The minimal genome concept

The Development and Opportunities of Predictive Biotechnology

Recent advances in bioeconomy allow a holistic view of existing and new process chains and enable novel production routines continuously advanced by academia and industry. All this progress benefits from a growing number of prediction tools that have found their way into the field. For example, automated genome annotations, tools for building model structures of proteins, and structural protein prediction methods such as AlphaFold2TM or RoseTTAFold have gained popularity in recent years. Recently, it has become apparent that more and more AI-based tools are being developed and used for biocatalysis and biotechnology. This is an excellent opportunity for academia and industry to accelerate advancements in the field further. Biotechnology, as a rapidly growing interdisciplinary field, stands to benefit greatly from these developments.

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.

Architecture, Function, Regulation, and Evolution of α-Glucans Metabolic Enzymes in Prokaryotes

Bacteria have acquired sophisticated mechanisms for assembling and disassembling polysaccharides of different chemistry. α-d-Glucose homopolysaccharides, so-called α-glucans, are the most widespread polymers in nature being key components of microorganisms. Glycogen functions as an intracellular energy storage while some bacteria also produce extracellular assorted α-glucans. The classical bacterial glycogen metabolic pathway comprises the action of ADP-glucose pyrophosphorylase and glycogen synthase, whereas extracellular α-glucans are mostly related to peripheral enzymes dependent on sucrose. An alternative pathway of glycogen biosynthesis, operating via a maltose 1-phosphate polymerizing enzyme, displays an essential wiring with the trehalose metabolism to interconvert disaccharides into polysaccharides. Furthermore, some bacteria show a connection of intracellular glycogen metabolism with the genesis of extracellular capsular α-glucans, revealing a relationship between the storage and structural function of these compounds. Altogether, the current picture shows that bacteria have evolved an intricate α-glucan metabolism that ultimately relies on the evolution of a specific enzymatic machinery. The structural landscape of these enzymes exposes a limited number of core catalytic folds handling many different chemical reactions. In this Review, we present a rationale to explain how the chemical diversity of α-glucans emerged from these systems, highlighting the underlying structural evolution of the enzymes driving α-glucan bacterial metabolism.

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

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.

Controlled exchange of protein and nucleic acid signals from and between synthetic minimal cells

Synthetic minimal cells are a class of bioreactors that have some, but not all, functions of live cells. Here, we report a critical step toward the development of a bottom-up minimal cell: cellular export of functional protein and RNA products. We used cell-penetrating peptide tags to translocate payloads across a synthetic cell vesicle membrane. We demonstrated efficient transport of active enzymes and transport of nucleic acid payloads by RNA-binding proteins. We investigated influence of a concentration gradient alongside other factors on the efficiency of the translocation, and we show a method to increase product accumulation in one location. We demonstrate the use of this technology to engineer molecular communication between different populations of synthetic cells, to exchange protein and nucleic acid signals. The synthetic minimal cell production and export of proteins or nucleic acids allows experimental designs that approach the complexity and relevancy of natural biological systems. A record of this paper's transparent peer review process is included in the supplemental information.

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.

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 Minimal Translation Machinery: What We Can Learn From Naturally and Experimentally Reduced Genomes

The current theoretical proposals of minimal genomes have not attempted to outline the essential machinery for proper translation in cells. Here, we present a proposal of a minimal translation machinery based on (1) a comparative analysis of bacterial genomes of insects’ endosymbionts using a machine learning classification algorithm, (2) the empiric genomic information obtained from Mycoplasma mycoides JCVI-syn3.0 the first minimal bacterial genome obtained by design and synthesis, and (3) a detailed functional analysis of the candidate genes based on essentiality according to the DEG database (Escherichia coli and Bacillus subtilis) and the literature. This proposed minimal translational machinery is composed by 142 genes which must be present in any synthetic prokaryotic cell designed for biotechnological purposes, 76.8% of which are shared with JCVI-syn3.0. Eight additional genes were manually included in the proposal for a proper and efficient translation.

Microbial cell surface engineering for high-level synthesis of bio-products

Microbial cell surface layers, which mainly include the cell membrane, cell wall, periplasmic space, outer membrane, capsules, S-layers, pili, and flagella, control material exchange between the cell and the extracellular environment, and have great impact on production titers and yields of various bio-products synthesized by microbes. Recent research work has made exciting achievements in metabolic engineering using microbial cell surface components as novel regulation targets without direct modifications of the metabolic pathways of the desired products. This review article will summarize the accomplishments obtained in this emerging field, and will describe various engineering strategies that have been adopted in bacteria and yeasts for the enhancement of mass transfer across the cell surface, improvement of protein expression and folding, modulation of cell size and shape, and re-direction of cellular resources, all of which contribute to the construction of more efficient microbial cell factories toward the synthesis of a variety of bio-products. The existing problems and possible future directions will also be discussed.

An assessment of genome annotation coverage across the bacterial tree of life

Although gene-finding in bacterial genomes is relatively straightforward, the automated assignment of gene function is still challenging, resulting in a vast quantity of hypothetical sequences of unknown function. But how prevalent are hypothetical sequences across bacteria, what proportion of genes in different bacterial genomes remain unannotated, and what factors affect annotation completeness? To address these questions, we surveyed over 27 000 bacterial genomes from the Genome Taxonomy Database, and measured genome annotation completeness as a function of annotation method, taxonomy, genome size, 'research bias' and publication date. Our analysis revealed that 52 and 79 % of the average bacterial proteome could be functionally annotated based on protein and domain-based homology searches, respectively. Annotation coverage using protein homology search varied significantly from as low as 14 % in some species to as high as 98 % in others. We found that taxonomy is a major factor influencing annotation completeness, with distinct trends observed across the microbial tree (e.g. the lowest level of completeness was found in the Patescibacteria lineage). Most lineages showed a significant association between genome size and annotation incompleteness, likely reflecting a greater degree of uncharacterized sequences in 'accessory' proteomes than in 'core' proteomes. Finally, research bias, as measured by publication volume, was also an important factor influencing genome annotation completeness, with early model organisms showing high completeness levels relative to other genomes in their own taxonomic lineages. Our work highlights the disparity in annotation coverage across the bacterial tree of life and emphasizes a need for more experimental characterization of accessory proteomes as well as understudied lineages.

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.

Life in The Context of Order and Complexity

It is generally accepted that life requires structural complexity. However, a chaotic mixture of organic compounds like the one formed by extensive reaction sequences over time may be extremely complex, but could just represent a static asphalt-like dead end situation. Likewise, it is accepted that life requires a certain degree of structural order. However, even extremely ordered structures like mineral crystals show no tendency to be alive. So neither complexity nor order alone can characterize a living organism. In order to come close to life, and in order for life to develop to higher organisms, both conditions have to be fulfilled and advanced simultaneously. Only a combination of the two requirements, complexity and structural order, can mark the difference between living and dead matter. It is essential for the development of prebiotic chemistry into life and characterizes the course and the result of Darwinian evolution. For this reason, it is worthwhile to define complexity and order as an essential pair of characteristics of life and to use them as fundamental parameters to evaluate early steps in prebiotic development. A combination of high order and high complexity also represents a universal type of biosignature which could be used to identify unknown forms of life or remnants thereof.

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.

Metagenomic Analysis of Fish-Associated Ca. Parilichlamydiaceae Reveals Striking Metabolic Similarities to the Terrestrial Chlamydiaceae

Chlamydiae are an example of obligate intracellular bacteria that possess highly reduced, compact genomes (1.0-3.5 Mbp), reflective of their abilities to sequester many essential nutrients from the host that they no longer need to synthesize themselves. The Chlamydiae is a phylum with a very wide host range spanning mammals, birds, fish, invertebrates, and unicellular protists. This ecological and phylogenetic diversity offers ongoing opportunities to study intracellular survival and metabolic pathways and adaptations. Of particular evolutionary significance are Chlamydiae from the recently proposed Ca. Parilichlamydiaceae, the earliest diverging clade in this phylum, species of which are found only in aquatic vertebrates. Gill extracts from three Chlamydiales-positive Australian aquaculture species (Yellowtail kingfish, Striped trumpeter, and Barramundi) were subject to DNA preparation to deplete host DNA and enrich microbial DNA, prior to metagenome sequencing. We assembled chlamydial genomes corresponding to three Ca. Parilichlamydiaceae species from gill metagenomes, and conducted functional genomics comparisons with diverse members of the phylum. This revealed highly reduced genomes more similar in size to the terrestrial Chlamydiaceae, standing in contrast to members of the Chlamydiae with a demonstrated cosmopolitan host range. We describe a reduction in genes encoding synthesis of nucleotides and amino acids, among other nutrients, and an enrichment of predicted transport proteins. Ca. Parilichlamydiaceae share 342 orthologs with other chlamydial families. We hypothesize that the genome reduction exhibited by Ca. Parilichlamydiaceae and Chlamydiaceae is an example of within-phylum convergent evolution. The factors driving these events remain to be elucidated.

Auxotrophy to Xeno-DNA: an exploration of combinatorial mechanisms for a high-fidelity biosafety system for synthetic biology applications

BACKGROUND

Biosafety is a key aspect in the international Genetically Engineered Machine (iGEM) competition, which offers student teams an amazing opportunity to pursue their own research projects in the field of Synthetic Biology. iGEM projects often involve the creation of genetically engineered bacterial strains. To minimize the risks associated with bacterial release, a variety of biosafety systems were constructed, either to prevent survival of bacteria outside the lab or to hinder horizontal or vertical gene transfer.

MAIN BODY

Physical containment methods such as bioreactors or microencapsulation are considered the first safety level. Additionally, various systems involving auxotrophies for both natural and synthetic compounds have been utilized by iGEM teams in recent years. Combinatorial systems comprising multiple auxotrophies have been shown to reduced escape frequencies below the detection limit. Furthermore, a number of natural toxin-antitoxin systems can be deployed to kill cells under certain conditions. Additionally, parts of naturally occurring toxin-antitoxin systems can be used for the construction of 'kill switches' controlled by synthetic regulatory modules, allowing control of cell survival. Kill switches prevent cell survival but do not completely degrade nucleic acids. To avoid horizontal gene transfer, multiple mechanisms to cleave nucleic acids can be employed, resulting in 'self-destruction' of cells. Changes in light or temperature conditions are powerful regulators of gene expression and could serve as triggers for kill switches or self-destruction systems. Xenobiology-based containment uses applications of Xeno-DNA, recoded codons and non-canonical amino acids to nullify the genetic information of constructed cells for wild type organisms. A 'minimal genome' approach brings the opportunity to reduce the genome of a cell to only genes necessary for survival under lab conditions. Such cells are unlikely to survive in the natural environment and are thus considered safe hosts. If suitable for the desired application, a shift to cell-free systems based on Xeno-DNA may represent the ultimate biosafety system.

CONCLUSION

Here we describe different containment approaches in synthetic biology, ranging from auxotrophies to minimal genomes, which can be combined to significantly improve reliability. Since the iGEM competition greatly increases the number of people involved in synthetic biology, we will focus especially on biosafety systems developed and applied in the context of the iGEM competition.

Genomic organization underlying deletional robustness in bacterial metabolic systems

Large-scale DNA deletions and gene loss are pervasive in bacterial genomes. This observation raises the possibility that evolutionary adaptation has altered bacterial genome organization to increase its robustness to large-scale tandem gene deletions. To find out, we systematically analyzed 55 bacterial genome-scale metabolisms and showed that metabolic gene ordering renders an organism's viability in multiple nutrient environments significantly more robust against tandem multigene deletions than expected by chance. This excess robustness is caused by multiple factors, which include the clustering of essential metabolic genes, a greater-than-expected distance of synthetically lethal metabolic gene pairs, and the clustering of nonessential metabolic genes. By computationally creating minimal genomes, we show that a nonadaptive origin of such clustering could in principle arise as a passive byproduct of bacterial genome growth. However, because genome randomization forces such as translocation and inversion would eventually erode such clustering, adaptive processes are necessary to sustain it. We provide evidence suggesting that this organization might result from adaptation to ongoing gene deletions, and from selective advantages associated with coregulating functionally related genes. Horizontal gene transfer in the presence of gene deletions contributes to sustaining the clustering of essential genes. In sum, our observations suggest that the genome organization of bacteria is driven by adaptive processes that provide phenotypic robustness in response to large-scale gene deletions. This robustness may be especially important for bacterial populations that take advantage of gene loss to adapt to new environments.

A Proposal of the Ur-proteome

Herein we outline a plausible proteome, encoded by assuming a primeval RNY genetic code. We unveil the primeval phenotype by using only the RNA genotype; it means that we recovered the most ancestral proteome, mostly made of the 8 amino acids encoded by RNY triplets. By looking at those fragments, it is noticeable that they are positioned, not at catalytic sites, but in the cofactor binding sites. It implies that the stabilization of a molecule appeared long before its catalytic activity, and therefore the Ur-proteome comprised a set of proteins modules that corresponded to Cofactor Stabilizing Binding Sites (CSBSs), which we call the primitive bindome. With our method, we reconstructed the structures of the "first protein modules" that Sobolevsky and Trifonov (2006) found by using only RMSD. We also examine the probable cofactors that bound to them. We discuss the notion of CSBSs as the first proteins modules in progenotes in the context of several proposals about the primitive forms of life.

Advances and perspectives in computational prediction of microbial gene essentiality

The minimal subset of genes required for cellular growth, survival and viability of an organism are classified as essential genes. Knowledge of essential genes gives insight into the core structure and functioning of a cell. This might lead to more efficient antimicrobial drug discovery, to elucidation of the correlations between genotype and phenotype, and a better understanding of the minimal requirements for a (synthetic) cell. Traditionally, constructing a catalog of essential genes for a given microbe involved costly and time-consuming laboratory experiments. While experimental methods have produced abundant gene essentiality data for model organisms like Escherichia coli and Bacillus subtilis, the knowledge generated cannot automatically be extrapolated to predict essential genes in all bacteria. In addition, essential genes identified in the laboratory are by definition 'conditionally essential', as they are essential under the specified experimental conditions: these might not resemble conditions in the microorganisms' natural habitat(s). Also, large-scale experimental assaying for essential genes is not always feasible because of the time investment required to setup these assays. The ability to rapidly and precisely identify essential genes in silico is therefore important and has great potential for applications in medicine, biotechnology and basic biological research. Here, we review the advances made in the use of computational methods to predict microbial gene essentiality, perspectives for the future of these techniques and the possible practical applications of essential genes.

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.

A novel proposal of a simplified bacterial gene set and the neo-construction of a general minimized metabolic network

A minimal gene set (MGS) is critical for the assembly of a minimal artificial cell. We have developed a proposal of simplifying bacterial gene set to approximate a bacterial MGS by the following procedure. First, we base our simplified bacterial gene set (SBGS) on experimentally determined essential genes to ensure that the genes included in the SBGS are critical. Second, we introduced a half-retaining strategy to extract persistent essential genes to ensure stability. Third, we constructed a viable metabolic network to supplement SBGS. The proposed SBGS includes 327 genes and required 431 reactions. This report describes an SBGS that preserves both self-replication and self-maintenance systems. In the minimized metabolic network, we identified five novel hub metabolites and confirmed 20 known hubs. Highly essential genes were found to distribute the connecting metabolites into more reactions. Based on our SBGS, we expanded the pool of targets for designing broad-spectrum antibacterial drugs to reduce pathogen resistance. We also suggested a rough semi-de novo strategy to synthesize an artificial cell, with potential applications in industry.

The evolution of early cellular systems viewed through the lens of biological interactions

The minimal cell concept represents a pragmatic approach to the question of how few genes are required to run a cell. This is a helpful way to build a parts-list, and has been more successful than attempts to deduce a minimal gene set for life by inferring the gene repertoire of the last universal common ancestor, as few genes trace back to this hypothetical ancestral state. However, the study of minimal cellular systems is the study of biological outliers where, by practical necessity, coevolutionary interactions are minimized or ignored. In this paper, we consider the biological context from which minimal genomes have been removed. For instance, some of the most reduced genomes are from endosymbionts and are the result of coevolutionary interactions with a host; few such organisms are "free-living." As few, if any, biological systems exist in complete isolation, we expect that, as with modern life, early biological systems were part of an ecosystem, replete with organismal interactions. We favor refocusing discussions of the evolution of cellular systems on processes rather than gene counts. We therefore draw a distinction between a pragmatic minimal cell (an interesting engineering problem), a distributed genome (a system resulting from an evolutionary transition involving more than one cell) and the looser coevolutionary interactions that are ubiquitous in ecosystems. Finally, we consider the distributed genome and coevolutionary interactions between genomic entities in the context of early evolution.

A novel essential domain perspective for exploring gene essentiality

MOTIVATION

Genes with indispensable functions are identified as essential; however, the traditional gene-level studies of essentiality have several limitations. In this study, we characterized gene essentiality from a new perspective of protein domains, the independent structural or functional units of a polypeptide chain.

RESULTS

To identify such essential domains, we have developed an Expectation-Maximization (EM) algorithm-based Essential Domain Prediction (EDP) Model. With simulated datasets, the model provided convergent results given different initial values and offered accurate predictions even with noise. We then applied the EDP model to six microbial species and predicted 1879 domains to be essential in at least one species, ranging 10-23% in each species. The predicted essential domains were more conserved than either non-essential domains or essential genes. Comparing essential domains in prokaryotes and eukaryotes revealed an evolutionary distance consistent with that inferred from ribosomal RNA. When utilizing these essential domains to reproduce the annotation of essential genes, we received accurate results that suggest protein domains are more basic units for the essentiality of genes. Furthermore, we presented several examples to illustrate how the combination of essential and non-essential domains can lead to genes with divergent essentiality. In summary, we have described the first systematic analysis on gene essentiality on the level of domains.

CONTACT

huilu.bioinfo@gmail.com or Long.Lu@cchmc.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Systems biology perspectives on minimal and simpler cells

The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells.

Discovering essential domains in essential genes

Genes with indispensable functions are identified as essential; however, the traditional gene-level perspective of essentiality has several limitations. We hypothesized that protein domains, the independent structural or functional units of a polypeptide chain, are responsible for gene essentiality. If the essentiality of domains is known, the essential genes could be identified. To find such essential domains, we have developed an EM algorithm-based Essential Domain Prediction (EDP) Model. With simulated datasets, the model provided convergent results given different initial values and offered accurate predictions even with noise. We then applied the EDP model to six microbes and predicted 3,450 domains to be essential in at least one species, ranging 8-24 % in each species.

The origins of cellular life

All life on earth can be naturally classified into cellular life forms and virus-like selfish elements, the latter being fully dependent on the former for their reproduction. Cells are reproducers that not only replicate their genome but also reproduce the cellular organization that depends on semipermeable, energy-transforming membranes and cannot be recovered from the genome alone, under the famous dictum of Rudolf Virchow, Omnis cellula e cellula. In contrast, simple selfish elements are replicators that can complete their life cycles within the host cell starting from genomic RNA or DNA alone. The origin of the cellular organization is the central and perhaps the hardest problem of evolutionary biology. I argue that the origin of cells can be understood only in conjunction with the origin and evolution of selfish genetic elements. A scenario of precellular evolution is presented that involves cohesion of the genomes of the emerging cellular life forms from primordial pools of small genetic elements that eventually segregated into hosts and parasites. I further present a model of the coevolution of primordial membranes and membrane proteins, discuss protocellular and non-cellular models of early evolution, and examine the habitats on the primordial earth that could have been conducive to precellular evolution and the origin of cells.

Evolving protein-protein interaction networks: A model based on duplication and mutation at different rates

We present a model describing the evolution of protein-protein interaction networks. The model is based on gene duplication and mutation. Considering rates of gene duplication and mutation, the average node degree and cluster coefficient are calculated for different parameters. The predicted degree distribution and cluster coefficient are in good agreement with the observed statistical properties obtained from the analysis of the yeast proteome.

Minimal genome encoding proteins with constrained amino acid repertoire

Minimal bacterial gene set comprises the genetic elements needed for survival of engineered bacterium on a rich medium. This set is estimated to include 300-350 protein-coding genes. One way of simplifying an organism with such a minimal genome even further is to constrain the amino acid content of its proteins. In this study, comparative genomics approaches and the results of gene knockout experiments were used to extrapolate the minimal gene set of mollicutes, and bioinformatics combined with the knowledge-based analysis of the structure-function relationships in these proteins and their orthologs, paralogs and analogs was applied to examine the challenges of completely replacing the rarest residue, cysteine. Among several known functions of cysteine residues, their roles in the active centers of the enzymes responsible for deoxyribonucleoside synthesis and transfer RNA modification appear to be crucial, as no alternative chemistry is known for these reactions. Thus, drastic reduction of the content of the rarest amino acid in a minimal proteome appears to be possible, but its complete elimination is challenging.

Protein charge and mass contribute to the spatio-temporal dynamics of protein-protein interactions in a minimal proteome

We constructed and simulated a "minimal proteome" model using Langevin dynamics. It contains 206 essential protein types that were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins that tend to have larger sizes can provide a large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that "proper" populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of Escherichia coli may have a larger protein-protein interaction network than that based on the lower organism Mycoplasma pneumoniae.

A statistical framework for improving genomic annotations of prokaryotic essential genes

Large-scale systematic analysis of gene essentiality is an important step closer toward unraveling the complex relationship between genotypes and phenotypes. Such analysis cannot be accomplished without unbiased and accurate annotations of essential genes. In current genomic databases, most of the essential gene annotations are derived from whole-genome transposon mutagenesis (TM), the most frequently used experimental approach for determining essential genes in microorganisms under defined conditions. However, there are substantial systematic biases associated with TM experiments. In this study, we developed a novel Poisson model–based statistical framework to simulate the TM insertion process and subsequently correct the experimental biases. We first quantitatively assessed the effects of major factors that potentially influence the accuracy of TM and subsequently incorporated relevant factors into the framework. Through iteratively optimizing parameters, we inferred the actual insertion events occurred and described each gene’s essentiality on probability measure. Evaluated by the definite mapping of essential gene profile in Escherichia coli, our model significantly improved the accuracy of original TM datasets, resulting in more accurate annotations of essential genes. Our method also showed encouraging results in improving subsaturation level TM datasets. To test our model’s broad applicability to other bacteria, we applied it to Pseudomonas aeruginosa PAO1 and Francisella tularensis novicida TM datasets. We validated our predictions by literature as well as allelic exchange experiments in PAO1. Our model was correct on six of the seven tested genes. Remarkably, among all three cases that our predictions contradicted the TM assignments, experimental validations supported our predictions. In summary, our method will be a promising tool in improving genomic annotations of essential genes and enabling large-scale explorations of gene essentiality. Our contribution is timely considering the rapidly increasing essential gene sets. A Webserver has been set up to provide convenient access to this tool. All results and source codes are available for download upon publication at http://research.cchmc.org/essentialgene/.

Bioplastics science from a policy vantage point

Society is fundamentally ambivalent to the use of plastics. On the one hand, plastics are uniquely flexible materials that have seen them occupy a huge range of functions, from simple packing materials to complex engineering components. On the other hand, their durability has raised concerns about their end-of-life disposal. When that disposal route is landfill, their invulnerability to microbial decomposition, combined with relatively low density and high bulk, means that plastics will occupy increasing amounts of landfill space in a world where available suitable landfill sites is shrinking. The search for biodegradable plastics and their introduction to the marketplace would appear to be a suitable amelioration strategy for such a problem. And yet the uptake of biodegradable plastics has been slow. The term biodegradable itself has entered public controversy, with accidental and intended misuse of the term; the intended misuse has led to accusations and instances of 'greenwashing'. For this and other reasons standards for biodegradability and compostability testing of plastics have been sought. An environmental dilemma with more far-reaching implications is climate change. The need for rapid and deep greenhouse gas (GHG) emissions cuts is one of the drivers for the resurgence of industrial biotechnology generally, and the search for bio-based plastics more specifically. Bio-based has come to mean plastics based on renewable resources, but this need not necessarily imply biodegradability. If the primary purpose is GHG emissions savings, then once again plastics durability can be a virtue, if the end-of-life solution can be energy recovery during incineration or recycling. The pattern of production is shifting from the true biodegradable plastics to the bio-based plastics, and that trend is likely to persist into the future. This paper looks at aspects of the science of biodegradable and bio-based plastics from the perspective of policy advisers and makers. It is often said that the bioplastics suffer from a lack of a favourable policy regime when compared to the wide-ranging set of policy instruments that are available on both the supply and demand side of biofuels production. Some possible policy measures are discussed.

Exploration of the core metabolism of symbiotic bacteria

Background

A large number of genome-scale metabolic networks is now available for many organisms, mostly bacteria. Previous works on minimal gene sets, when analysing host-dependent bacteria, found small common sets of metabolic genes. When such analyses are restricted to bacteria with similar lifestyles, larger portions of metabolism are expected to be shared and their composition is worth investigating. Here we report a comparative analysis of the small molecule metabolism of symbiotic bacteria, exploring common and variable portions as well as the contribution of different lifestyle groups to the reduction of a common set of metabolic capabilities.

Results

We found no reaction shared by all the bacteria analysed. Disregarding those with the smallest genomes, we still do not find a reaction core, however we did find a core of biochemical capabilities. While obligate intracellular symbionts have no core of reactions within their group, extracellular and cell-associated symbionts do have a small core composed of disconnected fragments. In agreement with previous findings in Escherichia coli, their cores are enriched in biosynthetic processes whereas the variable metabolisms have similar ratios of biosynthetic and degradation reactions. Conversely, the variable metabolism of obligate intracellular symbionts is enriched in anabolism.

Conclusion

Even when removing the symbionts with the most reduced genomes, there is no core of reactions common to the analysed symbiotic bacteria. The main reason is the very high specialisation of obligate intracellular symbionts, however, host-dependence alone is not an explanation for such absence. The composition of the metabolism of cell-associated and extracellular bacteria shows that while they have similar needs in terms of the building blocks of their cells, they have to adapt to very distinct environments. On the other hand, in obligate intracellular bacteria, catabolism has largely disappeared, whereas synthetic routes appear to have been selected for depending on the nature of the symbiosis. As more genomes are added, we expect, based on our simulations, that the core of cell-associated and extracellular bacteria continues to diminish, converging to approximately 60 reactions.

Extreme genome reduction in symbiotic bacteria

Since 2006, numerous cases of bacterial symbionts with extraordinarily small genomes have been reported. These organisms represent independent lineages from diverse bacterial groups. They have diminutive gene sets that rival some mitochondria and chloroplasts in terms of gene numbers and lack genes that are considered to be essential in other bacteria. These symbionts have numerous features in common, such as extraordinarily fast protein evolution and a high abundance of chaperones. Together, these features point to highly degenerate genomes that retain only the most essential functions, often including a considerable fraction of genes that serve the hosts. These discoveries have implications for the concept of minimal genomes, the origins of cellular organelles, and studies of symbiosis and host-associated microbiota.

Loss of genetic redundancy in reductive genome evolution

Biological systems evolved to be functionally robust in uncertain environments, but also highly adaptable. Such robustness is partly achieved by genetic redundancy, where the failure of a specific component through mutation or environmental challenge can be compensated by duplicate components capable of performing, to a limited extent, the same function. Highly variable environments require very robust systems. Conversely, predictable environments should not place a high selective value on robustness. Here we test this hypothesis by investigating the evolutionary dynamics of genetic redundancy in extremely reduced genomes, found mostly in intracellular parasites and endosymbionts. By combining data analysis with simulations of genome evolution we show that in the extensive gene loss suffered by reduced genomes there is a selective drive to keep the diversity of protein families while sacrificing paralogy. We show that this is not a by-product of the known drivers of genome reduction and that there is very limited convergence to a common core of families, indicating that the repertoire of protein families in reduced genomes is the result of historical contingency and niche-specific adaptations. We propose that our observations reflect a loss of genetic redundancy due to a decreased selection for robustness in a predictable environment.

Synthetic toxicology: where engineering meets biology and toxicology

This article examines the implications of synthetic biology (SB) for toxicological sciences. Starting with a working definition of SB, we describe its current subfields, namely, DNA synthesis, the engineering of DNA-based biological circuits, minimal genome research, attempts to construct protocells and synthetic cells, and efforts to diversify the biochemistry of life through xenobiology. Based on the most important techniques, tools, and expected applications in SB, we describe the ramifications of SB for toxicology under the label of synthetic toxicology. We differentiate between cases where SB offers opportunities for toxicology and where SB poses challenges for toxicology. Among the opportunities, we identified the assistance of SB to construct novel toxicity testing platforms, define new toxicity-pathway assays, explore the potential of SB to improve in vivo biotransformation of toxins, present novel biosensors developed by SB for environmental toxicology, discuss cell-free protein synthesis of toxins, reflect on the contribution to toxic use reduction, and the democratization of toxicology through do-it-yourself biology. Among the identified challenges for toxicology, we identify synthetic toxins and novel xenobiotics, biosecurity and dual-use considerations, the potential bridging of toxic substances and infectious agents, and do-it-yourself toxin production.

Essential molecular functions associated with the circular code evolution

A circular code is a set of trinucleotides allowing the reading frames in genes to be retrieved locally, i.e. anywhere in genes and in particular without start codons, and automatically with a window of few nucleotides. In 1996, a common circular code, called X, was identified in large populations of eukaryotic and prokaryotic genes. Hence, it is believed to be an ancestral structural property of genes. A new computational approach based on comparative genomics is developed to identify essential molecular functions associated with circular codes. It is based on a quantitative and sensitive statistical method (FPTF) to identify three permuted trinucleotide sets in the three frames of genes, a flower automaton algorithm to determine if a trinucleotide set is a circular code or not, and an integrated Gene Ontology and Taxonomy (iGOT) database. By carrying out automatic circular code analyses on a huge number of gene populations where each population is associated with a particular molecular function, it identifies 266 gene populations having circular codes close to X. Surprisingly, their molecular functions include 98% of those covered by the essential genes of the DEG database (Database of Essential Genes). Furthermore, three trinucleotides GTG, AAG and GCG, replacing three trinucleotides of the code X and called "evolutionary" trinucleotides, significantly occur in these 266 gene populations. Finally, a new method developed to analyse and quantify the stability of a set of trinucleotides demonstrates that these evolutionary trinucleotides are associated with a significant increase of the stability of the common circular code X. Indeed, its stability increases from the 1502th rank to the 16th rank after the replacement of the three evolutionary trinucleotides among 9920 possible trinucleotide replacement sets.

The bacterial essence of tiny symbiont genomes

Bacterial genomes vary in size over two orders of magnitude. The Mycoplasma genitalium genome has historically defined the extreme small end of this spectrum, and has therefore heavily informed theoretical and experimental work aimed at determining the minimal gene content necessary to support cellular life. Recent genomic data from insect symbionts have revealed bacterial genomes that are incredibly small-two to four times smaller than M. genitalium-and these tiny genomes have raised questions about the limits of genome reduction and have blurred the once-clear distinction between autonomous cellular life and highly integrated organelle. New data from various systems with symbiotic bacterial or archaeal partners have begun to shed light on how these bacteria may function with such small gene sets, but major mechanistic questions remain.

Novel Helicobacter pylori therapeutic targets: the unusual suspects

Understanding the current status of the discovery and development of anti-Helicobacter therapies requires an overview of the searches for therapeutic targets performed to date. A summary is given of the very substantial body of work conducted in the quest to find Helicobacter pylori genes that could be suitable candidates for therapeutic intervention. The products of most of these genes perform metabolic functions, and others have roles in growth, cell motility and colonization. The genes identified as potential targets have been organized into three categories according to their degree of characterization. A short description and evaluation is provided of the main candidates in each category. Investigations of potential therapeutic targets have generated a wealth of information about the physiology and genetics of H. pylori, and its interactions with the host, but have yielded little by way of new therapies.

Theoretical methods for identifying important functional genes in bacterial genomes

Some functional genes, such as essential genes, highly expressed genes and horizontally transferred genes, play important roles in the survival and pathogenicity of bacteria. This review attempts to summarize current computational methods in identifying the above functional genes from bacterial genomes, which is of significant importance in exploring the bacterial genomes.

Use of a riboswitch-controlled conditional hypomorphic mutation to uncover a role for the essential csrA gene in bacterial autoaggregation

Essential genes encode biological functions critical for cell survival. Correspondingly, their null mutants are often difficult to obtain, which impedes subsequent genetic and functional analysis. Here, we describe the development and utility of a theophylline-responsive riboswitch that enables target gene expression to be specifically "tuned" from low to high levels, which may be used to generate conditional hypomorphic mutants. Low levels of gene activity in the absence of the ligand (theophylline) permit cell survival, enabling gene activities to be investigated. Normal gene expression levels and wild-type phenotypes can be restored by the addition of the ligand. We demonstrate the utility of this approach with csrA, an essential gene in Escherichia coli that encodes the global regulatory protein CsrA. We placed the theophylline-responsive riboswitch immediately upstream of the csrA ribosome binding site, with the resulting mutant named switch-csrA. Hypomorphism of switch-csrA and its specific responsiveness to theophylline were verified by phenotypic examination and translation analysis. The utility of switch-csrA revealed a previously unidentified function for CsrA, namely its role as a repressor of cellular autoaggregation. Specifically, switch-csrA in the non-ligand-bound form produced low levels of CsrA, and its cells autoaggregated. Theophylline binding induced conformational changes in the riboswitch and permitted efficient csrA translation; consequently, autoaggregation did not occur. Our results indicate that CsrA modulates autoaggregation via the polysaccharide adhesin poly-beta-1,6-N-acetyl-D-glucosamine. In summary, the use of ligand-responsive riboswitches to construct conditional hypomorphic mutants represents a novel approach for investigating the activities of essential genes, which effectively complements traditional genetic approaches.

Metabolic engineering of a reduced-genome strain of Escherichia coli for L-threonine production

Background

Deletion of large blocks of nonessential genes that are not needed for metabolic pathways of interest can reduce the production of unwanted by-products, increase genome stability, and streamline metabolism without physiological compromise. Researchers have recently constructed a reduced-genome Escherichia coli strain MDS42 that lacks 14.3% of its chromosome.

Results

Here we describe the reengineering of the MDS42 genome to increase the production of the essential amino acid L-threonine. To this end, we over-expressed a feedback-resistant threonine operon (thrA*BC), deleted the genes that encode threonine dehydrogenase (tdh) and threonine transporters (tdcC and sstT), and introduced a mutant threonine exporter (rhtA23) in MDS42. The resulting strain, MDS-205, shows an ~83% increase in L-threonine production when cells are grown by flask fermentation, compared to a wild-type E. coli strain MG1655 engineered with the same threonine-specific modifications described above. And transcriptional analysis revealed the effect of the deletion of non-essential genes on the central metabolism and threonine pathways in MDS-205.

Conclusion

This result demonstrates that the elimination of genes unnecessary for cell growth can increase the productivity of an industrial strain, most likely by reducing the metabolic burden and improving the metabolic efficiency of cells.

Gene essentiality analysis based on DEG, a database of essential genes

Essential genes are the genes that are indispensable for the survival of an organism. The genome-scale identification of essential genes has been performed in various organisms, and we consequently constructed DEG, a Database that contains currently available essential genes. Here we analyzed functional distributions of essential genes in DEG, and found that some essential-gene functions are even conserved between the prokaryote (bacteria) and the eukaryote (yeast), e.g., genes involved in information storage and processing are overrepresented, whereas those involved in metabolism are underrepresented in essential genes compared with non-essential ones. In bacteria, species specificity in functional distribution of essential genes is mainly due to those involved in cellular processes. Furthermore, within the category of information storage and processing, function of translation, ribosomal structure, and biogenesis are predominant in essential genes. Finally, some potential pitfalls for analyzing gene essentiality based on DEG are discussed.

In-frame deletion of Escherichia coli essential genes in complex regulon

A conditional knockout-rescue system was developed to construct an in-frame deletion strain ofEscherichia coli essential genes. The target was flanked with marker genes and FRT (FLP recognition target) sites, and a plasmid containing arabinose-induced FLP recombinase was transformed. After arabinose induction, cells could survive only when target protein activity was provided in trans. We selected three essential genes as targets, yaeT, fabZ, and dnaE, which are components of the complex eight-gene regulon yaeT-hlpA-lpxD-fabZ-lpxA-1pxB-rnhB-dnaE. Deletion of these three genes exhibit no polar effects on their adjacent genes in terms of cell viability, meaning that this system not only allows for the simplified study of protein interactions and homolog screening in other organisms, but also facilitates the null mutant construction of essential genes.