AYbRAH: a curated ortholog database for yeasts and fungi spanning 600 million years of evolution

Evaluating oleaginous yeasts for enhanced microbial lipid production using sweetwater as a sustainable feedstock

BACKGROUND

Yeasts exhibit promising potential for the microbial conversion of crude glycerol, owing to their versatility in delivering a wide range of value-added products, particularly lipids. Sweetwater, a methanol-free by-product of the fat splitting process, has emerged as a promising alternative feedstock for the microbial utilization of crude glycerol. To further optimize sweetwater utilization, we compared the growth and lipid production capabilities of 21 oleaginous yeast strains under different conditions with various glycerol concentrations, sweetwater types and pH.

RESULTS

We found that nutrient limitation and the unique carbon composition of sweetwater boosted significant lipid accumulation in several strains, in particular Rhodosporidium toruloides NRRL Y-6987. Subsequently, to decipher the underlying mechanism, the transcriptomic changes of R. toruloides NRRL Y-6987 were further analyzed, indicating potential sugars and oligopeptides in sweetwater supporting growth and lipid accumulation as well as exogenous fatty acid uptake leading to the enhanced lipid accumulation.

CONCLUSION

Our comparative study successfully demonstrated sweetwater as a cost-effective feedstock while identifying R. toluroides NRRL Y-6987 as a highly promising microbial oil producer. Furthermore, we also suggested potential sweetwater type and strain engineering targets that could potentially enhance microbial lipid production.

Pervasive, conserved secondary structure in highly charged protein regions

Understanding how protein sequences confer function remains a defining challenge in molecular biology. Two approaches have yielded enormous insight yet are often pursued separately: structure-based, where sequence-encoded structures mediate function, and disorder-based, where sequences dictate physicochemical and dynamical properties which determine function in the absence of stable structure. Here we study highly charged protein regions (>40% charged residues), which are routinely presumed to be disordered. Using recent advances in structure prediction and experimental structures, we show that roughly 40% of these regions form well-structured helices. Features often used to predict disorder-high charge density, low hydrophobicity, low sequence complexity, and evolutionarily varying length-are also compatible with solvated, variable-length helices. We show that a simple composition classifier predicts the existence of structure far better than well-established heuristics based on charge and hydropathy. We show that helical structure is more prevalent than previously appreciated in highly charged regions of diverse proteomes and characterize the conservation of highly charged regions. Our results underscore the importance of integrating, rather than choosing between, structure- and disorder-based approaches.

Multiple nutrient transporters enable cells to mitigate a rate-affinity tradeoff

Eukaryotic genomes often encode multiple transporters for the same nutrient. For example, budding yeast has 17 hexose transporters (HXTs), all of which potentially transport glucose. Using mathematical modelling, we show that transporters that use either facilitated diffusion or symport can have a rate-affinity tradeoff, where an increase in the maximal rate of transport decreases the transporter’s apparent affinity. These changes affect the import flux non-monotonically, and for a given concentration of extracellular nutrient there is one transporter, characterised by its affinity, that has a higher import flux than any other. Through encoding multiple transporters, cells can therefore mitigate the tradeoff by expressing those transporters with higher affinities in lower concentrations of nutrients. We verify our predictions using fluorescent tagging of seven HXT genes in budding yeast and follow their expression over time in batch culture. Using the known affinities of the corresponding transporters, we show that their regulation in glucose is broadly consistent with a rate-affinity tradeoff: as glucose falls, the levels of the different transporters peak in an order that mostly follows their affinity for glucose. More generally, evolution is constrained by tradeoffs. Our findings indicate that one such tradeoff often occurs in the cellular transport of nutrients.

From yeast to humans, cells often express multiple different types of transporters for the same nutrient, and it is puzzling why a single high-affinity transporter is not expressed instead. Here we initially use mathematical modelling to demonstrate that transporters facilitating diffusion and those powered by the proton motive force can both exhibit a rate-affinity tradeoff, for quite general conditions. A transporter with a higher affinity necessarily has a lower rate, and vice versa. The tradeoff implies that there is a range of nutrient concentrations for which a transporter, characterised by its affinity, has a higher import flux than any other transporter with a different affinity. To mitigate the tradeoff, genomes may therefore encode multiple different transporters, and cells that express each transporter in the concentrations where it imports best will uptake nutrients at higher rates. Consistently, we show that as cells of budding yeast consume glucose, they express five types of hexose transporters in an order that follows the transporters’ affinities.

Gcorn fungi: A Web Tool for Detecting Biases between Gene Evolution and Speciation in Fungi

(1) Background: Fungi contain several millions of species, and the diversification of fungal genes has been achieved by speciation, gene duplication, and horizontal gene transfer. Although several databases provide information on orthologous and paralogous events, these databases show no information on biases between gene mutation and speciation. Here, we designed the Gcorn fungi database to better understand such biases. (2) Methods: Amino acid sequences of fungal genes in 249 species, which contain 2,345,743 sequences, were used for this database. Homologous genes were grouped at various thresholds of the homology index, which was based on the percentages of gene mutations. By grouping genes that showed highly similar homology indices to each other, we showed functional and evolutionary traits in the phylogenetic tree depicted for the gene of interest. (3) Results: Gcorn fungi provides well-summarized information on the evolution of a gene lineage and on the biases between gene evolution and speciation, which are quantitatively identified by the Robinson–Foulds metric. The database helps users visualize these traits using various depictions. (4) Conclusions: Gcorn fungi is an open access database that provides a variety of information with which to understand gene function and evolution.

ExVe: The knowledge base of orthologous proteins identified in fungal extracellular vesicles

Extracellular vesicles (EVs) are double-membrane particles associated with intercellular communication. Since the discovery of EV production in the fungus Cryptococcus neoformans, the importance of EV release in its physiology and pathogenicity has been investigated. To date, few studies have investigated the proteomic content of EVs from multiple fungal species. Our main objective was to use an orthology approach to compare proteins identified by EV shotgun proteomics in 8 pathogenic and 1 nonpathogenic species. Using protein information from the UniProt and FungiDB databases, we integrated data for 11,433 hits in fungal EVs with an orthology perspective, resulting in 3,834 different orthologous groups. OG6_100083 (Hsp70 Pfam domain) was the unique orthologous group that was identified for all fungal species. Proteins with this protein domain are associated with the stress response, survival and morphological changes in different fungal species. Although no pathogenic orthologous group was found, we identified 5 orthologous groups exclusive to S. cerevisiae. Using the criteria of at least 7 pathogenic fungi to define a cluster, we detected the 4 unique pathogenic orthologous groups. Taken together, our data suggest that Hsp70-related proteins might play a key role in fungal EVs, regardless of the pathogenic status. Using an orthology approach, we identified at least 4 protein domains that could be novel therapeutic targets against pathogenic fungi. Our results were compiled in the herein described ExVe database, which is publicly available at http://exve.icc.fiocruz.br.

Characterization of a Maltase from an Early-Diverged Non-Conventional Yeast Blastobotrys adeninivorans

Genome of an early-diverged yeast Blastobotrys (Arxula) adeninivorans (Ba) encodes 88 glycoside hydrolases (GHs) including two α-glucosidases of GH13 family. One of those, the rna_ARAD1D20130g-encoded protein (BaAG2; 581 aa) was overexpressed in Escherichia coli, purified and characterized. We showed that maltose, other maltose-like substrates (maltulose, turanose, maltotriose, melezitose, malto-oligosaccharides of DP 4‒7) and sucrose were hydrolyzed by BaAG2, whereas isomaltose and isomaltose-like substrates (palatinose, α-methylglucoside) were not, confirming that BaAG2 is a maltase. BaAG2 was competitively inhibited by a diabetes drug acarbose (Ki = 0.8 µM) and Tris (Ki = 70.5 µM). BaAG2 was competitively inhibited also by isomaltose-like sugars and a hydrolysis product-glucose. At high maltose concentrations, BaAG2 exhibited transglycosylating ability producing potentially prebiotic di- and trisaccharides. Atypically for yeast maltases, a low but clearly recordable exo-hydrolytic activity on amylose, amylopectin and glycogen was detected. Saccharomyces cerevisiae maltase MAL62, studied for comparison, had only minimal ability to hydrolyze these polymers, and its transglycosylating activity was about three times lower compared to BaAG2. Sequence identity of BaAG2 with other maltases was only moderate being the highest (51%) with the maltase MalT of Aspergillus oryzae.