A small number of high-burden countries account for the majority of tuberculosis cases worldwide. Detailed data are lacking from these regions. To explore the evolutionary history of M. tuberculosis in China — the third highest TB burden country — we analyzed a countrywide collection of 4,578 isolates. Little genetic diversity was detected within the large M. tuberculosis population in China, with 99.4% of the bacterial population belonging to lineage 2 and three sublineages of lineage 4. The deeply rooted phylogenetic positions and geographic restriction of these four genotypes indicate that their populations expanded in situ following a small number of introductions to China. Coalescent analyses suggest that these bacterial sub-populations emerged in China around 1,000 years ago, expanded in parallel from the 12th century onward, and the whole population peaked in the late 18th century. More recently, sublineage L2.3, which is indigenous to China and exhibited relatively high transmissibility and extensive global dissemination, came to dominate the population dynamics of M. tuberculosis in China. Our results indicate that historical expansion of four M. tuberculosis strains shaped the current TB epidemic in China, and highlight the long-term genetic continuity of the indigenous M. tuberculosis population.

National Natural Science Foundation of China, National Science and Technology Major Project of China, and US National Institutes of Health.

Compensatory mutations have been suggested to promote multidrug-resistant tuberculosis (MDR-TB) transmission, but their role in facilitating the recent transmission of MDR-TB is unclear. To investigate the epidemiological significance of compensatory mutations, we analyzed a four-year population-based collection of MDR-TB strains from Shanghai (the most populous city in China) and 1346 published global MDR-TB strains. We report that MDR-TB strains with compensatory mutations in the rpoA, rpoB, or rpoC genes were neither more frequently clustered nor found in larger clusters than those without compensatory mutations. Our results suggest that compensatory mutations are not a major contributor to the current epidemic of MDR-TB.

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.

It is generally believed that drug resistance among treated tuberculosis (TB) patients is as a result of acquired drug resistance due to inappropriate treatment. Previous studies have shown that primary drug resistance caused by transmission also plays a role among treated cases. Differentiating the two types of drug resistance will help in developing appropriate strategies for control of drug resistant tuberculosis. In this study, we tested the hypothesis that drug resistance among treated TB patients is mainly caused by primary resistance rather than acquired resistance. Defining resistance profiles by molecular drug susceptibility test, we used Unit Variable Number Tandem Repeats (VNTR) to genotype and Whole Genome Sequencing (WGS) to confirm the accordance of the first and last Mycobacterium tuberculosis isolates from treated pulmonary TB patients in Shanghai from 2009–2015. Among 81 patients with increasing drug resistance, out of 390 patients enrolled, paired isolates from 59.3% (48/81) had different VNTR patterns indicating primary drug resistance. Our results have demonstrated that primary resistance due to exogenous reinfection is the major cause of drug resistance among treated TB patients in Shanghai; thus, strategies aimed at preventing and interrupting transmission are urgently needed to effectively reduce the epidemic of drug resistant tuberculosis.

No abstract

Debris flow is a type of special torrent containing numerous solid materials. With many types of factors affecting debris flow, there is no reliable basis for the selection of risk factors for debris flow risk assessment. Therefore, to study the factors affecting debris flow, exploring a reliable method for assessing the relative importance of these factors is a significant endeavor in debris flow prevention and control work. In this research, debris flow risk assessment was combined with meta-analysis to analyze quantitatively the relative importance of risk factors of debris flow in northwest and southwest China. The final relative importance of each factor in northwest China is as follows, maximum relative height difference > slope of main channel > maximum daily precipitation > ratio of longitudinal slope > drainage area > length of main channel. In addition, in southwest China, maximum relative height difference > maximum daily precipitation > slope of main channel > ratio of longitudinal slope > length of main channel > drainage area. The meta-analysis results were accurate, which can provide a reliable basis for the selection of debris flow risk factors in debris flow risk assessment. Furthermore, it provides strong support for the application of meta-analysis in risk assessment of other geological hazards.

Abstract. Debris flow is a type of special torrent containing numerous solid materials. It is characterized by sudden outbreak, short duration, and strong destructive force. The occurrence of debris flow is often affected by hydrogeological and geological conditions, including basin area, main ditch length, relative height difference, slope, bed bending coefficient, daily maximum rainfall and so on. With many types of factors affecting debris flow, no reliable basis for selecting factors to evaluate debris flow risk has been established. Therefore, to study the factors affecting debris flow, exploring a reliable method for assessing the relative importance of such factors is an important endeavor in debris flow prevention and control work. In this research, debris flow risk assessment was combined with meta-analysis to analyze quantitatively the relative importance of risk factors of debris flow in northwest and southwest China. Results show that debris flow in northwest China is mainly affected by topography and geological structure. Rainfall plays an important role in stimulating debris flow in this area. For debris flow in southwest China, topography, geological structure, and rainfall conditions all have considerable influence. Meta-analysis can provide a basis for the selection of risk factors of debris flow and has certain reliability.