Protein-Interaction-Networks: More than mere modules

Cellular function is widely believed to be organized in a modular fashion. On all scales and at all levels of complexity, relatively independent sub-units perform relatively independent sub-tasks of biological function. This functional modularity must be reflected in the topology of molecular networks. But how a functional module should be represented in an interaction network is an open question. In protein-interaction networks (PIN), one can identify a protein-complex as a module on a small scale, i.e. modules are understood as densely linked, resp. interacting, groups of proteins, that are only sparsely interacting with the rest of the network. In this contribution, we show that extrapolating this concept of cohesively linked clusters of proteins as modules to the scale of the entire PIN inevitable misses important and functionally relevant structure inherent in the network. As an alternative, we introduce a novel way of decomposing a network into functional roles and show that this represents network structure and function more efficiently. This finding should have a profound impact on all module assisted methods of protein function prediction and should shed new light on how functional modules can be represented in molecular interaction networks in general

SMART 5: domains in the context of genomes and networks

The Simple Modular Architecture Research Tool (SMART) is an online resource () used for protein domain identification and the analysis of protein domain architectures. Many new features were implemented to make SMART more accessible to scientists from different fields. The new ‘Genomic’ mode in SMART makes it easy to analyze domain architectures in completely sequenced genomes. Domain annotation has been updated with a detailed taxonomic breakdown and a prediction of the catalytic activity for 50 SMART domains is now available, based on the presence of essential amino acids. Furthermore, intrinsically disordered protein regions can be identified and displayed. The network context is now displayed in the results page for more than 350 000 proteins, enabling easy analyses of domain interactions

Preventing Phosphorylation of Sterol Regulatory Element-Binding Protein 1a by MAP-Kinases Protects Mice from Fatty Liver and Visceral Obesity

The transcription factor sterol regulatory element binding protein (SREBP)-1a plays a pivotal role in lipid metabolism. Using the SREBP-1a expressing human hepatoma cell line HepG2 we have shown previously that human SREBP-1a is phosphorylated at serine 117 by ERK-mitogen-activated protein kinases (MAPK). Using a combination of cell biology and protein chemistry approach we show that SREBP-1a is also target of other MAPK-families, i.e. c-JUN N-terminal protein kinases (JNK) or p38 stress activated MAP kinases. Serine 117 is also the major phosphorylation site in SREBP-1a for JNK. In contrast to that the major phosphorylation sites of p38 MAPK family are serine 63 and threonine 426. Functional analyses reveal that phosphorylation of SREBP-1a does not alter protein/DNA interaction. The identified phosphorylation sites are specific for both kinase families also in cellular context. To provide direct evidence that phosphorylation of SREBP-1a is a regulatory principle of biological and clinical relevance, we generated transgenic mice expressing mature transcriptionally active N-terminal domain of human SREBP–1a variant lacking all identified phosphorylaton sites designed as alb-SREBP-1aΔP and wild type SREBP-1a designed as alb-SREBP-1a liver specific under control of the albumin promoter and a liver specific enhancer. In contrast to alb-SREBP–1a mice the phosphorylation–deficient mice develop no enlarged fatty livers under normocaloric conditions. Phenotypical examination reveales a massive accumulation of adipose tissue in alb-SREBP-1a but not in the phosphorylation deficient alb-SREBP-1aΔP mice. Moreover, preventing phosphorylation of SREBP-1a protects mice also from dyslipidemia. In conclusion, phosphorylation of SREBP-1a by ERK, JNK and p38 MAPK-families resembles a biological principle and plays a significant role, in vivo

Liver-Specific Expression of Transcriptionally Active SREBP-1c Is Associated with Fatty Liver and Increased Visceral Fat Mass

The pathogenesis of fatty liver is not understood in detail, but lipid overflow as well as de novo lipogenesis (DNL) seem to be the key points of hepatocyte accumulation of lipids. One key transcription factor in DNL is sterol regulatory element-binding protein (SREBP)-1c. We generated mice with liver-specific over-expression of mature human SREBP-1c under control of the albumin promoter and a liver-specific enhancer (alb-SREBP-1c) to analyze systemic perturbations caused by this distinct alteration. SREBP-1c targets specific genes and causes key enzymes in DNL and lipid metabolism to be up-regulated. The alb-SREBP-1c mice developed hepatic lipid accumulation featuring a fatty liver by the age of 24 weeks under normocaloric nutrition. On a molecular level, clinical parameters and lipid-profiles varied according to the fatty liver phenotype. The desaturation index was increased compared to wild type mice. In liver, fatty acids (FA) were increased by 50% (p<0.01) and lipid composition was shifted to mono unsaturated FA, whereas lipid profile in adipose tissue or serum was not altered. Serum analyses revealed a ∼2-fold (p<0.01) increase in triglycerides and free fatty acids, and a ∼3-fold (p<0.01) increase in insulin levels, indicating insulin resistance; however, no significant cytokine profile alterations have been determined. Interestingly and unexpectedly, mice also developed adipositas with considerably increased visceral adipose tissue, although calorie intake was not different compared to control mice. In conclusion, the alb-SREBP-1c mouse model allowed the elucidation of the systemic impact of SREBP-1c as a central regulator of lipid metabolism in vivo and also demonstrated that the liver is a more active player in metabolic diseases such as visceral obesity and insulin resistance

Explorative data analysis of MCL reveals gene expression networks implicated in survival and prognosis supported by explorative CGH analysis

<p>Abstract</p> <p>Background</p> <p>Mantle cell lymphoma (MCL) is an incurable B cell lymphoma and accounts for 6% of all non-Hodgkin's lymphomas. On the genetic level, MCL is characterized by the hallmark translocation t(11;14) that is present in most cases with few exceptions. Both gene expression and comparative genomic hybridization (CGH) data vary considerably between patients with implications for their prognosis.</p> <p>Methods</p> <p>We compare patients over and below the median of survival. Exploratory principal component analysis of gene expression data showed that the second principal component correlates well with patient survival. Explorative analysis of CGH data shows the same correlation.</p> <p>Results</p> <p>On chromosome 7 and 9 specific genes and bands are delineated which improve prognosis prediction independent of the previously described proliferation signature. We identify a compact survival predictor of seven genes for MCL patients. After extensive re-annotation using GEPAT, we established protein networks correlating with prognosis. Well known genes (CDC2, CCND1) and further proliferation markers (WEE1, CDC25, aurora kinases, BUB1, PCNA, E2F1) form a tight interaction network, but also non-proliferative genes (SOCS1, TUBA1B CEBPB) are shown to be associated with prognosis. Furthermore we show that aggressive MCL implicates a gene network shift to higher expressed genes in late cell cycle states and refine the set of non-proliferative genes implicated with bad prognosis in MCL.</p> <p>Conclusion</p> <p>The results from explorative data analysis of gene expression and CGH data are complementary to each other. Including further tests such as Wilcoxon rank test we point both to proliferative and non-proliferative gene networks implicated in inferior prognosis of MCL and identify suitable markers both in gene expression and CGH data.</p

Das menschliche Proteom ist geformt durch Evolution und Interaktion

Das menschliche Genom ist seit 2001 komplett sequenziert. Ein Großteil der Proteine wurde mittlerweile beschrieben und täglich werden bioinformatische Vorhersagen praktisch bestätigt. Als weiteres Großprojekt wurde kürzlich die Sequenzierung des Genoms von 1000 Menschen gestartet. Trotzdem ist immer noch wenig über die Evolution des gesamten menschlichen Proteoms bekannt. Proteindomänen und ihre Kombinationen sind teilweise sehr detailliert erforscht, aber es wurden noch nicht alle Domänenarchitekturen des Menschen in ihrer Gesamtheit miteinander verglichen. Der verwendete große hochqualitative Datensatz von Protein-Protein-Interaktionen und Komplexen stammt aus dem Jahr 2006 und ermöglicht es erstmals das menschliche Proteom mit einer vorher nicht möglichen Genauigkeit analysieren zu können. Hochentwickelte Cluster Algorithmen und die Verfügbarkeit von großer Rechenkapazität befähigen uns neue Information über Proteinnetzwerke ohne weitere Laborarbeit zu gewinnen. Die vorliegende Arbeit analysiert das menschliche Proteom auf drei verschiedenen Ebenen. Zuerst wurde der Ursprung von Proteinen basierend auf ihrer Domänenarchitektur analysiert, danach wurden Protein-Protein-Interaktionen untersucht und schließlich erfolgte Einteilung der Proteine nach ihren vorhandenen und fehlenden Interaktionen. Die meisten bekannten Proteine enthalten mindestens eine Domäne und die Proteinfunktion ergibt sich aus der Summe der Funktionen der einzelnen enthaltenen Domänen. Proteine, die auf der gleichen Domänenarchitektur basieren, das heißt die die gleichen Domänen in derselben Reihenfolge besitzen, sind homolog und daher aus einem gemeinsamen ursprünglichen Protein entstanden. Die Domänenarchitekturen der ursprünglichen Proteine wurden für 750000 Proteine aus 1313 Spezies bestimmt. Die Gruppierung von Spezies und ihrer Proteine ergibt sich aus taxonomischen Daten von NCBI-Taxonomy, welche mit zusätzlichen Informationen basierend auf molekularen Markern ergänzt wurden. Der resultierende Datensatz, bestehend aus 5817 Domänen und 32868 Domänenarchitekturen, war die Grundlage für die Bestimmung des Ursprungs der Proteine aufgrund ihrer Domänenarchitekturen. Es wurde festgestellt, dass nur ein kleiner Teil der neu evolvierten Domänenarchitekturen eines Taxons gleichzeitig auch im selben Taxon neu entstandene Proteindomänen enthält. Ein weiteres Ergebnis war, dass Domänenarchitekturen im Verlauf der Evolution länger und komplexer werden, und dass so verschiedene Organismen wie der Fadenwurm, die Fruchtfliege und der Mensch die gleiche Menge an unterschiedlichen Proteinen haben, aber deutliche Unterschiede in der Anzahl ihrer Domänenarchitekturen aufweisen. Der zweite Teil beschäftigt sich mit der Frage wie neu entstandene Proteine Bindungen mit dem schon bestehenden Proteinnetzwerk eingehen. In früheren Arbeiten wurde gezeigt, dass das Protein-Interaktions-Netzwerk ein skalenfreies Netz ist. Skalenfreie Netze, wie zum Beispiel das Internet, bestehen aus wenigen Knoten mit vielen Interaktionen, genannt Hubs, und andererseits aus vielen Knoten mit wenigen Interaktionen. Man vermutet, dass zwei Mechanismen zur Entstehung solcher Netzwerke führen. Erstens müssen neue Proteine um auch Teil des Proteinnetzwerkes zu werden mit Proteinen interagieren, die bereits Teil des Netzwerkes sind. Zweitens interagieren die neuen Proteine, gemäß der Theorie der bevorzugten Bindung, mit höherer Wahrscheinlichkeit mit solchen Proteinen im Netzwerk, die schon an zahlreichen weiteren Protein-Interaktionen beteiligt sind. Die Human Protein Reference Database stellt ein auf Informationen aus in-vivo Experimenten beruhendes Proteinnetzwerk für menschliche Proteine zur Verfügung. Basierend auf den in Kapitel I gewonnenen Informationen wurden die Proteine mit dem Ursprungstaxon ihrer Domänenarchitekturen versehen. Dadurch wurde gezeigt, dass ein Protein häufiger mit Proteinen, die im selben Taxon entstanden sind, interagiert, als mit Proteinen, die in anderen Taxa neu aufgetreten sind. Es stellte sich heraus, dass diese Interaktionsraten für alle Taxa deutlich höher waren, als durch das Zufallsmodel vorhergesagt wurden. Alle Taxa enthalten den gleichen Anteil an Proteinen mit vielen Interaktionen. Diese zwei Ergebnisse sprechen dagegen, dass die bevorzugte Bindung der alleinige Mechanismus ist, der zum heutigen Aufbau des menschlichen Proteininteraktion-Netzwerks beigetragen hat. Im dritten Teil wurden Proteine basierend auf dem Vorhandensein und der Abwesenheit von Interaktionen in Gruppen eingeteilt. Proteinnetzwerke können in kleine hoch vernetzte Teile zerlegt werden, die eine spezifische Funktion ausüben. Diese Gruppen können mit hoher statistischer Signifikanz berechnet werden, haben meistens jedoch keine biologische Relevanz. Mit einem neuen Algorithmus, welcher zusätzlich zu Interaktionen auch Nicht-Interaktionen berücksichtigt, wurde ein Datensatz bestehend aus 8,756 Proteinen und 32,331 Interaktionen neu unterteilt. Eine Einteilung in elf Gruppen zeigte hohe auf Gene Ontology basierte Werte und die Gruppen konnten signifikant einzelnen Zellteilen zugeordnet werden. Eine Gruppe besteht aus Proteinen, welche wenige Interaktionen miteinander aber viele Interaktionen zu zwei benachbarten Gruppen besitzen. Diese Gruppe enthält eine signifikant erhöhte Anzahl an Transportproteinen und die zwei benachbarten Gruppen haben eine erhöhte Anzahl an einerseits extrazellulären und andererseits im Zytoplasma und an der Membran lokalisierten Proteinen. Der Algorithmus hat damit unter Beweis gestellt das die Ergebnisse nicht bloß statistisch sondern auch biologisch relevant sind. Wenn wir auch noch weit vom Verständnis des Ursprungs der Spezies entfernt sind, so hat diese Arbeit doch einen Beitrag zum besseren Verständnis der Evolution auf dem Level der Proteine geleistet. Im Speziellen wurden neue Erkenntnisse über die Beziehung von Proteindomänen und Domänenarchitekturen, sowie ihre Präferenzen für Interaktionspartner im Interaktionsnetzwerk gewonnen.The human genome has been sequenced since 2001. Most proteins have been characterized now and with everyday more bioinformatical predictions are experimentally verified. A project is underway to sequence thousand humans. But still, little is known about the evolution of the human proteome itself. Domains and their combinations are analysed in detail but not all of the human domain architectures at once. Like no one before, we have large datasets of high quality human protein-protein-protein interactions and complexes available which allow us to characterize the human proteome with unmatched accuracy. Advanced clustering algorithms and computing power enable us to gain new information about protein interactions without touching a pipette. In this work, the human proteome is analysed at three different levels. First, the origin of the different types of proteins was analysed based on their domain architectures. The second part focuses on the protein-protein interactions. Finally, in the third part, proteins are clustered based on their interactions and non-interactions. Most proteins are built of domains and their function is the sum of their domain functions. Proteins that share the same domain architecture, the linear order of domains are homologues and should have originated from one common ancestral protein. This ancestor was calculated for roughly 750 000 proteins from 1313 species. The relations between the species are based on the NCBI Taxonomy and additional molecular data. The resulting data set of 5817 domains and 32868 domain architectures was used to estimate the origin of these proteins based on their architectures. It could be observed, that new domain architectures are only in a small fraction composed of domains arisen at the same taxon. It was also found that domain architectures increase in length and complexity in the course of evolution and that different organisms like worm, and human share nearly the same amount of proteins but differ in their number of distinct domain architectures. The second part of this thesis focuses on protein-protein interactions. This chapter addresses the question how new evolved proteins form connections within the existing network. The network built of protein-protein interactions was shown to be scale free. Scale free networks, like the internet, consist of few hubs with many connections and many nodes with few connections. They are thought to arise by two mechanisms. First, newly emerged proteins interact with proteins of the network. Second, according to the theory of preferential attachment, new proteins have a higher chance to interact with already interaction rich proteins. The Human Protein Reference Database provides an on in-vivo interaction data based network for human. With the data obtained from chapter one, proteins were marked with their taxon of origin based on their domain architectures. The interaction ratio of proteins of the same taxa compared to all interactions was calculated and higher values than the random model showed for nearly every taxa. On the other hand, there was no enrichment of proteins originated at the taxon of cellular organisms for the node degree found. The node degree is the number of links for this node. According to the theorie of preferential attachment the oldest nodes should have the most interactions and newly arisen proteins should be preferably attached to them not together. Both could not be shown in this analysis, preferential attachment could therefore not be the only explanation for the forming of the human protein interaction network. Finally in part three, proteins and all their interactions in the network are analysed. Protein networks can be divided into smaller highly interacting parts carrying out specific functions. This can be done with high statistical significance but still, it does not reflect the biological significance. Proteins were clustered based on their interactions and non-interactions with other proteins. A version with eleven clusters showed high gene ontology based ratings and clusters related to specific cell parts. One cluster consists of proteins having very few interactions together but many to proteins of two other clusters. This first cluster is significantly enriched with transport proteins and the two others are enriched with extracellular and cytoplasm/membrane located proteins. The algorithm seems therefore well suited to reflect the biological importance behind functional modules. Although we are still far from understanding the origin of species, this work has significantly contributed to a better understanding of evolution at the protein level and has, in particular, shown the relation of protein domains and protein architectures and their preferences for binding partners within interaction networks

Physiological and historical determinants of the distribution and abundance of insects

Understanding the consequences of past and future climatic changes on biodiversity has become one of the most important challenges of current ecological research. Due to the fundamental importance of climate for determining the distribution and abundance of species, climatic changes have led to strong shifts of species’ ranges to higher altitudes and latitudes as well as to local changes in the phenology and abundance of species during the last decades. Nevertheless, most organisms are incapable of rapid responses to such changes as they are constrained by, for instance, phylogenetic conservatism in thermal adaptations and dispersal limitations. Therefore, a mechanistic understanding of the variation in functional traits of species is crucial for predicting biological responses to climate change. However, so far, most trait-based inferences focused on endotherm taxa, whereas the physiological processes shaping the diversity patterns of ectothermic organisms, particularly of insects, remain poorly understood. The overall objective of this PhD thesis is to investigate the importance of interactions between environmental factors and species’ functional traits across regions, scales and taxa, to improve forecasts of the ecological consequences of climate change as well as our understanding of the ecological and evolutionary processes that determine biogeographical patterns, the range size and the abundance of insects. Insects, like 99.9 % of the species on our planet, are ectothermic organisms that in contrast to endothermic organisms, mainly depend on thermal energy from their environment for their activity and for maintaining vital physiological processes. Ectotherms therefore evolved adaptations to the temperature regime in which they live. From a physiological perspective, strong arguments exist that biophysical principles link variation in species’ colour lightness and body size to heat gain and loss in endothermic animals. Larger species retain body heat more efficiently than smaller species owing to their lower surface-area-to-volume ratio, and darker coloured species heat up faster than lighter coloured species because they absorb more solar radiation. Other functions include enhanced immunocompetence of larger species and enhanced pathogen resistance (Gloger’s rule) as well as UV protection of darker species. Mechanistic links between these two morphological traits, species’ physiology and climate are hence probably important determinants of variation in the distribution and abundance of ectotherm organisms, but the limited availability of distributional and morphological data has so far hampered a large-scale perspective on the physiological processes that shape biogeographical patterns in insects. Constraints to the evolution of species’ morphological traits and dispersal abilities can limit the colonization of regions characterized by new climates or habitats and thereby influence geographical patterns in the phylogenetic diversity or geographical rarity of taxa. On the one hand, spatial concentrations of rare species are important conservation targets, because they indicate the distribution of species that are both particularly vulnerable to extinction in the future and unique elements of biodiversity. On the other hand, overall patterns of these facets of diversity provide information about past dispersal events and the ecological processes that shaped contemporary patterns of biodiversity. In six chapters of my thesis I investigate whether biogeographical patterns of insect assemblages are driven by variation in the colour lightness and the body size. I show that melanin-based thermoregulation, pathogen resistance and UV protection are important mechanisms that influence the distribution of dragonflies, butterflies and moths at both local and continental scales. In all studies, species assemblages in cooler climates are on average darker coloured than assemblages in warmer climates. Furthermore, in line with the prediction that darker colouration is advantageous in regions with high humidity and in regions with high solar radiation due to the protective functions of melanin, colour lightness generally decreases with increasing precipitation and insolation. Body size clines are less strong and differ considerably among the considered taxa. In addition, I demonstrate that contrasting effects of the benefits and the energetic costs of an investment into body size and melanization on the range size and abundance of butterfly species can offset each other when their interactions with components of the energy budget are not taken into account. Thus, larger and darker butterfly species only have wider distributions and are more abundant if they compensate the costs of an investment into body size and melanization by reducing mobility costs or increasing energy uptake. In three additional chapters, I investigate whether evolutionary constraints on species’ thermal adaptations and dispersal ability influence the composition of insect assemblages and I assess the extent to which diversity patterns of insects are shaped by the contemporary climate and historical climatic changes. Using European dragonflies, I show that both phylogenetic conservatism of thermal adaptations and dispersal limitations constrain the recolonization of previously glaciated areas of Europe, resulting in a decrease of the endemism and phylogenetic diversity of assemblages with decreasing temperature and the increasing proportion of species with a high dispersal ability. In addition, I demonstrate that the climatic changes since the Last Glacial Maximum are consistently major drivers of the endemism and species richness of mammals, birds, amphibians and dragonflies across Africa. However, the results of this study also indicate that the signatures of species’ responses to historical climatic changes differ considerably between the considered taxa and are currently less effectively protected. Finally, using a group of flightless orthopterans endemic to Africa, I exemplify that the diversity of this group, and probability most of the insect diversity today found in the Eastern Arc Mountain biodiversity hotspot, has been generated by the interplay of humid periods that allowed the spread of forest-bound lineages across Africa with aridity-driven fragmentations of forests and their associated faunas. In conclusion, I demonstrate that both body size and colour lightness are major determinants of distribution and abundance of insects, across taxa, regions and scales. Despite the significant contributions of other functions of colour lightness, such as pathogen resistance and UV protection, as well as of the thermoregulatory function of body size, melanin-based thermoregulation is the most important and a strikingly general mechanism that shapes biogeographical patterns of insect. To understand and predict the effects of body size and colour lightness on ecological dynamics of insect species it is, however, crucial to account for their interactions with components of the energy budget, because the contrasting effects of an investment into body size, wing size and melanization on the range size and abundance of species can partly offset each other. Purely correlative approaches that predict spatio-temporal variation in the distribution and abundance of insect species based on easily measured morphological traits are therefore prone to false mechanistic conclusions and likely underestimate the functional importance of morphological traits. Furthermore, phylogenetic conservatism of thermal adaptations and dispersal limitations affect trait-environment relationships and species’ responses to historical climatic changes. Together these results highlight the potential of models that integrate morphological, climatic and phylogenetic data for improving predictions of species’ responses to climate change as well as our understanding of the processes that generated and maintain the remarkable diversity of insects on Earth

Physiological and historical determinants of the distribution and abundance of insects

Understanding the consequences of past and future climatic changes on biodiversity has become one of the most important challenges of current ecological research. Due to the fundamental importance of climate for determining the distribution and abundance of species, climatic changes have led to strong shifts of species’ ranges to higher altitudes and latitudes as well as to local changes in the phenology and abundance of species during the last decades. Nevertheless, most organisms are incapable of rapid responses to such changes as they are constrained by, for instance, phylogenetic conservatism in thermal adaptations and dispersal limitations. Therefore, a mechanistic understanding of the variation in functional traits of species is crucial for predicting biological responses to climate change. However, so far, most trait-based inferences focused on endotherm taxa, whereas the physiological processes shaping the diversity patterns of ectothermic organisms, particularly of insects, remain poorly understood. The overall objective of this PhD thesis is to investigate the importance of interactions between environmental factors and species’ functional traits across regions, scales and taxa, to improve forecasts of the ecological consequences of climate change as well as our understanding of the ecological and evolutionary processes that determine biogeographical patterns, the range size and the abundance of insects. Insects, like 99.9 % of the species on our planet, are ectothermic organisms that in contrast to endothermic organisms, mainly depend on thermal energy from their environment for their activity and for maintaining vital physiological processes. Ectotherms therefore evolved adaptations to the temperature regime in which they live. From a physiological perspective, strong arguments exist that biophysical principles link variation in species’ colour lightness and body size to heat gain and loss in endothermic animals. Larger species retain body heat more efficiently than smaller species owing to their lower surface-area-to-volume ratio, and darker coloured species heat up faster than lighter coloured species because they absorb more solar radiation. Other functions include enhanced immunocompetence of larger species and enhanced pathogen resistance (Gloger’s rule) as well as UV protection of darker species. Mechanistic links between these two morphological traits, species’ physiology and climate are hence probably important determinants of variation in the distribution and abundance of ectotherm organisms, but the limited availability of distributional and morphological data has so far hampered a large-scale perspective on the physiological processes that shape biogeographical patterns in insects. Constraints to the evolution of species’ morphological traits and dispersal abilities can limit the colonization of regions characterized by new climates or habitats and thereby influence geographical patterns in the phylogenetic diversity or geographical rarity of taxa. On the one hand, spatial concentrations of rare species are important conservation targets, because they indicate the distribution of species that are both particularly vulnerable to extinction in the future and unique elements of biodiversity. On the other hand, overall patterns of these facets of diversity provide information about past dispersal events and the ecological processes that shaped contemporary patterns of biodiversity. In six chapters of my thesis I investigate whether biogeographical patterns of insect assemblages are driven by variation in the colour lightness and the body size. I show that melanin-based thermoregulation, pathogen resistance and UV protection are important mechanisms that influence the distribution of dragonflies, butterflies and moths at both local and continental scales. In all studies, species assemblages in cooler climates are on average darker coloured than assemblages in warmer climates. Furthermore, in line with the prediction that darker colouration is advantageous in regions with high humidity and in regions with high solar radiation due to the protective functions of melanin, colour lightness generally decreases with increasing precipitation and insolation. Body size clines are less strong and differ considerably among the considered taxa. In addition, I demonstrate that contrasting effects of the benefits and the energetic costs of an investment into body size and melanization on the range size and abundance of butterfly species can offset each other when their interactions with components of the energy budget are not taken into account. Thus, larger and darker butterfly species only have wider distributions and are more abundant if they compensate the costs of an investment into body size and melanization by reducing mobility costs or increasing energy uptake. In three additional chapters, I investigate whether evolutionary constraints on species’ thermal adaptations and dispersal ability influence the composition of insect assemblages and I assess the extent to which diversity patterns of insects are shaped by the contemporary climate and historical climatic changes. Using European dragonflies, I show that both phylogenetic conservatism of thermal adaptations and dispersal limitations constrain the recolonization of previously glaciated areas of Europe, resulting in a decrease of the endemism and phylogenetic diversity of assemblages with decreasing temperature and the increasing proportion of species with a high dispersal ability. In addition, I demonstrate that the climatic changes since the Last Glacial Maximum are consistently major drivers of the endemism and species richness of mammals, birds, amphibians and dragonflies across Africa. However, the results of this study also indicate that the signatures of species’ responses to historical climatic changes differ considerably between the considered taxa and are currently less effectively protected. Finally, using a group of flightless orthopterans endemic to Africa, I exemplify that the diversity of this group, and probability most of the insect diversity today found in the Eastern Arc Mountain biodiversity hotspot, has been generated by the interplay of humid periods that allowed the spread of forest-bound lineages across Africa with aridity-driven fragmentations of forests and their associated faunas. In conclusion, I demonstrate that both body size and colour lightness are major determinants of distribution and abundance of insects, across taxa, regions and scales. Despite the significant contributions of other functions of colour lightness, such as pathogen resistance and UV protection, as well as of the thermoregulatory function of body size, melanin-based thermoregulation is the most important and a strikingly general mechanism that shapes biogeographical patterns of insect. To understand and predict the effects of body size and colour lightness on ecological dynamics of insect species it is, however, crucial to account for their interactions with components of the energy budget, because the contrasting effects of an investment into body size, wing size and melanization on the range size and abundance of species can partly offset each other. Purely correlative approaches that predict spatio-temporal variation in the distribution and abundance of insect species based on easily measured morphological traits are therefore prone to false mechanistic conclusions and likely underestimate the functional importance of morphological traits. Furthermore, phylogenetic conservatism of thermal adaptations and dispersal limitations affect trait-environment relationships and species’ responses to historical climatic changes. Together these results highlight the potential of models that integrate morphological, climatic and phylogenetic data for improving predictions of species’ responses to climate change as well as our understanding of the processes that generated and maintain the remarkable diversity of insects on Earth

Une nouvelle libellule Hawker du Jurassique moyen de Chine (Odonata : Aeshnoptera)

International audienceA new genus and species Linqibinia panae of paracymatophlebiid hawker dragonfly is described from the Middle Jurassic Haifanggou Formation (Inner Mongolia, China). Previously only known from Karatau in Kazakhstan, the discovery of another member of this family extends its range across Central Asia. It confirms that the Aeshnoptera was among the most diverse odonatan clades during the Middle-Late Jurassic.Le nouveau genre et la nouvelle espèce Linqibinia panae de Aeshnoptera Paracymatophlebiidae sont décrits du Jurassique moyen (formation de Haifanggou, Mongolie intérieure, Chine). Cette famille n’était connue que de Karatau au Kazakhstan ; cette découverte étend sa distribution au travers de l’Asie centrale. Elle confirme que les Aeshnoptera étaient parmi les clades d’Odonata les plus diversifiés au Jurassique moyen–supérieur