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Viral Genome Release and Native Viral Particle Conversion Measured Through Temperature Ramping in Real Time PCR Machine Resource Report Resource Website |
Antonio Real-Hohn | 10.17504/protocols.io.p2xdqfn | This protocol was developed to use common wet lab device (Real Time PCR machine) to detect viral genome release and native viral particle conversion. We used temperature ramping for inducing genome uncoating and fluorescent probes for RNA/DNA and/or proteins, to detect genome and/or capsid changes. | Medizinische Universität Wien | 1 | 2018 | Antonio Real-Hohn 2018. Viral Genome Release and Native Viral Particle Conversion Measured Through Temperature Ramping in Real Time PCR Machine. protocols.io dx.doi.org/10.17504/protocols.io.p2xdqfn | 2021-03-29 03:09:08 | ||||
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Yeast Crude Protein Extraction Resource Report Resource Website |
Alan Cone | 10.17504/protocols.io.ebnbame | Ju Lab | Quick crude protein extraction from budding or fission yeast. | Wright State University | 1 | 2016 | Alan Cone 2016. Yeast Crude Protein Extraction. protocols.io dx.doi.org/10.17504/protocols.io.ebnbame | 2021-03-29 03:09:08 | |||
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Assay of anthocyanin biosynthetic enzyme activity Resource Report Resource Website |
Hongfang Zhu | 10.17504/protocols.io.h2mb8c6 | Zhu H, Li X, Zhai W, Liu Y, Gao Q, Liu J, Ren L, Chen H, Zhu Y (2017) Effects of low light on photosynthetic properties, antioxidant enzyme activity, and anthocyanin accumulation in purple pak-choi (Brassica campestris ssp. Chinensis Makino). PLoS ONE 12(6): e0179305. doi: 10.1371/journal.pone.0179305 | https://doi.org/10.1371/journal.pone.0179305 | 1 | 2017 | Hongfang Zhu 2017. Assay of anthocyanin biosynthetic enzyme activity. protocols.io dx.doi.org/10.17504/protocols.io.h2mb8c6 | 2021-03-29 03:09:08 | ||||
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Script R1: Virome Contig and Sequencing Statistics Resource Report Resource Website |
HANNIGAN GD, GRICE EA, ET AL. | 10.17504/protocols.io.eh5bb86 | VERVE Net, Club Grice | This protocol outlines the analysis used to plot contig coverage statistics, as well as sequence count and length stats. We begin with visualizing contig length vs coverage. We then visualize the distributions of sequence counts per sample as a probability density plot (similar idea as a histogram), and then do the same for median sequence length. Based on the methods from the following publication:Hannigan, Geoffrey D., et al. "The Human Skin Double-Stranded DNA Virome: Topographical and Temporal Diversity, Genetic Enrichment, and Dynamic Associations with the Host Microbiome." mBio 6.5 (2015): e01578-15. | Kindler L, Stoliartchouk A, Teytelman L, Hurwitz BL, Method-centered digital communities on protocols.io for fast-paced scientific innovation. F1000Research doi: 10.12688/f1000research.9453.2 | DEPARTMENT OF DERMATOLOGY UNIVERSITY OF PENNSYLVANIA, DEPARTMENT OF DERMATOLOGY UNIVERSITY OF PENNSYLVANIA, DEPARTMENT OF DERMATOLOGY UNIVERSITY OF PENNSYLVANIA | http://mbio.asm.org/content/6/5/e01578-15.full | 1 | 2016 | HANNIGAN GD, GRICE EA, ET AL. 2016. Script R1: Virome Contig and Sequencing Statistics. protocols.io dx.doi.org/10.17504/protocols.io.eh5bb86 | 2021-03-29 03:09:17 | |
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Whitefly DNA extraction, partial mtCO1 gene amplification and gel electrophoresis Resource Report Resource Website |
Joachim Nwezeobi, Onyeyirichi Onyegbule, Chukwuemeka Nkere, Joseph Onyeka, Sharon van Brunschot, Susan Seal, John Colvin | 10.17504/protocols.io.bdvri656 | National Institute of Agricultural Botany, Cambridge, United Kingdom, National Root Crops Research Institute, Umudike, Umuahia, Abia State, Nigeria, National Root Crops Research Institute, Umudike, Umuahia, Abia State, Nigeria, National Root Crops Research Institute, Umudike, Umuahia, Abia State, Nigeria, Natural Resources Institute, University of Greenwich, Central Avenue, Chatham Maritime, Kent, United Kingdom, Natural Resources Institute, University of Greenwich, Central Avenue, Chatham Maritime, Kent, United Kingdom, Natural Resources Institute, University of Greenwich, Central Avenue, Chatham Maritime, Kent, United Kingdom | 1 | 2020 | Joachim Nwezeobi, Onyeyirichi Onyegbule, Chukwuemeka Nkere, Joseph Onyeka, Sharon van Brunschot, Susan Seal, John Colvin 2020. Whitefly DNA extraction, partial mtCO1 gene amplification and gel electrophoresis. protocols.io dx.doi.org/10.17504/protocols.io.bdvri656 | 2021-03-29 03:09:17 | |||||
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Serial Dilution of Nucleofected iPSC Pools Resource Report Resource Website |
Celeste Karch, Rita Martinez, Jacob Marsh | 10.17504/protocols.io.x76frre | Neurodegeneration Method Development Community | Washington University in St Louis, Washington University in St Louis, Washington University in St Louis | 1 | 2019 | Celeste Karch, Rita Martinez, Jacob Marsh 2019. Serial Dilution of Nucleofected iPSC Pools. protocols.io dx.doi.org/10.17504/protocols.io.x76frre | 2021-03-29 03:09:17 | ||||
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Analysis of the Derivatives of Sialic Acid in Pig Tissues Resource Report Resource Website |
Chon-Ho Yen | 10.17504/protocols.io.zd6f29e | Sialic acid is a generic term for the N- or O-substituted derivatives of neuraminic acid, a monosaccharide with a nine-carbon backbone. N-glycolylneuraminic acid (Neu5Gc or NGNA) is not synthesized in the human body, so most of the sialic acid in the body is N-acetylneuraminic acid (Neu5Ac or NANA), while other animals have two kinds of sialic acid (NANA and NGNA). There may be NGNA in biotech products manufactured from nonhuman animal source, and a detectable method is needed to determine the derivatives of sialic acid in the product. | Tu C, Chuang C, Hsiao K, Chen C, Chen C, Peng S, Su Y, Chiou M, Yen C, Hung S, Yang T, Chen C (2019) Lessening of porcine epidemic diarrhoea virus susceptibility in piglets after editing of the CMP-N-glycolylneuraminic acid hydroxylase gene with CRISPR/Cas9 to nullify N-glycolylneuraminic acid expression. PLoS ONE 14(5): e0217236. doi: 10.1371/journal.pone.0217236 | Division of Animal Technology, Animal Technology Laboratories, Agricultural Technology Research Institute, No.1, Ln. 51, Dahu Rd., Xiangshan Dist., Hsinchu City 30093, Taiwan | https://doi.org/10.1371/journal.pone.0217236 | 1 | 2019 | Chon-Ho Yen 2019. Analysis of the Derivatives of Sialic Acid in Pig Tissues. protocols.io dx.doi.org/10.17504/protocols.io.zd6f29e | 2021-03-29 03:09:17 | ||
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SYSB 3036 W04: Homology searches Resource Report Resource Website |
Frank Aylward | 10.17504/protocols.io.vqse5we | Virginia Tech | 1 | 2018 | Frank Aylward 2018. SYSB 3036 W04: Homology searches. protocols.io dx.doi.org/10.17504/protocols.io.vqse5we | 2021-03-29 03:09:16 | |||||
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Gel Electrophoresis Resource Report Resource Website |
Alba Balletbó | 10.17504/protocols.io.7eehjbe | iGEM Wageningen 2019 | Gel electrophoresis is the standard lab procedure for separating DNA by size (e.g., length in base pairs) for visualization and purification. Electrophoresis uses an electrical field to move the negatively charged DNA through an agarose gel matrix toward a positive electrode. Shorter DNA fragments migrate through the gel more quickly than longer ones. Thus, you can determine the approximate length of a DNA fragment by running it on an agarose gel alongside a DNA ladder (a collection of DNA fragments of known lengths). | Wageningen University | 1 | 2019 | Alba Balletbó 2019. Gel Electrophoresis. protocols.io dx.doi.org/10.17504/protocols.io.7eehjbe | 2021-03-29 03:09:16 | |||
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Digestion Mixture for M0302 (v2) Resource Report Resource Website |
NEB | 10.17504/protocols.io.erhbd36 | New England Biolabs (NEB) | New England Biolabs | https://www.neb.com/protocols/2014/08/11/determining-genome-targeting-efficiency-using-t7-endonuclease-i | 1 | 2016 | NEB 2016. Digestion Mixture for M0302 (v2). protocols.io dx.doi.org/10.17504/protocols.io.erhbd36 | 2021-03-29 03:09:16 | |||
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NASC-seq (new transcriptome alkylation-dependent single-cell RNA sequencing) protocol Resource Report Resource Website |
Gert-Jan Hendriks, Lisa Anna Jung, Anton J.M. Larsson, Oscar Andersson Forsman, Michael Lidschreiber, Katja Lidschreiber, Patrick Cramer, Rickard Sandberg | 10.17504/protocols.io.whtfb6n | Karolinska Institute Stockholm, Karolinska Institute Stockholm, Karolinska Institute Stockholm, Karolinska Institute Stockholm, Max Planck Institute for Biophysical Chemistry & Karolinska Institute Stockholm, Max Planck Institute for Biophysical Chemistry & Karolinska Institute Stockholm, Max Planck Institute for Biophysical Chemistry & Karolinska Institute Stockholm, Karolinska Institute Stockholm | 1 | 2019 | Gert-Jan Hendriks, Lisa Anna Jung, Anton J.M. Larsson, Oscar Andersson Forsman, Michael Lidschreiber, Katja Lidschreiber, Patrick Cramer, Rickard Sandberg 2019. NASC-seq (new transcriptome alkylation-dependent single-cell RNA sequencing) protocol. protocols.io dx.doi.org/10.17504/protocols.io.whtfb6n | 2021-03-29 03:09:16 | |||||
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Protocol for "Evaluation of a Conceptual Framework for Predicting Navigation Performance in Virtual Reality" Resource Report Resource Website |
Jascha Grübel, Tyler Thrash, Christoph Hölscher, Victor Schinazi | 10.17504/protocols.io.jbdcii6 | Previous research in spatial cognition has often relied on simple spatial tasks in static environments in order to draw inferences regarding navigation performance. These tasks are typically divided into categories (e.g., egocentric or allocentric) that reflect different two-systems theories. Unfortunately, this two-systems approach has been insufficient for reliably predicting navigation performance in virtual reality (VR). In the present experiment, participants were asked to learn and navigate towards goal locations in a virtual city and then perform eight simple spatial tasks in a separate environment. These eight tasks were organised along four orthogonal dimensions (static/dynamic, perceived/remembered, egocentric/allocentric, and distance/direction). We employed confirmatory and exploratory analyses in order to assess the relationship between navigation performance and performances on these simple tasks. We provide evidence that a dynamic task (i.e., intercepting a moving object) is capable of predicting navigation performance in a familiar virtual environment better than several categories of static tasks. These results have important implications for studies on navigation in VR that tend to over-emphasise the role of spatial memory. Given that our dynamic tasks required efficient interaction with the human interface device (HID), they were more closely aligned with the perceptuomotor processes associated with locomotion than wayfinding. In the future, researchers should consider training participants on HIDs using a dynamic task prior to conducting a navigation experiment. Performances on dynamic tasks should also be assessed in order to avoid confounding skill with an HID and spatial knowledge acquisition. | Grübel J, Thrash T, Hölscher C, Schinazi VR (2017) Evaluation of a conceptual framework for predicting navigation performance in virtual reality. PLoS ONE 12(9): e0184682. doi: 10.1371/journal.pone.0184682 | ETH Zürich, ETH Zürich, ETH Zürich, ETH Zürich | https://doi.org/10.1371/journal.pone.0184682 | 1 | 2017 | Jascha Grübel, Tyler Thrash, Christoph Hölscher, Victor Schinazi 2017. Protocol for "Evaluation of a Conceptual Framework for Predicting Navigation Performance in Virtual Reality". protocols.io dx.doi.org/10.17504/protocols.io.jbdcii6 | 2021-03-29 03:09:16 | ||
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Weekly Quality Control Resource Report Resource Website |
Lukas Snoek, Tinka Beemsterboer | 10.17504/protocols.io.w8efhte | Spinoza Centre, REC-L | The weekly quality control at the Spinoza Centre REC evaluates the signal quality/performance of the 3T Philips Achieva TX (R5, v3.0). | Spinoza Centre (REC-L), Spinoza Centre (REC-L) | 3 | 2019 | Lukas Snoek, Tinka Beemsterboer 2019. Weekly Quality Control. protocols.io dx.doi.org/10.17504/protocols.io.w8efhte | 2021-03-29 03:09:16 | |||
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Quantitative (q)PCR and Differential Expression Analysis Resource Report Resource Website |
Jeffrey Lewis, Amanda Scholes | 10.17504/protocols.io.bbgpijvn | Protist Research to Optimize Tools in Genetics (PROT-G), Lewis Lab | A generalizable protocol for measuring relative changes in gene expression via qPCR (cDNA synthesis, qPCR primer optimization, and qPCR analysis), with specific optimization for the budding yeast Saccharomyces cerevisiae. | Scholes AN, Lewis JA, Comparison of RNA isolation methods on RNA-Seq: implications for differential expression and meta-analyses. BMC Genomics doi: 10.1186/s12864-020-6673-2 | University of Arkansas - Fayetteville, University of Arkansas - Fayetteville | https://doi.org/10.1186/s12864-020-6673-2 | 1 | 2020 | Jeffrey Lewis, Amanda Scholes 2020. Quantitative (q)PCR and Differential Expression Analysis. protocols.io dx.doi.org/10.17504/protocols.io.bbgpijvn | 2021-03-29 03:09:17 | |
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BACRB - Parallel Sequencing of Barcoded BAC Clones by random tagging PCR Resource Report Resource Website |
Elena Hilario, Marcus Davy, Roy Storey, Richard Newcomb, Ross N Crowhurst, Roger P Hellens | 10.17504/protocols.io.p3adqie | A genome is assembled by connecting large scaffolds via a collection of thousands of mate-paired ends of various sizes (3-20 kbp). Terminal ends of long DNA fragments can be obtained by sequencing large insert clones by Sanger sequencing, a labour-intensive and expensive approach. Here we describe a high-throughput protocol to tag 11,520 BAC plasmids randomly with barcoded oligonucleotides at the end of a random hexamer by PCR.This method assisted the kiwifruit (Actinidia chinensis) genome assembly in a similar way as mate paired end datasets. Although not fully sequenced, each randomly tagged BAC clone provides a collection of short sequence tags mapped to a genome across one or multiple scaffolds under three different scenarios: validate a single scaffold, join two scaffolds, or group several scaffolds by proximity only. Our method provides a simple way of cataloging BAC libraries to assist genome assembly projects. | Plant and Food Research, Plant and Food Research, Plant and Food Research, Plant and Food Research, Plant and Food Research, Queensland University of Technology | https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4656-3 | 1 | 2018 | Elena Hilario, Marcus Davy, Roy Storey, Richard Newcomb, Ross N Crowhurst, Roger P Hellens 2018. BACRB - Parallel Sequencing of Barcoded BAC Clones by random tagging PCR. protocols.io dx.doi.org/10.17504/protocols.io.p3adqie | 2021-03-29 03:09:17 | |||
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SYSB 3036 W11: Gene Expression and RNA-Seq Resource Report Resource Website |
Frank Aylward | 10.17504/protocols.io.v4qe8vw | Virginia Tech | 1 | 2018 | Frank Aylward 2018. SYSB 3036 W11: Gene Expression and RNA-Seq. protocols.io dx.doi.org/10.17504/protocols.io.v4qe8vw | 2021-03-29 03:09:17 | |||||
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Protocol used in Evidence supporting cryptic species complexes within two sessile microinvertebrates, Limnias melicerta and L. ceratophylli (Rotifera, Gnesiotrocha) Resource Report Resource Website |
Azar Kordbacheh, Robert L. Wallace, Elizabeth J. Walsh | 10.17504/protocols.io.tppemmn | Sample collection and cultureAquatic plant samples were collected from habitats across the USA and a sediment sample from Australia (Tables S1.1, S1.2). Limnias melicerta and L. ceratophylli were identified and isolated from rehydrated sediments or by removing a piece of vegetation to which they were attached. Species identification was based on tube structure, shape of corona, antennae length, and the number of dorsal nodules [1]. Clonal lineages initiated from single females were cultured in modified MBL media [2] and fed a mixture of the algae Chlorella vulgaris Berijerinck, 1890 (The UTEX Culture Collection of Algae at the University of Texas at Austin [UTEX] strain 30) and Chlamydomonasreinhardtii Dangeard, 1888 (UTEX strain 90). Rotifers in this genus produce tubes of hardened secretions [3]; we added powdered carmine (Alfa Aesar, UK) to lab cultures to provide a supplementary matrix to aid tube construction and to increase their visibility in culture. Voucher specimens were deposited in the UTEP Biodiversity Collections at The University of Texas at El Paso (L. melicerta: UTEP:Zoo:43, 105-134; L. ceratophylli: UTEP:Zoo:32-42, UTEP:Zoo:52-61).Deposited specimens included approximately 10 individuals from each population preserved in 95% ethanol and 10 clonal individuals preserved in 4% buffered formalin for molecular analyses and identification, respectively. DNA Extraction and gene amplificationDNA was extracted from one individual of each clonal lineage by adding 13 µl Chelex®-100 (Bio-Rad Laboratories, CA, USA) and incubating at 100°C for 10 min. DNA templates were stored at -80°C until used for amplification. Number of clonal lineages examined from each population is given in Tables S1.1 and S1.2.An approximate 630 bp portion of the cytochrome c oxidase subunit I (COI) gene was amplified using the primers LCO1490: 5' -GGTCAACAAATCATAAAGATATTGG-3' and HCO2198: 5'-TAAACTTCAGGGTGACCAAAAAATCA-3' [4]. The entire nuclear internal transcribed spacer region (ITS) was amplified using the primers ITS4: 5'-TCCTCCGCTTATTGATATGC-3' and ITS5: 5'-GGAAGTAAAAGTCGTAACAAGG-3' [5], and 865 bp of the 18S rRNA gene was amplified using primers 3F: 5’-GTTCGATTCCGGAGAGGG-3’ as modified by Giribet et al. [6] and primer 18Sbi: 5’-CTAGAGTCTCGTTCGTTATCGG-3’ as modified by Whiting et al. [7].PCR reactions contained 10 µl of genomic DNA, 1 µl of each primer (500 ng/ µl), 22 µl HPLC grade sterile water, 1 µl GoTaq® G2 DNA Polymerase (Promega), 10 µl 5X PCR buffer B (10 mM MgCl2, pH 8.5) or 5X PCR buffer A (7.5 mM MgCl2, pH 8.5), followed by adding 5 µl dNTP mix (2.5 mM each of dATP, dCTP, dGTP, dTTP) at 80ºC. PCR cycles were run on a thermocycler (TECHNE TC-412) and consisted of an initial denaturation at 94ºC for 1 min, followed by denaturation at 94ºC for 1 min, annealing at 48ºC for 2 min and extension at 72ºC for 3 min for 35 cycles, and a final extension step at 72ºC for 7 min. To verify the size of amplification products we used electrophoresis, and we purified them using GENECLEAN® kits (MP Biomedicals, LLC) before sequencing. Sequencing was done at UTEP’s BBRC Genomic Analysis Core Facility on an Applied Biosystems 3130xl Genetic Analyzer using BigDye Terminator v3.1 Cycle Sequencing Kits (Applied Biosystems). GenBank accession numbers for all sequences obtained are given in Tables S1.1 (L. melicerta) and S1.2 (L. ceratophylli). The COI gene sequences of L. melicerta (accession number, KT870155.1) and L. ceratophylli(KT870157.1) from GenBank are not included in our analyses for two reasons. 1) The COI sequence of L. melicerta KT870155.1 is 330 bp, which was much shorter than COI sequences obtained in this study (623 bp). 2) The COI sequence of L. ceratophylli KT870157.1 grouped with cryptic species M of L. melicerta in phylogenetic analyses. Additional 18S rRNA sequences (L. melicerta: KM873599.1, L. ceratophylli: KM873598.1) and a COI sequence from L. melicerta (KT870154.1) were included from GenBank. Sinantherina socialis(Linneaus, 1758) and Ptygura pilula (Cubitt, 1872) were included as outgroups in phylogenetic analyses for the COI gene. Floscularia conifera (Hudson, 1886) andPtygura brachiata (Hudson, 1886) were used as outgroup taxa in phylogenetic analyses based on ITS region. For analysis of 18S rRNA sequences, we used Collotheca campanulata as the outgroup (Table S1.1).Genetic DiversityFinchTV v 1.4.0 [8] was used to check sequences manually, especially for potential double peaks in the ITS region sequences. The ITS region alignment was uploaded to the SeqPhase online tool (http://seqphase.mpg.de/seqphase/) to phase the sequences as described by Flot [9]. Contigs for all sequences were made using CAP 3 [10] and were aligned using MAFFT v 7 [11]. Mesquite v 3.2 [12] was used to manually check the alignments and to translate COI gene sequences to proteins. To measure substitution saturation, we used DAMBE v 6 [13]. Number of polymorphic sites, number of parsimony informative sites, number of haplotypes, haplotype diversity (h), and nucleotide diversity (π) were calculated using DnaSp v 5.10.01 [14], and uncorrected pairwise sequences distances ("p") were calculated in Mega v 7.0 [15]. A haplotype network was constructed using the median joining method in Network v 5.0.3 [16]. Species delimitation Models for sequence evolution were TPM2uF+I+G for the COI gene, TPM1uF+I for the ITS region, and JC for the 18S rRNA gene as determined using Jmodeltest2 [17,18] available at the Cipres Science Gateway 3.3 [19]. To construct the phylogenetic trees, Bayesian analysis was run for 107 generations with two parallel runs and a 25% burn in period using MrBayes v 3.2.6 on XSEDE high-throughput computing resources available at Cipres Science Gateway [19]. Phylogenetic analyses were implemented in BEAST and *BEAST [20] using GTR+I+G model of sequence evolution for the COI gene and GTR+I model for the ITS region. TPM2uF and TPM1uF models are not available in BEAST. However, both of these models are classified under the GTR model. Thus GTR was used in both instances.To determine the number of evolutionary entities (putative cryptic species), we used Generalized Mixed Yule Coalescent (GMYC, [21]), Poisson Tree Process (PTP, [22]), Automatic Barcoding Gap Discovery (ABGD, [23]), *BEAST v 1.8.3 [20], and Bayesian Species Delimitation (BSD) implemented in Bayesian Phylogenetics and Phylogeography software (BPP v 3.1, [24–26]). We used BEAST v 1.8.3 [20] to construct ultrametric trees and *BEAST v 1.8.3 [20] for species delimitation. Both analyses were run for the COI gene and ITS region sequences separately for 107 generations, with sampling every 1,000 generations. Tracer v 1.6.0 [27] was used to check the effective sample size (ESS>200) and to verify convergence. Consensus trees were obtained using TreeAnnotator v 1.8.3 with a 25% burn in. Ultrametric trees were used for species delimitation in single threshold and multiple threshold GMYC [28] (http://species.h-its.org/gmyc/, accessed June 12, 2018), Bayesian GMYC (bGMYC) [29] and PTP methods. bGMYC was run using the R package bGMYC v 1.0.2 for 100,000 iterations with sampling every 1,000 iterations. We ran PTP by uploading the ultrametric trees to the online tool available at http://species.h-its.org/ptp/(accessed June 12, 2018) andused default settings. ABGD delimitation was done by uploading the sequence alignment to the online tool available at wwwabi.snv.jussieu.fr/public/abgd/ under the default settings (accessed June 12, 2018).*BEAST v 1.8.3 [20] was run under assumptions regarding the number of species for both the COI gene and ITS region sequences. Lineages having posterior probabilities > 0.90 were retained in *BEAST analyses. To run BSD, the phylogenetic tree based on Bayesian inference was used as the guide tree, and we used the joint species delimitation and tree estimation method (unguided species delimitation) that does not rely on the topology of the guide tree.Isolation by Distance Geographic distance matrices were constructed using Geographic Distance Matrix Generator v 1.2.3 [30]. To test the correlation between genetic variation and geographic distances (log transformed; km) among populations, Mantel tests with 10,000 permutations were run using the R package ecodist v 1.2.9 [31]. Trophi morphologyTrophi were prepared for scanning electron microscopy (SEM) by dissolving rotifer tissue in ~5% sodium hypochlorite, rinsing with deionized water 10-15 times, and air-drying on circular cover slips at room temperature [32]. Trophi were coated with gold/palladium using a Gatan 682 PECS sputter coater. SEM images were obtained at 20 kV using a Hitachi S-4800 system. Trophi were prepared for individuals from one clonal lineage from each examined population. We used a geometric morphometric approach to study variation in the shape and size of 92 trophi for L. melicerta and 60 trophi for L. ceratophylli among putative cryptic species. This method uses Cartesian coordinates for a set of anatomical landmarks [33]. SEM images were obtained from caudal and frontal views of the trophi. Using TPS series software [34], nine landmarks on the caudal view and 10 on the frontal view of the trophi were digitized (Fig 1). Configuration of landmarks were analyzed using Generalized Procrustes Analysis [33]. Trophi size was calculated as Centroid Size (CS): i.e., the square root of the sum of squared distances between landmarks and their centroid [35]. Variation in the shape of trophi based on landmarks was examined using Discriminant Analysis in SPSS v 24 [36]. Because trophi centroid size was not normally distributed, variation in size among putative cryptic species was tested using a non-parametric Kruskal-Wallis test, and between the two morphospecies using a non-parametric Man-Whitney U test implemented in SPSS v 24 [36]. References1. Wallace RL, Kordbacheh A, Walsh EJ. Key to the currently recognized species of Limnias Schrank, 1803 (Rotifera, Monogononta, Gnesiotrocha, Flosculariidae). Zootaxa. 2018;4442: 307–318. doi.org/10.11646/zootaxa.4442.2.7.2. Stemberger RS. A general approach to the culture of planktonic rotifers. Can J Fish Aquat Sci. 1981;38: 721–724. doi:10.1139/f81-095.3. Wallace RL, Nogrady T, Snell TW, Ricci C. Rotifera 1: Biology, ecology and systematics. 2nd ed. Nogrady T, editor. Kenobi Productions, 2006, 293 pp. 4. Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R. DNA primers for amplification of mitochondrial cytochrome coxidase subunit I from diverse metazoan invertebrates. 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Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999;16: 37–48. 17. Darriba D, Taboada GL, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nat Methods. 2012;9: 772. http://dx.doi.org/10.1038/nmeth.2109.18. Guindon S, Gascuel O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 2003;52: 696–704. doi:10.1080/10635150390235520.19. Miller MA, Pfeiffer W, Schwartz T. Creating the CIPRES science gateway for inference of large phylogenetic trees. 2010. Gateway Computing Environments Workshop, 2010, pp. 1–8. doi:10.1109/GCE.2010.5676129.20. Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol. 2012;29: 1969–1973. doi:10.1093/molbev/mss075.21. Pons J, Barraclough TG, Gomez-Zurita J, Cardoso A, Duran DP, Hazell S, et al. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. 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Rotifera of some lakes in the floodplain of the River Niger (Imo State, Nigeria). New species and other taxonomic considerations. Hydrobiologia. 1993;250: 39–61. doi:10.1007/BF00007494.33. Adams DC, Rohlf FJ, Slice DE. Geometric morphometrics: Ten years of progress following the revolution. Ital J Zool. 2004;71: 5–16. doi:10.1080/11250000409356545.34. Rohlf FJ. The tps series of software. Hystrix. 2015;26: 1–4. doi:10.4404/hystrix-26.1-11264.35. Cavalcanti MJ, Monteiro LR, Lopes PRD. Landmark-based morphometric analysis in selected species of serranid fishes (Perciformes: Teleostei). Zool Stud. 1999;38: 287–294. 36. IBM Corp. IBM SPSS statistics for windows, version 24.0. IBM Corp. 2016. | Kordbacheh A, Wallace RL, Walsh EJ (2018) Evidence supporting cryptic species within two sessile microinvertebrates, Limnias melicerta and L. ceratophylli (Rotifera, Gnesiotrocha). PLoS ONE 13(10): e0205203. doi: 10.1371/journal.pone.0205203 | University of Texas at El Paso, Ripon College, University of Texas at El paso | https://doi.org/10.1371/journal.pone.0205203 | 1 | 2018 | Azar Kordbacheh, Robert L. Wallace, Elizabeth J. Walsh 2018. Protocol used in Evidence supporting cryptic species complexes within two sessile microinvertebrates, Limnias melicerta and L. ceratophylli (Rotifera, Gnesiotrocha). protocols.io dx.doi.org/10.17504/protocols.io.tppemmn | 2021-03-29 03:09:17 | ||
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High molecular weight gDNA extraction after Mayjonade et al. optimised for eucalyptus for nanopore sequencing Resource Report Resource Website |
Miriam Schalamun, Benjamin Schwessinger | 10.17504/protocols.io.khkct4w | High molecular weight DNA extraction from all kingdoms, Plantae | Extraction of high quality DNA for long read sequencing e.g. the Oxford Nanopore Optimized for DNA extraction from eucalyptus grandis and eucalyptus pauciflora. This protocol contains an optional Chloroform clean up step which is necessary for eucalyptus but might not be for other tissue. For long DNA fragments don't vortex the DNA sample. | Schalamun M, Nagar R, Kainer D, Beavan E, Eccles D, Rathjen JP, Lanfear R, Schwessinger B, Harnessing the MinION: An example of how to establish long‐read sequencing in a laboratory using challenging plant tissue from . Molecular Ecology Resources 19(1). doi: 10.1111/1755-0998.12938 | , Australian National University | https://doi.org/10.1111/1755-0998.12938 | 9 | 2017 | Miriam Schalamun, Benjamin Schwessinger 2017. High molecular weight gDNA extraction after Mayjonade et al. optimised for eucalyptus for nanopore sequencing. protocols.io dx.doi.org/10.17504/protocols.io.khkct4w | 2021-03-29 03:09:17 | |
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Detection and Sorting of Extracellular Vesicles and Viruses using nanoFACS Resource Report Resource Website |
Aizea Morales-Kastresana, Joshua Welsh, Jennifer Jones | 10.17504/protocols.io.bj6xkrfn | Translational Nanobiology Section | Recent advances in high resolution flow cytometry (HRFC), which show improvements in both light scatter and fluorescence sensitivity have resulted in the development of techniques that better isolate, stain and analyze single EVs(Boing et al., 2014; Groot Kormelink et al., 2016; Morales-Kastresana, Musich, Welsh, Telford, Demberg, Wood, Bigos, Ross, Kachynski, Dean, Feton, et al., 2019; Morales-Kastresana et al., 2017; Stoner et al., 2016; van der Vlist, Nolte-'t Hoen, Stoorvogel, Arkesteijn, & Wauben, 2012). Below, we describe protocols to fluorescently label EVs using CFDA-SE (hereinafter called CFSE), as well as antibodies targeted at specific EV surface proteins. We also provide guidelines for residual dye and antibody removal, appropriate data acquisition by HRFC and EV counting by HRFC. Figure 1summarizes these protocols.The EVs used in this protocol are derived from the DC2.4 cell line, and bone marrow derived dendritic cells (BMDCs). The DC2.4 cell line are immature dendritic cells (DCs) with very low expression of typical DC markers on their surface (unpublished observation and(Hargadon, Forrest, & Reddy, 2012)) and that release a morphologically homogeneous population of EVs (~130 nm in diameter). DC2.4 EVs will be used to demonstrate a CFSE staining in Basic Protocol 1, as well as being used as a negative control for antibody-based staining methods (Basic Protocol 2). Bone marrow dendritic cell (BMDC)-derived EVs are more heterogeneous in diameter (100-200 nm) and composition(Morales-Kastresana, Musich, Welsh, Telford, Demberg, Wood, Bigos, Ross, Kachynski, Dean, Felton, et al., 2019), and express DC markers such as MHC-II. BMDC EVs will be used to demonstrate antigen-specific staining with fluorochrome-conjugated antibodies in Basic Protocol 2. DC2.4 and BMDC-derived EVs were isolated by serial ultracentrifugation, with concentration and diameter distribution characterized by NTA, as described before(Morales-Kastresana, Musich, Welsh, Telford, Demberg, Wood, Bigos, Ross, Kachynski, Dean, Feton, et al., 2019; Morales-Kastresana et al., 2017). | Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health | 1 | 2020 | Aizea Morales-Kastresana, Joshua Welsh, Jennifer Jones 2020. Detection and Sorting of Extracellular Vesicles and Viruses using nanoFACS. protocols.io dx.doi.org/10.17504/protocols.io.bj6xkrfn | 2021-03-29 03:09:18 | |||
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UPPA-PROTEIN Concentrate™ Resource Report Resource Website |
G-Biosciences | 10.17504/protocols.io.e5gbg3w | G-Biosciences | The UPPA-PROTEIN Concentrate™ kit is used to quantitatively concentrate dilute protein samples as low as 1ng/ml into a small volume. Protein precipitation and concentration are not affected by the presence of detergents, chaotropics, or other common laboratory agents. | https://www.gbiosciences.com/image/pdfs/protocol/786-120_protocol.pdf | 1 | 2017 | G-Biosciences 2017. UPPA-PROTEIN Concentrate™. protocols.io dx.doi.org/10.17504/protocols.io.e5gbg3w | 2021-03-29 03:09:18 |
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