Modern views of ancient metabolic networks

Metabolism is a molecular, cellular, ecological and planetary phenomenon, whose fundamental principles are likely at the heart of what makes living matter different from inanimate one. Systems biology approaches developed for the quantitative analysis of metabolism at multiple scales can help understand metabolism's ancient history. In this review, we highlight work that uses network-level approaches to shed light on key innovations in ancient life, including the emergence of proto-metabolic networks, collective autocatalysis and bioenergetics coupling. Recent experiments and computational analyses have revealed new aspects of this ancient history, paving the way for the use of large datasets to further improve our understanding of life's principles and abiogenesis.https://www.sciencedirect.com/science/article/pii/S2452310017302196Published versio

The compositional and evolutionary logic of metabolism

Metabolism displays striking and robust regularities in the forms of modularity and hierarchy, whose composition may be compactly described. This renders metabolic architecture comprehensible as a system, and suggests the order in which layers of that system emerged. Metabolism also serves as the foundation in other hierarchies, at least up to cellular integration including bioenergetics and molecular replication, and trophic ecology. The recapitulation of patterns first seen in metabolism, in these higher levels, suggests metabolism as a source of causation or constraint on many forms of organization in the biosphere. We identify as modules widely reused subsets of chemicals, reactions, or functions, each with a conserved internal structure. At the small molecule substrate level, module boundaries are generally associated with the most complex reaction mechanisms and the most conserved enzymes. Cofactors form a structurally and functionally distinctive control layer over the small-molecule substrate. Complex cofactors are often used at module boundaries of the substrate level, while simpler ones participate in widely used reactions. Cofactor functions thus act as "keys" that incorporate classes of organic reactions within biochemistry. The same modules that organize the compositional diversity of metabolism are argued to have governed long-term evolution. Early evolution of core metabolism, especially carbon-fixation, appears to have required few innovations among a small number of conserved modules, to produce adaptations to simple biogeochemical changes of environment. We demonstrate these features of metabolism at several levels of hierarchy, beginning with the small-molecule substrate and network architecture, continuing with cofactors and key conserved reactions, and culminating in the aggregation of multiple diverse physical and biochemical processes in cells.Comment: 56 pages, 28 figure

Intermediary metabolism

Caenorhabditis elegans has orthologs for most of the key enzymes involved in eukaryotic intermediary metabolism, suggesting that the major metabolic pathways are probably present in this species. We discuss how metabolic patterns and activity change as the worm traverses development and ages, or responds to unfavorable external factors, such as temperature extremes or shortages in food or oxygen. Dauer diapause is marked by an enhanced resistance to oxidative stress and a shift toward microaerobic and anaplerotic metabolic pathways and hypometabolism, as indicated by the increased importance of the malate dismutation and glyoxylate pathways and the repression of citric acid cycle activity. These alterations promote prolonged survival of the dauer larva; some of these changes also accompany the extended lifespan of insulin/IGF-1 and several mitochondrial mutants. We also present a brief overview of the nutritional requirements, energy storage and waste products generated by C. elegans

Environmental boundary conditions for the origin of life converge to an organo-sulfur metabolism

Published in final edited form as: Nat Ecol Evol. 2019 December ; 3(12): 1715–1724. doi:10.1038/s41559-019-1018-8.It has been suggested that a deep memory of early life is hidden in the architecture of metabolic networks, whose reactions could have been catalyzed by small molecules or minerals before genetically encoded enzymes. A major challenge in unravelling these early steps is assessing the plausibility of a connected, thermodynamically consistent proto-metabolism under different geochemical conditions, which are still surrounded by high uncertainty. Here we combine network-based algorithms with physico-chemical constraints on chemical reaction networks to systematically show how different combinations of parameters (temperature, pH, redox potential and availability of molecular precursors) could have affected the evolution of a proto-metabolism. Our analysis of possible trajectories indicates that a subset of boundary conditions converges to an organo-sulfur-based proto-metabolic network fuelled by a thioester- and redox-driven variant of the reductive tricarboxylic acid cycle that is capable of producing lipids and keto acids. Surprisingly, environmental sources of fixed nitrogen and low-potential electron donors are not necessary for the earliest phases of biochemical evolution. We use one of these networks to build a steady-state dynamical metabolic model of a protocell, and find that different combinations of carbon sources and electron donors can support the continuous production of a minimal ancient 'biomass' composed of putative early biopolymers and fatty acids.80NSSC17K0295 - Intramural NASA; 80NSSC17K0296 - Intramural NASA; T32 GM100842 - NIGMS NIH HHSAccepted manuscrip

Life’s unity and flexibility: the ecological link

The small size, ubiquity, metabolic versatility and flexibility, and genetic plasticity (horizontal transfer) of microbes allow them to tolerate and quickly adapt to unfavorable and/or changing environmental conditions. Prokaryotes are endowed with sophisticated cellular envelopes that contain molecules not found elsewhere in the biological world. Although prokaryotic cells lack the organelles that characterize their eukaryotic counterparts, their interiors are surprisingly complex. Prokaryotes sense their environment and respond as individual cells to specific environmental challenges; but prokaryotes also act cooperatively, displaying communal activities. In many microbial ecosystems, the functionally active unit is not a single species or population (clonal descendence of the same bacterium) but a consortium of two or more types of cells living in close symbiotic association. Only recently have we become aware that microbes are the basis for the functioning of the biosphere. Thus, we are at a unique time in the history of science, in which the interaction of technological advances and the exponential growth in our knowledge of the present microbial diversity will lead to significant advances not only in microbiology but also in biology and other sciences in general. [Int Microbiol 2006; 9(3):225-235

LGEM+^\text{+}: a first-order logic framework for automated improvement of metabolic network models through abduction

Scientific discovery in biology is difficult due to the complexity of the systems involved and the expense of obtaining high quality experimental data. Automated techniques are a promising way to make scientific discoveries at the scale and pace required to model large biological systems. A key problem for 21st century biology is to build a computational model of the eukaryotic cell. The yeast Saccharomyces cerevisiae is the best understood eukaryote, and genome-scale metabolic models (GEMs) are rich sources of background knowledge that we can use as a basis for automated inference and investigation. We present LGEM+, a system for automated abductive improvement of GEMs consisting of: a compartmentalised first-order logic framework for describing biochemical pathways (using curated GEMs as the expert knowledge source); and a two-stage hypothesis abduction procedure. We demonstrate that deductive inference on logical theories created using LGEM+, using the automated theorem prover iProver, can predict growth/no-growth of S. cerevisiae strains in minimal media. LGEM+ proposed 2094 unique candidate hypotheses for model improvement. We assess the value of the generated hypotheses using two criteria: (a) genome-wide single-gene essentiality prediction, and (b) constraint of flux-balance analysis (FBA) simulations. For (b) we developed an algorithm to integrate FBA with the logic model. We rank and filter the hypotheses using these assessments. We intend to test these hypotheses using the robot scientist Genesis, which is based around chemostat cultivation and high-throughput metabolomics.Comment: 15 pages, one figure, two tables, two algorithm

Biological generalizations and the search for extraterrestrial life

Biological exploration for extraterrestrial lif

Introduction to fungal physiology

This chapter describes some basic aspects of fungal cell physiology, focusing primarily on nutrition, growth, metabolism in unicellular yeasts and filamentous fungi, and cell death. It considers the most common growth forms, the filamentous fungi and unicellular yeasts. Fungal growth involves transport and assimilation of nutrients, followed by their integration into cellular components, followed by biomass increase and eventual cell division or septation. The physiology of vegetative reproduction and its control in fungi has been most widely studied in two model eukaryotes, the budding yeast, Saccharomyces cerevisiae, and the fission yeast, Schizosaccharomyces pombe. An understanding of the death of fungal cells is important from a fundamental viewpoint because fungi, especially yeasts, represent valuable model systems for the study of cellular aging and apoptosis (programed cell death). Recycling and redeployment of cellular material also helps drive the apical growth of filamentous fungi and the mycelium explores and extends through the environment