An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model: Combining automated radiological analysis with clinical and biomarkers data.

BACKGROUND: Tuberculosis (TB) kills approximately 1.6 million people yearly despite the fact anti-TB drugs are generally curative. Therefore, TB-case detection and monitoring of therapy, need a comprehensive approach. Automated radiological analysis, combined with clinical, microbiological, and immunological data, by machine learning (ML), can help achieve it. METHODS: Six rhesus macaques were experimentally inoculated with pathogenic Mycobacterium tuberculosis in the lung. Data, including Computed Tomography (CT), were collected at 0, 2, 4, 8, 12, 16, and 20 weeks. RESULTS: Our ML-based CT analysis (TB-Net) efficiently and accurately analyzed disease progression, performing better than standard deep learning model (LLM OpenAI's CLIP Vi4). TB-Net based results were more consistent than, and confirmed independently by, blinded manual disease scoring by two radiologists and exhibited strong correlations with blood biomarkers, TB-lesion volumes, and disease-signs during disease pathogenesis. CONCLUSION: The proposed approach is valuable in early disease detection, monitoring efficacy of therapy, and clinical decision making.

The interplay of PTEN and AKT nexus in breast cancer: a molecular perspective.

BACKGROUND: Breast cancer is a highly prevalent and life-threatening ailment that is commonly detected among the females. The downregulation of PTEN in breast cancer is associated with a poor prognosis, aggressive tumor type, and metastasis to lymph nodes, as it activates the pro-survival pathway PI3K/AKT, which is considered the ultimate proliferative pathway. MATERIAL AND METHODS: The mRNA expression of PTEN and AKT genes was investigated using RT-qPCR and TaqMan primer probe chemistry. Moreover DNA was also isolated from the same tissue samples and exonic regions of both genes were amplified for mutational analysis. The proteins expression of PTEN and AKT from seven human breast cancer cell lines was checked through western blot experiments. RESULT: The study revealed a decrease in PTEN expression in 73.3% of the samples, whereas an increase in AKT expression in 40% of samples was observed when compared to the distant normal breast tissue. Conversely, the remaining 60% of samples exhibited a decrease in AKT mRNA expression. There was no observed alteration in the genetic sequence of AKT and PTEN within the targeted amplified regions of breast cancer samples. The high levels of PTEN protein in T-47D and MDA-MB-453 resulted in a lower p-AKT. Two cell lines ZR-75-1 and MDA-MB-468 appeared to be PTEN negative on western blot but mRNA was detected on RT-qPCR. CONCLUSION: In breast cancer the status/expression of PTEN & AKT at mRNA and protein level might be obliging in forecasting the path of disease progression, treatment and prognosis.

A Chemical Probe for Dehydrobutyrine.

Bacterial phosphothreonine lyases, or phospholyases, catalyze a unique post-translational modification that introduces dehydrobutyrine (Dhb) or dehydroalanine (Dha) in place of phosphothreonine or phosphoserine residues, respectively. We report the use of a phospha-Michael reaction to label proteins and peptides modified with Dha or Dhb. We demonstrate that a nucleophilic phosphine probe is able to modify Dhb-containing proteins and peptides that were recalcitrant to reaction with thiol or amine nucleophiles under mild aqueous conditions. Furthermore, we used this reaction to detect multiple Dhb-modified proteins in mammalian cell lysates, including histone H3, a previously unknown target of phospholyases. This method should prove useful for identifying new phospholyase targets, profiling the biomarkers of bacterial infection, and developing enzyme-mediated strategies for bioorthogonal labeling in living cells.

Plasma antibody profiles in non-human primate tuberculosis.

BACKGROUND: Tuberculosis (TB) in non-human primates (NHPs) is highly contagious, requiring efficient identification of animals infected with Mycobacterium tuberculosis. Tuberculin skin test is usually used but lacks desirable sensitivity/specificity and efficiency. METHODS: We aimed to develop an immunoassay for plasma antibodies against M. tuberculosis. A key challenge is that not all infected animals contain antibodies against the same M. tuberculosis antigen. Therefore, a multiplex panel of 28 antigens (Luminex(®) -Platform) was developed. RESULTS: Data revealed antibodies against eight antigens (Rv3875, Rv3875-Rv3874 fusion, Rv3874, Rv0934, Rv3881, Rv1886c, Rv2031, Rv3841) in experimentally infected (M. tuberculosis strains: Erdman and H37Rv) NHPs (rhesus and cynomolgus macaques). In a naturally acquired M. tuberculosis infection, rhesus macaques (n = 15) with lung TB pathology (n = 10) contained antibodies to five additional antigens (Rv0831, Rv2220, Rv0054, Rv1099, and Rv0129c). CONCLUSIONS: Results suggest that this user-friendly and easily implementable multiplex panel, containing 13 M. tuberculosis antigens, may provide a high-throughput alternative for NHP TB screening.

Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings.

Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore, during the early stages of the pandemic tests were not available in any capacity. We utilized an automated machine learning (ML) approach to train and evaluate thousands of models on a clinical dataset consisting of commonly available clinical and laboratory data, along with cytokine profiles for patients (n = 150). These models were then further tested for generalizability on an out-of-sample secondary dataset (n = 120). We were able to develop a ML model for rapid and reliable screening of patients as COVID-19 positive or negative using three approaches: commonly available clinical and laboratory data, a cytokine profile, and a combination of the common data and cytokine profile. Of the tens of thousands of models automatically tested for the three approaches, all three approaches demonstrated > 92% sensitivity and > 88 specificity while our highest performing model achieved 95.6% sensitivity and 98.1% specificity. These models represent a potential effective deployable solution for COVID-19 status classification for symptomatic patients in resource-limited settings and provide proof-of-concept for rapid development of screening tools for novel emerging infectious diseases.

Dynamics of temporal immune responses in nonhuman primates and humans immunized with COVID-19 vaccines.

We assessed the humoral immune responses to a COVID-19 vaccine in a well-controlled rhesus macaque model compared to humans immunized with two mRNA vaccines over several months post-second dose. The plasma IgG levels against seven coronaviruses (including SARS-CoV-2) and antibody subtypes (IgG 1-4 and IgM) against SARS-CoV-2 were evaluated using multiplex assays. The neutralization capacity of plasma antibodies against the original SAR-CoV-2 isolate and nine variants was evaluated in vaccinated humans and non-human primates. Immunization of macaques and humans with SARS-CoV-2 vaccines induced a robust neutralizing antibody response. In non-SIV-infected adult macaques immunized with an adenoviral vector expressing S-RBD (n = 7) or N protein (n = 3), elevated levels of IgG and neutralizing antibodies were detected 2 weeks post-second dose. Immune responses to the S-RBD vaccine in SIV-infected adult macaques (n = 2) were similar to the non-SIV-infected animals. Adult humans immunized with Pfizer (n = 35) or Moderna (n = 18) vaccines developed IgG and neutralizing antibodies at 4 weeks post-second dose. In both vaccine groups, IgG 1 was the predominant subtype, followed by IgG 3. The IgG levels, including total and IgG 1,2,3 elicited by the Moderna vaccine, were significantly higher than the corresponding levels elicited by the Pfizer vaccine at 4 weeks post-second dose. A significant correlation was observed between the plasma total IgG antibody levels and neutralization titers in both macaques and humans. Furthermore, broad-spectrum neutralization antibodies against several variants of SARS-CoV-2 were detected in the plasma of both macaques and humans after two vaccinations.

A high-fat diet containing whole walnuts (Juglans regia) reduces tumour size and growth along with plasma insulin-like growth factor 1 in the transgenic adenocarcinoma of the mouse prostate model.

Prostate cancer (PCa) has been linked to fat intake, but the effects of both different dietary fat levels and types remain inconsistent and incompletely characterised. The effects on PCa in the transgenic adenocarcinoma of the mouse prostate (TRAMP) cancer model of an elevated fat (20 % of energy as fat) diet containing 155 g of whole walnuts were compared to those of an elevated fat (20 % of energy as soyabean oil) diet with matched macronutrients, tocopherols as well as a low-fat (8 % of energy as soyabean oil) diet. Mice, starting at 8 weeks of age, consumed one of the three different diets ad libitum; and prostates, livers and blood were obtained after 9, 18 or 24 weeks of feeding. No differences were observed in whole animal growth rates in either high-fat (HF) diet group, but prostate tumour weight and growth rate were reduced in the walnut diet group. Walnut diet group prostate weight, plasma insulin-like growth factor 1, resistin and LDL were lower at 18 weeks, while no statistically significant prostate weight differences by diet were seen at 9 or 24 weeks. Multiple metabolites in the livers differed by diet at 9 and 18 weeks. The walnut diet's beneficial effects probably represent the effects of whole walnuts' multiple constituents and not via a specific fatty acid or tocopherols. Moreover, as the two HF diets had dissimilar effects on prostate tumour growth rate and size, and yet had the same total fat and tocopherol composition and content, this suggests that these are not strongly linked to PCa growth.

The Rv3874-Rv3875 chimeric protein shows a promiscuous serodiagnostic potential for tuberculosis.

Tuberculosis (TB) stays a major cause of death globally after COVID-19 and HIV. An early diagnosis to control TB effectively, needs a fast reliable diagnostic method with high sensitivity. Serodiagnosis involving polyclonal antibodies detection against an antigen of Mycobacterium tuberculosis (Mtb) in serum samples can be instrumental. In our study, Rv3874 and Rv3875 antigens were cloned, expressed, and purified individually and as a chimeric construct in Escherichia coli BL21. Enzyme-Linked Immunosorbent Assay (ELISA) based findings revealed that the Rv3874-Rv3875 chimeric construct was two-fold more sensitive (59.7%) than the individual sensitivities of Rv3874 (28.4%) and Rv3875 (24.9%) for 201 serum TB positive samples. Furthermore, the fusion construct was a little more sensitive (60.4%) for male subjects than that for females (58.8%). Lastly, our preliminary findings, molecular insights of secondary structure, and statistical and in silico analysis of each construct also advocate that CEP can be considered a better immunodiagnostic tool in addition to previously reported EC skin test.

Prediction of Tuberculosis Using an Automated Machine Learning Platform for Models Trained on Synthetic Data.

High-quality medical data is critical to the development and implementation of machine learning (ML) algorithms in healthcare; however, security, and privacy concerns continue to limit access. We sought to determine the utility of "synthetic data" in training ML algorithms for the detection of tuberculosis (TB) from inflammatory biomarker profiles. A retrospective dataset (A) comprised of 278 patients was used to generate synthetic datasets (B, C, and D) for training models prior to secondary validation on a generalization dataset. ML models trained and validated on the Dataset A (real) demonstrated an accuracy of 90%, a sensitivity of 89% (95% CI, 83-94%), and a specificity of 100% (95% CI, 81-100%). Models trained using the optimal synthetic dataset B showed an accuracy of 91%, a sensitivity of 93% (95% CI, 87-96%), and a specificity of 77% (95% CI, 50-93%). Synthetic datasets C and D displayed diminished performance measures (respective accuracies of 71% and 54%). This pilot study highlights the promise of synthetic data as an expedited means for ML algorithm development.

Peripheral γδ T Cells Regulate Neutrophil Expansion and Recruitment in Experimental Psoriatic Arthritis.

OBJECTIVE: This study was undertaken to identify the mechanistic role of γδ T cells in the pathogenesis of experimental psoriatic arthritis (PsA). METHODS: In this study, we performed interleukin-23 (IL-23) gene transfer in wild-type (WT) and T cell receptor δ-deficient (TCRδ-/- ) mice and conducted tissue phenotyping in the joint, skin, and nails to characterize the inflammatory infiltrate. We further performed detailed flow cytometry, immunofluorescence staining, RNA sequencing, T cell repertoire analysis, and in vitro T cell polarization assays to identify regulatory mechanisms of γδ T cells. RESULTS: We demonstrated that γδ T cells support systemic granulopoiesis, which is critical for murine PsA-like pathology. Briefly, γδ T cell ablation inhibited the expression of neutrophil chemokines CXCL1 and CXCL2 and neutrophil CD11b+Ly6G+ accumulation in the aforementioned PsA-related tissues. Although significantly reduced expression of granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-17A was detected systemically in TCRδ-/- mice, no GM-CSF+/IL-17A+ γδ T cells were detected locally in the inflamed skin or bone marrow in WT mice. Our data showed that nonresident γδ T cells regulate the expansion of an CD11b+Ly6G+ neutrophil population and their recruitment to joint and skin tissues, where they develop hallmark pathologic features of human PsA. CONCLUSION: Our findings do not support the notion that tissue-resident γδ T cells initiate the disease but demonstrate a novel role of γδ T cells in neutrophil regulation that can be exploited therapeutically in PsA patients.

Synthesis of 1,2,4-triazole derivatives containing benzothiazoles as pharmacologically active molecule.

In attempt to make significant pharmacologically active molecule, we report here the synthesis and in vitro antimicrobial and antitubercular activity of various series of 3-(3-pyridyl)-5-(4-nitrophenyl)-4-(N-substituted-1,3-benzothiazol-2-amino)-4H-1,2,4-triazole. The antimicrobial activity of title compounds were examined against two Gram-positive bacteria (Staphylococcus aureus, Streptococcus pyogenes), two Gram-negative bacteria (Escherichia coli, Pseudomonas aeruginosa), and three fungi (Candida albicans, Aspergillus niger, Aspergillus clavatus) using the broth microdilution method and antitubercular activity H(37)Rv using Lowenstein-Jensen agar method.

Serodiagnostic evaluation of fusion proteins from multiple antigens of Mycobacterium tuberculosis for active TB.

Tuberculosis (TB) is a global health problem, being prevalent in the developing countries. A rapid, reliable and cost effective diagnostic method would help in controlling TB in the endemic populations. Development of suitable fusion molecules detecting multiple antibodies produced against Mycobacterium tuberculosis antigens would enhance sensitivity of serodiagnostic assays. In this study, EspC, CFP7 and PPE57 antigens of M. tuberculosis were selected for constructing fusion molecules after prediction of B-cell epitopes using in silico tools. Fusion proteins EspC-CFP7, HspX-EspC-CFP7 and HspX-EspC-CFP7-PPE57 were expressed in E.coli (BL21). The serodiagnostic potential of the individual antigens and their fusions was analyzed by screening 230 plasma samples of pulmonary TB patients. The single antigens HspX, EspC, CFP7, PPE57 showed sensitivities of 30%, 31%, 22% and 35%, respectively. The fusion protein EspC-CFP7 showed sensitivity of 43%. Linking of HspX antigen to the N-terminus of EspC-CFP7 fusion molecule increased sensitivity to 58%, while joining PPE57 antigen to the C-terminus of HspX-EspC-CFP7 increased sensitivity to 69%. The fusion protein HspX-EspC-CFP7-PPE57 seems to be a promising molecule for use in the development of fusions with higher sensitivity.

Automated machine learning for endemic active tuberculosis prediction from multiplex serological data.

Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Clinical interpretation of these complex datasets requires development of suitable algorithms, a time consuming and tedious undertaking addressed by the automated machine learning platform MILO (Machine Intelligence Learning Optimizer). MILO seamlessly integrates data processing, feature selection, model training, and model validation to simultaneously generate and evaluate thousands of models. These models were then further tested for generalizability on out-of-sample secondary and tertiary datasets. Out of 31 antigens evaluated, a 23-antigen model was the most robust on both the secondary dataset (TB vs healthy) and the tertiary dataset (TB vs COPD) with sensitivity of 90.5% and respective specificities of 100.0% and 74.6%. MILO represents a user-friendly, end-to-end solution for automated generation and deployment of optimized models, ideal for applications where rapid clinical implementation is critical such as emerging infectious diseases.

Enhanced serodiagnostic potential of a fusion molecule consisting of Rv1793, Rv2628 and a truncated Rv2608 of Mycobacterium tuberculosis.

Serodiagnosis of tuberculosis (TB) can be rapid, reliable and cost-effective if the issue of variable antibody responses of TB patients against different Mycobacterium tuberculosis (Mtb) antigens can be overcome by developing fusion proteins containing epitopes from multiple antigens of Mtb. In this study, Mtb antigens Rv1793, Rv2628, Rv2608 and a truncated variant produced by removing non-epitopic region from N-terminal of Rv2608 (tnRv2608), and the fusion protein Rv1793-Rv2628-tnRv2608 (TriFu64), were expressed in E. coli and purified. Plasma samples from TB patients characterized by sex, age and sputum/culture positivity, were used to compare the sensitivity of the single antigens with the fusion protein. Sensitivity of Rv1793, Rv2628 and Rv2608, was 27.8%, 39% and 36.3%, respectively. Truncation of Rv2608 increased sensitivity by approximately 35% in confirmed TB cases. Sensitivity of the fusion construct, TriFu64 increased to 66% with a specificity of 100%. Importantly, tnRv2608 was better able to detect sputum and culture negative patients, and this carried through to the fusion protein. We demonstrate that fusion of Mtb proteins ensures broad sensitivity across disease types, sex and age groups in a Pakistani population.

Gut microbiome dysbiosis and correlation with blood biomarkers in active-tuberculosis in endemic setting.

Tuberculosis (TB) is the largest infectious disease with 10 million new active-TB patients and1.7 million deaths per year. Active-TB is an inflammatory disease and is increasingly viewed as an imbalance of immune responses to M. tb. infection. The mechanisms of a switch from latent infection to active disease is not well worked out but a shift in the immune responses is thought to be responsible. Increasingly, the role of gut microbiota has been described as a major influencer of the immune system. And because the gut is the largest immune organ, we aimed to analyze the gut microbiome in active-TB patients in a TB-endemic country, Pakistan. The study revealed that Ruminococcacea, Enetrobactericeae, Erysipelotrichaceae, Bifidobacterium, etc. were the major genera associated with active-TB, also associated with chronic inflammatory disease. Plasma antibody profiles against several M. tb. antigens, as specific biomarkers for active-TB, correlated closely with the patient gut microbial profiles. Besides, bcoA gene copy number, indicative of the level of butyrate production by the gut microbiome was five-fold lower in TB patients compared to healthy individuals. These findings suggest that gut health in TB patients is compromised, with implications for disease morbidity (e.g., severe weight loss) as well as immune impairment.

Immune response dynamics in COVID-19 patients to SARS-CoV-2 and other human coronaviruses.

COVID-19 serological test must have high sensitivity as well as specificity to rule out cross-reactivity with common coronaviruses (HCoVs). We have developed a quantitative multiplex test, measuring antibodies against spike (S) proteins of SARS-CoV-2, SARS-CoV, MERS-CoV, and common human coronavirus strains (229E, NL63, OC43, HKU1), and nucleocapsid (N) protein of SARS-CoV viruses. Receptor binding domain of S protein of SARS-CoV-2 (S-RBD), and N protein, demonstrated sensitivity (94% and 92.5%, respectively) in COVID-19 patients (n = 53), with 98% specificity in non-COVID-19 respiratory-disease (n = 98), and healthy-controls (n = 129). Anti S-RBD and N antibodies appeared five to ten days post-onset of symptoms, peaking at approximately four weeks. The appearance of IgG and IgM coincided while IgG subtypes, IgG1 and IgG3 appeared soon after the total IgG; IgG2 and IgG4 remained undetectable. Several inflammatory cytokines/chemokines were found to be elevated in many COVID-19 patients (e.g., Eotaxin, Gro-α, CXCL-10 (IP-10), RANTES (CCL5), IL-2Rα, MCP-1, and SCGF-b); CXCL-10 was elevated in all. In contrast to antibody titers, levels of CXCL-10 decreased with the improvement in patient health suggesting it as a candidate for disease resolution. Importantly, anti-N antibodies appear before S-RBD and differentiate between vaccinated and infected people-current vaccines (and several in the pipeline) are S protein-based.

Plasma Linoleate Diols Are Potential Biomarkers for Severe COVID-19 Infections.

Polyunsaturated fatty acids are metabolized into regulatory lipids important for initiating inflammatory responses in the event of disease or injury and for signaling the resolution of inflammation and return to homeostasis. The epoxides of linoleic acid (leukotoxins) regulate skin barrier function, perivascular and alveolar permeability and have been associated with poor outcomes in burn patients and in sepsis. It was later reported that blocking metabolism of leukotoxins into the vicinal diols ameliorated the deleterious effects of leukotoxins, suggesting that the leukotoxin diols are contributing to the toxicity. During quantitative profiling of fatty acid chemical mediators (eicosanoids) in COVID-19 patients, we found increases in the regioisomeric leukotoxin diols in plasma samples of hospitalized patients suffering from severe pulmonary involvement. In rodents these leukotoxin diols cause dramatic vascular permeability and are associated with acute adult respiratory like symptoms. Thus, pathways involved in the biosynthesis and degradation of these regulatory lipids should be investigated in larger biomarker studies to determine their significance in COVID-19 disease. In addition, incorporating diols in plasma multi-omics of patients could illuminate the COVID-19 pathological signature along with other lipid mediators and blood chemistry.

Antimycobacterial and antimicrobial study of new 1,2,4-triazoles with benzothiazoles.

In this study, we report the antimycobacterial and antimicrobial evaluation of newly synthesized 3-(3-pyridyl)-5-(4-methoxyphenyl)-4-(N-substituted-1,3-benzothiazol-2-amino)-4H-1,2,4-triazole 6a-j in good yields. All the synthesized compounds have been established by elemental analysis, IR, ¹H NMR, ¹³C-NMR and Mass spectral data. In-vitro antimycobacterial activity was carried out against (Mycobacterium tuberculosis) H37Rv strain using Lowenstein-Jensen medium and antimicrobial activity against two Gram positive bacteria (Staphylococcus aureus, Streptococcus pyogenes), two Gram negative bacteria (Escherichia coli, Pseudomonas aeruginosa) and three fungal species (Candida albicans, Aspergillus niger, Aspergillus clavatus) using the broth microdilution method. Compounds 2e, 6a, 6g, 6h, and 6j exhibited promising antimicrobial activity whereas compound 6j showed very good antimycobacterial activity.

Designing fusion molecules from antigens of Mycobacterium tuberculosis for detection of multiple antibodies in plasma of TB patients.

Tuberculosis (TB) is amongst the deadliest diseases worldwide. For effective control of TB a rapid, reliable and sensitive method for its diagnosis is essential. Serodiagnosis detecting multiple antibodies against antigens of Mycobacterium tuberculosis (Mtb) in blood samples could prove beneficial. Based on the epitope position in the molecule, two truncated variants of Rv1984c, i.e., Tn1Rv1984c and Tn2Rv1984c were expressed in Escherichia coli. Screening of the Rv1984c, Tn1Rv1984c and Tn2Rv1984c against 231 sera samples from the culture positive TB patients showed sensitivities of 34.2%, 49.4% and 26.8%, respectively. Another antigen Rv1352 was analyzed for the location of epitopes, which had not been reported before. A fusion molecule consisting of Tn1Rv1984c and Rv1352, expressed in E. coli, showed enhanced sensitivity of 62.8%. Joining another antigen Rv2031c to the N-terminus of Tn1Rv1984c-Rv1352, improved sensitivity to 71.4%. The fusion construct Rv2031c-Tn1Rv1984c-Rv1352 showed comparatively higher sensitivity of 73.4% in the male group as compared to 67% in the female group. Data derived for the secondary structure analysis through Circular Dichroism (CD) spectroscopy and prediction on the basis of molecular modelling was also in agreement. This construct can be a potential base for producing constructs with greater sensitivity through fusion of epitopes from additional Mtb antigens.

Evaluation of multi-antigen serological screening for active tuberculosis among people living with HIV.

Better triage tests for screening tuberculosis (TB) disease are needed for people living with HIV (PLHIV). We performed the first evaluation of a previously-validated 8-antigen serological panel to screen PLHIV for pulmonary TB in Kampala, Uganda. We selected a random 1:1 sample with and without TB (defined by sputum culture) from a cohort of PLHIV initiating antiretroviral therapy. We used a multiplex microbead immunoassay and an ensemble machine learning classifier to determine the area under the receiver operating characteristic curve (AUC) for Ag85A, Ag85B, Ag85C, Rv0934-P38, Rv3881, Rv3841-BfrB, Rv3873, and Rv2878c. We then assessed the performance with the addition of four TB-specific antigens ESAT-6, CFP-10, Rv1980-MPT64, and Rv2031-HSPX, and every antigen combination. Of 262 participants (median CD4 cell-count 152 cells/µL [IQR 65-279]), 138 (53%) had culture-confirmed TB. The 8-antigen panel had an AUC of 0.53 (95% CI 0.40-0.66), and the additional 4 antigens did not improve performance (AUC 0.51, 95% CI 0.39-0.64). When sensitivity was restricted to ≥90% for the 8- and 12-antigen panel, specificity was 2.2% (95% CI 0-17.7%) and 8.1% (95% CI 0-23.9%), respectively. A three-antigen combination (Rv0934-P38, Ag85A, and Rv2031-HSPX) outperformed both panels, with an AUC of 0.60 (95% CI 0.48-0.73), 90% sensitivity (95% CI 78.2-96.7%) and 29.7% specificity (95% CI 15.9-47%). The multi-antigen panels did not achieve the target accuracy for a TB triage test among PLHIV. We identified a new combination that improved performance for TB screening in an HIV-positive sample compared to an existing serological panel in Uganda, and suggests an approach to identify novel antigen combinations specifically for screening TB in PLHIV.