Insights into microbial evolution and ecology from genetic analysis of diverse archaeological materials

Medientyp: E-Book; Hochschulschrift

Titel: Insights into microbial evolution and ecology from genetic analysis of diverse archaeological materials

Beteiligte: Sabin, Susanna [VerfasserIn]; Krause, Johannes [AkademischeR BetreuerIn]; Warinner, Christina [AkademischeR BetreuerIn]; Comas, Inaki [AkademischeR BetreuerIn]

Körperschaft: Friedrich-Schiller-Universität Jena

Erschienen: Jena, [2019?]

Umfang: 1 Online-Ressource (172 Seiten); Illustrationen, Diagramme; 30 cm

Sprache: Englisch

DOI: 10.22032/dbt.40574

Identifikator:

Schlagwörter: Genom > Archäologische Stätte > Befund > Mikroorganismus > Gesundheit

Entstehung:

Hochschulschrift: Dissertation, Friedrich-Schiller-Universität Jena, 2019

Anmerkungen: Kumulative Dissertation, enthält Zeitschriftenaufsätze
Tag der Verteidigung: 01.11.2019
Zusammenfassungen in deutscher und englischer Sprache

Beschreibung: The study of human health over time offers valuable pathways for understanding multiple aspects of human experience and biology. Determining the presence of a disease in an ancient individual or community can give us insights into daily life during that time, and comparing human microbiota between different human groups over time and space can offer insights into behavior and diet. Assessing the health of past populations may provide new perspectives on concomitant social or political changes, and contribute to our understanding of how those populations managed, or failed to manage, crises and change. On a broader level, identifying and interrogating humanity’s relationship with infectious and commensal microbes may offer insights into human evolution and adaptation. Most hopefully, the knowledge gained from the basic science of past human health may one day lead to discoveries that can be applied to modern medicine. For example, the evolutionary history of a specific pathogen may allow us to understand how it may behave in the future, and the constitution of ancient human microbiota may allow us to interrogate what taxa have been gained and lost over time in certain populations and what this may mean for modern oral and gut health. The study of past human health has always, by necessity, been an interdisciplinary endeavor. The task of diagnosis, difficult in living populations, becomes increasingly complicated with the passage of time, and the meaning and value of historical diagnosis, depending on the theoretical tides among medical historians, modern clinicians, and anthropologists, may fluctuate (Arrizabalaga, 2002; Waldron, 2009). Historical documentation or art pieces may offer verbal descriptions or visual depictions of ill health, but may be open to broad interpretation due to differing medical conventions and terminology over time and space, embellishment of the artist, or even political concerns that may or may not be evident to the scholar attempting a diagnosis (Mitchell, 2011). Health can also be inferred from human remains in archaeological contexts or the archaeological contexts themselves. Mass graves or multiple burials, for example, could signal an epidemic event (Blakely and Detweiler-Blakely, 1989; Rugg, 2000). Disease processes can leave traces in surviving soft tissue in the case of mummified individuals or in hard tissue, and as human remains that survive in the archaeological record are mostly skeletonized, bone tends to be the most common medium from which paleopathologists attempt to diagnose deceased, archaeological individuals. However, pathological changes in bone are not always specific to a single condition or infection, and not all conditions and infections leave signs in the Introduction 5 skeleton. For those conditions that can leave signs in the skeleton, whether or not this occurs depends on numerous factors, such as, for example, the immunocompetency of the individual or the severity of the infection. Even in the event that there are pathognomonic signs of a specific infection identified in a skeletonized individual, that information cannot be used to infer evolutionary dynamics of the infecting organism.

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