ERC FUNDED PROJECTS

Recent advances in systems-level study of cells and organisms have revealed the enormous potential to live more sustainably through better use of biological processes. Plants sustainably synthesize the most abundant and diverse materials on Earth. By applying recent advances in life science technology, we can better harness renewable plant resources and bioconversion processes, to develop environmentally and politically sustainable human enterprise and lifestyles. At the same time, the global market for high-value biochemicals and bioplastics from forest and agricultural sources is rapidly increasing, which presents new opportunities for forest and agricultural sectors. The overall aim of BHIVE is to illuminate uncharted regions of genome and metagenome sequences to discover entirely new protein families that can be used to sustainably synthesize novel, high-value biomaterials from renewable plant resources. The approach will include three parallel research thrusts: 1) strategic analysis of transcriptome and metagenome sequences to identify proteins with entirely unknown function relevant to biomass (lignocellulose) transformation, 2) mapping of uncharted regions within phylogenetic trees of poorly characterized enzyme families with recognized potential to modify the chemistry and biophysical properties of plant polysaccharides, and 3) the design and development of novel enzyme screens to directly address the increasing limitations of existing assays to uncover entirely new protein functions. BHIVE will be unique in its undivided focus on characterizing lignocellulose-active proteins encoded by the 30-40% of un-annotated sequence, or genomic “dark matter”, typical of nearly all genome sequences. In this way, BHIVE tackles a key constraint to fully realizing the societal and environmental benefits of the genomics era.

1 977 781 €

Start date: 2015-09-01, End date: 2020-12-31

Spacetime defines existence and evolution of materials. A key path to human’s sustainability through materials innovation can hardly circumvent materials dimensionalities. Despite numerous studies in electrically distinct 2D semiconductors, the route to engage them in high-performance photocatalysts remains elusive. Herein, CATCH proposes a cross-dimensional activation strategy of 2D semiconductors to implement practical photocatalysis. It operates electronic structures of dimensionally paradoxical 2D semiconductors and spatially limited nD (n=0-2) guests, directs charge migration processes, mass-produces advanced catalysts and elucidates time-evolved catalysis. Synergic impacts crossing 2D-nD will lead to > 95%/hour rates for pollutant removal and >20% quantum efficiencies for H2 evolution under visible light. CATCH enumerates chemical coordination and writes reaction equations with sub-nanosecond precision. CATCH employs density functional theory optimization and data mining prediction to select most probable heterojunctional peers from hetero/homo- dimensions. Through facile but efficient wet and dry synthesis, nanostructures will be bonded to basal planes or brinks of 2D slabs. CATCH benefits in-house techniques for product characterizations and refinements and emphasizes on cutting-edge in situ studies to unveil photocatalysis at advanced photon sources. Assisted with theoretical modelling, ambient and time-evolved experiments will illustrate photocatalytic dynamics and kinetics in mixed spacetime. CATCH unites low-dimensional materials designs by counting physical and electronic merits from spacetime confinements. It metrologically elaborates photocatalysis in an elevated 2D+nD+t, alters passages of materials combinations crossing dimensions, and directs future photocatalyst designs. Standing on cross-dimensional materials innovation and photocatalysis study, CATCH breaks the deadlock of practical photocatalysis that eventually leads to sustainability.

1 999 946 €

Start date: 2021-05-01, End date: 2026-04-30

It has been recognized that growing cells within 3D structures reduces the gap between 2D in vitro cell cultures and native tissue physiology. This has been paving the way for the development of reliable 3D in vitro cell-based platforms with major impact in the reduction/elimination of animal experimentation, diseases modelling and drug development. So far, the many strategies that have been followed to bioengineer in vitro 3D human tissue models mostly rely on the random culture of cells within a 3D structure without reflecting the compositional and structural complexity of the native tissues. Recently proposed bioprinting technologies that allow accurate and high speed deposition of various cells and matrices at high resolution, have therefore great potential in the development of physiologically reliable 3D in vitro tissue models by recreating the different microenvironments/microfunctionalities found in each tissue. Nonetheless, among the components required for bioprinting, bioinks in particular have demanding requirements and much has still to be done regarding their intrinsic formulation to lead cell behaviour and support specific functionalities. ECM_INK intends to tackle this issue by developing cells-self extracellular matrices-based bioinks to create accurate and pathophysiological relevant 3D in vitro diseased skin tissue models. The development of cell phenotype-driven bioinks will generate complex microenvironments comprising varied cell types within matrices that were specifically designed to attain a particular response from each one of those cell types. The use of cells from patients suffering from chronic, genetic and neoplastic skin diseases represents a major advantage that will be reflected in the accuracy and functionality of the respective 3D in vitro models. The ultimate confirmation of their potential will be complete after validation using animal-free approaches reinforcing the intrinsic relationship of ECM_INK with the 3Rs policy.

1 998 939 €

Start date: 2017-05-01, End date: 2022-10-31

Accounting for vegetation structure – clumping of foliage into shoots or crowns – is the largest remaining challenge in modelling scattered and absorbed radiation in complex vegetation canopies such as forests. Clumping controls the radiation regime of forest canopies, yet it is poorly quantified. Currently, the communities working with vegetation structure and optical measurements do not have a common understanding of the concept. The FREEDLES project sets out to develop a universal method for quantifying clumping of foliage in forests based on detailed 3D structure and spectral reflectance data. Clumping will be linked to photon recollision probability, an exciting new development in the field of photon transport modelling. Photon recollision probability will, in turn, be used to develop a spectral scaling algorithm which will connect the spectra of vegetation at all hierarchical levels from needles and leaves to crowns, stands and landscapes. The spectral scaling algorithm will be validated with detailed reference measurements in both laboratory and natural conditions, and applied to interpret forest variables from satellite images at different spatial resolutions. The proposed approach is contrary to many other lines of current development where more complexity is favoured in canopy radiation models. If successful, the approach will significantly improve estimates of absorbed and scattered radiation fields in forests and retrieval results of forest biophysical variables from satellite data. Future applications can also be expected in global radiation and carbon balance estimation and in chlorophyll fluorescence models for forests. Most importantly, the spectral scaling model will open new horizons for our scientific understanding of photon-vegetation interactions.

1 963 590 €

Start date: 2018-05-01, End date: 2023-04-30