Minimal Cells-Real and Imagined

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.

Use and dual use of synthetic biology

A brief history of the field shows that the impression of novelty we have today when we talk about synthetic biology is merely the sign of a rapid loss of memory of the events surrounding its creation. The dangers of misuse were identified even before the first experiments, but this has not led to a shared awareness. Building a cell ab initio involves combining a machine (called a chassis by specialists in the field) and a program in the form of synthetic DNA. Only the latter—the program—is the subject of the vast majority of work in the field, and it is there that the risks of misuse appear. Combined with knowledge of the genomic sequence of pathogens, DNA synthesis makes it possible to reconstitute dangerous organisms or even to develop new ways of propagating malicious software. Finally, the lack of thought given to the risk of accidents when laboratories develop gain-of-function experiments that increase the virulence of a pathogen makes a world where this type of experiments is developed particularly dangerous.

Experimental evolution of gene essentiality in bacteria

Essential gene products carry out fundamental cellular activities in interaction with other components. However, the lack of essential gene mutants and appropriate methodologies to link essential gene functions with their partners poses significant challenges. Here, we have generated deletion mutants in 32 genes previously identified as essential, with 23 mutants showing extremely slow growth in the SK36 strain of Streptococcus sanguinis. The 23 genes corresponding to these mutants encode components of diverse pathways, are widely conserved among bacteria, and are essential in many other bacterial species. Whole-genome sequencing of 243 independently evolved populations of these mutants has identified >1000 spontaneous suppressor mutations in experimental evolution. Many of these mutations define new gene and pathway relationships, such as F1Fo-ATPase/V1Vo-ATPase/TrkA1-H1 that were demonstrated across multiple Streptococcus species. Patterns of spontaneous mutations occurring in essential gene mutants differed from those found in wildtype. While gene duplications occurred rarely and appeared most often at later stages of evolution, substitutions, deletions, and insertions were prevalent in evolved populations. These essential gene deletion mutants and spontaneous mutations fixed in the mutant populations during evolution establish a foundation for understanding gene essentiality and the interaction of essential genes in networks.

Biological evolution is dead in the water of Darwin's warm little pond

The origin of life and its evolution are generally taught as occurring by abiogenesis and gene-centric neo-Darwinism. Significant biological evolutionary changes are preserved and given direction (descent with modification) by Darwin's (Spencer's) natural selection by survival of the fittest. Only survival of the fittest (adapted/broadened) is available to provide a 'naturalistic' direction to prefer one outcome/reaction over another for abiogenesis. Thus, assembly of first life must reach some threshold (the first minimal cell) before 'survival of the fittest' (the only naturalistic explanation available) can function as Darwin proposed for biological change. We propose the novel concept that the requirement for co-origination of vitamins with enzymes is a fundamental, but overlooked, problem that survival of the fittest (even broadly redefined beyond Darwin) cannot reasonably overcome. We support this conclusion with probability calculations. We focus on the stage of evolution involving the transition from non-life to the first, minimal living cell. We show that co-origination of required biochemical processes makes the origin of life probabilistically absurdly improbable even when all assumptions are chosen to unreasonably favor evolutionary theories.

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.

Darwinian Evolution of Self-Replicating DNA in a Synthetic Protocell

Replication, heredity, and evolution are characteristic of Life. We and others have postulated that the reconstruction of a synthetic living system in the laboratory will be contingent on the development of a genetic self-replicator capable of undergoing Darwinian evolution. Although DNA-based life dominates, the in vitro reconstitution of an evolving DNA self-replicator has remained challenging. We hereby emulate in liposome compartments the principles according to which life propagates information and evolves. Using two different experimental configurations supporting intermittent or semi-continuous evolution (i.e., with or without DNA extraction, PCR, and re-encapsulation), we demonstrate sustainable replication of a linear DNA template - encoding the DNA polymerase and terminal protein from the Phi29 bacteriophage - expressed in the 'protein synthesis using recombinant elements' (PURE) system. The self-replicator can survive across multiple rounds of replication-coupled transcription-translation reactions in liposomes and, within only ten evolution rounds, accumulates mutations conferring a selection advantage. Combined data from next-generation sequencing with reverse engineering of some of the enriched mutations reveal nontrivial and context-dependent effects of the introduced mutations. The present results are foundational to build up genetic complexity in an evolving synthetic cell, as well as to study evolutionary processes in a minimal cell-free system.

Evolution recovers the fitness of Acinetobacter baylyi strains with large deletions through mutations in deletion-specific targets and global post-transcriptional regulators

Organelles and endosymbionts have naturally evolved dramatically reduced genome sizes compared to their free-living ancestors. Synthetic biologists have purposefully engineered streamlined microbial genomes to create more efficient cellular chassis and define the minimal components of cellular life. During natural or engineered genome streamlining, deletion of many non-essential genes in combination often reduces bacterial fitness for idiosyncratic or unknown reasons. We investigated how and to what extent laboratory evolution could overcome these defects in six variants of the transposon-free Acinetobacter baylyi strain ADP1-ISx that each had a deletion of a different 22- to 42-kilobase region and two strains with larger deletions of 70 and 293 kilobases. We evolved replicate populations of ADP1-ISx and each deletion strain for ~300 generations in a chemically defined minimal medium or a complex medium and sequenced the genomes of endpoint clonal isolates. Fitness increased in all cases that were examined except for two ancestors that each failed to improve in one of the two environments. Mutations affecting nine protein-coding genes and two small RNAs were significantly associated with one of the two environments or with certain deletion ancestors. The global post-transcriptional regulators rnd (ribonuclease D), csrA (RNA-binding carbon storage regulator), and hfq (RNA-binding protein and chaperone) were frequently mutated across all strains, though the incidence and effects of these mutations on gene function and bacterial fitness varied with the ancestral deletion and evolution environment. Mutations in this regulatory network likely compensate for how an earlier deletion of a transposon in the ADP1-ISx ancestor of all the deletion strains restored csrA function. More generally, our results demonstrate that fitness lost during genome streamlining can usually be regained rapidly through laboratory evolution and that recovery tends to occur through a combination of deletion-specific compensation and global regulatory adjustments.

Promising non-model microbial cell factories obtained by genome reduction

The development of sustainable processes is the most important basis to realize the shift from the fossil-fuel based industry to bio-based production. Non-model microbes represent a great resource due to their advantageous traits and unique repertoire of bioproducts. However, most of these microbes require modifications to improve their growth and production capacities as well as robustness in terms of genetic stability. For this, genome reduction is a valuable and powerful approach to meet industry requirements and to design highly efficient production strains. Here, we provide an overview of various genome reduction approaches in prokaryotic microorganisms, with a focus on non-model organisms, and highlight the example of a successful genome-reduced model organism chassis. Furthermore, we discuss the advances and challenges of promising non-model microbial chassis.

Synthetic lethality and the minimal genome size problem

Gene knockout studies suggest that ~300 genes in a bacterial genome and ~1,100 genes in a yeast genome cannot be deleted without loss of viability. These single-gene knockout experiments do not account for negative genetic interactions, when two or more genes can each be deleted without effect, but their joint deletion is lethal. Thus, large-scale single-gene deletion studies underestimate the size of a minimal gene set compatible with cell survival. In yeast Saccharomyces cerevisiae, the viability of all possible deletions of gene pairs (2-tuples), and of some deletions of gene triplets (3-tuples), has been experimentally tested. To estimate the size of a yeast minimal genome from that data, we first established that finding the size of a minimal gene set is equivalent to finding the minimum vertex cover in the lethality (hyper)graph, where the vertices are genes and (hyper)edges connect k-tuples of genes whose joint deletion is lethal. Using the Lovász-Johnson-Chvatal greedy approximation algorithm, we computed the minimum vertex cover of the synthetic-lethal 2-tuples graph to be 1,723 genes. We next simulated the genetic interactions in 3-tuples, extrapolating from the existing triplet sample, and again estimated minimum vertex covers. The size of a minimal gene set in yeast rapidly approaches the size of the entire genome even when considering only synthetic lethalities in k-tuples with small k. In contrast, several studies reported successful experimental reductions of yeast and bacterial genomes by simultaneous deletions of hundreds of genes, without eliciting synthetic lethality. We discuss possible reasons for this apparent contradiction.IMPORTANCEHow can we estimate the smallest number of genes sufficient for a unicellular organism to survive on a rich medium? One approach is to remove genes one at a time and count how many of such deletion strains are unable to grow. However, the single-gene knockout data are insufficient, because joint gene deletions may result in negative genetic interactions, also known as synthetic lethality. We used a technique from graph theory to estimate the size of minimal yeast genome from partial data on synthetic lethality. The number of potential synthetic lethal interactions grows very fast when multiple genes are deleted, revealing a paradoxical contrast with the experimental reductions of yeast genome by ~100 genes, and of bacterial genomes by several hundreds of genes.

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.

Three Biopolymers and Origin of Life Scenarios

To track down the possible roots of life, various models for the initial living system composed of different combinations of the three extant biopolymers, RNA, DNA, and proteins, are presented. The suitability of each molecular set is assessed according to its ability to emerge autonomously, sustain, and evolve continuously towards life as we know it. The analysis incorporates current biological knowledge gained from high-resolution structural data and large sequence datasets, together with experimental results concerned with RNA replication and with the activity demonstrated by standalone constructs of the ribosomal Peptidyl Transferase Center region. The scrutiny excludes the DNA-protein combination and assigns negligible likelihood to the existence of an RNA-DNA world, as well as to an RNA world that contained a replicase made of RNA. It points to the precedence of an RNA-protein system, whose model of emergence suggests specific processes whereby a coded proto-ribosome ribozyme, specifically aminoacylated proto-tRNAs and a proto-polymerase enzyme, could have autonomously emerged, cross-catalyzing the formation of each other. This molecular set constitutes a feasible starting point for a continuous evolutionary path, proceeding via natural processes from the inanimate matter towards life as we know it.

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.

Building synthetic chromosomes from natural DNA

De novo chromosome synthesis is costly and time-consuming, limiting its use in research and biotechnology. Building synthetic chromosomes from natural components is an unexplored alternative with many potential applications. In this paper, we report CReATiNG (Cloning, Reprogramming, and Assembling Tiled Natural Genomic DNA), a method for constructing synthetic chromosomes from natural components in yeast. CReATiNG entails cloning segments of natural chromosomes and then programmably assembling them into synthetic chromosomes that can replace the native chromosomes in cells. We use CReATiNG to synthetically recombine chromosomes between strains and species, to modify chromosome structure, and to delete many linked, non-adjacent regions totaling 39% of a chromosome. The multiplex deletion experiment reveals that CReATiNG also enables recovery from flaws in synthetic chromosome design via recombination between a synthetic chromosome and its native counterpart. CReATiNG facilitates the application of chromosome synthesis to diverse biological problems.

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.

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.

Engineering tRNA abundances for synthetic cellular systems

Routinizing the engineering of synthetic cells requires specifying beforehand how many of each molecule are needed. Physics-based tools for estimating desired molecular abundances in whole-cell synthetic biology are missing. Here, we use a colloidal dynamics simulator to make predictions for how tRNA abundances impact protein synthesis rates. We use rational design and direct RNA synthesis to make 21 synthetic tRNA surrogates from scratch. We use evolutionary algorithms within a computer aided design framework to engineer translation systems predicted to work faster or slower depending on tRNA abundance differences. We build and test the so-specified synthetic systems and find qualitative agreement between expected and observed systems. First principles modeling combined with bottom-up experiments can help molecular-to-cellular scale synthetic biology realize design-build-work frameworks that transcend tinker-and-test.

Gene editing tools for mycoplasmas: references and future directions for efficient genome manipulation

Mycoplasmas are successful pathogens that cause debilitating diseases in humans and various animal hosts. Despite the exceptionally streamlined genomes, mycoplasmas have evolved specific mechanisms to access essential nutrients from host cells. The paucity of genetic tools to manipulate mycoplasma genomes has impeded studies of the virulence factors of pathogenic species and mechanisms to access nutrients. This review summarizes several strategies for editing of mycoplasma genomes, including homologous recombination, transposons, clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system, and synthetic biology. In addition, the mechanisms and features of different tools are discussed to provide references and future directions for efficient manipulation of mycoplasma genomes.

Building synthetic chromosomes from natural DNA

De novo chromosome synthesis is costly and time-consuming, limiting its use in research and biotechnology. Building synthetic chromosomes from natural components is an unexplored alternative with many potential applications. In this paper, we report CReATiNG (Cloning, Reprogramming, and Assembling Tiled Natural Genomic DNA), a method for constructing synthetic chromosomes from natural components in yeast. CReATiNG entails cloning segments of natural chromosomes and then programmably assembling them into synthetic chromosomes that can replace the native chromosomes in cells. We used CReATiNG to synthetically recombine chromosomes between strains and species, to modify chromosome structure, and to delete many linked, non-adjacent regions totaling 39% of a chromosome. The multiplex deletion experiment revealed that CReATiNG also enables recovery from flaws in synthetic chromosome design via recombination between a synthetic chromosome and its native counterpart. CReATiNG facilitates the application of chromosome synthesis to diverse biological problems.

The Long Road to a Synthetic Self-Replicating Central Dogma

The construction of a biochemical system capable of self-replication is a key objective in bottom-up synthetic biology. Throughout the past two decades, a rapid progression in the design of in vitro cell-free systems has provided valuable insight into the requirements for the development of a minimal system capable of self-replication. The main limitations of current systems can be attributed to their macromolecular composition and how the individual macromolecules use the small molecules necessary to drive RNA and protein synthesis. In this Perspective, we discuss the recent steps that have been taken to generate a minimal cell-free system capable of regenerating its own macromolecular components and maintaining the homeostatic balance between macromolecular biogenesis and consumption of primary building blocks. By following the flow of biological information through the central dogma, we compare the current versions of these systems to date and propose potential alterations aimed at designing a model system for self-replicative synthetic cells.

Engineering resource allocation in artificially minimized cells: Is genome reduction the best strategy?

The elimination of the expression of cellular functions that are not needed in a certain well-defined artificial environment, such as those used in industrial production facilities, has been the goal of many cellular minimization projects. The generation of a minimal cell with reduced burden and less host-function interactions has been pursued as a tool to improve microbial production strains. In this work, we analysed two cellular complexity reduction strategies: genome and proteome reduction. With the aid of an absolute proteomics data set and a genome-scale model of metabolism and protein expression (ME-model), we quantitatively assessed the difference of reducing genome to the correspondence of reducing proteome. We compare the approaches in terms of energy consumption, defined in ATP equivalents. We aim to show what is the best strategy for improving resource allocation in minimized cells. Our results show that genome reduction by length is not proportional to reducing resource use. When we normalize calculated energy savings, we show that strains with the larger calculated proteome reduction show the largest resource use reduction. Furthermore, we propose that reducing highly expressed proteins should be the target as the translation of a gene uses most of the energy. The strategies proposed here should guide cell design when the aim of a project is to reduce the maximum amount or cellular resources.

Fake cells and the aura of life: A philosophical diagnostic of synthetic life

Synthetic biology is often seen as the engineering turn in biology. Philosophically speaking, entities created by synthetic biology, from synthetic cells to xenobots, challenge the ontological divide between the organic and inorganic, as well as between the natural and the artificial. Entities such as synthetic cells can be seen as hybrid or transitory objects, or neo-things. However, what has remained philosophically underexplored so far is the impact these hybrid neo-things will have on (our phenomenological experience of) the living world. By extrapolating from Walter Benjamin's account of how technological reproducibility affects the aura of art, we embark upon an exploratory inquiry that seeks to fathom how the technological reproducibility of life itself may influence our experience and understanding of the living. We conclude that, much as technologies that enabled reproduction corroded the aura of original artworks (as Benjamin argued), so too will the aura of life be under siege in the era of synthetic lifeforms. This article zooms in on a specific case study, namely the research project Building a Synthetic Cell (BaSyC) and its mission to create a synthetic cell-like entity, as autonomous as possible, focusing on the properties that differentiate organic from synthetic cells.

Versatile tools of synthetic biology applied to drug discovery and production

Although synthetic biology is an emerging research field, which has come to prominence within the last decade, it already has many practical applications. Its applications cover the areas of pharmaceutical biotechnology and drug discovery, bringing essential novel methods and strategies such as metabolic engineering, reprogramming the cell fate, drug production in genetically modified organisms, molecular glues, functional nucleic acids and genome editing. This review discusses the main avenues for synthetic biology application in pharmaceutical biotechnology. The authors believe that synthetic biology will reshape drug development and drug production to a similar extent as the advances in organic chemical synthesis in the 20th century. Therefore, synthetic biology already plays an essential role in pharmaceutical, biotechnology, which is the main focus of this review.

Hydrogels as functional components in artificial cell systems

Recent years have seen substantial efforts aimed at constructing artificial cells from various molecular components with the aim of mimicking the processes, behaviours and architectures found in biological systems. Artificial cell development ultimately aims to produce model constructs that progress our understanding of biology, as well as forming the basis for functional bio-inspired devices that can be used in fields such as therapeutic delivery, biosensing, cell therapy and bioremediation. Typically, artificial cells rely on a bilayer membrane chassis and have fluid aqueous interiors to mimic biological cells. However, a desire to more accurately replicate the gel-like properties of intracellular and extracellular biological environments has driven increasing efforts to build cell mimics based on hydrogels. This has enabled researchers to exploit some of the unique functional properties of hydrogels that have seen them deployed in fields such as tissue engineering, biomaterials and drug delivery. In this Review, we explore how hydrogels can be leveraged in the context of artificial cell development. We also discuss how hydrogels can potentially be incorporated within the next generation of artificial cells to engineer improved biological mimics and functional microsystems.

Synthetic chromosomes, genomes, viruses, and cells

Synthetic genomics is the construction of viruses, bacteria, and eukaryotic cells with synthetic genomes. It involves two basic processes: synthesis of complete genomes or chromosomes and booting up of those synthetic nucleic acids to make viruses or living cells. The first synthetic genomics efforts resulted in the construction of viruses. This led to a revolution in viral reverse genetics and improvements in vaccine design and manufacture. The first bacterium with a synthetic genome led to construction of a minimal bacterial cell and recoded Escherichia coli strains able to incorporate multiple non-standard amino acids in proteins and resistant to phage infection. Further advances led to a yeast strain with a synthetic genome and new approaches for animal and plant artificial chromosomes. On the horizon there are dramatic advances in DNA synthesis that will enable extraordinary new opportunities in medicine, industry, agriculture, and research.

EcoliGD: An Online Tool for Designing Escherichia coli Genome

Synthetic biology is an important interdisciplinary field that has emerged in this century, focusing on the rewriting and reprogramming of DNA through the cycles of "design-edit", and so, the cell's own operating system, its genome, is naturally coming into focus. Here, we propose EcoliGD, an online genome design tool with a visual interactive interface and the function of browsing information, as well as the ability to perform insertion, exchange, deletion, and codon replacement operations on the E. coli genome and display the results in real-time. Users can utilize EcoliGD to check various functional characteristic about E. coli genes, to help them build their genomes. Furthermore, we also collected experimentally verified large genomic segments that have been successfully deleted from the genome for users to choose from and simplify the genome. EcoliGD can help recode the entire E. coli genome, providing a novel way to explore the diversity and function of this microorganism. The EcoliGD web tool is available at http://guolab.whu.edu.cn/EcoliGD/.

Genome Engineering of the Fast-Growing Mycoplasma feriruminatoris toward a Live Vaccine Chassis

Development of a new generation of vaccines is a key challenge for the control of infectious diseases affecting both humans and animals. Synthetic biology methods offer new ways to engineer bacterial chassis that can be used as vectors to present heterologous antigens and train the immune system against pathogens. Here, we describe the construction of a bacterial chassis based on the fast-growing Mycoplasma feriruminatoris, and the first steps toward its application as a live vaccine against contagious caprine pleuropneumonia (CCPP). To do so, the M. feriruminatoris genome was cloned in yeast, modified by iterative cycles of Cas9-mediated deletion of loci encoding virulence factors, and transplanted back in Mycoplasma capricolum subsp. capricolum recipient cells to produce the designed M. feriruminatoris chassis. Deleted genes encoded the glycerol transport and metabolism systems GtsABCD and GlpOKF and the Mycoplasma Ig binding protein-Mycoplasma Ig protease (MIB-MIP) immunoglobulin cleavage system. Phenotypic assays of the M. feriruminatoris chassis confirmed the corresponding loss of H₂O₂ production and IgG cleavage activities, while growth remained unaltered. The resulting mycoplasma chassis was further evaluated as a platform for the expression of heterologous surface proteins. A genome locus encoding an inactivated MIB-MIP system from the CCPP-causative agent Mycoplasma capricolum subsp. capripneumoniae was grafted in replacement of its homolog at the original locus in the chassis genome. Both heterologous proteins were detected in the resulting strain using proteomics, confirming their expression. This study demonstrates that advanced genome engineering methods are henceforth available for the fast-growing M. feriruminatoris, facilitating the development of novel vaccines, in particular against major mycoplasma diseases.

Engineering artificial photosynthetic life-forms through endosymbiosis

The evolutionary origin of the photosynthetic eukaryotes drastically altered the evolution of complex lifeforms and impacted global ecology. The endosymbiotic theory suggests that photosynthetic eukaryotes evolved due to endosymbiosis between non-photosynthetic eukaryotic host cells and photosynthetic cyanobacterial or algal endosymbionts. The photosynthetic endosymbionts, propagating within the cytoplasm of the host cells, evolved, and eventually transformed into chloroplasts. Despite the fundamental importance of this evolutionary event, we have minimal understanding of this remarkable evolutionary transformation. Here, we design and engineer artificial, genetically tractable, photosynthetic endosymbiosis between photosynthetic cyanobacteria and budding yeasts. We engineer various mutants of model photosynthetic cyanobacteria as endosymbionts within yeast cells where, the engineered cyanobacteria perform bioenergetic functions to support the growth of yeast cells under defined photosynthetic conditions. We anticipate that these genetically tractable endosymbiotic platforms can be used for evolutionary studies, particularly related to organelle evolution, and also for synthetic biology applications.

Reduction of the Bacterial Genome by Transposon-Mediated Random Deletion

Genome reduction is an important strategy in synthetic biology for constructing functional chassis cells or minimal genomes. However, the limited knowledge of complex gene functions and interactions makes genome reduction by rational design encounter a bottleneck. Here, we present an iterative and random genome reduction method for Escherichia coli, named "transposon-mediated random deletion (TMRD)". TMRD generates random double-strand breaks (DSBs) in the genome by combining Tn5 transposition with the CRISPR/Cas9 system and allows genomic deletions of various sizes at random positions during DSB repair through the intracellular alternative end-joining mechanism. Using E. coli MG1655 as the original strain, a pool of cells with multiple random genomic deletions were obtained after five reduction cycles. The growth rates of the obtained cells were comparable to that of MG1655, while the electroporation efficiency increased by at least 2 magnitudes. TMRD can generate a small E. coli library carrying multiple and random genomic deletions while enriching the cells with environmental fitness in the population. TMRD has the potential to be widely applied in the construction of minimal genomes or chassis cells for metabolic engineering.

LoxTnSeq: random transposon insertions combined with cre/lox recombination and counterselection to generate large random genome reductions

The removal of unwanted genetic material is a key aspect in many synthetic biology efforts and often requires preliminary knowledge of which genomic regions are dispensable. Typically, these efforts are guided by transposon mutagenesis studies, coupled to deepsequencing (TnSeq) to identify insertion points and gene essentiality. However, epistatic interactions can cause unforeseen changes in essentiality after the deletion of a gene, leading to the redundancy of these essentiality maps. Here, we present LoxTnSeq, a new methodology to generate and catalogue libraries of genome reduction mutants. LoxTnSeq combines random integration of lox sites by transposon mutagenesis, and the generation of mutants via Cre recombinase, catalogued via deep sequencing. When LoxTnSeq was applied to the naturally genome reduced bacterium Mycoplasma pneumoniae, we obtained a mutant pool containing 285 unique deletions. These deletions spanned from > 50 bp to 28 Kb, which represents 21% of the total genome. LoxTnSeq also highlighted large regions of non-essential genes that could be removed simultaneously, and other non-essential regions that could not, providing a guide for future genome reductions.

The Codon Usage in the Minimal Natural Cell

A statistical analysis of the variation in contents with the size of the current known smallest genomes, N. deltocephalinicola, C. ruddii, N. equitans, and M. genitalium, enabled the indication of a minimal set of codons capable of naturally building a modern-type free-living unicellular organism in an early stage of evolution. Using a linear regression model, the potential codon distribution in the minimal natural cell was predicted and compared to the composition of the smallest synthetic, JCVI-Syn3.0. The distribution of the molecular weight of potentially coded amino acids was also calculated. The main differences in the features of the minimal natural cell and H. Sapiens genome were analyzed. In this regard, the content percentage of respective amino acids and their polarization charge properties were reported and compared. The fractions of occurring nucleotides were calculated, too. Then, the estimated numbers of codons in a minimal natural cell were related to the expected numbers for random distribution. Shown increase, or decrease in the contents, relative to the calculated random filling was related to the evolutionary preferences, varying with the subsequent eras of the evolution of genetic code.

Investigation of the lncRNA THOR in Mice Highlights the Importance of Noncoding RNAs in Mammalian Male Reproduction

THOR is a highly conserved testis-specific long noncoding RNA (lncRNA). The interaction between THOR and the development of the male reproductive system remains unclear. Herein, CRISPR/Cas9 technology was used to establish a stable THOR-deficient mouse model, and the relationship between THOR and the fertility of adult male mice was investigated. The male mice in which THOR was deleted were smaller than the WT male mice. Moreover, their survival rate was reduced by 60%, their fertility was reduced by 50%, their testicular size and sperm motility were reduced by 50%, their testicular cell apoptosis was increased by 7-fold, and their ratio of female-to-male offspring was imbalanced (approximately 1:3). Furthermore, to elucidate the mechanisms of male reproductive system development, the mRNA levels of THOR targets were measured by qRT-PCR. Compared with WT mice, the THOR-deficient mice exhibited significantly decreased mRNA levels of IGF2BP1, c-MYC, IGF1, and IGF2. MEK-ERK signaling pathway expression was downregulated as determined by Western blot. We found that THOR targeted the MER-ERK signaling pathway downstream of IGF2 by binding to IGF2BP1 and affected testicular and sperm development in male mice. These results may also provide perspectives for exploring the roles of lncRNAs in human reproductive development and the pathogenesis and potential therapeutic targets of infertility.

Testing Theoretical Minimal Genomes Using Whole-Cell Models

The minimal gene set for life has often been theorized, with at least ten produced for Mycoplasma genitalium (M. genitalium). Due to the difficulty of using M. genitalium in the lab, combined with its long replication time of 12-15 h, none of these theoretical minimal genomes have been tested, even with modern techniques. The publication of the M. genitalium whole-cell model provided the first opportunity to test them, simulating the genome edits in silico. We simulated minimal gene sets from the literature, finding that they produced in silico cells that did not divide. Using knowledge from previous research, we reintroduced specific essential and low essential genes in silico; enabling cellular division. This reinforces the need to identify species-specific low essential genes and their interactions. Any genome designs created using the currently incomplete and fragmented gene essentiality information will very likely require in vivo reintroductions to correct issues and produce dividing cells.

Genome-scale metabolic modeling reveals key features of a minimal gene set

Mesoplasma florum, a fast-growing near-minimal organism, is a compelling model to explore rational genome designs. Using sequence and structural homology, the set of metabolic functions its genome encodes was identified, allowing the reconstruction of a metabolic network representing ˜ 30% of its protein-coding genes. Growth medium simplification enabled substrate uptake and product secretion rate quantification which, along with experimental biomass composition, were integrated as species-specific constraints to produce the functional iJL208 genome-scale model (GEM) of metabolism. Genome-wide expression and essentiality datasets as well as growth data on various carbohydrates were used to validate and refine iJL208. Discrepancies between model predictions and observations were mechanistically explained using protein structures and network analysis. iJL208 was also used to propose an in silico reduced genome. Comparing this prediction to the minimal cell JCVI-syn3.0 and its parent JCVI-syn1.0 revealed key features of a minimal gene set. iJL208 is a stepping-stone toward model-driven whole-genome engineering.

Antibiotic tolerance, persistence, and resistance of the evolved minimal cell, Mycoplasma mycoides JCVI-Syn3B

Antibiotic resistance is a growing problem, but bacteria can evade antibiotic treatment via tolerance and persistence. Antibiotic persisters are a small subpopulation of bacteria that tolerate antibiotics due to a physiologically dormant state. Hence, persistence is considered a major contributor to the evolution of antibiotic-resistant and relapsing infections. Here, we used the synthetically developed minimal cell Mycoplasma mycoides JCVI-Syn3B to examine essential mechanisms of antibiotic survival. The minimal cell contains only 473 genes, and most genes are essential. Its reduced complexity helps to reveal hidden phenomenon and fundamental biological principles can be explored because of less redundancy and feedback between systems compared to natural cells. We found that Syn3B evolves antibiotic resistance to different types of antibiotics expeditiously. The minimal cell also tolerates and persists against multiple antibiotics. It contains a few already identified persister-related genes, although lacking many systems previously linked to persistence (e.g. toxin-antitoxin systems, ribosome hibernation genes).

Non-essential ribosomal proteins in bacteria and archaea identified using COGs

Ribosomal proteins (RPs) are highly conserved across the bacterial and archaeal domains. Although many RPs are essential for survival, genome analysis demonstrates the absence of some RP genes in many bacterial and archaeal genomes. Furthermore, global transposon mutagenesis and/or targeted deletion showed that elimination of some RP genes had only a moderate effect on the bacterial growth rate. Here, we systematically analyze the evolutionary conservation of RPs in prokaryotes by compiling the list of the ribosomal genes that are missing from one or more genomes in the recently updated version of the Clusters of Orthologous Genes (COG) database. Some of these absences occurred because the respective genes carried frameshifts, presumably, resulting from sequencing errors, while others were overlooked and not translated during genome annotation. Apart from these annotation errors, we identified multiple genuine losses of RP genes in a variety of bacteria and archaea. Some of these losses are clade-specific, whereas others occur in symbionts and parasites with dramatically reduced genomes. The lists of computationally and experimentally defined non-essential ribosomal genes show a substantial overlap, revealing a common trend in prokaryote ribosome evolution that could be linked to the architecture and assembly of the ribosomes. Thus, RPs that are located at the surface of the ribosome and/or are incorporated at a late stage of ribosome assembly are more likely to be non-essential and to be lost during microbial evolution, particularly, in the course of genome compaction.IMPORTANCEIn many prokaryote genomes, one or more ribosomal protein (RP) genes are missing. Analysis of 1,309 prokaryote genomes included in the COG database shows that only about half of the RPs are universally conserved in bacteria and archaea. In contrast, up to 16 other RPs are missing in some genomes, primarily, tiny (<1 Mb) genomes of host-associated bacteria and archaea. Ten universal and nine archaea-specific ribosomal proteins show clear patterns of lineage-specific gene loss. Most of the RPs that are frequently lost from bacterial genomes are located on the ribosome periphery and are non-essential in Escherichia coli and Bacillus subtilis These results reveal general trends and common constraints in the architecture and evolution of ribosomes in prokaryotes.

The Metabolic Building Blocks of a Minimal Cell

Defining the essential gene components for a system to be considered alive is a crucial step toward the synthesis of artificial life. Fifteen years ago, Gil and coworkers proposed the core of a putative minimal bacterial genome, which would provide the capability to achieve metabolic homeostasis, reproduce, and evolve to a bacterium in an ideally controlled environment. They also proposed a simplified metabolic chart capable of providing energy and basic components for a minimal living cell. For this work, we have identified the components of the minimal metabolic network based on the aforementioned studies, associated them to the KEGG database and, by applying the MetaDAG methodology, determined its Metabolic Building Blocks (MBB) and reconstructed its metabolic Directed Acyclic Graph (m-DAG). The reaction graph of this metabolic network consists of 80 compounds and 98 reactions, while its m-DAG has 36 MBBs. Additionally, we identified 12 essential reactions in the m-DAG that are critical for maintaining the connectivity of this network. In a similar manner, we reconstructed the m-DAG of JCVI-syn3.0, which is an artificially designed and manufactured viable cell whose genome arose by minimizing the one from Mycoplasma mycoides JCVI-syn1.0, and of "Candidatus Nasuia deltocephalinicola", the bacteria with the smallest natural genome known to date. The comparison of the m-DAGs derived from a theoretical, an artificial, and a natural genome denote slightly different lifestyles, with a consistent core metabolism. The MetaDAG methodology we employ uses homogeneous descriptors and identifiers from the KEGG database, so that comparisons between bacterial strains are not only easy but also suitable for many research fields. The modeling of m-DAGs based on minimal metabolisms can be the first step for the synthesis and manipulation of minimal cells.

Integrative characterization of the near-minimal bacterium Mesoplasma florum

The near-minimal bacterium Mesoplasma florum is an interesting model for synthetic genomics and systems biology due to its small genome (~ 800 kb), fast growth rate, and lack of pathogenic potential. However, fundamental aspects of its biology remain largely unexplored. Here, we report a broad yet remarkably detailed characterization of M. florum by combining a wide variety of experimental approaches. We investigated several physical and physiological parameters of this bacterium, including cell size, growth kinetics, and biomass composition of the cell. We also performed the first genome-wide analysis of its transcriptome and proteome, notably revealing a conserved promoter motif, the organization of transcription units, and the transcription and protein expression levels of all protein-coding sequences. We converted gene transcription and expression levels into absolute molecular abundances using biomass quantification results, generating an unprecedented view of the M. florum cellular composition and functions. These characterization efforts provide a strong experimental foundation for the development of a genome-scale model for M. florum and will guide future genome engineering endeavors in this simple organism.

Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology

Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells in silico offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.

Rapid and assured genetic engineering methods applied to Acinetobacter baylyi ADP1 genome streamlining

One goal of synthetic biology is to improve the efficiency and predictability of living cells by removing extraneous genes from their genomes. We demonstrate improved methods for engineering the genome of the metabolically versatile and naturally transformable bacterium Acinetobacter baylyi ADP1 and apply them to a genome streamlining project. In Golden Transformation, linear DNA fragments constructed by Golden Gate Assembly are directly added to cells to create targeted deletions, edits, or additions to the chromosome. We tested the dispensability of 55 regions of the ADP1 chromosome using Golden Transformation. The 18 successful multiple-gene deletions ranged in size from 21 to 183 kb and collectively accounted for 23.4% of its genome. The success of each multiple-gene deletion attempt could only be partially predicted on the basis of an existing collection of viable ADP1 single-gene deletion strains and a new transposon insertion sequencing (Tn-Seq) dataset that we generated. We further show that ADP1’s native CRISPR/Cas locus is active and can be retargeted using Golden Transformation. We reprogrammed it to create a CRISPR-Lock, which validates that a gene has been successfully removed from the chromosome and prevents it from being reacquired. These methods can be used together to implement combinatorial routes to further genome streamlining and for more rapid and assured metabolic engineering of this versatile chassis organism.

Rasheed M, Chen Y, Hu C, Chen H, Sagné E, Citti C, Guo A. An emerging role for cyclic dinucleotide phosphodiesterase and nanoRNase activities in Mycoplasma bovis: Securing survival in cell culture

Mycoplasmas are host-restricted prokaryotes with a nearly minimal genome. To overcome their metabolic limitations, these wall-less bacteria establish intimate interactions with epithelial cells at mucosal surfaces. The alarming rate of antimicrobial resistance among pathogenic species is of particular concern in the medical and veterinary fields. Taking advantage of the reduced mycoplasma genome, random transposon mutagenesis was combined with high-throughput screening in order to identify key determinants of mycoplasma survival in the host-cell environment and potential targets for drug development. With the use of the ruminant pathogen Mycoplasma bovis as a model, three phosphodiesterases of the DHH superfamily were identified as essential for the proliferation of this species under cell culture conditions, while dispensable for axenic growth. Despite a similar domain architecture, recombinant Mbov_0327 and Mbov_0328 products displayed different substrate specificities. While rMbovP328 protein exhibited activity towards cyclic dinucleotides and nanoRNAs, rMbovP327 protein was only able to degrade nanoRNAs. The Mbov_0276 product was identified as a member of the membrane-associated GdpP family of phosphodiesterases that was found to participate in cyclic dinucleotide and nanoRNA degradation, an activity which might therefore be redundant in the genome-reduced M. bovis. Remarkably, all these enzymes were able to convert their substrates into mononucleotides, and medium supplementation with nucleoside monophosphates or nucleosides fully restored the capacity of a Mbov_0328/0327 knock-out mutant to grow under cell culture conditions. Since mycoplasmas are unable to synthesize DNA/RNA precursors de novo, cyclic dinucleotide and nanoRNA degradation are likely contributing to the survival of M. bovis by securing the recycling of purines and pyrimidines. These results point toward proteins of the DHH superfamily as promising targets for the development of new antimicrobials against multidrug-resistant pathogenic mycoplasma species.

Toward a high-quality pan-genome landscape of Bacillus subtilis by removal of confounding strains

Pan-genome analysis is widely used to study the evolution and genetic diversity of species, particularly in bacteria. However, the impact of strain selection on the outcome of pan-genome analysis is poorly understood. Furthermore, a standard protocol to ensure high-quality pan-genome results is lacking. In this study, we carried out a series of pan-genome analyses of different strain sets of Bacillus subtilis to understand the impact of various strains on the performance and output quality of pan-genome analyses. Consequently, we found that the results obtained by pan-genome analyses of B. subtilis can be influenced by the inclusion of incorrectly classified Bacillus subspecies strains, phylogenetically distinct strains, engineered genome-reduced strains, chimeric strains, strains with a large number of unique genes or a large proportion of pseudogenes, and multiple clonal strains. Since the presence of these confounding strains can seriously affect the quality and true landscape of the pan-genome, we should remove these deviations in the process of pan-genome analyses. Our study provides new insights into the removal of biases from confounding strains in pan-genome analyses at the beginning of data processing, which enables the achievement of a closer representation of a high-quality pan-genome landscape of B. subtilis that better reflects the performance and credibility of the B. subtilis pan-genome. This procedure could be added as an important quality control step in pan-genome analyses for improving the efficiency of analyses, and ultimately contributing to a better understanding of genome function, evolution and genome-reduction strategies for B. subtilis in the future.

Designing minimal genomes using whole-cell models

In the future, entire genomes tailored to specific functions and environments could be designed using computational tools. However, computational tools for genome design are currently scarce. Here we present algorithms that enable the use of design-simulate-test cycles for genome design, using genome minimisation as a proof-of-concept. Minimal genomes are ideal for this purpose as they have a simple functional assay whether the cell replicates or not. We used the first (and currently only published) whole-cell model for the bacterium Mycoplasma genitalium. Our computational design-simulate-test cycles discovered novel in silico minimal genomes which, if biologically correct, predict in vivo genomes smaller than JCVI-Syn3.0; a bacterium with, currently, the smallest genome that can be grown in pure culture. In the process, we identified 10 low essential genes and produced evidence for at least two Mycoplasma genitalium in silico minimal genomes. This work brings combined computational and laboratory genome engineering a step closer.

Genome engineering will one day benefit from computational tools that can design genomes with desired functions. Here the authors develop computational design-simulate-test algorithms to design minimal genomes based on the whole-cell model of Mycoplasma genitalium.

Conserved Central Intraviral Protein Interactome of the Herpesviridae Family

Protein interactions are major driving forces behind the functional phenotypes of biological processes. As such, evolutionary footprints are reflected in system-level collections of protein-protein interactions (PPIs), i.e., protein interactomes. We conducted a comparative analysis of intraviral protein interactomes for representative species of each of the three subfamilies of herpesviruses (herpes simplex virus 1, human cytomegalovirus, and Epstein-Barr virus), which are highly prevalent etiologic agents of important human diseases. The intraviral interactomes were reconstructed by combining experimentally supported and computationally predicted protein-protein interactions. Using cross-species network comparison, we then identified family-wise conserved interactions and protein complexes, which we defined as a herpesviral "central" intraviral protein interactome. A large number of widely accepted conserved herpesviral protein complexes are present in this central intraviral interactome, encouragingly supporting the biological coherence of our results. Importantly, these protein complexes represent most, if not all, of the essential steps required during a productive life cycle. Hence the central intraviral protein interactome could plausibly represent a minimal infectious interactome of the herpesvirus family across a variety of hosts. Our data, which have been integrated into our herpesvirus interactomics database, HVint2.0, could assist in creating comprehensive system-level computational models of this viral lineage.IMPORTANCE Herpesviruses are an important socioeconomic burden for both humans and livestock. Throughout their long evolutionary history, individual herpesvirus species have developed remarkable host specificity, while collectively the Herpesviridae family has evolved to infect a large variety of eukaryotic hosts. The development of approaches to fight herpesvirus infections has been hampered by the complexity of herpesviruses' genomes, proteomes, and structural features. The data and insights generated by our study add to the understanding of the functional organization of herpesvirus-encoded proteins, specifically of family-wise conserved features defining essential components required for a productive infectious cycle across different hosts, which can contribute toward the conceptualization of antiherpetic infection strategies with an effect on a broader range of target species. All of the generated data have been made freely available through our HVint2.0 database, a dedicated resource of curated herpesvirus interactomics purposely created to promote and assist future studies in the field.

Blocking the Trigger: Inhibition of the Initiation of Bacterial Chromosome Replication as an Antimicrobial Strategy

All bacterial cells must duplicate their genomes prior to dividing into two identical daughter cells. Chromosome replication is triggered when a nucleoprotein complex, termed the orisome, assembles, unwinds the duplex DNA, and recruits the proteins required to establish new replication forks. Obviously, the initiation of chromosome replication is essential to bacterial reproduction, but this process is not inhibited by any of the currently-used antimicrobial agents. Given the urgent need for new antibiotics to combat drug-resistant bacteria, it is logical to evaluate whether or not unexploited bacterial processes, such as orisome assembly, should be more closely examined for sources of novel drug targets. This review will summarize current knowledge about the proteins required for bacterial chromosome initiation, as well as how orisomes assemble and are regulated. Based upon this information, we discuss current efforts and potential strategies and challenges for inhibiting this initiation pharmacologically.

Genome-driven cell engineering review: in vivo and in silico metabolic and genome engineering

Producing 'designer cells' with specific functions is potentially feasible in the near future. Recent developments, including whole-cell models, genome design algorithms and gene editing tools, have advanced the possibility of combining biological research and mathematical modelling to further understand and better design cellular processes. In this review, we will explore computational and experimental approaches used for metabolic and genome design. We will highlight the relevance of modelling in this process, and challenges associated with the generation of quantitative predictions about cell behaviour as a whole: although many cellular processes are well understood at the subsystem level, it has proved a hugely complex task to integrate separate components together to model and study an entire cell. We explore these developments, highlighting where computational design algorithms compensate for missing cellular information and underlining where computational models can complement and reduce lab experimentation. We will examine issues and illuminate the next steps for genome engineering.

An Evaluation of Machine Learning Approaches for the Prediction of Essential Genes in Eukaryotes Using Protein Sequence-Derived Features

The availability of whole-genome sequences and associated multi-omics data sets, combined with advances in gene knockout and knockdown methods, has enabled large-scale annotation and exploration of gene and protein functions in eukaryotes. Knowing which genes are essential for the survival of eukaryotic organisms is paramount for an understanding of the basic mechanisms of life, and could assist in identifying intervention targets in eukaryotic pathogens and cancer. Here, we studied essential gene orthologs among selected species of eukaryotes, and then employed a systematic machine-learning approach, using protein sequence-derived features and selection procedures, to investigate essential gene predictions within and among species. We showed that the numbers of essential gene orthologs comprise small fractions when compared with the total number of orthologs among the eukaryotic species studied. In addition, we demonstrated that machine-learning models trained with subsets of essentiality-related data performed better than random guessing of gene essentiality for a particular species. Consistent with our gene ortholog analysis, the predictions of essential genes among multiple (including distantly-related) species is possible, yet challenging, suggesting that most essential genes are unique to a species. The present work provides a foundation for the expansion of genome-wide essentiality investigations in eukaryotes using machine learning approaches.

Ureaplasma diversum protein interaction networks: evidence of horizontal gene transfer and evolution of reduced genomes among Mollicutes

Ureaplasma diversum is a member of the Mollicutes class responsible for urogenital tract infection in cattle and small ruminants. Studies indicate that the process of horizontal gene transfer, the exchange of genetic material among different species, has a crucial role in mollicute evolution, affecting the group's characteristic genomic reduction process and simplification of metabolic pathways. Using bioinformatics tools and the STRING database of known and predicted protein interactions, we constructed the protein-protein interaction network of U. diversum and compared it with the networks of other members of the Mollicutes class. We also investigated horizontal gene transfer events in subnetworks of interest involved in purine and pyrimidine metabolism and urease function, chosen because of their intrinsic importance for host colonization and virulence. We identified horizontal gene transfer events among Mollicutes and from Ureaplasma to Staphylococcus aureus and Corynebacterium, bacterial groups that colonize the urogenital niche. The overall tendency of genome reduction and simplification in the Mollicutes is echoed in their protein interaction networks, which tend to be more generalized and less selective. Our data suggest that the process was permitted (or enabled) by an increase in host dependence and the available gene repertoire in the urogenital tract shared via horizontal gene transfer.