Tilbake til det grunnleggende : forenkling av mikrobielle samfunn for å tolke komplekse interaksjoner

Microbes are everywhere and contribute to many essential processes relevant for planet Earth, ranging from biogeochemical cycles to complex human behavior. The means to achieve these colossal tasks for such small and, at first glance, simple organisms rely on their ability to assemble in heterogeneous communities in which populations with different taxonomies and functions coexist and complement each other. Some microbes are of particular interest for human civilization and have long been used for everyday tasks, such as the production of bread and wine. More recently, large-scale industrial and civil projects have taken advantage of the transformative capabilities of microbial communities, with key examples being biogas reactors, mining and wastewater treatment. Decades of classical microbiology, based on pure culture isolates and their physiological characterization, have built the foundations of modern microbial ecology. Molecular analysis of microbes and microbial communities has generated an understanding that for many microbial populations cultivation is hard to achieve and that breaking a community apart impacts its function. These limitations have driven the development of technical tools that bring us directly in contact with communities in their natural environment. In the mid 2000’s the recently established “omics” techniques were quickly adapted to their “meta-omics” version, enabling direct analysis of the microbial samples without culture. Every class of molecules (DNA, RNA, protein, metabolite, etc.) can now theoretically be analyzed from the entire community within a given sample. Metagenomics uses community DNA to build the phylogenetic picture and the genetic potential, whereas metatranscriptomics and metaproteomics employ RNA and proteins respectively to inquire the gene expression of the community. Finally, meta-metabolomics can close the loop and describe the metabolic activity of the microbes. Here, we combined the four aforementioned major meta-omics disciplines in a gene- and population-centric perspective to re-iterate the same Aristotelian question underlying microbial ecology: how is it possible that the whole is more than the sum of its parts? Along the detailed answers provided by the individual communities in various environments, we also tried to learn something about biology itself. We first addressed in a saccharolytic and methane-producing minimalistic consortium (SEM1b), the strain-specific interplay engaged in (hemi)cellulose degradation, explaining the ubiquity of Coprothermobacter proteolyticus in biogas reactors. We showed through the genetic potential of the C. proteolyticus-affiliated COPR1 population, the putative acquisition via horizontal gene transfer of a gene cassette for hemicellulose degradation. Moreover, we showed how the gene expression of these COPR1 genes were both coherent with the release of hemicellulose by another population of the community (RCLO1) and synced with the gene expression of the orthologous genes of an already known hemicellulolytic population (CLOS1). Conclusively, we demonstrated how the same purified COPR1 protein (Glycosyl Hydrolases 16) showed endoglucanase activity on several hemicellulose substrates. Secondly, we explored the combined application of absolute omics-based quantification of RNA and proteins using SEM1b as a benchmark community, due to its lower complexity (less than 12 populations) and relatively resolved biology. We subsequently demonstrated that the uncultured bacterial populations in SEM1b followed the expected protein-to-RNA ratio (102-104) of previously analyzed cultured bacteria in exponential phase. In contrast, an archaeon population from SEM1b showed values in the range 103-105, the same as what has been reported for eukaryotes (yeast and human) in the literature. In addition, we modeled the linearity (k) between genome-centric transcriptomes and proteomes over time and used it to predict the essential metabolic populations of the SEM1b community through converging and parallel k-trends, which was subsequently confirmed via classical pathway analysis. Finally, we estimated the translation and the protein degradation rates, coming to the conclusion that some of the processes in the cell that require a rapid tuning (e.g. metabolism and motility) are regulated (also) post-transcriptionally. Thirdly we sought to apply our approach of collapsing complex datasets into simplistic metrics in order to identify underlying community trends, onto a more complex and “real-world” microbiome. To do this, we resolved more than one year of weekly sampling from a lipid-accumulating community (Shif-LAO) that inhabits a wastewater treatment in Shifflange (Luxembourg), and showed an extreme genetic redundancy and turnover in contrast to a more conservative trend in functions. Moreover, we demonstrated how the time patterns (e.g. seasonality) in both gene count and gene expression are linked with the physico-chemical parameters associated with the corresponding samples. Furthermore, we built the static reaction network underlying the whole community over the complete dataset (51 temporal samples). From this, we characterized the sub-network for lipid accumulation, and showed that its more expressed nodes were defined by resource competition between different taxa (deduced via inverse taxonomic richness and gene expression over time). In contrast, the nitrogen metabolism sub-network instead exhibited a dominant taxon and a keystone ammonia oxidizing monooxygenase, the first enzyme of ammonia oxidation, which may lead to the production of nitrous gas (a powerful greenhouse gas). Overall, our results presented in this thesis build a comprehensive repertoire of interactions in microbial communities ranging from a simplistic (10’s of populations) consortium to a natural complex microbiome (100’s of populations). These were ultimately uncovered using an array of techniques, including unsupervised gene expression clustering, pathway analysis, reaction networks, co-expression networks, eigengenes and linearity trends between transcriptome and proteome. Moreover, we learnt that to achieve a full understanding of microbial ecology and detailed interactions, we need to integrate all the meta-omics layers quantified with absolute measurements. However, when scaling these approaches to real-world communities the massive amounts of generated data brings new challenges and necessitates simplifying strategies to reduce complexity and extrapolate ecological trends.Mikroorganismer er overalt og de bidrar til mange essensielle prosesser som er viktige for planeten vår, alt fra biokjemiske sykluser til kompleks menneskelig oppførsel. Midlene disse små, og ved første øyekast enkle organismene bruker for å oppnå så betydelige oppgaver på, ligger i deres evne til å forenes i et heterogent samfunn der ulike populasjoner med en forskjellig taksonomi og funksjoner sameksisterer og utfyller hverandre. Noen mikrobielle samfunn er av særlig interesse for oss mennesker, og har i lang tid blitt utnyttet i hverdagslige gjøremål, slik som produksjon av brød og vin. I senere tid har også stor-skala industri og kommunale anlegg, for eksempel biogass reaktorer og renseanlegg, dratt nytte av mikrobesamfunns evne til å transformere. Tiår med klassisk mikrobiologi, basert på dyrking og fysiologisk karakterisering av renkulturer har bygget grunnlaget for moderne mikrobiell økologi. Molekylære analyser av mikrober og mikrobielle samfunn har resultert i forståelsen om at mange mikrobielle populasjoner er vanskelige å kultivere, og at en oppdeling av samfunnet vil påvirke dens funksjoner. Disse begrensningene har vært en drivkraft for utviklingen av tekniske verktøy som kan bringe oss i direkte kontakt med mikrobesamfunnet i deres naturlige miljø. I midten av 2000-talles ble de nylig etablerte «omikk»-teknikkene raskt adoptert til også å gjelde «meta-omikk», som muliggjør direkte analysering av mikrobielle samfunn uten kultivering. I dag kan i teorien hver molekylerære klasse (DNA, RNA, proteiner, metabolitter, osv.) bli analysert fra hele mikrobesamfunn i en bestemt prøve. I metagenomikk benyttes DNA-innholdet til å konstruere et fylogenetisk bilde av samfunnet og det genetiske potensiale, mens metatranskriptomikk og metaproteomikk bruker henholdsvis RNA og proteiner for å se på gen-uttrykket i samfunnet. Meta-metabolomikk kan slutte sirkelen ved å beskrive den metabolske aktiviteten til mikrobene. I arbeidet som ligger til grunn for denne avhandlingen, kombinerte vi fire av de nevnte fagfeltene innen meta-omikk i et gen- og populasjons-orientert perspektiv for å gjenta det samme Aristoteliske spørsmålet bak mikrobiell økologi: hvordan er det mulig at helheten er større enn summen av enkeltdelene? Sammen med de detaljerte svarene som ble gitt av de enkelte mikrobesamfunnene i ulike miljøer, forsøkte vi også å lære noe om biologi i seg selv. Først adresserte vi det stamme-spesifikke samspillet involvert i (hemi)cellulose degradering i et sakkarolytisk og metan-produserende minimalistisk konsortium (SEM1b), som belyser omfanget av Coprothermobacter proteolyticus i biogass reaktorer. Gjennom det genetiske potensiale til COPR1-populasjonen tilknyttet C. proteolyticus, viste vi den antatte ervervelsen, via horisontal gen-overføring, av en gen-kassett for nedbrytning av hemicellulose. Videre viste vi hvordan genuttrykket til disse COPR1-genene var i samsvar med frigivelsen av hemicellulose av en annen populasjon i samfunnet (RCLO1), og synkronisert med genuttrykket av de ortologe genene fra en allerede kjent hemicellulolytisk populasjon (CLOS1). Avslutningsvis demonstrerte vi hvordan det samme rensede COPR1-proteinet (glykosid-hydrolase 16) viste endoglukanase-aktivitet på flere hemicellulosesubstrater. På grunn av lavere kompleksitet (færre enn 12 populasjoner) og en relativt kjent biologi, benytte vi SEM1b videre som et referansesamfunn for å utforske den kombinerte anvendelsen av absolutt omikk-basert kvantifisering av RNA og proteiner. Vi demonstrerte deretter at de ukultiverte bakterie-populasjonene i SEM1b fulgte en protein-til-RNA ratio (102-104) som var forventet basert på tidligere analyser av bakteriekulturer i eksponentiell fase. I kontrast til dette viste en arkeonpopulasjon fra SEM1b verdier i området mellom 103-105, som er det samme som tidligere rapportert i litteraturen for eukaryote (gjær og menneske). I tillegg modellerte vi lineariteten (k) mellom genom-orienterte transkriptomer og proteomer over tid, og brukte dette til å forutsi de essensielle metabolsk populasjon i SEM1b-samfunnet gjennom konvergerende og parallelle k-trender, som senere ble bekreftet via klassiske analyser av metabolske synteseveier. Til slutt estimerte vi frekvensen av translasjon og protein degradering, hvorpå vi konkluderte med at noen av prosessene i en celle som krever rask innstilling (som for eksempel metabolisme og bevegelse) er regulert (også) post- transkripsjonelt. Til slutt ønsket vi å anvende vår tilnærming for å sette komplekse datasett inn i forenklede matriser for å identifisere underliggende trender i mikrosamfunnet, på et mer komplekst og virkelighetsnært mikrobiom. Til dette benyttet vi et mer enn ett år med ukentlige prøvetakninger fra en lipid-akkumulerende mikrobesamfunn (Shif-LAO) i et renseanlegg i Shifflange (Luxembourg), og avdekket en ekstrem genetisk redundans og turnover, i motsetning til en mer konservativ trend i funksjoner. Videre demonstrerte vi hvordan tidsavhengige mønstre (som for eksempel sesongvariasjoner) i både antall gener og genuttrykk er knyttet til fysisk-kjemiske parameter assosiert med de tilsvarende prøvene. I tillegg rekonstruerte vi det underliggende statiske reaksjonsnettverket til mikrobesamfunnet over hele datasettet (51 prøver over tid). Basert på dette, karakteriserte vi sub-nettverk for lipid-akkumulering, og demonstrerte at mer uttrykte noder var definert av konkurransen om ressurser mellom ulike taksonomiske grupper (antatt via reversert taksonomisk diversitet og genuttrykk over tid). I motsetning til dette, viste nettverket for nitrogen-metabolismen i stedet et dominerende taxon og en keystone ammoniakk-oksiderende monooxygenase, det første enzymet i ammoniakk oksidasjon, som fører til produksjonen av lystgass (en svært sterk klimagass). Resultatene presentert i denne doktorgradsavhandlingen bygger på et omfattende repertoar av interaksjoner i mikrobielle samfunn som spenner fra et forenklet konsortium (titalls populasjoner) til et naturlig komplekst mikrobiom (hundretalls populasjoner). Disse mikrobiomene ble til slutt kartlagt ved hjelp av en rekke teknikker, blant annet unsupervised gruppering av genutrykk, analyser av metabolisk synteseveier, nettverk av reaksjoner og co-uttrykte gener, eigengener og lineære trender mellom transkriptom og proteom. I tillegg erfarte vi at for å oppnå en full forståelse av mikrobiell økologi og detaljerte interaksjoner må vi integrere alle lagene av meta-omikk, kvantifisert med absolutte målinger. Når man oppskalering disse tilnærmingen til virkelige mikrobesamfunn, bringer imidlertid enorme mengder generert data til nye utfordringer som nødvendiggjør en forenkling av strategier for å redusere kompleksiteten og ekstrapolerer økologiske trender

Numerical simulations of atomic-scale disordering processes at impact between two rough crystalline surfaces

Numerical calculations have been used to throw light on the mechanical deformation and the atomic mixing processes taking place when two different metallic systems collide at low temperature. To this end, two semicrystals terminating with a free surface were pushed each against the other at a given relative velocity. Surfaces of different roughness were considered under different impact conditions. Simple mechanical loads on plane surfaces did not induce any significant mixing of atomic species at the interface, observed instead in collisions involving either rough surfaces or plane surfaces undergoing a relative sliding. In the case of rough surfaces, the local contact between the semicrystals is initially sustained by surface asperities. The atoms there located experience thus sudden mechanical loads and an unusual localization of kinetic energy, which enhance their mobility and favor the mixing process. A diffuse interfacial region with a disordered structure correspondingly appears. Its structural features were not significantly modified by the thermal relaxation processes occurring after the compressive load removal

Lightweight Design Solutions in the Automotive Field: Environmental Modelling Based on Fuel Reduction Value Applied to Diesel Turbocharged Vehicles

A tailored model for the assessment of environmental benefits achievable by “light-weighting” in the automotive field is presented. The model is based on the Fuel Reduction Value (FRV) coefficient, which expresses the Fuel Consumption (FC) saving involved by a 100 kg mass reduction. The work is composed of two main sections: simulation and environmental modelling. Simulation modelling performs an in-depth calculation of weight-induced FC whose outcome is the FRV evaluated for a wide range of Diesel Turbocharged (DT) vehicle case studies. Environmental modelling converts fuel saving to impact reduction basing on the FRVs obtained by simulations. Results show that for the considered case studies, FRV is within the range 0.115–0.143 and 0.142–0.388 L/100 km × 100 kg, respectively, for mass reduction only and powertrain adaptation (secondary effects). The implementation of FRVs within the environmental modelling represents the added value of the research and makes the model a valuable tool for application to real case studies of automotive lightweight LCA

Life Cycle Assessment in the automotive sector: a comparative case study of Internal Combustion Engine (ICE) and electric car

Abstract Transportation represents one of the major contributors to several environmental burdens such as Green-House-Gas (GHG) emissions and resource depletion. Considering the European Union, light duty vehicles are responsible for roughly 10% of total energy use and air emissions. As a consequence, the need for higher fuel/energy efficiency in both conventional and electric cars has become urgent and the efforts across industrial and research players have proposed a range of innovative solutions with great potential. This study presents a comparative Life Cycle Assessment of Internal Combustion Engine (ICE) and electric vehicles. The analysis follows a "from cradle-to-grave" approach and it captures the whole Life-Cycle (LC) of the car subdivided into production, use and End-of-Life stages. The inventory is mainly based on primary data and the assessment takes into account a wide range of impact categories to both human and eco-system health. The eco-profile of the different vehicle configurations is assessed and the main environmental hotspots affecting conventional and electric cars are identified and critically discussed. The dependence of impacts on LC mileage is investigated for both propulsion technologies and the break-even point for the effective environmental convenience of electric car is determined considering several use phase electricity sources. The analysis is completed with a comparison of GHG emissions with the results of previous LCA studies

Non-monotonic variation of the grain size in Cu nanopowders subjected to ball milling

Ball milling (BM) a Cu nanopowder resulted in an increase of the average grain size from 8 to 52 nm, followed by a gradual decrease to 19 nm. In contrast, the grain size of coarse-grained Cu decreased monotonically from 290 nm to 19 nm. Fitting a model to the kinetic curves indicates that the two processes have similar activated volumes during collisions. It also reveals that particles over 100 nm are formed when nanoparticles are compressed during a collision for the first time.University of Cagliari and performed within the European Community Horizon 2020 Programme, COST Action CA15102 Solutions for Critical Raw Materials under Extreme Conditions (CRM_EXTREME

design of a device for stress corrosion testing in pressurized chambers

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Modeling of point defects annihilation in multilayered cu/nb composites under irradiation

This work focuses on a mathematical modeling of the response to irradiation of a multilayer composite material. Nonstationary balance equations are utilized to account for production, recombination, transport, and annihilation, or removal, of vacancies and interstitials at interfaces. Although the model developed has general validity, Cu/Nb multilayers are used as case study. Layer thickness, temperature, radiation intensity, and surface recombination coefficients were varied systematically to investigate their effect on point defect annihilation processes at interfaces. It is shown that point defect annihilation at interfaces mostly depends on point defect diffusion. The ability of interfaces to remove point defects can be described by a simple map constructed using only two dimensionless parameters, which provides a general tool to estimate the efficiency of vacancy and interstitial removal in multilayer composite materials

A Classical molecular dynamics study of recombination reactions in a microporous solid

Classical molecular dynamics calculations have been applied to the study of the recombination reaction of photodissociated radical species. Within a simplified reaction scheme it has been possible to get qualitative information about the influence of the environment. A comparison has been made between reactions in a liquid solvent and in a complex structured environment, such as a microporous silicate. Marked differences in the recombination yield and in the energy relaxation mechanism have been observed