Hallstatt miners consumed blue cheese and beer
during the Iron Age and retained a non-Westernized
gut microbiome until the Baroque period
dGut microbiome and diet of European salt miners determined
dUntil the Baroque, the microbiome resembled that of modern
dFood-fermenting fungi in Iron Age feces indicates blue
cheese and beer consumption
Frank Maixner, Mohamed S. Sarhan,
Kun D. Huang, ..., Albert Zink,
Hans Reschreiter, Kerstin Kowarik
Maixner et al. describe the gut
microbiome and diet of European salt
miners using paleofeces dating from the
Bronze Age to the Baroque period. This
analysis provides evidence for recent
changes in the gut microbiome due to
industrialization and for the consumption
of fermented food and beverages in Iron
2200 1000 15
400 1000 1492 Present
Sex and mt
Maixner et al., 2021, Current Biology 31, 1–14
December 6, 2021 ª2021 The Authors. Published by Elsevier Inc.
Hallstatt miners consumed blue cheese and beer
during the Iron Age and retained a non-Westernized
gut microbiome until the Baroque period
*Mohamed S. Sarhan,
Kun D. Huang,
Seamus R. Morrone,
Michael R. Hoopmann,
Robert L. Moritz,
and Kerstin Kowarik
Institute for Mummy Studies, EURAC Research, Viale Druso 1, 39100 Bolzano, Italy
Department CIBIO, University of Trento, Via Sommarive 9, 38123 Povo (Trento), Italy
Department of Sustainable Agro-Ecosystems and Bioresources, Fondazione Edmund Mach, Via Edmund Mach 1, 38010 San Michele
all’Adige (TN), Italy
CUBE (Division of Computational Systems Biology), Centre for Microbiology and Environmental Systems Science, University of Vienna,
Althanstraße 14, 1090 Vienna, Austria
Institute of Botany, University of Innsbruck, Sternwartestraße 15, 6020 Innsbruck, Austria
Interfaculty Department of Legal Medicine & Department of Classics, University of Salzburg, Ignaz-Harrer-Straße 79, 5020 Salzburg, Austria
Reiss-Engelhorn-Museen, Zeughaus C5, 68159 Mannheim, Germany
aomtrie, D6,3, 61859 Mannheim, Germany
Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109, USA
Center Agriculture Food Environment (C3A), University of Trento, 38010 San Michele all’Adige (TN), Italy
Prehistoric Department, Museum of Natural History Vienna, Burgring 7, 1010 Vienna, Austria
These authors contributed equally
*Correspondence: firstname.lastname@example.org (F.M.), email@example.com (K.K.)
We subjected human paleofeces dating from the Bronze Age to the Baroque period (18
century AD) to in-
depth microscopic, metagenomic, and proteomic analyses. The paleofeces were preserved in the under-
ground salt mines of the UNESCO World Heritage site of Hallstatt in Austria. This allowed us to reconstruct
the diet of the former population and gain insights into their ancient gut microbiome composition. Our dietary
survey identiﬁed bran and glumes of different cereals as some of the most prevalent plant fragments. This
highly ﬁbrous, carbohydrate-rich diet was supplemented with proteins from broad beans and occasionally
with fruits, nuts, or animal food products. Due to these traditional dietary habits, all ancient miners up to
the Baroque period have gut microbiome structures akin to modern non-Westernized individuals whose diets
are also mainly composed of unprocessed foods and fresh fruits and vegetables. This may indicate a shift in
the gut community composition of modern Westernized populations due to quite recent dietary and lifestyle
changes. When we extended our microbial survey to fungi present in the paleofeces, in one of the Iron Age
samples, we observed a high abundance of Penicillium roqueforti and Saccharomyces cerevisiae DNA.
Genome-wide analysis indicates that both fungi were involved in food fermentation and provides the ﬁrst mo-
lecular evidence for blue cheese and beer consumption in Iron Age Europe.
Paleofeces are naturally preserved ancient feces found in dry
caves, desert areas, waterlogged environments, and frozen hab-
itats. Speciﬁc environmental processes such as desiccation or
freezing prevent their deterioration in mummies, ancient latrines,
bogs, and soils.
Previous studies have shown that paleofecal
material still contains plant macro- and microfossils, parasite
eggs, and even ancient biomolecules (DNA, proteins, metabo-
Ancient paleofeces have therefore recently been used
as a source of information to study prehistoric nutrition pat-
and to analyze single representatives
or the overall composition of the intestinal microbiome of our an-
One of the few archaeological sites where well-preserved
paleofeces can be found is the protohistoric salt mines of the
Current Biology 31, 1–14, December 6, 2021 ª2021 The Authors. Published by Elsevier Inc. 1
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Please cite this article in press as: Maixner et al., Hallstatt miners consumed blue cheese and beer during the Iron Age and retained a non-Westernized
gut microbiome until the Baroque period, Current Biology (2021), https://doi.org/10.1016/j.cub.2021.09.031
Austrian UNESCO World Heritage area Hallstatt-Dachstein/Sal-
zkammergut. Protohistoric salt mines offer ideal preservation
conditions for organic materials. The high salt concentrations
and the constant annual temperature of around 8C inside the
isolated mine workings preserve organic artifacts very well.
The Hallstatt salt mines located in the Eastern Alps (Figure 1)
offer one of the world’s oldest and most continuous record of un-
derground salt mining.
Large-scale underground mining in
the Hallstatt salt mountains dates back at least to the 14
tury BC (late Bronze Age). Several protohistoric (Bronze, Iron
Age) and historic (14
century AD to present) mining phases
are well documented. The site also gave name to the early period
of the Iron Age in Europe, the so-called Hallstatt Period (800 to
400 BC). Dense layers of production waste reaching several
meters of thickness were excavated from the protohistoric
Bronze Age and Iron Age mine workings of Hallstatt, uncovering
thousands of wooden tools and construction elements, imple-
ments made from fur, rawhide, hundreds of woolen textile frag-
ments, grass, bast ropes, and human excrements.
jects provide insights into the daily life of a Bronze Age and
Iron Age mining community ranging from mining technology, or-
ganization of production, and resource management to human
health, dietary habits, social organization of production pro-
cesses, and social status within a mining system. These aspects
have been studied extensively in Hallstatt based on a combina-
tion of data sources encompassing the protohistoric mine work-
ing, Bronze Age meat-curing facilities, and large Iron Age
Early Iron Age
2610 2604 2611 2612
1301-1121 cal BC
650-545 cal BC
652-544 cal BC
1720-1783 cal AD
Figure 1. The Hallstatt salt mine and radiocarbon-dated paleofeces samples used in this study
(A) The salt mines are located in Upper Austria.
(B) Finding sites of the four paleofeces samples in the Bronze Age, Iron Age, and Baro que mining area. The symbol color corresponds to the radiocarbon date of
(C) Macroscopic appearance of the four paleofeces samples. The scale bar corresponds to 1 cm of length. The sample description includes the sample ID, the
mine workings name, and the radiocarbon date. The provided radiocarbon date range corresponds to the Cal 2-sigma values with the highest probability.
(D) Temporal assignment of the radiocarbon-dated paleofeces to the major European time periods from the Bronze Age onward.
See also Figure S1 for details of the salt crystals surrounding sample 2612. Data S1A and S1B provide additional information about the samples and the
2Current Biology 31, 1–14, December 6, 2021
Please cite this article in press as: Maixner et al., Hallstatt miners consumed blue cheese and beer during the Iron Age and retained a non-Westernized
gut microbiome until the Baroque period, Current Biology (2021), https://doi.org/10.1016/j.cub.2021.09.031
Here we focus on the question of the structure and evolution of
dietary habits as well as the human gut microbiome in one of Eu-
rope’s most important early production communities. We used
microscopic, metagenomic, and proteomic analysis to charac-
terize nutrition patterns of the protohistoric (Bronze Age, early
Iron Age) and historic (Baroque period, 18
century AD) miners
and metagenomic analysis to determine the structure and
evolution of the gut microbiome. Our ﬁndings will enhance the
understanding of early European dietary habits (especially the
production and consumption of processed foodstuffs) and pro-
vide further evidence of the recent change in gut microbiome
structure as result of industrialization and Westernization
Paleofeces from Bronze Age to Baroque Period contain
ancient endogenous DNA
In this study, we initially subjected four paleofeces samples,
collected from Bronze Age and Iron Age Hallstatt mine workings,
to radiocarbon dating, then to in-depth microscopic and molec-
ular analysis (Figures 1A–1C; STAR Methods;Data S1A). The
four paleofeces samples can be macroscopically differentiated
into three samples containing a high amount of ﬁbrous plant ma-
terial (2610, 2604, 2611) and one more homogeneous sample
(2612) that does not contain any visible larger plant fragments
(Figures 1 andS1A). Radiocarbon analyses date the roughly
structured samples to the Late Bronze Age (2610) and Iron Age
(2604, 2611), which is in perfect accordance with the proposed
period of usage of the mine workings where the paleofeces
have been found.
In contrast, the ﬁne-textured paleofeces
2612 sampled in an Iron Age minedates to the Baroque period
century AD) (Figure 1C; Data S1B). For this part of the salt
mine, however, it is historically documented that the mine work-
ings had started to be reused from the beginning of 18
Independently of the paleofeces’ age, their storage
time since excavation (some samples were recovered in the
year 1983), or the mode of excavation (wet sieving versus direct
sampling) (Figure S1), we could retrieve biomolecules (DNA and
protein) from all samples for the subsequent molecular analysis
(Data S1 and S2;STAR Methods). Proteomics analysis provided
the ﬁrst evidence for the presence of endogenous biomolecules
in the paleofeces material. The most abundant peptides were as-
signed to human intestinal tract proteins that are involved in food
digestive processes (Data S2B, S2D, S2F, and S2H). The DNA of
the paleofeces material was further subjected to a deep shotgun
sequencing approach resulting in 57,130,584 to 221,314,691
quality-ﬁltered reads (Data S1C). A ﬁrst taxonomic overview us-
ing DIAMOND against the NCBI NR database revealed that the
majority of reads in the samples are assigned to Bacteria
(93.9% to 78.9% of all assigned reads), with Firmicutes and Bac-
teroidetes being the most abundant phyla of this kingdom (Fig-
ures S2A–S2D). Less than 7.5% of the reads were eukaryotic,
with up to 6.7% fungal reads in sample 2604. The Metazoa
and Viridiplantae reads, important for the molecular reconstruc-
tion of the diet, comprised 0.5% to 0.01% of all assigned reads.
Further analysis of the human DNA in the paleofeces revealed an
endogenous DNA content between 0.26% and 0.06%, sufﬁcient
for molecular sex and mitochondrial haplogroup assignment
(Data S1D). The highly fragmented human reads display a very
low deamination pattern at the 50ends (Figures S2E–S2H). In
the most recent sample (2612), the reads appear even less frag-
mented and display almost no DNA damage. Considering the
age of these samples, the DNA damage is exceptionally low.
This high preservation is most likely due to the rapid desiccation
of the samples in the salt mine, which may result in reduced hy-
drolytic damage of the biomolecules. Our analyses show that the
four paleofeces come from male individuals that carry distinct
mitogenomes with low contamination estimates (1% to 2%),
indicating that each sample represents unique unmixed ancient
Ancient paleofeces display a gut microbiome structure
similar to modern non-Westernized individuals
We compared the microbiome structure of the paleofeces to a
large number of contemporary metagenomes (n = 823) (Data
S1E). Principal coordinate analysis (PCoA) performed on a spe-
cies-level taxonomic composition shows that the paleofeces
from the Bronze Age to the Baroque period cluster with stool
samples from contemporary non-Westernized individuals (Fig-
ure 2A) with diets mainly consisting of unprocessed foods and
fresh fruits and vegetables.
This clustering is similarly observed
for encoded metabolic pathways (Figure 2B). All the paleofecal
samples were distinct from the oral and, more importantly,
from the soil samples, suggesting little evidence of soil contam-
ination, which is sometimes observed in ancient metagenomics
The source prediction analysis further supports the
sample preservation (Data S1F).
To further assess the paleofeces samples, we analyzed the
prevalence of the top 15 most abundant species in the paleofe-
ces compared to 8,968 gut microbiomes of healthy Westernized
and non-Westernized adults (Data S1G). As a result, 13 out of the
15 most abundant species were identiﬁed to be associated with
human gut environment, of which 11 species were found to be
more prevalent in modern non-Westernized compared to West-
ernized populations. Five of these species, Biﬁdobacterium
angulatum,Lactobacillus ruminis,Catenibacterium mitsuokai,
Prevotella copri, and Clostridium ventriculi, were over twice as
prevalent in non-Westernized populations (Figure 2C; Data
S1H). One of the two species not associated with the human
gut is the halophilic archaeon Halococcus morrhuae, which sur-
vives on a high concentration of salt.
It was observed in low
abundance in the paleofeces sample 2612, the only sample
that was not subjected to wet sieving. Therefore, we assume
that the archaeon was introduced from the environment via the
salt crystals (Figure S1B). In the paleofeces samples 2604 and
2611, we also identiﬁed Clostridium perfringens, a known intes-
tinal foodborne pathogen,
that also occurs free living in the soil
and other environments.
Since an infection with C. perfringens
causes acute diarrhea and the paleofeces does not indicate any
characteristics pointing to that disease, we assume that the
presence of this bacterium is due to an environmental
contaminant rather than a remnant of food spoilage in the
miners’ gut. When all paleofecal microbiome members were
considered in population prevalence analysis, 100 out of
158 species were found in R5% stool samples from modern
healthy adult individuals and 65% of these species are overrep-
resented in non-Westernized populations in comparison with
Current Biology 31, 1–14, December 6, 2021 3
Please cite this article in press as: Maixner et al., Hallstatt miners consumed blue cheese and beer during the Iron Age and retained a non-Westernized
gut microbiome until the Baroque period, Current Biology (2021), https://doi.org/10.1016/j.cub.2021.09.031
the Westernized equivalent (Data S1I). A similar result was ob-
tained when we decreased the prevalence threshold to 1%
The Prevotella copri complex, which is highly prevalent in non-
Westernized populations and prevalent in previously investi-
gated ancient samples,
was identiﬁed in all paleofecal samples,
representing, on average, 7.3% (1.6%–14.7%) of the relative
abundance (Figure 2C; Data S1K). Consistent with previous ﬁnd-
we found multiple clades of the complex to be present in
each of the paleofeces samples (Figure 2D) with the exception
of Clade D, which was barely detectable in sample 2604
and 2612. All other clades were detected with relative abun-
dances > 0.01% in all samples (Figure 2D; Data S1L). Of note,
in contrast to other samples, the sample 2604 displayed higher
abundance of bacterial species such as Lactobacillus brevis,
Biﬁdobacterium merycicum,Biﬁdobacterium angulatum, and
Lactobacillus plantarum (Data S1K) that are known to be of pro-
biotic activities or involved in processing of dairy products.
Microscopic and molecular reconstruction of the
Hallstatt miners’ diet
Next, we aimed to reconstruct the dietary components in the pa-
leofeces using both a microscopic and a molecular survey. The
above-mentioned structural differences between the paleofeces
became even more evident in the microscopic analyses. The
Baroque period sample 2612 was much ﬁner textured than all
other samples from protohistory (Figure 1C). This was also re-
ﬂected in the macro-remain composition of the paleofeces,
showing that samples 2610, 2604, and 2611 contained a lot of
seeds contrary to 2612, which consisted of frequent tissues of
Relative abundance (%)
Oscillibacter sp. CAG241
Non-westernized (n = 725)
Westernized (n = 8243)
Relative abundance (%)
P. copri complex
0.10.0-0.1-0.2 0.30.2 0.5 0.60.4
-0.15 0.100.05-0.05 0.0-0.10-0.20 0.15
2610 2604 2611 2612
Figure 2. Overview of microbial composition and metabolic pathways of paleofeces samples in comparison to a large collection of contem-
(A) Principal coordinate analysis (PCoA) based on microbial abundance proﬁled using MetaPhlAn 3.0
between four paleofeces samples and 823 contemporary
samples characterized by sampling environment, body site, and non-Westernized lifestyle.
(B) Principal coordinate analysis (PCoA) based on metabolic pathway abundance proﬁled using HUMAnN 3.0
between four paleofeces samples and the same
contemporary samples used in (A).
(C) Prevalence of the top 15 most enriched species of four paleofeces samples in non-Westernized and Westernized datasets comprising 8,968 stool samples
from healthy adult individuals. Asterisk indicates species that is likely from external contamination.
(D) Relative abundance of P. copri four clades estimated using MetaPhlAn 3.0
in each paleofecal sample.
See also Figure S1 for additional microbial proﬁles in the DNA ‘‘wash-out’’ experiment. Data S1 contains additional information about the comparative datasets
and the results obtained by the prevalence and abundance analysis.
4Current Biology 31, 1–14, December 6, 2021
Triticum aestivum cultivar CS TA3008, KJ614396.1
Triticum turgidum subsp. durum, KJ614398.1
Triticum aestivum subsp. macha, LC005978.1
Triticum turgidum subsp. dicoccoides, KJ614400.1
Triticum aestivum subsp. spelta, KJ614403.1
Aegilops speltoides var. ligustica, KJ614404.1
Triticum timopheevii subsp. timopheevii, KJ614410.1
Secale cereale, KC912691.1
0% 20% 40% 60% 80% 100%
Number of peptides
Figure 3. Microscopic and molecular dietary analysis of the Hallstatt paleofeces
(A) Plant macro-remains microscopically detected in the four paleofeces samples. The scale bar indicates 1 mm of length. The heatmap shows the log-scale
macro-remain counts normalized to 3.7 g sample. The sample with asterisk was assessed in a semiquantitative manner. For further details, please referto
(B) Most abundant taxa (plants, nematodes, animals, fungi) detected in the four paleofeces metagenomes and proteomes. The circle size and circle color
correspond to log10 ‘‘normalized’’ number of reads per million at genus and species levels, respectively. The asterisks in the proteome heatmap mean the
peptides were assigned only to genus level.
(C) Phylogenetic assignment of two partial Triticum chloroplast genomes in the 2604 and 2610 metagenomes. The comparative dataset included
complete chloroplast genomes of selected members of the Triticeae tribe (NCBI accession numbers are provided in the ﬁgure). The tree was
calculated using the maximum-likelihood algorithm (PhyML) based on 136,160 informative positions. Black circles symbolize parsimony and
neighbor joining bootstrap support (>90%) based on 100 and 1,000 iterations, respectively. The scale bar indicates 10% estimated sequence
(legend continued on next page)
Current Biology 31, 1–14, December 6, 2021 5
fruit husks and seed coats (Figure 3A; Data S1M). Generally, all
samples displayed a predominance of cereal remains.
Microscopic analysis revealed that the Bronze Age sample
(2610) consisted more or less exclusively of cereal remains,
which originated from barley (Hordeum vulgare), spelt (Triticum
spelta), some emmer (Triticum dicoccum), proso millet (Panicum
miliaceum), and a few weeds, e.g., corn cockle (Agrostemma gi-
thago) and poison parsley (Aethusa cynapium). The Iron Age
samples (2604, 2611) were characterized by a predominance
of cereal remains from barley (Hordeum vulgare), spelt (Triticum
spelta), millets (P. miliaceum,Setaria italica), and a little emmer
(T. dicoccum). Furthermore, in sample 2611, testa remains of
broad beans (Vicia faba) and seeds of opium poppies (Papaver
somniferum) were observed. Crab apples (Malus sylvestris) and
bilberries/cranberries (Vaccinium myrtillus/vitis-idea) in sample
2604 document the consumption of gathered wild fruits. Striking
in the Iron Age sample 2604 was the contamination with weeds,
in particular corn cockle (Agrostemma githago). In the sample
2612 from the Baroque time, the microscopic pattern was
notably different from the other samples. The plant material
was ﬁnely ground, and entire fruits were missing apart from a di-
gested mericarp of anise (Pimpinella anisum). The plant tissue
belonged to bran (fragments of cereal testa, pericarp, hairs, hi-
lum, endosperm) of wheat (Triticum sp.). The precise species
was unidentiﬁable, but according to the rare occurrence of
tube cells in the pericarp fragments, a member of the tetra- or
hexaploid wheat group is suggested. Bran of barley
(H. vulgare) was also observed in minor quantities. Furthermore,
the consumption of legumes is documented by testa remains of
garden bean (Phaseolus vulgare) in this sample.
In addition to the microscopic analysis, we subjected paleofe-
ces biomolecules (DNA and proteins) to molecular dietary ana-
lyses. Both metagenomic and proteomic analyses included a
homology search against different databases, followed by
strict ﬁltering steps of the obtained hits and a subsequent in-
depth analysis of selected identiﬁed taxa (STAR Methods;Fig-
ure S3;Data S1N, S1O, S2B, S2D, S2F, and S2H). For the plant
diet, we could conﬁrm the presence of the most abundant
domesticated plant macro-remains, including broomcorn millet
(P. milliaceum), barley (H. vulgare), and wheat (Triticum spp.)
(Figure 3B). In addition, we found DNA-based evidence of the
presence of walnut (Juglans regia) in the sample 2604 and pro-
tein-based support for the occurrence of opium poppy seeds
(P. somniferum) in the sample 2611. In addition to the foxtail mil-
let (S. italica), which appeared with high grain number, all the low
abundant wild plants unveiled by the microscopic investigation
were not identiﬁed in our molecular survey, which has undergone
strict ﬁltering to minimize the false positives (STAR Methods).
Further phylogenetic analysis assigned the Triticum spp. chloro-
plast genomes of the samples 2604 and 2610 closest to the
chloroplasts of tetraploid (emmer, durum) and hexaploid (spelt
wheat, bread wheat) wheat varieties, respectively (Figures 3C,
S3A, and S3B; Data S1P). Additional comparison with the bread
wheat genome revealed an equal subgenome (A, B, and D) rep-
resentation in the 2604 and 2610 metagenomic reads, which
suggests, in combination with the microscopic identiﬁcation of
numerous characteristic grains, glumes, and spikelets, the pres-
ence of hexaploid spelt wheat (T. spelta) in these paleofeces
(Figure 3D). Beside the plant diet, we obtained molecular evi-
dence for the consumption of cattle (Bos taurus) and swine
meats (Sus scrofa) throughout all investigated time periods
(Figures 3B and S3D). Interestingly, the most abundant cattle
proteins in sample 2611 (hemoglobin and coagulation proteins)
indicate the plant diet was supplemented by blood-rich animal
tissues (e.g., muscle, liver) (Data S2F). The molecular analyses
revealed in addition, that individuals from both the Iron Age
(2611) and the Baroque (2612) suffered from intestinal infections
of whipworms (Trichuris trichuria) and roundworm (Ascaris spp.)
(Figure 3B and S3D–S3G). Finally, all samples showed a contin-
uous low background with fungal DNA mainly coming from
Molecular evidence for blue cheese and beer
consumption during the Iron Age
In contrast to all other samples, the Iron Age sample 2604 dis-
played an exceptionally high abundance of Penicillium roqueforti
and Saccharomyces cerevisiae proteins (Data S2D) and DNA
(Data S1N), making up to 7%–22% of total eukaryotic reads.
This was characteristic of this sample as compared with the
other samples that did not show such prevalence—even the
sample 2611, which was taken from a similar context and dated
back to the same time point. To authenticate the data and gain
further insights into their potential ecological signiﬁcance, we
mapped the high-quality reads of sample 2604 against the refer-
ence genomes of these two fungi (Figure S4A; Data S1O). With
11–133coverage, we were able to reconstruct >92% of both ge-
nomes, displaying even coverage and SNP distribution. To
conﬁrm whether these two fungi are of ancient origin and not
modern contaminants, we initially checked the ancient DNA
damage pattern of the mapped reads. Both fungi displayed
typical ancient DNA damage patterns, with levels comparable
to the human endogenous DNA (Figures S4B and S4C). Hence,
and considering their extraordinarily high abundance and exclu-
sive incidence in this sample, we assumed their endogenous
originality to the coprolite microbial community. Additionally,
both fungi are commonly used nowadays in food processing:
P. roqueforti is used for cheese fermentation, and S. cerevisiae
is used for fermenting bread and alcoholic beverages including
beer, mead, and wine. Therefore, we assume that they could
have been involved in food processing at that time. To test this
assumption, we used the reconstructed genomes for further
comparative phylogeny and population genetic analyses to infer
whether they had been truly involved in food processing or were
just transient environmental microbes.
(D) Wheat subgenome (A, B, and D) representation in the 2604 and 2610 metagenomes (Data S1), aligned to the modern hexaploid bread wheat reference
genome (accession number GCA_900519105). Both the wheat chloroplast and nuclear reads were highly fragmented and display aDNA-speciﬁc damage
patterns (Figures S3H–S3K).
See also Figure S3 for details about the comparative analysis, phylogenet ic assignment, and damage pattern of selected plant, animal, and parasite DNA. Data S1
provides further details of the macro-remains, comparative datasets, dietary DNA, and mapping statistics. Data S2 provides additional information about the
comparative datasets and proteomics results.
6Current Biology 31, 1–14, December 6, 2021
First, we compared our putative P. roqueforti strain to 33 other
sequenced modern P. roqueforti strains coming from different
The comparative dataset included 18
cheese-fermenting and 15 non-cheese-fermenting strains (Data
S1Q), in addition to Penicillium psychrosexualis and Penicillium
carneum as an outgroup. After mapping the raw reads of all
strains to the reference P. roqueforti genome FM164 and data
ﬁltering, we resolved 120,337 SNPs, which were used for inferring
maximum likelihood (ML) phylogenetic relationships among the
tested strains (STAR Methods). Consistent with the original pub-
lication of Dumas and colleagues,
the resulting phylogeny re-
vealed four distinct clades: a Roquefort cheese clade, a non-
Roquefort cheese clade containing blue cheeses others than
Roquefort, a silage/food spoilage clade, and a wood/food
spoilage clade (Figure 4A). Initially, the phylogenetic analysis
separated the non-Roquefort cheese clade from the other, then
the Roquefort cheese clade was diverged from the other food
spoilage clades. The ancient P. roqueforti strain showed highest
similarity to the non-Roquefort cheese strains, being clustered
together with their corresponding clade as an earlier divergent.
The reason behind such early divergence might be attributed to
the recent acquisition of some genomic regions—most impor-
tantly, CheesyTer and Wallaby—by the non-Roquefort cheese
strains. This gene acquisition most likely happened via repeated
multiplication of selected spores of the best cheeses on bread
used as a growth medium in the late 19
century and early 20
century before the advent of microbiological in vitro culturing
Thereby, modern non-Roquefort strains were
exposed to extensive selection coupled to horizontal gene trans-
fer events from other cheese-producing Penicillium spp. or even
Importantly, our Iron Age strain did not
contain any of those recently acquired fragments, which comes
in congruence with the hypothesis that such domestication
events occurred during the last two centuries.
We further used the tool ADMIXTURE to infer the degree of
admixture among the strains. By assuming the presence of 3 an-
cestries (K = 3), we could clearly distinguish the non-Roquefort,
Roquefort, and food spoilage strains (Figure 4B). Our putative
strain displayed 70% cheese-producing ancestry (60% of the
non-Roquefort and 10% of Roquefort cheese) and 30% food-
spoiler ancestry. Both the phylogenetic placement and ADMIX-
TURE proﬁle indicate that the ancient P. roqueforti has already
been under positive selection toward the non-Roquefort cheese
cluster, a selection process that most likely occurred during the
process of cheeseproduction. Some archeological ﬁndings exca-
vated from the mines might have been usedfor that purpose (Fig-
ure 4C), as they showed some traces of fatty food products.
Next, we compared the ancient S. cerevisiae genome to 157
recent strains coming from different ecological niches, i.e.,
food, alcoholic beverages (e.g., beer, wine, sake, and spirits),
biofuels, and laboratories, as well as wild strains (Data S1R).
ML phylogenetic analysis, based on 375,629 SNP positions,
distinguished 2 main clades. The ﬁrst main clade splits into two
subclades, with one containing most of the beer strains (beer 1
clade) that show a successive sub-clustering based on the origin
of the strains (Figure 4D). The other subclade (henceforth referred
to as ‘‘mixed’’ clade) included a mixture of bread, wine, beer, and
spirit strains. The second main clade is composed of two sub-
clades: a wine clade and another beer clade (beer 2). All other
wild, laboratory, and sake strains fall to the base of the whole phy-
logeny. The ancient S. cerevisiae strain clustered basal to the
second main clade, which includes the wine and beer 2 strains.
Further population structure analysis displayed high admixture
in our putative strain, resembling primarily the wine ancestral
population (47%), followed by 29.2% beer ancestries (Fig-
ure S4D) and only 19% wild strain ancestry. Therefore, and
considering the ML phylogenetic assignment, we assume that
the possibility of our strain to be of wild origin is unlikely. The re-
sults rather indicate higher similarity to wine and beer strains.
Principal component analysis (PCA) provided further indication
for the domestication of our strain in alcoholic beverage fermen-
tation. Along the PC1 that explains 25.42% of the variation, our
strain clustered closer to the strains of beer 2 than to the strains
of the wine clade (Figure 4E). This was further supported with pro-
teomic analysis (Data S2D) that unveiled that most of the peptides
assigned to the genus Saccharomyces derived from proteins
involved in alcohol fermentation pathways (e.g., glycolysis). To
further narrow down the possible routes of domestication, we
decided to differentiate the strains based on functional marker
genes (Data S1S). According to recent literature,
RTM1,BIO1/BIO6, and the chromosomal regions A/B/C can be
used to differentiate yeast strains based on their functional
niches. The gene RTM1 is a strong domestication marker respon-
sible for conferring resistance against the toxicity of molasses
and other rich-sugar substrates and is assumed to be positively
selected in beer yeast strains.
The genes BIO1 and BIO6,
which are involved in de novo biosynthesis of biotin, are highly
selected in sake fermenting yeasts, due to lack of biotin in the
fermentation substrates, such as rice.
The regions A, B, and
C are horizontally transferred genomic regions from other yeast
genera, e.g., Kluyveromyces,Pichia, and Zygosaccharomyces.
These regions contain 39 genes distributed over 3 different chro-
mosomes and are assumed to play a role in wine fermentation.
Therefore, we searched the presence of these marker genes in
our comparative dataset, including our ancient strain. In accor-
dance with the literature, almost all beer strains—either of clade
1 or clade 2—were positive for RTM1, while the wine clade was
mainly positive for the genomic regions A/B/C. The mixed clade
contained both RTM1 and the regions A/B/C. The sake clade
exclusively contained the BIO1/BIO6 genes and partially the
RTM1 gene. The wild strains, isolated from cacao in Africa, clus-
tered in the basal clade and did not contain any of these marker
genes (Figure 4D; Data S1T), contrary to our strain that contained
the RTM1 and lackedthe BIO1/BIO6 genes andthe regions A/B/C.
Based on the previous ﬁndings—i.e., (1) the ancient DNA dam-
age proﬁle, (2) the high prevalence of S. cerevisiae reads, (3) the
presence of fermentable cereal substrates such as wheat and
barley, (4) the phylogenetic assignment of the ancient yeast
strain, (5) the yeast admixture proﬁle, and (6) the distribution of
marker genes—we assume that this yeast is of ancient origin
and has been involved in beer fermentation, although the
mode of fermentation is unknown (i.e., bottom, top, or sponta-
Our interdisciplinary analyses of the samples have given detailed
insight into the microbiome evolution and dietary habits and food
Current Biology 31, 1–14, December 6, 2021 7
West Africa (WA)
−0.1 0.0 0.1 0.2
Tree scale: 0.1
Tree scale: 0.1
Figure 4. Genome-wide SNP analysis of ancient fungal ‘‘strains’’ versus modern industrial and wild/environmental strains
(A) Maximum likelihood (ML) phylogenetic analysis of the Penicillium roqueforti genome assembled from the sample 2604 in addition to other previously published
P. roqueforti genomes.
A total number of 120,359 SNP positions were used for the analysi s. P. roqueforti FM164 was used as a reference, while P. carneum and
P. psychrosexualis were used as outgroups. The scale bar depicts 0.1 substitutions per residue. Colored strips indicate the P. roqueforti population as previously
For further information on the comparison dataset, please refer to Data S1Q.
(B) Population structure analysis of P. roqueforti 2604 with the same previous dataset, considerin g 3 ancestries (K = 3 with lowest cross-validation error), based on
120,337 SNPs. The order of labels corresponds to the clustering in panel (A).
(C) Wooden containers that have been found among other archeological ﬁndings in the mines and assumed to be used as cheese strainers
(D) ML phylogenetic analysis of Saccharomyces cerevisiae genome assembled from the sample 2604 compared with other published S. cerevisiae genomes.
The dataset for the analysis included 375,629 SNPs. The Saccharomyces paradoxus CBS432 was used as an outgroup. The scale bar depicts 0.1 substitutions
per residue. The colored strips indicate the clade/origin as reported previously.
The colored dots at the tree edges refer to the presence/absence of functional
Blue dots in (A) and (C) indicate bootstrap support >80% based on 1,000 bootstrap replicates.
(E) Principal component analysis based on 136,712 SNP, of the S. cerevisiae strains.
For additional information on the coverage and SNP density, DNA damage, and ADMIXTURE, please refer to Figure S4.Data S1 provides further details about the
comparative datasets, mapping results, and functional marker analysis.
8Current Biology 31, 1–14, December 6, 2021
processing techniques of the Hallstatt miners over the past three
millennia. Molecular and microscopic investigations revealed
that the miner’s diet was mainly composed of cereals, such as
domesticated wheats (emmer and spelt), barley, common mil-
lets, and foxtail millets. This carbohydrate-rich diet was supple-
mented with proteins from broad beans and occasionally with
fruits, nuts, or animal products. The food remains in the protohis-
toric sample with abundant entire fruits and seeds were less pro-
cessed than those of the Baroque sample, which consisted of
ﬁnely ground wheat. This suggests that the protohistoric miners
consumed the cereals and legumes in a sort of gruel or
whereas miners in the 18th century AD ate their ce-
reals in a more processed form, e.g., as a bread or biscuit.
In general, such carbohydrate-rich ﬁbrous dietary components
as observedin the Bronze Age and Iron Age samplesare typical for
traditional communities and are considered to be the main drivers
of the non-Westernized microbiome structure.
with this observation, our analysis showed that the Hallstatt pale-
ofecal samples contain microbial features similar to gut micro-
biomes of modern non-Westernized populations (Figures 2Aand
2B). Species identiﬁed in the samples, such as Lactobacillus rumi-
nis,Catenibacterium mitsuokai,andPrevotella copri,werealso
found to be highly prevalent in present-day individuals with a
more traditional lifestyle (Figure 2C). Furthermore, our paleofecal
samples were rich in the P. copri complex (Figure 2D), including
the four clades that are nearly ubiquitous and co-present in non-
Of particular interest, P. copri
members have been shown to be associated with the digestion
of complex carbohydrates,
which are the major component
of an unprocessed ﬁbrous plant diet. Finding paleofeces highly
resembling that of non-Westernized individuals, in terms of micro-
biome structure, supports previous observations.
It also adds
weight to the hypothesis that the modern industrialized human gut
microbiome hasdiverged from an ancestral state, probably due to
modern lifestyle, diet, or medical advances. Interestingly,this non-
Westernized microbiome structure has been observed in all four
paleofeces dating from the Bronze Age to the Baroque period,
which would indicate quite a recent change in the gut community.
However, to spot the critical time points when this shift in the hu-
man gut microbiomebegan requires more ancient samples span-
ning a wider time range; of particular interest would be samples
from the past two or three centuries, when major dietary and med-
ical changes occurred. Overall, our results support the theory that
the shift from traditional to an industrial Westernized lifestyle might
be the driving force for changing the human gut microbiome from
its ancestral state.
In one of the Iron Age samples (2604), the molecular analyses
indicated consumption of fermented food and beverages. The
fungal analysis revealed a high prevalence of Penicillium roque-
forti and Saccharomyces cerevisiae, which are nowadays
involved in fermenting blue cheeses and alcoholic beverages,
respectively, with clear signs of domestication. Following rapidly
in the wake of ruminant animal domestication (mainly cattle,
sheep, and goat),cheese production represents one of the oldest
and widespread food preservation techniques developed by hu-
The oldest evidence for milk use dates back to the
Neolithic in the Fertile Crescent yet provides only indirect evi-
dence for fermentation.
The oldest reported chemical evidence
for processing of milk into fermented products (i.e., keﬁr dairy) is
dated back to the Early Bronze Age in Western China.
dications, including actual preserved pieces of cheese, whey
strainers, and recipesfor cheese production, were found in North-
ern Europe, the Middle and Near East, and the Mediterranean ba-
Here, we report evidence for the domestication of the
fungus Penicillium roqueforti in the course of food processing in
millennium BC that would likely produce a cheese resem-
bling a blue cheese (non-Roquefort cheese clade, in Figure 4A).
To our knowledge, this represents the earliest known evidence
for directed cheese ripening and afﬁnage in Europe, adding a
crucial aspect to an emerging picture of highly sophisticated culi-
nary traditions in European protohistory.
Importantly, the pro-
duction of blue cheese today involves a surface application of
dry salt; therefore, it is characterized by a high salt content of
up to 7.5% (w/w).
The cheese curd could have been collected,
desiccated, and inoculated with the fungi in wooden cheese con-
tainers like the ones excavated in the Hallstatt mines (Figure 4C).
The presence of P. roqueforti indicates a major step in ruminant
milk processing from fresh to ripened cheese, which could have
offered, in addition to new ﬂavors, several advantages to the Hall-
statt miners including longer storage (i.e., months) and less
lactose content in the fermented dairy product.
lactose content may have helped the ancient minors to better
digest milk products, living in a time when lactose persistence fre-
quencies only started to rise in Europe.
The presence of salt as
well as the constant temperature (8C) and humidity inside the
Hallstatt mine workings represent ideal conditions for blue cheese
production, following the current cheese production standards.
It is noteworthy that the early discovery of the Roquefort cheese
was linked to Roquefort-sur-Soulzon caves in France, which
maintain a temperature of 10Cand90% humidity over the
year. With such conditions protecting the cheese from desicca-
tion, these caves have been used exclusively for centuries for
ripening and aging of the ‘‘Roquefort’’ cheese.
Indications for the production of fermented alcoholic bever-
ages in protohistory are abundant, albeit frequently ambig-
and can be found in the Near East, Middle East, Far
East, and Europe.
Evidence for the production of grape
wine in Europe and viniculture in the Near East dates back to
Such evidence was mainly
based on chemical residue analysis or archaeobotanical analysis
or indicated in ancient inscriptions. Recently scientists claimed
that they were able to revive an ancient yeast strain from Egyp-
tian potteries and used it to ferment beer.
Here we were able
to reconstruct >90% of the S. cerevisiae genome from an Iron
Age-dated paleofecal sample. We used different molecular
analysis at the genome level to infer the possible routes of
domestication for this yeast. Our results suggested it was used
in beer fermentation. Together with the results of the dietary
analysis that showed presence of different fermentable cereals,
e.g., wheat, barley, and millets, we can envisage how the
fermentation was carried out.
It might be assumed that the fermentation was carried out in a
spontaneous manner—i.e., by adding water to wort and allowing
the fermentation process to take place by the wild air-borne
yeasts or the constitutional microbiota of the used cereals.
We do not see, however, indications for other yeasts species,
such as Brettanomyces bruxellensis, that co-occur in spontane-
ously fermented beers.
In addition, we see clear indications of
Current Biology 31, 1–14, December 6, 2021 9
domestication and continuous supply of new admixture compo-
nents to this yeast, which might suggest that fermentation ves-
sels were repeatedly used for this purpose or the inoculation of
the fermentation batches has been done by back-slopping
(i.e., inoculation of new fermentation batches with portions of
Albeit varied evidence for beer production
in protohistoric Europe exists,
these beers could not be
preserved for longer time periods and would have had to be
consumed rapidly after production,
which also presupposes
that the beer would have had to be produced either in Hallstatt
itself or in the very near surroundings.
Considering the constant temperature of 8C inside the Hall-
statt mines, it might be expected that this yeast was used for pro-
duction of lager-like beer, when fermentation is carried out at low
temperatures (also known as bottom-fermentation) and results in
a beer that can be stored for longer time periods.
however, the bottom-fermentation was most likely developed af-
ter the year 1553, when the Duke of Bavaria Albrecht V forbade
brewing during summer months.
Additionally, Gonc¸ alves and
colleagues demonstrated that Saccharomyces pastorianus
strains, which are hybrids of S. cerevisiae and another Saccharo-
myces species and are used for production of lager beers,
belong to the main beer clade (Figure 4D).
Therefore, we postu-
late that the beer produced at that time is similar to what would
nowadays be known as pale beer, produced mainly by top-fer-
menting S. cerevisiae strains.
Paleofeces material displays an archaeological information
source that provides insights into the diet and gut microbiome
composition of ancestors. Here, we had access to four paleofe-
ces samples from the Hallstatt salt mines dating from the Bronze
Age to the Baroque period. The constant low annual temperature
and high salt concentrations inside the mine preserved both
plant macro-remains and biomolecules (DNA and protein) in
the paleofeces. We demonstrate the indispensable complemen-
tarity of using microscopic and molecular approaches in
resolving the paleofecal dietary residual components and to
reconstruct the ancient gut microbiome. Furthermore, we
extended our paleofeces microbiome analysis to focusing on
key microbes that are involved in food processing, which opens
new avenues in understanding fermentation history. In the future,
additional samples from different time points will provide a more
ﬁne-scaled diachronic picture, which may help us to understand
the role of dietary changes in shaping our gut microbiome and
how much this was further inﬂuenced by modern lifestyles or
medical advances recently introduced through industrialization
Detailed methods are provided in the online version of this paper
and include the following:
dKEY RESOURCES TABLE
BData and code availability
dEXPERIMENTAL MODEL AND SUBJECT DETAILS
BPaleofeces samples, radiocarbon dating
BMicroscopic analysis of the paleofeces
BMolecular analysis of the paleofeces
dQUANTIFICATION AND STATISTICAL ANALYSIS
Supplemental information can be found online at https://doi.org/10.1016/j.
We acknowledge the following funding sources: Programma Ricerca Budget
prestazioni Eurac 2017 of the Province of Bolzano, Italy, and the South Tyro-
lean grant legge 14 (F.M., M.S.S., S.Z., and A.Z.). Additional support was pro-
vided by the European Regional Development Fund 2014-2020_CALL-FESR
2017 Research and Innovation_Autonomous Province of Bolzano South Ty-
rol_Project: FESR1078-MummyLabs. The authors thank the Department of
Innovation, Research and University of the Autonomous Province of Bozen/
Bolzano for covering the Open Access publication costs. We thank Dr. John
Wilson (ProtiFi, USA) for helpful discussions regarding proteomics sample
preparation. This work was in addition supported by the European Research
Council grant ERC-STG Project MetaPG (N.S.); the US National Institutes of
Health, National Institute for General Medical Sciences under grant no.
GM087221 and the Ofﬁce of the Director 1S10OD026936; and the US National
Science Foundation award 1920268 (R.L.M.). We would like to thank Eva-Ma-
ria Geigl and the two anonymous reviewers for their insightful comments that
helped to improve the manuscript.
F.M., K.O., N.S., A.Z., H.R., and K.K. conceived the investigation. F.M., A.S.,
R.L.M., K.O., N.S., A.Z., H.R., and K.K. designed experiments. K.O., A.S.,
F.M., A.Z., H.R., and K.K. were involved in the sampling campaign. F.M.,
A.S., U.K., M.R.H., and K.O. conducted the experiments. F.M., M.S.S.,
K.D.H., A.T., A.S., S.Z., A.B.-M., P.M., J.C.-K., W.R., U.K., S.R.M., M.R.H.,
O.R.-S., T.R., and K.O. performed analyses. F.M and M.S.S. wrote the manu-
script with contributions from K.D.H., A.T., A.B.-M., J.C.-K., M.R.H., O.R.-S.,
T.R., R.L.M., K.O., N.S., A.Z., H.R., and K.K.
DECLARATION OF INTERESTS
The authors declare no competing interests.
Received: May 27, 2021
Revised: August 16, 2021
Accepted: September 14, 2021
Published: October 13, 2021
1. Fry, G. (1985). Analysis of fecal material. In The Analysis of Prehistoric
Diets, , R.J. Gilbert, and J. Mielke, eds. (Academic Press), pp. 127–154.
2. Shillito, L.-M., Blong, J.C., Green, E.J., and van Asperen, E.N. (2020). The
what, how and why of archaeological coprolite analysis. Earth Sci. Rev.
3. Gilbert, M.T.P., Jenkins, D.L., Go
¨therstrom, A., Naveran, N., Sanchez,
J.J., Hofreiter, M., Thomsen, P.F., Binladen, J., Higham, T.F.G., Yohe,
R.M., 2nd., et al. (2008). DNA from pre-Clovis human coprolites in
Oregon, North America. Science 320, 786–789.
4. Maixner, F., Turaev, D., Cazenave-Gassiot, A., Janko, M., Krause-Kyora,
B., Hoopmann, M.R., Kusebauch, U., Sartain, M., Guerriero, G.,
O’Sullivan, N., et al. (2018). The iceman’s last meal consisted of fat,
wild meat, and cereals. Curr. Biol. 28, 2348–2355.e9.
10 Current Biology 31, 1–14, December 6, 2021
5. Poinar, H.N., Kuch, M., Sobolik, K.D., Barnes, I., Stankiewicz, A.B.,
Kuder, T., Spaulding, W.G., Bryant, V.M., Cooper, A., and P€
(2001). A molecular analysis of dietary diversity for three archaic Native
Americans. Proc. Natl. Acad. Sci. USA 98, 4317–4322.
6. Mitchell, P.D. (2017). Human parasites in the Roman World: health con-
sequences of conquering an empire. Parasitology 144, 48–58.
7. Reinhard, K.J., Ferreira, L.F., Bouchet, F., Sianto, L., Dutra, J.M.F.,
Iniguez, A., Leles, D., Le Bailly, M., Fugassa, M., Pucu, E., and Arau
A. (2013). Food, parasites, and epidemiological transitions: a broad
perspective. Int. J. Paleopathol. 3, 150–157.
8. Maixner, F., Krause-Kyora, B., Turaev, D., Herbig, A., Hoopmann, M.R.,
Hallows, J.L., Kusebauch, U., Vigl, E.E., Malfertheiner, P., Megraud, F.,
et al. (2016). The 5300-year-old Helicobacter pylori genome of the
Iceman. Science 351, 162–165.
9. Tett, A., Huang, K.D., Asnicar, F., Fehlner-Peach, H., Pasolli, E., Karcher,
N., Armanini, F., Manghi, P., Bonham, K., Zolfo, M., et al. (2019). The
Prevotella copri complex comprises four distinct clades underrepre-
sented in Westernized populations. Cell Host Microbe 26, 666–679.e7.
10. Tito, R.Y., Knights, D., Metcalf, J., Obregon-Tito, A.J., Cleeland, L., Naj ar,
F., Roe, B., Reinhard, K., Sobolik, K., Belknap, S., et al. (2012). Insights
from characterizing extinct human gut microbiomes. PLoS ONE 7,
11. Borry, M., Cordova, B., Perri, A., Wibowo, M., Prasad Honap, T., Ko, J.,
Yu, J., Britton, K., Girdland-Flink, L., Power, R.C., et al. (2020). CoproID
predicts the source of coprolites and paleofeces using microbiome
composition and host DNA content. PeerJ 8, e9001.
12. Wibowo, M.C., Yang, Z., Borry, M., Hu
¨bner, A., Huang, K.D., Tierney,
B.T., Zimmerman, S., Barajas-Olmos, F., Contreras-Cubas, C., Garcı
Ortiz, H., et al. (2021). Reconstruction of ancient microbial genomes
from the human gut. Nature 594, 234–239.
13. Harding, A. (2013). Salt in Prehistoric Europe (Sidestone Press).
14. Reschreiter, H., and Kowarik, K. (2019). Bronze Age mining in Hallst att. A
new picture of everyday life in the salt mines and beyond. Archaeologia
Austriaca 103, 99–136.
15. Grabner, M., W€
achter, E., Nicolussi, K., Bolka, M., Sormaz, T., Steier, P.,
Wild, E.M., Barth, F.E., Kern, A., Rudorfer, J., et al. (2021). Prehistoric salt
mining in Hallstatt, Austria. New chronologies out of small wooden frag-
ments. Dendrochronologia 66, 125814.
16. Kowarik, K. (2019). Mining and landscape: synthesis. In Hallst€
Beziehungsgeschichten. Wirtschaftsstrukturen und Umfeldbeziehungen
der bronze- und €
altereisenzeitlichen Salzbergbaue von Hallstatt/OO
Kowarik, ed. (Obero
¨sterreichisches Landesmuseum), pp. 245–266.
17. Festi, D., Brandner, D., Grabner, M., Knierzinger, W., Reschreiter, H., and
Kowarik, K. (2021). 3500 years of environmental sustainability in the
large-scale alpine mining district of Hallstatt, Austria. Journal of
Archaeological Science: Reports 35, 102670.
18. Wochenberichte (1723). Hofschreiberamt Hallstatt. https://www.
19. Brewster, R., Tamburini, F.B., Asiimwe, E., Oduaran, O., Hazelhurst, S.,
and Bhatt, A.S. (2019). Surveying gut microbiome research in Africans:
toward improved diversity and representation. Trends Microbiol. 27,
20. Key, F.M., Posth, C., Krause, J., Herbig, A., and Bos, K.I. (2017). Mining
metagenomic data sets for ancient DNA: recommended protocols for
authentication. Trends Genet. 33, 508–520.
21. Beghini, F., McIver, L.J., Blanco-Mı
´guez, A., Dubois, L., Asnicar, F.,
Maharjan, S., Mailyan, A., Manghi, P., Scholz, M., Thomas, A.M., et al.
(2021). Integrating taxonomic, functional, and strain-level proﬁling of
diverse microbial communities with bioBakery 3. eLife 10, e65088.
22. Grant, W.D. (2015). Halococcus. In Bergey’s Manual of Systematics of
Archaea and Bacteria, , M.E. Trujillo, S. Dedysh, P. DeVos, B. Hedlund,
ampfer, F.A. Rainey, and W.B. Whitman, eds. (John Wiley and Sons).
´a, S., Vidal, J.E., Heredia, N., and Juneja, V.K. (2019). Clostridium
perfringens. In Food Microbiology: Fundamentals and Frontiers, 5th
Edition, , M.P. Doyle, F. Diez-Gonzalez, and C. Hill, eds. (American
Society of Microbiology).
24. Voidarou, C., Bezirtzoglou, E., Alexopoulos, A., Plessas, S., Stefanis, C.,
Papadopoulos, I., Vavias, S., Stavropoulou, E., Fotou, K., Tzora, A., and
Skoufos, I. (2011). Occurrence of Clostridium perfringens from different
cultivated soils. Anaerobe 17, 320–324.
25. Pasolli, E., De Filippis, F., Mauriello, I.E., Cumbo, F., Walsh, A.M., Leech,
J., Cotter, P.D., Segata, N., and Ercolini, D. (2020). Large-scale genome-
wide analysis links lactic acid bacteria from food with the gut micro-
biome. Nat. Commun. 11, 2610.
26. Dumas, E., Feurtey, A., Rodrı
´guez de la Vega, R.C., Le Prieur, S., Snirc,
A., Coton, M., Thierry, A., Coton, E., Le Piver, M., Roueyre, D., et al.
(2020). Independent domestication events in the blue-cheese fungus
Penicillium roqueforti. Mol. Ecol. 29, 2639–2660.
27. Ropars, J., Rodrı
´guez de la Vega, R.C., Lo
´pez-Villavicencio, M., Gouzy,
J., Sallet, E., Dumas, E
´., Lacoste, S., Debuchy, R., Dupont, J., Branca,
A., and Giraud, T. (2015). Adaptive horizontal gene transfers between
multiple cheese-associated fungi. Curr. Biol. 25, 2562–2569.
28. Cheeseman, K., Ropars, J., Renault, P., Dupont, J., Gouzy, J., Branca,
A., Abraham, A.-L., Ceppi, M., Conseiller, E., Debuchy, R., et al. (2014).
Multiple recent horizontal transfers of a large genomic region in cheese
making fungi. Nat. Commun. 5, 2876.
29. Ropars, J., Didiot, E., Rodrı
´guez de la Vega, R.C., Bennetot, B., Coton,
M., Poirier, E., Coton, E., Snirc, A., Le Prieur, S., and Giraud, T. (2020).
Domestication of the emblematic white cheese-making fungus
Penicillium camemberti and its diversiﬁcation into two varieties. Curr.
Biol. 30, 4441–4453.e4.
30. Gallone, B., Steensels, J., Prahl, T., Soriaga, L., Saels, V., Herrera-
Malaver, B., Merlevede, A., Roncoroni, M., Voordeckers, K., Miraglia,
L., et al. (2016). Domestication and divergence of Saccharomyces cere-
visiae beer yeasts. Cell 166, 1397–1410.e16.
31. Gonc¸ alves, M., Pontes, A., Almeida, P., Barbosa, R., Serra, M., Libkind,
D., Hutzler, M., Gonc¸ alves, P., and Sampaio, J.P. (2016). Distinct domes-
tication trajectories in top-fermenting beer yeasts and wine yeasts. Curr.
Biol. 26, 2750–2761.
32. Pontes, A.,Hutzler, M., Brito, P.H., andSampaio, J.P. (2020). Revisiting the
taxonomic synonyms and populations of Saccharomyces cerevisiae—
phylogeny, phenotypes, ecology and domestication. Microorganisms 8,
33. Marsit, S., Leducq, J.-B., Durand, E
´., Marchant, A., Filteau, M., and
Landry, C.R. (2017). Evolutionary biology through the lens of budding
yeast comparative genomics. Nat. Rev. Genet. 18, 581–598.
34. Ness, F., and Aigle, M. (1995). RTM1: a member of a new family of telo-
meric repeated genes in yeast. Genetics 140, 945–956.
35. Wu, H., Ito, K., and Shimoi, H. (2005). Identiﬁcation and characterization
of a novel biotin biosynthesis gene in Saccharomyces cerevisiae. Appl.
Environ. Microbiol. 71, 6845–6855.
36. Novo, M., Bigey, F., Beyne, E., Galeote, V., Gavory, F., Mallet, S.,
Cambon, B., Legras, J.-L., Wincker, P., Casaregola, S., and Dequin, S.
(2009). Eukaryote-to-eukaryote gene transfer events revealed by the
genome sequence of the wine yeast Saccharomyces cerevisiae
EC1118. Proc. Natl. Acad. Sci. USA 106, 16333–16338.
37. Heiss, A.G., Jakobitsch, T., Wiesinger, S., and Trebsche, P. (2021). Dig
out, dig in! Plant-based diet at the Late Bronze Age copper production
site of Prigglitz-Gasteil (Lower Austria) and the relevance of processed
foodstuffs for the supply of Alpine Bronze Age miners. PLoS ONE 16,
38. Makki, K., Deehan, E.C., Walter, J., and B€
ackhed, F. (2018). The impact
of dietary ﬁber on gut microbiota in host health and disease. Cell Host
Microbe 23, 705–715.
39. Crittenden, A.N., and Schnorr, S.L. (2017). Current views on hunter-gath-
erer nutrition and the evolution of the human diet. Am. J. Phys. Anthropol.
162 (Suppl 63 ), 84–109.
Current Biology 31, 1–14, December 6, 2021 11
40. De Filippis, F., Pasolli, E., Tett, A., Tarallo, S., Naccarati, A., De Angelis,
M., Neviani, E., Cocolin, L., Gobbetti, M., Segata, N., and Ercolini, D.
(2019). Distinct genetic and functional traits of human intestinal
Prevotella copri strains are associated with different habitual diets. Cell
Host Microbe 25, 444–453.e3.
´lvez, E.J.C., Iljazovic, A., Amend, L., Lesker, T.R., Renault, T.,
Thiemann, S., Hao, L., Roy, U., Gronow, A., Charpentier, E., and
Strowig, T. (2020). Distinct polysaccharide utilization determines inter-
species competition between intestinal Prevotella spp. Cell Host
Microbe 28, 838–852.e6.
42. Fehlner-Peach, H., Magnabosco, C., Raghavan, V., Scher, J.U., Tett, A.,
Cox, L.M., Gottsegen, C., Watters, A., Wiltshire-Gordon, J.D., Segata, N.,
et al. (2019). Distinct polysaccharide utilization proﬁles of human intesti-
nal Prevotella copri isolates. Cell Host Microbe 26, 680–690.e5.
43. Blaser, M.J. (2017). The theory of disappearing microbiota and the epi-
demics of chronic diseases. Nat. Rev. Immunol. 17, 461–463.
44. Pasolli, E., Asnicar, F., Manara, S., Zolfo, M., Karcher, N., Armanini, F.,
Beghini, F., Manghi, P., Tett, A., Ghensi, P., et al. (2019). Extensive unex-
plored human microbiome diversity revealed by over 150,000 genomes
from metagenomes spanning age, geography, and lifestyle. Cell 176,
45. Sonnenburg, E.D., and Sonnenburg, J.L. (2019). The ancestral and indus-
trialized gut microbiota and implications for human health. Nat. Rev.
Microbiol. 17, 383–390.
46. Fox, P.F., Guinee, T.P., Cogan, T.M., and McSweeney, P.L. (2017).
Cheese: historical aspects. Fundamentals of Cheese Science
(Springer), pp. 1–10.
47. Evershed, R.P., Payne, S., Sherratt, A.G., Copley, M.S., Coolidge, J.,
Urem-Kotsu, D., Kotsakis, K., Ozdo
gan, M., Ozdo
Nieuwenhuyse, O., et al. (2008). Earliest date for milk use in the Near
East and southeastern Europe linked to cattle herding. Nature 455,
48. Yang, Y., Shevchenko, A., Knaust, A., Abuduresule, I., Li, W., Hu, X.,
Wang, C., and Shevchenko, A. (2014). Proteomics evidence for keﬁr dairy
in Early Bronze Age China. J. Archaeol. Sci. 45, 178–186.
ero, J. (1985). The cuisine of ancient Mesopotamia. The Biblical
Archaeologist 48, 36–47.
50. Greco, E., El-Aguizy, O., Ali, M.F., Foti, S., Cunsolo, V., Saletti, R., and
Ciliberto, E. (2018). Proteomic analyses on an ancient Egyptian cheese
and biomolecular evidence of brucellosis. Anal. Chem. 90, 9673–9676.
51. McClure, S.B., Magill, C., Podrug, E., Moore, A.M.T., Harper, T.K.,
Culleton, B.J., Kennett, D.J., and Freeman, K.H. (2018). Fatty acid spe-
ciﬁc d13C values reveal earliest Mediterranean cheese production
7,200 years ago. PLoS ONE 13, e0202807.
52. Salque, M., Bogucki, P.I., Pyzel, J., Sobkowiak-Tabaka, I., Grygiel, R.,
Szmyt, M., and Evershed, R.P. (2013). Earliest evidence for cheese mak-
ing in the sixth millennium BC in northern Europe. Nature 493, 522–525.
53. Cakmakci, S., Gundogdu, E., Hayaloglu, A.A., Dagdemir, E., Gurses, M.,
Cetin, B., and Tahmas-Kahyaoglu, D. (2012). Chemical and microbiolog-
ical status and volatile proﬁles of mouldy C ivil cheese, a T urkish
mould-ripened variety. Int. J. Food Sci. Technol. 47, 2405–2412.
54. Monti, L., Pelizzola, V., Povolo, M., Fontana, S., and Contarini, G. (2019).
Study on the sugar content of blue-veined ‘‘Gorgonzola’’ PDO cheese.
Int. Dairy J. 95, 1–5.
55. Burger, J., Link, V., Blo
¨cher, J., Schulz, A., Sell, C., Pochon, Z.,
Zegarac, A., Hofmanova
´, Z., Winkelbach, L., et al.
(2020). Low prevalence of lactase persistence in Bronze Age Europe in-
dicates ongoing strong selection over the last 3,000 years. Curr. Biol. 30,
56. Cantor, M.D., van den Tempel, T., Hansen, T.K., and Ardo
¨, Y. (2017). Blue
cheese. In Cheese,, , P.L.H. McSweeney, P.F. Fox, P.D. Cotter, and D.W.
Everett, eds. (Elsevier), pp. 929–954.
57. Capozzi, V., and Spano, G. (2011). Food microbial biodiversity and ‘‘mi-
crobes of protected origin’’. Front. Microbiol. 2, 237.
58. Desmasures, N. (2014). Mold-ripened varieties. In Encyclopedia of Food
Microbiology, , C. Batt, ed. (Elsevier), pp. 409–416.
59. Heiss, A.G., Azorı
´n, M.B., Antolı
´n, F., Kubiak-Martens, L., Marinova, E.,
Arendt, E.K., Biliaderis, C.G., Kretschmer, H., Lazaridou, A., Stika,
H.-P., et al. (2020). Mashes to mashes, crust to crust. Presenting a novel
microstructural marker for malting in the archaeological record. PLoS
ONE 15, e0231696.
60. Zarnkow, M., Otto, A., and Einwag, B. (2011). Interdisciplinary investiga-
tions into the brewing technology of the ancient Near East and the poten-
tial of the cold mashing process. In Liquid Bread: Beer and Brewing in
Cross-cultural Perspective, , W. Schiefenho
¨vel, and H. Macbeth, eds.
(Berghahn Books), pp. 47–54.
61. Liu, L., Wang, J., Rosenberg, D., Zhao, H., Lengyel, G., and Nadel, D.
(2018). Fermented beverage and food storage in 13,000 y-old stone mor-
tars at Raqefet Cave, Israel: Investigating Natuﬁan ritual feasting. Journal
of Archaeological Science: Reports 21, 783–793.
62. Wang, J., Liu, L., Ball, T., Yu, L., Li, Y., and Xing, F. (2016). Revealing a
5,000-y-old beer recipe in China. Proc. Natl. Acad. Sci. USA 113,
63. Farag, M.A., Elmassry, M.M., Baba, M., and Friedman, R. (2019).
Revealing the constituents of Egypt’s oldest beer using infrared and
mass spectrometry. Sci. Rep. 9, 16199.
64. Damerow, P. (2012). Sumerian beer: the origins of brewing technology in
ancient Mesopotamia. Cuneiform Digital Library Journal 2, 1–20.
65. Stika, H.P. (2011). Beer in prehistoric Europe. In Liquid Bread: Beer and
Brewing in Cross-Cultural Perspective, , W. Schiefenho
¨vel, and H.
Macbeth, eds. (Berghahn Books), pp. 55–62.
66. Rosenstock, E., and Scheibner, A. (2017). Fermentierter Brei und vergor-
enes Malz: Bier in der Vorgeschichte Su
¨dwestasiens und Europas.
Mitteilungen der Anthropologischen Gesellschaft Wien 147, 31–62.
67. Guerra-Doce, E. (2015). The origins of inebriation: archaeological evi-
dence of the consumption of fermented beverages and drugs in prehis-
toric Eurasia. J. Archaeol. Method Theory 22, 751–782.
68. McGovern, P., Jalabadze, M., Batiuk, S., Callahan, M.P., Smith, K.E.,
Hall, G.R., Kvavadze, E., Maghradze, D., Rusishvili, N., Bouby, L., et al.
(2017). Early neolithic wine of Georgia in the South Caucasus. Proc.
Natl. Acad. Sci. USA 114, E10309–E10318.
69. Aouizerat, T., Gutman, I., Paz, Y., Maeir, A.M., Gadot, Y., Gelman, D.,
Szitenberg, A., Drori, E., Pinkus, A., Schoemann, M., et al. (2019).
Isolation and characterization of live yeast cells from ancient vessels as
a tool in bio-archaeology. MBio 10, e00388, e19.
70. Basso, R.F., Alcarde, A.R., and Portugal, C.B. (2016). Could non-
Saccharomyces yeasts contribute on innovative brewing fermentations?
Food Res. Int. 86, 112–120.
71. Spitaels, F., Wieme, A.D., Janssens, M., Aerts, M., Daniel, H.-M., Van
Landschoot, A., De Vuyst, L., and Vandamme, P. (2014). The microbial
diversity of traditional spontaneously fermented lambic beer. PLoS
ONE 9, e95384.
72. Spitaels, F., Wieme, A.D., Snauwaert, I., De Vuyst, L., and Vandamme, P.
(2017). Microbial ecology of traditional beer fermentations. In Brewing
Microbiology: Current Research, Omics and Microbial Ecology, , N.A.
Bokulich, and C.W. Bamforth, eds. (Caister Academic Press),
73. Baker, E.P., Peris, D., Moriarty, R.V., Li, X.C., Fay, J.C., and Hittinger,
C.T. (2019). Mitochondrial DNA and temperature tolerance in lager
yeasts. Sci. Adv. 5, v1869.
74. Dornbusch, H.D. (1998). Prost!: The Story of German Beer (Brewers
75. NCBI Resource Coordinators (2017). Database resources of the National
Center for Biotechnology Information. Nucleic Acids Res. 45 (D1),
76. Banchi, E., Ametrano, C.G., Greco, S., Stankovi
c, D., Muggia, L., and
Pallavicini, A. (2020). PLANiTS: a curated sequence reference dataset
for plant ITS DNA metabarcoding. Database (Oxford) 2020, baz155.
12 Current Biology 31, 1–14, December 6, 2021
77. Nilsson, R.H., Larsson, K.-H., Taylor, A.F.S., Bengtsson-Palme, J.,
Jeppesen, T.S., Schigel, D., Kennedy, P., Picard, K., Glo
Tedersoo, L., et al. (2019). The UNITE database for molecular identiﬁca-
tion of fungi: handling dark taxa and parallel taxonomic classiﬁcations.
Nucleic Acids Res. 47 (D1), D259–D264.
78. Ratnasingham, S., and Hebert, P.D. (2007). bold: The Barcode of Life
Data System (http://www.barcodinglife.org). Mol. Ecol. Notes 7,
79. Buchﬁnk, B., Reuter, K., and Drost, H.-G. (2021). Sensitive protein align-
ments at tree-of-life scale using DIAMOND. Nat. Methods 18, 366–368.
80. Huson, D.H., Beier, S., Flade, I., Go
´rska, A., El-Hadidi, M., Mitra, S.,
Ruscheweyh, H.J., and Tappu, R. (2016). MEGAN Community Edition -
interactive exploration and analysis of large-scale microbiome
sequencing data. PLoS Comput. Biol. 12, e1004957.
81. Ondov, B.D., Bergman, N.H., and Phillippy, A.M. (2011). Interactive
metagenomic visualization in a Web browser. BMC Bioinformatics 12,
82. Li, H., and Durbin, R. (2010). Fast and accurate long-read alignment with
Burrows-Wheeler transform. Bioinformatics 26, 589–595.
83. Neukamm, J., Peltzer, A., and Nieselt, K. (2021). DamageProﬁler: fast
damage pattern calculation for ancient DNA. Bioinformatics btab190.
84. Renaud, G., Slon, V., Duggan, A.T., and Kelso, J. (2015). Schmutzi: esti-
mation of contamination and endogenous mitochondrial consensus call-
ing for ancient DNA. Genome Biol. 16, 224.
85. Skoglund, P., Stora
˚, J., Go
¨m, A., and Jakobsson, M. (2013).
Accurate sex identiﬁcation of ancient human remains using DNA shotgun
sequencing. J. Archaeol. Sci. 40, 4477–4482.
86. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N.,
Marth, G., Abecasis, G., and Durbin, R.; 1000 Genome Project Data
Processing Subgroup (2009). The Sequence Alignment/Map format
and SAMtools. Bioinformatics 25, 2078–2079.
87. Weissensteiner, H., Pacher, D., Kloss-Brandst€
atter, A., Forer, L., Specht,
G., Bandelt, H.J., Kronenberg, F., Salas, A., and Scho
¨nherr, S. (2016).
HaploGrep 2: mitochondrial haplogroup classiﬁcation in the era of
high-throughput sequencing. Nucleic Acids Res. 44 (W1), W58-63.
88. Langmead, B., and Salzberg, S.L. (2012). Fast gapped-read alignment
with Bowtie 2. Nat. Methods 9, 357–359.
89. Korneliussen, T.S., Albrechtsen, A., and Nielsen, R. (2014). ANGSD: anal-
ysis of next generation sequencing data. BMC Bioinformatics 15, 356.
90. Katoh, K., Misawa, K., Kuma, K., and Miyata, T. (2002). MAFFT: a novel
method for rapid multiple sequence alignment based on fast Fourier
transform. Nucleic Acids Res. 30, 3059–3066.
91. Ludwig, W., Strunk, O., Westram, R., Richter, L., Meier, H., Yadhukumar,
Buchner, A., Lai, T., Steppi, S., Jobb, G., et al. (2004). ARB: a software
environment for sequence data. Nucleic Acids Res. 32, 1363–1371.
92. Guindon, S., and Gascuel, O. (2003). A simple, fast, and accurate algo-
rithm to estimate large phylogenies by maximum likelihood. Syst. Biol.
93. Altschul, S.F., Gish, W., Miller, W., Myers, E.W., and Lipman, D.J. (1990).
Basic local alignment search tool. J. Mol. Biol. 215, 403–410.
94. Cook, D.E., and Andersen, E.C. (2017). VCF-kit: assorted utilities for the
variant call format. Bioinformatics 33, 1581–1582.
95. Stamatakis, A. (2014). RAxML version 8: a tool for phylogenetic analysis
and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313.
96. Letunic, I., and Bork, P. (2021). Interactive Tree Of Life (iTOL) v5: an online
tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49
97. Alexander, D.H., and Lange, K. (2011). Enhancements to the
ADMIXTURE algorithm for individual ancestry estimation. BMC
Bioinformatics 12, 246.
98. Kessner, D., Chambers, M., Burke, R., Agus, D., and Mallick, P. (2008).
ProteoWizard: open source software for rapid proteomics tools develop-
ment. Bioinformatics 24, 2534–2536.
99. Deutsch, E.W., Mendoza, L., Shteynberg, D., Slagel, J., Sun, Z., and
Moritz, R.L. (2015). Trans-Proteomic Pipeline, a standardized data pro-
cessing pipeline for large-scale reproducible proteomics informatics.
Proteomics Clin. Appl. 9, 745–754.
100. Keller, A., Nesvizhskii, A.I., Kolker, E., and Aebersold, R. (2002). Empirical
statistical model to estimate the accuracy of peptide identiﬁcations made
by MS/MS and database search. Anal. Chem. 74, 5383–5392.
101. Nesvizhskii, A.I., Keller, A., Kolker, E., and Aebersold, R. (2003). A statis-
tical model for identifying proteins by tandem mass spectrometry. Anal.
Chem. 75, 4646–4658.
102. Hoopmann, M.R., Winget, J.M., Mendoza, L., and Moritz, R.L. (2018).
StPeter: seamless label-free quantiﬁcation with the trans-proteomic
pipeline. J. Proteome Res. 17, 1314–1320.
103. Eng, J.K., Jahan, T.A., and Hoopmann, M.R. (2013). Comet: an open-
source MS/MS sequence database search tool. Proteomics 13, 22–24.
104. Gurdeep Singh, R., Tanca, A., Palomba, A., Van der Jeugt, F.,
Verschaffelt, P., Uzzau, S., Martens, L., Dawyndt, P., and Mesuere, B.
(2019). Unipept 4.0: functional analysis of metaproteome data.
J. Proteome Res. 18, 606–615.
105. Stuiver, M., and Polach, H.A. (1977). Discussion reporting of 14C data.
Radiocarbon 19, 355–363.
106. Reimer, P.J., Austin, W.E.N., Bard, E., Bayliss, A., Blackwell, P.G., Bronk
Ramsey, C., Butzin, M., Cheng, H., Edwards, R.L., Friedrich, M., et al.
(2020). The IntCal20 Northern Hemisphere radiocarbon age calibration
curve (0–55 cal kBP). Radiocarbon 62, 725–757.
107. Pearsall, D.M. (2015). Paleoethnobotany: A Handbook of Procedures
(Left Coast Press).
108. Cappers, R.T., Bekker, R.M., and Jans, J.E. (2006). Digitale zadenatlas
van Nederland (Barkhuis Publishing).
109. Jacomet, S. (2006). Bestimmung von Getreidefunden aus arch-
aologischen Ausgrabungen (Universit€
110. Neef, R., Cappers, R.T., and Bekker, R.M. (2012). Digital Atlas of
Economic Plants in Archaeology (Barkhuis).
111. Hohmann, B., Deutschmann, F., and Gassner, G. (1989). Mikroskopische
Untersuchungen pﬂanzlicher Lebensmittel: mit einem Kapitel u
mikroskopische Untersuchung der wichtigsten als Futtermittel verwen-
deten tierischen Produkte (Gustav Fischer Verlag).
112. Tang, J.N., Zeng, Z.G., Wang, H.N., Yang, T., Zhang, P.J., Li, Y.L., Zhang,
A.Y., Fan, W.Q., Zhang, Y., Yang, X., et al. (2008). An effective method for
isolation of DNA from pig faeces and comparison of ﬁve different
methods. J. Microbiol. Methods 75, 432–436.
113. Kircher, M., Sawyer, S., and Meyer, M. (2012). Double indexing over-
comes inaccuracies in multiplex sequencing on the Illumina platform.
Nucleic Acids Res. 40, e3.
114. Meyer, M., Kircher, M., Gansauge, M.T., Li, H., Racimo, F., Mallick, S.,
Schraiber, J.G., Jay, F., Pru
¨fer, K., de Filippo, C., et al. (2012). A high-
coverage genome sequence from an archaic Denisovan individual.
Science 338, 222–226.
115. Rosenbloom, K.R., Armstrong, J., Barber, G.P., Casper, J., Clawson, H.,
Diekhans, M., Dreszer, T.R., Fujita, P.A., Guruvadoo, L., Haeussler, M.,
et al. (2015). The UCSC Genome Browser database: 2015 update.
Nucleic Acids Res. 43, D670–D681.
116. Andrews, R.M., Kubacka, I., Chinnery, P.F., Lightowlers, R.N., Turnbull,
D.M., and Howell, N. (1999). Reanalysis and revision of the Cambridge
reference sequence for human mitochondrial DNA. Nat. Genet. 23, 147.
117. Knights, D., Kuczynski, J., Charlson, E.S., Zaneveld, J., Mozer, M.C.,
Collman, R.G., Bushman, F.D., Knight, R., and Kelley, S.T. (2011).
Bayesian community-wide culture-independent microbial source
tracking. Nat. Methods 8, 761–763.
118. Marchione, D.M., Ilieva, I., Devins, K., Sharpe, D., Pappin, D.J., Garcia,
B.A., Wilson, J.P., and Wojcik, J.B. (2020). HYPERsol: high-quality data
Current Biology 31, 1–14, December 6, 2021 13
from archival FFPE tissue for clinical proteomics. J. Proteome Res. 19,
119. Martens, L., Chambers, M., Sturm, M., Kessner, D., Levander, F.,
Shofstahl, J., Tang, W.H., Ro
¨mpp, A., Neumann, S., Pizarro, A.D., et al.
(2011). mzML–a community standard for mass spectrometry data. Mol.
Cell. Proteomics 10, 000133.
120. Moosa, J.M., Guan, S., Moran, M.F., and Ma, B. (2020). Repeat-preser-
ving decoy database for false discovery rate estimation in peptide iden-
tiﬁcation. J. Proteome Res. 19, 1029–1036.
121. Shteynberg, D., Deutsch, E.W., Lam, H., Eng, J.K., Sun, Z., Tasman, N.,
Mendoza, L., Moritz, R.L., Aebersold, R., and Nesvizhskii, A.I. (2011).
iProphet: multi-level integrative analysis of shotgun proteomic data im-
proves peptide and protein identiﬁcation rates and error estimates.
Mol. Cell. Proteomics 10, 007690.
122. Perez-Riverol, Y., Csordas, A., Bai, J., Bernal-Llinares, M.,
Hewapathirana, S., Kundu, D.J., Inuganti, A., Griss, J., Mayer, G.,
Eisenacher, M., et al. (2019). The PRIDE database and related tools
and resources in 2019: improving support for quantiﬁcation data.
Nucleic Acids Res. 47 (D1), D442–D450.
14 Current Biology 31, 1–14, December 6, 2021
KEY RESOURCES TABLE
REAGENT or RESOURCE SOURCE IDENTIFIER
Paleofeces sample from the Bronze Age This study 2610
Paleofeces sample from the Iron Age This study 2604
Paleofeces sample from the Iron Age This study 2611
Paleofeces sample from the Baroque time This study 2612
Chemicals, peptides, and recombinant proteins
Sodium phosphate Sigma-Aldrich Cat #342483
Trypsin gold Promega Cat # V528A
Critical commercial assays
S-Trap ProtiFi Cat #K02-mini-10
Paleofeces metagenomic shotgun datasets This study ENA: PRJEB44507
Chloroplast genome database N/A https://www.ncbi.nlm.nih.gov/genome/organelle
Fungal ITS database
BOLD system databases
Software and algorithms
DeDup tool N/A https://github.com/apeltzer/DeDup
Molecular sex determination
python package scikit-bio N/A http://scikit-bio.org/
FastQ Screen N/A https://github.com/StevenWingett/FastQ-Screen
ARB software package
Picard tools N/A https://broadinstitute.github.io/picard/
GATK4 N/A https://gatk.broadinstitute.org/hc
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