Biology subjects

Gall, A.

Publications and source records attributed to Gall, A..

6 recordsLinked to original sources

bioRxiv2022

Single Pixel Reconstruction Imaging: taking confocal imaging to the extreme

Light nanoscopy is attracting widespread interest for the visualization of fluorescent structures at the nanometer scale, especially in cellular biology. To achieve nanoscale resolution, one has to surpass the diffraction limit--a fundamental phenomenon determining the spot size of focused light. Recently, a variety of methods have overcome this limit, yet in practice they are often constrained by the requirement of special fluorophores, nontrivial data processing, or high price and complex implementation. For this reason, confocal fluorescence microscopy that yields relatively low resolution is still the dominant method in biomedical sciences. It was shown that image scanning microscopy (ISM) with an array detector instead of a point detector could improve the resolution of confocal microscopy. Here we review the principles of the confocal microscopy and present a simple method based on ISM with a different image reconstruction approach, which can be easily implemented in any camera-based laser-scanning set-up to experimentally obtain the theoretical resolution limit of the confocal microscopy. Our method, Single Pixel Reconstruction Imaging (SPiRI) enables high-resolution 3D imaging utilizing image formation only from a single pixel of each of the recorded frames. We achieve experimental axial resolution of 330 nm, which was not shown before by basic confocal or ISM-based systems. Contrary to the majority of techniques, SPiRI method exhibits a low lateral-to-axial FWHM aspect ratio, which means a considerable improvement in 3D fluorescence imaging of cellular structures. As a demonstration of SPiRI application in biomedical sciences, we present a 3D structure of bacterial chromosome with excellent precision.

biophysics↗

bioRxiv2022

Manganese excess and deficiency affects photosynthesis and metabolism in Marchantia polymorpha

Manganese is an essential metal for plant growth. The most important Mn-containing enzyme is the Mn4CaO5 cluster that catalyses water oxidation in Photosystem II. Mn deficiency primarily affects photosynthesis, while Mn excess is generally toxic. Mn excess and deficiency were studied in the liverwort Marchantia polymorpha, an emerging model ideally suited for analysis of metal stress since it accumulates rapidly toxic substances due to the absence of well-developed vascular and radicular systems and a reduced cuticle. We established growth conditions for Mn excess and deficiency, performed analysis of metal content in thalli and isolated chloroplasts and determined metabolites. Metabolome analysis revealed a strong accumulation of N-methylalanine upon exposure to Mn excess and a different response of Marchantia to heavy metal stress than that known for higher plants. We investigated photosynthetic performance by chlorophyll fluorescence at room temperature and at 77K, P700 absorption and by studying the susceptibility of thalli to photoinhibition. In vivo super-resolution fluorescence microscopy was used to visualize changes in the organization of the thylakoid membrane under Mn excess and deficiency. Non-optimal Mn concentrations changed the ratio of photosystem I to photosystem II and altered the organisation of thylakoid membranes. Mn deficiency seems to favour cyclic electron flow around photosystem I protecting thereby photosystem II against photoinhibition.

plant biology↗

bioRxiv2020

The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data

The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser, incorporating a new Ensembl gene set, multiple variant sets (including novel variation calls), and annotation from several relevant resources integrated into the reference SARS-CoV-2 assembly. This work included key adaptations of existing Ensembl genome annotation methods to model ribosomal slippage, stringent filters to elucidate the highest confidence variants and utilisation of our comparative genomics pipelines on viruses for the first time. Since May 2020, the content has been regularly updated and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.

bioinformatics↗

bioRxiv2020

Midbrain dopaminergic inputs gate amygdala intercalated cell clusters by distinct and cooperative mechanisms

AO_SCPLOWBSTRACTC_SCPLOWDopaminergic signaling plays an important role in associative learning including fear and extinction learning. Dopaminergic midbrain neurons encode prediction error-like signals when threats differ from expectations. Within the amygdala, GABAergic intercalated cell (ITC) clusters receive the densest dopaminergic projections, but their physiological consequences are incompletely understood. ITCs are important for fear extinction, a function thought to be supported by activation of ventromedial cluster ITCs that inhibit central amygdala fear output. In mice, we reveal two distinct mechanisms how mesencephalic dopaminergic afferents control ITCs. Firstly, they co-release GABA to mediate rapid, direct inhibition. Secondly, dopamine suppresses inhibitory interactions between distinct ITC clusters via presynaptic D1-receptors. Early extinction training augments both, GABA co-release onto dorso-medial ITCs and dopamine-mediated suppression of dorso- to ventromedial inhibition between ITC clusters. These findings provide novel insights into dopaminergic mechanisms shaping the activity balance between distinct ITC clusters that could support their opposing roles in fear behavior.

neuroscience↗

bioRxiv2017

PHYLOSCANNER: Analysing Within- and Between-Host Pathogen Genetic Diversity to Identify Transmission, Multiple Infection, Recombination and Contamination

A central feature of pathogen genomics is that different infectious particles (virions, bacterial cells, etc.) within an infected individual may be genetically distinct, with patterns of relatedness amongst infectious particles being the result of both within-host evolution and transmission from one host to the next. Here we present a new software tool, phyloscanner, which analyses pathogen diversity from multiple infected hosts. phyloscanner provides unprecedented resolution into the transmission process, allowing inference of the direction of transmission from sequence data alone. Multiply infected individuals are also identified, as they harbour subpopulations of infectious particles that are not connected by within-host evolution, except where recombinant types emerge. Low-level contamination is flagged and removed. We illustrate phyloscanner on both viral and bacterial pathogens, namely HIV-1 sequenced on Illumina and Roche 454 platforms, HCV sequenced with the Oxford Nanopore MinION platform, and Streptococcus pneumoniae with sequences from multiple colonies per individual. phyloscanner is available from https://github.com/BDI-pathogens/phyloscanner.

evolutionary biology↗

bioRxiv2016

Easy and Accurate Reconstruction of Whole HIV Genomes from Short-Read Sequence Data

Next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of rapid between- and within-host evolution may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by effectively aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to preprocess reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We use shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read data produced with the Illumina platform, for 65 existing publicly available samples and 50 new samples. We show the systematic superiority of mapping to shivers constructed reference over mapping the same reads to the standard reference HXB2: an average of 29 bases per sample are called differently, of which 98.5% are supported by higher coverage. We also provide a practical guide to working with imperfect contigs.

bioinformatics↗