Dairying enabled Early Bronze Age Yamnaya steppe expansions

Abstract

During the Early Bronze Age, populations of the western Eurasian steppe expanded across an immense area of northern Eurasia. Combined archaeological and genetic evidence supports widespread Early Bronze Age population movements out of the Pontic–Caspian steppe that resulted in gene flow across vast distances, linking populations of Yamnaya pastoralists in Scandinavia with pastoral populations (known as the Afanasievo) far to the east in the Altai Mountains1,2 and Mongolia3. Although some models hold that this expansion was the outcome of a newly mobile pastoral economy characterized by horse traction, bulk wagon transport4–6 and regular dietary dependence on meat and milk5, hard evidence for these economic features has not been found. Here we draw on proteomic analysis of dental calculus from individuals from the western Eurasian steppe to demonstrate a major transition in dairying at the start of the Bronze Age. The rapid onset of ubiquitous dairying at a point in time when steppe populations are known to have begun dispersing offers critical insight into a key catalyst of steppe mobility. The identification of horse milk proteins also indicates horse domestication by the Early Bronze Age, which provides support for its role in steppe dispersals. Our results point to a potential epicentre for horse domestication in the Pontic–Caspian steppe by the third millennium bc, and offer strong support for the notion that the novel exploitation of secondary animal products was a key driver of the expansions of Eurasian steppe pastoralists by the Early Bronze Age. Analysis of ancient proteins suggests that Early Bronze Age dairying and horse domestication catalysed eastern Yamnaya migrations.

Full text

Nature | Vol 598 | 28 October 2021 | 629
Article
Dairying enabled Early Bronze Age Yamnaya
steppe expansions
Shevan Wilkin1,2 ✉, Alicia Ventresca Miller1,3, Ricardo Fernandes1,4,5, Robert Spengler1,
William T.-T. Taylor1,6, Dorcas R. Brown7, David Reich8,9,10,1 1, Douglas J. Kennett12,
Brendan J. Culleton13, Laura Kunz14, Claudia Fortes14, Aleksandra Kitova15, Pavel Kuznetsov16,
Andrey Epimakhov17,18, Victor F. Zaibert19, Alan K. Outram20, Egor Kitov21,22,
Aleksandr Khokhlov16, David Anthony7,11 & Nicole Boivin1,23,24,25 ✉
During the Early Bronze Age, populations of the western Eurasian steppe expanded
across an immense area of northern Eurasia. Combined archaeological and genetic
evidence supports widespread Early Bronze Age population movements out of the
Pontic–Caspian steppe that resulted in gene ow across vast distances, linking
populations of Yamnaya pastoralists in Scandinavia with pastoral populations (known
as the Afanasievo) far to the east in the Altai Mountains1,2 and Mongolia3. Although
some models hold that this expansion was the outcome of a newly mobile pastoral
economy characterized by horse traction, bulk wagon transport4–6 and regular dietary
dependence on meat and milk5, hard evidence for these economic features has not
been found. Here we draw on proteomic analysis of dental calculus from individuals
from the western Eurasian steppe to demonstrate a major transition in dairying at the
start of the Bronze Age. The rapid onset of ubiquitous dairying at a point in time when
steppe populations are known to have begun dispersing oers critical insight into a
key catalyst of steppe mobility. The identication of horse milk proteins also indicates
horse domestication by the Early Bronze Age, which provides support for its role in
steppe dispersals. Our results point to a potential epicentre for horse domestication
in the Pontic–Caspian steppe by the third millennium , and oer strong support for
the notion that the novel exploitation of secondary animal products was a key driver
of the expansions of Eurasian steppe pastoralists by the Early Bronze Age.
The pastoralist populations of the Eurasian steppe have long been a
source of archaeological and historical fascination. Although the later
history of steppe pastoralists—including the rise of the Xiongnu and
Mongol empires in the east—is reasonably well-established, the early
emergence and expansion of pastoralist groups in the steppe occurred
before the historical era and has largely been reconstructed on the
basis of archaeological and linguistic data
1,6,7
. More recently, ancient
DNA evidence has provided insights into early steppe populations,
revealing evidence for a major influx of steppe ancestry into Europe in
the Late Neolithic that effectively transformed the European genetic
landscape
1,2,8
. Archaeogenetic data also link these same populations
(referred to as Yamnaya) with pastoral Afanasievo populations far to the
east in the Altai Mountains1,2 and Mongolia3. Combined archaeological
and genetic evidence supports widespread population movements in
the Early Bronze Age (about 3300 to 2500 ) from the Pontic–Caspian
steppe that resulted in gene flow across vast distances, linking Yamnaya
pastoralist populations in Scandinavia with groups that expanded
into Siberia9.
Although the Yamnaya expansions are well-established, the driving
forces behind them remain unclear. A widely cited theory holds that
the early spread of herders across Eurasia was facilitated by a newly
mobile pastoral economy that was made possible by a combination
of horse traction and bulk wagon transport
4–6
. Together with regular
dietary dependence on meat and milk
5
, this opened up the steppe to
exploitation and occupation by pastoralist communities. Yet for all its
persuasiveness, the model remains inadequately supported by direct
https://doi.org/10.1038/s41586-021-03798-4
Received: 4 April 2021
Accepted: 5 July 2021
Published online: 15 September 2021
Open access
Check for updates
1Department of Archaeology, Max Planck Institute for the Science of Human History, Jena, Germany. 2Institute for Evolutionary Medicine, Faculty of Medicine, University of Zürich, Zürich,
Switzerland. 3Department of Anthropology, University of Michigan, Ann Arbor, MI, USA. 4School of Archaeology, University of Oxford, Oxford, UK. 5Faculty of Arts, Masaryk University,
Brno-střed, Czech Republic. 6Department of Anthropology, University of Colorado, Museum of Natural History, Boulder, CO, USA. 7Department of Anthropology, Hartwick College, Oneonta, NY,
USA. 8Department of Genetics, Harvard Medical School, Boston, MA, USA. 9Broad Institute of Harvard and MIT, Cambridge, MA, USA. 10Howard Hughes Medical Institute, Harvard Medical
School, Boston, MA, USA. 11Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA. 12Department of Anthropology, University of California, Santa Barbara, CA,
USA. 13Institutes of Energy and the Environment, The Pennsylvania State University, University Park, PA, USA. 14Functional Genomics Centre Zürich, University of Zürich/ETH, Zürich, Switzerland.
15Center for Egyptological Studies, Russian Academy of Sciences, Moscow, Russian Federation. 16Samara State University of Social Sciences and Education, Samara, Russian Federation. 17South
Ural State University, Chelyabinsk, Russian Federation. 18Institute of History and Archaeology, Ural Branch of the Russian Academy of Sciences, Yekaterinburg, Russian Federation. 19Institute of
Archaeology and Steppe Civilizations, Al-Farabi Kazakh National University, Almaty, Kazakhstan. 20Department of Archaeology, University of Exeter, Exeter, UK. 21Center of Human Ecology,
Institute of Ethnology and Anthropology, Russian Academy of Sciences, Moscow, Russian Federation. 22Faculty of History, Archaeology, and Ethnology, Al-Farabi Kazakh National University,
Almaty, Kazakhstan. 23School of Social Science, The University of Queensland, Brisbane, Queensland, Australia. 24Department of Anthropology and Archaeology, University of Calgary, Calgary,
Alberta, Canada. 25Department of Anthropology, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA. ✉e-mail: wilkin@shh.mpg.de; boivin@shh.mpg.de
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630 | Nature | Vol 598 | 28 October 2021
Article
archaeological or biomolecular data. Archaeological evidence for
the use of bulk wagon transport by the Eneolithic Maikop and Early
Bronze Age Yamnaya groups exists in the form of carts and bridling
materials10, but two other critical components of the model—a reliance
on domesticated horses and ruminant dairying—remain archaeologi-
cally unproven.
The domestication status of Eurasian horses has long been
debated
5,6,11–14
, and recent archaeogenetic findings
15
have shifted our
understanding of early horses at the Eneolithic site of Botai in north-
ern Kazakhstan by identifying them as Equus przewalskii rather than
the modern-day domestic horse (Equus caballus)
5,6
. Although horses
do appear in Early Bronze Age assemblages on the steppe, it remains
unclear whether they were being ridden
7,11,16,17
, or indeed whether they
were part of pastoral herds or simply hunted. On the eastern Eurasian
steppe, growing evidence suggests that horses were not ridden
11,12,18
or milked19 before about 1200, and horses may have been uncom-
mon in early pastoralist assemblages
20
. Early ruminant dairying on the
western steppe has also been inadequately demonstrated, as human
stable isotope data from the region suggests—but cannot confirm—
dairy consumption
21,22
. Palaeoproteomics, which is the only method
that is able to evince individual dairy consumption (rather than milk
production) and provide taxonomic resolution, has so far been mini-
mally applied to steppe populations. Across Yamnaya and Afanasievo
populations, dairying evidence is available only for a few individuals
from the eastern steppe who have ancestry from western steppe groups;
the earliest individual provides only a taxonomically ambiguous rumi-
nant (Ovis/Bos)peptide result19.
To address the heavily debated question of what drove Yamnaya
expansions across the steppe6,23–25, we conducted proteomic analysis
of dental calculus sampled from 56steppe individuals who span the
Eneolithic to Late Bronze Age, and who date from between 4600 and
1700. Our samples from the Eneolithic (about 4600 to 3300) are
from 19individuals from 5sites: Murzikha2 (6 individuals), Khvalynsk1
and Khvalynsk2 (9individuals), Ekaterinovka Mys (1individual), Leb-
yazhinka5 (1individual) and Khlopkov Bugor (2individuals) (Fig.1,
Supplementary Fig.1a). Ancient DNA results from Khvalynsk and other
Eneolithic sites in the Volga and northern Caucasus
2,7,26
support the
existence of an Eneolithic population across this region that was geneti-
cally similar to the Yamnaya population, but who lacked the additional
farmer (Anatolian) ancestry that would arrive later on the steppe
7
. Pub-
lished stable isotope and archaeological studies applied to Eneolithic
populations from the Pontic region point to an economy based on
fishing, the gathering of local plants and the keeping of domesticated
animals
6,21,27,28
.Given the importance of the horse in reconstructions of
early pastoralist expansions, we also examined dental calculus from two
individuals from the well-known site of Botai. With faunal assemblages
dominated by horse remains
11–13
and early lipid studies of ceramics
indicating horse milking at the site by 3500
13
, the site is central to
discussions of early horse milking and dairying in the Eurasian steppe.
Our Bronze Age samples come from 35individuals from 20sites in the
Volga–Ural steppes that can be divided into two chronological groups:
the Early Bronze Age (about 3300 to 2500) era of Yamnaya-culture
mobile pastoralism
29,30
; and the Middle–Late Bronze Age transition
(about 2500–1700), when chariots, fortified settlements and
new western-derived influence genetic ancestries appeared with the
Sintashta culture
31
. The cemetery sites and the number of individu-
als (in parentheses) from the Early Bronze Age are: Krasikovskyi1 (2)
Krasnokholm3 (1), Krivyanskiy9 (2), Kutuluk1 (2), Leshchevskoe1 (1),
Lopatino1 (1), Mustayevo5 (2), Nizhnaya Pavlovka (1), Panitskoe (1),
Podlesnoe (1), Pyatiletka (1) and Trudovoy (1); and, from the Middle–
Late Bronze Age transition, Bolshekaraganskyi (1), Kalinovsky1 (2),
Kamennyi Ambar5 (3), KrasikovskyiI (1), Krivyanskiy9 (3), Lopatino1
and Lopatino2 (2), Potapovka1 (1), Shumayevo2 (1) and Utevka6 (5)
(Supplementary Fig.1b, c). Archaeological and stable isotope find
-
ings6,22 indicate that the diet of Early Bronze Age Yamnaya groups was
focused on herd animals, specifically cattle, sheep and goat. Horse
remains also appear in quantity on a few steppe archaeological sites,
but the status of Early Bronze Age horses—whether domesticated or
hunted—has remained unclear
32,33
. The Middle–Late Bronze Age transi-
tion saw a shift to greater horse exploitation and chariot use, within
the context of an ongoing dietary focus on domesticated livestock.
Of the 56ancient human dental calculus samples we tested, 55 were
successfully extracted and produced identifiable protein data. Of these
55, 48 (87%) were determined to have strong signals for preservation
through an assessment of proteins commonly found within the oral
cavity; detailed information on this assessment is provided in Methods,
Supplementary Table3.
The earliest samples in our study (about 4600 to 4000) are from
5Eneolithic sites in southwestern Russia located on or close to the
Volga River and its tributaries. Of the samples from these 19individu-
als, 11 were successfully extracted and well-preserved, and 10of these
did not show any evidence for dairy consumption (Figs.1a, 2a). The
calculus of one individual contained two peptides specific to bovine
(Bos, Bubalis and Bison) α-S1-casein, a milk curd protein. However, as
the only dietary peptides contained in this sample were specific to
casein and evidence for the most commonly recovered dairy protein
β-lactoglobulin (BLG) was lacking, dairy consumption in this individual
could not be confidently confirmed. In general, casein peptides appear
to preserve more poorly than BLG in archaeological calculus, and thus
are most often identified together with other dairy protein peptides
rather than alone
19,34–37
. Additionally, within the two identified casein
peptides, there is only one possible amino acid deamidation site, which
renders any estimation of the antiquity of these peptides exceedingly
challenging. A previously published paper
38
demonstrates the extreme
variability in deamidation of amino acids in milk proteins, which fur-
ther limits our ability to confirm the authenticity of this dairy finding.
The calculus from the two additional Botai individuals demonstrated
adequate preservation, but also lacked evidence for dairy consumption.
For the Early Bronze Age individuals (dating to the onset of the Yam-
naya cultural horizon), dairy peptides were recovered from 15 of the
16individual calculus samples we analysed (Fig.1b, 2b). All 15indi-
viduals with positive dairy results contained multiple peptide spec-
tral matches to ruminant dairy proteins (including BLG), and some
individuals also contained α-S1 casein, α-S2-casein or both. Although
many of the milk peptides were only specific to higher taxonomic levels
(such as Pecora, an infraorder within Artiodactyla (cow, sheep, goat,
buffalo, yak, reindeer, deer and antelope)), others enabled more spe-
cific taxonomic classifications, including to family, genus or species.
We found Ovis, Capra and Bos attributions, and the calculus of many
individuals contained dairy peptides from several species. Notably,
we identified Equus milk peptides from the protein BLGI in 2 of 17Early
Bronze Age individuals, both from the southwestern site of Krivyan-
skiy9 (3305 to 2633 calibrated years  (Supplementary Table5 pro-
vides individual accelerator mass spectrometry dating information)).
Although the genus Equus includes horse, donkey and kiang, only horse
species (E.caballus, E.przewalskii, Equus hemionus and Equus ferus)
are archaeologically attested in the steppe in the Early Bronze Age,
supporting the Equus identification as horse.
For the Middle–Late Bronze Age transition, calculus samples from 15
of 19 individuals were positive for evidence of ruminant milk consump-
tion (Figs.1c, 2c). Similar to the Early Bronze Age, we identified BLG,
α-S1-casein and α-S2-casein, as well as the whey protein α-lactalbumin.
Taxonomic identifications again ranged from the Pecora infraorder to
genus-level identifications (including Ovis and Bos), but without any
specific identifications for Capra or Equus. Supplementary Table4 pro-
vides a full accounting of all identified dairy proteins for each individual.
Overall, our results point to a clear and marked shift in milk con-
sumption patterns between the Eneolithic and Early Bronze Age in the
Pontic–Caspian Steppe. The majority of Eneolithic individuals (10 out
of 11 (92%)) in our assemblage lack any evidence for milk consumption,
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Nature | Vol 598 | 28 October 2021 | 631
c
Krasikovskyi
Utevka 6
Kriviyanskiy IX
Kalinovka 2/2
1/3
1/1
1/1
Kammenyi Abmar
Bolshekaraganskyi1/1
1/1
Lopatino II 1/1
b
Kriviyanskiy IX
Panitskoe1/1
2/2
Lopatino I1/1
Nizhnaya Pavlovka 1/1
Kutuluk I 2/2 Krasikovskyi 1/1
Pyatileka 1/1
Trudovoy1/1Krasnokholm III 1/1
Mustayevo V 1/2
Podlesnoe1/1
Leshchevskoe 4/5
Kholpkovsky Bugor
Khavalynsk 1 and 2
Murzikha 20/2
0/6
a
0/2
Eneolithic sites People with dairy/total per site Early Bronze Age sites Middle/Late Bronze Age sites
Fig. 1 | Map sh owing sites t hat yielded i ndividual s with prese rved ancien t
proteins. a–c, Eneolithic (a), Early Bron ze Age (b) and Middle–L ate Bronze
Age (c) sites in the Pont ic–Caspian re gion, showing t he number of indiv iduals
with a posi tive dairy ident ificatio n out of the total nu mber of individ uals with
preser ved ancient prote ins for each site. S trong evidenc e of preservat ion of
equine or rum inant milk protein i dentifie rs are depicte d with black anim al
icons; the sin gle individual w ith equivocal ly identifi ed caseinpept ides is shown
with a grey ic on. For a map of all sites (in cluding those w ithout prese rved
proteins), see Supp lementar y Fig.1. Base maps w ere created usin g QGIS 3.1 2
(https://qgis.org/en/site/), and use Natural Ear th vector map d ata from ht tps: //
www.naturalearthdata.com/downloads/. The horseimage is repro duced from
ref. 33; shee p silhouette, pu blic domain (https://thenounproject.com/
icon/12538/).
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632 | Nature | Vol 598 | 28 October 2021
Article
whereas the overwhelming majority of Early Bronze Age individuals
(15 out of 16 (94%)) contain ample proteomic evidence for dairy con-
sumption in their calculus. Although a single individual at Eneolithic
Khvalynsk with somewhat equivocal evidence for the consumption
of dairy from cattle may indicate small-scale dairy use, the reliability
of this single identification is questionable. Our findings suggest that
regular dairy consumption in the Pontic–Caspian Steppe began only
at the time of the Eneolithic-to-Early Bronze Age transition. Although
neighbouring Eneolithic farming populations in Europe appear to have
been dairying39, those living across the steppe frontier did not adopt
milking practices, which suggests the presence of a cultural frontier.
The proteomic data are in broad agreement with findings from lipid
analyses in the Ukraine (Supplementary Information section 2, Sup-
plementary Table2). They also agree with stable isotope analysis of
individuals from Eneolithic-to-Bronze-Age Samara showing a corre-
sponding shift from a heavy reliance on fish, deer and other riverine
forest (C3) resources to a greater reliance on terrestrial and grassland
(C3 and C4) animal products22,40.
One important advantage of proteomic data is their ability, in some
cases, to provide species-specific protein identifications. Our study
offers evidence for the Bronze Age milking of sheep, goat and cattle,
which fits with evidence for the herding of these animals. The lush
valleys of the Pontic–Caspian Steppe provided ample forage and hydra-
tion for mixed herds of arid-adapted sheep and goat, as well as more
water-reliant cattle
41,42
. Although a recent study has shown that lactase
persistence—which results from the presence of an allele that enables
production of lactase into adulthood—was rare in steppe populations
of the Early Bronze Age43, we find that the western steppe community
was regularly consuming dairy that could have included fresh milk and/
or other processed products with reduced lactose, such as yogurts,
cheeses or fermented milk beverages.
Our study of dental calculus from the Eneolithic site of Botai to the
east, where early horse milking has been suggested by lipid analysis
(albeit equivocally
44
), did not yield milk proteins. Although two samples
are insufficient for drawing broad conclusions, this finding does not sup-
port widespread milk consumption at the site13,45,46. However, two cal-
culus samples from Early Bronze Age individuals of the Pontic–Caspian
region do provide evidence for the consumption of horse milk. Com-
bined with archaeogenetic evidence15 that places the Botai horses
on a different evolutionary trajectory than the domesticated DOM2
E.caballus lineage, this finding—if backed up by further sampling and
analysis—would seem to firmly shift the focus of sustained early horse
domestication on the Eurasian steppe to the Pontic–Caspian region.
So far, the oldest horse specimens that carry the DOM2 lineage date
to between 2074 to 1625 calibrated years , at which time the line-
age is archaeologically attested in present-day Russia, Romania and
Georgia
15
. Our identification of—to our knowledge—the earliest horse
milk proteins yet identified on the steppe or anywhere else reveals the
presence of domestic horses in the western steppe by the Early Bronze
Age, which suggests that the region (where the first evidence for horse
chariots later emerged at about 2000 
47
) may have been the initial
epicentre for domestication of the DOM2 lineage during the late fourth
or third millennium .
Overall, our findings offer strong support to the notion of a second-
ary products revolution
48,49
in the Eurasian steppe by the Early Bronze
Age. This change in subsistence economy, indicated by dietary stable
isotopes in human bones as well as by proteomics, was accompanied by
the widespread abandonment of Eneolithic riverine settlement sites,
the appearance of kurgan cemeteries in the previously unexploited arid
plateaus between the river valleys, and the inclusion of wheeled vehi-
cles and occasional horse bones in Yamnaya graves. At the same time,
the steppe Yamnaya population expanded westward into Europe and
eastward to the Altai Mountains (a range of 6,000km)
1,3,50
. Although we
cannot offer direct insight into the question of horse riding or traction
on the basis of our data, evidence for milked horses certainly makes
horse domestication more likely, and may indicate that horses had a role
in the spread of Yamnaya groups. The triad of animal traction, dairying
and horse domestication appears to have had an instrumental role in
transforming Pontic–Caspian economies and opening up the broader
steppe to human habitation by the Early Bronze Age. If some or even all
of these elements were present before the Bronze Age, it is only from
this latter period that we witness their intensive and sustained exploita-
tion amongst numerous groups. Although other factors will no doubt
also have been important, the emergence of more mobile, pastoralist
societies adapted to survival on the cold and arid steppe—where horses
may have opened up snow-covered pasturage for other animals
18
, and
milk would have provided a sustained source of protein, nutrients
and fluids—was undoubtedly critical to the expansion of Bronze Age
pastoralists such the Yamnaya groups.
Online content
Any methods, additional references, Nature Research reporting sum-
maries, source data, extended data, supplementary information,
BOTAI 1
BOTAI 2
KB N-7
KB N-8
KHA1 N-39
KHA1 N-61/62
KHA2 N-1
KHA2 N-2
KHA2 N-4
MUR2 K-1 N-130
MUR2 N-130.1
MUR2 N-94/7
MUR2 N-98
0102030
PSM count
0102
03
0
PSM count
Individual
Individual
Individual
a
KRA3 K.1 N-1
KRI9 K.2 N-2
KRI9 K.4 N-21
KRS K.1 N-1
KRS K.2 N-1
KUT1 K.3 N-4
KUT1 K.4 N-1
LES K.1 N-1
LOP1 K.3p N-1
MUS5 K.1 N-1
MUS5 NK.8 N-2
NP K.2 N-3
PAN N-6
POD K.1 N-3
PYA K.6 N-2
TRU K.5 N-1
01020304050
PSM count
b
BKK K.25 Pit-24
KAL K.1 N-4
KAL1 K.1 N-6
KB5 K.2 A 987
KB5 K.2 MR11 CK-1 A944
KB5 K.4 MR5 CK-2 A 937
KRI9 K.1 N-30
KRI9 K.5 N-6
KRS K.3 N-1
LOP K.3 N-2
LOP2 K.1 N-1 K.2
POT K.5 N-3
SHU2 K.6 N-1
UTE6 K.4 N-1
UTE6 K.4 N-5
UTE6 K.4 N-6
UTE6 K.6 N-2 K-1
UTE6 K.6 N-6
c
Taxonomy
Pecora
Bovidae
Caprinae
Ovis/Bovinae
Ovis
Capra
Bos
Equus
Fig. 2 | Hist ogram of taxon omic speci ficity o f dairy pep tide spec tral matche s per indivi dual. a–c, Histogra ms for individual s with evidenc e for consumption
of dairy, from the En eolithic (a), Early Bronze Ag e (b) and Middle and Lat e Bronze Age (c). PSM, pept ide spectra l match.
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Nature | Vol 598 | 28 October 2021 | 633
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Article
Methods
No statistical methods were used to predetermine sample size. The
experiments were not randomized, and investigators were not blinded
to allocation during experiments and outcome assessment.
Protein extraction and data analysis methods
Sample collection. Dental calculus was collected at the Department of
Archaeology at Samara State University and the Museum at the Institute
of Plant and Animal Ecology at the Ural Branch of the Russian Academy
of Sciences. Calculus was collected in sterile tubes and hand-carried to
the Max Planck Institute for the Science of Human History (MPI-SHH)
in Jena. Calculus from the Botai site was sampled at the site; it was col-
lected in sterile tubes and shipped to MPI-SHH. Each calculus sample
was removed using a clean dental scaler, and implements were cleaned
with alcohol swabs between the sampling of different individuals. Con-
tamination from modern human keratin and environmental collagen
that may have occurred owing to previous sampling for ancient DNA
or stable isotope analysis was reduced through the use of nitrile gloves
during collection, and samples were taken directly from the teeth into
clean, 2-ml Eppendorf tubes, in which they were stored until protein
extraction in the Palaeoproteomics Laboratory at the MPI-SHH.
Protein extraction. For samples with a ‘Z’ designation, proteins were
extracted using a modified low-volume filter-aided sample prepara-
tion that has previously been described
35
. To decrease contamination,
1 ml of 0.5 M EDTA was then added to each sample tube, samples were
rotated for 5 min followed by centrifugation at 20,000 rcf for 10 min
to remove the any contamination on the outer layer of calculus; the
supernatant was then removed and retained. Then, 1 ml of 0.5 M EDTA
was added to each decontaminated sample, and the sample was al-
lowed to decalcify on a rotator for 5–7 days at room temperature until
completion. After demineralization, samples were centrifuged at top
speed (20,000 rcf) for 5 min. Eight hundred µl of EDTA supernatant
was removed andstored for future analysis. Separately, 50 µl of urea
solution (8 M) was added to a 30-kDa Millipore Microcon filter unit.
Samples were denatured, reduced and alkylated with 30 µl of sodium
dodecyl sulfate (SDS)-lysis buffer (4% w/v SDS, 100 mM Tris/HCL pH 8.2
and 0.1 M DTT), incubated at 95°C for 5 min, and 100 µl of iodoaceta-
mide (IAA) solution (0.5 M IAA and 8 M UA) was added to the filter units
and was mixed at 600 rpm for 1 min in the dark. Following incubation,
the samples were centrifuged at 14,000g for 10 min. Two hundred µl
of UA (8 M) was added to the filter unit, followed by the lysed sample
supernatant and units centrifuged for 20 min at 14,000g. UA was used
twice to remove the IAA and followed by centrifugation for 12–15 min
at top speed. One hundred µl of 0.5 M NaCl was added to each filter
unit, spun for 12 min at 14,000g. This step was repeated and the flow-
through discarded. The filter units were transferred to new units, and
120 µl of trypsin solution (3 µl of 0.4 µg µl−1 trypsin in 117 µl of 0.05 M
triethylammoniumbicarbonate) was added to each unit. Units were
thermomixed at 600 rpm for 1 min and then incubated overnight at
37°C. Following digestion, samples centrifuged for 20 min at 14,000g
and acidified with 5% TFA to a pH of <2.
Stage tips (Thermo Scientific StageTips 200 µl C18 tips) were cleaned
with 100% methanol, followed by 60% acetonitrile (ACN) solution (60%
ACN, 0.1% TFA and 39.9% ddH
2
O). Then, each was equilibrated with
2 washes of 150 µl of 3% ACN solution (3% ACN, 0.1% TFA and 96.9%
ddH
2
O). Samples were then loaded onto the tips and twice washedwith
3% ACN and 0.1% TFA and the flowthrough discarded. Peptides were col-
lected in new tubes from the stage tip with 150 µl 60% ACN solution and
each was dried in an evaporator and stored at −80°C until liquid chro-
matography with tandem mass spectrometry (LC–MS/MS) analysis.
Samples with a ‘DA’ were extracted using a single pot, solid phase
enhanced sample preparation (SP3) modified for archaeological den-
tal calculus samples. One millilitre of 0.5 M EDTA was added to each
sample, and samples were then placed on a rotator for 5 min and cen-
trifuged at top speed (20,000 rcf) for 10 min. The entire supernatant
was removed and retained, and an additional 500 µl of 0.5 M EDTA for
demineralization was added and samples were placed back onto the
rotator for 5–7 days.
Following demineralization, samples were centrifuged at 20,000 rcf
for 10 min, and 400 µl of the supernatant was removed and retained.
To increase denaturation, reduce and alkylate, 200 µl of 6 M guanidine
hydrochloride and 30 µl of 40 mM CAA, 100 mM TCEP were added
to the pellet and remaining supernatant and mixed through resus-
pension. Samples were then placed on a heating block (Cell Media,
Thermoshaker Pro) and heated to 99°C for 10 min. Upon removing
samples from heat, 20 µl of a20 µg µl−1 50/50 mixture of hydrophilic
and hydrophobic SeraMag SpeedBeads was added to each sample, and
to increase protein–bead adhesion, 350 µl of 100% ethanol was then
added to each tube. Samples were then placed on the ThermoMixer
for 5 min at 1,000 rpm at 24°C. Upon removal from the ThermoMixer,
tubes were placed on a magnetic rack, which moved the beads to the
wall side of the tube. With the proteins now adhering to the beads,
the entire supernatant was removed and retained for possible later
analysis. To remove any non-proteinaceous materials, 3 washes of
200 µl 80% ethanol were carried out. Once the beads were thoroughly
washed, 100 µl of 100 mM ammonium bicarbonate was added to each
tube, as well as 0.2 µg of trypsin. Samples were then placed on the Ther-
moMixer at 37°C at 750 rpm. After 10 min, samples were resuspended
and left on the ThermoMixer overnight (18 h) for protein digestion.
Following digestion, sample tubes were centrifuged at 20,000 rcf for
1 min, and then placed back onto the magnetic rack. The entire super-
natant was removed and transferred to a clean tube. Each sample was
then acidified with 5% TFA to reduce the pH to <2. Acidified sample
tubes were again centrifuged at top speed for five minutes to push
any remaining non-proteinaceous materials into a pellet and improve
stage tip clean up. Stage tips were prepared with 150 µl MeOH, and
centrifuged at 2,000 rcf, followed by 60% ACN, 0.1% TFA and another
round of centrifugation. To equilibrate the stage tips, we added
150 µl 3% ACN, 0.1% TFA, followed by another centrifugation step, and
these steps were then repeated. Samples were added to each stage
tip, and centrifuged for 3 min at 2000 rcf, or until the entire sample
had passed the stage tip. This was followed by an additional 2 rinse
steps with 3% ACN, 0.1% TFA . Samples were not eluted at the MPI-SHH,
but retained on stage tips in the −20°C freezer until shipment to the
Functional Genomics Center Zürich at the University of Zürich. A full
detailed protocol is available at protocols.io (https://doi.org/10.17504/
protocols.io.bfgrjjv6).
High performance LC–MS/MS analysis. The samples were sent on
stage tips to the Functional Genomics Center. There, the peptides were
eluted from the stage tips and dried. After resolubilization in 10 µl of
3% ACN, 0.1% formic acid, the peptide level was normalized using the
DeNovix DS-11 Series Spectrophotometer.
LC–MS/MS analysis. For samples with a laboratory identifier that
starts with Z (Supplementary Table3), mass spectrometry analysis was
performed on a Q Exactive HF mass spectrometer (Thermo Scientific)
equipped with a Digital PicoView source (New Objective) and coupled
to a M-Class UPLC (Waters). Solvent composition at the two channels
was 0.1% formic acid for channel A and 0.1% formic acid, 99.9% ACN for
channel B. Column temperature was 50°C. For each sample, 4 µl of pep-
tides were loaded on a commercial ACQUITY UPLC M-Class Symmetry
C18 Trap column (100 Å, 5 µm, 180 µm × 20 mm, Waters) followed by
ACQUITY UPLC M-Class HSS T3 column (100 Å, 1.8 µm, 75 µm × 250 mm,
Waters). The peptides were eluted at a flow rate of 300 nl min
−1
by a
gradient from 5 to 40% B in 62 min. Column was cleaned after the run by
increasing to 98% B and holding 98% B for 5 min before re-establishing
the loading condition. Samples were acquired in a given order.
Content courtesy of Springer Nature, terms of use apply. Rights reserved

The mass spectrometer was operated in data-dependent mode,
acquiring full-scan mass spectra (350−1,500 m/z) at a resolution of
120,000 at 200 m/z after accumulation to a target value of 3,000,000,
and a maximum injection time of 50 ms, followed by higher-energy col-
lision dissociation (HCD) fragmentation on the six most intense signals
per cycle. HCD spectra were acquired at a resolution of 120,000 using a
normalized collision energy of 28 and a maximum injection time of 247
ms. The automatic gain control was set to 100,000 ions. Charge state
screening was enabled. Singly, unassigned and charge states higher
than six were rejected. Only precursors with intensity above 18,000
were selected for MS/MS. Precursor masses previously selected for MS/
MS measurement were excluded from further selection for 30 s, and
the exclusion window was set at 10 ppm. The samples were acquired
using internal lock mass calibration on m/z 371.1012 and 445.1200.
For samples with laboratory identifiers starting with DA (Supple-
mentary Table3), mass spectrometry analysis was performed on a Q
Exactive mass spectrometer (Thermo Scientific) equipped with a Digital
PicoView source (New Objective) and coupled to a nanoAcquity UPLC
(Waters). Solvent composition at the two channels was 0.1% formic acid
for channel A and 0.1% formic acid, 99.9% ACN for channel B. Column
temperature was 50°C. For each sample, 4 µl of peptides were loaded
on a commercial ACQUITY UPLC M-Class Symmetry C18 Trap column
(100 Å, 5 µm, 180 µm × 20 mm, Waters) followed by ACQUITY UPLC
M-Class HSS T3 column (100 Å, 1.8 µm, 75 µm × 250 mm, Waters). The
peptides were eluted at a flow rate of 300 nl min
−1
by a gradient from
8 to 22% B in 49 min and to 32% B in additional 11 min. Column was
cleaned after the run by increasing to 95% B and holding 95% B for 5 min
before re-establishing the loading condition. Samples were acquired
in a given order.
The mass spectrometer was operated in data-dependent mode,
acquiring a full-scan mass spectra (300−1,700 m/z) at a resolution of
70,000 at 200 m/z after accumulation to a target value of 3,000,000,
and a maximum injection time of 110 ms followed by HCD fragmenta-
tion on the 12 most intense signals per cycle. HCD spectra were acquired
at a resolution of 35,000 using a normalized collision energy of 25 and
a maximum injection time of 110 ms. The automatic gain control was
set to 50,000 ions. Charge state screening was enabled. Singly, unas-
signed and charge states higher than seven were rejected. Only precur-
sors with intensity above 9,100 were selected for MS/MS. Precursor
masses previously selected for MS/MS measurement were excluded
from further selection for 30 s, and the exclusion window was set at 10
ppm. The samples were acquired using internal lock mass calibration
on m/z 371.1012 and 445.1200.
As all samples in our study were digested with trypsin, peptides
had either an arginine or lysine at the C terminus. This resulted in the
C-terminal fragments remaining charged, and therefore identified at
a higher intensity than b-ions (Extended Data Fig.1). The mass spec-
trometry proteomics data were handled using the local laboratory
information management system
51
and all relevant data have been
deposited to the ProteomeXchange Consortium via the PRIDE (http://
www.ebi.ac.uk/pride) partner repository.
Data analysis. To account for as much variation of milk-associated
proteins as possible during MS/MS ion searches, a supplementary
database of milk protein sequences that had not been reviewed was
curated from UniProtKB in addition to those from ancient horses, as
previously generated
19
. As a previous publication
19
, peak lists were gen-
erated from raw files by selecting the top 100 peaks using MSConvert
from the ProteoWizard software package version 3.0.11781
52
. Sample
analysis results were searched using Mascot
53
(version 2.6.0) against
the Swiss-Prot database in combination with a curated milk protein
database19. Results were exported from Mascot as .csv files, and further
processed through an internally created tool, MS-MARGE
19,54
, to esti
-
mate the validity of peptide identifications and summarize the findings.
False-discovery rates at both the peptide spectral match and protein
level were calculated using MS-MARGE by counting the number of de-
coy hits after filtering for e-value and minimum peptide support, then
dividing this value by the number of target hits minus the number of
decoys. The resulting value is multiplied by 100 to provide an estimate
of the false-discovery rate. For each individual sample, we aimed for a
protein false-discovery rate of under 5% and a peptide false-discovery
rate of under 2% (Supplementary Table4). A minimum of two individual
peptide spectral matches were required for each specific protein iden-
tification, and only peptide spectral matches with an evalue of below
0.01 were accepted. After filtering criteria were applied, we observed a
range of variation in the numbers of proteins identified, with samples
ranging from 25 to 196 confidently identified protein families.
Sequence similarities between casein and Jeotgalicoccus. During
necessary BLAST searches to authenticate the taxonomic specificity of
ruminant α-S1 casein peptides, we found identical sequence matches to
theoretical proteins for the numerous bacterial firmicute species from
the genus Jeotgalicoccus (NCBI reference sequence: WP_188349304.1).
Upon further investigation, the full amino acid sequence for these
hypothetical bacterial proteins is almost identical to ruminant casein
sequences, which is probably due to laboratory contamination dur
-
ing the genomic sequencing. As its listing in the NCBI database is not
associated with a publication, we assume this is probably contamina-
tion. Supplementary Figure2 shows the alignment comparing the α-S1
casein sequence for Bos taurus, Bos grunniens, Bubalus bubalis and
Jeotgalicoccus species.
Proteome preservation assessment with the Oral Signature Screen-
ing Database. To confirm the preservation of thecalculus fromindi-
viduals included in this study, the metaproteome from each sample
was examined for a combination of specific protein types. Following a
previous publication6 we compared the data from each sample against
the Oral Signature Screening Database (OSSD) to determine the number
of common laboratory contaminants, contaminants introduced during
handling and curation, regularly recovered human immune proteins
found in the oral cavity, and bacterial proteins common to the human
oral microbiome. Supplementary Table3 contains the overall count
of OSSD proteins pulled from our filtered results, as well as the result
of the oral microbiome protein identifiers + human immune proteins
divided by the total number of OSSD proteins multiplied by 100 to find
the ‘authenticity’ of oral signature proteins in comparison to the total
proteins recovered. To determine who among the individuals passed our
screening, we applied a different threshold to each time period. For the
Early and Middle Bronze Age, we applied a previously published stand-
ard
37
, and for the Eneolithic period samples we lowered the standard to
40% to take into account increased protein degradation over time. Indi-
viduals who had calculus that fell below the authenticity threshold were
excluded from the study, but remain listed on the preservation table.
Sample authenticity is further supported by an absence of dietary pro-
teins in all positive (archaeological sheep bone with known proteome)
and negative controls (extraction blank), as well as the fact that none
of the control samples showed any evidence of a typical oral protein
signature. Protein preservation varies greatly between different envi-
ronments and can even differ between individuals at the same site37,55,
and this assessment should be conducted on a project-by-project basis.
Bayesian estimates of dietary contributions from freshwater protein
and radiocarbon calibration adjusted for freshwater dietary radio-
carbon reservoir effects for Eneolithic individuals. Chronologies
based on human radiocarbon dates require estimates of individual
aquatic dietary intakes, as well as estimates of aquatic radiocarbon
reservoir effects of consumed aquatic protein
56,57
. For the latter, we con-
sidered a wide potential variability of between 0 and 1,000 years, which
covers previously reported archaeological measurements of coeval
terrestrial and aquatic samples and the majority of measurements made
Content courtesy of Springer Nature, terms of use apply. Rights reserved

Article
on modern freshwater species from our study region
58
. To estimate
the dietary contributions from aquatic protein we used the Bayesian
mixing model ReSources developed within the Pandora & IsoMemo
initiatives (https://isomemoapp.com/). ReSources is a R-based model
that follows a similar implementation to the Bayesian mixing model
FRUITS
59
. We defined a two-end member model (terrestrial versus fresh-
water animal protein) with stable nitrogen reference values for these
(δ
15
N
terrestrial
=7.1±2‰, δ
15
N
freshwater
=10.6±1‰) calculated following a
literature review of previously reported values for bone collagen ex-
tracted from terrestrial and freshwater animal species within the study
region26,60. As with previous similar models, protein reference values
are corrected for offsets between bone collagen and edible meat, and
the implemented model also included a dietary to consumer isotopic
offset56,57. For each human bone collagen δ15N value, ReSources pro-
vided an estimate (expressed as a mean and s.d.) of the dietary intake
of freshwater protein. This estimate was included within the Bayes-
ian chronological model OxCal v.4.4 to express the degree of mixing
between the terrestrial radiocarbon calibration curve IntCal20 and a
freshwater radiocarbon curve
61,62
. The latter was defined from IntCal20
by adding a uniform prior of between 0 and 1,000 years. Calibrated
radiocarbon dates for each individual are expressed as 95% credible
intervals. An example of the OxCal code is given below.
Plot()
{
Curve(“IntCal20”,”IntCal20.14c”);
Curve(“FRE”,”IntCal20.14c”);
Delta_R(“LocalFRE”, U(0,1000));
Mix_Curves(“Date1”, “IntCal20”,”LocalFRE”, 63,26);
R_Date(“OxA-35976”, 5965, 20);
Mix_Curves(“Date2”, “IntCal20”,”LocalFRE”, 36,22);
R_Date(“OxA-37350”, 4390, 20);
};
Radiocarbon sample preparation methods
Bone sample preparation methods for radiocarbon data followed pre-
viously described methods63. In brief, the outer bone surfaces were
removed manually and all samples were soaked in successive washes
of methanol, acetone and dichloromethane for 30min each at room
temperature to remove adhesives and consolidants, and rinsed in
>18.2MΩ cm
−1
water. Bones were demineralized in 0.5N HCl for 24-36h
at 5°C, and then gelatinized in 0.01N HCl for 12h at 60°C. On the basis
of crude gelatin yield and quality, the gelatin was either ultrafiltered
(30-kDa MWCO), or hydrolysed for XAD purification. Resulting material
was then combusted under vacuum in sealed quartz tubes with CuO
and Ag wire, and the resulting CO2 was converted to graphite using H2
reduction over an iron catalyst. Radiocarbon content was measured
on a 500-kV NEC 1.5SDH-1 compact accelerator, and conventional ages
were calculated by normalizing to OXII oxalic acid standards and cor-
recting for fractionation using the δ13C ratio measure on the AMS64.
Reporting summary
Further information on research design is available in theNature
Research Reporting Summary linked to this paper.
Data availability
All raw, peak and result protein data have been uploaded to ProteomEx-
change (http://www.proteomexchange.org). Files are available under
the project accession: PXD022300, and the project DOI is https://doi.
org/10.6019/PXD022300. S.W. can also be contacted at shevan.wilkin@
iem.uzh.ch.
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ms-marge/src/master/ (2018).
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palaeoproteomic analyses of dental calculus, https://doi.org/10.5281/zenodo.3698271
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Acknowledgements We thank the Max Planck Society for providing the funding for this
project. D.R. is an Investigator of the Howard Hughes Medical Institute. A.E. was supported by
a grant from the Russian Science Federation, grant number 20-18-00402. We thank A. Dittman
for insights on protein mass spectra.
Author contributions S.W. and N.B. designed the study; S.W., A. Khokhlov, E.K., V.F.Z., A.K.O.,
D.R.B., P.K., A. Kitovaand A.E. participated in sample collection; S.W. conducted the protein
extractions and analysed the data; L.K. and C.F. ran the samples on the LC–MS/MS; D.R., R.F.,
B.J.C., D.K., A. Khokhlov and E.K. provided radiocarbon dates; S.W. and N.B. wrote the draft
with the help of A.V.M., W.T.-T.T., R.S., D.A., E.K. and A. Khokhlov, and with input from all other
co-authors.
Funding Open access funding provided by Max Planck Society.
Competing interests The authors declare no competing interests.
Additional information
Supplementary information The online version contains supplementary material available at
https://doi.org/10.1038/s41586-021-03798-4.
Correspondence and requests for materials should be addressed to Shevan Wilkin or Nicole
Boivin.
Peer review information Nature thanks the anonymous, reviewer(s) for their contribution to
the peer review of this work. Peer reviewer reports are available.
Reprints and permissions information is available at http://www.nature.com/reprints.
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Extende d Data Fig. 1 | MS 2 spectra for d airy protei ns. a, BLG peptide s pecific
to Ovis or Bovinae for DA420. b, BLG I pe ptide specif ic to Equus for DA420.
c, Equus BLG I pe ptide for Z438. d, MS2 spe ctra for a Capra-specif ic BLG peptid e
for Z438. e, α-S1 casein f rom DA430 specif ic to Bovinae. f, Se cond α-S1 casein
peptide sp ecific to B ovidae, also from DA43 0. Horse, goat and cow i mages
are reproduc ed from ref. 37; sheep silho uette, publi c domain
(https://thenounproject.com/icon/12538/).
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nature research | reporting summary October 2018
Corresponding author(s):
Shevan Wilkin
Nicole Boivin
Last updated by author(s): Jun 14, 2021
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Data collection Mass spectrometry analysis was performed on a Q Exactive HF mass spectrometer (Thermo Scientific) equipped with a Digital PicoView
source (New Objective) and coupled to a M-Class or nanoAcquity UPLC (Waters).
Data analysis To transfer raw MS/MS files to Mascot Generic Files (mgf) we used the program MSConvert from the ProteoWizard software package
version 3.0.11781. Then, data were searched using Mascot (version 2.6.0) and filtered using MS-MARGE (https://bitbucket.org/rwhagan/
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Sample size Sample size was determined by the number of archaeological individuals that had accumulated dental calculus available for collection.
Data exclusions Dental calculus samples that did not pass the preservation threshold were excluded from further analysis, however, these samples are still
listed and their preservation score is provided in Supplementary Table S3.
Replication These findings can be easily replicated by downloading either the 'raw' or 'mgf' files and re-searching them against the same databases.
Randomization Samples were not randomized as it was not necessary for the type of study we conducted.
Blinding As the individuals were not tested for any sort of reaction or non-reaction blinding was not necessary for our study.
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Animals and other organisms
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Palaeontology
Specimen provenance Dental calculus samples were collected from Samara State University Department of Archaeology Collection Saplesand the
scientific collections of the Museum at the Institute of Plant and Animal Ecology (Ural Branch of the Russian Academy of
Sciences).
Specimen deposition ProteomExchagne http://www.proteomexchange.org/ login: reviewer_pxd022300@ebi.ac.uk and password of: 7TwobDNV
Dating methods AMS radiocarbon dating was conducted to dates some individuals. Bone sample preparation methods for radiocarbon data
follow those as described in Narasimhan et al. Briefly, the outer bone surfaces were removed manually and all samples were
soaked in successive washes of methanol, acetone and dichloromethane for 30 min each at room temperature to remove
adhesives and consolidants and rinsed in >18.2 MΩ/cm water. Bones were demineralized in 0.5N HCl for 24-36 hr at 5°C, and
then gelatinized in 0.01N HCl for 12hr at 60°C. Based on crude gelatin yield and quality, the gelatin was either ultrafiltered (30k
Da MWCO), or hydrolyzed for XAD purification. Resulting material was then combusted under vacuum in sealed quartz tubes
with CuO and Ag wire, and the resulting CO2 was converted to graphite using H2 reduction over an iron catalyst. Radiocarbon
content was measured on a 500kV NEC 1.5SDH-1 compact accelerator, and conventional ages were calculated by normalizing to
OXII oxalic acid standards and correcting for fractionation using the δ13C ratio measure on the AMS15.
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