Scaling laws in enzyme function reveal a new kind of biochemical universality

Exploring the enzymatic repertoires of Bacteria and Archaea and their associations with metabolic maps

The evolution, survival, and adaptation of microbes are consequences of gene duplication, acquisition, and divergence in response to environmental challenges. In this context, enzymes play a central role in the evolution of organisms, because they are fundamental in cell metabolism. Here, we analyzed the enzymatic repertoire in 6,467 microbial genomes, including their abundances, and their associations with metabolic maps. We found that the enzymes follow a power-law distribution, in relation to the genome sizes. Therefore, we evaluated the total proportion enzymatic classes in relation to the genomes, identifying a descending-order proportion: transferases (EC:2.-), hydrolases (EC:3.-), oxidoreductases (EC:1.-), ligases (EC:6.-), lyases (EC:4.-), isomerases (EC:5.-), and translocases (EC:7-.). In addition, we identified a preferential use of enzymatic classes in metabolism pathways for xenobiotics, cofactors and vitamins, carbohydrates, amino acids, glycans, and energy. Therefore, this analysis provides clues about the functional constraints associated with the enzymatic repertoire of functions in Bacteria and Archaea.

Limitations of Current Machine-Learning Models in Predicting Enzymatic Functions for Uncharacterized Proteins

Thirty to seventy percent of proteins in any given genome have no assigned function and have been labeled as the protein "unknownme". This large knowledge gap prevents the biological community from fully leveraging the plethora of genomic data that is now available. Machine-learning approaches are showing some promise in propagating functional knowledge from experimentally characterized proteins to the correct set of isofunctional orthologs. However, they largely fail to predict enzymatic functions unseen in the training set, as shown by dissecting the predictions made for 450 enzymes of unknown function from the model bacteria Escherichia coli using the DeepECTransformer platform. Lessons from these failures can help the community develop machine-learning methods that assist domain experts in making testable functional predictions for more members of the uncharacterized proteome.

Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems

The intricate and complex features of enzymatic reaction networks (ERNs) play a key role in the emergence and sustenance of life. Constructing such networks in vitro enables stepwise build up in complexity and introduces the opportunity to control enzymatic activity using physicochemical stimuli. Rational design and modulation of network motifs enable the engineering of artificial systems with emergent functionalities. Such functional systems are useful for a variety of reasons such as creating new-to-nature dynamic materials, producing value-added chemicals, constructing metabolic modules for synthetic cells, and even enabling molecular computation. In this review, we offer insights into the chemical characteristics of ERNs while also delving into their potential applications and associated challenges.

Enzyme characterization of lactic acid bacteria isolated from duck excreta

Background and Aim

The production of lignocellulosic biomass waste in the agricultural sector of Indonesia is quite high annually. Utilization of lignocellulosic biomass waste through fermentation technology can be used as feed and biofuel. Fermentation technology requires the involvement of micro-organisms such as bacteria (lactic acid bacteria or LAB). LABs can be isolated from various sources, such as duck excreta. However, there have not been many reports of LAB from duck excreta. The present study aimed to characterize LAB enzymes isolated from duck excreta and obtain LAB enzymes with superior fermentation properties.

Materials and Methods

A total of 11 LAB cultures obtained from duck excreta in Yogyakarta, Indonesia, were tested. Enzyme characterization of each LAB was performed using the API ZYM kit (BioMérieux, Marcy-I'Etoile, France). The bacterial cell suspension was dropped onto the API ZYM™ cupule using a pipette and incubated for 4 h at 37°C. After incubation, ZYM A and ZYM B were dripped onto the API ZYM cupule, and color changes were observed for approximately 10 s under a strong light source.

Results

Esterase activity was moderate for all LABs. The activity of α-chymotrypsin, β-glucuronidase, α-fucosidase, and α-mannosidase was not observed in a total of 10 LAB. The phosphohydrolase and amino peptidase enzyme activity of seven LABs was strong. Only six LAB samples showed protease activity. The glycosyl hydrolase (GH) activity was observed in a total of 8 LAB, while the activity of 2 LAB was strong (Lactococcus lactis subsp. lactis K5 and Lactobacillus brevis M4A).

Conclusion

A total of 2 LABs have superior properties. L. lactis subsp. lactis K5 and L. brevis M4A have a high potential to be used in fermentation. They have the potential for further research, such as their effectiveness in fermentation, lignocellulose hydrolysis, feed additives, molecular characterization to detect specific enzymes, and their specific activities.

Life detection in a universe of false positives: Can the Fatal Flaws of Exoplanet Biosignatures be Overcome Absent a Theory of Life?

Astrobiology aims to determine the distribution and diversity of life in the universe. But as the word "biosignature" suggests, what will be detected is not life itself, but an observation implicating living systems. Our limited access to other worlds suggests this observation is more likely to reflect out-of-equilibrium gasses than a writhing octopus. Yet, anything short of a writhing octopus will raise skepticism about what has been detected. Resolving that skepticism requires a theory to delineate processes due to life and those due to abiotic mechanisms. This poses an existential question for life detection: How do astrobiologists plan to detect life on exoplanets via features shared between non-living and living systems? We argue that you cannot without an underlying theory of life. We illustrate this by analyzing the hypothetical detection of an "Earth 2.0" exoplanet. Without a theory of life, we argue the community should focus on identifying unambiguous features of life via four areas: examining life on Earth, building life in the lab, probing the solar system, and searching for technosignatures. Ultimately, we ask, what exactly do astrobiologists hope to learn by searching for life?

Scaling of Protein Function across the Tree of Life

Scaling laws are a powerful way to compare genomes because they put all organisms onto a single curve and reveal nontrivial generalities as genomes change in size. The abundance of functional categories across genomes has previously been found to show power law scaling with respect to the total number of functional categories, suggesting that universal constraints shape genomic category abundance. Here, we look across the tree of life to understand how genome evolution may be related to functional scaling. We revisit previous observations of functional genome scaling with an expanded taxonomy by analyzing 3,726 bacterial, 220 archaeal, and 79 unicellular eukaryotic genomes. We find that for some functional classes, scaling is best described by multiple exponents, revealing previously unobserved shifts in scaling as genome-encoded protein annotations increase or decrease. Furthermore, we find that scaling varies between phyletic groups at both the domain and phyla levels and is less universal than previously thought. This variability in functional scaling is not related to taxonomic phylogeny resolved at the phyla level, suggesting that differences in cell plan or physiology outweigh broad patterns of taxonomic evolution. Since genomes are maintained and replicated by the functional proteins encoded by them, these results point to functional degeneracy between taxonomic groups and unique evolutionary trajectories toward these. We also find that individual phyla frequently span scaling exponents of functional classes, revealing that individual clades can move across scaling exponents. Together, our results reveal unique shifts in functions across the tree of life and highlight that as genomes grow or shrink, proteins of various functions may be added or lost.

Enzyme function and evolution through the lens of bioinformatics

Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.

False Positives and the Challenge of Testing the Alien Hypothesis

The origin of life and the detection of alien life have historically been treated as separate scientific research problems. However, they are not strictly independent. Here, we discuss the need for a better integration of the sciences of life detection and origins of life. Framing these dual problems within the formalism of Bayesian hypothesis testing, we demonstrate via simple examples how high confidence in life detection claims require either (1) a strong prior hypothesis about the existence of life in a particular alien environment, or conversely, (2) signatures of life that are not susceptible to false positives. As a case study, we discuss the role of priors and hypothesis testing in recent results reporting potential detection of life in the venusian atmosphere and in the icy plumes of Enceladus. While many current leading biosignature candidates are subject to false positives because they are not definitive of life, our analyses demonstrate why it is necessary to shift focus to candidate signatures that are definitive. This indicates a necessity to develop methods that lack substantial false positives, by using observables for life that rely on prior hypotheses with strong theoretical and empirical support in identifying defining features of life. Abstract theories developed in pursuit of understanding universal features of life are more likely to be definitive and to apply to life-as-we-don't-know-it. We discuss Molecular Assembly theory as an example of such an observable which is applicable to life detection within the solar system. In the absence of alien examples these are best validated in origin of life experiments, substantiating the need for better integration between origins of life and biosignature science research communities. This leads to a conclusion that extraordinary claims in astrobiology (e.g., definitive detection of alien life) require extraordinary explanations, whereas the evidence itself could be quite ordinary.

Esterase Sequence Composition Patterns for the Identification of Catalytic Triad Microenvironment Motifs

Ester hydrolysis is of wide biomedical interest, spanning from the green synthesis of pharmaceuticals to biomaterials' development. Existing peptide-based catalysts exhibit low catalytic efficiency compared to natural enzymes, due to the conformational heterogeneity of peptides. Moreover, there is lack of understanding of the correlation between the primary sequence and catalytic function. For this purpose, we statistically analyzed 22 EC 3.1 hydrolases with known catalytic triads, characterized by unique and well-defined mechanisms. The aim was to identify patterns at the sequence level that will better inform the creation of short peptides containing important information for catalysis, based on the catalytic triad, oxyanion holes and the triad residues microenvironments. Moreover, fragmentation schemes of the primary sequence of selected enzymes alongside the study of their amino acid frequencies, composition, and physicochemical properties are proposed. The results showed highly conserved catalytic sites with distinct positional patterns and chemical microenvironments that favor catalysis and revealed variations in catalytic site composition that could be useful for the design of minimalistic catalysts.

The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database

The recent development of artificial intelligence provides us with new and powerful tools for studying the mysterious relationship between organism evolution and protein evolution. In this work, based on the AlphaFold Protein Structure Database (AlphaFold DB), we perform comparative analyses of the proteins of different organisms. The statistics of AlphaFold-predicted structures show that, for organisms with higher complexity, their constituent proteins will have larger radii of gyration, higher coil fractions, and slower vibrations, statistically. By conducting normal mode analysis and scaling analyses, we demonstrate that higher organismal complexity correlates with lower fractal dimensions in both the structure and dynamics of the constituent proteins, suggesting that higher functional specialization is associated with higher organismal complexity. We also uncover the topology and sequence bases of these correlations. As the organismal complexity increases, the residue contact networks of the constituent proteins will be more assortative, and these proteins will have a higher degree of hydrophilic-hydrophobic segregation in the sequences. Furthermore, by comparing the statistical structural proximity across the proteomes with the phylogenetic tree of homologous proteins, we show that, statistical structural proximity across the proteomes may indirectly reflect the phylogenetic proximity, indicating a statistical trend of protein evolution in parallel with organism evolution. This study provides new insights into how the diversity in the functionality of proteins increases and how the dimensionality of the manifold of protein dynamics reduces during evolution, contributing to the understanding of the origin and evolution of lives.

A consensus view of the proteome of the last universal common ancestor

The availability of genomic and proteomic data from across the tree of life has made it possible to infer features of the genome and proteome of the last universal common ancestor (LUCA). A number of studies have done so, all using a unique set of methods and bioinformatics databases. Here, we compare predictions across eight such studies and measure both their agreement with one another and with the consensus predictions among them. We find that some LUCA genome studies show a strong agreement with the consensus predictions of the others, but that no individual study shares a high or even moderate degree of similarity with any other individual study. From these observations, we conclude that the consensus among studies provides a more accurate depiction of the core proteome of the LUCA and its functional repertoire. The set of consensus LUCA protein family predictions between all of these studies portrays a LUCA genome that, at minimum, encoded functions related to protein synthesis, amino acid metabolism, nucleotide metabolism, and the use of common, nucleotide-derived organic cofactors.

Schrödinger and the Possible Existence of Different Types of Life

Eighty years ago, Nobel Prize-winner physicist Erwin Schrödinger gave three lectures in Dublin’s Trinity College, titled What is Life? The physical aspect of the living cell to explain life in terms of the chemistry and physics laws. Life definitions rely on the cellular theory, which poses in the first place that life is made up of cells. The recent discovery of giant viruses, along with the development of synthetic cells at the beginning of century 21st, has challenged the current idea of what life is. Thus, rather than having arrived at a close answer to Schrödinger’s question, modern biology has touched down at a novel scenario in which several types of life—as opposed to only one—actually might exist on Earth and possibly the Universe. Eighty years after the Dublin lectures, the Schrödinger question could be: “What are lives”?