Project description:Ivory is a highly prized material in many cultures since it can be carved into intricated designs and have a highly polished surface. Due to its popularity, the animals from which ivory can be sourced have started to come under threat. Identification of the ivory species is not only important for compliance with the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), it can also provide important information about the context in which the work was created. In this work, we have developed a minimally invasive workflow to remove minimal amounts of material from precious objects, and, using high-resolution mass spectrometry-based proteomics, identified the taxonomy of several ivory and bone objects from the collection of The Metropolitan Museum of Art dating from as early as 4000 B.C. We built an inhouse proteomic databases of underrepresented species based on exemplars obtained from the Mammology American Museum of Natural History collection and proposed alternative data analysis workflows for rare samples containing sparse and inconsistently preserved organic material. This is a first application demonstrating extensive and accurate ivory species identification using proteomics to unlock sequence uncertainties, e.g. Leu/Ile-discrimination.
Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.
Project description:Metagenome sequencing All specimens were collected and immediately stored in a -80 freezer. All BALF samples were subjected to MS. DNA was extracted from BALF using the TIANamp Micro DNA kit (DP316, Tiangen Biotech). DNA libraries were constructed with the end-repair method and then sequenced on the BGI Sequencer platform (BGI Genomics, Shenzhen, China). Bioinformatic pipeline analysis Low-quality and short (<35 bp) reads were removed from raw data using fastp [10]. Remaining reads were mapped to the human reference genome (hg19) using the Burrows-Wheeler method to remove sequences of human origin. Filtered reads were classified with RefSeq, downloaded from NCBI (ftp://ftp.ncbi.nlm.nih.gov/genomes/).
Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.
