High Resolution Intravital Imaging of Subcellular Structures of Mouse Abdominal Organs Using a Microstage Device

Intravital imaging of brain and bone marrow cells in the skull with subcellular resolution has revolutionized neurobiology, immunology and hematology. However, the application of this powerful technology in studies of abdominal organs has long been impeded by organ motion caused by breathing and heartbeat. Here we describe for the first time a simple device designated ‘microstage’ that effectively reduces organ motions without causing tissue lesions. Combining this microstage device with an upright intravital laser scanning microscope equipped with a unique stick-type objective lens, the system enables subcellular-level imaging of abdominal organs in live mice. We demonstrate that this technique allows for the quantitative analysis of subcellular structures and gene expressions in cells, the tracking of intracellular processes in real-time as well as three-dimensional image construction in the pancreas and liver of the live mouse. As the aforementioned analyses based on subcellular imaging could be extended to other intraperitoneal organs, the technique should offer great potential for investigation of physiological and disease-specific events of abdominal organs. The microstage approach adds an exciting new technique to the in vivo imaging toolbox

DNA methylation on N6-adenine in mammalian embryonic stem cells

It has been widely accepted that 5-methylcytosine is the only form of DNA methylation in mammalian genomes. Here we identify N6-methyladenine as another form of DNA modification in mouse embryonic stem cells. Alkbh1 encodes a demethylase for N6-methyladenine. An increase of N6-methyladenine levels in Alkbh1-deficient cells leads to transcriptional silencing. N6-methyladenine deposition is inversely correlated with the evolutionary age of LINE-1 transposons; its deposition is strongly enriched at young (6 million years old) L1 elements. The deposition of N6-methyladenine correlates with epigenetic silencing of such LINE-1 transposons, together with their neighbouring enhancers and genes, thereby resisting the gene activation signals during embryonic stem cell differentiation. As young full-length LINE-1 transposons are strongly enriched on the X chromosome, genes located on the X chromosome are also silenced. Thus, N6-methyladenine developed a new role in epigenetic silencing in mammalian evolution distinct from its role in gene activation in other organisms. Our results demonstrate that N6-methyladenine constitutes a crucial component of the epigenetic regulation repertoire in mammalian genomes

Computational optical imaging with a photonic lantern

[EN] The thin and flexible nature of optical fibres often makes them the ideal technology to view biological processes in-vivo, but current microendoscopic approaches are limited in spatial resolution. Here, we demonstrate a route to high resolution microendoscopy using a multicore fibre (MCF) with an adiabatic multimode-to-single-mode "photonic lantern" transition formed at the distal end by tapering. We show that distinct multimode patterns of light can be projected from the output of the lantern by individually exciting the single-mode MCF cores, and that these patterns are highly stable to fibre movement. This capability is then exploited to demonstrate a form of single-pixel imaging, where a single pixel detector is used to detect the fraction of light transmitted through the object for each multimode pattern. A custom computational imaging algorithm we call SARA-COIL is used to reconstruct the object using only the pre-measured multimode patterns themselves and the detector signals.This work was funded through the "Proteus" Engineering and Physical Sciences Research Council (EPSRC) Interdisciplinary Research Collaboration (IRC) (EP/K03197X/1), by the Science and Technology Facilities Council (STFC) through STFC-CLASP grants ST/K006509/1 and ST/K006460/1, STFC Consortium grants ST/N000625/1 and ST/N000544/1. S.L. acknowledges support from the National Natural Science Foundation of China under Grant no. 61705073. DBP acknowledges support from the Royal Academy of Engineering, and the European Research Council (PhotUntangle, 804626). The authors thank Philip Emanuel for the use of his confocal image of A549 cells and Eckhardt Optics for their image of the USAF 1951 target. The authors sincerely thank the anonymous reviewers of this paper for their detailed and considered feedback which helped us to improve the quality of this paper significantly.Choudhury, D.; Mcnicholl, DK.; Repetti, A.; Gris-Sánchez, I.; Li, S.; Phillips, DB.; Whyte, G.... (2020). Computational optical imaging with a photonic lantern. Nature Communications. 11(1):1-9. https://doi.org/10.1038/s41467-020-18818-6S19111Wood, H. A. C., Harrington, K., Birks, T. A., Knight, J. C. & Stone, J. M. High-resolution air-clad imaging fibers. Opt. Lett. 43, 5311–5314 (2018).Akram, A. R. et al. In situ identification of Gram-negative bacteria in human lungs using a topical fluorescent peptide targeting lipid A. Sci. Transl. Med. 10, eaal0033 (2018).Shin, J., Bosworth, B. T. & Foster, M. A. Compressive fluorescence imaging using a multi-core fiber and spatially dependent scattering. Opt. Lett. 42, 109–112 (2017).Papadopoulos, I. N., Farahi, S., Moser, C. & Psaltis, D. Focusing and scanning light through a multimode optical fiber using digital phase conjugation. Opt. Express 20, 10583–10590 (2012).Čižmár, T. & Dholakia, K. Exploiting multimode waveguides for pure fibre-based imaging. Nat. Commun. 3, 1027 (2012).Plöschner, M., Tyc, T. & Čižmár, T. Seeing through chaos in multimode fibres. Nat. Photon. 9, 529–535 (2015).Birks, T. A., Gris-Sánchez, I., Yerolatsitis, S., Leon-Saval, S. G. & Thomson, R. R. The photonic lantern. Adv. Opt. Photon. 7, 107–167 (2015).Birks, T. A., Mangan, B. J., Díez, A., Cruz, J. L. & Murphy, D. F. Photonic lantern’ spectral filters in multi-core fiber. Opt. Express 20, 13996–14008 (2012).Edgar, M. P., Gibson, G. M. & Padgett, M. J. Principles and prospects for single-pixel imaging. Nat. Photon. 13, 13–20 (2019).Mahalati, R. N., Yu, Gu. R. & Kahn, J. M. Resolution limits for imaging through multi-mode fiber. Opt. Express 21, 1656–1668 (2013).Amitonova, L. V. & de Boer, J. F. Compressive imaging through a multimode fiber. Opt. Lett. 43, 5427–5430 (2018).Mallat, S. A Wavelet Tour of Signal Processing 2nd edn (Academic Press, Burlington, MA, 2009).Lustig, M., Donoho, D. & Pauly, J. M. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn. Reson. Med. 58, 1182–1195 (2007).Davies, M., Puy, G., Vandergheynst, P. & Wiaux, Y. A compressed sensing framework for magnetic resonance fingerprinting. SIAM J. Imaging Sci. 7, 2623–2656 (2014).Wiaux, Y., Puy, G., Scaife, A. M. M. & Vandergheynst, P. Compressed sensing imaging techniques in radio interferometry. Mon. Not. R. Astron. Soc. 395, 1733–1742 (2009).Carrillo, R. E., McEwen, J. D. & Wiaux, Y. Sparsity averaging reweighted analysis (SARA): a novel algorithm for radio-interferometric imaging. Mon. Not. R. Astron. Soc. 426, 1223–1234 (2012).Katz, O., Bromberg, Y. & Silberberg, Y. Compressive ghost imaging. Appl. Phys. Lett. 95, 131110 (2009).Sun, B., Welsh, S. S., Edgar, M. P., Shapiro, J. H. & Padgett, M. J. Normalized ghost imaging. Opt. Express 20, 16892–16901 (2012).Kim, M., Park, C., Rodriguez, C., Park, Y. & Cho, Y.-H. Superresolution imaging with optical fluctuation using speckle patterns illumination. Sci. Rep. 5, 16525 (2015).Combettes, P. L. & Pesquet, J. -C. in Fixed-Point Algorithms for Inverse Problems in Science and Engineering (Springer, New York, 2011).Komodakis, N. & Pesquet, J.-C. Playing with duality: an overview of recent primal dual approaches for solving large-scale optimization problems. IEEE Signal Proc. Mag. 32, 31–54 (2015).Chandrasekharan, H. K. et al. Multiplexed single-mode wavelength-to-time mapping of multimode light. Nat. Commun. 8, 14080 (2017).Wadsworth, W. J. et al. Very high numerical aperture fibers. Photon. Technol. Lett. 16, 843–845 (2004).Pesquet, J.-C. & Repetti, A. A class of randomized primal-dual algorithms for distributed optimization. J. Nonlinear Convex Anal. 16, 2353–2490 (2015).Chambolle, A., Ehrhardt, M. J., Richtárik, P. & Schönlieb, C.-B. Stochastic primal-dual hybrid gradient algorithm with arbitrary sampling and imaging applications. SIAM J. Optim. 28, 2783–2808 (2018).Bolte, J., Sabach, S. & Teboulle, M. Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Math. Program. 146, 459–494 (2014).Chouzenoux, E., Pesquet, J.-C. & Repetti, A. A block coordinate variable metric forward-backward algorithm. J. Glob. Optim. 66, 457–485 (2016).Flusberg, B. A. et al. Fiber-optic fluorescence imaging. Nat. Methods 2, 941–950 (2005).Tsvirkun, V. et al. Bending-induced inter-core group delays in multicore fibers. Opt. Express 25, 31863–31875 (2017).Candès, E. J., Wakin, M. B. & Boyd, S. Enhancing sparsity by reweighted l1 minimization. J. Fourier Anal. Appl. 14, 877–905 (2008).Condat, L. A primal–dual splitting method for convex optimization involving lipschitzian, proximable and linear composite terms. J. Optim. Theory Appl. 158, 460–479 (2013).Vu, B. C. A splitting algorithm for dual monotone inclusions involving cocoercive operators. Adv. Comp. Math. 38, 667–681 (2013)

Adaptive Movement Compensation for In Vivo Imaging of Fast Cellular Dynamics within a Moving Tissue

In vivo non-linear optical microscopy has been essential to advance our knowledge of how intact biological systems work. It has been particularly enabling to decipher fast spatiotemporal cellular dynamics in neural networks. The power of the technique stems from its optical sectioning capability that in turn also limits its application to essentially immobile tissue. Only tissue not affected by movement or in which movement can be physically constrained can be imaged fast enough to conduct functional studies at high temporal resolution. Here, we show dynamic two-photon Ca2+ imaging in the spinal cord of a living rat at millisecond time scale, free of motion artifacts using an optical stabilization system. We describe a fast, non-contact adaptive movement compensation approach, applicable to rough and weakly reflective surfaces, allowing real-time functional imaging from intrinsically moving tissue in live animals. The strategy involves enslaving the position of the microscope objective to that of the tissue surface in real-time through optical monitoring and a closed feedback loop. The performance of the system allows for efficient image locking even in conditions of random or irregular movements

Overlaps Between Autism and Language Impairment: Phenomimicry or Shared Etiology?

Traditionally, autistic spectrum disorder (ASD) and specific language impairment (SLI) are regarded as distinct conditions with separate etiologies. Yet these disorders co-occur at above chance levels, suggesting shared etiology. Simulations, however, show that additive pleiotropic genes cannot account for observed rates of language impairment in relatives, which are higher for probands with SLI than for those with ASD + language impairment. An alternative account is in terms of ‘phenomimicry’, i.e., language impairment in comorbid cases may be a consequence of ASD risk factors, and different from that seen in SLI. However, this cannot explain why molecular genetic studies have found a common risk genotype for ASD and SLI. This paper explores whether nonadditive genetic influences could account for both family and molecular findings. A modified simulation involving G × G interactions obtained levels of comorbidity and rates of impairment in relatives more consistent with observed values. The simulations further suggest that the shape of distributions of phenotypic trait scores for different genotypes may provide evidence of whether a gene is involved in epistasis

Genomic fluidity: an integrative view of gene diversity within microbial populations

<p>Abstract</p> <p>Background</p> <p>The dual concepts of pan and core genomes have been widely adopted as means to assess the distribution of gene families within microbial species and genera. The core genome is the set of genes shared by a group of organisms; the pan genome is the set of all genes seen in any of these organisms. A variety of methods have provided drastically different estimates of the sizes of pan and core genomes from sequenced representatives of the same groups of bacteria.</p> <p>Results</p> <p>We use a combination of mathematical, statistical and computational methods to show that current predictions of pan and core genome sizes may have no correspondence to true values. Pan and core genome size estimates are problematic because they depend on the estimation of the occurrence of rare genes and genomes, respectively, which are difficult to estimate precisely because they are rare. Instead, we introduce and evaluate a robust metric - genomic fluidity - to categorize the gene-level similarity among groups of sequenced isolates. Genomic fluidity is a measure of the dissimilarity of genomes evaluated at the gene level.</p> <p>Conclusions</p> <p>The genomic fluidity of a population can be estimated accurately given a small number of sequenced genomes. Further, the genomic fluidity of groups of organisms can be compared robustly despite variation in algorithms used to identify genes and their homologs. As such, we recommend that genomic fluidity be used in place of pan and core genome size estimates when assessing gene diversity within genomes of a species or a group of closely related organisms.</p

Monitoring neural activity with bioluminescence during natural behavior

Existing techniques for monitoring neural activity in awake, freely behaving vertebrates are invasive and difficult to target to genetically identified neurons. We used bioluminescence to non-invasively monitor the activity of genetically specified neurons in freely behaving zebrafish. Transgenic fish with the Ca^(2+)-sensitive photoprotein green fluorescent protein (GFP)-Aequorin in most neurons generated large and fast bioluminescent signals that were related to neural activity, neuroluminescence, which could be recorded continuously for many days. To test the limits of this technique, we specifically targeted GFP-Aequorin to the hypocretin-positive neurons of the hypothalamus. We found that neuroluminescence generated by this group of ~20 neurons was associated with periods of increased locomotor activity and identified two classes of neural activity corresponding to distinct swim latencies. Our neuroluminescence assay can report, with high temporal resolution and sensitivity, the activity of small subsets of neurons during unrestrained behavior

Combined linkage and linkage disequilibrium analysis of a motor speech phenotype within families ascertained for autism risk loci

Using behavioral and genetic information from the Autism Genetics Resource Exchange (AGRE) data set we developed phenotypes and investigated linkage and association for individuals with and without Autism Spectrum Disorders (ASD) who exhibit expressive language behaviors consistent with a motor speech disorder. Speech and language variables from Autism Diagnostic Interview-Revised (ADI-R) were used to develop a motor speech phenotype associated with non-verbal or unintelligible verbal behaviors (NVMSD:ALL) and a related phenotype restricted to individuals without significant comprehension difficulties (NVMSD:C). Using Affymetrix 5.0 data, the PPL framework was employed to assess the strength of evidence for or against trait-marker linkage and linkage disequilibrium (LD) across the genome. Ingenuity Pathway Analysis (IPA) was then utilized to identify potential genes for further investigation. We identified several linkage peaks based on two related language-speech phenotypes consistent with a potential motor speech disorder: chromosomes 1q24.2, 3q25.31, 4q22.3, 5p12, 5q33.1, 17p12, 17q11.2, and 17q22 for NVMSD:ALL and 4p15.2 and 21q22.2 for NVMSD:C. While no compelling evidence of association was obtained under those peaks, we identified several potential genes of interest using IPA. Conclusion: Several linkage peaks were identified based on two motor speech phenotypes. In the absence of evidence of association under these peaks, we suggest genes for further investigation based on their biological functions. Given that autism spectrum disorders are complex with a wide range of behaviors and a large number of underlying genes, these speech phenotypes may belong to a group of several that should be considered when developing narrow, well-defined, phenotypes in the attempt to reduce genetic heterogeneity