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Simple Summary
Urokinase-type plasminogen activator (urokinase, uPA) is a widely discussed biomarker for cancer prognosis and diagnosis. The gold standard for the determination of protein biomarkers in physiological samples is the enzyme-linked immunosorbent assay (ELISA). Here, antibodies are used to detect the specific protein.
In our study, recently published urokinase aptamers were tested for their use in a sandwich assay format as alternative specific recognition elements. Different aptamer combinations were used for the detection of uPA in a sandwich-assay format and a combination of aptamers and antibodies additionally allowed the differentiation of human high and low molecular weight- (HMW- and LMW-) uPA. Hence, uPA aptamers offer a valuable alternative as specific recognition elements for analytical purposes. Since aptamers are easy to synthesize and modify, they can be used as a cost-effective alternative in sandwich assay formats for the detection of uPA in physiological samples.
Abstract
Urokinase-type plasminogen activator (urokinase, uPA) is a frequently discussed biomarker for prognosis, diagnosis, and recurrence of cancer.
In a previous study, we developed ssDNA aptamers that bind to different forms of human urokinase, which are therefore assumed to have different binding regions.
In this study, we demonstrate the development of aptamer-based sandwich assays that use different combinations of these aptamers to detect high molecular weight- (HMW-) uPA in a micro titer plate format.
By combining aptamers and antibodies, it was possible to distinguish between HMW-uPA and low molecular weight- (LMW-) uPA.
For the best performing aptamer combination, we calculated the limit of detection (LOD) and limit of quantification (LOQ) in spiked buffer and urine samples with an LOD up to 50 ng/mL and 138 ng/mL, respectively.
To show the specificity and sequence dependence of the reporter aptamer uPAapt-02-FR, we have identified key nucleotides within the sequence that are important for specific folding and binding to uPA using a fluorescent dye-linked aptamer assay (FLAA). Since uPA is a much-discussed marker for prognosis and diagnosis in various types of cancers, these aptamers and their use in a micro titer plate assay format represent a novel, promising tool for the detection of uPA and for possible diagnostic applications.
Background:
The current range of disease-modifying treatments (DMTs) for relapsing-remitting multiple sclerosis (RRMS) has placed more importance on the accurate monitoring of disease progression for timely and appropriate treatment decisions. With a rising number of measurements for disease progression, it is currently unclear how well these measurements or combinations of them can monitor more mildly affected RRMS patients.
Objectives:
To investigate several composite measures for monitoring disease activity and their potential relation to the biomarker neurofilament light chain (NfL) in a clearly defined early RRMS patient cohort with a milder disease course.
Methods:
From a total of 301 RRMS patients, a subset of 46 patients being treated with a continuous first-line therapy was analyzed for loss of no evidence of disease activity (lo-NEDA-3) status, relapse-associated worsening (RAW) and progression independent of relapse activity (PIRA), up to seven years after treatment initialization.
Kaplan-Meier estimates were used for time-to-event analysis. Additionally, a Cox regression model was used to analyze the effect of NIL levels on outcome measures in this cohort.
Results:
In this mildly affected cohort, both lo-NEDA-3 and PIRA frequently occurred over a median observational period of 67.2 months and were observed in 39 (84.8%) and 23 (50.0%) patients, respectively.
Additionally, 12 out of 26 PIRA manifestations (46.2%) were observed without a corresponding lo-NEDA-3 status. Jointly, either PIRA or lo-NEDA-3 showed disease activity in all patients followed-up for at least the median duration (67.2 months). NfL values demonstrated an association with the occurrence of relapses and RAW.
Conclusion:
The complementary use of different disease progression measures helps mirror ongoing disease activity in mildly affected early RRMS patients being treated with continuous first-line therapy.
Urokinase-type plasminogen activator is widely discussed as a marker for cancer prognosis and diagnosis and as a target for cancer therapies. Together with its receptor, uPA plays an important role in tumorigenesis, tumor progression and metastasis. In the present study, systematic evolution of ligands by exponential enrichment (SELEX) was used to select single-stranded DNA aptamers targeting different forms of human uPA. Selected aptamers allowed the distinction between HMW-uPA and LMW-uPA, and therefore, presumably, have different binding regions. Here, uPAapt-02-FR showed highly affine binding with a K-D of 0.7 nM for HMW-uPA and 21 nM for LMW-uPA and was also able to bind to pro-uPA with a K-D of 14 nM. Furthermore, no cross-reactivity to mouse uPA or tissue-type plasminogen activator (tPA) was measured, demonstrating high specificity. Suppression of the catalytic activity of uPA and inhibition of uPAR-binding could be demonstrated through binding with different aptamers and several of their truncated variants. Since RNA aptamers are already known to inhibit uPA-uPAR binding and other pathological functions of the uPA system, these aptamers represent a novel, promising tool not only for detection of uPA but also for interfering with the pathological functions of the uPA system by additionally inhibiting uPA activity.
The Hartousov mofette system is a natural CO2 degassing site in the central Cheb Basin (Eger Rift, Central Europe). In early 2016 a 108 m deep core was obtained from this system to investigate the impact of ascending mantle-derived CO2 on indigenous deep microbial communities and their surrounding life habitat. During drilling, a CO2 blow out occurred at a depth of 78.5 meter below surface (mbs) suggesting a CO2 reservoir associated with a deep low-permeable CO2-saturated saline aquifer at the transition from Early Miocene terrestrial to lacustrine sediments. Past microbial communities were investigated by hopanoids and glycerol dialkyl glycerol tetraethers (GDGTs) reflecting the environmental conditions during the time of deposition rather than showing a signal of the current deep biosphere. The composition and distribution of the deep microbial community potentially stimulated by the upward migration of CO2 starting during Mid Pleistocene time was investigated by intact polar lipids (IPLs), quantitative polymerase chain reaction (qPCR), and deoxyribonucleic acid (DNA) analysis. The deep biosphere is characterized by microorganisms that are linked to the distribution and migration of the ascending CO2-saturated groundwater and the availability of organic matter instead of being linked to single lithological units of the investigated rock profile. Our findings revealed high relative abundances of common soil and water bacteria, in particular the facultative, anaerobic and potential iron-oxidizing Acidovorax and other members of the family Comamonadaceae across the whole recovered core. The results also highlighted the frequent detection of the putative sulfate-oxidizing and CO2-fixating genus Sulfuricurvum at certain depths. A set of new IPLs are suggested to be indicative for microorganisms associated to CO2 accumulation in the mofette system.
Extra-cellular matrix (ECM) components are important and their stabilization is significant in maintaining normal healthy joint environment. In osteoarthritis (OA), ECM components are altered and indicate disease progression. The joint ECM is composed of proteoglycans (aggrecan, perlecan,inter α-trypsin inhibitor), glycoproteins (fibronectin, lubricin, COMP) and collagen types (most abundantly collagen type II) which represent structural and functional transformation during disease advancement. ECM investigation revealed significant biomarkers of OA that could be used as a diagnostic and therapeutic tool in different canine orthopedic diseases. This review deliberates our current findings of how the components of ECM change at the molecular level during disease progression in canine OA.
Parkinson's disease (PD) shows high heterogeneity with regard to the underlying molecular pathogenesis involving multiple pathways and mechanisms. Diagnosis is still challenging and rests entirely on clinical features. Thus, there is an urgent need for robust diagnostic biofluid markers. Untargeted metabolomics allows establishing low-molecular compound biomarkers in a wide range of complex diseases by the measurement of various molecular classes in biofluids such as blood plasma, serum, and cerebrospinal fluid (CSF). Here, we applied untargeted high-resolution mass spectrometry to determine plasma and CSF metabolite profiles. We semiquantitatively determined small-molecule levels (<= 1.5 kDa) in the plasma and CSF from early PD patients (disease duration 0-4 years; n = 80 and 40, respectively), and sex-and age-matched controls (n = 76 and 38, respectively). We performed statistical analyses utilizing partial least square and random forest analysis with a 70/30 training and testing split approach, leading to the identification of 20 promising plasma and 14 CSF metabolites. The semetabolites differentiated the test set with an AUC of 0.8 (plasma) and 0.9 (CSF). Characteristics of the metabolites indicate perturbations in the glycerophospholipid, sphingolipid, and amino acid metabolism in PD, which underscores the high power of metabolomic approaches. Further studies will enable to develop a potential metabolite-based biomarker panel specific for PD
Anthropogenic climate change alters the hydrological cycle. While certain areas experience more intense precipitation events, others will experience droughts and increased evaporation, affecting water storage in long-term reservoirs, groundwater, snow, and glaciers. High elevation environments are especially vulnerable to climate change, which will impact the water supply for people living downstream. The Himalaya has been identified as a particularly vulnerable system, with nearly one billion people depending on the runoff in this system as their main water resource. As such, a more refined understanding of spatial and temporal changes in the water cycle in high altitude systems is essential to assess variations in water budgets under different climate change scenarios.
However, not only anthropogenic influences have an impact on the hydrological cycle, but changes to the hydrological cycle can occur over geological timescales, which are connected to the interplay between orogenic uplift and climate change. However, their temporal evolution and causes are often difficult to constrain. Using proxies that reflect hydrological changes with an increase in elevation, we can unravel the history of orogenic uplift in mountain ranges and its effect on the climate.
In this thesis, stable isotope ratios (expressed as δ2H and δ18O values) of meteoric waters and organic material are combined as tracers of atmospheric and hydrologic processes with remote sensing products to better understand water sources in the Himalayas. In addition, the record of modern climatological conditions based on the compound specific stable isotopes of leaf waxes (δ2Hwax) and brGDGTs (branched Glycerol dialkyl glycerol tetraethers) in modern soils in four Himalayan river catchments was assessed as proxies of the paleoclimate and (paleo-) elevation. Ultimately, hydrological variations over geological timescales were examined using δ13C and δ18O values of soil carbonates and bulk organic matter originating from sedimentological sections from the pre-Siwalik and Siwalik groups to track the response of vegetation and monsoon intensity and seasonality on a timescale of 20 Myr.
I find that Rayleigh distillation, with an ISM moisture source, mainly controls the isotopic composition of surface waters in the studied Himalayan catchments. An increase in d-excess in the spring, verified by remote sensing data products, shows the significant impact of runoff from snow-covered and glaciated areas on the surface water isotopic values in the timeseries.
In addition, I show that biomarker records such as brGDGTs and δ2Hwax have the potential to record (paleo-) elevation by yielding a significant correlation with the temperature and surface water δ2H values, respectively, as well as with elevation. Comparing the elevation inferred from both brGDGT and δ2Hwax, large differences were found in arid sections of the elevation transects due to an additional effect of evapotranspiration on δ2Hwax. A combined study of these proxies can improve paleoelevation estimates and provide recommendations based on the results found in this study.
Ultimately, I infer that the expansion of C4 vegetation between 20 and 1 Myr was not solely dependent on atmospheric pCO2, but also on regional changes in aridity and seasonality from to the stable isotopic signature of the two sedimentary sections in the Himalaya (east and west).
This thesis shows that the stable isotope chemistry of surface waters can be applied as a tool to monitor the changing Himalayan water budget under projected increasing temperatures. Minimizing the uncertainties associated with the paleo-elevation reconstructions were assessed by the combination of organic proxies (δ2Hwax and brGDGTs) in Himalayan soil. Stable isotope ratios in bulk soil and soil carbonates showed the evolution of vegetation influenced by the monsoon during the late Miocene, proving that these proxies can be used to record monsoon intensity, seasonality, and the response of vegetation. In conclusion, the use of organic proxies and stable isotope chemistry in the Himalayas has proven to successfully record changes in climate with increasing elevation. The combination of δ2Hwax and brGDGTs as a new proxy provides a more refined understanding of (paleo-)elevation and the influence of climate.
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.
Femtosecond-Pulsed laser written and etched fiber bragg gratings for fiber-optical biosensing
(2018)
We present the development of a label-free, highly sensitive fiber-optical biosensor for online detection and quantification of biomolecules. Here, the advantages of etched fiber Bragg gratings (eFBG) were used, since they induce a narrowband Bragg wavelength peak in the reflection operation mode. The gratings were fabricated point-by-point via a nonlinear absorption process of a highly focused femtosecond-pulsed laser, without the need of prior coating removal or specific fiber doping. The sensitivity of the Bragg wavelength peak to the surrounding refractive index (SRI), as needed for biochemical sensing, was realized by fiber cladding removal using hydrofluoric acid etching. For evaluation of biosensing capabilities, eFBG fibers were biofunctionalized with a single-stranded DNA aptamer specific for binding the C-reactive protein (CRP). Thus, the CRP-sensitive eFBG fiber-optical biosensor showed a very low limit of detection of 0.82 pg/L, with a dynamic range of CRP detection from approximately 0.8 pg/L to 1.2 mu g/L. The biosensor showed a high specificity to CRP even in the presence of interfering substances. These results suggest that the proposed biosensor is capable for quantification of CRP from trace amounts of clinical samples. In addition, the adaption of this eFBG fiber-optical biosensor for detection of other relevant analytes can be easily realized.
Zinc is an essential trace element, making it crucial to have a reliable biomarker for evaluating an individual’s zinc status. The total serum zinc concentration, which is presently the most commonly used biomarker, is not ideal for this purpose, but a superior alternative is still missing. The free zinc concentration, which describes the fraction of zinc that is only loosely bound and easily exchangeable, has been proposed for this purpose, as it reflects the highly bioavailable part of serum zinc. This report presents a fluorescence-based method for determining the free zinc concentration in human serum samples, using the fluorescent probe Zinpyr-1. The assay has been applied on 154 commercially obtained human serum samples. Measured free zinc concentrations ranged from 0.09 to 0.42 nM with a mean of 0.22 ± 0.05 nM. It did not correlate with age or the total serum concentrations of zinc, manganese, iron or selenium. A negative correlation between the concentration of free zinc and total copper has been seen for sera from females. In addition, the free zinc concentration in sera from females (0.21 ± 0.05 nM) was significantly lower than in males (0.23 ± 0.06 nM). The assay uses a sample volume of less than 10 µL, is rapid and cost-effective and allows us to address questions regarding factors influencing the free serum zinc concentration, its connection with the body’s zinc status, and its suitability as a future biomarker for an individual’s zinc status.
Zinc is an essential trace element, making it crucial to have a reliable biomarker for evaluating an individual’s zinc status. The total serum zinc concentration, which is presently the most commonly used biomarker, is not ideal for this purpose, but a superior alternative is still missing. The free zinc concentration, which describes the fraction of zinc that is only loosely bound and easily exchangeable, has been proposed for this purpose, as it reflects the highly bioavailable part of serum zinc. This report presents a fluorescence-based method for determining the free zinc concentration in human serum samples, using the fluorescent probe Zinpyr-1. The assay has been applied on 154 commercially obtained human serum samples. Measured free zinc concentrations ranged from 0.09 to 0.42 nM with a mean of 0.22 ± 0.05 nM. It did not correlate with age or the total serum concentrations of zinc, manganese, iron or selenium. A negative correlation between the concentration of free zinc and total copper has been seen for sera from females. In addition, the free zinc concentration in sera from females (0.21 ± 0.05 nM) was significantly lower than in males (0.23 ± 0.06 nM). The assay uses a sample volume of less than 10 µL, is rapid and cost-effective and allows us to address questions regarding factors influencing the free serum zinc concentration, its connection with the body’s zinc status, and its suitability as a future biomarker for an individual’s zinc status.
The transfer of particulate organic carbon from continents to the ocean is an important component of the global carbon cycle. Transfer to and burial of photosynthetically fixed biospheric organic carbon in marine sediments can effectively sequester atmospheric carbon dioxide over geological timescales. The exhumation and erosion of fossil organic carbon contained in sedimentary rocks, i.e. petrogenic carbon, can result in remineralization, releasing carbon to the atmosphere. In contrast, eroded petrogenic organic carbon that gets transferred back to the ocean and reburied does not affect atmospheric carbon content.
Mountain ranges play a key role in this transfer since they can source vast amounts of sediment including particulate organic carbon. Globally, the export of both, biospheric and petrogenic organic carbon has been linked to sediment export. Additionally, short transfer times from mountains to the ocean and high sediment concentrations have been shown to increase the likelihood of organic carbon burial. While the importance of mountain ranges in the organic carbon cycle is now widely recognized, the processes acting within mountain ranges to influence the storage, cycling and mobilization of organic carbon, as well as carbon fluxes from mountain ranges remain poorly constrained.
In this thesis, I employ different methods to assess the nature and fate of particulate organic carbon in mountain belts, ranging from the molecular to regional landscape scale. These studies are located along the Trans-Himalayan Kali Gandaki River in Central Nepal. This river traverses all major geological and climatic zones of the Himalaya, from the dry northern Tibetan plateau to the high-relief, monsoon dominated steep High Himalaya and the lower relief and abundant vegetation of the Lesser Himalayan region.
First, I document how biospheric organic matter has accumulated during the Holocene in the headwaters of the Kali Gandaki River valley, by combining compound specific isotope measurements with different dating methods and grain size data, and investigate the stability of this organic carbon reservoir on millennial timescales. I show, that around 1.6 ka an eco-geomorphic tipping point occurred leading to a destabilization of the landscape resulting in today’s high erosion rates and the excavation of the aged organic carbon reservoir. This study highlights the climatic and geomorphic controls on biospheric organic carbon storage and release from mountain ranges.
Second, I systematically investigate the spatial variation of particulate organic carbon fluxes across the Himalaya along the Kali Gandaki River, using bulk stable and radioactive isotopes combined with a new Bayesian modeling approach. The detailed dataset allows the distinction of aged and modern biospheric organic carbon as well as petrogenic organic carbon across the Himalayan mountain range and the investigation of the role of climatic and geomorphic factors in their riverine export. The data suggest a decoupling of the particulate organic carbon from the sediment yield along the Kali Gandaki River, partially driven by climatic and geomorphic processes. In contrast to the suspended sediment, a large part of the particulate organic carbon exported by the river originates from the Tibetan part of the catchment and is dominated by petrogenic organic carbon derived from Jurassic shales with only minor contributions of modern and aged biospheric organic carbon. These findings emphasize the importance of organic carbon source distribution and erosion mechanisms in determining the organic carbon export from mountain ranges.
In a third step, I explore the potential of ultra-high resolution mass spectrometry for particulate organic carbon transport studies. I have generated a novel and unprecedented high-resolution molecular dataset, which contains up to 103 molecular formulas of the lipid fraction of particulate organic matter for modern and aged biospheric carbon, petrogenic organic carbon and river sediments. First, I test if this dataset can be used to better resolve different organic carbon sources and to identify new geochemical tracers. Using multivariate statistics, I identify up to 10² characteristic molecular formulas for the major organic carbon sources in the upper part of the Kali Gandaki catchment, and trace their transfer from the surrounding landscape into the river sediment. Second, I test the potential of the molecular dataset to trace molecular transformations along source-to-sink pathways. I identify changes in molecular metrics derived from the dataset, which are characteristic of transformation processes during incorporation of litter into soil, the aging of soil material, and the mobilization of the organic carbon into the river. These two studies demonstrate that high-resolution molecular datasets open a promising analytical window on particulate organic carbon and can provide novel insights into the composition, sourcing and transformation of riverine particulate organic carbon.
Collectively, these studies advance our understanding of the processes contributing to the storage and mobilization of organic carbon in the Central Himalaya, the mountain belt that dominates global erosional fluxes. They do so by identifying the major sources of particulate organic carbon to the Trans-Himalayan Kali Gandaki River, by elucidating their sensitivity to climate and geomorphic processes, and by identifying some of the transformations of this material on the molecular scale. As a result, the thesis demonstrates that the amount and composition of organic carbon routed from mountain belts is a function of the dynamic interactions of geologic, biologic, geomorphic and climatic processes within the mountain belt. This understanding will ultimately help in answering whether the build-up and erosion of mountain ranges over geological time represents a net carbon source or sink to the atmosphere. Beyond this, the thesis contributes to our technical ability to characterize organic matter and attribute it to sources by scoping the potential of high-end molecular analysis.
The Central Asian Pamir Mountains (Pamirs) are a high-altitude region sensitive to climatic change, with only few paleoclimatic records available. To examine the glacial-interglacial hydrological changes in the region, we analyzed the geochemical parameters of a 31-kyr record from Lake Karakul and performed a set of experiments with climate models to interpret the results. delta D values of terrestrial biomarkers showed insolation-driven trends reflecting major shifts of water vapor sources. For aquatic biomarkers, positive delta D shifts driven by changes in precipitation seasonality were observed at ca. 31-30, 28-26, and 17-14 kyr BP. Multiproxy paleoecological data and modelling results suggest that increased water availability, induced by decreased summer evaporation, triggered higher lake levels during those episodes, possibly synchronous to northern hemispheric rapid climate events. We conclude that seasonal changes in precipitation-evaporation balance significantly influenced the hydrological state of a large waterbody such as Lake Karakul, while annual precipitation amount and inflows remained fairly constant.
Background
High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods.
Methods
We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort.
Results
We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis.
Conclusions
We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.
Frailty and sarcopenia share some underlying characteristics like loss of muscle mass, low muscle strength, and low physical performance. Imaging parameters and functional examinations mainly assess frailty and sarcopenia criteria; however, these measures can have limitations in clinical settings. Therefore, finding suitable biomarkers that reflect a catabolic muscle state e.g. an elevated muscle protein turnover as suggested in frailty, are becoming more relevant concerning frailty diagnosis and risk assessment.
3-Methylhistidine (3-MH) and its ratios 3-MH-to-creatinine (3-MH/Crea) and 3 MH-to-estimated glomerular filtration rate (3-MH/eGFR) are under discussion as possible biomarkers for muscle protein turnover and might support the diagnosis of frailty. However, there is some skepticism about the reliability of 3-MH measures since confounders such as meat and fish intake might influence 3-MH plasma concentrations. Therefore, the influence of dietary habits and an intervention with white meat on plasma 3-MH was determined in young and healthy individuals. In another study, the cross-sectional associations of plasma 3-MH, 3-MH/Crea and 3-MH/eGFR with the frailty status (robust, pre-frail and frail) were investigated.
Oxidative stress (OS) is a possible contributor to frailty development, and high OS levels as well as low micronutrient levels are associated with the frailty syndrome. However, data on simultaneous measures of OS biomarkers together with micronutrients are lacking in studies including frail, pre-frail and robust individuals. Therefore, cross-sectional associations of protein carbonyls (PrCarb), 3-nitrotyrosine (3-NT) and several micronutrients with the frailty status were determined.
A validated UPLC-MS/MS (ultra-performance liquid chromatography tandem mass spectrometry) method for the simultaneous quantification of 3-MH and 1-MH (1 methylhistidine, as marker for meat and fish consumption) was presented and used for further analyses. Omnivores showed higher plasma 3-MH and 1-MH concentrations than vegetarians and a white meat intervention resulted in an increase in plasma 3-MH, 3 MH/Crea, 1-MH and 1-MH/Crea in omnivores. Elevated 3-MH and 3-MH/Crea levels declined significantly within 24 hours after this white meat intervention. Thus, 3-MH and 3-MH/Crea might be used as biomarker for muscle protein turnover when subjects did not consume meat 24 hours prior to blood samplings.
Plasma 3-MH, 3-MH/Crea and 3-MH/eGFR were higher in frail individuals than in robust individuals. Additionally, these biomarkers were positively associated with frailty in linear regression models, and higher odds to be frail were found for every increase in 3 MH and 3-MH/eGFR quintile in multivariable logistic regression models adjusted for several confounders. This was the first study using 3-MH/eGFR and it is concluded that plasma 3-MH, 3-MH/Crea and 3-MH/eGFR might be used to identify frail individuals or individuals at higher risk to be frail, and that there might be threshold concentrations or ratios to support these diagnoses.
Higher vitamin D3, lutein/zeaxanthin, γ-tocopherol, α-carotene, β-carotene, lycopene and β-cryptoxanthin concentrations and additionally lower PrCarb concentrations were found in robust compared to frail individuals in multivariate linear models. Frail subjects had higher odds to be in the lowest than in the highest tertile for vitamin D3 α-tocopherol, α-carotene, β-carotene, lycopene, lutein/zeaxanthin, and β cryptoxanthin, and had higher odds to be in the highest than in the lowest tertile for PrCarb than robust individuals in multivariate logistic regression models. Thus, a low micronutrient together with a high PrCarb status is associated with pre-frailty and frailty.
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.
In dieser Arbeit steht die Entwicklung einer Sensorplattform für biochemische Anwendungen, welche auf einem optischen Detektionsprinzips beruht, im Vordergrund. Während der Entwicklung wurden zwei komplementäre Konzeptideen behandelt, zum einen ein Sensor, der auf photonischen Kristallen und Wellenleiterstrukturen basiert und zum anderen einen faserbasierten Sensor, der chemisch modifizierte Faser-Bragg-Gitter enthält. Das optische Detektionsprinzip in beiden Sensorideen ist die resultierende Brechungsindexänderung als messbare physikochemische Kenngröße.
Das aus der Natur bekannte Phänomen der photonischen Kristalle, das u. a. bei Opalen und bei Schmetterlingen zu finden ist, wurde bereits 1887 von Lord Rayleigh beschrieben. Er beschrieb die optischen Eigenschaften von periodischen mehrschichtigen Filmen, welche als vereinfachtes Modell eines eindimensionalen photonischen Kristalls verstanden werden können. Die Periodizität der Brechungsindexänderung resultiert in einem optischen Filter für Frequenzen in einem bestimmten spektralen Bereich, weshalb dann dort keine Lichtausbreitung mehr möglich ist. Wird dieses System aber durch eine Defektstelle in der Brechungsindexperiodizität gestört, sodass daraus zwei perfekt periodische Systeme entstehen, ist die Lichtausbreitung für eine bestimmte Frequenz dennoch möglich. In der Folge resultiert daraus ein schmalbandiges Signal im Transmissionsspektrum. Die erlaubte Frequenz ist dabei u. a. abhängig vom Brechungsindexunterschied des periodischen Systems, d.h. Veränderung des Brechungsindexes einer Schicht führt zu einer spektralen Verschiebung der erlaubten Frequenz, dadurch kann dieses Sensorkonzept für biochemische Sensorik ausgenutzt werden [1]. Diese Entwicklung des auf photonischen Kristallen basierenden Sensors war eine Kooperation mit dem Industriepartner „Nanoplus GmbH“. In der Doktorarbeit wurden Simulationen und praktischen Arbeiten zur Designentwicklung des Sensors und die Arbeiten an einem ersten Modellaufbau für die biochemischen Anwendungen durchgeführt.
Für den faserbasierten Sensor wurden Faser-Bragg-Gitter in den Faserkern hineingeschrieben. Hill et al. entdeckten 1978, dass solche Gitterstrukturen genau wie photonische Kristalle als optische Filter fungieren [2]. Die Gitter bestehen dabei aus Änderungen des Brechungsindexes im Faserkern. Im Laufe der nächsten vierzig Jahren wurden verschiedene Einschreibetechniken und Gitterstrukturen entwickelt, weshalb die Eigenschaften der jeweiligen Gitterstrukturen variieren. Eine solche Gitterstruktur sind u. a. die Faser-Bragg-Gitter, deren Gitterperiode, d. h. die Abstände der Brechungsindexmodifikationen, sich im Nanometer- bis Mikrometerbereich befinden. Aufgrund der kleinen Gitterperiode wird eine rückwärtsführende Welle im Kern für eine bestimmte Frequenz bzw. Wellenlänge, der Bragg-Wellenlänge, erzeugt. Im Endeffekt resultiert daraus ein schmalbandiges Signal sowohl im Transmissionsspektrum, als auch im Reflexionsspektrum. Die Resonanzwellenlänge ist dabei proportional zu der Gitterperiode und dem effektiven Brechungsindex, welcher vom Brechungsindex des Kerns und des kernumgebenen Materials abhängig ist. Letztlich eignet sich diese Technik für physikochemische Sensorik. Im Rahmen dieser Arbeit wurden die Gitter mit Hilfe einer relativen neuen Herstellungsmethode in die Fasern geschrieben [3]. Anschließend stand die Entwicklung eines Biosensors im Vordergrund, wobei zunächst ein Protokoll zum Ätzen der Faser mit Flusssäure entwickelt worden ist, dass das System sensitiv zum umgebenen Brechungsindex macht. Am Ende wurde ein Modellaufbau realisiert, indem ein Modellsystem, hier die Detektion vom C-reaktiven Protein mittels spezifischen einzelsträngigen DNS-Aptameren, erfolgreich getestet und quantifiziert worden ist.
1 Mandal, S.; Erickson, D. Nanoscale Optofluidic Sensor Arrays. Opt. Express 2008, 16 (3), 1623–1631.
2 Hill, K. O.; Fujii, Y.; Johnson, D. C.; Kawasaki, B. S. Photosensitivity in Optical Fiber Waveguides: Application to Reflection Filter Fabrication. Appl. Phys. Lett. 1978, 32 (10), 647–649.
3 Martínez, A.; Dubov, M.; Khrushchev, I.; Bennion, I. Direct Writing of Fibre Bragg Gratings by Femtosecond Laser. Electron. Lett. 2004, 40 (19), 1170.
Neuroinflammatory and neurodegenerative diseases such as Parkinson's (PD) and multiple sclerosis (MS) often result in a severe impairment of the patient´s quality of life. Effective therapies for the treatment are currently not available, which results in a high socio-economic burden. Due to the heterogeneity of the disease subtypes, stratification is particularly difficult in the early phase of the disease and is mainly based on clinical parameters such as neurophysiological tests and central nervous imaging. Due to good accessibility and stability, blood and cerebrospinal fluid metabolite markers could serve as surrogates for neurodegenerative processes. This can lead to an improved mechanistic understanding of these diseases and further be used as "treatment response" biomarkers in preclinical and clinical development programs. Therefore, plasma and CSF metabolite profiles will be identified that allow differentiation of PD from healthy controls, association of PD with dementia (PDD) and differentiation of PD subtypes such as akinetic rigid and tremor dominant PD patients. In addition, plasma metabolites for the diagnosis of primary progressive MS (PPMS) should be investigated and tested for their specificity to relapsing-remitting MS (RRMS) and their development during PPMS progression.
By applying untargeted high-resolution metabolomics of PD patient samples and in using random forest and partial least square machine learning algorithms, this study identified 20 plasma metabolites and 14 CSF metabolite biomarkers. These differentiate against healthy individuals with an AUC of 0.8 and 0.9 in PD, respectively. We also identify ten PDD specific serum metabolites, which differentiate against healthy individuals and PD patients without dementia with an AUC of 1.0, respectively. Furthermore, 23 akinetic-rigid specific plasma markers were identified, which differentiate against tremor-dominant PD patients with an AUC of 0.94 and against healthy individuals with an AUC of 0.98. These findings also suggest more severe disease pathology in the akinetic-rigid PD than in tremor dominant PD. In the analysis of MS patient samples a partial least square analysis yielded predictive models for the classification of PPMS and resulted in 20 PPMS specific metabolites. In another MS study unknown changes in human metabolism were identified after administration of the multiple sclerosis drug dimethylfumarate, which is used for the treatment of RRMS. These results allow to describe and understand the hitherto completely unknown mechanism of action of this new drug and to use these findings for the further development of new drugs and targets against RRMS.
In conclusion, these results have the potential for improved diagnosis of these diseases and improvement of mechanistic understandings, as multiple deregulated pathways were identified. Moreover, novel Dimethylfumarate targets can be used to aid drug development and treatment efficiency. Overall, metabolite profiling in combination with machine learning identified as a promising approach for biomarker discovery and mode of action elucidation.
Global climate change is one of the greatest challenges of the 21st century, with influence on the environment, societies, politics and economies. The (semi-)arid areas of Southern Africa already suffer from water scarcity. There is a great variety of ongoing research related to global climate history but important questions on regional differences still exist.
In southern African regions terrestrial climate archives are rare, which makes paleoclimate studies challenging. Based on the assumption that continental pans (sabkhas) represent a suitable geo-archive for the climate history, two different pans were studied in the southern and western Kalahari Desert. A combined approach of molecular biological and biogeochemical analyses is utilized to investigate the diversity and abundance of microorganisms and to trace temporal and spatial changes in paleoprecipitation in arid environments. The present PhD thesis demonstrates the applicability of pan sediments as a late Quaternary geo-archive based on microbial signature lipid biomarkers, such as archaeol, branched and isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs) as well as phospholipid fatty acids (PLFA). The microbial signatures contained in the sediment provide information on the current or past microbial community from the Last Glacial Maximum to the recent epoch, the Holocene. The results are discussed in the context of regional climate evolution in southwestern Africa. The seasonal shift of the Innertropical Convergence Zone (ITCZ) along the equator influences the distribution of precipitation- and climate zones. The different expansion of the winter- and summer rainfall zones in southern Africa was confirmed by the frequency of certain microbial biomarkers. A period of increased precipitation in the south-western Kalahari could be described as a result of the extension of the winter rainfall zone during the last glacial maximum (21 ± 2 ka). Instead a period of increased paleoprecipitation in the western Kalahari was indicated during the Late Glacial to Holocene transition. This was possibly caused by a southwestern shift in the position of the summer rainfall zone associated to the southward movement of the ITCZ.
Furthermore, for the first time this study characterizes the bacterial and archaeal life based on 16S rRNA gene high-throughput sequencing in continental pan sediments and provides an insight into the recent microbial community structure. Near-surface processes play an important role for the modern microbial ecosystem in the pans. Water availability as well as salinity might determine the abundance and composition of the microbial communities. The microbial community of pan sediments is dominated by halophilic and dry-adapted archaea and bacteria. Frequently occurring microorganisms such as, Halobacteriaceae, Bacillus and Gemmatimonadetes are described in more detail in this study.