Oxford nanopore sequencing in clinical microbiology and infection diagnostics.

Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.

Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.

Nanopore sequencing device analysis systems simultaneously generate multiple picoamperage current signals representing the passage of DNA or RNA nucleotides ratcheted through a biomolecule nanopore array by motor proteins. Squiggles are a noisy and time-distorted representation of an underlying nucleotide sequence, "gold standard model", due to experimental and algorithmic artefacts. Other research fields use dynamic time warped-space averaging (DTWA) algorithms to produce a consensus signal from multiple time-warped sources while preserving key features distorted by standard, linear-averaging approaches. We compared the ability of DTW Barycentre averaging (DBA), minimize mean (MM) and stochastic sub-gradient descent (SSG) DTWA algorithms to generate a consensus signal from squiggle-space ensembles of RNA molecules Enolase, Sequin R1-71-1 and Sequin R2-55-3 without knowledge of their associated gold standard model. We propose techniques to identify the leader and distorted squiggle features prior to DTWA consensus generation. New visualization and warping-path metrics are introduced to compare consensus signals and the best estimate of the "true" consensus, the study's gold standard model. The DBA consensus was the best match to the gold standard for both Sequin studies but was outperformed in the Enolase study. Given an underlying common characteristic across a squiggle ensemble, we objectively evaluate a novel "voting scheme" that improves the local similarity between the consensus signal and a given fraction of the squiggle ensemble. While the gold standard is not used during voting, the increase in the match of the final voted-on consensus to the underlying Enolase and Sequin gold standard sequences provides an indirect success measure for the proposed voting procedure in two ways: First is the decreased least squares warped distance between the final consensus and the gold model, and second, the voting generates a final consensus length closer to the known underlying RNA biomolecule length. The results suggest considerable potential in marrying squiggle analysis and voted-on DTWA consensus signals to provide low-noise, low-distortion signals. This will lead to improved accuracy in detecting nucleotides and their deviation model due to chemical modifications (a.k.a. epigenetic information). The proposed combination of ensemble voting and DTWA has application in other research fields involving time-distorted, high entropy signals.

The lifelong impact of fetal growth restriction on cardiac development.

BACKGROUND: Maternal nutrient restriction (MNR) is a widespread cause of fetal growth restriction (FGR), an independent predictor of heart disease and cardiovascular mortality. Our objective was to examine the developmental and long-term impact of MNR-induced FGR on cardiac structure in a model that closely mimics human development. METHODS: A reduction in total caloric intake spanning pregestation through to lactation in guinea pig sows was used to induce FGR. Proliferation, differentiation, and apoptosis of cardiomyocytes were assessed in late-gestation fetal, neonatal, and adult guinea pig hearts. Proteomic analysis and pathway enrichment were performed on fetal hearts. RESULTS: Cardiomyocyte proliferation and the number of mononucleated cells were enhanced in the MNR-FGR fetal and neonatal heart, suggesting a delay in cardiomyocyte differentiation. In fetal hearts of MNR-FGR animals, apoptosis was markedly elevated and the total number of cardiomyocytes reduced, the latter remaining so throughout neonatal and into adult life. A reduction in total cardiomyocyte number in adult MNR-FGR hearts was accompanied by exaggerated hypertrophy and a disorganized architecture. Pathway analysis identified genes related to cell proliferation, differentiation, and survival. CONCLUSIONS: FGR influences cardiomyocyte development during critical windows of development, leading to a permanent deficiency in cardiomyocyte number and compensatory hypertrophy in a rodent model that recapitulates human development.

SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models.

BACKGROUND: Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. RESULTS: SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. CONCLUSIONS: SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/.

An expression-directed linear mixed model discovering low-effect genetic variants.

Detecting genetic variants with low-effect sizes using a moderate sample size is difficult, hindering downstream efforts to learn pathology and estimating heritability. In this work, by utilizing informative weights learned from training genetically predicted gene expression models, we formed an alternative approach to estimate the polygenic term in a linear mixed model. Our linear mixed model estimates the genetic background by incorporating their relevance to gene expression. Our protocol, expression-directed linear mixed model, enables the discovery of subtle signals of low-effect variants using moderate sample size. By applying expression-directed linear mixed model to cohorts of around 5,000 individuals with either binary (WTCCC) or quantitative (NFBC1966) traits, we demonstrated its power gain at the low-effect end of the genetic etiology spectrum. In aggregate, the additional low-effect variants detected by expression-directed linear mixed model substantially improved estimation of missing heritability. Expression-directed linear mixed model moves precision medicine forward by accurately detecting the contribution of low-effect genetic variants to human diseases.

Genomic compartmentalization of gene families encoding core components of metazoan signaling systems.

To investigate the role of gene localization and genome organization in cell-cell signalling and regulation, we mapped the distribution pattern of gene families that comprise core components of intercellular communication networks. Our study is centered on the distinct evolutionarily conserved metazoan signalling pathways that employ proteins in the receptor tyrosine kinase, WNT, hedgehog, NOTCH, Janus kinase/STAT, transforming growth factor beta, and nuclear hormone receptor protein families. Aberrant activity of these signalling pathways is closely associated with the promotion and maintenance of human cancers. The cataloguing and mapping of genes encoding these signalling proteins and comparisons across species has led us to propose that the genome can be subdivided into six genome-wide primary linkage groups (PLGs). PLGs are composed of assemblages of gene families that are often mutually exclusive, raising the possibility of unique functional identities for each group. Examination of the localization patterns of genes with distinct functions in signal transduction demonstrates dichotomous segregation patterns. For example, gene families of cell-surface receptors localize to genomic compartments that are distinct from the locations of their cognate ligand gene families. Additionally, genes encoding negative-acting components of signalling pathways (inhibitors and antagonists) are topologically separated from their positive regulators and other signal transducer genes. We, therefore, propose the existence of conserved genomic territories that encode key proteins required for the proper activity of metazoan signaling and regulatory systems. Disruption in this pattern of topologic genomic organization may contribute to aberrant regulation in hereditary or acquired diseases such as cancer. We further propose that long-range looping genomic regulatory interactions may provide a mechanism favouring the remarkable retention of these conserved gene clusters during chordate evolution.

Sequential multi-omics analysis identifies clinical phenotypes and predictive biomarkers for long COVID.

The post-acute sequelae of COVID-19 (PASC), also known as long COVID, is often associated with debilitating symptoms and adverse multisystem consequences. We obtain plasma samples from 117 individuals during and 6 months following their acute phase of infection to comprehensively profile and assess changes in cytokines, proteome, and metabolome. Network analysis reveals sustained inflammatory response, platelet degranulation, and cellular activation during convalescence accompanied by dysregulation in arginine biosynthesis, methionine metabolism, taurine metabolism, and tricarboxylic acid (TCA) cycle processes. Furthermore, we develop a prognostic model composed of 20 molecules involved in regulating T cell exhaustion and energy metabolism that can reliably predict adverse clinical outcomes following discharge from acute infection with 83% accuracy and an area under the curve (AUC) of 0.96. Our study reveals pertinent biological processes during convalescence that differ from acute infection, and it supports the development of specific therapies and biomarkers for patients suffering from long COVID.

Kupffer cell-like syncytia replenish resident macrophage function in the fibrotic liver.

Kupffer cells (KCs) are localized in liver sinusoids but extend pseudopods to parenchymal cells to maintain their identity and serve as the body's central bacterial filter. Liver cirrhosis drastically alters vascular architecture, but how KCs adapt is unclear. We used a mouse model of liver fibrosis and human tissue to examine immune adaptation. Fibrosis forced KCs to lose contact with parenchymal cells, down-regulating "KC identity," which rendered them incapable of clearing bacteria. Commensals stimulated the recruitment of monocytes through CD44 to a spatially distinct vascular compartment. There, recruited monocytes formed large aggregates of multinucleated cells (syncytia) that expressed phenotypical KC markers and displayed enhanced bacterial capture ability. Syncytia formed via CD36 and were observed in human cirrhosis as a possible antimicrobial defense that evolved with fibrosis.

Methylene blue in combination with sunlight as a low cost and effective disinfection method for coronavirus-contaminated PPE.

Using the Murine Hepatitis Virus (MHV) A59 coronavirus as a SARS-CoV-2 animal surrogate, we validated that methylene blue (MB) in combination with sunlight exposure is a robust, fast, and low-cost decontamination method for PPE that should be added to the toolbox of practical pandemic preparedness.

Disease-specific motifs can be identified in circulating nucleic acids from live elk and cattle infected with transmissible spongiform encephalopathies.

To gain insight into the disease progression of transmissible spongiform encephalopathies (TSE), we searched for disease-specific patterns in circulating nucleic acids (CNA) in elk and cattle. In a 25-month time-course experiment, CNAs were isolated from blood samples of 24 elk (Cervus elaphus) orally challenged with chronic wasting disease (CWD) infectious material. In a separate experiment, blood-sample CNAs from 29 experimental cattle (Bos taurus) 40 months post-inoculation with clinical bovine spongiform encephalopathy (BSE) were analyzed according to the same protocol. Next-generation sequencing provided broad elucidation of sample CNAs: we detected infection-specific sequences as early as 11 months in elk (i.e. at least 3 months before the appearance of the first clinical signs) and we established CNA patterns related to BSE in cattle at least 4 months prior to clinical signs. In elk, a progression of CNA sequence patterns was found to precede and correlate with macro-observable disease progression, including delayed CWD progression in elk with PrP genotype LM. Some of the patterns identified contain transcription-factor-binding sites linked to endogenous retroviral integration. These patterns suggest that retroviruses may be connected to the manifestation of TSEs. Our results may become useful for the early diagnosis of TSE in live elk and cattle.

Reconstructing SARS-CoV-2 infection dynamics through the phylogenetic inference of unsampled sources of infection.

The COVID-19 pandemic has illustrated the importance of infection tracking. The role of asymptomatic, undiagnosed individuals in driving infections within this pandemic has become increasingly evident. Modern phylogenetic tools that take into account asymptomatic or undiagnosed individuals can help guide public health responses. We finetuned established phylogenetic pipelines using published SARS-CoV-2 genomic data to examine reasonable estimate transmission networks with the inference of unsampled infection sources. The system utilised Bayesian phylogenetics and TransPhylo to capture the evolutionary and infection dynamics of SARS-CoV-2. Our analyses gave insight into the transmissions within a population including unsampled sources of infection and the results aligned with epidemiological observations. We were able to observe the effects of preventive measures in Canada's "Atlantic bubble" and in populations such as New York State. The tools also inferred the cross-species disease transmission of SARS-CoV-2 transmission from humans to lions and tigers in New York City's Bronx Zoo. These phylogenetic tools offer a powerful approach in response to both the COVID-19 and other emerging infectious disease outbreaks.

Characterization of microglial transcriptomes in the brain and spinal cord of mice in early and late experimental autoimmune encephalomyelitis using a RiboTag strategy.

Microglia play an important role in the pathogenesis of multiple sclerosis and the mouse model of MS, experimental autoimmune encephalomyelitis (EAE). To more fully understand the role of microglia in EAE we characterized microglial transcriptomes before the onset of motor symptoms (pre-onset) and during symptomatic EAE. We compared the transcriptome in brain, where behavioral changes are initiated, and spinal cord, where damage is revealed as motor and sensory deficits. We used a RiboTag strategy to characterize ribosome-bound mRNA only in microglia without incurring possible transcriptional changes after cell isolation. Brain and spinal cord samples clustered separately at both stages of EAE, indicating regional heterogeneity. Differences in gene expression were observed in the brain and spinal cord of pre-onset and symptomatic animals with most profound effects in the spinal cord of symptomatic animals. Canonical pathway analysis revealed changes in neuroinflammatory pathways, immune functions and enhanced cell division in both pre-onset and symptomatic brain and spinal cord. We also observed a continuum of many pathways at pre-onset stage that continue into the symptomatic stage of EAE. Our results provide additional evidence of regional and temporal heterogeneity in microglial gene expression patterns that may help in understanding mechanisms underlying various symptomology in MS.

Interoperability with Moby 1.0--it's better than sharing your toothbrush!

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.

Stirred suspension bioreactors maintain naïve pluripotency of human pluripotent stem cells.

Due to their ability to standardize key physiological parameters, stirred suspension bioreactors can potentially scale the production of quality-controlled pluripotent stem cells (PSCs) for cell therapy application. Because of differences in bioreactor expansion efficiency between mouse (m) and human (h) PSCs, we investigated if conversion of hPSCs, from the conventional "primed" pluripotent state towards the "naïve" state prevalent in mPSCs, could be used to enhance hPSC production. Through transcriptomic enrichment of mechano-sensing signaling, the expression of epigenetic regulators, metabolomics, and cell-surface protein marker analyses, we show that the stirred suspension bioreactor environment helps maintain a naïve-like pluripotent state. Our research corroborates that converting hPSCs towards a naïve state enhances hPSC manufacturing and indicates a potentially important role for the stirred suspension bioreactor's mechanical environment in maintaining naïve-like pluripotency.

A shared core microbiome in soda lakes separated by large distances.

In alkaline soda lakes, concentrated dissolved carbonates establish productive phototrophic microbial mats. Here we show how microbial phototrophs and autotrophs contribute to this exceptional productivity. Amplicon and shotgun DNA sequencing data of microbial mats from four Canadian soda lakes indicate the presence of > 2,000 species of Bacteria and Eukaryotes. We recover metagenome-assembled-genomes for a core microbiome of < 100 abundant bacteria, present in all four lakes. Most of these are related to microbes previously detected in sediments of Asian alkaline lakes, showing that common selection principles drive community assembly from a globally distributed reservoir of alkaliphile biodiversity. Detection of > 7,000 proteins show how phototrophic populations allocate resources to specific processes and occupy complementary niches. Carbon fixation proceeds by the Calvin-Benson-Bassham cycle, in Cyanobacteria, Gammaproteobacteria, and, surprisingly, Gemmatimonadetes. Our study provides insight into soda lake ecology, as well as a template to guide efforts to engineer biotechnology for carbon dioxide conversion.

Differential microglia and macrophage profiles in human IDH-mutant and -wild type glioblastoma.

Microglia and macrophages are the largest component of the inflammatory infiltrate in glioblastoma (GBM). However, whether there are differences in their representation and activity in the prognostically-favorable isocitrate dehydrogenase (IDH)-mutated compared to -wild type GBMs is unknown. Studies on human specimens of untreated IDH-mutant GBMs are rare given they comprise 10% of all GBMs and often present at lower grades, receiving treatments prior to dedifferentiation that can drastically alter microglia and macrophage phenotypes. We were able to obtain large samples of four previously untreated IDH-mutant GBM. Using flow cytometry, immunofluorescence techniques with automated segmentation protocols that quantify at the individual-cell level, and comparison between single-cell RNA-sequencing (scRNA-seq) databases of human GBM, we discerned dissimilarities between GBM-associated microglia and macrophages (GAMMs) in IDH-mutant and -wild type GBMs. We found there are significantly fewer GAMM in IDH-mutant GBMs, but they are more pro-inflammatory, suggesting this contributes to the better prognosis of these tumors. Our pro-inflammatory score which combines the expression of inflammatory markers (CD68/HLA-A, -B, -C/TNF/CD163/IL10/TGFB2), Iba1 intensity, and GAMM surface area also indicates that more pro-inflammatory GAMMs are associated with longer overall survival independent of IDH status. Interrogation of scRNA-seq databases demonstrates microglia in IDH-mutants are mainly pro-inflammatory, while anti-inflammatory macrophages that upregulate genes such as FCER1G and TYROBP predominate in IDH-wild type GBM. Taken together, these observations are the first head-to-head comparison of GAMMs in treatment-naïve IDH-mutant versus -wild type GBMs. Our findings highlight biological disparities in the innate immune microenvironment related to IDH prognosis that can be exploited for therapeutic purposes.

Characterization of a Unique Form of Arrhythmic Cardiomyopathy Caused by Recessive Mutation in LEMD2.

Nuclear envelope proteins have been shown to play an important role in the pathogenesis of inherited dilated cardiomyopathy. Here, we present a remarkable cardiac phenotype caused by a homozygous LEMD2 mutation in patients of the Hutterite population with juvenile cataract. Mutation carriers develop arrhythmic cardiomyopathy with mild impairment of left ventricular systolic function but severe ventricular arrhythmias leading to sudden cardiac death. Affected cardiac tissue from a deceased patient and fibroblasts exhibit elongated nuclei with abnormal condensed heterochromatin at the periphery. The patient fibroblasts demonstrate cellular senescence and reduced proliferation capacity, which may suggest an involvement of LEM domain containing protein 2 in chromatin remodeling processes and premature aging.

Glucocorticoid-driven transcriptomes in human airway epithelial cells: commonalities, differences and functional insight from cell lines and primary cells.

BACKGROUND: Glucocorticoids act on the glucocorticoid receptor (GR; NR3C1) to resolve inflammation and, as inhaled corticosteroids (ICS), are the cornerstone of treatment for asthma. However, reduced efficacy in severe disease or exacerbations indicates a need to improve ICS actions. METHODS: Glucocorticoid-driven transcriptomes were compared using PrimeView microarrays between primary human bronchial epithelial (HBE) cells and the model cell lines, pulmonary type II A549 and bronchial epithelial BEAS-2B cells. RESULTS: In BEAS-2B cells, budesonide induced (≥2-fold, P ≤ 0.05) or, in a more delayed fashion, repressed (≤0.5-fold, P ≤ 0.05) the expression of 63, 133, 240, and 257 or 15, 56, 236, and 344 mRNAs at 1, 2, 6, and 18 h, respectively. Within the early-induced mRNAs were multiple transcriptional activators and repressors, thereby providing mechanisms for the subsequent modulation of gene expression. Using the above criteria, 17 (BCL6, BIRC3, CEBPD, ERRFI1, FBXL16, FKBP5, GADD45B, IRS2, KLF9, PDK4, PER1, RGCC, RGS2, SEC14L2, SLC16A12, TFCP2L1, TSC22D3) induced and 8 (ARL4C, FLRT2, IER3, IL11, PLAUR, SEMA3A, SLC4A7, SOX9) repressed mRNAs were common between A549, BEAS-2B and HBE cells at 6 h. As absolute gene expression change showed greater commonality, lowering the cut-off (≥1.25 or ≤ 0.8-fold) within these groups produced 93 induced and 82 repressed genes in common. Since large changes in few mRNAs and/or small changes in many mRNAs may drive function, gene ontology (GO)/pathway analyses were performed using both stringency criteria. Budesonide-induced genes showed GO term enrichment for positive and negative regulation of transcription, signaling, proliferation, apoptosis, and movement, as well as FOXO and PI3K-Akt signaling pathways. Repressed genes were enriched for inflammatory signaling pathways (TNF, NF-κB) and GO terms for cytokine activity, chemotaxis and cell signaling. Reduced growth factor expression and effects on proliferation and apoptosis were highlighted. CONCLUSIONS: While glucocorticoids repress mRNAs associated with inflammation, prior induction of transcriptional activators and repressors may explain longer-term responses to these agents. Furthermore, positive and negative effects on signaling, proliferation, migration and apoptosis were revealed. Since many such gene expression changes occurred in human airways post-ICS inhalation, the effects observed in cell lines and primary HBE cells in vitro may be relevant to ICS in vivo.

Interspecies data mining to predict novel ING-protein interactions in human.

BACKGROUND: The INhibitor of Growth (ING) family of type II tumor suppressors (ING1-ING5) is involved in many cellular processes such as cell aging, apoptosis, DNA repair and tumorigenesis. To expand our understanding of the proteins with which the ING proteins interact, we designed a method that did not depend upon large-scale proteomics-based methods, since they may fail to highlight transient or relatively weak interactions. Here we test a cross-species (yeast, fly, and human) bioinformatics-based approach to identify potential human ING-interacting proteins with higher probability and accuracy than approaches based on screens in a single species. RESULTS: We confirm the validity of this screen and show that ING1 interacts specifically with three of the three proteins tested; p38MAPK, MEKK4 and RAD50. These novel ING-interacting proteins further link ING proteins to cell stress and DNA damage signaling, providing previously unknown upstream links to DNA damage response pathways in which ING1 participates. The bioinformatics approach we describe can be used to create an interaction prediction list for any human proteins with yeast homolog(s). CONCLUSION: None of the validated interactions were predicted by the conventional protein-protein interaction tools we tested. Validation of our approach by traditional laboratory techniques shows that we can extract value from the voluminous weak interaction data already elucidated in yeast and fly databases. We therefore propose that the weak (low signal to noise ratio) data from large-scale interaction datasets are currently underutilized.

Maintenance of ancestral complexity and non-metazoan genes in two basal cnidarians.

Cnidarians are among the simplest extant animals; however EST analyses reveal that they have a remarkably high level of genetic complexity. In this article, we show that the full diversity of metazoan signaling pathways is represented in this phylum, as are antagonists previously known only in chordates. Many of the cnidarian ESTs match genes previously known only in non-animal kingdoms. At least some of these represent ancient genes lost by all bilaterians examined so far, rather than genes gained by recent lateral gene transfer.