DOI: 10.5061/dryad.sn02v6xcd
title: Diversity, adaptation and metabolic potential of the microbiome in biofilms from a high-temperature hot spring

description: Hot spring microbiomes have garnered significant research attention from
 exploring the diversity of prokaryotic communities to genes and functional
 potentials. While cyanobacteria-rich biofilms, characterized by warm
 temperatures, have been extensively studied, there is limited
 investigation into high-temperature streamer biofilm communities (SBC)
 devoid of photosynthetic ability. Here, we studied the biofilm of a Dusun
 Tua (DT) hot spring with a temperature of 75°C and a pH of 7.6. This
 grey-tan colored biofilm appeared at sites where water had slowed down
 following the deposition of plants and inorganic debris along the hot
 spring after a flood event. Amplicon sequencing of V3-V4 regions of 16S
 rRNA showed that dominant phyla included the Aquificota, Chloroflexota,
 and Desulfobacterota together with other abundant amplicon sequence
 variants from the Bacteroidota, Deinococcota, Hydrothermae and
 Armatimonadota. These microbial populations appeared to be distinct from
 other reported SBCs from Yellowstone National Park in the USA and Rehai
 Hot Springs in China. Additional shotgun sequencing of the DT biofilm
 revealed functional insights which were compared to counterparts obtained
 from low-temperature biofilms to identify possible thermophilic traits. GC
 content of tRNA and amino acid preferences were found to be clear
 indicators of thermophilicity. However, other signatures such as reverse
 gyrase, heat shock proteins, and average GC content of the genome may not
 be reliable indicators. The genome-centric analyses revealed that DT
 biofilm members were primarily chemo-organoheterotrophic,
 chemolithoautotrophic, and chemolithoheterotrophic. We speculate that the
 biofilm could utilize plant litter as carbon sources, but the efficiency
 of this process is estimated to be low due to rapid water flux that would
 rapidly remove dissolved organic carbon. The results of this study enhance
 current understanding of microbial diversity, thermal adaptation and
 metabolic processes related to carbon, nitrogen, sulfur and other
 metabolisms for hot springs in tropical climates with high allochthonous
 plant litter inputs.
description: <strong>Methodology</strong>
 <em>Sampling and DNA extraction</em>
 The Dusun Tua (DT) hot spring is located at 3.136838613811952,
 101.83446401515266. Sampling trips were performed in July 2022 (labelled
 DT-7) and November 2022 (DT-11). Samples of the gray-tan biofilm were
 randomly collected and immediately transported to the laboratory and
 frozen at −20 °C within 12 h. The bulk genomes of the samples were
 extracted using SPINeasy<sup>TM </sup>DNA extraction kit (MP
 Biomedicals, Irvin, CA, USA) according to the manufacturer’s recommended
 protocol. DT biofilm samples were lysed via bead beating, following 3
 cycles (20 Hz) for 1 minutes each. The extracted DNA were evaluated using
 a Nanodrop<sup>TM</sup> 1000 spectrophotometer (Thermo
 Scientific, Wilmington, DE, USA), a Qubit 3.0 Fluorometer (Invitrogen,
 Merelbeke, Belgium) and with a 1% w/v agarose gel
 electrophoresis.  
 <em>Shotgun sequencing and data
 processing</em> The duplicated extracted
 metagenomic DNA from each sampling time were pooled prior to fragmentation
 by a Covaris sonicator (Covaris, Woburn, USA). Then, the fragmented DNA
 was used for dual-indexed, paired-end library construction following the
 Illumina DNA Prep kit protocol (Illumina, San Diego, USA). The constructed
 library samples were analyzed in Qubit 3.0 Fluorometer and Agilent
 Bioanalyzer 2100 (Agilent Technologies, Palo Alto, USA). Shotgun
 metagenome sequencing was carried out in an Illumina NovaSeq 6000 with the
 running mode of PE 150 (paired-end 150 bp). A minimum of 20 Gb (equivalent
 to approximately 66.5 million paired end reads) output was reserved for
 each sample. The resulting raw pair-end reads were trimmed and filtered
 using seqtk-v1.4. In addition, the identical genomic sample undergone
 Nanopore long-read sequencing. We conducted library preparation directly
 following the Nanopore-recommended protocol SQK-NBD112-24 (Q20+ chemistry
 on R10.4 flow cell), omitting genome shearing to prioritize obtaining
 longer reads. The Nanopore Ligation Sequencing Kit SQK-LSK112 protocol was
 adhered to, including AMPure treatment, adapter ligation, purification,
 and Qubit quantification. Samples were loaded onto a MinION R10.4 flow
 cell within Mk1C, operating with MinKNOW v.22.05.8. Basecalling was
 performed using MinKNOW coupled with Guppy v6.1.5, configured with
 FLO-MIN112-Super-Accurate settings. After basecalling, the process
 involved the removal of barcodes, trimming and filtering reads, followed
 by subjecting those meeting Q20 criteria (&lt;5% error) to de novo
 assembly using Flye v2.9 (parameters: --nano-hq --meta). Co-assembly was
 then performed with the pooled Illumina clean reads (DT_7 and DT_11) along
 with Nanopore long reads data using MegaHIT v1.29.
   The taxonomy classification of the assembled
 contigs were carried out using kraken2 v2.1.3. The tRNAs within the
 metagenome were identified using tRNAscan-SE v2.0.12. The genes or coding
 region of the metagenome were predicted using Prodigal v2.6.3. Assessment
 of thermophilic adaptation is performed via comparison between the
 thermophilic DT sample and the psychrophilic GF_Ru and GF_NZ samples
 (0.5-7.7°C, pH 7.54-7.68) based on several parameters. The raw reads for
 GF_Ru and GF_NZ samples were obtained from NCBI and contigs were generated
 using the procedure described earlier. The overall and tRNA GC content of
 the samples were obtained by running a python script against the contigs
 and tRNA sequence. The amino acid composition of the samples were also
 obtained by running a python script against the coding region of the
 samples. Sequences of antifreeze proteins were retrieved from UniProt
 database. The reference sequence of reverse gyrases were also retrieved
 from the UniProt Reviewed protein database. Genes encoding heat shock
 proteins were identified from a manually curated database, heat shock
 protein information resource (HSPIR). The proteins of interest were then
 identified using DIAMOND v2.1.9 based of the aforementioned
 databases. <em>Metagenome-assembled genome and
 metabolic pathway reconstruction</em>
 Co-assembled contigs of Illumina shotgun data and Nanopore data
 were used to construct MAGs using the binning tools MetaBAT2 v2.12.1,
 CONCOCT v1.0.0, and MaxBin2 v2.2.6  followed by the bin refinement
 & reassembly module of metaWRAP v1.3. The quality of the MAGs were
 assessed using CheckM v1.2.2. Taxonomic classification of the MAGs was
 performed using GTDB-tk v2.3.2 with the Genome Taxonomy Database (GTDB) as
 a reference. The phylogenetic trees of the MAGs were constructed using
 IQ-TREE v2.0.6 with default parameters  and using ModelFinder for
 substitution model selection. The phylogenetic trees generated were
 subsequently visualized via iTOL. The metabolic functional profiles of the
 MAGs are predicted using METABOLIC v4.0.  
description: ``` # Diversity, adaptation and metabolic potential of the microbiome in
 biofilms from a high-temperature hot spring
 https://doi:10.5061/dryad.sn02v6xcd Raw reads for amplicon and shotgun
 sequencing data are publicly available in NCBI with BioProject number
 PRJNA1082868 and BioSample accessions SAMN40219291 and SAMN40219292. The
 contigs for medium- and high-quality metagenome-assembled genomes (MAGs)
 are available in this open-access repository Dryad platform. This dataset
 are the MAGs fasta files of a biofilm found in a hot spring. ##
 Description of the data and file structure The MAGs information can be
 used as part of microbiology and bioinformatic analyses. This may include
 genome-to-genome comparison between individual MAG with closely related
 MAG or cultured microbial genomes. The fasta files can be used for
 phylogenetic tree construction. Besides, the files have ample of genes
 sequences suitable for gene mining.There is no missing data codes. The
 files are named from bin.1.XXX.fa to bin.61.XXX.fa, in which XXX could be
 orig, strict, or permissive, a short-note (designation) generated by
 metaWRAP that describe the approach for binning process. Please refer to
 metaWRAP (https://github.com/bxlab/metaWRAP) to understand the
 differences. The phyla or the affiliation for each MAGs is not provided in
 this dataset. Users who are interested may read the related published
 article. ## Sharing/Access information Raw reads for amplicon and shotgun
 sequencing data are publicly available in NCBI with BioProject number
 PRJNA1082868 and BioSample accessions SAMN40219291 and SAMN40219292. Links
 to other publicly accessible locations of the data:
 https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1082868 ##
 Code/Software No special code was used for this work.Standard procedure
 was made accordance to the steps provided in this link:
 https://github.com/bxlab/metaWRAP ```