Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism

Metabolic Profile of the Genome-Reduced Bacillus subtilis Strain IIG-Bs-27-39: An Attractive Chassis for Recombinant Protein Production

The Gram-positive bacterium Bacillus subtilis is extensively used in the industry for the secretory production of proteins with commercial value. To further improve its performance, this microbe has been the subject of extensive genome engineering efforts, especially the removal of large genomic regions that are dispensable or even counterproductive. Here, we present the genome-reduced B. subtilis strain IIG-Bs-27-39, which was obtained through systematic deletion of mobile genetic elements, as well as genes for extracellular proteases, sporulation, flagella formation, and antibiotic production. Different from previously characterized genome-reduced B. subtilis strains, the IIG-Bs-27-39 strain was still able to grow on minimal media. We used this feature to benchmark strain IIG-Bs-27-39 against its parental strain 168 with respect to heterologous protein production and metabolic parameters during bioreactor cultivation. The IIG-Bs-27-39 strain presented superior secretion of difficult-to-produce staphylococcal antigens, as well as higher specific growth rates and biomass yields. At the metabolic level, changes in byproduct formation and internal amino acid pools were observed, whereas energetic parameters such as the ATP yield, ATP/ADP levels, and adenylate energy charge were comparable between the two strains. Intriguingly, we observed a significant increase in the total cellular NADPH level during all tested conditions and increases in the NAD+ and NADP(H) pools during protein production. This indicates that the IIG-Bs-27-39 strain has more energy available for anabolic processes and protein production, thereby providing a link between strain physiology and production performance. On this basis, we conclude that the genome-reduced strain IIG-Bs-27-39 represents an attractive chassis for future biotechnological applications.

The Construction of an Environmentally Friendly Super-Secreting Strain of Bacillus subtilis through Systematic Modulation of Its Secretory Pathway Using the CRISPR-Cas9 System

Achieving commercially significant yields of recombinant proteins in Bacillus subtilis requires the optimization of its protein production pathway, including transcription, translation, folding, and secretion. Therefore, in this study, our aim was to maximize the secretion of a reporter α-amylase by overcoming potential bottlenecks within the secretion process one by one, using a clustered regularly interspaced short palindromic repeat-Cas9 (CRISPR-Cas9) system. The strength of single and tandem promoters was evaluated by measuring the relative α-amylase activity of AmyQ integrated into the B. subtilis chromosome. Once a suitable promoter was selected, the expression levels of amyQ were upregulated through the iterative integration of up to six gene copies, thus boosting the α-amylase activity 20.9-fold in comparison with the strain harboring a single amyQ gene copy. Next, α-amylase secretion was further improved to a 26.4-fold increase through the overexpression of the extracellular chaperone PrsA and the signal peptide peptidase SppA. When the final expression strain was cultivated in a 3 L fermentor for 90 h, the AmyQ production was enhanced 57.9-fold. The proposed strategy allows for the development of robust marker-free plasmid-less super-secreting B. subtilis strains with industrial relevance.

Reconstructing the transcriptional regulatory network of probiotic L. reuteri is enabled by transcriptomics and machine learning

Limosilactobacillus reuteri, a probiotic microbe instrumental to human health and sustainable food production, adapts to diverse environmental shifts via dynamic gene expression. We applied the independent component analysis (ICA) to 117 RNA-seq data sets to decode its transcriptional regulatory network (TRN), identifying 35 distinct signals that modulate specific gene sets. Our findings indicate that the ICA provides a qualitative advancement and captures nuanced relationships within gene clusters that other methods may miss. This study uncovers the fundamental properties of L. reuteri's TRN and deepens our understanding of its arginine metabolism and the co-regulation of riboflavin metabolism and fatty acid conversion. It also sheds light on conditions that regulate genes within a specific biosynthetic gene cluster and allows for the speculation of the potential role of isoprenoid biosynthesis in L. reuteri's adaptive response to environmental changes. By integrating transcriptomics and machine learning, we provide a system-level understanding of L. reuteri's response mechanism to environmental fluctuations, thus setting the stage for modeling the probiotic transcriptome for applications in microbial food production.

IMPORTANCE

We have studied Limosilactobacillus reuteri, a beneficial probiotic microbe that plays a significant role in our health and production of sustainable foods, a type of foods that are nutritionally dense and healthier and have low-carbon emissions compared to traditional foods. Similar to how humans adapt their lifestyles to different environments, this microbe adjusts its behavior by modulating the expression of genes. We applied machine learning to analyze large-scale data sets on how these genes behave across diverse conditions. From this, we identified 35 unique patterns demonstrating how L. reuteri adjusts its genes based on 50 unique environmental conditions (such as various sugars, salts, microbial cocultures, human milk, and fruit juice). This research helps us understand better how L. reuteri functions, especially in processes like breaking down certain nutrients and adapting to stressful changes. More importantly, with our findings, we become closer to using this knowledge to improve how we produce more sustainable and healthier foods with the help of microbes.

Bacillus subtilis NDmed, a model strain for biofilm genetic studies

The Bacillus subtilis strain NDmed was isolated from an endoscope washer-disinfector in a medical environment. NDmed can form complex macrocolonies with highly wrinkled architectural structures on solid medium. In static liquid culture, it produces thick pellicles at the interface with air as well as remarkable highly protruding ''beanstalk-like'' submerged biofilm structures at the solid surface. Since these mucoid submerged structures are hyper-resistant to biocides, NDmed has the ability to protect pathogens embedded in mixed-species biofilms by sheltering them from the action of these agents. Additionally, this non-domesticated and highly biofilm forming strain has the propensity of being genetically manipulated. Due to all these properties, the NDmed strain becomes a valuable model for the study of B. subtilis biofilms. This review focuses on several studies performed with NDmed that have highlighted the sophisticated genetic dynamics at play during B. subtilis biofilm formation. Further studies in project using modern molecular tools of advanced technologies with this strain, will allow to deepen our knowledge on the emerging properties of multicellular bacterial life.

Bacillus sp. as a microbial cell factory: Advancements and future prospects

Bacillus sp. is one of the most distinctive gram-positive bacteria, able to grow efficiently using cheap carbon sources and secrete a variety of useful substances, which are widely used in food, pharmaceutical, agricultural and environmental industries. At the same time, Bacillus sp. is also recognized as a safe genus with a relatively clear genetic background, which is conducive to the industrial production of target metabolites. In this review, we discuss the reasons why Bacillus sp. has been so extensively studied and summarize its advances in systems and synthetic biology, engineering strategies to improve microbial cell properties, and industrial applications in several metabolic engineering applications. Finally, we present the current challenges and possible solutions to provide a reliable basis for Bacillus sp. as a microbial cell factory.

Direct comparison of spatial transcriptional heterogeneity across diverse Bacillus subtilis biofilm communities

Bacillus subtilis can form various types of spatially organised communities on surfaces, such as colonies, pellicles and submerged biofilms. These communities share similarities and differences, and phenotypic heterogeneity has been reported for each type of community. Here, we studied spatial transcriptional heterogeneity across the three types of surface-associated communities. Using RNA-seq analysis of different regions or populations for each community type, we identified genes that are specifically expressed within each selected population. We constructed fluorescent transcriptional fusions for 17 of these genes, and observed their expression in submerged biofilms using time-lapse confocal laser scanning microscopy (CLSM). We found mosaic expression patterns for some genes; in particular, we observed spatially segregated cells displaying opposite regulation of carbon metabolism genes (gapA and gapB), indicative of distinct glycolytic or gluconeogenic regimes coexisting in the same biofilm region. Overall, our study provides a direct comparison of spatial transcriptional heterogeneity, at different scales, for the three main models of B. subtilis surface-associated communities.

Redox signaling-driven modulation of microbial biosynthesis and biocatalysis

Microbial communication can drive coordinated functions through sensing, analyzing and processing signal information, playing critical roles in biomanufacturing and life evolution. However, it is still a great challenge to develop effective methods to construct a microbial communication system with coordinated behaviors. Here, we report an electron transfer triggered redox communication network consisting of three building blocks including signal router, optical verifier and bio-actuator for microbial metabolism regulation and coordination. In the redox communication network, the Fe3+/Fe2+ redox signal can be dynamically and reversibly transduced, channeling electrons directly and specifically into bio-actuator cells through iron oxidation pathway. The redox communication network drives gene expression of electron transfer proteins and simultaneously facilitates the critical reducing power regeneration in the bio-actuator, thus enabling regulation of microbial metabolism. In this way, the redox communication system efficiently promotes the biomanufacturing yield and CO2 fixation rate of bio-actuator. Furthermore, the results demonstrate that this redox communication strategy is applicable both in co-culture and microbial consortia. The proposed electron transfer triggered redox communication strategy in this work could provide an approach for reducing power regeneration and metabolic optimization and could offer insights into improving biomanufacturing efficiency.

Local flux coordination and global gene expression regulation in metabolic modeling

Genome-scale metabolic networks (GSMs) are fundamental systems biology representations of a cell's entire set of stoichiometrically balanced reactions. However, such static GSMs do not incorporate the functional organization of metabolic genes and their dynamic regulation (e.g., operons and regulons). Specifically, there are numerous topologically coupled local reactions through which fluxes are coordinated; the global growth state often dynamically regulates many gene expression of metabolic reactions via global transcription factor regulators. Here, we develop a GSM reconstruction method, Decrem, by integrating locally coupled reactions and global transcriptional regulation of metabolism by cell state. Decrem produces predictions of flux and growth rates, which are highly correlated with those experimentally measured in both wild-type and mutants of three model microorganisms Escherichia coli, Saccharomyces cerevisiae, and Bacillus subtilis under various conditions. More importantly, Decrem can also explain the observed growth rates by capturing the experimentally measured flux changes between wild-types and mutants. Overall, by identifying and incorporating locally organized and regulated functional modules into GSMs, Decrem achieves accurate predictions of phenotypes and has broad applications in bioengineering, synthetic biology, and microbial pathology.

Efficient, Formal, Material, and Final Causes in Biology and Technology

This paper considers how a classification of causal effects as comprising efficient, formal, material, and final causation can provide a useful understanding of how emergence takes place in biology and technology, with formal, material, and final causation all including cases of downward causation; they each occur in both synchronic and diachronic forms. Taken together, they underlie why all emergent levels in the hierarchy of emergence have causal powers (which is Noble's principle of biological relativity) and so why causal closure only occurs when the upwards and downwards interactions between all emergent levels are taken into account, contra to claims that some underlying physics level is by itself causality complete. A key feature is that stochasticity at the molecular level plays an important role in enabling agency to emerge, underlying the possibility of final causation occurring in these contexts.

What remains from living cells in bacterial lysate-based cell-free systems

Because they mimic cells while offering an accessible and controllable environment, lysate-based cell-free systems (CFS) have emerged as valuable biotechnology tools for synthetic biology. Historically used to uncover fundamental mechanisms of life, CFS are nowadays used for a multitude of purposes, including protein production and prototyping of synthetic circuits. Despite the conservation of fundamental functions in CFS like transcription and translation, RNAs and certain membrane-embedded or membrane-bound proteins of the host cell are lost when preparing the lysate. As a result, CFS largely lack some essential properties of living cells, such as the ability to adapt to changing conditions, to maintain homeostasis and spatial organization. Regardless of the application, shedding light on the black-box of the bacterial lysate is necessary to fully exploit the potential of CFS. Most measurements of the activity of synthetic circuits in CFS and in vivo show significant correlations because these only require processes that are preserved in CFS, like transcription and translation. However, prototyping circuits of higher complexity that require functions that are lost in CFS (cell adaptation, homeostasis, spatial organization) will not show such a good correlation with in vivo conditions. Both for prototyping circuits of higher complexity and for building artificial cells, the cell-free community has developed devices to reconstruct cellular functions. This mini-review compares bacterial CFS to living cells, focusing on functional and cellular process differences and the latest developments in restoring lost functions through complementation of the lysate or device engineering.

A Systems Biology Approach To Disentangle the Direct and Indirect Effects of Global Transcription Factors on Gene Expression in Escherichia coli

Delineating the pleiotropic effects of global transcriptional factors (TFs) is critical for understanding the system-wide regulatory response in a particular environment. Currently, with the availability of genome-wide TF binding and gene expression data for Escherichia coli, several gene targets can be assigned to the global TFs, albeit inconsistently. Here, using a systematic integrated approach with emphasis on metabolism, we characterized and quantified the direct effects as well as the growth rate-mediated indirect effects of global TFs using deletion mutants of FNR, ArcA, and IHF regulators (focal TFs) under glucose fermentative conditions. This categorization enabled us to disentangle the dense connections seen within the transcriptional regulatory network (TRN) and determine the exact nature of focal TF-driven epistatic interactions with other global and pathway-specific local regulators (iTFs). We extended our analysis to combinatorial deletions of these focal TFs to determine their cross talk effects as well as conserved patterns of regulatory interactions. Moreover, we predicted with high confidence several novel metabolite-iTF interactions using inferred iTF activity changes arising from the allosteric effects of the intracellular metabolites perturbed as a result of the absence of focal TFs. Further, using compendium level computational analyses, we revealed not only the coexpressed genes regulated by these focal TFs but also the coordination of the direct and indirect target expression in the context of the economy of intracellular metabolites. Overall, this study leverages the fundamentals of TF-driven regulation, which could serve as a better template for deciphering mechanisms underlying complex phenotypes. IMPORTANCE Understanding the pleiotropic effects of global TFs on gene expression and their relevance underlying a specific response in a particular environment has been challenging. Here, we distinguish the TF-driven direct effects and growth rate-mediated indirect effects on gene expression using single- and double-deletion mutants of FNR, ArcA, and IHF regulators under anaerobic glucose fermentation. Such dissection assists us in unraveling the precise nature of interactions existing between the focal TF(s) and several other TFs, including those altered by allosteric effects of intracellular metabolites. We were able to recapitulate the previously known metabolite-TF interactions and predict novel interactions with high confidence. Furthermore, we determined that the direct and indirect gene expression have a strong connection with each other when analyzed using the coexpressed- or coregulated-gene approach. Deciphering such regulatory patterns explicitly from the metabolism point of view would be valuable in understanding other unpredicted complex regulation existing in nature.

Global landscape of lysine acylomes in Bacillus subtilis

Lysine acetylation is a common posttranslational modification that regulates numerous biochemical functions in both eukaryotic and prokaryotic species. In addition, several new non-acetyl acylations are structurally different from lysine acetylation and participate in diverse physiological functions. Here, a comprehensive analysis of several lysine acylomes was performed by combining the high-affinity antibody enrichment with high-resolution LC-MS/MS. In total, we identified 2536 lysine acetylated sites, 4723 propionylated sites, 2150 succinylated sites and 3001 malonylated sites in Bacillus subtilis, respectively. These acylated proteins account for 35.8% of total protein in this bacterium. The four lysine acylomes showed a motif preference for glutamate surrounding the modified lysine residues, and a functional preference for several metabolic pathways, such as carbon metabolism, fatty acid metabolism, and ribosome. In addition, more protein-protein interaction clusters were identified in the propionylated substrates than other three lysine acylomes. In summary, our study presents a global landscape of acylation in the Gram-positive model organism Bacillus and their potential functions in metabolism and physiology.

Metabolic Engineering of Bacillus subtilis for Riboflavin Production: A Review

Riboflavin (vitamin B₂) is one of the essential vitamins that the human body needs to maintain normal metabolism. Its biosynthesis has become one of the successful models for gradual replacement of traditional chemical production routes. B. subtilis is characterized by its short fermentation time and high yield, which shows a huge competitive advantage in microbial fermentation for production of riboflavin. This review summarized the advancements of regulation on riboflavin production as well as the synthesis of two precursors of ribulose-5-phosphate riboflavin (Ru5P) and guanosine 5'-triphosphate (GTP) in B. subtilis. The different strategies to improve production of riboflavin by metabolic engineering were also reviewed.

Towards AI-driven longevity research: An overview

While in the past technology has mostly been utilized to store information about the structural configuration of proteins and molecules for research and medical purposes, Artificial Intelligence is nowadays able to learn from the existing data how to predict and model properties and interactions, revealing important knowledge about complex biological processes, such as aging. Modern technologies, moreover, can rely on a broader set of information, including those derived from the next-generation sequencing (e.g., proteomics, lipidomics, and other omics), to understand the interactions between human body and the external environment. This is especially relevant as external factors have been shown to have a key role in aging. As the field of computational systems biology keeps improving and new biomarkers of aging are being developed, artificial intelligence promises to become a major ally of aging research.

NetREX-CF integrates incomplete transcription factor data with gene expression to reconstruct gene regulatory networks

The inference of Gene Regulatory Networks (GRNs) is one of the key challenges in systems biology. Leading algorithms utilize, in addition to gene expression, prior knowledge such as Transcription Factor (TF) DNA binding motifs or results of TF binding experiments. However, such prior knowledge is typically incomplete, therefore, integrating it with gene expression to infer GRNs remains difficult. To address this challenge, we introduce NetREX-CF-Regulatory Network Reconstruction using EXpression and Collaborative Filtering-a GRN reconstruction approach that brings together Collaborative Filtering to address the incompleteness of the prior knowledge and a biologically justified model of gene expression (sparse Network Component Analysis based model). We validated the NetREX-CF using Yeast data and then used it to construct the GRN for Drosophila Schneider 2 (S2) cells. To corroborate the GRN, we performed a large-scale RNA-Seq analysis followed by a high-throughput RNAi treatment against all 465 expressed TFs in the cell line. Our knockdown result has not only extensively validated the GRN we built, but also provides a benchmark that our community can use for evaluating GRNs. Finally, we demonstrate that NetREX-CF can infer GRNs using single-cell RNA-Seq, and outperforms other methods, by using previously published human data.

Magnetothermal Control of Temperature-Sensitive Repressors in Superparamagnetic Iron Nanoparticle-Coated Bacillus subtilis

Superparamagnetic iron oxide nanoparticles (SPIONs) are used as contrast agents in magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), and resulting images can be used to guide magnetothermal heating. Alternating magnetic fields (AMF) cause local temperature increases in regions with SPIONs, and we investigated the ability of magnetic hyperthermia to regulate temperature-sensitive repressors (TSRs) of bacterial transcription. The TSR, TlpA39, was derived from a Gram-negative bacterium and used here for thermal control of reporter gene expression in Gram-positive, Bacillus subtilis. In vitro heating of B. subtilis with TlpA39 controlling bacterial luciferase expression resulted in a 14.6-fold (12 hours; h) and 1.8-fold (1 h) increase in reporter transcripts with a 10.0-fold (12 h) and 12.1-fold (1 h) increase in bioluminescence. To develop magnetothermal control, B. subtilis cells were coated with three SPION variations. Electron microscopy coupled with energy dispersive X-ray spectroscopy revealed an external association with, and retention of, SPIONs on B. subtilis. Furthermore, using long duration AMF we demonstrated magnetothermal induction of the TSRs in SPION-coated B. subtilis with a maximum of 5.6-fold increases in bioluminescence. After intramuscular injections of SPION-coated B. subtilis, histology revealed that SPIONs remained in the same locations as the bacteria. For in vivo studies, 1 h of AMF is the maximum exposure due to anesthesia constraints. Both in vitro and in vivo, there was no change in bioluminescence after 1 h of AMF treatment. Pairing TSRs with magnetothermal energy using SPIONs for localized heating with AMF can lead to transcriptional control that expands options for targeted bacteriotherapies.

The impact of PrsA over-expression on the Bacillus subtilis transcriptome during fed-batch fermentation of alpha-amylase production

The production of the alpha-amylase (AMY) enzyme in Bacillus subtilis at a high rate leads to the accumulation of unfolded AMY, which causes secretion stress. The over-expression of the PrsA chaperone aids enzyme folding and reduces stress. To identify affected pathways and potential mechanisms involved in the reduced growth, we analyzed the transcriptomic differences during fed-batch fermentation between a PrsA over-expressing strain and control in a time-series RNA-seq experiment. We observe transcription in 542 unannotated regions, of which 234 had significant changes in expression levels between the samples. Moreover, 1,791 protein-coding sequences, 80 non-coding genes, and 20 riboswitches overlapping UTR regions of coding genes had significant changes in expression. We identified putatively regulated biological processes via gene-set over-representation analysis of the differentially expressed genes; overall, the analysis suggests that the PrsA over-expression affects ATP biosynthesis activity, amino acid metabolism, and cell wall stability. The investigation of the protein interaction network points to a potential impact on cell motility signaling. We discuss the impact of these highlighted mechanisms for reducing secretion stress or detrimental aspects of PrsA over-expression during AMY production.

Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis

BACKGROUND

Elucidating cellular metabolism led to many breakthroughs in biotechnology, synthetic biology, and health sciences. To date, deriving metabolic fluxes by ¹³C tracer experiments is the most prominent approach for studying metabolic fluxes quantitatively, often with high accuracy and precision. However, the technique has a high demand for experimental resources. Alternatively, flux balance analysis (FBA) has been employed to estimate metabolic fluxes without labeling experiments. It is less informative but can benefit from the low costs and low experimental efforts and gain flux estimates in experimentally difficult conditions. Methods to integrate relevant experimental data have been emerged to improve FBA flux estimations. Data from transcription profiling is often selected since it is easy to generate at the genome scale, typically embedded by a discretization of differential and non-differential expressed genes coding for the respective enzymes.

RESULT

We established the novel method Linear Programming based Gene Expression Model (LPM-GEM). LPM-GEM linearly embeds gene expression into FBA constraints. We implemented three strategies to reduce thermodynamically infeasible loops, which is a necessary prerequisite for such an omics-based model building. As a case study, we built a model of B. subtilis grown in eight different carbon sources. We obtained good flux predictions based on the respective transcription profiles when validating with ¹³C tracer based metabolic flux data of the same conditions. We could well predict the specific carbon sources. When testing the model on another, unseen dataset that was not used during training, good prediction performance was also observed. Furthermore, LPM-GEM outperformed a well-established model building methods.

CONCLUSION

Employing LPM-GEM integrates gene expression data efficiently. The method supports gene expression-based FBA models and can be applied as an alternative to estimate metabolic fluxes when tracer experiments are inappropriate.

Trade-offs predicted by metabolic network structure give rise to evolutionary specialization and phenotypic diversification

Mitigating trade-offs between different resource-utilization functions is key to an organism's ecological and evolutionary success. These trade-offs often reflect metabolic constraints with a complex molecular underpinning; therefore, their consequences for evolutionary processes have remained elusive. Here, we investigate how metabolic architecture induces resource utilization constraints and how these constraints, in turn, elicit evolutionary specialization and diversification. Guided by the metabolic network structure of the bacterium Lactococcus cremoris, we selected two carbon sources (fructose and galactose) with predicted co-utilization constraints. By evolving L. cremoris on either fructose, galactose or a mix of both sugars, we imposed selection favoring divergent metabolic specializations or co-utilization of both resources, respectively. Phenotypic characterization revealed the evolution of either fructose or galactose specialists in the single-sugar treatments. In the mixed sugar regime, we observed adaptive diversification: both specialists coexisted, and no generalist evolved. Divergence from the ancestral phenotype occurred at key pathway junctions in the central carbon metabolism. Fructose specialists evolved mutations in the fbp and pfk genes that appear to balance anabolic and catabolic carbon fluxes. Galactose specialists evolved increased expression of pgmA (the primary metabolic bottleneck of galactose metabolism) and silencing of ptnABCD (the main glucose transporter) and ldh (regulator/enzyme of downstream carbon metabolism). Overall, our study shows how metabolic network architecture and historical contingency serve to predict targets of selection and inform the functional interpretation of evolved mutations. The elucidation of the relationship between molecular constraints and phenotypic trade-offs contributes to an integrative understanding of evolutionary specialization and diversification.

A Sporulation-Specific sRNA Bvs196 Contributing to the Developing Spore in Bacillus velezensis

Many putative sRNAs have been characterized using bioinformatic analysis and high-throughput sequencing in Gram-positive Bacillus strains, but there are only a few functional studies on the sRNAs involved in the spore formation developmental process. In particular, there is no sRNA confirmed experimentally to regulate the late stages of sporulation. Bvs196 is an sRNA with a length of 294 nucleotides that is abundantly expressed in the stationary phase of several media and independently transcribed in Bacillus velezensis strain PEBA20, as validated by RNA-seq and Northern blot,. It is also confirmed, by qRT-PCR, that Bvs196 is transcribed abundantly throughout the intermediate and late stages of sporulation. Using the gfpmut3a gene transcriptional reporter demonstrates that Bvs196 is expressed specifically in the forespore during sporulation and controlled by σF and σG (mainly by σG). This was observed by fluorescence microscopy and multi-function microplate reader. Further evolutionary conservation analysis found that Bvs196 is widely present in Bacillus with a strongly conserved and stable secondary structure. Resistance phenotypic assays of spores formed from the Bvs196 deletion mutant, the overexpressed Bvs196 mutant, and the wild-type strain revealed that the absence of Bvs196 led to reduced heat and UV resistance and enhanced formaldehyde resistance. We determined, by MST analysis, that Bvs196 can directly interact with spo0A and sspN-tlp mRNAs in vitro, and that short incomplete complementary paired bases affect the binding affinity of Bvs196 to target mRNAs. Our results suggest that Bvs196 is a novel sporulation-specific sRNA of B. velezensis, 294 nt in length, independently transcribed under the control of σF and σG in the forespore during sporulation, and that it affects spore resistance, and is able to directly interact with spo0A and sspN-tlp mRNAs. The remarkable conservation and impressive expression level of Bvs196 imply that it acts as an important conservative regulator, presumably by interacting with many other unknown targets in the forespore, and therefore contributing to spore properties. This work provides new clues for further understanding of the spore formation regulatory network.

Microbial chassis engineering drives heterologous production of complex secondary metabolites

The cryptic secondary metabolite biosynthetic gene clusters (BGCs) far outnumber currently known secondary metabolites. Heterologous production of secondary metabolite BGCs in suitable chassis facilitates yield improvement and discovery of new-to-nature compounds. The two juxtaposed conventional model microorganisms, Escherichia coli, Saccharomyces cerevisiae, have been harnessed as microbial chassis to produce a bounty of secondary metabolites with the help of certain host engineering. In last decade, engineering non-model microbes to efficiently biosynthesize secondary metabolites has received increasing attention due to their peculiar advantages in metabolic networks and/or biosynthesis. The state-of-the-art synthetic biology tools lead the way in operating genetic manipulation in non-model microorganisms for phenotypic optimization or yields improvement of desired secondary metabolites. In this review, we firstly discuss the pros and cons of several model and non-model microbial chassis, as well as the importance of developing broader non-model microorganisms as alternative programmable heterologous hosts to satisfy the desperate needs of biosynthesis study and industrial production. Then we highlight the lately advances in the synthetic biology tools and engineering strategies for optimization of non-model microbial chassis, in particular, the successful applications for efficient heterologous production of multifarious complex secondary metabolites, e.g., polyketides, nonribosomal peptides, as well as ribosomally synthesized and post-translationally modified peptides. Lastly, emphasis is on the perspectives of chassis cells development to access the ideal cell factory in the artificial intelligence-driven genome era.

The nucleotide messenger (p)ppGpp is an anti-inducer of the purine synthesis transcription regulator PurR in Bacillus

The nucleotide messenger (p)ppGpp allows bacteria to adapt to fluctuating environments by reprogramming the transcriptome. Despite its well-recognized role in gene regulation, (p)ppGpp is only known to directly affect transcription in Proteobacteria by binding to the RNA polymerase. Here, we reveal a different mechanism of gene regulation by (p)ppGpp in Firmicutes: (p)ppGpp directly binds to the transcription factor PurR to downregulate purine biosynthesis gene expression upon amino acid starvation. We first identified PurR as a receptor of (p)ppGpp in Bacillus anthracis. A co-structure with Bacillus subtilis PurR reveals that (p)ppGpp binds to a PurR pocket reminiscent of the active site of phosphoribosyltransferase enzymes that has been repurposed to serve a purely regulatory role, where the effectors (p)ppGpp and PRPP compete to allosterically control transcription. PRPP inhibits PurR DNA binding to induce transcription of purine synthesis genes, whereas (p)ppGpp antagonizes PRPP to enhance PurR DNA binding and repress transcription. A (p)ppGpp-refractory purR mutant in B. subtilis fails to downregulate purine synthesis genes upon amino acid starvation. Our work establishes the precedent of (p)ppGpp as an effector of a classical transcription repressor and reveals the key function of (p)ppGpp in regulating nucleotide synthesis through gene regulation, from soil bacteria to pathogens.

Glycolysis/gluconeogenesis specialization in microbes is driven by biochemical constraints of flux sensing

Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic reorganization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis, and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa, and Pseudomonas putida. We combined growth dynamics and dynamic changes in intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis, and growth and uncovered fundamental limitations of the regulatory network: After nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.

Global metabolic regulation in Vibrio parahaemolyticus under polymyxin B stimulation

Vibrio parahaemolyticus is responsible for infection diseases of people who consume the contaminated seafood, but its metabolic regulation profile in response to colistin, the last treatment option for multidrug-resistant Gram-negative bacteria, remains unclear. In this study, the metabolic regulation profile of V. parahaemolyticus ATCC33846 under polymyxin B stimulation has been investigated. V. parahaemolyticus exposed to polymyxin B resulted in 4597 differentially transcribed genes, including 673 significantly up-regulated genes and 569 significantly down-regulated genes. In V. parahaemolyticus under polymyxin B stimulation, the cellular antioxidant systems to prevent bacteria from oxidant stress was activated, the synthesis of some nonessential macromolecules was reduced, and the assembly and modification of lipopolysaccharide and peptidoglycan to resist the attack from other antibiotics were promoted. These findings provide new insights into polymyxin B-related stress response in V. parahaemolyticus which should be useful for developing novel drugs for infection.

The arbitrium system controls prophage induction

Some Bacillus-infecting bacteriophages use a peptide-based communication system, termed arbitrium, to coordinate the lysis-lysogeny decision. In this system, the phage produces AimP peptide during the lytic cycle. Once internalized by the host cell, AimP binds to the transcription factor AimR, reducing aimX expression and promoting lysogeny. Although these systems are present in a variety of mobile genetic elements, their role in the phage life cycle has only been characterized in phage phi3T during phage infection. Here, using the B. subtilis SPβ prophage, we show that the arbitrium system is also required for normal prophage induction. Deletion of the aimP gene increased phage reproduction, although the aimR deletion significantly reduced the number of phage particles produced after prophage induction. Moreover, our results indicated that AimR is involved in a complex network of regulation and brought forward two new players in the SPβ lysis-lysogeny decision system, YopN and the phage repressor YopR. Importantly, these proteins are encoded in an operon, the function of which is conserved across all SPβ-like phages encoding the arbitrium system. Finally, we obtained mutant phages in the arbitrium system, which behaved almost identically to the wild-type (WT) phage, indicating that the arbitrium system is not essential in the laboratory but is likely beneficial for phage fitness in nature. In support of this, by possessing a functional arbitrium system, the SPβ phage can optimize production of infective particles while also preserving the number of cells that survive after prophage induction, a strategy that increases phage persistence in nature.

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The arbitrium system controls prophage induction in B. subtilis

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An operon downstream of the arbitrium system is involved in controlling lysogeny

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The operon is functionally conserved in SPβ-like phages encoding arbitrium systems

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YopR acts as the phage repressor in SPβ

An extensive and dynamic trans-omic network illustrating prominent regulatory mechanisms in response to insulin in the liver

An effective combination of multi-omic datasets can enhance our understanding of complex biological phenomena. To build a context-dependent network with multiple omic layers, i.e., a trans-omic network, we perform phosphoproteomics, transcriptomics, proteomics, and metabolomics of murine liver for 4 h after insulin administration and integrate the resulting time series. Structural characteristics and dynamic nature of the network are analyzed to elucidate the impact of insulin. Early and prominent changes in protein phosphorylation and persistent and asynchronous changes in mRNA and protein levels through non-transcriptional mechanisms indicate enhanced crosstalk between phosphorylation-mediated signaling and protein expression regulation. Metabolic response shows different temporal regulation with transient increases at early time points across categories and enhanced response in the amino acid and nucleotide categories at later time points as a result of process convergence. This extensive and dynamic view of the trans-omic network elucidates prominent regulatory mechanisms that drive insulin responses through intricate interlayer coordination.

Identification of an RNA sponge that controls the RoxS riboregulator of central metabolism in Bacillus subtilis

sRNAs are a taxonomically-restricted but transcriptomically-abundant class of post-transcriptional regulators. While of major importance for adaption to the environment, we currently lack global-scale methodology enabling target identification, especially in species without known RNA hub proteins (e.g. Hfq). Using psoralen RNA cross-linking and Illumina-sequencing we identify RNA-RNA interacting pairs in vivo in Bacillus subtilis, resolving previously well-described interactants. Although sRNA-sRNA pairings are rare (compared with sRNA-mRNA), we identify a robust example involving the conserved sRNA RoxS and an unstudied sRNA RosA (Regulator of sRNA A). We show RosA to be the first confirmed RNA sponge described in a Gram-positive bacterium. RosA interacts with at least two sRNAs, RoxS and FsrA. The RosA/RoxS interaction not only affects the levels of RoxS but also its processing and regulatory activity. We also found that the transcription of RosA is repressed by CcpA, the key regulator of carbon-metabolism in B. subtilis. Since RoxS is already known to be transcriptionally controlled by malate via the transcriptional repressor Rex, its post-transcriptional regulation by CcpA via RosA places RoxS in a key position to control central metabolism in response to varying carbon sources.

Self-Organization and Information Processing: From Basic Enzymatic Activities to Complex Adaptive Cellular Behavior

One of the main aims of current biology is to understand the origin of the molecular organization that underlies the complex dynamic architecture of cellular life. Here, we present an overview of the main sources of biomolecular order and complexity spanning from the most elementary levels of molecular activity to the emergence of cellular systemic behaviors. First, we have addressed the dissipative self-organization, the principal source of molecular order in the cell. Intensive studies over the last four decades have demonstrated that self-organization is central to understand enzyme activity under cellular conditions, functional coordination between enzymatic reactions, the emergence of dissipative metabolic networks (DMN), and molecular rhythms. The second fundamental source of order is molecular information processing. Studies on effective connectivity based on transfer entropy (TE) have made possible the quantification in bits of biomolecular information flows in DMN. This information processing enables efficient self-regulatory control of metabolism. As a consequence of both main sources of order, systemic functional structures emerge in the cell; in fact, quantitative analyses with DMN have revealed that the basic units of life display a global enzymatic structure that seems to be an essential characteristic of the systemic functional metabolism. This global metabolic structure has been verified experimentally in both prokaryotic and eukaryotic cells. Here, we also discuss how the study of systemic DMN, using Artificial Intelligence and advanced tools of Statistic Mechanics, has shown the emergence of Hopfield-like dynamics characterized by exhibiting associative memory. We have recently confirmed this thesis by testing associative conditioning behavior in individual amoeba cells. In these Pavlovian-like experiments, several hundreds of cells could learn new systemic migratory behaviors and remember them over long periods relative to their cell cycle, forgetting them later. Such associative process seems to correspond to an epigenetic memory. The cellular capacity of learning new adaptive systemic behaviors represents a fundamental evolutionary mechanism for cell adaptation.

Genome-wide analysis of in vivo CcpA binding with and without its key co-factor HPr in the major human pathogen group A Streptococcus

Catabolite control protein A (CcpA) is a master regulator of carbon source utilization and contributes to the virulence of numerous medically important Gram‐positive bacteria. Most functional assessments of CcpA, including interaction with its key co‐factor HPr, have been performed in nonpathogenic bacteria. In this study we aimed to identify the in vivo DNA binding profile of CcpA and assess the extent to which HPr is required for CcpA‐mediated regulation and DNA binding in the major human pathogen group A Streptococcus (GAS). Using a combination RNAseq/ChIP‐seq approach, we found that CcpA affects transcript levels of 514 of 1667 GAS genes (31%) whereas direct DNA binding was identified for 105 GAS genes. Three of the directly regulated genes encode the key GAS virulence factors Streptolysin S, PrtS (IL‐8 degrading proteinase), and SpeB (cysteine protease). Mutating CcpA Val301 to Ala (strain 2221‐CcpA‐V301A) abolished interaction between CcpA and HPr and impacted the transcript levels of 205 genes (40%) in the total CcpA regulon. By ChIP‐seq analysis, CcpAV301A bound to DNA from 74% of genes bound by wild‐type CcpA, but generally with lower affinity. These data delineate the direct CcpA regulon and clarify the HPr‐dependent and independent activities of CcpA in a key pathogenic bacterium.

Multi-omics Analysis of CRISPRi-Knockdowns Identifies Mechanisms that Buffer Decreases of Enzymes in E. coli Metabolism

Enzymes maintain metabolism, and their concentration affects cellular fitness: high enzyme levels are costly, and low enzyme levels can limit metabolic flux. Here, we used CRISPR interference (CRISPRi) to study the consequences of decreasing E. coli enzymes below wild-type levels. A pooled CRISPRi screen with 7,177 strains demonstrates that metabolism buffers fitness defects for hours after the induction of CRISPRi. We characterized the metabolome and proteome responses in 30 CRISPRi strains and elucidated three gene-specific buffering mechanisms: ornithine buffered the knockdown of carbamoyl phosphate synthetase (CarAB) by increasing CarAB activity, S-adenosylmethionine buffered the knockdown of homocysteine transmethylase (MetE) by de-repressing expression of the methionine pathway, and 6-phosphogluconate buffered the knockdown of 6-phosphogluconate dehydrogenase (Gnd) by activating a bypass. In total, this work demonstrates that CRISPRi screens can reveal global sources of metabolic robustness and identify local regulatory mechanisms that buffer decreases of specific enzymes. A record of this paper's transparent peer review process is included in the Supplemental Information.

Cell-free synthesis system-assisted pathway bottleneck diagnosis and engineering in Bacillus subtilis

Metabolic engineering is a key technology for cell factories construction by rewiring cellular resources to achieve efficient production of target chemicals. However, the existence of bottlenecks in synthetic pathway can seriously affect production efficiency, which is also one of the core issues for metabolic engineers to solve. Therefore, developing an approach for diagnosing potential metabolic bottlenecks in a faster and simpler manner is of great significance to accelerate cell factories construction. The cell-free reaction system based on cell lysates can transfer metabolic reactions from in vivo to in vitro, providing a flexible access to directly change protein and metabolite variables, thus provides a potential solution for rapid identification of bottlenecks. Here, bottleneck diagnosis of the N-acetylneuraminic acid (NeuAc) biosynthesis pathway in industrially important chassis microorganism Bacillus subtilis was performed using cell-free synthesis system. Specifically, a highly efficient B. subtilis cell-free system for NeuAc de novo synthesis was firstly constructed, which had a 305-fold NeuAc synthesis rate than that in vivo and enabled fast pathway dynamics analysis. Next, through the addition of all potential key intermediates in combination with substrate glucose respectively, it was found that insufficient phosphoenolpyruvate supply was one of the NeuAc pathway bottlenecks. Rational in vivo metabolic engineering of NeuAc-producing B. subtilis was further performed to eliminate the bottleneck. By down-regulating the expression level of pyruvate kinase throughout the growth phase or only in the stationary phase using inhibitory N-terminal coding sequences (NCSs) and growth-dependent regulatory NCSs respectively, the maximal NeuAc titer increased 2.0-fold. Our study provides a rapid method for bottleneck diagnosis, which may help to accelerate the cycle of design, build, test and learn cycle for metabolic engineering.

Developing rapid growing Bacillus subtilis for improved biochemical and recombinant protein production

Bacillus subtilis is a model Gram-positive bacterium, which has been widely used as industrially important chassis in synthetic biology and metabolic engineering. Rapid growth of chassis is beneficial for shortening the fermentation period and enhancing production of target product. However, engineered B. subtilis with faster growth phenotype is lacking. Here, fast-growing B. subtilis were constructed through rational gene knockout and adaptive laboratory evolution using wild type strain B. subtilis 168 (BS168) as starting strain. Specifically, strains BS01, BS02, and BS03 were obtained through gene knockout of oppD, hag, and flgD genes, respectively, resulting 15.37%, 24.18% and 36.46% increases of specific growth rate compared with BS168. Next, strains A28 and A40 were obtained through adaptive laboratory evolution, whose specific growth rates increased by 39.88% and 43.53% compared to BS168, respectively. Then these two methods were combined via deleting oppD, hag, and flgD genes respectively on the basis of evolved strain A40, yielding strain A4003 with further 7.76% increase of specific growth rate, reaching 0.75 h^-1 in chemical defined M9 medium. Finally, bioproduction efficiency of intracellular product (ribonucleic acid, RNA), extracellular product (acetoin), and recombinant proteins (green fluorescent protein (GFP) and ovalbumin) by fast-growing strain A4003 was tested. And the production of RNA, acetoin, GFP, and ovalbumin increased 38.09%, 5.40%, 9.47% and 19.79% using fast-growing strain A4003 as chassis compared with BS168, respectively. The developed fast-growing B. subtilis strains and strategies used for developing these strains should be useful for improving bioproduction efficiency and constructing other industrially important bacterium with faster growth phenotype.

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Fast-growing Bacillus subtilis were constructed through rational gene knockout and adaptive laboratory evolution.

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Specific growth rate of engineered B. subtilis ​increased 53.06% compared with ​B. subtilis 168, reaching 0.75 h^-1 ​in M9 medium.

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Production of RNA, acetoin, and ovalbumin increased 38.09%, 5.40%, and 19.79% using fast-growing strain as chassis.

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.

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.

Spo0A can efficiently enhance the expression of the alkaline protease gene aprE in Bacillus licheniformis by specifically binding to its regulatory region

The expression of enzymes in Bacillus licheniformis, such as the valuable extracellular alkaline protease AprE, is highly regulated by a complex transcriptional regulation mechanism. Here, we found that the transcript abundance of aprE varies >343-fold in response to the supply of nutrients or to environmental challenges. To identify the underlying regulatory mechanism, the core promoter of aprE and several important upstream regulatory regions outside the promoter were firstly confirmed by 5'-RACE and mutagenesis experiments. The specific proteins that bind to the identified sequences were subsequently captured by DNA pull-down experiments, which yielded the transcriptional factors (TFs) Spo0A, CggR, FruR, YhcZ, as well as fragments of functionally unassigned proteins. Further electrophoretic mobility shift assay (EMSA) and DNase I foot-printing experiments indicated that Spo0A can directly bind to the region from -92 to -118 nucleotides upstream of the transcription start site, and the deletion of this specific region drastically decreased the production of AprE. Taken together, these results indicated that the expression of aprE was mainly regulated by the interplay between Spo0A and its cognate DNA sequence, which was successfully applied to overproduce AprE in a genetically modified host harboring three aprE expression cassettes. The DNA binding proteins may serve to increase the efficiency of transcription by creating an additional binding site for RNA polymerase. The discovery of this mechanism significantly increases our understanding of the aprE transcription mechanism, which is of great importance for AprE overproduction.

Quorum sensing for population-level control of bacteria and potential therapeutic applications

Quorum sensing (QS), a microbial cell-to-cell communication process, dynamically regulates a variety of metabolism and physiological activities. In this review, we provide an update on QS applications based on autoinducer molecules including acyl-homoserine lactones (AHLs), auto-inducing peptides (AIPs), autoinducer 2 (AI-2) and indole in population-level control of bacteria, and highlight the potential in developing novel clinical therapies. We summarize the development in the combination of various genetic circuits such as genetic oscillators, toggle switches and logic gates with AHL-based QS devices in Gram-negative bacteria. An overview is then offered to the state-of-the-art of much less researched applications of AIP-based QS devices with Gram-positive bacteria, followed by a review of the applications of AI-2 and indole based QS for interspecies communication among microbial communities. Building on these general-purpose QS applications, we highlight the disruptions and manipulations of QS devices as potential clinical therapies for diseases caused by biofilm formation, antibiotic resistance and the phage invasion. The last part of reviewed literature is dedicated to mathematical modelling for QS applications. Finally, the key challenges and future perspectives of QS applications in monoclonal synthetic biology and synthetic ecology are discussed.

CRISPRi-Guided Multiplexed Fine-Tuning of Metabolic Flux for Enhanced Lacto-N-neotetraose Production in Bacillus subtilis

Lacto-N-neotetraose (LNnT), one of the oligosaccharides in human milk, has many beneficial effects on infant health. In a recent work, we have constructed a recombinant Bacillus subtilis strain for the production of LNnT. Here, we further improved LNnT production with a xylose-induced clustered regularly interspaced short palindromic repeats interference system. In particular, the expressions of pfkA and pyk genes in the Embden-Meyerhof-Parnas pathway module, zwf gene in the pentose phosphate pathway module, and mnaA gene in the teichoic acid synthesis module were downregulated. The LNnT titer was increased from 1.32 to 1.55 g/L. Furthermore, to improve the conversion efficiency of lacto-N-triose II to LNnT, we knocked out tuaD gene in branch pathway and improved the expression of lgtB gene, resulting in the further increase of LNnT titer to 2.01 g/L. Finally, the addition time and amount of inducer xylose were optimized, and LNnT titer reached 2.30 g/L in shake flask and 5.41 g/L in 3 L bioreactor.

Bacterial growth physiology and RNA metabolism

Bacteria are sophisticated systems with high capacity and flexibility to adapt to various environmental conditions. Each prokaryote however possesses a defined metabolic network, which sets its overall metabolic capacity, and therefore the maximal growth rate that can be reached. To achieve optimal growth, bacteria adopt various molecular strategies to optimally adjust gene expression and optimize resource allocation according to the nutrient availability. The resulting physiological changes are often accompanied by changes in the growth rate, and by global regulation of gene expression. The growth-rate-dependent variation of the abundances in the cellular machineries, together with condition-specific regulatory mechanisms, affect RNA metabolism and fate and pose a challenge for rational gene expression reengineering of synthetic circuits. This article is part of a Special Issue entitled: RNA and gene control in bacteria, edited by Dr. M. Guillier and F. Repoila.

Recombinant expression and biochemical characterization of a novel keratinase BsKER71 from feather degrading bacterium Bacillus subtilis S1-4

Bacillus subtilis S1-4, isolated from chicken feather could efficiently degrade feathers by secreting several extracellular proteases. In order to get insight into the individual protease involved in keratin hydrolysis, a keratinase designed as BsKER71 was cloned and expressed in Bacillus subtilis WB600. In silico analysis revealed that BsKER71 protein contained a mature protein of 36.1 kDa. Further, purified BsKER71 could hydrolyze a variety of natural proteins, such as fibrous protein, collagen protein, casein, keratin and bovine serum albumin. In addition, this keratinase exhibited high enzyme activity in a wide range of pH and optimal pH of 10.0 and 9.0 in the hydrolysis of casein and keratin, respectively. Similarly, the optimal temperature was 55 °C and 50 °C for the hydrolysis of above two substrates, respectively. The hydrolytic activity was significantly inhibited by phenylmethanesulfonyl fluoride (PMSF), indicating the presence of serine residue in the active site. Moreover, ethylenediaminetetraacetic acid (EDTA) and phenanthroline moderately inhibited the hydrolytic activity. The catalytic activity was stimulated by Mg²⁺ and Ca²⁺, but greatly inhibited by Cu²⁺. Furthermore, several chemicals exhibited different effects on the hydrolysis of casein and keratin by BsKER71. These results provided a better understanding of BsKER71 from feather degrading bacterium B. subtilis S1-4.

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome.

Mechanistic insight into the regulation of transcriptional modules remains scarce. Here, the authors identify statistically independent gene sets by applying independent component analysis to a high-quality E. coli RNA-seq data compendium and find that most gene sets represent the effects of specific transcriptional regulators.

Transcriptome analysis of Xanthomonas oryzae pv. oryzicola exposed to H2O2 reveals horizontal gene transfer contributes to its oxidative stress response

Xanthomonas oryzae pv. oryzicola (Xoc), the causal agent of bacterial leaf streak, is one of the most severe seed-borne bacterial diseases of rice. However, the molecular mechanisms underlying Xoc in response to oxidative stress are still unknown. In this study, we performed a time-course RNA-seq analysis on the Xoc in response to H2O2, aiming to reveal its oxidative response network. Overall, our RNA sequence analysis of Xoc revealed a significant global gene expression profile when it was exposed to H2O2. There were 7, 177, and 246 genes that were differentially regulated at the early, middle, and late stages after exposure, respectively. Three genes (xoc_1643, xoc_1946, xoc_3249) showing significantly different expression levels had proven relationships with oxidative stress response and pathogenesis. Moreover, a hypothetical protein (XOC_2868) showed significantly differential expression, and the xoc_2868 mutants clearly displayed a greater H2O2 sensitivity and decreased pathogenicity than those of the wild-type. Gene localization and phylogeny analysis strongly suggests that this gene may have been horizontally transferred from a Burkholderiaceae ancestor. Our study not only provides a first glance of Xoc's global response against oxidative stress, but also reveals the impact of horizontal gene transfer in the evolutionary history of Xoc.

Systematic identification of metabolites controlling gene expression in E. coli

Metabolism controls gene expression through allosteric interactions between metabolites and transcription factors. These interactions are usually measured with in vitro assays, but there are no methods to identify them at a genome-scale in vivo. Here we show that dynamic transcriptome and metabolome data identify metabolites that control transcription factors in E. coli. By switching an E. coli culture between starvation and growth, we induce strong metabolite concentration changes and gene expression changes. Using Network Component Analysis we calculate the activities of 209 transcriptional regulators and correlate them with metabolites. This approach captures, for instance, the in vivo kinetics of CRP regulation by cyclic-AMP. By testing correlations between all pairs of transcription factors and metabolites, we predict putative effectors of 71 transcription factors, and validate five interactions in vitro. These results show that combining transcriptomics and metabolomics generates hypotheses about metabolism-transcription interactions that drive transitions between physiological states.

Interactions between metabolites and transcription factors are known to control gene expression but analyzing these events at genome-scale is challenging. Here, the authors integrate dynamic metabolome and transcriptome data from E.coli to predict regulatory metabolite-transcription factor interactions.

Development of a novel strategy for robust synthetic bacterial promoters based on a stepwise evolution targeting the spacer region of the core promoter in Bacillus subtilis

Background

Promoter evolution by synthetic promoter library (SPL) is a powerful approach to development of functional synthetic promoters to synthetic biology. However, it requires much tedious and time-consuming screenings because of the plethora of different variants in SPL. Actually, a large proportion of mutants in the SPL are significantly lower in strength, which contributes only to fabrication of a promoter library with a continuum of strength. Thus, to effectively obtain the evolved synthetic promoter exhibiting higher strength, it is essential to develop novel strategies to construct mutant library targeting the pivotal region rather than the arbitrary region of the template promoter. In this study, a strategy termed stepwise evolution targeting the spacer of core promoter (SETarSCoP) was established in Bacillus subtilis to effectively evolve the strength of bacterial promoter.

Results

The native promoter, P_srfA, from B. subtilis, which exhibits higher strength than the strong promoter P43, was set as the parental template. According to the comparison of conservation of the spacer sequences between − 35 box and − 10 box among a set of strong and weak native promoter, it revealed that 7-bp sequence immediately upstream of the − 10 box featured in the regulation of promoter strength. Based on the conservative feature, two rounds of consecutive evolution were performed targeting the hot region of P_srfA. In the first round, a primary promoter mutation library (pPML) was constructed by mutagenesis targeting the 3-bp sequence immediately upstream of the − 10 box of the P_srfA. Subsequently, four evolved mutants from pPML were selected to construction of four secondary promoter mutation libraries (sPMLs) based on mutagenesis of the 4-bp sequence upstream of the first-round target. After the consecutive two-step evolution, the mutant P_BH4 was identified and verified to be a highly evolved synthetic promoter. The strength of P_BH4 was higher than P_srfA by approximately 3 times. Moreover, P_BH4 also exhibited broad suitability for different cargo proteins, such as β-glucuronidase and nattokinase. The proof-of-principle test showed that SETarSCoP successfully evolved both constitutive and inducible promoters.

Conclusion

Comparing with the commonly used SPL strategy, SETarSCoP facilitates the evolution process to obtain strength-evolved synthetic bacterial promoter through fabrication and screening of small-scale mutation libraries. This strategy will be a promising method to evolve diverse bacterial promoters to expand the toolbox for synthetic biology.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1148-3) contains supplementary material, which is available to authorized users.

Metabolism-Centric Trans-Omics

Two recent studies in Cell and Science demonstrate the reconstruction of global mechanistic networks and identification of regulatory principles from multi-omics data.

Differentiation of Vegetative Cells into Spores: a Kinetic Model Applied to Bacillus subtilis

Spore-forming bacteria are natural contaminants of food raw materials, and sporulation can occur in many environments from farm to fork. In order to characterize and to predict spore formation over time, we developed a model that describes both the kinetics of growth and the differentiation of vegetative cells into spores. The model is based on a classical growth model and enables description of the kinetics of sporulation with the addition of three parameters specific to sporulation. Two parameters are related to the probability of each vegetative cell to commit to sporulation and to form a spore, and the last one is related to the time needed to form a spore once the cell is committed to sporulation. The goodness of fit of this growth-sporulation model was assessed using growth-sporulation kinetics at various temperatures in laboratory medium or in whey for Bacillus subtilis, Bacillus cereus, and Bacillus licheniformis The model accurately describes the kinetics in these different conditions, with a mean error lower than 0.78 log₁₀ CFU/ml for the growth and 1.08 log₁₀ CFU/ml for the sporulation. The biological meaning of the parameters was validated with a derivative strain of Bacillus subtilis 168 which produces green fluorescent protein at the initiation of sporulation. This model provides physiological information on the spore formation and on the temporal abilities of vegetative cells to differentiate into spores and reveals the heterogeneity of spore formation during and after growth.IMPORTANCE The growth-sporulation model describes the progressive transition from vegetative cells to spores with sporulation parameters describing the sporulation potential of each vegetative cell. Consequently, the model constitutes an interesting tool to assess the sporulation potential of a bacterial population over time with accurate parameters such as the time needed to obtain one resistant spore and the probability of sporulation. Further, this model can be used to assess these data under various environmental conditions in order to better identify the conditions favorable for sporulation regarding the time to obtain the first spore and/or the concentrations of spores which could be reached during a food process.