Deep Coverage Research Articles

Uncovering Molecular Heterogeneity in the Kidney With Spatially Targeted Mass Spectrometry.

The kidney functions through the coordination of approximately one million multifunctional nephrons in 3-dimensional space. Molecular understanding of the kidney has relied on transcriptomic, proteomic, and metabolomic analyses of kidney homogenate, but these approaches do not resolve cellular identity and spatial context. Mass spectrometry analysis of isolated cells retains cellular identity but not information regarding its cellular neighborhood and extracellular matrix. Spatially targeted mass spectrometry is uniquely suited to molecularly characterize kidney tissue while retaining in situ cellular context. This review summarizes advances in methodology and technology for spatially targeted mass spectrometry analysis of kidney tissue. Profiling technologies such as laser capture microdissection (LCM) coupled to liquid chromatography tandem mass spectrometry provide deep molecular coverage of specific tissue regions, while imaging technologies such as matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) molecularly profile regularly spaced tissue regions with greater spatial resolution. These technologies individually have furthered our understanding of heterogeneity in nephron regions such as glomeruli and proximal tubules, and their combination is expected to profoundly expand our knowledge of the kidney in health and disease.

A mammalian methylation array for profiling methylation levels at conserved sequences

Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures up to 36k CpGs per species that are well conserved across many mammalian species. We designed a set of probes that can tolerate specific cross-species mutations. We annotate the array in over 200 species and report CpG island status and chromatin states in select species. Calibration experiments demonstrate the high fidelity in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of conserved cytosines facilitating the development of epigenetic biomarkers, and it increases the probability that biological insights gained in one species will translate to others.

High Spatial Resolution MALDI Imaging Mass Spectrometry of Fresh-Frozen Bone.

Bone and bone marrow are vital to mammalian structure, movement, and immunity. These tissues are also commonly subjected to molecular alterations giving rise to debilitating diseases like rheumatoid arthritis and osteomyelitis. Technologies such as matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) facilitate the discovery of spatially resolved chemical information in biological tissue samples to help elucidate the complex molecular processes underlying pathology. Traditionally, preparation of osseous tissue for MALDI IMS has been difficult due to its mineralized composition and heterogeneous morphology, and compensation for these challenges with decalcification and fixation protocols can remove or delocalize molecular species. Here, sample preparation methods were advanced to enable multimodal MALDI IMS of undecalcified, fresh-frozen murine femurs, allowing the distribution of endogenous lipids to be linked to tissue structures and cell types. Adhesive-bound bone sections were mounted onto conductive glass slides with microscopy-compatible glue and freeze-dried to minimize artificial bone marrow damage. High spatial resolution (10 μm) MALDI IMS was employed to characterize lipid distributions, and use of complementary microscopy modalities aided tissue and cell assignments. For example, various phosphatidylcholines localize to the bone marrow, adipose tissue, marrow adipose tissue, and muscle. Further, sphingomyelin(42:1) was abundant in megakaryocytes, whereas sphingomyelin(42:2) was diminished in this cell type. These data reflect the vast molecular and cellular heterogeneity indicative of the bone marrow and the soft tissue surrounding the femur. Multimodal MALDI IMS has the potential to advance bone-related biomedical research by offering deep molecular coverage with spatial relevance in a preserved native bone microenvironment.

Unearthing soil arthropod diversity through DNA metabarcoding.

DNA metabarcoding has the potential to greatly advance understanding of soil biodiversity, but this approach has seen limited application for the most abundant and species-rich group of soil fauna–the arthropods. This study begins to address this gap by comparing information on species composition recovered from metabarcoding two types of bulk samples (specimens, soil) from a temperate zone site and from bulk soil samples collected at eight sites in the Arctic. Analysis of 22 samples (3 specimen, 19 soil) revealed 410 arthropod OTUs belonging to 112 families, 25 orders, and nine classes. Studies at the temperate zone site revealed little overlap in species composition between soil and specimen samples, but more overlap at higher taxonomic levels (families, orders) and congruent patterns of α- and β-diversity. Expansion of soil analyses to the Arctic revealed locally rich, highly dissimilar, and spatially structured assemblages compatible with dispersal limited and environmentally driven assembly. The current study demonstrates that DNA metabarcoding of bulk soil enables rapid, large-scale assessments of soil arthropod diversity. However, deep sequence coverage is required to adequately capture the species present in these samples, and expansion of the DNA barcode reference library is necessary to improve taxonomic resolution of the sequences recovered through this approach.

A strategy for a high enrichment of insect mitochondrial DNA for mitogenomic analysis.

Next-generation sequencing has dramatically fostered insect mitogenomic research in recent years. However, studies on the insect mitochondrial genome (mitogenome) assembly mainly rely on the sequencing data from total DNA, which is not cost-effective as a huge data from nuclear DNA are wasted. Besides, many mitogenomic studies require genomic information from individual organisms, whereas the DNA yield from small individual insects is too low to meet the sequencing requirements. Here, we describe a strategy for a high enrichment of insect mitochondrial DNA (mtDNA) using rolling circle amplification (RCA) technique. This strategy consists of standard DNA extraction, RCA enrichment, next-generation sequencing and mitogenome assembly. We have evaluated the performance of this strategy on nine insect species representing eight families of insecta, three other invertebrates, and even two vertebrate specimens. Results show that our strategy is especially suitable for insects, which allows almost all tested insect mtDNA contents to reach 80% and above. A further examination of enrichment efficiency of our strategy among different taxa shows that it is also applicable to other invertebrates and even some vertebrates such as Rhacophorus and ptyas species, although its enrichment efficiency in these groups is lower than that of insects. After treatment with our strategy, small flux sequencing data can realize the assembly of mitogenome with deep coverage, providing a solid base for subsequent mitogenome-based studies.

Framing Migration in Southern European Media: Perceptions of Spanish, Italian, and Greek Specialized Journalists

ABSTRACT Greece, Italy, and Spain are the Southern European borders and the main entrances for migrants and refugees to Europe, a movement that was particularly visible after the 2015 “refugee crisis of the Mediterranean.” In this context, immigration is used as a political tool, and the object of major media coverage. However, previous studies have shown that this coverage tends to be partial and prejudiced. This study, conducted during the COVID-19 pandemic, uses the frame building theory to study the perceptions of journalists covering migration issues regarding ways to improve the representation of migrants in the media of these three countries. For that, in-depth interviews were conducted with 94 Greek, Italian, and Spanish journalists. The precarity of the profession, the focus on conflictive approaches, and discrimination based on national origin or religion are mentioned as the biggest challenges. Professionals covering this information demand more individualized and deeper coverage, giving the migrants’ condition greater visibility, and giving voice to the migrants themselves, as they are the protagonists of the stories. Greater attention to journalistic ethics and the defense of vulnerable groups is considered essential to achieve this.

Trapped Ion Mobility Spectrometry Reduces Spectral Complexity in Mass Spectrometry-Based Proteomics.

In bottom-up mass spectrometry-based proteomics, deep proteome coverage is limited by high cofragmentation rates. Cofragmentation occurs when more than one analyte is isolated by the quadrupole and the subsequent fragmentation event produces fragment ions of heterogeneous origin. One strategy to reduce cofragmentation rates is through effective peptide separation techniques such as chromatographic separation and, the more recently popularized, ion mobility (IM) spectrometry, which separates peptides by their collisional cross section. Here, we use a computational model to investigate the capability of the trapped IM spectrometry (TIMS) device at effectively separating peptide ions and quantify the separation power of the TIMS device in the context of a parallel accumulation-serial fragmentation (PASEF) workflow. We found that TIMS separation increases the number of interference-free MS1 peptide features 9.2-fold, while decreasing the average peptide density in precursor spectra 6.5-fold. In a data-dependent acquisition PASEF workflow, IM separation increases the number of spectra without cofragmentation by a factor of 4.1 and the number of high-quality spectra 17-fold. Using a categorical model, we estimate that this observed decrease in spectral complexity results in an increased likelihood for peptide spectral matches, which may improve peptide identification rates. In the context of a data-independent acquisition workflow, the reduction in spectral complexity resulting from IM separation is estimated to be equivalent to a 4-fold decrease in the isolation window width (from 25 to 6.5 Da). Our study demonstrates that TIMS separation decreases spectral complexity by reducing cofragmentation rates, suggesting that TIMS separation may contribute toward the high identification rates observed in PASEF workflows.

Parental Somatic Mosaicism Uncovers Inheritance of an Apparently De Novo GFAP Mutation.

Alexander disease is a leukodystrophy caused by heterozygous mutations of GFAP gene. Recurrence in siblings from healthy parents provides a confirmation to the transmission of variants through germinal mosaicism. With the use of DNA isolated from peripheral blood, next-generation sequencing (NGS) of GFAP locus was performed with deep coverage (≥500×) in 11 probands and their parents (trios) with probands heterozygous for apparently de novo GFAP mutations. Indeed, one parent had somatic mosaicism, estimated in the range of 8.9%–16%, for the mutant allele transmitted to the affected sibling. Parental germline mosaicism deserves attention, as it is critical in assessing the risk of recurrence in families with Alexander disease.

LC\u2013MS peak assignment based on unanimous selection by six machine learning algorithms

Recent mass spectrometry (MS)-based techniques enable deep proteome coverage with relative quantitative analysis, resulting in increased identification of very weak signals accompanied by increased data size of liquid chromatography (LC)–MS/MS spectra. However, the identification of weak signals using an assignment strategy with poorer performance results in imperfect quantification with misidentification of peaks and ratio distortions. Manually annotating a large number of signals within a very large dataset is not a realistic approach. In this study, therefore, we utilized machine learning algorithms to successfully extract a higher number of peptide peaks with high accuracy and precision. Our strategy evaluated each peak identified using six different algorithms; peptide peaks identified by all six algorithms (i.e., unanimously selected) were subsequently assigned as true peaks, which resulted in a reduction in the false-positive rate. Hence, exact and highly quantitative peptide peaks were obtained, providing better performance than obtained applying the conventional criteria or using a single machine learning algorithm.

In-depth assembly of organ and development dissected Picrorhiza kurroa proteome map using mass spectrometry

BackgroundPicrorhiza kurroa Royle ex Benth. being a rich source of phytochemicals, is a promising high altitude medicinal herb of Himalaya. The medicinal potential is attributed to picrosides i.e. iridoid glycosides, which synthesized in organ-specific manner through highly complex pathways. Here, we present a large-scale proteome reference map of P. kurroa, consisting of four morphologically differentiated organs and two developmental stages.ResultsWe were able to identify 5186 protein accessions (FDR < 1%) providing a deep coverage of protein abundance array, spanning around six orders of magnitude. Most of the identified proteins are associated with metabolic processes, response to abiotic stimuli and cellular processes. Organ specific sub-proteomes highlights organ specialized functions that would offer insights to explore tissue profile for specific protein classes. With reference to P. kurroa development, vegetative phase is enriched with growth related processes, however generative phase harvests more energy in secondary metabolic pathways. Furthermore, stress-responsive proteins, RNA binding proteins (RBPs) and post-translational modifications (PTMs), particularly phosphorylation and ADP-ribosylation play an important role in P. kurroa adaptation to alpine environment. The proteins involved in the synthesis of secondary metabolites are well represented in P. kurroa proteome. The phytochemical analysis revealed that marker compounds were highly accumulated in rhizome and overall, during the late stage of development.ConclusionsThis report represents first extensive proteomic description of organ and developmental dissected P. kurroa, providing a platform for future studies related to stress tolerance and medical applications.

Comparative Proteomics Demonstrates Altered Metabolism Pathways in Cotrimoxazole- Resistant and Amikacin-Resistant Klebsiella pneumoniae Isolates.

Antibiotic resistance (AMR) has always been a hot topic all over the world and its mechanisms are varied and complicated. Previous evidence revealed the metabolic slowdown in resistant bacteria, suggesting the important role of metabolism in antibiotic resistance. However, the molecular mechanism of reduced metabolism remains poorly understood, which inspires us to explore the global proteome change during antibiotic resistance. Here, the sensitive, cotrimoxazole-resistant, amikacin-resistant, and amikacin/cotrimoxazole -both-resistant KPN clinical isolates were collected and subjected to proteome analysis through liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). A deep coverage of 2,266 proteins were successfully identified and quantified in total, representing the most comprehensive protein quantification data by now. Further bioinformatic analysis showed down-regulation of tricarboxylic acid cycle (TCA) pathway and up-regulation of alcohol metabolic or glutathione metabolism processes, which may contribute to ROS clearance and cell survival, in drug-resistant isolates. These results indicated that metabolic pathway alteration was directly correlated with antibiotic resistance, which could promote the development of antibacterial drugs from “target” to “network.” Moreover, combined with minimum inhibitory concentration (MIC) of cotrimoxazole and amikacin on different KPN isolates, we identified nine proteins, including garK, uxaC, exuT, hpaB, fhuA, KPN_01492, fumA, hisC, and aroE, which might contribute mostly to the survival of KPN under drug pressure. In sum, our findings provided novel, non-antibiotic-based therapeutics against resistant KPN.

Insights from Initial Variant Detection by Sequencing Single Sperm in Cattle

Meiotic de novo mutation (DNM) is one of the important phenomena contributing to gamete genome diversity. However, except for humans and a few model organisms, they are not well studied in livestock, including cattle. Moreover, bulk sperm samples have been routinely utilized in experiments, which include millions of single sperm cells and only report high-frequency variants. In this study, we isolated and sequenced 143 single sperms from two Holstein bulls and identified hundreds of candidate DNM events in ten sperms with deep sequencing coverage. We estimated DNM rates ranging from 1.08 × 10−8 to 3.78 × 10−8 per nucleotide per generation. We further validated 12 out of 14 selected DNM events using Sanger sequencing. To our knowledge, this is the first single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of point mutations and male fertility. Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for genetic variant detection using single-cell sequencing data.

The LOFAR LBA Sky Survey: Deep Fields

We present the first sub-mJy (≈0.7 mJy beam−1) survey to be completed below 100 MHz, which is over an order of magnitude deeper than previously achieved for widefield imaging of any field at these low frequencies. The high-resolution (15 × 15 arcsec) image of the Boötes field at 34–75 MHz is made from 56 hours of observation with the LOw Frequency ARray (LOFAR) Low Band Antenna (LBA) system. The observations and data reduction, including direction-dependent calibration, are described here. We present a radio source catalogue containing 1948 sources detected over an area of 23.6 deg2, with a peak flux density threshold of 5σ. Using existing datasets, we characterise the astrometric and flux density uncertainties, finding a positional uncertainty of ∼​1.2 arcsec and a flux density scale uncertainty of about 5 per cent. Using the available deep 144-MHz data, we identified 144-MHz counterparts to all the 54-MHz sources, and produced a matched catalogue within the deep optical coverage area containing 829 sources. We calculate the Euclidean-normalised differential source counts and investigate the low-frequency radio source spectral indices between 54 and 144 MHz. Both show a general flattening in the radio spectral indices for lower flux density sources, from ∼ − 0.75 at 144-MHz flux densities between 100 and 1000 mJy to ∼ − 0.5 at 144-MHz flux densities between 5 and 10 mJy. Such flattening is attributable to a growing population of star forming galaxies and compact core-dominated AGN.

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.

Breed-specific reference sequence optimized mapping accuracy of NGS analyses for pigs

BackgroundReference sequences play a vital role in next-generation sequencing (NGS), impacting mapping quality during genome analyses. However, reference genomes usually do not represent the full range of genetic diversity of a species as a result of geographical divergence and independent demographic events of different populations. For the mitochondrial genome (mitogenome), which occurs in high copy numbers in cells and is strictly maternally inherited, an optimal reference sequence has the potential to make mitogenome alignment both more accurate and more efficient. In this study, we used three different types of reference sequences for mitogenome mapping, i.e., the commonly used reference sequence (CU-ref), the breed-specific reference sequence (BS-ref) and the sample-specific reference sequence (SS-ref), respectively, and compared the accuracy of mitogenome alignment and SNP calling among them, for the purpose of proposing the optimal reference sequence for mitochondrial DNA (mtDNA) analyses of specific populationsResultsFour pigs, representing three different breeds, were high-throughput sequenced, subsequently mapping reads to the reference sequences mentioned above, resulting in a largest mapping ratio and a deepest coverage without increased running time when aligning reads to a BS-ref. Next, single nucleotide polymorphism (SNP) calling was carried out by 18 detection strategies with the three tools SAMtools, VarScan and GATK with different parameters, using the bam results mapping to BS-ref. The results showed that all eighteen strategies achieved the same high specificity and sensitivity, which suggested a high accuracy of mitogenome alignment by the BS-ref because of a low requirement for SNP calling tools and parameter choices.ConclusionsThis study showed that different reference sequences representing different genetic relationships to sample reads influenced mitogenome alignment, with the breed-specific reference sequences being optimal for mitogenome analyses, which provides a refined processing perspective for NGS data.

Rapid Characterization of Complex Killer Cell Immunoglobulin-Like Receptor (KIR) Regions Using Cas9 Enrichment and Nanopore Sequencing.

Long-read sequencing approaches have considerably improved the quality and contiguity of genome assemblies. Such platforms bear the potential to resolve even extremely complex regions, such as multigenic immune families and repetitive stretches of DNA. Deep sequencing coverage, however, is required to overcome low nucleotide accuracy, especially in regions with high homopolymer density, copy number variation, and sequence similarity, such as the MHC and KIR gene clusters of the immune system. Therefore, we have adapted a targeted enrichment protocol in combination with long-read sequencing to efficiently annotate complex KIR gene regions. Using Cas9 endonuclease activity, segments of the KIR gene cluster were enriched and sequenced on an Oxford Nanopore Technologies platform. This provided sufficient coverage to accurately resolve and phase highly complex KIR haplotypes. Our strategy eliminates PCR-induced amplification errors, facilitates rapid characterization of large and complex multigenic regions, including its epigenetic footprint, and is applicable in multiple species, even in the absence of a reference genome.

Multiomics Method Enabled by Sequential Metabolomics and Proteomics for Human Pluripotent Stem-Cell-Derived Cardiomyocytes.

Human pluripotent stem-cell-derived cardiomyocytes (hPSC-CMs) show immense promise for patient-specific disease modeling, cardiotoxicity screening, and regenerative therapy development. However, thus far, hPSC-CMs in culture have not recapitulated the structural or functional properties of adult CMs in vivo. To gain global insight into hPSC-CM biology, we established a multiomics method for analyzing the hPSC-CM metabolome and proteome from the same cell culture, creating multidimensional profiles of hPSC-CMs. Specifically, we developed a sequential extraction to capture metabolites and proteins from the same hPSC-CM monolayer cultures and analyzed these extracts using high-resolution mass spectrometry. Using this method, we annotated 205 metabolites/lipids and 4319 proteins from 106 cells with high reproducibility. We further integrated the proteome and metabolome measurements to create network profiles of molecular phenotypes for hPSC-CMs. Out of 310 pathways identified using metabolomics and proteomics, 40 pathways were considered significantly overrepresented (false-discovery-rate-corrected p ≤ 0.05). Highly populated pathways included those involved in protein synthesis (ribosome, spliceosome), ATP generation (oxidative phosphorylation), and cardiac muscle contraction. This multiomics method achieves a deep coverage of metabolites and proteins, creating a multidimensional view of the hPSC-CM phenotype, which provides a strong technological foundation to advance the understanding of hPSC-CM biology. Raw data are available in the MassIVE repository with identifier MSV000088010.

Microbial characterisation and Cold-Adapted Predicted Protein (CAPP) database construction from the active layer of Greenland's permafrost.

ABSTRACTPermafrost represents a reservoir for the biodiscovery of cold-adapted proteins which are advantageous in industrial and medical settings. Comparisons between different thermo-adapted proteins can give important information for cold-adaptation bioengineering. We collected permafrost active layer samples from 34 points along a proglacial transect in southwest Greenland. We obtained a deep read coverage assembly (>164x) from nanopore and Illumina sequences for the purposes of i) analysing metagenomic and metatranscriptomic trends of the microbial community of this area, and ii) creating the Cold-Adapted Predicted Protein (CAPP) database. The community showed a similar taxonomic composition in all samples along the transect, with a solid permafrost-shaped community, rather than microbial trends typical of proglacial systems. We retrieved 69 high- and medium-quality metagenome-assembled clusters, 213 complete biosynthetic gene clusters and more than three million predicted proteins. The latter constitute the CAPP database that can provide cold-adapted protein sequence information for protein- and taxon-focused amino acid sequence modifications for the future bioengineering of cold-adapted enzymes. As an example, we focused on the enzyme polyphenol oxidase, and demonstrated how sequence variation information could inform its protein engineering.

Experimental Performance Evaluation of NB-IOT Deployment Modes in Urban Area

Narrow-band Internet of Things is a new promising radio technology standard that addresses the requirements of the IoT. The technology provides improved indoor coverage, support of massive number of low data rate devices, low delay sensitivity, ultra-low device cost, low device power consumption and optimized network architecture. The technology can be deployed in three different operational modes: (1) in-band, (2) guard-band, or (3) standalone in dedicated spectrum. The choice of NB-IoT deployment scenario has a significant impact on the quality and performance of the network. In this article, presented the results of an experimental study of the performance of all three scenarios for NB-IoT deploying in a real working cellular network under equal operating conditions for consideration. The following parameters chosen as an assessment measure: radio coverage, network capacity and user experience. The research shown that exact the standalone mode provide the best performance for these parameters. In addition, we have confirmed that all three NB-IoT scenarios coexist perfectly on 2G/4G networks and satisfy the original requirements of 3GPP's in deep coverage and robust quality of network service.

PRODUÇÃO, CIRCULAÇÃO E RECEPÇÃO DO JORNALISMO CONTEMPORÂNEO: BREVE PANORAMA

This text proposes to outline a brief overview of the conditions of production, circulation and consumption of journalism in a social context of deep media coverage, marked by ubiquity and interconnection. Critical-analytical, the article includes a literature review that combines studies of journalism with sociosemiotics, with the premise that media coverage promotes the autonomy of journalistic discourse in time and space and also fosters the access revolution. In the course of the information production cycle, circulation emerges with an instance of repositioning reception, also reconfiguring the role of production and catalyzing new communicative contracts.