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Aspergillus

Aspergillus is a genus of filamentous fungi that are ubiquitous in the environment.
These fungi are known for their ability to produce a wide range of secondary metabolites, some of which can be beneficial while others can be toxic or pathogenic.
Aspergillus species are commonly found in soil, decaying organic matter, and indoor environments, and can cause a variety of diseases in humans, animals, and plants.
Research on Aspergillus is crucial for understanding its ecology, physiology, and potential applications in biotechnology and medicine.
PubCompare.ai can help optimize Aspergillus research by providing access to protocols from literature, preprints, and patents, while using AI-driven comparisons to identify the best protocols and products, improving reproducibility and accuracy in Aspergillus studies.

Most cited protocols related to «Aspergillus»

1
Integrating Functional Ontologies in FungiFun2
Figure 1A illustrates the three functional ontologies that are integrated into FungiFun2, i. e. Gene Ontology (GO; Ashburner et al., 2000 (link)), Kyoto Encyclopedia of Genes and Genomes (KEGG; Kanehisa and Goto, 2000 (link)) and Functional Catalogue (FunCat; Rüpp et al., 2004 (link)). FunCat gene to category associations were downloaded from MIPS through the PEDANT database (Walter et al., 2009 (link)). For GO, several data source have been used: Candida Genome Database (CGD; Inglis et al., 2012 (link)), Aspergillus Genome Database (AspGD; Cerqueira et al., 2014 (link)), Saccharomyces Genome Database (SGD; Cherry et al., 2012 (link)), UniProt-GOA-project at European Bioinformatics Institute (EBI) and Ensembl Fungi (Kersey et al., 2010 (link)). Additionally, we included GO gene to category associations by applying Blast2GO (Conesa et al., 2005 (link)). To do so, proteomes were obtained from BROAD, NCBI or in-house data (Schwartze et al., 2014 (link), Linde et al., 2014 (link)). Finally, KEGG gene to pathway associations were obtained from the KEGG FTP server.
With the help of a semi-automatic procedure, all available strains in the used databases are listed. Each strain may have different data sources, where the preferred version needs to be manually selected. Afterward, flat files are automatically downloaded and parsed into a MySQL database using Python and R scripts. These scripts guarantee that the database stays up-to-date with only small effort. Currently, ontologies formed by FunCat, KEGG and GO were downloaded from nine different sources. Primarily obtained from EBI, GO gene/protein to category association is available for 258 strains. FunCat gene/protein to category association is available for 180 strains. Finally, KEGG pathway association is available for 71 strains.
Figure 1B illustrates main features of the user interface. To run FungiFun2, users need to chose a strain, select an ontology, supply the tool with a list of candidate IDs and choose a P-value cutoff. After strain selection, the user may check for available (alternative) IDs. Only those ontologies can be used for which annotation is currently available. Advanced options allow for alternative P-value calculations and multiple test corrections, for upload of a background list, for in/exclusion of categories and for the selection of GO evidence codes.
Figure 1C illustrates main aspects for the calculation of enriched categories as well as results, graphs and tables. On the server side, a PHP script parses user input, controls calculations of statistics, graphs and tables and finally creates data for the result page. P-values indicating the significance of the enrichment are calculated with Fisher’s exact test or hypergeometric test. Multiple test correction may be performed, e.g. via FDR (Benjamini and Hochberg, 1995 ). The R-package RamiGO (Schröder et al., 2013 (link)) is used to visualize significantly enriched GO categories within the GO hierarchy. Bar, pie and column charts are created with help of the JavaScript library Highcharts, whereas customizable result tables are created with JavaScript library DataTables.
Figure 1D illustrates parts of the results of a FungiFun2 run. Each output can be customized directly in the Web interface as well as downloaded in commonly used formats. The number of enriched categories as well as the number of genes within enriched and non-enriched categories give an overview of the results. Specific pie and bar charts allow users to visualize the number of genes in the significant categories compared with the number of genes in the input list. Finally, graphs highlighting enriched categories within the hierarchies of the ontologies are available. Results are displayed in tables focusing on categories or genes, which can be interactively rearranged and filtered.
Funding: J.L. and S.P. were supported by the Deutsche Forschungsgemeinschaft (DFG) CRC/Transregio 124 ‘Pathogenic fungi and theirhuman host: Networks of interaction’, subproject INF.
Conflict of interest: none declared.
Priebe S., Kreisel C., Horn F., Guthke R, & Linde J. (2014). FungiFun2: a comprehensive online resource for systematic analysis of gene lists from fungal species. Bioinformatics, 31(3), 445-446.
Publication 2014
Aspergillus Candida DNA Library Europeans Fungi Gene Products, Protein Genes Genome Macrophage Inflammatory Protein-1 Pathogenicity Proteome Prunus cerasus Python Saccharomyces
2
Fungal Identification Using Secondary Barcodes

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Publication 2014
Aspergillus Base Sequence Calmodulin DNA, Fungal DNA, Ribosomal Fungi Gene Amplification Genes Introns Oligonucleotide Primers Pseudogenes RNA polymerase II largest subunit Strains Trees Tubulin
3
Clinical Applications of Western Blotting
Western blotting is a valuable tool to studies ranging from regulatory signaling processes to confirmatory serum diagnosis of HIV [68 (link)–70 (link)]. The evolution of western blot technique from identification of a specific protein in a complex mixture to the direct detection of protein in a single cell allows this technique to be an important analytical tool for clinical research. An advanced single cell western blotting technique was employed to study stem cell signaling and differentiation as well as drug response in tumor cells [69 (link)]. Through single cell western blotting it was possible to analyze cell-to-cell variations in approximately 2000 cells simultaneously within complex populations of cells [71 (link)]. With the integration of intact cell imaging, the technique allows the identification of protein expression changes of a single drug resistant tumor cell and its isoforms among heterogeneous population of tumor cells in human glioblastoma cells treated with chemotherapeutic daunomycin [69 (link)]. Identification of upregulated multidrug resistant protein, P-glycoprotein in living glioblastoma subpopulations was indicative of an active drug eflux pump as an underlying mechanism for drug resistance [69 (link),71 (link)]. With the application of 2-DE gel separation together with spotting of protein by peptide mass fingerprint, the analysis of clinically relevant Helicobacter pylori (H. pylori) in related gastric disease conditions (chronic gastritis, duodenal ulcer) was possible [72 (link)]. The database of H. pylori (low expressed and membrane proteins) was created through the application of one-dimensional or 2-DE/MALDI-mass spectrometry techniques [72 (link)]. In a similar manner, the Simple Western technique was employed for the analysis of 15-valent pneumococcal vaccine PCV15-CRM197 [73 (link)]. Due to its high sensitivity and automation, the Simple Western method may be extended to analyze serotypes of other polysaccharide protein conjugate vaccines [73 (link)].
Western blotting is commonly used for the clinical diagnosis of various parasitic and fungal diseases including echinococcosis [74 (link)], toxoplasmosis [75 (link)], and aspergillosis [76 (link)]. In a recent study, the assay was successfully used for the reliable serodiagnosis of Farmer’s lung disease (FLD), a pulmonary disorder caused by inhalation of antigenic particles [77 (link)]. Thus, this technique can be exploited for rapid routine diagnosis of FLD in clinics [77 (link)]. Similarly, for immunodiagnostic of tuberculosis meningitis which is a chronic disease of central nervous system different molecular and immunological methods were used for clinical diagnosis of the disease. However, each of these techniques has their own limitations [78 (link)]. To overcome diagnostic issues of lower sensitivity and specificity, the immunoreactivity to Mycobacterium tuberculosis antigens was performed by western blotting [78 (link)]. Furthermore, western blotting was performed for the early and sensitive diagnosis of congenital toxoplasmosis [79 (link)] and was employed for rapid and sensitive serological diagnosis of a serious infectious disease paracoccidioidomycosis (PCM) [80 (link)]. Using immunoblotting, a new subgroup of human lymphotropic retroviruses (HTLV), was detected in patients with the acquired immunodeficiency syndrome (AIDS) [81 (link)]. Antigens of HTLV-III, specifically detected by antibodies in serum from AIDS or pre-AIDS patients [81 (link)]. Western blotting has also been used as a test for variant Creutzfeldt-Jakob Disease [82 (link)], some forms of Lyme disease [83 (link)] and is sometimes used as a confirmatory test for Hepatitis B [84 ] and Herpes Type 2 [85 (link)] infections. Western blots have also been used to confirm feline immunodeficiency status in cats [86 (link)].
Recently, a commercial Aspergillus western blotting IgG kit was developed by LD Bio Diagnostics (France) to carry out immunoblotting for the clinical diagnosis of chronic aspergillosis. The commercial kit was found to be sensitive and can analyze hundreds of samples from patients with aspergillus disease [87 (link)]. Thus, the clinical applications of western blotting technique will continue to progress as further advancements are made to improve sensitivity and reproducibility of the western blot.
Mishra M., Tiwari S, & Gomes A.V. (2017). Protein purification and analysis: next generation Western blotting techniques. Expert review of proteomics, 14(11), 1037-1053.
Publication 2017
Acquired Immunodeficiency Syndrome Antibodies Antigens Aspergillosis Aspergillus Biological Assay Biological Evolution Cells Central Nervous System Diseases Communicable Diseases Complex Mixtures CRM197 (non-toxic variant of diphtheria toxin) Daunorubicin Diagnosis Duodenal Ulcer Echinococcosis Farmers Felidae Fingerprints, Peptide Gastritis Glioblastoma Helicobacter pylori Hepatitis B HIV Antigens Homo sapiens Hypersensitivity Immunodiagnosis Immunologic Deficiency Syndromes Immunologic Techniques Infection Inhalation Lung Diseases Lyme Disease Mass Spectrometry Membrane Proteins Mycobacterium tuberculosis antigens Mycoses Neoplasms New Variant Creutzfeldt-Jakob Disease P-Glycoprotein Paracoccidioidomycosis Patients Pharmaceutical Preparations Pharmacotherapy Pneumococcal Vaccine Polysaccharides Population Group Protein Isoforms Proteins Resistance, Drug Retroviridae Serodiagnosis Serum Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Staphylococcal Protein A Stem, Plant Stem Cells Stomach Diseases T-Cell Leukemia Viruses, Human Toxoplasmosis Toxoplasmosis, Congenital Tuberculosis, Meningeal Vaccines, Conjugate Western Blot Western Blotting
4
Phylogenetic Analysis of Aspergillus and Penicillium
The phylogenies presented in this study are based on sequences obtained from the NCBI nucleotide database (GenBank), genome-sequenced strains (GenBank, DOE Joint Genome Institute (JGI)) and sequences newly generated in this study. A selection of strains was made to study the phylogenetic relationships within the Eurotiales. The selection aimed to include the current known diversity in the order. In most cases, the types of the species and genera were included. An overview of strains and species is given in Table S1 (Supplementary Information - online only). The phylogenetic relationship of the accepted Aspergillus and Penicillium species was determined with the aim to introduce a new series classification in those genera. We aimed to include all Aspergillus and Penicillium species from the list of accepted species (see below) that had tubulin (BenA), calmodulin (CaM) and/or RNA polymerase II second largest subunit (RPB2) sequences. Species belonging to the same subgenus were analysed together in one dataset, resulting in eight datasets (Aspergillus, Circumdati, Cremei, Fumigati, Nidulantes, Polypaecilum (in Aspergillus)); Aspergilloides and Penicillium (in Penicillium). Steenwyk et al. (2019) , using a phylogenomic approach, showed that sect. Nigri does not belong to subgen. Circumdati and the species belonging to this section were therefore analysed in a separate dataset. Finally, in order to determine the taxonomic position of Aspergillus texensis and Penicillium cellarum, two separate datasets were constructed and analysed. Publicly available sequences on GenBank were supplemented with newly generated sequences of A. minisclerotigenes and P. aurantiogriseum strains (for the A. texensis and P. cellarum datasets, respectively) present in the CBS and DTO culture collection housed at the Westerdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Houbraken J., Kocsubé S., Visagie C.M., Yilmaz N., Wang X.C., Meijer M., Kraak B., Hubka V., Bensch K., Samson R.A, & Frisvad J.C. (2020). Classification of Aspergillus, Penicillium, Talaromyces and related genera (Eurotiales): An overview of families, genera, subgenera, sections, series and species. Studies in Mycology, 95, 5-169.
Publication 2020
Aspergillus Aspergillus texensis Base Sequence Calmodulin Eurotiales Genome GZMB protein, human Joints Nucleotides Penicillium Penicillium cellarum RNA polymerase II largest subunit Species Specificity Strains Tubulin
5
Standardized Aspergillus Species Identification

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Publication 2014
Aspergillus Cells Character Conidia Diagnosis Exudate Head Microscopy Mycelium Pigmentation RBBP8 protein, human Reproduction, Asexual Vaccination

Most recents protocols related to «Aspergillus»

1
Standardizing Fungal Inoculum Concentrations

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Publication 2023
Animals Aspergillus Candida albicans Eye Fusarium Vaccination
2
COPD and Small Airway Disease: Observational Study
In this study, we used data collected from participants enrolled consecutively in part of the National Science and Technology Support Plan Program for the 12th and 13th Five-Year Plans, which were community-based, observational surveys of COPD conducted in Guangdong, China in 2012–2019 (14 (link),15 (link)). Questionnaire and spirometry data were collected from all participants. A subset of participants had CPET available. The present study includes participants with eligible questionnaires, spirometry, and CPET data who were enrolled from July 2012 to August 2019. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethics Committee of Scientific Research Project Review of the First Affiliated Hospital of Guangzhou Medical University (No. 2013-37). All study participants provided written informed consent.
The main inclusion criteria were as follows: aged 40–80 years; acceptable CPET data; eligible spirometry before and after a bronchodilator test; and a completed standard epidemiological respiratory questionnaire. The following exclusion criteria were applied: GOLD stage II–IV [ratio of FEV1 to FVC <0.70 and FEV1 <80% of the predicted value]; respiratory tract infection or exacerbation in the 4 weeks before screening; previous lobectomy; malignant tumor newly discovered and being treated; history of other lung disease (e.g., asthma, lung cancer, active pulmonary tuberculosis, pneumoconiosis, extensive bronchiectasis, pulmonary aspergillus); and severe cardiovascular disease or other contraindications to CPET.
We used three indicators of post-bronchodilator spirometry to assess SAD, namely, maximal mid-expiratory flow, forced expiratory flow at 50% of vital capacity, and forced expiratory flow at 75% of vital capacity. When at least two of these three indicators were below 65% of predicted values, we considered the participants to have SAD (1 (link),13 (link)). Non-COPD was defined as a post-bronchodilator spirometry FEV1/FVC value of ≥0.70, mild COPD as a post-bronchodilator FEV1/FVC <0.70, and FEV1 ≥80% of the predicted value.
The participants were divided into a control group (without COPD or SAD), a SAD group (SAD without COPD), and a GOLD I group (mild COPD).
Deng Z., Li X., Li C., Zheng Y., Wu F., Wang Z., Liu S., Tian H., Zheng J., Peng J., Huang P., Yang H., Xiao S., Wen X., Yang C., Luo X., Peng G., Li B., Zhou Y, & Ran P. (2023). Impaired exercise capacity in individuals with non-obstructive small airway dysfunction. Journal of Thoracic Disease, 15(2), 472-483.
Publication 2023
Aspergillus Asthma Bronchiectasis Bronchodilator Agents Cardiovascular Diseases Chronic Obstructive Airway Disease Clostridium perfringens epsilon-toxin Ethics Committees, Research Exhaling Gold Infantile Neuroaxonal Dystrophy Lung Lung Cancer Lung Diseases Malignant Neoplasms Pneumoconiosis Respiratory Rate Respiratory Tract Infections Spirometry Tuberculosis, Pulmonary
3
Cellulolytic Aspergillus Isolate Compost Production
The isolate of Aspergillus sp. (Bioggp 3) was obtained from a previous study in which they were isolated from the isolation process of mixed leaf litter and soil taken from the pineapple plantation of PT. Great Giant Pineapple (PT. GGP) Terbanggi Besar, Central Lampung, Indonesia. The isolate showed cellulolytic and xylanolytic activity with a cellulolytic index 4.00 ± 0.783 and xylanolytic index 4.20 ± 1.03 respectively [16] (link). The compost material used is pineapple plant biomass which consists of leaves and stems. The selection of cellulolytic fungi isolates was done by modification of the Congo-Red method [17] (link). Isolates were obtained were cultured in Cellulose Agar (cellulose 5.0, NaNO3 1.0, K2HPO4 1.8, MgSO4.7H2O 0.9, KCl 0.5, 0.5 yeast extract, casein hydrolysat 0.5, agar 20 and distilled water 1L). Confirmation of cellulose-degrading ability of fungal isolates was performed by streaking it on cellulose agar media. Media were 2 layer media (bilayer) with the bottom layer was a PDA of 1/5 recipes, agar 1.5, and distilled water 100 mL. The top layer was Carboxymethyl Cellulose (CMC) 1–2%, agar 1.5 and distilled water 100 mL. Once inoculated with fungi in the middle of the test media, the cultures were then incubated for 4 days [18] . The media were added with 0.1% Congo-Red and allowed to stand for 20 minutes at room temperature. Media was washed with 1 M NaCl. Isolates producing cellulase formed a halo (clear zone) around the colony. The use of Congo-Red as an indicator for cellulose degradation in an agar medium provides the basis for a rapid and sensitive screening test for cellulolytic fungi. Colonies showing decolorization of Congo-Red were taken as positive cellulose-degrading fungal colonies [7] (link), and only these were taken for further study. The production of Aspergillus sp. inoculum was carried out in the Microbiology Lab, while composting applications were conducted at the Green House Botany Laboratory, Department of Biology, Universitas Lampung. Compost chemical analysis was carried out at PT. GGP.
Irawan B., Saputra A., Farisi S., Yulianty Y., Wahyuningsih S., Noviany N., Yandri Y, & Hadi S. (2023). The use of cellulolytic Aspergillus sp. inoculum to improve the quality of Pineapple compost. AIMS Microbiology, 9(1), 41-54.
Publication 2023
Agar Aspergillus Carboxymethylcellulose Caseins Cellulase Cellulose Fungi Gigantism Green Plants isolation Pineapple Plants potassium phosphate, dibasic Sodium Chloride Stem, Plant Sulfate, Magnesium Yeasts
4
Aspergillus Spore Productivity and Viability
The parameters measured in this study were the number of spores and values of the Colony Forming Unit (CFU) in the Aspergillus sp. inoculum in corn media, with C, N, P, and P the C/N ratio of pineapple litter compost. The calculations of the number of spores and CFU values were conducted to determine the productivity and viability of the fungi inoculum, respectively. The compost content analysis was also performed in order to observe the quality of pineapple litter compost. The data obtained were analyzed descriptively and presented in graphical form. All the results were statistically analyzed using analysis of variance (ANOVA) test. Treatment means were compared using the least significant difference (CD, P ≤ 0.05), which allowed the determination of significance between different applications.
Irawan B., Saputra A., Farisi S., Yulianty Y., Wahyuningsih S., Noviany N., Yandri Y, & Hadi S. (2023). The use of cellulolytic Aspergillus sp. inoculum to improve the quality of Pineapple compost. AIMS Microbiology, 9(1), 41-54.
Publication 2023
Aspergillus Corns Fungi Pineapple Spores
5
Pineapple Litter Composting with Aspergillus
The research used a single factor Completely Randomized Design (CRD), as a treatment that is the difference in the composition of compost materials arranged in 6 levels: KP1; KP2; KP3; P1; P2, and P3. Each treatment was carried out in 3 repetitions; hence it obtained 18 experimental units [19] .
The stages involved were:
(1) Inoculum development,
(2) Inoculum application in pineapple litter composting.
Inoculum development was made using modification of Gaind et al. method [20] (link). Corn grains were used as substitute for fungal strain growth. The corn grains were finely ground and sifted before it was mixed with 4% calcium sulphate, and 2% calcium carbonate (in 1 L distilled water). A loopful of Aspergillus sp. culture was inoculated in each 100 g corn grains added with 25 mL of solutions (sterilized at 15 lb pressure for 1 h) and incubated at 25 °C for 15 days. Each strain's whole growth, including mycelium, spores, and the grains, was used as the inoculum. The inoculum was counted for the number of spores and viability by calculating CFUs [18] .
Composting was carried out by modifying the Takakura Home Method (THM) [21] , for 7 weeks. The composting process was carried out in a perforated basket with a lid. Basket was lined with cardboard to keep the conditions moist when composting. Next, compost materials were put in the basket and add with Aspergillus sp inoculum.
The composition of raw materials were pineapple leaf, stem litters and mixture of both created into 6 treatments (KP1, KP2, KP3, P1, P2, and P3; K = treatments without inoculum), as the following details,
KP1 = pineapple leaf litter:cow manure (2:1)
KP2 = pineapple stem litter:cow manure (2:1)
KP3 = pineapple leaf litter:pineapple stem litter:cow manure (1:1:1)
P1 = pineapple leaf litter:cow manure (2:1) + 1% inoculum (30 g)
P2 = pineapple stem litter:cow manure (2:1) + 1% inoculum (30 g)
P3 = pineapple leaf litter: pineapple stem litter: cow manure (1:1:1) + 1% inoculum (30 g)
The compost quality testing was carried out by analyzing the levels of carbon (C), nitrogen (N), phosphorus (P), potassium (K), and C/N ratio. Total organic carbon was determined using wet digestion method [22] (link). Nitrogen totals were calculated by the Kjeldahl method [23] . Phosphorus was measured by a spectrophotometer using phosphomolybdate blue method [24] (link). Potassium was measured by a flame photometer.
Irawan B., Saputra A., Farisi S., Yulianty Y., Wahyuningsih S., Noviany N., Yandri Y, & Hadi S. (2023). The use of cellulolytic Aspergillus sp. inoculum to improve the quality of Pineapple compost. AIMS Microbiology, 9(1), 41-54.
Publication 2023
Aspergillus Calcium Sulfate Carbon Carbonate, Calcium Cereals Corns Digestion Mycelium Nitrogen Patient Holding Stretchers phosphomolybdic acid Phosphorus Pineapple Plant Leaves Potassium Pressure Spores Stem, Plant Strains

Top products related to «Aspergillus»

1
Platelia aspergillus eia by Bio-Rad
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The Platelia Aspergillus EIA is a diagnostic test used for the detection of Aspergillus antigens in human serum samples. It is an enzyme immunoassay (EIA) that provides a qualitative result to aid in the diagnosis of aspergillosis.
2
Miracloth by Merck Group
Sourced in United States, Germany, United Kingdom, Japan, Ireland
Miracloth is a high-quality filtration material made from pure cellulose. It is designed to provide efficient and reliable separation of solid and liquid components in a variety of laboratory applications.
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Immunocap by Thermo Fisher Scientific
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The ImmunoCAP is a laboratory instrument used for in vitro allergen-specific IgE testing. It provides quantitative measurement of IgE antibodies to a wide range of allergens. The ImmunoCAP system utilizes fluorescent enzyme immunoassay technology to detect and measure IgE levels in patient samples.
4
Platelia aspergillus enzyme immunoassay by Bio-Rad
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The Platelia Aspergillus enzyme immunoassay is a laboratory diagnostic test used to detect the presence of Aspergillus antigen in human serum or plasma samples. It is a sandwich-type enzyme-linked immunosorbent assay (ELISA) that utilizes monoclonal antibodies to identify the galactomannan antigen, which is a component of the Aspergillus cell wall.
5
Potato dextrose agar (pda) by Thermo Fisher Scientific
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The PDA (Photodiode Array) is a lab equipment product offered by Thermo Fisher Scientific. It is a device that uses an array of photodiodes to detect and measure the intensity of light over a range of wavelengths. The core function of the PDA is to provide high-speed, sensitive, and accurate optical detection for various analytical applications.
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Tween 20 is a non-ionic detergent commonly used in biochemical applications. It is a polyoxyethylene sorbitan monolaurate, a surfactant that can be used to solubilize and stabilize proteins and other biomolecules. Tween 20 is widely used in various laboratory techniques, such as Western blotting, ELISA, and immunoprecipitation, to prevent non-specific binding and improve the efficiency of these assays.
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DMSO is a versatile organic solvent commonly used in laboratory settings. It has a high boiling point, low viscosity, and the ability to dissolve a wide range of polar and non-polar compounds. DMSO's core function is as a solvent, allowing for the effective dissolution and handling of various chemical substances during research and experimentation.
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Platelia aspergillus by Bio-Rad
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The Platelia Aspergillus is a diagnostic kit designed for the detection of Aspergillus galactomannan antigen in human serum and bronchoalveolar lavage fluid samples. It is used as an aid in the diagnosis of invasive aspergillosis.
10
Fungitell assay by Associates of Cape Cod
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The Fungitell assay is a quantitative test that measures (1→3)-β-D-glucan, a cell wall component found in most fungal species. The assay is designed to aid in the diagnosis of invasive fungal infections.

More about "Aspergillus"

Aspergillus is a ubiquitous genus of filamentous fungi found in soil, decaying organic matter, and indoor environments.
These versatile microorganisms are known for their ability to produce a wide range of secondary metabolites, some of which can be beneficial while others can be toxic or pathogenic.
Aspergillus species are of great importance in various fields, including biotechnology, medicine, and agriculture.
Research on Aspergillus is crucial for understanding its ecology, physiology, and potential applications.
The Platelia Aspergillus enzyme immunoassay (EIA) and ImmunoCAP tests are commonly used diagnostic tools for detecting Aspergillus infections, such as invasive aspergillosis.
Miracloth, a filtration material, is often employed in Aspergillus research for separating fungal biomass from culture media.
In biotechnology, Aspergillus species are utilized for the production of enzymes, organic acids, and other valuable compounds.
Protocols involving media like potato dextrose agar (PDA) and surfactants like Tween 20 are frequently used in Aspergillus cultivation and extraction processes.
The Fungitell assay, which measures (1→3)-β-D-glucan, can aid in the diagnosis of invasive fungal infections caused by Aspergillus and other fungi.
To optimize Aspergillus research, scientists can leverage tools like PubCompare.ai, which provides access to protocols from literature, preprints, and patents.
Using AI-driven comparisons, researchers can identify the best protocols and products, improving reproducibility and accuracy in their Aspergillus studies.
For purification steps, techniques like Q SEPHAROSE® High Performance column chromatography may be employed.
By incorporating these insights and resources, researchers can enhance their understanding of Aspergillus and its diverse applications, leading to advancements in fields such as medicine, agriculture, and industrial biotechnology.