Biological pest control | EPFL Graph Search

Biological control or biocontrol is a method of controlling pests, whether pest animals such as insects and mites, weeds, or pathogens affecting animals or plants by using other organisms. It relies on predation, parasitism, herbivory, or other natural mechanisms, but typically also involves an active human management role. It can be an important component of integrated pest management (IPM) programs. There are three basic strategies for biological control: classical (importation), where a natural enemy of a pest is introduced in the hope of achieving control; inductive (augmentation), in which a large population of natural enemies are administered for quick pest control; and inoculative (conservation), in which measures are taken to maintain natural enemies through regular reestablishment. Natural enemies of insects play an important part in limiting the densities of potential pests. Biological control agents such as these include predators, parasitoids, pathogens, and competitor

The modern analogue of a Cretaceous coral with a calcitic skeleton

Anders Meibom, Jaroslaw Hubert Stolarski

It was argued that, in contrast to all known modern scleractinian corals that form aragonite skeletons, the original mineralogy of the Cretaceous "Coelosmilia" (ca. 70-65 Ma) was calcite during a period when the Mg2+/Ca2+ ratio of the seawater was presumably the lowest in Phanerozoic (Science 2007 318: 92-94). This is consistent with the idea that scleractinians extend only partial control over their skeletal mineralogy, because calcite is the preferred calcium carbonate polymorph (over aragonite) during abiotic CaCO3 precipitation in low Mg2+/Ca2+ seawater conditions. However, subsequently it was found that a number of different Cretaceous corals formed purely aragonite coralla in the same low Mg2+/Ca2+ conditions, suggesting instead that biological control over the skeletal mineralogy differs between taxonomically different corals (Geology 2017 45:319-322) and posing the question why was "Coelosmilia’s" skeletal mineralogy affected by the seawater chemistry changes and not that of the other corals. An unusual feature of "Coelosmilia" is the infilling of a significant portion of the calice with dense, banded skeletal deposits. They are crystallographically continuous with earlier formed layers of septa, wall and axial structures, but show distinct biogeochemical signatures. To date, no modern analogs of such corals were known, and it was tempting to argue that this skeletal infilling represents secondary, purely abiotic deposits (similar to marine cements, which would be calcitic in Cretaceous seas). Here we document a living scleractinian coral that exhibits a structural organization identical to Cretaceous "Coelosmilia", including dense calicular infilling that is a species-specific feature. Surprisingly, the inner parts of these skeletal elements are composed of fibrous calcite, whereas the rest of the skeleton is aragonitic. We suggest that this modern coral is phylogenetically related to "Coelosmilia" and capable of formation of strictly biologically controlled skeletal mineralogy, which can include both aragonitic and calcitic structures. This original bipartite skeletal organization may explain several diagenetic phenomena that we observe in "Coelosmilia", and is highly relevant for the proper geochemical sampling of corals with such skeletal organization.

2019

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

Andrea Baccarini, Irina Gorodetskaya, Christel Sybille Hassler, Sebastian Johannes Heinz-Josef Landwehr, Katherine Colby Leonard, Robin Lewis Modini, Fernando Perez Cruz, Julia Schmale, Jenny Thomas

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.

2021

Integration of microfluidics and multimodal optics for translational bioanalytics

Daniel Migliozzi

Numerous analytical techniques for life sciences have been at the basis of the improvement of medical diagnostics and treatments. Current challenges in bioanalytics are related to the conception of methods enabling large amount of information to be extracted from biological samples, in order to be translated into concrete solutions for the patient. From this point of view, microfluidics constitutes a key element to automate, accelerate and standardize bioanalytical tests. At the same time, obtaining precise information from the analyte of interest is crucial to specifically address diagnoses and therapies. Since the high flexibility of optical readouts can give access to a multitude of diverse aspects of biological matter in multiplexed fashion, in this thesis we have chosen to integrate microfluidics and multimodal optics to address specific problems in translational bioanalytics: drug screening and tumor diagnostics. In the first part of the work, we approached the problem of drug screening on living organisms, and especially the possibility to provide as much information as possible on potential mechanisms of action and clinical targets. For this, we aimed at developing a method to study the model organism Caenorhabditis elegans, i.e. a small soil worm that is widely used by researchers to study physiopathology at whole-organism scale. In fact, while offering the systemic information that is missing with cellular models, this small organism is much easier to handle and grow in large amounts compared to rodents, for which the costs and the ethical concerns are substantial. Moreover, its large genetic homology with humans supports translational analysis and its genetic manipulation is well mastered to model human diseases. Thus, we developed a microfluidic array to select small separated populations of C. elegans specimens, and combined fluorescence and bright-field imaging along with high-throughput feature recognition and signal detection to identify the mode-of-action of an antibiotic. Also, we demonstrated real-time, very large field-of-view capability on multiplexed motility assays for the assessment of the dose-response relation of an anesthetic. Furthermore, to enable on-site antibiotic testing, we explored a method to empower low-magnification optical systems with dielectric micro- and macro-spheres for the detection of pathogens in liquid media. Such dielectric objects offer potential solutions to increase the resolution and the sensitivity of imaging systems in a cost-effective fashion. We first characterized the parameters that govern the resolution increase in the case of microsphere-assisted incoherent microscopy and demonstrated it by imaging silicon microstructures and fluorescent bacteria. Then, we developed a method to easily fabricate microfluidic chips that integrate custom designs and precise location of highly-diffractive macro-spheres, and used it for on-chip detection of bacteria in a flow. In the second part of the work, we aimed at developing a technique to assess the status of individual tumor and immune cells in the conventional tissue sections used in the clinics. The first step was to combine fluorescence-based image segmentation with automated microfluidics to quantify, at the single-cell level, the overexpression of two proteins used as biomarkers for breast cancer diagnostics. We first assessed our method on biological controls such as breast cancer cell lines, and then combined it with ...

EPFL2019