Proteome partitioning constraints in long-term laboratory evolution

Adaptive laboratory evolution experiments provide a controlled context in which the dynamics of selection and adaptation can be followed in real-time at the single-nucleotide level. And yet this precision introduces hundreds of degrees-of-freedom as genetic changes accrue in parallel lineages over generations. On short timescales, physiological constraints have been leveraged to provide a coarse-grained view of bacterial gene expression characterized by a small set of phenomenological parameters. Here, we ask whether this same framework, operating at a level between genotype and fitness, informs physiological changes that occur on evolutionary timescales. Using a strain adapted to growth in glucose minimal medium, we find that the proteome is substantially remodeled over 40 000 generations. The most striking change is an apparent increase in enzyme efficiency, particularly in the enzymes of lower-glycolysis. We propose that deletion of metabolic flux-sensing regulation early in the adaptation results in increased enzyme saturation and can account for the observed proteome remodeling.

Essential genes identification model based on sequence feature map and graph convolutional neural network

BACKGROUND

Essential genes encode functions that play a vital role in the life activities of organisms, encompassing growth, development, immune system functioning, and cell structure maintenance. Conventional experimental techniques for identifying essential genes are resource-intensive and time-consuming, and the accuracy of current machine learning models needs further enhancement. Therefore, it is crucial to develop a robust computational model to accurately predict essential genes.

RESULTS

In this study, we introduce GCNN-SFM, a computational model for identifying essential genes in organisms, based on graph convolutional neural networks (GCNN). GCNN-SFM integrates a graph convolutional layer, a convolutional layer, and a fully connected layer to model and extract features from gene sequences of essential genes. Initially, the gene sequence is transformed into a feature map using coding techniques. Subsequently, a multi-layer GCN is employed to perform graph convolution operations, effectively capturing both local and global features of the gene sequence. Further feature extraction is performed, followed by integrating convolution and fully-connected layers to generate prediction results for essential genes. The gradient descent algorithm is utilized to iteratively update the cross-entropy loss function, thereby enhancing the accuracy of the prediction results. Meanwhile, model parameters are tuned to determine the optimal parameter combination that yields the best prediction performance during training.

CONCLUSIONS

Experimental evaluation demonstrates that GCNN-SFM surpasses various advanced essential gene prediction models and achieves an average accuracy of 94.53%. This study presents a novel and effective approach for identifying essential genes, which has significant implications for biology and genomics research.

Comparison of wild-type KT2440 and genome-reduced EM42 Pseudomonas putida strains for muconate production from aromatic compounds and glucose

Pseudomonas putida KT2440 is a robust, aromatic catabolic bacterium that has been widely engineered to convert bio-based and waste-based feedstocks to target products. Towards industrial domestication of P. putida KT2440, rational genome reduction has been previously conducted, resulting in P. putida strain EM42, which exhibited characteristics that could be advantageous for production strains. Here, we compared P. putida KT2440- and EM42-derived strains for cis,cis-muconic acid production from an aromatic compound, p-coumarate, and in separate strains, from glucose. To our surprise, the EM42-derived strains did not outperform the KT2440-derived strains in muconate production from either substrate. In bioreactor cultivations, KT2440- and EM42-derived strains produced muconate from p-coumarate at titers of 45 g/L and 37 g/L, respectively, and from glucose at 20 g/L and 13 g/L, respectively. To provide additional insights about the differences in the parent strains, we analyzed growth profiles of KT2440 and EM42 on aromatic compounds as the sole carbon and energy sources. In general, the EM42 strain exhibited reduced growth rates but shorter growth lags than KT2440. We also observed that EM42-derived strains resulted in higher growth rates on glucose compared to KT2440-derived strains, but only at the lowest glucose concentrations tested. Transcriptomics revealed that genome reduction in EM42 had global effects on transcript levels and showed that the EM42-derived strains that produce muconate from glucose exhibit reduced modulation of gene expression in response to changes in glucose concentrations. Overall, our results highlight that additional studies are warranted to understand the effects of genome reduction on microbial metabolism and physiology, especially when intended for use in production strains.

Available strategies for improving the biosynthesis of surfactin: a review

Surfactin is an excellent biosurfactant with a wide range of application prospects in many industrial fields. However, its low productivity and high cost have largely limited its commercial applications. In this review, the pathways for surfactin synthesis in Bacillus strains are summarized and discussed. Further, the latest strategies for improving surfactin production, including: medium optimization, genome engineering methods (rational genetic engineering, genome reduction, and genome shuffling), heterologous synthesis, and the use of synthetic biology combined with metabolic engineering approaches to construct high-quality artificial cells for surfactin production using xylose, are described. Finally, the prospects for improving surfactin synthesis are discussed in detail.

A Programmable CRISPR/Cas9 Toolkit Improves Lycopene Production in Bacillus subtilis

Bacillus subtilis has been widely used and generally recognized as a safe host for the production of recombinant proteins, high-value chemicals, and pharmaceuticals. Thus, its metabolic engineering attracts significant attention. Nevertheless, the limited availability of selective markers makes this process difficult and time-consuming, especially in the case of multistep biosynthetic pathways. Here, we employ CRISPR/Cas9 technology to build an easy cloning toolkit that addresses commonly encountered obstacles in the metabolic engineering of B. subtilis, including the chromosomal integration locus, promoter, terminator, and guide RNA (gRNA) target. Six promoters were characterized, and the promoter strengths ranged from 0.9- to 23-fold that of the commonly used strong promoter P43. We characterized seven terminators in B. subtilis, and the termination efficiencies (TEs) of the seven terminators are all more than 90%. Six gRNA targets were designed upstream of the promoter and downstream of the terminator. Using a green fluorescent protein (GFP) reporter, we confirmed integration efficiency with the single-locus integration site is up to 100%. We demonstrated the applicability of this toolkit by optimizing the expression of a challenging but industrially important product, lycopene. By heterologous expression of the essential genes for lycopene synthesis on the B. subtilis genome, a total of 13 key genes involved in the lycopene biosynthetic pathway were manipulated. Moreover, our findings showed that the gene cluster ispG-idi-dxs-ispD could positively affect the production of lycopene, while the cluster dxr-ispE-ispF-ispH had a negative effect on lycopene production. Hence, our multilocus integration strategy can facilitate the pathway assembly for production of complex chemicals and pharmaceuticals in B. subtilis. IMPORTANCE We present a toolkit that allows for rapid cloning procedures and one-step subcloning to move from plasmid-based expression to stable chromosome integration and expression in a production strain in less than a week. The utility of the customized tool was demonstrated by integrating the MEP (2C-methyl-d-erythritol-4-phosphate) pathway, part of the pentose phosphate pathway (PPP), and the hetero-lycopene biosynthesis genes by stable expression in the genome. The tool could be useful to engineer B. subtilis strains through diverse recombination events and ultimately improve its potential and scope of industrial application as biological chassis.

Pullulanase: unleashing the power of enzyme with a promising future in the food industry

Pullulanases are the most important industrial group of enzymes in family 13 glycosyl hydrolases. They hydrolyze either α-1,6 and α-1,4 or both glycosidic bonds in pullulan as well as other carbohydrates to produce glucose, maltose, and maltotriose syrups, which have important uses in food and other related sectors. However, very less reports are available on pullulanase production from native strains because of low yield issues. In line with the increasing demands for pullulanase, it has become important to search for novel pullulanase-producing microorganisms with high yields. Moreover, high production costs and low yield are major limitations in the industrial production of pullulanase enzymes. The production cost of pullulanase by using the solid-state fermentation (SSF) process can be minimized by selecting agro-industrial waste. This review summarizes the types, sources, production strategies, and potential applications of pullulanase in different food and other related industries. Researchers should focus on fungal strains producing pullulanase for better yield and low production costs by using agro-waste. It will prove a better enzyme in different food processing industries and will surely reduce the cost of products.

Trimming the genomic fat: minimising and re-functionalising genomes using synthetic biology

Naturally evolved organisms typically have large genomes that enable their survival and growth under various conditions. However, the complexity of genomes often precludes our complete understanding of them, and limits the success of biotechnological designs. In contrast, minimal genomes have reduced complexity and therefore improved engineerability, increased biosynthetic capacity through the removal of unnecessary genetic elements, and less recalcitrance to complete characterisation. Here, we review the past and current genome minimisation and re-functionalisation efforts, with an emphasis on the latest advances facilitated by synthetic genomics, and provide a critical appraisal of their potential for industrial applications.

Recent advances in genetic tools for engineering probiotic lactic acid bacteria

Synthetic biology has grown exponentially in the last few years, with a variety of biological applications. One of the emerging applications of synthetic biology is to exploit the link between microorganisms, biologics, and human health. To exploit this link, it is critical to select effective synthetic biology tools for use in appropriate microorganisms that would address unmet needs in human health through the development of new game-changing applications and by complementing existing technological capabilities. Lactic acid bacteria (LAB) are considered appropriate chassis organisms that can be genetically engineered for therapeutic and industrial applications. Here, we have reviewed comprehensively various synthetic biology techniques for engineering probiotic LAB strains, such as clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 mediated genome editing, homologous recombination, and recombineering. In addition, we also discussed heterologous protein expression systems used in engineering probiotic LAB. By combining computational biology with genetic engineering, there is a lot of potential to develop next-generation synthetic LAB with capabilities to address bottlenecks in industrial scale-up and complex biologics production. Recently, we started working on Lactochassis project where we aim to develop next generation synthetic LAB for biomedical application.

Identification of discriminant features from stationary pattern of nucleotide bases and their application to essential gene classification

Introduction: Essential genes are essential for the survival of various species. These genes are a family linked to critical cellular activities for species survival. These genes are coded for proteins that regulate central metabolism, gene translation, deoxyribonucleic acid replication, and fundamental cellular structure and facilitate intracellular and extracellular transport. Essential genes preserve crucial genomics information that may hold the key to a detailed knowledge of life and evolution. Essential gene studies have long been regarded as a vital topic in computational biology due to their relevance. An essential gene is composed of adenine, guanine, cytosine, and thymine and its various combinations. Methods: This paper presents a novel method of extracting information on the stationary patterns of nucleotides such as adenine, guanine, cytosine, and thymine in each gene. For this purpose, some co-occurrence matrices are derived that provide the statistical distribution of stationary patterns of nucleotides in the genes, which is helpful in establishing the relationship between the nucleotides. For extracting discriminant features from each co-occurrence matrix, energy, entropy, homogeneity, contrast, and dissimilarity features are computed, which are extracted from all co-occurrence matrices and then concatenated to form a feature vector representing each essential gene. Finally, supervised machine learning algorithms are applied for essential gene classification based on the extracted fixed-dimensional feature vectors. Results: For comparison, some existing state-of-the-art feature representation techniques such as Shannon entropy (SE), Hurst exponent (HE), fractal dimension (FD), and their combinations have been utilized. Discussion: An extensive experiment has been performed for classifying the essential genes of five species that show the robustness and effectiveness of the proposed methodology.

Predicting stress response and improved protein overproduction in Bacillus subtilis

Bacillus subtilis is a well-characterized microorganism and a model for the study of Gram-positive bacteria. The bacterium can produce proteins at high densities and yields, which has made it valuable for industrial bioproduction. Like other cell factories, metabolic modeling of B. subtilis has discovered ways to optimize its metabolism toward various applications. The first genome-scale metabolic model (M-model) of B. subtilis was published more than a decade ago and has been applied extensively to understand metabolism, to predict growth phenotypes, and served as a template to reconstruct models for other Gram-positive bacteria. However, M-models are ill-suited to simulate the production and secretion of proteins as well as their proteomic response to stress. Thus, a new generation of metabolic models, known as metabolism and gene expression models (ME-models), has been initiated. Here, we describe the reconstruction and validation of a ME model of B. subtilis, iJT964-ME. This model achieved higher performance scores on the prediction of gene essentiality as compared to the M-model. We successfully validated the model by integrating physiological and omics data associated with gene expression responses to ethanol and salt stress. The model further identified the mechanism by which tryptophan synthesis is upregulated under ethanol stress. Further, we employed iJT964-ME to predict amylase production rates under two different growth conditions. We analyzed these flux distributions and identified key metabolic pathways that permitted the increase in amylase production. Models like iJT964-ME enable the study of proteomic response to stress and the illustrate the potential for optimizing protein production in bacteria.

Bacterial genome reductions: Tools, applications, and challenges

Bacterial cells are widely used to produce value-added products due to their versatility, ease of manipulation, and the abundance of genome engineering tools. However, the efficiency of producing these desired biomolecules is often hindered by the cells’ own metabolism, genetic instability, and the toxicity of the product. To overcome these challenges, genome reductions have been performed, making strains with the potential of serving as chassis for downstream applications. Here we review the current technologies that enable the design and construction of such reduced-genome bacteria as well as the challenges that limit their assembly and applicability. While genomic reductions have shown improvement of many cellular characteristics, a major challenge still exists in constructing these cells efficiently and rapidly. Computational tools have been created in attempts at minimizing the time needed to design these organisms, but gaps still exist in modelling these reductions in silico. Genomic reductions are a promising avenue for improving the production of value-added products, constructing chassis cells, and for uncovering cellular function but are currently limited by their time-consuming construction methods. With improvements to and the creation of novel genome editing tools and in silico models, these approaches could be combined to expedite this process and create more streamlined and efficient cell factories.

Enhanced production of l-sorbose by systematic engineering of dehydrogenases in Gluconobacter oxydans

l-Sorbose is an essential intermediate for the industrial production of vitamin C (l-ascorbic acid). However, the formation of fructose and some unknown by-products significantly reduces the conversion ratio of D-sorbitol to l-sorbose. This study aimed to identify the key D-sorbitol dehydrogenases in Gluconobacter oxydans WSH-003 by gene knockout. Then, a total of 38 dehydrogenases were knocked out in G. oxydans WSH-003, and 23 dehydrogenase-deficient strains could increase l-sorbose production. G. oxydans-30, wherein a pyrroloquinoline quinone-dependent glucose dehydrogenase was deleted, showed a significant reduction of a by-product with the extension of fermentation time. In addition, the highest conversion ratio of 99.60% was achieved in G. oxydans MD-16, in which 16 different types of dehydrogenases were inactivated consecutively. Finally, the gene vhb encoding hemoglobin was introduced into the strain. The titer of l-sorbose was 298.61 g/L in a 5-L bioreactor. The results showed that the systematic engineering of dehydrogenase could significantly enhance the production of l-sorbose.

Constitutive expression of the global regulator AbrB restores the growth defect of a genome-reduced Bacillus subtilis strain and improves its metabolite production

Partial bacterial genome reduction by genome engineering can improve the productivity of various metabolites, possibly via deletion of non-essential genome regions involved in undesirable metabolic pathways competing with pathways for the desired end products. However, such reduction may cause growth defects. Genome reduction of Bacillus subtilis MGB874 increases the productivity of cellulases and proteases but reduces their growth rate. Here, we show that this growth defect could be restored by silencing redundant or less important genes affecting exponential growth by manipulating the global transcription factor AbrB. Comparative transcriptome analysis revealed that AbrB-regulated genes were upregulated and those involved in central metabolic pathway and synthetic pathways of amino acids and purine/pyrimidine nucleotides were downregulated in MGB874 compared with the wild-type strain, which we speculated were the cause of the growth defects. By constitutively expressing high levels of AbrB, AbrB regulon genes were repressed, while glycolytic flux increased, thereby restoring the growth rate to wild-type levels. This manipulation also enhanced the productivity of metabolites including γ-polyglutamic acid. This study provides the first evidence that undesired features induced by genome reduction can be relieved, at least partly, by manipulating a global transcription regulation system. A similar strategy could be applied to other genome engineering-based challenges aiming toward efficient material production in bacteria.

Efficient Large-Scale and Scarless Genome Engineering Enables the Construction and Screening of Bacillus subtilis Biofuel Overproducers

Bacillus subtilis is a versatile microbial cell factory that can produce valuable proteins and value-added chemicals. Long fragment editing techniques are of great importance for accelerating bacterial genome engineering to obtain desirable and genetically stable host strains. Herein, we develop an efficient CRISPR-Cas9 method for large-scale and scarless genome engineering in the Bacillus subtilis genome, which can delete up to 134.3 kb DNA fragments, 3.5 times as long as the previous report, with a positivity rate of 100%. The effects of using a heterologous NHEJ system, linear donor DNA, and various donor DNA length on the engineering efficiencies were also investigated. The CRISPR-Cas9 method was then utilized for Bacillus subtilis genome simplification and construction of a series of individual and cumulative deletion mutants, which are further screened for overproducer of isobutanol, a new generation biofuel. These results suggest that the method is a powerful genome engineering tool for constructing and screening engineered host strains with enhanced capabilities, highlighting the potential for synthetic biology and metabolic engineering.

Enhanced production of polyhydroxyalkanoates in Pseudomonas putida KT2440 by a combination of genome streamlining and promoter engineering

Polyhydroxyalkanoates (PHAs), a class of bioplastics produced by a variety of microorganisms, have become the ideal alternatives for oil-derived plastics due to their superior physicochemical and material characteristics. Pseudomonas putida KT2440 can produce medium-chain-length PHA (mcl-PHA) from various substrates. In this study, a novel strategy of the large-scale deletion of genomic islands (GIs) coupling with promoter engineering was developed in P. putida KT2440 for constructing the minimal genome cell factories (MGF) capable of efficiently producing mcl-PHA. Firstly, P. putida KTU-U13, a 13 GIs- and upp-deleted mutant derived from the parental strain P. putida KT2440, was used as a starting strain for further deletion of GIs to generate a series of genome-reduced strains. Subsequently, the two minimal genome strains KTU-U24 and KTU-U27, which had a 7.19% and 8.35% reduction relative to the genome size of KT2440 and were advantageous over the strain KTU (KT2440∆upp) and KTU-U13 in several physiological traits such as the maximum specific growth rate, plasmid transformation efficiency, heterologous protein expression capacity and PHA production capacity, were selected as the chassis cells for PHA metabolic engineering. To prevent the formation of the by-product gluconic acid, the glucose dehydrogenase gene was deleted in KTU-U24 and KTU-U27, resulting in KTU-U24∆gcd and KTU-U27∆gcd. To enhance the transcriptional level of PHA synthase genes (phaC) and the supply of the precursor acetyl-CoA, a strong endogenous promoter P46 was inserted into upstream of the phaC operon and pyruvate dehydrogenase gene in the genome of KTU-U24∆gcd and KTU-U27∆gcd, to generate KTU-U24∆gcd-P46CA and KTU-U27∆gcd-P46CA, with the PHA yield of 50.5 wt% and 53.8 wt% (weight percent of PHA in cell dry weight). Finally, KTU-U27∆gcd-P46CA, the most minimal KT2440 chassis currently available, was able to accumulate the PHA to 55.82 wt% in a 5-l fermentor, which is the highest PHA yield obtained with P. putida KT2440 so far. This study suggests that genome streamlining in combination with promoter engineering may be a feasible strategy for the development of the MGF for the efficient production of high value products. Moreover, further streamlining of the P. putida KT2440 genome has great potential to create the optimal chassis for synthetic biology applications.

The Bacillus subtilis Minimal Genome Compendium

To better understand cellular life, it is essential to decipher the contribution of individual components and their interactions. Minimal genomes are an important tool to investigate these interactions. Here, we provide a database of 105 fully annotated genomes of a series of strains with sequential deletion steps of the industrially relevant model bacterium Bacillus subtilis starting with the laboratory wild type strain B. subtilis 168 and ending with B. subtilis PG38, which lacks approximately 40% of the original genome. The annotation is supported by sequencing of key intermediate strains as well as integration of literature knowledge for the annotation of the deletion scars and their potential effects. The strain compendium presented here represents a comprehensive genome library of the entire MiniBacillus project. This resource will facilitate the more effective application of the different strains in basic science as well as in biotechnology.

A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes

Background: Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes.

Methods: We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level.

Results: We show that the core regions determined by our method contain all or almost all essential genes. This demonstrates the accuracy of our method as essential genes should be core genes. We show that we outperform previous methods by this measure. We also explain why there are exceptions to this rule for our method.

Conclusions: We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species.

An overview and future prospects of recombinant protein production in Bacillus subtilis

Bacillus subtilis is a well-characterized Gram-positive bacterium and a valuable host for recombinant protein production because of its efficient secretion ability, high yield, and non-toxicity. Here, we comprehensively review the recent studies on recombinant protein production in B. subtilis to update and supplement other previous reviews. We have focused on several aspects, including optimization of B. subtilis strains, enhancement and regulation of expression, improvement of secretion level, surface display of proteins, and fermentation optimization. Among them, optimization of B. subtilis strains mainly involves undirected chemical/physical mutagenesis and selection and genetic manipulation; enhancement and regulation of expression comprises autonomous plasmid and integrated expression, promoter regulation and engineering, and fine-tuning gene expression based on proteases and molecular chaperones; improvement of secretion level predominantly involves secretion pathway and signal peptide screening and optimization; surface display of proteins includes surface display of proteins on spores or vegetative cells; and fermentation optimization incorporates medium optimization, process condition optimization, and feeding strategy optimization. Furthermore, we propose some novel methods and future challenges for recombinant protein production in B. subtilis.Key points• A comprehensive review on recombinant protein production in Bacillus subtilis.• Novel techniques facilitate recombinant protein expression and secretion.• Surface display of proteins has significant potential for different applications.

Novel perspective on a conventional technique: Impact of ultra-low temperature on bacterial viability and protein extraction

Ultra-low temperature (ULT) storage of microbial biomass is routinely practiced in biological laboratories. However, there is very little insight regarding the effects of biomass storage at ULT and the structure of the cell envelope, on cell viability. Eventually, these aspects influence bacterial cell lysis which is one of the critical steps for biomolecular extraction, especially protein extraction. Therefore, we studied the effects of ULT-storage (-80°C) on three different bacterial platforms: Escherichia coli, Bacillus subtilis and the cyanobacterium Synechocystis sp. PCC 6803. By using a propidium iodide assay and a modified MTT assay we determined the impact of ULT storage on cellular viability. Subsequently, the protein extraction efficiency was determined by analyzing the amount of protein released following the storage. The results successfully established that longer the ULT-storage time lower is the cell viability and larger is the protein extraction efficiency. Interestingly, E. coli and B. subtilis exhibited significant reduction in cell viability over Synechocystis 6803. This indicates that the cell membrane structure and composition may play a major role on cell viability in ULT storage. Interestingly, E. coli exhibited concomitant increase in cell lysis efficiency resulting in a 4.5-fold increase (from 109 μg/ml of protein on day 0 to 464 μg/ml of protein on day 2) in the extracted protein titer following ULT storage. Furthermore, our investigations confirmed that the protein function, tested through the extraction of fluorescent proteins from cells stored at ULT, remained unaltered. These results established the plausibility of using ULT storage to improve protein extraction efficiency. Towards this, the impact of shorter ULT storage time was investigated to make the strategy more time efficient to be adopted into protocols. Interestingly, E. coli transformants expressing mCherry yielded 2.7-fold increase (93 μg/mL to 254 μg/mL) after 10 mins, while 4-fold increase (380 μg/mL) after 120 mins of ULT storage in the extracted soluble protein. We thereby substantiate that: (1) the storage time of bacterial cells in -80°C affect cell viability and can alter protein extraction efficiency; and (2) exercising a simple ULT-storage prior to bacterial cell lysis can improve the desired protein yield without impacting its function.

Synthetic biology-inspired strategies and tools for engineering of microbial natural product biosynthetic pathways

Microbial-derived natural products (NPs) and their derivative products are of great importance and used widely in many fields, especially in pharmaceutical industries. However, there is an immediate need to establish innovative approaches, strategies, and techniques to discover new NPs with novel or enhanced biological properties, due to the less productivity and higher cost on traditional drug discovery pipelines from natural bioresources. Revealing of untapped microbial cryptic biosynthetic gene clusters (BGCs) using DNA sequencing technology and bioinformatics tools makes genome mining possible for NP discovery from microorganisms. Meanwhile, new approaches and strategies in the area of synthetic biology offer great potentials for generation of new NPs by engineering or creating synthetic systems with improved and desired functions. Development of approaches, strategies and tools in synthetic biology can facilitate not only exploration and enhancement in supply, and also in the structural diversification of NPs. Here, we discussed recent advances in synthetic biology-inspired strategies, including bioinformatics and genetic engineering tools and approaches for identification, cloning, editing/refactoring of candidate biosynthetic pathways, construction of heterologous expression hosts, fitness optimization between target pathways and hosts and detection of NP production.

A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes

Background: Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes. Methods: We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level. Results: We show that the core regions determined by our method contain all or almost all essential genes. This demonstrates the accuracy of our method as essential genes should be core genes. We show that we outperform previous methods by this measure. We also explain why there are exceptions to this rule for our method. Conclusions: We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species.

A Bacillus subtilis ΔpdxT mutant suppresses vitamin B6 limitation by acquiring mutations enhancing pdxS gene dosage and ammonium assimilation

Pyridoxal-5'-phosphate (PLP), the biologically active form of vitamin B6, serves as a cofactor for many enzymes. The Gram-positive model bacterium Bacillus subtilis synthesizes PLP via the PdxST enzyme complex, consisting of the PdxT glutaminase and the PdxS PLP synthase subunits, respectively. PdxT converts glutamine to glutamate and ammonia of which the latter is channelled to PdxS. At high extracellular ammonium concentrations, the PdxS PLP synthase subunit does not depend on PdxT. Here, we assessed the potential of a B. subtilis ΔpdxT mutant to adapt to PLP limitation at the genome level. The majority of ΔpdxT suppressors had amplified a genomic region containing the pdxS gene. We also identified mutants having acquired as yet undescribed mutations in ammonium assimilation genes, indicating that the overproduction of PdxS and the NrgA ammonium transporter partially relieve vitamin B6 limitation in a ΔpdxT mutant when extracellular ammonium is scarce. Furthermore, we found that PdxS positively affects complex colony formation in B. subtilis. The catalytic mechanism of the PdxS PLP synthase subunit could be the reason for the limited evolution of the enzyme and why we could not identify a PdxS variant producing PLP independently of PdxT at low ammonium concentrations.

Protein-protein interaction network and potential drug target candidates of Streptococcus suis

AIMS

This study aimed to explore potential drug targets of Streptococcus suis at the system level.

METHODS AND RESULTS

A homologous protein mapping method was used in the construction of a protein-protein interaction (PPI) network of S. suis, which presented 1147 non-redundant interaction pairs among 286 proteins. The parameters of PPI networks were calculated and showed scale-free network properties. In all, 41 possibly essential proteins identified from 47 highly connected proteins were selected as potential drug target candidates. Of these proteins, 30 were already regarded as drug targets in other bacterial species. Six transporters with high connections to other functional proteins were identified as probably not essential but important functional proteins. Afterward, the subnetwork centred with cell division protein FtsZ was used in confirming the PPI network through bacterial two-hybrid analysis.

CONCLUSIONS

The predicted PPI network covers 13·04% of the proteome in S. suis. The selected 41 potential drug target candidates are conserved between S. suis and several model bacteria.

SIGNIFICANCE AND IMPACT OF THE STUDY

The predictions included proteins known to be drug targets, and a verifying experiment confirmed the reliability of predicted interactions. This work is the first to present systematic computational PPI data for S. suis and provides potential drug targets, which are valuable in exploring novel anti-streptococcus drugs.

Engineering of a genome-reduced strain Bacillus amyloliquefaciens for enhancing surfactin production

Background

Genome reduction and metabolic engineering have emerged as intensive research hotspots for constructing the promising functional chassis and various microbial cell factories. Surfactin, a lipopeptide-type biosurfactant with broad spectrum antibiotic activity, has wide application prospects in anticancer therapy, biocontrol and bioremediation. Bacillus amyloliquefaciens LL3, previously isolated by our lab, contains an intact srfA operon in the genome for surfactin biosynthesis.

Results

In this study, a genome-reduced strain GR167 lacking ~ 4.18% of the B. amyloliquefaciens LL3 genome was constructed by deleting some unnecessary genomic regions. Compared with the strain NK-1 (LL3 derivative, ΔuppΔpMC1), GR167 exhibited faster growth rate, higher transformation efficiency, increased intracellular reducing power level and higher heterologous protein expression capacity. Furthermore, the chassis strain GR167 was engineered for enhanced surfactin production. Firstly, the iturin and fengycin biosynthetic gene clusters were deleted from GR167 to generate GR167ID. Subsequently, two promoters PR_suc and PR_tpxi from LL3 were obtained by RNA-seq and promoter strength characterization, and then they were individually substituted for the native srfA promoter in GR167ID to generate GR167IDS and GR167IDT. The best mutant GR167IDS showed a 678-fold improvement in the transcriptional level of the srfA operon relative to GR167ID, and it produced 311.35 mg/L surfactin, with a 10.4-fold increase relative to GR167.

Conclusions

The genome-reduced strain GR167 was advantageous over the parental strain in several industrially relevant physiological traits assessed and it was highlighted as a chassis strain for further genetic modification. In future studies, further reduction of the LL3 genome can be expected to create high-performance chassis for synthetic biology applications.

A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification

Essential genes contain key information of genomes that could be the key to a comprehensive understanding of life and evolution. Because of their importance, studies of essential genes have been considered a crucial problem in computational biology. Computational methods for identifying essential genes have become increasingly popular to reduce the cost and time-consumption of traditional experiments. A few models have addressed this problem, but performance is still not satisfactory because of high dimensional features and the use of traditional machine learning algorithms. Thus, there is a need to create a novel model to improve the predictive performance of this problem from DNA sequence features. This study took advantage of a natural language processing (NLP) model in learning biological sequences by treating them as natural language words. To learn the NLP features, a supervised learning model was consequentially employed by an ensemble deep neural network. Our proposed method could identify essential genes with sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC), and area under the receiver operating characteristic curve (AUC) values of 60.2%, 84.6%, 76.3%, 0.449, and 0.814, respectively. The overall performance outperformed the single models without ensemble, as well as the state-of-the-art predictors on the same benchmark dataset. This indicated the effectiveness of the proposed method in determining essential genes, in particular, and other sequencing problems, in general.

Screening of a genome-reduced Corynebacterium glutamicum strain library for improved heterologous cutinase secretion

The construction of microbial platform organisms by means of genome reduction is an ongoing topic in biotechnology. In this study, we investigated whether the deletion of single or multiple gene clusters has a positive effect on the secretion of cutinase from Fusarium solani pisi in the industrial workhorse Corynebacterium glutamicum. A total of 22 genome-reduced strain variants were compared applying two Sec signal peptides from Bacillus subtilis. High-throughput phenotyping using robotics-integrated microbioreactor technology with automated harvesting revealed distinct cutinase secretion performance for a specific combination of signal peptide and genomic deletions. The biomass-specific cutinase yield for strain GRS41_51_NprE was increased by ~ 200%, although the growth rate was reduced by ~ 60%. Importantly, the causative deletions of genomic clusters cg2801-cg2828 and rrnC-cg3298 could not have been inferred a priori. Strikingly, bioreactor fed-batch cultivations at controlled growth rates resulted in a complete reversal of the screening results, with the cutinase yield for strain GRS41_51_NprE dropping by ~ 25% compared to the reference strain. Thus, the choice of bioprocess conditions may turn a 'high-performance' strain from batch screening into a 'low-performance' strain in fed-batch cultivation. In conclusion, future studies are needed in order to understand metabolic adaptations of C. glutamicum to both genomic deletions and different bioprocess conditions.

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.

Applicability of Chromatographic Co-Elution for Antibiotic Target Identification

Identification of the molecular target is a crucial step in evaluating novel antibiotics. To support target identification, a label-free method based on chromatographic co-elution has previously been developed. Target identification by chromatographic coelution (TICC) exploits the alteration of the elution profile of target-bound drug versus free drug in ion exchange (IEX) chromatography to identify potential target proteins from elution fractions. The applicability of TICC for antibiotic research is investigated by evaluating which proteins, that is, putative targets, can be monitored in Bacillus subtilis. Coelution of components of known protein complexes provides a read-out for how well the native state of proteins is conserved during chromatography. Rifampicin, which targets RNA polymerase, is used in a proof-of-concept study.

The Cu(II) Reductase RclA Protects Escherichia coli against the Combination of Hypochlorous Acid and Intracellular Copper

Enterobacteria, including Escherichia coli, bloom to high levels in the gut during inflammation and strongly contribute to the pathology of inflammatory bowel diseases. To survive in the inflamed gut, E. coli must tolerate high levels of antimicrobial compounds produced by the immune system, including toxic metals like copper and reactive chlorine oxidants such as hypochlorous acid (HOCl). Here, we show that extracellular copper is a potent detoxifier of HOCl and that the widely conserved bacterial HOCl resistance enzyme RclA, which catalyzes the reduction of copper(II) to copper(I), specifically protects E. coli against damage caused by the combination of HOCl and intracellular copper. E. coli lacking RclA was highly sensitive to HOCl when grown in the presence of copper and was defective in colonizing an animal host. Our results indicate that there is unexpected complexity in the interactions between antimicrobial toxins produced by innate immune cells and that bacterial copper status is a key determinant of HOCl resistance and suggest an important and previously unsuspected role for copper redox reactions during inflammation.IMPORTANCE During infection and inflammation, the innate immune system uses antimicrobial compounds to control bacterial populations. These include toxic metals, like copper, and reactive oxidants, including hypochlorous acid (HOCl). We have now found that RclA, a copper(II) reductase strongly induced by HOCl in proinflammatory Escherichia coli and found in many bacteria inhabiting epithelial surfaces, is required for bacteria to resist killing by the combination of intracellular copper and HOCl and plays an important role in colonization of an animal host. This finding indicates that copper redox chemistry plays a critical and previously underappreciated role in bacterial interactions with the innate immune system.

Complete Genome Sequence of the Prototrophic Bacillus subtilis subsp. subtilis Strain SP1

Here, we present the complete genome sequence of the Bacillus subtilis strain SP1. This strain is a descendant of the laboratory strain 168. The strain is suitable for biotechnological applications because the prototrophy for tryptophan has been restored. Due to laboratory cultivation, the strain has acquired 24 additional sequence variations.

Here, we present the complete genome sequence of the Bacillus subtilis strain SP1. This strain is a descendant of the laboratory strain 168. The strain is suitable for biotechnological applications because the prototrophy for tryptophan has been restored. Due to laboratory cultivation, the strain has acquired 24 additional sequence variations.

Advances on systems metabolic engineering of Bacillus subtilis as a chassis cell

The Gram-positive model bacterium Bacillus subtilis, has been broadly applied in various fields because of its low pathogenicity and strong protein secretion ability, as well as its well-developed fermentation technology. B. subtilis is considered as an attractive host in the field of metabolic engineering, in particular for protein expression and secretion, so it has been well studied and applied in genetic engineering. In this review, we discussed why B. subtilis is a good chassis cell for metabolic engineering. We also summarized the latest research progress in systematic biology, synthetic biology and evolution-based engineering of B. subtilis, and showed systemic metabolic engineering expedite the harnessing B. subtilis for bioproduction.

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

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

Engineering the gut microbiota to treat chronic diseases

Gut microbes play vital roles in host health and disease. A number of commensal bacteria have been used as vectors for genetic engineering to create living therapeutics. This review highlights recent advances in engineering gut bacteria for the treatment of chronic diseases such as metabolic diseases, cancer, inflammatory bowel diseases, and autoimmune disorders. KEY POINTS: • Bacterial homing to tumors has been exploited to deliver therapeutics in mice models. • Engineered bacteria show promise in mouse models of metabolic diseases. • Few engineered bacterial treatments have advanced to clinical studies.

The essential genome of Ralstonia solanacearum

Ralstonia solanacearum is a scientifically/economically important plant pathogenic bacterium. The plant disease caused by R. solanacearum causes huge economic losses, and efficient control measures for the disease remain limited. To gain a better system-level understanding of R. solanacearum, we generated a near-saturated transposon insertion library of R. solanacearum GMI1000 with approximately 240,000 individual insertion mutants. Transposon sequencing (Tn-seq) allowed the mapping of 70.44%-80.96% of all potential insertion sites of the mariner C9 transposase in the genome of R. solanacearum and the identification of 465 genes essential for the growth of R. solanacearum in rich medium. Functional and comparative analyses of essential genes revealed that many basic physiological and biochemical processes such as transcription differ between R. solanacearum and other bacteria. A comparative analysis of essential genes also suggested that 34 genes might be essential only for Ralstonia group bacteria, whereas another 16 essential genes are unique to Ralstonia, providing high-priority candidate targets for developing R. solanacearum-specific drugs.

Linking Engineered Cells to Their Digital Twins: A Version Control System for Strain Engineering

As DNA sequencing and synthesis become cheaper and more easily accessible, the scale and complexity of biological engineering projects is set to grow. Yet, although there is an accelerating convergence between biotechnology and digital technology, a deficit in software and laboratory techniques diminishes the ability to make biotechnology more agile, reproducible, and transparent while, at the same time, limiting the security and safety of synthetic biology constructs. To partially address some of these problems, this paper presents an approach for physically linking engineered cells to their digital footprint-we called it digital twinning. This enables the tracking of the entire engineering history of a cell line in a specialized version control system for collaborative strain engineering via simple barcoding protocols.

Experimental Challenges for Reduced Genomes: The Cell Model Escherichia coli

Genome reduction, as a top-down approach to obtain the minimal genetic information essential for a living organism, has been conducted with bacterial cells for decades. The most popular and well-studied cell models for genome reduction are Escherichia coli strains. As the previous literature intensively introduced the genetic construction and application of the genome-reduced Escherichia coli strains, the present review focuses the design principles and compares the reduced genome collections from the specific viewpoint of growth, which represents a fundamental property of living cells and is an important feature for their biotechnological application. For the extended simplification of the genomic sequences, the approach of experimental evolution and concern for medium optimization are newly proposed. The combination of the current techniques of genomic construction and the newly proposed methodologies could allow us to acquire growing Escherichia coli cells carrying the extensively reduced genome and to address the question of what the minimal genome essential for life is.

Toward a Synthetic Yeast Endosymbiont with a Minimal Genome

Based on the endosymbiotic theory, one of the key events that occurred during mitochondrial evolution was an extensive loss of nonessential genes from the protomitochondrial endosymbiont genome and transfer of some of the essential endosymbiont genes to the host nucleus. We have developed an approach to recapitulate various aspects of endosymbiont genome minimization using a synthetic system consisting of Escherichia coli endosymbionts within host yeast cells. As a first step, we identified a number of E. coli auxotrophs of central metabolites that can form viable endosymbionts within yeast cells. These studies provide a platform to identify nonessential biosynthetic pathways that can be deleted in the E. coli endosymbionts to investigate the evolutionary adaptations in the host and endosymbiont during the evolution of mitochondria.

Evolution of bacteria seen through their essential genes: the case of Pseudomonas aeruginosa and Azotobacter vinelandii

Pseudomonas aeruginosa is a metabolically versatile bacterium and also an important opportunistic pathogen. It has a remarkable genomic structure since the genetic information encoding its pathogenicity-related traits belongs to its core-genome while both environmental and clinical isolates are part of the same population with a highly conserved genomic sequence. Unexpectedly, considering the high level of sequence identity and homologue gene number shared between different P. aeruginosa isolates, the presence of specific essential genes of the two type strains PAO1 and PA14 has been reported to be highly variable. Here we report the detailed bioinformatics analysis of the essential genes of P. aeruginosa PAO1 and PA14 that have been previously experimentally identified and show that the reported gene variability was owed to sequencing and annotation inconsistencies, but that in fact they are highly conserved. This bioinformatics analysis led us to the definition of 348 P. aeruginosa general essential genes. In addition we show that 342 of these 348 essential genes are conserved in Azotobacter vinelandii, a nitrogen-fixing, cyst-forming, soil bacterium. These results support the hypothesis of A. vinelandii having a polyphyletic origin with a Pseudomonads genomic backbone, and are a challenge to the accepted theory of bacterial evolution.

Potential use of Bacillus genera for metals removal from spent catalysts

The aim of the present study was to isolate microorganisms able to tolerate Ni²⁺ and V⁵⁺ from different sites located close to a mineral mine in Guanajuato, Mexico, and then to evaluate their ability to remove metals contained in a spent catalyst. Seventeen isolates were obtained; among them seven presented a minimum inhibitory concentration (MIC) higher than 200 mg/L of Ni²⁺ and V⁵⁺ each. Nickel and Vanadium removal was evaluated in 9 K liquid medium added with spent catalyst at 16% (s/v) pulp density and incubated at 30 °C, 150 rpm for 7 days. Only three isolates which were coded as PRGSd-MS-2, MNSH2-AH-3, and MNSS-AH-4 showed a significant removal at the end of treatment corresponding in mg kg^-1 (or percentage metal removal) of 138 (32%), 123 (29%), and 101 (24%) for Ni, respectively; and 557 (26%), 737 (34%), and 456 (21%) mg kg^-1 for V, respectively. The same isolates were capable to remove also Al, Fe, As, and Mg at different extent. Cell morphology changes were observed, in comparison to the control system at the end of biological treatment as a higher quantity of spores for MNSH2-AH-3, 2 μm cells in pairs for MNSS-AH-4, also long chain-vegetative cells having inclusions into the cell surface were observed for PRGSd-MS-2. The three isolated microorganisms were identified by sequencing of the 16S gene as Bacillus thuringiensis, Bacillus megaterium, and Bacillus sp, respectively, suggesting its potential use in the treatment of this solid industrial waste.

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.

Essential metabolism for a minimal cell

JCVI-syn3A, a robust minimal cell with a 543 kbp genome and 493 genes, provides a versatile platform to study the basics of life. Using the vast amount of experimental information available on its precursor, Mycoplasma mycoides capri, we assembled a near-complete metabolic network with 98% of enzymatic reactions supported by annotation or experiment. The model agrees well with genome-scale in vivo transposon mutagenesis experiments, showing a Matthews correlation coefficient of 0.59. The genes in the reconstruction have a high in vivo essentiality or quasi-essentiality of 92% (68% essential), compared to 79% in silico essentiality. This coherent model of the minimal metabolism in JCVI-syn3A at the same time also points toward specific open questions regarding the minimal genome of JCVI-syn3A, which still contains many genes of generic or completely unclear function. In particular, the model, its comparison to in vivo essentiality and proteomics data yield specific hypotheses on gene functions and metabolic capabilities; and provide suggestions for several further gene removals. In this way, the model and its accompanying data guide future investigations of the minimal cell. Finally, the identification of 30 essential genes with unclear function will motivate the search for new biological mechanisms beyond metabolism.

One way that researchers can test whether they understand a biological system is to see if they can accurately recreate it as a computer model. The more they learn about living things, the more the researchers can improve their models and the closer the models become to simulating the original. In this approach, it is best to start by trying to model a simple system.

Biologists have previously succeeded in creating ‘minimal bacterial cells’. These synthetic cells contain fewer genes than almost all other living things and they are believed to be among the simplest possible forms of life that can grow on their own. The minimal cells can produce all the chemicals that they need to survive – in other words, they have a metabolism. Accurately recreating one of these cells in a computer is a key first step towards simulating a complete living system.

Breuer et al. have developed a computer model to simulate the network of the biochemical reactions going on inside a minimal cell with just 493 genes. By altering the parameters of their model and comparing the results to experimental data, Breuer et al. explored the accuracy of their model. Overall, the model reproduces experimental results, but it is not yet perfect. The differences between the model and the experiments suggest new questions and tests that could advance our understanding of biology. In particular, Breuer et al. identified 30 genes that are essential for life in these cells but that currently have no known purpose.

Continuing to develop and expand models like these to reproduce more complex living systems provides a tool to test current knowledge of biology. These models may become so advanced that they could predict how living things will respond to changing situations. This would allow scientists to test ideas sooner and make much faster progress in understanding life on Earth. Ultimately, these models could one day help to accelerate medical and industrial processes to save lives and enhance productivity.

Tn-Core: A Toolbox for Integrating Tn-seq Gene Essentiality Data and Constraint-Based Metabolic Modeling

The design of synthetic cells requires a detailed understanding of the relevance of genes and gene networks underlying complex cellular phenotypes. Transposon-sequencing (Tn-seq) and constraint-based metabolic modeling can be used to probe the core genetic and metabolic networks underlying a biological process. Integrating these highly complementary experimental and in silico approaches has the potential to yield a highly comprehensive understanding of the core networks of a cell. Specifically, it can facilitate the interpretation of Tn-seq data sets and identify gaps in the data that could hinder the engineering of the cellular system, while also providing refined models for the accurate predictions of cellular metabolism. Here, we present Tn-Core, the first easy-to-use computational pipeline specifically designed for integrating Tn-seq data with metabolic modeling, prepared for use by both experimental and computational biologists. Tn-Core is a MATLAB toolbox that contains several custom functions, and it is built upon existing functions within the COBRA Toolbox and the TIGER Toolbox. Tn-Core takes as input a genome-scale metabolic model, Tn-seq data, and optionally RNA-seq data, and returns: (i) a context-specific core metabolic model; (ii) an evaluation of redundancies within core metabolic pathways, and optionally (iii) a refined genome-scale metabolic model. A simple, user-friendly workflow, requiring limited knowledge of metabolic modeling, is provided that allows users to run the analyses and export the data as easy-to-explore files of value to both experimental and computational biologists. We demonstrate the utility of Tn-Core using Sinorhizobium meliloti, Pseudomonas aeruginosa, and Rhodobacter sphaeroides genome-scale metabolic reconstructions as case studies.