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Longitudinal study of the scalp
microbiome suggests coconut oil
to enrich healthy scalp commensals
Rituja Saxena1,4, Parul Mittal1,4, Cecile Clavaud2,4, Darshan B. Dhakan1, Nita Roy3,
Lionel Breton2, Namita Misra2,3* & Vineet K. Sharma1*
Dandru is a recurrent chronic scalp disorder, aecting majority of the population worldwide.
Recently a metagenomic study of the Indian scalp microbiome described an imperative role of
bacterial commensals in providing essential vitamins and amino acids to the scalp. Coconut oil and
its formulations are commonly applied on the scalp in several parts of the world to maintain scalp
health. Thus, in this study we examined the eect of topical application of coconut oil on the scalp
microbiome (bacterial and fungal) at the taxonomic and functional levels and their correlation
with scalp physiological parameters. A 16-weeks-long time-course study was performed including
12-weeks of treatment and 4-weeks of relapse phase on a cohort of 140 (70 healthy and 70 dandru)
Indian women, resulting in ~ 900 metagenomic samples. After the treatment phase, an increase in
the abundance of Cutibacterium acnes and Malassezia globosa in dandru scalp was observed, which
were negatively correlated to dandru parameters. At the functional level, an enrichment of healthy
scalp-related bacterial pathways, such as biotin metabolism and decrease in the fungal pathogenesis
pathways was observed. The study provides novel insights on the eect of coconut oil in maintaining a
healthy scalp and in modulating the scalp microbiome.
e human skin including the scalp surface, serves as the body’s rst line of defence as well as a host to a myriad
of microorganisms, which includes both bacteria and fungi1. e application of high-throughput next-generation
sequencing and robust computational analysis has led to an in-depth understanding of the scalp microbiome in
the recent years2–4, providing novel clues on the pathophysiology of scalp-related disorders such as dandru and
seborrheic dermatitis in dierent countries5–9. Dandru is one of the most common scalp condition aecting
majority of the population worldwide10. It is a recurrent, chronic, sub-inammatory disorder, which is character-
ized by scaly patches and sometimes itching10,11. Various environmental and intrinsic factors are reported to be
linked to the development of dandru, such as the sebum composition, host susceptibility, scalp microbiome,
and a combined interaction between all of these.
Global studies have revealed that the scalp microbiome is characterized by a rather low bacterial diversity,
as compared to the other body sites12,13, and is dominated by Cutibacterium acnes (formerly Propionibacterium
acnes), Staphylococcus epidermidis and Malassezia spp.4–7. Staphylococcus epidermidis and Cutibacterium acnes
are found to be the key bacterial players, where dandru is commonly marked with an increased abundance of S.
epidermidis on the scalp5–7. Among the fungal microbiota, dierent species of Malassezia, specically M. restricta
and M. globosa have shown varying proportions in populations of dierent countries5,14–16. Specic strains of
M. restricta have been identied in the dandru patients at the genotypic level17. e ability of Malassezia sp. to
metabolize and oxidize sebum-derived lipids (triglycerides, squalene, fatty acids, etc.) is an additional source
of potential inammatory compounds18. M. restricta is also known to induce cytotoxicity to skin cells invitro,
suggesting an active role in the acceleration of dandru19. A strong association of uncharacterised Malassezia
species with dandru is also observed in a few recent studies4,7. Further, scalp bacteria have been reported to
have a stronger association with scaling severity than fungi suggesting that bacteria could have an implication in
the clinical symptoms14,15. However, whether the scalp microbiome variation is a cause or a consequence of the
unhealthy condition of the scalp remains unclear. S. epidermidis and C. acnes are also a part of the commensal
microbiota and reported to have benecial activities on the skin through immune response modulation and
OPEN
These authors
*email: namita.misra@rd.loreal.com;
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protection against pathogens20–22. In our recent metagenomic study carried out on the scalp microora of the
Indian population, we have observed enrichment of bacterial pathways related to the synthesis and metabolism
of amino acids, biotin and B-vitamins in healthy scalp compared to dandru, revealing a new potential role of
bacterial commensals in maintaining the scalp nutrient homeostasis4.
Current anti-dandru therapies involve topical antifungal agents such as azoles, the clinical ecacy of which is
accompanied by a reduction in the proportion of Malassezia spp. on the scalp23–26. However, it is usually observed
that at the cessation of the treatment, the relapse restores the initial symptoms24,27. Scalp-related products such
as oils, shampoo and other cosmetics are also used worldwide to maintain scalp health and hygiene28,29. Among
which, coconut oil is the most widely used product in African and Asian countries, including India, to ameliorate
scalp health and hair growth29–31. Not much is known about the mode of action of coconut oil. Firstly, the anti-
fungal activity of lauric acid, the major fatty acid contained in the oil, is suspected to prevent the proliferation of
pathogens29,31–34. Secondly, coconut oil is known to have a biophysical action on the skin barrier function, since
it helps to decrease the TEWL (trans-epidermal water loss) on long-term application35,36. However, no study has
yet systematically examined the eect of topical application of coconut oil on the scalp microbiome.
Due to the recently established role of the microbiome on skin and scalp health, a few studies have inves-
tigated the eect of emollients 37,38 and topical medication39,40 on the skin microbiome. Here, we carried out a
16-weeks-long time-course study to understand the impact of coconut oil application on the scalp microbiome
(bacterial and fungal) of 140 individuals with healthy and dandru scalp. A treatment phase was carried out
for 12-weeks followed by 4-weeks of the relapse phase in which no application of oil was performed. e scalp
clinical parameters were also recorded throughout the study and correlated with the taxonomic and functional
prole of the scalp microbiome. e present study aims to provide insights on the potential eect of coconut oil
on the scalp fungal and bacterial microbiome.
Results
Recently, we reported the functional role of scalp microbiome (bacterial and fungal) in a cohort of 140 Indian
individuals consisting of 70 individuals with healthy and 70 with dandru scalp4. In the current study, we have
used the same cohort to perform a time-course study to understand the impact of coconut oil application on the
scalp. Amplicon and shotgun metagenomic analysis revealed the major microbial species and their functional
pathways in the healthy and dandru scalp microbiome at the baseline. From the amplicon analysis, the core
scalp microbiome was dened as the taxonomic groups with ≥ 1% abundance in at least 80% of the samples,
which represented the stable and consistent microbial population in the microbiome associated with the scalp
environment. To examine the eect of coconut oil (O) on the scalp microbiome, the changes in the relative
abundance of the core microbiome and their associated functional pathways were analysed and compared with
a ‘neutral shampoo’ (S) aer 12-weeks of treatment phase (T) followed by four weeks of relapse phase (R). e
study design is presented in Fig.1 and details on the nomenclature of groups and samples is provided in sup-
plementary methods.
Taxonomic variations in the fungal microbiome after the treatment and relapse phases. Tax-
onomic analysis of the baseline microora showed the alpha-diversity of the fungal population to be signicantly
lower (p ≤ 0.001) in the healthy scalp (HB: Healthy scalp Baseline) compared to the dandru scalp (DB: Dandru
scalp Baseline) (Fig.S1a). A high abundance of M. globosa (p ≤ 0.0001) was observed in HB (16.23%) compared
to DB (6.41%) (Fig.S1b–d). A strikingly high proportion of OTUs corresponding to uncharacterized Malasse-
zia spp. was observed. One of these OTUs belonged to uncultured species of Malassezia (> 95% identity with
Uncultured Malassezia, Genbank ID—KC785585.1) and others belonged to unknown Malassezia species (also
at > 95% identity), of which, six OTUs (sequences provided in Supplementary Text) showed an identity of ≥ 85%
with M. restricta, and were assigned to a subgroup of Malassezia (i.e. species close to M. restricta). erefore,
the uncharacterized Malassezia sequences formed three subgroups: (1) uncultured Malassezia, (2) Malassezia
sp., and (3) species close to M. restricta, as described previously4. e uncultured Malassezia was signicantly
abundant (p ≤ 0.0001) in DB (25.26%) compared to HB (14.44%). Malassezia sp. and species close to M. restricta
were also signicantly (p ≤ 0.01) higher in DB compared to HB (Fig.S1d).
e alpha-diversity (Shannon index and number of observed species) of the fungal microbiome increased
signicantly (p ≤ 0.0001) aer oil treatment (HOT) and aer-shampoo application (HST) in the healthy scalp
compared to the baseline (HB) (Fig.S1a). It also showed a signicant increase (p ≤ 0.0001) in oil-treated healthy
scalp at the relapse phase (HOR) as compared to baseline (HB) and treatment phase (HOT). However, there was
no signicant eect seen on the alpha-diversity of the dandru groups.
Proportions of M. restricta and M. globosa along with the Malassezia subgroups (1, 2 and 3), constituting the
fungal core of the scalp, were examined in the three phases. Aer oil-treatment, the abundance of M. restricta
reduced signicantly (p = 0.03) in DOT (26.55%) compared to DB (33%) (Fig.2a and Fig.S2a–e). e abundance
of M. globosa increased signicantly in both healthy (HOT = 23.23%, p = 0.02) and dandru scalp (DOT = 9.74%,
p ≤ 0.001) compared to the baseline, i.e. HB (16.23%) and DB (6.41%), respectively. It also increased signicantly
(p ≤ 0.05) in DST (14.32%) compared to DB (6.41%), while there was no signicant dierence between HST
and HB. e abundance of Malassezia sp. increased signicantly (p ≤ 0.0001) in HOT (8.86%) and HST (10%)
compared to HB (2.37%). It also increased signicantly (p ≤ 0.05) in DST (12.28%) compared to DB (10.12%).
Additionally, the ratio of M. restricta to M. globosa, which was observed to be signicantly higher (p = 0.004) in
the dandru scalp compared to the healthy scalp, decreased signicantly (p = 0.001) in DOT compared to DB
(Fig.S1e).
Group-wise analysis using repeated measures ANOVA conrmed the signicant variations (FDR adj. p ≤ 0.05)
in M. globosa aer oil-treatment in both healthy and dandru scalp, and aer shampoo-application in the
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healthy scalp (Fig.2b and TableS1a). A similar trend was shown by Malassezia sp. in oil and shampoo-treated
healthy scalp. e abundance of M. globosa decreased signicantly (p ≤ 0.01) in HOR (13.41%) and HSR (9.44%)
compared to HOT (23.23%) and HST (19.32%), respectively (Fig.S3a–e). A signicant decrease (p = 0.03) in the
abundance of uncultured Malassezia was also observed in DOR (18.37%) compared to DOT (23.60%) (Fig.2a).
ese results suggest that the eect of oil-treatment on the changes in the fungal community was not sustained
for dandru group aer the relapse phase, in contrast to the healthy group.
Taxonomic variations in the bacterial microbiome after the treatment and relapse
phases. ere was no signicant dierence observed in the alpha-diversity of the bacterial microbiome
between healthy (HB) and dandru (DB) group at the baseline (Fig.S4a). e weighted UniFrac distances does
not show a signicant dierence between healthy (HB) and dandru (DB) group at the baseline (Fig.S4b). At
the species level, the abundance of S. epidermidis was observed to be signicantly higher (p = 0.0002) in dan-
dru (28.11%) than in healthy (14.83%) scalp (Fig.S4c–e). e abundance of C. acnes did not vary signicantly
(p ≥ 0.05) between dandru (30.83%) and healthy (24.42%) scalp.
Aer the treatment phase, there was a signicant increase (p ≤ 0.01) in the bacterial diversity (Shannon index)
in the healthy scalp aer oil-treatment (HOT) and not with shampoo-application (HST) compared to baseline
(Fig.S4a). e weighted UniFrac distances showed a signicant decrease in within-sample distances in HOT
compared to HB, while it was not signicant for DOT compared to DB (Fig.S4b). Interestingly, oil-treated
groups (HOT and DOT) showed lower UniFrac distances compared to the shampoo-treated group (HST and
DST respectively), suggesting a distinct eect of coconut oil on the scalp bacterial communities.
At the taxonomic level, we have focussed on the variations in the abundance of the two main species C.
acnes and S. epidermidis that constitute the core microbiome. e proportion of C. acnes increased signicantly
(p ≤ 0.0001) in HOT (45.29%) compared to HB (24.42%) (Fig.3a and Fig.S5a–e). Although less than HOT,
it also showed a signicant increase (p ≤ 0.0001) in HST (40.09%) compared to HB. e ratio of C. acnes to
S. epidermidis, which was signicantly higher (p = 0.01) in the healthy scalp compared to the dandru scalp,
was signicantly higher (p = 0.008) in HOT compared to HB (Fig.S5f). Signicant fold-change dierences
were observed in the abundance of bacterial species between oil-treatment and shampoo-application (Fig.3b).
Interestingly, C. acnes and Propionibacterium sp. showed signicant (p ≤ 0.05) fold-changes aer oil-treatment
compared to shampoo-application. Fold change analysis was applied to both bacterial and fungal population,
however the results were found to be signicant (p ≤ 0.05) only for the bacterial microbiome. We did not nd any
Figure1. Study Design. Swab samples were collected at three phases, baseline (t = 1), treatment phase (t = 2)
and relapse phase (t = 3) from healthy and dandru scalps. Bacterial and fungal DNA was extracted from
the collected swab samples, and amplicon (bacterial 16S rRNA V3 and fungal ITS1 region) and shotgun
metagenomic sequencing were performed to carry out the taxonomic and functional analysis. In the gure,
H = healthy scalp, D = dandru scalp, O = oil-treatment, S = shampoo-treatment, and B, T and R = the three
phases or time-points i.e. Baseline, Treatment and Relapse phase, and n = number of subjects in each group.
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fungal species to show signicant fold-changes between the groups and hence, the results only from the bacterial
microbiome are included here. Among the other species, Corynebacterium sp., showed the maximum level of
fold-change (from < 5 to > 20 times, p ≤ 0.05) aer oil-treatment. Repeated measures ANOVA (FDR adj. p ≤ 0.05)
conrmed an increase in the abundance of C. acnes in healthy subjects aer oil-treatment (Fig.3c, TableS1b).
Changes in the proportion of C. acnes and S. epidermidis were retained (p ≥ 0.05) aer the relapse phase (Fig.3c
and Fig.S6). ese results suggest an apparent benecial eect of coconut oil on the core bacterial species aer
12weeks treatment, which appears to be retained at the relapse phase.
Figure2. Comparison of fungal population at the three phases. (a) Bubble plots representing the top ve
fungal species across all the groups. e bubble size indicates mean relative abundance of species within each
group. Square brackets indicate the groups between which a signicant dierence in the species abundance was
observed (p ≤ 0.05, Wilcoxon test, + indicates the group with the higher abundance among the two). (b) Core
fungal species showing signicant variations across the three phases (FDR adjusted p ≤ 0.05, repeated measures
ANOVA).
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Correlation of microbial species with host physiological parameters. Dandru scalp is character-
ized by in increased TEWL indicating an altered barrier function, and a few studies have described the variation
in the host-associated physiological parameters in the healthy and dandru scalp8,41. erefore, a systematic
investigation of the host physiological parameters was carried out at all the three phases of the study and cor-
related with the scalp microbiome (TableS2).
e three Malassezia subgroups showed signicant positive correlation (FDR adj. p ≤ 0.05) with dandru
scores and itching, whereas, M. globosa was negatively correlated with these parameters (Fig.4a). e taxa
corresponding to unknown Malassezia sp. showed a signicant negative correlation with TEWL. Uncultured
Malassezia showed a negative correlation with hydration, and M. restricta showed a positive correlation with
sebum level and hydration.
Among the bacterial population, S. epidermidis displayed a signicant positive correlation (FDR adj. p ≤ 0.05)
with dandru scores, TEWL and itching. However, Propionibacterium sp. correlated negatively with these
parameters, and C. acnes showed a signicant negative correlation with TEWL (Fig.4b). Although being low
in abundance, Flavobacterium sp. and C. kroppenstedtii showed a pattern similar to Propionibacterium sp. and
S. epidermidis, respectively.
e host physiological parameters were also compared in the oil and shampoo-treated groups across the three
phases using repeated measures ANOVA. e results showed a reduction in TEWL and dandru scores in both
healthy and dandru groups aer the coconut oil treatment phase (TableS1c). It is to be noted that the results for
coconut oil treatment are more concordant when studied at taxonomic level compared to the host physiological
parameters, which are inuenced by many other factors beyond the scope of this study.
Figure3. Comparison of bacterial population at the three phases. (a) Bubble plots representing the top ve
bacterial species across all the groups. e bubble size indicates mean relative abundance of species within each
group. Square brackets indicate the groups between which a signicant dierence in the species abundance
was observed (p ≤ 0.05, Wilcoxon test, + indicates the group with the higher abundance among the two). (b)
Signicant fold-change dierences (p ≤ 0.05) observed in bacterial species abundance between oil-treatment and
shampoo-application. No signicant dierence was observed in the fungal species between the two treatment
groups. (c) Core bacterial species showing signicant variations across the three phases (FDR adjusted p ≤ 0.05,
repeated measures ANOVA).
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Functional variations in the scalp microbiome. e shotgun metagenomic analysis showed several
fungal KEGG pathways to vary signicantly (p ≤ 0.05, Wilcoxon test) between the healthy and dandru scalp
at the baseline as reported earlier (Fig.S7a)4. In brief, the amino acid metabolism pathways (histidine, cysteine
and methionine metabolism) and lipoic acid metabolism pathway were more abundant in healthy scalp than in
dandru scalp. Further, pathways for N-glycan biosynthesis, which are implicated in cell-host interaction, were
enriched in the dandru scalp42. Several fungal pathways also showed signicant variations in their proportions
aer the treatment phase, which were statistically tested at all three phases using repeated measures ANOVA
(TableS1d; Fig.5). Aer oil-treatment, histidine metabolism pathway showed a signicant increase in both
healthy and dandru groups, however, it was also observed in the shampoo group suggesting that it is not linked
to the oil application. In contrast, the proportion of N-glycan biosynthesis and cell cycle pathways decreased in
both healthy and dandru scalps in the oil treated group and not in the shampoo group compared to baseline
(Fig.5). is eect was not sustained at the relapse phase, since there was a signicant increase at the relapse
phase (t = 3) compared to the treatment phase (t = 2). However, the initial baseline levels were not recovered.
Functional analysis of the bacterial microbiome showed the pathways related to vitamins and cofactors
(biotin, porphyrin and chlorophyll, vitamin-B6, nicotinate and nicotinamide metabolism, ubiquinone and other
terpenoid-quinone biosynthesis), and amino acids (alanine, aspartate, arginine, glutamate and proline and lysine
metabolism and biosynthesis) to be signicantly higher in healthy scalp than dandru scalp at the baseline, as
reported earlier (Fig.S7b)4. Results from the previous study have shown these pathways to be positively correlated
with C. acnes, suggesting it to be the major contributor for biotin and other B-vitamins on the scalp surface4.
Bacterial KEGG pathways showed signicant variations aer oil-treatment compared to shampoo-application in
the dandru scalp (Fig.6). e biotin metabolism pathway showed a substantial increase in DOT compared to
DB. e variations in pathway abundance were also tested statistically at the three phases using repeated meas-
ures ANOVA (TableS1e). e abundance of KOs related to biotin metabolism and biotin transport pathways
also increased aer oil-treatment compared to shampoo-application in the healthy and dandru scalp (Fig.7,
Fig.S7c and d).
Discussion
is study reports the eect of topical application of coconut oil on the scalp microbiome in a cohort of 140
Indian women using high-throughput sequencing and computational analysis. Since, bacteria and fungi are the
major scalp microbial species, we examined both using bacterial 16S rRNA and fungal ITS1 amplicon sequenc-
ing, respectively, followed by the shotgun metagenomic sequencing, which helped to understand the impact of
coconut oil on the scalp microbiome.
Coconut oil is commonly used in several parts of the world to maintain scalp health and to moisturise the
skin in addition to repair hair damage, through a direct or indirect mode of action29,31. Supporting studies have
Figure4. Spearman’s correlation between microbial taxa and host physiological parameters. (a) Fungal and (b)
bacterial taxa showing signicant correlations (+ , FDR adjusted p ≤ 0.05) with any of the parameters are plotted
as a heatmap.
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demonstrated the inhibitory role of coconut oil and its major component, lauric acid, on the growth and invasion
of dermatophytes on the skin more eciently than other hair oils commonly used in India such as mustard oil,
cantharidine oil, amla oil, etc.32–34. It is also known to decrease the TEWL on long-term application on the skin
surface, and increases the hydration levels36, which could play an important role in shaping the microbiome of
the scalp surface. us, it seems reasonable to speculate a potent eect of coconut oil application on the scalp
physiology, which in turn modies the scalp microbiome4,8.
In our previous study of the scalp microbiome in the Indian cohort, we have obtained the baseline microbial
composition of both fungal and bacterial communities, which has been reported and reanalysed for the current
study4. e determination of baseline microora helped to elucidate the potential benecial role of microbiome
by comparing their compositional changes aer the treatment phase. Cutibacterium acnes and Staphylococcus
epidermidis emerged as major bacterial colonizers, and Malassezia restricta and Malassezia globosa as the major
fungal colonisers. Similar association of these species with the healthy and dandru scalp has also been observed
Figure5. Functional analysis of fungal microbiome. e proportions of fungal pathways showing signicant
variations across all the three phases in the following groups (FDR adjusted p ≤ 0.05, repeated measures
ANOVA) are shown in the box plots: (a) Healthy oil-treated group, (b) dandru oil-treated group, (c) healthy
shampoo-treated group and (d) dandru shampoo-treated group.
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in other studies from dierent population such as, from France, China, Brazil, etc.5–8. A noteworthy observation
at the baseline was the high abundance of uncharacterised Malassezia sp. in the dandru scalp compared to
the healthy scalp, and its signicant positive correlation with dandru-associated parameters. A high propor-
tion of uncultured Malassezia (> 37% of the total fungal population) has also been observed recently in the
Brazilian population7. e results also showed M. globosa to be negatively correlated with dandru score and
itching, and S. epidermidis and uncharacterised Malassezia sp. to be positively correlated with these parameters.
Similar variation in the proportion of M. globosa was also reported in a Chinese cohort using the Illumina
sequencing technology8. However, a few other studies have reported contrasting results, which could be a result
of lower cohort size, dierences in the country of origin of populations and usage of conventional sequencing
technologies5,7,9,43.
e above taxonomic results were conrmed in this study by recording the host physiological parameters at
all the three time-points. e results also showed the benecial role of bacterial scalp microbiome in supplying
essential vitamins and amino acids to the host as observed in the previous study, where a positive correlation of
C. acnes was also observed with the pathways related to the metabolism of biotin and other B-vitamins that are
essential for maintaining a healthy scalp4.
e time-course study revealed an apparent benecial eect of coconut oil application on the fungal scalp
microbiome in enhancing the core fungal species associated with a healthy microora. e abundance of M.
globosa, which was correlated with the healthy scalp, increased aer the application of coconut oil in the healthy
and dandru scalp. e abundance of M. restricta reduced signicantly in the dandru scalp aer oil-treatment
as compared to the baseline. Further, a signicant decrease in the ratio of M. restricta to M. globosa was observed
in dandru subjects aer the application of coconut oil. is ratio was similar to the baseline healthy compo-
sition reported in this cohort and other populations, which points towards a probable role of coconut oil in
maintaining a healthy fungal scalp microbiome7. e pathways related to pathogenesis, survival and adhesion
(N-glycan biosynthesis and cell cycle pathways) showed a signicant reduction aer the application of coconut
oil, suggesting its role in lowering the abundance of fungal pathogenic species. e eect of coconut oil was not
sustained for dandru group, mainly in the fungal community. is observation could be explained by a limited
eect of the oil on the fungal microbiome in the dandru scalp. e fungal taxa found on the dandru scalp were
signicantly dierent compared to healthy scalp and could be more resistant to lauric acid.
e benecial eects of coconut oil were more prominently evident on the bacterial microbiome compared to
the fungal microbiome. It was observed that C. acnes and Propionibacterium sp., which are reportedly associated
Figure6. Functional analysis of bacterial microbiome. Dierentially abundant bacterial KEGG pathways aer
(a) oil-treatment and (b) shampoo application in the dandru group (which showed p ≤ 0.05, Wilcoxon test) are
shown in the bar graphs. None of the pathways showed signicant dierences in the healthy group.
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with a healthy scalp, showed a signicant increase aer oil-treatment in both the healthy and dandru scalp4–7.
Further, the ratio of C. acnes to S. epidermidis was also notably increased aer the oil-treatment. ese results
suggest that oil helps in enhancing the benecial bacterial species in both healthy and dandru scalp. is was
further conrmed by the signicant increase in the biotin metabolism pathway aer oil-treatment, which was
majorly contributed by C. acnes and Propionibacterium sp. Biotin and other B-vitamins are crucial precursors for
dierent enzymes required for vital biochemical reactions in the living cells, and are also essential for a healthy
skin and scalp surface44. Biotin is also reported to reduce cellular inammation and improve skin barrier qual-
ity, scalp health and hair growth35,36. Since, humans and other mammals cannot synthesize biotin, they obtain
it through exogenous sources by import mechanism of the Na-dependent multivitamin transporters (SMVT)
and biotin-specic transport components45,46. us, it is tempting to speculate the benecial eect of coconut
oil on the scalp microbiome primarily via creating physiological conditions that favour the benecial microbial
community involved in the biosynthesis of nutrients essential for scalp nutrition.
is study demonstrates a positive eect of coconut oil on the scalp microbial communities and their func-
tional potential. We could speculate that microbiome changes are the rst step towards the restoration of a
healthy scalp that will lead to perceptible benets to host much later than the time-lines included in this study,
and thus provide a long-term benet compared to short-term benet as observed in the case of the neutral
shampoo. Another signicant outcome of the study is that beyond antifungal agents, other approaches could
be considered for dandru treatment targeting both fungal and bacterial microbiome. However, further studies
are needed to understand the underlying mechanisms and nutritional signicance of coconut oil for the scalp
microbiome. A pre-emptive approach aimed at reducing the susceptibility to dandru by maintaining/reinstat-
ing a healthy scalp microbiome, in addition to improving scalp barrier functions, seems a novel opportunity to
achieve long-lasting eects.
Materials and methods
Ethics approval and consent to participate. e research protocol was approved by the Independ-
ent Ethics Committee for Evaluation of Protocols for Clinical Research, CLINICOM, Bengaluru, India (Study
number ARC/COSB/1444) and was conducted in accordance with the principles expressed in the World Medi-
Figure7. Schematic representation of biotin metabolism pathway describing the signicantly enriched KOs
(p ≤ 0.05) in the dataset.
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cal Association Declaration of Helsinki. A written informed consent was obtained from all subjects prior to any
study-related procedures.
Subject recruitment and study design. e study was carried out on a previously reported cohort of
140 Indian women4. Firstly, 184 female volunteers were screened for the study, out of which 70 individuals with
healthy and 70 with dandru scalp (aged between 20–45years, mean age 34.6) were enrolled with the associa-
tion of MS Clinical research (Bengaluru, India), who had used coconut oil occasionally in the past one year. e
volunteers were non-smokers, free from any cutaneous diseases, did not use anti-hair-loss treatment at least
for three months prior to sampling, did not use anti-dandru shampoos and hair-related products (such as for
bleaching, straightening, dyeing, permanent waving, etc.) on scalp and hair for at least three weeks prior to sam-
pling, and did not consume antibiotics or apply systemic antifungals for one month prior to sampling.
Dandru grading and clinical evaluation of scalp physiological parameters. Dandru level was
scored according to a grading scale as previously described5. Scalp physiological parameters were measured
using appropriate devices and protocols. Sebumeter (SM815, Courage & Khazaka, Germany) was used to meas-
ure the sebum level of the scalp following manufacturer’s instructions. VapoMeter (Deln Technologies, Fin-
land) was used to measure the TEWL (trans-epidermal water loss) that measures the integrity of barrier function
of the scalp by following the manufacturer’s instructions47. All the measurements were performed in triplicates
and values presenting coecient of variation < 15% were considered as relevant. Corneometer (CK Electronic
GmbH, Germany) measurement was performed on the scalp surface to check the hydration levels following the
manufacturer’s instructions. e above measurements were performed on a shaved trimmed mini-area before
the oil-treatment and shampoo wash at the investigational site by a dedicated operator. Following clinical or
physiological parameters were recorded for each subject across the three phases: adherent dandru score (ADS),
total dandru score (TDS) i.e. adherent and non-adherent, hydration, sebum level, TEWL, erythema and itching
(TableS2).
Treatment. e volunteers were asked to use a bland or neutral shampoo (L’Oréal India Pvt. Ltd.) two times
a week for a period of four weeks prior to the beginning of the study to standardize the scalp condition (baseline,
Day-0 or t = 1). Four subjects from the healthy group and ve from the dandru group did not continue aer
the baseline sampling, and therefore, the remaining 66 subjects with healthy scalp and 65 with dandru scalp
were followed-up throughout the course of the study. During the treatment phase (Day-84 or t = 2), 32 subjects
with dandru scalp and 33 with healthy scalp received controlled oil-treatment twice a week for 12weeks at the
center (MS Clinical Research, Bengaluru, India). e treatment consisted of 20min of scalp massage with 10ml
of pure coconut oil (100% rened coconut oil, Cargill, India) followed by two hours leave-on, and then a bland
shampoo wash (20ml). e remaining 33 subjects with dandru scalp and 33 with healthy scalp were subjected
to only the shampoo wash twice a week at the center (MS Clinical research, Bengaluru, India) for 12weeks with
no application of coconut oil. During the relapse phase (Day-112 or t = 3), all the 131 subjects received a topical
application of only the bland shampoo on the scalp twice a week for four weeks. Subjects were advised not to use
any hair or scalp products other than the study products.
Sampling of the scalp microbiome. e volunteers were asked not to perform scalp wash for two days
prior to the sampling procedure. Samples from the scalp (vertex or crown of the head) were obtained at the
baseline (t = 1), at the end of 12weeks of treatment phase (t = 2) and aer the relapse phase (t = 3). Sampling
was conducted as previously described with minor modications5. A sterile cotton swab soaked in a solution
containing collection solution (0.15M NaCl and 0.1% Tween 20) was rubbed onto the scalp surface (between
the hairs) under a zig-zag pattern, to cover a total surface of 4 cm2 in a non-overlapping manner. At the end of
the procedure, the head of each swab was cut from the handle and placed into a tube containing 5ml of collec-
tion buer. As described previously5, swabs were stored at 4°C and processed for DNA isolation within 24h. In
addition, a few sterile cotton swabs (as negative controls) were cut from the handle and placed in the collection
buer, and further processed using identical procedure.
High-throughput sequencing DNA extraction. e DNA extraction method was validated, as
described above4. Since, the DNA extraction strategy can inuence the microbiota community proling, the
DNA extraction method was developed using dierent bacterial fungal species and ensured that maximum
quantity of DNA was recovered by the optimized protocols.
Two identical samples of 2ml each were generated from one collection tube. e microbial cell suspension
from each tube was pelleted by centrifugation at 10,000g for 30min, at 4°C. For bacterial DNA extraction, the
cells were re-suspended in 180ml of lysis buer (20mM Tris–HCl, 2mM EDTA, 1.2% TritonX100 (w/v); pH
8.0) and incubated for 30min at 37°C. Further 25µl of proteinase K and 200µl buer AL (Qiagen, MD, USA)
were added to the mixture and incubated for 30min at 56°C.
For fungal DNA extraction, the cells were re-suspended in 600ml of lysis buer (1M Sorbitol, 100mM
EDTA, 14mM β-mercaptoethanol) and incubated with Zymolyase-T20 (200 U) for 30min at 30°C. e result-
ing spheroplasts were centrifuged for 10min at 300 × g and the supernatant was discarded. e spheroplasts
were re-suspended in 180µl of Buer ATL and incubated with 20µl of proteinase K (Qiagen, MD, USA) for
15min at 56°C.
e remaining steps were performed according to the manufacturer’s protocol and the extracted DNA was
stored at -20°C. DNA concentration was measured using Qubit ds DNA HS kit on Qubit 2.0 uorometer (Life
technologies, Carlsbard, CA, USA).
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PCR amplication and high-throughput sequencing. e PCR amplication and high-throughput
sequencing was performed as explained in a previous study4. Equal concentration of bacterial and fungal DNA
was used (~ 1ng) for PCR amplication of 16S rRNA V3 hypervariable region and ITS1 region, respectively (see
supplementary methods for details on primers and protocol used). Four bacterial samples and two fungal sam-
ples did not show any amplication, and therefore were not included in the study. Aer evaluating the amplied
products on 2% w/v agarose gel, the products were puried using Ampure XP kit (Beckman Coulter, Brea, CA
USA). Amplicon libraries were prepared using primers for V3 and ITS1 regions by following the Illumina 16S
metagenomic library preparation guide. e metagenomic libraries were prepared using Illumina Nextera XT
sample preparation kit (Illumina Inc., USA).
Based on the minimal DNA concentration (> 0.2ng/µl) required to carry out the library preparation for shot-
gun sequencing, 14 subjects with healthy scalp and 14 with dandru scalp were selected from each time-point for
shotgun metagenome sequencing of their bacterial and fungal DNA. us, a total of 398 bacterial and 400 fungal
amplicon samples, and 84 bacterial and 84 fungal metagenomic samples were sequenced in this study (TableS2).
Both the amplicon and shotgun metagenome libraries were evaluated on 2100 Bioanalyzer using DNA1000
kit for amplicon, and High Sensitivity DNA kit for metagenome (Agilent Technologies, Santa Clara, CA, USA) to
estimate the library size. e libraries were further quantied on a Qubit 2.0 uorometer using Qubit dsDNA HS
kit (Life technologies, USA) and by qPCR using KAPA SYBR FAST qPCR Master mix and Illumina standards and
primer premix (KAPA Biosystems, Wilmington, MA, USA) following the Illumina suggested protocol. Libraries
in equal concentrations were loaded on Illumina NextSeq 500 platform using NextSeq 500/550 v2 sequencing
reagent kit (Illumina Inc., USA) and 150bp paired-end sequencing was performed for both types of libraries at
the Next-Generation Sequencing (NGS) Facility, IISER Bhopal, India.
Assignment of bacterial 16S rRNA (V3) and fungal ITS1 amplicon reads. e raw sequence data
was subjected to quality trimming and ambiguity ltering using NGSQC toolkit and the paired-end reads were
assembled for each amplicon sequence using FLASH48,49. Quality ltration of fastq reads was carried out using
NGSQC toolkit and all the reads with 80% of bases ≥ Q30 quality scores were selected for further analysis. Prim-
ers from the reads were removed using Cutadapt50 and reads without the primer sequences were discarded.Clus-
tering was carried out using closed-reference OTU picking and de novo OTU picking protocol of QIIME v1.951
at ≥ 97% identity. e custom ITS1 database prepared previously4 and Greengenes database v13_5 were used as
a reference for fungal and bacterial taxonomic assignment, respectively52.
α-diversity was calculated using the Shannon index metrics and observed species aer rarefying from 100
sequences at a step size of 6,000 for V3 as well as for ITS1 amplicons using QIIME v1.9. Pielou’s evenness was
calculated to identify the distribution of species with respect to their proportion in each sample groups using
the R-package53. Weighted UniFrac distances were measured for the bacterial population, and not for fungal
samples, due to the highly variable nature of ITS1 sequences, which makes them dicult to interpret informative
and meaningful phylogenetic information54,55.
For the taxonomic assignment of de novo OTUs, sequences were aligned against the respective databases
using BLAT, and the assignment was performed using Lowest Common Ancestor (LCA) algorithm52,56. e
negative control samples showed a high abundance of fungal genus Pachysolen and bacterial genus Actinotalea,
which are commonly found in environments such as air and soil, and not associated with the skin or scalp57,58.
Hence, the OTUs from these genera were excluded from the analysis.
Shotgun metagenomic data analysis. Metagenomic reads with 60% bases above Q25 were considered
for the analysis49. For fungal metagenome, the bacterial contaminant reads were removed by alignment against
the bacterial reference genomes retrieved from NCBI, and the human contaminant reads were removed using
BMTagger59. e remaining fungal reads from each sample were assembled independently into contigs using
SOAPdenovo at a k-mer size of 75bp.
For bacterial metagenome, the human and fungal contaminant reads were removed by aligning the sequences
using BLAT against human HG19 assembly and custom fungal genome database, respectively60. ese fun-
gal genes and genomes were downloaded from Aspergillus database, FungiDB (release-30), Fungal Genome
Initiative-Broad Institute, Fungi Ensembl, Saccharomyces Genome Database, Candida Genome Database and
NCBI to construct a custom fungal genome database56,61–65. If any fungal gene sequences were not available in
these databases, the gene sequences were extracted from the genome sequences based on the gtf information
using SAMtools66. e high-quality reads were assembled at a k-mer length of 47 (the k-mer length was esti-
mated using kmerGenie67) using SOAPdenovo, and the genes were predicted from the assembled contigs using
MetaGeneMark68,69.
e fungal contigs with ≥ 300bp length were selected and fungal genes were predicted from scaolds using
AUGUSTUS1,68,70. In order to increase the coverage of genes from fungal genomes found in our dataset, a total of
2,421,207 CDS were added from 303 fungal genomes from Ensembl fungi database. For bacteria, an additional
parameter of identity > 50% with ≥ 60% coverage or aligned length > 300 was used. e relative abundance of each
KO was calculated by adding up the abundance of genes mapping to the same KO ID, which was then used to
calculate the relative abundance of KO ID in each sample. A similar approach was used to calculate the relative
abundance of eggNOGs in each sample.
Non-redundant bacterial gene catalogue was generated by using CD-HIT, which consisted of 19,729,749 bac-
terial genes. A total of 207,763 genes were used as a reference fungal gene set consisting of non-redundant 27,937
genes from assembled metagenomes combined with CDS obtained from Ensembl Fungi genomes database71. In
total, 587,400 bacterial and 81,395 fungal non-redundant genes were identied in the dataset (see supplementary
methods for details on gene quantication).
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Taxonomic assignment of reads from metagenomic data. e fungal reference genomes were
retrieved from National Centre for Biotechnology Information (NCBI). e archaeal and bacterial genomes
were retrieved from NCBI and Ensembl database. e metagenomic reads were aligned to the reference fungal
and bacterial genomes and the mapped reads were considered for further analysis72,73.
KEGG assignment of genes. e KEGG v60 was updated by retrieving new sequences for KO IDs from
the KEGG server74. e bacterial and fungal genes were annotated by alignment against KEGG and eggNOG
v4.0 databases75–78. Protein sequences were assigned to eggNOG and KEGG orthologous groups based on the
highest scoring hit containing at least one HSP (highest-scoring segment pair) above 60 bits and E-value ≤ 10–6
as described previously4. In total, 4,064 and 3,532 KO IDs were obtained from the combined fungal and bacterial
gene catalogue, respectively. Pathway abundance was calculated by adding the relative abundance of each KO ID
belonging to a particular pathway.
Statistical analysis. e species abundance and KEGG pathway composition were compared between dif-
ferent groups using Wilcoxon test to identify signicant (p ≤ 0.05) variations. All the comparisons were per-
formed pairwise for each group using R soware79. In this study, same subjects were sampled at three dierent
phases, therefore, to identify the species and pathways that presented signicant (p ≤ 0.05) variations across the
three phases, repeated measures ANOVA was performed. e species that showed a relative abundance of ≥ 1%
in at least 20 samples were considered in this analysis. To identify the signicantly varying fold-change in species
abundance due to treatment, the fold-changes in species abundance were calculated as t = 2/t = 1 for each subject
and compared using Wilcoxon test.
e Spearman’s Rank Correlation Coecients with FDR adj. p-value were calculated to correlate clinical
parameters with species. Species with ≥ 1% proportion in at least 20 samples were selected for the correlation
analysis. Correlations were tested across all the phases to obtain the largest set of values for each parameter. Hier-
archical clustering algorithm was used for clustering the highly-correlated pathways and species in the samples.
Figures2b, 3b, 5, 6, S7a and S7b were created using ‘ggplot2’ package in R version 3.080. Figure4 was created
with ‘heatmap2’ function using ‘gplots’ package in R79. e FiguresS4a and S4b were created using the ‘boxplot’
function from ‘graphics’ package in R79.
Data availability
e high-throughput sequence data generated from this study have been deposited under the project number
PRJNA415710 in the NCBI BioProject database and will be made publicly available on publication or on request
at the time of peer review.
Received: 7 June 2020; Accepted: 4 February 2021
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Acknowledgements
Authors would like to thank Dr. Mukta Sachdev, Medical Director, MS Clinical Research for her support during
the clinical study. We also acknowledge Francois Pradier, Director, L’Oréal Research and Innovation, India for
his support for the study and Dr. Audrey Gueniche for her help in interpreting the clinical results. We thank
Subarna Saha, Mahesh M Veeranagaiah and Prashant Hegde for participating in preparing the clinical protocol
and carrying out the clinical sampling. We thank the NGS facility and HPC facility at IISER Bhopal for provid-
ing the infrastructure to carry out the sequencing experiments and computational analysis, respectively. RS and
DBD acknowledge DST-INSPIRE and UGC (Govt. of India), respectively for providing research fellowships.
Author contributions
C.C., N.M. and V.K.S. conceived the idea. C.C., N.R., L.B., N.M. and V.K.S. designed the study. R.S., C.C., N.M.
and V.K.S. designed the experiments. R.S. carried out the experimental processing and sequencing of the DNA
samples. P.M. performed the computational analysis of amplicon data. P.M. and D.B.D. performed the compu-
tational analysis of the metagenomic data. P.M., D.B.D. and R.S. carried out the statistical analysis of amplicon
and metagenomic data and its correlation with the clinical parameters. R.S., P.M., C.C., D.B.D., N.M. and V.K.S.
interpreted the results and prepared the gures and tables. R.S., P.M., C.C., D.B.D., N.R., L.B., N.M. and V.K.S.
prepared the manuscript. All authors read and approved the nal manuscript.
Funding
is study was supported by L’Oréal Research and Innovation (Project no. CONS/BIO/2015050) and intramural
funding from IISER Bhopal.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 021- 86454-1.
Correspondence and requests for materials should be addressed to N.M.orV.K.S.
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