Microbial degradation and valorization of poly(ethylene terephthalate) (PET) monomers.

The polyethylene terephthalate (PET) is one of the major plastics with a huge annual production. Alongside with its mass production and wide applications, PET pollution is threatening and damaging the environment and human health. Although mechanical or chemical methods can deal with PET, the process suffers from high cost and the hydrolyzed monomers will cause secondary pollution. Discovery of plastic-degrading microbes and the corresponding enzymes emerges new hope to cope with this issue. Combined with synthetic biology and metabolic engineering, microbial cell factories not only provide a promising approach to degrade PET, but also enable the conversion of its monomers, ethylene glycol (EG) and terephthalic acid (TPA), into value-added compounds. In this way, PET wastes can be handled in environment-friendly and more potentially cost-effective processes. While PET hydrolases have been extensively reviewed, this review focuses on the microbes and metabolic pathways for the degradation of PET monomers. In addition, recent advances in the biotransformation of TPA and EG into value-added compounds are discussed in detail.

[Effect of three kinds of drinking water on learning and memory and hippocampal neurotransmitter of mice].

OBJECTIVE: To explore the effect of three kinds of drinking water on learning and memory and hippocampal neurotransmitter of mice. METHODS: Water quality parameters, including total dissolved solid( TDS), total hardness, oxygen consumed( OC), sodium, potassium, calcium, magnesium and metasilicic acid, were measured for pure water, tap water and natural mineral water. A total of 60 ICR mice( half male and half female) were randomly divided into three groups and fed with pure water( control group), tap water and mineral water for 90 days. After learning-memory abilities were detected with Morris water maze and passive avoidance test, mice were killed and hippocampi were removed immediately to measure contents of acetylcholine( Ach), nitric oxide( NO), glutamic acid( Glu) and gamma-aminobutyric acid( GABA) and activities of acetylcholinesterase( ACh E), choline acetyltransferase( Ch AT) and total nitric oxide synthase( T-NOS). RESULTS: Water quality parameters were higher in tap water and natural mineral water than in pure water. On the first day of place navigation test, the escape latency of tap water group [( 69. 15 ± 50. 87) s]was obviously shorter than that of pure water group [( 86. 07 ± 44. 03) s]( P < 0. 05), and mice in tap water group chose effect strategies( 51. 25%) more frequently compared to control mice( 30%)( P <0. 05). In the probe trial, the swimming time of the targeted quadrant was significantly longer in tap water group [( 28. 44 ± 10. 17) s] or mineral water group [( 28. 81 ±12. 43) s] than in pure water group [( 19. 84 ± 9. 59) s ]( P < 0. 05). In passive avoidance test, the training latency and testing latency were significantly longer in tap water group [( 60. 27 ± 57. 84) and( 209. 54 ± 121. 41) s] or mineral water group[( 58. 12 ± 42. 52) and( 271. 40 ± 90. 44) s]than in pure water group [( 10. 99 ± 9. 40)and( 72. 77 ± 67. 51) s ]( P < 0. 05), as the frequency of electric shock and the percentage of animals showing errors in tap water group [( 0. 90 ± 0. 88) times and 50%]or mineral water group [( 0. 10 ± 0. 32) times and 20%]were obviously less than those in pure water group [( 5. 00 ± 4. 62) times and 90% ]( P < 0. 05). Compared with pure water group [( 8. 53 ± 2. 12) µg / mg prot and( 0. 94 ± 0. 49) U / mg prot], a significant increase of Ach concentration and a significant decrease of ACh E activity were observed in tap water group [( 11. 18 ± 3. 46) µg / mg prot and( 0. 41 ± 0. 21) U / mg prot]or mineral water group [( 12. 91 ± 3. 91) µg / mg prot and( 0. 54 ± 0. 28) U / mg prot]( P < 0. 05). CONCLUSION: Compared with pure water, long-term drinking tap water or mineral water is more beneficial to learning and memory of mice, and it may be associated with a higher content of hippocampal Ach.

Establishing CRISPRi for Programmable Gene Repression and Genome Evolution in Cupriavidus necator.

Cupriavidus necator H16 is a "Knallgas" bacterium with the ability to utilize various carbon sources and has been employed as a versatile microbial cell factory to produce a wide range of value-added compounds. However, limited genome engineering, especially gene regulation methods, has constrained its full potential as a microbial production platform. The advent of CRISPR/Cas9 technology has shown promise in addressing this limitation. Here, we developed an optimized CRISPR interference (CRISPRi) system for gene repression in C. necator by expressing a codon-optimized deactivated Cas9 (dCas9) and appropriate single guide RNAs (sgRNAs). CRISPRi was proven to be a programmable and controllable tool and could successfully repress both exogenous and endogenous genes. As a case study, we decreased the accumulation of polyhydroxyalkanoate (PHB) via CRISPRi and rewired the carbon fluxes to the synthesis of lycopene. Additionally, by disturbing the expression of DNA mismatch repair gene mutS with CRISPRi, we established CRISPRi-Mutator for genome evolution, rapidly generating mutant strains with enhanced hydrogen peroxide tolerance and robustness in microbial electrosynthesis (MES) system. Our work provides an efficient CRISPRi toolkit for advanced genetic manipulation and optimization of C. necator cell factories for diverse biotechnology applications.

Radiomic nomogram for predicting high-risk cytogenetic status in multiple myeloma based on fat-suppressed T2-weighted magnetic resonance imaging.

Rationale and Objectives: Radiomics has demonstrated potential in predicting the cytogenetic status of multiple myeloma (MM). However, the role of single-sequence radiomic nomograms in predicting the high-risk cytogenetic (HRC) status of MM remains underexplored. This study aims to develop and validate radiomic nomograms based on fat-suppressed T2-weighted images (T2WI-FS) for predicting MM's HRC status, facilitating pre-treatment decision-making and prognostic assessment. Materials and methods: A cohort of 159 MM patients was included, comprising 71 HRC and 88 non-HRC cases. Regions of interest within the most significant tumor lesions on T2WI-FS images were manually delineated, yielding 1688 features. Fourteen radiomic features were selected using 10-fold cross-validation, employing methods such as variance thresholds, Student's t-test, redundancy analysis, and least absolute shrinkage and selection operator (LASSO). Logistic regression was utilized to develop three prediction models: a clinical model (model 1), a T2WI-FS radiomic model (model 2), and a combined clinical-radiomic model (model 3). Receiver operating characteristic (ROC) curves evaluated and compared the diagnostic performance of these models. Kaplan-Meier survival analysis and log-rank tests assessed the prognostic value of the radiomic nomograms. Results: Models 2 and 3 demonstrated significantly greater diagnostic efficacy compared to model 1 (p < 0.05). The areas under the ROC curve for models 1, 2, and 3 were as follows: training set-0.650, 0.832, and 0.846; validation set-0.702, 0.730, and 0.757, respectively. Kaplan-Meier survival analysis indicated comparable prognostic values between the radiomic nomogram and MM cytogenetic status, with log-rank test results (p < 0.05) and concordance indices of 0.651 and 0.659, respectively; z-score test results were not statistically significant (p = 0.153). Additionally, Kaplan-Meier analysis revealed that patients in the non-HRC group, low-RS group, and aged ≤ 60 years exhibited the longest overall survival, while those in the HRC group, high-RS group, and aged > 60 years demonstrated the shortest overall survival (p = 0.004, Log-rank test). Conclusions: Radiomic nomograms are capable of predicting the HRC status in MM. The cytogenetic status, radiomics model Rad score, and age collectively influence the overall survival of MM patients. These factors potentially contribute to pre-treatment clinical decision-making and prognostic assessment.

Diagnostic Value of Dual-Energy CT Virtual Non-Calcium and Rho/Z Images for Bone Marrow Infiltration in Primary Malignant Bone Tumors.

RATIONALE AND OBJECTIVES: We investigated the diagnostic performance of dual-energy CT (DECT) virtual non-calcium (VNCa) and Rho/Z images for bone marrow infiltration of primary malignant bone tumors (PMBTs). MATERIALS AND METHODS: We retrospectively analyzed 65 patients with PMBT who underwent DECT and MRI within 2 weeks. DECT was used to evaluate the presence and extent of marrow involvement surrounding PMBTs using the SCT, VNCa, and Rho/Z images. MRI was used as the reference standard for measurements. CT values of normal and involved bone marrow areas were measured on VNCa images, and Zeff values were measured on Rho/Z images. The statistical methods used were the 2*C chi-square test, ANOVA test, paired samples t test, and diagnostic performance of the different variables were evaluated using receiver operating characteristic curves. RESULTS: VNCa and Rho/Z images showed higher accuracy (91%, 92% vs. 67%) and sensitivity (90%, 92% vs. 69%) than SCT images for diagnosing bone marrow infiltration in patients with PMBT. The maximum longitudinal diameter of tumor involvement measurements was statistically different between VNCa and SCT, Rho/Z and SCT, MRI, and SCT (all p < 0.05, p = 0.047, p = 0.049, and p = 0.023, respectively). The maximum transverse diameter was statistically significant between SCT and MRI, VNCa and MRI, Rho/Z and MRI (all p < 0.05, and p = 0.015, and p = 0.044, and p = 0.047, respectively). The HU or Zeff values based on the area of interest of VNCa and Rho/Z images differed significantly between the normal and infiltrated bone marrow area (p < 0.001). Receiver operating characteristic curve analysis revealed area under the curves of 0.995 and 0.988, respectively, with cut-off values of -31.57 HU and 7.8, and the sensitivity of both was 96.9%. CONCLUSION: DECT-VNCa and Rho/Z images have good diagnostic value when evaluating bone marrow infiltration in PMBTs.

Recent advances in the discovery, characterization, and engineering of poly(ethylene terephthalate) (PET) hydrolases.

Poly(ethylene terephthalate) (PET) is a class of polyester plastic composed of terephthalic acid (TPA) and ethylene glycol (EG). The accumulation of large amount of PET waste has resulted in severe environmental and health problems. Microbial polyester hydrolases with the ability to degrade PET provide an economy- and environment-friendly approach for the treatment of PET waste. In recent years, many PET hydrolases have been discovered and characterized from various microorganisms and engineered for better performance under practical application conditions. Here, recent progress in the discovery, characterization, and enzymatic mechanism elucidation of PET hydrolases is firstly reviewed. Then, structure-guided protein engineering of PET hydrolases with increased enzymatic activities, expanded substrate specificity, as well as improved protein stability is summarized. In addition, strategies for efficient expression of recombinant PET hydrolases, including secretory expression and cell-surface display, are briefly introduced. This review is concluded with future perspectives in biodegradation and subsequent biotransformation of PET wastes to produce value-added compounds.

Synthetic biology toolkit for engineering Cupriviadus necator H16 as a platform for CO2 valorization.

BACKGROUND: CO2 valorization is one of the effective methods to solve current environmental and energy problems, in which microbial electrosynthesis (MES) system has proved feasible and efficient. Cupriviadus necator (Ralstonia eutropha) H16, a model chemolithoautotroph, is a microbe of choice for CO2 conversion, especially with the ability to be employed in MES due to the presence of genes encoding [NiFe]-hydrogenases and all the Calvin-Benson-Basham cycle enzymes. The CO2 valorization strategy will make sense because the required hydrogen can be produced from renewable electricity independently of fossil fuels. MAIN BODY: In this review, synthetic biology toolkit for C. necator H16, including genetic engineering vectors, heterologous gene expression elements, platform strain and genome engineering, and transformation strategies, is firstly summarized. Then, the review discusses how to apply these tools to make C. necator H16 an efficient cell factory for converting CO2 to value-added products, with the examples of alcohols, fatty acids, and terpenoids. The review is concluded with the limitation of current genetic tools and perspectives on the development of more efficient and convenient methods as well as the extensive applications of C. necator H16. CONCLUSIONS: Great progress has been made on genetic engineering toolkit and synthetic biology applications of C. necator H16. Nevertheless, more efforts are expected in the near future to engineer C. necator H16 as efficient cell factories for the conversion of CO2 to value-added products.

Random Base Editing for Genome Evolution in Saccharomyces cerevisiae.

Because of the limited understanding of cellular metabolism and regulatory networks, the rational engineering of complex industrial traits remains a grand challenge for the construction of microbial cell factories. Thus the development of simple, efficient, and programmable genome evolution techniques is still in high demanded for industrial biotechnology. In the present study, we established a random base editing (rBE) system for genome evolution in Saccharomyces cerevisiae. By fusing an unspecific single-stranded DNA (ssDNA)-binding protein to a cytidine deaminase, rBE introduced C to T mutations in a genome-wide manner. Specifically, we chose DNA-replication-related proteins, including replication factor A (RFA1, RFA2, and RFA3), DNA primase (PRI1), DNA helicase A (HCS1), and topoisomerase I (TOP1), to mediate the deamination of genomic ssDNA. As a proof of concept, we roughly estimated the rBE-mediated yeast genome mutation rate using the CAN1 mutation/canavanine resistance reporter system. We then evaluated the performance of these rBEs in improving the resistance against isobutanol and acetate and increasing the production of ß-carotene. Finally, we employed the optimal rBE for the continuous genome evolution of a yeast cell factory resistant to 9% isobutanol. Owing to the conservation of DNA replication mechanisms, rBE is generally applicable and theoretically can be adopted for the continuous genome evolution of all organisms.