Cleaning the Cellular Factory:Deletion of McrA in Aspergillus oryzae NSAR1 and the generation of a novel kojic acid deficient strain for cleaner heterologous production of secondary metabolites

The use of filamentous fungi as cellular factories, where natural product pathways can be refactored and expressed in a host strain, continues to aid the field of natural product discovery. Much work has been done to develop host strains which are genetically tractable, and for which there are multiple selectable markers and controllable expression systems. To fully exploit these strains, it is beneficial to understand their natural metabolic capabilities, as such knowledge can rule out host metabolites from analysis of transgenic lines and highlight any potential interplay between endogenous and exogenous pathways. Additionally, once identified, the deletion of secondary metabolite pathways from host strains can simplify the detection and purification of heterologous compounds. To this end, secondary metabolite production in Aspergillus oryzae strain NSAR1 has been investigated via the deletion of the newly discovered negative regulator of secondary metabolism, mcrA (multicluster regulator A). In all ascomycetes previously studied mcrA deletion led to an increase in secondary metabolite production. Surprisingly, the only detectable phenotypic change in NSAR1 was a doubling in the yields of kojic acid, with no novel secondary metabolites produced. This supports the previous claim that secondary metabolite production has been repressed in A. oryzae and demonstrates that such repression is not McrA-mediated. Strain NSAR1 was then modified by employing CRISPR-Cas9 technology to disrupt the production of kojic acid, generating the novel strain NSARΔK, which combines the various beneficial traits of NSAR1 with a uniquely clean secondary metabolite background

Evolutionary profiling reveals the heterogeneous origins of classes of human disease genes: implications for modeling disease genetics in animals

Background: The recent expansion of whole-genome sequence data available from diverse animal lineages provides an opportunity to investigate the evolutionary origins of specific classes of human disease genes. Previous studies have observed that human disease genes are of particularly ancient origin. While this suggests that many animal species have the potential to serve as feasible models for research on genes responsible for human disease, it is unclear whether this pattern has meaningful implications and whether it prevails for every class of human disease. Results: We used a comparative genomics approach encompassing a broad phylogenetic range of animals with sequenced genomes to determine the evolutionary patterns exhibited by human genes associated with different classes of disease. Our results support previous claims that most human disease genes are of ancient origin but, more importantly, we also demonstrate that several specific disease classes have a significantly large proportion of genes that emerged relatively recently within the metazoans and/or vertebrates. An independent assessment of the synonymous to non-synonymous substitution rates of human disease genes found in mammals reveals that disease classes that arose more recently also display unexpected rates of purifying selection between their mammalian and human counterparts. Conclusions: Our results reveal the heterogeneity underlying the evolutionary origins of (and selective pressures on) different classes of human disease genes. For example, some disease gene classes appear to be of uncommonly recent (i.e., vertebrate-specific) origin and, as a whole, have been evolving at a faster rate within mammals than the majority of disease classes having more ancient origins. The novel patterns that we have identified may provide new insight into cases where studies using traditional animal models were unable to produce results that translated to humans. Conversely, we note that the larger set of disease classes do have ancient origins, suggesting that many non-traditional animal models have the potential to be useful for studying many human disease genes. Taken together, these findings emphasize why model organism selection should be done on a disease-by-disease basis, with evolutionary profiles in mind

A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

Mitochondrial uncoupling links lipid catabolism to Akt inhibition and resistance to tumorigenesis

To support growth, tumour cells reprogramme their metabolism to simultaneously upregulate macromolecular biosynthesis while maintaining energy production. Uncoupling proteins (UCPs) oppose this phenotype by inducing futile mitochondrial respiration that is uncoupled from ATP synthesis, resulting in nutrient wasting. Here using a UCP3 transgene targeted to the basal epidermis, we show that forced mitochondrial uncoupling inhibits skin carcinogenesis by blocking Akt activation. Similarly, Akt activation is markedly inhibited in UCP3 overexpressing primary human keratinocytes. Mechanistic studies reveal that uncoupling increases fatty acid oxidation and membrane phospholipid catabolism, and impairs recruitment of Akt to the plasma membrane. Overexpression of Akt overcomes metabolic regulation by UCP3, rescuing carcinogenesis. These findings demonstrate that mitochondrial uncoupling is an effective strategy to limit proliferation and tumorigenesis through inhibition of Akt, and illuminate a novel mechanism of crosstalk between mitochondrial metabolism and growth signalling

Urban Air Mobility Airspace Integration Concepts and Considerations

Urban Air Mobility (UAM) - defined as safe and efficient air traffic operations in a metropolitan area for manned aircraft and unmanned aircraft systems - is being researched and developed by industry, academia, and government. Significant resources have been invested toward cultivating an ecosystem for Urban Air Mobility that includes manufacturers of electric vertical takeoff and landing aircraft, builders of takeoff and landing areas, and researchers of the airspace integration concepts, technologies, and procedures needed to conduct Urban Air Mobility operations safely and efficiently alongside other airspace users. This paper provides high-level descriptions of both emergent and early expanded operational concepts for Urban Air Mobility that NASA is developing. The scope of this work is defined in terms of missions, aircraft, airspace, and hazards. Past and current Urban Air Mobility operations are also reviewed, and the considerations for the data exchange architecture and communication, navigation, and surveillance requirements are also discussed. This paper will serve as a starting point to develop a framework for NASA's Urban Air Mobility airspace integration research and development efforts with partners and stakeholders that could include fast-time simulations, human-in-the-loop (HITL) simulations, and flight demonstrations

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Imidazole propionate is increased in diabetes and associated with dietary patterns and altered microbial ecology

Microbiota-host-diet interactions contribute to the development of metabolic diseases. Imidazole propionate is a novel microbially produced metabolite from histidine, which impairs glucose metabolism. Here, we show that subjects with prediabetes and diabetes in the MetaCardis cohort from three European countries have elevated serum imidazole propionate levels. Furthermore, imidazole propionate levels were increased in subjects with low bacterial gene richness and Bacteroides 2 enterotype, which have previously been associated with obesity. The Bacteroides 2 enterotype was also associated with increased abundance of the genes involved in imidazole propionate biosynthesis from dietary histidine. Since patients and controls did not differ in their histidine dietary intake, the elevated levels of imidazole propionate in type 2 diabetes likely reflects altered microbial metabolism of histidine, rather than histidine intake per se. Thus the microbiota may contribute to type 2 diabetes by generating imidazole propionate that can modulate host inflammation and metabolism

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Biomarkers of Nutrition for Development (BOND)—Iron Review

This is the fifth in the series of reviews developed as part of the Biomarkers of Nutrition for Development (BOND) program. The BOND Iron Expert Panel (I-EP) reviewed the extant knowledge regarding iron biology, public health implications, and the relative usefulness of currently available biomarkers of iron status from deficiency to overload. Approaches to assessing intake, including bioavailability, are also covered. The report also covers technical and laboratory considerations for the use of available biomarkers of iron status, and concludes with a description of research priorities along with a brief discussion of new biomarkers with potential for use across the spectrum of activities related to the study of iron in human health. The I-EP concluded that current iron biomarkers are reliable for accurately assessing many aspects of iron nutrition. However, a clear distinction is made between the relative strengths of biomarkers to assess hematological consequences of iron deficiency versus other putative functional outcomes, particularly the relationship between maternal and fetal iron status during pregnancy, birth outcomes, and infant cognitive, motor and emotional development. The I-EP also highlighted the importance of considering the confounding effects of inflammation and infection on the interpretation of iron biomarker results, as well as the impact of life stage. Finally, alternative approaches to the evaluation of the risk for nutritional iron overload at the population level are presented, because the currently designated upper limits for the biomarker generally employed (serum ferritin) may not differentiate between true iron overload and the effects of subclinical inflammation

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe