The protein sets for all newly included bacterial and archaeal genomes, the yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe, the microsporidian Encaephalitozoon cuniculi, the thale cress Arabidopsis thaliana, and the fruit fly Drosophila melanogaster were extracted from the Genome division of the (NCBI, NIH, Bethesda). The protein sequences for the nematode Caenorhabditis elegans were from the WormPep67 database, the sequences for Homo sapiens were from the NCBI build 30.
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Microspora
Microspora
Microspora: A diverse group of eukaryotic, single-celled organisms that play a crucial role in environmental ecosystems.
These microscopic fungi-like creatures are known for their unique life cycle and ability to infect a wide range of hosts, including insects, invertebrates, and even some vertebrates.
Microsporiosis, the disease caused by Microspora infections, can have significant impacts on human and animal health, making the study of these organisms a critical area of research.
PubCompare.ai's AI-driven platform can enhace the reproducibility and accuracy of Microspora research by helping scientists effortlessly locate the best protocols from literature, preprints, and patents, leveraging AI-driven comparisons to identify the most effective approaches.
Ths can take your Microspora studies to new heights and advance our understanding of these fasinating microbes.
These microscopic fungi-like creatures are known for their unique life cycle and ability to infect a wide range of hosts, including insects, invertebrates, and even some vertebrates.
Microsporiosis, the disease caused by Microspora infections, can have significant impacts on human and animal health, making the study of these organisms a critical area of research.
PubCompare.ai's AI-driven platform can enhace the reproducibility and accuracy of Microspora research by helping scientists effortlessly locate the best protocols from literature, preprints, and patents, leveraging AI-driven comparisons to identify the most effective approaches.
Ths can take your Microspora studies to new heights and advance our understanding of these fasinating microbes.
Most cited protocols related to «Microspora»
Amino Acid Sequence
Arabidopsis thalianas
Bacteria
Caenorhabditis elegans
Cuniculus
Drosophila
Drosophila melanogaster
Genome
Genome, Archaeal
Homo sapiens
Microspora
Nematoda
Proteins
Saccharomyces cerevisiae
Schizosaccharomyces pombe
Yeasts
Orthologous gene families were identified for the three Nematocida, seven other microsporidia, 12 fungi, and one choanoflagellate outgroup (see Supplemental Methods) using ORTHOMCL version 1.4 with a Markov inflation index of 1.5 and a maximum e-value of 1 × 10−5. To estimate a phylogeny, we selected 53 orthologs present as single copy in all genomes. Amino acid sequences of these clusters were aligned using MUSCLE (Edgar 2004 (link)), and poorly aligned regions were trimmed using trimAl under default settings (Capella-Gutierrez et al. 2009 (link)). We then estimated a phylogeny using the PROTGAMMABLOSUM62 model in RAxML (Stamatakis 2006 (link)) with 1000 bootstrap replicates. We compared this multi-ortholog-based phylogeny with phylogenies with Microsporidia repositioned to be (1) sister group to Rhizopus, and (2) sister group to the chytrids, with the approximately unibiased test (Shimodaira 2002 (link)) as implemented in CONSEL (Shimodaira and Hasegawa 2001 (link)), using the single-copy core amino acid alignments used to generate the organismal phylogeny. For further details, see the Supplemental Methods.
Amino Acids
Amino Acid Sequence
Choanoflagellata
Fungi
Genes
Genome
Microspora
Muscle Tissue
Rhizopus
Microsporidia MB specific primers (MB18SF: CGCCGGCCGTGAAAAATTTA and MB18SR: CCTTGGACGTGGGAGCTATC) were designed to target the Microsporidia MB 18S rRNA gene region and tested for specificity on a variety of Microsporidia-infected mosquito controls (including Hazardia, Parathelohania and Takaokaspora). For detection, the PCR reaction volume was 10 µl, consisting of 2 µl HOTFirepol® Blend Master mix Ready-To-Load (Solis Biodyne, Estonia, mix composition: 7.5 mM Magnesium chloride, 2 mM of each dNTPs, HOT FIREPol® DNA polymerase), 0.5 µl of 5 pmol µl−1 of both forward and reverse primers, 2 µl of the template and 5 µl nuclease-free PCR water. The PCR cyclic conditions used were; initial denaturation at 95 °C for 15 min, further denaturation at 95 °C for 1 min, followed by annealing at 62 °C for 90 s and extension at 72 °C for a further 60 s, all done for 35 cycles. Final elongation was done at 72 °C for 5 min. Microsporidia MB was also quantified by qPCR using MB18SF/ MB18SR primers, with normalization against the Anopheles ribosomal S7 host gene56 (link) (primers, S7F: TCCTGGAGCTGGAGATGAAC and S7R: GACGGGTCTGTACCTTCTGG). The primer efficiencies were determined using published methods57 (link). Samples were considered negative if the cycle threshold (Ct) value was greater than 35 or if the melt curve did not align with the positive control. These conditions were met for all negative control samples, which was DNA extracted from An. arabiensis from the insectary at icipe, Nairobi. The qPCR reaction volume was 10 µl, consisting of 2 µl HOT FIREPol® EvaGreen® HRM no ROX Mix (Solis Biodyne, Estonia, mix composition: 12.5 mM Magnesium chloride, EvaGreen® dye, BSA, dNTPs, HOT FIREPol® DNA Polymerase and 5× EvaGreen® HRM buffer), 0.5 µl of 5 pmol µl−1 of both forward and reverse primers, 2 µl of the template and 5 µl nuclease-free PCR water. Finally, melt curves were generated including temperature ranges from 65 °C to 95 °C. Standard curves were also generated to determine amplification efficiency. An. arabiensis were considered to be infected if Microsporidia MB was detected in either head and thorax or abdomen compartments. All reactions were carried out on a MIC qPCR cycler (Bio Molecular Systems, Australia).
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Abdomen
Anopheles
Buffers
Chest
DNA-Directed DNA Polymerase
Genes
Head
Magnesium Chloride
MICA protein, human
Microspora
Oligonucleotide Primers
Ribosomes
RNA, Ribosomal, 18S
Species identification was performed using BLASTn searches [49 (link)] against NCBI GenBank and the Barcode of Life Data System (BOLD) [50 (link)]. Additionally, relevant primary literature with available genetic data for amphipods or microsporidians was consulted. Identification was positive, if our query sequence showed at least 98 % sequence identity with one or more reference sequences. A 98 % identity threshold (or 2 % accepted intraspecific variability) was chosen for the identification of amphipods and microsporidian lineages. For the latter, our strategy accounts for potential intragenomic variability present in some microsporidians at the SSU rRNA locus [51 (link)], whereas a 2 % threshold for CO1 is far below commonly observed values of interspecific variability in amphipods [52 (link)]. For the identification of clades (or potential cryptic species) within G. pulex the CO1-alignment of Lagrue et al. [53 (link)] was used. For visualization of the different host and parasite lineages, Neighbor-Joining trees were calculated with the program MEGA6 [54 (link)] under the pairwise-deletion option for the CO1- and SSU rDNA—alignment, respectively. Node support was calculated by 1000 bootstrap replicates. Trees were rooted with the respective outgroup sequence. Outgroups were omitted for the final visualization of trees.
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Amphipoda
CFC1 protein, human
Deletion Mutation
DNA, Ribosomal
Microspora
Parasites
Reproduction
Ribosomal RNA
Trees
A total of 1339 residual nucleic acid extractions from stool samples were included in the assessment. Those materials comprised 20 residual samples from patients that had tested positive for intestinal microsporidiosis in the routine diagnostics department of the Bernhard Nocht Institute for Tropical Medicine in Hamburg (which is the German National Reference Center for Tropical Pathogens in Hamburg, Germany), 59 residual samples from a previous study in the Colombian tropics [42 (link)], 140 residual samples from migrants [43 (link)], 195 residual samples from German policemen deployed in the tropics [44 (link)], 22 residual samples from German soldiers [45 (link)] returning from tropical deployments, and 903 residual DNA samples from African HIV-positive patients from previous studies from Ghana [46 (link),47 (link)]. The samples were chosen to ensure a sufficient likelihood of intestinal carriage of microsporidia as associated with the history of travel [18 (link)] or immunosuppression [10 (link)]. In line with the ethical clearance for this test comparison, the residual sample materials were anonymized and no patient-specific data could be presented, which would be an admitted violation of the STARD (Standards for Reporting Diagnostic Accuracy) criteria [48 (link)]. All samples had been stored at −80 °C prior to their submission for periods between few months and 15 years.
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Diagnosis
Feces
HIV Seropositivity
Immunosuppression
Intestines
Microspora
Microsporidiosis
Migrants
Negroid Races
Nucleic Acids
pathogenesis
Patients
Police Officer
Soldiers
Most recents protocols related to «Microspora»
Whole-genome sequences of 10 O. colligata samples, each from a different D. magna clone collected from a different population, were obtained from the illumina sequencing (Table 1 ). Sequences from clones FI-SK-17-1, NO-V-7, and GB-EP-1 were reused from Haag et al. (2020) (link) (NCBI database; SRA accession: SRP211974, Bioproject ID: PRJNA419750), sequences from clone RU-BAYA1-1 were reused from Angst et al. (2022) (link) (NCBI database; SRA accession: SRP346323, Bioproject ID: PRJNA780787), and for clone FI-SK-17-1 additional sequencing was done. We used the D. longispina-specific Ordospora pajunii for analyses that needed an outgroup (NCBI database; Bioproject ID: PRJNA630072; de Albuquerque et al. 2022 (link)). Some samples with observed microsporidia gut infection (i.e. based on published criteria for identifying O. colligata infection) showed <1× average whole-genome coverage for O. colligata. To verify the presumed parasite at species level, we performed polymerase chain reactions (PCRs) of the small subunit of microsporidian ribosomal DNA followed by Sanger sequencing (Supplementary Table 1 and Methods ).
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Anxiety
Clone Cells
Genome
Hepatitis A Antigens
Infection
Microspora
Microsporidiosis
Parasites
Polymerase Chain Reaction
Ribosome Subunits, Small
We used parasites derived from material collected within the framework of a large-scale biogeographic study of the host species, D. magna (Fields et al. 2015 (link), 2018 (link), 2022 (link); Seefeldt and Ebert 2019 (link)). From each population, animals were brought to the laboratory and one iso-female line, i.e. clone, was created. We checked these clones for infections with microsporidia by phase-contrast microscopy, using squash-preparations or samples of the gut. The panel includes whole-genome sequencing of D. magna clones with illumina paired-end reads using HiSeq 2500 and NovaSeq 6000 sequencers.
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Animals
Clone Cells
Females
Host Specificity
Infection
Microscopy, Phase-Contrast
Microspora
Parasites
Squashes
For calculating the average number of nucleotide differences (π) between O. colligata genomes, we used pixy v.0.95 (Korunes and Samuk 2021 (link)). Beforehand, we filtered out alleles with less than half or more than double the average sample coverage. Finally, we averaged the estimated π-values over one Kilobase pair (kb) windows. Similarly, we calculated the non-/synonymous per-site nucleotide diversity (πN and πS) for the coding sequences of O. colligata using the script selectionStats.py (https://github.com/tatumdmortimer/popgen-stats ). Both methods are consistent with theoretical expectations and comparable among species as they take invariant sites into account for their calculations (Korunes and Samuk 2021 (link)). The ratio of πN and πS was separately calculated for BUSCO genes (Benchmarking Universal Single-Copy Orthologs) identified using BUSCO v.4.0.1 (Seppey et al. 2019 ) and its microsporidia_odb10 database (Creation date: August 05, 2020) and compared with published πN/πS values of H. tvaerminnensis (Angst et al. 2022 (link)).
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Alleles
Anxiety
Exons
Genes
Genome
Microspora
Nucleotides
For some analyses (specified below), it was necessary to remove the Encephalitozoon species. To this end, we defined an extended data set (including all species from “Protein and transcript data” above) and a core data set (from which the Encephalitozoon species were removed). In the analyses described in “Gene family histories” below, we used a core data set that excluded the Encephalitozoon species. This was because the microsporidia, which are distantly related to the fungi in the species tree and have severely reduced genomes, confounded these analyses and reduced our ability to detect gain and loss events in the Pneumocystis lineage.
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Encephalitozoon
Fungi
Genes
Genome
Microspora
Pneumocystis
Proteins
Trees
Escherichia coli DH5α
was used for cloning following standard recombinant DNA techniques. E. coli BL21(DE3) was used for expression of protein. Aspergillus oryzae NSAR1 (niaD–, sC–, ΔargB, adeA–) and A. oryzae NSPlD1 (niaD–, sC–, ΔpryG, ΔligD) were used as the host for fungal expression. Discosia sp. batta1 was used for genomic DNA preparation
and draft genome sequencing. Pestalotiopsis fici MAFF
237190, P. microspora NBRC 30316, and Aspergillus
candidus NBRC 8816 were used for genomic DNA preparation.
was used for cloning following standard recombinant DNA techniques. E. coli BL21(DE3) was used for expression of protein. Aspergillus oryzae NSAR1 (niaD–, sC–, ΔargB, adeA–) and A. oryzae NSPlD1 (niaD–, sC–, ΔpryG, ΔligD) were used as the host for fungal expression. Discosia sp. batta1 was used for genomic DNA preparation
and draft genome sequencing. Pestalotiopsis fici MAFF
237190, P. microspora NBRC 30316, and Aspergillus
candidus NBRC 8816 were used for genomic DNA preparation.
Aspergillus oryzae
Escherichia coli
Genome
Microspora
Pestalotiopsis fici
Proteins
Recombinant DNA
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More about "Microspora"
Microspora, also known as microsporidia, are a diverse group of eukaryotic, single-celled organisms that play a crucial role in environmental ecosystems.
These microscopic, fungi-like creatures are renowned for their unique life cycle and ability to infect a wide range of hosts, including insects, invertebrates, and even some vertebrates.
Microsporiosis, the disease caused by Microspora infections, can have significant impacts on human and animal health, making the study of these organisms a critical area of research.
To enhance the reproducibility and accuracy of Microspora research, scientists can leverage PubCompare.ai's AI-driven platform.
This innovative tool helps researchers effortlessly locate the best protocols from literature, preprints, and patents, leveraging AI-driven comparisons to identify the most effective approaches.
By utilizing PubCompare.ai, researchers can take their Microspora studies to new heights and advance their understanding of these fascinating microbes.
In the lab, researchers may employ various tools and techniques to study Microspora, such as the Axio Imager M1 compound microscope, EverBrite mounting medium, IQ SYBR Green Supermix for qPCR, and the Eclipse(50i) compound microscope.
Fluorescent dyes like Cal Fluor 610 and Calcofluor white can be used to visualize and identify Microspora spores, while extraction methods like the DNeasy Blood and Tissue Kit can be used to isolate DNA for molecular analyses.
Statistical software like Statistica 6.0 may also be utilized to analyze the data generated from Microspora studies.
By incorporating these insights and tools, researchers can elevate their Microspora research, leading to a deeper understanding of these intriguing microorganisms and their impact on ecosystems and human health.
These microscopic, fungi-like creatures are renowned for their unique life cycle and ability to infect a wide range of hosts, including insects, invertebrates, and even some vertebrates.
Microsporiosis, the disease caused by Microspora infections, can have significant impacts on human and animal health, making the study of these organisms a critical area of research.
To enhance the reproducibility and accuracy of Microspora research, scientists can leverage PubCompare.ai's AI-driven platform.
This innovative tool helps researchers effortlessly locate the best protocols from literature, preprints, and patents, leveraging AI-driven comparisons to identify the most effective approaches.
By utilizing PubCompare.ai, researchers can take their Microspora studies to new heights and advance their understanding of these fascinating microbes.
In the lab, researchers may employ various tools and techniques to study Microspora, such as the Axio Imager M1 compound microscope, EverBrite mounting medium, IQ SYBR Green Supermix for qPCR, and the Eclipse(50i) compound microscope.
Fluorescent dyes like Cal Fluor 610 and Calcofluor white can be used to visualize and identify Microspora spores, while extraction methods like the DNeasy Blood and Tissue Kit can be used to isolate DNA for molecular analyses.
Statistical software like Statistica 6.0 may also be utilized to analyze the data generated from Microspora studies.
By incorporating these insights and tools, researchers can elevate their Microspora research, leading to a deeper understanding of these intriguing microorganisms and their impact on ecosystems and human health.