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Biology subjects

Lukes, T.

Publications and source records attributed to Lukes, T..

8 recordsLinked to original sources

DynaMAP: Dynamic Microbiome Abundance Profiling through high density optical mapping

Microbial abundance profiling is rapidly becoming an essential method in biomedical research, though it is often costly and time intensive. We present DynaMAP, a rapid approach for microbiome profiling that uses single-molecule imaging to develop an optical map of metagenomic DNA. DynaMAP achieves strain-level taxonomic profiling without requiring base-by-base sequencing and with a one-day turnaround time. In doing so, it delivers microbiome profiling that is comparable to shotgun sequencing but operates more efficiently, strongly expanding the possibility for microbiome analysis.

microbiology↗

Commitment to cytokinetic furrowing requires the coordinate activity of microtubules and Plk1

At anaphase, spindle microtubules (MTs) position the cleavage furrow and trigger actomyosin assembly by localizing the small GTPase RhoA and the scaffolding protein anillin to a narrow band along the equatorial cortex [1-6]. Using vertebrate somatic cells we examined the temporal control of furrow assembly. Although its positioning commences at anaphase onset, furrow maturation is not complete until [~]10-11 min later. The maintenance of the RhoA/anillin scaffold initially requires continuous signaling from the spindle; loss of either MTs or polo-like kinase 1 (Plk1) activity prevents proper RhoA/anillin localization to the equator, thereby disrupting furrowing. However, we find that at [~]6 min post-anaphase, the cortex becomes "committed to furrowing"; loss of either MTs or Plk1 after this stage does not prevent eventual furrowing, even though at this point the contractile apparatus has not fully matured. Also at this stage, the RhoA/anillin scaffold at the equator becomes permanent. Surprisingly, concurrent loss of both MTs and Plk1 activity following the "commitment to furrowing" stage results in persistent, asymmetric "half-furrows", with only one cortical hemisphere retaining RhoA/anillin, and undergoing ingression. This phenotype is reminiscent of asymmetric furrows caused by a physical block between spindle and cortex [7-9], or by acentric spindle positioning [10-12]. The formation of these persistent "half-furrows" suggests a potential feedback mechanism between the spindle and the cortex that maintains cortical competency along the presumptive equatorial region prior to the "commitment to furrowing" stage of cytokinesis, thereby ensuring the eventual ingression of a symmetric cleavage furrow.

cell biology↗

OpenSIM: open source microscope add-on for structured illumination microscopy

Super-resolution techniques expand the abilities of researchers who have the knowledge and resources to either build or purchase a system. This excludes the part of the research community without these capabilities. Here we introduce the openSIM add-on to upgrade existing optical microscopes to Structured Illumination super-resolution Microscopes (SIM). The openSIM is an open-hardware system, designed and documented to be easily duplicated by other laboratories, making super-resolution modality accessible to facilitate innovative research. The add-on approach gives a performance improvement for pre-existing lab equipment without the need to build a completely new system.

bioengineering↗

High speed multi-plane super-resolution structured illumination microscopy of living cells using an image-splitting prism

Super-resolution structured illumination microscopy (SR-SIM) can be conducted at video-rate acquisition speeds when combined with high-speed spatial light modulators and sCMOS cameras, rendering it particularly suitable for live cell imaging. If, however, three-dimensional (3D) information is desired, the sequential acquisition of vertical image stacks employed by current setups significantly slows down the acquisition process. In this work we present a multi-plane approach to SR-SIM that overcomes this slowdown via the simultaneous acquisition of multiple object planes, employing a recently introduced multi-plane image splitting prism combined with high-speed SR-SIM illumination. This strategy requires only the introduction of a single optical element and the addition of a second camera to acquire a laterally super-resolved three-dimensional image stack. We demonstrate the performance of multi-plane SR-SIM by applying this instrument to the dynamics of live mitochondrial network.

biophysics↗

Identifying microbial species by single-molecule DNA optical mapping and resampling statistics

Single molecule DNA mapping has the potential to serve as a powerful complement to high-throughput sequencing in metagenomic analysis. Offering longer read lengths and forgoing the need for complex library preparation and amplification, mapping stands to provide an unbiased view into the composition of complex viromes and/or microbiomes. To fully enable mapping-based metagenomics, sensitivity and specificity of DNA map analysis and identification need to be improved. Using detailed simulations and experimental data, we first demonstrate how fluorescence imaging of surface stretched, sequence specifically labeled DNA fragments can yield highly sensitive identification of targets. Secondly, a new analysis technique is introduced to increase specificity of the analysis, allowing even closely related species to be resolved. Thirdly, we show how an increase in resolution improves sensitivity. Finally, we demonstrate that these methods are capable of identifying species with long genomes such as bacteria with high sensitivity.

genomics↗

Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction

BackgroundStructured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution).\n\nFindingsFive complete and freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods, and with newer Bayesian restoration approaches which we are developing.\n\nConclusionVarious methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments is not typically published. Publicly available, high quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data was processed with SIMToolbox, an open source and freely available software solution for SIM.

biophysics↗

Super-resolution fight club: A broad assessment of 2D & 3D single-molecule localization microscopy software

With the widespread uptake of 2D and 3D single molecule localization microscopy, a large set of different data analysis packages have been developed to generate super-resolution images. To guide researchers on the optimal analytical software for their experiments, we have designed, in a large community effort, a competition to extensively characterise and rank these options. We generated realistic simulated datasets for popular imaging modalities - 2D, astigmatic 3D, biplane 3D, and double helix 3D - and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D single molecule localization microscopy software, provides a holistic view of how the latest 2D and 3D single molecule localization software perform in realistic conditions, and ultimately provides insight into the current limits of the field.

biophysics↗

Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors

BackgroundSuper-resolution single molecule localization microscopy (SMLM) is a method for achieving resolution beyond the classical limit in optical microscopes (approx. 200 nm laterally). Yellow fluorescent protein (YFP) has been used for super-resolution single molecule localization microscopy, but less frequently than other fluorescent probes. Working with YFP in SMLM is a challenge because a lower number of photons are emitted per molecule compared to organic dyes which are more commonly used. Publically available experimental data can facilitate development of new data analysis algorithms.\n\nFindingsFour complete, freely available single molecule super-resolution microscopy datasets on YFP-tagged growth factor receptors expressed in a human cell line are presented including both raw and analyzed data. We report methods for sample preparation, for data acquisition, and for data analysis, as well as examples of the acquired images. We also analyzed the SMLM data sets using a different method: super-resolution optical fluctuation imaging (SOFI). The two modes of analysis offer complementary information about the sample. A fifth single molecule super-resolution microscopy dataset acquired with the dye Alexa 532 is included for comparison purposes.\n\nConclusionThis dataset has potential for extensive reuse. Complete raw data from SMLM experiments has typically not been published. The YFP data exhibits low signal to noise ratios, making data analysis a challenge. These data sets will be useful to investigators developing their own algorithms for SMLM, SOFI, and related methods. The data will also be useful for researchers investigating growth factor receptors such as ErbB3.

bioinformatics↗