Use of multiphoton tomography and fluorescence lifetime imaging to investigate skin pigmentation in vivo

There is a growing body of literature showing the usefulness of multiphoton tomography (MPT) and fluorescence lifetime imaging for in situ characterization of skin constituents and the ensuing development of noninvasive diagnostic tools against skin diseases. Melanin and pigmentation-associated skin cancers constitute some of the major applications. We show that MPT and fluorescence lifetime imaging can be used to measure changes in cutaneous melanin concentration and that these can be related to the visible skin color. Melanin in the skin of African, Indian, Caucasian, and Asian volunteers is detected on the basis of its emission wavelength and fluorescence lifetimes in solution and in a melanocyte-keratinocyte cell culture. Fluorescence intensity is used to characterize the melanin content and distribution as a function of skin type and depth into the skin (stratum granulosum and stratum basale). The measured fluorescence intensities in given skin types agree with melanin amounts reported by others using biopsies. Our results suggest that spatial distribution of melanin in skin can be studied using MPT and fluorescence lifetime imaging, but further studies are needed to ascertain that the method can resolve melanin amount in smaller depth intervals

Exact Asymptotic Results for a Model of Sequence Alignment

Finding analytically the statistics of the longest common subsequence (LCS) of a pair of random sequences drawn from c alphabets is a challenging problem in computational evolutionary biology. We present exact asymptotic results for the distribution of the LCS in a simpler, yet nontrivial, variant of the original model called the Bernoulli matching (BM) model which reduces to the original model in the large c limit. We show that in the BM model, for all c, the distribution of the asymptotic length of the LCS, suitably scaled, is identical to the Tracy-Widom distribution of the largest eigenvalue of a random matrix whose entries are drawn from a Gaussian unitary ensemble. In particular, in the large c limit, this provides an exact expression for the asymptotic length distribution in the original LCS problem.Comment: 4 pages Revtex, 2 .eps figures include

Bethe Ansatz in the Bernoulli Matching Model of Random Sequence Alignment

For the Bernoulli Matching model of sequence alignment problem we apply the Bethe ansatz technique via an exact mapping to the 5--vertex model on a square lattice. Considering the terrace--like representation of the sequence alignment problem, we reproduce by the Bethe ansatz the results for the averaged length of the Longest Common Subsequence in Bernoulli approximation. In addition, we compute the average number of nucleation centers of the terraces.Comment: 14 pages, 5 figures (some points are clarified

Comparison of Spectra in Unsequenced Species

International audienceWe introduce a new algorithm for the mass spectromet- ric identication of proteins. Experimental spectra obtained by tandem MS/MS are directly compared to theoretical spectra generated from pro- teins of evolutionarily closely related organisms. This work is motivated by the need of a method that allows the identication of proteins of unsequenced species against a database containing proteins of related organisms. The idea is that matching spectra of unknown peptides to very similar MS/MS spectra generated from this database of annotated proteins can lead to annotate unknown proteins. This process is similar to ortholog annotation in protein sequence databases. The difficulty with such an approach is that two similar peptides, even with just one mod- ication (i.e. insertion, deletion or substitution of one or several amino acid(s)) between them, usually generate very dissimilar spectra. In this paper, we present a new dynamic programming based algorithm: Packet- SpectralAlignment. Our algorithm is tolerant to modications and fully exploits two important properties that are usually not considered: the notion of inner symmetry, a relation linking pairs of spectrum peaks, and the notion of packet inside each spectrum to keep related peaks together. Our algorithm, PacketSpectralAlignment is then compared to SpectralAlignment [1] on a dataset of simulated spectra. Our tests show that PacketSpectralAlignment behaves better, in terms of results and execution tim

Elucidating the role of Agl in bladder carcinogenesis by generation and characterization of genetically engineered mice

Amylo-\u3b1-1,6-glucosidase,4-\u3b1-glucanotransferase (AGL) is an enzyme primarily responsible for glycogen debranching. Germline mutations lead to glycogen storage disease type III (GSDIII). We recently found AGL to be a tumor suppressor in xenograft models of human bladder cancer (BC) and low levels of AGL expression in BC are associated with poor patient prognosis. However, the impact of low AGL expression on the susceptibility of normal bladder to carcinogenesis is unknown. We address this gap by developing a germline Agl knockout (Agl-/-) mouse that recapitulates biochemical and histological features of GSDIII. Agl-/- mice exposed to N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN) had a higher BC incidence compared with wild-type mice (Agl+/+). To determine if the increased BC incidence observed was due to decreased Agl expression in the urothelium specifically, we developed a urothelium-specific conditional Agl knockout (Aglcko) mouse using a Uroplakin II-Cre allele. BBN-induced carcinogenesis experiments repeated in Aglcko mice revealed that Aglcko mice had a higher BC incidence than control (Aglfl/fl) mice. RNA sequencing revealed that tumors from Agl-/- mice had 19 differentially expressed genes compared with control mice. An 'Agl Loss' gene signature was developed and found to successfully stratify normal and tumor samples in two BC patient datasets. These results support the role of AGL loss in promoting carcinogenesis and provide a rationale for evaluating Agl expression levels, or Agl Loss gene signature scores, in normal urothelium of populations at risk of BC development such as older male smokers

A high-throughput de novo sequencing approach for shotgun proteomics using high-resolution tandem mass spectrometry

<p>Abstract</p> <p>Background</p> <p>High-resolution tandem mass spectra can now be readily acquired with hybrid instruments, such as LTQ-Orbitrap and LTQ-FT, in high-throughput shotgun proteomics workflows. The improved spectral quality enables more accurate <it>de novo </it>sequencing for identification of post-translational modifications and amino acid polymorphisms.</p> <p>Results</p> <p>In this study, a new <it>de novo </it>sequencing algorithm, called Vonode, has been developed specifically for analysis of such high-resolution tandem mass spectra. To fully exploit the high mass accuracy of these spectra, a unique scoring system is proposed to evaluate sequence tags based primarily on mass accuracy information of fragment ions. Consensus sequence tags were inferred for 11,422 spectra with an average peptide length of 5.5 residues from a total of 40,297 input spectra acquired in a 24-hour proteomics measurement of <it>Rhodopseudomonas palustris</it>. The accuracy of inferred consensus sequence tags was 84%. According to our comparison, the performance of Vonode was shown to be superior to the PepNovo v2.0 algorithm, in terms of the number of <it>de novo </it>sequenced spectra and the sequencing accuracy.</p> <p>Conclusions</p> <p>Here, we improved <it>de novo </it>sequencing performance by developing a new algorithm specifically for high-resolution tandem mass spectral data. The Vonode algorithm is freely available for download at <url>http://compbio.ornl.gov/Vonode</url>.</p