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      Cellular extrusion bioprinting improves kidney organoid reproducibility and conformation.

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          Abstract

          Directed differentiation of human pluripotent stem cells to kidney organoids brings the prospect of drug screening, disease modelling and the generation of tissue for renal replacement. Currently, these applications are hampered by organoid variability, nephron immaturity, low throughput and limited scale. Here we apply extrusion-based 3D cellular bioprinting to deliver rapid and high throughput generation of kidney organoids with highly reproducible cell number and viability. We demonstrate that manual organoid generation can be replaced by 6- or 96-well organoid bioprinting and evaluate relative toxicity of aminoglycosides as a proof of concept for drug testing. In addition, 3D bioprinting enabled precise manipulation of biophysical properties including organoid size, cell number and conformation, with modification of organoid conformation substantially increasing nephron yield per starting cell number. This facilitated the manufacture of uniformly patterned kidney tissue sheets with functional proximal tubular segments. Hence, automated extrusion-based bioprinting for kidney organoid production deliver improvements in throughput, quality control, scale and structure, facilitating in vitro and in vivo applications of stem cell-derived human kidney tissue.

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          Most cited references43

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Is Open Access

              limma powers differential expression analyses for RNA-sequencing and microarray studies

              limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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                Author and article information

                Journal
                101155473
                30248
                Nat Mater
                Nat Mater
                Nature materials
                1476-1122
                9 December 2020
                23 November 2020
                February 2021
                23 May 2021
                : 20
                : 2
                : 260-271
                Affiliations
                [1. ]Murdoch Children’s Research Institute, Flemington Rd, Parkville, VIC, Australia
                [2. ]Organovo Inc, San Diego, CA, USA
                [3. ]Department of Anatomy and Neuroscience, The University of Melbourne, VIC, Australia.
                [4. ]Department of Paediatrics, The University of Melbourne, VIC, Australia.
                Author notes
                [#]

                equal first authors: These authors have contributed equally to the generation of this manuscript

                Author contributions

                KL, JMV, JWH, BS, SP, SCP, AEC and MHL contributed to experimental design and planning. KL, JMV, JWH, AC, KB, DA, PXE, SW, SH, KST, FL, LJH developed methods and reagents, performed and analysed experiments. All authors contributed to interpretation of data. KL, JMV, JWH, AEC and MHL contributed to writing of the manuscript.

                [* ]Author for correspondence: M.H.L.: +61 3 9936 6206; melissa.little@ 123456mcri.edu.au
                Article
                NIHMS1634620
                10.1038/s41563-020-00853-9
                7855371
                33230326
                40bd36e1-4946-4b74-a21d-c09429633f62

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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                Categories
                Article

                Materials science
                pluripotent stem cell,kidney,kidney organoid,3d bioprinting,nephrotoxicity
                Materials science
                pluripotent stem cell, kidney, kidney organoid, 3d bioprinting, nephrotoxicity

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