Genome analysis technologies: towards species identification by genotype.

Traditional identification of species has been based on phenotypic traits, although it is clear that, theoretically, genotype-based classification is more accurate. This is especially the case for microorganisms which possess less identifiable traits and are more easily influenced by environment. Therefore, technology that allows identification of species based on genotype is highly desirable. Whole genome sequencing can provide a sufficient amount of information and can be determinative for this purpose but is very impractical for routine use. Thus, a competent technology is needed that allows a reproducible reduction in the amount of information required about a whole genome, while still providing sufficiently accurate identification. It is almost imperative for such a technology to be of a high cost-performance and of easy handling. Universality and portability are also strongly desired. Based on these criteria, the current state of genome analysis technologies are reviewed. Among various methodologies discussed here, amplified fragment length polymorphism (AFLP), genome profiling (GP) and microarrays are the subject of particular attention. As species identification is a base for most fields of biology including microbiology, ecology, epidemiology and for various biotechnologies, it is of paramount importance to establish a more efficient, easily handled and more objective methodology, in parallel with conventional phenotype-based methodologies. GP is currently considered to have the most optimal nature for identification of species since it can reproducibly reduce a huge amount of genome information to a manageable size by way of random polymerase chain reaction and can extract a sufficient amount of information for species identification from the DNA fragments thus profiled by temperature gradient gel electrophoresis. The potential ability of DNA microarrays for this purpose is also discussed and promises much for the future.     

LeafNet: A computer vision system for automatic plant species identification

AimsTaxon identification is an important step in many plant ecological studies. Its efficiency and reproducibility might greatly benefit from partly automating this task. Image-based identification systems exist, but mostly rely on hand-crafted algorithms to extract sets of features chosen a priori to identify species of selected taxa. In consequence, such systems are restricted to these taxa and additionally require involving experts that provide taxonomical knowledge for developing such customized systems. The aim of this study was to develop a deep learning system to learn discriminative features from leaf images along with a classifier for species identification of plants. By comparing our results with customized systems like LeafSnap we can show that learning the features by a convolutional neural network (CNN) can provide better feature representation for leaf images compared to hand-crafted features.MethodsWe developed LeafNet, a CNN-based plant identification system. For evaluation, we utilized the publicly available LeafSnap, Flavia and Foliage datasets.ResultsEvaluating the recognition accuracies of LeafNet on the LeafSnap, Flavia and Foliage datasets reveals a better performance of LeafNet compared to hand-crafted customized systems.ConclusionsGiven the overall species diversity of plants, the goal of a complete automatisation of visual plant species identification is unlikely to be met solely by continually gathering assemblies of customized, specialized and hand-crafted (and therefore expensive) identification systems. Deep Learning CNN approaches offer a self-learning state-of-the-art alternative that allows adaption to different taxa just by presenting new training data instead of developing new software systems.     

New approaches towards automated oligoribonucleotide synthesis.

Several protecting group combinations have been investigated to achieve an automated oligoribonucleotide synthesis on a solid support. The use of 2'-O-tert-butyldimethylsilyl-5'-O-monomethoxytrityl-ribonucleoside -3'-(p-nitrophenylethyl, N,N-diethyl)-phosphoramidites in conjunction with beta-eliminating blocking groups at the aglycone gave satisfactory results. An inverse protecting group strategy based upon analogously substituted 5'-O-2-dansylethoxycarbonyl-2'-O-4- methoxytetrahydropyran-4-yl-phosphoramidites can be regarded as another promising approach.     

A polyphasic approach towards the identification of strains belonging to Lactobacillus acidophilus and related species

A set of 98 strains belonging to nine species of the Lactobacillus acidophilus rRNA-group have been analysed by SDS-PAGE of cellular proteins, RAPD-PCR and AFLP with fluorescently labeled primers in order to find improved methods for their identification. Strains of the following phenotypically highly similar species were examined: L. acidophilus, L. amylovorus, L. crispatus, L. johnsonii, L. gasseri, L. gallinarum, L. helveticus, L. iners and L. amylolyticus. Although the majority of the species can be differentiated by SDS-PAGE of whole-cell proteins, the latter technique showed poor discrimination between L. gasseri and L. johnsonii strains and between some strains of L. amylovorus and L. gallinarum. However, this study shows that the RAPD-PCR (using at least 3 different primers followed by numerical analysis of the combined patterns) and AFLP are most suitable genomic fingerprinting techniques for the differentiation of all the species listed above, and that databases for identification can be constructed, particularly when commercially available molecular tool-kits are used. The separate species status of the recently described L. amylolyticus and L. iners was fully confirmed.     

PseudoPipe: an automated pseudogene identification pipeline

MOTIVATION: Mammalian genomes contain many 'genomic fossils' i.e. pseudogenes. These are disabled copies of functional genes that have been retained in the genome by gene duplication or retrotransposition events. Pseudogenes are important resources in understanding the evolutionary history of genes and genomes. RESULTS: We have developed a homology-based computational pipeline ('PseudoPipe') that can search a mammalian genome and identify pseudogene sequences in a comprehensive and consistent manner. The key steps in the pipeline involve using BLAST to rapidly cross-reference potential "parent" proteins against the intergenic regions of the genome and then processing the resulting "raw hits" -- i.e. eliminating redundant ones, clustering together neighbors, and associating and aligning clusters with a unique parent. Finally, pseudogenes are classified based on a combination of criteria including homology, intron-exon structure, and existence of stop codons and frameshifts.     

昆虫图像自动鉴别技术

昆虫是地球上物种多样性最为丰富的生物类群,其物种鉴定任务复杂而艰巨,可靠的物种鉴定是开展昆虫学工作的重要基础之一。当前,国内外的人工昆虫物种鉴定能力均不能满足实际需求,因而人们开始不断探索利用计算机自动鉴定昆虫的原理和方法。目前,模式识别技术的迅猛发展已为昆虫图像的自动鉴定提供可能。文章概述昆虫图像自动鉴定技术研究的历史与现状,总结主要原理和方法,介绍工作流程,并展望发展前景。     

New equipment for the scaled up production of small spherical biocatalysts

Summary A new apparatus with a capacity up to 24 kg per hour for physical entrapment of cell fragments or whole cells in polymeric networks was constructed, based on a high speed rotating nozzle-ring. Immobilized biocatalysts are prepared at laboratory scale with bead size under 1 mm diameter, with a deviation of 10 % or less in size distribution.     

Evaluation of the Biolog automated microbial identification system

Biolog's identification system was used to identify 39 American Type Culture Collection reference taxa and 45 gram-negative isolates from water samples. Of the reference strains, 98% were identified to genus level and 76% to species level within 4 to 24 h. Identification of some authentic strains of Enterobacter, Klebsiella, and Serratia was unreliable. A total of 93% of the water isolates were identified.     

A one step genotypic identification of Lactococcus lactis subspecies at the species/strain levels

A Lactococcus lactis subspecies-specific primer was designed based on their repetitive genome sequences. This primer enabled L. lactis subspecies to be identified simultaneously at both the species level and also the strain level. Based on studies using 70 strains of L. lactis and 60 strains of other non-target bacteria, the identification completely matched that obtained by the sequence of the 16S rRNA gene. However, inconsistency between phenotypic and genotypic characteristics was observed in some strains isolated from milk.     

Diabetic retinopathy: recent advances towards understanding neurodegeneration and vision loss

Diabetic retinopathy(DR) is one of the most common retinal diseases world-wide. It has a complex pathology that involves the vasculature of the inner retina and breakdown of the blood-retinal barrier. Extensive research has determined that DR is not only a vascular disease but also has a neurodegenerative component and that essentially all types of cells in the retina are affected, leading to chronic loss of visual function. A great deal of work using animal models of DR has established the loss of neurons and pathology of other cell types, including supporting glial cells. There has also been an increased emphasis on measuring retinal function in the models, as well as further validation and extension of the animal studies by clinical and translational research. This article will attempt to summarize the more recent developments in research towards understanding the complexities of retinal neurodegeneration and functional vision loss in DR.     

Evaluation of the Biolog automated microbial identification system.

Biolog's identification system was used to identify 39 American Type Culture Collection reference taxa and 45 gram-negative isolates from water samples. Of the reference strains, 98% were identified to genus level and 76% to species level within 4 to 24 h. Identification of some authentic strains of Enterobacter, Klebsiella, and Serratia was unreliable. A total of 93% of the water isolates were identified.     

Molecular identification of mosquito species

Complexes of closely related cryptic species, that are indistinguishable morphologically yet have different ecology and host preferences, are widespread in mosquitoes. The advantages of DNA-based methods of identification mean that they have now largely replaced other methods of species determination for such complexes. Here we discuss the relative merits of three different approaches to species identification, all of which use amplification of the ribosomal RNA genes by the polymerase chain reaction. They include: restriction fragment length polymorphism in the Anopheles maculipennis complex from the UK; allele-specific amplification in the An. dims complex from Thailand; and single strand conformational polymorphism in the An. minimus complex from Thailand. The application of these methods is considered in the context of recent data on intraspecific genetic variation, geographic population structure and genetic introgression.     

Stress induced lipid production in Chlorella vulgaris: Relationship with specific intracellular reactive species levels

Microalgae have significant potential to be an important alternative energy source, but the challenges to the commercialization of bio‐oil from microalgae need to be overcome for the potential to be realized. The application of stress can be used to improve bio‐oil yields from algae. Nevertheless, the understanding of stress effects is fragmented due to the lack of a suitable, direct quantitative marker for stress. The lack of understanding seems to have limited the development of stress based strategies to improve bio‐oil yields, and hence the commercialization of microalgae‐based bio‐oil. In this study, we have proposed and used the specific intracellular reactive species levels (siROS) particularly hydroxyl and superoxide radical levels, separately, as direct, quantitative, markers for stress, irrespective of the type of stress induced. Although ROS reactions are extremely rapid, the siROS level can be assumed to be at pseudo‐steady state compared to the time scales of metabolism, growth and production, and hence they can be effective stress markers at particular time points. Also, the specific intracellular (si‐) hydroxyl and superoxide radical levels are easy to measure through fluorimetry. Interestingly, irrespective of the conditions employed in this study, that is, nutrient excess/limitation or different light wavelengths, the cell concentrations are correlated to the siROS levels in an inverse power law fashion. The composite plots of cell concentration (y) and siROS (x) yielded the correlations of y = k₁ · x^?0.7 and y = k₂ · x^?0.79, for si‐hydroxyl and si‐superoxide radical levels, respectively. The specific intracellular (si‐) neutral lipid levels, which determine the bio‐oil productivity, are related in a direct power law fashion to the specific hydroxyl radical levels. The composite plot of si‐neutral lipid levels (z) and si‐hydroxyl radical level (x) yielded a correlation of z = k₃ · x^0.65. More interestingly, a nutrient shift caused a significant change in the sensitivity of neutral lipid accumulation to the si‐hydroxyl radical levels. Biotechnol. Bioeng. 2013; 110: 1627–1636. © 2013 Wiley Periodicals, Inc.