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Strains

Strains refer to genetically distinct variants or subpopulations within a microbial species.
These variations can arise through natural selection, genetic engineering, or directed evolution.
Strains often exhibit unique phenotypic characteristics, such as differences in virulence, metabolic capabilities, or sensitivity to antimicrobial agents.
The identification and characterization of strains is crucial for understanding microbial diversity, epidemiology, and the development of targeted treatments or interventions.
Researchers utilize a variety of techniques, including genome sequencing, proteomics, and phenotypic assays, to differentiate and classify microbial strains.
Effective strain optimization is essential for optimizing experimental protocols and identifying the most suitable solutions for your research needs.
Pubtmcompare.ai's intelligent strain analysis tools can help streamline this process and revolutionize your research workflows.

Most cited protocols related to «Strains»

In multivariate analyses such as PCA, large differences in variances between columns are corrected by standardizing each column; i.e. dividing each column by its standard deviation. Thus each column will have the same weight in the multivariate analysis. For OTU abundance tables, such a procedure is inappropriate as the disparities in column sums can be 100-fold. Methods based on chi-squared distances rather than variances deal with this by comparing weighted column profiles [62] , computed as relative abundances for each OTU within a column, with the overall column sum retained as a weighting factor. However, chi-square distances are sums of squares and can be overly sensitive to outliers and sequencing “jackpot” effects such as those occurring in pyrosequencing data [63] (link). Bray-Curtis distances can be a useful alternative, as it is based on the distance between profiles, as long as the differences in actual column sums are also accounted for in the final study. The other approach to the problem of disparities between column sums has been to subsample the over-abundant columns down to the same number as the smaller ones. However this results in a loss of information, rarely an optimal procedure in statistical contexts. This subsampling procedure is inspired by the popular idea of rarefaction in coverage studies first invented by Sanders [64] , but has yet to be proved beneficial for all microbial community structures. The parallels between gene expression microarray analyses and microbial abundance analyses was mentioned in [65] (link), which proposed several expression-inspired strategies for robustifying abundance measurements. The main points were that rankings and thresholding are important in the presence of noise and high variability in sequence depths. As in gene expression analysis filtering the OTUs is beneficial, especially in the latter multiple testing adjustments. The phyloseq package enables easy filtering and rank transformations in the same vein as robust multi-array averaging (rma) [66] (link). We provide further details in (McMurdie and Holmes, [67] ).
Publication 2013
factor A Gene Expression Microarray Analysis Gene Expression Profiling Microbial Community Structure Strains Veins
The up-to-date reference 16S rRNA gene sequences were maintained as described earlier [3 (link)]. We attempted to select a sequence with the best quality for each species by using the following strategy. For cases in which multiple sequences were available for a type strain, the sequence extracted from its whole-genome assembly (WGA) was selected. As for PCR-derived sequences, the quality of sequencing was checked manually by secondary-structure-aware alignment using the EzEditor program [13 (link)]. Maximum-likelihood phylogenetic trees of each taxonomic group, such as phyla, classes, orders or families, were generated from manually aligned 16S rRNA gene sequences using RAxML software [14 (link)]. All 16S rRNA gene sequences were assigned taxonomically to the species level as a part of the complete taxonomic hierarchy which consisted of phylum, class, order, family, genus and species (subspecies if applicable).
Publication 2017
Genes Genome Ribosomal RNA Genes RNA, Ribosomal, 16S Strains Trees

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Publication 2015
Biopharmaceuticals Genes Strains
Details of the new and updated lineage data sets as well as the new software developments that make up BUSCO v3 are presented in the Supplementary Material online and in the user guide online at http://busco.ezlab.org. BUSCO has been developed and tested on Linux, the codebase is written for Python and runs with the standard Python packages. BUSCO is licensed and freely distributed under the MIT Licence. The BUSCO v3 source code is available through the GitLab project, https://gitlab.com/ezlab/busco, and built as a virtual machine with dependencies preinstalled.
Versions and accessions of all the genome assemblies, annotated gene sets, or transcriptomes assessed by BUSCO as part of this study are detailed in the Supplementary Material online, along with the settings used for each analysis. The Augustus ab initio gene prediction analyses are described in detail in the Supplementary Material online, to compute the coverage scores the predicted protein sequences were aligned against their respective reference annotations using BLASTp (e.g., a coverage score of 100% means that every amino acid of a reference protein is found in the predicted protein with no insertions, deletions, or substitutions). Details of the preprocessing, BUSCO completeness analyses, and postprocessing of the rodent data sets for the phylogenomics study are all presented in the Supplementary Material online, proteins selected for the superalignment were aligned using MAFFT (Katoh and Standley 2013 (link)) and filtered with trimAl (Capella-Gutiérrez et al. 2009 (link)), and the maximum likelihood tree was built using RAxML (Stamatakis 2014 (link)).
Publication 2017
Amino Acids Amino Acid Sequence Gene Deletion Genes Genome Insertion Mutation Proteins Python Rodent Staphylococcal Protein A Strains Transcriptome Trees
In the following two sections, we describe how to create a custom leukocyte signature matrix and apply it to study cellular heterogeneity and TIL survival associations in melanoma tumors profiled by The Cancer Genome Atlas (TCGA). Readers can follow along by creating ‘LM6’, a leukocyte RNA-Seq signature matrix comprised of six peripheral blood immune subsets (B cells, CD8 T cells, CD4 T cells, NK cells, monocytes/macrophages, neutrophils; GSE60424 [20 ]). Key input files are provided on the CIBERSORT website (‘Menu>Download’).
A custom signature file can be created by uploading the Reference sample file and the Phenotype classes file (section 3.3.2) to the online CIBERSORT application (SeeFigure 2) or can be created using the downloadable Java package. To build a custom gene signature matrix with the latter, the user should download the Java package from the CIBERSORT website and place all relevant files under the package folder. To link Java with R, run the following in R:
Within R:

> library(Rserve)

> Rserve(args=“–no-save”)

Command line:

> java -Xmx3g -Xms3g -jar CIBERSORT.jar -M Mixture_file -P Reference_sample_file -c phenotype_class_file -f

The last argument (-f) will eliminate non-hematopoietic genes from the signature matrix and is generally recommended for signature matrices tailored to leukocyte deconvolution. The user can also run this step on the website by choosing the corresponding reference sample file and phenotype class file (seeFigure 2). The CIBERSORT website will generate a gene signature matrix located under ‘Uploaded Files’ for future download.
Following signature matrix creation, quality control measures should be taken to ensure robust performance (see ‘Calibration of in silico TIL profiling methods’ in Newman et al.) [17 (link)]. Factors that can adversely affect signature matrix performance include poor input data quality, significant deviations in gene expression between cell types that reside in different tissue compartments (e.g., blood versus tissue), and cell populations with statistically indistinguishable expression patterns. Manual filtering of poorly performing genes in the signature matrix (e.g., genes expressed highly in the tumor of interest) may improve performance.
To benchmark our custom leukocyte matrix (LM6), we compared it to LM22 using a set of TCGA lung squamous cell carcinoma tumors profiled by RNA-Seq and microarray (n = 130 pairs). Deconvolution results were significantly correlated for all cell subsets shared between the two signature matrices (P < 0.0001). Notably, since LM6 was derived from leukocytes isolated from peripheral blood [20 ,21 (link)], we restricted the CD4 T cell comparison to naïve and resting memory CD4 T cells in LM22. Once validation is complete, a CIBERSORT signature matrix can be broadly applied to mixture samples as described in section 3.3 (e.g., SeeFigure 4).
Publication 2018
B-Lymphocytes BLOOD CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes cDNA Library Cells Genes, vif Genetic Diversity Genetic Heterogeneity Hematopoietic System Leukocytes Lung Neoplasms Macrophage Malignant Neoplasms Melanoma Memory Microarray Analysis Monocytes Natural Killer Cells Neoplasms Neutrophil Phenotype Population Group RNA-Seq RNA Motifs Squamous Cell Carcinoma Strains Tissues

Most recents protocols related to «Strains»

Example 6

TbpB and NMB0313 genes were amplified from the genome of Neisseria meningitidis serotype B strain B16B6. The LbpB gene was amplified from Neisseria meningitidis serotype B strain MC58. Full length TbpB was inserted into Multiple Cloning Site 2 of pETDuet using restriction free cloning ((F van den Ent, J. Löwe, Journal of Biochemical and Biophysical Methods (Jan. 1, 2006)).). NMB0313 was inserted into pET26, where the native signal peptide was replaced by that of pelB. Mutations and truncations were performed on these vectors using site directed mutagenesis and restriction free cloning, respectively. Pairs of vectors were transformed into E. coli C43 and were grown overnight in LB agar plates supplemented with kanamycin (50 μg/mL) and ampicillin (100 μg/mL).

tbpB genes were amplified from the genomes of M. catarrhalis strain 035E and H. influenzae strain 86-028NP and cloned into the pET52b plasmid by restriction free cloning as above. The corresponding SLAMs (M. catarrhalis SLAM 1, H. influenzae SLAM1) were inserted into pET26b also using restriction free cloning. A 6His-tag was inserted between the pelB and the mature SLAM sequences as above. Vectors were transformed into E. coli C43 as above.

Cells were harvested by centrifugation at 4000 g and were twice washed with 1 mL PBS to remove any remaining growth media. Cells were then incubated with either 0.05-0.1 mg/mL biotinylated human transferrin (Sigma-aldrich T3915-5 MG), α-TbpB (1:200 dilution from rabbit serum for M. catarrhalis and H. influenzae; 1:10000 dilution from rabbit serum for N. meningitidis), or α-LbpB (1:10000 dilution from rabbit serum-obtained a gift from J. Lemieux) or α-fHbp (1:5000 dilution from mouse, a gift from D. Granoff) for 1.5 hours at 4° C., followed by two washes with 1 mL of PBS. The cells were then incubated with R-Phycoerythrin-conjugated Streptavidin (0.5 mg/ml Cedarlane) or R-phycoerythrin conjugated Anti-rabbit IgG (Stock 0.5 mg/ml Rockland) at 25 ug/mL for 1.5 hours at 4° C. The cells were then washed with 1 mL PBS and resuspended in 200 uL fixing solution (PBS+2% formaldehyde) and left for 20 minutes. Finally, cells were washed with 2×1 mL PBS and transferred to 5 mL polystyrene FACS tubes. The PE fluorescence of each sample was measured for PE fluorescence using a Becton Dickinson FACSCalibur. The results were analyzed using FLOWJO software and were presented as mean fluorescence intensity (MFI) for each sample. For N. meningtidis experiments, all samples were compared to wildtype strains by normalizing wildtype fluorescent signals to 100%. Errors bars represent the standard error of the mean (SEM) across three experiments. Results were plotted statistically analysed using GraphPad Prism 5 software. The results shown in FIG. 6 for the SLPs, TbpB (FIG. 6A), LbpB. (FIG. 6B) and fHbp (FIG. 6C) demonstrate that SLAM effects translocation of all three SLP polypeptides in E. coli. The results shown in FIG. 10 demonstrate that translocation of TbpB from M. catarrhalis (FIG. 10C) and in H. influenzae (FIG. 10D) in E. coli require the co-expression of the required SLAM protein (Slam is an outer membrane protein that is required for the surface display of lipidated virulence factors in Neisseria. Hooda Y, Lai C C, Judd A, Buckwalter C M, Shin H E, Gray-Owen S D, Moraes T F. Nat Microbiol. 2016 Feb. 29; 1:16009).

Patent 2024
ADRB2 protein, human Agar Ampicillin anti-IgG Cells Centrifugation Cloning Vectors Culture Media Escherichia coli Fluorescence Formaldehyde Genes Genome Haemophilus influenzae Homo sapiens Kanamycin Lipoproteins Membrane Proteins Moraxella catarrhalis Mus Mutagenesis, Site-Directed Mutation Neisseria Neisseria meningitidis Phycoerythrin Plasmids Polypeptides Polystyrenes prisma Rabbits Serum Signaling Lymphocytic Activation Molecule Family Member 1 Signal Peptides Strains Streptavidin Technique, Dilution Transferrin Translocation, Chromosomal Virulence Factors

Example 2

As discussed herein above, the disclosed methods improve the antiseptic properties of a dental implant without using charged metallic ions via conversion of the nitrogen moieties in titanium nitride surface to a positively charged quaternary ammonium via a Menschutkin reaction.

To prepare the antibacterial quaternized TiN surface, an implant which has been coated with TiN was used. The implant was cleaned to improve yield. The implant was washed with two solvents in sequence, acetone and isopropanol, to remove any dust particulate and other residue. The native oxide layer was removed by sonicating in 1:10 HCl:deionized water for 1 minute. This treatment additionally removes any residue that may not have been removed by the solvents. Acetonitrile was used as the solvent; however, any solvent may be used with preference for polar solvents giving improved reaction times (Stanger K., et al. J Org Chem. 2007 72(25):9663-8; Harfenist M., et al. J Am Chem Soc 1957 79(16):4356-4358). An excess of allyl bromide was added to the solvent and continuously stirred. The sample was then submerged in the solution, and full reaction of the surface occurred within about 60 minutes, as confirmed by contact angle measurement. A reference was also measured by submerging in solvent for the duration with no reactant to ensure any changes in surface properties was due to the quaternization.

TABLE 2
SampleContact Angle (°)
As-deposited TiN<6
In solvent 2 hrs (no reaction)16 ± 2
Allyl bromide 30 minutes67 ± 1
Allyl bromide 60 minutes72 ± 3
Allyl bromide 120 minutes71 ± 2

Without wishing to be bound by a particular theory, the increased hydrophobicity of the treated surfaces can be due to the presence of the allyl groups on the surface which will impart some hydrophobicity. The contact angle measurements provide information on whether or not a reaction has occurred and whether it has saturated.

The biocidal activity was tested using live bacteria cultures from a patient's mouth, which provides the full flora to act against rather than targeting an individual strain of bacteria. The bacteria was incubated on the sample surface using several bacteria film thicknesses. The thickness is defined by keeping the same interaction surface area while varying the volume of bacteria solution added. Across two separate patients and several separate growths, within 4 hours 40-50% reduction in bacteria unit counts were observed for quaternized TiN as compared to traditional Titanium implants, outperforming traditional TiN coatings. FIG. 4 shows for two separate patients a set of typical bacteria growth result of the quaternized samples. The exact efficiency varies, as each patient has different flora which varies depending on environmental factors such as hygiene, diet, and familial history.

Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of skill in the art to which the disclosed invention belongs. Publications cited herein and the materials for which they are cited are specifically incorporated by reference.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present disclosure without departing from the scope or spirit of the disclosure. Other aspects of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Patent 2024
Acetone acetonitrile allyl bromide Ammonium Anti-Bacterial Agents Anti-Infective Agents, Local Bacteria Diet Implant, Dental Ions Isopropyl Alcohol Metals Nitrogen Oral Cavity Oxides Patients Solvents Strains Surface Properties Titanium titanium nitride

Example 2

PAO1, the parent strain of PGN5, is a wild-type P. aeruginosa strain that produces relatively small amounts of alginate and exhibits a non-mucoid phenotype; thus, PGN5 is also non-mucoid when cultured (FIG. 3A). In PAO1, the alginate biosynthetic operon, which contains genes required for alginate production, is negatively regulated. Activation of this operon leads to alginate production and a mucoid phenotype. For example, over-expression of mucE, an activator of the alginate biosynthetic pathway, induces a strong mucoid phenotype in the PAO1 strain (e.g., P. aeruginosa strain VE2; FIG. 3B). The plasmid pUCP20-pGm-mucE, which constitutively over-expresses MucE, was used to test whether the genetically-modified PGN5 strain could produce alginate. Indeed, the presence of this plasmid in PGN5 (PGN5+mucE) induced a mucoid phenotype (FIG. 3B). To measure the amount of alginate produced by PGN5+mucE on a cellular level, a standard carbazole assay was performed, which showed that the PGN5+mucE and VE2 (i.e., PAO1+mucE) strains produce comparable amounts of alginate (FIG. 3C; 80-120 g/L wet weight).

To examine whether the alginate produced by PGN5+mucE was similar in composition to alginate produced by VE2, HPLC was performed to compare the M and G content of alginate produced by each strain. The chromatograms obtained from alginate prepared from VE2 and PGN5+mucE were identical (FIG. 3D), and the M:G ratios were comparable to a commercial alginate control (data not shown). To confirm that the physical properties of VE2 and PGN5+mucE alginates were also similar, alginate gels were prepared from alginate produced by each strain and the viscosity and yield stress was measured. The viscosities of VE2 and PGN5+mucE alginate gels were comparable at 73.58 and 72.12 mPa, respectively (FIG. 3E). Similarly, the yield stress of VE2 and PGN5+mucE alginate gels were comparable at 47.34 and 47.16 Pa, respectively (FIG. 3G).

Patent 2024
Alginate Alginates Anabolism Biological Assay Biosynthetic Pathways carbazole Cells Gels Genes High-Performance Liquid Chromatographies Operon Parent Phenotype Physical Processes Plasmids Pseudomonas aeruginosa Strains Viscosity

Example 1

a. Materials and Methods

i. Vector Construction

1. Virus-Like Particle

As most broadly neutralizing HPV antibodies are derived from the highly conserved N-terminal region of L2, amino acids 14-122 of HPV16 L2 were used to create HBc VLPs. L2 with flanking linker regions was inserted into the tip of the a-helical spike of an HBc gene copy which was fused to another copy of HBc lacking the L2 insert. This arrangement allows the formation of HBc dimers that contain only a single copy of L2, increasing VLP stability (Peyret et al. 2015). This heterodimer is referred to as HBche-L2. A dicot plant-optimized HPV16 L2 coding sequence was designed based upon the sequence of GenBank Accession No. CAC51368.1 and synthesized in vitro using synthetic oligonucleotides by the method described (Stemmer et al., 1995). The plant-optimized L2 nucleotide sequence encoding residues 1-473 is posted at GenBank Accession No. KC330735. PCR end-tailoring was used to insert Xbal and SpeI sites flanking the L2 aa 14-122 using primers L2-14-Xba-F (SEQ ID NO. 1: CGTCTAGAGTCCGCAACCCAACTTTACAAG) and L2-122-Spe-R (SEQ ID NO. 2: G GGACTAGTTGGGGCACCAGCATC). The SpeI site was fused to a sequence encoding a 6His tag, and the resulting fusion was cloned into a geminiviral replicon vector (Diamos, 2016) to produce pBYe3R2K2Mc-L2(14-122)6H.

The HBche heterodimer VLP system was adapted from Peyret et al (2015). Using the plant optimized HBc gene (Huang et al., 2009), inventors constructed a DNA sequence encoding a dimer comprising HBc aa 1-149, a linker (G2S)5G (SEQ ID NO. 39), HBc aa 1-77, a linker GT(G4S)2 (SEQ ID NO. 40), HPV-16 L2 aa 14-122, a linker (GGS)2GSSGGSGG (SEQ ID NO. 41), and HBc aa 78-176. The dimer sequence was generated using multiple PCR steps including overlap extensions and insertion of BamHI and SpeI restriction sites flanking the L2 aa 14-122, using primers L2-14-Bam-F (SEQ ID NO. 3: CAGGATCCGCAACC CAACTTTACAAGAC) and L2-122-Spe-R (SEQ ID NO. 2). The HBche-L2 coding sequence was inserted into a geminiviral replicon binary vector pBYR2eK2M (FIG. 3), which includes the following elements: CaMV 35S promoter with duplicated enhancer (Huang et al., 2009), 5′ UTR of N. benthamiana psaK2 gene (Diamos et al., 2016), intron-containing 3′ UTR and terminator of tobacco extensin (Rosenthal et al, 2018), CaMV 35S 3′ terminator (Rosenthal et al, 2018), and Rb7 matrix attachment region (Diamos et al., 2016).

2. Recombinant Immune Complex

The recombinant immune complex (RIC) vector was adapted from Kim et al., (2015). The HPV-16 L2 (aa 14-122) segment was inserted into the BamHI and SpeI sites of the gene encoding humanized mAb 6D8 heavy chain, resulting in 6D8 epitope-tagged L2. The heavy chain fusion was inserted into an expression cassette linked to a 6D8 kappa chain expression cassette, all inserted into a geminiviral replicon binary vector (FIG. 3, RIC vector). Both cassettes contain CaMV 35S promoter with duplicated enhancer (Huang et al., 2009), 5′ UTR of N. benthamiana psaK2 gene (Diamos et al., 2016), intron-containing 3′ UTR and terminator of tobacco extensin (Rosenthal et al, 2018), and Rb7 matrix attachment region (Diamos et al., 2016).

ii. Agroinfiltration of Nicotiana benthamiana Leaves

Binary vectors were separately introduced into Agrobacterium tumefaciens EHA105 by electroporation. The resulting strains were verified by restriction digestion or PCR, grown overnight at 30° C., and used to infiltrate leaves of 5- to 6-week-old N. benthamiana maintained at 23-25° C. Briefly, the bacteria were pelleted by centrifugation for 5 minutes at 5,000 g and then resuspended in infiltration buffer (10 mM 2-(N-morpholino)ethanesulfonic acid (MES), pH 5.5 and 10 mM MgSO4) to OD600=0.2, unless otherwise described. The resulting bacterial suspensions were injected by using a syringe without needle into leaves through a small puncture (Huang et al. 2004). Plant tissue was harvested after 5 DPI, or as stated for each experiment. Leaves producing GFP were photographed under UV illumination generated by a B-100AP lamp (UVP, Upland, CA).

iii. Protein Extraction

Total protein extract was obtained by homogenizing agroinfiltrated leaf samples with 1:5 (w:v) ice cold extraction buffer (25 mM sodium phosphate, pH 7.4, 100 mM NaCl, 1 mM EDTA, 0.1% Triton X-100, 10 mg/mL sodium ascorbate, 0.3 mg/mL PMSF) using a Bullet Blender machine (Next Advance, Averill Park, NY) following the manufacturer's instruction. To enhance solubility, homogenized tissue was rotated at room temperature or 4° C. for 30 minutes. The crude plant extract was clarified by centrifugation at 13,000 g for 10 minutes at 4° C. Necrotic leaf tissue has reduced water weight, which can lead to inaccurate measurements based on leaf mass. Therefore, extracts were normalized based on total protein content by Bradford protein assay kit (Bio-Rad) with bovine serum albumin as standard.

iv. SDS-PAGE and Western Blot

Clarified plant protein extract was mixed with sample buffer (50 mM Tris-HCl, pH 6.8, 2% SDS, 10% glycerol, 0.02% bromophenol blue) and separated on 4-15% polyacrylamide gels (Bio-Rad). For reducing conditions, 0.5M DTT was added, and the samples were boiled for 10 minutes prior to loading. Polyacrylamide gels were either transferred to a PVDF membrane or stained with Coomassie stain (Bio-Rad) following the manufacturer's instructions. For L2 detection, the protein transferred membranes were blocked with 5% dry milk in PBST (PBS with 0.05% tween-20) overnight at 4° C. and probed with polyclonal rabbit anti-L2 diluted 1:5000 in 1% PBSTM, followed by goat anti-rabbit horseradish peroxidase conjugate (Sigma). Bound antibody was detected with ECL reagent (Amersham).

v. Immunization of Mice and Sample Collection

All animals were handled in accordance to the Animal Welfare Act and Arizona State University IACUC. Female BALB/C mice, 6-8 weeks old, were immunized subcutaneously with purified plant-expressed L2 (14-122), HBche-L2 VLP, L2 RIC, or PBS mixed 1:1 with Imject® Alum (Thermo Scientific, Rockford, IL). In all treatment groups, the total weight of antigen was set to deliver an equivalent 5 μg of L2. Doses were given on days 0, 21, and 42. Serum collection was done as described (Santi et al. 2008) by submandibular bleed on days 0, 21, 42, and 63.

vi. Antibody Measurements

Mouse antibody titers were measured by ELISA. Bacterially-expressed L2 (amino acids 11-128) was bound to 96-well high-binding polystyrene plates (Corning), and the plates were blocked with 5% nonfat dry milk in PBST. After washing the wells with PBST (PBS with 0.05% Tween 20), the diluted mouse sera were added and incubated. Mouse antibodies were detected by incubation with polyclonal goat anti-mouse IgG-horseradish peroxidase conjugate (Sigma). The plate was developed with TMB substrate (Pierce) and the absorbance was read at 450 nm. Endpoint titers were taken as the reciprocal of the lowest dilution which produced an OD450 reading twice the background. IgG1 and IgG2a antibodies were measured with goat-anti mouse IgG1 or IgG2a horseradish peroxidase conjugate.

vii. Electron Microscopy

Purified samples of HBche or HBche-L2 were initially incubated on 75/300 mesh grids coated with formvar. Following incubation, samples were briefly washed twice with deionized water then negatively stained with 2% aqueous uranyl acetate. Transmission electron microscopy was performed with a Phillips CM-12 microscope, and images were acquired with a Gatan model 791 CCD camera.

viii. Statistical Analysis

The significance of vaccine treatments and virus neutralization was measured by non-parametric Mann-Whitney test using GraphPad prism software. Two stars (**) indicates p values <0.05. Three stars (***) indicates p values <0.001.

b. Design and Expression of HBc VLPs and RIC Displaying HPV16 L2

BeYDV plant expression vectors (FIG. 3) expressing either the target VLP HBche-L2, or L2 and HBche alone as controls, were agroinfiltrated into the leaves of N. benthamiana and analyzed for VLP production. After 4-5 days post infiltration (DPI), leaves displayed only minor signs of tissue necrosis, indicating that the VLP was well-tolerated by the plants (FIG. 4A). Leaf extracts analyzed by reducing SDS-PAGE showed an abundant band near the predicted size of 51 kDa for HBche-L2, just above the large subunit of rubisco (RbcL). HBche was detected around the predicted size of 38 kDa (FIG. 4B). Western blot probed with anti-L2 polyclonal serum detected a band for HBche-L2 at ˜51 kDa (FIG. 4B). These results indicate that this plant system is capable of producing high levels of L2-containing HBc VLP.

To express L2-containing MC, amino acids 14-122 of HPV16 L2 were fused with linker to the C-terminus of the 6D8 antibody heavy chain and tagged with the 6D8 epitope (Kim et al. 2015). A BeYDV vector (FIG. 3) expressing both the L2-fused 6D8 heavy chain and the light chain was agroinfiltrated into leaves of N. benthamiana and analyzed for RIC production. To create more homogenous human-type glycosylation, which has been shown to improve antibody Fc receptor binding in vivo, transgenic plants silenced for xylosyltransferase and fucosyltransferase were employed (Castilho and Steinkellner 2012). By western blot, high molecular weight bands >150 kDa suggestive of RIC formation were observed (FIG. 4C). Expression of soluble L2 RIC was lower than HBche-L2 due to relatively poor solubility of the RIC (FIG. 4C).

After rigorous genetic optimization, the N. benthamiana system is capable of producing very high levels of recombinant protein, up to 30-50% of the total soluble plant protein, in 4-5 days (Diamos et al. 2016). Using this system, we produced and purified milligram quantities of fully assembled and potently immunogenic HBc VLPs displaying HPV L2 through a simple one-step purification process (FIGS. 4A-4C and 6).

c. Purification and Characterization of HBche-L2 and L2 RIC

To assess the assembly of HBc-L2 VLP, clarified plant extracts containing either HBche-L2 or HBche were analyzed by sucrose gradient sedimentation. HBche-L2 sedimented largely with HBche, which is known to form VLP, though a small increase in density was observed with HBche-L2, perhaps due to the incorporation of L2 into the virus particle (FIG. 5A). To demonstrate particle formation, sucrose fractions were examined by electron microscopy. Both HBche and HBche-L2 formed ˜30 nm particles, although the appearance of HBche-L2 VLP suggested slightly larger, fuller particles (FIGS. 5C and 5D). As most plant proteins do not sediment with VLP, pooling peak sucrose fractions resulted in >95% pure HBche-L2 (FIG. 5B), yielding sufficient antigen (>3 mg) for vaccination from a single plant leaf.

L2 RIC was purified from plant tissue by protein G affinity chromatography. By SDS-PAGE, an appropriately sized band was visible >150 kDa that was highly pure (FIG. 5B). Western blot confirmed the presence of L2 in this band, indicating proper RIC formation (FIG. 5B). L2 RIC bound to human complement C1q receptor with substantially higher affinity compared to free human IgG standard, suggesting proper immune complex formation (FIG. 5E).

d. Mouse Immunization with HBche-L2 and L2 RIC

Groups of Balb/c mice (n=8) were immunized, using alum as adjuvant, with three doses each of 5 μg L2 delivered as either L2 alone, HBche-L2 VLP, L2 RIC, or a combination of half VLP and half RIC. VLP and RIC, alone or combined, greatly enhanced antibody titers compared to L2 alone by more than an order of magnitude at all time points tested (FIG. 6). After one or two doses, the combined VLP/RIC treatment group outperformed both the VLP or RIC groups, reaching mean endpoint titers of >200,000, which represent a 700-fold increase over immunization with L2 alone (FIG. 6). After the third dose, both the VLP and combined VLP/RIC groups reached endpoint titers >1,300,000, a 2-fold increase over the RIC alone group. To determine the antibody subtypes produced by each treatment group, sera were assayed for L2-binding IgG1 and IgG2a. All four groups produced predominately IgG1 (FIG. 7, note dilutions). However, RIC and especially VLP-containing groups had an elevated ratio of IgG2a:IgG1 (>3-fold) compared to L2 alone (FIG. 7).

In vitro neutralization of HPV16 pseudovirions showed that the VLP and RIC groups greatly enhanced neutralization compared to L2 alone (FIG. 5, p<0.001). Additionally, VLP and RIC combined further enhanced neutralization activity ($5-fold, p<0.05) compared to either antigen alone, supporting the strong synergistic effect of delivering L2 by both platforms simultaneously.

In this study, by displaying amino acids 11-128 on the surface of plant-produced HBc VLPs, L2 antibody titers as high as those seen with L1 vaccines were generated (FIG. 6). Mice immunized with L2 alone had highly variable antibody titers, with titers spanning two orders of magnitude. By contrast, the other groups had much more homogenous antibody responses, especially the VLP-containing groups, which had no animals below an endpoint titer of 1:1,000,000 (FIG. 6). These results underscore the potential of HBc VLP and RIC to provide consistently potent immune responses against L2. Moreover, significant synergy of VLP and RIC systems was observed when the systems were delivered together, after one or two doses (FIG. 6). Since equivalent amounts of L2 were delivered with each dose, the enhanced antibody titer did not result from higher L2 doses. Rather, these data suggest that higher L2-specific antibody production may be due to augmented stimulation of L2-specific B cells by T-helper cells that were primed by RIC-induced antigen presenting cells. Although treatment with VLP and RIC alone reached similar endpoint titers as the combined VLP/RIC group after 3 doses, virus neutralization was substantially higher (>5-fold) in the combined group (FIG. 8). Together, these data indicate unique synergy exists when VLP and RIC are delivered together. Inventors have observed similarly significant synergistic enhancement of immunogenicity for a variety of other antigens.

Mice immunized with L2 alone had highly variable antibody titers, with titers spanning two orders of magnitude. By contrast, the VLP and VLP/RIC groups had much more homogenous antibody responses, with no animals below an endpoint titer of 1:1,000,000 (FIG. 6). These results underscore the potential of HBc VLP and RIC to provide consistently potent immune responses against L2.

Fc gamma receptors are present on immune cells and strongly impact antibody effector functions such as antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity (Jefferis 2009). In mice, these interactions are controlled in part by IgG subtypes. IgG1 is associated with a Th2 response and has limited effector functions. By contrast, IgG2a is associated with a Th1 response and more strongly binds complement components (Neuberger and Raj ewsky 1981) and Fc receptors (Radaev 2002), enhancing effector functions and opsonophagocytosis by macrophages (Takai et al. 1994). Immunization with L2 alone was found to produce low levels of IgG2a, however immunization with RIC and VLP produced significant increases in IgG2a titers. VLP-containing groups in particular showed a 3-fold increase in the ratio of IgG2a to IgG1 antibodies (FIG. 7). Importantly, production of IgG2a is associated with successful clearance of a plethora of viral pathogens (Coutelier et al. 1988; Gerhard et al. 1997; Wilson et al. 2000; Markine-Goriaynoff and Coutelier 2002).

The glycosylation state of the Fc receptor also plays an important role in antibody function. Advances in glycoengineering have led to the development of transgenic plants with silenced fucosyl- and xylosyl-transferase genes capable of producing recombinant proteins with authentic human N-glycosylation (Strasser et al. 2008). Antibodies produced in this manner have more homogenous glycoforms, resulting in improved interaction with Fc gamma and complement receptors compared to the otherwise identical antibodies produced in mammalian cell culture systems (Zeitlin et al. 2011; Hiatt et al. 2014; Strasser et al. 2014; Marusic et al. 2017). As the known mechanisms by which RIC vaccines increase immunogenicity of an antigen depend in part on Fc and complement receptor binding, HPV L2 RIC were produced in transgenic plants with silenced fucosyl- and xylosyl-transferase. Consistent with these data, we found that L2 RIC strongly enhanced the immunogenicity of L2 (FIG. 6). However, yield suffered from insolubility of the RIC (FIG. 4C). We found that the 11-128 segment of L2 expresses very poorly on its own in plants and may be a contributing factor to poor L2 RIC yield. Importantly, we have produced very high yields of RIC with different antigen fusions. Thus, in some aspects, antibody fusion with a shorter segment of L2 could substantially improve the yield of L2 RIC.

e. Neutralization of HPV Pseudovirions

Neutralization of papilloma pseudoviruses (HPV 16, 18, and 58) with sera from mice immunized IP with HBc-L2 VLP and L2(11-128) showed neutralization of HPV 16 at titers of 400-1600 and 200-800, respectively (Table 1). More mice IP-immunized with HBc-L2 VLP had antisera that cross-neutralized HPV 18 and HPV 58 pseudoviruses, compared with mice immunized with L2(11-128). Anti-HBc-L2 VLP sera neutralized HPV 18 at titers of 400 and HPV 58 at titers ranging from 400-800 (Table 1), while anti-L2(11-128) sera neutralized HPV 18 at a titer of 200 and HPV 58 at a titer of 400 (Table 1). None of the sera from intranasal-immunized mice demonstrated neutralizing activity, consistent with lower anti-L2 titers for intranasal than for intraperitoneal immunized mice.

TABLE 1
L2-specific serum IgG and pseudovirus neutralization
titers from IP immunized mice
Neutralization of Pseudoviruses
ImmunogenSerum IgGHPV 16HPV 18HPV 58
HBc-L2>50,000 400
~70,0001600400400
>80,0001600400800
L2 (11-128)~8000 200
~12,000 400
~50,000 800200400

Patent 2024
3' Untranslated Regions 5' Untranslated Regions AA 149 Agrobacterium tumefaciens aluminum potassium sulfate aluminum sulfate Amino Acids Animals Animals, Transgenic Antibodies Antibody Formation Antigen-Presenting Cells Antigens B-Lymphocytes Bacteria Bromphenol Blue Buffers Cell Culture Techniques Cells Centrifugation Chromatography, Affinity Cloning Vectors Cold Temperature Combined Modality Therapy complement 1q receptor Complement Receptor Complex, Immune Complex Extracts Cytotoxicities, Antibody-Dependent Cell Cytotoxin Digestion DNA, A-Form DNA Sequence Edetic Acid Electron Microscopy Electroporation Enzyme-Linked Immunosorbent Assay Epitopes ethane sulfonate Fc Receptor Females Formvar Fucosyltransferase G-substrate Gamma Rays Genes Genes, vif Glycerin Goat Helix (Snails) Helper-Inducer T-Lymphocyte Homo sapiens Homozygote Horseradish Peroxidase Human papillomavirus 16 Human papillomavirus 18 Human Papilloma Virus Vaccine IGG-horseradish peroxidase IgG1 IgG2A Immune Sera Immunoglobulin Heavy Chains Immunoglobulins Immunologic Factors Institutional Animal Care and Use Committees Introns Inventors L2 protein, Human papillomavirus type 16 Light Macrophage Mammals Matrix Attachment Regions Mice, Inbred BALB C Microscopy Milk, Cow's Morpholinos Mus Necrosis Needles Nicotiana Oligonucleotide Primers Oligonucleotides Open Reading Frames Opsonophagocytosis Papilloma Pathogenicity Plant Development Plant Extracts Plant Leaves Plant Proteins Plants Plants, Transgenic polyacrylamide gels Polystyrenes polyvinylidene fluoride prisma Protein Glycosylation Proteins Punctures Rabbits Receptors, IgG Recombinant Proteins Replicon Reproduction Response, Immune Ribulose-Bisphosphate Carboxylase Large Subunit Satellite Viruses SDS-PAGE Serum Serum Albumin, Bovine Sodium Ascorbate Sodium Chloride sodium phosphate Specimen Collection Stars, Celestial Strains Sucrose Sulfate, Magnesium Syringes System, Immune Technique, Dilution Tissue, Membrane Tissues Transferase Transmission Electron Microscopy Triton X-100 Tromethamine Tween 20 Ultraviolet Rays uranyl acetate Vaccination Vaccines Vaccines, Recombinant Virion Viroids Virus Vision Western Blotting xylosyltransferase

Example 2

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the with the agricultural composition will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the with the agricultural composition will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

The inoculants were prepared from isolates grown as spread plates on R2A incubated at 25° C. for 48 to 72 hours. Colonies were harvested by blending with sterile distilled water (SDW) which was then transferred into sterile containers. Serial dilutions of the harvested cells were plated and incubated at 25° C. for 24 hours to estimate the number of colony forming units (CFU) in each suspension. Dilutions were prepared using individual isolates or blends of isolates (consortia) to deliver 1×105 cfu/microbe/seed and seeds inoculated by either imbibition in the liquid suspension or by overtreatment with 5% vegetable gum and oil.

Seeds corresponding to the plants of table 15 were planted within 24 to 48 hours of treatment in agricultural soil, potting media or inert growing media. Plants were grown in small pots (28 mL to 200 mL) in either a controlled environment or in a greenhouse. Chamber photoperiod was set to 16 hours for all experiments on all species. Air temperature was typically maintained between 22-24° C.

Unless otherwise stated, all plants were watered with tap water 2 to 3 times weekly. Growth conditions were varied according to the trait of interest and included manipulation of applied fertilizer, watering regime and salt stress as follows:

    • Low N—seeds planted in soil potting media or inert growing media with no applied N fertilizer
    • Moderate N—seeds planted in soil or growing media supplemented with commercial N fertilizer to equivalent of 135 kg/ha applied N
    • Insol P—seeds planted in potting media or inert growth substrate and watered with quarter strength Pikovskaya's liquid medium containing tri-calcium phosphate as the only form phosphate fertilizer.
    • Cold Stress—seeds planted in soil, potting media or inert growing media and incubated at 10° C. for one week before being transferred to the plant growth room.
    • Salt stress—seeds planted in soil, potting media or inert growing media and watered with a solution containing between 100 to 200 mg/L NaCl.

Untreated (no applied microbe) controls were prepared for each experiment. Plants were randomized on trays throughout the growth environment. Between 10 and 30 replicate plants were prepared for each treatment in each experiment. Phenotypes were measured during early vegetative growth, typically before the V3 developmental stage and between 3 and 6 weeks after sowing. Foliage was cut and weighed. Roots were washed, blotted dry and weighed. Results indicate performance of treatments against the untreated control.

TABLE 15
StrainShootRoot
Microbe sp.IDCropAssayIOC (%)IOC (%)
Bosea thiooxidans123EfficacyEfficacy
overall100%100%
Bosea thiooxidans54522WheatEarly vigor - insol P30-40 
Bosea thiooxidans54522RyegrassEarly vigor50-60 50-60 
Bosea thiooxidans54522RyegrassEarly vigor - moderate P0-100-10
Duganella violaceinigra111EfficacyEfficacy
overall100%100%
Duganella violaceinigra66361TomatoEarly vigor0-100-10
Duganella violaceinigra66361TomatoEarly vigor30-40 40-50 
Duganella violaceinigra66361TomatoEarly vigor20-30 20-30 
Herbaspirillum huttiense222Efficacy
overall100%
Herbaspirillum huttiense54487WheatEarly vigor - insol P30-40 
Herbaspirillum huttiense60507MaizeEarly vigor - salt stress0-100-10
Janthinobacterium sp.222Efficacy
Overall100%
Janthinobacterium sp.54456WheatEarly vigor - insol P30-40 
Janthinobacterium sp.54456WheatEarly vigor - insol P0-10
Janthinobacterium sp.63491RyegrassEarly vigor - drought0-100-10
stress
Massilia niastensis112EfficacyEfficacy
overall80%80%
Massilia niastensis55184WheatEarly vigor - salt stress0-1020-30 
Massilia niastensis55184WinterEarly vigor - cold stress0-1010-20 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress20-30 20-30 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress10-20 10-20 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress<0<0
wheat
Novosphingobium rosa211EfficacyEfficacy
overall100%100%
Novosphingobium rosa65589MaizeEarly vigor - cold stress0-100-10
Novosphingobium rosa65619MaizeEarly vigor - cold stress0-100-10
Paenibacillus amylolyticus111EfficacyEfficacy
overall100%100%
Paenibacillus amylolyticus66316TomatoEarly vigor0-100-10
Paenibacillus amylolyticus66316TomatoEarly vigor10-20 10-20 
Paenibacillus amylolyticus66316TomatoEarly vigor0-100-10
Pantoea agglomerans323EfficacyEfficacy
33%50%
Pantoea agglomerans54499WheatEarly vigor - insol P40-50 
Pantoea agglomerans57547MaizeEarly vigor - low N<00-10
Pantoea vagans55529MaizeEarly vigor<0<0
(formerly P. agglomerans)
Polaromonas ginsengisoli111EfficacyEfficacy
66%100%
Polaromonas ginsengisoli66373TomatoEarly vigor0-100-10
Polaromonas ginsengisoli66373TomatoEarly vigor20-30 30-40 
Polaromonas ginsengisoli66373TomatoEarly vigor<010-20 
Pseudomonas fluorescens122Efficacy
100%
Pseudomonas fluorescens54480WheatEarly vigor - insol P>100 
Pseudomonas fluorescens56530MaizeEarly vigor - moderate N0-10
Rahnella aquatilis334EfficacyEfficacy
80%63%
Rahnella aquatilis56532MaizeEarly vigor - moderate N10-20 
Rahnella aquatilis56532MaizeEarly vigor - moderate N0-100-10
Rahnella aquatilis56532WheatEarly vigor - cold stress0-1010-20 
Rahnella aquatilis56532WheatEarly vigor - cold stress<00-10
Rahnella aquatilis56532WheatEarly vigor - cold stress10-20 <0
Rahnella aquatilis57157RyegrassEarly vigor<0
Rahnella aquatilis57157MaizeEarly vigor - low N0-100-10
Rahnella aquatilis57157MaizeEarly vigor - low N0-10<0
Rahnella aquatilis58013MaizeEarly vigor0-1010-20 
Rahnella aquatilis58013MaizeEarly vigor - low N0-10<0
Rhodococcus erythropolis313Efficacy
66%
Rhodococcus erythropolis54093MaizeEarly vigor - low N40-50 
Rhodococcus erythropolis54299MaizeEarly vigor - insol P>100 
Rhodococcus erythropolis54299MaizeEarly vigor<0<0
Stenotrophomonas chelatiphaga611EfficacyEfficacy
60%60%
Stenotrophomonas chelatiphaga54952MaizeEarly vigor0-100-10
Stenotrophomonas chelatiphaga47207MaizeEarly vigor<0 0
Stenotrophomonas chelatiphaga64212MaizeEarly vigor0-1010-20 
Stenotrophomonas chelatiphaga64208MaizeEarly vigor0-100-10
Stenotrophomonas chelatiphaga58264MaizeEarly vigor<0<0
Stenotrophomonas maltophilia612EfficacyEfficacy
43%66%
Stenotrophomonas maltophilia54073MaizeEarly vigor - low N50-60 
Stenotrophomonas maltophilia54073MaizeEarly vigor<00-10
Stenotrophomonas maltophilia56181MaizeEarly vigor0-10<0
Stenotrophomonas maltophilia54999MaizeEarly vigor0-100-10
Stenotrophomonas maltophilia54850MaizeEarly vigor 00-10
Stenotrophomonas maltophilia54841MaizeEarly vigor<00-10
Stenotrophomonas maltophilia46856MaizeEarly vigor<0<0
Stenotrophomonas rhizophila811EfficacyEfficacy
12.5%37.5%
Stenotrophomonas rhizophila50839MaizeEarly vigor<0<0
Stenotrophomonas rhizophila48183MaizeEarly vigor<0<0
Stenotrophomonas rhizophila45125MaizeEarly vigor<0<0
Stenotrophomonas rhizophila46120MaizeEarly vigor<00-10
Stenotrophomonas rhizophila46012MaizeEarly vigor<0<0
Stenotrophomonas rhizophila51718MaizeEarly vigor0-100-10
Stenotrophomonas rhizophila66478MaizeEarly vigor<0<0
Stenotrophomonas rhizophila65303MaizeEarly vigor<00-10
Stenotrophomonas terrae221EfficacyEfficacy
50%50%
Stenotrophomonas terrae68741MaizeEarly vigor<0<0
Stenotrophomonas terrae68599MaizeEarly vigor<00-10
Stenotrophomonas terrae68599Capsicum *Early vigor20-30 20-30 
Stenotrophomonas terrae68741Capsicum *Early vigor10-20 20-30 

The data presented in table 15 describes the efficacy with which a microbial species or strain can change a phenotype of interest relative to a control run in the same experiment. Phenotypes measured were shoot fresh weight and root fresh weight for plants growing either in the absence of presence of a stress (assay). For each microbe species, an overall efficacy score indicates the percentage of times a strain of that species increased a both shoot and root fresh weight in independent evaluations. For each species, the specifics of each independent assay is given, providing a strain ID (strain) and the crop species the assay was performed on (crop). For each independent assay the percentage increase in shoot and root fresh weight over the controls is given.

Patent 2024
Ammonia Asparagine Aspartic Acid Biological Assay Bosea thiooxidans Calcium Phosphates Capsicum Cells Chlorophyll Cold Shock Stress Cold Temperature Crop, Avian Dietary Fiber DNA Replication Droughts Drought Tolerance Embryophyta Environment, Controlled Farmers Fertilization Glutamic Acid Glutamine Glycine Growth Disorders Herbaspirillum Herbaspirillum huttiense Leucine Lolium Lycopersicon esculentum Lysine Maize Massilia niastensis Methionine Microbial Consortia Nitrates Nitrites Nitrogen Novosphingobium rosa Paenibacillus Paenibacillus amylolyticus Pantoea agglomerans Pantoea vagans Phenotype Phosphates Photosynthesis Plant Development Plant Embryos Plant Leaves Plant Proteins Plant Roots Plants Polaromonas ginsengisoli Pseudoduganella violaceinigra Pseudomonas Pseudomonas fluorescens Rahnella Rahnella aquatilis Retention (Psychology) Rhodococcus erythropolis Rosa Salt Stress Sodium Chloride Sodium Chloride, Dietary Stenotrophomonas chelatiphaga Stenotrophomonas maltophilia Stenotrophomonas rhizophila Stenotrophomonas terrae Sterility, Reproductive Strains Technique, Dilution Threonine Triticum aestivum Tryptophan Tyrosine Vegetables Zea mays

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More about "Strains"

Genetic Variants, Subpopulations, Microbial Diversity, Epidemiology, Targeted Treatments, Experimental Protocols, Strain Optimization, Strain Analysis, FBS, DMEM, Whatman No. 1 Filter Paper, TRIzol Reagent, RNeasy Mini Kit, Penicillin/Streptomycin, C57BL/6J Mice, Streptomycin Strains refer to genetically distinct variants or subpopulations within a microbial species.
These variations can arise through natural selection, genetic enginering, or directed evolution.
Strains often exhibit unique phenotypic characteristics, such as differences in virulence, metabolic capabilities, or sensitivity to antimicrobial agents like Penicillin and Streptomycin.
Identifying and characterizing these strains is crucial for understanding microbial diversity, epidemiology, and developing targeted treatments or interventions.
Researchers utilize a variety of techniques, including genome sequencing, proteomics, and phenotypic assays (e.g. using FBS, DMEM, Whatman No. 1 filter paper) to differentiate and classify microbial strains.
Effective strain optimization is essential for optimizing experimental protocols and identifying the most suitable solutions for your research needs.
Tools like PubCompare.ai's intelligent strain analysis can help streamline this process by locating the best protocols from literature, pre-prints, and patents, and comparing strains side-by-side to find the optimal solutions.
This can revolutionize your research workflows and help you work more efficiently, whether you're using TRIzol reagent, the RNeasy Mini Kit, or studying C57BL/6J mice.