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. 2025 Jun 13;13(6):1375.
doi: 10.3390/microorganisms13061375.

Bacterial Metabolic Activity of High-Mountain Lakes in a Context of Increasing Regional Temperature

Affiliations

Bacterial Metabolic Activity of High-Mountain Lakes in a Context of Increasing Regional Temperature

Boyanka Angelova et al. Microorganisms. .

Abstract

Global warming poses a significant threat to lake ecosystems, with high-mountain lakes being among the earliest and most severely impacted. However, the processes affecting water ecology under climate change remain poorly understood. This study investigates, for the first time, the effects of regional warming on three high-mountain lakes, Sulzata, Okoto and Bubreka, located in the Rila Mountains, Bulgaria, by examining shifts in bacterial metabolic capacity in relation to the rate and range of utilizable carbon sources using the Biolog EcoPlate™ assay. Over the last decade, ice-free water temperatures in the lakes have risen by an average of 2.6 °C, leading to increased nutrient concentrations and enhanced primary productivity, particularly in the shallowest lake. Bacterial communities responded to these changes by increasing their metabolic rates and shifting substrate preferences from carbohydrates to carboxylic acids. While the utilization rates of some carbon sources remained stable, others showed significant changes-some increased (e.g., D-galactonic acid γ-lactone and itaconic acid), while others decreased (e.g., α-D-lactose and D-xylose). The most pronounced effects of warming were observed in June, coinciding with the onset of the growing season. These findings suggest that rising temperatures may substantially alter bacterial metabolic potential, contributing to a long-term positive feedback loop between lake nutrient cycling and climate change.

Keywords: Biolog EcoPlateTM; bacterial functional diversity; bacterial metabolic shifts; glacial lakes; global warming.

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Conflict of interest statement

The authors declare no conflicts of interest. The funders supported this scientific work only financially. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Map of the Seven Rila Lakes cirque, northwest Rila Mountains, Bulgaria with the highest situated Sulzata (42°11′50.0″ N 23°18′38.9″ E), Okoto (42°11′57.5″ N 23°18′23.1″ E), and Bubreka (42°12′19.6″ N 23°18′26.4″ E) Lakes.
Figure 2
Figure 2
Dendrogram of the clustering analysis (group average—unweighted pair-group) illustrating the grouping of Sulzata (Sul), Okoto (Oko), and Bubreka (Bub) Lake environments (clusters) based on similarity in water characteristics (Euclidean distance) during June (J), August (A), and October (O) in the years 2015 (15), 2022 (22), 2023 (23), and 2024 (24).
Figure 3
Figure 3
Lake water temperature presented as (a) mean water temperature (°C) for the reference (2015 and 2022; n = 27) and recent (2023 and 2024; n = 45) years, and (b) temperature differences in June (n = 18), August (n = 27) and October (n = 18) for Sulzata (Sul), Okoto (Oko), and Bubreka (Bub) Lakes.
Figure 4
Figure 4
Bacterial metabolic activity shown as: (a) monthly average well color development (AWCD) in Sulzata (Sul), Okoto (Oko), and Bubreka (Bub) lakes (n = 3 per lake); and (b) rates of change in AWCD and water temperature (T) in recent years compared to reference years, presented as means across all lakes. In panel (a), the lines represent the average AWCD values for all lakes for each corresponding month.
Figure 5
Figure 5
Community-level physiological profiles (CLPPs) of bacteria from Sulzata (Sul), Okoto (Oko), and Bubreka (Bub) Lakes, expressed in the left column as means of reference (Mean_reference) and recent years (Mean_2023/2024), and in the right column as differences between the two monitoring periods.
Figure 6
Figure 6
RDA plot of CSs’ (blue dots) distribution in relation to sampling months and lakes (black dot—Sul; brown squire—Oko and violet diamond—Bub) and correlations with environmental variables (lines).

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