Profiling Microbial Communities in Idiopathic Granulomatous Mastitis.

Idiopathic granulomatous mastitis (IGM) is a rare and benign inflammatory breast disease with ambiguous aetiology. Contrastingly, lactational mastitis (LM) is commonly diagnosed in breastfeeding women. To investigate IGM aetiology, we profiled the microbial flora of pus and skin in patients with IGM and LM. A total of 26 patients with IGM and 6 patients with LM were included in the study. The 16S rRNA sequencing libraries were constructed from 16S rRNA gene amplified from total DNA extracted from pus and skin swabs in patients with IGM and LM controls. Constructed libraries were multiplexed and paired-end sequenced on HiSeq4000. Metagenomic analysis was conducted using modified microbiome abundance analysis suite customised R-resource for paired pus and skin samples. Microbiome multivariable association analyses were performed using linear models. A total of 21 IGM and 3 LM paired pus and skin samples underwent metagenomic analysis. Bray−Curtis ecological dissimilarity distance showed dissimilarity across four sample types (IGM pus, IGM skin, LM pus, and LM skin; PERMANOVA, p < 0.001). No characteristic dominant genus was observed across the IGM samples. The IGM pus samples were more diverse than corresponding IGM skin samples (Shannon and Simpson index; Wilcoxon paired signed-rank tests, p = 0.022 and p = 0.07). Corynebacterium kroppenstedtii, reportedly associated with IGM in the literature, was higher in IGM pus samples than paired skin samples (Wilcoxon, p = 0.022). Three other species and nineteen genera were statistically significant in paired IGM pus−skin comparison after antibiotic treatment adjustment and multiple comparisons correction. Microbial profiles are unique between patients with IGM and LM. Inter-patient variability and polymicrobial IGM pus samples cannot implicate specific genus or species as an infectious cause for IGM.

Gene expression responses to anti-tuberculous drugs in a whole blood model.

BACKGROUND: There is a need for better tools to evaluate new or repurposed TB drugs. The whole blood bactericidal activity (WBA) assay has been advocated for this purpose. We investigated whether transcriptional responses in the WBA assay resemble TB responses in vivo, and whether the approach might additionally reveal mechanisms of action. RESULTS: 1422 of 1798 (79%) of differentially expressed genes in WBA incubated with the standard combination of rifampicin, isoniazid, pyrazinamide and ethambutol were also expressed in sputum (P < 0.0001) obtained from patients taking the same combination of drugs; these comprised well-established treatment-response genes. Gene expression profiles in WBA incubated with the standard drugs individually, or with moxifloxacin or faropenem (with amoxicillin and clavulanic acid) clustered by individual drug exposure. Distinct pathways were detected for individual drugs, although only with isoniazid did these relate to known mechanisms of drug action. CONCLUSIONS: Substantial agreement between whole blood cultures and sputum and the ability to differentiate individual drugs suggest that transcriptomics may add value to the whole blood assay for evaluating new TB drugs.

A blood RNA transcript signature for TB exposure in household contacts.

BACKGROUND: Current tools for diagnosing latent TB infection (LTBI) detect immunological memory of past exposure but are unable to determine whether exposure is recent. We sought to identify a whole-blood transcriptome signature of recent TB exposure. METHODS: We studied household contacts of TB patients; healthy volunteers without recent history of TB exposure; and patients with active TB. We performed whole-blood RNA sequencing (in all), an interferon gamma release assay (IGRA; in contacts and healthy controls) and PET/MRI lung scans (in contacts only). We evaluated differentially-expressed genes in household contacts (log2 fold change ≥1 versus healthy controls; false-discovery rate < 0.05); compared these to differentially-expressed genes seen in the active TB group; and assessed the association of a composite gene expression score to independent exposure/treatment/immunological variables. RESULTS: There were 186 differentially-expressed genes in household contacts (n = 26, age 22-66, 46% male) compared with healthy controls (n = 5, age 29-38, 100% male). Of these genes, 141 (76%) were also differentially expressed in active TB (n = 14, age 27-69, 71% male). The exposure signature included genes from inflammatory response, type I interferon signalling and neutrophil-mediated immunity pathways; and genes such as BATF2 and SCARF1 known to be associated with incipient TB. The composite gene-expression score was higher in IGRA-positive contacts (P = 0.04) but not related to time from exposure, isoniazid prophylaxis, or abnormalities on PET/MRI (all P > 0.19). CONCLUSIONS: Transcriptomics can detect TB exposure and, with further development, may be an approach of value for epidemiological research and targeting public health interventions.

A blood RNA transcriptome signature for COVID-19.

BACKGROUND: COVID-19 is a respiratory viral infection with unique features including a more chronic course and systemic disease manifestations including multiple organ involvement; and there are differences in disease severity between ethnic groups. The immunological basis for disease has not been fully characterised. Analysis of whole-blood RNA expression may provide valuable information on disease pathogenesis. METHODS: We studied 45 patients with confirmed COVID-19 infection within 10 days from onset of illness and a control group of 19 asymptomatic healthy volunteers with no known exposure to COVID-19 in the previous 14 days. Relevant demographic and clinical information was collected and a blood sample was drawn from all participants for whole-blood RNA sequencing. We evaluated differentially-expressed genes in COVID-19 patients (log2 fold change ≥ 1 versus healthy controls; false-discovery rate < 0.05) and associated protein pathways and compared these to published whole-blood signatures for respiratory syncytial virus (RSV) and influenza. We developed a disease score reflecting the overall magnitude of expression of internally-validated genes and assessed the relationship between the disease score and clinical disease parameters. RESULTS: We found 135 differentially-expressed genes in the patients with COVID-19 (median age 35 years; 82% male; 36% Chinese, 53% South Asian ethnicity). Of the 117 induced genes, 14 were found in datasets from RSV and 40 from influenza; 95 genes were unique to COVID-19. Protein pathways were mostly generic responses to viral infections, including apoptosis by P53-associated pathway, but also included some unique pathways such as viral carcinogenesis. There were no major qualitative differences in pathways between ethnic groups. The composite gene-expression score was correlated with the time from onset of symptoms and nasal swab qPCR CT values (both p < 0.01) but was not related to participant age, gender, ethnicity or the presence or absence of chest X-ray abnormalities (all p > 0.05). CONCLUSIONS: The whole-blood transcriptome of COVID-19 has overall similarity with other respiratory infections but there are some unique pathways that merit further exploration to determine clinical relevance. The approach to a disease score may be of value, but needs further validation in a population with a greater range of disease severity.