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Background
Teleost fishes comprise more than half of the vertebrate species. Within teleosts, most phylogenies consider the split between Osteoglossomorpha and Euteleosteomorpha/Otomorpha as basal, preceded only by the derivation of the most primitive group of teleosts, the Elopomorpha. While Osteoglossomorpha are generally species poor, the taxon contains the African weakly electric fish (Mormyroidei), which have radiated into numerous species. Within the mormyrids, the genus Campylomormyrus is mostly endemic to the Congo Basin. Campylomormyrus serves as a model to understand mechanisms of adaptive radiation and ecological speciation, especially with regard to its highly diverse species-specific electric organ discharges (EOD). Currently, there are few well-annotated genomes available for electric fish in general and mormyrids in particular. Our study aims at producing a high-quality genome assembly and to use this to examine genome evolution in relation to other teleosts. This will facilitate further understanding of the evolution of the osteoglossomorpha fish in general and of electric fish in particular.
Results
A high-quality weakly electric fish (C. compressirostris) genome was produced from a single individual with a genome size of 862 Mb, consisting of 1,497 contigs with an N50 of 1,399 kb and a GC-content of 43.69%. Gene predictions identified 34,492 protein-coding genes, which is a higher number than in the two other available Osteoglossomorpha genomes of Paramormyrops kingsleyae and Scleropages formosus. A Computational Analysis of gene Family Evolution (CAFE5) comparing 33 teleost fish genomes suggests an overall faster gene family turnover rate in Osteoglossomorpha than in Otomorpha and Euteleosteomorpha. Moreover, the ratios of expanded/contracted gene family numbers in Osteoglossomorpha are significantly higher than in the other two taxa, except for species that had undergone an additional genome duplication (Cyprinus carpio and Oncorhynchus mykiss). As potassium channel proteins are hypothesized to play a key role in EOD diversity among species, we put a special focus on them, and manually curated 16 Kv1 genes. We identified a tandem duplication in the KCNA7a gene in the genome of C. compressirostris.
Conclusions
We present the fourth genome of an electric fish and the third well-annotated genome for Osteoglossomorpha, enabling us to compare gene family evolution among major teleost lineages. Osteoglossomorpha appear to exhibit rapid gene family evolution, with more gene family expansions than contractions. The curated Kv1 gene family showed seven gene clusters, which is more than in other analyzed fish genomes outside Osteoglossomorpha. The KCNA7a, encoding for a potassium channel central for EOD production and modulation, is tandemly duplicated which may related to the diverse EOD observed among Campylomormyrus species.
The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism.
Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83%) of single lethal knock-outs and 75% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.
Progressive habitat fragmentation threatens plant species with narrow habitat requirements. While local environmental conditions define population growth rates and recruitment success at the patch level, dispersal is critical for population viability at the landscape scale. Identifying the dynamics of plant meta-populations is often confounded by the uncertainty about soil-stored population compartments. We combined a landscape-scale assessment of an amphibious plant's population structure with measurements of dispersal complexity in time to track dispersal and putative shifts in functional connectivity. Using 13 microsatellite markers, we analyzed the genetic structure of extant Oenanthe aquatica populations and their soil seed banks in a kettle hole system to uncover hidden connectivity among populations in time and space. Considerable spatial genetic structure and isolation-by-distance suggest limited gene flow between sites. Spatial isolation and patch size showed minor effects on genetic diversity. Genetic similarity found among extant populations and their seed banks suggests increased local recruitment, despite some evidence of migration and recent colonization. Results indicate stepping-stone dispersal across adjacent populations. Among permanent and ephemeral demes the resulting meta-population demography could be determined by source-sink dynamics. Overall, these spatiotemporal connectivity patterns support mainland-island dynamics in our system, highlighting the importance of persistent seed banks as enduring sources of genetic diversity.
Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas.
Aquatic ecosystems are frequently overlooked as fungal habitats, although there is increasing evidence that their diversity and ecological importance are greater than previously considered. Aquatic fungi are critical and abundant components of nutrient cycling and food web dynamics, e.g., exerting top-down control on phytoplankton communities and forming symbioses with many marine microorganisms. However, their relevance for microphytobenthic communities is almost unexplored. In the light of global warming, polar regions face extreme changes in abiotic factors with a severe impact on biodiversity and ecosystem functioning. Therefore, this study aimed to describe, for the first time, fungal diversity in Antarctic benthic habitats along the salinity gradient and to determine the co-occurrence of fungal parasites with their algal hosts, which were dominated by benthic diatoms. Our results reveal that Ascomycota and Chytridiomycota are the most abundant fungal taxa in these habitats. We show that also in Antarctic waters, salinity has a major impact on shaping not just fungal but rather the whole eukaryotic community composition, with a diversity of aquatic fungi increasing as salinity decreases. Moreover, we determined correlations between putative fungal parasites and potential benthic diatom hosts, highlighting the need for further systematic analysis of fungal diversity along with studies on taxonomy and ecological roles of Chytridiomycota.
This study focuses on three key aspects: (a) crude throat swab samples in a viral transport medium (VTM) as templates for RT-LAMP reactions; (b) a biotinylated DNA probe with enhanced specificity for LFA readouts; and (c) a digital semi-quantification of LFA readouts. Throat swab samples from SARS-CoV-2 positive and negative patients were used in their crude (no cleaning or pre-treatment) forms for the RT-LAMP reaction. The samples were heat-inactivated but not treated for any kind of nucleic acid extraction or purification. The RT-LAMP (20 min processing time) product was read out by an LFA approach using two labels: FITC and biotin. FITC was enzymatically incorporated into the RT-LAMP amplicon with the LF-LAMP primer, and biotin was introduced using biotinylated DNA probes, specifically for the amplicon region after RT-LAMP amplification. This assay setup with biotinylated DNA probe-based LFA readouts of the RT-LAMP amplicon was 98.11% sensitive and 96.15% specific. The LFA result was further analysed by a smartphone-based IVD device, wherein the T-line intensity was recorded. The LFA T-line intensity was then correlated with the qRT-PCR Ct value of the positive swab samples. A digital semi-quantification of RT-LAMP-LFA was reported with a correlation coefficient of R2 = 0.702. The overall RT-LAMP-LFA assay time was recorded to be 35 min with a LoD of three RNA copies/µL (Ct-33). With these three advancements, the nucleic acid testing-point of care technique (NAT-POCT) is exemplified as a versatile biosensor platform with great potential and applicability for the detection of pathogens without the need for sample storage, transportation, or pre-processing.
The physiological dependence of animals on dietary intake of vitamins, amino acids, and fatty acids is ubiquitous. Sharp differences in the availability of these vital dietary biomolecules among different resources mean that consumers must adopt a range of strategies to meet their physiological needs. We review the emerging work on omega-3 long-chain polyunsaturated fatty acids, focusing predominantly on predator-prey interactions, to illustrate that trade-off between capacities to consume resources rich in vital biomolecules and internal synthesis capacity drives differences in phenotype and fitness of consumers. This can then feedback to impact ecosystem functioning. We outline how focus on vital dietary biomolecules in eco-eco-devo dynamics can improve our understanding of anthropogenic changes across multiple levels of biological organization.
Starch is a biopolymer for which, despite its simple composition, understanding the precise mechanism behind its formation and regulation has been challenging. Several approaches and bioanalytical tools can be used to expand the knowledge on the different parts involved in the starch metabolism. In this sense, a comprehensive analysis targeting two of the main groups of molecules involved in this process: proteins, as effectors/regulators of the starch metabolism, and maltodextrins as starch components and degradation products, was conducted in this research work using potato plants (Solanum tuberosum L. cv. Desiree) as model of study. On one side, proteins physically interacting to potato starch were isolated and analyzed through mass spectrometry and western blot for their identification. Alternatively, starch interacting proteins were explored in potato tubers from transgenic plants having antisense inhibition of starch-related enzymes and on tubers stored under variable environmental conditions. Most of the proteins recovered from the starch granules corresponded to previously described proteins having a specific role in the starch metabolic pathway. Another set of proteins could be grouped as protease inhibitors, which were found weakly interacting to starch. Variations in the protein profile obtained after electrophoresis separation became clear when tubers were stored under different temperatures, indicating a differential expression of proteins in response to changing environmental conditions.
On the other side, since maltodextrin metabolism is thought to be involved in both starch initiation and degradation, soluble maltooligosaccharide content in potato tubers was analyzed in this work under diverse experimental variables. For this, tuber disc samples from wild type and transgenic lines strongly repressing either the plastidial or cytosolic form of the -glucan phosphorylase and phosphoglucomutase were incubated with glucose, glucose-6-phosphate, and glucose-1-phosphate solutions to evaluate the influence of such enzymes on the conversion of the carbon sources into soluble maltodextrins, in comparison to wild-type samples. Relative maltodextrin amounts analyzed through capillary electrophoresis equipped with laser-induced fluorescence (CE-LIF) revealed that tuber discs could immediately uptake glucose-1-phosphate and use it to produce maltooligosaccharides with a degree of polymerization of up to 30 (DP30), in contrast to transgenic tubers with strong repression of the plastidial glucan phosphorylase. The results obtained from the maltodextrin analysis support previous indications that a specific transporter for glucose-1-phosphate may exist in both the plant cells and the plastidial membranes, thereby allowing a glucose-6-phosphate independent transport. Furthermore, it confirms that the plastidial glucan phosphorylase is responsible for producing longer maltooligosaccharides in the plastids by catalyzing a glucan polymerization reaction when glucose-1-phosphate is available. All these findings contribute to a better understanding of the role of the plastidial glucan phosphorylase as a key enzyme directly involved in the synthesis and degradation of glucans and their implication on starch metabolism.
Cells are built from a variety of macromolecules and metabolites. Both, the proteome and the metabolome are highly dynamic and responsive to environmental cues and developmental processes. But it is not their bare numbers, but their interactions that enable life. The protein-protein (PPI) and protein-metabolite interactions (PMI) facilitate and regulate all aspects of cell biology, from metabolism to mitosis. Therefore, the study of PPIs and PMIs and their dynamics in a cell-wide context is of great scientific interest. In this dissertation, I aim to chart a map of the dynamic PPIs and PMIs across metabolic and cellular transitions. As a model system, I study the shift from the fermentative to the respiratory growth, known as the diauxic shift, in the budding yeast Saccharomyces cerevisiae. To do so, I am applying a co-fractionation mass spectrometry (CF-MS) based method, dubbed protein metabolite interactions using size separation (PROMIS). PROMIS, as well as comparable methods, will be discussed in detail in chapter 1.
Since PROMIS was developed originally for Arabidopsis thaliana, in chapter 2, I will describe the adaptation of PROMIS to S. cerevisiae. Here, the obtained results demonstrated a wealth of protein-metabolite interactions, and experimentally validated 225 previously predicted PMIs. Applying orthogonal, targeted approaches to validate the interactions of a proteogenic dipeptide, Ser-Leu, five novel protein-interactors were found. One of those proteins, phosphoglycerate kinase, is inhibited by Ser-Leu, placing the dipeptide at the regulation of glycolysis.
In chapter 3, I am presenting PROMISed, a novel web-tool designed for the analysis of PROMIS- and other CF-MS-datasets. Starting with raw fractionation profiles, PROMISed enables data pre-processing, profile deconvolution, scores differences in fractionation profiles between experimental conditions, and ultimately charts interaction networks. PROMISed comes with a user-friendly graphic interface, and thus enables the routine analysis of CF-MS data by non-computational biologists.
Finally, in chapter 4, I applied PROMIS in combination with the isothermal shift assay to the diauxic shift in S. cerevisiae to study changes in the PPI and PMI landscape across this metabolic transition. I found a major rewiring of protein-protein-metabolite complexes, exemplified by the disassembly of the proteasome in the respiratory phase, the loss of interaction of an enzyme involved in amino acid biosynthesis and its cofactor, as well as phase and structure specific interactions between dipeptides and enzymes of central carbon metabolism.
In chapter 5, I am summarizing the presented results, and discuss a strategy to unravel the potential patterns of dipeptide accumulation and binding specificities. Lastly, I recapitulate recently postulated guidelines for CF-MS experiments, and give an outlook of protein interaction studies in the near future.
Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security.
Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species.
Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity.
Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs.
In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses.