Project acronym DEEP PURPLE
Project DEEP PURPLE: darkening of the Greenland Ice Sheet
Researcher (PI) Martyn TRANTER, Alexandre Barbosa Anesio, Liane Benning
Host Institution (HI) AARHUS UNIVERSITET
Country Denmark
Call Details Synergy Grants (SyG), SyG, ERC-2019-SyG
Summary The stability of the Greenland Ice Sheet (GrIS) is a threat to coastal communities worldwide. The PIs have changed our understanding of why it darkens during the melt season, becoming increasingly deep purple due to pigmented ice algal blooms in the ice surface, producing more melt and accelerating the GrIS towards its tipping point, and increasing sea level. The next step jump in our understanding of biological darkening will be provided by DEEP PURPLE, which will establish the factors that control ice algal blooms. These factors are essential for modelling of future melting, which require a process-based understanding of blooming. DEEP PURPLE will quantify the synergies between the biology, chemistry and physics of ice algae micro-niches in rotting, melting ice, and examine the combination of factors which stabilise them. State-of-the-science analytical and observational methods will be employed to characterise the complex mosaic of wet ice habitats, dependent on factors such as the hydrology, nutrient status, particulate content and light fields within these continually evolving ice-water-particulate-microbe systems. We will quantitatively assess why and how the fine light mineral dust particulates contained within the melting ice amplify the growth of ice algae. The particulate content and composition of different layers in the GrIS is dependent on age, and so the algae that the melting ice can support may fundamentally change over time. We look back to understand if the ice biome has changed through the Anthropocene via analyse of fjord sediments. The first draft genome of ice algae will show their key adaptations to glacier surface habitats. DEEP PURPLE looks forward by providing the critical field data sets and conceptual models of ice algal growth that will facilitate the next generation of predictive models of sea level rise due to biologically enhanced melting of the GrIS.
Summary
The stability of the Greenland Ice Sheet (GrIS) is a threat to coastal communities worldwide. The PIs have changed our understanding of why it darkens during the melt season, becoming increasingly deep purple due to pigmented ice algal blooms in the ice surface, producing more melt and accelerating the GrIS towards its tipping point, and increasing sea level. The next step jump in our understanding of biological darkening will be provided by DEEP PURPLE, which will establish the factors that control ice algal blooms. These factors are essential for modelling of future melting, which require a process-based understanding of blooming. DEEP PURPLE will quantify the synergies between the biology, chemistry and physics of ice algae micro-niches in rotting, melting ice, and examine the combination of factors which stabilise them. State-of-the-science analytical and observational methods will be employed to characterise the complex mosaic of wet ice habitats, dependent on factors such as the hydrology, nutrient status, particulate content and light fields within these continually evolving ice-water-particulate-microbe systems. We will quantitatively assess why and how the fine light mineral dust particulates contained within the melting ice amplify the growth of ice algae. The particulate content and composition of different layers in the GrIS is dependent on age, and so the algae that the melting ice can support may fundamentally change over time. We look back to understand if the ice biome has changed through the Anthropocene via analyse of fjord sediments. The first draft genome of ice algae will show their key adaptations to glacier surface habitats. DEEP PURPLE looks forward by providing the critical field data sets and conceptual models of ice algal growth that will facilitate the next generation of predictive models of sea level rise due to biologically enhanced melting of the GrIS.
Max ERC Funding
11 007 344 €
Duration
Start date: 2020-01-01, End date: 2025-12-31
Project acronym KILL-OR-DIFFERENTIAT
Project Using cell-cell interactions to unlock new cancer treatments: Forcing neural crest tumors back onto the developmental path
Researcher (PI) Igor ADAMEYKO, Olivier Delattre, Peter Kharchenko, Susanne Schlisio
Host Institution (HI) MEDIZINISCHE UNIVERSITAET WIEN
Country Austria
Call Details Synergy Grants (SyG), SyG, ERC-2019-SyG
Summary The interactions between tumor and its microenvironment are often critical to uncovering the mechanisms of tumor survival. A striking example is the recent success of immunotherapy approaches that expose tumor cells to immune attack by disrupting a specific interaction between the tumor and infiltrating lymphocytes. The tumor can also repress immune response by inducing complex interactions among dozens of immune and stromal cell types that typically make up tumor microenvironment, however those remain largely uncharacterized as we currently lack systematic approaches to uncover relevant cell-cell interactions. The alternative to killing tumor cells, either directly or through immune system, is to force them to differentiate. Such strategy is particularly promising for tumors arising due to failure of progenitor populations to follow proper differentiation cascade. Here as well, the progress has been limited by lack of understanding of specific intercellular signals that that are disrupted in tumorigenesis.
We propose a systematic approach for characterizing cell-cell interactions in complex microenvironments through joint analysis of spatially-resolved and disassociated single-cell transcriptomics. We will apply it to identify inter-cellular signals and pathways that can push tumors of neural crest origin, including as pheochromocytoma (PCC), paraganglioma (PGL) and neuroblastoma (NB), towards terminal differentiation. Building on our expertise with neural crest development, we will use single-cell profiling to map individual tumor cells onto developmental trajectory of neural crest differentiation. Spatial transcriptomics analysis will then be used to identify the sources and nature of microenvironment signals that channel neural crest differentiation during normal development. Contrasting interactions in normal and tumor tissues we will then aim to identify factors, pathways or signals that would push that PCC, PGL and NB tumors towards benign state.
Summary
The interactions between tumor and its microenvironment are often critical to uncovering the mechanisms of tumor survival. A striking example is the recent success of immunotherapy approaches that expose tumor cells to immune attack by disrupting a specific interaction between the tumor and infiltrating lymphocytes. The tumor can also repress immune response by inducing complex interactions among dozens of immune and stromal cell types that typically make up tumor microenvironment, however those remain largely uncharacterized as we currently lack systematic approaches to uncover relevant cell-cell interactions. The alternative to killing tumor cells, either directly or through immune system, is to force them to differentiate. Such strategy is particularly promising for tumors arising due to failure of progenitor populations to follow proper differentiation cascade. Here as well, the progress has been limited by lack of understanding of specific intercellular signals that that are disrupted in tumorigenesis.
We propose a systematic approach for characterizing cell-cell interactions in complex microenvironments through joint analysis of spatially-resolved and disassociated single-cell transcriptomics. We will apply it to identify inter-cellular signals and pathways that can push tumors of neural crest origin, including as pheochromocytoma (PCC), paraganglioma (PGL) and neuroblastoma (NB), towards terminal differentiation. Building on our expertise with neural crest development, we will use single-cell profiling to map individual tumor cells onto developmental trajectory of neural crest differentiation. Spatial transcriptomics analysis will then be used to identify the sources and nature of microenvironment signals that channel neural crest differentiation during normal development. Contrasting interactions in normal and tumor tissues we will then aim to identify factors, pathways or signals that would push that PCC, PGL and NB tumors towards benign state.
Max ERC Funding
9 377 151 €
Duration
Start date: 2020-10-01, End date: 2026-09-30
