a) Gene Expression profiling of Brn3AP RGCs and their brain targets by RNASeq (Sajgo et al, PNAS 2017) We have established an immunoaffinity purification strategy based on our Brn3CKOAP alleles. Using this strategy, we identified (i) genes enriched in RGCs compared to the retina, (ii) genes enriched in Brn3aAP vs Brn3bAP RGCs (presumed to convey the specific features distinguishing RGC cell types), and (iii) genes up- or downregulated by loss of Brn3a or Brn3b (potentially mediating the developmental programs that the Brn3s are thought to directly or indirectly regulate in RGCs). About 3000 transcripts are enriched in RGCs when compared to the retina, and about 900 transcripts are found to be regulated by Brn3b and/or Brn3a. We find that Brn3b loss affects RGCs significantly more than Brn3a loss. Moreover, the transcripts selectively expressed in RGCs, or affected by Brn3b loss are distinct for the different stages of development. A secondary situ hybridization validation screen was conducted on P3 eye sections, and find that more than half of the 233 targets are actually RGC specific. A similar ratio was found for 265 genes that were confirmed by queries of the Allen Institute In Situ Hybridization atlas of E15 mouse embryos. We complemented these RGC profiles with RNAseq analysis of retinorecipient brain nuclei at P3, an age when RGC axons have reached the target and synapse formation is extremely active, and report our findings in the same study. Amongst the many differentially expressed genes in our screen, we have focused on two classes of molecules: (i) transcription factors, (ii) adhesion molecules/signaling receptors. We find that, whereas about 60 % of all annotated transcription associated genes are expressed in RGCs, 322 genes are enriched in RGCs compared to retinas, and 95 are under Brn3 control. These transcription factors, some of which had already been described, generate a wide combinatorial code demonstrating specificity for distinct RGC subpopulations. Interestingly a much smaller number of adhesion molecules and guidance receptors are enriched in our RGC populations (about 200 transcripts). To address the potential functions of molecules identified in our screen, we overexpressed a small subset (10 genes) in HEK293 cells, and find that several of them have the capacity to induce membrane processes reminiscent of neurites. It could therefore be that cell-autonomous mechanisms participate in determining neuronal arbor formation, that is then further refined and positioned by transmembrane receptors/adhesion molecules mediating cell-cell and/or cell-matrix interactions. This novel way of thinking about neuronal arbor formation will drive our research moving forward. Using a Cre dependent, AAV-based overexpression approach to determine the subcellular localization of some of our targets in vivo in Brn3bCre RGCs, we find distributions consistent with roles in vesicle trafficking within neurites or at synapses. Finally, out of a set of 79 genes proposed to be associated with Glaucoma in human genetics studies, only 12 appeared to be enriched in RGCs, potentially revealing molecular pathways associated with susceptibility to RGC damage. Thus, our RGC gene expression profiling project promises to be an extremely useful resource for the visual system field and in general for the neuroscience community. c) Behavior Tests for visual function in mice (Kretschmer 2017, Wang 2017) During animal locomotion or position adjustments, the visual system uses image stabilization reflexes to compensate for global shifts in the visual scene. These reflexes elicit compensatory head movements (optomotor response, OMR) in unrestrained animals or compensatory eye movements (optokinetic response, OKR) in head-fixed or unrestrained animals exposed to globally rotating striped patterns. We have used our newly developed software and apparatus to accurately quantitate mouse head movements during OMR, eye movements during OKR, and determine eye movements in freely behaving mice. We provided the first direct comparison of OMR and OKR gains (head or eye velocity/stimulus velocity) and found that the two reflexes have comparable dependencies on stimulus luminance, contrast, spatial frequency, and velocity. OMR and OKR are similarly affected in genetically modified mice with defects in RGCs compared with wild-type, suggesting they are driven by the same sensory input (RGC type). OKR eye movements have much higher gains than the OMR head movements, but neither can fully compensate global visual shifts. However, combined eye and head movements can be detected in unrestrained mice performing OMR, suggesting they can cooperate to achieve image stabilization, as previously described for other species. Our methodology has been successfully applied by us and multiple groups within the NEI, for the analysis of visual abilities in mice with genetic defects, and models for disease state and therapeutic intervention. The software and hardware we developed is now available as a commercial system, and we are implementing this system that will become part of the NEI Visual Function Core. c) Multichannel electrophysiology for the analysis of Retinal Ganglion Cell Function In this past year we have continued our development of a machine learning algorithm for the unsupervised detection and classification of RGC recordings from ex vivo retinas stimulated with a variety of visual stimuli. We had published a short report on a skeleton version of the algorithm, and have another manuscript for the full version under review. We have applied this approach to the analysis of response properties of intrinsically photosensitive RGCs that carried mutant versions of the photopigment Melanopsin in a collaborative project lead by Drs. P. Robinson and S. Hattar. This research, for which we additionally contributed AAV targeting vectors and behavior analysis apparatus and expertise, demonstrated that phosphorylation of the c terminal tail of Melanopsin plays a key role in the shut-off of the photopigment, and regulates the length of both ipRGC light reponses and Pupillary Light Reflex recovery times. d) RGC-32 involvement in Th17 responses during experimentally induced autoimmune reactions. While in Dr. Horea Russ lab at UMMS, I had cloned and characterized RGC-32, a vertebrate specific gene upregulated in proliferating tissues, regenerative context, and tumors. Injured tissues react by inflammatory responses that attempt to clear the noxious influence, but at the same time repair the damage. Somatic cells can be affected in a variety of ways by these signals. One type of adaptive response is the induction of stress response genes, assumption of less mature tissue phenotypes, or even reactivation of cell cycle. Dr. Rus and I conducted a screen for genes induced by complement system challenge in primary oligodendrocyte cell cultures. We further characterized one of the identified genes, RGC-32, and showed that it interacts with cell cycle regulators, and can positively or negatively affect cell cycle activation in different contexts. More recently, I have collaborated with Dr. Rus to generate a knock-out for RGC-32, and members of his group discovered that RGC-32 plays a role in T lymphocytes, in particular in their differentiation towards the Th17 fate. This in turn could affect the progression of experimentally induced auto-immune reactions (experimental autoimmune Encephalomyelitis, a murine model for multiple sclerosis). Thus RGC-32 could be a potential regulator of tissue repair or regeneration, especially in the context of inflammatory processes.
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