In-depth Analysis of IS6110 Genomic Variability in the Mycobacterium tuberculosis Complex

Mapping high-risk areas for Mycobacterium tuberculosis complex bacteria transmission: Linking host space use and environmental contamination

In many Mediterranean ecosystems, animal tuberculosis (TB), caused by Mycobacterium bovis, an ecovar of Mycobacterium tuberculosis complex (MTBC), is maintained by multi-host communities. It is hypothesised that interspecies transmission is mainly indirect via shared contaminated environments. Therefore, identifying spatial areas where MTBC bacteria occur and quantifying space use by susceptible hosts might help predict the spatial likelihood of transmission across the landscape. Here, we aimed to evaluate the transmission risk of MTBC in a multi-host system involving wildlife (ungulates and carnivores) and cattle (Bos taurus). We collected eighty-nine samples from natural substrates (water, soil, and mud) at 38 sampling sites in a TB endemic area within a Mediterranean agroforestry system in Portugal. These samples were analysed by real-time PCR to detect MTBC DNA. Additionally, host-specific space use intensity maps were obtained through camera-trapping covering the same sampling sites. Results evidenced that a significant proportion of samples were positive for MTBC DNA (49 %), suggesting that the contamination is widespread in the area. Moreover, they showed that the probability of MTBC occurrence in the environment was significantly influenced by topographic features (i.e., slope), although other non-significant predictor related with soil conditions (SMI: soil moisture index) incorporated the MTBC contamination model. The integration of host space use intensity maps with the spatial detection of MTBC showed that the red deer (Cervus elaphus) and wild boar (Sus scrofa) exhibited the highest percentages of high-risk areas for MTBC transmission. Furthermore, when considering the co-occurrence of multiple hosts, transmission risk analyses revealed that 26.5 % of the study area represented high-risk conditions for MTBC transmission, mainly in forest areas.

Integrating Genomic Data with the Development of CRISPR-Based Point-of-Care-Testing for Bacterial Infections

Purpose of Review

Bacterial infections and antibiotic resistance contribute to global mortality. Despite many infections being preventable and treatable, the lack of reliable and accessible diagnostic tools exacerbates these issues. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-based diagnostics has emerged as a promising solution. However, the development of CRISPR diagnostics has often occurred in isolation, with limited integration of genomic data to guide target selection. In this review, we explore the synergy between bacterial genomics and CRISPR-based point-of-care tests (POCT), highlighting how genomic insights can inform target selection and enhance diagnostic accuracy.

Recent Findings

We review recent advances in CRISPR-based technologies, focusing on the critical role of target sequence selection in improving the sensitivity of CRISPR-based diagnostics. Additionally, we examine the implementation of these technologies in resource-limited settings across Asia and Africa, presenting successful case studies that demonstrate their potential.

Summary

The integration of bacterial genomics with CRISPR technology offers significant promise for the development of effective point-of-care diagnostics.

Accuracy of molecular diagnostic assays for detection of Mycobacterium bovis: A systematic review and meta-analysis

Bovine tuberculosis (bovine TB) is a chronic wasting disease of cattle caused primarily by Mycobacterium bovis. Controlling bovine TB requires highly sensitive, specific, quick, and reliable diagnostic methods. This systematic review and meta-analysis evaluated molecular diagnostic tests for M. bovis detection to inform the selection of the most viable assay. On a per-test basis, loop-mediated isothermal amplification (LAMP) showed the highest overall sensitivity of 99.0% [95% CI: 86.2%-99.9%] and specificity of 99.8% [95% CI: 96.2%-100.00%]. Quantitative real-time polymerase chain reaction (qPCR) outperformed conventional PCR and nested PCR (nPCR) with a diagnostic specificity of 96.6% [95% CI: 88.9%-99.0%], while the diagnostic sensitivity of 70.8% [95% CI: 58.6-80.5%] was comparable to that of nPCR at 71.4% [95% CI: 60.7-80.2%]. Test sensitivity was higher with the input of milk samples (90.9% [95% CI: 56.0%-98.7%]), while specificity improved with tests based on major M. bovis antigens (97.8% [95% CI: 92.3%-99.4%]), the IS6110 insertion sequence (95.4% [95% CI: 87.6%-98.4%]), and the RD4 gene (90.7% [95% CI: 52.2%-98.9%]). The design of the currently available molecular diagnostic assays, while mostly based on nonspecific gene targets, prevents them from being accurate enough to diagnose M. bovis infections in cattle, despite their promise. Future assay development should focus on the RD4 region since it is the only target identified by genome sequence data as being distinctive for detecting M. bovis. The availability of a sufficiently accurate diagnostic test combined with the routine screening of milk samples can decrease the risk of zoonotic transmissions of M. bovis.

Detection of Mycobacterium tuberculosis Complex in Sputum Samples Using Droplet Digital PCR Targeting mpt64

Tuberculosis (TB) is one of the top 10 causes of death worldwide. It is challenging to find methods of diagnosis of active pulmonary TB that are sensitive enough to detect cases for proper treatment before unintentional transmission. Droplet digital PCR (ddPCR) is a highly sensitive method to detect genetic material of pathogens, but it has rarely been used for diagnosis of TB. This study compared the sensitivity of ddPCR with that of GeneXpert and AFB smear microscopy in 180 leftover sputum samples from patients suspected of having TB on the basis of clinical symptoms and radiography. Absolute quantification of copy numbers of MTB-specific genes was possible using ddPCR targeting the mpt64 gene. Among the 180 samples, 41.1% were diagnosed as having TB using ddPCR. The sensitivities of AFB smear microscopy, GeneXpert and ddPCR were 41.9%, 82.4% and 100%, respectively. AFB smear microscopy and GeneXpert both had a specificity of 100%, and the specificity of ddPCR was 95.3%. The accuracy of ddPCR (97.2%) is higher than that of GeneXpert (92.7%). This robust ddPCR system could potentially be used as a method for early diagnosis of TB.