Abstract Although studies on skin microbiome of acute and chronic wounds abound, evidence on newly built microbial communities of subacute wounds remains scant. To characterize the skin microbiome of recently healed (scarred) burn wounds in relation to unaffected skin surfaces, we collected weekly swabs from patients with moderate to severe burns in the 3rd postburn month for 4 weeks in 2015. We performed skin type (moist, dry, and oily)‐matched comparisons within six burn patients (43 pairs of swabs) and with 13 skin‐healthy, control patients (22 pairs of samples) using 16S ribosomal RNA gene sequencing results. Results of comparative microbiome analysis showed that, there were no substantial variations in the microbial abundance (all p > 0.05) or composition (all p > 0.01, adjusted for multiple comparisons) between samples obtained from wound scars and those from unaffected surfaces of burn patients. Nor did we find significant temporal dynamics in microbial richness or diversity in burn samples (all p ≥ 0.05). However, samples from burn patients harbored more Firmicutes (median: 25.6%, interquartile range [IQR]: 14.3%–52.8%) than those of control patients (14.9%, IQR: 6.7%–27.0%; p : 0.016), even after adjusting for host age, sex, and skin type‐matching ( p : 0.026). The number of observed bacterial operational taxonomic units at the genus level was reduced in burn patients (median: 62, IRQ: 32–85) as compared to control patients (median: 128, IQR: 112–136; age‐, skin type‐adjusted p < 0.01). Meanwhile, estimates of community diversity and evenness for surveyed body sites of burn patients were higher than those of control patients (all adjusted p ≤ 0.05). With a much‐reduced bacterial burden and a relative overgrowth of Staphylococcus spp., the skin microbiota of burn patients remained dysbiotic in the subacute phase as compared to that of skin‐normal patients.
ABSTRACT Background How biologics affect psoriasis patients’ risks for SSTIs in a pragmatic clinical setting remains unclear. Methods In a cohort of adult psoriasis outpatients (aged 20 years or older) who visited the Dermatology Clinic in 2010-2015, we compared incident SSTI risks between patients using biologics (users) versus nonbiologics (nonusers). We also estimated SSTI risks in biologics-associated time-periods relative to nonbiologics only in users. We applied random effects Cox proportional hazard models with propensity score-stratification to account for differential baseline hazards. Results Over a median follow-up of 2.8 years (interquartile range: 1.5, 4.3), 172 of 922 patients ever received biologics (18.7%); 233 SSTI incidents occurred during 2518.3 person-years, with an overall incidence of 9.3/100 person-years (95% confidence interval [CI]: 8.1, 10.6). In univariate analysis, users showed an 89% lower risk for SSTIs than nonusers (hazard ratio [HR]: 0.11, 95%CI: 0.05, 0.26); the association persisted in a multivariable model (adjusted HR: 0.26, 95%CI: 0.12, 0.58). Among biologics users, biologics-exposed time-periods were associated with a nonsignificant 21% increased risk (adjusted HR: 1.21, 95%CI: 0.41, 3.59). Conclusions Despite of adjusting for the underlying risk profiles, risk comparisons between biologics users and nonusers remained confounded by treatment selection. By comparing time-periods being exposed versus unexposed to biologics among users, the current analysis did not find evidence for an increased SSTI risk that was associated with biologics use in psoriasis patients.
Despite intensive medical treatment, patients with glioblastoma (grade IV glioma [GBM]) have a low 5-year survival rate of 5.5%. In this study, the authors tried to improve currently used therapies by identification of a therapeutic target, IGFBP3, for glioma treatment.
SUMMARY Background How intranasal mupirocin decolonisation affects the human nasal microbiota remains unknown. To characterize the temporal dynamics of the nasal microbial community in healthy staphylococcal carriers in response to intranasal mupirocin decolonisation, we serially sampled the anterior nares of four healthy carriers to determine the nasal microbial profile via sequencing of bacterial 16S ribosomal DNA. Results Before decolonisation, the nasal microbiota differed by the initial, culture-based staphylococcal carriage status, with Firmicutes (54.1%) and Proteobacteria (75.8%) dominating the microbial community in the carriers and the noncarrier, separately. The nasal microbiota lost its diversity immediately after decolonisation (Shannon diversity: 1.33, 95% confidence interval [CI]: 1.06-1.54) as compared to before decolonisation (1.78, 95%CI: 0.58-1.93). The initial staphylococcal carriage status, expression levels of human neutrophil peptide 1, and sampling times were major contributors to the between-community dissimilarities ( P for marginal permutation test: .014) though of borderline significance when considering data correlation ( P for blocked permutation test: .047) in both nonmetric multidimensional scaling and constrained correspondence analysis. Results of univariable and multivariable differential abundance analysis further showed that, in addition to Staphylococci, multiple genera of Actinobacteria and Proteobacteria were differentially enriched or depleted by mupirocin use. Conclusions Mupirocin could affect both Gram-positive and Gram-negative commensals along with altered host antimicrobial responses. How the nasal microbiome recovered after short-term antibiotic perturbation depended on the initial staphylococcal carriage status. The potential risks associated with loss of colonisation resistance need to be considered in high-risk populations receiving targeted decolonisation.
Next-generation sequencing (NGS) technologies-based transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery, novel transcriptional isoforms and genomic sequence variations. However, this technique also poses many biological and informatics challenges to extracting meaningful biological information. The RNA-seq data analysis is built on the foundation of high quality initial genome localization and alignment information for RNA-seq sequences. Toward this goal, we have developed RNASEQR to accurately and effectively map millions of RNA-seq sequences. We have systematically compared RNASEQR with four of the most widely used tools using a simulated data set created from the Consensus CDS project and two experimental RNA-seq data sets generated from a human glioblastoma patient. Our results showed that RNASEQR yields more accurate estimates for gene expression, complete gene structures and new transcript isoforms, as well as more accurate detection of single nucleotide variants (SNVs). RNASEQR analyzes raw data from RNA-seq experiments effectively and outputs results in a manner that is compatible with a wide variety of specialized downstream analyses on desktop computers.
The molecular characteristics of glioma patients, such as 1p/19q codeletion, MGMT promoter region methylation, and IDH1/IDH2 mutations, carry important information for tumor classification, biological behavior, and the prediction of patient survival. We sought to address the clinical characteristics of brain tumor patients in the Taiwanese population. Our aim was to compare the H&E-based classification and the 2016 WHO classification in glioma patients. 192 patients were recruited in this study including glioblastomas (GBMs) and lower-grade gliomas (LGGs). We performed assays to determine the statuses of 1p/19q codeletion, MGMT promoter methylation, and IDH mutations in tumors and assessed their associations with survival time. We also compared the difference between H&E and WHO 2016 classification. Using the H&E classification, the overall survival time (OST) was associated with IDH status in astrocytoma and oligoastrocytoma patients but not in oligodendroglioma and GBM patients. However, OST showed no significant correlation with MGMT promoter methylation in all the groups. Furthermore, no significant association was observed between 1p/19q codeletion and OST in GBM patients. Using the WHO 2016 classification, our results indicated that astrocytoma and oligodendroglioma patients with mutant IDH showed a significantly prolonged OST than patients with wild-type IDH. However, only oligodendroglioma patients with MGMT hypermethylation demonstrated statistically significant difference. Prognostic factors, including the age at diagnosis, IDH mutations, MGMT promoter methylation, and 1p/19q codeletion, could independently predict patient survival. Based on the WHO 2016 classification of glioma, the new histological groups provide a better and objective method to categorize glioma patients and predict patient survival.
The methylation status of O-6-methylguanine-DNA methyltransferase (MGMT) is associated with the prognosis in gliomas and in other cancers. Recent studies showed that rs16906252, an SNP in the MGMT promoter, is associated with promoter methylation and is a predictor of the overall survival time (OST) and the response to temozolomide (TMZ) treatment. However, these findings haven't been systematically investigated in the Han-Chinese population. We analyzed the relevance between rs16906252 polymorphisms, the MGMT methylation status, and the OST in 72 Han-Chinese gliomas patients. The MGMT promoter methylation was measured by bisulfite conversion followed by pyro-sequencing, while rs16906252 was measured by restriction endonuclease digestion. Contrary to the previous findings, we found no association between rs16906252 genotypes and promoter methylation on MGMT. The lower-grade glioma (LGGs) patients carrying the C allele with rs16906252 showed a surprisingly better OST (P = 0.04). Furthermore, the LGG patients carrying hypo-methylated MGMT promoter and rs16906252 T allele showed significantly poorer prognosis. The prognostic benefit of MGMT promoter methylation and genotypes on gliomas patients is marginal. A new molecular stratified patient grouping of LGGs is potentially associated with poorer OST. Active MGMT might have a protective role in LGG tumors, enabling evolution to severe malignancy.
ABSTRACT Background How skin microbiota in psoriasis patients responded to systematic therapeutics remained unknown. Objectives To profile temporal shifts in transcriptionally active skin microbiota in psoriasis patients receiving systemic therapies. Methods We prospectively enrolled 61 psoriasis patients and 29 skin-healthy controls in 2015-2019. Using RNA-based 16S rRNA gene sequencing, we analyzed 969 samples from skin lesions and compared microbial abundance and diversity by therapeutic classes and disease severity. Results Lesional microbiota in patients on conventional systemics and TNF- α inhibitor was different in relative abundances in Firmicutes (7.83% higher, adjusted P < 0.001) and Proteobacteria (6.98% lower, adjusted P < 0.01) from that in patients on anti-interleukin monoclonal antibodies (anti-ILAb) at baseline. The only difference during treatment was a 1.47% lower abundance in Bacteroides associated with nonbiologics use (adjusted P < 0.01). We identified no indicator taxa by disease severity at baseline yet noticed that a minor relative reduction in Corynebacterium sp. was associated with clinical responses to treatment. Compared to anti-ILAb, TNF- α inhibitor and nonbiologics were associated with -0.21 lower Shannon Diversity (adjusted P < 0.01) and 0.03 higher Shannon Evenness (adjusted P < 0.01). Results of ordinated principal coordinates analysis revealed that, lesional microbiota from patients of these 3 therapeutic groups was compositionally distinct. Our work also demonstrated concurrent changes in clonal shifts in systemic T cell receptor clonotypes that were associated with systemic use of biologics. Conclusions Community abundances and diversities of skin microbiota may be useful in distinguishing skin microbiota from patients receiving different systemic therapeutics. Specifically, use of anti-ILAb and TNF- α inhibitor was associated with sample-wise microbial abundances and diversities, but not richness, over time. These findings highlighted the potential utility of skin microbiota as biomarkers for personalized treatment plans in patients with moderate-to-severe psoriasis.
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