**4.3 Mother's education**

Maternal education, which is related to household wealth, is a determinant of good childcare knowledge and practices. The education attainment of mothers is mostly significant in the analysis of LVM.

The results with two indicators are quite similar to the results with three indicators with regard to this variable. This result supports the suggestion that an educated mother assumes the responsibility of taking a sick child to receive health care.  These findings are consistent with many studies in the context of developing countries (Africa Nutrition chartbooks 1996, Borooah 2002), which reported that maternal education has a strong and significant effect on stunting. They found that at primary levels of education,, effects on stunting are small or negligible, and they increase only at secondary or higher levels.(Chartbooks 1996; Borooah 2002).

#### **4.4 Working mothers**

Work has a non significant effect on the malnutrition status of children in Nigeria. The results are consistent with some previous studies and not consistent with others. Some studies reported that when mothers are working, the household income is increased and the access to better food will be increased, as well as the access to a quality level of medical care. On the other hand, when mothers are employed outside the home, the duration of full breastfeeding is shortened and necessitates supplementary feeding. This is usually preformed by illiterate care-takers, which might affect the health of children negatively.


Preface

Antioxidants are compounds that inhibit oxidation, that is, they prevent free radicalinduced tissue damage by avoiding the formation of radicals, scavenging them, or by promoting their decomposition. A direct link is observed between compounds with antioxidant activity and the prevention of chronic diseases like cancer or cardiovascular diseases. In this context, a variety of terrestrial plants, marine organisms, and foods are known to be rich in antioxidants, including herbs, fruits, vegetables, plants, algae, and others. Thus, it is of great importance to collect information about antioxidant molecules and their mechanisms of action and their characterization and relation to human diseases. It is also important to study sources of antioxidants and applications of antioxidants in medicine, nutraceuticals, and foods.

The book addresses recent developments in antioxidants from natural sources. Chapter 1 includes introductory concepts regarding antioxidant types and their chemical structures, whereas Chapter 2 addresses the relationship between antioxidants and the prevention of chronic diseases. Chapter 3 describes the antioxidant cellular mechanisms. Chapters 4–10 examine the sources of natural antioxidants, including some medicinal plants, foods, and microalgae. Finally, Chapters 11–13 describe some applications and practical uses of antioxidants. For example, Chapter 11 discusses the development of beverages with high anthocyanin content, Chapter 12 presents strategies for using antioxidants to improve animal reproduction, and Chapter 13 examines the uses of antioxidants in food processing.

We would like to thank our IntechOpen Commissioning Editor Ana Simcic and Author Service Manager Dolores Kuzelj for all the help and support during the publishing process. We especially appreciate and thank all authors that have contributed to the book, with a special mention to Dennis R.A. Mans from the Anton de Kom University of Suriname for contributing two chapters. Finally, we would like to thank all the authors, colleagues, and reviewers that participated in the review process of the book.

> **Paz Otero Fuertes and María Fraga Corral** Faculty of Science, Department of Analytical Chemistry and Food Science, Nutrition and Bromatology Group, University of Vigo, Ourense, Spain

Section 1


Understanding the central processing of auditory information is incomplete without considering the descending systems. Morphologically, the auditory cortex sends a large number of descending fibers to the subcortical nuclei (corticofugal projections, Doucet et al., 2002, 2003; Coomes and Schofield, 2004), including the auditory thalamus (Roger and Arnault, 1989; Winer et al., 2001), inferior colliculus (Andersen et al., 1980; Faye-Lund, 1985; Coleman and Clerici, 1987; Herbert et al., 1991; Saldaña et al., 1996; Winer et al., 1998, 2002; Bajo and Moore, 2005; Coomes et al., 2005; Bajo et al., 2007; Peterson and Schofield, 2007; Markovitz et al., 2013) and cochlear nucleus (Weedman and Ryugo, 1996a,b; Jacomme et al., 2003; Schofield and Coomes, 2005a,b; Meltzer and Ryugo, 2006; Schofield et al., 2006). In addition, the corticofugal system implements a highly selective modulation of the physiological response in the subcortical nuclei (Yan and Suga, 1996, 1999; Ma and Suga, 2001a; Nakamoto et al., 2008; Bajo et al., 2010). In the frequency domain, focal activation of the primary auditory cortex (AI) shifts the receptive fields of neurons in the subcortical nuclei towards the best frequency (BF) of activated AI neurons and reorganizes the frequency maps of those subcortical nuclei including the ventral division of the medial geniculate body (MGBv; Zhang and Suga, 2000; Tang et al., 2012), the central nucleus of the inferior colliculus (ICc; Yan and Suga, 1998; Zhang and Suga, 2000; Yan et al., 2005; Yan and Ehret, 2001, 2002; Ma and Suga, 2001b, 2003) and even the anteroventral cochlear nucleus (AVCN; Luo et al., 2008; Liu et al., 2010).

Frequency-specific corticofugal modulation appears to be a feature of the lemniscal auditory pathway. Up to now, it has been exclusively observed in the lemniscal subcortical nuclei (MGBv, ICc and AVCN) and not in the non-lemniscal nuclei (Calford and Aitkin, 1983; Imig and Morel, 1983; Hu et al., 1994) including those found in the medial division of the medial geniculate body (MGBm) and the external nucleus of the inferior colliculus (ICx; Jen et al., 2001; Zhang and Suga, 2005; Wu and Yan, 2007; Tang et al., 2012). Given that the lemniscal auditory pathway is also characterized by a sharp tuning in sound frequency and a strict tonotopic projection (Calford, 1983; Rodrigues-Dageff et al., 1989; Redies and Brandner, 1991; Anderson and Linden, 2011), the question raised here is whether the frequency-specificity of corticofugal modulation is limited to the lemniscal system or dominated by the tonotopy regime of the central auditory system.

The dorsal cochlear nucleus (DCN) is tonotopically organized (Young et al., 1992; Luo et al., 2009). In contrast to the AVCN, the DCN receives inputs from both the auditory and somatosensory systems (Baizer et al., 2012), and projects to the ICx and MGBm (Malmierca et al., 2002). The DCN could therefore be a nonlemniscal nucleus because it is tightly associated to non-lemniscal auditory system (Malmierca et al., 2002; Ryugo et al., 2003; Luo et al., 2012). In the present study, we examined the effects of focal electrical stimulation of the AI (ESAI) on the auditory responses of the DCN neurons. Our data show that ESAI induced a frequencyspecific shift in the frequency tunings of the DCN neurons, similar to the modulation of the AVCN (Luo et al., 2008; Liu et al., 2010).

## **MATERIALS AND METHODS**

C57 female mice, aged 4–7 weeks and weighing 14.6–20.7 g, were used in this study. All protocols and procedures were approved by the Animal Care Committee of the University of Calgary (protocol number: M04044). Animals were anesthetized with a mixture of ketamine (85 mg/kg, i.p., Bimeda-MTC Animal Health Inc., Canada) and xylazine (15 mg/kg, i.p., Bimeda-MTC Animal Health Inc.). The anesthetic level was maintained by additional doses of ketamine and xylazine, 17 mg/kg and 3 mg/kg respectively. Under anesthesia, the mouse's head was fixed in a custom-made head holder by rigidly clamping between the palate and nasal/frontal bones. The mouth bar was adjusted to align bregma and lambda of the skull in one horizontal plane. Once the mouse's head was positioned, the scalp was incised along the midline and subcutaneous tissue and muscle were removed to expose the skull. Two holes, 3 and 2 mm in diameter respectively, were drilled to expose the right cerebellum above the cochlear nucleus (5.6–6.5 mm posterior to bregma, 2.1–2.6 mm lateral to the midline) and the left AI (2.2–3.6 mm posterior to bregma, 4–4.5 mm lateral to the midline). After surgery, the animal was placed in a sound-proof chamber to record the response of DCN neurons before and after electrical stimulation of the auditory cortex (**Figure 1**). During all surgery and electrophysiological experiments, the animal's body temperature was maintained at a constant 37◦C using a feedback-controlled heating pad.

## **ACOUSTIC STIMULATION**

Tone bursts, 60-ms duration with 5-ms rise and fall times, were used as acoustic stimuli. They were digitally synthesized and converted into analog sinusoidal waves by an Enhanced Realtime Processor (RP2, Tucker-Davis Tech., Gainesville, FL, USA). The signals were then fed to a tweeter via a digital attenuator (PA5, Tucker-Davis Tech., Gainesville, FL, USA). The output amplitude of the tone bursts was expressed as dB SPL within 1 dB accuracy (reference 20 µPa). The tweeter was placed 45◦ to the right of and 13 cm away from the mouse's right ear. During calibration, the tweeter was driven by 20-volt sinusoidal peak-topeak bursts without attenuation. It was calibrated at the right and left ear of the animal with a condenser microphone (Model 2520, Larson-Davis Laboratories, USA) and a microphone preamplifier (Model 2200C, Larson-Davis Laboratories, USA). Frequencies and intensities of tone bursts were varied either manually or automatically with software (BrainWare, Tucker-Davis Tech., Gainesville, FL, USA).

## **RECORDING AND ELECTRICAL STIMULATION OF THE AI**

A tungsten electrode (∼2 M impedance, FHC, USA) was advanced perpendicular to the surface of the left auditory cortex. The electrode was initially connected to the preamplifier of the data acquisition system. Signals from the electrode were fed to

a 16-channel preamplifier, amplified 10,000 times and filtered using a bandwidth of 0.3–10 kHz (RA16, Tucker-Davis Tech., Gainesville, FL, USA), and recorded with software (BrainWare, Tucker-Davis Tech., Gainesville, FL, USA). A pure tone with manual alternation of frequencies and amplitudes was continuously delivered once per second during the electrode penetration. Tone-evoked action potentials were frequently located at layers III/IV of the AI. The lowest amplitude (minimum threshold) and the corresponding frequency at which the neuron showed a response were determined by manual alternation of the tone frequency and amplitude. After 5 ∼ 8 penetrations, a rough tonotopy of the AI and the intended location for stimulation of the AI were determined. Once the electrode was in position and the tone-evoked action potentials were observed again, the frequency tunings of the AI neurons were measured with a series of tone bursts at 10 dB above the MT and frequencies that varied from 3 to 40 kHz in 1 kHz steps. Tone stimuli were presented 15 times at each frequency. The frequency to which the neuron showed the largest response magnitude was defined as the BF of the AI neuron. The electrode was then disconnected from the recording system and reconnected to the output of a constant current isolator (A360, WPI Inc., Sarasata, FL) for the ESAI. The electrode was advanced to a depth of about 700–800 µm below the brain surface to layer V of the AI where it was maintained for the duration of the experiment. This procedure ensured that the locations of the recording and stimulating sites were in the same AI cell column with the same BFs.

An indifferent electrode was placed on the brain surface just adjacent to the stimulating electrode. The negative pulses (monophasic, 0.1 ms, 500 nA constant current) were generated by a stimulator (Grass S88, Natus Neurology, West Warwick, RI) and a constant-current isolator (A360, WPI, Inc., Sarasata, FL, USA). The electrical pulses were synchronized with the offset of the tone bursts at BF and 20 dB above the MT of the cortical neurons. The combined acoustic from the tweeter and electric stimuli were respectively delivered in both ears (with a right predominance) and to the left AI at a rate of 4 Hz for 7 min; this stimulus paradigm was also used in our previous study (Yan and Ehret, 2002).

## **DCN RECORDING**

Two tungsten electrodes (∼2 M impedance) were dorsoventrally positioned in the right cochlear nucleus. The space between the two electrodes was 100 µm. The location of the DCN was determined physiologically. A pure tone with manual alteration of its frequency and amplitude was continuously delivered once per second during electrode penetration. Tone-evoked responses were commonly observed at a depth of 2.5 mm below the surface of the cerebellum. Once the responses to the tone stimuli were observed, the minimum threshold and the corresponding frequency were measured by manually alternating the frequency and amplitude of the tone. The frequencies at the minimum threshold were measured for each 100-µm interval to map, in an approximate manner, the tonotopic organization along the dorsal-ventral axis. According to the three-dimensional tonotopy of the cochlear nucleus obtained from our previous study (Luo et al., 2009), the frequencies at the minimum threshold decreased dorsoventrally in the same frequency range for both the DCN and posteroventral cochlear nucleus (PVCN) neurons. Thus, the ventral boundary of the DCN was determined when the frequency at the minimum threshold increased as the electrode was advanced into the PVCN. The electrode was then withdrawn in ∼100-µm intervals until the action potential recordings stabilized. The minimum threshold and the corresponding frequency of the recorded DCN neuron were determined manually again, and the frequency tunings of the DCN neuron was also measured with the same procedure used for the AI neurons. These response curves of the DCN neurons served as control responses. The frequency to which the neuron showed the largest response magnitude was defined as the BF of the DCN neuron. A negative current of electrical pulses was then delivered to the AI for the micro-electrical stimulation of the AI neurons (4/s for 7 min). The response curves of DCN neurons were again recorded immediately after cortical stimulation and every 30 min until a recovery rate of at least 50% in the BF was obtained.

## **DATA PROCESSING**

The tungsten electrode (∼2 M impedance) often detected multiunit activities. Cluster cutting isolated and selected single-unit action potentials by examining eight parameters of the action potential waveform, i.e., peak, valley, spike height, spike width, peak time, valley time, and two user-defined voltages (Yan and Ehret, 2002; Yan et al., 2002). Single-unit responses to the series of tones were eventually displayed using post-stimulus timecumulative (PSTC) histograms with a bin width of 1 ms. The BFs of the DCN neurons were compared before (pre-ES BF) and after (post-ES BF) the ESAI. Since the ranges of upward and downward BF shifts were found to be similar, the BF shifts were expressed using a linear kHz scale (Sakai and Suga, 2001; Yan and Ehret, 2002). The changes in the BFs of DCN neurons were analyzed according to the differences in BFs between the recorded DCN neurons and the stimulated cortical neurons.

## **STATISTICAL ANALYSIS**

Data were expressed as mean ± SD. The paired *t*-test (twotailed) was used to compare the differences between groups of data. A *p*-value of <0.05 was considered to be statistically significant.

## **RESULTS**

The effects of ESAI were studied in 60 contralateral DCN neurons from 26 mice (2–4 neurons per mouse). The BFs of recorded DCN neurons ranged from 10 to 27 kHz and the BFs of stimulated cortical neurons ranged from 10 to 28 kHz. These values fell within the central range of mouse hearing (Zhang et al., 2005). Our data show that the AI significantly impacts the auditory response of the DCN neurons. The changes in the response properties of DCN neurons occurred within 30 min, peaked at 1.5 h, and recovered at 3 h after the ESAI.

The ESAI clearly changed the frequency tunings of the contralateral DCN neurons. **Figure 2** shows three different examples of DCN neurons modulated by ESAI. In **Figure 2A**, the BFs of both cortical and DCN neurons were 11 kHz (matched). The auditory response of the DCN neuron increased after the ESAI (facilitation) while the BF of the DCN neuron did not change. **Figure 2B** shows that the pre-ES BF of the DCN neuron was 21 kHz while the cortical neuron had a BF of 27 kHz (unmatched). The auditory response at the pre-ES BF (21 kHz, control) of the DCN neuron decreased after the ESAI (inhibition). Hereafter, we use the "facilitation" and "inhibition" for simplicity. These terms represent the overall increase and decrease in neuronal activity without prejudging their underlying neurobiological mechanisms. However, the auditory response at 24 kHz (post-ES BF of DCN neuron) showed the largest increase. Both the facilitation and inhibition by ESAI resulted in a BF shift of the DCN neuron from 21 to 24 kHz. In **Figure 2C**, the pre-ES BF (16 kHz) of the DCN neuron was higher than the BF (11 kHz) of the cortical neuron (unmatched). The BF of this DCN neuron shifted from 16 to 14 kHz after the ESAI. Thus, the changes in the BF of the DCN neurons appear to be determined by the relationship between the BFs of the DCN and AI neurons: (1) the DCN BFs did not change when the BFs of the DCN neurons and those of the AI neurons were matched; and (2) the DCN BFs shifted towards the BFs of the AI neurons when the BFs of the DCN and AI neurons were unmatched.

We also analyzed the effect of ESAI on the frequency tunings of all 60 DCN neurons. The DCN neurons were classified according to the difference between the BFs of the DCN neurons and AI neurons: (1) unmatched group (14 neurons, BFDCN ≈ BFAI, **Figure 3**, open circles and open bar); (2) unmatched Group 1 (21 neurons, BFDCN − BFAI < −1 kHz, **Figure 3**, filled circles and filled bars); and (3) unmatched Group 2 (25 neurons, BFDCN − BFAI > 1 kHz, **Figure 3**, filled circles and filled bars). For the auditory response (spikes) at the pre-ES BF and 10 dB above the MT of DCN neurons (control), the response increased after the ESAI for the matched group (**Figure 3A**, open circles) while it decreased for the unmatched group (**Figure 3A**, filled black circles). On average, the response of the matched group (**Figure 3B**, open bar) significantly increased by 9.95% (*p* < 0.01). In contrast, the response of the unmatched group (**Figure 3B**, filled black bars) significantly decreased by 6.71% (*p* < 0.001) for the unmatched Group 1 and 8.36% (*p* < 0.001) for the unmatched Group 2. For the auditory response (spikes) at the post-ES BF and 10 dB above the MT of DCN neurons, the response increased after ESAI for the unmatched group (**Figure 3A**, filled gray circles). On average, the response of the unmatched group (**Figure 3B**, filled gray bars) significantly increased by 12.25% (*p* < 0.001) for the unmatched Group 1 and 10.49% (*p* < 0.001) for the unmatched Group 2. Thus, the ESAI remarkably inhibits the auditory response at the pre-ES BF of DCN neurons while it facilities the auditory response at the post-ES BF when the BFs of the DCN and AI neuron are unmatched.

Our results indicate that the shifts in DCN BFs appear to be associated with the BFs of stimulated cortical neurons. To clarify this issue, we further analyzed the correlation of the shifts in DCN BFs to the BFs of the stimulated AI neurons. It became apparent that the BF changes of DCN neurons were systematically associated with the differences in the BFs between the stimulated AI neurons and the recorded DCN neurons (**Figure 4A**). The shift in BFs was linearly correlated with the differences between the BFs of the AI and DCN neurons (*R* 2 = 0.811; *p* < 0.01). When the BFs of AI neurons were higher than the BFs of DCN neurons, cortical stimulation significantly increased the BFs of DCN neurons by 2.07 kHz (*p* < 0.001), and when BFs of cortical neurons were lower than the BFs of DCN neurons, cortical stimulation significantly decreased the BFs of DCN neurons by 2.77 kHz (*p* < 0.001) (**Figure 4B**, filled bars). When the BFs of AI neurons were the same as the BFs of DCN neurons (**Figure 4A**, open circles), cortical stimulation did not shift the BFs of DCN neurons (**Figure 4B**, open bar).

## **DISCUSSION**

Our data clearly demonstrated that the auditory cortex modulated the auditory responses of the DCN neurons in a frequency-specific manner. The BF shifts of DCN neurons were significantly correlated to the differences in the BFs between the stimulated AI neurons and the recorded DCN neurons. Thus, the DCN and AVCN not only exhibit mirror-symmetrical tonotopic maps (Luo et al., 2009), but also share a similar pattern of corticofugal modulation (Luo et al., 2008; Liu et al., 2010). Therefore, the frequency-specificity of corticofugal modulation appears to be dominated by the tonotopy regime of the central auditory system. However, the AVCN and DCN belong to two distinct auditory pathways (lemniscal vs. non-lemniscal, respectively) with different anatomical and physiological properties (Calford and Aitkin, 1983; Imig and Morel, 1983; Hu et al., 1994). Given that the corticofugal modulation of AVCN re-shapes the high-fidelity representation of initial sound information and impacts the sound information that progresses upwards through the lemniscal pathway, what is the function of the corticofugal modulation of the DCN in the non-lemniscal pathway?

The non-lemniscal auditory pathway engages in functions complementary with those of the lemniscal auditory pathway including the integration of information within and across sensory modalities, detection of changes in ongoing stimuli and interestingly, tinnitus (Young et al., 1995; Malmierca et al., 2002; Ryugo et al., 2003; Luo et al., 2012). The hyperactivity of the DCN neurons is considered to be a physiological correlate of the somatosensory tinnitus (Kaltenbach and McCaslin, 1996; Zhang and Kaltenbach, 1998; Baizer et al., 2012), and the corticofugal feedbacks, via the frequency-specific enhancement of the tinnitus-related frequencies, could be partially responsible (Mulders and Robertson, 2009; Eggermont, 2012, 2013). Our findings demonstrate that the DCN is modulated by the AI in a frequency-specific manner, suggesting that the AI may contribute

change the BF but increased the auditory responses of the matched DCN neurons (A1, A2), while the BFs of the unmatched DCN neurons shifted towards the cortical BF (B1, B2 and C1, C2). The ESAI caused

BFs of the stimulated cortical neurons. In the bottom row of panels, the dark gray area represents facilitation, whereas the light gray area represents inhibition.

to the chronic form of tinnitus through its modulation of the DCN. The DCN is a relay for auditory information ascending from the periphery to the non-lemniscal pathway. Thus, the AI may also be involved in the other functions of the non-lemniscal pathway.

In addition to tonotopic organization and multisensory inputs, the DCN is a layered structure and consists of distinct cell types including the fusiform cells, giant cells, granule neurons and cartwheel cells (Mugnaini et al., 1980; Browner and Baruch, 1982; Webster and Trune, 1982; Ryugo and Willard, 1985; Willott et al., 1992; Willott, 2001). It has been shown *in vitro* studies that different types of neurons have different membrane properties and firing patterns (Hirsch and Oertel, 1988; Oertel and Wu, 1989; Zhang and Oertel, 1993a,b,c). It would be interesting to determine how the corticofugal modulation is associated with the layered structure and cell types of DCN.

Considering the multiple descending projections within the auditory system, the auditory cortex may modulate the DCN in a direct or indirect manner. The corticofugal projections to the

DCN originate from large pyramidal neurons in layer V of the AI, and some fibers directly innervate fusiform cells in all layers of the DCN (Jacomme et al., 2003; Meltzer and Ryugo, 2006; Schofield and Coomes, 2005a,b). These fibers allow the cortical neurons to directly impact the activity of the principal DCN neurons. However, the majority of corticofugal fibers terminate in granule cell lamina between the DCN and the PVCN (Weedman and Ryugo, 1996a,b; Doucet et al., 2002, 2003). The corticaldependent modulation of DCN neuronal activity through these fibers may involve intrinsic connections between granule cell lamina and the DCN as well as interconnections between the DCN and the ventral cochlear nucleus (Mugnaini et al., 1980; Snyder and Leake, 1988; Wickesberg and Oertel, 1988; Manis, 1989). Although the number of corticofugal fibers to the DCN is much lower than those to the granule cell lamina, we speculate that the highly specific corticofugal modulation is likely mediated by the corticofugal fibers directly projecting to DCN neurons. This is similar to our observations in the case of corticocollicular modulation. The corticocollicular projections mostly target the caudal cortex, dorsal cortex and lateral nucleus of the inferior colliculus, while the tonotopically-organized ICc only receives

The error bars represent the SEM.

sparse but tonotopic descending projections from the AI (Saldaña et al., 1996; Winer et al., 1998, 2002; Bajo and Moore, 2005; Bajo et al., 2007). Additionally, direct glutamatergic projections from the AI to the ICc are believed to be responsible for the frequencyspecific corticofugal modulation of the ICc (Yan et al., 2005).

In sum, the AI modulates the neural responses in the DCN in a highly frequency-specific manner, similar to the corticofugal modulation of the AVCN. Thus, the frequency-specificity of corticofugal modulation does not appear limited to the lemniscal ascending pathway but dominated by the tonotopy regime of the auditory system. As the DCN receives many descending projections, their involvement in corticofugal modulation requires careful study.

## **ACKNOWLEDGMENTS**

This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada (Discovery Grant), the Campbell McLaurin Chair for Hearing Deficiencies, and Alberta Innovates—Health Solutions.

## **REFERENCES**

**Conflict of Interest Statement**: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 18 May 2014; accepted: 16 June 2014; published online: 01 July 2014*. *Citation: Kong L, Xiong C, Li L and Yan J (2014) Frequency-specific corticofugal modulation of the dorsal cochlear nucleus in mice. Front. Syst. Neurosci. 8:125. doi: 10.3389/fnsys.2014.00125*

*This article was submitted to the journal Frontiers in Systems Neuroscience*.

*Copyright © 2014 Kong, Xiong, Li and Yan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## Acoustic input and efferent activity regulate the expression of molecules involved in cochlear micromechanics

#### **Veronica Lamas 1 , Juan C. Arévalo1 , José M. Juiz 2 and Miguel A. Merchán1\***

1 Laboratory of Neurobiology of Hearing, Institute for Neuroscience of Castilla y Leon, University of Salamanca, Salamanca, Spain 2 Facultad de Medicina de Albacete, Instituto de Investigación en Discapacidades Neurológicas (IDINE), Universidad de Castilla La Mancha, Albacete, Spain

#### **Edited by:**

Paul Hinckley Delano, Universidad de Chile, Chile

#### **Reviewed by:**

Jiri Popelar, Institute of Experimental Medicine AS CR, Czech Republic Maria Eugenia Gomez-Casati, INGEBI-CONICET Buenos aires, Argentina

#### **\*Correspondence:**

Miguel A. Merchán, Laboratory of Neurobiology of Hearing, Institute for Neuroscience of Castilla y Leon, University of Salamanca, Pintor Fernando Gallego 1, 37007 Salamanca, Spain e-mail<EMAIL_ADDRESS>
Electromotile activity in auditory outer hair cells (OHCs) is essential for sound amplification. It relies on the highly specialized membrane motor protein prestin, and its interactions with the cytoskeleton. It is believed that the expression of prestin and related molecules involved in OHC electromotility may be dynamically regulated by signals from the acoustic environment. However little is known about the nature of such signals and how they affect the expression of molecules involved in electromotility in OHCs. We show evidence that prestin oligomerization is regulated, both at short and relatively long term, by acoustic input and descending efferent activity originating in the cortex, likely acting in concert. Unilateral removal of the middle ear ossicular chain reduces levels of trimeric prestin, particularly in the cochlea from the side of the lesion, whereas monomeric and dimeric forms are maintained or even increased in particular in the contralateral side, as shown in Western blots. Unilateral removal of the auditory cortex (AC), which likely causes an imbalance in descending efferent activity on the cochlea, also reduces levels of trimeric and tetrameric forms of prestin in the side ipsilateral to the lesion, whereas in the contralateral side prestin remains unaffected, or even increased in the case of trimeric and tetrameric forms. As far as efferent inputs are concerned, unilateral ablation of the AC up-regulates the expression of α10 nicotinic Ach receptor (nAChR) transcripts in the cochlea, as shown by RT-Quantitative real-time PCR (qPCR). This suggests that homeostatic synaptic scaling mechanisms may be involved in dynamically regulating OHC electromotility by medial olivocochlear efferents. Limited, unbalanced efferent activity after unilateral AC removal, also affects prestin and β-actin mRNA levels. These findings support that the concerted action of acoustic and efferent inputs to the cochlea is needed to regulate the expression of major molecules involved in OHC electromotility, both at the transcriptional and posttranscriptional levels.

**Keywords: prestin oligomerization, acetylcholine** α**10 receptors, auditory cortex ablation, conductive hearing loss, descending control**

## **INTRODUCTION**

Electromotility of outer hair cells (OHCs) in the organ of Corti is essential for active mechanical amplification of sound signals (Elgoyhen and Franchini, 2011). Somatic electromotility, i.e., the ability of OHCs to shorten or elongate in response to membrane voltage changes, depends on the unique properties of the membrane motor protein Prestin, whose voltage-dependent conformational changes are transferred to the actin cytoskeleton, a final effector of OHC micromechanical activation. The molecular structure of Prestin, its mechanisms and role in OHC electromotility, have been extensively studied (He et al., 2014). However, the complexity and extremely fast speed rates of operation of Prestin in particular and electromotility mechanisms in general, raise questions about regulation by incoming signals and possible adaptations to altered auditory input. There is some evidence that conductive hearing loss induces up-regulation of prestin mRNA (Mazurek et al., 2007; Yu et al., 2008; Yang et al., 2009). Up regulation of Prestin also has been reported after noise-induced hearing loss in preserved regions of the organ of Corti, consistent with compensatory mechanisms to stabilize thresholds and frequency discrimination (Xia et al., 2013).

Descending central feedback channeled through the efferent olivocochlear system is a major dynamic modulator of OHC electromotility and hence cochlear amplification (Elgoyhen and Franchini, 2011). Activity of medial olivocochlear cell (MOC) fibers acting on OHCs contributes to adapt cochlear gain by adjusting cochlear amplification. This effect is mediated by acetylcholine (Ach) released by MOC endings at the base of OHCs. Ach binds to a postsynaptic nicotinic Ach receptor (nAchR) assembled from α9 and α10 subunits whose activation hyperpolarizes OHCs. Ach-mediated hyperpolarization of OHCs has been linked to changes in axial electromotility amplitude and OHC compliance (He and Dallos, 1999, 2000).

Convergence of acoustic input and efferent connections on OHCs, raises the possibility that the expression of proteins involved in somatic electromotility is dynamically balanced by the interaction of signals from the acoustic environment and ongoing feedback from descending efferent inputs, primarily from MOC. To test this hypothesis, we compared the effects of a conductive unilateral hearing loss induced by removal of the ossicular chain (Sumner et al., 2005) with that of a partial deactivation of MOC activity by restricted ablation of the auditory cortex (AC). Previous work from our laboratory supports that in the rat AC restricted ablations induce a reversible deafness likely through descending, corticofugal control of MOC fibers (Lamas et al., 2013).

We tested changes in Prestin protein expression by Western blot after unilateral conductive hearing loss as a measure of regulation by acoustic input imbalance, and compared this with changes in Prestin protein expression after unilateral AC ablation. In parallel, because OHC electromotility regulation by MOC involves specialized cholinergic neurotransmission, we tested by qRT-PCR whether the expression of the alpha10 nAChR gene mRNA, a staple of cholinergic neurotransmission at the MOC-OHC synapse (Dallos et al., 1997; Maison et al., 2002, 2007; Batta et al., 2004; Vetter et al., 2007), changes along with the expression of Prestin and β-actin genes, as cell markers of the effects of MOC inactivation on OHC electromotility.

## **METHODS**

This study was carried out in accordance with Spanish (Royal Decree 53/2013-Law 32/2007) and European Union (Directive 2010/63/EU) regulations on the care and use of animals in biomedical research.

Sixty eight young male Wistar rats weighing between 250–300 g were used in this study. One set of 12 animals was used in experiments of middle ear ossicle removal. Eight animals underwent surgical removal of the ossicular chain as described below, and were randomly assigned to one of two post-surgery day (PSD) survival groups, 7 PSD (*n* = 4) or 15 PSD (*n* = 4). The remaining animals were assigned to the normal control group (*n* = 4). For the cortical ablation experiments, a total of 49 animals were used. Forty-two underwent AC surgical removal, and were randomly assigned to one of three survival time groups: 1, 7 or 15 PSD (*n* = 14 for each PSD). The remaining 14 animals were used as normal controls.

## **SURGICAL PROCEDURES**

The AC ablations were performed under deep anesthesia using a mixture of ketamine chlorhydrate (30 mg/kg Imalgene 1000, Rhone Méreuse, Lyon, France) and xylazine chlorhydrate (5 mg/Kg, Rompun, Bayer, Leverkusen, Germany), as previously described in Lamas et al. (2013). The animals were returned to their cages after the ablations, carefully monitoring postsurgery recovery. Once the corresponding lesion survival time was completed, animals were anesthetized with 0.1 ml of sodium Pentobarbitol injected intraperitoneally (ip), and decapitated in order to collect the brain and the cochleae. After this, brains were immersed in 4% p-formaldehyde whereas the cochleae were immediately frozen in liquid nitrogen for qRT-PCR or Western blotting, as described below in detail.

The middle ear ossicular chain removal was performed under the same anesthetic cocktail and conditions. The left external acoustic meatus was exposed under microscopy control. The eardrum was punctured with the aid of a needle and the ossicular chain removed by extraction with tweezers. After surgery, the presence of an intact footplate attached to the oval window was confirmed under the microscope. Animals were returned to their cages after the ablations, carefully monitoring the postsurgery recovery. Once the corresponding post lesional survival times were completed, animals were anesthetized with 0.1 ml sodium Pentobarbitol, ip, and decapitated in order to collect the cochleae.

Once collected the cochleae were immediately frozen in liquid nitrogen for Western blotting.

## **RNA EXTRACTION**

To study expression of target mRNAs with qRT-PCR, total RNA was purified from the collected and homogenized cochleae using TRIZOL® (Gibco BRL, Gaithersburg, MD, USA) following the manufacturer's protocol and a column from an RNeasy mini kit (Qiagen, Valencia, CA, USA) according to manufacturer's instructions. RNA concentrations were determined using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies Inc., Wilmington, USA). Each RNA sample was assayed three times and an average value was determined. RNA quality was assessed on an RNA 6000 NanoLabChip (Agilent Technologies, Palo Alto, CA, USA), using an Agilent 2100 Bioanalyzer to assess the integrity of the 18S and 28S rRNA bands, and an RNA integrity number (RIN) was assigned, with 0 corresponding to fully degraded RNA and 10 corresponding to intact RNA. For all Quantitative real-time PCR (qPCR), only RNA samples with RIN of at least 7.5 were used, with the vast majority of samples having a RIN of at least 8.0. These values meet requirements for reproductible qPCR experiments (Fleige et al., 2006).

## **QUANTITAVE REAL-TIME PCR**

RNA (2 µg), primed with oligo-dT, was reverse-transcribed into cDNA at 37◦C for 2 h using the first-strand cDNA synthesis kit (Promega Corporation, Madison, WI, USA) in a 20 µl volume, and stored at −20◦C until use, according to manufacturer's instructions. In all cases, a reverse transcriptase negative control was used for testing genomic DNA contamination.

qPCR was performed using the SYBR-Green method with a 2 × Master Mix (Applied Biosystems). Each reaction contained 10 µl of Master Mix, 0.4 µl of each pair of primers (**Table 1**), 3 µl of each cDNA sample in a different serial cDNA quantity for each gene, and MilliQ-grade water up to 20 µl. The amplification reaction took place in an ABI Prism 7000 detection system (Applied Biosystems), with the following conditions: 10 min at 95◦C followed by 40 cycles of 15 s at 95◦C and 1 min at 60◦C depending on each pair of primers. Three PCR reactions were performed for each sample per plate, and each experiment was repeated twice. The ribosomal protein L-19 endogenous gene was used as reference gene.

#### **Table 1 | Primers used in the RT-qPCR study**.

\*Location of the primers for the rat sequency in the Gene Bank. \*\*Amplification efficiency.

The comparative threshold cycle (Ct) method was used to collect quantitative data (Schmittgen and Livak, 2008). Following the removal of outliers, raw fluorescence data were used to determine the PCR amplification efficiency (E) according to the formula E = [10(−1/slope)−1]∗ 100. All amplifications had an E value of 100 ± 10%, the E value close to 100% being an indicator of efficient amplification. The relative gene expression value ("fold change") for each transcript was calculated according to the equation E−(∆Ct "condition 1"−∆Ct "condition 2") , where "condition 1" corresponds to experimental samples (PSD1, 7 and 15), "condition 2" to samples of control animals and ∆Ct of each "condition" is Ct"experimental gene"−Ct"endogenous gene" (Livak and Schmittgen, 2001; Schmittgen and Livak, 2008). A standard error for each relative gene expression value was calculated as a measure of data variation.

### **WESTERN-BLOT**

Western blot analyses were performed according to Yu et al. (2011) with slight modifications. The cochleae were lysed in a lysis buffer (5 mM Tris pH 6.8, 2% SDS, 2 mM EDTA, 2 mM EGTA, 1 mM phenylmethylsulfonyl fluoride, 1 µg/mL aprotinin, 2 µg/mL leueptine, 1 mM vanadate, 10 mM sodium fluoride and 20 mM β-glycerophosphate) for 1 h at 4◦C with gentle shaking and then centrifuged at 13000 × g for 15 min to eliminate debris. Protein concentration was quantified using Qubit Fluorometric quantification (Life Technologies). Lysates were added 5x SDS buffer and boiled for 6 min to denature the proteins. Proteins (20 µg/sample) were resolved by 7.5% SDS– PAGE and Western blots were performed with antibodies against the different proteins. Blots were developed in WesternBrigth ECL detection kit (Advansta). Films were digitized using an Epson V750 scanner.

Antibodies used were anti-Prestin (1:500) made in rabbit, a kind gift from Dr. Bechara Kachar (Laboratory of Cell Structure and Dynamics, National Institute on Deafness and Other Communication Disorders, NIH, Bethesda, Maryland), anti-beta tubulin (1:4000) and anti-actin (1:4000) from Sigma.

## **ABR RECORDINGS**

ABRs were recorded immediately before and after removal of the ossicular chain, and 7 days post injury. Recordings were performed using a close-field real-time signal processing system (Tucker-Davis Technologies (TDT), System 3, Alachua, Fl, USA), as previously described in Lamas et al. (2013).

On the side of the ossicle chain removal, the four characteristic waves of the rat ABR disappeared, thresholds were increased up to 90 dB SPL and did not show any recovery 7 days after the surgery (**Figure 1**). Fifteen days after the injury, waves were visible at 80 dB SPL. The side contralateral to the experimental lesion showed ABR thresholds similar to those of pre-lesion condition at all post lesional times (**Figure 1**). The amplitude of the four waves for this side was increased by 50–100% relative to pre-lesion condition at 15 PSD.

Changes in the ABR from animals with unilateral ablations of the AC have been previously described in Lamas et al. (2013). Briefly, on the side of the lesion the amplitude of the waves was decreased by 25–40% relative to pre-lesion condition at 1 PSD, and recovered at 7 PSD. The side contralateral to the ablation showed ABR amplitudes similar to those of pre-lesion condition at all post-lesion times.

## **STATISTICAL ANALYSIS**

Real-time PCR results are shown as mean ± SD and were tested for significance using one-way ANOVA with Scheffe and Bonferroni *post hoc* tests. Ipsi- vs. contralateral statistical comparisons were carried out with Student's *t*-test. Differences were considered significant at the *p* < 0.05 level. Statistical analysis was performed using the SPSS-IBM software, version 20 (SPSS Inc., Chicago, IL, USA).

#### **LOCALIZATION OF THE LESIONS IN AC**

The localization of the lesions in AC was performed as described in Lamas et al. (2013). Briefly, after perfusion fixation and brain removal, the lateral surface of the brain was photographed using a Nikon camera located 21 cm above the cortex surface, and the photograph was superimposed to a purposely built coordinates map (Lamas et al., 2013). The extension of the lesion expressed in percent area of AC was calculated using the "area dimensioning tool" of Canvas X software (Lamas et al., 2013).

All ablations specifically encroached the major subdivisions of the AC (primary, dorsal and ventral cortices), and affected all AC layers but not the underlaying white matter. Lesions included a region ranging from 70 to 100% of the total AC area (**Table 2**).

## **RESULTS**

## **PRESTIN PROTEIN OLIGOMERIZATION AFTER SOUND ATTENUATION BY UNILATERAL MIDDLE EAR OSSICLE REMOVAL**

Western blotting was performed to assess oligomerization and relative amount of Prestin protein in the cochlea at two survival times (7 or 15 PSD) after unilateral removal of the middle ear ossicles. Protein levels in the sides ipsi- and contralateral to

**Table 2 | Extent of lesions in the rat brain AC**.

This table shows the percentage of AC affected by lesions in the experimental groups. Data are presented by Mean ± standard deviation. WB = Western Blott. RT-qPCR = Reverse Transcription quantitative polymerase chain reaction.

the lesion were compared. After blotting cochlear samples with antiprestin antibodies, Prestin was displayed in Western blots from control animals in bands corresponding mostly to 80, 160 and 240 kDa (**Figure 2**—7 PSD, control animals on the two left tracks), in accordance with the reported molecular weights of the monomers, dimers and trimers of this protein, respectively (Matsuda et al., 2004).

There were no major differences in the pattern of immunoblot staining between both survival groups after middle ear ossicle removal. **Figure 2** shows Western blots from three representative cases at 7 PSD. Western blots from animals at 15 PSD are not shown. Bands corresponding to Prestin monomers in animals after ossicle removal were comparable to those seen in control animals, regardless of survival time (**Figure 2**, lower arrow). However, the bands corresponding to prestin dimers (160 kDa) stood out more strongly labeled in animals with unilateral conductive deafness. This 160 kDa band was more marked in the side contralateral to the lesioned ear (**Figure 2**, second arrow from bottom). In general, bands corresponding to trimers were attenuated or absent at 7 and 15 PSD both in the cochleae ipsi- and contralateral to the lesion. Interestingly, however, in one case at 7 PSD after unilateral ossicle chain removal, the band corresponding to prestin trimers in the cochlea contralateral to the lesion, was comparable in intensity to that of controls (**Figure 2**, third arrow from the bottom).

Bands corresponding to the potential localization of tetramers (320 kDa) were faint or undetectable either in controls or in the conductive deafness experimental group at any survival time.

## **PRESTIN PROTEIN OLIGOMERIZATION AFTER ATTENUATION OF DESCENDING INPUT TO THE COCHLEA BY UNILATERAL AC ABLATION**

The effects of unilateral AC ablation on the oligomerization and relative amount of prestin protein in the cochlea, were also tested by Western blot. In the cochleae ipsilateral to the AC lesion, there were no immunolabeled bands above 160 KDa, indicating disappearance of trimeric Prestin forms relative to controls, with tetrameric forms being absent, like in control animals. Bands corresponding to monomers and dimers were unchanged relative to controls (**Figure 3**).

Western blot analysis of the cochleae contralateral to the AC lesion showed a banding pattern for monomers and dimers similar to that found in the ipsilateral side and therefore comparable to control cochleae. However, different to the ipsilateral side, dense bands at the 240 kDa location, corresponding to an intense expression of Prestin trimers were detected in most animals (**Figure 3**) at all survival times. A band at 320 kDa corresponding to Prestin tetramers was also visible in the side contralateral to the lesion.

No major differences were seen in the patterns of Prestin expression detected by Western blot at any of the three tested survival times, 1, 7 or 15 PSD (**Figure 3**).

### **nAchR** α**10-SUBUNIT, PRESTIN AND BETA-ACTIN mRNA LEVELS AFTER PARTIAL INACTIVATION OF DESCENDING INPUT TO THE COCHLEA BY AC ABLATION**

We carried out qRT-PCR to assess changes in the expression of the α10-subunit of the OHC nAChR, Prestin and β-actin

mRNA in the cochlea ipsi and contralateral to the lesion at different times after AC ablations. Collectively, these three markers should give an indication of how partial inactivation of MOC affects the molecular machinery of the OHC involved in electromotility.

The α10-subunit transcripts of the nAChR showed a significant decrease in the cochleae ipsilateral to the lesion at 1 PSD after the AC ablation (**Figure 4A**). However, both at 7 and 15 PSD, α10 mRNA levels were significantly increased (**Figure 4A** gray bars). The increase in the α10-subunit transcripts was above two fold relative to control values at 7 PSD and above four fold at 15 PSD (**Figure 4A**).

The cochleae contralateral to the lesion did not show statistically significant changes in the expression of the α10 subunit at 1 PSD. However, both at 7 PSD and 15 PSD α10 mRNA levels were increased. These increases were four fold relative to control values at 7 PSD, and two fold at 15 PSD, respectively (**Figure 4A** white bars).

Prestin transcripts showed a significant threefold increase relative to control values in the cochlea ipsilateral to the lesion, at 1 PSD (**Figure 4B** gray bar). Increased transcript levels were even larger at 7 PSD, reaching six fold relative to controls, and returned to values similar to those of controls at 15 PSD (**Figure 4B** gray bars).

The cochlea contralateral to the lesion did not show any significant change in the expression of prestin at 1 PSD. An eight fold increase relative to control values was found at 7 PSD whereas at 15 PSD there was a significant decrease below control values (**Figure 4B** white bars).

The analysis of β-actin transcripts showed a significant decrease relative to control values in the cochlea ipsilateral to the lesion at 1 PSD following AC ablation. β-actin transcript levels returned to values comparable to those of controls at 7 PSD and decreased again at 15 PSD (*p* < 0.001)

(**Figure 4C** gray bars). No statistically significant changes were found in the expression of the β-actin gene in the contralateral cochlea at any PSD after AC ablation (**Figure 4C** white bars).

that present differences between the ipsi- and contralateral ears are framed in a box, and their statistical significance is shown at the bottom. \*p < 0.05;

## **DISCUSSION**

\*\*p < 0.01; \*\*\*p < 0.001.

The first key finding reported in this paper is that oligomerization of the OHC membrane motor protein Prestin is regulated by the interaction of acoustic input and centrifugal efferent cholinergic neurotransmission on OHCs.

In the normally functioning auditory receptor, monomeric and oligomeric forms of Prestin coexist, as shown in Western blots from control animals (see **Figures 2**, **3**). Prestin oligomers include mostly dimers and trimers, whereas tetrameric forms are barely detectable in cochlear homogenates from control animals. The absence of tetrameric forms in our control Western blots is compatible with current views of Prestin oligomerization. Whereas tetramers may actually be present but not detectable in our control cochleae, the view that prestin functions strictly as a tetramer (Hallworth and Nichols, 2012) has been seriously challenged. Correlative electrophysiological and dynamic fluorescence measurements suggest that sub-tetrameric oligomers, or even monomers, are functional (Bian et al., 2013) and not mere precursors for the assembly of tetramers.

Dampened acoustic input subsequent to unilateral middle ear ossicle removal, diminishes prestin trimers, often below detection levels, in Western blots from cochleae in the side of the lesion. Dimeric forms, however, are preserved or even increased. These findings suggest that Prestin oligomerization beyond dimers requires normal acoustic input. Actually, Xia et al. (2013) have reported global increases in Prestin protein levels in the cochlea after noise-induced hearing loss, but these authors did not provide evidence as to whether such an increase was attributable to monomers or one or several oligomeric forms. The mechanism and role of this activity-dependent oligomerization will have to be elucidated. Shutting off oligomerization of larger Prestin forms while simultaneously increasing dimeric forms, might represent a mechanism to adapt cochlear micromechanics and amplification to diminished acoustic stimuli. On the other hand, the finding of relatively more dense dimeric bands in the cochlea contralateral to the lesion along with less frequent loss of trimers, may be related to subtle compensatory changes in the unmanipulated cochlea, driven by acoustic input imbalance between both ears, as discussed further in detail.

A second most relevant finding is that activity of the cochlear efferent system is also required to regulate Prestin oligomeric assembly. Evidence comes from results of ablation of the AC. Descending projections are complex, and include direct corticopontine and indirect colliculopontine pathways. At least corticopontine projections, are bilateral and symmetric, although more dense in the ipsilateral side (Doucet et al., 2002; Doucet and Ryugo, 2003; Schofield and Coomes, 2005), and innervate MOC in the ventral nucleus of the trapezoid body (Mulders and Robertson, 2000). MOC, in turn, send efferent axons bilaterally to OHCs, modulating its micro-mechanical properties (Guinan, 2006). Due to the excitatory nature of the corticofugal projection (Feliciano and Potashner, 1995), its degeneration after unilateral AC ablation induces loss of excitation on MOC, more marked in the ipsilateral side and, therefore an imbalance of efferent input between both ears (León et al., 2012).

After unilateral ablation of the AC, Prestin trimers were barely detectable in the cochlea ipsilateral to the lesion, whereas monomer and dimer bands were generally comparable to controls. In contrast, dense trimer bands were visible in the cochlea contralateral to the AC ablation. Prestin tetramers were also clearly detectable in the cochlea contralateral to the lesion. These findings suggest that diminished efferent activity on OHCs in the side of the AC ablation, also limits the assembly of higher forms of Prestin oligomers. Thus, monomeric and dimeric forms of Prestin might represent stable pools, relatively unaffected by changes in the acoustic or efferent input to the cochlea, at least after manipulations like those reported here. It is relevant that in the cochlea contralateral to the AC lesion, less affected by loss of efferent activity, Prestin trimers and tetramers are more intensely expressed. This may represent a mechanism to adapt cochlear amplification to efferent imbalance between both ears, whose intrinsic molecular nature is unknown.

Taken together, these findings support that Prestin oligomerization (Zheng et al., 2006; Mio et al., 2008) is regulated both by acoustic input and efferent activity. This may be part of mechanisms to adapt electromotility and cochlear amplification to altered inputs, including input imbalance between both ears. This prediction is worth pursuing through further experimental work.

A third finding is that efferent activity also regulates the expression of key genes involved in electromotility. The expression of the alpha10 subunit of the nAchR, Prestin and betaactin genes are affected by diminished and unbalanced activity in the MOC, probably also as part of adaptations to altered input.

The main neurotransmitter in MOC is Ach (Warr, 1975; Altschuler et al., 1985; Vetter et al., 1991) which binds to an α9/α10 nAchR on OHCs (Elgoyhen et al., 1994, 2001), modulating motility and axial stiffness (Sziklai and Dallos, 1993; Sziklai et al., 1996, 2001; Dallos et al., 1997; Kalinec et al., 2000). In our unilateral AC ablation model, an expected loss of MOC cholinergic activity correlates with an acute (1 PSD) decrease in the gene expression of the α-10 subunit. This is followed by increased expression at 7 and 15 PSD, which is comparatively greater in the side ipsilateral to the AC lesion, where the activity of the descending corticopontine projection likely is less affected (Doucet et al., 2002; Doucet and Ryugo, 2003; Schofield and Coomes, 2005). This changes in the expression of the nAChR alpha-10 subunit point to OHC adaptation to loss of cholinergic input. The nature and function of such adaptations are unknown and need to be investigated in the future.

Likely as part of adaptive responses to limited MOC activity on OHCs, Prestin gene up regulation is seen in the cochlea ipsilateral to the AC ablation at short times (1 and 7 PSD) after the lesion, with a return to control values at 15 PSD. In the cochlea contralateral to the AC lesion, however, increased Prestin mRNA levels are found just at 7 PSD, with levels at 15 PSD slightly decreased relative to controls. Whereas these oscillations in Prestin gene expression do not bear a linear relation with changes in protein levels seen in Western blots, they probably represent additional levels of regulation by efferent activity or an indirect effect of GABA or CGRP release by the MOC terminals (Maison et al., 2003).

It is also interesting that there is a significant drop in the expression of the β-actin gene at 1 PSD in the cochlea ipsilateral to the cortical lesion. Down-regulation of the β-actin gene could be partly responsible of a greater motor deactivation (Matsumoto et al., 2010) and may reflect the effect on one of the final targets of efferent regulation on OHCs. This may be related to decreased activity in the ipsilateral cochlea, with higher thresholds and a decrease in the amplitude of ABR waves, after unilateral AC lesions (Lamas et al., 2013). In this regard it is interesting to note that at 15 days PSD, prestin gene expression returns to levels similar to controls, while expression levels of the nAChR α10 subunit are still increased. This change, which coincides in time with the recovery of the ABRs previously observed by us (Lamas et al., 2013), may reflect an OHC electromotile "resetting" induced by nAchr receptor adaptations at the MOC-OHC synapse. Therefore, the activity-dependent regulation of the α10 subunit, prestin and β-actin genes reported in this paper may reflect OHC adaptations to changes in MOC activity to compensate for limited and/or unbalanced corticofugal excitation.

In conclusion in this paper we suggest that at least two mechanisms are at work in combination to balance the micromechanical response of the OHC after a decrease in inner ear activity: changes in oligomerization of Prestin and MOC cholinergic neurotransmission along with regulation of the expression of Prestin and β-actin genes.

## **AUTHORS CONTRIBUTIONS**

Miguel A. Merchán and Veronica Lamas designed the experiments. Veronica Lamas and Juan C. Arévalo performed the experiments and analyzed data. Veronica Lamas, Juan C. Arévalo, José M. Juiz and Miguel A. Merchán participated in the discussion of the results. José M. Juiz, Miguel A. Merchán and Veronica Lamas, wrote the paper.

## **ACKNOWLEDGMENTS**

The authors would like to thank Javier Herrero Turrión for his excellent technical assistance, and Dr. Bechara Kachar for providing us with the prestin antibody. This research was supported by the grants from the Ministry of Economy and Competitiveness of the Government of Spain, BFU2012-39982-C02 and BFU2012- 39982-C01. This article was written in memory of Dr. Pablo Gil Loyzaga (1954–2013).

## **REFERENCES**

**Conflict of Interest Statement**: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 21 October 2014; accepted: 24 December 2014; published online: 20 January 2015*.

*Citation: Lamas V, Arévalo JC, Juiz JM and Merchán MA (2015) Acoustic input and efferent activity regulate the expression of molecules involved in cochlear micromechanics. Front. Syst. Neurosci. 8:253. doi: 10.3389/fnsys.2014.00253*

*This article was submitted to the journal Frontiers in Systems Neuroscience*.

*Copyright © 2015 Lamas, Arévalo, Juiz and Merchán. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms*.