Mycobacterial genomics and structural bioinformatics: opportunities and challenges in drug discovery

Similarity of drug targets to human microbiome metaproteome promotes pharmacological promiscuity

Similarity between candidate drug targets and human proteins is commonly assessed to minimize the occurrence of side effects. Although numerous drugs have been found to disrupt the health of the human microbiome, no comprehensive comparison between established drug targets and the human microbiome metaproteome has yet been conducted. Therefore, herein, sequence and structure alignments between human and pathogen drug targets and representative human gut, oral, and vaginal microbiome metaproteomes were performed. Both human and pathogen drug targets were found to be similar in sequence, function, structure, and drug binding capacity to proteins in diverse pathogenic and non-pathogenic bacteria from all three microbiomes. The gut metaproteome was identified as particularly susceptible overall to off-target effects. Certain symptoms, such as infections and immune disorders, may be more common among drugs that non-selectively target host microbiota. These findings suggest that similarities between human microbiome metaproteomes and drug target candidates should be routinely checked.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

A Bibliometric Analysis of Leprosy during 2000-2021 from Web of Science Database

In recent years, after the essential elimination of leprosy (the prevalence of which is <1/100,000), the trends, research hotpots, and frontiers of leprosy research are not clear. This study provides a detailed overview of leprosy in terms of papers, journal, language, year, citations, h-index, author keywords, institution, and country through bibliometrics. The results are as follows: (1) The publication rate has increased in recent years, and 8892 papers were obtained. Most of the publications are in English, and the subject categories are mainly focused on “Dermatology.” The “leprosy review” published the most significant number of papers on leprosy, followed by “Plos Neglected Tropical Disease” and “International Journal of Leprosy and Other Mycobacterial Diseases.” (2) Leprosy-related research was contributed to by 24,672 authors, and the ten authors with the most significant number of publications were identified. (3) The University of London (including the London School of Hygiene and Tropical Medicine) has the highest h-index, and Fundacao Oswaldo Cruz is the most productive institution. (4) Brazil, India, the United States, the United Kingdom, and the Netherlands are the most productive countries, and the collaborative network reveals that they have established close cooperation with other countries. France has the highest average number of citations. (5) The keyword co-occurrence network identifies five highly relevant clusters representing topical issues in leprosy research (public health, leprosy vaccine, immune mechanisms, treatment, and genomics research). Overall, these results provide valuable insights for scholars, research institutions, and policymakers to better understand developments in the field of leprosy.

Mycobacterium abscessus: insights from a bioinformatic perspective

Mycobacterium abscessus is a nontuberculous mycobacterium, associated with broncho-pulmonary infections in individuals suffering from cystic fibrosis, bronchiectasis, and pulmonary diseases. The risk factors for transmission include biofilms, contaminated water resources, fomites, and infected individuals. M. abscessus is extensively resistant to antibiotics. To date, there is no vaccine and combination antibiotic therapy is followed. However, drug toxicities, low cure rates, and high cost of treatment make it imperfect. Over the last 20 years, bioinformatic studies on M. abscessus have advanced our understanding of the pathogen. This review integrates knowledge from the analysis of genomes, microbiomes, genomic variations, phylogeny, proteome, transcriptome, secretome, antibiotic resistance, and vaccine design to further our understanding. The utility of genome-based studies in comprehending disease progression, surveillance, tracing transmission routes, and epidemiological outbreaks on a global scale has been highlighted. Furthermore, this review underlined the importance of using computational methodologies for pinpointing factors responsible for pathogen survival and resistance. We reiterate the significance of interdisciplinary research to fight M. abscessus. In a nutshell, the outcome of computational studies can go a long way in creating novel therapeutic avenues to control M. abscessus mediated pulmonary infections.

Diagnostic accuracy of nanopore sequencing using respiratory specimens in the diagnosis of pulmonary tuberculosis

OBJECTIVES

The aim of this study was to assess the role of nanopore sequencing using respiratory specimens in the early diagnosis of pulmonary tuberculosis (PTB) and simultaneously compare it head-to-head with Mycobacterium tuberculosis (MTB) culture, and Xpert MTB/rifampin (RIF).

METHODS

The clinical data of 164 patients with suspected PTB were retrospectively reviewed to determine the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of the acid-fast bacilli (AFB) smear, MTB culture, Xpert MTB/RIF, and nanopore sequencing and assess their diagnostic accuracy compared with culture combined with clinical diagnosis.

RESULTS

The overall sensitivity, specificity, PPV, NPV, and AUC of the AFB smear were 27.6%, 87.5%, 84.2%, 33.3%, and 0.58, respectively; for MTB culture, these values were 57.8%, 100.0%, 100.0%, 49.5%, and 0.79, respectively; for Xpert MTB/RIF, these values were 62.9%, 97.9%, 98.7%, 52.2%, and 0.80, respectively; and for nanopore sequencing, these values were 94.8%, 97.9%, 99.1%, 88.7%, and 0.96, respectively.

CONCLUSION

The diagnostic accuracy of nanopore sequencing was excellent in terms of PTB diagnosis and was considerably better than that of the Xpert MTB/RIF and MTB culture. Nanopore sequencing could be an effective alternative to Xpert MTB/RIF for the initial detection of PTB to improve the accuracy of PTB diagnosis.

Differences between Mycobacterium chimaera and tuberculosis Using Ocular Multimodal Imaging: A Systematic Review

Due to their non-specific diagnostic patterns of ocular infection, differential diagnosis between Mycobacterium (M.) chimaera and tuberculosis can be challenging. In both disorders, ocular manifestation can be the first sign of a systemic infection, and a delayed diagnosis might reduce the response to treatment leading to negative outcomes. Thus, it becomes imperative to distinguish chorioretinal lesions associated with M. chimaera, from lesions due to M. tuberculosis and other infectious disorders. To date, multimodal non-invasive imaging modalities that include ultra-wide field fundus photography, fluorescein and indocyanine green angiography, optical coherence tomography and optical coherence tomography angiography, facilitate in vivo examination of retinal and choroidal tissues, enabling early diagnosis, monitoring treatment response, and relapse detection. This approach is crucial to differentiate between active and inactive ocular disease, and guides clinicians in their decisional-tree during the patients’ follow-up. In this review, we summarized and compared the available literature on multimodal imaging data of M. chimaera infection and tuberculosis, emphasizing similarities and differences in imaging patterns between these two entities and highlighting the relevance of multimodal imaging in the management of the infections.

Application of Computational Methods in Understanding Mutations in Mycobacterium tuberculosis Drug Resistance

The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) impedes the End TB Strategy by the World Health Organization aiming for zero deaths, disease, and suffering at the hands of tuberculosis (TB). Mutations within anti-TB drug targets play a major role in conferring drug resistance within Mtb; hence, computational methods and tools are being used to understand the mechanisms by which they facilitate drug resistance. In this article, computational techniques such as molecular docking and molecular dynamics are applied to explore point mutations and their roles in affecting binding affinities for anti-TB drugs, often times lowering the protein’s affinity for the drug. Advances and adoption of computational techniques, chemoinformatics, and bioinformatics in molecular biosciences and resources supporting machine learning techniques are in abundance, and this has seen a spike in its use to predict mutations in Mtb. This article highlights the importance of molecular modeling in deducing how point mutations in proteins confer resistance through destabilizing binding sites of drugs and effectively inhibiting the drug action.

Repurposing Drugs to Combat Drug Resistance in Leprosy: A Review of Opportunities

Leprosy is caused by extremely slow-growing and uncultivated mycobacterial pathogens, namely Mycobacterium leprae and M. lepromatosis. Nearly 95% of the new cases of leprosy recorded globally are found in India, Brazil, and 20 other priority countries [WHO, 2019], of which nearly two-thirds of the cases are reported in India alone. Currently, leprosy is treated with dapsone, rifampicin, and clofazimine, also known as multi-drug therapy [MDT], as per the recommendations of WHO since 1981. Still, the number of new leprosy cases recorded globally has remained constant in the last one-decade ,and resistance to multiple drugs has been documented in various parts of the world, even though relapses are rare in patients treated with MDT. Antimicrobial resistance testing against M. leprae or the evaluation of the anti-leprosy activity of new drugs remains a challenge as leprosy bacilli do not grow in vitro. Besides, developing a new drug against leprosy through the conventional drug development process is not economically attractive or viable for pharma companies. Therefore, a promising alternative is the repurposing of existing drugs/approved medications or their derivatives for assessing their anti-leprosy potential. It is an efficient method to identify novel medicinal and therapeutic properties of approved drug molecules. Any combinatorial chemotherapy that combines these repurposed drugs with the existing first-line [MDT] and second-line drugs could improve the bactericidal and synergistic effects against these notorious bacteria and can help in achieving the much-cherished goal of "leprosy-free world". This review highlights novel opportunities for drug repurposing to combat resistance to current therapeutic approaches.

Secretome characterization of clinical isolates from the Mycobacterium abscessus complex provides insight into antigenic differences

BACKGROUND

Mycobacterium abscessus (MAB) is a widely disseminated pathogenic non-tuberculous mycobacterium (NTM). Like with the M. tuberculosis complex (MTBC), excreted / secreted (ES) proteins play an essential role for its virulence and survival inside the host. Here, we used a robust bioinformatics pipeline to predict the secretome of the M. abscessus ATCC 19977 reference strain and 15 clinical isolates belonging to all three MAB subspecies, M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense.

RESULTS

We found that ~ 18% of the proteins encoded in the MAB genomes were predicted as secreted and that the three MAB subspecies shared > 85% of the predicted secretomes. MAB isolates with a rough (R) colony morphotype showed larger predicted secretomes than isolates with a smooth (S) morphotype. Additionally, proteins exclusive to the secretomes of MAB R variants had higher antigenic densities than those exclusive to S variants, independent of the subspecies. For all investigated isolates, ES proteins had a significantly higher antigenic density than non-ES proteins. We identified 337 MAB ES proteins with homologues in previously investigated M. tuberculosis secretomes. Among these, 222 have previous experimental support of secretion, and some proteins showed homology with protein drug targets reported in the DrugBank database. The predicted MAB secretomes showed a higher abundance of proteins related to quorum-sensing and Mce domains as compared to MTBC indicating the importance of these pathways for MAB pathogenicity and virulence. Comparison of the predicted secretome of M. abscessus ATCC 19977 with the list of essential genes revealed that 99 secreted proteins corresponded to essential proteins required for in vitro growth.

CONCLUSIONS

This study represents the first systematic prediction and in silico characterization of the MAB secretome. Our study demonstrates that bioinformatics strategies can help to broadly explore mycobacterial secretomes including those of clinical isolates and to tailor subsequent, complex and time-consuming experimental approaches accordingly. This approach can support systematic investigation exploring candidate proteins for new vaccines and diagnostic markers to distinguish between colonization and infection. All predicted secretomes were deposited in the Secret-AAR web-server ( http://microbiomics.ibt.unam.mx/tools/aar/index.php ).

Strategies for drug target identification in Mycobacterium leprae

Hansen's disease (HD), or leprosy, continues to be endemic in many parts of the world. Although multidrug therapy (MDT) is successful in curing a large number of patients, some of them abandon it because it is a long-term treatment. Therefore, identification of new drug targets in Mycobacterium leprae is considered of high importance. Here, we introduce an overview of in silico and in vitro studies that might be of help in this endeavor. The essentiality of M. leprae proteins is reviewed with discussion of flux balance analysis, gene expression, and knockout articles. Finally, druggability techniques are proposed for the validation of new M. leprae protein targets (see Fig. 1).

Comparison of the CapitalBio™Mycobacterium RT-PCR detection test and Xpert MTB/RIF assay for diagnosis of renal tuberculosis

The purpose of this study is to compare the efficiency difference between CapitalBio™Mycobacterium real-time polymerase chain reaction (RT-PCR) detection test and Xpert MTB/RIF assay for the diagnosis of renal tuberculosis (TB). We analyzed 117 samples collected between July 1, 2018, and October 31, 2019, from patients with suspected renal TB to determine the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of the CapitalBio™ Mycobacterium RT-PCR detection test for renal TB and to evaluate its diagnostic accuracy compared with Xpert MTB/RIF assay. Five cases were excluded from this study because of incomplete data. Taking clinical diagnosis as the gold standard, for the Xpert MTB/RIF assay, the sensitivity was 87.95% (78.96-94.07%), specificity 96.55% (82.24-99.91%), PPV 98.65% (92.70-99.97%), NPV 73.68% (56.90-86.60%), and AUC 0.92 (0.86-0.96). For the CapitalBio™Mycobacterium RT-PCR detection test, the overall sensitivity was 84.34% (74.71-91.39%), specificity 93.10% (77.23-99.15%), PPV 97.22% (90.32-99.66%), NPV 67.50% (50.87-81.43%), and AUC 0.89(0.81-0.94). The diagnostic efficiency of the CapitalBio™Mycobacterium RT-PCR detection test was similar to that of the Xpert MTB/RIF assay in patients with renal TB. Hence, the CapitalBio™Mycobacterium RT-PCR detection test presents a valuable alternative for the diagnosis of renal TB.

A Comparative Genomics Approach for Shortlisting Broad-Spectrum Drug Targets in Nontuberculous Mycobacteria

Many members of nontuberculous mycobacteria (NTM) are opportunistic pathogens causing several infections in animals. The incidence of NTM infections and emergence of drug-resistant NTM strains are rising worldwide, emphasizing the need to develop novel anti-NTM drugs. The present study is aimed to identify broad-spectrum drug targets in NTM using a comparative genomics approach. The study identified 537 core proteins in NTM of which 45 were pathogen specific and essential for the survival of pathogens. Furthermore, druggability analysis indicated that 15 were druggable among those 45 proteins. These 15 proteins, which were core proteins, pathogen-specific, essential, and druggable, were considered as potential broad-spectrum candidates. Based on their locations in cytoplasm and membrane, targets were classified as drug and vaccine targets. The identified 15 targets were different enzymes, carrier proteins, transcriptional regulator, two-component system protein, ribosomal, and binding proteins. The identified targets could further be utilized by researchers to design inhibitors for the discovery of antimicrobial agents.

Genomics, Computational Biology and Drug Discovery for Mycobacterial Infections: Fighting the Emergence of Resistance

Tuberculosis (TB) and leprosy are mycobacterial infections caused by Mycobacterium tuberculosis and Mycobacterium leprae respectively. These diseases continue to be endemic in developing countries where the cost of new medicines presents major challenges. The situation is further exacerbated by the emergence of resistance to many front-line antibiotics. A priority now is to design new antimycobacterials that are not only effective in combatting the diseases but are also less likely to give rise to resistance. In both these respects understanding the structure of drug targets in M. tuberculosis and M. leprae is crucial. In this review we describe structure-guided approaches to understanding the impacts of mutations that give rise to antimycobacterial resistance and the use of this information in the design of new medicines.

Biology of antimicrobial resistance and approaches to combat it

Insufficient development of new antibiotics and the rising resistance of bacteria to those that we have are putting the world at risk of losing the most widely curative class of medicines currently available. Preventing deaths from antimicrobial resistance (AMR) will require exploiting emerging knowledge not only about genetic AMR conferred by horizontal gene transfer or de novo mutations but also about phenotypic AMR, which lacks a stably heritable basis. This Review summarizes recent advances and continuing limitations in our understanding of AMR and suggests approaches for combating its clinical consequences, including identification of previously unexploited bacterial targets, new antimicrobial compounds, and improved combination drug regimens.

Structure-Based Drug Design for Tuberculosis: Challenges Still Ahead

Structure-based and computer-aided drug design approaches are commonly considered to have been successful in the fields of cancer and antiviral drug discovery but not as much for antibacterial drug development. The search for novel anti-tuberculosis agents is indeed an emblematic example of this trend. Although huge efforts, by consortiums and groups worldwide, dramatically increased the structural coverage of the Mycobacterium tuberculosis proteome, the vast majority of candidate drugs included in clinical trials during the last decade were issued from phenotypic screenings on whole mycobacterial cells. We developed here three selected case studies, i.e., the serine/threonine (Ser/Thr) kinases—protein kinase (Pkn) B and PknG, considered as very promising targets for a long time, and the DNA gyrase of M. tuberculosis, a well-known, pharmacologically validated target. We illustrated some of the challenges that rational, target-based drug discovery programs in tuberculosis (TB) still have to face, and, finally, discussed the perspectives opened by the recent, methodological developments in structural biology and integrative techniques.

CapitalBio Mycobacterium real-time polymerase chain reaction detection test: Rapid diagnosis of Mycobacterium tuberculosis and nontuberculous mycobacterial infection

OBJECTIVES

To evaluate the accuracy of the CapitalBio Mycobacterium real-time polymerase chain reaction (RT-PCR) detection test for pulmonary Mycobacterium tuberculosis (MTB) and nontuberculous mycobacterial (NTM) infection.

METHODS

This study analyzed 2,460 samples from patients with suspected pulmonary mycobacterial infection collected between 01 June 2018 and 31 July 2019. It aimed to determine the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of the CapitalBio Mycobacterium detection test for MTB and NTM infections, and to evaluate its diagnostic accuracy compared with mycobacterial culture.

RESULTS

The sensitivity, specificity, PPV, NPV, and AUC of the CapitalBio Mycobacterium detection test for MTB was 83.0%, 79.9%, 80.8%, 82.2%, and 0.81, respectively. This was similar to the diagnostic accuracy of Xpert MTB/RIF for MTB and was significantly higher than that of smear. For pulmonary NTM infection, the sensitivity, specificity, PPV, NPV, and AUC of the test was 82.0%, 99.6%, 94.1%, 98.5%, and 0.91, respectively. The diagnostic accuracy of the CapitalBio Mycobacterium detection test was also significantly higher than that of smear for NTM.

CONCLUSIONS

The CapitalBio Mycobacterium detection test had good diagnostic accuracy for MTB and NTM infections. This is of great significance for the differential diagnosis of early pulmonary mycobacterial infection.

Biosynthesis of Galactan in Mycobacterium tuberculosis as a Viable TB Drug Target?

While target-based drug design has proved successful in several therapeutic areas, this approach has not yet provided compelling outcomes in the field of antibacterial agents. This statement remains especially true for the development of novel therapeutic interventions against tuberculosis, an infectious disease that is among the top ten leading causes of death globally. Mycobacterial galactan is an important component of the protective cell wall core of the tuberculosis pathogen and it could provide a promising target for the design of new drugs. In this review, we summarize the current knowledge on galactan biosynthesis in Mycobacterium tuberculosis, including landmark findings that led to the discovery and understanding of three key enzymes in this pathway: UDP-galactose mutase, and galactofuranosyl transferases GlfT1 and GlfT2. Moreover, we recapitulate the efforts aimed at their inhibition. The predicted common transition states of the three enzymes provide the lucrative possibility of multitargeting in pharmaceutical development, a favourable property in the mitigation of drug resistance. We believe that a tight interplay between target-based computational approaches and experimental methods will result in the development of original inhibitors that could serve as the basis of a new generation of drugs against tuberculosis.

Azaaurones as Potent Antimycobacterial Agents Active against MDR- and XDR-TB

Herein we report the screening of a small library of aurones and their isosteric counterparts, azaaurones and N-acetylazaaurones, against Mycobacterium tuberculosis. Aurones were found to be inactive at 20 μm, whereas azaaurones and N-acetylazaaurones emerged as the most potent compounds, with nine derivatives displaying MIC₉₉ values ranging from 0.4 to 2.0 μm. In addition, several N-acetylazaaurones were found to be active against multidrug-resistant (MDR) and extensively drug-resistant (XDR) clinical M. tuberculosis isolates. The antimycobacterial mechanism of action of these compounds remains to be determined; however, a preliminary mechanistic study confirmed that they do not inhibit the mycobacterial cytochrome bc1 complex. Additionally, microsomal metabolic stability and metabolite identification studies revealed that N-acetylazaaurones are deacetylated to their azaaurone counterparts. Overall, these results demonstrate that azaaurones and their N-acetyl counterparts represent a new entry in the toolbox of chemotypes capable of inhibiting M. tuberculosis growth.