Biology subjects

Wenzel, M.

Publications and source records attributed to Wenzel, M..

26 records · Page 2Linked to original sources

bioRxiv2019

New flat embedding method for transmission electron microscopy reveals an unknown mechanism of tetracycline

Transmission electron microscopy (TEM) is an important imaging technique in bacterial research and requires ultrathin sectioning of resin embedding of cell pellets. This method consumes milli- to deciliters of culture and results in sections of randomly orientated cells. For rod-shaped bacteria, this makes it exceedingly difficult to find longitudinally cut cells, which precludes large-scale quantification of morphological phenotypes. Here, we describe a new fixation method using either thin agarose layers or carbon-coated glass surfaces that enables flat embedding of bacteria. This technique allows for the observation of thousands of longitudinally cut rod-shaped cells per single section and requires only microliter culture volumes. We successfully applied this technique to Gram-positive Bacillus subtilis, Gram-negative Escherichia coli, the tuberculosis vaccine strain Mycobacterium bovis BCG, and the cell wall-lacking mycoplasma Acholeplasma laidlawii. To assess the potential of the technique to quantify morphological phenotypes, we examined cellular changes induced by a panel of different antibiotics. Surprisingly, we found that the ribosome inhibitor tetracycline causes significant deformations of the cell membrane. Further investigations showed that the presence of tetracycline in the cell membrane changes membrane organization and affects the peripheral membrane proteins MinD, MinC, and MreB, which are important for regulation of cell division and elongation. Importantly, we could show that this effect is not the result of ribosome inhibition but is a secondary antibacterial activity of tetracycline that has defied discovery for more than 50 years.\n\nSignificanceBacterial antibiotic resistance is a serious public health problem and novel antibiotics are urgently needed. Before a new antibiotic can be brought to the clinic, its antibacterial mechanism needs to be elucidated. Transmission electron microscopy is an important tool to investigate these mechanisms. We developed a flat embedding method that enables examination of many more bacterial cells than classical protocols, enabling large-scale quantification of phenotypic changes. Flat embedding can be adapted to most growth conditions and microbial species and can be employed in a wide variety of microbiological research fields. Using this technique, we show that even well-established antibiotics like tetracycline can have unknown additional antibacterial activities, demonstrating how flat embedding can contribute to finding new antibiotic mechanisms.

microbiology↗

bioRxiv2019

USMPep: Universal Sequence Models for Major Histocompatibility Complex Binding Affinity Prediction

BackgroundImmunotherapy is a promising route towards personalized cancer treatment. A key algorithmic challenge in this process is to decide if a given peptide (neoepitope) binds with the major histocompatibility complex (MHC). This is an active area of research and there are many MHC binding prediction algorithms that can predict the MHC binding affinity for a given peptide to a high degree of accuracy. However, most of the state-of-the-art approaches make use of complicated training and model selection procedures, are restricted to peptides of a certain length and/or rely on heuristics.\n\nResultsWe put forward USMPep, a simple recurrent neural network that reaches state-of-the-art approaches on MHC class I binding prediction with a single, generic architecture and even a single set of hyperparameters both on IEDB benchmark datasets and on the very recent HPV dataset. Moreover, the algorithm is competitive for a single model trained from scratch, while ensembling multiple regressors and language model pretraining can still slightly improve the performance. The direct application of the approach to MHC class II binding prediction shows a solid performance despite of limited training data.\n\nConclusionsWe demonstrate that competitive performance in MHC binding affinity prediction can be reached with a standard architecture and training procedure without relying on any heuristics.

immunology↗

bioRxiv2019

Control of septum thickness by a large protein ring

Gram-positive bacteria divide by forming a thick cross wall. How the thickness of this septal wall is controlled is unknown. In this type of bacteria, the key cell division protein FtsZ is anchored to the cell membrane by two proteins, FtsA and SepF. We have isolated SepF homologues from different bacterial species and found that they all polymerize into large protein rings with diameters varying from 19 to 41 nm. Importantly, these values correlated well with the thickness of their septa. To test whether ring diameter determines septal thickness, we tried to construct different SepF chimeras with the purpose to manipulate the diameter of the SepF protein ring. This was indeed possible and confirmed that the conserved core domain of SepF determines ring diameter. Importantly, when SepF chimeras with a smaller diameter were expressed in the bacterial host Bacillus subtilis, the thickness of its septa also became smaller. These results strongly support a model in which septal thickness is controlled by curved molecular clamps formed by SepF polymers attached to the leading edge of nascent septa. This also implies that the intrinsic shape of a protein polymer can function as a mould to shape the cell wall. Significance StatementMany bacteria form a thick cell wall and divide by forming a cross wall. How they control the thickness of their cell wall and cross wall is unknown. In this study we show that in these bacteria the cell division protein SepF forms very large protein rings with diameters that correspond to the diameter of their cross walls. Importantly, when we reduced the diameter of SepF rings in the bacterial host Bacillus subtilis the cross wall also became thinner. These results provide strong evidence that a large protein ring can function as a mould to control the thickness of the cell wall that divides these bacterial cells.

microbiology↗

bioRxiv2019

Adaptations of energy metabolism in cetaceans have consequences for their response to foraging disruption

Cetaceans have varied their anatomical structure, physiology and metabolism to adapt to the challenges of aquatic life. Key to this change is the deposition of blubber. This adipose tissue plays a significant regulatory and signaling role in mammalian metabolism. As foraging disruption by human activities is emerging as a key conservation threat for cetaceans, we need to understand how selection for aquatic life might have altered key nutrient sensing pathways associated with adipose signaling. We compared selection pressure on those energy metabolism biological pathways by contrasting the rate of substitution observed in genes associated with them in cetacean and artiodactyl genomes. We then estimated the likely consequence of these selection pressures for pathway functions. Here we show that genes involved in the insulin, mTOR, SIRT and NF-{kappa}B pathways were under significant positive selection in cetaceans compared to their terrestrial sister taxon. Our results suggest these genes may have been positively selected to adapt to a glucose-poor diet and it is unlikely that fat depots signaling function in the same manner as in terrestrial mammals. Secondary adaptation to life in water significantly affected functions in nutrient sensing pathways in cetaceans. Insulin is not likely to play the same role in energy balance as it does in terrestrial mammals and adiposity is not likely to have the deleterious health consequences it has in terrestrial mammals. The physiological ecology of cetacean fat deposition, and therefore its value as a condition index, needs to be interpreted in this evolutionary context.

evolutionary biology↗

bioRxiv2019

Universal Deep Sequence Models for Protein Classification

MotivationInferring the properties of a protein from its amino acid sequence is one of the key problems in bioinformatics. Most state-of-the-art approaches for protein classification tasks are tailored to single classification tasks and rely on handcrafted features such as position-specific-scoring matrices from expensive database searches. We argue that this level of performance can be reached or even be surpassed by learning a task-agnostic representation once, using self-supervised language modeling, and transferring it to specific tasks by a simple finetuning step.\n\nResultsWe put forward a universal deep sequence model that is pretrained on unlabeled protein sequences from Swiss-Prot and finetuned on protein classification tasks. We apply it to three prototypical tasks, namely enzyme class prediction, gene ontology prediction and remote homology and fold detection. The proposed method performs on par with state-of-the-art algorithms that were tailored to these specific tasks or, for two out of three tasks, even outperforms them. These results stress the possibility of inferring protein properties from the sequence alone and, on more general grounds, the prospects of modern natural language processing methods in omics.\n\nAvailabilitySource code is available under https://github.com/nstrodt/UDSMProt.\n\nContactfirstname.lastname@hhi.fraunhofer.de

synthetic biology↗

bioRxiv2018

Reduced repertoire of cortical microstates and neuronal ensembles in medically-induced loss of consciousness

Medically-induced loss of consciousness (mLOC) has been linked to a macroscale break-down of brain connectivity, yet the neural microcircuit correlates of mLOC remain unknown. We applied non-linear t-stochastic neighbor embedding (t-SNE) and Lempel-Ziv-Welch complexity analysis to two-photon calcium imaging and local field potential (LFP) measurements of cortical microcircuit activity across anesthetic depth in mice, and to micro-electrode array recordings in human subjects. We find that mLOC disrupts population activity patterns by i) a reduction of discriminable network microstates and ii) a reduction of independent neuronal ensembles. These alterations are not explained by a simple reduction of neuronal activity and reveal abnormal functional microcircuits. Thus, normal neuronal ensemble dynamics could contribute to the emergence of conscious states.

neuroscience↗

bioRxiv2018

Seizures start as silent microseizures by neuronal ensembles

Understanding seizure formation and spread remains a critical goal of epilepsy research. While many studies have documented seizure spread, it remains mysterious how they start. We used fast in-vivo two-photon calcium imaging to reconstruct, at cellular resolution, the dynamics of focal cortical seizures as they emerge in epileptic foci (intrafocal), and subsequently propagate (extrafocal). We find that seizures start as intrafocal coactivation of small numbers of neurons (ensembles), which are electrographically silent. These silent \"microseizures\" expand saltatorily until they break into neighboring cortex, where they progress smoothly and first become detectable by LFP. Surprisingly, we find spatially heterogeneous calcium dynamics of local PV interneuron sub-populations, which rules out a simple role of inhibitory neurons during seizures. We propose a two-step model for the circuit mechanisms of focal seizures, where neuronal ensembles first generate a silent microseizure, followed by widespread neural activation in a travelling wave, which is then detected electrophysiologically.

neuroscience↗

bioRxiv2017

Role of inhibitory control in modulating spread of focal ictal activity

Focal seizure propagation is classically thought to be spatially contiguous. However, distribution of seizures through a large-scale epileptic network has been theorized. Here, we used a multielectrode array, wide field calcium imaging, and two-photon calcium imaging to study focal seizure propagation pathways in an acute rodent neocortical 4-aminopyridine model. Although ictal neuronal bursts did not propagate beyond a 2-3 mm region, they were associated with hemisphere-wide field potential fluctuations and parvalbumin-positive interneuron activity outside the seizure focus. While bicuculline surface application enhanced contiguous seizure propagation, focal bicuculline microinjection at sites distant to the 4-aminopyridine focus resulted in epileptic network formation with maximal activity at the two foci. Our study suggests that both classical and epileptic network propagation can arise from localized inhibition defects, and that the network appearance can arise in the context of normal brain structure without requirement for pathological connectivity changes between sites.

neuroscience↗