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Arrhythmogenic cardiomyopathy is an inherited heart muscle disorder leading to ventricular arrhythmias and heart failure, mainly as a result of mutations in cardiac desmosomal genes. Desmosomes are cell-cell junctions mediating adhesion of cardiomyocytes; however, the molecular and cellular mechanisms underlying the disease remain widely unknown. Desmocollin-2 is a desmosomal cadherin serving as an anchor molecule required to reconstitute homeostatic intercellular adhesion with desmoglein-2. Cardiac specific lack of desmoglein-2 leads to severe cardiomyopathy, whereas overexpression does not. In contrast, the corresponding data for desmocollin-2 are incomplete, in particular from the view of protein overexpression. Therefore, we developed a mouse model overexpressing desmocollin-2 to determine its potential contribution to cardiomyopathy and intercellular adhesion pathology. We generated transgenic mice overexpressing DSC2 in cardiac myocytes. Transgenic mice developed a severe cardiac dysfunction over 5 to 13 weeks as indicated by 2D-echocardiography measurements. Corresponding histology and immunohistochemistry demonstrated fibrosis, necrosis and calcification which were mainly localized in patches near the epi- and endocardium of both ventricles. Expressions of endogenous desmosomal proteins were markedly reduced in fibrotic areas but appear to be unchanged in non-fibrotic areas. Furthermore, gene expression data indicate an early up-regulation of inflammatory and fibrotic remodeling pathways between 2 to 3.5 weeks of age. Cardiac specific overexpression of desmocollin-2 induces necrosis, acute inflammation and patchy cardiac fibrotic remodeling leading to fulminant biventricular cardiomyopathy.

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.

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.

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.

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.

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. Alkaline lakes have some of the highest productivity rates in freshwater ecosystems. Here the authors report amplicon, metagenome, and proteome sequencing from microbial mat communities of four alkaline lakes in Canada, and compare these lakes to central Asian soda lakes, revealing a shared core microbiome despite the geographical distance.

Elicitor-induced sanguinarine accumulation in opium poppy (Papaver somniferum) cell cultures provides a responsive model system to profile modulations in gene transcripts and metabolites related to alkaloid biosynthesis. An annotated expressed sequence tag (EST) database was assembled from 10,224 random clones isolated from an elicitor-treated opium poppy cell culture cDNA library. The most abundant ESTs encoded defense proteins, and enzymes involved in alkaloid metabolism and S-adenosylmethionine-dependent methyl transfer. ESTs corresponding to 40 enzymes involved in the conversion of sucrose to sanguinarine were identified. A corresponding DNA microarray was probed with RNA from cell cultures collected at various time-points after elicitor treatment, and compared with RNA from control cells. Several diverse transcript populations were coordinately induced, with alkaloid biosynthetic enzyme and defense protein transcripts displaying the most rapid and substantial increases. In addition to all known sanguinarine biosynthetic gene transcripts, mRNAs encoding several upstream primary metabolic enzymes were coordinately induced. Fourier transform-ion cyclotron resonance-mass spectrometry was used to characterize the metabolite profiles of control and elicitor-treated cell cultures. Principle component analysis revealed a significant and dynamic separation in the metabolome, represented by 992 independent detected analytes, in response to elicitor treatment. Identified metabolites included sanguinarine, dihydrosanguinarine, and the methoxylated derivatives dihydrochelirubine and chelirubine, and the alkaloid pathway intermediates N-methylcoclaurine, N-methylstylopine, and protopine. Some of the detected analytes showed temporal changes in abundance consistent with modulations in the profiles of alkaloid biosynthetic gene transcripts.

Replicative senescence occurs in response to shortened telomeres and is triggered by ATM and TP53‐mediated DNA damage signaling that blocks replication. hTERT lengthens telomeres, which is thought to block damage signaling and the onset of senescence. We find that normal diploid fibroblasts expressing hTERT mutants unable to maintain telomere length do not initiate DNA damage signaling and continue to replicate, despite having telomeres shorter than senescent cells. The TRF1 and TRF2 DNA binding proteins of the shelterin complex stabilize telomeres, and we find that expression of different mutant hTERT proteins decreases levels of the Siah1 E3 ubiquitin ligase that targets TRF2 to the proteasome, by increasing levels of the CDC20 and FBXO5 E3 ligases that target Siah1. This restores the TRF2:TRF1 ratio to block the activation of ATM and subsequent activation of TP53 that is usually associated with DNA damage‐induced senescence signaling. All hTERT variants reduce DNA damage signaling, and this occurs concomitantly with telomeres assuming a more compact, denser conformation than senescent cells as measured by super‐resolution microscopy. This indicates that hTERT variants induce TRF2‐mediated telomere compaction that is independent of telomere length, and it plays a dominant role in regulating the DNA damage signaling that induces senescence and blocks replication of human fibroblasts. These observations support the idea that very short telomeres often seen in cancer cells may fail to induce senescence due to selective stabilization of components of the shelterin complex, increasing telomere density, rather than maintaining telomere length via the reverse transcriptase activity of hTERT. In contrast to the dogma that a subset of short telomeres initiates senescence, hTERT variants unable to maintain telomere length block senescence by stabilizing TRF2 via inhibiting upstream E3 ubiquitin ligases. This noncanonical hTERT function also compacts telomeres and blocks senescence‐associated DNA damage signaling. Cancer cells expressing hTERT may bypass senescence by maintaining TRF2 levels and telomere density to block DNA damage signaling and become immortal, even with very short telomeres.

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/ .