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. 2017 Dec;20(12):1787-1795.
doi: 10.1038/s41593-017-0011-2. Epub 2017 Nov 13.

A Multiregional Proteomic Survey of the Postnatal Human Brain

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Free PMC article

A Multiregional Proteomic Survey of the Postnatal Human Brain

Becky C Carlyle et al. Nat Neurosci. .
Free PMC article

Abstract

Detailed observations of transcriptional, translational and post-translational events in the human brain are essential to improving our understanding of its development, function and vulnerability to disease. Here, we exploited label-free quantitative tandem mass-spectrometry to create an in-depth proteomic survey of regions of the postnatal human brain, ranging in age from early infancy to adulthood. Integration of protein data with existing matched whole-transcriptome sequencing (RNA-seq) from the BrainSpan project revealed varied patterns of protein-RNA relationships, with generally increased magnitudes of protein abundance differences between brain regions compared to RNA. Many of the differences amplified in protein data were reflective of cytoarchitectural and functional variation between brain regions. Comparing structurally similar cortical regions revealed significant differences in the abundances of receptor-associated and resident plasma membrane proteins that were not readily observed in the RNA expression data.

Figures

Figure 1
Figure 1. Resource overview and peptide library illustrate broad coverage of both the adult human brain and of expressed genes
A) Individual brain regions (dorsolateral frontal cortex (DFC), primary visual cortex (V1C), hippocampus (HIP), amygdala (AMY), mediodorsal nucleus of the thalamus (MD), striatum (STR) and cerebellum (CBC)) and ages used in this study; all samples pooled for fractionation were derived from adult brains. B) On average 7,945 proteins were detected in each brain region, with 8,980 proteins detected in at least one region and 6,529 proteins detected in all 7 regions. C) Over two-thirds (6,529 of 8,980) of the proteins detected were consistently identified in all 7 brain regions. Counts of proteins (bars, top) detected in each combination of regions (black dots, below) are shown for all combinations indicating enrichment or depletion in a single region. Region-specific dropouts are far more frequent than region-specific detections; with the exception of 148 CBC-specific proteins, the largest groups are single region depletions that, together, total 717 proteins. D) Using the whole-brain distribution of gene expression (all genes; grey) defined by RNA-seq, peptides (green) correspond to the majority of higher abundance mRNAs (RNA coding genes, black). E) Sliding a lower threshold from the left to right of the histogram for each brain region, a robust pattern of increasing peptide coverage is observed with increasing RNA expression.
Figure 2
Figure 2. Differentially expressed proteins across human brain regions and post-natal development
A) The majority of significantly differentially expressed genes were between brain regions, rather than over developmental periods (Two-way ANOVA, significant DEX defined as Bonferroni corrected p value < 0.05. Adjusted p values of n=5141 genes across 7 regions (6 DoF, Fig 1A) 6 timepoints (1 DoF, Fig 1A) in Table S5). B) Clustering all samples subjected to MS/MS using proteins significantly differentially expressed between brain regions revealed expected bulk differences between brain regions. Samples are defined by the same colour scheme used to depict regions and developmental period in Figs 2C and 2D (see also fully labelled zoomable version in Fig S5). Cerebellum (CBC) and Striatum (STR) are clear outliers (lower left), as they are by RNA-seq, and the remaining samples cluster well by region with the exception of occasional outlying samples derived from the youngest subject, HSB139 (dark blue). C) Clustering all proteins significantly differentially expressed between regions reveals consistent patterns of expression that favour region-specific enrichment or region-specific depletion in abundance (all clusters Fig S6, dendrogram Fig S7). Variable y axes are used to best visualize the inter-regional differences within clusters. The center line indicates the median, limits indicate the interquartile range (IQR), and the whiskers either 1.5* the IQR or the min/max value if it falls within 1.5* the IQR. Each individual data point is shown as a dot. D) Clustering all proteins significantly differentially expressed over developmental period reveals proteins enriched shortly after birth (period 8) and proteins more gently increasing or decreasing in abundance over developmental period. Boxplots are defined the same as Fig 2C.
Figure 3
Figure 3. Comparison of the proteome and transcriptome of the human brain
A) Principal component analysis of RNA and protein data show a clear separation of the cerebellum from the other six regions in the first two PCs in both datasets. Clustering of samples by region is tighter in these components in the protein data compared to RNA. B) The cumulative frequency of Pearson correlations between each gene’s RNA and protein shows a modest median correlation of 0.32 (n=5039). However, when considering only genes significantly differentially expressed at the protein level between brain regions (n=1776), these correlations are significantly increased (median 0.5; K-S pVal < 10−16).
Figure 4
Figure 4. Abundance and enrichment of the 20 most enriched proteins and RNAs in each brain region
Scatter plots of log10 protein and RNA abundance vs log2 fold enrichment (in each region over the median of all other regions) for the top 20 genes enriched in each region. Variable y axes are used to reflect the variation in abundance of the most enriched proteins between regions. Points representing genes enriched in a given region in both RNA and protein are slightly enlarged and highlighted with a black outline. Generally, the abundance and fold-enrichments of these gene products is highest in sub-cortical regions (CBC, STR) compared to neocortical regions (V1C, DFC).
Figure 5
Figure 5. Ontological enrichments of inter-regional protein and RNA changes
A) RNA and protein abundance differences between pairs of brain regions for genes significantly differentially expressed at the protein level. Genes are coloured based on their agreement or disagreement between the RNA and protein measurements; genes for which the protein variability between regions is <2-fold of that reported at the RNA-level were considered consistent (green and grey points). Purple coloured genes are those with consistent direction but variable magnitude of change (≥2-fold) between the regions at the protein and RNA level, while red genes disagree in the direction of change between RNA and protein. Blue genes vary between regions according to protein but not RNA, orange genes vary by RNA but not protein. Inset pie charts illustrate the relative dominance of genes in the green ‘agree’ and blue ‘protein-only’ categories. B) Distribution of the number of gene products annotated in each of the colour categories defined in A) across all unique pairs of brain regions. The center line indicates the median, limits indicate the IQR, and the whiskers either 1.5* the IQR or the min/max value if it falls within 1.5* the IQR. C) Scatter plots for the DFC/STR comparison show the position of gene products contained within ontological terms of interest. RNA processing genes are enriched by ‘protein-only’. Regulation of GTPase activity shows an enrichment in the ‘agree’ category. Synaptic transmission genes are found in both ‘RNA-only’ and ‘partial-agree’. Genes involved in translation are almost entirely in the ‘no change’ category.
Figure 6
Figure 6. Comparison of the human and mouse brain proteome
A) The cumulative frequency of Pearson correlations for each 1:1 ortholog protein between human and mouse shows a median correlation of 0.3 (n=4052). When considering only genes significantly differentially expressed at the protein level between human brain regions (n=1517), these correlations are significantly increased (median 0.65; K-S pVal < 10−16). B) Human and mouse protein abundance differences between two example brain regions, PFC and STR, shows a lower overall degree of consistency between organisms compared to between human RNA and protein (see Fig 5A). As before, genes are coloured based on their agreement or disagreement between human and mouse; genes for which the human variability between regions was <2-fold of that reported for mouse were considered consistent (green and grey points). Purple coloured genes are those with consistent direction, but variable magnitude of change between the regions of human and mouse, while red genes disagree even in the direction of change. Blue and orange genes vary between regions according to human but not mouse and vice-versa. C) Distribution of the number of genes annotated in each of the colour categories defined in B) across all unique pairs of brain regions. The center line indicates the median, limits indicate the IQR, and the whiskers either 1.5* the IQR or the min/max value if it falls within 1.5* the IQR. D) Genes with poor correlation between human and mouse regions tend to have more sequence differences in their coding sequence compared to those genes with greater correlation (red vs. green (p = 0.04) or grey (p-value = 8.97E-06)). Box plots are defined as in 6C, with the individual points representing outliers that fall 1.5* below the IQR.

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