Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strains

Strategies for shortening tuberculosis therapy

In the absence of effective patient-stratification approaches, tuberculosis (TB) treatment relies on overtreating most patients to ensure high cure rates. Shortening treatment duration without compromising efficacy is therefore high on the agenda of the global TB community. While new and better drugs are certainly needed, we argue that innovative but rational treatment strategies, using both new and existing therapies, will help achieve this goal. There is growing recognition that patient stratification, based on host and pathogen factors, is key to delivering the right drug regimen for the right duration. In this Perspective, we review the current knowledge on the heterogeneity of TB disease and propose approaches to optimize treatment duration in distinct patient groups, taking into consideration the realities of TB control globally. We emphasize key insights that improve the understanding of bacterial vulnerabilities in patients with easy-to-treat and hard-to-treat TB, helping to reduce diagnostic uncertainties. We explore how the TB research community can integrate disease biology, pathology and symptoms, to rethink therapeutic strategies and reduce TB treatment duration.

Ecology, global diversity and evolutionary mechanisms in the Mycobacterium tuberculosis complex

With the COVID-19 pandemic receding, tuberculosis (TB) is again the number one cause of human death to a single infectious agent. TB is caused by bacteria that belong to the Mycobacterium tuberculosis complex (MTBC). Recent advances in genome sequencing have provided new insights into the ecology and evolution of the MTBC. This includes the discovery of new phylogenetic lineages within the MTBC, a deeper understanding of the host tropism among the various animal-adapted lineages, enhanced knowledge on the evolutionary dynamics of antimicrobial resistance and transmission, as well as a better grasp of the within-host MTBC diversity. Moreover, advances in long-read sequencing are increasingly highlighting the relevance of structural genomic variation in the MTBC. These findings not only shed new light on the biology and epidemiology of TB, but also give rise to new questions and research avenues. The purpose of this Review is to summarize these new insights and discuss their implications for global TB control.

Onset of infectiousness explains differences in transmissibility across Mycobacterium tuberculosis lineages

Mycobacterium tuberculosis complex (MTBC) lineages show substantial variability in virulence, but the epidemiological consequences of this variability have not been studied in detail. Here, we aimed for a lineage-specific epidemiological characterization by applying phylodynamic models to genomic data from different countries, representing the most abundant MTBC lineages. Our results suggest that all lineages are associated with similar durations and levels of infectiousness, resulting in similar reproductive numbers. However, L1 and L6 are associated with a delayed onset of infectiousness, leading to longer periods between subsequent transmission events. Together, our findings highlight the role of MTBC genetic diversity in tuberculosis disease progression and transmission.

Impact of rpoB gene mutations and Rifampicin-resistance levels on treatment outcomes in Rifampicin-resistant tuberculosis

BACKGROUND

Although many studies have examined the connection between mutations in the rpoB gene and drug resistance, the impact of common mutations on treatment outcomes for RR-TB is not yet fully understood.

OBJECTIVES

This study explores the relationship between rpoB gene mutations and drug-resistant phenotypes, assesses their role in predicting RR-TB prognosis, and investigates the impact of disputed rpoB mutations in M. tuberculosis on treatment outcomes.

METHODS

192 rifampicin-resistant isolates were retested for drug susceptibility and gene sequencing. Minimum inhibitory concentrations (MICs) were determined for 98 isolates with disputed rpoB gene mutations. These mutations can cause low-level resistance to rifampicin, leading to inconsistencies in drug susceptibility testing and impacting medication therapy decisions.

RESULTS

Of 192 cases, 116 (60.4%) achieved successful outcomes, while 76 (39.6%) were unsuccessful. Among the 98 isolates tested for phenotypic drug susceptibility testing (DST) based on minimum inhibitory concentration (MIC), 67 (68.4%) showed high-level resistance with a MIC of ≥ 1 µg/mL. In contrast, 31 (31.6%) drug-susceptible tuberculosis isolates exhibited low-level resistance with a MIC of < 1.0 µg/mL. Of the 31 isolates with low-level resistance, 14 (45.2%) had successful treatment outcomes, while 17 (54.8%) did not. Among the 67 isolates with high-level resistance, 41 (61.2%) achieved successful outcomes, whereas 26 (38.8%) did not. In analysing the 14 codons of the Rifampicin Resistance Determining Region (RRDR) of the rpoB gene, the Leu430Pro codon showed the highest odds ratio (OR) of 2.98 (95% CI: 0.96-9.27) with a p-value of 0.0591, indicating statistically not significant. However, this suggests a potential association with rifampicin resistance that requires further investigation, particularly in areas with high drug-resistant tuberculosis prevalence. Other reported variants had lower odds ratios: Asp435Val with 1.23 (95% CI: 0.32-4.75), Asp435Tyr with 1.86 (95% CI: 0.60-5.76), His445Tyr with 1.16 (95% CI: 0.47-2.91), and Ser450Leu with 1.44 (95% CI: 0.81-2.58).

CONCLUSIONS

This study indicates that low-level rifampicin mono-resistance in tuberculosis (TB) patients is associated with poor clinical outcomes. A mutation at the Leu430Pro codon showed the highest odds ratio of 2.98 (p-value 0.0591), suggesting a potential association with rifampicin resistance that warrants further research, especially in areas with high drug-resistant TB. It highlights the need for more aggressive treatment strategies for patients with low-level rifampicin resistance, even if they seem solely mono-resistant.

Understanding Mycobacterium tuberculosis through its genomic diversity and evolution

Pathogen evolution and genomic diversity are shaped by specific host immune pressures and therapeutic interventions. Analysis of the extant genomes of circulating strains of Mycobacterium tuberculosis, a leading cause of infectious mortality that has co-evolved with humans for thousands of years, can provide new insights into host-pathogen interactions that underlie specific aspects of pathogenesis and onward transmission. With the explosion in the number of fully sequenced M. tuberculosis strains that are now paired with detailed clinical data, there are new opportunities to understand the evolutionary basis for and consequences of M. tuberculosis strain diversity. This review examines mechanistic findings that have emerged from pairing whole genome sequencing data and evolutionary analysis with functional dissection of specific bacterial variants. These include improved understanding of secreted effectors that modulate the properties and migratory behavior of infected macrophages as well as bacterial genetic alterations important for survival within hypoxic microenvironments. Genomic, evolutionary, and functional analyses across diverse M. tuberculosis strains will identify prominent bacterial adaptations to their human hosts and shape our understanding of TB disease biology and the host immune response.

Nanoclay Mediated Two-Pronged Strategy for Infected-Wound Healing

Photothermal therapy (PTT) is an efficient way to combat bacterial infections and circumvent multidrug resistance. However, balancing efficacious bacterial killing and minimizing damage to the surrounding normal tissues remain a great challenge. Herein, a highly cooperative Prussian blue/kaolinite (PB/Kaol) hybrid nanosystem is constructed for antibacterial therapy to accelerate the healing of infected wounds. After hybridization with Kaol, the prepared PB/Kaol forms interfacial Al-O-Fe bonds, a fast charge transfer channel from Kaol to PB, which contributes to the enhanced photothermal effect of PB/Kaol. Additionally, the hydroxyl and Lewis acid-base sites of the Kaol surface could promote the adhesion of PB/Kaol to bacteria, thereby ensuring that as much hyperthermia as possible is focused on the bacteria and minimizing damage to the surrounding healthy tissues. Furthermore, PB/Kaol inherits the anti-inflammatory and hemostasis functions of PB and Kaol, resulting in the rapid healing of infected wounds.

The chosen few: Mycobacterium tuberculosis isolates for IMPAc-TB

The three programs that make up the Immune Mechanisms of Protection Against Mycobacterium tuberculosis Centers (IMPAc-TB) had to prioritize and select strains to be leveraged for this work. The CASCADE team based at Seattle Children's Research Institute are leveraging M.tb H37Rv, M.tb CDC1551, and M.tb SA161. The HI-IMPACT team based at Harvard T.H. Chan School of Public Health, Boston, have selected M.tb Erdman as well as a novel clinical isolate recently characterized during a longitudinal study in Peru. The PHOENIX team also based at Seattle Children's Research Institute have selected M.tb HN878 and M.tb Erdman as their isolates of choice. Here, we describe original source isolation, genomic references, key virulence characteristics, and relevant tools that make these isolates attractive for use. The global context for M.tb lineage 2 and 4 selection is reviewed including what is known about their relative abundance and acquisition of drug resistance. Host-pathogen interactions seem driven by genomic differences on each side, and these play an important role in pathogenesis and immunity. The few M.tb strains chosen for this work do not reflect the vast genomic diversity within this species. They do, however, provide specific virulence, pathology, and growth kinetics of interest to the consortium. The strains selected should not be considered as "representative" of the growing available array of M.tb isolates, but rather tools that are being used to address key outstanding questions in the field.

Predicting bacterial fitness in Mycobacterium tuberculosis with transcriptional regulatory network-informed interpretable machine learning

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis disease, the greatest source of global mortality by a bacterial pathogen. Mtb adapts and responds to diverse stresses such as antibiotics by inducing transcriptional stress-response regulatory programs. Understanding how and when these mycobacterial regulatory programs are activated could enable novel treatment strategies for potentiating the efficacy of new and existing drugs. Here we sought to define and analyze Mtb regulatory programs that modulate bacterial fitness. We assembled a large Mtb RNA expression compendium and applied these to infer a comprehensive Mtb transcriptional regulatory network and compute condition-specific transcription factor activity profiles. We utilized transcriptomic and functional genomics data to train an interpretable machine learning model that can predict Mtb fitness from transcription factor activity profiles. We demonstrated that this transcription factor activity-based model can successfully predict Mtb growth arrest and growth resumption under hypoxia and reaeration using only RNA-seq expression data as a starting point. These integrative network modeling and machine learning analyses thus enable the prediction of mycobacterial fitness under different environmental and genetic contexts. We envision these models can potentially inform the future design of prognostic assays and therapeutic intervention that can cripple Mtb growth and survival to cure tuberculosis disease.