embCAB Sequence Variation Among Ethambutol-Resistant Mycobacterium Tuberculosis Isolates Without embB306 Mutation

Mechanisms of resistance to ethambutol in Mycobacterium tuberculosis remain inadequately described. Although there is mounting evidence that mutations of codon 306 in embB play a key role, a significant number of phenotypically ethambutol-resistant strains do not carry mutations in this codon. Here, other mutations in the embCAB operon are suggested to be involved in resistance development

Genomic Diversity among Drug Sensitive and Multidrug Resistant Isolates of Mycobacterium tuberculosis with Identical DNA Fingerprints

complex (MTBC), the causative agent of tuberculosis (TB), is characterized by low sequence diversity making this bacterium one of the classical examples of a genetically monomorphic pathogen. Because of this limited DNA sequence variation, routine genotyping of clinical MTBC isolates for epidemiological purposes relies on highly discriminatory DNA fingerprinting methods based on mobile and repetitive genetic elements. According to the standard view, isolates exhibiting the same fingerprinting pattern are considered direct progeny of the same bacterial clone, and most likely reflect ongoing transmission or disease relapse within individual patients.We generated 23.9 million (K-1) and 33.0 million (K-2) paired 50 bp purity filtered reads corresponding to a mean coverage of 483.5 fold and 656.1 fold respectively. Compared with the laboratory strain H37Rv both Beijing isolates shared 1,209 SNPs. The two Beijing isolates differed by 130 SNPs and one large deletion. The susceptible isolate had 55 specific SNPs, while the MDR variant had 75 specific SNPs, including the five known resistance-conferring mutations. isolates exhibiting identical DNA fingerprinting patterns can harbour substantial genomic diversity. Because this heterogeneity is not captured by traditional genotyping of MTBC, some aspects of the transmission dynamics of tuberculosis could be missed or misinterpreted. Furthermore, a valid differentiation between disease relapse and exogenous reinfection might be impossible using standard genotyping tools if the overall diversity of circulating clones is limited. These findings have important implications for clinical trials of new anti-tuberculosis drugs

High Resolution Discrimination of Clinical Mycobacterium tuberculosis Complex Strains Based on Single Nucleotide Polymorphisms

Recently, the diversity of the Mycobacterium tuberculosis complex (MTBC) population structure has been described in detail. Based on geographical separation and specific host pathogen co-evolution shaping MTBC virulence traits, at least 20 major lineages/genotypes have evolved finally leading to a clear influence of strain genetic background on transmissibility, clinical presentation/outcome, and resistance development. Therefore, high resolution genotyping for characterization of strains in larger studies is mandatory for understanding mechanisms of host-pathogen-interaction and to improve tuberculosis (TB) control. Single nucleotide polymorphisms (SNPs) represent the most reliable markers for lineage classification of clinical isolates due to the low levels of homoplasy, however their use is hampered either by low discriminatory power or by the need to analyze a large number of genes to achieve higher resolution. Therefore, we carried out de novo sequencing of 26 genes (approx. 20000 bp per strain) in a reference collection of MTBC strains including all major genotypes to define a highly discriminatory gene set. Overall, 161 polymorphisms were detected of which 59 are genotype-specific, while 13 define deeper branches such as the Euro-American lineage. Unbiased investigation of the most variable set of 11 genes in a population based strain collection (one year, city of Hamburg, Germany) confirmed the validity of SNP analysis as all strains were classified with high accuracy. Taken together, we defined a diagnostic algorithm which allows the identification of 17 MTBC phylogenetic lineages with high confidence for the first time by sequencing analysis of just five genes. In conclusion, the diagnostic algorithm developed in our study is likely to open the door for a low cost high resolution sequence/SNP based differentiation of the MTBC with a very high specificity. High throughput assays can be established which will be needed for large association studies that are mandatory for detailed investigation of host-pathogen-interaction during TB infection

Prognosis Predictions by Families, Physicians, and Nurses of Patients with Severe Acute Brain Injury: Agreement and Accuracy.

Effective shared decision-making relies on some degree of alignment between families and the medical team regarding a patient's likelihood of recovery. Patients with severe acute brain injury (SABI) are often unable to participate in decisions, and therefore family members make decisions on their behalf. The goal of this study was to evaluate agreement between prognostic predictions by families, physicians, and nurses of patients with SABI regarding their likelihood of regaining independence and to measure each group's prediction accuracy. This observational cohort study, conducted from 01/2018 to 07/2020, was based in the neuroscience and medical/cardiac intensive care units of a single center. Patient eligibility included a diagnosis of SABI-specifically stroke, traumatic brain injury, or hypoxic ischemic encephalopathy-and a Glasgow Coma Scale ≤ 12 after hospital day 2. At enrollment, families, physicians, and nurses were asked separately to predict a patient's likelihood of recovering to independence within 6 months on a 0-100 scale, regardless of whether a formal family meeting had occurred. True outcome was based on modified Rankin Scale assessment through a family report or medical chart review. Prognostic agreement was measured by (1) intraclass correlation coefficient; (2) mean group prediction comparisons using paired Student's t-tests; and (3) prevalence of concordance, defined as an absolute difference of less than 20 percentage points between predictions. Accuracy for each group was measured by calculating the area under a receiver operating characteristic curve (C statistic) and compared by using DeLong's test. Data were collected from 222 patients and families, 45 physicians, and 103 nurses. Complete data on agreement and accuracy were available for 187 and 177 patients, respectively. The intraclass correlation coefficient, in which 1 indicates perfect correlation and 0 indicates no correlation, was 0.49 for physician-family pairs, 0.40 for family-nurse pairs, and 0.66 for physician-nurse pairs. The difference in mean predictions between families and physicians was 23.5 percentage points (p < 0.001), 25.4 between families and nurses (p < 0.001), and 1.9 between physicians and nurses (p = 0.38). Prevalence of concordance was 39.6% for family-physician pairs, 30.0% for family-nurse pairs, and 56.2% for physician-nurse pairs. The C statistic for prediction accuracy was 0.65 for families, 0.82 for physicians, and 0.76 for nurses. The p values for differences in C statistics were < 0.05 for family-physician and family-nurse groups and 0.18 for physician-nurse groups. For patients with SABI, agreement in predictions between families, physicians, and nurses regarding likelihood of recovery is poor. Accuracy appears higher for physicians and nurses compared with families, with no significant difference between physicians and nurses