Pulmonary Tuberculosis Notification Rate Within Shenzhen, China, 2010-2019: Spatial-Temporal Analysis.

BACKGROUND: Pulmonary tuberculosis (PTB) is a chronic communicable disease of major public health and social concern. Although spatial-temporal analysis has been widely used to describe distribution characteristics and transmission patterns, few studies have revealed the changes in the small-scale clustering of PTB at the street level. OBJECTIVE: The aim of this study was to analyze the temporal and spatial distribution characteristics and clusters of PTB at the street level in the Shenzhen municipality of China to provide a reference for PTB prevention and control. METHODS: Data of reported PTB cases in Shenzhen from January 2010 to December 2019 were extracted from the China Information System for Disease Control and Prevention to describe the epidemiological characteristics. Time-series, spatial-autocorrelation, and spatial-temporal scanning analyses were performed to identify the spatial and temporal patterns and high-risk areas at the street level. RESULTS: A total of 58,122 PTB cases from 2010 to 2019 were notified in Shenzhen. The annual notification rate of PTB decreased significantly from 64.97 per 100,000 population in 2010 to 43.43 per 100,000 population in 2019. PTB cases exhibited seasonal variations with peaks in late spring and summer each year. The PTB notification rate was nonrandomly distributed and spatially clustered with a Moran I value of 0.134 (P=.02). One most-likely cluster and 10 secondary clusters were detected, and the most-likely clustering area was centered at Nanshan Street of Nanshan District covering 6 streets, with the clustering time spanning from January 2010 to November 2012. CONCLUSIONS: This study identified seasonal patterns and spatial-temporal clusters of PTB cases at the street level in the Shenzhen municipality of China. Resources should be prioritized to the identified high-risk areas for PTB prevention and control.

Global rewiring of lipid metabolism to produce carotenoid by deleting the transcription factor genes ino2/ino4 in Saccharomyces cerevisiae.

The transcription factor complex INO2 and INO4 in Saccharomyces cerevisiae plays a vital role in lipid biosynthesis by activating multiple genes in the biosynthetic pathways of phospholipid, fatty acid, and sterol. Previous studies have reported conflicting results regarding the effects of ino2 and ino4 gene expression levels on target chemicals. Therefore, this study aimed to examine the influence of different ino2 and ino4 expression levels on carotenoid production (e.g., lycopene), which shares a common precursor, acetyl-CoA, with lipid metabolism. Surprisingly, 2.6- and 1.8-fold increase in lycopene yield in the ino2 and ino4 deletion strains were found, respectively. In contrast, ino2 overexpression did not promote lycopene accumulation. Additionally, there was a decrease in intracellular free fatty acids in the ino2 deletion strain. Comparative transcriptome analysis revealed a significant downregulation of genes related to lipid biosynthesis in the ino2 deletion strain. To our knowledge, this is the first report showing that deletion of transcription factor genes ino2 and ino4 can facilitate lycopene accumulation. These findings hold significant implications for the development of metabolically engineered S. cerevisiae with enhanced carotenoid production.

Design of a dual-responding genetic circuit for high-throughput identification of L-threonine-overproducing Escherichia coli.

L-threonine is a crucial amino acid that is extensively employed in the realms of food, animal feed and pharmaceuticals. Unfortunately, the lack of an appropriate biosensor has hindered the establishment of a robust high-throughput screening (HTS) system for the identification of the desired strains from random mutants. In this study, a dual-responding genetic circuit that capitalizes on the L-threonine inducer-like effect, the L-threonine riboswitch, and a signal amplification system was designed for the purpose of screening L-threonine overproducers. This platform effectively enhanced the performance of the enzyme and facilitated the identification of high L-threonine-producing strains from a random mutant library. Consequently, pathway optimization and directed evolution of the key enzyme enhanced L-threonine production by 4 and 7-fold, respectively. These results demonstrate the potential of biosensor design for dynamic metabolite detection and offer a promising tool for HTS and metabolic regulation for the development of L-threonine-hyperproducing strains.

Time-trend analysis of tuberculosis diagnosis in Shenzhen, China between 2011 and 2020.

Objective: To describe the trend of tuberculosis (TB) diagnosis in the migrant city Shenzhen, China, and analyze the risk factors of diagnosis delays. Methods: Demographic and clinical information of TB patients from 2011 to 2020 in Shenzhen were extracted. A bundle of measures to enhance TB diagnosis had been implemented since late 2017. We calculated the proportions of patients who underwent a patient delay (>30 days from syndrome onset to first care-seeking) or a hospital delay (>4 days from first care-seeking to TB diagnosis). Multivariable logistic regression was used to analyze the risk factors of diagnosis delays. Results: During the study period, 43,846 patients with active pulmonary TB were diagnosed and registered in Shenzhen. On average, the bacteriological positivity rate of the patients was 54.9%, and this increased from 38.6% in 2017 to 74.2% in 2020. Overall, 30.3 and 31.1% of patients had a patient delay or a hospital delay, respectively. Molecular testing significantly increased bacteriological positivity and decreased the risk of hospital delay. People >35 years old, the unemployed, and residents had a higher risk of delays in both patient care-seeking and hospital diagnosis than younger people, workers, or migrants. Compared with passive case-finding, active case-finding significantly decreased the risk of patient delay by 5.47 (4.85-6.19) times. Conclusion: The bacteriological positivity rate of TB patients in Shenzhen increased significantly but the diagnosis delays were still serious, which may need more attention when active case-finding in risk populations and optimization of molecular testing.

Engineering a Balanced Acetyl Coenzyme A Metabolism in Saccharomyces cerevisiae for Lycopene Production through Rational and Evolutionary Engineering.

Saccharomyces cerevisiae is increasingly being used for the production of chemicals derived from acetyl coenzyme A (acetyl-CoA). However, the inadequate supply of cytosolic acetyl-CoA often leads to low yields. Here, we developed a novel strategy for balancing acetyl-CoA metabolism and increasing the amount of the downstream product. First, the combination of acetaldehyde dehydrogenase (eutE) and acetoacetyl-CoA thiolase (AtoB) was optimized to redirect the acetyl-CoA flux toward the target pathway, with a 21-fold improvement in mevalonic acid production. Second, pathway engineering and evolutionary engineering were conducted to attenuate the growth deficiency, and a 10-fold improvement of the maximum productivity was achieved. Third, acetyl-CoA carboxylase (ACC1) was dynamically downregulated as the complementary acetyl-CoA pathway, and the yield was improved more than twofold. Fourth, the most efficient and complementary acetyl-CoA pathways were combined, and the final strain produced 68 mg/g CDW lycopene, which was among the highest yields reported in S. cerevisiae. This study demonstrates a new method of producing lycopene products by regulating acetyl-CoA metabolism.