Developing high-quality mouse monoclonal antibodies for neuroscience research - approaches, perspectives and opportunities.

High-quality antibodies (Abs) are critical to neuroscience research, as they remain the primary affinity proteomics reagent used to label and capture endogenously expressed protein targets in the nervous system. As in other fields, neuroscientists are frequently confronted with inaccurate and irreproducible Ab-based results and/or reporting. The UC Davis/NIH NeuroMab Facility was created with the mission of addressing the unmet need for high-quality Abs in neuroscience research by applying a unique approach to generate and validate mouse monoclonal antibodies (mAbs) optimized for use against mammalian brain (i.e., NeuroMabs). Here we describe our methodology of multi-step mAb screening focused on identifying mAbs exhibiting efficacy and specificity in labeling mammalian brain samples. We provide examples from NeuroMab screens, and from the subsequent specialized validation of those selected as NeuroMabs. We highlight the particular challenges and considerations of determining specificity for brain immunolabeling. We also describe why our emphasis on extensive validation of large numbers of candidates by immunoblotting and immunohistochemistry against brain samples is essential for identifying those that exhibit efficacy and specificity in those applications to become NeuroMabs. We describe the special attention given to candidates with less common non-IgG1 IgG subclasses that can facilitate simultaneous multiplex labeling with subclass-specific secondary antibodies. We detail our recent use of recombinant cloning of NeuroMabs as a method to archive all NeuroMabs, to unambiguously define NeuroMabs at the DNA sequence level, and to re-engineer IgG1 NeuroMabs to less common IgG subclasses to facilitate their use in multiplex labeling. Finally, we provide suggestions to facilitate Ab development and use, as to design, execution and interpretation of Ab-based neuroscience experiments. Reproducibility in neuroscience research will improve with enhanced Ab validation, unambiguous identification of Abs used in published experiments, and end user proficiency in Ab-based assays.