Cyclic lipopeptide-producing Pseudomonas koreensis group strains dominate the cocoyam rhizosphere of a Pythium root rot suppressive soil contrasting with P. putida prominence in conducive soils

Pseudomonas isolates from tropical environments have been underexplored and may form an untapped reservoir of interesting secondary metabolites. In this study, we compared Pseudomonas and cyclic lipopeptide (CLP) diversity in the rhizosphere of a cocoyam root rot disease (CRRD) suppressive soil in Boteva, Cameroon with those from four conducive soils in Cameroon and Nigeria. Compared with other soils, Boteva andosols were characterized by high silt, organic matter, nitrogen and calcium. Besides, the cocoyam rhizosphere at Boteva was characterized by strains belonging mainly to the P. koreensis and P. putida (sub)groups, with representations in the P. fluorescens, P. chlororaphis, P. jessenii and P. asplenii (sub)groups. In contrast, P. putida isolates were prominent in conducive soils. Regarding CLP diversity, Boteva was characterized by strains producing 11 different CLP types with cocoyamide A producers, belonging to the P. koreensis group, being the most abundant. However, putisolvin III-V producers were the most dominant in the rhizosphere of conducive soils in both Cameroon and Nigeria. Furthermore, we elucidated the chemical structure of putisolvin derivatives—putisolvin III-V, and described its biosynthetic gene cluster. We show that high Pseudomonas and metabolic diversity may be driven by microbial competition, which likely contributes to soil suppressiveness to CRRD.     

Changes in Retinal Function and Morphology Are Early Clinical Signs of Disease in Cattle with Bovine Spongiform Encephalopathy

Bovine spongiform encephalopathy (BSE) belongs to a group of fatal, transmissible protein misfolding diseases known as transmissible spongiform encephalopathies (TSEs). All TSEs are caused by accumulation of misfolded prion protein (PrP^Sc) throughout the central nervous system (CNS), which results in neuronal loss and ultimately death. Like other protein misfolding diseases including Parkinson’s disease and Alzheimer’s disease, TSEs are generally not diagnosed until the onset of disease after the appearance of unequivocal clinical signs. As such, identification of the earliest clinical signs of disease may facilitate diagnosis. The retina is the most accessible part of the central nervous system, and retinal pathology in TSE affected animals has been previously reported. Here we describe antemortem changes in retinal function and morphology that are detectable in BSE inoculated animals several months (up to 11 months) prior to the appearance of any other signs of clinical disease. We also demonstrate that differences in the severity of these clinical signs reflect the amount of PrP^Sc accumulation in the retina and the resulting inflammatory response of the tissue. These results are the earliest reported clinical signs associated with TSE infection and provide a basis for understanding the pathology and evaluating therapeutic interventions.     

Acid-sensing ion channel 3 mediates peripheral anti-hyperalgesia effects of acupuncture in mice inflammatory pain

Background  

Peripheral tissue inflammation initiates hyperalgesia accompanied by tissue acidosis, nociceptor activation, and inflammation mediators. Recent studies have suggested a significantly increased expression of acid-sensing ion channel 3 (ASIC3) in both carrageenan- and complete Freund's adjuvant (CFA)-induced inflammation. This study tested the hypothesis that acupuncture is curative for mechanical hyperalgesia induced by peripheral inflammation.     

Protein structure similarity from principle component correlation analysis

Background  

Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities.     

Design of inhibitors of Helicobacter pylori glutamate racemase as selective antibacterial agents: Incorporation of imidazoles onto a core pyrazolopyrimidinedione scaffold to improve bioavailabilty

Structure-activity relationships are presented around a series of pyrazolopyrimidinediones that inhibit the growth of Helicobacter pylori by targeting glutamate racemase, an enzyme that provides d-glutamate for the construction of N-acetylglucosamine-N-acetylmuramic acid peptidoglycan subunits assimilated into the bacterial cell wall. Substituents on the inhibitor scaffold were varied to optimize target potency, antibacterial activity and in vivo pharmacokinetic stability. By incorporating an imidazole ring at the 7-position of scaffold, high target potency was achieved due to a hydrogen bonding network that occurs between the 3-position nitrogen atom, a bridging water molecule and the side chains Ser152 and Trp244 of the enzyme. The lipophilicity of the scaffold series proved important for expression of antibacterial activity. Clearances in vitro and in vivo were monitored to identify compounds with improved plasma stability. The basicity of the imidazole may contribute to increased aqueous solubility at lower pH allowing for improved oral bioavailability.     

Conditional random pattern model for copy number aberration detection

Background  

DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable.     

The Association between Individual and Combined Components of Metabolic Syndrome and Chronic Kidney Disease among African Americans: The Jackson Heart Study

Introduction

Approximately 26.3 million people in the United States have chronic kidney disease and many more are at risk of developing the condition. The association between specific metabolic syndrome components and chronic kidney disease in African American individuals is uncertain.

Methods

Baseline data from 4,933 participants of the Jackson Heart Study were analyzed. Logistic regression models were used to estimate the odds and 95% confidence intervals of chronic kidney disease associated with individual components, metabolic syndrome, the number of components, and specific combinations of metabolic syndrome components.

Results

Metabolic syndrome was common with a prevalence of 42.0%. Chronic kidney disease was present in 19.4% of participants. The prevalence of metabolic components was high: elevated blood pressure (71.8%), abdominal obesity (65.8%), low fasting high density lipoprotein cholesterol (37.3%), elevated fasting glucose (32.2%) and elevated triglycerides (16.2%). Elevated blood pressure, triglycerides, fasting blood glucose, and abdominal obesity were significantly associated with increased odds of chronic kidney disease. Participants with metabolic syndrome had a 2.22-fold (adjusted odds ratio (AOR) 2.22; 95% CI, 1.78–2.78) increase in the odds of chronic kidney disease compared to participants without metabolic syndrome. The combination of elevated fasting glucose, elevated triglycerides, and abdominal obesity was associated with the highest odds for chronic kidney disease (AOR 25.11; 95% CI, 6.94–90.90).

Conclusion

Metabolic syndrome as well as individual or combinations of metabolic syndrome components are independently associated with chronic kidney disease in African American adults.     

Global research trends on bioflocculant potentials in wastewater remediation from 1990 to 2019 using a bibliometric approach

The preference of biofloculants over chemical flocculants in water and wastewater remediation systems has gained wider attention due to their biodegradability, innocuousness, safety to human and environmental friendliness. The present study aimed to evaluate research outputs on bioflocculant potentials in wastewater remediation from 1990 to 2019 using bibliometric analyses. To the best of our knowledge, this is the first bibliometric report in bioflocculant research. The subject bibliometric dataset was extracted from the Web of Science Core Collection (WoSCC) and Scopus using the Boolean, ‘bioflocculant* and waste*’ and analysed for indicators such as a yearly trend, productivity (authors, articles, country, institution and journal source), conceptual framework and collaboration network. We found 119 documents with 347 authors from 78 journal sources on the subject, an annual growth rate of 12·1%, and average citations/document of 15·08. Guo J. and Wang Y. were the top researchers with 15 and 12 outputs respectively. China (42%) and South Africa (9·24%) ranked the top two dominant countries in the field. The top journals were Bioresource Technology (9 papers, 506 citations), Applied Microbiology and Biotechnology (5 papers, 268 citations), whereas, the top institution was Chengdu University of Information and Technology (n = 9 documents) followed by Sichuan Univ. Sci. & Engn, China (n = 8 documents). This study found that lack of intercountry collaboration and research funding adversely affects research participants in the field.     

Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces

Background

Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data.

Results

Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG.

Conclusions

We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.