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. 2025 May 2;15(1):15388.
doi: 10.1038/s41598-025-94542-9.

Exploring prokaryotic diversity in permafrost-affected soils of Ladakh's Changthang region and its geochemical drivers

Affiliations

Exploring prokaryotic diversity in permafrost-affected soils of Ladakh's Changthang region and its geochemical drivers

Ahmad Ali et al. Sci Rep. .

Abstract

Global warming due to climate change has substantial impact on high-altitude permafrost affected soils. This raises a serious concern that the microbial degradation of sequestered carbon can result in alteration of the biogeochemical cycles. Therefore, the characterization of permafrost affected soil microbiomes, especially of unexplored high-altitude, low oxygen arid region, is important for predicting their response to climate change. This study presents the first report of the bacterial diversity of permafrost-affected soils in the Changthang region of Ladakh. The relationship between soil pH, organic carbon, electrical conductivity, and available micronutrients with the microbial diversity was investigated. Amplicon sequencing of permafrost affected soil samples from Jukti and Tsokar showed that Proteobacteria and Actinobacteria were the dominant phyla in all samples. The genera Brevitalea, Chthoniobacter, Sphingomonas, Hydrogenispora, Clostridium, Gaiella, Gemmatimonas were relatively abundant in the Jukti samples whereas the genera Thiocapsa, Actinotalea, Syntrophotalea, Antracticibcterium, Luteolibacter, Nitrospirillum dominated the Tsokar sample. Correlation analyses highlighted the influence of soil geochemical parameters on the bacterial community structure. PCoA analyses showed that the bacterial beta diversity varied significantly between the sampling locations (PERMANOVA test (F-value: 2.3316; R2 = 0.466, p = 0.001) and similar results were also obtained while comparing genus abundance data using the ANOSIM test (R = 0.345, p = 0.007).

Keywords: 16S rRNA; Alpine permafrost; Bacteria; Illumina sequencing; Microbiome.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Map and representative field photos. (a) Map of the sampling locations (b, c) Field photographs showing typical permafrost affected areas.
Fig. 2
Fig. 2
Sampling strategy for permafrost-affected soils from Tsokar and Jukti. (a) A total of 12 samples were sequenced, categorized as upper soil (1–20 cm; JUS and TUS) and core soil (20–40 cm; JCS and TCS) from each site, with three replicates for each category (e.g., JUS I–III, TCS I–III). (b) For geochemical analyses, soil samples from each depth were combined into composite samples, resulting in six composite samples (Tsokar upper/core and Jukti upper/core). Abbreviations: JUS—Jukti Upper Soil, JCS—Jukti Core Soil, TUS—Tsokar Upper Soil, TCS—Tsokar Core Soil.
Fig. 3
Fig. 3
Summary of Alpha diversity indices at genus level of JUS (n = 3), JCS (n = 3), TUS (n = 3) and TCS (n = 3). Chao 1 and ACE species indexes represent community richness; Shannon and Simpson represent diversity.
Fig. 4
Fig. 4
PCoA of bacterial community beta diversity in different samples.
Fig. 5
Fig. 5
Venn diagrams illustrating shared and unique microbial taxa among JUS, JCS, TUS, and TCS at genera level. A core microbiome of 183 taxa is shared across all groups, while unique taxa (e.g., 69 in JUS, 70 in TCS) reflect site and depth specific adaptations to permafrost soils.
Fig. 6
Fig. 6
LEfSe performed at OTU level of bacterial community data of TUS (n = 3), TCS (n = 3), JUS (n = 3) and JCS (n = 3).
Fig. 7
Fig. 7
LEfSe significantly discriminative OTUs with absolute LDA score ≥ 2.0. OTUs are associated with different soil cores.
Fig. 8
Fig. 8
Heatmap showing the potential predictive function of permafrost affected soil microbiome.
Fig. 9
Fig. 9
PCoA plots displaying various samples based on their predicted metabolic functions.
Fig. 10
Fig. 10
Relative abundance of major bacterial dominant phyla associated with different soil samples.

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