A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection

Incipient tuberculosis: a comprehensive overview

In the context of the evolving global health landscape shaped by the COVID-19 pandemic, tuberculosis (TB) is gaining renewed attention as a reemerging threat even in low-endemic countries. Immunological tests such as the tuberculin skin test (TST) and interferon-gamma release assay (IGRA) are pivotal in identifying tuberculosis infection (TBI). However, their inability to distinguish between past and ongoing infection poses a diagnostic challenge, possibly leading to the unnecessary treatment of a significant portion of the population with potential side effects. This review delves into the concept of incipient tuberculosis (ITB), a dynamic, presymptomatic stage characterized by heightened Mycobacterium tuberculosis complex (MTC) metabolic activity and replication that result in minimal radiological changes, signifying a transitional state between TBI and TB. Key focus areas include epidemiological factors, underlying pathogenesis, imaging findings, and the ongoing challenges in the identification of individuals with ITB through the development of new biomarkers and the use of whole-genome sequencing-based analyses to implement early treatment strategies.

New genetic biomarkers from transcriptome RNA-sequencing for Mycobacterium tuberculosis complex and Mycobacterium avium complex infections by bioinformatics analysis

The study aims to accurately identify differentially expressed genes (DEGs) and biological pathways in mycobacterial infections through bioinformatics for deeper disease understanding. Differentially expressed genes (DEGs) was explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Unique DEGs were submitted on least absolute shrinkage and selection operator (LASSO) regression analysis. 1,057 DEGs from two GSE datasets were identified, which were closely connected with NTM/ latent TB infection (LTBI)/active TB disease (ATB). It was demonstrated that these DEGs are mainly associated with detoxification processes, and virus and bacterial infections. Moreover, the METTL7B gene was the most informative marker for distinguishing LTBI and ATB with an area under the curve (AUC) of 0.983 (95%CI: 0.964 to 1). The significantly upregulated HBA1/2 genes were the most informative marker for distinguishing between individuals of IGRA-HC/NTM and LTBI (P < 0.001). Moreover, the upregulated HBD gene was also differ between IGRA-HC/NTM and ATB (P < 0.001). We have identified gene signatures associated with Mycobacterium infection in whole blood, which could be significant for understanding the molecular mechanisms and diagnosis of NTM, LTBI, or ATB.

Immunological roads diverged: mapping tuberculosis outcomes in mice

The journey from phenotypic observation to causal genetic mechanism is a long and challenging road. For pathogens like Mycobacterium tuberculosis (Mtb), which causes tuberculosis (TB), host-pathogen coevolution has spanned millennia, costing millions of human lives. Mammalian models can systematically recapitulate host genetic variation, producing a spectrum of disease outcomes. Leveraging genome sequences and deep phenotyping data from infected mouse genetic reference populations (GRPs), quantitative trait locus (QTL) mapping approaches have successfully identified host genomic regions associated with TB phenotypes. Here, we review the ongoing optimization of QTL mapping study design alongside advances in mouse GRPs. These next-generation resources and approaches have enabled identification of novel host-pathogen interactions governing one of the most prevalent infectious diseases in the world today.

Type I interferon exacerbates Mycobacterium tuberculosis induced human macrophage death

Type I interferons (IFN-I) are implicated in exacerbation of tuberculosis (TB), but the mechanisms are unclear. Mouse macrophages infected with Mycobacterium tuberculosis (Mtb) produce IFN-I, which contributes to their death. Here we investigate whether the same is true for human monocyte-derived macrophages (MDM). MDM prepared by a conventional method markedly upregulate interferon-stimulated genes (ISGs) upon Mtb infection, while MDM prepared to better restrict Mtb do so much less. A mixture of antibodies inhibiting IFN-I signaling prevents ISG induction. Surprisingly, secreted IFN-I are undetectable until nearly two days after ISG induction. These same antibodies do not diminish Mtb-infected MDM death. MDM induce ISGs in response to picogram/mL levels of exogenous IFN-I while depleting similar quantities from the medium. Exogenous IFN-I increase the proportion of dead MDM. We speculate that Mtb-infected MDM produce and respond to minute levels of IFN-I, and that only some of the resultant signaling is susceptible to neutralizing antibodies. Many types of cells may secrete IFN-I in patients with TB, where IFN-I is likely to promote the death of infected macrophages.

Advances in understanding immune homeostasis in latent tuberculosis infection

Nearly one-fourth of the global population is infected by Mycobacterium tuberculosis (Mtb), and approximately 90%-95% remain asymptomatic as latent tuberculosis infection (LTBI), an estimated 5%-10% of those with latent infections will eventually progress to active tuberculosis (ATB). Although it is widely accepted that LTBI transitioning to ATB results from a disruption of host immune balance and a weakening of protective immune responses, the exact underlying immunological mechanisms that promote this conversion are not well characterized. Thus, it is difficult to accurately predict tuberculosis (TB) progression in advance, leaving the LTBI population as a significant threat to TB prevention and control. This article systematically explores three aspects related to the immunoregulatory mechanisms and translational research about LTBI: (1) the distinct immunocytological characteristics of LTBI and ATB, (2) LTBI diagnostic markers discovery related to host anti-TB immunity and metabolic pathways, and (3) vaccine development focus on LTBI. This article is categorized under: Infectious Diseases > Molecular and Cellular Physiology Infectious Diseases > Genetics/Genomics/Epigenetics Immune System Diseases > Genetics/Genomics/Epigenetics.

Metagenomic insights into microbial adaptation to the salinity gradient of a typical short residence-time estuary

BACKGROUND

Microbial adaptation to salinity has been a classic inquiry in the field of microbiology. It has been demonstrated that microorganisms can endure salinity stress via either the "salt-in" strategy, involving inorganic ion uptake, or the "salt-out" strategy, relying on compatible solutes. While these insights are mostly based on laboratory-cultured isolates, exploring the adaptive mechanisms of microorganisms within natural salinity gradient is crucial for gaining a deeper understanding of microbial adaptation in the estuarine ecosystem.

RESULTS

Here, we conducted metagenomic analyses on filtered surface water samples collected from a typical subtropical short residence-time estuary and categorized them by salinity into low-, intermediate-, and high-salinity metagenomes. Our findings highlighted salinity-driven variations in microbial community composition and function, as revealed through taxonomic and Clusters of Orthologous Group (COG) functional annotations. Through metagenomic binning, 127 bacterial and archaeal metagenome-assembled genomes (MAGs) were reconstructed. These MAGs were categorized as stenohaline-specific to low-, intermediate-, or high-salinity-based on the average relative abundance in one salinity category significantly exceeding those in the other two categories by an order of magnitude. Those that did not meet this criterion were classified as euryhaline, indicating a broader range of salinity tolerance. Applying the Boruta algorithm, a machine learning-based feature selection method, we discerned important genomic features from the stenohaline bacterial MAGs. Of the total 12,162 COGs obtained, 40 were identified as important features, with the "inorganic ion transport and metabolism" COG category emerging as the most prominent. Furthermore, eight COGs were implicated in microbial osmoregulation, of which four were related to the "salt-in" strategy, three to the "salt-out" strategy, and one to the regulation of water channel activity. COG0168, annotated as the Trk-type K+ transporter related to the "salt-in" strategy, was ranked as the most important feature. The relative abundance of COG0168 was observed to increase with rising salinity across metagenomes, the stenohaline strains, and the dominant Actinobacteriota and Proteobacteria phyla.

CONCLUSIONS

We demonstrated that salinity exerts influences on both the taxonomic and functional profiles of the microbial communities inhabiting the estuarine ecosystem. Our findings shed light on diverse salinity adaptation strategies employed by the estuarine microbial communities, highlighting the crucial role of the "salt-in" strategy mediated by Trk-type K+ transporters for microorganisms thriving under osmotic stress in the short residence-time estuary. Video Abstract.

Comparison of gene set scoring methods for reproducible evaluation of tuberculosis gene signatures

BACKGROUND

Blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease. However, an unresolved issue is whether gene set enrichment analysis of the signature transcripts alone is sufficient for prediction and differentiation or whether it is necessary to use the original model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data and missing details about the original trained model. To facilitate the utilization of these signatures in TB research, comparisons between gene set scoring methods cross-data validation of original model implementations are needed.

METHODS

We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both rrebuilt original models and gene set scoring methods. Existing gene set scoring methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, were used as alternative approaches to obtain the profile scores. The area under the ROC curve (AUC) value was computed to measure performance. Correlation analysis and Wilcoxon paired tests were used to compare the performance of enrichment methods with the original models.

RESULTS

For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original models. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies.

CONCLUSION

Gene set enrichment scoring of existing gene sets can distinguish patients with active TB disease from other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.

Host Cell Death and Modulation of Immune Response against Mycobacterium tuberculosis Infection

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), a prevalent infectious disease affecting populations worldwide. A classic trait of TB pathology is the formation of granulomas, which wall off the pathogen, via the innate and adaptive immune systems. Some key players involved include tumor necrosis factor-alpha (TNF-α), foamy macrophages, type I interferons (IFNs), and reactive oxygen species, which may also show overlap with cell death pathways. Additionally, host cell death is a primary method for combating and controlling Mtb within the body, a process which is influenced by both host and bacterial factors. These cell death modalities have distinct molecular mechanisms and pathways. Programmed cell death (PCD), encompassing apoptosis and autophagy, typically confers a protective response against Mtb by containing the bacteria within dead macrophages, facilitating their phagocytosis by uninfected or neighboring cells, whereas necrotic cell death benefits the pathogen, leading to the release of bacteria extracellularly. Apoptosis is triggered via intrinsic and extrinsic caspase-dependent pathways as well as caspase-independent pathways. Necrosis is induced via various pathways, including necroptosis, pyroptosis, and ferroptosis. Given the pivotal role of host cell death pathways in host defense against Mtb, therapeutic agents targeting cell death signaling have been investigated for TB treatment. This review provides an overview of the diverse mechanisms underlying Mtb-induced host cell death, examining their implications for host immunity. Furthermore, it discusses the potential of targeting host cell death pathways as therapeutic and preventive strategies against Mtb infection.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians

A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n = 63) or did not progress to TB (controls, n = 63). Transcriptomic profiling of monocyte-derived DCs and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Four genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Age and sex influence antibody profiles associated with tuberculosis progression

Antibody features vary with tuberculosis (TB) disease state. Whether clinical variables, such as age or sex, influence associations between Mycobacterium tuberculosis-specific antibody responses and disease state is not well explored. Here we profiled Mycobacterium tuberculosis-specific antibody responses in 140 TB-exposed South African individuals from the Adolescent Cohort Study. We identified distinct response features in individuals progressing to active TB from non-progressing, matched controls. A multivariate antibody score differentially associated with progression (SeroScore) identified progressors up to 2 years before TB diagnosis, earlier than that achieved with the RISK6 transcriptional signature of progression. We validated these antibody response features in the Grand Challenges 6-74 cohort. Both the SeroScore and RISK6 correlated better with risk of TB progression in adolescents compared with adults, and in males compared with females. This suggests that age and sex are important, underappreciated modifiers of antibody responses associated with TB progression.

B cell heterogeneity in human tuberculosis highlights compartment-specific phenotype and functional roles

B cells are important in tuberculosis (TB) immunity, but their role in the human lung is understudied. Here, we characterize B cells from lung tissue and matched blood of patients with TB and found they are decreased in the blood and increased in the lungs, consistent with recruitment to infected tissue, where they are located in granuloma associated lymphoid tissue. Flow cytometry and transcriptomics identify multiple B cell populations in the lung, including those associated with tissue resident memory, germinal centers, antibody secretion, proinflammatory atypical B cells, and regulatory B cells, some of which are expanded in TB disease. Additionally, TB lungs contain high levels of Mtb-reactive antibodies, specifically IgM, which promotes Mtb phagocytosis. Overall, these data reveal the presence of functionally diverse B cell subsets in the lungs of patients with TB and suggest several potential localized roles that may represent a target for interventions to promote immunity or mitigate immunopathology.

Quantitative and Longitudinal Assessment of Systemic Innate Immunity in Health and Disease Using a 2D Gene Model

Dysregulation of innate immunity is deeply involved in infectious and autoimmune diseases. For a better understanding of pathogenesis and improved management of these diseases, it is of vital importance to implement convenient monitoring of systemic innate immunity. Built upon our previous works on the host transcriptional response to infection in peripheral blood, we proposed a 2D gene model for the simultaneous assessment of two major components of systemic innate immunity, including VirSig as the signature of the host response to viral infection and BacSig as the signature of the host response to bacterial infection. The revelation of dysregulation in innate immunity by this 2D gene model was demonstrated with a wide variety of transcriptome datasets. In acute infection, distinctive patterns of VirSig and BacSig activation were observed in viral and bacterial infection. In comparison, both signatures were restricted to a defined range in the vast majority of healthy adults, regardless of age. In addition, BacSig showed significant elevation during pregnancy and an upward trend during development. In tuberculosis (TB), elevation of BacSig and VirSig was observed in a significant portion of active TB patients, and abnormal BacSig was also associated with a longer treatment course. In cystic fibrosis (CF), abnormal BacSig was observed in a subset of patients, and no overall change in BacSig abnormality was observed after the drug treatment. In systemic sclerosis-associated interstitial lung disease (SSc-ILD), significant elevation of VirSig and BacSig was observed in some patients, and treatment with a drug led to the further deviation of BacSig from the control level. In systemic lupus erythematosus (SLE), positivity for the anti-Ro autoantibody was associated with significant elevation of VirSig in SLE patients, and the additive effect of VirSig/BacSig activation was also observed in SLE patients during pregnancy. Overall, these data demonstrated that the 2D gene model can be used to assess systemic innate immunity in health and disease, with the potential clinical applications including patient stratification, prescription of antibiotics, understanding of pathogenesis, and longitudinal monitoring of treatment response.

A protective role for type I interferon signaling following infection with Mycobacterium tuberculosis carrying the rifampicin drug resistance-conferring RpoB mutation H445Y

Interleukin-1 (IL-1) signaling is essential for controlling virulent Mycobacterium tuberculosis (Mtb) infection since antagonism of this pathway leads to exacerbated pathology and increased susceptibility. In contrast, the triggering of type I interferon (IFN) signaling is associated with the progression of tuberculosis (TB) disease and linked with negative regulation of IL-1 signaling. However, mice lacking IL-1 signaling can control Mtb infection if infected with an Mtb strain carrying the rifampin-resistance conferring mutation H445Y in its RNA polymerase β subunit (rpoB-H445Y Mtb). The mechanisms that govern protection in the absence of IL-1 signaling during rpoB-H445Y Mtb infection are unknown. In this study, we show that in the absence of IL-1 signaling, type I IFN signaling controls rpoB-H445Y Mtb replication, lung pathology, and excessive myeloid cell infiltration. Additionally, type I IFN is produced predominantly by monocytes and recruited macrophages and acts on LysM-expressing cells to drive protection through nitric oxide (NO) production to restrict intracellular rpoB-H445Y Mtb. These findings reveal an unexpected protective role for type I IFN signaling in compensating for deficiencies in IL-1 pathways during rpoB-H445Y Mtb infection.

Interferon-gamma release assay conversion after Mycobacterium tuberculosis exposure specifically associates with greater risk of progression to tuberculosis: A prospective cohort study in Leicester, UK

OBJECTIVES

We investigated whether quantifying the serial QuantiFERON-TB Gold (QFT) response improves tuberculosis (TB) risk stratification in pulmonary TB (PTB) contacts.

METHODS

A total of 297 untreated adult household PTB contacts, QFT tested at baseline and 3 months after index notification, were prospectively observed (median 1460 days). Normal variance of serial QFT responses was established in 46 extrapulmonary TB contacts. This informed categorisation of the response in QFT-positive PTB contacts as converters, persistently QFT-positive with significant increase (PPincrease), and without significant increase (PPno-increase).

RESULTS

In total, eight co-prevalent TB (disease ≤3 months after index notification) and 12 incident TB (>3 months after index notification) cases were diagnosed. Genetic linkage to the index strain was confirmed in all culture-positive progressors. The cumulative 2-year incident TB risk in QFT-positive contacts was 8.4% (95% confidence interval, 3.0-13.6%); stratifying by serial QFT response, significantly higher risk was observed in QFT converters (28%), compared with PPno-increase (4.8%) and PPincrease (3.7%). Converters were characterised by exposure to index cases with a shorter interval from symptom onset to diagnosis (median reduction 50.0 days, P = 0.013).

CONCLUSIONS

QFT conversion, rather than quantitative changes of a persistently positive serial QFT response, is associated with greater TB risk and exposure to rapidly progressive TB.

Large-scale analysis reveals splicing biomarkers for tuberculosis progression and prognosis

BACKGROUND

Emerging evidence suggests that aberrant alternative splicing (AS) may play an important role in tuberculosis (TB). However, current knowledge regarding the value of AS in TB progression and prognosis remains unclear.

METHOD

Public RNA-seq datasets related to TB progression and prognosis were searched and AS analyses were conducted based on SUPPA2. Percent spliced in (PSI) was used for quantifying AS events and multiple machine learning (ML) methods were employed to construct predictive models. Area under curve (AUC), sensitivity and specificity were calculated to evaluate the model performance.

RESULTS

A total of 1587 samples from 7 datasets were included. Among 923 TB-progression related differential AS events (DASEs), 3 events (GET1-skipping exon (SE), TPD52-alternative first exons (AF) and TIMM10-alternative 5' splice site (A5)) were selected as candidate biomarkers; however, their predictive performance was limited. For TB prognosis, 5 events (PHF23-AF, KIF1B-SE, MACROD2-alternative 3' splice site (A3), CD55-retained intron (RI) and GALNT11-AF) were selected as candidates from the 1282 DASEs. Six ML methods were used to integrate these 5 events and XGBoost outperformed than others. AUC, sensitivity and specificity of XGBoost model were 0.875, 81.1% and 83.5% in training set, while they were 0.805, 68.4% and 73.2% in test set.

CONCLUSION

GET1-SE, TPD52-AF and TIMM10-A5 showed limited role in predicting TB progression, while PHF23-AF, KIF1B-SE, MACROD2-A3, CD55-RI and GALNT11-AF could well predict TB prognosis and work as candidate biomarkers. This work preliminarily explored the value of AS in predicting TB progression and prognosis and offered potential targets for further research.

Neutrophil-plasmacytoid dendritic cell interaction leads to production of type I IFN in response to Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) can cause a latent infection that sometimes progresses to clinically active tuberculosis (TB). Type I interferons (IFN-I) have been implicated in initiating the progression from latency to active TB, in part because IFN-I stimulated genes are the earliest genes to be upregulated in patients as they advance to active TB. Plasmacytoid dendritic cells (pDCs) are major producers of IFN-I during viral infections and in response to autoimmune-induced neutrophil extracellular traps. pDCs have also been suggested to be the major producers of IFN-I during Mtb infection of mice and nonhuman primates, but direct evidence has been lacking. Here, we found that Mtb did not stimulate isolated human pDCs to produce IFN-I, but human neutrophils infected with Mtb-activated co-cultured pDCs to do so. Mtb-infected neutrophils produced neutrophil extracellular traps, whose exposed DNA is a well-known mechanism to activate pDCs to secrete IFN-I. We conclude that pDCs contribute to the IFN-I response during Mtb infection by interacting with infected neutrophils which may then promote Mtb pathogenesis.

Mycobacterium tuberculosis SecA2-dependent activation of host Rig-I/MAVs signaling is not conserved in Mycobacterium marinum

Retinoic acid inducible gene I (Rig-I) is a cytosolic pattern recognition receptor canonically described for its important role in sensing viral RNAs. Increasingly, bacterially-derived RNA from intracellular bacteria such as Mycobacterium tuberculosis, have been shown to activate the same host Rig-I/Mitochondrial antiviral sensing protein (MAVS) signaling pathway to drive a type-I interferon response that contributes to bacterial pathogenesis in vivo. In M. tuberculosis, this response is mediated by the protein secretion system SecA2, but little is known about whether this process is conserved in other pathogenic mycobacteria or the mechanism by which these nucleic acids gain access to the host cytoplasm. Because the M. tuberculosis and M. marinum SecA2 protein secretion systems share a high degree of genetic and functional conservation, we hypothesized that Rig-I/MAVS activation and subsequent induction of IFN-β secretion by host macrophages will also be conserved between these two mycobacterial species. To test this, we generated a ΔsecA2 M. marinum strain along with complementation strains expressing either the M. marinum or M. tuberculosis secA2 genes. Our results suggest that the ΔsecA2 strain has a growth defect in vitro but not in host macrophages. These intracellular growth curves also suggested that the calculation applied to estimate the number of bacteria added to macrophage monolayers in infection assays underestimates bacterial inputs for the ΔsecA2 strain. Therefore, to better examine secreted IFN-β levels when bacterial infection levels are equal across strains we plated bacterial CFUs at 2hpi alongside our ELISA based infections. This enabled us to normalize secreted levels of IFN-β to a standard number of bacteria. Applying this approach to both WT and MAVS-/- bone marrow derived macrophages we observed equal or higher levels of secreted IFN-β from macrophages infected with the ΔsecA2 M. marinum strain as compared to WT. Together our findings suggest that activation of host Rig-I/MAVS cytosolic sensors and subsequent induction of IFN-β response in a SecA2-dependent manner is not conserved in M. marinum under the conditions tested.

Whole blood RNA signatures in tuberculosis patients receiving H56:IC31 vaccine as adjunctive therapy

Introduction

Therapeutic vaccination in tuberculosis (TB) represents a Host Directed Therapy strategy which enhances immune responses in order to improve clinical outcomes and shorten TB treatment. Previously, we have shown that the subunit H56:IC31 vaccine induced both humoral and cellular immune responses when administered to TB patients adjunctive to standard TB treatment (TBCOX2 study, NCT02503839). Here we present the longitudinal whole blood gene expression patterns in H56:IC31 vaccinated TB patients compared to controls receiving standard TB treatment only.

Methods

The H56:IC31 group (N=11) and Control group (N=7) underwent first-line TB treatment for 182 days. The H56:IC31 group received 5 micrograms of the H56:IC31 vaccine (Statens Serum Institut; SSI, Valneva Austria GmbH) intramuscularly at day 84 and day 140. Total RNA was extracted from whole blood samples collected in PAXgene tubes on days 0, 84, 98, 140, 154, 182 and 238. The expression level of 183 immune-related genes was measured by high-throughput microfluidic qPCR (Biomark HD system, Standard BioTools).

Results

The targeted gene expression profiling unveiled the upregulation of modules such as interferon (IFN) signalling genes, pattern recognition receptors and small nucleotide guanosine triphosphate (GTP)-ases in the vaccinated group compared to controls two weeks after administration of the first H56:IC31 vaccine. Additionally, the longitudinal analysis of the Adolescent Cohort Study-Correlation of Risk (ACS-COR) signature showed a progressive downregulation in both study arms towards the end of TB treatment, in congruence with reported treatment responses and clinical improvements. Still, two months after the end of TB treatment, vaccinated patients, and especially those developing both cellular and humoral vaccine responses, showed a lower expression of the ACS-COR genes compared to controls.

Discussion

Our data report gene expression patterns following H56:IC31 vaccination which might be interpreted as a lower risk of relapse in therapeutically vaccinated patients. Further studies are needed to conclude if these gene expression patterns could be used as prognostic biosignatures for therapeutic TB vaccine responses.

Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

The glycopatterns of Pseudomonas aeruginosa as a potential biomarker for its carbapenem resistance

IMPORTANCE

Bacterial surface glycans are an attractive therapeutic target in response to antibiotics; however, current knowledge of the corresponding mechanisms is rather limited. Antimicrobial susceptibility testing, genome sequencing, and MALDI-TOF MS, commonly used in recent years to analyze bacterial resistance, are unable to rapidly and efficiently establish associations between glycans and resistance. The discovery of new antimicrobial strategies still requires the introduction of promising analytical methods. In this study, we applied lectin microarray technology and a machine-learning model to screen for important glycan structures associated with carbapenem-resistant P. aeruginosa. This work highlights that specific glycopatterns can be important biomarkers associated with bacterial antibiotic resistance, which promises to provide a rapid entry point for exploring new resistance mechanisms in pathogens.

Alterations of lipid-related genes during anti-tuberculosis treatment: insights into host immune responses and potential transcriptional biomarkers

Background

The optimal diagnosis and treatment of tuberculosis (TB) are challenging due to underdiagnosis and inadequate treatment monitoring. Lipid-related genes are crucial components of the host immune response in TB. However, their dynamic expression and potential usefulness for monitoring response to anti-TB treatment are unclear.

Methodology

In the present study, we used a targeted, knowledge-based approach to investigate the expression of lipid-related genes during anti-TB treatment and their potential use as biomarkers of treatment response.

Results and discussion

The expression levels of 10 genes (ARPC5, ACSL4, PLD4, LIPA, CHMP2B, RAB5A, GABARAPL2, PLA2G4A, MBOAT2, and MBOAT1) were significantly altered during standard anti-TB treatment. We evaluated the potential usefulness of this 10-lipid-gene signature for TB diagnosis and treatment monitoring in various clinical scenarios across multiple populations. We also compared this signature with other transcriptomic signatures. The 10-lipid-gene signature could distinguish patients with TB from those with latent tuberculosis infection and non-TB controls (area under the receiver operating characteristic curve > 0.7 for most cases); it could also be useful for monitoring response to anti-TB treatment. Although the performance of the new signature was not better than that of previous signatures (i.e., RISK6, Sambarey10, Long10), our results suggest the usefulness of metabolism-centric biomarkers.

Conclusions

Lipid-related genes play significant roles in TB pathophysiology and host immune responses. Furthermore, transcriptomic signatures related to the immune response and lipid-related gene may be useful for TB diagnosis and treatment monitoring.

Granulocytes subsets and their divergent functions in host resistance to Mycobacterium tuberculosis - a 'tipping-point' model of disease exacerbation

Granulocytes are innate immune effector cells with essential functions in host resistance to bacterial infections. I will discuss emerging evidence that during Mycobacterium tuberculosis infection, counter-intuitively, eosinophils are host-protective while neutrophils are host detrimental. Additionally, I will propose a 'tipping-point' model in which neutrophils are an integral part of a feedforward loop driving tuberculosis disease exacerbation.

Transcriptional signatures measured in whole blood correlate with protection against tuberculosis in inbred and outbred mice

Although BCG has been used for almost 100 years to immunize against Mycobacterium tuberculosis, TB remains a global public health threat. Numerous clinical trials are underway studying novel vaccine candidates and strategies to improve or replace BCG, but vaccine development still lacks a well-defined set of immune correlates to predict vaccine-induced protection against tuberculosis. This study aimed to address this gap by examining transcriptional responses to BCG vaccination in C57BL/6 inbred mice, coupled with protection studies using Diversity Outbred mice. We evaluated relative gene expression in blood obtained from vaccinated mice, because blood is easily accessible, and data can be translated to human studies. We first determined that the average peak time after vaccination is 14 days for gene expression of a small subset of immune-related genes in inbred mice. We then performed global transcriptomic analyses using whole blood samples obtained two weeks after mice were vaccinated with BCG. Using comparative bioinformatic analyses and qRT-PCR validation, we developed a working correlate panel of 18 genes that were highly correlated with administration of BCG but not heat-killed BCG. We then tested this gene panel using BCG-vaccinated Diversity Outbred mice and revealed associations between the expression of a subset of genes and disease outcomes after aerosol challenge with M. tuberculosis. These data therefore demonstrate that blood-based transcriptional immune correlates measured within a few weeks after vaccination can be derived to predict protection against M. tuberculosis, even in outbred populations.

Gene signature discovery and systematic validation across diverse clinical cohorts for TB prognosis and response to treatment

While blood gene signatures have shown promise in tuberculosis (TB) diagnosis and treatment monitoring, most signatures derived from a single cohort may be insufficient to capture TB heterogeneity in populations and individuals. Here we report a new generalized approach combining a network-based meta-analysis with machine-learning modeling to leverage the power of heterogeneity among studies. The transcriptome datasets from 57 studies (37 TB and 20 viral infections) across demographics and TB disease states were used for gene signature discovery and model training and validation. The network-based meta-analysis identified a common 45-gene signature specific to active TB disease across studies. Two optimized random forest regression models, using the full or partial 45-gene signature, were then established to model the continuum from Mycobacterium tuberculosis infection to disease and treatment response. In model validation, using pooled multi-cohort datasets to mimic the real-world setting, the model provides robust predictive performance for incipient to active TB risk over a 2.5-year period with an AUROC of 0.85, 74.2% sensitivity, and 78.3% specificity, which approximates the minimum criteria (>75% sensitivity and >75% specificity) within the WHO target product profile for prediction of progression to TB. Moreover, the model strongly discriminates active TB from viral infection (AUROC 0.93, 95% CI 0.91-0.94). For treatment monitoring, the TB scores generated by the model statistically correlate with treatment responses over time and were predictive, even before treatment initiation, of standard treatment clinical outcomes. We demonstrate an end-to-end gene signature model development scheme that considers heterogeneity for TB risk estimation and treatment monitoring.

Identification of immune biomarkers in recent active pulmonary tuberculosis

Tuberculosis (TB) has remained an unsolved problem and a major public health issue, particularly in developing countries. Pakistan is one of the countries with the highest tuberculosis infection rates globally. However, methods or biomarkers to detect early signs of TB infection are limited. Here, we characterized the mRNA profiles of immune responses in unstimulated Peripheral blood mononuclear cells obtained from treatment naïve patients with early signs of active pulmonary tuberculosis without previous history of clinical TB. We identified a unique mRNA profile in active TB compared to uninfected controls, including cytokines such as IL-27, IL-15, IL-2RA, IL-24, and TGFβ, transcription factors such as STAT1 and NFATC1 and immune markers/receptors such as TLR4, IRF1, CD80, CD28, and PTGDR2 from an overall 84 different transcripts analyzed. Among 12 significant differentially expressed transcripts, we identified five gene signatures which included three upregulated IL-27, STAT1, TLR4 and two downregulated IL-24 and CD80 that best discriminate between active pulmonary TB and uninfected controls with AUC ranging from 0.9 to 1. Our data identified a molecular immune signature associated with the early stages of active pulmonary tuberculosis and it could be further investigated as a potential biomarker of pulmonary TB.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians

A quarter of humanity is estimated to be latently infected with Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n=63) or did not progress to TB (controls, n=63). Transcriptomic profiling of monocyte-derived dendritic cells (DCs) and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Five genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

From tuberculosis bedside to bench: UBE2B splicing as a potential biomarker and its regulatory mechanism

Alternative splicing (AS) is an important approach for pathogens and hosts to remodel transcriptome. However, tuberculosis (TB)-related AS has not been sufficiently explored. Here we presented the first landscape of TB-related AS by long-read sequencing, and screened four AS events (S100A8-intron1-retention intron, RPS20-exon1-alternaitve promoter, KIF13B-exon4-skipping exon (SE) and UBE2B-exon7-SE) as potential biomarkers in an in-house cohort-1. The validations in an in-house cohort-2 (2274 samples) and public datasets (1557 samples) indicated that the latter three AS events are potential promising biomarkers for TB diagnosis, but not for TB progression and prognosis. The excellent performance of classifiers further underscored the diagnostic value of these three biomarkers. Subgroup analyses indicated that UBE2B-exon7-SE splicing was not affected by confounding factors and thus had relatively stable performance. The splicing of UBE2B-exon7-SE can be changed by heat-killed mycobacterium tuberculosis through inhibiting SRSF1 expression. After heat-killed mycobacterium tuberculosis stimulation, 231 ubiquitination proteins in macrophages were differentially expressed, and most of them are apoptosis-related proteins. Taken together, we depicted a global TB-associated splicing profile, developed TB-related AS biomarkers, demonstrated an optimal application scope of target biomarkers and preliminarily elucidated mycobacterium tuberculosis-host interaction from the perspective of splicing, offering a novel insight into the pathophysiology of TB.

Pathogenicity of Type I Interferons in Mycobacterium tuberculosis

Tuberculosis (TB) is a leading cause of mortality due to infectious disease and rates have increased during the emergence of COVID-19, but many of the factors determining disease severity and progression remain unclear. Type I Interferons (IFNs) have diverse effector functions that regulate innate and adaptive immunity during infection with microorganisms. There is well-documented literature on type I IFNs providing host defense against viruses; however, in this review, we explore the growing body of work that indicates high levels of type I IFNs can have detrimental effects to a host fighting TB infection. We report findings that increased type I IFNs can affect alveolar macrophage and myeloid function, promote pathological neutrophil extracellular trap responses, inhibit production of protective prostaglandin 2, and promote cytosolic cyclic GMP synthase inflammation pathways, and discuss many other relevant findings.

Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV

Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.

Host-directed immunotherapy of viral and bacterial infections: past, present and future

The advent of COVID-19 and the persistent threat of infectious diseases such as tuberculosis, malaria, influenza and HIV/AIDS remind us of the marked impact that infections continue to have on public health. Some of the most effective protective measures are vaccines but these have been difficult to develop for some of these infectious diseases even after decades of research. The development of drugs and immunotherapies acting directly against the pathogen can be equally challenging, and such pathogen-directed therapeutics have the potential disadvantage of selecting for resistance. An alternative approach is provided by host-directed therapies, which interfere with host cellular processes required for pathogen survival or replication, or target the host immune response to infection (immunotherapies) to either augment immunity or ameliorate immunopathology. Here, we provide a historical perspective of host-directed immunotherapeutic interventions for viral and bacterial infections and then focus on SARS-CoV-2 and Mycobacterium tuberculosis, two major human pathogens of the current era, to indicate the key lessons learned and discuss candidate immunotherapeutic approaches, with a focus on drugs currently in clinical trials.

Comparison of gene set scoring methods for reproducible evaluation of multiple tuberculosis gene signatures

Rationale

Many blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease, predict risk of progression from infection to disease, and monitor TB treatment outcomes. However, an unresolved issue is whether gene set enrichment analysis (GSEA) of the signature transcripts alone is sufficient for prediction and differentiation, or whether it is necessary to use the original statistical model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data, missing details about the original trained model, and inadequate publicly-available software tools or source code implementing models. To facilitate these signatures' replicability and appropriate utilization in TB research, comprehensive comparisons between gene set scoring methods with cross-data validation of original model implementations are needed.

Objectives

We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both re-rebuilt original models and gene set scoring methods to evaluate whether gene set scoring is a reasonable proxy to the performance of the original trained model. We have provided an open-access software implementation of the original models for all 19 signatures for future use.

Methods

We considered existing gene set scoring and machine learning methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, as alternative approaches to profile gene signature performance. The sample-size-weighted mean area under the curve (AUC) value was computed to measure each signature's performance across datasets. Correlation analysis and Wilcoxon paired tests were used to analyze the performance of enrichment methods with the original models.

Measurement and Main Results

For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original diagnostic models. PLAGE outperformed all other gene scoring methods. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies.

Conclusion

Gene set enrichment scoring of existing blood-based biomarker gene sets can distinguish patients with active TB disease from latent TB infection and other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.

Culture independent markers of nontuberculous mycobacterial (NTM) lung infection and disease in the cystic fibrosis airway

Nontuberculous mycobacteria (NTM) are opportunistic pathogens that affect a relatively small but significant portion of the people with cystic fibrosis (CF), and may cause increased morbidity and mortality in this population. Cultures from the airway are the only test currently in clinical use for detecting NTM. Culture techniques used in clinical laboratories are insensitive and poorly suited for population screening or to follow progression of disease or treatment response. The lack of sensitive and quantitative markers of NTM in the airway impedes patient care and clinical trial design, and has limited our understanding of patterns of acquisition, latency and pathogenesis of disease. Culture-independent markers of NTM infection have the potential to overcome many of the limitations of standard NTM cultures, especially the very slow growth, inability to quantitate bacterial burden, and low sensitivity due to required decontamination procedures. A range of markers have been identified in sputum, saliva, breath, blood, urine, as well as radiographic studies. Proposed markers to detect presence of NTM or transition to NTM disease include bacterial cell wall products and DNA, as well as markers of host immune response such as immunoglobulins and the gene expression of circulating leukocytes. In all cases the sensitivity of culture-independent markers is greater than standard cultures; however, most do not discriminate between various NTM species. Thus, each marker may be best suited for a specific clinical application, or combined with other markers and traditional cultures to improve diagnosis and monitoring of treatment response.

Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV

Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.

Inflammation-mediated tissue damage in pulmonary tuberculosis and host-directed therapeutic strategies

Treatment of tuberculosis (TB) involves the administration of anti-mycobacterial drugs for several months. The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb, the causative agent) together with increased disease severity in people with co-morbidities such as diabetes mellitus and HIV have hampered efforts to reduce case fatality. In severe disease, TB pathology is largely attributable to over-exuberant host immune responses targeted at controlling bacterial replication. Non-resolving inflammation driven by host pro-inflammatory mediators in response to high bacterial load leads to pulmonary pathology including cavitation and fibrosis. The need to improve clinical outcomes and reduce treatment times has led to a two-pronged approach involving the development of novel antimicrobials as well as host-directed therapies (HDT) that favourably modulate immune responses to Mtb. HDT strategies incorporate aspects of immune modulation aimed at downregulating non-productive inflammatory responses and augmenting antimicrobial effector mechanisms to minimise pulmonary pathology and accelerate symptom resolution. HDT in combination with existing antimycobacterial agents offers a potentially promising strategy to improve the long-term outcome for TB patients. In this review, we describe components of the host immune response that contribute to inflammation and tissue damage in pulmonary TB, including cytokines, matrix metalloproteinases, lipid mediators, and neutrophil extracellular traps. We then proceed to review HDT directed at these pathways.

A robust host-response-based signature distinguishes bacterial and viral infections across diverse global populations

Limited sensitivity and specificity of current diagnostics lead to the erroneous prescription of antibiotics. Host-response-based diagnostics could address these challenges. However, using 4,200 samples across 69 blood transcriptome datasets from 20 countries from patients with bacterial or viral infections representing a broad spectrum of biological, clinical, and technical heterogeneity, we show current host-response-based gene signatures have lower accuracy to distinguish intracellular bacterial infections from viral infections than extracellular bacterial infections. Using these 69 datasets, we identify an 8-gene signature to distinguish intracellular or extracellular bacterial infections from viral infections with an area under the receiver operating characteristic curve (AUROC) > 0.91 (85.9% specificity and 90.2% sensitivity). In prospective cohorts from Nepal and Laos, the 8-gene classifier distinguished bacterial infections from viral infections with an AUROC of 0.94 (87.9% specificity and 91% sensitivity). The 8-gene signature meets the target product profile proposed by the World Health Organization and others for distinguishing bacterial and viral infections.

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis

Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.

lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models

Background

Studies that utilize RNA Sequencing (RNA-Seq) in conjunction with designs that introduce dependence between observations (e.g. longitudinal sampling) require specialized analysis tools to accommodate this additional complexity. This R package contains a set of utilities to fit linear mixed effects models to transformed RNA-Seq counts that properly account for this dependence when performing statistical analyses.

Results

In a simulation study comparing lmerSeq and two existing methodologies that also work with transformed RNA-Seq counts, we found that lmerSeq was comprehensively better in terms of nominal error rate control and statistical power.

Conclusions

Existing R packages for analyzing transformed RNA-Seq data with linear mixed models are limited in the variance structures they allow and/or the transformation methods they support. The lmerSeq package offers more flexibility in both of these areas and gave substantially better results in our simulations.

Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform

BACKGROUND

Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers.

METHODS

The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker.

RESULTS

Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB.

CONCLUSIONS

The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.

Identification and validation of a T-cell-related MIR600HG/hsa-mir-21-5p competing endogenous RNA network in tuberculosis activation based on integrated bioinformatics approaches

Background: T cells play critical roles in the progression of tuberculosis (TB); however, knowledge regarding these molecular mechanisms remains inadequate. This study constructed a critical ceRNA network was constructed to identify the potentially important role of TB activation via T-cell regulation.

Methods: We performed integrated bioinformatics analysis in a randomly selected training set from the GSE37250 dataset. After estimating the abundance of 18 types of T cells using ImmuCellAI, critical T-cell subsets were determined by their diagnostic accuracy in distinguishing active from latent TB. We then identified the critical genes associated with T-cell subsets in TB activation through co-expression analysis and PPI network prediction. Then, the ceRNA network was constructed based on RNA complementarity detection on the DIANA-LncBase and mirDIP platform. The gene biomarkers included in the ceRNA network were lncRNA, miRNA, and targeting mRNA. We then applied an elastic net regression model to develop a diagnostic classifier to assess the significance of the gene biomarkers in clinical applications. Internal and external validations were performed to assess the repeatability and generalizability.

Results: We identified CD4⁺ T, Tr1, nTreg, iTreg, and Tfh as T cells critical for TB activation. A ceRNA network mediated by the MIR600HG/hsa-mir-21-5p axis was constructed, in which the significant gene cluster regulated the critical T subsets in TB activation. MIR600HG, hsa-mir-21-5p, and five targeting mRNAs (BCL11B, ETS1, EPHA4, KLF12, and KMT2A) were identified as gene biomarkers. The elastic net diagnostic classifier accurately distinguished active TB from latent. The validation analysis confirmed that our findings had high generalizability in different host background cases.

Conclusion: The findings of this study provided novel insight into the underlying mechanisms of TB activation and identifying prospective biomarkers for clinical applications.

Whole transcriptome sequencing reveals neutrophils’ transcriptional landscape associated with active tuberculosis

Neutrophils have been recognized to play an important role in the pathogenesis of tuberculosis in recent years. Interferon-induced blood transcriptional signatures in ATB are predominantly driven by neutrophils. In this study, we performed global RNA-seq on peripheral blood neutrophils from active tuberculosis patients (ATB, n=15); latent tuberculosis infections (LTBI, n=22); and healthy controls (HC, n=21). The results showed that greater perturbations of gene expression patterns happened in neutrophils from ATB individuals than HC or those with LTBI, and a total of 344 differentially expressed genes (DEGs) were observed. Functional enrichment analysis showed that besides the interferon signaling pathway, multiple pattern recognition receptor pathways were significantly activated in ATB, such as NOD-like receptors and Toll-like receptors. Meanwhile, we also observed that the expression of genes related to endocytosis, secretory granules, and neutrophils degranulation were downregulated. Our data also showed that the NF-κB signaling pathway might be inhibited in patients with ATB, which could increase Mycobacterium tuberculosis survival and lead to active tuberculosis status. Furthermore, we validated the accuracy of some differentially expressed genes in an independent cohort using quantitative PCR, and obtained three novel genes (RBM3, CSRNP1, SRSF5) with the ability to discriminate active tuberculosis from LTBI and HC.

Comprehensive lipid and lipid-related gene investigations of host immune responses to characterize metabolism-centric biomarkers for pulmonary tuberculosis

Despite remarkable success in the prevention and treatment of tuberculosis (TB), it remains one of the most devastating infectious diseases worldwide. Management of TB requires an efficient and timely diagnostic strategy. In this study, we comprehensively characterized the plasma lipidome of TB patients, then selected candidate lipid and lipid-related gene biomarkers using a data-driven, knowledge-based framework. Among 93 lipids that were identified as potential biomarker candidates, ether-linked phosphatidylcholine (PC O–) and phosphatidylcholine (PC) were generally upregulated, while free fatty acids and triglycerides with longer fatty acyl chains were downregulated in the TB group. Lipid-related gene enrichment analysis revealed significantly altered metabolic pathways (e.g., ether lipid, linolenic acid, and cholesterol) and immune response signaling pathways. Based on these potential biomarkers, TB patients could be differentiated from controls in the internal validation (random forest model, area under the curve [AUC] 0.936, 95% confidence interval [CI] 0.865–0.992). PC(O-40:4), PC(O-42:5), PC(36:0), and PC(34:4) were robust biomarkers able to distinguish TB patients from individuals with latent infection and healthy controls, as shown in the external validation. Small changes in expression were identified for 162 significant lipid-related genes in the comparison of TB patients vs. controls; in the random forest model, their utilities were demonstrated by AUCs that ranged from 0.829 to 0.956 in three cohorts. In conclusion, this study introduced a potential framework that can be used to identify and validate metabolism-centric biomarkers.

Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape

Funding

Mycobacterium tuberculosis infection drives a type I IFN signature in lung lymphocytes

Mycobacterium tuberculosis (Mtb) infects 25% of the world's population and causes tuberculosis (TB), which is a leading cause of death globally. A clear understanding of the dynamics of immune response at the cellular level is crucial to design better strategies to control TB. We use the single-cell RNA sequencing approach on lung lymphocytes derived from healthy and Mtb-infected mice. Our results show the enrichment of the type I IFN signature among the lymphoid cell clusters, as well as heat shock responses in natural killer (NK) cells from Mtb-infected mice lungs. We identify Ly6A as a lymphoid cell activation marker and validate its upregulation in activated lymphoid cells following infection. The cross-analysis of the type I IFN signature in human TB-infected peripheral blood samples further validates our results. These findings contribute toward understanding and characterizing the transcriptional parameters at a single-cell depth in a highly relevant and reproducible mouse model of TB.

Immunopathogenic overlap between COVID-19 and tuberculosis identified from transcriptomic meta-analysis and human macrophage infection

Current and previous tuberculosis (TB) increase the risk of COVID-19 mortality and severe disease. To identify mechanisms of immunopathogenic interaction between COVID-19 and TB, we performed a systematic review and patient-level meta-analysis of COVID-19 transcriptomic signatures, spanning disease severity, from whole blood, PBMCs, and BALF. 35 eligible signatures were profiled on 1181 RNA-seq samples from 853 individuals across the spectrum of TB infection. Thirteen COVID-19 gene-signatures had significantly higher "COVID-19 risk scores" in active TB and latent TB progressors compared with non-progressors and uninfected controls (p<0·005), in three independent cohorts. Integrative single-cell-RNAseq analysis identified FCN1- and SPP1-expressing macrophages enriched in severe COVID-19 BALF and active TB blood. Gene ontology and protein-protein interaction networks identified 12-gene disease-exacerbation hot spots between COVID-19 and TB. Finally, we in vitro validated that SARS-CoV-2 infection is increased in human macrophages cultured in the inflammatory milieu of Mtb-infected macrophages, correlating with TMPRSS2, IFNA1, IFNB1, IFNG, TNF, and IL1B induction.

Viral coinfection promotes tuberculosis immunopathogenesis by type I IFN signaling-dependent impediment of Th1 cell pulmonary influx

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is often exacerbated upon coinfection, but the underlying immunological mechanisms remain unclear. Here, to elucidate these mechanisms, we use an Mtb and lymphocytic choriomeningitis virus coinfection model. Viral coinfection significantly suppresses Mtb-specific IFN-γ production, with elevated bacterial loads and hyperinflammation in the lungs. Type I IFN signaling blockade rescues the Mtb-specific IFN-γ response and ameliorates lung immunopathology. Single-cell sequencing, tissue immunofluorescence staining, and adoptive transfer experiments indicate that viral infection-induced type I IFN signaling could inhibit CXCL9/10 production in myeloid cells, ultimately impairing pulmonary migration of Mtb-specific CD4⁺ T cells. Thus, our study suggests that augmented and sustained type I IFNs by virus coinfection prior to the pulmonary localization of Mtb-specific Th1 cells exacerbates TB immunopathogenesis by impeding the Mtb-specific Th1 cell influx. Our study highlights a negative function of viral coinfection-induced type I IFN responses in delaying Mtb-specific Th1 responses in the lung.

Viral coinfection alongside mycobacterium tuberculosis (Mtb) infection may lead to immune complications or interference with immune responses. Here the authors show that in mice infected with Mtb and LCMV virus the specific T_H1 response to MTb is reduced through a type I IFN response to the infecting virus.

A comparison of methods for multiple degree of freedom testing in repeated measures RNA-sequencing experiments

Background

As the cost of RNA-sequencing decreases, complex study designs, including paired, longitudinal, and other correlated designs, become increasingly feasible. These studies often include multiple hypotheses and thus multiple degree of freedom tests, or tests that evaluate multiple hypotheses jointly, are often useful for filtering the gene list to a set of interesting features for further exploration while controlling the false discovery rate. Though there are several methods which have been proposed for analyzing correlated RNA-sequencing data, there has been little research evaluating and comparing the performance of multiple degree of freedom tests across methods.

Methods

We evaluated 11 different methods for modelling correlated RNA-sequencing data by performing a simulation study to compare the false discovery rate, power, and model convergence rate across several hypothesis tests and sample size scenarios. We also applied each method to a real longitudinal RNA-sequencing dataset.

Results

Linear mixed modelling using transformed data had the best false discovery rate control while maintaining relatively high power. However, this method had high model non-convergence, particularly at small sample sizes. No method had high power at the lowest sample size. We found a mix of conservative and anti-conservative behavior across the other methods, which was influenced by the sample size and the hypothesis being evaluated. The patterns observed in the simulation study were largely replicated in the analysis of a longitudinal study including data from intensive care unit patients experiencing cardiogenic or septic shock.

Conclusions

Multiple degree of freedom testing is a valuable tool in longitudinal and other correlated RNA-sequencing experiments. Of the methods that we investigated, linear mixed modelling had the best overall combination of power and false discovery rate control. Other methods may also be appropriate in some scenarios.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12874-022-01615-8).

Human M1 macrophages express unique innate immune response genes after mycobacterial infection to defend against tuberculosis

Mycobacterium tuberculosis (Mtb) is responsible for approximately 1.5 million deaths each year. Though 10% of patients develop tuberculosis (TB) after infection, 90% of these infections are latent. Further, mice are nearly uniformly susceptible to Mtb but their M1-polarized macrophages (M1-MΦs) can inhibit Mtb in vitro, suggesting that M1-MΦs may be able to regulate anti-TB immunity. We sought to determine whether human MΦ heterogeneity contributes to TB immunity. Here we show that IFN-γ-programmed M1-MΦs degrade Mtb through increased expression of innate immunity regulatory genes (Inregs). In contrast, IL-4-programmed M2-polarized MΦs (M2-MΦs) are permissive for Mtb proliferation and exhibit reduced Inregs expression. M1-MΦs and M2-MΦs express pro- and anti-inflammatory cytokine-chemokines, respectively, and M1-MΦs show nitric oxide and autophagy-dependent degradation of Mtb, leading to increased antigen presentation to T cells through an ATG-RAB7-cathepsin pathway. Despite Mtb infection, M1-MΦs show increased histone acetylation at the ATG5 promoter and pro-autophagy phenotypes, while increased histone deacetylases lead to decreased autophagy in M2-MΦs. Finally, Mtb-infected neonatal macaques express human Inregs in their lymph nodes and macrophages, suggesting that M1 and M2 phenotypes can mediate immunity to TB in both humans and macaques. We conclude that human MФ subsets show unique patterns of gene expression that enable differential control of TB after infection. These genes could serve as targets for diagnosis and immunotherapy of TB.

Topologically associating domains are disrupted by evolutionary genome rearrangements forming species-specific enhancer connections in mice and humans

Distinguishing between conserved and divergent regulatory mechanisms is essential for translating preclinical research from mice to humans, yet there is a lack of information about how evolutionary genome rearrangements affect the regulation of the immune response, a rapidly evolving system. The current model is topologically associating domains (TADs) are conserved between species, buffering evolutionary rearrangements and conserving long-range interactions within a TAD. However, we find that TADs frequently span evolutionary translocation and inversion breakpoints near genes with species-specific expression in immune cells, creating unique enhancer-promoter interactions exclusive to the mouse or human genomes. This includes TADs encompassing immune-related transcription factors, cytokines, and receptors. For example, we uncover an evolutionary rearrangement that created a shared LPS-inducible regulatory module between OASL and P2RX7 in human macrophages that is absent in mice. Therefore, evolutionary genome rearrangements disrupt TAD boundaries, enabling sequence-conserved enhancer elements from divergent genomic locations between species to create unique regulatory modules.

It is currently unclear how evolutionary genome rearrangements affecting the mouse and human genomes influence the expression of genes important in immunity. Gilbertson et al. report that evolutionary genome rearrangements disrupt topologically associating domain boundaries, enabling sequence-conserved enhancer elements from divergent locations between species to create unique regulatory modules.

In-Depth Immunophenotyping With Mass Cytometry During TB Treatment Reveals New T-Cell Subsets Associated With Culture Conversion

Tuberculosis (TB) is a difficult-to-treat infection because of multidrug regimen requirements based on drug susceptibility profiles and treatment observance issues. TB cure is defined by mycobacterial sterilization, technically complex to systematically assess. We hypothesized that microbiological outcome was associated with stage-specific immune changes in peripheral whole blood during TB treatment. The T-cell phenotypes of treated TB patients were prospectively characterized in a blinded fashion using mass cytometry after Mycobacterium tuberculosis (Mtb) antigen stimulation with QuantiFERON-TB Gold Plus, and then correlated to sputum culture status. At two months of treatment, cytotoxic and terminally differentiated CD8⁺ T-cells were under-represented and naïve CD4⁺ T-cells were over-represented in positive- versus negative-sputum culture patients, regardless of Mtb drug susceptibility. At treatment completion, a T-cell immune shift towards differentiated subpopulations was associated with TB cure. Overall, we identified specific T-cell profiles associated with slow sputum converters, which brings new insights in TB prognostic biomarker research designed for clinical application.

Up-regulated SAMD9L modulated by TLR2 and HIF-1α as a promising biomarker in tuberculosis

The aim of this study was to identify potential biomarkers of TB in blood and determine their function in Mtb-infected macrophages. First of all, WGCNA was used to analyse 9451 genes with significant changes in TB patients' whole blood. The 220 interferon-γ-related genes were identified, and then 30 key genes were screened using Cytoscape. Then, the AUC values of key genes were calculated to further narrow the gene range. Finally, we identified 9 genes from GSE19444. ROC analysis showed that SAMD9L, among 9 genes, had a high diagnostic value (AUC = 0.925) and a differential diagnostic value (AUC>0.865). To further narrow down the range of DEGs, the top 10 hub-connecting genes were screened from monocytes (GSE19443). Finally, we obtained 4 genes (SAMD9L, GBP1, GBP5 and STAT1) by intersections of genes from monocytes and whole blood. Among them, it was found that the function of SAMD9L was unknown after data review, so this paper studied this gene. Our results showed that SAMD9L is up-regulated and suppresses cell necrosis, and might be regulated by TLR2 and HIF-1α during Mtb infection. In addition, miR-181b-5p is significantly up-regulated in the peripheral blood plasma of tuberculosis patients, which has a high diagnostic value (AUC = 0.969).