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> Living Beings > Eukaryote > Porifera

Porifera

Porifera, commonly known as sponges, are a diverse group of aquatic invertebrate animals that belong to the phylum Porifera.
Sponges are characterized by their porous bodies and a unique water vascular system that allows them to filter feed.
They are found in a variety of marine and freshwater environments, ranging from shallow coastal areas to deep oceans.
Sponges play a crucial role in many ecosystems, serving as important habitats for a wide range of organisms.
Reserach on porifera is vital for understanding their biology, ecology, and potential applications in fields such as pharmacology and biotechnology.
Pucompare.ai enhances porifera reseach by helping users locate the most reproducible and acurate protocols from literature, pre-prints, and patents, allowing researchers to optimize their sponge studies and streamline their workflow.

Most cited protocols related to «Porifera»

1
Robust Aitchison PCA for Beta Diversity
Cited 61 times
Case studies on real-world data sets were used to compare robust Aitchison PCA to the current state of the art in beta diversity comparison. The sponge, sleep apnea, infant, keyboard, and 88-soil data sets were acquired on 20 September 2018 from Qiita (47 (link)) with IDs of 10793, 10422, 101, 232, and 103, respectively. Each data set was run through Qiita with default trimming and Deblur (v. 1.1.0) sOTU (48 (link)) picking approach, using QIIME 2 (v. 2018.6.0) (49 (link)). The resulting BIOM (50 (link)) tables were then filtered for samples greater than 1,000 reads per sample. Phylogeny was built using the most up-to-date GreenGenes using SEPP (51 (link)), and taxonomy was assigned through scikit-learn with default QIIME 2 parameters.
The sponge data set was filtered using the metadata so that it contained only samples with either the label healthy or the label stressed. This resulted in a comparison with 218 remaining samples. Similarly, the sleep apnea study was filtered for IHH and air control samples, with a treatment duration of 6 weeks resulting in 189 remaining samples. The infant gut colonization case study was filtered for samples over 500 reads/sample and for a single sample from the mother with the title 101.Mother. The 88-soil data set was filtered for samples over 500 reads/samples. The keyboard data set was filtered for samples over 500 reads/sample and 15 reads/sOTU. Additionally, only subject IDs corresponding to M3, M2, and M9 were retained, giving 67 samples. For comparing ordinations at different numbers of samples, the data sets were filtered for having 1,000 sequences/sample and balanced to have equal numbers of each subgroup (i.e., equal Air and IHH samples). Then samples were removed randomly but equally from each subgroup; this was repeated 10 times. The first iteration was used to plot the ordinations, and the mean score of the iterations was used to plot KNN classification accuracy and PERMANOVA F-statistic.
Both data sets were then preprocessed with the robust centered log ratio (rclr) transform, and RPCA was run with a rank of 2 because there were two metadata categories of interest in each comparison. Weighted UniFrac distances were calculated using generalized UniFrac with an alpha of one (52 (link)). Bray-Curtis distances were calculated through QIIME 2 (49 (link)). Both weighted UniFrac and Bray-Curtis distances were calculated on tables rarefied to 1,000 reads per sample. PCoA and PERMANOVA analyses for the Bray-Curtis, RPCA distance matrix, and weighted UniFrac were calculated through scikit-bio. The resulting PCoA and PCA axes were plotted through matplotlib (53 (link)) with PC1 and PC2 in the x and y axes, respectively.
The original unprocessed (raw count) tables were sorted by feature loadings from RPCA. Features with a count sum of less than 10 across all samples were filtered out. The resulting table was then clr transformed with a pseudocount of one and plotted as a heat map. Each sOTU was given the lowest classification for the sleep apnea and sponge data sets, respectively.
The features in the PC1 axis of the feature loadings from RPCA were selected to represent a manageable number of taxa to compare between subgroups. Those selected features (sOTUs) from the feature loadings were used for log ratios. Log ratios were calculated from the table used to calculate them. The samples that contained zeros in either the numerator or denominator were removed before calculating the ratios. The correlations between the log ratio and PC1 axis were performed by Pearson correlation via SciPy (54 ).
Martino C., Morton J.T., Marotz C.A., Thompson L.R., Tripathi A., Knight R, & Zengler K. (2019). A Novel Sparse Compositional Technique Reveals Microbial Perturbations. mSystems, 4(1), e00016-19.
Publication 2019
Apnea Axial Loading Epistropheus Infant Mothers One-Alpha Polysomnography Porifera Sleep Apnea Syndromes
2
Global Microbiome Sampling Protocol
Cited 38 times
The global community of microbial ecologists was invited to submit samples for microbiome analysis, and samples were accepted for DNA extraction and sequencing provided that scientific justification and high-quality sample metadata were provided before sample submission. Standardized sampling procedures for each sample type were used by contributing investigators. Samples were collected fresh and, where possible, immediately frozen in liquid nitrogen and stored at −80 °C. Detailed sampling protocols are described in publications of the individual studies (Supplementary Table 1). Bulk samples (e.g., soil, sediment, feces) and fractionated bulk samples (e.g., sponge coral surface tissue, centrifuged turbid water) were taken using microcentrifuge tubes. Swabs (BD SWUBE dual cotton swabs or similar) were used for biofilm or surface samples. Filters (Sterivex cartridges, 0.2 μm, Millipore) were used for water samples. Samples were sent to laboratories in the United States for DNA extraction and sequencing: water samples to Argonne National Laboratory, soil samples to Lawrence Berkeley National Laboratory (pre-2014) or Pacific Northwest National Laboratory (2014 onward), and fecal and other samples to the University of Colorado Boulder (pre-2015) or the University of California San Diego (2015 onward).
Thompson L.R., Sanders J.G., McDonald D., Amir A., Ladau J., Locey K.J., Prill R.J., Tripathi A., Gibbons S.M., Ackermann G., Navas-Molina J.A., Janssen S., Kopylova E., Vázquez-Baeza Y., González A., Morton J.T., Mirarab S., Zech Xu Z., Jiang L., Haroon M.F., Kanbar J., Zhu Q., Jin Song S., Kosciolek T., Bokulich N.A., Lefler J., Brislawn C.J., Humphrey G., Owens S.M., Hampton-Marcell J., Berg-Lyons D., McKenzie V., Fierer N., Fuhrman J.A., Clauset A., Stevens R.L., Shade A., Pollard K.S., Goodwin K.D., Jansson J.K., Gilbert J.A, & Knight R. (2017). A communal catalogue reveals Earth’s multiscale microbial diversity. Nature, 551(7681), 457-463.
Publication 2017
Biofilms Coral Dietary Fiber Feces Freezing Gossypium Microbial Community Microbiome Nitrogen Porifera Tissues
3
Standardized Microbiome Sampling Protocol
Cited 37 times
The global community of microbial ecologists was invited to submit samples for microbiome analysis, and samples were accepted for DNA extraction and sequencing provided that scientific justification and high-quality sample metadata were provided before sample submission. Standardized sampling procedures for each sample type were used by contributing investigators. Samples were collected fresh and, where possible, immediately frozen in liquid nitrogen and stored at –80 °C. Detailed sampling protocols are described in publications of the individual studies (Supplementary Table 1). Bulk samples (for example, soil, sediment, faeces) and fractionated bulk samples (for example, sponge coral surface tissue, centrifuged turbid water) were taken using microcentrifuge tubes. Swabs (BD SWUBE dual cotton swabs or similar) were used for biofilm or surface samples. Filters (Sterivex cartridges, 0.2 μm, Millipore) were used for water samples. Samples were sent to laboratories in the United States for DNA extraction and sequencing: water samples to Argonne National Laboratory, soil samples to Lawrence Berkeley National Laboratory (pre-2014) or Pacific Northwest National Laboratory (2014 onward), and faecal and other samples to the University of Colorado Boulder (pre-2015) or the University of California San Diego (2015 onward).
Thompson L.R., Sanders J.G., McDonald D., Amir A., Ladau J., Locey K.J., Prill R.J., Tripathi A., Gibbons S.M., Ackermann G., Navas-Molina J.A., Janssen S., Kopylova E., Vázquez-Baeza Y., González A., Morton J.T., Mirarab S., Zech Xu Z., Jiang L., Haroon M.F., Kanbar J., Zhu Q., Jin Song S., Kosciolek T., Bokulich N.A., Lefler J., Brislawn C.J., Humphrey G., Owens S.M., Hampton-Marcell J., Berg-Lyons D., McKenzie V., Fierer N., Fuhrman J.A., Clauset A., Stevens R.L., Shade A., Pollard K.S., Goodwin K.D., Jansson J.K., Gilbert J.A, & Knight R. (2017). A communal catalogue reveals Earth’s multiscale microbial diversity. Nature, 551(7681), 457-463.
Publication 2017
Biofilms Coral Dietary Fiber Feces Freezing Gossypium Microbial Community Microbiome Nitrogen Porifera Tissues
4
Osteocyte-like phenotype culture
Cited 26 times
Tissue culture media were purchased from GIBCO BRL, fetal bovine serum (FBS) was from BioWhittaker. Rat tail collagen type 1, 99% pure, was purchased from Becton Dickinson Laboratories. All other reagents were purchased from Sigma Chemical Co. unless otherwise stated. Cells were expanded in permissive conditions (33°C in αMEM with 10% FBS, 100 units/ml penicillin, 50 µg/ml streptomycin, and 50 U/ml IFN-γ) on rat tail type I collagen-coated plates or gels or bovine type I collagen sponges. To induce osteogenesis, cells were plated at 80,000 cells/cm2 in osteogenic conditions (37°C with 50 µg/ml ascorbic acid and 4 mM β-glycerophosphate in the absence of IFN-γ). Collagen-coated surfaces were used because they were found to be effective at maintaining an osteocyte-like phenotype (10 (link)).
MLO-A5 cells, used as controls, are an established model of late osteoblasts with the ability to rapidly synthesize mineralized extracellular matrix (1 (link)). MLO-A5 cells are highly responsive to mechanical loading in 3D culture (15 (link)). MLO-Y4 cells, also used as controls, are an established model of osteocytes.
Woo S.M., Rosser J., Dusevich V., Kalajzic I, & Bonewald L.F. (2011). Cell Line IDG-SW3 Replicates Osteoblast-to-Late-Osteocyte Differentiation in vitro and Accelerates Bone Formation in vivo. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research, 26(11), 2634-2646.
Publication 2011
Ascorbic Acid beta-glycerol phosphate Bos taurus Cells Collagen Collagen Type I Culture Media Extracellular Matrix Fetal Bovine Serum Gels Interferon Type II Osteoblasts Osteocytes Osteogenesis Penicillins Phenotype Porifera Streptomycin Tail Tissues
5
Bacterial Diversity in Deep-Sea Sponges
Cited 21 times
We sequenced the V4-V5 region of bacterial rRNA genes from 19 deep-sea sponge and 5 control water samples. Samples were collected at locations along >5000 km of the European margins and spanned wide bathymetric gradients (130–958 m) (Reveillaud et al., 2014 (link)).
Eren A.M., Morrison H.G., Lescault P.J., Reveillaud J., Vineis J.H, & Sogin M.L. (2014). Minimum entropy decomposition: Unsupervised oligotyping for sensitive partitioning of high-throughput marker gene sequences. The ISME Journal, 9(4), 968-979.
Publication 2014
Europeans Genes, Bacterial Porifera Ribosomal RNA

Most recents protocols related to «Porifera»

1
Biocompatible Column for Concurrent Micro-PET/SPECT
Not available on PMC !

Example 1

FIG. 1 shows the biocompatible column 1 for concurrent micro-PET or micro-SPECT of the first cell culture 6a and the second cell culture 6b, which are both MTS. The column comprises the inlet 2, the axially oriented perfusion chamber 3 and the outlet 4. Both the inlet 2 and the outlet 4 are fluidly connected to the perfusion chamber 3. The perfusion chamber 3 comprises porous solid phase formed by four sponges, 7c, 7d, 7a, 7b, made of a biopolymer and which were pre-cut to fit into perfusion chamber 3. The liquid phase 5 consisting of growth medium extends from the inlet 2 through sponges 7c, 7d, 7a, 7b to the outlet 4. Sponges 7a and 7b have recesses 8a and 8b, respectively. The first cell culture 6a is located within recess 8a being in contact with sponge 7a, and the second cell culture 6b is located within recess 8b being in contact with sponge 7b. Sponges 7c and 7d neither have a recess nor a cell culture. The first cell culture 6a and the second cell culture 6b our separated from each other by sponge 7a. The column 1 further has one filter 50 adjacent to the inlet 2 and another filter 50 adjacent to sterile filter 51, which is adjacent to the outlet 4.

US11866684B2. Device and method for micro-PET or micro-SPECT of a cell culture (2024-01-09). DOC MEDIKUS GMBH [AT]. Inventors: Verena Pichler [AT].
Patent 2024
Biopolymers Cell Culture Techniques Culture Media Perfusion Porifera Sterility, Reproductive Tomography, Emission-Computed, Single-Photon
2
Micro-PET Imaging of 3D Cell Cultures
Not available on PMC !

Example 3

Four different columns were introduced into the micro-PET scanner and scanned:

    • a) a column prepared with silk sponges without cell cultures (background measurement),
    • b) a column prepared with spheroids pre-incubated with [18F] FDG (signal-to-noise ratio measurement),
    • c) a column prepared with spheroids which were placed in different distances and the [18F] FDG was introduced in a stop-flow mechanism (see FIG. 5), and
    • d) a column prepared with cells grown on silk sponges with a cell-free sponge in between (see FIG. 6).

The scan of column a) showed low binding of [18F] FDG to the silk sponge and low unspecific binding of polar compounds to silk in general.

The scan of column b) clearly indicated that the spheroids could be successfully detected within the column.

The scan of column c) confirmed the low specific binding of [18F] FDG to the silk scaffold, and portrayed a surprisingly high resolution between the spheroids, as all spheroids could be imaged separately, except for the spheroids 2 and 3. This result is particularly important, as the spheroid size of approximately 700 μm lies below the resolution of the micro-PET device used.

The scan of column d) clearly highlights the regions with HT29 cells (see FIG. 6), further indicating the high potential of the present invention.

US11866684B2. Device and method for micro-PET or micro-SPECT of a cell culture (2024-01-09). DOC MEDIKUS GMBH [AT]. Inventors: Verena Pichler [AT].
Patent 2024
Cell Culture Techniques F18, Fluorodeoxyglucose HT29 Cells Medical Devices Porifera Radionuclide Imaging Silk
3
In Vitro Drug Evaluation in 3D Bioscaffold
Not available on PMC !

Example 2

The main objective of the system is to facilitate in vitro drug and especially PET or SPECT tracer development by providing a method applicable for assessment of drug distribution, accumulation, metabolism and excretion in a 3D bioscaffold with interstitial stop-flow conditions. The system consists of a mobile phase, which delivers nutrients, O2 and CO2 as well as the drug/tracer or modifiers over a constant flow through a biological stationary phase consisting of cells, MTS or organoids embedded in biopolymer sponges. A prototype of the column with the biological stationary phase is shown in FIG. 2.

The system furthermore comprises a controllable pump system, an apparatus to fixate the column and control the temperature, as well as a micro-PET scanner as detection unit (see FIG. 3).

An example for preparation of the biocompatible column is shown in FIG. 4.

US11866684B2. Device and method for micro-PET or micro-SPECT of a cell culture (2024-01-09). DOC MEDIKUS GMBH [AT]. Inventors: Verena Pichler [AT].
Patent 2024
Biopharmaceuticals Biopolymers Cells Metabolism Nutrients Organoids Pharmaceutical Preparations Pharmacy Distribution Porifera Tomography, Emission-Computed, Single-Photon
4
Eukaryotic Transcriptome Analysis from Sponge Samples
RNA was extracted using Allprep DNA/RNA mini kit (Qiagen, Germany). Briefly, each extraction was performed using 30 mg of sponge sample placed in a Lysing Matrix E tube (MP Biomedicals, Santa Ana, CA) to which RLT buffer containing Reagent DX (Qiagen, Hilden, Germany) was added. Cells were disrupted using a TissueLyser II system (Qiagen, Germany) for 30 s at 30 Hz followed by 10-min centrifugation at maximum speed. All subsequent RNA extraction steps were performed according to the manufacturer’s protocol. SUPERase In (Life Technologies, USA) and TURBO DNA-free kit (Thermo Fisher Scientific, USA) were used for RNase inhibition and DNase treatments, respectively. RNA cleanup and concentration were done using the RNeasy MinElute kit (Qiagen, Germany). In order to achieve sufficient coverage of informative nonribosomal transcripts, rRNA was removed with a RiboMinus Eukaryote System V2 kit (Ambion, Life Technologies, USA) with eukaryotic mouse-rat-human probes coupled with prokaryotic probes. ERCC RNA Spike-In Control mixes (Life Technologies, USA) were added to 5 µg of total RNA. RNA concentrations were measured using a Qubit 2.0 Fluorometer and RNA reagents (Thermo Fisher Scientific, USA), before and after rRNA depletion. In parallel, RNA integrity and purity were determined using a TapeStation 2200 system, applying the High sensitivity RNA Screen Tape assay (Agilent Technologies, USA), before and after rRNA depletion as well. Ultimately, 13ng of rRNA-depleted RNA was processed for cDNA library preparations using the Collibri stranded RNA library prep kit (Thermo Fisher Scientific, USA) according to the manufacturer’s protocol with the sole exception being that, following the addition of the index codes, cDNA amplification was performed with 8 rather than the 9–11 recommended PCR cycles. The number of PCR cycles was optimized for our samples to reduce PCR bias. The libraries were quantified using Invitrogen Collibri Library Quantification Kit (Invitrogen, Thermo Fisher Scientific) according to the manufacturer’s guide using real-time qPCR. For pre-sequencing quality control (QC), 2-μl aliquots of each provided library were pooled. The resulting QC pool was size and concentration checked on an Agilent D1000 TapeStation system and a Qubit 2.0 fluorometer, respectively. The pool was adjusted to 1nM and loaded on an Illumina MiniSeq Mid Output flow cell at 1.5pM. After demultiplexing, the percent of each library was used to calculate new volumes to use for constructing a normalized sequencing pool. This pool was also size and concentration checked, as described above, and subsequently normalized to 2nM. The normalized pool was run on an Illumina NextSeq High Output flowcell at 2.2pM.
Ramírez G.A., Bar-Shalom R., Furlan A., Romeo R., Gavagnin M., Calabrese G., Garber A.I, & Steindler L. (2023). Bacterial aerobic methane cycling by the marine sponge-associated microbiome. Microbiome, 11, 49.
Publication 2023
Biological Assay Buffers cDNA Library Cells Centrifugation Deoxyribonucleases DNA, Complementary Endoribonucleases Eukaryota Homo sapiens Hypersensitivity Mus Porifera Prokaryotic Cells Psychological Inhibition Ribosomal RNA
5
Sampling Adriatic Aplysina aerophoba
Mediterranean Aplysina aerophoba specimens were sampled from the Northern Adriatic in the Gulf of Trieste (45°36.376, 13°43.1874), using SCUBA, within meters of each other. Four individual sponge specimens were separately sampled twice in a 24-h period (at 12:00 noon day 1 and 12:00 noon day 2). Immediately upon collection, all tissues were in situ preserved in RNALater® (Sigma-Aldrich) solution using an underwater chamber as detailed elsewhere [60 (link)] and, once out of the water, kept on ice for a few hours prior to freezing and transport to shore-based storage at −80°C.
Ramírez G.A., Bar-Shalom R., Furlan A., Romeo R., Gavagnin M., Calabrese G., Garber A.I, & Steindler L. (2023). Bacterial aerobic methane cycling by the marine sponge-associated microbiome. Microbiome, 11, 49.
Publication 2023
Porifera Tissues

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More about "Porifera"

Sponges, also known as poriferans, are a diverse group of aquatic invertebrate animals that belong to the phylum Porifera.
These fascinating creatures are characterized by their porous bodies and a unique water vascular system, which allows them to filter feed.
Sponges can be found in a variety of marine and freshwater environments, from shallow coastal areas to the deep oceans, and play a crucial role in many ecosystems, serving as important habitats for a wide range of organisms.
Research on sponges, or poriferans, is vital for understanding their biology, ecology, and potential applications in fields such as pharmacology and biotechnology.
PubCompare.ai, an innovative AI-driven platform, enhances porifera research by helping users locate the most reproducible and accurate protocols from literature, pre-prints, and patents.
This allows researchers to optimize their sponge studies and streamline their workflow.
In addition to sponges, other key topics related to porifera research include the use of various reagents and tools, such as DC-Stimulator Plus, FBS (Fetal Bovine Serum), Gelfoam, Lipofectamine 2000, DC-STIMULATOR, Lipiodol, Progreat, S-4800, Puromycin, and Lipiodol Ultra-Fluide.
These products and technologies can play a vital role in various aspects of porifera research, from cell culture and transfection to imaging and drug delivery.
By leveraging the insights and capabilities of PubCompare.ai, researchers can elevate their porifera studies, uncover new discoveries, and contribute to the broader understanding of these fascinating aquatic invertebrates and their potential applications in diverse fields.