Health monitoring in birds using bio-loggers and whole blood transcriptomics

AbstractMonitoring and early detection of emerging infectious diseases in wild animals is of crucial global importance, yet reliable ways to measure immune status and responses are lacking for animals in the wild. Here we assess the usefulness of bio-loggers for detecting disease outbreaks in free-living birds and confirm detailed responses using leukocyte composition and large-scale transcriptomics. We simulated natural infections by viral and bacterial pathogens in captive mallards (Anas platyrhynchos), an important natural vector for avian influenza virus. We show that body temperature, heart rate and leukocyte composition change reliably during an acute phase immune response. Using genome-wide gene expression profiling of whole blood across time points we confirm that immunostimulants activate pathogen-specific gene regulatory networks. By reporting immune response related changes in physiological and behavioural traits that can be studied in free-ranging populations, we provide baseline information with importance to the global monitoring of zoonotic diseases.

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Dynamics of host populations affected by the emerging fungal pathogen Batrachochytrium salamandrivorans

Royal Society Open Science ◽

10.1098/rsos.160801 ◽

2017 ◽

Vol 4 (3) ◽

pp. 160801 ◽

Cited By ~ 16

Author(s):

Benedikt R. Schmidt ◽

Claudio Bozzuto ◽

Stefan Lötters ◽

Sebastian Steinfartz

Keyword(s):

Emerging Infectious Diseases ◽

Disease Outbreaks ◽

Host Population ◽

Mitigation Measures ◽

Disease Emergence ◽

Batrachochytrium Salamandrivorans ◽

In The Wild ◽

Successful Control ◽

Using Data ◽

Local Extirpation

Emerging infectious diseases cause extirpation of wildlife populations. We use an epidemiological model to explore the effects of a recently emerged disease caused by the salamander-killing chytrid fungus Batrachochytrium salamandrivorans ( Bsal ) on host populations, and to evaluate which mitigation measures are most likely to succeed. As individuals do not recover from Bsal , we used a model with the states susceptible, latent and infectious, and parametrized the model using data on host and pathogen taken from the literature and expert opinion. The model suggested that disease outbreaks can occur at very low host densities (one female per hectare). This density is far lower than host densities in the wild. Therefore, all naturally occurring populations are at risk. Bsal can lead to the local extirpation of the host population within a few months. Disease outbreaks are likely to fade out quickly. A spatial variant of the model showed that the pathogen could potentially spread rapidly. As disease mitigation during outbreaks is unlikely to be successful, control efforts should focus on preventing disease emergence and transmission between populations. Thus, this emerging wildlife disease is best controlled through prevention rather than subsequent actions.

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MON-719 The Cellular and Molecular Landscape of Hypothalamic Patterning and Differentiation

Journal of the Endocrine Society ◽

10.1210/jendso/bvaa046.1237 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

Author(s):

Thomas Kim

Keyword(s):

Cell Fate ◽

Regulatory Networks ◽

Large Scale ◽

Molecular Mechanisms ◽

Brain Atlas ◽

Specific Gene ◽

Cell Fate Specification ◽

Human Hypothalamus ◽

Fate Specification ◽

Time Points

Abstract The hypothalamus is a central regulator of physiological homeostasis. During development, multiple transcription factors coordinate the patterning and specification of hypothalamic nuclei. However, the molecular mechanisms controlling hypothalamic patterning and cell fate specification are poorly understood. To identify genes that control these processes, we have used single-cell RNA sequencing (scRNA-Seq) to profile mouse hypothalamic gene expression across multiple developmental time points. We have further utilised scRNA-Seq to phenotype mutations in genes that play major roles in early hypothalamic patterning. To first understand hypothalamic development, hypothalami were collected at both embryonic (E10-E16, E18) and postnatal (PN4, PN8, PN14, PN45) time points. At early stages, when the bulk of hypothalamic patterning occurs (E11-E13), we observe a clear separation between mitotic progenitors and postmitotic neural precursor cells. We likewise observed clean segregation among cells expressing regional hypothalamic markers identified in previous large-scale analysis of hypothalamic development. This analysis reveals new region-specific markers and identifies candidate genes for selectively regulating patterning and cell fate specification in individual hypothalamic regions. With our rich dataset of developing mouse hypothalamus, we integrated our dataset with the Allen Brain Atlas in situ data, publicly available adult hypothalamic scRNA-Seq dataset to understand hierarchy of hypothalamic cell differentiation, as well as re-defining cell types of the hypothalamus. We next used scRNA-Seq to phenotype multiple mutant lines, including a line that has been extensively characterised as a proof of concept (Ctnnb1 overexpression), and lines that have not been characterised (Nkx2.1, Nkx2.2, Dlx1/2 deletion). We show that this approach can rapidly and comprehensively characterize mutants that have altered hypothalamic patterning, and in doing so, have identified multiple genes that simultaneously repress posterior hypothalamic identity while promoting prethalamic identity. This result supports a modified columnar model of organization for the diencephalon, where prethalamus and hypothalamus are situated in adjacent dorsal and ventral domains of the anterior diencephalon. These data serve as a resource for further studies of hypothalamic development and dysfunction, and able to delineate transcriptional regulatory networks of hypothalamic formation. Lastly, using our mouse hypothalamus as a guideline, we are comparing dataset of developing chicken, zebrafish and human hypothalamus, to identify evolutionarily conserved and divergent region-specific gene regulatory networks. We aim to use this knowledge and information of key molecular pathways of human hypothalamic development and produce human hypothalamus organoids.

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Lineage-Specific Epigenomic and Genomic Activation of the Oncogene HNF4A Promotes Gastrointestinal Adenocarcinomas

10.1101/812149 ◽

2019 ◽

Cited By ~ 1

Author(s):

Jian Pan ◽

Tiago C. Silva ◽

Nicole Gull ◽

Qian Yang ◽

Jasmine Plummer ◽

...

Keyword(s):

Regulatory Networks ◽

Large Scale ◽

The Cancer Genome Atlas ◽

Specific Gene ◽

Distal Enhancer ◽

Chromosome Conformation ◽

Chip Sequencing ◽

Specific Manner

AbstractBackgroundsGastrointestinal adenocarcinomas (GIACs) of the tubular GI tract including esophagus, stomach, colon and rectum comprise most GI cancers and share a spectrum of genomic features. However, the unified epigenomic changes specific to GIACs are less well-characterized.We applied mathematical algorithms to large-scale DNA methylome and transcriptome profiles to reconstruct transcription factor (TF) networks using 907 GIAC samples from The Cancer Genome Atlas (TCGA). Complementary epigenomic technologies were performed to investigate HNF4A activation, including Circularized Chromosome Conformation Capture (4C), Chromatin immunoprecipitation (ChIP) sequencing, Whole Genome Bisulfite Sequencing (WGBS), and Assay for Transposase-Accessible Chromatin (ATAC) sequencing. In vitro and in vivo cellular phenotypical assays were conducted to study HNF4A functions.ResultsWe identified a list of functionally hyperactive master regulator (MR)TFs shared across different GIACs. As the top candidate, HNF4A exhibited prominent genomic and epigenomic activation in a GIAC-specific manner. We further characterized a complex interplay between HNF4A promoter and three distal enhancer elements, which was coordinated by GIAC-specific MRTFs including ELF3, GATA4, GATA6 and KLF5. HNF4A also self-regulated its own promoter and enhancers. Functionally, HNF4A promoted cancer proliferation and survival by transcriptionally activating many downstream targets including HNF1A and factors of Interleukin signaling in a lineage-specific manner.ConclusionWe use a large cohort of patient samples and an unbiased mathematical approach to highlight lineage-specific oncogenic MRTFs, which provide new insights into the GIAC-specific gene regulatory networks, and identify potential therapeutic strategies against these common cancers.

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Large-scale modeling of condition-specific gene regulatory networks by information integration and inference

Nucleic Acids Research ◽

10.1093/nar/gku916 ◽

2014 ◽

Vol 42 (21) ◽

pp. e166-e166 ◽

Cited By ~ 10

Author(s):

Daniel Christian Ellwanger ◽

Jörn Florian Leonhardt ◽

Hans-Werner Mewes

Keyword(s):

Gene Regulatory Networks ◽

Information Integration ◽

Regulatory Networks ◽

Large Scale ◽

Specific Gene ◽

Scale Modeling ◽

Gene Regulatory ◽

Large Scale Modeling

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The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

British Journal of Cancer ◽

10.1038/s41416-021-01491-x ◽

2021 ◽

Author(s):

Ekaterina Bourova-Flin ◽

Samira Derakhshan ◽

Afsaneh Goudarzi ◽

Tao Wang ◽

Anne-Laure Vitte ◽

...

Keyword(s):

Gene Expression ◽

Squamous Cell ◽

Large Scale ◽

Biomarker Discovery ◽

Gene Expression Signature ◽

Predictive Biomarkers ◽

Specific Gene ◽

Specific Expression ◽

Intrinsic Nature ◽

Independent Cohort

Abstract Background Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test. Methods A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry. Results A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort. Discussion The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

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Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation

International Journal of Computer Vision ◽

10.1007/s11263-021-01494-4 ◽

2021 ◽

Author(s):

Mehdi Bahri ◽

Eimear O’ Sullivan ◽

Shunwang Gong ◽

Feng Liu ◽

Xiaoming Liu ◽

...

Keyword(s):

Large Scale ◽

Training Time ◽

3D Face ◽

In The Wild ◽

Previous State ◽

Surface Translation ◽

Visual Attention Mechanism ◽

Diverse Data ◽

Human Faces ◽

Robust To Noise

AbstractStandard registration algorithms need to be independently applied to each surface to register, following careful pre-processing and hand-tuning. Recently, learning-based approaches have emerged that reduce the registration of new scans to running inference with a previously-trained model. The potential benefits are multifold: inference is typically orders of magnitude faster than solving a new instance of a difficult optimization problem, deep learning models can be made robust to noise and corruption, and the trained model may be re-used for other tasks, e.g. through transfer learning. In this paper, we cast the registration task as a surface-to-surface translation problem, and design a model to reliably capture the latent geometric information directly from raw 3D face scans. We introduce Shape-My-Face (SMF), a powerful encoder-decoder architecture based on an improved point cloud encoder, a novel visual attention mechanism, graph convolutional decoders with skip connections, and a specialized mouth model that we smoothly integrate with the mesh convolutions. Compared to the previous state-of-the-art learning algorithms for non-rigid registration of face scans, SMF only requires the raw data to be rigidly aligned (with scaling) with a pre-defined face template. Additionally, our model provides topologically-sound meshes with minimal supervision, offers faster training time, has orders of magnitude fewer trainable parameters, is more robust to noise, and can generalize to previously unseen datasets. We extensively evaluate the quality of our registrations on diverse data. We demonstrate the robustness and generalizability of our model with in-the-wild face scans across different modalities, sensor types, and resolutions. Finally, we show that, by learning to register scans, SMF produces a hybrid linear and non-linear morphable model. Manipulation of the latent space of SMF allows for shape generation, and morphing applications such as expression transfer in-the-wild. We train SMF on a dataset of human faces comprising 9 large-scale databases on commodity hardware.

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Digital proximity tracing on empirical contact networks for pandemic control

Nature Communications ◽

10.1038/s41467-021-21809-w ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

G. Cencetti ◽

G. Santin ◽

A. Longa ◽

E. Pigani ◽

A. Barrat ◽

...

Keyword(s):

Large Scale ◽

Disease Outbreaks ◽

Physical Distance ◽

Contact Tracing ◽

Reproductive Number ◽

Modeling Framework ◽

Infectious Disease Outbreaks ◽

Contact Patterns ◽

Contact Data ◽

The Impact

AbstractDigital contact tracing is a relevant tool to control infectious disease outbreaks, including the COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features and heterogeneities of real-world contact patterns influencing contagion dynamics. We fill this gap with a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread in real environments. We find that restrictive policies are more effective in containing the epidemic but come at the cost of unnecessary large-scale quarantines. Policy evaluation through their efficiency and cost results in optimized solutions which only consider contacts longer than 15–20 minutes and closer than 2–3 meters to be at risk. Our results show that isolation and tracing can help control re-emerging outbreaks when some conditions are met: (i) a reduction of the reproductive number through masks and physical distance; (ii) a low-delay isolation of infected individuals; (iii) a high compliance. Finally, we observe the inefficacy of a less privacy-preserving tracing involving second order contacts. Our results may inform digital contact tracing efforts currently being implemented across several countries worldwide.

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Multiple Alu exonization in 3’UTR of a primate specific isoform of CYP20A1 creates a potential miRNA sponge

Genome Biology and Evolution ◽

10.1093/gbe/evaa233 ◽

2020 ◽

Author(s):

Aniket Bhattacharya ◽

Vineet Jha ◽

Khushboo Singhal ◽

Mahar Fatima ◽

Dayanidhi Singh ◽

...

Keyword(s):

Heat Shock ◽

Cortical Neurons ◽

Regulatory Networks ◽

Large Scale ◽

Neuronal Development ◽

Random Sets ◽

Rna Seq ◽

Orphan Gene ◽

Mirna Sponge ◽

Human Neurons

Abstract Alu repeats contribute to phylogenetic novelties in conserved regulatory networks in primates. Our study highlights how exonized Alus could nucleate large-scale mRNA-miRNA interactions. Using a functional genomics approach, we characterize a transcript isoform of an orphan gene, CYP20A1 (CYP20A1_Alu-LT) that has exonization of 23 Alus in its 3’UTR. CYP20A1_Alu-LT, confirmed by 3’RACE, is an outlier in length (9 kb 3’UTR) and widely expressed. Using publically available datasets, we demonstrate its expression in higher primates and presence in single nucleus RNA-seq of 15928 human cortical neurons. miRanda predicts ∼4700 miRNA recognition elements (MREs) for ∼1000 miRNAs, primarily originated within these 3’UTR-Alus. CYP20A1_Alu-LT could be a potential multi-miRNA sponge as it harbors ≥10 MREs for 140 miRNAs and has cytosolic localization. We further tested whether expression of CYP20A1_Alu-LT correlates with mRNAs harboring similar MRE targets. RNA-seq with conjoint miRNA-seq analysis was done in primary human neurons where we observed CYP20A1_Alu-LT to be downregulated during heat shock response and upregulated in HIV1-Tat treatment. 380 genes were positively correlated with its expression (significantly downregulated in heat shock and upregulated in Tat) and they harbored MREs for nine expressed miRNAs which were also enriched in CYP20A1_Alu-LT. MREs were significantly enriched in these 380 genes compared to random sets of differentially expressed genes (p = 8.134e-12). Gene ontology suggested involvement of these genes in neuronal development and hemostasis pathways thus proposing a novel component of Alu-miRNA mediated transcriptional modulation that could govern specific physiological outcomes in higher primates.

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Large-Scale Atmospheric Dispersal Simulations Identify Likely Airborne Incursion Routes of Wheat Stem Rust Into Ethiopia

Phytopathology ◽

10.1094/phyto-01-17-0035-fi ◽

2017 ◽

Vol 107 (10) ◽

pp. 1175-1186 ◽

Cited By ~ 9

Author(s):

M. Meyer ◽

L. Burgin ◽

M. C. Hort ◽

D. P. Hodson ◽

C. A. Gilligan

Keyword(s):

Stem Rust ◽

Large Scale ◽

Dispersion Model ◽

Fungal Spores ◽

Disease Outbreaks ◽

Particle Dispersion ◽

East African ◽

Wheat Stem Rust ◽

Sub Saharan ◽

African Rift

In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa’s largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different ‘what-if’ scenarios of disease outbreaks in potential source countries in different months of the wheat season.

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