Science Collected Works - Research Publications
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ItemMorphodynamics of an erodible channel under varying discharge(WILEY, 2021-09-30)Abstract Alluvial channels arise through the interaction between morphology, hydraulics, and sediment transport, known as the ‘fluvial trinity’. Over relatively short timescales where climate and geology are fixed but discharge and sediment supply may vary, this process facilitates adjustments towards steady state, where the system oscillates around a mean condition. The relationship between changes in conditions and geomorphic response may be highly complex and nonlinear, especially in systems with multiple modes of adjustment. This study examines the adjustment of an erodible channel with fixed banks and a widely graded sediment mixture to successive increases in discharge. With each increase in discharge, components of the fluvial trinity adjusted towards a steady state. Particularly at relatively low discharges, adjustments were controlled by intrinsic thresholds and highlighted important morphodynamic processes. Notably, there was a strong interplay between channel morphology and sediment transport, and an effect whereby larger‐than‐average grains controlled channel deformation. These two processes occurred at the bar scale and were highly spatialised, which has two important implications: (1) reach‐averaged representations of process provide only partial insight into morphodynamics; and (2) models of rivers that suppress these process feedbacks and size‐dependent transport may not replicate morphodynamics that typically occur in field conditions. The experiments provide quantitative evidence for conceptual models describing exponential approaches towards steady state and the potential for transiency if disturbance frequency exceeds the recovery time. They also highlight how in natural rivers, particularly those with greater degrees of freedom for adjustment (notably, lateral adjustment and meandering), continuous changes in discharge may lead to nonlinear rather than steady‐state behaviour. In these settings, more holistic analytical frameworks that embrace different aspects of the system are critical in understanding the direction, magnitude and timing of channel adjustments.
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ItemInsect Antennal Morphology: The Evolution of Diverse Solutions to Odorant Perception(Yale University, 2018-12-01)Chemical communication involves the production, transmission, and perception of odors. Most adult insects rely on chemical signals and cues to locate food resources, oviposition sites or reproductive partners and, consequently, numerous odors provide a vital source of information. Insects detect these odors with receptors mostly located on the antennae, and the diverse shapes and sizes of these antennae (and sensilla) are both astonishing and puzzling: what selective pressures are responsible for these different solutions to the same problem - to perceive signals and cues? This review describes the selection pressures derived from chemical communication that are responsible for shaping the diversity of insect antennal morphology. In particular, we highlight new technologies and techniques that offer exciting opportunities for addressing this surprisingly neglected and yet crucial component of chemical communication.
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ItemDiscovery of food identity markers by metabolomics and machine learning technology(NATURE PORTFOLIO, 2019-07-04)Verification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to screen food markers when coupled to efficient data analysis. This study explored feasibility of random forest (RF) machine learning, specifically its inherent feature extraction for non-targeted metabolic marker discovery. The distinction of chia, linseed, and sesame that have gained attention as "superfoods" served as test case. Chemical fractions of non-processed seeds and of wheat cookies with seed ingredients were profiled. RF technology classified original seeds unambiguously but appeared overdesigned for material with unique secondary metabolites, like sesamol or rosmarinic acid in the Lamiaceae, chia. Most unique metabolites were diluted or lost during cookie production but RF technology classified the presence of the seed ingredients in cookies with 6.7% overall error and revealed food processing markers, like 4-hydroxybenzaldehyde for chia and succinic acid monomethylester for linseed additions. RF based feature extraction was adequate for difficult classifications but marker selection should not be without human supervision. Combination with alternative data analysis technologies is advised and further testing of a wide range of seeds and food processing methods.
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ItemCOSNeti: ComplexOme-Structural Network Interpreter used to study spatial enrichment in metazoan ribosomes(BMC, 2021-12-20)BACKGROUND: Upon environmental stimuli, ribosomes are surmised to undergo compositional rearrangements due to abundance changes among proteins assembled into the complex, leading to modulated structural and functional characteristics. Here, we present the ComplexOme-Structural Network Interpreter ([Formula: see text]), a computational method to allow testing whether ribosomal proteins (rProteins) that exhibit abundance changes under specific conditions are spatially confined to particular regions within the large ribosomal complex. RESULTS: [Formula: see text] translates experimentally determined structures into graphs, with nodes representing proteins and edges the spatial proximity between them. In its first implementation, [Formula: see text] considers rProteins and ignores rRNA and other objects. Spatial regions are defined using a random walk with restart methodology, followed by a procedure to obtain a minimum set of regions that cover all proteins in the complex. Structural coherence is achieved by applying weights to the edges reflecting the physical proximity between purportedly contacting proteins. The weighting probabilistically guides the random-walk path trajectory. Parameter tuning during region selection provides the option to tailor the method to specific biological questions by yielding regions of different sizes with minimum overlaps. In addition, other graph community detection algorithms may be used for the [Formula: see text] workflow, considering that they yield different sized, non-overlapping regions. All tested algorithms result in the same node kernels under equivalent regions. Based on the defined regions, available abundance change information of proteins is mapped onto the graph and subsequently tested for enrichment in any of the defined spatial regions. We applied [Formula: see text] to the cytosolic ribosome structures of Saccharomyces cerevisiae, Oryctolagus cuniculus, and Triticum aestivum using datasets with available quantitative protein abundance change information. We found that in yeast, substoichiometric rProteins depleted from translating polysomes are significantly constrained to a ribosomal region close to the tRNA entry and exit sites. CONCLUSIONS: [Formula: see text] offers a computational method to partition multi-protein complexes into structural regions and a statistical approach to test for spatial enrichments of any given subsets of proteins. [Formula: see text] is applicable to any multi-protein complex given appropriate structural and abundance-change data. [Formula: see text] is publicly available as a GitHub repository https://github.com/MSeidelFed/COSNet_i and can be installed using the python installer pip.
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ItemUnravelling the Metabolic and Hormonal Machinery During Key Steps of Somatic Embryogenesis: A Case Study in Coffee(MDPI, 2019-10)Somatic embryogenesis (SE) is one of the most promising processes for large-scale dissemination of elite varieties. However, for many plant species, optimizing SE protocols still relies on a trial-and-error approach. Using coffee as a model plant, we report here the first global analysis of metabolome and hormone dynamics aiming to unravel mechanisms regulating cell fate and totipotency. Sampling from leaf explant dedifferentiation until embryo development covered 15 key stages. An in-depth statistical analysis performed on 104 metabolites revealed that massive re-configuration of metabolic pathways induced SE. During initial dedifferentiation, a sharp decrease in phenolic compounds and caffeine levels was also observed while auxins, cytokinins and ethylene levels were at their highest. Totipotency reached its highest expression during the callus stages when a shut-off in hormonal and metabolic pathways related to sugar and energetic substance hydrolysis was evidenced. Abscisic acid, leucine, maltotriose, myo-inositol, proline, tricarboxylic acid cycle metabolites and zeatin appeared as key metabolic markers of the embryogenic capacity. Combining metabolomics with multiphoton microscopy led to the identification of chlorogenic acids as markers of embryo redifferentiation. The present analysis shows that metabolite fingerprints are signatures of cell fate and represent a starting point for optimizing SE protocols in a rational way.
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ItemSeparation and Paired Proteome Profiling of Plant Chloroplast and Cytoplasmic Ribosomes(MDPI, 2020-07)Conventional preparation methods of plant ribosomes fail to resolve non-translating chloroplast or cytoplasmic ribosome subunits from translating fractions. We established preparation of these ribosome complexes from Arabidopsis thaliana leaf, root, and seed tissues by optimized sucrose density gradient centrifugation of protease protected plant extracts. The method co-purified non-translating 30S and 40S ribosome subunits separated non-translating 50S from 60S subunits, and resolved assembled monosomes from low oligomeric polysomes. Combining ribosome fractionation with microfluidic rRNA analysis and proteomics, we characterized the rRNA and ribosomal protein (RP) composition. The identity of cytoplasmic and chloroplast ribosome complexes and the presence of ribosome biogenesis factors in the 60S-80S sedimentation interval were verified. In vivo cross-linking of leaf tissue stabilized ribosome biogenesis complexes, but induced polysome run-off. Omitting cross-linking, the established paired fractionation and proteome analysis monitored relative abundances of plant chloroplast and cytoplasmic ribosome fractions and enabled analysis of RP composition and ribosome associated proteins including transiently associated biogenesis factors.
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ItemSystematic Review of Plant Ribosome Heterogeneity and Specialization(FRONTIERS MEDIA SA, 2020-06-25)Plants dedicate a high amount of energy and resources to the production of ribosomes. Historically, these multi-protein ribosome complexes have been considered static protein synthesis machines that are not subject to extensive regulation but only read mRNA and produce polypeptides accordingly. New and increasing evidence across various model organisms demonstrated the heterogeneous nature of ribosomes. This heterogeneity can constitute specialized ribosomes that regulate mRNA translation and control protein synthesis. A prominent example of ribosome heterogeneity is seen in the model plant, Arabidopsis thaliana, which, due to genome duplications, has multiple paralogs of each ribosomal protein (RP) gene. We support the notion of plant evolution directing high RP paralog divergence toward functional heterogeneity, underpinned in part by a vast resource of ribosome mutants that suggest specialization extends beyond the pleiotropic effects of single structural RPs or RP paralogs. Thus, Arabidopsis is a highly suitable model to study this phenomenon. Arabidopsis enables reverse genetics approaches that could provide evidence of ribosome specialization. In this review, we critically assess evidence of plant ribosome specialization and highlight steps along ribosome biogenesis in which heterogeneity may arise, filling the knowledge gaps in plant science by providing advanced insights from the human or yeast fields. We propose a data analysis pipeline that infers the heterogeneity of ribosome complexes and deviations from canonical structural compositions linked to stress events. This analysis pipeline can be extrapolated and enhanced by combination with other high-throughput methodologies, such as proteomics. Technologies, such as kinetic mass spectrometry and ribosome profiling, will be necessary to resolve the temporal and spatial aspects of translational regulation while the functional features of ribosomal subpopulations will become clear with the combination of reverse genetics and systems biology approaches.
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ItemThe transcriptional regulator CprK detects chlorination by combining direct and indirect readout mechanisms(ROYAL SOC, 2013-04-19)The transcriptional regulator CprK controls the expression of the reductive dehalogenase CprA in organohalide-respiring bacteria. Desulfitobacterium hafniense CprA catalyses the reductive dechlorination of the terminal electron acceptor o-chlorophenol acetic acid, generating the phenol acetic acid product. It has been shown that CprK has ability to distinguish between the chlorinated CprA substrate and the de-halogenated end product, with an estimated an estimated 10(4)-fold difference in affinity. Using a green fluorescent protein GFPUV-based transcriptional reporter system, we establish that CprK can sense o-chlorophenol acetic acid at the nanomolar level, whereas phenol acetic acid leads to transcriptional activation only when approaching micromolar levels. A structure-activity relationship study, using a range of o-chlorophenol acetic-acid-related compounds and key CprK mutants, combined with pKa calculations on the effector binding site, suggests that the sensitive detection of chlorination is achieved through a combination of direct and indirect readout mechanisms. Both the physical presence of the bulky chloride substituent as well as the accompanying electronic effects lowering the inherent phenol pKa are required for high affinity. Indeed, transcriptional activation by CprK appears strictly dependent on establishing a phenolate-K133 salt bridge interaction, rather than on the presence of a halogen atom per se. As K133 is strictly conserved within the CprK family, our data suggest that physiological function and future applications in biosensing are probably restricted to phenolic compounds.
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ItemVisualization of poly(ADP-ribose) bound to PARG reveals inherent balance between exo- and endo-glycohydrolase activities(NATURE PUBLISHING GROUP, 2013-08)Poly-ADP-ribosylation is a post-translational modification that regulates processes involved in genome stability. Breakdown of the poly(ADP-ribose) (PAR) polymer is catalysed by poly(ADP-ribose) glycohydrolase (PARG), whose endo-glycohydrolase activity generates PAR fragments. Here we present the crystal structure of PARG incorporating the PAR substrate. The two terminal ADP-ribose units of the polymeric substrate are bound in exo-mode. Biochemical and modelling studies reveal that PARG acts predominantly as an exo-glycohydrolase. This preference is linked to Phe902 (human numbering), which is responsible for low-affinity binding of the substrate in endo-mode. Our data reveal the mechanism of poly-ADP-ribosylation reversal, with ADP-ribose as the dominant product, and suggest that the release of apoptotic PAR fragments occurs at unusual PAR/PARG ratios.
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ItemNUMT Confounding Biases Mitochondrial Heteroplasmy Calls in Favor of the Reference Allele(FRONTIERS MEDIA SA, 2019-09-25)Homology between mitochondrial DNA (mtDNA) and nuclear DNA of mitochondrial origin (nuMTs) causes confounding when aligning short sequence reads to the reference human genome, as the true sequence origin cannot be determined. Using a systematic in silico approach, we here report the impact of all potential mitochondrial variants on alignment accuracy and variant calling. A total of 49,707 possible mutations were introduced across the 16,569 bp reference mitochondrial genome (16,569 × 3 alternative alleles), one variant at-at-time. The resulting in silico fragmentation and alignment to the entire reference genome (GRCh38) revealed preferential mapping of mutated mitochondrial fragments to nuclear loci, as variants increased loci similarity to nuMTs, for a total of 807, 362, and 41 variants at 333, 144, and 27 positions when using 100, 150, and 300 bp single-end fragments. We subsequently modeled these affected variants at 50% heteroplasmy and carried out variant calling, observing bias in the reported allele frequencies in favor of the reference allele. Four variants (chrM:6023A, chrM:4456T, chrM:5147A, and chrM:7521A) including a possible hypertension factor, chrM:4456T, caused 100% loss of coverage at the mutated position (with all 100 bp single-end fragments aligning to homologous, nuclear positions instead of chrM), rendering these variants undetectable when aligning to the entire reference genome. Furthermore, four mitochondrial variants reported to be pathogenic were found to cause significant loss of coverage and select haplogroup-defining SNPs were shown to exacerbate the loss of coverage caused by surrounding variants. Increased fragment length and use of paired-end reads both improved alignment accuracy.