Age-related brain atrophy is not a homogenous process: Different functional brain networks associate differentially with aging and blood factors.

Aging is characterized by a progressive loss of brain volume at an estimated rate of 5% per decade after age 40. While these morphometric changes, especially those affecting gray matter and atrophy of the temporal lobe, are predictors of cognitive performance, the strong association with aging obscures the potential parallel, but more specific role, of individual subject physiology. Here, we studied a cohort of 554 human subjects who were monitored using structural MRI scans and blood immune protein concentrations. Using machine learning, we derived a cytokine clock (CyClo), which predicted age with good accuracy (Mean Absolute Error = 6 y) based on the expression of a subset of immune proteins. These proteins included, among others, Placenta Growth Factor (PLGF) and Vascular Endothelial Growth Factor (VEGF), both involved in angiogenesis, the chemoattractant vascular cell adhesion molecule 1 (VCAM-1), the canonical inflammatory proteins interleukin-6 (IL-6) and tumor necrosis factor alpha (TNFα), the chemoattractant IP-10 (CXCL10), and eotaxin-1 (CCL11), previously involved in brain disorders. Age, sex, and the CyClo were independently associated with different functionally defined cortical networks in the brain. While age was mostly correlated with changes in the somatomotor system, sex was associated with variability in the frontoparietal, ventral attention, and visual networks. Significant canonical correlation was observed for the CyClo and the default mode, limbic, and dorsal attention networks, indicating that immune circulating proteins preferentially affect brain processes such as focused attention, emotion, memory, response to social stress, internal evaluation, and access to consciousness. Thus, we identified immune biomarkers of brain aging which could be potential therapeutic targets for the prevention of age-related cognitive decline.

"Integrative genomic analysis of the bioprospection of regulators and accessory enzymes associated with cellulose degradation in a filamentous fungus (Trichoderma harzianum)".

BACKGROUND: Unveiling fungal genome structure and function reveals the potential biotechnological use of fungi. Trichoderma harzianum is a powerful CAZyme-producing fungus. We studied the genomic regions in T. harzianum IOC3844 containing CAZyme genes, transcription factors and transporters. RESULTS: We used bioinformatics tools to mine the T. harzianum genome for potential genomics, transcriptomics, and exoproteomics data and coexpression networks. The DNA was sequenced by PacBio SMRT technology for multiomics data analysis and integration. In total, 1676 genes were annotated in the genomic regions analyzed; 222 were identified as CAZymes in T. harzianum IOC3844. When comparing transcriptome data under cellulose or glucose conditions, 114 genes were differentially expressed in cellulose, with 51 being CAZymes. CLR2, a transcription factor physically and phylogenetically conserved in Trichoderma spp., was differentially expressed under cellulose conditions. The genes induced/repressed under cellulose conditions included those important for plant biomass degradation, including CIP2 of the CE15 family and a copper-dependent LPMO of the AA9 family. CONCLUSIONS: Our results provide new insights into the relationship between genomic organization and hydrolytic enzyme expression and regulation in T. harzianum IOC3844. Our results can improve plant biomass degradation, which is fundamental for developing more efficient strains and/or enzymatic cocktails to produce hydrolytic enzymes.

Extremophiles as a Model of a Natural Ecosystem: Transcriptional Coordination of Genes Reveals Distinct Selective Responses of Plants Under Climate Change Scenarios.

The goal of this research was to generate networks of co-expressed genes to explore the genomic responses of Rhizophora mangle L. populations to contrasting environments and to use gene network analysis to investigate their capacity for adaptation in the face of historical and future perturbations and climatic changes. RNA sequencing data were generated for R. mangle samples collected under field conditions from contrasting climate zones in the equatorial and subtropical regions of Brazil. A gene co-expression network was constructed using Pearson's correlation coefficient, showing correlations among 78,364 transcriptionally coordinated genes. Each region exhibited two distinct network profiles; genes correlated with the oxidative stress response showed higher relative expression levels in subtropical samples than in equatorial samples, whereas genes correlated with the hyperosmotic salinity response, heat response and UV response had higher expression levels in the equatorial samples than in the subtropical samples. In total, 992 clusters had enriched ontology terms, which suggests that R. mangle is under higher stress in the equatorial region than in the subtropical region. Increased heat may thus pose a substantial risk to species diversity at the center of its distribution range in the Americas. This study, which was performed using trees in natural field conditions, allowed us to associate the specific responses of genes previously described in controlled environments with their responses to the local habitat where the species occurs. The study reveals the effects of contrasting environments on gene expression in R. mangle, shedding light on the different abiotic variables that may contribute to the genetic divergence previously described for the species through the use of simple sequence repeats (SSRs). These effects may result from two fundamental processes in evolution, namely, phenotypic plasticity and natural selection.