A model for the coevolution of the genetic code and the process of protein synthesis - Review and assessment
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Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support. In this perspective, we assert that the cultural barriers between the ML and PBM communities limit the potential of ML, and even its ‘hybridization’ with PBM, for EES applications. Fundamental, but often ignored, differences between ML and PBM are discussed as well as their strengths and weaknesses in light of three overarching modelling objectives in EES, (1) nowcasting and prediction, (2) scenario analysis, and (3) diagnostic learning. The paper ponders over a ‘coevolutionary’ approach to model building, shifting away from a borrowing to a co-creation culture, to develop a generation of models that leverage the unique strengths of ML such as scalability to big data and high-dimensional mapping, while remaining faithful to process-based knowledge base and principles of model explainability and interpretability, and therefore, falsifiability.
The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.
We describe perturbation theory (PT) models of galaxy bias for applications to photometric galaxy surveys. We model the galaxy-galaxy and galaxy-matter correlation functions in configuration space and validate against measurements from mock catalogs designed for the Dark Energy Survey (DES). We find that an effective PT model with five galaxy bias parameters provides a good description of the 3D correlation functions above scales of 4 Mpc/$h$ and $z < 1$. Our tests show that at the projected precision of the DES-Year 3 analysis, two of the non-linear bias parameters can be fixed to their co-evolution values, and a third (the $k^2$ term for higher derivative bias) set to zero. The agreement is typically at the 2 percent level over scales of interest, which is the statistical uncertainty of our simulation measurements. To achieve this level of agreement, our {\it fiducial} model requires using the full non-linear matter power spectrum (rather than the 1-loop PT one). We also measure the relationship between the non-linear and linear bias parameters and compare them to their expected co-evolution values. We use these tests to motivate the galaxy bias model and scale cuts for the cosmological analysis of the Dark Energy Survey; our conclusions are generally applicable to all photometric surveys.
A myriad of cellular events are regulated by allostery; therefore, evolution of this process is of fundamental interest. Here, we use ancestral sequence reconstruction to resurrect ancestors of two colocalizing proteins, Aurora A kinase and its allosteric activator TPX2 (targeting protein for Xklp2), to experimentally characterize the evolutionary path of allosteric activation. Autophosphorylation of the activation loop is the most ancient activation mechanism; it is fully developed in the oldest kinase ancestor and has remained stable over 1 billion years of evolution. As the microtubule-associated protein TPX2 appeared, efficient kinase binding to TPX2 evolved, likely owing to increased fitness by virtue of colocalization. Subsequently, TPX2-mediated allosteric kinase regulation gradually evolved. Surprisingly, evolution of this regulation is encoded in the kinase and did not arise by a dominating mechanism of coevolution.
We relate the anomaly in the noise color of spin ice to the emergent nature of its magnetic monopoles and their random walk. Monopoles are quasi-particles, and the spin vacuum in which they wander is not structureless. Rather, the underlying spin ensemble filters the thermal white noise, leading to non-trivial coevolution. Thus, monopoles can be considered as "dressed" random walkers, activated by a non-trivial stochastic noise that subsumes mutual interactions and the coevolution of their spin vacuum. From this, we suggest that recent experimental results are interpretable in terms of monopole subdiffusion. Furthermore, we then conjecture relations between the color of the noise and other observables, such as relaxation time, monopole density, the dynamic exponent, and the order of the annihilation reaction, which suggests to us the introduction of spin-ice-specific critical exponents in a neighborhood of the ice manifold criticality.
The feedback from the accretion of central supermassive black holes (SMBHs) is a hot topic in the coevolution of SMBHs and their host galaxies. By tracing the large-scale outflow using the line profile and bulk velocity shift of [O III ]λ5007, the evolutionary role of outflow is studied here on a large sample of 221 type 2 quasars (QSO2s) extracted from Reyes et al. By following our previous study on local Seyfert 2 galaxies, the current spectral analysis on the Sloan Digital Sky Survey spectroscopic database enables us to arrive at the following results: (1) by using the Lick indices, we confirm that QSO2s are, on average, more frequently associated with younger stellar populations than Seyfert galaxies; (2) QSO2s with a stronger outflow tend to be associated with a younger stellar population, which implies a coevolution between the feedback from SMBHs and the host in QSO2s; (3) although occupied at the high L bol /L Edd end, the QSO2s follow the L bol /L Edd -D n (4000) sequence established from local, less-luminous Seyfert galaxies, which suggests a decrease of the accretion activity of SMBHs and also of feedback as the circumnuclear stellar population continuously ages.
A computer program was used to test Wong's coevolution theory of the genetic code. The codon correlations between the codons of biosynthetically related amino acids in the universal genetic code and in randomly generated genetic codes were compared. It was determined that many codon correlations are also present within random genetic codes and that among the random codes there are always several which have many more correlations than that found in the universal code. Although the number of correlations depends on the choice of biosynthetically related amino acids, the probability of choosing a random genetic code with the same or greater number of codon correlations as the universal genetic code was found to vary from 0.1% to 34% (with respect to a fairly complete listing of related amino acids). Thus, Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acids, is statistical in nature.
Abstract Aims Plant-specific microbial diversity reflecting host-microbe coevolution was frequently shown at the structural level but less on the functional scale. We studied the microbiome of three compartments at the soil root interface (root endosphere, rhizosphere, bulk soil) of medicinal plants cultivated under organic management in Egypt. The study aimed to examine the impact of the rhizosphere on microbial community composition and diversity in desert agricultural soil, as well as to identify specific functions associated with the rhizosphere. Methods The microbiome community structure, diversity, and microbial functioning were evaluated through the utilization of 16S rRNA gene amplicon and shotgun metagenome sequencing. Results We found the typical rhizosphere effect and plant-species-specific enrichment of bacterial diversity. The annual plants Calendula officinalis and Matricaria chamomilla ( Asteraceae ) were more similar than the perennial Solanum distichum ( Solanaceae ). Altogether, plant species explained 50.5% of the variation in bacterial community structures in the rhizosphere. Our results indicate a stronger effect of the plant species in terms of modulating bacterial community structures in the rhizosphere than in root endosphere samples. The plant-driven rhizosphere effect could be linked to redundant plant beneficial functions in the microbiome, while enrichment of specific genes related to amino acid ion transport and metabolism, carbohydrate transport and metabolism, defense mechanisms, and secondary metabolites biosynthesis were more specific. Conclusions The study explores the microbiome continuum at the soil-root interface of medicinal plant species, revealing significant bacterial community structure shifts and plant specificity. The study provides insights into the essential microbiome components contributing to rhizosphere functionality.
The U.S. National Academies report on Environmental Engineering for the 21st Century identified five grand challenges of sustainably supplying food, water, and energy; curbing climate change and adapting to its impacts; designing a future without pollution and waste; creating efficient, healthy, resilient cities; and fostering informed decisions and actions. (1) Addressing many of the grand challenges will require embracing the intersections of environmental science, engineering, and geosciences. These three fields are inherently interdisciplinary, and they naturally intersect with each other (Figure 1). Geosciences, or Earth sciences, study the dynamics of different spheres of Earth. One of its missions is to detect the availability of mineral, water, and fuel resources, for sustainable development, and new research opportunities were identified in “coevolution of life, environment, and climate” and “biogeochemical and water cycles in terrestrial environments and impacts of global change” by the U.S. National Research Council. (2) Environmental science and engineering focus on the spheres that intersect with human activities. Environmental science puts an emphasis on understanding the migration of naturally occurring and anthropogenic contaminants in the environment and their impact on ecosystem and human health, and environmental engineering centers on developing technologies for water supply, mineral exploration, and environmental remediation to mitigate adverse impacts.
Abstract Permafrost influences 25% of land in the Northern Hemisphere, where it stabilizes the ground beneath communities and infrastructure and sequesters carbon. However, the coevolution of permafrost, river dynamics, and vegetation in Arctic environments remains poorly understood. As rivers meander, they erode the floodplain at cutbanks and build new land through bar deposition, creating sequences of landforms with distinct formation ages. Here we mapped these sequences along the Koyukuk River floodplain, Alaska, analyzing permafrost occurrence, and landform and vegetation types. We used radiocarbon and optically stimulated luminescence (OSL) dating to develop a floodplain age map. Deposit ages ranged from modern to 10 ka, with more younger deposits near the modern channel. Permafrost rapidly reached 50% areal extent in all deposits older than 200 years then gradually increased up to ∼85% extent for deposits greater than 4 Kyr old. Permafrost extent correlated with increases in black spruce and wetland abundance, as well as increases in permafrost extent within wetland, and shrub and scrub vegetation classes. We developed an inverse model to constrain permafrost formation rate as a function of air temperature. Permafrost extent initially increased by ∼25% per century, in pace with vegetation succession, before decelerating to <10% per millennia as insulating overbank mud and moss slowly accumulated. Modern permafrost extent on the Koyukuk floodplain therefore reflects a dynamic balance between widespread, time‐varying permafrost formation and rapid, localized degradation due to cutbank erosion that might trigger a rapid loss of permafrost with climatic warming.
Abstract The Portevin-Le Chatelier (PLC) effect is a phenomenon by which plastic slip in metallic materials becomes unstable, resulting in jerky flow and the onset of inhomogeneous deformation. The PLC effect is thought to be fundamentally caused by the dynamic interplay between dislocations and solute atoms. However, this interplay is almost always inaccessible experimentally due to the extremely fine length and time scales over which it occurs. In this paper, simulations of jerky flow in W-O interstitial solid solutions reveal three dynamic regimes emerging from the simulated strain rate-temperature space: one resembling standard solid solution strengthening, another one mimicking solute cloud formation, and a third one where dislocation/solute coevolution leads to jerky flow as a precursor of dynamic strain aging. The simulations are carried out in a stochastic framework that naturally captures rare events in a rigorous manner, providing atomistic resolution over diffusive time scales using no adjustable parameters.
Evidence indicates that supermassive black holes (SMBHs) exist at the centres of most galaxies. Their mass correlates with the galactic bulge mass, suggesting a coevolution with their host galaxies, most likely through powerful winds. X-ray observations have detected highly ionized winds outflowing at sub-relativistic speeds from the accretion disks around SMBHs. However, the limited spectral resolution of present X-ray instruments has left the physical structure and location of the winds poorly understood, hindering accurate estimates of their kinetic power. Here, in this study, the first X-Ray Imaging and Spectroscopy Mission (XRISM) observation of the luminous quasar PDS 456 is reported. The high-resolution spectrometer Resolve aboard XRISM enabled the discovery of five discrete velocity components outflowing at 20–30% of the speed of light. This demonstrates that the wind structure is highly inhomogeneous, which probably consists of up to a million clumps. The mass outflow rate is estimated to be 60–300 solar masses per year, with the wind kinetic power exceeding the Eddington luminosity limit. Compared with the galaxy-scale outflows, the kinetic power is more than three orders of magnitude larger, whereas the momentum flux is ten times larger. These estimates disfavour both energy-driven and momentum-driven outflow models. This suggests that such wind activity occurs in less than 10% of the quasar phase and/or that its energy/momentum is not efficiently transferred to the galaxy-scale outflows owing to the clumpiness of the wind and the interstellar medium.
Bacteria and archaea possessing the hgcAB gene pair methylate inorganic mercury (Hg) to form highly toxic methylmercury. HgcA consists of a corrinoid binding domain and a transmembrane domain, and HgcB is a dicluster ferredoxin. However, their detailed structure and function have not been thoroughly characterized. We modeled the HgcAB complex by combining metagenome sequence data mining, coevolution analysis, and Rosetta structure calculations. In addition, we overexpressed HgcA and HgcB in Escherichia coli, confirmed spectroscopically that they bind cobalamin and [4Fe-4S] clusters, respectively, and incorporated these cofactors into the structural model. Surprisingly, the two domains of HgcA do not interact with each other, but HgcB forms extensive contacts with both domains. The model suggests that conserved cysteines in HgcB are involved in shuttling HgII, methylmercury, or both. These findings refine our understanding of the mechanism of Hg methylation and expand the known repertoire of corrinoid methyltransferases in nature.
Vertebrate lungs contain diverse microbial communities, but little is known about the drivers of community composition or consequences for health. Microbiome assembly by processes such as dispersal, coevolution, and host-switching can be probed with comparative surveys; however, few studies exist for lung microbiomes, particularly for the fungal component, the mycobiome. Distinguishing among fungal taxa that are generalist or specialist symbionts, potential pathogens, or incidentally inhaled spores is urgent because of potential for emerging diseases. Here, we characterize the avian lung mycobiome and test the relative influences of environment, phylogeny, and functional traits. We used metabarcoding and culturing from 195 lung samples representing 32 bird species across 20 families. We identified 526 fungal taxa as estimated by distinct sequence types (zOTUs) including many opportunistic pathogens. These were predominantly from the phylum Ascomycota (79%) followed by Basidiomycota (16%) and Mucoromycota (5%). Yeast and yeast-like taxa (Malassezia, Filobasidium, Saccharomyces, Meyerozyma, and Aureobasidium) and filamentous fungi (Cladosporium, Alternaria, Neurospora, Fusarium, and Aspergillus) were abundant. Lung mycobiomes were strongly shaped by environmental exposure, and further modulated by host identity, traits, and phylogenetic affinities. Our results implicate migratory bird species as potential vectors for long-distance dispersal of opportunistically pathogenic fungi.
Galaxies and their central supermassive black holes are known to coevolve, but the physical background for this is unknown as of yet. The High-z Universe probed via Lensing by QSOs (HULQ) project aims to investigate this coevolution by using quasi-stellar object (QSO) host galaxies acting as gravitational lenses (QSO lenses). We present the results of the spectroscopic observation of the first QSO lens candidate from the HULQ project, HULQ J0002+0239, which consists of a QSO host galaxy at z d = 1.455 and four seemingly lensed objects in a cross-like configuration. Deep optical spectra of two of the possibly lensed objects with z ~ 24.5 mag were obtained with the Gemini Multi-Object Spectrograph on the Gemini North Telescope. Their spectra reveal that the objects are newly discovered galaxies at z = 0.29 and z = 1.11, and we conclude that HULQ J0002+0239 is not a QSO lens. Our QSO lens search results are so far in agreement with the predicted number of QSO lenses, and we discuss how the future investigation of additional QSO lens candidates could tell us more about the evolution of the black hole mass and host galaxy scaling relations.
The relation between the mass of the supermassive black hole (SMBH) in the center of galaxies and their bulge mass or central velocity dispersion is well known. This suggests a coevolution between the SMBHs and their galaxy hosts. Our aim is to study this relation, specifically, for radio loud galaxies, and as a function of redshift z. We selected a sample of 42 radio galaxies and active galactic nuclei (AGN) with broad emission lines and spectroscopic redshifts between z = 0.3 - 4 by cross-matching the low radio frequency sources from Very Large Array (VLA) FIRST with spectroscopically confirmed galaxies from wide-field surveys, including Sloan Digital Sky Survey (SDSS) DR14 ugriz and Dark Energy Survey (DES) DR2 grzY in the optical, Wield Infrared Survey Explorer (WISE), and the Galaxy And Mass Assembly (GAMA) spectroscopic survey. We characterized the stellar mass (M $\star$ ), star formation, and black hole properties (mass of the central SMBH, Eddington ratio η, and jet power, Q jet ). The relation between SMBH mass, M $\star$ , η, and z is placed into context by comparing them with scaling relations (M BH –M $\star$ , M BH /M $\star$ –z, M BH –Q jet , and Q jet –η) from the literature. On the basis of a multiwavelength spectral energy distribution modeling, our radio sources are broadly consistent with being on the star-forming main sequence. They have sub-Eddington accretion rates, η ≃ 1% on average, as typically found in type I AGN, while higher accretion rates favor more powerful jets to be launched by the central engine. We find overmassive SMBHs in (17 ± 5)% of our radio sources, similarly to previous studies on nearby early-type galaxies. Altogether, an evolutionary scenario in which radio-mode AGN feedback regulates the accretion onto the SMBHs and the stellar mass assembly of the radio sources is discussed, which may explain the observed phenomenology. This pilot study represents a benchmark for future studies using wide-field surveys such as those with Euclid and the Vera Rubin Observatory.
Which galaxies in the general population turn into active galactic nuclei (AGNs) is a keystone of galaxy formation and evolution. Thanks to SRG/eROSITA’s contiguous 140 square degree pilot survey field, we constructed a large, complete, and unbiased soft X-ray flux-limited (FX > 6.5 × 10 -15 erg s -1 cm -2 ) AGN sample at low redshift, 0.05 < z < 0.55. Two summary statistics, the clustering using spectra from SDSS-V and galaxy-galaxy lensing with imaging from HSC, are measured and interpreted with halo occupation distribution and abundance matching models. Both models successfully account for the observations. We obtain an exceptionally complete view of the AGN halo occupation distribution. The population of AGNs is broadly distributed among halos with a mean mass of 3.9 -2.4 +2.0 × 10 12 M ⊙ . This corresponds to a large-scale halo bias of b(z = 0.34) = 0.99 -0.10 +0.08 . The central occupation has a large transition parameter, σ log 10 (M) = 1.28 ± 0.2. The satellite occupation distribution is characterized by a shallow slope, α sat = 0.73 ± 0.38. We find that AGNs in satellites are rare, with f sat < 20%. Most soft X-ray-selected AGNs are hosted by central galaxies in their dark matter halo. A weak correlation between soft X-ray luminosity and large-scale halo bias is confirmed (3.3σ). We discuss the implications of environmental-dependent AGN triggering. This study paves the way toward fully charting, in the coming decade, the coevolution of X-ray AGNs, their host galaxies, and dark matter halos by combining eROSITA with SDSS-V, 4MOST, DESI, LSST, and Euclid data.