Genetically engineered livestock for biomedical models

To commemorate Transgenic Animal Research Conference X, this review summarizes the recent progress in developing genetically engineered livestock species as biomedical models. The first of these conferences was held in 1997, which turned out to be a watershed year for the field, with two significant events occurring. One was the publication of the first transgenic livestock animal disease model, a pig with retinitis pigmentosa. Before that, the use of livestock species in biomedical research had been limited to wild-type animals or disease models that had been induced or were naturally occurring. The second event was the report of Dolly, a cloned sheep produced by somatic cell nuclear transfer. Cloning subsequently became an essential part of the process for most of the models developed in the last 18 years and is stilled used prominently today. This review is intended to highlight the biomedical modeling achievements that followed those key events, many of which were first reported at one of the previous nine Transgenic Animal Research Conferences. Also discussed are the practical challenges of utilizing livestock disease models now that the technical hurdles of model development have been largely overcome.     

Marmoset models commonly used in biomedical research

The common marmoset (Callithrix jacchus) is a small, nonendangered New World primate that is native to Brazil and has been used extensively in biomedical research. Historically the common marmoset has been used in neuroscience, reproductive biology, infectious disease, and behavioral research. Recently, the species has been used increasingly in drug development and safety assessment. Advantages relate to size, cost, husbandry, and biosafety issues as well as unique physiologic differences that may be used in model development. Availability and ease of breeding in captivity suggest that they may represent an alternative species to more traditional nonhuman primates. The marmoset models commonly used in biomedical research are presented, with emphasis on those that may provide an alternative to traditional nonhuman primate species.     

重组工程系统研究进展

大肠杆菌的同源重组依靠内源性的RecA蛋白。RecBCD降解双链线性DNA分子,因此必须构建环状质粒打靶载体才能完成体内重组,操作过程繁琐,所需同源臂长。最近建立起的依赖于Rac噬菌体的ET重组系统和基于入噬菌体的Red重组系统,可有效利用线性DNA片段作为打靶分子,对大肠杆菌染色体DNA和BAC、PAC载体中包含的真核细胞基因组DNA进行基因敲除、敲入、替换、单碱基突变及体内基因克隆等修饰。这2种系统重组效率高,用PCR方法便可合成双链线性DNA打靶分子,不需要限制酶和连接酶,操作过程简单、精确、快速、经济,大大缩短了构建打靶载体的时间,成为功能基因组研究的有力工具。     

Percentile growth charts for biomedical studies using a porcine model

Increasing rates of obesity and heart disease are compromising quality of life for a growing number of people. There is much research linking adult disease with the growth and development both in utero and during the first year of life. The pig is an ideal model for studying the origins of developmental programming. The objective of this paper was to construct percentile growth curves for the pig for use in biomedical studies. The body weight (BW) of pigs was recorded from birth to 150 days of age and their crown-to-rump length was measured over the neonatal period to enable the ponderal index (PI; kg/m3) to be calculated. Data were normalised and percentile curves were constructed using Cole's lambda-mu-sigma (LMS) method for BW and PI. The construction of these percentile charts for use in biomedical research will allow a more detailed and precise tracking of growth and development of individual pigs under experimental conditions.     

Workshop report: Cryopreservation of aquatic biomedical models

The genetic resources of aquatic biomedical model organisms are the products of millions of years of evolution, decades of scientific development, and hundreds of millions of dollars of research funding investment. Genetic resources (e.g., specific alleles, transgenes, or combinations) of each model organism can be considered a form of scientific wealth that can be accumulated and exchanged, typically in the form of live animals or germplasm. Large-scale maintenance of live aquatic organisms that carry these genetic resources is inefficient, costly, and risky. In situ maintenance may be substantially enhanced and backed up by combining cryopreserved germplasm repositories and genetic information systems with live animal culture. Unfortunately, cryopreservation has not advanced much beyond the status of an exploratory research for most aquatic species, lacks widespread application, and methods for successful cryopreservation remain poorly defined. For most aquatic species biological materials other than sperm or somatic cells are not comprehensively banked to represent and preserve a broad range of genetic diversity for each species. Therefore, new approaches and standardization are needed for repository-level application to ensure reproducible recovery of cryopreserved materials. Additionally, development of new technologies is needed to address preservation of novel biological materials, such as eggs and embryos of aquatic species. To address these goals, the Office of Research Infrastructure Programs (ORIP) of the National Institutes of Health (NIH) hosted the Cryopreservation of Aquatic Biomedical Models Workshop on January 7 to 8, 2017, in conjunction with the 8th Aquatic Animal Models of Human Disease Conference in Birmingham, Alabama. The goals of the workshop were to assess the status of germplasm cryopreservation in various biomedical aquatic models and allow representatives of the scientific community to develop and prioritize a consensus of specific actionable recommendations that will move the field of cryopreservation of aquatic resources forward. This workshop included sessions devoted to new approaches for cryopreservation of aquatic species, discussion of current efforts and approaches in preservation of aquatic model germplasm, consideration of needs for standardization of methods to support reproducibility, and enhancement of repository development by establishment of scalable high-throughput technologies. The following three broad recommendations were forwarded from workshop attendees:1Establish a comprehensive, centralized unit (“hub”) to programmatically develop training for and documentation of cryopreservation methods for aquatic model systems. This would include development of species-specific protocols and approaches, outreach programs, community development and standardization, freezing services and training of the next generation of experts in aquatic cryopreservation.2Provide mechanisms to support innovative technical advancements that will increase the reliability, reproducibility, simplicity, throughput, and efficiency of the cryopreservation process, including vitrification and pipelines for sperm, oocytes, eggs, embryos, larvae, stem cells, and somatic cells of all aquatic species. This recommendation encompasses basic cryopreservation knowledge and engineering technology, such as microfluidics and automated processing technologies.3Implement mechanisms that allow the various aquatic model stock centers to increase their planning, personnel, ability to secure genetic resources and to promote interaction within an integrated, comprehensive repository network for aquatic model species repositories.     

New yeast recombineering tools for bacteria

Recombineering with Saccharomyces cerevisiae is a powerful methodology that can be used to clone multiple unmarked pieces of DNA to generate complex constructs with high efficiency. Here, we introduce two new tools that utilize the native recombination enzymes of S. cerevisiae to facilitate the manipulation of DNA. First, yeast recombineering was used to make directed nested deletions in a bacteria–yeast shuttle plasmid using only one or two single stranded oligomers, thus obviating the need for a PCR step. Second, we have generated several new shuttle vectors for yeast recombineering capable of replication in a wide variety of bacterial genera. As a demonstration of utility, some of the approaches and vectors generated in this study were used to make a pigP deletion mutation in the opportunistic pathogen Serratia marcescens.     

The use of ruminant models in biomedical perinatal research

Animal models are of critical importance in biomedical research. Although rodents and lagomorphs are the most commonly used species, larger species are required, especially when surgical approaches or new medical devices have to be evaluated. In particular, in the field of perinatal medicine, they are critical for the evaluation of new pharmacologic treatments and the development of new invasive procedures in fetuses. In some areas, such as developmental genetics, reproductive biotechnologies and metabolic programming, the contribution of ruminants is essential. The current report focuses on some of the most outstanding examples of great biomedical advances carried out with ruminant models in the field of perinatal research. Experiments recently carried in our research unit using ruminants are also briefly described.     

Transfer of porcine embryos through mini-laparotomy

The aim of this experiment was to examine the suitability of mini-laparotomy for transferring embryos in pigs. Expanded blastocysts collected from estrus-induced prepuberal gilts were transferred to the uterus of synchronous recipients. Each recipient received 18 embryos transferred unilaterally either by conventional laparotomy (n = 20), mini-laparotomy (n = 15) or laparoscopy (n = 14). The mini-laparotomy consisted of a midventral incision of 4 cm enabling the surgeon to grasp a uterine horn with two fingers and exteriorize about 3 cm of it. To close the suture wound, only three or four interrupted skin sutures are required. Pregnancy rates after conventional surgery, mini-laparotomy and laparoscopy were 60.67 and 21%, respectively. Corresponding litter size was 7.4, 6.2 and 6.0 and total embryo survival 25, 23 and 7%. The differences in pregnancy rate and total embryo survival between conventional and mini-surgery were negligible, whereas between laparoscopy and the other two techniques it was significant. It may be concluded that, with a little practice, the time saving and less traumatic mini-laparotomy is a practicable alternative to conventional surgery.     

(Re)Creating Rituals through Contemporary Dance

After fieldwork on the ten-hour performance “Insomnia 2–In Memoriam” about rituals and death, the author asks how the deRothfils company makes life meaningful through audience interaction with this dance creation. She explores the notion of ritual for performance analysis, drawing on Catherine Bell’s framework. She examines four dimensions of the performance, each showing how various aspects of ritual are generated: reviving esthetic features, fulfilling social needs through collective encounters, experiencing strong affects, and offering a space for existential reflection. The article concludes with a more general question of how this artistic process produces knowledge.     

Exploring and linking biomedical resources through multidimensional semantic spaces

BACKGROUND: The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). RESULTS: This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. CONCLUSIONS: Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for integration, exploration, and analysis tasks. Results over a real scenario demonstrate the viability and usefulness of the approach, as well as the quality of the generated multidimensional semantic spaces.     

Creating protein models from electron-density maps using particle-filtering methods

MOTIVATION: One bottleneck in high-throughput protein crystallography is interpreting an electron-density map, that is, fitting a molecular model to the 3D picture crystallography produces. Previously, we developed ACMI (Automatic Crystallographic Map Interpreter), an algorithm that uses a probabilistic model to infer an accurate protein backbone layout. Here, we use a sampling method known as particle filtering to produce a set of all-atom protein models. We use the output of ACMI to guide the particle filter's sampling, producing an accurate, physically feasible set of structures. RESULTS: We test our algorithm on 10 poor-quality experimental density maps. We show that particle filtering produces accurate all-atom models, resulting in fewer chains, lower sidechain RMS error and reduced R factor, compared to simply placing the best-matching sidechains on ACMI's trace. We show that our approach produces a more accurate model than three leading methods--Textal, Resolve and ARP/WARP--in terms of main chain completeness, sidechain identification and crystallographic R factor. AVAILABILITY: Source code and experimental density maps available at http://ftp.cs.wisc.edu/machine-learning/shavlik-group/programs/acmi/     

Fast and scalable neural embedding models for biomedical sentence classification

Background

Biomedical literature is expanding rapidly, and tools that help locate information of interest are needed. To this end, a multitude of different approaches for classifying sentences in biomedical publications according to their coarse semantic and rhetoric categories (e.g., Background, Methods, Results, Conclusions) have been devised, with recent state-of-the-art results reported for a complex deep learning model. Recent evidence showed that shallow and wide neural models such as fastText can provide results that are competitive or superior to complex deep learning models while requiring drastically lower training times and having better scalability. We analyze the efficacy of the fastText model in the classification of biomedical sentences in the PubMed 200k RCT benchmark, and introduce a simple pre-processing step that enables the application of fastText on sentence sequences. Furthermore, we explore the utility of two unsupervised pre-training approaches in scenarios where labeled training data are limited.

Results

Our fastText-based methodology yields a state-of-the-art F1 score of.917 on the PubMed 200k benchmark when sentence ordering is taken into account, with a training time of only 73 s on standard hardware. Applying fastText on single sentences, without taking sentence ordering into account, yielded an F1 score of.852 (training time 13 s). Unsupervised pre-training of N-gram vectors greatly improved the results for small training set sizes, with an increase of F1 score of.21 to.74 when trained on only 1000 randomly picked sentences without taking sentence ordering into account.

Conclusions

Because of it’s ease of use and performance, fastText should be among the first choices of tools when tackling biomedical text classification problems with large corpora. Unsupervised pre-training of N-gram vectors on domain-specific corpora also makes it possible to apply fastText when labeled training data are limited.

     

Invertebrate models for biomedical research, testing, and education

Invertebrate animals have been used as medicinals for 4,000 years and have served as models for research and teaching since the late 1800s. Interest in invertebrate models has increased over the past several decades as the research community has responded to public concerns about the use of vertebrate animals in research. As a result, invertebrates are being evaluated and recognized as models for many diseases and conditions. Their use has led to discoveries in almost every area of biology and medicine--from embryonic development to aging processes. Species range from terrestrial invertebrates such as nematodes and insects to freshwater and marine life including planarians, crustaceans, molluscs, and many others. The most often used models are the fruit fly Drosophila melanogaster and the minuscule nematode Caenorhabditis elegans. Topics in this article are categorized by biologic system, process, or disease with discussion of associated invertebrate models. Sections on bioactive products discovered from invertebrates follow the models section, and the article concludes with uses of invertebrates in teaching. The models reviewed can serve as references for scientists, researchers, veterinarians, institutional animal care and use committees (IACUCs), and others interested in alternatives to vertebrate animals.     

Semiparametric models and inference for biomedical time series with extra-variation

Biomedical trials often give rise to data having the form of time series of a common process on separate individuals. One model which has been proposed to explain variations in such series across individuals is a random effects model based on sample periodograms. The use of spectral coefficients enables models for individual series to be constructed on the basis of standard asymptotic theory, whilst variations between individuals are handled by permitting a random effect perturbation of model coefficients. This paper extends such methodology in two ways: first, by enabling a nonparametric specification of underlying spectral behaviour; second, by addressing some of the tricky computational issues which are encountered when working with this class of random effect models. This leads to a model in which a population spectrum is specified nonparametrically through a dynamic system, and the processes measured on individuals within the population are assumed to have a spectrum which has a random effect perturbation from the population norm. Simulation studies show that standard MCMC algorithms give effective inferences for this model, and applications to biomedical data suggest that the model itself is capable of revealing scientifically important structure in temporal characteristics both within and between individual processes.