Bedaquiline for treatment of non-tuberculous mycobacteria (NTM): a systematic review and meta-analysis.

BACKGROUND: Non-tuberculous mycobacteria (NTM) infections are increasing in incidence and associated mortality. NTM are naturally resistant to a variety of antibiotics, complicating treatment. We conducted a literature assessment on the efficacy of bedaquiline in treating NTM species in vitro and in vivo (animal models and humans); meta-analyses were performed where possible. METHOD: Four databases were searched using specific terms. Publications were included according to predefined criteria. Bedaquiline's impact on NTM in vitro, MICs and epidemiological cut-off (ECOFF) values were evaluated. A meta-analysis of bedaquiline efficacy against NTM infections in animal models was performed. Culture conversion, cure and/or relapse-free cure were used to evaluate the efficacy of bedaquiline in treating NTM infection in humans. RESULTS: Fifty studies met the inclusion criteria: 33 assessed bedaquiline's impact on NTM in vitro, 9 in animal models and 8 in humans. Three studies assessed bedaquiline's efficacy both in vitro and in vivo. Due to data paucity, an ECOFF value of 0.5 mg/mL was estimated for Mycobacterium abscessus only. Meta-analysis of animal studies showed a 1.86× reduction in bacterial load in bedaquiline-treated versus no treatment within 30 days. In humans, bedaquiline-including regimens were effective in treating NTM extrapulmonary infection but not pulmonary infection. CONCLUSIONS: Bedaquiline demonstrated strong antibacterial activity against various NTM species and is a promising drug to treat NTM infections. However, data on the genomic mutations associated with bedaquiline resistance were scarce, preventing statistical analyses for most mutations and NTM species. Further studies are urgently needed to better inform treatment strategies.

Human dermal fibroblast-derived exosomes induce macrophage activation in systemic sclerosis.

OBJECTIVES: Prior work demonstrates that co-cultured macrophages and fibroblasts from patients with SSc engage in reciprocal activation. However, the mechanism by which these cell types communicate and contribute to fibrosis and inflammation in SSc is unknown. METHODS: Fibroblasts were isolated from skin biopsies obtained from 7 SSc patients or 6 healthy age and gender-matched control subjects following written informed consent. Human donor-derived macrophages were cultured with exosomes isolated from control or SSc fibroblasts for an additional 48 h. Macrophages were immunophenotyped using flow cytometry, qRT-PCR and multiplex. For mutual activation studies, exosome-activated macrophages were co-cultured with SSc or healthy fibroblasts using Transwells. RESULTS: Macrophages activated with dermal fibroblast-derived exosomes from SSc patients upregulated surface expression of CD163, CD206, MHC Class II and CD16 and secreted increased levels of IL-6, IL-10, IL-12p40 and TNF compared with macrophages incubated with healthy control fibroblasts (n = 7, P < 0.05). Exosome-stimulated macrophages and SSc fibroblasts engaged in reciprocal activation, as production of collagen and fibronectin was significantly increased in SSc fibroblasts receiving signals from SSc exosome-stimulated macrophages (n = 7, P < 0.05). CONCLUSION: In this work, we demonstrate for the first time that human SSc dermal fibroblasts mediate macrophage activation through exosomes. Our findings suggest that macrophages and fibroblasts engage in cross-talk in SSc skin, resulting in mutual activation, inflammation, and extracellular matrix (ECM) deposition. Collectively, these studies implicate macrophages and fibroblasts as cooperative mediators of fibrosis in SSc and suggest therapeutic targeting of both cell types may provide maximal benefit in ameliorating disease in SSc patients.

Oral Class I and III antiarrhythmic drugs for maintaining sinus rhythm after catheter ablation of atrial fibrillation.

BACKGROUND: Recurrence of atrial tachyarrhythmias (ATa) following catheter ablation for atrial fibrillation (AF) is a common problem. Antiarrhythmic drugs have been used shortly after ablation in an attempt to maintain sinus rhythm, particularly Class I and III agents. However, it still needs to be established if the use of Class I or III antiarrhythmic medications, or both, reduce the risk of recurrence of ATa. OBJECTIVES: To assess the effects of oral Class I and III antiarrhythmic drugs versus control (standard medical therapy without Class I or III antiarrhythmics, or placebo) for maintaining sinus rhythm in people undergoing catheter ablation for AF. SEARCH METHODS: We systematically searched CENTRAL, MEDLINE, Embase, Web of Science Core Collection, and two clinical trial registers without restrictions on language or date to 5 August 2022. SELECTION CRITERIA: We sought published, unpublished, and ongoing parallel-design, randomised controlled trials (RCTs) involving adult participants undergoing ablation for AF, with subsequent comparison of Class I and/or III antiarrhythmic use versus control (standard medical therapy or non-Class I and/or III antiarrhythmic use). DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane and performed meta-analyses with risk ratios (RR) and Peto odds ratios (Peto OR). Our primary outcomes were recurrence of atrial tachyarrhythmias; adverse events: thromboembolic events; adverse events: myocardial infarction; adverse events: new diagnosis of heart failure; and adverse events: requirement for one or more hospitalisations for atrial tachyarrhythmia. Our secondary outcomes were: all-cause mortality; and requirement for one or more repeat ablations. Where possible, we performed comparison analysis by Class I and/or III antiarrhythmic and divided follow-up periods for our primary outcome. We performed comprehensive assessments of risk of bias and certainty of evidence applying the GRADE methodology. MAIN RESULTS: We included nine RCTs involving a total of 3269 participants. Participants were on average 59.3 years old; 71.0% were male; and 72.9% and 27.4% had paroxysmal and persistent AF, respectively. Class I and/or III antiarrhythmics may reduce recurrence of ATa at 0 to 3 months postablation (risk ratio (RR) 0.74, 95% confidence interval (CI) 0.59 to 0.94, 8 trials, 3046 participants, low-certainty evidence) and likely reduce recurrence at > 3 to 6 months, our a priori primary time point (RR 0.85, 95% CI 0.78 to 0.93, 5 trials, 2591 participants, moderate-certainty evidence). Beyond six months the evidence is very uncertain, and the benefit of antiarrhythmics may not persist (RR 1.14, 95% CI 0.84 to 1.55, 4 trials, 2244 participants, very low-certainty evidence). The evidence suggests that Class I and/or III antiarrhythmics may not increase the risk of thromboembolic events, myocardial infarction, all-cause mortality, or requirement for repeat ablation, at 0 to 3, > 3 to 6, and > 6 months (where data were available; low- to very low-certainty evidence). The use of Class I and/or III antiarrhythmics postablation likely reduces hospitalisations for ATa by approximately 57% at 0 to 3 months (RR 0.43, 95% CI 0.28 to 0.64, moderate-certainty evidence). No data were available beyond three months. No data were available on new diagnoses of heart failure. Fewer data were available for Class I and III antiarrhythmics individually. Based on only one and two trials (n = 125 to 309), Class I antiarrhythmics may have little effect on recurrence of ATa at 0 to 3, > 3 to 6, and > 6 months (RR 0.88, 95% CI 0.64 to 1.20, 2 trials, 309 participants; RR 0.54, 95% CI 0.25 to 1.19, 1 trial, 125 participants; RR 0.87, 95% CI 0.57 to 1.32, 1 trial, 125 participants; low-certainty evidence throughout); requirement for hospitalisation for ATa at 0 to 3 months (low-certainty evidence); or requirement for repeat ablation at 0 to 3 months (low-certainty evidence). No data were available for thromboembolic events, myocardial infarction, new diagnosis of heart failure, or all-cause mortality at any time points, or hospitalisation or repeat ablation beyond three months. Class III antiarrhythmics may have little effect on recurrence of ATa at up to 3 months and at > 3 to 6 months (RR 0.76, 95% CI 0.50 to 1.16, 4 trials, 599 participants, low-certainty evidence; RR 0.82, 95% CI 0.62 to 1.09, 2 trials, 318 participants, low-certainty evidence), and beyond 6 months one trial reported a possible increase in recurrence of ATa (RR 1.95, 95% CI 1.29 to 2.94, 1 trial, 112 participants, low-certainty evidence). Class III antiarrhythmics likely reduce hospitalisations for ATa at 0 to 3 months (RR 0.40, 95% CI 0.26 to 0.63, moderate-certainty evidence), and may have little effect on all-cause mortality (low- to very low-certainty evidence). The effect of Class III antiarrhythmics on thromboembolic events and requirement for repeat ablation was uncertain (very low-certainty evidence for both outcomes). No data were available for myocardial infarction or new diagnosis of heart failure at any time point, outcomes other than recurrence beyond 6 months, or for hospitalisation and repeat ablation > 3 to 6 months. We assessed the majority of included trials as at low or unclear risk of bias. One trial reported an error in the randomisation process, raising the potential risk of selection bias; most of the included trials were non-blinded; and two trials were at high risk of attrition bias. AUTHORS' CONCLUSIONS: We found evidence to suggest that the use of Class I and/or III antiarrhythmics up to 3 months after ablation is associated with a reduced recurrence of ATa 0 to 6 months after ablation, which may not persist beyond 6 months, and an immediate reduction in hospitalisation for ATa 0 to 3 months after ablation. The evidence suggests there is no difference in rates of all-cause mortality, thromboembolic events, or myocardial infarction between Class I and/or III antiarrhythmics versus control.

Comparative Performance of Genomic Methods for the Detection of Pyrazinamide Resistance and Heteroresistance in Mycobacterium tuberculosis.

Pyrazinamide is an important component of both drug-susceptible and drug-resistant tuberculosis treatment regimens. Although approximately 50% of rifampin-resistant isolates are also resistant to pyrazinamide, pyrazinamide susceptibility testing is not routinely performed due to the challenging nature of the assay. We investigated the diagnostic accuracy of genotypic and phenotypic methods and explored the occurrence of pyrazinamide heteroresistance. We assessed pyrazinamide susceptibility among 358 individuals enrolled in the South African EXIT-RIF cohort using Sanger and targeted deep sequencing (TDS) of the pncA gene, whole-genome sequencing (WGS), and phenotypic drug susceptibility testing. We calculated the diagnostic accuracy of the different methods and investigated the prevalence and clinical impact of pncA heteroresistance. True pyrazinamide susceptibility status was assigned to each isolate using the Köser classification and expert rules. We observed 100% agreement across genotypic methods for detection of pncA fixed mutations; only TDS confidently identified three isolates (0.8%) with minor variants. For the 355 (99.2%) isolates that could be assigned true pyrazinamide status with confidence, phenotypic DST had a sensitivity of 96.5% (95% confidence interval [CI], 93.8 to 99.3%) and specificity of 100% (95% CI, 100 to 100%), both Sanger sequencing and WGS had a sensitivity of 97.1% (95% CI, 94.6 to 99.6%) and specificity of 97.8% (95% CI, 95.7 to 99.9%), and TDS had sensitivity of 98.8% (95% CI, 97.2 to 100%) and specificity of 97.8% (95% CI, 95.7 to 99.9%). We demonstrate high sensitivity and specificity for pyrazinamide susceptibility testing among all assessed genotypic methods. The prevalence of pyrazinamide heteroresistance in Mycobacterium tuberculosis isolates was lower than that identified for other first-line drugs.

A genomic meta-analysis of clinical variables and their association with intrinsic molecular subsets in systemic sclerosis.

OBJECTIVES: Four intrinsic molecular subsets (inflammatory, fibroproliferative, limited, normal-like) have previously been identified in SSc and are characterized by unique gene expression signatures and pathways. The intrinsic subsets have been linked to improvement with specific therapies. Here, we investigated associations between baseline demographics and intrinsic molecular subsets in a meta-analysis of published datasets. METHODS: Publicly available gene expression data from skin biopsies of 311 SSc patients measured by DNA microarray were classified into the intrinsic molecular subsets. RNA-sequencing data from 84 participants from the ASSET trial were used as a validation cohort. Baseline clinical demographics and intrinsic molecular subsets were tested for statistically significant associations. RESULTS: Males were more likely to be classified in the fibroproliferative subset (P = 0.0046). SSc patients who identified as African American/Black were 2.5 times more likely to be classified as fibroproliferative compared with White/Caucasian patients (P = 0.0378). ASSET participants sera positive for anti-RNA pol I and RNA pol III autoantibodies were enriched in the inflammatory subset (P = 5.8 × 10-5, P = 9.3 × 10-5, respectively), while anti-Scl-70 was enriched in the fibroproliferative subset. Mean modified Rodnan Skin Score (mRSS) was statistically higher in the inflammatory and fibroproliferative subsets compared with normal-like (P = 0.0027). The average disease duration for inflammatory subset was less than fibroproliferative and normal-like intrinsic subsets (P = 8.8 × 10-4). CONCLUSIONS: We identified multiple statistically significant differences in baseline demographics between the intrinsic subsets that may represent underlying features of disease pathogenesis (e.g. chronological stages of fibrosis) and have implications for treatments that are more likely to work in certain SSc populations.

Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.

OBJECTIVE: We sought to determine histologic and gene expression features of clinical improvement in early diffuse cutaneous systemic sclerosis (dcSSc; scleroderma). METHODS: Fifty-eight forearm biopsies were evaluated from 26 individuals with dcSSc in two clinical trials. Histologic/immunophenotypic assessments of global severity, alpha-smooth muscle actin (aSMA), CD34, collagen, inflammatory infiltrate, follicles and thickness were compared with gene expression and clinical data. Support vector machine learning was performed using scleroderma gene expression subset (normal-like, fibroproliferative, inflammatory) as classifiers and histology scores as inputs. Comparison of w-vector mean absolute weights was used to identify histologic features most predictive of gene expression subset. We then tested for differential gene expression according to histologic severity and compared those with clinical improvement (according to the Combined Response Index in Systemic Sclerosis). RESULTS: aSMA was highest and CD34 lowest in samples with highest local Modified Rodnan Skin Score. CD34 and aSMA changed significantly from baseline to 52 weeks in clinical improvers. CD34 and aSMA were the strongest predictors of gene expression subset, with highest CD34 staining in the normal-like subset (p<0.001) and highest aSMA staining in the inflammatory subset (p=0.016). Analysis of gene expression according to CD34 and aSMA binarised scores identified a 47-gene fibroblast polarisation signature that decreases over time only in improvers (vs non-improvers). Pathway analysis of these genes identified gene expression signatures of inflammatory fibroblasts. CONCLUSION: CD34 and aSMA stains describe distinct fibroblast polarisation states, are associated with gene expression subsets and clinical assessments, and may be useful biomarkers of clinical severity and improvement in dcSSc.

SARS-CoV-2 Impairs Dendritic Cells and Regulates DC-SIGN Gene Expression in Tissues.

The current spreading coronavirus SARS-CoV-2 is highly infectious and pathogenic. In this study, we screened the gene expression of three host receptors (ACE2, DC-SIGN and L-SIGN) of SARS coronaviruses and dendritic cells (DCs) status in bulk and single cell transcriptomic datasets of upper airway, lung or blood of COVID-19 patients and healthy controls. In COVID-19 patients, DC-SIGN gene expression was interestingly decreased in lung DCs but increased in blood DCs. Within DCs, conventional DCs (cDCs) were depleted while plasmacytoid DCs (pDCs) were augmented in the lungs of mild COVID-19. In severe cases, we identified augmented types of immature DCs (CD22+ or ANXA1+ DCs) with MHCII downregulation. In this study, our observation indicates that DCs in severe cases stimulate innate immune responses but fail to specifically present SARS-CoV-2. It provides insights into the profound modulation of DC function in severe COVID-19.

Discordances between molecular assays for rifampicin resistance in Mycobacterium tuberculosis: frequency, mechanisms and clinical impact.

BACKGROUND: Molecular assays are endorsed for detection and confirmation of rifampicin-resistant TB. The frequency, causal mechanisms and impact of discordant results between molecular tests are not well understood. METHODS: The prevalence of discordant results was determined by pairwise comparison of molecular test results in a cohort of 749 rifampicin-resistant TB patients in three South African provinces. Culture isolates were sent to a research laboratory for WGS and rifampicin MIC determination. Clinical information was collected through medical file review. RESULTS: The prevalence of discordances between Xpert MTB/RIF and MTBDRplus was 14.5% (95% CI 10.9%-18.9%), 5.6% (95% CI 2.2%-13.4%) between two consecutive Xpert assays and 4.2% (95% CI 2.2%-7.8%) between two consecutive MTBDRplus assays. Likely mechanisms of discordances were false rifampicin susceptibility on MTBDRplus (due to variants not included in mutant probes or heteroresistance with loss of minor variants in culture), false resistance on molecular assay in rifampicin-susceptible isolates, and human error. The healthcare worker changed the treatment regimen in 33% of patients with discordant results and requested 232 additional molecular tests after a first confirmatory test was performed in 460 patients. A follow-up Xpert assay would give the healthcare worker the 'true' rifampicin-resistant TB diagnosis in at least 73% of discordant cases. CONCLUSIONS: The high rate of discordant results between Xpert and MTBDRplus has important implications for the laboratory, clinician and patient. While root causes for discordant result are multiple, a follow-up Xpert assay could guide healthcare workers to the correct treatment in most patients.

BioMethyl: an R package for biological interpretation of DNA methylation data.

MOTIVATION: The accumulation of publicly available DNA methylation datasets has resulted in the need for tools to interpret the specific cellular phenotypes in bulk tissue data. Current approaches use either single differentially methylated CpG sites or differentially methylated regions that map to genes. However, these approaches may introduce biases in downstream analyses of biological interpretation, because of the variability in gene length. There is a lack of approaches to interpret DNA methylation effectively. Therefore, we have developed computational models to provide biological interpretation of relevant gene sets using DNA methylation data in the context of The Cancer Genome Atlas. RESULTS: We illustrate that Biological interpretation of DNA Methylation (BioMethyl) utilizes the complete DNA methylation data for a given cancer type to reflect corresponding gene expression profiles and performs pathway enrichment analyses, providing unique biological insight. Using breast cancer as an example, BioMethyl shows high consistency in the identification of enriched biological pathways from DNA methylation data compared to the results calculated from RNA sequencing data. We find that 12 out of 14 pathways identified by BioMethyl are shared with those by using RNA-seq data, with a Jaccard score 0.8 for estrogen receptor (ER) positive samples. For ER negative samples, three pathways are shared in the two enrichments with a slight lower similarity (Jaccard score = 0.6). Using BioMethyl, we can successfully identify those hidden biological pathways in DNA methylation data when gene expression profile is lacking. AVAILABILITY AND IMPLEMENTATION: BioMethyl R package is freely available in the GitHub repository (https://github.com/yuewangpanda/BioMethyl). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Machine learning predicts stem cell transplant response in severe scleroderma.

OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT clinical trial to scleroderma intrinsic subsets and tested the hypothesis that they predict long-term response to HSCT. METHODS: We analysed gene expression from PBCs of SCOT participants to identify differential treatment response. PBC gene expression data were generated from 63 SCOT participants at baseline and follow-up timepoints. Participants who completed treatment protocol were stratified by intrinsic gene expression subsets at baseline, evaluated for event-free survival (EFS) and analysed for differentially expressed genes (DEGs). RESULTS: Participants from the fibroproliferative subset on HSCT experienced significant improvement in EFS compared with fibroproliferative participants on CYC (p=0.0091). In contrast, EFS did not significantly differ between CYC and HSCT arms for the participants from the normal-like subset (p=0.77) or the inflammatory subset (p=0.1). At each timepoint, we observed considerably more DEGs in HSCT arm compared with CYC arm with HSCT arm showing significant changes in immune response pathways. CONCLUSIONS: Participants from the fibroproliferative subset showed the most significant long-term benefit from HSCT compared with CYC. This study suggests that intrinsic subset stratification of patients may be used to identify patients with SSc who receive significant benefit from HSCT.

Global skin gene expression analysis of early diffuse cutaneous systemic sclerosis shows a prominent innate and adaptive inflammatory profile.

OBJECTIVES: Determine global skin transcriptome patterns of early diffuse systemic sclerosis (SSc) and how they differ from later disease. METHODS: Skin biopsy RNA from 48 patients in the Prospective Registry for Early Systemic Sclerosis (PRESS) cohort (mean disease duration 1.3 years) and 33 matched healthy controls was examined by next-generation RNA sequencing. Data were analysed for cell type-specific signatures and compared with similarly obtained data from 55 previously biopsied patients in Genetics versus Environment in Scleroderma Outcomes Study cohort with longer disease duration (mean 7.4 years) and their matched controls. Correlations with histological features and clinical course were also evaluated. RESULTS: SSc patients in PRESS had a high prevalence of M2 (96%) and M1 (94%) macrophage and CD8 T cell (65%), CD4 T cell (60%) and B cell (69%) signatures. Immunohistochemical staining of immune cell markers correlated with the gene expression-based immune cell signatures. The prevalence of immune cell signatures in early diffuse SSc patients was higher than in patients with longer disease duration. In the multivariable model, adaptive immune cell signatures were significantly associated with shorter disease duration, while fibroblast and macrophage cell type signatures were associated with higher modified Rodnan Skin Score (mRSS). Immune cell signatures also correlated with skin thickness progression rate prior to biopsy, but did not predict subsequent mRSS progression. CONCLUSIONS: Skin in early diffuse SSc has prominent innate and adaptive immune cell signatures. As a prominently affected end organ, these signatures reflect the preceding rate of disease progression. These findings could have implications in understanding SSc pathogenesis and clinical trial design.

Lysyl oxidase enzymes mediate TGF-ß1-induced fibrotic phenotypes in human skin-like tissues.

Cutaneous fibrosis is a common complication seen in mixed connective tissue diseases. It often occurs as a result of TGF-ß-induced deposition of excessive amounts of collagen in the skin. Lysyl oxidases (LOXs), a family of extracellular matrix (ECM)-modifying enzymes responsible for collagen cross-linking, are known to be increased in dermal fibroblasts from patients with fibrotic diseases, denoting a possible role of LOXs in fibrosis. To directly study this, we have developed two bioengineered, in vitro skin-like models: human skin equivalents (hSEs), and self-assembled stromal tissues (SASs) that contain either normal or systemic sclerosis (SSc; scleroderma) patient-derived fibroblasts. These tissues provide an organ-level structure that could be combined with non-invasive, label-free, multiphoton microscopy (SHG/TPEF) to reveal alterations in the organization and cross-linking levels of collagen fibers during the development of cutaneous fibrosis, which demonstrated increased stromal rigidity and activation of dermal fibroblasts in response to TGF-ß1. Specifically, inhibition of specific LOXs isoforms, LOX and LOXL4, in foreskin fibroblasts (HFFs) resulted in antagonistic effects on TGF-ß1-induced fibrogenic hallmarks in both hSEs and SASs. In addition, a translational relevance of these models was seen as similar antifibrogenic phenotypes were achieved upon knocking down LOXL4 in tissues containing SSc patient-derived-dermal fibroblasts (SScDFs). These findings point to a pivotal role of LOXs in TGF-ß1-induced cutaneous fibrosis through impaired ECM homeostasis in skin-like tissues, and show the value of these tissue platforms in accelerating the discovery of antifibrosis therapeutics.

Feature specific quantile normalization enables cross-platform classification of molecular subtypes using gene expression data.

Motivation: Molecular subtypes of cancers and autoimmune disease, defined by transcriptomic profiling, have provided insight into disease pathogenesis, molecular heterogeneity and therapeutic responses. However, technical biases inherent to different gene expression profiling platforms present a unique problem when analyzing data generated from different studies. Currently, there is a lack of effective methods designed to eliminate platform-based bias. We present a method to normalize and classify RNA-seq data using machine learning classifiers trained on DNA microarray data and molecular subtypes in two datasets: breast invasive carcinoma (BRCA) and colorectal cancer (CRC). Results: Multiple analyses show that feature specific quantile normalization (FSQN) successfully removes platform-based bias from RNA-seq data, regardless of feature scaling or machine learning algorithm. We achieve up to 98% accuracy for BRCA data and 97% accuracy for CRC data in assigning molecular subtypes to RNA-seq data normalized using FSQN and a support vector machine trained exclusively on DNA microarray data. We find that maximum accuracy was achieved when normalizing RNA-seq datasets that contain at least 25 samples. FSQN allows comparison of RNA-seq data to existing DNA microarray datasets. Using these techniques, we can successfully leverage information from existing gene expression data in new analyses despite different platforms used for gene expression profiling. Availability and implementation: FSQN has been submitted as an R package to CRAN. All code used for this study is available on Github (https://github.com/jenniferfranks/FSQN). Contact: michael.l.whitfield@dartmouth.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

The potential use of rifabutin for treatment of patients diagnosed with rifampicin-resistant tuberculosis.

Background: Use of the Xpert MTB/RIF assay has increased the number of people diagnosed with rifampicin-resistant tuberculosis (RR-TB), especially in South Africa where Xpert is now the initial diagnostic for individuals with TB symptoms. We hypothesized that a proportion of RR-TB patients determined by Xpert can be treated with a rifabutin-containing regimen. Methods: Rifabutin susceptibility by rpoB mutation was assessed in 349 individuals from South Africa and 172 from Belgium. rpoB polymorphisms were identified by Sanger sequencing. Rifampicin and rifabutin susceptibility was assessed phenotypically. A systematic review was performed to comprehensively collate information on rifabutin susceptibility by rpoB polymorphism. Rifabutin susceptibility was assigned to rpoB polymorphisms based on their positive likelihood ratios and ORs. Results: One hundred and twelve rpoB polymorphisms (67.9% from literature) were identified from all 2045 RR-TB patients, of which 17 polymorphisms could be classified as susceptible/resistant to rifabutin. Eleven polymorphisms were associated with rifabutin susceptibility. The 516GTC mutation was the most common, representing 70% (South Africa) and 76% (Belgium) of all rifabutin-susceptible isolates. At a population level, the 11 polymorphisms associated with rifabutin susceptibility occurred in 33.2% and 16.6% of all South African and Belgian patients diagnosed with RR-TB, respectively. Conclusions: Identification of the exact rpoB polymorphism leading to the diagnosis of RR-TB has the potential to allow inclusion of rifabutin in the treatment regimen of a substantial proportion of RR-TB patients. A randomized controlled trial evaluating the efficacy of a rifabutin-containing TB treatment regimen in these selected patients is needed to provide the evidence required for a change in policy.

A subset of replication-dependent histone mRNAs are expressed as polyadenylated RNAs in terminally differentiated tissues.

Histone proteins are synthesized in large amounts during S-phase to package the newly replicated DNA, and are among the most stable proteins in the cell. The replication-dependent (RD)-histone mRNAs expressed during S-phase end in a conserved stem-loop rather than a polyA tail. In addition, there are replication-independent (RI)-histone genes that encode histone variants as polyadenylated mRNAs. Most variants have specific functions in chromatin, but H3.3 also serves as a replacement histone for damaged histones in long-lived terminally differentiated cells. There are no reported replacement histone genes for histones H2A, H2B or H4. We report that a subset of RD-histone genes are expressed in terminally differentiated tissues as polyadenylated mRNAs, likely serving as replacement histone genes in long-lived non-dividing cells. Expression of two genes, HIST2H2AA3 and HIST1H2BC, is conserved in mammals. They are expressed as polyadenylated mRNAs in fibroblasts differentiated in vitro, but not in serum starved fibroblasts, suggesting that their expression is part of the terminal differentiation program. There are two histone H4 genes and an H3 gene that encode mRNAs that are polyadenylated and expressed at 5- to 10-fold lower levels than the mRNAs from H2A and H2B genes, which may be replacement genes for the H3.1 and H4 proteins.

A multiprotein occupancy map of the mRNP on the 3' end of histone mRNAs.

The animal replication-dependent (RD) histone mRNAs are coordinately regulated with chromosome replication. The RD-histone mRNAs are the only known cellular mRNAs that are not polyadenylated. Instead, the mature transcripts end in a conserved stem-loop (SL) structure. This SL structure interacts with the stem-loop binding protein (SLBP), which is involved in all aspects of RD-histone mRNA metabolism. We used several genomic methods, including high-throughput sequencing of cross-linked immunoprecipitate (HITS-CLIP) to analyze the RNA-binding landscape of SLBP. SLBP was not bound to any RNAs other than histone mRNAs. We performed bioinformatic analyses of the HITS-CLIP data that included (i) clustering genes by sequencing read coverage using CVCA, (ii) mapping the bound RNA fragment termini, and (iii) mapping cross-linking induced mutation sites (CIMS) using CLIP-PyL software. These analyses allowed us to identify specific sites of molecular contact between SLBP and its RD-histone mRNA ligands. We performed in vitro crosslinking assays to refine the CIMS mapping and found that uracils one and three in the loop of the histone mRNA SL preferentially crosslink to SLBP, whereas uracil two in the loop preferentially crosslinks to a separate component, likely the 3'hExo. We also performed a secondary analysis of an iCLIP data set to map UPF1 occupancy across the RD-histone mRNAs and found that UPF1 is bound adjacent to the SLBP-binding site. Multiple proteins likely bind the 3' end of RD-histone mRNAs together with SLBP.

Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

PURPOSE OF REVIEW: The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. RECENT FINDINGS: Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. SUMMARY: Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

Downregulation of miR-193b in systemic sclerosis regulates the proliferative vasculopathy by urokinase-type plasminogen activator expression.

OBJECTIVES: To investigate the role of microRNA-193b-3p (miR-193b) in the vascular pathophysiology of systemic sclerosis (SSc). METHODS: Expression of miR-193b in skin biopsies and fibroblasts from patients with SSc and normal healthy (NH) controls were determined by real-time PCR. Transfection with miR-193b precursor and inhibitor were used to confirm targets of miR-193b. Proliferative effects of urokinase-type plasminogen activator (uPA) were determined by water-soluble tetrazolium salt-1 assay and by analysis of proliferating cell nuclear antigen expression. Fluorescence activated cell sorting analysis was performed to investigate the effect of uPA on apoptosis. For inhibition of the uPA-cellular receptor for uPA (uPAR) pathway, uPAR neutralising antibodies and low molecular weight uPA were used. RESULTS: We found that miR-193b was downregulated in SSc fibroblasts and skin sections as compared with NH controls. The expression of miR-193b was not affected by major profibrotic cytokines and hypoxia. Induction of miR-193b in SSc fibroblasts suppressed, and accordingly, knockdown of miR-193b increased the levels of messenger RNA and protein for uPA. uPA was found to be upregulated in SSc as compared with NH controls in a transforming growth factor-ß dependent manner, and uPA was strongly expressed in vascular smooth muscle cells in SSc skin section. Interestingly, uPA induced cell proliferation and inhibited apoptosis of human pulmonary artery smooth muscle cells, and these effects were independent of uPAR signalling. CONCLUSIONS: In SSc, the downregulation of miR-193b induces the expression of uPA, which increases the number of vascular smooth muscle cells in an uPAR-independent manner and thereby contributes to the proliferative vasculopathy with intimal hyperplasia characteristic for SSc.

Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms.

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6-12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk.

Mycobacterium tuberculosis pncA Polymorphisms That Do Not Confer Pyrazinamide Resistance at a Breakpoint Concentration of 100 Micrograms per Milliliter in MGIT.

Sequencing of the Mycobacterium tuberculosis pncA gene allows for pyrazinamide susceptibility testing. We summarize data on pncA polymorphisms that do not confer resistance at a susceptibility breakpoint of 100 µg/ml pyrazinamide in MGIT within a cohort of isolates from South Africa and the U.S. Centers for Disease Control and Prevention.