Biology subjects

Matlock, A.

Publications and source records attributed to Matlock, A..

3 recordsLinked to original sources

bioRxiv2022

EDoF-Miniscope: pupil engineering for extended depth-of-field imaging in a fluorescence miniscope

Extended depth of field (EDoF) microscopy has emerged as a powerful solution to greatly increase the access into neuronal populations in table-top imaging platforms. Here, we present EDoF-Miniscope, which integrates an optimized thin and lightweight binary diffractive optical element (DOE) onto the gradient refractive index (GRIN) lens of a head-mounted fluorescence miniature microscope, i.e. "miniscope". We achieve an alignment accuracy of 70 m to allow a 2.8X depth-of-field extension between the twin foci. We optimize the phase profile across the whole back aperture through a genetic algorithm that considers the primary GRIN lens aberrations, optical property of the submersion media, and axial intensity loss from tissue scattering in a Fourier optics forward model. Compared to other computational miniscopes, our EDoF-Miniscope produces high-contrast signals that can be recovered by a simple algorithm and can successfully capture volumetrically distributed neuronal signals without significantly compromising the speed, signal-to-noise, signal-to-background, and maintain a comparable 0.9-m lateral spatial resolution and the size and weight of the miniature platform. We demonstrate the robustness of EDoF-Miniscope against scattering by characterizing its performance in 5-m and 10-m beads embedded in scattering phantoms. We demonstrate that EDoF-Miniscope facilitates deeper interrogations of neuronal populations in a 100-m thick mouse brain sample, as well as vessels in a mouse brain. Built from off-the-shelf components augmented by a customizable DOE, we expect that this low-cost EDoF-Miniscope may find utility in a wide range of neural recording applications.

bioengineering↗

bioRxiv2020

An integrated multi-omic analysis of iPSC-derived motor neurons from C9ORF72 ALS patients

Neurodegenerative diseases present a challenge for systems biology, due to the lack of reliable animal models and the difficulties in obtaining samples from patients at early stages of disease, when interventions might be most effective. Studying induced pluripotent stem cell (iPSC)-derived neurons could overcome these challenges and dramatically accelerate and broaden therapeutic strategies. Here we undertook a network-based multi-omic characterization of iPSC-derived motor neurons from ALS patients carrying genetically dominant hexanucleotide expansions in C9orf72 to gain a deeper understanding of the relationship between DNA, RNA, epigenetics and protein in the same pool of tissue. ALS motor neurons showed the expected C9orf72-related alterations to specific nucleoporins and production of dipeptide repeats. RNA-seq, ATAC-seq and data-independent acquisition mass-spectrometry (DIA-MS) proteomics were then performed on the same motor neuron cultures. Using integrative computational methods that combined all of the omics, we discovered a number of novel dysregulated pathways including biological adhesion and extracellular matrix organization and disruption in other expected pathways such as RNA splicing and nuclear transport. We tested the relevance of these pathways in vivo in a C9orf72 Drosophila model, analyzing the data to determine which pathways were causing disease phenotypes and which were compensatory. We also confirmed that some pathways are altered in late-stage neurodegeneration by analyzing human postmortem C9 cervical spine data. To validate that these key pathways were integral to the C9 signature, we prepared a separate set of C9orf72 and control motor neuron cultures using a different differentiation protocol and applied the same methods. As expected, there were major overall differences between the differentiation protocols, especially at the level of in individual omics data. However, a number of the core dysregulated pathways remained significant using the integrated multiomic analysis. This new method of analyzing patient specific neural cultures allows the generation of disease-related hypotheses with a small number of patient lines which can be tested in larger cohorts of patients.

neuroscience↗

bioRxiv2019

piNET: a versatile web platform for downstream analysis and visualization of proteomics data

Large proteomics data, including those generated by mass spectrometry, are being generated to characterize biological systems at the protein level. Computational methods and tools to identify and quantify peptides, proteins and post-translational modifications (PTMs) that are captured in modern mass spectrometers have matured over the years. On the other hand, tools for downstream analysis, interpretation and visualization of proteomics data sets, in particular those involving PTMs, require further improvement and integration to accelerate scientific discovery and maximize the impact of proteomics studies by connecting them better with biological knowledge across not only proteomics, but also other Omics domains. With the goal of addressing these challenges, the piNET server has been developed as a versatile web platform to facilitate mapping, annotation, analysis and visualization of peptide, PTM, and protein level quantitative data generated by either targeted, shotgun or other proteomics approaches. Building on our experience with large scale analysis of gene and protein expression profiles as part of the Library of Integrated Network Cellular Signatures (LINCS) project, piNET has been designed as a fast, versatile and easy to use web-based tool with three modules that provide mapping from peptides (with PTMs) to proteins, from PTM sites to modifying enzymes that target those sites, and finally from proteins (with PTMs) to pathways, and for further mechanistic insights to LINCS signatures of chemical and genetic perturbations. piNET is freely available at http://www.pinet-server.org.

bioinformatics↗