There is evidence that certain club cells (CCs) in the murine airways associated with neuroepithelial bodies (NEBs) and terminal bronchioles are resistant to the xenobiotic naphthalene (Nap) and repopulate the airways after Nap injury. The identity and significance of these progenitors (variant CCs, v-CCs) have remained elusive. A recent screen for CC markers identified rare Uroplakin3a (Upk3a)-expressing cells (U-CCs) with a v-CC-like distribution. Here, we employ lineage analysis in the uninjured and chemically injured lungs to investigate the role of U-CCs as epithelial progenitors. U-CCs proliferate and generate CCs and ciliated cells in uninjured airways long-term and, like v-CCs, after Nap. U-CCs have a higher propensity to generate ciliated cells than non-U-CCs. Although U-CCs do not contribute to alveolar maintenance long-term, they generate alveolar type I and type II cells after Bleomycin (Bleo)-induced alveolar injury. Finally, we report that Upk3a cells exist in the NEB microenvironment of the human lung and are aberrantly expanded in conditions associated with neuroendocrine hyperplasias.

The missing human proteome comprises predicted protein-coding genes with no credible protein level evidence detected so far and constitutes ~18% of the human protein coding genes (neXtProt release 19/9/2014). The missing proteins may be of pharmacological interest as many of these are membrane receptors, thus requiring comprehensive characterization. In the present study, we explored various computational parameters, crucial during protein searches from tandem mass spectrometry (MS) data, for their impact on missing protein identification. Variables taken into consideration are differences in search database composition, shared peptides, semitryptic searches, post-translational modifications (PTMs), and transcriptome guided proteogenomic searches. We used a multialgorithmic approach for protein detection from publicly available mass spectra from recent studies covering diverse human tissues and cell types. Using the aforementioned approaches, we successfully detected 24 missing proteins (22-PE2, 1-PE4, and 1-PE5). Maximum of these identifications could be attributed to differences in reference proteome databases, exemplifying use of a single standard database for human protein detection from MS data. Our results suggest that search strategies with modified parameters can be rewarding alternatives for extensive profiling of missing proteins. We conclude that using complementary spectral data searches incorporating different parameters like PTMs, against a comprehensive and compact search database, might lead to discoveries of the proteins attributed so far as the missing human proteome.