Project description:Melioidosis, caused by Gram negative bacteria Burkholderia pseudomallei, is a major type of community-acquired septicemia in Southeast Asia and Northern Australia with high mortality and morbidity rate. More accurate and rapid diagnosis is needed for improving the management of septicemic melioidosis. We previously identified 37-gene candidate signature to distinguish septicemic melioidosis from sepsis due to other pathogens. The aims of this current study were to independently validate our previous biomarker and consolidate gene selection from each of our microarray data set for establishing a targeted assay for the differential diagnosis of melioidosis. Blood samples were collected from patients who presented with severe inflammatory response syndromes from 3 provincial hospitals in Northeast of Thailand during September 2009 and November 2011. Only culture-confirmed sepsis were included in the study (n=166). We generated a new microarray dataset comprising of 29 patients with septicemic melioidosis and 54 patients with sepsis due to other pathogens. Validation of the 37-gene signature using this new dataset demonstrated the prediction accuracy of approximately 80% for detecting type of sepsis. In order to develop a nanoliter-scale high throughput PCR technology, we further identified additional gene signature from this new microarray dataset and by revisiting our published data. Altogether 85 genes including 6 housekeeping genes were selected. Using multi-steps iteration approach we could reduce the number of biomarkers to 12 genes while the performance is comparable to that of the full panel. The high performance (accuracy >70%) of this 12-gene signature could be validated in a second independent set of samples. The 12-gene panel identified by our study provides high performance for the differential diagnosis of septicemic melioidosis. This finding will be useful for improving the management of septicemic melioidosis in term of diagnosis, treatment and follow up.
Project description:Burkholderia pseudomallei is the causative agent of melioidosis a disease endemic in South-East Asia and Northern Australia. The mortality rates in these areas are unacceptably high even with antibiotic treatment, attributed to intrinsic and acquired resistance of B. pseudomallei to antibiotics. With very few options for therapeutics there is an urgent requirement to identify anti-bacterial targets for the development of novel, effective treatments. In this study we examine the role and effect of ppiB on the proteome. Using LFQ analysis we show loss of ppiB has dramatic effect on the Burkholderia pseudomallei proteome.
Project description:Melioidosis, caused by Gram negative bacteria Burkholderia pseudomallei, is a major type of community-acquired septicemia in Southeast Asia and Northern Australia with high mortality and morbidity rate. More accurate and rapid diagnosis is needed for improving the management of septicemic melioidosis. We previously identified 37-gene candidate signature to distinguish septicemic melioidosis from sepsis due to other pathogens. The aims of this current study were to independently validate our previous biomarker and consolidate gene selection from each of our microarray data set for establishing a targeted assay for the differential diagnosis of melioidosis. Blood samples were collected from patients who presented with severe inflammatory response syndromes from 3 provincial hospitals in Northeast of Thailand during September 2009 and November 2011. Only culture-confirmed sepsis were included in the study (n=166). We generated a new microarray dataset comprising of 29 patients with septicemic melioidosis and 54 patients with sepsis due to other pathogens. Validation of the 37-gene signature using this new dataset demonstrated the prediction accuracy of approximately 80% for detecting type of sepsis. In order to develop a nanoliter-scale high throughput PCR technology, we further identified additional gene signature from this new microarray dataset and by revisiting our published data. Altogether 85 genes including 6 housekeeping genes were selected. Using multi-steps iteration approach we could reduce the number of biomarkers to 12 genes while the performance is comparable to that of the full panel. The high performance (accuracy >70%) of this 12-gene signature could be validated in a second independent set of samples. The 12-gene panel identified by our study provides high performance for the differential diagnosis of septicemic melioidosis. This finding will be useful for improving the management of septicemic melioidosis in term of diagnosis, treatment and follow up. Total RNA from whole blood obtained from patients with sepsis caused by B.pseudomallei (n=29) or other pathogens (n=54) and uninfected controls (28 healthy and 27 subjects with type 2 diabetes mellitus) were collected. In order to validate the published signature, microarray data were generated from these samples. This dataset was also used for an independent selection of signature for septicemic melioidosis. The same RNA samples were used for validation by a high throughput real-time PCR technique, Fluidigm.
Project description:Burkholderia mallei and Burkholderia pseudomallei are both potential biological threats agents. Melioidosis caused by B. pseudomallei is endemic in Southeast Asia and Northern Australia, while glanders caused by B. mallei infections are rare. Here we studied the proteomes of different B. mallei and B. pseudomallei isolates to determine species specific characteristics. Analyzing the expressed proteomes of B. mallei and B. pseudomallei revealed differences between B. mallei and B. pseudomallei but also between isolates from the same species. Expression of multiple virulence factors and proteins of several PKS/NRPS clusters was demonstrated. Proteome analysis can be used not only to identify bacteria but also to characterize the expression of important factors that putatively contribute to pathogenesis of B. mallei and B. pseudomallei.
Project description:The product of dosage compensation in human females is the compacted inactive X chromosome (Xi). Here we show that loss of SET domain bifurcated 1 (SETDB1) results in decompaction of the Xi territory coupled with reactivation on the Xi of a powerful enhancer within the 1.4 Mb interleukin-1 receptor accessory protein like 1 (IL1RAPL1) gene at Xp21.2. The enhancer is centrally located in a 0.5 Mb region corresponding to the 3’ third of the IL1RAPL1 locus that transitions from a heterochromatic territory to a euchromatic configuration on the Xi in the absence of SETDB1. This same region showing chromatin instability is part of a common chromosome fragile site that is frequently deleted or rearranged in patients afflicted with intellectual disability and other neurological ailments. Immediately adjacent to the enhancer is an ERVL-MaLR element that drives bi-directional transcription of novel long sense and antisense transcripts. Deletion of the enhancer from the Xa (but not Xi), resulted in detection of bi-directional expression from the Xi coupled with decompaction of the chromosome territory, supporting a critical role for SETDB1 in maintaining this interval in a silent state to facilitate Xi compaction.
Project description:Melioidosis is a neglected tropical disease caused by the Gram-negative bacterium Burkholderia pseudomallei. It is widespread in Southeast Asia and under-reported across tropical regions worldwide. Patients present with a range of clinical syndromes including sepsis, pneumonia and focal abscesses, with a mortality rate of 40% in hospitalized patients in Thailand. Up to two-thirds of patients with melioidosis have diabetes mellitus. In this experiment we sought to characterize pathways activated by whole killed B. pseudomallei bacteria and by three vaccine candidate proteins from B. pseudomallei, BPSL2520 (uncharacterized protein), BPSS1525 (BopE) and BPSL2096 (AhpC) in patients with diabetes and acute melioidosis.
Project description:Melioidosis is a severe infectious disease caused by Burkholderia pseudomallei, a gram-negative bacillus classified by the NIAID as a category B priority agent. Septicemia is the most common presentation of the disease with 40% mortality rate even with appropriate treatments. Faster diagnostic procedures are required to improve therapeutic response and survival rates. We have used microarray technology to generate genome-wide transcriptional profiles (>48,000 transcripts) of whole blood obtained from patients with septicemic melioidosis (n=32), patients with sepsis caused by other pathogens (n=31), and uninfected controls (n=29). Unsupervised analyses demonstrated the existence of a whole blood transcriptional signature distinguishing patients with sepsis from control subjects. The majority of changes observed were common to both septicemic melioidosis and sepsis caused by other infections, including genes related to inflammation, interferon-related genes, neutrophils, cytotoxic cells, and T cells. Finally, class prediction analysis identified a 37 transcript candidate diagnostic signature that distinguished melioidosis from sepsis caused by other organisms with 100% and 78% accuracy in training and independent test sets, respectively. This finding was confirmed by the independent validation set, which showed 80% prediction accuracy. This signature was highly enriched in genes coding for products involved in the MHC Class II antigen processing and presentation pathway. Transcriptional patterns of whole blood RNA distinguish patients with septicemic melioidosis from patients with sepsis caused by other pathogens. Once confirmed in a large scale trial this diagnostic signature might constitute the basis of a differential diagnostic assay.
Project description:The response of soil microbial community to climate warming through both function shift and composition reorganization may profoundly influence global nutrient cycles, leading to potential significant carbon release from the terrain to the atmosphere. Despite the observed carbon flux change in northern permafrost, it remains unclear how soil microbial community contributes to this ecosystem alteration. Here, we applied microarray-based GeoChip 4.0 to investigate the functional and compositional response of subsurface (15~25cm) soil microbial community under about one year’s artificial heating (+2°C) in the Carbon in Permafrost Experimental Heating Research site on Alaska’s moist acidic tundra. Statistical analyses of GeoChip signal intensities showed significant microbial function shift in AK samples. Detrended correspondence analysis and dissimilarity tests (MRPP and ANOSIM) indicated significant functional structure difference between the warmed and the control communities. ANOVA revealed that 60% of the 70 detected individual genes in carbon, nitrogen, phosphorous and sulfur cyclings were substantially increased (p<0.05) by heating. 18 out of 33 detected carbon degradation genes were more abundant in warming samples in AK site, regardless of the discrepancy of labile or recalcitrant C, indicating a high temperature sensitivity of carbon degradation genes in rich carbon pool environment. These results demonstrated a rapid response of northern permafrost soil microbial community to warming. Considering the large carbon storage in northern permafrost region, microbial activity in this region may cause dramatic positive feedback to climate change, which is important and necessary to be integrated into climate change models.