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Background In 1975, the mummified body of a female has been found in the Franciscan church in Basel, Switzerland. Molecular and genealogic analyses unveiled her identity as Anna Catharina Bischoff (ACB), a member of the upper class of post-reformed Basel, who died at the age of 68 years, in 1787. The reason behind her death is still a mystery, especially that toxicological analyses revealed high levels of mercury, a common treatment against infections at that time, in different body organs. The computed tomography (CT) and histological analysis showed bone lesions in the femurs, the rib cage, and the skull, which refers to a potential syphilis case. Results Although we could not detect any molecular signs of the syphilis-causing pathogen Treponema pallidum subsp. pallidum, we realized high prevalence of a nontuberculous mycobacterium (NTM) species in brain tissue sample. The genome analysis of this NTM displayed richness of virulence genes and toxins, and similarity to other infectious NTM, known to infect immunocompromised patients. In addition, it displayed potential resistance to mercury compounds, which might indicate a selective advantage against the applied treatment. This suggests that ACB might have suffered from an atypical mycobacteriosis during her life, which could explain the mummy’s bone lesion and high mercury concentrations. Conclusions The study of this mummy exemplifies the importance of employing differential diagnostic approaches in paleopathological analysis, by combining classical anthropological, radiological, histological, and toxicological observations with molecular analysis. It represents a proof-of-concept for the discovery of not-yet-described ancient pathogens in well-preserved specimens, using de novo metagenomic assembly.

We applied ancient DNA methods to shed light on the origin of ancient Hungarians and their relation to modern populations. Hungarians moved into the Carpathian Basin from the Eurasian Pontic steppes in the year 895 AD as a confederation of seven tribes, but their further origin remains obscure. Here, we present 17 mtDNA haplotypes and four Y-chromosome haplogroups, which portray the genetic composition of an entire small cemetery of the first generation Hungarians. Using novel algorithms to compare these mitochondrial DNA haplogroups with other ancient and modern Eurasian data, we revealed that a significant portion of the Hungarians probably originated from a long ago consolidated gene pool in Central Asia-South Siberia, which still persists in modern Hungarians. Another genetic layer of the early Hungarians was obtained during their westward migrations by admixing with various populations of European origin, and an important component of these was derived from the Caucasus region. Most of the modern populations, which are genetically closest relatives of ancient Hungarians, today speak non-Indo-European languages. Our results contribute to our understanding of the peopling of Europe by providing ancient DNA data from a still genetically poorly studied period of medieval human migrations.

The Tyrolean Iceman, a Copper-age ice mummy, is one of the best-studied human individuals. While the genome of the Iceman has largely been decoded, tissue-specific proteomes have not yet been investigated. We studied the proteome of two distinct brain samples using gel-based and liquid chromatography-mass spectrometry-based proteomics technologies together with a multiple-databases and -search algorithms-driven data-analysis approach. Thereby, we identified a total of 502 different proteins. Of these, 41 proteins are known to be highly abundant in brain tissue and 9 are even specifically expressed in the brain. Furthermore, we found 10 proteins related to blood and coagulation. An enrichment analysis revealed a significant accumulation of proteins related to stress response and wound healing. Together with atomic force microscope scans, indicating clustered blood cells, our data reopens former discussions about a possible injury of the Iceman's head near the site where the tissue samples have been extracted.

Currently, one of the biggest challenges in microbial and ecosystem ecology is to develop conceptual models that organize the growing body of information on environmental microbiology into a clear mechanistic framework with a direct link to ecosystem processes. Doing so will enable development of testable hypotheses to better direct future research and increase understanding of key constraints on biogeochemical networks. Although the understanding of phenotypic and genotypic diversity of microorganisms in the environment is rapidly accumulating, how controls on microbial physiology ultimately affect biogeochemical fluxes remains poorly understood. We propose that insight into constraints on biogeochemical cycles can be achieved by a more rigorous evaluation of microbial community biomass composition within the context of ecological stoichiometry. Multiple recent studies have pointed to microbial biomass stoichiometry as an important determinant of when microorganisms retain or recycle mineral nutrients. We identify the relevant cellular components that most likely drive changes in microbial biomass stoichiometry by defining a conceptual model rooted in ecological stoichiometry. More importantly, we show how X-ray microanalysis (XRMA), nanoscale secondary ion mass spectroscopy (NanoSIMS), Raman microspectroscopy, and in situ hybridization techniques (for example, FISH) can be applied in concert to allow for direct empirical evaluation of the proposed conceptual framework. This approach links an important piece of the ecological literature, ecological stoichiometry, with the molecular front of the microbial revolution, in an attempt to provide new insight into how microbial physiology could constrain ecosystem processes.

Stoichiometry of microbial biomass is a key determinant of nutrient recycling in a wide variety of ecosystems. However, little is known about the underlying causes of variance in microbial biomass stoichiometry. This is primarily because of technological constraints limiting the analysis of macromolecular composition to large quantities of microbial biomass. Here, we use Raman microspectroscopy (MS), to analyze the macromolecular composition of single cells of two species of bacteria grown on minimal media over a wide range of resource stoichiometry. We show that macromolecular composition, determined from a subset of identified peaks within the Raman spectra, was consistent with macromolecular composition determined using traditional analytical methods. In addition, macromolecular composition determined by Raman MS correlated with total biomass stoichiometry, indicating that analysis with Raman MS included a large proportion of a cell's total macromolecular composition. Growth phase (logarithmic or stationary), resource stoichiometry and species identity each influenced each organism's macromolecular composition and thus biomass stoichiometry. Interestingly, the least variable peaks in the Raman spectra were those responsible for differentiation between species, suggesting a phylogenetically specific cellular architecture. As Raman MS has been previously shown to be applicable to cells sampled directly from complex environments, our results suggest Raman MS is an extremely useful application for evaluating the biomass stoichiometry of environmental microorganisms. This includes the ability to partition microbial biomass into its constituent macromolecules and increase our understanding of how microorganisms in the environment respond to resource heterogeneity.