Biology subjects

Schubert, P.

Publications and source records attributed to Schubert, P..

6 recordsLinked to original sources

bioRxiv2024

Short periods of decreased water flow may modulate long-term ocean acidification in reef-building corals

Ocean acidification (OA) poses a major threat to reef-building corals. Although water flow variability is common in coral reefs and modulates coral physiology, the interactive effects of flow and OA on corals remain poorly understood. Therefore, we performed a three-month OA experiment investigating the effect of changes in flow on coral physiology. We exposed the reef-building corals Acropora cytherea, Pocillopora verrucosa, and Porites cylindrica to control (pH 8.0) and OA (pH 7.8) conditions at moderate flow (6 cm s-1) and monitored OA effects on growth. Throughout the experiment, we intermittently exposed all corals to low flow (2 cm s-1) for 1.5 h and measured their photosynthesis:photosynthesis (P:R) ratio under low and moderate flow. On average, corals under OA calcified 18 % less and grew 23 % less in surface area than those at ambient pH. We observed species-specific interactive effects of OA and flow on coral physiology. P:R ratios decreased after 12 weeks of OA in A. cytherea (22 %) and P. cylindrica (28 %) under moderate flow, but were unaffected by OA under low flow. P:R ratios were stable in P. verrucosa. These results suggest that short periods of decreased water flow may modulate OA effects on some coral species, indicating that flow variability is a factor to consider when assessing long-term effects of climate change.

physiology↗

bioRxiv2023

Common types of microdebris affect the physiology of reef-building corals

Marine debris, particularly microdebris (< 1 mm) poses a potential threat to marine life, including reef-building corals. While previous research has mainly focused on the impact of single polymer microplastics, the effects of natural microdebris, composed of a mixture of materials, have not been explored. Therefore, this study aimed to assess the effects of different microdebris, originating from major sources of pollution, on reef-building corals. For this, we exposed two scleractinian coral species, Pocillopora verrucosa and Stylophora pistillata, known to frequently ingest microplastics, to four types of microdebris in an 8-week laboratory experiment: fragmented environmental plastic debris, artificial fibers from clothing, residues from the automobile sector consisting of tire wear, brake abrasion, and varnish flakes, a single polymer microplastic treatment consisting of polyethylene particles, and a microdebris-free control treatment. Specifically, we (I) compared the effects of the different microdebris on coral growth, necrosis, and photosynthesis, (II) investigated the difference between the microdebris mixtures and the exposure to the single polymer treatment, and (III) identified potential mechanisms causing species-specific effects by contrasting the feeding responses of the two coral species on microdebris and natural food. We show that the fibers and tire wear had the strongest effects on coral physiology, with P. verrucosa being more affected than S. pistillata. Both species showed increased volume growth in response to the microdebris treatments, accompanied by decreased calcification in P. verrucosa. Photosynthetic efficiency of the symbionts was enhanced in both species. The species-specific physiological responses might be attributed to feeding reactions, with P. verrucosa responding significantly more often to microdebris than S. pistillata. These findings highlight the effect of different microdebris on coral physiology and the need for future studies to use particle mixtures to better mimic naturally occurring microdebris and assess its effect on corals in more detail. HighlightsO_LIThe effects of major sources of microdebris pollution on coral physiology were compared. C_LIO_LIOverall, microdebris had only minor impacts on coral physiology. C_LIO_LIArtificial fibers and tire wear caused the strongest effect on coral physiology. C_LIO_LISingle polymer and complex microdebris caused similar, yet species-specific effects. C_LIO_LISpecies-specific effects might be due to different feeding behaviors. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/569976v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1ba7ba8org.highwire.dtl.DTLVardef@c5795org.highwire.dtl.DTLVardef@4a10deorg.highwire.dtl.DTLVardef@9983e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2022

More than Mycobacterium tuberculosis: specific site-of-disease microbial communities, functional capacities, and their distinct clinical profiles in tuberculous lymphadenitis

BackgroundLymphadenitis is the most common extrapulmonary tuberculosis (EPTB) manifestation and a major cause of death. The microbiome is important to human health but uninvestigated in EPTB. We profiled the site-of-disease lymph node microbiome in tuberculosis lymphadenitis (TBL). MethodsFine needle aspiration biopsies (FNABs) were collected from 159 pre-treatment presumptive TBL patients in Cape Town, South Africa. 16S Illumina MiSeq rRNA gene sequencing was done. ResultsWe analysed 89 definite TBLs (dTBLs) and 61 non-TBLs (nTBLs), which had similar -but different {beta}-diversities (p=0.001). Clustering identified five lymphotypes prior to TB status stratification: Mycobacterium-, Prevotella- and Streptococcus-dominant lymphotypes were more frequent in dTBLs whereas a Corynebacterium-dominantlymphotype and a fifth lymphotype (no dominant taxon) were more frequent in nTBLs. When restricted to dTBLs, clustering identified a Mycobacterium-dominant lymphotype with low -diversity and other non-Mycobacterium-dominated lymphotypes (termed Prevotella-Corynebacterium and Prevotella-Streptococcus). The Mycobacterium dTBL lymphotype was associated with HIV-positivity and clinical features characteristic of severe lymphadenitis (e.g., node size). dTBL microbial communities were enriched with potentially proinflammatory microbial short chain fatty acid metabolic pathways (propanoate, butanoate) vs. those in nTBLs. 11% (7/61) of nTBLs had Mycobacterium reads. ConclusionsTBL at the site-of-disease is not microbially homogenous and distinct microbial community clusters exist that are associated with different immunomodulatory potentials and clinical characteristics. Non-Mycobacterium-dominated dTBL lymphotypes, which contain taxa potentially targeted by TB treatment, represent less severe potentially earlier stage disease. These investigations lay foundations for studying the microbiomes role in lymphatic TB and the long-term clinical significance of lymphotypes requires prospective evaluation.

molecular biology↗

bioRxiv2021

Interactive effects of microplastic pollution and heat stress on reef-building corals

Plastic pollution is an emerging stressor that increases pressure on ecosystems such as coral reefs that are already challenged by climate change. However, the effect of plastic pollution in combination with global warming is largely unknown. Thus, the goal of this study was to determine the cumulative effect of microplastic pollution with that of global warming on reef-building coral species and to compare the severity of both stressors. For this, we conducted a series of three controlled laboratory experiments and exposed a broad range of coral species (Acropora muricata, Montipora digitata, Porites lutea, Pocillopora verrucosa, and Stylophora pistillata) to microplastic particles in a range of concentrations (2.5-2,500 particles L-1) and mixtures (from different industrial sectors) at ambient temperatures and in combination with heat stress. We show that microplastic can occasionally have a negative effect on the corals thermal tolerance. In comparison to heat stress, however, microplastic constitutes a minor stressor. While heat stress led to decreased photosynthetic efficiency of algal symbionts, and increased bleaching, tissue necrosis, and mortality, treatment with microplastic particles had only minor effects on the physiology and health of the tested coral species at ambient temperatures. These findings underline that while efforts to reduce plastic pollution should continue, they should not replace more urgent efforts to halt global warming, which are immediately needed to preserve remaining coral reef ecosystems. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/454458v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@c2eeb0org.highwire.dtl.DTLVardef@1c49ea6org.highwire.dtl.DTLVardef@18bab59org.highwire.dtl.DTLVardef@9e952b_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2020

Structure of autosynthetic models of balanced cell growth and numerical optimization of their growth rate

Genome-scale reaction network models are available for many prokaryotic organisms. Yet, to predict the proteome and metabolome of the cell from them, additional information about (i) the nonlinear enzyme kinetics and (ii) the regulation of protein expression by metabolic signals is necessary. Knowledge about the latter could be sidestepped by assuming that expression regulation has evolved to achieve the protein composition that maximizes cellular growth rate. A general mathematical framework for optimizing the growth rate of models comprising an arbitrarily complex metabolic network and a relatively simple protein-synthesis network was recently formulated independently by two research groups [de Groot et al., PLoS Comput. Biol. 16, e1007559 (2020); Dourado & Lercher, Nature Commun. 11, 1226 (2020)]. Here, this formalism is further developed with particular focus on carrying out the optimization numerically. To this end, we identify the concentrations of the enzymes as the independent variables of the optimization problem and propose novel multiplicative updates for the iterative calculation of the dependent metabolite concentrations. The reduced gradient method, with analytical derivatives, is employed for the numerical optimization. Additionally, the roles of the dilution of the metabolite concentrations by growth and the commonly invoked constraint on the cell dry mass density are clarified. These developments should lay the basis for the practical optimization of large-scale kinetic models, thus formally connecting the physiological "macrostate" of the cell, characterized by its growth rate, to its "microstate", described by the cell proteome and metabolome. Author summaryAn evolving population of non-interacting, unicellular organisms in a constant environment will maximize its growth rate. By expressing the growth rate as a mathematical function of the cellular composition, it becomes possible to formulate an optimization problem whose solution yields the cell proteome and metabolome at the maximal growth rate. The formulation and solution of such an optimization problem has the potential to elucidate fundamental optimality principles in living cells and to enable the engineering of complex biological systems. Building on previous work, here we address the task of solving this optimization problem numerically. In the process, we elucidate the mathematical role of some common simplifying approximations. This allows us to organize many of the existing formulations of the optimization problem into a hierarchy, whose lower levels are reached by invoking these approximations.

systems biology↗

bioRxiv2018

Learning cellular morphology with neural networks

Reconstruction and annotation of volume electron microscopy data sets of brain tissue is challenging, but can reveal invaluable information about neuronal circuits. Significant progress has recently been made in automated neuron reconstruction, as well as automated detection of synapses. However, methods for automating the morphological analysis of nanometer-resolution reconstructions are less established, despite their diverse application possibilities. Here, we introduce cellular morphology neural networks (CMNs), based on multi-view projections sampled from automatically reconstructed cellular fragments of arbitrary size and shape. Using unsupervised training we inferred morphology embeddings (\"Neuron2vec\") of neuron reconstructions and trained CMNs to identify glia cells in a supervised classification paradigm which was then used to resolve neuron reconstruction errors. Finally, we demonstrate that CMNs can be used to identify subcellular compartments and the cell types of neuron reconstructions.

neuroscience↗