Cellular metabolism is tightly regulated by many signaling pathways and processes, including lysine acetylation of proteins. While lysine acetylation of metabolic enzymes can directly influence enzyme activity, there is growing evidence that lysine acetylation can also impact protein localization. As the Saccharomyces cerevisiae lysine acetyltransferase complex NuA4 has been implicated in a variety of metabolic processes, we have explored whether NuA4 controls the localization and/or protein levels of metabolic proteins. We performed a high-throughput microscopy screen of over 360 GFP-tagged metabolic proteins and identified 23 proteins whose localization and/or abundance changed upon deletion of the NuA4 scaffolding subunit, EAF1. Within this, three proteins were required for glycogen synthesis and 14 proteins were associated with the mitochondria. We determined that in eaf1Δ cells the transcription of glycogen biosynthesis genes is upregulated resulting in increased proteins and glycogen production. Further, in the absence of EAF1, mitochondria are highly fused, increasing in volume approximately 3-fold, and are chaotically distributed but remain functional. Both the increased glycogen synthesis and mitochondrial elongation in eaf1Δ cells are dependent on Bcy1, the yeast regulatory subunit of PKA. Surprisingly, in the absence of EAF1, Bcy1 localization changes from being nuclear to cytoplasmic and PKA activity is altered. We found that NuA4-dependent localization of Bcy1 is dependent on a lysine residue at position 313 of Bcy1. However, the glycogen accumulation and mitochondrial elongation phenotypes of eaf1Δ, while dependent on Bcy1, were not fully dependent on Bcy1-K313 acetylation state and subcellular localization of Bcy1. As NuA4 is highly conserved with the human Tip60 complex, our work may inform human disease biology, revealing new avenues to investigate the role of Tip60 in metabolic diseases.

The relationship between several intriguing perinatal phenomena, namely, modal, optimal, and relative birthweight and gestational age, remains poorly understood, especially the mechanism by which relative birthweight and gestational age resolve the paradox of intersecting perinatal mortality curves.

Birthweight and gestational age distributions and birthweight- and gestational age-specific perinatal death rates of low- and high-risk cohorts in the United States, 2004-2015, were estimated using births-based and extended fetuses-at-risk formulations. The relationships between these births-based distributions and rates, and the first derivatives of fetuses-at-risk birth and perinatal death rates were examined in order to assess how the rate of change in fetuses-at-risk rates affects gestational age distributions and births-based perinatal death rate patterns.

Modal gestational age typically exceeded optimal gestational age because both were influenced by the peak in the first derivative of the birth rate, hs-based models of perinatal death.The vast net of fibres within and underneath the cortex is optimised to support the convergence of different levels of brain organisation. Here, we propose a novel coordinate system of the human cortex based on an advanced model of its connectivity. Our approach is inspired by seminal, but so far largely neglected models of cortico-cortical wiring established by postmortem anatomical studies and capitalises on cutting-edge in vivo neuroimaging and machine learning. The new model expands the currently prevailing diffusion magnetic resonance imaging (MRI) tractography approach by incorporation of additional features of cortical microstructure and cortico-cortical proximity. Studying several datasets and different parcellation schemes, we could show that our coordinate system robustly recapitulates established sensory-limbic and anterior-posterior dimensions of brain organisation. A series of validation experiments showed that the new wiring space reflects cortical microcircuit features (including pyramidal neuron depth and glial expression) and allowed for competitive simulations of functional connectivity and dynamics based on resting-state functional magnetic resonance imaging (rs-fMRI) and human intracranial electroencephalography (EEG) coherence. Our results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation. Our evaluations demonstrate the cortical wiring space bridges across scales of neural organisation and can be easily translated to single individuals.There is increased awareness of the possibility of developmental memories resulting from evolutionary learning. Genetic regulatory and neural networks can be modelled by analogous formalism raising the important question of productive analogies in principles, processes and performance. We investigate the formation and persistence of various developmental memories of past phenotypes asking how the number of remembered past phenotypes scales with network size, to what extent memories stored form by Hebbian-like rules, and how robust these developmental “devo-engrams” are against networks perturbations (graceful degradation). The analogy between neural and genetic regulatory networks is not superficial in that it allows knowledge transfer between fields that used to be developed separately from each other. Known examples of spectacular phenotypic radiations could partly be accounted for in such terms.The evolution of cross-feeding among individuals of the same species can help generate genetic and phenotypic diversity even in completely homogeneous environments. this website Cross-feeding Escherichia coli strains, where one strain feeds on a carbon source excreted by another strain, rapidly emerge during experimental evolution in a chemically minimal environment containing glucose as the sole carbon source. Genome-scale metabolic modeling predicts that cross-feeding of 58 carbon sources can emerge in the same environment, but only cross-feeding of acetate and glycerol has been experimentally observed. Here we use metabolic modeling to ask whether acetate and glycerol cross-feeding are especially likely to evolve, perhaps because they require less metabolic change, and thus perhaps also less genetic change than other cross-feeding interactions. However, this is not the case. The minimally required metabolic changes required for acetate and glycerol cross feeding affect dozens of chemical reactions, multiple biochemical pathways, as well as multiple operons or regulons.