DNA methylation promotes the expression of PPARγ transcript 1 at least in part by preventing NRF1 binding to the promoter P1 of chicken PPARγ gene

Peroxisome proliferator-activated receptor gamma (PPARγ) is a master regulator of adipogenesis. Our previous study revealed that chicken PPARγ has 3 alternative promoters named as P1, P2, and P3, and the DNA methylation of promoter P3 was negatively associated with PPARγ mRNA expression in abdominal adipose tissue (AAT). However, the methylation status of promoters P1 and P2 is unclear. Here we assessed promoter P1 methylation status in AAT of Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF). The results showed that promoter P1 methylation differed in AAT between the lean and fat lines of NEAUHLF at 7 wk of age (p < 0.05), and AAT expression of PPARγ transcript 1 (PPARγ1), which was derived from the promoter P1, was greatly higher in fat line than in lean line at 2 and 7 wk of age. The results of the correlation analysis showed that P1 methylation was positively correlated with PPARγ1 expression at 7 wk of age (Pearson's r = 0.356, p = 0.0242), suggesting P1 methylation promotes PPARγ1 expression. To explore the underlying molecular mechanism of P1 methylation on PPARγ1 expression, bioinformatics analysis, dual-luciferase reporter assay, pyrosequencing, and electrophoresis mobility shift assay (EMSA) were performed. The results showed that transcription factor NRF1 repressed the promoter activity of the unmethylated P1, but not the methylated P1. Of all the 4 CpGs (CpG48, CpG49, CpG50, and CpG51), which reside within or nearby the NRF1 binding sites of the P1, only CpG49 methylation in AAT was remarkably higher in the fat line than in lean line at 7 wk of age (3.18 to 0.57, p < 0.05), and CpG49 methylation was positively correlated with PPARγ1 expression (Pearson's r = 0.3716, p = 0.0432). Furthermore, EMSA showed that CpG49 methylation reduced the binding of NRF1 to the P1. Taken together, our findings illustrate that P1 methylation promotes PPARγ1 expression at least in part by preventing NRF1 from binding to the promoter P1.

TGF-β1 Inhibition of ACE2 Mediated by miRNA Uncovers Novel Mechanism of SARS-CoV-2 Pathogenesis

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for COVID-19, utilizes receptor binding domain (RBD) of spike glycoprotein to interact with angiotensin (Ang)-converting enzyme 2 (ACE2). Altering ACE2 levels may affect entry of SARS-CoV-2 and recovery from COVID-19. Decreased cell surface density of ACE2 leads to increased local levels of Ang II and may contribute to mortality resulting from acute lung injury and fibrosis during COVID-19. Studies published early during the COVID-19 pandemic reported that people with cystic fibrosis (PwCF) had milder symptoms, compared to people without CF. This finding was attributed to elevated ACE2 levels and/or treatment with the high efficiency CFTR modulators. Subsequent studies did not confirm these findings reporting variable effects of CFTR gene mutations on ACE2 levels. Transforming growth factor (TGF)-β signaling is essential during SARS-CoV-2 infection and dominates the chronic immune response in severe COVID-19, leading to pulmonary fibrosis. TGF-β1 is a gene modifier associated with more severe lung disease in PwCF but its effects on the COVID-19 course in PwCF is unknown. To understand whether TGF-β1 affects ACE2 levels in the airway, we examined miRNAs and their gene targets affecting SARS-CoV-2 pathogenesis in response to TGF-β1. Small RNAseq and micro(mi)RNA profiling identified pathways uniquely affected by TGF-β1, including those associated with SARS-CoV-2 invasion, replication, and the host immune responses. TGF-β1 inhibited ACE2 expression by miR-136-3p and miR-369-5p mediated mechanism in CF and non-CF bronchial epithelial cells. ACE2 levels were higher in two bronchial epithelial cell models expressing the most common CF-causing mutation in CFTR gene F508del, compared to controls without the mutation. After TGF-β1 treatment, ACE2 protein levels were still higher in CF, compared to non-CF cells. TGF-β1 prevented the modulator-mediated rescue of F508del-CFTR function while the modulators did not prevent the TGF-β1 inhibition of ACE2 levels. Finally, TGF-β1 reduced the interaction between ACE2 and the recombinant spike RBD by lowering ACE2 levels and its binding to RBD. Our data demonstrate novel mechanism whereby TGF-β1 inhibition of ACE2 in CF and non-CF bronchial epithelial cells may modulate SARS-CoV-2 pathogenicity and COVID-19 severity. By reducing ACE2 levels, TGF-β1 may decrease entry of SARS-CoV-2 into the host cells while hindering the recovery from COVID-19 due to loss of the anti-inflammatory and regenerative effects of ACE2. The above outcomes may be modulated by other, miRNA-mediated effects exerted by TGF-β1 on the host immune responses, leading to a complex and yet incompletely understood circuitry.

Genomic glucocorticoid action in embryonic mouse neural stem cells

Prenatal exposure to synthetic glucocorticoids (sGCs) reprograms brain development and predisposes the developing fetus towards potential adverse neurodevelopmental outcomes. Using a mouse model of sGC administration, previous studies show that these changes are accompanied by sexually dimorphic alterations in the transcriptome of neural stem and progenitor cells (NSPCs) derived from the embryonic telencephalon. Because cell type-specific gene expression profiles tightly regulate cell fate decisions and are controlled by a flexible landscape of chromatin domains upon which transcription factors and enhancer elements act, we multiplexed data from four genome-wide assays: RNA-seq, ATAC-seq (assay for transposase accessible chromatin followed by genome wide sequencing), dual cross-linking ChIP-seq (chromatin immunoprecipitation followed by genome wide sequencing), and microarray gene expression to identify novel relationships between gene regulation, chromatin structure, and genomic glucocorticoid receptor (GR) action in NSPCs. These data reveal that GR binds preferentially to predetermined regions of accessible chromatin to influence gene programming and cell fate decisions. In addition, we identify SOX2 as a transcription factor that impacts the genomic response of select GR target genes to sGCs (i.e., dexamethasone) in NSPCs.

Differential Gene Expression Analysis Reveals Global LMTK2 Regulatory Network and Its Role in TGF-β1 Signaling

Lemur tyrosine kinase 2 (LMTK2) is a transmembrane Ser/Thr kinase whose role has been increasingly recognized; however, when compared to other kinases, understanding of the LMTK2 networks and biological functions is still limited. Recent data have shown that transforming growth factor (TGF)-β1 plays a role in modulating LMTK2 function by controlling its endocytic trafficking in human bronchial epithelial cells. Here, we aimed to unveil the LMTK2 regulatory network and elucidate how it affects cellular functions and disease pathways in either TGF-β1 dependent or independent manner. To understand how the LMTK2 and TGF-β1 pathways interconnect, we knocked down (KD) LMTK2 using small(si)RNA-mediated silencing in human bronchial epithelial CFBE41o- cells, treated cells with TGF-β1 or vehicle control, and performed differential gene expression analysis by RNA sequencing (RNAseq). In vehicle-treated cells, LMTK2 KD affected expression of 2,506 genes while it affected 4,162 genes after TGF-β1 stimulation. Bioinformatics analysis shows that LMTK2 is involved in diverse cellular functions and disease pathways, such as cell death and survival, cellular development, and cancer susceptibility. In summary, our study increases current knowledge about the LMTK2 network and its intersection with the TGF-β1 signaling pathway. These findings will serve as basis for future exploration of the predicted LMTK2 interactions and signaling pathways.

[The role of large-scale testing platform in the prevention and control of the COVID-19 pandemic: an empirical study based on a novel numerical model]

Objective: China adopted an unprecedented province-scale quarantine since January 23rd 2020, after the novel coronavirus (COVID-19) broke out in Wuhan in December 2019. Responding to the challenge of limited testing capacity, large-scale (>20 000 tests per day) standardized and fully-automated laboratory (Huo-Yan) was built as an ad-hoc measure. There is so far no empirical data or mathematical model to reveal the impact of the testing capacity improvement since quarantine. Methods: Based on the suspected case data released by the Health Commission of Hubei Province and the daily testing data of Huo-Yan Laboratory, the impact of detection capabilities on the realization of "clearing" and "clearing the day" of supected cases was simulated by establishing a novel non-linear and competitive compartments differential model. Results: Without the establishment of Huo-Yan, the suspected cases would increase by 47% to 33 700, the corresponding cost of quarantine would be doubled, the turning point of the increment of suspected cases and the achievement of "daily settlement" (all newly discovered suspected cases are diagnosed according to the nucleic acid testing result) would be delayed for a whole week and 11 days. If the Huo-Yan Laboratory could ran at its full capacity, the number of suspected cases could start to decrease at least a week earlier, the peak of suspected cases would be reduced by at least 44%, and the quarantine cost could be reduced by more than 72%. Ideally, if a daily testing capacity of 10 500 tests was achieved immediately after the Hubei lockdown, "daily settlement" for all suspected cases could be achieved. Conclusions: Large-scale, standardized clinical testing platform, with nucleic acid testing, high-throughput sequencing, and immunoprotein assessment capabilities, need to be implemented simultaneously in order to maximize the effect of quarantine and minimize the duration and cost of the quarantine. Such infrastructure, for both common times and emergencies, is of great significance for the early prevention and control of infectious diseases.

MON-727 The Chromatin Landscape of Glucocorticoid Regulated Genes in Mouse Embryonic Neural Stem / Progenitor Cells

Stem/Progenitor Cells

Antenatal administration of Dexamethasone (Dex), a synthetic glucocorticoid (GC), is a common clinical intervention for women at risk for preterm birth or in preterm labor that effectively reduces fetal risk of mortality and bronchopulmonary-related comorbidities. Despite the therapeutic potential of Dex, excess GC act adversely in the developing central nervous system to reprogram distinct neural circuits in the brain by acting through the glucocorticoid receptor (GR). For example, prenatal exposure to excess GCs can impact neural stem and progenitor cell (NSPC) proliferation leading to long-term alterations in prefrontal cortical neuronal complexity, which could contribute to behavioral and cognitive impairments later in life. The GR is a member of the nuclear receptor superfamily that, when bound by a ligand, translocates from the cytoplasm to the nucleus and associates indirectly or directly with DNA elements (e.g. glucocorticoid responsive elements or GREs) resulting in the activation and/or repression of target genes. While GR-regulated transcriptomes have been identified in many NSPC models, the mechanisms responsible for programming these cells for GC-responsiveness remain largely unknown. We therefore used transposase accessible chromatin followed by genome-wide sequencing (Omni ATAC-seq) to characterize the chromatin landscape of primary embryonic mouse NSPCs in response to an acute in vitro treatment with Dex. We identified a small, yet distinct fraction (0.002%, p&lt;0.05) of open chromatin sites that were Dex-inducible. 95% of these Dex-induced changes in chromatin accessibility occur within intronic or intergenic regions, suggesting the presence of long-range enhancer-promoter contacts that mediate NSPC transcriptional responses to Dex. Motif enrichment analysis revealed putative GRE sites located in Dex-inducible open chromatin within -5kb/+2kb of a Dex-induced gene, providing possible DNA targets of GR for further validation. A number of other transcription factors implicated in neurodevelopmental processes were found to underlie both Dex-inducible and constitutively open chromatin regions. Characterization of the precise epigenetic and transcriptional response to excess GC in-utero, and its influence on acute and chronic neurological outcomes, will encourage the development of alternative GC treatment regimens that could protect the developing brain from insult while providing optimal health outcomes in neonates.

Precise Targeting of miRNA Sites Restores CFTR Activity in CF Bronchial Epithelial Cells

MicroRNAs that are overexpressed in cystic fibrosis (CF) bronchial epithelial cells (BEC) negatively regulate CFTR and nullify the beneficial effects of CFTR modulators. We hypothesized that it is possible to reverse microRNA-mediated inhibition of CFTR using CFTR-specific target site blockers (TSBs) and to develop a drug-device combination inhalation therapy for CF. Lead microRNA expression was quantified in a series of human CF and non-CF samples and in vitro models. A panel of CFTR 3' untranslated region (UTR)-specific locked nucleic acid antisense oligonucleotide TSBs was assessed for their ability to increase CFTR expression. Their effects on CFTR activity alone or in combination with CFTR modulators were measured in CF BEC models. TSB encapsulation in poly-lactic-co-glycolic acid (PLGA) nanoparticles was assessed as a proof of principle of delivery into CF BECs. TSBs targeting the CFTR 3' UTR 298-305:miR-145-5p or 166-173:miR-223-3p sites increased CFTR expression and anion channel activity and enhanced the effects of ivacaftor/lumacaftor or ivacaftor/tezacaftor in CF BECs. Biocompatible PLGA-TSB nanoparticles promoted CFTR expression in primary BECs and retained desirable biophysical characteristics following nebulization. Alone or in combination with CFTR modulators, aerosolized CFTR-targeting TSBs encapsulated in PLGA nanoparticles could represent a promising drug-device combination therapy for the treatment for CFTR dysfunction in the lung.

Impact of hidradenitis suppurativa on work loss, indirect costs and income

Background

Hidradenitis suppurativa (HS), a chronic cutaneous disease, can negatively affect work life.

Objectives

This retrospective cohort study evaluates the indirect burden among employed patients with HS in the U.S.A.

Methods

Newly diagnosed and general patients with HS, who were employees (age 18–64 years) from a large claims database (Q1 1999 to Q1 2015), were matched 1 : 5 to controls. Income growth and risk of leaving the workforce were assessed among the newly diagnosed HS and control cohorts in the 5‐year study period. Income, work loss days and indirect costs (absenteeism and disability) were assessed among the general HS and control cohorts in the 1‐year study period.

Results

Newly diagnosed (n = 1003, mean age 39·5 years, 66·3% female) and general patients with HS (n = 1204, mean age 39·9 years, 69·1% female) were matched to 5015 and 6020 controls, respectively. Newly diagnosed patients with HS had significantly slower income growth ($324 per year) and higher risk of leaving the workforce (adjusted hazard ratio 1·65, 95% confidence interval 1·45–1·88) compared with controls (all P < 0·05). General patients with HS had more total days of work loss (18·4 vs. 7·7), higher annual total indirect costs ($2925 vs. $1483) and lower annual income ($54 925 vs. $62 357) than controls (all P < 0·001).

Conclusions

Patients with newly diagnosed HS and general patients with HS experienced a greater indirect burden than matched controls.

What's already known about this topic?

Hidradenitis suppurativa (HS), a chronic inflammatory disease, can negatively affect work life.

What does this study add?

This retrospective claims analysis found that HS is associated with high indirect burden, in terms of slower income growth, higher risk of leaving the workforce and higher indirect costs.

These results indicate that patients with HS have unmet disease management needs.

Linked Editorial: Zouboulis. Br J Dermatol 2019; 181:7–8.

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Validation of combinatorial probe-anchor ligation-based sequencing as non-invasive prenatal test for trisomy at a central laboratory

OBJECTIVE

To evaluate the clinical validity of a new ultrahigh-throughput non-invasive prenatal test (NIPT) based on combinatorial probe-anchor ligation (cPAL) sequencing of cell-free fetal DNA (cffDNA) using centralized testing.

METHODS

Maternal plasma samples were obtained from 10 594 singleton pregnancies in high-risk populations at 20 centers in China, including 8155 that were collected retrospectively and 2439 prospectively. Fetal outcome data and karyotyping results were documented as gold standard and were double blinded during NIPT. The clinical performance of the ultrahigh-throughput sequencing method, cPAL, for NIPT was validated by evaluating its sensitivity, specificity and positive predictive value (PPV) in detecting trisomies 21, 18 and 13 as the centralized testing mode in the reference laboratory. To ensure stable and reproducible performance of centralized cPAL-based NIPT in detecting trisomies, a series of quality-control systems, including sequencing of two sets of artificial samples, were employed and evaluated.

RESULTS

Ten prospective cases were excluded from the study because of incomplete clinical data. Four prospective samples failed to generate a NIPT result due to assay failure, presenting a failure rate of 0.16% (4/2429). A total of 168 retrospective cases and 47 prospective cases had a positive NIPT result for trisomy, giving respective positive rates of 2.06% and 1.94%. Four false-positive and no false-positive cases were observed in the retrospective and prospective groups, respectively, resulting in PPV of 97.62% (95% CI, 94.02-99.35%) and 100% (95% CI, 92.45-100%), respectively. In the retrospective group, sensitivity and specificity were, respectively, 100% (95% CI, 97.07-100%) and 99.98% (95% CI, 99.94-100%) for trisomy 21, 100% (95% CI, 97.75-100%) and 99.98% (95% CI, 99.94-100%) for trisomy 18, and 100% (95% CI, 15.81-100%) and 100% (95% CI, 99.95-100%) for trisomy 13. In the prospective group, sensitivity and specificity were, respectively, 100% (95% CI, 90.75-100%) and 100% (95% CI, 99.85-100%) for trisomy 21, 100% (95% CI, 63.06-100%) and 100% (95% CI, 99.85-100%) for trisomy 18, and 100% (95% CI, 2.50-100%) and 100% (95% CI, 99.85-100%) for trisomy 13.

CONCLUSION

In this multicenter study with a full quality-control system, NIPT by centralized cPAL-based testing showed high stability and performance comparable to those of previous validation studies in high-risk populations. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Real-world costs of ischemic stroke by discharge status

OBJECTIVE

The objective of this study was to estimate the acute healthcare costs of ischemic stroke during hospitalization and the quarterly all-cause healthcare costs for the first year after discharge by discharge status.

METHODS

Adult patients with a hospitalization with a diagnosis of ischemic stroke (ICD-9-CM: 434.xx or 436.xx) between 1 January 2006 and 31 March 2015 were identified from a large US commercial claims database. Patients were classified into three cohorts based on their discharge status from the first stroke hospitalization, i.e. dead at discharge, discharged with disability, or discharged without disability. Third-party (medical and pharmacy) and out-of-pocket costs were adjusted to 2015 USD.

RESULTS

A total of 7919 patients dead at discharge, 45,695 patients discharged with disability, and 153,778 patients discharged without disability were included in this analysis. The overall average age was 59.7 years and 52.3% were male. During hospitalization, mean total costs (third-party and out-of-pocket) were $68,370 for patients dead at discharge, $73,903 for patients discharged with disability, and $24,448 for patients discharged without disability (p < .001 for each pairwise comparison); mean third-party costs were $63,605 for patients dead at discharge, $67,861 for patients discharged with disability and $19,267 for patients discharged without disability (p < .001 for each pairwise comparison). During the first year after discharge, mean total costs for patients discharged with disability vs. without disability were $46,850 vs. $30,132 (p < .001). Mean third-party costs for patients discharged with disability vs. without disability were $19,116 vs. $10,976 during the first quarter after discharge, $10,236 vs. $6926 during the second quarter, $8241 vs. $5810 during the third quarter, and $6875 vs. $5292 during the fourth quarter (p < .001 for each quarter).

CONCLUSION

The results demonstrated the high economic burden of ischemic stroke, especially among patients discharged with disability with the highest costs incurred during the inpatient stays.

Novel Polymorphisms of Adrenergic, Alpha-1B-, Receptor and Peroxisome Proliferator-activated Receptor Gamma, Coactivator 1 Beta Genes and Their Association with Egg Production Traits in Local Chinese Dagu Hens

Adrenergic, alpha-1B-, receptor (ADRA1B) and peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PPARGC1B) genes are involved in regulation of hen ovarian development. In this study, these two genes were investigated as possible molecular markers associated with hen-housed egg production, egg weight (EW) and body weight in Chinese Dagu hens. Samples were analyzed using the polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) technique, followed by sequencing analysis. Two novel single nucleotide polymorphisms (SNPs) were identified within the candidate genes. Among them, an A/G transition at base position 1915 in exon 2 of ADRA1B gene and a T/C mutation at base position 6146 in the 3′-untranslated region (UTR) of PPARGC1B gene were found to be polymorphic and named SNP A1915G and T6146C, respectively. The SNP A1915G (ADRA1B) leads to a non-synonymous substitution (aspartic acid 489-to-glycine). The 360 birds from the Dagu population were divided into genotypes AA and AG, allele A was found to be present at a higher frequency. Furthermore, the AG genotype correlated with significantly higher hen-housed egg production (HHEP) at 30, 43, 57, and 66 wks of age and with a higher EW at 30 and 43 wks (p<0.05). For the SNP T6146C (PPARGC1B), the hens were typed into TT and TC genotypes, with the T allele shown to be dominant. The TC genotype was also markedly correlated with higher HHEP at 57 and 66 wks of age and EW at 30 and 43 wks (p<0.05). Moreover, four haplotypes were reconstructed based on these two SNPs, with the AGTC haplotype found to be associated with the highest HHEP at 30 to 66 wks of age and with higher EW at 30 and 43 wks (p<0.05). Collectively, the two SNPs identified in this study might be used as potential genetic molecular markers favorable in the improvement of egg productivity in chicken breeding.

Association of novel polymorphisms of forkhead box L2 and growth differentiation factor-9 genes with egg production traits in local Chinese Dagu hens

Transcription factor forkhead box L2 (FOXL2) and growth differentiation factor-9 (GDF9) genes have critical roles in the regulation of hen ovarian development. In the present study, these genes were explored as possible molecular markers associated with BW, hen-housed egg production, and egg weight in Chinese Dagu hens. Samples were analyzed using the PCR-single strand conformation polymorphism (PCR-SSCP) technique followed by sequencing analysis, and two novel single nucleotide polymorphisms (SNPs) were identified within these candidate genes. Among them, an A/G transition at base position 238 in the coding region of the FOXL2 gene and a G/T transversion at base position 1609 in exon 2 of the GDF9 gene were found to be polymorphic and named SNPs A238G and G1609T, respectively. The SNP A238G (FOXL2) leads to a nonsynonymous substitution (isoleucine77-to-valine), and when the 360 Dagu hen samples were divided into genotypes AA and AB, allele A was found to be present at a higher frequency. Furthermore, the AA genotype correlated with significantly higher hen-housed egg production at 30, 43, 57, and 66 wk of age and with a higher egg weight at 43 wk (P<0.05). For the SNP G1609T (GDF9), the hens were typed into TT and TC genotypes, with the T allele shown to be dominant. The TC genotype was also markedly correlated with higher hen-housed egg production and a higher egg weight (P<0.05). Moreover, four haplotypes were reconstructed based on these two SNPs, with the AATC haplotype found to be correlated with the highest hen-housed egg production at 30 to 66 wk of age and with higher egg weights at 43 wk (P<0.05). Collectively, the two SNPs identified in this study might be used as possible genetic molecular markers to aid in the improvement of egg production traits in chicken breeding.

New insights into implication of the SLIT/ROBO pathway in the prehierarchical follicle development of hen ovary

The SLIT/Roundabout (ROBO) pathway is involved in follicle development of mammalian ovary, and 2 secreted hormones activin A and inhibin A have potential roles in modulation of the SLIT/ROBO system, but the related actions remain poorly understood in bird. The aims of the present study were to examine the spatial and temporal expression of the SLIT ligand genes (SLIT1, SLIT2, and SLIT3) and their receptor ROBO1, ROBO2, ROBO3, and ROBO4 genes in various-sized prehierarchical follicles during hen ovary development and the effects of activin A and inhibin A on the expression of these genes in the cultured hen follicles. Our result demonstrated that the transcripts of the 3 SLIT genes were highly expressed in the developing follicles and expression patterns of the SLIT transcripts were different from those of ROBO genes detected by real-time quantitative reverse transcriptase PCR. Both SLIT and ROBO transcripts were predominantly expressed in oocytes and granulosa cells from the prehierarchichal follicles examined by in situ hybridization. The localization for SLIT and ROBO proteins was revealed by immunohistochemistry similar to the spatial distribution of their transcript. In cultured follicles (4 to 8 mm in diameter), the expression levels of SLIT and ROBO members are hormonally regulated by activin A (10 ng/mL) and/or inhibin A (20 ng/mL) after treatment for 24 h. However, the expression of only SLIT2, SLIT3, and ROBO3 mRNA presented a directly opposite response to activin A and inhibin A hormones. These results indicate that SLIT/ROBO pathway is implicated in the prehierarchical follicular development of the hen ovary by an intrafollicular autocrine and/or paracrine action, and is influenced by activin A and inhibin A hormones.

Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions

BACKGROUND

The clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity.

RESULTS

A software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed, we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from Burkholderia xenovorans, a TR of unknown function and predicted that this TR was related to the glycine, threonine and serine degradation. We tested the binding of metabolites in these pathways and for those that bound, their ability to modulate TR binding to its specific DNA operator sequence. Using rtPCR, we confirmed that methylglyoxal was an effector of Bxe_3018.

CONCLUSION

These studies provide the proof of concept and validation of a systematic approach to the discovery of the biological activity for proteins of unknown function, in this case a TR. Bxe_B3018 is a methylglyoxal responsive TR that controls the expression of an operon composed of a putative efflux system.

Clinical features of macrophage activation syndrome in the adult northern Chinese population

OBJECTIVE

Macrophage activation syndrome (MAS) is a relatively rare but potentially fatal complication of childhood rheumatic illnesses. We sought to provide insight for the timely recognition and diagnosis of MAS and efficacious disease management in adults with rheumatic diseases.

METHODS

Clinical files for eight adult MAS patients treated at the Second Affiliated Hospital of Harbin Medical University were analyzed for clinical manifestations, laboratory investigations, therapeutic measurements and clinical outcomes.

RESULTS

The study included male and female patients with ages ranging from 16 to 59 years old. All patients were diagnosed with underlying rheumatic diseases with five patients having adult-onset Still's disease (AOSD), two patients having systemic lupus erythematosus (SLE) and one patient having Sjögren's syndrome (SS). The interval from fever onset to MAS diagnosis varied from seven days to 40 days. The most common clinical presentations were prolonged high fever, respiratory symptoms and jaundice. No patients had symptoms involving the central nervous system (CNS). Laboratory findings showed peripheral cytopenias, elevated liver enzymes, elevated triglycerides, hypofibrinogenemia and bone marrow hemophagocytosis. Potential effective treatments for MAS include glucocorticoid plus immunoglobulin therapy, but delays in diagnosis and treatment may lead to a fatal disease course.

CONCLUSION

MAS in adults may not be as rare as was once thought, although the clinical features of MAS in adults often differ from those seen in children. The MAS mortality in adults is far higher than that for children. A diagnosis of MAS should be considered when a patient with rheumatic disease presents with prolonged high fever, peripheral cytopenia and liver failure. Collection of bone marrow aspirates is critical for accurate diagnosis and MAS therapy should begin as early as possible.

Hypocrea lixii, novel endophytic fungi producing anticancer agent cajanol, isolated from pigeon pea (Cajanus cajan [L.] Millsp.)

AIMS

The aim was to isolate, identify and characterize endophytes from pigeon pea (Cajanus cajan [L.] Millsp.), as novel producer of cajanol and its in vitro cytotoxicity assay.

METHODS AND RESULTS

Isolation, identification and characterization of novel endophytes producing cajanol from the roots of pigeon pea were investigated. The endophytes were identified as Hypocrea lixii by morphological and molecular methods. Cajanol produced by endophytes were quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). R-18 produced the highest levels of cajanol (322·4 ± 10·6 μg l(-1) or 102·8 ± 6·9 μg g(-1) dry weight of mycelium) after incubation for 7 days. The cytotoxicity towards human lung carcinoma cells (A549) of fungal cajanol was investigated in vitro.

CONCLUSIONS

First, a novel endophyte Hypocrea lixii, producing anticancer agent cajanol, was isolated from the host pigeon pea (Cajanus cajan [L.] Millsp.). Fungal cajanol possessed stronger cytotoxicity activity towards A549 cells in time- and dose-dependent manners.

SIGNIFICANCE AND IMPACT OF THE STUDY

This endophyte is a potential handle for scientific and commercial exploitation, and it could provide a promising alterative approach for large-scale production of cajanol to satisfy new anticancer drug development.

Binding of nucleoid-associated protein fis to DNA is regulated by DNA breathing dynamics

Physicochemical properties of DNA, such as shape, affect protein-DNA recognition. However, the properties of DNA that are most relevant for predicting the binding sites of particular transcription factors (TFs) or classes of TFs have yet to be fully understood. Here, using a model that accurately captures the melting behavior and breathing dynamics (spontaneous local openings of the double helix) of double-stranded DNA, we simulated the dynamics of known binding sites of the TF and nucleoid-associated protein Fis in Escherichia coli. Our study involves simulations of breathing dynamics, analysis of large published in vitro and genomic datasets, and targeted experimental tests of our predictions. Our simulation results and available in vitro binding data indicate a strong correlation between DNA breathing dynamics and Fis binding. Indeed, we can define an average DNA breathing profile that is characteristic of Fis binding sites. This profile is significantly enriched among the identified in vivo E. coli Fis binding sites. To test our understanding of how Fis binding is influenced by DNA breathing dynamics, we designed base-pair substitutions, mismatch, and methylation modifications of DNA regions that are known to interact (or not interact) with Fis. The goal in each case was to make the local DNA breathing dynamics either closer to or farther from the breathing profile characteristic of a strong Fis binding site. For the modified DNA segments, we found that Fis-DNA binding, as assessed by gel-shift assay, changed in accordance with our expectations. We conclude that Fis binding is associated with DNA breathing dynamics, which in turn may be regulated by various nucleotide modifications.

Cellular transcription factors (TFs) are proteins that regulate gene expression, and thereby cellular activity and fate, by binding to specific DNA segments. The physicochemical determinants of protein-DNA binding specificity are not completely understood. Here, we report that the propensity of transient opening and re-closing of the double helix, resulting from thermal fluctuations, aka “DNA breathing” or “DNA bubbles,” can be associated with binding affinity in the case of Fis, a well-studied nucleoid-associated protein in Escherichia coli. We found that a particular breathing profile is characteristic of high-affinity Fis binding sites and that DNA fragments known to bind Fis in vivo are statistically enriched for this profile. Furthermore, we used simulations of DNA breathing dynamics to guide design of gel-shift experiments aimed at testing the idea that local breathing influences Fis binding. As a result, we show that via nucleotide modifications but without modifying nucleotides that directly contact Fis, we were able to transform a low-affinity Fis binding site into a high-affinity site and vice versa. The nucleotide modifications were designed only based on DNA breathing simulations. Our study suggests that strong Fis-DNA binding depends on DNA breathing - a novel physicochemical characteristic that could be used for prediction and rational design of TF binding sites.

Improved predictions of transcription factor binding sites using physicochemical features of DNA

Typical approaches for predicting transcription factor binding sites (TFBSs) involve use of a position-specific weight matrix (PWM) to statistically characterize the sequences of the known sites. Recently, an alternative physicochemical approach, called SiteSleuth, was proposed. In this approach, a linear support vector machine (SVM) classifier is trained to distinguish TFBSs from background sequences based on local chemical and structural features of DNA. SiteSleuth appears to generally perform better than PWM-based methods. Here, we improve the SiteSleuth approach by considering both new physicochemical features and algorithmic modifications. New features are derived from Gibbs energies of amino acid-DNA interactions and hydroxyl radical cleavage profiles of DNA. Algorithmic modifications consist of inclusion of a feature selection step, use of a nonlinear kernel in the SVM classifier, and use of a consensus-based post-processing step for predictions. We also considered SVM classification based on letter features alone to distinguish performance gains from use of SVM-based models versus use of physicochemical features. The accuracy of each of the variant methods considered was assessed by cross validation using data available in the RegulonDB database for 54 Escherichia coli TFs, as well as by experimental validation using published ChIP-chip data available for Fis and Lrp.

Prediction of metabolic reactions based on atomic and molecular properties of small-molecule compounds

MOTIVATION

Our knowledge of the metabolites in cells and their reactions is far from complete as revealed by metabolomic measurements that detect many more small molecules than are documented in metabolic databases. Here, we develop an approach for predicting the reactivity of small-molecule metabolites in enzyme-catalyzed reactions that combines expert knowledge, computational chemistry and machine learning.

RESULTS

We classified 4843 reactions documented in the KEGG database, from all six Enzyme Commission classes (EC 1-6), into 80 reaction classes, each of which is marked by a characteristic functional group transformation. Reaction centers and surrounding local structures in substrates and products of these reactions were represented using SMARTS. We found that each of the SMARTS-defined chemical substructures is widely distributed among metabolites, but only a fraction of the functional groups in these substructures are reactive. Using atomic properties of atoms in a putative reaction center and molecular properties as features, we trained support vector machine (SVM) classifiers to discriminate between functional groups that are reactive and non-reactive. Classifier accuracy was assessed by cross-validation analysis. A typical sensitivity [TP/(TP+FN)] or specificity [TN/(TN+FP)] is ≈0.8. Our results suggest that metabolic reactivity of small-molecule compounds can be predicted with reasonable accuracy based on the presence of a potentially reactive functional group and the chemical features of its local environment.

AVAILABILITY

The classifiers presented here can be used to predict reactions via a web site (http://cellsignaling.lanl.gov/Reactivity/). The web site is freely available.

Using sequence-specific chemical and structural properties of DNA to predict transcription factor binding sites

An important step in understanding gene regulation is to identify the DNA binding sites recognized by each transcription factor (TF). Conventional approaches to prediction of TF binding sites involve the definition of consensus sequences or position-specific weight matrices and rely on statistical analysis of DNA sequences of known binding sites. Here, we present a method called SiteSleuth in which DNA structure prediction, computational chemistry, and machine learning are applied to develop models for TF binding sites. In this approach, binary classifiers are trained to discriminate between true and false binding sites based on the sequence-specific chemical and structural features of DNA. These features are determined via molecular dynamics calculations in which we consider each base in different local neighborhoods. For each of 54 TFs in Escherichia coli, for which at least five DNA binding sites are documented in RegulonDB, the TF binding sites and portions of the non-coding genome sequence are mapped to feature vectors and used in training. According to cross-validation analysis and a comparison of computational predictions against ChIP-chip data available for the TF Fis, SiteSleuth outperforms three conventional approaches: Match, MATRIX SEARCH, and the method of Berg and von Hippel. SiteSleuth also outperforms QPMEME, a method similar to SiteSleuth in that it involves a learning algorithm. The main advantage of SiteSleuth is a lower false positive rate.

Carbon-fate maps for metabolic reactions

MOTIVATION

Stable isotope labeling of small-molecule metabolites (e.g. (13)C-labeling of glucose) is a powerful tool for characterizing pathways and reaction fluxes in a metabolic network. Analysis of isotope labeling patterns requires knowledge of the fates of individual atoms and moieties in reactions, which can be difficult to collect in a useful form when considering a large number of enzymatic reactions.

RESULTS

We report carbon-fate maps for 4605 enzyme-catalyzed reactions documented in the KEGG database. Every fate map has been manually checked for consistency with known reaction mechanisms. A map includes a standardized structure-based identifier for each reactant (namely, an InChI string); indices for carbon atoms that are uniquely derived from the metabolite identifiers; structural data, including an identification of homotopic and prochiral carbon atoms; and a bijective map relating the corresponding carbon atoms in substrates and products. Fate maps are defined using the BioNetGen language (BNGL), a formal model-specification language, which allows a set of maps to be automatically translated into isotopomer mass-balance equations.

AVAILABILITY

The carbon-fate maps and software for visualizing the maps are freely available (http://cellsignaling.lanl.gov/FateMaps/).

Prediction of oxidoreductase-catalyzed reactions based on atomic properties of metabolites

MOTIVATION

Our knowledge of metabolism is far from complete, and the gaps in our knowledge are being revealed by metabolomic detection of small-molecules not previously known to exist in cells. An important challenge is to determine the reactions in which these compounds participate, which can lead to the identification of gene products responsible for novel metabolic pathways. To address this challenge, we investigate how machine learning can be used to predict potential substrates and products of oxidoreductase-catalyzed reactions.

RESULTS

We examined 1956 oxidation/reduction reactions in the KEGG database. The vast majority of these reactions (1626) can be divided into 12 subclasses, each of which is marked by a particular type of functional group transformation. For a given transformation, the local structures of reaction centers in substrates and products can be characterized by patterns. These patterns are not unique to reactants but are widely distributed among KEGG metabolites. To distinguish reactants from non-reactants, we trained classifiers (linear-kernel Support Vector Machines) using negative and positive examples. The input to a classifier is a set of atomic features that can be determined from the 2D chemical structure of a compound. Depending on the subclass of reaction, the accuracy of prediction for positives (negatives) is 64 to 93% (44 to 92%) when asking if a compound is a substrate and 71 to 98% (50 to 92%) when asking if a compound is a product. Sensitivity analysis reveals that this performance is robust to variations of the training data. Our results suggest that metabolic connectivity can be predicted with reasonable accuracy from the presence or absence of local structural motifs in compounds and their readily calculated atomic features.

AVAILABILITY

Classifiers reported here can be used freely for noncommercial purposes via a Java program available upon request.

Design, synthesis, and biological evaluation of a series of lavendustin A analogues that inhibit EGFR and Syk tyrosine kinases, as well as tubulin polymerization

A series of N-alkylamide analogues of the lavendustin A pharmacophore were synthesized and tested for inhibition of the epidermal growth factor receptor (EGFR) protein tyrosine kinase and the nonreceptor protein tyrosine kinase Syk. Although several compounds in the series were effective inhibitors of both kinases, it seemed questionable whether their inhibitory effects on these kinases were responsible for the cytotoxic properties observed in a variety of human cancer cell cultures. Accordingly, a COMPARE analysis of the cytotoxicity profile of the most cytotoxic member of the series was performed, and the results indicated that its cytotoxicity profile was similar to that of antitubulin agents. This mechanism of action was supported by demonstrating that most compounds in the series were moderately effective as inhibitors of tubulin polymerization. This suggests that the lavendustin A analogues reported here, as well as some of the previously reported lavendustin A analogues, may be acting as cytotoxic agents by a mechanism involving the inhibition of tubulin polymerization.

Electrical stimulation of acupuncture points enhances gastric myoelectrical activity in humans

OBJECTIVE

Acupuncture is known to enhance gastric motility. Electrical acustimulation has been shown to reduce gastric tachyarrhymia in vection-induced motion sickness. The aim of this study was to investigate the effect of electrical stimulation of acupuncture points on gastric myoelectrical activity in healthy humans.

METHODS

Nine healthy native Chinese were studied. Gastric myoelectrical activity was recorded using surface electrogastrography (EGG). The EGG recording was made in the fasting state, in a study period during which acupuncture points were electrically stimulated continuously, and in a recovery period after stimulation. The percentage of regular slow waves was assessed by computing the percentage of 2 to 4 cycles per minute slow waves in the EGG.

RESULTS

Electrical stimulation significantly increased the percentage of regular slow waves, which was sustained in the recovery period. The increase of the regular slow wave activity resulted from the normalization of arrhythmia.

CONCLUSION

Electrical stimulation of acupuncture points may enhance the regularity of gastric myoelectrical activity and may be an option for treatment of gastric dysrhythmia.