bluuebunny/crossref_metadata_2025 huggingface dataset:
Manipulating and elucidating mitochondrial gene expression with engineered proteins
Authors: Wallis Christopher P. , Scott Louis H. , Filipovska Aleksandra , Rackham Oliver
Published: December 2019

Many conventional, modern genome engineering tools cannot be used to study mitochondrial genetics due to the unusual structure and physiology of the mitochondrial genome. Here, we review a number of newly developed, synthetic biology-based approaches for altering levels of mutant mammalian mitochondrial DNA and mitochondrial RNAs, including transcription activator-like effector nucleases, zinc finger nucleases and engineered RNA-binding proteins. These approaches allow researchers to manipulate and visualize mitochondrial processes and may provide future therapeutics.

This article is part of the theme issue ‘Linking the mitochondrial genotype to phenotype: a complex endeavour’.
Mapping and editing animal mitochondrial genomes: can we overcome the challenges?
Authors: Klucnika Anna , Ma Hansong
Published: December 2019

The animal mitochondrial genome, although small, can have a big impact on health and disease. Non-pathogenic sequence variation among mitochondrial DNA (mtDNA) haplotypes influences traits including fertility, healthspan and lifespan, whereas pathogenic mutations are linked to incurable mitochondrial diseases and other complex conditions like ageing, diabetes, cancer and neurodegeneration. However, we know very little about how mtDNA genetic variation contributes to phenotypic differences. Infrequent recombination, the multicopy nature and nucleic acid-impenetrable membranes present significant challenges that hamper our ability to precisely map mtDNA variants responsible for traits, and to genetically modify mtDNA so that we can isolate specific mutants and characterize their biochemical and physiological consequences. Here, we summarize the past struggles and efforts in developing systems to map and edit mtDNA. We also assess the future of performing forward and reverse genetic studies on animal mitochondrial genomes.

This article is part of the theme issue ‘Linking the mitochondrial genotype to phenotype: a complex endeavour’.
Data-driven prediction of genetic interactions in Candida glabrata
Authors: Invergo Brandon , Ames Ryan , Usher Jane
Published: December 2019

The rapid acquisition of drug resistance by Candida glabrata has placed an increased burden on health systems. Combination therapies, which apply multiple known compounds, can thwart the compensatory behaviours that lead to drug resistance and can open therapeutic avenues that were not previously available. Genetic interactions, in which the loss of a pair of genes has a stronger effect than the loss of either of the genes alone, can be useful in identifying targets for combination therapy. However, the number of possible interactions is immense while experimentally establishing a genetic interaction is non-trivial. We are developing a method for predicting genetic interactions in C. glabrata as a means to prioritize the experimental validation of interactions and combination therapies. The method applies machine-learning techniques to infer genetic interactions from diverse data in C. glabrata and from other yeast species, such as coexpression, protein-protein interactions and coevolution. We are establishing the method by building a model for Saccharomyces cerevisiae to validate against the large-scale genetic interaction data available for that species. This model will then integrated with C. glabrata-specific data, validated against known genetic interactions, and used to produce novel predictions for further characterisation in the lab.
Topology-driven protein-protein interaction network analysis detects genetic sub-networks regulating reproductive capacity
Authors: Kumar Tarun , Blondel Leo , Extavour Cassandra G.
Published: December 2019

Understanding the genetic regulation of organ structure is a fundamental problem in developmental biology. Here, we use egg-producing structures of insect ovaries, called ovarioles, to deduce systems-level gene regulatory relationships from quantitative functional genetic analysis. We previously showed that Hippo signalling, a conserved regulator of animal organ size, regulates ovariole number inDrosophila melanogaster. To comprehensively determine how Hippo signalling interacts with other pathways in this regulation, we screened all known signalling pathway genes, and identified Hpo-dependent and Hpo-independent signalling requirements. Network analysis of known protein-protein interactions among screen results identified independent gene regulatory sub-networks regulating one or both of ovariole number and egg laying. These sub-networks predict involvement of previously uncharacterised genes with higher accuracy than the original candidate screen. This shows that network analysis combining functional genetic and large-scale interaction data can predict function of novel genes regulating development.
Machine Learning Predicts New Anti-CRISPR Proteins
Authors: Eitzinger Simon , Asif Amina , Watters Kyle E. , Iavarone Anthony T. , Knott Gavin J. , Doudna Jennifer A. , Afsar Minhas Fayyaz ul Amir
Published: December 2019

The increasing use of CRISPR-Cas9 in medicine, agriculture and synthetic biology has accelerated the drive to discover new CRISPR-Cas inhibitors as potential mechanisms of control for gene editing applications. Many such anti-CRISPRs have been found in mobile genetic elements that disable the CRISPR-Cas adaptive immune system. However, comparing all currently known anti-CRISPRs does not reveal a shared set of properties that can be used for facile bioinformatic identification of new anti-CRISPR families. Here, we describe AcRanker, a machine learning based method for identifying new potential anti-CRISPRs directly from proteomes using protein sequence information only. Using a training set of known anti-CRISPRs, we built a model based on XGBoost ranking and extensively benchmarked it through non-redundant cross-validation and external validation. We then applied AcRanker to predict candidate anti-CRISPRs from self-targeting bacterial genomes and discovered two previously unknown anti-CRISPRs: AcrllA16 (ML1) and AcrIIA17 (ML8). We show that AcrIIA16 strongly inhibits Streptococcus iniae Cas9 (SinCas9) and weakly inhibits Streptococcus pyogenes Cas9 (SpyCas9). We also show that AcrIIA17 inhibits both SpyCas9 and SauCas9 with low potency. The addition of AcRanker to the anti-CRISPR discovery toolkit allows researchers to directly rank potential anti-CRISPR candidate genes for increased speed in testing and validation of new anti-CRISPRs. A web server implementation for AcRanker is available online at http://acranker.pythonanywhere.com/.
Discovery of functional gene markers of bacteria for monitoring hydrocarbon pollution in the marine environment - a metatranscriptomics approach
Authors: Knapik Kamila , Bagi Andrea , Krolicka Adriana , Baussant Thierry
Published: December 2019

The use of natural marine bacteria as “oil sensors” for the detection of pollution events can be suggested as a novel way of monitoring oil occurrence at sea. Nucleic acid-based devices generically called genosensors are emerging as potentially promising tools forin situdetection of specific microbial marker genes suited for that purpose. Functional marker genes are particularly interesting as targets for oil-related genosensing but their identification remains a challenge. Here, seawater samples, collected in tanks with oil addition mimicking a realistic oil spill scenario, were filtered and archived by the Environmental Sample Processor (ESP), a fully robotized genosensor, and the samples were then used for post-retrieval metatranscriptomic analysis. After extraction, RNA from ESP-archived samples at start, day 4 and day 7 of the experiment was used for sequencing. Metatranscriptomics revealed that several KEGG pathways were significantly enriched in samples exposed to oil. However, these pathways were highly expressed also in the non-oil-exposed water samples, most likely as a result of the release of natural organic matter from decaying phytoplankton. Temporary peaks of aliphatic alcohol and aldehyde dehydrogenases and monoaromatic ring-degrading enzymes (e.g.ben,box, anddmpclusters) were observed on day 4 in both control and oil tanks. Few alkane 1-monooxygenase genes were upregulated on oil, mostly transcribed by familiesPorticoccaceaeandRhodobacteraceae, together with aromatic ring-hydroxylating dioxygenases, mostly transcribed byRhodobacteraceae. Few transcripts from obligate hydrocarbonoclastic genera ofAlcanivorax,OleispiraandCycloclasticus, were significantly enriched in the oil-treated tank in comparison to control, and these were mostly transporters and genes involved in nitrogen and phosphorous acquisition. This study highlights the importance of seasonality,i.e., phytoplankton occurrence and senescence leading to organic compound release which can be used preferentially by bacteria over oil compounds, delaying the latter process. As a result, such seasonal effect can reduce the sensitivity of genosensing tools employing bacterial functional genes to sense oil. A better understanding of the use of natural organic matter by bacteria involved in oil-biodegradation is needed to develop an array of functional markers enabling the rapid and specificin situdetection of anthropogenic pollution.
Mechanisms underlying higher order interactions: from quantitative definitions to ecological processes
Authors: Kleinhesselink Andrew R. , Kraft Nathan J.B. , Levine Jonathan M.
Published: December 2019

When species simultaneously compete with two or more species of competitor, higher order interactions (HOIs) can lead to emergent properties not present when species interact in isolated pairs. In order to extend ecological theory to multi-competitor communities, ecologists must develop a practical and general definition for HOIs that can be applied to a wide range of competition models. In this paper we propose a definition for HOIs and outline a set of criteria for testing whether a model has or does not have HOIs. These criteria are valuable for empirical ecologists in need of clarity when discussing HOIs in empirical data. We also provide thorough discussion of how our definition compares with previous definitions of HOIs and interaction modification in the literature. In the second part of the paper we demonstrate the steps required for a rigorous test of HOIs in empirical data. To do this we simulate resource competition between three annual plant species which differ in phenology. We then fit phenomenological competition models to the outcome of simulated competition and use these to test for the presence of HOIs. In our simulations, we find the strength of HOIs varies with phenology: species that grow later experience stronger HOIs than earlier growing species. Our simulation shows how HOIs could emerge in ecosystems where resource availability and individual size change rapidly throughout the course of the growing season and where there are differences in the timing of resource acquisition between competitors.
Three complete genome sequences of Penguin megrivirus from ornithogenic soil, Adelie penguin and Weddell seal of Antarctica
Authors: Aasdev Ashutosh , Mishra Anamika , Nair Manoj , Pawar Satyam D , Dubey Chandan K , Bhatia Sandeep , Dastidar Prabir G , Singh Vijendra Pal , Raut Ashwin Ashok
Published: December 2019

We report the complete genome sequences of Penguin megriviruses from three different sources from Antarctica namely feces of Adelie penguin, feces of Weddell seal and ornithogenic soil. Phylogenetic analysis indicates the prevalence of very similar viruses in different sources of Antarctic environment. These genome sequences aid to understand the evolution of megriviruses in Antarctic ecology and reveal their place in global megrivirus phylogeny.
The Collaborative Cross Graphical Genome
Authors: Su Hang , Chen Ziwei , Rao Jaytheert , Najarian Maya , Shorter John , Pardo Manuel de Villena Fernando , McMillan Leonard
Published: December 2019

The mouse reference is one of the most widely used and accurately assembled mammalian genomes, and is the foundation for a wide range of bioinformatics and genetics tools. However, it represents the genomic organization of a single inbred mouse strain. Recently, inexpensive and fast genome sequencing has enabled the assembly of other common mouse strains at a quality approaching that of the reference. However, using these alternative assemblies in standard genomics analysis pipelines presents significant challenges. It has been suggested that a pangenome reference assembly, which incorporates multiple genomes into a single representation, are the path forward, but there are few standards for, or instances of practical pangenome representations suitable for large eukaryotic genomes. We present a pragmatic graph-based pangenome representation as a genomic resource for the widely-used recombinant-inbred mouse genetic reference population known as the Collaborative Cross (CC) and its eight founder genomes. Our pangenome representation leverages existing standards for genomic sequence representations with backward-compatible extensions to describe graph topology and genome-specific annotations along paths. It packs 83 mouse genomes (8 founders + 75 CC strains) into a single graph representation that captures important notions relating genomes such as identity-by-descent and highly variable genomic regions. The introduction of special anchor nodes with sequence content provides a valid coordinate framework that divides large eukaryotic genomes into homologous segments and addresses most of the graph-based position reference issues. Parallel edges between anchors place variants within a context that facilitates orthogonal genome comparison and visualization. Furthermore, our graph structure allows annotations to be placed in multiple genomic contexts and simplifies their maintenance as the assembly improves. The CC reference pangenome provides an open framework for new tool chain development and analysis.
Conditioning a collective avoidance response in rummy-nose tetra
Authors: Lecheval Valentin , Hemelrijk Charlotte K. , Theraulaz Guy
Published: December 2019

We develop an experimental method to induce controlled and local perturbations in a group of fish. Using the paradigm of the shuttle box we condition aversive escape reactions in groups of rummy-nose tetra (Hemigrammus rhodostomus) in response to a green light. Our experiments suggest that aversive conditioning can (i) be used successfully in this schooling species, (ii) trigger collective escape reactions and (iii) be transferred from the training set-up to a new environment. These results are discussed in the context of propagation of information among group members in reaction to external stimuli such as perturbations mimicking sudden changes in the environment, e.g. predator attack.
Mechanistic models of signaling pathways deconvolute the functional landscape of glioblastoma at single cell resolution
Authors: Falco Matías M. , Peña-Chilet María , Loucera Carlos , Hidalgo Marta R. , Dopazo Joaquín
Published: December 2019

The rapid development of single cell RNA-sequencing (scRNA-seq) technologies is revealing an unexpectedly large degree of heterogeneity in gene expression levels across the different cells that compose the same tissue sample. However, little is known on the functional consequences of this heterogeneity and the contribution of individual cell-fate decisions to the collective behavior of the tissues these cells are part of. Mechanistic models of signaling pathways have already proven to be useful tools for understanding relevant aspects of cell functionality. Here we propose to use this mechanistic modeling strategy to deconvolute the complexity of the functional behavior of a tissue by dissecting it into the individual functional landscapes of its component cells by using a single-cell RNA-seq experiment of glioblastoma cells. This mechanistic modeling analysis revealed a high degree of heterogeneity at the scale of signaling circuits, suggesting the existence of a complex functional landscape at single cell level. Different clusters of neoplastic glioblastoma cells have been characterized according to their differences in signaling circuit activity profiles, which only partly overlap with the conventional glioblastoma subtype classification. The activity of signaling circuits that trigger cell functionalities which can easily be assimilated to cancer hallmarks reveals different functional strategies with different degrees of aggressiveness followed by any of the clusters.

In addition, mechanistic modeling allows simulating the effect of interventions on the components of the signaling circuits, such as drug inhibitions. Thus, effects of drug inhibitions at single cell level can be dissected, revealing for the first time the mechanisms that individual cells use to avoid the effect of a targeted therapy which explain why and how a small proportion of cells display, in fact, different degrees of resistance to the treatment. The results presented here strongly suggest that mechanistic modeling at single cell level not only allows uncovering the molecular mechanisms of the tumor progression but also can predict the success of a treatment and can contribute to a better definition of therapeutic targets in the future.
Glutamine Deprivation Regulates the Origin and Function of Cancer Cell Exosomes
Authors: Fan Shih-Jung , Kroeger Benjamin , Marie Pauline P. , Bridges Esther M. , Mason John D. , McCormick Kristie , Zois Christos , Sheldon Helen , Alham Nasullah Khalid , Johnson Errin , Ellis Matthew , Stefana M. Irina , Mendes Cláudia C. , Wainwright S. Mark , Cunningham Christopher , Hamdy Freddie C. , Morris John F. , Harris Adrian L. , Wilson Clive , Goberdhan Deborah C. I.
Published: December 2019

Exosomes are secreted extracellular vesicles (EVs) carrying diverse cargos, which can modulate recipient cell behaviour. They are thought to derive from intraluminal vesicles formed in late endosomal multivesicular bodies (MVBs). An alternate exosome formation mechanism, which is conserved from fly to human, is described here, with exosomes carrying unique cargos, including the GTPase Rab11, generated in Rab11-positive recycling endosomal MVBs. Release of these exosomes from cancer cells is increased by reducing Akt/mechanistic Target of Rapamycin (mTORC1) signalling or depleting the key metabolic substrate glutamine, which diverts membrane flux through recycling endosomes. The resulting vesicles promote tumour cell proliferation and turnover, and modulate blood vessel networks in xenograft mouse modelsin vivo. Their growth-promoting activity, which is also observedin vitro, is Rab11a-dependent, involves ERK-MAPK-signalling and is inhibited by antibodies against Amphiregulin, an EGFR ligand concentrated on these vesicles. Therefore, glutamine depletion or mTORC1 inhibition stimulates release of Rab11a-exosomes with pro-tumorigenic functions, which we propose promote stress-induced tumour adaptation.
Minimized double guide RNA libraries enable scale-limited CRISPR/Cas9 screens
Authors: Peets Elin Madli , Crepaldi Luca , Zhou Yan , Allen Felicity , Elmentaite Rasa , Noell Guillaume , Turner Gemma , Iyer Vivek , Parts Leopold
Published: December 2019

Genetic screens based on CRISPR/Cas technology are a powerful tool for understanding cellular phenotypes. However, the coverage and replicate requirements result in large experiment sizes, which are limiting when samples are scarce, or the protocols are expensive and laborious. Here, we present an approach to reduce the scale of genome-wide perturbation screens up to fivefold without sacrificing performance. To do so, we deliver two randomly paired gRNAs into each cell, and rely on recent advances in gRNA design, as well as availability of gRNA effect measurements, to reduce the number of gRNAs per gene. We designed a human genome-wide library that has effective size of 30,000 constructs, yet targets each gene with three gRNAs. Our minimized double guide RNA library gives similar results to a standard single gRNA one, but using substantially fewer cells. We demonstrate that genome-wide screens can be optimized in a demanding model of induced pluripotent stem cells, reducing reagent cost 70% per replicate compared to conventional approach, while retaining high performance. The screen design and the reduction in scale it provides will enable functional genomics experiments across many possible combinations of environments and genetic backgrounds, as well as in hard to obtain and culture primary cells.
Distinct life histories impact dikaryotic genome evolution in the rust fungus Puccinia striiformis causing stripe rust in wheat
Authors: Schwessinger Benjamin , Chen Yan-Jun , Tien Richard , Vogt Josef Korbinian , Sperschneider Jana , Nagar Ramawatar , McMullan Mark , Sicheritz-Ponten Thomas , Sørensen Chris K. , Hovmøller Mogens Støvring , Rathjen John P. , Justesen Annemarie Fejer
Published: December 2019

Stripe rust of wheat, caused by the obligate biotrophic fungus Puccinia striiformis f. sp. tritici, is a major threat to wheat production world-wide with an estimated yearly loss of US $1 billion. The recent advances in long-read sequencing technologies and tailored-assembly algorithms enabled us to disentangle the two haploid genomes of Pst. This provides us with haplotype-specific information at a whole-genome level. Exploiting this novel information, we perform whole genome comparative genomics of two P. striiformis f. sp. tritici isolates with contrasting life histories. We compare one isolate of the old European lineage (PstS0), which has been asexual for over 50 years, and a Warrior isolate (PstS7 lineage) from a novel incursion into Europe in 2011 from a sexual population in the Himalayan region. This comparison provides evidence that long-term asexual evolution leads to genome expansion, accumulation of transposable elements, and increased heterozygosity at the single nucleotide, structural and allele levels. At the whole genome level, candidate effectors are not compartmentalized and do not exhibit reduced levels of synteny. Yet we were able to identify two subsets of candidate effector populations. About 70% of candidate effectors are invariant between the two isolates while 30% are hypervariable. The latter might be involved in host adaptation on wheat and explain the different phenotypes of the two isolates. Overall this detailed comparative analysis of two haplotype-aware assemblies of P. striiformis f. sp. tritici are the first steps in understanding the evolution of dikaryotic rust fungi at a whole genome level.
TORC1 regulates the transcriptional response to glucose and developmental cycle via the Tap42-Sit4-Rrd1/2 pathway in Saccharomyces cerevisiae
Authors: Alfatah Mohammad , Wong Jin Huei , Krishnan Vidhya Gomathi , Lee Yong Cheow , Sin Quan Feng , Goh Corinna Jie Hui , Kong Kiat Whye , Hoon Shawn , Arumugam Prakash
Published: December 2019

Target of Rapamycin Complex 1 (TORC1) is a highly conserved eukaryotic protein complex that couples the presence of growth factors and nutrients in the environment with cellular proliferation. TORC1 is primarily implicated in linking amino acid levels with cellular growth in yeast and mammals. Although glucose deprivation has been shown to cause TORC1 inactivation in yeast, the precise role of TORC1 in glucose signaling and the underlying mechanisms remain unclear. In this paper, we demonstrate that the presence of glucose in the growth medium is both necessary and sufficient for TORC1 activation. TORC1 activity increases upon addition of glucose to yeast cells growing in a non-fermentable carbon source. Conversely, shifting yeast cells from glucose to a non-fermentable carbon source reduces TORC1 activity. Analysis of transcriptomic data revealed that glucose and TORC1 co-regulate about 27% (1668/6004) of yeast genes. We demonstrate that TORC1 orchestrates the expression of glucose-response genes mainly via the Tap42-Sit4-Rrd1/Rrd2 pathway. To confirm TORC1’s role in glucose-signaling, we tested its role in spore germination, a glucose-dependent developmental state transition in yeast. TORC1 regulates the glucose-responsive genes during spore germination and inhibition of TORC1 blocks spore germination. We propose that a regulatory loop that involves activation of TORC1 by glucose and regulation of glucose-responsive genes by TORC1, mediates nutritional control of growth and development in yeast.
Stepwise autophosphorylation regulates biased agonism of the insulin receptor
Authors: Yunn Na-Oh , Park Mangeun , Noh Jungeun , Ryu Sung Ho
Published: December 2019

Insulin is a key regulator of energy metabolism in peripheral tissues but also functions as a growth factor. Insulin binding to the insulin receptor (IR) leads to autophosphorylation of intracellular tyrosine residues, which simultaneously initiates a multitude of signals and functions. In contrast, some artificial (non-insulin) ligands for the IR result in biased agonism, selectively activating the PI3K/AKT pathway and metabolic effects without activating mitogen-activated protein kinase (MAPK) pathway and mitogenic effects. However, the precise mechanism of biased agonism at the receptor level remains unclear. The biased agonist IR-A48 aptamer selectively induces mono-phosphorylation of Tyr1150 residue (m-pY1150) in the kinase domain of IR. Hence, we hypothesized that IR autophosphorylation is a stepwise process in which formation of m-pY1150 represents an intermediate step. To explore this idea, we used hybrid receptors in which insulin can bind only one of the two binding sites of the dimeric receptor. Asymmetric insulin binding selectively induced symmetric m-pY1150 in both kinase domains. Moreover, the juxtamembrane domain, which interacts with the kinase domain, restricted the full activation of IR, and symmetric m-pY1150 played a crucial role in the rearrangement of intracellular domains to release this restriction. Our findings demonstrate that the symmetry of insulin binding to a dimeric receptor determines the stepwise autophosphorylation of IR. Furthermore, considering that the degree of ligand symmetry on a receptor depends mainly on ligand concentration, our results suggest that IR may play metabolic-biased roles in peripheral tissues dependent on local insulin concentrations.
Pan-organ model integration of metabolic and regulatory processes in type 1 diabetes
Authors: Ben Guebila Marouen , Thiele Ines
Published: December 2019

Type 1 diabetes mellitus (T1D) is a systemic disease triggered by a local autoimmune inflammatory reaction in insulin-producing cells that disrupts the glucose-insulin-glucagon system and induces organ-wide, long-term effects on glycolytic and nonglycolytic processes. Mathematical modeling of the whole-body regulatory bihormonal system has helped to identify intervention points to ensure better control of T1D but was limited to a coarse-grained representation of metabolism. To extend the depiction of T1D, we developed a whole-body model using a novel integrative modeling framework that links organ-specific regulation and metabolism. The developed framework allowed the correct prediction of disrupted metabolic processes in T1D, highlighted pathophysiological processes common with neurodegenerative disorders, and suggested calcium channel blockers as potential adjuvants for diabetes control. Additionally, the model predicted the occurrence of insulin-dependent rewiring of interorgan crosstalk. Moreover, a simulation of a population of virtual patients allowed an assessment of the impact of inter and intraindividual variability on insulin treatment and the implications for clinical outcomes. In particular, GLUT4 was suggested as a potential pharmacogenomic regulator of intraindividual insulin efficacy. Taken together, the organ-resolved, dynamic model may pave the way for a better understanding of human pathology and model-based design of precise allopathic strategies.
Experimental and stochastic models of melanoma T-cell therapy define impact of subclone fitness on selection of antigen loss variants
Authors: Glodde Nicole , Kraut Anna , van den Boorn-Konijnenberg Debby , Vadder Saskia , Kreten Florian , Schmid-Burgk Jonathan L. , Aymans Pia , Echelmeyer Kai , Rumpf Martin , Landsberg Jennifer , Bald Tobias , Tüting Thomas , Bovier Anton , Hölzel Michael
Published: December 2019

Antigen loss is a key mechanism how tumor cells escape from T-cell immunotherapy. Using a mouse model of melanoma we directly compared antigen downregulation by phenotypic adaptation with genetically hardwired antigen loss. Unexpectedly, genetic ablation of Pmel, the melanocyte differentiation antigen targeted by adoptively transferred CD8+T-cells, impaired melanoma cell growth in untreated tumors due to competitive pressure exerted by the bulk wild-type population. This established an evolutionary scenario, where T-cell immunotherapy imposed a dynamic fitness switch on wild-type melanoma cells and antigen loss variants, which resulted in highly variable enrichment of the latter in recurrent tumors. Stochastic simulations by an individual-based continuous-time Markov process suggested variable fitness of subclones within the antigen loss variant population as the most likely cause, which was validated experimentally. In summary, we provide a framework to better understand how subclone heterogeneity in tumors influences immune selection of genetic antigen loss variants through stochastic events.
Predicting cancer origins with a DNA methylation-based deep neural network model
Authors: Zheng Chunlei , Xu Rong
Published: December 2019

Cancer origin determination combined with site-specific treatment of metastatic cancer patients is critical to improve patient outcomes. Existing pathology and gene expression-based techniques often have limited performance. In this study, we developed a deep neural network (DNN)-based classifier for cancer origin prediction using DNA methylation data of 7,339 patients of 18 different cancer origins from The Cancer Genome Atlas (TCGA). This DNN model was evaluated using four strategies: (1) when evaluated by 10-fold cross-validation, it achieved an overall specificity of 99.72% (95% CI 99.69%-99.75%) and sensitivity of 92.59% (95% CI 91.87%-93.30%); (2) when tested on hold-out testing data of 1,468 patients, the model had an overall specificity of 99.83% and sensitivity of 95.95%; (3) when tested on 143 metastasized cancer patients (12 cancer origins), the model achieved an overall specificity of 99.47% and sensitivity of 95.95%; and (4) when tested on an independent dataset of 581 samples (10 cancer origins), the model achieved overall specificity of 99.91% and sensitivity of 93.43%. Compared to existing pathology and gene expression-based techniques, the DNA methylation-based DNN classifier showed higher performance and had the unique advantage of easy implementation in clinical settings.
Detecting Operons in Bacterial Genomes via Visual Representation Learning
Authors: Assaf Rida , Xia Fangfang , Stevens Rick
Published: December 2019

Contiguous genes in prokaryotes are often arranged into operons. Detecting operons plays a critical role in inferring gene functionality and regulatory networks. Human experts annotate operons by visually inspecting gene neighborhoods across pileups of related genomes. These visual representations capture the inter-genic distance, strand direction, gene size, functional relatedness, and gene neighborhood conservation, which are the most prominent operon features mentioned in the literature. By studying these features, an expert can then decide whether a genomic region is part of an operon. We propose a deep learning based method named Operon Hunter that uses visual representations of genomic fragments to make operon predictions. Using transfer learning and data augmentation techniques facilitates leveraging the powerful neural networks trained on image datasets by re-training them on a more limited dataset of extensively validated operons. Our method outperforms the previously reported state-of-the-art tools, especially when it comes to predicting full operons and their boundaries accurately. Furthermore, our approach makes it possible to visually identify the features influencing the network’s decisions to be subsequently cross-checked by human experts.
Identifying Novel Targets by using Drug-binding Site Signature: A Case Study of Kinase Inhibitors
Authors: Naveed Hammad , Reglin Corinna , Schubert Thomas , Gao Xin , Arold Stefan T. , Maitland Michael L.
Published: December 2019

Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to the mechanism-independent effects of these drugs. Identifying these mechanism-independent interactions could improve drug safety and support drug repurposing. We have developed “iDTPnd”, a computational approach for large-scale discovery of novel targets for known drugs. For a given drug, we construct a positive and a negative structural signature that captures the weakly conserved structural features of drug binding sites. To facilitate assessment of unintended targets iDTPnd also provides a docking-based interaction score and its statistical significance. We were able to confirm the interaction of sorafenib, imatinib, dasatinib, sunitinib, and pazopanib with their known targets at a sensitivity and specificity of 52% and 55% respectively. We have validated 10 predicted novel targets, usingin vitroexperiments. Our results suggest that proteins other than kinases, such as nuclear receptors, cytochrome P450 or MHC Class I molecules can also be physiologically relevant targets of kinase inhibitors. Our method is general and broadly applicable for the identification of protein-small molecule interactions, when sufficient drug-target 3D data are available.
Detecting Protein Antigens in Sodium Dodecyl Sulfate-Polyacrylamide Gels
Authors: Greenfield Edward A. , DeCaprio James , Brahmandam Mohan
Published: December 2019

In some cases, a native protein can be isolated in its pure form from cell lysates or tissue preparation using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Antigens purified this way often induce good antibody responses. After electrophoresis, the band of protein of interest must be located in the gel. A variety of identification methods can be used, all of which are designed to avoid excessive fixation of the protein in the gel matrix. The choice of method depends partly on the abundance of the polypeptide. Three methods are commonly used: (1) staining side strips cut from the edge of the gel, (2) light staining of the gel itself, and (3) locating the band by radioactive labeling of the antigen. Staining strips of the gel cut from its sides avoids the need to fix the gel. When isolating abundant proteins that are well separated from other bands, staining side strips is a useful method. If the protein is not abundant or is located close to a contaminating band making a clean excision difficult, use one of the other staining methods. If the protein is reasonably abundant, then a light staining of the proteins in the gel with Coomassie Blue G will permit localization without fixing. Alternatively, the bands in the gel can be visualized by immersing the gel in sodium acetate or copper chloride. If the protein is radiolabeled with 125I, 32P, or 35S, then use an autoradiogram as a template to excise the band of interest.
Preparing Protein Antigens from Sodium Dodecyl Sulfate-Polyacrylamide Gels for Immunization
Authors: Greenfield Edward A. , DeCaprio James , Brahmandam Mohan
Published: December 2019

Some native proteins can be isolated in pure form from cell lysates or tissue preparation using SDS-polyacrylamide gel electrophoresis (SDS-PAGE). Antigens purified this way often induce good antibody responses. There are many different ways to process a gel fragment containing the protein of interest for injection. Such samples can be processed into small pieces and then injected, either by fragmenting the gel by passing it repeatedly through a syringe, or drying the entire gel slice and grinding it into a powder. Injections using the whole gel fragment should only be used with larger animals such as rabbits. For mice or other small animals, electroelution or electrophoretic transfer of the protein should be used to prepare the protein for injection. In the latter method, the protein is transferred to a suitable membrane, such as nitrocellulose or PVDF. The location of the desired protein is identified by staining, and the protein band is then cut from the surrounding membrane, minced, and dissolved in a small amount of dimethyl sulfoxide before subcutaneous injection into the animal.
Easy Transformation of Escherichia coli: Nanoparticle-Mediated Transformation
Authors: Green Michael R. , Sambrook Joseph
Published: December 2019

In this protocol, a colloidal solution containing mineral nanofibers is mixed with Escherichia coli and plasmid DNA and plated immediately on the appropriate selective plates. Sliding frictional forces, created when the bacteria are spread with a polystyrene stir stick across the surface of the agar, may result in penetration of the bacteria by the mineral fibers with its adherent cargo of DNA. The number of transformants increases during the first 60 sec of exposure to the mineral fiber:DNA complex and then reaches a plateau of ∼1 × 106 to 2 × 106 transformants/milligrams of DNA. Although not highly efficient, the method is very simple.
Airline safety management system issues: a practitioner’s perspective
Authors: Chaves Filipe
Published: December 2019

Purpose

This study aims to introduce the reader to some problems faced by safety practitioners operating within an airline safety department, particularly risk assessment subjectivity, and processing of flight data monitoring events. In doing so, it attempts to propose solutions to these issues.

Design/methodology/approach

Quality management tools, including six sigma, in combination with flight data monitoring, are proposed as a solution to the issues identified.

Findings

The proposed solutions reduce the subjectivity of some risk assessments and help airlines to efficiently process flight data monitoring events.

Research limitations/implications

This paper presents a two-part case study of how these issues have been dealt with by an airline. However, as demonstrated by the literature review, there seems to exist further advanced methods, some of them still in a developmental stage, to deal more effectively with the problems discussed.

Originality/value

This study is particularly directed and more valuable to small-scale airlines. These are more susceptible to the lack of resources needed to implement advanced approaches into the safety management system, but still want to adopt a systematic way of conducting business. Furthermore, it highlights common issues faced by safety practitioners in airlines and should hopefully stimulate the discussion around the topic and promote other academics/practitioners to share viable solutions.
A comprehensive assessment process for children with autism spectrum disorders
Authors: Di Renzo Magda , Guerriero Viviana , Petrillo Massimiliano , Racinaro Lidia , Vanadia Elena , Bianchi di Castelbianco Federico
Published: December 2019

Purpose

The assessment of Autism Spectrum Disorders (ASD) in childhood has two essential aspects: the identification of the risk (under 30 months of age) and the definition of a diagnosis that takes into account its core areas as well as further non-specific aspects. The purpose of this paper is to present an approach that considers the combination of clinical evaluation with the use of tools that analyse the various levels of the child’s functioning as fundamental.

Design/methodology/approach

The comprehensive assessment at the Institute of Ortofonologia in Rome provides the ADOS-2 and the Leiter-R for the evaluation of the symptomatology, the severity level, the non-verbal cognitive functioning and the fluid reasoning; the TCE and the UOI are used to identify, respectively, the child’s emotional skills and the ability to understand the intentions of others, as precursors of the theory of mind. Within this assessment, the Brief-P, the Short Sensory Profile and the RBS are also included for the evaluation of executive functions, sensory pattern and of restricted and repetitive behaviours, as observed by parents.

Findings

How to define a reliable development profile, which allows to plan a specific intervention calibrated on the potential of the child and on his development trajectory, is described. Two clinical cases are also presented.

Originality/value

The entire process is aimed both at a detailed assessment of the child’s functioning and at identifying a specific therapeutic project and predictive factors for achieving an optimal outcome.
Mining the treasure of palm leaf manuscripts through information retrieval techniques
Authors: Singh Bhupendra , Ahuja Neelu Jyoti
Published: December 2019

Purpose

This paper aims to popularize information retrieval from palm leaf manuscripts among computer scientists to make available the guidance of the age-old heritage in shaping the future.

Design/methodology/approach

With computer technology penetrating every aspect of life, information retrieval algorithms can be exploited to help build a system which can dig into the ocean of knowledge from these manuscripts.

Findings

The knowledge in them covers all aspects of life. Be it religious beliefs, literature, science, mathematics, or any other. However, due to discontinuation of practice of copying their content on fresh leaves, they now possess a fragile life which needs to be preserved at the earliest. The modern means of digitization can help in their preservation.

Research limitations

The Government of India and other organizations are doing commendable job of preserving and safeguarding country’s heritage and age-old knowledge system through the movement of digitization. In the years to come, the agonizing problem of manuscripts degradation will be eradicated completely. However, next when it will come to mining the knowledge treasure out of these manuscripts, we would be confronted with another helpless situation.

Practical implications

The digitization process would capture the manuscripts from present physical palm leaf to digital image form by clicking high-quality pictures. All the text in a palm leaf will be available in the form of images, but on these images, a simple search for any word would not be possible.

Originality/value

Working towards mining the treasure of knowledge from the palm leaf manuscripts, hordes of challenges have been outlined. Over and above the problem of preventing decay to palm leaf manuscripts is the challenge of deciphering text, image analysis, information retrieval and search. Search is further associated with issues of meaningful and useful extraction through semantic analysis. This paper advocates the dire need for systematic research to be undertaken in this field opening up avenues for past knowledge to guide future prospects in several domains.
Gaps between competence and importance of employability skills: evidence from Malaysia
Authors: Kenayathulla Husaina Banu , Ahmad Nor Aziah , Idris Abdul Rahman
Published: December 2019

Purpose

The purpose of this paper is to identify the gaps between the importance perceived and the competence gained by the hospitality students in terms of the employability skills.

Design/methodology/approach

Questionnaires were distributed to 841 hospitality students in five regions in Malaysia. Descriptive and inferential statistics were used to analyze the data.

Findings

The findings show that there are significant differences between importance perceived and competence attained in teamwork, leadership, basic, technical skills and ethical skills. Additionally, the finding of this study indicates that the culinary and bakery students perceive that they are not given adequate exposure to possess such skills. It is important to ensure that graduates are equipped with the twenty-first century skills such as problem solving and analytic, decision making, organization and time management, risk taking and communication.

Research limitations/implications

The findings provide insights to curriculum developers and policy makers on the appropriate interventions that need to be taken to improve the employability skills of the graduates.

Originality/value

An original contribution is made by linking employability model to TVET sector.
“Does your walk match your talk?” Analyzing IPSASs diffusion in developing and developed countries
Authors: Polzer Tobias , Gårseth-Nesbakk Levi , Adhikari Pawan
Published: December 2019

Purpose

The purpose of this paper is to provide a global overview of the adoption status of International Public Sector Accounting Standards (IPSASs) in the different contexts of developed and developing countries on central government level, particularly delineating key reform issues and attempts to overcome these.

Design/methodology/approach

Drawing on an analytical framework that combines neo-institutional theory with diffusion theory, prior research and official documents were re-analysed.

Findings

There are substantial differences regarding whether countries acknowledge having experienced large implementation challenges and the extent to which the reform benefits have been achieved. The study sheds light on the (institutional) underpinnings of these differences.

Research limitations/implications

First, the analysis could be extended to regional and local governments, as well as social funds. Both qualitative and quantitative strategies are suggested. Second, the implementation of the conceptual framework deserves further attention. Third, further research should more thoroughly scrutinise cost-benefit analyses used for justifying the (non)implementation of IPSASs, and in particular the assumptions that are being made in such analyses.

Practical implications

The paper informs policymakers and standard setters by delineating the areas and issues complicating the widespread adoption of IPSASs across countries, including pointing out directions to overcome these.

Social implications

Substantial amounts of public money are invested internationally to converge accounting standards and translate them into native languages. A close(r) monitoring is needed to ensure that these efforts obtain sufficient value for money.

Originality/value

This study is original as it applies an analytical framework that combines neo-institutional theory and diffusion theory to examine public sector accounting convergence issues internationally. Such an approach explicitly puts a focus on decoupling between reform “talk” (decision) and “walk” (implementation) and helps to analyse the reasons for this decoupling.