Untangling species-level composition of complex bacterial communities through a novel metagenomic approach

16S small-subunit (SSU) rRNA gene-based bacterial profiling is the gold standard for cost-effective taxonomic reconstruction of complex bacterial populations down to the genus level. However, it has been proven ineffective in clinical and research settings requiring higher taxonomic resolution. We therefore developed a bacterial profiling method based on the internal transcribed spacer (ITS) region employing optimized primers and a comprehensive ITS database for accurate cataloguing of bacterial communities at (sub)species resolution. Performance of the microbial ITS profiling pipeline was tested through analysis of host-associated, food, and environmental matrices, while its efficacy in clinical settings was assessed through analysis of mucosal biopsy specimens of colorectal cancer, leading to the identification of putative novel biomarkers. The data collected indicate that the proposed pipeline represents a major step forward in cost-effective identification and screening of microbial biomarkers at (sub)species level, with relevant impact in research, industrial, and clinical settings. IMPORTANCE We developed a novel method for accurate cataloguing of bacterial communities at (sub)species level involving amplification of the internal transcribed spacer (ITS) region through optimized primers, followed by next-generation sequencing and taxonomic classification of amplicons by means of a comprehensive database of bacterial ITS sequences. Host-associated, food, and environmental matrices were employed to test the performance of the microbial ITS profiling pipeline. Moreover, mucosal biopsy samples from colorectal cancer patients were analyzed to demonstrate the scientific relevance of this profiling approach in a clinical setting through identification of putative novel biomarkers. The results indicate that the ITS-based profiling pipeline proposed here represents a key metagenomic tool with major relevance for research, industrial, and clinical settings

Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test

This paper proposes a new procedure to construct test statistics for hypothesis testing by computer vision and metrics learning. The application highlighted in this paper is applying computer vision on Q-Q plot to construct a new test statistic for normality test. Traditionally, there are two families of approaches for verifying the probability distribution of a random variable. Researchers either subjectively assess the Q-Q plot or objectively use a mathematical formula, such as Kolmogorov-Smirnov test, to formally conduct a normality test. Graphical assessment by human beings is not rigorous whereas normality test statistics may not be accurate enough when the uniformly most powerful test does not exist. It may take tens of years for statistician to develop a new and more powerful test statistic. The first step of the proposed method is to apply computer vision techniques, such as pre-trained ResNet, to convert a Q-Q plot into a numerical vector. Next step is to apply metric learning to find an appropriate distance function between a Q-Q plot and the centroid of all Q-Q plots under the null hypothesis, which assumes the target variable is normally distributed. This distance metric is the new test statistic for normality test. Our experimentation results show that the machine-learning-based test statistics can outperform traditional normality tests in all cases, particularly when the sample size is small. This study provides convincing evidence that the proposed method could objectively create a powerful test statistic based on Q-Q plots and this method could be modified to construct many more powerful test statistics for other applications in the future

Role of sortase-dependent pili of Bifidobacterium bifidum PRL2010 in modulating bacterium-host interactions

Bifidobacteria represent one of the dominant groups of microorganisms colonizing the human infant intestine. Commensal bacteria that interact with a eukaryotic host are believed to express adhesive molecules on their cell surface that bind to specific host cell receptors or soluble macromolecules. Whole-genome transcription profiling of Bifidobacterium bifidum PRL2010, a strain isolated from infant stool, revealed a small number of commonly expressed extracellular proteins, among which were genes that specify sortase-dependent pili. Expression of the coding sequences of these B. bifidum PRL2010 appendages in nonpiliated Lactococcus lactis enhanced adherence to human enterocytes through extracellular matrix protein and bacterial aggregation. Furthermore, such piliated L. lactis cells evoked a higher TNF-α response during murine colonization compared with their nonpiliated parent, suggesting that bifidobacterial sortase-dependent pili not only contribute to adherence but also display immunomodulatory activity

Bifidobacteria exhibit social behavior through carbohydrate resource sharing in the gut

Bifidobacteria are common and frequently dominant members of the gut microbiota of many animals, including mammals and insects. Carbohydrates are considered key carbon sources for the gut microbiota, imposing strong selective pressure on the complex microbial consortium of the gut. Despite its importance, the genetic traits that facilitate carbohydrate utilization by gut microbiota members are still poorly characterized. Here, genome analyses of 47 representative Bifidobacterium (sub)species revealed the genes predicted to be required for the degradation and internalization of a wide range of carbohydrates, outnumbering those found in many other gut microbiota members. The glycan-degrading abilities of bifidobacteria are believed to reflect available carbon sources in the mammalian gut. Furthermore, transcriptome profiling of bifidobacterial genomes supported the involvement of various chromosomal loci in glycan metabolism. The widespread occurrence of bifidobacterial saccharolytic features is in line with metagenomic and metatranscriptomic datasets obtained from human adult/infant faecal samples, thereby supporting the notion that bifidobacteria expand the human glycobiome. This study also underscores the hypothesis of saccharidic resource sharing among bifidobacteria through species-specific metabolic specialization and cross feeding, thereby forging trophic relationships between members of the gut microbiota

Role of sortase-dependent pili of Bifidobacterium bifidum PRL2010 in modulating bacterium-host interactions

Bifidobacteria represent one of the dominant groups of microorganisms colonizing the human infant intestine. Commensal bacteria that interact with a eukaryotic host are believed to express adhesive molecules on their cell surface that bind to specific host cell receptors or soluble macromolecules. Whole-genome transcription profiling of Bifidobacterium bifidum PRL2010, a strain isolated from infant stool, revealed a small number of commonly expressed extracellular proteins, among which were genes that specify sortase-dependent pili. Expression of the coding sequences of these B. bifidum PRL2010 appendages in nonpiliated Lactococcus lactis enhanced adherence to human enterocytes through extracellular matrix protein and bacterial aggregation. Furthermore, such piliated L. lactis cells evoked a higher TNF-\u3b1 response during murine colonization compared with their nonpiliated parent, suggesting that bifidobacterial sortase-dependent pili not only contribute to adherence but also display immunomodulatory activity

Automatic leak detection in water distribution networks

A large percentage of water is lost in many water distribution systems in transit from the treatment plant to the consumer. Available statistics show that the amount of real (physical) water losses may exceed 30% of the input volume (EPA, 2010). Several techniques and equipment for pinpointing leaks are available. Acoustic devices are the principal type of equipment used to locate leaks in distribution systems (Hunaidi et al., 2006, Hunaidi et al., 2000, Gao et al., 2005, Khulief et al., 2012). This work investigates the use of vibration monitoring tools and acoustic measurements for the detection of burst leaks in water pipelines. The long-term project, planned by the R&D department of the multi-utility Hera S.p.A. (Bologna, Italy), aims at developing a device for automatically detecting bursts located in the customer connection branches running from the mains to the user\u2019s water meter. The system should permit early detection of water leaks and, together with a DMA software management and the system for automatic meter reading (AMR), is expected to improve the efficiency of the water distribution system

Expression of sortase-dependent pili of Bifidobacterium bifidum PRL2010 in response to environmental gut conditions

Cell surface pili have recently been found in many different bifidobacterial species, including the infant gut commensal Bifidobacterium bifidum PRL2010. Pili produced by PRL2010 have been shown to be important molecular mediators for bacterial interaction with its human host. However, nothing is known about the modulation of their expression in response to cues that reflect the gastro intestinal environment, such as thermal, acidic, and osmotic challenges, or the presence of other gut microorganisms. Here, we investigated how different stress conditions that simulate the gastrointestinal niche influence the expression of PRL2010 sortase-dependent pili, and how this may impact on the coexistence and interaction with other human gut commensals

The human gut microbiota and its interactive connections to diet

The microbiota of the gastrointestinal tract plays an important role in human health. In addition to their metabolic interactions with dietary constituents, gut bacteria may also be involved in more complex host interactions, such as modulation of the immune system. Furthermore, the composition of the gut microbiota may be important in reducing the risk of contracting particular gut infections. Changes in the microbiota during an individual's lifespan are accompanied by modifications in multiple health parameters, and such observations have prompted intense scientific efforts aiming to understand the complex interactions between the microbiota and its human host, as well as how this may be influenced by diet