Hearing loss is the biggest risk factor for tinnitus, and hearing-loss-related pathological changes in the auditory pathway have been hypothesized as the mechanism underlying tinnitus. However, due to the comorbidity of tinnitus and hearing loss, it has been difficult to differentiate between neural correlates of tinnitus and consequences of hearing loss. In this study, we dissociated tinnitus and hearing loss in FVB mice, which exhibit robust resistance to tinnitus following monaural noise-induced hearing loss. Furthermore, knock-down of glutamate decarboxylase 65 (GAD65) expression in auditory cortex (AI) by RNA interference gave rise to tinnitus in normal-hearing FVB mice. We found that tinnitus was significantly correlated with downregulation of GAD65 in the AI. By contrast, cortical map distortions, which have been hypothesized as a mechanism underlying tinnitus, were correlated with hearing loss but not tinnitus. Our findings suggest new strategies for the rehabilitation of tinnitus and other phantom sensation, such as phantom pain.

Methodologies employing LC-MS/MS have been increasingly used for characterization and identification of residual host cell proteins (HCPs) in biopharmaceutical products to ensure their consistent product quality and safety for patients. To improve the sensitivity and reliability for HCP detection, we developed a high pH-low pH two-dimensional reversed phase LC-MS/MS approach in conjunction with offline fraction concatenation. Proof-of -concept was established using a model in which seven proteins spanning a size range of 29−78 kDa are spiked into a purified antibody product to simulate the presence of low-level HCPs. By incorporating a tandem column configuration and a shallow gradient through the seconddimension, all seven proteins were consistently identified at 10 ppm with 100% success rate following LC-MS/MS analysis of six concatenated fractions across multiple analysts, column lots and injection loads. Using the more complex Universal Proteomic Standard 1 (UPS-1) as an HCP model, positive identification was consistently achieved for 19 of the 22 proteins in 8−12 ppm range (10 ppm ±20%). For the first time, we demonstrate an effective LC-MS/MS strategy that not only has high sensitivity but also high reliability for HCP detection. The method performance has high impact on pharmaceutical company practices in using advanced LC-MS/MS technology to ensure product quality and patient safety.

Residual host cell proteins (HCPs) present in biotherapeutics can pose potential safety risks for patients or affect product stability, thus prompting a critical need to monitor HCPs in drug substance or product to ensure product safety and quality. Current approaches for robust HCP identification at or above 10 ppm levels require either concatenated peptide fractionation or enrichment via antibody depletion, which challenges the direct quantitation of HCPs. This paper describes a simple, fast sample preparation method without the need for sample fractionation or enrichment; instead, we utilize trypsin-friendly sodium deoxycholate (SDC) as an advantageous denaturant that can be effectively removed following acidification at the end of sample digestion. This new approach enables the end-to-end one-dimensional liquid chromatography–tandem mass spectrometry (1D LC–MS/MS) workflow (i.e., from sample preparation to HCP identification) to be completed in 7–8 h while demonstrating the ability to consistently identify HCPs across a broad molecular weight range at 10 ppm or above.

Residual host cell proteins (HCPs) in the drug product can affect product quality, stability, and/or safety. In particular, highly active hydrolytic enzymes at sub-ppm levels can negatively impact the shelf life of drug products but are challenging to identify by liquid chromatography−mass spectrometry/mass spectrometry (LC−MS/MS) due to their high dynamic range between HCPs and biotherapeutic proteins. We employed new strategies to address the challenge: (1) native digest at a high protein concentration; (2) sodium deoxycholate added during the reduction step to minimize the inadvertent omission of HCPs observed with native digestion; and (3) solid phase extraction with 50% MeCN elution prior to LC−MS/MS analysis to ensure effective mAb removal. A 50 cm long nanoflow charged surface hybrid column was also packed to allow for higher sample load for increased sensitivity. Our workflow has increased the sensitivity for HCP identification by 10-to 100-fold over previous reports and showed the robustness as low as 0.1 ppm for identifying HCPs (34.5 to 66.2 kDa MW). The method capability was further confirmed by consistently identifying >85% of 48 UPS-1 proteins (0.10 to 1.34 ppm, 6.3 to 82.9 kDa MW) in a monoclonal antibody (mAb) and the largest number (746) of mouse proteins from NIST mAb reported to date by a single analysis. Our work has filled a significant gap in HCP analysis for detecting and demonstrating HCP clearance, in particular, extremely low-level hydrolases in drug process development.

Host cell proteins (HCPs) are process-related impurities derived from the manufacturing of recombinant biotherapeutics. Residual HCP in drug products, ranging from 1 to 100 ppm (ng HCP/mg product) or even below sub-ppm level, may affect product quality, stability, efficacy, or safety. Therefore, removal of HCPs to appropriate levels is critical for the bioprocess development of biotherapeutics. Liquid chromatography-mass spectrometry (LC-MS) analysis has become an important tool to identify, quantify, and monitor the clearance of individual HCPs. This review covers the technical advancement of sample preparation strategies, new LC-MS-based techniques, and data analysis approaches to robustly and sensitively measure HCPs while overcoming the high dynamic range analytical challenges. We also discuss our strategy for LC-MS-based HCP workflows to enable fast support of process development throughout the product life cycle, and provide insights into developing specific analytical strategies leveraging LC-MS tools to control HCPs in process and mitigate their potential risks to drug quality, stability, and patient safety.