Diagenesis of archaeological bone and tooth

An understanding of the structural complexity of mineralised tissues is fundamental for exploration into the field of diagenesis. Here we review aspects of current and past research on bone and tooth diagenesis using the most comprehensive collection of literature on diagenesis to date. Environmental factors such as soil pH, soil hydrology and ambient temperature, which influence the preservation of skeletal tissues are assessed, while the different diagenetic pathways such as microbial degradation, loss of organics, mineral changes, and DNA degradation are surveyed. Fluctuating water levels in and around the bone is the most harmful for preservation and lead to rapid skeletal destruction. Diagenetic mechanisms are found to work in conjunction with each other, altering the biogenic composition of skeletal material. This illustrates that researchers must examine multiple diagenetic pathways to fully understand the post-mortem interactions of archaeological skeletal material and the burial environment

Microbial Metagenomics : A Tale of the Dead and the Living

It is a microbial world we live in: microbes outnumber other organisms by several orders of magnitude, and they have great importance for the environment. However, environmental microbes are notoriously difficult to grow in the laboratory, and using culture independent techniques is necessary to expand our view. In this thesis, I apply metagenomics and single-cell genomics to environmental samples from ancient human remains and lakes. First, I used metagenomics to learn about bacteria from a Neanderthal’s bone and the gut of Ötzi, a frozen natural mummy. Both were exploratory studies where the main question was what kind of bacteria are present. I found out that Streptomyces dominated this particular Neanderthal fossil, and the DNA lacked the damage that is often seen in ancient samples. Ötzi's gut sample was dominated by Clostridia and fungi belonging to Basidiomycota. Second, ten single-cell amplified genomes of freshwater Alphaproteobacterium LD12 and three metagenomes from Swedish lakes were sequenced. Comparative metagenomics allowed hypothesizing about which functions are important for microbe proliferation in freshwater, pointing to osmoregulation and transport proteins and, possibly, to different strategies of metabolizing sugars. I also focused on SAR11 sister-groups in oceans and lakes. Phylogenies and sequence evolutionary distance estimates indicated the existence of microclusters within LD12, showing variation in abundance between lakes. The most striking difference was the relative amount of recombination compared to mutation, the estimated r/m ratio. SAR11 marine and their freshwater cousins are found at the opposite extremes of the r/m range, lowest and highest, respectively. The genetic background or sequence diversity did not explain the observed dramatic difference, so it is possibly connected to environmental adaptation or population dynamics. In addition, I have spent a substantial amount of effort benchmarking available metagenomic methods, for example fragment recruitment of metagenomes to reference genomes. In conclusion, my exploratory metagenomic studies have shed some light on the bacteria present in ancient human remains; comparative metagenomics has suggested the importance of substrate preference on functional differences between lakes and oceans; finally, single-cell genomes have allowed some insight into molecular evolutionary processes taking place in the freshwater LD12 bacterium.

Substitution patterns in the Neanderthal and <i>Streptomyces</i> rRNA genes.

<p>Substitution frequencies inferred from the (A) Neanderthal and (B) Streptomyces small and large subunit rRNA gene contigs. Complementary substitutions ratios are reported together giving six groups in total. Vertical bars indicate the estimated level of sequencing errors. Coverage of sequence reads for the (C, D) small subunit and (E, F) large subunit rRNA gene sequences from (C, E) Metazoa and (D, F) Streptomycetales.</p

Schematic overview of the analysis workflow.

<p>Schematic overview of the analysis workflow.</p

Phylogeny of rRNA gene sequences.

<p>The longest rRNA consensus sequence assembled from the Neanderthal data and assigned to Streptmycetales is shown in red (SSU_Streptomycetales C11). The rRNA gene sequences amplified from the cave sediment are shown in green colour. <i>Streptomyces coelicolor</i>, used as a reference in the alignment is shown in blue. The PCR-amplified sequences from the cave sediment are shown in green. “ACT primers clone A5_G07” refer to amplifications with the actinobacterial-specific primers, while the four sequences obtained from the universal primers 27f and 1492r are referred to as “universal primers clone u2_C02, 05, 08 and 09″. The phylogeny was inferred using the maximum likelihood method. Numbers refer to bootstrap support values higher than 75%.</p

Phylogeny of microbial collagenases.

<p>Collagenase consensus sequences are coloured in red (Contigs 108, 111–113). The actinobacterial clade is highlighted in yellow and subfamilies M09A and B are indicated. The <i>Streptomyces</i> reference sequences from the MEROPS M09 family are shown in green and the family holotypes in blue. MEROPS references displayed with species names and (arbitrary) collagenase copy number. The phylogeny was inferred using the maximum likelihood method. Numbers refer to bootstrap support values higher than 75%.</p

Phylogeny of prolyl aminopeptidases.

<p>Propyl aminopeptidase consensus sequences are coloured red (Contigs C1103–C1106). The clade containing contig C1104 and two <i>Streptomyces</i> species is shown in yellow. The <i>Streptomyces</i> reference sequences from MEROPS S33 family are shown in green and family holotypes in blue. MEROPS id is indicated for each sequence. The phylogeny was inferred using the maximum likelihood method. Numbers refer to bootstrap support values higher than 75%.</p