Recent genomic data has revealed multiple interactions between Neandertals and humans, but there is currently little genetic evidence about Neandertal behavior, diet, or health. We shotgun sequenced ancient DNA from five Neandertal dental calculus specimens to characterize regional differences in Neandertal ecology. At Spy, Belgium, Neandertal diet was heavily meat based, and included woolly rhinoceros and wild sheep-animals characteristic of a steppe environment. In El Sidrón, Spain, no meat was detected in the dental calculus, but dietary components including mushrooms, pine nuts, and moss reflected forest gathering. Differences in diet were also linked to an overall shift in the oral bacterial community (microbiota) in Neandertals, suggesting that meat consumption contributed to significant variation between Neandertal microbiota. Evidence for self-medication was identified in one El Sidrón Neandertal with a dental abscess, who also likely suffered from a chronic gastrointestinal pathogen (Enterocytozoon bieneusi). Lastly, we characterized a nearly complete genome of the archaeal commensal Methanobrevibacter oralis in Neandertals-the oldest draft microbial genome generated to date at ~48,000 years old (10.2 depth). DNA preserved within dental calculus represents an important new resource of behavioral and health information for ancient hominid specimens, as well as a unique long-term study system for microbial evolution.

Bacteria are not only ubiquitous on earth but can also be incredibly diverse within clean laboratories and reagents. The presence of both living and dead bacteria in laboratory environments and reagents is especially problematic when examining samples with low endogenous content (e.g., skin swabs, tissue biopsies, ice, water, degraded forensic samples or ancient material), where contaminants can outnumber endogenous microorganisms within samples. The contribution of contaminants within high‐throughput studies remains poorly understood because of the relatively low number of contaminant surveys. Here, we examined 144 negative control samples (extraction blank and no‐template amplification controls) collected in both typical molecular laboratories and an ultraclean ancient DNA laboratory over 5 years to characterize long‐term contaminant diversity. We additionally compared the contaminant content within a home‐made silica‐based extraction method, commonly used to analyse low endogenous content samples, with a widely used commercial DNA extraction kit. The contaminant taxonomic profile of the ultraclean ancient DNA laboratory was unique compared to modern molecular biology laboratories, and changed over time according to researcher, month and season. The commercial kit also contained higher microbial diversity and several human‐associated taxa in comparison to the home‐made silica extraction protocol. We recommend a minimum of two strategies to reduce the impacts of laboratory contaminants within low‐biomass metagenomic studies: (a) extraction blank controls should be included and sequenced with every batch of extractions and (b) the contributions of laboratory contamination should be assessed and reported in each high‐throughput metagenomic study.

17Bacteria are not only ubiquitous on earth but can also be incredibly diverse 18 within clean laboratories and reagents. The presence of both living and dead bacteria 19 in laboratory environments and reagents is especially problematic when examining 20 samples with low endogenous content (e.g. skin swabs, tissue biopsies, ice, water, 21 degraded forensic samples, or ancient material), where contaminants can outnumber 22 endogenous microorganisms within samples. The contribution of contaminants within 23 high-throughput studies remains poorly understood because of the relatively low 24 number of contaminant surveys. Here, we examined 144 negative control samples 25 (extraction blank and no-template amplification controls) collected in both typical 26 molecular laboratories and an ultraclean ancient DNA laboratory over five years to 27 characterize long-term contaminant diversity. We additionally compared the 28 contaminant content within a homemade silica-based extraction method, commonly 29 used to analyse low-endogenous samples, with a widely used commercial DNA 30 extraction kit. The contaminant taxonomic profile of the ultraclean ancient DNA 31 laboratory was unique compared to the modern molecular biology laboratories, and 32 changed over time according to researchers, month, and season. The commercial kit 33 contained higher microbial diversity and several human-associated taxa in comparison 34to the homemade silica extraction protocol. We recommend a minimum of two 35 strategies to reduce the impacts of laboratory contaminants within low-biomass 36 metagenomic studies: 1) extraction blank controls should be included and sequenced 37 with every batch of extractions and 2) the contributions of laboratory contamination 38 should be assessed and reported in each high-throughput metagenomic study. 39 3 Main Text: 40In the new era of culture-independent microbiome research, targeted amplicon 41 or 'metabarcoding' approaches are now routinely used to amplify DNA from 42 microbial species across the tree of life. However, these methods lack the ability to 43 select for either specific species or to exclude contaminants [1]. Although these 44 techniques have provided invaluable insight into otherwise cryptic microbial 45 communities, the increased sensitivity and lack of target specificity leaves microbiota 46 studies particularly susceptible to the effects of contamination. Such effects are 47 widespread, as several recent studies have indicated that contaminant microbial DNA 48 can be routinely isolated from laboratory reagents and surfaces [2][3][4] and that this 49 signal has significantly impacted the interpretation and characterization of microbiota 50 in high-throughput sequencing studies. For example, Salter et al. recently 51 demonstrated that bacterial DNA present in laboratory reagents is present in both 52 quality-filtered 16S ribosomal RNA (rRNA) gene and shotgun metagenomic datasets 53 and significantly impacts the interpretation of results [3]. Multiple microbial 54

We used 15 short tandem repeat (STR) loci (D8S1179, D21S11, D7S820, CSF1PO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, VWA, TPOX, D18S51, D5S818, and FGA) to genetically characterize 361 individuals from 11 indigenous populations (Amuzgo, Chinanteco, Chontal, Huave, Mazateco, Mixe, Mixteco, Triqui, Zapoteco del Istmo, Zapoteco del Valle, and Zoque) from Oaxaca, Mexico. We also used previously published data from other Mexican peoples (Maya, Chol, Tepehua, Otomí, and Mestizos from northern and central Mexico) to delineate genetic relations, for a total of 541 individuals. Average heterozygosity (H) was lower in most populations from Oaxaca (range 0.687 in Zoque to 0.756 in Chontal) than values observed in Mestizo populations from Mexico (0.758 and 0.793 in central and northern Mestizo, respectively) but higher than values observed in other Amerindian populations from South America; the same relation was true for the number of alleles (n(a) ). We tested (using the software Structure) whether major geographic or linguistic barriers to gene flow existed among the populations of Oaxaca and found that the populations appeared to constitute one or two genetic groups, suggesting that neither geographic location nor linguistics had an effect on the genetic structure of these culturally and linguistically highly diverse indigenous peoples. Moreover, we found a low but statistically significant between-population differentiation. In addition, the genetic structure of Oaxacan populations did not fit an isolation-by-distance model. Finally, using AMOVA and a Bayesian clustering approach, we did not detect significant geographic or linguistic barriers to gene flow within Oaxaca. These results suggest that the indigenous communities of Oaxaca, although culturally isolated, can be genetically defined as a large, nearly panmictic population in which migration could be a more important population mechanism than genetic drift. Finally, compared with outgroups in Mexico (both indigenous peoples and Mestizos), three groups were apparent. Among them, only the Otomí population from Hidalgo has a different culture and language.