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A maize enzyme from the 2-oxoglutarate-dependent oxygenase family with unique kinetic properties, mediates resistance against pathogens and regulates senescence

In plants, salicylic acid (SA) hydroxylation regulates SA homoeostasis, playing an essential role during plant development and response to pathogens. This reaction is catalysed by SA hydroxylase enzymes, which hydroxylate SA producing 2,3-dihydroxybenzoic acid (2,3-DHBA) and/or 2,5-dihydroxybenzoic acid (2,5-DHBA). Several SA hydroxylases have recently been identified and characterised from different plant species, but no such activity has yet been reported in maize. In this work, we describe the identification and characterisation of a new SA hydroxylase in maize plants. This enzyme, with high sequence similarity to previously described SA hydroxylases from Arabidopsis and rice, converts SA into 2,5-DHBA; however, it has different kinetic properties to those of previously characterised enzymes, and it also catalysers the conversion of the flavonoid dihydroquercetin into quercetin in in vitro activity assays, suggesting that the maize enzyme may have different roles in vivo to those previously reported from other species. Despite this, ZmS5H can complement the pathogen resistance and the early senescence phenotypes of Arabidopsis s3h mutant plants. Finally, we characterised a maize mutant in the S5H gene (s5hMu) that has altered growth, senescence and increased resistance against Colletotrichum graminicola infection, showing not only alterations in SA and 2,5-DHBA but also in flavonol levels. Together, the results presented here provide evidence that SA hydroxylases in different plant species have evolved to show differences in catalytic properties that may be important to fine tune SA levels and other phenolic compounds such as flavonols, to regulate different aspects of plant development and pathogen defence.

Genome-wide association study identifies multiple loci influencing duck serum biochemical indicators in the laying period

1. Laying performance is an important economic trait in poultry. The blood is essential in transporting nutrients to the yolk and albumen and is necessary for egg formation.2. This study calculated the phenotypic relationships of duck egg quality, egg production efficiency and 22 serum parameters in the egg-laying stage. Using a variety of methodologies, a genome-wide association study (GWAS) was carried out to uncover the genetic foundations of the 22 serum biochemical markers of laying ducks.3. Spearman correlation coefficients between the egg production (226-329 per day) and the serum parameters were all weak, being less than 0.3. This analysis was done on 22 serum parameters, with total protein (TP), total triglycerides (TG), calcium (Ca) and phosphorous (P) having the highest correlation coefficients (r = 0.56-0.88). The coefficients for blood markers, such as total cholesterol (CHOL), total bilirubin (TBIL), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) varied from 0.70-0.94.4. Based on single-marker single-trait genome-wide analyses by a mixed linear model program of EMMAX, nine candidate genes were associated with enzyme traits (AST/ALT aspartate transaminase/glutamic-pyruvic transaminase, creatine kinase) and 19 candidate genes were associated with metabolism and protein-related serum parameters (glucose, total bile acid, uric acid (UA), albumin (ALB).5. The mvLMM (multivariate linear mixed model) of GEMMA software was used to carry out multiple trait integrated GWAS. Two candidate genes were found in the TP-TG-CA-P analysis and seven candidate genes in the CHOL_LDL-C_HDL-C_TBIL study. There was a high genetic correlation between the two groups.

Mechanisms of Panax Ginseng on Treating Sepsis by RNA-Seq Technology

Purpose

To explore the potential active targets and mechanisms of Panax Ginseng in the treatment of sepsis using network pharmacology and RNA-seq technology.

Patients and Methods

Patients with sepsis and healthy volunteers were collected according to SEPSIS 3.0, and their peripheral blood was used for RNA-seq analysis. The active ingredients and targets of Panax Ginseng were obtained using the TCMSP database, PPI and GO analysis were performed for disease-drug intersection targets. Then, we used Meta-analysis to screen core genes. Finally, single-cell RNA-seq was used to perform cell localization analysis on core genes.

Results

RNA-seq analysis collected 4521 sepsis-related genes, TCMSP database obtained 86 Panax Ginseng active ingredients and their 294 active targets. PPI and GO analysis showed intersection targets were closely linked, and mainly involved in cellular response to chemical stress, response to drug and molecule of bacterial origin, etc. Then, core targets, IL1B, ALOX5, BCL2 and IL4R, were sorted by Meta-analysis, and all four genes have high expression in the sepsis survivor group compared to the sepsis non-survivor group; single-cell RNA-seq revealed that IL1B was mainly localized in macrophages, ALOX5 was mainly localized in macrophages and B cells, BCL2 was mainly localized in natural killer cells, T cells and B cells, IL4R was widely distributed in immune cells. Finally, according to the correspondence between the active ingredients and targets of Panax Ginseng in TCMSP database, we found that Ginsenoside rh2 regulates the expression of IL1B, Ginsenoside rf regulates the expression of IL1B and IL4R, Kaempferol regulates the expression of ALOX5 and BCL2, and β-sitosterol regulates the expression of BCL2.

Conclusion

Ginsenoside rh2, Ginsenoside rf, Kaempferol and β-sitosterol may produce anti-sepsis effects by regulating the expression of IL1B, ALOX5, BCL2 and IL4R, thus improving the survival rate of sepsis patients.

The complete organellar genomes of the entheogenic plant Psychotria viridis (Rubiaceae), a main component of the ayahuasca brew

Psychotria viridis (Rubioideae: Rubiaceae), popularly known as chacrona, is commonly found as a shrub in the Amazon region and is well-known to produce psychoactive compounds, such as the N,N-dimethyltryptamine (DMT). Together with the liana Banisteropsis caapi, P. viridis is one of the main components of the Amerindian traditional, entheogenic beverage known as ayahuasca. In this work, we assembled and annotated the organellar genomes (ptDNA and mtDNA), presenting the first genomics resources for this species. The P. viridis ptDNA exhibits 154,106 bp, encoding all known ptDNA gene repertoire found in angiosperms. The Psychotria genus is a complex paraphyletic group, and according to phylogenomic analyses, P. viridis is nested in the Psychotrieae clade. Comparative ptDNA analyses indicate that most Rubiaceae plastomes present conserved ptDNA structures, often showing slight differences at the junction sites of the major four regions (LSC-IR-SSC). For the mitochondrion, assembly graph-based analysis supports a complex mtDNA organization, presenting at least two alternative and circular mitogenomes structures exhibiting two main repeats spanning 24 kb and 749 bp that may symmetrically isomerize the mitogenome into variable arrangements and isoforms. The circular mtDNA sequences (615,370 and 570,344 bp) encode almost all plant mitochondrial genes (except for the ccmC, rps7, rps10, rps14, rps19, rpl2 and rpl16 that appears as pseudogenes, and the absent genes sdh3, rps2, rsp4, rsp8, rps11, rpl6, and rpl10), showing slight variations related to exclusive regions, ptDNA integration, and relics of previous events of LTR-RT integration. The detection of two mitogenomes haplotypes is evidence of heteroplasmy as observed by the complex organization of the mitochondrial genome using graph-based analysis. Taken together, these results elicit the primary insights into the genome biology and evolutionary history of Psychotria viridis and may be used to aid strategies for conservation of this sacred, entheogenic species.

Improving the topology prediction of α-helical transmembrane proteins with deep transfer learning

Transmembrane proteins (TMPs) are essential for cell recognition and communication, and they serve as important drug targets in humans. Transmembrane proteins' 3D structures are critical for determining their functions and drug design but are hard to determine even by experimental methods. Although some computational methods have been developed to predict transmembrane helices (TMHs) and orientation, there is still room for improvement. Considering that the pre-trained language model can make full use of massive unlabeled protein sequences to obtain latent feature representation for TMPs and reduce the dependence on evolutionary information, we proposed DeepTMpred, which used pre-trained self-supervised language models called ESM, convolutional neural networks, attentive neural network and conditional random fields for alpha-TMP topology prediction. Compared with the current state-of-the-art tools on a non-redundant dataset of TMPs, DeepTMpred demonstrated superior predictive performance in most evaluation metrics, especially at the TMH level. Furthermore, DeepTMpred could also obtain reliable prediction results for TMPs without much evolutionary feature in a few seconds. A tutorial on how to use DeepTMpred can be found in the colab notebook (https://colab.research.google.com/github/ISYSLAB-HUST/DeepTMpred/blob/master/notebook/test.ipynb).

PROTEOMIC ANALYSIS OF TAENIA SOLIUM CYST FLUID BY SHOTGUN LC-MS/MS

Taenia solium cysts were collected from pig skeletal muscle and analyzed via a shotgun proteomic approach to identify known proteins in the cyst fluid and to explore host-parasite interactions. Cyst fluid was aseptically collected and analyzed with shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene alignment and annotation were performed using Blast2GO software followed by gene ontology analysis of the annotated proteins. The pathways were further analyzed with the Kyoto Encyclopedia of Genes and Genomes (KEGG), and a protein-protein interaction (PPI) network map was generated using STRING software. A total of 158 known proteins were identified, most of which were low-molecular-mass proteins. These proteins were mainly involved in cellular and metabolic processes, and their molecular functions were predominantly related to catalytic activity and binding functions. The pathway enrichment analysis revealed that the known proteins were mainly enriched in the PI3K-Akt and glycolysis/gluconeogenesis signaling pathways. The nodes in the PPI network mainly consisted of enzymes involved in sugar metabolism. The cyst fluid proteins screened in this study may play important roles in the interaction between the cysticerci and the host. The shotgun LC-MS/MS, gene ontology, KEGG, and PPI network map data will be used to identify and analyze the cyst fluid proteome of cysticerci, which will provide a basis for further exploration of the invasion and activities of T. solium.

Trends and Applications of Omics Technologies to Functional Characterisation of Enzymes and Protein Metabolites Produced by Fungi

Identifying and adopting industrial applications for proteins and enzymes derived from fungi strains have been at the focal point of several studies in recent times. To facilitate such studies, it is necessary that advancements and innovation in mycological and molecular characterisation are concomitant. This review aims to provide a detailed overview of the necessary steps employed in both qualitative and quantitative research using the omics technologies that are pertinent to fungi characterisation. This stems from the understanding that data provided from the functional characterisation of fungi and their metabolites is important towards the techno-economic feasibility of large-scale production of biological products. The review further describes how the functional gaps left by genomics, internal transcribe spacer (ITS) regions are addressed by transcriptomics and the various techniques and platforms utilised, including quantitive reverse transcription polymerase chain reaction (RT-qPCR), hybridisation techniques, and RNA-seq, and the insights such data provide on the effect of environmental changes on fungal enzyme production from an expressional standpoint. The review also offers information on the many available bioinformatics tools of analysis necessary for the analysis of the overwhelming data synonymous with the omics approach to fungal characterisation.

The NanoInformatics Knowledge Commons: Capturing spatial and temporal nanomaterial transformations in diverse systems

The empirical necessity for integrating informatics throughout the experimental process has become a focal point of the nano-community as we work in parallel to converge efforts for making nano-data reproducible and accessible. The NanoInformatics Knowledge Commons (NIKC) Database was designed to capture the complex relationship between nanomaterials and their environments over time in the concept of an 'Instance'. Our Instance Organizational Structure (IOS) was built to record metadata on nanomaterial transformations in an organizational structure permitting readily accessible data for broader scientific inquiry. By transforming published and on-going data into the IOS we are able to tell the full transformational journey of a nanomaterial within its experimental life cycle. The IOS structure has prepared curated data to be fully analyzed to uncover relationships between observable phenomenon and medium or nanomaterial characteristics. Essential to building the NIKC database and associated applications was incorporating the researcher's needs into every level of development. We started by centering the research question, the query, and the necessary data needed to support the question and query. The process used to create nanoinformatic tools informs usability and analytical capability. In this paper we present the NIKC database, our developmental process, and its curated contents. We also present the Collaboration Tool which was built to foster building new collaboration teams. Through these efforts we aim to: 1) elucidate the general principles that determine nanomaterial behavior in the environment; 2) identify metadata necessary to predict exposure potential and bio-uptake; and 3) identify key characterization assays that predict outcomes of interest.

Marine Bioactive Peptides in Supplements and Functional Foods - A Commercial Perspective

Many bioactive peptides have been described from marine sources and much marine biomass is still not explored or utilized in products. Marine peptides can be developed into a variety of products, and there is a significant interest in the use of bioactive peptides from marine sources for nutraceuticals or functional foods. We present here a mini-review collecting the knowledge about the value chain of bioactive peptides from marine sources used in nutraceuticals and functional foods. Many reports describe bioactive peptides from marine sources, but in order to make these available to the consumers in commercial products, it is important to connect the bioactivities associated with these peptides to commercial opportunities and possibilities. In this mini-review, we present challenges and opportunities for the commercial use of bioactive peptides in nutraceuticals and functional food products. We start the paper by introducing approaches for isolation and identification of bioactive peptides and candidates for functional foods. We further discuss market-driven innovation targeted to ensure that isolated peptides and suggested products are marketable and acceptable by targeted consumers. To increase the commercial potential and ensure the sustainability of the identified bioactive peptides and products, we discuss scalability, regulatory frameworks, production possibilities and the shift towards greener technologies. Finally, we discuss some commercial products from marine peptides within the functional food market. We discuss the placement of these products in the larger picture of the commercial sphere of functional food products from bioactive peptides.

Metabolomics and Network Pharmacology-Based Investigation into the Mechanisms Underlying the Therapeutic Effect of a New Chinese Traditional Medicine (Cui Nai Ling) on Bromocriptine-Induced Hypogalactia

As a traditional veterinary medicine to promote lactation, Cui Nai Ling (CNL) can not only increase milk supply and promote health but also improve the overall physiological function and immunity of the animals. In order to further improve CNL's effect on lactation, we have previously made a new CNL (NCNL) by adding Tetrapanacis Medulla and replacing Vaccariae Semen with fried Vaccariae Semen in CNL. We have demonstrated that the lactation-promoting effect of NCNL is better than that of CNL. However, the underlying mechanisms by which NCNL promotes lactation are unclear. In this study, we performed metabolomics, network pharmacology, and pharmacodynamic studies to explore the underlying mechanisms by which NCNL promotes lactation in rats with bromocriptine-induced hypogalactia. The results showed that NCNL significantly improved the loss of appetite in female adult rats and the weight loss of pups caused by the disorder of lactation. Biochemical analysis showed that NCNL could regulate the levels of PRL, T4, E2, Ca, UREA, GLU, ALT, AST, TCHO, and TG in serum. The pathological results showed that NCNL could promote lactation and increase the mammary gland index by improving breast acinar tissue morphology in rats with hypogalactia. Network pharmacology studies showed that NCNL promotes lactation through P13K-Akt, insulin resistance, and prolactin signaling pathways, among which the most frequently affected pathway was the P13K-Akt signaling pathway. Metabolomics studies showed that NCNL can significantly upregulate phenylalanine, tyrosine, and tryptophan biosynthesis and tyrosine metabolism pathways and downregulate cysteine and methionine metabolism pathways. NCNL can significantly increase the serum prolactin concentration, improve the glucose and lipid metabolism disorders, and regulate PI3K-Akt, insulin resistance, and prolactin pathways to affect the amino acids' metabolism in the mammary gland and ultimately exert its therapeutic effect on bromocriptine-induced postpartum hypogalactia. These findings revealed the effect and application value of NCNL on animals with postpartum hypogalactia.

Dynamics of the transcriptional landscape during human fetal testis and ovary development

STUDY QUESTION

Which transcriptional program triggers sex differentiation in bipotential gonads and downstream cellular events governing fetal testis and ovary development in humans?

SUMMARY ANSWER

The characterization of a dynamically regulated protein-coding and non-coding transcriptional landscape in developing human gonads of both sexes highlights a large number of potential key regulators that show an early sexually dimorphic expression pattern.

WHAT IS KNOWN ALREADY

Gonadal sex differentiation is orchestrated by a sexually dimorphic gene expression program in XX and XY developing fetal gonads. A comprehensive characterization of its non-coding counterpart offers promising perspectives for deciphering the molecular events underpinning gonad development and for a complete understanding of the etiology of disorders of sex development in humans.

STUDY DESIGN, SIZE, DURATION

To further investigate the protein-coding and non-coding transcriptional landscape during gonad differentiation, we used RNA-sequencing (RNA-seq) and characterized the RNA content of human fetal testis (N = 24) and ovaries (N = 24) from 6 to 17 postconceptional week (PCW), a key period in sex determination and gonad development.

PARTICIPANTS/MATERIALS, SETTING, METHODS

First trimester fetuses (6-12 PCW) and second trimester fetuses (13-14 and 17 PCW) were obtained from legally induced normally progressing terminations of pregnancy. Total RNA was extracted from whole human fetal gonads and sequenced as paired-end 2 × 50 base reads. Resulting sequences were mapped to the human genome, allowing for the assembly and quantification of corresponding transcripts.

MAIN RESULTS AND THE ROLE OF CHANCE

This RNA-seq analysis of human fetal testes and ovaries at seven key developmental stages led to the reconstruction of 22 080 transcripts differentially expressed during testicular and/or ovarian development. In addition to 8935 transcripts displaying sex-independent differential expression during gonad development, the comparison of testes and ovaries enabled the discrimination of 13 145 transcripts that show a sexually dimorphic expression profile. The latter include 1479 transcripts differentially expressed as early as 6 PCW, including 39 transcription factors, 40 long non-coding RNAs and 20 novel genes. Despite the use of stringent filtration criteria (expression cut-off of at least 1 fragment per kilobase of exon model per million reads mapped, fold change of at least 2 and false discovery rate adjusted P values of less than <1%), the possibility of assembly artifacts and of false-positive differentially expressed transcripts cannot be fully ruled out.

LARGE-SCALE DATA

Raw data files (fastq) and a searchable table (.xlss) containing information on genomic features and expression data for all refined transcripts have been submitted to the NCBI GEO under accession number GSE116278.

LIMITATIONS, REASONS FOR CAUTION

The intrinsic nature of this bulk analysis, i.e. the sequencing of transcripts from whole gonads, does not allow direct identification of the cellular origin(s) of the transcripts characterized. Potential cellular dilution effects (e.g. as a result of distinct proliferation rates in XX and XY gonads) may account for a few of the expression profiles identified as being sexually dimorphic. Finally, transcriptome alterations that would result from exposure to pre-abortive drugs cannot be completely excluded. Although we demonstrated the high quality of the sorted cell populations used for experimental validations using quantitative RT-PCR, it cannot be totally excluded that some germline expression may correspond to cell contamination by, for example, macrophages.

WIDER IMPLICATIONS OF THE FINDINGS

For the first time, this study has led to the identification of 1000 protein-coding and non-coding candidate genes showing an early, sexually dimorphic, expression pattern that have not previously been associated with sex differentiation. Collectively, these results increase our understanding of gonad development in humans, and contribute significantly to the identification of new candidate genes involved in fetal gonad differentiation. The results also provide a unique resource that may improve our understanding of the fetal origin of testicular and ovarian dysgenesis syndromes, including cryptorchidism and testicular cancers.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the French National Institute of Health and Medical Research (Inserm), the University of Rennes 1, the French School of Public Health (EHESP), the Swiss National Science Foundation [SNF n° CRS115_171007 to B.J.], the French National Research Agency [ANR n° 16-CE14-0017-02 and n° 18-CE14-0038-02 to F.C.], the Medical Research Council [MR/L010011/1 to P.A.F.] and the European Community's Seventh Framework Programme (FP7/2007-2013) [under grant agreement no 212885 to P.A.F.] and from the European Union's Horizon 2020 Research and Innovation Programme [under grant agreement no 825100 to P.A.F. and S.M.G.]. There are no competing interests related to this study.

The mwtab Python Library for RESTful Access and Enhanced Quality Control, Deposition, and Curation of the Metabolomics Workbench Data Repository

The Metabolomics Workbench (MW) is a public scientific data repository consisting of experimental data and metadata from metabolomics studies collected with mass spectroscopy (MS) and nuclear magnetic resonance (NMR) analyses. MW has been constantly evolving; updating its ‘mwTab’ text file format, adding a JavaScript Object Notation (JSON) file format, implementing a REpresentational State Transfer (REST) interface, and nearly quadrupling the number of datasets hosted on the repository within the last three years. In order to keep up with the quickly evolving state of the MW repository, the ‘mwtab’ Python library and package have been continuously updated to mirror the changes in the ‘mwTab’ and JSONized formats and contain many new enhancements including methods for interacting with the MW REST interface, enhanced format validation features, and advanced features for parsing and searching for specific metabolite data and metadata. We used the enhanced format validation features to evaluate all available datasets in MW to facilitate improved curation and FAIRness of the repository. The ‘mwtab’ Python package is now officially released as version 1.0.1 and is freely available on GitHub and the Python Package Index (PyPI) under a Clear Berkeley Software Distribution (BSD) license with documentation available on ReadTheDocs.

Dynamics of the Stool Virome in Very Early-Onset Inflammatory Bowel Disease

BACKGROUND AND AIMS

Dysbiosis of the gut microbiota is a well-known correlate of the pathogenesis of inflammatory bowel disease [IBD]. However, few studies have examined the microbiome in very early-onset [VEO] IBD, which is defined as onset of IBD before 6 years of age. Here we focus on the viral portion of the microbiome-the virome-to assess possible viral associations with disease processes, reasoning that any viruses potentially associated with IBD might grow more robustly in younger subjects, and so be more detectable.

METHODS

Virus-like particles [VLPs] were purified from stool samples collected from patients with VEO-IBD [n = 54] and healthy controls [n = 23], and characterized by DNA and RNA sequencing and VLP particle counts.

RESULTS

The total number of VLPs was not significantly different between VEO-IBD and healthy controls. For bacterial viruses, the VEO-IBD subjects were found to have a higher ratio of Caudovirales vs to Microviridae compared to healthy controls. An increase in Caudovirales was also associated with immunosuppressive therapy. For viruses infecting human cells, Anelloviridae showed higher prevalence in VEO-IBD compared to healthy controls. Within the VEO-IBD group, higher levels of Anelloviridae DNA were also positively associated with immunosuppressive treatment. To search for new viruses, short sequences enriched in VEO-IBD samples were identified, and some could be validated in an independent cohort, although none was clearly viral; this provides sequence tags to interrogate in future studies.

CONCLUSIONS

These data thus document perturbations to normal viral populations associated with VEO-IBD, and provide a biomarker-Anelloviridae DNA levels-potentially useful for reporting the effectiveness of immunosuppression.

RNA profiling of human testicular cells identifies syntenic lncRNAs associated with spermatogenesis

STUDY QUESTION

Is the noncoding transcriptional landscape during spermatogenesis conserved between human and rodents?

SUMMARY ANSWER

We identified a core group of 113 long noncoding RNAs (lncRNAs) and 20 novel genes dynamically and syntenically transcribed during spermatogenesis.

WHAT IS KNOWN ALREADY

Spermatogenesis is a complex differentiation process driven by a tightly regulated and highly specific gene expression program. Recently, several studies in various species have established that a large proportion of known lncRNAs are preferentially expressed during meiosis and spermiogenesis in a testis-specific manner.

STUDY DESIGN, SIZE, DURATION

To further investigate lncRNA expression in human spermatogenesis, we carried out a cross-species RNA profiling study using isolated testicular cells.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Human testes were obtained from post-mortem donors (N = 8, 51 years old on average) or from prostate cancer patients with no hormonal treatment (N = 9, 80 years old on average) and only patients with full spermatogenesis were used to prepare enriched populations of spermatocytes, spermatids, Leydig cells, peritubular cells and Sertoli cells. To minimize potential biases linked to inter-patient variations, RNAs from two or three donors were pooled prior to RNA-sequencing (paired-end, strand-specific). Resulting reads were mapped to the human genome, allowing for assembly and quantification of corresponding transcripts.

MAIN RESULTS AND THE ROLE OF CHANCE

Our RNA-sequencing analysis of pools of isolated human testicular cells enabled us to reconstruct over 25 000 transcripts. Among them we identified thousands of lncRNAs, as well as many previously unidentified genes (novel unannotated transcripts) that share many properties of lncRNAs. Of note is that although noncoding genes showed much lower synteny than protein-coding ones, a significant fraction of syntenic lncRNAs displayed conserved expression during spermatogenesis.

LARGE SCALE DATA

Raw data files (fastq) and a searchable table (.xlss) containing information on genomic features and expression data for all refined transcripts have been submitted to the NCBI Gene Expression Omnibus under accession number GSE74896.

LIMITATIONS, REASONS FOR CAUTION

Isolation procedures may alter the physiological state of testicular cells, especially for somatic cells, leading to substantial changes at the transcriptome level. We therefore cross-validated our findings with three previously published transcriptomic analyses of human spermatogenesis. Despite the use of stringent filtration criteria, i.e. expression cut-off of at least three fragments per kilobase of exon model per million reads mapped, fold-change of at least three and false discovery rate adjusted P-values of less than <1%, the possibility of assembly artifacts and false-positive transcripts cannot be fully ruled out.

WIDER IMPLICATIONS OF THE FINDINGS

For the first time, this study has led to the identification of a large number of conserved germline-associated lncRNAs that are potentially important for spermatogenesis and sexual reproduction. In addition to further substantiating the basis of the human testicular physiology, our study provides new candidate genes for male infertility of genetic origin. This is likely to be relevant for identifying interesting diagnostic and prognostic biomarkers and also potential novel therapeutic targets for male contraception.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by l'Institut national de la santé et de la recherche médicale (Inserm); l'Université de Rennes 1; l'Ecole des hautes études en santé publique (EHESP); INERIS-STORM to B.J. [N 10028NN]; Rennes Métropole 'Défis scientifiques émergents' to F.C (2011) and A.D.R (2013). The authors have no competing financial interests.

Genome-wide association study of shank length and diameter at different developmental stages in chicken F2 resource population

In order to find SNPs and genes affecting shank traits, we performed a GWAS in a chicken F2 population of eight half-sib families from five hatches derived from reciprocal crosses between an Arian fast-growing line and an Urmia indigenous slow-growing chicken. A total of 308 birds were genotyped using a 60K chicken SNP chip. Shank traits including shank length and diameter were measured weekly from birth to 12 weeks of age. A generalized linear model and a compressed mixed linear model (CMLM) were applied to achieve the significant regions. The value of the average genomic inflation factor (λ statistic) of the CMLM model (0.99) indicated that the CMLM was more effective than the generalized linear model in controlling the population structure. The genes surrounding significant SNPs and their biological functions were identified from NCBI, Ensembl and UniProt databases. The results indicated that 12 SNPs at 12 different ages passed the LD-adjusted 5% Bonferroni significant threshold. Two SNPs were significant for shank length and nine SNPs were significant for shank diameter. The significant SNPs were located near to or inside 11 candidate genes. The results showed that a number of significant SNPs in the middle ages were higher than the rest. The MXRA8 gene was related to the significant SNP at week 1 that promotes proliferation of growth plate chondrocytes. A unique SNP of Gga_rs16689511 located on chicken Z chromosome within the LOC101747628 gene was related to shank length at three different ages of birds (weeks 8, 9 and 11). The significant SNPs for shank diameter were found at weeks 4 and 7 (four and five SNPs respectively). The identifications of SNPs and genes here could contribute to a better understanding of the genetic control of shank traits in chicken.

The Wild Mouse (Micromys minutus): Reservoir of a Novel Campylobacter jejuni Strain

Campylobacter jejuni is one of the most common zoonotic pathogens worldwide. Although the main sources of human C. jejuni infection are livestock, wildlife can also affect C. jejuni transmission in humans. However, it remains unclear whether wild mice harbor C. jejuni and are involved in the "environment-wildlife-livestock-human" transmission cycle of C. jejuni in humans. Here, we characterized C. jejuni from wild mice and identified genetic traces of wild mouse-derived C. jejuni in other hosts using a traditional approach, along with comparative genomics. We captured 115 wild mice (49 Mus musculus and 66 Micromys minutus) without any clinical symptoms from 22 sesame fields in Korea over 2 years. Among them, M. minutus were typically caught in remote areas of human houses and C. jejuni was solely isolated from M. minutus (42/66, 63.6%). We identified a single clone (MLST ST-8388) in all 42 C. jejuni isolates, which had not been previously reported, and all isolates had the same virulence/survival-factor profile, except for the plasmid-mediated virB11 gene. No isolates exhibited antibiotic resistance, either in phenotypic and genetic terms. Comparative-genomic analysis and MST revealed that C. jejuni derived from M. minutus (strain SCJK2) was not genetically related to those derived from other sources (registered in the NCBI genome database and PubMLST database). Therefore, we hypothesize that C. jejuni from M. minutus is a normal component of the gut flora following adaptation to the gastro-intestinal tract. Furthermore, M. minutus-derived C. jejuni had different ancestral lineages from those derived from other sources, and there was a low chance of C. jejuni transmission from M. minutus to humans/livestock because of their habitat. In conclusion, M. minutus may be a potential reservoir for a novel C. jejuni, which is genetically different from those of other sources, but may not be involved in the transmission of C. jejuni to other hosts, including humans and livestock. This study could form the basis for further studies focused on understanding the transmission cycle of C. jejuni, as well as other zoonotic pathogens originating from wild mice.

A Coordinated Approach by Public Domain Bioinformatics Resources to Aid the Fight Against Alzheimer's Disease Through Expert Curation of Key Protein Targets

BACKGROUND

The analysis and interpretation of data generated from patient-derived clinical samples relies on access to high-quality bioinformatics resources. These are maintained and updated by expert curators extracting knowledge from unstructured biological data described in free-text journal articles and converting this into more structured, computationally-accessible forms. This enables analyses such as functional enrichment of sets of genes/proteins using the Gene Ontology, and makes the searching of data more productive by managing issues such as gene/protein name synonyms, identifier mapping, and data quality.

OBJECTIVE

To undertake a coordinated annotation update of key public-domain resources to better support Alzheimer's disease research.

METHODS

We have systematically identified target proteins critical to disease process, in part by accessing informed input from the clinical research community.

RESULTS

Data from 954 papers have been added to the UniProtKB, Gene Ontology, and the International Molecular Exchange Consortium (IMEx) databases, with 299 human proteins and 279 orthologs updated in UniProtKB. 745 binary interactions were added to the IMEx human molecular interaction dataset.

CONCLUSION

This represents a significant enhancement in the expert curated data pertinent to Alzheimer's disease available in a number of biomedical databases. Relevant protein entries have been updated in UniProtKB and concomitantly in the Gene Ontology. Molecular interaction networks have been significantly extended in the IMEx Consortium dataset and a set of reference protein complexes created. All the resources described are open-source and freely available to the research community and we provide examples of how these data could be exploited by researchers.

The Terrestrial Carnivorous Plant Utricularia reniformis Sheds Light on Environmental and Life-Form Genome Plasticity

Utricularia belongs to Lentibulariaceae, a widespread family of carnivorous plants that possess ultra-small and highly dynamic nuclear genomes. It has been shown that the Lentibulariaceae genomes have been shaped by transposable elements expansion and loss, and multiple rounds of whole-genome duplications (WGD), making the family a platform for evolutionary and comparative genomics studies. To explore the evolution of Utricularia, we estimated the chromosome number and genome size, as well as sequenced the terrestrial bladderwort Utricularia reniformis (2n = 40, 1C = 317.1-Mpb). Here, we report a high quality 304 Mb draft genome, with a scaffold NG50 of 466-Kb, a BUSCO completeness of 87.8%, and 42,582 predicted genes. Compared to the smaller and aquatic U. gibba genome (101 Mb) that has a 32% repetitive sequence, the U. reniformis genome is highly repetitive (56%). The structural differences between the two genomes are the result of distinct fractionation and rearrangements after WGD, and massive proliferation of LTR-retrotransposons. Moreover, GO enrichment analyses suggest an ongoing gene birth-death-innovation process occurring among the tandem duplicated genes, shaping the evolution of carnivory-associated functions. We also identified unique patterns of developmentally related genes that support the terrestrial life-form and body plan of U. reniformis. Collectively, our results provided additional insights into the evolution of the plastic and specialized Lentibulariaceae genomes.

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens

Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request.

Accessing Expert-Curated Pharmacological Data in the IUPHAR/BPS Guide to PHARMACOLOGY

The IUPHAR/BPS Guide to PHARMACOLOGY is an expert-curated, open-access database of information on drug targets and the substances that act on them. This unit describes the procedures for searching and downloading ligand-target binding data and for finding detailed annotations and the most relevant literature. The database includes concise overviews of the properties of 1,700 data-supported human drug targets and related proteins, divided into families, and 9,000 small molecule and peptide experimental ligands and approved drugs that bind to those targets. More detailed descriptions of pharmacology, function, and pathophysiology are provided for a subset of important targets. The information is reviewed regularly by expert subcommittees of the IUPHAR Committee on Receptor Nomenclature and Drug Classification. A new immunopharmacology portal has recently been added, drawing together data on immunological targets, ligands, cell types, processes and diseases. The data are available for download and can be accessed computationally via Web services. © 2018 by John Wiley & Sons, Inc.

A combined computational strategy of sequence and structural analysis predicts the existence of a functional eicosanoid pathway in Drosophila melanogaster

This study reports on a putative eicosanoid biosynthesis pathway in Drosophila melanogaster and challenges the currently held view that mechanistic routes to synthesize eicosanoid or eicosanoid-like biolipids do not exist in insects, since to date, putative fly homologs of most mammalian enzymes have not been identified. Here we use systematic and comprehensive bioinformatics approaches to identify most of the mammalian eicosanoid synthesis enzymes. Sensitive sequence analysis techniques identified candidate Drosophila enzymes that share low global sequence identities with their human counterparts. Twenty Drosophila candidates were selected based upon (a) sequence identity with human enzymes of the cyclooxygenase and lipoxygenase branches, (b) similar domain architecture and structural conservation of the catalytic domain, and (c) presence of potentially equivalent functional residues. Evaluation of full-length structural models for these 20 top-scoring Drosophila candidates revealed a surprising degree of conservation in their overall folds and potential analogs for functional residues in all 20 enzymes. Although we were unable to identify any suitable candidate for lipoxygenase enzymes, we report structural homology models of three fly cyclooxygenases. Our findings predict that the D. melanogaster genome likely codes for one or more pathways for eicosanoid or eicosanoid-like biolipid synthesis. Our study suggests that classical and/or novel eicosanoids mediators must regulate biological functions in insects–predictions that can be tested with the power of Drosophila genetics. Such experimental analysis of eicosanoid biology in a simple model organism will have high relevance to human development and health.

Draft Genome Sequence of the Plant Growth-Promoting Rhizobacterium Pseudomonas protegens Strain BNJ-SS-45, Isolated from Rhizosphere Soil of Wheat (Triticum aestivum)

Here, we present the draft genome sequence of Pseudomonas protegens strain BNJ-SS-45, which was isolated from wheat rhizosphere. The genome is assembled with 7,116,445 bp with a GC content of 63.34% consisting of 32 scaffolds. The genome is useful in prediction of secondary metabolites, particularly rhizoxin, pyoverdine, and bacteriocin.

Signal-anchor sequences are an essential factor for the Golgi-plasma membrane localization of type II membrane proteins

Despite studies of the mechanism underlying the intracellular localization of membrane proteins, the specific mechanisms by which each membrane protein localizes to the endoplasmic reticulum, Golgi apparatus, and plasma membrane in the secretory pathway are unclear. In this study, a discriminant analysis of endoplasmic reticulum, Golgi apparatus and plasma membrane-localized type II membrane proteins was performed using a position-specific scoring matrix derived from the amino acid propensity of the sequences around signal-anchors. The possibility that the sequence around the signal-anchor is a factor for identifying each localization group was evaluated. The discrimination accuracy between the Golgi apparatus and plasma membrane-localized type II membrane proteins was as high as 90%, indicating that, in addition to other factors, the sequence around signal-anchor is an essential component of the selection mechanism for the Golgi and plasma membrane localization. These results may improve the use of membrane proteins for drug delivery and therapeutic applications.

Divergent and convergent evolution of housekeeping genes in human-pig lineage

Housekeeping genes are ubiquitously expressed and maintain basic cellular functions across tissue/cell type conditions. The present study aimed to develop a set of pig housekeeping genes and compare the structure, evolution and function of housekeeping genes in the human–pig lineage. By using RNA sequencing data, we identified 3,136 pig housekeeping genes. Compared with human housekeeping genes, we found that pig housekeeping genes were longer and subjected to slightly weaker purifying selection pressure and faster neutral evolution. Common housekeeping genes, shared by the two species, achieve stronger purifying selection than species-specific genes. However, pig- and human-specific housekeeping genes have similar functions. Some species-specific housekeeping genes have evolved independently to form similar protein active sites or structure, such as the classical catalytic serine–histidine–aspartate triad, implying that they have converged for maintaining the basic cellular function, which allows them to adapt to the environment. Human and pig housekeeping genes have varied structures and gene lists, but they have converged to maintain basic cellular functions essential for the existence of a cell, regardless of its specific role in the species. The results of our study shed light on the evolutionary dynamics of housekeeping genes.

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

Identification and characterization of sodium and chloride-dependent gamma-aminobutyric acid (GABA) transporters from eukaryotic pathogens as a potential drug target

We explored 285 completed eukaryotic pathogen genomes for GABA transporter proteins as effective chemotherapy targets. We identified 8 GABA proteins that spread across 4 phyla with 5 different pathogen species; Eimeria mitis Houghton, Neospora caninum Liverpool, S. mansoni, S. haematobium and Trichinella spiralis. Sub-cellular localization prediction revealed that these proteins are integral membrane and are mostly insoluble. It is found that about 81% of these proteins are non-crystallizable and 15% are crystallizable. Transmembrane helices predictions show that the GABA transporters have 10, 11, 12 and 14 TMHs with 15, 23, 31 and 11%, respectively. It is further observed that most of these GABA transporters are from several parasites`genomes.

PTS: a pharmaceutical target seeker

Identifying protein targets for a bioactive compound is critical in drug discovery. Molecular similarity is a main approach to fish drug targets, and is based upon an axiom that similar compounds may have the same targets. The molecular structural similarity of a compound and the ligand of a known target can be gauged in topological (2D), steric (3D) or static (pharmacophoric) metric. The topologic metric is fast, but unable to represent steric and static profile of a bioactive compound. Steric and static metrics reflect the shape properties of a compound if its structure were experimentally obtained, and could be unreliable if they were based upon the putative conformation data. In this paper, we report a pharmaceutical target seeker (PTS), which searches protein targets for a bioactive compound based upon the static and steric shape comparison by comparing a compound structure against the experimental ligand structure. Especially, the crystal structures of active compounds were taken into similarity calculation and the predicted targets can be filtered according to multi activity thresholds. PTS has a pharmaceutical target database that contains approximately 250 000 ligands annotated with about 2300 protein targets. A visualization tool is provided for a user to examine the result.

Database URL: http://www.rcdd.org.cn/PTS

Rat Genome and Model Resources

Rats remain a major model for studying disease mechanisms and discovery, validation, and testing of new compounds to improve human health. The rat’s value continues to grow as indicated by the more than 1.4 million publications (second to human) at PubMed documenting important discoveries using this model. Advanced sequencing technologies, genome modification techniques, and the development of embryonic stem cell protocols ensure the rat remains an important mammalian model for disease studies. The 2004 release of the reference genome has been followed by the production of complete genomes for more than two dozen individual strains utilizing NextGen sequencing technologies; their analyses have identified over 80 million variants. This explosion in genomic data has been accompanied by the ability to selectively edit the rat genome, leading to hundreds of new strains through multiple technologies. A number of resources have been developed to provide investigators with access to precision rat models, comprehensive datasets, and sophisticated software tools necessary for their research. Those profiled here include the Rat Genome Database, PhenoGen, Gene Editing Rat Resource Center, Rat Resource and Research Center, and the National BioResource Project for the Rat in Japan.

Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.

Patterns of Genomic Variation in the Opportunistic Pathogen Candida glabrata Suggest the Existence of Mating and a Secondary Association with Humans

Candida glabrata is an opportunistic fungal pathogen that ranks as the second most common cause of systemic candidiasis. Despite its genus name, this yeast is more closely related to the model yeast Saccharomyces cerevisiae than to other Candida pathogens, and hence its ability to infect humans is thought to have emerged independently. Moreover, C. glabrata has all the necessary genes to undergo a sexual cycle but is considered an asexual organism due to the lack of direct evidence of sexual reproduction. To reconstruct the recent evolution of this pathogen and find footprints of sexual reproduction, we assessed genomic and phenotypic variation across 33 globally distributed C. glabrata isolates. We cataloged extensive copy-number variation, which particularly affects genes encoding cell-wall-associated proteins, including adhesins. The observed level of genetic variation in C. glabrata is significantly higher than that found in Candida albicans. This variation is structured into seven deeply divergent clades, which show recent geographical dispersion and large within-clade genomic and phenotypic differences. We show compelling evidence of recent admixture between differentiated lineages and of purifying selection on mating genes, which provides the first evidence for the existence of an active sexual cycle in this yeast. Altogether, our data point to a recent global spread of previously genetically isolated populations and suggest that humans are only a secondary niche for this yeast.

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Candida glabrata strains can be clustered into highly genetically divergent clades

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Genetic structure suggests a recent global spread of previously isolated populations

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The existence of sex in C. glabrata is supported by genomic footprints of selection

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Mating-type switching occurs in C. glabrata natural populations but is error prone

PixelDB: Protein-peptide complexes annotated with structural conservation of the peptide binding mode

PixelDB, the Peptide Exosite Location Database, compiles 1966 non-redundant, high-resolution structures of protein-peptide complexes filtered to minimize the impact of crystal packing on peptide conformation. The database is organized to facilitate study of structurally conserved versus non-conserved elements of protein-peptide engagement. PixelDB clusters complexes based on the structural similarity of the peptide-binding protein, and by comparing complexes within a cluster highlights examples of domains that engage peptides using more than one binding mode. PixelDB also identifies conserved peptide core structural motifs characteristic of each binding mode. Peptide regions that flank core motifs often make non-structurally conserved interactions with the protein surface in regions we call exosites. Many examples establish that exosite contacts can be important for enhancing protein binding and interaction specificity. PixelDB provides a resource for computational and structural biologists to study, model, and predict core-motif and exosite-contacting peptide interactions. PixelDB is available to the community without restriction in a convenient flat-file format with accompanying visualization tools.

LPI-NRLMF: lncRNA-protein interaction prediction by neighborhood regularized logistic matrix factorization

LncRNA-protein interactions play important roles in many important cellular processes including signaling, transcriptional regulation, and even the generation and progression of complex diseases. However, experimental methods for determining proteins bound by a specific lncRNA remain expensive, difficult and time-consuming, and only a few theoretical approaches are available for predicting potential lncRNA-protein associations. In this study, we developed a novel matrix factorization computational approach to uncover lncRNA-protein relationships, namely lncRNA-protein interactions prediction by neighborhood regularized logistic matrix factorization (LPI-NRLMF). Moreover, it is a semi-supervised and does not need negative samples. As a result, new model obtained reliable performance in the leave-one-out cross validation (the AUC of 0.9025 and AUPR of 0.6924), which significantly improved the prediction performance of previous models. Furthermore, the case study demonstrated that many lncRNA-protein interactions predicted by our method can be successfully confirmed by experiments. It is anticipated that LPI-NRLMF could serve as a useful resource for potential lncRNA-protein association identification.

Overview on the Biochemical Potential of Filamentous Fungi to Degrade Pharmaceutical Compounds

Pharmaceuticals represent an immense business with increased demand due to intensive livestock raising and an aging human population, which guarantee the quality of human life and well-being. However, the development of removal technologies for these compounds is not keeping pace with the swift increase in their use. Pharmaceuticals constitute a potential risk group of multiclass chemicals of increasing concern since they are extremely frequent in all environments and have started to exhibit negative effects on micro- and macro-fauna as well as on human health. In this context, fungi are known to be extremely diverse and poorly studied microorganisms despite being well suited for bioremediation processes, taking into account their metabolic and physiological characteristics for the transformation of even highly toxic xenobiotic compounds. Increasing studies indicate that fungi can transform many structures of pharmaceutical compounds, including anti-inflammatories, β-blockers, and antibiotics. This is possible due to different mechanisms in combination with the extracellular and intracellular enzymes, which have broad of biotechnological applications. Thus, fungi and their enzymes could represent a promising tool to deal with this environmental problem. Here, we review the studies performed on pharmaceutical compounds biodegradation by the great diversity of these eukaryotes. We examine the state of the art of the current application of the Basidiomycota division, best known in this field, as well as the assembly of novel biodegradation pathways within the Ascomycota division and the Mucoromycotina subdivision from the standpoint of shared enzymatic systems, particularly for the cytochrome P450 superfamily of enzymes, which appear to be the key enzymes in these catabolic processes. Finally, we discuss the latest advances in the field of genetic engineering for their further application.

Prolonged K+ deficiency increases intracellular ATP, cell cycle arrest and cell death in renal tubular cells

BACKGROUND

Chronic potassium (K⁺) deficiency can cause renal damage namely hypokalemic nephropathy with unclear pathogenic mechanisms. In the present study, we investigated expression and functional alterations in renal tubular cells induced by prolonged K⁺ deficiency.

METHODS

MDCK cells were maintained in normal-K⁺ (CNK) (K⁺=5.3mmol/L), low-K⁺ (CLK) (K⁺=2.5mmol/L), or K⁺-depleted (CKD) (K⁺=0mmol/L) medium for 10days (n=5 independent cultures/condition). Differentially expressed proteins were identified by a proteomics approach followed by various functional assays.

RESULTS

Proteomic analysis revealed 46 proteins whose levels significantly differed among groups. The proteomic data were confirmed by Western blotting. Gene Ontology (GO) classification and protein network analysis revealed that majority of the altered proteins participated in metabolic process, whereas the rest involved in cellular component organization/biogenesis, cellular process (e.g., cell cycle, regulation of cell death), response to stress, and signal transduction. Interestingly, ATP measurement revealed that intracellular ATP production was increased in CLK and maximum in CKD. Flow cytometry showed cell cycle arrest at S-phase and G2/M-phase in CLK and CKD, respectively, consistent with cell proliferation and growth assays, which showed modest and marked degrees of delayed growth and prolonged doubling time in CLK and CKD, respectively. Cell death quantification also revealed modest and marked degrees of increased cell death in CLK and CKD, respectively.

CONCLUSIONS

In conclusion, prolonged K⁺ deficiency increased intracellular ATP, cell cycle arrest and cell death in renal tubular cells, which might be responsible for mechanisms underlying the development of hypokalemic nephropathy.

Recent advances and clinical insights into the use of proteomics in the study of atherosclerosis

INTRODUCTION

The application of new proteomics methods may help to identify new diagnostic/predictive molecular markers in an attempt to improve the clinical management of atherosclerosis. Areas covered: Technological advances in proteomics have enhanced its sensitivity and multiplexing capacity, as well as the possibility of studying protein interactions and tissue structure. These advances will help us better understand the molecular mechanisms at play in atherosclerosis as a biological system. Moreover, this should help identify new predictive/diagnostic biomarkers and therapeutic targets that may facilitate effective risk stratification and early diagnosis, with the ensuing rapid implementation of treatment. This review provides a comprehensive overview of the novel methods in proteomics, including state-of-the-art techniques, novel biological samples and applications for the study of atherosclerosis. Expert commentary: Collaboration between clinicians and researchers is crucial to further validate and introduce new molecular markers to manage atherosclerosis that are identified using the most up to date proteomic approaches.

Proteomics Research in Cardiovascular Medicine and Biomarker Discovery

Proteomics is a systems physiology discipline to address the large-scale characterization of protein species within a biological system, be it a cell, a tissue, a body biofluid, an organism, or a cohort population. Building on advances from chemical analytical platforms (e.g., mass spectrometry and other technologies), proteomics approaches have contributed powerful applications in cardiovascular biomedicine, most notably in: 1) the discovery of circulating protein biomarkers of heart diseases from plasma samples; and 2) the identification of disease mechanisms and potential therapeutic targets in cardiovascular tissues, in both preclinical models and translational studies. Contemporary proteomics investigations offer powerful means to simultaneously examine tens of thousands of proteins in various samples, and understand their molecular phenotypes in health and disease. This concise review introduces study design considerations, example applications and use cases, as well as interpretation and analysis of proteomics data in cardiovascular biomedicine.

From the research laboratory to the database: the Caenorhabditis elegans kinome in UniProtKB

Protein kinases form one of the largest protein families and are found in all species, from viruses to humans. They catalyze the reversible phosphorylation of proteins, often modifying their activity and localization. They are implicated in virtually all cellular processes and are one of the most intensively studied protein families. In recent years, they have become key therapeutic targets in drug development as natural mutations affecting kinase genes are the cause of many diseases. The vast amount of data contained in the primary literature and across a variety of biological data collections highlights the need for a repository where this information is stored in a concise and easily accessible manner. The UniProt Knowledgebase meets this need by providing the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequence and functional information. Here, we describe the expert curation process for kinases, focusing on the Caenorhabditis elegans kinome. The C. elegans kinome is composed of 438 kinases and almost half of them have been functionally characterized, highlighting that C. elegans is a valuable and versatile model organism to understand the role of kinases in biological processes.

A two-step discriminated method to identify thermophilic proteins

Improving thermostability of an enzyme can accelerate the relevant chemical reaction. Thus, the analysis and prediction of thermophilic proteins are conducive to protein engineering and enzyme design. In this study, a novel method based on two-step discrimination was proposed to distinguish between thermophilic and non-thermophilic proteins. The model was rigorously benchmarked on an objective dataset including 915 thermophilic proteins and 793 non-thermophilic proteins. Results showed that the overall accuracy of our method is 94.44% in 5-fold cross-validation, which is higher than those of other published methods. We believe that the two-step discriminated strategy will become a promising method in the relevant field of protein bioinformatics.

The Genomic Impact of DNA CpG Methylation on Gene Expression; Relationships in Prostate Cancer

The process of DNA CpG methylation has been extensively investigated for over 50 years and revealed associations between changing methylation status of CpG islands and gene expression. As a result, DNA CpG methylation is implicated in the control of gene expression in developmental and homeostasis processes, as well as being a cancer-driver mechanism. The development of genome-wide technologies and sophisticated statistical analytical approaches has ushered in an era of widespread analyses, for example in the cancer arena, of the relationships between altered DNA CpG methylation, gene expression, and tumor status. The remarkable increase in the volume of such genomic data, for example, through investigators from the Cancer Genome Atlas (TCGA), has allowed dissection of the relationships between DNA CpG methylation density and distribution, gene expression, and tumor outcome. In this manner, it is now possible to test that the genome-wide correlations are measurable between changes in DNA CpG methylation and gene expression. Perhaps surprisingly is that these associations can only be detected for hundreds, but not thousands, of genes, and the direction of the correlations are both positive and negative. This, perhaps, suggests that CpG methylation events in cancer systems can act as disease drivers but the effects are possibly more restricted than suspected. Additionally, the positive and negative correlations suggest direct and indirect events and an incomplete understanding. Within the prostate cancer TCGA cohort, we examined the relationships between expression of genes that control DNA methylation, known targets of DNA methylation and tumor status. This revealed that genes that control the synthesis of S-adenosyl-l-methionine (SAM) associate with altered expression of DNA methylation targets in a subset of aggressive tumors.

Draft Genome Sequence of the Plant Growth-Promoting Rhizobacterium Pseudomonas fluorescens Strain CREA-C16 Isolated from Pea (Pisum sativum L.) Rhizosphere

Herein, we report the draft genome sequence of Pseudomonas fluorescens strain CREA-C16, a plant growth-promoting rhizobacterium that was isolated from the rhizosphere of Pisum sativum L. plants. The genome sequence is ~6 Mb in size, with a G+C content of 60.1%, and includes 4,457 candidate protein-encoding genes.

Cytogenetic Resources and Information

The main databases devoted stricto sensu to cancer cytogenetics are the "Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer" ( http://cgap.nci.nih.gov/Chromosomes/Mitelman ), the "Atlas of Genetics and Cytogenetics in Oncology and Haematology" ( http://atlasgeneticsoncology.org ), and COSMIC ( http://cancer.sanger.ac.uk/cosmic ).However, being a complex multistep process, cancer cytogenetics are broadened to "cytogenomics," with complementary resources on: general databases (nucleic acid and protein sequences databases; cartography browsers: GenBank, RefSeq, UCSC, Ensembl, UniProtKB, and Entrez Gene), cancer genomic portals associated with recent international integrated programs, such as TCGA or ICGC, other fusion genes databases, array CGH databases, copy number variation databases, and mutation databases. Other resources such as the International System for Human Cytogenomic Nomenclature (ISCN), the International Classification of Diseases for Oncology (ICD-O), and the Human Gene Nomenclature Database (HGNC) allow a common language.Data within the scientific/medical community should be freely available. However, most of the institutional stakeholders are now gradually disengaging, and well-known databases are forced to beg or to disappear (which may happen!).

Selected Bioinformatic Tools and MS (MALDI-TOF, PMF) Techniques Used in the Strategy for the Identification of Oat Proteins After 2-DE

Computer analysis of protein maps obtained from the separation of proteins with two-dimensional polyacrylamide gel electrophoresis (2-DE), in combination with mass spectrometry (MS) analysis and selected bioinformatic tools is used in the strategy for the identification of oat proteins. In proteomic research the most often used MS technique is the combination of ion sources: matrix-assisted laser desorption/ionization (MALDI) and the analyzer of the time of flight (TOF), i.e., MALDI-TOF MS.This chapter describes the possibilities of the use of selected bioinformatic tools (UniProtKB database, ProtParam, Compute pI/MW programs) for initial identification of separated oat proteins (especially prolamin fractions) with the 2-DE technique. Also the procedure of preparation of samples obtained from cut out protein spots for analysis with the MALDI-TOF MS and peptide mass fingerprinting (PMF) technique is presented.Among oat prolamins separated with the 2-DE technique (see Chapter 17 ), 13 protein spots are considered to be the most characteristic (range of MW 27.0-34.6 kDa, pI 5.7-7.6) for this fraction of proteins. Among them there are four protein spots (MW 27.0-28.0 kDa) and two spots (MW 31.4-32.1 kDa) which can correspond to avenins (Accession numbers (AC) in UniProtKB: L0L5I0, I4EP88, I4EP64, L0L4I8 and F2Q9W5, L0L6J0, respectively).

SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations

The SUBcellular location database for Arabidopsis proteins (SUBA4, http://suba.live) is a comprehensive collection of manually curated published data sets of large-scale subcellular proteomics, fluorescent protein visualization, protein-protein interaction (PPI) as well as subcellular targeting calls from 22 prediction programs. SUBA4 contains an additional 35 568 localizations totalling more than 60 000 experimental protein location claims as well as 37 new suborganellar localization categories. The experimental PPI data has been expanded to 26 327 PPI pairs including 856 PPI localizations from experimental fluorescent visualizations. The new SUBA4 user interface enables users to choose quickly from the filter categories: ‘subcellular location’, ‘protein properties’, ‘protein–protein interaction’ and ‘affiliations’ to build complex queries. This allows substantial expansion of search parameters into 80 annotation types comprising 1 150 204 new annotations to study metadata associated with subcellular localization. The ‘BLAST’ tab contains a sequence alignment tool to enable a sequence fragment from any species to find the closest match in Arabidopsis and retrieve data on subcellular location. Using the location consensus SUBAcon, the SUBA4 toolbox delivers three novel data services allowing interactive analysis of user data to provide relative compartmental protein abundances and proximity relationship analysis of PPI and coexpression partners from a submitted list of Arabidopsis gene identifiers.

Alternative Splicing May Not Be the Key to Proteome Complexity

Alternative splicing is commonly believed to be a major source of cellular protein diversity. However, although many thousands of alternatively spliced transcripts are routinely detected in RNA-seq studies, reliable large-scale mass spectrometry-based proteomics analyses identify only a small fraction of annotated alternative isoforms. The clearest finding from proteomics experiments is that most human genes have a single main protein isoform, while those alternative isoforms that are identified tend to be the most biologically plausible: those with the most cross-species conservation and those that do not compromise functional domains. Indeed, most alternative exons do not seem to be under selective pressure, suggesting that a large majority of predicted alternative transcripts may not even be translated into proteins.