Autoimmunity and the microbiome: T‐cell receptor mimicry of “self” and microbial antigens mediates self tolerance in holobionts

I propose a T‐cell receptor (TcR)‐based mechanism by which immunity mediates both “genetic self” and “microbial self” thereby, connecting microbiome disease with autoimmunity. The hypothesis is based on simple principles. First, TcR are selected to avoid strong cross‐reactivity with “self,” resulting in selection for a TcR repertoire mimicking “genetic self.” Second, evolution has selected for a “microbial self” that mimics “genetic self” so as to share tolerance. In consequence, our TcR repertoire also mimics microbiome antigenicity, providing a novel mechanism for modulating tolerance to it. Also, the microbiome mimics the TcR repertoire, acting as a secondary immune system. I call this TcR‐microbiome mimicry “holoimmunity” to denote immune tolerance to the “holobiont self.” Logically, microbiome‐host mimicry means that autoimmunity directed at host antigens will also attack components of the microbiome, and conversely, an immunological attack on the microbiome may cross‐react with host antigens producing “holoautoimmunity.”

     

Microbial Interaction Network Estimation via Bias-Corrected Graphical Lasso

With the increasing availability of microbiome 16S data, network estimation has become a useful approach to studying the interactions between microbial taxa. Network estimation on a set of variables is frequently explored using graphical models, in which the relationship between two variables is modeled via their conditional dependency given the other variables. Various methods for sparse inverse covariance estimation have been proposed to estimate graphical models in the high-dimensional setting, including graphical lasso. However, current methods do not address the compositional count nature of microbiome data, where abundances of microbial taxa are not directly measured, but are reflected by the observed counts in an error-prone manner. Adding to the challenge is that the sum of the counts within each sample, termed “sequencing depth,” is an experimental technicality that carries no biological information but can vary drastically across samples. To address these issues, we develop a new approach to network estimation, called BC-GLASSO (bias-corrected graphical lasso), which models the microbiome data using a logistic normal multinomial distribution with the sequencing depths explicitly incorporated, corrects the bias of the naive empirical covariance estimator arising from the heterogeneity in sequencing depths, and builds the inverse covariance estimator via graphical lasso. We demonstrate the advantage of BC-GLASSO over current approaches to microbial interaction network estimation under a variety of simulation scenarios. We also illustrate the efficacy of our method in an application to a human microbiome data set.

     

Composition and stability of the vervet monkey milk microbiome

The human milk microbiome is vertically transmitted to offspring during the postnatal period and has emerged as a critical driver of infant immune and metabolic development. Despite this importance in humans, the milk microbiome of nonhuman primates remains largely unexplored. This dearth of comparative work precludes our ability to understand how species‐specific differences in the milk microbiome may differentially drive maternal effects and limits how translational models can be used to understand the role of vertically transmitted milk microbes in human development. Here, we present the first culture‐independent data on the milk microbiome of a nonhuman primate. We collected milk and matched fecal microbiome samples at early and late lactation from a cohort of captive lactating vervet monkeys (N = 15). We found that, similar to humans, the vervet monkey milk microbiome comprises a shared community of taxa that are universally present across individuals. However, unlike in humans, this shared community is dominated by the genera Lactobacillus, Bacteroides, and Prevotella. We also found that, in contrast to previous culture‐dependent studies in humans, the vervet milk microbiome exhibits greater alpha‐diversity than the gut microbiome across lactation. Finally, we did not find support for the translocation of microbes from the gut to the mammary gland within females (i.e., “entero‐mammary pathway”). Taken together, our results show that the vervet monkey milk microbiome is taxonomically diverse, distinct from the gut microbiome, and largely stable. These findings demonstrate that the milk microbiome is a unique substrate that may selectively favor the establishment and persistence of particular microbes across lactation and highlights the need for future experimental studies on the origin of microbes in milk.     

Rhizosphere microbiome: revisiting the synergy of plant-microbe interactions

Sustainable enhancement in food production from less available arable land must encompass a balanced use of inorganic, organic, and biofertilizer sources of plant nutrients to augment and maintain soil fertility and productivity. The varied responses of microbial inoculants across fields and crops, however, have formed a major bottleneck that hinders its widespread adoption. This necessitates an intricate analysis of the inter-relationships between soil microbial communities and their impact on host plant productivity. The concept of “biased rhizosphere,” which evolved from the interactions among different components of the rhizosphere including plant roots and soil microflora, strives to garner a better understanding of the complex rhizospheric intercommunications. Moreover, knowledge on rhizosphere microbiome is essential for developing strategies for shaping the rhizosphere to benefit the plants. With the advent of molecular and “omics” tools, a better understanding of the plant-microbe association could be acquired which could play a crucial role in drafting the future “biofertilizers.” The present review, therefore aims to (a) to introduce the concepts of rhizosphere hotspots and microbiomes and (b) to detail out the methodologies for creating biased rhizospheres for plant-mediated selection of beneficial microorganisms and their roles in improving plant performance.

     

微生物组学及其在厌氧消化中的研究进展

我国每年产生大量的有机废弃物,如果处置不当将会对生态、气候以及人类健康造成重大影响。厌氧消化是一种可靠的、绿色的、可持续的有机废弃物处理方式,但由于缺乏准确有效的监测手段,厌氧消化微观过程常常被视为“黑盒”。随着微生物组学的发展,学者们在菌群与运行参数关联性分析、代谢途径分析等方面有了更深入的认识。本文从“三阶段、四菌群”的厌氧消化过程出发,介绍了常用微生物组学的类型,包括:16S rRNA基因组、宏基因组、宏转录组和宏蛋白组;详细阐述了物种组成分析、α多样性分析、OTU相似性分析以及多元统计学分析等6种常用的微生物群落生物信息学分析方法;系统回顾了厌氧消化过程的微生物学研究进展,以期能为分析厌氧消化的微生物群落结构和功能、开发新的厌氧消化工艺和技术提供支持。     

Robust and Powerful Differential Composition Tests for Clustered Microbiome Data

Thanks to advances in high-throughput sequencing technologies, the importance of microbiome to human health and disease has been increasingly recognized. Analyzing microbiome data from sequencing experiments is challenging due to their unique features such as compositional data, excessive zero observations, overdispersion, and complex relations among microbial taxa. Clustered microbiome data have become prevalent in recent years from designs such as longitudinal studies, family studies, and matched case–control studies. The within-cluster dependence compounds the challenge of the microbiome data analysis. Methods that properly accommodate intra-cluster correlation and features of the microbiome data are needed. We develop robust and powerful differential composition tests for clustered microbiome data. The methods do not rely on any distributional assumptions on the microbial compositions, which provides flexibility to model various correlation structures among taxa and among samples within a cluster. By leveraging the adjusted sandwich covariance estimate, the methods properly accommodate sample dependence within a cluster. The two-part version of the test can further improve power in the presence of excessive zero observations. Different types of confounding variables can be easily adjusted for in the methods. We perform extensive simulation studies under commonly adopted clustered data designs to evaluate the methods. We demonstrate that the methods properly control the type I error under all designs and are more powerful than existing methods in many scenarios. The usefulness of the proposed methods is further demonstrated with two real datasets from longitudinal microbiome studies on pregnant women and inflammatory bowel disease patients. The methods have been incorporated into the R package “miLineage” publicly available at https://tangzheng1.github.io/tanglab/software.html.

     

The microbiota in spider mite feces potentially reflects intestinal bacterial communities in the host

Microorganisms provide many physiological functions to herbivorous hosts. Spider mites (genus Tetranychus) are important agricultural pests throughout the world; however, the composition of the spider mite microbial community, especially gut microbiome, remains unclear. Here, we investigated the bacterial community in five spider mite species and their associated feces by deep sequencing of the 16S rRNA gene. The composition of the bacterial community was significantly different among the five prevalent spider mite species, and some bacterial symbionts showed host‐species specificity. Moreover, the abundance of the bacterial community in spider mite feces was significantly higher than that in the corresponding spider mite samples. However, Flavobacterium was detected in all samples, and represent a “core microbiome”. Remarkably, the maternally inherited endosymbiont Wolbachia was detected in both spider mite and feces. Overall, these results offer insight into the complex community of symbionts in spider mites, and give a new direction for future studies.     

Vaginal microbiome variances in sample groups categorized by clinical criteria of bacterial vaginosis

Background

One of the most common and recurrent vaginal infections is bacterial vaginosis (BV). The diagnosis is based on changes to the “normal” vaginal microbiome; however, the normal microbiome appears to differ according to reproductive status and ethnicity, and even among individuals within these groups. The Amsel criteria and Nugent score test are widely used for diagnosing BV; however, these tests are based on different criteria, and so may indicate distinct changes in the vaginal microbial community. Nevertheless, few studies have compared the results of these test against metagenomics analysis.

Methods

Vaginal flora samples from 77 participants were classified according to the Amsel criteria and Nugent score test. The microbiota composition was analyzed using 16S ribosome RNA gene amplicon sequencing. Bioinformatics analysis and multivariate statistical analysis were used to evaluate the microbial diversity and function.

Results

Only 3 % of the participants diagnosed BV negative using the Amsel criteria (A−) were BV-positive according to the Nugent score test (N+), while over half of the BV-positive patients using the Amsel criteria (A+) were BV-negative according to the Nugent score test (N−). Thirteen genera showed significant differences in distribution among BV status defined by BV tests (e.g., A − N−, A + N− and A + N+). Variations in the four most abundant taxa, Lactobacillus, Gardnerella, Prevotella, and Escherichia, were responsible for most of this dissimilarity. Furthermore, vaginal microbial diversity differed significantly among the three groups classified by the Nugent score test (N−, N+, and intermediate flora), but not between the Amsel criteria groups. Numerous predictive microbial functions, such as bacterial chemotaxis and bacterial invasion of epithelial cells, differed significantly among multiple BV test, but not between the A− and A+ groups.

Conclusions

Metagenomics analysis can greatly expand our current understanding of vaginal microbial diversity in health and disease. Metagenomics profiling may also provide more reliable diagnostic criteria for BV testing.

     

Reduced skin bacterial diversity correlates with increased pathogen infection intensity in an endangered amphibian host

The fungal pathogen Batrachochytrium dendrobatidis (Bd) infects the skin of amphibians and has caused severe declines and extinctions of amphibians globally. In this study, we investigate the interaction between Bd and the bacterial skin microbiome of the endangered Sierra Nevada yellow‐legged frog, Rana sierrae, using both culture‐dependent and culture‐independent methods. Samples were collected from two populations of R. sierrae that likely underwent Bd epizootics in the past, but that continue to persist with Bd in an enzootic disease state, and we address the hypothesis that such “persistent” populations are aided by mutualistic skin microbes. Our 16S rRNA metabarcoding data reveal that the skin microbiome of highly infected juvenile frogs is characterized by significantly reduced species richness and evenness, and by strikingly lower variation between individuals, compared to juveniles and adults with lower infection levels. Over 90% of DNA sequences from the skin microbiome of highly infected frogs were derived from bacteria in a single order, Burkholderiales, compared to just 54% in frogs with lower infection levels. In a culture‐dependent Bd inhibition assay, the bacterial metabolites we evaluated all inhibited the growth of Bd. Together, these results illustrate the disruptive effects of Bd infection on host skin microbial community structure and dynamics, and suggest possible avenues for the development of anti‐Bd probiotic treatments.     

Metacommunity theory for transmission of heritable symbionts within insect communities

Microbial organisms are ubiquitous in nature and often form communities closely associated with their host, referred to as the microbiome. The microbiome has strong influence on species interactions, but microbiome studies rarely take interactions between hosts into account, and network interaction studies rarely consider microbiomes. Here, we propose to use metacommunity theory as a framework to unify research on microbiomes and host communities by considering host insects and their microbes as discretely defined “communities of communities” linked by dispersal (transmission) through biotic interactions. We provide an overview of the effects of heritable symbiotic bacteria on their insect hosts and how those effects subsequently influence host interactions, thereby altering the host community. We suggest multiple scenarios for integrating the microbiome into metacommunity ecology and demonstrate ways in which to employ and parameterize models of symbiont transmission to quantitatively assess metacommunity processes in host‐associated microbial systems. Successfully incorporating microbiota into community‐level studies is a crucial step for understanding the importance of the microbiome to host species and their interactions.     

The journey of gut microbiome – An introduction and its influence on metabolic disorders

Background

Metabolic disorders such as Obesity, Diabetes Type 2 (T2DM) and Inflammatory Bowel Diseases (IBD) are the most prevalent globally. Recently, there has been a surge in the evidence indicating the correlation between the intestinal microbiota and development of these metabolic conditions apart from predisposing genetic and epigenetic factors. Gut microbiome is pivotal in controlling the host metabolism and physiology. But imbalances in the microbiota patterns lead to these disorders via several pathways. Animal and human studies so far have concentrated mostly on metagenomics for the whole microbiome characterization to understand how microbiome supports health in general. However, the accurate mechanisms connecting the metabolic disorders and alterations in gut microbial composition in host and the metabolites employed by the microorganisms in regulating the metabolic disorders is still vague.

Objective

The review delineates the latest findings about the role of gut microbiome to the pathophysiology of Obesity, IBD and Diabetes Mellitus. Here, we provide a brief introduction to the gut microbiome followed by the current therapeutic interventions in restoration of the disrupted intestinal microbiota.

Methods

A methodical PubMed search was performed using keywords like “gut microbiome,” “obesity,” “diabetes,” “IBD,” and “metabolic syndromes.” All significant and latest publications up to January 2018 were accounted for the review.

Results

Out of the 93 articles cited, 63 articles focused on the gut microbiota association to these disorders. The rest 18 literature outlines the therapeutic approaches in maintaining the gut homeostasis using probiotics, prebiotics and faecal microbial transplant (FMT).

Conclusion

Metabolic disorders have intricate etiology and thus a lucid understanding of the complex host-microbiome inter-relationships will open avenues to novel therapeutics for the diagnosis, prevention and treatment of the metabolic diseases.

     

Experimental evidence of microbial inheritance in plants and transmission routes from seed to phyllosphere and root

While the environment is considered the primary origin of the plant microbiome, the potential role of seeds as a source of transmitting microorganisms has not received much attention. Here we tested the hypothesis that the plant microbiome is partially inherited through vertical transmission. An experimental culturing device was constructed to grow oak seedlings in a microbe-free environment while keeping belowground and aboveground tissues separated. The microbial communities associated with the acorn's embryo and pericarp and the developing seeding's phyllosphere and root systems were analysed using amplicon sequencing of fungal ITS and bacterial 16S rDNA. Results showed that the seed microbiome is diverse and non-randomly distributed within an acorn. The microbial composition of the phyllosphere was diverse and strongly resembled the composition found in the embryo, whereas the roots and pericarp each had a less diverse and distinct microbial community. Our findings demonstrate a high level of microbial diversity and spatial partitioning of the fungal and bacterial community within both seed and seedling, indicating inheritance, niche differentiation and divergent transmission routes for the establishment of root and phyllosphere communities.     

Gut microbiome changes in overweight male adults following bowel preparation

Background

Human gut microbiome has an essential role in human health and disease. Although the major dominant microbiota within individuals have been reported, the change of gut microbiome caused by external factors, such as antibiotic use and bowel cleansing, remains unclear. We conducted this study to investigate the change of gut microbiome in overweight male adults after bowel preparation, where none of the participants had been diagnosed with any systemic diseases.

Methods

A total of 20 overweight, male Taiwanese adults were recruited, and all participants were omnivorous. The participants provided fecal samples and blood samples at three time points: prior to bowel preparation, 7 days after colonoscopy, and 28 days after colonoscopy. The microbiota composition in fecal samples was analyzed using 16S ribosome RNA gene amplicon sequencing.

Results

Our results demonstrated that the relative abundance of the most dominant bacteria hardly changed from prior to bowel preparation to 28 days after colonoscopy. Using the ratio of Prevotella to the sum of Prevotella and Bacteroides in the fecal samples at baseline, the participants were separated into two groups. The fecal samples of the Type 1 group was Bacteroides-dominant, and that of the Type 2 group was Prevotella-dominant with a noticeable presence Bacteroides. Bulleidia appears more in the Type 1 fecal samples, while Akkermensia appears more in the Type 2 fecal samples. Of each type, the gut microbial diversity differed slightly among the three collection times. Additionally, the Type 2 fecal microbiota was temporarily susceptible to bowel cleansing. Predictive functional analysis of microbial community reveals that their activities for the mineral absorption metabolism and arachidonic acid metabolism differed significantly between the two types. Depending on their fecal type, the variance of triglycerides and C-reactive protein also differed between the two types of participants.

Conclusions

Depending upon the fecal type, the microbial diversity and the predictive functional modules of microbial community differed significantly after bowel preparation. In addition, blood biochemical markers presented somewhat associated with fecal type. Therefore, our results might provide some insights as to how knowledge of the microbial community could be used to promote health through personalized clinical treatment.

     

Explore mediated co-varying dynamics in microbial community using integrated local similarity and liquid association analysis

Background

Discovering the key microbial species and environmental factors of microbial community and characterizing their relationships with other members are critical to ecosystem studies. The microbial co-occurrence patterns across a variety of environmental settings have been extensively characterized. However, previous studies were limited by their restriction toward pairwise relationships, while there was ample evidence of third-party mediated co-occurrence in microbial communities.

Methods

We implemented and applied the triplet-based liquid association analysis in combination with the local similarity analysis procedure to microbial ecology data. We developed an intuitive scheme to visualize those complex triplet associations along with pairwise correlations. Using a time series from the marine microbial ecosystem as example, we identified pairs of operational taxonomic units (OTUs) where the strength of their associations appeared to relate to the values of a third “mediator” variable. These “mediator” variables appear to modulate the associations between pairs of bacteria.

Results

Using this analysis, we were able to assess the OTUs’ ability to regulate its functional partners in the community, typically not manifested in the pairwise correlation patterns. For example, we identified Flavobacteria as a multifaceted player in the marine microbial ecosystem, and its clades were involved in mediating other OTU pairs. By contrast, SAR11 clades were not active mediators of the community, despite being abundant and highly correlated with other OTUs. Our results suggested that Flavobacteria are more likely to respond to situations where particles and unusual sources of dissolved organic material are prevalent, such as after a plankton bloom. On the other hand, SAR11s are oligotrophic chemoheterotrophs with inflexible metabolisms, and their relationships with other organisms may be less governed by environmental or biological factors.

Conclusions

By integrating liquid association with local similarity analysis to explore the mediated co-varying dynamics, we presented a novel perspective and a useful toolkit to analyze and interpret time series data from microbial community. Our augmented association network analysis is thus more representative of the true underlying dynamic structure of the microbial community. The analytic software in this study was implemented as new functionalities of the ELSA (Extended local similarity analysis) tool, which is available for free download (http://bitbucket.org/charade/elsa).

     

An Alternative Hypothesis For The Origin of the Name Blackfoot

Abstract

Recent ethnographic work with Cree informants supports the hypothesis that the original Cree. term for “Blackfoot” Indians referred to animal (perhaps horse’s) hooves rather than to artificially blackened feet or moccasins.     

Vertical vs. horizontal transmission of the microbiome in a key disease vector,Ixodes pacificus

Vector‐borne pathogens are increasingly found to interact with the vector's microbiome, influencing disease transmission dynamics. However, the processes that regulate the formation and development of the microbiome are largely unexplored for most tick species, an emerging group of disease vectors. It is not known how much of the tick microbiome is acquired through vertical transmission vs. horizontally from the environment or interactions with bloodmeal sources. Using 16S rRNA sequencing, we examined the microbiome of Ixodes pacificus, the vector of Lyme disease in the western USA, across life stages and infection status. We also characterized microbiome diversity in field and laboratory‐collected nymphal ticks to determine how the surrounding environment affects microbiome diversity. We found a decrease in both species richness and evenness as the tick matures from larva to adult. When the dominant Rickettsial endosymbiont was computationally removed from the tick microbial community, we found that infected nymphs had lower species evenness than uninfected ticks, suggesting that lower microbiome diversity is associated with pathogen transmission in wild‐type ticks. Furthermore, laboratory‐reared nymph microbiome diversity was found to be compositionally distinct and significantly depauperate relative to field‐collected nymphs. These results highlight unique patterns in the microbial community of I. pacificus that is distinct from other tick species. We provide strong evidence that ticks acquire a significant portion of their microbiome through exposure to their environment despite a loss of overall diversity through life stages. We provide evidence that loss of microbial diversity is at least in part due to elimination of microbial diversity with bloodmeal feeding but other factors may also play a role.     

Hydrology shapes microbial communities and microbiome-mediated growth of an Everglades tree island species

Plant-associated microbiomes can improve plant fitness by ameliorating environmental stress, providing a promising avenue for improving outplantings during restoration. However, the effects of water management on these microbial communities and their cascading effects on primary producers are unresolved for many imperiled ecosystems. One such habitat, Everglades tree islands, has declined by 54% in some areas, releasing excess nutrients into surrounding wetlands and exacerbating nutrient pollution. We conducted a factorial experiment, manipulating the soil microbiome and hydrological regime experienced by a tree island native, Ficus aurea, to determine how microbiomes impact growth under two hydrological management plans. All plants were watered to simulate natural precipitation, but plants in the “unconstrained” management treatment were allowed to accumulate water above the soil surface, while the “constrained” treatment had a reduced stage to avoid soil submersion. We found significant effects of the microbiomes on overall plant performance and aboveground versus belowground investment; however, these effects depended on hydrological treatment. For instance, microbiomes increased investment in roots relative to aboveground tissues, but these effects were 142% stronger in the constrained compared to unconstrained water regime. Changes in hydrology also resulted in changes in the prokaryotic community composition, including a >20 log₂fold increase in the relative abundance of Rhizobiaceae, and hydrology-shifted microbial composition was linked to changes in plant performance. Our results suggest that differences in hydrological management can have important effects on microbial communities, including taxa often involved in nitrogen cycling, which can in turn impact plant performance.     

马铃薯全生育期内根际微生物组变化规律

[目的]陆生植物根际环境与土壤中的微生物菌群关系密切,其根际微生物群落动态极可能直接影响着植物健康及养分高效利用。虽然根际益生菌已被证实可用于提高作物生产力,但由于缺乏对这些菌群组成动态变化规律的认识了解,它们的开发受到限制。研究马铃薯全生育期根际菌群的动态变化规律,探讨根际菌群变化与马铃薯发育时期的相关性,为针对马铃薯不同生长时期开发专用生物益生菌肥奠定理论基础。[方法]本研究着眼于马铃薯田间全生命周期微生物组动态变化,通过Illumina MiSeq高通量测序技术对不同时间点马铃薯根际细菌16S rRNA基因V3-V4区和真菌ITS区测序并对操作分类单位(OTU)进行聚类,分析样品间微生物群落的多样性特征,并通过机器学习的方法建立模型,将根际菌群与田间马铃薯发育时间相关联。[结果]根际菌群在马铃薯各个发育阶段随时间变化明显,营养生长阶段的微生物群落结构发生了显著变化,随着结薯期的开始逐渐稳定,直到块茎成熟后期根际菌群再次出现较大变化,且在不同施肥处理间呈现较大差异。进一步基于模型挖掘了与马铃薯发育时间相关联的22个特征细菌类群和16个特征真菌类群,其中苗期和结薯末期的特征类群分别为梭菌(Clostridium)和放线菌(Actinobacteria)。[结论]马铃薯的生长发育时期是影响根际微生物群落组成的主要因素,益生菌肥的添加主要影响马铃薯结薯末期的细菌微生物菌群结构。     

Full-repertoire comparison of the microscopic objects composing the human gut microbiome with sequenced and cultured communities

The study of the human gut microbiome is essential in microbiology and infectious diseases as specific alterations in the gut microbiome might be associated with various pathologies, such as chronic inflammatory disease, intestinal infection and colorectal cancer. To identify such dysregulations, several strategies are being used to create a repertoire of the microorganisms composing the human gut microbiome. In this study, we used the “microscomics” approach, which consists of creating an ultrastructural repertoire of all the cell-like objects composing stool samples from healthy donors using transmission electron microscopy (TEM). We used TEM to screen ultrathin sections of 8 resin-embedded stool samples. After exploring hundreds of micrographs, we managed to elaborate ultrastructural categories based on morphological criteria or features. This approach explained many inconsistencies observed with other techniques, such as metagenomics and culturomics. We highlighted the value of our culture-independent approach by comparing our microscopic images to those of cultured bacteria and those reported in the literature. This study helped to detect “minimicrobes” Candidate Phyla Radiation (CPR) for the first time in human stool samples. This “microscomics” approach is non-exhaustive but complements already existing approaches and adds important data to the puzzle of the microbiota.

     

Maternal obesity is associated with gut microbial metabolic potential in offspring during infancy

Children born to obese mothers are at increased risk for obesity, but the mechanisms behind this association are not fully understood. Our study aimed to investigate differences in the functions encoded by the microbiome of infants at 18 months of age when the transition from early infant-feeding to solid family foods is established. To investigate the impact of maternal prepregnancy body mass index on infants’ gut microbiome, faecal samples from infants born to normoweight (n = 21) and obese mothers (n = 18) were analysed by 16S rRNA gene sequencing and a functional-inference-based microbiome analysis. Our results indicated that Firmicutes was significantly enriched in infants born to normoweight mothers whereas Bacteroidetes was significantly enriched in infants born to obese women. In both microbiomes, the greatest number of genes (>50%) that were assigned a function encoded for proteins involved in “metabolism” among tier 1 KEGG Orthology (KO) categories. At lower KO functional categories, the microbiome of infants born to normoweight mothers was characterized by a significant enrichment in the abundances of “pentose phosphate pathway” (p = 0.037), “lysine biosynthesis” (p = 0.043), “glycerolipid metabolism” (p = 0.042), and “C5-branched dibasic acid metabolism” (p = 0.045). Notably, the microbiome of infants born to obese mothers was significantly enriched in “streptomycin biosynthesis” (p = 0.047), “sulphur metabolism” (p = 0.041), “taurine and hypotaurine metabolism” (p = 0.036), and “lipopolysaccharide biosynthesis” (p = 0.043). In summary, our study showed that maternal prepregnancy obesity may imprint a selective gut microbial composition during late infancy with distinct functional performances.