The Exploring Functional Role of Ammonium Transporters of Aspergillus oryzae in Nitrogen Metabolism: Challenges towards Cell Biomass Production.

Ammonium is a source of fermentable inorganic nitrogen essential for the growth and development of filamentous fungi. It is involved in several cellular metabolic pathways underlying nitrogen transport and assimilation. Ammonium can be transferred into the cell by an ammonium transporter. This study explored the role of ammonium transporters in nitrogen metabolism and cell biomass production in Aspergillus oryzae strain BCC 7051. Specific sequences encoding ammonium transporters (Amts) in A. oryzae were identified using genomic analysis. Four of the identified ammonium transporter genes, aoamt1-aoamt4, showed similarity in deduced amino acid sequences to the proteins in the ammonium transporter/methylammonium permease (AMT/MEP) family. Transcriptional analysis showed that the expression of aoamt2 and aoamt3 was ammonium-dependent, and was highly upregulated under ammonium-limited conditions. Their functional roles are characterized by genetic perturbations. The gene disruption and overexpression of aoamt3 indicated that the protein encoded by it was a crucial ammonium transporter associated with nitrogen metabolism and was required for filamentous growth. Compared with the wild type, the aoamt3-overexpressing strain showed superior growth performance, high biomass yield, and low glucose consumption. These results shed light on further improvements in the production of potent bioproducts by A. oryzae by manipulating the ammonium uptake capacity and nitrogen metabolism.

Metabolic Regulation of Sugar Assimilation for Lipid Production in Aspergillus oryzae BCC7051 through Comparative Transcriptome Perspective.

Microbial lipid production with cost effectiveness is a prerequisite for the oleochemical sector. In this work, genome-wide transcriptional responses on the utilization of xylose and glucose in oleaginous Aspergillus oryzae were studied with relation to growth and lipid phenotypic traits. Comparative analysis of the active growth (t1) and lipid-accumulating (t2) stages showed that the C5 cultures efficiently consumed carbon sources for biomass and lipid production comparable to the C6 cultures. By pairwise comparison, 599 and 917 differentially expressed genes (DEGs) were identified in the t1 and t2 groups, respectively, in which the consensus DEGs were categorized into polysaccharide-degrading enzymes, membrane transports, and cellular processes. A discrimination in transcriptional responses of DEGs set was also found in various metabolic genes, mostly in carbohydrate, amino acid, lipid, cofactors, and vitamin metabolisms. Although central carbohydrate metabolism was shared among the C5 and C6 cultures, the metabolic functions in acetyl-CoA and NADPH generation, and biosynthesis of terpenoid backbone, fatty acid, sterol, and amino acids were allocated for leveraging biomass and lipid production through at least transcriptional control. This study revealed robust metabolic networks in the oleaginicity of A. oryzae governing glucose/xylose flux toward lipid biosynthesis that provides meaningful hints for further process developments of microbial lipid production using cellulosic sugar feedstocks.

Ensemble-AMPPred: Robust AMP Prediction and Recognition Using the Ensemble Learning Method with a New Hybrid Feature for Differentiating AMPs.

Antimicrobial peptides (AMPs) are natural peptides possessing antimicrobial activities. These peptides are important components of the innate immune system. They are found in various organisms. AMP screening and identification by experimental techniques are laborious and time-consuming tasks. Alternatively, computational methods based on machine learning have been developed to screen potential AMP candidates prior to experimental verification. Although various AMP prediction programs are available, there is still a need for improvement to reduce false positives (FPs) and to increase the predictive accuracy. In this work, several well-known single and ensemble machine learning approaches have been explored and evaluated based on balanced training datasets and two large testing datasets. We have demonstrated that the developed program with various predictive models has high performance in differentiating between AMPs and non-AMPs. Thus, we describe the development of a program for the prediction and recognition of AMPs using MaxProbVote, which is an ensemble model. Moreover, to increase prediction efficiency, the ensemble model was integrated with a new hybrid feature based on logistic regression. The ensemble model integrated with the hybrid feature can effectively increase the prediction sensitivity of the developed program called Ensemble-AMPPred, resulting in overall improvements in terms of both sensitivity and specificity compared to those of currently available programs.

Safety Assessment of a Nham Starter Culture Lactobacillus plantarum BCC9546 via Whole-genome Analysis.

The safety of microbial cultures utilized for consumption is vital for public health and should be thoroughly assessed. Although general aspects on the safety assessment of microbial cultures have been suggested, no methodological detail nor procedural guideline have been published. Herein, we propose a detailed protocol on microbial strain safety assessment via whole-genome sequence analysis. A starter culture employed in traditional fermented pork production, nham, namely Lactobacillus plantarum BCC9546, was used as an example. The strain's whole-genome was sequenced through several next-generation sequencing techniques. Incomplete plasmid information from the PacBio sequencing platform and shorter chromosome size from the hybrid Oxford Nanopore-Illumina platform were noted. The methods for 1) unambiguous species identification using 16S rRNA gene and average nucleotide identity, 2) determination of virulence factors and undesirable genes, 3) determination of antimicrobial resistance properties and their possibility of transfer, and 4) determination of antimicrobial drug production capability of the strain were provided in detail. Applicability of the search tools and limitations of databases were discussed. Finally, a procedural guideline for the safety assessment of microbial strains via whole-genome analysis was proposed.

Systematic genome analysis of a novel arachidonic acid-producing strain uncovered unique metabolic traits in the production of acetyl-CoA-derived products in Mortierellale fungi.

The fungi in order Mortierellales are attractive producers for long-chain polyunsaturated fatty acids (PUFAs). Here, the genome sequencing and assembly of a novel strain of Mortierella sp. BCC40632 were done, yielding 65 contigs spanning of 49,964,116 total bases with predicted 12,149 protein-coding genes. We focused on the acetyl-CoA in relevant to its derived metabolic pathways for biosynthesis of macromolecules with biological functions, including PUFAs, eicosanoids and carotenoids. By comparative genome analysis between Mortierellales and Mucorales, the signature genetic characteristics of the arachidonic acid-producing strains, including Δ5-desaturase and GLELO-like elongase, were also identified in the strain BCC40632. Remarkably, this fungal strain contained only n-6 pathway of PUFA biosynthesis due to the absence of Δ15-desaturase or ω3-desaturase gene in contrast to other Mortierella species. Four putative enzyme sequences in the eicosanoid biosynthetic pathways were identified in the strain BCC40632 and others Mortierellale fungi, but were not detected in the Mucorales. Another unique metabolic trait of the Mortierellales was the inability in carotenoid synthesis as a result of the lack of phytoene synthase and phytoene desaturase genes. The findings provide a perspective in strain optimization for production of tailored-made products with industrial applications.

PSO-LocBact: A Consensus Method for Optimizing Multiple Classifier Results for Predicting the Subcellular Localization of Bacterial Proteins.

Several computational approaches for predicting subcellular localization have been developed and proposed. These approaches provide diverse performance because of their different combinations of protein features, training datasets, training strategies, and computational machine learning algorithms. In some cases, these tools may yield inconsistent and conflicting prediction results. It is important to consider such conflicting or contradictory predictions from multiple prediction programs during protein annotation, especially in the case of a multiclass classification problem such as subcellular localization. Hence, to address this issue, this work proposes the use of the particle swarm optimization (PSO) algorithm to combine the prediction outputs from multiple different subcellular localization predictors with the aim of integrating diverse prediction models to enhance the final predictions. Herein, we present PSO-LocBact, a consensus classifier based on PSO that can be used to combine the strengths of several preexisting protein localization predictors specially designed for bacteria. Our experimental results indicate that the proposed method can resolve inconsistency problems in subcellular localization prediction for both Gram-negative and Gram-positive bacterial proteins. The average accuracy achieved on each test dataset is over 98%, higher than that achieved with any individual predictor.

Functional Characterization of Novel U6 RNA Polymerase III Promoters: Their Implication for CRISPR-Cas9-Mediated Gene Editing in Aspergillus oryzae.

U6 RNA polymerase III promoter (PU6), which is a key element in controlling the generation of single-guide RNA (sgRNA) for gene editing through CRISPR-Cas9 system, was investigated in this work. Using bioinformatics approach, two novel U6 ribonucleic acid (U6 RNA) sequences of Aspergillus niger were identified, showing that they had conserved motifs similar to other U6 RNAs. The putative PU6 located at the upstream sequence of A. niger U6 RNA exhibited the consensus motif, CCAATYA, and the TATA box which shared highly conserved characteristics across Aspergilli, whereas the A- and B-boxes were found at the intragenic and downstream of the structural genes, respectively. Using Aspergillus oryzae as a workhorse system, the function of A. niger PU6s for controlling the transcripts of sgRNA was verified, in which the orotidine-5'-phosphate decarboxylase (pyrG) sequence was used as a target for gene disruption through CRISPR-Cas9 system. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) analysis of the selected pyrG auxotrophic strains showed the expression of sgRNA, indicating that the non-native promoters could efficiently drive sgRNA expression in A. oryzae. These identified promoters are useful genetic tools for precise engineering of metabolic pathways in the industrially important fungus through the empowered CRISPR-Cas9-associated gene-editing system.

Genome Characterization of Oleaginous Aspergillus oryzae BCC7051: A Potential Fungal-Based Platform for Lipid Production.

The selected robust fungus, Aspergillus oryzae strain BCC7051 is of interest for biotechnological production of lipid-derived products due to its capability to accumulate high amount of intracellular lipids using various sugars and agro-industrial substrates. Here, we report the genome sequence of the oleaginous A. oryzae BCC7051. The obtained reads were de novo assembled into 25 scaffolds spanning of 38,550,958 bps with predicted 11,456 protein-coding genes. By synteny mapping, a large rearrangement was found in two scaffolds of A. oryzae BCC7051 as compared to the reference RIB40 strain. The genetic relationship between BCC7051 and other strains of A. oryzae in terms of aflatoxin production was investigated, indicating that the A. oryzae BCC7051 was categorized into group 2 nonaflatoxin-producing strain. Moreover, a comparative analysis of the structural genes focusing on the involvement in lipid metabolism among oleaginous yeast and fungi revealed the presence of multiple isoforms of metabolic enzymes responsible for fatty acid synthesis in BCC7051. The alternative routes of acetyl-CoA generation as oleaginous features and malate/citrate/pyruvate shuttle were also identified in this A. oryzae strain. The genome sequence generated in this work is a dedicated resource for expanding genome-wide study of microbial lipids at systems level, and developing the fungal-based platform for production of diversified lipids with commercial relevance.

Integrative computational approach for genome-based study of microbial lipid-degrading enzymes.

Lipid-degrading or lipolytic enzymes have gained enormous attention in academic and industrial sectors. Several efforts are underway to discover new lipase enzymes from a variety of microorganisms with particular catalytic properties to be used for extensive applications. In addition, various tools and strategies have been implemented to unravel the functional relevance of the versatile lipid-degrading enzymes for special purposes. This review highlights the study of microbial lipid-degrading enzymes through an integrative computational approach. The identification of putative lipase genes from microbial genomes and metagenomic libraries using homology-based mining is discussed, with an emphasis on sequence analysis of conserved motifs and enzyme topology. Molecular modelling of three-dimensional structure on the basis of sequence similarity is shown to be a potential approach for exploring the structural and functional relationships of candidate lipase enzymes. The perspectives on a discriminative framework of cutting-edge tools and technologies, including bioinformatics, computational biology, functional genomics and functional proteomics, intended to facilitate rapid progress in understanding lipolysis mechanism and to discover novel lipid-degrading enzymes of microorganisms are discussed.

Genome mining of fungal lipid-degrading enzymes for industrial applications.

Lipases are interesting enzymes, which contribute important roles in maintaining lipid homeostasis and cellular metabolisms. Using available genome data, seven lipase families of oleaginous and non-oleaginous yeast and fungi were categorized based on the similarity of their amino acid sequences and conserved structural domains. Of them, triacylglycerol lipase (patatin-domain-containing protein) and steryl ester hydrolase (abhydro_lipase-domain-containing protein) families were ubiquitous enzymes found in all species studied. The two essential lipases rendered signature characteristics of integral membrane proteins that might be targeted to lipid monolayer particles. At least one of the extracellular lipase families existed in each species of yeast and fungi. We found that the diversity of lipase families and the number of genes in individual families of oleaginous strains were greater than those identified in non-oleaginous species, which might play a role in nutrient acquisition from surrounding hydrophobic substrates and attribute to their obese phenotype. The gene/enzyme catalogue and relevant informative data of the lipases provided by this study are not only valuable toolboxes for investigation of the biological role of these lipases, but also convey potential in various industrial applications.

Repertoire of malic enzymes in yeast and fungi: insight into their evolutionary functional and structural significance.

Malic enzyme (ME) is one of the important enzymes for furnishing the cofactor NAD(P)H for the biosynthesis of fatty acids and sterols. Due to the existence of multiple ME isoforms in a range of oleaginous microbes, a molecular basis for the evolutionary relationships amongst the enzymes in oleaginous fungi was investigated using sequence analysis and structural modelling. Evolutionary distance and structural characteristics were used to discriminate the MEs of yeasts and fungi into several groups. Interestingly, the NADP(+)-dependent MEs of Mucoromycotina had an unusual insertion region (FLxxPG) that was not found in other fungi. However, the subcellular compartment of the Mucoromycotina enzyme could not be clearly identified by an analysis of signal peptide sequences. A constructed structural model of the ME of Mucor circinelloides suggested that the insertion region is located at the N-terminus of the enzyme (aa 159-163). In addition, it is presumably part of the dimer interface region of the enzyme, which might provide a continuously positively charged pocket for the efficient binding of negatively charged effector molecules. The discovery of the unique structure of the Mucoromycotina ME suggests the insertion region could be involved in particular kinetics of this enzyme, which may indicate its involvement in the lipogenesis of industrially important oleaginous microbes.

Draft genome sequence of Arthrospira platensis C1 (PCC9438).

Arthrospira platensis is a cyanobacterium that is extensively cultivated outdoors on a large commercial scale for consumption as a food for humans and animals. It can be grown in monoculture under highly alkaline conditions, making it attractive for industrial production. Here we describe the complete genome sequence of A. platensis C1 strain and its annotation. The A. platensis C1 genome contains 6,089,210 bp including 6,108 protein-coding genes and 45 RNA genes, and no plasmids. The genome information has been used for further comparative analysis, particularly of metabolic pathways, photosynthetic efficiency and barriers to gene transfer.

Systems biology and metabolic engineering of Arthrospira cell factories.

Arthrospira are attractive candidates to serve as cell factories for production of many valuable compounds useful for food, feed, fuel and pharmaceutical industries. In connection with the development of sustainable bioprocessing, it is a challenge to design and develop efficient Arthrospira cell factories which can certify effective conversion from the raw materials (i.e. CO2 and sun light) into desired products. With the current availability of the genome sequences and metabolic models of Arthrospira, the development of Arthrospira factories can now be accelerated by means of systems biology and the metabolic engineering approach. Here, we review recent research involving the use of Arthrospira cell factories for industrial applications, as well as the exploitation of systems biology and the metabolic engineering approach for studying Arthrospira. The current status of genomics and proteomics through the development of the genome-scale metabolic model of Arthrospira, as well as the use of mathematical modeling to simulate the phenotypes resulting from the different metabolic engineering strategies are discussed. At the end, the perspective and future direction on Arthrospira cell factories for industrial biotechnology are presented.

Alternative routes of acetyl-CoA synthesis identified by comparative genomic analysis: involvement in the lipid production of oleaginous yeast and fungi.

For a bio-based economy, microbial lipids offer a potential solution as alternative feedstocks in the oleochemical industry. The existing genome data for the promising strains, oleaginous yeasts and fungi, allowed us to investigate candidate orthologous sequences that participate in their oleaginicity. Comparative genome analysis of the non-oleaginous (Saccharomyces cerevisiae, Candida albicans and Ashbya gossypii) and oleaginous strains (Yarrowia lipolytica, Rhizopus oryzae, Aspergillus oryzae and Mucor circinelloides) showed that 209 orthologous protein sequences of the oleaginous microbes were distributed over several processes of the cells. Based on the 41 sequences categorized by metabolism, putative routes potentially involved in the generation of precursors for fatty acid and lipid synthesis, particularly acetyl-CoA, were then identified that were not present in the non-oleaginous strains. We found a set of the orthologous oleaginous proteins that was responsible for the biosynthesis of this key two-carbon metabolite through citrate catabolism, fatty acid ß-oxidation, leucine metabolism and lysine degradation. Our findings suggest a relationship between carbohydrate, lipid and amino acid metabolism in the biosynthesis of acetyl-CoA, which contributes to the lipid production of oleaginous microbes.