Despite over 100 years of study, there are still many fundamental questions about binaural hearing that remain unanswered, including how impairments of binaural function are related to the mechanisms of binaural hearing. This review focuses on a number of studies that are fundamental to understanding what is known about the effects of peripheral hearing loss, aging, traumatic brain injury, strokes, brain tumors, and multiple sclerosis (MS) on binaural function. The literature reviewed makes clear that while each of these conditions has the potential to impair the binaural system, the specific abilities of a given patient cannot be known without performing multiple behavioral and/or neurophysiological measurements of binaural sensitivity. Future work in this area has the potential to bring awareness of binaural dysfunction to patients and clinicians as well as a deeper understanding of the mechanisms of binaural hearing, but it will require the integration of clinical research with animal and computational modeling approaches. The ability to process the information available in pressure waves arriving at the two ears  is available to living creatures ranging from insects  to humanBinaural function has been studied clinically from as far back as 1876 . The impSince these early clinical studies, much has been revealed about the anatomy and physiology of the binaural system. Degradation of the transduction of pressure waves in the air to fluid motion in the cochlea, known as “conductive hearing loss” (CHL), can arise from blockages in the ear canal, perforations of the tympanic membrane, blockages of the middle ear, or dysfunction of the bones of the middle ear (the “ossicles”) due to breakage or stiffening. All of these could delay or distort neural phase-locking and introduce either systematic or random error into the binaural analysis, especially if there was a substantial asymmetry between the two ears. The next site of potential dysfunction is the cochlea itself, impairment of which is known as SNHL. SNHL is defined as involving the basilar membrane, the fluids of the cochlear ducts, the organ of Corti, inner, and outer hair cells, and the stria vascularis, which is responsible for the blood supply to the cochlea. Damage or dysfunction at any of these sites has the potential to reduce both the amount of neural signaling as well as the accuracy of phase-locking to the pressure waves reaching the outer ear.While the clinical diagnosis of CHL and SNHL relies upon the detection of pure tones presented via earphones  or bone-vibration , it does not involve any measure of phase-locking. If AC and BC measurements reveal similar thresholds, but detection requires higher tone levels than is normal for a tone of that frequency, as specified by international standards e.g., , then CHAs can be seen in All of the earliest work on impaired localization , but instead of detecting a signal in noise, the task asks the listener to report directly on their binaural percept. The earliest work  involvedIn addition to behavioral methods, researchers have also used neurophysiological responses from cortical neurons to compare binaural responses in patients to those found in control participants. That binaural signals produce different neurophysiological responses than do diotic signals has been known for many years , but onlThe section on methods of characterizing binaural impairment describes a range of techniques that have all been applied to listeners with peripheral hearing loss (CHL and/or SNHL). This section will review a selection of those studies, focusing on the earliest studies that pioneered the methods and then moving on to those studies with the largest number of participants and the most comprehensive methods. While tentative conclusions are drawn in some cases, the field of clinical research in the area of binaural dysfunction is still developing its evidence base. For this reason, the emphasis of this, as of the later sections, is as much on what has been done as on what has been learned.The first tests of clinical patients’ binaural function using modern methods, in which sensitivity is dissociated from response bias, occurred in the 1980s. Prior to this time, all of the tests involved methods that were susceptible to response bias. For example, the localization of single sounds through identifying a location or adjusting knob can be influenced by expectations of where the sounds are likely to appear. Similarly, pressing a button when a sound is presented or repeating a spoken word depends on the willingness of the listener to report what they experienced. Discrimination tasks, in which two intervals are presented, only one of which contains a target, allows sensitivity to a stimulus to be measured independently of the expectations or willingness of the observer with regard to making a response . HäuslerTo better understand the sources of between-subject variance in localization, While this is only a sample of the data that have been collected on localization abilities of those with peripheral impairment, the interested reader is referred to Overall, the studies described above, as well as those reviewed by While asking listeners to report the location of sounds presented over headphones is a direct method of measuring binaural sensitivity, the MLD has the advantage of simplifying the task to one of detection of a signal in noise, which does not require introspection about binaural percepts and thus may lead to more reliable performance. 0S0), or the noise was diotic and speech was delayed to the left or right ear by 0.8 ms (N0ST). The MLD was defined as the difference between the levels that produced the same percentage of correct responses for N0S0 and N0ST, based on the psychometric functions obtained. Data were compared to that of a control group of 20 listeners with normal hearing thresholds, who had an average MLD of roughly 7.5 dB.For ten listeners with symmetrical CHL (PTA of at least 60 dB HL in both ears), the MLD was only slightly lower than that of the controls (7 dB). Ten listeners with asymmetrical conductive loss  had an average MLD of 4.5 dB when the poorer ear was leading in time, which was further reduced to 2.5 dB when the better ear was leading. For those with Ménière’s disease , the MLD was roughly – 0.5 dB when the signal to the poorer ear was leading in time and was 3.5 dB when the better ear was leading in time. For those with presbycusis, the MLD was 6 dB. These results support the findings of 0S0, where both signals were diotic, and N0Sπ and NπS0 and where one signal was diotic and the other was reversed in phase at the two ears. As the methods from the two studies were essentially identical, the results have been combined here. Additional data from this study will be described in the section titled “Studies on Binaural Function With Participants With Central Dysfunction” as well. Combining the patients with peripheral loss across both studies results in a group of 124 patients: 62 with high-frequency noise-induced hearing loss, a group of 32 people with unilateral losses due to Ménière’s disease, 10 patients with unilateral conductive loss, and 20 patients with presbycusis. Results were compared to data from 62 control participants with normal hearing. Ninety-one percent of those with Ménière’s disease showed abnormal performance, as opposed to only 50% of those patients with presbycusis or conductive losses. Thirty-seven percent of those with noise trauma performed abnormally. These results support the conclusion that low-frequency hearing loss, which is more common in Ménière’s disease than in the other groups, is one of the aspects of peripheral hearing loss most likely to result in binaural dysfunction.n = 651). The main result, consistent with the data just reviewed, was that the MLD was found to depend on hearing thresholds at 500 Hz and to follow the same audibility function measured by One of the essential insights into both peripheral loss and binaural impairment that has emerged in the past two decades is the idea that peripheral loss can lead not only to reduced sensitivity to pure-tones, but can also interfere with phase-locking at the level of the auditory nerve. Recognition of the importance of sensitivity to both the TFS and the TES of the binaural stimulus has led to significant advancements in both the testing and modeling of binaural impairment. For example, Another area in which the effects of peripheral loss have been studied extensively but are still poorly understood mechanistically is that of SRM, which is defined as any improvement in target detection or recognition that accompanies the introduction of spatial cues that differ between a stimulus to be detected or identified (the target) and a stimulus to be ignored (the masker). Binaural release from masking (BRM) refers to the improvements that occur when a binaural cue is provided, which may or may not result in a spatial percept. It is worth distinguishing the two, especially when the goal is to understand the underlying mechanisms.n = 82) varying in age, with and without mild-to-moderate SNHL. The results were used to make a predictive linear regression model of performance which was able to account for 38% of the variance in SRM with only the audiogram. Early work, described in the section on peripheral loss and binaural sensitivity to interaural differences, focused on the MLD, using headphone presentation in the presence of noise . Much ofOther studies with symmetrically placed maskers  have alsOne study that has applied such a direct approach is From the data presented in sections “Peripheral Loss and Binaural Sensitivity to Interaural Differences” and “Peripheral Loss and SRM,” it is clear that at least some listeners with poorer pure-tone detection thresholds are impaired on tasks requiring good TFS sensitivity, especially for narrowband stimuli and those in which the ITD is not present in the TES . On the The modeling approaches that have been most successful in predicting the binaural abilities of individual listeners (rather than group differences) have combined pure-tone detection thresholds with metrics unrelated to spatial cues such as age, measures of speech understanding , and/or While many researchers have focused their studies of binaural impairment on the relationship with pure-tone detection thresholds, as audiological practice might suggest, there are a number of other groups that have conducted investigations of some of the other ways in which binaural function could be impaired. Much of the earliest work on binaural impairment was conducted with patients with normal or near-normal pure-tone detection thresholds who were diagnosed with MS, strokes, brain tumors, or traumatic brain injury. More recently, there has been considerable interest in the effects of aging, alone and in combination with hearing loss, on binaural function. The results of such studies are extremely important for connecting the animal literature on binaural processing to the human literature on binaural function. In animals, detailed information can be gained about the pathways and signal processing associated with the binaural system, but data on complex behavioral tasks are very difficult to obtain. With humans, the opposite is generally true. The exception is when imaging data are available showing precise lesion locations for a patient who has also performed spatial hearing tasks. As imaging techniques improve and our understanding of neurological disease progresses, there is great opportunity for our knowledge of the mechanisms of binaural hearing to improve as well.One of the most difficult issues associated with the study of hearing loss, especially in the high frequencies, is the comorbidity with aging. For binaural impairment, this issue is especially important to address, as there is considerable reason to believe that those with aging auditory systems can potentially suffer from a wide range of monaural and cognitive impairments that are likely to influence performance on tests of binaural function (reviewed in n = 12) could detect binaural FM of 0.4 Hz on average, the middle-aged group (43–57 years) could only detect binaural FM of 0.8 Hz, and the older group (aged 65–77 years) needed almost 2 Hz of modulation before they could perform the task. The younger group also performed better than the other two groups when the stimuli were presented diotically, but even the younger listeners still needed more than 2 Hz of modulation in order to perform the task with no binaural difference. When the stimuli were presented diotically to the middle-aged and older groups, they needed 3 and 3.5 Hz, respectively.r = 0.08) but more strongly correlated at higher frequencies (r = 0.439). Listeners were asked to detect IPDs in low frequency (250 or 500 Hz) tones amplitude-modulated at a rate of 20 Hz. IPDs were applied to either the carrier or the modulator in order to test the hypothesis that there is an age-related deficit in TFS processing that is independent of a binaural impairment. Presentation levels were set by first measuring the detection threshold for the stimuli and presenting all stimuli at a minimum of 30 dB SL. The data revealed age-related deficits in binaural processing for the 500 Hz tones, whether the IPD was applied to the carrier or the modulator, and for the 250 Hz tones, but only when the IPD was applied to the modulator. These data were taken to support a generalized age-related decline in temporal processing rather than a specifically binaural impairment.r = 0.56). All stimuli were presented at 60 dB SPL. The hypothesis tested was that there would be at most small effects of age on AM detection at either rate, but that FM detection would be more impaired with aging for the slow-rate stimulus, where only TFS cues were available. Contrary to expectations, however, age effects were observed not only for both slow and fast FM presented diotically or dichotically, but also for fast dichotic AM. These results also support the idea that impairments in temporal processing associated with aging are likely to involve a variety of processes, including, but not limited to, TFS sensitivity.n = 78) varying in age (18–75 years) and hearing loss (0–40 dB HL at 2 kHz). Listeners were tested on monaural, binaural, and bilateral timing discrimination tasks with brief (4 ms) stimuli with narrow or broad frequency content, all centered at 2 kHz. In the monaural task, listeners were asked to detect a gap between two stimuli, in the binaural task they were asked to detect an ITD, and in the bilateral task, they detected delays between the presentation of a signal to the left and right ear. Gaps, ITDs, and bilateral delays were adaptively varied to determine threshold. Presentation level was set to 30 dB above detection threshold for each stimulus. Rather than relying upon group differences or partial correlations, a linear mixed model was developed in which performance across all stimuli and tasks was modeled, taking into account each individual’s age and stimulus detection thresholds. One advantage of this approach is that each individual can be assigned an intercept value for their function, reflecting that individual’s ability to perform psychophysical tasks. The model predicted 20–40% increases in monaural gap detection thresholds per decade of aging, 15–20% increases in ITD discrimination thresholds with every decade, and 0.9–10% increases in bilateral delay sensitivity, all independently of increases in temporal processing ability with increases in signal detection thresholds. Many of the studies examining the effects of hearing loss on SRM, especially with speech stimuli, have also focused on the effects of aging. Early work measuring the MLD with tones e.g.,  was repln = 30). While SRM did not differ between the groups, performance for the older listeners was worse than a model based on the audiogram predicted, and there was a strong correlation between age and performance in the spatially separated condition. n = 40) and observed relatively small effects of age independent of hearing loss. These results with SRM support the findings of age-related declines in binaural sensitivity and localization accuracy. The primary difficulty with interpreting all of these results, however, is that it is unclear whether the mechanisms by which aging and hearing loss cause binaural impairment are fundamentally different. Future work combining human studies with computational models of the binaural system can shed light on this, especially if informed by animal models of binaural impairments associated with age and hearing loss.As mentioned in the section on aging and binaural sensitivity, In summary, our understanding of the mechanisms relating aging to binaural sensitivity is far from complete. What is clear is that there are aging effects that can be observed both behaviorally and neurally, and that animal and computational models have the potential to both clarify existing data and point the way toward new approaches to the study of aging and binaural function.Multiple sclerosis is a disease of the nervous system that leads to lesions both at the level of the brainstem and at the cortex. While there have been a small number of studies of binaural sensitivity in MS patients, the promise of modern imaging technologies has only begun to be explored. With the ability to identify specific lesions and relate them to binaural function, it may be possible to obtain evidence in humans of the specific roles of various brain areas; evidence that only animal models could previously provide. This is also the promise of the work detailed in the section on the effects of brain tumors and lesions on binaural sensitivity.The existing literature shows clearly that MS patients are likely to have binaural deficits. One of the earliest reports to show this was the MLD data on 100 patients with MS reported by In addition to the MLD, some studies have also examined sensitivity to ITD and ILD directly, such as “The fact that different tests  give independently normal and abnormal performance, even with the same stimulus, suggests that different regions of the brain are involved in processing the different aspects of the stimulus, such as interaural time delay versus interaural intensity differences” (p. 42).This statement reveals how useful it can be to test patients with neurological disorders and how essential it is to pair these tests with animal models and the results of neurophysiological experiments. While it is well-accepted today that ITD and ILD are processed by independent brain regions, these patient data were early indicators that preceded the more definitive neurophysiological studies to come.In the 1990s, several additional studies of lateralization and sensitivity to interaural differences were conducted with patients suffering from MS . Due to While it is tempting to imagine that the earliest work on binaural impairment focused primarily on peripheral hearing loss, the reality is that Yet, despite these remarkable aspects, some important elements are missing from “information flow on the auditory nerve is extremely disrupted by some auditory nerve lesions. The timing and intensity information can be essentially eliminated at supra-threshold levels, even when the threshold value is only slightly affected. If one postulates a tumor pressing against nerve fibers, it is easy to imagine not only a disruption of the timing of individual action potentials but also an interference with the number of firings  without an associated change in the absolute detection threshold. I am not aware of an animal model for this condition” (p. 41).It is probably fair to say that little has changed in terms of our understanding of the effects of eighth-nerve tumors on binaural hearing in the intervening decades. On the other hand, one area that has been very informative is the study of patients with strokes that impinge on the auditory brain regions. Horizontal localization in patients with cortical and brainstem damage from strokes was also studied by The work of the Vietnam Head Injury Study VHIS;  stands eAnother population found to have difficulties with binaural tasks is those who have experienced head trauma . BinauraThis heterogeneity across patients may explain why These results, like the data reviewed from patients who have suffered strokes, developed MS, or are undergoing the normal aging process, reveal the complexity of doing clinical research with patient populations. Nonetheless, shedding light on binaural dysfunction is of great benefit to the patients and to the clinicians who treat them. The binaural system is poorly understood by the general public, and even by most clinical specialists. By clarifying the dysfunction likely to occur among patients with various diseases, it becomes possible to develop new clinical tests as well as to train clinicians in how to counsel those with binaural impairment. In addition, there is potential to deepen our understanding of how the binaural system functions by learning what mechanisms can be impaired and how such mechanisms can change binaural processing.The work reviewed in the sections above suggests that, while much has been learned about binaural impairment since the first reports over 100 years ago, there is still much to be discovered. The field would benefit from further research in a number of areas, including animal models and computational modeling. As is clear from this review, the approach of testing participants who have diseases known (or suspected) to affect the binaural system has substantial potential benefit in two different ways. The first is that we are likely to learn more about those diseases and what abilities and difficulties people with those diseases are likely to experience. The second is that these diseases allow scientific investigation of auditory processing that has been perturbed in ways that are otherwise only possible to do in animal research.It should be noted that despite the many studies and conditions discussed, this review has not been comprehensive, as there has been no discussion of binaural development in children, nor of the effects on binaural function of many additional auditory and brain diseases. In some cases, such as with development, this was due to a need to limit the scope, and in many others it was due to the lack of a well-developed literature. There are many reasons for the limited literature on binaural impairment, both for some of the conditions discussed and for many of those not discussed. The most important is that there are substantial challenges associated with analyzing “nature’s experiments.” The most difficult obstacle is that, unlike in the laboratory, the perturbations of the system are not uniform and are not easily documented. This is why it is of great benefit to develop animal and computational models, where clear relationships can be established between internal modifications of the system and externally measured values. In addition, it is of great value to take advantage of existing human brain imaging technologies and push for the development of new methods that will allow the binaural system to be more clearly revealed.The other significant obstacle to taking advantage of the binaural impairments imposed by disease, injury, and natural biological processes is one of scientific and clinical culture, rather than techniques or knowledge. While some of the literature cited above reveals collaborations among clinicians and scientists and publications of clinical and basic research in the same journals, much more of it does not. The early literature is striking for a number of reasons, including the creativity and innovation shown in the methods and the insight revealed by the scientists. One aspect that should not be overlooked, however, is the degree to which the work was being done by clinician scientists, testing their own patients using cutting-edge methods. Progress in clinical research on binaural impairment depends on using the newest approaches in testing binaural hearing to better understand the abilities of large numbers of patients with similar disease states, as revealed by the best clinical metrics available. To do this requires us to attend the same conferences, publish in the same journals, and collaborate on grant applications together. Only in this way can new approaches for clinical care be developed and new insight gained into the ways that the binaural system can change its functioning in the course of a human lifetime.The author confirms being the sole contributor of this work and has approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background: Tinnitus is a serious health condition. It can be debilitating and as such negatively affects a patient's quality of life. People with tinnitus often experience distress, depression, anxiety, frequent mood swings, sleep disturbances, irritability, frustration, poor concentration, and possible suicidal thoughts or actions.Objective: The goal of this article is to introduce an acupuncture system, based on neurophysiology and termed Neuropuncture, as a possible effective treatment method for tinnitus accompanied with and/or secondary to hearing loss. The treatment protocol works by targeting the greater auricular nerve, trigeminal nerve, cervical plexus, and auditory cortex to neuromodulate, neurorehabilitate, and neuroregulate the nervous system and repair the nerve damage.Design: Three case studies are presented herein as examples. They are based on neurophysiologic mechanism of tinnitus and hearing loss, treatment principle, treatment methods, and subjective and clinically objective tests. Electroacupuncture protocols used various frequencies with microcurrent and millicurrent stimulation.Conclusions: Neuropuncture system is an effective treatment for patients with acute and chronic subjective tinnitus and hearing loss. Results showed reduction of tinnitus and partial restoration of hearing loss. Further research and possible large-scale trial studies are suggested. It is estimated 90% of tinnitus cases occur with underlying hearing loss.2Tinnitus is the perception of sound when there is an absence of actual external noise.3 Tinnitus is considered as a pathology that involves synaptic plasticity at the level of the synapses between inner hair cells and the auditory nerve.4 Specifically when sound waves hit the tympanic membrane, the vibration causes the Organ of Corti and its hair cells to generate electrical signals that are then sent to the brain for interpretation. The tympanic membrane is innervated by the auriculotemporal branch of the trigeminal nerve, the auricular branch of the facial nerve, the auricular branch of the vagus nerve, and the glossopharyngeal nerve.5Tinnitus is commonly described as ringing in the ears. It can also sound like roaring, hissing, buzzing, whistling, swooshing, ringing, or clicking. It may be soft or loud, and high or low pitched, and can happen in 1 or both ears. It can be the result of a number of health conditions but is not a disease by itself.6Sensory innervation to the external ear is supplied by both cranial and spinal nerves. Branches of the trigeminal, facial, and vagus nerves  are the cranial nerve components, while the lesser occipital and greater auricular  nerves are the spinal nerve components involved. The vestibulocochlear nerve, also known as cranial nerve 8 (CN VIII), has distinct nuclei within the brainstem and the cochlear nerve is responsible for hearing.7 and enhance the excitability and conductivity of the auditory nerve.8 Karavis reported how the neurophysiology mechanism of acupuncture activates neural pathways that created multifactorial phenomenon throughout the body.9 Han concluded that acupuncture or electrical stimulation in specific frequencies applied to certain body sites can facilitate the release of specific neuropeptides in the central nervous system (CNS), which subsequently elicit physiologic effects and activate self-healing mechanisms.10–14 Kim et al.15 in a recent trial study showed that electroacupuncture is more effective than manual acupuncture and TENS  for people with chronic tinnitus.Recent studies have shown that acupuncture could regulate inflammatory response,Based on these theories and clinical experience, the authors report herein the use of this acupuncture protocol and preliminary results on patients with acute and chronic tinnitus secondary to hearing loss treatments as a possible effective and clinically reproducible treatment method.For tinnitus and hearing loss, the treatment principles are focused on local inflammation; target specific nerves such as the greater auricular nerve, facial nerve, trigeminal nerve, and vagus nerve; target specific neural plexuses that innervate the vestibulocochlear nerve, and also target the CNS specifically the auditory cortex. This acupuncture system utilizes electroacupuncture to neuromodulate the damaged nerves, neuroregulate the neural plexuses, and neurorehabilitate regions of the brain to repair them back to health.16 These points are located near regions of the TCM  points. They are GANP (Greater Auricular Neuropuncture Point) (The authors used 7 Neuropuncture points.e Point) , SRNP (Se Point) , TriFNP e Point) , PANP (Pe Point)  of the ae Point)  of both 17 concluded neither the loudness nor other psychoacoustic measures of tinnitus had a consistent relationship to the severity of this condition, hence there was no standard protocol for tinnitus evaluation.The main Neuropuncture prescription for tinnitus is to connect the lead with electrical clamps to GANP and SRNP, and another lead to TriFNP to PANP on the affected side. The Neuropuncture Electrical Dosage is 25 Hz microcurrent. In an alternate modified Neuropuncture prescription for tinnitus the third lead is connected from HTJJ C2 and C3 to the Neuropuncture Scalp Auditory Cortex region bilaterally. See A 57-year-old woman came to the office on June 19, 2019 seeking relief from her tinnitus and hearing loss. Her vital signs, including blood pressure and pulse rates, were within normal limits. Her current medical history included severe sinusitis, insomnia, fatigue, and stress.One year ago, patient started to feel fullness in her left ear and experienced a high pitch ringing and vertigo. She felt very congested in her frontal sinuses and both ears, with the left ear being worse. She then developed a very loud high-pitch noise with hearing loss in her left ear at an SUD scale of 8/10. The noise interrupted her sleep at night. Patient went to her ear, nose, and throat (ENT) doctor, an audiogram was performed and showed significant hearing loss in her left ear, registering 40 dB within the range of 250 to 4,000 Hz, with rapid reduction beyond it.A main Neuropuncture tinnitus prescription was performed at the first treatment. Patient reported that hearing began to return slowly afterward. After 3 treatments, she reported that she was able to hear a different “layer” of sound (she is a musician) and began to enjoy listening to music again. A total 12 treatments twice a week, including Tinnitus Main and Modified Protocols, were conducted. Patient reported having tremendous “draining” from her ears and the ringing changed from high pitch to a different lower tone with much less intensity with an SUD scale of 4/10. Her relationship with her husband improved because she did not have to constantly ask him to repeat himself in conversation.The patient saw her ENT doctor for her 1 year follow-up in June, 2020. The result of the audiology test showed a significant improvement in hearing of her left ear. She was able to hear low frequency at 250 Hz clearly and high frequencies ranging from 4,000 to 6,000 Hz at 15 dB. Eighteen months follow-up in the office showed the tinnitus was occasionally noticeable; her SUD scale was at 1/10 and her hearing continued to improve.A 54-year-old woman came to the office on July 21, 2020 reporting that she had completely lost hearing in the left ear. Her vital signs, including blood pressure and pulse rate, were within normal limits. Her current medical history includes loss of hearing in the left ear, tinnitus with low-pitch roaring noise at an SUD scale of 6/10, insomnia, headaches, blurry vision with nystagmus, severe sinus congestion, neck pain, and hot flashes.The loss of hearing happened immediately after her fourth craniectomy for resection of posterior fossa recurrent ependymoma located in the left lateral recess of the fourth ventricle. She was diagnosed with unilateral sensorineural hearing loss (SNHL).Before the first Neuropuncture treatment, a quick rudimentary test was conducted to check the ability of hearing by clicking the fingernails outside the left ear. Patient reported not being able to hear anything. Neuropuncture tinnitus main protocol was used at the first session. After completing the treatment, again using the same finger clicking test, the patient reported that she was able to regain some hearing. The sinus congestion was much reduced after the second treatment. After the third treatment, she was able to hear conversation if spoken close to the left ear. Patient reported that the low-pitch roaring noises had significantly reduced to an SUD scale of 2/10. She also reported that she was able to hear partial conversations between family members and sometimes understood news reporting on the television.An audiogram test was performed on August 21, 2020 after 9 treatments and that included Tinnitus Main and Modified Protocols. Patient showed improvement of her left ear that she could hear from 500 to 2,000 Hz at 20 dB. She still showed poor hearing for the low- and high-pitch sound, but this was certainly better than the complete loss of hearing in July 2020.A 52-year-old man came to the office on July 2, 2020 complaining of tinnitus and fullness in his right ear. His vital signs, including blood pressure and pulse rate, were within normal limits. Patient's current medical history includes right ear tinnitus, loss of hearing, with a fullness sensation.He reported feeling fluid in his right ear back in 2004, and his ENT doctor implanted an ear tube to help drain the fluid. This ear tube was removed in 2012. Patient started having tinnitus in 2016. He visited his ENT doctor who found a hole in the ear drum in 2018. Patient continued feeling the fullness in his right ear with high pitch ringing sound at an SUD scale of 6/10. In June 2020, the ENT doctor suggested inserting another ear tube and prescribed steroid medicine. However, patient decided to pursue the acupuncture route.After the first Neuropuncture tinnitus prescription treatment, patient reported feeling immediate relief, with the right ear fullness reduced, and the intensity of the high pitch dropped 2 U in the SUD scale from 6/10 to 4/10. The Neuropuncture treatment plan was 6 weeks for a total of 12 treatments that included Tinnitus Main and Modified protocols. At the end of the treatment plan on September 24, 2020 the patient reported that the tinnitus was noticeable reduced to an SUD scale of 1/10, and he only experienced slight “sloshing/flapping” sound once or twice a day.Neuropuncture therapy based on neuroscience and neurophysiology target the damaged nerves by stimulating the neural plexus, spinal nerves, and the auditory cortex in the CNS to neurorehabilitate, neuromodulate, and neuroregulate the ear back to health. The 3 case reports discussed earlier show acute and chronic subjective tinnitus and/or hearing loss with very different complaints and causes. The first case patient suffered long-term severe sinusitis, the second case patient suffered hearing loss and tinnitus postcraniectomy, and the third case patient had fullness in the ear with a puncture to the eardrum. Additional cases presented in 18 Unfortunately, there are no drugs or effective therapies to benefit those people who are suffering. Based on the 3 representative case reports discussed in detail, together with additional cases in Tinnitus can negatively affect the quality of life. Hearing loss is a major public health issue. Goman et al. estimated that during the next 43 years, the number of people with hearing loss in the United States is projected to almost double.


Emerging research supports that triclosan (TCS), an antimicrobial agent found in thousands of consumer products, exacerbates colitis and colitis-associated colorectal tumorigenesis in animal models. While the intestinal toxicities of TCS require the presence of gut microbiota, the molecular mechanisms involved have not been defined. Here we show that intestinal commensal microbes mediate metabolic activation of TCS in the colon and drive its gut toxicology. Using a range of in vitro, ex vivo, and in vivo approaches, we identify specific microbial β-glucuronidase (GUS) enzymes involved and pinpoint molecular motifs required to metabolically activate TCS in the gut. Finally, we show that targeted inhibition of bacterial GUS enzymes abolishes the colitis-promoting effects of TCS, supporting an essential role of specific microbial proteins in TCS toxicity. Together, our results define a mechanism by which intestinal microbes contribute to the metabolic activation and gut toxicity of TCS, and highlight the importance of considering the contributions of the gut microbiota in evaluating the toxic potential of environmental chemicals. Triclosan (TCS), an antimicrobial agent commonly found in consumer products, has been reported to exacerbates colitis in animal models. Here, using in vitro and in vivo approaches, the authors show that gut bacterial enzymes can drive the metabolic activation and gut toxicity of TCS, highlighting an important role of intestinal microbial factors in the complex etiology of colitis. In 2015, an estimated ~1.3% of U.S. adults (~3 million) were diagnosed with IBD3, representing a 50% increase from 1999 (~2 million)4. IBD can severely impact life quality, as symptoms include abdominal pain, diarrhea, and rectal bleeding, and there is no cure. Current anti-IBD treatments can result in serious side effects and idiopathic patient responses5. More alarmingly, IBD patients have increased risks of developing colorectal cancer6. While the increase in IBD prevalence has been linked to exposure to environmental chemicals9, the potential mechanisms involved have remained unclear.The incidence and prevalence of inflammatory bowel disease (IBD), the chronic inflammation of intestinal tissues10. In 2016, the USA Food and Drug Administration (FDA) removed TCS from over-the-counter handwashing products; however, it remains approved for use in a wide range of products such as toothpaste, mouthwash, hand sanitizers, cosmetics, and toys11. It is a ubiquitous environmental contaminant and a top-ten US river pollutant10. Health problems connected to TCS include increased risks of allergies and asthma, altered immune responses, disruption of endocrine functions, and increased development of antibiotic resistance10. Specific to the gastrointestinal tract, we recently showed that exposure to TCS, at human-relevant doses, increased the severity of colitis and exaggerated the development of colitis-associated colorectal cancer in mouse models12. This finding supports that TCS could be a potential risk factor for IBD and associated diseases, though further studies are needed to determine its impacts in human populations13.Triclosan (TCS) is an antimicrobial ingredient present in more than 2000 consumer and industrial products and detected in ~75% of urine samples tested in USA12. However, the specific mechanisms connecting the gut microbiota with TCS toxicity are unknown. The discovery of such gut microbial factors will define a molecular mechanism of TCS-driven gut pathology and increase our understanding of host-microbiota interactions. Previous studies have shown that once TCS enters the body, it is rapidly metabolized in host tissues, such as the liver, to form the glucuronide-conjugated metabolite TCS-glucuronide (TCS-G), which is biologically inactive and is thought to be quickly eliminated from the body14. Given this rapid metabolic inactivation, though, it has remained unclear how exposure to low-dose TCS causes gut toxicity in vivo. We hypothesize that gut microbial enzymes act on key TCS metabolites in the colon, leading to unique gut metabolic profiles highlighted by reactivation of TCS in the gut and resulting in subsequent gut toxicology. Here, using a range of in vitro, ex vivo, and in vivo approaches, we define the unique TCS metabolic patterns that lead to intestinal toxicity, pinpoint the specific gut microbial enzymes that drive the colitis-promoting effects of TCS, and disrupt those enzymes by selectively targeting the gut microbiota. These data reveal the critical roles played by gut microbial enzymes in the metabolic activation and gut toxicity of TCS.Because TCS exposure fails to promote colonic inflammation in germ-free mice, the toxicity of TCS requires the presence of the gut microbiota12. We found that after TCS exposure, the dominant TCS compound found in the liver, bile, heart, and small intestine was the biologically inactive conjugated metabolite TCS-G. In contrast, the mouse cecum and colon were dominated by free TCS. The TCS metabolites found in the digesta of the 4th section of the mouse small intestine were 36.9% free TCS, 55.4% TCS-G, and 7.7% sulfate-conjugated TCS (TCS-sulfate); while the fecal content exhibited 99.1% free TCS with only 0.7% TCS-G and 0.2% TCS-sulfate , then were randomly assigned to two groups that used personal care products like toothpaste with or without TCS for up to four months ; although two subjects (one in the control group and one in the TCS group) showed detectable levels of TCS even at t = 0  with TCS via a one-time oral gavage of TCS, then analyzed colonic TCS metabolic profiles at 31, we hypothesize that gut microbial GUS orthologs would catalyze the conversion of TSC-G to TCS. The human and mouse gut microbiome have been shown to contain hundreds of unique gut microbial GUS enzymes, which exhibit distinct substrate specificities toward varying glucuronides32. Previous studies have shown that microbial GUS enzymes can be categorized into seven distinct clades based on active site architecture and/or cofactor binding33. We created a panel of 32 purified gut microbial GUS enzymes, which represent the seven clades, for in vitro enzymatic screening34. We first screened this panel for TCS-G cleavage activity using a coupled assay and found that Loop 1 and flavin mononucleotide (FMN)-binding GUS orthologs were most efficient at utilizing this substrate  with the conversion of TCS-G to TCS. Because intestinal β-glucuronidase (GUS) enzymes have been shown to convert a wide range of glucuronidated metabolites to their corresponding aglyconesate Fig. . We thenate Fig. .Fig. 3Sp35. First, we examined human feces for their ability to activate TCS from TCS-G. Proteins were extracted from the fecal samples of three female and three male donors as described35. TCS-G turnover by the resultant mixtures revealed that all samples performed the reaction and that turnover rates varied by more than threefold , while the abundance of the other forms of GUS detected failed to exhibit correlation with TCS activation, including the abundance of FMN-binding GUS enzymes  GUS, which was the most active Loop 1 GUS protein identified from our in vitro enzymatic assays   are positioned to potentially contact TCS-G  GUS, also efficiently process TCS-G  GUS, that we show poorly processes TCS-G  and found that a 3- to 4-week treatment with GUSi had little effects on body weight, colon length, colonic or systematic inflammation, or colon histology in mice  in the colon -induced colitis in mice  cells were treated with 1 µM of TCS or TCS-G and inflammatory responses were studied. The 1 µM concentration was chosen based on data presented above showing that TCS in the stool of TCS-exposed humans was up to ~1000 pmol/g  and found that at all tested doses, the gut tissues had similar metabolic profiles of TCS and were dominated by free TCS. In addition, we found that after the mice were exposed to TCS, notably at the lower doses (1 and 10 ppm in diet), the concentrations of TCS in mouse gut tissues are comparable or within several folds of the concentrations of TCS observed in the stool of TCS-exposed human subjects , while their metabolic fates in the gut tissues are not well characterized42. This is partially explained by the diversity of the gut microbial enzymes: the sequencing data from the Human Microbiome Project suggests that the human and mouse gut microbiotas contain hundreds of unique gut microbial GUS enzymes, which have different substrate specificities varying from small compounds to macromolecules32. Novel gut microbial GUS enzymes could be identified from further microbiota sequencing and/or functional characterization. Such variation in substrate specificity among GUS enzymes is due in part to the length and positioning of loops enclosing the GUS active site31. Using sequence data from the Human Microbiota Project database, we binned GUS enzymes into seven structural classes based on their loop architecture27. We created a panel of 32 purified gut microbial GUS enzymes, which represent the seven classes, for in vitro enzymatic assays34. Using this strategy, we observed that Loop 1 and FMN-binding GUS enzymes were particularly efficient at processing TCS-G in vitro. This result suggests that these two classes were likely responsible for the majority of in vivo turnover of TCS-G as well. In support of this notion, using the approach of activity-based probe-enabled proteomics, we found that Loop 1 GUS, but not other classes such as Mini loop 1, No loop (non-FMN binding), and No Loop GUS, is correlated with TCS-G turnover in fimo. We were surprised, however, that there was no correlation between FMN-binding GUS enzymes and TCS-G turnover in fimo. One potential explanation could be that Loop 1 GUS enzymes vary mainly in the contiguous loop 1 sequence motif, which is only 15–20 residues in length. In contrast, FMN-binding GUS enzymes vary mainly in their large C-terminal domains of ~150 residues in length. To date, no structure of an FMN-binding GUS C-terminal domain has been reported, as they have remained mobile and unresolved in the structures determined thus far. Sequence identity does not appear to be sufficient to distinguish the differences between fast and slow-processing FMN-binding enzymes. For example, the sequence identity between the two fastest FMN-binding processors, Rh3 and R. gnavus 3 GUS, is 52.1%, while the sequence identity between the fastest and the slowest FMN-binding enzymes, Rh3 and Rh2 GUS, is 50.9%. It is possible that the abundance of efficient or fast FMN-binding GUS enzymes would correlate with in fimo TCS-G processing rates; but to date, because of the size of these C-terminal domains of FMN-binding GUS enzymes and our lack of structural knowledge about these domains, the specific motif(s) critical for TCS-G processing remain undefined. Overall, these results support that specific microbial GUS enzymes process TCS-G.To date, the specific gut microbial enzymes involved in the toxicity of environmental pollutants remain largely unknown27. In the sampled 139 human subjects from the Human Microbiota Project, ~40% did not have Loop-1 GUS in the fecal microbiota, and there was a wide range of abundance levels of Loop-1 GUS in those who have the Loop-1 GUS orthologs27. Here, we also showed that the fecal bacteria from different human subjects have a different abundance of Loop-1 GUS, leading to varied capacities to convert TCS-G to TCS. While future studies are needed to determine whether individuals with specific microbial GUS activities are more susceptible to the adverse effects of TCS exposure, such studies could chart the metabolic individuality of TCS and clarify the potential toxic effects of TCS on human health. More importantly, these studies will help to establish gut microbial enzymes as potential predictive markers for environmental toxicology.Through the discovery of the specific gut microbial enzymes involved in the metabolism and toxicology of TCS, our research could help to better evaluate its toxic potentials and clarify its individual effects in different populations. Based on our findings, upon TCS exposure, human subjects with a different abundance of Loop-1 or specific FMN-binding GUS enzymes could have varied colonic metabolism of TCS, resulting in inter-individual variations in biological responses to TCS exposure. Our previous study has revealed that there is significant inter-individual variability in the abundance of Loop-1 GUS orthologs in human fecal microbiotas38, we used a pharmacological approach and employed GUSi as a chemical probe to elucidate the molecular mechanisms of TCS37. We showed that GUSi effectively inhibited GUS-mediated TCS-G processing in vitro and ex vivo, with little effect on commensal microbes, growth of mammalian intestinal cells, or activity of mammalian GUS enzyme. These findings support that GUSi is highly selective toward the gut microbial GUS enzymes and therefore it is feasible to use GUSi to study the functional roles of gut microbial GUS enzymes in the gut toxicity of TCS. Next, we found that TCS exposure increased the severity of DSS-induced colitis in mice, however, the colitis-enhancing effects of TCS were abolished by co-administration of GUSi, confirming that the gut microbial GUS is required for the gut toxicity of TCS. Besides the DSS-induced colitis model, our previous study showed that TCS exposure exacerbated piroxicam-induced colitis in specific pathogen-free (SPF) Il-10−/− mice12. The conventionally housed Il-10−/− mice develop spontaneous colitis, and this spontaneous model can better model human IBD compared with the piroxicam-induced colitis model in SPF Il-10−/− mice43. It would be important to determine whether TCS exposure exacerbates colitis in the spontaneous Il-10−/− model and to elucidate the extent to which microbial GUS enzymes contribute to the biological effects of TCS in the spontaneous Il-10−/− model. Finally, we found that TCS (the product of GUS) exerts direct pro-inflammatory effects on cultured intestinal epithelial cells, while TCS-G (the substrate of GUS) was biologically inactive. Overall, these results support that GUS-mediated de-glucuronidation reaction leads to accumulation of free TCS in the colon and contributes to its pro-inflammatory effects in vivo. Since GUS-mediated de-glucuronidation is a common metabolic reaction involved in xenobiotic metabolism38, and has been suggested to be the fourth phase of drug and xenobiotic metabolism44, our findings may also apply to other environmental chemicals.Our results suggest that gut microbial GUS enzymes play critical roles in the metabolic reactivation and gut toxicity of TCS. Because genetic tools that specifically target gut microbial GUS enzymes are sparseIn summary, here we connect specific gut microbial enzymes with the metabolic reactivation of TCS in the colon and show that these enzymes drive adverse events caused by TCS. The data presented will help to better evaluate the individual effects of TCS in different populations. They also suggest that the safety of TCS and related compounds should be reconsidered given their potential for intestinal damage. Beyond TCS, it seems likely that gut microbial enzymes could contribute to the metabolism and toxicology of other chemicals, highlighting the critical importance of incorporating the microbiota in our understanding of environmental toxicology and mechanisms of disease.15, were conducted in accordance with the protocol approved by the Institutional Review Board of Stanford University. All subjects provided informed consent for their specimens to be used for studies of the microbiome; samples had been deidentified by the time this specific project was undertaken.The animal experiments were conducted in accordance with protocols approved by the Institutional Animal Care and Use Committee of the University of Massachusetts  and Massachusetts Host-Microbiome Center at the Brigham and Women’s Hospital . The analysis of the de-identified human urine and stool samples, which are from a previous human study 13C12-TCS, 99% purity) was obtained from Cambridge Isotope Laboratories .Triclosan  was purchased from Alfa Aesar . TCS-glucuronide  and TCS-sulfate (95% purity) were from Santa Cruz Biotechnology . Stable isotope-labeled triclosan (l-cystine (3 g/kg), sucrose (100 g/kg), dyetrose (132 g/kg), cornstarch (397.486 g/kg), cellulose (50 g/kg), mineral mix #210025 (35 g/kg), vitamin mix #310025 (10 g/kg), choline bitartrate(2.5 g/kg), corn oil (70 g/kg), and vitamin A palmitate (0.016 g/kg)12. The ingredients for the preparation of the diet, except corn oil, were purchased from Dyets Inc. . The commercial sample of corn oil  was purchased from a local market in Amherst, MA, and purified by a silicic acid-activated charcoal chromatography to remove any pre-existing lipid oxidation compounds, then the purified oil was fortified with 400 ppm tocopherols, flushed with N2, and stored at −80 °C until use.C57BL/6 male mice (age = 6 weeks) were purchased from Charles River and maintained in a specific pathogen-free animal facility. The mice were treated with a modified AIN-93G diet which contains 1, 10, or 80 ppm TCS for 4 weeks, then the mice were sacrificed to harvest tissues for LC-MS/MS analysis. The composition of the diet is casein (200 g/kg), 21 and us23. After 5 days, the mice were treated with a modified AIN-93G diet which contains 80 ppm TCS . After another 4 weeks, the mice were sacrificed, and their tissues were collected for LC-MS/MS analysis.C57BL/6 male mice (age = 6 weeks) were given drinking water with or without an antibiotic cocktail (a mixture of 1.0 g/L ampicillin and 0.5 g/L neomycin) throughout the entire experiment. This antibiotic composition was used in previous studies by othershttps://www.graphpad.com/scientific-software/prism/) with the parameters as follows: the baseline is set as Y = 0 and the peaks that are less than 10% of the distance from minimum to maximum Y are ignored.C57BL/6 male mice (age = 6 weeks) were supplied with drinking water with or without the antibiotic cocktail for 7 days, then the mice were treated with a one-time oral gavage of 8 mg/kg TCS which was dissolved in polyethylene glycol 400 (PEG-400). At t = 4, 8, 12, and 24 h post the oral gavage, the mice were sacrificed to harvest tissues for analysis. The Area under the curve (AUC)  until the end of the experiment. After another 3 weeks, the mice were stimulated with 2% DSS  in drinking water for 6 days to induce colitis. At end of the experiment, the mice were sacrificed for analysis.C57BL/6 male mice were orally gavaged with a specific GUS inhibitor (GUSi) UNC10201652 (dose = 1 mg/kg) or vehicle  every other day throughout the experiment, as described previouslyC57BL/6 male mice were orally gavaged with GUSi UNC10201652 (dose = 1 mg/kg) or vehicle  every other day for 24 days . At end of the experiment, the mouse feces were collected and subjected to sequencing, and the mice were sacrificed for biochemical analysis.13C12-TCS was used as the surrogate standard during the extraction. The extracts were re-dissolved in methanol with the amount that was proportional to sample weights or volumes, then centrifugated  before the LC-MS/MS analysis.Mouse tissues and human stool were placed in homogenizer tubes with beads and 1 mL methanol, then homogenized using a bead-disruptor . Samples were centrifuged at 10,000 rpm for 3 min. The supernatant was collected and then centrifuged again at 14,000 rpm for 5 min. In total, 500 μL of the supernatant was then collected, and vacuum centrifuged to dryness. For bacterial broth (50 μL) and human urine (100 μL), each sample was combined with 1 mL methanol and placed on ice. After 10 min on ice, samples were centrifuged at 14,000 rpm for 5 min. 500 μL of the supernatant was then collected and vacuum centrifuged to dryness. Stable isotope-labeled TCS, TCS-G, and TCS-sulfate in the samples were quantified using a Thermo Scientific Dionex Ultimate 3000 ultrahigh performance liquid chromatography (UHPLC) system coupled with a TSQ Quantiva Triple Quadrupole Mass Spectrometer. ACQUITY UPLC C18 column  was used for chromatographic separation. Data acquisition was performed by multiple reaction monitoring (MRM) in negative ionization mode. Details of the instrumental methods are provided in Supplementary Table n = 3 replicates). No significant differences were found among these three compounds. Therefore, 13C12-TCS was used for the signal correction of TCS, TCS-G, and TCS-sulfate, and it is a strategy for the absolute quantitation of analytes when internal standards are unavailable45. For the quantification of TCS, TCS-G, and TCS-sulfate by LC-MS/MS in the different experiments, blank samples from the control group without TCS exposure were used as the matrixes for calibration curve standards. During the instrumental analysis, the matrix calibration curve was performed at the beginning and at the end of every sample batch. All reported concentrations were determined based on a standard curve with 7–10 data points.The spike recoveries of the three target compounds in the matrixes of mouse colon digesta were determined. The recoveries  were 101.6 ± 8.9 and 95.6 ± 3.4 for TCS, 91.6 ± 5.4 and 87.1 ± 5.9 for TCS-G, 95.1 ± 1.4 and 96.9 ± 6.0 for TCS-sulfate, based on two spiked levels of 2 pmol/mg and 10 pmol/mg, respectively  under an atmosphere of 85% N2, 10% CO2, and 5% H2. In addition, the remaining supernatant (~0.6 mL) containing culturable bacteria was then mixed with sterile 50% glycerol (0.3 mL) and stored at −80 °C as stock for future experiments.Mouse fecal tissues and human stool samples were collected, dissolved in sterile PBS with 0.05% E. coli expression, synthesized, and ligated into a pLIC-His vector by BioBasic. Genes were transformed into BL21-G E. coli competent cells. A 100 mL culture was grown overnight at 37 °C in LB broth with ampicillin (100 µg/mL) and shaking at 215 RPM. The following day, 50 mL overnight culture was added to 1.5 L of LB broth with ampicillin and ~40 µL Antifoam 204. For FMN-binding enzymes, 500 µM FMN was added to the culture flask. The culture was incubated at 37 °C and 215 RPM until it reached an OD of 0.6. The culture was then induced with 1-thio-β-d-galactopyranoside (100 µM) and incubated overnight at 18 °C.All genes were codon-optimized for g for 20 min at 4 °C in a Sorvall (model RC-3B) swinging bucket centrifuge. Pellets were resuspended in 35 mL Buffer A  with DNAse, lysozyme, and one EDTA-free protease inhibitor tablet (Roche). The resuspension was sonicated twice using 1 s pulses for 1.5 min and the resultant suspension was pelleted at 17,000 × g for 45 min in a Beckman Coulter J2-HC centrifuge. The supernatant was syringe-filtered using a 0.22-µm filter.Cells were pelleted at 4,500 × The filtrate was flowed over a 5-mL nickel-nitrilotriacetic acid HP column  using the Aktaexpress FPLC (Amersham Bioscience) and washed with Buffer A. Protein was eluted using a linear gradient of Buffer A to Buffer B . Fractions containing the protein of interest were collected and applied to a HiLoad 16/60 Superdex 200 gel-filtration column (GE Life Sciences). Samples were eluted in S200 buffer . Fractions containing the protein of interest were analyzed via SDS-PAGE. Those with >95% purity were combined and concentrated to ~10 mg/mL using 50 kDa cutoff molecular weight centrifuge concentrators (EMD Millipore). Samples were snap-frozen using liquid nitrogen and stored at −80 °C.All mutants were created using site-directed mutagenesis. Primers were synthesized by IDT Technologies  and 0.5 g autoclaved garnet beads. The mixture was vortexed until homogenous and centrifuged at low speed (300 × g for 5 min at 4 °C). The supernatant was decanted. In all, 25 mL buffer was added to the pellet and the vortex and centrifugation steps repeated. The supernatants from these steps were then combined and centrifuged at low speed for two more cycles. The resultant supernatant was sonicated twice using 1 s pulses for 1.5 min and the lysate was centrifuged at 17,000 × g for 20 min in a Beckman Coulter J2-HC centrifuge. The decanted lysate was then washed with several exchanges of extraction buffer to remove metabolites and small molecules. Total protein concentration was quantitated using a Bradford assay. The fecal lysate was diluted to 1 mg/mL concentration and snap-frozen in small aliquots.Fecal extracts were prepared and proteomic analysis was performed exactly as previously describedg in 1.5 mL Amicon 10 K cutoff spin concentrators. After centrifugation, the total volume was brought to 1 mL using extraction buffer with 0.05% SDS. In total, 15 µL streptavidin sepharose beads (GE) were added and samples incubated at room temperature for 1 h. Beads were then washed 3 times with 300 µL extraction buffer with 0.1% SDS, three times with 300 µL extraction buffer alone, and three times with 300 µL 50 mM NH4HCO3. Samples were centrifuged at 400 × g for 2 min at 4 °C between washes, and the supernatant decanted. Beads were then resuspended in 100 µL 50 mM NH4HCO3 and stored at −20 °C.In all, 3.5 mg purified fecal extract was incubated with 10 µM biotin-activity-based probe complex in 500 µL extraction buffer with 1% dimethyl sulfoxide for 1 h at 37 °C. To quench, 125 µl 10% sodium dodecyl sulfate (SDS) was added and samples were heated to 95 °C for 5 min. Samples were cooled on ice and washed with extraction buffer containing 0.05% SDS three times by centrifugation for 5 min at 14,000 × 4HCO3 and reduced with dithiothreitol at 65 °C for 30 min. 2-chloroacetamide was then added and the mixture was incubated in the dark for 20 min at room temperature. Mixtures were centrifuged at 200 × g for 2 min at room temperature to pellet beads. The supernatant was decanted and trypsinized with 2.5 µg of trypsin overnight at 37 °C. Mixtures were then concentrated to 100 µL in a speedvac and desalted with C18 desalting columns (Thermo Scientific). Samples were reconcentrated using the speedvac and 100 µL LC-Optima MS grade water was added to solubilize samples. Samples were extracted with ethyl acetate and concentrated in the speedvac. The Pierce QFP assay (Thermo) was used to quantify and normalize peptides.The resultant bead mixture was added to 0.5% Rapigest (Waters) in 50 mM NHm/z were acquired using the Orbitrap at a resolution of 120,000 and 1e6 AGC target. MS2 spectra were collected with 1.6 m/z isolation width and were analyzed using the 3 s TopSpeed CHOPIN method by the Orbitrap or the linear ion trap depending on peak charge and intensity46. Orbitrap MS2 scans were acquired at 7500 resolution with a 5e4 AGC and 22 ms maximum injection time after HCD fragmentation with normalized energy of 30%. Rapid linear ion trap MS2 scans were obtained with a 4e3 AGC, 250 ms maximum injection time after CID 30 fragmentation. Precursor ions were chosen based on intensity thresholds (>1e3) from the full scan and on charge states with a 30-s dynamic exclusion window. Polysiloxane 371.10124 was used as the lock mass. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE47 partner repository with the dataset identifier PXD025887.Trypsinized peptides were separated using reverse-phase nano-high-performance liquid chromatography (nano-HPLC) coupled with a nanoACQUITY ultraperformance liquid chromatography (UPLC) system (Waters Corporation). Peptides were trapped and separated in a 2 cm column , and a 25-cm EASYspray analytical column  at 300 nL/min and 35 °C, respectively. A 60 min. gradient of 2% to 25% buffer B (0.1% formic acid in acetonitrile) was conducted on an Orbitrap Fusion Lumos mass spectrometer (Thermo Scientific) with ion source at 2.4 kV and ion transfer tube at 300 °C. MS scans from 350 to 2000 48 with MaxQuant version 1.6.2.349 to identify peptides and protein groups. The integrated reference catalog of the human gut microbiome database50 combined with the UniProtKB/Swiss-Prot human sequence database 51 with total 9,920,788 sequences was used as the database search. Search parameters were static carbamidomethyl cysteine modification, specific trypsin digestion with up to two missed cleavages, variable protein N-terminal acetylation and methionine oxidation, match between runs, and label-free quantification (LFQ) with a minimum ratio count of 2. A false discovery rate (FDR) of 1% was used for filtering protein identifications, and potential contaminants and decoys were removed.Data were processed using Metalab verson 1.1.1Escherichia coli , Clostridium perfringens , Streptococcus agalactiae , and Bacteroides fragilis . A sequence identity threshold 28% was required with at least one of the four representative proteins. In addition, all conserved residues had to be present and correctly aligned to the representative protein that passed the identity threshold. The conserved residues were: EcGUS E413, E504, N566, K568; CpGUS E412, E505, N567, K569; SaGUS E408, E501, N563, K565; and BfGUS E395, E476, N547, K549. GUS loop classes were determined by multiple sequence alignment with representative proteins, followed by examination of each sequence for specific loop criteria as defined by Pollet et al.27 and Pellock et al.52.GUS enzymes in each database were identified by pairwise alignment to the representative GUS proteins 53. Reactions were incubated at 37 °C for 30 min, and absorbance was monitored continuously at 340 nm using a BMG Labtech PHERAstar plate reader. The initial velocity of the reaction was fit using linear regression in MATLAB. Rates are the average of three biological replicates ±SEM.TCS-G was resuspended in 100% DMSO to a concentration of 10 mM. The assay reaction mixture consisted of 10 µL NAD+ , 5 µL uronate dehydrogenase , 5 µL various GUSs , and 30 µL TCS-G . Components were previously diluted in assay buffer  or . The pH of each reaction was determined using the optimal pH of the reaction as determined using pNPGg, and the supernatant was subjected to analysis by HPLC on an Agilent 1260 Infinity II system using an Agilent InfinityLab Poroshell 120 C18 column . The column temperature was set to 38 °C with a flow rate of 0.9 ml/min and injection volume of 40 μL. Conditions were set to flow 98% A (water with 0.1% formic acid) and 2% B (acetonitrile with 0.1% formic acid) for two minutes. A linear gradient was then set to flow to 98% B over 10 min and held for 4 min. Conditions were then ramped down to 98% A for 1 min and re-equilibrated at 98% A for 2 min. Analytes were detected using an Agilent DAD detector at a wavelength of 280 nm. Concentrations of TCS-G were determined using a standard curve of TCS-G (0-250 μM). Reaction curves were fit using linear regression, and the resultant initial velocities were plotted against substrate concentration to determine kcat/KM. Reported catalytic efficiencies are the average of three biological replicates ±SEM.Assay mixtures contained 10 μL GUS , 30 μL TCS-G , and 10 μL assay buffer  or . Control reactions replaced GUS with buffer. Reactions were quenched at five time points with 50 μL 25% trichloroacetic acid. Samples were centrifuged for 10 min at 16,000 × g, and the supernatant was analyzed using the method described for the catalytic efficiency assay. Inhibition was calculated by the equation below:min is the signal of the uninhibited reaction, AUCmax is the signal of the 100% inhibited reaction, and AUCinh is the signal of the reaction at a given concentration of inhibitor. Percent inhibition values were plotted against the log of inhibitor concentration, and GraphPad Prism 8.0 was used to determine IC50 values.Reaction mixtures containing 10 µL GUS , 10 µL TCS-G , 5 µL inhibitor (various concentrations), and 25 µL buffer  or  were incubated for 10 min and quenched with 50 µL 25% trichloroacetic acid. Samples were centrifuged 10 min at 16,000 × g in a tabletop centrifuge, and the supernatant was analyzed via the same HPLC method described for the catalytic efficiency assay. Reaction rates were determined by fitting progress curves using linear regression and are expressed as initial turnover rates (µM/s). Controls contained fecal extract that had been heat-killed at 95 °C for 5 min. Reported rates are the average of three biological replicates ±SEM.Reaction mixtures contained 5 µL fecal extract , 30 µL TCS-G , and 15 µL assay buffer . Reactions were quenched at five time points with 50 µL 25% trichloroacetic acid. Samples were centrifuged 20 min at 16,000 × g in a tabletop centrifuge, and the supernatant was analyzed via the same HPLC method described for the catalytic efficiency assay. Controls contained 5 µL buffer in place of GUSi. Inhibition was calculated using Eq. Reaction mixtures contained 5 µL fecal extract , 10 µL TCS-G , 5 µL GUSi , and 30 µL assay buffer . Reactions were quenched at 30 min with 50 µL 25% trichloroacetic acid. Samples were centrifuged 20 min at 16,000 × Roseburia hominis 3 GUS, crystals were produced in a condition containing 100 nL 12.5 mg/mL Rh3 GUS and 200 nL 0.2 M LiCl, 20% PEG 3350. For Faecalibacterium prausnizii L2-1 GUS, FpL2-1 GUS at 15 mg/mL was preincubated with UNC10201652 (GUSi) and PNPG in tenfold excess prior to addition to the crystalline solution. Crystals formed in a condition containing 200 nL GUS and 100 nL 0.2 M potassium thiocyanate (KSCN), 20%(w/v) PEG 3350.Crystals were produced using the sitting drop vapor diffusion method at 20 °C. Trays were set up using the Art Robbins Instruments Crystal Phoenix robot or an Oryx4 robot (Douglas Instruments) and Hampton Research three-well midi crystallization plates (Swissci). For R. hominis 2 structure (PDB 6MVH) was used as a search model. For FpL2-1 GUS, a FpL2-1 model produced using the Phyre2 server was used as a search model54. Maps and models output from molecular replacement were run through the Autobuild function of Phenix (version 1.17.1-3660)55. Structures were refined using phenix.refine, and Coot (version 0.9.4) was used for manual, visual inspection, and ligand fitting56. Final PDB coordinates were deposited to the RCSB Protein Data Bank under the codes 7KGZ (Rh3) and 7KGY (FpL2-1 with GUSi).Crystals were cryo-protected using the crystal solutions as described above with 20% glycerol. Diffraction data were collected at 100 K at APS beamline 23-ID-D. Data were processed using XDS and structures were solved using molecular replacement in Phenix. For Rh3 GUS, the http://www.schrodinger.com) induced fit docking pipeline. The Schrödinger Protein Preparation module was used to prepare proteins for docking by adding hydrogens, deleting water molecules more than 3 Å from the ligand, generating protonation states based on the protein’s ideal pH (as determined previously via in vitro assays), and creating metal and disulfide bonds. Default settings were used with the exception of the pH protonation states. The wizard was used to preprocess the structure, remove waters, optimize H-bonds, and minimize the structure.TCS-G docking into various GUS enzymes was carried out using the Schrödinger , glucuronic acid was added into the active site of each GUS using PyMOL by aligning each GUS to 6BJQ. The box center was then chosen as the glucuronic acid location with a box size of 30 Å. Core constraints were added to restrict docking of TCS-G to the existing glucuronic acid structure using the maximum common substructure. Glide redocking was performed at XP precision. Top docking poses were chosen based on the IFD Docking score and the Glide Score, as well as visual examination to confirm probable binding mode.Ligands were prepared using the Ligprep module. Ionization states were generated at pH 6.5 ± 0.5. Induced fit docking was used to dock TCS-G into the active sites of each GUS enzyme. Using a previously solved structure of 57. Enzyme (0.125 mg/mL) in CD buffer  was loaded into a 1-mm cuvette. The Chirascan Plus instrument (Applied Photophysis Limited) was used to acquire 1) scan spectra from 185 to 260 nM at 20 °C and 2) a melting profile at 193 nm from 20 to 94 °C. Spectra acquired with buffer alone were used to correct for background signal.The protein stabilities of Rh3 GUS and Fp2-L1 GUS and their mutants were determined using the circular dichroism method2. MC38 cells were seeded at 20% confluency and left to settle overnight. Cells were then treated with either 1 μM TCS, TCS-G, or vehicle (DMSO). After 48 h, cells were harvested for RT-qPCR analysis. Cell medium was collected for ELISA analysis using the CBA Mouse Inflammation Kit (BD Sciences) according to the manufacturer’s instructions, and data were acquired using a BD LSR Fortessa flow cytometer (BD Biosciences) and analyzed using FlowJo software (Treestar).MC38 intestinal epithelial cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and incubated at 37 °C under an atmosphere of 5% COg for 5 min at 4 °C. The concentrations of cytokines in plasma were determined using the CBA Mouse Inflammation Kit (BD Biosciences) as described above.Blood samples were harvested via cardiac puncture and collected in blood collection tubes (Covidien). The plasma fractions were prepared by centrifugation of the harvested blood at 3000 × Gapdh expression was used as an internal control.Total RNA of colon tissues and MC38 cells were isolated using Trizol reagent (Ambion) according to the manufacturer’s instruction. RNA was reverse transcribed into cDNA using the High Capacity cDNA Reverse Transcription kit (Applied Biosystem) according to the manufacturer’s instructions. In all, 20 μL PCR reactions were prepared using the Maxima SYBR Green Master Mix (Thermo Fisher Scientific), and qPCR was carried out using a DNA Engine Opticon System (Bio-Rad Laboratories). Mouse-specific primer sequences (Thermo Fisher Scientific) used to detect inflammatory biomarkers are listed in Supplementary Table TM dye  according to the manufacturer’s instructions to exclude dead cells. Gating and cell identification strategies are as follows: briefly, cell doublets and clumps were eliminated using FSC-A gating and debris was eliminated using FSC-A vs SSC-A. Dead cells were gated out using Zombie Violet™ dye. Flow cytometry data were acquired on a BD LSR FortessaTMcell analyzer  and analyzed using FlowJo software . Gating strategies used for the identification of major immune cell populations are shown in Supplementary Fig. Distal colon tissues were dissected, washed with cold PBS, and digested with Hank’s balanced salt solution  supplemented with 1 mM dithiothreitol (DTT) and 5 mM EDTA at 4 °C . The released cells were stained with FITC-conjugated anti-mouse CD45 , PerCP/Cy5.5-conjugated anti-mouse F4/80 , and PE/Cy7-conjugated anti-mouse Ly-6G/Ly-6C (GR-1)  with a 1:100 diluted solution. Cells were stained with Zombie VioletThe dissected colon tissues were fixed in 10% neutral buffered formalin (Thermo Fisher Scientific) for 48 h. After dehydration, the tissues were embedded in paraffin and sliced (5 mm) by Rotary Microtome (Thermo Fisher Scientific). The slices were dewaxed in serial xylene and rehydrated through ethanol solutions, stained with hematoxylin and eosin (Sigma-Aldrich), and images were obtained under 200× magnification . The histologic scores were evaluated by a blinded observer according to the following measures: crypt architecture, degree of inflammatory cell infiltration, muscle thickening, goblet cell depletion, and crypt abscess. The histologic damage score is the sum of each individual score.DNA was extracted from mouse fecal samples using QIAmp DNA Stool Mini Kit  following instructions from the manufacturer with an additional bead-beating step. The quantity of the extracted DNA was measured using a NanoDrop Spectrophotometer (Thermo Fisher Scientific), and the quality was verified using gel electrophoresis. The DNA was then subjected to further analysis.16S rRNA primers are in Supplementary Table DNA extracted from mouse fecal samples were subjected to qPCR analysis using a DNA Engine Opticon System . In all, 20 μL PCR reactions were made using the Maxima SYBR_green Master Mix (Thermo Fisher Scientific), and DNA was normalized to 5 ng/μL per reaction. The 16S rRNA gene were amplified with primers 341F (5’-CCTAYGGGRBGCASCAG-3’) and 806R (5’-GGACTACNNGGGTATCTAAT-3’). PCR products were detected on 2% agarose gels by electrophoresis and purified using the Qiagen Gel Extraction Kit . Sequencing libraries were generated using NEBNext Ultra DNA Library Pre Kit for Illumina, following the manufacturer’s recommendations and index codes were added. The library quality was assessed using the Qubit 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2100 system. The library was sequenced on an Illumina platform and 250 bp paired-end reads were generated.DNA quality was monitored on 1% agarose gels. The V3–V4 hypervariable regions of the bacteria 58 and Phytools package 0.7 v59 in R . Statistical tests were performed in R. Kruskal-Wallis rank-sum test was used to compare alpha diversity indexes among treatments. The beta diversity was calculated using Phytools 0.7 v. The weighted UniFrac distance method was used to create the matrix followed by PCoA to compare similarity among treatments. All plots were obtained using ggplot260.To analysis difference in abundance patterns among samples, beta diversity using weighted UniFrac distance followed by Principal Coordinate Analysis (PCoA) and non-metric multidimensional scaling (NMDS) analysis. The alpha diversity was considered as the richness of the samples, number of OTUs present per treatment. We calculated Simpson, Shannon, Chao1 index using QIIME2 version 2019.7.0Mouse (MC38) or human (Caco2 and HCT-116) intestinal cells were grown in DMEM medium fortified with 10% FBS (EMD Millipore Corporation). The cells were seeded in 96-well plates, then treated with GUSi or vehicle (0.2% v/v DMSO) for 24 h. Cell viability was determined using an MTT assay.t test; otherwise, significance was determined by Wilcoxon–Mann–Whitney test. The statistical comparison of three groups was analyzed using one-way ANOVA by Tukey’s multiple comparisons. The statistical analyses were performed using SAS (version 9.3) statistical software and GraphPad Prism (version 8.0 or 9.0). P < 0.05 was considered statistically significant.Data are mean ± SEM. For the comparison between two groups, Shapiro–Wilk test was used to verify the normality of data; when data were normally distributed, statistical significance was determined using two-sided Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


ATP6V1B2 gene, a known causal allele for dominant deafness-onychodystrophy (DDOD), was identified in the mother and son with DDOD. However, a novel heterozygous variant  in TJP2, a known causal gene for hearing-loss, was also detected in the patients. In family 2, the same mutation  of ATP6V1B2 was detected from the father and daughter with DDOD. Furthermore, a novel heterozygous variant  in the KIF11 gene was identified from the spouse with sensorineural hearing-loss and epilepsy. Notably, genotype-phenotype analysis of KIF11-associated disorders revealed that the p.M245V and two reported hearing-loss-associated variants (p.S235C and p.H244Y) are all mapped to a single β-sheet (Ser235∼M245) in the kinesin motor domain. Together, this is the first demonstration that ATP6V1B2-caused DDOD is an autosomal dominant genetic disease, compared to previous cases with de novo mutation. Our findings expand the variant spectrum of hearing-loss-associated genes and provide new insights on understanding of hearing-loss candidate genes ATP6V1B2, TJP2, and KIF11.A cohort of 542 individuals in 166 families with congenital hearing loss was recruited for whole-exome sequencing analysis. Here, we report the identification of three variants in five affected individuals in two unrelated families. In family 1, a nonsense mutation  in the  Approximately 30% of affected individuals with hearing loss are considered to be syndromic . In addition, one family member in family 2 was affected with congenital hearing loss and epilepsy.de novo heterozygous variant  in the ATP6V1B2 gene (MIM: 606939) (The cause of DDOD syndrome (MIM: 220500) was first identified, from three unrelated cases, to be a  606939) . One add 606939) . The var 606939) . More re 606939) .ATP6V1B2 gene thus far. All other seven variants are heterozygous missense alleles, linked to various conditions such as neurodevelopmental disorder, Cutis laxa, Zimmermann-Laband syndrome, epilepsy, intellectual disability, and mild gingival and nail abnormalities (HGMD). However, it remains undetermined whether this LoF variant  is also responsible for patients with family history segregating as an autosomal dominant (AD) form since the DDOD syndrome was first recognized in 1961  in gnomAD database  from five affected individuals in two families. Detailed genotype-phenotype analysis is applied for further characterizations of hearing loss-associated variants and potential pathogenesis.In the present study, we show clinical findings of four individuals in two unrelated families affected with DDOD in AD form, and one individual affected with congenital sensorineural hearing loss and epilepsy in the family 2. By whole-exome sequencing (WES) analysis, we report the identification and characterization of three variants in three disease-associated genes , followed by high-throughput sequencing by HiSeq2000 sequencer (Illumina Inc.). After strict quality control, the clean reads were aligned to the human reference genome (hg19) for SNP calling and deleterious variants were predicted by multiple commonly used programs, such as MutationTaster, Polyphen-2, and SIFT, as described in previous study  . DetectTJP2 using primers (forward: 5′-AGGAAAGGCCAAGTTCCAGA-3′ and reverse: 5′-GCATCCTCCCGCACTAATCC-3′). The RT-PCR products were examined by 1.5% agarose gel electrophoresis and Sanger sequencing.To analyze a potential splicing variant, total RNAs were isolated from peripheral blood lymphocyte cells using TRIzol and reverse-transcribed using M-MLV reverse transcriptase . RT-PCR was performed to analyze the c.1590T>G variant-containing region of In family 1, the 6-year-old boy  was firs+3) after an uneventful pregnancy. There was no history of ototoxic drug use during pregnancy and no asphyxia and no history of injury at birth. Her growth measurements in terms of body weight, height, and head circumference were within normal ranges. She was not good at active expression and showed poor memory. Physical examination revealed her bilateral nail anomalies in fingers and toes  from four affected individuals with hearing loss and onychodystrophy, i.e., the affected mother and son in family 1 and the affected father and daughter in family 2. This variant was previously reported as a de novo variant in multiple cases with deafness and onychodystrophy  in the ystrophy  as well ystrophy . In the Based on ACMG/AMP classification , this vaTJP2 gene (GenBank: NM_004817), a known candidate gene for intrahepatic cholestasis and sensorineural hearing loss , thereby increasing a donor site at g.108836. To confirm the predicted splicing site, RT-PCR analysis was conducted to examine the c.1590T>G-containing region using the proband’s peripheral blood lymphocyte cells and normal control sample. The 406-bp RT-PCR product as a normal control was clearly detected by electrophoresis and further confirmed by Sanger sequencing  . This variant is predicted to be disease-causing and is not recorded in gnomAD or ChES database . At least 100 different mutations of the gene have been reported in patients with autosomal dominant microcephaly with or without chorioretinopathy, lymphedema, or mental retardation (MIM: 152950 and HGMD). Among them, two missense mutations (p.S235C and p.H244Y) in KIF11 were previously identified in two unrelated patients with severe hearing loss in addition to chorioretinopathy and microcephaly , a multi-subunit enzyme that mediates acidification of intracellular organelles in endomembrane organelles, such as vacuoles, lysosomes, and endosomes , indicating its role in development of these tissues. To date, seven different variants in the ATP6V1B2 gene are curated in HGMD. Only the LoF variant  at the very C-terminal region is repeatedly linked to hearing loss and onychodystrophy . Furthermore, Atp6v1b2 c.1516C>T knockin mice displayed obvious cognitive defects and impaired hippocampal CA1 structure. However, hearing loss or abnormal cochlear morphology was not detected in the c.1516C>T knockin mice  have been identified to cause hearing loss, while recessive mutations in the same gene are associated with DOORS syndrome (HGMD). In addiTJP2 gene encodes a protein of 1,190 amino acids, which is a member of the membrane-associated guanylate kinase homologous family  is a plus-end directed homotetrameric microtubule motor that functions during mitosis in microtubule crosslinking, antiparallel microtubule sliding, and bipolar spindle formation. In HGMA, 100 different variants in KIF11 are linked to several conditions, such as microcephaly, lymphoedema, chorioretinopathy, and hearing loss. We found that the two reported hearing loss-associated variants  and current variant  in KIF11 are clustered in the second beta-sheet in the catalytic domain of Kinesin motor. Presumably, this region might be involved in protein-protein interaction in CNS tissues including cochlear cells. Further studies are thus needed to clarify how KIF11 is involved in the hearing process.ATP6V1B2, TJP2, and KIF11 on hearing functions.Taken together, we report here on five patients of two families with variants in three hearing loss associated genes. Our findings expand variant spectrums of hearing loss candidate genes, and shed new insights of pathogenetic effects of