Molecular characterization of the human gut microbiota: the effect of aging

Age-related physiological changes in the gastrointestinal tract, as well as modification in lifestyle, nutritional behaviour, and functionality of the host immune system, inevitably affect the gut microbiota. The study presented here is focused on the application and comparison of two different microarray approaches for the characterization of the human gut microbiota, the HITChip and the HTF-Microb.Array, with particular attention to the effects of the aging process on the composition of this ecosystem. By using the Human Intestinal Tract Chip (HITChip), recently developed at the Wageningen University, The Netherland, we explored the age-related changes of gut microbiota during the whole adult lifespan, from young adults, through elderly to centenarians. We observed that the microbial composition and diversity of the gut ecosystem of young adults and seventy-years old people is highly similar but differs significantly from that of the centenarians. After 100 years of symbiotic association with the human host, the microbiota is characterized by a rearrangement in the Firmicutes population and an enrichment of facultative anaerobes. The presence of such a compromised microbiota in the centenarians is associated with an increased inflammation status, also known as inflamm-aging, as determined by a range of peripheral blood inflammatory markers. In parallel, we overtook the development of our own phylogenetic microarray with a lower number of targets, aiming the description of the human gut microbiota structure at high taxonomic level. The resulting chip was called High Taxonomic level Fingerprinting Microbiota Array (HTF-Microb.Array), and was based on the Ligase Detection Reaction (LDR) technology, which allowed us to develop a fast and sensitive tool for the fingerprint of the human gut microbiota in terms of presence/absence of the principal groups. The validation on artificial DNA mixes, as well as the pilot study involving eight healthy young adults, demonstrated that the HTF-Microb.Array can be used to successfully characterize the human gut microbiota, allowing us to obtain results which are in approximate accordance with the most recent characterizations. Conversely, the evaluation of the relative abundance of the target groups on the bases of the relative fluorescence intensity probes response still has some hindrances, as demonstrated by comparing the HTF.Microb.Array and HITChip high taxonomic level fingerprints of the same centenarians.

Fingerprint Recognition: Enhancement, Feature Extraction and Automatic Evaluation of Algorithms

The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.