Systems biology perspectives on minimal and simpler cells

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.

Implementation of Fluorescent-Protein-Based Quantification Analysis in L-Form Bacteria

Cell-wall-less (L-form) bacteria exhibit morphological complexity and heterogeneity, complicating quantitative analysis of them under internal and external stimuli. Stable and efficient labeling is needed for the fluorescence-based quantitative cell analysis of L-forms during growth and proliferation. Here, we evaluated the expression of multiple fluorescent proteins (FPs) under different promoters in the Bacillus subtilis L-form strain LR2 using confocal microscopy and imaging flow cytometry. Among others, Pylb-derived NBP3510 showed a superior performance for inducing several FPs including EGFP and mKO2 in both the wild-type and L-form strains. Moreover, NBP3510 was also active in Escherichia coli and its L-form strain NC-7. Employing these established FP-labeled strains, we demonstrated distinct morphologies in the L-form bacteria in a quantitative manner. Given cell-wall-deficient bacteria are considered protocell and synthetic cell models, the generated cell lines in our work could be valuable for L-form-based research.

Integration of text mining and biological network analysis: Identification of essential genes in sulfate-reducing bacteria

The growth and survival of an organism in a particular environment is highly depends on the certain indispensable genes, termed as essential genes. Sulfate-reducing bacteria (SRB) are obligate anaerobes which thrives on sulfate reduction for its energy requirements. The present study used Oleidesulfovibrio alaskensis G20 (OA G20) as a model SRB to categorize the essential genes based on their key metabolic pathways. Herein, we reported a feedback loop framework for gene of interest discovery, from bio-problem to gene set of interest, leveraging expert annotation with computational prediction. Defined bio-problem was applied to retrieve the genes of SRB from literature databases (PubMed, and PubMed Central) and annotated them to the genome of OA G20. Retrieved gene list was further used to enrich protein-protein interaction and was corroborated to the pangenome analysis, to categorize the enriched gene sets and the respective pathways under essential and non-essential. Interestingly, the sat gene (dde_2265) from the sulfur metabolism was the bridging gene between all the enriched pathways. Gene clusters involved in essential pathways were linked with the genes from seleno-compound metabolism, amino acid metabolism, secondary metabolite synthesis, and cofactor biosynthesis. Furthermore, pangenome analysis demonstrated the gene distribution, where 69.83% of the 116 enriched genes were mapped under "persistent," inferring the essentiality of these genes. Likewise, 21.55% of the enriched genes, which involves specially the formate dehydrogenases and metallic hydrogenases, appeared under "shell." Our methodology suggested that semi-automated text mining and network analysis may play a crucial role in deciphering the previously unexplored genes and key mechanisms which can help to generate a baseline prior to perform any experimental studies.

Small-molecule autocatalytic networks are universal metabolic fossils

Life and the genetic code are self-referential and so are autocatalytic networks made of simpler, small molecules. Several origins of life theories postulate autocatalytic chemical networks preceding the primordial genetic code, yet demonstration with biochemical systems is lacking. Here, small-molecule reflexively autocatalytic food-generated networks (RAFs) ranging in size from 3 to 619 reactions were found in all of 6683 prokaryotic metabolic networks searched. The average maximum RAF size is 275 reactions for a rich organic medium and 93 for a medium with a single organic cofactor, NAD. In the rich medium, all universally essential metabolites are produced with the exception of glycerol-1-p (archaeal lipid precursor), phenylalanine, histidine and arginine. The 300 most common reactions, present in at least 2732 RAFs, are mostly involved in amino acid biosynthesis and the metabolism of carbon, 2-oxocarboxylic acid and purines. ATP and NAD are central in generating network complexity, and because ATP is also one of the monomers of RNA, autocatalytic networks producing redox and energy currencies are a strong candidate niche of the origin of a primordial information-processing system. The wide distribution of small-molecule autocatalytic networks indicates that molecular reproduction may be much more prevalent in the Universe than hitherto predicted. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Experimental Evolution Expands the Breadth of Adaptation to an Environmental Gradient Correlated With Genome Reduction

Whether and how adaptive evolution adjusts the breadth of adaptation in coordination with the genome are essential issues for connecting evolution with ecology. To address these questions, experimental evolution in five Escherichia coli strains carrying either the wild-type genome or a reduced genome was performed in a defined minimal medium (C0). The ancestral and evolved populations were subsequently subjected to fitness and chemical niche analyses across an environmental gradient with 29 combinations of eight chemical components of the minimal medium. The results showed that adaptation was achieved not only specific to the evolutionary condition (C0), but also generally, to the environmental gradient; that is, the breadth of adaptation to the eight chemical niches was expanded. The magnitudes of the adaptive improvement and the breadth increase were both correlated with genome reduction and were highly significant in two out of eight niches (i.e., glucose and sulfate). The direct adaptation-induced correlated adaptation to the environmental gradient was determined by only a few genome mutations. An additive increase in fitness associated with the stepwise fixation of mutations was consistently observed in the reduced genomes. In summary, this preliminary survey demonstrated that evolution finely tuned the breadth of adaptation correlated with genome reduction.

Mitochondria Encapsulation in Hydrogel-Based Artificial Cells as ATP Producing Subunits

Artificial cells (ACs) aim to mimic selected structural and functional features of mammalian cells. In this context, energy generation is an important challenge to be addressed when self-sustained systems are desired. Here, mitochondria isolated from HepG2 cells are employed as natural subunits that facilitate chemically driven adenosine triphosphate (ATP) synthesis. The successful mitochondria isolation is confirmed by monitoring the preserved inner membrane potential, the respiration, and the ATP production ability. The encapsulation of the isolated mitochondria in gelatin-based hydrogels results in similar initial ATP production compared to mitochondria in solution with a sustained ATP production over 24 h. Furthermore, luciferase is coencapsulated with the mitochondria in gelatin-based particles to create ACs and employ the in situ produced ATP to drive the catalytic conversion of d-luciferin. The coencapsulation of luciferase-loaded liposomes with mitochondria in gelatin-based hydrogels is additionally explored where the encapsulation of mitochondria and liposomes resulted in clustering effects that are likely contributing to the functional performance of the active entities. Taken together, mitochondria show potential in cell mimicry to facilitate energy-dependent processes.

Biology transcends the limits of computation

Cognition-sensing and responding to the environment-is the unifying principle behind the genetic code, origin of life, evolution, consciousness, artificial intelligence, and cancer. However, the conventional model of biology seems to mistake cause and effect. According to the reductionist view, the causal chain in biology is chemicals → code → cognition. Despite this prevailing view, there are no examples in the literature to show that the laws of physics and chemistry can produce codes, or that codes produce cognition. Chemicals are just the physical layer of any information system. In contrast, although examples of cognition generating codes and codes controlling chemicals are ubiquitous in biology and technology, cognition remains a mystery. Thus, the central question in biology is: What is the nature and origin of cognition? In order to elucidate this pivotal question, we must cultivate a deeper understanding of information flows. Through this lens, we see that biological cognition is volitional (i.e., deliberate, intentional, or knowing), and while technology is constrained by deductive logic, living things make choices and generate novel information using inductive logic. Information has been called "the hard problem of life' and cannot be fully explained by known physical principles (Walker et al., 2017). The present paper uses information theory (the mathematical foundation of our digital age) and Turing machines (computers) to highlight inaccuracies in prevailing reductionist models of biology, and proposes that the correct causation sequence is cognition → code → chemicals.

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.

Alternative conformation of the C-domain of the P140 protein from Mycoplasma genitalium

The human pathogen Mycoplasma genitalium is responsible for urethritis in men, and for cervicitis and pelvic inflammatory disease in women. The adherence of M. genitalium to host target epithelial cells is mediated through an adhesion complex called Nap, which is essential for infectivity. Nap is a transmembrane dimer of heterodimers of the immunodominant proteins P110 and P140. The M. genitalium genome contains multiple copies of portions that share homology with the extracellular regions of P140 and P110 encoded by the genes mg191 and mg192, respectively. Homologous recombination between the genes and the copies allows the generation of a large diversity of P140 and P110 variants to overcome surveillance by the host immune system. Interestingly, the C-terminal domain (C-domain) of the extracellular region of P140, which is essential for the function of Nap by acting as a flexible stalk anchoring the protein to the mycoplasma membrane, presents a low degree of sequence variability. In the present work, the X-ray crystal structures of two crystal forms of a construct of the P140 C-domain are reported. In both crystal forms, the construct forms a compact octamer with D4 point-group symmetry. The structure of the C-domain determined in this work presents significant differences with respect to the structure of the C-domain found recently in intact P140. The structural plasticity of the C-domain appears to be a possible mechanism that may help in the functioning of the mycoplasma adhesion complex.

A RAGE Based Strategy for the Genome Engineering of the Human Respiratory Pathogen Mycoplasma pneumoniae

Genome engineering of microorganisms has become a standard in microbial biotechnologies. Several efficient tools are available for the genetic manipulation of model bacteria such as Escherichia coli and Bacillus subtilis, or the yeast Saccharomyces cerevisiae. Difficulties arise when transferring these tools to nonmodel organisms. Synthetic biology strategies relying on genome transplantation (GT) aim at using yeast cells for engineering bacterial genomes cloned as artificial chromosomes. However, these strategies remain unsuccessful for many bacteria, including Mycoplasma pneumoniae (MPN), a human pathogen infecting the respiratory tract that has been extensively studied as a model for systems biology of simple unicellular organisms. Here, we have designed a novel strategy for genome engineering based on the recombinase-assisted genomic engineering (RAGE) technology for editing the MPN genome. Using this strategy, we have introduced a 15 kbp fragment at a specific locus of the MPN genome and replaced 38 kbp from its genome by engineered versions modified either in yeast or in E. coli. A strain harboring a synthetic version of this fragment cleared of 13 nonessential genes could also be built and propagated in vitro. These strains were depleted of known virulence factors aiming at creating an avirulent chassis for SynBio applications. Such a chassis and technology are a step forward to build vaccines or deliver therapeutic compounds in the lungs to prevent or cure respiratory diseases in humans.

A Middle-Out Modeling Strategy to Extend a Colon Cancer Logical Model Improves Drug Synergy Predictions in Epithelial-Derived Cancer Cell Lines

Cancer is a heterogeneous and complex disease and one of the leading causes of death worldwide. The high tumor heterogeneity between individuals affected by the same cancer type is accompanied by distinct molecular and phenotypic tumor profiles and variation in drug treatment response. In silico modeling of cancer as an aberrantly regulated system of interacting signaling molecules provides a basis to enhance our biological understanding of disease progression, and it offers the means to use computer simulations to test and optimize drug therapy designs on particular cancer types and subtypes. This sets the stage for precision medicine: the design of treatments tailored to individuals or groups of patients based on their tumor-specific molecular cancer profiles. Here, we show how a relatively large manually curated logical model can be efficiently enhanced further by including components highlighted by a multi-omics data analysis of data from Consensus Molecular Subtypes covering colorectal cancer. The model expansion was performed in a pathway-centric manner, following a partitioning of the model into functional subsystems, named modules. The resulting approach constitutes a middle-out modeling strategy enabling a data-driven expansion of a model from a generic and intermediate level of molecular detail to a model better covering relevant processes that are affected in specific cancer subtypes, comprising 183 biological entities and 603 interactions between them, partitioned in 25 functional modules of varying size and structure. We tested this model for its ability to correctly predict drug combination synergies, against a dataset of experimentally determined cell growth responses with 18 drugs in all combinations, on eight cancer cell lines. The results indicate that the extended model had an improved accuracy for drug synergy prediction for the majority of the experimentally tested cancer cell lines, although significant improvements of the model's predictive performance are still needed. Our study demonstrates how a tumor-data driven middle-out approach toward refining a logical model of a biological system can further customize a computer model to represent specific cancer cell lines and provide a basis for identifying synergistic effects of drugs targeting specific regulatory proteins. This approach bridges between preclinical cancer model data and clinical patient data and may thereby ultimately be of help to develop patient-specific in silico models that can steer treatment decisions in the clinic.

Correlated chromosomal periodicities according to the growth rate and gene expression

Linking genetic information to population fitness is crucial to understanding living organisms. Despite the abundant knowledge of the genetic contribution to growth, the overall patterns/features connecting genes, their expression, and growth remain unclear. To reveal the quantitative and direct connections, systematic growth assays of single-gene knockout Escherichia coli strains under both rich and poor nutritional conditions were performed; subsequently, the resultant growth rates were associated with the original expression levels of the knockout genes in the parental genome. Comparative analysis of growth and the transcriptome identified not only the nutritionally differentiated fitness cost genes but also a significant correlation between the growth rates of the single-gene knockout strains and the original expression levels of these knockout genes in the parental strain, regardless of the nutritional variation. In addition, the coordinated chromosomal periodicities of the wild-type transcriptome and the growth rates of the strains lacking the corresponding genes were observed. The common six-period periodicity was somehow attributed to the essential genes, although the underlying mechanism remains to be addressed. The correlated chromosomal periodicities associated with the gene expression-growth dataset were highly valuable for bacterial growth prediction and discovering the working principles governing minimal genetic information.

Key Challenges in Designing CHO Chassis Platforms

Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines.

The Construction of Biological 'Inter-Identity' as the Outcome of a Complex Process of Protocell Development in Prebiotic Evolution

The concept of identity is used both (i) to distinguish a system as a particular material entity that is conserved as such in a given environment (token-identity: i.e., identity as permanence or endurance over time), and (ii) to relate a system with other members of a set (type-identity: i.e., identity as an equivalence relationship). Biological systems are characterized, in a minimal and universal sense, by a highly complex and dynamic, far-from-equilibrium organization of very diverse molecular components and transformation processes (i.e., 'genetically instructed cellular metabolisms') that maintain themselves in constant interaction with their corresponding environments, including other systems of similar nature. More precisely, all living entities depend on a deeply convoluted organization of molecules and processes (a naturalized von Neumann constructor architecture) that subsumes, in the form of current individuals (autonomous cells), a history of ecological and evolutionary interactions (across cell populations). So one can defend, on those grounds, that living beings have an identity of their own from both approximations: (i) and (ii). These transversal and trans-generational dimensions of biological phenomena, which unfold together with the actual process of biogenesis, must be carefully considered in order to understand the intricacies and metabolic robustness of the first living cells, their underlying uniformity (i.e., their common biochemical core) and the eradication of previous -or alternative- forms of complex natural phenomena. Therefore, a comprehensive approach to the origins of life requires conjugating the actual properties of the developing complex individuals (fusing and dividing protocells, at various stages) with other, population-level features, linked to their collective-evolutionary behavior, under much wider and longer-term parameters. On these lines, we will argue that life, in its most basic sense, here on Earth or anywhere else, demands crossing a high complexity threshold and that the concept of 'inter-identity' can help us realize the different aspects involved in the process. The article concludes by pointing out some of the challenges ahead if we are to integrate the corresponding explanatory frameworks, physiological and evolutionary, in the hope that a more general theory of biology is on its way.

Comprehensive dissection of dispensable genomic regions in Streptomyces based on comparative analysis approach

BACKGROUND

Large-scale genome reduction has been performed to significantly improve the performance of microbial chassis. Identification of the essential or dispensable genes is pivotal for genome reduction to avoid synthetic lethality. Here, taking Streptomyces as an example, we developed a combinatorial strategy for systematic identification of large and dispensable genomic regions in Streptomyces based on multi-omics approaches.

RESULTS

Phylogenetic tree analysis revealed that the model strains including S. coelicolor A3(2), S. albus J1074 and S. avermitilis MA-4680 were preferred reference for comparative analysis of candidate genomes. Multiple genome alignment suggested that the Streptomyces genomes embodied highly conserved core region and variable sub-telomeric regions, and may present symmetric or asymmetric structure. Pan-genome and functional genome analyses showed that most conserved genes responsible for the fundamental functions of cell viability were concentrated in the core region and the vast majority of abundant genes were dispersed in the sub-telomeric regions. These results suggested that large-scale deletion can be performed in sub-telomeric regions to greatly streamline the Streptomyces genomes for developing versatile chassis.

CONCLUSIONS

The integrative approach of comparative genomics, functional genomics and pan-genomics can not only be applied to perform a multi-tiered dissection for Streptomyces genomes, but also work as a universal method for systematic analysis of removable regions in other microbial hosts in order to generate more miscellaneous and versatile chassis with minimized genome for drug discovery.

Structure of P46, an immunodominant surface protein from Mycoplasma hyopneumoniae: interaction with a monoclonal antibody

Mycoplasma hyopneumoniae is a prokaryotic pathogen that colonizes the respiratory ciliated epithelial cells in swine. Infected animals suffer respiratory lesions, causing major economic losses in the porcine industry. Characterization of the immunodominant membrane-associated proteins from M. hyopneumoniae may be instrumental in the development of new therapeutic approaches. Here, the crystal structure of P46, one of the main surface-antigen proteins, from M. hyopneumoniae is presented and shows N- and C-terminal α/β domains connected by a hinge. The structures solved in this work include a ligand-free open form of P46 (3.1 Å resolution) and two ligand-bound structures of P46 with maltose (2.5 Å resolution) and xylose (3.5 Å resolution) in open and closed conformations, respectively. The ligand-binding site is buried in the cleft between the domains at the hinge region. The two domains of P46 can rotate with respect to each other, giving open or closed alternative conformations. In agreement with this structural information, sequence analyses show similarities to substrate-binding members of the ABC transporter superfamily, with P46 facing the extracellular side as a functional subunit. In the structure with xylose, P46 was also bound to a high-affinity (K_d = 29 nM) Fab fragment from a monoclonal antibody, allowing the characterization of a structural epitope in P46 that exclusively involves residues from the C-terminal domain. The Fab structure in the complex with P46 shows only small conformational rearrangements in the six complementarity-determining regions (CDRs) with respect to the unbound Fab (the structure of which is also determined in this work at 1.95 Å resolution). The structural information that is now available should contribute to a better understanding of sugar nutrient intake by M. hyopneumoniae. This information will also allow the design of protocols and strategies for the generation of new vaccines against this important swine pathogen.

Chromosome-free bacterial cells are safe and programmable platforms for synthetic biology

A type of chromosome-free cell called SimCells (simple cells) has been generated from Escherichia coli, Pseudomonas putida, and Ralstonia eutropha. The removal of the native chromosomes of these bacteria was achieved by double-stranded breaks made by heterologous I-CeuI endonuclease and the degradation activity of endogenous nucleases. We have shown that the cellular machinery remained functional in these chromosome-free SimCells and was able to process various genetic circuits. This includes the glycolysis pathway (composed of 10 genes) and inducible genetic circuits. It was found that the glycolysis pathway significantly extended longevity of SimCells due to its ability to regenerate ATP and NADH/NADPH. The SimCells were able to continuously express synthetic genetic circuits for 10 d after chromosome removal. As a proof of principle, we demonstrated that SimCells can be used as a safe agent (as they cannot replicate) for bacterial therapy. SimCells were used to synthesize catechol (a potent anticancer drug) from salicylic acid to inhibit lung, brain, and soft-tissue cancer cells. SimCells represent a simplified synthetic biology chassis that can be programmed to manufacture and deliver products safely without interference from the host genome.

The Future of Origin of Life Research: Bridging Decades-Old Divisions

Research on the origin of life is highly heterogeneous. After a peculiar historical development, it still includes strongly opposed views which potentially hinder progress. In the 1st Interdisciplinary Origin of Life Meeting, early-career researchers gathered to explore the commonalities between theories and approaches, critical divergence points, and expectations for the future. We find that even though classical approaches and theories-e.g. bottom-up and top-down, RNA world vs. metabolism-first-have been prevalent in origin of life research, they are ceasing to be mutually exclusive and they can and should feed integrating approaches. Here we focus on pressing questions and recent developments that bridge the classical disciplines and approaches, and highlight expectations for future endeavours in origin of life research.

Minimalist Protocell Design: A Molecular System Based Solely on Proteins that Form Dynamic Vesicular Membranes Embedding Enzymatic Functions

Life in its molecular context is characterized by the challenge of orchestrating structure, energy and information processes through compartmentalization and chemical transformations amenable to mimicry of protocell models. Here we present an alternative protocell model incorporating dynamic membranes based on amphiphilic elastin-like proteins (ELPs) rather than phospholipids. For the first time we demonstrate the feasibility of combining vesicular membrane formation and biocatalytic activity with molecular entities of a single class: proteins. The presented self-assembled protein-membrane-based compartments (PMBCs) accommodate either an anabolic reaction, based on free DNA ligase as an example of information transformation processes, or a catabolic process. We present a catabolic process based on a single molecular entity combining an amphiphilic protein with tobacco etch virus (TEV) protease as part of the enclosure of a reaction space and facilitating selective catalytic transformations. Combining compartmentalization and biocatalytic activity by utilizing an amphiphilic molecular building block with and without enzyme functionalization enables new strategies in bottom-up synthetic biology, regenerative medicine, pharmaceutical science and biotechnology.

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.

Rational construction of genome-reduced and high-efficient industrial Streptomyces chassis based on multiple comparative genomic approaches

BACKGROUND

Streptomyces chattanoogensis L10 is the industrial producer of natamycin and has been proved a highly efficient host for diverse natural products. It has an enormous potential to be developed as a versatile cell factory for production of heterologous secondary metabolites. Here we developed a genome-reduced industrial Streptomyces chassis by rational 'design-build-test' pipeline.

RESULTS

To identify candidate large non-essential genomic regions accurately and design large deletion rationally, we performed genome analyses of S. chattanoogensis L10 by multiple computational approaches, optimized Cre/loxP recombination system for high-efficient large deletion and constructed a series of universal suicide plasmids for rapid loxP or loxP mutant sites inserting into genome. Subsequently, two genome-streamlined mutants, designated S. chattanoogensis L320 and L321, were rationally constructed by depletion of 1.3 Mb and 0.7 Mb non-essential genomic regions, respectively. Furthermore, several biological performances like growth cycle, secondary metabolite profile, hyphae morphological engineering, intracellular energy (ATP) and reducing power (NADPH/NADP⁺) levels, transformation efficiency, genetic stability, productivity of heterologous proteins and secondary metabolite were systematically evaluated. Finally, our results revealed that L321 could serve as an efficient chassis for the production of polyketides.

CONCLUSIONS

Here we developed the combined strategy of multiple computational approaches and site-specific recombination system to rationally construct genome-reduced Streptomyces hosts with high efficiency. Moreover, a genome-reduced industrial Streptomyces chassis S. chattanoogensis L321 was rationally constructed by the strategy, and the chassis exhibited several emergent and excellent performances for heterologous expression of secondary metabolite. The strategy could be widely applied in other Streptomyces to generate miscellaneous and versatile chassis with minimized genome. These chassis can not only serve as cell factories for high-efficient production of valuable polyketides, but also will provide great support for the upgrade of microbial pharmaceutical industry and drug discovery.

Chasing bacterial chassis for metabolic engineering: a perspective review from classical to non-traditional microorganisms

The last few years have witnessed an unprecedented increase in the number of novel bacterial species that hold potential to be used for metabolic engineering. Historically, however, only a handful of bacteria have attained the acceptance and widespread use that are needed to fulfil the needs of industrial bioproduction - and only for the synthesis of very few, structurally simple compounds. One of the reasons for this unfortunate circumstance has been the dearth of tools for targeted genome engineering of bacterial chassis, and, nowadays, synthetic biology is significantly helping to bridge such knowledge gap. Against this background, in this review, we discuss the state of the art in the rational design and construction of robust bacterial chassis for metabolic engineering, presenting key examples of bacterial species that have secured a place in industrial bioproduction. The emergence of novel bacterial chassis is also considered at the light of the unique properties of their physiology and metabolism, and the practical applications in which they are expected to outperform other microbial platforms. Emerging opportunities, essential strategies to enable successful development of industrial phenotypes, and major challenges in the field of bacterial chassis development are also discussed, outlining the solutions that contemporary synthetic biology-guided metabolic engineering offers to tackle these issues.

A planarian nidovirus expands the limits of RNA genome size

RNA viruses are the only known RNA-protein (RNP) entities capable of autonomous replication (albeit within a permissive host environment). A 33.5 kilobase (kb) nidovirus has been considered close to the upper size limit for such entities; conversely, the minimal cellular DNA genome is in the 100–300 kb range. This large difference presents a daunting gap for the transition from primordial RNP to contemporary DNA-RNP-based life. Whether or not RNA viruses represent transitional steps towards DNA-based life, studies of larger RNA viruses advance our understanding of the size constraints on RNP entities and the role of genome size in virus adaptation. For example, emergence of the largest previously known RNA genomes (20–34 kb in positive-stranded nidoviruses, including coronaviruses) is associated with the acquisition of a proofreading exoribonuclease (ExoN) encoded in the open reading frame 1b (ORF1b) in a monophyletic subset of nidoviruses. However, apparent constraints on the size of ORF1b, which encodes this and other key replicative enzymes, have been hypothesized to limit further expansion of these viral RNA genomes. Here, we characterize a novel nidovirus (planarian secretory cell nidovirus; PSCNV) whose disproportionately large ORF1b-like region including unannotated domains, and overall 41.1-kb genome, substantially extend the presumed limits on RNA genome size. This genome encodes a predicted 13,556-aa polyprotein in an unconventional single ORF, yet retains canonical nidoviral genome organization and expression, as well as key replicative domains. These domains may include functionally relevant substitutions rarely or never before observed in highly conserved sites of RdRp, NiRAN, ExoN and 3CLpro. Our evolutionary analysis suggests that PSCNV diverged early from multi-ORF nidoviruses, and acquired additional genes, including those typical of large DNA viruses or hosts, e.g. Ankyrin and Fibronectin type II, which might modulate virus-host interactions. PSCNV's greatly expanded genome, proteomic complexity, and unique features–impressive in themselves–attest to the likelihood of still-larger RNA genomes awaiting discovery.

RNA viruses are the only known RNA-protein (RNP) entities capable of autonomous replication. The upper genome size for such entities was assumed to be <35 kb; conversely, the minimal cellular DNA genome is in the 100–300 kilobase (kb) range. This large difference presents a daunting gap for the proposed evolution of contemporary DNA-RNP-based life from primordial RNP entities. Here, we describe a nidovirus from planarians, named planarian secretory cell nidovirus (PSCNV), whose 41.1 kb genome is 23% larger than any riboviral genome yet discovered. This increase is nearly equivalent in size to the entire poliovirus genome, and it equips PSCNV with an unprecedented extra coding capacity to adapt. PSCNV has broken apparent constraints on the size of the genomic subregion that encodes core replication machinery in other nidoviruses, including coronaviruses, and has acquired genes not previously observed in RNA viruses. This virus challenges and advances our understanding of the limits to RNA genome size.

Aptamer-enabled uptake of small molecule ligands

The relative ease of isolating aptamers with high specificity for target molecules suggests that molecular recognition may be common in the folds of natural RNAs. We show here that, when expressed in cells, aptamers can increase the intracellular concentrations of their small molecule ligands. We have named these aptamers as DRAGINs (Drug Binding Aptamers for Growing Intracellular Numbers). The DRAGIN property, assessed here by the ability to enhance the toxicity of their ligands, was found for some, but not all, aminoglycoside aptamers. One aptamer protected cells against killing by its ligand. Another aptamer promoted killing as a singlemer and protected against killing as a tandemer. Based on a mathematical model, cell protection vs. killing is proposed as governed by aptamer affinity and access to the inner surface of the cell membrane, with the latter being a critical determinant. With RNA molecules proposed as the earliest functional polymers to drive the evolution of life, we suggest that RNA aptamer-like structures present in primitive cells might have selectively concentrated precursors for polymer synthesis. Riboswitches may be the evolved forms of these ancient aptamer-like “nutrient procurers”. Aptamers with DRAGIN capability in the modern world could be applied for imaging cells, in synthetic cell constructs, or to draw drugs into cells to make “undruggable” targets accessible to small molecule inhibitors.

Designing with living systems in the synthetic yeast project

Synthetic biology is challenged by the complexity and the unpredictability of living systems. While one response to this complexity involves simplifying cells to create more fully specified systems, another approach utilizes directed evolution, releasing some control and using unpredictable change to achieve design goals. Here we discuss SCRaMbLE, employed in the synthetic yeast project, as an example of synthetic biology design through working with living systems. SCRaMbLE is a designed tool without being a design tool, harnessing the activities of the yeast rather than relying entirely on scientists’ deliberate choices. We suggest that directed evolution at the level of the whole organism allows scientists and microorganisms to “collaborate” to achieve design goals, suggesting new directions for synthetic biology.

Synthetic biology often views the organism as a chassis into which a circuit can be inserted. Here the authors explore the idea of the organism as a core aspect of design, aiding researchers in navigating the genetic space opened up by SCRaMbLE.

On an algorithmic definition for the components of the minimal cell

Living cells are highly complex systems comprising a multitude of elements that are engaged in the many convoluted processes observed during the cell cycle. However, not all elements and processes are essential for cell survival and reproduction under steady-state environmental conditions. To distinguish between essential from expendable cell components and thus define the ‘minimal cell’ and the corresponding ‘minimal genome’, we postulate that the synthesis of all cell elements can be represented as a finite set of binary operators, and within this framework we show that cell elements that depend on their previous existence to be synthesized are those that are essential for cell survival. An algorithm to distinguish essential cell elements is presented and demonstrated within an interactome. Data and functions implementing the algorithm are given as supporting information. We expect that this algorithmic approach will lead to the determination of the complete interactome of the minimal cell, which could then be experimentally validated. The assumptions behind this hypothesis as well as its consequences for experimental and theoretical biology are discussed.

Developing genome-reduced Pseudomonas chlororaphis strains for the production of secondary metabolites

BACKGROUND

The current chassis organisms or various types of cell factories have considerable advantages and disadvantages. Therefore, it is necessary to develop various chassis for an efficient production of different bioproducts from renewable resources. In this context, synthetic biology offers unique potentialities to produce value-added products of interests. Microbial genome reduction and modification are important strategies for constructing cellular chassis and cell factories. Many genome-reduced strains from Escherichia coli, Bacillus subtilis, Corynebacterium glutamicum and Streptomyces, have been widely used for the production of amino acids, organic acids, and some enzymes. Some Pseudomonas strains could serve as good candidates for ideal chassis cells since they grow fast and can produce many valuable metabolites with low nutritional requirements and strong environmental adaptability. Pseudomonas chlororaphis GP72 is a non-pathogenic plant growth-promoting rhizobacterium that possesses capacities of tolerating various environmental stresses and synthesizing many kinds of bioactive compounds with high yield. These include phenazine-1-carboxylic acid (PCA) and 2-hydroxyphenazine (2-OH-PHZ), which exhibit strong bacteriostatic and antifungal activity toward some microbial pathogens.

RESULTS

We depleted 685 kb (10.3% of the genomic sequence) from the chromosome of P. chlororaphis GP72(rpeA-) by a markerless deletion method, which included five secondary metabolic gene clusters and 17 strain-specific regions (525 non-essential genes). Then we characterized the 22 multiple-deletion series (MDS) strains. Growth characteristics, production of phenazines and morphologies were changed greatly in mutants with large-fragment deletions. Some of the genome-reduced P. chlororaphis mutants exhibited more productivity than the parental strain GP72(rpeA-). For example, strain MDS22 had 4.4 times higher production of 2-OH-PHZ (99.1 mg/L) than strain GP72(rpeA-), and the specific 2-OH-PHZ production rate (mmol/g/h) increased 11.5-fold. Also and MDS10 had the highest phenazine production (852.0 mg/L) among all the studied strains with a relatively high specific total phenazine production rate (0.0056 g/g/h).

CONCLUSIONS

In conclusion, P. chlororaphis strains with reduced genome performed better in production of secondary metabolites than the parent strain. The newly developed mutants can be used for the further genetic manipulation to construct chassis cells with the less complex metabolic network, better regulation and more efficient productivity for diverse biotechnological applications.

Coordinated Changes in Mutation and Growth Rates Induced by Genome Reduction

Genome size is determined during evolution, but it can also be altered by genetic engineering in laboratories. The systematic characterization of reduced genomes provides valuable insights into the cellular properties that are quantitatively described by the global parameters related to the dynamics of growth and mutation. In the present study, we analyzed a small collection of W3110 Escherichia coli derivatives containing either the wild-type genome or reduced genomes of various lengths to examine whether the mutation rate, a global parameter representing genomic plasticity, was affected by genome reduction. We found that the mutation rates of these cells increased with genome reduction. The correlation between genome length and mutation rate, which has been reported for the evolution of bacteria, was also identified, intriguingly, for genome reduction. Gene function enrichment analysis indicated that the deletion of many of the genes encoding membrane and transport proteins play a role in the mutation rate changes mediated by genome reduction. Furthermore, the increase in the mutation rate with genome reduction was highly associated with a decrease in the growth rate in a nutrition-dependent manner; thus, poorer media showed a larger change that was of higher significance. This negative correlation was strongly supported by experimental evidence that the serial transfer of the reduced genome improved the growth rate and reduced the mutation rate to a large extent. Taken together, the global parameters corresponding to the genome, growth, and mutation showed a coordinated relationship, which might be an essential working principle for balancing the cellular dynamics appropriate to the environment.

Genome reduction is a powerful approach for investigating the fundamental rules for living systems. Whether genetically disturbed genomes have any specific properties that are different from or similar to those of natively evolved genomes has been under investigation. In the present study, we found that Escherichia coli cells with reduced genomes showed accelerated nucleotide substitution errors (mutation rates), although these cells retained the normal DNA mismatch repair systems. Intriguingly, this finding of correlation between reduced genome size and a higher mutation rate was consistent with the reported evolution of mutation rates. Furthermore, the increased mutation rate was quantitatively associated with a decreased growth rate, indicating that the global parameters related to the genome, growth, and mutation, which represent the amount of genetic information, the efficiency of propagation, and the fidelity of replication, respectively, are dynamically coordinated.

Giant liposome formation toward the synthesis of well-defined artificial cells

This review focuses on microfluidic technologies for giant liposome formations which emulate environments of biological cells.

Large-scale reduction of the Bacillus subtilis genome: consequences for the transcriptional network, resource allocation, and metabolism

Understanding cellular life requires a comprehensive knowledge of the essential cellular functions, the components involved, and their interactions. Minimized genomes are an important tool to gain this knowledge. We have constructed strains of the model bacterium, Bacillus subtilis, whose genomes have been reduced by ∼36%. These strains are fully viable, and their growth rates in complex medium are comparable to those of wild type strains. An in-depth multi-omics analysis of the genome reduced strains revealed how the deletions affect the transcription regulatory network of the cell, translation resource allocation, and metabolism. A comparison of gene counts and resource allocation demonstrates drastic differences in the two parameters, with 50% of the genes using as little as 10% of translation capacity, whereas the 6% essential genes require 57% of the translation resources. Taken together, the results are a valuable resource on gene dispensability in B. subtilis, and they suggest the roads to further genome reduction to approach the final aim of a minimal cell in which all functions are understood.

Construction of a minimal genome as a chassis for synthetic biology

Microbial diversity and complexity pose challenges in understanding the voluminous genetic information produced from whole-genome sequences, bioinformatics and high-throughput ‘-omics’ research. These challenges can be overcome by a core blueprint of a genome drawn with a minimal gene set, which is essential for life. Systems biology and large-scale gene inactivation studies have estimated the number of essential genes to be ∼300–500 in many microbial genomes. On the basis of the essential gene set information, minimal-genome strains have been generated using sophisticated genome engineering techniques, such as genome reduction and chemical genome synthesis. Current size-reduced genomes are not perfect minimal genomes, but chemically synthesized genomes have just been constructed. Some minimal genomes provide various desirable functions for bioindustry, such as improved genome stability, increased transformation efficacy and improved production of biomaterials. The minimal genome as a chassis genome for synthetic biology can be used to construct custom-designed genomes for various practical and industrial applications.

The Blueprint of a Minimal Cell: MiniBacillus

Bacillus subtilis is one of the best-studied organisms. Due to the broad knowledge and annotation and the well-developed genetic system, this bacterium is an excellent starting point for genome minimization with the aim of constructing a minimal cell. We have analyzed the genome of B. subtilis and selected all genes that are required to allow life in complex medium at 37°C. This selection is based on the known information on essential genes and functions as well as on gene and protein expression data and gene conservation. The list presented here includes 523 and 119 genes coding for proteins and RNAs, respectively. These proteins and RNAs are required for the basic functions of life in information processing (replication and chromosome maintenance, transcription, translation, protein folding, and secretion), metabolism, cell division, and the integrity of the minimal cell. The completeness of the selected metabolic pathways, reactions, and enzymes was verified by the development of a model of metabolism of the minimal cell. A comparison of the MiniBacillus genome to the recently reported designed minimal genome of Mycoplasma mycoides JCVI-syn3.0 indicates excellent agreement in the information-processing pathways, whereas each species has a metabolism that reflects specific evolution and adaptation. The blueprint of MiniBacillus presented here serves as the starting point for a successive reduction of the B. subtilis genome.

Correlation between genome reduction and bacterial growth

Genome reduction by removing dispensable genomic sequences in bacteria is commonly used in both fundamental and applied studies to determine the minimal genetic requirements for a living system or to develop highly efficient bioreactors. Nevertheless, whether and how the accumulative loss of dispensable genomic sequences disturbs bacterial growth remains unclear. To investigate the relationship between genome reduction and growth, a series of Escherichia coli strains carrying genomes reduced in a stepwise manner were used. Intensive growth analyses revealed that the accumulation of multiple genomic deletions caused decreases in the exponential growth rate and the saturated cell density in a deletion-length-dependent manner as well as gradual changes in the patterns of growth dynamics, regardless of the growth media. Accordingly, a perspective growth model linking genome evolution to genome engineering was proposed. This study provides the first demonstration of a quantitative connection between genomic sequence and bacterial growth, indicating that growth rate is potentially associated with dispensable genomic sequences.

Tactic, reactive, and functional droplets outside of equilibrium

Droplets subject to non-equilibrium conditions can exhibit a range of biomimetic and “intelligent” behaviors.

Rational design of efficient modular cells

The modular cell design principle is formulated to devise modular (chassis) cells. These cells can be assembled with exchangeable production modules in a plug-and-play fashion to build microbial cell factories for efficient combinatorial biosynthesis of novel molecules, requiring minimal iterative strain optimization steps. A modular cell is designed to be auxotrophic, containing core metabolic pathways that are necessary but insufficient to support cell growth and maintenance. To be functional, it must tightly couple with an exchangeable production module containing auxiliary metabolic pathways that not only complement cell growth but also enhance production of targeted molecules. We developed a MODCELL (modular cell) framework based on metabolic pathway analysis to implement the modular cell design principle. MODCELL identifies genetic modifications and requirements to construct modular cell candidates and their associated exchangeable production modules. By defining the degree of similarity and coupling metrics, MODCELL can evaluate which exchangeable production module(s) can be tightly coupled with a modular cell candidate. We first demonstrated how MODCELL works in a step-by-step manner for example metabolic networks, and then applied it to design modular Escherichia coli cells for efficient combinatorial biosynthesis of five alcohols (ethanol, propanol, isopropanol, butanol and isobutanol) and five butyrate esters (ethyl butyrate, propyl butyrate, isopropyl butyrate, butyl butyrate and isobutyl butyrate) from pentose sugars (arabinose and xylose) and hexose sugars (glucose, mannose, and galactose) under anaerobic conditions. We identified three modular cells, MODCELL1, MODCELL2 and MODCELL3, that can couple well with Group 1 of modules (ethanol, isobutanol, butanol, ethyl butyrate, isobutyl butyrate, butyl butyrate), Group 2 (isopropanol, isopropyl butyrate), and Group 3 (propanol, isopropanol), respectively. We validated the design of MODCELL1 for anaerobic production of ethanol, butanol, and ethyl butyrate using experimental data available in literature.