Determination of Antioxidant, Antimicrobial Activity, Heavy Metals and Elements Content of Seaweed Extracts

In vitro antibacterial, antibiofilm activities, and phytochemical properties of Posidonia oceanica (L.) Delile: An endemic Mediterranean seagrass

In the antibiotic resistance era, utilizing understudied sources for novel antimicrobials or antivirulence agents can provide new advances against antimicrobial resistant pathogens. In this study, we aimed to investigate antibacterial and antibiofilm activities of Posidonia oceanica (L.) Delile against Enterococcus faecalis ATCC 29212, Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922 and Klebsiella pneumoniae ATCC 700603 and several S. aureus clinical isolates obtained from medical devices, including patient urinary catheters and breast implant infections, with varying antibiotic recalcitrance profiles. The ethanolic and methanolic extracts from P. oceanica rhizome exhibited significant antibacterial activity against E. faecalis and S. aureus, as well as drug resistant S. aureus clinical isolates. Furthermore, significant antibiofilm activity was observed against S. aureus and E. faecalis treated with ER, MR1, and MR2. P. oceanica extracts also exhibited synergistic antimicrobial activity with ciprofloxacin against E. faecalis, sensitizing E. faecalis to a lower ciprofloxacin concentration. Collectively, our data demonstrate the selective antibacterial and antibiofilm activity of the extracts of P. oceanica against Gram-positive bacteria and clinical isolates along with potentiation of current antibiotics, which suggests that P. oceanica can be further investigated as a potential source for novel therapeutic options in the treatment of drug resistant bacterial infections.

Heavy metal tolerance, and metal biosorption by exopolysaccharides produced by bacterial strains isolated from marine hydrothermal vents

The present study highlights heavy metal tolerance, EPS production, and biosorption capacity of four hydrothermal vent bacterial strains, namely Exiguobacterium aquaticum, Mammaliicoccus sciuri, Micrococcus luteus, and Jeotgalicoccus huakuii against As, Cd, Cr, Cu, Co, Pb and Ni. The biosorption assay showed high removal efficiency of As (83%) by E. aquaticum, Cd (95%) by M. sciuri, Cu (94%) by M. luteus, and Ni (89%) by J. huakuii and their produced EPS with these metals in aqueous solution were 84%, 85%, 98%, and 91%, respectively. The maximum EPS yield was attained by optimized medium composition consisting of 1% Xylose, and 1% NaCl at pH 7. In metal-amended conditions, the four bacterial strains showed induced EPS production in the initial concentrations. SEM with EDX and CLSM images showed that the growth and EPS production of bacterial strains were affected by metal ion concentrations. A phenol sulphuric acid method and BCA assay were used to identify both the carbohydrate and total protein content of four extracted EPS. A DPPH assay revealed that EPS influences free radical scavenging and has a highly enhanced synergistic effect with its antioxidant activity. FT-IR analysis of four extracted EPS showed the shifting of peaks in the functional groups of EPS before and after adsorption of metal ions. At pH 5 and after 60 min contact time metal removal efficiency and adsorption capacity increased as calculated for As, Cd, Cu, and Ni by four extracted EPS: (86%, 20 mg/g), (74%, 19 mg/g), (94%, 60 mg/g) and (89%, 32 mg/g) and (89%, 16 mg/g), (85%, 16 mg/g), (96%, 22 mg/g) and (91%, 16 mg/g), respectively. The Langmuir compared to the Freundlich model was found to better represent the adsorption by EPS providing maximum adsorption capacities for As (34.65 mg/g), Cd (52.88 mg/g), Cu (24.91 mg/g), and Ni (58.38 mg/g).

Direct and robust citramalate production from brown macroalgae using fast-growing Vibrio sp. dhg

Brown macroalgae is a promising feedstock for biorefinery owing to its high biomass productivity and contents of carbohydrates such as alginate and mannitol. However, the limited availability of microbial platforms efficiently catabolizing the brown macroalgae sugars has restricted its utilization. In this study, the direct production of citramalate, an important industrial compound, was demonstrated from brown macroalgae by utilizing Vibrio sp. dhg, which has a remarkably efficient catabolism of alginate and mannitol. Specifically, citramalate synthase from Methanocaldococcus jannaschii was synthetically expressed, and competing pathways were removed to maximally redirect the carbon flux toward citramalate production. Notably, a resulting strain, VXHC, produced citramalate up to 9.8 g/L from a 20 g/L mixture of alginate and mannitol regardless of their ratios. Citramalate was robustly produced even when diverse brown macroalgae were provided directly. Collectively, this study showcased the high potential of brown macroalgae biorefinery using Vibrio sp. dhg.

Seaweeds in Food: Current Trends

Edible seaweeds are an excellent source of macronutrients, micronutrients, and bioactive compounds, and they can be consumed raw or used as ingredients in food products. However, seaweeds may also bioaccumulate potentially hazardous compounds for human health and animals, namely, heavy metals. Hence, the purpose of this review is to analyze the recent trends of edible seaweeds research: (i) nutritional composition and bioactive compounds, (ii) the use and acceptability of seaweeds in foodstuffs, (iii) the bioaccumulation of heavy metals and microbial pathogens, and (iv) current trends in Chile for using seaweeds in food. In summary, while it is evident that seaweeds are consumed widely worldwide, more research is needed to characterize new types of edible seaweeds as well as their use as ingredients in the development of new food products. Additionally, more research is needed to maintain control of the presence of heavy metals to assure a safe product for consumers. Finally, the need to keep promoting the benefits of seaweed consumption is emphasized, adding value in the algae-based production chain, and promoting a social algal culture.

Prediction Model of Soil Heavy Metal Content Based on Particle Swarm Algorithm Optimized Neural Network

In 2014, the relevant research data from the Ministry of Environmental Protection and the Ministry of Land and Resources showed that the total exceedance rate of soil heavy metal pollution in China had reached 16.1%, and in the construction of ecological civilization in the 13th Five-Year Plan, China has made the prevention and control of soil heavy metal pollution as the focus of prevention and control. Therefore, in this paper, four neural optimization network models, that is, radial basis neural network (RBFNN), generalized regression neural network (GRNN), wavelet neural network (WNN), and fuzzy neural network (FNN), are simulated and created to measure and correlate the soil heavy metal content in a city in northwest China and a city in central China from the actual situation in China. The simulations were conducted. Finally, by analyzing the comparison of predicted and true values of these four models on the test data of two sets of experimental data, the distribution of predicted differences to true values, and the calculation results of three error indicators, we found that WNN has the best prediction performance when using RBFNN, GRNN, WNN, and FNN for soil heavy metal content prediction.