DNA barcoding and morphological identification of spiny lobsters in South Korean waters: a new record of Panulirus longipes and Panulirus homarus homarus

To date, 19 species of spiny lobsters from the genus Panulirus have been discovered, of which only P. japonicus, P. penicilatus, P. stimpsoni, and P. versicolor have been documented in South Korean waters. In this study, we aimed to identify and update the current list of spiny lobster species that inhabit South Korean waters based on the morphological features and the phylogenetic profile of cytochrome oxidase I (COI) of mitochondrial DNA (mtDNA). Spiny lobsters were collected from the southern and eastern coasts of Jeju Island, South Korea. Phylogenetic analyses were performed using neighbor-joining (NJ), maximum likelihood (ML), and Bayesian inference (BI) methods. The ML tree was used to determine the spiny lobster lineages, thereby clustering the 17 specimens collected in this study into clades A, B, C, and D, which were reciprocally monophyletic with P. japonicus, P. homarus homarus, P. longipes, and P. stimpsoni, respectively. These clades were also supported by morphological examinations. Interestingly, morphological variations, including the connected pleural and transverse groove at the third abdominal somite, were observed in four specimens that were genetically confirmed as P. japonicus. This finding is novel within the P. japonicus taxonomical reports. Additionally, this study updates the documentation of spiny lobsters inhabiting South Korean waters as P. longipes and P. homarus homarus were recorded for the first time in this region.

GFICLEE: ultrafast tree-based phylogenetic profile method inferring gene function at the genomic-wide level

Background Phylogenetic profiling is widely used to predict novel members of large protein complexes and biological pathways. Although methods combined with phylogenetic trees have significantly improved prediction accuracy, computational efficiency is still an issue that limits its genome-wise application. Results Here we introduce a new tree-based phylogenetic profiling algorithm named GFICLEE, which infers common single and continuous loss (SCL) events in the evolutionary patterns. We validated our algorithm with human pathways from three databases and compared the computational efficiency with current tree-based with 10 different scales genome dataset. Our algorithm has a better predictive performance with high computational efficiency. Conclusions The GFICLEE is a new method to infers genome-wide gene function. The accuracy and computational efficiency of GFICLEE make it possible to explore gene functions at the genome-wide level on a personal computer.

Procoagulant and Antimicrobial Effects of Chitosan in Wound Healing

Chitosan, a polysaccharide derived from chitin, has excellent wound healing properties, including intrinsic antimicrobial and hemostatic activities. This study investigated the effectiveness of chitosan dressing and compared it with that of regular gauze dressing in controlling clinically surgical bleeding wounds and profiled the community structure of the microbiota affected by these treatments. The dressings were evaluated based on biocompatibility, blood coagulation factors in rat, as well as antimicrobial and procoagulant activities, and the microbial phylogenetic profile in patients with abdominal surgical wounds. The chitosan dressing exhibited a uniformly fibrous morphology with a large surface area and good biocompatibility. Compared to regular gauze dressing, the chitosan dressing accelerated platelet aggregation, indicated by the lower ratio of prothrombin time and activated partial thromboplastin time, and had outstanding blood absorption ability. Adenosine triphosphate assay results revealed that the chitosan dressing inhibited bacterial growth up to 8 d post-surgery. Moreover, 16S rRNA-based sequencing revealed that the chitosan dressing effectively protected the wound from microbial infection and promoted the growth of probiotic microbes, thereby improving skin immunity and promoting wound healing. Our findings suggest that chitosan dressing is an effective antimicrobial and procoagulant and promotes wound repair by providing a suitable environment for beneficial microbiota.

Spatial progression and molecular heterogeneity of IDH-mutant glioblastoma determined by DNA methylation-based mapping

Glioblastoma (GBM) is the most common malignant primary central nervous system (CNS) neoplasm in adults, and has an almost universally poor prognosis. Recently, an emphasis on genetic and epigenetic profiling has revealed a number of molecular features useful in the diagnostic and prognostic classification of GBM, advancing our understanding of the underlying features that make these tumors so aggressive and providing the rationale for the creation of better targeted therapeutics. One such method, DNA methylation profiling, has recently emerged as an important technique for the classification of CNS tumors, with diagnostic accuracy in some cases surpassing traditional methods. However, how DNA methylation profiles change with the course of the disease remains less understood. Here, we present a case of a 30-year-old male with primary IDH-mutant GBM with widespread recurrence and death two years later. Using unsupervised hierarchical clustering of methylation probes, we created a phylogenetic map to trace the tumor path as it spread from the initial biopsy site throughout the right hemisphere, across the corpus callosum to the contralateral hemisphere, and into the brainstem. We identified molecular divergence between the right and left hemisphere GBM samples marked by distinct copy number profile alterations, alterations in specific methylation sites, and regional loss of MGMT promoter methylation, providing a potential mechanism for treatment resistance in this case. In summary, this case both highlights the molecular diversity in GBM, and illustrates a novel use for methylation profiling in establishing a phylogenetic profile to allow for spatial mapping of tumor progression.

New Brucella variant isolated from Croatian cattle

Background A novel Brucella strain closely related to Brucella (B.) melitensis biovar (bv) 3 was found in Croatian cattle during testing within a brucellosis eradication programme. Case presentation Standardised serological, brucellin skin test, bacteriological and molecular diagnostic screening for Brucella infection led to positive detection in one dairy cattle herd. Three isolates from that herd were identified to species level using the Bruce ladder method. Initially, two strains were typed as B. melitensis and one as B. abortus, but multiplex PCR based on IS711 and the Suis ladder showed that all of them to belong to B. melitensis, and the combination of whole-genome and multi-locus sequencing as well as Multi-Locus Variable numbers of tandem repeats Analysis (MLVA) highlighted a strong proximity within the phylogenetic branch of B. melitensis strains previously isolated from Croatia, Albania, Kosovo and Bosnia and Herzegovina. Two isolates were determined to be B. melitensis bv. 3, while the third showed a unique phylogenetic profile, growth profile on dyes and bacteriophage typing results. This isolate contained the 609-bp omp31 sequence, but not the 723-bp omp31 sequence present in the two isolates of B. melitensis bv. 3. Conclusions Identification of a novel Brucella variant in this geographic region is predictable given the historic endemicity of brucellosis. The emergence of a new variant may reflect a combination of high prevalence among domestic ruminants and humans as well as weak eradication strategies. The zoonotic potential, reservoirs and transmission pathways of this and other Brucella variants should be explored.

Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes

Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets or expanding the analyses to larger scales. Automated orthology inference should allow such large-scale analyses, but substantial differences between orthologous groups generated by different approaches are observed. We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regard to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the last eukaryotic common ancestor’s gene content, pervasiveness of gene loss and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other. We find that most orthology methods reconstruct a large last eukaryotic common ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time, derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large-scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementation The data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies.

Exploring metal resistance genes and mechanisms in copper enriched metal ore metagenome

Heavy metal pollution is a major global health challenge. In order to develop bioremediation solution for decontamination of environment from heavy metals one appropriate step is to investigate heavy metal resistance strategies used by microbial communities in the metal contaminated environments. The aim of the present study was to understand detailed mechanisms by which long time heavy metal (HM) exposed microbial community use to cope with excess of HMs. We exploited the Illumina high throughput metagenomic approach to examine taxonomical and functional diversity of copper enriched soil metagenome. Three enriched metagenomes were compared against 94 metagenomes derived from non-contaminated soils. Taxonomic composition analysis showed that phylogenetic profile of metal contaminated soils were enriched with γ-Proteobacteria. Comparison of functional profile of the two group reveled significant difference with potential role in HM resistance (HMR). Enriched SEED categories were “Membrane Transport”, “Cell Wall and Capsule”, “Stress Response”, “Iron acquisition and metabolism” and “virulence and defense mechanisms”. Raw metagenomic reads were assembled into scaffolds and predicted Open Reading Frames (ORFs) were searched against metal resistance gene database (BacMet). Based on enriched genes and gene categories and search of known HMR genes we concluded the microbial community cope with HM using at least 10 different mechanisms. Copper resistance genes were more abundant in the metagenome relative to other metals and pumping metals out of the cell were more abundant relative to other HMR mechanism. Results of the present study could be very helpful in understanding of HMR mechanism used by microbial communities.

Morphological and Molecular Identification of Three Genera of the Family Heptageniidae (Ephemeroptera) from Ava Sheen Branch/ Greater Zab Tributary, North of Iraq

The aquatic Heptageniidae family of Ava-sheen branch (Greater Zab Tributary) in Duhok Governorate/ Iraq was studied. Samples were collected using Surber stream sampler to study their diagnostic morphological characteristics and molecular phylogenetic profile using a nuclear gene 16s ribosomal RNA. The morphological and molecular identification supported that the three species, Epeorus longimanus, Heptagenia elegantula and Ephemerella cornutus belong to Heptageniidae family, while the molecular results also confirmed the monophyletic origin of these three genera.

Comparing orthology methods and their performance by recapitulating patterns of eukaryotic genome evolution

Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets, or expanding the analyses to larger scales. Automated orthology inference should allow such large scale analyses, but substantial differences between orthologous groups generated by different approaches are observed.We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regards to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the Last Eukaryotic Common Ancestor’s gene content, pervasiveness of gene loss, and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other.We find that most orthology methods reconstruct a large Last Eukaryotic Common Ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large scale evaluation, the obtained orthologous groups differ vastly from one another.Availability and implementationThe data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies.SummaryWe compared multiple orthology inference methods by looking at how well they perform in recapitulating multiple observations made in eukaryotic genome evolution.Co-occurrence of proteins is predicted fairly well by most methods and all show similar behaviour when looking at loss numbers and dynamics.All the methods show imperfect overlap when compared to manually curated orthologous groups and when compared to orthologous groups of the other methods.Differences are compared between methods by looking at how the inferred orthologies represent a high-quality set of manually curated orthologous groups.We conclude that all methods behave similar when describing general patterns in eukaryotic genome evolution. However, there are large differences within the orthologies themselves, arising from how a method can differentiate between distant homology, recent duplications, or classifying orthologous groups.