Periodic Reporting for period 1 - DET-TB (Detection of the different phases of Mycobacterium tuberculosis infection and prediction of the development of tuberculosis disease progression by application of novel interferon gamma release assay)
Periodo di rendicontazione: 2023-11-01 al 2025-10-31
Sintesi del contesto e degli obiettivi generali del progetto
Tuberculosis (TB) remains one of the world’s leading infectious killers, second only to COVID-19, and continues to pose a major global health threat. Despite being a preventable and curable disease, gaps in early detection, timely treatment, and prevention strategies have led to persistent transmission and increased mortality. The End TB Strategy set by the World Health Organization (WHO) emphasizes the urgent need for innovative diagnostic and therapeutic tools to accelerate TB control and elimination. However, current diagnostic methods, such as the tuberculin skin test (TST) and interferon-gamma release assays (IGRAs), are unable to accurately distinguish between latent, incipient, subclinical, and active forms of TB or to predict disease progression. This diagnostic limitation hinders effective patient management and undermines public health interventions.
The overall objective of this project was to identify and validate novel Mycobacterium tuberculosis (Mtb) antigens that can be used to develop next-generation immunodiagnostic assays capable of differentiating various phases of TB infection and predicting progression to active disease.
The overall objective of this project was to identify and validate novel Mycobacterium tuberculosis (Mtb) antigens that can be used to develop next-generation immunodiagnostic assays capable of differentiating various phases of TB infection and predicting progression to active disease.
Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti
1.2.1 Work Package 1
Explain the work carried out in WP1 during the reporting period giving details of the work carried out by each beneficiary/affiliated entity involved.
Objectives: O 1.1 In silico identification and immunity characterization of latency-associated proteins of Mtb and antigens actively secreted in the first growth phase that elicit TB-specific CD8+ T cells
For the selection of DosR regulon proteins of Mtb, we utilized the bioinformatic tools. At first, the full-length protein sequences of all the DosR regulon proteins retrieved from Mycobrowser server (https://mycobrowser.epfl.ch/(si apre in una nuova finestra)). The retrieved sequence subjected to VaxiJen server (https://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html(si apre in una nuova finestra)) and other bioinformatic tools to identify the antigenic proteins.
Binding prediction methods were used for the selection of potential epitopes. The methods are developed using experimental peptide binding data for different MHC alleles to train machine learning algorithms that in turn can be used to predict the binding for any arbitrary peptide.
• MHC class I and MHC class II binding epitopes
MHC I binding epitopes play a significant in the immune response by allowing cytotoxic T lymphocytes (CTLs) to recognize the infection. Similarly, the MHC II binding epitopes play a crucial role in presenting antigens to helper T lymphocytes. Therefore, we identified the MHC I and MHC II binding epitopes within the selected antigenic DosR regulon proteins of Mtb using the Immune Epitope Database Analysis Resource (http://tools.iedb.org/main/(si apre in una nuova finestra)). The IEDB provides sequences of all possible peptides or epitopes for the specified length along with the predicted binding affinity (IC50) for each epitope. The epitopes with the IC50 < 100nM (a threshold associated with immunogenicity), were selected for further analysis.
• Immunological characterization
Prediction of the antigenicity, allergenicity, and toxicity of epitopes is crucial for the elicitation of robust immune responses and identifying potential adverse reactions. To achieve this, a variety of bioinformatics tools were employed. Initially, the epitopes exhibiting strong binding affinity (IC50 < 100nM) were subjected to VaxiJen to predict their antigenicity. Additionally, the epitopes will also be subjected to ToxinPred (http://crdd.osdd.net/raghava/toxinpred/(si apre in una nuova finestra)) and AllerTOP (https://www.ddg-pharmfac.net/AllerTOP/(si apre in una nuova finestra)) for the prediction of their toxicity and allergenicity, respectively. Similarly, understanding the cytokine profile induced by the epitopes is vital in the cell-mediated immunity. Therefore, the IFN-γ inducibility of epitopes were evaluated using INFepitope (https://webs.iiitd.edu.in/raghava/ifnepitope/(si apre in una nuova finestra)). Finally, epitopes meeting the specified criteria were selected for further analysis.
• Prediction of 3D structure
For the prediction of 3D structure of DosR regulon proteins of Mtb, the computational homology modelling were employed. The sequences of the protein were subjected to newest AlphaFold3 for the structure prediction.
• Mapping of immunogenic regions of the proteins
The localization of epitopes is crucial within the 3D structure of the protein, as surface epitopes serve as targets for antibody binding and function as recognition sites for the immune system. Therefore, the location of each immunogenic epitope within its DosR regulon protein were evaluated to predict their ability to trigger an immune response. In this connection, the initial step involves merging overlapping epitopes or peptide sequences, treating them collectively as a single epitope. Following this, the merged sequence will undergo evaluation to ascertain its retention of immunogenic characteristics. Finally, the location of all the obtained immunogenic epitopes within the 3D structure of their DosR regulon protein were visually analyzed.
The full-length protein sequences of 5 resuscitation promoting factor (RPF) proteins (Rv0867c, Rv1009, Rv1884c, Rv2389c, Rv2450c) were downloaded from the Mycobrowser server. We have also used software such as Vaxijen2.0 IEDB-AR, PSIPRED, GenTHREADER, MEMSAT-2 and IFNEpitope server to make our predictions. Using the Vaxijen2.0 software, we have identified some interesting antigenic scores for each promiscuous epitope. Our threshold score was set at 0.5 which is considered antigenic; based on the promiscuity and the scores, we selected the best peptide epitopes for further study. The sequences were subsequently subjected to Immune Epitope Database Analysis Resource (IEDB-AR) to predict MHC-II binding epitopes. All the human alleles were selected and the prediction method used was NN-align 2.3.
We also ran the sequence of predicted epitopes through VaxiJen v2.0 and IFNepitope server to predict antigenicity, and IFN-γ inducing epitopes. In case of Rv0867c, total of seven epitopes were predicted to be antigenic and positive inducer of IFN-γ, however, five epitopes were overlapped which led to the selection of only three epitopes. Similarly, in case of Rv1009, three epitopes were predicted to be antigenic and positive inducer of IFN-γ, however, two epitopes were overlapped which led to the selection of only two epitopes. Similarly, in case of Rv1884c and Rv2389c, only one epitope was predicted to be antigenic and positive inducer of IFN-γ. In case of Rv2450c, three epitopes were predicted to be antigenic and positive inducer of IFN-γ, however, two epitopes were overlapped which led to the selection of only two epitopes. Additionally, a selection of random epitopes was also made for each Rpf, contributing to the expansion of our dataset. For the prediction of 3D structure of Rpf proteins of Mtb, the sequences were subjected to Alphafold. The best predicted obtained 3D model of each protein was selected for further analysis. The location of each immunogenic epitope within its Rpf protein was located. At first, the overlapping epitopes were merged and considered as a single epitope. Following this, the merged sequence was evaluated to ascertain their retention of immunogenic characteristics. Finally, the location all the obtained immunogenic epitopes within the 3D structure of their Rpf protein was visually analyzed. For the prediction of the 3D structure of Rpf, the computational homology modelling was employed. As the Protein DataBank did not have a crystallized structure for Rpf, the 3D structure was predicted using AlphaFold. The best predicted model for each Rpf was selected for the analysis of location of epitopes. The figure 3 depicted the predicted 3D structures of all the Rpf protein along with the highlighted location of selected epitopes. The yellow color showed the epitopes that were predicted to be antigenic and positive inducer of IFN-γ, while the orange color showed the randomly selected epitopes.
The proteins included in the dataset are Rv0569, Rv1738, Rv1812c, Rv1813c, Rv1996, Rv2004c, Rv2006, Rv2028c, Rv2029c, Rv2031c, Rv2625c, Rv2628, Rv2630, Rv3129, and Rv3134c.
Progress Summary:
• All planned in silico analyses completed.
• Epitopes identified computationally.
• Milestone (epitope identification) achieved on schedule.
Work Package 2: Gene Cloning and Sub-Cloning
Objectives: O 2.1 Gene cloning and sub-cloning of small library of latency-associated proteins of Mtb and antigens actively secreted in the first growth phase that elicit TB-specific CD8+ T cells
Activities Carried Out:
• Assessed feasibility of protein production considering cost, time, and past technical challenges.
• Decision made to replace recombinant protein production with synthetic peptide synthesis.
• Ordered peptides from GenScript (≥95% purity, 4 mg each, 20 amino acids).
• Additional NCN OPUS grant obtained to partially cover peptide synthesis costs.
Progress Summary:
• Original objective partially modified due to resource constraints.
• Peptide synthesis enabled continuation of experimental work without delay.
Deliverables Completed:
Procurement of selected peptides.
Milestones Achieved:
Strategy adaptation from protein expression to peptide synthesis.
Status:
Completed
Scientific Deviations:
None
Implementation/Progress Rating:
Excellent
Training and Knowledge Transfer:
• Team members were trained on handling and storage of synthetic peptides.
• Experimental protocols were updated and communicated to all relevant personnel.
• Knowledge sharing sessions conducted on decision-making process for switching from recombinant protein to peptide synthesis.
Work package 3. Expression and Purification of Recombinant Protein, Preparation and validation of the antigens
Objectives: O 3.1 Preparation of the Mtb latency-associated proteins and proteins actively secreted in the first growth phase that elicit TB-specific CD8+ T cells
Activities Carried Out:
• Prepared 5-peptide and 10-peptide pools at 10 µg/mL, plated in triplicate.
• Included negative controls and PHA positive controls (5 µg/mL).
• Designed plate layouts to ensure reproducibility and comparability.
Progress Summary:
• Peptide pools successfully prepared and ready for immunological testing.
• Assay procedures standardized and documented.
Deliverables Completed:
• Prepared peptide pools with quality control measures.
Milestones Achieved:
• Standardized experimental setup for blood stimulation assays.
Gene cloning and sub-cloning of a small library of latency-associated Mycobacterium tuberculosis (Mtb) proteins, as well as early-secreted antigens known to elicit TB-specific CD8⁺ T-cell responses, were initially planned. However, after estimating the cost and time required for cloning, expression, and purification—and considering the host institute’s previous unsuccessful attempts to express several of these proteins in earlier projects—it was concluded that recombinant protein production was not feasible within the available resources. Consequently, the experimental strategy was revised to use synthetic peptides instead. Peptide synthesis was outsourced to a commercial provider (GenScript), which supplied peptides at >95% purity, with 4 mg obtained for each peptide. Due to budget limitations, the full cost of peptide synthesis could not be covered by the original project funds; therefore, additional financial support was obtained through an NCN OPUS grant, which partially supported the peptide procurement.
Status: Partially completed
Scientific Deviations: Due to technical and resource limitations, the initial plan to express and purify recombinant proteins was replaced with synthetic peptide synthesis. This deviation was justified by prior unsuccessful attempts at recombinant expression and cost constraints. The project adapted by ordering high-purity synthetic peptides from GenScript.
Implementation/Progress Rating: Good
Training and Knowledge Transfer: The researcher gained experience in experimental design, peptide pool preparation, and quality control measures, transferring knowledge to the host regarding peptide-based alternatives to recombinant protein production.
Work package 4. Structural analysis of selected proteins and analysis of the stability of recombinant proteins
Objectives: O 4.1 The structural analysis of the selected proteins.
five resuscitation promoting factors (RpfA-E).
This section provides structural and functional insights on five known Rpfs (A-E) as mentioned above [1-8]. To date, some truncated apo structures of Rpfs (B, C, E) or RpfB in complex with triacetyl-beta-chitotriose (triNAG) and benzamidine (BEN) were resolved, particularly catalytic domain using X-Ray or NMR spectroscopy; however, there are no available structures of RpfA and RpfD.
The Rpf family contributes to Mtb resuscitation by hydrolyzing peptidoglycan (PGN), the main component of the Mtb cell wall [9]. Structurally, all Rpfs share a conserved catalytic domain comprising approximately 70 amino acids, including six alpha helices, and adopt similar folds with each other and c-type lysosome [2].
RpfC, consisting of 176 residues, includes the catalytic domain and an N-terminal signal sequence, which is presumed to have an extracellular role [6, 7]. The catalytic domain includes Glu13 with a nearby hydrophobic pocket formed by Val9, Trp18, Leu30, Phe32, Ile55, and Trp70. Maione et al. suggest that a highly conserved disulfide bridge between Cys12-Cys73 in RpfC may modulate the shape of the catalytic cleft of RpfC [7]. Mutations in these residues (one or both) can dramatically weaken its muralytic activity and inhibit bacterial resuscitation in Mtb [7, 10].
Similar to other members of the family, RpfD (154 residues), has a catalytic domain with conserved catalytic formed by Glu61 with Ile57, Trp66, Leu78, Ile80, Ile103, and Trp118 along with a disulfide bridge (Cys60-Cys124).
Lastly, RpfE (172 residues) consists of a catalytic domain and a Pro/Ala rich domain. It contains a conserved Glu16 with a hydrophobic pocket, with disulfide bonds between Cys15 and Cys76 that are essential for its structural integrity and function, similar to other Rpfs [8]. Unlike RpfB, RpfE lacks the two short 3-10 helices found in the α2–α3 loop [8]. Additionally, the catalytic cleft of RpfE is wider than that of RpfB, resulting in a larger surface area and volume for the catalytic cleft.
Status: Completed
Scientific Deviations: Minor: Some proteins (RpfA and RpfD) lacked crystallized structures, requiring computational homology modeling via AlphaFold instead of experimental X-ray/NMR structures. This adaptation did not affect project objectives.
Implementation/Progress Rating: Excellent
Training and Knowledge Transfer: The researcher was trained in 3D protein modeling, domain analysis, and visualization tools, while sharing epitope mapping results with the host for functional interpretation.
Work package 5. Interferon-Gamma Release Assay (IGRA) using recombinant latency-associated protein
Objectives: O 5.1 Stimulation of blood sample with latency-associated proteins
O 5.2 Evaluation of diagnostic accuracy of latency-associated immunodominant antigen candidates in individuals with different phase of TB infection, and healthy controls,
Progress Summary:
• Patient recruitment and immunological assays successfully completed.
• Initial datasets generated for further analysis and planned publications.
Deliverables Completed:
• Collection and stimulation of blood samples.
• IFN-γ measurement datasets and preliminary analysis.
Milestones Achieved:
• Completion of participant recruitment.
• Completion of blood stimulation.
Status: Completed
Scientific Deviations: Minor adaptation in patient recruitment: collaborations in Poland were unsuccessful, leading to successful recruitment in Zagreb, Croatia.
Implementation/Progress Rating: Excellent
Training and Knowledge Transfer: The researcher gained experience in clinical collaboration, ethical compliance, patient sample handling, and IFN-γ immunoassays, transferring both computational and experimental expertise to the host. The host team benefited from the researcher’s in silico epitope selection expertise.
Work package 6. Project and training management
Objectives: O 6.1 Provide efficient administrative, technical and scientific management of the project, O 6.2 Provide effective training. O 6.3 Communication and dissemination of project goals, procedures and results, development of Exploitation Plan and plan of the management of IP Rights
Progress Summary:
• Administrative and scientific objectives achieved.
• Training and supervision completed as planned.
• Dissemination activities ongoing through workshops, network meetings, and planned publications.
Status: Completed
Scientific Deviations: None.
Implementation/Progress Rating: Excellent
Training and Knowledge Transfer: The researcher participated in project management, reporting, grant writing, and dissemination activities. Knowledge transfer included supervision of junior lab staff and presentations at conference
s and workshops, fostering both leadership and scientific communication skills.
Explain the work carried out in WP1 during the reporting period giving details of the work carried out by each beneficiary/affiliated entity involved.
Objectives: O 1.1 In silico identification and immunity characterization of latency-associated proteins of Mtb and antigens actively secreted in the first growth phase that elicit TB-specific CD8+ T cells
For the selection of DosR regulon proteins of Mtb, we utilized the bioinformatic tools. At first, the full-length protein sequences of all the DosR regulon proteins retrieved from Mycobrowser server (https://mycobrowser.epfl.ch/(si apre in una nuova finestra)). The retrieved sequence subjected to VaxiJen server (https://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html(si apre in una nuova finestra)) and other bioinformatic tools to identify the antigenic proteins.
Binding prediction methods were used for the selection of potential epitopes. The methods are developed using experimental peptide binding data for different MHC alleles to train machine learning algorithms that in turn can be used to predict the binding for any arbitrary peptide.
• MHC class I and MHC class II binding epitopes
MHC I binding epitopes play a significant in the immune response by allowing cytotoxic T lymphocytes (CTLs) to recognize the infection. Similarly, the MHC II binding epitopes play a crucial role in presenting antigens to helper T lymphocytes. Therefore, we identified the MHC I and MHC II binding epitopes within the selected antigenic DosR regulon proteins of Mtb using the Immune Epitope Database Analysis Resource (http://tools.iedb.org/main/(si apre in una nuova finestra)). The IEDB provides sequences of all possible peptides or epitopes for the specified length along with the predicted binding affinity (IC50) for each epitope. The epitopes with the IC50 < 100nM (a threshold associated with immunogenicity), were selected for further analysis.
• Immunological characterization
Prediction of the antigenicity, allergenicity, and toxicity of epitopes is crucial for the elicitation of robust immune responses and identifying potential adverse reactions. To achieve this, a variety of bioinformatics tools were employed. Initially, the epitopes exhibiting strong binding affinity (IC50 < 100nM) were subjected to VaxiJen to predict their antigenicity. Additionally, the epitopes will also be subjected to ToxinPred (http://crdd.osdd.net/raghava/toxinpred/(si apre in una nuova finestra)) and AllerTOP (https://www.ddg-pharmfac.net/AllerTOP/(si apre in una nuova finestra)) for the prediction of their toxicity and allergenicity, respectively. Similarly, understanding the cytokine profile induced by the epitopes is vital in the cell-mediated immunity. Therefore, the IFN-γ inducibility of epitopes were evaluated using INFepitope (https://webs.iiitd.edu.in/raghava/ifnepitope/(si apre in una nuova finestra)). Finally, epitopes meeting the specified criteria were selected for further analysis.
• Prediction of 3D structure
For the prediction of 3D structure of DosR regulon proteins of Mtb, the computational homology modelling were employed. The sequences of the protein were subjected to newest AlphaFold3 for the structure prediction.
• Mapping of immunogenic regions of the proteins
The localization of epitopes is crucial within the 3D structure of the protein, as surface epitopes serve as targets for antibody binding and function as recognition sites for the immune system. Therefore, the location of each immunogenic epitope within its DosR regulon protein were evaluated to predict their ability to trigger an immune response. In this connection, the initial step involves merging overlapping epitopes or peptide sequences, treating them collectively as a single epitope. Following this, the merged sequence will undergo evaluation to ascertain its retention of immunogenic characteristics. Finally, the location of all the obtained immunogenic epitopes within the 3D structure of their DosR regulon protein were visually analyzed.
The full-length protein sequences of 5 resuscitation promoting factor (RPF) proteins (Rv0867c, Rv1009, Rv1884c, Rv2389c, Rv2450c) were downloaded from the Mycobrowser server. We have also used software such as Vaxijen2.0 IEDB-AR, PSIPRED, GenTHREADER, MEMSAT-2 and IFNEpitope server to make our predictions. Using the Vaxijen2.0 software, we have identified some interesting antigenic scores for each promiscuous epitope. Our threshold score was set at 0.5 which is considered antigenic; based on the promiscuity and the scores, we selected the best peptide epitopes for further study. The sequences were subsequently subjected to Immune Epitope Database Analysis Resource (IEDB-AR) to predict MHC-II binding epitopes. All the human alleles were selected and the prediction method used was NN-align 2.3.
We also ran the sequence of predicted epitopes through VaxiJen v2.0 and IFNepitope server to predict antigenicity, and IFN-γ inducing epitopes. In case of Rv0867c, total of seven epitopes were predicted to be antigenic and positive inducer of IFN-γ, however, five epitopes were overlapped which led to the selection of only three epitopes. Similarly, in case of Rv1009, three epitopes were predicted to be antigenic and positive inducer of IFN-γ, however, two epitopes were overlapped which led to the selection of only two epitopes. Similarly, in case of Rv1884c and Rv2389c, only one epitope was predicted to be antigenic and positive inducer of IFN-γ. In case of Rv2450c, three epitopes were predicted to be antigenic and positive inducer of IFN-γ, however, two epitopes were overlapped which led to the selection of only two epitopes. Additionally, a selection of random epitopes was also made for each Rpf, contributing to the expansion of our dataset. For the prediction of 3D structure of Rpf proteins of Mtb, the sequences were subjected to Alphafold. The best predicted obtained 3D model of each protein was selected for further analysis. The location of each immunogenic epitope within its Rpf protein was located. At first, the overlapping epitopes were merged and considered as a single epitope. Following this, the merged sequence was evaluated to ascertain their retention of immunogenic characteristics. Finally, the location all the obtained immunogenic epitopes within the 3D structure of their Rpf protein was visually analyzed. For the prediction of the 3D structure of Rpf, the computational homology modelling was employed. As the Protein DataBank did not have a crystallized structure for Rpf, the 3D structure was predicted using AlphaFold. The best predicted model for each Rpf was selected for the analysis of location of epitopes. The figure 3 depicted the predicted 3D structures of all the Rpf protein along with the highlighted location of selected epitopes. The yellow color showed the epitopes that were predicted to be antigenic and positive inducer of IFN-γ, while the orange color showed the randomly selected epitopes.
The proteins included in the dataset are Rv0569, Rv1738, Rv1812c, Rv1813c, Rv1996, Rv2004c, Rv2006, Rv2028c, Rv2029c, Rv2031c, Rv2625c, Rv2628, Rv2630, Rv3129, and Rv3134c.
Progress Summary:
• All planned in silico analyses completed.
• Epitopes identified computationally.
• Milestone (epitope identification) achieved on schedule.
Work Package 2: Gene Cloning and Sub-Cloning
Objectives: O 2.1 Gene cloning and sub-cloning of small library of latency-associated proteins of Mtb and antigens actively secreted in the first growth phase that elicit TB-specific CD8+ T cells
Activities Carried Out:
• Assessed feasibility of protein production considering cost, time, and past technical challenges.
• Decision made to replace recombinant protein production with synthetic peptide synthesis.
• Ordered peptides from GenScript (≥95% purity, 4 mg each, 20 amino acids).
• Additional NCN OPUS grant obtained to partially cover peptide synthesis costs.
Progress Summary:
• Original objective partially modified due to resource constraints.
• Peptide synthesis enabled continuation of experimental work without delay.
Deliverables Completed:
Procurement of selected peptides.
Milestones Achieved:
Strategy adaptation from protein expression to peptide synthesis.
Status:
Completed
Scientific Deviations:
None
Implementation/Progress Rating:
Excellent
Training and Knowledge Transfer:
• Team members were trained on handling and storage of synthetic peptides.
• Experimental protocols were updated and communicated to all relevant personnel.
• Knowledge sharing sessions conducted on decision-making process for switching from recombinant protein to peptide synthesis.
Work package 3. Expression and Purification of Recombinant Protein, Preparation and validation of the antigens
Objectives: O 3.1 Preparation of the Mtb latency-associated proteins and proteins actively secreted in the first growth phase that elicit TB-specific CD8+ T cells
Activities Carried Out:
• Prepared 5-peptide and 10-peptide pools at 10 µg/mL, plated in triplicate.
• Included negative controls and PHA positive controls (5 µg/mL).
• Designed plate layouts to ensure reproducibility and comparability.
Progress Summary:
• Peptide pools successfully prepared and ready for immunological testing.
• Assay procedures standardized and documented.
Deliverables Completed:
• Prepared peptide pools with quality control measures.
Milestones Achieved:
• Standardized experimental setup for blood stimulation assays.
Gene cloning and sub-cloning of a small library of latency-associated Mycobacterium tuberculosis (Mtb) proteins, as well as early-secreted antigens known to elicit TB-specific CD8⁺ T-cell responses, were initially planned. However, after estimating the cost and time required for cloning, expression, and purification—and considering the host institute’s previous unsuccessful attempts to express several of these proteins in earlier projects—it was concluded that recombinant protein production was not feasible within the available resources. Consequently, the experimental strategy was revised to use synthetic peptides instead. Peptide synthesis was outsourced to a commercial provider (GenScript), which supplied peptides at >95% purity, with 4 mg obtained for each peptide. Due to budget limitations, the full cost of peptide synthesis could not be covered by the original project funds; therefore, additional financial support was obtained through an NCN OPUS grant, which partially supported the peptide procurement.
Status: Partially completed
Scientific Deviations: Due to technical and resource limitations, the initial plan to express and purify recombinant proteins was replaced with synthetic peptide synthesis. This deviation was justified by prior unsuccessful attempts at recombinant expression and cost constraints. The project adapted by ordering high-purity synthetic peptides from GenScript.
Implementation/Progress Rating: Good
Training and Knowledge Transfer: The researcher gained experience in experimental design, peptide pool preparation, and quality control measures, transferring knowledge to the host regarding peptide-based alternatives to recombinant protein production.
Work package 4. Structural analysis of selected proteins and analysis of the stability of recombinant proteins
Objectives: O 4.1 The structural analysis of the selected proteins.
five resuscitation promoting factors (RpfA-E).
This section provides structural and functional insights on five known Rpfs (A-E) as mentioned above [1-8]. To date, some truncated apo structures of Rpfs (B, C, E) or RpfB in complex with triacetyl-beta-chitotriose (triNAG) and benzamidine (BEN) were resolved, particularly catalytic domain using X-Ray or NMR spectroscopy; however, there are no available structures of RpfA and RpfD.
The Rpf family contributes to Mtb resuscitation by hydrolyzing peptidoglycan (PGN), the main component of the Mtb cell wall [9]. Structurally, all Rpfs share a conserved catalytic domain comprising approximately 70 amino acids, including six alpha helices, and adopt similar folds with each other and c-type lysosome [2].
RpfC, consisting of 176 residues, includes the catalytic domain and an N-terminal signal sequence, which is presumed to have an extracellular role [6, 7]. The catalytic domain includes Glu13 with a nearby hydrophobic pocket formed by Val9, Trp18, Leu30, Phe32, Ile55, and Trp70. Maione et al. suggest that a highly conserved disulfide bridge between Cys12-Cys73 in RpfC may modulate the shape of the catalytic cleft of RpfC [7]. Mutations in these residues (one or both) can dramatically weaken its muralytic activity and inhibit bacterial resuscitation in Mtb [7, 10].
Similar to other members of the family, RpfD (154 residues), has a catalytic domain with conserved catalytic formed by Glu61 with Ile57, Trp66, Leu78, Ile80, Ile103, and Trp118 along with a disulfide bridge (Cys60-Cys124).
Lastly, RpfE (172 residues) consists of a catalytic domain and a Pro/Ala rich domain. It contains a conserved Glu16 with a hydrophobic pocket, with disulfide bonds between Cys15 and Cys76 that are essential for its structural integrity and function, similar to other Rpfs [8]. Unlike RpfB, RpfE lacks the two short 3-10 helices found in the α2–α3 loop [8]. Additionally, the catalytic cleft of RpfE is wider than that of RpfB, resulting in a larger surface area and volume for the catalytic cleft.
Status: Completed
Scientific Deviations: Minor: Some proteins (RpfA and RpfD) lacked crystallized structures, requiring computational homology modeling via AlphaFold instead of experimental X-ray/NMR structures. This adaptation did not affect project objectives.
Implementation/Progress Rating: Excellent
Training and Knowledge Transfer: The researcher was trained in 3D protein modeling, domain analysis, and visualization tools, while sharing epitope mapping results with the host for functional interpretation.
Work package 5. Interferon-Gamma Release Assay (IGRA) using recombinant latency-associated protein
Objectives: O 5.1 Stimulation of blood sample with latency-associated proteins
O 5.2 Evaluation of diagnostic accuracy of latency-associated immunodominant antigen candidates in individuals with different phase of TB infection, and healthy controls,
Progress Summary:
• Patient recruitment and immunological assays successfully completed.
• Initial datasets generated for further analysis and planned publications.
Deliverables Completed:
• Collection and stimulation of blood samples.
• IFN-γ measurement datasets and preliminary analysis.
Milestones Achieved:
• Completion of participant recruitment.
• Completion of blood stimulation.
Status: Completed
Scientific Deviations: Minor adaptation in patient recruitment: collaborations in Poland were unsuccessful, leading to successful recruitment in Zagreb, Croatia.
Implementation/Progress Rating: Excellent
Training and Knowledge Transfer: The researcher gained experience in clinical collaboration, ethical compliance, patient sample handling, and IFN-γ immunoassays, transferring both computational and experimental expertise to the host. The host team benefited from the researcher’s in silico epitope selection expertise.
Work package 6. Project and training management
Objectives: O 6.1 Provide efficient administrative, technical and scientific management of the project, O 6.2 Provide effective training. O 6.3 Communication and dissemination of project goals, procedures and results, development of Exploitation Plan and plan of the management of IP Rights
Progress Summary:
• Administrative and scientific objectives achieved.
• Training and supervision completed as planned.
• Dissemination activities ongoing through workshops, network meetings, and planned publications.
Status: Completed
Scientific Deviations: None.
Implementation/Progress Rating: Excellent
Training and Knowledge Transfer: The researcher participated in project management, reporting, grant writing, and dissemination activities. Knowledge transfer included supervision of junior lab staff and presentations at conference
s and workshops, fostering both leadership and scientific communication skills.
Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)
Overview of the Results
This project delivers a comprehensive, structure-guided identification and immunological prioritisation of latency-associated and early-resuscitation antigens of Mycobacterium tuberculosis. By integrating in silico antigen screening, epitope prediction, structural modelling, and human blood-based immunological assays, the project generates a validated pipeline and a set of high-confidence antigenic targets relevant to latent TB infection (LTBI).
Key outputs include:
• Identification of 15 antigenic DosR-regulon proteins and 5 RPF proteins with high predicted immunogenicity.
• Selection of non-toxic, non-allergenic, IFN-γ–inducing CD8⁺/CD4⁺ T-cell epitopes.
• Structure-based epitope mapping using AlphaFold models, including for proteins lacking experimental structures.
• Structural and functional characterisation of the resuscitation-promoting factor (Rpf) family (A–E), providing new insights into conserved and variable immunologically relevant regions.
• Generation of human immunological datasets using synthetic peptide pools in blood stimulation assays.
Together, these results establish a robust foundation for translational TB diagnostics and vaccine development targeting latency and early reactivation—an area insufficiently addressed by current tools.
________________________________________
Results Beyond the Current State of the Art
• Shift from active-disease antigens to latency-associated targets: Most current TB diagnostics and vaccine candidates rely on antigens expressed during active infection. This project systematically addresses latency and resuscitation biology, filling a major gap.
• Structure-guided immunogenicity assessment: Unlike conventional sequence-based epitope prediction, this work integrates 3D structural information to prioritise surface-exposed and structurally stable epitopes.
• Feasible, scalable experimental strategy: The strategic shift to synthetic peptide-based assays enables reproducibility, scalability, and easier regulatory translation compared to recombinant protein approaches.
________________________________________
This project delivers a comprehensive, structure-guided identification and immunological prioritisation of latency-associated and early-resuscitation antigens of Mycobacterium tuberculosis. By integrating in silico antigen screening, epitope prediction, structural modelling, and human blood-based immunological assays, the project generates a validated pipeline and a set of high-confidence antigenic targets relevant to latent TB infection (LTBI).
Key outputs include:
• Identification of 15 antigenic DosR-regulon proteins and 5 RPF proteins with high predicted immunogenicity.
• Selection of non-toxic, non-allergenic, IFN-γ–inducing CD8⁺/CD4⁺ T-cell epitopes.
• Structure-based epitope mapping using AlphaFold models, including for proteins lacking experimental structures.
• Structural and functional characterisation of the resuscitation-promoting factor (Rpf) family (A–E), providing new insights into conserved and variable immunologically relevant regions.
• Generation of human immunological datasets using synthetic peptide pools in blood stimulation assays.
Together, these results establish a robust foundation for translational TB diagnostics and vaccine development targeting latency and early reactivation—an area insufficiently addressed by current tools.
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Results Beyond the Current State of the Art
• Shift from active-disease antigens to latency-associated targets: Most current TB diagnostics and vaccine candidates rely on antigens expressed during active infection. This project systematically addresses latency and resuscitation biology, filling a major gap.
• Structure-guided immunogenicity assessment: Unlike conventional sequence-based epitope prediction, this work integrates 3D structural information to prioritise surface-exposed and structurally stable epitopes.
• Feasible, scalable experimental strategy: The strategic shift to synthetic peptide-based assays enables reproducibility, scalability, and easier regulatory translation compared to recombinant protein approaches.
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