Estimating the relative proportions of SARS-CoV-2 strains from wastewater samples

Wastewater surveillance has become essential for monitoring the spread of SARS-CoV-2. The quantification of SARS-CoV-2 RNA in wastewater correlates with the Covid-19 caseload in a community. However, estimating the proportions of different SARS-CoV-2 strains has remained technically difficult. We present a method for estimating the relative proportions of SARS-CoV-2 strains from wastewater samples. The method uses an initial step to remove unlikely strains, imputation of missing nucleotides using the global SARS-CoV-2 phylogeny, and an Expectation-Maximization (EM) algorithm for obtaining maximum likelihood estimates of the proportions of different strains in a sample. Using simulations with a reference database of >3 million SARS-CoV-2 genomes, we show that the estimated proportions accurately reflect the true proportions given sufficiently high sequencing depth and that the phylogenetic imputation is highly accurate and substantially improves the reference database.

Microbiota in Gingival Crevicular Fluid Before and After Mechanical Debridement With Antimicrobial Photodynamic Therapy in Peri-Implantitis

ObjectivesThis study aims to compare the microbiota of gingival crevicular fluid (GCF) before and after mechanical debridement (MD) with antimicrobial photodynamic therapy (aPDT) and determine the core efficient microbiota in peri-implantitis after treatment.MethodsWe recruited 9 patients (14 implants) treated with MD+aPDT for peri-implantitis at our center from February 1, 2018, to February 1, 2019. GCF was collected using filter paper strip before and after the treatment. The bacterial 16S rRNA was amplified and sequenced using an Illumina MiSeq platform to characterize the GCF. Bioinformatics and statistical analyses were performed using QIIME2 and R.ResultsA total of 4,110,861 high-quality sequences were obtained from GCF samples. Based on the reference database, 1,120 amplicon sequence variants (ASVs) were finally harvested. Principal coordinates analysis indicated significant differences in the bacterial community structure between the 180 days after-treatment group and pre-treatment group. Difference analysis and least discriminant analysis showed that the differences were mainly reflected in non-dominant bacteria between these two groups. The non-dominant genera with significantly different distribution between the 180 days after-treatment group and the pre-treatment group included Lactobacillus, Pedobacter, Bulleidia, Centipeda, Desulfovibrio, Ochrobactrum, Staphylococcus, Microbacterium, Brevundimonas, Desulfobulbus, and Parvimonas. Moreover, a total of 29 predictive functional categories at KEGG level 2 were identified. The significant difference pathways at KEGG level 2 between after-treatment and pre-treatment were concentrated in infectious disease-related pathways.ConclusionsPatients with peri-implantitis have significant changes in the low-abundance bacteria of the GCF before and after MD+aPDT. MD+aPDT may change the composition of GCF microbiota by increasing the abundance of cluster 1 (beneficial) and decreasing that of cluster 4 (harmful), which may decrease metabolic response to infection and thus improve peri-implantitis.

One Bat’s Waste is Another Man’s Treasure: A DNA Metabarcoding Approach for the Assessment of Biodiversity and Ecosystem Services Using Bat Faeces

Arthropod populations are constantly changing due to changes in climate and the globalisation of trade and travel. Effective and diverse monitoring techniques are required to understand these changes. DNA metabarcoding has facilitated the development of a broad monitoring method to sample arthropod diversity from environmental and faecal samples. In this study, we applied DNA metabarcoding to DNA extracted from bat faecal pellets of Rhinolophus hipposideros, the lesser horseshoe bat in Ireland, a highly protected bat species of conservation concern in Europe. From as few as 24 bat faecal pellets, we detected 161 arthropod species, spanning 11 orders, including 38 pest species of which five were determined to be priority pests, highlighting important ecosystem services. We also report the identification 14 species not previously reported in Ireland, but upon further investigation found that many of these are likely misidentified due to inadequacies in the genetic reference database. For the first time, we were able to use non-invasively collected bat samples to examine the role of sex in the diet of bats and found that the male and female diets did not differ significantly. However, sampling location did explain variation within the diet, highlighting how landscape features influence arthropod composition and diversity. We discuss the current limitations of the methodology in Ireland, how these can be overcome in future studies, and how this data can be used for biodiversity monitoring and informing conservation management of protected bat species.

Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates

Patterns of sequencing coverage along a bacterial genome---summarized by a peak-to-trough ratio (PTR)---have been shown to accurately reflect microbial growth rates, revealing a new facet of microbial dynamics and host-microbe interactions. Here, we introduce CoPTR (Compute PTR): a tool for computing PTRs from complete reference genomes and assemblies. Using simulations and data from growth experiments in simple and complex communities, we show that CoPTR is more accurate than the current state-of-the-art, while also providing more PTR estimates overall. We further develop theory formalizing a biological interpretation for PTRs. Using a reference database of 2935 species, we applied CoPTR to a case-control study of 1304 metagenomic samples from 106 individuals with inflammatory bowel disease. We show that growth rates are personalized, are only loosely correlated with relative abundances, and are associated with disease status. We conclude by demonstrating how PTRs can be combined with relative abundances and metabolomics to investigate their effect on the microbiome.

A proteomics informed by transcriptomics insight into the proteome of Ornithodoros erraticus adult tick saliva

Background The argasid tick Ornithodoros erraticus is the main vector of tick-borne human relapsing fever (TBRF) and African swine fever (ASF) in the Mediterranean Basin. The prevention and control of these diseases would greatly benefit from the elimination of O. erraticus populations, and anti-tick vaccines are envisaged as an effective and sustainable alternative to chemical acaricide usage for tick control. Ornithodoros erraticus saliva contains bioactive proteins that play essential functions in tick feeding and host defence modulation, which may contribute to host infection by tick-borne pathogens. Hence, these proteins could be candidate antigen targets for the development of vaccines aimed at the control and prevention of O. erraticus infestations and the diseases this tick transmits. The objective of the present work was to obtain and characterise the proteome of the saliva of O. erraticus adult ticks as a means to identify and select novel salivary antigen targets. Methods A proteomics informed by transcriptomics (PIT) approach was applied to analyse samples of female and male saliva separately using the previously obtained O. erraticus sialotranscriptome as a reference database and two different mass spectrometry techniques, namely liquid chromatography–tandem mass spectrometry (LC–MS/MS) in data-dependent acquisition mode and sequential window acquisition of all theoretical fragment ion spectra MS (SWATH-MS). Results Up to 264 and 263 proteins were identified by LC–MS/MS in the saliva of O. erraticus female and male ticks, respectively, totalling 387 non-redundant proteins. Of these, 224 were further quantified by SWATH-MS in the saliva of both male and female ticks. Quantified proteins were classified into 23 functional categories and their abundance compared between sexes. Heme/iron-binding proteins, protease inhibitors, proteases, lipocalins and immune-related proteins were the categories most abundantly expressed in females, while glycolytic enzymes, protease inhibitors and lipocalins were the most abundantly expressed in males. Ninety-seven proteins were differentially expressed between the sexes, of which 37 and 60 were overexpressed in females and males, respectively. Conclusions The PIT approach demonstrated its usefulness for proteomics studies of O. erraticus, a non-model organism without genomic sequences available, allowing the publication of the first comprehensive proteome of the saliva of O. erraticus reported to date. These findings confirm important quantitative differences between sexes in the O. erraticus saliva proteome, unveil novel salivary proteins and functions at the tick–host feeding interface and improve our understanding of the physiology of feeding in O. erraticus ticks. The integration of O. erraticus sialoproteomic and sialotranscriptomic data will drive a more rational selection of salivary candidates as antigen targets for the development of vaccines aimed at the control of O. erraticus infestations and the diseases it transmits. Graphical Abstract

Appraisal of water quality and ecological sensitivity with reference to riverfront development along the River Gomti, India

The conflict between the vitality of natural ecosystem versus artificially developed systems has existed since decades. The ecological sensitivity and socio-economic aspects associated with riverfront development along rivers have attracted the attention of environmentalists and ecologists across the globe. The present study evaluates the impacts of channelization and riverfront development on the water quality of river Gomti through Water Pollution Index (WPI) and other statistical tools. Of the total studied sites, 75% were found to be in the ‘highly polluted’ category even after the development of riverfront. An approximate increase of 274.5% and 171.76% was witnessed in the WPI values at the midstream sites of Kudiaghat and Daliganj, respectively. This increase in the WPI values clearly stated the deteriorated water quality of river Gomti after the channelization. The major issue of domestic sewage discharge with partial or no treatment into the river seems to be unresolved even after a considerable period of riverfront development. This study can provide a reference database toward development of such projects across the globe.

PRESERVAÇÃO, CONSERVAÇÃO E RESTAURAÇÃO DOCUMENTAL: revisão sistemática na LISTA, ISTA e BRAPCI = DOCUMENT PRESERVATION, CONSERVATION AND RESTORATION: systematic review in LISTA, ISTA and BRAPCI

Este artigo tem como objetivo geral analisar a bibliografia sobre conservação, preservação e restauração de documentos físicos, publicada no período de 2016 a 2021 e disponível na Library, Information Science and Technology Abstracts (LISTA), na Information Science and Technology Abstracts (ISTA) e na Base de Dados Referencial de Artigos de Periódicos em Ciência da Informação (BRAPCI). Quanto a metodologia utilizada, é caracterizado como um estudo exploratório e descritivo, com abordagem quanti-qualitativa, tendo a bibliografia como principal fonte de dados. O método de revisão sistemática da literatura norteador do estudo foi o Preferred Reporting Items for Systematic Reviews and Meta-Analyses ou PRISMA. Foram encontrados 27 artigos de periódicos e tecidas as considerações quanto à autoria, palavras-chave e subtemáticas. Os estudos sobre à cerca das áreas apresentadas são insuficientes em frente à quantidade de documentos físicos existentes, posto que, para que haja uma melhor demanda informacional, são necessárias pesquisas científicas e técnicas aprimoradas para o manuseio adequado desses documentos, de forma a não os danificar.AbstractThis article aims to analyze the bibliography on preservation, conservation andrestoration of physical documents, published from 2016 to 2021 and available inLibrary, Information Science and Technology Abstracts, Information Science andTechnology Abstracts and Reference Database of Articles from Periodicals inInformation Science. As for the methodology used, it is characterized as anexploratory and descriptive study, with a quantitative approach, having thebibliography as the main source of data. The method of systematic literature review guiding the study was the Preferred Reporting Items for Systematic Reviews and Meta-Analyses or PRISMA. Twenty-seven articles from journals were found and considerations were made regarding authorship, keywords and sub-themes. Studies on the areas presented are insufficient compared to the amount of existing physical documents, since, in order to make better use of information in these types of supports, more scientific research and improved techniques are needed for the proper handling of these documents, in order to do not damage them.

NGS read classification using AI

Clinical metagenomics is a powerful diagnostic tool, as it offers an open view into all DNA in a patient’s sample. This allows the detection of pathogens that would slip through the cracks of classical specific assays. However, due to this unspecific nature of metagenomic sequencing, a huge amount of unspecific data is generated during the sequencing itself and the diagnosis only takes place at the data analysis stage where relevant sequences are filtered out. Typically, this is done by comparison to reference databases. While this approach has been optimized over the past years and works well to detect pathogens that are represented in the used databases, a common challenge in analysing a metagenomic patient sample arises when no pathogen sequences are found: How to determine whether truly no evidence of a pathogen is present in the data or whether the pathogen’s genome is simply absent from the database and the sequences in the dataset could thus not be classified? Here, we present a novel approach to this problem of detecting novel pathogens in metagenomic datasets by classifying the (segments of) proteins encoded by the sequences in the datasets. We train a neural network on the sequences of coding sequences, labeled by taxonomic domain, and use this neural network to predict the taxonomic classification of sequences that can not be classified by comparison to a reference database, thus facilitating the detection of potential novel pathogens.

Phytool, a ShinyApp to homogenise taxonomy of freshwater microalgae from DNA barcodes and microscopic observations

Methods for biomonitoring of freshwater phytoplankton are evolving rapidly with eDNA-based methods, offering great complementarity with microscopy. Metabarcoding approaches have been more commonly used over the last years, with a continuous increase in the amount of data generated. Depending on the researchers and the way they assigned barcodes to species (bioinformatic pipelines and molecular reference databases), the taxonomic assignment obtained for HTS DNA reads might vary. This is also true for traditional taxonomic studies by microscopy with regular adjustments of the classification and taxonomy. For those reasons (leading to non-homogeneous taxonomies), gap-analyses and comparisons between studies become even more challenging and the curation processes to find potential consensus names are time-consuming. Here, we present a web-based application (Phytool), developed with ShinyApp (Rstudio), that aims to make the harmonisation of taxonomy easier and in a more efficient way, using a complete and up-to-date taxonomy reference database for freshwater microalgae. Phytool allows users to homogenise and update freshwater phytoplankton taxonomical names from sequence files and data tables directly uploaded in the application. It also gathers barcodes from curated references in a user-friendly way in which it is possible to search for specific organisms. All the data provided are downloadable with the possibility to apply filters in order to select only the required taxa and fields (e.g. specific taxonomic ranks). The main goal is to make accessible to a broad range of users the connection between microscopy and molecular biology and taxonomy through different ready-to-use functions. This study estimates that only 25% of species of freshwater phytoplankton in Phytobs are associated with a barcode. We plead for an increased effort to enrich reference databases by coupling taxonomy and molecular methods. Phytool should make this crucial work more efficient. The application is available at https://caninuzzo.shinyapps.io/phytool_v1/