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Natural DNA storage allows cellular differentiation, evolution, the growth of our children and controls all our ecosystems. Here, we discuss the fundamental aspects of DNA storage and recent advances in this field, with special emphasis on natural processes and solutions that can be exploited. We point out new ways of efficient DNA and nucleotide storage that are inspired by nature. Within a few years DNA-based information storage may become an attractive and natural complementation to current electronic data storage systems. We discuss rapid and directed access (e.g. DNA elements such as promotors, enhancers), regulatory signals and modulation (e.g. lncRNA) as well as integrated high-density storage and processing modules (e.g. chromosomal territories). There is pragmatic DNA storage for use in biotechnology and human genetics. We examine DNA storage as an approach for synthetic biology (e.g. light-controlled nucleotide processing enzymes). The natural polymers of DNA and RNA offer much for direct storage operations (read-in, read-out, access control). The inbuilt parallelism (many molecules at many places working at the same time) is important for fast processing of information. Using biology concepts from chromosomal storage, nucleic acid processing as well as polymer material sciences such as electronical effects in enzymes, graphene, nanocellulose up to DNA macramé , DNA wires and DNA-based aptamer field effect transistors will open up new applications gradually replacing classical information storage methods in ever more areas over time (decades).
We steered the soil microbiome via applications of organic residues (mix of cover crop residues, sewage sludge + compost, and digestate + compost) to enhance multiple ecosystem services in line with climate-smart agriculture. Our result highlights the potential to reduce greenhouse gases (GHG) emissions from agricultural soils by the application of specific organic amendments (especially digestate + compost). Unexpectedly, also the addition of mineral fertilizer in our mesocosms led to similar combined GHG emissions than one of the specific organic amendments. However, the application of organic amendments has the potential to increase soil C, which is not the case when using mineral fertilizer. While GHG emissions from cover crop residues were significantly higher compared to mineral fertilizer and the other organic amendments, crop growth was promoted. Furthermore, all organic amendments induced a shift in the diversity and abundances of key microbial groups. We show that organic amendments have the potential to not only lower GHG emissions by modifying the microbial community abundance and composition, but also favour crop growth-promoting microorganisms. This modulation of the microbial community by organic amendments bears the potential to turn soils into more climate-smart soils in comparison to the more conventional use of mineral fertilizers.
Healthy functioning of the female reproductive tract (FRT) depends on balanced and dynamic regulation by hormones during the menstrual cycle, pregnancy and childbirth. The mucosal epithelial lining of different regions of the FRT—ovaries, fallopian tubes, uterus, cervix and vagina—facilitates the selective transport of gametes and successful transfer of the zygote to the uterus where it implants and pregnancy takes place. It also prevents pathogen entry. Recent developments in three-dimensional (3D) organoid systems from the FRT now provide crucial experimental models that recapitulate the cellular heterogeneity and physiological, anatomical and functional properties of the organ in vitro. In this review, we summarise the state of the art on organoids generated from different regions of the FRT. We discuss the potential applications of these powerful in vitro models to study normal physiology, fertility, infections, diseases, drug discovery and personalised medicine.
The mason wasp Odynerus spinipes shows an exceptional case of intrasexual cuticular hydrocarbon (CHC) profile dimorphism. Females of this species display one of two CHC profiles (chemotypes) that differ qualitatively and quantitatively from each other. The ratio of the two chemotypes was previously shown to be close to 1:1 at three sites in Southern Germany, which might not be representative given the Palearctic distribution of the species. To infer the frequency of the two chemotypes across the entire distributional range of the species, we analyzed with GC–MS the CHC profile of 1042 dry-mounted specimens stored in private and museum collections. We complemented our sampling by including 324 samples collected and preserved specifically for studying their CHCs. We were capable of reliably identifying the chemotypes in 91% of dry-mounted samples, some of which collected almost 200 years ago. We found both chemotypes to occur in the Far East, the presumed glacial refuge of the species, and their frequency to differ considerably between sites and geographic regions. The geographic structure in the chemotype frequencies could be the result of differential selection regimes and/or different dispersal routes during the colonization of the Western Palearctic. The presented data pave the route for disentangling these factors by providing information where to geographically sample O. spinipes for population genetic analyses. They also form the much-needed basis for future studies aiming to understand the evolutionary and geographic origin as well as the genetics of the astounding CHC profile dimorphism that O. spinipes females exhibit.
Chapter I: Introduction
Temperature is a major driver of biodiversity and abundance patterns on our planet, which becomes particularly relevant facing the entanglement of an imminent biodiversity and climate crisis. Climate shapes the composition of species assemblages either directly via abiotic filtering mechanisms or indirectly through alterations in biotic interactions. Insects - integral elements of Earth’s ecosystems - are affected by climatic variation such as warming, yet responses vary among species. While species’ traits, antagonistic biotic interactions, and even species’ microbial mutualists may determine temperature-dependent assembly processes, the lion’s share of these complex relationships remains poorly understood due to methodological constraints. Mountains, recognized as hotspots of diversity and threatened by rapidly changing climatic conditions, can serve as natural experimental settings to study the response of insect assemblages and their trophic interactions to temperature variation, instrumentalizing the high regional heterogeneity of micro- and macroclimate. With this thesis, we aim to enhance our mechanistic understanding of temperature-driven assembly processes within insect communities, exemplified by Orthoptera, that are significant herbivores in temperate mountain grassland ecosystems. Therefore, we combined field surveys of Orthoptera assemblages on grassland sites with molecular tools for foodweb reconstruction, primarily leveraging the elevational gradients offered by the complex topography within the Berchtesgaden Alpine region (Bavaria, Germany) as surrogate for temperature variation (space-for-time substitution approach). In this framework, we studied the effects of temperature variation on (1) species richness, abundance, community composition, and interspecific as well as intraspecific trait patterns, (2) ecological feeding specialisation, and (3) previously neglected links to microbial associates found in the faeces.
Chapter II: Temperature-driven assembly processes
Climate varies at multiple scales. Since microclimate is often overlooked, we assessed effects of local temperature deviations on species and trait compositions of insect communities along macroclimatic temperature gradients in Chapter II. Therefore, we employed joint species distribution modelling to explore how traits drive variation in the climatic niches of Orthoptera species at grassland sites characterized by contrasting micro- and macroclimatic conditions. Our findings revealed two key insights: (1) additive effects of micro- and macroclimate on the diversity, but (2) interactive effects on the abundance of several species, resulting in turnover and indicating that species possess narrower climatic niches than their elevational distributions might imply. This chapter suggests positive effects of warming on Orthoptera, but also highlights that the interplay of macro- and microclimate plays a pivotal role in structuring insect communities. Thus, it underscores the importance of considering both elements when predicting the responses of species to climate change. Additionally, this chapter revealed inter- and intraspecific effects of traits on the niches and distribution of species.
Chapter III: Dietary specialisation along climatic gradients
A crucial trait linked to the position of climatic niches is dietary specialisation. According to the ‘altitudinal niche-breadth hypothesis’, species of high-elevation habitats should be less specialized compared to their low-elevation counterparts. However, empirical evidence on shifts in specialization is scarce for generalist insect herbivores and existing studies often fail to control for the phylogeny and abundance of interaction partners. In Chapter III, we used a combination of field observations and amplicon sequencing to reconstruct dietary relationships between Orthoptera and plants along an extensive temperature gradient. We did not find close but flexible links between individual grasshopper and plant taxa in space. While interaction network specialisation increased with temperature, the corrected dietary specialisation pattern peaked at intermediate elevations on assemblage level. These nuanced findings demonstrate that (1) resource availability, (2) phylogenetic relationships, and (3) climate can affect empirical foodwebs intra- and interspecifically and, hence, the dietary specialisation of herbivorous insects. In this context, we discuss that the underlying mechanisms involved in shaping the specialisation of herbivore assemblages may switch along temperature clines.
Chapter IV: Links between faecal microbe communities, feeding habits, and climate
Since gut microbes affect the fitness and digestion of insects, studying their diversity could provide novel insights into specialisation patterns. However, their association with insect hosts that differ in feeding habits and specialisation has never been investigated along elevational climatic gradients. In Chapter IV, we utilized the dietary information gathered in Chapter III to characterize links between insects with distinct feeding behaviour and the microbial communities present in their faeces, using amplicon sequencing. Both, feeding and climate affected the bacterial communities. However, the large overlap of microbes at site level suggests that common bacteria are acquired from the shared feeding environment, such as the plants consumed by the insects. These findings emphasize the influence of a broader environmental context on the composition of insect gut microbial communities.
Chapter V: Discussion & Conclusions
Cumulatively, the sections of this dissertation provide support for the hypothesis that climatic conditions play a role in shaping plant–herbivore systems. The detected variation of taxonomic and functional compositions contributes to our understanding of assembly processes and resulting diversity patterns within Orthoptera communities, shedding light on the mechanisms that structure their trophic interactions in diverse climates. The combined results presented suggest that a warmer climate could foster an increase of Orthoptera species richness in Central European semi-natural grasslands, also because the weak links observed between insect herbivores and plants are unlikely to limit decoupled range shifts. However, the restructuring of Orthoptera communities in response to warmer temperatures depends on species' traits such as moisture preferences or phenology. Notably, we were able to demonstrate a crucial role of microclimate for many species, partly unravelling narrower climatic niches than their elevational ranges suggest. We found evidence that not only Orthoptera community composition, specialisation, and traits varied along elevational gradients, but even microbial communities in the faeces of Orthoptera changed, which is a novel finding. This complex restructuring and reassembly of communities, coupled with the nonlinear specialisation of trophic interactions and a high diversity of associated bacteria, emphasize our currently incomplete comprehension of how ecosystems will develop under future climatic conditions, demanding caution in making simplified predictions for biodiversity change under climate warming. Since these predictions may benefit from including biotic interactions and both, micro- and macroclimate based on our findings, conservation authorities and practitioners must not neglect improving microclimatic conditions to ensure local survival of a diverse set of threatened and demanding species. In this context, mountains can play a pivotal role for biodiversity conservation since these offer heterogeneous microclimatic conditions in proximity that can be utilized by species with distinct niches.
Infection research largely relies on classical cell culture or mouse models. Despite having delivered invaluable insights into host-pathogen interactions, both have limitations in translating mechanistic principles to human pathologies. Alternatives can be derived from modern Tissue Engineering approaches, allowing the reconstruction of functional tissue models in vitro. Here, we combined a biological extracellular matrix with primary tissue-derived enteroids to establish an in vitro model of the human small intestinal epithelium exhibiting in vivo-like characteristics. Using the foodborne pathogen Salmonella enterica serovar Typhimurium, we demonstrated the applicability of our model to enteric infection research in the human context. Infection assays coupled to spatio-temporal readouts recapitulated the established key steps of epithelial infection by this pathogen in our model. Besides, we detected the upregulation of olfactomedin 4 in infected cells, a hitherto unrecognized aspect of the host response to Salmonella infection. Together, this primary human small intestinal tissue model fills the gap between simplistic cell culture and animal models of infection, and shall prove valuable in uncovering human-specific features of host-pathogen interplay.
In the fast-evolving landscape of biomedical research, the emergence of big data has presented researchers with extraordinary opportunities to explore biological complexities. In biomedical research, big data imply also a big responsibility. This is not only due to genomics data being sensitive information but also due to genomics data being shared and re-analysed among the scientific community. This saves valuable resources and can even help to find new insights in silico. To fully use these opportunities, detailed and correct metadata are imperative. This includes not only the availability of metadata but also their correctness. Metadata integrity serves as a fundamental determinant of research credibility, supporting the reliability and reproducibility of data-driven findings. Ensuring metadata availability, curation, and accuracy are therefore essential for bioinformatic research. Not only must metadata be readily available, but they must also be meticulously curated and ideally error-free. Motivated by an accidental discovery of a critical metadata error in patient data published in two high-impact journals, we aim to raise awareness for the need of correct, complete, and curated metadata. We describe how the metadata error was found, addressed, and present examples for metadata-related challenges in omics research, along with supporting measures, including tools for checking metadata and software to facilitate various steps from data analysis to published research.
Highlights
• Data awareness and data integrity underpins the trustworthiness of results and subsequent further analysis.
• Big data and bioinformatics enable efficient resource use by repurposing publicly available RNA-Sequencing data.
• Manual checks of data quality and integrity are insufficient due to the overwhelming volume and rapidly growing data.
• Automation and artificial intelligence provide cost-effective and efficient solutions for data integrity and quality checks.
• FAIR data management, various software solutions and analysis tools assist metadata maintenance.
Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.
CRISPR/Cas9 gene editing has revolutionised loss-of-function experiments in Leishmania, the causative agent of leishmaniasis. As Leishmania lack a functional non-homologous DNA end joining pathway however, obtaining null mutants typically requires additional donor DNA, selection of drug resistance-associated edits or time-consuming isolation of clones. Genome-wide loss-of-function screens across different conditions and across multiple Leishmania species are therefore unfeasible at present. Here, we report a CRISPR/Cas9 cytosine base editor (CBE) toolbox that overcomes these limitations. We employed CBEs in Leishmania to introduce STOP codons by converting cytosine into thymine and created http://www.leishbaseedit.net/ for CBE primer design in kinetoplastids. Through reporter assays and by targeting single- and multi-copy genes in L. mexicana, L. major, L. donovani, and L. infantum, we demonstrate how this tool can efficiently generate functional null mutants by expressing just one single-guide RNA, reaching up to 100% editing rate in non-clonal populations. We then generated a Leishmania-optimised CBE and successfully targeted an essential gene in a plasmid library delivered loss-of-function screen in L. mexicana. Since our method does not require DNA double-strand breaks, homologous recombination, donor DNA, or isolation of clones, we believe that this enables for the first time functional genetic screens in Leishmania via delivery of plasmid libraries.
PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in Bacillus subtilis, (ii) making Vaccinia virus oncolytic by switching on its viral replication mainly in cancer cells and triggering cancer cell apoptosis and (iii) optogenetic control of nucleotide processing protein networks to operate DNA storage. Multilevel communication between components is critical for efficient network switching, as demonstrated by a general census on prokaryotic and eukaryotic networks and comparing design with synthetic networks using PRO-Simat. The tool is available at https://prosimat.heinzelab.de/ as a web-based query server.