Quantifying dynamic mechanisms of auto-regulation in Escherichia coli with synthetic promoter in response to varying external phosphate levels

Stringent Response of Cyanobacteria and Other Bacterioplankton during Different Stages of a Harmful Cyanobacterial Bloom

We conducted a field study to investigate the role of stringent response in cyanobacteria and coexisting bacterioplankton during nutrient-deprived periods at various stages of bloom in a freshwater lake (Utah Lake) for the first time. Using metagenomics and metatranscriptomics analyses, we examined the cyanobacterial ecology and expression of important functional genes related to stringent response, N and P metabolism, and regulation. Our findings mark a significant advancement in understanding the mechanisms by which toxic cyanobacteria survive and proliferate during nitrogen (N) and phosphorus (P) limitations. We successfully identified and analyzed the metagenome-assembled genomes (MAGs) of the dominant bloom-forming cyanobacteria, namely, Dolichospermum circinale, Aphanizomenon flos-aquae UKL13-PB, Planktothrix agardhii, and Microcystis aeruginosa. By mapping RNA-seq data to the coding sequences of the MAGs, we observed that these four prevalent cyanobacteria species activated multiple functions to adapt to the depletion of inorganic nutrients. During and after the blooms, the four dominant cyanobacteria species expressed high levels of transcripts related to toxin production, such as microcystins (mcy), anatoxins (ana), and cylindrospermopsins (cyr). Additionally, genes associated with polyphosphate (poly-P) storage and the stringent response alarmone (p)ppGpp synthesis/hydrolysis, including ppk, relA, and spoT, were highly activated in both cyanobacteria and bacterioplankton. Under N deficiency, the main N pathways shifted from denitrification and dissimilatory nitrate reduction in bacterioplankton toward N2-fixing and assimilatory nitrate reduction in certain cyanobacteria with a corresponding shift in the community composition. P deprivation triggered a stringent response mediated by spoT-dependent (p)ppGpp accumulation and activation of the Pho regulon in both cyanobacteria and bacterioplankton, facilitating inorganic and organic P uptake. The dominant cyanobacterial MAGs exhibited the presence of multiple alkaline phosphatase (APase) transcripts (e.g., phoA in Dolichospermum, phoX in Planktothrix, and Microcystis), suggesting their ability to synthesize and release APase enzymes to convert ambient organic P into bioavailable forms. Conversely, transcripts associated with bacterioplankton-dominated pathways like denitrification were low and did not align with the occurrence of intense cyanoHABs. The strong correlations observed among N, P, stringent response metabolisms and the succession of blooms caused by dominant cyanobacterial species provide evidence that the stringent response, induced by nutrient limitation, may activate unique N and P functions in toxin-producing cyanobacteria, thereby sustaining cyanoHABs.

Functional expansion of the natural inorganic phosphorus starvation response system in Escherichia coli

Phosphorus, an indispensable nutrient, plays an essential role in cell composition, metabolism, and signal transduction. When inorganic phosphorus (Pi) is scarce, the Pi starvation response in E. coli is activated to increase phosphorus acquisition and drive the cells into a non-growing state to reduce phosphorus consumption. In the six decades of research history, the initiation, output, and shutdown processes of the Pi starvation response have been extensively studied. Simultaneously, Pi starvation has been used in biosensor development, recombinant protein production, and natural product biosynthesis. In this review, we focus on the output process and the applications of the Pi starvation response that have not been summarized before. Meanwhile, based on the current status of mechanistic studies and applications, we propose practical strategies to develop the natural Pi starvation response into a multifunctional and standardized regulatory system in four aspects, including response threshold, temporal expression, intensity range, and bifunctional regulation, which will contribute to its broader application in more fields such as industrial production, medical analysis, and environmental protection.

Administration of the probiotic Lactiplantibacillus paraplantarum is effective in controlling hyperphosphatemia in 5/6 nephrectomy rat model

AIMS

Several studies have linked gut microbes to human diseases. Most of the mechanisms by which lactic acid bacteria have beneficial effects on the human body are related to immune modulation. Controlled studies of the ability of lactic acid bacteria to absorb phosphorus directly from the intestine and thereby control serum phosphorus level in in vivo uremic animal models are limited.

MATERIALS AND METHODS

We screened lactic acid bacteria living in Korean fermented foods to identify those that absorb the most phosphorus and noted Lactiplantibacillus paraplantarum KCCM 11826P. The mechanism through which better intracellular absorption of phosphorus occurs in this strain was studied using genomic DNA sequencing. After the strain was administered to 5/6 nephrectomized rats for 6 weeks, it was observed whether hyperphosphatemia had improved.

KEY FINDINGS

The L. paraplantarum KCCM 11826P strain has a polyP gene cluster; thus, it absorbs phosphorus better than other bacteria and can suppress strains that produce indole. Supplementing the diets of 5/6 nephrectomized rats with this L. paraplantarum strain significantly decreased serum phosphate level (by 22 %) and reduced blood indoxyl sulphate concentration (by 40 %) compared with vehicle treatment.

SIGNIFICANCE

These results suggest that Lactiplantibacillus preparations can be used for multiple purposes, such as the removal of phosphorus and uremic toxins from patients with chronic kidney disease (CKD). This study also demonstrates the novel concept of a probiotic phosphate binder.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

A portable library of phosphate-depletion based synthetic promoters for customable and automata control of gene expression in bacteria

Industrial biotechnology gene expression systems relay on constitutive promoters compromising cellular growth from the start of the bioprocess, or on inducible devices, which require manual addition of cognate inducers. To overcome this shortcoming, we engineered an automata regulatory system based on cell-stress mechanisms. Specifically, we engineered a synthetic and highly portable phosphate-depletion library of promoters inspired by bacterial PHO starvation system (Pliar promoters). Furthermore, we fully characterized 10 synthetic promoters within the background of two well-known bacterial workhorses such as E. coli W and P. putida KT2440. The promoters displayed an interesting host-dependent performance and a wide strength spectrum ranging from 0.4- to 1.3-fold when compared to the wild-type phosphatase alkaline promoter (PphoA). By comparing with available gene expression systems, we proved the suitability of this new library for the automata and effective decoupling of growth from production in P. putida. Growth phase-dependent expression of these promoters could therefore be activated by fine tuning the initial concentration of phosphate in the medium. Finally, the Pliar library was implemented in the SEVA platform in a ready-to-use mode allowing its broad use by the scientific community.

The inverse correlation between robustness and sensitivity to autoregulation in two-component systems

Two-component systems (TCS) are signal transduction systems in bacteria and many other organisms that relay the sensory signal to genetic components. TCS consist of two proteins: a histidine kinase and a response regulator that the histidine kinase activates. This seemingly simple machinery can generate complex regulatory dynamics that enables the level of gene expression that matches the input signal: many TCS response regulators act on their own genes as transcription factors, resulting in a positive autoregulation mechanism. This regulation, in return, modulates the transcription factor activity as a function of the input signal. Positive autoregulation does not necessarily result in positive feedback. Sensitivity to autoregulation is quantified as the output level amplification resulting from the positive autoregulation mechanism. Another structural property of these systems is formally characterized as "robustness": in a robust TCS, the output of the system is solely a function of the input signal. Thus, a robust TCS remains insensitive to fluctuations in the concentrations of its protein components and, this way, maintains the precision in the output transcription factor activity in response to input stimulus. In this paper, we show with a formal model that TCS operate on a spectrum of inverse correlation between robustness and sensitivity to autoregulation. Our model predicts that the modulation by positive autoregulation is a function of loss in TCS robustness, for example, by spontaneous dephosphorylation of the histidine kinase. Consequently, the loss in robustness provides a proportional modulation by positive autoregulation to widen the response range with a scaled amplification of the output. At the other end of the spectrum, in the presence of a strictly robust TCS machinery, amplification of the transcription factor activity by autoregulation is diminished. We show that our results are in agreement with published experimental results. Our results suggest that these TCS evolve to converge at a trade-off between robustness and positive autoregulation.

Stochastic Simulations as a Tool for Assessing Signal Fidelity in Gene Expression in Synthetic Promoter Design

Simple Summary

Synthetic biology is an emerging discipline, offering new perspectives in many industrial fields, from pharma and row-material production to renewable energy. Developing synthetic biology applications is often a lengthy and expensive process with extensive and tedious trial-and-error runs. Computational models can direct the engineering of biological circuits in a computer-aided design setting. By providing a virtual lab environment, in silico models of synthetic circuits can contribute to a quantitative understanding of the underlying molecular pathways before a wet-lab implementation. Here, we illustrate this notion from the point of view of signal fidelity and noise relationship. Noise in gene expression can undermine signal fidelity with implications on the well-functioning of the engineered organisms. For our analysis, we use a specific biological circuit that regulates the gene expression in bacterial inorganic phosphate economy. Applications that use this circuit include those in pollutant detection and wastewater treatment. We provide computational models with different levels of molecular detail as virtual labs. We show that inherent fluctuations in the gene expression machinery can be predicted via stochastic simulations to introduce control in the synthetic promoter design process. Our analysis suggests that noise in the system can be alleviated by strong synthetic promoters with slow unbinding rates. Overall, we provide a recipe for the computer-aided design of synthetic promoter libraries with specific signal to noise characteristics.

Abstract

The design and development of synthetic biology applications in a workflow often involve connecting modular components. Whereas computer-aided design tools are picking up in synthetic biology as in other areas of engineering, the methods for verifying the correct functioning of living technologies are still in their infancy. Especially, fine-tuning for the right promoter strength to match the design specifications is often a lengthy and expensive experimental process. In particular, the relationship between signal fidelity and noise in synthetic promoter design can be a key parameter that can affect the healthy functioning of the engineered organism. To this end, based on our previous work on synthetic promoters for the E. coli PhoBR two-component system, we make a case for using chemical reaction network models for computational verification of various promoter designs before a lab implementation. We provide an analysis of this system with extensive stochastic simulations at a single-cell level to assess the signal fidelity and noise relationship. We then show how quasi-steady-state analysis via ordinary differential equations can be used to navigate between models with different levels of detail. We compare stochastic simulations with our full and reduced models by using various metrics for assessing noise. Our analysis suggests that strong promoters with low unbinding rates can act as control tools for filtering out intrinsic noise in the PhoBR context. Our results confirm that even simpler models can be used to determine promoters with specific signal to noise characteristics.

Analysis of the characteristics of phosphine production by anaerobic digestion based on microbial community dynamics, metabolic pathways, and isolation of the phosphate-reducing strain

Although phosphine is ubiquitously present in anaerobic environments, little is known regarding the microbial community dynamics and metabolic pathways associated with phosphine formation in an anaerobic digestion system. This study investigated the production of phosphine in anaerobic digestion, with results indicating that phosphine production mainly occurred during logarithmic microbial growth. Dehydrogenase and hydrogen promoted the production of phosphine, with a maximum phosphine concentration of 300 mg/m³. The abundance of Ruminococcaceae and Escherichia was observed to promote phosphine generation. The analysis of metabolic pathways based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the MetaCyc pathway database revealed the highest relative abundance of replication and repair in genetic information processing; further, the cofactor, prosthetic group, electron carrier, and vitamin biosynthesis were observed to be closely related to phosphine formation. A phylogenetic tree was reconstructed based on the neighbor-joining method. The results indicated the clear evolutionary position of the isolated Pseudescherichia sp. SFM4 strain, adjacent to Escherichia, with a stable phosphate-reducing ability for a maximum phosphine concentration of 26 mg/m³. The response surface experiment indicated that the initial optimal conditions for phosphine production by SFM4 could be achieved with nitrogen, carbon, and phosphorus loads of 6.17, 300, and 10 mg/L, respectively, at pH 7.47. These results provide comprehensive insights into the dynamic changes in the microbial structure, isolated single bacterial strain, and metabolic pathways associated with phosphine formation. They also provide information on the molecular biology associated with phosphorus recycling.