Environmental DNA Application to Identify Protozoan Community in the Sediment of Balekambang Lake, Dieng, Central Java

Authors

  • Shafa Tasya Nabila Diponegoro University, Indonesia
  • Tri Retnaningsih Soeprobowati Diponegoro University, Indonesia
  • Ni Kadek Dita Cahyani Diponegoro  University, Indonesia
  • Jumari Jumari Diponegoro University, Indonesia
  • Riche Hariyati Diponegoro University, Indonesia
  • Henk Heijnis Australian Nuclear for Science and Technology, Australia

DOI:

https://doi.org/10.51264/inajl.v5i1.48

Keywords:

Protozoa, Next Generation Sequencing (NGS), Environmental DNA, 18S rRNA, Balekambang Dieng

Abstract

Lake Balekambang, Dieng, has a high level of sedimentation that can affect water quality, so it is necessary to identify organisms to assess the lake's environmental conditions. The use of eDNA methods in Indonesia is minimal, especially in the Dieng area. This research aims to identify the protozoan communities in sediment samples from Lake Balekambang using the Environmental DNA (eDNA) method to assess the lake ecosystem. This study targeting the 18S rRNA gene for single cell eukaryotes. Data analysis was performed using GALAXY and RStudio. Bioinformatics analysis obtained 51,172 reads divided into 48 Amplicon Sequence Variants (ASVs). All specimens were identified as eukaryotes. Protozoa taxa that can be identified are Tritrichomonadidae, Ophryoscolecidae, Gregarinidae, Cyrtolophosididae, Hexamitidae, Isotrichidae, Oxytrichidae, Vannellidae, Vermamoebidae, and other unidentified Eukaryota taxa. Using the eDNA method this study able to identify the protozoan community found in the sediments of Lake Balekambang, Dieng. Protozoa taxa that are identified are taxa that generally inhabit the rumen of ruminants and the gastrointestinal tract of rodents, and are generally pathogens that can cause disease in humans and animals. New knowledge about Environmental DNA Metabarcoding (eDNA) can support research in identifying organisms. This study shows that the eDNA method utilizing the Next Generation Sequencing (NGS) approach are able to identify the protist more effectively, massively, and quickly compared to conventional methods based on morphological characteristics.

Author Biographies

Shafa Tasya Nabila, Diponegoro University, Indonesia

Department  of  Biology,  Faculty  of  Science  and  Mathematics,  Diponegoro  University Semarang, Indonesia

Tri Retnaningsih Soeprobowati, Diponegoro University, Indonesia

Department  of  Biology,  Faculty  of  Science  and  Mathematics,  Diponegoro  University Semarang, Indonesia
Cluster for Paleolimnology (CPalim), School of Postgraduate Studies, Diponegoro University, Semarang, Indonesia

Ni Kadek Dita Cahyani, Diponegoro  University, Indonesia

Department  of  Biology,  Faculty  of  Science  and  Mathematics,  Diponegoro  University, Semarang, Indonesia

Jumari Jumari, Diponegoro University, Indonesia

Department  of  Biology,  Faculty  of  Science  and  Mathematics,  Diponegoro  University, Semarang, Indonesia

Riche Hariyati, Diponegoro University, Indonesia

Department  of  Biology,  Faculty  of  Science  and  Mathematics,  Diponegoro  University, Semarang, Indonesia

Henk Heijnis, Australian Nuclear for Science and Technology, Australia

Cluster for Paleolimnology (CPalim), Diponegoro University, Semarang, Indonesia
Adjunct Professor, Diponegoro University, Semarang, Indonesia
Australian Nuclear for Science and Technology, Australia

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2024-08-29