The InterPro protein families database: the classification resource after 15 years

Pathways of Iron and Sulfur Acquisition, Cofactor Assembly, Destination, and Storage in Diverse Archaeal Methanogens and Alkanotrophs

Archaeal methanogens, methanotrophs, and alkanotrophs have a high demand for iron (Fe) and sulfur (S); however, little is known of how they acquire, traffic, deploy, and store these elements. Here, we examined the distribution of homologs of proteins mediating key steps in Fe/S metabolism in model microorganisms, including iron(II) sensing/uptake (FeoAB), sulfide extraction from cysteine (SufS), and the biosynthesis of iron-sulfur [Fe-S] clusters (SufBCDE), siroheme (Pch2 dehydrogenase), protoheme (AhbABCD), cytochrome c (Cyt c) (CcmCF), and iron storage/detoxification (Bfr, FtrA, and IssA), among 326 publicly available, complete or metagenome-assembled genomes of archaeal methanogens/methanotrophs/alkanotrophs. The results indicate several prevalent but nonuniversal features, including FeoB, SufBC, and the biosynthetic apparatus for the basic tetrapyrrole scaffold, as well as its siroheme (and F₄₃₀) derivatives. However, several early-diverging genomes lacked SufS and pathways to synthesize and deploy heme. Genomes encoding complete versus incomplete heme biosynthetic pathways exhibited equivalent prevalences of [Fe-S] cluster binding proteins, suggesting an expansion of catalytic capabilities rather than substitution of heme for [Fe-S] in the former group. Several strains with heme binding proteins lacked heme biosynthesis capabilities, while other strains with siroheme biosynthesis capability lacked homologs of known siroheme binding proteins, indicating heme auxotrophy and unknown siroheme biochemistry, respectively. While ferritin proteins involved in ferric oxide storage were widespread, those involved in storing Fe as thioferrate were unevenly distributed. Collectively, the results suggest that differences in the mechanisms of Fe and S acquisition, deployment, and storage have accompanied the diversification of methanogens/methanotrophs/alkanotrophs, possibly in response to differential availability of these elements as these organisms evolved.

IMPORTANCE Archaeal methanogens, methanotrophs, and alkanotrophs, argued to be among the most ancient forms of life, have a high demand for iron (Fe) and sulfur (S) for cofactor biosynthesis, among other uses. Here, using comparative bioinformatic approaches applied to 326 genomes, we show that major differences in Fe/S acquisition, trafficking, deployment, and storage exist in this group. Variation in these characters was generally congruent with the phylogenetic placement of these genomes, indicating that variation in Fe/S usage and deployment has contributed to the diversification and ecology of these organisms. However, incongruency was observed among the distribution of cofactor biosynthesis pathways and known protein destinations for those cofactors, suggesting auxotrophy or yet-to-be-discovered pathways for cofactor biosynthesis.

Maple syrup urine disease: Characteristics of diagnosis and treatment in 45 patients in Chile

Maple urine syrup disease (MSUD) is an autosomal recessive disorder characterized by deficient activity of the branched-chain alpha ketoacid dehydrogenase (BCKAD) enzymatic complex due to biallelic variants in the alpha (BCKDHA) or beta (BCKDHB) subunits or the acyltransferase component (DBT). Treatment consists in leucine (LEU), isoleucine (ILE), and valine (VAL) (branched-chain amino acids) dietary restriction and strict metabolic control. to determine the characteristics of the Chilean cohort with MSUD currently in follow-up at Instituto de Nutrición y Tecnología de los Alimentos, during the 1990-2017 period Retrospective analytical study in 45 MSUD cases. Measured: biochemical parameters (LEU, ILE, and VAL), anthropometric evaluation, and neurocognitive development. In 18 cases undergoing genetic study were analyzed according to the gene and protein location, number of affected alleles, and type of posttranslational modification affected. Then, 45 patients with MSUD diagnosis were identified during the period: 37 were alive at the time of the study. Average diagnosis age was 71 ± 231 days. Average serum diagnosis LEU concentrations: 1.463 ± 854.1 μmol/L, VAL 550 ± 598 μmol/L and ILE 454 ± 458 μmol/L. BCKDHB variants explain 89% cases, while BCKDHA and DBT variants explain 5.5% of cases each. Variants p.Thr338Ile in BCKDHA, p.Pro240Thr and p.Ser342Asn in BCKDHB have not been previously reported in literature. Average serum follow-up LEU concentrations were 252.7 ± 16.9 μmol/L in the <5 years group and 299 ± 123.2 μmol/L in ≥5 years. Most cases presented some degree of developmental delay. Early diagnosis and treatment is essential to improve the long-term prognosis. Frequent blood LEU measurements are required to optimize metabolic control and to establish relationships between different aspects analyzed.

Disease gene prediction with privileged information and heteroscedastic dropout

Motivation

Recently, machine learning models have achieved tremendous success in prioritizing candidate genes for genetic diseases. These models are able to accurately quantify the similarity among disease and genes based on the intuition that similar genes are more likely to be associated with similar diseases. However, the genetic features these methods rely on are often hard to collect due to high experimental cost and various other technical limitations. Existing solutions of this problem significantly increase the risk of overfitting and decrease the generalizability of the models.

Results

In this work, we propose a graph neural network (GNN) version of the Learning under Privileged Information paradigm to predict new disease gene associations. Unlike previous gene prioritization approaches, our model does not require the genetic features to be the same at training and test stages. If a genetic feature is hard to measure and therefore missing at the test stage, our model could still efficiently incorporate its information during the training process. To implement this, we develop a Heteroscedastic Gaussian Dropout algorithm, where the dropout probability of the GNN model is determined by another GNN model with a mirrored GNN architecture. To evaluate our method, we compared our method with four state-of-the-art methods on the Online Mendelian Inheritance in Man dataset to prioritize candidate disease genes. Extensive evaluations show that our model could improve the prediction accuracy when all the features are available compared to other methods. More importantly, our model could make very accurate predictions when >90% of the features are missing at the test stage.

Availability and implementation

Our method is realized with Python 3.7 and Pytorch 1.5.0 and method and data are freely available at: https://github.com/juanshu30/Disease-Gene-Prioritization-with-Privileged-Information-and-Heteroscedastic-Dropout.

Pleiotropic roles of Ras GTPases in the nematode-trapping fungus Arthrobotrys oligospora identified through multi-omics analyses

The nematode-trapping fungi are ideal agents for controlling pathogenic nematodes. Arthrobotrys oligospora is a representative species of the same, producing traps for nematode predation. Here, three orthologous Ras GTPases (Ras2, Ras3, and Rheb) were characterized in A. oligospora. Our results indicate that they play pleiotropic roles in regulating the mycelial growth, conidiation, stress resistance, and pathogenicity of A. oligospora. Furthermore, deletion of Aoras2 and Aorheb significantly affected the mitochondrial activity, reactive oxygen species levels, lipid storage, and autophagy. Transcriptome analyses of ΔAoras2 mutant revealed that many repressed genes were associated with signal transduction, energy production, and carbohydrate transport and metabolism. Moreover, metabolic profile analyses showed that AoRas2 and AoRheb affect the biosynthesis of secondary metabolites in A. oligospora. Collectively, these findings provide an in-depth insight into the essential roles of Ras GTPases in vegetative growth, development, and pathogenicity and highlight their importance in the lifestyle switch of the nematode-trapping fungi.

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Ras GTPases play a multifunctional role in the lifestyle switch of A. oligospora

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Ras GTPases affect multiple cellular processes, including mitochondrial activity

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AoRas2 plays a key role in regulating global gene expression and nematode predation

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AoRas2 and AoRheb significantly affect the biosynthesis of secondary metabolites

MyCLADE: a multi-source domain annotation server for sequence functional exploration

The ever-increasing number of genomic and metagenomic sequences accumulating in our databases requires accurate approaches to explore their content against specific domain targets. MyCLADE is a user-friendly webserver designed for targeted functional profiling of genomic and metagenomic sequences based on a database of a few million probabilistic models of Pfam domains. It uses the MetaCLADE multi-source domain annotation strategy, modelling domains based on multiple probabilistic profiles. MyCLADE takes a list of protein sequences and possibly a target set of domains/clans as input and, for each sequence, it provides a domain architecture built from the targeted domains or from all Pfam domains. It is linked to the Pfam and QuickGO databases in multiple ways for easy retrieval of domain and clan information. E-value, bit-score, domain-dependent probability scores and logos representing the match of the model with the sequence are provided to help the user to assess the quality of each annotation. Availability and implementation: MyCLADE is freely available at http://www.lcqb.upmc.fr/myclade.

Chromosome-Scale Genome Assembly of the Resurrection Plant Acanthochlamys bracteata (Velloziaceae)

Acanthochlamys bracteata (Velloziaceae) is a resurrection plant with cold tolerance. Herein, a chromosome-level reference genome of A. bracteata based on Nanopore, Illumina, and Hi-C data is reported. The high-quality assembled genome was 197.97 Mb, with a scaffold N50 value of 8.64 Mb and a contig N50 value of 6.96 Mb. We annotated 23,509 protein-coding genes. Eight contracted gene families and three expanded gene families were detected. Repeat sequences accounted for approximately 28.63% of the genome. The LEA1 and Dehydrin gene families, which are involved in desiccation resistance, expanded in A. bracteata. We identified genes involved in chilling tolerance, COLD1.

Computational identification of putative common genomic drug and vaccine targets in Mycoplasma genitalium

Mycoplasma genitalium is an obligate intracellular bacterium that is responsible for several sexually transmitted infections, including non-gonococcal urethritis in men and several inflammatory reproductive tract syndromes in women. Here, we applied subtractive genomics and reverse vaccinology approaches for in silico prediction of potential vaccine and drug targets against five strains of M. genitalium. We identified 403 genes shared by all five strains, from which 104 non-host homologous proteins were selected, comprising of 44 exposed/secreted/membrane proteins and 60 cytoplasmic proteins. Based on the essentiality, functionality, and structure-based binding affinity, we finally predicted 19 (14 novel) putative vaccine and 7 (2 novel) candidate drug targets. The docking analysis showed six molecules from the ZINC database as promising drug candidates against the identified targets. Altogether, both vaccine candidates and drug targets identified here may contribute to the future development of therapeutic strategies to control the spread of M. genitalium worldwide.

Carbamoyl Phosphate Synthase Subunit CgCPS1 Is Necessary for Virulence and to Regulate Stress Tolerance in Colletotrichum gloeosporioides

Glomerella leaf spot (GLS) is a severe infectious disease of apple whose infective area is growing gradually and thus poses a huge economic threat to the world. Different species of Colletotrichum including Colletotrichum gloeosporioides are responsible for GLS. For efficient GLS control, it is important to understand the mechanism by which the cruciferous crops and C. gloeosporioides interact. Arginine is among one of the several types of amino acids, which plays crucial role in biochemical and physiological functions of fungi. The arginine biosynthesis pathway involved in virulence among plant pathogenic fungi is poorly understood. In this study, CgCPS1 gene encoding carbamoyl phosphate synthase involved in arginine biosynthesis has been identified and inactivated experimentally. To assess the effects of CgCPS1, we knocked out CgCPS1 in C. gloeosporioides and evaluated its effects on virulence and stress tolerance. The results showed that deletion of CgCPS1 resulted in loss of pathogenicity. The Δcgcps1 mutants showed slow growth rate, defects in appressorium formation and failed to develop lesions on apple leaves and fruits leading to loss of virulence while complementation strain (CgCPS1-C) fully restored its pathogenicity. Furthermore, mutant strains showed extreme sensitivity to high osmotic stress displaying that CgCPS1 plays a vital role in stress response. These findings suggest that CgCPS1 is major factor that mediates pathogenicity in C. gloeosporioides by encoding carbamoyl phosphate that is involved in arginine biosynthesis and conferring virulence in C. gloeosporioides.

A Peek into the Plasmidome of Global Sewage

Plasmids can provide a selective advantage for microorganisms to survive and adapt to new environmental conditions. Plasmid-encoded traits, such as antimicrobial resistance (AMR) or virulence, impact the ecology and evolution of bacteria and can significantly influence the burden of infectious diseases. Insight about the identity and functions encoded on plasmids on the global scale are largely lacking. Here, we investigate the plasmidome of 24 samples (22 countries, 5 continents) from the global sewage surveillance project. We obtained 105-Gbp Oxford Nanopore and 167-Gbp Illumina NextSeq DNA sequences from plasmid DNA preparations and assembled 165,302 contigs (159,322 circular). Of these, 58,429 carried genes encoding for plasmid-related and 11,222 for virus/phage-related proteins. About 90% of the circular DNA elements did not have any similarity to known plasmids. Those that exhibited similarity had similarity to plasmids whose hosts were previously detected in these sewage samples (e.g., Acinetobacter, Escherichia, Moraxella, Enterobacter, Bacteroides, and Klebsiella). Some AMR classes were detected at a higher abundance in plasmidomes (e.g., macrolide-lincosamide-streptogramin B, macrolide, and quinolone) compared to the respective complex sewage samples. In addition to AMR genes, a range of functions were encoded on the candidate plasmids, including plasmid replication and maintenance, mobilization, and conjugation. In summary, we describe a laboratory and bioinformatics workflow for the recovery of plasmids and other potential extrachromosomal DNA elements from complex microbiomes. Moreover, the obtained data could provide further valuable insight into the ecology and evolution of microbiomes, knowledge about AMR transmission, and the discovery of novel functions.

IMPORTANCE This is, to the best of our knowledge, the first study to investigate plasmidomes at a global scale using long read sequencing from complex untreated domestic sewage. Previous metagenomic surveys have detected AMR genes in a variety of environments, including sewage. However, it is unknown whether the AMR genes were present on the microbial chromosome or located on extrachromosomal elements, such as plasmids. Using our approach, we recovered a large number of plasmids, of which most appear novel. We identified distinct AMR genes that were preferentially located on plasmids, potentially contributing to their transmissibility. Overall, plasmids are of great importance for the biology of microorganisms in their natural environments (free-living and host-associated), as well as for molecular biology and biotechnology. Plasmidome collections may therefore be valuable resources for the discovery of fundamental biological mechanisms and novel functions useful in a variety of contexts.

Transcriptome differences between Cupriavidus necator NH9 grown with 3-chlorobenzoate and that grown with benzoate

RNA-seq analysis of Cupriavidus necator NH9, a 3-chlorobenzoate degradative bacterium, cultured with 3-chlorobenzaote and benzoate, revealed strong induction of genes encoding enzymes in degradation pathways of the respective compound, including the genes to convert 3-chlorobenzaote and benzoate to chlorocatechol and catechol, respectively, and the genes of chlorocatechol ortho-cleavage pathway for conversion to central metabolites. The genes encoding transporters, components of the stress response, flagellar proteins, and chemotaxis proteins showed altered expression patterns between 3-chlorobenzoate and benzoate. Gene Ontology enrichment analysis revealed that chemotaxis-related terms were significantly upregulated by benzoate compared with 3-chlorobenzoate. Consistent with this, in semisolid agar plate assays, NH9 cells showed stronger chemotaxis to benzoate than to 3-chlorobenzoate. These results, combined with the absence of genes related to uptake/chemotaxis for 3-chlorobenzoate located closely to the degradation genes of 3-chlorobenzoate, suggested that NH9 has not fully adapted to the utilization of chlorinated benzoate, unlike benzoate, in nature.

Predicting phosphorylation sites using machine learning by integrating the sequence, structure, and functional information of proteins

BACKGROUND

Post-translational modification (PTM) is a biological process that alters proteins and is therefore involved in the regulation of various cellular activities and pathogenesis. Protein phosphorylation is an essential process and one of the most-studied PTMs: it occurs when a phosphate group is added to serine (Ser, S), threonine (Thr, T), or tyrosine (Tyr, Y) residue. Dysregulation of protein phosphorylation can lead to various diseases-most commonly neurological disorders, Alzheimer's disease, and Parkinson's disease-thus necessitating the prediction of S/T/Y residues that can be phosphorylated in an uncharacterized amino acid sequence. Despite a surplus of sequencing data, current experimental methods of PTM prediction are time-consuming, costly, and error-prone, so a number of computational methods have been proposed to replace them. However, phosphorylation prediction remains limited, owing to substrate specificity, performance, and the diversity of its features.

METHODS

In the present study we propose machine-learning-based predictors that use the physicochemical, sequence, structural, and functional information of proteins to classify S/T/Y phosphorylation sites. Rigorous feature selection, the minimum redundancy/maximum relevance approach, and the symmetrical uncertainty method were employed to extract the most informative features to train the models.

RESULTS

The RF and SVM models generated using diverse feature types in the present study were highly accurate as is evident from good values for different statistical measures. Moreover, independent test sets and benchmark validations indicated that the proposed method clearly outperformed the existing methods, demonstrating its ability to accurately predict protein phosphorylation.

CONCLUSIONS

The results obtained in the present work indicate that the proposed computational methodology can be effectively used for predicting putative phosphorylation sites further facilitating discovery of various biological processes mechanisms.

Conserved white-rot enzymatic mechanism for wood decay in the Basidiomycota genus Pycnoporus

White-rot (WR) fungi are pivotal decomposers of dead organic matter in forest ecosystems and typically use a large array of hydrolytic and oxidative enzymes to deconstruct lignocellulose. However, the extent of lignin and cellulose degradation may vary between species and wood type. Here, we combined comparative genomics, transcriptomics and secretome proteomics to identify conserved enzymatic signatures at the onset of wood-decaying activity within the Basidiomycota genus Pycnoporus. We observed a strong conservation in the genome structures and the repertoires of protein-coding genes across the four Pycnoporus species described to date, despite the species having distinct geographic distributions. We further analysed the early response of P. cinnabarinus, P. coccineus and P. sanguineus to diverse (ligno)-cellulosic substrates. We identified a conserved set of enzymes mobilized by the three species for breaking down cellulose, hemicellulose and pectin. The co-occurrence in the exo-proteomes of H₂O₂-producing enzymes with H₂O₂-consuming enzymes was a common feature of the three species, although each enzymatic partner displayed independent transcriptional regulation. Finally, cellobiose dehydrogenase-coding genes were systematically co-regulated with at least one AA9 lytic polysaccharide monooxygenase gene, indicative of enzymatic synergy in vivo. This study highlights a conserved core white-rot fungal enzymatic mechanism behind the wood-decaying process.

The order of PDZ3 and TrpCage in fusion chimeras determines their properties-a biophysical characterization

Most of the structural proteins known today are composed of domains that carry their own functions while keeping their structural properties. It is supposed that such domains, when taken out of the context of the whole protein, can retain their original structure and function to a certain extent. Information on the specific functional and structural characteristics of individual domains in a new context of artificial fusion proteins may help to reveal the rules of internal and external domain communication. Moreover, this could also help explain the mechanism of such communication and address how the mutual allosteric effect plays a role in a such multi-domain protein system. The simple model system of the two-domain fusion protein investigated in this work consisted of a well-folded PDZ3 domain and an artificially designed small protein domain called Tryptophan Cage (TrpCage). Two fusion proteins with swapped domain order were designed to study their structural and functional features as well as their biophysical properties. The proteins composed of PDZ3 and TrpCage, both identical in amino acid sequence but different in composition (PDZ3-TrpCage, TrpCage-PDZ3), were studied using circualr dichroism (CD) spectrometry, analytical ultracentrifugation, and molecular dynamic simulations. The biophysical analysis uncovered different structural and denaturation properties of both studied proteins, revealing their different unfolding pathways and dynamics.

Graph Convolutional Autoencoder and Fully-Connected Autoencoder with Attention Mechanism Based Method for Predicting Drug-Disease Associations

Predicting novel uses for approved drugs helps in reducing the costs of drug development and facilitates the development process. Most of previous methods focused on the multi-source data related to drugs and diseases to predict the candidate associations between drugs and diseases. There are multiple kinds of similarities between drugs, and these similarities reflect how similar two drugs are from the different views, whereas most of the previous methods failed to deeply integrate these similarities. In addition, the topology structures of the multiple drug-disease heterogeneous networks constructed by using the different kinds of drug similarities are not fully exploited. We therefore propose GFPred, a method based on a graph convolutional autoencoder and a fully-connected autoencoder with an attention mechanism, to predict drug-related diseases. GFPred integrates drug-disease associations, disease similarities, three kinds of drug similarities and attributes of the drug nodes. Three drug-disease heterogeneous networks are constructed based on the different kinds of drug similarities. We construct a graph convolutional autoencoder module, and integrate the attributes of the drug and disease nodes in each network to learn the topology representations of each drug node and disease node. As the different kinds of drug attributes contribute differently to the prediction of drug-disease associations, we construct an attribute-level attention mechanism. A fully-connected autoencoder module is established to learn the attribute representations of the drug and disease nodes. Finally, the original features of the drug-disease node pairs are also important auxiliary information for their association prediction. A combined strategy based on a convolutional neural network is proposed to fully integrate the topology representations, the attribute representations, and the original features of the drug-disease pairs. The ablation studies showed the contributions of data related to three types of drug attributes. Comparison with other methods confirmed that GFPred achieved better performance than several state-of-the-art prediction methods. In particular, case studies confirmed that GFPred is able to retrieve more actual drug-disease associations in the top k part of the prediction results. It is helpful for biologists to discover real associations by wet-lab experiments.

Protein analysis and stability: Overcoming trial-and-error by grouping according to physicochemical properties

Today proteins are possibly the most important class of substances. Yet new tasks for proteins are still often solved by trial-and-error approaches. However, in some areas these euphemistically called "screening approaches" are not suitable. E.g. stability tests just take too long and therefore require a more strategic, target-orientated concept. This concept is available by grouping proteins according to their physicochemical properties and then pulling out the right drawer for new tasks. These properties include size, then charge and hydrophobicity as well as their patchinesses, and the degree of order. In addition, solubility, the content of (free) enthalpy, aromatic-amino-acid- and α/β-frequency as well as helix capping, and corresponding patchiness, the number of specific motifs and domains as well as the typical concentration range can be helpful to discriminate between different groups of proteins. Analyzing correlations will reduce the necessary amount of parameters and additional ones, which may be still undiscovered at the present time, can be identified looking at protein subgroups with similar physicochemical properties which still behave heterogeneously. Step-by-step the methodology will be improved. Possibly protein stability will be the driver of this process, but all other areas such as production, purification and analytics including sample pre-treatment and the choice of appropriate separation conditions for e.g. chromatography and electrophoresis will profit from a rational strategy.

Gene Coexpression Network Reveals Highly Conserved, Well-Regulated Anti-Ageing Mechanisms in Old Ant Queens

Evolutionary theories of ageing predict a reduction in selection efficiency with age, a so-called “selection shadow,” due to extrinsic mortality decreasing effective population size with age. Classic symptoms of ageing include a deterioration in transcriptional regulation and protein homeostasis. Understanding how ant queens defy the trade-off between fecundity and lifespan remains a major challenge for the evolutionary theory of ageing. It has often been discussed that the low extrinsic mortality of ant queens, that are generally well protected within the nest by workers and soldiers, should reduce the selection shadow acting on old queens. We tested this by comparing strength of selection acting on genes upregulated in young and old queens of the ant, Cardiocondyla obscurior. In support of a reduced selection shadow, we find old-biased genes to be under strong purifying selection. We also analyzed a gene coexpression network (GCN) with the aim to detect signs of ageing in the form of deteriorating regulation and proteostasis. We find no evidence for ageing. In fact, we detect higher connectivity in old queens indicating increased transcriptional regulation with age. Within the GCN, we discover five highly correlated modules that are upregulated with age. These old-biased modules regulate several antiageing mechanisms such as maintenance of proteostasis, transcriptional regulation, and stress response. We observe stronger purifying selection on central hub genes of these old-biased modules compared with young-biased modules. These results indicate a lack of transcriptional ageing in old C. obscurior queens, possibly facilitated by strong selection at old age and well-regulated antiageing mechanisms.

Genomic analysis of novel Yarrowia-like yeast symbionts associated with the carrion-feeding burying beetle Nicrophorus vespilloides

Background

Mutualistic interactions with microbes can help insects adapt to extreme environments and unusual diets. An intriguing example is the burying beetle Nicrophorus vespilloides, which feeds and reproduces on small vertebrate carcasses. Its fungal microbiome is dominated by yeasts that potentially facilitate carcass utilization by producing digestive enzymes, eliminating cadaver-associated toxic volatiles (that would otherwise attract competitors), and releasing antimicrobials to sanitize the microenvironment. Some of these yeasts are closely related to the biotechnologically important species Yarrowia lipolytica.

Results

To investigate the roles of these Yarrowia-like yeast (YLY) strains in more detail, we selected five strains from two different phylogenetic clades for third-generation sequencing and genome analysis. The first clade, represented by strain B02, has a 20-Mb genome containing ~ 6400 predicted protein-coding genes. The second clade, represented by strain C11, has a 25-Mb genome containing ~ 6300 predicted protein-coding genes, and extensive intraspecific variability within the ITS–D1/D2 rDNA region commonly used for species assignments. Phenotypic microarray analysis revealed that both YLY strains were able to utilize a diverse range of carbon and nitrogen sources (including microbial metabolites associated with putrefaction), and can grow in environments with extreme pH and salt concentrations.

Conclusions

The genomic characterization of five yeast strains isolated from N. vespilloides resulted in the identification of strains potentially representing new YLY species. Given their abundance in the beetle hindgut, and dominant growth on beetle-prepared carcasses, the analysis of these strains has revealed the genetic basis of a potential symbiotic relationship between yeasts and burying beetles that facilitates carcass digestion and preservation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07597-z.

Whole-genome resequencing of Osmanthus fragrans provides insights into flower color evolution

Osmanthus fragrans is a well-known ornamental plant that has been domesticated in China for 2500 years. More than 160 cultivars have been found during this long period of domestication, and they have subsequently been divided into four cultivar groups, including the Yingui, Jingui, Dangui, and Sijigui groups. These groups provide a set of materials to study genetic evolution and variability. Here, we constructed a reference genome of O. fragrans 'Liuyejingui' in the Jingui group and investigated its floral color traits and domestication history by resequencing a total of 122 samples, including 119 O. fragrans accessions and three other Osmanthus species, at an average sequencing depth of 15×. The population structure analysis showed that these 119 accessions formed an apparent regional cluster. The results of linkage disequilibrium (LD) decay analysis suggested that varieties with orange/red flower color in the Dangui group had undergone more artificial directional selection; these varieties had the highest LD values among the four groups, followed by the Sijigui, Jingui, and Yingui groups. Through a genome-wide association study, we further identified significant quantitative trait loci and genomic regions containing several genes, such as ethylene-responsive transcription factor 2 and Arabidopsis pseudoresponse regulator 2, that are positively associated with petal color. Moreover, we found a frameshift mutation with a 34-bp deletion in the first coding region of the carotenoid cleavage dioxygenase 4 gene. This frameshift mutation existed in at least one site on both alleles in all varieties of the Dangui group. The results from this study shed light on the genetic basis of domestication in woody plants, such as O. fragrans.

Identification of a Chlorovirus PBCV-1 Protein Involved in Degrading the Host Cell Wall during Virus Infection

Chloroviruses are unusual among viruses infecting eukaryotic organisms in that they must, like bacteriophages, penetrate a rigid cell wall to initiate infection. Chlorovirus PBCV-1 infects its host, Chlorella variabilis NC64A by specifically binding to and degrading the cell wall of the host at the point of contact by a virus-packaged enzyme(s). However, PBCV-1 does not use any of the five previously characterized virus-encoded polysaccharide degrading enzymes to digest the Chlorella host cell wall during virus entry because none of the enzymes are packaged in the virion. A search for another PBCV-1-encoded and virion-associated protein identified protein A561L. The fourth domain of A561L is a 242 amino acid C-terminal domain, named A561L^D4, with cell wall degrading activity. An A561L^D4 homolog was present in all 52 genomically sequenced chloroviruses, infecting four different algal hosts. A561L^D4 degraded the cell walls of all four chlorovirus hosts, as well as several non-host Chlorella spp. Thus, A561L^D4 was not cell-type specific. Finally, we discovered that exposure of highly purified PBCV-1 virions to A561L^D4 increased the specific infectivity of PBCV-1 from about 25–30% of the particles forming plaques to almost 50%. We attribute this increase to removal of residual host receptor that attached to newly replicated viruses in the cell lysates.

The acylfulvene alkylating agent, LP-184, retains nanomolar potency in non-small cell lung cancer carrying otherwise therapy-refractory mutations

More than 40% of non-small cell lung cancer (NSCLC) patients lack actionable targets and require non-targeted chemotherapeutics. Many become refractory to drugs due to underlying resistance-associated mutations. KEAP1 mutant NSCLCs further activate NRF2 and upregulate its client PTGR1. LP-184, a novel alkylating agent belonging to the acylfulvene class is a prodrug dependent upon PTGR1. We hypothesized that NSCLC with KEAP1 mutations would continue to remain sensitive to LP-184. LP-184 demonstrated highly potent anticancer activity both in primary NSCLC cell lines and in those originating from brain metastases of primary lung cancers. LP-184 activity correlated with PTGR1 transcript levels but was independent of mutations in key oncogenes (KRAS and KEAP1) and tumor suppressors (TP53 and STK11). LP-184 was orders of magnitude more potent in vitro than cisplatin and pemetrexed. Correlative analyses of sensitivity with cell line gene expression patterns indicated that alterations in NRF2, MET, EGFR and BRAF consistently modulated LP-184 sensitivity. These correlations were then extended to TCGA analysis of 517 lung adenocarcinoma patients, out of which 35% showed elevated PTGR1, and 40% of those further displayed statistically significant co-occurrence of KEAP1 mutations. The gene correlates of LP-184 sensitivity allow additional personalization of therapeutic options for future treatment of NSCLC.

Reverse vaccinology and subtractive genomics approaches for identifying common therapeutics against Mycobacterium leprae and Mycobacterium lepromatosis

BACKGROUND

Mycobacterium leprae and Mycobacterium lepromatosis are gram-positive bacterial pathogens and the causative agents of leprosy in humans across the world. The elimination of leprosy cannot be achieved by multidrug therapy alone, and highlights the need for new tools and drugs to prevent the emergence of new resistant strains.

METHODS

In this study, our contribution includes the prediction of vaccine targets and new putative drugs against leprosy, using reverse vaccinology and subtractive genomics. Six strains of Mycobacterium leprae and Mycobacterium lepromatosis (4 and 2 strains, respectively) were used for comparison taking Mycobacterium leprae strain TN as the reference genome. Briefly, we used a combined reverse vaccinology and subtractive genomics approach.

RESULTS

As a result, we identified 12 common putative antigenic proteins as vaccine targets and three common drug targets against Mycobacterium leprae and Mycobacterium lepromatosis. Furthermore, the docking analysis using 28 natural compounds with three drug targets was done.

CONCLUSIONS

The bis-naphthoquinone compound Diospyrin (CID 308140) obtained from indigenous plant Diospyros spp. showed the most favored binding affinity against predicted drug targets, which can be a candidate therapeutic target in the future against leprosy.

Thiocyanate and Organic Carbon Inputs Drive Convergent Selection for Specific Autotrophic Afipia and Thiobacillus Strains Within Complex Microbiomes

Thiocyanate (SCN^–) contamination threatens aquatic ecosystems and pollutes vital freshwater supplies. SCN^–-degrading microbial consortia are commercially adapted for remediation, but the impact of organic amendments on selection within SCN^–-degrading microbial communities has not been investigated. Here, we tested whether specific strains capable of degrading SCN^– could be reproducibly selected for based on SCN^– loading and the presence or absence of added organic carbon. Complex microbial communities derived from those used to treat SCN^–-contaminated water were exposed to systematically increased input SCN concentrations in molasses-amended and -unamended reactors and in reactors switched to unamended conditions after establishing the active SCN^–-degrading consortium. Five experiments were conducted over 790 days, and genome-resolved metagenomics was used to resolve community composition at the strain level. A single Thiobacillus strain proliferated in all reactors at high loadings. Despite the presence of many Rhizobiales strains, a single Afipia variant dominated the molasses-free reactor at moderately high loadings. This strain is predicted to break down SCN^– using a novel thiocyanate desulfurase, oxidize resulting reduced sulfur, degrade product cyanate to ammonia and CO₂ via cyanate hydratase, and fix CO₂ via the Calvin–Benson–Bassham cycle. Removal of molasses from input feed solutions reproducibly led to dominance of this strain. Although sustained by autotrophy, reactors without molasses did not stably degrade SCN^– at high loading rates, perhaps due to loss of biofilm-associated niche diversity. Overall, convergence in environmental conditions led to convergence in the strain composition, although reactor history also impacted the trajectory of community compositional change.

Mycobacterial STAND adenylyl cyclases: The HTH domain binds DNA to form biocrystallized nucleoids

Mycobacteria harbor a unique class of adenylyl cyclases with a complex domain organization consisting of an N-terminal putative adenylyl cyclase domain fused to a nucleotide-binding adaptor shared by apoptotic protease-activating factor-1, plant resistance proteins, and CED-4 (NB-ARC) domain, a tetratricopeptide repeat (TPR) domain, and a C-terminal helix-turn-helix (HTH) domain. The products of the rv0891c-rv0890c genes represent a split gene pair, where Rv0891c has sequence similarity to adenylyl cyclases, and Rv0890c harbors the NB-ARC-TPR-HTH domains. Rv0891c had very low adenylyl cyclase activity so it could represent a pseudoenzyme. By analyzing the genomic locus, we could express and purify Rv0890c and find that the NB-ARC domain binds ATP and ADP, but does not hydrolyze these nucleotides. Using systematic evolution of ligands by exponential enrichment (SELEX), we identified DNA sequences that bound to the HTH domain of Rv0890c. Uniquely, the HTH domain could also bind RNA. Atomic force microscopy revealed that binding of Rv0890c to DNA was sequence independent, and binding of adenine nucleotides to the protein induced the formation of higher order structures that may represent biocrystalline nucleoids. This represents the first characterization of this group of proteins and their unusual biochemical properties warrant further studies into their physiological roles in future.

Ubiquitome analysis reveals the involvement of lysine ubiquitination in the spermatogenesis process of adult buffalo (Bubalus bubalis) testis

Protein ubiquitination, a major and conserved post-translational modification, is known to play a critical regulatory role in many biological processes in eukaryotes. Although several ubiquitinated proteins have been found in buffalo (Bubalus bubalis) testis in our previous studies, large-scale profiling of buffalo testis ubiquitome has not been reported to date. In the present study, we first identified a global profiling of lysine ubiquitination of adult buffalo testis using a highly sensitive LC-MS/MS coupled with immune-affinity enrichment of ubiquitinated peptides. In total, 422 lysine ubiquitination sites were identified in 262 proteins in adult buffalo testis tissue. Bioinformatics analysis showed that the ubiquitinated proteins are involved in a variety of biological processes and diverse subcellular localizations. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein interaction network analysis indicated that proteasome, glycolysis/gluconeogenesis and gap junction pathways are modulated by protein ubiquitination in testis. Besides, 44 ubiquitinated proteins may involve in spermatogenesis according to the SpermatogenesisOnline database, of which, the ubiquitination of HSPA2 and UCHL1 were confirmed by Immunoprecipitation (IP)/Western blot analysis. Taken together, these data provide a global view of ubiquitome in buffalo testis for the first time, and serve as an important resource for exploring the physiological role especially spermatogenesis of lysine ubiquitination in testis in mammals.

In Silico Analysis of Huntingtin Homologs in Lower Eukaryotes

Huntington's disease is a rare neurodegenerative and autosomal dominant disorder. HD is caused by a mutation in the gene coding for huntingtin (Htt). The result is the production of a mutant Htt with an abnormally long polyglutamine repeat that leads to pathological Htt aggregates. Although the structure of human Htt has been determined, albeit at low resolution, its functions and how they are performed are largely unknown. Moreover, there is little information on the structure and function of Htt in other organisms. The comparison of Htt homologs can help to understand if there is a functional conservation of domains in the evolution of Htt in eukaryotes. In this work, through a computational approach, Htt homologs from lower eukaryotes have been analysed, identifying ordered domains and modelling their structure. Based on the structural models, a putative function for most of the domains has been predicted. A putative C. elegans Htt-like protein has also been analysed following the same approach. The results obtained support the notion that this protein is a orthologue of human Htt.

Genome Sequence of the Bacteriophage CL31 and Interaction with the Host Strain Corynebacterium glutamicum ATCC 13032

In this study, we provide a comprehensive analysis of the genomic features of the phage CL31 and the infection dynamics with the biotechnologically relevant host strain Corynebacterium glutamicum ATCC 13032. Genome sequencing and annotation of CL31 revealed a 45-kbp genome composed of 72 open reading frames, mimicking the GC content of its host strain (54.4%). An ANI-based distance matrix showed the highest similarity of CL31 to the temperate corynephage Φ16. While the C. glutamicum ATCC 13032 wild type strain showed only mild propagation of CL31, a strain lacking the cglIR-cglIIR-cglIM restriction-modification system was efficiently infected by this phage. Interestingly, the prophage-free strain C. glutamicum MB001 featured an even accelerated amplification of CL31 compared to the ∆resmod strain suggesting a role of cryptic prophage elements in phage defense. Proteome analysis of purified phage particles and transcriptome analysis provide important insights into structural components of the phage and the response of C. glutamicum to CL31 infection. Isolation and sequencing of CL31-resistant strains revealed SNPs in genes involved in mycolic acid biosynthesis suggesting a role of this cell envelope component in phage adsorption. Altogether, these results provide an important basis for further investigation of phage-host interactions in this important biotechnological model organism.

Divergent CPEB prion-like domains reveal different assembly mechanisms for a generic amyloid-like fold

BACKGROUND

Amyloids are ordered, insoluble protein aggregates, characterized by a cross-β sheet quaternary structure in which molecules in a β-strand conformation are stacked along the filament axis via intermolecular interactions. While amyloids are typically associated with pathological conditions, functional amyloids have also been identified and are present in a wide variety of organisms ranging from bacteria to humans. The cytoplasmic polyadenylation element-binding (CPEB) prion-like protein is an mRNA-binding translation regulator, whose neuronal isoforms undergo activity-dependent aggregation, a process that has emerged as a plausible biochemical substrate for memory maintenance. CPEB aggregation is driven by prion-like domains (PLD) that are divergent in sequence across species, and it remains unknown whether such divergent PLDs follow a similar aggregating assembly pathway. Here, we describe the amyloid-like features of the neuronal Aplysia CPEB (ApCPEB) PLD and compare them to those of the Drosophila ortholog, Orb2 PLD.

RESULTS

Using in vitro single-molecule and bulk biophysical methods, we find transient oligomers and mature amyloid-like filaments that suggest similarities in the late stages of the assembly pathway for both ApCPEB and Orb2 PLDs. However, while prior to aggregation the Orb2 PLD monomer remains mainly as a random coil in solution, ApCPEB PLD adopts a diversity of conformations comprising α-helical structures that evolve to coiled-coil species, indicating structural differences at the beginning of their amyloid assembly pathways.

CONCLUSION

Our results indicate that divergent PLDs of CPEB proteins from different species retain the ability to form a generic amyloid-like fold through different assembly mechanisms.

ATP binding cassette importers in eukaryotic organisms

ATP-binding cassette (ABC) transporters are ubiquitous across all realms of life. Dogma suggests that bacterial ABC transporters include both importers and exporters, whilst eukaryotic members of this family are solely exporters, implying that ABC import function was lost during evolution. This view is being challenged, for example energy-coupling factor (ECF)-type ABC importers appear to fulfil important roles in both algae and plants where they form the ABCI sub-family. Herein we discuss whether bacterial Type I and Type II ABC importers also made the transition into extant eukaryotes. Various studies suggest that Type I importers exist in algae and the liverwort family of primitive non-vascular plants, but not in higher plants. The existence of eukaryotic Type II importers is also supported: a transmembrane protein homologous to vitamin B12 import system transmembrane protein (BtuC), hemin transport system transmembrane protein (HmuU) and high-affinity zinc uptake system membrane protein (ZnuB) is present in the Cyanophora paradoxa genome. This protein has homologs within the genomes of red algae. Furthermore, its candidate nucleotide-binding domain (NBD) shows closest similarity to other bacterial Type II importer NBDs such as BtuD. Functional studies suggest that Type I importers have roles in maintaining sulphate levels in the chloroplast, whilst Type II importers probably act as importers of Mn²⁺ or Zn²⁺ , as inferred by comparisons with bacterial homologs. Possible explanations for the presence of these transporters in simple plants, but not in other eukaryotic organisms, are considered. In order to utilise the existing nomenclature for eukaryotic ABC proteins, we propose that eukaryotic Type I and II importers be classified as ABCJ and ABCK transporters, respectively.

DIAMOND+MEGAN: Fast and Easy Taxonomic and Functional Analysis of Short and Long Microbiome Sequences

One main approach to computational analysis of microbiome sequences is to first align against a reference database of annotated protein sequences (NCBI-nr) and then perform taxonomic and functional binning of the sequences based on the resulting alignments. For both short and long reads (or assembled contigs), alignment is performed using DIAMOND, whereas taxonomic and functional binning, followed by inter- active exploration and analysis, is performed using MEGAN. We provide two step-by-step descriptions of this approach: © 2021 The Authors. Basic Protocol 1: Taxonomic and functional analysis of short read microbiome sequences Support Protocol 1: Preprocessing Basic Protocol 2: taxonomic and functional analysis of assembled long read microbiome sequences Support Protocol 2: Taxonomic binning and CheckM.

Crystal structures of the EVE-HNH endonuclease VcaM4I in the presence and absence of DNA

Many modification-dependent restriction endonucleases (MDREs) are fusions of a PUA superfamily modification sensor domain and a nuclease catalytic domain. EVE domains belong to the PUA superfamily, and are present in MDREs in combination with HNH nuclease domains. Here, we present a biochemical characterization of the EVE-HNH endonuclease VcaM4I and crystal structures of the protein alone, with EVE domain bound to either 5mC modified dsDNA or to 5mC/5hmC containing ssDNA. The EVE domain is moderately specific for 5mC/5hmC containing DNA according to EMSA experiments. It flips the modified nucleotide, to accommodate it in a hydrophobic pocket of the enzyme, primarily formed by P24, W82 and Y130 residues. In the crystallized conformation, the EVE domain and linker helix between the two domains block DNA binding to the catalytic domain. Removal of the EVE domain and inter-domain linker, but not of the EVE domain alone converts VcaM4I into a non-specific toxic nuclease. The role of the key residues in the EVE and HNH domains of VcaM4I is confirmed by digestion and restriction assays with the enzyme variants that differ from the wild-type by changes to the base binding pocket or to the catalytic residues.

The root-knot nematode effector MiEFF18 interacts with the plant core spliceosomal protein SmD1 required for giant cell formation

The root-knot nematode Meloidogyne incognita secretes specific effectors (MiEFF) and induces the redifferentiation of plant root cells into enlarged multinucleate feeding 'giant cells' essential for nematode development. Immunolocalizations revealed the presence of the MiEFF18 protein in the salivary glands of M. incognita juveniles. In planta, MiEFF18 localizes to the nuclei of giant cells demonstrating its secretion during plant-nematode interactions. A yeast two-hybrid approach identified the nuclear ribonucleoprotein SmD1 as a MiEFF18 partner in tomato and Arabidopsis. SmD1 is an essential component of the spliceosome, a complex involved in pre-mRNA splicing and alternative splicing. RNA-seq analyses of Arabidopsis roots ectopically expressing MiEFF18 or partially impaired in SmD1 function (smd1b mutant) revealed the contribution of the effector and its target to alternative splicing and proteome diversity. The comparison with Arabidopsis galls data showed that MiEFF18 modifies the expression of genes important for giant cell ontogenesis, indicating that MiEFF18 modulates SmD1 functions to facilitate giant cell formation. Finally, Arabidopsis smd1b mutants exhibited less susceptibility to M. incognita infection, and the giant cells formed on these mutants displayed developmental defects, suggesting that SmD1 plays an important role in the formation of giant cells and is required for successful nematode infection.

Multiple Pathways to Homothallism in Closely Related Yeast Lineages in the Basidiomycota

Sexual reproduction in fungi relies on proteins with well-known functions encoded by the mating type (MAT) loci. In the Basidiomycota, MAT loci are often bipartite, with the P/R locus encoding pheromone precursors and pheromone receptors and the HD locus encoding heterodimerizing homeodomain transcription factors (Hd1/Hd2). The interplay between different alleles of these genes within a single species usually generates at least two compatible mating types. However, a minority of species are homothallic, reproducing sexually without an obligate need for a compatible partner. Here, we examine the organization and function of the MAT loci of Cystofilobasidium capitatum, a species in the order Cystofilobasidiales, which is unusually rich in homothallic species. We determined MAT gene content and organization in C. capitatum and found that it resembles a mating type of the closely related heterothallic species Cystofilobasidium ferigula To explain the homothallic sexual reproduction observed in C. capitatum, we examined HD protein interactions in the two Cystofilobasidium species and determined C. capitatum MAT gene expression both in a natural setting and upon heterologous expression in Phaffia rhodozyma, a homothallic species belonging to a clade sister to that of Cystofilobasidium. We conclude that the molecular basis for homothallism in C. capitatum appears to be distinct from that previously established for P. rhodozyma Unlike in the latter species, homothallism in C. capitatum may involve constitutive activation or dispensability of the pheromone receptor and the functional replacement of the usual Hd1/Hd2 heterodimer by an Hd2 homodimer. Overall, our results suggest that homothallism evolved multiple times within the Cystofilobasidiales.IMPORTANCE Sexual reproduction is important for the biology of eukaryotes because it strongly impacts the dynamics of genetic variation. In fungi, although sexual reproduction is usually associated with the fusion between cells belonging to different individuals (heterothallism), sometimes a single individual is capable of completing the sexual cycle alone (homothallism). Homothallic species are unusually common in a fungal lineage named Cystofilobasidiales. Here, we studied the genetic bases of homothallism in one species in this lineage, Cystofilobasidium capitatum, and found it to be different in several aspects from those of another homothallic species, Phaffia rhodozyma, belonging to the genus most closely related to Cystofilobasidium Our results strongly suggest that homothallism evolved independently in Phaffia and Cystofilobasidium, lending support to the idea that transitions between heterothallism and homothallism are not as infrequent as previously thought. Our work also helps to establish the Cystofilobasidiales as a model lineage in which to study these transitions.

From Data Mining of Chitinophaga sp. Genome to Enzyme Discovery of a Hyperthermophilic Metallocarboxypeptidase

For several centuries, microorganisms and enzymes have been used for many different applications. Although many enzymes with industrial applications have already been reported, different screening technologies, methods and approaches are constantly being developed in order to allow the identification of enzymes with even more interesting applications. In our work, we have performed data mining on the Chitinophaga sp. genome, a gram-negative bacterium isolated from a bacterial consortium of sugarcane bagasse isolated from an ethanol plant. The analysis of 8 Mb allowed the identification of the chtcp gene, previously annotated as putative Cht4039. The corresponding codified enzyme, denominated as ChtCP, showed the HEXXH conserved motif of family M32 from thermostable carboxypeptidases. After expression in E. coli, the recombinant enzyme was characterized biochemically. ChtCP showed the highest activity versus benziloxicarbonil Ala-Trp at pH 7.5, suggesting a preference for hydrophobic substrates. Surprisingly, the highest activity of ChtCP observed was between 55 °C and 75 °C, and 62% activity was still displayed at 100 °C. We observed that Ca2+, Ba2+, Mn2+ and Mg2+ ions had a positive effect on the activity of ChtCP, and an increase of 30 °C in the melting temperature was observed in the presence of Co2+. These features together with the structure of ChtCP at 1.2 Å highlight the relevance of ChtCP for further biotechnological applications.

Protein domain identification methods and online resources

Protein domains are the basic units of proteins that can fold, function, and evolve independently. Knowledge of protein domains is critical for protein classification, understanding their biological functions, annotating their evolutionary mechanisms and protein design. Thus, over the past two decades, a number of protein domain identification approaches have been developed, and a variety of protein domain databases have also been constructed. This review divides protein domain prediction methods into two categories, namely sequence-based and structure-based. These methods are introduced in detail, and their advantages and limitations are compared. Furthermore, this review also provides a comprehensive overview of popular online protein domain sequence and structure databases. Finally, we discuss potential improvements of these prediction methods.

Computational resources for identifying and describing proteins driving liquid-liquid phase separation

One of the most intriguing fields emerging in current molecular biology is the study of membraneless organelles formed via liquid–liquid phase separation (LLPS). These organelles perform crucial functions in cell regulation and signalling, and recent years have also brought about the understanding of the molecular mechanism of their formation. The LLPS field is continuously developing and optimizing dedicated in vitro and in vivo methods to identify and characterize these non-stoichiometric molecular condensates and the proteins able to drive or contribute to LLPS. Building on these observations, several computational tools and resources have emerged in parallel to serve as platforms for the collection, annotation and prediction of membraneless organelle-linked proteins. In this survey, we showcase recent advancements in LLPS bioinformatics, focusing on (i) available databases and ontologies that are necessary to describe the studied phenomena and the experimental results in an unambiguous way and (ii) prediction methods to assess the potential LLPS involvement of proteins. Through hands-on application of these resources on example proteins and representative datasets, we give a practical guide to show how they can be used in conjunction to provide in silico information on LLPS.

Phenotypic Characterization and Whole-Genome Analysis of a Novel Bacteriophage HCF1 Infecting Citrobacter amalonaticus and C. freundii

Citrobacter species often occur in sewage, food, soil, wastewater, and in the intestinal tract of animals and humans. Citrobacter spp. cause urinary tract infections (UTIs) and infantile meningitis in humans. Due to the presence of plasmid-encoded resistance genes, Citrobacter spp. are often resistant to many antibiotics. In this study, Citrobacter virus HCF1, a novel virulent bacteriophage capable of killing Citrobacter amalonaticus and Citrobacter freundii, was isolated from the sewage water. The isolated bacteriophage was characterized with respect to transmission electron microscopy, one-step growth curve, host range, in vitro efficacy, storage stability, and environmental stress tolerance. The one-step growth curve analysis revealed that the latent period of HCF1 was 30 min and the estimated burst size was 121 plaque-forming units (PFU) per bacterial cell. Host range testing indicated that the HCF1 was specific to the Citrobacter genus. In vitro efficacy assay in the effluent of an anaerobic biodigester showed that the HCF1 completely eliminated the host within 4 and 5 h at MOI:100 and MOI:10, respectively, thereby indicating its potential for combating C. amalonaticus infections. The isolated bacteriophage is considerably stable and tolerant to environmental stress. Furthermore, the complete genome of HCF1 was sequenced using Oxford Nanopore sequencing and the data were subjected to detailed bioinformatic analyses. NCBI-BLASTn analysis revealed that the HCF1 genome had a query coverage of 15-21% and a maximum similarity of 77.27-78.49% with 11 bacteriophages of the Drexlerviridae family. Detailed bioinformatic analysis of the genome profile suggests that HCF1 is a novel T1svirus belonging to the Tempevirinae subfamily of the Drexlerviridae family.

SNF-NN: computational method to predict drug-disease interactions using similarity network fusion and neural networks

BACKGROUND

Drug repositioning is an emerging approach in pharmaceutical research for identifying novel therapeutic potentials for approved drugs and discover therapies for untreated diseases. Due to its time and cost efficiency, drug repositioning plays an instrumental role in optimizing the drug development process compared to the traditional de novo drug discovery process. Advances in the genomics, together with the enormous growth of large-scale publicly available data and the availability of high-performance computing capabilities, have further motivated the development of computational drug repositioning approaches. More recently, the rise of machine learning techniques, together with the availability of powerful computers, has made the area of computational drug repositioning an area of intense activities.

RESULTS

In this study, a novel framework SNF-NN based on deep learning is presented, where novel drug-disease interactions are predicted using drug-related similarity information, disease-related similarity information, and known drug-disease interactions. Heterogeneous similarity information related to drugs and disease is fed to the proposed framework in order to predict novel drug-disease interactions. SNF-NN uses similarity selection, similarity network fusion, and a highly tuned novel neural network model to predict new drug-disease interactions. The robustness of SNF-NN is evaluated by comparing its performance with nine baseline machine learning methods. The proposed framework outperforms all baseline methods ([Formula: see text] = 0.867, and [Formula: see text]=0.876) using stratified 10-fold cross-validation. To further demonstrate the reliability and robustness of SNF-NN, two datasets are used to fairly validate the proposed framework's performance against seven recent state-of-the-art methods for drug-disease interaction prediction. SNF-NN achieves remarkable performance in stratified 10-fold cross-validation with [Formula: see text] ranging from 0.879 to 0.931 and [Formula: see text] from 0.856 to 0.903. Moreover, the efficiency of SNF-NN is verified by validating predicted unknown drug-disease interactions against clinical trials and published studies.

CONCLUSION

In conclusion, computational drug repositioning research can significantly benefit from integrating similarity measures in heterogeneous networks and deep learning models for predicting novel drug-disease interactions. The data and implementation of SNF-NN are available at http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php .

HN1L promotes invasion and metastasis of the esophagogastric junction adenocarcinoma

Background

Adenocarcinoma of the esophagogastric junction (AEG) refers to cancer that crosses the line of the gastroesophageal junction and includes distal esophageal cancer and proximal gastric cancer. It is characterized by early metastasis and a poor prognosis and has few treatment options. Here, we report a novel potential therapeutic target, hematological and neurological expressed 1‐like (HN1L), in AEG.

Methods

A total of 38 patients who underwent surgical resection of AEG at the Department of Thoracic Surgery of Shandong Provincial Hospital from September 2018 to June 2019 were enrolled into the study. We detected the expression of HN1L in AEG and adjacent nontumor tissues by IHC staining. The clinicopathological characteristics of HN1L were statistically analyzed. Then, the expression of HN1L in different cell lines was detected by RT‐q PCR. Finally, AGS and HGC‐27 cell lines were performed to inhibit HN1L by shRNA in order to explore its role in the development of AEG.

Results

Immunohistochemical staining showed that the expression of HN1L in cancer tissues was higher than that in nontumor tissue (p < 0.001). High expression of HN1L was significantly correlated with TNM stage (p = 0.013) and lymph node metastasis (p = 0.03). The expression of HN1L was upregulated in tumor cell lines compared with normal cell line. Additionally, Cell function studies demonstrated that lentivirus‐mediated shRNA silencing of HN1L expression could effectively reduce the proliferation, invasion, and metastasis of tumor cell lines and promote their apoptosis (p < 0.05).

Conclusions

HN1L expression might contribute to the invasion and metastasis of AEG and is a promising therapeutic target.

Whole exome sequencing identifies the potential for genetic rescue in iconic and critically endangered Panamanian harlequin frogs

Avoiding extinction in a rapidly changing environment often relies on a species' ability to quickly adapt in the face of extreme selective pressures. In Panamá, two closely related harlequin frog species (Atelopus varius and Atelopus zeteki) are threatened with extinction due to the fungal pathogen Batrachochytrium dendrobatidis (Bd). Once thought to be nearly extirpated from Panamá, A. varius have recently been rediscovered in multiple localities across their historical range; however, A. zeteki are possibly extinct in the wild. By leveraging a unique collection of 186 Atelopus tissue samples collected before and after the Bd outbreak in Panama, we describe the genetics of persistence for these species on the brink of extinction. We sequenced the transcriptome and developed an exome-capture assay to sequence the coding regions of the Atelopus genome. Using these genetic data, we evaluate the population genetic structure of historical A. varius and A. zeteki populations, describe changes in genetic diversity over time, assess the relationship between contemporary and historical individuals, and test the hypothesis that some A. varius populations have rapidly evolved to resist or tolerate Bd infection. We found a significant decrease in genetic diversity in contemporary (compared to historical) A. varius populations. We did not find strong evidence of directional allele frequency change or selection for Bd resistance genes, but we uncovered a set of candidate genes that warrant further study. Additionally, we found preliminary evidence of recent migration and gene flow in one of the largest persisting A. varius populations in Panamá, suggesting the potential for genetic rescue in this system. Finally, we propose that previous conservation units should be modified, as clear genetic breaks do not exist beyond the local population level. Our data lay the groundwork for genetically informed conservation and advance our understanding of how imperiled species might be rescued from extinction.

Proteomics-Based Data Integration of Wheat Cultivars Facing Fusarium graminearum Strains Revealed a Core-Responsive Pattern Controlling Fusarium Head Blight

Fusarium head blight (FHB), mainly occurring upon Fusarium graminearum infection in a wide variety of small-grain cereals, is supposed to be controlled by a range of processes diverted by the fungal pathogen, the so-called susceptibility factors. As a mean to provide relevant information about the molecular events involved in FHB susceptibility in bread wheat, we studied an extensive proteome of more than 7,900 identified wheat proteins in three cultivars of contrasting susceptibilities during their interaction with three F. graminearum strains of different aggressiveness. No cultivar-specific proteins discriminated the three wheat genotypes, demonstrating the establishment of a core proteome regardless of unequivocal FHB susceptibility differences. Quantitative protein analysis revealed that most of the FHB-induced molecular adjustments were shared by wheat cultivars and occurred independently of the F. graminearum strain aggressiveness. Although subtle abundance changes evidenced genotype-dependent responses to FHB, cultivar distinction was found to be mainly due to basal abundance differences, especially regarding the chloroplast functions. Integrating these data with previous proteome mapping of the three F. graminearum strains facing the three same wheat cultivars, we demonstrated strong correlations between the wheat protein abundance changes and the adjustments of fungal proteins supposed to interfere with host molecular functions. Together, these results provide a resourceful dataset that expands our understanding of the specific molecular events taking place during the wheat-F. graminearum interaction.

Expansion of RiPP biosynthetic space through integration of pan-genomics and machine learning uncovers a novel class of lanthipeptides

Microbial natural products constitute a wide variety of chemical compounds, many which can have antibiotic, antiviral, or anticancer properties that make them interesting for clinical purposes. Natural product classes include polyketides (PKs), nonribosomal peptides (NRPs), and ribosomally synthesized and post-translationally modified peptides (RiPPs). While variants of biosynthetic gene clusters (BGCs) for known classes of natural products are easy to identify in genome sequences, BGCs for new compound classes escape attention. In particular, evidence is accumulating that for RiPPs, subclasses known thus far may only represent the tip of an iceberg. Here, we present decRiPPter (Data-driven Exploratory Class-independent RiPP TrackER), a RiPP genome mining algorithm aimed at the discovery of novel RiPP classes. DecRiPPter combines a Support Vector Machine (SVM) that identifies candidate RiPP precursors with pan-genomic analyses to identify which of these are encoded within operon-like structures that are part of the accessory genome of a genus. Subsequently, it prioritizes such regions based on the presence of new enzymology and based on patterns of gene cluster and precursor peptide conservation across species. We then applied decRiPPter to mine 1,295 Streptomyces genomes, which led to the identification of 42 new candidate RiPP families that could not be found by existing programs. One of these was studied further and elucidated as a representative of a novel subfamily of lanthipeptides, which we designate class V. The 2D structure of the new RiPP, which we name pristinin A3 (1), was solved using nuclear magnetic resonance (NMR), tandem mass spectrometry (MS/MS) data, and chemical labeling. Two previously unidentified modifying enzymes are proposed to create the hallmark lanthionine bridges. Taken together, our work highlights how novel natural product families can be discovered by methods going beyond sequence similarity searches to integrate multiple pathway discovery criteria.

This study shows that decRiPPter, an innovative algorithmic approach using pan-genomics and machine learning, can discover novel types of ribosomally synthesized peptide (RIPP) natural products, including a new class of lanthipeptides.

A New Phage Lysin Isolated from the Oral Microbiome Targeting Streptococcus pneumoniae

Streptococcus pneumoniae is highly pathogenic and causes several mucosal and invasive infections. Due to the rising number of multidrug-resistant (MDR) strains of S. pneumoniae, new antimicrobials with alternative mechanisms of action are urgently needed. In this study, we identified two new Streptococcal phages from the oral microbiome, 23TH and SA01. Their lysins, 23TH_48 and SA01_53, were recombinantly expressed, characterized and tested for their lethality. SA01_53 was found to only lyse its host strain of S. anginosus, while 23TH_48 was found to possess a broader lytic activity beyond its host strain of S. infantis, with several S. pneumoniae isolates sensitive to its lytic activity. 23TH_48 at a concentration of five activity units per mL (U/mL) was found to reduce cell counts of S. pneumoniae DSM 24048 by 4 log₁₀ colony forming units per mL (CFU/mL) within 1 h and effectively prevented and destroyed biofilms of S. pneumoniae R6 at concentrations of 228.8 ng/µL and 14.3 ng/µL, respectively. Given its high lytic activity, 23TH_48 could prove to be a promising candidate to help combat pneumococcal infections.

In silico screening and experimental analysis of family GH11 xylanases for applications under conditions of alkaline pH and high temperature

BACKGROUND

Xylanases are one of the most extensively used enzymes for biomass digestion. However, in many instances, their use is limited by poor performance under the conditions of pH and temperature required by the industry. Therefore, the search for xylanases able to function efficiently at alkaline pH and high temperature is an important objective for different processes that use lignocellulosic substrates, such as the production of paper pulp and biofuels.

RESULTS

A comprehensive in silico analysis of family GH11 sequences from the CAZY database allowed their phylogenetic classification in a radial cladogram in which sequences of known or presumptive thermophilic and alkalophilic xylanases appeared in three clusters. Eight sequences from these clusters were selected for experimental analysis. The coding DNA was synthesized, cloned and the enzymes were produced in E. coli. Some of these showed high xylanolytic activity at pH values > 8.0 and temperature > 80 °C. The best enzymes corresponding to sequences from Dictyoglomus thermophilum (Xyn5) and Thermobifida fusca (Xyn8). The addition of a carbohydrate-binding module (CBM9) to Xyn5 increased 4 times its activity at 90 °C and pH > 9.0. The combination of Xyn5 and Xyn8 was proved to be efficient for the saccharification of alkali pretreated rice straw, yielding xylose and xylooligosaccharides.

CONCLUSIONS

This study provides a fruitful approach for the selection of enzymes with suitable properties from the information contained in extensive databases. We have characterized two xylanases able to hydrolyze xylan with high efficiency at pH > 8.0 and temperature > 80 °C.

Deletion of pksA attenuates the melanogenesis, growth and sporulation ability and causes increased sensitivity to stress response and antifungal drugs in the human pathogenic fungus Fonsecaea monophora

Fonsecaea monophora, which is very similar to Fonsecaea pedrosoi in morphological features, has been commonly misdiagnosed as F. pedrosoi. Like F. pedrosoi, F. monophora has been also identified as a predominant pathogen of Chromoblastomycosis (CBM). Melanin has been recognized as a virulence factor in several fungi, however, it is still largely unknown about the biological role of melanin and how melanin is synthesized in F. monophora. In this study, we identified two putative polyketide synthase genes (pks), AYO21_03016 (pksA) and AYO21_10638, by searching against the genome of F. monophora. AYO21_03016 and AYO21_10638 were further targeted disrupted by Agrobacterium tumefaciens-mediated transformation (ATMT). We discovered that pksA gene was the major polyketide synthase required for melanin synthesis in F. monophora, rather than AYO21_10638. Phenotypic analysis showed that, knocking out of the pksA gene attenuated melanogenesis, growth rate, sporulation ability and virulence of F. monophora, as compared with wild-type and complementation strain (pksA-C). Furthermore, the ΔpksA mutant was confirmed to be more sensitive to the oxidative stress, extreme pH environment, and antifungal drugs including itraconazole (ITC), terbinafine (TER), and amphotericin B (AMB). Taken together, these findings enabled us to comprehend the role of pksA in regulating DHN-melanin pathway and its effect on the biological function of F. monophora.

Identification of novel non-homologous drug targets against Acinetobacter baumannii using subtractive genomics and comparative metabolic pathway analysis

Lack of effective antibiotics and the development of multidrug resistance in clinical isolates of nosocomial pathogen Acinetobacter baumanni has necessitated the identification of novel drug targets. The study is divided into three phases, in phase I, four different sets of proteins were subjected to a chokepoint, plasmid, resistance genes, and virulence factors analysis. After phase 1 analysis we obtained two hundred twenty-two proteins which were analyzed further in the phase II for essentiality and homology. Fifty-eight proteins identified as target candidates were studied for qualitative characteristics. Among them, 32 were identified as cytoplasmic membrane, 17 as cytoplasmic, one as periplasmic, one as outer membrane, two as extracellular, and location of 5 was not known. Druggability analysis revealed that 18 proteins were druggable, and 40 were novel. Drug targets obtained in the present study can be utilized for the identification of novel antimicrobials for the treatment of infections caused by multidrug-resistant A. baumannii. Predicted drug targets can be evaluated for their binding affinity by molecular docking studies and thus accelerating the process of drug discovery.

An updated evolutionary study of the Notch family reveals a new ancient origin and novel invariable motifs as potential pharmacological targets

Notch family proteins play a key role in a variety of developmental processes by controlling cell fate decisions and operating in a great number of biological processes in several organ systems, such as hematopoiesis, somatogenesis, vasculogenesis, neurogenesis and homeostasis. The Notch signaling pathway is crucial for the majority of developmental programs and regulates multiple pathogenic processes. Notch family receptors' activation has been largely related to its multiple effects in sustaining oncogenesis. The Notch signaling pathway constitutes an ancient and conserved mechanism for cell to cell communication. Much of what is known about Notch family proteins function comes from studies done in Caenorhabditis Elegans and Drosophila Melanogaster. Although, human Notch homologs had also been identified, the molecular mechanisms which modulate the Notch signaling pathway remained substantially unknown. In this study, an updated evolutionary analysis of the Notch family members among 603 different organisms of all kingdoms, from bacteria to humans, was performed in order to discover key regions that have been conserved throughout evolution and play a major role in the Notch signaling pathway. The major goal of this study is the presentation of a novel updated phylogenetic tree for the Notch family as a reliable phylogeny "map", in order to correlate information of the closely related members and identify new possible pharmacological targets that can be used in pathogenic cases, including cancer.

"Integrative genomic analysis of the bioprospection of regulators and accessory enzymes associated with cellulose degradation in a filamentous fungus (Trichoderma harzianum)"

BACKGROUND

Unveiling fungal genome structure and function reveals the potential biotechnological use of fungi. Trichoderma harzianum is a powerful CAZyme-producing fungus. We studied the genomic regions in T. harzianum IOC3844 containing CAZyme genes, transcription factors and transporters.

RESULTS

We used bioinformatics tools to mine the T. harzianum genome for potential genomics, transcriptomics, and exoproteomics data and coexpression networks. The DNA was sequenced by PacBio SMRT technology for multiomics data analysis and integration. In total, 1676 genes were annotated in the genomic regions analyzed; 222 were identified as CAZymes in T. harzianum IOC3844. When comparing transcriptome data under cellulose or glucose conditions, 114 genes were differentially expressed in cellulose, with 51 being CAZymes. CLR2, a transcription factor physically and phylogenetically conserved in Trichoderma spp., was differentially expressed under cellulose conditions. The genes induced/repressed under cellulose conditions included those important for plant biomass degradation, including CIP2 of the CE15 family and a copper-dependent LPMO of the AA9 family.

CONCLUSIONS

Our results provide new insights into the relationship between genomic organization and hydrolytic enzyme expression and regulation in T. harzianum IOC3844. Our results can improve plant biomass degradation, which is fundamental for developing more efficient strains and/or enzymatic cocktails to produce hydrolytic enzymes.

Whole-genome de novo assemblies reveal extensive structural variations and dynamic organelle-to-nucleus DNA transfers in African and Asian rice

Asian cultivated rice (Oryza sativa) and African cultivated rice (Oryza glaberrima) originated from the wild rice species Oryza rufipogon and Oryza barthii, respectively. The genomes of both cultivated species have undergone profound changes during domestication. Whole-genome de novo assemblies of O. barthii, O. glaberrima, O. rufipogon and Oryza nivara, produced using PacBio single-molecule real-time (SMRT) and next-generation sequencing (NGS) technologies, showed that Gypsy-like retrotransposons are the major contributors to genome size variation in African and Asian rice. Through the detection of genome-wide structural variations (SVs), we observed that besides 28 shared SV hot spots, another 67 hot spots existed in either the Asian or African rice genomes. Based on gene annotation information of the SVs, we established that organelle-to-nucleus DNA transfers resulted in numerous SVs that participated in the nuclear genome divergence of rice species and subspecies. We detected 52 giant nuclear integrants of organelle DNA (NORGs, defined as >10 kb) in six Oryza AA genomes. In addition, we developed an effective method to genotype giant NORGs, based on genome assembly, and first showed the dynamic change in the distribution of giant NORGs in rice natural population. Interestingly, 16 highly differentiated giant NORGs tended to accumulate in natural populations of Asian rice from higher latitude regions, grown at lower temperatures and light intensities. Our study provides new insight into the genome divergence of African and Asian rice, and establishes that organelle-to-nucleus DNA transfers, as potentially powerful contributors to environmental adaptation during rice evolution, play a major role in producing SVs in rice genomes.