17q21 Variants Disturb Mucosal Host Defense in Childhood Asthma.

Rationale: The strongest genetic risk factor for childhood-onset asthma, the 17q21 locus, is associated with increased viral susceptibility and disease-promoting processes.Objectives: To identify biological targets underlying the escalated viral susceptibility associated with the clinical phenotype mediated by the 17q21 locus.Methods: Genome-wide transcriptome analysis of nasal brush samples from 261 children (78 healthy, 79 with wheezing at preschool age, 104 asthmatic) within the ALLIANCE (All-Age-Asthma) cohort, with a median age of 10.0 (range, 1.0-20.0) years, was conducted to explore the impact of their 17q21 genotype (SNP rs72163891). Concurrently, nasal secretions from the same patients and visits were collected, and high-sensitivity mesoscale technology was employed to measure IFN protein levels.Measurements and Main Results: This study revealed that the 17q21 risk allele induces a genotype- and asthma/wheeze phenotype-dependent enhancement of mucosal GSDMB expression as the only relevant 17q21-encoded gene in children with preschool wheeze. Increased GSDMB expression correlated with the activation of a type-1 proinflammatory, cell-lytic immune, and natural killer signature, encompassing key genes linked to an IFN type-2-signature (IFNG, CXCL9, CXCL10, KLRC1, CD8A, GZMA). Conversely, there was a reduction in IFN type 1 and type 3 expression signatures at the mRNA and protein levels.Conclusions: This study demonstrates a novel disease-driving mechanism induced by the 17q21 risk allele. Increased mucosal GSDMB expression is associated with a cell-lytic immune response coupled with compromised airway immunocompetence. These findings suggest that GSDMB-related airway cell death and perturbations in the mucosal IFN signature account for the increased vulnerability of 17q21 risk allele carriers to respiratory viral infections during early life, opening new options for future biological interventions.The All-Age-Asthma (ALLIANCE) cohort is registered at www.clinicaltrials.gov (pediatric arm, NCT02496468).

Epidemiology of respiratory viruses among children during the SARS-CoV-2 pandemic: A systematic review and meta-analysis.

OBJECTIVE: This meta-analysis aimed to assess the prevalence of respiratory viruses among children under the special conditions of the COVID-19 pandemic. METHODS: Five databases were systematically searched to assess the pooled prevalence of various respiratory viruses in different age groups, regions, seasons, and in patients with and without confirmed SARS-CoV-2 coinfection. Moreover, we looked at the virus distribution in the first and second half of the pandemic and countries with distinct economic status. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed, and the systematic review was registered on PROSPERO (CRD42022379297). RESULTS: Enterovirus/rhinovirus and human respiratory syncytial virus (HRSV) were the most prevalent pathogens among children. The prevalence of HRSV increased in the second half of the pandemic. The prevailing viruses vary according to the SARS-CoV-2-coinfection status, season, region, and country´s economic status. CONCLUSION: This meta-analysis shows the epidemiology of respiratory viruses other than SARS-CoV-2 in children aged 0 to 12 years during the COVID-19 pandemic. Because major events, such as a pandemic, can alter epidemiology patterns, it is important to know them to improve health education measures, develop vaccines and medicines for vulnerable groups, as a guide for prevention strategies, and help with clinical decisions.

Old foes following news ways?-Pandemic-related changes in the epidemiology of viral respiratory tract infections.

INTRODUCTION: Following lockdown periods and restricting public health measures in response to the COVID-19 pandemic, respiratory tract infections (RTIs) rose significantly worldwide. This led to an increased burden on children's hospitals compromising medical care of acutely and chronically ill children. We characterized changes in the epidemiological pattern of circulating respiratory viral infections. METHODS: We assessed the number of patients with RTIs and the annual distribution of virus detections between 2019 and 2022 based on 4809 clinical samples (4131 patients) from a German pediatric tertiary care-center. We investigated the impact of lockdown periods on spectra of circulating respiratory viruses, pattern of coinfections, age, and seasonality of infections. RESULTS: A fourfold increase in the number of respiratory virus detections was observed in 2022 vs 2019 with numbers doubling in 2022 (vs 2021). In 2022, seasonal patterns of circulating virus, particularly Adeno and seasonal Coronavirus were far less pronounced compared to previous years, in fact almost disappeared for Rhinoviruses.". SARS-CoV-2, Parainfluenza- and human Metapneumovirus detections increased significantly in 2022 (2019 vs 2022, p < 0.01). Coinfections with multiple viruses occurred more frequently since 2021 compared to pre-pandemic years, especially in younger children (2019 vs 2022, p < 0.01). CONCLUSION: Compared to pre-pandemic years, we observed a dramatic increase in pediatric RTIs with an incrementing spectrum of viruses and a predominance in Rhino/Enterovirus infections - leading to a high rate of hospital admissions, particularly in conjunction with other viruses. This caused an acute shortage in medical care and may also be followed by an increase of virus-triggered secondary chronic respiratory diseases like asthma-rendering a burden on the health system.

Global prevalence of respiratory virus infections in adults and adolescents during the COVID-19 pandemic: A systematic review and meta-analysis.

OBJECTIVES: Since the beginning of the COVID-19 pandemic, efforts have been made to contain the spread of the virus. However, the epidemiological burden of other respiratory viruses during the pandemic is unclear. We aim to address the epidemiology of respiratory viruses on adults/adolescents since the beginning of the pandemic. METHODS: We systematically searched five databases and performed a meta-analysis to explore the pooled prevalence of respiratory viruses in different geographical regions, age groups, and periods and compared the prevalence between COVID-19 cases and non-COVID-19 patients. RESULTS: Enteroviruses/rhinoviruses were highly prevalent compared to other viruses. Different viruses were dominant in different regions. No significant differences in prevalence were found between different age groups, except for human metapneumovirus. There was an increase in prevalence of non-SARS-CoV-2 viruses in the second half of the pandemic (July 2021-December 2022). Comparison of COVID-19 and non-COVID patients showed a higher prevalence in the non-COVID group, significant for influenza, seasonal coronaviruses, and human parainfluenza viruses. CONCLUSION: Our findings indicate that enteroviruses/rhinoviruses were less impacted by healthcare measures compared with other respiratory viruses. The relaxation of measures in the second half led to an increased pooled prevalence of infections. Several factors may explain the lower prevalence among individuals infected with COVID-19.

Update of European Society of Clinical Microbiology and Infectious Diseases coronavirus disease 2019 guidelines: diagnostic testing for severe acute respiratory syndrome coronavirus 2.

SCOPE: Since the onset of COVID-19, several assays have been deployed for the diagnosis of SARS-CoV-2. The European Society of Clinical Microbiology and Infectious Diseases (ESCMID) published the first set of guidelines on SARS-CoV-2 in vitro diagnosis in February 2022. Because the COVID-19 landscape is rapidly evolving, the relevant ESCMID guidelines panel releases an update of the previously published recommendations on diagnostic testing for SARS-CoV-2. This update aims to delineate the best diagnostic approach for SARS-CoV-2 in different populations based on current evidence. METHODS: An ESCMID COVID-19 guidelines task force was established by the ESCMID Executive Committee. A small group was established, half appointed by the chair, and the remaining selected with an open call. The panel met virtually once a week. For all decisions, a simple majority vote was used. A list of clinical questions using the population, intervention, comparison, and outcome (PICO) format was developed at the beginning of the process. For each PICO, 2 panel members performed a literature search focusing on systematic reviews with a third panellist involved in case of inconsistent results. The panel reassessed the PICOs previously defined as priority in the first set of guidelines and decided to address 49 PICO questions, because 6 of them were discarded as outdated/non-clinically relevant. The 'Grading of Recommendations Assessment, Development and Evaluation (GRADE)-adoption, adaptation, and de novo development of recommendations (ADOLOPMENT)' evidence-to-decision framework was used to produce the guidelines. QUESTIONS ADDRESSED BY THE GUIDELINES AND RECOMMENDATIONS: After literature search, we updated 16 PICO questions; these PICOs address the use of antigen-based assays among symptomatic and asymptomatic patients with different ages, COVID-19 severity status or risk for severe COVID-19, time since the onset of symptoms/contact with an infectious case, and finally, types of biomaterials used.

T2-high asthma phenotypes across lifespan.

RATIONALE: In adults, personalised asthma treatment targets patients with type 2 (T2)-high and eosinophilic asthma phenotypes. It is unclear whether such classification is achievable in children. OBJECTIVES: To define T2-high asthma with easily accessible biomarkers and compare resulting phenotypes across all ages. METHODS: In the multicentre clinical All Age Asthma Cohort (ALLIANCE), 1125 participants (n=776 asthmatics, n=349 controls) were recruited and followed for 2 years (1 year in adults). Extensive clinical characterisation (questionnaires, blood differential count, allergy testing, lung function and sputum induction (in adults)) was performed at baseline and follow-ups. Interleukin (IL)-4, IL-5 and IL-13 were measured after stimulation of whole blood with lipopolysaccharide (LPS) or anti-CD3/CD28. MEASUREMENTS AND MAIN RESULTS: Based on blood eosinophil counts and allergen-specific serum IgE antibodies, patients were categorised into four mutually exclusive phenotypes: "atopy-only", "eosinophils-only", "T2-high" (eosinophilia + atopy) and "T2-low" (neither eosinophilia nor atopy). The T2-high phenotype was found across all ages, even in very young children in whom it persisted to a large degree even after 2 years of follow-up. T2-high asthma in adults was associated with childhood onset, suggesting early origins of this asthma phenotype. In both children and adults, the T2-high phenotype was characterised by excessive production of specific IgE to allergens (p<0.0001) and, from school age onwards, by increased production of IL-5 after anti-CD3/CD28 stimulation of whole blood. CONCLUSIONS: Using easily accessible biomarkers, patients with T2-high asthma can be identified across all ages delineating a distinct phenotype. These patients may benefit from therapy with biologicals even at a younger age.

Impact of imposed social isolation and use of face masks on asthma course and mental health in pediatric and adult patients with recurrent wheeze and asthma.

BACKGROUND: There is currently a dramatic increase in the number of COVID-19 cases worldwide, and further drastic restrictions in our daily life will be necessary to contain this pandemic. The implications of restrictive measures like social-distancing and mouth-nose protection on patients with chronic respiratory diseases have hardly been investigated. METHODS: Our survey, was conducted within the All Age Asthma Cohort (ALLIANCE), a multicenter longitudinal observational study. We assessed the effects of COVID-19 imposed social isolation and use of facial masks, on asthma course and mental health in patients with asthma and wheezing. RESULTS: We observed a high rate of problems associated with using facemasks and a significant reduction in the use of routine medical care. In addition to unsettling impacts, such as an increase in depression symptoms in adults, an astonishing and pleasing effect was striking: preschool children experienced an improvement in disease condition during the lockdown. This improvement can be attributed to a significant reduction in exposure to viral infections. CONCLUSION: Long-term observation of this side effect may help improve our understanding of the influence of viral infections on asthma in early childhood.

Fusarium head blight resistance in European winter wheat: insights from genome-wide transcriptome analysis.

BACKGROUND: Fusarium head blight (FHB) is a devastating disease of wheat worldwide. Resistance to FHB is quantitatively controlled by the combined effects of many small to medium effect QTL. Flowering traits, especially the extent of extruded anthers, are strongly associated with FHB resistance. RESULTS: To characterize the genetic basis of FHB resistance, we generated and analyzed phenotypic and gene expression data on the response to Fusarium graminearum (Fg) infection in 96 European winter wheat genotypes, including several lines containing introgressions from the highly resistant Asian cultivar Sumai3. The 96 lines represented a broad range in FHB resistance and were assigned to sub-groups based on their phenotypic FHB severity score. Comparative analyses were conducted to connect sub-group-specific expression profiles in response to Fg infection with FHB resistance level. Collectively, over 12,300 wheat genes were Fusarium responsive. The core set of genes induced in response to Fg was common across different resistance groups, indicating that the activation of basal defense response mechanisms was largely independent of the resistance level of the wheat line. Fg-induced genes tended to have higher expression levels in more susceptible genotypes. Compared to the more susceptible non-Sumai3 lines, the Sumai3-derivatives demonstrated higher constitutive expression of genes associated with cell wall and plant-type secondary cell wall biogenesis and higher constitutive and Fg-induced expression of genes involved in terpene metabolism. Gene expression analysis of the FHB QTL Qfhs.ifa-5A identified a constitutively expressed gene encoding a stress response NST1-like protein (TraesCS5A01G211300LC) as a candidate gene for FHB resistance. NST1 genes are key regulators of secondary cell wall biosynthesis in anther endothecium cells. Whether the stress response NST1-like gene affects anther extrusion, thereby affecting FHB resistance, needs further investigation. CONCLUSION: Induced and preexisting cell wall components and terpene metabolites contribute to resistance and limit fungal colonization early on. In contrast, excessive gene expression directs plant defense response towards programmed cell death which favors necrotrophic growth of the Fg pathogen and could thus lead to increased fungal colonization.

DNA methylation analysis in plants: review of computational tools and future perspectives.

Genome-wide DNA methylation studies have quickly expanded due to advances in next-generation sequencing techniques along with a wealth of computational tools to analyze the data. Most of our knowledge about DNA methylation profiles, epigenetic heritability and the function of DNA methylation in plants derives from the model species Arabidopsis thaliana. There are increasingly many studies on DNA methylation in plants-uncovering methylation profiles and explaining variations in different plant tissues. Additionally, DNA methylation comparisons of different plant tissue types and dynamics during development processes are only slowly emerging but are crucial for understanding developmental and regulatory decisions. Translating this knowledge from plant model species to commercial crops could allow the establishment of new varieties with increased stress resilience and improved yield. In this review, we provide an overview of the most commonly applied bioinformatics tools for the analysis of DNA methylation data (particularly bisulfite sequencing data). The performances of a selection of the tools are analyzed for computational time and agreement in predicted methylated sites for A. thaliana, which has a smaller genome compared to the hexaploid bread wheat. The performance of the tools was benchmarked on five plant genomes. We give examples of applications of DNA methylation data analysis in crops (with a focus on cereals) and an outlook for future developments for DNA methylation status manipulations and data integration.

Time series non-Gaussian Bayesian bivariate model applied to data on HMPV and RSV: a case of Dadaab in Kenya.

BACKGROUND: Human metapneumovirus (HMPV) have similar symptoms to those caused by the respiratory syncytial virus (RSV). The modes of transmission and dynamics of time series data still remain poorly understood. Climatic factors have long been suspected to be implicated in impacting on the number of cases for these epidemics. Currently, only a few models satisfactorily capture the dynamics of time series data of these two viruses. Our objective was to assess the presence of influence of high incidences between the viruses and to ascertain whether higher incidences of one virus are influenced by the other. METHODS: In this study, we used a negative binomial model to investigate the relationship between RSV and HMPV while adjusting for climatic factors. We specifically aimed at establishing the heterogeneity in the autoregressive effect to account for the influence between these viruses. RESULTS: In this study, our findings showed that RSV incidence contributed to the severity of HMPV incidence. This was achieved through comparison of 12 models with different structures, including those with and without interaction between climatic factors. The models with climatic factors out-performed those without. CONCLUSIONS: The study has improved our understanding of the dynamics of RSV and HMPV in relation to climatic cofactors thereby setting a platform to devise better intervention measures to combat the epidemics. We conclude that preventing and controlling RSV infection subsequently reduces the incidence of HMPV.

Reconstruction and inference of the Lactococcus lactis MG1363 gene co-expression network.

Lactic acid bacteria are Gram-positive bacteria used throughout the world in many industrial applications for their acidification, flavor and texture formation attributes. One of the species, Lactococcus lactis, is employed for the production of fermented milk products like cheese, buttermilk and quark. It ferments lactose to lactic acid and, thus, helps improve the shelf life of the products. Many physiological and transcriptome studies have been performed in L. lactis in order to comprehend and improve its biotechnological assets. Using large amounts of transcriptome data to understand and predict the behavior of biological processes in bacterial or other cell types is a complex task. Gene networks enable predicting gene behavior and function in the context of transcriptionally linked processes. We reconstruct and present the gene co-expression network (GCN) for the most widely studied L. lactis strain, MG1363, using publicly available transcriptome data. Several methods exist to generate and judge the quality of GCNs. Different reconstruction methods lead to networks with varying structural properties, consequently altering gene clusters. We compared the structural properties of the MG1363 GCNs generated by five methods, namely Pearson correlation, Spearman correlation, GeneNet, Weighted Gene Co-expression Network Analysis (WGCNA), and Sparse PArtial Correlation Estimation (SPACE). Using SPACE, we generated an L. lactis MG1363 GCN and assessed its quality using modularity and structural and biological criteria. The L. lactis MG1363 GCN has structural properties similar to those of the gold-standard networks of Escherichia coli K-12 and Bacillus subtilis 168. We showcase that the network can be used to mine for genes with similar expression profiles that are also generally linked to the same biological process.

Hidden variation in polyploid wheat drives local adaptation.

Wheat has been domesticated into a large number of agricultural environments and has the ability to adapt to diverse environments. To understand this process, we survey genotype, repeat content, and DNA methylation across a bread wheat landrace collection representing global genetic diversity. We identify independent variation in methylation, genotype, and transposon copy number. We show that these, so far unexploited, sources of variation have had a significant impact on the wheat genome and that ancestral methylation states become preferentially "hard coded" as single nucleotide polymorphisms (SNPs) via 5-methylcytosine deamination. These mechanisms also drive local adaption, impacting important traits such as heading date and salt tolerance. Methylation and transposon diversity could therefore be used alongside SNP-based markers for breeding.

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model.

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes.

Effect of climate on incidence of respiratory syncytial virus infections in a refugee camp in Kenya: A non-Gaussian time-series analysis.

Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infections (ALRTI) in children. Children younger than 1 year are the most susceptible to RSV infection. RSV infections occur seasonally in temperate climate regions. Based on RSV surveillance and climatic data, we developed statistical models that were assessed and compared to predict the relationship between weather and RSV incidence among refugee children younger than 5 years in Dadaab refugee camp in Kenya. Most time-series analyses rely on the assumption of Gaussian-distributed data. However, surveillance data often do not have a Gaussian distribution. We used a generalized linear model (GLM) with a sinusoidal component over time to account for seasonal variation and extended it to a generalized additive model (GAM) with smoothing cubic splines. Climatic factors were included as covariates in the models before and after timescale decompositions, and the results were compared. Models with decomposed covariates fit RSV incidence data better than those without. The Poisson GAM with decomposed covariates of climatic factors fit the data well and had a higher explanatory and predictive power than GLM. The best model predicted the relationship between atmospheric conditions and RSV infection incidence among children younger than 5 years. This knowledge helps public health officials to prepare for, and respond more effectively to increasing RSV incidence in low-resource regions or communities.

Spore Heat Activation Requirements and Germination Responses Correlate with Sequences of Germinant Receptors and with the Presence of a Specific spoVA2mob Operon in Foodborne Strains of Bacillus subtilis.

Spore heat resistance, germination, and outgrowth are problematic bacterial properties compromising food safety and quality. Large interstrain variation in these properties makes prediction and control of spore behavior challenging. High-level heat resistance and slow germination of spores of some natural Bacillus subtilis isolates, encountered in foods, have been attributed to the occurrence of the spoVA2mob operon carried on the Tn1546 transposon. In this study, we further investigate the correlation between the presence of this operon in high-level-heat-resistant spores and their germination efficiencies before and after exposure to various sublethal heat treatments (heat activation, or HA), which are known to significantly improve spore responses to nutrient germinants. We show that high-level-heat-resistant spores harboring spoVA2mob required higher HA temperatures for efficient germination than spores lacking spoVA2mob The optimal spore HA requirements additionally depended on the nutrients used to trigger germination, l-alanine (l-Ala), or a mixture of l-asparagine, d-glucose, d-fructose, and K+ (AGFK). The distinct HA requirements of these two spore germination pathways are likely related to differences in properties of specific germinant receptors. Moreover, spores that germinated inefficiently in AGFK contained specific changes in sequences of the GerB and GerK germinant receptors, which are involved in this germination response. In contrast, no relation was found between transcription levels of main germination genes and spore germination phenotypes. The findings presented in this study have great implications for practices in the food industry, where heat treatments are commonly used to inactivate pathogenic and spoilage microbes, including bacterial spore formers.IMPORTANCE This study describes a strong variation in spore germination capacities and requirements for a heat activation treatment, i.e., an exposure to sublethal heat that increases spore responsiveness to nutrient germination triggers, among 17 strains of B. subtilis, including 9 isolates from spoiled food products. Spores of industrial foodborne isolates exhibited, on average, less efficient and slower germination responses and required more severe heat activation than spores from other sources. High heat activation requirements and inefficient, slow germination correlated with elevated resistance of spores to heat and with specific genetic features, indicating a common genetic basis of these three phenotypic traits. Clearly, interstrain variation and numerous factors that shape spore germination behavior challenge standardization of methods to recover highly heat-resistant spores from the environment and have an impact on the efficacy of preservation techniques used by the food industry to control spores.

Quantitative modeling and analytic assessment of the transcription dynamics of the XlnR regulon in Aspergillus niger.

BACKGROUND: Transcription of genes coding for xylanolytic and cellulolytic enzymes in Aspergillus niger is controlled by the transactivator XlnR. In this work we analyse and model the transcription dynamics in the XlnR regulon from time-course data of the messenger RNA levels for some XlnR target genes, obtained by reverse transcription quantitative PCR (RT-qPCR). Induction of transcription was achieved using low (1 mM) and high (50 mM) concentrations of D-xylose (Xyl). We investigated the wild type strain (Wt) and a mutant strain with partial loss-of-function of the carbon catabolite repressor CreA (Mt). RESULTS: An improved kinetic differential equation model based on two antagonistic Hill functions was proposed, and fitted to the time-course RT-qPCR data from the Wt and the Mt by numerical optimization of the parameters. We show that perturbing the XlnR regulon with Xyl in low and high concentrations results in different expression levels and transcription dynamics of the target genes. At least four distinct transcription profiles were observed, particularly for the usage of 50 mM Xyl. Higher transcript levels were observed for some genes after induction with 1 mM rather than 50 mM Xyl, especially in the Mt. Grouping the expression profiles of the investigated genes has improved our understanding of induction by Xyl and the according regulatory role of CreA. CONCLUSIONS: The model explains for the higher expression levels at 1 mM versus 50 mM in both Wt and Mt. It does not yet fully encapsulate the effect of partial loss-of-function of CreA in the Mt. The model describes the dynamics in most of the data and elucidates the time-dynamics of the two major regulatory mechanisms: i) the activation by XlnR, and ii) the carbon catabolite repression by CreA.

Evaluation of design strategies for time course experiments in genetic networks: case study of the XlnR regulon in Aspergillus niger.

One of the challenges in genetic network reconstruction is finding experimental designs that maximize the information content in a data set. In this paper, the information value of mRNA transcription time course experiments was used to compare experimental designs. The study concerns the dynamic response of genes in the XlnR regulon of Aspergillus niger, with the goal to find the best moment in time to administer an extra pulse of inducing D-xylose. Low and high D-xylose pulses were used to perturb the XlnR regulon. Evaluation of the experimental methods was based on simulation of the regulon. Models that govern the regulation of the target genes in this regulon were used for the simulations. Parameter sensitivity analysis, the Fisher Information Matrix (FIM) and the modified E-criterion were used to assess the design performances. The results show that the best time to give a second D-xylose pulse is when the D-xylose concentration from the first pulse has not yet completely faded away. Due to the presence of a repression effect the strength of the second pulse must be optimized, rather than maximized. The results suggest that the modified E-criterion is a better metric than the sum of integrals of absolute sensitivity for comparing alternative designs.

d-Xylose concentration-dependent hydrolase expression profiles and the function of CreA and XlnR in Aspergillus niger.

Aspergillus niger is an important organism for the production of industrial enzymes such as hemicellulases and pectinases. The xylan-backbone monomer, d-xylose, is an inducing substance for the coordinate expression of a large number of polysaccharide-degrading enzymes. In this study, the responses of 22 genes to low (1 mM) and high (50 mM) d-xylose concentrations were investigated. These 22 genes encode enzymes that function as xylan backbone-degrading enzymes, accessory enzymes, cellulose-degrading enzymes, or enzymes involved in the pentose catabolic pathway in A. niger. Notably, genes encoding enzymes that have a similar function (e.g., xylan backbone degradation) respond in a similar manner to different concentrations of d-xylose. Although low d-xylose concentrations provoke the greatest change in transcript levels, in particular, for hemicellulase-encoding genes, transcript formation in the presence of high concentrations of d-xylose was also observed. Interestingly, a high d-xylose concentration is favorable for certain groups of genes. Furthermore, the repressing influence of CreA on the transcription and transcript levels of a subset of these genes was observed regardless of whether a low or high concentration of d-xylose was used. Interestingly, the decrease in transcript levels of certain genes on high d-xylose concentrations is not reflected by the transcript level of their activator, XlnR. Regardless of the d-xylose concentration applied and whether CreA was functional, xlnR was constitutively expressed at a low level.

Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger.

BACKGROUND: In this paper the dynamics of the transcription-translation system for XlnR regulon in Aspergillus niger is modeled. The model is based on Hill regulation functions and uses ordinary differential equations. The network response to a trigger of D-xylose is considered and stability analysis is performed. The activating, repressive feedback, and the combined effect of the two feedbacks on the network behavior are analyzed. RESULTS: Simulation and systems analysis showed significant influence of activating and repressing feedback on metabolite expression profiles. The dynamics of the D-xylose input function has an important effect on the profiles of the individual metabolite concentrations. Variation of the time delay in the feedback loop has no significant effect on the pattern of the response. The stability and existence of oscillatory behavior depends on which proteins are involved in the feedback loop. CONCLUSIONS: The dynamics in the regulation properties of the network are dictated mainly by the transcription and translation degradation rate parameters, and by the D-xylose consumption profile. This holds true with and without feedback in the network. Feedback was found to significantly influence the expression dynamics of genes and proteins. Feedback increases the metabolite abundance, changes the steady state values, alters the time trajectories and affects the response oscillatory behavior and stability conditions. The modeling approach provides insight into network behavioral dynamics particularly for small-sized networks. The analysis of the network dynamics has provided useful information for experimental design for future in vitro experimental work.