African swine fever virus regulates host energy and amino acid metabolism to promote viral replication

African swine fever is one of the most serious viral diseases caused by African swine fever virus (ASFV). The metabolic changes induced by ASFV infection remain unknown. Here, PAMs infected with ASFV was analyzed by ultra-high-performance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS) in combination with multivariate statistical analysis. A total of 90 metabolites were significantly changed after ASFV infection, and most of them belong to amino acids and TCA cycle intermediates. ASFV infection induced increase of most of amino acids in host during the early stages of infection, and amino acids decreased in the late stages of infection. ASFV infection did not significantly affected glycolysis pathway, whereas it induced the increase of citrate, succinate, α-ketoglutarate, and oxaloacetate levels in the TCA cycle, suggesting that ASFV infection promoted TCA cycle. The activity of aspartate aminotransferase and glutamate production were significantly elevated in ASFV-infected cells and pigs, resulting in reversible transition between TCA cycle and amino acids synthesis. Aspartate, glutamate, and TCA cycle were essential for ASFV replication. In addition, ASFV infection induced an increase in lactate level using lactate dehydrogenase, which led to low expression of IFN-β and increased of ASFV replication. Our data, for the first time, indicated that ASFV infection controls IFN-β production through RIG-I-mediated signaling pathways. These data identified a novel mechanism evolved by ASFV to inhibit host innate immune responses, and will provide insights for development of new preventive or therapeutic strategies targeting the altered metabolic pathways. IMPORTANCE In order to promote viral replication, viruses often cause severe immunosuppression and seize organelles to synthesize a large number of metabolites required for self-replication. African swine fever virus (ASFV) has developed many strategies to evade host innate immune responses. However, the impact of ASFV infection on host cellular metabolism remains unknown. Here, for the first time, we analyzed the metabolomic profiles of ASFV-infected PAMs cells. ASFV infection increased host TCA cycle and amino acids metabolism. Aspartate, glutamate, and TCA cycle promoted ASFV replication. ASFV infection also induced the increase of lactate production to inhibit innate immune responses for self-replication. This study identified novel immune evasion mechanisms utilized by ASFV and provided viewpoints on ASFV-host interactions, which is critical for guiding the design of new prevention strategies against ASFV targeting the altered metabolic pathways.

Mutations in artificial self-replicating tiles: A step toward Darwinian evolution

Artificial self-replication and exponential growth holds the promise of gaining a better understanding of fundamental processes in nature but also of evolving new materials and devices with useful properties. A system of DNA origami dimers has been shown to exhibit exponential growth and selection. Here we introduce mutation and growth advantages to study the possibility of Darwinian-like evolution. We seed and grow one dimer species, AB, from A and B monomers that doubles in each cycle. A similar species from C and D monomers can replicate at a controlled growth rate of two or four per cycle but is unseeded. Introducing a small mutation rate so that AB parents infrequently template CD offspring we show experimentally that the CD species can take over the system in approximately six generations in an advantageous environment. This demonstration opens the door to the use of evolution in materials design.

Kinematic self-replication in reconfigurable organisms

All living systems perpetuate themselves via growth in or on the body, followed by splitting, budding, or birth. We find that synthetic multicellular assemblies can also replicate kinematically by moving and compressing dissociated cells in their environment into functional self-copies. This form of perpetuation, previously unseen in any organism, arises spontaneously over days rather than evolving over millennia. We also show how artificial intelligence methods can design assemblies that postpone loss of replicative ability and perform useful work as a side effect of replication. This suggests other unique and useful phenotypes can be rapidly reached from wild-type organisms without selection or genetic engineering, thereby broadening our understanding of the conditions under which replication arises, phenotypic plasticity, and how useful replicative machines may be realized.

Insect-host control of obligate, intracellular symbiont density

Many insects rely on intracellular bacterial symbionts to supplement their specialized diets with micronutrients. Using data from diverse and well-studied insect systems, we propose three lines of evidence suggesting that hosts have tight control over the density of their obligate, intracellular bacterial partners. First, empirical studies have demonstrated that the within-host symbiont density varies depending on the nutritional and developmental requirements of the host. Second, symbiont genomes are highly reduced and have limited capacity for self-replication or transcriptional regulation. Third, several mechanisms exist for hosts to tolerate, regulate and remove symbionts including physical compartmentalization and autophagy. We then consider whether such regulation is adaptive, by discussing the relationship between symbiont density and host fitness. We discuss current limitations of empirical studies for exploring fitness effects in host–symbiont relationships, and emphasize the potential for using mathematical models to formalize evolutionary hypotheses and to generate testable predictions for future work.

Small RNAs Worm Up Transgenerational Epigenetics Research

DNA is central to the propagation and evolution of most living organisms due to the essential process of its self-replication. Yet it also encodes factors that permit epigenetic (not included in DNA sequence) flow of information from parents to their offspring and beyond. The known mechanisms of epigenetic inheritance include chemical modifications of DNA and chromatin, as well as regulatory RNAs. All these factors can modulate gene expression programs in the ensuing generations. The nematode Caenorhabditis elegans is recognized as a pioneer organism in transgenerational epigenetic inheritance research. Recent advances in C. elegans epigenetics include the discoveries of control mechanisms that limit the duration of RNA-based epigenetic inheritance, periodic DNA motifs that counteract epigenetic silencing establishment, new mechanistic insights into epigenetic inheritance carried by sperm, and the tantalizing examples of inheritance of sensory experiences. This review aims to highlight new findings in epigenetics research in C. elegans with the main focus on transgenerational epigenetic phenomena dependent on small RNAs.

Self-replication of a quantum artificial organism driven by single-photon pulses

Imitating the transition from inanimate to living matter is a longstanding challenge. Artificial life has achieved computer programs that self-replicate, mutate, compete and evolve, but lacks self-organized hardwares akin to the self-assembly of the first living cells. Nonequilibrium thermodynamics has achieved lifelike self-organization in diverse physical systems, but has not yet met the open-ended evolution of living organisms. Here, I look for the emergence of an artificial-life code in a nonequilibrium physical system undergoing self-organization. I devise a toy model where the onset of self-replication of a quantum artificial organism (a chain of lambda systems) is owing to single-photon pulses added to a zero-temperature environment. I find that spontaneous mutations during self-replication are unavoidable in this model, due to rare but finite absorption of off-resonant photons. I also show that the replication probability is proportional to the absorbed work from the photon, thereby fulfilling a dissipative adaptation (a thermodynamic mechanism underlying lifelike self-organization). These results hint at self-replication as the scenario where dissipative adaptation (pointing towards convergence) coexists with open-ended evolution (pointing towards divergence).

The view of microbes as energy converters illustrates the trade-off between growth rate and yield

The application of thermodynamics to microbial growth has a long tradition that originated in the middle of the 20th century. This approach reflects the view that self-replication is a thermodynamic process that is not fundamentally different from mechanical thermodynamics. The key distinction is that a free energy gradient is not converted into mechanical (or any other form of) energy but rather into new biomass. As such, microbes can be viewed as energy converters that convert a part of the energy contained in environmental nutrients into chemical energy that drives self-replication. Before the advent of high-throughput sequencing technologies, only the most central metabolic pathways were known. However, precise measurement techniques allowed for the quantification of exchanged extracellular nutrients and heat of growing microbes with their environment. These data, together with the absence of knowledge of metabolic details, drove the development of so-called black-box models, which only consider the observable interactions of a cell with its environment and neglect all details of how exactly inputs are converted into outputs. Now, genome sequencing and genome-scale metabolic models (GEMs) provide us with unprecedented detail about metabolic processes inside the cell. However, mostly due to computational complexity issues, the derived modelling approaches make surprisingly little use of thermodynamic concepts. Here, we review classical black-box models and modern approaches that integrate thermodynamics into GEMs. We also illustrate how the description of microbial growth as an energy converter can help to understand and quantify the trade-off between microbial growth rate and yield.