Continuous cropping of Sugar beet changed rhizospheric fungi significantly than non-cropping

A group from National Sugar Crop Improvement Centre, Heilongjiang University, Harbin, China, etc. has reported about difference of rhizosphere between continuous and non-continuous cropping groups of sugar beet rhizosphere.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490479/

There were significant differences in fungal community composition between continuous and non-continuous cropping groups of sugar beet rhizosphere.
Compared with non-continuous cropping, continuous cropping increased the relative abundance of potentially pathogenic fungi such as Tausonia, Gilbellulopsis, and Fusarium, but decreased the relative abundance of Olpidium.


Left figure=rhizospheric bacteria, Right figure=rhizospheric fungi
where, Sc, continuous cropping bulk soil; Sn, non-continuous cropping bulk soil; Rc, continuous cropping rhizosphere soil; Rn, non-continuous cropping rhizosphere soil; Bc, continuous cropping sugar beetroot; Bn, non-continuous cropping sugar beetroot.

OsRMC binding to CBM1 of a blast fungal xylanase blocks access to cellulose and inhibits infection of pathogenic fungi

A group from Iwate Biotechnology Research Center, Kitakami, Iwate, Japan, etc. has reported that OsRMC binding to CBM1 of a blast fungal xylanase blocks access to cellulose, resulting in the inhibition of xylanase enzymatic activity.
https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1010792

The plant apoplastic space is filled with the primary cell wall, mainly composed of the polysaccharides cellulose, hemicellulose, and pectin. Hemicellulosic polysaccharides play an important role in controlling the physical properties of the cell wall. Xyloglucan in dicotyledonous and xylan in monocotyledonous plants are the major hemicellulosic polysaccharides by quantity and strengthen the cell wall by forming cross-bridges between cellulose microfibrils. A cell wall composed of heteropolysaccharides also provides a physical barrier against plant pathogen invasion.

Plant pathogenic fungi secrete a battery of cell wall-degrading enzymes (CWDEs) that catalyze hydrolytic and oxidative degradation of plant cell wall polysaccharides, assisting fungal penetration and colonization.

Plants have evolved various activity-inhibiting proteins as a defense against fungal cell wall-degrading enzymes (CWDEs), but how plants counteract the function of fungal enzymes containing carbohydrate binding modules (CBMs) remains unknown. Here, it was demonstrated that OsRMC, a CBM1-interacting protein (CBMIP) of rice (Oryza sativa), binding to CBM1 of a blast fungal xylanase blocks access to cellulose, resulting in the inhibition of xylanase enzymatic activity. Where, OsRMC is a member of the Cysteine-rich repeat secretion proteins (CRRSPs) containing two DUF26, and binds mannose as well as CBM1.


(LEFT)Rice leaves of wild-type (Hitomebore) control (Con) and OsRMC-overexpressing (OsRMC-OX) lines 4 days after inoculation of M. oryzae inoculation.
(RIGHT)The amount of M. oryzae fungal mass in rice leaf was monitored by quantifying the ratio of M. oryzae genomic DNA to rice genomic DNA obtained by PCR.

Effects of nitrogen fertilization onto powdery mildew and damping-off disease infestation in winter wheat

A group from Department of Nutritional Crop Physiology, Institute of Crop Science, University of Hohenheim, Stuttgart, Germany, etc. has reported about effects of nitrogen fertilization onto Blumeria graminis f. sp. tritici (Bgt) and Gaeumannomyces graminis f. sp. tritici (Ggt) infestation.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500508/

In this study, the role of nitrogen sources, including nitrate, ammonium, and cyanamide, on Bgt and Ggt infestation in winter wheat was investigated, to gain insights into the plant’s physical and biochemical mechanisms mediated by the interaction between nitrogen source and pathogen characterizing rhizo bacterial and fungal flora using next-generation sequencing.

Wheat inoculated with the foliar pathogen Bgt was comparatively up to 80% less infested when fertilized with nitrate or cyanamide than with ammonium.

Bacterial richness ranged from 720 to 969 ASVs and it did not differ among the four fertilization N treatments. Likewise, bacterial community structure was not affected by N application and N form. However, fungal richness ranged from 161 to 312 ASVs and it was higher in soil without any fertilization and in the ammonium treatment, while the soil amended with nitrate showed the lowest value in richness.

Fucoidan-based combination chemotherapy is effective for the treatment of docetaxel-resistant prostate cancer

A group from Department of Anesthesiology, Show Chwan Memorial Hospital, Changhua 50008, Taiwan, etc. has reported that fucoidan-based combination chemotherapy may exert beneficial effects and facilitate the treatment of docetaxel-resistant prostate cancer (PCa).
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500773/

The standard treatment for advanced PCa is androgen deprivation therapy (ADT). Although hormone-sensitive PCa is curable with ADT, most patients progress to castration-resistant prostate cancer (CRPCa) and metastatic CRPCa (mCRPCa). Front-line docetaxel treatment is administered to patients with CRPCa and mCRPCa to improve survival. Docetaxel is a chemotherapeutic agent belonging to the taxane class of drugs. Docetaxel-based chemotherapy has shown survival benefits and has emerged as the primary treatment for CRPCa. Nevertheless, docetaxel resistance after half a year of therapy has emerged as an urgent clinical concern in patients with CRPCa and mCRPCa.

Fucoidan, sourced from various matrices of brown seaweed, is primarily composed of a complex sulfated polysaccharide, shows anti-cancer effects, and binds to P-selectin.

In this study, it was demonstrated that the combination of Fucoidan/Docetaxel on docetaxel-resistant DU/DX50 cells shows a potent synergistic antiproliferative effect as shown below.

It was also observed that fucoidan reduced the migration and invasion of DU/DX50 cells. Since the protein levels of IL-1R, IKKα, NF-κB p50, and Cox2 were downregulated with an increased concentration of fucoidan, the observed attenuation of cancer cell migration, invasion, and cell viability would be due to the binding effect between fucoidan and P-selectin, resulting in the downregulation of the IL-1R signaling pathway, including reduced levels of NFκB p50 and Cox-2. It is known that IKKα and NF-κB p50 are involved in cancer cell proliferation and metastasis, and the activation of Cox2 promotes tumor growth and resistance to chemotherapy and radiotherapy.

Effects of synthetic microbial consortia derived from rhizosphere soil of wheat against a pathogen causing wheat root rot disease

A group from North Central Agriculture Research Laboratory, USDA-ARS, Brookings, SD, USA, etc. has reported about the effects of synthetic microbial consortia derived from rhizosphere soil of wheat against rhizoctonia solani AG8, a pathogen causing root rot disease.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9473337/

The effects of bacteria, including 14 single strains and 10 SynComs, on wheat root rot disease caused by R. solani AG8 were evaluated in soil in the greenhouse. After 3 weeks, compared with wheat growth in AG8 inoculated soil (CK1, CK2), wheat treated with some single bacterial strains and SynComs reduced root rot at different levels. Among them, wheat treated with single bacterial strains (Pseudomonas sp. B5, Rhodococcus erythropolis B43, Chryseobacterium soldanellicola P38, and Pedobacter sp. P44) and SynComs (C1, C3, C4, C7, C8, C9, and C10) significantly reduced wheat root rot score, compared with the controls (CK1 and CK2) in AG8 inoculated soil. Further, the fresh root weight of wheat treated with single bacterial strains (Pseudomonas spp. B5 and B11, and Chryseobacterium sp. B7) and SynComs (C1, C4, C7, C8, C9, and C10) were greater than those of the controls in AG8 inoculated soil.

SynCom 1(C1): Pseudomonas sp. B5, Pseudomonas sp. B11, Pseudomonas sp. B12, Pseudomonas sp. P25
SynCom 2(C2): Chryseobacterium sp. B7, Chryseobacterium soldanellicola P38, Chryseobacterium sp. P43
SynCom 3(C3): Sphingomonas sp. B17, Cupriavidus campinensis B20, Asticcacaulis sp. B27, Rhodococcus erythropolis B43
SynCom 4(C4): Cupriavidus campinensis B20, Asticcacaulis sp. B27, Rhodococcus erythropolis B43, Chryseobacterium soldanellicola P38
SynCom 5(C5): Cupriavidus campinensis B20, Rhodococcus erythropolis B43, Janthinobacterium lividum BJ, Chryseobacterium soldanellicola P38
SynCom 6(C6): Streptomyces sp. B6, Chryseobacterium sp. B7, Pseudomonas sp. B12, Sphingomonas sp. B17
SynCom 7(C7): Pseudomonas sp. B5, Streptomyces sp. B6, Chryseobacterium sp. B7, Pseudomonas sp. B11
SynCom 8(C8): Pseudomonas sp. B12, Sphingomonas sp. B17, Cupriavidus campinensis B20, Asticcacaulis sp. B27
SynCom 9(C9): Pseudomonas sp. B12, Rhodococcus erythropolis B43, Janthinobacterium lividum BJ, Pedobacter sp. P44
SynCom 10(C10): All 14 bacterial strains

Antiviral activity of UDA llectin against SARS-CoV-2

A group from Laboratory of Virology and Chemotherapy, Rega Institute, Department of Microbiology, Immunology and Transplantation, KU Leuven, Belgium, etc. has reported about antiviral activity of UDA against SARS-CoV-2.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468479/

UDA is one of the smallest plant lectins reported, and has a binding preference for GlcNAc and high-mannose sugars on target glycoproteins.

It was shown that UDA prevents viral replication of the early Wuhan-Hu-1 strain in Vero E6 cells (IC50 = 225 nM), but also the replication of SARS-CoV-2 variants of concern, including Alpha, Beta and Gamma (IC50 ranging from 115 to 171 nM). In addition, UDA exerts antiviral activity against the latest circulating Delta and Omicron variant in U87.ACE2+ cells (IC50 values are 1.6 and 0.9 µM, respectively).

It was found that UDA is not acting as a direct receptor-attachment competitor, and its strongest interaction site is not located in the RBD from SPR analyses.

Site-specific N-Linked glycan characterization of PSMA from metastatic prostate cancer cells

A group from Leroy T. Canoles Jr. Cancer Research Center, Eastern Virginia Medical School, Norfolk, Virginia 23507, USA, etc. has reported about site-specific N-Linked glycopeptide characterization of Prostate-Specific Membrane Antigen from metastatic prostate cancer cells.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9435049/

The prostate-specific membrane antigen (PSMA), also known as folate hydrolase 1 (FOLH1) or glutamate carboxypeptidase 2, was previously studied as a PCa biomarker in tissues and body fluids using conventional biochemical methods with mixed results. PSMA is not exclusively expressed in prostatic tumors; the protein is expressed in low abundance in prostate epithelium, in the neo-vasculature of exclusive solid tumor types, and in some healthy tissues including proximal renal tubes, duodenum, and ganglia of the nervous system. In PCa, PSMA abundance increases with disease severity, and up to 100-fold higher abundance has been observed in advanced aggressive forms of the disease compared to normal tissue.

In this study, two PCa cell lines, LNCaP cells (CRL-1740) and MDAPCa2b (ATCC CRL-2422) were used to compare site-specific N-linked glycopeptide characterization of PSMA.
It was demonstrated that there are significant differences in the expression of several glycans in two cell lines LNCaP and MDAPCa2b (see below), which have different phenotypes, and further there are significantly more glycans identified in MDAPCa2b compared to LNCaP cells.
These studies will form the basis of developing site-specific PSMA glycoform-based prognostic markers for PCa disease stratification in the future.

How extract the features of the complex systems of rhizobacterial microbiomes, and efficiently control the microbiomes?

For self-organizing complex systems, feature extraction methods such as principal component analysis and clustering analysis are often used. Conversely, it means that there is no other good analysis methodology close at hand. In self-organizing complex systems, the properties of the whole can often be neither understood nor predicted by knowledge of its constituents alone, and the interactions between the constituents of the system give rise to new structures and functions, and those will appear on a large scale.
In the case of the rhizobacterial microbiomes, it is possible that when good bacteria is exceeded a certain threshold, opportunistic bacteria become allies and a synergistic effect appears remarkably. The reverse is also true, and when the number of bad bacteria exceeds a certain threshold, the plant dies at once.

The problem is how to perform feature extraction (in other words, pattern recognition) of such a complex system of rhizobacterial microbiome in the field (farm). At the research level, 16S rRNA read analysis of the rhizobacterial microbiomes and computer analysis on the full use of the obtained big data might be able to visualize the hidden patterns which could not be identified with  conventional methods. But, can such a method be used in the field? No, this kind of work will remain in the world of papers. If the technology is not easy for anyone to use, it will not succeed in reality as a business. To be used on site, it has to be cheap, and it has to give immediate results.

Bacillus, Pseudomonas, Streptomyces, Arthrobacter are said to be representative good bacteria as rhizobacteria, and Enterobacter and Barkholderia are also to be good bacteria.
The bacterial classification of such representative good bacteria and bad bacteria is written below.
First of all, good bacteria,
Actinobacteria phylum→ Actinobacteria class → Streptomyces order → Streptomycetae → Streptomyces genus (good guys)
Proteobacteria phylum → γ-Proteobacterial class → Pseudomonad order → Pseudomonadidae → Pseudomonas genus (typical good guys)
Proteobacteria phylum → γ-Proteobacterial class → Enterobacter order → Enterobacteraceae → Enterobacter genus (good guys)
Proteobacteria phylum → β-Proteobacterial class → Barkholderia order → Barkholderidae → Balkholderia genus (good)
Firmicutes phylum→ Bacillus class → Bacillus order → Bacillus family → Bacillus genus (typical good guy)
Actinobacteria phylum→ Actinobacteria class → Actinobacteria family→ Micrococcaceae → Arthrobacter genus (good guys)
and bad bacteria,
Ascomycota phylum → Hydrangea class → Pistanthus → Asteraceae → Fusarium genus (typical bad guys)

If we can sense the phylum Actinobacteria, Proteobacteria, and Firmicutes, it will be possible that we can grasp major patterns in the rhizosphere, I think.
For your information, Proteobacteria are Gram-negative bacteria, while Actinobacteria and Firmicutes are Gram-positive bacteria.

Humic acid could be a good organic fertilizer in greenhouse-planted cherry tomato

A group from College of Environment, Zhejiang University of Technology, Hangzhou 310032, China, etc. has reported that Humic acid could be a good organic fertilizer in greenhouse-planted cherry tomato.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434616/

Due to the adverse effects of chemical fertilization on greenhouse soils, nowadays, special attention has been paid to organic and biological fertilizers or those technical managements that avoid soil fertility reduction in greenhouses. Humic acid is a component of humus, and it is also a natural component and contributes toward the reduction of the diseases and stresses and increase of the crop yield. Actually, several studies have shown that Humic acid application in vegetable production can improve the primary and secondary metabolism of plants, increase crop yields and quality, and decrease pests and diseases. Humic acid can accelerate soil organic material decomposition by increasing the microbial activity in soil. Furthermore, Humic acid can also alter the root exudation profile by affecting the plant metabolism and thus influence the structure of the rhizosphere microbial community. Principal coordinate analysis of the bacterial communities revealed that control, Humic acid application, and organic fertilizer formed different clusters.


where, humic acid (HA), farmyard manure (FM), commercial organic fertilizer (COF), and control check (CK)

Milk lactose can improve diarrhea problems in young pigs

A group from Laboratory of Virology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium, etc. has reported that lactose can improve diarrhea problems in young pigs by a combination of a direct effect by reducing rotavirus infection and inhibiting the growth of bacterial pathogens by balancing the environment.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9428151/

Rotavirus is an important pathogen causing diarrhea in animals and humans. High morbidity and mortality are mainly observed during the first weeks after birth. The rotavirus particles have 11 double-stranded RNA segments encoding six structural viral proteins (VP1-VP4, VP6, and VP7) and six non-structural proteins (NSP1-NSP6). Rota virus has been classified into 10 species, and RVA, B, and C are the most common genotypes that infect humans and animals, including pigs. Among them, the RVA strains have the highest prevalence in a variety of species and is a main cause of diarrhea in the veterinary world.

The carbohydrate binding specificity of recombinant VP8* protein of RBA was determined using a glycan array comprised of 300 glycans, and it was found that it binds to β-lactose strongly.
It was also shown that β-lactose decreases rotavirus infection of MA104 cells with dose dependent manner.

where, RVA strains 13R054 G5P[7] and 12R046 G9P[23]