Recent Developments of Exploration and Detection of Shallow-Water Hydrothermal Systems

Prokaryotic communities associated with marine hydrothermal systems of the Gulf of California

Introduction

Marine hydrothermal systems (MHS) are considered extreme environments due to their unique physicochemical conditions, which are challenging for most organisms. This study investigates the microbial communities in three MHS sites in Baja California Sur, Mexico.

Methods

Sediment samples were collected in two seasons of the year: rainy and dry season. Bacterial DNA was extracted, the V3-V4 regions of the 16S rRNA gene were amplified.

Results and discussion

The analysis of microbial community structure and composition revealed that species richness and diversity were higher at control sites (not influenced by hydrothermal conditions). Samples from the MHS showed temporal variation in richness, as measured by the Chao1 index. Alphaproteobacteria and Gammaproteobacteria were the dominant classes. No significant differences in community structure were found between the seasons or between the control and MHS sites. However, the analysis did reveal differences in community structure among the three hydrothermal locations: Burro, Santispac, and Agua Caliente. The presence of Gammaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, and Betaproteobacteria highlights their key roles in primary production within shallow hydrothermal systems, these microbial communities demonstrate their capacity to colonize diverse substrates. This study enhances the microbiological understanding of hydrothermal environments in Baja California Sur, and molecular analysis of unculturable microbes could provide further insights into their physiology and ecological roles in shallow hydrothermal systems.

Shallow-Water Hydrothermal Vents as Natural Accelerators of Bacterial Antibiotic Resistance in Marine Coastal Areas

Environmental contamination by heavy metals (HMs) poses several indirect risks to human health, including the co-spreading of genetic traits conferring resistance to both HMs and antibiotics among micro-organisms. Microbial antibiotic resistance (AR) acquisition is enhanced at sites anthropogenically polluted by HMs, as well as in remote systems naturally enriched in HMs, such as hydrothermal vents in the deep sea. However, to date, the possible role of hydrothermal vents at shallower water depths as hot spots of microbial AR gain and spreading has not been tested, despite the higher potential risks associated with the closer vicinity of such ecosystems to coasts and human activities. In this work, we collected waters and sediments at the Panarea shallow-water hydrothermal vents, testing the presence of culturable marine bacteria and their sensitivity to antibiotics and HMs. All of the bacterial isolates showed resistance to at least one antibiotic and one HM and, most notably, 80% of them displayed multi-AR on average to 12 (min 8, max 15) different antibiotics, as well as multi-HM tolerance. We show that our isolates displayed high similarity (≥99%) to common marine bacteria, affiliating with Actinobacteria, Gammaproteobacteria, Alphaproteobacteria and Firmicutes, and all displayed wide growth ranges for temperature and salinity during in vitro physiological tests. Notably, the analysis of the genomes available in public databases for their closest relatives highlighted the lack of genes for AR, posing new questions on the origin of multi-AR acquisition in this peculiar HM-rich environment. Overall, our results point out that shallow-water hydrothermal vents may contribute to enhance AR acquisition and spreading among common marine bacteria in coastal areas, highlighting this as a focus for future research.

A Rigid Cuckoo Search Algorithm for Solving Short-Term Hydrothermal Scheduling Problem

The key criteria of the short-term hydrothermal scheduling (StHS) problem is to minimize the gross fuel cost for electricity production by scheduling the hydrothermal power generators considering the constraints related to power balance; the gross release of water, and storage limitations of the reservoir, and the operating limitations of the thermal generators and hydropower plants. For addressing the same problem, numerous algorithms were being used, and related studies exist in the literature; however, they possess limitations concerning the solution state and the number of iterations it takes to reach the solution state. Hence, this article proposes using an enhanced cuckoo search algorithm (CSA) called the rigid cuckoo search algorithm (RCSA), a modified version of the traditional CSA for solving the StHS problem. The proposed RCSA improves the solution state and decreases the iteration numbers related to the CSA with a modified Lévy flight. Here, the movement distances are divided into multiple possible steps, which has infinite diversity. The effectiveness of RCSA has been validated by considering the hydrothermal power system. The observed results reveal the superior performance of RCSA among all other compared algorithms that recently have been used for the StHS problem. It is also observed that the RCSA approach has achieved minimum gross costs than other techniques. Thus, the proposed RCSA proves to be a highly effective and convenient approach for addressing the StHS problems