Cellular and molecular dynamics in the lungs of neonatal and juvenile mice in response to E. coli

Bacterial pneumonia in neonates can cause significant morbidity and mortality when compared to other childhood age groups. To understand the immune mechanisms that underlie these age-related differences, we employed a mouse model of Escherichia coli pneumonia to determine the dynamic cellular and molecular differences in immune responsiveness between neonates (PND 3-5) and juveniles (PND 12-18), at 24, 48, and 72 hr. Cytokine gene expression from whole lung extracts was also quantified at these time points, using quantitative RT-PCR. E. coli challenge resulted in rapid and significant increases in neutrophils, monocytes, and γδT cells, along with significant decreases in dendritic cells and alveolar macrophages in the lungs of both neonates and juveniles. E. coli-challenged juvenile lung had significant increases in interstitial macrophages and recruited monocytes that were not observed in neonatal lungs. Expression of IFNγ-responsive genes was positively correlated with the levels and dynamics of MHCII-expressing innate cells in neonatal and juvenile lungs. Several facets of immune responsiveness in the wild-type neonates were recapitulated in juvenile MHCII-/- juveniles. Employing a pre-clinical model of E. coli pneumonia, we identified significant differences in the early cellular and molecular dynamics in the lungs that likely contribute to the elevated susceptibility of neonates to bacterial pneumonia and could represent targets for intervention to improve respiratory outcomes and survivability of neonates.

Identification of Neuronal Lineages in the Drosophila Peripheral Nervous System with a "Digital" Multi-spectral Lineage Tracing System

Elucidating cell lineages provides crucial understanding of development. Recently developed sequencing-based techniques enhance the scale of lineage tracing but eliminate the spatial information offered by conventional approaches. Multi-spectral labeling techniques, such as Brainbow, have the potential to identify lineage-related cells in situ. Here, we report nuclear Bitbow (nBitbow), a “digital” version of Brainbow that greatly expands the color diversity for scoring cells, and a suite of statistical methods for quantifying the lineage relationship of any two cells. Applying these tools to the Drosophila peripheral nervous system (PNS), we determined lineage relationship between all neuronal pairs. This study demonstrates nBitbow as an efficient tool for in situ lineage mapping, and the complete lineage relationship among larval PNS neurons opens new possibilities for studying how neurons gain specific features and circuit connectivity.

Veling et al. report a multi-color labeling system and statistical methods for mapping cell lineages. They identify the lineage relationship of all neurons in the peripheral nervous system of Drosophila larvae and show the utility of this technique in mapping neurons in the CNS.