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.

Implications for TB control among migrants in large cities in China: A prospective population-based genomic epidemiology study in Shenzhen.

Internal migrants are a challenge for TB control in large Chinese cities and understanding this epidemiology is crucial for designing effective control and prevention strategies. We conducted a prospective genomic epidemiological study of culture-positive TB patients diagnosed between June 1, 2018 and May 31, 2021 in the Longhua District of Shenzhen. Treatment status was obtained from local and national TB registries and all isolates were sequenced. Genomic clusters were defined as strains differing by ≤12 SNPs. Risk factors for clustering were identified with multivariable analysis and then Bayesian models and TransPhylo were used to infer the timing of transmission within clusters. Of the 2277 culture-positive patients, 70.1% (1596/2277) were migrants: 72.1% (1043/1446) of the migrants patients developed TB within two years of arriving in Longhua; 38.8% within 6 months of arriving; and 12.3% (104/843) had TB symptoms when they arrived. Only 15.4% of Longhua strains were in genomic clusters. More than one third (33.6%) of patients were not treated in Shenzhen but were involved in nearly one third of the recent transmission events. Clustering was associated with migrants not treated in Shenzhen, males, and teachers/trainers. TB in Longhua is prinicipally due to reactivation of infections in migrants, but a proportion may have had clinical or incipient TB upon arrival in the district. Patients diagnosed but not treated in Longhua were involved in recent local TB transmission. Controlling TB in Shenzhen will require strategies to comprehensively diagnose and treat active TB in the internal migrant population.

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.

Whole-Genome Sequencing for Resistance Level Prediction in Multidrug-Resistant Tuberculosis.

Defining the precise relationship between resistance mutations and quantitative phenotypic drug susceptibility testing will increase the value of whole-genome sequencing (WGS) for predicting tuberculosis drug resistance. However, a large number of WGS data sets currently lack corresponding quantitative phenotypic data-the MICs. Using MYCOTBI plates, we determined the MICs to nine antituberculosis drugs for 154 clinical multidrug-resistant tuberculosis isolates from the Shenzhen Center for Chronic Disease Control in Shenzhen, China. Comparing MICs with predicted drug-resistance profiles inferred by WGS showed that WGS could predict the levels of resistance to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. We also found some mutations that may not be associated with drug resistance, such as EmbB D328G, mutations in the gid gene, and C-12T in the eis promoter. However, some strains carrying the same mutations showed different levels of resistance to the corresponding drugs. The MICs of different strains with the RpsL K88R, fabG1 C-15T mutations and some with mutations in embB and rpoB, had MICs to the corresponding drugs that varied by 8-fold or more. This variation is unexplained but could be influenced by the bacterial genetic background. Additionally, we found that 32.3% of rifampicin-resistant isolates were rifabutin-susceptible, particularly those with rpoB mutations H445D, H445L, H445S, D435V, D435F, L452P, S441Q, and S441V. Studying the influence of bacterial genetic background on the MIC and the relationship between rifampicin-resistant mutations and rifabutin resistance levels should improve the ability of WGS to guide the selection of medical treatment regimens. IMPORTANCE Whole-genome sequencing (WGS) has excellent potential in drug-resistance prediction. The MICs are essential indications of adding a particular antituberculosis drug dosage or changing the entire treatment regimen. However, the relationship between many known drug-resistant mutations and MICs is unclear, especially for rarer ones. The results showed that WGS could predict resistance levels to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. However, some mutations may not be associated with drug resistance, and some others may confer various MICs to strains carrying them. Also, 32.3% of rifampicin (RIF)-resistant strains were classified as sensitive to rifabutin (RFB), and some mutations in the rpoB gene may be associated with this phenotype. Our data on the MIC distribution of strains with some rarer mutations add to the accumulated data on the resistance level associated with such mutations to help guide further research and draw meaningful conclusions.

SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission.

Whole genome sequencing (WGS) can provide insight into drug-resistance, transmission chains and the identification of outbreaks, but data analysis remains an obstacle to its routine clinical use. Although several drug-resistance prediction tools have appeared, until now no website integrates drug-resistance prediction with strain genetic relationships and species identification of nontuberculous mycobacteria (NTM). We have established a free, function-rich, user-friendly online platform for MTB WGS data analysis (SAM-TB, http://samtb.szmbzx.com) that integrates drug-resistance prediction for 17 antituberculosis drugs, detection of variants, analysis of genetic relationships and NTM species identification. The accuracy of SAM-TB in predicting drug-resistance was assessed using 3177 sequenced clinical isolates with results of phenotypic drug-susceptibility tests (pDST). Compared to pDST, the sensitivity of SAM-TB for detecting multidrug-resistant tuberculosis was 93.9% [95% confidence interval (CI) 92.6-95.1%] with specificity of 96.2% (95% CI 95.2-97.1%). SAM-TB also analyzes the genetic relationships between multiple strains by reconstructing phylogenetic trees and calculating pairwise single nucleotide polymorphism (SNP) distances to identify genomic clusters. The incorporated mlstverse software identifies NTM species with an accuracy of 98.2% and Kraken2 software can detect mixed MTB and NTM samples. SAM-TB also has the capacity to share both sequence data and analysis between users. SAM-TB is a multifunctional integrated website that uses WGS raw data to accurately predict antituberculosis drug-resistance profiles, analyze genetic relationships between multiple strains and identify NTM species and mixed samples containing both NTM and MTB. SAM-TB is a useful tool for guiding both treatment and epidemiological investigation.

Lesion Heterogeneity and Long-Term Heteroresistance in Multidrug-Resistant Tuberculosis.

Tuberculosis heteroresistance, in which only a fraction of the bacteria in a patient with tuberculosis contains drug-resistant mutations, has been a rising concern. However, its origins and prevalence remain elusive. Here, whole-genome sequencing was performed on 83 serial isolates from 31 patients with multidrug-resistant tuberculosis, and heteroresistance was detected in isolates from 21 patients (67.74%). Heteroresistance persisted in the host for long periods, spanning months to years, and was associated with having multiple tubercular lesions. Our findings indicate that heteroresistance is common and persistent in patients with multidrug-resistant tuberculosis and may affect the success of their treatment regimens.

A population-based genomic epidemiological study of the source of tuberculosis infections in an emerging city: Shenzhen, China.

BACKGROUND: Tuberculosis (TB) in emerging cities is often a disease of recent immigrants, and understanding this epidemiology is crucial for designing effective control and prevention strategies. METHODS: We conducted a retrospective population-based genomic epidemiological study of culture-positive pulmonary TB patients diagnosed between June 2014 and November 2017 in the Bao'an District of Shenzhen, a Chinese city with dramatic recent growth. After whole genome sequencing, transmission clusters were defined as strains differing by no more than 12 SNPs. FINDINGS: Of 1696 culture-positive TB patients, 93•8% (1591/1696) were migrants, with 51•6% (821/1591) employed in housekeeping or unemployed. Of the 1460 migrants with known residence time, 47•7% (697/1460) developed TB within two years after arriving in Bao'an. Only 12•2% (207/1696) of Bao'an isolates were in genomic clusters, indicating that recent transmission was not the primary cause of TB in Bao'an. The isolates' median terminal branch length was 56 SNPs, more than could have accumulated since the arrival of the migrants in Bao'an. The migrants' isolates had genotypic distributions similar to those in their home provinces. One strain isolated in Bao'an belonged to a clade circulating in the patient's home province, providing further evidence that the strains were brought to Bao'an with the migrants. INTERPRETATION: TB in the Bao'an District is principally caused by reactivation of infections acquired by migrants in their home provinces. Nearly half developed TB within two years after arriving in Bao'an, suggesting a need for increased TB screening of migrants, especially housekeeping workers and the unemployed. FUNDING: Sanming Project of Medicine in Shenzhen; National Science and Technology Major Project of China; Natural Science Foundation of China.

[Subspecies identification for Mycobacterium abscessus group].

OBJECTIVE: To identify the subspecies of Mycobacterium abscessus (M.abscessus) group. METHODS: The corresponding genes (hsp65 and rpoB) in 19 clinical isolates (CIs) of M.abscessus group susceptible to clarithromycin were amplified by PCR. Phylogenetic analyses and subspecies identification of the hsp65 gene and rpoB gene were conducted separately and jointly by using the Mega program and PhyML program, and the conflicting species were further identified by the internally transcribed spacer (ITS) sequencing. The rrl and erm(41) of M.abscessus group detection were performed by PCR sequencing, and MICs of inducible resistance to clarithromycin were determined by the broth microdilution method, and then the phenotypic patterns of 19 isolates were analyzed. RESULTS: Comparisons between hsp65 and rpoB sequences of the 19 clinical isolates led to the identification of 10 CIs as Mycobacterium (M). massiliense, 4 CIs as Mycobacterium (M). abscessus, and 1 CI as Mycobacterium (M). bolletii, while the other 4 isolates were identified as M. massiliense by hsp65 gene sequencing and as M.abscessus by rpoB gene sequencing. Ultimately the 4 conflicting isolates were identified as M. massiliense by ITS sequencing. No mutations in the rrl gene with clarithromycin resistance were found. The -35 sequence of the erm (41) promoter of M.abscessus was different from that of M. bolletii and M. massiliense, and the nucleotide at position 28 was polymorphic (T28 or C28); -35 sequence and the nucleotide at position 28 were the same in erm (41) for M. bolletii and M. massiliense. Fourteen M. massiliense strains shared 100% (14/14) homology for erm (41) with 276 bp deletions and 2 bp deletions, and no deletions were found in 4 CIs as M.abscessus and 1 CIs as M. bolletii. The clarithromycin inducible resistance test showed that 3 M.abscessus with T28 (CI02, CI04, CI12) and 1 M. bolletii (CI18) strains were highly resistant, and the other 14 M. massiliense and 1 M.abscessus with polymorphic C28 (CI17) strains remained susceptible. No correlations between -35 sequence of erm (41) promoter and clarithromycin inducible resistance were found. CONCLUSIONS: Hsp65 is applicable to the identification of the subspecies of M.abscessus group, and due to the fact that subspecies of M.abscessus group shows distinct genotytpcally feature in erm (41) sequencing and phenotypic feature in clarithromycin susceptibility, hsp65 and erm (41) can be applied to the identification of subspecies of M.abscessus group, and the resulting data may be useful for clinical diagnosis and treatments.

[Drug sensitivity analysis of Mycobacterium chelonae and Mycobacterium abscessus and evaluation of Etest for susceptibility testing].

OBJECTIVE: To study the drug resistance profile of Mycobacterium(M.) chelonae and M.abscessus and to evaluate the clinical application of Etest(epsilometer test) for susceptibility testing. METHODS: Twenty clinical isolates of M.abscessus and 16 clinical isolates of M.chelonae from clinical specimens were collected.Strain identification was carried out by GenoType Mycobacterium CM assay(Hain Lifescience, Germany). The accuracy was evaluated by comparing Etest results to those obtained by broth microdilution. Thirty-six isolates were tested against amikacin, cefoxitin, ciprofloxacin, clarithromycin, doxycycline, imipenem, linezolid, sulfamethoxazole and tobramycin. The agreement among MICs and interpretive category was evaluated. Chi-squared test was used to compare observed frequency of each of the 2 examples. RESULTS: All of the isolates(36/36) were sensitive to amikacin and cefoxitin, and only 1 isolate(1/36) was resistant to clarithromycin, but more isolates(29/36) were resistant to ciprofloxacin, doxycycline, imipenem and sulfamethoxazole.For M.chelonae, only 2/16 were resistant to linezolid, and 7/16 resistant to tobramycin.For M.abscessus, more than 12/20 were resistant to linezolid and 16/20 resistant to tobramycin. The agreement between broth microdilution MICs and Etest MICs for 9 drugs was 149/324.With amikacin, clarithromycin, doxycycline and imipenem, the agreement for interpretive category was excellent(35/36), followed by sulfamethoxazole(34/36), which corresponded to rarely very major error of 2/36.With ciprofloxacin and tobramycin, agreement for interpretive category was 31/36 and 26/36.With cefoxitin and linezolid, the agreement of Etest MICs was the lowest(14/36), resulting in the resistant category. CONCLUSIONS: Isolates of M.chelonae and M.abscessus exhibit far more susceptibility to amikacin, cefoxitin and clarithromycin than any other antimicrobial agents.Linezolid and tobramycin showed sensitivity to some isolates of M.chelonae.It is suitable for the Etest method as a simple reliable method for the drug susceptibility of amikacin, ciprofloxacin, clarithromycin, doxycycline, imipenem, and tobramycin except to cefoxitin and linezolid. The Etest method of determining sulfamethoxazole susceptibility should be careful.

[Detection of pncA mutation associated with pyrazinamide resistance in Mycobacterium tuberculosis by high-resolution melting cure analysis].

OBJECTIVE: To evaluate the application of a high-resolution melting (HRM) curve analysis for rapid detection of pyrazinamide resistance in Mycobacterium tuberculosis (M. tuberculosis). METHODS: Clinical isolates of M. tuberculosis were collected from Shenzhen from 2007 - 2009 and pncA mutations were characterized by sequence analysis. HRM analysis method was established and used to determine pncA gene mutation in 49 pncA mutant isolates and 78 wild type isolates. BCATEC MGIT 960 was used as the standard method to evaluate application of the HRM curve. RESULTS: Among 49 pncA mutant isolates, 48 isolates were characterized as mutant and 1 isolate with double point mutations misclassified as wild type by using HRM detection. In 78 wild type isolates, HRM found 6 mutant isolates. Using the BCATEC MGIT 960 to detect pyrazinamide drug susceptibility, 62 isolates were found resistant and 65 were susceptible. Among the 62 resistant strains by HRM results 53 strains were resistant, and among the 65 susceptible stains by HRM results 64 were susceptible. Compared to the results of BACTEC MGIT 960, the sensitivity and specificity of HRM were 85.5% (53/62) and 98.5% (64/65), respectively. The Youden index was found to be 0.840. CONCLUSIONS: The results showed a good correlation between HRM curve analysis and BACTEC MGIT 960. HRM curve analysis is a rapid and accurate method that can be used as a screening test for identification of resistance to pyrazinamide.

[Characteristics of pncA gene in multidrug-resistant Mycobacterium tuberculosis isolates and its correlation with drug resistance to pyrazinamide].

OBJECTIVE: To understand the characteristics of pncA gene in multidrug-resistant Mycobacterium tuberculosis isolates and its correlation with drug resistance to pyrazinamide. METHODS: A total of 127 clinical isolates of multidrug-resistant mycobacterium tuberculosis were collected from Shenzhen from year 2007 to 2009. PZA susceptibility was determined by the BACTEC MGIT 960 PZA method. Pyrazinamidase (PZase) activity testing and pncA gene sequencing were performed in all the isolates. The type and frequency of mutations in pncA were determined. Correlation analysis among PZA susceptibility and PZase activity, pncA mutation was performed. RESULTS: Among the 127 isolates, 62 isolates (48.8%) were found resistance to PZA. Among the 62 PZA resistant isolates, 45 isolates which had various pncA mutations were negative for PZase. Mutation rate was 77.4% (48/62) in total PZA resistance isolates. Different types of 48 resistant isolates were identified in the pncA gene, including base substitution (33 isolates), frame shift mutation (12 isolates) and codon mutation (3 isolates). No mutations except one isolate (N11D) existed in all PZA-susceptibility isolates which were positive for PZase. A total of 5 mutations which have not been described previously were found as follows: H57P, P62Q, G108R, D110Y and G162V. The correlation among the PZA susceptibility and the PZase activity (r = 0.895, P < 0.05), the pncA mutation (r = 0.779, P < 0.05) were significant in 127 multidrug-resistant isolates. CONCLUSION: A high diversity of pncA gene mutation was found among PZA resistant strains of MTB. This study revealed five new mutations of the pncA gene that were not previously described, which scattered in the hot-spot regions located in the metal coordination site and active site of the enzyme. Mutations had a high correlation with the PZA resistance.