From Molecules to Life: Quantifying the Complexity of Chemical and Biological Systems in the Universe

Beyond nothingness in the formation and functional relevance of voids in polymer films

Voids-the nothingness-broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials.

Artificial Cytoskeleton Assembly for Synthetic Cell Motility

Imitation of cellular processes in cell-like compartments is a current research focus in synthetic biology. Here, a method is introduced for assembling an artificial cytoskeleton in a synthetic cell model system based on a poly(N-isopropyl acrylamide) (PNIPAM) composite material. Toward this end, a PNIPAM-based composite material inside water-in-oil droplets that are stabilized with PNIPAM-functionalized and commercial fluorosurfactants is introduced. The temperature-mediated contraction/release behavior of the PNIPAM-based cytoskeleton is investigated. The reversibility of the PNIPAM transition is further examined in bulk and in droplets and it could be shown that hydrogel induced deformation could be used to controllably manipulate droplet-based synthetic cell motility upon temperature changes. It is envisioned that a combination of the presented artificial cytoskeleton with naturally occurring components might expand the bandwidth of the bottom-up synthetic biology.

The hierarchical organization of autocatalytic reaction networks and its relevance to the origin of life

Prior work on abiogenesis, the emergence of life from non-life, suggests that it requires chemical reaction networks that contain self-amplifying motifs, namely, autocatalytic cores. However, little is known about how the presence of multiple autocatalytic cores might allow for the gradual accretion of complexity on the path to life. To explore this problem, we develop the concept of a seed-dependent autocatalytic system (SDAS), which is a subnetwork that can autocatalytically self-maintain given a flux of food, but cannot be initiated by food alone. Rather, initiation of SDASs requires the transient introduction of chemical “seeds.” We show that, depending on the topological relationship of SDASs in a chemical reaction network, a food-driven system can accrete complexity in a historically contingent manner, governed by rare seeding events. We develop new algorithms for detecting and analyzing SDASs in chemical reaction databases and describe parallels between multi-SDAS networks and biological ecosystems. Applying our algorithms to both an abiotic reaction network and a biochemical one, each driven by a set of simple food chemicals, we detect SDASs that are organized as trophic tiers, of which the higher tier can be seeded by relatively simple chemicals if the lower tier is already activated. This indicates that sequential activation of trophically organized SDASs by seed chemicals that are not much more complex than what already exist could be a mechanism of gradual complexification from relatively simple abiotic reactions to more complex life-like systems. Interestingly, in both reaction networks, higher-tier SDASs include chemicals that might alter emergent features of chemical systems and could serve as early targets of selection. Our analysis provides computational tools for analyzing very large chemical/biochemical reaction networks and suggests new approaches to studying abiogenesis in the lab.

The level of complexity seen in even the simplest living system is too great to have arisen in its current form without a long history of complexification. In this paper, we explore the view that open environments on the early Earth that received an ongoing flux of food chemicals could have complexified gradually by the sequential activation of autocatalytic chemical reaction systems. We develop the concept of seed-dependent autocatalytic systems (SDASs)–subnetworks whose components can self-propagate once activated by “seed” molecules, which might result from rare reactions or import from other environments. We developed new computational tools for detecting SDASs in reaction databases and determining if they are hierarchically organized, such that the activation of a lower-tier SDAS allows a higher-tier SDAS to then be seeded, much like the relationship between producers and consumers in an ecosystem. We apply our algorithms to two chemical reaction networks, one biological and the other abiotic, and find that both contain hierarchically organized SDASs. These results support the fundamental continuity of the way that the chemistry of non-life and life is organized and suggest new classes of laboratory experiment.

Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Molecular size and molecular structure: Discriminating their changes upon chemical reactions in terms of information entropy

Structural descriptors take the central place in the digitalization of chemical reactions. Information entropy is one of such descriptors that has been a seminal for numerous derivative indices. Previously, we have studied the rules of calculating information entropies of molecular ensembles based on the corresponding values of constituting molecules and found that the complexity of the ensemble has the contributions from the molecular structure and the size of the molecules. Considering chemical reaction as the conversion of one molecular ensemble to another allows calculating the change in information entropy as well as its components associated with molecular-structure and molecular-size changes. We demonstrate that both total information entropy change and its contributions are characteristic for the selected classes of chemical reactions and exemplify this approach with the cycloaddition and exchange reactions widespread in organic chemistry.

Information Entropy in Chemistry: An Overview

Basic applications of the information entropy concept to chemical objects are reviewed. These applications deal with quantifying chemical and electronic structures of molecules, signal processing, structural studies on crystals, and molecular ensembles. Recent advances in the mentioned areas make information entropy a central concept in interdisciplinary studies on digitalizing chemical reactions, chemico-information synthesis, crystal engineering, as well as digitally rethinking basic notions of structural chemistry in terms of informatics.

Fuzzy Recurrence Exponents of Subcellular-Nanostructure Dynamics in Time-lapse Confocal Imaging

Studying the dynamics of nanostructures in the intracellular space is important because it allows gaining insights into the mechanism of complex biological functions of organelles. Understanding such dynamical processes can contribute to the development of nanomedicine for the diagnosis and treatment of many diseases caused by the interaction of multiple genes and environmental factors. Here a quantitative measure of spatial-temporal dynamics of nanostructures within a cell line in the context of nonlinear dynamics is introduced, where early endosomes, late endosomes, and lysosomes recorded by time-lapse confocal imaging are examined. The mathematical derivation of the proposed technique is based on the concept of recurrence dynamics and sequential rate of change over time. The quantification introduced as fuzzy recurrence exponents can be generalized for characterizing the dynamics of experimental evolutions in other nanostructures of living cells captured under the optical microscope.

Metacode: One code to rule them all

The code of codes or metacode is a microcosm where biological layers, as well as their codes, interact together allowing the continuity of information flow in organisms by increasing biological entities' complexity. Through this novel organic code, biological systems scale towards niches with higher informatic freedom building structures that increase the entropy in the universe. Code biology has developed a novel informational framework where biological entities strive themselves through the information flow carried out through organic codes consisting of two molecular or functional landscapes intertwined through arbitrary linkages via an adaptor whose nature is autonomous from molecular determinism. Here we will integrate genomic and epigenomic codes according to the evidence released in ENCODE (phase 3), psychENCODE and GTEx project, outlining the principles of the metacode, to address the continuous nature of biological systems and their inter-layered information flow. This novel complex metacode maps from very constrained sets of elements (i.e., regulation sites modulating gene expression) to new ones with greater freedom of decoding (i.e., a continuous cell phenotypic space). This leads to a new domain in code biology where biological systems are informatic attractors that navigate an energy metaspace through a complexity-noise balance, stalling in emergent niches where organic codes take meaning.

Ultra-high-performance liquid chromatography high-resolution mass spectrometry variants for metabolomics research

Ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) variants currently represent the best tools to tackle the challenges of complexity and lack of comprehensive coverage of the metabolome. UHPLC offers flexible and efficient separation coupled with high-sensitivity detection via HRMS, allowing for the detection and identification of a broad range of metabolites. Here we discuss current common strategies for UHPLC-HRMS-based metabolomics, with a focus on expanding metabolome coverage.

Chemical Fueling Enables Molecular Complexification of Self-Replicators*

Unravelling how the complexity of living systems can (have) emerge(d) from simple chemical reactions is one of the grand challenges in contemporary science. Evolving systems of self-replicating molecules may hold the key to this question. Here we show that, when a system of replicators is subjected to a regime where replication competes with replicator destruction, simple and fast replicators can give way to more complex and slower ones. The structurally more complex replicator was found to be functionally more proficient in the catalysis of a model reaction. These results show that chemical fueling can maintain systems of replicators out of equilibrium, populating more complex replicators that are otherwise not readily accessible. Such complexification represents an important requirement for achieving open-ended evolution as it should allow improved and ultimately also new functions to emerge.

Construction and characterization of a novel glucose dehydrogenase-leucine dehydrogenase fusion enzyme for the biosynthesis of L-tert-leucine

Background

Biosynthesis of l-tert-leucine (l-tle), a significant pharmaceutical intermediate, by a cofactor regeneration system friendly and efficiently is a worthful goal all the time. The cofactor regeneration system of leucine dehydrogenase (LeuDH) and glucose dehydrogenase (GDH) has showed great coupling catalytic efficiency in the synthesis of l-tle, however the multi-enzyme complex of GDH and LeuDH has never been constructed successfully.

Results

In this work, a novel fusion enzyme (GDH–R3–LeuDH) for the efficient biosynthesis of l-tle was constructed by the fusion of LeuDH and GDH mediated with a rigid peptide linker. Compared with the free enzymes, both the environmental tolerance and thermal stability of GDH–R3–LeuDH had a great improved since the fusion structure. The fusion structure also accelerated the cofactor regeneration rate and maintained the enzyme activity, so the productivity and yield of l-tle by GDH–R3–LeuDH was all enhanced by twofold. Finally, the space–time yield of l-tle catalyzing by GDH–R3–LeuDH whole cells could achieve 2136 g/L/day in a 200 mL scale system under the optimal catalysis conditions (pH 9.0, 30 °C, 0.4 mM of NAD⁺ and 500 mM of a substrate including trimethylpyruvic acid and glucose).

Conclusions

It is the first report about the fusion of GDH and LeuDH as the multi-enzyme complex to synthesize l-tle and reach the highest space–time yield up to now. These results demonstrated the great potential of the GDH–R3–LeuDH fusion enzyme for the efficient biosynthesis of l-tle.

Hsp70 and the Unfolded Protein Response as a Challenging Drug Target and an Inspiration for Probe Molecule Development

The unfolded protein response (UPR) is a cellular stress response mechanism that is critical for cell survival. Pharmacological modulation of the ATPase activity of the chaperone Hsp70 can trigger UPR-mediated cell death, thus removing pathogenic cells in human malignancies, or, alternatively, stimulate survival, thereby preventing apoptosis in neuronal cells and slowing the progress of inflammation, neurodegeneration, and aging. This Viewpoint highlights the complexity of the protein homeostasis network and discusses different approaches for modulating Hsp70 activity, including the use of a chemical reaction development-inspired library of Hsp70 agonists and antagonists.

Deciphering Biosignatures in Planetary Contexts

Microbial life permeates Earth's critical zone and has likely inhabited nearly all our planet's surface and near subsurface since before the beginning of the sedimentary rock record. Given the vast time that Earth has been teeming with life, do astrobiologists truly understand what geological features untouched by biological processes would look like? In the search for extraterrestrial life in the Universe, it is critical to determine what constitutes a biosignature across multiple scales, and how this compares with "abiosignatures" formed by nonliving processes. Developing standards for abiotic and biotic characteristics would provide quantitative metrics for comparison across different data types and observational time frames. The evidence for life detection falls into three categories of biosignatures: (1) substances, such as elemental abundances, isotopes, molecules, allotropes, enantiomers, minerals, and their associated properties; (2) objects that are physical features such as mats, fossils including trace-fossils and microbialites (stromatolites), and concretions; and (3) patterns, such as physical three-dimensional or conceptual n-dimensional relationships of physical or chemical phenomena, including patterns of intermolecular abundances of organic homologues, and patterns of stable isotopic abundances between and within compounds. Five key challenges that warrant future exploration by the astrobiology community include the following: (1) examining phenomena at the "right" spatial scales because biosignatures may elude us if not examined with the appropriate instrumentation or modeling approach at that specific scale; (2) identifying the precise context across multiple spatial and temporal scales to understand how tangible biosignatures may or may not be preserved; (3) increasing capability to mine big data sets to reveal relationships, for example, how Earth's mineral diversity may have evolved in conjunction with life; (4) leveraging cyberinfrastructure for data management of biosignature types, characteristics, and classifications; and (5) using three-dimensional to n-D representations of biotic and abiotic models overlain on multiple overlapping spatial and temporal relationships to provide new insights.

Systems chemical analytics: introduction to the challenges of chemical complexity analysis

We present concepts of complexity, and complex chemistry in systems subjected to biotic and abiotic transformations, and introduce analytical possibilities to disentangle chemical complexity into its elementary parts as a global integrated approach termed systems chemical analytics.

Data-Driven Astrochemistry: One Step Further within the Origin of Life Puzzle

Astrochemistry, meteoritics and chemical analytics represent a manifold scientific field, including various disciplines. In this review, clarifications on astrochemistry, comet chemistry, laboratory astrophysics and meteoritic research with respect to organic and metalorganic chemistry will be given. The seemingly large number of observed astrochemical molecules necessarily requires explanations on molecular complexity and chemical evolution, which will be discussed. Special emphasis should be placed on data-driven analytical methods including ultrahigh-resolving instruments and their interplay with quantum chemical computations. These methods enable remarkable insights into the complex chemical spaces that exist in meteorites and maximize the level of information on the huge astrochemical molecular diversity. In addition, they allow one to study even yet undescribed chemistry as the one involving organomagnesium compounds in meteorites. Both targeted and non-targeted analytical strategies will be explained and may touch upon epistemological problems. In addition, implications of (metal)organic matter toward prebiotic chemistry leading to the emergence of life will be discussed. The precise description of astrochemical organic and metalorganic matter as seeds for life and their interactions within various astrophysical environments may appear essential to further study questions regarding the emergence of life on a most fundamental level that is within the molecular world and its self-organization properties.