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1.  Isolation, Identification and Characterization of Yeasts from Fermented Goat Milk of the Yaghnob Valley in Tajikistan 
The geographically isolated region of the Yaghnob Valley, Tajikistan, has allowed its inhabitants to maintain a unique culture and lifestyle. Their fermented goat milk constitutes one of the staple foods for the Yaghnob population, and is produced by backslopping, i.e., using the previous fermentation batch to inoculate the new one. This study addresses the yeast composition of the fermented milk, assessing genotypic, and phenotypic properties. The 52 isolates included in this study revealed small species diversity, belonging to Kluyveromyces marxianus, Pichia fermentans, Saccharomyces cerevisiae, and one Kazachstania unispora. The K. marxianus strains showed two different genotypes, one of which never described previously. The two genetically different groups also differed significantly in several phenotypic characteristics, such as tolerance toward high temperatures, low pH, and presence of acid. Microsatellite analysis of the S. cerevisiae strains from this study, compared to 350 previously described strains, attributed the Yaghnobi S. cerevisiae to two different ancestry origins, both distinct from the wine and beer strains, and similar to strains isolated from human and insects feces, suggesting a peculiar origin of these strains, and the existence of a gut reservoir for S. cerevisiae. Our work constitutes a foundation for strain selection for future applications as starter cultures in food fermentations. This work is the first ever on yeast diversity from fermented milk of the previously unexplored area of the Yaghnob Valley.
PMCID: PMC5093317  PMID: 27857705
yeast; fermented goat milk; Yaghnob Valley Tajikistan; identification; phenotyping; genotyping
2.  Age and Gender Affect the Composition of Fungal Population of the Human Gastrointestinal Tract 
The fungal component of the human gut microbiota has been neglected for long time due to the low relative abundance of fungi with respect to bacteria, and only recently few reports have explored its composition and dynamics in health or disease. The application of metagenomics methods to the full understanding of fungal communities is currently limited by the under representation of fungal DNA with respect to the bacterial one, as well as by the limited ability to discriminate passengers from colonizers. Here, we investigated the gut mycobiota of a cohort of healthy subjects in order to reduce the gap of knowledge concerning fungal intestinal communities in the healthy status further screening for phenotypical traits that could reflect fungi adaptation to the host. We studied the fecal fungal populations of 111 healthy subjects by means of cultivation on fungal selective media and by amplicon-based ITS1 metagenomics analysis on a subset of 57 individuals. We then characterized the isolated fungi for their tolerance to gastrointestinal (GI) tract-like challenges and their susceptibility to antifungals. A total of 34 different fungal species were isolated showing several phenotypic characteristics associated with intestinal environment such as tolerance to body temperature (37°C), to acidic and oxidative stress, and to bile salts exposure. We found a high frequency of azoles resistance in fungal isolates, with potential and significant clinical impact. Analyses of fungal communities revealed that the human gut mycobiota differs in function of individuals' life stage in a gender-related fashion. The combination of metagenomics and fungal cultivation allowed an in-depth understanding of the fungal intestinal community structure associated to the healthy status and the commensalism-related traits of isolated fungi. We further discussed comparatively the results of sequencing and cultivation to critically evaluate the application of metagenomics-based approaches to fungal gut populations.
PMCID: PMC4971113  PMID: 27536299
commensal fungi; human gut mycobiota; antifungal resistance; fungal metagenomics; fungi-host interactions
3.  Altered gut microbiota in Rett syndrome 
Microbiome  2016;4:41.
The human gut microbiota directly affects human health, and its alteration can lead to gastrointestinal abnormalities and inflammation. Rett syndrome (RTT), a progressive neurological disorder mainly caused by mutations in MeCP2 gene, is commonly associated with gastrointestinal dysfunctions and constipation, suggesting a link between RTT’s gastrointestinal abnormalities and the gut microbiota. The aim of this study was to evaluate the bacterial and fungal gut microbiota in a cohort of RTT subjects integrating clinical, metabolomics and metagenomics data to understand if changes in the gut microbiota of RTT subjects could be associated with gastrointestinal abnormalities and inflammatory status.
Our findings revealed the occurrence of an intestinal sub-inflammatory status in RTT subjects as measured by the elevated values of faecal calprotectin and erythrocyte sedimentation rate. We showed that, overall, RTT subjects harbour bacterial and fungal microbiota altered in terms of relative abundances from those of healthy controls, with a reduced microbial richness and dominated by microbial taxa belonging to Bifidobacterium, several Clostridia (among which Anaerostipes, Clostridium XIVa, Clostridium XIVb) as well as Erysipelotrichaceae, Actinomyces, Lactobacillus, Enterococcus, Eggerthella, Escherichia/Shigella and the fungal genus Candida.
We further observed that alterations of the gut microbiota do not depend on the constipation status of RTT subjects and that this dysbiotic microbiota produced altered short chain fatty acids profiles.
We demonstrated for the first time that RTT is associated with a dysbiosis of both the bacterial and fungal component of the gut microbiota, suggesting that impairments of MeCP2 functioning favour the establishment of a microbial community adapted to the costive gastrointestinal niche of RTT subjects. The altered production of short chain fatty acids associated with this microbiota might reinforce the constipation status of RTT subjects and contribute to RTT gastrointestinal physiopathology.
Electronic supplementary material
The online version of this article (doi:10.1186/s40168-016-0185-y) contains supplementary material, which is available to authorized users.
PMCID: PMC4967335  PMID: 27473171
Gut microbiota; Mycobiota; Rett syndrome; SCFAs; Metataxonomics; Intestinal dysbiosis; Constipation
4.  Dynamic changes in microbiota and mycobiota during spontaneous ‘Vino Santo Trentino’ fermentation 
Microbial Biotechnology  2016;9(2):195-208.
Vino Santo is a sweet wine produced from late harvesting and pressing of Nosiola grapes in a small, well‐defined geographical area in the Italian Alps. We used metagenomics to characterize the dynamics of microbial communities in the products of three wineries, resulting from spontaneous fermentation with almost the same timing and procedure. Comparing fermentation dynamics and grape microbial composition, we show a rapid increase in a small number of wine yeast species, with a parallel decrease in complexity. Despite the application of similar protocols, slight changes in the procedures led to significant differences in the microbiota in the three cases of fermentation: (i) fungal content of the must varied significantly in the different wineries, (ii) P ichia membranifaciens persisted in only one of the wineries, (iii) one fermentation was characterized by the balanced presence of S accharomyces cerevisiae and H anseniaspora osmophila during the later phases. We suggest the existence of a highly winery‐specific ‘microbial‐terroir’ contributing significantly to the final product rather than a regional ‘terroir’. Analysis of changes in abundance during fermentation showed evident correlations between different species, suggesting that fermentation is the result of a continuum of interaction between different species and physical–chemical parameters.
PMCID: PMC4767281  PMID: 26780037
5.  A computational pipeline to discover highly phylogenetically informative genes in sequenced genomes: application to Saccharomyces cerevisiae natural strains 
Nucleic Acids Research  2012;40(9):3834-3848.
The quest for genes representing genetic relationships of strains or individuals within populations and their evolutionary history is acquiring a novel dimension of complexity with the advancement of next-generation sequencing (NGS) technologies. In fact, sequencing an entire genome uncovers genetic variation in coding and non-coding regions and offers the possibility of studying Saccharomyces cerevisiae populations at the strain level. Nevertheless, the disadvantageous cost-benefit ratio (the amount of details disclosed by NGS against the time-expensive and expertise-demanding data assembly process) still precludes the application of these techniques to the routinely assignment of yeast strains, making the selection of the most reliable molecular markers greatly desirable. In this work we propose an original computational approach to discover genes that can be used as a descriptor of the population structure. We found 13 genes whose variability can be used to recapitulate the phylogeny obtained from genome-wide sequences. The same approach that we prove to be successful in yeasts can be generalized to any other population of individuals given the availability of high-quality genomic sequences and of a clear population structure to be targeted.
PMCID: PMC3351171  PMID: 22266652
6.  DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells 
Immunome Research  2010;6:10.
The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs).
Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DC-ATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules.
The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies.
PMCID: PMC3000836  PMID: 21092113

Results 1-6 (6)