Development of high yielding strain of Pleurotus tuber-regium: fructification, nutritional and phylogenetic studies.

Mushrooms are nutritionally rich, healthy and medicinal. Pleurotus tuber-regium (Fr.) is one of the nutritious medicinal mushroom found in the tropics and subtropics, but with history of slow growth and low sclerotia yield. In this study, mutants were created by mycelia exposure to ultraviolet irradiation (at a wavelength of 254 nm and a distance of 45 cm), for 3 h and sub-cultured at 30 min interval. The DNA from the wild and mutant strains were extracted, PCR amplified and sequenced. A phylogenetic tree was constructed to show the degree of similarity and differences between the wild and the mutant strains. Fructification studies were conducted on Rhodes grass straw and sawdust to determine the viability of the mutant strains and any nutritional improvement. The wild strain of P. tuber-regium and mutant produced at 30 min (Pt30) cultivated on sawdust and Rhodes straw, yielded sclerotia with biological efficiency of 8.8 and 47.6% respectively. Proximate analysis of the sclerotium showed that the mutant, Pt30, had improved nutritional compositions compared to the wild strain with a total non-structural carbohydrate concentration of 2.41 g as against 0.93 g. Conclusively in this study, better strains of P. tuber-regium were produced with faster growth rate, higher mycelia ramification rate on lignocellulosic substrate and a higher sclerotia yield than the wild P. tuber-regium. It was also established that mutagenesis is capable of improving P. tuber-regium for a successful commercial venture in sclerotia production.

Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models.

Predictive microbiology is a rapidly evolving field that has gained significant interest over the years due to its diverse application in food safety. Predictive models are widely used in food microbiology to estimate the growth of microorganisms in food products. These models represent the dynamic interactions between intrinsic and extrinsic food factors as mathematical equations and then apply these data to predict shelf life, spoilage, and microbial risk assessment. Due to their ability to predict the microbial risk, these tools are also integrated into hazard analysis critical control point (HACCP) protocols. However, like most new technologies, several limitations have been linked to their use. Predictive models have been found incapable of modeling the intricate microbial interactions in food colonized by different bacteria populations under dynamic environmental conditions. To address this issue, researchers are integrating several new technologies into predictive models to improve efficiency and accuracy. Increasingly, newer technologies such as whole genome sequencing (WGS), metagenomics, artificial intelligence, and machine learning are being rapidly adopted into newer-generation models. This has facilitated the development of devices based on robotics, the Internet of Things, and time-temperature indicators that are being incorporated into food processing both domestically and industrially globally. This study reviewed current research on predictive models, limitations, challenges, and newer technologies being integrated into developing more efficient models. Machine learning algorithms commonly employed in predictive modeling are discussed with emphasis on their application in research and industry and their advantages over traditional models.

Epigenetic modifications in solid tumor metastasis in people of African ancestry.

This review focuses on the critical role of epigenetic modifications in solid tumor metastasis, particularly in people of African ancestry. Epigenetic alterations, such as DNA methylation, histone modifications, alterations in non-coding RNAs, and mRNA methylation, significantly influence gene expression, contributing to cancer development and progression. Despite the primary focus on populations of European, American, and Asian descent in most cancer research, this work emphasizes the importance of studying the unique genetic and epigenetic landscapes of African populations for a more inclusive approach in understanding and treating cancer. Insights from this review have the potential to pave the way for the development of effective, tailored treatments, and provide a richer resource for understanding cancer progression and metastasis. Specific focus was placed on the role of DNA methylation, histone modifications, non-coding RNAs, and mRNA methylation in solid tumor metastasis, including how these modifications contribute to the regulation of tumor suppressor genes and oncogenes, influence cellular pathways and signaling, and interact with the immune system. Moreover, this review elaborates on the development of epigenetic-targeted therapeutic strategies and the current advances in this field, highlighting the promising applications of these therapies in improving outcomes for African ancestry populations disproportionately affected by certain types of cancer. Nevertheless, this work acknowledges the challenges that lie ahead, particularly the under-representation of African populations in cancer genomic and epigenomic studies and the technical complications associated with detecting subtle epigenetic modifications. Emphasis is placed on the necessity for more inclusive research practices, the development of more robust and sensitive methods for detecting and interpreting epigenetic changes, and the understanding of the interplay between genetic and epigenetic variations. The review concludes with an optimistic outlook on the future of epigenetic research in People of African ancestry, urging the concerted efforts of researchers, clinicians, funding agencies, and policymakers to extend the benefits of this research to all populations.

Whole genomic sequence of Enterobacter sichuanensis AJI 2411 - A plant growth promoting rhizobacteria.

Enterobacter sichuanensis AJI 2411 is a rhizobacteria displaying plant growth promoting potentials, which was isolated from the rhizosphere of soybeans in Ede, Osun State, Nigeria. The full genome of Enterobacter sichuanensis AJI 2411 was sequenced and reported in this study to shed light on the molecular mechanisms that aids the bacteria's plant growth-promoting abilities.

Bioinformatics Designing and Molecular Modelling of a Universal mRNA Vaccine for SARS-CoV-2 Infection.

At this present stage of COVID-19 re-emergence, designing an effective candidate vaccine for different variants of SARS-CoV-2 is a study worthy of consideration. This research used bioinformatics tools to design an mRNA vaccine that captures all the circulating variants and lineages of the virus in its construct. Sequences of these viruses were retrieved across the six continents and analyzed using different tools to screen for the preferable CD8+ T lymphocytes (CTL), CD4+ T lymphocytes (HTL), and B-cell epitopes. These epitopes were used to design the vaccine. In addition, several other co-translational residues were added to the construct of an mRNA vaccine whose molecular weight is 285.29686 kDa with an estimated pI of 9.2 and has no cross affinity with the human genome with an estimated over 68% to cover the world population. It is relatively stable, with minimal deformability in its interaction with the human innate immune receptor, which includes TLR 3 and TLR 9. The overall result has proven that the designed candidate vaccine is capable of modulating cell-mediated immune responses by activating the actions of CD4+ T cells, natural killer cells, and macrophages, and displayed an increased memory T cell and B cell activities, which may further be validated via in vivo and in vitro techniques.

Detection of hepatitis C virus among HIV patients in Port Harcourt, Rivers State.

BACKGROUND: Hepatitis C virus (HCV) a major human pathogen infecting millions of individuals worldwide, thereby increasing the risks for chronic liver diseases and has been discovered that HIV/HCV co-infected patients have a greater risk. OBJECTIVE: To determine the prevalence of HCV infection among HIV infected people in Port Harcourt, Rivers State. METHODOLOGY: The patients were from the ages of 18 and above attending the antiretroviral clinic for over 6 months. The mean age of the participants was 36.91±8.38. Data were gotten from the 550 patients using a modified questionnaire and 5mls of blood samples were collected through venepuncture into EDTA bottles and spun at 3000rpm for 10 minutes separating the plasma from the whole blood. The CD4+ count was gotten from the patients' file and the samples kept at -700C till analized. HCV antibody was detected using a commercially available third generation kit manufactured by Melsin Medical Co and statistical analysis was done using a Stata version 16. P value was determined using ANOVA. RESULT: Total number positive to the HCV antibody was 24(4.4%) of which 8(33.3%) were males, while 16(66.7%) were females. Prevalence (29.2%) was among patients in the 31-35 age range. The CD4+ count ranged from 22-864 cells/µl with a mean value of 303.08±194. CONCLUSION: From this study HIV/HCV co-infection occurs among HIV infected people in Port Harcourt. The CD4+ count was discovered to be low and was not age, nor gender dependent. HIV infected people should therefore be routinely screened for HCV.

Designing a conserved peptide-based subunit vaccine against SARS-CoV-2 using immunoinformatics approach.

The widespread of coronavirus (COVID-19) is a new global health crisis that poses a threat to the world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in bats and was discovered first in Wuhan, Hubei province, China in December 2019. Immunoinformatics and bioinformatics tools were employed for the construction of a multi-epitope subunit vaccine to prevent the diseases. The antigenicity, toxicity and allergenicity of all epitopes used in the construction of the vaccine were predicted and then conjugated with adjuvants and linkers. Vaccine Toll-Like Receptors (2, 3, 4, 8 and 9) complex was also evaluated. The vaccine construct was antigenic, non-toxic and non-allergic, which indicates the vaccines ability to induce antibodies in the host, making it an effective vaccine candidate. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-020-00062-x.

Influence of eco-friendly phytotoxic metabolites from Lasiodiplodia pseudotheobromae C1136 on physiological, biochemical, and ultrastructural changes on tested weeds.

In this study, the active metabolites from both the wild strain of Lasiodiplodia pseudotheobromae C1136 and three genetically enhanced strains of C1136 were obtained through random mutagenesis. The effect of the active metabolites from these strains was evaluated in relation to physiological, biochemical, and ultrastructural changes on the leaves of two weeds (Amaranthus hybridus and Echinochloa crus-galli). The phytotoxic metabolites secreted by the genetically enhanced strains showed a decrease in the pigments (chl a, chl b, and carotenoids), carbohydrate content, and the amino acid profile. On the other hand, an increase in total phenols of the tested leaves was observed when compared with the untreated leaves. The scanning electron microscopy showed the presence of damages, necrosis, degradation, and ultrastructural changes on the tested leaf tissues of the weeds. Also, increased lipid peroxidation and electrolyte leakage were also observed on the tested weeds treated with phytotoxic metabolites secreted by the genetically enhanced strains. We also showed that the phytotoxins from the strains of C1136 are biocompatible and that it improved soil CO2 evolution, organic carbon content, and enzymatic activity (acidic and alkaline phosphatase, dehydrogenases, cellulase, catalase). The study validates the severe pathological effects of phytotoxic metabolites from the strains of C1136 on the leaves of the weeds presented in this study. The mode of action of the phytotoxic metabolites produced from this bioherbicidal isolates will go a long way in preventing environmental hazards.

A critical appraisal of COVID-19 as a nosocomial infection: an African perspective.

The pandemic of Coronavirus disease 19 is not abating since the outbreak began in December 2019. Africa is currently experiencing a surge after an initial low incidence and nosocomial infections could be contributing to this. A dominant factor responsible for this is a weak healthcare system because of many years of neglect due to abysmal budgetary allocation to the sector. The testing capacity for COVID-19 diagnosis in Africa is grossly inadequate coupled with a severe shortage of personal protective equipment and inadequate infectious diseases expert. These factors exposed the frontline health workers and patients to the hazard of nosocomial infection with the attendants´ morbidity and mortality. Deliberate efforts need to be made toward reducing nosocomial COVID-19 infection.

Laboratory diagnosis of COVID-19 in Africa: availability, challenges and implications.

The COVID-19 infection has been a matter of urgency to tackle around the world today, there exist 200 countries around the world and 54 countries in Africa that the COVID-19 infection cases have been confirmed. This situation prompted us to look into the challenges African laboratories are facing in the diagnosis of novel COVID-19 infection. A limited supply of essential laboratory equipment and test kits are some of the challenges faced in combatting the novel virus in Africa. Also, there is inadequate skilled personnel, which might pose a significant danger in case there is a surge in COVID-19 infection cases. The choice of diagnostic method in Africa is limited as there are only two available diagnostic methods being used out of the six methods used globally, thereby reducing the opportunity of supplementary diagnosis, which will further lead to inappropriate diagnosis and affect the accuracy of diagnostic reports. Furthermore, challenges like inadequate power supply, the method used in sample collection, storage and transportation of specimens are also significant as they also pose their respective implication. From the observations, there is an urgent need for more investment into the laboratories for proper, timely, and accurate diagnosis of COVID-19.

Exploration of surface glycoprotein to design multi-epitope vaccine for the prevention of Covid-19.

Stimulation and generation of T and B cell-mediated long-term immune response are essential for the curbing of a deadly virus such as SAR-CoV-2 (Severe Acute Respiratory Corona Virus 2). Immunoinformatics approach in vaccine design takes advantage of antigenic and non-allergenic epitopes present on the spike glycoprotein of SARS-CoV-2 to elicit immune responses. T cells and B cells epitopes were predicted, and the selected residues were subjected to allergenicity, antigenicity and toxicity screening which were linked by appropriate linkers to form a multi-epitope subunit vaccine. The physiochemical properties of the vaccine construct were analyzed, and the molecular weight, molecular formula, theoretical isoelectric point value, half-life, solubility score, instability index, aliphatic index and GRAVY were predicted. The vaccine structure was constructed, refined, validated, and disulfide engineered to get the best model. Molecular binding simulation and molecular dynamics simulation were carried out to predict the stability and binding affinity of the vaccine construct with TLRs. Codon acclimatization and in silico cloning were performed to confirm the vaccine expression and potency. Results obtained indicated that this novel vaccine candidate is non-toxic, capable of initiating the immunogenic response and will not induce an allergic reaction. The highest binding energy was observed in TLR4 (Toll-like Receptor 4) (-1398.1), and the least is TLR 2 (-1479.6). The steady rise in Th (T-helper) cell population with memory development was noticed, and IFN-g (Interferon gamma) was provoked after simulation. At this point, the vaccine candidate awaits animal trial to validate its efficacy and safety for use in the prevention of the novel COVID-19 (Coronavirus Disease 2019) infections.

Optimization of the Process for Producing Biomass and Exopolysaccharide from the King Tuber Oyster Mushroom, Pleurotus tuber-regium (Agaricomycetes), for Biotechnological Applications.

The optimization of microbial growth for biotechnological purposes traditionally requires an approach that uses only one variable at a time, which has many drawbacks. This research used a completely randomized approach to optimize carbon and nitrogen nutrient requirements and growth factors (pH and temperature) for Pleurotus tuber-regium in order to optimally produce biomass and extracellular polysaccharide (EPS) in shake-flask cultures. An artificial neural network (ANN) module was used to simulate the fungus-growing process and hence determine optimal conditions. The experiments demonstrated the effectiveness of the EPS fraction from P. tuber-regium in preserving hepatic cells against paracetamol-induced damage. Totals of 0.699 g biomass and 0.291 g EPS per 100 mL medium were obtained, whereas the ANN predicted 0.750 g biomass and 0.300 g EPS per 100 mL medium, thereby achieving 93.20% predictability for biomass and 73.00% predictability for EPS. Conditions for optimal EPS and biomass production for P. tuber-regium were quite different. Rat hepatic cells that had been fortified with the EPS fraction from P. tuber-regium were effectively preserved against liver damage. By using a mathematical approach, this study established optimal fermentation conditions for mycelia biomass and EPS production by P. tuber-regium and the relevant biotechnological implications.

Environmental fate and effects of granular pesta formulation from strains of Pseudomonas aeruginosa C1501 and Lasiodiplodia pseudotheobromae C1136 on soil activity and weeds.

This work investigated the effect of variably formulated pesta granules containing wild and UV mutated Pseudomonas aeruginosa and Lasiodiplodia pseudotheobromae on the rate of CO2 evolution, organic carbon content, enzymatic activity (acidic and alkaline phosphatase, dehydrogenases, urease and protease) and representative soil microorganisms in the soils using different assay techniques. After the 35th day period of experiment, the pesta granule formulation BH4 showed the best evolution of CO2 (824 ±â€¯6.2 mg CO2 kg-1 soil hr-1) as against control treatment (689 ±â€¯3.7 mg CO2 kg-1 soil hr-1). Enzymes activities, organic carbon content of 3.8% on the 15th day of study and stable representation of microorganisms that include actinomycetes, fungi, heterogenous as well as soil nitrogen-mediatory bacteria were equally at their maximum level BH4 treatments. The phytotoxic assay showed no inhibitory effect on Solanum lycopersicum seeds and seedlings compared to the observed growth inhibition on the tested weeds (Amaranthus hybridus and Echinocholoa crus-galli) which corresponds with positive control glyphosate treatment. The glyphosate treated soil had the least critical results on parameters investigated during the study. The order of bioherbicidal activity is BH4>BH2>BH6>BH3>BH1>BH5>positive control. Results from this study confirmed the target efficacy of variably formulated pesta granules which is sustainable, cheap, ecologically suitable and recent. This is in addition to recognizing the microbial-derived formulations as characteristically potent alternative to chemical herbicides utility in agrosystems practice. Further study of the underlining factor responsible for the bioherbicidal performances of the variably formulated pesta granules and field trials are critical for their future commercialization.