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Samples from coastal tropical waters of Central Sulawesi, Bangka Island and Bawean Island in Indonesia and from the Great Barrier Reef at Fitzroy Island in Queensland, Australia were analysed for species composition of diatom assemblages with a focus on Olifantiella. Whereas samples from Fitzroy Island littoral in Australia retrieved only one species of Olifantiella, in Poso Bay, Indonesia, we observed at least six species. All established taxa were documented with light (LM) and scanning electron microscope (SEM) and principal component analysis (PCA) analysis was used to compare the species, based on the basic valve parameters of length, width, length to width ratio and striae density. A new species of the genus Olifantiella, O. gondwanensis is described from Australia. In addition, we showed the distinct nature of O. pilosella var. rhizophorae permitting to species status. Particular attention is placed on girdle bands in this genus.

Abstract Typical Quantitative Systems Pharmacology (QSP) workflows involve discussion of biology, supported by graphical diagrams, followed by construction of large Ordinary Differential Equation models. QSP Designer facilitates this process by providing enhanced graphical notation, which enables hierarchical presentation with modules and handling of combinatorial complexity with diagram node arrays. Whereas the software includes a simulation engine, a major feature is full model code generation in MATLAB, R, C, and Julia to support multiple modeling communities.

Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL) grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users) increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a web server allowing constraint based simulations of the genome scale metabolic reaction networks of E. coli, S. cerevisiae and M. tuberculosis. Conclusions Acorn is a free software package, which can be installed by research groups to create a web based environment for computer simulations of genome scale metabolic reaction networks. It facilitates shared access to models and creation of publicly available constraint based modelling resources.

Abstract Background Whilst being closely related to the model actinomycete Streptomyces coelicolor A3(2), S. lividans 66 differs from it in several significant and phenotypically observable ways, including antibiotic production. Previous comparative gene hybridization studies investigating such differences have used low-density (one probe per gene) PCR-based spotted arrays. Here we use new experimentally optimised 104,000 × 60-mer probe arrays to characterize in detail the genomic differences between wild-type S. lividans 66, a derivative industrial strain, TK24, and S. coelicolor M145. Results The high coverage and specificity (detection of three nucleotide differences) of the new microarrays used has highlighted the macroscopic genomic differences between two S. lividans strains and S. coelicolor. In a series of case studies we have validated the microarray and have identified subtle changes in genomic structure which occur in the Asp-activating adenylation domains of CDA non-ribosomal peptide synthetase genes which provides evidence of gene shuffling between these domains. We also identify single nucleotide sequence inter-species differences which exist in the actinorhodin biosynthetic gene cluster. As the glyoxylate bypass is non-functional in both S. lividans strains due to the absence of the gene encoding isocitrate lyase it is likely that the ethylmalonyl-CoA pathway functions as the alternative mechanism for the assimilation of C2 compounds. Conclusions This study provides evidence for widespread genetic recombination, rather than it being focussed at 'hotspots', suggesting that the previously proposed 'archipelago model' of genomic differences between S. coelicolor and S. lividans is unduly simplistic. The two S. lividans strains investigated differ considerably in genetic complement, with TK24 lacking 175 more genes than its wild-type parent when compared to S. coelicolor. Additionally, we confirm the presence of bldB in S. lividans and deduce that S. lividans 66 and TK24, both deficient in the glyoxylate bypass, possess an alternative metabolic mechanism for the assimilation of C2 compounds. Given that streptomycetes generally display high genetic instability it is envisaged that these high-density arrays will find application for rapid assessment of genome content (particularly amplifications/deletions) in mutational studies of S. coelicolor and related species.

Abstract Background It is quite important to simulate the metabolic changes of a cell in response to the change in culture environment and/or specific gene knockouts particularly for the purpose of application in industry. If this could be done, the cell design can be made without conducting exhaustive experiments, and one can screen out the promising candidates, proceeded by experimental verification of a select few of particular interest. Although several models have so far been proposed, most of them focus on the specific metabolic pathways. It is preferred to model the whole of the main metabolic pathways in Escherichia coli, allowing for the estimation of energy generation and cell synthesis, based on intracellular fluxes and that may be used to characterize phenotypic growth. Results In the present study, we considered the simulation of the main metabolic pathways such as glycolysis, TCA cycle, pentose phosphate (PP) pathway, and the anapleorotic pathways using enzymatic reaction models of E. coli. Once intracellular fluxes were computed by this model, the specific ATP production rate, the specific CO2 production rate, and the specific NADPH production rate could be estimated. The specific ATP production rate thus computed was used for the estimation of the specific growth rate. The CO2 production rate could be used to estimate cell yield, and the specific NADPH production rate could be used to determine the flux of the oxidative PP pathway. The batch and continuous cultivations were simulated where the changing patterns of extracellular and intra-cellular metabolite concentrations were compared with experimental data. Moreover, the effects of the knockout of such pathways as Ppc, Pck and Pyk on the metabolism were simulated. It was shown to be difficult for the cell to grow in Ppc mutant due to low concentration of OAA, while Pck mutant does not necessarily show this phenomenon. The slower growth rate of the Ppc mutant was properly estimated by taking into account the lower specific ATP production rate. In the case of Pyk mutant, the enzyme level regulation was made clear such that Pyk knockout caused PEP concentration to be up-regulated and activated Ppc, which caused the increase in MAL concentration and backed up reduced PYR through Mez, resulting in the phenotypic growth characteristics similar to the wild type. Conclusions It was shown to be useful to simulate the main metabolism of E. coli for understanding metabolic changes inside the cell in response to specific pathway gene knockouts, considering the whole main metabolic pathways. The comparison of the simulation result with the experimental data indicates that the present model could simulate the effect of the specific gene knockouts to the changes in the metabolisms to some extent.

The infertility of many couples rests on an enigmatic dysfunction of the man's sperm. To gain insight into the underlying pathomechanisms, we assessed the function of the sperm-specific multisubunit CatSper-channel complex in the sperm of almost 2,300 men undergoing a fertility workup, using a simple motility-based test. We identified a group of men with normal semen parameters but defective CatSper function. These men or couples failed to conceive naturally and upon medically assisted reproduction via intrauterine insemination and in vitro fertilization. Intracytoplasmic sperm injection (ICSI) was, ultimately, required to conceive a child. We revealed that the defective CatSper function was caused by variations in CATSPER genes. Moreover, we unveiled that CatSper-deficient human sperm were unable to undergo hyperactive motility and, therefore, failed to penetrate the egg coat. Thus, our study provides the experimental evidence that sperm hyperactivation is required for human fertilization, explaining the infertility of CatSper-deficient men and the need of ICSI for medically assisted reproduction. Finally, our study also revealed that defective CatSper function and ensuing failure to hyperactivate represents the most common cause of unexplained male infertility known thus far and that this sperm channelopathy can readily be diagnosed, enabling future evidence-based treatment of Affected couples., Introduction Infertility is on the rise, but the underlying causes still remain mostly unknown. In fact, for about a third of infertile men, semen parameters are within reference limits (normozoospermia) [...]

Abstract Immunogenicity against therapeutic proteins frequently causes attrition owing to its potential impact on pharmacokinetics, pharmacodynamics, efficacy, and safety. Predicting immunogenicity is complex because of its multifactorial drivers, including compound properties, subject characteristics, and treatment parameters. To integrate these, the Immunogenicity Simulator was developed using published, predominantly late‐stage trial data from 15 therapeutic proteins. This single‐blinded evaluation with subject‐level data from 10 further monoclonals assesses the Immunogenicity Simulator's credibility for application during the drug development process.

Abstract The purpose of the study was to evaluate the possibility of parameterizing the state of soil surface roughness (SSR) based on proximal measurements of spectral reflectance in the VIS‐NIR range, which is important for the needs of monitoring the state of soil surfaces. SSR should be constantly monitored as it provides an insight into a range of hydrological and erosive soil processes and improves the interpretation of remote sensing data. SSR and the spectral reflectance of three texturally different soils were measured under simulated rainfall in laboratory condition. The relationship between the SSR parameters and soil spectra was determined using regression random forest models. Various spectral data processing methods were tested and the best wavelengths for SSR description after rainfall were found. Two roughness indices were used to describe the SSR: Height Standard Deviation (HSD) and T3D (Tortuosity index). Although both shared a significant correlation with SSR, the T3D index demonstrated a more pronounced rainfall effect and a closer correlation with spectral data than HSD. The best determination of T3D was obtained with the raw spectra (RAW) (R2 = 0.71), as well as with spectra transformed with the baseline alignment first derivative (BA1d) method (R2 = 0.71) or the Savitzky‐Golay (SG) method (R2 = 0.69). Different wavelengths were the best SSR predictors depending on the spectral transformation method (VIPs ‐ Variable Importance in Projection). For both roughness indices, the NIR wavelengths (725–820 nm) yielded the highest VIP Score in models based on RAW spectra, while those in the VIS region (450–772 nm) were most important in models based on transformed spectra.

Abstract Background The understanding of whole genome sequences in higher eukaryotes depends to a large degree on the reliable definition of transcription units including exon/intron structures, translated open reading frames (ORFs) and flanking untranslated regions. The best currently available chicken transcript catalog is the Ensembl build based on the mappings of a relatively small number of full length cDNAs and ESTs to the genome as well as genome sequence derived in silico gene predictions. Results We use Long Serial Analysis of Gene Expression (LongSAGE) in bursal lymphocytes and the DT40 cell line to verify the quality and completeness of the annotated transcripts. 53.6% of the more than 38,000 unique SAGE tags (unitags) match to full length bursal cDNAs, the Ensembl transcript build or the genome sequence. The majority of all matching unitags show single matches to the genome, but no matches to the genome derived Ensembl transcript build. Nevertheless, most of these tags map close to the 3' boundaries of annotated Ensembl transcripts. Conclusions These results suggests that rather few genes are missing in the current Ensembl chicken transcript build, but that the 3' ends of many transcripts may not have been accurately predicted. The tags with no match in the transcript sequences can now be used to improve gene predictions, pinpoint the genomic location of entirely missed transcripts and optimize the accuracy of gene finder software.

RNA polymerase III (RNAP III) holoenzyme activity and the processing of its products have been linked to several metabolic dysfunctions in lower and higher eukaryotes. Alterations in the activity of RNAP III-driven synthesis of non-coding RNA cause extensive changes in glucose metabolism. Increased RNAP III activity in the S. cerevisiae maf1Δ strain is lethal when grown on a non-fermentable carbon source. This lethal phenotype is suppressed by reducing tRNA synthesis. Neither the cause of the lack of growth nor the underlying molecular mechanism have been deciphered, and this area has been awaiting scientific explanation for a decade. Our previous proteomics data suggested mitochondrial dysfunction in the strain. Using model mutant strains maf1Δ (with increased tRNA abundance) and rpc128-1007 (with reduced tRNA abundance), we collected data showing major changes in the TCA cycle metabolism of the mutants that explain the phenotypic observations. Based on 13C flux data and analysis of TCA enzyme activities, the present study identifies the flux constraints in the mitochondrial metabolic network. The lack of growth is associated with a decrease in TCA cycle activity and downregulation of the flux towards glutamate, aspartate and phosphoenolpyruvate (PEP), the metabolic intermediate feeding the gluconeogenic pathway. rpc128-1007, the strain that is unable to increase tRNA synthesis due to a mutation in the C128 subunit, has increased TCA cycle activity under non-fermentable conditions. To summarize, cells with non-optimal activity of RNAP III undergo substantial adaptation to a new metabolic state, which makes them vulnerable under specific growth conditions. Our results strongly suggest that balanced, non-coding RNA synthesis that is coupled to glucose signaling is a fundamental requirement to sustain a cell’s intracellular homeostasis and flexibility under changing growth conditions. The presented results provide insight into the possible role of RNAP III in the mitochondrial metabolism of other cell types.

ObjectivesTo develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.DesignAnalysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.SettingMultiple institutions that were members of international PRACTICAL consortium.ParticipantsAll consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.Main outcome measuresPrediction with hazard score of age of onset of aggressive cancer in validation set.ResultsIn the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.ConclusionsPolygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Optimal use and distribution of coronavirus disease 2019 (COVID‐19) vaccines involves adjustments of dosing. Due to the rapidly evolving pandemic, such adjustments often need to be introduced before full efficacy data are available. As demonstrated in other areas of drug development, quantitative systems pharmacology (QSP) is well placed to guide such extrapolation in a rational and timely manner. Here, we propose for the first time how QSP can be applied in the context of COVID‐19 vaccine development.

UnlabelledBreast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.SignificanceWe demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic, whereas the influenza A virus (IAV) causes seasonal epidemics and occasional pandemics. Both viruses lead to widespread infection and death. SARS-CoV-2 and the influenza virus are RNA viruses. The SARS-CoV-2 genome is an approximately 30 kb, positive sense, 5′ capped single-stranded RNA molecule. The influenza A virus genome possesses eight single-stranded negative-sense segments. The RNA secondary structure in the untranslated and coding regions is crucial in the viral replication cycle. The secondary structure within the RNA of SARS-CoV-2 and the influenza virus has been intensively studied. Because the whole of the SARS-CoV-2 and influenza virus replication cycles are dependent on RNA with no DNA intermediate, the RNA is a natural and promising target for the development of inhibitors. There are a lot of RNA-targeting strategies for regulating pathogenic RNA, such as small interfering RNA for RNA interference, antisense oligonucleotides, catalytic nucleic acids, and small molecules. In this review, we summarized the knowledge about the inhibition of SARS-CoV-2 and influenza A virus propagation by targeting their RNA secondary structure.

Among types of trinucleotide repeats, there is some disproportion in the frequency of their occurrence in the human exome. This research presents new data describing the folding and thermodynamic stability of short, tandem RNA repeats of 23 types, focusing on the rare, yet poorly analyzed ones. UV-melting experiments included the presence of PEG or potassium and magnesium ions to determine their effect on the stability of RNA repeats structures. Rare repeats predominantly stayed single-stranded but had the potential for base pairing with other partially complementary repeat tracts. A coexistence of suitably complementary repeat types in a single RNA creates opportunities for interaction in the context of the secondary structure of RNA. We searched the human transcriptome for model RNAs in which different, particularly rare trinucleotide repeats coexist and selected the GABRA4 and CHIC1 RNAs to study intramolecular interactions between the repeat tracts that they contain. In vitro secondary structure probing results showed that the UAA and UUG repeat tracts, present in GABRA4 3′ UTR, form a double helix, which separates one of its structural domains. For the RNA CHIC1 ORF fragment containing four short AGG repeat tracts and the CGU tract, we proved the formation of quadruplexes that blocked reverse transcription.