Biology subjects

Schulz, C.

Publications and source records attributed to Schulz, C..

31 records · Page 2Linked to original sources

bioRxiv2021

Quantification of macromolecular biomass composition for constraint-based metabolic modeling

Genome-scale metabolic models (GEMs) are mathematical representations of metabolism that allow for in silico simulation of metabolic phenotypes and capabilities. A prerequisite for these predictions is an accurate representation of the biomolecular composition of the cell necessary for replication and growth, implemented in GEMs as the so-called biomass objective function (BOF). The BOF contains the metabolic precursors required for synthesis of the cellular macro- and micromolecular constituents (e.g. protein, RNA, DNA), and its composition is highly dependent on the particular organism, strain, and growth condition. Despite its critical role, the BOF is rarely constructed using specific measurements of the modeled organism, drawing the validity of this approach into question. Thus, there is a need to establish robust and reliable protocols for experimental condition-specific biomass determination. Here, we address this challenge by presenting a general pipeline for biomass quantification, evaluating its performance on Escherichia coli K-12 MG1655 sampled during balanced exponential growth under controlled conditions in a batch-fermentor set-up. We significantly improve both the coverage and molecular resolution compared to previously published workflows, quantifying 91.6% of the biomass. Our measurements display great correspondence with previously reported measurements, and we were also able to detect subtle characteristics specific to the particular E. coli strain. Using the modified E. coli GEM iML1515a, we compare the feasible flux ranges of our experimentally determined BOF with the original BOF, finding that the changes in BOF coefficients considerably affect the attainable fluxes at the genome-scale.

systems biology↗

bioRxiv2021

Scent dog identification of SARS-CoV-2 infections, similar across different body fluids

BackgroundThe main strategy to contain the current SARS-CoV-2 pandemic remains to implement a comprehensive testing, tracing and quarantining strategy until vaccination of the population is adequate. MethodsTen dogs were trained to detect SARS-CoV-2 infections in beta-propiolactone inactivated saliva samples. The subsequent cognitive transfer performance for the recognition of non-inactivated samples were tested on saliva, urine, and sweat in a randomised, double-blind controlled study. ResultsDogs were tested on a total of 5242 randomised sample presentations. Dogs detected non-inactivated saliva samples with a diagnostic sensitivity of 84% and specificity of 95%. In a subsequent experiment to compare the scent recognition between the three non-inactivated body fluids, diagnostic sensitivity and specificity were 95% and 98% for urine, 91% and 94% for sweat, 82%, and 96% for saliva respectively. ConclusionsThe scent cognitive transfer performance between inactivated and non-inactivated samples as well as between different sample materials indicates that global, specific SARS-CoV-2-associated volatile compounds are released across different body secretions, independently from the patients symptoms. FundingThe project was funded as a special research project of the German Armed Forces. The funding source DZIF-Fasttrack 1.921 provided us with means for biosampling.

animal behavior and cognition↗

bioRxiv2021

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection

The immune system of most SARS-CoV-2 infected individuals limits viral spread to the upper airways without pulmonary involvement. This prevents the development of pneumonic COVID-19. However, the protective immunological responses causative of successful viral containment in the upper airways remain unclear. Here, we combine longitudinal single-cell RNA sequencing, proteomic profiling, multidimensional flow cytometry, RNA-Seq of FACS-sorted leukocyte subsets and multiplex plasma interferon profiling to uncover temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients. We compare host responses in a high-risk patient population infected with SARS-CoV-2 but without pulmonary involvement to patients with COVID-19 pneumonia. Our data reveal a distinct immunological signature of successful viral containment, characterized by an early prominent interferon stimulated gene (ISG) upregulation across immune cell subsets. In addition, reduced cytotoxic potential of Natural Killer (NK) and T cells, as well as a monocyte phenotype with immune-modulatory potential are hallmarks of protective immunity. Temporal resolution across disease trajectories highlights ISG upregulation as particularly prominent early in the disease and confirms increased expression also in comparison to healthy controls. We validate this distinct temporal ISG signature by in-depth RNA-seq of FACS-sorted leukocyte subsets in a large prospective ambulatory SARS-CoV-2 infected cohort confirming early and robust ISG upregulation particularly in monocytes and T cells. In conclusion, our data demonstrate a protective ISG phenotype in patients with successful containment of SARS-CoV-2 infection without progression to COVID-19. This early protective interferon response might be exploited as a therapeutic approach and for disease course prediction.

immunology↗

bioRxiv2020

Integrated scRNA-seq analysis identifies conserved transcriptomic features of mononuclear phagocytes in mouse and human atherosclerosis

RationaleAccumulation of mononuclear phagocytes (monocytes, macrophages and dendritic cells) in the vessel wall is a hallmark of atherosclerosis. Although single-cell RNA-sequencing (scRNA-seq) has shed new light on immune cell transcriptional diversity in atherosclerosis, it is still unknown whether the transcriptional states of mononuclear phagocytes are conserved between mouse and human atherosclerosis. ObjectiveTo integrate and compare macrophage and dendritic cell transcriptomes in mouse and human atherosclerosis. Methods and resultsWe integrated 12 scRNA-seq datasets of immune cells isolated from healthy or atherosclerotic mouse aortas, and scRNA-seq data from 11 patients (n=4 coronary vessels, n=7 carotid endarterectomy specimens) from two independent studies. Integration of mouse data recovered previously described macrophage populations and identified novel subpopulations with discrete transcriptomic signatures within populations of aortic resident (Lyve1), inflammatory (Il1b), as well as foamy (Trem2hi) macrophages. We identified unique transcriptomic features distinguishing aortic intimal resident macrophages from atherosclerosis-associated Trem2hi macrophages. Also, populations of Xcr1+ type 1 classical dendritic cells (cDC1), Cd209a+ cDC2 and mature DCs (Ccr7, Fscn1) were detected. In humans, we uncovered macrophage and dendritic cell populations with gene expression patterns similar to those observed in mice in both vascular beds. In particular, core transcripts of the foamy/Trem2hi signature (TREM2, SPP1, GPNMB, CD9) mapped to a specific population of macrophages in human lesions. Cross-species data integration demonstrated transcriptionally proximal macrophage and dendritic cell populations in mice and humans. ConclusionsWe demonstrate conserved transcriptomics features of macrophages and dendritic cells in atherosclerosis in mice and humans, emphasizing the relevance of mouse models to study mononuclear phagocytes in atherosclerosis.

immunology↗

bioRxiv2020

Genome-scale metabolic modelling when changes in environmental conditions affect biomass composition

Genome-scale metabolic modeling is an important tool in understanding metabolism, by enhancing collation of knowledge, interpretation of data, and prediction of metabolic capabilities. A central assumption in the construction and use of genome-scale models is that the in vivo organism is evolved for optimal growth, where growth is represented by flux through a biomass objective function (BOF). While the specific composition of the BOF is crucial, its formulation is often inherited from similar organisms due to the experimental challenges associated with its proper determination. However, a cells macro-molecular composition is not fixed and it responds to changes in environmental conditions. As a consequence, initiatives for the high-fidelity determination of cellular biomass composition have been launched. Thus, there is a need for a mathematical and computational framework capable of using multiple measurements of cellular biomass composition in different environments. Here, we propose two different computational approaches for directly addressing this challenge: Biomass Trade-off Weighting (BTW) and Higher-dimensional-plane InterPolation (HIP). In lieu of experimental data on biomass composition-variation in response to changing nutrient environment, we assess the properties of BTW and HIP using three hypothetical, yet biologically plausible, BOFs for the Escherichia coli genome-scale metabolic model iML1515. We find that the BTW and HIP formulations have a significant impact on model performance and phenotypes. Furthermore, the BTW method generates larger growth rates in all environments when compared to HIP. Using acetate secretion and the respiratory quotient as proxies for phenotypic changes, we find marked differences between the methods as HIP generates BOFs more similar to a reference BOF than BTW. We conclude that the presented methods constitute a first conceptual step in developing genome-scale metabolic modelling approaches capable of addressing the inherent dependence of cellular biomass composition on nutrient environments. Author summaryChanges in the environment promote changes in an organisms metabolism. To achieve balanced growth states for near-optimal function, cells respond through metabolic rearrangements, which may influence the biosynthesis of metabolic precursors for building a cells molecular constituents. Therefore, it is necessary to take the dependence of biomass composition on environmental conditions into consideration. While measuring the biomass composition for some environments is possible, and should be done, it cannot be completed for all possible environments. In this work, we propose two main approaches, BTW and HIP, for addressing the challenge of estimating biomass composition in response to environmental changes. We evaluate the phenotypic consequences of BTW and HIP by characterizing their effect on growth, secretion potential, respiratory efficiency, and gene essentiality of a cell. Our work constitutes a first conceptual step in accounting for the influence of growth conditions on biomass composition, and in turn the biomass compositions effect on metabolic phenotypic traits, within constraint-based modelling. As such, we believe it will improve the relevance of constraint-based methods in metabolic engineering and drug discovery, since the biosynthetic potential of microbes for generating industrially relevant products or drugs often is closely linked to their biomass composition.

systems biology↗

bioRxiv2020

Genome-scale reconstructions to assess metabolic phylogeny and organism clustering

Approaches for systematizing information of relatedness between organisms is important in biology. Phylogenetic analyses based on sets of highly conserved genes are currently the basis for the Tree of Life. Genome-scale metabolic reconstructions contain high-quality information regarding the metabolic capability of an organism and are typically restricted to metabolically active enzyme-encoding genes. While there are many tools available to generate draft reconstructions, expert-level knowledge is still required to generate and manually curate high-quality genome-scale metabolic models and to fill gaps in their reaction networks. Here, we use the tool AutoKEGGRec to construct 975 genome-scale metabolic draft reconstructions encoded in the KEGG database without further curation. The organisms are selected across all three domains, and their metabolic networks serve as basis for generating phylogenetic trees. We find that using all reactions encoded, these metabolism-based comparisons give rise to a phylogenetic tree with close similarity to the Tree of Life. While this tree is quite robust to reasonable levels of noise in the metabolic reaction content of an organism, we find a significant heterogeneity in how much noise an organism may tolerate before it is incorrectly placed in the tree. Furthermore, by using the protein sequences for particular metabolic functions and pathway sets, such as central carbon-, nitrogen-, and sulfur-metabolism, as basis for the organism comparisons, we generate highly specific phylogenetic trees. We believe the generation of phylogenetic trees based on metabolic reaction content, in particular when focused on specific functions and pathways, could aid the identification of functionally important metabolic enzymes and be of value for genome-scale metabolic modellers and enzyme-engineers.

bioinformatics↗

bioRxiv2020

Multi-species ELISA for the detection of antibodies against SARS-CoV-2 in animals

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with millions of infected humans and hundreds of thousands of fatalities. As the novel disease - referred to as COVID-19 - unfolded, occasional anthropozoonotic infections of animals by owners or caretakers were reported in dogs, felid species and farmed mink. Further species were shown to be susceptible under experimental conditions. The extent of natural infections of animals, however, is still largely unknown. Serological methods will be useful tools for tracing SARS-CoV-2 infections in animals once test systems are validated for use in different species. Here, we developed an indirect multi-species ELISA based on the receptor-binding domain (RBD) of SARS-CoV-2. The newly established ELISA was validated using 59 sera of infected or vaccinated animals including ferrets, raccoon dogs, hamsters, rabbits, chickens, cattle and a cat, and a total of 220 antibody-negative sera of the same animal species. Overall, a diagnostic specificity of 100.0% and sensitivity of 98.31% was achieved, and the functionality with every species included in this study could be demonstrated. Hence, a versatile and reliable ELISA protocol was established that enables high-throughput antibody detection in a broad range of animal species, which may be used for outbreak investigations, to assess the seroprevalence in susceptible species or to screen for reservoir or intermediate hosts.

microbiology↗

bioRxiv2020

The impact of genetic background and gender on the increase in mitotic index in response to mating of Drosophila melanogaster

The replenishment of specialized cells depends on the activity of stem cells. Recent advances in stem cell research have shown that the germline stem cells (GSCs) in Drosophila melanogaster can increase their mitotic activity in response to mating. Here, we show that this ability to respond to mating is eliminated if the males are mutant for the ABC transporter, White, the genetic background for a plethora of fly lines. Furthermore, we were not able to reproduce previous findings that female flies increase their GSC numbers and mitotic activity upon mating. Our findings underline the importance of careful experimental design and control specimen.

developmental biology↗

bioRxiv2019

Tertiary lymphoid tissue develops during normal aging in mice and humans

Aging has multifaceted effects on the immune system in the context of systemic responses to specific vaccines and pathogens, but how aging affects tissue-specific immunity is not well-defined. Chronic bladder inflammation is highly prevalent in older women, but mechanisms by which aging promotes these pathologies remain unknown. Here we report distinct, age-associated changes to the immune compartment in the otherwise normal female (but not in male) mouse urinary bladder and parallel changes in older women with chronic bladder inflammation. In aged mice, the bladder epithelium became more permeable, and the homeostatic immune landscape shifted from a limited, innate immune-predominant surveillance to an inflammatory, adaptive immune-predominant environment. Strikingly, lymphoid cells were organized into tertiary lymphoid tissues, hereafter named bladder tertiary lymphoid tissue (bTLT). Analogous bTLTs were found in older women, many of whom had a history of recurrent urinary tract infection (UTI). Aged mice responded poorly to experimental UTI, experiencing spontaneous recurrences at higher rates than young mice. However, bTLT formation was dependent on aging and independent of infection. Furthermore, bTLTs in aged mice played a role in de novo antibody responses and urinary IgA production by recruitment of naive B cells that form germinal centers and mature into IgA-secreting plasma cells. Finally, TNF was a key driver of bTLT formation, as aged TNF-/- mice lacked bTLTs. Both aged TNF-/- and wild type mice exhibited increased bladder permeability, suggesting that epithelial dysfunction may be an upstream mediator of chronic, age-associated bladder inflammation. Thus, bTLTs arise as a function of age and may underlie chronic, age-associated bladder inflammation. Our model establishes a platform for further investigation of age-association tissue inflammation and translation to new treatment strategies.\n\nOne Sentence SummaryMice develop bladder tertiary lymphoid tissue (bTLT) during aging that is dependent on TNF and independent of urinary tract infection.

immunology↗

bioRxiv2019

Notch signaling is required for survival of the germline stem cell lineage in testes of Drosophila melanogaster

In all metazoan species, sperm is produced from germline stem cells. These self-renew and produce daughter cells that amplify and differentiate dependent on interactions with somatic support cells. In the male gonad of Drosophila melanogaster, the germline and somatic cyst cells co-differentiate as cysts, an arrangement in which the germline is completely enclosed by cytoplasmic extensions from the cyst cells. Notch is a developmentally relevant receptor in a pathway requiring immediate proximity with the signal sending cell. Here, we show that Notch is expressed in the cyst cells of wild-type testes. Notch becomes activated in the transition zone, an apical area of the testes in which the cyst cells express stage-specific transcription factors and the enclosed germline finalizes transit-amplifying divisions. Reducing the ligand Delta from the germline cells via RNA-Interference or reducing the receptor Notch from the cyst cells via CRISPR resulted in cell death concomitant with loss of germline cells from the transition zone. This shows that Notch signaling is essential for the survival of the germline stem cell lineage.

developmental biology↗

bioRxiv2018

G-Protein signaling increases germline stem cell activity in Drosophila males in response to multiple rounds of mating

Adult stem cells divide to renew the stem cell pool and replenish specialized cells that are lost due to death or usage. However, little is known about the mechanisms regulating how stem cells adjust to a demand for specialized cells. A failure of the stem cells to respond to this demand can have serious consequences, such as tissue loss, or prolonged recovery post injury. Here, we challenge the male germline stem cells (GSCs) of Drosophila melanogaster for the production of specialized cells using mating experiments. We show that repeated mating reduced the sperm pool and accelerated germline stem cell (GSC) divisions. The increase in GSC divisions depended on the activity of the highly conserved G-proteins. Germline expression of RNA-Interference (RNA-i) constructs against G-proteins or a dominant negative G-protein eliminated the increase in GSC divisions in mated males. Consistent with a role for the G-proteins in the regulation of GSC divisions, RNA-i against seven out of 35 G-protein coupled receptors (GPCRs) within the germline cells also eliminated the capability of males to accelerate their GSC divisions in response to mating. Our data show that GSCs are receptive to GPCR stimulus, potentially through a network of interactions among multiple signaling pathways.

developmental biology↗

bioRxiv2018

Alzheimer’s disease risk SNPs show no strong effect on miRNA expression in human lymphoblastoid cell lines

The role of microRNAs (miRNAs) in the pathogenesis of Alzheimers disease (AD) is currently extensively investigated. In this study, we assessed the potential impact of AD genetic risk variants on miRNA expression by performing large-scale bioinformatic data integration. Our analysis was based on genetic variants from three AD genome-wide association studies (GWAS). Association with miRNA expression was tested by expression quantitative trait loci (eQTL) analysis using next-generation miRNA sequencing data generated in lymphoblastoid cell lines (LCL). While, overall, we did not identify a strong effect of AD GWAS variants on miRNA expression in this cell type we highlight two notable outliers, i.e. miR-29c-5p and miR-6840-5p. MiR-29c-5p was recently reported to be involved in the regulation of BACE1 and SORL1 expression. In conclusion, despite two exceptions our large-scale assessment provides only limited support for the hypothesis that AD GWAS variants act as miRNA eQTLs.

genetics↗

bioRxiv2018

TGF-βRII knock-down promotes tumor growth and chemoresistance to gemcitabine of pancreatic cancer cells via phosphorylation of STAT3

Pancreatic adenocarcinoma (PDAC) is one of the most deadly cancers in the western countries because of a lack of early diagnostic markers and efficient therapeutics. At the time of diagnosis, more than 80% of patients have metastasis or locally advanced cancer and are therefore not eligible for surgical resection. Pancreatic cancer cell also harbour a high resistance to chemotherapeutic drugs such as gemcitabine that is one of the main palliative treatment for PDAC.\n\nTGF-{beta} possesses both tumor-suppressive and oncogenic activities in pancreatic cancer. TGF-{beta} signalling pathway plays complex role during carcinogenesis by initially inhibiting epithelial growth and later promoting the progression of advanced tumors and thus emerged as tumor suppressor pathway. TGF-{beta} binds to its receptor TGF-{beta}RII and activates different pathways: canonical pathway involving the Smad proteins and alternative pathways such as MAPKs. Smad4 is mutated in 50-80% of PDAC. Mutations of TGF-{beta}RII also occurs (5-10%). In order to decipher the role of TGF-{beta} in carcinogenesis and chemoresistance, we decided to characterize the knocking down of TGF-{beta}RII that is the first actor of TGF-{beta} signalling. We developed pancreatic cancer cell lines stably invalidated for TGF-{beta}RII and studied the impact on biological properties of pancreatic cancer cells both in vitro and in vivo. We show that TGF-{beta}RII silencing alters tumor growth and migration as well as resistance to. TGF-{beta}RII silencing also leads to S727 STAT3 and S-63 c-Jun phosphorylation, decrease of MRP3 and increase of MRP4 ABC transporter expression and induction of a partial EMT phenotype.\n\nIn the future, the better understanding TGF-{beta} signaling pathways and underlying cellular mechanisms in chemoresistance to gemcitabine may bring new therapeutic tools to clinicians.

cancer biology↗