Engineered Mycobacterium tuberculosis antigen assembly into core-shell nanobeads for diagnosis of tuberculosis

Abstract

Despite recent advances in diagnosis, tuberculosis (TB) remains one of the ten leading causes of death worldwide. Here, we engineered Mycobacterium tuberculosis (Mtb) proteins (ESAT6, CFP10, and MTB7.7) to self-assemble into core-shell nanobeads for enhanced TB diagnosis.Respective purified Mtb antigen-coated polyester beads were characterized and their functionality in TB diagnosis was tested in whole blood cytokine release assays. Sensitivity and specificity were studied in 11 pulmonary TB patients (PTB) and 26 healthy individuals composed of 14 Tuberculin Skin Test negative (TSTn) and 12 TST positive (TSTp). The production of 6 cytokines was determined (IFNγ, IP10, IL2, TNFα, CCL3, and CCL11). To differentiate PTB from healthy individuals (TSTp + TSTn), the best individual cytokines were IL2 and CCL11 (>80% sensitivity and specificity) and the best combination was IP10 + IL2 (>90% sensitivity and specificity). We describe an innovative approach using full-length antigens attached to biopolyester nanobeads enabling sensitive and specific detection of human TB.

Spotlight on mycobacterial lipid exploitation using nanotechnology for diagnosis, vaccines, and treatments

“…According to original and systematic analyses, good diagnostic performances are achieved only with multiple markers, 81. , 82. , 83.…”

Challenges and the Way forward in Diagnosis and Treatment of Tuberculosis Infection

“…The Mtb-specific immune response showed that multiple cytokines, i.e., IFN-γ, IL-2, IL-6, IL-8, IP-10, MCP-1, MIP-1β, and TNF-α, were released when blood from patients with TB (cultured-confirmed) is stimulated with Mtb Ags (ESAT-6+CFP-10+TB7.7) [ 49 ]. Our team also demonstrated that the cytokine levels after the stimulation with fusion proteins of these Ags in coated polyester nanobeads could be used to differentiate PTB, TST + , and TST − healthy individuals by measuring the difference or ratio with unstimulated cytokine levels [ 116 ]. IL-2 and CCL11 were the best individual cytokines to differentiate between PTB and healthy individuals (TST + and TST − ) with a sensitivity and specificity of >80%, and the best combinations were IP-10+IL-2 and IFN-γ+IP-10+IL-2 with a sensitivity and specificity of >90%.…”

“…IL-2 and CCL11 were the best individual cytokines to differentiate between PTB and healthy individuals (TST + and TST − ) with a sensitivity and specificity of >80%, and the best combinations were IP-10+IL-2 and IFN-γ+IP-10+IL-2 with a sensitivity and specificity of >90%. These markers also had a similar sensitivity to differentiate between PTB and TBI (TST + ) [ 116 ]. Immunological profiles with multiple markers showed that IFN-γ, IP-10, IL-2, IL-6, CCL3, and CCL8 could not only be used as biomarker signatures for TBI, but also to elucidate the risk of reactivation [ 117 ].…”

“…Here, we will discuss the suitability of commonly reported cytokines/chemokines, including IL-2, IP-10, TNF-α, IL-10, and VEGF as adjunct markers for IGRA to aid in the diagnosis of TBI based on serum profiles at unstimulated and stimulated conditions, and a literature search, including meta-analysis studies. The determination of multiple cytokines upon stimulation with Mtb-specific Ags may help identify potential biomarkers for the diagnosis of TB and discriminate ATB from TBI, as shown in Table 3 [ 116 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 ].…”

Nanotechnology on agent identification, diseases diagnosis and therapeutic approaches

“…In the clinical field, nanoparticles cover different sectors, from diagnosis and to treatment of infectious and noninfectious diseases (Malekjahani et al, 2019;Noor et al, 2020;Sadani et al, 2020). For instance, diagnostic tools have used nanoparticles to detect specific molecules, whether they are proteins, DNA, or other markers of interest (Cinti et al, 2017;Rizzo et al, 2021;Sheffee et al, 2021;Vaquer et al, 2021) Thus, technological advances in nanoparticle production and development can lead to more efficient, low cost, and labelfree based medical devices (Gahlawat & Choudhury, 2019).…”