Multiplexed in-situ mutagenesis driven by a dCas12a-based dual-function base editor.

Mutagenesis driving genetic diversity is vital for understanding and engineering biological systems. However, the lack of effective methods to generate in-situ mutagenesis in multiple genomic loci combinatorially limits the study of complex biological functions. Here, we design and construct MultiduBE, a dCas12a-based multiplexed dual-function base editor, in an all-in-one plasmid for performing combinatorial in-situ mutagenesis. Two synthetic effectors, duBE-1a and duBE-2b, are created by amalgamating the functionalities of cytosine deaminase (from hAPOBEC3A or hAID*Δ ), adenine deaminase (from TadA9), and crRNA array processing (from dCas12a). Furthermore, introducing the synthetic separator Sp4 minimizes interference in the crRNA array, thereby facilitating multiplexed in-situ mutagenesis in both Escherichia coli and Bacillus subtilis. Guided by the corresponding crRNA arrays, MultiduBE is successfully employed for cell physiology reprogramming and metabolic regulation. A novel mutation conferring streptomycin resistance has been identified in B. subtilis and incorporated into the mutant strains with multiple antibiotic resistance. Moreover, surfactin and riboflavin titers of the combinatorially mutant strains improved by 42% and 15-fold, respectively, compared with the control strains with single gene mutation. Overall, MultiduBE provides a convenient and efficient way to perform multiplexed in-situ mutagenesis.

CRISPR-dCas12a-mediated genetic circuit cascades for multiplexed pathway optimization.

The production efficiency of microbial cell factories is sometimes limited by the lack of effective methods to regulate multiple targets in a coordinated manner. Here taking the biosynthesis of glucosamine-6-phosphate (GlcN6P) in Bacillus subtilis as an example, a 'design-build-test-learn' framework was proposed to achieve efficient multiplexed optimization of metabolic pathways. A platform strain was built to carry biosensor signal-amplifying circuits and two genetic regulation circuits. Then, a synthetic CRISPR RNA array blend for boosting and leading (ScrABBLE) device was integrated into the platform strain, which generated 5,184 combinatorial assemblies targeting three genes. The best GlcN6P producer was screened and engineered for the synthesis of valuable pharmaceuticals N-acetylglucosamine and N-acetylmannosamine. The N-acetylglucosamine titer reached 183.9 g liter-1 in a 15-liter bioreactor. In addition, the potential generic application of the ScrABBLE device was also verified using three fluorescent proteins as a case study.

Enhancing glucaric acid production from myo-inositol in Escherichia coli by eliminating cell-to-cell variation.

Glucaric acid (GA) is a value-added chemical and can be used to manufacture food additives, anticancer drugs, and polymers. The non-genetic cell-to-cell variations in GA biosynthesis are naturally inherent, indicating the presence of both high- and low-performance cells in culture. Low-performance cells can lead to nutrient waste and inefficient production. Furthermore, myo-inositol oxygenase (MIOX) is a key rate-limiting enzyme with the problem of low stability and activity in GA production. Therefore, eliminating cell-to-cell variations and increasing MIOX stability can select high-performance cells and improve GA production. In this study, an in vivo GA bioselector was constructed based on GA biosensor and tetracycline efflux pump protein TetA to continuously select GA-efficient production strains. Additionally, the upper limit of the GA biosensor was improved to 40 g/L based on ribosome-binding site optimization, achieving efficient enrichment of GA high-performance cells. A small ubiquitin-like modifier (SUMO) enhanced MIOX stability and activity. Overall, we used the GA bioselector and SUMO-MIOX fusion in fed-batch GA production and achieved a 5.52-g/L titer in Escherichia coli, which was 17-fold higher than that of the original strain.IMPORTANCEGlucaric acid is a non-toxic valuable product that was mainly synthesized by chemical methods. Due to the problems of non-selectivity, inefficiency, and environmental pollution, GA biosynthesis has attracted significant attention. The non-genetic cell-to-cell variations and MIOX stability were both critical factors for GA production. In addition, the high detection limit of the GA biosensor was a key condition for performing high-throughput screening of GA-efficient production strains. To increase GA titer, this work eliminated the cell-to-cell variations by GA bioselector constructed based on GA biosensor and TetA, and improved the stability and activity of MIOX in the GA biosynthetic pathway through fusing the SUMO to MIOX. Finally, these approaches improved the GA production by 17-fold to 5.52 g/L at 65 h. This study represents a significant step toward the industrial application of GA biosynthetic pathways in E. coli.

Biosensor-Based Multigene Pathway Optimization for Enhancing the Production of Glycolate.

Glycolate is widely used in industry, especially in the fields of chemical cleaning, cosmetics, and medical materials, and has broad market prospects for the future. Recent advances in metabolic engineering and synthetic biology have significantly improved the titer and yield of glycolate. However, an expensive inducer was used in previous studies, which is not feasible for use in large-scale industrial fermentations. To constitutively biosynthesize glycolate, the expression level of each gene of the glycolate synthetic pathway needs to be systemically optimized. The main challenge of multigene pathway optimization is being able to select or screen the optimum strain from the randomly assembled library by an efficient high-throughput method within a short time. To overcome these challenges, we firstly established a glycolate-responsive biosensor and developed agar plate- and 48-well deep-well plate-scale high-throughput screening methods for the rapid screening of superior glycolate producers from a large library. A total of 22 gradient-strength promoter-5'-untranslated region (UTR) complexes were randomly cloned upstream of the genes of the glycolate synthetic pathway, generating a large random assembled library. After rounds of screening, the optimum strain was obtained from 6 × 105 transformants in a week, and it achieved a titer of 40.9 ± 3.7 g/liter glycolate in a 5-liter bioreactor. Furthermore, high expression levels of the enzymes YcdW and GltA were found to promote glycolate production, whereas AceA has no obvious impact on glycolate production. Overall, the glycolate biosensor-based pathway optimization strategy presented in this work provides a paradigm for other multigene pathway optimizations. IMPORTANCE The use of strong promoters, such as pTrc and T7, to control gene expression not only needs the addition of expensive inducers but also results in excessive protein expression that may result in unbalanced metabolic flux and the waste of cellular building blocks and energy. To balance the metabolic flux of glycolate biosynthesis, the expression level of each gene needs to be systemically optimized in a constitutive manner. However, the lack of high-throughput screening methods restricted glycolate synthetic pathway optimization. Our work firstly established a glycolate-response biosensor, and agar plate- and 48-well plate-scale high-throughput screening methods were then developed for the rapid screening of optimum pathways from a large library. Finally, we obtained a glycolate-producing strain with good biosynthetic performance, and the use of the expensive inducer isopropyl-ß-d-thiogalactopyranoside (IPTG) was avoided, which broadens our understanding of the mechanism of glycolate synthesis.

Dynamic control of the distribution of carbon flux between cell growth and butyrate biosynthesis in Escherichia coli.

Microbial cell factories offer an economic and environmentally friendly method for the biosynthesis of acetyl-CoA-derived chemicals. However, the static control of carbon flux can cause direct and indirect competition for acetyl-CoA between cell growth and chemical biosynthesis, limiting the efficiency of microbial cell factories. Herein, recombinase-based genetic circuits were developed to achieve the optimal distribution of acetyl-CoA between cell growth and butyrate biosynthesis. First, three dynamic devices-a turn-on switch, a turn-off switch, and a recombinase-based inverter (RBI)-were constructed based on Bxb1 recombinase. Then, the turn-on switch was used to dynamically control the butyrate biosynthetic pathway, which directly improved the consumption of acetyl-CoA. Next, the turn-off switch was applied to dynamically control cell growth, which indirectly enhanced the supply of acetyl-CoA. Finally, an RBI was adopted for the dynamic dual control of the distribution of acetyl-CoA between cell growth and butyrate biosynthesis. The final butyrate production rate was increased to 34 g/L, with a productivity of 0.405 g/L/h. The strategy described herein will pave the way for the development of high-performance microbial cell factories for the production of other desirable chemicals. KEY POINTS: • Competition for acetyl-CoA between cell growth and synthesis limits productivity. • Recombinase-based genetic circuits were developed to dynamic control of acetyl-CoA. • Optimal distribution of acetyl-CoA between cell growth and synthesis was achieved.

Rapid evolution of hyaluronan synthase to improve hyaluronan production and molecular mass in Bacillus subtilis.

OBJECTIVES: To improve the production and molecular mass of the glycosaminoglycan hyaluronan (HA) in Bacillus subtilis by engineering hyaluronan synthase (HAS) from Streptococcus zooepidemicus. RESULTS: By mutating regions within HAS intracellular domains, five positive variants exhibiting higher HA production (from 1.22 to 2.24 g l-1) and molecular mass values (from 1.20 to 1.36 × 106 Da) were constructed and characterized. Overexpression of the V5 variant and the genes tuaD and glmU increased HA production and molecular mass to 2.8 g l-1 and 2.4 × 106 Da, respectively. CONCLUSIONS: This study provides a novel strategy for improving HA production and its molecular mass.

Engineered CBEs based on Macaca fascicularis A3A with improved properties for precise genome editing.

Cytidine deaminase defines the properties of cytosine base editors (CBEs) for C-to-T conversion. Replacing the cytidine deaminase rat APOBEC1 (rA1) in CBEs with a human APOBEC3A (hA3A) improves CBE properties. However, the potential CBE application of macaque A3A orthologs remains undetermined. Our current study develops and evaluates engineered CBEs based on Macaca fascicularis A3A (mA3A). Here, we demonstrate that BE4-mA3A and its RNA-editing-derived variants exhibit improved CBE properties, except for DNA off-target activity, compared to BE3-rA1 and BE4-rA1. Unexpectedly, deleting Ser-Val-Arg (SVR) in BE4-mA3A dramatically reduces DNA and RNA off-target activities and improves editing accuracy, with on-target efficiency unaffected. In contrast, a chimeric BE4-hA3A-SVR+ shows editing efficiency increased by about 50%, with other properties unaffected. Our findings demonstrate that mA3A-based CBEs could provide prototype options with advantages over rA1- and hA3A-based CBEs for further optimization, highlighting the importance of the SVR motif in defining CBE intrinsic properties.

Highly Efficient Production of UDP-Glucose from Sucrose via the Semirational Engineering of Sucrose Synthase and a Cascade Route Design.

Nucleotide sugars are essential precursors for carbohydrate synthesis but are in scarce supply. Uridine diphosphate (UDP)-glucose is a core building block in nucleotide sugar preparation, making its efficient synthesis critical. Here, a process for producing valuable UDP-glucose and functional mannose from sucrose was established and improved via a semirational sucrose synthase (SuSy) design and the accurate D-mannose isomerase (MIase) cascade. Engineered SuSy exhibited enzyme activity 2.2-fold greater than that of the WT. The structural analysis identified a latch-hinge combination as the hotspot for enhancing enzyme activity. Coupling MIase, process optimization, and reaction kinetic analysis revealed that MIase addition during the high-speed UDP-glucose synthesis phase distinctly accelerated the entire process. The simultaneous triggering of enzyme modules halved the reaction time and significantly increased the UDP-glucose yield. A maximum UDP-glucose yield of 83%, space-time yield of 70 g/L/h, and mannose yield of 32% were achieved. This novel and efficient strategy for sucrose value-added exploitation has industrial promise.

Multivariate Evaluation of DNA Quality Differences in Different Preanalytical Procedures in Mouse Livers.

Successful histogenetic research relies on proper handling of tissue samples to maximize DNA quality. As the largest gland in the body, the liver is particularly sensitive to sample mishandling owing to its enzymatic and transcriptional activity. However, the impact of preanalytical procedures on the quality of extracted liver DNA remains poorly understood. In this study, we assessed the impact of extraction methods, duration of ex vivo liver ischemia, liver storage time, and temperature on extracted DNA quality. Comprehensive parameters such as DNA yields, purity, DNA integrity number, the percentage of double-stranded DNA (%dsDNA), and PCR amplification of the GAPDH gene fragment were assessed to identify the quality of extracted DNA. Our results revealed that these preanalytical processes had little effect on DIN values and PCR efficiency of GAPDH gene fragments for each sample, whereas the DNA yields, purity, and %dsDNAs varied widely across different processes. For liver DNA extraction, RNase is necessary to isolate "pure" DNA, and the presence of RNase could significantly increase the %dsDNA. In addition, significant increases in the yields, purity, and %dsDNA of extracted DNA were observed in the TissueLyser-processed livers compared with the mortar and pestle or shear cell disruption methods. Further investigation revealed that livers experiencing longer periods of ex vivo ischemia resulted in significantly compromised DNA yields, and to obtain sufficient DNA, the ex vivo liver ischemia should be limited to within 30 minutes. Moreover, compared with storage of livers at -80°C, storage of livers in the vapor phase of liquid nitrogen yielded a higher quality of the extracted DNA. Our findings exhibited significant implications for liver-derived DNA quality assessment and management.

Engineering an AI-based forward-reverse platform for the design of cross-ribosome binding sites of a transcription factor biosensor.

A cross-ribosome binding site (cRBS) adjusts the dynamic range of transcription factor-based biosensors (TFBs) by controlling protein expression and folding. The rational design of a cRBS with desired TFB dynamic range remains an important issue in TFB forward and reverse engineering. Here, we report a novel artificial intelligence (AI)-based forward-reverse engineering platform for TFB dynamic range prediction and de novo cRBS design with selected TFB dynamic ranges. The platform demonstrated superior in processing unbalanced minority-class datasets and was guided by sequence characteristics from trained cRBSs. The platform identified correlations between cRBSs and dynamic ranges to mimic bidirectional design between these factors based on Wasserstein generative adversarial network (GAN) with a gradient penalty (GP) (WGAN-GP) and balancing GAN with GP (BAGAN-GP). For forward and reverse engineering, the predictive accuracy was up to 98% and 82%, respectively. Collectively, we generated an AI-based method for the rational design of TFBs with desired dynamic ranges.

Accumulated precursors of specific GPI-anchored proteins upregulate GPI biosynthesis with ARV1.

We previously reported that glycosylphosphatidylinositol (GPI) biosynthesis is upregulated when endoplasmic reticulum-associated degradation (ERAD) is defective; however, the underlying mechanistic basis remains unclear. Based on a genome-wide CRISPR-Cas9 screen, we show that a widely expressed GPI-anchored protein CD55 precursor and ER-resident ARV1 are involved in upregulation of GPI biosynthesis under ERAD-deficient conditions. In cells defective in GPI transamidase, GPI-anchored protein precursors fail to obtain GPI, with the remaining uncleaved GPI-attachment signal at the C-termini. We show that ERAD deficiency causes accumulation of the CD55 precursor, which in turn upregulates GPI biosynthesis, where the GPI-attachment signal peptide is the active element. Among the 31 GPI-anchored proteins tested, only the GPI-attachment signal peptides of CD55, CD48, and PLET1 enhance GPI biosynthesis. ARV1 is prerequisite for the GPI upregulation by CD55 precursor. Our data indicate that GPI biosynthesis is balanced to need by ARV1 and precursors of specific GPI-anchored proteins.

Perturbation of intestinal stem cell homeostasis and radiation enteritis recovery via dietary titanium dioxide nanoparticles.

Small intestinal health and enteritis incidence are tightly coupled to the homeostasis of intestinal stem cells (ISCs), which are sensitive to dietary alterations. However, little is known about the impact of food additives on ISC pool. Here, we demonstrate that chronic exposure to low-dose TiO2 NPs, a commonly used food additive, significantly hampers primary human and mouse ISC-derived organoid formation and growth by specifically attenuating Wnt signal transduction. Mechanistically, TiO2 NPs alter the endocytic trafficking of the Wnt receptor LRP6 and prevent the nuclear entry of ß-catenin. Notably, dietary TiO2 NPs elicit modest chronic stress in healthy intestines and considerably impede the recovery of radiation enteritis by perturbing the homeostasis of ISCs in vivo. Our results identify a health concern of TiO2 NP exposure on ISC homeostasis and radiation enteritis recovery. These findings suggest extra precaution during the treatment of radiation enteritis and provide new insights into food additive-ISC interaction.

Creation of Architecturally Minimal Transcriptionally Activating Riboswitches Responsive to Theophylline Reveals an Unconventional Design Strategy.

Riboswitches are noncoding RNA switches that are largely utilized in bacteria and play a significant role in synthetic biology. Nonetheless, their natural counterparts possess lengthy sequences and intricate structures, posing challenges for their modular integration into complex gene circuits. Consequently, it is imperative to develop simplified synthetic riboswitches that can be effortlessly incorporated into gene circuits. The conventional approach to generate synthetic riboswitches entails tedious library construction and extensive screening, which frequently yields suboptimal performance. To overcome this obstacle, alternative methods are urgently needed. In this study, we created a novel approach to designing a diverse set of transcription-activating riboswitches that exhibit high performance and broad compatibility. The strategy involved starting with a synthetic theophylline RNA aptamer and designing an expression platform that forms a transcriptional terminator in its inactive state but switches to an antiterminator when it is activated. Several sequences were designed, constructed, and subjected to virtual screening, resulting in the identification of two transcription-activating riboswitches. These riboswitches were then engineered to reduce the basal leakage and increase the activation level through extending the hairpin region using a screened random sequence. These architecturally minimal synthetic riboswitches were highly adapted to different constitutive promoters in a modular manner, generating a differentially responsive output to theophylline. As a proof-of-principle, the synthetic riboswitches were applied to rewire a synthetic quorum-sensing circuit (QSC). The reprogrammed QSC successfully modulated the temporal responsive profile against the activation. This strategy is expected to expand the variety of high-performance riboswitches that are responsive to different ligands, thereby further facilitating the design of complex genetic circuits.

Model-driven design of synthetic N-terminal coding sequences for regulating gene expression in yeast and bacteria.

N-terminal coding sequences (NCSs) are key regulatory elements for fine-tuning gene expression during translation initiation-the rate-limiting step of translation. However, owing to the complex combinatory effects of NCS biophysical factors and endogenous regulation, designing NCSs remains challenging. In this study, a multi-view learning strategy for model-driven generation of synthetic NCSs for Saccharomyces cerevisiae and Bacillus subtilis are implemented, which are widely used in laboratories and industries. NCS libraries for S. cerevisiae and B. subtilis with nearly 150,000 cells were sorted. Next, model training was performed with NCS deep features extracted from DNA, codon, and amino acid sequences, as well as calculated features from the minimum free energy (MFE) and tRNA adaption index. Two models were separately developed for generating synthetic NCSs for both up- and down-regulating gene expression with accuracies higher than 65% for S. cerevisiae and B. subtilis. Synthetic NCSs were then applied to enhance bioproduction, yielding 1.48- and 1.71-fold production improvements of D-limonene by S. cerevisiae and ovalbumin by B. subtilis, respectively. This work provides model-driven design of synthetic NCSs as a toolbox for regulating gene expression in S. cerevisiae and B. subtilis. The machine learning-based modeling approach can be used for NCS design in other microorganisms.

Improper preanalytical processes on peripheral blood compromise RNA quality and skew the transcriptional readouts of mRNA and LncRNA.

Genetic and epigenetic reprogramming caused by disease states in other tissues is always systemically reflected in peripheral blood leukocytes (PBLs). Accurate transcriptional readouts of Messenger RNA (mRNA) and Long non-coding RNA (lncRNA) in peripheral blood leukocytes are fundamental for disease-related study, diagnosis and treatment. However, little is known about the impact of preanalytical variables on RNA quality and downstream messenger RNA and Long non-coding RNA readouts. In this study, we explored the impact of RNA extraction kits and timing of blood placement on peripheral blood leukocyte-derived RNA quality. A novel enhanced evaluation system including RNA yields, purity, RNA integrity number (RIN) values and ß-actin copies was employed to more sensitively identify RNA quality differences. The expression levels of informative mRNAs and Long non-coding RNAs in patients with chronic obstructive pulmonary disease (COPD) or triple-negative breast cancer (TNBC) were measured by Quantitative reverse transcription polymerase chain reaction (qRT-PCR) to investigate the impact of RNA quality on transcriptional readouts. Our results showed that the quality of RNA extracted by different kits varies greatly, and commercial kits should be evaluated and managed before batch RNA extraction. In addition, the quality of extracted RNA was highly correlated with the timing of blood placement, and the copy number of ß-actin was significantly decreased after leaving blood at RT over 12 h. More importantly, compromised RNA leads to skewed transcriptional readouts of informative mRNAs and Long non-coding RNAs in patients with chronic obstructive pulmonary disease or triple-negative breast cancer. These findings have significant implications for peripheral blood leukocyte-derived RNA quality management and suggest that quality control is necessary prior to the analysis of patient messenger RNA and Long non-coding RNA expression.

S100A2: A potential biomarker to differentiate malignant from tuberculous pleural effusion.

BACKGROUND: S100 calcium binding protein A2 (S100A2)-which has been testified to have an abnormal expression in non-small cell lung cancer (NSCLC)-is considered as an effective biomarker in the diagnosis and prognosis of this malignancy. In this study, we detected the S100A2 levels in pleural effusion, aiming to evaluate its potential value in differentiating malignant pleural effusion (MPE) from tuberculous pleural effusion (TPE). METHODS: We collected pleural effusion from 104 NSCLC patients with MPE and 96 tubercular pleurisy cases. Enzyme-linked immunosorbent assay (ELISA) was performed to measure the levels of S100A2 in these samples. Meanwhile, the serum S100A2 levels were also examined in same subjects. The data concerning the expression of those commonly-used markers, including CEA, CYFRA211 and NSE, were obtained from medical records. RESULTS: Like other classified biomarkers, S100A2 had an over-expression in both pleural effusion and sera of the NSCLC patients compared with controls (P = 0.000), though having a lower P value. Receiver operating characteristic (ROC) analysis showed that the levels of S100A2 in pleural effusion (PE) could distinguish MPE from tuberculous pleurisy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.887), and its diagnostic value in hydrothorax was obviously higher than in serum (AUC = 0.709). CONCLUSION: Our results indicate that levels of S100A2 are significantly elevated in MPE, and that S100A2 may serve as a diagnostic biomarker for NSCLC patients with MPE. In further studies, we will validate our findings with a larger sample population.

Data-Driven and in Silico-Assisted Design of Broad Host-Range Minimal Intrinsic Terminators Adapted for Bacteria.

Efficient transcription termination relying on intrinsic terminators is critical to maintain cell fitness by avoiding unwanted read-through in bacteria. Natural intrinsic terminator (NIT) typically appears in mRNA as a hairpin followed by approximately eight conserved uridines (U-tract) at the 3' terminus. Owing to their simple structure, small size, and protein independence, assorted NITs have been redesigned as robust tools to construct gene circuits. However, most NITs exert functions to adapt to their physiological requirements rather than the demand for building synthetic gene circuits, rendering uncertain working performance when they are constructed intact in synthetic gene circuits. Here, rather than modifying NITs, we established a data-driven and in silico-assisted (DISA) design framework to forward engineer minimal intrinsic terminators (MITs). By comprehensively analyzing 75 natural intrinsic terminators from Bacillus subtilis, we revealed that two pivotal features, the length of the U-tract and the thermodynamics of the terminator hairpin, were involved in the sequence-activity relationship (SAR) of termination efficiency (TE). As per the SAR, we leveraged DISA to fabricate an array of MITs composed of in silico-assisted designed minimal hairpins and fixed U-tracts. Most of these MITs exhibited high TE in diverse Gram-positive and Gram-negative bacteria. In contrast, the TEs of the NITs were highly varied in different hosts. Moreover, TEs of MITs were flexibly tuned over a wide range by modulating the length of the U-tract. Overall, these results demonstrate an efficient framework to forward design functional and broad host-range terminators independent of tedious and iterative screening of mutagenesis libraries of natural terminators.

Reprogramming microbial populations using a programmed lysis system to improve chemical production.

Microbial populations are a promising model for achieving microbial cooperation to produce valuable chemicals. However, regulating the phenotypic structure of microbial populations remains challenging. In this study, a programmed lysis system (PLS) is developed to reprogram microbial cooperation to enhance chemical production. First, a colicin M -based lysis unit is constructed to lyse Escherichia coli. Then, a programmed switch, based on proteases, is designed to regulate the effective lysis unit time. Next, a PLS is constructed for chemical production by combining the lysis unit with a programmed switch. As a result, poly (lactate-co-3-hydroxybutyrate) production is switched from PLH synthesis to PLH release, and the content of free PLH is increased by 283%. Furthermore, butyrate production with E. coli consortia is switched from E. coli BUT003 to E. coli BUT004, thereby increasing butyrate production to 41.61 g/L. These results indicate the applicability of engineered microbial populations for improving the metabolic division of labor to increase the efficiency of microbial cell factories.

Realization of Robust and Precise Regulation of Gene Expression by Multiple Sigma Recognizable Artificial Promoters.

Precise regulation of gene expression is fundamental for tailor-made gene circuit design in synthetic biology. Current strategies for this type of development are mainly based on directed evolution beginning with a native promoter template. The performances of engineered promoters are usually limited by the growth phase because only one promoter is recognized by one type of sigma factor (σ). Here, we constructed multiple-σ recognizable artificial hybrid promoters (AHPs) composed of tandems of dual and triple natural minimal promoters (NMPs). These NMPs, which use σA, σH and σW, had stable functions in different growth phases. The functions of these NMPs resulted from an effect called transcription compensation, in which AHPs sequentially use one type of σ in the corresponding growth phase. The strength of the AHPs was influenced by the combinatorial order of each NMP and the length of the spacers between the NMPs. More importantly, the output of the precise regulation was achieved by equipping AHPs with synthetic ribosome binding sites and by redesigning them for induced systems. This strategy might offer promising applications to rationally design robust synthetic promoters in diverse chassis to spur the construction of more complex gene circuits, which will further the development of synthetic biology.

Dynamic urinary proteomic analysis in a Walker 256 intracerebral tumor model.

BACKGROUND: Patients with primary and metastatic brain cancer have an extremely poor prognosis, mostly due to the late diagnosis of disease. Urine, which lacks homeostatic mechanisms, is an ideal biomarker source that accumulates early and highly sensitive changes to provide information about the early stage of disease. METHODS: A rat model mimicking the local tumor growth process in the brain was established with intracerebral Walker 256 (W256) cell injection. Urine samples were collected on days 3, 5, and 8 after injection, and then analyzed by liquid chromatography coupled with tandem mass spectrometry. RESULTS: In the intracerebral W256 model, no obvious clinical manifestations or abnormal magnetic resonance imaging (MRI) signals were found on days 3 or 5; at these time points, 9 proteins were changed significantly in the urine of all eight tumor rats. On day 8, when tumors were detected by MRI, 25 differential proteins were identified, including 10 that have been reported to be closely related to brain metastasis or primary tumors. The differential urinary proteome was compared with those from the subcutaneous W256 model and the intracerebral C6 model. Few differential proteins overlapped, and specific differential protein patterns were observed among the three models. CONCLUSIONS: These findings demonstrate that early changes in the urine proteome can be detected in the intracerebral W256 model. The urinary proteome can reflect the difference when tumor cells with different growth characteristics are inoculated into the brain and when identical tumor cells are inoculated into different areas, specifically, the subcutis and the brain.