The geological record provides hints at a link between the variations in the shape of the Earth's orbit and pulses of evolution or adaptation of marine calcifying phytoplankton (i.e., coccolithophores) during the last 2 Ma of Earth's history. These pulses are expressed as a reduction in diversity and increased proliferation of certain morphotypes belonging to the Noelaerhabdaceae family, recorded almost ubiquitously in sedimentary sequences ranging from low to high-mid latitudes of the global ocean. Such eccentricity-forced changes in the biological pump and the production and export of carbon by phytoplankton populations could be an important mediator between orbital forcing and the global carbon cycle, possibly modifying the geochemistry of the global ocean reservoir by accelerating deep dissolution processes. To test whether this dynamic occurs consistently in time and across all latitudes, observations at high latitudinal extremes, where the involvement of siliceous phytoplankton populations could be susceptible to the forcing, are critically required. Applying an innovative combination of micropaleontological, geochemical and image analysis techniques on nannofossil assemblages over selected intervals from the sediments retrieved during Expedition 403, with a sampling of sufficient resolution for orbital scale features, we aim to characterise the patterns of variability of phytoplankton populations (amount and diversity) and net production and export of carbon through time. This will provide critical notions to elucidate the co-evolution of phytoplankton dynamics and environment at the Fram Strait, its drivers and feedbacks on the regional production of carbon and a plausible connection with the global content.

Studies investigating the effects of nanoplastics (NPs) on aquatic organisms used concentrations between 2 to 7 order-of-magnitudes higher than those predicted in the open ocean in order to be able to track NPs. These studies divided the community between those sounding the alarm due to the observed ecotoxicological effects, and those predicting that NP concentrations in the environment are far below any threshold-effect. In reality most experiments were inadequately designed, and thus the results unsatisfying. Fit-to-purpose experimental designs have been hindered by a lack of appropriate NP models, tracking methods, and monitoring strategies for environmentally realistic concentrations. Using 14C-labelled NPs and conventional nuclear techniques, we have recently modelled that scallops, chronically exposed (over a year) to environmentally realistic NP concentrations (15 ug/L) might accumulate and reach NPs concentrations in body tissue where effects have been observed by those sounding the alarm. Astonishingly, this suggests that NPs might already be beyond threshold-effects in organisms and harming the marine biota. Here, we will deliver an innovative approach that will overcome the analytical limitations for detecting, mapping and quantifying NPs in realistic environmental settings. By combining 14C-labelling of NPs with the ultimate sensitivity of Accelerator Mass Spectrometry (AMS), METABOLISM will allow to investigate whether NPs in the oceans are already beyond "threshold-effect" concentrations in tissues. METABOLISM will: i) provide representative intrinsically radiolabelled NP models; ii) perform chronic NP exposures with a model organism (i.e. mussels) at environmentally realistic NP concentrations (ppt-levels); iii) develop the combustion AMS to generate toxicokinetic data; iv) explore the LA-AMS to produce spatially-resolve 14C measurement to quantify tissue distribution of NPs. The approach proposed here is essential and will produce unique, valuable and fundamental knowledge on the combined long-term accumulation of NPs in aquatic environments. This is critical for developing appropriate management strategies regarding plastic litter. If successful, METABOLISM will indeed support policy makers in improving environmental risk assessments of NPs and other contaminants of emerging concerns (CEC). It is envisioned that the approach proposed herein will enable a step-change in the research on CECs and will allow the study of many different aspects of their fates (e.g., transformation, fragmentation, biomineralization, biodistribution). METABOLISM chooses a highly innovative approach to address its research questions. It combines radiochemistry and unlock the power of the AMS to resolve important environmental questions. It will establish 14C-labelled NPs as a gold standard for performing realistic laboratory-based studies. It is fundamental research that will have a critical impact beyond its overall goal. The research proposed will, for instance, have a huge impact on the use of 14C as low-level tracer in biomedical studies (i.e. micro-dosing), where appropriate methods are often missing. The approach proposed is unique and will allow to perform ground-breaking science that goes beyond the state-of-the-art. METABOLISM builds an inter-disciplinary research team that integrates the relevant expertise in environmental analytical chemistry, radiochemistry and physics.

Cells respond to stress via rapid signalling through post-translational modifications (PTMs) of proteins. Protein phosphorylation is by far the most studied PTM, although other ones are being increasingly studied as well. Mass spectrometry (MS)-based proteomics techniques are becoming increasingly central in the life sciences and personalised medicine studies, and represent the most used experimental approach for studying PTMs. PTM-enriched proteomics datasets are complex to analyse. There is still a significant fraction of the generated mass spectra that cannot be assigned to a peptide sequence, and then remain unidentified. Regrettably then, generated data in these studies cannot be used yet to its full potential. Therefore, there is the need to develop novel analysis approaches for proteomics datasets. Beyond data analysis, a common challenge is to extract biologically and functionally relevant information from the proteomics results, including e.g. a list of detected PTMs (e.g. phosphosites). However, currently it is hard to prioritise the detected PTMs for downstream analysis, which can involve expensive follow-on studies. Artificial Intelligence (AI) approaches including Machine Learning (ML) and Deep Learning (DL) are revolutionising proteomics, enabling improvements in many steps of the proteomics analysis workflow. These developments in AI approaches for proteomics have largely been enabled by the wide availability of datasets in the public domain. The PRIDE database (European Bioinformatics Institute, EMBL-EBI, UK) is the world-leading proteomics data repository, accounting for >80% of stored datasets worldwide. UniProt (EMBL-EBI) is the most used protein knowledge-base and it is increasingly incorporating PTM data, including information about their functional relevance. In this proposal called PTM-AI we will use AI to further leverage the huge amount of public proteomics datasets to improve the detection and functional characterization of PTMs. PTM-AI includes the teams in charge of the world-leading resources PRIDE and UniProt, and two International groups active in AI approaches for proteomics: the Beltrao (Switzerland) and Renard/Schlaffner groups (Germany).

Some of the most spectacular data in the recent history of earth science have been derived from the drilling of the polar ice caps. Foremost amongst these is the revelation that the atmospheric CO2 content was about one-third lower (roughly 80ppmV) during the Last Glacial Maximum than during the warmer period of the past 10 thousand years. Thus, it is widely believed that changes in atmospheric CO2 strongly amplified glacial-interglacial climate change. Although a clear explanation has yet to emerge for the observed CO2 decline during glacials and rise during interglacials, mass balance arguments clearly point to the ocean exchange as the primary modulator of the CO2 changes on these time scales. Recent studies have pointed to the Southern Ocean due to the tight coupling between carbon dioxide levels and climate in the southern hemisphere high latitudes. One prevailing model involving the SO envisions that at the end of the last glacial cycle (deglacial) climate reorganisation, the reduction in sea ice cover and strengthening wind fields may have stirred up deep ocean waters rich in carbon and nutrients to the surface releasing CO2 that has been stored in the deep ocean during the glacial period. However, this model presents a paradox. In the modern SO, the physical release of CO2 is roughly compensated by the uptake of carbon by algae during photosynthesis at the sea surface utilising the nutrients that accompany CO2 in the resurfacing deep waters. Therefore for the CO2 release model to work conditions in SO should have been unfavourable for the biological uptake allowing globally significant CO2 efflux to occur. In the proposal we hypothesize that one potential factor that could have constrained biological CO2 uptake in the SO is the dearth of Fe during algal growth. The substantial decline in dust inputs (important source of Fe) during the deglacial recorded in Anatrctic ice cores lends support to this idea. Therefore, we propose to investigate the role of productivity on CO2 efflux from the SO during the last deglaciation by investigating the nature and magnitude of marine productivity, relative macronutrient utilisation (nitrate and silicic acid), micronutrient (Fe & Zn) bio-availability and in a carefully selected set of marine sediment cores covering this period. We propose to apply state-of-art geochemical and isotopic tools recently developed including silicon and nitrogen isotopes as proxies for macronutrient utilisation and diatom-bound trace metals as tracers of Fe and Zn biological availability in combination with more conventional proxies of productivity and dust inputs. By doing so, we propose to address a fundamental and lingering question in Earth System Science- that is "What are the controls on glacial-interglacial CO2 change?"

With age, we gradually accumulate both environmentally and intrinsically generated defects at different levels in our bodies: from errors in DNA (mutations), proteins (aggregates), organelles (mitochondrial dysfunction) to cells (cancer) and organs (heart failure). Ageing is the largest risk factor for the majority of human diseases in the Western world, including progressive diseases such as Alzheimer's and Parkinson's, diseases like cancer that show variable rates of onset, and catastrophic systems failures such as heart-attack and stroke. While the study of specific ageing-related disease processes has long been a major focus of biomedical and biological research, there is a growing realisation of the importance of analyzing the normal ageing process itself as an essential part of the problem, and of exploring ways to slow or reverse its effects. Ageing is a multi-factorial problem that can be seen as an inevitable feature of the ravages of time and the harmful environments in which organisms live. Recent discoveries, however, demonstrate that ageing can be modified in dramatic ways by relatively simple interventions. For example, single gene mutations and dietary restriction can delay ageing and provide a universal improvement in health late in the life of laboratory animals. Moreover, the pathways involved in ageing are conserved in evolution, and genetic variants in their components are associated with differences in lifespan in humans. A central challenge of ageing research, however, remains to tease out a comprehensive and unified picture of the genetic factors and mechanisms determining longevity. We plan to utilize fission yeast as a model organism to advance our understanding of complex processes with fundamental importance for ageing. Remarkably, many of these processes are now known to be similar from yeast to human. Yeast cells enter a quiescent, non-dividing state under limiting nutrients, and the lifespan in this state depends on both genetic and environmental factors. Such quiescent yeast cells provide a valuable system to analyze basic processes affecting ageing and longevity. We will analyze how the global regulation of genes and proteins is modified during ageing, and how any changes might affect longevity. We will also exploit a collection of all viable gene knock-out mutants to systematically identify those genes that lead to longer or shorter lifespan. We will further examine how lifespan varies among wild yeast strains from different geographical locations, and whether this variation goes with changes in gene expression. Finally, we will integrate these complementary global data sets and follow-up the most promising findings to uncover particular roles of specific genetic factors in cellular ageing and longevity. Importantly, this research will provide a valuable platform to understand the genetic factors involved in ageing in humans, to eventually develop interventions that slow ageing and thus prevent or delay the numerous age-associated diseases.