Shortlisting SARS‐CoV‐2 Peptides for Targeted Studies from Experimental Data‐Dependent Acquisition Tandem Mass Spectrometry Data

Detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a crucial tool for fighting the COVID‐19 pandemic. This dataset brief presents the exploration of a shotgun proteomics dataset acquired on SARS‐CoV‐2 infected Vero cells. Proteins from inactivated virus samples were extracted, digested with trypsin, and the resulting peptides were identified by data‐dependent acquisition tandem mass spectrometry. The 101 peptides reporting for six viral proteins were specifically analyzed in terms of their analytical characteristics, species specificity and conservation, and their proneness to structural modifications. Based on these results, a shortlist of 14 peptides from the N, S, and M main structural proteins that could be used for targeted mass‐spectrometry method development and diagnostic of the new SARS‐CoV‐2 is proposed and the best candidates are commented.     

Plasmonic Biosensor Controlled by DNAzyme for On‐Site Genetic Detection of Pathogens

On‐site predetection of pathogens could significantly decrease of a disease outbreak or national loss in most of the countries. However, conventional detection techniques are limited in use for on‐site detection due to the necessity of specialized skill or equipment. Therefore, it is necessary to develop a new technique that can predetect pathogens in the field without special skills or equipment. Here, a DNAzyme strategy to control a plasmonic biosensor for rapid and simple visual detection of Salmonella choleraesuis is adopted. Multicomponent DNAzyme formed by target addition can cleave the linker effectively at 50 °C. Linker cleavage induces dispersion of two DNA‐immobilized gold nanoparticles and color change. Under optimized assay conditions, the target could be detected via visual discrimination sensitively and specifically. Moreover, the biosensor shows the possibility of practical use with contaminants and a 16S rRNA real target. As a result, the proposed plasmonic biosensor can visually detect S. choleraesuis without unstable enzymes, a specialized technique, or equipment. Therefore, these advantages could allow that this biosensor would be used for on‐site predetection to lower the risk of transmission of infectious diseases.     

Anthropogenic noise reduces avian feeding efficiency and increases vigilance along an urban–rural gradient regardless of species’ tolerances to urbanisation

Anthropogenic noise can adversely impact urban bird populations by interfering with vocal communication. Less research has addressed if anthropogenic noise masks the adventitious sounds that birds use to aid predator detection, which may lead to increased vigilance and reduced feeding efficiency. We test this hypothesis using a controlled playback experiment along an urban–rural gradient in Sheffield (UK). We also test the related predictions that anthropogenic noise has the greatest impacts on vigilance and feeding efficiency in rural populations, and on species that are more sensitive to urbanisation. We focus on six passerines, in order from most to least urbanised (based on how urbanisation influences population densities): blue tit Cyanistes caeruleus, robin Erithacus rubeculla, great tit Parus major, chaffinch Fringilla coelebs, coal tit Periparus ater and nuthatch Sitta europaea. We used play-back of anthropogenic urban noise and a control treatment at 46 feeding stations located along the urban–rural gradient. We assess impacts on willingness to visit feeders, feeding and vigilance rates. Exposure to anthropogenic noise reduced visit rates to supplementary feeding stations, reduced feeding rates and increased vigilance. Birds at more urban sites exhibit less marked treatment induced reductions in feeding rates, suggesting that urban populations may be partially habituated or adapted to noisy environments. There was no evidence, however, that more urbanised species were less sensitive to the impacts of noise on any response variable. Our results support the adventitious sound masking hypothesis. Urban noise may thus interfere with the ability of birds to detect predators, reducing their willingness to use food rich environments and increase vigilance rates resulting in reduced feeding rates. These adverse impacts may compromise the quality of otherwise suitable foraging habitats in noisy urban areas. They are likely to be widespread as they arise in a range of species including common urban birds.     

Loop-mediated isothermal amplification assay for the detection of Plasmopara viticola infecting grapes

Grapes downy mildew caused by obligate oomycete plant pathogen Plasmopara viticola is a devastating disease worldwide, resulting in significant yield and quality losses. A field survey was conducted in two major grapes cultivated areas of Tamil Nadu for the incidence of grapevine downy mildew. The disease incidence was 43.42%–76.69%, and the highest disease incidence of 76.69% was observed in the Theni district. Totally eight P. viticola isolates were collected from different places in Coimbatore and Theni districts. These isolates were confirmed through microscopic observation and sequencing of COX 2 gene, and the phylogenetic tree was developed to study their phylogenetic relationship among the isolates which shows 97–100% sequence similarity with other P. viticola isolates and less sequence similarity with Plasmopara species. The loop-mediated isothermal amplification (LAMP) assay was developed based on the CesA4 gene sequence of P. viticola. The assay developed was more sensitive as it detected P. viticola genomic DNA up to 20 fmg. LAMP assay specificity was proved by carrying out the assay with genomic DNA extracted from other Oomycetes and fungal plant pathogens. Finally, LAMP assay was validated by testing seventy-eight grapevine leaf samples collected from seven different locations. LAMP assay showed a positive reaction in sixty-two samples tested out of seventy-eight samples tested. Therefore, the LAMP assay described should helpful for early and specific detection of downy mildew pathogen and help in mitigating disease incidence.     

Congruent population genetic structures and divergence histories in anther‐smut fungi and their host plants Silene italica and the Silene nutans species complex

Study of the congruence of population genetic structure between hosts and pathogens gives important insights into their shared phylogeographical and coevolutionary histories. We studied the population genetic structure of castrating anther‐smut fungi (genus Microbotryum) and of their host plants, the Silene nutans species complex, and the morphologically and genetically closely related Silene italica, which can be found in sympatry. Phylogeographical population genetic structure related to persistence in separate glacial refugia has been recently revealed in the S. nutans plant species complex across Western Europe, identifying several distinct lineages. We genotyped 171 associated plant–pathogen pairs of anther‐smut fungi and their host plant individuals using microsatellite markers and plant chloroplastic single nucleotide polymorphisms. We found clear differentiation between fungal populations parasitizing S. nutans and S. italica plants. The population genetic structure of fungal strains parasitizing the S. nutans plant species complex mirrored the host plant genetic structure, suggesting that the pathogen was isolated in glacial refugia together with its host and/or that it has specialized on the plant genetic lineages. Using random forest approximate Bayesian computation (ABC‐RF), we found that the divergence history of the fungal lineages on S. nutans was congruent with that previously inferred for the host plant and probably occurred with ancient but no recent gene flow. Genome sequences confirmed the genetic structure and the absence of recent gene flow between fungal genetic lineages. Our analyses of individual host–pathogen pairs contribute to a better understanding of co‐evolutionary histories between hosts and pathogens in natural ecosystems, in which such studies remain scarce.     

生物多样性与传染性疾病的关系: 进展、挑战与展望

在全球生物多样性快速丧失的背景下, 理解生物多样性如何影响传染性疾病风险具有重要意义。大量研究表明, 宿主多样性对传染性疾病可能存在稀释效应(即疾病风险随宿主生物多样性的增加而降低), 但是也有放大效应或者没有影响的证据。本文首先介绍了关于生物多样性与传染性疾病关系的研究进展, 以及该领域的热点研究问题, 包括宿主多样性-疾病关系的格局和空间依赖性、稀释效应的体系依赖性和系统发育稀释效应等。随后,介绍了相关研究伴随的争议和批判, 主要集中在: 稀释效应发生的普遍性、生物多样性-疾病关系实验研究的发表偏好性以及部分疾病生态学家对生物多样性和传染性疾病之间简单数字关系的过分关注。最后指出稀释效应与物种共存、全球变化对稀释效应的影响、进化与稀释效应、稀释效应在政策制定中的应用等领域可能是今后的主要研究方向。     

Balancing selection in Pattern Recognition Receptor signalling pathways is associated with gene function and pleiotropy in a wild rodent

Pathogen‐mediated balancing selection is commonly considered to play an important role in the maintenance of genetic diversity, in particular in immune genes. However, the factors that may influence which immune genes are the targets of such selection are largely unknown. To address this, here we focus on Pattern Recognition Receptor (PRR) signalling pathways, which play a key role in innate immunity. We used whole‐genome resequencing data from a population of bank voles (Myodes glareolus) to test for associations between balancing selection, pleiotropy and gene function in a set of 123 PRR signalling pathway genes. To investigate the effect of gene function, we compared genes encoding (a) receptors for microbial ligands versus downstream signalling proteins, and (b) receptors recognizing components of microbial cell walls, flagella and capsids versus receptors recognizing features of microbial nucleic acids. Analyses based on the nucleotide diversity of full coding sequences showed that balancing selection primarily targeted receptor genes with a low degree of pleiotropy. Moreover, genes encoding receptors recognizing components of microbial cell walls etc. were more important targets of balancing selection than receptors recognizing nucleic acids. Tests for localized signatures of balancing selection in coding and noncoding sequences showed that such signatures were mostly located in introns, and more evenly distributed among different functional categories of PRR pathway genes. The finding that signatures of balancing selection in full coding sequences primarily occur in receptor genes, in particular those encoding receptors for components of microbial cell walls etc., is consistent with the idea that coevolution between hosts and pathogens is an important cause of balancing selection on immune genes.     

水相中氢气浓度检测方法的建立

近年来,研究表明氢分子具有广泛的生物学效应,饮用富氢水（hydrogen-rich water,HRW）是其主要的摄取方法,但目前对于水相中氢气浓度检测方法的研究甚少。为了建立适用于测定水相中氢气浓度的检测方法,利用纯水氢气发生器制备饱和富氢水。然后,利用氢气微电极直接测定水相中的氢气浓度,结果表明,在不同氢气浓度范围内（0～1.620 0 mg·L-1和0～0.202 5 mg·L-1）,氢气浓度与微电极信号值均呈现良好的线性关系,方法检出限（method detection limit,MDL）为4.3×10-3 mg·L-1。同时,采用顶空方式将水相中的氢气转移到气相中,通过气相色谱法测定氢气的浓度,结果表明,在不同氢气浓度范围内（0～1.620 0 mg·L-1和0～0.202 5 mg·L-1）,氢气浓度与气相色谱峰面积均具有良好的线性关系,MDL为8.7×10-4 mg·L-1。研究结果表明,氢微电极法和气相色谱法均可用于水相中氢气浓度的精确定量,即成功建立了采用氢气微电极及顶空气相色谱测定水相中氢气含量的检测方法。     

Voice Pathologies Classification and Detection Using EMD-DWT Analysis Based on Higher Order Statistic Features

BackgroundThe voice is a prominent tool allowing people to communicate and to change information in their daily activities. However, any slight alteration in the voice production system may affect the voice quality. Over the last years, researchers in biomedical engineering field worked to develop a robust automatic system that may help clinicians to perform a preventive diagnosis in order to detect the voice pathologies in an early stage.MethodIn this context, pathological voice detection and classification method based on EMD-DWT analysis and Higher Order Statistics (HOS) features, is proposed. Also DWT coefficients features are extracted and tested. To carry out our experiments a wide subset of voice signal from normal subjects and subjects which suffer from the five most frequent pathologies in the Saarbrücken Voice Database (SVD), is selected. In The first step, we applied the Empirical Mode Decomposition (EMD) to the voice signal. Afterwards, among the obtained candidates of Intrinsic Mode Functions (IMFs), we choose the robust one based on temporal energy criterion. In the second step, the selected IMF was decomposed via the Discrete Wavelet Transform (DWT). As a result, two features vector includes six HOSs parameters, and a features vector includes six DWT features were formed from both approximation and detail coefficients. In order to classify the obtained data a support vector machine (SVM) is employed. After having trained the proposed system using the SVD database, the system was evaluated using voice signals of volunteer's subjects from the Neurological department of RABTA Hospital of Tunis.ResultsThe proposed method gives promising results in pathological voices detection. The accuracies reached 99.26% using HOS features and 93.1% using DWT features for SVD database. In the classification, an accuracy of 100% was reached for “Funktionelle Dysphonia vs. Rekrrensparese” based on HOS features. Nevertheless, using DWT features the accuracy achieved was 90.32% for “Hyperfunktionelle Dysphonia vs. Rekurrensparse”. Furthermore, in the validation the accuracies reached were 94.82%, 91.37% for HOS and DWT features, respectively. In the classification the highest accuracies reached were for classifying “Parkinson versus Paralysis” 94.44% and 88.87% based on HOS and DWT features, respectively.ConclusionHOS features show promising results in the automatic voice pathology detection and classification compared to DWT features. Thus, it can reliably be used as noninvasive tool to assist clinical evaluation for pathological voices identification.     

A Generic Approach for Efficient Detection of Vascular Structures

Vascular segmentation is often required in medical image analysis for various imaging modalities. Despite the rich literature in the field, the proposed methods need most of the time adaptation to the particular investigation and may sometimes lack the desired accuracy in terms of true positive and false positive detection rate. This paper proposes a general method for vascular segmentation based on locally connected filtering applied in a multiresolution scheme. The filtering scheme performs progressive detection and removal of the vessels from the image relief at each resolution level, by combining directional 2D-3D locally connected filters (LCF). An important property of the LCF is that it preserves (positive contrasted) structures in the image if they are topologically connected with other similar structures in their local environment. Vessels, which appear as curvilinear structures, can be filtered out by an appropriate LCF set-up which will minimally affect sheet-like structures. The implementation in a multiresolution framework allows dealing with different vessel sizes. The outcome of the proposed approach is illustrated on several image modalities including lung, liver and coronary arteries. It is shown that besides preserving high accuracy in detecting small vessels, the proposed technique is less sensitive with respect to noise and the presence of pathologies of positive-contrast appearance on the images. The detection accuracy is compared with a previously developed approach on the 20 patient database from the VESSEL12 challenge.