Essential metabolism for a minimal cell

The design and engineering of synthetic genomes

Synthetic genomics seeks to design and construct entire genomes to mechanistically dissect fundamental questions of genome function and to engineer organisms for diverse applications, including bioproduction of high-value chemicals and biologics, advanced cell therapies, and stress-tolerant crops. Recent progress has been fuelled by advancements in DNA synthesis, assembly, delivery and editing. Computational innovations, such as the use of artificial intelligence to provide prediction of function, also provide increasing capabilities to guide synthetic genome design and construction. However, translating synthetic genome-scale projects from idea to implementation remains highly complex. Here, we aim to streamline this implementation process by comprehensively reviewing the strategies for design, construction, delivery, debugging and tailoring of synthetic genomes as well as their potential applications.

Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity

Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechanisms and interactions. Advances in structural biology and molecular simulations have revealed how protein systems respond to changes in their environments, such as ligand binding, stress conditions, or perturbations like mutations and post-translational modifications, influencing signal transduction and cellular phenotypes. Here, we discuss how computational approaches, ranging from molecular dynamics (MD) simulations to AI-driven methods, are instrumental in studying protein dynamics from isolated molecules to large assemblies. These techniques elucidate conformational landscapes, ligand-binding mechanisms, and protein-protein interactions and are starting to support the construction of multiscale realistic representations of highly complex systems, ranging up to whole cell models. With cryo-electron microscopy, cryo-electron tomography, and AlphaFold accelerating the structural characterization of protein networks, we suggest that integrating AI and Machine Learning with multiscale MD methods will enhance fundamental understating for systems of ever-increasing complexity, usher in exciting possibilities for predictive modeling of the behavior of cell compartments or even whole cells. These advances are indeed transforming biophysics and chemical biology, offering new opportunities to study biomolecular mechanisms at atomic resolution.

Robust and highly efficient transformation method for a minimal mycoplasma cell

Mycoplasmas have been widely investigated for their pathogenicity, as well as for genomics and synthetic biology. Conventionally, transformation of mycoplasmas was not highly efficient, and due to the low transformation efficiency, large amounts of DNA and recipient cells were required for that purpose. Here, we report a robust and highly efficient transformation method for the minimal cell JCVI-syn3B, which was created through streamlining the genome of Mycoplasma mycoides. When the growth states of JCVI-syn3B were examined in detail by focusing on such factors as pH, color, absorbance, colony forming unit, and transformation efficiency, it was found that the growth phase after the lag phase can be divided into three distinct phases, of which the highest transformation efficiency was observed during the early exponential growth phase. Notably, the transformation efficiency of up to 4.4 × 10-2 transformants per cell per microgram of plasmid DNA was obtained. A method to obtain several hundred to several thousand transformants with less than 0.2 mL of culture with approximately 1 × 107-108 cells and 10 ng of plasmid DNA was developed. Moreover, a transformation method using a frozen stock of transformation-ready cells was established. These procedures and information could simplify and enhance the transformation process of minimal cells, facilitating advanced genetic engineering and biological research using minimal cells.

IMPORTANCE

Mycoplasmas are parasitic and pathogenic bacteria for many animals. They are also useful bacteria to understand the cellular process of life and for bioengineering because of their simple metabolism, small genomes, and cultivability. Genetic manipulation is crucial for these purposes, but transformation efficiency in mycoplasmas is typically quite low. Here, we report a highly efficient transformation method for the minimal genome mycoplasma JCVI-syn3B. Using this method, transformants can be obtained with only 10 ng of plasmid DNA, which is around one-thousandth of the amount required for traditional mycoplasma transformations. Moreover, a convenient method using frozen stocks of transformation-ready cells was established. These improved methods play a crucial role in further studies using minimal cells.

The Transformation Experiment of Frederick Griffith I: Its Narrowing and Potential for the Creation of Novel Microorganisms

The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely related. One reason for this limitation of the "creative potential" of "classical" transformation is the requirement for adequate "fitting" of newly synthesized polypeptide components, directed by the donor genome, to interacting counterparts encoded by the pre-existing acceptor genome. Transformation was introduced in 1928 by Frederick Griffith in the course of the demonstration of the instability of pneumococci and their conversion from rough, non-pathogenic into smooth, virulent variants. Subsequently, this method turned out to be critical for the identification of DNA as the sole matter of inheritance. Importantly, the initial experimental design (1.0) also considered the inheritance of both structural (e.g., plasma membranes) and cybernetic information (e.g., metabolite fluxes), which, in cooperation, determine topological and cellular heredity, as well as fusion and blending of bacterial cells. In contrast, subsequent experimental designs (1.X) were focused on the use of whole-cell homogenates and, thereafter, of soluble and water-clear fractions deprived of all information and macromolecules other than those directing protein synthesis, including outer-membrane vesicles, bacterial prions, lipopolysaccharides, lipoproteins, cytoskeletal elements, and complexes thereof. Identification of the reasons for this narrowing may be helpful in understanding the potential of transformation for the creation of novel microorganisms.

Learning maximally spanning representations improves protein function annotation

Automated protein function annotation is a fundamental problem in computational biology, crucial for understanding the functional roles of proteins in biological processes, with broad implications in medicine and biotechnology. A persistent challenge in this problem is the imbalanced, long-tail distribution of available function annotations: a small set of well-studied function classes account for most annotated proteins, while many other classes have few annotated proteins, often due to investigative bias, experimental limitations, or intrinsic biases in protein evolution. As a result, existing machine learning models for protein function prediction tend to only optimize the prediction accuracy for well-studied function classes overrepresented in the training data, leading to poor accuracy for understudied functions. In this work, we develop MSRep, a novel deep learning-based protein function annotation framework designed to address this imbalance issue and improve annotation accuracy. MSRep is inspired by an intriguing phenomenon, called neural collapse (NC), commonly observed in high-accuracy deep neural networks used for classification tasks, where hidden representations in the final layer collapse to class-specific mean embeddings, while maintaining maximal inter-class separation. Given that NC consistently emerges across diverse architectures and tasks for high-accuracy models, we hypothesize that inducing NC structure in models trained on imbalanced data can enhance both prediction accuracy and generalizability. To achieve this, MSRep refines a pre-trained protein language model to produce NC-like representations by optimizing an NC-inspired loss function, which ensures that minority functions are equally represented in the embedding space as majority functions, in contrast to conventional classification methods whose embedding spaces are dominated by overrepresented classes. In evaluations across four protein function annotation tasks on the prediction of Enzyme Commission numbers, Gene3D codes, Pfam families, and Gene Ontology terms, MSRep demonstrates superior predictive performance for both well- and underrepresented classes, outperforming several state-of-the-art annotation tools. We anticipate that MSRep will enhance the annotation of understudied functions and novel, uncharacterized proteins, advancing future protein function studies and accelerating the discovery of new functional proteins. The source code of MSRep is available at https://github.com/luo-group/MSRep.

A sweeping view of avian mycoplasmas biology drawn from comparative genomic analyses

BACKGROUND

Avian mycoplasmas are small bacteria associated with several pathogenic conditions in many wild and poultry bird species. Extensive genomic data are available for many avian mycoplasmas, yet no comparative studies focusing on this group of mycoplasmas have been undertaken so far.

RESULTS

Here, based on the comparison of forty avian mycoplasma genomes belonging to ten different species, we provide insightful information on the phylogeny, pan/core genome, energetic metabolism, and virulence of these avian pathogens. Analyses disclosed considerable inter- and intra-species genomic variabilities, with genome sizes that can vary by twice as much. Phylogenetic analysis based on concatenated orthologous genes revealed that avian mycoplasmas fell into either Hominis or Pneumoniae groups within the Mollicutes and could split into various clusters. No host co-evolution of avian mycoplasmas can be inferred from the proposed phylogenetic scheme. With 3,237 different gene clusters, the avian mycoplasma group under study proved diverse enough to have an open pan genome. However, a set of 150 gene clusters was found to be shared between all avian mycoplasmas, which is likely encoding essential functions. Comparison of energy metabolism pathways showed that avian mycoplasmas rely on various sources of energy. Superposition between phylogenetic and energy metabolism groups revealed that the glycolytic mycoplasmas belong to two distinct phylogenetic groups (Hominis and Pneumoniae), while all the arginine-utilizing mycoplasmas belong only to Hominis group. This can stand for different evolutionary strategies followed by avian mycoplasmas and further emphasizes the diversity within this group. Virulence determinants survey showed that the involved gene arsenals vary significantly within and between species, and could even be found in species often reported apathogenic. Immunoglobulin-blocking proteins were detected in almost all avian mycoplasmas. Although these systems are not exclusive to this group, they seem to present some particular features making them unique among mycoplasmas.

CONCLUSION

This comparative genomic study uncovered the significant variable nature of avian mycoplasmas, furthering our knowledge on their biological attributes and evoking new hallmarks.

Improving the Annotations of JCVI-Syn3a Proteins

The JCVI-Syn3 organism is a minimal organism derived from Mycoplasma mycoides capri, which is capable of self-replication. While the ancestor has 863 genes, the synthetic progeny has only 473, with 434 of these coding for proteins. Despite initial efforts to understand all functions of the organism, a significant number of these protein-coding genes still have unknown functions, and subsequent studies have been only partially successful in elucidating their roles. In this study, we employ our innovative method PROST to identify homologs and better understand these previously unidentified genes. PROST employs protein language embeddings and enables the identification of remote homologs with as low as 16% sequence identity. PROST successfully finds functionally annotated homologs for 93% of the minimal genome with a high level of accuracy, both confirming previously identified functions, as well as proposing new functions for others. The results of our study can be accessed at https://bit.ly/prost-syn3a .

Biomimetic Materials to Fabricate Artificial Cells

As the foundation of life, a cell is generally considered an advanced microreactor with a complicated structure and function. Undeniably, this fascinating complexity motivates scientists to try to extricate themselves from natural living matter and work toward rebuilding artificial cells in vitro. Driven by synthetic biology and bionic technology, the research of artificial cells has gradually become a subclass. It is not only held import in many disciplines but also of great interest in its synthesis. Therefore, in this review, we have reviewed the development of cell and bionic strategies and focused on the efforts of bottom-up strategies in artificial cell construction. Different from starting with existing living organisms, we have also discussed the construction of artificial cells based on biomimetic materials, from simple cell scaffolds to multiple compartment systems, from the construction of functional modules to the simulation of crucial metabolism behaviors, or even to the biomimetic of communication networks. All of them could represent an exciting advance in the field. In addition, we will make a rough analysis of the bottlenecks in this field. Meanwhile, the future development of this field has been prospecting. This review may bridge the gap between materials engineering and life sciences, forming a theoretical basis for developing various life-inspired assembly materials.

Capsular Polysaccharide Production in Bacteria of the Mycoplasma Genus: A Huge Diversity of Pathways and Synthases for So-Called Minimal Bacteria

Mycoplasmas are wall-less bacteria with many species spread across various animal hosts in which they can be pathogenic. Despite their reduced anabolic capacity, some mycoplasmas are known to secrete hetero- and homopolysaccharides, which play a role in host colonization through biofilm formation or immune evasion, for instance. This study explores how widespread the phenomenon of capsular homopolysaccharide secretion is within mycoplasmas, and investigates the diversity of both the molecules produced and the synthase-type glycosyltransferases responsible for their production. Fourteen strains representing 14 (sub)species from four types of hosts were tested in vitro for their polysaccharide secretion using both specific (immunodetection) and nonspecific (sugar dosage) assays. We evidenced a new, atypical homopolymer of β-(1 → 6)-glucofuranose (named glucofuranan) in the human pathogen Mycoplasma (M.) fermentans, as well as a β-(1 → 6)-glucopyranose polymer for the turkey pathogen M. iowae and galactan (β-(1 → 6)-galactofuranose) and β-(1 → 2)-glucopyranose for M. bovigenitalium infecting ruminants. Sequence and phylogenetic analyses revealed a huge diversity of synthases from varied Mycoplasma species. The clustering of these membrane-embedded glycosyltransferases into three main groups was only partially correlated to the structure of the produced homopolysaccharides.

A tuneable minimal cell membrane reveals that two lipid species suffice for life

All cells are encapsulated by a lipid membrane that facilitates their interactions with the environment. How cells manage diverse mixtures of lipids, which dictate membrane property and function, is experimentally challenging to address. Here, we present an approach to tune and minimize membrane lipid composition in the bacterium Mycoplasma mycoides and its derived 'minimal cell' (JCVI-Syn3A), revealing that a two-component lipidome can support life. Systematic reintroduction of phospholipids with different features demonstrates that acyl chain diversity is more important for growth than head group diversity. By tuning lipid chirality, we explore the lipid divide between Archaea and the rest of life, showing that ancestral lipidomes could have been heterochiral. However, in these simple organisms, heterochirality leads to impaired cellular fitness. Thus, our approach offers a tunable minimal membrane system to explore the fundamental lipidomic requirements for life, thereby extending the concept of minimal life from the genome to the lipidome.

Discovery of deep-sea coral symbionts from a novel clade of marine bacteria with severely reduced genomes

Microbes perform critical functions in corals, yet most knowledge is derived from the photic zone. Here, we discover two mollicutes that dominate the microbiome of the deep-sea octocoral, Callogorgia delta, and likely reside in the mesoglea. These symbionts are abundant across the host's range, absent in the water, and appear to be rare in sediments. Unlike other mollicutes, they lack all known fermentative capabilities, including glycolysis, and can only generate energy from arginine provided by the coral host. Their genomes feature several mechanisms to interact with foreign DNA, including extensive CRISPR arrays and restriction-modification systems, which may indicate their role in symbiosis. We propose the novel family Oceanoplasmataceae which includes these symbionts and others associated with five marine invertebrate phyla. Its exceptionally broad host range suggests that the diversity of this enigmatic family remains largely undiscovered. Oceanoplasmataceae genomes are the most highly reduced among mollicutes, providing new insight into their reductive evolution and the roles of coral symbionts.

Minimisation of metabolic networks defines a new functional class of genes

Construction of minimal metabolic networks (MMNs) contributes both to our understanding of the origins of metabolism and to the efficiency of biotechnological processes by preventing the diversion of flux away from product formation. We have designed MMNs using a novel in silico synthetic biology pipeline that removes genes encoding enzymes and transporters from genome-scale metabolic models. The resulting minimal gene-set still ensures both viability and high growth rates. The composition of these MMNs has defined a new functional class of genes termed Network Efficiency Determinants (NEDs). These genes, whilst not essential, are very rarely eliminated in constructing an MMN, suggesting that it is difficult for metabolism to be re-routed to obviate the need for such genes. Moreover, the removal of NED genes from an MMN significantly reduces its global efficiency. Bioinformatic analyses of the NED genes have revealed that not only do these genes have more genetic interactions than the bulk of metabolic genes but their protein products also show more protein-protein interactions. In yeast, NED genes are predominantly single-copy and are highly conserved across evolutionarily distant organisms. These features confirm the importance of the NED genes to the metabolic network, including why they are so rarely excluded during minimisation.

A tuneable minimal cell membrane reveals that two lipid species suffice for life

All cells are encapsulated by a lipid membrane which facilitates the interaction between life and its environment. How life exploits the diverse mixtures of lipids that dictate membrane property and function has been experimentally challenging to address. We introduce an approach to tune and minimize lipidomes in Mycoplasma mycoides and the Minimal Cell (JCVI-Syn3A) revealing that a 2-component lipidome can support life. Systematically reintroducing phospholipid features demonstrated that acyl chain diversity is more critical for growth than head group diversity. By tuning lipid chirality, we explored the lipid divide between Archaea and the rest of life, showing that ancestral lipidomes could have been heterochiral. Our approach offers a tunable minimal membrane system to explore the fundamental lipidomic requirements for life, thereby extending the concept of minimal life from the genome to the lipidome.

Reduction-to-synthesis: the dominant approach to genome-scale synthetic biology

Advances in systems and synthetic biology have propelled the construction of reduced bacterial genomes. Genome reduction was initially focused on exploring properties of minimal genomes, but more recently it has been deployed as an engineering strategy to enhance strain performance. This review provides the latest updates on reduced genomes, focusing on dual-track approaches of top-down reduction and bottom-up synthesis for their construction. Using cases from studies that are based on established industrial workhorse strains, we discuss the construction of a series of synthetic phenotypes that are candidates for biotechnological applications. Finally, we address the possible uses of reduced genomes for biotechnological applications and the needed future research directions that may ultimately lead to the total synthesis of rationally designed genomes.

Genome engineering on size reduction and complexity simplification: A review

BACKGROUND

Genome simplification is an important topic in the field of life sciences that has attracted attention from its conception to the present day. It can help uncover the essential components of the genome and, in turn, shed light on the underlying operating principles of complex biological systems. This has made it a central focus of both basic and applied research in the life sciences. With the recent advancements in related technologies and our increasing knowledge of the genome, now is an opportune time to delve into this topic.

AIM OF REVIEW

Our review investigates the progress of genome simplification from two perspectives: genome size reduction and complexity simplification. In addition, we provide insights into the future development trends of genome simplification.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Reducing genome size requires eliminating non-essential elements as much as possible. This process has been facilitated by advances in genome manipulation and synthesis techniques. However, we still need a better and clearer understanding of living systems to reduce genome complexity. As there is a lack of quantitative and clearly defined standards for this task, we have opted to approach the topic from various perspectives and present our findings accordingly.

Selectively advantageous instability in biotic and pre-biotic systems and implications for evolution and aging

Rules of biology typically involve conservation of resources. For example, common patterns such as hexagons and logarithmic spirals require minimal materials, and scaling laws involve conservation of energy. Here a relationship with the opposite theme is discussed, which is the selectively advantageous instability (SAI) of one or more components of a replicating system, such as the cell. By increasing the complexity of the system, SAI can have benefits in addition to the generation of energy or the mobilization of building blocks. SAI involves a potential cost to the replicating system for the materials and/or energy required to create the unstable component, and in some cases, the energy required for its active degradation. SAI is well-studied in cells. Short-lived transcription and signaling factors enable a rapid response to a changing environment, and turnover is critical for replacement of damaged macromolecules. The minimal gene set for a viable cell includes proteases and a nuclease, suggesting SAI is essential for life. SAI promotes genetic diversity in several ways. Toxin/antitoxin systems promote maintenance of genes, and SAI of mitochondria facilitates uniparental transmission. By creating two distinct states, subject to different selective pressures, SAI can maintain genetic diversity. SAI of components of synthetic replicators favors replicator cycling, promoting emergence of replicators with increased complexity. Both classical and recent computer modeling of replicators reveals SAI. SAI may be involved at additional levels of biological organization. In summary, SAI promotes replicator genetic diversity and reproductive fitness, and may promote aging through loss of resources and maintenance of deleterious alleles.

Experimental evolution for the recovery of growth loss due to genome reduction

As the genome encodes the information crucial for cell growth, a sizeable genomic deficiency often causes a significant decrease in growth fitness. Whether and how the decreased growth fitness caused by genome reduction could be compensated by evolution was investigated here. Experimental evolution with an Escherichia coli strain carrying a reduced genome was conducted in multiple lineages for approximately 1000 generations. The growth rate, which largely declined due to genome reduction, was considerably recovered, associated with the improved carrying capacity. Genome mutations accumulated during evolution were significantly varied across the evolutionary lineages and were randomly localized on the reduced genome. Transcriptome reorganization showed a common evolutionary direction and conserved the chromosomal periodicity, regardless of highly diversified gene categories, regulons, and pathways enriched in the differentially expressed genes. Genome mutations and transcriptome reorganization caused by evolution, which were found to be dissimilar to those caused by genome reduction, must have followed divergent mechanisms in individual evolutionary lineages. Gene network reconstruction successfully identified three gene modules functionally differentiated, which were responsible for the evolutionary changes of the reduced genome in growth fitness, genome mutation, and gene expression, respectively. The diversity in evolutionary approaches improved the growth fitness associated with the homeostatic transcriptome architecture as if the evolutionary compensation for genome reduction was like all roads leading to Rome.

Minimal Bacterial Cell JCVI-syn3B as a Chassis to Investigate Interactions between Bacteria and Mammalian Cells

Mycoplasmas are atypical bacteria with small genomes that necessitate colonization of their respective animal or plant hosts as obligate parasites, whether as pathogens, or commensals. Some can grow axenically in specialized complex media yet show only host-cell-dependent growth in cell culture, where they can survive chronically and often through interactions involving surface colonization or internalization. To develop a mycoplasma-based system to identify genes mediating such interactions, we exploited genetically tractable strains of the goat pathogen Mycoplasma mycoides (Mmc) with synthetic designer genomes representing the complete natural organism (minus virulence factors; JCVI-syn1.0) or its reduced counterpart (JCVI-syn3B) containing only those genes supporting axenic growth. By measuring growth of surviving organisms, physical association with cultured human cells (HEK-293T, HeLa), and induction of phagocytosis by human myeloid cells (dHL-60), we determined that JCVI-syn1.0 contained a set of eight genes (MMSYN1-0179 to MMSYN1-0186, dispensable for axenic growth) conferring survival, attachment, and phagocytosis phenotypes. JCVI-syn3B lacked these phenotypes, but insertion of these genes restored cell attachment and phagocytosis, although not survival. These results indicate that JCVI-syn3B may be a powerful living platform to analyze the role of specific gene sets, from any organism, on the interaction with diverse mammalian cells in culture.

The synthetic future of algal genomes

Algae are diverse organisms with significant biotechnological potential for resource circularity. Taking inspiration from fermentative microbes, engineering algal genomes holds promise to broadly expand their application ranges. Advances in genome sequencing with improvements in DNA synthesis and delivery techniques are enabling customized molecular tool development to confer advanced traits to algae. Efforts to redesign and rebuild entire genomes to create fit-for-purpose organisms currently being explored in heterotrophic prokaryotes and eukaryotic microbes could also be applied to photosynthetic algae. Future algal genome engineering will enhance yields of native products and permit the expression of complex biochemical pathways to produce novel metabolites from sustainable inputs. We present a historical perspective on advances in engineering algae, discuss the requisite genetic traits to enable algal genome optimization, take inspiration from whole-genome engineering efforts in other microbes for algal systems, and present candidate algal species in the context of these engineering goals.

The minimum energy required to build a cell

Understanding the energy requirements for cell synthesis accurately and comprehensively has been a longstanding challenge. We introduce a computational model that estimates the minimum energy necessary to build any cell from its constituent parts. This method combines omics and internal cell compositions from various sources to calculate the Gibbs Free Energy of biosynthesis independently of specific metabolic pathways. Our public tool, Synercell, can be used with other models for minumum species-specific energy estimations in any well-sequenced species. The energy for synthesising the genome, transcriptome, proteome, and lipid bilayer of four cell types: Escherichia coli, Saccharomyces cerevisiae, an average mammalian cell and JCVI-syn3A were estimated. Their modelled minimum synthesis energies at 298 K were 9.54 × 10 - 11 J/cell, 4.99 × 10 - 9 J/cell, 3.71 × 10 - 7 J/cell and 3.69 × 10 - 12 respectively. Gram-for-gram synthesis of lipid bilayers requires the most energy, followed by the proteome, genome, and transcriptome. The average per gram cost of biomass synthesis is in the 300s of J/g for all four cells. Implications for the generalisability of cell construction and applications to biogeosciences, cellular biology, biotechnology, and astrobiology are discussed.

Decoding semiotic minimal genome: a non-genocentric approach

The search for the minimum information required for an organism to sustain a cellular system network has rendered both the identification of a fixed number of known genes and those genes whose function remains to be identified. The approaches used in such search generally focus their analysis on coding genomic regions, based on the genome to proteic-product perspective. Such approaches leave other fundamental processes aside, mainly those that include higher-level information management. To cope with this limitation, a non-genocentric approach based on genomic sequence analysis using language processing tools and gene ontology may prove an effective strategy for the identification of those fundamental genomic elements for life autonomy. Additionally, this approach will provide us with an integrative analysis of the information value present in all genomic elements, regardless of their coding status.

Mesoplasma florum: a near-minimal model organism for systems and synthetic biology

Mesoplasma florum is an emerging model organism for systems and synthetic biology due to its small genome (∼800 kb) and fast growth rate. While M. florum was isolated and first described almost 40 years ago, many important aspects of its biology have long remained uncharacterized due to technological limitations, the absence of dedicated molecular tools, and since this bacterial species has not been associated with any disease. However, the publication of the first M. florum genome in 2004 paved the way for a new era of research fueled by the rise of systems and synthetic biology. Some of the most important studies included the characterization and heterologous use of M. florum regulatory elements, the development of the first replicable plasmids, comparative genomics and transposon mutagenesis, whole-genome cloning in yeast, genome transplantation, in-depth characterization of the M. florum cell, as well as the development of a high-quality genome-scale metabolic model. The acquired data, knowledge, and tools will greatly facilitate future genome engineering efforts in M. florum, which could next be exploited to rationally design and create synthetic cells to advance fundamental knowledge or for specific applications.

Recent advances in the characterization of essential genes and development of a database of essential genes

Over the past few decades, there has been a significant interest in the study of essential genes, which are crucial for the survival of an organism under specific environmental conditions and thus have practical applications in the fields of synthetic biology and medicine. An increasing amount of experimental data on essential genes has been obtained with the continuous development of technological methods. Meanwhile, various computational prediction methods, related databases and web servers have emerged accordingly. To facilitate the study of essential genes, we have established a database of essential genes (DEG), which has become popular with continuous updates to facilitate essential gene feature analysis and prediction, drug and vaccine development, as well as artificial genome design and construction. In this article, we summarized the studies of essential genes, overviewed the relevant databases, and discussed their practical applications. Furthermore, we provided an overview of the main applications of DEG and conducted comprehensive analyses based on its latest version. However, it should be noted that the essential gene is a dynamic concept instead of a binary one, which presents both opportunities and challenges for their future development.

Replicating Chromosomes in Whole-Cell Models of Bacteria

Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication of genetic material. In a recent study, we presented a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics. This approach was used to investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell cycle. To achieve cell-scale chromosome structures that are realistic, we modeled the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. Additionally, the polymer interacts with ribosomes distributed according to cryo-electron tomograms of Syn3A. The polymer model was further augmented by computational models of loop extrusion by structural maintenance of chromosomes (SMC) protein complexes and topoisomerase action, and the modeling and analysis of multi-fork replication states.

Chemical Reaction Models in Synthetic Promoter Design in Bacteria

We discuss the formalism of chemical reaction networks (CRNs) as a computer-aided design interface for using formal methods in engineering living technologies. We set out by reviewing formal methods within a broader view of synthetic biology. Based on published results, we illustrate, step by step, how mathematical and computational techniques on CRNs can be used to study the structural and dynamic properties of the designed systems. As a case study, we use an E. coli two-component system that relays the external inorganic phosphate concentration signal to genetic components. We show how CRN models can scan and explore phenotypic regimes of synthetic promoters with varying detection thresholds, thereby providing a means for fine-tuning the promoter strength to match the specification.

Integrative modeling of JCVI-Syn3A nucleoids with a modular approach

A lattice-based method is presented for creating 3D models of entire bacterial nucleoids integrating ultrastructural information cryoelectron tomography, genomic and proteomic data, and experimental atomic structures of biomolecules and assemblies. The method is used to generate models of the minimal genome bacterium JCVI-Syn3A, producing a series of models that test hypotheses about transcription, condensation, and overall distribution of the genome. Lattice models are also used to generate atomic models of an entire JCVI-Syn3A cell.

Concepts of a synthetic minimal cell: Information molecules, metabolic pathways, and vesicle reproduction

How do the living systems emerge from non-living molecular assemblies? What physical and chemical principles supported the process? To address these questions, a promising strategy is to artificially reconstruct living cells in a bottom-up way. Recently, the authors developed the "synthetic minimal cell" system showing recursive growth and division cycles, where the concepts of information molecules, metabolic pathways, and cell reproduction were artificially and concisely redesigned with the vesicle-based system. We intentionally avoided using the sophisticated molecular machinery of the biological cells and tried to redesign the cells in the simplest forms. This review focuses on the similarities and differences between the biological cells and our synthetic minimal cell concerning each concept of cells. Such comparisons between natural and artificial cells will provide insights on how the molecules should be assembled to create living systems to the wide readers in the field of synthetic biology, artificial cells, and protocells research. This review article is an extended version of the Japanese article "Growth and division of vesicles coupled with information molecules," published in SEIBUTSU-BUTSURI vol. 61, p. 378-381 (2021).

Comparative untargeted and targeted metabonomics reveal discriminations in metabolite profiles between Mycoplasma capricolum subsp. capripneumoniae and Mycoplasma capricolum subsp. capricolum

Background

Mycoplasmas are among the smallest prokaryotic microbes that can grow and proliferate on non-living media. They have reduced genomes, which may be associated with a concomitant reduction in their metabolic capacity. Mycoplasma capricolum subsp. capripneumoniae (Mccp) and Mycoplasma capricolum subsp. capricolum (Mcc), both belong to the Mycoplasma mycoides cluster, are significant important pathogenic Mycoplasma species in veterinary research field. They share high degree of genome homology but Mcc grows markedly faster and has higher growth titer than Mccp.

Methods

This study investigated the metabolites of these two pathogenic bacteria from the middle and late stages of the logarithmic growth phase through liquid chromatography-mass spectrometry-based metabolomics and targeted energy metabolomics. The multivariate analysis was conducted to identify significant differences between the two important Mycoplasma species.

Results

A total of 173 metabolites were identified. Of them, 33 and 34 metabolites involved in purine and pyrimidine, pyruvate metabolism, and amino acid synthesis were found to significantly differ in the middle and late stages, respectively. The abundance of fructose 1,6-bisphosphate, ADP, and pyruvate was higher in Mcc than in Mccp during the whole logarithmic period. Lactate was upregulated in slow-growing Mccp. The pH buffering agent N-[2-hydroxyethyl]piperazine-N'-[2-ethanesulfonic acid] added to media effectively prevented pH reduction and increase bacterial viability and protein biomass. The multivariate analysis revealed that the two Mycoplasma species significantly differed in glucose metabolism, growth factor transport and metabolism, cholesterol utilization, and environmental regulation.

Conclusion

The study data are beneficial for understanding the metabolomic characteristics of these two crucial Mycoplasma species and shedding more light on mycoplasma metabolism, and serve as a resource for the pathogenesis and development of related vaccines.

Evaluation of a Method for Standardized Antimicrobial Susceptibility Testing with Mycoplasma hyorhinis Field Isolates

Organizations like the Clinical and Laboratory Standards Institute (CLSI) or the European Committee of Antimicrobial Susceptibility Testing (EUCAST) provide standardized methodologies for antimicrobial susceptibility testing of a wide range of nonfastidious and fastidious bacteria, but so far not for Mycoplasma spp. of animal origin. Recently, a proposed method for the standardized broth microdilution testing of Mycoplasma hyorhinis using commercial Sensititre microtiter plates was presented. In this study, we evaluated this broth microdilution method with 37 field isolates and tested their susceptibility toward the following antimicrobial agents: doxycycline, enrofloxacin, erythromycin, florfenicol, gentamicin, marbofloxacin, tetracycline, tiamulin, tilmicosin, tulathromycin, and tylosin. The isolates originated from different countries, isolation sites, and years. The broth microdilution method was carried out using a modified Friis broth as the culture and test medium. For macrolides and lincosamides, a bimodal distribution with elevated MIC values could be observed for almost half of the tested field isolates, deducing reduced susceptibility toward these substances. With a recently published protocol, we were able to test a variety of field isolates, and consistent data could be obtained. Using this method, monitoring studies of Mycoplasma hyorhinis isolates can be carried out in a comparable manner, and the observed susceptibility profiles can be screened for possible changes in MIC values in the future.

Epistemology of synthetic biology: a new theoretical framework based on its potential objects and objectives

Synthetic biology is a new research field which attempts to understand, modify, and create new biological entities by adopting a modular and systemic conception of the living organisms. The development of synthetic biology has generated a pluralism of different approaches, bringing together a set of heterogeneous practices and conceptualizations from various disciplines, which can lead to confusion within the synthetic biology community as well as with other biological disciplines. I present in this manuscript an epistemological analysis of synthetic biology in order to better define this new discipline in terms of objects of study and specific objectives. First, I present and analyze the principal research projects developed at the foundation of synthetic biology, in order to establish an overview of the practices in this new emerging discipline. Then, I analyze an important scientometric study on synthetic biology to complete this overview. Afterwards, considering this analysis, I suggest a three-level classification of the object of study for synthetic biology (which are different kinds of living entities that can be built in the laboratory), based on three successive criteria: structural hierarchy, structural origin, functional origin. Finally, I propose three successively linked objectives in which synthetic biology can contribute (where the achievement of one objective led to the development of the other): interdisciplinarity collaboration (between natural, artificial, and theoretical sciences), knowledge of natural living entities (past, present, future, and alternative), pragmatic definition of the concept of "living" (that can be used by biologists in different contexts). Considering this new theoretical framework, based on its potential objects and objectives, I take the position that synthetic biology has not only the potential to develop its own new approach (which includes methods, objects, and objectives), distinct from other subdisciplines in biology, but also the ability to develop new knowledge on living entities.

Comparative genomics hints at dispensability of multiple essential genes in two Escherichia coli L-form strains

Despite the critical role of bacterial cell walls in maintaining cell shapes, certain environmental stressors can induce the transition of many bacterial species into a wall-deficient state called L-form. Long-term induced Escherichia coli L-forms lose their rod shape and usually hold significant mutations that affect cell division and growth. Besides this, the genetic background of L-form bacteria is still poorly understood. In the present study, the genomes of two stable L-form strains of E. coli (NC-7 and LWF+) were sequenced and their gene mutation status was determined and compared with their parental strains. Comparative genomic analysis between two L-forms reveals both unique adaptions and common mutated genes, many of which belong to essential gene categories not involved in cell wall biosynthesis, indicating that L-form genetic adaptation impacts crucial metabolic pathways. Missense variants from L-forms and Lenski's long-term evolution experiment (LTEE) were analyzed in parallel using an optimized DeepSequence pipeline to investigate predicted mutation effects (α) on protein functions. We report that the two L-form strains analyzed display a frequency of 6-10% (0% for LTEE) in mutated essential genes where the missense variants have substantial impact on protein functions (α<0.5). This indicates the emergence of different survival strategies in L-forms through changes in essential genes during adaptions to cell wall deficiency. Collectively, our results shed light on the detailed genetic background of two E. coli L-forms and pave the way for further investigations of the gene functions in L-form bacterial models.

Adaptive evolution of a minimal organism with a synthetic genome

The bacterial strain JCVI-syn3.0 stands as the first example of a living organism with a minimized synthetic genome, derived from the Mycoplasma mycoides genome and chemically synthesized in vitro. Here, we report the experimental evolution of a syn3.0- derived strain. Ten independent replicates were evolved for several hundred generations, leading to growth rate improvements of > 15%. Endpoint strains possessed an average of 8 mutations composed of indels and SNPs, with a pronounced C/G- > A/T transversion bias. Multiple genes were repeated mutational targets across the independent lineages, including phase variable lipoprotein activation, 5 distinct; nonsynonymous substitutions in the same membrane transporter protein, and inactivation of an uncharacterized gene. Transcriptomic analysis revealed an overall tradeoff reflected in upregulated ribosomal proteins and downregulated DNA and RNA related proteins during adaptation. This work establishes the suitability of synthetic, minimal strains for laboratory evolution, providing a means to optimize strain growth characteristics and elucidate gene functionality.

Dynamics of chromosome organization in a minimal bacterial cell

Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication and inheritance of genetic material. By creating a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics, we investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell-cycle. To achieve cell-scale chromosome structures that are realistic, we model the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. In addition, the conformations of the circular DNA must avoid overlapping with ribosomes identitied in cryo-electron tomograms. While Syn3A lacks the complex regulatory systems known to orchestrate chromosome segregation in other bacteria, its minimized genome retains essential loop-extruding structural maintenance of chromosomes (SMC) protein complexes (SMC-scpAB) and topoisomerases. Through implementing the effects of these proteins in our simulations of replicating chromosomes, we find that they alone are sufficient for simultaneous chromosome segregation across all generations within nested theta structures. This supports previous studies suggesting loop-extrusion serves as a near-universal mechanism for chromosome organization within bacterial and eukaryotic cells. Furthermore, we analyze ribosome diffusion under the influence of the chromosome and calculate in silico chromosome contact maps that capture inter-daughter interactions. Finally, we present a methodology to map the polymer model of the chromosome to a Martini coarse-grained representation to prepare molecular dynamics models of entire Syn3A cells, which serves as an ultimate means of validation for cell states predicted by the WCM.

Reconstruction of the last bacterial common ancestor from 183 pangenomes reveals a versatile ancient core genome

BACKGROUND

Cumulative sequencing efforts have yielded enough genomes to construct pangenomes for dozens of bacterial species and elucidate intraspecies gene conservation. Given the diversity of organisms for which this is achievable, similar analyses for ancestral species are feasible through the integration of pangenomics and phylogenetics, promising deeper insights into the nature of ancient life.

RESULTS

We construct pangenomes for 183 bacterial species from 54,085 genomes and identify their core genomes using a novel statistical model to estimate genome-specific error rates and underlying gene frequencies. The core genomes are then integrated into a phylogenetic tree to reconstruct the core genome of the last bacterial common ancestor (LBCA), yielding three main results: First, the gene content of modern and ancestral core genomes are diverse at the level of individual genes but are similarly distributed by functional category and share several poorly characterized genes. Second, the LBCA core genome is distinct from any individual modern core genome but has many fundamental biological systems intact, especially those involving translation machinery and biosynthetic pathways to all major nucleotides and amino acids. Third, despite this metabolic versatility, the LBCA core genome likely requires additional non-core genes for viability, based on comparisons with the minimal organism, JCVI-Syn3A.

CONCLUSIONS

These results suggest that many cellular systems commonly conserved in modern bacteria were not just present in ancient bacteria but were nearly immutable with respect to short-term intraspecies variation. Extending this analysis to other domains of life will likely provide similar insights into more distant ancestral species.

Evolution of a minimal cell

Possessing only essential genes, a minimal cell can reveal mechanisms and processes that are critical for the persistence and stability of life1,2. Here we report on how an engineered minimal cell3,4 contends with the forces of evolution compared with the Mycoplasma mycoides non-minimal cell from which it was synthetically derived. Mutation rates were the highest among all reported bacteria, but were not affected by genome minimization. Genome streamlining was costly, leading to a decrease in fitness of greater than 50%, but this deficit was regained during 2,000 generations of evolution. Despite selection acting on distinct genetic targets, increases in the maximum growth rate of the synthetic cells were comparable. Moreover, when performance was assessed by relative fitness, the minimal cell evolved 39% faster than the non-minimal cell. The only apparent constraint involved the evolution of cell size. The size of the non-minimal cell increased by 80%, whereas the minimal cell remained the same. This pattern reflected epistatic effects of mutations in ftsZ, which encodes a tubulin-homologue protein that regulates cell division and morphology5,6. Our findings demonstrate that natural selection can rapidly increase the fitness of one of the simplest autonomously growing organisms. Understanding how species with small genomes overcome evolutionary challenges provides critical insights into the persistence of host-associated endosymbionts, the stability of streamlined chassis for biotechnology and the targeted refinement of synthetically engineered cells2,7-9.

Cell-Free Expression System Derived from a Near-Minimal Synthetic Bacterium

Cell-free expression (CFE) systems are fundamental to reconstituting metabolic pathways in vitro toward the construction of a synthetic cell. Although an Escherichia coli-based CFE system is well-established, simpler model organisms are necessary to understand the principles behind life-like behavior. Here, we report the successful creation of a CFE system derived from JCVI-syn3A (Syn3A), the minimal synthetic bacterium. Previously, high ribonuclease activity in Syn3A lysates impeded the establishment of functional CFE systems. Now, we describe how an unusual cell lysis method (nitrogen decompression) yielded Syn3A lysates with reduced ribonuclease activity that supported in vitro expression. To improve the protein yields in the Syn3A CFE system, we optimized the Syn3A CFE reaction mixture using an active machine learning tool. The optimized reaction mixture improved the CFE 3.2-fold compared to the preoptimized condition. This is the first report of a functional CFE system derived from a minimal synthetic bacterium, enabling further advances in bottom-up synthetic biology.

A Hitchhiker's Guide to Supplying Enzymatic Reducing Power into Synthetic Cells

The construction from scratch of synthetic cells by assembling molecular building blocks is unquestionably an ambitious goal from a scientific and technological point of view. To realize functional life-like systems, minimal enzymatic modules are required to sustain the processes underlying the out-of-equilibrium thermodynamic status hallmarking life, including the essential supply of energy in the form of electrons. The nicotinamide cofactors NAD(H) and NADP(H) are the main electron carriers fueling reductive redox reactions of the metabolic network of living cells. One way to ensure the continuous availability of reduced nicotinamide cofactors in a synthetic cell is to build a minimal enzymatic module that can oxidize an external electron donor and reduce NAD(P)+. In the diverse world of metabolism there is a plethora of potential electron donors and enzymes known from living organisms to provide reducing power to NAD(P)+ coenzymes. This perspective proposes guidelines to enable the reduction of nicotinamide cofactors enclosed in phospholipid vesicles, while avoiding high burdens of or cross-talk with other encapsulated metabolic modules. By determining key requirements, such as the feasibility of the reaction and transport of the electron donor into the cell-like compartment, we select a shortlist of potentially suitable electron donors. We review the most convenient proteins for the use of these reducing agents, highlighting their main biochemical and structural features. Noting that specificity toward either NAD(H) or NADP(H) imposes a limitation common to most of the analyzed enzymes, we discuss the need for specific enzymes─transhydrogenases─to overcome this potential bottleneck.

Minimal Out-of-Equilibrium Metabolism for Synthetic Cells: A Membrane Perspective

Life-like systems need to maintain a basal metabolism, which includes importing a variety of building blocks required for macromolecule synthesis, exporting dead-end products, and recycling cofactors and metabolic intermediates, while maintaining steady internal physical and chemical conditions (physicochemical homeostasis). A compartment, such as a unilamellar vesicle, functionalized with membrane-embedded transport proteins and metabolic enzymes encapsulated in the lumen meets these requirements. Here, we identify four modules designed for a minimal metabolism in a synthetic cell with a lipid bilayer boundary: energy provision and conversion, physicochemical homeostasis, metabolite transport, and membrane expansion. We review design strategies that can be used to fulfill these functions with a focus on the lipid and membrane protein composition of a cell. We compare our bottom-up design with the equivalent essential modules of JCVI-syn3a, a top-down genome-minimized living cell with a size comparable to that of large unilamellar vesicles. Finally, we discuss the bottlenecks related to the insertion of a complex mixture of membrane proteins into lipid bilayers and provide a semiquantitative estimate of the relative surface area and lipid-to-protein mass ratios (i.e., the minimal number of membrane proteins) that are required for the construction of a synthetic cell.

Towards a Standardized Antimicrobial Susceptibility Testing Method for Mycoplasma hyorhinis

Conducting antimicrobial susceptibility testing (AST) in a comparable manner requires the availability of a standardized method. Organizations, such as the Clinical and Laboratory Standards Institute (CLSI) or the European Committee on Antimicrobial Susceptibility Testing (EUCAST), provide standardized protocols for a range of fastidious bacteria but not for Mycoplasma hyorhinis. We developed a broth microdilution method for testing M. hyorhinis in a standardized and harmonized way using a modified Friis broth devoid of antimicrobial or otherwise bacterial growth-inhibiting agents. The type strain M. hyorhinis DSM 25591 was chosen to establish the methodology. The antimicrobial agents of interest were doxycycline, enrofloxacin, erythromycin, florfenicol, gentamicin, marbofloxacin, tetracycline, tiamulin, tilmicosin, tulathromycin, and tylosin, tested by using commercial Sensititre^TM microtiter plates. In addition, the suitability of the methodology was evaluated via variation of the individual ingredients of the modified Friis broth by either using different batches or choosing other distributors. Despite these alterations, the method provided reliable results. We obtained repeatable minimal inhibitory concentrations for all six tested field isolates and the M. hyorhinis type strain. With this newly proposed method, we aim to provide an improved AST method for diagnostic laboratories and monitoring purposes with better comparability between times and countries. In addition, this new method will allow for an improvement of targeted treatments using antimicrobial agents and thereby reduce the options for resistance development.

A model industrial workhorse: Bacillus subtilis strain 168 and its genome after a quarter of a century

The vast majority of genomic sequences are automatically annotated using various software programs. The accuracy of these annotations depends heavily on the very few manual annotation efforts that combine verified experimental data with genomic sequences from model organisms. Here, we summarize the updated functional annotation of Bacillus subtilis strain 168, a quarter century after its genome sequence was first made public. Since the last such effort 5 years ago, 1168 genetic functions have been updated, allowing the construction of a new metabolic model of this organism of environmental and industrial interest. The emphasis in this review is on new metabolic insights, the role of metals in metabolism and macromolecule biosynthesis, functions involved in biofilm formation, features controlling cell growth, and finally, protein agents that allow class discrimination, thus allowing maintenance management, and accuracy of all cell processes. New 'genomic objects' and an extensive updated literature review have been included for the sequence, now available at the International Nucleotide Sequence Database Collaboration (INSDC: AccNum AL009126.4).

Genome engineering via gene editing technologies in microalgae

CRISPR-Cas has revolutionized genetic modification with its comparative simplicity and accuracy, and it can be used even at the genomic level. Microalgae are excellent feedstocks for biofuels and nutraceuticals because they contain high levels of fatty acids, carotenoids, and other metabolites; however, genome engineering for microalgae is not yet as developed as for other model organisms. Microalgal engineering at the genetic and metabolic levels is relatively well established, and a few genomic resources are available. Their genomic information was used for a "safe harbor" site for stable transgene expression in microalgae. This review proposes further genome engineering schemes including the construction of sgRNA libraries, pan-genomic and epigenomic resources, and mini-genomes, which can together be developed into synthetic biology for carbon-based engineering in microalgae. Acetyl-CoA is at the center of carbon metabolic pathways and is further reviewed for the production of molecules including terpenoids in microalgae.

Understudied proteins and understudied functions in the model bacterium Bacillus subtilis-A major challenge in current research

Model organisms such as the Gram-positive bacterium Bacillus subtilis have been studied intensively for decades. However, even for model organisms, no function has been identified for about one fourth of all proteins. It has recently been realized that such understudied proteins as well as poorly studied functions set a limitation to our understanding of the requirements for cellular life, and the Understudied Proteins Initiative has been launched. Of poorly studied proteins, those that are strongly expressed are likely to be important to the cell and should therefore be considered high priority in further studies. Since the functional analysis of unknown proteins can be extremely laborious, a minimal knowledge is required prior to targeted functional studies. In this review, we discuss strategies to obtain such a minimal annotation, for example, from global interaction, expression, or localization studies. We present a set of 41 highly expressed and poorly studied proteins of B. subtilis. Several of these proteins are thought or known to bind RNA and/or the ribosome, some may control the metabolism of B. subtilis, and another subset of particularly small proteins may act as regulatory elements to control the expression of downstream genes. Moreover, we discuss the challenges of poorly studied functions with a focus on RNA-binding proteins, amino acid transport, and the control of metabolic homeostasis. The identification of the functions of the selected proteins not only will strongly advance our knowledge on B. subtilis, but also on other organisms since many of the proteins are conserved in many groups of bacteria.

ecmtool: fast and memory-efficient enumeration of elementary conversion modes

MOTIVATION

Characterizing all steady-state flux distributions in metabolic models remains limited to small models due to the explosion of possibilities. Often it is sufficient to look only at all possible overall conversions a cell can catalyze ignoring the details of intracellular metabolism. Such a characterization is achieved by elementary conversion modes (ECMs), which can be conveniently computed with ecmtool. However, currently, ecmtool is memory intensive, and it cannot be aided appreciably by parallelization.

RESULTS

We integrate mplrs-a scalable parallel vertex enumeration method-into ecmtool. This speeds up computation, drastically reduces memory requirements and enables ecmtool's use in standard and high-performance computing environments. We show the new capabilities by enumerating all feasible ECMs of the near-complete metabolic model of the minimal cell JCVI-syn3.0. Despite the cell's minimal character, the model gives rise to 4.2×109 ECMs and still contains several redundant sub-networks.

AVAILABILITY AND IMPLEMENTATION

ecmtool is available at https://github.com/SystemsBioinformatics/ecmtool.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Investigation of Genome Biology by Synthetic Genome Engineering

Synthetic genomes were designed based on an understanding of natural genomic information, offering an opportunity to engineer and investigate biological systems on a genome-wide scale. Currently, the designer version of the M. mycoides genome and the E. coli genome, as well as most of the S. cerevisiae genome, have been synthesized, and through the cycles of design-build-test and the following engineering of synthetic genomes, many fundamental questions of genome biology have been investigated. In this review, we summarize the use of synthetic genome engineering to explore the structure and function of genomes, and highlight the unique values of synthetic genomics.

Molecular dynamics simulation of an entire cell

The ultimate microscope, directed at a cell, would reveal the dynamics of all the cell's components with atomic resolution. In contrast to their real-world counterparts, computational microscopes are currently on the brink of meeting this challenge. In this perspective, we show how an integrative approach can be employed to model an entire cell, the minimal cell, JCVI-syn3A, at full complexity. This step opens the way to interrogate the cell's spatio-temporal evolution with molecular dynamics simulations, an approach that can be extended to other cell types in the near future.

Cellular mechanics during division of a genomically minimal cell

Genomically minimal cells, such as JCVI-syn3.0 and JCVI-syn3A, offer an empowering framework to study relationships between genotype and phenotype. With a polygenic basis, the fundamental physiological process of cell division depends on multiple genes of known and unknown function in JCVI-syn3A. A physical description of cellular mechanics can further understanding of the contributions of genes to cell division in this genomically minimal context. We review current knowledge on genes in JCVI-syn3A contributing to two physical parameters relevant to cell division, namely, the surface-area-to-volume ratio and membrane curvature. This physical view of JCVI-syn3A may inform the attribution of gene functions and conserved processes in bacterial physiology, as well as whole-cell models and the engineering of synthetic cells.

Global coordination of the mutation and growth rates across the genetic and nutritional variety in Escherichia coli

Fitness and mutability are the primary traits of living organisms for adaptation and evolution. However, their quantitative linkage remained largely deficient. Whether there is any general relationship between the two features and how genetic and environmental variables influence them remained unclear and were addressed here. The mutation and growth rates of an assortment of Escherichia coli strain collections, including the wild-type strains and the genetically disturbed strains of either reduced genomes or deletion of the genes involved in the DNA replication fidelity, were evaluated in various media. The contribution of media to the mutation and growth rates was differentiated depending on the types of genetic disturbance. Nevertheless, the negative correlation between the mutation and growth rates was observed across the genotypes and was common in all media. It indicated the comprehensive association of the correlated mutation and growth rates with the genetic and medium variation. Multiple linear regression and support vector machine successfully predicted the mutation and growth rates and the categories of genotypes and media, respectively. Taken together, the study provided a quantitative dataset linking the mutation and growth rates, genotype, and medium and presented a simple and successful example of predicting bacterial growth and mutability by data-driven approaches.

Toward the Complete Functional Characterization of a Minimal Bacterial Proteome

Recently, we presented a whole-cell kinetic model of the genetically minimal bacterium JCVI-syn3A that described the coupled metabolic and genetic information processes and predicted behaviors emerging from the interactions among these networks. JCVI-syn3A is a genetically reduced bacterial cell that has the fewest number and smallest fraction of genes of unclear function, with approximately 90 of its 452 protein-coding genes (that is less than 20%) unannotated. Further characterization of unclear JCVI-syn3A genes strengthens the robustness and predictive power of cell modeling efforts and can lead to a deeper understanding of biophysical processes and pathways at the cell scale. Here, we apply computational analyses to elucidate the functions of the products of several essential but previously uncharacterized genes involved in integral cellular processes, particularly those directly affecting cell growth, division, and morphology. We also suggest directed wet-lab experiments informed by our analyses to further understand these "missing puzzle pieces" that are an essential part of the mosaic of biological interactions present in JCVI-syn3A. Our workflow leverages evolutionary sequence analysis, protein structure prediction, interactomics, and genome architecture to determine upgraded annotations. Additionally, we apply the structure prediction analysis component of our work to all 452 protein coding genes in JCVI-syn3A to expedite future functional annotation studies as well as the inverse mapping of the cell state to more physical models requiring all-atom or coarse-grained representations for all JCVI-syn3A proteins.

The divergent genome of Scorpion Group 1 (SG1) intracellular bacterium from the venom glands of Vaejovis smithi (Scorpiones: Vaejovidae)

Scorpions were among the first animals on land around 430 million years ago. Like many arachnids, scorpions have evolved complex venoms used to paralyze their prey and for self-defense. Here we sequenced and analyzed the metagenomic DNA from venom glands from Vaejovis smithi scorpions. A metagenome-assembled genome (MAG) of 624,025 bp was obtained corresponding to the previously reported Scorpion Group 1 (SG1). The SG1 genome from venom glands had a low GC content (25.8%) characteristic of reduced genomes, many hypothetical genes and genes from the reported minimal set of bacterial genes. Phylogenomic reconstructions placed the uncultured SG1 distant from other reported bacteria constituting a taxonomic novelty. By PCR we detected SG1 in all tested venom glands from 30 independent individuals. Microscopically, we observed SG1 inside epithelial cells from the venom glands using FISH and its presence in scorpion embryos suggested that SG1 is transferred from mother to offspring.