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一种用于对浅水淡水湖泊中浮游细菌多样性进行高分辨率分析的长读长测序方法。

A long-read sequencing approach to high-resolution profiling of bacterioplankton diversity in a shallow freshwater lake.

作者信息

Castro Márquez Stephanie O, Tóth Viktor R, Kolchanova Sofiia, Wolfsberger Walter W, Oleksyk Taras K

机构信息

Department of Biological Sciences, Oakland University, Rochester, MI, USA.

Department of Biology, University of Puerto Rico - Mayagüez, Mayagüez, Puerto Rico.

出版信息

Sci Rep. 2025 Apr 10;15(1):12224. doi: 10.1038/s41598-025-96558-7.

DOI:10.1038/s41598-025-96558-7
PMID:40210952
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11986156/
Abstract

Lake Balaton, a large shallow freshwater lake in Hungary, exhibits diverse bacterioplankton communities influenced by various environmental factors. This study aims to evaluate the bacterial diversity in Lake Balaton using the long-read approach to 16 S rRNA gene sequencing. Water samples were collected from a wide network of 33 locations across the lake's four basins and analyzed for bacterial community composition. Sequencing results revealed a high taxonomic diversity with significant zonal variations. Dominant families included Comamonadaceae, Burkholderiaceae, and Methylophilaceae. Environmental parameters such as temperature, pH, and CDOM were found to significantly correlate with bacterial abundance and diversity. The study underscores the utility and portability of using the long-read sequencing technology in assessing microbial diversity and provides insights into the ecological dynamics of bacterioplankton in freshwater lakes.

摘要

巴拉顿湖是匈牙利的一个大型浅水淡水湖,其浮游细菌群落多样,受多种环境因素影响。本研究旨在采用长读长方法对16S rRNA基因进行测序,以评估巴拉顿湖的细菌多样性。从该湖四个流域的33个地点组成的广泛网络中采集水样,并分析细菌群落组成。测序结果显示出高度的分类多样性以及显著的区域差异。优势科包括丛毛单胞菌科、伯克霍尔德菌科和嗜甲基菌科。研究发现温度、pH值和有色溶解有机物等环境参数与细菌丰度和多样性显著相关。该研究强调了使用长读长测序技术评估微生物多样性的实用性和可移植性,并为淡水湖浮游细菌的生态动态提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/20d3199bcd4e/41598_2025_96558_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/ef818846e2b6/41598_2025_96558_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/8c3e79695fa4/41598_2025_96558_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/ecf98317adce/41598_2025_96558_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/20d3199bcd4e/41598_2025_96558_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/ef818846e2b6/41598_2025_96558_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/8e4e5b7f48f0/41598_2025_96558_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/ff8d734d2c16/41598_2025_96558_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/b3d9380c1f47/41598_2025_96558_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/8c3e79695fa4/41598_2025_96558_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/ecf98317adce/41598_2025_96558_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/11986156/20d3199bcd4e/41598_2025_96558_Fig7_HTML.jpg

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Advancements in long-read genome sequencing technologies and algorithms.
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