Cell-type deconvolution with immune pathways identifies gene networks of host defense and immunopathology in leprosy

CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues

Motivation

Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods.

Results

In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods.

Availability and implementation

https://github.com/Papatheodorou-Group/CATD_snakemake.

Leprosy: treatment, prevention, immune response and gene function

Since the leprosy cases have fallen dramatically, the incidence of leprosy has remained stable over the past years, indicating that multidrug therapy seems unable to eradicate leprosy. More seriously, the emergence of rifampicin-resistant strains also affects the effectiveness of treatment. Immunoprophylaxis was mainly carried out through vaccination with the BCG but also included vaccines such as LepVax and MiP. Meanwhile, it is well known that the infection and pathogenesis largely depend on the host's genetic background and immunity, with the onset of the disease being genetically regulated. The immune process heavily influences the clinical course of the disease. However, the impact of immune processes and genetic regulation of leprosy on pathogenesis and immunological levels is largely unknown. Therefore, we summarize the latest research progress in leprosy treatment, prevention, immunity and gene function. The comprehensive research in these areas will help elucidate the pathogenesis of leprosy and provide a basis for developing leprosy elimination strategies.

MuSiC2: cell-type deconvolution for multi-condition bulk RNA-seq data

Cell-type composition of intact bulk tissues can vary across samples. Deciphering cell-type composition and its changes during disease progression is an important step toward understanding disease pathogenesis. To infer cell-type composition, existing cell-type deconvolution methods for bulk RNA sequencing (RNA-seq) data often require matched single-cell RNA-seq (scRNA-seq) data, generated from samples with similar clinical conditions, as reference. However, due to the difficulty of obtaining scRNA-seq data in diseased samples, only limited scRNA-seq data in matched disease conditions are available. Using scRNA-seq reference to deconvolve bulk RNA-seq data from samples with different disease conditions may lead to a biased estimation of cell-type proportions. To overcome this limitation, we propose an iterative estimation procedure, MuSiC2, which is an extension of MuSiC, to perform deconvolution analysis of bulk RNA-seq data generated from samples with multiple clinical conditions where at least one condition is different from that of the scRNA-seq reference. Extensive benchmark evaluations indicated that MuSiC2 improved the accuracy of cell-type proportion estimates of bulk RNA-seq samples under different conditions as compared with the traditional MuSiC deconvolution. MuSiC2 was applied to two bulk RNA-seq datasets for deconvolution analysis, including one from human pancreatic islets and the other from human retina. We show that MuSiC2 improves current deconvolution methods and provides more accurate cell-type proportion estimates when the bulk and single-cell reference differ in clinical conditions. We believe the condition-specific cell-type composition estimates from MuSiC2 will facilitate the downstream analysis and help identify cellular targets of human diseases.

Host-Related Laboratory Parameters for Leprosy Reactions

Leprosy reactions are acute inflammatory episodes that complicate the course of a Mycobacterium leprae infection and are the major cause of leprosy-associated pathology. Two types of leprosy reactions with relatively distinct pathogenesis and clinical features can occur: type 1 reaction, also known as reversal reaction, and type 2 reaction, also known as erythema nodosum leprosum. These acute nerve-destructive immune exacerbations often cause irreversible disabilities and deformities, especially when diagnosis is delayed. However, there is no diagnostic test to detect or predict leprosy reactions before the onset of clinical symptoms. Identification of biomarkers for leprosy reactions, which impede the development of symptoms or correlate with early-onset, will allow precise diagnosis and timely interventions to greatly improve the patients' quality of life. Here, we review the progress of research aimed at identifying biomarkers for leprosy reactions, including its correlation with not only immunity but also genetics, transcripts, and metabolites, providing an understanding of the immune dysfunction and inflammation that underly the pathogenesis of leprosy reactions. Nevertheless, no biomarkers that can reliably predict the subsequent occurrence of leprosy reactions from non-reactional patients and distinguish type I reaction from type II have yet been found.

Analysis of Bulk RNA Sequencing Data Reveals Novel Transcription Factors Associated With Immune Infiltration Among Multiple Cancers

Tumor-infiltrating immune cells shape the tumor microenvironment and are closely related to clinical outcomes. Several transcription factors (TFs) have also been reported to regulate the antitumor activity and immune cell infiltration. This study aimed to quantify the populations of different immune cells infiltrated in tumor samples based on the bulk RNA sequencing data obtained from 50 cancer patients using the CIBERSORT and the EPIC algorithm. Weighted gene coexpression network analysis (WGCNA) identified eigengene modules strongly associated with tumorigenesis and the activation of CD4+ memory T cells, dendritic cells, and macrophages. TF genes FOXM1, MYBL2, TAL1, and ERG are central in the subnetworks of the eigengene modules associated with immune-related genes. The analysis of The Cancer Genome Atlas (TCGA) cancer data confirmed these findings and further showed that the expression of these potential TF genes regulating immune infiltration, and the immune-related genes that they regulated, was associated with the survival of patients within multiple cancers. Exome-seq was performed on 24 paired samples that also had RNA-seq data. The expression quantitative trait loci (eQTL) analysis showed that mutations were significantly more frequent in the regions flanking the TF genes compared with those of non-TF genes, suggesting a driver role of these TF genes regulating immune infiltration. Taken together, this study presented a practical method for identifying genes that regulate immune infiltration. These genes could be potential biomarkers for cancer prognosis and possible therapeutic targets.

Neutrophil NETworking in ENL: Potential as a Putative Biomarker: Future Insights

Erythema nodosum leprosum (ENL), also known as type 2 reaction (T2R) is an immune complex mediated (type III hypersensitivity) reactional state encountered in patients with borderline lepromatous and lepromatous leprosy (BL and LL) either before, during, or after the institution of anti-leprosy treatment (ALT). The consequences of ENL may be serious, leading to permanent nerve damage and deformities, constituting a major cause of leprosy-related morbidity. The incidence of ENL is increasing with the increasing number of multibacillary cases. Although the diagnosis of ENL is not difficult to make for physicians involved in the care of leprosy patients, its management continues to be a most challenging aspect of the leprosy eradication program: the chronic and recurrent painful skin lesions, neuritis, and organ involvement necessitates prolonged treatment with prednisolone, thalidomide, and anti-inflammatory and immunosuppressive drugs, which further adds to the existing morbidity. In addition, the use of immunosuppressants like methotrexate, azathioprine, cyclosporine, or biologics carries a risk of reactivation of persisters (Mycobacterium leprae), apart from their own end-organ toxicities. Most ENL therapeutic guidelines are primarily designed for acute episodes and there is scarcity of literature on management of patients with chronic and recurrent ENL. It is difficult to predict which patients will develop chronic or recurrent ENL and plan the treatment accordingly. We need simple point-of-care or ELISA-based tests from blood or skin biopsy samples, which can help us in identifying patients who are likely to require prolonged treatment and also inform us about the prognosis of reactions so that appropriate therapy may be started and continued for better ENL control in such patients. There is a significant unmet need for research for better understanding the immunopathogenesis of, and biomarkers for, ENL to improve clinical stratification and therapeutics. In this review we will discuss the potential of neutrophils (polymorphonuclear granulocytes) as putative diagnostic and prognostic biomarkers by virtue of their universal abundance in human blood, functional versatility, phenotypic heterogeneity, metabolic plasticity, differential hierarchical cytoplasmic granule mobilization, and their ability to form NETs (neutrophil extracellular traps). We will touch upon the various aspects of neutrophil biology relevant to ENL pathophysiology in a step-wise manner. We also hypothesize about an element of metabolic reprogramming of neutrophils by M. leprae that could be investigated and exploited for biomarker discovery. In the end, a potential role for neutrophil derived exosomes as a novel biomarker for ENL will also be explored.

The cellular architecture of the antimicrobial response network in human leprosy granulomas

Granulomas are complex cellular structures composed predominantly of macrophages and lymphocytes that function to contain and kill invading pathogens. Here, we investigated the single-cell phenotypes associated with antimicrobial responses in human leprosy granulomas by applying single-cell and spatial sequencing to leprosy biopsy specimens. We focused on reversal reactions (RRs), a dynamic process whereby some patients with disseminated lepromatous leprosy (L-lep) transition toward self-limiting tuberculoid leprosy (T-lep), mounting effective antimicrobial responses. We identified a set of genes encoding proteins involved in antimicrobial responses that are differentially expressed in RR versus L-lep lesions and regulated by interferon-γ and interleukin-1β. By integrating the spatial coordinates of the key cell types and antimicrobial gene expression in RR and T-lep lesions, we constructed a map revealing the organized architecture of granulomas depicting compositional and functional layers by which macrophages, T cells, keratinocytes and fibroblasts can each contribute to the antimicrobial response.

Blood RNA signature RISK4LEP predicts leprosy years before clinical onset

BACKGROUND

Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection.

METHODS

We investigated differential gene expression (DGE) by RNA-Seq between progressors before presence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR).

FINDINGS

Although no significant intra-individual longitudinal variation within leprosy progressors was identified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identified a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted in a final 4-gene signature, designated RISK4LEP (MT-ND2, REX1BD, TPGS1, UBC) (AUC=86.4%).

INTERPRETATION

This study identifies for the first time a prospective transcriptional risk signature in blood predicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in contacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development.

FUNDING

This study was supported by R2STOP Research grant, the Order of Malta-Grants-for-Leprosy-Research, the Q.M. Gastmann-Wichers Foundation and the Leprosy Research Initiative (LRI) together with the Turing Foundation (ILEP# 702.02.73 and # 703.15.07).

Large-Scale Gene Expression Signatures Reveal a Microbicidal Pattern of Activation in Mycobacterium leprae-Infected Monocyte-Derived Macrophages With Low Multiplicity of Infection

Leprosy is a disease with a clinical spectrum of presentations that is also manifested in diverse histological features. At one pole, lepromatous lesions (L-pole) have phagocytic foamy macrophages heavily parasitized with freely multiplying intracellular Mycobacterium leprae. At the other pole, the presence of epithelioid giant cells and granulomatous formation in tuberculoid lesions (T-pole) lead to the control of M. leprae replication and the containment of its spread. The mechanism that triggers this polarization is unknown, but macrophages are central in this process. Over the past few years, leprosy has been studied using large scale techniques to shed light on the basic pathways that, upon infection, rewire the host cellular metabolism and gene expression. M. leprae is particularly peculiar as it invades Schwann cells in the nerves, reprogramming their gene expression leading to a stem-like cell phenotype. This modulatory behavior exerted by M. leprae is also observed in skin macrophages. Here, we used live M. leprae to infect (10:1 multiplicity of infection) monocyte-derived macrophages (MDMs) for 48 h and analyzed the whole gene expression profile using microarrays. In this model, we observe an intense upregulation of genes consistent with a cellular immune response, with enriched pathways including peptide and protein secretion, leukocyte activation, inflammation, and cellular divalent inorganic cation homeostasis. Among the most differentially expressed genes (DEGs) are CCL5/RANTES and CYP27B1, and several members of the metallothionein and metalloproteinase families. This is consistent with a proinflammatory state that would resemble macrophage rewiring toward granulomatous formation observed at the T-pole. Furthermore, a comparison with a dataset retrieved from the Gene Expression Omnibus of M. leprae-infected Schwann cells (MOI 100:1) showed that the patterns among the DEGs are highly distinct, as the Schwann cells under these conditions had a scavenging and phagocytic gene profile similar to M2-like macrophages, with enriched pathways rearrangements in the cytoskeleton, lipid and cholesterol metabolism and upregulated genes including MVK, MSMO1, and LACC1/FAMIN. In summary, macrophages may have a central role in defining the paradigmatic cellular (T-pole) vs. humoral (L-pole) responses and it is likely that the multiplicity of infection and genetic polymorphisms in key genes are gearing this polarization.

Advances in the Immunology and Genetics of Leprosy

Leprosy, a disease caused by the intracellular parasite Mycobacterium leprae or Mycobacterium lepromatosis, has affected humans for more than 4,000 years and is a stigmatized disease even now. Since clinical manifestations of leprosy patients present as an immune-related spectrum, leprosy is regarded as an ideal model for studying the interaction between host immune response and infection; in fact, the landscape of leprosy immune responses has been extensively investigated. Meanwhile, leprosy is to some extent a genetic disease because the genetic factors of hosts have long been considered major contributors to this disease. Many immune-related genes have been discovered to be associated with leprosy. However, immunological and genetic findings have rarely been studied and discussed together, and as a result, the effects of gene variants on leprosy immune responses and the molecular mechanisms of leprosy pathogenesis are largely unknown. In this context, we summarized advances in both the immunology and genetics of leprosy and discussed the perspective of the combination of immunological and genetic approaches in studying the molecular mechanism of leprosy pathogenesis. In our opinion, the integrating of immunological and genetic approaches in the future may be promising to elucidate the molecular mechanism of leprosy onset and how leprosy develops into different types of leprosy.

Identification of a systemic interferon-γ inducible antimicrobial gene signature in leprosy patients undergoing reversal reaction

Reversal reactions (RRs) in leprosy are characterized by a reduction in the number of bacilli in lesions associated with an increase in cell-mediated immunity against the intracellular bacterium Mycobacterium leprae, the causative pathogen of leprosy. To identify the mechanisms that contribute to cell-mediated immunity in leprosy, we measured changes in the whole blood-derived transcriptome of patients with leprosy before, during and after RR. We identified an ‘RR signature’ of 1017 genes that were upregulated at the time of the clinical diagnosis of RR. Using weighted gene correlated network analysis (WGCNA), we detected a module of 794 genes, bisque4, that was significantly correlated with RR, of which 434 genes were part of the RR signature. An enrichment for both IFN-γ and IFN-β downstream gene pathways was present in the RR signature as well as the RR upregulated genes in the bisque4 module, including those encoding proteins of the guanylate binding protein (GBP) family that contributes to antimicrobial responses against mycobacteria. Specifically, GBP1, GBP2, GBP3 and GBP5 mRNAs were upregulated in the RR peripheral blood transcriptome, with GBP1, GBP2 and GBP5 mRNAs also upregulated in the RR disease lesion transcriptome. These data indicate that RRs involve a systemic upregulation of IFN-γ downstream genes including GBP family members as part of the host antimicrobial response against mycobacteria.

Reversal reaction (RR) is a major cause of tissue injury and disabilities in leprosy, resulting from the rapid onset of cell-mediated immune responses to the intracellular bacterium Mycobacterium leprae. To identify the mechanisms related to the increase in cell-mediated immunity in RR, we measured changes in the whole blood-derived transcriptome of patients with leprosy before, during and after RR. We identified that RRs are associated with an IFN-γ induced inflammatory response including an antimicrobial gene network containing the GBP1, GBP2, GBP3 and GBP5 mRNAs in the peripheral blood. Furthermore, we show that GBP1, GBP2 and GBP5 mRNAs are also upregulated at the site of disease in RR patients. In summary, our study suggests that RR involves a systemic induction of IFN-γ regulated genes that contributes to an antimicrobial response against the pathogen, releasing ligands and antigens that can further amplify the inflammatory response.

Organization of the Skin Immune System and Compartmentalized Immune Responses in Infectious Diseases

The skin is an organ harboring several types of immune cells that participate in innate and adaptive immune responses. The immune system of the skin comprises both skin cells and professional immune cells that together constitute what is designated skin-associated lymphoid tissue (SALT). In this review, I extensively discuss the organization of SALT and the mechanisms involved in its responses to infectious diseases of the skin and mucosa. The nature of these SALT responses, and the cellular mediators involved, often determines the clinical course of such infections. I list and describe the components of innate immunity, such as the roles of the keratinocyte barrier and of inflammatory and natural killer cells. I also examine the mechanisms involved in adaptive immune responses, with emphasis on new cytokine profiles, and the role of cell death phenomena in host-pathogen interactions and control of the immune responses to infectious agents. Finally, I highlight the importance of studying SALT in order to better understand host-pathogen relationships involving the skin and detail future directions in the immunological investigation of this organ, especially in light of recent findings regarding the skin immune system.

microRNAs in Mycobacterial Infection: Modulation of Host Immune Response and Apoptotic Pathways

Our current knowledge of mycobacterial infections in humans has progressively increased over the past few decades. The infection of Mycobacterium tuberculosis causes tuberculosis (TB) disease, which has reasoned for excessive morbidity and mortality worldwide, and has become a foremost issue of health problem globally. Mycobacterium leprae, another member of the family Mycobacteriaceae, is responsible for causing a chronic disease known as leprosy that mainly affects mucosa of the upper respiratory tract, skin, peripheral nerves, and eyes. Ample amount of existing data suggests that pathogenic mycobacteria have skilled in utilizing different mechanisms to escape or offset the host immune responses. They hijack the machinery of immune cells through the modulation of microRNAs (miRs), which regulate gene expression and immune responses of the host. Evidence shows that miRs have now gained considerable attention in the research, owing to their involvement in a broad range of inflammatory processes that are further implicated in the pathogenesis of several diseases. However, the knowledge of functions of miRs during mycobacterial infections remains limited. This review summarises recent findings of differential expression of miRs, which are used to good advantage by mycobacteria in offsetting host immune responses generated against them.

High-Throughput Identification of the Plasma Proteomic Signature of Inflammatory Bowel Disease

BACKGROUND

The molecular aetiology of inflammatory bowel disease [IBD] and its two subtypes, ulcerative colitis [UC] and Crohn's disease [CD], have been carefully investigated at genome and transcriptome levels. Recent advances in high-throughput proteome quantification has enabled comprehensive large-scale plasma proteomics studies of IBD.

METHODS

The study used two cohorts: [1] The CERTIFI-cohort: 42 samples from the CERTIFI trial of anti-TNFα-refractory CD patients; [2] the PROgECT-UNITI-HCs cohort: 46 UC samples of the PROgECT study, 84 CD samples of the UNITI I and UNITI II studies, and 72 healthy controls recruited in Mount Sinai Hospital, New York, USA. The plasma proteome for these two cohorts was quantified using high-throughput platforms.

RESULTS

For the PROgECT-UNITI-HCs cohort, we measured a total of 1310 proteins. Of these, 493 proteins showed different plasma levels in IBD patients to the plasma levels in controls at 10% false discovery rate [FDR], among which 11 proteins had a fold change greater than 2. The proteins upregulated in IBD were associated with immunity functionality, whereas the proteins downregulated in IBD were associated with nutrition and metabolism. The proteomic profiles were very similar between UC and CD. In the CERTIFI cohort, 1014 proteins were measured, and it was found that the plasma protein level had little correlation with the blood or intestine transcriptomes.

CONCLUSIONS

We report the largest proteomics study to date on IBD and controls. A large proportion of plasma proteins are altered in IBD, which provides insights into the disease aetiology and indicates a potential for biomarker discovery.

Neutrophils in Leprosy

Leprosy is an infectious disease caused by the intracellular bacillus Mycobacterium leprae that mainly affects the skin and peripheral nerves. One of the most intriguing aspects of leprosy is the diversity of its clinical forms. Paucibacillary patients are characterized as having less than five skin lesions and rare bacilli while the lesions in multibacillary patients are disseminated with voluminous bacilli. The chronic course of leprosy is often interrupted by acute episodes of an inflammatory immunological response classified as either reversal reaction or erythema nodosum leprosum (ENL). Although ENL is considered a neutrophilic immune-complex mediated condition, little is known about the direct role of neutrophils in ENL and leprosy disease overall. Recent studies have shown a renewed interest in neutrophilic biology. One of the most interesting recent discoveries was that the neutrophilic population is not homogeneous. Neutrophilic polarization leads to divergent phenotypes (e.g., a pro- and antitumor profile) that are dynamic subpopulations with distinct phenotypical and functional abilities. Moreover, there is emerging evidence indicating that neutrophils expressing CD64 favor systemic inflammation during ENL. In the present review, neutrophilic involvement in leprosy is discussed with a particular focus on ENL and the potential of neutrophils as clinical biomarkers and therapeutic targets.

Correlates of immune exacerbations in leprosy

Leprosy is still a considerable health threat in pockets of several low and middle income countries worldwide where intense transmission is witnessed, and often results in irreversible disabilities and deformities due to delayed- or misdiagnosis. Early detection of leprosy represents a substantial hurdle in present-day leprosy health care. The dearth of timely diagnosis has, however, particularly severe consequences in the case of inflammatory episodes, designated leprosy reactions, which represent the major cause of leprosy-associated irreversible neuropathy. There is currently no accurate, routine diagnostic test to reliably detect leprosy reactions, or to predict which patients will develop these immunological exacerbations. Identification of host biomarkers for leprosy reactions, particularly if correlating with early onset prior to development of clinical symptoms, will allow timely interventions that contribute to decreased morbidity. Development of a point-of-care (POC) test based on such correlates would be a definite game changer in leprosy health care. In this review, proteomic-, transcriptomic and metabolomic research strategies aiming at identification of host biomarker-based correlates of leprosy reactions are discussed, next to external factors associated with occurrence of these episodes. The vast diversity in research strategies combined with the variability in patient- and control cohorts argues for harmonisation of biomarker discovery studies with geographically overarching study sites. This will improve identification of specific correlates associated with risk of these damaging inflammatory episodes in leprosy and subsequent application to rapid field tests.

KLRD1-expressing natural killer cells predict influenza susceptibility

BACKGROUND

Influenza infects tens of millions of people every year in the USA. Other than notable risk groups, such as children and the elderly, it is difficult to predict what subpopulations are at higher risk of infection. Viral challenge studies, where healthy human volunteers are inoculated with live influenza virus, provide a unique opportunity to study infection susceptibility. Biomarkers predicting influenza susceptibility would be useful for identifying risk groups and designing vaccines.

METHODS

We applied cell mixture deconvolution to estimate immune cell proportions from whole blood transcriptome data in four independent influenza challenge studies. We compared immune cell proportions in the blood between symptomatic shedders and asymptomatic nonshedders across three discovery cohorts prior to influenza inoculation and tested results in a held-out validation challenge cohort.

RESULTS

Natural killer (NK) cells were significantly lower in symptomatic shedders at baseline in both discovery and validation cohorts. Hematopoietic stem and progenitor cells (HSPCs) were higher in symptomatic shedders at baseline in discovery cohorts. Although the HSPCs were higher in symptomatic shedders in the validation cohort, the increase was statistically nonsignificant. We observed that a gene associated with NK cells, KLRD1, which encodes CD94, was expressed at lower levels in symptomatic shedders at baseline in discovery and validation cohorts. KLRD1 expression in the blood at baseline negatively correlated with influenza infection symptom severity. KLRD1 expression 8 h post-infection in the nasal epithelium from a rhinovirus challenge study also negatively correlated with symptom severity.

CONCLUSIONS

We identified KLRD1-expressing NK cells as a potential biomarker for influenza susceptibility. Expression of KLRD1 was inversely correlated with symptom severity. Our results support a model where an early response by KLRD1-expressing NK cells may control influenza infection.

Innate Immune Responses in Leprosy

Leprosy is an infectious disease that may present different clinical forms depending on host immune response to Mycobacterium leprae. Several studies have clarified the role of various T cell populations in leprosy; however, recent evidences suggest that local innate immune mechanisms are key determinants in driving the disease to its different clinical manifestations. Leprosy is an ideal model to study the immunoregulatory role of innate immune molecules and its interaction with nervous system, which can affect homeostasis and contribute to the development of inflammatory episodes during the course of the disease. Macrophages, dendritic cells, neutrophils, and keratinocytes are the major cell populations studied and the comprehension of the complex networking created by cytokine release, lipid and iron metabolism, as well as antimicrobial effector pathways might provide data that will help in the development of new strategies for leprosy management.

The versatility of the CD1 lipid antigen presentation pathway

The family of non-classical major histocompatibility complex (MHC) class-I like CD1 molecules has an emerging role in human disease. Group 1 CD1 includes CD1a, CD1b and CD1c, which function to display lipids on the cell surface of antigen-presenting cells for direct recognition by T-cells. The recent advent of CD1 tetramers and the identification of novel lipid ligands has contributed towards the increasing number of CD1-restricted T-cell clones captured. These advances have helped to identify novel donor unrestricted and semi-invariant T-cell populations in humans and new mechanisms of T-cell recognition. However, although there is an opportunity to design broadly acting lipids and harness the therapeutic potential of conserved T-cells, knowledge of their role in health and disease is lacking. We briefly summarize the current evidence implicating group 1 CD1 molecules in infection, cancer and autoimmunity and show that although CD1 are not as diverse as MHC, recent discoveries highlight their versatility as they exhibit intricate mechanisms of antigen presentation.

Computational de novo discovery of distinguishing genes for biological processes and cell types in complex tissues

Bulk tissue samples examined by gene expression studies are usually heterogeneous. The data gained from these samples display the confounding patterns of mixtures consisting of multiple cell types or similar cell types in various functional states, which hinders the elucidation of the molecular mechanisms underlying complex biological phenomena. A realistic approach to compensate for the limitations of experimentally separating homogenous cell populations from mixed tissues is to computationally identify cell-type specific patterns from bulk, heterogeneous measurements. We designed the CellDistinguisher algorithm to analyze the gene expression data of mixed samples, identifying genes that best distinguish biological processes and cell types. Coupled with a deconvolution algorithm that takes cell type specific gene lists as input, we show that CellDistinguisher performs as well as partial deconvolution algorithms in predicting cell type composition without the need for prior knowledge of cell type signatures. This approach is also better in predicting cell type signatures than the one-step traditional complete deconvolution methods. To illustrate its wide applicability, the algorithm was tested on multiple publicly available data sets. In each case, CellDistinguisher identified genes reflecting biological processes typical for the tissues and development stages of interest and estimated the sample compositions accurately.

CD1b-restricted GEM T cell responses are modulated by Mycobacterium tuberculosis mycolic acid meromycolate chains

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major human pandemic. Germline-encoded mycolyl lipid-reactive (GEM) T cells are donor-unrestricted and recognize CD1b-presented mycobacterial mycolates. However, the molecular requirements governing mycolate antigenicity for the GEM T cell receptor (TCR) remain poorly understood. Here, we demonstrate CD1b expression in TB granulomas and reveal a central role for meromycolate chains in influencing GEM-TCR activity. Meromycolate fine structure influences T cell responses in TB-exposed individuals, and meromycolate alterations modulate functional responses by GEM-TCRs. Computational simulations suggest that meromycolate chain dynamics regulate mycolate head group movement, thereby modulating GEM-TCR activity. Our findings have significant implications for the design of future vaccines that target GEM T cells.

Cytokines as biomarkers to monitoring the impact of multidrug therapy in immune response of leprosy patients

Leprosy or Hansen's disease is a chronic infectious disease of the skin and nerves, caused by the intracellular bacilli Mycobacterium leprae. It is characterized by a spectrum of clinical forms depending on the host's immune response to M. leprae. Patients with tuberculoid (TT) leprosy have strong cell-mediated immunity (CMI) with elimination of the bacilli, whereas patients with lepromatous (LL) leprosy exhibit defective CMI to M. leprae. Despite advances in the understanding of the pathogenesis of leprosy and the development of new therapeutic strategies, there is a need for the identification of biomarkers which be used for early diagnosis and to discrimination between different forms of the disease, as prognostic markers. Here, we analyzed the serum levels of IL-1β, IL-6, IL-8, IL-10, IL-12p70, IL-13, IL-17A, IFN-γ and TNF in order to address the contribution of these cytokines in late phase of M. leprae infection, and the impact of multidrug therapy (MDT). Our results demonstrated that patients of LL group presented higher expression of serum levels of inflammatory cytokines before MDT, while TT patients presented a balance between inflammatory and regulatory cytokines. MDT changes the profile of serum cytokines in M. leprae infected patients, as evidenced by the cytokine network, especially in TT patients. LL patients displayed a multifaceted cytokine system characterized by strong connecting axes involving inflammatory/regulatory molecules, while TT patients showed low involvement of regulatory cytokines in network overall. Cytokines can be identified as good biomarkers of the impact of MDT on the immune system and the effectiveness of treatment.