SUMMARY In social interactions among mammals, individuals are recognized by olfactory cues, but identifying the key signals among thousands of compounds remains a major challenge. To address this need, we developed a new technique, Component-Activity Matching (CAM), to select candidate ligands that “explain” patterns of bioactivity across diverse complex mixtures. Using mouse urine from eight different sexes and strains, we identified 23 components to explain firing rates in seven of eight functional classes of vomeronasal sensory neurons. Focusing on a class of neurons selective for females, we identified a novel family of vomeronasal ligands, steroid carboxylic acids. These ligands accounted for much of the neuronal activity of urine from some female strains, were necessary for normal levels of male investigatory behavior of female scents and sufficed to trigger mounting behavior. CAM represents the first step towards an exhaustive characterization of the molecular cues for natural behavior in a mammalian olfactory system.

Polysorbate (PS) is a widely used polymeric excipient in biotherapeutic formulations to stabilize and protect protein drugs. Commercial PS is a highly heterogeneous mixture of structurally related components. PS composition can impact the stabilizer performance of PS in formulated protein drugs. Characterization of PS heterogeneity is, however, analytically challenging. In this work, a high-throughput screening protocol is presented for the profiling of the PS-80 polysorbate form using high resolution mass spectrometry (HRMS) coupled with a rapid hydrogen/deuterium (H/D) exchange in deuterated methanol. The protocol takes advantage of accurate mass measurements from HRMS analysis and utilizes H/D exchange-induced mass shifts that are characteristic to structures (particularly the number of terminal hydroxyl groups) of PS molecules to definitively identify species. In particular, mass shifts caused by deuterium uptake were used (1) to confirm molecular identities assigned by accurate mass measurements (which adds an extra level of identification confidence) and (2) to differentiate isomers that have an identical mass (thus, undistinguishable by high mass accuracy), but differ in the number of terminal hydroxyls. These data were input to an automated searching algorithm against a molecular mass database covering over 17000 potential PS-80 molecular species. The identified species were then visualized with Kendrick Mass Defect plots. The analysis protocol identified and profiled over 180 species from PS-80 samples in a high-throughput fashion without requiring chromatographic separation to reduce complexity of mixtures or tandem mass spectrometric analysis to conduct structural elucidation.

Abstract. Conjugated estrogens purified from pregnant mares urine has been used as estrogen hormone replacement therapy since 1942. Previously, methods were proposed to identify and quantify the components of this complex mixture but ultimately were withdrawn due to incomplete characterization of the product and difficulties in transferring the method between laboratories. The aim of the current study is to develop a LC method that can reliably detect multiple steroidal components in conjugated estrogen tablets and measure their relative amount. The method developed was optimized for UHPLC columns, and the elution profile was analyzed using high-resolution mass spectrometry. A total of 60 steroidal components were identified using their exact m/z, product ion spectra of known, and predicted conjugated estrogen structures. These components were consistently present in 23 lots of Premarin tablets spanning two production years. The ten conjugated estrogens identified in the USP monograph and other additional estrogens reported elsewhere are among the 60 steroidal components reported here. The LC-MS method was tested in different laboratories using multiple samples, and the obtained results were reproducible among laboratories.