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The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes and 8658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical reaction networks to random reaction networks reveals that the observed biological scaling is not a product of chemistry alone but instead emerges due to the particular structure of selected reactions commonly participating in living processes. We show that the topology of biochemical networks for the three domains of life is quantitatively distinguishable, with >80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Together, our results point to a deeper level of organization in biochemical networks than what has been understood so far.

The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes and 8658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical reaction networks to random reaction networks reveals that the observed biological scaling is not a product of chemistry alone but instead emerges due to the particular structure of selected reactions commonly participating in living processes. We show that the topology of biochemical networks for the three domains of life is quantitatively distinguishable, with >80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Together, our results point to a deeper level of organization in biochemical networks than what has been understood so far.

In December 2019, the Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus SARS-CoV-2, emerged in Wuhan, Hubei province, China1 and soon spread across the world. In this ongoing pandemic, public health concerns and the urgent need for effective therapeutic measures require a deep understanding of its epidemiology, transmissibility and pathogenesis. Here we analyzed the clinical, molecular and immunological data from 326 confirmed cases of COVID-19 in Shanghai. Genomic sequences of SARS-CoV-2 assembled from 112 quality samples together with sequences in the Global Initiative on Sharing All Influenza Data (GISAID) showed a stable evolution and suggested two major lineages with differential exposure history during the early phase of the outbreak in Wuhan. Nevertheless, they exhibited similar virulence and clinical outcomes. Lymphocytopenia, especially the reduced CD4+ and CD8+ T cell counts upon admission, was predictive of disease progression. High levels of IL-6 and IL-8 during treatment were observed in patients with severe or critical disease and correlated with decreased lymphocyte count. The determinants of disease severity seemed to stem mostly from host factors such as age, lymphocytopenia, and its associated cytokine storm, whereas viral genetic variation did not significantly affect the outcomes.

Recent major surveys show that reductions in genomic complexity - including the loss of key genes - have successfully shaped the evolution of life throughout history.

"It is now possible to trace the migratory paths of anatomically modern humans using genetic data. Early research pointed to a sub-Saharan African origin for modern humans by around 200,000-150,000 years ago1, and analyses of autosomal markers2 and Y DNA haplogroups3, 4 suggest the earliest structuring of the human population occurred approximately 140,000 years ago5,6,7,8. Initial efforts to characterize the movement of early humans in relation to ancestry grouped populations according to five geographical regions: Sub-Saharan Africa, Europe/the Middle East/Central Asia/South Asia, East Asia, Oceania, and the Americas9. Subsequent analyses allowed for refinement of the genetic history of global ancestries, revealing regional structure through the identification of 710, 1411, and 19 ancestries2."

Efforts to track SARS-CoV-2 sequences have helped identify worrying variants - but researchers are blind to emerging mutations in some regions.