Marine Microbial Polysaccharides: An Untapped Resource for Biotechnological Applications.

As the largest habitat on Earth, the marine environment harbors various microorganisms of biotechnological potential. Indeed, microbial compounds, especially polysaccharides from marine species, have been attracting much attention for their applications within the medical, pharmaceutical, food, and other industries, with such interest largely stemming from the extensive structural and functional diversity displayed by these natural polymers. At the same time, the extreme conditions within the aquatic ecosystem (e.g., temperature, pH, salinity) may not only induce microorganisms to develop a unique metabolism but may also increase the likelihood of isolating novel polysaccharides with previously unreported characteristics. However, despite their potential, only a few microbial polysaccharides have actually reached the market, with even fewer being of marine origin. Through a synthesis of relevant literature, this review seeks to provide an overview of marine microbial polysaccharides, including their unique characteristics. In particular, their suitability for specific biotechnological applications and recent progress made will be highlighted before discussing the challenges that currently limit their study as well as their potential for wider applications. It is expected that this review will help to guide future research in the field of microbial polysaccharides, especially those of marine origin.

Identification of Crown of Thorns Starfish (COTS) using Convolutional Neural Network (CNN) and attention model.

Coral reefs play important roles in the marine ecosystem, from providing shelter to aquatic lives to being a source of income to others. However, they are in danger from outbreaks of species like the Crown of Thorns Starfish (COTS) and the widespread coral bleaching from rising sea temperatures. The identification of COTS for detecting outbreaks is a challenging task and is often done through snorkelling and diving activities with limited range, where strong currents result in poor image capture, damage of capturing equipment, and are of high risks. This paper proposes a novel approach for the automatic detection of COTS based Convolutional Neural Network (CNN) with an enhanced attention module. Different pre-trained CNN models, namely, VGG19 and MobileNetV2 have been applied to our dataset with the aim of detecting and classifying COTS using transfer learning. The architecture of the pre-trained models was optimised using ADAM optimisers and an accuracy of 87.1% was achieved for VGG19 and 80.2% for the MobileNetV2. The attention model was developed and added to the CNN to determine which features in the starfish were influencing the classification. The enhanced model attained an accuracy of 92.6% while explaining the causal features in COTS. The mean average precision of the enhanced VGG-19 with the addition of the attention model was 95% showing an increase of 2% compared to only the enhanced VGG-19 model.

Metabarcoding assessment of fungal diversity in brown algae and sponges of Mauritius.

Marine fungi are largely associated with second most inhabitants of the marine ecosystem such as sponges and algae. They are important colonizers and play vital ecological roles, such as nutrient cycling, organic matter decomposition, and symbiosis with other organisms. High throughput sequencing methods have been used successfully to reveal unknown fungal communities associated with a number of hosts particularly in the marine environment. However, the diversity of marine fungi associated with sponges and brown algae in Mauritius remains largely unknown. Traditional methods based on culturing do not provide reliable estimate of fungal diversity as only those that are able to grow under laboratory conditions are dominant; in addition, a large proportion of fungi, cultured in vitro remain most of the time unidentifiable, given that there are no sporulating structures to be examined morphologically. To overcome these limitations, we employed Illumina sequencing to unravel fungi species present in the sponges, Iotrochota sp. and Biemna sp. and the brown algae Turbinaria conoides, Sargassum pfeifferae, and Sargassum obovatum, collected from the north of Mauritius. Diversity analyses revealed that Biemna sp. had the highest diversity from the sampled sponges with fungi from 24 orders being recovered while from brown algae; Turbinaria conoides had the highest diversity with recovery of fungal taxa of the orders Botryosphaeriales, Chaetothyriales, Eurotiales, Hypocreales, and Mucorales with the latter four orders being common in both sampled algae and sponges. Beta diversity analyses revealed clustering only in the algae, Turbinaria conoides, and Sargassum pfeifferae and not in the co-occurring sponges, indicating that sampling location did not have much influence on fungal diversity. Our findings provide the first amplicon sequencing based insights of the fungal communities associated with macro-algae and sponges in Mauritius and supplements research on the fungal community existing in the oceans around the world.

Fungal Species from Rhododendron sp.: Discosia rhododendricola sp.nov, Neopestalotiopsis rhododendricola sp.nov and Diaporthe nobilis as a New Host Record.

In the present study, we report two new asexual fungal species (i.e., Discosia rhododendricola, Neopestalotiopsis rhododendricola (Sporocadaceae) and a new host for a previously described species (i.e., Diaporthe nobilis; Diaporthaceae). All species were isolated from Rhododendron spp. in Kunming, Yunnan Province, China. All taxa are described based on morphology, and phylogenetic relationships were inferred using a multigenic approach (LSU, ITS, RPB2, TEF1 and TUB2). The phylogenetic analyses indicated that D. rhododendronicola sp. nov. is phylogenetically related to D. muscicola, and N. rhododendricola sp. nov is related to N. sonnaratae. Diaporthe nobilis is reported herein as a new host record from Rhododendron sp. for China, and its phylogeny is depicted based on ITS, TEF1 and TUB2 sequence data.

Prevalence, Genomic Characterization, and Risk Assessment of Human Pathogenic Vibrio Species in Seafood.

ABSTRACT: Pathogenic Vibrio species are largely responsible for human diseases associated with consumption of contaminated seafood. The aim of this study was to determine the prevalence, population densities, species diversity, and molecular characteristics of pathogenic Vibrio in various seafood commodities and the health risks associated with consumption of these contaminated commodities. Samples of finfish and shellfish (oysters and sea urchins) were collected from various regions and analyzed for Vibrio with the most-probable-number (MPN) technique. Genomic DNA of putative Vibrio isolates was analyzed by whole genome sequencing for taxonomic identification and identification of virulence and antimicrobial resistance genes. The risk of Vibrio-related illnesses due to the consumption of contaminated seafood was assessed with Risk Ranger. Populations of presumptive Vibrio were 2.6 to 4.4 log MPN/g and correlated with season; Vibrio levels were significantly higher (P < 0.05) in the summer. Fifteen Vibrio isolates were identified as Vibrio alginolyticus (five isolates), Vibrio parahaemolyticus (six isolates), Vibrio harveyi (two isolates), and Vibrio diabolicus (two isolates). Two of the six V. parahaemolyticus isolates (ST 2504 and ST 2505) from oysters harbored either the tdh gene for thermostable direct hemolysin or the trh gene for thermostable direct hemolysin-related hemolysin. In addition to virulence genes, the shellfish isolates also harbored genes encoding resistance to multiple antibiotics, including tetracycline, penicillin, quinolone, and ß-lactams, thus arousing concern. The risk assessment predicted that an estimated 21 cases of V. parahaemolyticus-associated gastroenteritis could occur in the general population annually due to consumption of contaminated oysters. This study highlights both the wide prevalence and diversity of Vibrio in seafood and the potential for certain strains to threaten public health.

Heavy metal bioaccumulation in commercial Lethrinidae fish species in Mauritius.

Concentrations of heavy metals arsenic, cadmium, lead and mercury and trace elements chromium, copper, nickel and zinc were tested in the muscle tissue of four commercial edible lethrinids fish species from different region of Mauritius. Sky emperor (Lethrinus mahsena) was collected from coastal regions as well as offshore regions (banks) for this study. Blackspot emperor (Lethrinus harak) and spangled emperor (Lethrinus nebulosus) were also studied for their popularity in the fish market. Condition factor was calculated for each fish and the highest value obtained was in Lethrinus mahsena collected from offshore regions (2.598 cm/g). Flame atomic absorption spectrometry was used to analyse copper, nickel and zinc while, graphite furnace technique was used for cadmium, chromium and lead. Mercury levels were evaluated with the cold vapour technique and arsenic with the thermal hydride cell. The level of lead, mercury, copper, nickel and zinc ranged from 0.0011-0.0024 mg/L, 0.0016-0.0036 mg/L, 0.080-0.389 mg/L, 0.566-1.192 mg/L and 0.219-0.422 respectively in wet weight. Interspecies variations in levels of heavy metals and trace elements were observed for nickel and no significant variations occurred for mercury, lead and zinc. Concentrations of heavy metals and trace elements were all within the permissible level except for nickel. As per this study, the Food Act 1998 of Mauritius must be reviewed in order to incorporate the Maximum Permissible Level for nickel.