Distribution of a novel enzyme of sialidase family among native filamentous fungi

Distinct proteomes and allergen profiles appear across the life-cycle stages of Alternaria alternata

BACKGROUND

Alternaria alternata is associated with allergic respiratory diseases, which can be managed with allergen extract-based diagnostics and immunotherapy. It is not known how spores and hyphae contribute to allergen content. Commercial allergen extracts are manufactured by extracting proteins without separating the different forms of the fungus.

OBJECTIVE

We sought to determine differences between spore and hyphae proteomes and how allergens are distributed in Aalternata.

METHODS

Data-independent acquisition mass spectrometry was used to quantitatively compare the proteomes of asexual spores (nongerminating and germinating) with vegetative hyphae.

RESULTS

We identified 4515 proteins in nongerminating spores, germinating spores, and hyphae; most known allergens are more abundant in nongerminating spores. On comparing significant protein fold-change differences between nongerminating spores and hyphae, we found that 174 proteins were upregulated in nongerminating spores and 80 proteins in hyphae. Among the spore proteins are ones functionally involved in cell wall synthesis, responding to cellular stress, and maintaining redox balance and homeostasis. On comparing nongerminating and germinating spores, 25 proteins were found to be upregulated in nongerminating spores and 54 in germinating spores. Among the proteins specific to germinating spores were proteases known to be virulence factors. One of the most abundant proteins in the spore proteome is sialidase, which has not been identified as an allergen but may be important in the pathogenicity of this fungus. Major allergen Alt a 1 is present at low levels in spores and hyphae and appears to be largely secreted into growth media.

CONCLUSIONS

Spores and hyphae express overlapping but distinct proteomes. Most known allergens are found more abundantly in nongerminating spores.

Glucose Catabolite Repression Participates in the Regulation of Sialidase Biosynthesis by Antarctic Strain Penicillium griseofulvum P29

Sialidases (neuraminidases) catalyze the removal of terminal sialic acid residues from glycoproteins. Novel enzymes from non-clinical isolates are of increasing interest regarding their application in the food and pharmaceutical industry. The present study aimed to evaluate the participation of carbon catabolite repression (CCR) in the regulation of cold-active sialidase biosynthesis by the psychrotolerant fungal strain Penicillium griseofulvum P29, isolated from Antarctica. The presence of glucose inhibited sialidase activity in growing and non-growing fungal mycelia in a dose- and time-dependent manner. The same response was demonstrated with maltose and sucrose. The replacement of glucose with glucose-6-phosphate also exerted CCR. The addition of cAMP resulted in the partial de-repression of sialidase synthesis. The CCR in the psychrotolerant strain P. griseofulvum P29 did not depend on temperature. Sialidase might be subject to glucose repression by both at 10 and 25 °C. The fluorescent assay using 4MU-Neu5Ac for enzyme activity determination under increasing glucose concentrations evidenced that CCR may have a regulatory role in sialidase production. The real-time RT-PCR experiments revealed that the sialidase gene was subject to glucose repression. To our knowledge, this is the first report that has studied the effect of CCR on cold-active sialidase, produced by an Antarctic strain.

Structural and functional characterization of cold-active sialidase isolated from Antarctic fungus Penicillium griseofulvum P29

The fungal strain, Penicillium griseofulvum P29, isolated from a soil sample taken from Terra Nova Bay, Antarctica, was found to be a good producer of sialidase (P29). The present study was focused on the purification and structural characterization of the enzyme. P29 enzyme was purified using a Q-Sepharose column and fast performance liquid chromatography separation on a Mono Q column. The determined molecular mass of the purified enzyme of 40 kDa by SDS-PAGE and 39924.40 Da by matrix desorption/ionization mass spectrometry (MALDI-TOF/MS) analysis correlated well with the calculated mass (39903.75 kDa) from the amino acid sequence of the enzyme. P29 sialidase shows a temperature optimum of 37 °C and low-temperature stability, confirming its cold-active nature. The enzyme is more active towards α(2 → 3) sialyl linkages than those containing α(2 → 6) linkages. Based on the determined amino acid sequence and 3D structural modeling, a 3D model of P29 sialidase was presented, and the properties of the enzyme were explained. The conformational stability of the enzyme was followed by fluorescence spectroscopy, and the new enzyme was found to be conformationally stable in the neutral pH range of pH 6 to pH 9. In addition, the enzyme was more stable in an alkaline environment than in an acidic environment. The purified cold-active enzyme is the only sialidase produced and characterized from Antarctic fungi to date.

Trends in biological data integration for the selection of enzymes and transcription factors related to cellulose and hemicellulose degradation in fungi

Fungi are key players in biotechnological applications. Although several studies focusing on fungal diversity and genetics have been performed, many details of fungal biology remain unknown, including how cellulolytic enzymes are modulated within these organisms to allow changes in main plant cell wall compounds, cellulose and hemicellulose, and subsequent biomass conversion. With the advent and consolidation of DNA/RNA sequencing technology, different types of information can be generated at the genomic, structural and functional levels, including the gene expression profiles and regulatory mechanisms of these organisms, during degradation-induced conditions. This increase in data generation made rapid computational development necessary to deal with the large amounts of data generated. In this context, the origination of bioinformatics, a hybrid science integrating biological data with various techniques for information storage, distribution and analysis, was a fundamental step toward the current state-of-the-art in the postgenomic era. The possibility of integrating biological big data has facilitated exciting discoveries, including identifying novel mechanisms and more efficient enzymes, increasing yields, reducing costs and expanding opportunities in the bioprocess field. In this review, we summarize the current status and trends of the integration of different types of biological data through bioinformatics approaches for biological data analysis and enzyme selection.