A Human Brain Map of Mitochondrial Respiratory Capacity and Diversity.

Mitochondrial oxidative phosphorylation (OxPhos) powers brain activity1,2, and mitochondrial defects are linked to neurodegenerative and neuropsychiatric disorders3,4, underscoring the need to define the brain's molecular energetic landscape5-10. To bridge the cognitive neuroscience and cell biology scale gap, we developed a physical voxelization approach to partition a frozen human coronal hemisphere section into 703 voxels comparable to neuroimaging resolution (3×3×3 mm). In each cortical and subcortical brain voxel, we profiled mitochondrial phenotypes including OxPhos enzyme activities, mitochondrial DNA and volume density, and mitochondria-specific respiratory capacity. We show that the human brain contains a diversity of mitochondrial phenotypes driven by both topology and cell types. Compared to white matter, grey matter contains >50% more mitochondria. We show that the more abundant grey matter mitochondria also are biochemically optimized for energy transformation, particularly among recently evolved cortical brain regions. Scaling these data to the whole brain, we created a backward linear regression model integrating several neuroimaging modalities11, thereby generating a brain-wide map of mitochondrial distribution and specialization that predicts mitochondrial characteristics in an independent brain region of the same donor brain. This new approach and the resulting MitoBrainMap of mitochondrial phenotypes provide a foundation for exploring the molecular energetic landscape that enables normal brain functions, relating it to neuroimaging data, and defining the subcellular basis for regionalized brain processes relevant to neuropsychiatric and neurodegenerative disorders.

A Human Brain Map of Mitochondrial Respiratory Capacity and Diversity.

Mitochondrial oxidative phosphorylation (OxPhos) powers brain activity1,2, and mitochondrial defects are linked to neurodegenerative and neuropsychiatric disorders3,4, underscoring the need to define the brain's molecular energetic landscape5-10. To bridge the cognitive neuroscience and cell biology scale gap, we developed a physical voxelization approach to partition a frozen human coronal hemisphere section into 703 voxels comparable to neuroimaging resolution (3×3×3 mm). In each cortical and subcortical brain voxel, we profiled mitochondrial phenotypes including OxPhos enzyme activities, mitochondrial DNA and volume density, and mitochondria-specific respiratory capacity. We show that the human brain contains a diversity of mitochondrial phenotypes driven by both topology and cell types. Compared to white matter, grey matter contains >50% more mitochondria. We show that the more abundant grey matter mitochondria also are biochemically optimized for energy transformation, particularly among recently evolved cortical brain regions. Scaling these data to the whole brain, we created a backward linear regression model integrating several neuroimaging modalities11, thereby generating a brain-wide map of mitochondrial distribution and specialization that predicts mitochondrial characteristics in an independent brain region of the same donor brain. This new approach and the resulting MitoBrainMap of mitochondrial phenotypes provide a foundation for exploring the molecular energetic landscape that enables normal brain functions, relating it to neuroimaging data, and defining the subcellular basis for regionalized brain processes relevant to neuropsychiatric and neurodegenerative disorders.

Mitochondria in epithelial ovarian carcinoma exhibit abnormal phenotypes and blunted associations with biobehavioral factors.

Malignant tumor cells exhibit mitochondrial alterations and are also influenced by biobehavioral processes, but the intersection of biobehavioral factors and mitochondria in malignant tumors remains unexplored. Here we examined multiple biochemical and molecular markers of mitochondrial content and function in benign tissue and in high-grade epithelial ovarian carcinoma (EOC) in parallel with exploratory analyses of biobehavioral factors. First, analysis of a publicly-available database (n = 1435) showed that gene expression of specific mitochondrial proteins in EOC is associated with survival. Quantifying multiple biochemical and molecular markers of mitochondrial content and function in tissue from 51 patients with benign ovarian masses and 128 patients with high-grade EOC revealed that compared to benign tissue, EOCs exhibit 3.3-8.4-fold higher mitochondrial content and respiratory chain enzymatic activities (P < 0.001) but similar mitochondrial DNA (mtDNA) levels (- 3.1%), documenting abnormal mitochondrial phenotypes in EOC. Mitochondrial respiratory chain activity was also associated with interleukin-6 (IL-6) levels in ascites. In benign tissue, negative biobehavioral factors were inversely correlated with mitochondrial content and respiratory chain activities, whereas positive biobehavioral factors tended to be positively correlated with mitochondrial measures, although effect sizes were small to medium (r = - 0.43 to 0.47). In contrast, serous EOCs showed less pronounced biobehavioral-mitochondrial correlations. These results document abnormal mitochondrial functional phenotypes in EOC and warrant further research on the link between biobehavioral factors and mitochondria in cancer.

Maternal perinatal calorie restriction temporally regulates the hepatic autophagy and redox status in male rat.

Intrauterine growth restriction (IUGR) leads to adult obesity, cardiovascular disease, and non-alcoholic fatty liver disease/steatohepatitis. Animal models have shown that combined intrauterine and early postnatal calorie restriction (IPCR) ameliorates these sequelae in adult life. The mechanism by which IPCR protects against adult onset disease is not understood. Autophagy, a lysosomal degradative process, recycles cellular constituents and eliminates damaged organelles, proteins, and oxidants. In this study, we hypothesized that IPCR could regulate autophagy in the liver of male rat offspring. At birth (d1) of male IUGR rat offspring and on day 21 (p21) of life, IPCR male rat offspring had a profound decrease in hepatic autophagy in all three stages of development: initiation, elongation, and maturation. However, upon receiving a normal diet ad-lib throughout adulthood, aged IPCR rats (day 450 of life (p450)), had increased hepatic autophagy, in direct contrast to what was seen in early life. The decreased autophagy at d21 led to the accumulation of ubiquitinated proteins and lipid oxidative products, whereas the increased autophagy in late life had the opposite effect. Oxidized lipids were unchanged at d1 by IUGR treatment indicating that decreased autophagy precedes oxidative stress in early life. When cellular signaling pathways regulating autophagy were examined, the 5' adenosine monophosphate-activated protein kinase pathway (AMPK), and not endoplasmic stress pathways, was found to be altered, suggesting that autophagy is regulated through AMPK signaling pathway in IPCR rats. Taken together, this study reveals that the perinatal nutritional status establishes a nutritionally sensitive memory that enhances hepatic autophagy in late life, a process that perhaps acts as a protective mechanism to limited nutrition.

High definition infrared spectroscopic imaging for lymph node histopathology.

Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.