaptic boutons originating from FS neurons in layer 4 barrels. We used sections from mice that expressed GFP in parvalbumin-positive neurons – the commonly accepted biochemical marker for FS neurons (Cauli et al., 1997; Reyes et al., 1998; Gibson et al., 1999) - and that additionally were WT or KO for the NL2 gene. The parvalbumin-GFP mice have been used previously to reliably count presynaptic terminals originating from parvalbumin-positive neurons due to strong GFP expression in the terminals (Chattopadhyaya et al., 2004). The use of these mice is further justified by the fact that unitary IPSCs originating from the GFP-positive neurons display a similar decrease with NL2 KO as described above (see next Results section; Fig. 9B).
We subjected cortical sections to double immunostaining for the inhibitory presynaptic marker, vesicular GABA transporter (VGAT), and for GFP (Fig. 8A), and counted puncta that colocalized both proteins (Fig. 8B). We did not detect changes in VGAT and in VGAT/GFP-colocalized puncta number in the NL2 KO mice (Fig. 8C,D), suggesting that the density of synapses formed by FS neurons is unchanged. These data are consistent with a previous study indicating no alteration in synapse number in the NL1-2-3 triple KO (Varoqueaux et al., 2006). No change in GFP-positive cell number was detected in layers 2–5 (52.2±7.2 vs. 59.6±3.7 cells/mm2, n=11,8). Therefore, the mechanism underlying the increased CV remains unclear (see Discussion).
Fast-spiking neurons exist in all layers of neocortex and the hippocampus. We next took an initial step towards determining whether the NL2 deletion decreases inhibitory synaptic transmission mediated by all FS neurons in neocortex. We measured unitary IPSCs originating from layer 2/3 parvalbumin-positive neurons, which are known to be the biochemical equivalent of FS neurons (i.e. these classifications apply to the same group of inhibitory neurons) (Cauli et al., 1997; Reyes et al., 1998; Gibson et al., 1999). We used the mouse line that selectively expresses GFP in parvalbumin-positive inhibitory neurons (see Methods) and performed simultaneous recordings of neighboring layer 2/3 GFP-positive and pyramidal neurons. As with layer 4 FS neurons, IPSC amplitude was decreased with NL2 deletion (by 42%, Fig. 9A,B), while the connection frequency was not detectably altered (Chi-Square test; Fig. 9C). No changes in short-term plasticity (Fig. 9D,E), IPSC risetime (1.1±.05 vs. 1.2±.08 ms, n=19,8), or IPSC duration at half-height (13.4±.65 vs. 12.9±.9 ms) were observed. Thus, the NL2 deletion may universally impair synaptic inhibition mediated by FS neurons (and equivalently, parvalbumin-positive neurons) in the neocortex.
We next determined whether the NL2 KO decreases synaptic transmission in all inhibitory synapses, independent of the subtype of inhibitory neuron involved. We prepared slices from NL2 expressing and NL2 KO mice that selectively express GFP in another inhibitory neuron subtype – the somatostatin-positive inhibitory neurons (see Methods) – and recorded from neighboring GFP-positive inhibitory interneurons and pyramidal excitatory neurons in layer 2/3 of somatosensory cortex (Fig. 10A). In contrast to IPSCs mediated by unitary connections originating from FS neurons, the NL2 KO did not decrease IPSC amplitudes evoked from somatostatin-positive neurons; in fact, a statistical trend for an increase was apparent (p=0.08, Fig. 10B). No connection frequency change was detected (Chi-Square test, Fig. 10C). Short-term depression increased in both DKO and NL2 KO mice, indicating that the presynaptic release probability may have increased with NL2 deletion (Fig. 10D,E). As with FS cells, no changes in risetime (2.3±0.2, 2.2±0.1, 2.5±0.2, 2.0±0.1 ms; n=18,16,18,11) or duration at half-height (14.3±0.8, 14.8±0.5, 14.9±0.5, 13.8±0.8 ms) were observed. NL1 played no discernable role at this synaptic connection (Fig. 10B–E).
NL1 and NL2 are hypothesized to function specifically at excitatory and inhibitory synapses, respectively (Song et al., 1999; Graf et al., 2004). While this specificity applies to synapses targeting excitatory neurons, no attempt has been made to examine specificity in inhibitory neurons (Varoqueaux et al., 2004; Chubykin et al., 2007). During recordings examining IPSCs, we also measured the reciprocal EPSCs (Fig. 11A,B). Effects of the NL deletions were only detected in FS neurons, where the average EPSC amplitude was larger with the NL2 deletion compared with WT* neurons (Fig. 11C; Fishers PLSD, p<0.03). No changes in connection frequency (parvalbumin: 35/48, 22/28, 21/29, 17/22; somatostatin: 28/50, 31/42, 21/32, 16/23: WT*, NL1 KO, NL2 KO, DKO, respectively) or short-term plasticity (Fig. 11E,F) were detected with any genotypic manipulation.
Excitatory responses onto FS neurons had slightly faster kinetics in NL2 KO mice than in WT* mice. While no change in risetime was observed, there was 10% decrease in the duration at half-height with the NL2 deletion (3.6.2±0.8, 3.2±0.1, 3.4±0.3, 2.7±0.2 ms; p<0.04, 2-way ANOVA; n=19,13,17,7). No changes in risetime or duration were observed for EPSCs targeting somatostatin-positive neurons.
Although deletion of NLs does not alter the overall cytoarchitecture of the mouse brain (Varoqueaux et al., 2006), it is possible that the synaptic alterations we observed are secondary to alterations in electrophysiological membrane properties. Therefore, we examined the effects of the NL1 KO and NL2 KO on 2 standard membrane properties – input resistance and resting potential – in layer 4 and layer 2/3 cells (Supp. Fig. 8). Intrinsic membrane properties changed little, except for a ~15% increase in the input resistance of layer 4 FS cells in the DKO mice. A slight depolarization was observed in the layer 2/3 excitatory neurons of NL1 KO mice. We additionally examined the membrane capacitance in a subset of layer 4 excitatory neurons in WT* and NL2 KO animals, and found no difference (11±0.4 vs. 11.3±0.4 pF, n=30,37). Since membrane capacitance is proportional to cell size, these data suggest that our in-depth examination of the inhibition mediated by layer 4 FS cells in the NL2 KO mice is likely not confounded by changes in postsynaptic cell size. In summary, the alterations induced by NL deletion are highly synapse-specific, and are unlikely the result of an indirect effect through alterations in electrophysiological membrane properties.
We used NL1 and NL2 KO mice to examine the role of NLs at unitary (cell-to-cell) connections between neocortical neurons of known subtype. Consistent with previous studies, our data strongly implicate NL2 in the regulation of inhibitory synaptic function (Graf et al., 2004; Varoqueaux et al., 2004; Chubykin et al., 2007). Upon deletion of NL2, the IPSC amplitude was uniformly scaled down (40–50%) at unitary connections originating from FS neurons. This scaling was mediated by a decrease in quantal amplitude and quantal content. No decrease was observed for unitary IPSCs originating from somatostatin-positive neurons, suggesting a role for NL2 that is dependent on the inhibitory neuron subtype (Summarized in Fig. 12). In contrast, the NL1 deletion had little effect on synaptic function of inhibitory synapses originating from both inhibitory subtypes (except for a change in short-term plasticity at layer 4 FS synapses).
The strength of a unitary inhibitory connection can be described as a function of the total number of release sites (N), and the response amplitude (q) and release probability (Pr) at each site - Response Strength = N*q*Pr (Johnston and Wu, 1995). We consider q to be a measure of a synaptic response evoked by the release of a single neurotransmitter vesicle. Our measurements of quantal amplitude with mIPSCs (Fig. 2) and in low Ca2+ experiments (Fig. 4) are measurements of q, and hence suggest that the “single release” synaptic response size is decreased in NL2 KO mice. A change in q is most commonly attributed to a change in postsynaptic receptor function (Kilman et al., 2002; Lissin et al., 1998; Luhmann and Prince, 1991; Malenka and Nicoll, 1999; Murthy et al., 2001).
Because the decrease in quantal amplitude was 28%, while the decrease in unitary IPSC amplitude was ~50%, this aspect of synaptic function probably does not fully account for the connection strength decrease in the NL2 KO mice. We provide evidence that the remaining difference may be accounted for by a decrease in quantal content (m=N*Pr), which is the average number of quanta released by an action potential. We infer this change from the observed increase in the CV of unitary IPSCs originating from FS neurons (Fig. 5D), since an increase in the CV is thought to be linked to a decrease in quantal content (Faber and Korn, 1991; Johnston and Wu, 1995; Hefft et al., 2002).
Based on its definition, the quantal content can be lowered by a decrease in either N, Pr, or both. Our measurements of short-term plasticity suggest that Pr in the NL2 KO mice may be increased (short trains in layer 4, Fig. 1E) or unchanged (long trains in layer 4 in Supp. Fig. 5 and short trains in layer 2/3 in Fig. 9E), and therefore, cannot account for the quantal content decrease. On the other hand, the relationship between Pr and short-term plasticity is not always clear and is dependent on other factors (Geppert et al., 1997; von Gersdorff et al., 1997; Blatow et al., 2003; Xu and Wu, 2005; Schluter et al., 2006).
The lack of a decrease in short-term plasticity nevertheless appears to suggest that N is decreased in the NL2 KO mice, but 3 of our findings argue against a decreased N. Specifically, we observed no decrease in any of the following: 1) the connection frequency of unitary connections originating from FS neurons (Fig. 1C, Fig. 5C, and Fig. 9C), 2) mIPSC frequency (Fig. 2), and 3) puncta number for both a GABAA and parvalbumin presynaptic marker (Fig. 8). If indeed, N were decreased in the NL2 KO mice, what can account for the lack of change in the 3 measurements just stated? First, NL2 may not affect the frequency of unitary IPSC connections, but may regulate the number of synapses mediating a unitary connection only after that connection is established. Second, mIPSC frequency may not be a reliable assay for synapse number involved in evoked transmission (Reim et al., 2001; Calakos et al., 2004), and in the particular case here, mIPSCs are contaminated by inhibitory events originating from non-FS synapses. Third, the puncta counts may not be sensitive enough to detect the differences measured physiologically nor be an accurate marker for functional release sites with postsynaptic targets. In summary, the relative contributions of N and PR in the quantal content decrease is unresolved.
For WT mice (specifically, NL2[+/+,+/−]), we have quantified the following relationship - with increasing unitary IPSC amplitude, the quantal size increases and the CV decreases. This relationship was unchanged in the NL2 KO mice (Fig. 6).
Based on these unaltered relationships and the lack of change in IPSC kinetics (Fig. 7), it appears that synapses in the NL2 KO mice are fairly normal except for two aspects: 1) a slight change in the short-term plasticity as measured by short stimulus trains, and 2) the scaling down by ~50% the wild-type connection amplitude while preserving the shape of the amplitude distribution (Fig. 5F). Because the relationships stated above are unaltered in the NL2 KO mice, the change in the quantal amplitude and the CV in NL2 KO mice can be precisely predicted by the 52% scaling of the NL2[+/+,+/−] distribution of the unitary IPSC amplitude (<3% error, Fig. 6). Interestingly, the unitary (cell-to-cell) connection frequency of FS neurons is normal. Therefore, while NL2 does not appear necessary for establishing the normal number of unitary connections originating from neighboring FS neurons, it appears to be needed to “scale up” the unitary connections at the developmental stage studied here. We speculate that the “scaling up” would include both an increase in quantal size and quantal content.
Arguably the most important result of our study is the observation that the effects of the NL2 deletion on unitary IPSC amplitude were differential between inhibitory neuronal subtypes. The amplitude of IPSCs originating from FS and parvalbumin-positive neurons (which are thought to be identical) was decreased ~2-fold in the NL2 KO mice (Fig. 1B, Fig. 5B, Fig. 9B). Because the same reduction occurred for the output of FS neurons in two different neocortical layers (layer 4 and 2/3), NL2 may specifically regulate the output of neocortical FS neurons in general.
In contrast, no change in IPSC amplitude was observed at unitary inhibitory connections originating from somatostatin-positive neurons (Fig. 10B). Therefore, NL2 may act to promote inhibitory inputs from FS neurons, but play a much diminished role for input from somatostatin-positive inhibitory neurons. Short-term plasticity, on the other hand, may be similarly regulated by NL2 at synapses originating from both layer 4 FS neurons and somatostatin-positive neurons since both of these synapses were more depressing in the NL2 KO mice (Fig. 1E, Fig. 10E).
The different effects of the NL2 deletion on unitary connections originating from FS and somatostatin-positive inhibitory neurons may occur for two possible reasons. First, NL2 may have a differential functional role at these 2 synapse subtypes – perhaps due to differential expression of NL2 and/or neurexin splice variants (Boucard et al., 2005; Chih et al., 2006). Second, NL2 may function at only one of the inhibitory synapse types, and changes at the other synapse type may originate from indirect effects of the NL2 deletion. While NL2 has been shown to be localized to inhibitory synapses, no data exist about its localization with respect to inhibitory synapse subtype.
The NL1 deletion had little effect at inhibitory synapses originating from both subtypes – the exception being an alteration in short-term plasticity at connections originating from layer 4 FS neurons (Fig. 1E). It has already been shown that NL1 deletion has no effect on the amplitude of unitary IPSCs mediated by FS cells (Chubykin et al., 2007), and here, we extend this principle to IPSCs mediated by somatostatin-positive neurons.
On the other hand, the hypothesis that NL1 is selective for excitatory synapses may have to be modified. At excitatory synapses targeting the inhibitory neurons examined here, NL1 had no detectable effects while NL2 deletion caused an increase in unitary EPSC amplitude onto FS neurons (Fig. 11C). This finding may either indicate that NL2 plays a role at both inhibitory and excitatory synapses (Chih et al., 2005; Chih et al., 2006), or reflect a compensatory upregulation of excitatory inputs onto FS neurons induced by the decrease of their outputs.
It is possible that our observed changes are due to second order, indirect effects. But the decrease in FS-mediated inhibition is consistent with both the localization of NL2 at inhibitory synapses and the ability of NL2 to promote greater inhibition in a subset of transfected neurons in culture (Chubykin et al., 2007). Interestingly, we did not observe membrane alterations in any of the cell types in the NL2 KO (Supp. Fig. 8). Therefore, the synaptic effects that we observe are highly specific, and not part of a large repertoire of general changes.
We examined synaptic function and activity at a developmental stage where synapses are still undergoing proliferation, and circuits are being refined. Activity, driven partially through sensory inputs, plays an important role in this process, and activity regulates the strength of inhibitory connections in neocortex (Welker et al., 1989; Rutherford et al., 1997; Chattopadhyaya et al., 2004; Maffei et al., 2004; Bartley et al., 2008). In these prior studies, activity has been demonstrated to increase inhibition through increased quantal amplitude and synapse number (Kilman et al., 2002; but see Maffei et al., 2006). We speculate that NL2 may play a role in this process by “scaling up” unitary connections in response to activity. This would be consistent with evidence indicating an activity-dependent function for NL1 and NL2 after overexpression (Chubykin et al., 2007). Interestingly, chronic elimination of activity has a similar effect on unitary IPSC amplitude as described for the NL2 KO mice in this study – a decrease in inhibitory input provided by FS neurons and no effect on inhibitory input originating from somatostatin-positive neurons (Bartley et al., 2008).
This research was supported by grants from the National Institutes of Health (HD056370 to J.R.G.; NS045711 and HD052731 to K.M.H; R37 MH52804-08 to T.C.S.), the Simons Foundation (to T.C.S.), and Autism Speaks (to K.M.H.). We thank Kris Loerwald for assistance in genotyping and immunocytochemistry.