Anti-Apoptotic Machinery Protects the Necrotrophic Fungus Botrytis cinerea from Host-Induced Apoptotic-Like Cell Death during Plant Infection

Necrotrophic fungi are unable to occupy living plant cells. How such pathogens survive first contact with living host tissue and initiate infection is therefore unclear. Here, we show that the necrotrophic grey mold fungus Botrytis cinerea undergoes massive apoptotic-like programmed cell death (PCD) following germination on the host plant. Manipulation of an anti-apoptotic gene BcBIR1 modified fungal response to PCD-inducing conditions. As a consequence, strains with reduced sensitivity to PCD were hyper virulent, while strains in which PCD was over-stimulated showed reduced pathogenicity. Similarly, reduced levels of PCD in the fungus were recorded following infection of Arabidopsis mutants that show enhanced susceptibility to B. cinerea. When considered together, these results suggest that Botrytis PCD machinery is targeted by plant defense molecules, and that the fungal anti-apoptotic machinery is essential for overcoming this host-induced PCD and hence, for establishment of infection. As such, fungal PCD machinery represents a novel target for fungicides and antifungal drugs

A Primer on Regression Methods for Decoding cis-Regulatory Logic

The rapidly emerging field of systems biology is helping us to understand the molecular determinants of phenotype on a genomic scale [1]. Cis-regulatory elements are major sequence-based determinants of biological processes in cells and tissues [2]. For instance, during transcriptional regulation, transcription factors (TFs) bind to very specific regions on the promoter DNA [2,3] and recruit the basal transcriptional machinery, which ultimately initiates mRNA transcription (Figure 1A). Learning cis-Regulatory Elements from Omics Data A vast amount of work over the past decade has shown that omics data can be used to learn cis-regulatory logic on a genome-wide scale [4-6]--in particular, by integrating sequence data with mRNA expression profiles. The most popular approach has been to identify over-represented motifs in promoters of genes that are coexpressed [4,7,8]. Though widely used, such an approach can be limiting for a variety of reasons. First, the combinatorial nature of gene regulation is difficult to explicitly model in this framework. Moreover, in many applications of this approach, expression data from multiple conditions are necessary to obtain reliable predictions. This can potentially limit the use of this method to only large data sets [9]. Although these methods can be adapted to analyze mRNA expression data from a pair of biological conditions, such comparisons are often confounded by the fact that primary and secondary response genes are clustered together--whereas only the primary response genes are expected to contain the functional motifs [10]. A set of approaches based on regression has been developed to overcome the above limitations [11-32]. These approaches have their foundations in certain biophysical aspects of gene regulation [26,33-35]. That is, the models are motivated by the expected transcriptional response of genes due to the binding of TFs to their promoters. While such methods have gathered popularity in the computational domain, they remain largely obscure to the broader biology community. The purpose of this tutorial is to bridge this gap. We will focus on transcriptional regulation to introduce the concepts. However, these techniques may be applied to other regulatory processes. We will consider only eukaryotes in this tutorial

Metagenomic and Metabolic Profiling of Nonlithifying and Lithifying Stromatolitic Mats of Highborne Cay, The Bahamas

BACKGROUND: Stromatolites are laminated carbonate build-ups formed by the metabolic activity of microbial mats and represent one of the oldest known ecosystems on Earth. In this study, we examined a living stromatolite located within the Exuma Sound, The Bahamas and profiled the metagenome and metabolic potential underlying these complex microbial communities. METHODOLOGY/PRINCIPAL FINDINGS: The metagenomes of the two dominant stromatolitic mat types, a nonlithifying (Type 1) and lithifying (Type 3) microbial mat, were partially sequenced and compared. This deep-sequencing approach was complemented by profiling the substrate utilization patterns of the mats using metabolic microarrays. Taxonomic assessment of the protein-encoding genes confirmed previous SSU rRNA analyses that bacteria dominate the metagenome of both mat types. Eukaryotes comprised less than 13% of the metagenomes and were rich in sequences associated with nematodes and heterotrophic protists. Comparative genomic analyses of the functional genes revealed extensive similarities in most of the subsystems between the nonlithifying and lithifying mat types. The one exception was an increase in the relative abundance of certain genes associated with carbohydrate metabolism in the lithifying Type 3 mats. Specifically, genes associated with the degradation of carbohydrates commonly found in exopolymeric substances, such as hexoses, deoxy- and acidic sugars were found. The genetic differences in carbohydrate metabolisms between the two mat types were confirmed using metabolic microarrays. Lithifying mats had a significant increase in diversity and utilization of carbon, nitrogen, phosphorus and sulfur substrates. CONCLUSION/SIGNIFICANCE: The two stromatolitic mat types retained similar microbial communities, functional diversity and many genetic components within their metagenomes. However, there were major differences detected in the activity and genetic pathways of organic carbon utilization. These differences provide a strong link between the metagenome and the physiology of the mats, as well as new insights into the biological processes associated with carbonate precipitation in modern marine stromatolites

Association between age at disease onset of anti-neutrophil cytoplasmic antibody-associated vasculitis and clinical presentation and short-term outcomes

Objectives: ANCA-associated vasculitis (AAV) can affect all age groups. We aimed to show that differences in disease presentation and 6 month outcome between younger- A nd older-onset patients are still incompletely understood. Methods: We included patients enrolled in the Diagnostic and Classification Criteria for Primary Systemic Vasculitis (DCVAS) study between October 2010 and January 2017 with a diagnosis of AAV. We divided the population according to age at diagnosis: <65 years or ≥65 years. We adjusted associations for the type of AAV and the type of ANCA (anti-MPO, anti-PR3 or negative). Results: A total of 1338 patients with AAV were included: 66% had disease onset at <65 years of age [female 50%; mean age 48.4 years (s.d. 12.6)] and 34% had disease onset at ≥65 years [female 54%; mean age 73.6 years (s.d. 6)]. ANCA (MPO) positivity was more frequent in the older group (48% vs 27%; P = 0.001). Younger patients had higher rates of musculoskeletal, cutaneous and ENT manifestations compared with older patients. Systemic, neurologic,cardiovascular involvement and worsening renal function were more frequent in the older-onset group. Damage accrual, measured with the Vasculitis Damage Index (VDI), was significantly higher in older patients, 12% of whom had a 6 month VDI ≥5, compared with 7% of younger patients (P = 0.01). Older age was an independent risk factor for early death within 6 months from diagnosis [hazard ratio 2.06 (95% CI 1.07, 3.97); P = 0.03]. Conclusion: Within 6 months of diagnosis of AAV, patients >65 years of age display a different pattern of organ involvement and an increased risk of significant damage and mortality compared with younger patients

Microstructures and Textures of Hot Rolled and Hot Rolled-Normalized 2.9 % Silicon Steel Sheets

Effect of hot rolling and effect of hot rolled-normalizing on microstructures and textures of silicon steel sheets were investigated. In hot rolled steel sheets, fine elongated grains and etch pits were observed. , and were strong orientations at the core of steel sheet. At surface and subsurface, and orientations were dominant orientations. In hot rolled-normalized steel sheets, coarse elongated grains and randomly distributed etch pits were observed. Volume fraction (%) of orientation was found to be decreasing from core to surface, similar trend was found for and orientations. & orientations are the dominant orientations at the surface. Volume fraction (%) of is more than Goss at the surface

Sulfide-oxidizing activity and bacterial community structure in a fluidized bed reactor from a zero-discharge mariculture system

In the present work we describe a comprehensive analysis of sulfide oxidation in a fluidized bed reactor (FBR) from an environmentally sustainable, zero-discharge mariculture system. The FBR received oxygen-depleted effluent from a digestion basin (DB) that is responsible for gasification of organic matter and nitrogen. The FBR is a crucial component in this recirculating system because it safeguards the fish from the toxic sulfide produced in the DB. Microscale sulfide oxidation potential and bacterial community composition within FBR biofilms were correlated to biofilter performance by integrating bulk chemical, microsensor (O2, pH, and H2S), and molecular microbial community analyses. The FBR consistently oxidized sulfide during two years of continuous operation, with an estimated average sulfide removal rate of 1.3 g of sulfide-S L(FBR)(-1) d(-1). Maximum sulfide oxidation rates within the FBR biofilms were 0.36 and 0.21 mg of sulfide-S cm(-3) h(-1) in the oxic and anoxic layers, respectively, indicating that both oxygen and nitrate serve as electron acceptors for sulfide oxidation. The estimated anoxic sulfide removal rate, as extrapolated from bench scale, autotrophic, nitrate-amended experiments, was 0.7 g of sulfide-S L(FBR)(-1) d(-1), which is approximately 50% of the total estimated sulfide removal in the FBR. Community composition analyses using denaturing gradient gel electrophoresis (DGGE) of bacterial 16S rRNA gene fragments from FBR samples taken at six-month intervals revealed several sequences that were closely affiliated with sulfide-oxidizing bacteria. These included the denitrifying, sulfide-oxidizing bacteria Thiomicrospira denitrificans, members of the filamentous Thiothrix genus, and sulfide-oxidizing symbionts from the Gammaproteobacteria. In addition, marine Alphaproteobacteria and Bacteroidetes species were present in all of the DGGE profiles examined. DGGE analyses showed significant shifts in the bacterial community composition between profiles over two years of sampling, indicating the presence of a diverse and dynamic microbial community within the functionally stable FBR. The FBR's combined capacity for both oxic and anoxic sulfide oxidation, as indicated by bulk chemical, microsensor, and molecular microbial analyses, gives it significant functional elasticity, which is crucial for proper performance in the dynamic environment of this mariculture system

Mass spectrometric metabolomic imaging of biofilms on corroding steel surfaces using laser ablation and solvent capture by aspiration

Ambient laser ablation and solvent capture by aspiration (LASCA) mass spectrometric imaging was combined with metabolomics high-performance liquid chromatography (HPLC) mass spectrometry analysis and light profilometry to investigate the correlation between chemical composition of marine bacterial biofilms on surfaces of 1018 carbon steel and corrosion damage of steel underneath the biofilms. Pure cultures of Marinobacter sp. or a wild population of bacteria present in coastal seawater served as sources of biofilms. Profilometry data of biofilm-free surfaces demonstrated heterogeneous distributions of corrosion damage. LASCA data were correlated with areas on the coupons varying in the level of corrosion attack, to reveal differences in chemical composition within biofilm regions associated with corroding and corrosion-free zones. Putative identification of selected compounds was carried out based on HPLC results and subsequent database searches. This is the first report of successful ambient chemical and metabolomic imaging of marine biofilms on corroding metallic materials. The metabolic analysis of such biofilms is challenging due to the presence in the biofilm of large amounts of corrosion products. However, by using the LASCA imaging interface, images of more than 1000 ions (potential metabolites) are generated, revealing striking heterogeneities within the biofilm. In the two model systems studied here, it is found that some of the patterns observed in selected ion images closely correlate with the occurrence and extent of corrosion in the carbon steel substrate as revealed by profilometry, while others do not. This approach toward the study of microbially influenced corrosion (MIC) holds great promise for approaching a fundamental understanding of the mechanisms involved in MIC. (C) 2015 American Vacuum Society