610 Medizin und Gesundheit
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ResearcherID
- D-1221-2009 (1)
The Escherichia coli effector EspJ blocks Src kinase activity via amidation and ADP ribosylation
(2014)
The hallmark of enteropathogenic Escherichia coli (EPEC) infection is the formation of actin-rich pedestal-like structures, which are generated following phosphorylation of the bacterial effector Tir by cellular Src and Abl family tyrosine kinases. This leads to recruitment of the Nck-WIP-N-WASP complex that triggers Arp2/3-dependent actin polymerization in the host cell. The same phosphorylation-mediated signalling network is also assembled downstream of the Vaccinia virus protein A36 and the phagocytic Fc-gamma receptor FcγRIIa. Here we report that the EPEC type-III secretion system effector EspJ inhibits autophosphorylation of Src and phosphorylation of the Src substrates Tir and FcγRIIa. Consistent with this, EspJ inhibits actin polymerization downstream of EPEC, Vaccinia virus and opsonized red blood cells. We identify EspJ as a unique adenosine diphosphate (ADP) ribosyltransferase that directly inhibits Src kinase by simultaneous amidation and ADP ribosylation of the conserved kinase-domain residue, Src E310, resulting in glutamine-ADP ribose.
Purpose
To achieve a highly balanced comparison of trabecular bypass stenting (IS2, iStent inject) with ab interno trabeculectomy (T, Trabectome) by exact matching.
Methods
Fifty-three IS2 eyes were matched to 3446 T eyes. Patients were matched using exact matching by baseline intraocular pressure (IOP), the number of glaucoma medications, and glaucoma type, and using nearest neighbor matching by age. Individuals without a close match were excluded. All surgeries were combined with phacoemulsification.
Results
A total of 78 eyes (39 in each group) could be matched as exact pairs with a baseline IOP of 18.3 ± 5.1 mmHg and glaucoma medications of 2.7 ± 1.2 in each. IOP in IS2 was reduced to 14.6 ± 4.2 mmHg at 3 months and in T to a minimum of 13.1 ± 3.2 mmHg at 1 month. In IS2, IOP began to rise again at 6 months, eventually exceeding baseline. At 24 months, IOP in IS2 was 18.8 ± 9.0 mmHg and in T 14.2 ± 3.5 mmHg. IS2 had a higher average IOP than T at all postoperative visits (p < 0.05 at 1, 12, 18 months). Glaucoma medications decreased to 2.0 ± 1.5 in IS2 and to 1.5 ± 1.4 in T.
Conclusion
T resulted in a larger and sustained IOP reduction compared with IS2 where a rebound occurred after 6 months to slightly above preoperative values.
The green synthesis of silver nanoparticles (SNPs) using plant extracts is an eco-friendly method. It is a single step and offers several advantages such as time reducing, cost-effective and environmental non-toxic. Silver nanoparticles are a type of Noble metal nanoparticles and it has tremendous applications in the field of diagnostics, therapeutics, antimicrobial activity, anticancer and neurodegenerative diseases. In the present work, the aqueous extracts of aerial parts of Lampranthus coccineus and Malephora lutea F. Aizoaceae were successfully used for the synthesis of silver nanoparticles. The formation of silver nanoparticles was early detected by a color change from pale yellow to reddish-brown color and was further confirmed by transmission electron microscope (TEM), UV–visible spectroscopy, Fourier transform infrared (FTIR) spectroscopy, dynamic light scattering (DLS), X-ray diffraction (XRD), and energy-dispersive X-ray diffraction (EDX). The TEM analysis of showed spherical nanoparticles with a mean size between 12.86 nm and 28.19 nm and the UV- visible spectroscopy showed λ\(_{max}\) of 417 nm, which confirms the presence of nanoparticles. The neuroprotective potential of SNPs was evaluated by assessing the antioxidant and cholinesterase inhibitory activity. Metabolomic profiling was performed on methanolic extracts of L. coccineus and M. lutea and resulted in the identification of 12 compounds, then docking was performed to investigate the possible interaction between the identified compounds and human acetylcholinesterase, butyrylcholinesterase, and glutathione transferase receptor, which are associated with the progress of Alzheimer’s disease. Overall our SNPs highlighted its promising potential in terms of anticholinesterase and antioxidant activity as plant-based anti-Alzheimer drug and against oxidative stress.
To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or noncoding RNAs, are harder to detect. RNA sequencing (RNA-seq) has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-seq data in order to generate high-resolution annotations is challenging, time consuming, and requires numerous steps. We have constructed a powerful and modular tool called ANNOgesic that provides the required analyses and simplifies RNA-seq-based bacterial and archaeal genome annotation. It can integrate data from conventional RNA-seq and differential RNA-seq and predicts and annotates numerous features, including small noncoding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/.
Among the defense strategies developed in microbes over millions of years, the innate adaptive CRISPR-Cas immune systems have spread across most of bacteria and archaea. The flexibility, simplicity, and specificity of CRISPR-Cas systems have laid the foundation for CRISPR-based genetic tools. Yet, the efficient administration of CRISPR-based tools demands rational designs to maximize the on-target efficiency and off-target specificity. Specifically, the selection of guide RNAs (gRNAs), which play a crucial role in the target recognition of CRISPR-Cas systems, is non-trivial. Despite the fact that the emerging machine learning techniques provide a solution to aid in gRNA design with prediction algorithms, design rules for many CRISPR-Cas systems are ill-defined, hindering their broader applications.
CRISPR interference (CRISPRi), an alternative gene silencing technique using a catalytically dead Cas protein to interfere with transcription, is a leading technique in bacteria for functional interrogation, pathway manipulation, and genome-wide screens. Although the application is promising, it also is hindered by under-investigated design rules. Therefore, in this work, I develop a state-of-art predictive machine learning model for guide silencing efficiency in bacteria leveraging the advantages of feature engineering, data integration, interpretable AI, and automated machine learning. I first systematically investigate the influential factors that attribute to the extent of depletion in multiple CRISPRi genome-wide essentiality screens in Escherichia coli and demonstrate the surprising dominant contribution of gene-specific effects, such as gene expression level. These observations allowed me to segregate the confounding gene-specific effects using a mixed-effect random forest (MERF) model to provide a better estimate of guide efficiency, together with the improvement led by integrating multiple screens. The MERF model outperformed existing tools in an independent high-throughput saturating screen. I next interpret the predictive model to extract the design rules for robust gene silencing, such as the preference for cytosine and disfavoring for guanine and thymine within and around the protospacer adjacent motif (PAM) sequence. I further incorporated the MERF model in a web-based tool that is freely accessible at www.ciao.helmholtz-hiri.de.
When comparing the MERF model with existing tools, the performance of the alternative gRNA design tool optimized for CRISPRi in eukaryotes when applied to bacteria was far from satisfying, questioning the robustness of prediction algorithms across organisms. In addition, the CRISPR-Cas systems exhibit diverse mechanisms albeit with some similarities. The captured predictive patterns from one dataset thereby are at risk of poor generalization when applied across organisms and CRISPR-Cas techniques. To fill the gap, the machine learning approach I present here for CRISPRi could serve as a blueprint for the effective development of prediction algorithms for specific organisms or CRISPR-Cas systems of interest. The explicit workflow includes three principle steps: 1) accommodating the feature set for the CRISPR-Cas system or technique; 2) optimizing a machine learning model using automated machine learning; 3) explaining the model using interpretable AI. To illustrate the applicability of the workflow and diversity of results when applied across different bacteria and CRISPR-Cas systems, I have applied this workflow to analyze three distinct CRISPR-Cas genome-wide screens. From the CRISPR base editor essentiality screen in E. coli, I have determined the PAM preference and sequence context in the editing window for efficient editing, such as A at the 2nd position of PAM, A/TT/TG downstream of PAM, and TC at the 4th to 5th position of gRNAs. From the CRISPR-Cas13a screen in E. coli, in addition to the strong correlation with the guide depletion, the target expression level is the strongest predictor in the model, supporting it as a main determinant of the activation of Cas13-induced immunity and better characterizing the CRISPR-Cas13 system. From the CRISPR-Cas12a screen in Klebsiella pneumoniae, I have extracted the design rules for robust antimicrobial activity across K. pneumoniae strains and provided a predictive algorithm for gRNA design, facilitating CRISPR-Cas12a as an alternative technique to tackle antibiotic resistance.
Overall, this thesis presents an accurate prediction algorithm for CRISPRi guide efficiency in bacteria, providing insights into the determinants of efficient silencing and guide designs. The systematic exploration has led to a robust machine learning approach for effective model development in other bacteria and CRISPR-Cas systems. Applying the approach in the analysis of independent CRISPR-Cas screens not only sheds light on the design rules but also the mechanisms of the CRISPR-Cas systems. Together, I demonstrate that applied machine learning paves the way to a deeper understanding and a broader application of CRISPR-Cas systems.
Invasive fungal infections (IFIs) are difficult to diagnose and to treat and, despite several available antifungal drugs, cause high mortality rates. In the past decades, the incidence of IFIs has continuously increased. More recently, SARS-CoV-2-associated lethal IFIs have been reported worldwide in critically ill patients. Combating IFIs requires a more profound understanding of fungal pathogenicity to facilitate the development of novel antifungal strategies. Animal models are indispensable for studying fungal infections and to develop new antifungals. However, using mammalian animal models faces various hurdles including ethical issues and high costs, which makes large-scale infection experiments extremely challenging. To overcome these limitations, we optimized an invertebrate model and introduced a simple calcofluor white (CW) staining protocol to macroscopically and microscopically monitor disease progression in silkworms (Bombyx mori) infected with the human pathogenic filamentous fungi Aspergillus fumigatus and Lichtheimia corymbifera. This advanced silkworm A. fumigatus infection model could validate knockout mutants with either attenuated, strongly attenuated or unchanged virulence. Finally, CW staining allowed us to efficiently visualize antifungal treatment outcomes in infected silkworms. Conclusively, we here present a powerful animal model combined with a straightforward staining protocol to expedite large-scale in vivo research of fungal pathogenicity and to investigate novel antifungal candidates.
Regulation of effector T cells is an important mechanism to control organ-specific inflammation. Thereby regulatory T cells (Treg cells) are essential for maintaining peripheral immune tolerance and for establishing parenchyma immune homeostasis. A novel population of natural human Treg characterized by the constitutive expression of the immune-tolerogenic human HLA-G molecule has been identified. In the first part of the study, we elucidated the mechanism(s) by which CD4+ HLA-Gpos Treg modulates their cellular targets namely autologous HLA-G negative responder T cells (HLAGneg Tresp). Using a suppression system free of antigen-presenting cells (APC), we demonstrate a T-T cell interaction resulting in suppression of HLA-Gneg Tresp. We could also show that this suppression was independent of cell-cell contact. Importantly, stimulus of T cell receptor (TCR) on HLA-Gpos Treg facilitated their suppressive capacity. We also observed that removal of HLA-Gpos Treg from the established co-cultures could restore the ability of HLA-Gneg Tresp to proliferate upon TCR re-stimulation, indicating that the suppression was reversible. Further, HLA-Gpos Treg–mediated suppression was critically depending on the secretion of IL-10 but not TGF-β. Taken together, this part of the work provides an in-depth characterization of the mechanisms of how HLA-Gpos Treg suppresses T responder cells in direct T-T interactions. Understanding the suppressive mechanism used by HLA-Gpos Treg may help to develop therapeutic strategies to modulate regulatory arms of T-cell suppression. In the second part of this study, the potential role of HLA-Gpos Treg in the pathophysiological process of Multiple Sclerosis (MS), a prototypic autoimmune inflammatory central nervous system (CNS), has been investigated. We found that HLA-Gpos Treg are enriched in the cerebrospinal fluid (CSF) from MS patients, but not in non-inflammatory controls. CSFderived HLA-Gpos Treg showed predominance of central memory (CD45RA-CD27+) phenotype, exhibited markers of activation (ICOS), and had significantly higher expression of the inflammatory chemokine receptor CCR5. Importantly, these cells demonstrated as potent suppressors to autologous CD4+ T-cell proliferation. Using an in vitro model of human blood brain barrier, we showed that HLA-Gpos Treg have a strong propensity to migrate, which could be facilitated by MIP1α and RANTES (ligands of CCR5) but not MIP3β (a ligand of CCR7). The HLA-Gpos Treg migration triggered by chemokines was also associated with a gain of suppressive capacity upon cellular transmigration. In contrast to CD4+CD25+ naturally occurring FoxP3-expressing Treg, HLA-Gpos Treg from patients with MS did not exhibit impaired function, suggesting that HLA-Gpos Treg are selectively recruited to the sites of CNS inflammation in an effort to combat destructive inflammation during MS. Our results contribute to the understanding of the role and function of HLA-Gpos Treg and provide an important example of “beneficial” T-cell inflammation in CNS autoimmunity- interesting both from a patho/-physiological and a therapeutically point of view.
Aging is known to be a risk factor for structural abnormalities and functional decline in the nervous system. Characterizing age-related changes is important to identify putative pathways to overcome deleterious effects and improve life quality for the elderly. In this study, the peripheral nervous system of 24-month-old aged C57BL/6 mice has been investigated and compared to 12-month-old adult mice. Aged mice showed pathological alterations in their peripheral nerves similar to nerve biopsies from elderly human individuals, with nerve fibers showing demyelination and axonal damage. Such changes were lacking in nerves of adult 12-month-old mice and adult, non-aged humans. Moreover, neuromuscular junctions of 24-month-old mice showed increased denervation compared to adult mice. These alterations were accompanied by elevated numbers of macrophages in the peripheral nerves of aged mice. The neuroinflammatory conditions were associated with impaired myelin integrity and with a decline of nerve conduction properties and muscle strength in aged mice.
To determine the pathological impact of macrophages in the aging mice, macrophage depletion was performed in mice by oral administration of CSF-1R specific kinase (c-FMS) inhibitor PLX5622 (300 mg/kg body weight), which reduced the number of macrophages in the peripheral nerves by 70%. The treated mice showed attenuated demyelination, less muscle denervation and preserved muscle strength. This indicates that macrophage-driven inflammation in the peripheral nerves is partially responsible for the age-related neuropathy in mice.
Based on previous observations that systemic inflammation can accelerate disease progression in mouse models of neurodegenerative diseases, it was hypothesized that systemic inflammation can exacerbate the peripheral neuropathy found in aged mice. To investigate this hypothesis, aged C57BL/6 mice were intraperitoneally injected with a single dose of lipopolysaccharide (LPS; 500 μg/kg body weight) to induce systemic inflammation by mimicking bacterial infection, mostly via activation of Toll-like receptors (TLRs). Altered endoneurial macrophage activation, highlighted by Trem2 downregulation, was found in LPS injected aged mice one month after injection. This was accompanied by a so far rarely observed form of axonal perturbation, i.e., the occurrence of “dark axons” characterized by a damaged cytoskeleton and an increased overall electron density of the axoplasm. At the same time, however, LPS injection reduced demyelination and muscle denervation in aged mice. Interestingly, TREM2 deficiency in aged mice led to similar changes to LPS injection. This suggests that LPS injection likely mitigates aging-related demyelination and muscle denervation via Trem2 downregulation.
Taken together, this study reveals the role of macrophage-driven inflammation as a pathogenic mediator in age-related peripheral neuropathy, and that targeting macrophages might be an option to mitigate peripheral neuropathies in aging individuals. Furthermore, this study shows that systemic inflammation may be an ambivalent modifier of age-related nerve damage, leading to a distinct type of axonal perturbation, but in addition to functionally counteracting, dampened demyelination and muscle denervation. Translationally, it is plausible to assume that tipping the balance of macrophage polarization to one direction or the other may determine the functional outcome in the aging peripheral nervous system of the elderly.
Functional versus morphological assessment of vascular age in patients with coronary heart disease
(2021)
Communicating cardiovascular risk based on individual vascular age (VA) is a well acknowledged concept in patient education and disease prevention. VA may be derived functionally, e.g. by measurement of pulse wave velocity (PWV), or morphologically, e.g. by assessment of carotid intima-media thickness (cIMT). The purpose of this study was to investigate whether both approaches produce similar results. Within the context of the German subset of the EUROASPIRE IV survey, 501 patients with coronary heart disease underwent (a) oscillometric PWV measurement at the aortic, carotid-femoral and brachial-ankle site (PWVao, PWVcf, PWVba) and derivation of the aortic augmentation index (AIao); (b) bilateral cIMT assessment by high-resolution ultrasound at three sites (common, bulb, internal). Respective VA was calculated using published equations. According to VA derived from PWV, most patients exhibited values below chronological age indicating a counterintuitive healthier-than-anticipated vascular status: for VA(PWVao) in 68% of patients; for VA\(_{AIao}\) in 52% of patients. By contrast, VA derived from cIMT delivered opposite results: e.g. according to VA\(_{total-cIMT}\) accelerated vascular aging in 75% of patients. To strengthen the concept of VA, further efforts are needed to better standardise the current approaches to estimate VA and, thereby, to improve comparability and clinical utility.
Purpose
Growing evidence implies that transition to parenthood triggers symptoms of mental burden not only in women but likewise in men, especially in high-risk pregnancies. This is the first study that examined and compared the prevalence rates of depression, anxiety, and somatic symptom burden of expectant fathers who face different risk situations during pregnancy.
Methods
Prevalence rates of paternal depression (Edinburgh postnatal depression scale), anxiety (generalized anxiety disorder seven), and somatic symptom burden (somatic symptom scale eight) were examined in two risk samples and one control group in the third trimester of their partners’ pregnancy: risk sample I (n = 41) consist of expectant fathers whose partners were prenatally hospitalized due to medical complications; risk sample II (n = 52) are fathers whose partners were prenatally mentally distressed; and control group (n = 70) are those non-risk pregnancies.
Results
On a purely descriptive level, the data display a trend of higher symptom burden of depression, anxiety, and somatic symptoms in the two risk samples, indicating that expectant fathers, whose pregnant partners were hospitalized or suffered prenatal depression, were more prenatally distressed. Exploratory testing of group differences revealed an almost three times higher prevalence rate of anxiety in fathers whose partner was hospitalized (12.2%) compared to those non-risks (4.3%).
Conclusion
Results underline the need for screening implementations for paternal prenatal psychological distress, as well as specific prevention and treatment programs, especially for fathers in risk situations, such as their pregnant partners’ prenatal hospitalization.
The study was registered with the German clinical trials register (DRKS00020131) on 2019/12/09.