Disciplines
Anthropology | Archaeological Anthropology | Bioinformatics | Biological and Physical Anthropology | Genetics and Genomics | Genomics | Life Sciences | Microbiology | Social and Behavioral Sciences
Abstract (300 words maximum)
This interdisciplinary study aimed to compare screening methods for detection of Mycobacterium tuberculosis complex (MTBC) and examine the suitability of these bioinformatics pipelines in anthropological studies. This study analyzes skeletal samples from 28 Polish individuals in the Neolithic period under PRJNA422903 from the Sequence Read Archive (SRA). These individuals showed bone lesions that are consistent with tuberculosis. Identification of pathogens from complex samples relies heavily on methods in bioinformatics after next-generation sequencing (NGS). Environmental contamination and spurious identification of pathogens based on fragmentary data are some of the drawbacks of NGS screening methods that can lead to incorrect epidemiological conclusions. The importance of analytical tools that can provide less ambiguous answers to questions of identification and differentiation of bacteria from the MTBC in ancient data cannot be downplayed. After adapter trimming with Trim Galore!, Kraken2 was used for taxonomic classification with custom-built databases for this study. Our methods revealed additional species of MTBC and Mycobacterium avium complex (MAC) that were previously unreported by the originator of this dataset, including Mycobacterium tuberculosis XDR1219 and Mycobacterium avium hominissuis. Our established bioinformatics pipeline has therefore been more effective than previously published screening methods and it is suitable for other studies in anthropology and paleopathology using NGS technologies.
Academic department under which the project should be listed
CSM - Molecular and Cellular Biology
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Primary Investigator (PI) Name
Tsai-Tien Tseng
Comparing Screening Methods for Detection of Mycobacterium Tuberculosis Complex in Ancient Skeletal Samples
This interdisciplinary study aimed to compare screening methods for detection of Mycobacterium tuberculosis complex (MTBC) and examine the suitability of these bioinformatics pipelines in anthropological studies. This study analyzes skeletal samples from 28 Polish individuals in the Neolithic period under PRJNA422903 from the Sequence Read Archive (SRA). These individuals showed bone lesions that are consistent with tuberculosis. Identification of pathogens from complex samples relies heavily on methods in bioinformatics after next-generation sequencing (NGS). Environmental contamination and spurious identification of pathogens based on fragmentary data are some of the drawbacks of NGS screening methods that can lead to incorrect epidemiological conclusions. The importance of analytical tools that can provide less ambiguous answers to questions of identification and differentiation of bacteria from the MTBC in ancient data cannot be downplayed. After adapter trimming with Trim Galore!, Kraken2 was used for taxonomic classification with custom-built databases for this study. Our methods revealed additional species of MTBC and Mycobacterium avium complex (MAC) that were previously unreported by the originator of this dataset, including Mycobacterium tuberculosis XDR1219 and Mycobacterium avium hominissuis. Our established bioinformatics pipeline has therefore been more effective than previously published screening methods and it is suitable for other studies in anthropology and paleopathology using NGS technologies.