The gut microbiota of warm-blooded vertebrates consists of bacterial species belonging to two main phyla; Firmicutes and Bacteroidetes. However, does it mean that the same bacterial species are found in humans and chickens? Here we show that the ability to survive in an aerobic environment is central for host species adaptation. Known bacterial species commonly found in humans, pigs, chickens and Antarctic gentoo penguins are those capable of extended survival under aerobic conditions, i.e., either spore-forming, aerotolerant or facultatively anaerobic bacteria. Such bacteria are ubiquitously distributed in the environment, which acts as the source of infection with similar probability in humans, pigs, chickens, penguins and likely any other warm-blooded omnivorous hosts. On the other hand, gut anaerobes with no specific adaptation for survival in an aerobic environment exhibit host adaptation. This is associated with their vertical transmission from mothers to offspring and long-term colonisation after administration of a single dose. This knowledge influences the design of next-generation probiotics. The origin of aerotolerant or spore-forming probiotic strains may not be that important. On the other hand, if Bacteroidetes and other host-adapted species are used as future probiotics, host preference should be considered.

• Keywords
• chicken, endospore, environment, gut microbiota, host adaptation, human, penguin, pig, spread,
• Publication type
• Journal Article MeSH

In this review, we link ecological adaptations of different gut microbiota members with their potential for use as a new generation of probiotics. Gut microbiota members differ in their adaptations to survival in aerobic environments. Interestingly, there is an inverse relationship between aerobic survival and abundance or potential for prolonged colonization of the intestinal tract. Facultative anaerobes, aerotolerant Lactobacilli and endospore-forming Firmicutes exhibit high fluctuation, and if such bacteria are to be used as probiotics, they must be continuously administered to mimic their permanent supply from the environment. On the other hand, species not expressing any form of aerobic resistance, such as those from phylum Bacteroidetes, commonly represent host-adapted microbiota members characterized by vertical transmission from mothers to offspring, capable of long-term colonization following a single dose administration. To achieve maximal probiotic efficacy, the mode of their administration should thus reflect their natural ecology.

• Keywords
• chicken, gut, human, microbiota, pig, probiotics,
• MeSH
• Adaptation, Biological physiology   MeSH
• Lactobacillus physiology   MeSH
• Humans MeSH
• Probiotics pharmacology   therapeutic use   MeSH
• Gastrointestinal Microbiome physiology   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Review MeSH

Bacteroidaceae are common gut microbiota members in all warm-blooded animals. However, if Bacteroidaceae are to be used as probiotics, the species selected for different hosts should reflect the natural distribution. In this study, we therefore evaluated host adaptation of bacterial species belonging to the family Bacteroidaceae. B. dorei, B. uniformis, B. xylanisolvens, B. ovatus, B. clarus, B. thetaiotaomicron and B. vulgatus represented human-adapted species while B. gallinaceum, B. caecigallinarum, B. mediterraneensis, B. caecicola, M. massiliensis, B. plebeius and B. coprocola were commonly detected in chicken but not human gut microbiota. There were 29 genes which were present in all human-adapted Bacteroides but absent from the genomes of all chicken isolates, and these included genes required for the pentose cycle and glutamate or histidine metabolism. These genes were expressed during an in vitro competitive assay, in which human-adapted Bacteroides species overgrew the chicken-adapted isolates. Not a single gene specific for the chicken-adapted species was found. Instead, chicken-adapted species exhibited signs of frequent horizontal gene transfer, of KUP, linA and sugE genes in particular. The differences in host adaptation should be considered when the new generation of probiotics for humans or chickens is designed.

• Keywords
• Bacteroides, caecum, chicken, glutamate decarboxylase, human, microbiome, microbiota, pentose cycle,
• Publication type
• Journal Article MeSH

Studies analyzing the composition of gut microbiota are quite common at present, mainly due to the rapid development of DNA sequencing technologies within the last decade. This is valid also for chickens and their gut microbiota. However, chickens represent a specific model for host-microbiota interactions since contact between parents and offspring has been completely interrupted in domesticated chickens. Nearly all studies describe microbiota of chicks from hatcheries and these chickens are considered as references and controls. In reality, such chickens represent an extreme experimental group since control chicks should be, by nature, hatched in nests in contact with the parent hen. Not properly realising this fact and utilising only 16S rRNA sequencing results means that many conclusions are of questionable biological relevance. The specifics of chicken-related gut microbiota are therefore stressed in this review together with current knowledge of the biological role of selected microbiota members. These microbiota members are then evaluated for their intended use as a form of next-generation probiotics.

• Keywords
• Bacteroidetes, Firmicutes, caecum, chicken, development, faecal, gut microbiota, ileum,
• Publication type
• Journal Article MeSH
• Review MeSH

Our understanding of human gut microbiota in health and disease depends on accurate and reproducible microbial data acquisition. The critical step in this process is to apply an appropriate methodology to extract microbial DNA, since biases introduced during the DNA extraction process may result in inaccurate microbial representation. In this study, we attempted to find a DNA extraction protocol which could be effectively used to analyze both the bacterial and fungal community. We evaluated the effect of five DNA extraction methods (QIAamp DNA Stool Mini Kit, PureLinkTM Microbiome DNA Purification Kit, ZR Fecal DNA MiniPrepTM Kit, NucleoSpin® DNA Stool Kit, and IHMS protocol Q) on bacterial and fungal gut microbiome recovery using (i) a defined system of germ-free mice feces spiked with bacterial or fungal strains, and (ii) non-spiked human feces. In our experimental setup, we confirmed that the examined methods significantly differed in efficiency and quality, which affected the identified stool microbiome composition. In addition, our results indicated that fungal DNA extraction might be prone to be affected by reagent/kit contamination, and thus an appropriate blank control should be included in mycobiome research. Overall, standardized IHMS protocol Q, recommended by the International Human Microbiome Consortium, performed the best when considering all the parameters analyzed, and thus could be applied not only in bacterial, but also in fungal microbiome research.

• Keywords
• 16S rDNA, DNA extraction method, ITS rDNA, fungal microbiota, gut microbiome, gut microbiota, gut mycobiome, gut mycobiota,
• Publication type
• Journal Article MeSH

Since microbiota may influence the physiology of its host including body weight increase, growth rate or feed intake, in this study we determined the microbiota composition in high or low residual feed intake (HRFI and LRFI) pig lines, of different age and/or subjected to sanitary stress by sequencing the V3/V4 variable region of 16S rRNA genes. Allisonella, Megasphaera, Mitsuokella, Acidaminococcus (all belonging to Firmicutes/class Negativicutes), Lactobacillus, Faecalibacterium, Catenibacterium, Butyrivibrio, Erysipelotrichaceae, Holdemania, Olsenella and Collinsella were more abundant in HRFI pigs. On the other hand, 26 genera including Bacteroides, Clostridium sensu stricto, Oscillibacter, Paludibacter, Elusimicrobium, Bilophila, Pyramidobacter and TM7 genera, and Clostridium XI and Clostridium XIVa clusters were more abundant in LRFI than HRFI pigs. Adaptation of microbiota to new diet after weaning was slower in LRFI than in HRFI pigs. Sanitary stress was of relatively minor influence on pig microbiota composition in both tested lines although abundance of Helicobacter increased in LRFI pigs subjected to stress. Selection for residual feed intake thus resulted in a selection of fecal microbiota of different composition. However, we cannot conclude whether residual feed intake was directly affected by different microbiota composition or whether the residual feed intake and microbiota composition are two independent consequences of yet unknown genetic traits differentially selected in the pigs of the two lines.

• MeSH
• RNA, Bacterial MeSH
• Diet * MeSH
• Species Specificity * MeSH
• Feces microbiology   MeSH
• Stress, Physiological physiology   MeSH
• Weaning MeSH
• Eating MeSH
• RNA, Ribosomal, 16S MeSH
• Gastrointestinal Microbiome genetics   physiology   MeSH
• Sus scrofa MeSH
• Age Factors MeSH
• Environment * MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH
• Names of Substances
• RNA, Bacterial MeSH
• RNA, Ribosomal, 16S MeSH

BACKGROUND: In order to start to understand the function of individual members of gut microbiota, we cultured, sequenced and analysed bacterial anaerobes from chicken caecum. RESULTS: Altogether 204 isolates from chicken caecum were obtained in pure cultures using Wilkins-Chalgren anaerobe agar and anaerobic growth conditions. Genomes of all the isolates were determined using the NextSeq platform and subjected to bioinformatic analysis. Among 204 sequenced isolates we identified 133 different strains belonging to seven different phyla - Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Verrucomicrobia, Elusimicrobia and Synergistetes. Genome sizes ranged from 1.51 Mb in Elusimicrobium minutum to 6.70 Mb in Bacteroides ovatus. Clustering based on the presence of protein coding genes showed that isolates from phyla Proteobacteria, Verrucomicrobia, Elusimicrobia and Synergistetes did not cluster with the remaining isolates. Firmicutes split into families Lactobacillaceae, Enterococcaceae, Veillonellaceae and order Clostridiales from which the Clostridium perfringens isolates formed a distinct sub-cluster. All Bacteroidetes isolates formed a separate cluster showing similar genetic composition in all isolates but distinct from the rest of the gut anaerobes. The majority of Actinobacteria clustered closely together except for the representatives of genus Gordonibacter showing that the genome of this genus differs from the rest of Actinobacteria sequenced in this study. Representatives of Bacteroidetes commonly encoded proteins (collagenase, hemagglutinin, hemolysin, hyaluronidase, heparinases, chondroitinase, mucin-desulfating sulfatase or glutamate decarboxylase) that may enable them to interact with their host. Aerotolerance was recorded in Akkermansia and Cloacibacillus and was also common among representatives of Bacteroidetes. On the other hand, Elusimicrobium and the majority of Clostridiales were highly sensitive to air exposure despite their potential for spore formation. CONCLUSIONS: Major gut microbiota members utilise different strategies for gut colonisation. High oxygen sensitivity of Firmicutes may explain their commonly reported decrease after oxidative burst during gut inflammation.

• Keywords
• Anaerobe, Butyrate, Chicken, Host-microbiota interactions, Metabolic pathway, Microbiome, Microbiota, Propionate, Whole genome sequencing,
• MeSH
• Bacteria, Anaerobic genetics   isolation & purification   MeSH
• Cecum microbiology   MeSH
• Genome Size MeSH
• DNA, Bacterial genetics   MeSH
• Phylogeny MeSH
• Chickens * MeSH
• Whole Genome Sequencing methods   MeSH
• Gastrointestinal Microbiome MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• DNA, Bacterial MeSH