Automatic analysis of the spectra of extracellular proteins based on their autocorrelation characteristics

Hardware and software for the automatic comparison of densitograms, based on the evaluation of their autocorrelation characteristics, can be used for establishing the characteristics of circulating staphylococcal populations and for their epidemiological marking.     

Cluster analysis of protein fourier transform infrared spectra

Cluster analysis techniques were used to examine a set of Fourier transform infrared (FT-IR) spectra of bovine serum albumin (BSA) in the adsorbed and nonadsorbed states. The region from 1480 to 1600 cm^?1, comprising the amide II band, was used. Spectra were preprocessed to compensate for linear baseline variation, and the single linkage method of cluster analysis was applied. As expected, the spectra of adsorbed and nonadsorbed BSA fell into two distinct clusters. However, no further clustering was observed among the adsorbed BSA spectra on the basis of surface type, suggesting that surface specificity of the spectral changes induced in BSA by adsorption is not detectable above experimental variation. This work illustrates the value of using cluster analysis in the FT-IR study of proteins as a complement to other data analysis methods.     

Classification ofChlorella strains by infrared absorption spectra of cell samples

The infrared absorption spectra of 29Chlorella strains were recorded over the range from 1,800 to 700 cm⁻¹. Temperature and light intensity upon algal culture gave no significant effect on the spectrum of late log phase cells. The spectra of cells grown in glucose media were different from those of cells grown autotrophically. It was possible to identify 5 groups of strains by comparison of the relative intensities of absorption bands ascribed to nucleic acid, protein, carbohydrate and others, and cell sizes. These groups corresponded well with the current classification ofChlorella.     

Molecular analysis of complex human cell populations: mutational spectra of MNNG and ICR-191

We describe a method to identify and enumerate mutants at the nucleotide level in complex cell populations. Several thousand different mutants were induced at the HPRT locus in human lymphoblastoid cultures by either MNNG, an alkylating agent, or by ICR-191, a substituted acridine. HPRT mutants were selected en masse by resistance to 6-thioguanine. The most frequent mutations (hotspots) in HPRT exon 3 were determined by a combination of denaturing gradient gel electrophoresis and polymerase chain reaction. MNNG predominantly produced GC----AT transitions at nucleotides in a GGGGGG sequence, while ICR-191 produced both +1 frameshifts in the same GGGGGG sequence and +1 frameshifts in a CCC sequence.     

Microarray analysis of ageing-related signatures and their expression in tumors based on a computational biology approach

Ageing and cancer have been associated with genetic and genomic changes.The identification of common signatures between ageing and cancer can reveal shared molecular mechanisms underlying them.In this study,we collected ageing-related gene signatures from ten published studies involved in six different human tissues and an online resource.We found that most of these gene signatures were tissuespecific and a few were related to multiple tissues.We performed a genome-wide examination of the expression of these signatures in various human tumor types,and found that a large proportion of these signatures were universally differentially expressed among normal vs.tumor phenotypes.Functional analyses of the highly-overlapping genes between ageing and cancer using DAVID tools have identified important functional categories and pathways linking ageing with cancer.The convergent and divergent mechanisms between ageing and cancer are discussed.This study provides insights into the biology of ageing and cancer,suggesting the possibility of potential interventions aimed at postponing ageing and preventing cancer.     

Calculation and use of protein-derived conformation-related spectra for the estimate of the secondary structure of proteins from their infrared spectra

This paper probes the calculation of conformation-related basis spectra from infrared spectra (amide I′band) of reference proteins of known conformational composition and, with their aid, the computation of conformations from the amide I′ band of globular proteins using in both approaches a least-squares, curve-fitting computer program for the analysis of the spectra. The following results were obtained. The infrared basis spectra for the α-helix conformation, the β-(antiparallel-chain pleated sheet) conformation and the ρ-conformation were calculated and their physical reality was substantiated. The basis spectra were shown to be similar when the absorption contributions of the side chains of amino acids were either neglected or taken into account (uncorrected or corrected basis spectra). The mutual correlation of the basis spectra, quantified by the roots of the diagonal elements of the inverse matrix, was found to be low enough only for the β-conformation to allow a statistically reliable estimate of the β-conformation content of proteins. The comparison of the percentages of the β-conformation derived from x-ray structural analysis or calculated from infrared spectra showed the suitability of the basis spectra for the rough estimate of the β-conformation percentages of proteins. The results were not significantly different when using the uncorrected or corrected basis spectra.     

Computer-aided analysis of infrared, circular dichroism and absorption spectra

Marquardt and Powell optimization methods without constraintson the optimized spectral parameters were employed for decompositionof complex i.r., c.d. and absorption spectra into componentbands. The procedure resolved experimental spectra into eightcomponent bands and it can be easily adjusted for a larger setof component bands. The CPU time required for achievement ofsatisfactory convergence of parameters for eight component bandsis rather large even when using mainframe computers and thereforedivision of spectra into a few non-overlapped parts is advisable.The program also can be used for calculation of absorption,c.d. and difference spectra from formatted raw spectral data. Received on January 13, 1986; accepted on April 7, 1986     

Neural network analyses of infrared spectra for classifying cell wall architectures

About 10% of plant genomes are devoted to cell wall biogenesis. Our goal is to establish methodologies that identify and classify cell wall phenotypes of mutants on a genome-wide scale. Toward this goal, we have used a model system, the elongating maize (Zea mays) coleoptile system, in which cell wall changes are well characterized, to develop a paradigm for classification of a comprehensive range of cell wall architectures altered during development, by environmental perturbation, or by mutation. Dynamic changes in cell walls of etiolated maize coleoptiles, sampled at one-half-d intervals of growth, were analyzed by chemical and enzymatic assays and Fourier transform infrared spectroscopy. The primary walls of grasses are composed of cellulose microfibrils, glucuronoarabinoxylans, and mixed-linkage (1 --> 3),(1 --> 4)-beta-D-glucans, together with smaller amounts of glucomannans, xyloglucans, pectins, and a network of polyphenolic substances. During coleoptile development, changes in cell wall composition included a transient appearance of the (1 --> 3),(1 --> 4)-beta-D-glucans, a gradual loss of arabinose from glucuronoarabinoxylans, and an increase in the relative proportion of cellulose. Infrared spectra reflected these dynamic changes in composition. Although infrared spectra of walls from embryonic, elongating, and senescent coleoptiles were broadly discriminated from each other by exploratory principal components analysis, neural network algorithms (both genetic and Kohonen) could correctly classify infrared spectra from cell walls harvested from individuals differing at one-half-d interval of growth. We tested the predictive capabilities of the model with a maize inbred line, Wisconsin 22, and found it to be accurate in classifying cell walls representing developmental stage. The ability of artificial neural networks to classify infrared spectra from cell walls provides a means to identify many possible classes of cell wall phenotypes. This classification can be broadened to phenotypes resulting from mutations in genes encoding proteins for which a function is yet to be described.     

Supervised learning methods for the recognition of melanoma cell lines through the analysis of their Raman spectra

Malignant melanoma is an aggressive form of skin cancer, which develops from the genetic mutations of melanocytes – the most frequent involving BRAF and NRAS genes. The choice and the effectiveness of the therapeutic approach depend on tumour mutation; therefore, its assessment is of paramount importance. Current methods for mutation analysis are destructive and take a long time; instead, Raman spectroscopy could provide a fast, label-free and non-destructive alternative. In this study, confocal Raman microscopy has been used for examining three in vitro melanoma cell lines, harbouring different molecular profiles and, in particular, specific BRAF and NRAS driver mutations. The molecular information obtained from Raman spectra has served for developing two alternative classification algorithms based on linear discriminant analysis and artificial neural network. Both methods provide high accuracy (≥90%) in discriminating all cell types, suggesting that Raman spectroscopy may be an effective tool for detecting molecular differences between melanoma mutations.     

圈养高山麝种群年龄组的粪便光谱判别

提出了一种利用粪便可见-近红外反射光谱进行圈养高山麝种群年龄组分析的新方法.以FieldSpec~((R))3地物光谱仪采集了145份高山麝粪便(成体麝粪样45份,亚成体和幼体各50份)的光谱数据,将其随机分成训练集(100份)和检验集(45份).光谱经S.Golay平滑和一阶导数处理后以主成分分析法(PCA)降维.以前6个主成分(含原始光谱95.00%的特征信息)作为新变量,利用训练集样本,分别以Fisher线性判别、Bayes逐步判别以及BP-神经网络(BP-ANN)3种方法建立高山麝种群年龄组的分析模型.对检验集45个未知样的预测表明,BP-ANN模型判别的准确率最高,为84.44%.3种方法所建的模型对幼麝粪样判别的准确率最高,可达93.33%.分析发现亚成体粪样具有过渡性质,但幼麝粪样与成体粪样易于判别.结果表明,利用粪便的可见-近红外反射光谱进行高山麝年龄组的快速、非接触性判别是可行的,且PCA 结合BP-ANN判别是一种优选方法.     

Distinguishing excess mutations and increased cell death based on variant allele frequencies

Tumors often harbor orders of magnitude more mutations than healthy tissues. The increased number of mutations may be due to an elevated mutation rate or frequent cell death and correspondingly rapid cell turnover, or a combination of the two. It is difficult to disentangle these two mechanisms based on widely available bulk sequencing data, where sequences from individual cells are intermixed and, thus, the cell lineage tree of the tumor cannot be resolved. Here we present a method that can simultaneously estimate the cell turnover rate and the rate of mutations from bulk sequencing data. Our method works by simulating tumor growth and finding the parameters with which the observed data can be reproduced with maximum likelihood. Applying this method to a real tumor sample, we find that both the mutation rate and the frequency of death may be high.     

Determination of protein secondary structure using factor analysis of infrared spectra

A method is presented for determining the secondary structural composition of a protein in aqueous solution from its infrared spectrum. A factor analysis approach is used to analyze the infrared spectra of 18 proteins whose crystal structures are known from X-ray studies. Factor analysis followed by multiple linear regression identifies those eigenspectra that correlate with the variation in properties described by the calibration set. The properties of interest in this study are % alpha-helix, % beta-sheet, and % turns. In the analysis of an unknown, the factor loadings required to reproduce its spectrum are substituted in the regression equation for each property to predict its secondary structural composition. The accuracy of the method was determined by removing each standard, in turn, from the calibration set and using a calibration set generated from the remainder to predict its composition. By this method we obtain standard errors of prediction of 3.9% for alpha-helix, 8.3% for beta-sheet, and 6.6% for turns. The method may also be applied to the spectra of proteins in 2H2O. The method has important advantages over those currently in use for the quantitative analysis of the infrared spectra of proteins. Manipulation of the spectrum is kept to a minimum, no curve-fitting is necessary, and the several amide I band components need not be assigned.     

Fourier transform infrared spectra of zucchini squash stored at chilling or non-chilling temperatures

Mention of a trademark, proprietary product, or vendor does not constitute a guarantee or warranty of the product by the U.S. Department of Agriculture and does not imply its approval to the exclusion of other products or vendors that might be suitable.Fourier transform infrared spectroscopy (FTIR) was used to investigate spectral changes in the epidermis of zucchini squash resulting from low temperature storage-chilling (5°C) or non-chilling (15°C). Increased levels of fluid (water) were found in the tissue after 2 days of 5°C storage. This increase was reversed to harvest levels when chilled squash were warmed to room temperature for 1 day. After 3 days at 5°C and 1 day at room temperature, a further increase in fluid levels was found in the epidermis. Squash chilled for 3 days were apparently beyond recovery as indicated by spectral changes, although visual symptoms of chilling injury were not apparent until another 3 days of exposure to 5°C. Spectra of epidermis tissues from squash stored at 15°C indicated a pattern of increased non-reversible fluid accumulation when storage was prolonged. These results suggest that FTIR spectroscopy may be a rapid way to detect changes in chilled tissues before the eventual appearance of visible symptoms.