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Xanthomonas

Xanthomonas is a genus of Gram-negative bacteria that includes several important plant pathogens.
These bacteria cause a variety of diseases in a wide range of crops, such as bacterial spot in tomatoes and peppers, and bacterial blight in rice and other cereals.
Xanthomonas species are characterized by the production of yellow pigments and the ability to form biofilms, which contribute to their pathogenicity.
Understanding the biology and control of these bacteria is crucial for protecting agricultural yields and ensuring food security.
Reseachers can leverage the power of AI-driven protocol comparisons through PubCompare.ai to optimize their Xanthomonas studies, enhance reproducibility, and identify the best protocols and products with ease.
Experienece the power of AI-powered research optimization today.

Most cited protocols related to «Xanthomonas»

1
Identifying Orthologous Genes for Phylogenetic Analysis
We applied a stringent criterion for eliminating nonhomologous sequences and paralogous sequences, since both are likely to lead to false conclusions regarding the organismal phylogeny and frequency of LGT. In particular, the criterion of “best reciprocal hits” between sequences for a genome pair can lead to false conclusions of orthology because the resulting gene pairs are not always closest relatives phylogenetically (Koski and Golding 2001 (link)). Instead, we used a cutoff for the degree of similarity as reflected in the BLASTP bit scores (Altschul et al. 1997 (link)). The bit score is dependent upon the scoring system (substitution matrix and gap costs) employed and takes into account both the degree of similarity and the length of the alignment between the query and the match sequences. We used it to detect homologous genes, described as follows. A bank of all annotated protein sequences of all included species was created. A BLASTP (Altschul et al. 1997 (link)) search was performed for all the proteins in each genome against the protein bank. This implies that all proteins were searched against both their resident genome and those from the 12 other species. The match of a given protein against itself gives a maximal bit score. To determine a threshold to group genes into a family, we examined the distribution of the ratio of the bit score to the maximal (self) bit score based on the proteins of E. coli compared against proteins of the 12 genomes (Figure 6). In each case, the distribution showed a clear bimodal pattern with a first peak of low similarity values, which is constant among comparisons and therefore probably represents random matches, and a second peak of higher similarity values, representing true homologous genes. For comparisons of E. coli proteins with those of the most distant species in our set, such as Vibrio, Xanthomonas, Xylella, and Pseudomonas, the separation of the two portions of the distribution occurs at about 30% of the maximal bit score. Thus, in order to apply a stringent criterion for homology, we inferred as homologous genes those presenting a bit score value higher or equal to 30% of the maximal bit score. A protein was included in a family if this criterion was satisfied for at least one member. Our cutoff was chosen to minimize inclusion of nonhomologous sequences within a family; consequently, it may exclude some homologs, especially fast-evolving ones.
After establishing homolog families, we selected the set that contained a single sequence in each represented genome and regarded these as likely orthologs that could give information about the organismal phylogeny and the frequency of LGT affecting orthologs in this bacterial group.
Lerat E., Daubin V, & Moran N.A. (2003). From Gene Trees to Organismal Phylogeny in Prokaryotes:The Case of the γ-Proteobacteria. PLoS Biology, 1(1), e19.
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Publication 2003
Bacteria Escherichia coli Proteins Genes Genes, vif Genome Proteins Pseudomonas Staphylococcal Protein A Vibrio Xanthomonas Xylella
2
Comparative Genomics of Stenotrophomonas Species
On August 1st, 2017, a total of 169 annotated Stenotrophomonas genome sequences were available in RefSeq, 134 of which were labeled as S. maltophilia. The corresponding GenBank files were retrieved, as well as the corresponding table with assembly metadata. Seven complete Xanthomonas spp. genomes were also downloaded to use them as outgroup sequences. In January 2018, the genome sequence of S. bentonitica strain VV6 was added to RefSeq and included in the revised version of this work to increase the taxon sampling.
Vinuesa P., Ochoa-Sánchez L.E, & Contreras-Moreira B. (2018). GET_PHYLOMARKERS, a Software Package to Select Optimal Orthologous Clusters for Phylogenomics and Inferring Pan-Genome Phylogenies, Used for a Critical Geno-Taxonomic Revision of the Genus Stenotrophomonas. Frontiers in Microbiology, 9, 771.
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Publication 2018
Genome Stenotrophomonas Strains Xanthomonas
3
Identifying Conserved Panorthologs Across Genomes
We began computation of putative panorthologs for each set of genomes using NCBI BLASTP (release 2.2.16) to analyze all genes in all genomes for sequence similarity. We kept for later processing all BLAST hits within an E-value threshold of 1. These hits include each gene's self hit. We stored the E-value, bit score and alignment length for each hit. When running BLASTP, we used default parameters except for setting the E-value threshold and for setting the maximum number of hits to keep.
We next identified homologs as those gene pairs that had BLAST hits in both directions within a given scaled bit score threshold. We scaled the bit scores by the bit score of the self hit of the query gene. That is, scaledBitScore(A->B) = bitScore(A->B)/bitScore(A->A). This method has been used previously to identify conserved homologs among bacterial genomes and has been shown to be more stringent than criteria based solely on reciprocal best matches using E values [17] (link).
We then formed homolog families by including two genes in a family if they had been identified as homologs. Note that not all pairs of genes in a family need to be identified as homologs. For example, if A and B are homologs, and B and C are homologs, then A and C will be in the same family even if A and C have not been identified as homologs. Finally we identified the putative panorthologs as being the genes from homolog families with exactly one gene from each genome. For each set of genomes we kept the largest set of panorthologs found by computing the putative panorthologs while varying the scaled bit score threshold from .1 to .9 in .1 increments.
The following scaled bit score thresholds were used for genome sets A–E depicted in Fig. 1, followed by the number of putative panorthologs identified at that threshold: group A: threshold = 0.7, 4141 panorthologs; group B: 0.7, 3758, group C: 0.4, 2203, group D: 0.3, 902, group E: 0.2, 581. To produce groups d and e, the five Bordetella genomes were first analyzed by this method (0.5, 1592) as well as the five Xanthomonas genomes (0.5, 2450). The intersections of these Bordetella and Xanthomonas panortholog sets with groups b and c were used to produce groups d and e, respectively.
Cooper V.S., Vohr S.H., Wrocklage S.C, & Hatcher P.J. (2010). Why Genes Evolve Faster on Secondary Chromosomes in Bacteria. PLoS Computational Biology, 6(4), e1000732.
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Publication 2010
Bordetella Genes Genome Genome, Bacterial Intersectional Framework MLL protein, human Xanthomonas
4
Genome Assembly and Annotation of Xanthomonas oryzae
Multiple rounds of assembly were performed, beginning with the shotgun reads and later including additional finishing reads. In the final assembly, 65,620 reads were trimmed to remove vector and low-quality sequence, and then assembled using Celera Assembler [63 (link)]. The large (212 kb) tandem repeat was initially collapsed into one copy, which had twice the depth of coverage of the rest of the genome. This anomaly was detected and corrected to two copies after analysis aided by the Hawkeye assembly diagnosis software [23 (link)]. Protein-coding genes were identified using Glimmer 3.0, which includes an algorithm to identify ribosome binding sites for each gene. Transcription terminators were predicted using TransTermHP [66 (link)] with parameter settings expected to yield over 90% accuracy. Transfer RNAs were identified with tRNAScanSE [67 (link)]. Regions with neither Glimmer predictions nor RNA genes were searched in all six frames using blastx [68 (link)] to identify any missed proteins, and all annotations were manually curated as described previously [69 (link)], using the Manatee online annotation system [70 ]. The origin and terminus of replication was determined using GC-skew analysis [18 (link)], which indicates an origin near position 50 kb and termini near 2,370 kb or 2,510 kb. The chromosome replication initiator gene dnaA, which is commonly found near the origin, is at position 45. Oligomer skew analysis [71 (link)], which identifies 8-mers preferentially located on the leading strand, indicates an origin at 4,895 kb (30 kb from the end of the genome) and a terminus at 2,381 kb, based on multiple 8-mers including CCCTGCCC and AGGACCAT. These 8-mers occur 328/376 and 218/248 times (over 87%) on the leading strand; for CCCTGCCC the likelihood that this occurred by chance is 3.6x10-45. To determine genome rearrangements, the MUMmer/Nucmer suite of genome alignment programs [72 (link)] was used to align Xoo PXO99A to the MAFF and KACC strains as well as to all other Xanthomonas genomes.
Salzberg S.L., Sommer D.D., Schatz M.C., Phillippy A.M., Rabinowicz P.D., Tsuge S., Furutani A., Ochiai H., Delcher A.L., Kelley D., Madupu R., Puiu D., Radune D., Shumway M., Trapnell C., Aparna G., Jha G., Pandey A., Patil P.B., Ishihara H., Meyer D.F., Szurek B., Verdier V., Koebnik R., Dow J.M., Ryan R.P., Hirata H., Tsuyumu S., Won Lee S., Ronald P.C., Sonti R.V., Van Sluys M.A., Leach J.E., White F.F, & Bogdanove A.J. (2008). Genome sequence and rapid evolution of the rice pathogen Xanthomonas oryzae pv. oryzae PXO99A. BMC Genomics, 9, 204.
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Publication 2008
Binding Sites Chromosomes Cloning Vectors Diagnosis DNA Replication Gene Order Gene Products, Protein Gene Rearrangement Genes Genome GPER protein, human Proteins Reading Frames Replication Origin Ribosomes Strains Tandem Repeat Sequences Transcription, Genetic Transfer RNA Trichechus Xanthomonas
5
Automated TAL Effector Gene Assembly
For each strain, a list of raw reads for tal gene regions was generated by using blasr (Chaisson & Tesler, 2012 (link)) to align reads to the BLS256 tal gene sequences, following the PacBio hgap Whitelisting protocol (PacBio, 2013a ). Next, a modification of the RS_PreAssembler protocol included in SMRTAnalysis 2.0 was run on these reads. In this modification, which we designated the RS_PreAssembler_TALs protocol, the ‘whiteList’ parameter for the filtering step was set to the tal gene read list. The minimum read-length cut-off was set to 4000, the seed read-length cut-off was set to 16000 to ensure that short-read to long-read alignments used for correction would be long enough to be unambiguous and the maxLCPLength was set to 14, as recommended for data using the XL-C2 enzyme and chemistry (PacBio, 2013b ). Specifically, the blasr options string was changed to ‘-minReadLength 4000 -maxScore −1000 -bestn 24 -maxLCPLength 14 -nCandidates 24’.
After preassembly, corrected reads were trimmed to estimated QV50 windows and filtered to those > 4000 bp using the SMRTAnalysis 2.0 trimFastqByQVWindow.py utility. Based on comparison with the reference genomes, these reads are typically 97% accurate. Reads were assembled using the Minimo assembler of amos 3.1.0 (Treangen et al., 2011 ), using NUCmer 3.1 (Kurtz et al., 2004 (link)) for the overlap step, for all 16 combinations of a 500, 1000, 2000 and 3000 minimum overlap length, and 91, 93, 95 and 97 minimum overlap per cent identity. Contig sets generated by each of these assemblies were polished separately with the RS_Resequencing protocol included in SMRTAnalysis 2.0. This protocol aligns reads to the assembled regions and uses the Quiver algorithm to call the consensus, regularly achieving 99.999% accuracy in regions with ≥60× coverage (Chin et al., 2013 (link)). For this, read filtering settings were set to those used for preassembly, the ‘Place Repeats Randomly’ option was unchecked and all other settings were left at defaults.
RVD sequences were determined from the 16 polished tal gene assemblies using a consensus approach. For each contig across all polished assemblies, encoded TAL effector CRRs were extracted and split into RVD sequences by conserved boundaries. Inspecting a sorted list of unique RVD sequences and the number of times they were encountered in the 16 assemblies (e.g. File S1, available in the online Supplementary Material), sequences ending in frameshifts or other anomalies that were prefixes of other sequences that occurred more often were discarded. The resulting list was retained as the correct RVD sequences. As an additional measure in case any tal genes were incompletely assembled before polishing, assemblies of the polished contigs in each set were carried out, again with Minimo, and the RVD sequence consensus process repeated. In all cases the results were identical.
This workflow for assembly of tal genes and extraction of encoded RVD sequences, which we have named the pbx toolkit, is automated and available on GitHub (https://github.com/boglab/pbx). The only required input is the path to a folder containing bas.h5 and bax.h5 files of raw sequence reads. Additional options allow specifying the sequences to use for identifying tal gene reads and the conserved repeat boundaries to use for RVD sequence determination. This enables the workflow to be easily adapted for use with other Xanthomonas genomes.
Booher N.J., Carpenter S.C., Sebra R.P., Wang L., Salzberg S.L., Leach J.E, & Bogdanove A.J. (2015). Single molecule real-time sequencing of Xanthomonas oryzae genomes reveals a dynamic structure and complex TAL (transcription activator-like) effector gene relationships. Microbial Genomics, 1(4), e000032.
Publication 2015
Chin Conserved Sequence Enzymes Frameshift Mutation Genes Genome hGAP Microcephalic Osteodysplastic Primordial Dwarfism, Type I Sequence Determinations Strains Transcription Activator-Like Effectors Tremor Xanthomonas

Most recents protocols related to «Xanthomonas»

1
Antimicrobial Evaluation of Leaf Extract and AgNPs
The antibacterial activity of the leaf extract and the biosynthesized AgNPs was assessed against Staphylococcus aureus (Gram-positive bacteria) and Xanthomonas spp. (Gram-negative bacteria) using the agar well diffusion method. Before use, the nutrient agar and petri dish were autoclaved. Then, 0.1 mL of pure bacterial culture was evenly spread on nutrient agar plates using an L-rod. Then, wells created by the well borer on agar plates were filled with 20 μL of aqueous samples of leaf extract and AgNPs (1000 ppm). Streptomycin and distilled water were employed as the positive and negative control, respectively. The plates were finally incubated at 37 °C for 24 h to obtain the results.
Using the agar well diffusion method, the antifungal activity of the leaf extract and the biosynthesized AgNPs were evaluated against Macrophomina phaseolina and Fusarium oxysporum. Before use, the potato dextrose agar and petri dish were autoclaved. Then, 0.1 mL of pure fungal culture was evenly spread on nutrient agar plates using an L-rod. The wells on the agar plates were then formed by the well borer, and 20 μL of aqueous samples of leaf extract and AgNPs (1000 ppm) was added. Nystatin and distilled water were employed as the positive and negative controls, respectively. The plates were finally incubated at 37 °C for 48 h to obtain the results.
Moond M., Singh S., Sangwan S., Rani S., Beniwal A., Rani J., Kumari A., Rani I, & Devi P. (2023). Phytofabrication of Silver Nanoparticles Using Trigonella foenum-graceum L. Leaf and Evaluation of Its Antimicrobial and Antioxidant Activities. International Journal of Molecular Sciences, 24(4), 3480.
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Publication 2023
Agar Anti-Bacterial Agents Antifungal Agents Bacteria Diffusion Fusarium oxysporum Glucose Gram-Positive Bacteria Gram Negative Bacteria Hyperostosis, Diffuse Idiopathic Skeletal Macrophomina phaseolina Nutrients Nystatin Plant Leaves Solanum tuberosum Staphylococcus aureus Streptomycin Xanthomonas
2
Antimicrobial Evaluation of Fenugreek Leaves
Himedia Private Limited provided the following chemicals: sodium carbonate, gallic acid, sodium sulphate, copper sulphate, sodium hydroxide, sodium bicarbonate, sodium potassium tartrate, sodium hydrogen arsenate, sodium phosphate, ammonium molybdate, phenol, 2,2-diphenyl-1-picrylhydrazyl (DPPH), aluminum chloride, silver nitrate (AgNO3), sodium nitrite, Folin–Ciocalteu reagent, Conc. sulfuric acid, catechin, nutrient agar (NA), and potato dextrose broth (PDB). The strains of Staphylococcus aureus (MTCC 96), Xanthomonas spp. (MTCC 11102), Fusarium oxysporum (MTCC 284), and Macrophomina phaseolina (MTCC 10399) were obtained from the Institute of Microbial Technology (IMTECH), Chandigarh, India’s culture collecting center for microbial resources. For the evaluation of antimicrobial activity, experiments were conducted in the department of microbiology, CCS HAU Hisar.
Trigonella foenum-graecum L. leaves of the Hisar Mukta (HM) 425 variety were procured from the Chaudhary Charan Singh Haryana Agricultural University’s Vegetable Science Research Farm. The collected leaf samples were verified by Dr. Anita, Assistant professor, Department of Botany and Plant physiology, CCS HAU, Hisar, India, by using an online platform (Tropicos and IPNI). The voucher specimens were verified by the Medicinal, Aromatic and Potential Crops Section, Department of Genetics and Plant Breeding, CCS HAU Hisar, by voucher specimen number 20.
Moond M., Singh S., Sangwan S., Rani S., Beniwal A., Rani J., Kumari A., Rani I, & Devi P. (2023). Phytofabrication of Silver Nanoparticles Using Trigonella foenum-graceum L. Leaf and Evaluation of Its Antimicrobial and Antioxidant Activities. International Journal of Molecular Sciences, 24(4), 3480.
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Publication 2023
Agar Agricultural Crops Aluminum Chloride ammonium molybdate Bicarbonate, Sodium Catechin diphenyl folin Fusarium oxysporum Gallic Acid Glucose Hydrogen Macrophomina phaseolina Microbicides Nutrients Phenols Plant Leaves Plant Physiological Phenomena Plants Silver Nitrate sodium arsenate sodium carbonate Sodium Hydroxide Sodium Nitrite sodium phosphate sodium potassium tartrate sodium sulfate Solanum tuberosum Specimen Collection Staphylococcus aureus Strains Sulfate, Copper Sulfuric Acids Trigonella foenum-graecum Vegetables Xanthomonas
3
Structural Analyses of Xanthomonadaceae FimT3
FimT3 modeling was performed using the Phyre2 web portal [42 (link)] and visualized via PyMOL version 2.4.0 (Schrödinger, LLC). The surface electrostatics of FimT3 was predicted using the APBS Electrostatics plugin from PyMOL. Sequence alignments of FimT3 with ComP, VC0858 and FimT from A. baylyi and L. pneumophila were performed by retrieving the respective sequences from NCBI, aligning through the T-Coffee Multiple Sequence Alignment Server [21 (link)] and visualizing using the BoxShade webserver (https://embnet.vital-it.ch/software/BOX_form.html). For FimT3 analyses within the Xanthomonadaceae family, DNA sequences of different FimT homologs from Xylella, Xanthomonas, Lysobacter and Stenotrophomonas were used as query for screening genomes of Xanthomonadaceae using CRB-BLAST [4 (link)] with default settings. Nucleotide sequences for the CRB-BLAST hits were then retrieved and aligned using MAFFT [41 (link)], followed by RAxML version 8.0.24 [73 (link)] to build a phylogenetic tree, which was visualized using Fig Tree version 1.4.4 (http://tree.bio.ed.ac.uk/). FimT3-encoding sequences were retrieved from the phylogenetic tree using the TREE2FASTA Perl script [63 (link)], translated into amino acid sequences and aligned using Clustal Omega (Clustal 12.1) to determine percentage of identical amino acids [48 (link)]. The visualization of the alignment of representative FimT3 sequences among X. fastidiosa strains and representative bacterial species belonging to the Xanthomonadaceae family was performed using the BoxShade webserver. The FimT3 GRxR motif sequence logo was generated using the WebLogo webserver [16 (link)].
Merfa M.V., Zhu X., Shantharaj D., Gomez L.M., Naranjo E., Potnis N., Cobine P.A, & De La Fuente L. (2023). Complete functional analysis of type IV pilus components of a reemergent plant pathogen reveals neofunctionalization of paralog genes. PLOS Pathogens, 19(2), e1011154.
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Publication 2023
Amino Acids Amino Acid Sequence Bacteria Base Sequence Coffee COMP protocol Electrostatics Ficus Genome Lysobacter Sequence Alignment Stenotrophomonas Strains Trees Xanthomonadaceae Xanthomonas Xylella
4
Antibiotic Activity of Pseudoiodinine and PCA
The MICs of pseudoiodinine and PCA for Xanthomonas spp. were determined by serial dilution. NA was prepared containing pseudoiodinine at 0–64 μg/mL or PCA at 0–256 μg/mL. Two microliters of bacterial suspension (OD600 = 1.0) were diluted threefold and spotted to NA plates. After a 48 h incubation at 28 °C, MICs were defined as the lowest concentration at which no growth was visible.
EC50 values of pseudoiodinine and PCA were determined according to growth inhibition. Briefly, 10 μL of bacterial suspension was added to 5 mL NB containing diluted concentrations of pseudoiodinine and PCA. OD600 values of the tested suspensions were measured when the control suspensions increased to OD600 = 1.0. The log of percentage inhibition based on OD600 values were regressed on the log of compound concentrations, and EC50 values were calculated. This experiment was performed three or more times independently.
The EC50 of M. oryzae R01-1 was determined in vitro by transferring plugs (0.5 cm2 diameter) of mycelium from an actively growing fungal colony to a series of OAM plates containing pseudoiodinine at 10, 15, 20, 25, 30, 35, 40, 45 and 50 μM. Fungal colony diameters were measured after a five-day incubation at 25 °C in darkness, and inhibition was calculated as percent of the control growth. EC50 values were calculated based on linear regression of colony diameter on log-transformed pseudoiodinine concentrations. Experiments were conducted three times independently.
Yang R., Shi Q., Huang T., Yan Y., Li S., Fang Y., Li Y., Liu L., Liu L., Wang X., Peng Y., Fan J., Zou L., Lin S, & Chen G. (2023). The natural pyrazolotriazine pseudoiodinine from Pseudomonas mosselii 923 inhibits plant bacterial and fungal pathogens. Nature Communications, 14, 734.
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Publication 2023
Bacteria Darkness Minimum Inhibitory Concentration Mycelium Psychological Inhibition Technique, Dilution Xanthomonas
5
Cultivation and Reagents for Pathogenic Bacteria
Phytopathogenic Xanthomonas spp. were cultivated in nutrient agar (NA) at 28 °C59 (link), and E. coli strains DH5α and BL21(DE3) were cultured in Luria Bertani (LB)60 medium at 37 °C. Tryptic soy broth (TSB; 30 g/L) was used for culturing Pseudomonas strains at 30 °C. The fungus M. oryzae R01-1 was grown in oatmeal (OAM)61 medium at 25 ˚C. The strains, plasmids and primers used in this study are listed in Supplementary data 1 and 2. When required, antibiotics were added at the following final concentrations (µg mL−1): kanamycin (Km), 25; rifampicin (Rif), 75; gentamicin (Gm), 20; and spectinomycin (Sp), 25. Chemical reagents including petroleum ether, ethyl acetate, n-butyl alcohol and methanol were purchased from Macklin (Shanghai, China). Phenazine-1-carboxylic acid (PCA) was provided by Dr. Yawen He (School of Life Sciences and Biotechnology, Shang Hai Jiao Tong University). Restriction enzymes were purchased from Takara Bio (Europe AB).
Yang R., Shi Q., Huang T., Yan Y., Li S., Fang Y., Li Y., Liu L., Liu L., Wang X., Peng Y., Fan J., Zou L., Lin S, & Chen G. (2023). The natural pyrazolotriazine pseudoiodinine from Pseudomonas mosselii 923 inhibits plant bacterial and fungal pathogens. Nature Communications, 14, 734.
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Publication 2023
1-phenazinecarboxylic acid Agar Antibiotics, Antitubercular Butyl Alcohol DNA Restriction Enzymes Escherichia coli ethyl acetate Fungi Gentamicin Kanamycin Methanol naphtha Nutrients Oligonucleotide Primers Plasmids Pseudomonas Rifampin Spectinomycin Strains tryptic soy broth Xanthomonas

Top products related to «Xanthomonas»

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Jack bean α mannosidase by Merck Group
Jack bean α-mannosidase is an enzyme that catalyzes the hydrolysis of terminal, non-reducing α-D-mannose residues in α-D-mannosides. This enzyme is commonly used in research applications.
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α l fucosidase from bovine kidney by Merck Group
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α-L-fucosidase is an enzyme isolated from bovine kidney. It catalyzes the hydrolysis of terminal α-L-fucose residues from various glycoconjugates.
3
α galactosidase from green coffee beans by Merck Group
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α-galactosidase from green coffee beans is an enzyme that catalyzes the hydrolysis of α-galactosides, such as raffinose and stachyose, into galactose and other simpler sugars. This enzyme is extracted from the green beans of the coffee plant.
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Xanthomonas manihotis β1 3 galactosidase by New England Biolabs
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Xanthomonas manihotis β1,3-galactosidase is an enzyme purified from the bacterium Xanthomonas manihotis. Its core function is to catalyze the hydrolysis of β-1,3-linked galactosides.
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β n acetylglucosaminidase from xanthomonas manihotis by New England Biolabs
Sourced in United Kingdom
β-N-acetylglucosaminidase from Xanthomonas manihotis is an enzyme that catalyzes the hydrolysis of terminal non-reducing N-acetyl-D-hexosamine residues in N-acetyl-β-D-hexosaminides.
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Xanthomonas by New England Biolabs
Xanthomonas is a laboratory equipment product designed for the culture and study of bacteria. It provides a controlled environment for the growth and observation of Xanthomonas, a genus of Gram-negative bacteria. The product's core function is to facilitate the cultivation and examination of Xanthomonas species.
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α fucosidase by Merck Group
α-fucosidase is an enzyme that catalyzes the hydrolysis of terminal α-L-fucose residues in various glycoconjugates. It is used in laboratory settings for the analysis and study of glycosidic structures.
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Dnaman software by Lynnon Biosoft
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More about "Xanthomonas"

Xanthomonas is a genus of Gram-negative, yellow-pigmented bacteria that are known for their ability to infect and cause diseases in a wide variety of important crops.
These plant pathogens are responsible for conditions such as bacterial spot in tomatoes and peppers, as well as bacterial blight in rice and other cereal crops.
The bacteria's pathogenicity is largely attributed to their production of yellow pigments and their capability to form biofilms, which can significantly contribute to their virulence and survival.
Understanding the biology and control of Xanthomonas species is crucial for protecting agricultural yields and ensuring food security.
Researchers studying Xanthomonas can leverage the power of AI-driven protocol comparisons through PubCompare.ai to optimize their research, enhance reproducibility, and identify the best protocols and products with ease.
This advanced tool can provide seamless access to relevant literature, preprints, and patents, allowing researchers to make informed decisions and take their Xanthomonas studies to new heights.
In addition to Xanthomonas, other enzymes like Jack bean α-mannosidase, α-L-fucosidase from bovine kidney, and α-galactosidase from green coffee beans have also been studied for their potential applications.
Xanthomonas manihotis β1,3-galactosidase and β-N-acetylglucosaminidase from Xanthomonas manihotis are also of interest, as they can provide insights into the biology and metabolism of these plant-pathogenic bacteria.
Researchers can also utilize DNAMAN software, a comprehensive bioinformatics tool, to analyze and compare DNA sequences, including those from Xanthomonas species.
The MiSeq platform, a powerful next-generation sequencing technology, has been employed in Xanthomonas research, enabling deeper understanding of the genetic makeup and evolution of these bacteria.
By leveraging the insights from the MeSH term description and metadescription, as well as drawing connections to related enzymes and bioinformatics tools, researchers can gain a comprehensive understanding of Xanthomonas and its impact on agriculture.
Experienece the power of AI-powered research optimization today and take your Xanthomonas studies to new heights.