DataSheet1_Characterization and engineering of plastic-degrading polyesterases jmPE13 and jmPE14 from Pseudomonas bacterium.docx

Polyester plastics are widely used in daily life, but also cause a large amount of waste. Degradation by microbial enzymes is the most promising way for the biobased upcycling of the wastes. However, there is still a shortage of high-performance enzymes, and more efficient polyester hydrolases need to be developed. Here we identified two polyester hydrolases, jmPE13 and jmPE14, from a previously isolated strain Pseudomonas sp. JM16B3. The proteins were recombinantly expressed and purified in E. coli, and their enzymatic properties were characterized. JmPE13 and jmPE14 showed hydrolytic activity towards polyethylene terephthalate (PET) and Poly (butylene adipate-co-terephthalate) (PBAT) at medium temperatures. The enzyme activity and stability of jmPE13 were further improved to 3- and 1.5-fold, respectively, by rational design. The results of our research can be helpful for further engineering of more efficient polyester plastic hydrolases and their industrial applications.</p

Facile and Rapid Generation of Large-Scale Microcollagen Gel Array for Long-Term Single-Cell 3D Culture and Cell Proliferation Heterogeneity Analysis

Microfabricated devices are suitable for single-cell analysis due to their high throughput, compatible dimensions and controllable microenvironment. However, existing devices for single-cell culture and analysis encounter some limitations, such as nutrient depletion, random cell migration and complicated fluid shear influence. Moreover, most of the single-cell culture and analysis devices are based on 2D cell culture conditions, even though 3D cell culture methods have been demonstrated to better mimic the real cell microenvironment in vivo. To solve these problems, herein we develop a microcollagen gel array (μCGA) based approach for high-throughput long-term single-cell culture and single-cell analysis under 3D culture conditions. Type-I collagen, a well-established 3D cell culture medium, was used as the scaffold for 3D cell growth. A 2 × 2 cm PDMS chip with 10 000 μCGA units was fabricated to encapsulate thousands of single cells in less than 15 min. Single cells were able to be confined and survive in μCGA units for more than 1 month. The capability of large-scale and long-term single-cell 3D culture under open culture conditions allows us to study cellular proliferation heterogeneity and drug cytotoxicity at the single-cell level. Compared with existing devices for single-cell analysis, μCGA solves the problems of nutrient depletion and random cellular migration, avoids the influence of complicated fluid shear, and mimics the real 3D growth environment in vivo, thereby providing a feasible 3D long-term single-cell culture method for single-cell analysis and drug screening

Effectiveness of Nature Reserve System for Conserving Tropical Forests: A Statistical Evaluation of Hainan Island, China

<div><p>Evaluating the effectiveness of existing nature reserve systems for the conservation of tropical forests is an urgent task to save the remaining biodiversity. Here, we tested the effectiveness of the reserve system on Hainan Island by conducting a three-way comparison of changes in forest area in locations within the reserves, adjacent to the reserves, and far outside of the reserves. We used a general linear model to control for the effects of covariates (historical forest area, elevation, slope, and distance to nearest roads), which may also be correlated with the changes in forest area, to better explain the effectiveness of the reserve system. From 2000 to 2010, the forest area inside Hainan’s nature reserve system showed an increase while adjacent unprotected areas and the wider, unprotected landscape both experienced deforestation. However, the simple inside-outside comparisons may overestimate the protective effect of the reserve system. Most nature reserves (>60%) showed increasing fragmentation. And the risk of rapid deforestation remained high at low elevations, where remaining forests tend to be easily logged and converted to commercial plantations. Future conservation efforts should pay more attention to those sites with less challenging environmental conditions.</p> </div

Mean forest area.

<p>Comparison of mean forest area (ha) between 2000 and 2010 across different sampling plots of 100 ha on Hainan Island (Group 1: inside nature reserves, Group 2: in adjacent 10-km unprotected areas, Group 3: in the wider unprotected landscape).</p>a<p>Wilcoxon Signed Ranks Test (2-tailed).</p

Table1_Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis.XLS

Background:Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis.Methods:Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP).Results:The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816.Conclusion:Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.</p

Nature reserve system of Hainan Island.

<p>The nature reserve system, adjacent unprotected areas (surrounding lands within 10 km of the nature reserve boundaries) and wider unprotected landscape (more than 10 km away from the nature reserve boundaries) overlaid with natural forest cover in 2010 and digital elevation model (DEM) of Hainan Island, China.</p

Changes in tropical forests across Hainan Island.

<p>Changes in the area of tropical forests inside nature reserves, in adjacent unprotected areas (within 10 km of nature reserves’ boundaries), and in the wider unprotected landscapes (>10 km from nature reserves’ boundaries) in Hainan, China, from 2000 to 2010.</p

Table2_Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis.DOC

Background:Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis.Methods:Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP).Results:The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816.Conclusion:Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.</p

Table3_Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis.DOC

Background:Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis.Methods:Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP).Results:The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816.Conclusion:Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.</p

The prevalence of IL28B genotypes with response to PEG-IFN-α/RBV treatment.

<p>The prevalence of IL28B genotypes with response to PEG-IFN-α/RBV treatment.</p