Microanalytical Mass Spectrometry with Super-Resolution Microscopy Reveals a Proteome Transition During Development of the Brain's Circadian Pacemaker.

During brain development, neuronal proteomes are regulated in part by changes in spontaneous and sensory-driven activity in immature neural circuits. A longstanding model for studying activity-dependent circuit refinement is the developing mouse visual system where the formation of axonal projections from the eyes to the brain is influenced by spontaneous retinal activity prior to the onset of vision and by visual experience after eye-opening. The precise proteomic changes in retinorecipient targets that occur during this developmental transition are unknown. Here, we developed a microanalytical proteomics pipeline using capillary electrophoresis (CE) electrospray ionization (ESI) mass spectrometry (MS) in the discovery setting to quantify developmental changes in the chief circadian pacemaker, the suprachiasmatic nucleus (SCN), before and after the onset of photoreceptor-dependent visual function. Nesting CE-ESI with trapped ion mobility spectrometry time-of-flight (TOF) mass spectrometry (TimsTOF PRO) doubled the number of identified and quantified proteins compared to the TOF-only control on the same analytical platform. From 10 ng of peptide input, corresponding to <∼0.5% of the total local tissue proteome, technical triplicate analyses identified 1894 proteins and quantified 1066 proteins, including many with important canonical functions in axon guidance, synapse function, glial cell maturation, and extracellular matrix refinement. Label-free quantification revealed differential regulation for 166 proteins over development, with enrichment of axon guidance-associated proteins prior to eye-opening and synapse-associated protein enrichment after eye-opening. Super-resolution imaging of select proteins using STochastic Optical Reconstruction Microscopy (STORM) corroborated the MS results and showed that increased presynaptic protein abundance pre/post eye-opening in the SCN reflects a developmental increase in synapse number, but not presynaptic size or extrasynaptic protein expression. This work marks the first development and systematic application of TimsTOF PRO for CE-ESI-based microproteomics and the first integration of microanalytical CE-ESI TimsTOF PRO with volumetric super-resolution STORM imaging to expand the repertoire of technologies supporting analytical neuroscience.

Capturing discrete latent structures: choose LDs over PCs.

High-dimensional biological data collection across heterogeneous groups of samples has become increasingly common, creating high demand for dimensionality reduction techniques that capture underlying structure of the data. Discovering low-dimensional embeddings that describe the separation of any underlying discrete latent structure in data is an important motivation for applying these techniques since these latent classes can represent important sources of unwanted variability, such as batch effects, or interesting sources of signal such as unknown cell types. The features that define this discrete latent structure are often hard to identify in high-dimensional data. Principal component analysis (PCA) is one of the most widely used methods as an unsupervised step for dimensionality reduction. This reduction technique finds linear transformations of the data which explain total variance. When the goal is detecting discrete structure, PCA is applied with the assumption that classes will be separated in directions of maximum variance. However, PCA will fail to accurately find discrete latent structure if this assumption does not hold. Visualization techniques, such as t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP), attempt to mitigate these problems with PCA by creating a low-dimensional space where similar objects are modeled by nearby points in the low-dimensional embedding and dissimilar objects are modeled by distant points with high probability. However, since t-SNE and UMAP are computationally expensive, often a PCA reduction is done before applying them which makes it sensitive to PCAs downfalls. Also, tSNE is limited to only two or three dimensions as a visualization tool, which may not be adequate for retaining discriminatory information. The linear transformations of PCA are preferable to non-linear transformations provided by methods like t-SNE and UMAP for interpretable feature weights. Here, we propose iterative discriminant analysis (iDA), a dimensionality reduction technique designed to mitigate these limitations. iDA produces an embedding that carries discriminatory information which optimally separates latent clusters using linear transformations that permit post hoc analysis to determine features that define these latent structures.

Early Leukocyte Responses in Ex-Vivo Models of Healing and Non-Healing Human Leishmania (Viannia) panamensis Infections.

Early host-pathogen interactions drive the host response and shape the outcome of natural infections caused by intracellular microorganisms. These interactions involve a number of immune and non-immune cells and tissues, along with an assortment of host and pathogen-derived molecules. Our current knowledge has been predominantly derived from research on the relationships between the pathogens and the invaded host cell(s), limiting our understanding of how microbes elicit and modulate immunological responses at the organismal level. In this study, we explored the early host determinants of healing and non-healing responses in human cutaneous leishmaniasis (CL) caused by Leishmania (Viannia) panamensis. We performed a comparative transcriptomic profiling of peripheral blood mononuclear cells from healthy donors (PBMCs, n=3) exposed to promastigotes isolated from patients with chronic (CHR, n=3) or self-healing (SH, n=3) CL, and compared these to human macrophage responses. Transcriptomes of L. V. panamensis-infected PBMCs showed enrichment of functional gene categories derived from innate as well as adaptive immune cells signatures, demonstrating that Leishmania modulates adaptive immune cell functions as early as after 24h post interaction with PBMCs from previously unexposed healthy individuals. Among differentially expressed PBMC genes, four broad categories were commonly modulated by SH and CHR strains: cell cycle/proliferation/differentiation, metabolism of macromolecules, immune signaling and vesicle trafficking/transport; the first two were predominantly downregulated, and the latter upregulated in SH and CHR as compared to uninfected samples. Type I IFN signaling genes were uniquely up-regulated in PBMCs infected with CHR strains, while genes involved in the immunological synapse were uniquely downregulated in SH infections. Similarly, pro-inflammatory response genes were upregulated in isolated macrophages infected with CHR strains. Our data demonstrate that early responses during Leishmania infection extend beyond innate cell and/or phagocytic host cell functions, opening new frontiers in our understanding of the triggers and drivers of human CL.

Genome-wide scans of myopia in Pennsylvania Amish families reveal significant linkage to 12q15, 8q21.3 and 5p15.33.

Myopia is one of the most common ocular disorders in the world, yet the genetic etiology of the disease remains poorly understood. Specialized founder populations, such as the Pennsylvania Amish, provide the opportunity to utilize exclusive genomic architecture, like unique haplotypes, to better understand the genetic causes of myopia. We perform genetic linkage analysis on Pennsylvania Amish families that have a strong familial history of myopia to map any potential causal variants and genes for the disease. 293 individuals from 25 extended families were genotyped on the Illumina ExomePlus array and merged with previous microsatellite data. We coded myopia affection as a binary phenotype; myopia was defined as having a mean spherical equivalent (MSE) of less than or equal to - 1 D (diopters). Two-point and multipoint parametric linkage analyses were performed under an autosomal dominant model. When allowing for locus heterogeneity, we identified two novel genome-wide significantly linked variants at 12q15 (heterogeneity LOD, HLOD = 3.77) in PTPRB and at 8q21.3 (HLOD = 3.35) in CNGB3. We identified further three genome-wide significant variants within a single family. These three variants were located in exons of SLC6A18 at 5p15.33 (LODs ranged from 3.51 to 3.37). Multipoint analysis confirmed the significant signal at 5p15.33 with six genome-wide significant variants (LODs ranged from 3.6 to 3.3). Further suggestive evidence of linkage was observed in several other regions of the genome. All three novel linked regions contain strong candidate genes, especially CNGB3 on 8q21.3, which has been shown to affect photoreceptors and cause complete color blindness. Whole genome sequencing on these regions is planned to conclusively elucidate the causal variants.