Transposable Elements and Stress in Vertebrates: An Overview

Since their identification as genomic regulatory elements, Transposable Elements (TEs) were considered, at first, molecular parasites and later as an important source of genetic diversity and regulatory innovations. In vertebrates in particular, TEs have been recognized as playing an important role in major evolutionary transitions and biodiversity. Moreover, in the last decade, a significant number of papers has been published highlighting a correlation between TE activity and exposition to environmental stresses and dietary factors. In this review we present an overview of the impact of TEs in vertebrate genomes, report the silencing mechanisms adopted by host genomes to regulate TE activity, and finally we explore the effects of environmental and dietary factor exposures on TE activity in mammals, which is the most studied group among vertebrates. The studies here reported evidence that several factors can induce changes in the epigenetic status of TEs and silencing mechanisms leading to their activation with consequent effects on the host genome. The study of TE can represent a future challenge for research for developing effective markers able to detect precocious epigenetic changes and prevent human diseases.     

Change in the Thermal Expansion of a Perovskite-Type Mixed Conductor Upon Sample Density

Thermal expansions (TEs) of dense and porous samples were studied for mixed conductor Sr(Co_0.9Nb_0.1)O_3−δ (SCNb). In Ar, the TEs of the porous samples were almost the same as those of a dense sample, which had the character of conventional TEs. In air, on the other hand, the TEs of porous samples were larger than the dense sample. The difference of TE in air resulted from a change in the chemical expansion, which originated from the variation of oxygen vacancy concentration. On decreasing the density, oxygen incorporation from air into SCNb took place at a lower temperature, and the length change upon chemical expansion was increased.     

Differences and Interactions in Placental Manganese and Iron Transfer across an In Vitro Model of Human Villous Trophoblasts

Manganese (Mn) as well as iron (Fe) are essential trace elements (TE) important for the maintenance of physiological functions including fetal development. However, in the case of Mn, evidence suggests that excess levels of intrauterine Mn are associated with adverse pregnancy outcomes. Although Mn is known to cross the placenta, the fundamentals of Mn transfer kinetics and mechanisms are largely unknown. Moreover, exposure to combinations of TEs should be considered in mechanistic transfer studies, in particular for TEs expected to share similar transfer pathways. Here, we performed a mechanistic in vitro study on the placental transfer of Mn across a BeWo b30 trophoblast layer. Our data revealed distinct differences in the placental transfer of Mn and Fe. While placental permeability to Fe showed a clear inverse dose-dependency, Mn transfer was largely independent of the applied doses. Concurrent exposure of Mn and Fe revealed transfer interactions of Fe and Mn, indicating that they share common transfer mechanisms. In general, mRNA and protein expression of discussed transporters like DMT1, TfR, or FPN were only marginally altered in BeWo cells despite the different exposure scenarios highlighting that Mn transfer across the trophoblast layer likely involves a combination of active and passive transport processes.     

The Intertwining of Transposable Elements and Non-Coding RNAs

Growing evidence shows a close association of transposable elements (TE) with non-coding RNAs (ncRNA), and a significant number of small ncRNAs originate from TEs. Further, ncRNAs linked with TE sequences participate in a wide-range of regulatory functions. Alu elements in particular are critical players in gene regulation and molecular pathways. Alu sequences embedded in both long non-coding RNAs (lncRNA) and mRNAs form the basis of targeted mRNA decay via short imperfect base-pairing. Imperfect pairing is prominent in most ncRNA/target RNA interactions and found throughout all biological kingdoms. The piRNA-Piwi complex is multifunctional, but plays a major role in protection against invasion by transposons. This is an RNA-based genetic immune system similar to the one found in prokaryotes, the CRISPR system. Thousands of long intergenic non-coding RNAs (lincRNAs) are associated with endogenous retrovirus LTR transposable elements in human cells. These TEs can provide regulatory signals for lincRNA genes. A surprisingly large number of long circular ncRNAs have been discovered in human fibroblasts. These serve as “sponges” for miRNAs. Alu sequences, encoded in introns that flank exons are proposed to participate in RNA circularization via Alu/Alu base-pairing. Diseases are increasingly found to have a TE/ncRNA etiology. A single point mutation in a SINE/Alu sequence in a human long non-coding RNA leads to brainstem atrophy and death. On the other hand, genomic clusters of repeat sequences as well as lncRNAs function in epigenetic regulation. Some clusters are unstable, which can lead to formation of diseases such as facioscapulohumeral muscular dystrophy. The future may hold more surprises regarding diseases associated with ncRNAs andTEs.     

Horizontal Transfer of LTR Retrotransposons Contributes to the Genome Diversity of Vitis

While horizontally transferred transposable elements (TEs) have been reported in several groups of plants, their importance for genome evolution remains poorly understood. To understand how horizontally transferred TEs contribute to plant genome evolution, we investigated the composition and activity of horizontally transferred TEs in the genomes of four Vitis species. A total of 35 horizontal transfer (HT) events were identified between the four Vitis species and 21 other plant species belonging to 14 different families. We determined the donor and recipient species for 28 of these HTs, with the Vitis species being recipients of 15 of them. As a result of HTs, 8–10 LTR retrotransposon clusters were newly formed in the genomes of the four Vitis species. The activities of the horizontally acquired LTR retrotransposons differed among Vitis species, showing that the consequences of HTs vary during the diversification of the recipient lineage. Our study provides the first evidence that the HT of TEs contributes to the diversification of plant genomes by generating additional TE subfamilies and causing their differential proliferation in host genomes.     

A method for measuring the kinetics of organically associated inorganic contaminant vaporization during coal combustion

A novel method is presented for the direct measurement of kinetic parameters under conditions that simulate the vaporization of inorganic material during coal combustion. This method will ultimately be used to generate key physical property data necessary to model and assess the vaporization behavior of trace elements (TEs) during coal combustion. The method uses a graphite furnace atomic absorption spectrometer (GFAAS) as the experimental platform for vaporization measurements for temperatures up to 2800 K. The method was used to model vaporization during coal pyrolysis for one of the three key contaminant domains: organically associated material. Significant testing was conducted for selected TEs under varied instrumental operational conditions that could affect activation energies, such as GFAAS ashing and atomization temperatures, TE concentration, and carrier gas flow rate. The vaporization activation energies determined were found to be independent of these operating conditions despite a significant difference in the degree of analyte vaporization observed at varied ashing temperatures.     

Novel Putative Transposable Element Associated with the Subtype E5 Botulinum Toxin Gene Cluster of Neurotoxigenic Clostridium butyricum Type E Strains from China

Previously, a whole-genome comparison of three Clostridium butyricum type E strains from Italy and the United States with different C. botulinum type E strains indicated that the bont/e gene might be transferred between the two clostridia species through transposition. However, transposable elements (TEs) have never been identified close to the bont/e gene. Herein, we report the whole genome sequences for four neurotoxigenic C. butyricum type E strains that originated in China. An analysis of the obtained genome sequences revealed the presence of a novel putative TE upstream of the bont/e gene in the genome of all four strains. Two strains of environmental origin possessed an additional copy of the putative TE in their megaplasmid. Similar putative TEs were found in the megaplasmids and, less frequently, in the chromosomes of several C. butyricum strains, of which two were neurotoxigenic C. butyricum type E strains, and in the chromosome of a single C. botulinum type E strain. We speculate that the putative TE might potentially transpose the bont/e gene at the intracellular and inter-cellular levels. However, the occasional TE occurrence in the clostridia genomes might reflect rare transposition events.     

Harnessing the Synthetic Capabilities of Glycopeptide Antibiotic Tailoring Enzymes: Characterization of the UK‐68,597 Biosynthetic Cluster

In this study, a draft genome sequence of Actinoplanes sp. ATCC 53533 was assembled, and an 81‐kb biosynthetic cluster for the unusual sulfated glycopeptide UK‐68,597 was identified. Glycopeptide antibiotics are important in the treatment of infections caused by Gram‐positive bacteria. Glycopeptides contain heptapeptide backbones that are modified by many tailoring enzymes, including glycosyltransferases, sulfotransferases, methyltransferases, and halogenases, generating extensive chemical and functional diversity. Several tailoring enzymes in the cluster were examined in vitro for their ability to modify glycopeptides, resulting in the synthesis of novel molecules. Tailoring enzymes were also expressed in the producer of the glycopeptide aglycone A47934, generating additional chemical diversity. This work characterizes the biosynthetic program of UK‐68,597 and demonstrates the capacity to expand glycopeptide chemical diversity by harnessing the unique chemistry of tailoring enzymes.     

Label Transfer Reagents to Probe p38 MAPK Binding Partners

Protein kinases are essential enzymes for cellular signaling, and are often regulated by participation in protein complexes. The mitogen‐activated protein kinase (MAPK) p38 is involved in multiple pathways, and its regulation depends on its interactions with other signaling proteins. However, the identification of p38‐interacting proteins is challenging. For this reason, we have developed label transfer reagents (LTRs) that allow labeling of p38 signaling complexes. These LTRs leverage the potency and selectivity of known p38 inhibitors to place a photo‐crosslinker and tag in the vicinity of p38 and its binding partners. Upon UV irradiation, proteins that are in close proximity to p38 are covalently crosslinked, and labeled proteins are detected and/or purified with an orthogonal chemical handle. Here we demonstrate that p38‐selective LTRs selectively label a diversity of p38 binding partners, including substrates, activators, and inactivators. Furthermore, these LTRs can be used in immunoprecipitations to provide low‐resolution structural information on p38‐containing complexes.     

A Bright Future for Evolutionary Methods in Drug Design

Most medicinal chemists understand that chemical space is extremely large, essentially infinite. Although high‐throughput experimental methods allow exploration of drug‐like space more rapidly, they are still insufficient to fully exploit the opportunities that such large chemical space offers. Evolutionary methods can synergistically blend automated synthesis and characterization methods with computational design to identify promising regions of chemical space more efficiently. We describe how evolutionary methods are implemented, and provide examples of published drug development research in which these methods have generated molecules with increased efficacy. We anticipate that evolutionary methods will play an important role in future drug discovery.     

Comparative Genomics: Insights on the Pathogenicity and Lifestyle of Rhizoctonia solani

Proper management of agricultural disease is important to ensure sustainable food security. Staple food crops like rice, wheat, cereals, and other cash crops hold great export value for countries. Ensuring proper supply is critical; hence any biotic or abiotic factors contributing to the shortfall in yield of these crops should be alleviated. Rhizoctonia solani is a major biotic factor that results in yield losses in many agriculturally important crops. This paper focuses on genome informatics of our Malaysian Draft R. solani AG1-IA, and the comparative genomics (inter- and intra- AG) with four AGs including China AG1-IA (AG1-IA_KB317705.1), AG1-IB, AG3, and AG8. The genomic content of repeat elements, transposable elements (TEs), syntenic genomic blocks, functions of protein-coding genes as well as core orthologous genic information that underlies R. solani’s pathogenicity strategy were investigated. Our analyses show that all studied AGs have low content and varying profiles of TEs. All AGs were dominant for Class I TE, much like other basidiomycete pathogens. All AGs demonstrate dominance in Glycoside Hydrolase protein-coding gene assignments suggesting its importance in infiltration and infection of host. Our profiling also provides a basis for further investigation on lack of correlation observed between number of pathogenicity and enzyme-related genes with host range. Despite being grouped within the same AG with China AG1-IA, our Draft AG1-IA exhibits differences in terms of protein-coding gene proportions and classifications. This implies that strains from similar AG do not necessarily have to retain similar proportions and classification of TE but must have the necessary arsenal to enable successful infiltration and colonization of host. In a larger perspective, all the studied AGs essentially share core genes that are generally involved in adhesion, penetration, and host colonization. However, the different infiltration strategies will depend on the level of host resilience where this is clearly exhibited by the gene sets encoded for the process of infiltration, infection, and protection from host.     

Evolutionary History of Bioessential Elements Can Guide the Search for Life in the Universe

Our understanding of life in the universe comes from one sample, life on Earth. Current and next-generation space missions will target exoplanets as well as planets and moons in our own solar system with the primary goal of detecting, interpreting and characterizing indications of possible biological activity. Thus, understanding life's fundamental characteristics is increasingly critical for detecting and interpreting potential biological signatures elsewhere in the universe. Astrobiologists have outlined the essential roles of carbon and water for life, but we have yet to decipher the rules governing the evolution of how living organisms use bioessential elements. Does the suite of life's essential chemical elements on Earth constitute only one possible evolutionary outcome? Are some elements so essential for biological functions that evolution will select for them despite low availability? How would this play out on other worlds that have different relative element abundances? When we look for life in the universe, or the conditions that could give rise to life, we must learn how to recognize it in extremely different chemical and environmental conditions from those on Earth. We argue that by exposing self-organizing biotic chemistries to different combinations of abiotic materials, and by mapping the evolutionary history of metalloenzyme biochemistry onto geological availabilities of metals, alternative element choices that are very different from life's present-day molecular structure might result. A greater understanding of the paleomolecular evolutionary history of life on Earth will create a predictive capacity for detecting and assessing life's existence on worlds where alternate evolutionary paths might have been taken.     

Antioxidant Capacity of Rapeseed Extracts Obtained by Conventional and Ultrasound‐Assisted Extraction

Ultrasound‐assisted extraction (UAE) and conventional solid–liquid extraction were applied to extract total antioxidants from two rapeseed varieties. The antioxidant capacities (AC) of winter and spring rapeseed cultivars were determined by four different analytical methods: ferric reducing antioxidant power (FRAP), cupric reducing antioxidant capacity (CUPRAC), 2,2′‐diphenyl‐1‐picrylhydrazyl (DPPH), 2,2′‐azino‐bis‐3‐ethylbenzothiazoline‐6‐sulfonic acid (ABTS). The average AC of the studied rapeseed cultivars ranged between 4.21–10.03 mmol Trolox (TE)/100 g, 7.82–10.61 mmol TE/100 g, 8.11–51.59 mmol TE/100 g, 22.48–43.13 mmol TE/100 g for FRAP, CUPRAC, DPPH and ABTS methods, respectively. There are positive correlations between total phenolics (TPC = 804–1625 mg sinapic acid (SA)/100 g) and AC of the studied rapeseed extracts (r = 0.2650–0.9931). Results of the principal component analysis (PCA) indicate that there are differences between the total amounts of antioxidants in rapeseed samples extracted by different extraction techniques. Rapeseed extracts obtained after 18 min of ultrasonication revealed the highest content of total antioxidants. The UAE is a very useful, efficient and rapid technique of oilseed samples preparation for determination of AC by different analytical methods.     

Chemical process fault diagnosis based on enchanted machine‐learning approach

In the chemical industry, fault diagnosis is a challenging task due to the complexity of chemical equipment. This paper proposes a machine learning‐based approach to achieve the goal of fault diagnosis. First, in order to reduce the impact of redundant features, support vector machine recursive feature elimination (SVMRFE) is used to select important features. The trained probabilistic neural network (PNN) is then used for fault diagnosis. Considering that the diagnostic performance is affected by its hidden layer element smoothing factor (σ), the modified bat algorithm (MBA) is used to optimize the PNN to obtain optimal global parameter values. The MBA adopts a better optimization mechanism than the basic algorithm and achieves excellent global convergence. It can globally optimize the smoothing factor, which effectively improves the fault diagnosis ability of the PNN. During the testing of the Tennessee Eastman (TE) process data set, we evaluate the performance of the proposed model by comparing the F₁‐score and accuracy of the different methods. The charts provided describe the fault diagnostic results and classification for the different models. The results indicate that the MBA has a better optimization ability than other traditional optimization algorithms. At the same time, the combination method proposed in this paper is also superior to others and can significantly improve the accuracy of TE process fault diagnosis.     

Identification of abnormal conditions in high-dimensional chemical process based on feature selection and deep learning

Identification of abnormal conditions is essential in the chemical process. With the rapid development of artificial intelligence technology, deep learning has attracted a lot of attention as a promising fault identification method in chemical process recently. In the high-dimensional data identification using deep neural networks, problems such as insufficient data and missing data, measurement noise, redundant variables, and high coupling of data are often encountered. To tackle these problems, a feature based deep belief networks (DBN) method is proposed in this paper. First, a generative adversarial network (GAN) is used to reconstruct the random and non-random missing data of chemical process. Second, the feature variables are selected by Spearman's rank correlation coefficient (SRCC) from high-dimensional data to eliminate the noise and redundant variables and, as a consequence, compress data dimension of chemical process. Finally, the feature filtered data is deeply abstracted, learned and tuned by DBN for multi-case fault identification. The application in the Tennessee Eastman (TE) process demonstrates the fast convergence and high accuracy of this proposal in identifying abnormal conditions for chemical process, compared with the traditional fault identification algorithms.