Clinical implication of novel drug resistance-conferring mutations in resistant tuberculosis

Deep learning on longitudinal CT scans: automated prediction of treatment outcomes in hospitalized tuberculosis patients

Three deep learning (DL)-based prediction models (PMs) using longitudinal CT images were developed to predict tuberculosis (TB) treatment outcomes. The internal dataset consists of 493 bacteriologically confirmed TB patients who completed the anti-tuberculosis treatment with three-time CT scans, including a pretreatment CT scan and two follow-up CT scans. PM1 was trained using only pretreatment CT scans, and PM2 and PM3 were developed by adding follow-up scans. An independent testing was performed on external dataset comprising 86 TB patients. The area under the curve for classifying success and drug-resistant (DR)-TB was improved on both internal (0.609 vs. 0.625 vs. 0.815) and external (0.627 vs. 0.705 vs. 0.735) dataset by adding follow-up scans. The accuracy and F1-score also showed an increasing tendency in the external test. Regular follow-up CT scans can aid in the treatment prediction, and special attention should be given to early intensive phase of treatment to identify high-risk DR-TB patients.

Pretomanid development and its clinical roles in treating tuberculosis

Tuberculosis (TB) is the leading infectious cause of mortality worldwide. Despite the development of different antituberculosis drugs, managing resistant mycobacteria is still challenging. The discovery of novel drugs and new methods of targeted drug delivery have the potential to improve treatment outcomes, lower the duration of treatment, and reduce adverse events. Following bedaquiline and delamanid, pretomanid is the third medicine approved as part of a novel drug regimen for treating drug-resistant TB. It is a promising drug that has the capacity to shape TB treatment and achieve the End TB strategy set by the World Health Organization. The effectiveness of pretomanid has been reported in different observational and clinical studies. However, long-term safety data in humans are not yet available and the pretomanid-based regimen is recommended under an operational research framework that prohibits its wider and programmatic use. Further research is needed before pretomanid can be celebrated as a promising candidate for the treatment of different categories of TB and specific patients. This review covers the update on pretomanid development and its clinical roles in treating Mycobacterium tuberculosis.

WITHDRAWN: Pretomanid for the treatment of Mycobacterium tuberculosis: Evidence on the development and clinical roles

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Antibiotic Susceptibility Patterns of Bacterial Isolates from Routine Clinical Specimens from Referral Hospitals in Tanzania: A Prospective Hospital-Based Observational Study

Introduction

Antimicrobial resistance is one of the biggest threats of modern public health. Although sub-Saharan Africa is highly burdened with infectious diseases, current data on antimicrobial resistance are sparse.

Methods

A prospective study was conducted between October 2018 and September 2019 to assess the antibiotic susceptibility patterns of clinical bacterial isolates obtained from four referral hospitals in Tanzania. We used standard media and Kirby-Bauer disc diffusion methods as per Clinical and Laboratory Standards Institute (CLSI) standards.

Results

We processed a total of 2620 specimens of which 388 (14.8%) were culture-positive from patients with a median (IQR) age of 28 (12–44) years. Of the positive cultures, 52.3% (203) were from females. Most collected specimens were ear pus 28.6% (111), urine 24.0% (93), wound pus 20.6% (80), stool 14.9% (58), and blood 8.3% (32). Predominant isolates were S. aureus 28.4% (110), E. coli 15.2% (59), P. aeruginosa 10.6% (41), P. mirabilis 7.0% (27), V. cholerae 01 Ogawa 6.2% (24), Klebsiella spp. 5.2% (20) and Streptococcus spp. 4.6% (18). Generally, the isolates exhibited a high level of resistance to commonly used antibiotics such as Ampicillin, Amoxicillin-Clavulanic acid, Erythromycin, Gentamicin, Tetracycline, Trimethoprim, third-generation Cephalosporins (Ceftriaxone and Ceftazidime), and reserved drugs (Clindamycin and Meropenem). S. aureus isolates were resistant to most of the antibiotics tested; 66.7% were classified as MRSA infections.

Conclusion

Antibiotic resistance to commonly prescribed antibiotics was alarmingly high. Our findings emphasize the need for comprehensive national control programs to combat antibiotic resistance.

A Glutamine Insertion at Codon 432 of RpoB Confers Rifampicin Resistance in Mycobacterium tuberculosis

Tuberculosis (TB) is an infectious respiratory disease caused by Mycobacterium tuberculosis and one of the top 10 causes of death worldwide. Treating TB is challenging; successful treatment requires a long course of multiple antibiotics. Rifampicin (RIF) is a first-line drug for treating TB, and the development of RIF-resistant M. tuberculosis makes treatment even more difficult. To determine the mechanism of RIF resistance in these strains, we searched for novel mutations by sequencing. Four isolates, CDC-1, CDC-2, CDC-3, and CDC-4, had high-level RIF resistance and unique mutations encoding RpoB G¹⁵⁸R, RpoB V¹⁶⁸A, RpoB S¹⁸⁸P, and RpoB Q⁴³²insQ, respectively. To evaluate their correlation with RIF resistance, plasmids carrying rpoB genes encoding these mutant proteins were transfected into the H₃₇Rv reference strain. The plasmid complementation of RpoB indicated that G¹⁵⁸R, V¹⁶⁸A, and S¹⁸⁸P did not affect the MIC of RIF. However, the MIC of RIF was increased in H₃₇Rv carrying RpoB Q⁴³²insQ. To confirm the correlation between RIF resistance and Q⁴³²insQ, we cloned an rpoB fragment carrying the insertion (encoding RpoB Q⁴³²insQ) into H₃₇Rv by homologous recombination using a suicide vector. All replacement mutants expressing RpoB Q⁴³²insQ were resistant to RIF (MIC > 1 mg/L). These results indicate that RpoB Q⁴³²insQ causes RIF resistance in M. tuberculosis.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.

Assessment of sputum smear-positive but culture-negative results among newly diagnosed pulmonary tuberculosis patients in Tanzania

Diagnosis of pulmonary tuberculosis (TB) in technology-limited countries is widely achieved by smear microscopy, which has limited sensitivity and specificity. The frequency and clinical implication of smear-positive but culture-negative among presumptive TB patients remains unclear. A cross-sectional substudy was conducted which aimed to identify the proportion of nontuberculous mycobacteria (NTM) infections among 94 “smear-positive culture-negative” patients diagnosed between January 2013 and June 2016 in selected health facilities in Tanzania. Out of 94 sputa, 25 (26.60%) were GeneXpert® mycobacteria TB positive and 11/94 (11.70%) repeat-culture positive; 5 were Capilia TB-Neo positive and confirmed by GenoType MTBC to be Mycobacterium tuberculosis/Mycobacterium canettii. The remaining 6 Capilia TB-Neo negative samples were genotyped by GenoType® CM/AS, identifying 3 (3.19%) NTM, 2 Gram positive bacteria, and 1 isolate testing negative, together, making a total of 6/94 (6.38%) confirmed false smear-positives. Twenty-eight (29.79%) were confirmed TB cases, while 60 (63.83%) remained unconfirmed cases. Out of 6 (6.38%) patients who were HIV positive, 2 patients were possibly coinfected with mycobacteria. The isolation of NTM and other bacteria among smear-positive culture-negative samples and the presence of over two third of unconfirmed TB cases emphasize the need of both advanced differential TB diagnostic techniques and good clinical laboratory practices to avoid unnecessary administration of anti-TB drugs.