Diversity of Bifidobacteria within the Infant Gut Microbiota

Background The human gastrointestinal tract (GIT) represents one of the most densely populated microbial ecosystems studied to date. Although this microbial consortium has been recognized to have a crucial impact on human health, its precise composition is still subject to intense investigation. Among the GIT microbiota, bifidobacteria represent an important commensal group, being among the first microbial colonizers of the gut. However, the prevalence and diversity of members of the genus Bifidobacterium in the infant intestinal microbiota has not yet been fully characterized, while some inconsistencies exist in literature regarding the abundance of this genus. Methods/Principal Findings In the current report, we assessed the complexity of the infant intestinal bifidobacterial population by analysis of pyrosequencing data of PCR amplicons derived from two hypervariable regions of the 16 S rRNA gene. Eleven faecal samples were collected from healthy infants of different geographical origins (Italy, Spain or Ireland), feeding type (breast milk or formula) and mode of delivery (vaginal or caesarean delivery), while in four cases, faecal samples of corresponding mothers were also analyzed. Conclusions In contrast to several previously published culture-independent studies, our analysis revealed a predominance of bifidobacteria in the infant gut as well as a profile of co-occurrence of bifidobacterial species in the infant’s intestine

Is there a special mechanism behind the changes in somatic cell and polymorphonuclear leukocyte counts, and composition of milk after a single prolonged milking interval in cows?

<p>Abstract</p> <p>Background</p> <p>A single prolonged milking interval (PMI) e.g. after a technical stop in an automated milking system is of concern for the producer since it is associated with a short-lasting increase in milk somatic cell count (SCC), which is a major quality criterion used at the dairy plants. The content of polymorphonuclear leukocytes (PMN) and how the milk quality is influenced has not been much investigated. The SCC peak occurs without any obvious antigen challenge, possibly indicating a different leukocyte attraction mechanism after a PMI than we see during mastitis.</p> <p>Methods</p> <p>Composite cow milk samples were taken at the milkings twice daily during 7 days before and 5 days after a PMI of 24 h. Milk was analyzed for SCC, PMN, fat, protein and lactose, and at some occasions also casein and free fatty acids (FFA).</p> <p>Results</p> <p>During the PMI the proportion of milk PMN increased sharply in spite of marginally increased SCC. The peak SCC was not observed until the second milking after the PMI, in the afternoon day 1. However, the peak SCC value in <it>morning </it>milk did not occur until one day later, concomitantly with a <it>decrease </it>in the proportion of PMN. After declining, SCC still remained elevated while PMN proportion was decreased throughout the study as was also the milk yield, after the first accumulation of milk during the PMI. Milk composition was changed the day after the PMI, (increased fat and protein content; decreased lactose, whey protein and FFA content) but the changes in the following days were not consistent except for lactose that remained decreased the rest of the study.</p> <p>Conclusion</p> <p>The PMI resulted in increased SCC and proportion of PMN. Additionally, it gave rise to minor alterations in the milk composition in the following milkings but no adverse effect on milk quality was observed. The recruitment of PMN, which was further enhanced the first day <it>after </it>the PMI, appeared to be independent of milk volume or accumulation of milk per se. Hence, we suggest that there is a special immunophysiological/chemoattractant background to the increased migration of leukocytes into the milk compartment observed during and after the PMI.</p

External validation suggests Integrin beta 3 as prognostic biomarker in serous ovarian adenocarcinomas

<p>Abstract</p> <p>Background</p> <p>The majority of women with ovarian cancer are diagnosed in late stages, and the mortality rate is high. The use of biomarkers as prognostic factors may improve the treatment and clinical outcome of these patients. We performed an external validation of the potential biomarkers CLU, ITGB3, CAPG, and PRAME to determine if the expression levels are relevant to use as prognostic factors.</p> <p>Methods</p> <p>We analysed the gene expression of CLU, ITGB3, CAPG, and PRAME in 30 advanced staged serous adenocarcinomas with quantitative real-time polymerase chain reaction (QPCR) and the protein levels were analysed in 98 serous adenocarcinomas with western blot for semiquantitative analysis. Statistical differences in mRNA and protein expressions between tumours from survivors and tumours from deceased patients were evaluated using the Mann-Whitney U test.</p> <p>Results</p> <p>The gene and protein ITGB3 (Integrin beta 3) were significantly more expressed in tumours from survivors compared to tumours from deceased patients, which is in concordance with our previous results. However, no significant differences were detected for the other three genes or proteins CLU, CAPG, and PRAME.</p> <p>Conclusion</p> <p>The loss of ITGB3 expression in tumours from deceased patients and high expression in tumours from survivors could be used as a biomarker for patients with advanced serous tumours.</p

Target Region Selection Is a Critical Determinant of Community Fingerprints Generated by 16S Pyrosequencing

Pyrosequencing of 16S rRNA genes allows for in-depth characterization of complex microbial communities. Although it is known that primer selection can influence the profile of a community generated by sequencing, the extent and severity of this bias on deep-sequencing methodologies is not well elucidated. We tested the hypothesis that the hypervariable region targeted for sequencing and primer degeneracy play important roles in influencing the composition of 16S pyrotag communities. Subgingival plaque from deep sites of current smokers with chronic periodontitis was analyzed using Sanger sequencing and pyrosequencing using 4 primer pairs. Greater numbers of species were detected by pyrosequencing than by Sanger sequencing. Rare taxa constituted nearly 6% of each pyrotag community and less than 1% of the Sanger sequencing community. However, the different target regions selected for pyrosequencing did not demonstrate a significant difference in the number of rare and abundant taxa detected. The genera Prevotella, Fusobacterium, Streptococcus, Granulicatella, Bacteroides, Porphyromonas and Treponema were abundant when the V1–V3 region was targeted, while Streptococcus, Treponema, Prevotella, Eubacterium, Porphyromonas, Campylobacer and Enterococcus predominated in the community generated by V4–V6 primers, and the most numerous genera in the V7–V9 community were Veillonella, Streptococcus, Eubacterium, Enterococcus, Treponema, Catonella and Selenomonas. Targeting the V4–V6 region failed to detect the genus Fusobacterium, while the taxa Selenomonas, TM7 and Mycoplasma were not detected by the V7–V9 primer pairs. The communities generated by degenerate and non-degenerate primers did not demonstrate significant differences. Averaging the community fingerprints generated by V1–V3 and V7–V9 primers providesd results similar to Sanger sequencing, while allowing a significantly greater depth of coverage than is possible with Sanger sequencing. It is therefore important to use primers targeted to these two regions of the 16S rRNA gene in all deep-sequencing efforts to obtain representational characterization of complex microbial communities

Temporal variability and effect of environmental variables on airborne bacterial communities in an urban area of Northern Italy

Despite airborne microorganisms representing a relevant fraction of atmospheric suspended particles, only a small amount of information is currently available on their abundance and diversity and very few studies have investigated the environmental factors influencing the structure of airborne bacterial communities. In this work, we used quantitative PCR and Illumina technology to provide a thorough description of airborne bacterial communities in the urban area of Milan (Italy). Forty samples were collected in 10-day sampling sessions, with one sessionper season.Themeanbacterialabundancewasabout104 ribosomal operons perm3 of air andwas lower inwinter than in the other seasons. Communitieswere dominated by Actinobacteridae, Clostridiales, Sphingobacteriales and fewproteobacterial orders (Burkholderiales, Rhizobiales, Sphingomonadales andPseudomonadales).Chloroplastswere abundant in all samples. Ahigher abundanceof Actinobacteridae,which are typical soil-inhabiting bacteria, and a lower abundance of chloroplasts in samples collected on cold days were observed. The variation in community composition observed within seasons was comparable to that observed between seasons, thus suggesting that airborne bacterial communities showlarge temporal variability, even between consecutive days. The structure of airborne bacterial communities therefore suggests that soil and plants are the sources which contribute most to the airborne communities of Milan atmosphere, but the structure of the bacterial community seems to depend mainly on the source of bacteria that predominates in a given period of time

Context, cognition and communication in language

Questions pertaining to the unique structure and organisation of language have a long history in the field of linguistics. In recent years, researchers have explored cultural evolutionary explanations, showing how language structure emerges from weak biases amplified over repeated patterns of learning and use. One outstanding issue in these frameworks is accounting for the role of context. In particular, many linguistic phenomena are said to to be context-dependent; interpretation does not take place in a void, and requires enrichment from the current state of the conversation, the physical situation, and common knowledge about the world. Modelling the relationship between language structure and context is therefore crucial for developing a cultural evolutionary approach to language. One approach is to use statistical analyses to investigate large-scale, cross-cultural datasets. However, due to the inherent limitations of statistical analyses, especially with regards to the inadequacy of these methods to test hypotheses about causal relationships, I argue that experiments are better suited to address questions pertaining to language structure and context. From here, I present a series of artificial language experiments, with the central aim being to test how manipulations to context influence the structure and organisation of language. Experiment 1 builds upon previous work in iterated learning and communication games through demonstrating that the emergence of optimal communication systems is contingent on the contexts in which languages are learned and used. The results show that language systems gradually evolve to only encode information that is informative for conveying the intended meaning of the speaker - resulting in markedly different systems of communication. Whereas Experiment 1 focused on how context influences the emergence of structure, Experiments 2 and 3 investigate under what circumstances do manipulations to context result in the loss of structure. While the results are inconclusive across these two experiments, there is tentative evidence that manipulations to context can disrupt structure, but only when interacting with other factors. Lastly, Experiment 4 investigates whether the degree of signal autonomy (the capacity for a signal to be interpreted without recourse to contextual information) is shaped by manipulations to contextual predictability: the extent to which a speaker can estimate and exploit contextual information a hearer uses in interpreting an utterance. When the context is predictable, speakers organise languages to be less autonomous (more context-dependent) through combining linguistic signals with contextual information to reduce effort in production and minimise uncertainty in comprehension. By decreasing contextual predictability, speakers increasingly rely on strategies that promote more autonomous signals, as these signals depend less on contextual information to discriminate between possible meanings. Overall, these experiments provide proof-of-concept for investigating the relationship between language structure and context, showing that the organisational principles underpinning language are the result of competing pressures from context, cognition, and communication