Proteomics of spatially identified tissues in whole organs

Spatial molecular profiling of complex tissues is essential to investigate cellular function in physiological and pathological states. However, methods for molecular analysis of biological specimens imaged in 3D as a whole are lacking. Here, we present DISCO-MS, a technology combining whole-organ imaging, deep learning-based image analysis, and ultra-high sensitivity mass spectrometry. DISCO-MS yielded qualitative and quantitative proteomics data indistinguishable from uncleared samples in both rodent and human tissues. Using DISCO-MS, we investigated microglia activation locally along axonal tracts after brain injury and revealed known and novel biomarkers. Furthermore, we identified initial individual amyloid-beta plaques in the brains of a young familial Alzheimer's disease mouse model, characterized the core proteome of these aggregates, and highlighted their compositional heterogeneity. Thus, DISCO-MS enables quantitative, unbiased proteome analysis of target tissues following unbiased imaging of entire organs, providing new diagnostic and therapeutic opportunities for complex diseases, including neurodegeneration.

Editorial for the Special Issue on Micro/Nanofluidic Devices for Single Cell Analysis, Volume II

The functional, genetic, or compositional heterogeneity of healthy and diseased tissues promotes significant challenges to drug discovery and development [...]

Quantitative Mining of Compositional Heterogeneity in Cryo-EM Datasets of Ribosome Assembly Intermediates

Macromolecular complexes are dynamic entities whose function is often intertwined with their many structural configurations. Single particle cryo-electron microscopy (cryo-EM) offers a unique opportunity to characterize macromolecular structural heterogeneity by virtue of its ability to place distinct populations into different groups through computational classification. However, current workflows are limited, and there is a dearth of tools for surveying the heterogeneity landscape, quantitatively analyzing heterogeneous particle populations after classification, deciding how many unique classes are represented by the data, and accurately cross-comparing reconstructions. Here, we develop a workflow that contains discovery and analysis modules to quantitatively mine cryo-EM data for a set of structures with maximal diversity. This workflow was applied to a dataset of E. coli 50S ribosome assembly intermediates, which is characterized by significant structural heterogeneity. We identified new branch points in the assembly process and characterized the interactions of an assembly factor with immature intermediates. While the tools described here were developed for ribosome assembly, they should be broadly applicable to the analysis of other heterogeneous cryo-EM datasets.

A site-and-branch-heterogeneous model on an expanded dataset favor mitochondria as sister to known Alphaproteobacteria

Determining the phylogenetic origin of mitochondria is key to understanding the ancestral mitochondrial symbiosis and its role in eukaryogenesis. However, the precise evolutionary relationship between mitochondria and their closest bacterial relatives remains hotly debated. The reasons include pervasive phylogenetic artefacts, as well as limited protein and taxon sampling. Here, we developed a new model of protein evolution that accommodates both across-site and across-branch compositional heterogeneity. We applied this site-and-branch-heterogeneous model (MAM60 + GFmix) to a considerably expanded dataset that comprises 108 mitochondrial proteins of alphaproteobacterial origin, and novel metagenome-assembled genomes from microbial mats, microbialites, and sediments. The MAM60 + GFmix model fits the data much better and agrees with analyses of compositionally homogenized datasets with conventional site-heterogenous models. The consilience of evidence thus suggests that mitochondria is sister to the Alphaproteobacteria to the exclusion of MarineProteo1 and Magnetococcia. We also show that the ancestral presence of a crista-developing MICOS complex (a Mitofilin domain-containing Mic60) supports this relationship.

Characterization of Three Complete Mitogenomes of Flatidae (Hemiptera: Fulgoroidea) and Compositional Heterogeneity Analysis in the Planthoppers’ Mitochondrial Phylogenomics

Although sequences of mitogenomes have been widely used for investigating phylogenetic relationship, population genetics, and biogeography in many members of Fulgoroidea, only one complete mitogenome of a member of Flatidae has been sequenced. Here, the complete mitogenomes of Cerynia lineola, Cromna sinensis, and Zecheuna tonkinensis are sequenced. The gene arrangements of the three new mitogenomes are consistent with ancestral insect mitogenomes. The strategy of using mitogenomes in phylogenetics remains in dispute due to the heterogeneity in base composition and the possible variation in evolutionary rates. In this study, we found compositional heterogeneity and variable evolutionary rates among planthopper mitogenomes. Phylogenetic analysis based on site-homogeneous models showed that the families (Delphacidae and Derbidae) with high values of Ka/Ks and A + T content tended to fall together at a basal position on the trees. Using a site-heterogeneous mixture CAT + GTR model implemented in PhyloBayes yielded almost the same topology. Our results recovered the monophyly of Fulgoroidea. In this study, we apply the heterogeneous mixture model to the planthoppers' phylogenetic analysis for the first time. Our study is based on a large sample and provides a methodological reference for future phylogenetic studies of Fulgoroidea.