Fungal ID

Mold and Fungal Identifications

MicroSeqTM Fungal LSU rRNA Gene Sequencing (PE Applied Biosystems)
DNA is extracted from fungal cells with enzymes. The LSU rRNA gene is selected and amplified using primers and thermacyclers. The LSU rRNA gene product is sequenced using cycle sequencing chemistry. The reactions are analyzed using automated DNA sequencers and software. Unknown fungal samples are identified using the MicroSeqTM software and LSU rRNA database, containing over 1,500 entries. Either the entire LSU rRNA gene or a smaller portion of the gene (300bp) can be sequenced. A printout of the sequence data and the identification is included in each report.

GC-FAME (Gas Chromatograph Fatty Acid Methyl Ester), also known as Cellular Fatty Acide Analysis, allows for microorganism identification based on the specific fatty acid composition of the cell wall. Fatty acids are extracted from cultured samples and are separated by gas chromatography. A computer generated, unique profile pattern of the extracted fatty acids (9 to 20 carbon chains long) are compared to our microbial databases of well over 2600 species and subspecies. Our reports include the fatty acid profiles, a listing of the best database matches, and an assigned statistical probability value indicating the confidence level of the identifications.

Fungal BIOLOG(R)
This automated identification system uses a 96-well microliter plate with 95 different carbon sources. The microorganism of interest is applied to each well. Each microorganism has unique capacities to oxidize some of the various carbon sources. When these carbon sources are oxidized by the microorganism, a purple dye develops visible patterns of positive (purple) and negative (clear) wells which provide a metabolic signature of the organism. The system’s computer examines the pattern signature with its database to determine an identification. Databases include aerobic and anaerobic bacteria, yeasts, and fungi.


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