570 Biowissenschaften; Biologie
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Institute
- Institut für Biochemie und Biologie (1141)
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We previously showed that purified 1-methoxy-3-indolylmethyl (1-MIM) glucosinolate, a secondary plant metabolite in Brassica species, is mutagenic in various in vitro systems and forms DNA and protein adducts in mouse models. In the present study, we administered 1-MIM glucosinolate in a natural matrix to mice, by feeding a diet containing pak choi powder and extract. Groups of animals were killed after 1, 2, 4 and 8 days of pak choi diet, directly or, in the case of the 8-day treatment, after 0, 8 and 16 days of recovery with pak choi-free diet. DNA adducts [N-2-(1-MIM)-dG, N-6-(1-MIM)-dA] in six tissues, as well as protein adducts [tau N-(1-MIM)-His] in serum albumin (SA) and hemoglobin (Hb) were determined using UPLC-MS/MS with isotopically labeled internal standards. None of the samples from the 12 control animals under standard diet contained any 1-MIM adducts. All groups receiving pak choi diet showed DNA adducts in all six tissues (exception: lung of mice treated for a single day) as well as SA and Hb adducts. During the feeding period, all adduct levels continuously increased until day 8 (in the jejunum until day 4). During the 14-day recovery period, N-2-(1-MIM)-dG in liver, kidney, lung, jejunum, cecum and colon decreased to 52, 41, 59, 11, 7 and 2%, respectively, of the peak level. The time course of N-6-(1-MIM)-dA was similar. Immunohistochemical analyses indicated that cell turnover is a major mechanism of DNA adduct elimination in the intestine. In the same recovery period, protein adducts decreased more rapidly in SA than in Hb, to 0.7 and 37%, respectively, of the peak level, consistent with the differential turnover of these proteins. In conclusion, the pak choi diet lead to the formation of high levels of adducts in mice. Cell and protein turnover was a major mechanism of adduct elimination, at least in gut and blood.
A balance to death
(2018)
Leaf senescence plays a crucial role in nutrient recovery in late-stage plant development and requires vast transcriptional reprogramming by transcription factors such as ORESARA1 (ORE1). A proteolytic mechanism is now found to control ORE1 degradation, and thus senescence, during nitrogen starvation.
Ecological communities are complex adaptive systems that exhibit remarkable feedbacks between their biomass and trait dynamics. Trait-based aggregate models cope with this complexity by focusing on the temporal development of the community’s aggregate properties such as its total biomass, mean trait and trait variance. They are based on particular assumptions about the shape of the underlying trait distribution, which is commonly assumed to be normal. However, ecologically important traits are usually restricted to a finite range, and empirical trait distributions are often skewed or multimodal. As a result, normal distribution-based aggregate models may fail to adequately represent the biomass and trait dynamics of natural communities. We resolve this mismatch by developing a new moment closure approach assuming the trait values to be beta-distributed. We show that the beta distribution captures important shape properties of both observed and simulated trait distributions, which cannot be captured by a Gaussian. We further demonstrate that a beta distribution-based moment closure can strongly enhance the reliability of trait-based aggregate models. We compare the biomass, mean trait and variance dynamics of a full trait distribution (FD) model to the ones of beta (BA) and normal (NA) distribution-based aggregate models, under different selection regimes. This way, we demonstrate under which general conditions (stabilizing, fluctuating or disruptive selection) different aggregate models are reliable tools. All three models predicted very similar biomass and trait dynamics under stabilizing selection yielding unimodal trait distributions with small standing trait variation. We also obtained an almost perfect match between the results of the FD and BA models under fluctuating selection, promoting skewed trait distributions and ongoing oscillations in the biomass and trait dynamics. In contrast, the NA model showed unrealistic trait dynamics and exhibited different alternative stable states, and thus a high sensitivity to initial conditions under fluctuating selection. Under disruptive selection, both aggregate models failed to reproduce the results of the FD model with the mean trait values remaining within their ecologically feasible ranges in the BA model but not in the NA model. Overall, a beta distribution-based moment closure strongly improved the realism of trait-based aggregate models.
Abiotic stresses cause oxidative damage in plants. Here, we demonstrate that foliar application of an extract from the seaweed Ascophyllum nodosum, SuperFifty (SF), largely prevents paraquat (PQ)-induced oxidative stress in Arabidopsis thaliana. While PQ-stressed plants develop necrotic lesions, plants pre-treated with SF (i.e., primed plants) were unaffected by PQ. Transcriptome analysis revealed induction of reactive oxygen species (ROS) marker genes, genes involved in ROS-induced programmed cell death, and autophagy-related genes after PQ treatment. These changes did not occur in PQ-stressed plants primed with SF. In contrast, upregulation of several carbohydrate metabolism genes, growth, and hormone signaling as well as antioxidant-related genes were specific to SF-primed plants. Metabolomic analyses revealed accumulation of the stress-protective metabolite maltose and the tricarboxylic acid cycle intermediates fumarate and malate in SF-primed plants. Lipidome analysis indicated that those lipids associated with oxidative stress-induced cell death and chloroplast degradation, such as triacylglycerols (TAGs), declined upon SF priming. Our study demonstrated that SF confers tolerance to PQ-induced oxidative stress in A. thaliana, an effect achieved by modulating a range of processes at the transcriptomic, metabolic, and lipid levels.
Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI<18.5 kg/m(2)) or obese (BMI30 kg/m(2)) categories, while the highest quartile of ABSI separated 18-39% of the individuals within each BMI category, which had 22-55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.
A Cell-free Expression Pipeline for the Generation and Functional Characterization of Nanobodies
(2022)
Cell-free systems are well-established platforms for the rapid synthesis, screening, engineering and modification of all kinds of recombinant proteins ranging from membrane proteins to soluble proteins, enzymes and even toxins. Also within the antibody field the cell-free technology has gained considerable attention with respect to the clinical research pipeline including antibody discovery and production. Besides the classical full-length monoclonal antibodies (mAbs), so-called "nanobodies" (Nbs) have come into focus. A Nb is the smallest naturally-derived functional antibody fragment known and represents the variable domain (VHH, similar to 15 kDa) of a camelid heavy-chain-only antibody (HCAb). Based on their nanoscale and their special structure, Nbs display striking advantages concerning their production, but also their characteristics as binders, such as high stability, diversity, improved tissue penetration and reaching of cavity-like epitopes. The classical way to produce Nbs depends on the use of living cells as production host. Though cell-based production is well-established, it is still time-consuming, laborious and hardly amenable for high-throughput applications. Here, we present for the first time to our knowledge the synthesis of functional Nbs in a standardized mammalian cell-free system based on Chinese hamster ovary (CHO) cell lysates. Cell-free reactions were shown to be time-efficient and easy-to-handle allowing for the "on demand" synthesis of Nbs. Taken together, we complement available methods and demonstrate a promising new system for Nb selection and validation.
Next-generation sequencing methods provide comprehensive data for the analysis of structural and functional analysis of the genome. The draft genomes with low contig number and high N50 value can give insight into the structure of the genome as well as provide information on the annotation of the genome. In this study, we designed a pipeline that can be used to assemble prokaryotic draft genomes with low number of contigs and high N50 value. We aimed to use combination of two de novo assembly tools (SPAdes and IDBA-Hybrid) and evaluate the impact of this approach on the quality metrics of the assemblies. The followed pipeline was tested with the raw sequence data with short reads (< 300) for a total of 10 species from four different genera. To obtain the final draft genomes, we firstly assembled the sequences using SPAdes to find closely related organism using the extracted 16 s rRNA from it. IDBA-Hybrid assembler was used to obtain the second assembly data using the closely related organism genome. SPAdes assembler tool was implemented using the second assembly, produced by IDBA-hybrid as a hint. The results were evaluated using QUAST and BUSCO. The pipeline was successful for the reduction of the contig numbers and increasing the N50 statistical values in the draft genome assemblies while preserving the coverage of the draft genomes.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.