Organism identification using a genome sequence-independent universal microarray probe set

There has been increasing interest and efforts devoted to developing biosensor technologies for identifying pathogens, particularly in the biothreat area. In this study, a universal set of short 12- and 13-mer oligonucleotide probes was derived independently of a priori genomic sequence information and used to generate unique species-dependent genomic hybridization signatures. The probe set sequences were algorithmically generated to be maximally distant in sequence space and not dependent on the sequence of any particular genome. The probe set is universally applicable because it is unbiased and independent of hybridization predictions based upon simplified assumptions regarding probe-target duplex formation from linear sequence analysis. Tests were conducted on microarrays containing 14,283 unique probes synthesized using an in situ light-directed synthesis methodology. The genomic DNA hybridization intensity patterns reproducibly differentiated various organisms (Bacillus subtilis, Yersinia pestis, Streptococcus pneumonia, Bacillus anthracis, and Homo sapiens), including the correct identification of a blinded "unknown" sample. Applications of this method include not only pathological and forensic genome identification in medicine and basic science, but also potentially a novel method for the discovery of unknown targets and associations inherent in dynamic nucleic acid populations such as represented by differential gene expression.     

A comparison of signal sequence prediction methods using a test set of signal peptides

We describe the creation of a test set containing secretory and non-secretory proteins. Five existing prediction programs for signal sequences and their cleavage sites are compared on the basis of this test set: SPScan, SigCleave, SignalP V1.1, SignalP V2.0. b2-HMM and SignalP V2.0.b2-NN.     

Rapid identification of Listeria species by using restriction fragment length polymorphism of PCR-amplified 23S rRNA gene fragments

A molecular method based on restriction fragment length polymorphism (RFLP) of PCR-amplified fragments of the 23S rRNA gene was designed to rapidly identify Listeria strains to the species level. Two fragments (S1, 460 bp, and S2, 890 bp) were amplified from boiled DNA. S2 was cut with the restriction enzymes XmnI or CfoI and, if needed, S1 was digested by either AluI or ClaI. This method was first optimized with six reference strains and then applied to 182 isolates collected from effluents of treatment plants. All isolates were also identified by the API Listeria kit, hemolysis, and phosphatidylinositol-specific phospholipase C production (PI-PLC) on ALOA medium. The PCR-RFLP method unambiguously identified 160 environmental strains, including 131 in concordance with the API system, and revealed that 22 isolates were mixed cultures of Listeria monocytogenes and Listeria innocua. Discrepant results were resolved by a multiplex PCR on the iap gene, which confirmed the PCR-RFLP data for 49 of the 51 discordances, including the 22 mixed cultures. Sequencing of the 16S rRNA gene for 12 selected strains and reconstruction of a phylogenetic tree validated the molecular methods, except for two unclassifiable strains. The 158 single identifiable isolates were 92 L. monocytogenes (including seven nonhemolytic and PI-PLC-negative strains), 61 L. innocua, 4 Listeria seeligeri, and 1 Listeria welshimeri strain. The PCR-RFLP method proposed here provides rapid, easy-to-use, inexpensive, and reliable identification of the six Listeria species. Moreover, it can detect mixtures of Listeria species and thus is particularly adapted to environmental and food microbiology.     

Rapid parallel mutation scanning of gene fragments using a microelectronic protein-DNA chip format

We have developed a method for the de novo discovery of genetic variations, including single nucleotide polymorphisms and mutations, on microelectronic chip devices. The method combines the features of electronically controlled DNA hybridisation on open-format microarrays, with mutation detection by a fluorescence-labelled mismatch- binding protein. Electronic addressing of DNA strands to distinct test sites of the chip allows parallel analysis of several individuals, as demonstrated for mutations in different exons of the p53 gene. This microelectronic chip-based mutation discovery assay may substitute for time-consuming sequencing studies and will complement existing technologies in genomic research.     

RNAMotifScan: automatic identification of RNA structural motifs using secondary structural alignment

Recent studies have shown that RNA structural motifs play essential roles in RNA folding and interaction with other molecules. Computational identification and analysis of RNA structural motifs remains a challenging task. Existing motif identification methods based on 3D structure may not properly compare motifs with high structural variations. Other structural motif identification methods consider only nested canonical base-pairing structures and cannot be used to identify complex RNA structural motifs that often consist of various non-canonical base pairs due to uncommon hydrogen bond interactions. In this article, we present a novel RNA structural alignment method for RNA structural motif identification, RNAMotifScan, which takes into consideration the isosteric (both canonical and non-canonical) base pairs and multi-pairings in RNA structural motifs. The utility and accuracy of RNAMotifScan is demonstrated by searching for kink-turn, C-loop, sarcin-ricin, reverse kink-turn and E-loop motifs against a 23S rRNA (PDBid: 1S72), which is well characterized for the occurrences of these motifs. Finally, we search these motifs against the RNA structures in the entire Protein Data Bank and the abundances of them are estimated. RNAMotifScan is freely available at our supplementary website (http://genome.ucf.edu/RNAMotifScan).     

fRMSDPred: predicting local RMSD between structural fragments using sequence information

The effectiveness of comparative modeling approaches for protein structure prediction can be substantially improved by incorporating predicted structural information in the initial sequence-structure alignment. Motivated by the approaches used to align protein structures, this article focuses on developing machine learning approaches for estimating the RMSD value of a pair of protein fragments. These estimated fragment-level RMSD values can be used to construct the alignment, assess the quality of an alignment, and identify high-quality alignment segments. We present algorithms to solve this fragment-level RMSD prediction problem using a supervised learning framework based on support vector regression and classification that incorporates protein profiles, predicted secondary structure, effective information encoding schemes, and novel second-order pairwise exponential kernel functions. Our comprehensive empirical study shows superior results compared with the profile-to-profile scoring schemes. We also show that for protein pairs with low sequence similarity (less than 12% sequence identity) these new local structural features alone or in conjunction with profile-based information lead to alignments that are considerably accurate than those obtained by schemes that use only profile and/or predicted secondary structure information.     

The identification of complementarity of molecular surfaces using fuzzy set theory

Fuzzy logic-based algorithms for the quantitative treatment of complementarity of molecular surfaces are presented. The identification of complementary surface patches can be considered as a first step for the solution of molecular docking problems. Based on these initial guesses, docking structures can be further optimized by standard technologies. In this work a simple downhill simplex method for the optimization is used. The algorithms are applied to various biomolecular complexes. For all these complexes, at least one structure was found to be in very good agreement with the experimental data.     

Automatic recognition of bird individuals on an open set using as-is recordings

The most common method used to determine the identity of an individual bird is the capture-mark-recapture technique. The method has several major disadvantages, e.g. some species are difficult to capture/recapture and the capturing process itself may cause significant stress in animals leading even to injuries of more vulnerable species. Some studies introduce systems based on methods used for human identification. An automatic system for recognition of bird individuals (ASRBI) described in this article is based on a Gaussian mixture model (GMM) and a universal background model (GMM-UBM) method extended by an advanced voice activity detection (VAD) algorithm. It is focused on recognizing the bird individuals on an open set, i.e. any number of unknown birds may appear anytime during the identification process as is common in nature. The introduced ASRBI processes the recordings just as if they were recorded by an ornithologist: with durations from seconds to minutes, containing noise and unwanted sounds, as well as masking of the singer, etc. Thanks to the VAD algorithm, the proposed system is fully automatic, no manual pre-processing of recordings is needed, neither by cutting off the songs nor syllables. The overall achieved identification accuracy is 78.5%, the lowest 60.3% and the highest 95.7%. In total, 90% of all experiments reach at least 70% accuracy. The result suggests the application of the GMM-UBM with VAD is feasible for individual identification on the open set processing real-life recordings. The described method is capable of reducing both the time consumption and human intervention in animal monitoring projects.     

Statistical analysis of a small set of time-ordered gene expression data using linear splines

MOTIVATION: Recently, the temporal response of genes to changes in their environment has been investigated using cDNA microarray technology by measuring the gene expression levels at a small number of time points. Conventional techniques for time series analysis are not suitable for such a short series of time-ordered data. The analysis of gene expression data has therefore usually been limited to a fold-change analysis, instead of a systematic statistical approach. METHODS: We use the maximum likelihood method together with Akaike's Information Criterion to fit linear splines to a small set of time-ordered gene expression data in order to infer statistically meaningful information from the measurements. The significance of measured gene expression data is assessed using Student's t-test. RESULTS: Previous gene expression measurements of the cyanobacterium Synechocystis sp. PCC6803 were reanalyzed using linear splines. The temporal response was identified of many genes that had been missed by a fold-change analysis. Based on our statistical analysis, we found that about four gene expression measurements or more are needed at each time point.     

Building structural models of peptides: a semi-automatic software

We present a software package that allows the construction anddisplay of structural models of proteins starting from the aminoacid sequence written in the one-letter code of standard databank format. The software includes a very fast and efficientalgorithm aimed at finding the global energy minimum of thepotential function describing the molecular interactions. Thewhole package is conceived to have maximum flexibility. Completelyautomatic procedures are envisaged for standard problems. Fornon-standard problems, the construction procedure can be interactivelyadopted to meet with different options. Received on February 19, 1990; accepted on August 31, 1990     

Molecular identification of a soybean protein kinase gene family by using PCR

In this study we report identification of six members of a protein kinase gene family from soybean (Glycine max L.). Two fully degenerate oligonucleotide primers corresponding to two conserved motifs (DLK-PENV and GTHEYLAPE) in the catalytic domains of eukaryotic protein serine/threonine kinases were used in a polymerase chain reaction (PCR) to amplify soybean cDNA. Sequence analysis showed that 28 of the PCR sequences represented six different putative protein serine/threonine kinases. These results not only demonstrate that catalytic domains of protein kinases are highly conserved between plants and other eukaryotes but also suggest that there are multiple genes encoding protein kinases in plants.     

Turning publicly available gene expression data into discoveries using gene set context analysis

Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data.     

Molecular cloning and expression of gene fragments from corynebacteriophage beta encoding enzymatically active peptides of diphtheria toxin

Two restriction fragments from corynebacteriophage beta vir tox+ that encode peptides similar to diphtheria toxin fragment A and the chain termination fragment, CRM45, have been cloned into Escherichia coli in plasmid pBR322. Clones containing the recombinant plasmids produced gene products that were active in catalyzing the ADP ribosylation of elongation factor 2 and were reactive with diphtheria toxin antiserum. Toxin-related peptides were found primarily in the periplasmic compartment and were degraded to nonimmunoreactive forms within 1 to 2 h of synthesis. The expression of both gene fragments appears to have originated from the diphtheria toxin promoter.     

Multivariate design and evaluation of a set of RGRPQ-derived innate immunity peptides

Oral commensal Streptococcus gordonii proteolytically cleave the salivary PRP-1 polypeptide into an RGRPQ innate peptide. The Arg and Gln termini are crucial for RGRPQ-mediated ammonia production and proliferation by S. gordonii SK12 and adhesion inhibition and desorption by Actinomyces naeslundii T14V, respectively. Here we have applied (i) a multivariate approach using RGRPQ-related peptides varied at amino acids 2, 3, and 4 simultaneously and (ii) size and N- and C-terminal modifications of RGRPQ to generate structure activity information. While the N-terminal arginine motif mediated ammonia production independent of peptide size, other responses required more or less full-length peptide motifs. The motifs for adhesion inhibition and desorption were the same. The adhesion and proliferation motifs required similarly a hydrophobic/low polarity amino acid 4 but differentially a hydrophilic or hydrophobic character of amino acids 2/3, respectively; polar peptides with small/hydrophilic and hydrophilic amino acids 2 and 3, respectively, had high adhesion inhibition/desorption activity, and lipophilic peptides with large/hydrophobic amino acids 2 and 3 had high proliferation activity. Accordingly, while RIWWQ had increased proliferation but abolished adhesion/desorption activity, peptides designed with hydrophilic amino acids 2 and 3 were predicted to behave in the opposite way. Moreover, a RGRPQ mimetic for all three responses should mimic small hydrophilic, large nitrogen-containing, and hydrophobic/low polarity amino acids 2, 3, and 4, respectively. Peptides fulfilling these criteria were 1-1.6-fold improved in all three responses. Thus, both mimetics and peptides with differential proliferation and adhesion activities may be generated for evaluation in biofilm models.     

Rapid parallel mutation scanning of gene fragments using a microelectronic protein–DNA chip format

We have developed a method for the de novo discovery of genetic variations, including single nucleotide polymorphisms and mutations, on microelectronic chip devices. The method combines the features of electronically controlled DNA hybridisation on open-format microarrays, with mutation detection by a fluorescence-labelled mismatch- binding protein. Electronic addressing of DNA strands to distinct test sites of the chip allows parallel analysis of several individuals, as demonstrated for mutations in different exons of the p53 gene. This microelectronic chip-based mutation discovery assay may substitute for time-consuming sequencing studies and will complement existing technologies in genomic research.     

自动识别技术在昆虫分类鉴别研究中的应用

昆虫的自动识别是重要的新兴研究领域,它以直接、快速、方便等优点日益受到人们的青睐。昆虫是世界上最大的生物类群,鉴定工作费时耗力,然而分类专家又在逐渐减少。近年来,昆虫自动识别技术的发展为解决这一矛盾提供了乐观的方案。众多分类学家不断探索自动识别的方法和理论,并开发出了一批识别软件。本文介绍自动识别的原理,分类讨论自动识别的技术和方法,并分析提出面临的困难和应对策略。     

Overall assessment of antimicrobial peptides in piglets: a set of meta-analyses

Developing alternatives to antibiotics is an urgent need in livestock production. Antimicrobial peptides (AMPs) are regarded as powerful antibiotic substitutes (ASs) because AMPs have broad-spectrum antimicrobial activities and growth-promoting ability. Here, we aimed to comprehensively assess the effects of AMPs on the growth performance, diarrhea rate, intestinal morphology and immunity of healthy or challenged piglets, compared with an antibiotics group or negative control group. We performed a set of meta-analyses of feeding trials from database inception to 27 May 2019. Among the 1379 identified studies, 20 were included in our meta-analyses (56 arms and 4067 piglets). The meta-analyses revealed that (1) compared with the negative control group, AMPs significantly improved the healthy piglets’ average daily gain (ADG), average daily feed intake (ADFI), gain : feed ratio (G/F), levels of immune globulin (Ig) IgM and IgG, and intestinal villus height : crypt depth ratio (V/C) (P < 0.05). Meanwhile, AMPs significantly increased the challenged piglets’ ADG, ADFI, G/F and V/C of the jejunum and ileum, and notably deceased the diarrhea rate (P < 0.05); (2) compared with antibiotics group, the effects of AMPs were slightly weaker than those of antibiotics in the healthy piglets, but AMPs have similar effects to those of antibiotics in challenged piglets. In a higher purity, the optimal dose of AMPs may be approximately 0.01%. Our findings indicate that AMPs can improve piglet growth performance, enhance immunity, benefit intestinal morphology and decrease the diarrheal rate. AMPs could be great ASs especially under infection conditions.