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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of the high-productivity marine microalga, Picochlorum renovo , as a photosynthetic protein secretion platform

Microalgae are remarkable in their ability to convert CO 2 and sunlight into renewable biomass and bioproducts. In this work, we have established a novel photosynthetic protein production platform via computational prediction and genetic engineering using native microalgal protein secretory signal peptides to achieve functional secretion of the fluorescent protein mCherry. Importantly, this work was conducted in the recently characterized alga Picochlorum renovo, an alga of industrial interest due to its rapid growth rate, tolerance to both high temperature and salinity, and genetically tractable nuclear and chloroplast genomes. Genomic queries allowed the identification of native secretory signal peptides, which were N-terminally fused to mCherry allowing for secretion into the culture supernatant. Further characterization revealed no impact on fitness, a production rate of 0.19 mg/L/day, and titer of 0.37 mg/L of transgenic mCherry protein in culture supernatant. These findings lay the foundation for applied genetic engineering approaches that could enable CO 2 -sequestering, sustainable photoproduction of industrially relevant enzymes at low cost.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genome features of a novel hydrocarbonoclastic Chryseobacterium oranimense strain and its comparison to bacterial oil-degraders and to other C. oranimense strains

For the first time, we report the whole genome sequence of a hydrocarbonoclastic Chryseobacterium oranimense strain isolated from Trinidad and Tobago (COTT) and its genes involved in the biotransformation of hydrocarbons and xenobiotics through functional annotation. The assembly consisted of 11 contigs with 2,794 predicted protein-coding genes which included a diverse group of gene families involved in aliphatic and polycyclic hydrocarbon degradation. Comparative genomic analyses with 18 crude-oil degrading bacteria in addition to two C. oranimense strains not associated with oil were carried out. The data revealed important differences in terms of annotated genes involved in the hydrocarbon degradation process that may explain the molecular mechanisms of hydrocarbon and xenobiotic biotransformation. Notably, many gene families were expanded to explain COTT’s competitive ability to manage habitat-specific stressors. Gene-based evidence of the metabolic potential of COTT supports the application of indigenous microbes for the remediation of polluted terrestrial environments and provides a genomic resource for improving our understanding of how to optimize these characteristics for more effective bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Identification of Glutaminyl Cyclase Genes Involved in Pyroglutamate Modification of Fungal Lignocellulolytic Enzymes

The breakdown of plant biomass to simple sugars is essential for the production of second-generation biofuels and high-value bioproducts. Currently, enzymes produced from filamentous fungi are used for deconstructing plant cell wall polysaccharides into fermentable sugars for biorefinery applications. A post-translational N-terminal pyroglutamate modification observed in some of these enzymes occurs when N-terminal glutamine or glutamate is cyclized to form a five-membered ring. This modification has been shown to confer resistance to thermal denaturation for CBH-1 and EG-1 cellulases. In mammalian cells, the formation of pyroglutamate is catalyzed by glutaminyl cyclases. Using the model filamentous fungus Neurospora crassa , we identified two genes ( qc-1 and qc-2 ) that encode proteins homologous to mammalian glutaminyl cyclases. We show that qc-1 and qc-2 are essential for catalyzing the formation of an N-terminal pyroglutamate on CBH-1 and GH5-1. CBH-1 and GH5-1 produced in a Δqc-1 Δqc-2 mutant, and thus lacking the N-terminal pyroglutamate modification, showed greater sensitivity to thermal denaturation, and for GH5-1, susceptibility to proteolytic cleavage. QC-1 and QC-2 are endoplasmic reticulum (ER)-localized proteins. The pyroglutamate modification is predicted to occur in a number of additional fungal proteins that have diverse functions. The identification of glutaminyl cyclases in fungi may have implications for production of lignocellulolytic enzymes, heterologous expression, and biotechnological applications revolving around protein stability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Genome Sequencing of Pleurozium schreberi : The Assembled and Annotated Draft Genome of a Pleurocarpous Feather Moss

The pleurocarpous feather moss Pleurozium schreberi is a ubiquitous moss species which plays a fundamental role in many terrestrial ecosystems, for instance within the boreal forest, the Earth’s largest terrestrial biome, this species plays a significant role in driving ecosystem nitrogen and carbon inputs and fluxes. By hosting dinitrogen (N 2 )-fixing cyanobacteria, the moss-cyanobacteria symbiosis constitutes the main nitrogen input into the ecosystem and by the high productivity and the low decomposability of the moss litter, P. schreberi contributes significantly to build-up soil organic matter, and therefore long-term C sequestration. Knowledge on P. schreberi genome will facilitate the development of ‘omics’ and system’s biology approaches to gain a more complete understanding of the physiology and ecological adaptation of the moss and the mechanisms underpinning the establishment of the symbiosis. Here we present the de novo assembly and annotation of P. schreberi genome that will help investigating these questions. The sequencing was performed using the HiSeq X platform with Illumina paired-end and mate-pair libraries prepared with CTAB extracted DNA. In total, the assembled genome was approximately 318 Mb, while repetitive elements account for 28.42% of the genome and 15,992 protein-coding genes were predicted from the genome, of which 84.23% have been functionally annotated. We anticipate that the genomic data generated will constitute a significant resource to study ecological and evolutionary genomics of P. schreberi, and will be valuable for evo-devo investigations as well as our understanding of the evolution of land plants by providing the genome of a pleurocarpous moss.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Stable calcium-free myocilin olfactomedin domain variants reveal challenges in differentiating between benign and glaucoma-causing mutations

Nonsynonymous gene mutations can be beneficial, neutral, or detrimental to the stability, structure, and biological function of the encoded protein, but the effects of these mutations are often not readily predictable. For example, the β-propeller olfactomedin domain of myocilin (mOLF) exhibits a complex interrelationship among structure(s), stability, and aggregation. Numerous mutations within mOLF are linked to glaucoma; the resulting variants are less stable, aggregation-prone, and sequestered intracellularly, causing cytotoxicity. In this study, we report the first stable mOLF variants carrying substitutions in the calcium-binding site that exhibit solution characteristics indistinguishable from those of glaucoma variants. Crystal structures of these stable variants at 1.8–2.0-Å resolution revealed features that we could not predict by molecular dynamics simulations, including loss of loop structure, helix unwinding, and a blade shift. Double mutants that combined a stabilizing substitution and a selected glaucoma-causing single-point mutant rescued in vitro folding and stability defects. In the context of full-length myocilin, secretion of stable single variants was indistinguishable from that of the WT protein, and the double mutants were secreted to varying extents. In summary, our finding that mOLF can tolerate particular substitutions that render the protein stable despite a conformational switch emphasizes the complexities in differentiating between benign and glaucoma-causing variants and provides new insight into the possible biological function of myocilin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Thousands of small, novel genes predicted in global phage genomes

Small genes (<150nucleotides) have been systematically overlooked in phage genomes. We employ a large scale comparative genomics approach to predict >40,000 small-gene families in 2.3 million phage genome contigs. We find that small genes in phage genomes are approximately 3-fold more prevalent than in host prokaryotic genomes. Our approach enriches for small genes that are translated in microbiomes, suggesting the small genes identified are coding. More than 9,000 families encode potentially secreted or transmembrane proteins, more than 5,000families encode predicted anti-CRISPR proteins, and more than500families encode predicted antimicrobial proteins. By combining homology and genomic-neighborhood analyses, we reveal substantial novelty and diversity within phage biology, including small phage genes found in multiple host phyla, small genes encoding proteins that play essential roles in host infection, and small genes that share genomic neighborhoods and whose encoded proteins may share related functions.

Fremin, Brayon↗
DOE OSTI2015

A bioinformatics prediction approach towards analyzing the glycosylation, co-expression and interaction patterns of epithelial membrane antigen (EMA/MUC1)

Epithelial membrane antigen (EMA or MUC1) is a heavily glycosylated, type I transmembrane glycoprotein commonly expressed by epithelial cells of duct organs. It has been shown to be aberrantly glycosylated in several diseases including cancer. Protein sequence based annotation and analysis of glycosylation profile of glycoproteins by robust computational and comprehensive algorithms provides possible insights to the mechanism(s) of anomalous glycosylation. In present report, by using a number of bioinformatics applications we studied EMA/MUC1 and explored its trans-membrane structural domain sequence that is widely subjected to glycosylation. Exploration of different extracellular motifs led to prediction of N and O-linked glycosylation target sites. Based on the putative O-linked target sites, glycosylated moieties and pathways were envisaged. Furthermore, Protein network analysis demonstrated physical interaction of EMA with a number of proteins and confirmed its functional involvement in cell growth and proliferation pathways. Gene Ontology analysis suggested an involvement of EMA in a number of functions including signal transduction, protein binding, processing and transport along with glycosylation. Thus, present study explored potential of bioinformatics prediction approach in analyzing glycosylation, co-expression and interaction patterns of EMA/MUC1 glycoprotein.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Predicting the viability of beta-lactamase: How folding and binding free energies correlate with beta-lactamase fitness

One of the long-standing holy grails of molecular evolution has been the ability to predict an organism’s fitness directly from its genotype. With such predictive abilities in hand, researchers would be able to more accurately forecast how organisms will evolve and how proteins with novel functions could be engineered, leading to revolutionary advances in medicine and biotechnology. In this work, we assemble the largest reported set of experimental TEM-1 β-lactamase folding free energies and use this data in conjunction with previously acquired fitness data and computational free energy predictions to determine how much of the fitness of β-lactamase can be directly predicted by thermodynamic folding and binding free energies. We focus upon β-lactamase because of its long history as a model enzyme and its central role in antibiotic resistance. Based upon a set of 21 β-lactamase single and double mutants expressly designed to influence protein folding, we first demonstrate that modeling software designed to compute folding free energies such as FoldX and PyRosetta can meaningfully, although not perfectly, predict the experimental folding free energies of single mutants. Interestingly, while these techniques also yield sensible double mutant free energies, we show that they do so for the wrong physical reasons. We then go on to assess how well both experimental and computational folding free energies explain single mutant fitness. We find that folding free energies account for, at most, 24% of the variance in β-lactamase fitness values according to linear models and, somewhat surprisingly, complementing folding free energies with computationally-predicted binding free energies of residues near the active site only increases the folding-only figure by a few percent. This strongly suggests that the majority of β-lactamase’s fitness is controlled by factors other than free energies. Overall, our results shed a bright light on to what extent the community is justified in using thermodynamic measures to infer protein fitness as well as how applicable modern computational techniques for predicting free energies will be to the large data sets of multiply-mutated proteins forthcoming.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Predicting variable gene content in Escherichia coli using conserved genes

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%–90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943–0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including “hypothetical proteins” was accurately predicted (F1 = 0.902 [0.898–0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876–0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Binding Affinity Prediction by Pairwise Function Based on Neural Network

In this paper, we present a new approach to estimate the binding affinity from given three-dimensional poses of protein–ligand complexes. In this scheme, every protein–ligand atom pair makes an additive free-energy contribution. The sum of these pairwise contributions then gives the total binding free energy or the logarithm of the dissociation constant. The pairwise contribution is calculated by a function implemented via a neural network that takes the properties of the two atoms and their distance as input. The pairwise function is trained using a portion of the PDBbind 2018 data set. The model achieves good accuracy for affinity predictions when evaluated with PDBbind 2018 and with the CASF-2016 benchmark, comparing favorably to many scoring functions such as that of AutoDock Vina. The framework here may be extended to incorporate other factors to further improve its accuracy and power.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Prediction of bacterial E3 ubiquitin ligase effectors using reduced amino acid peptide fingerprinting

Background Although pathogenic Gram-negative bacteria lack their own ubiquitination machinery, they have evolved or acquired virulence effectors that can manipulate the host ubiquitination process through structural and/or functional mimicry of host machinery. Many such effectors have been identified in a wide variety of bacterial pathogens that share little sequence similarity amongst themselves or with eukaryotic ubiquitin E3 ligases. Methods To allow identification of novel bacterial E3 ubiquitin ligase effectors from protein sequences we have developed a machine learning approach, the SVM-based Identification and Evaluation of Virulence Effector Ubiquitin ligases (SIEVE-Ub). We extend the string kernel approach used previously to sequence classification by introducing reduced amino acid (RED) alphabet encoding for protein sequences. Results We found that 14mer peptides with amino acids represented as simply either hydrophobic or hydrophilic provided the best models for discrimination of E3 ligases from other effector proteins with a receiver-operator characteristic area under the curve (AUC) of 0.90. When considering a subset of E3 ubiquitin ligase effectors that do not fall into known sequence based families we found that the AUC was 0.82, demonstrating the effectiveness of our method at identifying novel functional family members. Feature selection was used to identify a parsimonious set of 10 RED peptides that provided good discrimination, and these peptides were found to be located in functionally important regions of the proteins involved in E2 and host target protein binding. Our general approach enables construction of models based on other effector functions. We used SIEVE-Ub to predict nine potential novel E3 ligases from a large set of bacterial genomes. SIEVE-Ub is available for download at https://doi.org/10.6084/m9.figshare.7766984.v1 or https://github.com/biodataganache/SIEVE-Ub for the most current version.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Structural Insights into Separase Architecture and Substrate Recognition through Computational Modelling of Caspase-Like and Death Domains

Separases are large proteins that mediate sister chromatid disjunction in all eukaryotes. They belong to clan CD of cysteine peptidases and contain a well-conserved C-terminal catalytic protease domain similar to caspases and gingipains. However, unlike other well-characterized groups of clan CD peptidases, there are no high-resolution structures of separases and the details of their regulation and substrate recognition are poorly understood. Here we undertook an in-depth bioinformatical analysis of separases from different species with respect to their similarity in amino acid sequence and protein fold in comparison to caspases, MALT-1 proteins (mucosa-associated lymphoidtissue lymphoma translocation protein 1) and gingipain-R. A comparative model of the single C-terminal caspase-like domain in separase from C. elegans suggests similar binding modes of substrate peptides between these protein subfamilies, and enables differences in substrate specificity of separase proteins to be rationalised. We also modelled a newly identified putative death domain, located N-terminal to the caspase-like domain. The surface features of this domain identify potential sites of protein-protein interactions. Notably, we identified a novel conserved region with the consensus sequence WWxxRxxLD predicted to be exposed on the surface of the death domain, which we termed the WR motif. We envisage that findings from our study will guide structural and functional studies of this important protein family.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Mouse IgG2c Fc loop residues promote greater receptor-binding affinity than mouse IgG2b or human IgG1

The structures of non-human antibodies are largely unstudied despite the potential for the identification of alternative structural motifs and physical properties that will benefit a basic understanding of protein and immune system evolution as well as highlight unexplored motifs to improve therapeutic monoclonal antibody. Here we probe the structure and receptor-binding properties of the mouse IgG2c crystallizable fragment (Fc) to compare to mouse IgG2b and human IgG1 Fcs. Models of mIgG2c Fc determined by x-ray crystallography with a complex-type biantennary (to 2.05 Å) or a truncated (1)GlcNAc asparagine-linked (N)-glycan attached (to 2.04 Å) show differences in key regions related to mouse Fc γ receptor IV (mFcγRIV) binding. Mouse IgG2c forms different non-bonded interactions between the BC, DE and FG loops than the highly-conserved mIgG2b and binds to FcγRIV with 4.7-fold greater affinity in the complex-type glycoform. Secondary structural elements surrounding the Asn297 site of glycosylation form longer beta strands in the truncated mIgG2c Fc glycoform when compared to mIgG2c with the complex-type N-glycan. Solution NMR spectroscopy of the N-linked (1)GlcNAc residues show differences between mIgG2b, 2c and hIgG1 Fc that correlate to receptor binding affinity. Mutations targeting differences in mIgG2 DE and FG loops decreased affinity of mIgG2c for FcγRIV and increased affinity of mIgG2b. Changes in NMR spectra of the mutant Fc proteins mirrored these changes in affinity. Our studies identified structural and functional differences in highly conserved molecules that were not predicted from primary sequence comparison.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Live Cell Discovery of Microbial Vitamin Transport and Enzyme-Cofactor Interactions

The rapid completion of microbial genomes is inducing a conundrum in functional gene discovery. Novel methods are critically needed to shorten the gap between characterizing a microbial genome and experimentally validating bioinformatically-predicted functions. Of particular importance are transport mechanisms, used to shuttle nutrients and metabolites across cell mem-branes, such as B vitamins, which are indispensable to metabolic reactions crucial to the survival of diverse microbes ranging from members of environmental microbial communities to human pathogens. Methods to accurately assign function and specificity for a wide range of experimentally unidentified and/or predicted membrane-embedded transport proteins, and characterization of intra-cellular enzyme-cofactor/nutrient associations are needed to enable a significantly improved understanding of microbial biochemis-try and physiology, how microbes associate with others, and how they sense and respond to environmental perturbations. Chemical probes derived from B vitamins B1, B2, and B7 have allowed us to experimentally address the aforementioned needs by identifying B vitamin transporters and intracellular protein-cofactor associations through live cell labeling of the filamentous anoxygenic pho-toheterotroph, Chloroflexus aurantiacus J-10-fl, known for both B vitamin biosynthesis and environmental salvage. Our probes provide a unique opportunity to directly link cellular activity and protein function back to ecosystem and/or host dynamics by iden-tifying B vitamin transport and disposition mechanisms required for survival.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2023

Unraveling the functional dark matter through global metagenomics

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Metal affinity enrichment increases the range and depth of proteome identification for extracellular microbial proteins

Many key proteins, such as those involved in cellular signaling or transcription, are difficult to measure in microbial proteomic experiments due to the interfering presence of more abundant, dominant proteins. In an effort to enhance the identification of previously undetected proteins, as well as provide a methodology for selective enrichment, we evaluated and optimized immobilized metal affinity chromatography (IMAC) coupled with mass spectrometric characterization of extracellular proteins from an extremophilic microbial community. Seven different metals were tested for IMAC enrichment. The combined results added 20% greater proteomic depth to the extracellular proteome. Although this IMAC enrichment could not be conducted at the physiological pH of the environmental system, this approach did yield a reproducible and specific enrichment of groups of proteins with functions potentially vital to the community, thereby providing a more extensive biochemical characterization. Notably, 40 unknown proteins previously annotated as hypothetical were enriched and identified for the first time. Examples of identified proteins includes a predicted TonB signal sensing protein homologous to other known TonB proteins and a protein with a COXG domain previously identified in many chemolithoautotrophic microbes as having a function in the oxidation of CO.

Wheeler, Korin↗
DOE OSTI2021

Bioinformatic and Mechanistic Analysis of the Palmerolide PKS-NRPS Biosynthetic Pathway From the Microbiome of an Antarctic Ascidian

Complex interactions exist between microbiomes and their hosts. Increasingly, defensive metabolites that have been attributed to host biosynthetic capability are now being recognized as products of host-associated microbes. These unique metabolites often have bioactivity targets in human disease and can be purposed as pharmaceuticals. Polyketides are a complex family of natural products that often serve as defensive metabolites for competitive or pro-survival purposes for the producing organism, while demonstrating bioactivity in human diseases as cholesterol lowering agents, anti-infectives, and anti-tumor agents. Marine invertebrates and microbes are a rich source of polyketides. Palmerolide A, a polyketide isolated from the Antarctic ascidian Synoicum adareanum, is a vacuolar-ATPase inhibitor with potent bioactivity against melanoma cell lines. The biosynthetic gene clusters (BGCs) responsible for production of secondary metabolites are encoded in the genomes of the producers as discrete genomic elements. A candidate palmerolide BGC was identified from a S. adareanum microbiome-metagenome based on a high degree of congruence with a chemical structure-based retrobiosynthetic prediction. Protein family homology analysis, conserved domain searches, active site and motif identification were used to identify and propose the function of the ~75 kbp trans-acyltransferase (AT) polyketide synthase-non-ribosomal synthase (PKS-NRPS) domains responsible for the stepwise synthesis of palmerolide A. Though PKS systems often act in a predictable co-linear sequence, this BGC includes multiple trans-acting enzymatic domains, a non-canonical condensation termination domain, a bacterial luciferase-like monooxygenase (LLM), and is found in multiple copies within the metagenome-assembled genome (MAG). Detailed inspection of the five highly similar pal BGC copies suggests the potential for biosynthesis of other members of the palmerolide chemical family. This is the first delineation of a biosynthetic gene cluster from an Antarctic microbial species, recently proposed as Candidatus Synoicihabitans palmerolidicus. These findings have relevance for fundamental knowledge of PKS combinatorial biosynthesis and could enhance drug development efforts of palmerolide A through heterologous gene expression.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Insight into different environmental niches adaptation and allergenicity from the Cladosporium sphaerospermum genome, a common human allergy-eliciting Dothideomycetes

Cladosporium sphaerospermum, a dematiaceous saprophytic fungus commonly found in diverse environments, has been reported to cause allergy and other occasional diseases in humans. However, its basic biology and genetic information are largely unexplored. A clinical isolate C. sphaerospermum genome, UM 843, was re-sequenced and combined with previously generated sequences to form a model 26.89 Mb genome containing 9,652 predicted genes. Functional annotation on predicted genes suggests the ability of this fungus to degrade carbohydrate and protein complexes. Several putative peptidases responsible for lung tissue hydrolysis were identified. These genes shared high similarity with the Aspergillus peptidases. The UM 843 genome encodes a wide array of proteins involved in the biosynthesis of melanin, siderophores, cladosins and survival in high salinity environment. In addition, a total of 28 genes were predicted to be associated with allergy. Orthologous gene analysis together with 22 other Dothideomycetes showed genes uniquely present in UM 843 that encode four class 1 hydrophobins which may be allergens specific to Cladosporium. The mRNA of these hydrophobins were detected by RT-PCR. The genomic analysis of UM 843 contributes to the understanding of the biology and allergenicity of this widely-prevalent species.

59 BASIC BIOLOGICAL SCIENCES↗