Open access peer-reviewed chapter

Tuberculosis Diagnosis: Updates and Challenges

Written By

Prakruthi Shivakumar and Kavitha Sunil Shettigar

Reviewed: 17 August 2022 Published: 19 November 2022

DOI: 10.5772/intechopen.107168

From the Annual Volume

Bacterial Infectious Diseases Annual Volume 2023

Edited by Katarzyna Garbacz and Tomas Jarzembowski

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Abstract

Tuberculosis (TB) is caused by a single infectious agent, Mycobacterium tuberculosis, and a public health concern due to increased cases of drug-resistance and high mortality rates. Rapid identification of tuberculosis is necessary for its early treatment and to prevent the emergence of drug-resistant strains. For effective management of patients, rapid, cost-effective, and point-of-care (POC) diagnostic methods are required. The commonly used screening and identification methods are clinical examination, radiography, sputum smear microscopy, culture method, serological method, and tuberculin skin test. In addition, several molecular methods such as NAAT based GeneXpert, loop-mediated isothermal amplification (LAMP), line probe assay (LPA), whole genome sequencing (WGS) and other non-invasive methods of lateral flow urine lipoarabinomannan assay (LF-LAM) and eNose assays are developed. Sputum smear microscopy, Xpert MTB/RIF, and LED-Fluorescence microscopy (LED-FM) are the preferred methods to use in peripheral laboratories. The non-invasive methods of tuberculosis diagnosis are more beneficial in patients from whom collecting sputum sample is difficult particularly in children and HIV co-infected patients. Molecular methods can simultaneously identify the pathogen, M. tuberculosis, and mutations in drug-resistance genes. Even though, many advanced methods are currently available, accurate and affordable diagnostic method for tuberculosis is still challenging. Here, we review and highlight the uses and challenges of currently available conventional and advanced diagnostic methods of tuberculosis screening and diagnosis.

Keywords

  • tuberculosis
  • GeneXpert
  • LAMP
  • LPA
  • whole genome sequencing

1. Introduction

Until the coronavirus (COVID-19) pandemic, tuberculosis (TB) was the leading infectious disease, ranking above HIV/AIDS. Tuberculosis is an ancient bacterial infection and genetic evidence indicates that the causative infectious agent, Mycobacterium tuberculosis (Mtb), is infecting humans for more than 40,000 years and have originated from animal domestication [1]. Tuberculosis is a communicable disease and Mtb spreads through air droplets during coughing and sneezing. The global prevalence of TB in 2019 is approximately 10 million people. Global TB report of World Health Organization (WHO) has reported 5,946,816 pulmonary tuberculosis (PTB) patients, 206,030 patients with MDR/rifampicin-resistant (RR), and 12,350 patients with extensively drug-resistant (XDR) TB globally in 2019 [2]. The cases of pulmonary tuberculosis are higher than extrapulmonary cases. The majority of TB patients (about 90%) are found to be adults, with more cases being men than women [3]. Globally, among four people, approximately one demonstrates an immunological reaction to Mtb infection and they may either remain dormant or progress to an active infection. Patients who are infected with TB but not having significant signs of the active disease were previously defined to have latent TB and more recently changed to TB infection. Tuberculosis can affect the lungs, which is named pulmonary tuberculosis (PTB), or other organs, named extrapulmonary tuberculosis (EPTB) [4].

WHO recommends to utilize the TB screening tests initially to screen high-risk individuals and further identification of pulmonary tuberculosis for rapid diagnosis and early treatment initiation [5, 6]. Rapid and feasible diagnostic methods are required to screen and diagnose active TB cases, HIV positive patients, workers having current or past history of silica exposure, identify cases in high endemic regions and having limited access to healthcare facilities [7]. Systematic diagnostic methods to screen and diagnose TB include physical examination for signs and symptoms, Chest-X Rays, conventional culture method followed by antibiotic susceptibility testing, molecular tests such as Xpert MTB/RIF [7]. WHO recommended TB diagnostic methods include light emitting diode (LED) microscopy method, BACTEC Mycobacterium Growth Indicator Tube (MGIT) 960 system, Xpert MTB/RIF, lateral flow urine lipoarabinomannan assay (LF-LAM), loop-mediated isothermal amplification (LAMP), line probe assay (LPA). Sputum smear microscopy, Xpert MTB/RIF, and LED-Fluorescence microscopy (LED-FM) are the preferred methods to use in peripheral laboratories. A summary of commonly used screening and diagnostic tests is presented in Table 1 [8]. Even though, several advanced diagnostic methods are available, rapid and accurate diagnosis of TB is still challenging [9], particularly in regions with high endemic TB. In this review we provide an overview of various currently available methods to screen and diagnose tuberculosis.

TestPrinciple/TechnologySensitivity (%)Specificity (%)Target settingComments
Chest X-RaysImaging8789Secondary & tertiary centresEven though used as screening tool for PTB, etiological agent cannot be identified.
Used to differentiate primary & secondary TB.
Sputum smear microscopyZiehl-Neelsen (Z-N) staining & microscopic detection of bacilli32–9450–99Peripheral & reference labsCannot differentiate Mtb and other acid fast bacilli
LED-fluorescence methodAuramine staining & detection by fluorescent microscope52–9794–100Peripheral & reference labs
TB Detect kitBioFM-Filter-based sputum concentration & detection by kit method.~5588Peripheral & reference labsBiosafe & equipment-free method
Conventional culture methodGrowth on Lowenstein–Jensen (LJ) media & identification by colony morphology & biochemical tests93>99Secondary & tertiary centresLonger turnaround time
BACTEC Mycobacterium Growth Indicator Tube (MGIT) 960 systemLiquid culture method with drug susceptibility testing89
(smear +ve)
73
(smear −ve)
>99Reference labsMtb identification requires additional laboratory tests
Tuberculin skin test (TST)Host immune reaction to Mtb in body87–9874–96Secondary & tertiary centresFalse +ve in BCG vaccinated, NTM infected & high endemic regions
Low sensitivity in immune-compromised individuals
Serological testsDetection of Mtb mycolic acid components & inflammatory biomarkers87–9272–83Peripheral & reference labsResults may vary depending upon host metabolic and disease states
Interferon gamma release
assay (IGRA)
Immune response against Mtb antigen in bloodQFT (75–84)QFT (75–91)Secondary & tertiary centresNot recommended to predict active TB and treatment decisions
Lateral Flow urine lipoarabinomannan (LF-LAM)Antigen (mycobacterial cell wall components) detection in urine4492Reference labsCross reacts with other mycobacterial species & fungi
Xpert MTB/RIFNAAT qPCR98 (smear and culture +ve)99 (smear and culture −ve)Distric or sub-district
labs
Limited utility in resource-limited settings
Loop-mediated isothermal amplification (LAMP)NAAT76–8097–98Reference labsSimple method to use in resource-limited settings & high endemic regions

Table 1.

Commonly used tests for screening and diagnosis of TB and detection of drug resistance.

Key: PTB – pulmonary tuberculosis, TB – tuberculosis, Mtb – M. tuberculosis, LED - light emitting diode, BCG - Bacillus Calmette Guerin, NMT - nontuberculous mycobacteria, QFT - QuantiFERON-TB Gold, NAAT - nucleic acid amplifcation test, qPCR – quantitative PCR.

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2. Clinical diagnosis

The clinical manifestations of tuberculosis occur only in 5–10% of infected patients. In majority of TB patients, pulmonary tuberculosis is reported which affects mostly the lower respiratory system. The common clinical signs of pulmonary tuberculosis include hemoptysis, productive and prolonged cough, low-grade fever, loss of appetite, fatigue, night sweats, malaise, and weight loss [10]. Tubercle bacilli can also infect other body sites such as lymph nodes, kidneys, bone, joints, and meninges and is called extrapulmonary TB and its clinical signs and symptoms depend on the body sites being affected [11].

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3. Radiography

Chest X-Ray (CXR) is a common diagnostic tool that differentiates primary and secondary TB. Primary TB is manifested by the presence of a single lesion in the middle or lower-right lobe and enlarged draining lymph nodes. CXR shows endogenous reactivation in the apical site and typical lymph nodes with multiple secondary tubercles. In addition, miliary lesions spread throughout the lungs [12]. Even though Chest X-Ray detects pulmonary TB, it cannot identify its etiological agent.

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4. Advances in microscopy

Ziehl–Neelsen (ZN) stain is a traditional and common method and the sample is termed “smear positive” or “smear negative”, based on the presence or absence of Acid Fast Bacilli (AFB). The sensitivity of traditional ZN stain is lower and requires bacillary load of 5000–10,000 CFU/ml in sputum. In addition, it cannot differentiate Mtb and other acid-fast bacilli. The sensitivity of microscopic detection of Mtb is improved with fluorescence using carbolfuchsin and flourochromes such as Auramine-rhodamine which has been widely supported by WHO [8].

Recent developments in light emitting diode technology (LED) have increased the utility of fluorescent microscopy. LED microscopes use fluorescent stains and are more sensitive in pathogen detection. To maximize the identification, multiple sputum specimens can be collected and examined on the first visit itself, rather than asking the patient at a later date. WHO has endorsed front-loading, or so-called 1-day diagnosis under defined programmatic condition [13]. ‘TBDetect’ kit is a bio-safe and fluorescent microscopy filter (BioFM-Filter) based method and increased the diagnostic efficiency of smear microscopy and LED method due to increased performance, feasibility and safety considerations. TBDetect kit concentrates sputum by filtration using BioFM-Filter. The sensitivity of TBDetect is 20%, LED-Fluorescence microscopy (LED-FM) is 16.1% and ZN microscopy is 16% [14]. This equipment-free TBDetect kit is more potential in TB diagnosis and has more utility in routine laboratory settings. However, when compared with Xpert MTB/RIF for examining pulmonary and extrapulmonary TB in specimens of sputum, urine, gastric aspirates, and others, LED-FM has less sensitivity in Mtb detection [15].

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5. Advances in culture

All acid-fast bacilli are not M. tuberculosis and for definitive identification of pathogen, sputum smear microscopy and culturing of Mtb on suitable medium are required [16]. Sputum culturing is a sensitive method which can detect viable bacilli as low as 10 to 100 in volume of a few tenths of an ml. Culture method is more sensitive than sputum smear microscopy, in which sputum sample must have at least 5000 AFB/ml to get a positive result. The tubercle bacilli can be cultured on Lowenstein-Jensen (L-J) medium, egg-based medium and Ogawa’s medium [17]. The L-J medium has glycerol that improves Mtb growth, but not Mycobacterium bovis, whereas sodium pyruvate enhances M. bovis and few strains of drug-resistant Mtb culture in the medium [18].

WHO recommends the use of dual medium, solid medium (e.g. Lowenstein–Jensen or Middlebrook 7H11) and liquid medium (e.g. for use with the BACTEC Mycobacterium Growth Indicator Tube (MGIT) 960 system) to increase the sensitivity, specificity and avoid contamination and reduce turnaround time. The use of liquid culture medium in identification and drug-susceptibility testing (DST) was endorsed by WHO in 2007. BACTEC™MGIT™960 system contains liquid Middlebrook 7H9 medium that detects the increasing fluorescence signals, every 60 minutes, automatically as oxygen is consumed by growing bacilli. Oxygen quenches the fluorescent compound present at the bottom of MGIT. Growing Mtb uses oxygen in the MGIT and subsequently, the fluorescent compound is detected [19]. Currently used two models of BACTEC system are BACTEC460 and BACTEC MGIT960. BACTEC MGIT960 is a user-friendly system with having non-radiometric and continuous signal monitoring system and is more advanced than BACTEC460 [20]. The MGIT technology yields result in less than 8 days. Addition of Streptomycin, INH, rifampicin and ethambutanol at critical concentrations allows Automated MGIT technology to detect drug susceptibility. Mycobacterial culture remained the gold standard method for detection and drug susceptibility testing [4]. However, in MGIT method species identification of Mtb requires additional laboratory tests, and hence its utility is limited. Micro MGIT system is more advanced as it does not need any special instrument other than UV lamp for fluorescence detection and hence utility of Micro MGIT is more in resource-limited settings [21].

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6. Serological tests

Several commercially available antibody-based TB diagnostic tests are on the market, but clinical validation and current test performance are poor. Serum biomarkers are considered potential in diagnosing TB. Devising specific and accurate biomarkers which are consistent in different HIV status, ethnicities, and sites of TB infection is difficult; however, C-reactive protein, interferon-γ, interferon-γ inducible protein-10, fibrinogen, α2-macroglobulin, matrix metalloproteinase-9, transthyretin, complement factor H, and tumor necrosis factor-α have shown as potential biomarkers with 92% sensitivity and 72% specificity in detecting TB [22]. Trehalose esters of mycolic acids of Mtb cell wall lipids have been used in serological tests to diagnose PTB and the assay showed 87% sensitivity and 83% specificity [23]. If commercial methods are developed for these biomarkers, the serum assay would be rapid and effective in determining whether the patient needs further diagnostic testing. Most of these biomarkers are inflammatory markers and vary widely among patients depending upon their metabolic and disease states. Even though WHO is recommending against using commercial serological assays, antibodies, and combinations of antigens in the test panel improved performance of TB screening tests [24].

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7. Interferon gamma release assays

Past or current Mtb infection can be detected by measuring T-cell mediated interferon-gamma that are secreted following subsequent stimulation with specific Mtb antigens. QuantiFERON-TB Gold In-Tube assay (QFT-GIT, Cellestis Ltd., Australia) and the T-SPOT.TB (Oxford Immunotec, UK) are the two commercially available interferon-gamma release assay (IGRA) kits. These assay kits detect Mtb infection in blood samples by detecting plasma levels of immune cells secreted gamma interferon. The interferon gamma-specific Mtb antigens include early secretory antigenic target-6 (ESAT-6), culture filtrate protein 10 (CFP-10), and tuberculosis 7.7 antigens. The blood sample is considered TB positive if the gamma interferon levels are above a specified threshold [13, 25]. However, previous studies conducted in children and adults across the globe have reported that these two IGRA assays cannot differentiate latent Mtb infection from active tuberculosis disease and are less efficient than tuberculin skin test (TST). IGRA-based QIAreach QFT is a new and simplified version of QFT-PLUS. QIAreach QFT provides qualitative analysis using a fluorescence lateral flow reader, transportable, user-friendly and does not require well-trained personnel [26]. However, few reviews and meta-analyses have reported neither IGRA nor TST is highly accurate in predicting active tuberculosis. IGRA is not recommended for treatment decisions for suspected cases of TB instead UK National Institute for Health and Clinical Excellence guidelines and WHO suggest using IGRA as a supportive screening test in diagnostic laboratories particularly in low-and middle-income countries having high tuberculosis and HIV-infected patients [27, 28]. A negative result of IGRA assay may not definitively exclude active TB infection in a high-risk group. Compared to TSTs, IGRAs are more specific in infections caused by non-tuberculosis mycobacteria but they are wrongly marketed as a confirmatory TB test despite their limited clinical utility. IGRAs are more expensive and need tedious sample processing for accuracy in results. Even though IGRA evaluation studies and its recommendations required many years, effort, funding, and resources across the globe, it did not have a major contribution to successful tuberculosis control [13]. A recent meta-analysis has shown that heparin-binding hemagglutinin (HBHA) is a latency-associated Mtb antigen and HBHA-induced IGRA can be a promising diagnostic test to differentiate latent and active TB [29]. IGRA testing is also a cost-effective screening method [30].

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8. Tuberculin skin test

Tuberculin skin test (TST) was introduced around 100 years ago but is still in use for an initial TB screening to detect Mtb exposure in many countries. In TST purified protein derivative (PPD) tuberculin is injected intradermally and after 48–72 h the induration is measured (≥5 mm is considered positive) at the injected site to detect the individual’s immune response. The accurate TST result depends on well-experienced personnel for intradermal injection of PPD and its interpretation. The test is a simple and suitable method to detect Mtb exposure in geographical areas with rare TB cases, the test may be false positive in individuals from high endemic areas, vaccinated to Bacillus Calmette Guerin (BCG) and infected with non-tuberculous mycobacteria. However, TST has low sensitivity in immune-compromised patients [31].

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9. GeneXpert

The most significant development toward tuberculosis diagnosis was NAAT-based GeneXpert. It is a real-time PCR-based multifunctional, automated, point-of-care (POC), user-friendly diagnostic system. In GeneXpert M. tuberculosis complex and rifampicin (RIF) resistance (targets rpoB gene for RIF resistance and associated M. tuberculosis–specific flanking regions) can be simultaneously detected in 2 h of time. The sensitivity of GeneXpert is higher than the sputum smear microscopy and culture method. The assay has utility in detecting extra pulmonary tuberculosis with sensitivities of 53–95%. In addition to high sensitivity, the assay provides high specificity without any cross-reaction with nontuberculous mycobacteria. Among children having pulmonary tuberculosis, GeneXpert rapidly detects all the smear positive and 61% of smear-negative samples after two induced sputum samples. GeneXpert is successfully used for routine screening of patients before antiretroviral treatment [13].

Even though GeneXpert detects RIF resistance in initial multicentre evaluation with high sensitivity and specificity, few studies have reported that rpoB gene sequencing and other methods have detected false-positive RIF resistance in areas of low RIF resistance prevalence [32, 33]. Although GeneXpert is a long-awaited development in TB diagnosis, it may not be feasible in settings with a lack of infrastructure for working on real-time PCR and computers. The requirement of annual maintenance of equipment is another hindrance. To overcome the challenges, corrective measures are introduced, including the revision of diagnostic device software and redesigning cartridge oligonucleotide probes and the newer software and combination of the oligonucleotide probes, called G4 version cartridge is released [34].

As sputum smear microscopy and culture methods are having several limitations, WHO recommended Xpert (MTB/RIF or MTB/RIF Ultra) or Truenat (MTB or MTB Plus) in TB suspected individuals. These biomolecular diagnostic tests are also recommended to identify extra pulmonary TB and pediatric TB cases. This cartridge system is nucleic acid amplification tests (NAATs) based method and within 2 h of turnaround time detects the presence of Mtb DNA as well as mutations in rpoB which is a rifampicin drug resistance-associated gene [35, 36, 37]. Xpert assays are successful in diagnosing PTB in adults with 89% sensitivity and 99% specificity. The Xpert MTB/RIF Ultra assay is less specific than Xpert MTB/RIF assay as it fails to differentiate between dormant and active TB DNA samples. In addition, these assays are less sensitive in detecting Mtb in children and patients co-infected with HIV and extrapulmonary TB [38, 39, 40]. To overcome the limitations of high cost, and need of an uninterrupted power supply and to make these methods affordable in rural areas, several smaller and battery-operated technologies are in process. Currently, GeneXpert-Omni (Omni;Cepheid) is a promising, cost-effective, portable tool for widespread use in peripheral healthcare settings. It ensures point-of-care and is portable hence reducing the cost and time involved in transporting the specimens to central laboratories.

In addition to Omni, Cepheid is developing Xpert MTB/XDR assay to cover the detection of resistance to INH, FQL, ethionamide (ETH), and SLID. Similar to other Xpert assays, it is also a NAAT-based assay detecting 16 clinically significant mutations associated with resistance in 90 minutes. When compared to phenotypic drug sensitivity testing (pDST), it has 94% sensitivity and 100% specificity in detecting drug resistance [41]. Several large-scale multicentre clinical trials are currently ongoing in establishing it as a follow-on test to existing methods of Xpert MTB/RIF and MTB/RIF Ultra. The diagnostic performance of Xpert MTB/XDR needs to be improved for the early identification of drug resistance and shorter drug regimens.

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10. Loop-mediated isothermal amplification (LAMP)

LAMP is a rapid, easy, inexpensive, and highly specific NAAT-based method used to diagnose infectious diseases. It utilizes different sets of primers (minimum 4) which can identify the target sequence by recognizing distinct regions (minimum 6) of target gene giving high amplification efficiency with a sensitivity of 76–80% and 97–98%. It is a single-step amplification-based strand displacement reaction of approximately 15–60 min at a constant temperature of 65°C and subsequent amplicon detection by visual inspection of incorporated fluorescence [8]. It is a simple method and does not use any expensive reagents or equipment for result interpretation and can be used as a rapid diagnostic tool in resource-limited settings and high endemic regions [42, 43]. For diagnosing EPTB, LAMP assay has higher sensitivity [44].

11. Line probe assay

Line probe assay (LPA) is a rapid PCR-based method that amplifies DNA from Mtb and immobilization of oligonucleotides on a strip. In the presence of gene mutations, immobilized oligonucleotides emit a colorimetric signal indicating isoniazid or rifampicin drugs resistance as well as drug-sensitive strains in the sample [45]. LPAs are efficient to detect drug-resistant strains of Mtb in smear-positive samples [46] and has optimal diagnostic accuracy in smear-negative TB cases [47]. WHO has endorsed LPA as the initial detection method of multidrug-resistant TB (MDR) for isoniazid and rifampicin resistance in both pulmonary and extrapulmonary TB patients [48]. LPA-based commercial products for TB drug resistance include INNO-LiPA Rif TB Kit (Innogenetics, Zwijndrecht, Belgium), GenoType MTBDRplus (Hain Lifesciences-Bruker, Nehren, Germany), and Nipro NTM + MDRTB II (Osaka, Japan). Fluoroquinolone (FLQs) resistance can be detected by a more sensitive and new-generation LPA method (GenoType MTBDRsl version 2.0; Hain Lifesciences-Bruker) [8]. SL-LPA MTBDRs1 ((Hain Lifescience, Germany) is a second-generation line probe assay. MTBDRs1 (version 1.0) detects mutations in gyrA, rrs, embB genes and version 2.0 detects additional mutations in gyrB and eis promoter region. Even though LPA is a cost-minimizing method [49], its accuracy varies, and WHO has limited its utility in XDR-TB surveillance [48].

12. ddPCR (digital droplet PCR)

Droplet digital PCR (ddPCR) is a newly emerging technology and is being utilized in recent developments. In ddPCR, sample is diluted and partitioned into several hundred and millions of reaction chambers (Figure 1) [50]. Each separate chamber contains single or more copies of target sequence while rest do not contain target sequence and provides higher sensitivity than qPCR, detects single copy of DNA, and provides absolute quantification of gene expression [50]. This technique is used as a reference method in absolute quantification and detection of mutant DNA of drug-resistant subpopulations of Mtb [51]. The ddPCR has a higher sensitivity than quantitative or qPCR and Mtb infection can be detected in sputum and blood specimens of pulmonary and extrapulmonary TB patients [52, 53]. Though ddPCR detects a single copy of DNA per sample, is potent in absolute quantification, and works for both sputum and blood samples, it is prohibitively expensive and requires an uninterrupted power supply [25].

Figure 1.

Schematic Representation of principle of droplet digital PCR: Sample containing target sequence is partitioned into several droplets (in the magnitude of thousands) and then amplified separately. Each of these droplets are read by a dedicated droplet reader and fluorescence intensities are measured (indicative of positive/negative reactions) KEY: DNA – deoxyribonucleic acid.

13. CRISPR

Combined use of Clustered Regularly InterSPaced Repeats or CRISPR and CRISPR ASsociated nuclease 9, Cas9 is an approach involving a programmable enzyme which cuts DNA at specific sites (Figures 2 and 3) [25]. CRISPR is potential in detecting pediatric TB [54]. This test is a highly sensitive method with single-copy DNA detection, requires less sample requirement and a short turnaround time than Xpert method for detecting both pulmonary and extrapulmonary TB [55, 56]. CRISPR associated enzymes are used in SHERLOCK (specific-high sensitivity enzymatic reporter unlocking) platform which detects a single copy of RNA or DNA. This isothermal-based SHERLOCK technology can be used in places where electricity or portable readers are not available [57]. The combined LAMP and CRISPR-Cas12b detection method are more efficient in smear-negative paucibacillary TB patients [58].

Figure 2.

Schematic Representation of the CRISPR/Cas9 system: GuideRNA (gRNA) binds with Cas9 enzyme to form a complex. Cas9 endonuclease nicks the DNA a few bases upstream to a Protospacer Adjacent Motif (PAM) and mediates the cleavage of target DNA regions which are complementary to the gRNA. Key: RNA – ribonucleic acid, CRISPR/Cas9 - CRISPR (clustered regularly interspaced short palindromic repeat)-associated protein 9, crRNA - CRISPR RNA, tracrRNA - trans-activating crRNA.

Figure 3.

Schematic Representation of the CRISPR/Cas12a system: CRISPR RNA binds with Cas12a enzyme and forms a complex. Fluorescent probes (C) are in the periphery binding to quenchers (Q) with an oligonucleotide. The enzyme cleaves the target DNA and subsequently probes which activates the fluorescent signals. Key: CRISPR/Cas12a - CRISPR (clustered regularly interspaced short palindromic repeat)-associated protein 12a, DNA – Deoxyribonucleic acid.

14. MicroRNA detection

MicroRNAs have an active role in several biological processes and are used as biomarkers in diagnosis, treatment, and prognosis of a wide range of diseases including tuberculosis. Circulating mRNAs are consistent among individuals, stable, and least influenced by endogenous RNAse activity. MicroRNA expression studies in plasma samples of pulmonary TB patients and normal individuals have identified smiR-769-5p, miR-320a, and miR-22-3p as potent plasma-based biomarkers in TB diagnosis and miR-320a levels were significantly higher in drug-resistant TB [59]. In addition, plasma miRNA levels of hsa-miR-29a-3p, hsa-miR-155-5p, and hsa-miR-361-5p were found to be significantly upregulated in active tuberculosis compared to normal individuals. This plasma-based detection method is a convenient way of diagnosing TB in a population where it is difficult to obtain sputum, especially in pediatrics and extrapulmonary TB cases [60]. These circulating plasma miRNAs can further enable the differential diagnosis of latent and active TB. Diagnostic performance of miRNA can be increased by integrating serum miRNAs with diagnostic models developed by miRNA characteristics and electronic health records (HERs) [61, 62] and bioinformatics analysis [63]. Even though miRNA-based detection of TB is convenient in diagnosis in children, the method is challenging to adopt in resource-limited settings. In addition, the efficacy of the test depends on the correct sequence of miRNA. A considerable number of miRNAs are identified in children TB cases and only 7% of them are considered significant for the test [64].

15. Handheld electronic nose model

The handheld electronic nose model is a point-of-care and portable model and it can be used for tuberculosis screening in remote rural areas and health care settings and to rule out TB test in vulnerable populations [65]. This device detects infection via the presence of volatile organic compounds (VOC). The Aeonose (eNose BV, Zutphen, Netherlands) is an example of such model and this device has sensors and pre-concentrator. The patient needs to breathe through Aeonose via a disposable mouthpiece for 5 minutes. Breath data will be generated on the laptop and analyzed through the website of eNose. The preliminary results showed poor sensitivity and specificity in suspected tuberculosis patients. The portable and short turnaround time for results (< 5 minutes), makes the model more suitable in rural areas [66, 67].

16. Raman spectroscopy

Raman Spectroscopy (SR) is another diagnostic tool used to diagnose cancer and bacterial infections. It is a portal device and can be used in rural areas [68]. The phenomenon of Raman scattering is used to identify unique molecular markers of bacteria upon excitation with a particular wavelength of light. A combination of Surface-Enhanced Raman Spectroscopy (SERS) with a bead-beating module of a lab-on-a-chip (LOC) device can successfully differentiate Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM) [69]. SR with less cost, and short turnaround time is potential enough to diagnose active tuberculosis and latent tuberculosis [70]. The combination of SR with an optical microscope is useful in non-destructive identification of a single bacterial cell. SR is a rapid, user-friendly, non-invasive method for identification of pathogens. In addition, integration of machine learning can make SR a more effective TB screening method [71]. A recent study on developing PCR-based SERS has reported it can rapidly distinguish TB positive rifampicin-resistant and TB positive rifampicin-susceptible patients [72].

17. Artificial intelligence

The application of artificial intelligence (AI) along with historical methods of tuberculosis diagnosis such as Chest-X rays and smear microscopy is rapidly increasing and minimizes human errors in the interpretation of results [73, 74]. AI technology is in its initial stages which need to be validated with a large number of sample sizes. Depending upon the population used such as HIV co-infected patients or pediatrics, the results of AI vary widely [75]. Further, AI is under consideration by WHO as a technique to diagnose tuberculosis. In addition, the result images can be transferred via mobile phone technology from rural settings to server site and data can be analyzed with AI [76]. Artificial intelligence can be used to diagnose pulmonary and extrapulmonary TB [77] and to predict drug-resistant and drug-susceptible Mtb strains [78].

18. Electrochemical biosensor platform

Arginine film-based biosensor platform is a new PCR-free method used in the detection of tubercle bacilli. IS6110 gene is used as a biomarker. The probe corresponding to IS6110 gene will be immobilized on the biosensor platform and hybridized with a sputum sample or isolated DNA sample. The target gene will be identified based on electrochemical analysis using the principle of pulse voltammetry and methylene blue reduction signal measurement. The biosensor is a portable device with high sensitivity and selectivity for TB diagnosis [79]. An electrochemical device (EC) can be integrated to loop mediated isothermal amplification (LAMP) PCR for rapid detection of tubercle bacilli. LAMP-EC functions with a screen-printed graphene electrode (SPGE), redox probe, and a portable potentiostat for diagnosis of tuberculosis. The biosensor is a portable device. DNA isolation and hybridization with the sputum sample can be performed at room temperature, therefore, it can be used in rural areas [80].

19. Whole genome sequencing (WGS)

Whole genome sequencing (WGS) data has 96% concordance with culture-based drug sensitivity testing. It provides comprehensive detail of Mtb whole genome and genotypic sensitivity data to most drugs used in the treatment of MDR-TB. The correlation between genotypic results of WGS and phenotypic sensitivities is yet fully explored. WGS ideally can detect all the mutations in the genome and their functional characteristics [81]. This technique can be applied for genotypic and phenotypic characterization of organisms and profiling of drug susceptibility [82, 83] including detecting mutations in new drugs such as bedaquiline and delamanid [84]. The performance of WGS technology is further enhanced by incorporating a novel method ‘SplitStrains’ which helps to analyze WGS data of patients having mixed infections [85]. Due to high cost, the need of robust technologies, and technical expertise, initially, there was limited WGS utility in low-income countries [86]. In some countries, it is used as an important tool for case diagnosis and formulation of public health policies to trace TB contact cases in outbreak [87]. Even though NAAT and LPA methods are rapid, feasible, and accessible, detection of mutations in regions other than rifampicin resistance-associated gene rpoB is challenging. It is reported that 95% of resistance is due to mutations in this region, and WGS with the advanced genomics data on TB resistance can develop as a revolutionary to tailor TB treatment of each patient [4].

20. Flow cytometry assays of the M. tuberculosis: specific T-cell responses

The functional profile of T-cell mediated Mtb-specific responses to active disease and latent Mtb infection can be detected using polychromatic flow cytometry. Tuberculosis-specific flow cytometry panel comprises markers such as CD3, CD4, and CD8 which determine T-cell lineage, and interleukin 2, interferon-gamma, and tumor necrosis factor-alpha (TNF-a) antibodies as cytokine functional profile. TNF-α specific CD4 T cells are reported as a predictive marker to differentiate between active disease and the latent Mtb infection. The CD4 T-cell marker has higher sensitivity of 100% and specificity of 96% [88]. Even though flow cytometry is a highly sensitive method, antiretinal antibodies, and associated CD4+ T cells were not found significant in latent TB-associated uveitis or sarcoid uveitis patients [89].

21. Urine-based diagnostic tests

Urine samples ensure a non-invasive method of detection assays and are easy to collect from both adults, particularly in HIV-coinfected TB patients and children. Commercial methods are available to detect tuberculosis in urine samples. Unlike NAAT detecting Mtb DNA, lateral flow urine lipoarabinomannan (LF-LAM) test detects Mtb infection by identifying lipopolysaccharide of mycobacterial cell walls in urine samples. Even though commonly not used in many countries, LF-LAM is recommended to use in HIV-coinfected patients. LAM test helps early detection of TB and lowers TB deaths in people living with HIV (PLHIV) [90, 91]. It can be often used in low-resource settings and it is beneficial in patients in whom obtaining sputum samples is difficult. It has 42% sensitivity in HIV-coinfected having TB symptoms. However, the specificity is less as it cross-reacts with other mycobacterial species and fungi. Thus currently, it is recommended to use as an initial screening test in rural healthcare centers of high endemic areas with TB infection [92, 93].

Few studies reported lower sensitivity of LAM in patients with non-HIV infections and moderate to higher specificity in patients coinfected with HIV and having advanced immunodeficiency [94]. Many tuberculosis diagnostic tests are less sensitive in HIV-infected patients having advanced immunodeficiency but the sensitivity of LAM enzyme-linked immunosorbent assay (ELISA) is high even at lower CD4 lymphocyte cell counts. In most TB patients with CD4 cell count <50 cells/μl detectable amount of LAM antigen in urine is reported and it can be tested using TB-LAM Ag urine dip-stick assays. This advanced assay is a point-of-care lateral flow, low-cost ($3.50 per test), and highly specific in patient with advanced HIV-associated immunodeficiency [13].

22. Conclusion

Diagnosis of tuberculosis needs a rapid with possible reporting on the same day of sample collection and making a quick therapy decision. Current existing methods of the tuberculin skin test, smear microscopy, immunological test, and conventional PCR method still face several challenges for optimal diagnosis. Tuberculin skin test shows false positive results in certain populations such as patients with prior BCG vaccine, children with Mtb infection, HIV co-infected patients. Sputum AFB stain is a quick and easy method, it is not a confirmatory for Mtb as nontuberculous mycobacteria also take up the stain and even symptomatic patients may remain undiagnosed or undergo delayed diagnosis. Volatile Organic Compounds (VOC), LF-LAM and eNose assays in Mtb patients have some future potential. These non-invasive and cost-effective tests are useful in children or critically ill patients.

Conventional diagnostic methods are used as routine diagnostic methods, however, WHO recommends next-generation of NAATs as they provide fast and reliable results as point-of-care diagnostics in peripheral healthcare settings. Advanced methods of GeneXpert MTB/RIF (GX) are highly sensitive and specific one-step PCR-based methods with a short turnaround time of 2 h. NAAT-based GeneXpert is routinely used in clinical settings in many countries. In summary, in the current technological development, WHO recommends POC-NAATs (2nd generations) in addition to GeneXpert MTB/RIF and peripheral laboratories and the WGS method in at least reference laboratories in near future for TB diagnosis.

Acknowledgments

KSS thank Ms. Apoorva Jnana, PhD scholar, Department of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India for help.

Conflict of interest

The authors declare no conflict of interest.

Authors contributions

Both the authors contributed for the idea of the manuscript, literature review and data analysis. First draft was written by PK and critically revised by KSS. Both the authors read and approved the final version of the manuscript.

References

  1. 1. Wirth T, Hildebrand F, Allix-Beguec C, Wolbeling F, Kubica T, Kremer K, et al. Origin, spread and demography of the Mycobacterium tuberculosis complex. PLoS Pathogens. 2008;4(9):e1000160. DOI: 10.1371/journal.ppat.1000160
  2. 2. World Health Organization. Multidrug-Resistant Tuberculosis (MDR-TB)-2015. UPDATE. Geneva, Switzerland: WHO; 2015
  3. 3. Suliman S, Pelzer PT, Shaku M, Rozot V, Mendelsohn SC. Meeting report: Virtual global forum on tuberculosis vaccines, 20-22 April 2021. Vaccine. 2021;39(50):7223-7229. DOI: 10.1016/j.vaccine.2021.08.094 Epub 2021 Sep 15
  4. 4. Gill CM, Dolan L, Piggott LM, McLaughlin AM. New developments in tuberculosis diagnosis and treatment. Breathe. 2022;18(1):210149. DOI: 10.1183/20734735.0149-2021 Epub 2021 Mar 8
  5. 5. World Health Organization. Tuberculosis diagnostics. Geneva, Switzerland: WHO; 2016
  6. 6. World Health Organization. Tuberculosis Policy Statements. Geneva, Switzerland: WHO; 2018
  7. 7. World Health Organization. Systematic Screening for Active Tuberculosis: Principles and Recommendations. Geneva, Switzerland: WHO; 2013
  8. 8. Acharya B, Acharya A, Gautam S, Ghimire SP, Mishra G, Parajuli N, et al. Advances in diagnosis of tuberculosis: An update into molecular diagnosis of Mycobacterium tuberculosis. Molecular Biology Reports. 2020;47(5):4065-4075. DOI: 10.1007/s11033-020-05413-7 Epub 2020 Apr 4
  9. 9. Sulis G, Centis R, Sotgiu G, D’Ambrosio L, Pontali E, Spanevello A, et al. Recent developments in the diagnosis and management of tuberculosis. NPJ Primary Care Respiratory Medicine. 2016;26:16078. DOI: 10.1038/npjpcrm.2016.78
  10. 10. World Health Organization. Global Tuberculosis Report 2017. Geneva, Switzerland: WHO; 2017
  11. 11. Golden MP, Vikram HR. Extrapulmonary tuberculosis: An overview. American Family Physician. 2005;72(9):1761-1768
  12. 12. McMurray DN. Baron’s Medical Microbiology Textbook (online textbook). Galveston: University of Texas Medical Branch; 2001
  13. 13. McNerney R, Maeurer M, Abubakar I, Marais B, McHugh TD, Ford N, et al. Tuberculosis diagnostics and biomarkers: Needs, challenges, recent advances, and opportunities. Journal of Infectious Diseases. 2012;205(Suppl 2):S147-S158. DOI: 10.1093/infdis/jir860 Epub 2012 Apr 10
  14. 14. Anthwal D, Gupta RK, Gomathi NS, Tripathy SP, Das D, Pati S, et al. Evaluation of 'TBDetect' sputum microscopy kit for improved detection of Mycobacterium tuberculosis: A multi-centric validation study. Clinical Microbiology and Infection. 2021;27(6):911.e1-911.e7. DOI: 10.1016/j.cmi.2020.08.020 Epub 2020 Aug 21
  15. 15. Combo Georges TA, Aissata T, Fatimata D, Abou CC, Gagni C, Moise SA, et al. Performance of Xpert MTB/RIF in comparison with light-emitting diode-fluorescence microscopy and culture for detecting tuberculosis in pulmonary and extrapulmonary specimens in Bamako. Mali. International Journal of Mycobacteriology. 2020;9(4):397-304. DOI: 10.4103/ijmy.ijmy_171_20
  16. 16. Nema V. Tuberculosis diagnostics: Challenges and opportunities. Lung India. 2012;29(3):259-266. DOI: 10.4103/0970-2113.99112
  17. 17. Grange JM. Tuberculosis: Topley and Wilson’s Principle of Bacteriology, Virology and Immunity. 8th ed. Vol. II. London: Butler and Tanner Ltd; 1990. pp. 93-118
  18. 18. Watt B, Rayner A, Harris G. Mackie and McCartney Practical Medical Microbiology. 4th ed. International Student Edition. Churchill Livingstone: Edinburgh; 1996
  19. 19. Zhao P, Yu Q , Chen L, Zhang M. Evaluation of a liquid culture system in the detection of mycobacteria at an antituberculosis institution in China; A retrospective study. Journal of International Medical Research. 2016;44(5):1055-1060. DOI: 10.1177/0300060516655243 Epub 2016 Sep 29
  20. 20. Cruciani M, Scarparo C, Malena M, Bosco O, Serpelloni G, Mengoli C. Meta-analysis of BACTEC MGIT 960 and BACTEC 460 TB, with or without solid media, for detection of mycobacteria. Journal of Clinical Microbiology. 2004;42(5):2321-2325. DOI: 10.1128/JCM.42.5.2321-2325.2004
  21. 21. Rajani M, Banerjee M. Evaluation of various diagnostic techniques for the diagnosis of pulmonary and extra pulmonary tuberculosis at a tertiary care center in North India. Infectious Disorders Drug Targets. 2020;20(4):433-439. DOI: 10.2174/1871526519666191011165702
  22. 22. Morris TC, Hoggart CJ, Chegou NN, Kidd M, Oni T, Goliath R, et al. Evaluation of host serum protein biomarkers of tuberculosis in sub-Saharan Africa. Frontiers in Immunology. 2021;12:639174. DOI: 10.3389/fimmu.2021.639174
  23. 23. Jones A, Pitts M, Al Dulayymi JR, Gibbons J, Ramsay A, Goletti D, et al. New synthetic lipid antigens for rapid serological diagnosis of tuberculosis. PLoS One. 2017;12(8):e0181414. DOI: 10.1371/journal.pone.0181414
  24. 24. Jaganath D, Rajan J, Yoon C, Ravindran R, Andama A, Asege L, et al. Evaluation of multi-antigen serological screening for active tuberculosis among people living with HIV. PLoS One. 2020;15(6):e0234130. DOI: 10.1371/journal.pone.0234130
  25. 25. MacGregor-Fairlie M, Wilkinson S, Besra GS, Goldberg OP. Tuberculosis diagnostics: Overcoming ancient challenges with modern solutions. Emerging Topics in Life Sciences. 2020;4(4):423-436. DOI: 10.1042/ETLS20200335
  26. 26. Miotto P, Goletti D, Petrone L. Making IGRA testing easier: First performance report of QIAreach QFT for tuberculosis infection diagnosis. Pulmonology. 2022;28(1):4-5. DOI: 10.1016/j.pulmoe.2021.07.010 Epub 2021 Oct 28
  27. 27. World Health Organization. Use of Interferon-g Release Assays (IGRAs) in TB Control in Low and Middle-income Settings. Geneva, Switzerland: WHO; 2010
  28. 28. National Institute for Health and Clinical Excellence. NICE Clinical Guideline 117. Tuberculosis: Clinical Diagnosis and Management of Tuberculosis, and Measures for its Prevention and Control. London: National Institute for Health and Clinical Excellence; 2011
  29. 29. Tang J, Huang Y, Cai Z, Ma Y. Mycobacterial heparin-binding hemagglutinin (HBHA)-induced interferon-γ release assay (IGRA) for discrimination of latent and active tuberculosis: A systematic review and meta-analysis. PLoS One. 2021;16(7):e0254571. DOI: 10.1371/journal.pone.0254571
  30. 30. Al Abri S, Kowada A, Yaqoubi F, Al Khalili S, Ndunda N, Petersen E. Cost-effectiveness of IGRA/QFT-Plus for TB screening of migrants in Oman. International Journal of Infectious Diseases. 2020;92S:S72-S77. DOI: 10.1016/j.ijid.2020.03.010 Epub 2020 Mar 18
  31. 31. Titus K. TB Testing: New Approaches to Old Scourge. CAP Today; 2018. Available from: https://www.captodayonline.com/tb-testing-new-approaches-old-scourge/
  32. 32. Lawn SD, Brooks SV, Kranzer K, Nicol MP, Whitelaw A, Vogt M, et al. Screening for HIV-associated tuberculosis and rifampicin resistance before antiretroviral therapy using the Xpert MTB/RIF assay: A prospective study. PLoS Medicine. 2011;8(7):e1001067. DOI: 10.1371/journal.pmed.1001067 Epub 2011 Jul 26
  33. 33. Marlowe EM, Novak-Weekley SM, Cumpio J, Sharp SE, Momeny MA, Babst A, et al. Evaluation of the Cepheid Xpert MTB/RIF assay for direct detection of mycobacterium tuberculosis complex in respiratory specimens. Journal of Clinical Microbiology. 2011;49(4):1621-1623. DOI: 10.1128/JCM.02214-10 Epub 2011 Feb 2
  34. 34. FIND. Performance of Xpert MTB/RIF Version G4 Assay. Geneva: Foundation for Innovative New Diagnostics; 2011
  35. 35. Lawn SD, Mwaba P, Bates M, Piatek A, Alexander H, Marais BJ, et al. Advances in tuberculosis diagnostics: The Xpert MTB/RIF assay and future prospects for a point-of-care test. Lancet Infectious Diseases. 2013;13(4):349-361. DOI: 10.1016/S1473-3099(13)70008-2 Epub 2013 Mar 24
  36. 36. World Health Organisation. Global Tuberculosis Report 2020. Geneva, Switzerland: WHO; 2020
  37. 37. Kohli M, Schiller I, Dendukuri N, Yao M, Dheda K, Denkinger CM, et al. Xpert MTB/RIF Ultra and Xpert MTB/RIF assays for extrapulmonary tuberculosis and rifampicin resistance in adults. Cochrane Database of Systematic Reviews. 2021;1(1):CD012768. DOI: 10.1002/14651858.CD012768.pub3
  38. 38. Steingart KR, Schiller I, Horne DJ, Pai M, Boehme CC, Dendukuri N. Xpert® MTB/RIF assay for pulmonary tuberculosis and rifampicin resistance in adults. Cochrane Database of Systematic Reviews. 2014;2014(1):CD009593. DOI: 10.1002/14651858.CD009593.pub3 Update in: Cochrane Database of Systematic Reviews. 2019;6:CD009593
  39. 39. Arend SM, van Soolingen D. Performance of Xpert MTB/RIF Ultra: A matter of dead or alive. Lancet Infectious Diseases. 2018;18(1):8-10. DOI: 10.1016/S1473-3099(17)30695-3 Epub 2017 Dec 5
  40. 40. Dorman SE, Schumacher SG, Alland D, Nabeta P, Armstrong DT, King B, et al. Xpert MTB/RIF ultra for detection of Mycobacterium tuberculosis and rifampicin resistance: A prospective multicentre diagnostic accuracy study. Lancet Infectious Diseases;18(1):2018, 76-2084. DOI: 10.1016/S1473-3099(17)30691-6 Epub 2017 Nov 30. Erratum in: Lancet Infect Dis. 2018 Feb 21
  41. 41. Cao Y, Parmar H, Gaur RL, Lieu D, Raghunath S, Via N, et al. Xpert MTB/XDR: a 10-color reflex assay suitable for point-of-care settings to detect isoniazid, fluoroquinolone, and second-line-injectable-drug resistance directly from mycobacterium tuberculosis-positive sputum. Journal of Clinical Microbiology. 2021;59(3):e02314-e02320. DOI: 10.1128/JCM.02314-20
  42. 42. Pandey BD, Poudel A, Yoda T, Tamaru A, Oda N, Fukushima Y, et al. Development of an in-house loop-mediated isothermal amplification (LAMP) assay for detection of Mycobacterium tuberculosis and evaluation in sputum samples of Nepalese patients. Journal of Medical Microbiology. 2008;57(Pt 4):439-443. DOI: 10.1099/jmm.0.47499-0
  43. 43. Phetsuksiri B, Rudeeaneksin J, Srisungngam S, Bunchoo S, Klayut W, Nakajima C, et al. Comparison of loop-mediated isothermal amplification, microscopy, culture, and PCR for diagnosis of pulmonary tuberculosis. Japanese. Journal of Infectious Diseases. 2020;73(4):272-277. DOI: 10.7883/yoken.JJID.2019.335 Epub 2020 Feb 28
  44. 44. Singh P, Kanade S, Nataraj G. Performance of loop-mediated isothermal amplification assay for diagnosis of extrapulmonary tuberculosis and antituberculosis treatment initiation. International Journal of Mycobacteriology. 2021;10(4):373-378. DOI: 10.4103/ijmy.ijmy_218_21
  45. 45. World Health Organization. Molecular Line Probe Assays for Rapid Screening of Patients at Risk of Multidrug-resistant Tuberculosis. Geneva, Switzerland: WHO; 2008
  46. 46. Yadav RN, Kumar Singh B, Sharma R, Chaubey J, Sinha S, Jorwal P. Comparative performance of line probe assay (Version 2) and Xpert MTB/RIF assay for early diagnosis of rifampicin-resistant pulmonary tuberculosis. Tuberculosis and Respiratory Diseases. 2021;84(3):237-244. DOI: 10.4046/trd.2020.0171 Epub 2021 Mar 3
  47. 47. Singh BK, Sharma SK, Sharma R, Sreenivas V, Myneedu VP, Kohli M, et al. Diagnostic utility of a line probe assay for multidrug resistant-TB in smear-negative pulmonary tuberculosis. PLoS One. 2017;12(8):e0182988. DOI: 10.1371/journal.pone.0182988
  48. 48. World Health Organization. The Use of Molecular Line Probe Assays for the Detection of Resistance to Second-line Anti-tuberculosis Drugs. Geneva, Switzerland: WHO; 2016
  49. 49. Bogdanova EN, Mariandyshev AO, Balantcev GA, Eliseev PI, Nikishova EI, Gaida AI, et al. Cost minimization analysis of line probe assay for detection of multidrug-resistant tuberculosis in Arkhangelsk region of Russian Federation. PLoS One. 2019;14(1):e0211203. DOI: 10.1371/journal.pone.0211203
  50. 50. Nyaruaba R, Mwaliko C, Kering KK, Wei H. Droplet digital PCR applications in the tuberculosis world. Tuberculosis. 2019;117:85-92. DOI: 10.1016/j.tube.2019.07.001 Epub 2019 Jul 3
  51. 51. Rigouts L, Miotto P, Schats M, Lempens P, Cabibbe AM, Galbiati S, et al. Fluoroquinolone heteroresistance in Mycobacterium tuberculosis: Detection by genotypic and phenotypic assays in experimentally mixed populations. Scientific Reports. 2019;9(1):11760. DOI: 10.1038/s41598-019-48289-9
  52. 52. Yang J, Han X, Liu A, Bai X, Xu C, Bao F, et al. Use of digital droplet PCR to detect mycobacterium tuberculosis DNA in whole blood-derived DNA samples from patients with pulmonary and extrapulmonary tuberculosis. Frontiers in Cellular and Infection Microbiology. 2017;7:369. DOI: 10.3389/fcimb.2017.00369
  53. 53. Luo J, Luo M, Li J, Yu J, Yang H, Yi X, et al. Rapid direct drug susceptibility testing of Mycobacterium tuberculosis based on culture droplet digital polymerase chain reaction. International Journal of Tuberculosis and Lung Disease. 2019;23(2):219-225. DOI: 10.5588/ijtld.18.0182
  54. 54. Lyu C, Shi H, Cui Y, Li M, Yan Z, Yan L, et al. CRISPR-based biosensing is prospective for rapid and sensitive diagnosis of pediatric tuberculosis. International Journal of Infectious Diseases. 2020;101:183-187. DOI: 10.1016/j.ijid.2020.09.1428 Epub 2020 Sep 25
  55. 55. Li SY, Cheng QX, Liu JK, Nie XQ , Zhao GP, Wang J. CRISPR-Cas12a has both cis- and trans-cleavage activities on single-stranded DNA. Cell Research. 2018;28(4):491-493. DOI: 10.1038/s41422-018-0022-x Epub 2018 Mar 12
  56. 56. Ai JW, Zhou X, Xu T, Yang M, Chen Y, He GQ , et al. CRISPR-based rapid and ultra-sensitive diagnostic test for Mycobacterium tuberculosis. Emerging Microbes & Infections. 2019;8(1):1361-1369. DOI: 10.1080/22221751.2019.1664939
  57. 57. Gootenberg JS, Abudayyeh OO, Kellner MJ, Joung J, Collins JJ, Zhang F. Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6. Science. 2018;360(6387):439-444. DOI: 10.1126/science.aaq0179 Epub 2018 Feb 15
  58. 58. Sam IK, Chen YY, Ma J, Li SY, Ying RY, Li LX, et al. TB-QUICK: CRISPR-Cas12b-assisted rapid and sensitive detection of Mycobacterium tuberculosis. Journal of Infection. 2021;83(1):54-60. DOI: 10.1016/j.jinf.2021.04.032 Epub 2021 May 2
  59. 59. Cui JY, Liang HW, Pan XL, Li D, Jiao N, Liu YH, et al. Characterization of a novel panel of plasma microRNAs that discriminates between Mycobacterium tuberculosis infection and healthy individuals. PLoS One. 2017;12(9):e0184113. DOI: 10.1371/journal.pone.0184113
  60. 60. Ndzi EN, Nkenfou CN, Mekue LM, Zentilin L, Tamgue O, Pefura EWY, et al. MicroRNA hsa-miR-29a-3p is a plasma biomarker for the differential diagnosis and monitoring of tuberculosis. Tuberculosis (Edinburgh, Scotland). 2019;114:69-76. DOI: 10.1016/j.tube.2018.12.001 Epub 2018 Dec 6
  61. 61. Hu X, Liao S, Bai H, Wu L, Wang M, Wu Q , et al. Integrating exosomal microRNAs and electronic health data improved tuberculosis diagnosis. eBioMedicine. 2019;40:564-573. DOI: 10.1016/j.ebiom.2019.01.023 Epub 2019 Feb 8
  62. 62. Gao SH, Chen CG, Zhuang CB, Zeng YL, Zeng ZZ, Wen PH, et al. Integrating serum microRNAs and electronic health records improved the diagnosis of tuberculosis. Journal of Clinical Laboratory Analysis. 2021;35(8):e23871. DOI: 10.1002/jcla.23871 Epub 2021 Jun 9
  63. 63. Deng S, Shen S, El-Ashram S, Lu H, Luo D, Ye G, et al. Selecting hub genes and predicting target genes of microRNAs in tuberculosis via the bioinformatics analysis. Genetics Research. 2021;2021:6226291. DOI: 10.1155/2021/6226291
  64. 64. Togun TO, MacLean E, Kampmann B, Pai M. Biomarkers for diagnosis of childhood tuberculosis: A systematic review. PLoS One. 2018;13(9):e0204029. DOI: 10.1371/journal.pone.0204029
  65. 65. Coronel Teixeira R, IJdema D, Gómez C, Arce D, Roman M, Quintana Y, et al. The electronic nose as a rule-out test for tuberculosis in an indigenous population. Journal of Internal Medicine. 2021;290(2):386-391. DOI: 10.1111/joim.13281
  66. 66. Saktiawati AMI, Stienstra Y, Subronto YW, Rintiswati N, Sumardi GJW, Oord H, et al. Sensitivity and specificity of an electronic nose in diagnosing pulmonary tuberculosis among patients with suspected tuberculosis. PLoS One. 2019a;14(6):e0217963. DOI: 10.1371/journal.pone.0217963
  67. 67. Saktiawati AMI, Putera DD, Setyawan A, Mahendradhata Y, van der Werf TS. Diagnosis of tuberculosis through breath test: A systematic review. eBioMedicine. 2019b;46:202-214. DOI: 10.1016/j.ebiom.2019.07.056 Epub 2019 Aug 8
  68. 68. Lorenz B, Wichmann C, Stockel S, Rosch P, Popp J. Cultivation-free raman spectroscopic investigations of bacteria. Trends in Microbiology. 2017;25(5):413-424. DOI: 10.1016/j.tim.2017.01.002 Epub 2017 Feb 7
  69. 69. Muhlig A, Bocklitz T, Labugger I, Dees S, Henk S, Richter E, et al. LOC-SERS: A promising closed system for the identification of mycobacteria. Analytical Chemistry. 2016;88(16):7998-7904. DOI: 10.1021/acs.analchem.6b01152 Epub 2016 Jul 29
  70. 70. Kaewseekhao B, Nuntawong N, Eiamchai P, Roytrakul S, Reechaipichitkul W, Faksri K. Diagnosis of active tuberculosis and latent tuberculosis infection based on Raman spectroscopy and surface-enhanced Raman spectroscopy. Tuberculosis. 2020;121:101916. DOI: 10.1016/j.tube.2020.101916 Epub 2020 Feb 18
  71. 71. Ullah R, Khan S, Chaudhary II, Shahzad S, Ali H, Bilal M. Cost effective and efficient screening of tuberculosis disease with Raman spectroscopy and machine learning algorithms. Photodiagnosis and Photodynamic Therapy. 2020;32:101963. DOI: 10.1016/j.pdpdt.2020.101963 Epub 2020 Sep 21
  72. 72. Dastgir G, Majeed MI, Nawaz H, Rashid N, Raza A, Ali MZ, et al. Surface-enhanced Raman spectroscopy of polymerase chain reaction (PCR) products of Rifampin resistant and susceptible tuberculosis patients. Photodiagnosis and Photodynamic Therapy. 2022;38:102758. DOI: 10.1016/j.pdpdt.2022.102758 Epub 2022 Feb 11
  73. 73. Shah MI, Mishra S, Yadav VK, Chauhan A, Sarkar M, Sharma SK, et al. Ziehl-Neelsen sputum smear microscopy image database: A resource to facilitate automated bacilli detection for tuberculosis diagnosis. Journal of Medical Imaging. 2017;4(2):027503. DOI: 10.1117/1.JMI.4.2.027503 Epub 2017 Jun 30
  74. 74. Qin ZZ, Sander MS, Rai B, Titahong CN, Sudrungrot S, Laah SN, et al. Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems. Scientific Reports. 2019;9(1):15000. DOI: 10.1038/s41598-019-51503-3
  75. 75. Harris M, Qi A, Jeagal L, Torabi N, Menzies D, Korobitsyn A, et al. A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis. PLoS One. 2019;14(9):e0221339. DOI: 10.1371/journal.pone.0221339
  76. 76. Wahl B, Cossy-Gantner A, Germann S, Schwalbe NR. Artificial intelligence (AI) and global health: How can AI contribute to health in resource-poor settings? BMJ Global Health. 2018;3(4):e000798. DOI: 10.1136/bmjgh-2018-000798
  77. 77. Sharma A, Sharma A, Malhotra R, Singh P, Chakrabortty RK, Mahajan S, et al. An accurate artificial intelligence system for the detection of pulmonary and extra pulmonary Tuberculosis. Tuberculosis. 2021;131:102143. DOI: 10.1016/j.tube.2021.102143 Epub 2021 Nov 10
  78. 78. Jamal S, Khubaib M, Gangwar R, Grover S, Grover A, Hasnain SE. Artificial intelligence and machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis. Scientific Reports. 2020;10(1):5487. DOI: 10.1038/s41598-020-62368-2 Erratum in: Sci Rep. 2020 Sep 1;10(1):14660
  79. 79. Eloi P, Nascimento GA, Cordula C, Visani V, Castelletti H, Bezerra G, et al. Toward a point-of-care diagnostic for specific detection of Mycobacterium tuberculosis from sputum samples. Tuberculosis. 2020;121:101919. DOI: 10.1016/j.tube.2020.101919 Epub 2020 Mar 3
  80. 80. Jaroenram W, Kampeera J, Arunrut N, Karuwan C, Sappat A, Khumwan P, et al. Graphene-based electrochemical genosensor incorporated loop-mediated isothermal amplification for rapid on-site detection of Mycobacterium tuberculosis. Journal of Pharmaceutical and Biomedical Analysis. 2020;186:113333. DOI: 10.1016/j.jpba.2020.113333 Epub 2020 May 1
  81. 81. Wells WA, Boehme CC, Cobelens FG, Daniels C, Dowdy D, Gardiner E, et al. Alignment of new tuberculosis drug regimens and drug susceptibility testing: A framework for action. Lancet Infectious Diseases. 2013;13(5):449-458. DOI: 10.1016/S1473-3099(13)70025-2 Epub 2013 Mar 24
  82. 82. Witney AA, Gould KA, Arnold A, Coleman D, Delgado R, Dhillon J, et al. Clinical application of whole-genome sequencing to inform treatment for multidrug-resistant tuberculosis cases. Journal of Clinical Microbiology. 2015;53(5):1473-1483. DOI: 10.1128/JCM.02993-14 Epub 2015 Feb 11
  83. 83. Votintseva AA, Bradley P, Pankhurst L, Del Ojo EC, Loose M, Nilgiriwala K, et al. Same-day diagnostic and surveillance data for tuberculosis via whole-genome sequencing of direct respiratory samples. Journal of Clinical Microbiology. 2017;55(5):1285-1298. DOI: 10.1128/JCM.02483-16 Epub 2017 Mar 8
  84. 84. Bloemberg GV, Keller PM, Stucki D, Trauner A, Borrell S, Latshang T, et al. Acquired resistance to Bedaquiline and Delamanid in therapy for tuberculosis. New England Journal of Medicine. 2015;373(20):1986-1988. DOI: 10.1056/NEJMc1505196 Erratum in: New England Journal of Medicine. 2015;373(25):e29. Stuckia, David [corrected to Stucki, David]
  85. 85. Gabbassov E, Moreno-Molina M, Comas I, Libbrecht M, Chindelevitch L. SplitStrains, a tool to identify and separate mixed Mycobacterium tuberculosis infections from WGS data. Microbial Genomics. 2021;7(6):000607. DOI: 10.1099/mgen.0.000607
  86. 86. Eddabra R, Ait BH. Rapid molecular assays for detection of tuberculosis. Pneumonia. 2018;10:4. DOI: 10.1186/s41479-018-0049-2
  87. 87. Roycroft E, Fitzgibbon MM, Kelly DM, Scully M, McLaughlin AM, Flanagan PR, et al. The largest prison outbreak of TB in Western Europe investigated using whole-genome sequencing. International Journal of Tuberculosis and Lung Disease. 2021;25(6):491-497. DOI: 10.5588/ijtld.21.0033
  88. 88. Harari A, Rozot V, Bellutti Enders F, Perreau M, Stalder JM, Nicod LP, et al. Dominant TNF-α+ Mycobacterium tuberculosis-specific CD4+ T cell responses discriminate between latent infection and active disease. Nature Medicine. 2011;17(3):372-376. DOI: 10.1038/nm.2299 Epub 2011 Feb 20
  89. 89. Schrijver B, Hardjosantoso H, Ten Berge JCEM, Schreurs MWJ, Van Hagen PM, Brooimans RA, et al. No evidence for circulating retina specific autoreactive T-cells in latent tuberculosis-associated uveitis and sarcoid uveitis. Ocular Immunology and Inflammation. 2021;29(5):883-889. DOI: 10.1080/09273948.2019.1698752 Epub 2020 Jan 8
  90. 90. Ricks S, Denkinger CM, Schumacher SG, Hallett TB, Arinaminpathy N. The potential impact of urine-LAM diagnostics on tuberculosis incidence and mortality: A modelling analysis. PLoS Medicine. 2020;17(12):e1003466. DOI: 10.1371/journal.pmed.1003466
  91. 91. Nathavitharana RR, Lederer P, Chaplin M, Bjerrum S, Steingart KR, Shah M. Impact of diagnostic strategies for tuberculosis using lateral flow urine lipoarabinomannan assay in people living with HIV. Cochrane Database of Systematic Reviews. 2021;8(8):CD014641. DOI: 10.1002/14651858.CD014641
  92. 92. Bjerrum S, Schiller I, Dendukuri N, Kohli M, Nathavitharana RR, Zwerling AA, et al. Lateral flow urine lipoarabinomannan assay for detecting active tuberculosis in people living with HIV. Cochrane Database of Systematic Reviews. 2019;10(10):CD011420. DOI: 10.1002/14651858.CD011420.pub3 Epub ahead of print
  93. 93. Engel N, Mwaura M. Lateral flow urine lipoarabinomannan assay (LF-LAM) for the diagnosis of active tuberculosis in people living with HIV: Policy update (2019): Report user perspectives on TB LAM testing: Results from qualitative research. World Health Organization. Available from: https://apps.who.int/iris/handle/10665/329513. License: CC BY-NC-SA 3.0 IGO
  94. 94. Minion J, Leung E, Talbot E, Dheda K, Pai M, Menzies D. Diagnosing tuberculosis with urine lipoarabinomannan: Systematic review and meta-analysis. European Respiratory Journal. 2011;38(6):1398-1405. DOI: 10.1183/09031936.00025711 Epub 2011 Jun 23

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Prakruthi Shivakumar and Kavitha Sunil Shettigar

Reviewed: 17 August 2022 Published: 19 November 2022