Age Patterning in Wild Chimpanzee Gut Microbiota Diversity Reveals Differences from Humans in Early Life

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Metaproteomics Analysis Reveals the Adaptation Process for the Chicken Gut Microbiota

The animal gastrointestinal tract houses a large microbial community, the gut microbiota, that confers many benefits to its host, such as protection from pathogens and provision of essential metabolites. Metagenomic approaches have defined the chicken fecal microbiota in other studies, but here, we wished to assess the correlation between the metagenome and the bacterial proteome in order to better understand the healthy chicken gut microbiota. Here, we performed high-throughput sequencing of 16S rRNA gene amplicons and metaproteomics analysis of fecal samples to determine microbial gut composition and protein expression. 16 rRNA gene sequencing analysis identified Clostridiales, Bacteroidaceae, and Lactobacillaceae species as the most abundant species in the gut. For metaproteomics analysis, peptides were generated by using the Fasp method and subsequently fractionated by strong anion exchanges. Metaproteomics analysis identified 3,673 proteins. Among the most frequently identified proteins, 380 proteins belonged to Lactobacillus spp., 155 belonged to Clostridium spp., and 66 belonged to Streptococcus spp. The most frequently identified proteins were heat shock chaperones, including 349 GroEL proteins, from many bacterial species, whereas the most abundant enzymes were pyruvate kinases, as judged by the number of peptides identified per protein (spectral counting). Gene ontology and KEGG pathway analyses revealed the functions and locations of the identified proteins. The findings of both metaproteomics and 16S rRNA sequencing analyses are discussed.     

Comparative Diversity Analysis of Gut Microbiota in Two Different Human Flora-Associated Mouse Strains

The Kunming (KM) mouse is a closed colony mouse strain widely used in Chinese pharmacology, toxicology, and microbiology research laboratories. However, few studies have examined human flora-associated (HFA) microbial communities in KM mice. In this study, HFA models were built from germ-free KM and C57BL/6J mouse strains, and gut microbial diversity was analyzed by denaturing gradient gel electrophoresis (DGGE) and DNA sequencing. We found that the two strains of HFA mice were significantly different based on the UPGMA dendrogram and the Richness index, but dice similarity coefficients of mouse replicates were not significantly different between HFA-KM and HFA-C57BL/6J. Most of the dominant phyla of human gut microflora could be transferred into the guts of the two mouse strains. However, the predominant genus that formed in HFA-KM was Clostridium sp. and that in HFA-C57BL/6J was Blautia sp. These results imply that genotypes difference between the two mice strains is a critical factor in shaping the intestinal microflora. However, genetic differences of individuals within KM mouse populations failed to lead to individual difference in microflora. Successful generation of HFA-KM mice will facilitate studies examining how diet affects gut microbial structure, and will enable comparative studies for uncovering genetic factors that shape gut microbial communities.     

Gut Microbiota in Children Hospitalized with Oedematous and Non-Oedematous Severe Acute Malnutrition in Uganda

Background

Severe acute malnutrition (SAM) among children remains a major health problem in many developing countries. SAM manifests in both an oedematous and a non-oedematous form, with oedematous malnutrition in its most severe form also known as kwashiorkor. The pathogenesis of both types of malnutrition in children remains largely unknown, but gut microbiota (GM) dysbiosis has recently been linked to oedematous malnutrition. In the present study we aimed to assess whether GM composition differed between Ugandan children suffering from either oedematous or non-oedematous malnutrition.

Methodology/Principal Findings

As part of an observational study among children hospitalized with SAM aged 6–24 months in Uganda, fecal samples were collected at admission. Total genomic DNA was extracted from fecal samples, and PCR amplification was performed followed by Denaturing Gradient Gel Electrophoresis (DGGE) and tag-encoded 16S rRNA gene-targeted high throughput amplicon sequencing. Alpha and beta diversity measures were determined along with ANOVA mean relative abundance and G-test of independence followed by comparisons between groups. Of the 87 SAM children included, 62% suffered from oedematous malnutrition, 66% were boys and the mean age was 16.1 months. GM composition was found to differ between the two groups of children as determined by DGGE (p = 0.0317) and by high-throughput sequencing, with non-oedematous children having lower GM alpha diversity (p = 0.036). However, beta diversity analysis did not reveal larger differences between the GM of children with oedematous and non-oedematous SAM (ANOSIM analysis, weighted UniFrac, R = -0.0085, p = 0.584; unweighted UniFrac, R = 0.0719, p = 0.011).

Conclusions/Significance

Our results indicate that non-oedematous SAM children have lower GM diversity compared to oedematous SAM children, however no clear compositional differences were identified.     

Trypanosome Infection Establishment in the Tsetse Fly Gut Is Influenced by Microbiome-Regulated Host Immune Barriers

Tsetse flies (Glossina spp.) vector pathogenic African trypanosomes, which cause sleeping sickness in humans and nagana in domesticated animals. Additionally, tsetse harbors 3 maternally transmitted endosymbiotic bacteria that modulate their host''s physiology. Tsetse is highly resistant to infection with trypanosomes, and this phenotype depends on multiple physiological factors at the time of challenge. These factors include host age, density of maternally-derived trypanolytic effector molecules present in the gut, and symbiont status during development. In this study, we investigated the molecular mechanisms that result in tsetse''s resistance to trypanosomes. We found that following parasite challenge, young susceptible tsetse present a highly attenuated immune response. In contrast, mature refractory flies express higher levels of genes associated with humoral (attacin and pgrp-lb) and epithelial (inducible nitric oxide synthase and dual oxidase) immunity. Additionally, we discovered that tsetse must harbor its endogenous microbiome during intrauterine larval development in order to present a parasite refractory phenotype during adulthood. Interestingly, mature aposymbiotic flies (Gmm ^Apo) present a strong immune response earlier in the infection process than do WT flies that harbor symbiotic bacteria throughout their entire lifecycle. However, this early response fails to confer significant resistance to trypanosomes. Gmm ^Apo adults present a structurally compromised peritrophic matrix (PM), which lines the fly midgut and serves as a physical barrier that separates luminal contents from immune responsive epithelial cells. We propose that the early immune response we observe in Gmm ^Apo flies following parasite challenge results from the premature exposure of gut epithelia to parasite-derived immunogens in the absence of a robust PM. Thus, tsetse''s PM appears to regulate the timing of host immune induction following parasite challenge. Our results document a novel finding, which is the existence of a positive correlation between tsetse''s larval microbiome and the integrity of the emerging adult PM gut immune barrier.     

舜皇山母猪与长×大二元杂母猪肠道微生物多样性的比较分析

为了解舜皇山母猪耐粗饲与抗病等方面的特性与其肠道微生物组成的关系,运用16S r DNA高通量测序技术分析同一养殖场舜皇山母猪和长×大二元杂母猪肠道微生物的组成和多样性。结果发现:舜皇山母猪的肠道微生物多样性高于长×大二元杂母猪。两种品系猪肠道微生物均以厚壁菌门、拟杆菌门、螺旋体门为主,其在舜皇山母猪和长×大二元杂母猪肠道中的总丰度分别为92.86%和94.05%。在属水平上,两种品系猪肠道微生物均以Muribaculaceae、普雷沃氏菌科、产粪甾醇真细菌、瘤胃球菌科、密螺旋体属、Christensenellaceae等为主,但它们的相对丰度存在较明显的差异;另外,毛螺菌科和链球菌属细菌在舜皇山土猪肠道中的含量显著高于长×大二元杂母猪。Lefse分析显示:长×大二元杂母猪肠道微生物中差异显著的物种有15种;舜皇山母猪有28种,其中10种属于毛螺菌科,推测毛螺菌科在舜皇山母猪的抗病能力以及耐粗饲方面具有重要作用。此外,舜皇山母猪肠道中含有稀有细菌,如红杆菌,它们可能存在潜在的研究价值。     

Helminth Colonization Is Associated with Increased Diversity of the Gut Microbiota

Soil-transmitted helminths colonize more than 1.5 billion people worldwide, yet little is known about how they interact with bacterial communities in the gut microbiota. Differences in the gut microbiota between individuals living in developed and developing countries may be partly due to the presence of helminths, since they predominantly infect individuals from developing countries, such as the indigenous communities in Malaysia we examine in this work. We compared the composition and diversity of bacterial communities from the fecal microbiota of 51 people from two villages in Malaysia, of which 36 (70.6%) were infected by helminths. The 16S rRNA V4 region was sequenced at an average of nineteen thousand sequences per samples. Helminth-colonized individuals had greater species richness and number of observed OTUs with enrichment of Paraprevotellaceae, especially with Trichuris infection. We developed a new approach of combining centered log-ratio (clr) transformation for OTU relative abundances with sparse Partial Least Squares Discriminant Analysis (sPLS-DA) to enable more robust predictions of OTU interrelationships. These results suggest that helminths may have an impact on the diversity, bacterial community structure and function of the gut microbiota.     

Tsetse Fly (G.f. fuscipes) Distribution in the Lake Victoria Basin of Uganda

Tsetse flies transmit trypanosomes, the causative agent of human and animal African trypanosomiasis. The tsetse vector is extensively distributed across sub-Saharan Africa. Trypanosomiasis maintenance is determined by the interrelationship of three elements: vertebrate host, parasite and the vector responsible for transmission. Mapping the distribution and abundance of tsetse flies assists in predicting trypanosomiasis distributions and developing rational strategies for disease and vector control. Given scarce resources to carry out regular full scale field tsetse surveys to up-date existing tsetse maps, there is a need to devise inexpensive means for regularly obtaining dependable area-wide tsetse data to guide control activities. In this study we used spatial epidemiological modelling techniques (logistic regression) involving 5000 field-based tsetse-data (G. f. fuscipes) points over an area of 40,000 km², with satellite-derived environmental surrogates composed of precipitation, temperature, land cover, normalised difference vegetation index (NDVI) and elevation at the sub-national level. We used these extensive tsetse data to analyse the relationships between presence of tsetse (G. f. fuscipes) and environmental variables. The strength of the results was enhanced through the application of a spatial autologistic regression model (SARM). Using the SARM we showed that the probability of tsetse presence increased with proportion of forest cover and riverine vegetation. The key outputs are a predictive tsetse distribution map for the Lake Victoria basin of Uganda and an improved understanding of the association between tsetse presence and environmental variables. The predicted spatial distribution of tsetse in the Lake Victoria basin of Uganda will provide significant new information to assist with the spatial targeting of tsetse and trypanosomiasis control.     

Plant and Fungal Diversity in Gut Microbiota as Revealed by Molecular and Culture Investigations

Background

Few studies describing eukaryotic communities in the human gut microbiota have been published. The objective of this study was to investigate comprehensively the repertoire of plant and fungal species in the gut microbiota of an obese patient.

Methodology/Principal Findings

A stool specimen was collected from a 27-year-old Caucasian woman with a body mass index of 48.9 who was living in Marseille, France. Plant and fungal species were identified using a PCR-based method incorporating 25 primer pairs specific for each eukaryotic phylum and universal eukaryotic primers targeting 18S rRNA, internal transcribed spacer (ITS) and a chloroplast gene. The PCR products amplified using these primers were cloned and sequenced. Three different culture media were used to isolate fungi, and these cultured fungi were further identified by ITS sequencing. A total of 37 eukaryotic species were identified, including a Diatoms (Blastocystis sp.) species, 18 plant species from the Streptophyta phylum and 18 fungal species from the Ascomycota, Basidiomycota and Chytridiocomycota phyla. Cultures yielded 16 fungal species, while PCR-sequencing identified 7 fungal species. Of these 7 species of fungi, 5 were also identified by culture. Twenty-one eukaryotic species were discovered for the first time in human gut microbiota, including 8 fungi (Aspergillus flavipes, Beauveria bassiana, Isaria farinosa, Penicillium brevicompactum, Penicillium dipodomyicola, Penicillium camemberti, Climacocystis sp. and Malassezia restricta). Many fungal species apparently originated from food, as did 11 plant species. However, four plant species (Atractylodes japonica, Fibraurea tinctoria, Angelica anomala, Mitella nuda) are used as medicinal plants.

Conclusions/Significance

Investigating the eukaryotic components of gut microbiota may help us to understand their role in human health.     

Genome-Wide Comparative Analysis of Chemosensory Gene Families in Five Tsetse Fly Species

For decades, odour-baited traps have been used for control of tsetse flies (Diptera; Glossinidae), vectors of African trypanosomes. However, differential responses to known attractants have been reported in different Glossina species, hindering establishment of a universal vector control tool. Availability of full genome sequences of five Glossina species offers an opportunity to compare their chemosensory repertoire and enhance our understanding of their biology in relation to chemosensation. Here, we identified and annotated the major chemosensory gene families in Glossina. We identified a total of 118, 115, 124, and 123 chemosensory genes in Glossina austeni, G. brevipalpis, G. f. fuscipes, G. pallidipes, respectively, relative to 127 reported in G. m. morsitans. Our results show that tsetse fly genomes have fewer chemosensory genes when compared to other dipterans such as Musca domestica (n>393), Drosophila melanogaster (n = 246) and Anopheles gambiae (n>247). We also found that Glossina chemosensory genes are dispersed across distantly located scaffolds in their respective genomes, in contrast to other insects like D. melanogaster whose genes occur in clusters. Further, Glossina appears to be devoid of sugar receptors and to have expanded CO₂ associated receptors, potentially reflecting Glossina''s obligate hematophagy and the need to detect hosts that may be out of sight. We also identified, in all species, homologs of Ir84a; a Drosophila-specific ionotropic receptor that promotes male courtship suggesting that this is a conserved trait in tsetse flies. Notably, our selection analysis revealed that a total of four gene loci (Gr21a, GluRIIA, Gr28b, and Obp83a) were under positive selection, which confers fitness advantage to species. These findings provide a platform for studies to further define the language of communication of tsetse with their environment, and influence development of novel approaches for control.     

16S rRNA Gene-Based Analysis Reveals the Effects of Gestational Diabetes on the Gut Microbiota of Mice During Pregnancy

Hyperglycemia is one of the metabolic characteristics of gestational diabetes mellitus (GDM). Considering that GDM is able to cause changes in the gut bacterial community and function in the mother’s intestine compared with healthy pregnant women, we aimed to clarify the correlation between hyperglycemia and gut microbiota in a GDM mouse model. Mice were divided into four groups: CE0, GDME0, CE18, and GDME18. C and GDM represent the control (C) and GDM groups, while E0 and E18 represent early or late trimesters of embryo day 0 or 18, respectively. GDM mouse models were created by injecting streptozocin on embryo day 0. The gut microbiota was characterized using the Illumina MiSeq platform targeting the V3–4 region of the 16S rRNA. Operational taxonomic unit analysis revealed a significant difference between CE18 and CE0, in which Akkermansia and Prevotellaceae were more abundant in the early trimester group, CE0. Moreover, the Clostridiales_vadinBB60 group was more abundant, while Parasutterella was much lower in GDME18 than in CE18. The gut microbiota community structure correlated with the GDM state, and LEfSe and molecular ecological network analysis further confirmed these diversities. Our research shows that changes in the community structure of the gut microbiota from the early to late trimester correlate with the GDM state. Changes in the abundance of the probiotic bacteria Akkermansia, Prevotellaceae, and Parasutterella may be involved in the GDM state.     

Pyrotag Sequencing of the Gut Microbiota of the Cockroach Shelfordella lateralis Reveals a Highly Dynamic Core but Only Limited Effects of Diet on Community Structure

Although blattid cockroaches and termites share a common ancestor, their diets are distinctly different. While termites consume a highly specialized diet of lignocellulose, cockroaches are omnivorous and opportunistic feeders. The role of the termite gut microbiota has been studied intensively, but little is known about the cockroach gut microbiota and its function in digestion and nutrition, particularly the adaptation to different diets. Our analyses of the bacterial gut microbiota of the blattid cockroach Shelfordella lateralis combining terminal restriction fragment length polymorphism of their 16S rRNA genes with physiological parameters (microbial metabolites, hydrogen and methane emission) indicated substantial variation between individuals but failed to identify any diet-related response. Subsequent deep-sequencing of the 16S rRNA genes of the colonic gut microbiota of S. lateralis fed either a high- or a low-fiber diet confirmed the absence of bacterial taxa that responded to diet. Instead, we found a small number of abundant phylotypes that were consistently present in all samples and made up half of the community in both diet groups. They varied strongly in abundance between individual samples at the genus but not at the family level. The remaining phylotypes were inconsistently present among replicate batches. Our findings suggest that S. lateralis harbors a highly dynamic core gut microbiota that is maintained even after fundamental dietary shifts, and that any dietary effects on the gut community are likely to be masked by strong individual variations.     

Strain Tracking Reveals the Determinants of Bacterial Engraftment in the Human Gut Following Fecal Microbiota Transplantation

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中国林蛙蝌蚪肠道及皮肤微生物多样性分析

肠道及皮肤微生物群落对宿主的健康有着至关重要的影响.本研究使用16S rRNA基因测序技术研究中国林蛙(Rana chensinensis)Gosner38期蝌蚪肠道和皮肤共生微生物群落组成之间的差异.在门水平上,林蛙蝌蚪肠道中的优势门为变形菌门(Proteobacteria)、厚壁菌门(Firmicutes)和拟杆菌...     

Patients with Infections of The Central Nervous System Have Lowered Gut Microbiota Alpha Diversity

There are multiple lines of evidence for the existence of communication between the central nervous system (CNS), gut, and intestinal microbiome. Despite extensive analysis conducted on various neurological disorders, the gut microbiome was not yet analyzed in neuroinfections. In the current study, we analyzed the gut microbiome in 47 consecutive patients hospitalized with neuroinfection (26 patients had viral encephalitis/meningitis; 8 patients had bacterial meningitis) and in 20 matched for age and gender health controls. Using the QIIME pipeline, 16S rRNA sequencing and classification into operational taxonomic units (OTUs) were performed on the earliest stool sample available. Bacterial taxa such as Clostridium, Anaerostipes, Lachnobacterium, Lachnospira, and Roseburia were decreased in patients with neuroinfection when compared to controls. Alpha diversity metrics showed lower within-sample diversity in patients with neuroinfections, though there were no differences in beta diversity. Furthermore, there was no significant change by short-term (1–3 days) antibiotic treatment on the gut microbiota, although alpha diversity metrics, such as Chao1 and Shannon’s index, were close to being statistically significant. The cause of differences between patients with neuroinfections and controls is unclear and could be due to inflammation accompanying the disease; however, the effect of diet modification and/or hospitalization cannot be excluded.     

Vast Differences in Strain-Level Diversity in the Gut Microbiota of Two Closely Related Honey Bee Species

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A Genome-Wide Analysis of Populations from European Russia Reveals a New Pole of Genetic Diversity in Northern Europe

Several studies examined the fine-scale structure of human genetic variation in Europe. However, the European sets analyzed represent mainly northern, western, central, and southern Europe. Here, we report an analysis of approximately 166,000 single nucleotide polymorphisms in populations from eastern (northeastern) Europe: four Russian populations from European Russia, and three populations from the northernmost Finno-Ugric ethnicities (Veps and two contrast groups of Komi people). These were compared with several reference European samples, including Finns, Estonians, Latvians, Poles, Czechs, Germans, and Italians. The results obtained demonstrated genetic heterogeneity of populations living in the region studied. Russians from the central part of European Russia (Tver, Murom, and Kursk) exhibited similarities with populations from central–eastern Europe, and were distant from Russian sample from the northern Russia (Mezen district, Archangelsk region). Komi samples, especially Izhemski Komi, were significantly different from all other populations studied. These can be considered as a second pole of genetic diversity in northern Europe (in addition to the pole, occupied by Finns), as they had a distinct ancestry component. Russians from Mezen and the Finnic-speaking Veps were positioned between the two poles, but differed from each other in the proportions of Komi and Finnic ancestries. In general, our data provides a more complete genetic map of Europe accounting for the diversity in its most eastern (northeastern) populations.     

Monitoring Bacterial Community of Human Gut Microbiota Reveals an Increase in Lactobacillus in Obese Patients and Methanogens in Anorexic Patients

Background

Studies of the bacterial communities of the gut microbiota have revealed a shift in the ratio of Firmicutes and Bacteroidetes in obese patients. Determining the variations of microbial communities in feces may be beneficial for the identification of specific profiles in patients with abnormal weights. The roles of the archaeon Methanobrevibacter smithii and Lactobacillus species have not been described in these studies.

Methods and Findings

We developed an efficient and robust real-time PCR tool that includes a plasmid-based internal control and allows for quantification of the bacterial divisions Bacteroidetes, Firmicutes, and Lactobacillus as well as the methanogen M. smithii. We applied this technique to the feces of 20 obese subjects, 9 patients with anorexia nervosa, and 20 normal-weight healthy controls. Our results confirmed a reduction in the Bacteroidetes community in obese patients (p<0.01). We found a significantly higher Lactobacillus species concentration in obese patients than in lean controls (p = 0.0197) or anorexic patients (p = 0.0332). The M. smithii concentration was much higher in anorexic patients than in the lean population (p = 0.0171).

Conclusions

Lactobacillus species are widely used as growth promoters in the farm industry and are now linked to obesity in humans. The study of the bacterial flora in anorexic patients revealed an increase in M. smithii. This increase might represent an adaptive use of nutrients in this population.