Biology subjects

Clemens, S.

Publications and source records attributed to Clemens, S..

6 recordsLinked to original sources

bioRxiv2024

Nanoparticle-Supported, Rapid, and Electronic Detection of SARS-CoV-2 Antibodies and Antigens at Attomolar Level

Major challenges remain to precisely detect low-abundance proteins from diverse biofluids in a rapid and cost-effective manner. Here we present a gold nanoparticle (AuNP)-supported, rapid electronic detection (NasRED) platform with sub-femtomolar sensitivity and high specificity. Surface-functionalized AuNPs act as multivalent detectors to recognize target antigens and antibodies through high-affinity binding, subsequently forming aggregates precipitated in a microcentrifuge tube and producing a solution color change. The optical extinction of residual floating AuNPs is digitized using a customized circuitry incorporating inexpensive optoelectronic elements and feedback mechanisms for stabilized readout. Uniquely, NasRED introduces active fluidic forces through engineered centrifugation and vortex agitation, effectively promoting protein detection at low concentrations and accelerating signal generation. Using SARS-CoV-2 as a demonstration, NasRED enables detection of both antibodies and antigens from a small sample volume (6 {micro}L), distinguishes the viral antigens from those of human coronaviruses, and delivers test results in a short time (as fast as <15 min). The limits of detection (LoDs) for antibody detection are approximately 49 aM (7 fg/mL) in phosphate-buffered saline, or >3,000 times more sensitive than Enzyme-Linked Immunosorbent Assay (ELISA), [~]76 aM (11 fg/mL) in human pooled serum and in the femtomolar range in diluted whole blood. For nucleocapsid protein detection, NasRED LoDs are [~]190 aM (10 fg/mL) in human saliva and [~]2 fM (100 fg/mL) in nasal fluid. Unlike laboratory-based ELISA platforms, NasRED is a one-pot, in-solution assay that eliminates the needs for washing, labeling, expensive instrumentation or highly trained operators. With low reagent costs and a compact system footprint, this modular digital platform is well-suited for accurate, near-patient diagnosis and screening of a wide range of infectious and chronic diseases.

microbiology↗

bioRxiv2024

Specific redox and iron homeostasis responses in the root tip of Arabidopsis upon zinc excess

O_LIZinc (Zn) excess negatively impacts primary root growth in Arabidopsis. Yet, the effects of Zn excess on specific growth processes in the root tip remain largely unexplored. C_LIO_LITranscriptomics, ionomics and metabolomics were used to examine the specific impact of Zn excess on the root tip (RT) compared to the remaining root (RR). C_LIO_LIZn excess exposure resulted in shortened root apical meristem and elongation zone, with differentiation initiating closer to the tip of the root. Zn accumulated at a lower concentration in the RT than in RR. This pattern was associated with lower expression of Zn homeostasis and Fe deficiency response genes. C_LIO_LIA distinct distribution of Zn and Fe in RT and RR was highlighted by Laser Ablation ICP-MS analysis. C_LIO_LISpecialized Trp-derived metabolism genes, typically associated with redox and biotic stress responses, were specifically up-regulated in the RT upon Zn excess, among those Phytoalexin Deficient 3 (PAD3) encoding the last enzyme of camalexin synthesis. In roots of wild-type seedlings, camalexin concentration increased by 6-fold upon Zn excess and a pad3 mutant displayed increased Zn sensitivity and an altered ionome. C_LIO_LIOur results indicate that distinct redox and iron homeostasis mechanisms are key elements of the response to Zn excess in the RT. C_LI

plant biology↗

bioRxiv2024

A multi-omics analysis of Arabidopsis thaliana root tips under Cd exposure: A role of HY5 in limiting accumulation

O_LICadmium (Cd) is a major environmental pollutant with high toxicity potential. Even though a reduction of growth, including the primary root, is a clear consequence of Cd exposure, a profound understanding of the impact of Cd on the root apical meristem (RAM) and the elongation/differentiation zone (EDZ) is still lacking. C_LIO_LIIn this study, Arabidopsis thaliana roots were subjected to Cd and divided into root tips (RT) and remaining roots (RR) to separately assess the effect of Cd using transcriptomics, ionomics and metabolomics. C_LIO_LIElemental profiling revealed lower Cd accumulation in RT and differences in mineral contents between RT and RR. Transcriptomic analysis demonstrated distinct gene expression patterns in RT and RR, with Cd having less impact in RT. Functional enrichment analysis revealed genes associated with iron and sulfur homeostasis as well as the response to light in both RR and RT. RT-specific responses to Cd included several genes regulated by the transcription factor ELONGATED HYPOCOTYL 5 (HY5) and notably, the hy5 mutant showed increased Cd sensitivity and accumulation compared to the wild type. C_LIO_LIThis study provides comprehensive insights into the inhibitory effects of Cd on primary root growth, elucidating molecular mechanisms involved, particularly highlighting the role of HY5 in Cd accumulation. C_LI

plant biology↗

bioRxiv2023

Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification

Federated learning enables collaboration in medicine, where data is scattered across multiple centers without the need to aggregate the data in a central cloud. While, in general, machine learning models can be applied to a wide range of data types, graph neural networks (GNNs) are particularly developed for graphs, which are very common in the biomedical domain. For instance, a patient can be represented by a protein-protein interaction (PPI) network where the nodes contain the patient-specific omics features. Here, we present our Ensemble-GNN software package, which can be used to deploy federated, ensemble-based GNNs in Python. Ensemble-GNN allows to quickly build predictive models utilizing PPI networks consisting of various node features such as gene expression and/or DNA methylation. We exemplary show the results from a public dataset of 981 patients and 8469 genes from the Cancer Genome Atlas (TCGA).

bioinformatics↗

bioRxiv2023

Cysteine: an ancestral Cu binding ligand in green algae?

Growth of Chlamydomonas reinhardtii in zinc (Zn) limited medium leads to disruption of copper (Cu) homeostasis, resulting in up to 40-fold Cu over-accumulation relative to its typical Cu quota. We show that Chlamydomonas controls its Cu quota by balancing Cu import and export, which is disrupted in a Zn deficient cell, thus establishing a mechanistic connection between Cu and Zn homeostasis. Transcriptomics, proteomics and elemental profiling revealed that Zn-limited Chlamydomonas cells up-regulate a subset of genes encoding "first responder" proteins involved in sulfur (S) assimilation and consequently accumulate more intracellular S, which is incorporated into L-cysteine, {gamma}-glutamylcysteine and homocysteine. Most prominently, in the absence of Zn, free L-cysteine is increased ~80-fold, corresponding to ~ 2.8 x 109 molecules/cell. Interestingly, classic S-containing metal binding ligands like glutathione and phytochelatins do not increase. X-ray fluorescence microscopy showed foci of S accumulation in Zn-limited cells that co-localize with Cu, phosphorus and calcium, consistent with Cu-thiol complexes in the acidocalcisome, the site of Cu(I) accumulation. Notably, cells that have been previously starved for Cu do not accumulate S or Cys, causally connecting cysteine synthesis with Cu accumulation. We suggest that cysteine is an in vivo Cu(I) ligand, perhaps ancestral, that buffers cytosolic Cu.

biochemistry↗

bioRxiv2018

A curated list of genes that control elemental accumulation in plants.

Understanding the mechanisms underlying plants adaptation to their environment will require knowledge of the genes and alleles underlying elemental composition. Modern genetics is capable of quickly, and cheaply indicating which regions of DNA are associated with particular phenotypes in question, but most genes remain poorly annotated, hindering the identification of candidate genes. To help identify candidate genes underlying elemental accumulations, we have created the known ionome gene (KIG) list: a curated collection of genes experimentally shown to change uptake, accumulation, and distribution of elements. We have also created an automated computational pipeline to generate lists of KIG orthologs in other plant species using the PhytoMine database. The current version of KIG consists of 176 known genes covering 5 species, 23 elements and their 1588 orthologs in 10 species. Analysis of the known genes demonstrated that most were identified in the model plant Arabidopsis thaliana, and that transporter coding genes and genes altering the accumulation of iron and zinc are overrepresented in the current list.

plant biology↗