The so-called tRNAGlu1 of Escherichia coli is a stable denatured conformer of the major isoacceptor tRNAGlu2

A single peak of tRNAGlu is obtained upon chromatography of unfractionated tRNA from Escherichia coli on DEAE-Sephadex A-50 if this tRNA was previously renatured, whereas two peaks of tRNAGlu are resolved if the sample chromatographed is a mixture of native (renatured) and denatured tRNA. Higher resolution analysis of native E. coli tRNA by RPC-5 chromatography showed that most of the tRNAGlu is present in one peak, eluted shortly after a minor peak containing about or less than 5% of the total amount of tRNAGlu; these two peaks were also observed with commercially available tRNAGlu purified from E. coli. When denatured, the tRNAGlu present in each of these two peaks was eluted from the RPC-5 column at a much lower salt concentration. The properties of the denatured conformers obtained from native tRNAGlu present in the major and minor peaks, and the variation, with growth conditions of E. coli, in the relative amount of tRNAGlu in the minor peak suggest that the tRNAGlu present in the minor peak is an undermodified form of the tRNAGlu present in the major peak. This tRNAGluUUC (or tRNAGluSUC when modified in the anticodon) would then be the only tRNA species acceptor of glutamate in E. coli.     

Annotated regions of significance of SELDI-TOF-MS spectra for detecting protein biomarkers

Peak detection is a key step in the analysis of SELDI-TOF-MS spectra, but the current default method has low specificity and poor peak annotation. To improve data quality, scientists still have to validate the identified peaks visually, a tedious and time-consuming process, especially for large data sets. Hence, there is a genuine need for methods that minimize manual validation. We have previously reported a multi-spectral signal detection method, called RS for 'region of significance', with improved specificity. Here we extend it to include a peak quantification algorithm based on annotated regions of significance (ARS). For each spectral region flagged as significant by RS, we first identify a dominant spectrum for determining the number of peaks and the m/z region of these peaks. From each m/z region of peaks, a peak template is extracted from all spectra via the principal component analysis. Finally, with the template, we estimate the amplitude and location of the peak in each spectrum with the least-squares method and refine the estimation of the amplitude via the mixture model.We have evaluated the ARS algorithm on patient samples from a clinical study. Comparison with the standard method shows that ARS (i) inherits the superior specificity of RS, and (ii) gives more accurate peak annotations than the standard method. In conclusion, we find that ARS alleviates the main problems in the preprocessing of SELDI-TOF spectra. The R-package ProSpect that implements ARS is freely available for academic use at http://www.meb.ki.se/ yudpaw.     

A low-cost chromatograph data-collection system

A data collection system has been constructed, based on the low-cost BBC microcomputer, which provides for the digitization and storage of the data from one or more g.l.c. or h.p.l.c. instruments, or from other data sources with similar data rates. The data can be observed during collection on the graphics screen, and are then stored on disk for subsequent processing. This processing is designed to be interactive, so that the operator can influence decisions about base-line drifts, peak separations, etc. when integrating the peaks, and can decide which peaks are to be stored in a time/intensity record, on the basis of a visual display of the trace. A low cost multi-channel precision ADC, using isolated voltage-to-frequency transducers sited at the sources of data, and multiple counters at the computer, may be used to measure several signals simultaneously even when they originate at some distance from the computer, and extra memory can also be added to the BBC microcomputer to allow temporary storage of data. The software is written in machine code (for the data collection) and BASIC (for the analysis routines) so that modifications to the latter routines can be made easily. The user interface is suitable for routine users who have no computing experience.     

Low cost multi user multi platform accessible HPLC data acquisition system

Summary A low cost multi user multi platform accessible HPLC data acquisition system has been designed for use in a laboratory environment. This system uses available HPLC measurement systems that lack modern network communication tools and a low cost computer with reliable software. HPLC data are portable to any other computer by means of File Transport Protocol (FTP) communication and can then be used for data analysis. Off line analysis of ethanol data showed a substantial improvement over the old system in terms of data accuracy and skewness. Furthermore, off line data analysis could resolve hidden acetaldehyde peaks which revealed to be oscillatory.     

A novel peak detection approach with chemical noise removal using short‐time FFT for prOTOF MS data

Peak detection is a pivotal first step in biomarker discovery from MS data and can significantly influence the results of downstream data analysis steps. We developed a novel automatic peak detection method for prOTOF MS data, which does not require a priori knowledge of protein masses. Random noise is removed by an undecimated wavelet transform and chemical noise is attenuated by an adaptive short‐time discrete Fourier transform. Isotopic peaks corresponding to a single protein are combined by extracting an envelope over them. Depending on the S/N, the desired peaks in each individual spectrum are detected and those with the highest intensity among their peak clusters are recorded. The common peaks among all the spectra are identified by choosing an appropriate cut‐off threshold in the complete linkage hierarchical clustering. To remove the 1 Da shifting of the peaks, the peak corresponding to the same protein is determined as the detected peak with the largest number among its neighborhood. We validated this method using a data set of serial peptide and protein calibration standards. Compared with MoverZ program, our new method detects more peaks and significantly enhances S/N of the peak after the chemical noise removal. We then successfully applied this method to a data set from prOTOF MS spectra of albumin and albumin‐bound proteins from serum samples of 59 patients with carotid artery disease compared to vascular disease‐free patients to detect peaks with S/N≥2. Our method is easily implemented and is highly effective to define peaks that will be used for disease classification or to highlight potential biomarkers.     

Evidence for discrete cell kinetic subpopulations in mouse epidermis based on mathematical analysis

Abstract. Continuous (repeated) labelling studies in mouse epidermis indicate that nearly all cells are labelled after about 100 hr. Percentage labelled mitoses studies ([³H]TdR at 15.00 and 03.00 hours) have a first peak that does not reach 100% and has a half-width of about 10 hr. Small second and third peaks can be detected at about 90 and 180 hr, respectively. The changes with time in the number of labelled cells show a difference dependent on the time of day of [³H]TdR administration. Both curves show an early doubling in labelled cells which then decline, forming a peak of labelled cells. A second peak occurs at about 120 hr. This is followed by a progressive decline with no further peaks until values of about 1% labelling are obtained at 340 hr.
These experiments have been investigated mathematically. A computer programme has been devized that permits all three types of experiments to be analysed simultaneously. More importantly, it can analyse situations with a heterogeneity in cell cycle parameters in all proliferative subpopulations.
Various models for epidermal cell replacement have been considered. The data as a whole can best be explained if the basal layer contains at least two distinct subpopulations of cells and an exponentially decaying post-mitotic population with a half-life of about 30 hr. The proliferative sub-populations must be characterized by near integer differences in the length of cycle, the precursor (stem) compartment having the longer cycle. An inverse relationship is required for the length of S, i.e. the shortest time for the stem cells.
A full range of cell kinetic parameters can be calculated and are tabulated for the most appropriate model system which is one involving three transit proliferating subpopulations.     

Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping

Peak lists derived from nuclear magnetic resonance (NMR) spectra are commonly used as input data for a variety of computer assisted and automated analyses. These include automated protein resonance assignment and protein structure calculation software tools. Prior to these analyses, peak lists must be aligned to each other and sets of related peaks must be grouped based on common chemical shift dimensions. Even when programs can perform peak grouping, they require the user to provide uniform match tolerances or use default values. However, peak grouping is further complicated by multiple sources of variance in peak position limiting the effectiveness of grouping methods that utilize uniform match tolerances. In addition, no method currently exists for deriving peak positional variances from single peak lists for grouping peaks into spin systems, i.e. spin system grouping within a single peak list. Therefore, we developed a complementary pair of peak list registration analysis and spin system grouping algorithms designed to overcome these limitations. We have implemented these algorithms into an approach that can identify multiple dimension-specific positional variances that exist in a single peak list and group peaks from a single peak list into spin systems. The resulting software tools generate a variety of useful statistics on both a single peak list and pairwise peak list alignment, especially for quality assessment of peak list datasets. We used a range of low and high quality experimental solution NMR and solid-state NMR peak lists to assess performance of our registration analysis and grouping algorithms. Analyses show that an algorithm using a single iteration and uniform match tolerances approach is only able to recover from 50 to 80% of the spin systems due to the presence of multiple sources of variance. Our algorithm recovers additional spin systems by reevaluating match tolerances in multiple iterations. To facilitate evaluation of the algorithms, we developed a peak list simulator within our nmrstarlib package that generates user-defined assigned peak lists from a given BMRB entry or database of entries. In addition, over 100,000 simulated peak lists with one or two sources of variance were generated to evaluate the performance and robustness of these new registration analysis and peak grouping algorithms.     

Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into -values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx.     

Enthalpy distribution for the alpha-helix/random coil transition in a model peptide: a study of two-state behavior.

We use heat capacity data of Taylor et al. to calculate the enthalpy distribution of a model peptide using the moments/maximum-entropy method. The peptide was designed with small covalent loops at both ends of the molecule to nucleate alpha-helix thus giving a system that would be expected to show a helix-coil transition that is very close to being two state. If we subtract a background contribution from the heat capacity data, then the enthalpy distribution we obtain shows two distinct peaks representing helix and coil. The difference in the peak enthalpy values agrees closely with the DeltaH obtained from the two-state analysis. On the other hand, if we use the complete heat capacity without subtracting background we then obtain an enthalpy distribution that has only a single peak at all temperatures. We show that this result can be consistent with the existence of two states, helix and coil, but only if the range of variation of the enthalpy of each species is so large as to make the notion of a species fairly meaningless.     

CAMRA: Chemical shift based computer aided protein NMR assignments

A suite of programs called CAMRA (Computer Aided Magnetic Resonance Assignment) has been developed for computer assisted residue-specific assignments of proteins. CAMRA consists of three units: ORB, CAPTURE and PROCESS. ORB predicts NMR chemical shifts for unassigned proteins using a chemical shift database of previously assigned homologous proteins supplemented by a statistically derived chemical shift database in which the shifts are categorized according to their residue, atom and secondary structure type. CAPTURE generates a list of valid peaks from NMR spectra by filtering out noise peaks and other artifacts and then separating the derived peak list into distinct spin systems. PROCESS combines the chemical shift predictions from ORB with the spin systems identified by CAPTURE to obtain residue specific assignments. PROCESS ranks the top choices for an assignment along with scores and confidence values. In contrast to other auto-assignment programs, CAMRA does not use any connectivity information but instead is based solely on matching predicted shifts with observed spin systems. As such, CAMRA represents a new and unique approach for the assignment of protein NMR spectra. CAMRA will be particularly useful in conjunction with other assignment methods and under special circumstances, such as the assignment of flexible regions in proteins where sufficient NOE information is generally not available. CAMRA was tested on two medium-sized proteins belonging to the chemokine family. It was found to be effective in predicting the assignment providing a database of previously assigned proteins with at least 30% sequence identity is available. CAMRA is versatile and can be used to include and evaluate heteronuclear and three-dimensional experiments.     

Difference and consensus of whole cell Salmonella enterica subsp. enterica serovars matrix-assisted laser desorption/ionization time-of-flight mass spectrometry spectra

AIM: Application of MALDI-TOF MS for characterization of strains of Salmonella enterica subsp. enterica. METHODS AND RESULTS: Whole cells were analysed by MALDI-TOF MS. Spectra with a maximum of 500 mass peaks between (m/z) 0 and 25000 were examined for consensus peaks manually and by a computer software algorithm. Consensus peaks were observed by both methods for spectra of Salmonella enterica serovars Derby, Hadar, Virchow, Anatum, Typhimurium and Enteritidis. CONCLUSIONS: Differences in numbers of consensus peaks in spectra obtained by manual and computer comparison indicated that development of the software involving statistical analysis of peak accuracy is necessary. SIGNIFICANCE AND IMPACT OF THE STUDY: Development of an analysis system for peak profiles in whole cell MALDI-TOF MS spectra to enable intra and interlaboratory comparison.     

Searching for biological rhythms: peak detection in the periodogram of unequally spaced data

The classical power spectrum, computed in the frequency domain, outranks traditionally used periodograms derived in the time domain (such as the chi2 periodogram) regarding the search for biological rhythms. Unfortunately, classical power spectral analysis is not possible with unequally spaced data (e.g., time series with missing data). The Lomb-Scargle periodogram fixes this shortcoming. However, peak detection in the Lomb-Scargle periodogram of unequally spaced data requires some careful consideration. To guide researchers in the proper evaluation of detected peaks, therefore, a novel procedure and a computer program have recently become available. It is recommended that the Lomb-Scargle periodogram be the default method of periodogram analysis in future biomedical applications of rhythm investigation.     

MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis

Shotgun proteomics experiments are dependent upon database search engines to identify peptides from tandem mass spectra. Many of these algorithms score potential identifications by evaluating the number of fragment ions matched between each peptide sequence and an observed spectrum. These systems, however, generally do not distinguish between matching an intense peak and matching a minor peak. We have developed a statistical model to score peptide matches that is based upon the multivariate hypergeometric distribution. This scorer, part of the "MyriMatch" database search engine, places greater emphasis on matching intense peaks. The probability that the best match for each spectrum has occurred by random chance can be employed to separate correct matches from random ones. We evaluated this software on data sets from three different laboratories employing three different ion trap instruments. Employing a novel system for testing discrimination, we demonstrate that stratifying peaks into multiple intensity classes improves the discrimination of scoring. We compare MyriMatch results to those of Sequest and X!Tandem, revealing that it is capable of higher discrimination than either of these algorithms. When minimal peak filtering is employed, performance plummets for a scoring model that does not stratify matched peaks by intensity. On the other hand, we find that MyriMatch discrimination improves as more peaks are retained in each spectrum. MyriMatch also scales well to tandem mass spectra from high-resolution mass analyzers. These findings may indicate limitations for existing database search scorers that count matched peaks without differentiating them by intensity. This software and source code is available under Mozilla Public License at this URL: http://www.mc.vanderbilt.edu/msrc/bioinformatics/.     

Chromosome analysis and sorting in <Emphasis Type="Italic">Vicia sativa</Emphasis> using flow cytometry

Procedures were developed for flow cytometric analysis and sorting of mitotic chromosomes (flow cytogenetics) of common vetch (Vicia sativa L., 2n=12). Suspensions of intact chromosomes were prepared from root tips after cell cycle synchronization, formaldehyde fixation, and mechanical homogenization. On average, 3 × 10⁵ morphologically intact chromosomes could be isolated from 25 root tips. Flow cytometric analysis of DAPI-stained chromosomes resulted in histograms of relative fluorescence intensity (flow karyotypes) containing four peaks, representing particular chromosomes and/or pairs of chromosomes with similar relative DNA content. Peaks I and II were assigned to chromosomes 6 and 5, respectively. These chromosomes could be sorted with a purity exceeding 90 %. The two remaining peaks on the flow karyotype were composite, each of them representing a pair of chromosomes. Chromosomes 1 and 3 were assigned to composite peak III while chromosomes 2 and 4 were assigned to composite peak IV. The chromosomes could be sorted with a purity of 99 % from both composite peaks. Bivariate flow karyotyping after simultaneous staining of chromosomes with DAPI and mithramycin was not found helpful in discriminating additional chromosomes. This study extends the number of legume species for which flow cytogenetics is available and provides a new tool for targeted and effective analysis and mapping of common vetch genome.     

A model for thermograms

Thermograms are curves resulting from thermal analysis and are of great interest in the study of various food and biological products physical properties. A method to separate underlying peaks is proposed, and statistical properties of estimates for some characteristic parameters are derived. The total number of peaks can be estimated with a sequential analysis of the residual plots. For each new peak, a statistical criterion is proposed to check whether it is significantly different from the noise of the recording. As an example, the method is applied to a summer milk fat fusion thermogram.     

Background and peak evaluation of one parameter flow karyotypes on a PC/AT computer

Flow cytometry has become a fast, quantitative method for the classification of metaphase chromosomes in suspension (flow karyotyping) stained with fluorescent dyes. Such a flow karyotype (frequency distribution of the fluorescence signals) consists of several peaks. The peak pattern characterizes the analyzed chromosome complement. In many cases flow karyotypes contain a continuum of an unspecific background deriving from chromosome fragments or chromosome aggregates. For the quantitative evaluation of a flow karyotype this background has to be subtracted by a suitable background function. In this approach the application of chi 2-functions is described. The feasibility of this method to flow karyotypes has been concluded from a computer simulation of chromosome breaking under different conditions. In spite of the rather rough assumptions of the model compared to the complex reasons that influence chromosome breaking, the chi 2-function fits the background better than the exponential function in current use. The approximation of a Gaussian distribution function by the chi 2-function also makes it possible to use the same subtraction procedure for chromosome aggregates. The procedure was tested for isolated chromosomes of Chinese hamster cell lines under different states of breaking. For further evaluation of one parameter flow karyotypes a setup of computer routines has been developed for PC/AT and compatible computer systems. Different peak values of these flow karyotypes can be determined (e.g. peak mean, standard deviation, absolute and relative peak area etc.). The applied method is to fit Gaussian curves to each peak of an experimentally measured histogram by using an interactive program. Fluctuations depending on 'noise' may be suppressed by a 'k-nearest-neighbours' smoothing procedure.