Biology subjects

Barth, P.

Publications and source records attributed to Barth, P..

5 recordsLinked to original sources

bioRxiv2021

Computational design of highly signaling active membrane receptors through de novo solvent-mediated allosteric networks

Protein catalysis and allostery require the atomic-level orchestration and motion of residues, ligand, solvent and protein effector molecules, but the ability to design protein activity through precise protein-solvent cooperative interactions has not been demonstrated. Here, we report the design of a dozen novel membrane receptors catalyzing G-protein nucleotide exchange through diverse de novo engineered allosteric pathways mediated by cooperative networks of intra-protein, protein-ligand and solvent molecule interactions. Consistent with the predictions, designed protein activities strongly correlated with the level of solvent-mediated interaction network plasticity at flexible transmembrane helical interfaces. Several designs displayed considerably enhanced thermostability and activity compared to related natural receptors. The most stable and active variant crystallized in an unforeseen signaling active conformation, in excellent agreement with the design models. The allosteric network topologies of the best designs bear limited similarity to those of natural receptors and reveal a space of allosteric interactions larger than previously inferred from natural proteins. The approach should prove useful for engineering proteins with novel complex protein catalytic and signaling activities.

biophysics↗

bioRxiv2021

Computationally-guided tuning of ligand sensitivity in a GPCR-based sensor

Genetically-encoded fluorescent sensors for neuromodulators are increasingly used molecular tools in neuroscience. However, these protein-based biosensors are often limited by the sensitivity of the protein scaffold towards endogenous ligands. Here, we explored the possibility of applying computational design approaches for enhancing sensor sensitivity. Using the dopamine sensor dLight1 as proof of concept, we designed two variants that boost the sensors potency (EC50) for dopamine and norepinephrine by up to 5- and 15-fold, respectively. Interestingly, the largest effects were obtained through improved designed allosteric transmission in the transmembrane region of the sensor. Our approach should prove generally useful for enhancing sensing capabilities of a large variety of neuromodulator sensors.

bioengineering↗

bioRxiv2021

Computationally designed GPCR quaternary structures bias signaling pathway activation

Communication across membranes controls critical cellular processes and is achieved by receptors translating extracellular signals into selective cytoplasmic responses. While receptor tertiary structures can now be readily characterized, receptor associations into quaternary structures are very challenging to study and their implications in signal transduction remain poorly understood. Here, we report a computational approach for predicting membrane receptor self-associations, and designing receptor oligomers with various quaternary structures and signaling properties. Using this approach, we designed chemokine receptor CXCR4 dimers with reprogrammed stabilities, conformations, and abilities to activate distinct intracellular signaling proteins. In agreement with our predictions, the designed CXCR4s dimerized through distinct conformations and displayed different quaternary structural changes upon activation. Consistent with the active state models, all engineered CXCR4 oligomers activated the G protein Gi, but only a few specific dimer structures also recruited {beta}-arrestins. Overall, we demonstrate that quaternary structures represent an important unforeseen mechanism of receptor biased signaling and reveal the existence of a conformational switch at the dimer interface of several G protein-coupled receptors including CXCR4, mu-Opioid and type-2 Vasopressin receptors that selectively control the activation of G proteins vs {beta}-arrestin-mediated pathways. The approach should prove useful for predicting and designing receptor associations to uncover and reprogram selective cellular signaling functions.

biophysics↗

bioRxiv2021

Isolation and characterization of barley (Hordeum vulgare) extracellular vesicles and their role in RNAi-based crop protection

The demonstration that spray-induced gene silencing (SIGS) can confer strong disease resistance bypassing the laborious and time-consuming transgenic expression of double-stranded (ds)RNA to induce gene silencing of pathogenic targets was groundbreaking. However, future field applications will require fundamental mechanistic knowledge on dsRNA uptake, processing, and its transfer. There is increasing evidence that extracellular vesicles (EVs) mediate the transfer of transgene-derived small interfering (si)RNAs in host-induced gene silencing (HIGS) applications. Here, we examined the role of EVs regarding the translocation of sprayed dsRNA from barley (Hordeum vulgare) to the target fungus Fusarium graminearum. We found barley EVs with 156 nm in size containing predominantly 21 and 19 nucleotide (nt) siRNAs starting with a 5-terminal Adenine. Notably, barley EVs contain less siRNA compared to EVs isolated from transgenic HIGS Arabidopsis plants. Together our results further underpin mechanistic differences between HIGS and SIGS applications and a minor role of EVs in SIGS.

plant biology↗

bioRxiv2020

Platon: identification and characterization of bacterial plasmid contigs in short-read draft assembliesexploiting protein-sequence-based replicon distribution scores

Plasmids are extrachromosomal genetic elements replicating independently of the chromosome which play a vital role in the environmental adaptation of bacteria. Due to potential mobilization or conjugation capabilities, plasmids are important genetic vehicles for antimicrobial resistance genes and virulence factors with huge and increasing clinical implications. They are therefore subject to large genomic studies within the scientific community worldwide. As a result of rapidly improving next generation sequencing methods, the amount of sequenced bacterial genomes is constantly increasing, in turn raising the need for specialized tools to (i) extract plasmid sequences from draft assemblies, (ii) derive their origin and distribution, and (iii) further investigate their genetic repertoire. Recently, several bioinformatic methods and tools have emerged to tackle this issue; however, a combination of both high sensitivity and specificity in plasmid sequence identification is rarely achieved in a taxon-independent manner. In addition, many software tools are not appropriate for large high-throughput analyses or cannot be included into existing software pipelines due to their technical design or software implementation. In this study, we investigated differences in the replicon distributions of protein-coding genes on a large scale as a new approach to distinguish plasmid-borne from chromosome-borne contigs. We defined and computed statistical discrimination thresholds for a new metric: the replicon distribution score (RDS) which achieved an accuracy of 96.6%. The final performance was further improved by the combination of the RDS metric with heuristics exploiting several plasmid specific higher-level contig characterizations. We implemented this workflow in a new high-throughput taxon-independent bioinformatics software tool called Platon for the recruitment and characterization of plasmid-borne contigs from short-read draft assemblies. Compared to PlasFlow, Platon achieved a higher accuracy (97.5%) and more balanced predictions (F1=82.6%) tested on a broad range of bacterial taxa and better or equal performance against the targeted tools PlasmidFinder and PlaScope on sequenced E. coli isolates. Platon is available at: platon.computational.bio Data SummaryO_LIPlaton was developed as a Python 3 command line application for Linux. C_LIO_LIThe complete source code and documentation is available on GitHub under a GPL3 license: https://github.com/oschwengers/platon and platon.computational.bio. C_LIO_LIAll database versions are hosted at Zenodo: DOI 10.5281/zenodo.3349651. C_LIO_LIPlaton is available via bioconda package platon C_LIO_LIPlaton is available via PyPI package cb-platon C_LIO_LIBacterial representative sequences for UniProts UniRef90 protein clusters, complete bacterial genome sequences from the NCBI RefSeq database, complete plasmid sequences from the NCBI genomes plasmid section, created artificial contigs, RDS threshold metrics and raw protein replicon hit counts used to create and evaluate the marker protein sequence database are hosted at Zenodo: DOI 10.5281/zenodo.3759169 C_LIO_LI24 Escherichia coli isolates sequenced with short read (Illumina MiSeq) and long read sequencing technologies (Oxford Nanopore Technology GridION platform) used for real data benchmarks are available under the following NCBI BioProjects: PRJNA505407, PRJNA387731 C_LI Impact StatementPlasmids play a vital role in the spread of antibiotic resistance and pathogenicity genes. The increasing numbers of clinical outbreaks involving resistant pathogens worldwide pushed the scientific community to increase their efforts to comprehensively investigate bacterial genomes. Due to the maturation of next-generation sequencing technologies, nowadays entire bacterial genomes including plasmids are sequenced in huge scale. To analyze draft assemblies, a mandatory first step is to separate plasmid from chromosome contigs. Recently, many bioinformatic tools have emerged to tackle this issue. Unfortunately, several tools are implemented only as interactive or web-based tools disabling them for necessary high-throughput analysis of large data sets. Other tools providing such a high-throughput implementation however often come with certain drawbacks, e.g. providing taxon-specific databases only, not providing actionable, i.e. true binary classification or achieving biased classification performances towards either sensitivity or specificity. Here, we introduce the tool Platon implementing a new replicon distribution-based approach combined with higher-level contig characterizations to address the aforementioned issues. In addition to the plasmid detection within draft assemblies, Platon provides the user with valuable information on certain higher-level contig characterizations. We show that Platon provides a balanced classification performance as well as a scalable implementation for high-throughput analyses. We therefore consider Platon to be a powerful, species-independent and flexible tool to scan large amounts of bacterial whole-genome sequencing data for their plasmid content.

bioinformatics↗