Indigenous infants in remote Australia retain an ancestral gut microbiome despite encroaching Westernization

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The Western diet modifies the gut microbiome, promoting cardiometabolic disorders that disproportionately affect Indigenous Australians. Studies of Indigenous gut microbiomes are underrepresented in the literature and comparative studies in young children living in traditional and Western societies are lacking, limiting our understanding of early-life microbiome development in different cultural contexts. Therefore, we analyzed gut metagenomes of 50 Indigenous Australian infants (median age < one year) living remotely with variable access to Western foods, compared to age- and sex-matched non-Indigenous infants living in urban Australia. Indigenous infants exhibited greater alpha diversity and significant differences in beta diversity, with 114 species and 38 genera differing in abundance. Some taxa were unique to Indigenous infants, who had higher carriage of Bifidobacteria at younger ages and Prevotella at older ages. In contrast, non-Indigenous infants had a high abundance of Phocaeicola ( Bacteroides ) across ages. Notably, Indigenous infants had markedly higher numbers of gut viruses and fungi. These findings reveal that despite encroaching Westernization, these Indigenous infants begin life with a gut microbiome that retains key features of traditional societies worldwide. The Western gut microbiome has not been transmitted inter-generationally and has not yet emerged, attesting to the dominant influence of a remote environment and enduring traditional lifestyle. This study provides crucial insights into the early-life microbiome in an Indigenous population and highlights the importance of preserving traditional lifestyles to maintain microbiome diversity. Health sciences/Molecular medicine Biological sciences/Computational biology and bioinformatics/Sequence annotation Indigenous Australian infants gut microbiome metagenomic sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Indigenous Australians are distinguished as the oldest, continuous living culture, successful as hunter-gatherers and subsistence farmers for over 60,000 years, prior to European settlement 1 . Along with the degradation of their traditional culture, Indigenous Australians have experienced a marked increase in cardiometabolic, non-communicable diseases (NCDs), including obesity, diabetes, hypertension, cardiovascular diseases, chronic kidney disease and cancers 2 , 3 . NCDs are associated with chronic low-grade, systemic inflammation 4 , 5 and a shift to a less diverse gut microbiome (dysbiosis) 6 , 7 . These pathophysiological features are considered to be a maladaptive response to a ‘Western’ lifestyle, especially the‘Western’ diet which is high in saturated fat, simple carbohydrates, additives and processed components, and low in fiber 7 , 8 , in addition to other less understood influences such as the cumulative burden of spiritual, cultural and environmental stressors 9 . Following colonisation at birth, the gut harbors the largest and most diverse microbiome, critical for the development and ongoing health of the gut, immune and other body systems. Distinct taxonomic and functional differences have been identified between the gut microbiomes of traditional hunter-gatherer or subsistence societies compared to modern Western societies 10 , 11 , which provide insights into the evolution of the gut microbiome under the influence of ethnicity, environment and lifestyle. The gut microbiome of Western compared to traditional societies is less diverse, with a lower abundance of fiber-degrading bacteria that produce anti-inflammatory short chain fatty acids and a higher abundance of mucus-degrading bacteria, leading to impaired integrity of the gut epithelium with leakiness of bacterial products and systemic inflammation 12 . The Western gut microbiome contains a higher abundance of Bacteroides, Enterobacteria and Akkermansia, and a lower abundance of beneficial Bifidobacteria and Lactobacilli, whereas Prevotella, Treponema, Proteobacteria, Clostridiales and Ruminobacter predominate in the traditional gut microbiome, some of which have disappeared from the Western gut microbiome 10 , 11 . Counted among the hundreds of clans of Indigenous Australians are the Yolngu people, living in a remote area of northern Australia, whose traditional customs endure despite an increasingly pervasive Western lifestyle. Their diet comprises mainly Western style food and beverages with a variable mix of traditional foods (see Methods). The children are increasingly exposed to sugar-sweetened beverages and ultra-processed and takeaway foods, and experience periods of food scarcity 13 . Indigenous Australians appear to have a genetic propensity for strong inflammatory responses 14 . Indeed the Yolngu children display elevated concentrations of circulating inflammatory cytokines (Hasthi Dissanayake, personal communication), consistent with gut microbiome dysbiosis and a predisposition to NCDs. Analysis of the oral 15 and upper respiratory 16 microbiomes of Indigenous Australian children by 16S rRNA gene amplicon sequencing has revealed the carriage of unique bacteria potentially associated with an increased prevalence of NCDs, but knowledge of the gut microbiome in young Indigenous children is lacking. Whether the gut microbiome of these Indigenous infants is ancestral and to what extent and at what age it might exhibit features of Westernization is unknown. The infant’s gut microbiome is shaped initially by vertical transmission from the mother, but also by genetic background and environmental exposures such as living conditions, psychological stress, diet, water, soil, animals, toxins, parasitic infections and antibiotics, which vary between populations and may distinguish Indigenous children living remotely from children living in urban settings. In order to expand knowledge of the remote, Indigenous gut microbiome in early childhood, and as a basis on which to understand the impact of the Western lifestyle, we used shotgun metagenomic sequencing to compare the gut microbiomes of 50 randomly-selected Indigenous Australian infants living in a remote Yolngu community to those of 50 age- and sex-matched non-Indigenous infants living in different urban areas of Australia. Results The study groups comprised 24 Indigenous and 24 non-Indigenous females, median (IQR) ages 294 (153, 428) and 293 (114, 433) days, respectively, and 26 Indigenous and 26 non-Indigenous males, median (IQR) ages 360 (222, 476) and 377 (226, 467) days, respectively. Their characteristics are summarised in Table 1. The groups did not differ by gestational age at delivery, mode of delivery or birth weight, but the frequencies of current and exclusive beastfeeding were each markedly higher in the Indigenous infants (P 100, present in three or more samples. Kraken2 classified 371 virus (Indigenous=367; non-Indigenous=353), 31 fungus (Indigenous=31; non-Indigenous=31), and 15 other eukaryote species following their taxonomic confirmation with BLAST (Indigenous=12; non-Indigenous=10). Complete bacterial abundance data are provided in Supplementary data (Supplementary Table 2_Metaphlan.xlsx); all Kraken2 virus and eukaryote abundance data are available in Supplementary data (Supplementary Figure 1_Kraken.xlsx). Bacterial taxa proportions at the genus level (Fig. 1) revealed a high prevalence of Bifidobacteria in Indigenous infants, especially at younger ages, and of Prevotella, especially at older ages, in contrast to non-Indigenous infants who had a high prevalence of Phocaeicola ( Bacteroides ) across all ages. Viruses (Fig. 2) were significantly more abundant in Indigenous than non-Indigenous infants (17.2 vs. 2.9 million counts, respectively), and were different; furthermore, their abundance profile was more consistent in Indigenous infants, possibly due to their geographic homogeneity. In Indigenous infants, the dominant viruses were Enterobacteria ( Escherichia ) phages (as classified by the International Committee on Taxonomy of Viruses, https://ictv.global/), viz., Quadragintavirus ev129, Tequatrovirus, Evevirus ev239 and Jouyvirus ev017. These viruses were virtually non-existent in non-Indigenous infants. The most common viruses in non-Indigenous infants were the CrAssphages: Carjivirus communis, Carjivirus hominis and Kingevirus communis, which infect Bacteroides 17 . The potential pathogen, human mastadenovirus, appeared in the top 25 viruses in both Indigenous and non-Indigenous infants, in the former being strain F and in the latter being strains C and D. Its occurrence was sporadic in both populations, being present in only a few infants but at high counts. The only other potentially pathogenic virus in Indigenous infants was Primate bocaparvovirus 2 (human bocavirus 2c), known to cause respiratory tract infections. Fungi (Fig. 3) were also significantly more abundant in Indigenous than non-Indigenous infants (mean counts/sample 7,799 vs 115 , respectively). Candida albicans (226,104 counts) was by far the most abundant in Indigenous infants, especially at a younger age, and Saccharomyces cerevisiae (1,122 counts) the most abundant in non-Indigenous infants, although this was predominantly due to a single individual (888 counts). After S. cerevisiae, Aspergillus luchuensis was most abundant in non-Indigenous infants (248 counts), with counts spread more evenly over several samples. Due to the limited number of non-fungal eukaryotic genomes classified in the Kraken2 database, species level classification was not reliable without the BLAST check step. The abundances of the 15 identified and BLAST-confirmed non-fungal eukaryote taxa are shown as a heatmap (Fig. 4). Total counts of these classified eukaryotes were higher in Indigenous than non-Indigenous infants (22,190 and 10,674, respectively). Several animal food taxa were present in both Indigenous and non-Indigenous infants, viz, Bos taurus (beef), Sus scrofa (pork). Gallus gallus (chicken), as well as plant foods, e.g., Zea mays (maize), Musa acuminata (banana) and vitis vinifera (grape). The mollusc, Mizuhopecten yessoensis (scallop) and Citrus sinensis (sweet orange) were present only in Indigenous infants, and Spinacia oleracea (spinach) and Fragoria vesca (strawberry) only in non-Indigenous infants. For non-food eukaryotes, the house dust mite, Dermatophagoides pteronyssinus, and two parasites, Cryptosporidium parvum , and Blastocystis hominis were present only in several Indigenous infants. Bacterial alpha diversity Alpha diversity results are presented in Supplementary data (Supplementary Table 3_Metaphlan_diversity). Richness, Shannon and Simpson alpha diversity indices in population, sex and age categories for each taxonomic level are shown in Table 2. Significant Shannon indices (P < 0.05) for the two groups by population (family), sex (genus) and age category (species) are plotted in Fig. 5. Indigenous infants had significantly greater alpha diversity, observed at the family level and above (Shannon [family] P = 0.012). Females had significantly higher diversity than males at all levels above species (Shannon [genus] P = 0.030). As expected, alpha diversity increased with age at the species level in both populations (Shannon P = 0.042). All other comparisons can be viewed in the Supplementary data. Bacterial beta diversity Beta diversity was significantly different between populations (adjusted P-value = 0.001) and between sexes (adjusted P-value = 0.001) (Fig. 6). The age category was significant over all pair-wise comparisons (P = 0.04); within-pair comparisons, only the youngest vs oldest age categories (0 vs 3 and 1 vs 3) were significant (P = 0.001 and P = 0.009, respectively). These differences are not expected to impact differential abundance analysis between populations, because samples were matched for sex and age. Differential abundance Differential abundance (DA) results are presented in 2data (Supplementary Figure 2_differential abundance.xlsx). DA was significant for 114 species, 38 genera, 12 families, 8 orders, 3 classes and 2 phyla. The 25 most differentially abundant taxa prevalent in both populations (most positive or negative ALDEx2 effect) are shown (Fig. 7). Species virtually exclusive to Indigenous infants were Megaspaera spp., Streptococcus lactarius, Caecibacter spp., Parolsenella spp. and Prevotella spp; those almost exclusive to non-Indigenous infants were Muricomes oroticus and Fecalibacillus ssp. Bifidobacteria ssp. were dominant in Indigenous infants and Intestinibacter bartlettii, Clostridium AQ innocuum and Ruminococcus ssp. were dominant in non-Indigenous infants. At the genus level, Megasphera , Caecibacter , Parolsenella , Prevotella , Allisonella , Dialister , Thermophilibacter , Paratractidigestivibacter , Acidominococcus , UBA7748 , Olsenella and Coriobacterium were virtually unique to Indigenous infants, whereas Intestinibacter, Sellimonas , Ruminococcus , Muricomes , Clostridium , Ventrimonas , UBA9414 , Hespelia and Erysipelatoclostridium were the dominant genera in non-Indigenous infants. Markers of gut pathology Derived from neutrophils, calprotectin in feces is used as a marker of gut inflammation 18 . The concentration of fecal calprotectin is higher in very young children 19,20 , but the reference range is not well defined. In young Finnish children, the upper limit is regarded as 100 mg/g 19 . At this value, fecal calprotectin was increased in 46/50 (92%) Indigenous infants and 12/50 (24%) non-Indigenous infants (median [IQR]: 1318 [515, 1,809] vs 39.9 [4.40,102], respectively; P=0.0001) (Table 1). Males (1,287 mg/g) and females (1,123 mg/g) did not differ. Serum iFABP is a marker of gut epithelial integrity 21 . A reference range is not available for young children. Therefore, based on the median value of a control group in a study of childhood inflammatory bowel disease 22 , we used the 1.5 x IQR outlier rule to define the upper limit as 1,664 pg/ml. Serum iFABP was increased in 6 (12%) of Indigenous infants and 7 (14%) of non-Indigenous infants (median [IQR]: 637 (419-1091) vs 689 (517-1572), respectively; P=0.126) (Table 1). Discussion Metagenomic sequencing revealed major differences in the gut microbiomes between closely age- and sex-matched Australian Indigenous infants living remotely compared to Australian non-Indigenous infants living in urban environments. This is the first such comparative study of the gut microbiome in infants of which we are aware. The gut microbiome of the Indigenous infants contained significantly greater numbers of bacteria, viruses and fungi, and displayed greater bacterial diversity, 114 bacterial species being differentially abundant. Some taxa present in Indigenous infants, e.g., species from the families Prevotellaceae , Spirochaetaceae and Succinivibrionaceae , were absent in non-Indigenous infants. This is reminiscent of the ‘VANISH’ (volatile and/or associated negatively with industrialized societies of humans) bacterial species, reported to be missing in other studies of modern, urban societies compared to traditional hunter-gatherer or agricultural societies 11 , 23 . The gut microbiome of the Indigenous infants shared features with gut microbiomes of other pre-industrialised societies, but had a higher abundance of Bifidobacteria , inversely related to age. This is commensurate with the high rate of breastfeeding in the Indigenous infants, provisioning milk oligosaccharides that promote the growth of Bifidobacteria 24 . Prevotella , a marker of non-urban, pre-industrial microbiomes 10 , was prevalent in the older Indigenous infants, but not in the non-Indigenous infants, whereas Phocaeicola ( Bacteroides ), previously noted to be more abundant in urban societies 10 , 11 , characterized non-Indigenous infants across all ages. Differences in observed taxa could not be attributed to recent antibiotic (mainly amoxycillin) usage, which affected only a minority in each population. Our findings show that the gut microbiome of Yolngu Indigenous infants retains key features of traditional gut microbiomes and appears not to have been substantially modified by encroaching Westernization. The infant gut microbiome is shaped initially from birth by vertical transmission of microbiota from the mother’s gut, vagina, skin and milk 25 . Modes of birth and times of introduction of complementary food did not differ between the Indigenous and non-Indigenous infants. Therefore, it seems reasonable to assume that the gut microbiome of these Indigenous infants, aside from the high abundance of Bifidobacteria , reflects primarily that of their mothers, other family members, diet and environment. This is expected to change with age and weaning, but suggests a persisting inter-generational influence of the remote environment, traditional diet and lifestyle in concert with host genetics. Host-microbiota relationships evolve in response to diverse environmental modifiers, or lack thereof, including exposure to humans including family members, animals, plants, air, soil and water, as well as man-made products (e.g., chemicals, antibiotics, food preservatives etc). Although not documented here, these exposures would obviously differ between the Indigenous and non-Indigenous populations. The greater diversity of the gut microbiome in Indigenous infants could well reflect their distinctive exposures, and those of their mothers and other family members, to a more diverse natural environment compared to the built, urban and more ‘hygienic’ environment of the non-Indigenous infants. However, what we observed is a snapshot in what may be an ongoing inter-generational depletion of the traditional microbiome 26 . Two markers of gut pathology were measured in this study. Neutrophil-derived fecal calprotectin was significantly higher in Indigenous infants. While this would be expected to reflect gut inflammation, this may not necessarily be the case. Increased fecal calprotectin has been associated with gut bacteria that promote inflammation 18 , but these were not present in the Indigenous infants. Parasites modify the gut microbiome 27 , but they were detected microscopically in only 30% of Indigenous infants: protozoans (either Giardia intestinalis or Cryptosporidium spp) in 10 and helminths ( Trichiuris trichiuria or Ascaris lumbricoides ) in five (see also ref. 28), and fecal calprotectin was similar in infants with parasites and the group as a whole (median: 1133 vs 1318 mg/g). Next, while fecal calprotectin is a marker of Environmental Enteric Dysfunction (EED), a low-grade inflammatory disorder associated with stunting in children living in poor communities 29 , the Indigenous infants did not display other criteria of EED. Furthermore, iFABP, a marker of intestinal epithelial damage and permeability 21 , 22 , was not increased in Indigenous compared to non-Indigenous infants (Table 1). The possibility remains however that elevated fecal calprotectin could be a very early marker of EED. Fecal calprotectin in infancy may be also elevated for non-pathogenic reasons, a major one being exclusive breast feeding 30 , 31 . This is a plausible explanation for the difference between the Indigenous and non-Indigenous infants, in whom the proportions being exclusively breast fed were 84% and 22%, respectively, closely matching the proportions with raised fecal calprotectin. Follow-up studies as the children age and cease breast feeding may resolve the fecal calprotectin question. A caveat of this study which limits our conclusions is that microbiome data on the mothers was unavailable, as permission could not be obtained to collect samples from them. A further caveat is that while infants were closely matched for age and sex, the non-Indigenous infants had a first-degree relative with type 1 diabetes and were therefore at increased genetic risk for type 1 diabetes. Although none had detectable pancreatic islet autoantibodies, the earliest known marker of sub-clinical disease, we can’t exclude the possibility that their gut microbiome differs from that of children without genetic susceptibility to type 1 diabetes. Nevertheless, we show that the Indigenous infants start life with a distinctive ancestral gut microbiome. This suggests that if Westernization occurs in these infants it will be acquired, and has not been transmitted inter-generationally. Our findings extend knowledge of the infant gut microbiome and are a foundation on which to explore environmental and lifestyle factors that shape development of the gut microbiome and its relationship to future health in Indigenous children. Methods Subjects Fifty Indigenous infants, 24 females and 26 males, aged 22–617 days were recruited in October 2017 in a remote community in north-east Arnhem Land, Northern Territory, Australia, in the Early Life Child Health Observation (ELCHO) study. As described previously 28 , prior to commencing the study and after community engagement, the local research team participated in a week-long codesign and training program which involved telling the research story in the local language, with discussion of the study protocol, means of recruitment, data collection and consent. In this program, the concept of the microbiome was discussed using metaphors and microscopy to develop an understanding of the role of microscopic organisms in human health. Prior to enrolment, parents or guardians gave written informed consent on behalf of infant participants. After explanation and discussion in both English and local language, trained research staff collected maternal socio-demographic, nutritional, environmental, breast feeding and dietary data using a structured questionnaire. The majority of infants were being breast-fed. On up to three days in the week, their mothers consumed traditional foods, viz., seafoods such as turtle, shellfish, fish, oysters and crabs, mangrove worms, game such as kangaroo, bush fruits, plant roots and tuber-like yams. The study protocol was approved by the Human Research Ethics Committee of the Northern Territory Department of Health and Menzies School of Health Research (Ref. 2017–2814), Melbourne Health Human Research Ethics Committee (Ref. 2017.064), Miwatj Health Indigenous Corporation Board and the Local Shire Authority. Fecal samples were obtained within two hours from freshly soiled diapers, transferred to sterile 5mL screw cap containers, immediately frozen at -20°C, and transported on dry ice to the Peter Doherty Institute, Melbourne, where they were stored at − 80°C for 5 months before DNA extraction and metagenomic sequencing were performed at the Walter and Eliza Hall Institute, Melbourne. Indigenous Australian infants in this ELCHO study were matched (Supplementary data, Supplementary Table 1_metadata.xlsx) for sex, and as closely as possible for age, with non-Indigenous infants participating in the Australia-wide Environmental Determinants of Islet Autoimmunity (ENDIA) pregnancy-birth cohort study (Australia New Zealand Clinical Trials Registry ACTRN12613000794707), in which the child has a first-degree relative with type 1 diabetes 32 . Participants selected for this study were limited to urban areas of NSW, Victoria, South Australia, Western Australia and Queensland. Parents or guardians gave written informed consent for their children to participate in ENDIA research, including collaborative studies. Less than 50% of ENDIA infants in this study were being breastfed at the time of collection of stool samples, which were processed similarly to those of the Indigenous infants. Human Research Ethics Committee (HREC) approval was obtained at each clinical site, with the Women’s and Children’s Hospital, Adelaide acting as the lead HREC site under the Australian National Mutual Acceptance Scheme (HREC/16/WCHN/066). Fecal samples were collected similarly to those from the Indigenous children. None of the matched non-Indigenous ENDIA infants had developed autoantibodies to pancreatic islet cells, a marker of sub-clinical T1D, although five subsequently became seropositive after 4 years of age. Whole metagenome sequencing and taxonomic analysis DNA was extracted with the MoBio PowerSoil kit (MoBio Laboratories, Carlsbad, CA) and whole metagenome sequencing (WMS) libraries generated as previously described 33 . Sequencing by 2x150 bp paired-end chemistry was performed on an Illumina NovaSeq 6000 (Illumina, San Diego, California, USA) machine by the Ramaciotti Centre for Genomics (Sydney, Australia). Illumina reads for each sample were filtered by KneadData (v0.7.7 https://github.com/biobakery/kneaddata ) using default settings. Data were then further filtered to remove low entropy reads using a script based on the Shannon information index ( https://github.com/theo-allnutt-bioinformatics/scripts/blob/master/shannons-filter.py ). Where possible, following filtering, read counts were capped at 10 million per sample. Diversity analysis All bioinformatic pipelines, scripts and program settings are available at https://github.com/theo-allnutt-bioinformatics/Indigenous_gut_mircobiome_2023 . The bacterial taxonomic composition of infant gut metagenomic samples was profiled with MetaPhlAn 4.0 34 . MetaPlAn classifications were converted to GTDB species taxonomy ( https://gtdb.ecogenomic.org/ ) and taxa counts normalised to counts per million (cpm). Only taxa with > 100 total counts (prior to normalisation) and containing at least three non-zero samples were retained for analysis. Alpha diversity (diversity within microbial communities) metrics, viz., Richness, Shannon and Simpson indices, were calculated for the taxonomic levels Phylum, Class, Order, Family, Genus and Species using USEARCH v10.0.240 35 . Viruses, fungi and higher eukaryotes were classified and quantified using Kraken2 36 , as previously described 37 . The identity of Kraken2-classified taxa was checked by BLAST (nt database, 28/8/2022). Taxa with a predominant BLAST match other than the Kraken2 classification were excluded. Counts obtained from Kraken2 classifications were not normalised or adjusted. Bacterial differences in alpha diversity between groups defined by the variables 'population', 'sex' and 'age category' were tested using restricted maximum likelihood (REML) in the R package 'lmer'. Age in days was divided into four approximately equally sized categories (age 0, 13–149 days; age 1, 160–285 days; age 2, 306–441 days; and age 3, 458–617 days). Beta diversity (diversity between microbial communities) at the species level was analysed using the R package 'pairwiseAdonis' with Bray-Curtis distances, an implementation of Permanova ( https://github.com/pmartinezarbizu/pairwiseAdonis ). Differential abundance Differential abundance of raw counts between Indigenous ELCHO and non-Indigenous ENDIA infants was tested at each bacterial taxonomic level using ALDEx2 v1.31.0 38 . The Benjamini-Hochberg corrected P value of Welch’s t test was used to determine significance (P < 0.05) and significant results were ranked by the ALDEx2 effect-size metric. Differential abundance of Kraken2 counts was also tested with ALDEx2, but no lower threshold was applied to the number of non-zero count samples and only the species level was tested; a total abundance count threshold of 300 was used for viruses and 100 for fungi and other eukaryotes. It should be noted that, due to its limited coverage, the eukaryotic Kraken2 database classification of species 35 should be regarded as indicative only and not necessarily quantitative. Fecal calprotectin Fecal calprotectin (mg/g) was measured by quantitative, enzyme-linked immunoassay (CALPRO Oslo, Norway), according to the manufacturer’s instructions. Serum intestinal fatty acid binding protein (iFABP) Serum iFABP (pg/ml) was measured by ELISA (Enzyme-Linked Immunosorbent Assay; Hycult Biotech, The Netherlands), according to the manufacturer’s instructions. Fecal parasites Parasites in fecal samples were analysed directly by microscopy, both in the field and following fixation and storage in sodium-acetate formalin, as previously described 28 . Statistics Group differences between calprotectin and iFABP biomarkers were analysed by non-parametric, two-tail Mann-Whitney test, and proportions were compared by Fisher’s Exact test, using GraphPad Prism. Declarations Acknowledgments We acknowledge members of the Early Life Child Health Observation project team: David Djilimara, Elizabeth Bungawara, Lloyd Dhamarandji, Janice Djiliri, Jenny Shield, Norbert Ryan, Gatti, Jannie Kraayenhof, Noella Goveas. We thank the participants, their families and health workers in the community and, for their support Miwatj Health Aboriginal Corporation, the Marthakal Homelands Health Service, Families as First Teachers, and Beth Hilton-Thorpe and Christalla Hajisava. Author contributions LCH TRA SH AJR-S GG VG YD JJC MEC EAD TH GS JMW MASP PV B-AB Concept/Design x x x Methodology x x x x x x x x x x x x x x x x Investigation x x x x x Supervision x x x x x x x x x x x x x Writing the initial draft x x Reading/editing draft x x x x x x x x x x x x x x x x Funding acquisition x x x x x x x x x x x Data curation x x x x x Data analysis x x x Provision of resources x x x x x x x x x x x x x Competing interests The authors declare they have no competing interests. Funding The Indigenous studies were supported by a grant from the Hallmark Indigenous Research Initiative at the University of Melbourne, and a Royal Melbourne Hospital Home Lottery Grant (GIA-060-2018). The ENDIA studies were supported by JDRF Australia, the recipient of the Commonwealth of Australia grant for Accelerated Research under the Medical Research Future Fund (grant keys 3-SRA-2023-1374-M-N, 3-SRA-2020-966-M-N, 1-SRA-2019-871-M-B, 4-SRA-2015-127-M-B), and with funding from The Leona M. and Harry B. Helmsley Charitable Trust. In addition, LCH was the recipient of an Investigator Grant (APP 1173945) from the National Health and Medical Research Council of Australia. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Data Availability The original data presented in this study are included in the article and Supplementary Material. Further inquiries can be directed to the corresponding author. Data on individual living humans cannot be publicly available due to its sensitive nature, as regulated by privacy legislation. References Rasmussen, M. et al. 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Intestinal fatty acid binding protein: A rising therapeutic target in lipid metabolism. Prog. Lipid Res. 87 , 101178 (2022). https://doi.org/10.1016/j.plipres.2022.101178. Logan, M., MacKinder, M., Clark, C. M. et al. Intestinal fatty acid binding protein is a disease biomarker in paediatric coeliac disease and Crohn’s disease. BMC Gastroenterol. 22 , 260 (2022). https://doi.org/10.1186/s12876-022-02334-6. Carter, M. M. et al. Ultra-deep sequencing of Hadza hunter-gatherers recovers vanishing gut microbes. Cell 186 , 3111-3124.e13 (2023). https://doi.org/10.1016/j.cell.2023.05.046. Marcobal, A. et al. Bacteroides in the infant gut consume milk oligosaccharides via mucus-utilization pathways. Cell Host Microbe 10 , 507–514 (2011). Ferretti, P. et al. Mother-to-infant microbial transmission from different body sites shapes the developing infant gut microbiome. Cell Host Microbe 24 , 133–145 (2018). Sonnenburg, E.D., Smits, S.A., Tikhonov, M., Higginbottom, S.K., Wingreen, N.S., Sonnenburg, J.L. Diet-induced extinctions in the gut microbiota compound over generations. Nature 529 , 212-215 (2016). Leung, J. M., Graham, A. L. & Knowles, S. C. L. Parasite-microbiota interactions with the vertebrate gut: Synthesis through an ecological lens. Front. Microbiol. 9 , 843 (2018). https://doi.org/10.3389/fmicb.2018.00843. Hanieh, S. et al. Enteric pathogen infection and consequences for child growth in young Indigenous Australian children: A cross-sectional study. BMC Infect. Dis. 21 , 9 (2021). https://doi.org/10.1186/s12879-020-05685-1. Crane, R. J., Jones, K. D. J. & Berkley, J. A. Environmental enteric dysfunction: An overview. Food Nutr. Bull. 36 , S76-S87 (2015). https://doi.org/10.1177/15648265150361S113. Dorosko, S. M., Mackenzie, T. & Connor, R. I. Fecal calprotectin concentrations are higher in exclusively breastfed infants compared to those who are mixed-fed. Breastfeed Med. 3 , 117–119 (2008). https://doi.org/10.1089/bfm.2007.0036. Savino, F. et al. High fecal calprotectin levels in healthy, exclusively breast-fed infants. Neonatology 97 , 299–304 (2010). Penno, M. A. S. et al. Environmental determinants of islet autoimmunity (ENDIA): A pregnancy to early life cohort study in children at risk of type 1 diabetes. BMC Pediatr. 13 , 124 (2013). https://doi.org/10.1186/1471-2431-13-124. Roth-Schulze, A. J. et al. Type 1 diabetes in pregnancy is associated with distinct changes in the composition and function of the gut microbiome. Microbiome 9 , 167 (2021). https://doi.org/10.1186/s40168-021-01104-y. Blanco-Míguez, A. et al. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat. Biotechnol. 41 , 1633-1644 (2023). https://doi.org/10.1038/s41587-023-01688-w. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26 , 2460–2461 (2010). https://doi.org/10.1093/bioinformatics/btq461. Wood, D. E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol. 20 , 257 (2019). https://doi.org/10.1186/s13059-019-1891-0. Allnutt, T. R., Roth-Schulze, A. J. & Harrison, L. C. Expanding the taxonomic range in the fecal metagenome. BMC Bioinformatics 22 , 312 (2021). https://doi.org/10.1186/s12859-021-04212-6. Fernandes, A. D. et al. ANOVA-like differential expression (ALDEx) analysis for mixed population RNA-Seq. PLoS One 8 , e67019 (2013). https://doi.org/10.1371/journal.pone.0067019. Tables Table 1 and 2 are available in the Supplementary Files section. Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryFigure1Kraken.xlsx Dataset 1 SupplementaryFigure2differentialabundance.xlsx Dataset 2 SupplementaryTable1Metadata.xlsx Dataset 3 SupplementaryTable2Metaphlan.xlsx Dataset 4 SupplementaryTable3Metaphlandiversity.xlsx Dataset 5 NCOMMS2515185Rs.pdf Reporting summary table1and2.docx Cite Share Download PDF Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6101879","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":427680514,"identity":"1e887500-0b68-4566-b808-d26a5e232622","order_by":0,"name":"Leonard 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Gardens","correspondingAuthor":false,"prefix":"","firstName":"Theo","middleName":"","lastName":"Allnutt","suffix":""},{"id":427680516,"identity":"bc47c795-845f-48a4-8462-6b82bb390290","order_by":2,"name":"Sarah Hanieh","email":"","orcid":"","institution":"The Peter Doherty Institute for Infection and Immunity","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Hanieh","suffix":""},{"id":427680517,"identity":"457a0f3f-412d-4c28-8aa0-2f682bd0c298","order_by":3,"name":"Alexandra Roth-Schulze","email":"","orcid":"","institution":"Walter and Eliza Hall Institute of Medical Research","correspondingAuthor":false,"prefix":"","firstName":"Alexandra","middleName":"","lastName":"Roth-Schulze","suffix":""},{"id":427680518,"identity":"94560b8c-54df-4cc3-9416-1f190579c728","order_by":4,"name":"George Gurruwiwi","email":"","orcid":"","institution":"The Peter Doherty Institute for Infection and Immunity","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"","lastName":"Gurruwiwi","suffix":""},{"id":427680519,"identity":"859a744e-07d6-49bc-9348-ed46871f7106","order_by":5,"name":"Veronica Gondarra","email":"","orcid":"","institution":"The Peter Doherty Institute for Infection and Immunity","correspondingAuthor":false,"prefix":"","firstName":"Veronica","middleName":"","lastName":"Gondarra","suffix":""},{"id":427680520,"identity":"888486bb-36a2-43c6-803f-823ba4edf2bf","order_by":6,"name":"Jennifer Couper","email":"","orcid":"","institution":"Robinson Research Institute, University of Adelaide, South Australia, Australia","correspondingAuthor":false,"prefix":"","firstName":"Jennifer","middleName":"","lastName":"Couper","suffix":""},{"id":427680521,"identity":"45e89097-e071-44b9-9af0-12e6be3742bf","order_by":7,"name":"Maria Craig","email":"","orcid":"https://orcid.org/0000-0001-6004-576X","institution":"Children's Hospital at Westmead and University of Sydney, Sydney, New South Wales, Australia","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Craig","suffix":""},{"id":427680522,"identity":"815140fa-0e89-4582-afa5-e0f3f063518f","order_by":8,"name":"Elizabeth Davis","email":"","orcid":"","institution":"Children's Diabetes Centre, Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia","correspondingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"","lastName":"Davis","suffix":""},{"id":427680523,"identity":"a35b140b-c834-46a8-9c01-5aa544818d10","order_by":9,"name":"Tony Huynh","email":"","orcid":"","institution":"Department of Endocrinology and Diabetes, Queensland Children's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tony","middleName":"","lastName":"Huynh","suffix":""},{"id":427680524,"identity":"e63f39cf-a417-4e44-931a-561a0fa77706","order_by":10,"name":"Georgia Soldatos","email":"","orcid":"","institution":"Monash Centre for Health Research and Implementation","correspondingAuthor":false,"prefix":"","firstName":"Georgia","middleName":"","lastName":"Soldatos","suffix":""},{"id":427680525,"identity":"e27a4e96-a5be-4c59-a7f8-b8fec273dd6c","order_by":11,"name":"John Wentworth","email":"","orcid":"https://orcid.org/0000-0002-5197-3529","institution":"Department of Diabetes and Endocrinology, Royal Melbourne Hospital","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Wentworth","suffix":""},{"id":427680526,"identity":"840eb685-e40f-4b8c-9cfb-245c2374f164","order_by":12,"name":"Megan Penno","email":"","orcid":"https://orcid.org/0000-0002-9617-0826","institution":"University of Adelaide","correspondingAuthor":false,"prefix":"","firstName":"Megan","middleName":"","lastName":"Penno","suffix":""},{"id":427680527,"identity":"f7a52afa-abfc-4ff9-857c-73a3fcf29f1e","order_by":13,"name":"Peter Vuillermin","email":"","orcid":"https://orcid.org/0000-0002-6580-0346","institution":"Deakin University","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Vuillermin","suffix":""},{"id":427680528,"identity":"1e5db3e9-cdcd-4fae-83db-5df228db852a","order_by":14,"name":"Beverley-Ann Biggs","email":"","orcid":"","institution":"Peter Doherty Institute of Infection and Immunity","correspondingAuthor":false,"prefix":"","firstName":"Beverley-Ann","middleName":"","lastName":"Biggs","suffix":""}],"badges":[],"createdAt":"2025-02-25 06:15:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6101879/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6101879/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-65758-0","type":"published","date":"2025-12-03T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":78426138,"identity":"8762ecc5-01fa-405c-9daa-6f4570768fc1","added_by":"auto","created_at":"2025-03-13 06:24:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":123431,"visible":true,"origin":"","legend":"\u003cp\u003eBar charts of observed taxa (bacteria) proportions (25 most abundant) by MetaPhlAn.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea \u003c/strong\u003eELCHO (Indigenous) infants. \u003cstrong\u003eb \u003c/strong\u003eENDIA (Non-indigenous) infants. For each population, samples were ranked left to right by increasing age. Relative proportions of taxa are ranked highest from bottom to top.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/c169ff3042b695d4f4b576f1.png"},{"id":78426429,"identity":"12681ec5-0188-4130-872c-6c6fb2b21433","added_by":"auto","created_at":"2025-03-13 06:32:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":159518,"visible":true,"origin":"","legend":"\u003cp\u003eBar charts of observed taxa (viruses) proportions (25 most abundant) by Kraken2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea \u003c/strong\u003eELCHO (Indigenous) infants. \u003cstrong\u003eb \u003c/strong\u003eENDIA (Non-indigenous) infants. For each population, samples were ranked left to right by increasing age. Relative proportions of taxa are ranked highest from bottom to top.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/13a84750f845262d0851c170.png"},{"id":78427370,"identity":"d52f0470-7fa7-4317-a6be-6ed864724982","added_by":"auto","created_at":"2025-03-13 06:40:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":160695,"visible":true,"origin":"","legend":"\u003cp\u003eBar charts of observed taxa (fungi) proportions (25 most abundant) by Kraken2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea \u003c/strong\u003eELCHO (Indigenous) infants. \u003cstrong\u003eb \u003c/strong\u003eENDIA (Non-indigenous) infants. For each population, samples were ranked left to right by increasing age. Relative proportions of taxa are ranked highest from bottom to top.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/3fd357b14a905ca9a16d0c36.png"},{"id":78426430,"identity":"004ff934-2a80-4349-8f0c-f7111dc37305","added_by":"auto","created_at":"2025-03-13 06:32:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":78454,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of non-fungal eukaryote counts classified by Kraken2. Red = high abundance, green = low/zero abundance.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/4fe966e228c5abd800a18bb6.png"},{"id":78426145,"identity":"ae78be24-c120-4630-8160-eaf91a1736d1","added_by":"auto","created_at":"2025-03-13 06:24:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":57937,"visible":true,"origin":"","legend":"\u003cp\u003eDotplots of alpha diversity (Shannon index) by\u003cstrong\u003e a\u003c/strong\u003ePopulation (family), \u003cstrong\u003eb\u003c/strong\u003e Sex (genus) and \u003cstrong\u003ec \u003c/strong\u003eAge (species). Indigenous= red dots; non-Indigenous= blue dots.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/b67d41143a07786880b24d73.png"},{"id":78426433,"identity":"55c3b7cf-c429-47f8-8990-842f8561fbe3","added_by":"auto","created_at":"2025-03-13 06:32:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":72108,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal coordinate plots of beta diversity. In the same plot, points are coloured by \u003cstrong\u003ea\u003c/strong\u003e. Population; \u003cstrong\u003eb\u003c/strong\u003e Sex; \u003cstrong\u003ec \u003c/strong\u003eAge. PCO1 (x axis) = 13.3% and PCO2 (y axis) = 6.7% of total variation.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/39d18fb583d7de90ed5f248a.png"},{"id":78426151,"identity":"239cde75-22be-4b85-b663-e3265b3b5f02","added_by":"auto","created_at":"2025-03-13 06:24:25","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":311236,"visible":true,"origin":"","legend":"\u003cp\u003eSignificant differentially abundant taxa between ELCHO and ENDIA infants (ALDEx2 BH\u0026lt;0.05) (BH=expected Benjamini Hochberg-corrected P value of Welch’s t test). ALDEx2 was performed using clr normalisation, although the figures depict raw counts. For each taxon, highest to lowest abundance is indicated by red to green gradient.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/9c23e898c705215e04f79f48.png"},{"id":97418583,"identity":"e5999b63-ee1d-4777-abbc-d2be534d0842","added_by":"auto","created_at":"2025-12-04 08:05:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1743230,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/18c97d95-fc51-4bf7-a000-31433a34ada5.pdf"},{"id":78427369,"identity":"4c065a79-7e92-426b-97e3-1f768c63a1dd","added_by":"auto","created_at":"2025-03-13 06:40:25","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":604630,"visible":true,"origin":"","legend":"Dataset 1","description":"","filename":"SupplementaryFigure1Kraken.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/c8e15020e5841abb7228dd9e.xlsx"},{"id":78426143,"identity":"356ee2e3-51e2-447c-b31d-ffdc8cad3a81","added_by":"auto","created_at":"2025-03-13 06:24:25","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1189445,"visible":true,"origin":"","legend":"Dataset 2","description":"","filename":"SupplementaryFigure2differentialabundance.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/dd720c746c2b7a9255e33e20.xlsx"},{"id":78426147,"identity":"93ba08fd-9397-4e4c-999f-0c2ac5b55764","added_by":"auto","created_at":"2025-03-13 06:24:25","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13509,"visible":true,"origin":"","legend":"Dataset 3","description":"","filename":"SupplementaryTable1Metadata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/981edc48bc329b909ea7c21f.xlsx"},{"id":78426440,"identity":"067f798b-ca2b-4944-9edc-1e58712e710f","added_by":"auto","created_at":"2025-03-13 06:32:25","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3303419,"visible":true,"origin":"","legend":"\u003cp\u003eDataset 4\u003c/p\u003e","description":"","filename":"SupplementaryTable2Metaphlan.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/4e5311a62f7c46e66ca64fd0.xlsx"},{"id":78426157,"identity":"24526715-102a-4378-9ecd-3340fc020b9d","added_by":"auto","created_at":"2025-03-13 06:24:25","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":3410569,"visible":true,"origin":"","legend":"\u003cp\u003eDataset 5\u003c/p\u003e","description":"","filename":"SupplementaryTable3Metaphlandiversity.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/d566a32388c042362b693966.xlsx"},{"id":78426149,"identity":"290c3e86-0382-43c4-a123-21641a9e2431","added_by":"auto","created_at":"2025-03-13 06:24:25","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":2044988,"visible":true,"origin":"","legend":"Reporting summary","description":"","filename":"NCOMMS2515185Rs.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/af2e7c73833d9ba15567e5f1.pdf"},{"id":78426434,"identity":"676cfb06-0b57-4984-a1c3-0527e27209e3","added_by":"auto","created_at":"2025-03-13 06:32:25","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":459837,"visible":true,"origin":"","legend":"","description":"","filename":"table1and2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6101879/v1/e3ea3a1764ba205d70ea6e6e.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"\u003cp\u003eIndigenous infants in remote Australia retain an ancestral gut microbiome despite encroaching Westernization\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIndigenous Australians are distinguished as the oldest, continuous living culture, successful as hunter-gatherers and subsistence farmers for over 60,000 years, prior to European settlement\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Along with the degradation of their traditional culture, Indigenous Australians have experienced a marked increase in cardiometabolic, non-communicable diseases (NCDs), including obesity, diabetes, hypertension, cardiovascular diseases, chronic kidney disease and cancers\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. NCDs are associated with chronic low-grade, systemic inflammation\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and a shift to a less diverse gut microbiome (dysbiosis)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. These pathophysiological features are considered to be a maladaptive response to a \u0026lsquo;Western\u0026rsquo; lifestyle, especially the\u0026lsquo;Western\u0026rsquo; diet which is high in saturated fat, simple carbohydrates, additives and processed components, and low in fiber\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, in addition to other less understood influences such as the cumulative burden of spiritual, cultural and environmental stressors\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFollowing colonisation at birth, the gut harbors the largest and most diverse microbiome, critical for the development and ongoing health of the gut, immune and other body systems. Distinct taxonomic and functional differences have been identified between the gut microbiomes of traditional hunter-gatherer or subsistence societies compared to modern Western societies\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, which provide insights into the evolution of the gut microbiome under the influence of ethnicity, environment and lifestyle. The gut microbiome of Western compared to traditional societies is less diverse, with a lower abundance of fiber-degrading bacteria that produce anti-inflammatory short chain fatty acids and a higher abundance of mucus-degrading bacteria, leading to impaired integrity of the gut epithelium with leakiness of bacterial products and systemic inflammation\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The Western gut microbiome contains a higher abundance of Bacteroides, Enterobacteria and Akkermansia, and a lower abundance of beneficial Bifidobacteria and Lactobacilli, whereas Prevotella, Treponema, Proteobacteria, Clostridiales and Ruminobacter predominate in the traditional gut microbiome, some of which have disappeared from the Western gut microbiome\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCounted among the hundreds of clans of Indigenous Australians are the Yolngu people, living in a remote area of northern Australia, whose traditional customs endure despite an increasingly pervasive Western lifestyle. Their diet comprises mainly Western style food and beverages with a variable mix of traditional foods (see Methods). The children are increasingly exposed to sugar-sweetened beverages and ultra-processed and takeaway foods, and experience periods of food scarcity\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Indigenous Australians appear to have a genetic propensity for strong inflammatory responses\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Indeed the Yolngu children display elevated concentrations of circulating inflammatory cytokines (Hasthi Dissanayake, personal communication), consistent with gut microbiome dysbiosis and a predisposition to NCDs. Analysis of the oral\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and upper respiratory\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e microbiomes of Indigenous Australian children by 16S rRNA gene amplicon sequencing has revealed the carriage of unique bacteria potentially associated with an increased prevalence of NCDs, but knowledge of the gut microbiome in young Indigenous children is lacking. Whether the gut microbiome of these Indigenous infants is ancestral and to what extent and at what age it might exhibit features of Westernization is unknown. The infant\u0026rsquo;s gut microbiome is shaped initially by vertical transmission from the mother, but also by genetic background and environmental exposures such as living conditions, psychological stress, diet, water, soil, animals, toxins, parasitic infections and antibiotics, which vary between populations and may distinguish Indigenous children living remotely from children living in urban settings. In order to expand knowledge of the remote, Indigenous gut microbiome in early childhood, and as a basis on which to understand the impact of the Western lifestyle, we used shotgun metagenomic sequencing to compare the gut microbiomes of 50 randomly-selected Indigenous Australian infants living in a remote Yolngu community to those of 50 age- and sex-matched non-Indigenous infants living in different urban areas of Australia.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study groups comprised 24 Indigenous and 24 non-Indigenous females, median (IQR) ages 294 (153, 428) and 293 (114, 433) days, respectively, and 26 Indigenous and 26 non-Indigenous males, median (IQR) ages 360 (222, 476) and 377 (226, 467) days, respectively. Their characteristics are summarised in Table 1. The groups did not differ by gestational age at delivery, mode of delivery or birth weight, but the frequencies of current and exclusive beastfeeding were each markedly higher in the Indigenous infants (P\u0026lt;0.0001; Fisher\u0026rsquo;s Exact test). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTaxonomic profiles\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMetaPhlAn4 classified 1679 bacterial species (Indigenous=1581; non-Indigenous=1310) in the 100 samples, with counts \u0026gt; 100, present in three or more samples. Kraken2 classified 371 virus (Indigenous=367; non-Indigenous=353), 31 fungus (Indigenous=31; non-Indigenous=31), and 15 other eukaryote species following their taxonomic confirmation with BLAST (Indigenous=12; non-Indigenous=10). \u0026nbsp;Complete bacterial abundance data are provided in Supplementary data (Supplementary Table 2_Metaphlan.xlsx); all Kraken2 virus and eukaryote abundance data are available in Supplementary data (Supplementary Figure 1_Kraken.xlsx). Bacterial taxa proportions at the genus level (Fig. 1) revealed a high prevalence of \u003cem\u003eBifidobacteria\u0026nbsp;\u003c/em\u003ein Indigenous infants, especially at younger ages, and of Prevotella, especially at older ages, in contrast to non-Indigenous infants who had a high prevalence of \u003cem\u003ePhocaeicola\u0026nbsp;\u003c/em\u003e(\u003cem\u003eBacteroides\u003c/em\u003e) across all ages.\u003c/p\u003e\n\u003cp\u003eViruses (Fig. 2) were significantly more abundant in Indigenous than non-Indigenous infants (17.2 vs. 2.9 million counts, respectively), and were different; furthermore, their abundance profile was more consistent in Indigenous infants, possibly due to their geographic homogeneity. In Indigenous infants, the dominant viruses were Enterobacteria (\u003cem\u003eEscherichia\u003c/em\u003e) phages (as classified by the International Committee on Taxonomy of Viruses, https://ictv.global/), viz., Quadragintavirus ev129, Tequatrovirus, Evevirus ev239 and Jouyvirus ev017. These viruses were virtually non-existent in non-Indigenous infants. The most common viruses in non-Indigenous infants were the CrAssphages: Carjivirus communis, Carjivirus hominis and Kingevirus communis, which infect \u003cem\u003eBacteroides\u003c/em\u003e\u003csup\u003e17\u003c/sup\u003e.\u0026nbsp;The potential pathogen, human mastadenovirus, appeared in the top 25 viruses in both Indigenous and non-Indigenous infants, in the former being strain F and in the latter being strains C and D. Its occurrence was sporadic in both populations, being present in only a few infants but at high counts. The only other potentially pathogenic virus in Indigenous infants was Primate bocaparvovirus 2 (human bocavirus 2c), known to cause respiratory tract infections.\u003c/p\u003e\n\u003cp\u003eFungi (Fig. 3) were also significantly more abundant in Indigenous than non-Indigenous infants (mean counts/sample 7,799 vs 115\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003erespectively). \u003cem\u003eCandida albicans\u003c/em\u003e (226,104 counts) was by far the most abundant in Indigenous infants, especially at a younger age, and \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e (1,122 counts) the most abundant in non-Indigenous infants, although this was predominantly due to a single individual (888 counts). After \u003cem\u003eS. cerevisiae, Aspergillus luchuensis\u0026nbsp;\u003c/em\u003ewas most abundant in non-Indigenous infants (248 counts), with counts spread more evenly over several samples.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to the limited number of non-fungal eukaryotic genomes classified in the Kraken2 database, species level classification was not reliable without the BLAST check step. The abundances of the 15 identified and BLAST-confirmed non-fungal eukaryote taxa are shown as a heatmap (Fig. 4). Total counts of these classified eukaryotes were higher in Indigenous than non-Indigenous infants (22,190 and 10,674, respectively). Several animal food taxa were present in both Indigenous and non-Indigenous infants, viz, \u003cem\u003eBos taurus\u0026nbsp;\u003c/em\u003e(beef), \u003cem\u003eSus scrofa\u003c/em\u003e (pork). \u003cem\u003eGallus gallus\u0026nbsp;\u003c/em\u003e(chicken), as well as plant foods, e.g., \u003cem\u003eZea mays\u003c/em\u003e (maize), \u003cem\u003eMusa acuminata\u003c/em\u003e (banana) and vitis vinifera (grape). The mollusc, \u003cem\u003eMizuhopecten yessoensis\u003c/em\u003e (scallop) and \u003cem\u003eCitrus sinensis\u003c/em\u003e (sweet orange) were present only in Indigenous infants, and \u003cem\u003eSpinacia oleracea\u003c/em\u003e (spinach) and \u003cem\u003eFragoria vesca\u003c/em\u003e (strawberry) only in non-Indigenous infants. For non-food eukaryotes, the house dust mite, \u003cem\u003eDermatophagoides pteronyssinus,\u0026nbsp;\u003c/em\u003eand two parasites, \u003cem\u003eCryptosporidium parvum\u003c/em\u003e, and \u003cem\u003eBlastocystis hominis\u003c/em\u003e were present only in several Indigenous infants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBacterial alpha diversity\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAlpha diversity results are presented in Supplementary\u0026nbsp;\u003c/p\u003e\n\u003cp\u003edata (Supplementary Table 3_Metaphlan_diversity).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eRichness, Shannon and Simpson alpha diversity indices in population, sex and age categories for each taxonomic level are shown in Table 2. Significant Shannon indices (P \u0026lt; 0.05) for the two groups by population (family), sex (genus) and age category (species) are plotted in Fig. 5. Indigenous infants had significantly greater alpha diversity, observed at the family level and above (Shannon [family] P = 0.012). Females had significantly higher diversity than males at all levels above species (Shannon [genus] P = 0.030). As expected, alpha diversity increased with age at the species level in both populations (Shannon P = 0.042). All other comparisons can be viewed in the Supplementary data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBacterial beta diversity\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBeta diversity was significantly different between populations (adjusted P-value = 0.001) and between sexes (adjusted P-value = 0.001) (Fig. 6). The age category was significant over all pair-wise comparisons (P = 0.04); within-pair comparisons, only the youngest vs oldest age categories (0 vs 3 and 1 vs 3) were significant (P = 0.001 and P = 0.009, respectively). These differences are not expected to impact differential abundance analysis between populations, because samples were matched for sex and age.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDifferential abundance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDifferential abundance (DA) results are presented in 2data (Supplementary Figure 2_differential abundance.xlsx). DA was significant for 114 species, 38 genera, 12 families, 8 orders, 3 classes and 2 phyla. \u0026nbsp;The 25 most differentially abundant taxa prevalent in both populations (most positive or negative ALDEx2 effect) are shown (Fig. 7). Species virtually exclusive to Indigenous infants were \u003cem\u003eMegaspaera\u003c/em\u003e spp., \u003cem\u003eStreptococcus lactarius,\u003c/em\u003e \u003cem\u003eCaecibacter\u003c/em\u003e spp., \u003cem\u003eParolsenella\u003c/em\u003e spp. and \u003cem\u003ePrevotella\u003c/em\u003e spp; those almost exclusive to non-Indigenous infants were \u003cem\u003eMuricomes oroticus\u003c/em\u003e and \u003cem\u003eFecalibacillus\u003c/em\u003e ssp. \u003cem\u003eBifidobacteria\u003c/em\u003e ssp. were dominant in Indigenous infants and \u003cem\u003eIntestinibacter bartlettii, Clostridium\u003c/em\u003e \u003cem\u003eAQ innocuum\u003c/em\u003e and \u003cem\u003eRuminococcus\u003c/em\u003e ssp. were dominant in non-Indigenous infants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the genus level, \u003cem\u003eMegasphera\u003c/em\u003e, \u003cem\u003eCaecibacter\u003c/em\u003e, \u003cem\u003eParolsenella\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eAllisonella\u003c/em\u003e, \u003cem\u003eDialister\u003c/em\u003e, \u003cem\u003eThermophilibacter\u003c/em\u003e, \u003cem\u003eParatractidigestivibacter\u003c/em\u003e, \u003cem\u003eAcidominococcus\u003c/em\u003e, \u003cem\u003eUBA7748\u003c/em\u003e, \u003cem\u003eOlsenella\u003c/em\u003e and \u003cem\u003eCoriobacterium\u003c/em\u003e were virtually unique to Indigenous infants, whereas \u003cem\u003eIntestinibacter,\u003c/em\u003e \u003cem\u003eSellimonas\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003eMuricomes\u003c/em\u003e, \u003cem\u003eClostridium\u003c/em\u003e, \u003cem\u003eVentrimonas\u003c/em\u003e, \u003cem\u003eUBA9414\u003c/em\u003e, \u003cem\u003eHespelia\u003c/em\u003e and \u003cem\u003eErysipelatoclostridium\u003c/em\u003e were the dominant genera in non-Indigenous infants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMarkers of gut pathology\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDerived from neutrophils, calprotectin in feces is used as a marker of gut inflammation\u003csup\u003e18\u003c/sup\u003e. The concentration of fecal calprotectin is higher in very young children\u003csup\u003e19,20\u003c/sup\u003e, but the reference range is not well defined. In young Finnish children, the upper limit is regarded as 100 mg/g\u003csup\u003e19\u003c/sup\u003e. At this value, fecal calprotectin was increased in 46/50 (92%) Indigenous infants and 12/50 (24%) non-Indigenous infants (median [IQR]: 1318 [515, 1,809] vs 39.9 [4.40,102], respectively; P=0.0001) (Table 1). Males (1,287 mg/g) and females (1,123 mg/g) did not differ.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSerum iFABP is a marker of gut epithelial integrity\u003csup\u003e21\u003c/sup\u003e. A reference range is not available for young children. Therefore, based on the median value of a control group in a study of childhood inflammatory bowel disease\u003csup\u003e22\u003c/sup\u003e, we used the 1.5 x IQR outlier rule to define the upper limit as 1,664 pg/ml. Serum iFABP was increased in 6 (12%) of Indigenous infants and 7 (14%) of non-Indigenous infants (median [IQR]: 637 (419-1091) vs 689 (517-1572), respectively; P=0.126) (Table 1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMetagenomic sequencing revealed major differences in the gut microbiomes between closely age- and sex-matched Australian Indigenous infants living remotely compared to Australian non-Indigenous infants living in urban environments. This is the first such comparative study of the gut microbiome in infants of which we are aware. The gut microbiome of the Indigenous infants contained significantly greater numbers of bacteria, viruses and fungi, and displayed greater bacterial diversity, 114 bacterial species being differentially abundant. Some taxa present in Indigenous infants, e.g., species from the families \u003cem\u003ePrevotellaceae\u003c/em\u003e, \u003cem\u003eSpirochaetaceae\u003c/em\u003e and \u003cem\u003eSuccinivibrionaceae\u003c/em\u003e, were absent in non-Indigenous infants. This is reminiscent of the \u0026lsquo;VANISH\u0026rsquo; (volatile and/or associated negatively with industrialized societies of humans) bacterial species, reported to be missing in other studies of modern, urban societies compared to traditional hunter-gatherer or agricultural societies\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The gut microbiome of the Indigenous infants shared features with gut microbiomes of other pre-industrialised societies, but had a higher abundance of \u003cem\u003eBifidobacteria\u003c/em\u003e, inversely related to age. This is commensurate with the high rate of breastfeeding in the Indigenous infants, provisioning milk oligosaccharides that promote the growth of \u003cem\u003eBifidobacteria\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003ePrevotella\u003c/em\u003e, a marker of non-urban, pre-industrial microbiomes\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, was prevalent in the older Indigenous infants, but not in the non-Indigenous infants, whereas \u003cem\u003ePhocaeicola\u003c/em\u003e (\u003cem\u003eBacteroides\u003c/em\u003e), previously noted to be more abundant in urban societies\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, characterized non-Indigenous infants across all ages. Differences in observed taxa could not be attributed to recent antibiotic (mainly amoxycillin) usage, which affected only a minority in each population.\u003c/p\u003e \u003cp\u003eOur findings show that the gut microbiome of Yolngu Indigenous infants retains key features of traditional gut microbiomes and appears not to have been substantially modified by encroaching Westernization. The infant gut microbiome is shaped initially from birth by vertical transmission of microbiota from the mother\u0026rsquo;s gut, vagina, skin and milk\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Modes of birth and times of introduction of complementary food did not differ between the Indigenous and non-Indigenous infants. Therefore, it seems reasonable to assume that the gut microbiome of these Indigenous infants, aside from the high abundance of \u003cem\u003eBifidobacteria\u003c/em\u003e, reflects primarily that of their mothers, other family members, diet and environment. This is expected to change with age and weaning, but suggests a persisting inter-generational influence of the remote environment, traditional diet and lifestyle in concert with host genetics. Host-microbiota relationships evolve in response to diverse environmental modifiers, or lack thereof, including exposure to humans including family members, animals, plants, air, soil and water, as well as man-made products (e.g., chemicals, antibiotics, food preservatives etc). Although not documented here, these exposures would obviously differ between the Indigenous and non-Indigenous populations. The greater diversity of the gut microbiome in Indigenous infants could well reflect their distinctive exposures, and those of their mothers and other family members, to a more diverse natural environment compared to the built, urban and more \u0026lsquo;hygienic\u0026rsquo; environment of the non-Indigenous infants. However, what we observed is a snapshot in what may be an ongoing inter-generational depletion of the traditional microbiome\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTwo markers of gut pathology were measured in this study. Neutrophil-derived fecal calprotectin was significantly higher in Indigenous infants. While this would be expected to reflect gut inflammation, this may not necessarily be the case. Increased fecal calprotectin has been associated with gut bacteria that promote inflammation\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, but these were not present in the Indigenous infants. Parasites modify the gut microbiome\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, but they were detected microscopically in only 30% of Indigenous infants: protozoans (either \u003cem\u003eGiardia intestinalis\u003c/em\u003e or \u003cem\u003eCryptosporidium\u003c/em\u003e spp) in 10 and helminths (\u003cem\u003eTrichiuris trichiuria\u003c/em\u003e or \u003cem\u003eAscaris lumbricoides\u003c/em\u003e) in five (see also ref. 28), and fecal calprotectin was similar in infants with parasites and the group as a whole (median: 1133 vs 1318 mg/g). Next, while fecal calprotectin is a marker of Environmental Enteric Dysfunction (EED), a low-grade inflammatory disorder associated with stunting in children living in poor communities\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, the Indigenous infants did not display other criteria of EED. Furthermore, iFABP, a marker of intestinal epithelial damage and permeability\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, was not increased in Indigenous compared to non-Indigenous infants (Table\u0026nbsp;1). The possibility remains however that elevated fecal calprotectin could be a very early marker of EED. Fecal calprotectin in infancy may be also elevated for non-pathogenic reasons, a major one being exclusive breast feeding\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. This is a plausible explanation for the difference between the Indigenous and non-Indigenous infants, in whom the proportions being exclusively breast fed were 84% and 22%, respectively, closely matching the proportions with raised fecal calprotectin. Follow-up studies as the children age and cease breast feeding may resolve the fecal calprotectin question.\u003c/p\u003e \u003cp\u003eA caveat of this study which limits our conclusions is that microbiome data on the mothers was unavailable, as permission could not be obtained to collect samples from them. A further caveat is that while infants were closely matched for age and sex, the non-Indigenous infants had a first-degree relative with type 1 diabetes and were therefore at increased genetic risk for type 1 diabetes. Although none had detectable pancreatic islet autoantibodies, the earliest known marker of sub-clinical disease, we can\u0026rsquo;t exclude the possibility that their gut microbiome differs from that of children without genetic susceptibility to type 1 diabetes. Nevertheless, we show that the Indigenous infants start life with a distinctive ancestral gut microbiome. This suggests that if Westernization occurs in these infants it will be acquired, and has not been transmitted inter-generationally. Our findings extend knowledge of the infant gut microbiome and are a foundation on which to explore environmental and lifestyle factors that shape development of the gut microbiome and its relationship to future health in Indigenous children.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eFifty Indigenous infants, 24 females and 26 males, aged 22\u0026ndash;617 days were recruited in October 2017 in a remote community in north-east Arnhem Land, Northern Territory, Australia, in the Early Life Child Health Observation (ELCHO) study. As described previously\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, prior to commencing the study and after community engagement, the local research team participated in a week-long codesign and training program which involved telling the research story in the local language, with discussion of the study protocol, means of recruitment, data collection and consent. In this program, the concept of the microbiome was discussed using metaphors and microscopy to develop an understanding of the role of microscopic organisms in human health. Prior to enrolment, parents or guardians gave written informed consent on behalf of infant participants. After explanation and discussion in both English and local language, trained research staff collected maternal socio-demographic, nutritional, environmental, breast feeding and dietary data using a structured questionnaire. The majority of infants were being breast-fed. On up to three days in the week, their mothers consumed traditional foods, viz., seafoods such as turtle, shellfish, fish, oysters and crabs, mangrove worms, game such as kangaroo, bush fruits, plant roots and tuber-like yams. The study protocol was approved by the Human Research Ethics Committee of the Northern Territory Department of Health and Menzies School of Health Research (Ref. 2017\u0026ndash;2814), Melbourne Health Human Research Ethics Committee (Ref. 2017.064), Miwatj Health Indigenous Corporation Board and the Local Shire Authority.\u003c/p\u003e \u003cp\u003eFecal samples were obtained within two hours from freshly soiled diapers, transferred to sterile 5mL screw cap containers, immediately frozen at -20\u0026deg;C, and transported on dry ice to the Peter Doherty Institute, Melbourne, where they were stored at \u0026minus;\u0026thinsp;80\u0026deg;C for 5 months before DNA extraction and metagenomic sequencing were performed at the Walter and Eliza Hall Institute, Melbourne.\u003c/p\u003e \u003cp\u003eIndigenous Australian infants in this ELCHO study were matched (Supplementary data, Supplementary Table\u0026nbsp;1_metadata.xlsx) for sex, and as closely as possible for age, with non-Indigenous infants participating in the Australia-wide Environmental Determinants of Islet Autoimmunity (ENDIA) pregnancy-birth cohort study (Australia New Zealand Clinical Trials Registry ACTRN12613000794707), in which the child has a first-degree relative with type 1 diabetes\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Participants selected for this study were limited to urban areas of NSW, Victoria, South Australia, Western Australia and Queensland. Parents or guardians gave written informed consent for their children to participate in ENDIA research, including collaborative studies. Less than 50% of ENDIA infants in this study were being breastfed at the time of collection of stool samples, which were processed similarly to those of the Indigenous infants. Human Research Ethics Committee (HREC) approval was obtained at each clinical site, with the Women\u0026rsquo;s and Children\u0026rsquo;s Hospital, Adelaide acting as the lead HREC site under the Australian National Mutual Acceptance Scheme (HREC/16/WCHN/066). Fecal samples were collected similarly to those from the Indigenous children. None of the matched non-Indigenous ENDIA infants had developed autoantibodies to pancreatic islet cells, a marker of sub-clinical T1D, although five subsequently became seropositive after 4 years of age.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWhole metagenome sequencing and taxonomic analysis\u003c/h2\u003e \u003cp\u003eDNA was extracted with the MoBio PowerSoil kit (MoBio Laboratories, Carlsbad, CA) and whole metagenome sequencing (WMS) libraries generated as previously described\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Sequencing by 2x150 bp paired-end chemistry was performed on an Illumina NovaSeq 6000 (Illumina, San Diego, California, USA) machine by the Ramaciotti Centre for Genomics (Sydney, Australia).\u003c/p\u003e \u003cp\u003eIllumina reads for each sample were filtered by KneadData (v0.7.7 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/biobakery/kneaddata\u003c/span\u003e\u003cspan address=\"https://github.com/biobakery/kneaddata\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using default settings. Data were then further filtered to remove low entropy reads using a script based on the Shannon information index (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/theo-allnutt-bioinformatics/scripts/blob/master/shannons-filter.py\u003c/span\u003e\u003cspan address=\"https://github.com/theo-allnutt-bioinformatics/scripts/blob/master/shannons-filter.py\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Where possible, following filtering, read counts were capped at 10\u0026nbsp;million per sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDiversity analysis\u003c/h2\u003e \u003cp\u003eAll bioinformatic pipelines, scripts and program settings are available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/theo-allnutt-bioinformatics/Indigenous_gut_mircobiome_2023\u003c/span\u003e\u003cspan address=\"https://github.com/theo-allnutt-bioinformatics/Indigenous_gut_mircobiome_2023\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The bacterial taxonomic composition of infant gut metagenomic samples was profiled with MetaPhlAn 4.0\u003csup\u003e34\u003c/sup\u003e. MetaPlAn classifications were converted to GTDB species taxonomy (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gtdb.ecogenomic.org/\u003c/span\u003e\u003cspan address=\"https://gtdb.ecogenomic.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and taxa counts normalised to counts per million (cpm). Only taxa with \u0026gt;\u0026thinsp;100 total counts (prior to normalisation) and containing at least three non-zero samples were retained for analysis. Alpha diversity (diversity within microbial communities) metrics, viz., Richness, Shannon and Simpson indices, were calculated for the taxonomic levels Phylum, Class, Order, Family, Genus and Species using USEARCH v10.0.240\u003csup\u003e35\u003c/sup\u003e. Viruses, fungi and higher eukaryotes were classified and quantified using Kraken2\u003csup\u003e36\u003c/sup\u003e, as previously described\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The identity of Kraken2-classified taxa was checked by BLAST (nt database, 28/8/2022). Taxa with a predominant BLAST match other than the Kraken2 classification were excluded. Counts obtained from Kraken2 classifications were not normalised or adjusted.\u003c/p\u003e \u003cp\u003eBacterial differences in alpha diversity between groups defined by the variables 'population', 'sex' and 'age category' were tested using restricted maximum likelihood (REML) in the R package 'lmer'. Age in days was divided into four approximately equally sized categories (age 0, 13\u0026ndash;149 days; age 1, 160\u0026ndash;285 days; age 2, 306\u0026ndash;441 days; and age 3, 458\u0026ndash;617 days). Beta diversity (diversity between microbial communities) at the species level was analysed using the R package 'pairwiseAdonis' with Bray-Curtis distances, an implementation of Permanova (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/pmartinezarbizu/pairwiseAdonis\u003c/span\u003e\u003cspan address=\"https://github.com/pmartinezarbizu/pairwiseAdonis\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDifferential abundance\u003c/h2\u003e \u003cp\u003eDifferential abundance of raw counts between Indigenous ELCHO and non-Indigenous ENDIA infants was tested at each bacterial taxonomic level using ALDEx2 v1.31.0\u003csup\u003e38\u003c/sup\u003e. The Benjamini-Hochberg corrected P value of Welch\u0026rsquo;s t test was used to determine significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and significant results were ranked by the ALDEx2 effect-size metric. Differential abundance of Kraken2 counts was also tested with ALDEx2, but no lower threshold was applied to the number of non-zero count samples and only the species level was tested; a total abundance count threshold of 300 was used for viruses and 100 for fungi and other eukaryotes. It should be noted that, due to its limited coverage, the eukaryotic Kraken2 database classification of species\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e should be regarded as indicative only and not necessarily quantitative.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFecal calprotectin\u003c/h2\u003e \u003cp\u003eFecal calprotectin (mg/g) was measured by quantitative, enzyme-linked immunoassay (CALPRO Oslo, Norway), according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSerum intestinal fatty acid binding protein (iFABP)\u003c/h2\u003e \u003cp\u003eSerum iFABP (pg/ml) was measured by ELISA (Enzyme-Linked Immunosorbent Assay; Hycult Biotech, The Netherlands), according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFecal parasites\u003c/h2\u003e \u003cp\u003eParasites in fecal samples were analysed directly by microscopy, both in the field and following fixation and storage in sodium-acetate formalin, as previously described\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eGroup differences between calprotectin and iFABP biomarkers were analysed by non-parametric, two-tail Mann-Whitney test, and proportions were compared by Fisher\u0026rsquo;s Exact test, using GraphPad Prism.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003emembers of the Early Life Child Health Observation project team: David Djilimara, Elizabeth Bungawara, Lloyd Dhamarandji, Janice Djiliri, Jenny Shield, Norbert Ryan, Gatti, Jannie Kraayenhof, Noella Goveas. We thank the participants, their families and health workers in the community and, for their support Miwatj Health Aboriginal Corporation, the Marthakal Homelands Health Service, Families as First Teachers, and Beth Hilton-Thorpe and Christalla Hajisava.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"776\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003eLCH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003eTRA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003eSH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003eAJR-S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003eVG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003eYD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003eJJC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003eMEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003eEAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003eTH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003eGS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003eJMW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003eMASP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ePV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003eB-AB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eConcept/Design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eMethodology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eInvestigation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eSupervision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eWriting the initial draft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eReading/editing draft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eFunding acquisition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eData curation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eData analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0668%;\"\u003e\n \u003cp\u003eProvision of resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.26992%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.11311%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.42674%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.49871%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.52699%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.24165%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 5.78406%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.81234%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.37018%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.35476%;\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare they have no competing interests. \u0026nbsp; \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Indigenous studies were supported by a grant from the Hallmark Indigenous Research Initiative at the University of Melbourne, and a Royal Melbourne Hospital Home Lottery Grant (GIA-060-2018). The ENDIA studies were supported by JDRF Australia, the recipient of the Commonwealth of Australia grant for Accelerated Research under the Medical Research Future Fund (grant keys 3-SRA-2023-1374-M-N, 3-SRA-2020-966-M-N, 1-SRA-2019-871-M-B, 4-SRA-2015-127-M-B), and with funding from The Leona M. and Harry B. Helmsley Charitable Trust. In addition, LCH was the recipient of an Investigator Grant (APP 1173945) from the National Health and Medical Research Council of Australia. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original data presented in this study are included in the article and Supplementary Material. Further inquiries can be directed to the corresponding author. Data on individual living humans cannot be publicly available due to its sensitive nature, as regulated by privacy legislation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRasmussen, M. \u003cem\u003eet al.\u003c/em\u003e An Indigenous Australian genome reveals separate human dispersals into Asia. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e334\u003c/strong\u003e, 94-98 (2011). https://doi.org/10.1126/science.1211177.\u003c/li\u003e\n\u003cli\u003eZhao, Y., Connors, C., Wright, J., Guthridge, S. \u0026amp; Bailie, R. Estimating chronic disease prevalence among the remote Aboriginal population of the Northern Territory using multiple data sources. \u003cem\u003eAust. N. Z. J. Public Health\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 307-313 (2008).\u003c/li\u003e\n\u003cli\u003eHorwood, P. 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D. \u003cem\u003eet al.\u003c/em\u003e ANOVA-like differential expression (ALDEx) analysis for mixed population RNA-Seq. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, e67019 (2013). https://doi.org/10.1371/journal.pone.0067019.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Indigenous, Australian, infants, gut microbiome, metagenomic sequencing","lastPublishedDoi":"10.21203/rs.3.rs-6101879/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6101879/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe gut microbiomes of traditional Indigenous and 'Western' societies differ markedly in diversity and composition. The Western diet modifies the gut microbiome, promoting cardiometabolic disorders that disproportionately affect Indigenous Australians. Studies of Indigenous gut microbiomes are underrepresented in the literature and comparative studies in young children living in traditional and Western societies are lacking, limiting our understanding of early-life microbiome development in different cultural contexts. Therefore, we analyzed gut metagenomes of 50 Indigenous Australian infants (median age \u0026lt; one year) living remotely with variable access to Western foods, compared to age- and sex-matched non-Indigenous infants living in urban Australia. Indigenous infants exhibited greater alpha diversity and significant differences in beta diversity, with 114 species and 38 genera differing in abundance. Some taxa were unique to Indigenous infants, who had higher carriage of \u003cem\u003eBifidobacteria\u003c/em\u003eat younger ages and \u003cem\u003ePrevotella\u003c/em\u003e at older ages. In contrast, non-Indigenous infants had a high abundance of \u003cem\u003ePhocaeicola\u003c/em\u003e (\u003cem\u003eBacteroides\u003c/em\u003e) across ages. Notably, Indigenous infants had markedly higher numbers of gut viruses and fungi. These findings reveal that despite encroaching Westernization, these Indigenous infants begin life with a gut microbiome that retains key features of traditional societies worldwide. The Western gut microbiome has not been transmitted inter-generationally and has not yet emerged, attesting to the dominant influence of a remote environment and enduring traditional lifestyle. This study provides crucial insights into the early-life microbiome in an Indigenous population and highlights the importance of preserving traditional lifestyles to maintain microbiome diversity.\u003c/p\u003e","manuscriptTitle":"Indigenous infants in remote Australia retain an ancestral gut microbiome despite encroaching Westernization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-13 06:24:20","doi":"10.21203/rs.3.rs-6101879/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"183bb239-590a-424a-a312-67342f8f8821","owner":[],"postedDate":"March 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":45612445,"name":"Health sciences/Molecular medicine"},{"id":45612446,"name":"Biological sciences/Computational biology and bioinformatics/Sequence annotation"}],"tags":[],"updatedAt":"2025-12-04T08:05:40+00:00","versionOfRecord":{"articleIdentity":"rs-6101879","link":"https://doi.org/10.1038/s41467-025-65758-0","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-12-03 05:00:00","publishedOnDateReadable":"December 3rd, 2025"},"versionCreatedAt":"2025-03-13 06:24:20","video":"","vorDoi":"10.1038/s41467-025-65758-0","vorDoiUrl":"https://doi.org/10.1038/s41467-025-65758-0","workflowStages":[]},"version":"v1","identity":"rs-6101879","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6101879","identity":"rs-6101879","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}