1 Supplementary Notes

2

3 Supplementary Note 1. Functional characterization

4 Facial and gut microbiomes comparisons

5 We also identified 2 genes from lipid metabolism, 2 genes to glycan biosynthesis, and metabolism

6 and peptidoglycan biosynthesis, and 1 gene present only the face dataset related to

7 phenylpropanoid biosynthesis from Alistipes (related to protection from UV light, and defence

8 against herbivores and pathogens [1–3]). Interestingly, ~98x more in the face microbiome

9 is annotated as moderate halophilic (face= 11,239, gut= 115), as well as ~239 times more

10 psychrophilic bacteria in the face (face= 18,886, gut= 79). The top 5% with the largest difference

11 in abundance from the pathways that drive variation between the face and gut microbiomes,

12 contains the metabolism of fructose and mannose, starch and sucrose, galactose, and amino sugar

13 and nucleotide sugar, all of them more abundant in the gut microbiome.

14

15 Microbial cores

16 Besides the defined microbial taxonomic and functional cores obtained from the MGmapper

17 results (Additional File 11), we defined other types of cores based on the taxonomies assigned to

18 the annotated genes. The percentage of annotated genes in the face dataset has a median of 72.61%

19 (mean of 57.8%), and a median of the gut dataset is 66.75% (mean of 65.08%). From the nr gene

20 catalogue we defined 2 types of cores. A strict core, in which we keep those genes present in a

21 given minimum number of samples taking the taxa from where the genes derive into account

22 (Table S5). The second type of core, a relaxed one, does not take of the genes into

23 account, and keeps those genes present in a given minimum number of samples (Table S6).

1 24 Looking at the taxonomic identifications from the protein annotations, we found 12 virus taxa in

25 all the face samples, 7 fungi, and 26 bacterial strains. In the gut samples, we found 9 bacterial

26 strains, 11 fungi, and 18 viruses.

27

28 Cadaverine and putrescine: Three of the main molecules produced in a decomposing body are

29 nitrate reductase (converting nitrite to ammonia) [4], cadaverine (lysine decarboxylase) [5], and

30 putrescine (ornithine decarboxylase) [5] (Additional File 5). In this regard, we identified in the

31 face MOCAT nr strict core a spermidine synthase gene from Janthinobacterium sp. HH01, and

32 spermidine/putrescine ABC transporter ATPase in both face and gut MOCAT strict cores from

33 Herbaspirillum sp. GW103. Sulphur compounds are also emitted by decomposing carcasses [6],

34 likely derived from methionine and cysteine degradation. This likely explains the identification of

35 the metabolism of cysteine and methionine as the two most abundant subclasses from the amino

36 acids metabolism in both face and gut microbiomes. A carcass also produces volatile organic

37 compounds [7], such as acetone, methyl ethyl ketone, toluene, ethylbenzene, m,p-xylene, styrene,

38 and o-xylene. In this regard, toluene degradation is one of the subclasses not driving variation in

39 the face functional intra samples comparison, and the MOCAT face cores have more genes related

40 to xenobiotics biodegradation metabolism than those of the gut microbiome (Additional File 5).

41

42 Supplementary Note 2. Microbiome cores identifications

43 Core microbiome identification: In the filtered MGmapper taxonomic profiling, we identified

44 1,483 species in the facial samples, 638 of which are in at least 50% of the samples (relaxed core),

45 and only 184 in at least 80% of the samples (strict core). In the gut microbiome we found 1,419

46 microbial species, with only 322 present in at least 50% of the samples, and 129 in at least 80%.

2 47 In the functional characterization we identified a total of 238,065 nr unique bacterial genes in the

48 face microbiome and 387,951 nr unique bacterial genes in the gut microbiome (Additional File 4,

49 Tables S4, S5). Besides the defined microbial taxonomic and functional cores obtained from the

50 MGmapper results (Additional File 11), we defined other types of cores based on the taxonomies

51 assigned to the annotated genes. The percentage of annotated genes in the face dataset has a median

52 of 72.61% (mean of 57.8%), and a median of the gut dataset is 66.75% (mean of 65.08%). From

53 the nr gene catalogue we defined 2 types of cores. A strict core, in which we keep those genes

54 present in a given minimum number of samples taking the taxa from where the genes derive into

55 account (Table S5). The second type of core, a relaxed one, does not take taxonomy of the genes

56 into account, and keeps those genes present in a given minimum number of samples (Table S6).

57 Looking at the taxonomic identifications from the protein annotations, we found 12 virus taxa in

58 all the face samples, 7 fungi, and 26 bacterial strains. In the gut samples we found 9 bacterial

59 strains, 11 fungi, and 18 viruses.

60

61 Supplementary Note 3. Digestive role of the gut microbiome

62 Intestinal microbiome related to digestion: Among the taxa present in higher abundance in the

63 face microbiome than in the gut microbiome, we identified taxa and functions that are usually part

64 of the gut microbiome of mammals (Additional File 3). These bacteria could be derived from the

65 carrion but be removed from the vulture gut microbiome. For example, present only in the face

66 dataset is Cellulophaga lytica, which is capable of degrading proteins and polysaccharides [8], as

67 well as Flavobacterium columnare, which produces gelatin-degrading and chondroitin sulfate-

68 degrading enzymes [9,10]. This is relevant given that chondroitin sulfate is one of the main

69 structural components of cartilage. Although we did not identify these genes from F. columnare,

3 70 we identified chondroitin sulfate ABC lyase genes in both face (4 genes from Bacteroides and

71 Proteus) and gut microbiomes (13 genes from Bacteroides, Edwardsiella, and Proteus).

72

73 Fusobacterium digestive roles: It has been proposed that the abundance of Fusobacterium in the

74 gut could aid in the digestion of meat, given their ability to metabolize amino acids [11,12]. This

75 suggestion is supported by the finding of F. nucleatum and F. varium in the vulture’s gut

76 microbiome. One of the most abundant genes in the gut microbiome is an alpha-2-macroglobulin

77 family protein from F. mortiferum (the most abundant Fusobacterium in the gut), this protein has

78 been suggested to be used in bacteria as a colonization rather than a virulence factor [13]. Besides,

79 eukaryotic alpha-2-macroglobulin, produced by the liver, binds to and removes MMP-2 and MMP-

80 9 (active forms of the gelatinase), which is produced in the stomach to digest gelatin [13,14].

81 However, gelatin’s colloidal properties aid in the digestion of various types of food [15,16].

82 Furthermore, bacterial alpha-2-macroglobulin can be structurally very similar to that of eukaryotes

83 [17]. This suggests that Fusobacterium could also be playing digestive aiding roles in the vulture

84 gut.

85

86 Supplementary Note 4. Taxonomic characterization

87 Pathogenic characterization: Looking at the identified bacteria taking into account the strain

88 information (Additional File 12), the maximum number of potentially pathogenic bacteria

89 identified in a sample (a face sample) was 482, and the minimum was 10, with a mean of 159.8.

90 Each pathogen was present in a mean number of 11.98, a minimum of 1, and a maximum of 75

91 (Clostridium perfringens ATCC 13124 and Clostridium perfringens str. 13). We found that the

92 face has more different species of potential pathogens than the gut (P= 0.036, face mean= 189.79,

4 93 gut mean= 137.29). Present in at least 90% of the samples are three Clostridium perfringens strains

94 which produce gas gangrene [18], and one Stenotrophomonas maltophilia, which produces

95 bacteremia, bronchitis, pneumonia, and urinary tract infection [19]. In the gut samples, the most

96 abundant hosts for the potentially pathogenic bacteria are human, chicken, turkey, cattle, pigs, and

97 mouse. For those in the face, the most abundant hosts are human, followed by cattle, and plants.

98 Among the 19 potentially pathogenic bacteria present only in the gut samples are Brachyspira

99 pilosicoli, Campylobacter coli and Campylobacter jejuni strains, some strains of C. difficile and

100 E. coli, Salmonella enterica strains, and some Shigellas (S. boydii, S. dysenteriae, and S. flexneri).

101 And among those 50 present only in the face dataset, we found various strains of Acinetobacter

102 baumannii, Actinobacillus pleuropneumoniae, Burkholderia, Capnocytophaga gingivalis ATCC

103 33624, some Vibrio species (V. harveyi HY01, V. ordalii ATCC 33509, V. shilonii AK1, V.

104 splendidus 12B01, and V. tasmaniensis ZS-17), various Xanthomonas, among others (Table 2).

105

106 Fusobacteria and Clostridia pathogenicity: It has been speculated that the large amount of

107 Fusobacteria and Clostridia in the vulture gut outcompetes other more virulent and toxic relatives,

108 being harmless pathogenic versions that occupy the space and resources that more pathogenic

109 versions would occupy otherwise, thus serving as a sort of probiotics [20]. To examine this

110 hypothesis, we searched for toxin-related genes from these taxa in the gut functional core. We

111 identified two putative enterotoxins from C. perfringes, and interestingly, also a protein in two gut

112 samples from the bacteriocinogenic plasmid pIP404 from C. perfringes [21]; less toxin-related

113 genes were found for Fusobacterium (Additional Files 9, 10).

114

5 115 Supplementary Note 5. Microbiome mediated protection

116 Probiotics and beneficial functions: One of the most abundant taxa in the face microbiome is

117 Pseudomonas fluorescens, which can produce the antibiotic mupirocin [22]. This antibiotic is used

118 for treating skin, ear, and eye disorders by interfering with isoleucyl-tRNA synthetase activity of

119 pathogens, suggesting it may play a role in treating illnesses that some bacteria could cause on the

120 vulture. Among the potentially health-beneficial bacteria identified in higher abundance in the face

121 microbiome is Arthrobacter phenanthrenivorans (max. coverage in the facial samples= 4.4%,

122 max. coverage in the gut samples= 0.4%, with 163 annotated genes in the face and 66 annotated

123 genes in the gut), which is able to degrade phenanthrene [23], a skin-irritating poly-cyclic aromatic

124 hydrocarbon. Also, part of the facial functional core that takes taxonomy into account is

125 Hylemonella gracilis (max. coverage= ~4%, 69 assembled genes), which has been shown to

126 prevent long term colonization by Yersinia pestis [24]. Among the plasmids present only or most

127 abundantly in the gut microbiome, we identified those of probiotic bacteria Lactobacillus brevis

128 KB290 [25], L. casei W56 [26], L. paracasei [27], L. salivarius CECT 5713 [28], an L. reuteri

129 SD2112 [29], which produces the antimicrobial reuterin [30]. We also identified plasmids from

130 Lactobacillus sakei (max. coverage in the gut samples= 91.5%, max. coverage in the face samples=

131 26.85%), from which we also identified a putative bacteriocin immunity protein and a type II

132 secretion system protein coding gene in the nr gene catalogue. Folate has been related to skin

133 cancer prevention [31]. Notably, one of the most abundant sub-pathways in the face intra-sample

134 comparison was the folate biosynthesis. In this regard, we also identified the gene dihydropteroate

135 synthase type-2 from Acinetobacter sp. NIPH 899 in the facial microbiome. Furthermore,

136 aminobenzoate is used to treat skin disorders, and we found that the aminobenzoate degradation

6 137 subclass from the xenobiotics degradation metabolism is the most abundant in both face and gut

138 microbiomes.

139

140 Antibiotics: We identified several genes for the biosynthesis of antibiotics. Among the most

141 abundant metabolic subclasses in both face and gut microbiomes is the biosynthesis of

142 carbapenem. From the metabolism of terpenoids and polyketides, the most abundant subclasses in

143 the face and gut microbiome are the biosynthesis of tetracycline, macrolides, and ansamycins.

144 Also, among those subclasses not driving functional variation in the face microbiome are the

145 biosynthesis of monobactam, anthocyanin, and ansamycins. Furthermore, in the face MOCAT

146 strict core, we identified a gene involved in the production of naphthocyclinones antibiotics [32]

147 from Herbaspirillum frisingense [33].

148

149 Phages: In accordance to a potential phage therapy strategy, among the phages present only in the

150 face microbiome we identified the phage phi MR11, which eliminates multidrug resistant

151 Staphylococcus aureus [34]. Also Acinetobacter phage Petty, which infects Acinetobacter

152 baumanii [35], a multidrug resistant pathogen usually isolated from wounds and also identified in

153 our datasets. The phage Acibel004, active against A. baumanii [36], is also present only in the face

154 microbiome. From the face functional strict core, the most abundant phage is BPP-1, which infects

155 pathogenic Bordetella bacteria [37]. Among the identifications is the Enterobacteria phage P22

156 present only in the gut samples, infects the pathogenic S. typhimurium [38], which we also detected

157 in the gut microbiome. Furthermore, we identified the phage L-413C, which is specific for Yersinia

158 pestis [39] and identified as more abundant in the gut samples. Also present is the phage phi

159 CD119, which reduces toxin production in C. difficile [40]; notably, we also identified genes

7 160 related to C. difficile virulence. Also, the Enterobacteria phage HK620 was identified as more

161 abundant in the gut microbiome, this phage absorbs the O-antigen of E. coli H [41]. The gut

162 functional strict core contains the phage phiCD6356, which infects C. difficile [42], and phage

163 SPN3US, which has shown effective inhibition of Salmonella enterica [43]. Notably, we identified

164 putative virulent genes from S. enterica in the gut microbiome (Additional File 8).

165

166 Defense versus eukaryotes: Besides bacterial killing strategies, we also identified insecticide,

167 fungicide, and antiparasitic related taxa and genes. Among those taxa significantly more abundant

168 in the face microbiome we identified Lysinibacillus sphaericus, which produces insecticidal toxins

169 that control mosquito growth [44], and for which we assembled the gene coding for sphaericolysin,

170 an insecticidal pore-forming toxin. We also identified Pseudomonas entomophila (8 genes in the

171 gut samples, max. coverage in the gut samples= 0.2%, max. mapping reads in the gut samples=

172 216; 175 genes in the face samples, max. coverage in the face samples= 0.5%, max. mapping reads

173 in the face samples= 542) which infects insects causing lethality in fly larvae and adults [45,46]

174 and for which we identified in the nr gene set catalogue an insecticidal toxin SepC/Tcc class. We

175 also identified violaceusniger (present in 20 face samples, 0.1% max. coverage, 214

176 max mapping reads, 28 assembled genes; 11 gut samples, 0.03% max. coverage, 58 max mapping

177 reads, 15 assembled genes), which is an antifungal for various plant fungal pathogens [47,48].

178 Among the antiparasitic taxa in the face relaxed core, we identified Kitasatospora setae, which is

179 capable of producing the antitrichomonal setamycin [49], and Streptomyces bingchenggensis,

180 which produces the anthelmintic macrolide milbemycin [50]. We also identified Heterorhabditis

181 bacteriophora (found in 34 gut samples and 24 face samples), which kills pests like fleas, ants,

182 and flies by releasing Photorhabdus luminescens bacteria from their digestive tract [51].

8 183 Interestingly, we also identified this Photorhabdus bacteria (max. mapping reads in the gut

184 samples= 462, max. mapping reads in the face= 20). Although present in low amounts, we also

185 identified in 21 of the gut samples the Dictyostelium genera (D. intermedium and D. citrium, max.

186 mapping reads in the gut samples= 596, max. mapping reads in the face samples= 36), which is a

187 bacteriovorous protozoa present in the soil, where they keep bacterial populations in balance [52].

188 We also identified Adineta vaga, which feeds on dead organic matter, mainly dead bacteria and

189 protozoans [53] in 93.6% of the intestinal samples and 54.5% of the facial samples (gut normalized

190 abundance= 54,230, face normalized abundance= 7,972).

191

192 Non-antibiotic mechanisms: Among the taxa more abundant in the face microbiome, it is

193 interesting to note the identification of bacteria capable of growing in cancerigenous substances

194 and producers of anti-cancer immunosuppressant substances. This is of relevance given that such

195 bacteria might produce antimicrobial alternatives or products beneficial to the vulture to aid in

196 fighting the constant aggression of the toxins present in the carcasses. Present in the relaxed face

197 core we identified Chromobacterium violaceum [54] and Janthinobacterium sp. HH01 [55], which

198 produce violacein, an anticancer, antibacterial, antifungal, and antiviral compound.

199 Janthinobacterium sp. HH01 is also present in the face functional strict core. The bacteria

200 Polaromonas naphthalenivorans, capable of degrading the potentially carcinogenic naphthalene

201 [56], was present more abundantly in the face microbiome (max. mapping reads in face samples=

202 3,194, max. mapping reads gut samples= 60). This is of relevance given that 1-methyl naphthalene

203 is produced in carrion decomposition [57,58].

204

9 205 Biosurfactants represent a strong antimicrobial means of blind killing, including bacteria with

206 antibiotic resistance that would otherwise be difficult to treat. Interestingly, we identified the

207 biosurfactant producer fungi Yarrowia lipolytica [59], and the bacteria Rhodococcus erythropolis

208 [60] in both face and gut microbiomes. We also identified surfactin biosynthesis regulatory

209 proteins from Flavobacteriaceae. Furthermore, annotation of the non-mapping reads with

210 DIAMOND identified various surfactin synthetase proteins from various genera in the face

211 microbiome. Surfactin [61,62] is a very powerful surfactant that serves as antibacterial, antiviral,

212 antifungal, and attacks red blood cells with deadly efficiency.

213

214 Biofilm and colonization resistance: The presence of biofilm forming bacteria has been

215 suggested to play a protective role for the host [63]. We identified the biofilm-forming bacteria

216 Pseudomonas fluorescens [64] in higher abundance in the face and as part of the strict taxonomic

217 face microbiome core. Interestingly, in the gut functional core, we identified biofilm formation

218 promoter proteins from F. mortiferum, such as sialic acid-binding periplasmic protein [65], and

219 rubrerythrin [66]. And from C. perfringens, such as UDP-glucuronic acidepimerase [67], putative

220 alginate biosynthesis protein AlgI [68], and fibronectin-binding protein [69], as well as toxin-

221 antitoxin biofilm protein from E. coli [70] (Additional File 8). These results suggest that potentially

222 pathogenic bacteria could form biofilms which allow them to thrive in the gut.

223

224 Pathogenic biofilm formation: Notably, a biofilm-mediated protection scenario requires a special

225 interaction with the vulture’s immune response, otherwise a scenario such as that in the biofilm

226 formation in patients with cystic fibrosis (CF) would develop. The biofilm in CF patients results

227 in clinical symptoms due to the host immune response producing tissue damage as a result of the

10 228 chronic inflammation mediated by the immune complex that is trying to attack the highly resistant

229 bacteria in the biofilm [71]. Thus, the colonization resistance mechanism of the vulture

230 microbiome mediated by the biofilm formation requires that the vulture’s immune system does not

231 react against with a chronic inflammatory response. Interestingly, the

232 PIK3AP1 and TNFAIP3 genes, involved in B-cell development, antigen presentation, auto-

233 inflammation, and NF-kappa B activation, have been found to contain potentially functional

234 altering amino acid changes in the cinereous vulture (Aegypius monachus) [72]. Even more, in CF

235 patients it has been shown that sub-minimal inhibitory concentrations of some antibiotics, such as

236 erythromycin (from which we identified related genes in our nr gene set, Additional File 6) and

237 azithromycin, suppress the production of exoproducts, such as proteases and phospholipase C [73–

238 75]. The inhibition of these exoproducts reduces the antigenic load and thus could lead to the

239 decrease of immune system response. Similar modulatory mechanisms could be taking place in

240 the vulture gut microbiome, were we identified various antibiotics.

241

242 Supplementary Note 6. Resistance genes

243 In the ResFinder database search, we identified resistance genes in 17 out of the 33 face samples

244 (min= 6, 1st Qu= 18, median= 36, mean= 44.35, 3rd Qu= 72, max= 107), and in 36 out of the 46

245 gut samples (min= 6, 1st Qu= 10, median= 15, mean= 19.31, 3rd Qu= 25, max= 59), totalling 215

246 genes (166 in the face, and 139 in the gut) against 15 substances (15 in the face, and 14 in the gut).

247 There is no statistical difference in the number of substances with resistance genes identified by

248 vulture species (P= 0.30, C. atratus mean= 4.175, C. aura mean= 3.405), neither by sample type

249 (P= 0.92, gut mean= 3.84, face mean= 3.76), however there is a difference in the abundance, being

250 more abundant in the gut microbiome (P= 0.018, gut normalized mean= 88,016.84, face

11 251 normalized mean= 56,985.73) (Figure S14). The one substance with resistance genes in the most

252 number of samples (52) is tetracycline, and there is no substance with resistance genes in more

253 than 90% of the samples. In at least 50% of the face and gut samples there are resistance genes for

254 aminoglycoside, lincosamide, macrolides, and tetracycline. Only face samples were found to

255 contain resistance genes against sulphonamide. Interestingly, in the gut dataset there is an

256 abundance of genes resistant to lincosamide, which is used to treat pseudomembranous colitis

257 caused by C. difficile [76].

258 Searching against the Resfams database, we identified 170 different resistance genes in the face,

259 and 170 in the gut, totalling 170 unique resistance proteins. Samples have a minimum of 0

260 resistance proteins (one face sample) and a maximum of 170 (4 gut samples and 2 face samples),

261 with a mean of 104.3 proteins per sample, with each resistance protein being present in a mean

262 number of 47.23 samples (Figure S13C). There is a significant difference in the number of

263 identified proteins with resistance to antibiotics between face and gut (P= 0.049, face mean= 87.3,

264 gut mean= 117.0) (Figure S13A), although there is no statistical difference in the abundance (P=

265 0.69). The protein present in the most number of samples (69) is from the phosphotransferase

266 enzyme family, which confers resistance to various aminoglycosides [77]. The resistance genes

267 identified from the ResFams search can be classified as resistant to the following types of drugs:

268 i) for treatment of various diseases, such as urinary and respiratory diseases, meningitis,

269 tuberculosis, and against Staphylococcus and Streptococcus, ii) for the treatment of enteric

270 diseases, and iii) for the treatment of other diseases caused by fungi or protozoa. Interestingly,

271 there were also genes resistant to indiscriminate antibiotics, such as surfactants, organic solvents,

272 heavy metal ions, antifolates, and carcinogens and anticarcinogens.

273

12 274 Among the most abundant genes from the face MOCAT nr gene set we found antibiotic resistance

275 genes for aminoglycoside from A. baumanii, and kanamycin from Staphylococcus epidermidis. In

276 the search of the face dataset against the ResFinder database we identified a differentially abundant

277 number of resistance genes to macrolide. Given that some macrolides have antibiotic or antifungal

278 activity [78,79], their higher abundance in the face is expected taking into account that the face

279 has a significantly greater fungi diversity (P= 0.029), with many of them being derived from plant

280 pathogens. The face microbiome also contains more resistance genes towards phenicol than the

281 gut microbiome (rescaled mean face= 112,149.94, rescaled mean gut= 2,177.54). Their use against

282 infections in body parts such as eye and ear [80] could explain their higher abundance in the face

283 microbiome. In the ResFams database search we also identified resistance genes to drugs for the

284 treatments of diseases such as enteric diseases (e.g. streptogramin [81] and bicyclomycin [82]),

285 and tuberculosis (e.g. aminoglycoside [83] and oxazolidinones [84]). Interestingly, many of the

286 antibiotics with a resistance gene also pose serious adversities to the vulture, such as macrolides

287 [85] and cephalosporin [86], which cause digestive disturbances to humans.

288

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