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Nicola Vitulo

Publications and source records attributed to Nicola Vitulo.

5 recordsLinked to original sources

Piezophilic adaptation: a genomic point of view.

Two-thirds of Earth's surface is covered by oceans, yet the study of this massive integrated living system is still in its infancy. Various environmental variables, such as high salinity, low and changeable nutrient availability and depth-correlated gradients of light, temperature, nutrients and pressure shape the diversity, physiology and ecology of marine species. As oceans present an average depth of 3800 m, deep-sea ecosystems represent the most common marine ecological niche. One of the key environment variables that influences the life and evolution of deep-sea organisms is high pressure. This extreme widespread condition requires specific adaptations, the nature of which remains largely unknown. Recent advances in genomic approaches, such as in sequencing technologies and global expression profiling, are rapidly increasing the data available to understand microbial evolution, biochemistry, physiology and diversity. This review summarises the analysis of the results published so far about microbial high pressure adaptation from a genomic point of view. Understanding high pressure adaptation mechanisms is not just a scientific exercise but has important biotechnological implications. For example, hydrostatic pressure is a reality for food science and technology, both for food preparation and preservation. An understanding of the effects of pressure on biomolecules will expand its use in the medical, industrial and biotechnological fields.

Acclimatization↗

Laterally transferred elements and high pressure adaptation in Photobacterium profundum strains.

BACKGROUND: Oceans cover approximately 70% of the Earth's surface with an average depth of 3800 m and a pressure of 38 MPa, thus a large part of the biosphere is occupied by high pressure environments. Piezophilic (pressure-loving) organisms are adapted to deep-sea life and grow optimally at pressures higher than 0.1 MPa. To better understand high pressure adaptation from a genomic point of view three different Photobacterium profundum strains were compared. Using the sequenced piezophile P. profundum strain SS9 as a reference, microarray technology was used to identify the genomic regions missing in two other strains: a pressure adapted strain (named DSJ4) and a pressure-sensitive strain (named 3TCK). Finally, the transcriptome of SS9 grown under different pressure (28 MPa; 45 MPa) and temperature (4 degrees C; 16 degrees C) conditions was analyzed taking into consideration the differentially expressed genes belonging to the flexible gene pool. RESULTS: These studies indicated the presence of a large flexible gene pool in SS9 characterized by various horizontally acquired elements. This was verified by extensive analysis of GC content, codon usage and genomic signature of the SS9 genome. 171 open reading frames (ORFs) were found to be specifically absent or highly divergent in the piezosensitive strain, but present in the two piezophilic strains. Among these genes, six were found to also be up-regulated by high pressure. CONCLUSION: These data provide information on horizontal gene flow in the deep sea, provide additional details of P. profundum genome expression patterns and suggest genes which could perform critical functions for abyssal survival, including perhaps high pressure growth.

Atmospheric Pressure↗

MIDAW: a web tool for statistical analysis of microarray data.

MIDAW (microarray data analysis web tool) is a web interface integrating a series of statistical algorithms that can be used for processing and interpretation of microarray data. MIDAW consists of two main sections: data normalization and data analysis. In the normalization phase the simultaneous processing of several experiments with background correction, global and local mean and variance normalization are carried out. The data analysis section allows graphical display of expression data for descriptive purposes, estimation of missing values, reduction of data dimension, discriminant analysis and identification of marker genes. The statistical results are organized in dynamic web pages and tables, where the transcript/gene probes contained in a specific microarray platform can be linked (according to user choice) to external databases (GenBank, Entrez Gene, UniGene). Tutorial files help the user throughout the statistical analysis to ensure that the forms are filled out correctly. MIDAW has been developed using Perl and PHP and it uses R/Bioconductor languages and routines. MIDAW is GPL licensed and freely accessible at http://muscle.cribi.unipd.it/midaw/. Perl and PHP source codes are available from the authors upon request.

Algorithms↗

A leukemia-enriched cDNA microarray platform identifies new transcripts with relevance to the biology of pediatric acute lymphoblastic leukemia.

BACKGROUND AND OBJECTIVES: Microarray gene expression profiling has been widely applied to characterize hematologic malignancies, has attributed a molecular signature to leukemia subclasses and has allowed new subclasses to be distinguished. We set out to use microarray technology to identify novel genes relevant for leukemogenesis. To this end we used a unique leukemia-enriched cDNA microarray platform. DESIGN AND METHODS: The systematic sequencing of cDNA libraries of normal and leukemic bone marrow allowed us to increase the number of genes to yield a new release of a previously generated cDNA microarray. Using this platform we analyzed the expression profiles of 4,670 genes in bone marrow samples from 18 pediatric patients with acute lymphoblastic leukemia (ALL). RESULTS: Expression profiling consistently distinguished the leukemia patients into three groups, those with T-ALL, B-ALL and B-ALL with MLL/AF4 rearrangement, in agreement with the clinical classification. Our platform identified 30 genes that best discriminate these three subtypes. Using mini-array technology these 30 genes were validated in another cohort of 17 patients. In particular we identified two novel genes not previously reported: endomucin (EMCN) and ubiquitin specific protease 33 (USP33) that appear to be over-expressed in B-ALL relative to their expression in T-ALL. INTERPRETATION AND CONCLUSIONS: Microarray technology not only allows the distinction between disease subclasses but also offers a chance to identify new genes involved in leukemogenesis. Our approach of using a unique platform has proven to be fruitful in identifying new genes and we suggest exploration of other malignancies using this approach.

Adolescent↗

RAP: a new computer program for de novo identification of repeated sequences in whole genomes.

MOTIVATION: DNA repeats are a common feature of most genomic sequences. Their de novo identification is still difficult despite being a crucial step in genomic analysis and oligonucleotides design. Several efficient algorithms based on word counting are available, but too short words decrease specificity while long words decrease sensitivity, particularly in degenerated repeats. RESULTS: The Repeat Analysis Program (RAP) is based on a new word-counting algorithm optimized for high resolution repeat identification using gapped words. Many different overlapping gapped words can be counted at the same genomic position, thus producing a better signal than the single ungapped word. This results in better specificity both in terms of low-frequency detection, being able to identify sequences repeated only once, and highly divergent detection, producing a generally high score in most intron sequences. AVAILABILITY: The program is freely available for non-profit organizations, upon request to the authors. CONTACT: giorgio.valle@unipd.it SUPPLEMENTARY INFORMATION: The program has been tested on the Caenorhabditis elegans genome using word lengths of 12, 14 and 16 bases. The full analysis has been implemented in the UCSC Genome Browser and is accessible at http://genome.cribi.unipd.it.

Algorithms↗